Investigation of Adaptive Intelligent MPPT Algorithm for a Low-cost IoT Enabled Standalone PV System

Abstract

ABSTRACT This paper explicates a standalone solar photovoltaic system design to track maximum power by utilising intelligent adaptive control algorithms. Conventional MPPT algorithms are not efficient enough to follow the maximum power variable irradiation and temperature conditions. Therefore, an intelligent algorithm has been required to extract the maximum power in a standalone PV system. The present paper incorporates adaptive intelligent maximum power point tracking (MPPT) method adaptive neuro-fuzzy inference system (ANFIS) techniques to extract maximum voltage and power. The fuzzy logic controller (FLC) has been implemented to analyse the performance compared to the ANFIS method. Because of the utilisation of conventional techniques, the point of maximum power gets oscillated in a low irradiance level and the values move between forward and backwards but do not have a fixed value. The used ANFIS method takes all the possibility values from 0 to 1, increasing efficiency. The efficiency of the ANFIS-based MPPT method is 90% more accurate than those of other conventional methods, which has been presented in the paper. For the remote monitoring of the obtained voltage, current and power, internet of things (IoT) features have been incorporated into the considered standalone PV system. The presented standalone PV system has been experimentally verified and validated for the efficiency evaluation of the proposed ANFIS algorithm.