ANN and PSO based Approach for Solar Energy Forecasting: A Step Towards Sustainable Power Generation

Abstract

For proper designing and development of solar photovoltaic system, forecasting of solar energy becomes very important. Power developed by the solar photovoltaic system depends upon meteorological parameters like temperature solar irradiance. Variation in these parameters causes variation in power generated by the photovoltaic system. Hence forecasting becomes important. In this paper solar energy forecasting is done using artificial neural network and particle swarm optimization based artificial neural network. Artificial neural network is well established method used for forecasting purpose. However there output can further be improved by applying optimization technique. Here particle swarm optimization technique is used MATLAB software is used for coding the optimized neural network and ‘nftool’ application is used for simple artificial neural network. For ANN percentage error comes out to be 4.18% and for ANN-PSO it comes out to be 3.23%.