Experimental Validation of PSO and Neuro-Fuzzy Soft-Computing Methods for Power Optimization of PV installations

This paper proposes an experimental validation of two Soft-Computing Techniques (SCT). Particle Swarm Optimization (PSO) and Adaptive Neuro Fuzzy Inference System (ANFIS) are used for Maximum Power Point Tracking (MPPT). A database are collected from experimental tests of a photovoltaic array installed at Polytechnic High School of Dakar. To evaluate the performance, the proposed methods are simulated using a MATLAB/Simulink model for a photovoltaic system. Results show that ANFIS presents the best performances with a relatively small error and short response time.