An Intelligent Maximum Power Point Tracking Controller based on Brain Emotional Learning (BEL) for Standalone PV System

Abstract

This paper presents design of an intelligent controller to extract maximum power of standalone photovoltaic system (SPV). The Brain emotional learning based intelligent controller (BELBIC) is the limbic model of adaptive learning based on Mammalian Brain emotion control mechanism. This control ensures the quick convergence of the SPV operating point towards the maximum power point without any chattering. The intelligent learning abilities of BELBIC  makes the system robust under the presence of modeling uncertainties and external disturbances such as variable irradiance and temperature. A comparative analysis between the conventional P&O technique and the BELBIC is presented. The MATLAB based simulation results reveal the effectiveness of presented control scheme in terms of higher efficiency and quick convergence to MPP with reduced oscillations under various atmospheric conditions.