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

Journal Article · Fri Mar 20 00:00:00 EDT 2020 · IEEE Transactions on Smart Grid

DOI:https://doi.org/10.1109/tsg.2020.2981077· OSTI ID:1606127

Krishnan, Venkat ^[1]; Bugbee, Bruce ^[1]; Elgindy, Tarek ^[1]; Mateo, Carlos ^[2]; Duenas, Pablo ^[3]; Postigo, Fernando ^[2]; Lacroix, Jean-Sebastien ^[4]; Roman, Tomas San ^[2]; Palmintier, Bryan ^[1]

---

1. National Renewable Energy Lab. (NREL), Golden, CO (United States). Power Systems Engineering Center
2. Comillas Pontifical Univ., Madrid (Spain). Inst. for Research in Technology
3. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). MIT Energy Initiative
4. Eaton Corp., St-Bruno-de-Montarville, QC (Canada); BBA, Mont-Saint-Hilaire, QC (Canada)

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. Furthermore, 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.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Advanced Research Projects Agency - Energy (ARPA-E)
• Grant/Contract Number: AC36-08GO28308
• OSTI ID: 1606127
• Report Number(s): NREL/JA-5D00-72584; MainId:21564; UUID:c08dff0b-05cc-e811-9c19-ac162d87dfe5; MainAdminID:10040
• Journal Information: IEEE Transactions on Smart Grid, Journal Name: IEEE Transactions on Smart Grid Journal Issue: 5 Vol. 11; ISSN 1949-3053
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
electric distribution test feeders
power flow
smart grid use case
statistical metrics
synthetic data sets
validation