Performance Comparism Between Perturb and Observe – Particle Swarm Optimization (PoPso) and Perturb and Observe Algorithm for Maximum Power Point Tracking in Photovoltaic Systems
Publication Date : 08/03/2021
In implementing photovoltaic (PV) array under varying weather conditions, the photovoltaic systems power-voltage (P-V) characteristic is generally complex, exhibiting numerous maximum power points (MPP). To over this condition, this paper proposes a hybrid algorithm of perturb and observe with particle swarm optimization (PO-PSO) technique. Most predictable algorithms, such as PO will be trapped at the local MPP and thus restraining the maximum power generation. Therefore, analysis on PO-PSO algorithm is embarked on to maximize the PV generated power under same PSC (partial shading condition) in three different scenarios (I, II, III) with the following irradiances; scenario I (1000, 800, 400), scenario II (1000, 800, 800) and scenario III (800, 1000, 600). The performances of usual PO and the PO-PSO algorithms are looked into, particularly their responses under various scenarios using MATLAB Simulink software. The simulation results of the developed PO-PSO algorithm power output showed percentage enhancement of 143.43%, 0.043% and 97.6% when compared with PO power output under same partial shading condition (PSC) with irradiances (W/m 2 ) in scenarios I, scenario II and scenario III respectively. The PO-PSO method yielded low percentage deviation from standard test condition (STC) with (45.72%, 16.9%, 35.92% for scenario I, II and III respectively) when compared with PO with (77.7%, 16.94% and 67.57% for scenario I, II and III) showing that the PO-PSO model gives better performance when applied in PV systems with less deviation from STCs. This will assist the PV array system to attain global MPP (GMPP) faster and support the PV array to produce more stable and reliable power output compared to using only the PO algorithm.
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