Towards Green Energy for Smart Cities: Particle Swarm Optimization Based MPPT Approach

Abstract

This paper proposes an improved one-power-point (OPP) maximum power point tracking (MPPT) algorithm for wind energy conversion system (WECS) to overcome the problems of the conventional OPP MPPT algorithm, namely, the difficulty in getting a precise value of the optimum coefficient, requiring pre-knowledge of system parameters, and non-uniqueness of the optimum curve. The solution is based on combining the particle swarm optimization (PSO) and optimum-relation-based (ORB) MPPT algorithms. The PSO MPPT algorithm is used to search for the optimum coefficient. Once the optimum coefficient is obtained, the proposed algorithm switches to the ORB MPPT mode of operation. The proposed algorithm neither requires knowledge of system parameters nor mechanical sensors. In addition, it improves the efficiency of the WECS. The proposed algorithm is studied for two different wind speed profiles, and its tracking performance is compared with conventional optimum torque control (OTC) and conventional ORB MPPT algorithms under identical conditions. The improved performance of the algorithm in terms of tracking efficiency is validated through simulation using MATLAB/Simulink. The simulation results confirm that the proposed algorithm has a better performance in terms of tracking efficiency and energy extracted. The tracking efficiency of the PSO-ORB MPPT algorithm could reach up to 99.4% with 1.9% more harvested electrical energy than the conventional OTC and ORB MPPT algorithms. Experiments have been carried out to demonstrate the validity of the proposed MPPT algorithm. The experimental results compare well with system simulation results, and the proposed algorithm performs well, as expected.