Artificial Neural Network Based Mppt Algorithm for Modern Household with Electric Vehicle

Ján Morgoš,Peter Klčo,Karol Hrudkay

doi:10.26552/com.c.2022.1.c18-c26

Abstract

This paper deals with implementation of artificial neural network in the maximum power point tracking (MPPT) controller algorithm for modern household where electric vehicle (EV) was purchased. The proposed MPPT algorithm was designed to achieve the best possible efficiency of the MPP (maximum power point) tracking and the best possible energy harvesting to charge the EV’s battery. The artificial neural networks have strong advantage in fast input to output response of signals and the finding of MPP is faster than in commonly used algorithms. In this article, the optimised simulation model based on artificial neural network will be introduced. The proposed artificial neural network algorithm was designed for non-shielded photovoltaic panels.

Highlights

In recent years there has been growing interest in producing electricity from solar energy and other renewable energy sources (RES)
Than in the maximum power point tracking (MPPT) algorithm the estimated MPP current by the Artificial neural networks (ANN) is requested by the switching converter interpreted by the change of duty of the pulse width modulation (PWM) signal
The temperature, electrical current and voltage of the PV panel were chosen as input data of the neural network for MPPT control

Summary

Introduction

In recent years there has been growing interest in producing electricity from solar energy and other renewable energy sources (RES). Since it is truly renewable energy source, it is a valuable non-polluting alternative to fossil fuel energy sources in industrial, household or transport applications. The maintenance and cleaning of solar panels is not easy in some cases, i.e. on high-rise buildings. The whole PV panel industry has been growing market creating new job opportunities and new opportunities for research. New materials with higher efficiency are researched and new algorithms for the PV systems power control, as well [1,2,3,4]

Theoretical background

MPPT controller based on ANN

Methods

Simulation results

Findings

Conclusions