Research output per year
Research output per year
Clayton Barrows*, Eugene Preston, Andrea Staid, Gord Stephen, Jean Paul Watson, Aaron Bloom, Ali Ehlen, Jussi Ikäheimo, Jennie Jorgenson, Dheepak Krishnamurthy, Jessica Lau, Brendan McBennett, Matthew O'Connell
Research output: Contribution to journal › Article › Scientific › peer-review
Original language | English |
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Article number | 8753693 |
Pages (from-to) | 119-127 |
Journal | IEEE Transactions on Power Systems |
Volume | 35 |
Issue number | 1 |
DOIs | |
Publication status | Published - Jan 2020 |
MoE publication type | A1 Journal article-refereed |
Manuscript received August 22, 2018; revised January 8, 2019 and May 8, 2019; accepted June 16, 2019. Date of publication July 2, 2019; date of current version January 7, 2020. This work was supported by the Department of Energy’s Grid Modernization Initiative. Paper no. TPWRS-01297-2018. (Corresponding author: Clayton Barrows.) C. Barrows, A. Bloom, A. Ehlen, J. Jorgenson, D. Krishnamurthy, J. Lau, B. McBennett, M. O’Connell, and G. Stephen are with the National Renewable Energy Laboratory, Lakewood, CO 80401 USA (e-mail: [email protected]; [email protected]; [email protected]; [email protected]; [email protected]; jessica.lau@ nrel.gov; [email protected]; [email protected]; [email protected]). This work was made possible by the U.S. Department of Energy’s (DOE) Grid Modernization Initiative, which supports the Grid Modernization Laboratory Consortium. The authors would particularly like to thank Charlton Clark (Office of Energy Efficiency) and Kerry Cheung (Office of Electricity) at the DOE for their support. They would also like to acknowledge Rafael Castro (Polaris) and Hooman Ghaffarzadeh (Washington State University) for creating software-specific versions of the RTS-GMLC, Bethany Frew for her support and review, and the dozens of online collaborators who continue to contribute to and develop the RTS-GMLC model. This work was authored in part by Alliance for Sustainable Energy, LLC, the manager and operator of the National Renewable Energy Laboratory for the U.S. Department of Energy (DOE) under Contract DE-AC36-08GO28308. The views expressed in this paper do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. A portion of the research was performed using computational resources sponsored by the Department of Energy’s Office of Energy Efficiency and Renewable Energy and located at the National Renewable Energy Laboratory. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under Contract DE-NA-0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government.
Research output: Non-textual form › Software › Scientific