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. An extensive experimental validation of the proposed method on real data is also presented.
@article{arxiv.1903.04827,
title = {Estimation of Photovoltaic Generation Forecasting Models using Limited Information},
author = {Gianni Bianchini and Daniele Pepe and Antonio Vicino},
journal= {arXiv preprint arXiv:1903.04827},
year = {2019}
}