ANN-Based Large-Scale Cooperative Solar Generation Forecasting

Abstract

In this work we introduce the concept and method of so-called cooperative solar generation forecasting, where geographically close data sources are utilized in order to improve forecasting accuracy. We devised and examined various large scale one-hour-ahead artificial neural networks based solar generation forecasting scenarios to prove the benefits of cooperation. The introduced cooperative solar generation forecasting method showed significant improvement in forecasting accuracy, especially when combined with previous generation data, where a root mean square error reduction of at least 50% could be achieved in the majority of cases. We believe these results point to a scientific and economical benefit of international cooperation in solar generation forecasting.