A review of behind-the-meter solar forecasting. (May 2022)

• Record Type: Journal Article
• Authors: Erdener, Burcin Cakir; Feng, Cong; Doubleday, Kate; Florita, Anthony; Hodge, Bri-Mathias
• Is Part Of: Renewable & sustainable energy reviews. Volume 160(2022)
• Publication Date: 2022-05
• Subjects: Behind-the-meter -- Solar forecasting -- Solar photovoltaic; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2022.112224
• Languages: English
• ISSNs: 1364-0321

Abstract

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. Highlights: Behind-the-meter PV forecasting has the potential to impact power system operations. Precise estimation of BTM PV capacity is challenging due to partially recorded data. Capacity and specification estimation is often needed for reasonable BTM PV forecast.