Prediction of Photovoltaic Daily Energy Production using Artificial Neural Network with Different Sets of Inputs

Abstract

Photovoltaic (PV) can be considered as one of the greatest known forms of renewable energy.Though, the output performance of PV systems is very dependent on environmental conditions such as the PV modules’ temperature, peak sun hours and others. Hence, the prediction of PV system’s daily energy output production is very significant. The research in this paper is regarding the prediction of daily energy production of a 405.72KWP PV system that has been installed on rooftop by using Artificial Neural Network (ANN). Then, the prediction from ANN intended compared with the result from the mathematical method as well with the real data value. This research also investigates the optimal ANN input configuration to obtain the best results closest to the real data value. It can be analysed from the results that ANN with 12 input configurations is the optimal configuration that to predict the PV output closer to the daily energy production to mathematical method. Moreover, there are different results with different sets of input in ANN as there are no specific to fix the number of inputs.