A Novel Optimized Fuzzy Interfaced PID Controller MPPT Technique for Photovoltaic Systems under Unpredictable Environment

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Chinese explanation / 中文解读

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Original abstract

This paper explores, evaluates, and enhances Maximum Power Point Tracking (MPPT) strategies for Photovoltaic (PV) units working under highly changing atmospheric conditions. Although conventional techniques like Search and Rescue (SRA), Model Predictive Control (MPC), and sliding-mode control can be slow in converging, have more oscillations, or are computationally heavy, this paper presents an improved Fuzzy PID-based MPPT controller integrated with a Genetic Algorithm (GA) for the self-tuning of membership functions and PID parameters. The new controller achieves a remarkable improvement in the dynamic response by reaching the maximum power point in a shorter time, lowering the oscillations at steady state, and showing great flexibility to sudden changes in light intensity. Results of simulations performed with MATLAB/Simulink indicate that the proposed approach delivers an MPPT efficiency of 96.98%, which is better than the usual ones, like Fuzzy (96.28%), GA-Fuzzy (96.72%), ANFIS (96.58%), and DC-DC boost-based MPPT methods. The authors assert that the introduced improvements demonstrate the controller’s capability to improve the stability, reliability, and energy production of current solar PV systems, particularly in outdoor situations where the weather is highly changeable.

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