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DOE OSTI · 2484228

Performance Year 1 Technical Report - OPEN COG Grid: Extendable Coherent Models-Datasets for Cognitive Power Grids

Aravena, Ignacio [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)]·Sun, Chih-Che Ryan [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)]·Joo, Jhi-Young [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)]·Xie, Le [Texas A & M Univ., College Station, TX (United States)]·Majumder, Subir [Texas A & M Univ., College Station, TX (United States)]·Shi, Sienna [Texas A & M Univ., College Station, TX (United States)]·Peng, Jiangkai [National Renewable Energy Laboratory (NREL), Golden, CO (United States)]·Zhu, Xiangqi [National Renewable Energy Laboratory (NREL), Golden, CO (United States)]·Wang, Jiyu [National Renewable Energy Laboratory (NREL), Golden, CO (United States)]·Yang, Weihang [National Renewable Energy Laboratory (NREL), Golden, CO (United States)]
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Abstract

The OPEN COG Grid project is a collaborative effort between LLNL, NREL, and Texas A&M University (TAMU) to develop synthetic power system datasets that (i) contain all technical information that would be available in a real system, allowing to conduct studies ranging from dynamic simulation to long term planning studies; ii) are accessible to researchers from the broader data sciences community, as oppossed to power system experts only; and (iii) This report summarizes the work conducted during the first 15 months of execution of the project. These activities encompassed: 1. Conduct a survey of existing open data sets and open source power systems simulators, their supported use cases, and accessibility (Chapter 1). 2. Define a new extensible specification for power system data, covering all parameters necessary for most computational use cases (Chapter 2). 3. Collecting real technical system data to complete missing parameters in existing open source datasets (Chapter 3). 4. Develop models that capture the behavior of emergent actors in power grids, neglected by existing datasets; aggregated residential demand response (Chapter 4) and demand response of cryptocurrency miners (Chapter 5). 5. Collect detailed spatial information on distributed energy resources, particular, solar photovoltaic facilities (Chapter 6). The following chapters provide detailed descriptions of these tasks, the assumptions taken, and their findings. In conducting these tasks, the project team produced: two (accepted) conference papers; one journal paper under submission; one draft journal paper pending submission; released one repository with the developed power system data specification, with documentation and examples; and one extended dataset for the Texas power grid under review for release. The team hopes these contributions will enhance access to power system data and remove barriers to the development of new computational techniques for power systems, particularly, those inspired by cognitive sciences.

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BibTeXRIS

Aravena, Ignacio [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)], Sun, Chih-Che Ryan [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)], Joo, Jhi-Young [Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)], Xie, Le [Texas A & M Univ., College Station, TX (United States)], Majumder, Subir [Texas A & M Univ., College Station, TX (United States)], Shi, Sienna [Texas A & M Univ., College Station, TX (United States)], Peng, Jiangkai [National Renewable Energy Laboratory (NREL), Golden, CO (United States)], Zhu, Xiangqi [National Renewable Energy Laboratory (NREL), Golden, CO (United States)], Wang, Jiyu [National Renewable Energy Laboratory (NREL), Golden, CO (United States)], Yang, Weihang [National Renewable Energy Laboratory (NREL), Golden, CO (United States)]. 2024-12-06. Performance Year 1 Technical Report - OPEN COG Grid: Extendable Coherent Models-Datasets for Cognitive Power Grids. https://doi.org/10.2172/2484228

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