Estimation of photovoltaic generation forecasting models using limited information. (March 2020)

• Record Type: Journal Article
• Authors: Bianchini, Gianni; Pepe, Daniele; Vicino, Antonio
• Is Part Of: Automatica. Volume 113(2020)
• Publication Date: 2020-03
• Subjects: Energy systems -- Model fitting -- Forecasting -- Photovoltaic generation; Automatic control -- Periodicals; Automation -- Periodicals; 629.805
• DOI: 10.1016/j.automatica.2019.108688
• Languages: English
• ISSNs: 0005-1098

Abstract

Abstract: This work deals with the problem of estimating a photovoltaic generation forecasting model in scenarios where measurements of meteorological variables (i.e., solar irradiance and temperature) at the plant site are not available. A novel algorithm for the estimation of the parameters of the well-known PVUSA model of a photovoltaic plant is proposed. Such a method is characterized by a low computational complexity, and efficiently exploits only power generation measurements, a theoretical clear-sky irradiance model, and temperature forecasts provided by a meteorological service. The proposed method is validated on real data.