Real-Time Maximum Power Point Tracking Algorithm (MPPT) Control of PV Systems Using Fuzzy Logic Enhanced with Adaptive Dove Swarm Optimization (ADSO) on a dSPACE Platform

Abstract

Photovoltaic (PV) system has emerged as a reliable and resilient energy source due to their emission-free operation and minimal maintenance requirements. Maximum power point tracking (MPPT) approaches are required to ensure effective power extraction in various types of environmental conditions. This study presents a real-time MPPT control strategy with a boost converter for the DSPACE-implemented commercial PV panel. A fuzzy logic controller (FLC) is designed to work MPPT, and its performance is benchmark against the traditional incremental conduction (Inccond) algorithm. To further increase the tracking accuracy and dynamic reaction, the fuzzy logic controller is hybricated with the adaptive dove swarm optimization (ADSO) algorithm. The ADSO algorithm allows adaptive tuning of fuzzy membership features and rule sets based totally on real-time irradiance and temperature versions, effectively enhancing convergence velocity and robustness. Results from experiments indicate that the counselled Hybrid fuzzy-ADSO technique drastically outperforms IncCond in phrases of consistent-nation oscillation, response time and overshoot reduction. These results verify that the counselled technique for excessive efficiency is successful, actual-time MPPT control in PV structures.