Hybrid Optimized Fuzzy Logic Controller for Standalone Photovoltaic Systems with Two-Stage Converter

Abstract

Standalone solar PV systems have emerged as potential alternatives to electricity problems in areas where a grid is unavailable. Obtaining full power from a photoelectric system, DC-DC inverter, DC-AC converter, and control system presents great difficulties when building these devices. In this paper, Hybrid optimization (Chaotic Hybrid Butterfly Optimization Algorithm with Particle Swarm Optimization) based fuzzy logic controller for standalone PV battery system with two-stage converter. The power of PV systems may be decreased by the oscillation, random fluctuation, and slow speed of their power tracking. To tackle these issues, a novel Fuzzy logic with Particle Swarm Optimization technique is implemented to the MPPT controller under fast varying irradiance and PS conditions. The fuzzy logic controller (FLC) is proposed in this paper as a Maximum Power Point Tracking (MPPT) system to get maximum power from photovoltaic with changes in irradiation and temperature. Fuzzy logic naturally provides a superior controller for this type of nonlinear application. The new control strategy design was evaluated and validated using extensive MATLAB simulations under different scenarios, including load variations. The system output was evaluated using extensive MATLAB simulations.