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We encourage you to perform a real-time search of NLEBeta
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1

Modeling of Uncertainty in Wind Energy Forecast  

E-Print Network [OSTI]

regression and splines are combined to model the prediction error from Tunø Knob wind power plant. This data of the thesis is quantile regression and splines in the context of wind power modeling. Lyngby, February 2006Modeling of Uncertainty in Wind Energy Forecast Jan Kloppenborg Møller Kongens Lyngby 2006 IMM-2006

2

Today's Forecast: Improved Wind Predictions | Department of Energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind...

3

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center  

E-Print Network [OSTI]

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at wind energy sites are becoming paramount. Regime-switching space-time (RST) models merge meteorological forecast regimes at the wind energy site and fits a conditional predictive model for each regime

Washington at Seattle, University of

4

Probabilistic wind power forecasting -European Wind Energy Conference -Milan, Italy, 7-10 May 2007 Probabilistic short-term wind power forecasting  

E-Print Network [OSTI]

Probabilistic wind power forecasting - European Wind Energy Conference - Milan, Italy, 7-10 May 2007 Probabilistic short-term wind power forecasting based on kernel density estimators J´er´emie Juban jeremie.juban@ensmp.fr; georges.kariniotakis@ensmp.fr Abstract Short-term wind power forecasting tools

Paris-Sud XI, Université de

5

Wind Energy Technology Trends: Comparing and Contrasting Recent Cost and Performance Forecasts (Poster)  

SciTech Connect (OSTI)

Poster depicts wind energy technology trends, comparing and contrasting recent cost and performance forecasts.

Lantz, E.; Hand, M.

2010-05-01T23:59:59.000Z

6

Review of Wind Energy Forecasting Methods for Modeling Ramping Events  

SciTech Connect (OSTI)

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

7

Wind Forecasting Improvement Project | Department of Energy  

Office of Environmental Management (EM)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergyENERGYWomen Owned SmallOf TheViolations | Department of EnergyisWilliamForecasting

8

European Wind Energy Conference -Brussels, Belgium, April 2008 Data mining for wind power forecasting  

E-Print Network [OSTI]

European Wind Energy Conference - Brussels, Belgium, April 2008 Data mining for wind power-term forecasting of wind energy produc- tion up to 2-3 days ahead is recognized as a major contribution the improvement of predic- tion systems performance is recognised as one of the priorities in wind energy research

Paris-Sud XI, Université de

9

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime-Switching  

E-Print Network [OSTI]

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at a wind energy site and fits a conditional predictive model for each regime. Geographically dispersed was applied to 2-hour-ahead forecasts of hourly average wind speed near the Stateline wind energy center

Genton, Marc G.

10

Test application of a semi-objective approach to wind forecasting for wind energy applications  

SciTech Connect (OSTI)

The test application of the semi-objective (S-O) wind forecasting technique at three locations is described. The forecasting sites are described as well as site-specific forecasting procedures. Verification of the S-O wind forecasts is presented, and the observed verification results are interpreted. Comparisons are made between S-O wind forecasting accuracy and that of two previous forecasting efforts that used subjective wind forecasts and model output statistics. (LEW)

Wegley, H.L.; Formica, W.J.

1983-07-01T23:59:59.000Z

11

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

12

European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind Generation by a Dynamic  

E-Print Network [OSTI]

European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind. Abstract-Short-term wind power forecasting is recognized nowadays as a major requirement for a secure and economic integration of wind power in a power system. In the case of large-scale integration, end users

Paris-Sud XI, Université de

13

Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy  

SciTech Connect (OSTI)

The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'), or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability. The downside is costs are higher. In organized electricity markets, units that are committed for reliability reasons are paid their offer price even when prevailing market prices are lower. Often, these uplift charges are allocated to market participants that caused the inefficient dispatch in the first place. Thus, wind energy facilities are burdened with their share of costs proportional to their forecast errors. For Xcel Energy, wind energy uncertainty costs manifest depending on specific market structures. In the Public Service of Colorado (PSCo), inefficient commitment and dispatch caused by wind uncertainty increases fuel costs. Wind resources participating in the Midwest Independent System Operator (MISO) footprint make substantial payments in the real-time markets to true-up their day-ahead positions and are additionally burdened with deviation charges called a Revenue Sufficiency Guarantee (RSG) to cover out of market costs associated with operations. Southwest Public Service (SPS) wind plants cause both commitment inefficiencies and are charged Southwest Power Pool (SPP) imbalance payments due to wind uncertainty and variability. Wind energy forecasting helps mitigate these costs. Wind integration studies for the PSCo and Northern States Power (NSP) operating companies have projected increasing costs as more wind is installed on the system due to forecast error. It follows that reducing forecast error would reduce these costs. This is echoed by large scale studies in neighboring regions and states that have recommended adoption of state-of-the-art wind forecasting tools in day-ahead and real-time planning and operations. Further, Xcel Energy concluded reduction of the normalized mean absolute error by one percent would have reduced costs in 2008 by over $1 million annually in PSCo alone. The value of reducing forecast error prompted Xcel Energy to make substantial investments in wind energy forecasting research and development.

Parks, K.; Wan, Y. H.; Wiener, G.; Liu, Y.

2011-10-01T23:59:59.000Z

14

MPC for Wind Power Gradients --Utilizing Forecasts, Rotor Inertia, and Central Energy Storage  

E-Print Network [OSTI]

MPC for Wind Power Gradients -- Utilizing Forecasts, Rotor Inertia, and Central Energy Storage iterations. We demonstrate our method in simulations with various wind scenarios and prices for energy. INTRODUCTION Today, wind power is the most important renewable energy source. For the years to come, many

15

The Wind Forecast Improvement Project (WFIP): A Public/Private...  

Energy Savers [EERE]

The Wind Forecast Improvement Project (WFIP): A PublicPrivate Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The...

16

The Value of Wind Power Forecasting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Wind Power Forecasting Preprint Debra Lew and Michael Milligan National Renewable Energy Laboratory Gary Jordan and Richard Piwko GE Energy Presented at the 91 st American...

17

Wind Speed Forecasting for Power System Operation  

E-Print Network [OSTI]

In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

Zhu, Xinxin

2013-07-22T23:59:59.000Z

18

Forecasting wind speed financial return  

E-Print Network [OSTI]

The prediction of wind speed is very important when dealing with the production of energy through wind turbines. In this paper, we show a new nonparametric model, based on semi-Markov chains, to predict wind speed. Particularly we use an indexed semi-Markov model that has been shown to be able to reproduce accurately the statistical behavior of wind speed. The model is used to forecast, one step ahead, wind speed. In order to check the validity of the model we show, as indicator of goodness, the root mean square error and mean absolute error between real data and predicted ones. We also compare our forecasting results with those of a persistence model. At last, we show an application of the model to predict financial indicators like the Internal Rate of Return, Duration and Convexity.

D'Amico, Guglielmo; Prattico, Flavio

2013-01-01T23:59:59.000Z

19

The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations the Northern Study Area.  

SciTech Connect (OSTI)

This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times. A comprehensive analysis of wind energy forecast errors for the various model-based power forecasts was presented for a suite of wind energy ramp definitions. The results compiled over the year-long study period showed that the power forecasts based on the research models (ESRL_RAP, HRRR) more accurately predict wind energy ramp events than the current operational forecast models, both at the system aggregate level and at the local wind plant level. At the system level, the ESRL_RAP-based forecasts most accurately predict both the total number of ramp events and the occurrence of the events themselves, but the HRRR-based forecasts more accurately predict the ramp rate. At the individual site level, the HRRR-based forecasts most accurately predicted the actual ramp occurrence, the total number of ramps and the ramp rates (40-60% improvement in ramp rates over the coarser resolution forecast

Finley, Cathy [WindLogics

2014-04-30T23:59:59.000Z

20

Today's Forecast: Improved Wind Predictions | Department of Energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassiveSubmittedStatusButler Tina ButlerToday in Energy Today in Energy!EIA's Today

Note: This page contains sample records for the topic "wind energy forecasts" 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

Wind Energy Management System Integration Project Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

SciTech Connect (OSTI)

The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. In this report, a new methodology to predict the uncertainty ranges for the required balancing capacity, ramping capability and ramp duration is presented. Uncertainties created by system load forecast errors, wind and solar forecast errors, generation forced outages are taken into account. The uncertainty ranges are evaluated for different confidence levels of having the actual generation requirements within the corresponding limits. The methodology helps to identify system balancing reserve requirement based on a desired system performance levels, identify system breaking points, where the generation system becomes unable to follow the generation requirement curve with the user-specified probability level, and determine the time remaining to these potential events. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (California ISO) real life data have shown the effectiveness of the proposed approach. A tool developed based on the new methodology described in this report will be integrated with the California ISO systems. Contractual work is currently in place to integrate the tool with the AREVA EMS system.

Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

2010-09-01T23:59:59.000Z

22

Value of Wind Power Forecasting  

SciTech Connect (OSTI)

This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.

2011-04-01T23:59:59.000Z

23

The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations the Southern Study Area  

SciTech Connect (OSTI)

This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP)--Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 3 hours.

Freedman, Jeffrey M.; Manobianco, John; Schroeder, John; Ancell, Brian; Brewster, Keith; Basu, Sukanta; Banunarayanan, Venkat; Hodge, Bri-Mathias; Flores, Isabel

2014-04-30T23:59:59.000Z

24

Wind Power Forecasting  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered energy consumption byAbout PrintableBlenderWhatFellows - PastFarmWind

25

Wind Forecast Improvement Project Southern Study Area Final Report...  

Office of Environmental Management (EM)

Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern...

26

Wind Power Forecasting Data  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste and MaterialsWenjun DengWISPWind Industry Soars to New1Wind

27

A survey on wind power ramp forecasting.  

SciTech Connect (OSTI)

The increasing use of wind power as a source of electricity poses new challenges with regard to both power production and load balance in the electricity grid. This new source of energy is volatile and highly variable. The only way to integrate such power into the grid is to develop reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly variable at several different timescales: sub-hourly, hourly, daily, and seasonally. Wind energy, like other electricity sources, must be scheduled. Although wind power forecasting methods are used, the ability to predict wind plant output remains relatively low for short-term operation. Because instantaneous electrical generation and consumption must remain in balance to maintain grid stability, wind power's variability can present substantial challenges when large amounts of wind power are incorporated into a grid system. A critical issue is ramp events, which are sudden and large changes (increases or decreases) in wind power. This report presents an overview of current ramp definitions and state-of-the-art approaches in ramp event forecasting.

Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J. (Decision and Information Sciences); (INESC Porto)

2011-02-23T23:59:59.000Z

28

Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging  

E-Print Network [OSTI]

distribution; Numerical weather prediction; Skewed distribution; Truncated data; Wind energy. 1. INTRODUCTION- native. Purely statistical methods have been applied to short-range forecasts for wind speed only a fewProbabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging J. Mc

Raftery, Adrian

29

EWEC 2006, Athens, The Anemos Wind Power Forecasting Platform Technology The Anemos Wind Power Forecasting Platform Technology -  

E-Print Network [OSTI]

EWEC 2006, Athens, The Anemos Wind Power Forecasting Platform Technology 1 The Anemos Wind Power a professional, flexible platform for operating wind power prediction models, laying the main focus on state models from all over Europe are able to work on this platform. Keywords: wind energy, wind power

Boyer, Edmond

30

New Concepts in Wind Power Forecasting Models  

E-Print Network [OSTI]

New Concepts in Wind Power Forecasting Models Vladimiro Miranda, Ricardo Bessa, João Gama, Guenter to the training of mappers such as neural networks to perform wind power prediction as a function of wind for more accurate short term wind power forecasting models has led to solid and impressive development

Kemner, Ken

31

Optimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts  

E-Print Network [OSTI]

bid is computed by exploiting the forecast energy price for the day ahead market, the historical wind renewable energy resources, such as wind and photovoltaic, has grown rapidly. It is well known the problem of optimizing energy bids for an independent Wind Power Producer (WPP) taking part

Giannitrapani, Antonello

32

Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations  

E-Print Network [OSTI]

Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations Audun Botterud://www.dis.anl.gov/projects/windpowerforecasting.html IAWind 2010 Ames, IA, April 6, 2010 #12;Outline Background Using wind power forecasts in market operations ­ Current status in U.S. markets ­ Handling uncertainties in system operations ­ Wind power

Kemner, Ken

33

Funding Opportunity Announcement for Wind Forecasting Improvement...  

Office of Environmental Management (EM)

to improved forecasts, system operators and industry professionals can ensure that wind turbines will operate at their maximum potential. Data collected during this field...

34

Upcoming Funding Opportunity for Wind Forecasting Improvement...  

Office of Environmental Management (EM)

to improved forecasts, system operators and industry professionals can ensure that wind turbines will operate at their maximum potential. Data collected during this field...

35

Development and Deployment of an Advanced Wind Forecasting Technique  

E-Print Network [OSTI]

findings. Part 2 addresses how operators of wind power plants and power systems can incorporate advanced the output of advanced wind energy forecasts into decision support models for wind power plant and power and applications of power market simulation models around the world. Argonne's software tools are used extensively

Kemner, Ken

36

QUIKSCAT MEASUREMENTS AND ECMWF WIND FORECASTS  

E-Print Network [OSTI]

. (2004) this forecast error was encountered when assimilating satellite measurements of zonal wind speeds between satellite measurements and meteorological forecasts of near-surface ocean winds. This type of covariance enters in assimilation techniques such as Kalman filtering. In all, six residual fields

Malmberg, Anders

37

QUIKSCAT MEASUREMENTS AND ECMWF WIND FORECASTS  

E-Print Network [OSTI]

. (2004) this forecast error was encountered when assimilating satellite measurements of zonal wind speeds between satellite measurements and meteorological forecasts of near­surface ocean winds. This type of covariance enters in assimilation techniques such as Kalman filtering. In all, six residual fields

Malmberg, Anders

38

PSO (FU 2101) Ensemble-forecasts for wind power  

E-Print Network [OSTI]

PSO (FU 2101) Ensemble-forecasts for wind power Analysis of the Results of an On-line Wind Power Ensemble- forecasts for wind power (FU2101) a demo-application producing quantile forecasts of wind power correct) quantile forecasts of the wind power production are generated by the application. However

39

The effects of energy storage properties and forecast accuracy on mitigating variability in wind power generation  

E-Print Network [OSTI]

Electricity generation from wind power is increasing worldwide. Wind power can offset traditional fossil fuel generators which is beneficial to the environment. However, wind generation is unpredictable. Wind speeds have ...

Jaworsky, Christina A

2013-01-01T23:59:59.000Z

40

Optimal combined wind power forecasts using exogeneous variables  

E-Print Network [OSTI]

Optimal combined wind power forecasts using exogeneous variables Fannar ¨Orn Thordarson Kongens of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

Note: This page contains sample records for the topic "wind energy forecasts" 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

Distribution of Wind Power Forecasting Errors from Operational Systems (Presentation)  

SciTech Connect (OSTI)

This presentation offers new data and statistical analysis of wind power forecasting errors in operational systems.

Hodge, B. M.; Ela, E.; Milligan, M.

2011-10-01T23:59:59.000Z

42

Use of wind power forecasting in operational decisions.  

SciTech Connect (OSTI)

The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help efficiently address this challenge, and significant efforts have been invested in developing more accurate wind power forecasts. In this report, we document our work on the use of wind power forecasting in operational decisions.

Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V. (Decision and Information Sciences); (INESC Porto)

2011-11-29T23:59:59.000Z

43

Managing Wind Power Forecast Uncertainty in Electric Grids.  

E-Print Network [OSTI]

??Electricity generated from wind power is both variable and uncertain. Wind forecasts provide valuable information for wind farm management, but they are not perfect. Chapter (more)

Mauch, Brandon Keith

2012-01-01T23:59:59.000Z

44

Subhourly wind forecasting techniques for wind turbine operations  

SciTech Connect (OSTI)

Three models for making automated forecasts of subhourly wind and wind power fluctuations were examined to determine the models' appropriateness, accuracy, and reliability in wind forecasting for wind turbine operation. Such automated forecasts appear to have value not only in wind turbine control and operating strategies, but also in improving individual wind turbine control and operating strategies, but also in improving individual wind turbine operating strategies (such as determining when to attempt startup). A simple persistence model, an autoregressive model, and a generalized equivalent Markhov (GEM) model were developed and tested using spring season data from the WKY television tower located near Oklahoma City, Oklahoma. The three models represent a pure measurement approach, a pure statistical method and a statistical-dynamical model, respectively. Forecasting models of wind speed means and measures of deviations about the mean were developed and tested for all three forecasting techniques for the 45-meter level and for the 10-, 30- and 60-minute time intervals. The results of this exploratory study indicate that a persistence-based approach, using onsite measurements, will probably be superior in the 10-minute time frame. The GEM model appears to have the most potential in 30-minute and longer time frames, particularly when forecasting wind speed fluctuations. However, several improvements to the GEM model are suggested. In comparison to the other models, the autoregressive model performed poorly at all time frames; but, it is recommended that this model be upgraded to an autoregressive moving average (ARMA or ARIMA) model. The primary constraint in adapting the forecasting models to the production of wind turbine cluster power output forecasts is the lack of either actual data, or suitable models, for simulating wind turbine cluster performance.

Wegley, H.L.; Kosorok, M.R.; Formica, W.J.

1984-08-01T23:59:59.000Z

45

PSO (FU 2101) Ensemble-forecasts for wind power  

E-Print Network [OSTI]

PSO (FU 2101) Ensemble-forecasts for wind power Wind Power Ensemble Forecasting Using Wind Speed the problems of (i) transforming the meteorological ensembles to wind power ensembles and, (ii) correcting) data. However, quite often the actual wind power production is outside the range of ensemble forecast

46

Verification of hourly forecasts of wind turbine power output  

SciTech Connect (OSTI)

A verification of hourly average wind speed forecasts in terms of hourly average power output of a MOD-2 was performed for four sites. Site-specific probabilistic transformation models were developed to transform the forecast and observed hourly average speeds to the percent probability of exceedance of an hourly average power output. (This transformation model also appears to have value in predicting annual energy production for use in wind energy feasibility studies.) The transformed forecasts were verified in a deterministic sense (i.e., as continuous values) and in a probabilistic sense (based upon the probability of power output falling in a specified category). Since the smoothing effects of time averaging are very pronounced, the 90% probability of exceedance was built into the transformation models. Semiobjective and objective (model output statistics) forecasts were made compared for the four sites. The verification results indicate that the correct category can be forecast an average of 75% of the time over a 24-hour period. Accuracy generally decreases with projection time out to approx. 18 hours and then may increase due to the fairly regular diurnal wind patterns that occur at many sites. The ability to forecast the correct power output category increases with increasing power output because occurrences of high hourly average power output (near rated) are relatively rare and are generally not forecast. The semiobjective forecasts proved superior to model output statistics in forecasting high values of power output and in the shorter time frames (1 to 6 hours). However, model output statistics were slightly more accurate at other power output levels and times. Noticeable differences were observed between deterministic and probabilistic (categorical) forecast verification results.

Wegley, H.L.

1984-08-01T23:59:59.000Z

47

Value of Improved Wind Power Forecasting in the Western Interconnection (Poster)  

SciTech Connect (OSTI)

Wind power forecasting is a necessary and important technology for incorporating wind power into the unit commitment and dispatch process. It is expected to become increasingly important with higher renewable energy penetration rates and progress toward the smart grid. There is consensus that wind power forecasting can help utility operations with increasing wind power penetration; however, there is far from a consensus about the economic value of improved forecasts. This work explores the value of improved wind power forecasting in the Western Interconnection of the United States.

Hodge, B.

2013-12-01T23:59:59.000Z

48

Forecastability as a Design Criterion in Wind Resource Assessment: Preprint  

SciTech Connect (OSTI)

This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

Zhang, J.; Hodge, B. M.

2014-04-01T23:59:59.000Z

49

Probabilistic Wind Speed Forecasting using Ensembles and Bayesian Model Averaging  

E-Print Network [OSTI]

is to issue deterministic forecasts based on numerical weather prediction models. Uncertainty canProbabilistic Wind Speed Forecasting using Ensembles and Bayesian Model Averaging J. Mc discretization than is seen in other weather quantities. The prevailing paradigm in weather forecasting

Washington at Seattle, University of

50

Economic Evaluation of Short-Term Wind Power Forecasts in ERCOT: Preliminary Results; Preprint  

SciTech Connect (OSTI)

Historically, a number of wind energy integration studies have investigated the value of using day-ahead wind power forecasts for grid operational decisions. These studies have shown that there could be large cost savings gained by grid operators implementing the forecasts in their system operations. To date, none of these studies have investigated the value of shorter-term (0 to 6-hour-ahead) wind power forecasts. In 2010, the Department of Energy and National Oceanic and Atmospheric Administration partnered to fund improvements in short-term wind forecasts and to determine the economic value of these improvements to grid operators, hereafter referred to as the Wind Forecasting Improvement Project (WFIP). In this work, we discuss the preliminary results of the economic benefit analysis portion of the WFIP for the Electric Reliability Council of Texas. The improvements seen in the wind forecasts are examined, then the economic results of a production cost model simulation are analyzed.

Orwig, K.; Hodge, B. M.; Brinkman, G.; Ela, E.; Milligan, M.; Banunarayanan, V.; Nasir, S.; Freedman, J.

2012-09-01T23:59:59.000Z

51

Wind Energy  

Broader source: Energy.gov [DOE]

Presentation covers wind energy at the Federal Utility Partnership Working Group (FUPWG) meeting, held on November 18-19, 2009.

52

Wind Power Forecasting Error Distributions over Multiple Timescales (Presentation)  

SciTech Connect (OSTI)

This presentation presents some statistical analysis of wind power forecast errors and error distributions, with examples using ERCOT data.

Hodge, B. M.; Milligan, M.

2011-07-01T23:59:59.000Z

53

Skill forecasting from different wind power ensemble prediction methods This article has been downloaded from IOPscience. Please scroll down to see the full text article.  

E-Print Network [OSTI]

Skill forecasting from different wind power ensemble prediction methods This article has been Contact us My IOPscience #12;Skill forecasting from different wind power ensemble prediction methods uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation

Paris-Sud XI, Université de

54

Accuracy of near real time updates in wind power forecasting  

E-Print Network [OSTI]

· advantage: no NWP data necessary ­ very actual shortest term forecasts possible · wind power inputAccuracy of near real time updates in wind power forecasting with regard to different weather October 2007 #12;EMS/ECAM 2007 ­ Nadja Saleck Outline · Study site · Wind power forecasting - method

Heinemann, Detlev

55

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

56

ENERGY DEMAND FORECAST METHODS REPORT  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400 .......................................................................................................................................1-1 ENERGY DEMAND FORECASTING AT THE CALIFORNIA ENERGY COMMISSION: AN OVERVIEW

57

Forecasting of wind speed using wavelets analysis and cascade-correlation neural networks  

E-Print Network [OSTI]

for the city of Perpignan (south of France). In this sense, forecasting average wind speeds was the main such as sunlight, wind, rain or geothermal heat. Wind energy is actually one of the fastest-growing forms of electricity generation because wind is a clean, indigenous and inexhaustible energy resource that can generate

Paris-Sud XI, Université de

58

Gaussian Processes for Short-Horizon Wind Power Forecasting Joseph Bockhorst, Chris Barber  

E-Print Network [OSTI]

on this task, and attention has shifted to statistical and machine learning approaches. Among the challenges of wind energy into electrical trans- mission systems. The importance of wind forecasts for wind energy throughout a power system must be nearly in balance at all times, 2) because it depends strongly on wind

Bockhorst, Joseph

59

New Forecasting Tools Enhance Wind Energy Integration In Idaho and Oregon  

Office of Environmental Management (EM)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergyENERGY TAXBalanced Scorecard Federal2Energy SecondWells |Energy Services » NewNew

60

Solar Wind Forecasting with Coronal Holes  

E-Print Network [OSTI]

An empirical model for forecasting solar wind speed related geomagnetic events is presented here. The model is based on the estimated location and size of solar coronal holes. This method differs from models that are based on photospheric magnetograms (e.g., Wang-Sheeley model) to estimate the open field line configuration. Rather than requiring the use of a full magnetic synoptic map, the method presented here can be used to forecast solar wind velocities and magnetic polarity from a single coronal hole image, along with a single magnetic full-disk image. The coronal hole parameters used in this study are estimated with Kitt Peak Vacuum Telescope He I 1083 nm spectrograms and photospheric magnetograms. Solar wind and coronal hole data for the period between May 1992 and September 2003 are investigated. The new model is found to be accurate to within 10% of observed solar wind measurements for its best one-month periods, and it has a linear correlation coefficient of ~0.38 for the full 11 years studied. Using a single estimated coronal hole map, the model can forecast the Earth directed solar wind velocity up to 8.5 days in advance. In addition, this method can be used with any source of coronal hole area and location data.

S. Robbins; C. J. Henney; J. W. Harvey

2007-01-09T23:59:59.000Z

Note: This page contains sample records for the topic "wind energy forecasts" 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

Forecasting Uncertainty Related to Ramps of Wind Power Production  

E-Print Network [OSTI]

- namic reserve quantification [8], for the optimal oper- ation of combined wind-hydro power plants [5, 1Forecasting Uncertainty Related to Ramps of Wind Power Production Arthur Bossavy, Robin Girard - The continuous improvement of the accuracy of wind power forecasts is motivated by the increasing wind power

Boyer, Edmond

62

Energy Department Announces $2.5 Million to Improve Wind Forecasting |  

Broader source: Energy.gov (indexed) [DOE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergyENERGYWomentheATLANTA, GA5 & 6, 2012 MEETING OFCalifornia ConcentratingDepartment of

63

Wind power forecasting in U.S. electricity markets.  

SciTech Connect (OSTI)

Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts.

Botterud, A.; Wang, J.; Miranda, V.; Bessa, R. J.; Decision and Information Sciences; INESC Porto

2010-04-01T23:59:59.000Z

64

Wind power forecasting in U.S. Electricity markets  

SciTech Connect (OSTI)

Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts. (author)

Botterud, Audun; Wang, Jianhui; Miranda, Vladimiro; Bessa, Ricardo J.

2010-04-15T23:59:59.000Z

65

Advanced statistical methods for shortterm wind power forecasting Research proposal draft  

E-Print Network [OSTI]

a promising Monte­Carlo training scheme (Neal 1995) to data from the wind­energy industry, with some successAdvanced statistical methods for short­term wind power forecasting Research proposal draft Alex 1994), but more powerful nonlinear techniques have received little attention (MacKay 1995). In the wind­energy

Barnett, Alex

66

WIND ENERGY Wind Energ. (2014)  

E-Print Network [OSTI]

WIND ENERGY Wind Energ. (2014) Published online in Wiley Online Library (wileyonlinelibrary Correspondence M. Wächter, ForWind-Center for Wind Energy Research, Institute of Physics, Carl Von Ossietzky on the operation of wind energy converters (WECs) imposing different risks especially in terms of highly dynamic

Peinke, Joachim

67

Investigating the Correlation Between Wind and Solar Power Forecast Errors in the Western Interconnection: Preprint  

SciTech Connect (OSTI)

Wind and solar power generations differ from conventional energy generation because of the variable and uncertain nature of their power output. This variability and uncertainty can have significant impacts on grid operations. Thus, short-term forecasting of wind and solar generation is uniquely helpful for power system operations to balance supply and demand in an electricity system. This paper investigates the correlation between wind and solar power forecasting errors.

Zhang, J.; Hodge, B. M.; Florita, A.

2013-05-01T23:59:59.000Z

68

Wind Power Forecasting Error Distributions: An International Comparison; Preprint  

SciTech Connect (OSTI)

Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

Hodge, B. M.; Lew, D.; Milligan, M.; Holttinen, H.; Sillanpaa, S.; Gomez-Lazaro, E.; Scharff, R.; Soder, L.; Larsen, X. G.; Giebel, G.; Flynn, D.; Dobschinski, J.

2012-09-01T23:59:59.000Z

69

Ramp Forecasting Performance from Improved Short-Term Wind Power Forecasting: Preprint  

SciTech Connect (OSTI)

The variable and uncertain nature of wind generation presents a new concern to power system operators. One of the biggest concerns associated with integrating a large amount of wind power into the grid is the ability to handle large ramps in wind power output. Large ramps can significantly influence system economics and reliability, on which power system operators place primary emphasis. The Wind Forecasting Improvement Project (WFIP) was performed to improve wind power forecasts and determine the value of these improvements to grid operators. This paper evaluates the performance of improved short-term wind power ramp forecasting. The study is performed for the Electric Reliability Council of Texas (ERCOT) by comparing the experimental WFIP forecast to the current short-term wind power forecast (STWPF). Four types of significant wind power ramps are employed in the study; these are based on the power change magnitude, direction, and duration. The swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental short-term wind power forecasts improve the accuracy of the wind power ramp forecasting, especially during the summer.

Zhang, J.; Florita, A.; Hodge, B. M.; Freedman, J.

2014-05-01T23:59:59.000Z

70

Wind Power Forecasting: State-of-the-Art 2009  

E-Print Network [OSTI]

Wind Power Forecasting: State-of-the-Art 2009 ANL/DIS-10-1 Decision and Information Sciences about Argonne and its pioneering science and technology programs, see www.anl.gov. #12;Wind Power

Kemner, Ken

71

Skill forecasting from ensemble predictions of wind power P. Pinson,a  

E-Print Network [OSTI]

Skill forecasting from ensemble predictions of wind power P. Pinson,a , H.Aa. Nielsena , H. Madsena with the commonly provided short-term wind power point predictions. Alternative approaches for the use uncertainty (and potential energy imbalances). Wind power ensemble predictions are derived from the conversion

Paris-Sud XI, Université de

72

Powering Up With Space-Time Wind Forecasting Amanda S. HERING and Marc G. GENTON  

E-Print Network [OSTI]

Powering Up With Space-Time Wind Forecasting Amanda S. HERING and Marc G. GENTON The technology to harvest electricity from wind energy is now advanced enough to make entire cities powered by it a reality be more realistically assessed with a loss measure that depends upon the power curve relating wind speed

Genton, Marc G.

73

Wind Energy Leasing Handbook  

E-Print Network [OSTI]

Wind Energy Leasing Handbook Wind Energy Leasing Handbook E-1033 Oklahoma Cooperative Extension?..................................................................................................................... 31 What do wind developers consider in locating wind energy projects?............................................................................................ 37 How do companies and individuals invest in wind energy projects?....................................................................

Balasundaram, Balabhaskar "Baski"

74

20% Wind Energy 20% Wind Energy  

E-Print Network [OSTI]

(government, industry, utilities, NGOs) Analyzes wind's potential contributions to energy security, economic · Transmission a challenge #12;Wind Power Class Resource Potential Wind Power Density at 50 m W/m 2 Wind Speed20% Wind Energy by 2030 20% Wind Energy by 2030 #12;Presentation and Objectives Overview Background

Powell, Warren B.

75

Wind power forecasting : state-of-the-art 2009.  

SciTech Connect (OSTI)

Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and uncertainty in wind power and to more efficiently operate power systems with large wind power penetrations. Moreover, in a market environment, the wind power contribution to the generation portofolio becomes important in determining the daily and hourly prices, as variations in the estimated wind power will influence the clearing prices for both energy and operating reserves. With the increasing penetration of wind power, WPF is quickly becoming an important topic for the electric power industry. System operators (SOs), generating companies (GENCOs), and regulators all support efforts to develop better, more reliable and accurate forecasting models. Wind farm owners and operators also benefit from better wind power prediction to support competitive participation in electricity markets against more stable and dispatchable energy sources. In general, WPF can be used for a number of purposes, such as: generation and transmission maintenance planning, determination of operating reserve requirements, unit commitment, economic dispatch, energy storage optimization (e.g., pumped hydro storage), and energy trading. The objective of this report is to review and analyze state-of-the-art WPF models and their application to power systems operations. We first give a detailed description of the methodologies underlying state-of-the-art WPF models. We then look at how WPF can be integrated into power system operations, with specific focus on the unit commitment problem.

Monteiro, C.; Bessa, R.; Miranda, V.; Botterud, A.; Wang, J.; Conzelmann, G.; Decision and Information Sciences; INESC Porto

2009-11-20T23:59:59.000Z

76

Comparison of Wind Power and Load Forecasting Error Distributions: Preprint  

SciTech Connect (OSTI)

The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent System Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.

Hodge, B. M.; Florita, A.; Orwig, K.; Lew, D.; Milligan, M.

2012-07-01T23:59:59.000Z

77

WIND POWER ENSEMBLE FORECASTING Henrik Aalborg Nielsen1  

E-Print Network [OSTI]

WIND POWER ENSEMBLE FORECASTING Henrik Aalborg Nielsen1 , Henrik Madsen1 , Torben Skov Nielsen1. In this paper we address the problems of (i) transforming the mete- orological ensembles to wind power ensembles the uncertainty which follow from historical (climatological) data. However, quite often the actual wind power

78

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand.Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product estimates. Margaret Sheridan provided the residential forecast. Mitch Tian prepared the peak demand

79

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Robert P. Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined provided estimates for demand response program impacts and contributed to the residential forecast. Mitch

80

Status of Centralized Wind Power Forecasting in North America: May 2009-May 2010  

SciTech Connect (OSTI)

Report surveys grid wind power forecasts for all wind generators, which are administered by utilities or regional transmission organizations (RTOs), typically with the assistance of one or more wind power forecasting companies.

Porter, K.; Rogers, J.

2010-04-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind energy forecasts" 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

Development and testing of improved statistical wind power forecasting methods.  

SciTech Connect (OSTI)

Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J. (Decision and Information Sciences); (INESC Porto)

2011-12-06T23:59:59.000Z

82

TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY  

E-Print Network [OSTI]

has developed longterm forecasts of transportation energy demand as well as projected ranges of transportation fuel and crude oil import requirements. The transportation energy demand forecasts makeCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY

83

Seasonal Forecasting of Extreme Wind and Precipitation Frequencies in Europe  

E-Print Network [OSTI]

Seasonal Forecasting of Extreme Wind and Precipitation Frequencies in Europe Matthew J. Swann;Abstract Flood and wind damage to property and livelihoods resulting from extreme precipitation events variability of these extreme events can be closely related to the large-scale atmospheric circulation

Feigon, Brooke

84

Matter & Energy Wind Energy  

E-Print Network [OSTI]

See Also: Matter & Energy Wind Energy Energy Technology Physics Nuclear Energy Petroleum 27, 2012) -- Energy flowing from large-scale to small-scale places may be prevented from flowing, indicating that there are energy flows from large to small scale in confined space. Indeed, under a specific

Shepelyansky, Dima

85

CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST Demand Forecast report is the product of the efforts of many current and former California Energy-2 Demand Forecast Disaggregation......................................................1-4 Statewide

86

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work to the residential forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid provided the projections

87

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network [OSTI]

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work and expertise of numerous the residential forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid provided the projections

88

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network [OSTI]

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work Sheridan provided the residential forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid

89

Wind energy systems: program summary  

SciTech Connect (OSTI)

The Federal Wind Energy Program (FWEP) was initiated to provide focus, direction and funds for the development of wind power. Each year a summary is prepared to provide the American public with an overview of government sponsored activities in the FWEP. This program summary describes each of the Department of Energy's (DOE) current wind energy projects initiated or renewed during FY 1979 (October 1, 1978 through September 30, 1979) and reflects their status as of April 30, 1980. The summary highlights on-going research, development and demonstration efforts and serves as a record of progress towards the program objectives. It also provides: the program's general management structure; review of last year's achievements; forecast of expected future trends; documentation of the projects conducted during FY 1979; and list of key wind energy publications.

None

1980-05-01T23:59:59.000Z

90

Wind energy bibliography  

SciTech Connect (OSTI)

This bibliography is designed to help the reader search for information on wind energy. The bibliography is intended to help several audiences, including engineers and scientists who may be unfamiliar with a particular aspect of wind energy, university researchers who are interested in this field, manufacturers who want to learn more about specific wind topics, and librarians who provide information to their clients. Topics covered range from the history of wind energy use to advanced wind turbine design. References for wind energy economics, the wind energy resource, and environmental and institutional issues related to wind energy are also included.

None

1995-05-01T23:59:59.000Z

91

Impacts of Improved Day-Ahead Wind Forecasts on Power Grid Operations: September 2011  

SciTech Connect (OSTI)

This study analyzed the potential benefits of improving the accuracy (reducing the error) of day-ahead wind forecasts on power system operations, assuming that wind forecasts were used for day ahead security constrained unit commitment.

Piwko, R.; Jordan, G.

2011-11-01T23:59:59.000Z

92

Intra-hour wind power variability assessment using the conditional range metric : quantification, forecasting and applications.  

E-Print Network [OSTI]

??The research presented herein concentrates on the quantification, assessment and forecasting of intra-hour wind power variability. Wind power is intrinsically variable and, due to the (more)

Boutsika, Thekla

2013-01-01T23:59:59.000Z

93

Central Wind Power Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities  

SciTech Connect (OSTI)

The report addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America.

Porter, K.; Rogers, J.

2009-12-01T23:59:59.000Z

94

Short-term Wind Power Forecasting Using Advanced Statistical T.S. Nielsen1  

E-Print Network [OSTI]

Short-term Wind Power Forecasting Using Advanced Statistical Methods T.S. Nielsen1 , H. Madsen1 , H considered in the ANEMOS project for short-term fore- casting of wind power. The total procedure typically in for prediction of wind power or wind speed, estimating the uncertainty of the wind power forecast, and finally

Paris-Sud XI, Université de

95

Optimal Storage Policies with Wind Forecast Uncertainties [Extended Abstract  

E-Print Network [OSTI]

Optimal Storage Policies with Wind Forecast Uncertainties [Extended Abstract] Nicolas Gast EPFL, IC/LCA2 1015 Lausanne Switzerland nicolas.gast@epfl.ch Dan-Cristian Tomozei EPFL, IC/LCA2 1015 Lausanne Switzerland dan-cristian.tomozei@epfl.ch Jean-Yves Le Boudec EPFL, IC/LCA2 1015 Lausanne Switzerland jean

Dalang, Robert C.

96

Grid-scale Fluctuations and Forecast Error in Wind Power  

E-Print Network [OSTI]

The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

Bel, G; Toots, M; Bandi, M M

2015-01-01T23:59:59.000Z

97

Grid-scale Fluctuations and Forecast Error in Wind Power  

E-Print Network [OSTI]

The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

G. Bel; C. P. Connaughton; M. Toots; M. M. Bandi

2015-03-29T23:59:59.000Z

98

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand The demand forecast is the combined product of the hard work and expertise of numerous California Energy for demand response program impacts and contributed to the residential forecast. Mitch Tian prepared

99

CALIFORNIA ENERGY COMMISSION0 Annual Update to the Forecasted  

E-Print Network [OSTI]

Values in TWh forthe Year2022 Formula Mid Demand Forecast Renewable Net High Demand Forecast Renewable Net Low Demand Forecast Renewable Net #12;CALIFORNIA ENERGY COMMISSION5 Demand Forecast · Retail Sales Forecast from California Energy Demand 2012 2022(CED 2011), Adopted Forecast* ­ Form 1.1c · Demand Forecast

100

Forecast Energy | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating Solar Power Basics (TheEtelligence (SmartHome Kyoung's pictureFlintFlowerForecast

Note: This page contains sample records for the topic "wind energy forecasts" 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

Wind speed forecasting at different time scales: a non parametric approach  

E-Print Network [OSTI]

The prediction of wind speed is one of the most important aspects when dealing with renewable energy. In this paper we show a new nonparametric model, based on semi-Markov chains, to predict wind speed. Particularly we use an indexed semi-Markov model, that reproduces accurately the statistical behavior of wind speed, to forecast wind speed one step ahead for different time scales and for very long time horizon maintaining the goodness of prediction. In order to check the main features of the model we show, as indicator of goodness, the root mean square error between real data and predicted ones and we compare our forecasting results with those of a persistence model.

D'Amico, Guglielmo; Prattico, Flavio

2013-01-01T23:59:59.000Z

102

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity forecast is the combined product of the hard work and expertise of numerous staff members in the Demand prepared the peak demand forecast. Ravinderpal Vaid provided the projections of commercial floor space

103

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work provided estimates for demand response program impacts and contributed to the residential forecast. Mitch

104

Next Generation Short-Term Forecasting of Wind Power Overview of the ANEMOS Project.  

E-Print Network [OSTI]

of difficulties to the power system operation. This is due to the fluctuating nature of wind generation to the management of wind generation. Accurate and reliable forecasting systems of the wind production are widely

Boyer, Edmond

105

Wind Energy Act (Maine)  

Broader source: Energy.gov [DOE]

The Maine Wind Energy Act is a summary of legislative findings that indicate the state's strong interest in promoting the development of wind energy and establish the state's desire to ease the...

106

Wind Energy Benefits, Wind Powering America (WPA) (Fact Sheet...  

Broader source: Energy.gov (indexed) [DOE]

Energy Benefits, Wind Powering America (WPA) (Fact Sheet), Wind And Water Power Program (WWPP) Wind Energy Benefits, Wind Powering America (WPA) (Fact Sheet), Wind And Water Power...

107

Wind energy information guide  

SciTech Connect (OSTI)

This book is divided into nine chapters. Chapters 1--8 provide background and annotated references on wind energy research, development, and commercialization. Chapter 9 lists additional sources of printed information and relevant organizations. Four indices provide alphabetical access to authors, organizations, computer models and design tools, and subjects. A list of abbreviations and acronyms is also included. Chapter topics include: introduction; economics of using wind energy; wind energy resources; wind turbine design, development, and testing; applications; environmental issues of wind power; institutional issues; and wind energy systems development.

NONE

1996-04-01T23:59:59.000Z

108

wind energy  

National Nuclear Security Administration (NNSA)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "ofEarlyEnergyDepartmentNationalRestart of the Reviewwill help prepareAi-rapter |warhead protection|5/%2A en

109

Enhanced Short-Term Wind Power Forecasting and Value to Grid Operations: Preprint  

SciTech Connect (OSTI)

The current state of the art of wind power forecasting in the 0- to 6-hour time frame has levels of uncertainty that are adding increased costs and risk on the U.S. electrical grid. It is widely recognized within the electrical grid community that improvements to these forecasts could greatly reduce the costs and risks associated with integrating higher penetrations of wind energy. The U.S. Department of Energy has sponsored a research campaign in partnership with the National Oceanic and Atmospheric Administration (NOAA) and private industry to foster improvements in wind power forecasting. The research campaign involves a three-pronged approach: 1) a 1-year field measurement campaign within two regions; 2) enhancement of NOAA's experimental 3-km High-Resolution Rapid Refresh (HRRR) model by assimilating the data from the field campaign; and 3) evaluation of the economic and reliability benefits of improved forecasts to grid operators. This paper and presentation provides an overview of the regions selected, instrumentation deployed, data quality and control, assimilation of data into HRRR, and preliminary results of HRRR performance analysis.

Orwig, K.; Clark, C.; Cline, J.; Benjamin, S.; Wilczak, J.; Marquis, M.; Finley, C.; Stern, A.; Freedman, J.

2012-09-01T23:59:59.000Z

110

TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY  

E-Print Network [OSTI]

requirements. The transportation energy demand forecasts make assumptions about fuel price forecastsCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY ENERGY COMMISSION Gordon Schremp, Jim Page, and Malachi Weng-Gutierrez Principal Authors Jim Page Project

111

2015 Iowa Wind Power Conference and Iowa Wind Energy Association...  

Energy Savers [EERE]

2015 Iowa Wind Power Conference and Iowa Wind Energy Association Midwest Regional Energy Job Fair 2015 Iowa Wind Power Conference and Iowa Wind Energy Association Midwest Regional...

112

Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison (Presentation)  

SciTech Connect (OSTI)

This presentation summarizes the work to investigate the uncertainty in wind forecasting at different times of year and compare wind forecast errors in different power systems using large-scale wind power prediction data from six countries: the United States, Finland, Spain, Denmark, Norway, and Germany.

Zhang, J.; Hodge, B.; Miettinen, J.; Holttinen, H.; Gomez-Lozaro, E.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Lovholm, A.; Berge, E.; Dobschinski, J.

2013-10-01T23:59:59.000Z

113

Session: Short-term forecasting of wind power (BT2.5) Track: Technical  

E-Print Network [OSTI]

Session: Short-term forecasting of wind power (BT2.5) Track: Technical BEST PRACTICE IN THE USE) Armines / Ecole des Mines Short-term forecasting of wind power for about 48 hours in advance is an established technique by now. Any utility getting over a few percent wind power penetration is buying a system

114

Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint  

SciTech Connect (OSTI)

One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer.

Zhang, J.; Hodge, B. M.; Gomez-Lazaro, E.; Lovholm, A. L.; Berge, E.; Miettinen, J.; Holttinen, H.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Dobschinski, J.

2013-10-01T23:59:59.000Z

115

Central Wind Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities: Revised Edition  

SciTech Connect (OSTI)

The report and accompanying table addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America. The first part of the table focuses on electric utilities and regional transmission organizations that have central wind power forecasting in place; the second part focuses on electric utilities and regional transmission organizations that plan to adopt central wind power forecasting in 2010. This is an update of the December 2009 report, NREL/SR-550-46763.

Rogers, J.; Porter, K.

2011-03-01T23:59:59.000Z

116

Module Handbook Specialisation Wind Energy  

E-Print Network [OSTI]

of Wind Turbines Module name: Wind potential, Aerodynamics & Loading of Wind Turbines Section Classes Evaluation of Wind Energy Potential Wind turbine Aerodynamics Static and dynamic Loading of Wind turbines Wind turbine Aerodynamics Static and dynamic Loading of Wind turbines Credit points 8 CP

Habel, Annegret

117

Upstream Measurements of Wind Profiles with Doppler Lidar for Improved Wind Energy Integration  

SciTech Connect (OSTI)

New upstream measurements of wind profiles over the altitude range of wind turbines will be produced using a scanning Doppler lidar. These long range high quality measurements will provide improved wind power forecasts for wind energy integration into the power grid. The main goal of the project is to develop the optimal Doppler lidar operating parameters and data processing algorithms for improved wind energy integration by enhancing the wind power forecasts in the 30 to 60 minute time frame, especially for the large wind power ramps. Currently, there is very little upstream data at large wind farms, especially accurate wind profiles over the full height of the turbine blades. The potential of scanning Doppler lidar will be determined by rigorous computer modeling and evaluation of actual Doppler lidar data from the WindTracer system produced by Lockheed Martin Coherent Technologies, Inc. of Louisville, Colorado. Various data products will be investigated for input into numerical weather prediction models and statistically based nowcasting algorithms. Successful implementation of the proposed research will provide the required information for a full cost benefit analysis of the improved forecasts of wind power for energy integration as well as the added benefit of high quality wind and turbulence information for optimal control of the wind turbines at large wind farms.

Rodney Frehlich

2012-10-30T23:59:59.000Z

118

WIND ENERGY Wind Energ. (2014)  

E-Print Network [OSTI]

in the near wake. In conclusion, WiTTS performs satisfactorily in the rotor region of wind turbine wakes under neutral stability. Copyright 2014 John Wiley & Sons, Ltd. KEYWORDS wind turbine wake; wake model; self in wind farms along several rows and columns. Because wind turbines generate wakes that propagate downwind

2014-01-01T23:59:59.000Z

119

20% Wind Energy by 2030 - Chapter 2: Wind Turbine Technology...  

Office of Environmental Management (EM)

20% Wind Energy by 2030: Increasing Wind Energy's Contribution to U.S. Electricity Supply U.S. Offshore Wind Manufacturing and Supply Chain Development Wind Program Accomplishments...

120

Updated Eastern Interconnect Wind Power Output and Forecasts for ERGIS: July 2012  

SciTech Connect (OSTI)

AWS Truepower, LLC (AWST) was retained by the National Renewable Energy Laboratory (NREL) to update wind resource, plant output, and wind power forecasts originally produced by the Eastern Wind Integration and Transmission Study (EWITS). The new data set was to incorporate AWST's updated 200-m wind speed map, additional tall towers that were not included in the original study, and new turbine power curves. Additionally, a primary objective of this new study was to employ new data synthesis techniques developed for the PJM Renewable Integration Study (PRIS) to eliminate diurnal discontinuities resulting from the assimilation of observations into mesoscale model runs. The updated data set covers the same geographic area, 10-minute time resolution, and 2004?2006 study period for the same onshore and offshore (Great Lakes and Atlantic coast) sites as the original EWITS data set.

Pennock, K.

2012-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind energy forecasts" 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.


121

Wind energy conversion system  

DOE Patents [OSTI]

The wind energy conversion system includes a wind machine having a propeller connected to a generator of electric power, the propeller rotating the generator in response to force of an incident wind. The generator converts the power of the wind to electric power for use by an electric load. Circuitry for varying the duty factor of the generator output power is connected between the generator and the load to thereby alter a loading of the generator and the propeller by the electric load. Wind speed is sensed electro-optically to provide data of wind speed upwind of the propeller, to thereby permit tip speed ratio circuitry to operate the power control circuitry and thereby optimize the tip speed ratio by varying the loading of the propeller. Accordingly, the efficiency of the wind energy conversion system is maximized.

Longrigg, Paul (Golden, CO)

1987-01-01T23:59:59.000Z

122

Managing Wind Power Forecast Uncertainty in Electric Brandon Keith Mauch  

E-Print Network [OSTI]

and faculty. There were many people who helped me during my doctoral studies. First, I want to thank my co-advisors for wind farm management, but they are not perfect. Chapter 2 presents a model of a wind farm with compressed air energy storage (CAES) participating freely in the day-ahead electricity market without

123

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST Energy Demand 2008-2018 forecast supports the analysis and recommendations of the 2007 Integrated Energy Commission demand forecast models. Both the staff draft energy consumption and peak forecasts are slightly

124

Wind energy applications guide  

SciTech Connect (OSTI)

The brochure is an introduction to various wind power applications for locations with underdeveloped transmission systems, from remote water pumping to village electrification. It includes an introductory section on wind energy, including wind power basics and system components and then provides examples of applications, including water pumping, stand-alone systems for home and business, systems for community centers, schools, and health clinics, and examples in the industrial area. There is also a page of contacts, plus two specific example applications for a wind-diesel system for a remote station in Antarctica and one on wind-diesel village electrification in Russia.

anon.

2001-01-01T23:59:59.000Z

125

American Wind Energy Association Wind Energy Finance and Investment...  

Broader source: Energy.gov (indexed) [DOE]

Wind Energy Finance and Investment Seminar American Wind Energy Association Wind Energy Finance and Investment Seminar October 20, 2014 8:00AM EDT to October 21, 2014 5:00PM EDT...

126

20% Wind Energy by 2030: Increasing Wind Energy's Contribution...  

Office of Environmental Management (EM)

: Increasing Wind Energy's Contribution to U.S. Electricity Supply 20% Wind Energy by 2030: Increasing Wind Energy's Contribution to U.S. Electricity Supply Here you will find the...

127

20% Wind Energy by 2030: Increasing Wind Energy's Contribution...  

Office of Environmental Management (EM)

Summary) 20% Wind Energy by 2030: Increasing Wind Energy's Contribution to U.S. Electricity Supply (Executive Summary) Executive summary of a report on the requirements needed...

128

Wind Energy Resources and Technologies  

Broader source: Energy.gov [DOE]

This page provides a brief overview of wind energy resources and technologies supplemented by specific information to apply wind energy within the Federal sector.

129

Wind Energy and Spatial Technology  

E-Print Network [OSTI]

2/3/2011 1 Wind Energy and Spatial Technology Lori Pelech Why Wind Energy? A clean, renewable 2,600 tons of carbon emissions annually ­ The economy · Approximately 85,000 wind energy workers to Construct a Wind Farm... Geo-Spatial Components of Wind Farm Development Process Selecting a Project Site

Schweik, Charles M.

130

Great Plains Wind Energy Transmission Development Project  

SciTech Connect (OSTI)

In fiscal year 2005, the Energy & Environmental Research Center (EERC) received funding from the U.S. Department of Energy (DOE) to undertake a broad array of tasks to either directly or indirectly address the barriers that faced much of the Great Plains states and their efforts to produce and transmit wind energy at the time. This program, entitled Great Plains Wind Energy Transmission Development Project, was focused on the central goal of stimulating wind energy development through expansion of new transmission capacity or development of new wind energy capacity through alternative market development. The original task structure was as follows: Task 1 - Regional Renewable Credit Tracking System (later rescoped to Small Wind Turbine Training Center); Task 2 - Multistate Transmission Collaborative; Task 3 - Wind Energy Forecasting System; and Task 4 - Analysis of the Long-Term Role of Hydrogen in the Region. As carried out, Task 1 involved the creation of the Small Wind Turbine Training Center (SWTTC). The SWTTC, located Grand Forks, North Dakota, consists of a single wind turbine, the Endurance S-250, on a 105-foot tilt-up guyed tower. The S-250 is connected to the electrical grid on the 'load side' of the electric meter, and the power produced by the wind turbine is consumed locally on the property. Establishment of the SWTTC will allow EERC personnel to provide educational opportunities to a wide range of participants, including grade school through college-level students and the general public. In addition, the facility will allow the EERC to provide technical training workshops related to the installation, operation, and maintenance of small wind turbines. In addition, under Task 1, the EERC hosted two small wind turbine workshops on May 18, 2010, and March 8, 2011, at the EERC in Grand Forks, North Dakota. Task 2 involved the EERC cosponsoring and aiding in the planning of three transmission workshops in the midwest and western regions. Under Task 3, the EERC, in collaboration with Meridian Environmental Services, developed and demonstrated the efficacy of a wind energy forecasting system for use in scheduling energy output from wind farms for a regional electrical generation and transmission utility. With the increased interest at the time of project award in the production of hydrogen as a critical future energy source, many viewed hydrogen produced from wind-generated electricity as an attractive option. In addition, many of the hydrogen production-related concepts involve utilization of energy resources without the need for additional electrical transmission. For this reason, under Task 4, the EERC provided a summary of end uses for hydrogen in the region and focused on one end product in particular (fertilizer), including several process options and related economic analyses.

Brad G. Stevens, P.E.; Troy K. Simonsen; Kerryanne M. Leroux

2012-06-09T23:59:59.000Z

131

Wind energy conversion system  

SciTech Connect (OSTI)

This patent describes a wind energy conversion system comprising: a propeller rotatable by force of wind; a generator of electricity mechanically coupled to the propeller for converting power of the wind to electric power for use by an electric load; means coupled between the generator and the electric load for varying the electric power drawn by the electric load to alter the electric loading of the generator; means for electro-optically sensing the speed of the wind at a location upwind from the propeller; and means coupled between the sensing means and the power varying means for operating the power varying means to adjust the electric load of the generator in accordance with a sensed value of wind speed to thereby obtain a desired ratio of wind speed to the speed of a tip of a blade of the propeller.

Longrigg, P.

1987-03-17T23:59:59.000Z

132

Wind Power Forecasting Error Frequency Analyses for Operational Power System Studies: Preprint  

SciTech Connect (OSTI)

The examination of wind power forecasting errors is crucial for optimal unit commitment and economic dispatch of power systems with significant wind power penetrations. This scheduling process includes both renewable and nonrenewable generators, and the incorporation of wind power forecasts will become increasingly important as wind fleets constitute a larger portion of generation portfolios. This research considers the Western Wind and Solar Integration Study database of wind power forecasts and numerical actualizations. This database comprises more than 30,000 locations spread over the western United States, with a total wind power capacity of 960 GW. Error analyses for individual sites and for specific balancing areas are performed using the database, quantifying the fit to theoretical distributions through goodness-of-fit metrics. Insights into wind-power forecasting error distributions are established for various levels of temporal and spatial resolution, contrasts made among the frequency distribution alternatives, and recommendations put forth for harnessing the results. Empirical data are used to produce more realistic site-level forecasts than previously employed, such that higher resolution operational studies are possible. This research feeds into a larger work of renewable integration through the links wind power forecasting has with various operational issues, such as stochastic unit commitment and flexible reserve level determination.

Florita, A.; Hodge, B. M.; Milligan, M.

2012-08-01T23:59:59.000Z

133

Wind Energy Systems Exemption  

Broader source: Energy.gov [DOE]

Tennessee House Bill 809, enacted into law in Public Chapter 377, Acts of 2003 and codified under Title 67, Chapter 5, states that wind energy systems operated by public utilities, businesses or...

134

Wind Energy Teachers Guide  

SciTech Connect (OSTI)

This guide, created by the American Wind Association, with support from the U.S. Department of Energy, is a learning tool about wind energy targeted toward grades K-12. The guide provides teacher information, ideas for sparking children's and students' interest, suggestions for activities to undertake in and outside the classroom, and research tools for both teachers and students. Also included is an additional resources section.

anon.

2003-01-01T23:59:59.000Z

135

The wind power probability density forecast problem can be formulated as: forecast the wind power pdf at time step t for each look-ahead time step t+k of a given time-horizon  

E-Print Network [OSTI]

The wind power probability density forecast problem can be formulated as: forecast the wind power ahead) knowing a set of explanatory variables (e.g. numerical weather predictions (NWPs), wind power measured values). Translating this sentence to an equation, we have: where pt+k is the wind power

Kemner, Ken

136

Univariate Modeling and Forecasting of Monthly Energy Demand Time Series  

E-Print Network [OSTI]

Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural demand time series based only on data for six years to forecast the demand for the seventh year. Both networks, Neural networks, Modeling, Forecasting, Energy demand, Time series forecasting, Power system

Abdel-Aal, Radwan E.

137

Collegiate Wind Competition Engages Tomorrow's Wind Energy Innovators...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Engages Tomorrow's Wind Energy Innovators Collegiate Wind Competition Engages Tomorrow's Wind Energy Innovators January 6, 2014 - 10:00am Addthis 2014 Collegiate Teams Boise State...

138

Wind Energy Kit | Photosynthetic Antenna Research Center  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Wind Energy Kit Wind Energy Kit Wind Energy :: Kit Materials List Below is a list of the different Wind Energy kits available. For more details, download the Wind Energy Kit List....

139

Evaluation of Advanced Wind Power Forecasting Models Results of the Anemos Project  

E-Print Network [OSTI]

1 Evaluation of Advanced Wind Power Forecasting Models ­ Results of the Anemos Project I. Martí1.kariniotakis@ensmp.fr Abstract An outstanding question posed today by end-users like power system operators, wind power producers or traders is what performance can be expected by state-of-the-art wind power prediction models. This paper

Paris-Sud XI, Université de

140

Global and multi-scale features of solar wind-magnetosphere coupling: From modeling to forecasting  

E-Print Network [OSTI]

and substorms; 2784 Magnetospheric Physics: Solar wind/magnetosphere interactions; 3210 Mathematical Geophysics in the solar wind-magnetosphere interaction, de- veloping first principles models that encompass allGlobal and multi-scale features of solar wind-magnetosphere coupling: From modeling to forecasting

Sitnov, Mikhail I.

Note: This page contains sample records for the topic "wind energy forecasts" 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

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty  

SciTech Connect (OSTI)

This paper presents four algorithms to generate random forecast error time series. The performance of four algorithms is compared. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets used in power grid operation to study the net load balancing need in variable generation integration studies. The four algorithms are truncated-normal distribution models, state-space based Markov models, seasonal autoregressive moving average (ARMA) models, and a stochastic-optimization based approach. The comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics (i.e., mean, standard deviation, autocorrelation, and cross-correlation). The results show that all methods generate satisfactory results. One method may preserve one or two required statistical characteristics better the other methods, but may not preserve other statistical characteristics as well compared with the other methods. Because the wind and load forecast error generators are used in wind integration studies to produce wind and load forecasts time series for stochastic planning processes, it is sometimes critical to use multiple methods to generate the error time series to obtain a statistically robust result. Therefore, this paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.

Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.

2013-07-25T23:59:59.000Z

142

Wind Events | Department of Energy  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Below is an industry calendar with meetings, conferences, and webinars of interest to the wind energy technology communities. IEA Wind Task 34 (WREN) Quarterly Webinar 3:...

143

Performance Indicators of Wind Energy Production  

E-Print Network [OSTI]

Modeling wind speed is one of the key element when dealing with the production of energy through wind turbines. A good model can be used for forecasting, site evaluation, turbines design and many other purposes. In this work we are interested in the analysis of the future financial cash flows generated by selling the electrical energy produced. We apply an indexed semi-Markov model of wind speed that has been shown, in previous investigation, to reproduce accurately the statistical behavior of wind speed. The model is applied to the evaluation of financial indicators like the Internal Rate of Return, semi-Elasticity and relative Convexity that are widely used for the assessment of the profitability of an investment and for the measurement and analysis of interest rate risk. We compare the computation of these indicators for real and synthetic data. Moreover, we propose a new indicator that can be used to compare the degree of utilization of different power plants.

D'Amico, G; Prattico, F

2015-01-01T23:59:59.000Z

144

Wind energy offers considerable promise; the wind itself is free,  

E-Print Network [OSTI]

Wind energy offers considerable promise; the wind itself is free, wind power is clean. One of these sources, wind energy, offers considerable promise; the wind itself is free, wind power is clean, and it is virtually inexhaustible. In recent years, research on wind energy has accelerated

Langendoen, Koen

145

Wind | Department of Energy  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels Data CenterEnergyAuthorizationSunShot Initiative SolarVehiclesWind Wind EERE

146

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022  

E-Print Network [OSTI]

PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022 AUGUST 2011 CEC-200-2011-011-SD CALIFORNIA or adequacy of the information in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast forecast. Mitch Tian prepared the peak demand forecast. Ravinderpal Vaid provided the projections

147

Examining Information Entropy Approaches as Wind Power Forecasting Performance Metrics: Preprint  

SciTech Connect (OSTI)

In this paper, we examine the parameters associated with the calculation of the Renyi entropy in order to further the understanding of its application to assessing wind power forecasting errors.

Hodge, B. M.; Orwig, K.; Milligan, M.

2012-06-01T23:59:59.000Z

148

Bias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction  

E-Print Network [OSTI]

from numerical weather prediction models, which is based on a state-of-the-art circular-processing techniques for forecasts from numerical weather prediction models tend to become ineffective or inapplicableBias Correction and Bayesian Model Averaging for Ensemble Forecasts of Surface Wind Direction Le

Washington at Seattle, University of

149

AUTOMATION OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S.  

E-Print Network [OSTI]

AUTOMATION OF ENERGY DEMAND FORECASTING by Sanzad Siddique, B.S. A Thesis submitted to the Faculty OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S. Marquette University, 2013 Automation of energy demand of the energy demand forecasting are achieved by integrating nonlinear transformations within the models

Povinelli, Richard J.

150

Weather forecast-based optimization of integrated energy systems.  

SciTech Connect (OSTI)

In this work, we establish an on-line optimization framework to exploit detailed weather forecast information in the operation of integrated energy systems, such as buildings and photovoltaic/wind hybrid systems. We first discuss how the use of traditional reactive operation strategies that neglect the future evolution of the ambient conditions can translate in high operating costs. To overcome this problem, we propose the use of a supervisory dynamic optimization strategy that can lead to more proactive and cost-effective operations. The strategy is based on the solution of a receding-horizon stochastic dynamic optimization problem. This permits the direct incorporation of economic objectives, statistical forecast information, and operational constraints. To obtain the weather forecast information, we employ a state-of-the-art forecasting model initialized with real meteorological data. The statistical ambient information is obtained from a set of realizations generated by the weather model executed in an operational setting. We present proof-of-concept simulation studies to demonstrate that the proposed framework can lead to significant savings (more than 18% reduction) in operating costs.

Zavala, V. M.; Constantinescu, E. M.; Krause, T.; Anitescu, M.

2009-03-01T23:59:59.000Z

151

The use of real-time off-site observations as a methodology for increasing forecast skill in prediction of large wind power ramps one or more hours ahead of their impact on a wind plant.  

SciTech Connect (OSTI)

ABSTRACT Application of Real-Time Offsite Measurements in Improved Short-Term Wind Ramp Prediction Skill Improved forecasting performance immediately preceding wind ramp events is of preeminent concern to most wind energy companies, system operators, and balancing authorities. The value of near real-time hub height-level wind data and more general meteorological measurements to short-term wind power forecasting is well understood. For some sites, access to onsite measured wind data - even historical - can reduce forecast error in the short-range to medium-range horizons by as much as 50%. Unfortunately, valuable free-stream wind measurements at tall tower are not typically available at most wind plants, thereby forcing wind forecasters to rely upon wind measurements below hub height and/or turbine nacelle anemometry. Free-stream measurements can be appropriately scaled to hub-height levels, using existing empirically-derived relationships that account for surface roughness and turbulence. But there is large uncertainty in these relationships for a given time of day and state of the boundary layer. Alternatively, forecasts can rely entirely on turbine anemometry measurements, though such measurements are themselves subject to wake effects that are not stationary. The void in free-stream hub-height level measurements of wind can be filled by remote sensing (e.g., sodar, lidar, and radar). However, the expense of such equipment may not be sustainable. There is a growing market for traditional anemometry on tall tower networks, maintained by third parties to the forecasting process (i.e., independent of forecasters and the forecast users). This study examines the value of offsite tall-tower data from the WINDataNOW Technology network for short-horizon wind power predictions at a wind farm in northern Montana. The presentation shall describe successful physical and statistical techniques for its application and the practicality of its application in an operational setting. It shall be demonstrated that when used properly, the real-time offsite measurements materially improve wind ramp capture and prediction statistics, when compared to traditional wind forecasting techniques and to a simple persistence model.

Martin Wilde, Principal Investigator

2012-12-31T23:59:59.000Z

152

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST forecast is the combined product of the hard work and expertise of numerous staff members in the Demand, and utilities. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption

153

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST forecast is the combined product of the hard work and expertise of numerous staff in the Demand Analysis. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data

154

OWEMES -Offshore Wind And Other Marine Renewable Energies In Mediterranean And European Seas Civitavecchia (Italy), 20th  

E-Print Network [OSTI]

OWEMES - Offshore Wind And Other Marine Renewable Energies In Mediterranean And European Seas Civitavecchia (Italy), 20th -22th April 2006 How to avoid Biases in Offshore Wind Power Forecasting Lueder von, adaptive system, Neural Network, single site forecast, systematic error Abstract Large-scale offshore wind

Heinemann, Detlev

155

SPRING 2014 wind energy's impact  

E-Print Network [OSTI]

SPRING 2014 wind energy's impact on birds, bats......... 2-3 school news........... 4-5 alumni news measurable benefits reaped by the use of wind energy. But, it is a fact: all energy sources, alternative Interactions with Offshore Wind Energy Facilities," involves the design, deployment and testing

Tullos, Desiree

156

Probabilistic Wind Resource Assessment and Power Predictions  

E-Print Network [OSTI]

Probabilistic Wind Resource Assessment and Power Predictions Luca Delle Monache (lucadm Accurate wind resource assessment and power forecasts and reliable quanXficaXon of their uncertainty Mo5va5on Power forecast: o Increase wind energy penetra

Firestone, Jeremy

157

Wind Energy | Department of Energy  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:YearRound-Up from theDepartment of Dept.| WEATHERIZATION5 | EnergyMayDepartment ofWind EnergyWind

158

Wind Program: Wind Vision | Department of Energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered energy consumption byAbout PrintableBlenderWhatFellows - PastFarmWindWind PowerWind

159

Paper presented at EWEC 2008, Brussels, Belgium (31 March-03 April) Uncertainty Estimation of Wind Power Forecasts  

E-Print Network [OSTI]

-Antipolis, France Abstract--Short-term wind power forecasting tools providing "single-valued" (spot) predictions associated to the future wind power produc- tion for performing more efficiently functions such as reserves and modelling architec- tures for probabilistic wind power forecasting. Then, a comparison is carried out

Paris-Sud XI, Université de

160

Wind Energy Sales Tax Exemption  

Broader source: Energy.gov [DOE]

Wind-energy conversion systems used as electric-power sources are exempt from Minnesota's sales tax. Materials used to manufacture, install, construct, repair or replace wind-energy systems also...

Note: This page contains sample records for the topic "wind energy forecasts" 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

Short-term Forecasting of Offshore Wind Farm Production Developments of the Anemos Project  

E-Print Network [OSTI]

Short-term Forecasting of Offshore Wind Farm Production ­ Developments of the Anemos Project J.a.brownsword@rl.ac.uk 6 Overspeed GmBH & Co.KG, 26129 Oldenburg, Germany Email: h.p.waldl@overspeed.de Key words: Offshore to the large dimensions of offshore wind farms, their electricity production must be known well in advance

Paris-Sud XI, Université de

162

Energy 101: Wind Turbines  

SciTech Connect (OSTI)

See how wind turbines generate clean electricity from the power of the wind. Highlighted are the various parts and mechanisms of a modern wind turbine.

None

2011-01-01T23:59:59.000Z

163

Energy 101: Wind Turbines  

ScienceCinema (OSTI)

See how wind turbines generate clean electricity from the power of the wind. Highlighted are the various parts and mechanisms of a modern wind turbine.

None

2013-05-29T23:59:59.000Z

164

Wind Energy Information Guide 2004  

SciTech Connect (OSTI)

The guide provides a list of contact information and Web site addresses for resources that provide a range of general and technical information about wind energy, including general information, wind and renewable energy, university programs and research institutes, international wind energy associations and others.

anon.

2004-01-01T23:59:59.000Z

165

2008 Wind Energy Projects, Wind Powering America (Poster)  

SciTech Connect (OSTI)

The Wind Powering America program produces a poster at the end of every calendar year that depicts new U.S. wind energy projects. The 2008 poster includes the following projects: Stetson Wind Farm in Maine; Dutch Hill Wind Farm in New York; Grand Ridge Wind Energy Center in Illinois; Hooper Bay, Alaska; Forestburg, South Dakota; Elbow Creek Wind Project in Texas; Glacier Wind Farm in Montana; Wray, Colorado; Smoky Hills Wind Farm in Kansas; Forbes Park Wind Project in Massachusetts; Spanish Fork, Utah; Goodland Wind Farm in Indiana; and the Tatanka Wind Energy Project on the border of North Dakota and South Dakota.

Not Available

2009-01-01T23:59:59.000Z

166

Wind | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergyENERGYWomen Owned SmallOfCoal_Budget_Fact_Sheet.pdf MoreDaily wholesaleDepartment ofWind The

167

Version:April 2014 Wind Energy EFA  

E-Print Network [OSTI]

Version:April 2014 Wind Energy EFA Wind energy has become a major source of clean energy. Wind backgrounds and knowledge of wind energy fundamentals are needed to fill these jobs. The Wind Energy EFA prepares students for a career in wind energy, and allows for completing all requirements

Kusiak, Andrew

168

The Solar Wind Energy Flux  

E-Print Network [OSTI]

The solar-wind energy flux measured near the ecliptic is known to be independent of the solar-wind speed. Using plasma data from Helios, Ulysses, and Wind covering a large range of latitudes and time, we show that the solar-wind energy flux is independent of the solar-wind speed and latitude within 10%, and that this quantity varies weakly over the solar cycle. In other words the energy flux appears as a global solar constant. We also show that the very high speed solar-wind (VSW > 700 km/s) has the same mean energy flux as the slower wind (VSW < 700 km/s), but with a different histogram. We use this result to deduce a relation between the solar-wind speed and density, which formalizes the anti-correlation between these quantities.

Chat, G Le; Meyer-Vernet, N

2012-01-01T23:59:59.000Z

169

20% Wind Energy by 2030  

SciTech Connect (OSTI)

This analysis explores one clearly defined scenario for providing 20% of our nations electricity demand with wind energy by 2030 and contrasts it to a scenario of no new wind power capacity.

Not Available

2008-07-01T23:59:59.000Z

170

WINDExchange: Wind Energy Ordinances  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered energy consumption byAbout Printable Version Bookmark and ShareDevelopmentWind

171

Wind Energy Program: Top 10 Program Accomplishments  

Broader source: Energy.gov [DOE]

Brochure on the top accomplishments of the Wind Energy Program, including the development of large wind machines, small machines for the residential market, wind tunnel testing, computer codes for modeling wind systems, high definition wind maps, and successful collaborations.

172

LARGE SCALE WIND CLIMATOLOGICAL EXAMINATIONS OF WIND ENERGY UTILIZATION  

E-Print Network [OSTI]

The aim of this article is to describe the particular field of climatology which analyzes air movement characteristics regarding utilization of wind for energy generation. The article describes features of wind energy potential available in Hungary compared to wind conditions in other areas of the northern quarter sphere in order to assist the wind energy use development in Hungary. Information on wind climate gives a solid basis for financial and economic decisions of stakeholders in the field of wind energy utilization.

Andrea Kircsi

173

WIND ENERGY POLICIES IN TURKEY  

E-Print Network [OSTI]

Energy is a strategic parameter, which demonstrates the development of a country. In Turkey, energy and energy politics are mainly based on the supply due to the inadequate fossil fuel resources. In the beginning of the 21 st century, due to the increase in the price of fossil fuels and environmental burdens, many countries showed renewed interest in alternative energy resources. Climate change and environmental problems caused by greenhouse gas emissions showed the importance of renewable energy resources and especially wind energy. The major reason for the interest in wind energy technologies out of many renewable energy resources is the bulk availability of this resource without any cost. In Turkey, the major solution to the dependency on foreign energy resources is: domestic production, development, and operation of renewable energy resources. However, in order to make these investments, suitable conditions and strategies must be generated. In order to accelerate the wind energy investments in Turkey: (i) the problems related to the interconnectivity of the wind power systems to the grid must be solved (ii) the guaranteed purchase price of the wind energy must be updated (iii) and the construction/operation of wind power plants must be subsidised by government initiatives. In this study, the politics related to wind energy is extensively reviewed and the possible suggestions/solutions related to the acceleration of wind energy production and investments in Turkey are given.

S?tk? Gner; Irem Firtina; Mehmet Meliko?lu; Ayhan Albostan

174

WIND ENERGY Wind Energ. 2013; 16:7790  

E-Print Network [OSTI]

energy industry lags far behind the wind energy industry, it has the potential to become a role player is equal to the long-term potential of onshore wind energy.1,2 Therefore, the utilisation of marineWIND ENERGY Wind Energ. 2013; 16:77­90 Published online 19 March 2012 in Wiley Online Library

Papalambros, Panos

175

WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy  

E-Print Network [OSTI]

Energy Efficiency and Renewable Energy, Wind and Hydropowerin Spain. Spanish Wind Energy Association (AEE) contributionin a Wind Turbine. Wind Energy (9:12); pp. 141161.

Lantz, Eric

2014-01-01T23:59:59.000Z

176

Cost of Offshore Wind Energy Charlene Nalubega  

E-Print Network [OSTI]

Cost of Offshore Wind Energy and Industrial Engineering The focus of my research is to estimate the cost of floating offshore wind turbines water as well as on land based wind farms. The specific offshore wind energy case under consideration

Mountziaris, T. J.

177

Rhaglen Ynni Gwynt Wind Energy Programme  

E-Print Network [OSTI]

Rhaglen Ynni Gwynt Wind Energy Programme Rhaglen Ynni Gwynt Wind Energy Programme Calculations supporting indicative figures used for the Wind Energy Programme Wind Energy (page) The energy to make,000,000 = 162.73 Therefore 4.5kWh/d/p = approximately 163 cups of tea per day per person Wind Energy Programme

178

Wind Energy Benefits (Fact Sheet)  

SciTech Connect (OSTI)

This fact sheet outlines the top 10 benefits of wind energy, including cost, water savings, job creation, indigenous resource, and low operating costs.

Not Available

2015-01-01T23:59:59.000Z

179

Commercial Wind Energy Property Valuation  

Broader source: Energy.gov [DOE]

Prior to 2007, wind energy devices generating electricity for commercial sale were assessed differently depending on where they were located. Some counties valued the entire turbine structure ...

180

analytical energy forecasting: Topics by E-print Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

COMMISSION Tom Gorin Lynn Marshall Principal Author Tom Gorin Project 11 Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Computer Technologies and...

Note: This page contains sample records for the topic "wind energy forecasts" 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

Wind Energy EFA Wind energy has become a major source of clean energy. Wind energy is expected to grow over the next  

E-Print Network [OSTI]

Wind Energy EFA Wind energy has become a major source of clean energy. Wind energy is expected of wind energy fundamentals are needed to fill these jobs. The Wind Energy EFA prepares students for a career in wind energy, and allows for completing all requirements for the Certificate in Wind Energy

Kusiak, Andrew

182

Energy 101: Wind Turbines - 2014 Update  

ScienceCinema (OSTI)

See how wind turbines generate clean electricity from the power of wind. The video highlights the basic principles at work in wind turbines, and illustrates how the various components work to capture and convert wind energy to electricity. This updated version also includes information on the Energy Department's efforts to advance offshore wind power. Offshore wind energy footage courtesy of Vestas.

None

2014-06-05T23:59:59.000Z

183

Energy 101: Wind Turbines - 2014 Update  

SciTech Connect (OSTI)

See how wind turbines generate clean electricity from the power of wind. The video highlights the basic principles at work in wind turbines, and illustrates how the various components work to capture and convert wind energy to electricity. This updated version also includes information on the Energy Department's efforts to advance offshore wind power. Offshore wind energy footage courtesy of Vestas.

None

2014-05-06T23:59:59.000Z

184

WIND ENERGY Wind Energ. 2013; 00:112  

E-Print Network [OSTI]

WIND ENERGY Wind Energ. 2013; 00:1­12 DOI: 10.1002/we RESEARCH ARTICLE Model predictive control in wind speed, ensuring certain power gradients, with an insignificant loss in energy production rejection, model predictive control, convex optimization, wind power control, energy storage, power output

185

Improved forecasts of extreme weather events by future space borne Doppler wind lidar  

E-Print Network [OSTI]

sensitive areas. To answer these questions simulation experiments with state-of-the-art numerical weather prediction (NWP) models have proved great value to test future meteorological observing systems a prioriImproved forecasts of extreme weather events by future space borne Doppler wind lidar Gert

Marseille, Gert-Jan

186

PROGRESS OF WIND ENERGY TECHNOLOGY  

E-Print Network [OSTI]

This paper provides an overview of the progress of wind energy technology, along with the current status of wind power worldwide. Over the period of 2000-2012 grid-connected installed wind power has increased by a factor of more than 16. Due to the fast growth in wind market, wind turbine technology has developed different design approaches during this period. In addition to this, issues such as power grid integration, environmental impact, and economics are studied and discussed briefly in this paper, as well.

Bar?? zerdem

187

Distributed Wind Energy in Idaho  

SciTech Connect (OSTI)

Project Objective: This project is a research and development program aimed at furthering distributed wind technology. In particular, this project addresses some of the barriers to distributed wind energy utilization in Idaho. Background: At its core, the technological challenge inherent in Wind Energy is the transformation of a highly variable form of energy to one which is compatible with the commercial power grid or another useful application. A major economic barrier to the success of distributed wind technology is the relatively high capital investment (and related long payback periods) associated with wind turbines. This project will carry out fundamental research and technology development to address both the technological and economic barriers. â?¢ Active drive train control holds the potential to improve the overall efficiency of a turbine system by allowing variable speed turbine operation while ensuring a tight control of generator shaft speed, thus greatly simplifying power conditioning. â?¢ Recent blade aerodynamic advancements have been focused on large, utility-scale wind turbine generators (WTGs) as opposed to smaller WTGs designed for distributed generation. Because of Reynolds Number considerations, blade designs do not scale well. Blades which are aerodynamically optimized for distributed-scale WTGs can potentially reduce the cost of electricity by increasing shaft-torque in a given wind speed. â?¢ Grid-connected electric generators typically operate at a fixed speed. If a generator were able to economically operate at multiple speeds, it could potentially convert more of the windâ??s energy to electricity, thus reducing the cost of electricity. This research directly supports the stated goal of the Wind and Hydropower Technologies Program for Distributed Wind Energy Technology: By 2007, reduce the cost of electricity from distributed wind systems to 10 to 15 cents/kWh in Class 3 wind resources, the same level that is currently achievable in Class 5 winds.

Gardner, John; Ferguson, James; Ahmed-Zaid, Said; Johnson, Kathryn; Haynes, Todd; Bennett, Keith

2009-01-31T23:59:59.000Z

188

Wind Power Forecasting Error Distributions over Multiple Timescales: Preprint  

SciTech Connect (OSTI)

In this paper, we examine the shape of the persistence model error distribution for ten different wind plants in the ERCOT system over multiple timescales. Comparisons are made between the experimental distribution shape and that of the normal distribution.

Hodge, B. M.; Milligan, M.

2011-03-01T23:59:59.000Z

189

Wind Energy R&D Opportunity: Energy Department Announces $125...  

Energy Savers [EERE]

Wind Energy R&D Opportunity: Energy Department Announces 125 Million for Transformational Energy Projects Wind Energy R&D Opportunity: Energy Department Announces 125 Million for...

190

NREL: Wind Research - Wind Energy Videos  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recoveryLaboratory | NationalJohn F. Geisz,AerialStaff Here you willWind Energy

191

Compensation Packages Wind Energy Easements  

E-Print Network [OSTI]

to provide rural landowners with information about the wind industry, which was just beginning to emerge in the Midwest and Great Plains. In particular, we focused on land leases and wind energy easements because such agreements provided the primary means for farmers to participate in wind energy development. Since then, the U.S. wind industry has grown dramatically, with commercial-scale installations in more than 30 states and the expectation of a record year for new installations in 2005. As wind energy development has spread, the knowledge base among landowners and rural communities has grown, and options for local participation have increased substantially. With more options and information sources on wind basics available, we believed this was the right time for Windustry to revisit our work on what continues to be the principal means for landowners to participate in wind development: land leases and wind energy easements. This work addresses the ever more sophisticated questions landowners have raised about hosting wind turbines, and also begins to define good practices for developers as many new companies, large and small, enter the industry. Our primary goals are:

Lease Agreement

192

Energy Department Announces 2016 Collegiate Wind Competition...  

Energy Savers [EERE]

Energy Department Announces 2016 Collegiate Wind Competition Participants Energy Department Announces 2016 Collegiate Wind Competition Participants February 18, 2015 - 1:30pm...

193

Searchlight Wind Energy Project DEIS Appendix A  

Broader source: Energy.gov (indexed) [DOE]

Searchlight Wind Energy Project DEIS Appendix A Page | A Appendix A: Public Scoping Report SCOPING SUMMARY REPORT SEARCHLIGHT WIND ENERGY PROJECT ENVIRONMENTAL IMPACT STATEMENT...

194

Application of Ensemble Sensitivity Analysis to Observation Targeting for Short-term Wind Speed Forecasting  

SciTech Connect (OSTI)

The operators of electrical grids, sometimes referred to as Balancing Authorities (BA), typically make critical decisions on how to most reliably and economically balance electrical load and generation in time frames ranging from a few minutes to six hours ahead. At higher levels of wind power generation, there is an increasing need to improve the accuracy of 0- to 6-hour ahead wind power forecasts. Forecasts on this time scale have typically been strongly dependent on short-term trends indicated by the time series of power production and meteorological data from a wind farm. Additional input information is often available from the output of Numerical Weather Prediction (NWP) models and occasionally from off-site meteorological towers in the region surrounding the wind generation facility. A widely proposed approach to improve short-term forecasts is the deployment of off-site meteorological towers at locations upstream from the wind generation facility in order to sense approaching wind perturbations. While conceptually appealing, it turns out that, in practice, it is often very difficult to derive significant benefit in forecast performance from this approach. The difficulty is rooted in the fact that the type, scale, and amplitude of the processes controlling wind variability at a site change from day to day if not from hour to hour. Thus, a location that provides some useful forecast information for one time may not be a useful predictor a few hours later. Indeed, some processes that cause significant changes in wind power production operate predominantly in the vertical direction and thus cannot be monitored by employing a network of sensors at off-site locations. Hence, it is very challenging to determine the type of sensors and deployment locations to get the most benefit for a specific short-term forecast application. Two tools recently developed in the meteorological research community have the potential to help determine the locations and parameters to measure in order to get the maximum positive impact on forecast performance for a particular site and short-term look-ahead period. Both tools rely on the use of NWP models to assess the sensitivity of a forecast for a particular location to measurements made at a prior time (i.e. the look-ahead period) at points surrounding the target location. The fundamental hypothesis is that points and variables with high sensitivity are good candidates for measurements since information at those points are likely to have the most impact on the forecast for the desired parameter, location and look-ahead period. One approach is called the adjoint method (Errico and Vukicevic, 1992; Errico, 1997) and the other newer approach is known as Ensemble Sensitivity Analysis (ESA; Ancell and Hakim 2007; Torn and Hakim 2008). Both approaches have been tested on large-scale atmospheric prediction problems (e.g. forecasting pressure or precipitation over a relatively large region 24 hours ahead) but neither has been applied to mesoscale space-time scales of winds or any other variables near the surface of the earth. A number of factors suggest that ESA is better suited for short-term wind forecasting applications. One of the most significant advantages of this approach is that it is not necessary to linearize the mathematical representation of the processes in the underlying atmospheric model as required by the adjoint approach. Such a linearization may be especially problematic for the application of short-term forecasting of boundary layer winds in complex terrain since non-linear shifts in the structure of boundary layer due to atmospheric stability changes are a critical part of the wind power production forecast problem. The specific objective of work described in this paper is to test the ESA as a tool to identify measurement locations and variables that have the greatest positive impact on the accuracy of wind forecasts in the 0- to 6-hour look-ahead periods for the wind generation area of California's Tehachapi Pass during the warm (high generation) season. The paper is organized

Zack, J; Natenberg, E; Young, S; Manobianco, J; Kamath, C

2010-02-21T23:59:59.000Z

195

WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy  

E-Print Network [OSTI]

Energy Efficiency and Renewable Energy, Wind and HydropowerSpeed Sites. European Wind Energy Association. Marseille,Innovation and the price of wind energy in the US. Energy

Lantz, Eric

2014-01-01T23:59:59.000Z

196

Wind Energy Status and Future Wind Engineering Challenges: Preprint  

SciTech Connect (OSTI)

This paper describes the current status of wind energy technology, the potential for future wind energy development and the science and engineering challenges that must be overcome for the technology to meet its potential.

Thresher, R.; Schreck, S.; Robinson, M.; Veers, P.

2008-08-01T23:59:59.000Z

197

International Energy Agency 2011 Wind Energy Annual Report Available...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

International Energy Agency 2011 Wind Energy Annual Report Available for Download International Energy Agency 2011 Wind Energy Annual Report Available for Download October 1, 2012...

198

Community Renewable Energy Success Stories: Wind Energy in Urban...  

Office of Environmental Management (EM)

Community Renewable Energy Success Stories: Wind Energy in Urban Environments Webinar (text version) Community Renewable Energy Success Stories: Wind Energy in Urban Environments...

199

Rhaglen Ynni Gwynt Wind Energy Programme  

E-Print Network [OSTI]

Rhaglen Ynni Gwynt Wind Energy Programme 1 WEP Internet Calculations Explained | 20/02/2013 Calculations supporting indicative figures used for the Wind Energy Programme Wind Energy (page) "The energy.2 Therefore 4.5kWh/d/p = approximately 160 cups of tea per day per person. Wind Energy Programme (page

200

The Future of Offshore Wind Energy  

E-Print Network [OSTI]

1 The Future of Offshore Wind Energy #12;2 #12;3 Offshore Wind Works · Offshore wind parks: 28 in 10 countries · Operational since 1991 · Current installed capacity: 1,250 MW · Offshore wind parks in the waters around Europe #12;4 US Offshore Wind Projects Proposed Atlantic Ocean Gulf of Mexico Cape Wind

Firestone, Jeremy

Note: This page contains sample records for the topic "wind energy forecasts" 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

Wind Energy at NREL's National Wind Technology Center  

ScienceCinema (OSTI)

It is a pure, plentiful natural resource. Right now wind is in high demand and it holds the potential to transform the way we power our homes and businesses. NREL is at the forefront of wind energy research and development. NREL's National Wind Technology Center (NWTC) is a world-class facility dedicated to accelerating and deploying wind technology.

None

2013-05-29T23:59:59.000Z

202

Wind Energy at NREL's National Wind Technology Center  

SciTech Connect (OSTI)

It is a pure, plentiful natural resource. Right now wind is in high demand and it holds the potential to transform the way we power our homes and businesses. NREL is at the forefront of wind energy research and development. NREL's National Wind Technology Center (NWTC) is a world-class facility dedicated to accelerating and deploying wind technology.

None

2010-01-01T23:59:59.000Z

203

Arnold Schwarzenegger California Wind Energy  

E-Print Network [OSTI]

Albany, New York Contract No. 500-03-006 Prepared For: Public Interest Energy Research (PIER) ProgramArnold Schwarzenegger Governor California Wind Energy Resource Modeling and Measurement Prepared For: California Energy Commission Public Interest Energy Research Program Prepared By: AWS Truewind

204

Wind Energy Permitting Standards  

Broader source: Energy.gov [DOE]

All wind facilities larger than 0.5 megawatts (MW) that begin construction after July 1, 2010, must obtain a permit from any county in which the facility is located. Facilities must also obtain...

205

Energy from Offshore Wind: Preprint  

SciTech Connect (OSTI)

This paper provides an overview of the nascent offshore wind energy industry including a status of the commercial offshore industry and the technologies that will be needed for full market development.

Musial, W.; Butterfield, S.; Ram, B.

2006-02-01T23:59:59.000Z

206

Wind Energy Conversion Systems (Minnesota)  

Broader source: Energy.gov [DOE]

This section distinguishes between large (capacity 5,000 kW or more) and small (capacity of less than 5,000 kW) wind energy conversion systems (WECS), and regulates the siting of large conversion...

207

WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy  

E-Print Network [OSTI]

Speed Sites. European Wind Energy Association. Marseille,Innovation and the price of wind energy in the US. EnergyThe Economics of Wind Energy. Renewable and Sustainable

Lantz, Eric

2014-01-01T23:59:59.000Z

208

Solar Energy Market Forecast | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revisionEnvReviewNonInvasiveExplorationUT-g GrantAtlas (PACA Region - France) Jump to:Energy

209

Paul S. Veers Wind Energy Technology Department  

E-Print Network [OSTI]

Paul S. Veers Wind Energy Technology Department Sandia National Laboratories Thursday, April 8th 3 Y WIND ENERGY SEMINAR SERIES Wind energy is a growing electricity source around the world, providing. The rapid expansion of wind is largely due to its relative similarity in levelized cost of energy to fossil

Ginzel, Matthew

210

Wind Gallery | Department of Energy  

Office of Environmental Management (EM)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergyENERGYWomen Owned SmallOf TheViolations | Department of EnergyisWilliamForecastingGallery

211

INFOGRAPHIC: Wind Energy in America | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

INFOGRAPHIC: Wind Energy in America INFOGRAPHIC: Wind Energy in America August 14, 2012 - 9:21am Addthis This infographic details key findings from the Energy Departments

212

Wind Success Stories | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

clean, affordable, and reliable domestic wind power tap into enormous energy-saving potential across the United States. Explore EERE's wind power success stories below. February...

213

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect (OSTI)

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model's parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. (Lawrence Berkeley Lab., CA (United States) Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.); Hwang, R. (Lawrence Berkeley Lab., CA (United States))

1992-02-01T23:59:59.000Z

214

A model for Long-term Industrial Energy Forecasting (LIEF)  

SciTech Connect (OSTI)

The purpose of this report is to establish the content and structural validity of the Long-term Industrial Energy Forecasting (LIEF) model, and to provide estimates for the model`s parameters. The model is intended to provide decision makers with a relatively simple, yet credible tool to forecast the impacts of policies which affect long-term energy demand in the manufacturing sector. Particular strengths of this model are its relative simplicity which facilitates both ease of use and understanding of results, and the inclusion of relevant causal relationships which provide useful policy handles. The modeling approach of LIEF is intermediate between top-down econometric modeling and bottom-up technology models. It relies on the following simple concept, that trends in aggregate energy demand are dependent upon the factors: (1) trends in total production; (2) sectoral or structural shift, that is, changes in the mix of industrial output from energy-intensive to energy non-intensive sectors; and (3) changes in real energy intensity due to technical change and energy-price effects as measured by the amount of energy used per unit of manufacturing output (KBtu per constant $ of output). The manufacturing sector is first disaggregated according to their historic output growth rates, energy intensities and recycling opportunities. Exogenous, macroeconomic forecasts of individual subsector growth rates and energy prices can then be combined with endogenous forecasts of real energy intensity trends to yield forecasts of overall energy demand. 75 refs.

Ross, M. [Lawrence Berkeley Lab., CA (United States)]|[Michigan Univ., Ann Arbor, MI (United States). Dept. of Physics]|[Argonne National Lab., IL (United States). Environmental Assessment and Information Sciences Div.; Hwang, R. [Lawrence Berkeley Lab., CA (United States)

1992-02-01T23:59:59.000Z

215

Paper accepted for presentation at 2003 IEEE Bologna PowerTech Conference, June 23-26, Bologna, Italy Wind Power Forecasting using Fuzzy Neural Networks  

E-Print Network [OSTI]

, Italy Wind Power Forecasting using Fuzzy Neural Networks Enhanced with On-line Prediction Risk) as input, to predict the power production of wind park8 48 hours ahead. The prediction system integrates of the numerical weather predictions. Index Term-Wind power, short-term forecasting, numerical weather predictions

Paris-Sud XI, Universit de

216

Wind Energy Permitting Standards (North Carolina)  

Broader source: Energy.gov [DOE]

North Carolina has statewide permitting requirements for wind energy facilities. Any wind turbine or collection of wind turbines located within a half mile of each other with a collective rated...

217

Wind Energy Career Development Program  

SciTech Connect (OSTI)

Saint Francis University has developed curriculum in engineering and in business that is meeting the needs of students and employers (Task 1) as well as integrating wind energy throughout the curriculum. Through a variety of approaches, the University engaged in public outreach and education that reached over 2,000 people annually (Task 2). We have demonstrated, through the success of these programs, that students are eager to prepare for emerging jobs in alternative energy, that employers are willing to assist in developing employees who understand the broader business and policy context of the industry, and that people want to learn about wind energy.

Gwen Andersen

2012-03-29T23:59:59.000Z

218

20% Wind Energy by 2030 - Chapter 6: Wind Power Markets Summary...  

Broader source: Energy.gov (indexed) [DOE]

6: Wind Power Markets Summary Slides 20% Wind Energy by 2030 - Chapter 6: Wind Power Markets Summary Slides Summary slides overviewing wind power markets, growth, applications, and...

219

Wind Forecast Improvement Project Southern Study Area Final Report |  

Broader source: Energy.gov (indexed) [DOE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "ofEarlyEnergyDepartment ofDepartment of Energy WhileTanklessLES'NeighborhoodThisApril2014Why3 01

220

SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS  

E-Print Network [OSTI]

SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS Detlev Heinemann Oldenburg.girodo@uni-oldenburg.de ABSTRACT Solar energy is expected to contribute major shares of the future global energy supply. Due to its and solar energy conversion processes has to account for this behaviour in respective operating strategies

Heinemann, Detlev

Note: This page contains sample records for the topic "wind energy forecasts" 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

Energy Department Announces Distributed Wind Competitiveness...  

Energy Savers [EERE]

for projects led by Pika Energy, Northern Power Systems, Endurance Wind Power, and Urban Green Energy that will help drive down the cost of small and medium-sized wind energy...

222

Space-time forecasting and evaluation of wind speed with statistical tests for comparing accuracy of spatial predictions  

E-Print Network [OSTI]

). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 11 Comparing the predictive distributions for the models when the TDD model produces the best forecast (top panel) and when the BST model produces the best forecast (bottom panel). The small vertical line on the x-axis of each plot represents... of wind to benefit humans is not a new concept. Historically, wind- mills have been used to pump water from wells or to grind grain for centuries. But fast- forwarding into the 21st century, ?windmills? are being used to generate electricity. Wind turbines...

Hering, Amanda S.

2010-10-12T23:59:59.000Z

223

Mesoscale Simulations of a Wind Ramping Event for Wind Energy Prediction  

SciTech Connect (OSTI)

Ramping events, or rapid changes of wind speed and wind direction over a short period of time, present challenges to power grid operators in regions with significant penetrations of wind energy in the power grid portfolio. Improved predictions of wind power availability require adequate predictions of the timing of ramping events. For the ramping event investigated here, the Weather Research and Forecasting (WRF) model was run at three horizontal resolutions in 'mesoscale' mode: 8100m, 2700m, and 900m. Two Planetary Boundary Layer (PBL) schemes, the Yonsei University (YSU) and Mellor-Yamada-Janjic (MYJ) schemes, were run at each resolution as well. Simulations were not 'tuned' with nuanced choices of vertical resolution or tuning parameters so that these simulations may be considered 'out-of-the-box' tests of a numerical weather prediction code. Simulations are compared with sodar observations during a wind ramping event at a 'West Coast North America' wind farm. Despite differences in the boundary-layer schemes, no significant differences were observed in the abilities of the schemes to capture the timing of the ramping event. As collaborators have identified, the boundary conditions of these simulations probably dominate the physics of the simulations. They suggest that future investigations into characterization of ramping events employ ensembles of simulations, and that the ensembles include variations of boundary conditions. Furthermore, the failure of these simulations to capture not only the timing of the ramping event but the shape of the wind profile during the ramping event (regardless of its timing) indicates that the set-up and execution of such simulations for wind power forecasting requires skill and tuning of the simulations for a specific site.

Rhodes, M; Lundquist, J K

2011-09-21T23:59:59.000Z

224

Funding Opportunity Announcement for Wind Forecasting Improvement Project  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:Year in3.pdf Flash2006-53.pdf0.pdfCost Savings |Safety,of Energy Funding Opportunityin Complex

225

Wind Energy Benefits, Wind Powering America (WPA) (Fact Sheet)  

SciTech Connect (OSTI)

This fact sheet outlines the top 10 benefits of wind energy, including cost, water savings, job creation, indigenous resource, and low operating costs.

Not Available

2011-04-01T23:59:59.000Z

226

Leveraging Weather Forecasts in Renewable Energy Navin Sharmaa,  

E-Print Network [OSTI]

Leveraging Weather Forecasts in Renewable Energy Systems Navin Sharmaa, , Jeremy Gummesonb , David, Binghamton, NY 13902 Abstract Systems that harvest environmental energy must carefully regulate their us- age to satisfy their demand. Regulating energy usage is challenging if a system's demands are not elastic, since

Shenoy, Prashant

227

Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems  

E-Print Network [OSTI]

Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems Navin Sharma,gummeson,irwin,shenoy}@cs.umass.edu Abstract--To sustain perpetual operation, systems that harvest environmental energy must carefully regulate their usage to satisfy their demand. Regulating energy usage is challenging if a system's demands

Shenoy, Prashant

228

Short-Term Solar Energy Forecasting Using Wireless Sensor Networks  

E-Print Network [OSTI]

Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Stefan Achleitner, Tao Liu an advantage for output power prediction. Solar Energy Prediction System Our prediction model is based variability of more then 100 kW per minute. For practical usage of solar energy, predicting times of high

Cerpa, Alberto E.

229

Shenyang Huachuang Wind Energy Corporation HCWE aka China Creative...  

Open Energy Info (EERE)

Shenyang Huachuang Wind Energy Corporation HCWE aka China Creative Wind Energy Co Ltd Jump to: navigation, search Name: Shenyang Huachuang Wind Energy Corporation (HCWE) (aka China...

230

Value Capture in the Global Wind Energy Industry  

E-Print Network [OSTI]

investigations/wind-energy-funds-going-overseas/ Dedrick,America. GWEC (Global Wind Energy Council) (2010). Globaland investment flows in the wind energy industry. Peterson

Dedrick, Jason; Kraemer, Kenneth L.

2011-01-01T23:59:59.000Z

231

WREF 2012: THE PAST AND FUTURE COST OF WIND ENERGY  

E-Print Network [OSTI]

2009). Technology Roadmap Wind Energy. Paris, France:EWEA. (2011). Pure Power Wind Energy Targets for 2020 andBelgium: European Wind Energy Association (19) Electric

Wiser, Ryan

2013-01-01T23:59:59.000Z

232

Department of Energy Wind Vision: An Industry Preview | Department...  

Broader source: Energy.gov (indexed) [DOE]

Department of Energy Wind Vision: An Industry Preview Department of Energy Wind Vision: An Industry Preview The "Department of Energy Wind Vision: An Industry Preview,"...

233

WREF 2012: THE PAST AND FUTURE COST OF WIND ENERGY  

E-Print Network [OSTI]

2009). Technology Roadmap Wind Energy. Paris, France:5) Cea, A; Simonot, E. (2011). The Cost of Wind Energy.Spanish Wind Energy Association (AEE) contribution to IEA

Wiser, Ryan

2013-01-01T23:59:59.000Z

234

EIS-0470: Cape Wind Energy Project, Final General Conformity...  

Broader source: Energy.gov (indexed) [DOE]

70: Cape Wind Energy Project, Final General Conformity Determination EIS-0470: Cape Wind Energy Project, Final General Conformity Determination Cape Wind Energy Project, Final...

235

Alternative Energy Provides a Second Wind  

E-Print Network [OSTI]

This report provides information for communities and other interested stakeholders about the development of wind energy at former mining sites. Local governments, residents and organizations may be interested in creating renewable energy resources and new economic opportunities at these sites. The report describes the mechanics of wind energy, details the various wind technology options, explores wind energys environmental, economic and social impacts at mining sites, and provides case studies and next steps to help get projects in place.

unknown authors

236

Wind energy | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectric Coop,SaveWhiskey Flats Geothermal Areaarticle is a stub.Wind) Jump to:

237

Wind energy | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectric Coop,SaveWhiskey Flats Geothermal Areaarticle is a stub.Wind) Jump

238

Comparison of Bottom-Up and Top-Down Forecasts: Vision Industry Energy Forecasts with ITEMS and NEMS  

E-Print Network [OSTI]

Comparisons are made of energy forecasts using results from the Industrial module of the National Energy Modeling System (NEMS) and an industrial economic-engineering model called the Industrial Technology and Energy Modeling System (ITEMS), a model...

Roop, J. M.; Dahowski, R. T

239

AWEA Wind Energy Regional Summit: Northeast  

Office of Energy Efficiency and Renewable Energy (EERE)

The AWEA Wind Energy Northeast Regional Summit will connect you with New England-area wind energy professionals and offers the opportunity to discuss significant issues related to land-based and...

240

Comments of the American Wind Energy...  

Broader source: Energy.gov (indexed) [DOE]

and wind power development. Assuming a conservative 35MWh value for curtailed wholesale energy would put a value of over 100 million on the wind energy that was curtailed...

Note: This page contains sample records for the topic "wind energy forecasts" 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

Currituck County- Wind Energy Systems Ordinance  

Broader source: Energy.gov [DOE]

In January 2008, Currituck County adopted an ordinance to regulate the use of wind-energy systems. The ordinance directs any individual or organization wishing to install a wind-energy system to...

242

Modular Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia: Energy Resources Jump to:46 -Energieprojekte GmbHMilo,Energy Information Modoc High School Space HeatingWind

243

Energy in the Wind  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsing Zirconia NanoparticlesSmart Grocer Program Sign-upEnergyTricksJohnEnergy Provi

244

Examples of Wind Energy Curtailment Practices  

SciTech Connect (OSTI)

This report addresses examples of wind energy curtailment practices internationally and in regions across the United States.

Rogers, J.; Fink, S.; Porter, K.

2010-07-01T23:59:59.000Z

245

Wind energy systems information user study  

SciTech Connect (OSTI)

This report describes the results of a series of telephone interviews with potential users of information on wind energy conversion. These interviews, part of a larger study covering nine different solar technologies, attempted to identify: the type of information each distinctive group of information users needed, and the best way of getting information to that group. Groups studied include: wind energy conversion system researchers; wind energy conversion system manufacturer representatives; wind energy conversion system distributors; wind turbine engineers; utility representatives; educators; county agents and extension service agents; and wind turbine owners.

Belew, W.W.; Wood, B.L.; Marle, T.L.; Reinhardt, C.L.

1981-01-01T23:59:59.000Z

246

NREL: Learning - Wind Energy Basics  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recoveryLaboratory | National NuclearoverAcquisitionEnergy SponsorsEnergyWind Energy

247

West Winds Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 NoPublic Utilities Address: 160 East 300 South Place: SaltTroyer & AssociatesWest CentralUkinrekWest Winds Wind

248

Wind Vision Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 NoPublic Utilities Address: 160 East 300 South Place:ReferenceEdit JumpWill County, Illinois:4 Sector WindOaxacaWind

249

Ris National Laboratory Wind Energy Department  

E-Print Network [OSTI]

and the wind power density 36 (Troen & Petersen, 1989). In screening for potential offshore wind 37farm sitesRisø National Laboratory Postprint Wind Energy Department Year 2006 Paper: www.risoe.dk/rispubl/art/2006_96.pdf Wind resource assessment from C-band SAR Merete Bruun Christiansen a, Wolfgang Koch b

250

Wind Energy Facility Reliability and Maintenance  

E-Print Network [OSTI]

Wind Energy Facility Reliability and Maintenance Eunshin Byon, Lewis Ntaimo, Chanan Singh and Yu related to wind energy facility reliability and mainte- nance focused more on qualitative aspects. In this chapter, we provide a comprehensive account of the existing research regarding wind energy facility

Ding, Yu

251

Integrating agricultural pest biocontrol into forecasts of energy biomass production  

E-Print Network [OSTI]

Analysis Integrating agricultural pest biocontrol into forecasts of energy biomass production T), University of Lome, 114 Rue Agbalepedogan, BP: 20679, Lome, Togo e Center for Agricultural & Energy Policy model of potential biomass supply that incorporates the effect of biological control on crop choice

Gratton, Claudio

252

Exploiting weather forecasts for sizing photovoltaic energy bids  

E-Print Network [OSTI]

1 Exploiting weather forecasts for sizing photovoltaic energy bids Antonio Giannitrapani, Simone for a photovoltaic (PV) power producer taking part into a competitive electricity market characterized by financial set from an Italian PV plant. Index Terms--Energy market, bidding strategy, photovoltaic power

Giannitrapani, Antonello

253

Sandia National Laboratories: Wind Energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1development Sandia, NREL Release Wave EnergyLinks WaterWind Energy National Rotor

254

Sandia National Laboratories: Wind Energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1development Sandia, NREL Release Wave EnergyLinks WaterWind Energy National

255

Wind Energy Education and Outreach Project  

SciTech Connect (OSTI)

The purpose of Illinois State University??s wind project was to further the education and outreach of the university concerning wind energy. This project had three major components: to initiate and coordinate a Wind Working Group for the State of Illinois, to launch a Renewable Energy undergraduate program, and to develop the Center for Renewable Energy that will sustain the Illinois Wind Working Group and the undergraduate program.

David G. Loomis

2011-04-15T23:59:59.000Z

256

Innovative Wind Energy, Inc | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpen EnergyBoard"Starting aLianhe WindInformationWind Energy,

257

WindEnergyPEIS  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste and MaterialsWenjun DengWISPWind Industry2

258

Cisco Wind Energy Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergyCTBarreisVolcanic National ParkCimarron I SolarCisco Wind Energy

259

WREF 2012: THE PAST AND FUTURE COST OF WIND ENERGY  

E-Print Network [OSTI]

WIND ENERGY by as much as 270% when comparing todays turbinesTurbines in Denmark. Presentation to IEA Wind Task 26 (12) European Wind Energy

Wiser, Ryan

2013-01-01T23:59:59.000Z

260

Jasper Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpen EnergyBoard"StartingInteruniversityIwasakiJasper Wind Jump

Note: This page contains sample records for the topic "wind energy forecasts" 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

WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy  

E-Print Network [OSTI]

Energy Laboratory. Danish Energy Agency (DEA). (1999). Wind2009) and the Danish Energy Agency (DEA) (1999), illustratedata is from the Danish Energy Agency wind turbine

Lantz, Eric

2014-01-01T23:59:59.000Z

262

Searchlight Wind Energy Project FEIS Appendix B  

Office of Environmental Management (EM)

Bird and Bat Conservation Strategy Searchlight BBCS i October 2012 Searchlight Wind Energy Project Bird and Bat Conservation Strategy Prepared for: Duke Energy Renewables 550...

263

Wind Energy Workforce Development: A Roadmap to a Wind Energy Educational Infrastructure (Presentation)  

SciTech Connect (OSTI)

Wind Powering America national technical director Ian Baring-Gould made this presentation about workforce development in the wind energy industry to an audience at the American Wind Energy Association's annual WINDPOWER conference in Anaheim. The presentation outlines job projections from the 20% Wind Energy by 2030 report and steps to take at all levels of educational institutions to meet those projections.

Baring-Gould, I.

2011-05-01T23:59:59.000Z

264

The communication dimension of wind energy  

E-Print Network [OSTI]

energy · People see the advantages of wind power as being more important than the disadvantagesThe communication dimension of wind energy: Challenges and opportunities #12;OPPORTUNITIES #12;Pew of industry Kick and Smith, 2008 #12;Other audience characteristics · A public relatively informed about wind

McCalley, James D.

265

Wind Energy Department Annual Progress Report 2002  

E-Print Network [OSTI]

Wind Energy Department Annual Progress Report 2002 Edited by Birgitte D. Johansen and Ulla Riis The new Test Station at Høvsøre Risø National Laboratory December 2003 Risø-R-1419(EN) #12;Wind Energy Aeroelastic Design (AED) p. 10 Atmospheric Physics (ATM) p. 15 Electrical Design and Control (EDS) p. 24 Wind

266

Wind Energy Department Annual Progress Report 2003  

E-Print Network [OSTI]

Wind Energy Department Annual Progress Report 2003 Edited by Birgitte D. Johansen and Ulla Riis 2003 p. 6 Projects of the Department Meteorology (MET) p. 11 Aeroelastic Design (AED) p. 30 Wind Turbines (VIM) p. 36 Wind Energy Systems (VES) p. 41 Test and Measurements (TEM) p. 53 Sparkær Blade Test

267

Capacity Building in Wind Energy for PICs  

E-Print Network [OSTI]

indicates that significant wind energy potential exists. · A monitoring project showed that in Rarotonga system. · About 30 other islands could have potential for grid connected wind turbines in the 100-1000 k1 Capacity Building in Wind Energy for PICs Presentation of the project Regional Workshop Suva

268

2010 Cost of Wind Energy Review  

SciTech Connect (OSTI)

This document provides a detailed description of NREL's levelized cost of wind energy equation, assumptions and results in 2010, including historical cost trends and future projections for land-based and offshore utility-scale wind.

Tegen, S.; Hand, M.; Maples, B.; Lantz, E.; Schwabe, P.; Smith, A.

2012-04-01T23:59:59.000Z

269

Camden County- Wind Energy Systems Ordinance  

Broader source: Energy.gov [DOE]

In September 2007, Camden County adopted a wind ordinance to regulate the use of wind-energy systems in the county and to describe the conditions by which a permit for installing such a system may...

270

Tyrrell County- Wind Energy Facility Ordinance  

Broader source: Energy.gov [DOE]

Tyrrell County, located in northeastern North Carolina, adopted a wind ordinance in 2009 to regulate the use of wind energy facilities in the unincorporated areas of the county. The ordinance is...

271

Hyde County- Wind Energy Facility Ordinance  

Broader source: Energy.gov [DOE]

Hyde County, located in eastern North Carolina, adopted a wind ordinance in 2008 to regulate the use of wind energy facilities throughout the county, including waters within the boundaries of Hyde...

272

Watauga County- Wind Energy System Ordinance  

Broader source: Energy.gov [DOE]

In 2006, Watauga County adopted a wind ordinance to regulate the use of wind-energy systems in the county and to describe the conditions by which a permit for installing such a system may be...

273

BP Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 NoPublic Utilities Address: 160 EastMaine: EnergyAustin Energy Place:Guidance DocumentsOperations |BPPurui NewBP Wind

274

Wind Vision | Department of Energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered energy consumption byAbout PrintableBlenderWhatFellows -Vision Wind Vision Addthis

275

Wind Vision | Department of Energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered energy consumption byAbout PrintableBlenderWhatFellows -Vision Wind Vision

276

Sandia National Laboratories: wind energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administrationcontroller systems controller systems Scaled Windwhite LED BriefWind Energy

277

Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids  

E-Print Network [OSTI]

1 Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids Yogesh Simmhan, prasanna}@usc.edu I. INTRODUCTION Smart Power Grids exemplify an emerging class of Cyber Physical-on paradigm to support operational needs. Smart Grids are an outcome of instrumentation, such as Phasor

Prasanna, Viktor K.

278

Prairie Winds Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth'sOklahoma/GeothermalOrangePeru:Job CorpPowerVerde IncStar (07) Wind FarmND

279

High Winds Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's Heat Jump to:Photon Place:NetHealthHigganum, Connecticut:Wind Farm Jump to:

280

Perceived Socioeconomic Impacts of Wind Energy in West Texas  

E-Print Network [OSTI]

Wind power is a fast growing alternative energy source. Since 2000, wind energy capacity has increased 24 percent per year with Texas leading the U.S. in installed wind turbine capacity. Most socioeconomic research in wind energy has focused...

Persons, Nicole D.

2010-07-14T23:59:59.000Z

Note: This page contains sample records for the topic "wind energy forecasts" 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.


281

20% Wind Energy by 2030 - Chapter 5: Wind Power Siting and Environment...  

Broader source: Energy.gov (indexed) [DOE]

5: Wind Power Siting and Environmental Effects Summary Slides 20% Wind Energy by 2030 - Chapter 5: Wind Power Siting and Environmental Effects Summary Slides Environment and siting...

282

Mountaineer Wind Energy Center | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's HeatMexico: EnergyMithun Jump to:Moe WindMontMoraineAbbeyI Wind

283

Wind and Wave Extremes over the World Oceans From Very Large Forecast Ensembles  

E-Print Network [OSTI]

Global return value estimates of significant wave height and 10-m neutral wind speed are estimated from very large aggregations of archived ECMWF ensemble forecasts at +240-h lead time from the period 2003-2012. The upper percentiles are found to match ENVISAT wind speed better than ERA-Interim (ERA-I), which tends to be biased low. The return estimates are significantly higher for both wind speed and wave height in the extratropics and the subtropics than what is found from ERA-I, but lower than what is reported by Caires and Sterl (2005) and Vinoth and Young (2011). The highest discrepancies between ERA-I and ENS240 are found in the hurricane-prone areas, suggesting that the ensemble comes closer than ERA-I in capturing the intensity of tropical cyclones. The width of the confidence intervals are typically reduced by 70% due to the size of the data sets. Finally, non-parametric estimates of return values were computed from the tail of the distribution. These direct return estimates compare very well with Ge...

Breivik, yvind; Abdalla, Saleh; Bidlot, Jean-Raymond

2013-01-01T23:59:59.000Z

284

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

E-Print Network [OSTI]

. 1. Introduction In recent years, wind energy production has under- gone rapid growth, and the U over both space and time. Therefore, the production rates of wind energy fluctuate more strongly than percentage of total power per capita coming from wind energy in 2010 (Department of Energy 2010). Even fewer

McCalley, James D.

285

Wind Energy and Economic Development in Nebraska  

SciTech Connect (OSTI)

This fact sheet summarizes a recent report by the National Renewable Energy Laboratory (NREL), Economic Development Benefits from Wind Power in Nebraska: A Report for the Nebraska Energy Office, which focuses on the estimated economic development impacts in Nebraska from development and operation of wind power in the state as envisioned in the U.S. Department of Energy's (DOE's) report, 20% Wind Energy by 2030.

Lantz, E.

2009-06-01T23:59:59.000Z

286

Wind Powering America Fact Sheet Series 1 Wind energy is more expensive than conventional energy.  

E-Print Network [OSTI]

Wind Powering America Fact Sheet Series 1 Wind energy is more expensive than conventional energy. Wind's variability does increase the day-to-day and minute-to- minute operating costs of a utility system because the wind variations do affect the operation of other plants. But investigations by utility

Massachusetts at Amherst, University of

287

Mid-Atlantic Regional Wind Energy Institute  

SciTech Connect (OSTI)

As the Department of Energy stated in its 20% Wind Energy by 2030 report, there will need to be enhanced outreach efforts on a national, state, regional, and local level to communicate wind development opportunities, benefits and challenges to a diverse set of stakeholders. To help address this need, PennFuture was awarded funding to create the Mid-Atlantic Regional Wind Energy Institute to provide general education and outreach on wind energy development across Maryland, Virginia, Delaware, Pennsylvania and West Virginia. Over the course of the two-year grant period, PennFuture used its expertise on wind energy policy and development in Pennsylvania and expanded it to other states in the Mid-Atlantic region. PennFuture accomplished this through reaching out and establishing connections with policy makers, local environmental groups, health and economic development organizations, and educational institutions and wind energy developers throughout the Mid-Atlantic region. PennFuture conducted two regional wind educational forums that brought together wind industry representatives and public interest organizations from across the region to discuss and address wind development in the Mid-Atlantic region. PennFuture developed the agenda and speakers in collaboration with experts on the ground in each state to help determine the critical issue to wind energy in each location. The sessions focused on topics ranging from the basics of wind development; model ordinance and tax issues; anti-wind arguments and counter points; wildlife issues and coalition building. In addition to in-person events, PennFuture held three webinars on (1) Generating Jobs with Wind Energy; (2) Reviving American Manufacturing with Wind Power; and (3) Wind and Transmission. PennFuture also created a web page for the institute (http://www.midatlanticwind.org) that contains an online database of fact sheets, research reports, sample advocacy letters, top anti-wind claims and information on how to address them, wind and wildlife materials and sample model ordinances. Video and presentations from each in-person meeting and webinar recordings are also available on the site. At the end of the two-year period, PennFuture has accomplished its goal of giving a unified voice and presence to wind energy advocates in the Mid-Atlantic region. We educated a broad range of stakeholders on the benefits of wind energy and gave them the tools to help make a difference in their states. We grew a database of over 500 contacts and hope to continue the discussion and work around the importance of wind energy in the region.

Courtney Lane

2011-12-20T23:59:59.000Z

288

Incorporating Wind Generation Forecast Uncertainty into Power System Operation, Dispatch, and Unit Commitment Procedures  

SciTech Connect (OSTI)

In this paper, an approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the "flying-brick" technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through integration with an EMS system illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems from other vendors.

Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Subbarao, Krishnappa

2010-10-19T23:59:59.000Z

289

Manzana Winds | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's Heat JumpIncMAKGalway Bay(HeldManhattan, Kansas: Energy ResourcesManzana Winds

290

Solar Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpenWende New EnergyAnatoliaSciraShenhuaWindPowerSohamBG Jump Place:

291

Minster Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpenWende New Energy Co LtdInformationMidwestMinster Wind Jump to:

292

National Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's HeatMexico: EnergyMithun JumpMuscoy,Jump9InformationCenter Jump to:Wind

293

Sandia National Laboratories: wind energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administrationcontroller systems controller systems Scaled Windwhite LED BriefWind EnergyiNEMI

294

Sandia National Laboratories: wind energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administrationcontroller systems controller systems Scaled Windwhite LED BriefWind EnergyiNEMIDutch

295

Sandia National Laboratories: wind energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administrationcontroller systems controller systems Scaled Windwhite LED BriefWind

296

Sandia National Laboratories: wind energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administrationcontroller systems controller systems Scaled Windwhite LED BriefWindNumerical

297

GL Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision has beenFfe2fb55-352f-473b-a2dd-50ae8b27f0a6TheoreticalFuelCell Energy IncFOR EGS Home > GroupsGL Wind

298

Establishing a Comprehensive Wind Energy Program  

SciTech Connect (OSTI)

This project was directed at establishing a comprehensive wind energy program in Indiana, including both educational and research components. A graduate/undergraduate course ME-514 - Fundamentals of Wind Energy has been established and offered and an interactive prediction of VAWT performance developed. Vertical axis wind turbines for education and research have been acquired, instrumented and installed on the roof top of a building on the Calumet campus and at West Lafayette (Kepner Lab). Computational Fluid Dynamics (CFD) calculations have been performed to simulate these urban wind environments. Also, modal dynamic testing of the West Lafayette VAWT has been performed and a novel horizontal axis design initiated. The 50-meter meteorological tower data obtained at the Purdue Beck Agricultural Research Center have been analyzed and the Purdue Reconfigurable Micro Wind Farm established and simulations directed at the investigation of wind farm configurations initiated. The virtual wind turbine and wind turbine farm simulation in the Visualization Lab has been initiated.

Fleeter, Sanford [Purdue University

2012-09-30T23:59:59.000Z

299

Altech Energy Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergy InformationTuriAlexandriaAlstom EnergyEnergy Wind Farm Jump

300

Prairie Wind Energy LLC | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia: Energy ResourcesLoadingPenobscot County, Maine:Plug Power IncPowder River EnergyCubePracticalPower,Wind Energy

Note: This page contains sample records for the topic "wind energy forecasts" 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

WREF 2012: THE PAST AND FUTURE COST OF WIND ENERGY  

E-Print Network [OSTI]

konomi (The Economy of Wind Power). EUDP 33033-0196.to the Chapter on Wind Power in Energy TechnologyAgency (DEA). (1999). Wind Power in Denmark: Technologies,

Wiser, Ryan

2013-01-01T23:59:59.000Z

302

Strengthening America's Energy Security with Offshore Wind (Fact Sheet) (Revised)  

SciTech Connect (OSTI)

This fact sheet provides a brief description of offshore wind energy development in the U.S. and DOE's Wind Program offshore wind R&D activities.

Not Available

2012-04-01T23:59:59.000Z

303

Value Capture in the Global Wind Energy Industry  

E-Print Network [OSTI]

Wind Energy Council, 2011 New installation in 2010 The wind industry value chain Wind turbineWind Energy Council (GWEC, 2011) domestic content in U.S. -deployed turbines

Dedrick, Jason; Kraemer, Kenneth L.

2011-01-01T23:59:59.000Z

304

Overview of Existing Wind Energy Ordinances  

Broader source: Energy.gov [DOE]

The purpose of this report is to educate and engage state and local governments, as well as policymakers, about existing large wind energy ordinances.

305

Carteret County- Wind Energy System Ordinance  

Broader source: Energy.gov [DOE]

Carteret County passed an ordinance to specify the permitting process and establish siting requirements for wind energy systems. There are different rules and a different permitting process...

306

Accelerating Offshore Wind Development | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

and support innovative offshore installations for commercial deployment by 2017. Offshore wind is a large, untapped energy resource, with the potential to generate 4,000 gigawatts...

307

Wind Energy Benefits, Wind Powering America (WPA) (Fact Sheet), Wind And Water Power Program (WWPP)  

Broader source: Energy.gov [DOE]

This fact sheet outlines the top 10 benefits of wind energy, including cost, water savings, job creation, indigenous resource, and low operating costs.

308

Solar and Wind Energy Equipment Exemption  

Broader source: Energy.gov [DOE]

In Wisconsin, any value added by a solar-energy system or a wind-energy system is exempt from general property taxes. A solar-energy system is defined as "equipment which directly converts and then...

309

Renewable Energy RFPs: Solicitation Response and Wind Contract Prices  

E-Print Network [OSTI]

Energy RFPs: Solicitation Response and Wind Contract Pricesenergy capacity (especially wind). Though detailed information on bid prices

Wiser, Ryan; Bolinger, Mark

2005-01-01T23:59:59.000Z

310

National Offshore Wind Energy Grid Interconnection Study  

SciTech Connect (OSTI)

The National Offshore Wind Energy Grid Interconnection Study (NOWEGIS) considers the availability and potential impacts of interconnecting large amounts of offshore wind energy into the transmission system of the lower 48 contiguous United States. A total of 54GW of offshore wind was assumed to be the target for the analyses conducted. A variety of issues are considered including: the anticipated staging of offshore wind; the offshore wind resource availability; offshore wind energy power production profiles; offshore wind variability; present and potential technologies for collection and delivery of offshore wind energy to the onshore grid; potential impacts to existing utility systems most likely to receive large amounts of offshore wind; and regulatory influences on offshore wind development. The technologies considered the reliability of various high-voltage ac (HVAC) and high-voltage dc (HVDC) technology options and configurations. The utility system impacts of GW-scale integration of offshore wind are considered from an operational steady-state perspective and from a regional and national production cost perspective.

Daniel, John P. [ABB Inc; Liu, Shu [ABB Inc; Ibanez, Eduardo [National Renewable Energy Laboratory; Pennock, Ken [AWS Truepower; Reed, Greg [University of Pittsburgh; Hanes, Spencer [Duke Energy

2014-07-30T23:59:59.000Z

311

Forecast of Regional Power Output of Wind Turbines Hans Georg Beyer, Detlev Heinemann, Harald Mellinghoff, Kai Monnich, Hans-Peter Waldl  

E-Print Network [OSTI]

Forecast of Regional Power Output of Wind Turbines Hans Georg Beyer, Detlev Heinemann, Harald of wind turbines connected to the public electricity grid will be intro- duced. Using this procedure and Northern Germany. At the moment, the installed capacity of wind turbines is in the order of magnitude

Heinemann, Detlev

312

WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy  

E-Print Network [OSTI]

in each of the wind energy markets around the globe. Alsoin each of the wind energy markets around the globe. Alsoprice of wind energy in wholesale markets. 13 3.1 Historical

Lantz, Eric

2014-01-01T23:59:59.000Z

313

Wyoming Wind Energy Center | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 NoPublic Utilities Address: 160 East 300 South Place:ReferenceEditWisconsin: EnergyEdison,Wind Energy Center Jump to:

314

HTH Wind Energy Inc | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpen EnergyBoard" form.Guizhou New Material DevHGEHTH Wind Energy

315

Han Wind Energy Corporation | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpen EnergyBoard" form.Guizhou New MaterialHan Wind Energy

316

Suzlon Wind Energy Corp | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia:FAQ < RAPID Jump to:Seadov Pty LtdSteen,Ltd Jump to: navigation, search Name:STS JumpSuzlon EnergyWind Energy

317

Illinois Wind Energy | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia: Energy Resources Jump to: navigation,Ohio:GreerHiCalifornia:ISI SolarIdanha, Oregon:IkeIllinois River EnergyWind

318

Upcoming Funding Opportunity to Develop and Field Test Wind Energy...  

Energy Savers [EERE]

and operating wind energy facilities in locations with sensitive bat species. As wind energy continues to grow as a renewable source of energy for communities throughout...

319

Three Essays on Energy Economics and Forecasting  

E-Print Network [OSTI]

This dissertation contains three independent essays relating energy economics. The first essay investigates price asymmetry of diesel in South Korea by using the error correction model. Analyzing weekly market prices in the pass-through of crude oil...

Shin, Yoon Sung

2012-02-14T23:59:59.000Z

320

Wind Energy Education and Training Programs (Postcard)  

SciTech Connect (OSTI)

As the United States dramatically expands wind energy deployment, the industry is challenged with developing a skilled workforce to support it. The Wind Powering America website features a map of wind energy education and training program locations at community colleges, universities, and other institutions in the United States. The map includes links to contacts and program details. This postcard is a marketing piece that stakeholders can provide to interested parties; it will guide them to this online resource for wind energy education and training programs episodes.

Not Available

2012-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind energy forecasts" 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

Fostering a Renewable Energy Technology Industry: An International Comparison of Wind Industry Policy Support Mechanisms  

E-Print Network [OSTI]

and Renewable Energy, Wind & Hydropower Technologiesand Renewable Energy, Wind & Hydropower Technologies2004. International Wind Energy Development, World Market

Lewis, Joanna; Wiser, Ryan

2005-01-01T23:59:59.000Z

322

The Cost of Transmission for Wind Energy: A Review of Transmission Planning Studies  

E-Print Network [OSTI]

2006. Transmission and Wind Energy: Capturing the Prevailingand Renewable Energy (Wind & Hydropower Technologiesand Renewable Energy Wind & Hydropower Technologies Program

Mills, Andrew D.

2009-01-01T23:59:59.000Z

323

IEA Wind Energy Annual Report 2000  

SciTech Connect (OSTI)

The twenty-third IEA Wind Energy Annual Report reviews the progress during 2000 of the activities in the Implementing Agreement for Co-operation in the Research and Development on Wind Turbine Systems under the auspices of the International Energy Agency (IEA). The agreement and its program, which is known as IEA R&D Wind, is a collaborative venture among 19 contracting parties from 17 IEA member countries and the European Commission.

Not Available

2001-05-01T23:59:59.000Z

324

Wind Energy Facilities and Residential Properties: The Effect of Proximity and View on Sales Prices  

E-Print Network [OSTI]

U.S. Department of Energy (Wind and Hydropower Technologiesand Renewable Energy (Wind & Hydropower TechnologiesPublic Perceptions of Wind Energy. Wind Energy, 2004, 8:2,

Hoen, Ben

2012-01-01T23:59:59.000Z

325

Wind Energy Facilities and Residential Properties: The Effect of Proximity and View on Sales Prices  

E-Print Network [OSTI]

and Renewable Energy (Wind & Hydropower TechnologiesU.S. Department of Energy (Wind and Hydropower TechnologiesPublic Perceptions of Wind Energy. Wind Energy, 2004, 8:2,

Hoen, Ben

2012-01-01T23:59:59.000Z

326

The KAMM/WAsP Numerical Wind Atlas A powerful ingredient for wind energy planning  

E-Print Network [OSTI]

The KAMM/WAsP Numerical Wind Atlas A powerful ingredient for wind energy planning J. Badger, N.G. Mortensen, J.C. Hansen Wind Energy Department Risø National Laboratory Great Wall World Renewable Energy Forum Beijing, 23-27 October 2006 #12;Wind Farm Planning National Wind Atlas Environmental Atlases Maps

327

2010 Wind Technologies Market Report  

E-Print Network [OSTI]

2011. North America Wind Energy Market Forecast: 20112025.study. Regions with fast energy markets, for example, changea sub-hourly, real-time energy market providing centralized,

Wiser, Ryan

2012-01-01T23:59:59.000Z

328

Xcel Energy Wind and Biomass Generation Mandate  

Broader source: Energy.gov [DOE]

Minnesota law (Minn. Stat. 216B.2423) requires Xcel Energy to build or contract for 225 megawatts (MW) of installed wind-energy capacity in the state by December 31, 1998, and to build or...

329

Distributed Wind Energy Association | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 NoPublic Utilities Address:011-DNA Jump to:52c8ff988c1Dering Harbor,Discount PowerEmerlingEnergyDistributed Wind

330

Port Clair Wind Energy | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpenWende New Energy CoFirstNovosPatriot Wind IncAsiaPolls Home >

331

Minco Wind Energy Center | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's HeatMexico: Energy Resources JumpMicrelBirds JumpMilner Dam WindIII Jump to:OK

332

Mogul Energy Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's HeatMexico: EnergyMithun Jump to:Moe Wind Farm Jump to: navigation,

333

Stateline Wind Energy Project | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revisionEnvReviewNonInvasiveExplorationUT-g GrantAtlas (PACA RegionSpringviewName Stateline Wind Energy Project

334

Ainsworth Wind Energy Facility | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergy Information LightningAiken Electric Coop IncAinsworth Wind

335

Wales Wind Energy Project | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 NoPublic Utilities Address: 160 East 300 South Place: Salt Lake City,Division of OilGuyane8031909°,Wales Wind Energy

336

EU Energy Wind Limited | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORT Americium/CuriumSunwaysDatangGmbH Jump to:ENERCONEU Energy (Wind)

337

AMEC Wind Energy | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 NoPublic Utilities Address: 160 East 300 SouthWater Rights,InformationWind Energy Jump to: navigation, search

338

Gary Wind Energy Project | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision has beenFfe2fb55-352f-473b-a2dd-50ae8b27f0a6TheoreticalFuelCell Energy IncFORTechnologyGammaGary Wind

339

Oliver Wind Energy Center | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth'sOklahoma/Geothermal < Oklahoma Jump to: navigation,Olene GapWind Energy

340

Idaho Wind Energy | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia: Energy Resources Jump to: navigation,Ohio:GreerHiCalifornia:ISI Solar JumpObtain EPAFormAdvisory GroupsWind

Note: This page contains sample records for the topic "wind energy forecasts" 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.


341

Wind energy and SAR wind mapping Charlotte Hasager(2) and merete christiansen(1)  

E-Print Network [OSTI]

offshore wind farms are operating and more are in construction. Thus the study is focussed on an area is ongoing, and the series of wind maps are used for investigation of offshore wind resources. In wind energy the siting of a wind farm is dependent upon reliable information about the wind climate within the area

342

20% Wind Energy By 2030 Meeting The Challenges Proceedings of...  

Office of Environmental Management (EM)

from the Wind Manufacturing Workshop: Achieving 20% Wind Energy in the U.S. by 2030, May 2009 U.S. Offshore Wind Manufacturing and Supply Chain Development Offshore Wind Projects...

343

Hull Wind: A Community Gets Green | Department of Energy  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Hull Wind: A Community Gets Green Hull Wind: A Community Gets Green U.S. Department of Energy Community and Renewable Energy Success Stories webinar series titled Wind Energy in...

344

Wind Power Today: Building a New Energy Future, Wind and Hydropower Technologies Program 2009 (Brochure)  

SciTech Connect (OSTI)

Wind Power Today is an annual publication that provides an overview of the wind energy research conducted by the U.S. Department of Energy Wind and Hydropower Technologies Program.

Not Available

2009-04-01T23:59:59.000Z

345

Energy Department Announces New Regional Approach to Wind Energy...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Energy Initiates New Outreach Efforts to Address a Changing Wind Industry This map shows wind potential capacity for turbine hub heights at 140 meters. Mapping the Frontier of New...

346

EIS-0470: Cape Wind Energy Project, Nantucket Sound, Offshore...  

Broader source: Energy.gov (indexed) [DOE]

0: Cape Wind Energy Project, Nantucket Sound, Offshore of Massachusetts EIS-0470: Cape Wind Energy Project, Nantucket Sound, Offshore of Massachusetts June 25, 2014 EIS-0470: Cape...

347

Deployment Barriers to Distributed Wind Energy: Workshop Report...  

Energy Savers [EERE]

Deployment Barriers to Distributed Wind Energy: Workshop Report, October 28, 2010 Deployment Barriers to Distributed Wind Energy: Workshop Report, October 28, 2010 This report...

348

Securing Clean, Domestic, Affordable Energy with Wind (Fact Sheet)  

SciTech Connect (OSTI)

This fact sheet provides a brief description of the Wind Energy Market and describes the U.S. Department of Energy's Wind Program research and development efforts.

Not Available

2012-10-01T23:59:59.000Z

349

NREL: Systems Engineering - 2015 Wind Energy Systems Engineering...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Research Systems Engineering Printable Version 2015 Wind Energy Systems Engineering Workshop The third NREL Wind Energy Systems Engineering Workshop took place on the 14th and 15th...

350

Chinas Wind Energy Development and Prediction.  

E-Print Network [OSTI]

??This thesis focuses on Chinas wind energy development, focusing on data pertaining to effects of wind energy development on economic, environmental, and social issues. It (more)

Wallin, Micah R.

2010-01-01T23:59:59.000Z

351

Wind Energy Status and R&D Challenges  

SciTech Connect (OSTI)

A presentation made to the European Wind Energy Conference in Athens, Greece, February 27--March 2, 2006, on wind energy technology.

Parsons, B.

2006-03-01T23:59:59.000Z

352

Expanding Educational Opportunities for the Wind Energy Workforce...  

Energy Savers [EERE]

Expanding Educational Opportunities for the Wind Energy Workforce Expanding Educational Opportunities for the Wind Energy Workforce April 11, 2013 - 12:00am Addthis The University...

353

Recovery Act: Wind Energy Consortia between Institutions of Higher...  

Broader source: Energy.gov (indexed) [DOE]

Recovery Act: Wind Energy Consortia between Institutions of Higher Learning and Industry Recovery Act: Wind Energy Consortia between Institutions of Higher Learning and Industry A...

354

Monitoring bat and bird fatalities at the Casselman Wind Energy...  

Broader source: Energy.gov (indexed) [DOE]

Monitoring bat and bird fatalities at the Casselman Wind Energy Center in Pennsylvania Monitoring bat and bird fatalities at the Casselman Wind Energy Center in Pennsylvania...

355

WInd engineering and Renewable Energy laboratory Gnie Mcanique  

E-Print Network [OSTI]

WInd engineering and Renewable Energy laboratory Section de Génie Mécanique - Master Project - Wind tunnel investigations on wind farms Juliette Coëffé (juliette.coeffe@epfl.ch) ABSTRACT Wind energy efficient and optimized wind energy systems are needed. To this end, this master project, carried out

Lausanne, Ecole Polytechnique Fédérale de

356

A COOLING SYSTEM FOR BUIDINGS USING WIND ENERGY  

E-Print Network [OSTI]

A COOLING SYSTEM FOR BUIDINGS USING WIND ENERGY Hamid Daiyan Islamic Azad University - Semnan in dray land, and only uses wind energy for conditioning. It technologies date back over 1000 years. Wind system, Wind energy, Temperature Fig.1 Wind tower of Doulat-Abad garden of Yazd with it's altitude is 33

357

MESOSCALE MODELLING OF WIND ENERGY OVER NON-HOMOGENEOUS TERRAIN  

E-Print Network [OSTI]

MESOSCALE MODELLING OF WIND ENERGY OVER NON-HOMOGENEOUS TERRAIN (ReviewArticle) Y. MAHRER.1. OBSERVATIONALAPPROACHES Evaluations of wind energy based on wind observations (usually surface winds) at well, the resolution of the wind energy pattern throughout an extended area by this methodology requires a large number

Pielke, Roger A.

358

Ris-R-1479(EN) Satellite information for wind energy  

E-Print Network [OSTI]

wind power potential. Scatterometer wind data are observed ~ twice per day, whereas SAR onlyRisø-R-1479(EN) Satellite information for wind energy applications Morten Nielsen, Poul Astrup Title: Satellite information for wind energy applications Department: Wind Energy Department Risø-R-1479

359

The Cost of Transmission for Wind Energy: A Review of Transmission Planning Studies  

E-Print Network [OSTI]

2006. Transmission and Wind Energy: Capturing the Prevailing40 6.2 20% Wind Energy: Wind Deployment System (and Renewable Energy (Wind & Hydropower Technologies

Mills, Andrew D.

2009-01-01T23:59:59.000Z

360

WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy  

E-Print Network [OSTI]

Energy Efficiency and Renewable Energy. Wiser, R. ; Lantz,Economics of Wind Energy. Renewable and Sustainable EnergyGolden, CO: National Renewable Energy Laboratory. Carbon

Lantz, Eric

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind energy forecasts" 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

Mountain Wind I Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's HeatMexico: EnergyMithun Jump to:Moe WindMontMoraineAbbeyI Wind Farm JumpIIIkW

362

Mountain Wind II Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's HeatMexico: EnergyMithun Jump to:Moe WindMontMoraineAbbeyI Wind Farm

363

Wind energy curriculum development at GWU  

SciTech Connect (OSTI)

A wind energy curriculum has been developed at the George Washington University, School of Engineering and Applied Science. Surveys of student interest and potential employers expectations were conducted. Wind industry desires a combination of mechanical engineering training with electrical engineering training. The curriculum topics and syllabus were tested in several graduate/undergraduate elective courses. The developed curriculum was then submitted for consideration.

Hsu, Stephen M [GWU

2013-06-08T23:59:59.000Z

364

2011 Cost of Wind Energy Review  

SciTech Connect (OSTI)

This report describes the levelized cost of energy (LCOE) for a typical land-based wind turbine installed in the United States in 2011, as well as the modeled LCOE for a fixed-bottom offshore wind turbine installed in the United States in 2011. Each of the four major components of the LCOE equation are explained in detail, such as installed capital cost, annual energy production, annual operating expenses, and financing, and including sensitivity ranges that show how each component can affect LCOE. These LCOE calculations are used for planning and other purposes by the U.S. Department of Energy's Wind Program.

Tegen, S.; Lantz, E.; Hand, M.; Maples, B.; Smith, A.; Schwabe, P.

2013-03-01T23:59:59.000Z

365

Wind Energy Guide for County Commissioners  

SciTech Connect (OSTI)

One of the key stakeholders associated with economic development are local government officials, who are often required to evaluate and vote on commercial wind energy project permits, as well as to determine and articulate what wind energy benefits accrue to their counties. Often these local officials lack experience with large-scale wind energy and need to make important decisions concerning what may be a complicated and controversial issue. These decisions can be confounded with diverse perspectives from various stakeholders. This project is designed to provide county commissioners, planners, and other local county government officials with a practical overview of information required to successfully implement commercial wind energy projects in their county. The guidebook provides readers with information on the following 13 topics: Brief Wind Energy Overview; Environmental Benefits; Wind Energy Myths and Facts; Economic Development Benefits; Wind Economics; The Development Process; Public Outreach; Siting Issues; Property Tax Incentives; Power System Impacts; Permitting, Zoning, and Siting Processes; Case Studies; and Further Information. For each of the above topics, the guidebook provides an introduction that identifies the topic, why local government should care, a topic snapshot, how the topic will arise, and a list of resources that define and assess the topic.

Costanti, M.

2006-10-01T23:59:59.000Z

366

Wind Energy Assessment using a Wind Turbine with Dynamic Yaw Control.  

E-Print Network [OSTI]

??The goal of this project was to analyze the wind energy potential over Lake Michigan. For this purpose, a dynamic model of a utility-scale wind (more)

Pervez, Md Nahid

2013-01-01T23:59:59.000Z

367

NREL: Systems Engineering - 2010 Wind Energy Systems Engineering...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

0 Wind Energy Systems Engineering Workshop The 1st NREL Wind Energy Systems Engineering Workshop took place on December 14, 2010, at the National Wind Technology Center (NWTC). The...

368

Aleutian Pribilof Islands Wind Energy Feasibility Study  

SciTech Connect (OSTI)

Under this project, the Aleutian Pribilof Islands Association (APIA) conducted wind feasibility studies for Adak, False Pass, Nikolski, Sand Point and St. George. The DOE funds were also be used to continue APIA's role as project coordinator, to expand the communication network quality between all participants and with other wind interest groups in the state and to provide continued education and training opportunities for regional participants. This DOE project began 09/01/2005. We completed the economic and technical feasibility studies for Adak. These were funded by the Alaska Energy Authority. Both wind and hydro appear to be viable renewable energy options for Adak. In False Pass the wind resource is generally good but the site has high turbulence. This would require special care with turbine selection and operations. False Pass may be more suitable for a tidal project. APIA is funded to complete a False Pass tidal feasibility study in 2012. Nikolski has superb potential for wind power development with Class 7 wind power density, moderate wind shear, bi-directional winds and low turbulence. APIA secured nearly $1M from the United States Department of Agriculture Rural Utilities Service Assistance to Rural Communities with Extremely High Energy Costs to install a 65kW wind turbine. The measured average power density and wind speed at Sand Point measured at 20m (66ft), are 424 W/m2 and 6.7 m/s (14.9 mph) respectively. Two 500kW Vestas turbines were installed and when fully integrated in 2012 are expected to provide a cost effective and clean source of electricity, reduce overall diesel fuel consumption estimated at 130,000 gallons/year and decrease air emissions associated with the consumption of diesel fuel. St. George Island has a Class 7 wind resource, which is superior for wind power development. The current strategy, led by Alaska Energy Authority, is to upgrade the St. George electrical distribution system and power plant. Avian studies in Nikolski and Sand Point have allowed for proper wind turbine siting without killing birds, especially endangered species and bald eagles. APIA continues coordinating and looking for funding opportunities for regional renewable energy projects. An important goal for APIA has been, and will continue to be, to involve community members with renewable energy projects and energy conservation efforts.

Bruce A. Wright

2012-03-27T23:59:59.000Z

369

Model Wind Energy Facility Ordinance  

Broader source: Energy.gov [DOE]

Note: This model ordinance was designed to provide guidance to local governments that wish to develop their own siting rules for wind turbines. While it was developed as part of a cooperative...

370

American Wind Energy Association Offshore WINDPOWER Conference...  

Broader source: Energy.gov (indexed) [DOE]

Offshore WINDPOWER Conference & Exhibition American Wind Energy Association Offshore WINDPOWER Conference & Exhibition October 7, 2014 9:00AM EDT to October 8, 2014 5:00PM EDT AWEA...

371

Overview of Existing Wind Energy Ordinances  

SciTech Connect (OSTI)

Due to increased energy demand in the United States, rural communities with limited or no experience with wind energy now have the opportunity to become involved in this industry. Communities with good wind resources may be approached by entities with plans to develop the resource. Although these opportunities can create new revenue in the form of construction jobs and land lease payments, they also create a new responsibility on the part of local governments to ensure that ordinances will be established to aid the development of safe facilities that will be embraced by the community. The purpose of this report is to educate and engage state and local governments, as well as policymakers, about existing large wind energy ordinances. These groups will have a collection of examples to utilize when they attempt to draft a new large wind energy ordinance in a town or county without existing ordinances.

Oteri, F.

2008-12-01T23:59:59.000Z

372

Pitt County- Wind Energy Systems Ordinance  

Broader source: Energy.gov [DOE]

The Pitt County Board of Commissioners adopted amendments to the county zoning ordinance in March 2010 which classify wind energy systems as an accessory use and establish siting and permitting...

373

Prediction of wind speed profiles for short-term forecasting in the offshore environment R.J. Barthelmie and G. Giebel  

E-Print Network [OSTI]

in the forecast wind speed/power output might be anticipated using a directional rather than a constant bias for the calibration phase. A further advantage is that statistical techniques can predict power output directly rather than having to take the additional step of predicting power output from wind speed through the power

374

WIND ENERGY Wind Energ. 2001; 4:173181 (DOI: 10.1002/we.54)  

E-Print Network [OSTI]

WIND ENERGY Wind Energ. 2001; 4:173­181 (DOI: 10.1002/we.54) Research Article Comparison of Geography, Indiana University, Bloomington, IN 47405, USA R. J. Barthelmie, Department of Wind Energy Wiley & Sons, Ltd. Introduction With the announcement of plans to develop offshore wind energy in many

Pryor, Sara C.

375

The Answer Is Blowing in the Wind: Analysis of Powering Internet Data Centers with Wind Energy  

E-Print Network [OSTI]

The Answer Is Blowing in the Wind: Analysis of Powering Internet Data Centers with Wind Energy Yan. As a result, many IDC operators have started using renewable energy, e.g., wind power, to power their data centers. Unfortunately, the utilization of wind energy has stayed at a low ratio due to the intermittent

376

WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy  

E-Print Network [OSTI]

Cost of Energy From U.S. Wind Power Projects. PresentationTrust. (2008). Offshore Wind Power: Big Challenge, BigAgency (DEA). (1999). Wind Power in Denmark: Technologies,

Lantz, Eric

2014-01-01T23:59:59.000Z

377

Sandia National Laboratories: Wind Energy Staff  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1development Sandia, NREL Release Wave EnergyLinks WaterWind EnergyEnergyWind Energy

378

Wind Energy Workforce Development: Engineering, Science, & Technology  

SciTech Connect (OSTI)

Broadly, this project involved the development and delivery of a new curriculum in wind energy engineering at the Pennsylvania State University; this includes enhancement of the Renewable Energy program at the Pennsylvania College of Technology. The new curricula at Penn State includes addition of wind energy-focused material in more than five existing courses in aerospace engineering, mechanical engineering, engineering science and mechanics and energy engineering, as well as three new online graduate courses. The online graduate courses represent a stand-alone Graduate Certificate in Wind Energy, and provide the core of a Wind Energy Option in an online intercollege professional Masters degree in Renewable Energy and Sustainability Systems. The Pennsylvania College of Technology erected a 10 kilowatt Xzeres wind turbine that is dedicated to educating the renewable energy workforce. The entire construction process was incorporated into the Renewable Energy A.A.S. degree program, the Building Science and Sustainable Design B.S. program, and other construction-related coursework throughout the School of Construction and Design Technologies. Follow-on outcomes include additional non-credit opportunities as well as secondary school career readiness events, community outreach activities, and public awareness postings.

Lesieutre, George A.; Stewart, Susan W.; Bridgen, Marc

2013-03-29T23:59:59.000Z

379

Design of wind farm layout for maximum wind energy capture Andrew Kusiak*, Zhe Song  

E-Print Network [OSTI]

Design of wind farm layout for maximum wind energy capture Andrew Kusiak*, Zhe Song Intelligent Accepted 24 August 2009 Available online 22 September 2009 Keywords: Wind farm Wind turbine Layout design Optimization Evolutionary algorithms Operations research a b s t r a c t Wind is one of the most promising

Kusiak, Andrew

380

Nancy Rader, Executive Director California Wind Energy Association  

E-Print Network [OSTI]

Nancy Rader, Executive Director California Wind Energy Association Improving Methods for Estimating Fatality of Birds and Bats at Wind Energy Facilities California Wind Energy Association Public Webinar Wind Energy Development 2008 CEC Research "Roadmap" on Impact Assessment Methods 2008 CEC PIER RFP 2009

Note: This page contains sample records for the topic "wind energy forecasts" 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

Tools supporting wind energy trade in deregulated markets  

E-Print Network [OSTI]

Tools supporting wind energy trade in deregulated markets ´Ulfar Linnet Kongens Lyngby 2005 IMM.imm.dtu.dk IMM-THESIS: ISSN 0909-3192 #12;Abstract A large share of the wind energy produced in Scandinavia in a fine, called regulation cost. As wind energy comes from an uncontrollable energy source - the wind

382

Tools supporting wind energy trade in deregulated markets  

E-Print Network [OSTI]

Tools supporting wind energy trade in deregulated markets ?? Ulfar Linnet Kongens Lyngby 2005 IMM.imm.dtu.dk IMM­THESIS: ISSN 0909­3192 #12; Abstract A large share of the wind energy produced in Scandinavia in a fine, called regulation cost. As wind energy comes from an uncontrollable energy source ­ the wind

383

High Energy Studies of Pulsar Wind Nebulae  

E-Print Network [OSTI]

The extended nebulae formed as pulsar winds expand into their surroundings provide information about the composition of the winds, the injection history from the host pulsar, and the material into which the nebulae are expanding. Observations from across the electromagnetic spectrum provide constraints on the evolution of the nebulae, the density and composition of the surrounding ejecta, the geometry of the systems, the formation of jets, and the maximum energy of the particles in the nebulae. Here I provide a broad overview of the structure of pulsar wind nebulae, with specific examples that demonstrate our ability to constrain the above parameters. The association of pulsar wind nebulae with extended sources of very high energy gamma-ray emission are investigated, along with constraints on the nature of such high energy emission.

Patrick Slane

2008-11-12T23:59:59.000Z

384

High Energy Studies of Pulsar Wind Nebulae  

E-Print Network [OSTI]

The extended nebulae formed as pulsar winds expand into their surroundings provide information about the composition of the winds, the injection history from the host pulsar, and the material into which the nebulae are expanding. Observations from across the electromagnetic spectrum provide constraints on the evolution of the nebulae, the density and composition of the surrounding ejecta, the geometry of the systems, the formation of jets, and the maximum energy of the particles in the nebulae. Here I provide a broad overview of the structure of pulsar wind nebulae, with specific examples that demonstrate our ability to constrain the above parameters. The association of pulsar wind nebulae with extended sources of very high energy gamma-ray emission are investigated, along with constraints on the nature of such high energy emission.

Slane, Patrick

2008-01-01T23:59:59.000Z

385

Utilization of Wind Energy at High Altitude  

E-Print Network [OSTI]

Ground based, wind energy extraction systems have reached their maximum capability. The limitations of current designs are: wind instability, high cost of installations, and small power output of a single unit. The wind energy industry needs of revolutionary ideas to increase the capabilities of wind installations. This article suggests a revolutionary innovation which produces a dramatic increase in power per unit and is independent of prevailing weather and at a lower cost per unit of energy extracted. The main innovation consists of large free-flying air rotors positioned at high altitude for power and air stream stability, and an energy cable transmission system between the air rotor and a ground based electric generator. The air rotor system flies at high altitude up to 14 km. A stability and control is provided and systems enable the changing of altitude. This article includes six examples having a high unit power output (up to 100 MW). The proposed examples provide the following main advantages: 1. Large power production capacity per unit - up to 5,000-10,000 times more than conventional ground-based rotor designs; 2. The rotor operates at high altitude of 1-14 km, where the wind flow is strong and steady; 3. Installation cost per unit energy is low. 4. The installation is environmentally friendly (no propeller noise). -- * Presented in International Energy Conversion Engineering Conference at Providence., RI, Aug. 16-19. 2004. AIAA-2004-5705. USA. Keyword: wind energy, cable energy transmission, utilization of wind energy at high altitude, air rotor, windmills, Bolonkin.

Alexander Bolonkin

2007-01-10T23:59:59.000Z

386

Forecasting the Market Penetration of Energy Conservation Technologies: The Decision Criteria for Choosing a Forecasting Model  

E-Print Network [OSTI]

capital requirements and research and development programs in the alum inum industry. : CONCLUSIONS Forecasting the use of conservation techndlo gies with a market penetration model provides la more accountable method of projecting aggrega...

Lang, K.

1982-01-01T23:59:59.000Z

387

Solar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting Questionnaire As someone who is familiar with solar energy issues, we hope that you will tak  

E-Print Network [OSTI]

is familiar with solar energy issues, we hope that you will take a few moments to answer this short survey on your needs for information on solar energy resources and forecasting. This survey is conducted with the California Solar Energy Collaborative (CSEC) and the California Solar Initiative (CSI) our objective

Islam, M. Saif

388

Cape Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORT Americium/CuriumSunways JV JumpBraselcoCMNACangnan Gelin WindWind

389

Wind-To-Hydrogen Energy Pilot Project  

SciTech Connect (OSTI)

WIND-TO-HYDROGEN ENERGY PILOT PROJECT: BASIN ELECTRIC POWER COOPERATIVE In an effort to address the hurdles of wind-generated electricity (specifically wind's intermittency and transmission capacity limitations) and support development of electrolysis technology, Basin Electric Power Cooperative (BEPC) conducted a research project involving a wind-to-hydrogen system. Through this effort, BEPC, with the support of the Energy & Environmental Research Center at the University of North Dakota, evaluated the feasibility of dynamically scheduling wind energy to power an electrolysis-based hydrogen production system. The goal of this project was to research the application of hydrogen production from wind energy, allowing for continued wind energy development in remote wind-rich areas and mitigating the necessity for electrical transmission expansion. Prior to expending significant funding on equipment and site development, a feasibility study was performed. The primary objective of the feasibility study was to provide BEPC and The U.S. Department of Energy (DOE) with sufficient information to make a determination whether or not to proceed with Phase II of the project, which was equipment procurement, installation, and operation. Four modes of operation were considered in the feasibility report to evaluate technical and economic merits. Mode 1 - scaled wind, Mode 2 - scaled wind with off-peak, Mode 3 - full wind, and Mode 4 - full wind with off-peak In summary, the feasibility report, completed on August 11, 2005, found that the proposed hydrogen production system would produce between 8000 and 20,000 kg of hydrogen annually depending on the mode of operation. This estimate was based on actual wind energy production from one of the North Dakota (ND) wind farms of which BEPC is the electrical off-taker. The cost of the hydrogen produced ranged from $20 to $10 per kg (depending on the mode of operation). The economic sensitivity analysis performed as part of the feasibility study showed that several factors can greatly affect, both positively and negatively, the "per kg" cost of hydrogen. After a September 15, 2005, meeting to evaluate the advisability of funding Phase II of the project DOE concurred with BEPC that Phase I results did warrant a "go" recommendation to proceed with Phase II activities. The hydrogen production system was built by Hydrogenics and consisted of several main components: hydrogen production system, gas control panel, hydrogen storage assembly and hydrogen-fueling dispenser The hydrogen production system utilizes a bipolar alkaline electrolyzer nominally capable of producing 30 Nm3/h (2.7 kg/h). The hydrogen is compressed to 6000 psi and delivered to an on-site three-bank cascading storage assembly with 80 kg of storage capacity. Vehicle fueling is made possible through a Hydrogenics-provided gas control panel and dispenser able to fuel vehicles to 5000 psi. A key component of this project was the development of a dynamic scheduling system to control the wind energy's variable output to the electrolyzer cell stacks. The dynamic scheduling system received an output signal from the wind farm, processed this signal based on the operational mode, and dispatched the appropriate signal to the electrolyzer cell stacks. For the study BEPC chose to utilize output from the Wilton wind farm located in central ND. Site design was performed from May 2006 through August 2006. Site construction activities were from August to November 2006 which involved earthwork, infrastructure installation, and concrete slab construction. From April - October 2007, the system components were installed and connected. Beginning in November 2007, the system was operated in a start-up/shakedown mode. Because of numerous issues, the start-up/shakedown period essentially lasted until the end of January 2008, at which time a site acceptance test was performed. Official system operation began on February 14, 2008, and continued through the end of December 2008. Several issues continued to prevent consistent operation, resulting in operation o

Ron Rebenitsch; Randall Bush; Allen Boushee; Brad G. Stevens; Kirk D. Williams; Jeremy Woeste; Ronda Peters; Keith Bennett

2009-04-24T23:59:59.000Z

390

Wind Turbine Tribology Seminar | Department of Energy  

Office of Environmental Management (EM)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergyENERGYWomen Owned SmallOf TheViolations | Department ofEnergy Wind Power06 WindofWind

391

Forecasting the Hourly Ontario Energy Price by Multivariate Adaptive Regression Splines  

E-Print Network [OSTI]

1 Forecasting the Hourly Ontario Energy Price by Multivariate Adaptive Regression Splines H. In this paper, the MARS technique is applied to forecast the hourly Ontario energy price (HOEP). The MARS models values of the latest pre- dispatch price and demand information, made available by the Ontario

Cañizares, Claudio A.

392

Ris Energy Report 5 Wind 2 In the past 20 years wind energy has proved itself as a  

E-Print Network [OSTI]

Risø Energy Report 5 Wind 2 6.1 Status In the past 20 years wind energy has proved itself all these achievements, wind energy remains on the fringes of power generation. For people working ignorance and emo- tional opposition. Wind energy is far from having been proved to lay people, large

393

Expedited Permitting of Grid-Scale Wind Energy Development (Maine)  

Broader source: Energy.gov [DOE]

Maine's Expedited Permitting of Grid-Scale Wind Energy Development statue provides an expedited permitting pathway for proposed wind developments in certain designated locations, known as expedited...

394

Assessment of Offshore Wind Energy Resources for the United States...  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Offshore Wind Energy Resources for the United States This report summarizes the offshore wind resource potential for the contiguous United States and Hawaii as of May 2009. The...

395

An exploration of wind energy and wind turbines  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:YearRound-Up fromDepartment ofEnergy Natural Gas:Austin,AnAn Exploration of Wind Energy and

396

Wind Energy in Indian Country: Turning to Wind for the Seventh Generation  

E-Print Network [OSTI]

Wind Energy in Indian Country: Turning to Wind for the Seventh Generation by Andrew D. Mills: ___________________________________________ Jane Stahlhut Date #12;Wind Energy in Indian Country A.D. Mills Abstract - ii - Abstract Utility-scale wind projects are increasingly being developed in rural areas of the United States. In the West

Kammen, Daniel M.

397

Cedar Point Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergyCTBarreis aCallahanWindSyracuse, NYCedar Creek Wind FarmPoint Wind

398

Cedar Ridge Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergyCTBarreis aCallahanWindSyracuse, NYCedar Creek WindRidge Wind Farm

399

Moraine Wind Power Project | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's HeatMexico: EnergyMithun Jump to:Moe WindMontMoraine II Wind Farm Jump to:Wind

400

Cedar Hills Wind Facility | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergyCTBarreis aCallahanWindSyracuse, NYCedar Creek Wind Farm IIFacility

Note: This page contains sample records for the topic "wind energy forecasts" 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

Indiana/Wind Resources | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia: Energy Resources Jump to:46 - 429 Throttled (bot load) Error 429Indiana Wind Resources WindTurbine-icon.png

402

THE DANISH CONSORTIUM FOR WIND ENERGY RESEARCH Lars Landberg1  

E-Print Network [OSTI]

THE DANISH CONSORTIUM FOR WIND ENERGY RESEARCH Lars Landberg1 and Peter Hauge Madsen2 1 Risø National Laboratory, Wind Energy Department, DK-4000 Roskilde, Denmark; lars.landberg@risoe.dk 2 Siemens Wind Power, DK-7330 Brande, Denmark Abstract The Danish Wind Energy Research Consortium

403

Strengthening America's Energy Security with Offshore Wind (Fact Sheet)  

SciTech Connect (OSTI)

This fact sheet describes the current state of the offshore wind industry in the United States and the offshore wind research and development activities conducted the U.S. Department of Energy Wind and Water Power Program.

Not Available

2012-02-01T23:59:59.000Z

404

Camp Springs Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergyCTBarreis aCallahan Divide Wind EnergyEnergyCameroon: WindCamp

405

Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability  

Broader source: Energy.gov [DOE]

Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability

406

DOE Announces Webinars on Real Time Energy Management, Solar Forecasting  

Broader source: Energy.gov (indexed) [DOE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "ofEarly Career Scientists'Montana. DOCUMENTS AVAILABLEReportEnergy EfficiencyDavis-BaconOffshore WindMetrics,

407

Wind Energy Stakeholder Outreach and Education  

SciTech Connect (OSTI)

Since August of 2001, Bob Lawrence and Associates, Inc. (BL&A) has applied its outreach and support services to lead a highly effective work effort on behalf of Wind Powering America (WPA). In recent years, the company has generated informative brochures and posters, researched and created case studies, and provided technical support to key wind program managers. BL&A has also analyzed Lamar, Colorados 162MW wind project and developed a highly regarded 'wind supply chain' report and outreach presentation. BL&As efforts were then replicated to characterize similar supply chain presentations in New Mexico and Illinois. Note that during the period of this contract, the recipient met with members of the DOE Wind Program a number of times to obtain specific guidance on tasks that needed to be pursued on behalf of this grant. Thus, as the project developed over the course of 5 years, the recipient varied the tasks and emphasis on tasks to comply with the on-going and continuously developing requirements of the Wind Powering America Program. This report provides only a brief summary of activities to illustrate the recipient's work for advancing wind energy education and outreach from 2001 through the end of the contract period in 2006. It provides examples of how the recipient and DOE leveraged the available funding to provide educational and outreach work to a wide range of stakeholder communities.

Bob Lawrence; Craig Cox; Jodi Hamrick; DOE Contact - Keith Bennett

2006-07-27T23:59:59.000Z

408

New England Wind Energy Education Project (NEWEEP)  

SciTech Connect (OSTI)

Project objective is to develop and disseminate accurate, objective information on critical wind energy issues impacting market acceptance of hundreds of land-based projects and vast off-shore wind developments proposed in the 6-state New England region, thereby accelerating the pace of wind installation from today's 140 MW towards the region's 20% by 2030 goals of 12,500 MW. Methodology: This objective will be accomplished by accumulating, developing, assembling timely, accurate, objective and detailed information representing the 'state of the knowledge' on critical wind energy issues impacting market acceptance, and widely disseminating such information. The target audience includes state agencies and local governments; utilities and grid operators; wind developers; agricultural and environmental groups and other NGOs; research organizations; host communities and the general public, particularly those in communities with planned or operating wind projects. Information will be disseminated through: (a) a series of topic-specific web conference briefings; (b) a one-day NEWEEP conference, back-to-back with a Utility Wind Interest Group one-day regional conference organized for this project; (c) posting briefing and conference materials on the New England Wind Forum (NEWF) web site and featuring the content on NEWF electronic newsletters distributed to an opt-in list of currently over 5000 individuals; (d) through interaction with and participation in Wind Powering America (WPA) state Wind Working Group meetings and WPA's annual All-States Summit, and (e) through the networks of project collaborators. Sustainable Energy Advantage, LLC (lead) and the National Renewable Energy Laboratory will staff the project, directed by an independent Steering Committee composed of a collaborative regional and national network of organizations. Major Participants - the Steering Committee: In addition to the applicants, the initial collaborators committing to form a Steering Committee consists of the Massachusetts Renewable Energy Trust; Maine Public Utilities Commission; New Hampshire office of Energy & Planning, the Connecticut Clean Energy Fund;, ISO New England; Utility Wind Interest Group; University of Massachusetts Wind Energy Center; Renewable Energy New England (a new partnership between the renewable energy industry and environmental public interest groups), and Lawrence Berkeley National Laboratory (conditionally). The Steering Committee will: (1) identify and prioritize topics of greatest interest or concern where detailed, objective and accurate information will advance the dialogue in the region; (2) identify critical outreach venues, influencers and experts; (3) direct and coordinate project staff; (4) assist project staff in planning briefings and conferences described below; (5) identify topics needing additional research or technical assistance and (6) identify and recruit additional steering committee members. Impacts/Benefits/Outcomes: By cutting through the clutter of competing and conflicting information on critical issues, this project is intended to encourage the market's acceptance of appropriately-sited wind energy generation.

Grace, Robert C.; Craddock, Kathryn A.; von Allmen, Daniel R.

2012-04-25T23:59:59.000Z

409

USAGE OF RADARS FOR WIND ENERGY APPICATIONS Determine the benefit of using radar observations for wind energy applications by  

E-Print Network [OSTI]

USAGE OF RADARS FOR WIND ENERGY APPICATIONS TASK: Determine the benefit of using radar observations for wind energy applications by analyzing i) the resolution effects and ii) sensitivity effects of weather radar systems. MOTIVATION: Wind energy applications strongly focus high-resolution wind observations

410

New Report: Integrating Variable Wind Energy into the Grid |...  

Broader source: Energy.gov (indexed) [DOE]

Report: Integrating Variable Wind Energy into the Grid New Report: Integrating Variable Wind Energy into the Grid December 19, 2011 - 2:00pm Addthis The Energy Department and...

411

NREL: Wind Research - U.S. Department of Energy Wind Program...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

U.S. Department of Energy Wind Program Announces New Round of Funding for 2016 Collegiate Wind Competition October 30, 2014 The U.S. Department of Energy's (DOE's) National...

412

Minnesota Wind Share Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's HeatMexico: Energy Resources JumpMicrelBirds JumpMilnerMinn-DakotaShare Wind

413

Stetson Wind Expansion Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revisionEnvReviewNonInvasiveExplorationUT-g GrantAtlas (PACAOpen Energy Information 2) Jump to:StereoscopyWind

414

Wind Power Partners '94 Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 NoPublic Utilities Address: 160 East 300 South Place:ReferenceEdit JumpWill County, Illinois:4 Sector Wind energy

415

American Wind Energy Association Wind Energy Finance and Investment Seminar  

Office of Environmental Management (EM)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergy Cooperation |South42.2 (April 2012) 1 Documentation andEnergy| Department of Energy|

416

Wind Program | Department of Energy  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels DataCombinedDepartment ofCareers »BatteriesVehiclesAboutMayEmissionsNews »Wind

417

Wind Program | Department of Energy  

Energy Savers [EERE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious RankCombustion |Energyon ArmedWaste and Materials Disposition InformationWind Program As a follow up to the

418

Rockland Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revisionEnvReviewNonInvasiveExplorationUT-g Grant ofRichardton Abbey Wind Farm It is

419

Rollins Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revisionEnvReviewNonInvasiveExplorationUT-g Grant ofRichardton Abbey Wind Farm It isRockwall,SectorIA) Jump

420

Scituate Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revisionEnvReviewNonInvasiveExplorationUT-g Grant ofRichardton AbbeyA Jump to:ScheringScituate Wind Jump to:

Note: This page contains sample records for the topic "wind energy forecasts" 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

Danielson Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentratingRenewable Solutions LLC JumpCrow Lake Wind107 CX at NorthDaly International UK

422

Pacific Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth'sOklahoma/GeothermalOrange County is aOrmesaPPT ResearchPacific Wind Facility

423

Wind turbine | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 NoPublic Utilities Address: 160 East 300 South Place:ReferenceEdit JumpWill County, Illinois:4 SectorWind forturbine:

424

Wiota Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 NoPublic Utilities Address: 160 East 300 South Place:ReferenceEdit JumpWill County,WindspireLocationWinslowWiota Wind

425

Fairhaven Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision has beenFfe2fb55-352f-473b-a2dd-50ae8b27f0a6 NoSan Leandro,LawFEMA -Single-WellValley45. ItFairhaven Wind

426

Wind Power | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORT Americium/Curium Vitrification Project AtOpenLabs Jump to:Wind Power

427

Harbor Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's Heat Jump to:Photon Place:Net JumpStrategy |Hammerfest StromHarbor Wind

428

Kahuku Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's Heat JumpInc Place: EdenOverview JumpJessi3bl'sJustin,KDOTKaheawa Wind

429

Kawailoa Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's Heat JumpInc Place: EdenOverviewKanematsuKas Farms Wind Farm Jump to:Jump

430

Lake Winds | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's Heat JumpInc Place:Keystone Clean Airjoin <Nacimiento,View GeothermalWinds

431

Statistical Analysis of Environment Canada's Wind Speed Data  

E-Print Network [OSTI]

Statistical Analysis of Environment Canada's Wind Speed Data Someshwar Singh Department Brunswick-Fredericton New Brunswick, Canada Email: jtaylor@unb.ca Abstract--Wind energy utilities use wind. This paper reports on a study of the histories of wind speed forecasts and actual wind speed data available

Taylor, James H.

432

Wind Vision Presentation | Department of Energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered energy consumption byAbout PrintableBlenderWhatFellows - PastFarmWindWind

433

Wyoming/Wind Resources | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 NoPublic Utilities Address: 160 East 300 South Place:ReferenceEditWisconsin: EnergyEdison,Wind EnergyWind Resources

434

ANL Wind Power Forecasting and Electricity Markets | Open Energy  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpenWende NewSowitec doWinvestFlumeFinalAIRMaster+AMIS (Smart

435

ANL Software Improves Wind Power Forecasting | Department of Energy  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE:Year in Review: Top Five EERE Blog Posts of(Revision 2) |6.pdfALIGNMENT: AFocus on Reducing

436

Cameron Ridge Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergyCTBarreis aCallahan Divide Wind EnergyEnergy

437

DOE SBIR Phase II Final Technical Report - Assessing Climate Change Effects on Wind Energy  

SciTech Connect (OSTI)

Specialized Vertum Partners software tools were prototyped, tested and commercialized to allow wind energy stakeholders to assess the uncertainties of climate change on wind power production and distribution. This project resulted in three commercially proven products and a marketing tool. The first was a Weather Research and Forecasting Model (WRF) based resource evaluation system. The second was a web-based service providing global 10m wind data from multiple sources to wind industry subscription customers. The third product addressed the needs of our utility clients looking at climate change effects on electricity distribution. For this we collaborated on the Santa Ana Wildfire Threat Index (SAWTi), which was released publicly last quarter. Finally to promote these products and educate potential users we released Gust or Bust, a graphic-novel styled marketing publication.

Whiteman, Cameron; Capps, Scott

2014-11-05T23:59:59.000Z

438

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS DISTRICT FORECASTS  

E-Print Network [OSTI]

> BUREAU HOME > AUSTRALIA > QUEENSLAND > FORECASTS DISTRICT FORECASTS IMPROVEMENTS FOR QUEENSLAND across Australia From October 2013, new and improved district forecasts will be introduced in Queensland Protection times FURTHER INFORMATION : www.bom.gov.au/NexGenFWS © Commonwealth of Australia, 2013 PTO> Wind

Greenslade, Diana

439

Ris National Laboratory DTU Wind Energy Department  

E-Print Network [OSTI]

wind speed, wind direction relative to the spinner and flow inclination angle. A wind tunnel concept anemometer is a wind measurement concept in which measurements of wind speed in the flow over a wind turbine on a modified 300kW wind turbine spinner, was mounted with three 1D sonic wind speed sensors. The flow around

440

ANEMOS: Development of a Next Generation Wind Power Forecasting System for the Large-Scale Integration of Onshore &  

E-Print Network [OSTI]

-NTUA, Greece. * georges.kariniotakis@ensmp.fr, tel:+33-493957501, Ecole des Mines de Paris, Centre d'Energetique 6% to 12% by 2010. Under this target, the problem of integration of RES and namely of wind energy

Paris-Sud XI, Université de

Note: This page contains sample records for the topic "wind energy forecasts" 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.


441

Wind energy resource atlas. Volume 4. The Northeast region  

SciTech Connect (OSTI)

This atlas of the wind energy resource is composed of introductory and background information, a regional summary of the wind resource, and assessments of the wind resource in each state of the region. Background is presented on how the wind resource is assessed and on how the results of the assessment should be interpreted. A description of the wind resource on a regional scale is then given. The results of the wind energy assessments for each state are assembled in this chapter into an overview and summary of the various features of the regional wind energy resource. An introduction and outline are provided for in the descriptions of the wind resource given for each state. Assessments for individual states are presented. The state wind energy resources are described in greater detail than is the regional wind energy resource, and features of selected stations are discussed. This preface outlines the use and interpretation of the information found in the state chapters.

Pickering, K.E.; Vilardo, J.M.; Schakenbach, J.T.; Elliott, D.L.; Barchet, W.R.; George, R.L.

1980-09-01T23:59:59.000Z

442

Power Control and Optimization of Photovoltaic and Wind Energy Conversion Systems /  

E-Print Network [OSTI]

77 5.2 Wind Energy Conversion System . . . . .Optimization and Control in Wind Energy Conversion SystemsAC matrix con- verter for wind energy conversion system, in

Ghaffari, Azad

2013-01-01T23:59:59.000Z

443

Wind Energy Facilities and Residential Properties: The Effect of Proximity and View on Sales Prices  

E-Print Network [OSTI]

and Renewable Energy (Wind & Hydropower Technologiesfor Understanding Public Perceptions of Wind Energy.Wind Energy. 8(2): 125 - 139. Durbin, J. and Watson, G. S. (

Hoen, Ben

2010-01-01T23:59:59.000Z

444

Fostering a Renewable Energy Technology Industry: An International Comparison of Wind Industry Policy Support Mechanisms  

E-Print Network [OSTI]

2004. International Wind Energy Development, World Market2005. International Wind Energy Development, World Market2004, March 2005. Canadian Wind Energy Association (CanWEA),

Lewis, Joanna; Wiser, Ryan

2005-01-01T23:59:59.000Z

445

Massachusetts Wind Energy Predevelopment Support Feasibility Study for Marblehead, Massachusetts  

E-Print Network [OSTI]

Massachusetts Wind Energy Predevelopment Support Program & Feasibility Study for Marblehead.ceere.org #12;Wind Energy Predevelopment Support Program ABSTRACT The Renewable Energy Research Lab (RERL in performing the preliminary steps leading toward the implementation of a wind energy project. RERL has

Massachusetts at Amherst, University of

446

International Collaboration on Offshore Wind Energy Under IEA Annex XXIII  

SciTech Connect (OSTI)

This paper defines the purpose of IEA Annex XXIII, the International Collaboration on Offshore Wind Energy. This international collaboration through the International Energy Agency (IEA) is an efficient forum from which to advance the technical and environmental experiences collected from existing offshore wind energy projects, as well as the research necessary to advance future technology for deep-water wind energy technology.

Musial, W.; Butterfield, S.; Lemming, J.

2005-11-01T23:59:59.000Z

447

The Potential for Wind Energy in Atlantic Canada  

E-Print Network [OSTI]

The Potential for Wind Energy in Atlantic Canada Larry Hughes and Sandy Scott Whale Lake Research World Renewable Energy Congress, Reading, September 1992. #12;Hughes/Scott: Wind Energy in Atlantic Canada 1 The Potential for Wind Energy in Atlantic Canada Abstract Canadians are among the highest per

Hughes, Larry

448

Contributed Paper Effects of Wind Energy Development on Nesting  

E-Print Network [OSTI]

Contributed Paper Effects of Wind Energy Development on Nesting Ecology of Greater Prairie 32611, U.S.A. Abstract: Wind energy is targeted to meet 20% of U.S. energy needs by 2030, but new sites for impacts of a wind energy development on the reproductive ecology of prairie-chickens in a 5-year study. We

Sandercock, Brett K.

449

Operational forecasting based on a modified Weather Research and Forecasting model  

SciTech Connect (OSTI)

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

450

Avian interactions with wind energy facilities: A summary  

SciTech Connect (OSTI)

Currently, wind energy plants have been constructed or plans are being developed for projects in at least 13 states within the United States, also Canada, Sweden, Denmark, Germany, Netherlands, United Kingdom, Spain and Scotland (EPRI 1994, Winkelman 1994). Approximately, 16,000 wind turbines currently operate in California, making this area the largest concentration of wind energy development in the world. Notwithstanding its positive social values, wind energy has been shown to cause avian mortalities. Since the 1970`s many studies have been done to understand the interaction between wind energy development and birds. However our knowledge and understanding of bird interactions with wind energy development is incomplete.

Colson, E.W. [Colson & Associates, Alamo, CA (United States)

1995-12-31T23:59:59.000Z

451

Wind turbines application for energy savings in Gas transportation system.  

E-Print Network [OSTI]

?? The Thesis shows the perspectives of involving renewable energy resources into the energy balance of Russia, namely the use of wind energy for the (more)

Mingaleeva, Renata

2014-01-01T23:59:59.000Z

452

Solar and Wind Energy Resource Assessment Programme's Renewable...  

Open Energy Info (EERE)

Energy Resource Explorer Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar and Wind Energy Resource Assessment Programme's Renewable Energy Resource Explorer...

453

The economic value of wind energy  

SciTech Connect (OSTI)

Today's wholesale electricity market passes intermittency costs to the ratepayer in the form of increased overall system cost, a hidden subsidy. Market managers need a competition that correctly allocates cost and provides consumers with the lowest price. One solution is for buyers to contract wind farms to provide energy on demand. (author)

Pavlak, Alex

2008-10-15T23:59:59.000Z

454

EWEC 2006 Wind Energy Conference and Exhibition Turbine Wake Model for Wind Resource Software  

E-Print Network [OSTI]

EWEC 2006 Wind Energy Conference and Exhibition 1 Turbine Wake Model for Wind Resource Software Ole) AT: #12;EWEC 2006 Wind Energy Conference and Exhibition 2 21 2 0TT C U= (1) 0 0(1 )wU a U= - (2); 1.5 0.75 AR Aw0 U0 Uw0 T #12;EWEC 2006 Wind Energy Conference and Exhibition 3 ( )2 0 1 ( , ) 1

455

ISET-Wind-Index Assessment of the Annual Available Wind Energy  

E-Print Network [OSTI]

Particularly in years with wind speeds that are clearly below average, dissatisfaction of operators and even liquidity problems are sparked through the unexpected low annual power production. An objective standard for the evaluation of the respective wind year is required for the internal estimation of the performance of wind farms, and for justification to share owners and banks. The annual wind conditions are composed from such a multitude of meteorological situations, differing from location to location, that the available wind energy at every individual location develops totally differently. A single code is therefore not sufficient to describe the wind year in Germany and, moreover, the evaluation of annual available wind energy must be carried out separately for the smallest areas possible. With the support of the Gothaer Rckversicherungen AG, a procedure has been developed at ISET which provides the proportion of the respective annual available wind energy, in relation to the long-term average available wind energy, for each 10 km x 10 km sized plan area in Germany. This amount, the ISET-Wind-Index, is founded on wind measurements at locations that are typical for wind energy use and therefore presents an objective standard. The measurement grid is part of the Scientific Measurement and Evaluation Programme (WMEP), which accompanies the 250 MW Wind project of the German Federal Ministry for Economy and Labour. The ISET-Wind-Index, which will be regularly updated, provides an objective standard for the estimation of annual available

Berthold Hahn; Kurt Rohrig

2003-01-01T23:59:59.000Z

456

Wind Direct Ltd | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpenWende NewSowitec do BrasilGmbHWeardale TaskEnergy LtdWhiteWindWind

457

Pioneer Asia Wind Turbines | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpenWende New Energy CoFirstNovosPatriot Wind IncAsia Wind Turbines

458

Wind Manufacturing Facilities | Department of Energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste and MaterialsWenjun DengWISPWind Industry Soars to New1 WindWind

459

Wind Turbine Basics | Department of Energy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear SecurityTensile Strain Switched FerromagnetismWaste and MaterialsWenjun DengWISPWind Industry Soars toWind» Wind

460

Casper Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergyCTBarreis aCallahanWind Farm Jump to:Case WesternCasper Wind Farm

Note: This page contains sample records for the topic "wind energy forecasts" 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

Cassia Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergyCTBarreis aCallahanWind Farm Jump to:Case WesternCasperCassia Wind

462

Cedar Rapids Wind Project | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergyCTBarreis aCallahanWindSyracuse, NYCedar Creek Wind FarmPoint

463

Montana/Wind Resources | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's HeatMexico: EnergyMithun Jump to:Moe WindMont Vista CapitalMontanaMontana Wind

464

Moraine II Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's HeatMexico: EnergyMithun Jump to:Moe WindMontMoraine II Wind Farm Jump to:

465

Mountain Home Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revision hasInformation Earth's HeatMexico: EnergyMithun Jump to:Moe WindMontMoraineAbbey JumpWind Farm

466

San Jacinto Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revisionEnvReviewNonInvasiveExplorationUT-g Grant ofRichardton Abbey WindSamsungFarms Sector Wind energyFarms

467

Story City Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home5b9fcbce19 No revisionEnvReviewNonInvasiveExplorationUT-g GrantAtlas (PACAOpen Energy InformationStony Creek WindStorrs,Wind

468

CWEX (Crop/Wind-Energy Experiment): Measurements of the interaction between crop agriculture and wind power.  

E-Print Network [OSTI]

??The current expansion of wind farms in the U.S. Midwest promotes an alternative renewable energy portfolio to conventional energy sources derived from fossil fuels. The (more)

Rajewski, Daniel Andrew

2013-01-01T23:59:59.000Z

469

Model Ordinance for Siting of Wind-Energy Systems  

Broader source: Energy.gov [DOE]

In 2009, the South Dakota Public Utilities Commission (PUC) created a [http://puc.sd.gov/commission/twg/WindEnergyOrdinance.pdf model ordinance] for siting wind-energy systems. This nine-page model...

470

Distributed Wind - Economical, Clean Energy for Industrial Facilities  

E-Print Network [OSTI]

Distributed wind energy works for industrial clients. Corporations and other organizations are choosing to add Distributed Wind energy to their corporate goals for a numerous reasons: economic, environmental, marketing, values, and attracting new...

Trapanese, A.; James, F.

2011-01-01T23:59:59.000Z

471

Federal Wind Energy Assistance through NREL (Fact Sheet)  

SciTech Connect (OSTI)

NREL assists with wind resource assessment and development activities initiated by federal agencies to facilitate distributed renewable energy projects at federal agency sites. This brief outlines the process for requesting NREL assistance with federal wind energy projects.

Not Available

2009-09-01T23:59:59.000Z

472

Town of Kill Devil Hills- Wind Energy Systems Ordinance  

Broader source: Energy.gov [DOE]

In October 2007, the town of Kill Devil Hills adopted an ordinance to regulate the use of wind-energy systems. The ordinance directs any individual or organization wishing to install a wind-energy...

473

Brown County Wind | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergyCTBarre BiomassTHISBrickyard EnergyBrockwayBrophy OccurrenceWind

474

Chamberlain Wind Project | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergyCTBarreis aCallahanWindSyracuse,CER.png El CERChai Energy

475

Entegrity Wind Systems Inc | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of Inspector GeneralDepartmentAUDIT REPORTOpen Energy Information Energy SectorEnertechEntegrity Wind

476

Invenergy Wind LLC | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data CenterFranconia, Virginia: Energy Resources Jump to:46 - 429 Throttled (bot load)InternationalRenewable Energy CouncilWind LLC Jump to:

477

Saturation wind power potential and its implications for wind energy  

E-Print Network [OSTI]

Board August 14, 2012 (received for review May 31, 2012) Wind turbines convert kinetic to electrical. As the number of wind turbines increases over large geographic regions, power extraction first increases the number of wind turbines over a large geographic region, indepen- dent of societal, environmental

478

Wind for Schools: Developing Education Programs to Train the Next Generation of the Wind Energy Workforce  

SciTech Connect (OSTI)

This paper provides an overview of the Wind for Schools project elements, including a description of host and collegiate school curricula developed for wind energy and the status of the current projects. The paper also provides focused information on how schools, regions, or countries can become involved or implement similar projects to expand the social acceptance and understanding of wind energy.

Baring-Gould, I.; Flowers, L.; Kelly, M.; Barnett, L.; Miles, J.

2009-08-01T23:59:59.000Z

479

Rural Communities Benefit from Wind Energy's Continued Success  

Broader source: Energy.gov [DOE]

John Stulp, Colorado Interbasin Compact Committee chairman, discusses how wind energy benefits rural communities, farms, and ranches.

480

Assessment of Offshore Wind Energy Leasing Areas for the BOEM Maryland Wind Energy Area  

SciTech Connect (OSTI)

The National Renewable Energy Laboratory (NREL), under an interagency agreement with the Bureau of Ocean Energy Management (BOEM), is providing technical assistance to identify and delineate leasing areas for offshore wind energy development within the Atlantic Coast Wind Energy Areas (WEAs) established by BOEM. This report focuses on NREL's evaluation of the delineation proposed by the Maryland Energy Administration (MEA) for the Maryland (MD) WEA and two alternative delineations. The objectives of the NREL evaluation were to assess MEA's proposed delineation of the MD WEA, perform independent analysis, and recommend how the MD WEA should be delineated.

Musial, W.; Elliott, D.; Fields, J.; Parker, Z.; Scott, G.; Draxl, C.

2013-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind energy forecasts" 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

Career Map: Wind Technician | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergyENERGYWomenthe HouseStudents Heal thePrepared for Energy Secretary SamuelresearchTwo wind

482

Camp Grove Wind Farm | Open Energy Information  

Open Energy Info (EERE)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Office of InspectorConcentrating SolarElectricEnergyCTBarreis aCallahan Divide Wind EnergyEnergyCameroon: EnergyGrove

483

America's Wind Testing Facilities | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergyENERGYWomen Ownedof EnergyAdvanced Biofuels |National Wind Technology Center - Colorado 1

484

American Wind Manufacturing | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary) "of EnergyEnergyENERGYWomen Ownedof EnergyAdvanced Biofuels |National Wind Technology Center -1 of 9

485

The Incremental Benefits of the Nearest Neighbor Forecast of U.S. Energy Commodity Prices  

E-Print Network [OSTI]

This thesis compares the simple Autoregressive (AR) model against the k- Nearest Neighbor (k-NN) model to make a point forecast of five energy commodity prices. Those commodities are natural gas, heating oil, gasoline, ethanol, and crude oil...

Kudoyan, Olga

2012-02-14T23:59:59.000Z

486

NREL: Energy Analysis - Energy Forecasting and Modeling Staff  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the Contributions and Achievements of WomenEventsTools UpdateChadDavidDylanEllaEnergy

487

Solar forecasting review  

E-Print Network [OSTI]

and forecasting of solar radiation data: a review,forecasting of solar- radiation data, Solar Energy, vol.sequences of global solar radiation data for isolated sites:

Inman, Richard Headen

2012-01-01T23:59:59.000Z

488

Wind energy calculated from SAR and scatterometer satellite data  

E-Print Network [OSTI]

. · Offshore wind resources estimated from SAR · On WASP · Wind indexing based on scatterometer · Wake effects footprint 62 m footprint Wind field maps from SAR are valid for 10 m height #12;7 Slide no. 62 m 10 m Upwind1 Slide no. 4 Wind energy calculated from SAR and scatterometer satellite data Charlotte Bay

489

FEBRUARY 1999 119O ' C O N N O R E T A L . Forecast Verification for Eta Model Winds Using Lake Erie  

E-Print Network [OSTI]

weather prediction step-coordinate Eta Model are able to forecast winds for the Great Lakes region, using Administration (NOAA) Coastal Ocean Program, the output of NCEP numerical atmospheric prediction models is being used as the forcing for numerical ocean prediction models for several U.S. coastal regions

490

Wind Energy Learning Curves for Reference in Expert Elicitations  

E-Print Network [OSTI]

Wind Energy Learning Curves for Reference in Expert Elicitations Sarah Mangels, Erin Baker. Abstract: This study presents future projections of wind energy capacity and cost based on historical data. The study will be used during wind- energy expert elicitations (formal interviews aimed to quantify

Mountziaris, T. J.

491

A New Approach To Wind Energy: Opportunities And Challenges  

E-Print Network [OSTI]

1 A New Approach To Wind Energy: Opportunities And Challenges John O. Dabiria , Julia R. Greera, Anchorage, AK 99508, USA Abstract. Despite common characterizations of modern wind energy technology as mature, there remains a persistent disconnect between the vast global wind energy resource--which is 20

Dabiri, John O.

492

Wind Energy Development and its Impacts on Wildlife  

E-Print Network [OSTI]

1 Wind Energy Development and its Impacts on Wildlife Carrie Lowe, M.S. Candidate UniversityOutline · Introduction · Wind energy in the U.S. I t ildlif· Impacts on wildlife · Guidelines · Future directions · References IntroductionIntroduction What is wind energy? · The process by which turbines convert the kinetic

Gray, Matthew

493

Ris-R-1239(EN) Wind Energy Department  

E-Print Network [OSTI]

Risø-R-1239(EN) Wind Energy Department: Scientific and Technical Progress 1999 - 2000 Birthe The activities of the Wind Energy Department fall within boundary layer meteorology, atmospheric turbulence-R-1239(EN) 3 Contents 1 Introduction 5 2 The Department of Wind Energy and Atmospheric Physics 5 3

494

Management and Conservation Short-Term Impacts of Wind Energy  

E-Print Network [OSTI]

Management and Conservation Short-Term Impacts of Wind Energy Development on Greater Sage associated with wind energy development on greater sage-grouse populations. We hypothesized that greater sage-grouse nest, brood, and adult survival would decrease with increasing proximity to wind energy infrastructure

Beck, Jeffrey L.

495

Assessing Desert Tortoise Survival and Reproduction at a Wind Energy  

E-Print Network [OSTI]

Assessing Desert Tortoise Survival and Reproduction at a Wind Energy Facility Near Palm Springs of their habitat are characterized by significant wind and solar energy potential. As a result, the species in the Mojave and Sonoran Deserts have preexisting wind energy facilities dating back over 25 years. One

496

Ris-R-1317(EN) Wind Energy Department  

E-Print Network [OSTI]

Risø-R-1317(EN) Wind Energy Department Annual Progress Report 2001 Birthe Skrumsager, Søren E The report describes the work of the Wind Energy Department at Risø National Laboratory in 2001. The research of the department aims to develop new opportunities in the exploitation of wind energy and to map and alleviate

497

2011-2012 Wind Energy Minor Form STUDENT INFORMATION  

E-Print Network [OSTI]

2011-2012 Wind Energy Minor Form STUDENT INFORMATION R Number (Current TTU Students Only Name First Name MI Choose 18 hours from the following list of courses in Wind Energy. All courses must be approved by a wind energy advisor and a grade of C or better achieved in each course. UNDERGRADUATE MINOR

Rock, Chris

498

A Vision for Systems Engineering Applied to Wind Energy (Presentation)  

SciTech Connect (OSTI)

This presentation was given at the Third Wind Energy Systems Engineering Workshop on January 14, 2015. Topics covered include the importance of systems engineering, a vision for systems engineering as applied to wind energy, and application of systems engineering approaches to wind energy research and development.

Felker, F.; Dykes, K.

2015-01-01T23:59:59.000Z

499

2006 European Wind Energy Conference 27th February-2nd  

E-Print Network [OSTI]

2006 European Wind Energy Conference 27th February-2nd March, Athens. Hybrid System Performance Wind Energy Conference 27th February-2nd March, Athens. 1/9 1 Introduction Uncertain and often, but not always, wind energy input as a means to reduce fuel consumption. There may be an element of storage

500

Wind Energy Applications of Unified and Dynamic Turbulence Models  

E-Print Network [OSTI]

Wind Energy Applications of Unified and Dynamic Turbulence Models Stefan Heinz and Harish Gopalan applicable as a low cost alternative. 1 Introduction There is a growing interest in using wind energy suggests the possibility of providing 20% of the electricity in the U.S. by wind energy in 2030

Heinz, Stefan