Optimization of Fuzzy Logic Controller Based Maximum Power Point Tracking Using Hierarchical Genetic Algorithms

Fuzzy logic controller (FLC)-based maximum power point tracking (MPPT) or simply fuzzy MPPT technique has attracted a large interest because it allows a more human approach to control and shows good performance compared to conventional techniques. However, in spite of the many advantages of the fuzzy MPPT, the design of this controller remains a difficult task due to the large number of parameters and fuzzy rules that needs an optimal tuning. This paper describes a new design method of fuzzy MPPT for photovoltaic conversion system using hierarchical genetic algorithms (HGAs). The chromosomes of HGAs are organized in hierarchical structure and able to optimize all parameters of fuzzy MPPT like the number of fuzzy rules and its consequents, and the membership functions parameters. The optimized fuzzy MPPT is tested in simulation and showed optimal responses even under rapid variations in irradiance. The proposed approach is compared to other fuzzy MPPT design methods currently in use, and the results confirm the superiority of our approach.