Support Vector Regression Machine Learning based Maximum Power Point Tracking for Solar Photovoltaic systems

Photovoltaic panels use the sun’s radiation on their surface to convert solar energy into electricity. This process is dependent temperature of and intensity sun's radiation. To escalate transformation, system must be functioned at its maximum power point (MPP). Every tracking (MPPT) technique has a distinct mechanism for The support vector machine (SVM) regression algorithm used in this work develop novel method MPP PV panel. panel technical parameters were prepare data training testing SVM model. predicts panel's relevant voltage specific irradiation temperature. duty cycle boost converter corresponding was evaluated using predicted values. result simulation shows that proposed control strategy forces near MPP. gives efficiency more than 94% despite variable climatic conditions during stable state operation. In addition, comparative analysis carried out with existing approaches confirm effective technique.