Extreme Photovoltaic Power Analytics for Electric Utilities

Obtaining high-fidelity information on extreme photovoltaic (PV) power is critical for electric utilities in system planning and operation. However, a scarcity of extreme data has made achieving an accurate estimate of extreme PV power a previously intractable challenge. In response to this challenge, this paper presents an Extreme PV power Analytics (EPVA). It develops k-means clustering to determine which PV systems have similar behaviors in terms of the extreme capacity factor (ECF) such that more extreme data can be combined for the purposes of conducting an extreme value analysis. This extreme value analysis is subsequently applied to obtain the distribution of ECFs. Zone partitioning results and ECF distribution results for The United Illuminating Company (UI) service territory are presented to validate the effectiveness and efficacy of EPVA.