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Title: Validation of Synthetic U.S. Electric Power Distribution System Data Sets

Abstract

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.

Authors:
ORCiD logo [1];  [1]; ORCiD logo [1];  [2];  [3];  [2];  [4]; ORCiD logo [1];  [2]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. Comillas Pontifical University
  3. Massachusetts Institute of Technology
  4. Eaton Corporation
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
U.S. Department of Energy, Advanced Research Projects Agency-Energy (ARPA-E)
OSTI Identifier:
1606127
Report Number(s):
NREL/JA-5D00-72584
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article
Journal Name:
IEEE Transactions on Smart Grid
Additional Journal Information:
Journal Name: IEEE Transactions on Smart Grid
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; electric distribution test feeders; synthetic data sets; validation; statistical metrics; power flow; smart grid use case

Citation Formats

Krishnan, Venkat K, Bugbee, Bruce, Elgindy, Tarek, Mateo, Carlos, Duenas, Pablo, Postigo, Fernando, Lacroix, Jean-Sebastien, Palmintier, Bryan S, and Gomez San Roman, Tomas. Validation of Synthetic U.S. Electric Power Distribution System Data Sets. United States: N. p., 2020. Web. doi:10.1109/TSG.2020.2981077.
Krishnan, Venkat K, Bugbee, Bruce, Elgindy, Tarek, Mateo, Carlos, Duenas, Pablo, Postigo, Fernando, Lacroix, Jean-Sebastien, Palmintier, Bryan S, & Gomez San Roman, Tomas. Validation of Synthetic U.S. Electric Power Distribution System Data Sets. United States. doi:10.1109/TSG.2020.2981077.
Krishnan, Venkat K, Bugbee, Bruce, Elgindy, Tarek, Mateo, Carlos, Duenas, Pablo, Postigo, Fernando, Lacroix, Jean-Sebastien, Palmintier, Bryan S, and Gomez San Roman, Tomas. Fri . "Validation of Synthetic U.S. Electric Power Distribution System Data Sets". United States. doi:10.1109/TSG.2020.2981077.
@article{osti_1606127,
title = {Validation of Synthetic U.S. Electric Power Distribution System Data Sets},
author = {Krishnan, Venkat K and Bugbee, Bruce and Elgindy, Tarek and Mateo, Carlos and Duenas, Pablo and Postigo, Fernando and Lacroix, Jean-Sebastien and Palmintier, Bryan S and Gomez San Roman, Tomas},
abstractNote = {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.},
doi = {10.1109/TSG.2020.2981077},
journal = {IEEE Transactions on Smart Grid},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {3}
}