Rahman, Md. MosaddequrNipa, KainatNinad, Md.Saad Ul IslamBadhon, Nurunnabi KhanSultan, Md.Tipu2022-02-152022-02-1520212021-10ID 16221011ID 16321006ID 16221021ID 16221023http://hdl.handle.net/10361/16247Cataloged from PDF version of thesis.Includes bibliographical references (pages 46-48).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electrical and Electronic Engineering, 2021.The objective of this study is to analysis and observe the performance of the photovoltaic (PV) modules in different environmental conditions by applying machine learning algorithm . There were two PV Modules , one is cleaned and other one is dusty . Real-time data from each sensor is effectively collected from November 2019 to February 2020, and prediction has been done on 2 different days from march month of 2020 from the weather station situated in Gabtoli. In this study short term performance analysis has been done with different error calculation. Result shows that, the performance depends on the volume of training dataset. In this study two artificial neural network models has been used to train and test the data of PV module output and assess the short term performance.48 pagesenBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.Short circuit currentTemperatureWind speedHumiditySolar irradianceMachine learningThesis