A Data-Driven Game-Theoretic Approach for Behind-the-Meter PV Generation Disaggregation

Bu, Fankun; Dehghanpour, Kaveh; Yuan, Yuxuan; Wang, Zhaoyu; Zhang, Yingchen

doi:10.1109/tpwrs.2020.2966732

A Data-Driven Game-Theoretic Approach for Behind-the-Meter PV Generation Disaggregation

Journal Article · Wed Jan 15 00:00:00 EST 2020 · IEEE Transactions on Power Systems

DOI:https://doi.org/10.1109/tpwrs.2020.2966732· OSTI ID:1961205

^[1]; ^[2]; Yuan, Yuxuan ^[2]; ^[2]; ^[3]

Iowa State Univ., Ames, IA (United States); Iowa State University
Iowa State Univ., Ames, IA (United States)
National Renewable Energy Lab. (NREL), Golden, CO (United States)

Rooftop solar photovoltaic (PV) power generator is a widely used distributed energy resource (DER) in distribution systems. Currently, the majority of PVs are installed behind-the-meter (BTM), where only customers' net demand is recorded by smart meters. Disaggregating BTM PV generation from net demand is critical to utilities for enhancing grid-edge observability. In this paper, a data-driven approach is proposed for BTM PV generation disaggregation using solar and demand exemplars. First, a data clustering procedure is developed to construct a library of candidate load/solar exemplars. To handle the volatility of BTM resources, a novel game-theoretic learning process is proposed to adaptively generate optimal composite exemplars using the constructed library of candidate exemplars, through repeated evaluation of disaggregation residuals. Lastly, the composite native demand and solar exemplars are employed to disaggregate solar generation from net demand using a semi-supervised source separator. The proposed methodology has been verified using real smart meter data and feeder models.

View Accepted Manuscript (DOE)

Research Organization:: Iowa State Univ., Ames, IA (United States)

Sponsoring Organization:: USDOE Office of Electricity (OE)

Grant/Contract Number:: OE0000875

OSTI ID:: 1961205

Alternate ID(s):: OSTI ID: 1660067

Journal Information:: IEEE Transactions on Power Systems, Journal Name: IEEE Transactions on Power Systems Journal Issue: 4 Vol. 35; ISSN 0885-8950

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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14 SOLAR ENERGY
Rooftop solar photovoltaic
distribution system
game theory
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