A Review of Behind-the-Meter Solar Forecasting

Burcin Cakir Erdener, Cong Feng, Kate Doubleday, Anthony Florita, Bri-Mathias Hodge

Research output: Contribution to journalArticlepeer-review

31 Scopus Citations

Abstract

Solar photovoltaic systems largely integrated within the distribution grid are operated ‘behind-the-meter’ and power generation cannot be directly monitored by most utilities. The increasing penetration of behind-the-meter solar photovoltaic systems can deter efficient network and market operations due to variability and uncertainty in net load, which is exacerbated by limited visibility and the difficulty in analyzing the hosting capacity. Risk introduced by behind-the-meter solar contributions may hinder reliable and secure grid operations due to biased system monitoring and forecasts. Accurate behind-the-meter estimations, together with capacity and specification forecasts, thus play a key role in balancing supply and demand and this article reviews the pertinent literature, identifying key characteristics and predictive methods for efficient behind-the-meter solar photovoltaic generation. Forecasting is central to methods herein. The fundamental characteristics of behind-the-meter solar forecasting, including which methods are applicable for scenario-driven use cases, are driven by the metrics most useful for system-wide performance evaluation. To this aim, the literature is reviewed with a focus on forecasting applications for aggregate, regional behind-the-meter generation useful to bulk system and utility operations. As distinguished from net load forecasting, subtleties in these coincident tasks are explored before concluding with recommendations for current practice and future implementations.

Original languageAmerican English
Article number112224
Number of pages18
JournalRenewable and Sustainable Energy Reviews
Volume160
DOIs
StatePublished - May 2022

Bibliographical note

Publisher Copyright:
© 2022

NREL Publication Number

  • NREL/JA-5D00-79550

Keywords

  • Behind-the-meter
  • Solar forecasting
  • Solar photovoltaic

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