Genetically Optimization of an Asymmetrical Fuzzy Logic Based Photovoltaic Maximum Power Point Tracking Controller

Abstract

This paper introduces a new fuzzy logic controller (FLC) based photovoltaic (PV) maximum power point tracking (MPPT) optimized with the genetic algorithm (GA). Four FLCs with five and seven numbers of triangular (tri) and generalized bell (g-bell) membership functions (MFs) are analyzed. The performances of the analyzed algorithms have been compared with the appropriate performances of the classical perturb and observe (P&O) algorithm by using the following criteria: the rise time (tr), the tracking accuracy of the output power, and the energy yield. The results showed that the FL-based PV MPPT controller with seven triangular (7-tri) MFs provides the best steady-state performances.

Keywords

• fuzzy logic
• genetic algorithms
• maximum power point trackers
• optimization
• photovoltaic systems