A novel approach for fuzzy logic PV inverter controller optimization using lightning search algorithm

Photovoltaic (PV) inverters convert DC voltage and current to AC quantities whose magnitude and frequency are controlled to obtain the desired output. While there are plenty of controllers, it is the fuzzy logic controller (FLC) that receives increasing attention. In this study, a novel metaheuristic optimization algorithm known as lightning search algorithm (LSA) is presented for solving the problem of trial and error procedure in obtaining membership functions (MFs) used in the conventional FLCs. The LSA mimics the natural phenomenon of lightning. It is generalized from the mechanism of step leader propagation. The proposed optimization algorithm considers the concept of fast particles known as projectiles. The probabilistic nature and tortuous characteristics of lightning discharges, which depend on the type of projectile, are modeled using various random distribution functions. To evaluate the reliability and efficiency of the proposed algorithm, the LSA is first tested using 10 benchmark functions with various characteristics necessary to evaluate a new algorithm. Then it is used in designing optimum FLC for standalone PV inverter. The result demonstrates that the LSA generally provides better outcome compared with the other tested methods with a high convergence rate.