OPTIMAL TUNING OF FUZZY LOGIC CONTROLLER PARAMETERS FOR INCREMENTAL CONDUCTANCE MPPT CONTROLLER BASED ON GREY WOLF OPTIMIZER ALGORITHM

Abstract

Nowadays Maximum Power Point Tracking (MPPT) controller is considered the central part of any photovoltaic system to achieve the maximum power at all time under the change in weather conditions. MPPT techniques like, Perturb and Observe (P&O), Incremental Conductance (IC) and Fractional Open-Circuit Voltage (FOCV) are the most commonly algorithm used due to low cost, easy implementation and simplicity. These algorithms are differing from each other according to sensors number, easy or complexity implementation and cost. The best algorithm is select according to accurate and fast tracking performance and minimum error due to changing conditions of weather. In this paper the optimal design for Incremental Conductance (IC) MPPT technique based on Fuzzy Logic controllers tuned by new optimization technique called Grey Wolf Optimizer (GWO) is applied for the largest PV project planned in Egypt. This PV project installed in Komombo, Aswan, Egypt and will have a total capacity of 20 MW. This study provides a comprehensive comparative study based on Average Power (A.P), transient behavior, Energy Availability (E.A) and Array Fill Factor (A.F.F) to choose the optimum control technique which is more suitable for controlling MPPT in Komombo PV power plant. MATLAB/SIMULINK is used to provide technical study and comprehensive analysis for the proposed PV power plant.