Litcius/Paper detail

Study on Artificial Neural Network Based MPPT Algorithm in PV Application

Swaroop Shyam, Arnab Ghosh

202312 citationsDOI

Abstract

This paper presents a descriptive study on Artificial Neural Network, and it solves the drawbacks of old MPPT techniques. This study includes a detailed analysis of the fundamental principles and operational aspects of ANN. The MATLAB Simulink is used to simulate the PV module, DC-DC boost converter, and the ANN MPPT algorithms of the MPPT control system. The simulation also compares the system's performance under varying solar irradiation rates, both fast and slow. A comparison is made with Perturb and Observe (P&O) MPPT method. The results on simulation 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.

Topics & Concepts

Maximum power point trackingMATLABArtificial neural networkComputer sciencePhotovoltaic systemControl theory (sociology)Control engineeringControl (management)Artificial intelligenceEngineeringVoltageElectrical engineeringInverterOperating systemPhotovoltaic System Optimization TechniquesPower Systems and Renewable EnergySolar Radiation and Photovoltaics
Study on Artificial Neural Network Based MPPT Algorithm in PV Application | Litcius