A new maximum power point control algorithm of photovoltaic generation system. Issue 3 (21st September 2018)

• Record Type: Journal Article
• Authors: Sun, Xiujun; Bian, Xiaoxue; Yang, Zhuo
• Is Part Of: Systems science & control engineering. Volume 6:Issue 3(2018)
• Page Start: 333
• Page End: 338
• Publication Date: 2018-09-21
• Subjects: Solar power generation -- multi-peak -- particle swarm algorithm -- Newton method; System theory -- Periodicals; Automatic control -- Periodicals; 003.05
• DOI: 10.1080/21642583.2018.1558419
• Languages: English
• ISSNs: 2164-2583

Abstract

ABSTRACT: Due to the severe environmental changes, especially in the context of the greatly change of the sunlight, the output power of the solar power system will be unstable. In the case of partial obstruction, the equivalent characteristic curves of the photovoltaic panel show a multi-peak state, traditional maximum power control technology is prone to misjudgment and cannot find the maximum power point (MPP). In order to solve this problem, a Newton method based on particle swarm optimization (PSO) is proposed to control the multi-peak MPP. The algorithm will firstly optimize the inertia weight of the particle swarm algorithm, then it will use the optimized particle swarm algorithm to search for the multi-peak MPP. The Newton method will rapidly solve the maximum value to achieve multi-peak MPP tracking when curves approaching to the maximum value. Construction of the boost chopper circuit, which was compared with the particle swarm algorithm and Newton method, was simulated under different light intensities by the simulation softwares such as Simulink and Matlab. The results show that Newton method based on the PSO can quickly find the maximum power with characteristics of good convergence speed and accuracy.