Predictive Analysis of Photovoltaic Power Generation Using Deep Learning

Abstract

A novel deep learning approach is proposed for the predictive analysis of trends in energy related time series, in particular those relevant to photovoltaic systems. Aim of the proposed approach is to grasp the trend of the time series, namely, if the series goes up, down or keep stable, instead of predicting the future numerical value. The modeling system is based on Long Short-Term Memory networks, which are a type of recurrent neural network able to extract information in samples located very far from the current one. This new approach has been tested in a real-world case study showing good robustness and accuracy.