Enhancing Solar Panel Efficiency Through Fuzzy Logic Control: A Case Study on Water Spraying and Air Cooling Techniques

As global energy demand continues to rise and natural resources are limited, the urgency for sustainable energy becomes increasingly significant. Renewable energy such as solar power has great potential due to its abundant availability, effective cost and minimal impact on the environment. Solar panels as a major component in renewable energy, have the potential to generate clean electricity but their efficiency is greatly affected by operational temperature. This research focuses on this challenge by developing an Internet of Things (IoT)-based temperature control and monitoring system that uses water spraying and air-cooling techniques to maintain optimal temperatures on the surface of solar panels. The system is designed to monitor and control the temperature in real-time, thereby reducing over-temperature and improving energy efficiency. The test results show an increase in solar panel efficiency ranging from 1.9% to 4.68%, with the highest increase occurring from 9:00 to 15:00. The fuzzy logic control system with performance test results includes a rise time of 149 seconds, steady-state error of $\mathbf{0. 1 2 \%}$, maximum overshoot of $\mathbf{- 0. 3 3 \%}$, and delay time of $\mathbf{7 4. 5}$ seconds. Extensive testing showed that the system was able to significantly reduce temperature spikes and improve system efficiency. The results of this study highlight the tremendous potential of water-based cooling systems and IoT technology in revolutionizing solar energy utilization, becoming an important step towards a more sustainable energy future.