Application of a novel metaheuristic algorithm based two-fold hysteresis current controller for a grid connected PV system using real time OPAL-RT based simulator

Abstract

Grid connected photovoltaic (GCPV) rooftop systems have been considered as fast development and promising renewable energy sources due to low maintenance cost, secure investment, noise-free and do not require additional space for installation. Various factors considered for the installation of GCPV are mathematical models of PV module, sizing methods based on techno-economic objectives, PV panels and configurations, selection of the final optimum configuration and environmental criteria. Selection of appropriate controller and its optimal design for power electronic based converters also plays a crucial role in the performance of GCPV. Therefore in this article, a two-fold hysteresis current controller (TFHCC) based on an Improved Arithmetic Optimization Algorithm (IAOA) is introduced and investigated for the first time, for a GCPV system to minimize the switching loss and total harmonic distortion (THD). A novel multi-objective function considering switching frequency and current error is proposed by assigning appropriate weights to obtain the optimal values of duty cycle and hysteresis bands using IAOA, AOA, Forensic Based Investigation (FBI), Differential Evolution (DE) and Particle Swarm Optimization (PSO) algorithms. TFHCC utilizes zero level of the inverter by properly switching it on for a half cycle only and either on or off for the other cycle. Comparative performance analysis of the optimal TFHCC obtained with different algorithms is presented and it is proved that IAOA based TFHCC exhibits substantial reductions in variation and magnitude of the average switching frequency by 2.82 kHz and THD by 0.65%. Initially, the study is carried out with MATLAB Simulink environment and then experimentally validated with real time simulator based on OPAL-RT 4510.