Hold-State Assisted Fuzzy Supervisory Strategy for Improving Stability in Hybrid Maximum Power Point Tracking Controllers for Standalone Photovoltaic Systems
Abstract
Maximum Power Point Tracking (MPPT) is an essential control technique for maximizing energy extraction from photovoltaic (PV) systems under varying environmental conditions. Although hybrid MPPT methods can improve tracking performance, conventional supervisory strategies may continue to update the controller and converter duty cycle after convergence, resulting in unnecessary control activity and steady-state oscillations. This paper proposes a Hold-State Assisted Fuzzy Supervisory Strategy that integrates Perturb and Observe (P&O) and Particle Swarm Optimization (PSO) through a fuzzy inference system, with a hold-state mechanism that maintains the converter duty cycle after the operating point reaches the maximum power point. The proposed controller was mathematically formulated and implemented in MATLAB/Simulink for a standalone photovoltaic system and evaluated under steady-state and dynamic irradiance conditions. Performance was assessed using tracking efficiency, convergence time, settling time, converter efficiency, power ripple, duty-cycle behaviour, supervisory switching behaviour, and computational performance. Simulation results show that the proposed controller achieved a tracking efficiency of 99.84%, converter efficiency of 96.88%, convergence time of 0.11 s, settling time of 0.15 s, and steady-state power ripple of 0.43%. Compared with conventional P&O and PSO controllers, the proposed strategy achieved faster convergence and settling, higher tracking and converter efficiency, and lower power ripple under the investigated operating conditions. The results demonstrate that incorporating a hold-state mechanism can improve steady-state stability while maintaining effective dynamic maximum power point tracking. The proposed strategy therefore provides a promising approach for improving the stability and performance of standalone photovoltaic systems.