Short-Term PV Power Forecasting Using Adaptive Neuro-Fuzzy Inference System

Due to the rapid increase in electricity demand and dwindling energy resources, people have begun to think about renewable energy resources. Solar photovoltaic energy is the dominating source of renewable energy. In this paper, the ANFIS model (adaptive neuro-fuzzy inference systems) is used to predict photovoltaic power. One-year historical data for PV, direct solar radiation, diffuse solar radiation and temperature are used for training and testing purposes. The forecasted result of the model is appreciable and evidence shows that the prediction error of the proposed model has significantly good accuracy with the other existing models.