基于自适应模糊-PID水冷技术提升光伏组件效率的实验研究

Abstract Photovoltaic ( PV ) modules are important components in solar energy systems, but their efficiency is significantly limited by excessive heat generation due to intense solar irradiance, especially in equatorial climates like Malaysia. This excessive heat not only reduces power conversion efficiency but also accelerates the degradation of PV modules, leading to shorter lifespans and higher maintenance costs. This research introduces an adaptive self-tuning Fuzzy-PID controller, optimized using the Sine Cosine Algorithm (SCA), to regulate an active water cooling system for enhanced PV performance. The Sine Cosine Algorithm (SCA) was selected for its efficient exploration–exploitation balance, enabling it to avoid local optima and converge to a global optimum, ensuring better parameter tuning for precise temperature regulation. This cooling system differentiates it from other methods by dynamically adjusting water flow based on real-time temperature feedback. This ensures improved power output while significantly reducing water consumption. Its adaptability surpasses conventional methods, with performance validated against free-flow cooling. The controller-based system effectively reduced the PV module’s temperature to an average of 40.0 °C, leading to a 12.2 % increase in power output while conserving water by 60 %. Its adaptive approach ensures optimal cooling efficiency, making it a superior choice for sustainable PV cooling systems.