A fuzzy-based failure mode effect and criticality analysis of solar photovoltaic systems

In this research work, a Failure Mode and Effect Analysis (FMEA) has been applied to a Solar Photovoltaic (SPV) system that consists of a photovoltaic module, an inverter, connecting cable, battery and a charge controller. The FMEA is a tool that can gauge the possible failure mode(s) in order to determine the probability of the failure. The traditional (crisp) method of FMEA ranks all failure modes using Risk Priority Number (RPN) according to severity order. However, traditional FMEA has several disadvantages (like chance of error, human intelligence, etc.) which may be overcome by integrating them with artificial intelligence techniques. Therefore, fuzzy logic is implemented to assess and ranks associated with each failure mode of different subassemblies of SPV system. Ranking of all failure modes has been done on the basis of fuzzy RPN, which is calculated by weighted Euclidean distance formula and centroid defuzzification method. It is expected that this work will help the designers and engineers by making them aware of the qualitative analysis of SPV systems.