Application of neural network to 24-hour-ahead generating power forecasting for PV system

In recent years, focus has been on environmental pollution issue resulting from consumption of fossil fuels, e.g., coal and oil. Thus, introduction of an alternative energy source such as solar energy is expected. However, insolation is not constant and output of photovoltaic (PV) system is influenced by meteorological conditions. In order to predict the power output for a PV system as accurately as possible, a method for insolation estimation is required. In this paper, the authors take the insolation of each month into consideration, and confirm the validity of using neural network to predict insolation by computer simulations. The proposed method utilizes any meteorological data and does not require complicated calculation and mathematical model.