Photovoltaic power generation maximum power point tracking algorithm based on chaotic particle swarm

Abstract

The invention discloses a photovoltaic power generation maximum power point tracking algorithm based on a chaotic particle swarm. Due to randomness of the particle swarm algorithm, the search efficiency is greatly reduced; therefore, chaotic motion is introduced into the particle swarm algorithm to improve the performance of the algorithm; the photovoltaic power generation maximum power tracking based on the chaotic particle swarm is mainly characterized in that chaotic motion is fused into a particle swarm algorithm; the problem of non-uniform distribution of randomly initialized particles ofthe particle swarm algorithm is solved by utilizing regularity and ergodicity of chaotic motion; the optimization range is expanded, population diversity is improved, it can be found that the chaos particle swarm algorithm can track the maximum power point of the photovoltaic power generation system more accurately under the external environment change by comparing results of the standard particle swarm algorithm, and the conversion efficiency of a photovoltaic array is improved.

Description

technical field [0001] The invention relates to the technical field of photovoltaic power generation systems, in particular to a chaotic particle swarm-based maximum power point tracking algorithm for photovoltaic power generation. Background technique [0002] With the development of the power system and the gradual improvement of environmental protection awareness, people are more and more interested in safe and efficient clean energy, such as photovoltaic power generation, wind power generation, etc. Photovoltaic power generation has the characteristics of convenient use and low cost. In recent years, the proportion of photovoltaic power generation capacity to the total power generation capacity has gradually increased. For photovoltaic power generation, how to maximize the power output of the photovoltaic array has become the focus of research. [0003] Photovoltaic arrays are affected by changes in the external environment (light intensity, temperature, trees and cloud...

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Problems solved by technology

Traditional tracking algorithms [Ma Yongxiang, Wang Yijun, Yan Qunmin. MPPT comprehensive optimization of photovoltaic arrays under local shadows [J]. Modern Electronic Technology, 2019, 42(11): 140-143+148.] are easy to fall into local optimum; Intelligent optimization method [Li Tianbo, Chu Jun, Chen Kunhua, etc. MPPT simulation and application based on particle swarm optimization [J]. Power Electronics Technology, 2012, 46(1): 7-9. There are problems, such as too many random variables in the particle swarm optimization algorithm, and the free randomness greatly reduces the search accuracy

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