A study of solar radiation forecasting based on weather classification using clustering

Abstract

In this paper, we aim to improve the accuracy of solar radiation prediction used for photovoltaic power generation by constructing a classification model that captures the characteristics of weather data. In our previous studies, we used the weather conditions published by the Japan Meteorological Agency for classification. In this study, we use a clustering method, which is unsupervised learning, for weather classification to create a new weather situation classification. We aim to improve the accuracy by constructing a weather situation classification model that is more suitable for solar radiation prediction than before.