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Improved Invasive Weed Optimization Algorithm for Global Maximum Power Point Tracking of PV Array Under Partial Shading Conditions

International Journal of Applied Metaheuristic Computing (IJAMC) • 2022
العودة
معلومات البحث
المؤلفون I. M. Abdelqawee Hegazy Zaher, Mohamed Husien Mohamed Eid, Radwa S. A. Gad
الكلمات المفتاحية Not Available
المجلة العلمية International Journal of Applied Metaheuristic Computing (IJAMC)
الناشر .igi-global
المجلد 13
العدد 1
الصفحات Not Available
publication.type International
رابط البحث Open Link
المواد المرفقة Not Available
الملخص
Photovoltaic (PV) array under partial shading conditions (PSCs) has several maximum power points (MPPs) on the power-voltage curve of the PV array. These points; have a unique global peak (GP) and the others are local peaks (LPs). This paper aims to study an improved version of a heuristic optimization technique namely, Invasive Weed Optimization (IWO) to track the global maximum power point (GMPP) of a PV array which is an important issue. The proposed improved IWO (IIWO) algorithm modifies IWO to speed up the convergence and make the system more efficient. In addition to study the effect of changing input parameters of IIWO on its performance. An overall statistical evaluation of IIWO, with standard IWO and Particle Swarm Optimization (PSO) is executed under different shading conditions. The simulation results show that IIWO has faster and better convergence as it can reach the GMPP in less