A Hybrid Model for Solar Radiation Forecasting towards Energy Efficient Buildings

Solar radiation forecasting is developed for electricity utilization in buildings to improve energy efficiency. In this paper, we first compare different machine learning methods for single-step solar radiation prediction, including multilayer perceptron (MLP), long short-term memory (LSTM), gradient boosting regression tree (GBRT), random forest (RF) and Informer. Then, we propose a hybrid model for short-term solar irradiation prediction, which is composed of a random forest model and an Informer model. Simulation results illustrate the effectiveness of our proposed hybrid model for balancing the accuracy-complexity tradeoff.