Extreme Photovoltaic Power Analytics for Electric Utilities

Obtaining high-fidelity information on extreme photovoltaic (PV) power is critical for electric utility system planning and operations. However, a scarcity of extreme data has previously made achieving an accurate estimate of extreme PV power an intractable challenge. In response to this challenge, this paper presents Extreme PV Power Analytics (EPVA). It utilizes k-means clustering to determine which PV systems have similar behaviors in their extreme capacity factors (ECFs) in order to incorporate more extreme data in 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 service territory are presented to validate the effectiveness and efficacy of EPVA.