Implementation and simulation analysis of GMPPT algorithm under partial shadow condition. (February 2019)

• Record Type: Journal Article
• Authors: Liying, Zhu; Liang, Ma; Zhigang, Liu; Mingxuan, Chen; Jianwen, Wu
• Is Part Of: Energy procedia. Volume 158(2019)
• Page Start: 418
• Page End: 423
• Publication Date: 2019-02
• Subjects: Photovoltaic power generation -- partial shadow -- quantum-behaved particle swarm optimization (QPSO) algorithm -- GMPPT -- MPPT; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2019.01.126
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: Due to partial occlusion, the output power and voltage curves of PV arrays appear multiple peak points, which increase the difficulty of designing the maximum power tracking system. The limitations of the conventional GMPPT method under the partial shadow are analyzed, and the failure of the traditional optimization algorithm is obtained. The optimization algorithm with strong global search ability can be used to solve the problem. A quantum-behaved particle swarm optimization (QPSO) algorithm is proposed and the implementation process of the algorithm is given. Finally, the standard particle swarm optimization (PSO) algorithm is compared with QPSO. It shows that QPSO is more suitable for solving the photovoltaic MPPT questions under partial shadow, effectively improving the photovoltaic utilization and generating electricity.