Journal
IEEE TRANSACTIONS ON SMART GRID
Volume 11, Issue 5, Pages 4477-4489Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2020.2981077
Keywords
Hafnium; 6G mobile communication; Germanium; Electric distribution test feeders; synthetic data~sets; validation; statistical metrics; power flow; smart grid use case
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Funding
- U.S. Department of Energy (DOE) [DE-AC36-08GO28308]
- Advanced Research Projects Agency-Energy (ARPA?E) under the GRID DATA Program
- Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE)
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There is a strong need for synthetic yet realistic distribution system test data sets that are as diverse, large, and complex to solve as real systems. Such data sets can facilitate the development of advanced algorithms and the assessment of emerging distributed energy resources while avoiding the need to acquire proprietary critical infrastructure or private data. Such synthetic data sets, however, are useful only if they are realistic enough to look and behave similarly to actual systems. This paper presents a comprehensive framework for validating synthetic distribution data sets using a three-pronged statistical, operational, and expert validation approach. It also presents a set of statistical and operational metric targets for achieving realistic data sets based on detailed characterization of more than 10,000 real U.S. utility feeders. The paper demonstrates the use of the proposed validation approach to validate three large-scale synthetic data sets developed by the authors representing Santa Fe, New Mexico; Greensboro, North Carolina; and the San Francisco Bay Area, California.
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