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1

Coupling the High Complexity Land Surface Model ACASA to the Mesoscale Model WRF  

E-Print Network (OSTI)

In this study, the Weather Research and Forecasting Model (WRF) is coupled with the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA), a high complexity land surface model. Although WRF is a state-of-the-art regional ...

Xu, L.

2

Verification of the WRF model during a high ozone event over Houston, TX  

E-Print Network (OSTI)

High ozone values were observed in Houston, TX during August 25 - September 1, 2000. A comparison of WRF data with observations and MM5 data was conducted to determine the WRF model's performance in simulating the meteorological conditions...

Ames, Douglas Seeley

2012-06-07T23:59:59.000Z

3

Atmospheric and seeing forecast: WRF model validation with in situ measurements at ORM  

Science Journals Connector (OSTI)

......orographic data to initialize WRF. 6 CONCLUSION For the first time, the WRF model, coupled with the...used to forecast not only local meteorological parameters...relative humidity and wind speed at ground level...simultaneous forecasts, the WRF-in situ instrument agreement......

C. Giordano; J. Vernin; H. VŠzquez Ramiů; C. MuŮoz-TuŮůn; A. M. Varela; H. Trinquet

2013-01-01T23:59:59.000Z

4

Simulation of Aerosol-Cloud Interactions in the WRF Model at the Southern Great Plains Site  

E-Print Network (OSTI)

The aerosol direct and indirect effects were investigated for three specific cases during the March 2000 Cloud IOP at the SGP site by using a modified WRF model. The WRF model was previously altered to include a two-moment bulk microphysical scheme...

Vogel, Jonathan 1988-

2012-08-21T23:59:59.000Z

5

From concentric eyewall to annular hurricane: A numerical study with the cloud-resolved WRF model  

E-Print Network (OSTI)

(secondary eyewall) in coincidence with a local tangential wind max- imum around the pre-existing eyewallFrom concentric eyewall to annular hurricane: A numerical study with the cloud-resolved WRF model Research and Forecasting (WRF) model, the transformation from a non- AH to an AH through a concentric

Wang, Bin

6

PNNL-Weather Research and Forecasting (WRF)-Chem Modeling in Mexico | Open  

Open Energy Info (EERE)

Weather Research and Forecasting (WRF)-Chem Modeling in Mexico Weather Research and Forecasting (WRF)-Chem Modeling in Mexico Jump to: navigation, search Name PNNL-Weather Research and Forecasting (WRF)-Chem Modeling in Mexico Agency/Company /Organization Pacific Northwest National Laboratory Sector Energy Topics Co-benefits assessment, - Environmental and Biodiversity, - Health, Background analysis Resource Type Publications Website http://www.pnl.gov/atmospheric Country Mexico UN Region Latin America and the Caribbean References PNNL-Weather Research and Forecasting (WRF)-Chem Modeling in Mexico[1] PNNL Publications on WRF-Chem modeling in Mexico include: Fast JD, M Shrivastava, RA Zaveri, and JC. Barnard. 2010. "Modeling particulates and direct radiative forcing from urban to synoptic scales downwind of Mexico City." Annual European Geosciences Union Assembly,

7

Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south-east Australia  

E-Print Network (OSTI)

values were driven mainly by WRF errors in wind speed simulation. However, in both cases the qualityFire weather simulation skill by the Weather Research and Forecasting (WRF) model over south-east Australia from 1985 to 2009 has been simulated using the Weather Research and Forecasting (WRF) model

Evans, Jason

8

WRF Model Simulation of Two Alberta Flooding Events and the Impact of Topography  

Science Journals Connector (OSTI)

This study examines simulations of two flooding events in Alberta, Canada, during June 2005, made using the Weather Research and Forecasting Model (WRF). The model was used in a manner readily accessible to nonmeteorologists (e.g., accepting ...

Thomas K. Flesch; Gerhard W. Reuter

2012-04-01T23:59:59.000Z

9

Object-Based Analysis and Verification of WRF Model Precipitation in the Low- and Midlatitude Pacific Ocean  

Science Journals Connector (OSTI)

An extended version of the Method for Object-based Diagnostic Evaluation (MODE) was used to perform a verification of precipitation provided by the Weather Research and Forecasting (WRF) model Tropical Channel Simulation (performed by NCAR). ...

Gregor Skok; Joe Tribbia; Joěe Rakovec

2010-12-01T23:59:59.000Z

10

Simulation of Urban Climate with High-Resolution WRF Model: A Case Study in Nanjing, China  

SciTech Connect

In this study, urban climate in Nanjing of eastern China is simulated using 1-km resolution Weather Research and Forecasting (WRF) model coupled with a single-layer Urban Canopy Model. Based on the 10-summer simulation results from 2000 to 2009 we find that the WRF model is capable of capturing the high-resolution features of urban climate over Nanjing area. Although WRF underestimates the total precipitation amount, the model performs well in simulating the surface air temperature, relative humidity, and precipitation frequency, diurnal cycle and inter-annual variability. We find that extremely hot events occur most frequently in urban area, with daily maximum (minimum) temperature exceeding 36ļC (28ļC) in around 40% (32%) of days. Urban Heat Island (UHI) effect at surface is more evident during nighttime than daytime, with 20% of cases the UHI intensity above 2.5ļC at night. However, The UHI affects the vertical structure of Planet Boundary Layer (PBL) more deeply during daytime than nighttime. Net gain for latent heat and net radiation is larger over urban than rural surface during daytime. Correspondingly, net loss of sensible heat and ground heat are larger over urban surface resulting from warmer urban skin. Because of different diurnal characteristics of urban-rural differences in the latent heat, ground heat and other energy fluxes, the near surface UHI intensity exhibits a very complex diurnal feature. UHI effect is stronger in days with less cloud or lower wind speed. Model results reveal a larger precipitation frequency over urban area, mainly contributed by the light rain events (<10 mm day-1). Consistent with satellite dataset, around 10-20% more precipitation occurs in urban than rural area at afternoon induced by more unstable urban PBL, which induces a strong vertical atmospheric mixing and upward moisture transport. A significant enhancement of precipitation is found in the downwind region of urban in our simulations in the afternoon.

Yang, Ben; Zhang, Yaocun; Qian, Yun

2012-08-05T23:59:59.000Z

11

Effects of vegetation and soil moisture on the simulated land surface processes from the coupled WRF/Noah model  

E-Print Network (OSTI)

simulations. Meso- scale models, which have been used not only for numerical weather prediction but also surface and atmosphere into numerical weather or climate prediction. This study describes coupled WRF [Chen et al., 1997; Pielke et al., 1997]. Numerical weather prediction with high spatial and tempo- ral

Small, Eric

12

Idealized WRF model sensitivity simulations of sea breeze types and their effects on offshore windfields: Supplementary material  

E-Print Network (OSTI)

and local winds had once again become orientated to favour development of backdoor sea breezes on the southIdealized WRF model sensitivity simulations of sea breeze types and their effects on offshore. Daytime temperatures were sufficiently high to trigger convection over land and the geostrophic wind

Meskhidze, Nicholas

13

Aerosol Indirect Effect on the Grid-scale Clouds in the Two-way Coupled WRF-CMAQ: Model Description, Development, Evaluation and Regional Analysis  

SciTech Connect

This study implemented first, second and glaciations aerosol indirect effects (AIE) on resolved clouds in the two-way coupled WRF-CMAQ modeling system by including parameterizations for both cloud drop and ice number concentrations on the basis of CMAQpredicted aerosol distributions and WRF meteorological conditions. The performance of the newly-developed WRF-CMAQ model, with alternate CAM and RRTMG radiation schemes, was evaluated with the observations from the CERES satellite and surface monitoring networks (AQS, IMPROVE, CASTNet, STN, and PRISM) over the continental U.S. (CONUS) (12-km resolution) and eastern Texas (4-km resolution) during August and September of 2006. The results at the AQS surface sites show that in August, the NMB values for PM2.5 over the eastern/western U.S (EUS/WUS) and western U.S. (WUS) are 5.3% (?0.1%) and 0.4% (-5.2%) for WRF-CMAQ/CAM (WRF-CMAQ/RRTMG), respectively. The evaluation of PM2.5 chemical composition reveals that in August, WRF-CMAQ/CAM (WRF-CMAQ/RRTMG) consistently underestimated the observed SO4 2? by -23.0% (-27.7%), -12.5% (-18.9%) and -7.9% (-14.8%) over the EUS at the CASTNet, IMPROVE and STN sites, respectively. Both models (WRF-CMAQ/CAM, WRF-CMAQ/RRTMG) overestimated the observed mean OC, EC and TC concentrations over the EUS in August at the IMPROVE sites. Both models generally underestimated the cloud field (SWCF) over the CONUS in August due to the fact that the AIE on the subgrid convective clouds was not considered when the model simulations were run at the 12 km resolution. This is in agreement with the fact that both models captured SWCF and LWCF very well for the 4-km simulation over the eastern Texas when all clouds were resolved by the finer domain. Both models generally overestimated the observed precipitation by more than 40% mainly because of significant overestimation in the southern part of the CONUS in August. The simulations of WRF-CMAQ/CAM and WRF-CMAQ/RRTMG show dramatic improvements for SWCF, LWCF, COD, cloud fractions and precipitation over the ocean relative to those of WRF default cases in August. The model performance in September is similar to that in August except for greater overestimation of PM2.5 due to the overestimations of SO4 2-, NH4 +, NO3 -, and TC over the EUS, less underestimation of clouds (SWCF) over the land areas due to about 10% lower SWCF values and less convective clouds in September.

Yu, Shaocai; Mathur, Rohit; Pleim, Jonathan; Wong, David; Gilliam, R.; Alapaty, Kiran; Zhao, Chun; Liu, Xiaohong

2014-10-24T23:59:59.000Z

14

Impacts of WRF Physics and Measurement Uncertainty on California Wintertime Model Wet Bias  

SciTech Connect

The Weather and Research Forecast (WRF) model version 3.0.1 is used to explore California wintertime model wet bias. In this study, two wintertime storms are selected from each of four major types of large-scale conditions; Pineapple Express, El Nino, La Nina, and synoptic cyclones. We test the impacts of several model configurations on precipitation bias through comparison with three sets of gridded surface observations; one from the National Oceanographic and Atmospheric Administration, and two variations from the University of Washington (without and with long-term trend adjustment; UW1 and UW2, respectively). To simplify validation, California is divided into 4 regions (Coast, Central Valley, Mountains, and Southern California). Simulations are driven by North American Regional Reanalysis data to minimize large-scale forcing error. Control simulations are conducted with 12-km grid spacing (low resolution) but additional experiments are performed at 2-km (high) resolution to evaluate the robustness of microphysics and cumulus parameterizations to resolution changes. We find that the choice of validation dataset has a significant impact on the model wet bias, and the forecast skill of model precipitation depends strongly on geographic location and storm type. Simulations with right physics options agree better with UW1 observations. In 12-km resolution simulations, the Lin microphysics and the Kain-Fritsch cumulus scheme have better forecast skill in the coastal region while Goddard, Thompson, and Morrison microphysics, and the Grell-Devenyi cumulus scheme perform better in the rest of California. The effect of planetary boundary layer, soil-layer, and radiation physics on model precipitation is weaker than that of microphysics and cumulus processes for short- to medium-range low-resolution simulations. Comparison of 2-km and 12-km resolution runs suggests a need for improvement of cumulus schemes, and supports the use of microphysics schemes in coarser-grid applications.

Chin, H S; Caldwell, P M; Bader, D C

2009-07-22T23:59:59.000Z

15

WRF-Var implementation for data assimilation experimentation at MIT  

E-Print Network (OSTI)

The goal of this Masters project is to implement the WRF model with 3D variational assimilation (3DVAR) at MIT. A working version of WRF extends the scope of experimentation to mesoscale problems in both real and idealized ...

Williams, John K. (John Kenneth)

2008-01-01T23:59:59.000Z

16

Sea Ice Enhancements to Polar WRF* Keith M. Hines1**  

E-Print Network (OSTI)

covering Europe and the Arctic Ocean demonstrate remote impacts of Arctic sea ice thickness on18 midSea Ice Enhancements to Polar WRF* Keith M. Hines1** , David H. Bromwich,1,2 , Lesheng Bai1 model (Polar WRF), a polar-optimized version of2 WRF, is developed by and available to the community

Howat, Ian M.

17

Gaseous Chemistry and Aerosol Mechanism Developments for Version 3.5.1 of the Online Regional Model, WRF-Chem  

SciTech Connect

We have made a number of developments in the regional coupled model WRF-Chem, with the aim of making the model more suitable for prediction of atmospheric composition and of interactions between air quality and weather. We have worked on the European domain, with a particular focus on making the model suitable for the study of night time chemistry and oxidation by the nitrate radical in the UK atmosphere. A reduced form of the Common Reactive Intermediates gas-phase chemical mechanism (CRIv2-R5) has been implemented to enable more explicit simulation of VOC degradation. N2O5 heterogeneous chemistry has been added to the existing sectional MOSAIC aerosol module, and coupled to both the CRIv2-R5 and existing CBM-Z gas phase scheme. Modifications have also been made to the sea-spray aerosol emission representation, allowing the inclusion of primary organic material in sea-spray aerosol. Driven by appropriate emissions, wind fields and chemical boundary conditions, implementation of the different developments is illustrated in order to demonstrate the impact that these changes have in the North-West European domain. These developments are now part of the freely available WRF-Chem distribution.

Archer-Nicholls, Scott; Lowe, Douglas; Utembe, Steve; Allan, James D.; Zaveri, Rahul A.; Fast, Jerome D.; Hodnebrog, Oivind; Denier van der Gon, Hugo; McFiggans, Gordon

2014-11-08T23:59:59.000Z

18

Modeling Multi Output Filtering Effects in PCMOS  

E-Print Network (OSTI)

Modeling Multi Output Filtering Effects in PCMOS Anshul Singh*, Arindam Basu, Keck-Voon Ling, Nanyang Technological University (NTU), Singapore *NTU-Rice Institute of Sustainable and Applied Infodynamics (ISAID), NTU, Singapore $School of Computer Engineering, NTU, Singapore §School of ECE, Georgia

Mooney, Vincent

19

Tracking tropical cloud systems - Observations for the diagnosis of simulations by the Weather Research and Forecasting (WRF) Model  

SciTech Connect

To aid in improving model parameterizations of clouds and convection, we examine the capability of models, using explicit convection, to simulate the life cycle of tropical cloud systems in the vicinity of the ARM Tropical Western Pacific sites. The cloud life cycle is determined using a satellite cloud tracking algorithm (Boer and Ramanathan, 1997), and the statistics are compared to those of simulations using the Weather Research and Forecasting (WRF) Model. Using New York Blue, a Blue Gene/L supercomputer that is co-operated by Brookhaven and Stony Brook, simulations are run at a resolution comparable to the observations. Initial results suggest a computational paradox where, even though the size of the simulated systems are about half of that observed, their longevities are still similar. The explanation for this seeming incongruity will be explored.

Vogelmann, A.M.; Lin, W.; Cialella, A.; Luke, E.; Jensen, M.; Zhang, M.

2010-03-15T23:59:59.000Z

20

Tracking tropical cloud systems for the diagnosis of simulations by the weather research and forecasting (WRF) model  

SciTech Connect

To aid in improving model parameterizations of clouds and convection, we examine the capability of models, using explicit convection, to simulate the life cycle of tropical cloud systems in the tropical warm pool. The cloud life cycle is determined using a satellite cloud tracking algorithm (Boer and Ramanathan, J. Geophys. Res., 1997), and the statistics are compared to those of simulations using the Weather Research and Forecasting (WRF) Model. Using New York Blue, a Blue Gene/L supercomputer that is co-operated by Brookhaven and Stony Brook, simulations are run at a resolution comparable to the observations. Initial results suggest that the organization of the mesoscale convective systems is particularly sensitive to the cloud microphysics parameterization used.

Vogelmann, A.M.; Lin, W.; Cialella, A.; Luke, E. P.; Jensen, M. P.; Zhang, M. H.; Boer, E.

2010-06-27T23:59:59.000Z

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Assessing the CAM5 Physics Suite in the WRF-Chem Model: Implementation, Resolution Sensitivity, and a First Evaluation for a Regional Case Study  

SciTech Connect

A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 when the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem Parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.

Ma, Po-Lun; Rasch, Philip J.; Fast, Jerome D.; Easter, Richard C.; Gustafson, William I.; Liu, Xiaohong; Ghan, Steven J.; Singh, Balwinder

2014-05-06T23:59:59.000Z

22

A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height  

Science Journals Connector (OSTI)

The Weather Research and Forecasting Model (WRF) with 10-km horizontal grid spacing was used to explore improvements in wind speed forecasts at a typical wind turbine hub height (80 m). An ensemble consisting of WRF model simulations with ...

Adam J. Deppe; William A. Gallus Jr.; Eugene S. Takle

2013-02-01T23:59:59.000Z

23

A sensitivity study of the WRF model in wind simulation for an area of high wind energy  

Science Journals Connector (OSTI)

The performance of the Weather Research and Forecast (WRF) model in wind simulation was evaluated under different numerical and physical options for an area of Portugal, located in complex terrain and characterized by its significant wind energy resource. The grid nudging and integration time of the simulations were the tested numerical options. Since the goal is to simulate the near-surface wind, the physical parameterization schemes regarding the boundary layer were the ones under evaluation. Also, the influences of the local terrain complexity and simulation domain resolution on the model results were also studied. Data from three wind measuring stations located within the chosen area were compared with the model results, in terms of Root Mean Square Error, Standard Deviation Error and Bias. Wind speed histograms, occurrences and energy wind roses were also used for model evaluation. Globally, the model accurately reproduced the local wind regime, despite a significant underestimation of the wind speed. The wind direction is reasonably simulated by the model especially in wind regimes where there is a clear dominant sector, but in the presence of low wind speeds the characterization of the wind direction (observed and simulated) is very subjective and led to higher deviations between simulations and observations. Within the tested options, results show that the use of grid nudging in simulations that should not exceed an integration time of 2 days is the best numerical configuration, and the parameterization set composed by the physical schemes MM5ĖYonsei UniversityĖNoah are the most suitable for this site. Results were poorer in sites with higher terrain complexity, mainly due to limitations of the terrain data supplied to the model. The increase of the simulation domain resolution alone is not enough to significantly improve the model performance. Results suggest that error minimization in the wind simulation can be achieved by testing and choosing a suitable numerical and physical configuration for the region of interest together with the use of high resolution terrain data, if available.

David Carvalho; Alfredo Rocha; Moncho Gůmez-Gesteira; Carlos Santos

2012-01-01T23:59:59.000Z

24

Evaluation of the WRF meteorological model results during a high ozone episode in SW Poland - the role of model initial conditions  

Science Journals Connector (OSTI)

In meteorological, as well as air quality, modelling, input data plays an important role in the accuracy of the results, next to the model configuration. There are many sources of meteorological data available, both global and regional, and they differ not only by spatial and temporal resolution, but also by the number of observations included in the reanalysis and method of data assimilation used. In this study, the performance of the weather research and forecasting (WRF) model with two global reanalyses (ERA-Interim and NCEP FNL) used as input datasets has been assessed for a period of high tropospheric ozone concentrations. Both WRF model runs are in good agreement with observations, with IOA statistic ranging from 0.78 for wind speed to 0.98 for surface pressure. The ERA-Interim simulation showed better results for surface pressure, temperature and wind speed, while the performance of both datasets for parameters related to atmospheric moisture (e.g., dew point temperature) was comparable.

Kinga WaŇ?aszek; Maciej Kryza; MaŇ?gorzata Werner

2014-01-01T23:59:59.000Z

25

Ecosystem feedbacks to climate change in California: Development, testing, and analysis using a coupled regional atmosphere and land-surface model (WRF3-CLM3.5)  

SciTech Connect

A regional atmosphere model [Weather Research and Forecasting model version 3 (WRF3)] and a land surface model [Community Land Model, version 3.5 (CLM3.5)] were coupled to study the interactions between the atmosphere and possible future California land-cover changes. The impact was evaluated on California's climate of changes in natural vegetation under climate change and of intentional afforestation. The ability of WRF3 to simulate California's climate was assessed by comparing simulations by WRF3-CLM3.5 and WRF3-Noah to observations from 1982 to 1991. Using WRF3-CLM3.5, the authors performed six 13-yr experiments using historical and future large-scale climate boundary conditions from the Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1). The land-cover scenarios included historical and future natural vegetation from the Mapped Atmosphere-Plant-Soil System-Century 1 (MC1) dynamic vegetation model, in addition to a future 8-million-ha California afforestation scenario. Natural vegetation changes alone caused summer daily-mean 2-m air temperature changes of -0.7 to +1 C in regions without persistent snow cover, depending on the location and the type of vegetation change. Vegetation temperature changes were much larger than the 2-m air temperature changes because of the finescale spatial heterogeneity of the imposed vegetation change. Up to 30% of the magnitude of the summer daily-mean 2-m air temperature increase and 70% of the magnitude of the 1600 local time (LT) vegetation temperature increase projected under future climate change were attributable to the climate-driven shift in land cover. The authors projected that afforestation could cause local 0.2-1.2 C reductions in summer daily-mean 2-m air temperature and 2.0-3.7 C reductions in 1600 LT vegetation temperature for snow-free regions, primarily because of increased evapotranspiration. Because some of these temperature changes are of comparable magnitude to those projected under climate change this century, projections of climate and vegetation change in this region need to consider these climate-vegetation interactions.

Subin, Z.M.; Riley, W.J.; Kueppers, L.M.; Jin, J.; Christianson, D.S.; Torn, M.S.

2010-11-01T23:59:59.000Z

26

Development of an Efficient Regional Four-Dimensional Variational Data Assimilation System for WRF  

Science Journals Connector (OSTI)

This paper presents the development of a single executable four-dimensional variational data assimilation (4D-Var) system based on the Weather Research and Forecasting (WRF) Model through coupling the variational data assimilation algorithm (WRF-...

Xin Zhang; Xiang-Yu Huang; Jianyu Liu; Jonathan Poterjoy; Yonghui Weng; Fuqing Zhang; Hongli Wang

2014-12-01T23:59:59.000Z

27

Evaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air analysis  

E-Print Network (OSTI)

analyses of regional mod- eling with Polar WRF have been performed with results compared to selected localEvaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air.1.1 of the Weather Research and Forecasting model (WRF), a highresolution regional scale model, is used to simulate

Howat, Ian M.

28

On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model  

SciTech Connect

This is a conference proceeding that is now being put together as a book. This is chapter 2 of the book: "INTEGRATED SYSTEMS OF MESO-METEOROLOGICAL AND CHEMICAL TRANSPORT MODELS" published by Springer. The chapter title is "On-line Chemistry within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model." The original conference was the COST-728/NetFAM workshop on Integrated systems of meso-meteorological and chemical transport models, Danish Meteorological Institute, Copenhagen, May 21-23, 2007.

Grell, Georg; Fast, Jerome D.; Gustafson, William I.; Peckham, Steven E.; McKeen, Stuart A.; Salzmann, Marc; Freitas, Saulo

2010-01-01T23:59:59.000Z

29

The WRF nested within the CESM: Simulations of a midlatitude cyclone over the Southern Great Plains  

E-Print Network (OSTI)

The WRF nested within the CESM: Simulations of a midlatitude cyclone over the Southern Great Plains system in which the Weather Research and Forecasting model (WRF) is nested within the Community Earth has missed this cyclogenesis, while the nested WRF at 30 km grid spacing (or finer

Ohta, Shigemi

30

Analysis of the causes of heavy aerosol pollution in Beijing, China: A case study with the WRF-Chem model  

Science Journals Connector (OSTI)

Abstract The causes and variability of a heavy haze episode in the Beijing region was analyzed. During the episode, the PM2.5 concentration reached a peak value of 450†?g/kg on January 18, 2013 and rapidly decreased to 100†?g/kg on January 19, 2013, characterizing a large variability in a very short period. This strong variability provides a good opportunity to study the causes of the haze formation. The in situ measurements (including surface meteorological data and vertical structures of the winds, temperature, humidity, and planetary boundary layer (PBL)) together with a chemical/dynamical regional model (WRF-Chem) were used for the analysis. In order to understand the rapid variability of the PM2.5 concentration in the episode, the correlation between the measured meteorological data (including wind speed, PBL height, relative humidity, etc.) and the measured particle concentration (PM2.5 concentration) was studied. In addition, two sensitive model experiments were performed to study the effect of individual contribution from local emissions and regional surrounding emissions to the heavy haze formation. The results suggest that there were two major meteorological factors in controlling the variability of the PM2.5 concentration, namely, surface wind speed and PBL height. During high wind periods, the horizontal transport of aerosol particles played an important role, and the heavy haze was formed when the wind speeds were very weak (less than 1†m/s). Under weak wind conditions, the horizontal transport of aerosol particles was also weak, and the vertical mixing of aerosol particles played an important role. As a result, the PBL height was a major factor in controlling the variability of the PM2.5 concentration. Under the shallow PBL height, aerosol particles were strongly confined near the surface, producing a high surface PM2.5 concentration. The sensitivity model study suggests that the local emissions (emissions from the Beijing region only) were the major cause for the heavy haze events. With only local emissions, the calculated peak value of the PM2.5 concentration was 350†?g/kg, which accounted for 78% of the measured peak value (450†?g/kg). In contrast, without the local emissions, the calculated peak value of the PM2.5 concentration was only 100†?g/kg, which accounted for 22% of the measured peak value.

Hui He; Xuexi Tie; Qiang Zhang; Xiange Liu; Qian Gao; Xia Li; Yang Gao

2014-01-01T23:59:59.000Z

31

Evaluating regional cloud-permitting simulations of the WRF model for the Tropical Warm Pool International Cloud Experiment (TWP-ICE, Darwin 2006)  

SciTech Connect

Data from the Tropical Warm Pool I5 nternational Cloud Experiment (TWPICE) were used to evaluate two suites of high-resolution (4-7 km, convection-resolving) simulations of the Advanced Research Weather Research and Forecasting (WRF) model with a focus on the performance of different cloud microphysics (MP) schemes. The major difference between these two suites of simulations is with and without the reinitializing process. Whenreinitialized every three days, the four cloud MP schemes evaluated can capture the general profiles of cloud fraction, temperature, water vapor, winds, and cloud liquid and ice water content (LWC and IWC, respectively). However, compared with surface measurements of radiative and moisture fluxes and satellite retrieval of top-of-the-atmosphere (TOA) fluxes, disagreements do exist. Large discrepancies with observed LWC and IWC and derived radiative heating profiles can be attributed to both the limitations of the cloud property retrievals and model performance. The simulated precipitation also shows a wide range of uncertainty as compared with observations, which could be caused by the cloud MP schemes, complexity of land-sea configuration, and the high temporal and spatial variability. In general, our result indicates the importance of large-scale initial and lateral boundary conditions in re-producing basic features of cloudiness and its vertical structures. Based on our case study, we find overall the six-hydrometer single-moment MP scheme(WSM6) [Hong and Lim, 2006] in the WRF model si25 mulates the best agree- ment with the TWPICE observational analysis.

Wang, Yi; Long, Charles N.; Leung, Lai-Yung R.; Dudhia, Jimy; McFarlane, Sally A.; Mather, James H.; Ghan, Steven J.; Liu, Xiaodong

2009-11-05T23:59:59.000Z

32

Community Climate System Model (CCSM) Experiments and Output Data  

DOE Data Explorer (OSTI)

The CCSM web makes the source code of various versions of the model freely available and provides access to experiments that have been run and the resulting output data.

33

Formalization of computer input and output: the Hadley model  

Science Journals Connector (OSTI)

Current digital evidence acquisition tools are effective, but are tested rather than formally proven correct. We assert that the forensics community will benefit in evidentiary ways and the scientific community will benefit in practical ways by moving beyond simple testing of systems to a formal model. To this end, we present a hierarchical model of peripheral input to and output from von Neumann computers, patterned after the Open Systems Interconnection model of networking. The Hadley model categorizes all components of peripheral input and output in terms of data flow; with constructive aspects concentrated in the data flow between primary memory and the computer sides of peripherals' interfaces. The constructive domain of Hadley is eventually expandable to all areas of the I/O hierarchy, allowing for a full view of peripheral input and output and enhancing the forensics community's capabilities to analyze, obtain, and give evidentiary force to data.

Matthew Gerber; John Leeson

2004-01-01T23:59:59.000Z

34

MODELING MULTI-OUTPUT FILTERING EFFECTS IN PCMOS Anshul Singh*  

E-Print Network (OSTI)

MODELING MULTI-OUTPUT FILTERING EFFECTS IN PCMOS Anshul Singh* , Arindam Basu , Keck-Voon Ling* and Vincent J. Mooney III*$§ Email: anshul.singh@research.iiit.ac.in, {arindam.basu, ekvling}@ntu, Nanyang Technological University (NTU), Singapore * NTU-Rice Institute of Sustainable and Applied

Mooney, Vincent

35

Interpreting and analyzing model output (A very cursory introduction) Here will talk briefly about using "ncview" and "matlab" to analyze output  

E-Print Network (OSTI)

using "ncview" and "matlab" to analyze output from your model. The model output is in netcdf format for the output. I use matlab to measure, plot, compute, etc.. Recall the the model output is stored in: /scratch shown at the top.) matlab I hope you have some experience with matlab. There are handy tutorials

Gerber, Edwin

36

Statistical post processing of model output from the air quality model LOTOS-EUROS  

E-Print Network (OSTI)

Statistical post processing of model output from the air quality model LOTOS-EUROS Annemiek processing of model output from the air quality model LOTOS-EUROS Author: Annemiek Pijnappel Supervisor summary Air quality forecasts are produced routinely, focusing on concentrations of polluting gases

Stoffelen, Ad

37

Two-Way Integration of WRF and CCSM for Regional Climate Simulations  

SciTech Connect

Under the support of the DOE award DE-SC0004670, we have successfully developed an integrated climate modeling system by nesting Weather Research and Forecasting (WRF) model within the Community Climate System Model (CCSM) and the ensuing new generation Community Earth System Model (CESM). The integrated WRF/CESM system is intended as one method of global climate modeling with regional simulation capabilities. It allows interactive dynamical regional downscaling in the computational flow of present or future global climate simulations. This capability substantially simplifies the process of dynamical downscaling by avoiding massive intermediate model outputs at high frequency that are typically required for offline regional downscaling. The inline coupling also has the advantage of higher temporal resolution for the interaction between regional and global model components. With the aid of the inline coupling, a capability has also been developed to ingest other global climate simulations (by CESM or other models), which otherwise may not have necessary intermediate outputs for regional downscaling, to realize their embedded regional details. It is accomplished by relaxing the global atmospheric state of the integrated model to that of the source simulations with an appropriate time scale. This capability has the potential to open a new venue for ensemble regional climate simulations using a single modeling system. Furthermore, this new modeling system provides an effective modeling framework for the studies of physical and dynamical feedbacks of regional weather phenomena to the large scale circulation. The projected uses of this capability include the research of up-scaling effect of regional weather system, and its use as an alternative physical representation of sub-scale processes in coarser-resolution climate models.

Lin, Wuyin [Brookhaven National Laboratory] [Brookhaven National Laboratory; Zhang, Minghua [Stony Brook University] [Stony Brook University; He, Juanxiong [Stony Brook University] [Stony Brook University; Jiao, Xiangmin [Stony Brook University] [Stony Brook University; Chen, Ying [Stony Brook University] [Stony Brook University; Colle, Brian [Stony Brook University] [Stony Brook University; Vogelmann, Andrew M. [Brookhaven National Laboratory] [Brookhaven National Laboratory; Liu, Ping [Stony Brook University] [Stony Brook University; Khairoutdinov, Marat [Stony Brook University] [Stony Brook University; Leung, Ruby [Pacific Northwest National Laboratory] [Pacific Northwest National Laboratory

2013-07-12T23:59:59.000Z

38

Measurement and Modeling of Solar and PV Output Variability: Preprint  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Measurement and Modeling of Measurement and Modeling of Solar and PV Output Variability Preprint M. Sengupta To be presented at SOLAR 2011 Raleigh, North Carolina May 17-21, 2011 Conference Paper NREL/CP-5500-51105 April 2011 NOTICE The submitted manuscript has been offered by an employee of the Alliance for Sustainable Energy, LLC (Alliance), a contractor of the US Government under Contract No. DE-AC36-08GO28308. Accordingly, the US Government and Alliance retain a nonexclusive royalty-free license to publish or reproduce the published form of this contribution, or allow others to do so, for US Government purposes. This report was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor any agency thereof, nor any of their employees, makes any warranty,

39

FORMALIZATION OF INPUT AND OUTPUT IN MODERN OPERATING SYSTEMS: THE HADLEY MODEL.  

E-Print Network (OSTI)

??We present the Hadley model, a formal descriptive model of input and output for modern computer operating systems. Our model is intentionally inspired by theÖ (more)

Gerber, Matthew

2005-01-01T23:59:59.000Z

40

Modelling agricultural ammonia emissions: impact on particulate matter Hamaoui-Laguel L.1  

E-Print Network (OSTI)

: air/soil temperature, air/soil humidity, wind speed and rainfall are provided to Volt'Air by the outputs of the meteorological mesoscale model WRF (Weather Research and Forecasting; http://www.wrf- model://www.orleans.inra.fr/les_unites/us_infosol) are available at local scale and have been interpolated on the chosen grid scale (0.15¬į X 0.10¬į). Data about

Paris-Sud XI, Université de

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Linear model-based estimation of blood pressure and cardiac output for Normal and Paranoid cases  

Science Journals Connector (OSTI)

Provisioning a generic simple linear mathematical model for Paranoid and Healthy cases leading to auxiliary investigation of the neuroleptic drugs effect imposed on cardiac output (CO) and blood pressure (BP). Multi-input single output system identification ... Keywords: Blood pressure, Cardiac output, Heart rate, MISO transfer function, Stroke volume, System identification

Mohamed Abdelkader Aboamer, Ahmad Taher Azar, Khaled Wahba, Abdallah S. Mohamed

2014-11-01T23:59:59.000Z

42

Atmospheric Rivers Induced Heavy Precipitation and Flooding in the Western U.S. Simulated by the WRF Regional Climate Model  

SciTech Connect

Twenty years of regional climate simulated by the Weather Research and Forecasting model for North America has been analyzed to study the influence of the atmospheric rivers and the role of the land surface on heavy precipitation and flooding in the western U.S. Compared to observations, the simulation realistically captured the 95th percentile extreme precipitation, mean precipitation intensity, as well as the mean precipitation and temperature anomalies of all the atmospheric river events between 1980-1999. Contrasting the 1986 President Day and 1997 New Year Day atmospheric river events, differences in atmospheric stability are found to have an influence on the spatial distribution of precipitation in the Coastal Range of northern California. Although both cases yield similar amounts of heavy precipitation, the 1997 case was found to produce more runoff compared to the 1986 case. Antecedent soil moisture, the ratio of snowfall to total precipitation (which depends on temperature), and existing snowpack all seem to play a role, leading to a higher runoff to precipitation ratio simulated for the 1997 case. This study underscores the importance of characterizing or simulating atmospheric rivers and the land surface conditions for predicting floods, and for assessing the potential impacts of climate change on heavy precipitation and flooding in the western U.S.

Leung, Lai R.; Qian, Yun

2009-02-12T23:59:59.000Z

43

NCAR WRF-based data assimilation and forecasting systems for wind energy applications power  

E-Print Network (OSTI)

NCAR WRF-based data assimilation and forecasting systems for wind energy applications power Yuewei of these modeling technologies w.r.t. wind energy applications. Then I'll discuss wind farm

Kim, Guebuem

44

Surface Wind Regionalization over Complex Terrain: Evaluation and Analysis of a High-Resolution WRF Simulation  

Science Journals Connector (OSTI)

This study analyzes the daily-mean surface wind variability over an area characterized by complex topography through comparing observations and a 2-km-spatial-resolution simulation performed with the Weather Research and Forecasting (WRF) model ...

Pedro A. Jimťnez; J. Fidel GonzŠlez-Rouco; Elena GarcŪa-Bustamante; Jorge Navarro; Juan P. MontŠvez; Jordi Vilŗ-Guerau de Arellano; Jimy Dudhia; Antonio MuŮoz-Roldan

2010-02-01T23:59:59.000Z

45

Investigation of the aerosol-cloud interaction using the WRF framework  

E-Print Network (OSTI)

In this dissertation, a two-moment bulk microphysical scheme with aerosol effects is developed and implemented into the Weather Research and Forecasting (WRF) model to investigate the aerosol-cloud interaction. Sensitivities of cloud properties...

Li, Guohui

2009-05-15T23:59:59.000Z

46

A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height ADAM J. DEPPE AND WILLIAM A. GALLUS JR.  

E-Print Network (OSTI)

A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height ADAM J. DEPPE AND WILLIAM A in wind speed forecasts at a typical wind turbine hub height (80 m). An ensemble consisting of WRF model ensemble members for forecasting wind speed. A second configuration using three random perturbations

McCalley, James D.

47

An Advanced simulation Code for Modeling Inductive Output Tubes  

SciTech Connect

During the Phase I program, CCR completed several major building blocks for a 3D large signal, inductive output tube (IOT) code using modern computer language and programming techniques. These included a 3D, Helmholtz, time-harmonic, field solver with a fully functional graphical user interface (GUI), automeshing and adaptivity. Other building blocks included the improved electrostatic Poisson solver with temporal boundary conditions to provide temporal fields for the time-stepping particle pusher as well as the self electric field caused by time-varying space charge. The magnetostatic field solver was also updated to solve for the self magnetic field caused by time changing current density in the output cavity gap. The goal function to optimize an IOT cavity was also formulated, and the optimization methodologies were investigated.

Thuc Bui; R. Lawrence Ives

2012-04-27T23:59:59.000Z

48

Investigating Output Accuracy for a Discrete Event Simulation Model and an Agent Based Simulation Model  

E-Print Network (OSTI)

In this paper, we investigate output accuracy for a Discrete Event Simulation (DES) model and Agent Based Simulation (ABS) model. The purpose of this investigation is to find out which of these simulation techniques is the best one for modelling human reactive behaviour in the retail sector. In order to study the output accuracy in both models, we have carried out a validation experiment in which we compared the results from our simulation models to the performance of a real system. Our experiment was carried out using a large UK department store as a case study. We had to determine an efficient implementation of management policy in the store's fitting room using DES and ABS. Overall, we have found that both simulation models were a good representation of the real system when modelling human reactive behaviour.

Majid, Mazlina Abdul; Siebers, Peer-Olaf

2010-01-01T23:59:59.000Z

49

Impact of natural and anthropogenic aerosols on stratocumulus and precipitation in the Southeast Pacific: A regional modeling study using WRF-Chem  

SciTech Connect

Cloud-system resolving simulations with the chemistry version of the Weather Research and Forecasting (WRF-Chem) model are used to quantify the impacts of regional anthropogenic and oceanic emissions on changes in aerosol properties, cloud macro- and microphysics, and cloud radiative forcing over the Southeast Pacific (SEP) during the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) (15 OctĖNov 16, 2008). The effects of oceanic aerosols on cloud properties, precipitation, and the shortwave forcing counteract those of anthropogenic aerosols. Despite the relatively small changes in Na concentrations (2-12%) from regional oceanic emissions, their net effect (direct and indirect) on the surface shortwave forcing is opposite and comparable or even larger in magnitude compared to those of regional anthropogenic emissions over the SEP. Two distinct regions are identified in the VOCALS-REx domain. The near-coast polluted region is characterized with strong droplet activation suppression of small particles by sea-salt particles, the more important role of the first than the second indirect effect, low surface precipitation rate, and low aerosol-cloud interaction strength associated with anthropogenic emissions. The relatively clean remote region is characterized with large contributions of Cloud Condensation Nuclei (CCN, number concentration denoted by NCCN) and droplet number concentrations (Nd) from non-local sources (lateral boundaries), a significant amount of surface precipitation, and high aerosol-cloud interactions under a scenario of five-fold increase in anthropogenic emissions. In the clean region, cloud properties have high sensitivity (e.g., 13% increase in cloud-top height and a 9% surface albedo increase) to the moderate increase in CCN concentration (?Nccn = 13 cm-3; 25%) produced by a five-fold increase in regional anthropogenic emissions. The increased anthropogenic aerosols reduce the precipitation amount over the relatively clean remote ocean. The reduction of precipitation (as a cloud water sink) more than doubles the wet scavenging timescale, resulting in an increased aerosol lifetime in the marine boundary layer. Therefore, the aerosol impacts on precipitation are amplified by the positive feedback of precipitation on aerosol. The positive feedback ultimately alters the cloud micro- and macro-properties, leading to strong aerosol-cloud-precipitation interactions. The higher sensitivity of clouds to anthropogenic aerosols over this region is also related to a 16% entrainment rate increase due to anthropogenic aerosols. The simulated aerosol-cloud-precipitation interactions are stronger at night over the clean marine region, while during the day, solar heating results in more frequent decoupling, thinner clouds, reduced precipitation, and reduced sensitivity to anthropogenic emissions. The simulated high sensitivity to the increased anthropogenic emissions over the clean region suggests that the perturbation of the clean marine environment with anthropogenic aerosols may have a larger effect on climate than that of already polluted marine environments.

Yang, Qing; Gustafson, William I.; Fast, Jerome D.; Wang, Hailong; Easter, Richard C.; Wang, Minghuai; Ghan, Steven J.; Berg, Larry K.; Leung, Lai-Yung R.; Morrison, H.

2012-09-28T23:59:59.000Z

50

Design of fast output sampling feedback control for smart structure model  

Science Journals Connector (OSTI)

In this paper, the problem of modelling and output feedback control design for a smart structural system using piezoelectric material as a sensor/actuator is addressed. The model for a smart cantilever beam is developed by the finite element method. ... Keywords: output feedback, smart structure, vibration control

M. Umapathy; B. Bandyopadhyay

2007-01-01T23:59:59.000Z

51

Use of Advanced Meteorological Model Output for Coastal Ocean Modeling in Puget Sound  

SciTech Connect

It is a great challenge to specify meteorological forcing in estuarine and coastal circulation modeling using observed data because of the lack of complete datasets. As a result of this limitation, water temperature is often not simulated in estuarine and coastal modeling, with the assumption that density-induced currents are generally dominated by salinity gradients. However, in many situations, temperature gradients could be sufficiently large to influence the baroclinic motion. In this paper, we present an approach to simulate water temperature using outputs from advanced meteorological models. This modeling approach was applied to simulate annual variations of water temperatures of Puget Sound, a fjordal estuary in the Pacific Northwest of USA. Meteorological parameters from North American Region Re-analysis (NARR) model outputs were evaluated with comparisons to observed data at real-time meteorological stations. Model results demonstrated that NARR outputs can be used to drive coastal ocean models for realistic simulations of long-term water-temperature distributions in Puget Sound. Model results indicated that the net flux from NARR can be further improved with the additional information from real-time observations.

Yang, Zhaoqing; Khangaonkar, Tarang; Wang, Taiping

2011-06-01T23:59:59.000Z

52

Probabilistic Forecasts of Wind Speed: Ensemble Model Output Statistics  

E-Print Network (OSTI)

. Over the past two decades, ensembles of numerical weather prediction (NWP) models have been developed and phrases: Continuous ranked probability score; Density forecast; Ensem- ble system; Numerical weather prediction; Heteroskedastic censored regression; Tobit model; Wind energy. 1 #12;1 Introduction Accurate

Washington at Seattle, University of

53

Ensemble regression : using ensemble model output for atmospheric dynamics and prediction  

E-Print Network (OSTI)

Ensemble regression (ER) is a linear inversion technique that uses ensemble statistics from atmospheric model output to make dynamical inferences and forecasts. ER defines a multivariate regression operator using ensemble ...

Gombos, Daniel (Daniel Lawrence)

2009-01-01T23:59:59.000Z

54

Modelling power output at nuclear power plant by neural networks  

Science Journals Connector (OSTI)

In this paper, we propose two different neural network (NN) approaches for industrial process signal forecasting. Real data is available for this research from boiling water reactor type nuclear power reactors. NNs are widely used for time series prediction, ... Keywords: evaluation methods, model input selection, neural networks, nuclear power plant, one-step ahead prediction

Jaakko Talonen; Miki Sirola; Eimontas Augilius

2010-09-01T23:59:59.000Z

55

Neural Networks for Post-processing Model Output: Caren Marzban  

E-Print Network (OSTI)

variables to the neural network are: Forecast hour, model forecast temperature, relative humidity, wind direction and speed, mean sea level pressure, cloud cover, and precipitation rate and amount. The single to being able to approximate a large class of functions, they are less inclined to overfit data than some

Marzban, Caren

56

Evaluation of a WRF dynamical downscaling simulation over California  

E-Print Network (OSTI)

long-term precipitation climatology from WRF, CCSM3, NARR,? Pr Fig. 2 Annual Pr climatology from WRF, CCSM3, and NARRresults shown here are climatologies and thus donít account

Caldwell, Peter; Chin, Hung-Neng S.; Bader, David C.; Bala, Govindasamy

2009-01-01T23:59:59.000Z

57

The Formation of Multiple Squall Lines and the Impacts of WSR-88D Radial Winds in a WRF Simulation  

Science Journals Connector (OSTI)

A detailed observational and Weather Research and Forecasting (WRF) model analysis utilizing Weather Surveillance Radar-1988 Doppler (WSR-88D), surface, and upper-air observations, as well as Geostationary Operational Environmental Satellite (...

Haldun Karan; Patrick J. Fitzpatrick; Christopher M. Hill; Yongzuo Li; Qingnong Xiao; Eunha Lim

2010-02-01T23:59:59.000Z

58

Multi-decadal Evaluation of WRF Downscaling Capabilities Over Western Australia in Simulating Rainfall and Temperature Extremes  

Science Journals Connector (OSTI)

We evaluate a 30 year (1981-2010) Weather Research and Forecast Model (WRF) regional climate simulation over the south-west of Western Australia (SWWA), a region with a Mediterranean climate, using ERA-Interim boundary conditions. Our analysis ...

Julia Andrys; Thomas J Lyons; Jatin Kala

59

Simulating atmosphere flow for wind energy applications with WRF-LES  

SciTech Connect

Forecasts of available wind energy resources at high spatial resolution enable users to site wind turbines in optimal locations, to forecast available resources for integration into power grids, to schedule maintenance on wind energy facilities, and to define design criteria for next-generation turbines. This array of research needs implies that an appropriate forecasting tool must be able to account for mesoscale processes like frontal passages, surface-atmosphere interactions inducing local-scale circulations, and the microscale effects of atmospheric stability such as breaking Kelvin-Helmholtz billows. This range of scales and processes demands a mesoscale model with large-eddy simulation (LES) capabilities which can also account for varying atmospheric stability. Numerical weather prediction models, such as the Weather and Research Forecasting model (WRF), excel at predicting synoptic and mesoscale phenomena. With grid spacings of less than 1 km (as is often required for wind energy applications), however, the limits of WRF's subfilter scale (SFS) turbulence parameterizations are exposed, and fundamental problems arise, associated with modeling the scales of motion between those which LES can represent and those for which large-scale PBL parameterizations apply. To address these issues, we have implemented significant modifications to the ARW core of the Weather Research and Forecasting model, including the Nonlinear Backscatter model with Anisotropy (NBA) SFS model following Kosovic (1997) and an explicit filtering and reconstruction technique to compute the Resolvable Subfilter-Scale (RSFS) stresses (following Chow et al, 2005).We are also modifying WRF's terrain-following coordinate system by implementing an immersed boundary method (IBM) approach to account for the effects of complex terrain. Companion papers presenting idealized simulations with NBA-RSFS-WRF (Mirocha et al.) and IBM-WRF (K. A. Lundquist et al.) are also presented. Observations of flow through the Altamont Pass (Northern California) wind farm are available for validation of the WRF modeling tool for wind energy applications. In this presentation, we use these data to evaluate simulations using the NBA-RSFS-WRF tool in multiple configurations. We vary nesting capabilities, multiple levels of RSFS reconstruction, SFS turbulence models (the new NBA turbulence model versus existing WRF SFS turbulence models) to illustrate the capabilities of the modeling tool and to prioritize recommendations for operational uses. Nested simulations which capture both significant mesoscale processes as well as local-scale stable boundary layer effects are required to effectively predict available wind resources at turbine height.

Lundquist, J K; Mirocha, J D; Chow, F K; Kosovic, B; Lundquist, K A

2008-01-14T23:59:59.000Z

60

Resampling of regional climate model output for the simulation of extreme river flows  

E-Print Network (OSTI)

for the simulation of extreme river flows. This is important to assess the impact of climate change on river flooding biases in the RCM data, the simulated extreme flood quantiles correspond quite well with those obtainedResampling of regional climate model output for the simulation of extreme river flows Robert

Haak, Hein

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Probabilistic Forecasting of (Severe) Thunderstorms in the Netherlands Using Model Output Statistics  

E-Print Network (OSTI)

Probabilistic Forecasting of (Severe) Thunderstorms in the Netherlands Using Model Output Statistics MAURICE J. SCHMEITS, KEES J. KOK, AND DAAN H. P. VOGELEZANG Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands (Manuscript received 29 April 2004, in final form 7 September 2004

Schmeits, Maurice

62

Using Weather Data and Climate Model Output in Economic Analyses of Climate Change  

SciTech Connect

Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overview of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.

Auffhammer, Maximilian [University of California at Berkeley; Hsiang, Solomon M. [Princeton University; Schlenker, Wolfram [Columbia University; Sobel, Adam H. [Columbia University

2013-06-28T23:59:59.000Z

63

Evaluation of WRF-Predicted Near-Hub-Height Winds and Ramp Events over a Pacific Northwest Site with Complex Terrain  

Science Journals Connector (OSTI)

One challenge with wind-power forecasts is the accurate prediction of rapid changes in wind speed (ramps). To evaluate the Weather Research and Forecasting (WRF) model's ability to predict such events, model simulations, conducted over an area of ...

Qing Yang; Larry K. Berg; Mikhail Pekour; Jerome D. Fast; Rob K. Newsom; Mark Stoelinga; Catherine Finley

2013-08-01T23:59:59.000Z

64

Cardiac output and stroke volume estimation using a hybrid of three models  

E-Print Network (OSTI)

Cardiac output (CO) and stroke volume (SV) are the key hemodynamic parameters to be monitored and assessed in ambulatory and critically ill patients. The purpose of this study was to introduce and validate a new algorithm ...

Arai, Tatsuya

65

Modelling Dynamic Constraints in Electricity Markets and the Costs of Uncertain Wind Output  

E-Print Network (OSTI)

shifts between periods. Finally, higher variable costs, incurred if power stations are operated below their optimal rating, are allocated to the locally lowest de- mand. For inflexible power stations like nuclear, combined cycle gas turbines or coal... the start of the station has to be decided several hours before delivering output. At the earlier time there is still uncertainty about the future demand, possible failures of power stations and predictions for wind-output. We represent the uncertainty...

Musgens, Felix; Neuhoff, Karsten

2006-03-14T23:59:59.000Z

66

Robust UAV Coordination for Target Tracking using Output-Feedback Model Predictive Control with Moving Horizon Estimation  

E-Print Network (OSTI)

Robust UAV Coordination for Target Tracking using Output-Feedback Model Predictive Control consider the control of two UAVs tracking an evasive moving ground vehicle. The UAVs are small fixed to maintain visibility. The control inputs to the UAVs are computed based on noisy measurements of the UAVs

Hespanha, Jo√£o Pedro

67

Output Analysis  

Science Journals Connector (OSTI)

Every discrete-event simulation experiment with random input generates random sample paths as output. Each path usually consists of a sequence of dependent observations that serve as the raw material for estim...

George S. Fishman

2001-01-01T23:59:59.000Z

68

Evaluating WRF-Chem aerosol indirect effects in Southeast Pacific marine stratocumulus during VOCALS-REx  

SciTech Connect

We evaluate a regional-scale simulation with the WRF-Chem model for the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx), which sampled the Southeast Pacific's persistent stratocumulus deck. Evaluation of VOCALS-REx ship-based and aircraft observations focuses on analyzing how aerosol loading affects marine boundary layer (MBL) dynamics and cloud microphysics. We compare local time series and campaign averaged longitudinal gradients, and highlight differences in model simulations with (W) and without wet (NW) deposition processes. The higher aerosol loadings in the NW case produce considerable changes in MBL dynamics and cloud microphysics, in accordance with the established conceptual model of aerosol indirect effects. These include increase in cloud albedo, increase in MBL and cloud heights, drizzle suppression, increase in liquid water content, and increase in cloud lifetime. Moreover, better statistical representation of aerosol mass and number concentration improves model fidelity in reproducing observed spatial and temporal variability in cloud properties, including top and base height, droplet concentration, water content, rain rate, optical depth (COD) and liquid water path (LWP). Together, these help to quantify confidence in WRF-Chem's modeled aerosol-cloud interactions, while identifying structural and parametric uncertainties including: irreversibility in rain wet removal; overestimation of marine DMS and sea salt emissions and accelerated aqueous sulfate conversion. Our findings suggest that WRF-Chem simulates marine cloud-aerosol interactions at a level sufficient for applications in forecasting weather and air quality and studying aerosol climate forcing, including the reliability required for policy analysis and geo-engineering applications.

Saide, Pablo; Spak, S. N.; Carmichael, Gregory; Mena-Carrasco, M. A.; Yang, Qing; Howell, S. G.; Leon, Dolislager; Snider, Jefferson R.; Bandy, Alan R.; Collett, Jeffrey L.; Benedict, K. B.; de Szoeke, S.; Hawkins, Lisa; Allen, Grant; Crawford, I.; Crosier, J.; Springston, S. R.

2012-03-30T23:59:59.000Z

69

WRF-Fire Applied in Bulgaria Nina Dobrinkova1  

E-Print Network (OSTI)

and Statistical Sciences University of Colorado Denver jan.mandel@ucdenver.edu Abstract. WRF-Fire consists in a wildfire. Bulgaria as part of this region also has huge problems with wildland fires. Statistics have been]. Even though the number of wildfires is increasing and the consequences are not only of environmental

Mustakerov, Ivan

70

Scalable extraction of error models from the output of error detection circuits  

E-Print Network (OSTI)

Accurate methods of assessing the performance of quantum gates are extremely important. Quantum process tomography and randomized benchmarking are the current favored methods. Quantum process tomography gives detailed information, but significant approximations must be made to reduce this information to a form quantum error correction simulations can use. Randomized benchmarking typically outputs just a single number, the fidelity, giving no information on the structure of errors during the gate. Neither method is optimized to assess gate performance within an error detection circuit, where gates will be actually used in a large-scale quantum computer. Specifically, the important issues of error composition and error propagation lie outside the scope of both methods. We present a fast, simple, and scalable method of obtaining exactly the information required to perform effective quantum error correction from the output of continuously running error detection circuits, enabling accurate prediction of large-scale behavior.

Austin G. Fowler; D. Sank; J. Kelly; R. Barends; John M. Martinis

2014-05-06T23:59:59.000Z

71

The Dispersion of Silver Iodide Particles from Ground-Based Generators over Complex Terrain. Part II: WRF Large-Eddy Simulations versus Observations  

Science Journals Connector (OSTI)

A numerical modeling study has been conducted to explore the ability of the Weather Research and Forecasting (WRF) model-based large-eddy simulation (LES) with 100-m grid spacing to reproduce silver iodide (AgI) particle dispersion by comparing ...

Lulin Xue; Xia Chu; Roy Rasmussen; Daniel Breed; Bruce Boe; Bart Geerts

2014-06-01T23:59:59.000Z

72

ARM - Measurement - Liquid water path  

NLE Websites -- All DOE Office Websites (Extended Search)

Cloud Products Using Visst Algorithm PRECIPRET : Precipitation Retrievals WRF-CHEM : Weather Research and Forecasting (WRF) Model Output Value-Added Products MWRAVG :...

73

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Landfill Gas: Consumption for Useful Thermal Output, B. Landfill Gas: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Million Cubic Feet) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 993 0 116 0 876 2004 2,174 0 735 10 1,429 2005 1,923 0 965 435 522 2006 2,051 0 525 1,094 433 2007 1,988 0 386 1,102 501 2008 1,025 0 454 433 138 2009 793 0 545 176 72 2010 1,623 0 1,195 370 58 2011 3,195 0 2,753 351 91 2012 3,189 0 2,788 340 61 2010 January 118 0 83 30 5 February 110 0 79 27 5 March 132 0 94 32 6 April 131 0 93 33 6 May 132 0 92 34 6 June 139 0 104 30 5 July 140 0 102 33 5 August 132 0 95 32 5 September 148 0 113 30 5

74

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Petroleum Coke: Consumption for Useful Thermal Output, B. Petroleum Coke: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 517 0 111 6 399 2003 763 0 80 9 675 2004 1,043 0 237 8 798 2005 783 0 206 8 568 2006 1,259 0 195 9 1,055 2007 1,262 0 162 11 1,090 2008 897 0 119 9 769 2009 1,007 0 126 8 873 2010 1,059 0 98 11 950 2011 1,080 0 112 6 962 2012 1,346 0 113 11 1,222 2010 January 92 0 10 1 81 February 93 0 10 1 82 March 84 0 12 1 71 April 76 0 9 1 66 May 84 0 10 0 75 June 93 0 8 0 86 July 89 0 8 0 80 August 87 0 2 1 84 September 82 0 2 1 79

75

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

F. Petroleum Coke: Consumption for Electricity Generation and Useful Thermal Output, F. Petroleum Coke: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 193,120 57,296 105,416 227 30,182 2003 197,827 69,695 92,384 309 35,440 2004 245,389 116,086 90,747 259 38,297 2005 256,441 115,727 111,098 260 29,356 2006 246,687 102,117 98,314 269 45,987 2007 208,198 77,941 81,845 348 48,064 2008 180,034 64,843 79,856 280 35,055 2009 166,449 77,919 52,428 245 35,856 2010 173,078 94,331 41,090 340 37,317 2011 176,349 99,257 40,167 173 36,752 2012 144,266 60,862 24,925 353 58,126 2010 January 14,949 7,995 3,716 38 3,199

76

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

C. Coal: Consumption for Electricity Generation and Useful Thermal Output, C. Coal: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 1,005,144 767,803 209,703 1,405 26,232 2003 1,031,778 757,384 247,732 1,816 24,846 2004 1,044,798 772,224 244,044 1,917 26,613 2005 1,065,281 761,349 276,135 1,922 25,875 2006 1,053,783 753,390 273,246 1,886 25,262 2007 1,069,606 764,765 280,377 1,927 22,537 2008 1,064,503 760,326 280,254 2,021 21,902 2009 955,190 695,615 238,012 1,798 19,766 2010 1,001,411 721,431 253,621 1,720 24,638 2011 956,470 689,316 243,168 1,668 22,319 2012 845,066 615,467 208,085 1,450 20,065

77

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

E. Landfill Gas: Consumption for Useful Thermal Output, E. Landfill Gas: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 500 0 61 0 439 2004 1,158 0 415 5 738 2005 994 0 519 212 263 2006 1,034 0 267 549 218 2007 985 0 226 532 228 2008 552 0 271 211 70 2009 440 0 313 91 37 2010 847 0 643 174 30 2011 1,635 0 1,422 165 48 2012 1,630 0 1,441 156 32 2010 January 61 0 44 14 3 February 58 0 42 13 3 March 67 0 49 15 3 April 67 0 49 15 3 May 68 0 49 16 3 June 73 0 56 14 3 July 73 0 55 16 2 August 69 0 52 15 3 September 79 0 62 14 3 October 75 0 59 14 2

78

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Coal: Consumption for Useful Thermal Output, B. Coal: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 17,561 0 2,255 929 14,377 2003 17,720 0 2,080 1,234 14,406 2004 24,275 0 3,809 1,540 18,926 2005 23,833 0 3,918 1,544 18,371 2006 23,227 0 3,834 1,539 17,854 2007 22,810 0 3,795 1,566 17,449 2008 22,168 0 3,689 1,652 16,827 2009 20,507 0 3,935 1,481 15,091 2010 21,727 0 3,808 1,406 16,513 2011 21,532 0 3,628 1,321 16,584 2012 19,333 0 2,790 1,143 15,400 2010 January 1,972 0 371 160 1,440 February 1,820 0 347 139 1,334 March 1,839 0 338 123 1,378 April 2,142 0 284 95 1,764

79

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

E. Petroleum Liquids: Consumption for Useful Thermal Output, E. Petroleum Liquids: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 76,737 0 1,669 3,276 71,788 2003 85,488 0 6,963 3,176 75,349 2004 124,809 0 8,592 7,219 108,997 2005 125,689 0 8,134 6,145 111,410 2006 87,137 0 6,740 3,481 76,916 2007 82,768 0 7,602 2,754 72,412 2008 45,481 0 7,644 2,786 35,051 2009 48,912 0 7,557 1,802 39,552 2010 29,243 0 6,402 1,297 21,545 2011 22,799 0 5,927 1,039 15,833 2012 18,233 0 5,871 746 11,616 2010 January 3,648 0 614 190 2,843 February 3,027 0 422 157 2,447 March 2,015 0 272 43 1,699

80

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

C. Petroleum Liquids: Consumption for Electricity Generation and Useful Thermal Output, C. Petroleum Liquids: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Barrels) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 146,643 88,595 39,320 1,210 17,517 2003 189,260 105,319 62,617 1,394 19,929 2004 185,761 103,793 57,843 1,963 22,162 2005 185,631 98,223 63,546 1,584 22,278 2006 87,898 53,529 18,332 886 15,150 2007 95,895 56,910 24,097 691 14,198 2008 61,379 38,995 14,463 621 7,300 2009 51,690 31,847 11,181 477 8,185 2010 44,968 30,806 9,364 376 4,422 2011 31,152 20,844 6,637 301 3,370 2012 25,702 17,521 5,102 394 2,685 2010 January 6,193 4,381 1,188 48 576

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

E. Wood / Wood Waste Biomass: Consumption for Useful Thermal Output, E. Wood / Wood Waste Biomass: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 682,060 0 9,585 727 671,747 2003 746,375 0 10,893 762 734,720 2004 1,016,124 0 14,968 1,493 999,663 2005 997,331 0 19,193 1,028 977,111 2006 1,049,161 0 18,814 1,045 1,029,303 2007 982,486 0 21,435 1,756 959,296 2008 923,889 0 18,075 1,123 904,690 2009 816,285 0 19,587 1,135 795,563 2010 876,041 0 18,357 1,064 856,620 2011 893,314 0 16,577 1,022 875,716 2012 883,158 0 19,251 949 862,958 2010 January 73,418 0 1,677 91 71,651 February 67,994 0 1,689 81 66,224

82

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

F. Landfill Gas: Consumption for Electricity Generation and Useful Thermal Output, F. Landfill Gas: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 66,270 3,930 59,149 1,753 1,438 2004 70,489 5,373 60,929 2,098 2,089 2005 68,897 5,650 59,144 2,571 1,532 2006 77,004 8,287 64,217 3,937 563 2007 80,697 8,620 68,657 2,875 544 2008 94,768 10,242 81,300 2,879 346 2009 100,261 9,748 87,086 3,089 337 2010 106,681 10,029 93,405 3,011 236 2011 114,173 11,146 91,279 11,497 251 2012 125,927 12,721 101,379 10,512 1,315 2010 January 8,502 853 7,379 251 19 February 7,882 830 6,823 209 20

83

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

E. Other Waste Biomass: Consumption for Useful Thermal Output, E. Other Waste Biomass: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 29,854 0 10,655 757 18,442 2004 30,228 0 12,055 2,627 15,547 2005 38,010 0 10,275 2,086 25,649 2006 36,966 0 8,561 2,318 26,087 2007 41,757 0 10,294 2,643 28,820 2008 41,851 0 9,674 1,542 30,635 2009 41,810 0 10,355 1,638 29,817 2010 47,153 0 8,436 1,648 37,070 2011 43,483 0 6,460 1,566 35,458 2012 46,863 0 6,914 1,796 38,153 2010 January 4,885 0 1,088 137 3,661 February 4,105 0 943 137 3,025 March 4,398 0 845 136 3,417 April 4,224 0 399 138 3,688

84

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

E. Petroleum Coke: Consumption for Useful Thermal Output, E. Petroleum Coke: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 14,395 0 3,192 179 11,024 2003 21,170 0 2,282 244 18,644 2004 29,342 0 6,768 226 22,347 2005 22,224 0 5,935 228 16,061 2006 38,169 0 5,672 236 32,262 2007 38,033 0 4,710 303 33,019 2008 27,100 0 3,441 243 23,416 2009 29,974 0 3,652 213 26,109 2010 31,303 0 2,855 296 28,152 2011 31,943 0 3,244 153 28,546 2012 38,777 0 3,281 315 35,181 2010 January 2,683 0 285 33 2,365 February 2,770 0 302 29 2,439 March 2,424 0 338 36 2,050 April 2,257 0 255 22 1,980

85

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

F. Other Waste Biomass: Consumption for Electricity Generation and Useful Thermal Output, F. Other Waste Biomass: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 64,629 2,456 26,514 5,323 30,337 2004 49,443 2,014 21,294 6,935 19,201 2005 55,862 2,485 17,640 6,763 28,974 2006 54,693 2,611 16,348 6,755 28,980 2007 60,840 2,992 19,155 6,692 32,001 2008 66,139 3,409 22,419 5,227 35,085 2009 66,658 3,679 23,586 5,398 33,994 2010 77,150 3,668 22,884 5,438 45,159 2011 74,255 4,488 22,574 5,382 41,810 2012 77,205 4,191 22,654 5,812 44,548 2010 January 7,109 189 2,166 458 4,295 February 6,441 275 2,151 429 3,586

86

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

F. Natural Gas: Consumption for Electricity Generation and Useful Thermal Output, F. Natural Gas: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 7,135,572 2,307,358 3,481,961 75,985 1,270,268 2003 6,498,549 1,809,003 3,450,177 60,662 1,178,707 2004 6,912,661 1,857,247 3,749,945 73,744 1,231,725 2005 7,220,520 2,198,098 3,837,717 69,682 1,115,023 2006 7,612,500 2,546,169 3,847,644 69,401 1,149,286 2007 8,181,986 2,808,500 4,219,827 71,560 1,082,099 2008 7,900,986 2,803,283 4,046,069 67,571 984,062 2009 8,138,385 2,981,285 4,062,633 77,077 1,017,390 2010 8,694,186 3,359,035 4,191,241 87,357 1,056,553

87

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Biogenic Municipal Solid Waste: Consumption for Useful Thermal Output, B. Biogenic Municipal Solid Waste: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 1,358 0 311 865 182 2004 2,743 0 651 1,628 464 2005 2,719 0 623 1,536 560 2006 2,840 0 725 1,595 520 2007 2,219 0 768 1,136 315 2008 2,328 0 806 1,514 8 2009 2,426 0 823 1,466 137 2010 2,287 0 819 1,316 152 2011 2,044 0 742 1,148 154 2012 1,986 0 522 1,273 190 2010 January 191 0 69 107 14 February 178 0 61 106 11 March 204 0 66 126 12 April 207 0 67 127 13 May 249 0 67 167 15 June 204 0 69 120 14 July 194 0 68 115 11

88

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

C. Landfill Gas: Consumption for Electricity Generation and Useful Thermal Output, C. Landfill Gas: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Million Cubic Feet) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 137,414 9,168 122,100 3,280 2,865 2004 146,018 11,250 126,584 4,091 4,093 2005 143,822 11,490 124,030 5,232 3,070 2006 162,084 16,617 136,632 7,738 1,096 2007 168,762 17,442 144,490 5,699 1,131 2008 196,802 20,465 170,001 5,668 668 2009 207,585 19,583 181,234 6,106 661 2010 219,954 19,975 193,623 5,905 451 2011 235,990 22,086 183,609 29,820 474 2012 259,564 25,193 204,753 27,012 2,606 2010 January 17,649 1,715 15,406 491 37 February 16,300 1,653 14,198 410 38

89

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

C. Petroleum Coke: Consumption for Electricity Generation and Useful Thermal Output, C. Petroleum Coke: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 7,353 2,125 3,691 8 1,529 2003 7,067 2,554 3,245 11 1,257 2004 8,721 4,150 3,223 9 1,339 2005 9,113 4,130 3,953 9 1,020 2006 8,622 3,619 3,482 10 1,511 2007 7,299 2,808 2,877 12 1,602 2008 6,314 2,296 2,823 10 1,184 2009 5,828 2,761 1,850 9 1,209 2010 6,053 3,325 1,452 12 1,264 2011 6,092 3,449 1,388 6 1,248 2012 5,021 2,105 869 13 2,034 2010 January 525 283 130 1 110 February 497 258 131 1 106 March 522 308 119 1 94

90

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

E. Biogenic Municipal Solid Waste: Consumption for Useful Thermal Output, E. Biogenic Municipal Solid Waste: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 13,694 0 3,118 8,858 1,718 2004 19,991 0 4,746 12,295 2,950 2005 20,296 0 4,551 11,991 3,754 2006 21,729 0 5,347 12,654 3,728 2007 16,174 0 5,683 8,350 2,141 2008 18,272 0 6,039 12,174 59 2009 18,785 0 6,229 11,535 1,021 2010 17,502 0 6,031 10,333 1,138 2011 16,766 0 5,807 9,731 1,227 2012 16,310 0 4,180 10,615 1,515 2010 January 1,476 0 518 851 107 February 1,365 0 444 835 86 March 1,572 0 486 992 93 April 1,598 0 495 1,003 100

91

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Petroleum Liquids: Consumption for Useful Thermal Output, B. Petroleum Liquids: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Barrels) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 12,228 0 286 384 11,558 2003 14,124 0 1,197 512 12,414 2004 20,654 0 1,501 1,203 17,951 2005 20,494 0 1,392 1,004 18,097 2006 14,077 0 1,153 559 12,365 2007 13,462 0 1,303 441 11,718 2008 7,533 0 1,311 461 5,762 2009 8,128 0 1,301 293 6,534 2010 4,866 0 1,086 212 3,567 2011 3,826 0 1,004 168 2,654 2012 3,097 0 992 122 1,984 2010 January 606 0 105 31 470 February 504 0 78 26 401 March 335 0 46 7 281 April 355 0 86 9 260 May 340 0 93 14 232

92

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

E. Natural Gas: Consumption for Useful Thermal Output, E. Natural Gas: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 885,987 0 267,675 45,359 572,953 2003 762,779 0 250,120 21,238 491,421 2004 1,085,191 0 398,476 40,122 646,593 2005 1,008,404 0 392,842 35,037 580,525 2006 968,574 0 339,047 33,928 595,599 2007 894,272 0 347,181 36,689 510,402 2008 813,794 0 333,197 33,434 447,163 2009 836,863 0 312,553 42,032 482,279 2010 841,521 0 308,246 47,001 486,274 2011 861,006 0 315,411 40,976 504,619 2012 909,087 0 330,354 48,944 529,788 2010 January 74,586 0 27,368 4,148 43,070 February 65,539 0 24,180 3,786 37,573

93

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Useful Thermal Output by Energy Source: Electric Power Sector Combined Heat and Power, 2002 - 2012 2. Useful Thermal Output by Energy Source: Electric Power Sector Combined Heat and Power, 2002 - 2012 (Billion Btus) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Renewable Sources Other Total Annual Totals 2002 40,020 1,319 2,550 214,137 5,961 12,550 4,732 281,269 2003 38,249 5,551 1,828 200,077 9,282 19,785 3,296 278,068 2004 39,014 5,731 2,486 239,416 18,200 17,347 3,822 326,017 2005 39,652 5,571 2,238 239,324 36,694 18,240 3,884 345,605 2006 38,133 4,812 2,253 207,095 22,567 17,284 4,435 296,579 2007 38,260 5,294 1,862 212,705 20,473 19,166 4,459 302,219 2008 37,220 5,479 1,353 204,167 22,109 17,052 4,854 292,234 2009 38,015 5,341 1,445 190,875 19,830 17,625 5,055 278,187

94

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Useful Thermal Output by Energy Source: Commerical Sector Combined Heat and Power, 2002 - 2012 3. Useful Thermal Output by Energy Source: Commerical Sector Combined Heat and Power, 2002 - 2012 (Billion Btus) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Renewable Sources Other Total Annual Totals 2002 18,477 2,600 143 36,265 0 6,902 4,801 69,188 2003 22,780 2,520 196 16,955 0 8,296 6,142 56,889 2004 22,450 4,118 165 21,851 0 8,936 6,350 63,871 2005 22,601 3,518 166 20,227 0 8,647 5,921 61,081 2006 22,186 2,092 172 19,370 0.22 9,359 6,242 59,422 2007 22,595 1,640 221 20,040 0 6,651 3,983 55,131 2008 22,991 1,822 177 20,183 0 8,863 6,054 60,091 2009 20,057 1,095 155 25,902 0 8,450 5,761 61,420 2010 19,216 845 216 29,791 13 7,917 5,333 63,330 2011 17,234 687 111 24,848 14 7,433 5,988 56,314

95

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

F. Petroleum Liquids: Consumption for Electricity Generation and Useful Thermal Output, F. Petroleum Liquids: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 912,218 553,390 243,561 7,229 108,031 2003 1,174,795 658,868 387,341 8,534 120,051 2004 1,156,763 651,712 358,685 11,763 134,603 2005 1,160,733 618,811 395,489 9,614 136,820 2006 546,529 335,130 112,052 5,444 93,903 2007 595,191 355,999 147,579 4,259 87,354 2008 377,848 242,379 87,460 3,743 44,266 2009 315,420 196,346 66,834 2,903 49,336 2010 273,357 188,987 55,444 2,267 26,660 2011 186,753 125,755 39,093 1,840 20,066 2012 153,189 105,179 29,952 2,364 15,695

96

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Natural Gas: Consumption for Useful Thermal Output, B. Natural Gas: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Million Cubic Feet) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 860,024 0 263,619 41,435 554,970 2003 721,267 0 225,967 19,973 475,327 2004 1,052,100 0 388,424 39,233 624,443 2005 984,340 0 384,365 34,172 565,803 2006 942,817 0 330,878 33,112 578,828 2007 872,579 0 339,796 35,987 496,796 2008 793,537 0 326,048 32,813 434,676 2009 816,787 0 305,542 41,275 469,970 2010 821,775 0 301,769 46,324 473,683 2011 839,681 0 308,669 39,856 491,155 2012 886,103 0 322,607 47,883 515,613 2010 January 72,867 0 26,791 4,086 41,990

97

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

E. Coal: Consumption for Useful Thermal Output, E. Coal: Consumption for Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 421,084 0 50,041 23,099 347,944 2003 416,700 0 47,817 28,479 340,405 2004 564,497 0 87,981 34,538 441,978 2005 548,666 0 88,364 34,616 425,685 2006 532,561 0 84,335 34,086 414,140 2007 521,717 0 83,838 34,690 403,189 2008 503,096 0 81,416 36,163 385,517 2009 462,674 0 90,867 32,651 339,156 2010 490,931 0 90,184 30,725 370,022 2011 479,822 0 84,855 28,056 366,911 2012 420,923 0 58,275 23,673 338,975 2010 January 44,514 0 8,627 3,445 32,442 February 40,887 0 8,041 3,024 29,823

98

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

F. Wood / Wood Waste Biomass: Consumption for Electricity Generation and Useful Thermal Output, F. Wood / Wood Waste Biomass: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 1,287,114 10,659 139,532 1,196 1,135,727 2003 1,265,669 16,545 150,745 1,199 1,097,180 2004 1,360,258 19,973 145,216 1,661 1,193,408 2005 1,352,582 27,373 157,600 1,235 1,166,373 2006 1,399,235 27,455 154,360 1,314 1,216,106 2007 1,335,511 31,568 154,388 2,040 1,147,516 2008 1,262,675 29,150 148,198 1,410 1,083,917 2009 1,136,729 29,565 150,481 1,408 955,276 2010 1,225,571 40,167 155,429 1,338 1,028,637 2011 1,240,937 35,474 146,684 1,504 1,057,275

99

Session EP23A. Aeolian Processes and Desert Landscape Development Impact of surface roughness and soil texture on mineral dust emission fluxes modeling  

E-Print Network (OSTI)

) · Meteorology using WRF and use of a Weibull wind speed distribution · Transport using CHIMERE The main sources models. Modeling of the period of March to July of 2011 with WRF and CHIMERE : · Models : WRF as a function of its use in local to global meteorological and dust transport models Comparison

Menut, Laurent

100

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

1. Useful Thermal Output by Energy Source: Total Combined Heat and Power (All Sectors), 2002 - 2012 1. Useful Thermal Output by Energy Source: Total Combined Heat and Power (All Sectors), 2002 - 2012 (Billion Btus) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Renewable Sources Other Total Annual Totals 2002 336,848 61,313 11,513 708,738 117,513 571,509 48,263 1,855,697 2003 333,361 68,329 16,934 610,122 110,263 632,366 54,960 1,826,335 2004 351,871 80,824 16,659 654,242 126,157 667,341 45,456 1,942,550 2005 341,806 79,362 13,021 624,008 138,469 664,691 41,400 1,902,757 2006 332,548 54,224 24,009 603,288 126,049 689,549 49,308 1,878,973 2007 326,803 50,882 25,373 554,394 116,313 651,230 46,822 1,771,816 2008 315,244 29,554 18,263 509,330 110,680 610,131 23,729 1,616,931 2009 281,557 32,591 20,308 513,002 99,556 546,974 33,287 1,527,276

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

Evaluation of and Suggested Improvements to the WSM6 Microphysics in WRF-ARW Using Synthetic and Observed GOES-13 Imagery  

Science Journals Connector (OSTI)

Synthetic satellite imagery can be employed to evaluate simulated cloud fields. Past studies have revealed that the Weather Research and Forecasting (WRF) single-moment 6-class (WSM6) microphysics scheme in the Advanced Research WRF (WRF-ARW) ...

Lewis Grasso; Daniel T. Lindsey; Kyo-Sun Sunny Lim; Adam Clark; Dan Bikos; Scott R. Dembek

2014-10-01T23:59:59.000Z

102

Assessing certainty and uncertainty in riparian habitat suitability models by identifying parameters with extreme outputs  

Science Journals Connector (OSTI)

The aim of this paper is to introduce a computationally efficient uncertainty assessment approach using an index-based habitat suitability model. The approach focuses on uncertainty in ecological knowledge regarding parameters of index curves and weights. ... Keywords: Habitat model, Riparian vegetation, Suitability index, Uncertainty

Baihua Fu, Joseph H. A. Guillaume

2014-10-01T23:59:59.000Z

103

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

F. Biogenic Municipal Solid Waste: Consumption for Electricity Generation and F. Biogenic Municipal Solid Waste: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 161,803 5,766 132,065 21,953 2,020 2004 161,567 3,705 129,562 25,204 3,096 2005 164,635 4,724 131,080 24,914 3,918 2006 168,716 4,078 135,127 25,618 3,893 2007 162,482 4,557 133,509 21,393 3,022 2008 166,723 4,476 136,080 26,108 59 2009 165,755 3,989 132,877 27,868 1,021 2010 162,436 3,322 130,467 27,509 1,138 2011 152,007 3,433 121,648 25,664 1,262 2012 152,045 3,910 117,598 28,923 1,614 2010 January 13,015 244 10,405 2,260 107

104

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

1. Emissions from Energy Consumption at 1. Emissions from Energy Consumption at Conventional Power Plants and Combined-Heat-and-Power Plants 2002 through 2012 (Thousand Metric Tons) Year Carbon Dioxide (CO2) Sulfur Dioxide (SO2) Nitrogen Oxides (NOx) 2002 2,423,963 10,881 5,194 2003 2,445,094 10,646 4,532 2004 2,486,982 10,309 4,143 2005 2,543,838 10,340 3,961 2006 2,488,918 9,524 3,799 2007 2,547,032 9,042 3,650 2008 2,484,012 7,830 3,330 2009 2,269,508 5,970 2,395 2010 2,388,596 5,400 2,491 2011 2,287,071 4,845 2,406 2012 2,156,875 3,704 2,148 Notes: The emissions data presented include total emissions from both electricity generation and the production of useful thermal output. See Appendix A, Technical Notes, for a description of the sources and methodology used to develop the emissions estimates.

105

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

C. Biogenic Municipal Solid Waste: Consumption for Electricity Generation and C. Biogenic Municipal Solid Waste: Consumption for Electricity Generation and Useful Thermal Output, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 22,554 695 18,611 2,952 296 2004 22,330 444 17,959 3,439 488 2005 22,089 560 17,655 3,289 584 2006 22,469 500 18,068 3,356 545 2007 21,796 553 17,885 2,921 437 2008 22,134 509 18,294 3,323 8 2009 22,095 465 17,872 3,622 137 2010 21,725 402 17,621 3,549 152 2011 19,016 388 15,367 3,103 158 2012 18,954 418 14,757 3,577 203 2010 January 1,737 30 1,402 291 14 February 1,562 25 1,276 250 11 March 1,854 36 1,500 306 12

106

A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling  

Science Journals Connector (OSTI)

...on a desktop computer. This is compared...features of the system. The important...resistance. The analysis also identified...and uncertainty analysis: applications to large-scale systems, vol. 2. Boca...for sensitivity analysis of large models...European Symp. on Computer Aided Process...

2012-01-01T23:59:59.000Z

107

A framework for interpreting climate model outputs Nadja A. Leith and Richard E. Chandler  

E-Print Network (OSTI)

to illustrate the methodology. Some key words: Climate change; Climate model uncertainty; Contemporaneous ARMA acknowledged that human activities have caused changes in the Earth's climate (Solomon et al., 2007). Indeed #12;the hydrological cycle (Solomon et al., 2007). To accommodate this possibility therefore, planners

Guillas, Serge

108

USE OF GENERAL CIRCULATION MODEL OUTPUT IN THE CREATION OF CLIMATE CHANGE SCENARIOS  

E-Print Network (OSTI)

, Sub-Saharan Africa and Venezuela, for use in biological effects models. By combining the general of Energy (MacCracken and Luther, 1985a, b; NRC, 1985; Trabalka, 1985; Strain and Cure, 1985; White, 1985, and possible solar variations, and all agree that surface air temperatures will rise, pre- cipitation patterns

Robock, Alan

109

Model Validation and Spatial Interpolation by Combining Observations with Outputs from Numerical  

E-Print Network (OSTI)

""r,c,rn The authors are for hel]JfuI #12;Abstract Constructing maps of pollution levels is vital for air quality concentrations. Key tlJords: air pollution, Ba~yesian inference, change of support, likelihood approaches, Matern Resolutions 2.5 Modeling a Nonstationary Covariance . 3 Estimation 3.1 Algorithm 4 Application: Air Pollution

Washington at Seattle, University of

110

CONSTRUCTION OF WRF/CAM TWO-WAY COUPLING SYSTEM AND PRELIMINARY RESULTS  

E-Print Network (OSTI)

/Atmospheric Sciences Division Brookhaven National Laboratory U.S. Department of Energy Office of Science ABSTRACT A WRF is incorporated into CCSM as a regional atmosphere component and communicates with other CCSM components via cpl7 to improve the accuracy and conservation, and maintain the stability for long term integration. WRF

111

Ecological-economic assessment of farms using multi-input multi-output models: life cycle assessment with multiple paired comparisons  

Science Journals Connector (OSTI)

A multi-input multi-output model is developed by extending the life cycle assessment framework for analysing the relationship between agricultural production and environmental impacts. The inputs include farmland and materials such as fertilisers, pesticides and animals. The outputs are of two types: one is agro-economic production, such as crop yields, and the other is environmental impacts, including greenhouse gas emissions. Additive and ratio models are defined for analysing the relationship between management intensity, land productivity and environmental impacts based on the farm model. After the framework of multiple paired comparisons is illustrated, the multi-input multi-output model is applied to rice farming in Japan. The results indicate that the additive and ratio models can be used for detecting the directions of changes. These models can be extended for analysing the land-use competition between food and energy production.

Kiyotada Hayashi

2014-01-01T23:59:59.000Z

112

Weather Research and Forecasting prevision model as a tool to search for the best sites for astronomy: application to La Palma, Canary Islands  

Science Journals Connector (OSTI)

......the capability of WRF to predict the...Palma. Maps of the wind velocity, cloudiness...the use of the WRF model in an astronomical...launched on our local computer every...at 0600-ut (local time is equal to...C_N^2$ The WRF model gives vertical...temperature and the wind velocity forecast......

C. Giordano; J. Vernin; H. Trinquet; C. MuŮoz-TuŮůn

2014-01-01T23:59:59.000Z

113

ZHANG, XUEJIN. Adapting the Weather Research and Forecasting Model for the Simulation of Regional Climate in East Africa. (Under the direction of Dr. Lian Xie).  

E-Print Network (OSTI)

and society for regional climate information. The current Weather Research and Forecasting (WRF) RCM inherits several advantages of the original WRF model. For example, (1) it can be used for multiple scale infrastructure to distinguish the scientific problems from engineering problems. In order to adapt WRF for long

Liu, Paul

114

A Case Study of Radar Observations and WRF LES Simulations of the Impact of Ground-Based Glaciogenic Seeding on Orographic Clouds and Precipitation. Part I: Observations and Model Validations  

Science Journals Connector (OSTI)

Profiling airborne radar data and accompanying large-eddy-simulation (LES) modeling are used to examine the impact of ground-based glaciogenic seeding on cloud and precipitation in a shallow stratiform orographic winter storm. This storm occurred ...

Xia Chu; Lulin Xue; Bart Geerts; Roy Rasmussen; Daniel Breed

2014-10-01T23:59:59.000Z

115

Assessing regional scale predictions of aerosols, marine stratocumulus, and their interactions during VOCALS-REx using WRF-Chem  

SciTech Connect

In the recent chemistry version (v3.3) of the Weather Research and Forecasting (WRF-Chem) model, we have coupled the Morrison double-moment microphysics scheme with interactive aerosols so that full two-way aerosol-cloud interactions are included in simulations. We have used this new WRF-Chem functionality in a study focused on assessing predictions of aerosols, marine stratocumulus clouds, and their interactions over the Southeast Pacific using measurements from the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) and satellite retrievals. This study also serves as a detailed analysis of our WRF-Chem simulations contributed to the VOCALS model Assessment (VOCA) project. The WRF-Chem 31-day (October 15-November 16, 2008) simulation with aerosol-cloud interactions (AERO hereafter) is also compared to a simulation (MET hereafter) with fixed cloud droplet number concentrations assumed by the default in Morrison microphysics scheme with no interactive aerosols. The well-predicted aerosol properties such as number, mass composition, and optical depth lead to significant improvements in many features of the predicted stratocumulus clouds: cloud optical properties and microphysical properties such as cloud top effective radius, cloud water path, and cloud optical thickness, and cloud macrostructure such as cloud depth and cloud base height. These improvements in addition to the aerosol direct and semi-direct effects, in turn, feed back to the prediction of boundary-layer characteristics and energy budgets. Particularly, inclusion of interactive aerosols in AERO strengths temperature and humidity gradients within capping inversion layer and lowers the MBL depth by 150 m from that of the MET simulation. Mean top-of-the-atmosphere outgoing shortwave fluxes, surface latent heat, and surface downwelling longwave fluxes are in better agreement with observations in AERO, compared to the MET simulation. Nevertheless, biases in some of the simulated meteorological quantities (e.g., MBL temperature and humidity over the remote ocean) and aerosol quantities (e.g., overestimations of supermicron sea salt mass) might affect simulated stratocumulus and energy fluxes over the SEP, and require further investigations. Although not perfect, the overall performance of the regional model in simulating mesoscale aerosol-cloud interactions is encouraging and suggests that the inclusion of spatially varying aerosol characteristics is important when simulating marine stratocumulus over the southeastern Pacific.

Yang, Qing; Gustafson, William I.; Fast, Jerome D.; Wang, Hailong; Easter, Richard C.; Morrison, H.; Lee, Y.- N.; Chapman, Elaine G.; Spak, S. N.; Mena-Carrasco, M. A.

2011-12-02T23:59:59.000Z

116

WRF wind simulation and wind energy production estimates forced by different reanalyses: Comparison with observed data for Portugal  

Science Journals Connector (OSTI)

Abstract The performance of the WRF mesoscale model in the wind simulation and wind energy estimates was assessed and evaluated under different initial and boundary forcing conditions. Due to the continuous evolution and progress in the development of reanalyses datasets, this work aims to compare an older, yet widely used, reanalysis (the NCEP-R2) with three recently released reanalyses datasets that represent the new generation of this type of data (ERA-Interim, NASA-MERRA and NCEP-CFSR). Due to its intensive use in wind energy assessment studies, the NCEP-GFS and NCEP-FNL analysis were also used to drive WRF and its results compared to those of the simulations driven by reanalyses. Six different WRF simulations were conducted and their results compared to measured wind data collected at thirteen wind measuring stations located in Portugal in areas of high wind energy potential. Based on the analysis and results presented in this work, it can be concluded that the new generation reanalyses are able to provide a considerable improvement in wind simulation when compared to the older reanalyses. Among all the initial and boundary conditions datasets tested here, ERA-Interim reanalysis is the one that likely provides the most realistic initial and boundary data, providing the best estimates of the local wind regimes and potential wind energy production. The NCEP-GFS and NCEP-FNL analyses seem to be the best alternatives to ERA-Interim, showing better results than all the other reanalyses datasets here tested, and can therefore be considered as valid alternatives to ERA-Interim, in particular for cases where reliable forcing data is needed for real-time applications due to its fast availability.

D. Carvalho; A. Rocha; M. Gůmez-Gesteira; C. Silva Santos

2014-01-01T23:59:59.000Z

117

P2.30 GRAVITY WAVE PHASE DISCREPANCIES IN WRF Stephen D. Jascourt  

E-Print Network (OSTI)

P2.30 GRAVITY WAVE PHASE DISCREPANCIES IN WRF Stephen D. Jascourt 1 UCAR/COMET Silver Spring, MD 1 initial and boundary conditions interpolated from the operational NAM. However, the land surface

118

Object Oriented Modeling of a Multiple-Input Multiple-Output Flyback Converter in Nicholas D. Benavides and Patrick L.Chapman  

E-Print Network (OSTI)

Object Oriented Modeling of a Multiple-Input Multiple-Output Flyback Converter in Dymola Nicholas D not lend itself to many traditional circuit simulators such as SPICE. The state equations of a converter dependent on the states, and cannot be determined prior to simulation, requiring the use of an iterative

Chapman, Patrick

119

A Comparison of Simulated Cloud Radar Output from the Multiscale Modeling Framework Global Climate Model with CloudSat Cloud Radar Observations  

SciTech Connect

Over the last few years a new type of global climate model (GCM) has emerged in which a cloud-resolving model is embedded into each grid cell of a GCM. This new approach is frequently called a multiscale modeling framework (MMF) or superparameterization. In this article we present a comparison of MMF output with radar observations from the NASA CloudSat mission, which uses a near-nadir-pointing millimeter-wavelength radar to probe the vertical structure of clouds and precipitation. We account for radar detection limits by simulating the 94 GHz radar reflectivity that CloudSat would observe from the high-resolution cloud-resolving model output produced by the MMF. Overall, the MMF does a good job of reproducing the broad pattern of tropical convergence zones, subtropical belts, and midlatitude storm tracks, as well as their changes in position with the annual solar cycle. Nonetheless, the comparison also reveals a number of model shortfalls including (1) excessive hydrometeor coverage at all altitudes over many convectively active regions, (2) a lack of low-level hydrometeors over all subtropical oceanic basins, (3) excessive low-level hydrometeor coverage (principally precipitating hydrometeors) in the midlatitude storm tracks of both hemispheres during the summer season (in each hemisphere), and (4) a thin band of low-level hydrometeors in the Southern Hemisphere of the central (and at times eastern and western) Pacific in the MMF, which is not observed by CloudSat. This band resembles a second much weaker ITCZ but is restricted to low levels.

Marchand, Roger T.; Haynes, J. M.; Mace, Gerald G.; Ackerman, Thomas P.; Stephens, Graeme L.

2009-01-13T23:59:59.000Z

120

Study of Multi-Scale Cloud Processes Over the Tropical Western Pacific Using Cloud-Resolving Models Constrained by Satellite Data  

SciTech Connect

Clouds in the tropical western Pacific are an integral part of the large scale environment. An improved understanding of the multi-scale structure of clouds and their interactions with the environment is critical to the ARM (Atmospheric Radiation Measurement) program for developing and evaluating cloud parameterizations, understanding the consequences of model biases, and providing a context for interpreting the observational data collected over the ARM Tropical Western Pacific (TWP) sites. Three-dimensional cloud resolving models (CRMs) are powerful tools for developing and evaluating cloud parameterizations. However, a significant challenge in using CRMs in the TWP is that the region lacks conventional data, so large uncertainty exists in defining the large-scale environment for clouds. This project links several aspects of the ARM program, from measurements to providing improved analyses, and from cloud-resolving modeling to climate-scale modeling and parameterization development, with the overall objective to improve the representations of clouds in climate models and to simulate and quantify resolved cloud effects on the large-scale environment. Our objectives will be achieved through a series of tasks focusing on the use of the Weather Research and Forecasting (WRF) model and ARM data. Our approach includes: -- Perform assimilation of COSMIC GPS radio occultation and other satellites products using the WRF Ensemble Kalman Filter assimilation system to represent the tropical large-scale environment at 36 km grid resolution. This high-resolution analysis can be used by the community to derive forcing products for single-column models or cloud-resolving models. -- Perform cloud-resolving simulations using WRF and its nesting capabilities, driven by the improved regional analysis and evaluate the simulations against ARM datasets such as from TWP-ICE to optimize the microphysics parameters for this region. A cirrus study (Mace and co-authors) already exists for TWP-ICE using satellite and ground-based observations. -- Perform numerical experiments using WRF to investigate how convection over tropical islands in the Maritime Continent interacts with large-scale circulation and affects convection in nearby regions. -- Evaluate and apply WRF as a testbed for GCM cloud parameterizations, utilizing the ability of WRF to run on multiple scales (from cloud resolving to global) to isolate resolution and physics issues from dynamical and model framework issues. Key products will be disseminated to the ARM and larger community through distribution of data archives, including model outputs from the data assimilation products and cloud resolving simulations, and publications.

Dudhia, Jimy

2013-03-12T23:59:59.000Z

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121

The feasibility of co-existence between conventional and genetically modified crops: Using machine learning to analyse the output of simulation models  

Science Journals Connector (OSTI)

Simulation models are a commonly used tool for the study of the co-existence of conventional and genetically modified (GM) crops. Among other things, they allow us to investigate the effects of using different crop varieties, cropping systems and farming practices on the levels of adventitious presence of GM material in conventional crops. We propose to use machine learning methods to analyse the output of simulation models to learn co-existence rules that directly link the above mentioned causes and effects. The outputs of the GENESYS model, designed to study the co-existence of conventional and GM oilseed rape crops, were analysed by using the machine learning methods of regression tree induction and relational decision tree induction. Co-existence and adventitious presence of GM material were studied in several contexts, including gene flow between pairs of fields, the interactions of this process with farming practices (cropping systems), and gene flow in the context of an entire field plan. Accurate models were learned, which also make use of the relational aspects of a field plan, using information on the neighboring fields of a field, and the farming practices applied in it. The use of relational decision tree induction to analyse the results of simulation models is a novel approach and holds the promise of learning more general co-existence rules by allowing us to vary the target field within a chosen field plan, as well as to consider completely different field plans at the same time.

Aneta Ivanovska; Celine Vens; Nathalie Colbach; Marko Debeljak; Saöo Děeroski

2008-01-01T23:59:59.000Z

122

Computational modelling of T-cell formation kinetics: output regulated by initial proliferation-linked deferral of developmental competence  

Science Journals Connector (OSTI)

...marrow-derived progenitors enter the thymus of an adult...our models validate the search for its molecular basis...At time zero, n cells enter the DN1pre compartment...11) best models in terms of G, the number of generations...11) best models in terms of G, the number of generations...

2013-01-01T23:59:59.000Z

123

Data Assimilation of Lightning in WRF 3/4-D VAR Using Observation Operators  

E-Print Network (OSTI)

@fsu.edu Abstract Compared to other types of satellite-derived data, assimilating lightning data into operationalData Assimilation of Lightning in WRF 3/4-D VAR Using Observation Operators Razvan S¬łtefanescu1. The early stages of our research will utilize existing ground-based lightning data that can be assimilated

Navon, Michael

124

The Impact of a Wildland Fire on Air Pollution Concentrations Using WRF/Chem/Fire: An Application over Murcia (Spain)  

Science Journals Connector (OSTI)

In this contribution we will show the impact on air pollution concentration of a Fire developed in the ... of Murcia (Spain). The impact on air pollution concentrations has been done using the WRF/ ... modifying ...

Roberto San Josť; Juan Luis PťrezÖ

2014-01-01T23:59:59.000Z

125

Assessing regional scale predictions of aerosols, marine stratocumulus, and their interactions during VOCALS-REx using WRF-Chem  

SciTech Connect

This study assesses the ability of the recent chemistry version (v3.3) of the Weather Research and Forecasting (WRF-Chem) model to simulate boundary layer structure, aerosols, stratocumulus clouds, and energy fluxes over the Southeast Pacific Ocean. Measurements from the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) and satellite retrievals (i.e., products from the MODerate resolution Imaging Spectroradiometer (MODIS), Clouds and Earth's Radiant Energy System (CERES), and GOES-10) are used for this assessment. The Morrison double-moment microphysics scheme is newly coupled with interactive aerosols in the model. The 31-day (15 October-16 November 2008) WRF-Chem simulation with aerosol-cloud interactions (AERO hereafter) is also compared to a simulation (MET hereafter) with fixed cloud droplet number concentrations in the microphysics scheme and simplified cloud and aerosol treatments in the radiation scheme. The well-simulated aerosol quantities (aerosol number, mass composition and optical properties), and the inclusion of full aerosol-cloud couplings lead to significant improvements in many features of the simulated stratocumulus clouds: cloud optical properties and microphysical properties such as cloud top effective radius, cloud water path, and cloud optical thickness. In addition to accounting for the aerosol direct and semi-direct effects, these improvements feed back to the simulation of boundary-layer characteristics and energy budgets. Particularly, inclusion of interactive aerosols in AERO strengthens the temperature and humidity gradients within the capping inversion layer and lowers the marine boundary layer (MBL) depth by 130 m from that of the MET simulation. These differences are associated with weaker entrainment and stronger mean subsidence at the top of the MBL in AERO. Mean top-of-atmosphere outgoing shortwave fluxes, surface latent heat, and surface downwelling longwave fluxes are in better agreement with observations in AERO, compared to the MET simulation. Nevertheless, biases in some of the simulated meteorological quantities (e.g., MBL temperature and humidity) and aerosol quantities (e.g., underestimations of accumulation mode aerosol number) might affect simulated stratocumulus and energy fluxes over the Southeastern Pacific, and require further investigation. The well-simulated timing and outflow patterns of polluted and clean episodes demonstrate the model's ability to capture daily/synoptic scale variations of aerosol and cloud properties, and suggest that the model is suitable for studying atmospheric processes associated with pollution outflow over the ocean. The overall performance of the regional model in simulating mesoscale clouds and boundary layer properties is encouraging and suggests that reproducing gradients of aerosol and cloud droplet concentrations and coupling cloud-aerosol-radiation processes are important when simulating marine stratocumulus over the Southeast Pacific.

Yang Q.; Lee Y.; Gustafson†Jr., W. I.; Fast, J. D.; Wang, H.; Easter, R. C.; Morrison, H.; Chapman, E. G.; Spak, S. N.; Mena-Carrasco, M. A.

2011-12-02T23:59:59.000Z

126

Cloud system resolving model simulations of tropical cloud systems observed during the Tropical  

E-Print Network (OSTI)

the Weather Research and Forecasting (WRF) model. The WRF model is configured with a highest-resolving domain convection. The second regime is a monsoon break, which contains intense localized systems that are rep-based observational systems including a polarimetric weather radar, cloud radar, wind profilers, radi- ation

Jakob, Christian

127

Evaluation of WRF predicted near hub-height winds and ramp events over a Pacific Northwest site with complex terrain  

SciTech Connect

The WRF model version 3.3 is used to simulate near hub-height winds and power ramps utilizing three commonly used planetary boundary-layer (PBL) schemes: Mellor-Yamada-Janji? (MYJ), University of Washington (UW), and Yonsei University (YSU). The predicted winds have small mean biases compared with observations. Power ramps and step changes (changes within an hour) consistently show that the UW scheme performed better in predicting up ramps under stable conditions with higher prediction accuracy and capture rates. Both YSU and UW scheme show good performance predicting up- and down- ramps under unstable conditions with YSU being slightly better for ramp durations longer than an hour. MYJ is the most successful simulating down-ramps under stable conditions. The high wind speed and large shear associated with low-level jets are frequently associated with power ramps, and the biases in predicted low-level jet explain some of the shown differences in ramp predictions among different PBL schemes. Low-level jets were observed as low as ~200 m in altitude over the Columbia Basin Wind Energy Study (CBWES) site, located in an area of complex terrain. The shear, low-level peak wind speeds, as well as the height of maximum wind speed are not well predicted. Model simulations with 3 PBL schemes show the largest variability among them under stable conditions.

Yang, Qing; Berg, Larry K.; Pekour, Mikhail S.; Fast, Jerome D.; Newsom, Rob K.; Stoelinga, Mark; Finley, Cathy

2013-08-16T23:59:59.000Z

128

Intercomparison of Bulk Microphysics Schemes in Model Simulations of Polar Lows  

Science Journals Connector (OSTI)

Four spiraliform polar lows, two over the Sea of Japan and two over the Nordic Seas, were simulated with the Weather Research and Forecasting (WRF) model. Five mixed-phase bulk microphysics schemes (BMS) provided with WRF were run respectively in ...

Longtao Wu; Grant W. Petty

2010-06-01T23:59:59.000Z

129

Block-structured adaptive meshes and reduced grids for atmospheric general circulation models  

Science Journals Connector (OSTI)

...grids are widely used for local weather predictions and...Research Forecasting Model WRF (Skamarock et al...small time steps if high wind speeds are present in...m and (c) meridional wind v (m1) at day 10 (McDonald...the advanced research WRF Version 2National Center...

2009-01-01T23:59:59.000Z

130

Comparing urban solid waste recycling from the viewpoint of urban metabolism based on physical input-output model: A case of Suzhou in China  

SciTech Connect

Highlights: Black-Right-Pointing-Pointer Impacts of solid waste recycling on Suzhou's urban metabolism in 2015 are analyzed. Black-Right-Pointing-Pointer Sludge recycling for biogas is regarded as an accepted method. Black-Right-Pointing-Pointer Technical levels of reusing scrap tires and food wastes should be improved. Black-Right-Pointing-Pointer Other fly ash utilization methods should be exploited. Black-Right-Pointing-Pointer Secondary wastes from reusing food wastes and sludge should be concerned. - Abstract: Investigating impacts of urban solid waste recycling on urban metabolism contributes to sustainable urban solid waste management and urban sustainability. Using a physical input-output model and scenario analysis, urban metabolism of Suzhou in 2015 is predicted and impacts of four categories of solid waste recycling on urban metabolism are illustrated: scrap tire recycling, food waste recycling, fly ash recycling and sludge recycling. Sludge recycling has positive effects on reducing all material flows. Thus, sludge recycling for biogas is regarded as an accepted method. Moreover, technical levels of scrap tire recycling and food waste recycling should be improved to produce positive effects on reducing more material flows. Fly ash recycling for cement production has negative effects on reducing all material flows except solid wastes. Thus, other fly ash utilization methods should be exploited. In addition, the utilization and treatment of secondary wastes from food waste recycling and sludge recycling should be concerned.

Liang Sai, E-mail: liangsai09@gmail.com [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China); Zhang Tianzhu, E-mail: zhangtz@mail.tsinghua.edu.cn [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China)

2012-01-15T23:59:59.000Z

131

Improving WRF-ARW Wind Speed Predictions using Genetic Programming  

Science Journals Connector (OSTI)

Numerical weather prediction models can produce wind speed forecasts at a very high space resolution. ... that GP is able to successfully downscale the wind speed predictions, reducing significantly the inherent ...

Giovanna Martinez-Arellano; Lars NolleÖ

2012-01-01T23:59:59.000Z

132

Evaluation of and Suggested Improvements to the WSM6 Microphysics in WRF- ARW Using Synthetic and Observed GOES-13 Imagery  

SciTech Connect

Synthetic satellite imagery can be employed to evaluate simulated cloud fields. Past studies have revealed that the Weather Research and Forecasting (WRF) WRF Single-Moment 6-class (WSM6) microphysics in WRF-ARW produces less upper level ice clouds within synthetic images compared to observations. Synthetic Geostationary Operational Environmental Satellite (GOES)-13 imagery at 10.7 ?m of simulated cloud fields from the 4 km National Severe Storms Laboratory (NSSL) WRF-ARW is compared to observed GOES-13 imagery. Histograms suggest that too few points contain upper level simulated ice clouds. In particular, side-by-side examples are shown of synthetic and observed convective anvils. Such images illustrate the lack of anvil cloud associated with convection produced by the NSSL WRF-ARW. A vertical profile of simulated hydrometeors suggests that too much cloud water mass may be converted into graupel mass, effectively reducing the main source of ice mass in a simulated anvil. Further, excessive accretion of ice by snow removes ice from an anvil by precipitation settling. Idealized sensitivity tests reveal that a 50% reduction of the conversion of cloud water mass to graupel and a 50% reduction of the accretion rate of ice by snow results in a significant increase in anvil ice of a simulated storm. Such results provide guidance as to which conversions could be reformulated, in a more physical manner, to increase simulated ice mass in the upper troposphere.

Grasso, Lewis; Lindsey, Daniel T.; Lim, Kyo-Sun; Clark, Adam; Bikos, Dan; Dembek, Scott R.

2014-10-01T23:59:59.000Z

133

Title Slide "The broadband acoustic output of  

E-Print Network (OSTI)

Title Slide "The broadband acoustic output of marine seismic airgun sources" Les Hatton CISM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . #12;Seismic sources ­ marine airguns Introduction Modelling Marine Life Impact Where next Overview #12 Normal speed surface movie of airgun firing Courtesy IO limited #12;Seismic sources ­ marine airguns

Hatton, Les

134

Effect of Terrestrial and Marine Organic Aerosol on Regional and Global Climate: Model Development, Application, and Verification with Satellite Data  

SciTech Connect

In this DOE project the improvements to parameterization of marine primary organic matter (POM) emissions, hygroscopic properties of marine POM, marine isoprene derived secondary organic aerosol (SOA) emissions, surfactant effects, new cloud droplet activation parameterization have been implemented into Community Atmosphere Model (CAM 5.0), with a seven mode aerosol module from the Pacific Northwest National Laboratory (PNNL)√?¬?√?¬Ę√?¬?√?¬?√?¬?√?¬?s Modal Aerosol Model (MAM7). The effects of marine aerosols derived from sea spray and ocean emitted biogenic volatile organic compounds (BVOCs) on microphysical properties of clouds were explored by conducting 10 year CAM5.0-MAM7 model simulations at a grid resolution 1.9√?¬?√?¬?√?¬?√?¬į√?¬?√?¬?√?¬?√?¬?2.5√?¬?√?¬?√?¬?√?¬į with 30 vertical layers. Model-predicted relationship between ocean physical and biological systems and the abundance of CCN in remote marine atmosphere was compared to data from the A-Train satellites (MODIS, CALIPSO, AMSR-E). Model simulations show that on average, primary and secondary organic aerosol emissions from the ocean can yield up to 20% increase in Cloud Condensation Nuclei (CCN) at 0.2% Supersaturation, and up to 5% increases in droplet number concentration of global maritime shallow clouds. Marine organics were treated as internally or externally mixed with sea salt. Changes associated with cloud properties reduced (absolute value) the model-predicted short wave cloud forcing from -1.35 Wm-2 to -0.25 Wm-2. By using different emission scenarios, and droplet activation parameterizations, this study suggests that addition of marine primary aerosols and biologically generated reactive gases makes an important difference in radiative forcing assessments. All baseline and sensitivity simulations for 2001 and 2050 using global-through-urban WRF/Chem (GU-WRF) were completed. The main objective of these simulations was to evaluate the capability of GU-WRF for an accurate representation of the global atmosphere by exploring the most accurate configuration of physics options in GWRF for global scale modeling in 2001 at a horizontal grid resolution of 1√?¬?√?¬?√?¬?√?¬į x 1√?¬?√?¬?√?¬?√?¬į. GU-WRF model output was evaluated using observational datasets from a variety of sources including surface based observations (NCDC and BSRN), model reanalysis (NCEP/ NCAR Reanalysis and CMAP), and remotely-sensed data (TRMM) to evaluate the ability of GU-WRF to simulate atmospheric variables at the surface as well as aloft. Explicit treatment of nanoparticles produced from new particle formation in GU-WRF/Chem-MADRID was achieved by expanding particle size sections from 8 to 12 to cover particles with the size range of 1.16 nm to 11.6 √?¬?√?¬?√?¬?√?¬Ķm. Simulations with two different nucleation parameterizations were conducted for August 2002 over a global domain at a 4√?¬?√?¬?√?¬?√?¬ļ by 5√?¬?√?¬?√?¬?√?¬ļ horizontal resolution. The results are evaluated against field measurement data from the 2002 Aerosol Nucleation and Real Time Characterization Experiment (ANARChE) in Atlanta, Georgia, as well as satellite and reanalysis data. We have also explored the relationship between √?¬?√?¬Ę√?¬?√?¬?√?¬?√?¬?clean marine√?¬?√?¬Ę√?¬?√?¬?√?¬?√?¬Ě aerosol optical properties and ocean surface wind speed using remotely sensed data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on board the CALIPSO satellite and the Advanced Microwave Scanning Radiometer (AMSR-E) on board the AQUA satellite. Detailed data analyses

Meskhidze, Nicholas; Zhang, Yang; Kamykowski, Daniel

2012-03-28T23:59:59.000Z

135

Multi-scale modeling and evaluation of urban surface energy balance in the Phoenix metropolitan area  

Science Journals Connector (OSTI)

Physical mechanisms of incongruency between observations and Weather Research and Forecasting (WRF) model predictions are examined. Limitations of evaluation are constrained by: i) parameterizations of model physics, ii) parameterizations of input ...

S.R. Shaffer; W.T.L. Chow; M. Georgescu; P. Hyde; G.D. Jenerette; A. Mahalov; M. Moustaoui; B.L. Ruddell

136

Enhanced performance CCD output amplifier  

DOE Patents (OSTI)

A low-noise FET amplifier is connected to amplify output charge from a che coupled device (CCD). The FET has its gate connected to the CCD in common source configuration for receiving the output charge signal from the CCD and output an intermediate signal at a drain of the FET. An intermediate amplifier is connected to the drain of the FET for receiving the intermediate signal and outputting a low-noise signal functionally related to the output charge signal from the CCD. The amplifier is preferably connected as a virtual ground to the FET drain. The inherent shunt capacitance of the FET is selected to be at least equal to the sum of the remaining capacitances.

Dunham, Mark E. (Los Alamos, NM); Morley, David W. (Santa Fe, NM)

1996-01-01T23:59:59.000Z

137

Caribbean Precipitation in Observations and IPCC AR4 Models  

E-Print Network (OSTI)

are observa- tions/reanalysis, blue dashed are CMIP, blue dotted are AMIP and red are WRF-ROMS ensemble members. In the precipita- tion plots, the solid green shows cumulus rain (from convective parameterization) and dashed-dotted green shows grid scale... pre- cipitation (from microphysics parameterization). . . . . . . . . . . . . . . . . . . . . 142 44 Monthly mean quantities for May and September from one en- semble of WRF-ROMS coupled regional model. Rainfall from contours are 2,4,6,8 mm...

Martin, Elinor Ruth

2012-10-19T23:59:59.000Z

138

The Landfall and Inland Penetration of a Flood-Producing Atmospheric River in Arizona. Part II: Sensitivity of Modeled Precipitation to Terrain Height and Atmospheric River Orientation  

Science Journals Connector (OSTI)

This manuscript documents numerical modeling experiments based on a January 2010 atmospheric river (AR) event that caused extreme precipitation in Arizona. The control experiment (CNTL), using the Weather Research and Forecasting (WRF) Model with ...

Mimi Hughes; Kelly M. Mahoney; Paul J. Neiman; Benjamin J. Moore; Michael Alexander; F. Martin Ralph

2014-10-01T23:59:59.000Z

139

Modeling the Atmospheric Boundary Layer Wind Response to Mesoscale Sea Surface Temperature Perturbations  

Science Journals Connector (OSTI)

The wind speed response to mesoscale SST variability is investigated over the Agulhas Return Current region of the Southern Ocean using the Weather Research and Forecasting (WRF) Model and the U.S. Navy Coupled OceanĖAtmosphere Mesoscale ...

Natalie Perlin; Simon P. de Szoeke; Dudley B. Chelton; Roger M. Samelson; Eric D. Skyllingstad; Larry W. OíNeill

2014-11-01T23:59:59.000Z

140

Resolved Turbulence Characteristics in Large-Eddy Simulations Nested within Mesoscale Simulations Using the Weather Research and Forecasting Model  

Science Journals Connector (OSTI)

One-way concurrent nesting within the Weather Research and Forecasting Model (WRF) is examined for conducting large-eddy simulations (LES) nested within mesoscale simulations. Wind speed, spectra, and resolved turbulent stresses and turbulence ...

Jeff Mirocha; Branko Kosovi?; Gokhan Kirkil

2014-02-01T23:59:59.000Z

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Sparse Convolved Gaussian Processes for Multi-output Regression  

E-Print Network (OSTI)

the concentration of different heavy metal pollutants [5]. Modelling multiple output variables is a challenge as we methodology for synthetic data and real world applications on pollution prediction and a sensor network. 1

Rattray, Magnus

142

Inflation uncertainty, growth uncertainty, oil prices, and output growth in the UK  

Science Journals Connector (OSTI)

This study examines the transmission and response of inflation uncertainty and output uncertainty on inflation and output growth in the UK using a bi-variate EGARCH model. Results suggest that inflation uncertain...

Ramprasad Bhar; Girijasankar Mallik

2013-12-01T23:59:59.000Z

143

Evaluation of Three Planetary Boundary Layer Schemes in the WRF Model XIAO-MING HU  

E-Print Network (OSTI)

. Introduction Southeast Texas, especially the Houston­Galveston area, frequently exceeds the National Ambient of Atmospheric Sciences, Texas A&M University, College Station, Texas, and Department of Meteorology Sciences, Texas A&M University, College Station, Texas FUQING ZHANG Department of Meteorology

144

Evaluated Crop Evapotranspiration over a Region of Irrigated Orchards with the Improved ACASAĖWRF Model  

E-Print Network (OSTI)

Among the uncertain consequences of climate change on agriculture are changes in timing and quantity of precipitation together with predicted higher temperatures and changes in length of growing season. The understanding ...

Falk, Matthias

145

Prediction of In-Cloud Icing Conditions at Ground Level Using the WRF Model  

Science Journals Connector (OSTI)

In-cloud icing on aircraft and ground structures can be observed every winter in many countries. In extreme cases ice can cause accidents and damage to infrastructure such as power transmission lines, telecommunication towers, wind turbines, ski ...

BjÝrn Egil Kringlebotn Nygaard; Jůn Egill KristjŠnsson; Lasse Makkonen

2011-12-01T23:59:59.000Z

146

A Framework to Determine the Probability Density Function for the Output Power of Wind Farms  

E-Print Network (OSTI)

A Framework to Determine the Probability Density Function for the Output Power of Wind Farms Sairaj to the power output of a wind farm while factoring in the availability of the wind turbines in the farm availability model for the wind turbines, we propose a method to determine the wind-farm power output pdf

Liberzon, Daniel

147

Assessing the Impacts of Different WRF Precipitation Physics in Hurricane Simulations  

E-Print Network (OSTI)

ABSTRACT Numerical weather prediction models play a majorthat numerical weather prediction models are particularlymodel with numerical weather prediction models (Olson et al.

Nasrollahi, Nasrin; AghaKouchak, Amir; Li, Jialun; Gao, Xiaogang; Hsu, Kuolin; Sorooshian, Soroosh

2012-01-01T23:59:59.000Z

148

Energy Input Output Calculator | Open Energy Information  

Open Energy Info (EERE)

Input Output Calculator Input Output Calculator Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Energy Input-Output Calculator Agency/Company /Organization: Department of Energy Sector: Energy Focus Area: Energy Efficiency Resource Type: Online calculator User Interface: Website Website: www2.eere.energy.gov/analysis/iocalc/Default.aspx Web Application Link: www2.eere.energy.gov/analysis/iocalc/Default.aspx OpenEI Keyword(s): Energy Efficiency and Renewable Energy (EERE) Tools Language: English References: EERE Energy Input-Output Calculator[1] The Energy Input-Output Calculator (IO Calculator) allows users to estimate the economic development impacts from investments in alternate electricity generating technologies. About the Calculator The Energy Input-Output Calculator (IO Calculator) allows users to estimate

149

Transforming the sensing and numerical prediction of high-impact local weather through dynamic adaptation  

Science Journals Connector (OSTI)

...interfaces and local and remote computing...output stored on local and remote servers...particularly the WRF model system now...of temperature, wind and humidity in...maximum sustained wind speeds for selected...their own daily WRF forecasts from...benefits wrought by local models applied...

2009-01-01T23:59:59.000Z

150

SciTech Connect: Two-Way Integration of WRF and CCSM for Regional...  

Office of Scientific and Technical Information (OSTI)

the Community Climate System Model (CCSM) and the ensuing new generation Community Earth System Model (CESM). The integrated WRFCESM system is intended as one method of...

151

Toward self-describing and workflow integrated Earth system models: A coupled atmosphere-ocean modeling system application  

Science Journals Connector (OSTI)

The complexity of Earth system models and their applications is increasing as a consequence of scientific advances, user demand, and the ongoing development of computing platforms, storage systems and distributed high-resolution observation networks. ... Keywords: Coupled Earth system models, Provenance information, ROMS, Scientific workflow, Self-describing models, WRF

Ufuk Utku Turuncoglu; Nuzhet Dalfes; Sylvia Murphy; Cecelia Deluca

2013-01-01T23:59:59.000Z

152

ASSIMILATION OF DOPPLER RADAR DATA INTO NUMERICAL WEATHER MODELS  

SciTech Connect

During the year 2008, the United States National Weather Service (NWS) completed an eight fold increase in sampling capability for weather radars to 250 m resolution. This increase is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current NWS operational model domains utilize grid spacing an order of magnitude larger than the radar data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of radar reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution was investigated under a Laboratory Directed Research and Development (LDRD) 'quick hit' grant to determine the impact of improved data resolution on model predictions with specific initial proof of concept application to daily Savannah River Site operations and emergency response. Development of software to process NWS radar reflectivity and radial velocity data was undertaken for assimilation of observations into numerical models. Data values within the radar data volume undergo automated quality control (QC) analysis routines developed in support of this project to eliminate empty/missing data points, decrease anomalous propagation values, and determine error thresholds by utilizing the calculated variances among data values. The Weather Research and Forecasting model (WRF) three dimensional variational data assimilation package (WRF-3DVAR) was used to incorporate the QC'ed radar data into input and boundary conditions. The lack of observational data in the vicinity of SRS available to NWS operational models signifies an important data void where radar observations can provide significant input. These observations greatly enhance the knowledge of storm structures and the environmental conditions which influence their development. As the increase in computational power and availability has made higher resolution real-time model simulations possible, the need to obtain observations to both initialize numerical models and verify their output has become increasingly important. The assimilation of high resolution radar observations therefore provides a vital component in the development and utility of numerical model forecasts for both weather forecasting and contaminant transport, including future opportunities to improve wet deposition computations explicitly.

Chiswell, S.; Buckley, R.

2009-01-15T23:59:59.000Z

153

Design of a next-generation regional weather research and forecast model.  

SciTech Connect

The Weather Research and Forecast (WRF) model is a new model development effort undertaken jointly by the National Center for Atmospheric Research (NCAR), the National Oceanic and Atmospheric Administration (NOAA), and a number of collaborating institutions and university scientists. The model is intended for use by operational NWP and university research communities, providing a common framework for idealized dynamical studies, fill physics numerical weather prediction, air-quality simulation, and regional climate. It will eventually supersede large, well-established but aging regional models now maintained by the participating institutions. The WRF effort includes re-engineering the underlying software architecture to produce a modular, flexible code designed from the outset to provide portable performance across diverse computing architectures. This paper outlines key elements of the WRF software design.

Michalakes, J.

1999-01-13T23:59:59.000Z

154

Evaluation of a Forward Operator to Assimilate Cloud Water Path into WRF-DART  

Science Journals Connector (OSTI)

Assimilating satellite-retrieved cloud properties into storm-scale models has received limited attention despite its potential to provide a wide array of information to a model analysis. Available retrievals include cloud water path (CWP), which ...

Thomas A. Jones; David J. Stensrud; Patrick Minnis; Rabindra Palikonda

2013-07-01T23:59:59.000Z

155

Analysis of Precipitation Using Satellite Observations and Comparisons with Global Climate Models  

E-Print Network (OSTI)

is investigated by comparisons with satellite observa- iv tions. Speci cally, six-year long (2000-2005) simulations are performed using a high- resolution (36-km) Weather Research Forecast (WRF) model and the Community Atmosphere Model (CAM) at T85 spatial... . . . . . . . . . . . . . . . . 31 B. Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 1. Satellite data . . . . . . . . . . . . . . . . . . . . . . . 33 2. Weather research and forecast model simulations . . . 34 3. Community atmosphere model simulations...

Murthi, Aditya

2011-08-08T23:59:59.000Z

156

Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs  

E-Print Network (OSTI)

Anisotropic gridĖadaptive strategies are presented for viscous flow simulations in which the accurate prediction of multiple aerodynamic outputs (such as the lift, drag, and moment coefficients) is required from a single ...

Venditti, David A.

157

Optimization on Solar Panels: Finding the Optimal Output Brian Y. Lu  

E-Print Network (OSTI)

Optimization on Solar Panels: Finding the Optimal Output Brian Y. Lu January 1, 2013 1 Introduction of solar panel: Routing the configuration between solar cells with a switch matrix. However, their result models and control policies for the optimal output of solar panels. The smallest unit on a solar panel

Lavaei, Javad

158

NAO Climatology: ROMS output is saved once every 3 days and written to an output file  

E-Print Network (OSTI)

NAO Climatology: ROMS output is saved once every 3 days and written to an output file every 6 days Output after 30 days in 6th file. The Starting Month = July Example: roms_low_his_levts0570dg.0120.nc.gz : July 3 roms_low_his_levts0570dg.0122.nc.gz : July 6 and July 9 roms_low_his_levts0570dg.0124.nc

Gangopadhyay, Avijit

159

Boosting America's Hydropower Output | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Boosting America's Hydropower Output Boosting America's Hydropower Output Boosting America's Hydropower Output October 9, 2012 - 2:10pm Addthis The Boulder Canyon Hydroelectric Facility's new, highly-efficient turbine. | Photo courtesy of the city of Boulder, Colorado. The Boulder Canyon Hydroelectric Facility's new, highly-efficient turbine. | Photo courtesy of the city of Boulder, Colorado. City of Boulder employees celebrate the completion of the Boulder Canyon Hydroelectric Modernization project. | Photo courtesy of the city of Boulder, Colorado. City of Boulder employees celebrate the completion of the Boulder Canyon Hydroelectric Modernization project. | Photo courtesy of the city of Boulder, Colorado. The Boulder Canyon Hydroelectric Facility's new, highly-efficient turbine. | Photo courtesy of the city of Boulder, Colorado.

160

PV output smoothing with energy storage.  

SciTech Connect

This report describes an algorithm, implemented in Matlab/Simulink, designed to reduce the variability of photovoltaic (PV) power output by using a battery. The purpose of the battery is to add power to the PV output (or subtract) to smooth out the high frequency components of the PV power that that occur during periods with transient cloud shadows on the PV array. The control system is challenged with the task of reducing short-term PV output variability while avoiding overworking the battery both in terms of capacity and ramp capability. The algorithm proposed by Sandia is purposely very simple to facilitate implementation in a real-time controller. The control structure has two additional inputs to which the battery can respond. For example, the battery could respond to PV variability, load variability or area control error (ACE) or a combination of the three.

Ellis, Abraham; Schoenwald, David Alan

2012-03-01T23:59:59.000Z

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Toward a new chemical mechanism in WRF/Chem for direct and indirect aerosol  

E-Print Network (OSTI)

, University of Colorado at Boulder, Boulder, Colorado, USA. 3 Earth System Research Laboratory, National Oceanic and Atmospheric administration, Boulder, Colorado, USA. e-mail: paolo to the coarse resolution of the inventory and by the missing of wildfire emissions. The modeled concentration

Curci, Gabriele

162

Predicting the Energy Output of Wind Farms Based on Weather Data: Important Variables and their Correlation  

E-Print Network (OSTI)

Wind energy plays an increasing role in the supply of energy world-wide. The energy output of a wind farm is highly dependent on the weather condition present at the wind farm. If the output can be predicted more accurately, energy suppliers can coordinate the collaborative production of different energy sources more efficiently to avoid costly overproductions. With this paper, we take a computer science perspective on energy prediction based on weather data and analyze the important parameters as well as their correlation on the energy output. To deal with the interaction of the different parameters we use symbolic regression based on the genetic programming tool DataModeler. Our studies are carried out on publicly available weather and energy data for a wind farm in Australia. We reveal the correlation of the different variables for the energy output. The model obtained for energy prediction gives a very reliable prediction of the energy output for newly given weather data.

Vladislavleva, Katya; Neumann, Frank; Wagner, Markus

2011-01-01T23:59:59.000Z

163

Gesture output: eyes-free output using a force feedback touch surface  

Science Journals Connector (OSTI)

We propose using spatial gestures not only for input but also for output. Analogous to gesture input, the proposed gesture output moves the user's finger in a gesture, which the user then recognizes. We use our concept in a mobile scenario where a motion ... Keywords: eyes free, force feedback, gestures, touch

Anne Roudaut; Andreas Rau; Christoph Sterz; Max Plauth; Pedro Lopes; Patrick Baudisch

2013-04-01T23:59:59.000Z

164

Procedia Computer Science 9 (2012) 887 896 1877-0509 2012 Published by Elsevier Ltd.  

E-Print Network (OSTI)

a mesoscale model (e.g., PRECIS, WRF) to simulate local effects at sub-daily time steps that are still variables except atmospheric pressure, wind speed, and precipitation. Correlations between downscaled output

Dietze, Michael

165

Single Inductor Dual Output Buck Converter  

E-Print Network (OSTI)

of value 3V. The main focus areas are low cross regulation between the outputs and supply of completely independent load current levels while maintaining desired values (1.2V,1.5 V) within well controlled ripple levels. Dynamic hysteresis control is used...

Eachempatti, Haritha

2010-07-14T23:59:59.000Z

166

Bioenergy technology balancing energy output with environmental  

E-Print Network (OSTI)

E2.3 Bioenergy technology ­ balancing energy output with environmental benefitsbenefits John standards #12;Is it right to grow bioenergy? Or How much bioenergy production is right? #12;Historical bioenergy Farmers historically used 25% land for horse feed #12;Energy crops are `solar panels' Solar energy

Levi, Ran

167

Modeling the Atmospheric Boundary Layer Wind Response to Mesoscale Sea Surface Temperature  

E-Print Network (OSTI)

(WRF) and COAMPS atmospheric models. The SST-induced wind response is assessed from eight simulations of the surface wind relative to the SST gradient. #12;3 1. Introduction Positive correlations of local surfaceModeling the Atmospheric Boundary Layer Wind Response to Mesoscale Sea Surface Temperature Natalie

Kurapov, Alexander

168

Administrator Ready Reference Guide Customizing an Output Style  

E-Print Network (OSTI)

may be in various sections of the instructions. Some things to look for: - line spacing Preview Utility (Tools, Preview Output Styles) or by simply opening the Output Style Editor (Bibliography, Edit button -- to the right of the output style drop- down). The Output Style Preview Utility

University of Technology, Sydney

169

Simulations of Organic Aerosol Concentrations in Mexico City Using the WRF-CHEM Model during the MCMA-2006/MILAGRO Campaign  

E-Print Network (OSTI)

) Aerodyne Research Inc, Billerica, MA, USA * Correspondence to: G. Li (lgh@mce2.org) and L.T. Molina

Meskhidze, Nicholas

170

Suitability of the Weather Research and Forecasting (WRF) Model to Predict the June 2005 Fire Weather for Interior Alaska  

E-Print Network (OSTI)

temperature, and daily accumulated shortwave radiation well. Daily minimum (maximum) temperature and relative to local fire management authorities on the potential for wild- fires to plan prescribed burns, alert of fire control into fire indices that reflect protection require- ments. The National Fire Danger Rating

Moelders, Nicole

171

Generalized Input-Output Inequality Systems  

SciTech Connect

In this paper two types of generalized Leontief input-output inequality systems are introduced. The minimax properties for a class of functions associated with the inequalities are studied. Sufficient and necessary conditions for the inequality systems to have solutions are obtained in terms of the minimax value. Stability analysis for the solution set is provided in terms of upper semi-continuity and hemi-continuity of set-valued maps.

Liu Yingfan [Department of Mathematics, Nanjing University of Post and Telecommunications, Nanjing 210009 (China)], E-mail: yingfanliu@hotmail.com; Zhang Qinghong [Department of Mathematics and Computer Science, Northern Michigan University, Marquette, MI 49855 (United States)], E-mail: qzhang@nmu.edu

2006-09-15T23:59:59.000Z

172

Characterizing detonator output using dynamic witness plates  

SciTech Connect

A sub-microsecond, time-resolved micro-particle-image velocimetry (PIV) system is developed to investigate the output of explosive detonators. Detonator output is directed into a transparent solid that serves as a dynamic witness plate and instantaneous shock and material velocities are measured in a two-dimensional plane cutting through the shock wave as it propagates through the solid. For the case of unloaded initiators (e.g. exploding bridge wires, exploding foil initiators, etc.) the witness plate serves as a surrogate for the explosive material that would normally be detonated. The velocity-field measurements quantify the velocity of the shocked material and visualize the geometry of the shocked region. Furthermore, the time-evolution of the velocity-field can be measured at intervals as small as 10 ns using the PIV system. Current experimental results of unloaded exploding bridge wire output in polydimethylsiloxane (PDMS) witness plates demonstrate 20 MHz velocity-field sampling just 300 ns after initiation of the wire.

Murphy, Michael John [Los Alamos National Laboratory; Adrian, Ronald J [Los Alamos National Laboratory

2009-01-01T23:59:59.000Z

173

Off-set stabilizer for comparator output  

DOE Patents (OSTI)

A stabilized off-set voltage is input as the reference voltage to a comparator. In application to a time-interval meter, the comparator output generates a timing interval which is independent of drift in the initial voltage across the timing capacitor. A precision resistor and operational amplifier charge a capacitor to a voltage which is precisely offset from the initial voltage. The capacitance of the reference capacitor is selected so that substantially no voltage drop is obtained in the reference voltage applied to the comparator during the interval to be measured.

Lunsford, James S. (Los Alamos, NM)

1991-01-01T23:59:59.000Z

174

Multi-criteria selection of an Air Quality Model configuration based on quantitative and linguistic evaluations  

Science Journals Connector (OSTI)

This study presents the application of multi-criteria evaluation in the selection of an optimal configuration for an Air Quality Model. The simulation domains focus on the Mexico City Metropolitan Area. A set of 10 different configurations were considered ... Keywords: Air quality, Multi-criteria evaluation, Pareto Fronts, WRF-Chem

V. H. Almanza; I. Batyrshin; G. Sosa

2014-02-01T23:59:59.000Z

175

Modelled and observed variability of the atmospheric circulation the Peruvian Current System: 2000-2005  

E-Print Network (OSTI)

on the characteristics of the local equatorward atmospheric circulation. Resolving the mesoscale variability of the heat Mesoscale Model (MM5) and Weather Research and Forecasting (WRF) that were run over the Peruvian Current System (PCS) [0N-19¬įS; 83¬įW-68¬įW] from November 2000- October 2005. Wind data as derived from

176

A numerical method for calculation of power output from ducted vertical axis hydro-current turbines  

Science Journals Connector (OSTI)

Abstract This paper investigates effects of ducting on power output from vertical axis hydro-current turbines. A numerical two-dimensional method based on the potential flow theory is developed for calculation of non-dimensional power output from these turbines. In this method, the blades are represented by vortex filaments. The vortex shedding from the blades is modeled by discrete vortices. A boundary element method is used to incorporate the duct shape which is represented by a series of panels with constant distributions of sources and doublets. The aerodynamic loading on the blades are calculated using a quasi-steady modeling. A time-marching scheme is used for implementation of the numerical method. The results of this method are compared with experimental results for a turbine model. A good correlation between the numerical and experimental results is obtained for tip speed ratios equal and higher than 2.25. However due to a lack of dynamic stall modeling, the numerical method is not able to predict power output accurately at lower tip speed ratios wherein effects of dynamic stall are significant. Both numerical and experimental results also showed that the power output from a turbine can increase significantly when it is enclosed within a well-designed duct. The maximum power output of the turbine model investigated in this paper showed a 74% increase when the turbine is operating within the duct relative to the case it is in free-stream conditions.

Mahmoud Alidadi; Sander Calisal

2014-01-01T23:59:59.000Z

177

Application of computer voice input/output  

SciTech Connect

The advent of microprocessors and other large-scale integration (LSI) circuits is making voice input and output for computers and instruments practical; specialized LSI chips for speech processing are appearing on the market. Voice can be used to input data or to issue instrument commands; this allows the operator to engage in other tasks, move about, and to use standard data entry systems. Voice synthesizers can generate audible, easily understood instructions. Using voice characteristics, a control system can verify speaker identity for security purposes. Two simple voice-controlled systems have been designed at Los Alamos for nuclear safeguards applicaations. Each can easily be expanded as time allows. The first system is for instrument control that accepts voice commands and issues audible operator prompts. The second system is for access control. The speaker's voice is used to verify his identity and to actuate external devices.

Ford, W.; Shirk, D.G.

1981-01-01T23:59:59.000Z

178

New Research Center to Increase Safety and Power Output of U.S. Nuclear  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

New Research Center to Increase Safety and Power Output of U.S. New Research Center to Increase Safety and Power Output of U.S. Nuclear Reactors New Research Center to Increase Safety and Power Output of U.S. Nuclear Reactors May 3, 2011 - 3:41pm Addthis Oak Ridge, Tenn. - Today the Department of Energy dedicated the Consortium for Advanced Simulation of Light Water Reactors (CASL), an advanced research facility that will accelerate the advancement of nuclear reactor technology. CASL researchers are using supercomputers to study the performance of light water reactors and to develop highly sophisticated modeling that will help accelerate upgrades at existing U.S. nuclear plants. These upgrades could improve the energy output of our existing reactor fleet by as much as seven reactors' worth at a fraction of the cost of building new reactors, while providing continued improvements in

179

Coordinated Output Regulation of Multiple Heterogeneous Linear Systems  

E-Print Network (OSTI)

, the generalizations of coordination of multiple linear dynamic systems to the cooperative output regulation problemCoordinated Output Regulation of Multiple Heterogeneous Linear Systems Ziyang Meng, Tao Yang, Dimos V. Dimarogonas, and Karl H. Johansson Abstract-- The coordinated output regulation problem

Dimarogonas, Dimos

180

The effect of small field output factor measurements on IMRT dosimetry  

SciTech Connect

Purpose: To evaluate how changes in the measured small field output factors affect the doses in intensity-modulated treatment planning. Methods: IMRT plans were created using Philips Pinnacle treatment planning system. The plans were optimized to treat a cylindrical target 2 cm in diameter and 2 cm in length. Output factors for 2 Multiplication-Sign 2 and 3 Multiplication-Sign 3 cm{sup 2} field sizes were changed by {+-}5%, {+-}10%, and {+-}20% increments from the baseline measurements and entered into the planning system. The treatment units were recommissioned in the treatment planning system after each modification of the output factors and treatment plans were reoptimized. All plans were delivered to a solid water phantom and dose measurements were made using an ionization chamber. The percentage differences between measured and computed doses were calculated. An Elekta Synergy and a Varian 2300CD linear accelerator were separately evaluated. Results: For the Elekta unit, decreasing the output factors resulted in higher measured than computed doses by 0.8% for -5%, 3.6% for -10%, and 8.7% for -20% steps. Increasing the output factors resulted in lower doses by 2.9% for +5%, 5.4% for +10%, and 8.3% for +20% steps. For the Varian unit no changes were observed for either increased or decreased output factors. Conclusions: The measurement accuracy of small field output factors are of importance especially when the treatment plan consists of small segments as in IMRT. The method proposed here could be used to verify the accuracy of the measured small field output factors for certain linear accelerators as well as to test the beam model. The Pinnacle treatment planning system model uses output factors as a function of jaw setting. Consequently, plans using the Elekta unit, which conforms the jaws to the segments, are sensitive to small field measurement accuracy. On the other hand, for the Varian unit, jaws are fixed and segments are modeled as blocked fields hence, the impact of small field output factors on IMRT monitor unit calculation is not evaluable by this method.

Azimi, Rezvan; Alaei, Parham; Higgins, Patrick [Department of Therapeutic Radiology-Radiation Oncology, University of Minnesota, Minneapolis, Minnesota 55455 (United States)

2012-08-15T23:59:59.000Z

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

AMPS, a real-time mesoscale modeling system, has provided a decade of service for scientific and logistical needs and has helped advance polar numerical weather prediction  

E-Print Network (OSTI)

and logistical needs and has helped advance polar numerical weather prediction as well as understanding support for the USAP. The concern at the time was the numerical weather prediction (NWP) guidance-time implementation of the Weather Research and Forecasting model (WRF; Skamarock et al. 2008) to support the U

Howat, Ian M.

182

Compact waveguide power divider with multiple isolated outputs  

DOE Patents (OSTI)

A waveguide power divider (10) for splitting electromagnetic microwave power and directionally coupling the divided power includes an input waveguide (21) and reduced height output waveguides (23) interconnected by axial slots (22) and matched loads (25) and (26) positioned at the unused ends of input and output guides (21) and (23) respectively. The axial slots are of a length such that the wave in the input waveguide (21) is directionally coupled to the output waveguides (23). The widths of input guide (21) and output guides (23) are equal and the width of axial slots (22) is one half of the width of the input guide (21).

Moeller, Charles P. (Del Mar, CA)

1987-01-01T23:59:59.000Z

183

An examination of the relationship between energy consumption and performance of transportation sector in Malaysia: output multipliers approach  

Science Journals Connector (OSTI)

The objective of the current study is to investigate the energy consumption and the performance of Malaysia's transportation sector. It applied output multiplier approach which is based on input-output model. Three input-output tables of Malaysia covering the 1991, 2000 and 2005 periods were used. The results indicate significant changes in the output multipliers of the transportation sector for the (1991-2005) period. Also, the transportation-to-energy subsector multipliers were found to increase over time. The increasing importance of transportation sector to the development of Malaysian economy resulted in a noticeable increase in the consumption of each energy subsector's output especially 'petrol and coal industries' products. Based on the research findings, several policy implications were suggested for the betterment of both sectors' performance and generally for the improvement of Malaysian economy.

Hussain Ali Bekhet; Azlina Abdullah

2013-01-01T23:59:59.000Z

184

GAMS program used to estimate capacity output using a distance function with both good and bad output, variable returns to scale and weak disposability of the bad outputs.  

E-Print Network (OSTI)

." VIMS Marine resource Report N. 2007-6. August 2007. Author: John B. Walden NMFS/NEFSC 166 Water St(obs) weights ; POSITIVE Variable weight, lambda; EQUATIONS CONSTR1(GOUTPUT, OBS) DEA constraint for each output

185

TRIPLE OUTPUT POWER SUPPLY Agilent MODEL E3630A  

E-Print Network (OSTI)

, manufacture, and intended use of the instrument. Agilent Technologies assumes no liability for the customer, the instrument chassis and cabinet must be connected to an electrical ground. The instrument must be connected to the ac power supply mains through a three-conductor power cable, with the third wire firmly connected

Ravikumar, B.

186

Modelling Power Output at Nuclear Power Plant by Neural Networks  

Science Journals Connector (OSTI)

In this paper, we propose two different neural network (NN) approaches for industrial process signal forecasting. Real data is available for this research from boiling water reactor type nuclear power reactors. N...

Jaakko Talonen; Miki Sirola; Eimontas Augilius

2010-01-01T23:59:59.000Z

187

Analytical input-output and supply chain study of China's coke and steel sectors  

E-Print Network (OSTI)

I design an input-output model to investigate the energy supply chain of coal-coke-steel in China. To study the demand, supply, and energy-intensity issues for coal and coke from a macroeconomic perspective, I apply the ...

Li, Yu, 1976-

2004-01-01T23:59:59.000Z

188

Constellation Shaping for Communication Channels with Quantized Outputs  

E-Print Network (OSTI)

average energy are selected more frequently than constellations with higher energy. However, the resultsConstellation Shaping for Communication Channels with Quantized Outputs Chandana Nannapaneni signal constellation and the output is quantized by a uniform scalar quantizer. The goal is to jointly

Valenti, Matthew C.

189

ANALOG-DIGITAL INPUT OUTPUT SYSTEM FOR APPLE CO  

E-Print Network (OSTI)

ADIOS ANALOG-DIGITAL INPUT OUTPUT SYSTEM FOR APPLE CO NATIONAL RADIO ASTRONOMY OBSERVATORY TABLES ADIOS - ANALOG-DIGITAL INPUT OUTPUT SYSTEM FOR APPLE COMPUTER TABLE FOR CONTENTS Page I Module and Apple Card (Photograph) Figure 3 Complete Apple/ADIOS System (Photograph) Figure 4 Analog

Groppi, Christopher

190

Most efficient quantum thermoelectric at finite power output  

E-Print Network (OSTI)

Machines are only Carnot efficient if they are reversible, but then their power output is vanishingly small. Here we ask, what is the maximum efficiency of an irreversible device with finite power output? We use a nonlinear scattering theory to answer this question for thermoelectric quantum systems; heat engines or refrigerators consisting of nanostructures or molecules that exhibit a Peltier effect. We find that quantum mechanics places an upper bound on both power output, and on the efficiency at any finite power. The upper bound on efficiency equals Carnot efficiency at zero power output, but decays with increasing power output. It is intrinsically quantum (wavelength dependent), unlike Carnot efficiency. This maximum efficiency occurs when the system lets through all particles in a certain energy window, but none at other energies. A physical implementation of this is discussed, as is the suppression of efficiency by a phonon heat flow.

Robert S. Whitney

2014-03-13T23:59:59.000Z

191

Relationship Among Efficiency and Output Power of Heat Energy Converters  

E-Print Network (OSTI)

Relationship among efficiency and output power of heat-electric energy converters as well as of any converters for transforming of heat energy into any other kind of energy is considered. It is shown, that the parameter efficiency does not determine univocally the output power of a converter. It is proposed to use another parameter for determination of working ability of heat energy converters. It is shown, that high output power can not be achieved by any kind of Stirling-type converters in spite of their high efficiency.

Alexander Luchinskiy

2004-09-02T23:59:59.000Z

192

Output, efficiency, emissions improved with Cat's 3500 series B engine  

SciTech Connect

Like most technologies, engine developments tend to follow evolutionary paths. And it's a given that the longer an engine's been around and the more successful it's been, the more likely it is that any changes made would be incremental. On the surface, such is the case with the Caterpillar 3500 Series B diesel engine, recently introduced in Europe and the United States. Based on the well-proven 3500 engine first introduced in 1980 and upgraded with a Phase II program five years later, most of the changes appear incremental. But taken as a whole, they provide a level of performance and durability that Caterpillar anticipates will make this engine an even stronger contender in power generation and marine applications for years to come. It's not hard to see why. Output has been increased between 17% and 30% on some models; fuel consumption is improved by as much as 15%; and with the new aftertreatment system introduced with the engines, emissions as low as 1.3 g/kWh NO[sub x] are said to be achieveable. This paper outlines the design, specifications, and highlights of the improvements in performance of these new engines. 3 figs.

Brezonick, M.

1995-03-01T23:59:59.000Z

193

Computability in Anonymous Networks: Revocable vs. Irrecovable Outputs  

E-Print Network (OSTI)

Computability in Anonymous Networks: Revocable vs. Irrecovable Outputs Yuval Emek1 , Jochen Seidel2, and leader election. 1 Introduction We study computability in networks, referred to hereafter as distributed

194

Failure mode and effects analysis outputs: are they valid?  

Science Journals Connector (OSTI)

Failure Mode and Effects Analysis (FMEA) is a prospective risk assessment tool that ... this study was to explore the validity of FMEA outputs within a hospital setting in the...

Nada Atef Shebl; Bryony Dean Franklin; Nick Barber

2012-06-01T23:59:59.000Z

195

Grid adaptation for functional outputs of compressible flow simulations  

E-Print Network (OSTI)

An error correction and grid adaptive method is presented for improving the accuracy of functional outputs of compressible flow simulations. The procedure is based on an adjoint formulation in which the estimated error in ...

Venditti, David Anthony, 1973-

2002-01-01T23:59:59.000Z

196

Reliable Gas Turbine Output: Attaining Temperature Independent Performance  

E-Print Network (OSTI)

of availability, it is the major option for future power generation. One inherent disadvantage of gas turbines is the degradation of output as the ambient air temperature increases. This reduction in output during times of peak load create a reliability..., power generation for offshore platforms, utility peak load 58 ESL-IE-92-04-10 Proceedings from the 14th National Industrial Energy Technology Conference, Houston, TX, April 22-23, 1992 power generation, emergency power, ship propulsion, and private...

Neeley, J. E.; Patton, S.; Holder, F.

197

Review of Wind Energy Forecasting Methods for Modeling Ramping Events  

SciTech Connect

Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.

Wharton, S; Lundquist, J K; Marjanovic, N; Williams, J L; Rhodes, M; Chow, T K; Maxwell, R

2011-03-28T23:59:59.000Z

198

Analysis of Temporal and Spatial Characteristics on Output of Wind Farms with Doubly Fed Induction Generator Wind Turbines  

Science Journals Connector (OSTI)

Due to the large number of wind turbines and covering too large area in a large wind farm, wake effects among wind turbines and wind speed time delays will have a greater impact of wind farms models. Taking wind farms with doubly fed induction generator(DFIG) ... Keywords: wind farm, modeling, temporal and spatial characteristics, DFIG, output characteristics

Shupo Bu; Xunwen Su

2012-12-01T23:59:59.000Z

199

Implementation of a generalized actuator disk wind turbine model into the weather research and forecasting model for large-eddy simulation applications  

Science Journals Connector (OSTI)

A generalized actuator disk (GAD) wind turbine parameterization designed for large-eddy simulation (LES) applications was implemented into the Weather Research and Forecasting (WRF) model. WRF-LES with the GAD model enables numerical investigation of the effects of an operating wind turbine on and interactions with a broad range of atmospheric boundary layer phenomena. Numerical simulations using WRF-LES with the GAD model were compared with measurements obtained from the Turbine Wake and Inflow Characterization Study (TWICS-2011) the goal of which was to measure both the inflow to and wake from a 2.3-MW wind turbine. Data from a meteorological tower and two light-detection and ranging (lidar) systems one vertically profiling and another operated over a variety of scanning modes were utilized to obtain forcing for the simulations and to evaluate characteristics of the simulated wakes. Simulations produced wakes with physically consistent rotation and velocity deficits. Two surface heat flux values of 20?W m?2 and 100?W m?2 were used to examine the sensitivity of the simulated wakes to convective instability. Simulations using the smaller heat flux values showed good agreement with wake deficits observed during TWICS-2011 whereas those using the larger value showed enhanced spreading and more-rapid attenuation. This study demonstrates the utility of actuator models implemented within atmospheric LES to address a range of atmospheric science and engineering applications. Validated implementation of the GAD in a numerical weather prediction code such as WRF will enable a wide range of studies related to the interaction of wind turbines with the atmosphere and surface.

J. D. Mirocha; B. Kosovic; M. L. Aitken; J. K. Lundquist

2014-01-01T23:59:59.000Z

200

Estimation of annual energy output from a tidal barrage using two different methods  

Science Journals Connector (OSTI)

In recent years, there have been growing international challenges relating to climate change and global warming, with a conflict developing between the need to create a low-carbon economy and rapid depleting reserves of fossil fuels. In addition to these challenges there continues to be the added complexity of a significant global increase in energy demand. Marine renewable energy from tidal barrages is carbon-free and has the potential to make a significant contribution to energy supplies now and in the future. Therefore, it is appropriate to evaluate the total energy that can be extracted from such barrages. In this study two different methods are proposed to estimate the total annual energy output from a barrage, including a theoretical estimation based on the principle associated with tidal hydrodynamics, and a numerical estimation based on the solutions obtained from a 2D hydrodynamic model. The proposed Severn Barrage in the UK was taken as a case study, and these two methods were applied to estimate the potential annual energy output from the barrage. The predicted results obtained using the two methods indicate that the magnitude of the annual energy output would range from 13 to 16†TWh, which is similar to the value of 15.6†TWh reported by the Department of Energy and Climate Change, in the UK. Further investigations show that the total annual energy output would increase by about 15% if a higher discharge coefficient were to be adopted for the sluice gates, or if the turbine performance were to be improved. However, the estimated annual energy output could exceed the value of 16†TWh if future technological advances in both sluice gate construction and turbine performance are included.

Junqiang Xia; Roger A. Falconer; Binliang Lin; Guangming Tan

2012-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Carbon Capture, Transport and Storage Regulatory Test Exercise: Output  

Open Energy Info (EERE)

Carbon Capture, Transport and Storage Regulatory Test Exercise: Output Carbon Capture, Transport and Storage Regulatory Test Exercise: Output Report Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Carbon Capture, Transport and Storage Regulatory Test Exercise: Output Report Focus Area: Clean Fossil Energy Topics: Market Analysis Website: cdn.globalccsinstitute.com/sites/default/files/publications/7326/carbo Equivalent URI: cleanenergysolutions.org/content/carbon-capture-transport-and-storage- Policies: Regulations Regulations: Emissions Mitigation Scheme The Scottish Government published this report to identify regulatory gaps or overlaps in the nation's framework for regulating carbon capture and storage (CCS). The report aims to streamline and better manage CCS regulation. It focuses on evaluating the risks, barriers, information gaps,

202

OECD Input-Output Tables | Open Energy Information  

Open Energy Info (EERE)

OECD Input-Output Tables OECD Input-Output Tables Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Input-Output Tables Agency/Company /Organization: Organisation for Economic Co-Operation and Development Topics: Co-benefits assessment, Market analysis, Co-benefits assessment, Pathways analysis Resource Type: Dataset Website: www.oecd.org/document/3/0,3343,en_2649_34445_38071427_1_1_1_1,00.html Country: Sweden, Finland, Japan, South Korea, Argentina, Australia, China, Israel, United Kingdom, Portugal, Romania, Greece, Poland, Slovakia, Chile, India, Canada, New Zealand, United States, Denmark, Norway, Spain, Austria, Italy, Netherlands, Ireland, France, Belgium, Brazil, Czech Republic, Estonia, Germany, Hungary, Luxembourg, Mexico, Slovenia, South Africa, Turkey, Indonesia, Switzerland, Taiwan, Russia

203

Development of a 402.5 MHz 140 kW Inductive Output Tube  

SciTech Connect

This report contains the results of Phase I of an SBIR to develop a Pulsed Inductive Output Tube (IOT) with 140 kW at 400 MHz for powering H-proton beams. A number of sources, including single beam and multiple beam klystrons, can provide this power, but the IOT provides higher efficiency. Efficiencies exceeding 70% are routinely achieved. The gain is typically limited to approximately 24 dB; however, the availability of highly efficient, solid state drivers reduces the significance of this limitation, particularly at lower frequencies. This program initially focused on developing a 402 MHz IOT; however, the DOE requirement for this device was terminated during the program. The SBIR effort was refocused on improving the IOT design codes to more accurately simulate the time dependent behavior of the input cavity, electron gun, output cavity, and collector. Significant improvement was achieved in modeling capability and simulation accuracy.

R. Lawrence Ives; Michael Read, Robert Jackson

2012-05-09T23:59:59.000Z

204

Output power characteristics and performance of TOPAZ II Thermionic Fuel Element No. 24  

SciTech Connect

A final report on the output power characteristics and capabilities of single cell TOPAZ II Thermionic Fuel Element (TFE) No. 24 is presented. Thermal power tests were conducted for over 3000 hours to investigate converter performance under normal and adverse operating conditions. Experiments conducted include low power testing, high power testing, air introduction to the interelectrode gap, collector temperature optimization, thermal modeling, and output power characteristic measurements. During testing, no unexpected degradation in converter performance was observed. The TFE has been removed from the test stand and returned to Scientific Industrial Association {open_quote}{open_quote}LUCH{close_quote}{close_quote} for materials analysis and report. This research was conducted at the Thermionic System Evaluation Test (TSET) Facility at the New Mexico Engineering Research Institute (NMERI) as a part of the Topaz International Program (TIP) by the Air Force Phillips Laboratory (PL). {copyright} {ital 1996 American Institute of Physics.}

Luchau, D.W.; Bruns, D.R. [Team Specialty Services, Inc., TOPAZ International Program, 901 University Blvd., SE, Albuquerque, New Mexico 87106 (United States); Izhvanov, O.; Androsov, V. [JV INERTEK, Scientific Industrial Association ``Luch``, 24 Zheleznodorozhnaya, Podolsk, (Russia) 142100

1996-03-01T23:59:59.000Z

205

An input-output approach to analyze the ways to increase total output of energy sectors: The case of Japan  

Science Journals Connector (OSTI)

The purpose of this study is to analyze the ways to increase total output of Japanese energy sectors in future time. In this study, Input-Output (IO) analysis is employed as a tool of analysis. This study focuses on petroleum refinery products and non-ferrous metals as analyzed sectors. The results show that positive impact observed in export and outside households consumption modifications while opposite impact is given by modification of import. The recommendations suggested based on these results are Japanese government should make breakthroughs so analyzed sector's export activities can increase and they have to careful in conducting import activities related to these sectors.

Ubaidillah Zuhdi

2014-01-01T23:59:59.000Z

206

Output-Based Regulations: A Handbook for Air Regulators (U.S. EPA), August 2004  

Energy.gov (U.S. Department of Energy (DOE))

Handbook providing practical information to help regulators decide if they want to use output-based regulations and explains how to develop an output-based emission standard

207

Output-Sensitive Algorithms for Tukey Depth and Related Problems  

E-Print Network (OSTI)

Output-Sensitive Algorithms for Tukey Depth and Related Problems David Bremner University of New de Bruxelles Pat Morin Carleton University Abstract The Tukey depth (Tukey 1975) of a point p halfspace that contains p. Algorithms for computing the Tukey depth of a point in various dimensions

Morin, Pat

208

Soft-Input Soft-Output Sphere Decoding Christoph Studer  

E-Print Network (OSTI)

Soft-Input Soft-Output Sphere Decoding Christoph Studer Integrated Systems Laboratory ETH Zurich Laboratory ETH Zurich, 8092 Zurich, Switzerland Email: boelcskei@nari.ee.ethz.ch Abstract--Soft-input soft, 8092 Zurich, Switzerland Email: studer@iis.ee.ethz.ch Helmut Bölcskei Communication Technology

209

Maximizing output from oil reservoirs without water breakthrough  

E-Print Network (OSTI)

Maximizing output from oil reservoirs without water breakthrough S.K. Lucas School of Mathematics, revised May 2003, published 45(3), 2004, 401­422 Abstract Often in oil reservoirs a layer of water lies, for example, Muskat [8], Bear [1]). When oil is removed from the reservoir by an oil well, it will generate

Lucas, Stephen

210

Model Development Development of a system emulating the global carbon cycle in Earth system models  

E-Print Network (OSTI)

developed a loosely coupled model (LCM) which can represent the outputs of a GCMbased Earth system model

K. Tachiiri; J. C. Hargreaves; J. D. Annan; A. Oka; A. Abe-ouchi; M. Kawamiya

2010-01-01T23:59:59.000Z

211

Effect of local government expenditure on the ratio of output to capital: Evidence from panel data at Chinaís provincial level  

Science Journals Connector (OSTI)

This paper divides the expenditure of local government into the productive and nonproductive expenditure for revealing the effect of local governmentís expenditure on output-capital efficiency through model and e...

Tao Jin; Jianhui Zhang

2011-06-01T23:59:59.000Z

212

Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe  

Science Journals Connector (OSTI)

Abstract This article combines and discusses three independent validations of global horizontal irradiance (GHI) multi-day forecast models that were conducted in the US, Canada and Europe. All forecast models are based directly or indirectly on numerical weather prediction (NWP). Two models are common to the three validation efforts Ė the ECMWF global model and the GFS-driven WRF mesoscale model Ė and allow general observations: (1) the GFS-based WRF- model forecasts do not perform as well as global forecast-based approaches such as ECMWF and (2) the simple averaging of modelsí output tends to perform better than individual models.

Richard Perez; Elke Lorenz; Sophie Pelland; Mark Beauharnois; Glenn Van Knowe; Karl Hemker Jr.; Detlev Heinemann; Jan Remund; Stefan C. MŁller; Wolfgang TraunmŁller; Gerald Steinmauer; David Pozo; Jose A. Ruiz-Arias; Vicente Lara-Fanego; Lourdes Ramirez-Santigosa; Martin Gaston-Romero; Luis M. Pomares

2013-01-01T23:59:59.000Z

213

Ecosystem feedbacks to climate change in California: Development, testing, and analysis using a coupled regional atmosphere and land-surface model (WRF3-CLM3.5)  

E-Print Network (OSTI)

at the expense of conifer forest and alpine/subalpine forestat the expense of conifer forest and alpine/subalpine forestcover (e.g. , mixed conifer forest) as combinations of

Subin, Z.M.

2012-01-01T23:59:59.000Z

214

Simulation of one-minute power output from utility-scale photovoltaic generation systems.  

SciTech Connect

We present an approach to simulate time-synchronized, one-minute power output from large photovoltaic (PV) generation plants in locations where only hourly irradiance estimates are available from satellite sources. The approach uses one-minute irradiance measurements from ground sensors in a climatically and geographically similar area. Irradiance is translated to power using the Sandia Array Performance Model. Power output is generated for 2007 in southern Nevada are being used for a Solar PV Grid Integration Study to estimate the integration costs associated with various utility-scale PV generation levels. Plant designs considered include both fixed-tilt thin-film, and single-axis-tracked polycrystalline Si systems ranging in size from 5 to 300 MW{sub AC}. Simulated power output profiles at one-minute intervals were generated for five scenarios defined by total PV capacity (149.5 MW, 222 WM, 292 MW, 492 MW, and 892 MW) each comprising as many as 10 geographically separated PV plants.

Stein, Joshua S.; Ellis, Abraham; Hansen, Clifford W.

2011-08-01T23:59:59.000Z

215

Clock-controlled generators with large period output sequences  

Science Journals Connector (OSTI)

Clock-controlled generators are a kind of pseudo-random number generators (PRNG). Recently, some clock-controlled generators based on jumping Linear Finite State Machines (LFSMs) have been proposed, such as Pomaranch and MICKEY. The period and the linear complexity of their output sequences need to be large enough to provide security against linear attacks. In this paper, a new condition for the period to reach its maximal value is presented. The condition is better than the previous one. Further, some clock-controlled generators are considered, including a new generator which uses a Feedback with Carry Shift Register (FCSR) as the control register. How to maximise the period of their output sequences is investigated.

Zhiqiang Lin

2014-01-01T23:59:59.000Z

216

Control of XeF laser output by pulse injecton  

SciTech Connect

Injection locking is investigated as a means for control of optical pulse duration and polarization in a XeF laser. Intense short-pulse generation in the ultraviolet is achieved by injection of a low-level 1-ns optical pulse into a XeF oscillator. Control of laser output polarization by injection locking is demonstrated and studied as a function of injected signal level. Enhancement of XeF electric-discharge laser efficiency by injection pulse ''priming'' is observed.

Pacala, T.J.; Christensen, C.P.

1980-04-15T23:59:59.000Z

217

Output power characteristics of the neutral xenon long laser  

SciTech Connect

Lasers which oscillate within inhomogeneously broadened gain media exhibit spectral hole burning and concomitant reduction in output power compared with equivalent homogeneously-broadened laser gain media. By increasing the cavity length, it may be possible to demonstrate at least a partial transition from an inhomogeneous laser cavity mode spectrum to a homogeneous spectrum. There are a number of high gain laser lines which are inhomogeneously-broadened transitions in electric discharges of neutral xenon. In neutral xenon lasers, as in the cases of many other gas lasers, the inhomogeneous spectral broadening mechanism arises from Doppler shifts, {Delta}{nu}{sub D}, of individual atoms in thermal motion within the electric discharge comprising the laser gain medium. Optical transitions corresponding to these noble gas atoms have natural linewidths, {Delta}{nu}{sub n}{lt}{Delta}{nu}{sub D}. Simulations of the output power characteristics of the xenon laser were carried out as a function of laser cavity parameters, including the cavity length, L. These calculations showed that when the intracavity mode spacing frequency, c/2L{lt}{Delta}{nu}{sub n}, the inhomogeneously broadened xenon mode spectrum converted to a homogeneously broadened oscillation spectrum with an increase in output power. These simulations are compared with experimental results obtained for the long laser oscillation characteristics of the (5d[5/2]{degree}{sub 2}{r_arrow}6p[3/2]{sub 1}) transition corresponding to the strong, high-gain 3.508 {mu} line in xenon.

Linford, G.J. [TRW Space and Electronics Group, Redondo Beach, CA (United States). Space and Technology Div.

1994-12-31T23:59:59.000Z

218

Analysis of photovoltaic module energy output under operating conditions in South Africa  

SciTech Connect

South Africa does not have any industry standard methodology to evaluate photovoltaic (PV) modules for energy production. The aim of this study is to characterize the energy production of PV modules deployed outdoors at the University of Port Elizabeth (UPE), Summerstrand, South Africa with the view of facilitating such a standard. The system developed for this study was designed to monitor the energy production of seven PV modules under normal operating conditions. An analysis of energy production of three of the PV modules under test, while operating under prevailing outdoor conditions, is given. Measured energy output is also compared with that predicted using an energy model.

Dyk, E.E. van; Meyer, E.L.; Scott, B.J.; O`Connor, D.A.; Wessels, J.B. [Univ. of Port Elizabeth (South Africa). Dept. of Physics

1997-12-31T23:59:59.000Z

219

NCPART: management of ICEMDDN output for numerical control users  

SciTech Connect

NCPART is a procedure developed by the Numerical Control Department at Bendix Kansas City Division to handle the entry to and exit from ICEMDDN, and process all of the local files output by ICEMDDN. The NCPART procedure is menu driven, and provides automatic access to ICEMDDN and any files necessary to process information with ICEM for numerical Control users. Basically, the procedure handles all of the ICEMDDN operations that involve operating system commands, and frees the NC programmer to concentrate on his/her work as a programmer.

Rossini, B.F.

1986-04-01T23:59:59.000Z

220

Waveguide submillimetre laser with a uniform output beam  

SciTech Connect

A method for producing non-Gaussian light beams with a uniform intensity profile is described. The method is based on the use of a combined waveguide quasi-optical resonator containing a generalised confocal resonator with an inhomogeneous mirror with absorbing inhomogeneities discretely located on its surface and a hollow dielectric waveguide whose size satisfies the conditions of self-imaging of a uniform field in it. The existence of quasi-homogeneous beams at the output of an optically pumped 0.1188-mm waveguide CH{sub 3}OH laser with a amplitude-stepped mirror is confirmed theoretically and experimentally. (lasers)

Volodenko, A V; Gurin, O V; Degtyarev, A V; Maslov, Vyacheslav A; Svich, V A; Topkov, A N [V.N. Karazin Kharkiv National University, Kharkiv (Ukraine)

2007-01-31T23:59:59.000Z

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Method and system for managing an electrical output of a turbogenerator  

DOE Patents (OSTI)

The system and method manages an electrical output of a turbogenerator in accordance with multiple modes. In a first mode, a direct current (DC) bus receives power from a turbogenerator output via a rectifier where turbogenerator revolutions per unit time (e.g., revolutions per minute (RPM)) or an electrical output level of a turbogenerator output meet or exceed a minimum threshold. In a second mode, if the turbogenerator revolutions per unit time or electrical output level of a turbogenerator output are less than the minimum threshold, the electric drive motor or a generator mechanically powered by the engine provides electrical energy to the direct current bus.

Stahlhut, Ronnie Dean (Bettendorf, IA); Vuk, Carl Thomas (Denver, IA)

2010-08-24T23:59:59.000Z

222

Regulatory Reform to Promote Clean Energy: The Potential of Output-Based Emissions Standards  

SciTech Connect

Barriers to industrial energy-efficient technologies hinder their use. A number of EPA analyses and industrial experts have found that the utilization of input-based emissions standards (measured in parts-per-million or pounds/MMBtu) in the Clean Air Act creates a regulatory barrier to the installation and deployment of technologies that emit fewer criteria pollutants and use energy more efficiently. Changing emission management strategies to an output-based emissions standard (measured in tons of pollutant emitted) is a way to ameliorate some of these barriers. Combined heat and power (CHP) is one of the key technologies that would see increased industrial application if the emissions standards were modified. Many states have made this change since the EPA first approved it in 2000, although direction from the Federal government could speed implementation modifications. To analyze the national impact of accelerated state adoption of output-based standards on CHP technologies, this paper uses detailed National Energy Modeling System (NEMS) and spreadsheet analysis illustrating two phased-in adoption scenarios for output-based emissions standards in the industrial sector. Benefit/cost metrics are calculated from a private and public perspective, and also a social perspective that considers the criteria and carbon air pollution emissions. These scenarios are compared to the reference case of AEO 2010 and are quite favorable, with a social benefit-cost ratio of 16.0 for a five-year phase-in scenario. In addition, the appropriateness of the Federal role, applicability, technology readiness, and administrative feasibility are discussed.

Cox, Matthew [Georgia Institute of Technology] [Georgia Institute of Technology; Brown, Dr. Marilyn Ann [Georgia Institute of Technology] [Georgia Institute of Technology; Jackson, Roderick K [ORNL] [ORNL

2011-01-01T23:59:59.000Z

223

Quantum teleportation scheme by selecting one of multiple output ports  

E-Print Network (OSTI)

The scheme of quantum teleportation, where Bob has multiple (N) output ports and obtains the teleported state by simply selecting one of the N ports, is thoroughly studied. We consider both deterministic version and probabilistic version of the teleportation scheme aiming to teleport an unknown state of a qubit. Moreover, we consider two cases for each version: (i) the state employed for the teleportation is fixed to a maximally entangled state, and (ii) the state is also optimized as well as Alice's measurement. We analytically determine the optimal protocols for all the four cases, and show the corresponding optimal fidelity or optimal success probability. All these protocols can achieve the perfect teleportation in the asymptotic limit of $N\\to\\infty$. The entanglement properties of the teleportation scheme are also discussed.

Satoshi Ishizaka; Tohya Hiroshima

2009-04-06T23:59:59.000Z

224

GAMS program used to estimate capacity output using a distance function with both desirable and undesirable outputs, and weak disposability for the undesirable outputs.  

E-Print Network (OSTI)

." VIMS Marine resource Report N. 2007-6. August 2007. Author: John B. Walden NMFS/NEFSC 166 Water St(obs,var) variuable input utilization rate weight(obs) weights ; POSITIVE Variable weight, lambda; EQUATIONS CONSTR1 /dd_res_crs.txt/ MODEL CAP /ALL/; /*Use all the equations. Alternatively, the model could be solved

225

A H-infinity Fault Detection and Diagnosis Scheme for Discrete Nonlinear System Using Output Probability Density Estimation  

SciTech Connect

In this paper, a H-infinity fault detection and diagnosis (FDD) scheme for a class of discrete nonlinear system fault using output probability density estimation is presented. Unlike classical FDD problems, the measured output of the system is viewed as a stochastic process and its square root probability density function (PDF) is modeled with B-spline functions, which leads to a deterministic space-time dynamic model including nonlinearities, uncertainties. A weighting mean value is given as an integral function of the square root PDF along space direction, which leads a function only about time and can be used to construct residual signal. Thus, the classical nonlinear filter approach can be used to detect and diagnose the fault in system. A feasible detection criterion is obtained at first, and a new H-infinity adaptive fault diagnosis algorithm is further investigated to estimate the fault. Simulation example is given to demonstrate the effectiveness of the proposed approaches.

Zhang Yumin; Lum, Kai-Yew [Temasek Laboratories, National University of Singapore, Singapore 117508 (Singapore); Wang Qingguo [Depa. Electrical and Computer Engineering, National University of Singapore, Singapore 117576 (Singapore)

2009-03-05T23:59:59.000Z

226

Effects of collector radius and chimney height on power output of a solar chimney power plant with turbines  

Science Journals Connector (OSTI)

A comprehensive theoretical model is proposed for the performance evaluation of a solar chimney power plant (SCPP), and has been verified by the experimental data of the Spanish prototype. This model takes account of the effects of flow and heat losses, and the temperature lapse rates inside and outside the chimney. There is a maximum power output for a certain SCPP under a given solar radiation condition, due to flow and heat losses and the installation of the turbines. In addition, the design flow rate of the turbine in the SCPP system is found beneficial for power output when it is lower than that at the†maximum power point. Furthermore, a limitation on the maximum collector radius exists for the maximum attainable power of the SCPP; whereas, no such limitation exists for chimney height in terms of contemporary construction technology.

Jing-yin Li; Peng-hua Guo; Yuan Wang

2012-01-01T23:59:59.000Z

227

Land surface feedbacks on spring precipitation in the Netherlands  

Science Journals Connector (OSTI)

In this paper the Weather Research and Forecasting (WRF) model is used to investigate the sensitivity of precipitation to soil moisture and urban areas in the Netherlands. We analyze the average output of a four day event from 10-13 May 1999 for ...

Emma E. Daniels; Ronald W.A. Hutjes; Geert Lenderink; Reinder J. Ronda; Albert A.M. Holtslag

228

GEOSS in Action The Mesoamerican  

E-Print Network (OSTI)

: Smoke or Dust May 21, 2007 Concern of a Toxic Cloud from Africa. SERVIR Analysis Determined it was local such as MM5 (left), WRF, and SPoRT model outputs, along with GOES imagery (above), provide a continuous;Visualization Tools for Decision Support · NASA and Commercial ­ SERVIR-Viz / NASA World Wind ­ Google Earth

Kuligowski, Bob

229

ADVANCES IN ATMOSPHERIC SCIENCES, VOL. 25, NO. 1, 2008, 1123 Total Deformation and its Role in Heavy Precipitation Events  

E-Print Network (OSTI)

Research and Forecasting (WRF) model output data. It is found that right before the occurrence of the terms shows that the pressure gradient plays a major role in determining the local change of total and wind velocity, only wind velocity is a vector. At the mesoscale, where the characteristic scale is less

Xue, Ming

230

Atmos. Chem. Phys., 12, 24092427, 2012 www.atmos-chem-phys.net/12/2409/2012/  

E-Print Network (OSTI)

positive impact on the other output variables, such as temperature and wind. By using the optimal of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft

Meskhidze, Nicholas

231

Robust Characterization of Model Physics Uncertainty for Simulations of Deep Moist Convection  

Science Journals Connector (OSTI)

This study explores the functional relationship between model physics parameters and model output variables for the purpose of 1) characterizing the sensitivity of the simulation output to the model formulation and 2) understanding model ...

Derek J. Posselt; Tomislava Vukicevic

2010-05-01T23:59:59.000Z

232

Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by  

NLE Websites -- All DOE Office Websites (Extended Search)

2: August 13, 2: August 13, 2007 Refinery Output by World Region to someone by E-mail Share Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by World Region on Facebook Tweet about Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by World Region on Twitter Bookmark Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by World Region on Google Bookmark Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by World Region on Delicious Rank Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by World Region on Digg Find More places to share Vehicle Technologies Office: Fact #482: August 13, 2007 Refinery Output by World Region on AddThis.com... Fact #482: August 13, 2007

233

Sandia National Laboratories: simulating solar-power-plant output...  

NLE Websites -- All DOE Office Websites (Extended Search)

Energy, Modeling & Analysis, News, News & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource...

234

Process and Intermediate Calculations User AccessInputs Outputs  

E-Print Network (OSTI)

density, canopy base height, fuel moisture) · Weather · Fire History · Ignition History Analytic Models Behavior · DEM (Elevation, slope, aspect) · Vegetation (Fuel models, crown cover, stand height, bulk Smoke Analysis Management of Unplanned Ignitions: Each cell is evaluated using a probabilistic footprint

235

Combining frequency and time domain approaches to systems with multiple spike train input and output  

E-Print Network (OSTI)

between neuronal spike trains. Prog Biophys Mol Biol Vapnikto systems with multiple spike train input and output D. R.Keywords Multiple spike trains ∑ Neural coding ∑ Maximum

Brillinger, D. R.; Lindsay, K. A.; Rosenberg, J. R.

2009-01-01T23:59:59.000Z

236

On using transputers to design the header and output processors for the PSi architecture  

E-Print Network (OSTI)

the complexity associatecl with general soft ware. From Upper Layer Needer Processor From Lower Leyei' Input Bus Concoction Processor Connection Processor 256 CP's Output Bus To Upper Layer Output Processor To Lower Layer Fig. 2. d. Block... yer From Lower Layer T2 T3 To Input Bus of CP's From Output Bus of CF's From Output Bus of Cfes Fig, 4. 1. e. Block diagram of Design I transputers has its own private memory. Tl acts as the header processor. Two of its serial links...

Manickam, Muralidhar

2012-06-07T23:59:59.000Z

237

A CSP Timed Input-Output Relation and a Strategy for Mechanised Conformance Verification  

Science Journals Connector (OSTI)

Here we propose a timed input-output conformance relation (named CSPTIO) based on the process algebra CSP. In contrast to other relations, CSPTIO...

Gustavo Carvalho; Augusto SampaioÖ

2013-01-01T23:59:59.000Z

238

Cavity dumping versus stationary output coupling in repetitively Q-switched solid-state lasers  

Science Journals Connector (OSTI)

A comparative theoretical analysis of continuously pumped actively Q-switched solid-state lasers differing in output coupling methods (cavity dumping versus a partially transmitting...

Grishin, Mikhail

2011-01-01T23:59:59.000Z

239

Wind Technology Modeling Within the System Advisor Model (SAM...  

NLE Websites -- All DOE Office Websites (Extended Search)

P. Gilman, J. Whitmore* National Renewable Energy Laboratory * Golden, Colorado OFFSHORE WINDPOWER 2014, Las Vegas, May 58, 2014 Model Basics Outputs and Advanced Analysis...

240

Large eddy simulation of wind turbine wake dynamics in the stable boundary layer using the Weather Research and Forecasting Model  

Science Journals Connector (OSTI)

Recently an actuator disk parameterization was implemented in the Weather Research and Forecasting (WRF) Model for large eddy simulation (LES) of wind turbine wakes. To thoroughly verify this model simulations of various types of turbines and atmospheric conditions must be evaluated against corresponding experimental data. In this work numerical simulations are compared to nacelle-based scanning lidar measurements taken in stable atmospheric conditions during a field campaign conducted at a wind farm in the western United States. Using several wake characteristicsósuch as the velocity deficit centerline location and wake widthóas metrics for model verification the simulations show good agreement with the observations. Notable results include a high average velocity deficit decreasing from 73% at a downwind distance x of 1.2 rotor diameters (D) to 25% at x?=?6.6D resulting from a low average wind speed and therefore high average turbine thrust coefficient. Moreover the wake width expands from 1.4D at x?=?1.2D to 2.3D at x?=?6.6D. Finally new featuresónamely rotor tilt and drag from the nacelle and toweróare added to the existing actuator disk model in WRF-LES. Compared to the rotor the effect of the tower and nacelle on the flow is relatively small but nevertheless important for an accurate representation of the entire turbine. Adding rotor tilt to the model causes the vertical location of the wake center to shift upward. Continued advancement of the actuator disk model in WRF-LES will help lead to optimized turbine siting and controls at wind farms.

Matthew L. Aitken; Branko Kosovi?; Jeffrey D. Mirocha; Julie K. Lundquist

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Extreme precipitations and temperatures over the U.S. Pacific Northwest : A comparison between observations, reanalysis data and regional models  

E-Print Network (OSTI)

reanalysis data and the nested WRF (Weather Research and Forecasting) and HadRM (Hadley States Pacific Northwest during 20032007. The WRF and HadRM simulations driven by the R2 reanalysis data and statistically significant, and slopes are close to 1. The WRF Domain 3 with its highest resolution (~12 km

Salathé Jr., Eric P.

242

HSPICE and WaveView Tutorial Hspice is used for circuit simulation and WaveView is used to view output waveforms.  

E-Print Network (OSTI)

NNano-E Hs Electron Sc San Fr S spice Q Mich Hamid nics & C chool of rancisco San Fra Spr Quick By be downloaded from the following website: http://ptm.asu.edu/ Click on the latest models and download 16nm PTM "hspice job aborted". In that case, please open the output file (inv.out) and search for error to see

Mahmoodi, Hamid

243

Estimating Solar PV Output Using Modern Space/Time Geostatistics (Presentation)  

SciTech Connect

This presentation describes a project that uses mapping techniques to predict solar output at subhourly resolution at any spatial point, develop a methodology that is applicable to natural resources in general, and demonstrate capability of geostatistical techniques to predict the output of a potential solar plant.

Lee, S. J.; George, R.; Bush, B.

2009-04-29T23:59:59.000Z

244

PWM Inverter Output Filter Cost to Losses Trade Off and Optimal Design  

E-Print Network (OSTI)

PWM Inverter Output Filter Cost to Losses Trade Off and Optimal Design Robert J. Pasterczyk Jean--This paper describes how to design the output filter of a PWM inverter used in a Uninterruptible Power SupplyVA 3-ph. PWM inverter is taken as example. B. Design Constraints Uninterruptible Power Supply (UPS

Paris-Sud XI, Université de

245

Quality assurance of solar thermal systems with the ISFH-Input/Output-Procedure  

E-Print Network (OSTI)

. Supplementary sensors may be necessary for some special solar systems (e. g. solar systems with several storagesQuality assurance of solar thermal systems with the ISFH- Input/Output-Procedure Peter Paerisch/Output-Controllers for in situ and automatic function control of solar thermal systems that were developed within the research

246

A Method of Decreasing Power Output Fluctuation of Solar Chimney Power Generating Systems  

Science Journals Connector (OSTI)

Severe fluctuation of power output is a common problem in the various generating systems of renewable energies. The hybrid energy storage system with water and soil is adopted to decrease the fluctuation of solar chimney power generating systems in the ... Keywords: Solar chimney power generating system, power output fluctuation, hybrid energy storage layer, collector, chimney

Meng Fanlong; Ming Tingzhen; Pan Yuan

2011-01-01T23:59:59.000Z

247

Optimizing the Output of a Human-Powered Energy Harvesting System with Miniaturization and Integrated Control  

E-Print Network (OSTI)

1 Optimizing the Output of a Human-Powered Energy Harvesting System with Miniaturization mechanical energy from human foot-strikes and explore its configuration and control towards optimized energy output. Dielectric Elastomers (DEs) are high-energy density, soft, rubber-like material

Potkonjak, Miodrag

248

Method for leveling the power output of an electromechanical battery as a function of speed  

DOE Patents (OSTI)

The invention is a method of leveling the power output of an electromechanical battery during its discharge, while at the same time maximizing its power output into a given load. The method employs the concept of series resonance, employing a capacitor the parameters of which are chosen optimally to achieve the desired near-flatness of power output over any chosen charged-discharged speed ratio. Capacitors are inserted in series with each phase of the windings to introduce capacitative reactances that act to compensate the inductive reactance of these windings. This compensating effect both increases the power that can be drawn from the generator before inductive voltage drops in the windings become dominant and acts to flatten the power output over a chosen speed range. The values of the capacitors are chosen so as to optimally flatten the output of the generator over the chosen speed range. 3 figs.

Post, R.F.

1999-03-16T23:59:59.000Z

249

Sinusoidal self-modulation in the output of a CO/sub 2/ laser with an intracavity saturable absorber  

SciTech Connect

Conditions under which a sinusoidally modulated laser output occurs in a CO/sub 2/ laser with a saturable absorber were studied experimentally and theoretically for a wide range of laser operating parameters. A novel type of transition between stability and instability appears in the high-pressure range of the saturable absorber. Through the rate-equation analysis based on the three-level (the gain medium): two-level (the loss medium) model, the observed pulse shapes and the features of transitions in the phase diagram are reproducible. The conditions of saturable absorbers to obtain the sinusoidal are clarified from the analysis.

Tanii, K.; Tachikawa, M.; Kajita, M.; Shimizu, T.

1988-01-01T23:59:59.000Z

250

Wind direction modelling using multiple observation points  

Science Journals Connector (OSTI)

...gains in the produced output power. chaos engineering|wind forecasting|multiple measurements...realized that the modelling of power output in wind turbines needs to be performed...region; in region 3, for high winds, the power output is subject to a threshold...

2008-01-01T23:59:59.000Z

251

Finding the quantum thermoelectric with maximal efficiency and minimal entropy production at given power output  

E-Print Network (OSTI)

We investigate the nonlinear scattering theory for quantum systems with strong Seebeck and Peltier effects, and consider their use as heat-engines and refrigerators with finite power outputs. This article gives detailed derivations of the results summarized in Phys. Rev. Lett. 112, 130601 (2014). It shows how to use the scattering theory to find (i) the quantum thermoelectric with maximum possible power output, and (ii) the quantum thermoelectric with maximum efficiency at given power output. The latter corresponds to a minimal entropy production at that power output. These quantities are of quantum origin since they depend on system size over electronic wavelength, and so have no analogue in classical thermodynamics. The maximal efficiency coincides with Carnot efficiency at zero power output, but decreases with increasing power output. This gives a fundamental lower bound on entropy production, which means that reversibility (in the thermodynamic sense) is impossible for finite power output. The suppression of efficiency by (nonlinear) phonon and photon effects is addressed in detail; when these effects are strong, maximum efficiency coincides with maximum power. Finally, we show in particular limits (typically without magnetic fields) that relaxation within the quantum system does not allow the system to exceed the bounds derived for relaxation-free systems, however a general proof of this remains elusive.

Robert S. Whitney

2015-01-28T23:59:59.000Z

252

X-ray source assembly having enhanced output stability, and fluid stream analysis applications thereof  

DOE Patents (OSTI)

An x-ray source assembly and method of operation are provided having enhanced output stability. The assembly includes an anode having a source spot upon which electrons impinge and a control system for controlling position of the anode source spot relative to an output structure. The control system can maintain the anode source spot location relative to the output structure notwithstanding a change in one or more operating conditions of the x-ray source assembly. One aspect of the disclosed invention is most amenable to the analysis of sulfur in petroleum-based fuels.

Radley, Ian (Glenmont, NY); Bievenue, Thomas J. (Delmar, NY); Burdett, John H. (Charlton, NY); Gallagher, Brian W. (Guilderland, NY); Shakshober, Stuart M. (Hudson, NY); Chen, Zewu (Schenectady, NY); Moore, Michael D. (Alplaus, NY)

2008-06-08T23:59:59.000Z

253

Optimization of the output and efficiency of a high power cascaded arc hydrogen plasma source  

SciTech Connect

The operation of a cascaded arc hydrogen plasma source was experimentally investigated to provide an empirical basis for the scaling of this source to higher plasma fluxes and efficiencies. The flux and efficiency were determined as a function of the input power, discharge channel diameter, and hydrogen gas flow rate. Measurements of the pressure in the arc channel show that the flow is well described by Poiseuille flow and that the effective heavy particle temperature is approximately 0.8 eV. Interpretation of the measured I-V data in terms of a one-parameter model shows that the plasma production is proportional to the input power, to the square root of the hydrogen flow rate, and is independent of the channel diameter. The observed scaling shows that the dominant power loss mechanism inside the arc channel is one that scales with the effective volume of the plasma in the discharge channel. Measurements on the plasma output with Thomson scattering confirm the linear dependence of the plasma production on the input power. Extrapolation of these results shows that (without a magnetic field) an improvement in the plasma production by a factor of 10 over where it was in van Rooij et al. [Appl. Phys. Lett. 90, 121501 (2007)] should be possible.

Vijvers, W. A. J.; Gils, C. A. J. van; Goedheer, W. J.; Meiden, H. J. van der; Veremiyenko, V. P.; Westerhout, J.; Lopes Cardozo, N. J.; Rooij, G. J. van [FOM-Institute for Plasma Physics Rijnhuizen, Association EURATOM-FOM, Trilateral Euregio Cluster, P.O. Box 1207, 3430 BE Nieuwegein (Netherlands); Schram, D. C. [Department of Applied Physics, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands)

2008-09-15T23:59:59.000Z

254

Primate Motor Cortex: Individual and Ensemble Neuron-Muscle Output Relationships  

E-Print Network (OSTI)

The specific aims of this study were to: 1) investigate the encoding of forelimb muscle activity timing and magnitude by corticomotoneuronal (CM) cells, 2) test the stability of primary motor cortex (M1) output to forelimb ...

Griffin, Darcy Michelle

2008-07-30T23:59:59.000Z

255

Augmentation of Power Output of Axisymmetric Ducted Wind Turbines by Porous Trailing Edge Disks  

E-Print Network (OSTI)

This paper presents analytical and experimental results that demonstrated that the power output from a ducted wind turbine can be dramatically increased by the addition of a trailing edge device such as a porous disk. In ...

widnall, sheila

2014-06-30T23:59:59.000Z

256

A Hardware Implementation of the Soft Output Viterbi Algorithm for Serially Concatenated Convolutional Codes  

E-Print Network (OSTI)

This thesis outlines the hardware design of a soft output Viterbi algorithm decoder for use in a serially concatenated convolutional code system. Convolutional codes and their related structures are described, as well as the algorithms used...

Werling, Brett William

2010-06-28T23:59:59.000Z

257

Code design for multiple-input multiple-output broadcast channels  

E-Print Network (OSTI)

Recent information theoretical results indicate that dirty-paper coding (DPC) achieves the entire capacity region of the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). This thesis presents practical code designs for Gaussian...

Uppal, Momin Ayub

2009-06-02T23:59:59.000Z

258

Power output enhancement of a vibration-driven electret generator for wireless sensor applications  

Science Journals Connector (OSTI)

We developed a compact vibration-driven electret generator that excelled at a power output. It succeeded in the operation of wireless sensor modules only on electricity from electret generators. This electret generator can supply enough power to operate a wireless sensor module without an external power source. It was necessary for enabling this operation to enhance the power output of the electret generator. We enhanced the power output by decreasing the parasitic capacitance. To decrease the parasitic capacitance, we fabricated a collector substrate using concave electrodes. We decreased it from 25 to 17 pF. As a result, the power output from our generator was enhanced from 40 to 100 ĶW considerably at an acceleration of 0.15 g (1.47 m s?2) and a resonance frequency of 30 Hz.

Tatsuakira Masaki; Kenji Sakurai; Toru Yokoyama; Masayo Ikuta; Hiroshi Sameshima; Masashi Doi; Tomonori Seki; Masatoshi Oba

2011-01-01T23:59:59.000Z

259

Variable-Speed Wind Generator System with Maximum Output Power Control  

Science Journals Connector (OSTI)

To achieve maximum output power from wind generator systems, the rotational speed of wind generators should be adjusted in real time according to natural wind speed. This chapter pays attention to an optimum rota...

Yoko Amano

2013-01-01T23:59:59.000Z

260

Total Pollution Effect and Total Energy Cost per Output of Different Products for Polish Industrial System  

Science Journals Connector (OSTI)

For many years a broad use has been made of the indices of total energy requirements in the whole large production system corresponding to unit output of particular goods (Boustead I., Hancock G.F., 1979). The...

Henryk W. Balandynowicz

1988-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Imprinting a complete information about a quantum channel on its output state  

E-Print Network (OSTI)

We introduce a novel property of bipartite quantum states, which we call "faithfulness", and we say that a state is faithful when acting with a channel on one of the two quantum systems, the output state carries a complete information about the channel. The concept of faithfulness can also be extended to sets of states, when the output states patched together carry a complete imprinting of the channel.

Giacomo Mauro D'Ariano; Paoloplacido Lo Presti

2002-11-20T23:59:59.000Z

262

Analytical Modeling Linking the FASTSim and ADOPT Software Tools  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Model Petroleum Impact Optimize for market share 6 Approach: Vehicle Powertrain Modeling Fuel Economy Inputs Vehicle Price Acceleration Outputs Component Sizes and Vehicle...

263

The effect of performance-based research funding on output of R&D results in the Czech Republic  

Science Journals Connector (OSTI)

We have studied the effects of performance-based research funding introduced to the Czech (CZ) R&D system in 2008 on outputs of R&D results. We have analyzed annual changes in number of various types of publications and applications including ... Keywords: Bibliometrics, Citation analysis, Patent output, Performance-based research funding, R&D results output

Jiri Vanecek

2014-01-01T23:59:59.000Z

264

Stochastic Model Output Statistics for Bias Correcting and Downscaling Precipitation Including Extremes  

Science Journals Connector (OSTI)

Precipitation is highly variable in space and time; hence, rain gauge time series generally exhibit additional random small-scale variability compared to area averages. Therefore, differences between daily precipitation statistics simulated by ...

Geraldine Wong; Douglas Maraun; Mathieu Vrac; Martin Widmann; Jonathan M. Eden; Thomas Kent

2014-09-01T23:59:59.000Z

265

Distributed quantitative precipitation forecasts combining information from radar and numerical weather prediction model outputs  

E-Print Network (OSTI)

Applications of distributed Quantitative Precipitation Forecasts (QPF) range from flood forecasting to transportation. Obtaining QPF is acknowledged to be one of the most challenging areas in hydrology and meteorology. ...

Ganguly, Auroop Ratan

2002-01-01T23:59:59.000Z

266

Statistical post-processing of High-Resolution Regional Climate Model Output  

Science Journals Connector (OSTI)

Statistical post-processing techniques have become essential tools for downscaling large scale information to the point scale, and also for providing a better probabilistic characterization of hydrometeorological variables in simulation and ...

Pablo A. Mendoza; Balaji Rajagopalan; Martyn P. Clark; Kyoko Ikeda; Roy Rasmussen

267

Sensitivity of Carbon Anode Baking Model Outputs to Kinetic Parameters Describing Pitch Pyrolysis  

Science Journals Connector (OSTI)

During the preheating, they will release volatiles (H2, CH4, tar) that will burn in the flue. ... The combustion of volatiles accounts for approximately 40Ė50% of the required heating, the rest being provided by natural gas; see burner ramps on Figure 1. ... Figure 2. Schematic representation of the pit and the flue wall. ...

FranÁois Grťgoire; Louis Gosselin; Houshang Alamdari

2013-02-20T23:59:59.000Z

268

Multiregional InputĖOutput Model for the Evaluation of Spanish Water Flows  

Science Journals Connector (OSTI)

Halfway through the first decade of the 21st century water withdrawals in Spain have been slightly less than 40 km3 per year (own estimations from ref 2), being around 60% abstracted by agriculture, 14.5% by the water distribution sector (distributed to industries and households), 16% by the energy and gas sectors, and 4% by industries. ... We also relate these water flows and demands with the regional water availability, in order to offer insights on the Spanish water stress, defined as volume of water consumed/availability per capita. ... Total WF to GDP ratio (SI Table SI2) is on average higher for Spain than for EU and lower than for the RW (the opposite for the last ratios of WF per capita). ...

Ignacio Cazcarro; Rosa Duarte; Julio SŠnchez Chůliz

2013-09-12T23:59:59.000Z

269

Dissemination of Climate Model Output to the Public and Commercial Sector  

SciTech Connect

Climate is defined by the Glossary of Meteorology as the mean of atmospheric variables over a period of time ranging from as short as a few months to multiple years and longer. Although the term climate is often used to refer to long-term weather statistics, the broader definition of climate is the time evolution of a system consisting of the atmosphere, hydrosphere, lithosphere, and biosphere. Physical, chemical, and biological processes are involved in interactions among the components of the climate system. Vegetation, soil moisture, and glaciers are part of the climate system in addition to the usually considered temperature and precipitation (Pielke, 2008). Climate change refers to any systematic change in the long-term statistics of climate elements (such as temperature, pressure, or winds) sustained over several decades or longer. Climate change can be initiated by external forces, such as cyclical variations in the Earth's solar orbit that are thought to have caused glacial and interglacial periods within the last 2 million years (Milankovitch, 1941). However, a linear response to astronomical forcing does not explain many other observed glacial and interglacial cycles (Petit et al., 1999). It is now understood that climate is influenced by the interaction of solar radiation with atmospheric greenhouse gasses (e.g., carbon dioxide, chlorofluorocarbons, methane, nitrous oxide, etc.), aerosols (airborne particles), and Earth's surface. A significant aspect of climate are the interannual cycles, such as the El Nino La Nina cycle which profoundly affects the weather in North America but is outside the scope of weather forecasts. Some of the most significant advances in understanding climate change have evolved from the recognition of the influence of ocean circulations upon the atmosphere (IPCC, 2007). Human activity can affect the climate system through increasing concentrations of atmospheric greenhouse gases, air pollution, increasing concentrations of aerosol, and land alteration. A particular concern is that atmospheric levels of CO{sub 2} may be rising faster than at any time in Earth's history, except possibly following rare events like impacts from large extraterrestrial objects (AMS, 2007). Atmospheric CO{sub 2} concentrations have increased since the mid-1700s through fossil fuel burning and changes in land use, with more than 80% of this increase occurring since 1900. The increased levels of CO{sub 2} will remain in the atmosphere for hundreds to thousands of years. The complexity of the climate system makes it difficult to predict specific aspects of human-induced climate change, such as exactly how and where changes will occur, and their magnitude. The Intergovernmental Panel for Climate Change (IPCC) was established by World Meteorological Organization (WMO) and the United Nations in 1988. The IPCC was tasked with assessing the scientific, technical and socioeconomic information needed to understand the risk of human-induced climate change, its observed and projected impacts, and options for adaptation and mitigation. The IPCC concluded in its Fourth Assessment Report (AR4) that warming of the climate system is unequivocal, and that most of the observed increase in globally averaged temperatures since the mid-20th century is very likely due to the observed increased in anthropogenic greenhouse gas concentrations (IPCC, 2007).

Robert Stockwell, PhD

2010-09-23T23:59:59.000Z

270

Scaling analyses of forcings and outputs of a simplified Last1 Millennium climate model2  

E-Print Network (OSTI)

its responses with those of multiproxies and the NASA GISS-ER2 GCM. 22 became too weak at 27 longer scales. At small scales, the GISS ER2

Lovejoy, Shaun

271

Economic impacts and challenges of Chinaís petroleum industry: An inputĖoutput analysis  

Science Journals Connector (OSTI)

It is generally acknowledged that the petroleum industry plays an important role in Chinaís national economic and social development. The direct, indirect, and induced impacts of Chinaís petroleum industry are analyzed in this study by using the InputĖOutput approach. The study also considers the main challenges that Chinaís economy might face in the future. The research results suggest the following: (1) The total economic impacts coefficients on output, given each unit of final demands change in extraction of petroleum and processing of petroleum, are 1.9180 and 3.2747 respectively, and the corresponding economic impacts coefficients on GDP are 1.0872 and 0.9001 respectively; (2) Extraction of petroleum has a more direct impact on GDP, while processing of petroleum has a greater effect on the total output; (3) Extraction of petroleumís total economic impacts coefficients on both output and GDP have remained stable in recent years after a period of long decline; processing of petroleumís total economic impacts coefficient on output is steadily increasing; (4) Import uncertainty, the likelihood of rising oil prices, and net oil exports caused by items manufactured with petroleum products (i.e. ďMade in ChinaĒ goods) are the main challenges the petroleum industry will cause for Chinaís overall economy.

Tang Xu; Zhang Baosheng; Feng Lianyong; Marwan Masri; Afshin Honarvar

2011-01-01T23:59:59.000Z

272

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

4. Existing Capacity by Producer Type, 2012 (Megawatts) 4. Existing Capacity by Producer Type, 2012 (Megawatts) Producer Type Number of Generators Generator Nameplate Capacity Net Summer Capacity Net Winter Capacity Electric Power Sector Electric Utilities 9,624 680,592 621,785 644,358 Independent Power Producers, Non-Combined Heat and Power Plants 6,148 412,045 374,964 389,349 Independent Power Producers, Combined Heat and Power Plants 609 39,916 35,266 38,023 Total 16,381 1,132,554 1,032,015 1,071,729 Commercial and Industrial Sectors Commercial Sector 962 3,610 3,223 3,349 Industrial Sector 1,680 31,832 27,795 29,381 Total 2,642 35,442 31,018 32,730 All Sectors Total 19,023 1,167,995 1,063,033 1,104,459 Notes: In 2011, EIA corrected the NAICS codes of several plants which resulted in a net capacity shift from the electric utility sector to the commercial sector.

273

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. U.S. Transformer Sustained Automatic Outage Counts B. U.S. Transformer Sustained Automatic Outage Counts and Hours by High-Voltage Size and NERC Region, 2012 Sustained Automatic Outage Counts High-Side Voltage (kV) Eastern Interconnection TRE WECC Contiguous U.S. 100-199 -- -- -- -- 200-299 -- -- 1.00 1.00 300-399 2.00 -- 4.00 6.00 400-599 14.00 -- 11.00 25.00 600+ -- -- -- -- Grand Total 16.00 -- 16.00 32.00 Sustained Automatic Outage Hours High-Side Voltage (kV) Eastern Interconnection TRE WECC Contiguous U.S. 100-199 -- -- -- -- 200-299 -- -- 27.58 27.58 300-399 153.25 -- 15.87 169.12 400-599 3,070.88 -- 258.37 3,329.25 600+ -- -- -- -- Grand Total 3,224.13 -- 301.82 3,525.95 Outage Hours per Outage Incident Eastern Interconnection TRE WECC Contiguous U.S.

274

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

6. Coal Consumption at Commercial and Institutional Users by Census Division and State" 6. Coal Consumption at Commercial and Institutional Users by Census Division and State" "(thousand short tons)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "Middle Atlantic",20,52,24,73,83,-12.4 " Pennsylvania",20,52,24,73,83,-12.4 "East North Central",112,197,127,309,331,-6.8 " Illinois",34,45,29,79,66,18.9 " Indiana","w","w","w","w","w","w" " Michigan","w","w","w","w","w","w"

275

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Number of Employees at Underground and Surface Mines by State and Mine Production Range, 2012" Number of Employees at Underground and Surface Mines by State and Mine Production Range, 2012" ,"Mine Production Range (thousand short tons)" "Coal-Producing State, Region1","Above 1,000","Above 500","Above 200","Above 100","Above 50","Above 10","Above 0","Zero2","Total Number" "and Mine Type",,"to 1,000","to 500","to 200","to 100","to 50","to 10",,"of Employees" "Alabama",3415,97,655,317,160,224,54,105,5041 " Underground",2981,"-","-","-",36,88,"-",81,3190 " Surface",434,97,655,317,124,136,54,24,1851

276

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

8. Average Sales Price of Coal by State and Mine Type, 2012 and 2011" 8. Average Sales Price of Coal by State and Mine Type, 2012 and 2011" "(dollars per short ton)" ,2012,,,2011,,,"Percent Change" "Coal-Producing","Underground","Surface","Total","Underground","Surface","Total","Underground","Surface","Total" "State" "Alabama",107.73,104.51,106.57,100.17,108.71,102.69,7.6,-3.9,3.8 "Alaska","-","w","w","-","w","w","-","w","w" "Arizona","-","w","w","-","w","w","-","w","w" "Arkansas","w","-","w","w","-","w","w","-","w"

277

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Underground Coal Production by State and Mining Method, 2012" Underground Coal Production by State and Mining Method, 2012" "(thousand short tons)" "Coal-Producing State and Region1","Continuous2","Conventional and","Longwall4","Total" ,,"Other3" "Alabama",139,20,12410,12570 "Arkansas",96,"-","-",96 "Colorado",757,"-",22889,23646 "Illinois",18969,"-",23868,42837 "Indiana",15565,"-","-",15565 "Kentucky Total",56179,2018,"-",58198 " Kentucky (East)",22090,2010,"-",24100 " Kentucky (West)",34089,9,"-",34098 "Maryland",797,"-","-",797 "Montana","-","-",5708,5708

278

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Coal Mining Productivity by State, Mine Type, and Union Status, 2012" Coal Mining Productivity by State, Mine Type, and Union Status, 2012" "(short tons produced per employee hour)" ,"Union",,"Nonunion" "Coal-Producing State and Region1","Underground","Surface","Underground","Surface" "Alabama",1.69,"-",0.66,1.8 "Alaska","-",5.98,"-","-" "Arizona","-",7.38,"-","-" "Arkansas","-","-",0.59,"-" "Colorado",4.9,6.09,6.02,4.45 "Illinois",2.09,"-",5.34,4.7 "Indiana","-","-",3.23,5.41 "Kentucky Total",3.02,2.45,2.36,3.06 " Kentucky (East)","-",2.45,1.64,2.65

279

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Average Sales Price of U.S. Coal by State and Disposition, 2012" Average Sales Price of U.S. Coal by State and Disposition, 2012" "(dollars per short ton)" "Coal-Producing State","Open Market1","Captive2","Total3" "Alabama",85.06,"-",106.57 "Alaska","w","-","w" "Arizona","w","-","w" "Arkansas","w","-","w" "Colorado",38.51,43.19,37.54 "Illinois",49.04,54.71,53.08 "Indiana",49.16,54.5,52.01 "Kentucky Total",61.85,73.08,63.12 " Kentucky (East)",75.8,73.08,75.62 " Kentucky (West)",48.6,"-",48.67 "Louisiana","w","-","w"

280

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

5. Emissions from Energy Consumption at 5. Emissions from Energy Consumption at Conventional Power Plants and Combined-Heat-and-Power Plants, by State, 2011 and 2012 (Thousand Metric Tons) Census Division and State Carbon Dioxide (CO2) Sulfur Dioxide (SO2) Nitrogen Oxides (NOx) Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 34,766 37,698 33 58 39 37 Connecticut 8,987 8,196 7 1 12 6 Maine 3,722 4,351 8 12 7 8 Massachusetts 14,346 16,404 15 22 14 14 New Hampshire 4,295 5,127 2 23 4 5 Rhode Island 3,403 3,595 0.03 0.07 2 3 Vermont 12 24 0.05 0.09 1 1 Middle Atlantic 161,786 171,603 275 370 187 203 New Jersey 16,120 16,917 4 5 14 13 New York 35,669 37,256 31 52 40 43 Pennsylvania 109,997 117,430 240 313 133 147

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281

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Recoverable Coal Reserves and Average Recovery Percentage at Producing Mines by State, 2012 and 2011" Recoverable Coal Reserves and Average Recovery Percentage at Producing Mines by State, 2012 and 2011" "(million short tons)" ,2012,,2011 "Coal-Producing","Recoverable Coal","Average Recovery","Recoverable Coal","Average Recovery","Percent Change" "State","Reserves","Percentage","Reserves","Percentage","Recoverable Coal" ,,,,,"Reserves" "Alabama",265,53.63,306,55.39,-13.2 "Alaska","w","w","w","w","w" "Arizona","w","w","w","w","w" "Arkansas","w","w","w","w","w"

282

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

7. Average Retail Price of Electricity to Ultimate Customers: 7. Average Retail Price of Electricity to Ultimate Customers: Total by End-Use Sector, 2003 - December 2012 (Cents per Kilowatthour) Period Residential Commercial Industrial Transportation All Sectors Annual Totals 2003 8.72 8.03 5.11 7.54 7.44 2004 8.95 8.17 5.25 7.18 7.61 2005 9.45 8.67 5.73 8.57 8.14 2006 10.40 9.46 6.16 9.54 8.90 2007 10.65 9.65 6.39 9.70 9.13 2008 11.26 10.36 6.83 10.74 9.74 2009 11.51 10.17 6.81 10.65 9.82 2010 11.54 10.19 6.77 10.57 9.83 2011 11.72 10.23 6.82 10.46 9.90 2012 11.88 10.09 6.67 10.21 9.84 2010 January 10.49 9.55 6.50 10.17 9.28 February 10.89 9.89 6.55 10.48 9.47 March 11.11 9.95 6.53 10.28 9.48 April 11.71 9.95 6.55 10.52 9.53 May 11.91 10.15 6.64 10.52 9.72

283

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

1. Stocks of Coal, Petroleum Liquids, and Petroleum Coke: Electric Power Sector, 2002 - 2012 1. Stocks of Coal, Petroleum Liquids, and Petroleum Coke: Electric Power Sector, 2002 - 2012 Electric Power Sector Electric Utilities Independent Power Producers Period Coal (Thousand Tons) Petroluem Liquids (Thousand Barrels) Petroleum Coke (Thousand Tons) Coal (Thousand Tons) Petroluem Liquids (Thousand Barrels) Petroleum Coke (Thousand Tons) Coal (Thousand Tons) Petroluem Liquids (Thousand Barrels) Petroleum Coke (Thousand Tons) End of Year Stocks 2002 141,714 43,935 1,711 116,952 29,601 328 24,761 14,334 1,383 2003 121,567 45,752 1,484 97,831 28,062 378 23,736 17,691 1,105 2004 106,669 46,750 937 84,917 29,144 627 21,751 17,607 309 2005 101,137 47,414 530 77,457 29,532 374 23,680 17,882 156 2006 140,964 48,216 674 110,277 29,799 456 30,688 18,416 217

284

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. U.S. Transmission Circuit Sustained Automatic Outage Counts and Hours A. U.S. Transmission Circuit Sustained Automatic Outage Counts and Hours by High-Voltage Size and NERC Region, 2012 Sustained Automatic Outage Counts Voltage Region Type Operating (kV) FRCC MRO NPCC RFC SERC SPP TRE WECC Contiguous U.S. AC 200-299 142 49 14 141 242 49 -- 484 1,121 AC 300-399 -- 88 107 95 46 56 80 165 637 AC 400-599 9 3 -- 22 86 -- -- 125 245 AC 600+ -- -- 6 9 -- -- -- -- 15 AC Total 151 140 127 267 374 105 80 774 2,018 DC 100-199 -- -- -- -- -- -- -- -- -- DC 200-299 -- 18 -- -- -- -- -- 5 23 DC 300-399 -- -- -- -- -- -- -- -- -- DC 400-499 -- 5 -- -- -- -- -- -- 5 DC 500-599 -- -- -- 5 -- -- -- 17 22 DC 600+ -- -- -- -- -- -- -- -- --

285

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Sales Price of Coal by State and Underground Mining Method, 2012" Sales Price of Coal by State and Underground Mining Method, 2012" "(dollars per short ton)" "Coal-Producing State","Continuous1","Conventional and","Longwall3","Total" ,,"Other2" "Alabama","w","-","w",107.73 "Arkansas","w","-","-","w" "Colorado","w","-",37.18,"w" "Illinois",48.08,"-",59.51,54.18 "Indiana",52.94,"-","-",52.94 "Kentucky Total","w","w","-",62.24 " Kentucky (East)","w","w","-",79.23 " Kentucky (West)",50.18,"-","-",50.18

286

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Steam Coal Exports by Customs District" Steam Coal Exports by Customs District" "(short tons)" ,,,,"Year to Date" "Customs District","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "Eastern Total",4951041,5566950,6554494,10517991,11407664,-7.8 " Baltimore, MD",1275530,831976,1715016,2107506,2852092,-26.1 " Boston, MA",7,"-",12,7,24,-70.8 " Buffalo, NY",1180,1516,2826,2696,5257,-48.7 " New York City, NY",3088,2664,2168,5752,6106,-5.8 " Norfolk, VA",3578715,4697769,4760354,8276484,8443756,-2 " Ogdensburg, NY",36894,3610,3090,40504,6838,492.3 " Philadelphia, PA",55513,29255,34241,84768,56733,49.4

287

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

and Number of Mines by State, County, and Mine Type, 2012" and Number of Mines by State, County, and Mine Type, 2012" "(thousand short tons)" ,"Underground",,"Surface",,"Total" "Coal-Producing","Number of Mines","Production","Number of Mines","Production","Number of Mines","Production" "State and County" "Alabama",8,12570,38,6752,46,19321 " Bibb","-","-",2,119,2,119 " Blount","-","-",2,236,2,236 " Fayette",1,2249,"-","-",1,2249 " Franklin","-","-",2,137,2,137 " Jackson","-","-",3,152,3,152 " Jefferson",3,3589,9,1106,12,4695

288

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Average Tested Heat Rates by Prime Mover and Energy Source, 2007 - 2012 2. Average Tested Heat Rates by Prime Mover and Energy Source, 2007 - 2012 (Btu per Kilowatthour) Prime Mover Coal Petroluem Natural Gas Nuclear 2007 Steam Generator 10,158 10,398 10,440 10,489 Gas Turbine -- 13,217 11,632 -- Internal Combustion -- 10,447 10,175 -- Combined Cycle W 10,970 7,577 -- 2008 Steam Generator 10,138 10,356 10,377 10,452 Gas Turbine -- 13,311 11,576 -- Internal Combustion -- 10,427 9,975 -- Combined Cycle W 10,985 7,642 -- 2009 Steam Generator 10,150 10,349 10,427 10,459 Gas Turbine -- 13,326 11,560 -- Internal Combustion -- 10,428 9,958 -- Combined Cycle W 10,715 7,605 -- 2010 Steam Generator 10,142 10,249 10,416 10,452 Gas Turbine -- 13,386 11,590 -- Internal Combustion -- 10,429 9,917 --

289

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

0. Receipts, Average Cost, and Quality of Fossil Fuels: Commerical Sector, 2002 - 2012 (continued) 0. Receipts, Average Cost, and Quality of Fossil Fuels: Commerical Sector, 2002 - 2012 (continued) Petroleum Coke Natural Gas All Fossil Fuels Receipts Average Cost Receipts Average Cost Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMbtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Mcf) (Dollars per MMBtu) (Dollars per Mcf) Percentage of Consumption (Dollars per MMBtu) Annual Totals 2002 0 0 -- -- -- -- 18,671 18,256 3.44 3.52 24.7 3.03 2003 0 0 -- -- -- 0.0 18,169 17,827 4.96 5.06 30.5 4.02 2004 0 0 -- -- -- 0.0 16,176 15,804 5.93 6.07 21.9 4.58 2005 0 0 -- -- -- 0.0 17,600 17,142 8.38 8.60 25.2 6.25 2006 0 0 -- -- -- 0.0 21,369 20,819 8.33 8.55 30.7 6.42

290

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3.A. Net Generation by Energy Source: Independent Power Producers, 2002 - 2012 3.A. Net Generation by Energy Source: Independent Power Producers, 2002 - 2012 (Thousand Megawatthours) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Nuclear Hydroelectric Conventional Renewable Sources Excluding Hydroelectric Hydroelectric Pumped Storage Other Total Annual Totals 2002 395,943 22,241 8,368 378,044 1,763 272,684 18,189 44,466 -1,309 8,612 1,149,001 2003 452,433 35,818 7,949 380,337 2,404 304,904 21,890 46,060 -1,003 8,088 1,258,879 2004 443,547 33,574 7,410 427,510 3,194 312,846 19,518 48,636 -962 7,856 1,303,129 2005 507,199 37,096 9,664 445,625 3,767 345,690 21,486 51,708 -1,174 6,285 1,427,346 2006 498,316 10,396 8,409 452,329 4,223 361,877 24,390 59,345 -1,277 6,412 1,424,421

291

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

9. Consumption of Coal for Electricity Generation by State by Sector, 9. Consumption of Coal for Electricity Generation by State by Sector, 2012 and 2011 (Thousand Tons) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 1,787 2,998 -40% 520 898 1,257 2,087 0 0 10 12 Connecticut 297 317 -6.5% 0 0 297 317 0 0 0 0 Maine 11 14 -18% 0 0 6 7 0 0 5 6 Massachusetts 959 1,769 -46% 0 0 954 1,763 0 0 5 6 New Hampshire 520 898 -42% 520 898 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0 Middle Atlantic 44,000 53,658 -18% 6 16 43,734 53,052 4 1 256 589

292

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

4. Average Retail Price of Electricity to Ultimate Customers 4. Average Retail Price of Electricity to Ultimate Customers by End-Use Sector 2002 through 2012 (Cents per kilowatthour) Year Residential Commercial Industrial Transportation Other Total Total Electric Industry 2002 8.44 7.89 4.88 N/A 6.75 7.20 2003 8.72 8.03 5.11 7.54 N/A 7.44 2004 8.95 8.17 5.25 7.18 N/A 7.61 2005 9.45 8.67 5.73 8.57 N/A 8.14 2006 10.40 9.46 6.16 9.54 N/A 8.90 2007 10.65 9.65 6.39 9.70 N/A 9.13 2008 11.26 10.36 6.83 10.74 N/A 9.74 2009 11.51 10.17 6.81 10.65 N/A 9.82 2010 11.54 10.19 6.77 10.57 N/A 9.83 2011 11.72 10.23 6.82 10.46 N/A 9.90 2012 11.88 10.09 6.67 10.21 N/A 9.84 Full-Service Providers 2002 8.40 7.77 4.78 N/A 6.65 7.13 2003 8.68 7.89 5.01 6.82 N/A 7.38

293

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Average Price of U.S. Steam Coal Exports" Average Price of U.S. Steam Coal Exports" "(dollars per short ton)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",65.1,63.67,73.81,64.48,78.9,-18.3 " Canada*",59.34,55.22,63.02,57.57,73.63,-21.8 " Dominican Republic",78.47,74.41,73.89,75.4,76.61,-1.6 " Honduras","-",54.58,54.43,54.58,54.43,0.3 " Jamaica",480,54.43,"-",54.72,55.42,-1.3 " Mexico",69.42,73.33,82.64,70.83,86.44,-18.1 " Other**",80.33,389.3,70.37,82.45,76.1,8.3

294

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Coal Production by Coalbed Thickness and Mine Type, 2012" Coal Production by Coalbed Thickness and Mine Type, 2012" "(thousand short tons)" "Coal Thickness (inches)","Underground","Surface","Total" "Under 7","-",17,17 "7 - Under 13","-",2108,2108 "13 - Under 19",429,6688,7117 "19 - Under 25",111,14107,14217 "25 - Under 31",4147,12913,17060 "31 - Under 37",15128,19022,34150 "37 - Under 43",23868,17285,41153 "43 - Under 49",26035,15597,41632 "49 - Under 55",18909,22544,41453 "55 - Under 61",36946,11285,48231 "61 - Under 67",43146,15074,58220 "67 - Under 73",40983,8783,49766 "73 - Under 79",32914,10193,43107 "79 - Under 85",27011,3554,30565

295

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Carbon Dioxide Uncontrolled Emission Factors 3. Carbon Dioxide Uncontrolled Emission Factors Fuel EIA Fuel Code Source and Tables (As Appropriate) Factor (Pounds of CO2 Per Million Btu)*** Bituminous Coal BIT Source: 1 205.30000 Distillate Fuel Oil DFO Source: 1 161.38600 Geothermal GEO Estimate from EIA, Office of Integrated Analysis and Forecasting 16.59983 Jet Fuel JF Source: 1 156.25800 Kerosene KER Source: 1 159.53500 Lignite Coal LIG Source: 1 215.40000 Municipal Solid Waste MSW Source: 1 (including footnote 2 within source) 91.90000 Natural Gas NG Source: 1 117.08000 Petroleum Coke PC Source: 1 225.13000 Propane Gas PG Sources: 1 139.17800 Residual Fuel Oil RFO Source: 1 173.90600 Synthetic Coal SC Assumed to have the emissions similar to Bituminous Coal. 205.30000

296

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Coal Imports by Customs District" Coal Imports by Customs District" "(short tons)" ,,,,"Year to Date" "Customs District","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "Eastern Total",469878,331008,156004,800886,350124,128.7 " Baltimore, MD","-","-",106118,"-",154318,"-" " Boston, MA",373985,154438,"-",528423,51185,"NM" " Buffalo, NY",44,"-","-",44,"-","-" " New York City, NY",1373,1402,487,2775,507,447.3 " Norfolk, VA","-",68891,"-",68891,35856,92.1 " Ogdensburg, NY","-",1,12,1,12,-91.7

297

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

U.S. Coke Exports" U.S. Coke Exports" "(short tons)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",162796,79217,201795,242013,340944,-29 " Canada*",73859,17837,112348,91696,161596,-43.3 " Mexico",88535,60517,86721,149052,176163,-15.4 " Other**",402,863,2726,1265,3185,-60.3 "South America Total",223,217,591,440,1158,-62 " Other**",223,217,591,440,1158,-62 "Europe Total",48972,59197,"-",108169,6,"NM" " Other**",347,11743,"-",12090,"-","-"

298

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

7. U.S. Coal Stocks, 2007 - 2013" 7. U.S. Coal Stocks, 2007 - 2013" "(thousand short tons)" ,"Coal Consumers" "Last Day of Quarter","Electric","Coke","Other","Commercial","Total","Coal Producers","Total" ,"Power","Plants","Industrial2","and",,"and" ,"Sector1",,,"Institutional Users",,"Distributors" 2007 " March 31",141389,2444,5756,"-",149588,34007,183595 " June 30",154812,2364,5672,"-",162849,32484,195333 " September 30",142666,1972,5811,"-",150448,30090,180538 " December 31",151221,1936,5624,"-",158781,33977,192758

299

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

5. Unit of Measure Equivalents 5. Unit of Measure Equivalents Unit Equivalent Kilowatt (kW) 1,000 (One Thousand) Watts Megawatt (MW) 1,000,000 (One Million) Watts Gigawatt (GW) 1,000,000,000 (One Billion) Watts Terawatt (TW) 1,000,000,000,000 (One Trillion) Watts Gigawatt 1,000,000 (One Million) Kilowatts Thousand Gigawatts 1,000,000,000 (One Billion) Kilowatts Kilowatthours (kWh) 1,000 (One Thousand) Watthours Megawatthours (MWh) 1,000,000 (One Million) Watthours Gigawatthours (GWh) 1,000,000,000 (One Billion) Watthours Terawatthours (TWh) 1,000,000,000,000 (One Trillion) Watthours Gigawatthours 1,000,000 (One Million) Kilowatthours Thousand Gigawatthours 1,000,000,000(One Billion Kilowatthours U.S. Dollar 1,000 (One Thousand) Mills U.S. Cent 10 (Ten) Mills Barrel of Oil 42 Gallons

300

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

6. Receipts, Average Cost, and Quality of Fossil Fuels: Electric Utilities, 2002 - 2012 (continued) 6. Receipts, Average Cost, and Quality of Fossil Fuels: Electric Utilities, 2002 - 2012 (continued) Petroleum Coke Natural Gas All Fossil Fuels Receipts Average Cost Receipts Average Cost Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMbtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Mcf) (Dollars per MMBtu) (Dollars per Mcf) Percentage of Consumption (Dollars per MMBtu) Annual Totals 2002 75,711 2,677 0.63 17.68 4.98 126.0 1,680,518 1,634,734 3.68 3.78 72.3 1.53 2003 89,618 3,165 0.74 20.94 5.51 124.0 1,486,088 1,439,513 5.59 5.77 81.6 1.74 2004 107,985 3,817 0.89 25.15 5.10 92.0 1,542,746 1,499,933 6.15 6.33 82.9 1.87 2005 102,450 3,632 1.29 36.31 5.16 87.9 1,835,221 1,780,721 8.32 8.57 83.4 2.38

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2 Stocks of Coal, Petroleum Liquids, and Petroleum Coke: 2 Stocks of Coal, Petroleum Liquids, and Petroleum Coke: Electric Power Sector, by State, 2012 and 2011 Census Division and State Coal (Thousand Tons) Petroleum Liquids (Thousand Barrels) Petroleum Coke (Thousand Tons) December 2012 December 2011 Percentage Change December 2012 December 2011 Percentage Change December 2012 December 2011 Percentage Change New England 1,030 1,389 -26% 2,483 2,680 -7.3% 0 0 -- Connecticut W W W 1,300 954 36% 0 0 -- Maine 0 0 -- W W W 0 0 -- Massachusetts W 675 W 837 990 -15% 0 0 -- New Hampshire W W W W W W 0 0 -- Rhode Island 0 0 -- W W W 0 0 -- Vermont 0 0 -- 51 49 3.0% 0 0 -- Middle Atlantic 7,553 7,800 -3.2% 5,496 6,591 -17% W W W New Jersey 926 871 6.3% 1,084 1,113 -2.6% 0 0 --

302

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

0. Coal Receipts at Commercial and Institutional Users by Census Division and State" 0. Coal Receipts at Commercial and Institutional Users by Census Division and State" "(thousand short tons)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "Middle Atlantic",25,54,32,79,90,-12 " Pennsylvania",25,54,32,79,90,-12 "East North Central",115,183,117,298,301,-0.9 " Illinois",31,42,28,73,67,8.1 " Indiana","w","w","w","w","w","w" " Michigan","w","w","w","w","w","w"

303

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Coal Receipts at Other Industrial Plants by Census Division and State" Coal Receipts at Other Industrial Plants by Census Division and State" "(thousand short tons)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "New England","w","w","w","w","w","w" " Maine","w","w","w","w","w","w" " Massachusetts","w","w","w","w","w","w" "Middle Atlantic",627,587,637,1214,1254,-3.1 " New York",214,178,194,392,377,4

304

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Major U.S. Coal Mines, 2012" Major U.S. Coal Mines, 2012" "Rank","Mine Name / Company","Mine Type","State","Production (short tons)" 1,"North Antelope Rochelle Mine / Peabody Powder River Mining Ll","Surface","Wyoming",107639188 2,"Black Thunder / Thunder Basin Coal Company Llc","Surface","Wyoming",93082919 3,"Cordero Mine / Cordero Mining Llc","Surface","Wyoming",39204736 4,"Antelope Coal Mine / Antelope Coal Llc","Surface","Wyoming",34316314 5,"Belle Ayr Mine / Alpha Coal West, Inc.","Surface","Wyoming",24227846 6,"Eagle Butte Mine / Alpha Coal West, Inc.","Surface","Wyoming",22466733

305

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

D. Petroleum Liquids: Consumption for Electricity Generation, D. Petroleum Liquids: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 835,481 553,390 241,892 3,953 36,243 2003 1,089,307 658,868 380,378 5,358 44,702 2004 1,031,954 651,712 350,093 4,544 25,606 2005 1,035,045 618,811 387,355 3,469 25,410 2006 459,392 335,130 105,312 1,963 16,987 2007 512,423 355,999 139,977 1,505 14,942 2008 332,367 242,379 79,816 957 9,215 2009 266,508 196,346 59,277 1,101 9,784 2010 244,114 188,987 49,042 970 5,115 2011 163,954 125,755 33,166 801 4,233 2012 134,956 105,179 24,081 1,618 4,078 2010 January 33,737 26,715 6,282 100 639

306

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

9. Total Capacity of Distributed and Dispersed Generators by Technology Type, 9. Total Capacity of Distributed and Dispersed Generators by Technology Type, 2005 through 2012 Capacity (MW) Year Internal Combustion Combustion Turbine Steam Turbine Hydro Wind Photovoltaic Storage Other Wind and Other Total Number of Generators Distributed Generators 2005 4,025.0 1,917.0 1,830.0 999.0 -- -- -- -- 995.0 9,766.0 17,371 2006 3,646.0 1,298.0 2,582.0 806.0 -- -- -- -- 1,081.0 9,411.0 5,044 2007 4,624.0 1,990.0 3,596.0 1,051.0 -- -- -- -- 1,441.0 12,702.0 7,103 2008 5,112.0 1,949.0 3,060.0 1,154.0 -- -- -- -- 1,588.0 12,863.0 9,591 2009 4,339.0 4,147.0 4,621.0 1,166.0 -- -- -- -- 1,729.0 16,002.0 13,006 2010 886.8 186.0 109.9 97.4 98.9 236.3 -- 372.7 -- 1,988.0 15,630

307

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

D. Wood / Wood Waste Biomass: Consumption for Electricity Generation, D. Wood / Wood Waste Biomass: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 605,054 10,659 129,947 469 463,980 2003 519,294 16,545 139,852 437 362,460 2004 344,134 19,973 130,248 168 193,745 2005 355,250 27,373 138,407 207 189,263 2006 350,074 27,455 135,546 269 186,803 2007 353,025 31,568 132,953 284 188,220 2008 338,786 29,150 130,122 287 179,227 2009 320,444 29,565 130,894 274 159,712 2010 349,530 40,167 137,072 274 172,016 2011 347,623 35,474 130,108 482 181,559 2012 390,342 32,723 138,217 478 218,924 2010 January 29,578 3,731 11,954 23 13,870

308

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

U.S. Coal Exports and Imports, 2007 - 2013" U.S. Coal Exports and Imports, 2007 - 2013" "(thousand short tons)" ,"January - March",,"April - June",,"July - September",,"October - December",,"Total" "Year","Exports","Imports","Exports","Imports","Exports","Imports","Exports","Imports","Exports","Imports" 2007,11139,8786,14702,8405,16198,10559,17124,8597,59163,36347 2008,15802,7640,23069,8982,20321,8485,22329,9101,81519,34208 2009,13335,6325,12951,5426,15159,5441,17653,5447,59097,22639 2010,17807,4803,21965,5058,21074,4680,20870,4811,81716,19353 2011,26617,3381,26987,3419,25976,3588,27679,2700,107259,13088 2012,28642,2022,37534,2329,31563,2415,28006,2394,125746,9159

309

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

1. Consumption of Petroleum Coke for Electricity Generation by State, by Sector, 1. Consumption of Petroleum Coke for Electricity Generation by State, by Sector, 2012 and 2011 (Thousand Tons) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 0 0 -- 0 0 0 0 0 0 0 0 Connecticut 0 0 -- 0 0 0 0 0 0 0 0 Maine 0 0 -- 0 0 0 0 0 0 0 0 Massachusetts 0 0 -- 0 0 0 0 0 0 0 0 New Hampshire 0 0 -- 0 0 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0 Middle Atlantic 56 121 -54% 0 0 0 94 0 0 56 27

310

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Nitrogen Oxides Uncontrolled Emission Factors 2. Nitrogen Oxides Uncontrolled Emission Factors Fuel, Code, Source and Emission Units Combustion System Type / Firing Configuration Cyclone Boiler Fluidized Bed Boiler Opposed Firing Boiler Spreader Stoker Boiler Fuel EIA Fuel Code Source and Tables (As Appropriate) Emissions Units Lbs = Pounds MMCF = Million Cubic Feet MG = Thousand Gallons Dry-Bottom Boilers Dry-Bottom Boilers Dry-Bottom Boilers Wet-Bottom Boilers Dry-Bottom Boilers Agricultural Byproducts AB Source: 1 Lbs per ton 1.20 1.20 1.20 N/A 1.20 Blast Furnace Gas BFG Sources: 1 (including footnote 7 within source); EIA estimates Lbs per MMCF 15.40 15.40 15.40 N/A 15.40 Bituminous Coal BIT Source: 2, Table 1.1-3 Lbs per ton 33.00 5.00 12.00 31.00 11.00 Black Liquor BLQ Source: 1 Lbs per ton ** 1.50 1.50 1.50 N/A 1.50

311

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2.1. Number of Ultimate Customers Served by Sector, by Provider, 2.1. Number of Ultimate Customers Served by Sector, by Provider, 2002 through 2012 Year Residential Commercial Industrial Transportation Other Total Total Electric Industry 2002 116,622,037 15,333,700 601,744 N/A 1,066,554 133,624,035 2003 117,280,481 16,549,519 713,221 1,127 N/A 134,544,348 2004 118,763,768 16,606,783 747,600 1,025 N/A 136,119,176 2005 120,760,839 16,871,940 733,862 518 N/A 138,367,159 2006 122,471,071 17,172,499 759,604 791 N/A 140,403,965 2007 123,949,916 17,377,219 793,767 750 N/A 142,121,652 2008 124,937,469 17,562,726 774,713 727 N/A 143,275,635 2009 125,177,175 17,561,661 757,519 705 N/A 143,497,060 2010 125,717,935 17,674,338 747,746 239 N/A 144,140,258 2011 126,143,072 17,638,062 727,920 92 N/A 144,509,146

312

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Average Price of U.S. Coke Exports" Average Price of U.S. Coke Exports" "(dollars per short ton)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",240.59,241.38,218.4,240.85,225.8,6.7 " Canada*",147.49,330.47,243.04,183.08,286.56,-36.1 " Mexico",316.57,211.63,189.12,273.97,171.71,59.6 " Other**",612.42,485.63,134.48,525.92,135.04,289.5 "South America Total",140.65,156.15,322.7,148.29,250.36,-40.8 " Other**",140.65,156.15,322.7,148.29,250.36,-40.8 "Europe Total",259.26,255.24,"-",257.06,427.83,-39.9

313

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Demand-Side Management Program Annual Effects by Program 2. Demand-Side Management Program Annual Effects by Program Category, by Sector, 2002 through 2012 Year Residential Commercial Industrial Transportation Total Energy Efficiency - Energy Savings (Thousand MWh) 2002 15,284 24,803 10,242 -- 50,328 2003 12,914 24,758 10,031 551 48,254 2004 17,185 24,290 11,137 50 52,663 2005 18,894 28,073 11,986 47 59,000 2006 21,150 28,720 13,155 50 63,076 2007 22,772 30,359 14,038 108 67,278 2008 25,396 34,634 14,766 75 74,871 2009 27,395 34,831 14,610 76 76,912 2010 32,150 37,416 17,259 89 86,914 2011 46,790 50,732 23,061 76 120,659 2012 54,516 58,894 25,023 92 138,525 Energy Efficiency - Actual Peak Load Reduction (MW) 2002 5,300 5,389 2,768 -- 13,457 2003 5,909 4,911 2,671 94 13,585

314

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Net Generation by Energy Source: Total (All Sectors), 2002 - 2012 A. Net Generation by Energy Source: Total (All Sectors), 2002 - 2012 (Thousand Megawatthours) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Nuclear Hydroelectric Conventional Renewable Sources Excluding Hydroelectric Hydroelectric Pumped Storage Other Total Annual Totals 2002 1,933,130 78,701 15,867 691,006 11,463 780,064 264,329 79,109 -8,743 13,527 3,858,452 2003 1,973,737 102,734 16,672 649,908 15,600 763,733 275,806 79,487 -8,535 14,045 3,883,185 2004 1,978,301 100,391 20,754 710,100 15,252 788,528 268,417 83,067 -8,488 14,232 3,970,555 2005 2,012,873 99,840 22,385 760,960 13,464 781,986 270,321 87,329 -6,558 12,821 4,055,423 2006 1,990,511 44,460 19,706 816,441 14,177 787,219 289,246 96,525 -6,558 12,974 4,064,702

315

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

8. Retail Sales of Electricity to Ultimate Customers by End-Use Sector, 8. Retail Sales of Electricity to Ultimate Customers by End-Use Sector, by State, 2012 and 2011 (Million Kilowatthours) Residential Commercial Industrial Transportation All Sectors Census Division and State Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 47,208 47,481 44,864 45,018 27,818 27,927 566 569 120,456 120,995 Connecticut 12,758 12,919 12,976 13,087 3,566 3,668 193 185 29,492 29,859 Maine 4,481 4,382 4,053 4,018 3,027 3,016 0 0 11,561 11,415 Massachusetts 20,313 20,473 17,723 17,767 16,927 16,974 350 357 55,313 55,570 New Hampshire 4,439 4,454 4,478 4,478 1,953 1,936 0 0 10,870 10,869 Rhode Island 3,121 3,129 3,640 3,660 923 916 24 27 7,708 7,732

316

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

C. Net Summer Capacity of Utility Scale Units Using Primarily Fossil Fuels and by State, 2012 and 2011 (Megawatts) C. Net Summer Capacity of Utility Scale Units Using Primarily Fossil Fuels and by State, 2012 and 2011 (Megawatts) Census Division and State Natural Gas Fired Combined Cycle Natural Gas Fired Combustion Turbine Other Natural Gas Coal Petroleum Coke Petroleum Liquids Other Gases Total Fossil Fuels Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 12,190.5 11,593.8 1,090.0 1,058.9 876.4 830.1 2,546.1 2,755.5 0.0 0.0 7,916.1 7,915.3 0.0 0.0 24,619.1 24,153.6 Connecticut 2,513.4 2,447.7 458.1 432.7 61.0 44.7 389.1 564.4 0.0 0.0 3,186.1 3,185.0 0.0 0.0 6,607.7 6,674.5 Maine 1,250.0 1,250.0 306.0 302.2 119.0 93.0 85.0 85.0 0.0 0.0 1,004.9 1,007.2 0.0 0.0 2,764.9 2,737.4

317

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

0. U.S. Coal Stocks at Manufacturing Plants by North American Industry Classification System (NAICS) Code" 0. U.S. Coal Stocks at Manufacturing Plants by North American Industry Classification System (NAICS) Code" "(thousand short tons)" "NAICS Code","June 30 2013","March 31 2013","June 30 2012","Percent Change" ,,,,"(June 30)" ,,,,"2013 versus 2012" "311 Food Manufacturing",875,926,1015,-13.9 "312 Beverage and Tobacco Product Mfg.",26,17,19,35.8 "313 Textile Mills",22,22,25,-13.9 "315 Apparel Manufacturing","w","w","w","w" "321 Wood Product Manufacturing","w","w","w","w" "322 Paper Manufacturing",570,583,743,-23.3 "324 Petroleum and Coal Products*",127,113,156,-18.7

318

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Recoverable Coal Reserves and Average Recovery Percentage at Producing U.S. Mines by Mine Production Range and Mine Type, 2012" Recoverable Coal Reserves and Average Recovery Percentage at Producing U.S. Mines by Mine Production Range and Mine Type, 2012" "(million short tons)" ,"Underground",,"Surface",,"Total" "Mine Production Range","Recoverable Coal","Average Recovery","Recoverable Coal","Average Recovery","Recoverable Coal","Average Recovery" "(thousand short tons)","Reserves","Percentage","Reserves","Percentage","Reserves","Percentage" "Over 1,000",4874,57.96,11153,91.28,16028,81.15 "Over 500 to 1,000",531,47.14,226,81.9,757,57.49 "Over 200 to 500",604,52.72,333,69.16,938,58.57

319

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

4. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: 4. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: Commercial Sector by State, 2012 Bituminous Subbituminous Lignite Census Division and State Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight New England 0 -- -- 0 -- -- 0 -- -- Connecticut 0 -- -- 0 -- -- 0 -- -- Maine 0 -- -- 0 -- -- 0 -- -- Massachusetts 0 -- -- 0 -- -- 0 -- -- New Hampshire 0 -- -- 0 -- -- 0 -- -- Rhode Island 0 -- -- 0 -- -- 0 -- -- Vermont 0 -- -- 0 -- -- 0 -- -- Middle Atlantic 0 -- -- 0 -- -- 0 -- --

320

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

8. Average Cost of Petroleum Liquids Delivered for Electricity Generation by State, 2012 and 2011 8. Average Cost of Petroleum Liquids Delivered for Electricity Generation by State, 2012 and 2011 (Dollars per MMBtu) Census Division and State Electric Power Sector Electric Utilities Independent Power Producers Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 New England 18.64 W W 21.43 21.12 18.47 W Connecticut W 21.91 W 23.87 NM W 21.93 Maine W W W -- NM W W Massachusetts 17.17 19.76 -13% 17.45 NM 17.16 19.66 New Hampshire 23.23 W W 23.23 19.90 -- W Rhode Island -- W W -- NM -- W Vermont 24.11 NM NM 24.11 NM -- -- Middle Atlantic W 20.15 W 21.01 19.21 W 20.66 New Jersey 19.77 18.36 7.7% -- NM 19.77 20.28 New York W 19.66 W 21.01 20.00 W 19.36 Pennsylvania 21.84 22.19 -1.6% -- NM 21.84 22.19

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Productive Capacity of Coal Mines by State, 2012 and 2011" Productive Capacity of Coal Mines by State, 2012 and 2011" "(thousand short tons)" ,2012,,,2011,,,"Percent Change" "Coal-Producing","Underground","Surface","Total","Underground","Surface","Total","Underground","Surface","Total" "State" "Alabama",14594,7967,22561,16102,8911,25013,-9.4,-10.6,-9.8 "Alaska","-","w","w","-","w","w","-","w","w" "Arizona","-","w","w","-","w","w","-","w","w" "Arkansas","w","-","w","w","-","w","w","-","w"

322

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Quantity and Average Price of U.S. Coal Imports by Origin, 2007 - 2013" Quantity and Average Price of U.S. Coal Imports by Origin, 2007 - 2013" "(thousand short tons and dollars per short ton)" "Year and Quarter","Australia","Canada","Colombia","Indonesia","China","Venezuela","Other","Total" ,,,,,,,"Countries" 2007,66,1967,26864,3663,50,3425,311,36347 2008,149,2027,26262,3374,45,2312,39,34208 2009,152,1288,17787,2084,9,1297,21,22639 2010,380,1767,14584,1904,53,582,83,19353 2011,62,1680,9500,856,22,779,188,13088 2012 " January - March","-",260,1594,59,7,80,22,2022 " April - June","-",281,1728,49,21,170,80,2329 " July - September","-",297,1762,266,39,"-",51,2415

323

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Average Sales Price of Coal by State, County, and Number of Mines, 2012" Average Sales Price of Coal by State, County, and Number of Mines, 2012" "Coal-Producing State and County","Number of Mines","Sales","Average Sales Price" ,,"(thousand short tons)","(dollars per short ton)" "Alabama",39,19021,106.57 " Bibb",1,"w","w" " Blount",2,"w","w" " Fayette",1,"w","w" " Franklin",1,"w","w" " Jackson",2,"w","w" " Jefferson",11,4298,146.04 " Marion",1,"w","w" " Tuscaloosa",7,8599,111.55 " Walker",11,2370,81.88

324

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Coal Stocks at Commercial and Institutional Users by Census Division and State" 2. Coal Stocks at Commercial and Institutional Users by Census Division and State" "(thousand short tons)" "Census Division","June 30 2013","March 31 2013","June 30 2012","Percent Change" "and State",,,,"(June 30)" ,,,,"2013 versus 2012" "Middle Atlantic",62,58,56,10.9 " Pennsylvania",62,58,56,10.9 "East North Central",168,171,197,-14.7 " Illinois","w","w","w","w" " Indiana",75,76,75,0.5 " Michigan","w","w","w","w" " Ohio",25,15,19,27 " Wisconsin",5,5,3,59.1 "West North Central",66,75,97,-32.2

325

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Summary Statistics for Coal Refining Plants, 2012 - 2013" 3. Summary Statistics for Coal Refining Plants, 2012 - 2013" "(thousand short tons)" "Year and","Coal Receipts","Average Price of Coal Receipts","Coal Used","Coal Stocks1" "Quarter",,"(dollars per short ton)" 2012 " January - March",2151,27.47,1756,771 " April - June",3844,25.42,3688,825 " July - September",5399,24.32,5286,812 " October - December",4919,24.55,4680,787 " Total",16313,25.06,15410 2013 " January - March",5067,24.6,4989,793 " April - June",4015,25.24,3754,756 " Total",9082,24.88,8744 "1 Reported as of the last day of the quarter." "Note: Average price is based on the cost, insurance, and freight (c.i.f. value). Total may not equal sum of components because of independent rounding."

326

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Proposed Transmission Capacity Additions by High-Voltage Size, 2013 - 2019 B. Proposed Transmission Capacity Additions by High-Voltage Size, 2013 - 2019 (Circuit Miles of Transmission) Voltage Circuit Miles Type Operating (kV) Year 2013 Year 2014 Year 2015 Year 2016 Year 2017 Year 2018 Year 2019 All Years AC 100-199 954 1,222 992 1,047 392 382 176 5,165 AC 200-299 1,003 792 1,398 319 539 427 118 4,596 AC 300-399 4,779 839 1,532 1,527 502 1,650 349 11,178 AC 400-599 399 708 669 643 660 1,151 334 4,564 AC 600+ -- -- 14 -- -- 69 -- 83 AC Total 7,134 3,562 4,606 3,536 2,092 3,679 978 25,586 DC 100-199 2 11 5 -- -- 7 -- 25 DC 200-299 -- -- -- -- -- -- -- -- DC 300-399 -- -- -- -- 333 -- -- 333 DC 400-599 -- -- 10 -- -- -- -- 10 DC 600+ -- -- -- -- -- -- -- --

327

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Revenue and Expense Statistics for Major U.S. Investor-Owned Electric Utilities, 2002 through 2012 (Million Dollars) 3. Revenue and Expense Statistics for Major U.S. Investor-Owned Electric Utilities, 2002 through 2012 (Million Dollars) Description 2002 2003 2004 2005 2006 2007 Utility Operating Revenues 219,609 230,151 238,759 265,652 275,501 270,964 ......Electric Utility 200,360 206,268 213,012 234,909 246,736 240,864 ......Other Utility 19,250 23,883 25,747 30,743 28,765 30,100 Utility Operating Expenses 189,062 201,057 206,960 236,786 245,589 241,198 ......Electric Utility 171,604 179,044 183,121 207,830 218,445 213,076 ............Operation 116,660 125,436 131,560 150,645 158,893 153,885 ..................Production 90,715 98,305 103,871 120,586 127,494 121,700 ........................Cost of Fuel 24,149 26,871 28,544 36,106 37,945 39,548

328

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

U.S. Coke Imports" U.S. Coke Imports" "(short tons)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Origin",2013,2013,2012,,,"Change" "North America Total",10284,2293,159462,12577,183712,-93.2 " Canada",3009,2293,159462,5302,183712,-97.1 " Panama",7275,"-","-",7275,"-","-" "South America Total",25267,13030,88424,38297,106612,-64.1 " Brazil","-","-",78595,"-",78595,"-" " Colombia",25267,13030,9829,38297,28017,36.7 "Europe Total",6044,40281,165027,46325,485791,-90.5

329

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Coal Production and Coalbed Thickness by Major Coalbeds and Mine Type, 2012" Coal Production and Coalbed Thickness by Major Coalbeds and Mine Type, 2012" ,"Production (thousand short tons)",,,"Thickness (inches)" "Coalbed ID Number1","Underground","Surface","Total","Average2","Low","High" "Coalbed Name" "1699 Wyodak","-",351188,351188,778,160,913 "0036 Pittsburgh",52476,3871,56348,74,18,138 "0489 No. 9",42193,12181,54374,61,24,74 "0484 Herrin (Illinois No. 6)",48526,1910,50436,71,46,89 "0212 Pittsburgh",27355,76,27431,75,27,98 "1701 Smith","-",23847,23847,822,745,912 "1696 Anderson-Dietz 1-Dietz 2","-",18992,18992,932,660,960

330

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

0. Average Retail Price of Electricity to Ultimate Customers by End-Use Sector, 0. Average Retail Price of Electricity to Ultimate Customers by End-Use Sector, by State, 2012 and 2011 (Cents per Kilowatthour) Residential Commercial Industrial Transportation All Sectors Census Division and State Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 15.71 15.89 13.68 14.31 11.83 12.55 6.68 7.85 14.02 14.49 Connecticut 17.34 18.11 14.65 15.57 12.67 13.24 9.69 10.25 15.54 16.35 Maine 14.66 15.38 11.53 12.29 7.98 8.88 -- -- 11.81 12.58 Massachusetts 14.91 14.67 13.84 14.33 12.57 13.38 4.91 6.14 13.79 14.11 New Hampshire 16.07 16.52 13.36 14.04 11.83 12.27 -- -- 14.19 14.74 Rhode Island 14.40 14.33 11.87 12.37 10.68 11.27 8.28 14.11 12.74 13.04

331

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Revenue from Retail Sales of Electricity to Ultimate Customers 3. Revenue from Retail Sales of Electricity to Ultimate Customers by Sector, by Provider, 2002 through 2012 (Million Dollars) Year Residential Commercial Industrial Transportation Other Total Total Electric Industry 2002 106,834 87,117 48,336 N/A 7,124 249,411 2003 111,249 96,263 51,741 514 N/A 259,767 2004 115,577 100,546 53,477 519 N/A 270,119 2005 128,393 110,522 58,445 643 N/A 298,003 2006 140,582 122,914 62,308 702 N/A 326,506 2007 148,295 128,903 65,712 792 N/A 343,703 2008 155,433 138,469 68,920 827 N/A 363,650 2009 157,008 132,940 62,504 828 N/A 353,280 2010 166,782 135,559 65,750 815 N/A 368,906 2011 166,714 135,926 67,606 803 N/A 371,049 2012 163,280 133,898 65,761 747 N/A 363,687

332

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

U.S. Metallurgical Coal Exports" U.S. Metallurgical Coal Exports" "(short tons)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",1503162,764701,1411897,2267863,2261900,0.3 " Canada*",975783,343309,1260473,1319092,1895263,-30.4 " Dominican Republic",94,51064,"-",51158,"-","-" " Mexico",527285,370328,151424,897613,366637,144.8 "South America Total",2091488,2561772,2389018,4653260,4543747,2.4 " Argentina",104745,155806,203569,260551,253841,2.6 " Brazil",1921144,2352098,2185449,4273242,4022618,6.2

333

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

1. Average Price of Coal Receipts at Commercial and Institutional Users by Census Division and State" 1. Average Price of Coal Receipts at Commercial and Institutional Users by Census Division and State" "(dollars per short ton)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "Middle Atlantic",139.64,145,158.61,143.29,158.91,-9.8 " Pennsylvania",139.64,145,158.61,143.29,158.91,-9.8 "East North Central",87.62,97.3,87.11,93.56,95.13,-1.7 " Illinois",59.27,60.3,62.17,59.86,66.69,-10.2 " Indiana","w","w","w","w","w","w" " Michigan","w","w","w","w","w","w"

334

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Average Price of Coal Receipts at Other Industrial Plants by Census Division and State" Average Price of Coal Receipts at Other Industrial Plants by Census Division and State" "(dollars per short ton)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "New England","w","w","w","w","w","w" " Maine","w","w","w","w","w","w" " Massachusetts","w","w","w","w","w","w" "Middle Atlantic",87.05,93.03,93.73,89.93,95.68,-6 " New York",102.14,105.8,117.15,103.8,117.61,-11.7

335

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

8. Coal Stocks at Coke Plants by Census Division" 8. Coal Stocks at Coke Plants by Census Division" "(thousand short tons)" "Census Division","June 30 2013","March 31 2013","June 30 2012","Percent Change" ,,,,"(June 30)" ,,,,"2013 versus 2012" "Middle Atlantic","w","w","w","w" "East North Central",1313,1177,1326,-1 "South Atlantic","w","w","w","w" "East South Central","w","w","w","w" "U.S. Total",2500,2207,2295,8.9 "w = Data withheld to avoid disclosure." "Note: Total may not equal sum of components because of independent rounding."

336

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

7 Receipts, Average Cost, and Quality of Fossil Fuels: Independent Power Producers, 2002 - 2012 7 Receipts, Average Cost, and Quality of Fossil Fuels: Independent Power Producers, 2002 - 2012 Coal Petroleum Liquids Receipts Average Cost Receipts Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMBtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Barrels) (Dollars per MMBtu) (Dollars per Barrel) Average Sulfur Percent by Weight Percentage of Consumption Annual Totals 2002 3,710,847 182,482 1.37 27.96 1.15 87.0 186,271 30,043 4.19 25.98 0.61 76.4 2003 4,365,996 223,984 1.34 26.20 1.15 90.4 347,546 56,138 5.41 33.50 0.58 89.7 2004 4,410,775 227,700 1.41 27.27 1.13 93.3 337,011 54,152 5.35 33.31 0.61 93.6 2005 4,459,333 229,071 1.56 30.39 1.10 83.0 381,871 61,753 8.30 51.34 0.54 97.2

337

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Metallurgical Coal Exports by Customs District" Metallurgical Coal Exports by Customs District" "(short tons)" ,,,,"Year to Date" "Customs District","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "Eastern Total",11716074,14136513,15167377,25852587,27578514,-6.3 " Baltimore, MD",2736470,4225450,5123600,6961920,9037970,-23 " Boston, MA","-","-","-","-",28873,"-" " Buffalo, NY",247714,121347,524040,369061,725698,-49.1 " Norfolk, VA",8730257,9784866,9519119,18515123,17784479,4.1 " Ogdensburg, NY",1633,4850,618,6483,1494,333.9 "Southern Total",3551564,3824484,4264938,7376048,8976503,-17.8

338

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3 Stocks of Coal, Petroleum Liquids, and Petroleum Coke: 3 Stocks of Coal, Petroleum Liquids, and Petroleum Coke: Electric Power Sector, by Census Divison, 2012 and 2011 Electric Power Sector Electric Utilities Independent Power Producers Census Division December 2012 December 2011 Percentage Change December 2012 December 2011 December 2012 December 2011 Coal (Thousand Tons) New England 1,030 1,389 -25.9% W W W W Middle Atlantic 7,553 7,800 -3.2% W W W W East North Central 36,139 37,262 -3.0% 27,069 27,316 9,070 9,946 West North Central 30,554 28,544 7.0% 30,554 28,544 0 0 South Atlantic 38,859 36,920 5.3% 35,527 33,163 3,331 3,757 East South Central 19,657 17,185 14.4% 19,657 17,185 0 0 West South Central 28,807 22,910 25.7% 17,047 15,125 11,760 7,785

339

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

D. Coal: Consumption for Electricity Generation, D. Coal: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 19,996,890 15,517,857 4,215,043 9,168 254,821 2003 20,366,879 15,391,188 4,745,545 13,080 217,066 2004 20,375,751 15,610,335 4,606,584 8,251 150,581 2005 20,801,716 15,397,688 5,250,824 8,314 144,889 2006 20,527,410 15,211,077 5,166,001 7,526 142,807 2007 20,841,871 15,436,110 5,287,202 7,833 110,727 2008 20,548,610 15,189,050 5,242,194 8,070 109,296 2009 18,240,611 13,744,178 4,390,596 7,007 98,829 2010 19,196,315 14,333,496 4,709,686 6,815 146,318 2011 18,074,298 13,551,416 4,399,144 7,263 116,475

340

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Net Generation by Energy Source: Electric Utilities, 2002 - 2012 A. Net Generation by Energy Source: Electric Utilities, 2002 - 2012 (Thousand Megawatthours) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Nuclear Hydroelectric Conventional Renewable Sources Excluding Hydroelectric Hydroelectric Pumped Storage Other Total Annual Totals 2002 1,514,670 52,838 6,286 229,639 206 507,380 242,302 3,089 -7,434 480 2,549,457 2003 1,500,281 62,774 7,156 186,967 243 458,829 249,622 3,421 -7,532 519 2,462,281 2004 1,513,641 62,196 11,498 199,662 374 475,682 245,546 3,692 -7,526 467 2,505,231 2005 1,484,855 58,572 11,150 238,204 10 436,296 245,553 4,945 -5,383 643 2,474,846 2006 1,471,421 31,269 9,634 282,088 30 425,341 261,864 6,588 -5,281 700 2,483,656

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341

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

10.6. Advanced Metering Count by Technology Type, 10.6. Advanced Metering Count by Technology Type, 2007 through 2012 Year Residential Commercial Industrial Transportation Total Automated Meter Reading (AMR) 2007 25,785,782 2,322,329 44,015 109 28,152,235 2008 36,425,943 3,529,985 77,122 13 40,033,063 2009 41,462,111 4,239,531 107,033 11 45,808,686 2010 43,913,225 4,611,877 159,315 626 48,685,043 2011 41,451,888 4,341,105 172,692 77 45,965,762 2012 43,455,437 4,691,018 185,862 125 48,330,822 Advanced Metering Infrastructure (AMI) 2007 2,202,222 262,159 9,106 2 2,473,489 2008 4,190,244 444,003 12,757 12 4,647,016 2009 8,712,297 876,419 22,675 10 9,611,401 2010 18,369,908 1,904,983 59,567 67 20,334,525 2011 33,453,548 3,682,159 154,659 7 37,290,373

342

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

0. Net Metering Customers and Capacity by Technology Type, by End Use Sector, 0. Net Metering Customers and Capacity by Technology Type, by End Use Sector, 2003 through 2012 Capacity (MW) Customers Year Residential Commercial Industrial Transportation Total Residential Commercial Industrial Transportation Total Historical Data 2003 N/A N/A N/A N/A N/A 5,870 775 168 -- 6,813 2004 N/A N/A N/A N/A N/A 14,114 1,494 215 3 15,826 2005 N/A N/A N/A N/A N/A 19,244 1,565 337 -- 21,146 2006 N/A N/A N/A N/A N/A 30,689 2,553 376 -- 33,618 2007 N/A N/A N/A N/A N/A 44,450 3,513 391 -- 48,354 2008 N/A N/A N/A N/A N/A 64,400 5,305 304 -- 70,009 2009 N/A N/A N/A N/A N/A 88,205 7,365 919 -- 96,489 Photovoltaic 2010 697.890 517.861 243.051 -- 1,458.802 137,618 11,897 1,225 -- 150,740

343

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Summary Statistics for the United States, 2002 - 2012 2. Summary Statistics for the United States, 2002 - 2012 (From Table 2.1.) Number of Ultimate Customers Year Residential Commercial Industrial Transportation Other Total 2002 116,622,037 15,333,700 601,744 N/A 1,066,554 133,624,035 2003 117,280,481 16,549,519 713,221 1,127 N/A 134,544,348 2004 118,763,768 16,606,783 747,600 1,025 N/A 136,119,176 2005 120,760,839 16,871,940 733,862 518 N/A 138,367,159 2006 122,471,071 17,172,499 759,604 791 N/A 140,403,965 2007 123,949,916 17,377,219 793,767 750 N/A 142,121,652 2008 124,937,469 17,562,726 774,713 727 N/A 143,275,635 2009 125,177,175 17,561,661 757,519 705 N/A 143,497,060 2010 125,717,935 17,674,338 747,746 239 N/A 144,140,258 2011 126,143,072 17,638,062 727,920 92 N/A 144,509,146

344

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Coal Disposition by State, 2012" Coal Disposition by State, 2012" "(thousand short tons)" "Coal-Producing State","Open Market Sales1","Captive Sales / Transactions2","Exports3","Total" "Alabama",8688,"-",10333,19021 "Alaska","w","-",968,"w" "Arizona","w","-","-","w" "Arkansas","w","-","-","w" "Colorado",20836,4552,3468,28856 "Illinois",29252,5113,12341,46705 "Indiana",17127,18404,375,35906 "Kentucky Total",76602,6884,5668,89154 " Kentucky (East)",37324,6884,3588,47796 " Kentucky (West)",39277,"-",2081,41358

345

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Natural Gas: Consumption for Electricity Generation, A. Natural Gas: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Million Cubic Feet) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 6,126,062 2,259,684 3,148,595 32,545 685,239 2003 5,616,135 1,763,764 3,145,485 38,480 668,407 2004 5,674,580 1,809,443 3,265,896 32,839 566,401 2005 6,036,370 2,134,859 3,349,921 33,785 517,805 2006 6,461,615 2,478,396 3,412,826 34,623 535,770 2007 7,089,342 2,736,418 3,765,194 34,087 553,643 2008 6,895,843 2,730,134 3,612,197 33,403 520,109 2009 7,121,069 2,911,279 3,655,712 34,279 519,799 2010 7,680,185 3,290,993 3,794,423 39,462 555,307 2011 7,883,865 3,446,087 3,819,107 47,170 571,501

346

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Consumption of Nautral Gas for Electricity Generation by State, by Sector, 2. Consumption of Nautral Gas for Electricity Generation by State, by Sector, 2012 and 2011 (Million Cubic Feet) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 460,887 461,590 -0.2% 3,652 4,218 428,781 432,350 8,630 6,287 19,824 18,735 Connecticut 120,380 110,546 8.9% 69 730 113,620 105,965 3,952 2,061 2,739 1,790 Maine 44,424 49,352 -10% 0 0 28,456 33,555 307 12 15,662 15,785 Massachusetts 184,330 190,063 -3.0% 2,792 2,393 176,497 182,865 3,749 3,761 1,293 1,045 New Hampshire 50,678 46,927 8.0% 754 1,046 49,655 45,765 139 0 131 115

347

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

D. Other Waste Biomass: Consumption for Electricity Generation, D. Other Waste Biomass: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 34,775 2,456 15,859 4,566 11,894 2004 19,215 2,014 9,240 4,308 3,654 2005 17,852 2,485 7,365 4,677 3,325 2006 17,727 2,611 7,788 4,436 2,893 2007 19,083 2,992 8,861 4,049 3,181 2008 24,288 3,409 12,745 3,684 4,450 2009 24,847 3,679 13,231 3,760 4,177 2010 29,996 3,668 14,449 3,790 8,090 2011 30,771 4,488 16,115 3,816 6,352 2012 30,342 4,191 15,740 4,016 6,395 2010 January 2,223 189 1,078 321 635 February 2,336 275 1,208 291 561 March 2,287 311 1,079 302 594

348

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

1. U.S. Coal Summary Statistics, 2007 - 2013" 1. U.S. Coal Summary Statistics, 2007 - 2013" "(thousand short tons)" "Year and","Production1","Imports","Waste Coal","Producer and","Consumption","Exports","Consumer","Losses and" "Quarter",,,"Supplied","Distributor",,,"Stocks2","Unaccounted" ,,,,"Stocks2",,,,"For3" 2007 " January - March",286041,8786,3264,34007,278727,11139,149588 " April - June",285687,8405,3387,32484,267106,14702,162849 " July - September",286035,10559,3697,30090,303665,16198,150448 " October - December",288872,8597,3727,33977,278500,17124,158781 " Total",1146635,36347,14076,,1127998,59163,,4085

349

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

1. Receipts, Average Cost, and Quality of Fossil Fuels: Industrial Sector, 2002 - 2012 1. Receipts, Average Cost, and Quality of Fossil Fuels: Industrial Sector, 2002 - 2012 Coal Petroleum Liquids Receipts Average Cost Receipts Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMBtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Barrels) (Dollars per MMBtu) (Dollars per Barrel) Average Sulfur Percent by Weight Percentage of Consumption Annual Totals 2002 294,234 13,659 1.45 31.29 1.56 52.1 29,137 4,638 3.55 22.33 1.24 26.5 2003 322,547 15,076 1.45 31.01 1.37 60.7 27,538 4,624 4.85 28.86 1.25 23.2 2004 326,495 15,324 1.63 34.79 1.43 57.6 25,491 4,107 4.98 30.93 1.38 18.5 2005 339,968 16,011 1.94 41.17 1.42 61.9 36,383 5,876 6.64 41.13 1.36 26.4

350

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: Electric Utilties by State, 2012 2. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: Electric Utilties by State, 2012 Bituminous Subbituminous Lignite Census Division and State Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight New England 353 2.20 7.7 0 -- -- 0 -- -- Connecticut 0 -- -- 0 -- -- 0 -- -- Maine 0 -- -- 0 -- -- 0 -- -- Massachusetts 0 -- -- 0 -- -- 0 -- -- New Hampshire 353 2.20 7.7 0 -- -- 0 -- -- Rhode Island 0 -- -- 0 -- -- 0 -- -- Vermont 0 -- -- 0 -- -- 0 -- --

351

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Productive Capacity and Capacity Utilization of Underground Coal Mines by State and Mining Method, 2012" Productive Capacity and Capacity Utilization of Underground Coal Mines by State and Mining Method, 2012" "(thousand short tons)" ,"Continuous1",,"Conventional and Other2",,"Longwall3",,"Total" "Coal-Producing","Productive","Capacity","Productive","Capacity","Productive","Capacity","Productive","Capacity" "State","Capacity","Utilization","Capacity","Utilization","Capacity","Utilization","Capacity","Utilization" ,,"Percent",,"Percent",,"Percent",,"Percent" "Alabama","w","w","-","-","w","w",14594,85.99

352

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

6. Receipts of Natural Gas Delivered for Electricity Generation by State, 2012 and 2011 6. Receipts of Natural Gas Delivered for Electricity Generation by State, 2012 and 2011 (Million Cubic Feet) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 440,421 484,260 -9.1% 3,652 4,226 419,062 434,504 3,636 13,156 14,072 32,373 Connecticut 112,084 116,563 -3.8% 71 738 112,012 107,121 0 3,210 0 5,494 Maine 42,374 56,230 -25% 0 0 28,302 33,578 0 NM 14,072 22,639 Massachusetts 175,314 198,295 -12% 2,789 2,393 168,890 184,156 3,636 7,872 0 3,875 New Hampshire 50,408 47,137 6.9% 754 1,046 49,655 45,725 0 0 0 NM

353

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. U.S. Transmission Circuit Sustained Automatic Outage Counts and Hours by Cause Code and by NERC Region, 2012 A. U.S. Transmission Circuit Sustained Automatic Outage Counts and Hours by Cause Code and by NERC Region, 2012 AC & DC Circuit Outage Counts Sustained Outage Causes FRCC MRO NPCC RFC SERC SPP TRE WECC Contiguous U.S. Weather, excluding lightning 6.00 27.00 3.00 30.00 63.00 12.00 -- 69.00 210.00 Lightning 5.00 10.00 8.00 5.00 31.00 16.00 13.00 57.00 145.00 Environmental -- 1.00 1.00 5.00 -- 1.00 -- -- 8.00 Contamination 14.00 -- -- -- 22.00 3.00 6.00 7.00 52.00 Foreign Interference 34.00 3.00 -- 4.00 13.00 1.00 2.00 14.00 71.00 Fire -- 2.00 -- 1.00 6.00 3.00 1.00 85.00 98.00 Vandalism, Terrorism, or Malicious Acts -- -- -- -- 2.00 -- -- 1.00 3.00 Failed AC Substation Equipment 18.00 16.00 35.00 63.00 57.00 16.00 15.00 65.00 285.00

354

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Winter Net Internal Demand, Capacity Resources, and Capacity Margins B. Winter Net Internal Demand, Capacity Resources, and Capacity Margins by North American Electric Reliability Corporation Assessment Area, 2012 Actual, 2013-2017 Projected Net Internal Demand (Megawatts) -- Winter Eastern Interconnection ERCOT Western Interconnection All Interconnections Period FRCC NPCC Balance of Eastern Region MAPP MISO PJM SERC SPP TRE WECC Contiguous U.S. Actual 2012 / 2013 36,409 45,545 386,359 4,925 74,430 122,566 149,359 35,079 46,909 101,706 616,927 Projected 2013 / 2014 43,384 46,008 399,149 5,385 75,320 132,229 145,657 40,558 51,435 107,341 647,317 Projected 2014 / 2015 44,060 46,090 403,883 5,500 76,252 134,742 146,130 41,259 53,742 109,418 657,192 Projected 2015 / 2016 44,596 46,184 408,927 5,563 77,058 137,338 147,201 41,767 55,346 110,814 665,866

355

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Noncoincident Peak Load by North American Electric Reliability Corporation Assessment Area, B. Noncoincident Peak Load by North American Electric Reliability Corporation Assessment Area, 2012 Actual, 2013-2017 Projected Summer Peak Load (Megawatts) Eastern Interconnection ERCOT Western Interconnection All Interconnections Period FRCC NPCC Balance of Eastern Region MAPP MISO PJM SERC SPP TRE WECC Contiguous U.S. Actual 2012 44,338 58,319 468,092 5,051 96,769 154,339 161,687 50,246 66,548 130,465 767,762 Projected 2013 45,668 59,969 469,857 5,109 96,192 155,553 159,032 53,971 67,998 133,523 777,015 Projected 2014 46,338 60,654 475,005 5,249 96,879 158,717 159,457 54,703 69,289 132,731 784,017 Projected 2015 47,053 61,428 484,637 5,360 97,565 162,216 164,150 55,346 71,423 134,183 798,724

356

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Coal Mining Productivity by State, Mine Type, and Mine Production Range, 2012" 3. Coal Mining Productivity by State, Mine Type, and Mine Production Range, 2012" "(short tons produced per employee hour)" ,"Mine Production Range (thousand short tons)" "Coal-Producing State, Region1","Above 1,000","Above 500","Above 200","Above 100","Above 50","Above 10","10 or Under","Total2" "and Mine Type",,"to 1,000","to 500","to 200","to 100","to 50" "Alabama",1.69,2.5,1.95,1.72,1.83,0.69,0.55,1.68 " Underground",1.73,"-","-","-",1.08,0.31,"-",1.64 " Surface",1.36,2.5,1.95,1.72,2.11,1.19,0.55,1.75

357

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

9. Average Cost of Petroleum Coke Delivered for Electricity Generation by State, 2012 and 2011 9. Average Cost of Petroleum Coke Delivered for Electricity Generation by State, 2012 and 2011 (Dollars per MMBtu) Census Division and State Electric Power Sector Electric Utilities Independent Power Producers Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 New England -- -- -- -- -- -- -- Connecticut -- -- -- -- -- -- -- Maine -- -- -- -- -- -- -- Massachusetts -- -- -- -- -- -- -- New Hampshire -- -- -- -- -- -- -- Rhode Island -- -- -- -- -- -- -- Vermont -- -- -- -- -- -- -- Middle Atlantic -- W W -- -- -- W New Jersey -- -- -- -- -- -- -- New York -- W W -- -- -- W Pennsylvania -- -- -- -- -- -- -- East North Central W W W 4.10 4.01 W W

358

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

5. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: 5. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: Industrial Sector by State, 2012 Bituminous Subbituminous Lignite Census Division and State Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight New England 19 0.66 6.9 0 -- -- 0 -- -- Connecticut 0 -- -- 0 -- -- 0 -- -- Maine 19 0.66 6.9 0 -- -- 0 -- -- Massachusetts 0 -- -- 0 -- -- 0 -- -- New Hampshire 0 -- -- 0 -- -- 0 -- -- Rhode Island 0 -- -- 0 -- -- 0 -- -- Vermont 0 -- -- 0 -- -- 0 -- --

359

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Existing Net Summer Capacity of Other Renewable Sources by Producer Type, 2002 through 2012 (Megawatts) B. Existing Net Summer Capacity of Other Renewable Sources by Producer Type, 2002 through 2012 (Megawatts) Year Wind Solar Thermal and Photovoltaic Wood and Wood-Derived Fuels Geothermal Other Biomass Total (Other Renewable Sources) Total (All Sectors) 2002 4,417 397 5,844 2,252 3,800 16,710 2003 5,995 397 5,871 2,133 3,758 18,153 2004 6,456 398 6,182 2,152 3,529 18,717 2005 8,706 411 6,193 2,285 3,609 21,205 2006 11,329 411 6,372 2,274 3,727 24,113 2007 16,515 502 6,704 2,214 4,134 30,069 2008 24,651 536 6,864 2,229 4,186 38,466 2009 34,296 619 6,939 2,382 4,317 48,552 2010 39,135 866 7,037 2,405 4,369 53,811 2011 45,676 1,524 7,077 2,409 4,536 61,221 2012 59,075 3,170 7,508 2,592 4,811 77,155

360

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Recoverable Coal Reserves and Average Recovery Percentage at Producing Underground Coal Mines by State and Mining Method, 2012" Recoverable Coal Reserves and Average Recovery Percentage at Producing Underground Coal Mines by State and Mining Method, 2012" "(million short tons)" ,"Continuous1",,"Conventional and Other2",,"Longwall3",,"Total" "Coal-Producing","Recoverable","Average Recovery","Recoverable","Average Recovery","Recoverable","Average Recovery","Recoverable","Average Recovery" "State","Coal Reserves","Percentage","Coal Reserves","Percentage","Coal Reserves","Percentage","Coal Reserves","Percentage" ,"at Producing",,"at Producing",,"at Producing",,"at Producing"

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. U.S. Transmission Circuit Outages by Type and NERC region, 2012 A. U.S. Transmission Circuit Outages by Type and NERC region, 2012 Outage Type FRCC MRO NPCC RFC SERC SPP TRE WECC Contiguous U.S. Circuit Outage Counts Automatic Outages (Sustained) 151.00 163.00 127.00 272.00 374.00 105.00 80.00 796.00 2,068.00 Non-Automatic Outages (Operational) 77.00 44.00 97.00 230.00 192.00 27.00 45.00 337.00 1,049.00 Non-Automatic Outages (Planned) 2,650.00 453.00 512.00 2,050.00 2,450.00 369.00 472.00 2,744.00 11,700.00 Circuit Outage Hours Automatic Outages (Sustained) 2,852.28 1,312.97 14,244.87 19,857.23 7,123.70 1,509.51 682.60 24,238.64 71,821.80 Non-Automatic Outages (Operational) 186.87 27.08 67.68 186.08 426.59 3.32 13.96 67.59 979.17 Non-Automatic Outages (Planned) 872.65 710.33 1,222.36 1,095.46 503.01 357.44 105.06 1,105.43 5,971.74

362

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Biogenic Municipal Solid Waste: Consumption for Electricity Generation, A. Biogenic Municipal Solid Waste: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 21,196 695 18,300 2,087 115 2004 19,587 444 17,308 1,811 24 2005 19,370 560 17,033 1,753 25 2006 19,629 500 17,343 1,761 25 2007 19,576 553 17,116 1,785 122 2008 19,805 509 17,487 1,809 0 2009 19,669 465 17,048 2,155 0 2010 19,437 402 16,802 2,233 0 2011 16,972 388 14,625 1,955 4 2012 16,968 418 14,235 2,304 12 2010 January 1,546 30 1,332 184 0 February 1,384 25 1,215 144 0 March 1,650 36 1,434 180 0 April 1,655 33 1,426 196 0

363

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Consumption of Landfill Gas for Electricity Generation by State, by Sector, 3. Consumption of Landfill Gas for Electricity Generation by State, by Sector, 2012 and 2011 (Million Cubic Feet) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 9,595 9,945 -3.5% 0 0 9,074 9,945 520 0 0 0 Connecticut 595 624 -4.6% 0 0 595 624 0 0 0 0 Maine 518 524 -1.0% 0 0 518 524 0 0 0 0 Massachusetts 3,603 3,623 -0.6% 0 0 3,603 3,623 0 0 0 0 New Hampshire 1,790 1,485 21% 0 0 1,270 1,485 520 0 0 0 Rhode Island 2,409 3,037 -21% 0 0 2,409 3,037 0 0 0 0

364

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

4. Average Price of Coal Delivered to End Use Sector by Census Division and State, 2012 and 2011" 4. Average Price of Coal Delivered to End Use Sector by Census Division and State, 2012 and 2011" "(dollars per short ton)" ,2012,,,,2011,,,,"Annual Percent Change" "Census Division","Electric","Other","Coke","Commercial","Electric","Other","Coke","Commercial","Electric","Other","Coke","Commercial" "and State","Power1","Industrial",,"and","Power1","Industrial",,"and","Power1","Industrial",,"and" ,,,,"Institutional",,,,"Institutional",,,,"Institutional" "New England",88.32,165.17,"-","-",87.62,"w","-","-",0.8,"w","-","-"

365

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

U.S. Coal Consumption by End-Use Sector, 2007 - 2013" U.S. Coal Consumption by End-Use Sector, 2007 - 2013" "(thousand short tons)" ,,,"Other Industrial",,,"Commercial and Institutional" "Year and","Electric","Coke","CHP2","Non-","Total","CHP4","Non-","Total","Total" "Quarter","Power","Plants",,"CHP3",,,"CHP5" ,"Sector1" 2007 " January - March",257516,5576,5834,8743,14578,547,510,1058,278727 " April - June",246591,5736,5552,8521,14074,426,279,705,267106 " July - September",283556,5678,5546,8180,13725,458,247,705,303665 " October - December",257478,5726,5605,8634,14238,495,563,1058,278500

366

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

9. Average Price of U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code" 9. Average Price of U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code" "(dollars per short ton)" ,,,,"Year to Date" "NAICS Code","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "311 Food Manufacturing",51.17,49.59,50.96,50.35,50.94,-1.2 "312 Beverage and Tobacco Product Mfg.",111.56,115.95,113.47,113.49,117.55,-3.5 "313 Textile Mills",115.95,118.96,127.41,117.4,128.07,-8.3 "315 Apparel Manufacturing","w","w","w","w","w","w" "321 Wood Product Manufacturing","w","w","w","w","w","w"

367

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Landfill Gas: Consumption for Electricity Generation, A. Landfill Gas: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Million Cubic Feet) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 136,421 9,168 121,984 3,280 1,989 2004 143,844 11,250 125,848 4,081 2,665 2005 141,899 11,490 123,064 4,797 2,548 2006 160,033 16,617 136,108 6,644 664 2007 166,774 17,442 144,104 4,598 630 2008 195,777 20,465 169,547 5,235 530 2009 206,792 19,583 180,689 5,931 589 2010 218,331 19,975 192,428 5,535 393 2011 232,795 22,086 180,856 29,469 384 2012 256,376 25,193 201,965 26,672 2,545 2010 January 17,531 1,715 15,323 461 32 February 16,189 1,653 14,120 384 33

368

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

. Receipts, Average Cost, and Quality of Fossil Fuels for the Electric Power Industry, 2002 through 2012 . Receipts, Average Cost, and Quality of Fossil Fuels for the Electric Power Industry, 2002 through 2012 Coal Petroleum Natural Gas All Fossil Fuels Average Cost Average Cost Average Cost Average Cost Period Receipts (Thousand Tons) Average Sulfur Percent by Weight (Dollars per MMBtu) (Dollars per Ton) Receipts (Thousand Barrels) Average Sulfur Percent by Weight (Dollars per MMBtu) (Dollars per Barrel) Receipts (Thousand Mcf) (Dollars per MMBtu) (Dollars per MMBtu) 2002 884,287 0.94 1.25 25.52 120,851 1.64 3.34 20.77 5,607,737 3.56 1.86 2003 986,026 0.97 1.28 26.00 185,567 1.53 4.33 26.78 5,500,704 5.39 2.28 2004 1,002,032 0.97 1.36 27.42 186,655 1.66 4.29 26.56 5,734,054 5.96 2.48 2005 1,021,437 0.98 1.54 31.20 194,733 1.61 6.44 39.65 6,181,717 8.21 3.25

369

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

9. Receipts, Average Cost, and Quality of Fossil Fuels: Commercial Sector, 2002 - 2012 9. Receipts, Average Cost, and Quality of Fossil Fuels: Commercial Sector, 2002 - 2012 Coal Petroleum Liquids Receipts Average Cost Receipts Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMBtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Barrels) (Dollars per MMBtu) (Dollars per Barrel) Average Sulfur Percent by Weight Percentage of Consumption Annual Totals 2002 9,580 399 2.10 50.44 2.59 28.4 503 91 5.38 29.73 0.02 7.5 2003 8,835 372 1.99 47.24 2.43 20.5 248 43 7.00 40.82 0.04 3.1 2004 10,682 451 2.08 49.32 2.48 23.5 3,066 527 6.19 35.96 0.20 26.9 2005 11,081 464 2.57 61.21 2.43 24.2 1,684 289 8.28 48.22 0.17 18.3 2006 12,207 518 2.63 61.95 2.51 27.5 798 137 13.50 78.70 0.17 15.5

370

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Coke and Breeze Production at Coke Plants" Coke and Breeze Production at Coke Plants" "(thousand short tons)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "Middle Atlantic","w","w","w","w","w","w" "East North Central",2303,2314,2365,4617,4754,-2.9 "South Atlantic","w","w","w","w","w","w" "East South Central","w","w","w","w","w","w" "U.S. Total",4152,4098,4104,8249,8233,0.2 "Coke Total",3954,3841,3863,7795,7721,1

371

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Electric Power Industry - Electricity Sales for Resale, 2. Electric Power Industry - Electricity Sales for Resale, 2002 through 2012 (Thousand Megawatthours) Year Electric Utilities Energy-Only Providers Independent Power Producers Combined Heat and Power U.S. Total 2002 1,838,901 5,757,283 943,531 28,963 8,568,678 2003 1,824,030 3,906,220 1,156,796 33,909 6,920,954 2004 1,923,440 3,756,175 1,053,364 25,996 6,758,975 2005 1,925,710 2,867,048 1,252,796 26,105 6,071,659 2006 1,698,389 2,446,104 1,321,342 27,638 5,493,473 2007 1,603,179 2,476,740 1,368,310 31,165 5,479,394 2008 1,576,976 2,718,661 1,355,017 30,079 5,680,733 2009 1,495,636 2,240,399 1,295,857 33,139 5,065,031 2010 1,541,554 2,946,452 1,404,137 37,068 5,929,211 2011 1,529,434 2,206,981 1,372,306 34,400 5,143,121

372

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Fuel-Switching Capacity of Operable Generators Reporting Petroleum Liquids as the Primary Fuel, 2. Fuel-Switching Capacity of Operable Generators Reporting Petroleum Liquids as the Primary Fuel, by Producer Type, 2012 (Megawatts, Percent) Fuel-Switchable Part of Total Producer Type Total Net Summer Capacity of All Generators Reporting Petroleum as the Primary Fuel Net Summer Capacity of Petroleum-Fired Generators Reporting the Ability to Switch to Natural Gas Fuel Switchable Capacity as Percent of Total Maximum Achievable Net Summer Capacity Using Natural Gas Electric Utilities 26,732 7,640 28.6 7,224 Independent Power Producers, Non-Combined Heat and Power Plants 18,644 7,867 42.2 6,628 Independent Power Producers, Combined Heat and Power Plants 317 -- -- -- Electric Power Sector Subtotal 45,693 15,507 33.9 13,852 Commercial Sector 443 21 4.8 21

373

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Petroleum Coke: Consumption for Electricity Generation, A. Petroleum Coke: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Thousand Tons) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 6,836 2,125 3,580 2 1,130 2003 6,303 2,554 3,166 2 582 2004 7,677 4,150 2,985 1 541 2005 8,330 4,130 3,746 1 452 2006 7,363 3,619 3,286 1 456 2007 6,036 2,808 2,715 2 512 2008 5,417 2,296 2,704 1 416 2009 4,821 2,761 1,724 1 335 2010 4,994 3,325 1,354 2 313 2011 5,012 3,449 1,277 1 286 2012 3,675 2,105 756 1 812 2010 January 433 283 121 0.17 29 February 404 258 120 0.15 25 March 438 308 108 0.19 23 April 382 253 107 0.12 22 May 415 261 129 0 25

374

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

5. Retail Sales of Electricity to Ultimate Customers: 5. Retail Sales of Electricity to Ultimate Customers: Total by End-Use Sector, 2003 - December 2012 (Million Kilowatthours) Period Residential Commercial Industrial Transportation All Sectors Annual Totals 2003 1,275,824 1,198,728 1,012,373 6,810 3,493,734 2004 1,291,982 1,230,425 1,017,850 7,224 3,547,479 2005 1,359,227 1,275,079 1,019,156 7,506 3,660,969 2006 1,351,520 1,299,744 1,011,298 7,358 3,669,919 2007 1,392,241 1,336,315 1,027,832 8,173 3,764,561 2008 1,379,981 1,335,981 1,009,300 7,700 3,732,962 2009 1,364,474 1,307,168 917,442 7,781 3,596,865 2010 1,445,708 1,330,199 970,873 7,712 3,754,493 2011 1,422,801 1,328,057 991,316 7,672 3,749,846 2012 1,374,515 1,327,101 985,714 7,320 3,694,650 2010

375

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Coal Carbonized at Coke Plants by Census Division" 3. Coal Carbonized at Coke Plants by Census Division" "(thousand short tons)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "Middle Atlantic","w","w","w","w","w","w" "East North Central",3051,2997,3092,6048,6156,-1.8 "South Atlantic","w","w","w","w","w","w" "East South Central","w","w","w","w","w","w" "U.S. Total",5471,5280,5296,10751,10579,1.6 "w = Data withheld to avoid disclosure."

376

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

4. Consumption of Biogenic Municipal Solid Waste for Electricity Generation by State, by Sector, 4. Consumption of Biogenic Municipal Solid Waste for Electricity Generation by State, by Sector, 2012 and 2011 (Thousand Tons) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 4,041 4,122 -2.0% 0 0 3,838 3,922 203 200 0 0 Connecticut 1,415 1,442 -1.9% 0 0 1,415 1,442 0 0 0 0 Maine 440 445 -1.3% 0 0 237 246 203 200 0 0 Massachusetts 2,017 2,063 -2.2% 0 0 2,017 2,063 0 0 0 0 New Hampshire 169 172 -2.0% 0 0 169 172 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0

377

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Summer Net Internal Demand, Capacity Resources, and Capacity Margins by North American Electric Reliability Assessment Area, A. Summer Net Internal Demand, Capacity Resources, and Capacity Margins by North American Electric Reliability Assessment Area, 2002 - 2012, Actual Net Internal Demand (Megawatts) -- Summer Eastern Interconnection ERCOT Western Interconnection All Interconnections Period FRCC NPCC Balance of Eastern Region ECAR MAAC MAIN MAPP MISO MRO PJM RFC SERC SPP TRE WECC Contiguous U.S. 2002 37,951 55,164 430,396 101,251 54,296 53,267 -- -- 28,825 -- -- 154,459 38,298 55,833 117,032 696,376 2003 40,387 53,936 422,253 98,487 53,566 53,617 -- -- 28,775 -- -- 148,380 39,428 59,282 120,894 696,752 2004 42,243 51,580 419,349 95,300 52,049 50,499 -- -- 29,094 -- -- 153,024 39,383 58,531 121,205 692,908

378

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Net Generation from Renewable Sources: Industrial Sector, 2002 - 2012 B. Net Generation from Renewable Sources: Industrial Sector, 2002 - 2012 (Thousand Megawatthours) Period Wind Solar Photovoltaic Solar Thermal Wood and Wood-Derived Fuels Landfill Gas Biogenic Municipal Solid Waste Other Waste Biomass Geothermal Conventional Hydroelectric Total Renewable Sources Annual Totals 2002 0 N/A N/A 29,643 N/A N/A N/A 0 3,825 N/A 2003 0 0 0 27,988 96 36 583 0 4,222 32,926 2004 0 0 0 28,367 120 30 647 0 3,248 32,413 2005 0 0 0 28,271 113 34 585 0 3,195 32,199 2006 0 0 0 28,400 29 35 509 0 2,899 31,872 2007 0 0 0 28,287 27 40 565 0 1,590 30,509 2008 0 0 0 26,641 21 0 800 0 1,676 29,138 2009 0 0 0 25,292 22 0 718 0 1,868 27,901 2010 0 2 0 25,706 15 0 853 0 1,668 28,244

379

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

6. Net Generation from Other Energy Sources 6. Net Generation from Other Energy Sources by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 2,153 2,019 6.7% 0 0 1,944 1,888 88 84 121 46 Connecticut 756 705 7.3% 0 0 756 704 0 0 0 1 Maine 424 390 8.7% 0 0 245 261 88 84 92 45 Massachusetts 906 860 5.5% 0 0 877 860 0 0 29 0 New Hampshire 66 64 2.6% 0 0 66 64 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0 Middle Atlantic 2,497 2,441 2.3% 0 0 1,924 1,975 465 344 107 122

380

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

U.S. Steam Coal Exports" U.S. Steam Coal Exports" "(short tons)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",1619502,1246181,2153814,2865683,3065683,-6.5 " Canada*",797861,599752,841061,1397613,1280803,9.1 " Dominican Republic",51698,160672,124720,212370,312741,-32.1 " Honduras","-",41664,34161,41664,68124,-38.8 " Jamaica",25,36311,"-",36336,33585,8.2 " Mexico",717687,407422,1116653,1125109,1331754,-15.5 " Other**",52231,360,37219,52591,38676,36

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

. Receipts and Quality of Coal Delivered for the Electric Power Industry, 2002 through 2012 . Receipts and Quality of Coal Delivered for the Electric Power Industry, 2002 through 2012 Bituminous Subbituminous Lignite Period Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight 2002 423,128 1.47 10.1 391,785 0.36 6.2 65,555 0.93 13.3 2003 467,286 1.50 10.0 432,513 0.38 6.4 79,869 1.03 14.4 2004 470,619 1.52 10.4 445,603 0.36 6.0 78,268 1.05 14.2 2005 480,179 1.56 10.5 456,856 0.36 6.2 77,677 1.02 14.0 2006 489,550 1.59 10.5 504,947 0.35 6.1 75,742 0.95 14.4 2007 467,817 1.62 10.3 505,155 0.34 6.0 71,930 0.90 14.0

382

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Coal Consumption at Other Industrial Plants by Census Division and State" Coal Consumption at Other Industrial Plants by Census Division and State" "(thousand short tons)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "New England","w","w",20,"w","w","w" " Maine","w","w","w","w","w","w" " Massachusetts","w","w","w","w","w","w" "Middle Atlantic",583,589,651,1171,1237,-5.3 " New York",155,181,206,337,374,-10.1

383

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

D. Landfill Gas: Consumption for Electricity Generation, D. Landfill Gas: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 65,770 3,930 59,089 1,753 998 2004 69,331 5,373 60,514 2,093 1,351 2005 67,902 5,650 58,624 2,360 1,269 2006 75,970 8,287 63,950 3,388 345 2007 79,712 8,620 68,432 2,344 316 2008 94,215 10,242 81,029 2,668 276 2009 99,821 9,748 86,773 2,999 301 2010 105,835 10,029 92,763 2,837 205 2011 112,538 11,146 89,857 11,332 203 2012 124,297 12,721 99,938 10,356 1,282 2010 January 8,441 853 7,335 236 17 February 7,824 830 6,781 197 17 March 9,056 1,013 7,796 226 21

384

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

D. Natural Gas: Consumption for Electricity Generation, D. Natural Gas: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 6,249,585 2,307,358 3,214,286 30,626 697,315 2003 5,735,770 1,809,003 3,200,057 39,424 687,286 2004 5,827,470 1,857,247 3,351,469 33,623 585,132 2005 6,212,116 2,198,098 3,444,875 34,645 534,498 2006 6,643,926 2,546,169 3,508,597 35,473 553,687 2007 7,287,714 2,808,500 3,872,646 34,872 571,697 2008 7,087,191 2,803,283 3,712,872 34,138 536,899 2009 7,301,522 2,981,285 3,750,080 35,046 535,111 2010 7,852,665 3,359,035 3,882,995 40,356 570,279 2011 8,052,309 3,511,732 3,906,484 48,509 585,584

385

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

4. Average Price of Coal Receipts at Coke Plants by Census Division" 4. Average Price of Coal Receipts at Coke Plants by Census Division" "(dollars per short ton)" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "Middle Atlantic","w","w","w","w","w","w" "East North Central",157.29,176.84,199.7,166.21,198.26,-16.2 "South Atlantic","w","w","w","w","w","w" "East South Central","w","w","w","w","w","w" "U.S. Total",157.26,171.51,191.48,163.85,190.51,-14

386

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

5. Demand-Side Management Program Direct and Indirect Costs, 5. Demand-Side Management Program Direct and Indirect Costs, 2002 through 2012 (Thousand Dollars) Year Energy Efficiency Load Management Direct Cost Indirect Cost Total Cost 2002 1,032,911 410,323 1,443,234 206,169 1,649,403 2003 807,403 352,137 1,159,540 137,670 1,340,686 2004 910,816 510,281 1,421,097 132,295 1,560,578 2005 1,180,576 622,287 1,802,863 127,925 1,939,115 2006 1,270,602 663,980 1,934,582 128,886 2,072,962 2007 1,677,969 700,362 2,378,331 160,326 2,604,711 2008 2,137,452 836,359 2,973,811 181,843 3,186,742 2009 2,221,480 944,261 3,165,741 394,193 3,607,076 2010 2,906,906 1,048,356 3,955,262 275,158 4,230,420 2011 4,002,672 1,213,102 5,215,774 328,622 5,544,396 2012 4,397,635 1,270,391 5,668,026 332,440 6,000,466

387

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Net Generation from Renewable Sources: Electric Utilities, 2002 - 2012 B. Net Generation from Renewable Sources: Electric Utilities, 2002 - 2012 (Thousand Megawatthours) Period Wind Solar Photovoltaic Solar Thermal Wood and Wood-Derived Fuels Landfill Gas Biogenic Municipal Solid Waste Other Waste Biomass Geothermal Conventional Hydroelectric Total Renewable Sources Annual Totals 2002 213 N/A N/A 709 N/A N/A N/A 1,402 242,302 N/A 2003 354 2 0 882 394 326 214 1,249 249,622 253,043 2004 405 6 0 1,209 460 198 166 1,248 245,546 249,238 2005 1,046 16 0 1,829 503 250 175 1,126 245,553 250,499 2006 2,351 15 0.18 1,937 705 228 190 1,162 261,864 268,452 2007 4,361 10 1 2,226 751 240 226 1,139 226,734 235,687 2008 6,899 16 1 1,888 844 211 252 1,197 229,645 240,953

388

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Petroleum Liquids: Consumption for Electricity Generation, A. Petroleum Liquids: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Thousand Barrels) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2002 134,415 88,595 39,035 826 5,959 2003 175,136 105,319 61,420 882 7,514 2004 165,107 103,793 56,342 760 4,212 2005 165,137 98,223 62,154 580 4,180 2006 73,821 53,529 17,179 327 2,786 2007 82,433 56,910 22,793 250 2,480 2008 53,846 38,995 13,152 160 1,538 2009 43,562 31,847 9,880 184 1,652 2010 40,103 30,806 8,278 164 855 2011 27,326 20,844 5,633 133 716 2012 22,604 17,521 4,110 272 702 2010 January 5,587 4,381 1,083 17 106 February 2,156 1,599 454 15 88

389

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

4. Average Power Plant Operating Expenses for Major U.S. Investor-Owned Electric Utilities, 2002 through 2012 (Mills per Kilowatthour) 4. Average Power Plant Operating Expenses for Major U.S. Investor-Owned Electric Utilities, 2002 through 2012 (Mills per Kilowatthour) Operation Maintenance Year Nuclear Fossil Steam Hydro-electric Gas Turbine and Small Scale Nuclear Fossil Steam Hydro-electric Gas Turbine and Small Scale 2002 9.00 2.59 3.71 3.26 5.04 2.67 2.62 2.38 2003 9.12 2.74 3.47 3.50 5.23 2.72 2.32 2.26 2004 8.97 3.13 3.83 4.27 5.38 2.96 2.76 2.14 2005 8.26 3.21 3.95 3.69 5.27 2.98 2.73 1.89 2006 9.03 3.57 3.76 3.51 5.69 3.19 2.70 2.16 2007 9.54 3.63 5.44 3.26 5.79 3.37 3.87 2.42 2008 9.89 3.72 5.78 3.77 6.20 3.59 3.89 2.72 2009 10.00 4.23 4.88 3.05 6.34 3.96 3.50 2.58 2010 10.50 4.04 5.33 2.79 6.80 3.99 3.81 2.73

390

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Price of U.S. Coal Imports" Price of U.S. Coal Imports" "(dollars per short ton)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Origin",2013,2013,2012,,,"Change" "North America Total",147.86,138.39,191.01,144.86,197.96,-26.8 " Canada",147.86,138.39,191,144.86,197.95,-26.8 " Mexico","-","-",286.23,"-",286.23,"-" "South America Total",75.29,80.74,86.52,77.2,87.17,-11.4 " Argentina","-","-",504.7,"-",504.7,"-" " Colombia",74.87,80.74,83.03,76.96,85.25,-9.7 " Peru",87.09,"-","-",87.09,"-","-"

391

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

4. Fuel-Switching Capacity of Operable Generators: From Natural Gas to Petroleum Liquids, 4. Fuel-Switching Capacity of Operable Generators: From Natural Gas to Petroleum Liquids, by Year of Initial Commercial Operation, 2012 (Megawatts, Percent) Year of Initial Commercial Operation Number of Generators Net Summer Capacity Fuel Switchable Net Summer Capacity Reported to Have No Factors that Limit the Ability to Switch to Petroleum Liquids Pre-1970 318 11,735 7,535 1970-1974 376 18,210 11,033 1975-1979 105 11,031 7,283 1980-1984 46 945 211 1985-1989 107 3,155 413 1990-1994 208 11,738 1,453 1995-1999 134 9,680 2,099 2000-2004 392 39,841 5,098 2005-2009 116 14,791 2,066 2010-2012 78 8,479 320 Total 1,880 129,604 37,510 Notes: Petroleum includes distillate fuel oil (all diesel and No. 1, No. 2, and No. 4 fuel oils), residual fuel oil (No. 5 and No. 6 fuel oils and bunker C fuel oil), jet fuel, kerosene, petroleum coke (converted to liquid petroleum, see Technical Notes for conversion methodology), waste oil, and beginning in 2011, synthetic gas and propane. Prior to 2011, synthetic gas and propane were included in Other Gases.

392

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

5. U.S. Coal Consumption at Manufacturing Plants by North American Industry Classification System (NAICS) Code" 5. U.S. Coal Consumption at Manufacturing Plants by North American Industry Classification System (NAICS) Code" "(thousand short tons)" ,,,,"Year to Date" "NAICS Code","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "311 Food Manufacturing",2256,2561,1864,4817,4343,10.9 "312 Beverage and Tobacco Product Mfg.",38,50,48,88,95,-7.7 "313 Textile Mills",31,29,21,60,59,2.2 "315 Apparel Manufacturing","w","w","w","w","w","w" "321 Wood Product Manufacturing","w","w","w","w","w","w"

393

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

D. Biogenic Municipal Solid Waste: Consumption for Electricity Generation, D. Biogenic Municipal Solid Waste: Consumption for Electricity Generation, by Sector, 2002 - 2012 (Billion Btus) Electric Power Sector Period Total (all sectors) Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Annual Totals 2003 148,110 5,766 128,947 13,095 302 2004 141,577 3,705 124,815 12,909 146 2005 144,339 4,724 126,529 12,923 164 2006 146,987 4,078 129,779 12,964 165 2007 146,308 4,557 127,826 13,043 881 2008 148,452 4,476 130,041 13,934 0 2009 146,971 3,989 126,649 16,333 0 2010 144,934 3,322 124,437 17,176 0 2011 135,241 3,433 115,841 15,933 34 2012 135,735 3,910 113,418 18,307 100 2010 January 11,540 244 9,886 1,410 0 February 10,313 190 9,030 1,094 0

394

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Average Quality of Fossil Fuel Receipts for the Electric Power Industry, 3. Average Quality of Fossil Fuel Receipts for the Electric Power Industry, 2002 through 2012 Coal Petroleum Natural Gas Period Average Btu per Pound Average Sulfur Percent by Weight Average Ash Percent by Weight Average Btu per Gallon Average Sulfur Percent by Weight Average Ash Percent by Weight Average Btu per Cubic Foot 2002 10,168 0.94 8.7 147,903 1.64 0.2 1,025 2003 10,137 0.97 9.0 147,086 1.53 0.1 1,030 2004 10,074 0.97 9.0 147,286 1.66 0.2 1,027 2005 10,107 0.98 9.0 146,481 1.61 0.2 1,028 2006 10,063 0.97 9.0 143,883 2.31 0.2 1,027 2007 10,028 0.96 8.8 144,546 2.10 0.1 1,027 2008 9,947 0.97 9.0 142,205 2.21 0.3 1,027 2009 9,902 1.01 8.9 141,321 2.14 0.2 1,025 2010 9,842 1.16 8.8 140,598 2.14 0.2 1,022

395

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

5. Net Generation from Hydroelectric (Pumped Storage) Power 5. Net Generation from Hydroelectric (Pumped Storage) Power by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England -305 -435 -29.9% 0 0 -305 -435 0 0 0 0 Connecticut 3 6 -51.5% 0 0 3 6 0 0 0 0 Maine 0 0 -- 0 0 0 0 0 0 0 0 Massachusetts -308 -440 -30.1% 0 0 -308 -440 0 0 0 0 New Hampshire 0 0 -- 0 0 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0 Middle Atlantic -1,022 -1,124 -9.0% -579 -630 -443 -494 0 0 0 0

396

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Average Price of U.S. Coal Exports" Average Price of U.S. Coal Exports" "(dollars per short ton)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",78.29,77.25,102.62,77.88,105.14,-25.9 " Canada*",81.61,80.7,110.67,81.3,112.16,-27.5 " Dominican Republic",78.54,75.09,73.89,75.77,76.61,-1.1 " Honduras","-",54.58,54.43,54.58,54.43,0.3 " Jamaica",480,54.43,"-",54.72,55.42,-1.3 " Mexico",73.45,75.81,94.36,74.35,100.95,-26.3 " Other**",80.33,389.3,70.37,82.45,76.1,8.3

397

SAS Output  

Annual Energy Outlook 2012 (EIA)

5. Receipts, Average Cost, and Quality of Fossil Fuels: Electric Utilities, 2002 - 2012 Coal Petroleum Liquids Receipts Average Cost Receipts Average Cost Period (Billion Btu)...

398

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

4. Weighted Average Cost of Fossil Fuels for the Electric Power Industry, 2002 through 2012 Coal Petroleum Natural Gas Total Fossil Bituminous Subbituminous Lignite All Coal Ranks...

399

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Fuel-Switching Capacity of Operable Generators: From Natural Gas to Petroleum Liquids, by Type of Prime Mover, 2012 (Megawatts, Percent) Prime Mover Type Number of Generators...

400

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

" Italy","-","-","-","-",3,"-" " Netherlands","-","-","-","-",1046,"-" " Russia",42439,"-","-",42439,"-","-" " Ukraine",80025,23142,"-",103167,22155,365.7 " United...

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

455,214 Other Gases 94 2,253 1,946 1,933 Nuclear 104 107,938 101,885 104,182 Hydroelectric Conventional 4,023 78,241 78,738 78,215 Wind 947 59,629 59,075 59,082 Solar...

402

SAS Output  

Annual Energy Outlook 2012 (EIA)

3,001 2,267 2,431 Other Gases 1 * * * 4 120 152 152 Nuclear -- -- -- -- -- -- -- -- Hydroelectric Conventional 15 345 344 342 28 317 315 314 Wind 149 12,953 12,885 12,885 1 13 12...

403

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Net Generation from Hydroelectric (Conventional) Power by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors...

404

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

because of independent rounding." "Source: U.S. Department of Labor, Mine Safety and Health Administration, Form 7000-2, 'Quarterly Mine Employment and Coal Production Report.'...

405

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2012 (From Chapter 2.) Supply (Million Megawatthours) Generation Year Electric Utilities IPP (Non-CHP) IPP (CHP) Commercial Sector Industrial Sector Total Imports Total...

406

SAS Output  

Annual Energy Outlook 2012 (EIA)

- Electricity Purchases, 2002 through 2012 (Thousand Megawatthours) Year Electric Utilities Energy-Only Providers Independent Power Producers Combined Heat and Power U.S. Total...

407

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

to Date" "Customs District","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "Eastern Total",14307904,16331296,16667115,3063920...

408

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

,,,,"Year to Date" "Commodity","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "Coke" " Sales",1969,1865,1969,3834,3905,-1.8 "...

409

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

18,481,678 1,320,095 624,502 45,083,186 19,106,180 2011 51,075,952 14,398,470 1,223,758 650,082 52,299,710 15,048,552 2012 57,971,110 11,392,267 1,285,959 603,382...

410

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Coal Productivity by State and Mine Type, 2012 and 2011" ,"Number of Mining Operations2",,,"Number of Employees3",,,"Average Production per Employee Hour" ,,,"(short tons)4"...

411

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Recoverable Coal Reserves at Producing Mines, Estimated Recoverable Reserves, and Demonstrated Reserve by Mining Method, 2012" "(million short tons)" ,"Underground - Minable...

412

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Coal Production and Number of Mines by State and Coal Rank, 2012" "(thousand short tons)" ,"Bituminous",,"Subbituminous",,"Lignite",,"Anthracite",,"Total" "Coal-Producing","Number...

413

SAS Output  

Gasoline and Diesel Fuel Update (EIA)

B. U.S. Transformer Outages by Type and NERC region, 2012 Outage Type Eastern Interconnection TRE WECC Contiguous U.S. Circuit Outage Counts Automatic Outages (Sustained) 16.00 --...

414

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2012 2,162,230 102,223 1,509 -- 2,265,963 In 2006 the single largest provider of green pricing services in the country discontinued service in two States. More than...

415

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Summer Net Internal Demand, Capacity Resources, and Capacity Margins B. Summer Net Internal Demand, Capacity Resources, and Capacity Margins by North American Electric Reliability Corporation Assessment Area, 2012 Actual, 2013-2017 Projected Net Internal Demand (Megawatts) -- Summer Eastern Interconnection ERCOT Western Interconnection All Interconnections Period FRCC NPCC Balance of Eastern Region MAPP MISO PJM SERC SPP TRE WECC Contiguous U.S. Actual 2012 44,338 58,319 469,273 4,967 96,769 156,319 158,041 53,177 66,548 130,465 768,943 Projected 2013 42,532 59,969 447,171 5,022 91,644 144,378 152,949 53,177 65,901 129,278 744,851 Projected 2014 43,142 60,654 448,912 5,161 92,331 144,497 152,843 54,080 67,592 128,200 748,499 Projected 2015 43,812 61,428 457,865 5,270 93,017 147,568 157,287 54,722 69,679 129,553 762,336

416

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Net Generation by Energy Source: Industrial Sector, 2002 - 2012 A. Net Generation by Energy Source: Industrial Sector, 2002 - 2012 (Thousand Megawatthours) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Nuclear Hydroelectric Conventional Renewable Sources Excluding Hydroelectric Hydroelectric Pumped Storage Other Total Annual Totals 2002 21,525 3,196 1,207 79,013 9,493 0 3,825 30,489 0 3,832 152,580 2003 19,817 3,726 1,559 78,705 12,953 0 4,222 28,704 0 4,843 154,530 2004 19,773 4,128 1,839 78,959 11,684 0 3,248 29,164 0 5,129 153,925 2005 19,466 3,804 1,564 72,882 9,687 0 3,195 29,003 0 5,137 144,739 2006 19,464 2,567 1,656 77,669 9,923 0 2,899 28,972 0 5,103 148,254 2007 16,694 2,355 1,889 77,580 9,411 0 1,590 28,919 0 4,690 143,128

417

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Existing Net Summer Capacity by Energy Source and Producer Type, 2002 through 2012 (Megawatts) A. Existing Net Summer Capacity by Energy Source and Producer Type, 2002 through 2012 (Megawatts) Year Coal Petroleum Natural Gas Other Gases Nuclear Hydroelectric Conventional Other Renewable Sources Hydroelectric Pumped Storage Other Energy Sources Total Total (All Sectors) 2002 315,350 59,651 312,512 2,008 98,657 79,356 16,710 20,371 686 905,301 2003 313,019 60,730 355,442 1,994 99,209 78,694 18,153 20,522 684 948,446 2004 313,020 59,119 371,011 2,296 99,628 77,641 18,717 20,764 746 962,942 2005 313,380 58,548 383,061 2,063 99,988 77,541 21,205 21,347 887 978,020 2006 312,956 58,097 388,294 2,256 100,334 77,821 24,113 21,461 882 986,215 2007 312,738 56,068 392,876 2,313 100,266 77,885 30,069 21,886 788 994,888

418

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

0. Average Cost of Natural Gas Delivered for Electricity Generation by State, 2012 and 2011 0. Average Cost of Natural Gas Delivered for Electricity Generation by State, 2012 and 2011 (Dollars per MMBtu) Census Division and State Electric Power Sector Electric Utilities Independent Power Producers Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 New England 3.69 4.94 -25% 4.73 5.70 3.68 4.93 Connecticut 3.88 4.97 -22% 6.45 NM 3.87 4.96 Maine W W W -- -- W W Massachusetts 3.55 4.88 -27% 4.47 5.75 3.53 4.87 New Hampshire W W W 5.54 6.01 W W Rhode Island 3.86 5.01 -23% -- -- 3.86 5.01 Vermont 4.06 5.22 -22% 4.06 5.22 -- -- Middle Atlantic 3.52 5.14 -32% 3.86 5.32 3.46 5.11 New Jersey 3.52 5.11 -31% -- -- 3.52 5.11 New York 3.85 5.45 -29% 3.86 5.32 3.84 5.50

419

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

. Average Operating Heat Rate for Selected Energy Sources, . Average Operating Heat Rate for Selected Energy Sources, 2002 through 2012 (Btu per Kilowatthour) Year Coal Petroleum Natural Gas Nuclear 2002 10,314 10,641 9,533 10,442 2003 10,297 10,610 9,207 10,422 2004 10,331 10,571 8,647 10,428 2005 10,373 10,631 8,551 10,436 2006 10,351 10,809 8,471 10,435 2007 10,375 10,794 8,403 10,489 2008 10,378 11,015 8,305 10,452 2009 10,414 10,923 8,159 10,459 2010 10,415 10,984 8,185 10,452 2011 10,444 10,829 8,152 10,464 2012 10,498 10,991 8,039 10,479 Coal includes anthracite, bituminous, subbituminous and lignite coal. Waste coal and synthetic coal are included starting in 2002. Petroleum includes distillate fuel oil (all diesel and No. 1 and No. 2 fuel oils), residual fuel oil (No. 5 and No. 6 fuel oils and bunker C fuel oil, jet fuel, kerosene, petroleum coke, and waste oil.

420

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

0. Net Generation from Natural Gas 0. Net Generation from Natural Gas by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 62,490 63,236 -1.2% 345 357 58,757 59,763 901 700 2,488 2,416 Connecticut 16,537 15,188 8.9% 6 NM 15,801 14,715 397 211 333 227 Maine 6,044 6,877 -12.1% 0 0 4,057 4,850 26 0.26 1,960 2,026 Massachusetts 24,672 25,940 -4.9% 278 240 23,812 25,120 416 443 166 136 New Hampshire 7,050 6,658 5.9% 58 80 6,947 6,552 16 0 29 26 Rhode Island 8,185 8,571 -4.5% 0 0 8,140 8,525 45 46 0 0

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

4. Average Quality of Coal Received at Commercial and Institutional Users by Census Division and State" 4. Average Quality of Coal Received at Commercial and Institutional Users by Census Division and State" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State1",2013,2013,2012,,,"Change" "Middle Atlantic" " Btu",12906,12815,11709,12844,12440,3.2 " Sulfur",1.03,0.92,0.99,0.96,0.97,-1 " Ash",8.94,8.62,10,8.72,9.11,-4.3 "Pennsylvania" " Btu",12906,12815,11709,12844,12440,3.2 " Sulfur",1.03,0.92,0.99,0.96,0.97,-1 " Ash",8.94,8.62,10,8.72,9.11,-4.3 "East North Central" " Btu",11928,12228,11682,12112,11933,1.5

422

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Major U.S. Coal Producers, 2012" Major U.S. Coal Producers, 2012" "Rank","Controlling Company Name","Production (thousand short tons)","Percent of Total Production" 1,"Peabody Energy Corp",192563,18.9 2,"Arch Coal Inc",136992,13.5 3,"Alpha Natural Resources LLC",104306,10.3 4,"Cloud Peak Energy",90721,8.9 5,"CONSOL Energy Inc",55752,5.5 6,"Alliance Resource Operating Partners LP",35406,3.5 7,"Energy Future Holdings Corp",31032,3.1 8,"Murray Energy Corp",29216,2.9 9,"NACCO Industries Inc",28207,2.8 10,"Patriot Coal Corp",23946,2.4 11,"Peter Kiewit Sons Inc",22725,2.2 12,"Westmoreland Coal Co",22215,2.2 13,"BHP Billiton Ltd",12580,1.2

423

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

5. Receipts of Petroleum Coke Delivered for Electricity Generation by State, 2012 and 2011 5. Receipts of Petroleum Coke Delivered for Electricity Generation by State, 2012 and 2011 (Thousand Tons) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 0 0 -- 0 0 0 0 0 0 0 0 Connecticut 0 0 -- 0 0 0 0 0 0 0 0 Maine 0 0 -- 0 0 0 0 0 0 0 0 Massachusetts 0 0 -- 0 0 0 0 0 0 0 0 New Hampshire 0 0 -- 0 0 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0 Middle Atlantic 106 79 35% 0 0 0 23 0 0 106 56 New Jersey 0 NM NM 0 0 0 0 0 0 0 NM

424

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

6. Net Generation 6. Net Generation by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 120,887 123,338 -2.0% 3,278 4,408 111,191 112,613 1,178 949 5,240 5,368 Connecticut 36,118 33,745 7.0% 37 93 35,347 33,208 397 211 337 233 Maine 14,429 15,974 -9.7% 0.17 1 10,186 10,890 208 176 4,035 4,907 Massachusetts 36,198 38,055 -4.9% 591 610 34,321 36,783 469 490 817 172 New Hampshire 19,264 20,066 -4.0% 2,017 2,994 17,170 17,020 49 20 29 31

425

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Net Summer Capacity of Utility Scale Units Using Primarily Renewable Energy Sources and by State, 2012 and 2011 (Megawatts) B. Net Summer Capacity of Utility Scale Units Using Primarily Renewable Energy Sources and by State, 2012 and 2011 (Megawatts) Census Division and State Wind Solar Photovoltaic Solar Thermal Conventional Hydroelectric Biomass Sources Geothermal Total Renewable Sources Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 784.1 422.8 49.2 13.9 0.0 0.0 1,956.9 1,946.9 1,367.5 1,421.6 0.0 0.0 4,157.7 3,805.2 Connecticut 0.0 0.0 0.0 0.0 0.0 0.0 122.2 121.7 172.5 178.2 0.0 0.0 294.7 299.9 Maine 427.6 322.5 0.0 0.0 0.0 0.0 742.3 742.3 534.6 576.0 0.0 0.0 1,704.5 1,640.8 Massachusetts 63.8 29.6 41.2 11.7 0.0 0.0 261.1 262.7 395.4 406.9 0.0 0.0 761.5 710.9

426

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: Independent Power Producers by State, 2012 3. Receipts and Quality of Coal by Rank Delivered for Electricity Generation: Independent Power Producers by State, 2012 Bituminous Subbituminous Lignite Census Division and State Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight Receipts (Thousand Tons) Average Sulfur Percent by Weight Average Ash Percent by Weight New England 732 0.87 10.5 41 0.09 2.0 0 -- -- Connecticut 0 -- -- 41 0.09 2.0 0 -- -- Maine 32 0.80 7.0 0 -- -- 0 -- -- Massachusetts 700 0.88 10.7 0 -- -- 0 -- -- New Hampshire 0 -- -- 0 -- -- 0 -- -- Rhode Island 0 -- -- 0 -- -- 0 -- -- Vermont 0 -- -- 0 -- -- 0 -- --

427

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

7. Average Cost of Coal Delivered for Electricity Generation by State, 2012 and 2011 7. Average Cost of Coal Delivered for Electricity Generation by State, 2012 and 2011 (Dollars per MMBtu) Census Division and State Electric Power Sector Electric Utilities Independent Power Producers Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 New England 3.59 3.68 -2.4% 4.07 3.55 3.34 3.74 Connecticut W W W -- -- W W Maine W W W -- -- W W Massachusetts W W W -- -- W W New Hampshire 4.07 3.55 15% 4.07 3.55 -- -- Rhode Island -- -- -- -- -- -- -- Vermont -- -- -- -- -- -- -- Middle Atlantic 2.50 2.68 -6.7% -- 2.92 2.50 2.63 New Jersey 4.05 4.18 -3.1% -- -- 4.05 4.18 New York 3.12 3.27 -4.6% -- 3.88 3.12 3.27 Pennsylvania 2.43 2.55 -4.7% -- 2.91 2.43 2.45

428

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

. Count of Electric Power Industry Power Plants, by Sector, by Predominant Energy Sources within Plant, 2002 through 2012 . Count of Electric Power Industry Power Plants, by Sector, by Predominant Energy Sources within Plant, 2002 through 2012 Year Coal Petroleum Natural Gas Other Gases Nuclear Hydroelectric Conventional Other Renewables Hydroelectric Pumped Storage Other Energy Sources Total (All Sectors) 2002 633 1,147 1,649 40 66 1,426 682 38 28 2003 629 1,166 1,693 40 66 1,425 741 38 27 2004 625 1,143 1,670 46 66 1,425 749 39 28 2005 619 1,133 1,664 44 66 1,422 781 39 29 2006 616 1,148 1,659 46 66 1,421 843 39 29 2007 606 1,163 1,659 46 66 1,424 929 39 25 2008 598 1,170 1,655 43 66 1,423 1,076 39 29 2009 593 1,168 1,652 43 66 1,427 1,219 39 28 2010 580 1,169 1,657 48 66 1,432 1,355 39 32

429

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Receipts, Average Cost, and Quality of Fossil Fuels: Industrial Sector, 2002 - 2012 (continued) 2. Receipts, Average Cost, and Quality of Fossil Fuels: Industrial Sector, 2002 - 2012 (continued) Petroleum Coke Natural Gas All Fossil Fuels Receipts Average Cost Receipts Average Cost Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMbtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Mcf) (Dollars per MMBtu) (Dollars per Mcf) Percentage of Consumption (Dollars per MMBtu) Annual Totals 2002 3,846 138 0.76 21.20 5.91 9.1 852,547 828,439 3.36 3.46 66.8 2.88 2003 16,383 594 1.04 28.74 5.73 47.3 823,681 798,996 5.32 5.48 69.9 4.20 2004 14,876 540 0.98 27.01 5.59 40.4 839,886 814,843 6.04 6.22 68.4 4.76 2005 16,620 594 1.21 33.75 5.44 58.2 828,882 805,132 8.00 8.24 74.3 6.18

430

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Existing Transmission Capacity by High-Voltage Size, 2012 A. Existing Transmission Capacity by High-Voltage Size, 2012 Voltage Circuit Miles Type Operating (kV) FRCC MRO NPCC RFC SERC SPP TRE WECC Contiguous U.S. AC 100-199 -- -- -- -- -- -- -- -- -- AC 200-299 6,018 7,813 1,538 6,933 21,757 2,948 -- 38,410 85,416 AC 300-399 -- 7,362 5,850 13,429 3,650 5,303 9,529 10,913 56,036 AC 400-599 1,201 543 -- 2,618 8,876 94 -- 12,794 26,125 AC 600-799 -- -- 190 2,226 -- -- -- -- 2,416 AC Multi-Circuit Structure 200-299 1,198 686 36 2,008 4,156 9 -- -- 8,092 AC Multi-Circuit Structure 300-399 -- 372 274 3,706 313 153 2,747 -- 7,564 AC Multi-Circuit Structure 400-599 -- -- -- 90 857 -- -- -- 947 AC Multi-Circuit Structure 600-799 -- -- -- -- -- -- -- -- --

431

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Net Energy for Load by North American Electric Reliability Corporation Assessment Area, A. Net Energy for Load by North American Electric Reliability Corporation Assessment Area, 2002 - 2012, Actual Net Energy (Thousands of Megawatthours) Eastern Interconnection ERCOT Western Interconnection All Interconnections Period FRCC NPCC Balance of Eastern Region ECAR MAAC MAIN MAPP MISO MRO PJM RFC SERC SPP TRE WECC Contiguous U.S. 2002 211,116 286,199 2,301,321 567,897 273,907 279,264 -- -- 150,058 -- -- 835,319 194,876 280,269 666,696 3,745,601 2003 219,021 288,791 2,255,233 545,109 276,600 267,068 -- -- 153,918 -- -- 826,964 185,574 283,868 664,754 3,711,667 2004 220,335 292,725 2,313,180 553,236 283,646 274,760 -- -- 152,975 -- -- 856,734 191,829 289,146 682,053 3,797,439 2005 226,544 303,607 2,385,461 -- -- -- -- -- 216,633 -- 1,005,226 962,054 201,548 299,225 685,624 3,900,461

432

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

U.S. Coal Exports" U.S. Coal Exports" "(short tons)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",3122664,2010882,3565711,5133546,5327583,-3.6 " Canada*",1773644,943061,2101534,2716705,3176066,-14.5 " Dominican Republic",51792,211736,124720,263528,312741,-15.7 " Honduras","-",41664,34161,41664,68124,-38.8 " Jamaica",25,36311,"-",36336,33585,8.2 " Mexico",1244972,777750,1268077,2022722,1698391,19.1 " Other**",52231,360,37219,52591,38676,36

433

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. U.S. Transformer Sustained Automatic Outage Counts and Hours by Cause Code and by NERC Region, 2012 B. U.S. Transformer Sustained Automatic Outage Counts and Hours by Cause Code and by NERC Region, 2012 Transformer Outage Counts Sustained Outage Causes FRCC MRO NPCC RFC SERC SPP TRE WECC Contiguous U.S. Weather, excluding lightning -- -- -- -- 1.00 -- -- -- 1.00 Lightning -- -- -- -- -- -- -- -- -- Environmental -- -- -- -- -- -- -- -- -- Contamination 1.00 -- -- -- -- -- -- -- 1.00 Foreign Interference -- -- -- -- -- -- -- -- -- Fire -- -- -- -- -- -- -- -- -- Vandalism, Terrorism, or Malicious Acts -- -- -- -- -- -- -- -- -- Failed AC Substation Equipment 3.00 1.00 -- 1.00 5.00 -- -- 4.00 14.00 Failed AC/DC Terminal Equipment -- -- -- -- -- -- -- -- -- Failed Protection System Equipment -- 1.00 -- -- 3.00 -- -- -- 4.00

434

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Net Summer Capacity of Utility Scale Units by Technology and by State, 2012 and 2011 (Megawatts) A. Net Summer Capacity of Utility Scale Units by Technology and by State, 2012 and 2011 (Megawatts) Census Division and State Renewable Sources Fossil Fuels Hydroelectric Pumped Storage Other Energy Storage Nuclear All Other Sources All Sources Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 4,157.7 3,805.2 24,619.1 24,153.6 1,753.4 1,709.4 3.0 3.0 4,630.3 4,653.7 48.0 26.0 35,211.5 34,350.9 Connecticut 294.7 299.9 6,607.7 6,674.5 29.4 29.4 0.0 0.0 2,102.5 2,102.5 26.0 26.0 9,060.3 9,132.3 Maine 1,704.5 1,640.8 2,764.9 2,737.4 0.0 0.0 0.0 0.0 0.0 0.0 22.0 0.0 4,491.4 4,378.2 Massachusetts 761.5 710.9 11,155.2 10,637.8 1,724.0 1,680.0 3.0 3.0 677.3 684.7 0.0 0.0 14,321.0 13,716.4

435

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

by State" by State" "(thousand short tons)" ,,,,"Year to Date" "Coal-Producing Region","April - June","January - March","April - June",2013,2012,"Percent" "and State",2013,2013,2012,,,"Change" "Alabama",4649,4410,5171,9059,10150,-10.8 "Alaska",442,300,542,742,1091,-32 "Arizona",2184,1825,2002,4009,4169,-3.8 "Arkansas",2,4,11,6,33,-83.1 "Colorado",5297,5781,6885,11079,13914,-20.4 "Illinois",13474,13996,12487,27470,24419,12.5 "Indiana",9516,9422,9147,18938,18794,0.8 "Kansas",5,5,5,9,8,23.7 "Kentucky Total",20683,20594,22803,41276,49276,-16.2 " Eastern (Kentucky)",10392,10144,12444,20536,27516,-25.4

436

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

0. Net Generation from Solar 0. Net Generation from Solar by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 35 7 427.1% 9 4 25 2 1 1 0 0 Connecticut 0 0 -- 0 0 0 0 0 0 0 0 Maine 0 0 -- 0 0 0 0 0 0 0 0 Massachusetts 30 5 521.6% 9 4 20 0.14 1 1 0 0 New Hampshire 0 0 -- 0 0 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 5 2 179.0% 0 0 5 2 0 0 0 0 Middle Atlantic 389 98 295.3% 41 19 303 65 37 8 8 5

437

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Winter Net Internal Demand, Capacity Resources, and Capacity Margins by North American Electric Reliability Assessment Area, A. Winter Net Internal Demand, Capacity Resources, and Capacity Margins by North American Electric Reliability Assessment Area, 2002 - 2012, Actual Net Internal Demand (Megawatts) -- Winter Eastern Interconnection ERCOT Western Interconnection All Interconnections Period FRCC NPCC Balance of Eastern Region ECAR MAAC MAIN MAPP MISO MRO PJM RFC SERC SPP TRE WECC Contiguous U.S. 2002 / 2003 42,001 45,980 360,748 84,844 46,159 39,974 -- -- 23,090 -- -- 137,541 29,140 44,719 94,554 588,002 2003 / 2004 36,229 47,850 357,026 86,332 45,625 39,955 -- -- 24,042 -- -- 133,244 27,828 41,988 100,337 583,430 2004 / 2005 41,449 47,859 371,011 91,800 45,565 40,618 -- -- 24,446 -- -- 139,486 29,096 44,010 101,002 605,331

438

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Coal Consumers in the Manufacturing and Coke Sectors, 2012" Coal Consumers in the Manufacturing and Coke Sectors, 2012" "Company Name","Plant Location" "Top Ten Manufacturers" "American Crystal Sugar Co","MN, ND" "Archer Daniels Midland","IA, IL, MN, ND, NE" "Carmeuse Lime Stone Inc","AL, IL, IN, KY, MI, OH, PA, TN, VA, WI" "Cemex Inc","AL, CA, CO, FL, GA, KY, OH, TN, TX" "Dakota Gasification Company","ND" "Eastman Chemical Company","TN" "Georgia-Pacific LLC","AL, GA, OK, VA, WI" "Holcim (US) Inc","AL, CO, MD, MO, MT, OK, SC, TX, UT" "NewPage Corporation","MD, MI, WI" "U S Steel Corporation","AL, IN, MI, MN"

439

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Net Generation from Renewable Sources: Commerical Sector, 2002 - 2012 B. Net Generation from Renewable Sources: Commerical Sector, 2002 - 2012 (Thousand Megawatthours) Period Wind Solar Photovoltaic Solar Thermal Wood and Wood-Derived Fuels Landfill Gas Biogenic Municipal Solid Waste Other Waste Biomass Geothermal Conventional Hydroelectric Total Renewable Sources Annual Totals 2002 0 N/A N/A 13 N/A N/A N/A 0 13 N/A 2003 0 0 0 13 152 717 420 0 72 1,374 2004 0 0 0 13 172 945 444 0 105 1,680 2005 0 0 0 16 218 953 486 0 86 1,759 2006 0 0 0 21 173 956 470 0 93 1,713 2007 0 0 0 15 203 962 434 0 77 1,691 2008 0 0.08 0 21 234 911 389 0 60 1,615 2009 0.21 0.04 0 20 318 1,045 386 0 71 1,839 2010 16 5 0 21 256 1,031 386 0 80 1,794 2011 51 84 0 26 952 971 393 0 26 2,502

440

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

4. Net Generation from Renewable Sources Excluding Hydroelectric 4. Net Generation from Renewable Sources Excluding Hydroelectric by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 8,557 8,015 6.8% 664 574 5,652 5,352 136 104 2,105 1,985 Connecticut 667 660 1.0% 0 0 667 660 0 0 0 0 Maine 4,099 4,495 -8.8% 0 0 2,468 2,421 92 89 1,539 1,985 Massachusetts 1,843 1,207 52.8% 68 48 1,198 1,145 11 13 566 0 New Hampshire 1,381 1,091 26.6% 347 291 1,003 800 31 0 0 0.35 Rhode Island 102 130 -21.8% 0 0 102 130 0 0 0 0

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441

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Average Quality of Coal Received at Manufacturing and Coke Plants by Census Division and State" 3. Average Quality of Coal Received at Manufacturing and Coke Plants by Census Division and State" ,,,,"Year to Date" "Census Division","April - June","January - March","April - June",2013,2012,"Percent" "and State1",2013,2013,2012,,,"Change" "New England" " Btu",13323,13196,13391,13253,13339,-0.6 " Sulfur",0.84,0.89,0.72,0.87,0.72,20.3 " Ash",5.95,5.81,5.93,5.87,6.09,-3.6 "Maine" " Btu","w","w","w","w","w","w" " Sulfur","w","w","w","w","w","w" " Ash","w","w","w","w","w","w"

442

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

9. Net Generation from Petroleum Coke 9. Net Generation from Petroleum Coke by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 0 0 -- 0 0 0 0 0 0 0 0 Connecticut 0 0 -- 0 0 0 0 0 0 0 0 Maine 0 0 -- 0 0 0 0 0 0 0 0 Massachusetts 0 0 -- 0 0 0 0 0 0 0 0 New Hampshire 0 0 -- 0 0 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0 Middle Atlantic 76 344 -78.0% 0 0 0 263 0 0 76 81 New Jersey 40 58 -30.6% 0 0 0 0 0 0 40 58

443

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

8. Net Generation from Petroleum Liquids 8. Net Generation from Petroleum Liquids by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 413 639 -35.4% 52 120 267 374 49 55 45 90 Connecticut 112 166 -32.6% 4 5 104 155 0.05 0 4 5 Maine 84 178 -52.8% 0.17 1 65 89 2 3 16 85 Massachusetts 174 197 -11.2% 15 40 98 128 37 28 25 NM New Hampshire 22 78 -72.1% 20 57 0.12 1 2 20 0.17 0.10 Rhode Island 18 14 31.0% 11 10 0.12 1 7 2 0 0 Vermont 3 8 -58.1% 2 6 0 0 1 2 0 0

444

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Average Number of Employees at Underground and Surface Mines by State and Union Status, 2012" Average Number of Employees at Underground and Surface Mines by State and Union Status, 2012" ,"Union",,"Nonunion" "Coal-Producing State","Underground","Surface","Underground","Surface" "and Region1" "Alabama",3044,70,89,1677 "Alaska","-",143,"-","-" "Arizona","-",432,"-","-" "Arkansas","-","-",70,"-" "Colorado",174,212,1858,261 "Illinois",647,58,3291,534 "Indiana","-","-",2054,1868 "Kentucky Total",564,93,10122,4595 " Kentucky (East)",48,93,6821,3943 " Kentucky (West)",516,"-",3301,652

445

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

A. Net Generation by Energy Source: Commerical Sector, 2002 - 2012 A. Net Generation by Energy Source: Commerical Sector, 2002 - 2012 (Thousand Megawatthours) Period Coal Petroleum Liquids Petroleum Coke Natural Gas Other Gas Nuclear Hydroelectric Conventional Renewable Sources Excluding Hydroelectric Hydroelectric Pumped Storage Other Total Annual Totals 2002 992 426 6 4,310 0.01 0 13 1,065 0 603 7,415 2003 1,206 416 8 3,899 0 0 72 1,302 0 594 7,496 2004 1,340 493 7 3,969 0 0 105 1,575 0 781 8,270 2005 1,353 368 7 4,249 0 0 86 1,673 0 756 8,492 2006 1,310 228 7 4,355 0.04 0 93 1,619 0 758 8,371 2007 1,371 180 9 4,257 0 0 77 1,614 0 764 8,273 2008 1,261 136 6 4,188 0 0 60 1,555 0 720 7,926 2009 1,096 157 5 4,225 0 0 71 1,769 0 842 8,165

446

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Average Number of Employees by State and Mine Type, 2012 and 2011" Average Number of Employees by State and Mine Type, 2012 and 2011" ,2012,,,2011,,,"Percent Change" "Coal-Producing","Underground","Surface","Total","Underground","Surface","Total","Underground","Surface","Total" "State and Region1" "Alabama",3190,1851,5041,3138,1618,4756,1.7,14.4,6 "Alaska","-",143,143,"-",136,136,"-",5.1,5.1 "Arizona","-",432,432,"-",419,419,"-",3.1,3.1 "Arkansas",70,3,73,67,3,70,4.5,"-",4.3 "Colorado",2032,473,2505,1927,478,2405,5.4,-1,4.2 "Illinois",3938,574,4512,3563,542,4105,10.5,5.9,9.9

447

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Capacity Utilization of Coal Mines by State, 2012 and 2011" Capacity Utilization of Coal Mines by State, 2012 and 2011" "(percent)" ,2012,,,2011 "Coal-Producing","Underground","Surface","Total","Underground","Surface","Total" "State" "Alabama",85.99,83.96,85.28,67.52,90.91,75.85 "Alaska","-","w","w","-","w","w" "Arizona","-","w","w","-","w","w" "Arkansas","w","-","w","w","-","w" "Colorado","w","w",76.65,"w","w",74.63 "Illinois",71.02,57.41,69.11,71.73,53.22,68.54

448

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. U.S. Coke Summary Statistics, 2007 - 2013" 2. U.S. Coke Summary Statistics, 2007 - 2013" "(thousand short tons)" "Year and","Production","Imports","Producer and","Consumption2","Exports" "Quarter",,,"Distributor" ,,,"Stocks1" 2007 " January - March",4000,454,717,4078,343 " April - June",4083,685,767,4428,291 " July - September",4063,521,637,4371,344 " October - December",4055,800,632,4394,466 " Total",16201,2460,,17270,1444 2008 " January - March",4036,850,478,4723,316 " April - June",3810,1243,505,4559,466 " July - September",4107,998,464,4494,653 " October - December",3694,512,916,3229,524

449

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Underground Coal Mining Productivity by State and Mining Method, 2012" 2. Underground Coal Mining Productivity by State and Mining Method, 2012" "(short tons produced per employee hour)" "Coal-Producing State, Region1 and Mine Type","Continuous2","Conventional and","Longwall4","Total" ,,"Other3" "Alabama",0.71,"-",1.69,1.66 "Arkansas",0.59,"-","-",0.59 "Colorado",1.9,"-",6.38,5.93 "Illinois",3.65,"-",6.6,4.86 "Indiana",3.25,"-","-",3.25 "Kentucky Total",2.43,1.77,"-",2.39 " Kentucky (East)",1.61,1.77,"-",1.62 " Kentucky (West)",3.61,"-","-",3.56 "Maryland",1.8,"-","-",1.8

450

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

1. Average Sales Price of Coal by State and Coal Rank, 2012" 1. Average Sales Price of Coal by State and Coal Rank, 2012" "(dollars per short ton)" "Coal-Producing State","Bituminous","Subbituminous","Lignite","Anthracite","Total" "Alabama",106.57,"-","-","-",106.57 "Alaska","-","w","-","-","w" "Arizona","w","-","-","-","w" "Arkansas","w","-","-","-","w" "Colorado","w","w","-","-",37.54 "Illinois",53.08,"-","-","-",53.08 "Indiana",52.01,"-","-","-",52.01

451

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Average Price of U.S. Coal Exports and Imports, 2007 - 2013" Average Price of U.S. Coal Exports and Imports, 2007 - 2013" "(dollars per short ton)" ,"January - March",,"April - June",,"July - September",,"October - December",,"Total" "Year","Exports","Imports","Exports","Imports","Exports","Imports","Exports","Imports","Exports","Imports" 2007,74.13,45.91,64.3,46.86,72.1,47.38,71.09,50.51,70.25,47.64 2008,81.81,52.91,97.24,55.59,102.51,64.65,104.97,65.33,97.68,59.83 2009,113.08,61.03,93.28,65.44,98.7,64.93,100.98,64.72,101.44,63.91 2010,106.52,62.02,121.36,71.91,125.45,77.12,126.16,76.18,120.41,71.77 2011,139.34,86,153,105.86,155.88,112.06,147.38,110.19,148.86,103.32

452

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

1. Coke and Breeze Stocks at Coke Plants by Census Division" 1. Coke and Breeze Stocks at Coke Plants by Census Division" "(thousand short tons)" "Census Division","April - June","January - March","April - June","Percent Change" ,2013,2013,2012,"(June 30)" ,,,,"2013 versus 2012" "Middle Atlantic","w","w","w","w" "East North Central",724,510,509,42.1 "South Atlantic","w","w","w","w" "East South Central","w","w","w","w" "U.S. Total",914,690,674,35.6 "Coke Total",757,573,594,27.5 "Breeze Total",157,117,80,95.2 "w = Data withheld to avoid disclosure."

453

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

5. Planned Generating Capacity Changes, by Energy Source, 2013-2017 5. Planned Generating Capacity Changes, by Energy Source, 2013-2017 Generator Additions Generator Retirements Net Capacity Additions Energy Source Number of Generators Net Summer Capacity Number of Generators Net Summer Capacity Number of Generators Net Summer Capacity 2013 U.S. Total 513 15,144 179 12,604 334 2,540 Coal 4 1,482 28 4,465 -24 -2,983 Petroleum 21 45 41 1,401 -20 -1,356 Natural Gas 87 6,818 55 2,950 32 3,868 Other Gases -- -- 1 4 -1 -4 Nuclear -- -- 4 3,576 -4 -3,576 Hydroelectric Conventional 17 385 36 185 -19 201 Wind 25 2,225 -- -- 25 2,225 Solar Thermal and Photovoltaic 277 3,460 1 1 276 3,459 Wood and Wood-Derived Fuels 10 489 -- -- 10 489 Geothermal 5 50 1 11 4 39

454

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Coal Production and Number of Mines by State and Mine Type, 2012 and 2011" Coal Production and Number of Mines by State and Mine Type, 2012 and 2011" "(thousand short tons)" ,2012,,2011,,"Percent Change" "Coal-Producing","Number of Mines","Production","Number of Mines","Production","Number of Mines","Production" "State and Region1" "Alabama",46,19321,52,19071,-11.5,1.3 " Underground",8,12570,9,10879,-11.1,15.5 " Surface",38,6752,43,8192,-11.6,-17.6 "Alaska",1,2052,1,2149,"-",-4.5 " Surface",1,2052,1,2149,"-",-4.5 "Arizona",1,7493,1,8111,"-",-7.6 " Surface",1,7493,1,8111,"-",-7.6 "Arkansas",2,98,2,133,"-",-26.4

455

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

8. Net Generation from Biomass 8. Net Generation from Biomass by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 7,229 7,138 1.3% 570 515 4,428 4,544 125 94 2,105 1,985 Connecticut 667 660 1.0% 0 0 667 660 0 0 0 0 Maine 3,212 3,788 -15.2% 0 0 1,581 1,714 92 89 1,539 1,985 Massachusetts 1,724 1,140 51.2% 0 0 1,157 1,137 1 3 566 0 New Hampshire 1,173 1,025 14.4% 347 291 795 734 31 0 0 0.35 Rhode Island 101 127 -21.1% 0 0 101 127 0 0 0 0

456

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Net Generation from Renewable Sources: Independent Power Producers, 2002 - 2012 B. Net Generation from Renewable Sources: Independent Power Producers, 2002 - 2012 (Thousand Megawatthours) Period Wind Solar Photovoltaic Solar Thermal Wood and Wood-Derived Fuels Landfill Gas Biogenic Municipal Solid Waste Other Waste Biomass Geothermal Conventional Hydroelectric Total Renewable Sources Annual Totals 2002 10,141 N/A N/A 8,300 N/A N/A N/A 13,089 18,189 N/A 2003 10,834 0 532 8,645 4,435 7,227 1,211 13,175 21,890 67,949 2004 13,739 0 569 8,528 4,377 6,978 884 13,563 19,518 68,154 2005 16,764 0 535 8,741 4,308 7,092 701 13,566 21,486 73,195 2006 24,238 0 493 8,404 4,771 7,259 774 13,406 24,390 83,736 2007 30,089 6 595 8,486 5,177 7,061 839 13,498 19,109 84,860 2008 48,464 60 787 8,750 6,057 6,975 1,040 13,643 23,451 109,226

457

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

7. Year-End Coal Stocks by Sector, Census Division, and State, 2012 and 2011" 7. Year-End Coal Stocks by Sector, Census Division, and State, 2012 and 2011" "(thousand short tons)" ,2012,,,,,2011,,,,,"Total" "Census Division","Electric","Other","Coke","Commercial","Producer","Electric","Other","Coke","Commercial","Producer",2012,2011,"Percent" "and State","Power1","Industrial",,"and","and","Power1","Industrial",,"and","and",,,"Change" ,,,,"Institutional","Distributor",,,,"Institutional","Distributor" "New England",1030,13,"-","-","-",1389,"w","-","-","-",1042,"w","w"

458

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Net Generation from Nuclear Energy 2. Net Generation from Nuclear Energy by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 36,116 34,283 5.3% 0 0 36,116 34,283 0 0 0 0 Connecticut 17,078 15,928 7.2% 0 0 17,078 15,928 0 0 0 0 Maine 0 0 -- 0 0 0 0 0 0 0 0 Massachusetts 5,860 5,085 15.2% 0 0 5,860 5,085 0 0 0 0 New Hampshire 8,189 8,363 -2.1% 0 0 8,189 8,363 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 4,989 4,907 1.7% 0 0 4,989 4,907 0 0 0 0

459

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

7. Net Generation from Coal 7. Net Generation from Coal by State, by Sector, 2012 and 2011 (Thousand Megawatthours) Electric Power Sector Census Division and State All Sectors Electric Utilities Independent Power Producers Commercial Sector Industrial Sector Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 4,103 6,848 -40.1% 1,268 2,208 2,793 4,592 0 0 42 47 Connecticut 653 526 24.2% 0 0 653 526 0 0 0 0 Maine 45 55 -18.0% 0 0 30 38 0 0 15 18 Massachusetts 2,137 4,059 -47.4% 0 0 2,110 4,029 0 0 27 30 New Hampshire 1,268 2,208 -42.6% 1,268 2,208 0 0 0 0 0 0 Rhode Island 0 0 -- 0 0 0 0 0 0 0 0 Vermont 0 0 -- 0 0 0 0 0 0 0 0

460

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

4. Nitrogen Oxides Control Technology Emissions Reduction Factors 4. Nitrogen Oxides Control Technology Emissions Reduction Factors Nitrogen Oxides Control Technology EIA-Code(s) Reduction Factor Advanced Overfire Air AA 30% Alternate Burners BF 20% Flue Gas Recirculation FR 40% Fluidized Bed Combustor CF 20% Fuel Reburning FU 30% Low Excess Air LA 20% Low NOx Burners LN 30% Other (or Unspecified) OT 20% Overfire Air OV 20% Selective Catalytic Reduction SR 70% Selective Catalytic Reduction With Low Nitrogen Oxide Burners SR and LN 90% Selective Noncatalytic Reduction SN 30% Selective Noncatalytic Reduction With Low NOx Burners SN and LN 50% Slagging SC 20% Notes: Starting with 1995 data, reduction factors for Advanced Overfire Air, Low NOx Burners, and Overfire Air were reduced by 10 percent.

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

2. Retail Sales and Direct Use of Electricity to Ultimate Customers 2. Retail Sales and Direct Use of Electricity to Ultimate Customers by Sector, by Provider, 2002 through 2012 (Megawatthours) Year Residential Commercial Industrial Transportation Other Total Direct Use Total End Use Total Electric Industry 2002 1,265,179,869 1,104,496,607 990,237,631 N/A 105,551,904 3,465,466,011 166,184,296 3,631,650,307 2003 1,275,823,910 1,198,727,601 1,012,373,247 6,809,728 N/A 3,493,734,486 168,294,526 3,662,029,012 2004 1,291,981,578 1,230,424,731 1,017,849,532 7,223,642 N/A 3,547,479,483 168,470,002 3,715,949,485 2005 1,359,227,107 1,275,079,020 1,019,156,065 7,506,321 N/A 3,660,968,513 150,015,531 3,810,984,044 2006 1,351,520,036 1,299,743,695 1,011,297,566 7,357,543 N/A 3,669,918,840 146,926,612 3,816,845,452

462

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

1. Total Electric Power Industry Summary Statistics, 2012 and 2011 1. Total Electric Power Industry Summary Statistics, 2012 and 2011 Net Generation and Consumption of Fuels for January through December Total (All Sectors) Electric Power Sector Commercial Industrial Electric Utilities Independent Power Producers Fuel Year 2012 Year 2011 Percentage Change Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Net Generation (Thousand Megawatthours) Coal 1,514,043 1,733,430 -12.7% 1,146,480 1,301,107 354,076 416,783 883 1,049 12,603 14,490 Petroleum Liquids 13,403 16,086 -16.7% 9,892 11,688 2,757 3,655 191 86 563 657 Petroleum Coke 9,787 14,096 -30.6% 5,664 9,428 1,758 3,431 6 3 2,359 1,234 Natural Gas 1,225,894 1,013,689 20.9% 504,958 414,843 627,833 511,447 6,603 5,487 86,500 81,911

463

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

9. Revenue from Retail Sales of Electricity to Ultimate Customers by End-Use Sector, 9. Revenue from Retail Sales of Electricity to Ultimate Customers by End-Use Sector, by State, 2012 and 2011 (Million Dollars) Residential Commercial Industrial Transportation All Sectors Census Division and State Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 Year 2012 Year 2011 New England 7,418 7,546 6,137 6,441 3,292 3,504 38 45 16,885 17,536 Connecticut 2,213 2,339 1,901 2,038 452 486 19 19 4,584 4,882 Maine 657 674 467 494 242 268 0 0 1,366 1,436 Massachusetts 3,029 3,003 2,453 2,547 2,127 2,270 17 22 7,627 7,842 New Hampshire 713 736 598 629 231 238 0 0 1,543 1,602 Rhode Island 450 449 432 453 99 103 2 4 982 1,008 Vermont 356 346 285 281 142 139 0 0 784 766

464

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

8. Receipts, Average Cost, and Quality of Fossil Fuels: Independent Power Producers, 2002 - 2012 (continued) 8. Receipts, Average Cost, and Quality of Fossil Fuels: Independent Power Producers, 2002 - 2012 (continued) Petroleum Coke Natural Gas All Fossil Fuels Receipts Average Cost Receipts Average Cost Average Cost Period (Billion Btu) (Thousand Tons) (Dollars per MMbtu) (Dollars per Ton) Average Sulfur Percent by Weight Percentage of Consumption (Billion Btu) (Thousand Mcf) (Dollars per MMBtu) (Dollars per Mcf) Percentage of Consumption (Dollars per MMBtu) Annual Totals 2002 47,805 1,639 1.03 29.98 4.85 44.4 3,198,108 3,126,308 3.55 3.63 91.6 2.42 2003 59,377 2,086 0.60 17.16 4.88 64.3 3,335,086 3,244,368 5.33 5.48 96.2 3.15 2004 73,745 2,609 0.72 20.30 4.95 81.0 3,491,942 3,403,474 5.86 6.01 93.1 3.43 2005 92,706 3,277 0.90 25.42 5.09 82.9 3,675,165 3,578,722 8.20 8.42 95.8 4.69

465

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

9. Coal Stocks at Other Industrial Plants by Census Division and State" 9. Coal Stocks at Other Industrial Plants by Census Division and State" "(thousand short tons)" "Census Division","June 30 2013","March 31 2013","June 30 2012","Percent Change" "and State",,,,"(June 30)" ,,,,"2013 versus 2012" "New England","w","w",21,"w" " Maine","w","w","w","w" " Massachusetts","w","w","w","w" "Middle Atlantic",295,251,286,3.2 " New York",137,78,107,27.6 " Pennsylvania",158,172,179,-11.5 "East North Central",734,692,761,-3.5 " Illinois",160,152,187,-14.1

466

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

4. Stocks of Coal by Coal Rank: Electric Power Sector, 2002 - 2012 4. Stocks of Coal by Coal Rank: Electric Power Sector, 2002 - 2012 Electric Power Sector Period Bituminous Coal Subbituminous Coal Lignite Coal Total End of Year Stocks 2002 70,704 66,593 4,417 141,714 2003 57,716 59,884 3,967 121,567 2004 49,022 53,618 4,029 106,669 2005 52,923 44,377 3,836 101,137 2006 67,760 68,408 4,797 140,964 2007 63,964 82,692 4,565 151,221 2008 65,818 91,214 4,556 161,589 2009 91,922 92,448 5,097 189,467 2010 81,108 86,915 6,894 174,917 2011 82,056 85,151 5,179 172,387 2012 86,437 93,833 4,846 185,116 2010, End of Month Stocks January 86,354 86,893 4,845 178,091 February 82,469 83,721 4,836 171,026 March 86,698 86,014 5,030 177,742 April 92,621 89,545 7,095 189,260 May 93,069 91,514 7,085 191,669

467

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

8. U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code" 8. U.S. Coal Receipts at Manufacturing Plants by North American Industry Classification System (NAICS) Code" "(thousand short tons)" ,,,,"Year to Date" "NAICS Code","April - June","January - March","April - June",2013,2012,"Percent" ,2013,2013,2012,,,"Change" "311 Food Manufacturing",2214,2356,1994,4570,4353,5 "312 Beverage and Tobacco Product Mfg.",48,37,53,85,90,-5.6 "313 Textile Mills",31,29,22,59,63,-6.1 "315 Apparel Manufacturing","w","w","w","w","w","w" "321 Wood Product Manufacturing","w","w","w","w","w","w"

468

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Average Price of U.S. Metallurgical Coal Exports" Average Price of U.S. Metallurgical Coal Exports" "(dollars per short ton)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Destination",2013,2013,2012,,,"Change" "North America Total",92.5,99.4,146.56,94.82,140.7,-32.6 " Canada*",99.83,125.2,142.46,106.43,138.19,-23 " Dominican Republic",114.6,77.21,"-",77.27,"-","-" " Mexico",78.93,78.54,180.76,78.77,153.65,-48.7 "South America Total",119.26,117.51,167.05,118.3,168.12,-29.6 " Argentina",146.7,131.08,182.47,137.36,196.37,-30.1 " Brazil",119.21,117.38,165.61,118.2,171.84,-31.2

469

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Coal Production by State, Mine Type, and Union Status, 2012" Coal Production by State, Mine Type, and Union Status, 2012" "(thousand short tons)" ,"Union",,"Nonunion",,"Total" "Coal-Producing","Underground","Surface","Underground","Surface","Underground","Surface" "State and Region1" "Alabama",12410,"-",139,6669,12549,6669 "Alaska","-",2052,"-","-","-",2052 "Arizona","-",7493,"-","-","-",7493 "Arkansas","-","-",96,"-",96,"-" "Colorado",1673,2655,21955,2265,23628,4920 "Illinois",2897,"-",39939,5649,42837,5649

470

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

B. Net Generation from Renewable Sources: Total (All Sectors), 2002 - 2012 B. Net Generation from Renewable Sources: Total (All Sectors), 2002 - 2012 (Thousand Megawatthours) Period Wind Solar Photovoltaic Solar Thermal Wood and Wood-Derived Fuels Landfill Gas Biogenic Municipal Solid Waste Other Waste Biomass Geothermal Conventional Hydroelectric Total Renewable Sources Annual Totals 2002 10,354 N/A N/A 38,665 N/A N/A N/A 14,491 264,329 N/A 2003 11,187 2 532 37,529 5,077 8,306 2,428 14,424 275,806 355,293 2004 14,144 6 569 38,117 5,128 8,151 2,141 14,811 268,417 351,485 2005 17,811 16 535 38,856 5,142 8,330 1,948 14,692 270,321 357,651 2006 26,589 15 493 38,762 5,677 8,478 1,944 14,568 289,246 385,772 2007 34,450 16 596 39,014 6,158 8,304 2,063 14,637 247,510 352,747

471

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

1. Sulfur Dioxide Uncontrolled Emission Factors 1. Sulfur Dioxide Uncontrolled Emission Factors Fuel, Code, Source and Emission Units Combustion System Type / Firing Configuration Fuel EIA Fuel Code Source and Tables (As Appropriate) Emissions Units Lbs = Pounds MMCF = Million Cubic Feet MG = Thousand Gallons Cyclone Boiler Fluidized Bed Boiler Opposed Firing Boiler Spreader Stoker Boiler Tangential Boiler All Other Boiler Types Combustion Turbine Internal Combustion Engine Agricultural Byproducts AB Source: 1 Lbs per ton 0.08 0.01 0.08 0.08 0.08 0.08 N/A N/A Blast Furnace Gas BFG Sources: 1 (including footnote 7 within source); 2, Table 1.4-2 (including footnote d within source) Lbs per MMCF 0.60 0.06 0.60 0.60 0.60 0.60 0.60 0.60 Bituminous Coal* BIT Source: 2, Table 1.1-3 Lbs per ton 38.00 3.80 38.00 38.00 38.00 38.00 N/A N/A

472

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Average Price of U.S. Coke Imports" Average Price of U.S. Coke Imports" "(dollars per short ton)" ,,,,"Year to Date" "Continent and Country","April - June","January - March","April - June",2013,2012,"Percent" "of Origin",2013,2013,2012,,,"Change" "North America Total",263.21,252.66,353.05,261.29,356.01,-26.6 " Canada",263.51,252.66,353.05,258.82,356.01,-27.3 " Panama",263.09,"-","-",263.09,"-","-" "South America Total",196.86,194.14,175.88,195.94,181.01,8.2 " Brazil","-","-",157.6,"-",157.6,"-" " Colombia",196.86,194.14,322.06,195.94,246.68,-20.6

473

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

1. Fuel-Switching Capacity of Operable Generators Reporting Natural Gas as the Primary Fuel, by Producer Type, 2012 1. Fuel-Switching Capacity of Operable Generators Reporting Natural Gas as the Primary Fuel, by Producer Type, 2012 (Megawatts, Percent) Fuel-Switchable Part of Total Producer Type Total Net Summer Capacity of All Generators Reporting Natural Gas as the Primary Fuel Net Summer Capacity of Natural Gas-Fired Generators Reporting the Ability to Switch to Petroleum Liquids Fuel Switchable Capacity as Percent of Total Maximum Achievable Net Summer Capacity Using Petroleum Liquids Fuel Switchable Net Summer Capacity Reported to Have No Factors that Limit the Ability to Switch to Petroleum Liquids Electric Utilities 206,774 78,346 37.9 74,835 23,624 Independent Power Producers, Non-Combined Heat and Power Plants 170,654 42,509 24.9 40,788 12,216

474

High Resolution Atmospheric Modeling for Wind Energy Applications  

SciTech Connect

The ability of the WRF atmospheric model to forecast wind speed over the Nysted wind park was investigated as a function of time. It was found that in the time period we considered (August 1-19, 2008), the model is able to predict wind speeds reasonably accurately for 48 hours ahead, but that its forecast skill deteriorates rapidly after 48 hours. In addition, a preliminary analysis was carried out to investigate the impact of vertical grid resolution on the forecast skill. Our preliminary finding is that increasing vertical grid resolution does not have a significant impact on the forecast skill of the WRF model over Nysted wind park during the period we considered. Additional simulations during this period, as well as during other time periods, will be run in order to validate the results presented here. Wind speed is a difficult parameter to forecast due the interaction of large and small length scale forcing. To accurately forecast the wind speed at a given location, the model must correctly forecast the movement and strength of synoptic systems, as well as the local influence of topography / land use on the wind speed. For example, small deviations in the forecast track or strength of a large-scale low pressure system can result in significant forecast errors for local wind speeds. The purpose of this study is to provide a preliminary baseline of a high-resolution limited area model forecast performance against observations from the Nysted wind park. Validating the numerical weather prediction model performance for past forecasts will give a reasonable measure of expected forecast skill over the Nysted wind park. Also, since the Nysted Wind Park is over water and some distance from the influence of terrain, the impact of high vertical grid spacing for wind speed forecast skill will also be investigated.

Simpson, M; Bulaevskaya, V; Glascoe, L; Singer, M

2010-03-18T23:59:59.000Z

475

Operational forecasting based on a modified Weather Research and Forecasting model  

SciTech Connect

Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

Lundquist, J; Glascoe, L; Obrecht, J

2010-03-18T23:59:59.000Z

476

InputĖoutput signal selection for damping of power system oscillations using wind power plants  

Science Journals Connector (OSTI)

Abstract During the last years wind power has emerged as one of the most important sources in the power generation share. Due to stringent Grid Code requirements, wind power plants (WPPs) should provide ancillary services such as fault ride-through and damping of power system oscillations to resemble conventional generation. Through an adequate selection of inputĖoutput signal pairs, \\{WPPs\\} can be effectively used to provide electromechanical oscillations damping. In this paper, different analysis techniques considering both controllability and observability measures and inputĖoutput interactions are compared and critically examined. Recommendations are drawn to select the best signal pairs available from \\{WPPs\\} to contribute to power oscillations damping. Control system design approaches including single-input single-output and multivariable control are considered. The recommendation of analysis techniques is justified through the tools usage in a test system including a WPP.

Josť Luis DomŪnguez-GarcŪa; Carlos E. Ugalde-Loo; Fernando Bianchi; Oriol Gomis-Bellmunt

2014-01-01T23:59:59.000Z

477

Formation and Spread of Aircraft-Induced Holes in Clouds  

Science Journals Connector (OSTI)

...cloud layer; a local sounding showed that...identified from local radiosondes, wind profilers, and...and Forecasting (WRF) model (10). The WRF model was configured...thermodynamic and wind conditions. The...surface and therefore local meteorology and...

Andrew J. Heymsfield; Gregory Thompson; Hugh Morrison; Aaron Bansemer; Roy M. Rasmussen; Patrick Minnis; Zhien Wang; Damao Zhang

2011-07-01T23:59:59.000Z

478

Central bank independence and the price-output-variability trade-off  

Science Journals Connector (OSTI)

Data on central bank independence (CBI) and implementation dates of CBI-reforms were used to investigate the relationship between CBI and a possible trade-off between inflation variability and output variability. No such trade-off was found, but there might still be stabilisation gains from CBI-reform.

Mats Landström

2014-01-01T23:59:59.000Z

479

Generalized Mercury/Waterfilling for Multiple-Input Multiple-Output Channels  

E-Print Network (OSTI)

Generalized Mercury/Waterfilling for Multiple-Input Multiple-Output Channels Fernando P procedure that generalizes the mercury/waterfilling algorithm, previously proposed for parallel non-interfering chan- nels. In this generalization the mercury level accounts for the sub- optimal (non-Gaussian) input

Verd√ļ, Sergio

480

SOLAR ENERGY (conditionally accepted 1/2010) QUANTIFYING PV POWER OUTPUT VARIABILITY  

E-Print Network (OSTI)

SOLAR ENERGY (conditionally accepted 1/2010) QUANTIFYING PV POWER OUTPUT VARIABILITY Thomas E create major problems that will require major mitigation efforts. #12;SOLAR ENERGY (conditionally industry believe it could constrain the penetration of gridconnected PV. The U.S. Department of Energy

Perez, Richard R.

Note: This page contains sample records for the topic "wrf model output" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

Information Technology and Intangible Output: The Impact of IT Investment on Innovation Productivity  

Science Journals Connector (OSTI)

Prior research concerning IT business value has established a link between firm-level IT investment and tangible returns such as output productivity. Research also suggests that IT is vital to intermediate processes such as those that produce intangible ... Keywords: IT business value, breakthrough innovation, information technology, innovation, knowledge production function, patents, productivity, research and development

Landon Kleis; Paul Chwelos; Ronald V. Ramirez; Iain Cockburn

2012-03-01T23:59:59.000Z

482

SHORT TERM PREDICTIONS FOR THE POWER OUTPUT OF ENSEMBLES OF WIND TURBINES AND PV-GENERATORS  

E-Print Network (OSTI)

SHORT TERM PREDICTIONS FOR THE POWER OUTPUT OF ENSEMBLES OF WIND TURBINES AND PV-GENERATORS Hans. For the conventional power park, the power production of the wind turbines presents a fluctuating 'negative load PRODUCTION OF WIND TURBINES For the forecast of the power production of wind turbines two approaches may

Heinemann, Detlev

483

Economic Input?Output Life-Cycle Assessment of Trade Between Canada and the United States  

Science Journals Connector (OSTI)

We use an economic input?output life-cycle assessment (EIO-LCA) technique to estimate the economy-wide energy intensity and greenhouse gas (GHG) emissions intensity for 45 manufacturing and resource sectors in Canada and the United States. ... Support?Activities?for?Agriculture ...

Jonathan Norman; Alex D. Charpentier; Heather L. MacLean

2007-01-23T23:59:59.000Z

484

Nuclear norm system identification with missing inputs and outputs Zhang Liua,  

E-Print Network (OSTI)

Nuclear norm system identification with missing inputs and outputs Zhang Liua, , Anders Hanssonb,1 formulation and uses the nuclear norm heuristic for structured low-rank matrix approximation, with the missing of the alternating direc- tion method of multipliers (ADMM) to solve regularized or non-regularized nuclear norm

Vandenberghe, Lieven

485

Handling Ambiguity via Input-Output Kernel Learning Xinxing Xu Ivor W. Tsang Dong Xu  

E-Print Network (OSTI)

of Computer Engineering, Nanyang Technological University, Singapore xuxi0006@ntu.edu.sg IvorTsang@ntu.edu.sg dongxu@ntu.edu.sg Abstract--Data ambiguities exist in many data mining and machine learning applications the effectiveness of our proposed IOKL framework. Keywords-Group Multiple Kernel Learning; Input-Output Kernel

Tsang Wai Hung "Ivor"

486

Uni-Traveling-Carrier Photodiodes with Increased Output Response and Low Intermodulation  

E-Print Network (OSTI)

Uni-Traveling-Carrier Photodiodes with Increased Output Response and Low Intermodulation Distortion-traveling-carrier photodiodes have been fabricated and tested to investigate the influence of the doping profile in several of the device layers on saturation characteristics and linearity. Two particular photodiode (PD) structures

Bowers, John

487

Development of Regional Wind Resource and Wind Plant Output Datasets for the Hawaiian Islands  

SciTech Connect

In March 2009, AWS Truepower was engaged by the National Renewable Energy Laboratory (NREL) to develop a set of wind resource and plant output data for the Hawaiian Islands. The objective of this project was to expand the methods and techniques employed in the Eastern Wind Integration and Transmission Study (EWITS) to include the state of Hawaii.

Manobianco, J.; Alonge, C.; Frank, J.; Brower, M.

2010-07-01T23:59:59.000Z

488

A comparison between raw EPS output, (modied) BMA and extended LR using ECMWF EPS precipitation reforecasts  

E-Print Network (OSTI)

A comparison between raw EPS output, (modied) BMA and extended LR using ECMWF EPS precipitation (EPS). 2. Data sets, statistical methods and predictand denitions The data sets used in this study [1 and precipitation data from a reforecasting exper- iment with the ECMWF EPS system. Figure 1: BMA-tted pdf of 24-h

Schmeits, Maurice

489

Abstract: Wind Energy Conversion Systems (WECS) produce fluctuating output power, which may cause voltage fluctuations and  

E-Print Network (OSTI)

Abstract: Wind Energy Conversion Systems (WECS) produce fluctuating output power, which may cause, solar energy conversion, virtual test bed simulation. Preprint Order Number: PE-531EC (02- plying its market-clearing mechanism. This mechanism determines the accepted and unaccepted energy bids

Gross, George

490

Greenland ice sheet surface mass balance variability (1988-2004) from calibrated Polar MM5 output*  

E-Print Network (OSTI)

1 Greenland ice sheet surface mass balance variability (1988-2004) from calibrated Polar MM5 output in Environmental Sciences, University of Colorado, Boulder, CO, USA 4 National Snow and Ice Data Center, University coherent regional patterns of Greenland ice sheet surface mass balance (SMB) change over a 17-year period

Howat, Ian M.

491

Sensorless Adaptive Output Feedback Control of Wind Energy Systems with PMS Generators  

E-Print Network (OSTI)

1 Sensorless Adaptive Output Feedback Control of Wind Energy Systems with PMS Generators A. El the problem of controlling wind energy conversion (WEC) systems involving permanent magnet synchronous is to maximize wind energy extraction which cannot be achieved without letting the wind turbine rotor operate

Boyer, Edmond

492

Using input-output techniques to address economic and energy issues in Malaysia  

E-Print Network (OSTI)

activities. Expand the basic activity: manufacturing into two activities: 1) high energy intensity 2) low energy intensity Assume they have equal share of output and their input structure is similar: Then assume? Assume electricity intensity: · high energy intensity 1.4 · low energy intensity 0.4 Now calculate

493

Shaping the output pulse of a linear-transformer-driver module W. A. Stygar,1  

E-Print Network (OSTI)

Shaping the output pulse of a linear-transformer-driver module W. A. Stygar,1 W. E. Fowler,1 K. R a linear-transformer- driver (LTD) module that drives an internal water-insulated transmission line-insulated radial-transmission-line impedance transformers [Phys. Rev. ST Accel. Beams 11, 030401 (2008)]. DOI: 10

494

Soliton quenching NLTL impulse circuit with a pulse forming network at the output  

DOE Patents (OSTI)

An impulse forming circuit is disclosed which produces a clean impulse from a nonlinear transmission line compressed step function without customary soliton ringing by means of a localized pulse shaping and differentiating network which shunts the nonlinear transmission line output to ground.

McEwan, Thomas E. (Livermore, CA); Dallum, Gregory E. (Livermore, CA)

1998-01-01T23:59:59.000Z

495

Soliton quenching NLTL impulse circuit with a pulse forming network at the output  

DOE Patents (OSTI)

An impulse forming circuit is disclosed which produces a clean impulse from a nonlinear transmission line compressed step function without customary soliton ringing by means of a localized pulse shaping and differentiating network which shunts the nonlinear transmission line output to ground. 5 figs.

McEwan, T.E.; Dallum, G.E.

1998-09-08T23:59:59.000Z

496

Improved thermoelectric power output from multilayered polyethylenimine doped carbon nanotube based organic composites  

SciTech Connect

By appropriately selecting the carbon nanotube type and n-type dopant for the conduction layers in a multilayered carbon nanotube composite, the total device thermoelectric power output can be increased significantly. The particular materials chosen in this study were raw single walled carbon nanotubes for the p-type layers and polyethylenimine doped single walled carbon nanotubes for the n-type layers. The combination of these two conduction layers leads to a single thermocouple Seebeck coefficient of 96 Ī 4??VK{sup ?1}, which is 6.3 times higher than that previously reported. This improved Seebeck coefficient leads to a total power output of 14.7 nW per thermocouple at the maximum temperature difference of 50?K, which is 44 times the power output per thermocouple for the previously reported results. Ultimately, these thermoelectric power output improvements help to increase the potential use of these lightweight, flexible, and durable organic multilayered carbon nanotube based thermoelectric modules in low powered electronics applications, where waste heat is available.

Hewitt, Corey A.; Montgomery, David S.; Barbalace, Ryan L.; Carlson, Rowland D.; Carroll, David L., E-mail: carroldl@wfu.edu [Center for Nanotechnology and Molecular Materials, Wake Forest University, 501 Deacon Blvd., Winston Salem, North Carolina 27105 (United States)

2014-05-14T23:59:59.000Z

497

On the use of fuzzy inference techniques in assessment models: part II: industrial applications  

Science Journals Connector (OSTI)

In this paper, we study the applicability of the monotone output property and the output resolution property in fuzzy assessment models to two industrial Failure Mode and Effect Analysis (FMEA) problems. First, t...

Kai Meng Tay; Chee Peng Lim

2008-09-01T23:59:59.000Z

498

Maximizing Power Output in Homogeneous Charge Compression Ignition (HCCI) Engines and Enabling Effective Control of Combustion Timing  

E-Print Network (OSTI)

Ford Motor Company, ďDiesel Engine Aftertreatment: How FordNational Laboratory, ďEngine Combustion NetworkĒ, http://High Power Output without Engine Knock and with Ultra-Low

Saxena, Samveg

2011-01-01T23:59:59.000Z

499

Maximizing Power Output in Homogeneous Charge Compression Ignition (HCCI) Engines and Enabling Effective Control of Combustion Timing  

E-Print Network (OSTI)

heat loss, while excessively delayed combustion timing (before misfire) can cause power output and efficiency losses because of incomplete oxidation of hydrocarbons

Saxena, Samveg

2011-01-01T23:59:59.000Z

500

U.S. Motor Vehicle Output and Other GDP, 1968-2007  

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Motor Vehicle Output and Other GDP, 1968-2007 Motor Vehicle Output and Other GDP, 1968-2007 Danilo J. Santini, Ph. D. Senior Economist Center for Transportation Research Argonne National Laboratory 9700 South Cass Avenue Phone: 630 252 3758 Fax: 630 252 3443 E-mail: dsantini@anl.gov David A Poyer, Ph.D. Associate Professor of Economics Morehouse College 830 Westview Dr. SW Atlanta, GA 30314 Phone: 404 681 2800, ext. 2553 E-mail: dpoyer@morehouse.edu THE 66th INTERNATIONAL ATLANTIC ECONOMIC CONFERENCE Montreal, Canada 9-12 October 2008 BUSINESS FLUCTUATIONS AND CYCLES 12 October 2008 Sunday 11:15 AM - 1:15 PM The submitted manuscript has been created by UChicago Argonne, LLC, Operator of Argonne National Laboratory ("Argonne"). Argonne, a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. . The U.S. Government