Type-2 Fuzzy Logic in Efficiency Enhancement and Health Monitoring of Solar Panel System

India is the largest populated country on the globe, and hence, the need for clean and cheap electricity is also very high due to environmental and social issues. The use of conventional fuels for the generation of energy is unsafe and costly in such developing countries. So, to produce a chief, easy, efficient, and reliable (CEER) generation of renewable energy like solar energy, so there is a need to take care of the health condition of solar panels regularly and analyze the data with the help of latest, advanced, and fuzzy-based techniques to detect the health of a solar panel for lossless and interrupted power supply. The satisfactory operation and long life of solar panel refer to health monitoring. Solar panels with health monitoring keep them clean and can avoid faults in panels and lines. It provides better and continuous output in the worst environmental conditions. The type-1 fuzzy sets cannot work properly in uncertainties conditions in the decision due to many parameters and different expert view. The type-2 fuzzy set can work with complex information as compared to type-1 fuzzy set that can deal with such uncertainties better because it provides more parameters and more degrees of freedom for the selection of parameters. The proposed type-2 fuzzy set is applied here for the health monitoring of solar panels. The performance of the proposed approach provides a better result when the dust is minimal on the solar panel. In this work, a simplified architecture for type-2 fuzzy set provides the better results and they cope well with the various health parameters of the solar panel and can handle the uncertainties of parameters better than their type-1 fuzzy set counterpart. MATLAB/Simulink and solar panels are used to design an efficient solar energy system; later on, performance analysis and health monitoring are performed. Health monitoring of solar panel systems increases efficiency and provides a continuous supply in bad conditions of weather. The system would be much better and would require collaboration with domain experts.