Neural network based estimation of maximum power generation from PV module using environmental information

This paper presents an application of an artificial neural network for the estimation of maximum power generation from PV module. The output power from a PV module depends on environmental factors such as irradiation and cell temperature. For the operation planning of power systems, the prediction of the power generation is inevitable for PV systems. For this purpose, irradiation, temperature and wind velocity are utilized as the input information to the proposed neural network. The output is the predicted maximum power generation under the condition given by those environmental factors. The efficiency of the proposed estimation scheme is evaluated by using actual data on daily, monthly and yearly bases. The proposed method gives highly accurate predictions compared with predictions using the conventional multiple regression model.