Short-term probabilistic forecasting models using Beta distributions for photovoltaic plants

Abstract

This article presents original probabilistic forecasting models for day-ahead hourly energy generation forecasts for a photovoltaic (PV) plant, based on a semi-parametric approach using three deterministic forecasts. Input information of these new models consists of data of hourly weather forecasts obtained from a Numerical Weather Prediction model and variables related to the sun position for future instants. The proposed models were satisfactorily applied to the case study of a real-life PV plant in Portugal. Probabilistic benchmark models were also applied to the same case study and their forecasting results compared with the ones of the proposed models. The computer results obtained with these proposed models achieve better point and probabilistic forecasting evaluation indexes values than the ones obtained with the benchmark models.