Comparative data analysis of a PV module system considering weather parameters

Abstract

Fastest growing economy of Bangladesh increase the great demand of power generation using renewable energy sources. However, uncertainty in the output power of the photovoltaic (PV) power generation station due to variation in meteorological parameters is of serious concern. As a solution to this issue this work aims to predict the accurate power of a PV system. The performance results of this study are presented in terms of Random forest, Artificial Neural Network (ANN) and Multiple Linear Regression model. Additionally, the performance results obtained with Random forest, Artificial Neural Network (ANN) and Linear Regression are compared to show that which model has better prediction accuracy and less error. This paper aims to employ and perform a comparison study of PV systems considering weather parameter using different algorithms of above-mentioned data forecasting methods. The data which will be taken from the mentor of our thesis will be used in this paper. The present study will also be very helpful to provide technical guidance to the prediction of the PV power System.