Title: Research of local shadow MPPT of photovoltaic array based on EV-IKMTOA

Authors: Lingzhi Yi; Dongfang Zhou; Chaodong Fan; Liyun Qiu

Addresses: Hunan Province Multi-Energy Cooperative Control Technology Engineering Research Centre, Ningxiang, Hunan, China; College of Information Engineering, Xiangtan University, Xiangtan, Hunan, China ' College of Information Engineering, Xiangtan University, Xiangtan, Hunan, China ' College of Information Engineering, Xiangtan University, Xiangtan, Hunan, China ' Intelligent Control Research Institute, China Metallurgical Changtian International Engineering Co., Ltd, Changsha, Hunan, China

Abstract: A general algorithm falls easily into the local extremum when it is searching in the local shadow environment, and it is difficult to achieve the maximum power point output of the photovoltaic array. In this paper, an improved molecular dynamics optimisation algorithm is proposed, which takes the P-I curve as the search area and reduces the particle search area. The algorithm adjusts the particle velocity by calculating the particle variance value, which can make the particles evenly distributed in the particle swarm, and coordinate the number of particles in the particle swarm and the number of iterations. Finally, the improved disturbance observation method is used to find the global optimal solution. The simulation results show that the proposed algorithm can jump out of local peaks, improving the convergence accuracy, and has an excellent response capability in dynamic environments.

Keywords: molecular dynamic algorithm; photovoltaic multi-peak MPPT global optimisation; disturbance observation; variance; local shadow.

DOI: 10.1504/IJAAC.2022.119417

International Journal of Automation and Control, 2022 Vol.16 No.1, pp.4 - 18

Received: 30 Jul 2019
Accepted: 04 Jan 2020
Published online: 03 Dec 2021 *

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