Comparison of Various Meteorological Parameters for Solar Radiation Prediction Using Artificial Neural Network

Renewable energy sources are currently considered an alternative source of energy because they swiftly regenerate themselves and may be utilized repeatedly. Weather, time of day, and geographic location all affect solar radiation. In the proposed work, solar radiation is predicted using an Artificial Neural Network (ANN) model. The prediction of diffuse insolation under a clear sky is done using the neural fitting tool (nftool). The suggested ANN model's mean square error and regression values are generated using the various meteorological data, such as humidity, air temperature, atmospheric pressure, and the number of days in the year, as input. The performance of the forecast solar radiation is then assessed using the various combinations of meteorological factors produced and applied to the neural network.