Sample records for resource datasets modeled

  1. Models Datasets

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'. William HirstLong-Term Market Penetration of

  2. Models and Datasets

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHighandSWPA / SPRA /Ml'. William HirstLong-Term Market Penetration

  3. Bhutan Solar Resources - Datasets - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:EzfeedflagBiomass ConversionsSouth Carolina:Energy LLC Place:BeverlyBeyWatchBhutan Solar

  4. Development of Regional Wind Resource and Wind Plant Output Datasets...

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

    50-47676 March 2010 Development of Regional Wind Resource and Wind Plant Output Datasets Final Subcontract Report 15 October 2007 - 15 March 2009 3TIER Seattle, Washington National...

  5. Afghanistan Pakistan High Resolution Wind Resource - Datasets - OpenEI

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat 1AMEE JumpAeroWind Inc. Place:AerospatialeAffton,Datasets

  6. BP-12 Final Models Datasets

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProductsAlternativeOperationalAugustDecade Later: Are WeOverview:R A

  7. Earth System Grid II, Turning Climate Datasets into Community Resources

    SciTech Connect (OSTI)

    Middleton, Don

    2006-08-01T23:59:59.000Z

    The Earth System Grid (ESG) II project, funded by the Department of Energy’s Scientific Discovery through Advanced Computing program, has transformed climate data into community resources. ESG II has accomplished this goal by creating a virtual collaborative environment that links climate centers and users around the world to models and data via a computing Grid, which is based on the Department of Energy’s supercomputing resources and the Internet. Our project’s success stems from partnerships between climate researchers and computer scientists to advance basic and applied research in the terrestrial, atmospheric, and oceanic sciences. By interfacing with other climate science projects, we have learned that commonly used methods to manage and remotely distribute data among related groups lack infrastructure and under-utilize existing technologies. Knowledge and expertise gained from ESG II have helped the climate community plan strategies to manage a rapidly growing data environment more effectively. Moreover, approaches and technologies developed under the ESG project have impacted datasimulation integration in other disciplines, such as astrophysics, molecular biology and materials science.

  8. The Earth System Grid Center for Enabling Technologies: Focusing Technologies on Climate Datasets and Resource Needs

    SciTech Connect (OSTI)

    Williams, Dean N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2007-09-26T23:59:59.000Z

    This report discusses a project that used prototyping technology to access and analyze climate data. This project was initially funded under the DOE’s Next Generation Internet (NGI) program, with follow-on support from BER and the Mathematical, Information, and Computational Sciences (MICS) office. In this prototype, we developed Data Grid technologies for managing the movement and replication of large datasets, and applied these technologies in a practical setting (i.e., an ESG-enabled data browser based on current climate data analysis tools), achieving cross-country transfer rates of more than 500 Mb/s. Having demonstrated the potential for remotely accessing and analyzing climate data located at sites across the U.S., we won the “Hottest Infrastructure” award in the Network Challenge event. While the ESG I prototype project substantiated a proof of concept (“Turning Climate Datasets into Community Resources”), the SciDAC Earth System Grid (ESG) II project made this a reality. Our efforts targeted the development of metadata technologies (standard schema, XML metadata extraction based on netCDF, and a Metadata Catalog Service), security technologies (Web-based user registration and authentication, and community authorization), data transport technologies (GridFTPenabled OPeNDAP-G for high-performance access, robust multiple file transport and integration with mass storage systems, and support for dataset aggregation and subsetting), as well as web portal technologies to provide interactive access to climate data holdings. At this point, the technology was in place and assembled, and ESG II was poised to make a substantial impact on the climate modelling community.

  9. Wind Resources by Class and Country At 50m - Datasets - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown ofNationwideWTEDBird,Wilsonville, Oregon: EnergyWindCooperatives Jumpto

  10. Solar Resources by Class and Country - Datasets - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro Industries Pvt LtdShawangunk, NewSingapore Jump to: navigation,Panels PlusCaliforniaSolar

  11. Linked data about: /lod/resource/datasets/373/

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal Pwer Plant Jump to:Landowners and WindLighting ControlWyoming:RhodeLienHwaLinked Open

  12. Advancements in Wind Integration Study Data Modeling: The Wind Integration National Dataset (WIND) Toolkit; Preprint

    SciTech Connect (OSTI)

    Draxl, C.; Hodge, B. M.; Orwig, K.; Jones, W.; Searight, K.; Getman, D.; Harrold, S.; McCaa, J.; Cline, J.; Clark, C.

    2013-10-01T23:59:59.000Z

    Regional wind integration studies in the United States require detailed wind power output data at many locations to perform simulations of how the power system will operate under high-penetration scenarios. The wind data sets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as be time synchronized with available load profiles. The Wind Integration National Dataset (WIND) Toolkit described in this paper fulfills these requirements. A wind resource dataset, wind power production time series, and simulated forecasts from a numerical weather prediction model run on a nationwide 2-km grid at 5-min resolution will be made publicly available for more than 110,000 onshore and offshore wind power production sites.

  13. Business Model Resources | Department of Energy

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

    Run a Program Getting Started Business Model Resources Business Model Resources Business Models Guide Business Model Planning Resources - Working with Partners Sample Program...

  14. Fact #871: May 4, 2015 Most Manufacturers Have Positive CAFE Credit Balances at the End of Model Year 2013 – Dataset

    Broader source: Energy.gov [DOE]

    Excel file and dataset for Most Manufacturers Have Positive CAFE Credit Balances at the End of Model Year 2013

  15. Nuclear Mass Datasets and Models at nuclearmasses.org

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    This online repository for nuclear mass information allows nuclear researchers to upload their own mass values, store then, share them with colleagues, and, in turn, visualize and analyze the work of others. The Resources link provides access to published information or tools on other websites. The Contributions page is where users will find software, documents, experimental mass data sets, and theoretical mass models that have been uploaded for sharing with the scientific community.

  16. Equilibrium Response and Transient Dynamics Datasets from VEMAP: Vegetation/Ecosystem Modeling and Analysis Project

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Users of the VEMAP Portal can access input files of numerical data that include monthly and daily files of geographic data, soil and site files, scenario files, etc. Model results from Phase I, the Equilibrium Response datasets, are available through the NCAR anonymous FTP site at http://www.cgd.ucar.edu/vemap/vresults.html. Phase II, Transient Dynamics, include climate datasets, models results, and analysis tools. Many supplemental files are also available from the main data page at http://www.cgd.ucar.edu/vemap/datasets.html.

  17. Development of Regional Wind Resource and Wind Plant Output Datasets for the Hawaiian Islands

    SciTech Connect (OSTI)

    Manobianco, J.; Alonge, C.; Frank, J.; Brower, M.

    2010-07-01T23:59:59.000Z

    In March 2009, AWS Truepower was engaged by the National Renewable Energy Laboratory (NREL) to develop a set of wind resource and plant output data for the Hawaiian Islands. The objective of this project was to expand the methods and techniques employed in the Eastern Wind Integration and Transmission Study (EWITS) to include the state of Hawaii.

  18. Integrated Resource Planning Model (IRPM)

    SciTech Connect (OSTI)

    Graham, T. B.

    2010-04-01T23:59:59.000Z

    The Integrated Resource Planning Model (IRPM) is a decision-support software product for resource-and-capacity planning. Users can evaluate changing constraints on schedule performance, projected cost, and resource use. IRPM is a unique software tool that can analyze complex business situations from a basic supply chain to an integrated production facility to a distributed manufacturing complex. IRPM can be efficiently configured through a user-friendly graphical interface to rapidly provide charts, graphs, tables, and/or written results to summarize postulated business scenarios. There is not a similar integrated resource planning software package presently available. Many different businesses (from government to large corporations as well as medium-to-small manufacturing concerns) could save thousands of dollars and hundreds of labor hours in resource and schedule planning costs. Those businesses also could avoid millions of dollars of revenue lost from fear of overcommitting or from penalties and lost future business for failing to meet promised delivery by using IRPM to perform what-if business-case evaluations. Tough production planning questions that previously were left unanswered can now be answered with a high degree of certainty. Businesses can anticipate production problems and have solutions in hand to deal with those problems. IRPM allows companies to make better plans, decisions, and investments.

  19. Nanostructure Determination by Co-Refining Models to Multiple Datasets

    SciTech Connect (OSTI)

    Billinge, Simon

    2011-05-31T23:59:59.000Z

    The results of the work are contained in the publications resulting from the grant (which are listed below). Here I summarize the main findings from the last period of the award, 2006-2007: • Published a paper in Science with Igor Levin outlining the “Nanostructure Problem”, our inability to solve structure at the nanoscale. • Published a paper in Nature demonstrating the first ever ab-initio structure determination of a nanoparticle from atomic pair distribution function (PDF) data. • Published one book and 3 overview articles on PDF methods and the nanostructure problem. • Completed a project that sought to find a structural response to the presence of the so-called “intermediate phase” in network glasses which appears close to the rigidity percolation threshold in these systems. The main result was that we did not see convincing evidence for this, which drew into doubt the idea that GexSe1-x glasses were a model system exhibiting rigidity percolation.

  20. Development of Regional Wind Resource and Wind Plant Output Datasets: Final Subcontract Report, 15 October 2007 - 15 March 2009

    SciTech Connect (OSTI)

    3TIER, Seattle, Washington

    2010-03-01T23:59:59.000Z

    This report describes the development of the necessary and needed wind and solar datasets used in the Western Wind and Solar Integration Study (WWSIS).

  1. State Energy Program: Kentucky Implementation Model Resources

    Broader source: Energy.gov [DOE]

    Below are resources associated with the U.S. Department of Energy's Weatherization and Intergovernmental Programs Office State Energy Program Kentucky Implementation Model.

  2. Modeling Resources for Activity Coordination and Scheduling

    E-Print Network [OSTI]

    Massachusetts at Amherst, University of

    Modeling Resources for Activity Coordination and Scheduling Rodion M. Podorozhny , Barbara Staudt describes experience in applying a resource man- agement system to problems in two areas of agent and activity coordi- nation. In the paper we argue that precise speci cation of resources is important

  3. Modeling Resources for Activity Coordination and Scheduling

    E-Print Network [OSTI]

    Massachusetts at Amherst, University of

    Modeling Resources for Activity Coordination and Scheduling Rodion M. Podorozhny , Barbara Staudt describes experience in applying a resource man­ agement system to problems in two areas of agent and activity coordi­ nation. In the paper we argue that precise specification of resources is important

  4. Assessing Spatial and Attribute Errors of Input Data in Large National Datasets for use in Population Distribution Models

    SciTech Connect (OSTI)

    Patterson, Lauren A [ORNL; Urban, Marie L [ORNL; Myers, Aaron T [ORNL; Bhaduri, Budhendra L [ORNL; Bright, Eddie A [ORNL; Coleman, Phil R [ORNL

    2007-01-01T23:59:59.000Z

    Geospatial technologies and digital data have developed and disseminated rapidly in conjunction with increasing computing performance and internet availability. The ability to store and transmit large datasets has encouraged the development of national datasets in geospatial format. National datasets are used by numerous agencies for analysis and modeling purposes because these datasets are standardized, and are considered to be of acceptable accuracy. At Oak Ridge National Laboratory, a national population model incorporating multiple ancillary variables was developed and one of the inputs required is a school database. This paper examines inaccuracies present within two national school datasets, TeleAtlas North America (TANA) and National Center of Education Statistics (NCES). Schools are an important component of the population model, because they serve as locations containing dense clusters of vulnerable populations. It is therefore essential to validate the quality of the school input data, which was made possible by increasing national coverage of high resolution imagery. Schools were also chosen since a 'real-world' representation of K-12 schools for the Philadelphia School District was produced; thereby enabling 'ground-truthing' of the national datasets. Analyses found the national datasets not standardized and incomplete, containing 76 to 90% of existing schools. The temporal accuracy of enrollment values of updating national datasets resulted in 89% inaccuracy to match 2003 data. Spatial rectification was required for 87% of the NCES points, of which 58% of the errors were attributed to the geocoding process. Lastly, it was found that by combining the two national datasets together, the resultant dataset provided a more useful and accurate solution. Acknowledgment Prepared by Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, Tennessee 37831-6285, managed by UT-Battelle, LLC for the U. S. Department of Energy undercontract no. DEAC05-00OR22725. Copyright This manuscript has been authored by employees of UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy. Accordingly, the United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes.

  5. Fact #854 January 5, 2015 Driving Ranges for All-Electric Vehicles in Model Year 2014 Vary from 62 to 265 Miles – Dataset

    Broader source: Energy.gov [DOE]

    Excel file with dataset for Driving Ranges for All-Electric Vehicles in Model Year 2014 Vary from 62 to 265 Miles

  6. ComSIS Vol. 1, No. 1, February 2004 75 Network Models of Massive Datasets

    E-Print Network [OSTI]

    Butenko, Sergiy

    , biotechnology, medicine, finance, astrophysics, ecology, geographical information systems, etc. [2, 10 in data mining, which essentially represents partitioning the set of elements of a certain dataset

  7. Development of Eastern Regional Wind Resource and Wind Plant Output Datasets: March 3, 2008 -- March 31, 2010

    SciTech Connect (OSTI)

    Brower, M.

    2009-12-01T23:59:59.000Z

    The objective of this project was to provide wind resource inputs to the Eastern Wind Integration and Transmission Study.

  8. Modeling of Customer Adoption of Distributed Energy Resources

    E-Print Network [OSTI]

    Modeling of Customer Adoption of Distributed Energy Resources CALIFORNIA ENERGY COMMISSION Reliability Technology Solutions Modeling of Customer Adoption of Distributed Energy Resources Prepared the consequences. #12;#12;Modeling of Customer Adoption of Distributed Energy Resources iii Table of Contents

  9. An Interactive Visualization Model for Large High-dimensional Datasets Division of Computing and Mathematics,University of Houston-Clear Lake,

    E-Print Network [OSTI]

    Ding, Wei

    An Interactive Visualization Model for Large High-dimensional Datasets Wei Ding Division of complex data, which is especially helpful for analysis of large high dimensional datasets. However, existing methods often lose simplicity and clarity while rendering large amount of complex data

  10. Electrical Model Development and Validation for Distributed Resources

    SciTech Connect (OSTI)

    Simoes, M. G.; Palle, B.; Chakraborty, S.; Uriarte, C.

    2007-04-01T23:59:59.000Z

    This project focuses on the development of electrical models for small (1-MW) distributed resources at the National Renewable Energy Laboratory's Distributed Energy Resources Test Facility.

  11. World Climate Research Programme (WCRP) Coupled Model Intercomparison Project phase 3 (CMIP3): Multi-Model Dataset Archive at PCMDI (Program for Climate Model Diagnosis and Intercomparison)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    In response to a proposed activity of the WCRP's Working Group on Coupled Modelling (WGCM),PCMDI volunteered to collect model output contributed by leading modeling centers around the world. Climate model output from simulations of the past, present and future climate was collected by PCMDI mostly during the years 2005 and 2006, and this archived data constitutes phase 3 of the Coupled Model Intercomparison Project (CMIP3). In part, the WGCM organized this activity to enable those outside the major modeling centers to perform research of relevance to climate scientists preparing the Fourth Asssessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The IPCC was established by the World Meteorological Organization and the United Nations Environmental Program to assess scientific information on climate change. The IPCC publishes reports that summarize the state of the science. This unprecedented collection of recent model output is officially known as the WCRP CMIP3 multi-model dataset. It is meant to serve IPCC's Working Group 1, which focuses on the physical climate system - atmosphere, land surface, ocean and sea ice - and the choice of variables archived at the PCMDI reflects this focus. A more comprehensive set of output for a given model may be available from the modeling center that produced it. As of November 2007, over 35 terabytes of data were in the archive and over 303 terabytes of data had been downloaded among the more than 1200 registered users. Over 250 journal articles, based at least in part on the dataset, have been published or have been accepted for peer-reviewed publication. Countries from which models have been gathered include Australia, Canada, China, France, Germany and Korea, Italy, Japan, Norway, Russia, Great Britain and the United States. Models, variables, and documentation are collected and stored. Check http://www-pcmdi.llnl.gov/ipcc/data_status_tables.htm to see at a glance the output that is available. (Description taken from http://www-pcmdi.llnl.gov/ipcc/about_ipcc.php)

  12. test dataset - Datasets - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin: EnergyWyandanch,Eaga SolarZoloHomeimprovesecurity Hometest

  13. Commons and Anticommons in a simple Renewable Resource Harvest Model

    E-Print Network [OSTI]

    Boschetti, Fabio

    Commons and Anticommons in a simple Renewable Resource Harvest Model June 20, 2007 M. Bredea a model where agents harvesting from a renewable resource can impose limita- tions on the harvesting that a fluctuation destabilizes the system into severe overexploitation. key words: renewable resources, commons

  14. Modeling Water Resource Systems under Climate Change: IGSM-WRS

    E-Print Network [OSTI]

    Strzepek, K.

    Through the integration of a Water Resource System (WRS) component, the MIT Integrated Global System Model (IGSM) framework has been enhanced to study the effects of climate change on managed water-resource systems. ...

  15. Distributed Energy Resources Market Diffusion Model

    SciTech Connect (OSTI)

    Maribu, Karl Magnus; Firestone, Ryan; Marnay, Chris; Siddiqui,Afzal S.

    2006-06-16T23:59:59.000Z

    Distributed generation (DG) technologies, such as gas-fired reciprocating engines and microturbines, have been found to be economically beneficial in meeting commercial-sector electrical, heating, and cooling loads. Even though the electric-only efficiency of DG is lower than that offered by traditional central stations, combined heat and power (CHP) applications using recovered heat can make the overall system energy efficiency of distributed energy resources (DER) greater. From a policy perspective, however, it would be useful to have good estimates of penetration rates of DER under various economic and regulatory scenarios. In order to examine the extent to which DER systems may be adopted at a national level, we model the diffusion of DER in the US commercial building sector under different technical research and technology outreach scenarios. In this context, technology market diffusion is assumed to depend on the system's economic attractiveness and the developer's knowledge about the technology. The latter can be spread both by word-of-mouth and by public outreach programs. To account for regional differences in energy markets and climates, as well as the economic potential for different building types, optimal DER systems are found for several building types and regions. Technology diffusion is then predicted via two scenarios: a baseline scenario and a program scenario, in which more research improves DER performance and stronger technology outreach programs increase DER knowledge. The results depict a large and diverse market where both optimal installed capacity and profitability vary significantly across regions and building types. According to the technology diffusion model, the West region will take the lead in DER installations mainly due to high electricity prices, followed by a later adoption in the Northeast and Midwest regions. Since the DER market is in an early stage, both technology research and outreach programs have the potential to increase DER adoption, and thus, shift building energy consumption to a more efficient alternative.

  16. Brady Geothermal 1D seismic velocity model - Datasets - OpenEI...

    Open Energy Info (EERE)

    1025. Number is 262. Title is "Brady 1D seismic velocity http:geothermaldata.orgdatasetbrady-1d-seismic-velocity-model-ambient-noise-prelim-prelim-brady-median-vpvsqs-model...

  17. Coupling Groundwater Modeling with Biology to Identify Strategic Water Resources

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Coupling Groundwater Modeling with Biology to Identify Strategic Water Resources Didier Graillot 1 ABSTRACT The identification of hydraulic interactions between rivers and groundwater is part and parcel hinders groundwater modeling everywhere and simulating water management scenarios in every place

  18. Resource Portfolio Model's Determination of Conservation's Cost-Effectiveness1

    E-Print Network [OSTI]

    ,008 average megawatts of conservation8. The electricity price forecast used for this initial estimResource Portfolio Model's Determination of Conservation's Cost- Effectiveness1 The regional Resource Portfolio Model (RPM) finds large amounts of conservation cost effective. The cost of some

  19. Improvement of Offshore Wind Resource Modeling in the Mid-

    E-Print Network [OSTI]

    Firestone, Jeremy

    Improvement of Offshore Wind Resource Modeling in the Mid- Atlantic Bight Wind Energy Symposium Sienkiewicz , Chris Hughes 26 February 2013 #12;Improving Atmospheric Models for Offshore Wind Resource Interaction Tower ­ 23 m NOAA Buzzard's Bay Tower ­ 25 m Cape Wind Tower (60 m from 2003-2011; just platform

  20. Continental-scale water resources modeling

    E-Print Network [OSTI]

    Washington at Seattle, University of

    /Norwegian Water Resources and Energy Directorate) Dennis P. Lettenmaier (University of Washington) #12;Outline, University of Frankfurt, Germany / Food and Agriculture Organization of the United Nations, Rome, Italy ­ Temporal: Daily · Input data ­ Precipitation, max/min temperature, wind ­ Land cover data (vegetation, soil

  1. Impact Assessment of Satellite-Derived Leaf Area Index Datasets Using a General Circulation Model

    E-Print Network [OSTI]

    Xue, Yongkang

    source (i.e., Advanced Very High Resolution Radiometer measurements) on a general circulation model: 10.1175/JCLI4054.1 © 2007 American Meteorological Society #12;Very High Resolution Radiometer (AVHRR radiative energy into latent and sensible heat fluxes, which results in discernable warming and decrease

  2. Preliminary firn-densification model with 38-site dataset M. K. Spencer,1

    E-Print Network [OSTI]

    Creyts, Timothy T.

    that densification rates are function- ally dependent on temperature, density and overburden load, and that power-densification modeling based on hot isostatic pressing with power- law creep is investigated using depth^density data free to vary during a data inversion using 38 depth^density profiles from locations collectively

  3. Representative well models for eight geothermal-resource areas

    SciTech Connect (OSTI)

    Carson, C.C.; Lin, Y.T.; Livesay, B.J.

    1983-02-01T23:59:59.000Z

    Representative well models have been constructed for eight major geothermal-resource areas. The models define representative times and costs associated with the individual operations that can be expected during drilling and completion of geothermal wells. The models were made for and have been used to evaluate the impacts of potential new technologies. The nature, construction, and validation of the models are presented.

  4. Energy Modeling Community Resources | 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 onYouTube YouTube Note: Since the YouTube|6721 FederalTexas Energy Incentive Programs,EnergyAugust 10, 2011 2:30Commercial

  5. Energy Modeling Community Resources | 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 DataDepartment of Energy Your Density Isn't Your Destiny:RevisedAdvisoryStandard |in STEMEnergyI.ofTrack 1should theJulyMayCommercial

  6. Datasets - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489 No revision hasda62829c05b No revision hasDatabus - QSubmit Order

  7. Wind resource assessment with a mesoscale non-hydrostatic model

    E-Print Network [OSTI]

    Boyer, Edmond

    Wind resource assessment with a mesoscale non- hydrostatic model Vincent Guénard, Center for Energy is developed for assessing the wind resource and its uncertainty. The work focuses on an existing wind farm mast measurements. The wind speed and turbulence fields are discussed. It is shown that the k

  8. "Modeling for effective and sustainable water resources management."

    E-Print Network [OSTI]

    Acton, Scott

    "Modeling for effective and sustainable water resources management." Teresa Culver Associate Professor tculver@virginia.edu ce.virginia.edu/faculty/culvert.html Dept. of Civil & Environmental Engineering University of Virginia Charlottesville, VA 434.982.6375 Environmental & Water Resources Group We

  9. Strategies for Energy Efficient Resource Management of Hybrid Programming Models

    E-Print Network [OSTI]

    1 Strategies for Energy Efficient Resource Management of Hybrid Programming Models Dong Li Member, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid hybrid programming models that use both message-passing and shared- memory, due to the increasing

  10. SECURITY MODELING FOR MARITIME PORT DEFENSE RESOURCE ALLOCATION

    SciTech Connect (OSTI)

    Harris, S.; Dunn, D.

    2010-09-07T23:59:59.000Z

    Redeployment of existing law enforcement resources and optimal use of geographic terrain are examined for countering the threat of a maritime based small-vessel radiological or nuclear attack. The evaluation was based on modeling conducted by the Savannah River National Laboratory that involved the development of options for defensive resource allocation that can reduce the risk of a maritime based radiological or nuclear threat. A diverse range of potential attack scenarios has been assessed. As a result of identifying vulnerable pathways, effective countermeasures can be deployed using current resources. The modeling involved the use of the Automated Vulnerability Evaluation for Risks of Terrorism (AVERT{reg_sign}) software to conduct computer based simulation modeling. The models provided estimates for the probability of encountering an adversary based on allocated resources including response boats, patrol boats and helicopters over various environmental conditions including day, night, rough seas and various traffic flow rates.

  11. Wind Integration Datasets from the National Renewable Energy Laboratory (NREL)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The Wind Integration Datasets provide time-series wind data for 2004, 2005, and 2006. They are intended to be used by energy professionals such as transmission planners, utility planners, project developers, and university researchers, helping them to perform comparisons of sites and estimate power production from hypothetical wind plants. NREL cautions that the information from modeled data may not match wind resource information shown on NREL;s state wind maps as they were created for different purposes and using different methodologies.

  12. Modeling Power System Operation with Intermittent Resources

    SciTech Connect (OSTI)

    Marinovici, Maria C.; Kirkham, Harold; Glass, Kevin A.; Carlsen, Leif C.

    2013-02-27T23:59:59.000Z

    Electricity generating companies and power system operators face the need to minimize total fuel cost or maximize total profit over a given time period. These issues become optimization problems subject to a large number of constraints that must be satisfied simultaneously. The grid updates due to smart-grid technologies plus the penetration of intermittent re- sources in electrical grid introduce additional complexity to the optimization problem. The Renewable Integration Model (RIM) is a computer model of interconnected power system. It is intended to provide insight and advice on complex power systems management, as well as answers to integration of renewable energy questions. This paper describes RIM basic design concept, solution method, and the initial suite of modules that it supports.

  13. Resource Planning Model: An Integrated Resource Planning and Dispatch Tool for Regional Electric Systems

    SciTech Connect (OSTI)

    Mai, T.; Drury, E.; Eurek, K.; Bodington, N.; Lopez, A.; Perry, A.

    2013-01-01T23:59:59.000Z

    This report introduces a new capacity expansion model, the Resource Planning Model (RPM), with high spatial and temporal resolution that can be used for mid- and long-term scenario planning of regional power systems. Although RPM can be adapted to any geographic region, the report describes an initial version of the model adapted for the power system in Colorado. It presents examples of scenario results from the first version of the model, including an example of a 30%-by-2020 renewable electricity penetration scenario.

  14. National resources for development -- a suggested decision model

    E-Print Network [OSTI]

    Henry, Sam Sherrill

    1973-01-01T23:59:59.000Z

    December 1973 Ma]or Sub]ect i Political Science NAT1ONAL RESOURCES FOR DEVELOPMENT ? A SUGGESTED DECISION MODEL A Thesis SAM SHERRILL HENRY, JR, Approved as to style and content by& ha rman of Comm ttee Gi uDP 'uu P Head of Depar ment Mem'ber Me... er December 19'73 ABSTRACT National Resources for Development -- A Suggested Decision Model (December 1973) Sam Sherrill Henry, Jr. , B. A. , Texas ARM University Directed bye Dr, Robert A. Bernstein This study is designed to analyze selected...

  15. GPS RINEX Files - Datasets - OpenEI Datasets

    Open Energy Info (EERE)

    Relationship Dataset Dataset extent Map data OpenStreetMap contributors Tiles by MapQuest License Creative Commons Attribution 4.0 Open Data Author University of...

  16. Surprise Valley water geochmical data - Datasets - OpenEI Datasets

    Open Energy Info (EERE)

    Relationship Dataset Dataset extent Map data OpenStreetMap contributors Tiles by MapQuest License Creative Commons Attribution 4.0 Open Data Author Lawrence...

  17. Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearch > TheNuclear Press ReleasesIn the InorganicResources Resources Policies,

  18. Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's PossibleRadiation Protection TechnicalResonant Soft X-Ray Scattering of0 Resource ProgramResources

  19. Welcome - OpenEI Datasets

    Open Energy Info (EERE)

    Search for a topic or click on a statistic to dive into our datasets. This is a featured section Placeholder OpenEI Datasets statistics 1k datasets 2 organizations 0 related items...

  20. Modeling of customer adoption of distributed energy resources

    E-Print Network [OSTI]

    2001-01-01T23:59:59.000Z

    of Dispersed Energy Resources Deployment. Berkeley, LawrenceAdoption of Distributed Energy Resources Ozbek, A. 2001.Adoption of Distributed Energy Resources Figure 39. Figure

  1. Solar Resource Assessment: Databases, Measurements, Models, and Information Sources (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2008-10-01T23:59:59.000Z

    Fact sheet for Solar Resource Assessment Workshop, Denver CO, Oct 29, 2008: ?Solar Resource Assessment Databases, Measurements, Models, and Information Sources

  2. Building Dynamic Models of Service Compositions with Simulation of Provision Resources

    E-Print Network [OSTI]

    Dustdar, Schahram

    Building Dynamic Models of Service Compositions with Simulation of Provision Resources Dragan compositions depends both on the composition structure, and on planning and management of compu- tational resources necessary for provision. Resource constraints on the service provider side have impact

  3. Modeling of customer adoption of distributed energy resources

    SciTech Connect (OSTI)

    Marnay, Chris; Chard, Joseph S.; Hamachi, Kristina S.; Lipman, Timothy; Moezzi, Mithra M.; Ouaglal, Boubekeur; Siddiqui, Afzal S.

    2001-08-01T23:59:59.000Z

    This report describes work completed for the California Energy Commission (CEC) on the continued development and application of the Distributed Energy Resources Customer Adoption Model (DER-CAM). This work was performed at Ernest Orlando Lawrence Berkeley National Laboratory (Berkeley Lab) between July 2000 and June 2001 under the Consortium for Electric Reliability Technology Solutions (CERTS) Distributed Energy Resources Integration (DERI) project. Our research on distributed energy resources (DER) builds on the concept of the microgrid ({mu}Grid), a semiautonomous grouping of electricity-generating sources and end-use sinks that are placed and operated for the benefit of its members. Although a {mu}Grid can operate independent of the macrogrid (the utility power network), the {mu}Grid is usually interconnected, purchasing energy and ancillary services from the macrogrid. Groups of customers can be aggregated into {mu}Grids by pooling their electrical and other loads, and the most cost-effective combination of generation resources for a particular {mu}Grid can be found. In this study, DER-CAM, an economic model of customer DER adoption implemented in the General Algebraic Modeling System (GAMS) optimization software is used, to find the cost-minimizing combination of on-site generation customers (individual businesses and a {mu}Grid) in a specified test year. DER-CAM's objective is to minimize the cost of supplying electricity to a specific customer by optimizing the installation of distributed generation and the self-generation of part or all of its electricity. Currently, the model only considers electrical loads, but combined heat and power (CHP) analysis capability is being developed under the second year of CEC funding. The key accomplishments of this year's work were the acquisition of increasingly accurate data on DER technologies, including the development of methods for forecasting cost reductions for these technologies, and the creation of a credible example California {mu}Grid for use in this study and in future work. The work performed during this year demonstrates the viability of DER-CAM and of our approach to analyzing adoption of DER.

  4. Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearch > TheNuclear Press ReleasesIn the Inorganic

  5. Modeling, Analysis, and Control of Demand Response Resources

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2013-01-01T23:59:59.000Z

    balancing, especially important in power systems with high penetrations of intermittent renewable resources like wind

  6. Modeling, Analysis, and Control of Demand Response Resources

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2012-01-01T23:59:59.000Z

    balancing, especially important in power systems with high penetrations of intermittent renewable resources like wind

  7. Optimal Control of Distributed Energy Resources using Model Predictive Control

    SciTech Connect (OSTI)

    Mayhorn, Ebony T.; Kalsi, Karanjit; Elizondo, Marcelo A.; Zhang, Wei; Lu, Shuai; Samaan, Nader A.; Butler-Purry, Karen

    2012-07-22T23:59:59.000Z

    In an isolated power system (rural microgrid), Distributed Energy Resources (DERs) such as renewable energy resources (wind, solar), energy storage and demand response can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizing costs associated with low battery life of energy storage and maintaining system frequency at the nominal operating value. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem. Simulation studies using high and low wind profiles, as well as, different MPC prediction horizons demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in wind and demand.

  8. Reference Inflow Characterization for River Resource Reference Model (RM2)

    SciTech Connect (OSTI)

    Neary, Vincent S [ORNL

    2011-12-01T23:59:59.000Z

    Sandia National Laboratory (SNL) is leading an effort to develop reference models for marine and hydrokinetic technologies and wave and current energy resources. This effort will allow the refinement of technology design tools, accurate estimates of a baseline levelized cost of energy (LCoE), and the identification of the main cost drivers that need to be addressed to achieve a competitive LCoE. As part of this effort, Oak Ridge National Laboratory was charged with examining and reporting reference river inflow characteristics for reference model 2 (RM2). Published turbulent flow data from large rivers, a water supply canal and laboratory flumes, are reviewed to determine the range of velocities, turbulence intensities and turbulent stresses acting on hydrokinetic technologies, and also to evaluate the validity of classical models that describe the depth variation of the time-mean velocity and turbulent normal Reynolds stresses. The classical models are found to generally perform well in describing river inflow characteristics. A potential challenge in river inflow characterization, however, is the high variability of depth and flow over the design life of a hydrokinetic device. This variation can have significant effects on the inflow mean velocity and turbulence intensity experienced by stationary and bottom mounted hydrokinetic energy conversion devices, which requires further investigation, but are expected to have minimal effects on surface mounted devices like the vertical axis turbine device designed for RM2. A simple methodology for obtaining an approximate inflow characterization for surface deployed devices is developed using the relation umax=(7/6)V where V is the bulk velocity and umax is assumed to be the near-surface velocity. The application of this expression is recommended for deriving the local inflow velocity acting on the energy extraction planes of the RM2 vertical axis rotors, where V=Q/A can be calculated given a USGS gage flow time-series and stage vs. cross-section area rating relationship.

  9. Unified Resource Modelling: Integrating knowledge into business processes

    E-Print Network [OSTI]

    regardless of their specific manifestation. Resource Business Process Service Contract Characteristic 1 of the performance of a quantifiable service. Contract involves one or more services that a resource offers

  10. Organizations - OpenEI Datasets

    Open Energy Info (EERE)

    ernateenergypromotioncentre Alternate Energy Promotion Centre 1 Dataset View Alternate Energy Promotion Centre alternativefuelsdatacenter Alternative Fuels Data Center 1...

  11. Resource Sharing in Performance Models Vlastimil Babka, Martin Decky, and Petr Tuma

    E-Print Network [OSTI]

    observed during the relatively isolated execution of benchmarks. Unless resource sharing is described shared resources [16,17,18,26,27,29] or points out the high cost of solving the performance model whenResource Sharing in Performance Models Vlastimil Babka, Martin Deck´y, and Petr T°uma Department

  12. Estimation of OTEC Global Resources with an Ocean General Circulation Model

    E-Print Network [OSTI]

    Frandsen, Jannette B.

    Ocean Thermal Energy Conversion (OTEC) relies on the availability of temperature differencesEstimation of OTEC Global Resources with an Ocean General Circulation Model Krishnakumar Rajagopalan Postdoctoral Fellow Department of Ocean and Resources Engineering University of Hawai'i Abstract

  13. Modeling access to wind resources in the United States

    SciTech Connect (OSTI)

    Short, W.D.

    1999-10-20T23:59:59.000Z

    To project the US potential to meet future electricity demands with wind energy, estimates of available wind resource and costs to access that resource are critical. The US Department of Energy (DOE) Energy Information Administration (EIA) annually estimates the US market penetration of wind in its Annual Energy Outlook series. For these estimates, the EIA uses wind resource data developed by the Pacific Northwest National Laboratory for each region of the country. However, the EIA multiplies the cost of windpower by several factors, some as large as 3, to account for resource quality, market factors associated with accessing the resource, electric grid impacts, and rapid growth in the wind industry. This paper examines the rationale behind these additional costs and suggests alternatives.

  14. Buildings Performance Database - Datasets - OpenEI Datasets

    Open Energy Info (EERE)

    data. The platform enables users to perform statistical analysis on an anonymous dataset of tens of thousands of commercial and residential buildings from across the country....

  15. Biofuel Enduse Datasets from the Bioenergy Knowledge Discovery Framework (KDF)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. [copied from https://www.bioenergykdf.net/content/about]

    Holdings include datasets, models, and maps. This is a very new resource, but the collections will grow due to both DOE contributions and individualsĆ data uploads. Currently the Biofuel Enduse collection includes 133 items. Most of these are categorized as literature, but 36 are listed as datasets and ten as models.

  16. Building Dynamic Models of Service Compositions With Simulation of Provision Resources

    E-Print Network [OSTI]

    Politécnica de Madrid, Universidad

    Building Dynamic Models of Service Compositions With Simulation of Provision Resources Dragan of service compositions depends both on the composition structure, and on planning and management of compu- tational resources necessary for provision. Resource constraints on the service provider side have impact

  17. Massive Datasets in Astronomy

    E-Print Network [OSTI]

    Robert J. Brunner; S. George Djorgovski; Thomas A. Prince; Alex S. Szalay

    2001-06-26T23:59:59.000Z

    Astronomy has a long history of acquiring, systematizing, and interpreting large quantities of data. Starting from the earliest sky atlases through the first major photographic sky surveys of the 20th century, this tradition is continuing today, and at an ever increasing rate. Like many other fields, astronomy has become a very data-rich science, driven by the advances in telescope, detector, and computer technology. Numerous large digital sky surveys and archives already exist, with information content measured in multiple Terabytes, and even larger, multi-Petabyte data sets are on the horizon. Systematic observations of the sky, over a range of wavelengths, are becoming the primary source of astronomical data. Numerical simulations are also producing comparable volumes of information. Data mining promises to both make the scientific utilization of these data sets more effective and more complete, and to open completely new avenues of astronomical research. Technological problems range from the issues of database design and federation, to data mining and advanced visualization, leading to a new toolkit for astronomical research. This is similar to challenges encountered in other data-intensive fields today. These advances are now being organized through a concept of the Virtual Observatories, federations of data archives and services representing a new information infrastructure for astronomy of the 21st century. In this article, we provide an overview of some of the major datasets in astronomy, discuss different techniques used for archiving data, and conclude with a discussion of the future of massive datasets in astronomy.

  18. Modeling of Thermal Storage Systems in MILP Distributed Energy Resource Models

    E-Print Network [OSTI]

    Steen, David

    2014-01-01T23:59:59.000Z

    and a Ph.D. in Energy and Resources, all from the Universityof distributed energy resources," in Power and EnergyPouresmaeil, "Distributed energy resources and benefits to

  19. PET: A PErsonalized Trust Model with Reputation and Risk Evaluation for P2P Resource Sharing

    E-Print Network [OSTI]

    Shi, Weisong

    PET: A PErsonalized Trust Model with Reputation and Risk Evaluation for P2P Resource Sharing the construction of a good cooperation, especially in the context of economic-based solutions for the P2P resource sharing. The trust model consists of two parts: reputation evaluation and risk evaluation. Reputation

  20. Andrew Ford BWeb for Modeling the Environment 1 Resource Economics

    E-Print Network [OSTI]

    Ford, Andrew

    for clean vehicles. Natural gas was also the most popular fuel for new power generation during of Natural Gas in the USA These exercises provide an opportunity to use system dynamics to study the life cycle of a non- renewable resource. Natural gas may be the most important source of energy in the United

  1. Modeling, Analysis, and Control of Demand Response Resources

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2013-01-01T23:59:59.000Z

    Modeling and control of aggregated heterogeneous thermostatically controlled loads for ancillary services”. In: Proceedings of the Power SystemsModeling and control of thermostatically controlled loads”. In: Pro- ceedings of 17 th Power Systems

  2. Modeling, Analysis, and Control of Demand Response Resources

    E-Print Network [OSTI]

    Mathieu, Johanna L.

    2012-01-01T23:59:59.000Z

    Modeling and control of aggregated heterogeneous thermostatically controlled loads for ancillary services”. In: Proceedings of the Power SystemsModeling and control of thermostatically controlled loads”. In: Pro- ceedings of 17 th Power Systems

  3. New Models Help Optimize Development of Bakken Shale Resources | Department

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's Possible for Renewable Energy:Nanowire Solar541,9337, 2011R - 445 CU

  4. A Resource Conceptual Model for the Ngatamariki Geothermal Field...

    Open Energy Info (EERE)

    Conceptual Model for the Ngatamariki Geothermal Field Based on Recent Exploration Well Drilling and 3D MT Resistivity Imaging Jump to: navigation, search OpenEI Reference...

  5. National Strategic Unconventional Resource Model | 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directed offOCHCO2:Introduction toManagement ofConverDyn NOPRNancy

  6. Hydrogen Demand and Resource Analysis (HyDRA) Model

    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 onYouTube YouTube Note: Since the.pdfBreaking of Blythe SolarContamination Detector Workshop HydrogenScenario

  7. Geothermal Resource Conceptual Models Using Surface Exploration Data | Open

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are8COaBulkTransmissionSitingProcess.pdf Jump1946865°,Park,2005)Energy Information )Et Al.,Energy||ImageryEnergy

  8. Geothermal resource conceptual models using surface exploration data | Open

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are8COaBulkTransmissionSitingProcess.pdf Jump1946865°,Park,2005)EnergyAmatitlan GeothermalEnergy Information

  9. Decoupling and Utility Business Model Resources | 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 DataDepartment of Energy Your Density Isn't Your Destiny:Revised Finding of No53197 This workDayton: ENERGY8Decommissioning Plan|

  10. Reference Model #1 - Tidal Energy: Resource Dr. Brian Polagye

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Scienceand Requirements Recently Approved JustificationBio-Inspired Solar FuelReduceReference

  11. Model Solar Guidelines: A Resource for North Carolina Homeowners

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy ChinaofSchaeferApril 1,(EAC)TABLE OF CONTENTSTogetherThe highDepartment of

  12. Modeling Through Shared Resources, No High-Fashion Experience Required |

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy ChinaofSchaeferApril 1,(EAC)TABLE OF CONTENTSTogetherThe highDepartmentDepartment of

  13. New Models Help Optimize Development of Bakken Shale Resources | Department

    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 DataDepartment of Energy Your Density Isn'tOrigin of Contamination in Many DevilsForumEngines | Department of EnergySensitive Speciesof

  14. Comprehensive ecosystem model-experiment synthesis using multiple datasets at two temperate forest free-air CO2 enrichment experiments: model performance and compensating biases

    SciTech Connect (OSTI)

    Walker, Anthony P [ORNL] [ORNL; Hanson, Paul J [ORNL] [ORNL; DeKauwe, Martin G [Macquarie University] [Macquarie University; Medlyn, Belinda [Macquarie University] [Macquarie University; Zaehle, S [Max Planck Institute for Biogeochemistry] [Max Planck Institute for Biogeochemistry; Asao, Shinichi [Colorado State University, Fort Collins] [Colorado State University, Fort Collins; Dietze, Michael [University of Illinois, Urbana-Champaign] [University of Illinois, Urbana-Champaign; Hickler, Thomas [Goethe University, Frankfurt, Germany] [Goethe University, Frankfurt, Germany; Huntinford, Chris [Centre for Ecology and Hydrology, Wallingford, United Kingdom] [Centre for Ecology and Hydrology, Wallingford, United Kingdom; Iversen, Colleen M [ORNL] [ORNL; Jain, Atul [University of Illinois, Urbana-Champaign] [University of Illinois, Urbana-Champaign; Lomas, Mark [University of Sheffield] [University of Sheffield; Luo, Yiqi [University of Oklahoma] [University of Oklahoma; McCarthy, Heather R [Duke University] [Duke University; Parton, William [Colorado State University, Fort Collins] [Colorado State University, Fort Collins; Prentice, I. Collin [Macquarie University] [Macquarie University; Thornton, Peter E [ORNL] [ORNL; Wang, Shusen [Canada Centre for Remote Sensing (CCRS)] [Canada Centre for Remote Sensing (CCRS); Wang, Yingping [CSIRO Marine and Atmospheric Research] [CSIRO Marine and Atmospheric Research; Warlind, David [Lund University, Sweden] [Lund University, Sweden; Weng, Ensheng [University of Oklahoma, Norman] [University of Oklahoma, Norman; Warren, Jeffrey [ORNL] [ORNL; Woodward, F. Ian [University of Sheffield] [University of Sheffield; Oren, Ram [Duke University] [Duke University; Norby, Richard J [ORNL] [ORNL

    2014-01-01T23:59:59.000Z

    Free Air CO2 Enrichment (FACE) experiments provide a remarkable wealth of data to test the sensitivities of terrestrial ecosystem models (TEMs). In this study, a broad set of 11 TEMs were compared to 22 years of data from two contrasting FACE experiments in temperate forests of the south eastern US the evergreen Duke Forest and the deciduous Oak Ridge forest. We evaluated the models' ability to reproduce observed net primary productivity (NPP), transpiration and Leaf Area index (LAI) in ambient CO2 treatments. Encouragingly, many models simulated annual NPP and transpiration within observed uncertainty. Daily transpiration model errors were often related to errors in leaf area phenology and peak LAI. Our analysis demonstrates that the simulation of LAI often drives the simulation of transpiration and hence there is a need to adopt the most appropriate of hypothesis driven methods to simulate and predict LAI. Of the three competing hypotheses determining peak LAI (1) optimisation to maximise carbon export, (2) increasing SLA with canopy depth and (3) the pipe model the pipe model produced LAI closest to the observations. Modelled phenology was either prescribed or based on broader empirical calibrations to climate. In some cases, simulation accuracy was achieved through compensating biases in component variables. For example, NPP accuracy was sometimes achieved with counter-balancing biases in nitrogen use efficiency and nitrogen uptake. Combined analysis of parallel measurements aides the identification of offsetting biases; without which over-confidence in model abilities to predict ecosystem function may emerge, potentially leading to erroneous predictions of change under future climates.

  15. Brady's Geothermal Field Seismic Network Metadata - Datasets...

    Open Energy Info (EERE)

    Relationship Dataset Dataset extent Map data OpenStreetMap contributors Tiles by MapQuest License Creative Commons Attribution 4.0 Open Data Author University of...

  16. Resource Sharing in QPN-based Performance Models Charles University Prague, Faculty of Mathematics and Physics, Prague, Czech Republic.

    E-Print Network [OSTI]

    Resource Sharing in QPN-based Performance Models V. Babka Charles University Prague, Faculty needed to solve the model can be significantly influenced by resource sharing, capturing this influence separate resource and performance models and proposes a method of integrating these models at the tool

  17. Form:Dataset | 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,dataset name below to add to the

  18. Final Map Draft Comparison Report WIND ENERGY RESOURCE MODELING AND MEASUREMENT PROJECT

    E-Print Network [OSTI]

    SOLUTIONS, LLC (now AWS Truewind LLC) 255 FULLER ROAD, SUITE 274 ALBANY, NEW YORK Michael Brower PrincipalII Final Map Draft Comparison Report #12;WIND ENERGY RESOURCE MODELING AND MEASUREMENT PROJECT Tel: 978-749-9591 Fax: 978-749-9713 mbrower@awstruewind.com August 10, 2004 #12;2 WIND ENERGY RESOURCE

  19. ORIGINAL PAPER "Modeling the impact of natural resource-based poverty

    E-Print Network [OSTI]

    Lehmann, Johannes

    ORIGINAL PAPER "Modeling the impact of natural resource-based poverty traps on food security and Dynamic Poverty Traps in East Africa. The Rockefeller Foundation is providing key financial support the interactions between natural resource-based poverty traps and food security for small- holder farms in highland

  20. Designing a Collaborative Problem Solving Environment for Integrated Water Resource Modeling

    SciTech Connect (OSTI)

    Thurman, David A.; Cowell, Andrew J.; Taira, Randal Y.; Frodge, Jonathan

    2004-06-14T23:59:59.000Z

    We report on our approach for designing a collaborative problem solving environment for hydrologists, water quality planners and natural resource managers, all roles within a natural resource management agency and stakeholders in an integrated water resource management process. We describe our approach in context of the Integrated Water Resource Modeling System (IWRMS), under development by Pacific Northwest National Laboratory for the Department of Natural Resources and Parks in King County, Washington. This system will integrate a collection of water resource models (watersheds, rivers, lakes, estuaries) to provide the ability to address water, land use, and other natural resource management decisions and scenarios, with the goal of developing an integrated modeling capability to address future land use and resource management scenarios and provide scientific support to decision makers. Here, we discuss the five-step process used to ascertain the (potentially opposing) needs and interests of stakeholders and provide results and summaries from our experiences. The results of this process guide user interface design efforts to create a collaborative problems solving environment supporting multiple users with differing scientific backgrounds and modeling needs. We conclude with a discussion of participatory interface design methods used to encourage stakeholder involvement and acceptance of the system as well as the lessons learned to date.

  1. Modeling U.S. water resources under climate change*

    E-Print Network [OSTI]

    in natural systems and runoff, and future scenarios of water demand for power plant cooling are consistent's Future, 2(4): 197­244 (doi: 10.1002/2013EF000214) © 2014 with kind permission from the authors. Reprint-driven, the Program uses extensive Earth system and economic data and models to produce quantitative analysis

  2. DOE Facility Database - Datasets - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOE Facility Database Data and Resources DOE Facility DatabaseCSV Preview

  3. Integrated modelling and assessment of regional groundwater resources in Germany and Benin, West Africa

    E-Print Network [OSTI]

    Cirpka, Olaf Arie

    1 Integrated modelling and assessment of regional groundwater resources in Germany and Benin, West.J.S. SONNEVELD [1] Institute of Hydraulic Engineering, Universitaet Stuttgart, Germany (Roland Conservation University of Bonn, Germany [3] Institute of Landscape Planning and Ecology, University

  4. Energy Generation by State and Technology (2009) - Datasets - OpenEI

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOEHazel Crest,EnergySerranopolis Jump to:Econ IncIRENADelhiFocusDatasets

  5. The Wind Integration National Dataset (WIND) toolkit (Presentation)

    SciTech Connect (OSTI)

    Caroline Draxl: NREL

    2014-01-01T23:59:59.000Z

    Regional wind integration studies require detailed wind power output data at many locations to perform simulations of how the power system will operate under high penetration scenarios. The wind datasets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as being time synchronized with available load profiles.As described in this presentation, the WIND Toolkit fulfills these requirements by providing a state-of-the-art national (US) wind resource, power production and forecast dataset.

  6. Models, Simulators, and Data-driven Resources for Oil and Natural Gas Research

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    NETL provides a number of analytical tools to assist in conducting oil and natural gas research. Software, developed under various DOE/NETL projects, includes numerical simulators, analytical models, databases, and documentation.[copied from http://www.netl.doe.gov/technologies/oil-gas/Software/Software_main.html] Links lead users to methane hydrates models, preedictive models, simulators, databases, and other software tools or resources.

  7. PoroTomo Subtask 3.5 GPS Data Analysis - Datasets - OpenEI Datasets

    Open Energy Info (EERE)

    Relationship Dataset Dataset extent Map data OpenStreetMap contributors Tiles by MapQuest License Creative Commons Attribution 4.0 Open Data Author University of...

  8. Porotomo Subtask 3.4 Raw Data - Datasets - OpenEI Datasets

    Open Energy Info (EERE)

    Relationship Dataset Dataset extent Map data OpenStreetMap contributors Tiles by MapQuest License Creative Commons Attribution 4.0 Open Data Author University of...

  9. Conductance Steamflow relationship - Datasets - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model, clickInformationNew| Open EnergyInformation Faulds,Concordia,

  10. Resources, Conservation and Recycling 51 (2007) 847869 Modeling obsolete computer stock under regional

    E-Print Network [OSTI]

    Illinois at Chicago, University of

    2007-01-01T23:59:59.000Z

    Resources, Conservation and Recycling 51 (2007) 847­869 Modeling obsolete computer stock under and recycling systems using GIS, and demonstrate the potential economic benefits from diverting electronic buildings. © 2007 Elsevier B.V. All rights reserved. Keywords: Computer recycling; Product inventory

  11. North West Hydro Resource Model Research to identify potential capacity and assist NW hydro power development

    E-Print Network [OSTI]

    Meju, Max

    North West Hydro Resource Model Research to identify potential capacity and assist NW hydro power University wide research, aims to develop a system to promote the exploitation of hydro power in North with regard to hydro schemes Reviewing and re-formulating ill defined requirements for environmental

  12. Modeling the Global Water Resource System in an Integrated Assessment Modeling Framework: IGSM-WRS

    E-Print Network [OSTI]

    Strzepek, Kenneth M.

    The availability of water resources affects energy, agricultural and environmental systems, which are linked together as well as to climate via the water cycle. As such, watersheds and river basins are directly impacted ...

  13. Bayesian evidence as a tool for comparing datasets

    E-Print Network [OSTI]

    Phil Marshall; Nutan Rajguru; Anze Slosar

    2007-10-30T23:59:59.000Z

    We introduce a new conservative test for quantifying the consistency of two or more datasets. The test is based on the Bayesian answer to the question, ``How much more probable is it that all my data were generated from the same model system than if each dataset were generated from an independent set of model parameters?''. We make explicit the connection between evidence ratios and the differences in peak chi-squared values, the latter of which are more widely used and more cheaply calculated. Calculating evidence ratios for three cosmological datasets (recent CMB data (WMAP, ACBAR, CBI, VSA), SDSS and the most recent SNe Type 1A data) we find that concordance is favoured and the tightening of constraints on cosmological parameters is indeed justified.

  14. 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

  15. beamer-tu-logo Introduction The full abstraction problem for PCF Quantitative models The resource calculus Conclusion

    E-Print Network [OSTI]

    Ayala-Rincón, Mauricio

    beamer-tu-logo Introduction The full abstraction problem for PCF Quantitative models The resource Preuves, Programmes et Systčmes Université Paris Diderot #12;beamer-tu-logo Introduction The full The full abstraction problem for PCF 3 Quantitative models 4 The resource calculus 5 Conclusion #12;beamer-tu-logo

  16. CKBGroup/2013 Workshop and Resources | Open Energy Information

    Open Energy Info (EERE)

    Get Involved Help Apps Datasets Community Login | Sign Up Search Page Edit History Facebook icon Twitter icon CKBGroup2013 Workshop and Resources < CKBGroup Jump to:...

  17. Distributed energy resources in practice: A case study analysis and validation of LBNL's customer adoption model

    E-Print Network [OSTI]

    Bailey, Owen; Creighton, Charles; Firestone, Ryan; Marnay, Chris; Stadler, Michael

    2003-01-01T23:59:59.000Z

    Pharmingen Distributed Energy Resources in Practice Tablemany regions. Distributed Energy Resources in Practice 10.of µGrid Distributed Energy Resource Potential Using DER-CAM

  18. Distributed energy resources customer adoption modeling with combined heat and power applications

    E-Print Network [OSTI]

    Siddiqui, Afzal S.; Firestone, Ryan M.; Ghosh, Srijay; Stadler, Michael; Edwards, Jennifer L.; Marnay, Chris

    2003-01-01T23:59:59.000Z

    Alex Farrell of the Energy and Resources Group, UniversityMicrogrid Distributed Energy Resource Potential Using DER-of Distributed Energy Resources: The CERTS MicroGrid

  19. Carrots and Sticks: A Comprehensive Business Model for the Successful Achievement of Energy Efficiency Resource Standards Environmental Energy Technologies Division March 2011

    E-Print Network [OSTI]

    Satchwell, Andrew

    2011-01-01T23:59:59.000Z

    Business Model for the Successful Achievement of Energy Efficiency ResourceBusiness Model for the Successful Achievement of Energy Efficiency Resourcebusiness model on utility ROE 13   Table 1. Lifetime savings, resource costs and benefits of alternative energy efficiency

  20. A Hydro-Economic Approach to Representing Water Resources Impacts in Integrated Assessment Models

    SciTech Connect (OSTI)

    Kirshen, Paul H.; Strzepek, Kenneth, M.

    2004-01-14T23:59:59.000Z

    Grant Number DE-FG02-98ER62665 Office of Energy Research of the U.S. Department of Energy Abstract Many Integrated Assessment Models (IAM) divide the world into a small number of highly aggregated regions. Non-OECD countries are aggregated geographically into continental and multiple-continental regions or economically by development level. Current research suggests that these large scale aggregations cannot accurately represent potential water resources-related climate change impacts. In addition, IAMs do not explicitly model the flow regulation impacts of reservoir and ground water systems, the economics of water supply, or the demand for water in economic activities. Using the International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT) model of the International Food Policy Research Institute (IFPRI) as a case study, this research implemented a set of methodologies to provide accurate representation of water resource climate change impacts in Integrated Assessment Models. There were also detailed examinations of key issues related to aggregated modeling including: modeling water consumption versus water withdrawals; ground and surface water interactions; development of reservoir cost curves; modeling of surface areas of aggregated reservoirs for estimating evaporation losses; and evaluating the importance of spatial scale in river basin modeling. The major findings include: - Continental or national or even large scale river basin aggregation of water supplies and demands do not accurately capture the impacts of climate change in the water and agricultural sector in IAMs. - Fortunately, there now exist gridden approaches (0.5 X 0.5 degrees) to model streamflows in a global analysis. The gridded approach to hydrologic modeling allows flexibility in aligning basin boundaries with national boundaries. This combined with GIS tools, high speed computers, and the growing availability of socio-economic gridded data bases allows assignment of demands to river basins to create hydro-economic zones that respect as much as possible both political and hydrologic integrity in different models. - To minimize pre-processing of data and add increased flexibility to modeling water resources and uses, it is recommended that water withdrawal demands be modeled, not consumptive requirements even though this makes the IAM more complex. - IAMs must consider changes in water availability for irrigation under climate change; ignoring them is more inaccurate than ignoring yield changes in crops under climate change. - Determining water availability and cost in river basins must include modeling streamflows, reservoirs and their operations, and ground water and its interaction with surface water. - Scale issues are important. The results from condensing demands and supplies in a large complex river basin to one node can be misleading for all uses under low flow conditions and instream flow uses under all conditions. Monthly is generally the most accurate scale for modeling river flows and demands. Challenges remain in integrating hydrologic units with political boundaries but the gridded approach to hydrologic modeling allows flexibility in aligning basin boundaries with political boundaries. - Using minimal reservoir cost data, it is possible to use basin topography to estimate reservoir storage costs. - Reservoir evaporation must be considered when assessing the usable water in a watershed. Several methods are available to estimate the relationship between aggregated storage surface area and storage volume. - For existing or future IAMs that can not use the appropriate aggregation for water, a water preprocessor may be required due the finer scale of hydrologic impacts.

  1. Seeing about Soil -- Management Lessons from a Simple Model for Renewable Resources

    E-Print Network [OSTI]

    Lichtenegger, Klaus

    2013-01-01T23:59:59.000Z

    Employing an effective cellular automata model, we investigate and analyze the build-up and erosion of soil. Depending on the strategy employed for handling agricultural production, in many cases we find a critical dependence on the prescribed production target, with a sharp transition between stable production and complete breakdown of the system. Strategies which are particularly well-suited for mimicking real-world management approaches can produce almost cyclic behaviour, which can also either lead to sustainable production or to breakdown. While designed to describe the dynamics of soil evolution, this model is quite general and may also be useful as a model for other renewable resources and may even be employed in other disciplines like psychology.

  2. Metering Best Practices Applied in the National Renewable Energy Laboratory's Research Support Facility: A Primer to the 2011 Measured and Modeled Energy Consumption Datasets

    SciTech Connect (OSTI)

    Sheppy, M.; Beach, A.; Pless, S.

    2013-04-01T23:59:59.000Z

    Modern buildings are complex energy systems that must be controlled for energy efficiency. The Research Support Facility (RSF) at the National Renewable Energy Laboratory (NREL) has hundreds of controllers -- computers that communicate with the building's various control systems -- to control the building based on tens of thousands of variables and sensor points. These control strategies were designed for the RSF's systems to efficiently support research activities. Many events that affect energy use cannot be reliably predicted, but certain decisions (such as control strategies) must be made ahead of time. NREL researchers modeled the RSF systems to predict how they might perform. They then monitor these systems to understand how they are actually performing and reacting to the dynamic conditions of weather, occupancy, and maintenance.

  3. Hydrologic Modeling with Arc Hydro Tools 1 Copyright 2007 ESRI. All rights reserved. Arc Hydro

    E-Print Network [OSTI]

    Kane, Andrew S.

    resources applications (template data model) Culmination of a three year process led by D.R. Maidment rights reserved. Inside the Geodatabase Geodatabase Survey datasets Survey folder Survey Locators Template Data Models (30+) HEC ...FEMA Project Data Models Feature TopologyObject ArcGIS Core Data Model

  4. Visualization Fusion: Hurricane Isabel Dataset Naeem Shareef

    E-Print Network [OSTI]

    Crawfis, Roger

    Visualization Fusion: Hurricane Isabel Dataset Ming Jiang Naeem Shareef Caixia Zhang Roger Crawfis in developing visualization techniques for the Hurricane Isabel dataset is to engender better understand- ing of the underlying physical phenomenon. We want the visualization to produce novel insights into how a hurricane

  5. CIM-EARTH: Community integrated model of economic and resource trajectories for humankind.

    SciTech Connect (OSTI)

    Elliott, J.; Foster, I.; Judd, K.; Moyer, E.; Munson, T.; Univ. of Chicago; Hoover Inst.

    2010-01-01T23:59:59.000Z

    Climate change is a global problem with local climatic and economic impacts. Mitigation policies can be applied on large geographic scales, such as a carbon cap-and-trade program for the entire U.S., on medium geographic scales, such as the NOx program for the northeastern U.S., or on smaller scales, such as statewide renewable portfolio standards and local gasoline taxes. To enable study of the environmental benefits, transition costs, capitalization effects, and other consequences of mitigation policies, we are developing dynamic general equilibrium models capable of incorporating important climate impacts. This report describes the economic framework we have developed and the current Community Integrated Model of Economic and Resource Trajectories for Humankind (CIM-EARTH) instance.

  6. DTE Energy Technologies With Detroit Edison Co. and Kinectrics Inc.: Distributed Resources Aggregation Modeling and Field Configuration Testing

    SciTech Connect (OSTI)

    Not Available

    2003-10-01T23:59:59.000Z

    Summarizes the work of DTE Energy Technologies, Detroit Edison, and Kinectrics, under contract to DOE's Distribution and Interconnection R&D, to develop distributed resources aggregation modeling and field configuration testing.

  7. On an improved sub-regional water resources management representation for integration into earth system models

    SciTech Connect (OSTI)

    Voisin, Nathalie; Li, Hongyi; Ward, Duane L.; Huang, Maoyi; Wigmosta, Mark S.; Leung, Lai-Yung R.

    2013-09-30T23:59:59.000Z

    Human influence on the hydrologic cycle includes regulation and storage, consumptive use and overall redistribution of water resources in space and time. Representing these processes is essential for applications of earth system models in hydrologic and climate predictions, as well as impact studies at regional to global scales. Emerging large-scale research reservoir models use generic operating rules that are flexible for coupling with earth system models. Those generic operating rules have been successful in reproducing the overall regulated flow at large basin scales. This study investigates the uncertainties of the reservoir models from different implementations of the generic operating rules using the complex multi-objective Columbia River Regulation System in northwestern United States as an example to understand their effects on not only regulated flow but also reservoir storage and fraction of the demand that is met. Numerical experiments are designed to test new generic operating rules that combine storage and releases targets for multi-purpose reservoirs and to compare the use of reservoir usage priorities, withdrawals vs. consumptive demand, as well as natural vs. regulated mean flow for calibrating operating rules. Overall the best performing implementation is the use of the combined priorities (flood control storage targets and irrigation release targets) operating rules calibrated with mean annual natural flow and mean monthly withdrawals. The challenge of not accounting for groundwater withdrawals, or on the contrary, assuming that all remaining demand is met through groundwater extractions, is discussed.

  8. Distributed energy resources in practice: A case study analysis and validation of LBNL's customer adoption model

    E-Print Network [OSTI]

    Bailey, Owen; Creighton, Charles; Firestone, Ryan; Marnay, Chris; Stadler, Michael

    2003-01-01T23:59:59.000Z

    Resources in Practice Source of Financial Estimates Project Cost Grants Received Annual Benefit (without capital

  9. NREL RSF Weather Data 2011 - Datasets - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal Pwer PlantMunhall, Pennsylvania: Energy Resources JumpNEFAppropriationReference ManualRSF Weather

  10. NREL Residential Buildings Group Partners - Datasets - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal Pwer PlantMunhall, Pennsylvania: Energy Resources JumpNEFAppropriationReference ManualRSF

  11. Carrots and Sticks: A Comprehensive Business Model for the Successful Achievement of Energy Efficiency Resource Standards Environmental Energy Technologies Division March 2011

    E-Print Network [OSTI]

    Satchwell, Andrew

    2011-01-01T23:59:59.000Z

    and energy costs. Model Inputs Utility Characterization Business-energy efficiency business model on utility ROE 13   Table 1. Lifetime savings, resource costs

  12. Gravity Survey of the Carson Sink - Data and Maps - Datasets...

    Open Energy Info (EERE)

    Relationship Dataset Dataset extent Map data OpenStreetMap contributors Tiles by MapQuest License Creative Commons Attribution 4.0 Open Data Author University of...

  13. D-Factor: A Quantitative Model of Application Slow-Down in Multi-Resource Shared Systems

    SciTech Connect (OSTI)

    Lim, Seung-Hwan [ORNL] [ORNL; Huh, Jae-Seok [ORNL] [ORNL; Kim, Youngjae [ORNL] [ORNL; Shipman, Galen M [ORNL] [ORNL; Das, Chita [Pennsylvania State University, University Park, PA] [Pennsylvania State University, University Park, PA

    2012-01-01T23:59:59.000Z

    Scheduling multiple jobs onto a platform enhances system utilization by sharing resources. The benefits from higher resource utilization include reduced cost to construct, operate, and maintain a system, which often include energy consumption. Maximizing these benefits comes at a price - resource contention among jobs increases job completion time. In this paper, we analyze slow-downs of jobs due to contention for multiple resources in a system; referred to as dilation factor. We observe that multiple-resource contention creates non-linear dilation factors of jobs. From this observation, we establish a general quantitative model for dilation factors of jobs in multi-resource systems. A job is characterized by a vector-valued loading statistics and dilation factors of a job set are given by a quadratic function of their loading vectors. We demonstrate how to systematically characterize a job, maintain the data structure to calculate the dilation factor (loading matrix), and calculate the dilation factor of each job. We validate the accuracy of the model with multiple processes running on a native Linux server, virtualized servers, and with multiple MapReduce workloads co-scheduled in a cluster. Evaluation with measured data shows that the D-factor model has an error margin of less than 16%. We also show that the model can be integrated with an existing on-line scheduler to minimize the makespan of workloads.

  14. Final Report: Phase II Nevada Water Resources Data, Modeling, and Visualization (DMV) Center

    SciTech Connect (OSTI)

    Jackman, Thomas [Desert Research Institute] [Desert Research Institute; Minor, Timothy [Desert Research Institute] [Desert Research Institute; Pohll, Gregory [Desert Research Institute] [Desert Research Institute

    2013-07-22T23:59:59.000Z

    Water is unquestionably a critical resource throughout the United States. In the semi-arid west -- an area stressed by increase in human population and sprawl of the built environment -- water is the most important limiting resource. Crucially, science must understand factors that affect availability and distribution of water. To sustain growing consumptive demand, science needs to translate understanding into reliable and robust predictions of availability under weather conditions that could be average but might be extreme. These predictions are needed to support current and long-term planning. Similar to the role of weather forecast and climate prediction, water prediction over short and long temporal scales can contribute to resource strategy, governmental policy and municipal infrastructure decisions, which are arguably tied to the natural variability and unnatural change to climate. Change in seasonal and annual temperature, precipitation, snowmelt, and runoff affect the distribution of water over large temporal and spatial scales, which impact the risk of flooding and the groundwater recharge. Anthropogenic influences and impacts increase the complexity and urgency of the challenge. The goal of this project has been to develop a decision support framework of data acquisition, digital modeling, and 3D visualization. This integrated framework consists of tools for compiling, discovering and projecting our understanding of processes that control the availability and distribution of water. The framework is intended to support the analysis of the complex interactions between processes that affect water supply, from controlled availability to either scarcity or deluge. The developed framework enables DRI to promote excellence in water resource management, particularly within the Lake Tahoe basin. In principle, this framework could be replicated for other watersheds throughout the United States. Phase II of this project builds upon the research conducted during Phase I, in which the hydrologic framework was investigated and the development initiated. Phase II concentrates on practical implementation of the earlier work but emphasizes applications to the hydrology of the Lake Tahoe basin. Phase 1 efforts have been refined and extended by creating a toolset for geographic information systems (GIS) that is usable for disparate types of geospatial and geo-referenced data. The toolset is intended to serve multiple users for a variety of applications. The web portal for internet access to hydrologic and remotely sensed product data, prototyped in Phase I, has been significantly enhanced. The portal provides high performance access to LANDSAT-derived data using techniques developed during the course of the project. The portal is interactive, and supports the geo-referenced display of hydrologic information derived from remotely sensed data, such as various vegetative indices used to calculate water consumption. The platform can serve both internal and external constituencies using inter-operating infrastructure that spans both sides of the DRI firewall. The platform is intended grow its supported data assets and to serve as a template for replication to other geographic areas. An unanticipated development during the project was the use of ArcGIS software on a new computer system, called the IBM PureSytems, and the parallel use of the systems for faster, more efficient image processing. Additional data, independent of the portal, was collected within the Sagehen basin and provides detailed information regarding the processes that control hydrologic responses within mountain watersheds. The newly collected data include elevation, evapotranspiration, energy balance and remotely sensed snow-pack data. A Lake Tahoe basin hydrologic model has been developed, in part to help predict the hydrologic impacts of climate change. The model couples both the surface and subsurface hydrology, with the two components having been independently calibrated. Results from the coupled simulations involving both surface water and groundwater processes

  15. A new bed elevation dataset for Greenland

    E-Print Network [OSTI]

    2013-01-01T23:59:59.000Z

    and bed data set for the Greenland ice sheet 1. Measure-bed elevation dataset for Greenland J. L. Bamber 1 , J. A.face mass balance of the Greenland ice sheet revealed by

  16. Spatial Modelling with Geographic Information Systems for Determination of Water Resources Vulnerability

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    (river or well). This method is based on spatial analysis tools integrated in Geographical Information is proposed. The vulnerability of a water resource is defined as the risk that the resource will become (rivers or aquifers) against pollution is an important challenge for decision- makers in water resources

  17. Distributed energy resources customer adoption modeling with combined heat and power applications

    SciTech Connect (OSTI)

    Siddiqui, Afzal S.; Firestone, Ryan M.; Ghosh, Srijay; Stadler, Michael; Edwards, Jennifer L.; Marnay, Chris

    2003-07-01T23:59:59.000Z

    In this report, an economic model of customer adoption of distributed energy resources (DER) is developed. It covers progress on the DER project for the California Energy Commission (CEC) at Berkeley Lab during the period July 2001 through Dec 2002 in the Consortium for Electric Reliability Technology Solutions (CERTS) Distributed Energy Resources Integration (DERI) project. CERTS has developed a specific paradigm of distributed energy deployment, the CERTS Microgrid (as described in Lasseter et al. 2002). The primary goal of CERTS distributed generation research is to solve the technical problems required to make the CERTS Microgrid a viable technology, and Berkeley Lab's contribution is to direct the technical research proceeding at CERTS partner sites towards the most productive engineering problems. The work reported herein is somewhat more widely applicable, so it will be described within the context of a generic microgrid (mGrid). Current work focuses on the implementation of combined heat and power (CHP) capability. A mGrid as generically defined for this work is a semiautonomous grouping of generating sources and end-use electrical loads and heat sinks that share heat and power. Equipment is clustered and operated for the benefit of its owners. Although it can function independently of the traditional power system, or macrogrid, the mGrid is usually interconnected and exchanges energy and possibly ancillary services with the macrogrid. In contrast to the traditional centralized paradigm, the design, implementation, operation, and expansion of the mGrid is meant to optimize the overall energy system requirements of participating customers rather than the objectives and requirements of the macrogrid.

  18. Distributed energy resources in practice: A case study analysis and validation of LBNL's customer adoption model

    SciTech Connect (OSTI)

    Bailey, Owen; Creighton, Charles; Firestone, Ryan; Marnay, Chris; Stadler, Michael

    2003-02-01T23:59:59.000Z

    This report describes a Berkeley Lab effort to model the economics and operation of small-scale (<500 kW) on-site electricity generators based on real-world installations at several example customer sites. This work builds upon the previous development of the Distributed Energy Resource Customer Adoption Model (DER-CAM), a tool designed to find the optimal combination of installed equipment, and idealized operating schedule, that would minimize the site's energy bills, given performance and cost data on available DER technologies, utility tariffs, and site electrical and thermal loads over a historic test period, usually a recent year. This study offered the first opportunity to apply DER-CAM in a real-world setting and evaluate its modeling results. DER-CAM has three possible applications: first, it can be used to guide choices of equipment at specific sites, or provide general solutions for example sites and propose good choices for sites with similar circumstances; second, it can additionally provide the basis for the operations of installed on-site generation; and third, it can be used to assess the market potential of technologies by anticipating which kinds of customers might find various technologies attractive. A list of approximately 90 DER candidate sites was compiled and each site's DER characteristics and their willingness to volunteer information was assessed, producing detailed information on about 15 sites of which five sites were analyzed in depth. The five sites were not intended to provide a random sample, rather they were chosen to provide some diversity of business activity, geography, and technology. More importantly, they were chosen in the hope of finding examples of true business decisions made based on somewhat sophisticated analyses, and pilot or demonstration projects were avoided. Information on the benefits and pitfalls of implementing a DER system was also presented from an additional ten sites including agriculture, education, health care, airport, and manufacturing facilities.

  19. Buildings Energy Data Book - Datasets - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:EzfeedflagBiomassSustainable andBucoda, Washington: Energy(B2G) (Smart Grid Project)

  20. Annual Coal Consumption by Country - Datasets - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat Place:Alvan2809328°,AnfuNorth, Texas: EnergyAnnouncingAnnual

  1. ADAPTIVE MANAGEMENT AND PLANNING MODELS FOR CULTURAL RESOURCES IN OIL & GAS FIELDS IN NEW MEXICO AND WYOMING

    SciTech Connect (OSTI)

    Peggy Robinson

    2004-01-01T23:59:59.000Z

    This report contains a summary of activities of Gnomon, Inc. and five subcontractors that have taken place during the second six months (July 1, 2003-December 31, 2003) under the DOE-NETL cooperative agreement: ''Adaptive Management and Planning Models for Cultural Resources in Oil & Gas Fields in New Mexico and Wyoming'', DE-FC26-02NT15445. Although Gnomon and all five subcontractors completed tasks during these six months, most of the technical experimental work was conducted by the subcontractor, SRI Foundation (SRIF). SRIF created a sensitivity model for the Loco Hills area of southeastern New Mexico that rates areas as having a very good chance, a good chance, or a very poor chance of containing cultural resource sites. SRIF suggested that the results of the sensitivity model might influence possible changes in cultural resource management (CRM) practices in the Loco Hills area of southeastern New Mexico.

  2. Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets

    E-Print Network [OSTI]

    Grossman, Robert

    Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets Allison P Heath,1 Megan E McNerney,1,2 Kevin P White,1,3,4 Robert L Grossman1,3,5 1 Institute for Genomics and Systems petabyte-scale cloud- based computing platforms containing these data, along with tools and resources

  3. FTT:Power : A global model of the power sector with induced technological change and natural resource depletion

    E-Print Network [OSTI]

    Mercure, J -F

    2012-01-01T23:59:59.000Z

    This work introduces a model of Future Technology Transformations for the power sector (FTT:Power), a representation of global power systems based on market competition, induced technological change (ITC) and natural resource use and depletion. It is the first component of a family of sectoral bottom-up models of technology, designed for integration into the global macroeconometric model E3MG. ITC occurs as a result of technological learning produced by cumulative investment and leads to highly nonlinear, irreversible and path dependent technological transitions. The model uses a dynamic coupled set of logistic differential equations. As opposed to traditional bottom-up energy models based on systems optimisation, such differential equations offer an appropriate treatment of the times and structure of change involved in sectoral technology transformations, as well as a much reduced computational load. Resource use and depletion are represented by local cost-supply curves, which give rise to different regional...

  4. Water resources: sustainable water supply management and basin wide modelling Internationally it has been recognized that the most important challenge to ensuring sustainable

    E-Print Network [OSTI]

    Barthelat, Francois

    Water resources: sustainable water supply management and basin wide modelling Internationally it has been recognized that the most important challenge to ensuring sustainable water use is implementing integrated water resources management (IWRM). It provides the best framework for balancing

  5. dataset | OpenEI Community

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapersWindey Wind Home Rmckeel's picturecontest Homedataset Home

  6. datasets | OpenEI Community

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapersWindey Wind Home Rmckeel's picturecontest Homedataset

  7. About - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat 1AMEE Jump to: navigation, search40Georgia:SL JumpAREGAbout CKAN

  8. OpenEI Community - dataset

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRoseConcernsCompany Oil and GasOff

  9. OpenEI Community - datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRoseConcernsCompany Oil and GasOff

  10. U.S. Life Cycle Inventory Database Dataset Additions -Type / Category Dataset Name

    E-Print Network [OSTI]

    U.S. Life Cycle Inventory Database Dataset Additions - Type / Category Dataset Name Chemical Manufacturing Polylactide Biopolymer Resin, at plant Chemical Manufacturing Recycled Postconsumer HDPE Pellet) Chemical Manufacturing Soy biodiesel, production, at plant Soy oil, refined, at plant Soy-based polyol

  11. ADAPTIVE MANAGEMENT AND PLANNING MODELS FOR CULTURAL RESOURCES IN OIL & GAS FIELDS IN NEW MEXICO AND WYOMING

    SciTech Connect (OSTI)

    Peggy Robinson

    2005-07-01T23:59:59.000Z

    This report summarizes activities that have taken place in the last six (6) months (January 2005-June 2005) under the DOE-NETL cooperative agreement ''Adaptive Management and Planning Models for Cultural Resources in Oil and Gas Fields, New Mexico and Wyoming'' DE-FC26-02NT15445. This project examines the practices and results of cultural resource investigation and management in two different oil and gas producing areas of the United States: southeastern New Mexico and the Powder River Basin of Wyoming. The project evaluates how cultural resource investigations have been conducted in the past and considers how investigation and management could be pursued differently in the future. The study relies upon full database population for cultural resource inventories and resources and geomorphological studies. These are the basis for analysis of cultural resource occurrence, strategies for finding and evaluating cultural resources, and recommendations for future management practices. Activities can be summarized as occurring in either Wyoming or New Mexico. Gnomon as project lead, worked in both areas.

  12. Computer resources Computer resources

    E-Print Network [OSTI]

    Yang, Zong-Liang

    Computer resources 1 Computer resources available to the LEAD group Cédric David 30 September 2009 #12;Ouline · UT computer resources and services · JSG computer resources and services · LEAD computers· LEAD computers 2 #12;UT Austin services UT EID and Password 3 https://utdirect.utexas.edu #12;UT Austin

  13. Journal of Environmental Economics and Management 54 (2007) 6883 Steady-state growth in a Hotelling model of resource extraction

    E-Print Network [OSTI]

    Lin, C.-Y. Cynthia

    remained zero over a long period of time. We use data on 14 minerals from 1970 to 2004 to estimate is a steady-state consistent with the empirical observation that the growth rates of market prices have prices 1. Introduction The basic Hotelling model of nonrenewable resource extraction predicts

  14. Category:Datasets | 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model, click here. Category:Conceptual Model Add.png Add aTechniques page?

  15. Carrots and Sticks: A Comprehensive Business Model for the Successful Achievement of Energy Efficiency Resource Standards

    E-Print Network [OSTI]

    Satchwell, Andrew

    2013-01-01T23:59:59.000Z

    energy efficiency business model on utility earnings EES w/energy efficiency business model on utility ROE EES w/RPCSticks: A Comprehensive Business Model for the Successful

  16. Carrots and Sticks: A Comprehensive Business Model for the Successful Achievement of Energy Efficiency Resource Standards

    E-Print Network [OSTI]

    Satchwell, Andrew

    2013-01-01T23:59:59.000Z

    a comprehensive energy efficiency business model on utilitya comprehensive energy efficiency business model on utilityframework of the energy efficiency business model. The

  17. Research project on CO2 geological storage and groundwater resources: Large-scale hydrological evaluation and modeling of impact on groundwater systems

    E-Print Network [OSTI]

    Birkholzer, Jens; Zhou, Quanlin; Rutqvist, Jonny; Jordan, Preston; Zhang, K.; Tsang, Chin-Fu

    2008-01-01T23:59:59.000Z

    storage on shallow groundwater and pressure-controlled72 5.2. Modeling of Regional Groundwater2 Geological Storage and Groundwater Resources Large-Scale

  18. Development of the resource model for the Decision Aids for Tunneling (DAT)

    E-Print Network [OSTI]

    Min, Sangyoon, 1973-

    2008-01-01T23:59:59.000Z

    The Decision Aids for Tunneling (DAT) are a computer based method with which distributions of tunnel construction time and cost as well as required and produced resources can be estimated considering uncertainties in ...

  19. Modeling the resource consumption of Housing in New Orleans using System Dynamics

    E-Print Network [OSTI]

    Quinn, David James, Ph. D. Massachusetts Institute of Technology

    2008-01-01T23:59:59.000Z

    This work uses Systems Dynamics as a methodology to analyze the resource requirements of New Orleans as it recovers from Hurricane Katrina. It examines the behavior of the city as a system of stocks, flows and time delays ...

  20. PERSPECTIVE Biomass transformation webs provide a unified approach to consumer resource modelling

    E-Print Network [OSTI]

    Getz, Wayne M.

    ), Wallenberg Research Centre at Stellenbosch University, Marais Street, Stellenbosch 7600, South Africa modelling Wayne M. Getz* Department of Environmental Science, Policy and Management, University), energy flow models (Jorda´n 2000), bioenergetic models (Romanuk et al. 2009), ecological networks (Brose

  1. Graduate Opportunities in Earth Systems Modeling and Climate Impacts on Hydrology and Water Resources

    E-Print Network [OSTI]

    Graduate Opportunities in Earth Systems Modeling and Climate Impacts on Hydrology and Water research assistantships available in the general area of earth systems modeling and climate impacts

  2. ORNL/TM-2011/360 Reference Inflow Characterization for River Resource Reference Model:

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC)Integrated CodesTransparencyDOENurseResourcesThe Value News and Awards

  3. NREL EFM DATA: Disaggregated Residential Load Cost Data - Datasets...

    Open Energy Info (EERE)

    Open Data Catalog Dataset Activity Stream NREL EFM DATA: Disaggregated Residential Load Cost Data The following data-set is for a benchmark residential home for all TMY3 locations...

  4. Integration of Water Resource Models with Fayetteville Shale Decision Support and Information System

    SciTech Connect (OSTI)

    Cothren, Jackson; Thoma, Greg; DiLuzio, Mauro; Limp, Fred

    2013-06-30T23:59:59.000Z

    Significant issues can arise with the timing, location, and volume of surface water withdrawals associated with hydraulic fracturing of gas shale reservoirs as impacted watersheds may be sensitive, especially in drought years, during low flow periods, or during periods of the year when activities such as irrigation place additional demands on the surface supply of water. Significant energy production and associated water withdrawals may have a cumulative impact to watersheds over the short-term. Hence, hydraulic fracturing based on water withdrawal could potentially create shifts in the timing and magnitude of low or high flow events or change the magnitude of river flow at daily, monthly, seasonal, or yearly time scales. These changes in flow regimes can result in dramatically altered river systems. Currently little is known about the impact of fracturing on stream flow behavior. Within this context the objective of this study is to assess the impact of the hydraulic fracturing on the water balance of the Fayetteville Shale play area and examine the potential impacts of hydraulic fracturing on river flow regime at subbasin scale. This project addressed that need with four unique but integrated research and development efforts: 1) Evaluate the predictive reliability of the Soil and Water Assessment Tool (SWAT) model based at a variety of scales (Task/Section 3.5). The Soil and Water Assessment Tool (SWAT) model was used to simulate the across-scale water balance and the respective impact of hydraulic fracturing. A second hypothetical scenario was designed to assess the current and future impacts of water withdrawals for hydraulic fracturing on the flow regime and on the environmental flow components (EFCs) of the river. The shifting of these components, which present critical elements to water supply and water quality, could influence the ecological dynamics of river systems. For this purpose, we combined the use of SWAT model and Richter et al.’s (1996) methodology to assess the shifting and alteration of the flow regime within the river and streams of the study area. 2) Evaluate the effect of measurable land use changes related to gas development (well-pad placement, access road completion, etc.) on surface water flow in the region (Task/Section 3.7). Results showed that since the upsurge in shale-gas related activities in the Fayetteville Shale Play (between 2006 and 2010), shale-gas related infrastructure in the region have increase by 78%. This change in land-cover in comparison with other land-cover classes such as forest, urban, pasture, agricultural and water indicates the highest rate of change in any land-cover category for the study period. A Soil and Water Assessment Tool (SWAT) flow model of the Little Red River watershed simulated from 2000 to 2009 showed a 10% increase in storm water runoff. A forecast scenario based on the assumption that 2010 land-cover does not see any significant change over the forecast period (2010 to 2020) also showed a 10% increase in storm water runoff. Further analyses showed that this change in the stream-flow regime for the forecast period is attributable to the increase in land-cover as introduced by the shale-gas infrastructure. 3) Upgrade the Fayetteville Shale Information System to include information on watershed status. (Tasks/Sections 2.1 and 2.2). This development occurred early in the project period, and technological improvements in web-map API’s have made it possible to further improve the map. The current sites (http://lingo.cast.uark.edu) is available but is currently being upgraded to a more modern interface and robust mapping engine using funds outside this project. 4) Incorporate the methodologies developed in Tasks/Sections 3.5 and 3.7 into a Spatial Decision Support System for use by regulatory agencies and producers in the play. The resulting system is available at http://fayshale.cast.uark.edu and is under review the Arkansas Natural Resources Commission.

  5. Market Power in Nonrenewable Resource Markets: An Empirical Dynamic Model1

    E-Print Network [OSTI]

    Lin, C.-Y. Cynthia

    resources are pivotal for the development of the modern economy. From fossil fuels to various minerals to estimate an upper bound for the price elasticity of demand for those markets exhibiting market power. We find that the demand for copper, iron, lead, and zinc is relatively inelastic, while the demand for tin

  6. Applying the Alaska model in a Resource-Poor State: The Example of Vermont

    E-Print Network [OSTI]

    Vermont, University of

    (Chile), diamonds (Botswana), or even phosphates (Kiribati). In the United States, the state of New Mexico has three SWFs, the Land Grant Permanent Fund (mineral resources and surface land), Severance Tax Permanent Fund (minerals), and Tobacco Settlement Permanent Fund. Wyoming has a fund from coal, oil, natural

  7. Reliability Modeling and Simulation of Composite Power Systems with Renewable Energy Resources and Storage

    E-Print Network [OSTI]

    Kim, Hagkwen

    2013-05-24T23:59:59.000Z

    This research proposes an efficient reliability modeling and simulation methodology in power systems to include photovoltaic units, wind farms and storage. Energy losses by wake effect in a wind farm are incorporated. Using the wake model, wind...

  8. Reliability Modeling and Simulation of Composite Power Systems with Renewable Energy Resources and Storage 

    E-Print Network [OSTI]

    Kim, Hagkwen

    2013-05-24T23:59:59.000Z

    This research proposes an efficient reliability modeling and simulation methodology in power systems to include photovoltaic units, wind farms and storage. Energy losses by wake effect in a wind farm are incorporated. Using the wake model, wind...

  9. A Unifying Platform for Water Resources Management Using Physically-Based Model and Remote Sensing Data

    E-Print Network [OSTI]

    Shin, Yongchul

    2012-12-07T23:59:59.000Z

    of a soil system under various environmental conditions. One disadvantage of physical models is their inability to model the vertical and horizontal heterogeneity of hydraulic properties in a soil system at the regional scale. In order to overcome...

  10. Carrots and Sticks: A Comprehensive Business Model for the Successful Achievement of Energy Efficiency Resource Standards

    E-Print Network [OSTI]

    Satchwell, Andrew

    2013-01-01T23:59:59.000Z

    business model for energy efficiency Historically, utilities in Arizona have been allowed to recover prudently incurred EE program costs;costs. We presented a comprehensive business model to achieve aggressive energyCosts Net Benefits Figure 1 Flowchart for analyzing impacts of portfolio of energy efficiency programs on stakeholders Model Inputs Business-

  11. Adaptive Management and Planning Models for Cultural Resources in Oil and Gas Fields in New Mexico and Wyoming

    SciTech Connect (OSTI)

    Eckerle, William; Hall, Stephen

    2005-12-30T23:59:59.000Z

    In 2002, Gnomon, Inc., entered into a cooperative agreement with the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL) for a project entitled, Adaptive Management and Planning Models for Cultural Resources in Oil and Gas Fields in New Mexico and Wyoming (DE-FC26-02NT15445). This project, funded through DOE’s Preferred Upstream Management Practices grant program, examined cultural resource management practices in two major oil- and gas-producing areas, southeastern New Mexico and the Powder River Basin of Wyoming (Figure 1). The purpose of this project was to examine how cultural resources have been investigated and managed and to identify more effective management practices. The project also was designed to build information technology and modeling tools to meet both current and future management needs. The goals of the project were described in the original proposal as follows: Goal 1. Create seamless information systems for the project areas. Goal 2. Examine what we have learned from archaeological work in the southeastern New Mexico oil fields and whether there are better ways to gain additional knowledge more rapidly or at a lower cost. Goal 3. Provide useful sensitivity models for planning, management, and as guidelines for field investigations. Goal 4. Integrate management, investigation, and decision- making in a real-time electronic system. Gnomon, Inc., in partnership with the Wyoming State Historic Preservation Office (WYSHPO) and Western GeoArch Research, carried out the Wyoming portion of the project. SRI Foundation, in partnership with the New Mexico Historic Preservation Division (NMHPD), Statistical Research, Inc., and Red Rock Geological Enterprises, completed the New Mexico component of the project. Both the New Mexico and Wyoming summaries concluded with recommendations how cultural resource management (CRM) processes might be modified based on the findings of this research.

  12. Production of BaBar Skimmed Analysis Datasets Using the Grid

    SciTech Connect (OSTI)

    Brew, C.A.J.; /Rutherford; Wilson, F.F.; /Rutherford; Castelli, G.; /Rutherford; Adye, T.; /Rutherford; Roethel, W.; /Rutherford; Luppi, E.; /INFN, Ferrara; Andreotti, D.; /INFN, Ferrara; Smith, D.; /SLAC; Khan, A.; /Brunel U.; Barrett, M.; /Brunel U.; Barlow, R.; /Manchester U.; Bailey, D.; /Manchester U.

    2011-11-10T23:59:59.000Z

    The BABAR Collaboration, based at Stanford Linear Accelerator Center (SLAC), Stanford, US, has been performing physics reconstruction, simulation studies and data analysis for 8 years using a number of compute farms around the world. Recent developments in Grid technologies could provide a way to manage the distributed resources in a single coherent structure. We describe enhancements to the BABAR experiment's distributed skimmed dataset production system to make use of European Grid resources and present the results with regard to BABAR's latest cycle of skimmed dataset production. We compare the benefits of a local and Grid-based systems, the ease with which the system is managed and the challenges of integrating the Grid with legacy software. We compare job success rates and manageability issues between Grid and non-Grid production.

  13. WATER RESOURCES ,'JEBRASKA WATER RESOURCES RESEARCH INSTITUTE

    E-Print Network [OSTI]

    Nebraska-Lincoln, University of

    of transportation, urban blight, agricultural practices, land use, etc. Water resources problems often result fromWATER RESOURCES ,'JEBRASKA WATER RESOURCES RESEARCH INSTITUTE 212 AGRICULTURAL ENGINEERING BUILDING formulate sound policy without a good deal of knowledge not presently available. Without adequate models

  14. Application of a dynamic linear programming model for optimum use of range resources over time

    E-Print Network [OSTI]

    Sharp, Wayne Winston

    1964-01-01T23:59:59.000Z

    ~ . ~ ~ ~ ~ ? ~ ~ ~ ~ ~ ~ ~ ~ Scope and Importance of Range Resource Use . . . . . . . . e. . . ? " . . Present Status of the Problem, Objectives of the Study 1 2 4 6 11 II. DESCRIPTION OF THE STUDY AREA, Size and Location of the Area, Major Soils and Types of Enterprises... ~ Cattle Transfer Equations , ee ~ ~ ~ ~ ~ ~ 46 46 48 52 54 55 58 6'I 62 66 66 68 7'1 75 75 76 76 77 77 The Function to be Maximized The Role of Management. Program I Program II Program III 80 80 82 82 83 V. RESULTS. Optimal...

  15. A Resource Conceptual Model for the Ngatamariki Geothermal Field Based on

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat 1 WindtheEnergy InformationOf TheLtdJalisco, Mexico |Recent

  16. Toward The Development Of Occurrence Models For Geothermal Resources In The

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-f <MaintainedInformationThePty LtdOpenHabitatandWindTorayArea,Western

  17. Renewable Diesel from Algal Lipids: An Integrated Baseline for Cost, Emissions, and Resource Potential from a Harmonized Model

    SciTech Connect (OSTI)

    Davis, R.; Fishman, D.; Frank, E. D.; Wigmosta, M. S.; Aden, A.; Coleman, A. M.; Pienkos, P. T.; Skaggs, R. J.; Venteris, E. R.; Wang, M. Q.

    2012-06-01T23:59:59.000Z

    The U.S. Department of Energy's Biomass Program has begun an initiative to obtain consistent quantitative metrics for algal biofuel production to establish an 'integrated baseline' by harmonizing and combining the Program's national resource assessment (RA), techno-economic analysis (TEA), and life-cycle analysis (LCA) models. The baseline attempts to represent a plausible near-term production scenario with freshwater microalgae growth, extraction of lipids, and conversion via hydroprocessing to produce a renewable diesel (RD) blendstock. Differences in the prior TEA and LCA models were reconciled (harmonized) and the RA model was used to prioritize and select the most favorable consortium of sites that supports production of 5 billion gallons per year of RD. Aligning the TEA and LCA models produced slightly higher costs and emissions compared to the pre-harmonized results. However, after then applying the productivities predicted by the RA model (13 g/m2/d on annual average vs. 25 g/m2/d in the original models), the integrated baseline resulted in markedly higher costs and emissions. The relationship between performance (cost and emissions) and either productivity or lipid fraction was found to be non-linear, and important implications on the TEA and LCA results were observed after introducing seasonal variability from the RA model. Increasing productivity and lipid fraction alone was insufficient to achieve cost and emission targets; however, combined with lower energy, less expensive alternative technology scenarios, emissions and costs were substantially reduced.

  18. A benchmark suite with virtualized reality models for supporting tracking evaluation and data set generation

    E-Print Network [OSTI]

    Boyer, Edmond

    ) Benchmark resources Sharing of benchmarking results A : Datasets GenerateA benchmark suite with virtualized reality models for supporting tracking evaluation and data set laurence.nigay@imag.fr Takeshi Kurata AIST, Japan t.kurata@aist.go.jp Abstract We describe a benchmark

  19. Sensing the Air We Breathe the OpenSense Zurich Dataset Jason Jingshi Li1

    E-Print Network [OSTI]

    Dalang, Robert C.

    pollution is a signifi- cant challenge for the sustainability of our environment. We quickly survey the air pollution modeling problem, introduce a new dataset of mobile air quality measurements in Zurich, and discuss the challenges of making sense of these data. Introduction Urban outdoor air pollution currently

  20. Steady-state growth in a Hotelling model of resource extraction

    E-Print Network [OSTI]

    Lin, C.-Y. Cynthia; Wagner, Gernot

    2007-01-01T23:59:59.000Z

    demand in the world oil market. Working paper. University ofapproach to the world oil market. The Journal of PoliticalA Cournot model of the oil market. Economica, 51 (203), 235-

  1. Journal of Theoretical Biology 246 (2007) 278289 A model of flexible uptake of two essential resources

    E-Print Network [OSTI]

    2007-01-01T23:59:59.000Z

    based on a multinutrient extension of the Droop model to allow a trade-off between ability to acquire variable, depending on growth rate and nutrient supply ratios (Droop, 1974; Sterner and Elser, 2002

  2. A general model of resource production and exchange in systems of interdependent specialists.

    SciTech Connect (OSTI)

    Conrad, Stephen Hamilton; Finley, Patrick D.; Beyeler, Walter Eugene; Brown, Theresa Jean; Glass, Robert John, Jr.; Breen, Peter; Kuypers, Marshall; Norton, Matthew David; Quach, Tu-Thach; Antognoli, Matthew; Mitchell, Michael David

    2011-11-01T23:59:59.000Z

    Infrastructures are networks of dynamically interacting systems designed for the flow of information, energy, and materials. Under certain circumstances, disturbances from a targeted attack or natural disasters can cause cascading failures within and between infrastructures that result in significant service losses and long recovery times. Reliable interdependency models that can capture such multi-network cascading do not exist. The research reported here has extended Sandia's infrastructure modeling capabilities by: (1) addressing interdependencies among networks, (2) incorporating adaptive behavioral models into the network models, and (3) providing mechanisms for evaluating vulnerability to targeted attack and unforeseen disruptions. We have applied these capabilities to evaluate the robustness of various systems, and to identify factors that control the scale and duration of disruption. This capability lays the foundation for developing advanced system security solutions that encompass both external shocks and internal dynamics.

  3. Renewable Resources: a national catalog of model projects. Volume 4. Western Solar Utilization Network Region

    SciTech Connect (OSTI)

    None

    1980-07-01T23:59:59.000Z

    This compilation of diverse conservation and renewable energy projects across the United States was prepared through the enthusiastic participation of solar and alternate energy groups from every state and region. Compiled and edited by the Center for Renewable Resources, these projects reflect many levels of innovation and technical expertise. In many cases, a critique analysis is presented of how projects performed and of the institutional conditions associated with their success or failure. Some 2000 projects are included in this compilation; most have worked, some have not. Information about all is presented to aid learning from these experiences. The four volumes in this set are arranged in state sections by geographic region, coinciding with the four Regional Solar Energy Centers. The table of contents is organized by project category so that maximum cross-referencing may be obtained. This volume includes information on the Western Solar Utilization Network Region. (WHK)

  4. Renewable Resources: a national catalog of model projects. Volume 3. Southern Solar Energy Center Region

    SciTech Connect (OSTI)

    None

    1980-07-01T23:59:59.000Z

    This compilation of diverse conservation and renewable energy projects across the United States was prepared through the enthusiastic participation of solar and alternate energy groups from every state and region. Compiled and edited by the Center for Renewable Resources, these projects reflect many levels of innovation and technical expertise. In many cases, a critique analysis is presented of how projects performed and of the institutional conditions associated with their success or failure. Some 2000 projects are included in this compilation; most have worked, some have not. Information about all is presented to aid learning from these experiences. The four volumes in this set are arranged in state sections by geographic region, coinciding with the four Regional Solar Energy Centers. The table of contents is organized by project category so that maximum cross-referencing may be obtained. This volume includes information on the Southern Solar Energy Center Region. (WHK)

  5. Renewable Resources: a national catalog of model projects. Volume 1. Northeast Solar Energy Center Region

    SciTech Connect (OSTI)

    None

    1980-07-01T23:59:59.000Z

    This compilation of diverse conservation and renewable energy projects across the United States was prepared through the enthusiastic participation of solar and alternate energy groups from every state and region. Compiled and edited by the Center for Renewable Resources, these projects reflect many levels of innovation and technical expertise. In many cases, a critique analysis is presented of how projects performed and of the institutional conditions associated with their success or failure. Some 2000 projects are included in this compilation; most have worked, some have not. Information about all is presented to aid learning from these experiences. The four volumes in this set are arranged in state sections by geographic region, coinciding with the four Regional Solar Energy Centers. The table of contents is organized by project category so that maximum cross-referencing may be obtained. This volume includes information on the Northeast Solar Energy Center Region. (WHK).

  6. Energy Efficient Radio Resource

    E-Print Network [OSTI]

    Yanikomeroglu, Halim

    Energy Efficient Radio Resource Management in a Coordinated Multi-Cell Distributed Antenna System Omer HALILOGLU Introduction System Model Performance Evaluation Conclusion References Energy Efficient Hacettepe University 5 September 2014 Omer HALILOGLU (Hacettepe University) Energy Efficient Radio Resource

  7. Solar Resource Assessment

    SciTech Connect (OSTI)

    Renne, D.; George, R.; Wilcox, S.; Stoffel, T.; Myers, D.; Heimiller, D.

    2008-02-01T23:59:59.000Z

    This report covers the solar resource assessment aspects of the Renewable Systems Interconnection study. The status of solar resource assessment in the United States is described, and summaries of the availability of modeled data sets are provided.

  8. Teacher Resources

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

    Teacher Resources For Teachers Teachers Visit the Museum We Visit You Teacher Resources Home Schoolers Plan Your School Visit invisible utility element Teacher Resources Scavenger...

  9. SMART: A Stochastic Multiscale Model for the Analysis of Energy Resources, Technology and Policy

    E-Print Network [OSTI]

    Powell, Warren B.

    -use strategies (level of demand, demand response). A major component will be renewable energy that depend from wind, demands, prices and rainfall. We also wish to model long-term investment decisions demonstrate the methodology using both spatially aggregate and disaggregate representations of energy supply

  10. Evaluating socio-economic state of a country analyzing airtime credit and mobile phone datasets

    E-Print Network [OSTI]

    Gutierrez, Thoralf; Blondel, Vincent D

    2013-01-01T23:59:59.000Z

    Reliable statistical information is important to make political decisions on a sound basis and to help measure the impact of policies. Unfortunately, statistics offices in developing countries have scarce resources and statistical censuses are therefore conducted sporadically. Based on mobile phone communications and history of airtime credit purchases, we estimate the relative income of individuals, the diversity and inequality of income, and an indicator for socioeconomic segregation for fine-grained regions of an African country. Our study shows how to use mobile phone datasets as a starting point to understand the socio-economic state of a country, which can be especially useful in countries with few resources to conduct large surveys.

  11. WATER RESOURCES RESEARCH, VOL. 29, NO. 11, PAGES 3727-3740, NOVEMBER 1993 Modeling of Multiphase Transport of Multicomponent Organic Contaminants

    E-Print Network [OSTI]

    Patzek, Tadeusz W.

    WATER RESOURCES RESEARCH, VOL. 29, NO. 11, PAGES 3727-3740, NOVEMBER 1993 Modeling of Multiphase, Berkeley A numerical compositionalsimulator (Multiphase Multicomponent Nonisothermal Organics Trans- portSimulator(M2NOTS))hasbeendevelopedformodelingtransient,three-dimensional,noniso- thermal, and multiphase

  12. Feedstock Production Datasets from the Bioenergy Knowledge Discovery Framework

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. [copied from https://www.bioenergykdf.net/content/about] Holdings include datasets, models, and maps and the collections are growing due to both DOE contributions and data uploads from individuals.

  13. Biofuel Distribution Datasets from the Bioenergy Knowledge Discovery Framework

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. [copied from https://www.bioenergykdf.net/content/about] Holdings include datasets, models, and maps and the collections are growing due to both DOE contributions and individuals' data uploads.

  14. Biofuel Production Datasets from DOE's Bioenergy Knowledge Discovery Framework (KDF)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. [copied from https://www.bioenergykdf.net/content/about]

    Holdings include datasets, models, and maps and the collections arel growing due to both DOE contributions and data uploads from individuals.

  15. Feedstock Logistics Datasets from DOE's Bioenergy Knowledge Discovery Framework (KDF)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    The Bioenergy Knowledge Discovery Framework invites users to discover the power of bioenergy through an interface that provides extensive access to research data and literature, GIS mapping tools, and collaborative networks. The Bioenergy KDF supports efforts to develop a robust and sustainable bioenergy industry. The KDF facilitates informed decision making by providing a means to synthesize, analyze, and visualize vast amounts of information in a relevant and succinct manner. It harnesses Web 2.0 and social networking technologies to build a collective knowledge system that can better examine the economic and environmental impacts of development options for biomass feedstock production, biorefineries, and related infrastructure. Holdings include datasets, models, and maps. [from https://www.bioenergykdf.net/content/about

  16. World Net Nuclear Electric Power Generation, 1980-2007 - Datasets...

    Open Energy Info (EERE)

    U.S. Energy Information ... World Net Nuclear Electric ... Dataset Activity Stream World Net Nuclear Electric Power Generation, 1980-2007 International data showing world net...

  17. Framework for Interactive Parallel Dataset Analysis on the Grid

    SciTech Connect (OSTI)

    Alexander, David A.; Ananthan, Balamurali; /Tech-X Corp.; Johnson, Tony; Serbo, Victor; /SLAC

    2007-01-10T23:59:59.000Z

    We present a framework for use at a typical Grid site to facilitate custom interactive parallel dataset analysis targeting terabyte-scale datasets of the type typically produced by large multi-institutional science experiments. We summarize the needs for interactive analysis and show a prototype solution that satisfies those needs. The solution consists of desktop client tool and a set of Web Services that allow scientists to sign onto a Grid site, compose analysis script code to carry out physics analysis on datasets, distribute the code and datasets to worker nodes, collect the results back to the client, and to construct professional-quality visualizations of the results.

  18. COMPUTATIONAL RESOURCES FOR BIOFUEL FEEDSTOCK SPECIES

    SciTech Connect (OSTI)

    Buell, Carol Robin [Michigan State University; Childs, Kevin L [Michigan State University

    2013-05-07T23:59:59.000Z

    While current production of ethanol as a biofuel relies on starch and sugar inputs, it is anticipated that sustainable production of ethanol for biofuel use will utilize lignocellulosic feedstocks. Candidate plant species to be used for lignocellulosic ethanol production include a large number of species within the Grass, Pine and Birch plant families. For these biofuel feedstock species, there are variable amounts of genome sequence resources available, ranging from complete genome sequences (e.g. sorghum, poplar) to transcriptome data sets (e.g. switchgrass, pine). These data sets are not only dispersed in location but also disparate in content. It will be essential to leverage and improve these genomic data sets for the improvement of biofuel feedstock production. The objectives of this project were to provide computational tools and resources for data-mining genome sequence/annotation and large-scale functional genomic datasets available for biofuel feedstock species. We have created a Bioenergy Feedstock Genomics Resource that provides a web-based portal or �clearing house� for genomic data for plant species relevant to biofuel feedstock production. Sequence data from a total of 54 plant species are included in the Bioenergy Feedstock Genomics Resource including model plant species that permit leveraging of knowledge across taxa to biofuel feedstock species.We have generated additional computational analyses of these data, including uniform annotation, to facilitate genomic approaches to improved biofuel feedstock production. These data have been centralized in the publicly available Bioenergy Feedstock Genomics Resource (http://bfgr.plantbiology.msu.edu/).

  19. Projecting Continental U.S. Water Stress Based on Global Datasets

    SciTech Connect (OSTI)

    Parish, Esther S [ORNL; Kodra, Evan [Northeastern University; Steinhaeuser, Karsten [University of Minnesota; Ganguly, Auroop R [Northeastern University

    2012-01-01T23:59:59.000Z

    Human populations may be adversely impacted by water stress, a situation which is commonly defined as a per capita water availability of less than 1700 cubic meters of freshwater per person per year. Water stress may result from either overuse of available freshwater resources or a reduction in the amount of available water due to decreases in rainfall and stored water supplies. Analyzing the interrelationship between human populations and water availability is complicated by the uncertainties associated with climate change projections and population projections. We have developed a simple methodology to integrate disparate climate and population data sources and develop first-order per capita water availability projections at the global scale. Simulations from the coupled land-ocean-atmosphere Community Climate System Model version 3 (CCSM3) forced with a range of hypothetical greenhouse gas emissions scenarios have been used to project grid-based changes in precipitation minus evapotranspiration as proxies for changes in runoff, or fresh water supply. Population growth changes, according to Intergovernmental Panel on Climate Change (IPCC) storylines, have been used as proxies for changes in fresh water demand by 2025, 2050 and 2100. These freshwater supply and demand projections have then been combined to yield estimates of per capita water availability aggregated by U.S. watershed. Results suggest that important insights might be extracted from the use of the process developed here, including the identification of potentially vulnerable areas in need of more detailed analysis. This high-level analysis also illustrates the relative importance of population growth versus climate change in in altering future freshwater supplies. However, these are only exemplary insights and, as such, could be considered hypotheses that should be rigorously tested with multiple climate models, multiple observational climate datasets, and more comprehensive population growth projections.

  20. One-way coupling of an integrated assessment model and a water resources model: evaluation and implications of future changes over the US Midwest

    SciTech Connect (OSTI)

    Voisin, Nathalie; Liu, Lu; Hejazi, Mohamad I.; Tesfa, Teklu K.; Li, Hongyi; Huang, Maoyi; Liu, Ying; Leung, Lai-Yung R.

    2013-11-18T23:59:59.000Z

    An integrated model is being developed to advance our understanding of the interactions between human activities, terrestrial system and water cycle, and how system interactions will be affected by a changing climate at the regional scale. As a first step towards that goal, a global integrated assessment model including a waterdemand model is coupled offline with a land surface hydrology – routing – water resources management model. A spatial and temporal disaggregation approach is developed to project the annual regional water demand simulations into a daily time step and subbasin representation. The model demonstrated reasonable ability to represent the historical flow regulation and water supply over the Midwest (Missouri, Upper Mississippi and Ohio). Implications for the future flow regulation, water supply and supply deficit are investigated using a climate change projection with the B1 emission scenario which affects both natural flow and water demand. Over the Midwest, changes in flow regulation are mostly driven by the change in natural flow due to the limited storage capacity over the Ohio and Upper Mississippi river basins. The changes in flow and demand have a combined effect on the Missouri Summer regulated flow. The supply deficit tends to be driven by the change in flow over the region. Spatial analysis demonstrates the relationship between the supply deficit and the change in demand over urban areas not along a main river or with limited storage, and over areas upstream of groundwater dependent fields with therefore overestimated demand.

  1. Improved Offshore Wind Resource Assessment in Global Climate Stabilization Scenarios

    SciTech Connect (OSTI)

    Arent, D.; Sullivan, P.; Heimiller, D.; Lopez, A.; Eurek, K.; Badger, J.; Jorgensen, H. E.; Kelly, M.; Clarke, L.; Luckow, P.

    2012-10-01T23:59:59.000Z

    This paper introduces a technique for digesting geospatial wind-speed data into areally defined -- country-level, in this case -- wind resource supply curves. We combined gridded wind-vector data for ocean areas with bathymetry maps, country exclusive economic zones, wind turbine power curves, and other datasets and relevant parameters to build supply curves that estimate a country's offshore wind resource defined by resource quality, depth, and distance-from-shore. We include a single set of supply curves -- for a particular assumption set -- and study some implications of including it in a global energy model. We also discuss the importance of downscaling gridded wind vector data to capturing the full resource potential, especially over land areas with complex terrain. This paper includes motivation and background for a statistical downscaling methodology to account for terrain effects with a low computational burden. Finally, we use this forum to sketch a framework for building synthetic electric networks to estimate transmission accessibility of renewable resource sites in remote areas.

  2. The Development of a Coordinated Database for Water Resources and Flow Model in the Paso Del Norte Watershed

    E-Print Network [OSTI]

    Sheng, Zhuping; Tillery, Sue; King, Phillip J.; Creel, Bobby; Brown, Christopher; Michelsen, Ari; Srinivasan, Raghavan; Granados, Alfredo

    &M University Agricultural Research Center at El Paso; Raghavan Srinivasan, Spatial Sciences Laboratory, Texas A&M University; and Alfredo Granados Universidad Autónoma de Ciudad Juárez, Mexico Texas Water Resources Institute Texas A... University New Mexico Water Resources Research Institute Texas A&M University Texas Agriculture Experiment Station Universidad Autónoma de Ciudad Juárez Centro de Información Geográfica Texas Water Resources Institute THE DEVELOPMENT...

  3. PoroTomo Subtask 3.4 Analysis of existing InSAR data - Datasets...

    Open Energy Info (EERE)

    Relationship Dataset Dataset extent Map data OpenStreetMap contributors Tiles by MapQuest License Creative Commons Attribution 4.0 Open Data Author University of...

  4. A Large-Scale, High-Resolution Hydrological Model Parameter Data Set for Climate Change Impact Assessment for the Conterminous US

    SciTech Connect (OSTI)

    Oubeidillah, Abdoul A [ORNL] [ORNL; Kao, Shih-Chieh [ORNL] [ORNL; Ashfaq, Moetasim [ORNL] [ORNL; Naz, Bibi S [ORNL] [ORNL; Tootle, Glenn [University of Alabama, Tuscaloosa] [University of Alabama, Tuscaloosa

    2014-01-01T23:59:59.000Z

    To extend geographical coverage, refine spatial resolution, and improve modeling efficiency, a computation- and data-intensive effort was conducted to organize a comprehensive hydrologic dataset with post-calibrated model parameters for hydro-climate impact assessment. Several key inputs for hydrologic simulation including meteorologic forcings, soil, land class, vegetation, and elevation were collected from multiple best-available data sources and organized for 2107 hydrologic subbasins (8-digit hydrologic units, HUC8s) in the conterminous United States at refined 1/24 (~4 km) spatial resolution. Using high-performance computing for intensive model calibration, a high-resolution parameter dataset was prepared for the macro-scale Variable Infiltration Capacity (VIC) hydrologic model. The VIC simulation was driven by DAYMET daily meteorological forcing and was calibrated against USGS WaterWatch monthly runoff observations for each HUC8. The results showed that this new parameter dataset may help reasonably simulate runoff at most US HUC8 subbasins. Based on this exhaustive calibration effort, it is now possible to accurately estimate the resources required for further model improvement across the entire conterminous United States. We anticipate that through this hydrologic parameter dataset, the repeated effort of fundamental data processing can be lessened, so that research efforts can emphasize the more challenging task of assessing climate change impacts. The pre-organized model parameter dataset will be provided to interested parties to support further hydro-climate impact assessment.

  5. A 20-Year Dataset of Downwelling Longwave Flux at the Arctic Surface from TOVS Satellite 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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del(ANL-IN-03-032) -Less isNFebruaryOctober 2, AlgeriaQ1 Q2 Q3 Ut NOTICE20-Year Dataset

  6. NREL EFM DATA: Disaggregated Residential Load Cost Data - Datasets...

    Open Energy Info (EERE)

    NREL EFM DATA: Disaggregated Residential Load Cost Data The following data-set is for a benchmark residential home for all TMY3 locations across all utilities in the US. The data...

  7. State Energy Data System (SEDS) Complete Dataset through 2009...

    Open Energy Info (EERE)

    State Energy Data System (SEDS) Complete Dataset through 2009 The State Energy Data System (SEDS) is compiled by the U.S. Energy Information Administration's (EIA); it is a...

  8. Determining Mountaintop Mining Locations in West Virginia Using Elevation Datasets

    E-Print Network [OSTI]

    Rowland, Danny

    2009-11-18T23:59:59.000Z

    Determining Mountaintop Mining Locations in West Virginia Using Elevation Datasets Danny Rowland Haskell Indian Nations University Image from: http://www.colorado.edu/geography/cartpro/cartography2/spring2006/syphers.../projects/westvirginia/whatis.htm Image from: http://washingtonindependent.com/49008/congress-takes-on-mountaintop-mining Mountaintop Mining Operation 2 Elevation datasets: NED & SRTM West Virginia NED SRTM Elevation Change Over ~30 Year Period 20021970’s SRTM Subtracted from...

  9. Final report for %22High performance computing for advanced national electric power grid modeling and integration of solar generation resources%22, LDRD Project No. 149016.

    SciTech Connect (OSTI)

    Reno, Matthew J.; Riehm, Andrew Charles; Hoekstra, Robert John; Munoz-Ramirez, Karina; Stamp, Jason Edwin; Phillips, Laurence R.; Adams, Brian M.; Russo, Thomas V.; Oldfield, Ron A.; McLendon, William Clarence, III; Nelson, Jeffrey Scott; Hansen, Clifford W.; Richardson, Bryan T.; Stein, Joshua S.; Schoenwald, David Alan; Wolfenbarger, Paul R.

    2011-02-01T23:59:59.000Z

    Design and operation of the electric power grid (EPG) relies heavily on computational models. High-fidelity, full-order models are used to study transient phenomena on only a small part of the network. Reduced-order dynamic and power flow models are used when analysis involving thousands of nodes are required due to the computational demands when simulating large numbers of nodes. The level of complexity of the future EPG will dramatically increase due to large-scale deployment of variable renewable generation, active load and distributed generation resources, adaptive protection and control systems, and price-responsive demand. High-fidelity modeling of this future grid will require significant advances in coupled, multi-scale tools and their use on high performance computing (HPC) platforms. This LDRD report demonstrates SNL's capability to apply HPC resources to these 3 tasks: (1) High-fidelity, large-scale modeling of power system dynamics; (2) Statistical assessment of grid security via Monte-Carlo simulations of cyber attacks; and (3) Development of models to predict variability of solar resources at locations where little or no ground-based measurements are available.

  10. Integrative analysis of transcriptomic and proteomic data of Shewanella oneidensis: missing value imputation using temporal datasets

    SciTech Connect (OSTI)

    Torres-García, Wandaliz [Arizona State University; Brown, Steven D [ORNL; Johnson, Roger [Arizona State University; Zhang, Weiwen [Arizona State University; Runger, George [Arizona State University; Meldrum, Deirdre [Arizona State University

    2011-01-01T23:59:59.000Z

    Despite significant improvements in recent years, proteomic datasets currently available still suffer large number of missing values. Integrative analyses based upon incomplete proteomic and transcriptomic da-tasets could seriously bias the biological interpretation. In this study, we applied a non-linear data-driven stochastic gradient boosted trees (GBT) model to impute missing proteomic values for proteins experi-mentally undetected, using a temporal transcriptomic and proteomic dataset of Shewanella oneidensis. In this dataset, genes expression was measured after the cells were exposed to 1 mM potassium chromate for 5-, 30-, 60-, and 90-min, while protein abundance was measured only for 45- and 90-min samples. With the goal of elucidating the relationship between temporal gene expression and protein abundance data, and then using it to impute missing proteomic values for samples of 45-min (which does not have cognate transcriptomic data) and 90-min, we initially used nonlinear Smoothing Splines Curve Fitting (SSCF) to identify temporal relationships among transcriptomic data at different time points and then imputed missing gene expression measurements for the sample at 45-min. After the imputation was validated by biological constrains (i.e. operons), we used a data-driven Gradient Boosted Trees (GBT) model to uncover possible non-linear relationships between temporal transcriptomic and proteomic data, and to impute protein abundance for the proteins experimentally undetected in the 45- and 90-min sam-ples, based on relevant predictors such as temporal mRNA gene expression data, cellular roles, molecular weight, sequence length, protein length, guanine-cytosine (GC) content and triple codon counts. The imputed protein values were validated using biological constraints such as operon, regulon and pathway information. Finally, we demonstrated that such missing value imputation improved characterization of the temporal response of S. oneidensis to chromate.

  11. Index of /datasets/files/39

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are8COaBulkTransmissionSitingProcess.pdfGetecGtel JumpCounty,Jump to:Unconventional GasBusinessesMinnesota:

  12. Index of /datasets/files/41

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are8COaBulkTransmissionSitingProcess.pdfGetecGtel JumpCounty,Jump to:Unconventional

  13. Widget:DatasetsRedirect | 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTri GlobalJump to:WestwoodCreatePage Jump to: navigation, search This

  14. Index of /datasets/files/39/pub

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, search OpenEIHesperia,IDGWP WindSatelliteInSAR Jump to:Efficiencypub [ICO] Name

  15. Index of /datasets/files/41/pub

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, search OpenEIHesperia,IDGWP WindSatelliteInSAR Jump to:Efficiencypub [ICO] Name/

  16. Index of /datasets/files/961/pub

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are8COaBulkTransmissionSitingProcess.pdfGetecGtel JumpCounty,Jump7 Varnish cache server DirectoryARCHIVE/ 02-Jul-2013

  17. Category:Datasets | 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof EnergyInnovation inOpen EnergyCallawayCaparaAcademic InstitutionsEdit History

  18. NREL: Transmission Grid Integration - Wind Integration Datasets

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's Possible for Renewable Energy: Grid IntegrationReportTransmission Planning andStudy PhaseWind

  19. Template:DatasetValue | 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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro Industries PvtStratosolar Jump to:HoldingsTechint Spasource History ViewDatabusNav

  20. Upload Data - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga, IndianaTurtleCooperativeCROSS-VALIDATION OF SWERA's

  1. Additional Resources

    Broader source: Energy.gov [DOE]

    The following resources are focused on Federal new construction and major renovation projects, sustainable construction, and the role of renewable energy technologies in such facilities. These...

  2. Sandia National Laboratories: Wave Energy Resource Characterization...

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

    eECEnergyComputational Modeling & SimulationWave Energy Resource Characterization at US Test Sites Wave Energy Resource Characterization at US Test Sites Sandia Report Presents...

  3. DECOMPOSITION OF MULTIVARIATE DATASETS WITH STRUCTURE/ORDERING

    E-Print Network [OSTI]

    analysis. However, contrary to Fourier decomposition these new variables are located in frequency as well as location (space, time, wavelength etc). 1 Introduction The maximum autocorrelation factor (MAF) analysisDECOMPOSITION OF MULTIVARIATE DATASETS WITH STRUCTURE/ORDERING OF OBSERVATIONS OR VARIABLES USING

  4. Eastern Renewable Generation Integration Study Solar Dataset (Presentation)

    SciTech Connect (OSTI)

    Hummon, M.

    2014-04-01T23:59:59.000Z

    The National Renewable Energy Laboratory produced solar power production data for the Eastern Renewable Generation Integration Study (ERGIS) including "real time" 5-minute interval data, "four hour ahead forecast" 60-minute interval data, and "day-ahead forecast" 60-minute interval data for the year 2006. This presentation provides a brief overview of the three solar power datasets.

  5. A Multivariate Probabilistic Method for Comparing Two Clinical Datasets

    E-Print Network [OSTI]

    Hauskrecht, Milos

    A Multivariate Probabilistic Method for Comparing Two Clinical Datasets Yuriy Sverchkov yus24@pitt a concise and math- ematically grounded description of multivariate differences between a pair of clinical (ICUs), or within the same ICU during different periods, may show systematically different outcomes

  6. Distributed energy resources at naval base ventura county building 1512

    E-Print Network [OSTI]

    Bailey, Owen C.; Marnay, Chris

    2004-01-01T23:59:59.000Z

    by a DER system. Distributed Energy Resources at Naval BaseFebruary 2003. “Distributed Energy Resources in Practice: A2004. “Distributed Energy Resources Customer Adoption Model

  7. Distributed energy resources at naval base ventura county building 1512

    E-Print Network [OSTI]

    Bailey, Owen C.; Marnay, Chris

    2004-01-01T23:59:59.000Z

    system. Distributed Energy Resources at Naval Base Ventura2003. “Distributed Energy Resources in Practice: A Case2004. “Distributed Energy Resources Customer Adoption Model

  8. Epistemological resources 1 Running Head: EPISTEMOLOGICAL RESOURCES

    E-Print Network [OSTI]

    Elby, Andy

    Epistemological resources 1 Running Head: EPISTEMOLOGICAL RESOURCES Epistemological resources University Maryland, College Park Trisha Kagey Montgomery County Public Schools #12;Epistemological resources are better understood as made up of finer-grained cognitive resources whose activation depends sensitively

  9. Resource Program

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's PossibleRadiation Protection TechnicalResonant Soft X-Ray Scattering of0 Resource Program

  10. Organic aerosol components observed in Northern Hemispheric datasets from Aerosol Mass Spectrometry

    E-Print Network [OSTI]

    Kroll, Jesse

    In this study we compile and present results from the factor analysis of 43 Aerosol Mass Spectrometer (AMS) datasets (27 of the datasets are reanalyzed in this work). The components from all sites, when taken together, ...

  11. On-line supplement to: SMART: A Stochastic Multi-scale Model for the Analysis of Energy Resources, Tech-

    E-Print Network [OSTI]

    Powell, Warren B.

    turbine, photovoltaic or hydro-power. Age is typically in units of years. Location can be expressed programming model, and a stochastic optimization problem. System state variables We divide the state variable

  12. Renewable Resources: a national catalog of model projects. Volume 2. Mid-American Solar Energy Complex Region

    SciTech Connect (OSTI)

    None

    1980-07-01T23:59:59.000Z

    This compilation of diverse conservation and renewable energy projects across the United States was prepared through the enthusiastic participation of solar and alternate energy groups from every state and region. Compiled and edited by the Center for Renewable Resources, these projects reflect many levels of innovation and technical expertise. In many cases, a critique analysis is presented of how projects performed and of the institutional conditions associated with their success or failure. Some 2000 projects are included in this compilation; most have worked, some have not. Information about all is presented to aid learning from these experiences. The four volumes in this set are arranged in state sections by geographic region, coinciding with the four Regional Solar Energy Centers. The table of contents is organized by project category so that maximum cross-referencing may be obtained. This volume includes information on the Mid-American Solar Energy Complex Region. (WHK)

  13. DEVise: Integrated Querying and Visual Exploration of Large Datasets (DEMO ABSTRACT)

    E-Print Network [OSTI]

    Liblit, Ben

    DEVise: Integrated Querying and Visual Exploration of Large Datasets (DEMO ABSTRACT) M. Livny, R of large tabular datasets (possibly containing or referencing multi­ media objects) from several sources meta­data summarizing the entire dataset, to large subsets of the actual data, to individual data

  14. Use of datasets derived from time-series AVHRR imagery as surrogates for land cover maps in predicting species' distributions

    E-Print Network [OSTI]

    Egbert, Stephen L.; Martí nez-Meyer, Enrique; Ortega-Huerta, Miguel; Peterson, A. Townsend

    2002-06-01T23:59:59.000Z

    to be the case, it may be possible to use AVHRR, MODIS, or similar imagery, either in raw form or as easily and cheaply derived datasets, as direct inputs to models that predict species’ distributions. II. METHODS In this pilot analysis, we selected... for Advanced Computational Infrastructure, Earth System Science (NPACI/ESS) Thrust. E.M-M. was supported by a graduate fellowship from the Direccion General de Asuntos del Personal Academico of the National University of Mexico (UNAM...

  15. Heavy Duty Diesel Particulate Matter and Fuel Consumption Modeling for Transportation Analysis

    E-Print Network [OSTI]

    Scora, George Alexander

    2011-01-01T23:59:59.000Z

    measured second-by-second fuel use. Mesoscale Modeling DataSet and Mesoscale ModelCalibration Mesoscale model calibration and validation

  16. Published in A. Drexl and A. Kimms (Eds), "Beyond Manufacturing Resource Planning (MRP II), Advanced Models and Methods for

    E-Print Network [OSTI]

    ), Advanced Models and Methods for Production Planning", Springer-Verlag, 1998, 379-411. Copyright, Springer (IDSS) to the lowest level of the PMS, namely the production activity control (PAC) subsystem. The IDSS the primitive Material Requirements Planning (MRP) features [22]. A production management system (PMS

  17. Filtergraph: An Interactive Web Application for Visualization of Astronomy Datasets

    E-Print Network [OSTI]

    Burger, Dan; Pepper, Joshua; Siverd, Robert J; Paegert, Martin; De Lee, Nathan M

    2013-01-01T23:59:59.000Z

    Filtergraph is a web application being developed and maintained by the Vanderbilt Initiative in Data-intensive Astrophysics (VIDA) to flexibly and rapidly visualize a large variety of astronomy datasets of various formats and sizes. The user loads a flat-file dataset into Filtergraph which automatically generates an interactive data portal that can be easily shared with others. From this portal, the user can immediately generate scatter plots of up to 5 dimensions as well as histograms and tables based on the dataset. Key features of the portal include intuitive controls with auto-completed variable names, the ability to filter the data in real time through user-specified criteria, the ability to select data by dragging on the screen, and the ability to perform arithmetic operations on the data in real time. To enable seamless data visualization and exploration, changes are quickly rendered on screen and visualizations can be exported as high quality graphics files. The application is optimized for speed in t...

  18. Parton distributions based on a maximally consistent dataset

    E-Print Network [OSTI]

    Juan Rojo

    2014-09-10T23:59:59.000Z

    The choice of data that enters a global QCD analysis can have a substantial impact on the resulting parton distributions and their predictions for collider observables. One of the main reasons for this has to do with the possible presence of inconsistencies, either internal within an experiment or external between different experiments. In order to assess the robustness of the global fit, different definitions of a conservative PDF set, that is, a PDF set based on a maximally consistent dataset, have been introduced. However, these approaches are typically affected by theory biases in the selection of the dataset. In this contribution, after a brief overview of recent NNPDF developments, we propose a new, fully objective, definition of a conservative PDF set, based on the Bayesian reweighting approach. Using the new NNPDF3.0 framework, we produce various conservative sets, which turn out to be mutually in agreement within the respective PDF uncertainties, as well as with the global fit. We explore some of their implications for LHC phenomenology, finding also good consistency with the global fit result. These results provide a non-trivial validation test of the new NNPDF3.0 fitting methodology, and indicate that possible inconsistencies in the fitted dataset do not affect substantially the global fit PDFs.

  19. Cultural Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power Administration would likeConstitution4 Department of

  20. STIL2 Swedish Office Buildings Survey - Datasets - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-f < RAPID‎ |Rippey Jump to:WY) JumpLandSRT Jump to:STIL2 Swedish Office

  1. Arkansas Water Resources Center

    E-Print Network [OSTI]

    Soerens, Thomas

    for the training of scientists in water resources. Through the years, projects have included irrigation, ground water modeling, non-point source pollution, quality of ground water and surface water, efficient septic heavy metals from pasture soil amended with varying rates of poultry litter Basic Information Title

  2. Utility Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron SpinPrincetonUsing Maps to Predict SolarJohnpotential-calc Sign InPages

  3. Archaeological Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041cloth DocumentationProductsAlternativeOperational Management » History »Dept

  4. Online Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearch > TheNuclear Astrophysics One ofSpeeding accessOfficeAdsorptionOnline

  5. Computing Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power Administration would like submit theInnovationComputationalEnergyEvents

  6. Volunteers - Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengthening aTurbulenceUtilize AvailableMedia1.1 TheVolker

  7. Business Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office511041clothAdvanced Materials Advanced MaterialsEnergy,EnvelopeJeffersonBusinessPractices Sign In About

  8. Marketing Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC)Integrated Codes |IsLove Your Home and It'llMappingMariaHereld Manager,Markdefault

  9. Subcontractor Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengthening a solid ... StrengtheningLab (NewportStudying theSubcontactor

  10. Teacher Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengthening a solidSynthesis of 2D AlloysTrails TakingRTapeUpdatedTeachers »

  11. Privacy Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's Possible forPortsmouth/Paducah47,193.70 Hg Mercury 35 Br Bromine 43 cPoints of Contact

  12. Mobile Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC)Integrated Codes |IsLove Your1 SECTION A. Revised:7,AMission MissionMistakesMoMobile

  13. FTT:Power : A global model of the power sector with induced technological change and natural resource depletion

    E-Print Network [OSTI]

    Mercure, Jean-Francois

    2011-08-25T23:59:59.000Z

    S Biomass+CCS BIGCC BIGCC+CCS Biogas Biogas+CCS S Hydro L Hydro Onshore Offshore Solar PV CSP Geothermal Wave Fuel Cells CHP 2010 2030 2050 2070 2090 0 10 20 30 40 50 Year El ec tri ci ty G en er at io n ( P W h ) 0 1 2 3 4 5 Year Ca pa cit y ( T W... ) Mitigation 2010 2030 2050 2070 2090 0 10 20 30 40 50 Year El ec tri ci ty G en er at io n ( P W h ) Nuclear Oil Coal Coal+CCS Gas Gas+CCS Biomass Biomass+CCS Hydro Wind Solar Geothermal Wave Figure 5: Model results for two sets of assumptions, a...

  14. Forney, Texas: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,dataset name belowDevelopmentForney,

  15. Fowler, California: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,datasetWind Farm JumpPhase

  16. Fredericksburg, Virginia: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,datasetWindFreEner-g

  17. Chile: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDataset Country Chile South America

  18. China: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDataset Country ChileDialogue,China: Energy

  19. Chino, California: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDataset Country ChileDialogue,China:

  20. Clayton, Georgia: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCity ofClark Energy CoopValley

  1. Clinton, Iowa: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCityFund JumpClimeCo CorporationClinton,

  2. Clintonville, Wisconsin: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCityFund JumpClimeCo

  3. Clovis, California: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCityFund JumpClimeCoWindpower

  4. Coalinga, California: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCityFundCo-benefits

  5. Coastal Barrier Resources Act | 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCityFundCo-benefitsCoalogix Inc Jump

  6. Trappe, Pennsylvania: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga, Indiana (Utility Company)LibraryDatasets -Trappe, Pennsylvania:

  7. Travilah, Maryland: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga, Indiana (Utility Company)LibraryDatasetsElectric Coop, Inc

  8. Trenton, Ohio: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga, Indiana (Utility Company)LibraryDatasetsElectricRiver SolarOhio:

  9. Fact #858 February 2, 2015 Retail Gasoline Prices in 2014 Experienced the Largest Decline since 2008 – Dataset

    Broader source: Energy.gov [DOE]

    Excel file with dataset for Retail Gasoline Prices in 2014 Experienced the Largest Decline since 2008

  10. Constructing Collaborative Desktop Storage Caches for Large Scientific Datasets

    SciTech Connect (OSTI)

    Vazhkudai, Sudharshan S [ORNL; Ma, Xiaosong [ORNL; Freeh, Vincent W [ORNL; Strickland, Jonathan W [ORNL; Tammineedi, Nandan [ORNL; Simon, Tyler A [ORNL; Scott, Stephen L [ORNL

    2006-08-01T23:59:59.000Z

    High-end computing is suffering a data deluge from experiments, simulations, and apparatus that creates overwhelming application dataset sizes. This has led to the proliferation of high-end mass storage systems, storage area clusters, and data centers. These storage facilities offer a large range of choices in terms of capacity and access rate, as well as strong data availability and consistency support. However, for most end-users, the "last mile" in their analysis pipeline often requires data processing and visualization at local computers, typically local desktop workstations. End-user workstations-despite having more processing power than ever before-are ill-equipped to cope with such data demands due to insufficient secondary storage space and I/O rates. Meanwhile, a large portion of desktop storage is unused. We propose the FreeLoader framework, which aggregates unused desktop storage space and I/O bandwidth into a shared cache/scratch space, for hosting large, immutable datasets and exploiting data access locality. This article presents the FreeLoader architecture, component design, and performance results based on our proof-of-concept prototype. Its architecture comprises contributing benefactor nodes, steered by a management layer, providing services such as data integrity, high performance, load balancing, and impact control. Our experiments show that FreeLoader is an appealing low-cost solution to storing massive datasets by delivering higher data access ratesthan traditional storage facilities, namely, local or remote shared file systems, storage systems, and Internet data repositories. In particular, we present novel data striping techniques that allow FreeLoader to efficiently aggregate a workstation's network communication bandwidth and local I/O bandwidth. In addition, the performance impact on the native workload of donor machines is small and can be effectively controlled. Further, we show that security features such as data encryptions and integrity checks can be easily added as filters for interested clients. Finally, we demonstrate how legacy applications can use the FreeLoader API to store and retrieve datasets.

  11. Top Resources | Commercial Buildings Resource Database

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

    Home Programs & Offices Consumer Information Commercial Buildings Resource Database Resources to support the adoption of energy-saving building technologies Search form Search...

  12. Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets

    E-Print Network [OSTI]

    Ho, Hsiang; Milenkovi?, Tijana; Memiševi?, Vesna; Aruri, Jayavani; Pržulj, Nataša; Ganesan, Anand K

    2010-01-01T23:59:59.000Z

    components within functional genomics datasets BMC SystemssiRNA-based functional genomics of pigmentation identifiesrelated functional genomics data. J R Soc Interface Motulsky

  13. Carrots and Sticks: A Comprehensive Business Model for the Successful Achievement of Energy Efficiency Resource Standards Environmental Energy Technologies DivisionMarch 2011

    SciTech Connect (OSTI)

    Satchwell, Andrew; Cappers, Peter; Goldman, Charles

    2011-03-22T23:59:59.000Z

    Energy efficiency resource standards (EERS) are a prominent strategy to potentially achieve rapid and aggressive energy savings goals in the U.S. As of December 2010, twenty-six U.S. states had some form of an EERS with savings goals applicable to energy efficiency (EE) programs paid for by utility customers. The European Union has initiated a similar type of savings goal, the Energy End-use Efficiency and Energy Services Directive, where it is being implemented in some countries through direct partnership with regulated electric utilities. U.S. utilities face significant financial disincentives under traditional regulation which affects the interest of shareholders and managers in aggressively pursuing cost-effective energy efficiency. Regulators are considering some combination of mandated goals ('sticks') and alternative utility business model components ('carrots' such as performance incentives) to align the utility's business and financial interests with state and federal energy efficiency public policy goals. European countries that have directed their utilities to administer EE programs have generally relied on non-binding mandates and targets; in the U.S., most state regulators have increasingly viewed 'carrots' as a necessary condition for successful achievement of energy efficiency goals and targets. In this paper, we analyze the financial impacts of an EERS on a large electric utility in the State of Arizona using a pro-forma utility financial model, including impacts on utility earnings, customer bills and rates. We demonstrate how a viable business model can be designed to improve the business case while retaining sizable ratepayer benefits. Quantifying these concerns and identifying ways they can be addressed are crucial steps in gaining the support of major stakeholder groups - lessons that can apply to other countries looking to significantly increase savings targets that can be achieved from their own utility-administered EE programs.

  14. Water Resource System Optimization by Geometric Programming

    E-Print Network [OSTI]

    Meier, W. L.; Shih, C. S.; Wray, D. J.

    Water resources planners and systems analysts are continually confronted with many complex optimization problems. Two major factors contribute to this problem. Firstly, mathematical modeling and system description capabilities in water resources...

  15. Arkansas Water Resources Center Annual Technical Report

    E-Print Network [OSTI]

    and heavy metals to surface runoff following storm events. Evaluating runoff water quality response, innovative domestic wastewater disposal systems, ground water modeling and landuse mapping, erosionArkansas Water Resources Center Annual Technical Report FY 2008 Arkansas Water Resources Center

  16. Resources | Argonne National Laboratory

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

    Resources Training & Development Mentoring Safety Program Brochure Postdoctoral Blog Resources The resources in this section have been curated to better support you in your...

  17. LANSCE | User Resources

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

    proposal process to the completion of the experiment, LANSCE provides its users with resources critical to their experiements and their experience. Lujan Resources WNR Resources...

  18. MATCH: Metadata Access Tool for Climate and Health Datasets

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    MATCH is a searchable clearinghouse of publicly available Federal metadata (i.e. data about data) and links to datasets. Most metadata on MATCH pertain to geospatial data sets ranging from local to global scales. The goals of MATCH are to: 1) Provide an easily accessible clearinghouse of relevant Federal metadata on climate and health that will increase efficiency in solving research problems; 2) Promote application of research and information to understand, mitigate, and adapt to the health effects of climate change; 3) Facilitate multidirectional communication among interested stakeholders to inform and shape Federal research directions; 4) Encourage collaboration among traditional and non-traditional partners in development of new initiatives to address emerging climate and health issues. [copied from http://match.globalchange.gov/geoportal/catalog/content/about.page

  19. Nebraska Water Resources Center Annual Technical Report

    E-Print Network [OSTI]

    : Groundwater, Models, Water Use Descriptors: Aquifer parameters, conjuntive use, groundwater modeling, surface-groundwater modeling, Surface- groundwater Relationships, Well hydraulics Problem and research objectives: ProblemNebraska Water Resources Center Annual Technical Report FY 2000 Introduction Welcome

  20. Department of Mathematics: Resources

    E-Print Network [OSTI]

    Resources Internal Resources Computing Information Business Office Information for TAs and Limited-Term Lecturers Information for Faculty Information for ...

  1. Parallel Processing of Large Datasets from NanoLC-FTICR-MS Measurements

    E-Print Network [OSTI]

    van Nieuwpoort, Rob V.

    for these biomarkers Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) is a powerful tool becauseParallel Processing of Large Datasets from NanoLC-FTICR-MS Measurements Y. E. M. van der Burgt, I parallel processing of large mass spectral datasets in a distributed computing environment is demonstrated

  2. Comparing GPU Implementations of Bilateral and Anisotropic Diffusion Filters for 3D Biomedical Datasets

    SciTech Connect (OSTI)

    Howison, Mark

    2010-05-06T23:59:59.000Z

    We compare the performance of hand-tuned CUDA implementations of bilateral and anisotropic diffusion filters for denoising 3D MRI datasets. Our tests sweep comparable parameters for the two filters and measure total runtime, memory bandwidth, computational throughput, and mean squared errors relative to a noiseless reference dataset.

  3. Decentralized K-means using randomized Gossip protocols for clustering large datasets

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Decentralized K-means using randomized Gossip protocols for clustering large datasets Jerome Fellus datasets distributed over a network of computational units using a decentralized K-means algorithm with a centralized K-means, provided a bound on the number of messages each node has to send is met. We provide

  4. Teaching Direct Marketing and Small Farm Viability: Resources for Instructors, 2nd Edition. Part 8 - Farm Employees and Innovative Models for Interns and Apprentices

    E-Print Network [OSTI]

    2015-01-01T23:59:59.000Z

    and Immigration Services web page will have currentIndustrial Relations. Check the web site often for currentlabor, interns and employees. WEB-BASED RESOURCES Division

  5. Modeling Musical Influence with Topic Models Uri Shalit uri.shalit@mail.huji.ac.il

    E-Print Network [OSTI]

    Weinshall, Daphne

    by applying topic-modeling tools (Blei & Lafferty, 2006; Gerrish & Blei, 2010) to a dataset of 24941 songs on Dynamic Topic Model (DTM) (Blei & Lafferty, 2006) and Doc- ument Influence Model (DIM) (Gerrish & Blei

  6. Session: Wind resources and site characterisation 2 (DW3.5) Track: Technical

    E-Print Network [OSTI]

    including wind shear, turbulence intensities etc., at potential wind turbine positions. - ApplicationSession: Wind resources and site characterisation 2 (DW3.5) Track: Technical THE BOLUND EXPERIMENT - A NEW DATASET OF LOCAL WIND CONDITIONS IN COMPLEX TERRAIN (abstract-ID: 357) Jeppe Johansen (Risø DTU

  7. National Geothermal Resource Assessment and Classification |...

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

    This work will enable lower riskcost deployment of conventional and EGS geothermal power. USGS is also supporting GTP input to DOE National Energy Modeling by providing resource...

  8. Carrots and Sticks: A Comprehensive Business Model for the Successful Achievement of Energy Efficiency Resource Standards Environmental Energy Technologies Division March 2011

    E-Print Network [OSTI]

    Satchwell, Andrew

    2011-01-01T23:59:59.000Z

    framework of the energy efficiency business model in furthera comprehensive energy efficiency business model on utilitya comprehensive energy efficiency business model on utility

  9. 1 Environmental Resource Policy ENVIRONMENTAL RESOURCE

    E-Print Network [OSTI]

    Vertes, Akos

    1 Environmental Resource Policy ENVIRONMENTAL RESOURCE POLICY GRADUATE Master's program · Master of Arts in the field of environmental resource policy (http://bulletin.gwu.edu/arts-sciences/environmental CERTIFICATE · Graduate certificate in contexts of environmental policy (http://bulletin.gwu.edu/arts-sciences/environmental

  10. Distributed Energy Resources at Naval Base Ventura County Building 1512: A Sensitivity Analysis

    E-Print Network [OSTI]

    Bailey, Owen C.; Marnay, Chris

    2005-01-01T23:59:59.000Z

    2003. “Distributed Energy Resources in Practice: A Case2004. “Distributed Energy Resources Customer Adoption ModelDistributed Energy Resource Technology Characterizations”

  11. Managing renewable resources via Collective Intelligence

    E-Print Network [OSTI]

    Boschetti, Fabio

    Managing renewable resources via Collective Intelligence Brede, M., F. Boschetti, and D. Mc.Brede,Fabio.Boschetti,David.Mcdonald]@csiro.au Keywords: ABM, Game Theory, Resource Exploitation, Optimisation. EXTENDED ABSTRACT In a recent set of work, 2001; Wolpert et al, 2004) into resource management modelling. These tools were designed to minimise

  12. Fact #834: August 18, 2014 About Two-Thirds of Transportation Energy Use is Gasoline for Light Vehicles – Dataset

    Broader source: Energy.gov [DOE]

    Excel file with dataset for Fact #834: About Two-Thirds of Transportation Energy Use is Gasoline for Light Vehicles

  13. Fact #857 January 26, 2015 Number of Partner Workplaces Offering Electric Vehicle Charging More Than Tripled Since 2011 – Dataset

    Broader source: Energy.gov [DOE]

    Excel file with dataset for Number of Partner Workplaces Offering Electric Vehicle Charging More Than Tripled Since 2011

  14. Fact #837: September 8, 2014 Gap between Net Imports and Total Imports of Petroleum is Widening – Dataset

    Broader source: Energy.gov [DOE]

    Excel file with dataset for Fact #837: Gap between Net Imports and Total Imports of Petroleum is Widening

  15. Fact #845: November 3, 2014 From 1970 to 2013 the Share of Older Vehicles in Operation has Increased – Dataset

    Broader source: Energy.gov [DOE]

    Excel file with dataset for Fact #845: From 1970 to 2013 the Share of Older Vehicles in Operation has Increased

  16. Fact #844: October 27, 2014 Electricity Generated from Coal has Declined while Generation from Natural Gas has Grown – Dataset

    Broader source: Energy.gov [DOE]

    Excel file with dataset for Fact #844: Electricity Generated from Coal has Declined while Generation from Natural Gas has Grown

  17. Fact #868: April 13, 2015 Automotive Technology Has Improved Performance and Fuel Economy of New Light Vehicles – Dataset

    Broader source: Energy.gov [DOE]

    Excel file and dataset for Automotive Technology Has Improved Performance and Fuel Economy of New Light Vehicles

  18. Spatial Clustering of Galaxies in Large Datasets Alexander S. Szalay, Department of Physics and Astronomy, Johns Hopkins University

    E-Print Network [OSTI]

    Narasayya, Vivek

    surveys using the Karhunen-Loeve transform as a case study. These large, homogenous datasets are alsoSpatial Clustering of Galaxies in Large Datasets Alexander S. Szalay, Department of Physics Microsoft Way Redmond, WA 98052 #12;Spatial Clustering of Galaxies in Large Datasets Alexander S. Szalaya

  19. The solar rotation rate from inversion of the first GONG datasets T. Corbard 1 , G. Berthomieu 1 , J. Provost 1

    E-Print Network [OSTI]

    Corbard, Thierry

    The solar rotation rate from inversion of the first GONG datasets T. Corbard 1 , G. Berthomieu 1 gives some results obtained by inverting the first GONG datasets for the rotational splittings of the so called averaging kernels Ÿ(r 0 ; ¯ 0 ; r; ¯) defined in Corbard et al. (1996). 2. GONG datasets

  20. Economic regulation of electricity distribution utilities under high penetration of distributed energy resources : applying an incentive compatible menu of contracts, reference network model and uncertainty mechanisms

    E-Print Network [OSTI]

    Jenkins, Jesse D. (Jesse David)

    2014-01-01T23:59:59.000Z

    Ongoing changes in the use and management of electricity distribution systems - including the proliferation of distributed energy resources, smart grid technologies (i.e., advanced power electronics and information and ...

  1. Licensing East Asian Resources

    E-Print Network [OSTI]

    Chu, Victoria; Eggleston, Holly

    2008-01-01T23:59:59.000Z

    our licensing of East Asian Resources here at UCSD. y It isthe history of electronic resources and the use of licensesclick through, or even use a resource with posted terms on a

  2. Natural Resources Districts (Nebraska)

    Broader source: Energy.gov [DOE]

    This statute establishes Natural Resources District, encompassing all of the area of the state, to conserve, protect, develop, and manage Nebraska's natural resources. These districts replace and...

  3. Solar radiation resource assessment

    SciTech Connect (OSTI)

    Not Available

    1990-11-01T23:59:59.000Z

    The bulletin discusses the following: introduction; Why is solar radiation resource assessment important Understanding the basics; the solar radiation resource assessment project; and future activities.

  4. Carrots and Sticks: A Comprehensive Business Model for the Successful Achievement of Energy Efficiency Resource Standards Environmental Energy Technologies Division March 2011

    E-Print Network [OSTI]

    Satchwell, Andrew

    2011-01-01T23:59:59.000Z

    of the energy efficiency business model in further detail.7   4.3 Business Modelenergy efficiency business model on utility earnings .

  5. New ORNL, N.C. State, LanzaTech DNA dataset is potent, accessible...

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

    Ron Walli Communications 865.576.0226 New ORNL, N.C. State, LanzaTech DNA dataset is potent, accessible tool Dawn Klingeman of Oak Ridge National Laboratory's Biosciences Division...

  6. Writing Assessment: Additional Resources

    E-Print Network [OSTI]

    Schweik, Charles M.

    29 Appendix A Writing Assessment: Additional Resources #12;30 Where can I find out more into the assessment process. On-campus resources give you with a "real person" to contact should you have questions Resources for Higher Education Outcomes Assessment http://www2.acs.ncsu.edu/UPA/survey/resource.htm Ohio

  7. Forest Resources and Management

    E-Print Network [OSTI]

    Forest Resources and Management Centre for The Centre for Forest Resources and Management aims the forest resource. Our aim is that British forests ­ from their creation to maturity and regeneration-energy development, forest resource forecasting, genetic improvement, woodland regeneration and creation, management

  8. Digital Elevation Model, 0.5-m, Barrow Environmental Observatory, Alaska, 2012

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Gangodagamage, Chandana; Wilson, Cathy; Rowland, Joel

    The dataset is a digital elevation model, DEM, of a 2km by 7km region in the vicinity of the Barrow Environmental Observatory near Barrow, Ak.

  9. Digital Elevation Model, 0.5-m, Barrow Environmental Observatory, Alaska, 2012

    SciTech Connect (OSTI)

    Gangodagamage, Chandana; Wilson, Cathy; Rowland, Joel

    2013-12-08T23:59:59.000Z

    The dataset is a digital elevation model, DEM, of a 2km by 7km region in the vicinity of the Barrow Environmental Observatory near Barrow, Ak.

  10. Modeling Topic Specific Credibility in Twitter Byungkyu Kang, John O'Donovan,

    E-Print Network [OSTI]

    California at Santa Barbara, University of

    users who tweeted about the topic "Libya". Results show that the social model outperfoms hybrid credibility ratings on the "Libya" dataset. Author Keywords Credibility, Trust, Microblogs, Data Mining

  11. NREL: Transmission Grid Integration - Solar Integration National Dataset

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's Possible for Renewable Energy: Grid IntegrationReport AvailableForecastingNewsToolkit

  12. The! Community! Earth! System! Model! (CESM)! Large! Ensemble! Project:! A! Community!3! Resource!for!Studying!Climate!Change!in!the!Presence!of!Internal!Climate!Variability!4!

    E-Print Network [OSTI]

    Kay, Jennifer

    !1! !2! The! Community! Earth! System! Model! (CESM)! Large! Ensemble! Project:! A! Community!3!Earth!System!Model!(CESM)!community!designed!the!CESM!Large!Ensemble!39! (CESMWLE)!with!the!explicit

  13. Conservation Conservation ResourcesConservation Resources

    E-Print Network [OSTI]

    sequestration,, coal gasification, carbon sequestration, energy storage, highenergy storage, highConfirm cost & availability of promising resources ­­ Oil sandsOil sands cogencogen, coal gasification, carbon

  14. Index of /datasets/files/39/pub/documentation

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are8COaBulkTransmissionSitingProcess.pdfGetecGtel JumpCounty,Jump to:Unconventional

  15. DOE Launches New Dataset on its Environmental Reviews | Department of

    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 DataDepartment of Energy Your Density Isn't Your Destiny: Theof"Wave theJulyD&DDepartment offorEnergy Lab ReceivesEnergy

  16. Wind Integration National Dataset (WIND) Toolkit | 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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy China 2015ofDepartment of EnergyThe U.S. DepartmentEnergyWilliam E.Much asPhoto4,

  17. OpenEI:Projects/Datasets Improvements | 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluatingGroup |JilinLuOpenNorthOlympia Green FuelsperCivicVersionNeutral point of

  18. OpenEI:Projects/Datasets Patterns | 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluatingGroup |JilinLuOpenNorthOlympia Green FuelsperCivicVersionNeutral point

  19. OpenEI - Organizations - OpenEI Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal Pwer PlantMunhall,Missouri: EnergyExcellenceOfficeOhio: Energy Resourcesen) OpenOpenBarter

  20. Technology Development and Field Trials of EGS Drilling Systems - Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro Industries PvtStratosolar Jump to:HoldingsTechint Spa Jump to:Technologiefabrik- OpenEI

  1. Technology Development and Field Trials of EGS Drilling Systems - Datasets

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro Industries PvtStratosolar Jump to:HoldingsTechint Spa Jump to:Technologiefabrik- OpenEI-

  2. Colorado thermal spring water geothermometry (public dataset) | 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CERCollier TechnologiesColoradoColoradoCourts

  3. Energy API and dataset overview | OpenEI Community

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489 No revision| OpenElectromagneticElmwoodEnerSpectivesolarAPI and

  4. Forrest City, Arkansas: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,dataset name

  5. Fort Bend County, Texas: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,dataset nameFort Bend County, Texas:

  6. Fort Defiance, Arizona: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,dataset nameFort Bend County,

  7. Fort Lauderdale, Florida: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,dataset nameFort Bend

  8. Fort Lupton, Colorado: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,dataset nameFort BendLupton,

  9. Fort Wayne, Indiana: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,dataset nameFort

  10. Fortuna Foothills, Arizona: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,dataset nameFortFortuna Foothills,

  11. Franklin County, Kentucky: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,datasetWind FarmKentucky: Energy

  12. Franklin County, Ohio: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,datasetWind FarmKentucky: EnergyOhio:

  13. Frederick County, Maryland: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489Information HydroFontana,datasetWindFreEner-g Jump

  14. China Lake Acres, California: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDataset Country Chile SouthIntegrated Energy

  15. Chino Hills, California: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDataset Country ChileDialogue,China: EnergyChino

  16. Chittenden County, Vermont: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDataset Country ChileDialogue,China:Chisolm

  17. Citrus Heights, California: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDataset CountryChoosEV JumpCircleCitizenre

  18. Clackamas County, Oregon: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCity of Holyoke,Monroe,CityCity

  19. Claverack, New York: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCity ofClark Energy Coop Inc Jump

  20. Clay County, Texas: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCity ofClark Energy Coop Inc

  1. Clermont County, Ohio: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCity ofClarkEnergy - QPowerClermont

  2. Cleveland County, Oklahoma: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCity ofClarkEnergy -

  3. Cochise County, Arizona: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCityFundCo-benefitsCoalogix IncCobbCochise

  4. Coconino County, Arizona: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCityFundCo-benefitsCoalogix

  5. College Park, Maryland: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCityFundCo-benefitsCoalogixfieldRaft

  6. College Station, Texas: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:PowerCER.png El CER esDatasetCityFundCo-benefitsCoalogixfieldRaft

  7. Transylvania County, North Carolina: Energy Resources | 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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga, Indiana (Utility Company)LibraryDatasets -

  8. Travelers Rest, South Carolina: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga, Indiana (Utility Company)LibraryDatasets -Trappe,GeneralTravelers

  9. Traverse County, Minnesota: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga, Indiana (Utility Company)LibraryDatasets

  10. Treasure County, Montana: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga, Indiana (Utility Company)LibraryDatasetsElectric Coop, IncTreasure

  11. Trego County, Kansas: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga, Indiana (Utility Company)LibraryDatasetsElectric Coop,

  12. Trempealeau County, Wisconsin: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga, Indiana (Utility Company)LibraryDatasetsElectric

  13. Trenton, New Jersey: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga, Indiana (Utility Company)LibraryDatasetsElectricRiver Solar |New

  14. Trenton, New Jersey: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga, Indiana (Utility Company)LibraryDatasetsElectricRiver Solar

  15. Treutlen County, Georgia: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown of Ladoga, Indiana (Utility Company)LibraryDatasetsElectricRiver

  16. Business Planning Resources

    Broader source: Energy.gov [DOE]

    Business Planning Resources, a presentation of the U.S. Department of Energy's Better Buildings Neighborhood Program.

  17. Statewide Forest Resource Strategy

    E-Print Network [OSTI]

    Resource Assessment (assessment). The assessment and strategy identify important forest lands and provideColorado Statewide Forest Resource Strategy #12;June 2010 Acknowledgments The Colorado State Forest Forest Resource Strategy. We also offer our thanks and acknowledgement to Greg Sundstrom, assistant staff

  18. Standard Nine: Financial Resources

    E-Print Network [OSTI]

    Snider, Barry B.

    105 Standard Nine: Financial Resources Overview The 1996 NEASC team report was critical of Brandeis's financial management, and focused on the need to increase financial resources, improve faculty and staff displays the University resource profile for FY1995 compared to the FY2005 profile. During this decade

  19. Life Sciences Shared Resources

    E-Print Network [OSTI]

    Myers, Lawrence C.

    Life Sciences Shared Resources Cancer.Dartmouth.eduMarch 2012 201202-19201202-19 #12;SHARED RESOURCES MANAGEMENT MANAGEMENT TEAM: Mark Israel, MD Director, Norris Cotton Cancer Center Bob Gerlach, MPA Associate Director, Norris Cotton Cancer Center CraigTomlinson, PhD Associate Director for Shared Resources

  20. Medical Student Resource Guide

    E-Print Network [OSTI]

    Chapman, Michael S.

    20132014 O.H.S.U. Medical Student Resource Guide #12;2013-2014 Medical Student Resource Guide 1 Oregon Health & Science University School of Medicine - Medical Student Resource Guide Welcome This is an exciting time to be in medicine. Advances in the sciences basic to the study and practice of medicine

  1. Resource Adequacy INTRODUCTION

    E-Print Network [OSTI]

    ) have acquired sufficient resources to satisfy forecasted future loads reliably. This definition whether there are sufficient non-hydro resources available to meet loads when the "fuel" for hydroelectric. For a number of reasons, resource development in the 1990s failed to keep pace with growth in the region and

  2. Proceedings ASCE EWRI World Water and Environmental Resources Congress 2005 May 15-19, 2005 Modeling and evaluating temperature dynamics in wastewater treatment plants

    E-Print Network [OSTI]

    Wells, Scott A.

    Modeling and evaluating temperature dynamics in wastewater treatment plants Scott A. Wells1 , Dmitriy treatment plants (WWTP). This type of model would allow operators to evaluate alternatives for reducing conditions. Temperatures were taken at 6 control points throughout the treatment plant and used as a basis

  3. Geothermal resources of California

    SciTech Connect (OSTI)

    Bezore, S.P.

    1984-06-01T23:59:59.000Z

    Geothermal resources may be classified into two types: high temperature, >150 C, suitable for electrical generation and low- to moderate-temperature, 20-150 C, suitable for direct use. To further the development of geothermal resources in California, a concentrated study of low-temperature and moderate-temperature geothermal resources has been conducted by the California Department of Conservation. As part of that study a map containing technical data on the geothermal resources of California is now available to help planners, local governments, etc. develop their local resources.

  4. Exploitative Competition in the Chemostat for Two Perfectly Substitutable Resources

    E-Print Network [OSTI]

    Wolkowicz, Gail S. K.

    Exploitative Competition in the Chemostat for Two Perfectly Substitutable Resources MARY M. BALLYK of microorganisms competing for two nonreproducing, growth-limiting resources in a chemostat, we focus on perfectly substitutable resources. Leon and Tumpson considered a model of perfectly substitutable resources in which

  5. Center for Electric & Hydrogen Technologies & Systems Resource Integration Group

    E-Print Network [OSTI]

    ,Analysis,Metrology,and Measurements of Renewable Energy Resources Renewable resources can vary considerably from one geographic and Instrumentation Team, provides renewable resource data for U.S. and international locations. Modeling Using, or to define the resource at specific locations where renewable technologies might be installed to meet

  6. Playing games against nature: optimal policies for renewable resource allocation

    E-Print Network [OSTI]

    Keinan, Alon

    Playing games against nature: optimal policies for renewable resource allocation Stefano Ermon- cision processes that arise as a natural model for many renewable resource allocation problems. Upon for the allocation of renewable resources. A key and unique aspect of such a resource type is the fact that

  7. Fact #850: December 8, 2014 Automatic Transmissions have closed the Fuel Economy Gap with Manual Transmissions- Dataset

    Broader source: Energy.gov [DOE]

    Excel file with dataset for Fact #850: December 8, 2014 Automatic Transmissions have closed the Fuel Economy Gap with Manual Transmissions

  8. Fact #851: December 15, 2014 The Average Number of Gears used in Transmissions Continues to Rise – Dataset

    Broader source: Energy.gov [DOE]

    Excel file with dataset for Fact #851: December 15, 2014 The Average Number of Gears used in Transmissions Continues to Rise

  9. Fact #838: September 15, 2014 Net Imports of Petroleum were Only 33% of U.S. Consumption in 2013- Dataset

    Broader source: Energy.gov [DOE]

    Excel file with dataset for Fact #838: Net Imports of Petroleum were Only 33% of U.S. Consumption in 2013

  10. Fact #839: September 22, 2014 World Petroleum Consumption Continues to Rise despite Declines from the United States and Europe- Dataset

    Broader source: Energy.gov [DOE]

    Excel file with dataset for Fact #839: World Petroleum Consumption Continues to Rise despite Declines from the United States and Europe

  11. Fact #846: November 10, 2014 Trucks Move 70% of all Freight by Weight and 74% of Freight by Value – Dataset

    Broader source: Energy.gov [DOE]

    Excel file with dataset for Fact #846: Trucks Move 70% of all Freight by Weight and 74% of Freight by Value

  12. Fact #853 December 29, 2014 Stop/Start Technology is in nearly 5% of All New Light Vehicles Produced- Dataset

    Broader source: Energy.gov [DOE]

    Excel file with dataset for Fact #853: December  29, 2014 Stop/Start Technology is in nearly 5% of All New Light Vehicles Produced

  13. Primer on gas integrated resource planning

    SciTech Connect (OSTI)

    Goldman, C.; Comnes, G.A.; Busch, J.; Wiel, S. [Lawrence Berkeley Lab., CA (United States)

    1993-12-01T23:59:59.000Z

    This report discusses the following topics: gas resource planning: need for IRP; gas integrated resource planning: methods and models; supply and capacity planning for gas utilities; methods for estimating gas avoided costs; economic analysis of gas utility DSM programs: benefit-cost tests; gas DSM technologies and programs; end-use fuel substitution; and financial aspects of gas demand-side management programs.

  14. Arkansas Water Resources Center Annual Technical Report

    E-Print Network [OSTI]

    wastewater disposal systems, ground water modeling and land use mapping, erosion and pollution, water quality focused on helping local, state and federal agencies understand, manage and protect water resources within Arkansas. AWRC has contributed substantially to the understanding and management of water resources through

  15. The Development of a Coordinated Database for Water Resources and Flow Model in the Paso Del Norte Watershed (Phase III) Part II Availability of Flow and Water Quality Data for the Rio Grande Project Area

    E-Print Network [OSTI]

    Tillery, Sue; Sheng, Zhuping; King, J. Phillip; Creel, Bobby; Brown, Christopher; Michelsen, Ari; Srinivasan, Raghavan; Granados, Alfredo

    2009-01-01T23:59:59.000Z

    Cruces, NM 88003 (575) 646-4337 i i Acknowledgement This document and the underlying pr oject activities detailed in this report reflect the joint efforts of many people working with the Paso del Norte Watershed Council (PdNWC). The authors... wish to acknowledge and extend our grat itude to the U.S. Army Corps of Engineers for the generous financial support extende d to the PdNWC for development of the Coordinated Water Resources Database and Model Developm ent Project (called Project...

  16. Bayesian time series models and scalable inference

    E-Print Network [OSTI]

    Johnson, Matthew James, Ph. D. Massachusetts Institute of Technology

    2014-01-01T23:59:59.000Z

    With large and growing datasets and complex models, there is an increasing need for scalable Bayesian inference. We describe two lines of work to address this need. In the first part, we develop new algorithms for inference ...

  17. Hawaii demand-side management resource assessment. Final report, Reference Volume 3 -- Residential and commercial sector DSM analyses: Detailed results from the DBEDT DSM assessment model; Part 1, Technical potential

    SciTech Connect (OSTI)

    NONE

    1995-04-01T23:59:59.000Z

    The Hawaii Demand-Side Management Resource Assessment was the fourth of seven projects in the Hawaii Energy Strategy (HES) program. HES was designed by the Department of Business, Economic Development, and Tourism (DBEDT) to produce an integrated energy strategy for the State of Hawaii. The purpose of Project 4 was to develop a comprehensive assessment of Hawaii`s demand-side management (DSM) resources. To meet this objective, the project was divided into two phases. The first phase included development of a DSM technology database and the identification of Hawaii commercial building characteristics through on-site audits. These Phase 1 products were then used in Phase 2 to identify expected energy impacts from DSM measures in typical residential and commercial buildings in Hawaii. The building energy simulation model DOE-2.1E was utilized to identify the DSM energy impacts. More detailed information on the typical buildings and the DOE-2.1E modeling effort is available in Reference Volume 1, ``Building Prototype Analysis``. In addition to the DOE-2.1E analysis, estimates of residential and commercial sector gas and electric DSM potential for the four counties of Honolulu, Hawaii, Maui, and Kauai through 2014 were forecasted by the new DBEDT DSM Assessment Model. Results from DBEDTs energy forecasting model, ENERGY 2020, were linked with results from DOE-2.1E building energy simulation runs and estimates of DSM measure impacts, costs, lifetime, and anticipated market penetration rates in the DBEDT DSM Model. Through its algorithms, estimates of DSM potential for each forecast year were developed. Using the load shape information from the DOE-2.1E simulation runs, estimates of electric peak demand impacts were developed. Numerous tables and figures illustrating the technical potential for demand-side management are included.

  18. Geothermal Resources and Technologies

    Broader source: Energy.gov [DOE]

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

  19. LANSCE | Lujan Center | Resources

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

    User Resources The links below describe equipment, laboratories, capabilities, and sample environments that are available to users. Users must plan ahead and specify their needs...

  20. Resources | Jefferson Lab

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearch > TheNuclear Press ReleasesIn the InorganicResourcesResources Resources

  1. Modelling and Management of Sustainable Basin-scale Water Resource Systems (Proceedings of a Boulder Symposium, July 1995). IAHS Publ. no. 231, 1995. 359

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    of a Boulder Symposium, July 1995). IAHS Publ. no. 231, 1995. 359 Multivariate flexible least squares analysis basin in Kentucky in the USA are used in the study. The method is found to perform well. INTRODUCTION. In this method, a state- space model is defined and it consists of observation and state equations. Based

  2. Wave Energy Resource Analysis for Use in Wave Energy Conversion 

    E-Print Network [OSTI]

    Pastor, J.; Liu, Y.; Dou, Y.

    2014-01-01T23:59:59.000Z

    In order to predict the response of wave energy converters an accurate representation of the wave climate resource is crucial. This paper gives an overview of wave resource modeling techniques as well as detailing a methodology for estimating...

  3. University of Massachusetts Amherst Department of Resource Economics

    E-Print Network [OSTI]

    Schweik, Charles M.

    University of Massachusetts Amherst Department of Resource Economics Working Paper No. 2006-4 http: common pool resources, field experiments, communication, regulation, hierarchical linear models JEL Economics University of Massachusetts, Stockbridge Hall, 80 Campus Center Way, Amherst, MA 01003 E

  4. 5D-ODETLAP: A NOVEL FIVE-DIMENSIONAL COMPRESSION METHOD ON TIME-VARYING MULTIVARIABLE GEOSPATIAL DATASET

    E-Print Network [OSTI]

    Franklin, W. Randolph

    5D-ODETLAP: A NOVEL FIVE-DIMENSIONAL COMPRESSION METHOD ON TIME-VARYING MULTIVARIABLE GEOSPATIAL dimensional (5D) geospatial dataset consists of several multivariable 4D datasets, which are sequences of time technique for 5D geospatial data as a whole, instead of applying 3D compression method on each 3D slice

  5. Stumbl: Using Facebook to Collect Rich Datasets for Opportunistic Networking Research

    E-Print Network [OSTI]

    Gesbert, David

    Stumbl: Using Facebook to Collect Rich Datasets for Opportunistic Networking Research Theus, mobility and communication ties. Stumbl is a Facebook application that provides participating users with a user-friendly interface to report their daily face-to-face meetings with other Facebook friends

  6. Discovery of Geospatial Discriminating Patterns from Remote Sensing Datasets Tomasz Stepinski

    E-Print Network [OSTI]

    Ding, Wei

    Discovery of Geospatial Discriminating Patterns from Remote Sensing Datasets Wei Ding Tomasz. Several geospatial feature vari- ables are fused together, and the vector of their values at each spatial cell is considered as a transaction to be used in association analysis. The concept of emerging

  7. Automatic Diabetic Macular Edema Detection in Fundus Images Using Publicly Available Datasets

    SciTech Connect (OSTI)

    Giancardo, Luca [ORNL; Meriaudeau, Fabrice [ORNL; Karnowski, Thomas Paul [ORNL; Li, Yaquin [University of Tennessee, Knoxville (UTK); Garg, Seema [University of North Carolina; Tobin Jr, Kenneth William [ORNL; Chaum, Edward [University of Tennessee, Knoxville (UTK)

    2011-01-01T23:59:59.000Z

    Diabetic macular edema (DME) is a common vision threatening complication of diabetic retinopathy. In a large scale screening environment DME can be assessed by detecting exudates (a type of bright lesions) in fundus images. In this work, we introduce a new methodology for diagnosis of DME using a novel set of features based on colour, wavelet decomposition and automatic lesion segmentation. These features are employed to train a classifier able to automatically diagnose DME. We present a new publicly available dataset with ground-truth data containing 169 patients from various ethnic groups and levels of DME. This and other two publicly available datasets are employed to evaluate our algorithm. We are able to achieve diagnosis performance comparable to retina experts on the MESSIDOR (an independently labelled dataset with 1200 images) with cross-dataset testing. Our algorithm is robust to segmentation uncertainties, does not need ground truth at lesion level, and is very fast, generating a diagnosis on an average of 4.4 seconds per image on an 2.6 GHz platform with an unoptimised Matlab implementation.

  8. A Common UniversityA Common University Dataset for Canada (CUDC)

    E-Print Network [OSTI]

    Garousi, Vahid

    extent of consensus among templates evaluate suitability of Canadian Undergraduate Survey Consortium survey items in current common university dataset templates #12;11/18/2008 6 May 2008: Steering Group and principles consensus template coordination of student surveys NSSE: improving the survey and how it is used

  9. Investigating Gait Recognition in the Short-Wave Infrared (SWIR) Spectrum: Dataset and Challenges

    E-Print Network [OSTI]

    Ross, Arun Abraham

    Investigating Gait Recognition in the Short-Wave Infrared (SWIR) Spectrum: Dataset and Challenges that can confound recognition accuracy. In the context of automated human gait recognition, evaluation has literature has explored recognition in the passive thermal band. The advent of sophisticated sensors has

  10. SOIL MOISTURE CHARACTERIZATION USING MULTI-ANGULAR POLARIMETRIC RADARSAT-2 DATASETS

    E-Print Network [OSTI]

    Boyer, Edmond

    SOIL MOISTURE CHARACTERIZATION USING MULTI-ANGULAR POLARIMETRIC RADARSAT-2 DATASETS Hongquan Wang to be a solution to improve the effectiveness of bare soil char- acterization. However, the potential single and multiple incidence angle acquisitions is investigated against in situ soil moisture

  11. Analyzing Massive Astrophysical Datasets: Can Pig/Hadoop or a Relational DBMS Help?

    E-Print Network [OSTI]

    Anderson, Richard

    Analyzing Massive Astrophysical Datasets: Can Pig/Hadoop or a Relational DBMS Help? Sarah Loebman1 distributed DBMS and in the Pig/Hadoop system. We compare the performance of the tools to each other of subatomic particles to the evolution of the universe. These simulations produce an ever more massive amount

  12. Arkansas Water Resources Center

    E-Print Network [OSTI]

    Soerens, Thomas

    Arkansas Water Resources Center WATER RESOURCES ASPECTS OF COAL TRANSPORTATION BY SLURRY PIPELINE Electric Power Production with Transmission by EHV Power lines 8 Coal Slurry Pipelining versus Rail Shipment. 10 General Description of the Coal Slurry Pipelining Process. 14 History of Coal Slurry Pipelines

  13. RESOURCE GUIDE RECYCLING ELECTRONICS

    E-Print Network [OSTI]

    Danforth, Bryan Nicholas

    ://www.thesoftlanding.com/ AVOIDING BISPHENOL-A Eden Organics Beans http://www.edenfoods.com/ CD and DVD recycling httpRESOURCE GUIDE RECYCLING ELECTRONICS Batteries and Accessories Office Depot Cell Phones Any Verizon Plastics Call your local Solid Waste Management Facility eCycling resource (EPA) http

  14. SPACE RESOURCES ROUNDTABLE IX

    E-Print Network [OSTI]

    Rathbun, Julie A.

    SPACE RESOURCES ROUNDTABLE IX Colorado School of Mines October 25-27, 2007 http://www.ISRUinfo.com Sponsored by: Colorado School of Mines Lunar and Planetary Institute Space Resources Roundtable, Inc. First Space Michael B. Duke, Colorado School of Mines Leslie Gertsch, University of Missouri-Rolla Alex

  15. Simulation of partial entanglement with nonsignaling resources

    E-Print Network [OSTI]

    Nicolas Brunner; Nicolas Gisin; Sandu Popescu; Valerio Scarani

    2008-11-14T23:59:59.000Z

    With the goal of gaining a deeper understanding of quantum non-locality, we decompose quantum correlations into more elementary non-local correlations. We show that the correlations of all pure entangled states of two qubits can be simulated without communication, hence using only non-signaling resources. Our simulation model works in two steps. First, we decompose the quantum correlations into a local and a non-local part. Second, we present a model for simulating the nonlocal part using only non-signaling resources. In our model partially entangled states require more nonlocal resources than maximally entangled states, but the less the state is entangled, the less frequently must the nonlocal resources be used.

  16. Latina/o Archival Resources

    E-Print Network [OSTI]

    Chu, Clara M.; Dean, Rebecca; Keilty, Patrick; Leong, Lindy

    2009-01-01T23:59:59.000Z

    database which can serve as a resource on and for Hispanics.Latino/a Archival Resources Updated by Clara M. Chu, RebeccaLatino Film and Video Resources Filmmaking Resources Latino

  17. Downscaled climate change impacts on agricultural water resources in Puerto Rico

    E-Print Network [OSTI]

    Harmsen, E.W.

    2010-01-01T23:59:59.000Z

    impacts uncertainty for water resources in the San JoaquinJournal of the American Water Resources Association.approach for surface subsurface water transport modeling in

  18. Resource AdequacyResource Adequacy Advisory Committee

    E-Print Network [OSTI]

    Oct 2016 to Sep 2017 Oct 2018 to Sep 2019 Number of Games 6160 (all comb hydro and wind) 6160 Random 2019 (proposed) Fed Hydro balancing reserves 900 INC and 1100 DEC 900 INC and 1100 DEC NonFed Hydro Energy Imbalance Market Not modeled Not modeled Borrowed hydro 1000 MWperiods 1000 MWperiods Hydro

  19. Jefferson Lab Human Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12 InvestigationLab GroupHuman Resources Human Resources

  20. Jefferson Lab Human Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12 InvestigationLab GroupHuman Resources Human Resources

  1. Resources for Academia | ORNL

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearch > TheNuclear Press ReleasesIn the InorganicResources ResourcesUniversity

  2. Resources | Critical Materials Institute

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearch > TheNuclear Press ReleasesIn the InorganicResourcesResources The

  3. Resources | Jefferson Lab

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Scienceand Requirements RecentlyElectronicResources Resources About one in every four

  4. Resources | 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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's PossibleRadiation Protection TechnicalResonant Soft X-Ray Scattering of0 Resource Resources

  5. Resources: ADEPS: LANL Inside

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's PossibleRadiation Protection TechnicalResonant Soft X-Ray Scattering of0 ResourceADEPS Resources

  6. ORISE Resources: Consumer Health Resource Information Service

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC)Integrated CodesTransparencyDOE Project *1980-1981 U.S. OR I GI N A L SHow

  7. EFRC Resources-Resources-PHaSe-EFRC

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisitingContract ManagementDiscovering HowAnaDynamic SwitchingE xProcess |EEOEFRC

  8. Federating LHCb datasets using the DIRAC File catalog

    E-Print Network [OSTI]

    Haen, Christophe; Frank, Markus; Tsaregorodtsev, Andrei

    2015-01-01T23:59:59.000Z

    In the distributed computing model of LHCb the File Catalog (FC) is a central component that keeps track of each file and replica stored on the Grid. It is federating the LHCb data files in a logical namespace used by all LHCb applications. As a replica catalog, it is used for brokering jobs to sites where their input data is meant to be present, but also by jobs for finding alternative replicas if necessary. The LCG File Catalog (LFC) used originally by LHCb and other experiments is now being retired and needs to be replaced. The DIRAC File Catalog (DFC) was developed within the framework of the DIRAC Project and presented during CHEP 2012. From the technical point of view, the code powering the DFC follows an Aspect oriented programming (AOP): each type of entity that is manipulated by the DFC (Users, Files, Replicas, etc) is treated as a separate 'concern' in the AOP terminology. Hence, the database schema can also be adapted to the needs of a Virtual Organization. LHCb opted for a highly tuned MySQL datab...

  9. Integrated Synthesis of the Permian Basin: Data and Models for Recovering Existing and Undiscovered Oil Resources from the Largest Oil-Bearing Basin in the U.S.

    SciTech Connect (OSTI)

    John Jackson; Katherine Jackson

    2008-09-30T23:59:59.000Z

    Large volumes of oil and gas remain in the mature basins of North America. This is nowhere more true than in the Permian Basin of Texas and New Mexico. A critical barrier to recovery of this vast remaining resource, however, is information. Access to accurate geological data and analyses of the controls of hydrocarbon distribution is the key to the knowledge base as well as the incentives needed by oil and gas companies. The goals of this project were to collect, analyze, synthesize, and deliver to industry and the public fundamental information and data on the geology of oil and gas systems in the Permian Basin. This was accomplished in two ways. First we gathered all available data, organized it, and placed it on the web for ready access. Data include core analysis data, lists of pertinent published reports, lists of available cores, type logs, and selected PowerPoint presentations. We also created interpretive data such as type logs, geological cross sections, and geological maps and placed them in a geospatially-registered framework in ARC/GIS. Second, we created new written syntheses of selected reservoir plays in the Permian basin. Although only 8 plays were targeted for detailed analysis in the project proposal to DOE, 14 were completed. These include Ellenburger, Simpson, Montoya, Fusselman, Wristen, Thirtyone, Mississippian, Morrow, Atoka, Strawn, Canyon/Cisco, Wolfcamp, Artesia Group, and Delaware Mountain Group. These fully illustrated reports include critical summaries of published literature integrated with new unpublished research conducted during the project. As such these reports provide the most up-to-date analysis of the geological controls on reservoir development available. All reports are available for download on the project website and are also included in this final report. As stated in our proposal, technology transfer is perhaps the most important component of the project. In addition to providing direct access to data and reports through the web, we published 29 papers dealing with aspects of Permian Basin and Fort Worth Basin Paleozoic geology, and gave 35 oral and poster presentations at professional society meetings, and 116 oral and poster presentations at 10 project workshops, field trips, and short courses. These events were attended by hundreds of scientists and engineers representing dozens of oil and gas companies. This project and the data and interpretations that have resulted from it will serve industry, academic, and public needs for decades to come. It will be especially valuable to oil and gas companies in helping to better identify opportunities for development and exploration and reducing risk. The website will be continually added to and updated as additional data and information become available making it a long term source of key information for all interested in better understanding the Permian Basin.

  10. Fact #869: April 20, 2015 Gasoline Direct Injection Captures 38% Market Share in Just Seven Years from First Significant Use – Dataset

    Broader source: Energy.gov [DOE]

    Excel file and dataset for Gasoline Direct Injection Captures 38% Market Share in Just Seven Years from First Significant Use

  11. Energy Efficiency Resource Standard

    Broader source: Energy.gov [DOE]

    In 2008, New Mexico enacted H.B. 305, the Efficient Use of Energy Act, which created an Energy Efficiency Resource Standard (EERS) for New Mexico’s electric utilities, and a requirement that all ...

  12. Human Resource Management Delegation

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1996-06-28T23:59:59.000Z

    The notice is to clarifies and updates existing Human Resource Management Delegation Authorities and the levels to which they are delegated. Expired 6-28-97. Does not cancel any directives.

  13. Water Resources Policy & Economics

    E-Print Network [OSTI]

    Buehrer, R. Michael

    Water Resources Policy & Economics FOR 4984 Selected Course Topics · Appropriative and riparian water institutions · Incentives for conservation · Water rights for in-stream environmental use · Surface water-groundwater management · Water quality regulations · Water markets · Economic and policy

  14. Arkansas Water Resources Center

    E-Print Network [OSTI]

    Soerens, Thomas

    Arkansas Water Resources Center DISPOSAL OF HOUSEHOLD WASTEWATER IN SOILS OF HIGH STONE CONTENT Agricultural Engineering and Civil Engineering University of Arkansas Fayetteville, Arkansas 72701 Arkansas and D. T. Mitchell Departments of Agronomy, Agricultural Engineering and Civil Engineering, University

  15. Natural Resource Specialist

    Broader source: Energy.gov [DOE]

    A successful candidate in this position will serve as a Natural Resource Specialist responsible for participating in the development and implementation of short-term and long-term regional (multi...

  16. Geothermal Resources Act (Texas)

    Broader source: Energy.gov [DOE]

    The policy of the state of Texas is to encourage the rapid and orderly development of geothermal energy and associated resources. The primary consideration of the development process is to provide...

  17. Utility Metering- AGL Resources

    Broader source: Energy.gov [DOE]

    Presentation—given at the Spring 2013 Federal Utility Partnership Working Group (FUPWG) meeting—discusses AGL Resources metering, including interruptible rate customers, large users, and meeting federal metering goals.

  18. Geospatial Toolkits and Resource Maps for Selected Countries from the National Renewable Energy Laboratory (NREL)

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    NREL developed the Geospatial Toolkit (GsT), a map-based software application that integrates resource data and geographic information systems (GIS) for integrated resource assessment. A variety of agencies within countries, along with global datasets, provided country-specific data. Originally developed in 2005, the Geospatial Toolkit was completely redesigned and re-released in November 2010 to provide a more modern, easier-to-use interface with considerably faster analytical querying capabilities. Toolkits are available for 21 countries and each one can be downloaded separately. The source code for the toolkit is also available. [Taken and edited from http://www.nrel.gov/international/geospatial_toolkits.html

  19. Resources & Links

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's PossibleRadiation Protection TechnicalResonant Soft X-Ray Scattering of0 Resource

  20. analytical resources securely: Topics by E-print Network

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

    Technologies and Information Sciences Websites Summary: An Analytical Model of Logic Resource Utilization for FPGA Architecture Development by Andrew H Designers constantly...

  1. NATURAL RESOURCES ASSESSMENT

    SciTech Connect (OSTI)

    D.F. Fenster

    2000-12-11T23:59:59.000Z

    The purpose of this report is to summarize the scientific work that was performed to evaluate and assess the occurrence and economic potential of natural resources within the geologic setting of the Yucca Mountain area. The extent of the regional areas of investigation for each commodity differs and those areas are described in more detail in the major subsections of this report. Natural resource assessments have focused on an area defined as the ''conceptual controlled area'' because of the requirements contained in the U.S. Nuclear Regulatory Commission Regulation, 10 CFR Part 60, to define long-term boundaries for potential radionuclide releases. New requirements (proposed 10 CFR Part 63 [Dyer 1999]) have obviated the need for defining such an area. However, for the purposes of this report, the area being discussed, in most cases, is the previously defined ''conceptual controlled area'', now renamed the ''natural resources site study area'' for this report (shown on Figure 1). Resource potential can be difficult to assess because it is dependent upon many factors, including economics (demand, supply, cost), the potential discovery of new uses for resources, or the potential discovery of synthetics to replace natural resource use. The evaluations summarized are based on present-day use and economic potential of the resources. The objective of this report is to summarize the existing reports and information for the Yucca Mountain area on: (1) Metallic mineral and mined energy resources (such as gold, silver, etc., including uranium); (2) Industrial rocks and minerals (such as sand, gravel, building stone, etc.); (3) Hydrocarbons (including oil, natural gas, tar sands, oil shales, and coal); and (4) Geothermal resources. Groundwater is present at the Yucca Mountain site at depths ranging from 500 to 750 m (about 1,600 to 2,500 ft) below the ground surface. Groundwater resources are not discussed in this report, but are planned to be included in the hydrology section of future revisions of the ''Yucca Mountain Site Description'' (CRWMS M&O 2000c).

  2. Resources, framing, and transfer p. 1 Resources, framing, and transfer

    E-Print Network [OSTI]

    Hammer, David

    Resources, framing, and transfer p. 1 Resources, framing, and transfer David Hammer Departments. #12;Resources, framing, and transfer p. 2 Resources, framing, and transfer David Hammer, Andrew Elby of activating resources, a language with an explicitly manifold view of cognitive structure. In this chapter, we

  3. RESOURCE ETH, 1ml RESOURCE ISO, 1 ml

    E-Print Network [OSTI]

    Lebendiker, Mario

    RESOURCE ETH, 1ml RESOURCE ISO, 1 ml RESOURCE PHE, 1 ml RESOURCE HIC Test Kit instructions i 56-1188-26 AB #12;Introduction RESOURCETM ETH (ether), ISO (isopropyl) and PHE (phenyl) are pre-packed high will have the strongest hydrophobicity followed by RESOURCE ISO and RESOUR- CE ETH succesively. Fig. 1

  4. Extracting Skull-Face Models from MRI datasets for use in Craniofacial

    E-Print Network [OSTI]

    Maddock, Steve

    to Esmeralda and my little Alan, To my mother Margarita who taught me to be generous... To my father Jorge who

  5. Identification of Contradictory Patterns in Experimental Datasets for the Development of Models for Electrical Cables

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    for Electrical Cables Diagnostics P. Baraldi1 , M. Compare1 , E. Zio1,2,* , M. de Nigris3 , G. Rizzi3 1 Energy thousands of PD patterns recorded by a software tool that processes the PD measurements when these hal, Availability, Maintainability, and Risk Management of International Journal of Performability Engineering 7, 1

  6. Essex, Massachusetts: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOEHazelPennsylvania: Energy Resources Jump

  7. SU-E-I-87: Automated Liver Segmentation Method for CBCT Dataset by Combining Sparse Shape Composition and Probabilistic Atlas Construction

    SciTech Connect (OSTI)

    Li, Dengwang [Shandong Normal University, Jinan, Shandong Province (China); Liu, Li [Shandong Normal University, Jinan, Shandong (China); Chen, Jinhu; Li, Hongsheng [Shandong Cancer Hospital and Institute, Jinan, Shandong (China)

    2014-06-01T23:59:59.000Z

    Purpose: The aiming of this study was to extract liver structures for daily Cone beam CT (CBCT) images automatically. Methods: Datasets were collected from 50 intravenous contrast planning CT images, which were regarded as training dataset for probabilistic atlas and shape prior model construction. Firstly, probabilistic atlas and shape prior model based on sparse shape composition (SSC) were constructed by iterative deformable registration. Secondly, the artifacts and noise were removed from the daily CBCT image by an edge-preserving filtering using total variation with L1 norm (TV-L1). Furthermore, the initial liver region was obtained by registering the incoming CBCT image with the atlas utilizing edge-preserving deformable registration with multi-scale strategy, and then the initial liver region was converted to surface meshing which was registered with the shape model where the major variation of specific patient was modeled by sparse vectors. At the last stage, the shape and intensity information were incorporated into joint probabilistic model, and finally the liver structure was extracted by maximum a posteriori segmentation.Regarding the construction process, firstly the manually segmented contours were converted into meshes, and then arbitrary patient data was chosen as reference image to register with the rest of training datasets by deformable registration algorithm for constructing probabilistic atlas and prior shape model. To improve the efficiency of proposed method, the initial probabilistic atlas was used as reference image to register with other patient data for iterative construction for removing bias caused by arbitrary selection. Results: The experiment validated the accuracy of the segmentation results quantitatively by comparing with the manually ones. The volumetric overlap percentage between the automatically generated liver contours and the ground truth were on an average 88%–95% for CBCT images. Conclusion: The experiment demonstrated that liver structures of CBCT with artifacts can be extracted accurately for following adaptive radiation therapy. This work is supported by National Natural Science Foundation of China (No. 61201441), Research Fund for Excellent Young and Middle-aged Scientists of Shandong Province (No. BS2012DX038), Project of Shandong Province Higher Educational Science and Technology Program (No. J12LN23), Jinan youth science and technology star (No.20120109)

  8. Essex, Vermont: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOEHazelPennsylvania: Energy Resources JumpVermont: Energy Resources Jump to:

  9. Estacada, Oregon: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOEHazelPennsylvania: Energy Resources JumpVermont: Energy Resources Jump

  10. Ester, Alaska: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOEHazelPennsylvania: Energy Resources JumpVermont: Energy Resources

  11. Estherwood, Louisiana: Energy 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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand JumpConceptual Model,DOEHazelPennsylvania: Energy Resources JumpVermont: Energy ResourcesEstes

  12. Toward a Data Scalable Solution for Facilitating Discovery of Science Resources

    SciTech Connect (OSTI)

    Weaver, Jesse R.; Castellana, Vito G.; Morari, Alessandro; Tumeo, Antonino; Purohit, Sumit; Chappell, Alan R.; Haglin, David J.; Villa, Oreste; Choudhury, Sutanay; Schuchardt, Karen L.; Feo, John T.

    2014-12-31T23:59:59.000Z

    Science is increasingly motivated by the need to process larger quantities of data. It is facing severe challenges in data collection, management, and processing, so much so that the computational demands of “data scaling” are competing with, and in many fields surpassing, the traditional objective of decreasing processing time. Example domains with large datasets include astronomy, biology, genomics, climate/weather, and material sciences. This paper presents a real-world use case in which we wish to answer queries pro- vided by domain scientists in order to facilitate discovery of relevant science resources. The problem is that the metadata for these science resources is very large and is growing quickly, rapidly increasing the need for a data scaling solution. We propose a system – SGEM – designed for answering graph-based queries over large datasets on cluster architectures, and we re- port performance results for queries on the current RDESC dataset of nearly 1.4 billion triples, and on the well-known BSBM SPARQL query benchmark.

  13. Coal resources of Kyrgyzstan

    SciTech Connect (OSTI)

    Landis, E.R.; Bostick, N.H.; Gluskoter, H.J.; Johnson, E.A. [Geological Survey, Denver, CO (United States); Harrison, C.D. [CQ Inc., Homer City, PA (United States); Huber, D.W.

    1995-12-31T23:59:59.000Z

    The rugged, mountainous country of Kyrgyzstan contains about one-half of the known coal resources of central Asia (a geographic and economic region that also includes Uzbekistan, Tadjikistan and Turkmenistan). Coal of Jurassic age is present in eight regions in Kyrgyzstan in at least 64 different named localities. Significant coal occurrences of about the same age are present in the central Asian countries of Kazakhstan, China, and Russia. Separation of the coal-bearing rocks into individual deposits results more than earth movements before and during formation of the present-day mountains and basins of the country than from deposition in separate basins.Separation was further abetted by deep erosion and removal of the coal-bearing rocks from many areas, followed by covering of the remaining coal-bearing rocks by sands and gravels of Cenozoic age. The total resources of coal in Kyrgyzstan have been reported as about 30 billion tons. In some of the reported localities, the coal resources are known and adequately explored. In other parts of the republic, the coal resources are inadequately understood or largely unexplored. The resource and reserve inventory of Kyrgyzstan is at best incomplete; for some purposes, such as short-term local and long-range national planning, it may be inadequate. Less than 8% of the total estimated resources are categorized as recoverable reserves, and the amount that is economically recoverable is unknown. The coal is largely of subbituminous and high-volatile C bituminous rank, most has low and medium ash and sulfur contents, and coals of higher rank (some with coking qualities) are present in one region. It is recommended that appropriate analyses and tests be made during planning for utilization.

  14. Jefferson Lab Human Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12 InvestigationLab Group Gets 10JeffersonHuman Resources

  15. Jefferson Lab Human Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12 InvestigationLab GroupHuman Resources Human

  16. Jefferson Lab Human Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12 InvestigationLab GroupHuman Resources Human print

  17. Jefferson Lab Human Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12 InvestigationLab GroupHuman Resources Human

  18. Jefferson Lab Human Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12 InvestigationLab GroupHuman Resources HumanAppraisal

  19. Jefferson Lab Information Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville PowerCherries 82981-1cnHigh SchoolIn12 InvestigationLab GroupHuman Resources

  20. Resources for Researchers | ORNL

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearch > TheNuclear Press ReleasesIn the InorganicResources

  1. Utilize Available Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengthening aTurbulenceUtilize Available Resources Print As soon as you arrive

  2. CASL - Industry Council Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisiting the TWPSuccess Stories Siteandscience, and8 FY0Link to Resources IndustryCASL

  3. CASL - Industry Council Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadapInactiveVisiting the TWPSuccess Stories Siteandscience, and8 FY0Link to Resources

  4. Small Business Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn April 23, 2014,Zaleski - PolicyWork Force with evenControlDepartment ofSBIRTheResources

  5. Draft 2009 Resource Program

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power AdministrationField Campaign:INEA : Papers69Christopher FeckoDraft Resource Program

  6. New Visualization Tools for Environmental Sensor Networks: Using Google Earth as an Interface to Micro-Climate and Multimedia Datasets

    E-Print Network [OSTI]

    Sean Askay

    2006-01-01T23:59:59.000Z

    to Micro-Climate and Multimedia Datasets A Thesis submittedof micro-climate and multimedia data, there existed noJames Reserve's sensor and multimedia networks. At the time

  7. On Optimizing Joint Inversion of Constrained Geophysical Datasets Anibal Sosa1 Leticia Velazquez1;2, Aaron Velasco3,

    E-Print Network [OSTI]

    Ward, Karen

    of Texas at El Paso, El Paso, Texas 79968-0514, USA 3Department of Geological Sciences, The University) algorithm to characterize 1D earth structure using geophysical datasets with two different optimization

  8. FY13 Summary Report on the Augmentation of the Spent Fuel Composition Dataset for Nuclear Forensics: SFCOMPO/NF

    SciTech Connect (OSTI)

    Brady Raap, Michaele C.; Lyons, Jennifer A.; Collins, Brian A.; Livingston, James V.

    2014-03-31T23:59:59.000Z

    This report documents the FY13 efforts to enhance a dataset of spent nuclear fuel isotopic composition data for use in developing intrinsic signatures for nuclear forensics. A review and collection of data from the open literature was performed in FY10. In FY11, the Spent Fuel COMPOsition (SFCOMPO) excel-based dataset for nuclear forensics (NF), SFCOMPO/NF was established and measured data for graphite production reactors, Boiling Water Reactors (BWRs) and Pressurized Water Reactors (PWRs) were added to the dataset and expanded to include a consistent set of data simulated by calculations. A test was performed to determine whether the SFCOMPO/NF dataset will be useful for the analysis and identification of reactor types from isotopic ratios observed in interdicted samples.

  9. Reference genome sequence of the model plant Setaria

    E-Print Network [OSTI]

    2012-01-01T23:59:59.000Z

    method for rapid multiple sequence alignment based on fastJ.L. Foxtail millet: A sequence-driven grass model system.of Large Biological Sequence Datasets under the Maximum

  10. Colorado Statewide Forest Resource Assessment

    E-Print Network [OSTI]

    Colorado Statewide Forest Resource Assessment A Foundation for Strategic Discussion and Private Forestry Redesign Initiative 2 National Guidance for Statewide Forest Resource Assessments 4 The Colorado Statewide Resource Assessment and all appendices are available online on the Colorado State Forest

  11. Environmental Protection and Natural Resources

    E-Print Network [OSTI]

    Sánchez-Rodríguez, Roberto; Mumme, Stephen

    2010-01-01T23:59:59.000Z

    impacts on U.S. water resources. ” In E. Claussen, V. Arroyoand California Water Resources: A Survey and Summary ofand Gleick, P. 1997. Water Resources Supply and Use in the

  12. Associate Vice President Human Resources

    E-Print Network [OSTI]

    Arnold, Jonathan

    Associate Vice President Human Resources Enjoy Athens! Great schools Affordable housing Eclectic Vice President for Human Resources. This position reports directly to the Vice President for Finance and Administration and provides leadership for the University's human resources programs and services

  13. Human Resources Simon Fraser University

    E-Print Network [OSTI]

    Kavanagh, Karen L.

    Human Resources Simon Fraser University Administrative and Professional Staff Job Description A. Identification Position Number: 31482 Position Title: Administrative Assistant (Human Resources Liaison) Name guidance, direction, coordination and effective management and implementation of SFU's Human Resources

  14. Water Resource Districts (North Dakota)

    Broader source: Energy.gov [DOE]

    Water Resource Districts are created throughout the state of North Dakota to manage, conserve, protect, develop, and control water resources. Each District will be governed by a Water Resource...

  15. Wild Resource Conservation Program (Pennsylvania)

    Broader source: Energy.gov [DOE]

    Established by The Wild Resource Conservation Act of 1982, the Wild Resource Conservation Program is a part of the Department of Conservation and Natural Resources. The program works closely with...

  16. Resources 10:2

    E-Print Network [OSTI]

    1996-01-01T23:59:59.000Z

    i c l e p u b l i s h e d i n Places. PLACES I 0:2 RESOURCESRESOURCES Mayors' Institute Alumni Over the last t e nPreserving and M a n a g i n g Resources Protecting Ties t o

  17. Resource Adequacy Advisory Committeey

    E-Print Network [OSTI]

    ) Total Resources Reported Net Gas-Fired Plants (2017) Import Assumption* "Surplus" Average Min B=D*1 in winter loads (summer didn't matter because we assumed no marketmatter because we assumed no market Report (April 2011) S. to N. Transfer (AC + DC) A B C D E F G 2010 Demand 1:2 Adequacy Requirement (AR

  18. Engineering and Mineral Resources

    E-Print Network [OSTI]

    Mohaghegh, Shahab

    News ????????????????? ® College of Engineering and Mineral Resources Winter 2008 table of contents. . . . . . . . . . . . . . . . . . . . 7 wvCROSSROADS DepartmentofCivilandEnvironmentalEngineering Civil engineering exchange program and environmental engineering with a focus in transportation will have the opportunity to study abroad as part

  19. Generating Resources Advisory Committee

    E-Print Network [OSTI]

    Generating Resources Advisory Committee May 28, 2014 Steve Simmons Gillian Charles #12;2 9:30 AM plants 10:45 AM Break 11:00 AM Peaking Technologies Continued... 11:30 AM Combined Cycle Combustion Turbine and Utility Scale Solar PV Reference plant updates Levelized cost of energy 12:00 PM Lunch

  20. Generating Resources Advisory Committee

    E-Print Network [OSTI]

    Generating Resources Advisory Committee February 27, 2014 Steven Simmons and Gillian Charles Upcoming Symposium 9:15 am Natural Gas Peaking Technologies Technology Trends Proposed reference plant Costing, Economies of Scale, Normalizations Reference Plants 12:30 pm Discussion of Next GRAC Meetings

  1. Resource Engineering MSc Programme

    E-Print Network [OSTI]

    Langendoen, Koen

    on ground-water flows, the safe storage of waste products underground and site remediation after to explore a specific aspect of the field in greater depth. The MSc track in Resource Engineering as the newest mining methods for underground, surface and deep-sea mining. Special attention is paid

  2. Arkansas Water Resources Center

    E-Print Network [OSTI]

    Soerens, Thomas

    :L\\faps 1.1Siteswhere fish (largemouth bass)tissueHg concentrationwere detetned(from 194 i riversArkansas Water Resources Center SPATIAL ANALYSIS OF THE CAUSE OF MERCURY CONTAMINATION OF FISH have beenconcernsabout mercury (Hg) contaminationin fish in Arkansas sincethe discovFryof the problem

  3. Water Resources Milind Sohoni

    E-Print Network [OSTI]

    Sohoni, Milind

    table The water table itself may cross many layers. Extraction of water from confined and unconfinedTD 603 Water Resources Milind Sohoni www.cse.iitb.ac.in/sohoni/ Lecture 5: Aquifer () August 16 above and below the ground, which affect the water balance. surface features affect infiltration

  4. Arkansas Water Resources Center

    E-Print Network [OSTI]

    Soerens, Thomas

    Arkansas Water Resources Center DISPOSAL OF HOUSEHOLD WASTEWATER IN SOILS OF HIGH STONE CONTENT Departments of Agronomy Agricultural Engineering and Civil Engineering University of Arkansas Fayetteville. Harper, H. D. Scott and C. L. Griffis Departments of Agronomy, Agricultural Engineering and Civil

  5. ResourceBounded Information

    E-Print Network [OSTI]

    Raja, Anita

    Query Input l Word processing package for aMac. l $200 price limit. l Search process should take 10 min Features l Active search and discovery. l Resource Bounded Reasoning. l Goal­driven and) C (75% 6) (25% 4) enables Subtask Relation Enables NLE Q = Quality D = Duration C = Cost Task

  6. Arkansas Water Resources Center

    E-Print Network [OSTI]

    Soerens, Thomas

    officials on the new Phase II Storm Water NPDES regulations and Best Management Practices available requirements. In addition, they are typically unaware of Best Management Practices (BMPs) that are availableArkansas Water Resources Center STORMWATER POLLUTION PREVENTION BMP WORKSHOP, DEMONSTRATION

  7. LIBRARY RESOURCES FOR FACULTY

    E-Print Network [OSTI]

    LIBRARY RESOURCES FOR FACULTY #12;Meet Us Pictured here are just a few of the people at the University of Toronto Libraries who support teaching, learning and research every day. Come in and say hello, Information Technology Services and OCUL Scholars Portal staff, Library Instruction, Information Commons Help

  8. Groundwater Everybody's Resource

    E-Print Network [OSTI]

    Groundwater Everybody's Resource Everybody's Responsibility Take Action Now! Michigan Groundwater Stewardship Program Check Inside I Water Cycle . . . . . . . 2 I Groundwater Quiz . . 3 I Risky Practice/ Safe for the benefit of people today and tomorrow. Groundwater is the water that fills spaces between rocks and soil

  9. Mentoring Resources | Argonne National Laboratory

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

    Resources Training & Development Mentoring Safety Program Brochure Postdoctoral Blog Mentoring Resources Divisional Mentoring Program Contacts Mentoring Agreement Argonne Lab-wide...

  10. Go Abroad in Natural ResourcesNatural Resources

    E-Print Network [OSTI]

    Escher, Christine

    Go Abroad in Natural ResourcesNatural Resources Program Contact: Connie Patterson Program.edu/ international The Natural Resources degree is ideally suited for students who wish to study abroad! The sustainable management of natural resources is a fundamental issue, both locally and globally. Scientists

  11. Contributions of Renewable Energy Resources to Re-source Diversity

    E-Print Network [OSTI]

    Gross, George

    1 Contributions of Renewable Energy Resources to Re- source Diversity George Gross, Fellow, IEEE Resources, Environmental Attributes of Renewable Resources PANEL PRESENTATION SUMMARY HE myriad changes of renewable energy resources in meeting future energy needs. The dwindling oil supplies and their in- creasing

  12. Distributed Energy Resources Market Diffusion Model

    E-Print Network [OSTI]

    Maribu, Karl Magnus; Firestone, Ryan; Marnay, Chris; Siddiqui, Afzal S.

    2006-01-01T23:59:59.000Z

    where both optimal installed capacity and profitability varyParameters DER-MaDiM Installed Capacity Energy Consumptiondifferent results, installed capacities, changes in energy

  13. Distributed Energy Resources Market Diffusion Model

    E-Print Network [OSTI]

    Maribu, Karl Magnus; Firestone, Ryan; Marnay, Chris; Siddiqui, Afzal S.

    2006-01-01T23:59:59.000Z

    engines, microturbines, gas turbines, and fuel cells. Byreciprocating engines, gas turbines, and microturbines. Costin the DER-CAM analysis Gas Turbine Capacity (kW) Capital

  14. Datasets - OpenEI Datasets

    Open Energy Info (EERE)

    a purpose and need statement is put together for the Grande Prairie Wind Project. PDF CHP Units in Washington State This is data taken from the website http:www.eea-inc.com...

  15. Beyond heat baths II: Framework for generalized thermodynamic resource theories

    E-Print Network [OSTI]

    Nicole Yunger Halpern

    2014-09-27T23:59:59.000Z

    Cutting-edge experiments, which involve the nano- and quantum scales, have been united with thermodynamics, which describes macroscopic systems, via resource theories. Resource theories have modeled small-scale exchanges of heat and information. Recently, the models were extended to particle exchanges, and a family of thermodynamic resource theories was proposed to model diverse baths, interactions, and free energies. This paper motivates and details the family's structure and prospective applications. How to model electrochemical, gravitational, magnetic, and other thermodynamic systems is explained. Szilard's engine and Landauer's Principle are generalized, as resourcefulness is shown to be convertible not only between informational and gravitational-energy forms, but also among varied physical degrees of freedom in the thermodynamic limit. Quantum operators associated with extensive variables offer opportunities to explore nonclassical noncommutation. This generalization of thermodynamic resource theories invites the modeling of realistic systems that might be harnessed to test small-scale statistical mechanics experimentally.

  16. Beyond heat baths II: Framework for generalized thermodynamic resource theories

    E-Print Network [OSTI]

    Nicole Yunger Halpern

    2015-06-17T23:59:59.000Z

    Thermodynamics, which describes vast systems, has been reconciled with small scales, relevant to single-molecule experiments, in resource theories. Resource theories have been used to model exchanges of energy and information. Recently, particle exchanges were modeled; and an umbrella family of thermodynamic resource theories was proposed to model diverse baths, interactions, and free energies. This paper motivates and details the family's structure and prospective applications. How to model electrochemical, gravitational, magnetic, and other thermodynamic systems is explained. Szilard's engine and Landauer's Principle are generalized, as resourcefulness is shown to be convertible not only between information and gravitational energy, but also among diverse degrees of freedom. Extensive variables are associated with quantum operators that might fail to commute, introducing extra nonclassicality into thermodynamic resource theories. This generalization expands the theories' potential for modeling realistic systems with which small-scale statistical mechanics might be tested experimentally.

  17. Lignocellulosic feedstock resource assessment

    SciTech Connect (OSTI)

    Rooney, T.

    1998-09-01T23:59:59.000Z

    This report provides overall state and national information on the quantity, availability, and costs of current and potential feedstocks for ethanol production in the United States. It characterizes end uses and physical characteristics of feedstocks, and presents relevant information that affects the economic and technical feasibility of ethanol production from these feedstocks. The data can help researchers focus ethanol conversion research efforts on feedstocks that are compatible with the resource base.

  18. Wood Resources International

    E-Print Network [OSTI]

    .3% Sweden 5.3% Finland 4.1% Russia 13.8% US 37.3% Germany 3.3% France 2.8% Poland 2.1% Other Europe 14 International Wood Fuel Removals in Europe 2002 Turkey 12.2% Poland 3.6% Romania 5.3% Hungary 4.1% Germany 7;Wood Resources International Production of energy from wood fuels in 2000 Source: EUBIONET 0 50 100 150

  19. ARM - Other Science Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625govInstrumentstdmadap Documentation TDMADAP : XDCnarrowbandheat fluxChinaNews : AMFAlaskaNews

  20. Resources | Critical Materials Institute

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Scienceand Requirements RecentlyElectronic

  1. warnell school Forestry & Natural Resources

    E-Print Network [OSTI]

    Hall, Daniel

    #12;#12;warnell school Forestry & Natural Resources 2009 Annual Report o #12;VisionTo be recognized as one of the top five forestry and natural resource programs in the United States. Mission's renewable natural resources; and to place latest ideas and technology in forestry and natural resource

  2. warnell school Forestry & Natural Resources

    E-Print Network [OSTI]

    Hall, Daniel

    warnell school Forestry & Natural Resources 2010 Annual Report o #12;VisionTo be recognized as one of the top five forestry and natural resource programs in the United States. MissionTo prepare resources; and to place latest ideas and technology in forestry and natural resource management into real

  3. HUMAN RESOURCES SIMON FRASER UNIVERSITY

    E-Print Network [OSTI]

    and inventories; identification and interviewing of internal resource persons; analysis and synthesis of data

  4. Renewable Energy Resources and Technologies

    Broader source: Energy.gov [DOE]

    Explore the following renewable energy technology areas for resources and information focusing on Federal application opportunities.

  5. Wind Resource Assessment of Gujarat (India)

    SciTech Connect (OSTI)

    Draxl, C.; Purkayastha, A.; Parker, Z.

    2014-07-01T23:59:59.000Z

    India is one of the largest wind energy markets in the world. In 1986 Gujarat was the first Indian state to install a wind power project. In February 2013, the installed wind capacity in Gujarat was 3,093 MW. Due to the uncertainty around existing wind energy assessments in India, this analysis uses the Weather Research and Forecasting (WRF) model to simulate the wind at current hub heights for one year to provide more precise estimates of wind resources in Gujarat. The WRF model allows for accurate simulations of winds near the surface and at heights important for wind energy purposes. While previous resource assessments published wind power density, we focus on average wind speeds, which can be converted to wind power densities by the user with methods of their choice. The wind resource estimates in this study show regions with average annual wind speeds of more than 8 m/s.

  6. International H2O Project (IHOP) 2002: Datasets Related to Atmospheric Moisture and Rainfall Prediction

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Schanot, Allen [IHOP 2002 PI; Friesen, Dick [IHOP 2002 PI

    IHOP 2002 was a field experiment that took place over the Southern Great Plains of the United States from 13 May to 25 June 2002. The chief aim of IHOP_2002 was improved characterization of the four-dimensional (4-D) distribution of water vapor and its application to improving the understanding and prediction of convection. The region was an optimal location due to existing experimental and operational facilities, strong variability in moisture, and active convection [copied from http://www.eol.ucar.edu/projects/ihop/]. The project's master list of data identifies 146 publicly accessible datasets.

  7. Biomass Resource Allocation among Competing End Uses

    SciTech Connect (OSTI)

    Newes, E.; Bush, B.; Inman, D.; Lin, Y.; Mai, T.; Martinez, A.; Mulcahy, D.; Short, W.; Simpkins, T.; Uriarte, C.; Peck, C.

    2012-05-01T23:59:59.000Z

    The Biomass Scenario Model (BSM) is a system dynamics model developed by the U.S. Department of Energy as a tool to better understand the interaction of complex policies and their potential effects on the biofuels industry in the United States. However, it does not currently have the capability to account for allocation of biomass resources among the various end uses, which limits its utilization in analysis of policies that target biomass uses outside the biofuels industry. This report provides a more holistic understanding of the dynamics surrounding the allocation of biomass among uses that include traditional use, wood pellet exports, bio-based products and bioproducts, biopower, and biofuels by (1) highlighting the methods used in existing models' treatments of competition for biomass resources; (2) identifying coverage and gaps in industry data regarding the competing end uses; and (3) exploring options for developing models of biomass allocation that could be integrated with the BSM to actively exchange and incorporate relevant information.

  8. Texas Water Resources Institute Annual Technical Report

    E-Print Network [OSTI]

    &M University (7 projects), Texas Tech University (1), West Texas A&M University (1), and the University. West Texas A&M University Student, Robert Taylor, conducted a pricing model to assess the effectsTexas Water Resources Institute Annual Technical Report FY 2006 #12;Introduction The Texas Water

  9. COMPUTATION AND ACTION UNDER BOUNDED RESOURCES

    E-Print Network [OSTI]

    Horvitz, Eric

    of Philosophy. Ronald A. Howard Department of Engineering--Economic Systems Stanford University (Principal resources. The model provides a perspective on the use of metareasoning techniques to balance the costs among observations and hypotheses. I found that it can be valuable to allocate a portion of costly

  10. COMPUTATION AND ACTION UNDER BOUNDED RESOURCES

    E-Print Network [OSTI]

    Horvitz, Eric

    of Philosophy. Ronald A. Howard Department of Engineering­Economic Systems Stanford University (Principal resources. The model provides a perspective on the use of metareasoning techniques to balance the costs among observations and hypotheses. I found that it can be valuable to allocate a portion of costly

  11. 1999 Pacific Northwest Loads and Resources Study.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    1999-12-01T23:59:59.000Z

    The Pacific Northwest Loads and Resources Study (White Book) is published annually by BPA and establishes the planning basis for supplying electricity to customers. It serves a dual purpose. First, the White Book presents projections of regional and Federal system load and resource capabilities, along with relevant definitions and explanations. Second, the White Book serves as a benchmark for annual BPA determinations made pursuant to its regional power sales contracts. Specifically, BPA uses the information in the White Book for determining the notice required when customers request to increase or decrease the amount of power purchased from BPA. The White Book will not be used in calculations for the 2002 regional power sales contract subscription process. The White Book compiles information obtained from several formalized resource planning reports and data submittals, including those from the Northwest Power Planning Council (Council) and the Pacific Northwest Utilities Conference Committee (PNUCC). The White Book is not an operational planning guide, nor is it used for determining BPA revenues. Operation of the Federal Columbia River Power System (FCRPS) is based on a set of criteria different from that used for resource planning decisions. Operational planning is dependent upon real-time or near-term knowledge of system conditions, including expectations of river flows and runoff, market opportunities, availability of reservoir storage, energy exchanges, and other factors affecting the dynamics of operating a power system. In this loads and resources study, resource availability is compared with a medium forecast of electricity consumption. The forecasted future electricity demands--firm loads--are subtracted from the projected capability of existing and ''contracted for'' resources to determine whether BPA and the region will be surplus or deficit. If Federal system resources are greater than loads in any particular year or month, there is a surplus of energy and/or capacity, which BPA may use or market to increase revenues. Conversely, if Federal system firm loads exceed available resources, there is a deficit of energy and/or capacity and BPA would add conservation or contract purchases as needed to meet its firm loads. The load forecast is derived by using econometric models and analysis to predict the loads that will be placed on electric utilities in the region. This study incorporates information on contract obligations and contract resources, combined with the resource capabilities obtained from public utility and investor-owned utility (IOU) customers through their annual data submittals to the PNUCC, from BPA's Firm Resource Exhibit (FRE Exhibit I) submittals, and through analysis of the Federal hydroelectric power system. The loads and resources analysis in this study simulates the operation of the power system under the Pacific Northwest Coordination Agreement (PNCA) produced by the Pacific Northwest Coordinating Group. The PNCA defines the planning and operation of the regional hydrosystem. The 1999 White Book is presented in two documents: (1) this summary of Federal system and Pacific Northwest region loads and resources; and (2) a technical appendix (available electronically only) detailing the loads and resources for each major Pacific Northwest generating utility. This analysis updates the December 1998 Pacific Northwest Loads and Resources Study. This analysis projects the yearly average energy consumption and resource availability for Operating Years (OY) 2000-01 through 2009-10. The study shows the Federal system's and the region's monthly estimated maximum electricity demand, monthly energy demand, monthly energy generation, and monthly maximum generating capability--capacity--for OY 2000-01, 2004-05, and 2009-10. The Federal system and regional monthly capacity surplus/deficit projections are summarized for 10 operating years. This document analyzes the Pacific Northwest's projected loads and available generating resources in two parts: (1) the loads and resources of the Federal system, for wh

  12. National Geothermal Resource Assessment and Classification |...

    Office of Environmental Management (EM)

    Resource Assessment and Classification National Geothermal Resource Assessment and Classification National Geothermal Resource Assessment and Classification presentation at the...

  13. Distributed Energy Resources for Carbon Emissions Mitigation

    E-Print Network [OSTI]

    Firestone, Ryan; Marnay, Chris

    2008-01-01T23:59:59.000Z

    Distributed Energy Resource Technology Characterizations. ”ABORATORY Distributed Energy Resources for Carbon Emissions5128 Distributed Energy Resources for Carbon Emissions

  14. ARM - CHAPS: Campaign Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearchSOLICITATIONIMODI FICATION OFMaterialsAnnualProjectMeasurements

  15. CMPC Marking Resource

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy China U.S. Department ofJune 2,The BigSidingState6Report, March003MEAM, MDEA, and

  16. Employee, Retiree Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItem NotEnergy,ARMFormsGasRelease Date:researchEmerging Threats and

  17. Fermilab | Resources for ...

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItem NotEnergy,ARMFormsGasReleaseSpeechesHall A This photophotoReleases Subscribe

  18. Fermilab | Resources | Industrial Partnerships

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItem NotEnergy,ARMFormsGasReleaseSpeechesHall A This photophotoReleases

  19. NETL: Natural Gas Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC)Integrated Codes |IsLoveReferenceAgenda Workshop AgendaGraphic of aEnergy

  20. Tri-Lab Resources

    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: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron Spin Transition in2,EHSS A-Z Site MapTrends, Discovery, &Tri-Lab