Study on Artificial Neural Network based MPPT Algorithm in PV Application

Abstract

This paper presents a comparative study between the Artificial Neural Network (ANN) and Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) method for photovoltaic (PV) applications. The study includes a detailed analysis of the fundamental principles and operational aspects of ANN and P&O MPPT methods. The MATLAB Simulink is used to simulate the PV module, DC-DC boost converter, and the ANN and P&O MPPT algorithms of the MPPT control system. The simulation also compares the system's performance under varying solar irradiation rates, both fast and slow. The simulation results demonstrate that ANN-based MPPT outperforms the P&O method in terms of efficiency and accuracy, particularly under dynamic weather and shading conditions. The proposed study provides a comprehensive understanding of the benefits and limitations of ANN and P&O MPPT methods and highlights the potential for future research.