MPPT control strategy for PV generation system based on improved PSO algorithm

SUN Kai; LIU Guangyu

doi:10.13873/J.1000-9787(2021)01-0049-04

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MPPT control strategy for PV generation system based on improved PSO algorithm

更新时间：2025-09-11

- MPPT control strategy for PV generation system based on improved PSO algorithm
- Vol. 40, Issue 1, Pages: 49-52(2021)
- 作者机构：
  
  杭州电子科技大学自动化学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2021)01-0049-04
  CLC： TP18;TM615
- Published：2021
- 稿件说明：
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[1]孙恺,刘光宇.基于改进PSO算法的光伏发电系统MPPT控制策略[J].传感器与微系统,2021,40(01):49-52.

SUN Kai, LIU Guangyu. MPPT control strategy for PV generation system based on improved PSO algorithm[J]. 2021, 40(1): 49-52.
[1]孙恺,刘光宇.基于改进PSO算法的光伏发电系统MPPT控制策略[J].传感器与微系统,2021,40(01):49-52. DOI： 10.13873/J.1000-9787(2021)01-0049-04.

SUN Kai, LIU Guangyu. MPPT control strategy for PV generation system based on improved PSO algorithm[J]. 2021, 40(1): 49-52. DOI： 10.13873/J.1000-9787(2021)01-0049-04.

摘要

光伏发电系统运行在局部阴影条件下

其P-V曲线呈现多个峰值

为了保证光伏发电系统能够工作在最大功率点下

提出一种改进粒子群优化（PSO）算法的最大功率点跟踪（MPPT）的控制策略。改进算法采用非线性自适应的学习因子和加速因子同时采用随机惯性权重。仿真实验和真实实验验证所提出的算法在光伏发电系统的MPPT控制中具有较快的收敛速度的同时具有较高的精准度和较小的搜索振荡。

Abstract

The photovoltaic（PV） power generation system operates under local shadow conditions.The PV curve of the PV power generation system presents multiple peaks.In order to ensure that the PV power generation system can work at the maximum power point

a control strategy for improving the maximum power point tracking（MPPT）of the particle swarm optimization（PSO） algorithm is proposed.The improved algorithm adopts nonlinear adaptive learning factor and acceleration factor and adopts random inertia weight.Simulation experiment and the real experiment are carried out to verify that the proposed algorithm has a faster convergence speed in the MPPT control of the PV power generation system

and has higher precision and smaller search oscillation.

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references

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