Influence of wind speed on solar pv plant power production—prediction model using decision-based artificial neural network

Abstract

An effort has been made to study the different factors influencing the output of a solar photovoltaic (PV) plant. Environmental factors play a significant role in planning the placement of PV modules. Various factors like irradiation, wind speed, atmospheric temperature and cloud coverage affect the power obtained from the plant. Establishing a relationship between the multiple factors and the output of the plant makes it easy to decide and plan the site of installation of the module and for further research purposes. The effect of wind speed on the power output of S. N. Mohanty solar plant located in Patapur, Cuttack (Odisha, IN) is studied. The research work has been carried out with data acquired every 15 min from January 2015 to December 2015 and keeping the irradiation constant. The monthly plots help establish a relationship between the wind speed and the power generated from the plant. The data is then used to create and train a neural network model which is used to predict the power output of the plant given the appropriate input data. This paper demonstrates the training of artificial neural network using environmental and PV module data (module temperature, wind speed and month).