摘要
光伏发电系统的输出功率具有显著的非线性特性,且易受辐照度、温度等环境因素扰动,导致功率输出不稳定。现有的最大功率点跟踪(MPPT)技术在动态环境下的追踪精度与响应速度仍存在不足。为此,提出一种基于模式搜索与粒子群优化(PSO)相结合的最大功率点跟踪控制技术。该技术是将局部探索能力较强的模式搜索算法和全局开采能力较强的粒子群优化算法进行有效结合,从而提高光伏系统在各种环境条件下的效率。通过粒子群优化算法在可行域内进行全局搜索,同时引入柯西变异机制以扩大粒子搜索范围,增强算法的全局寻优能力;并且融合模式搜索法对搜索到的较优解进行局部寻优,以提高解的精度。仿真结果表明,通过两种算法的结合,所提方法能在更短时间内找到全局最大功率点;与标准粒子群优化算法相比,该混合算法在静态局部阴影、动态局部阴影两种工况下都能快速准确地追踪到最大功率点。
The output power of photovoltaic power generation system has significant nonlinear characteristics and is susceptible to environmental factors such as irradiance and temperature,leading to the instability of the power output.The existing maximum power point tracking(MPPT)technology still lacks tracking accuracy and response speed in dynamic environments.On this basis,a MPPT control technology based on pattern search and particle swarm optimization(PSO)is proposed.In this technology,the pattern search algorithm with the strong local exploration ability and the particle swarm algorithm with strong global exploitation ability are combined to improve the efficiency of photovoltaic systems under diverse environmental conditions.By conducting a comprehensive search within the feasible region using the particle swarm algorithm and incorporating Cauchy mutation mechanism to broaden its search range,this approach can enhance its global optimization capability.The PSO algorithm is used to conduct global search within the feasible domain,and Cauchy mutation mechanism is introduced to expand the particle search range and enhance the global optimization capability of the algorithm.Furthermore,it can realize the local optimization by integrating pattern search method to improve the solution accuracy.The simulation results show that,in combination with two algorithms,the proposed method can find the global maximum power point in a shorter time.In comparison with standard PSO algorithm,this hybrid approach can swiftly and accurately track maximum power points under both static and dynamic local shading conditions.
作者
李润基
孟丽囡
LI Runji;MENG Linan(Liaoning University of Technology,Jinzhou 121001,China)
出处
《现代电子技术》
北大核心
2025年第12期83-88,共6页
Modern Electronics Technique
关键词
最大功率点追踪
模式搜索技术
粒子群优化算法
柯西变异
局部搜索
全局优化
maximum power point tracking
pattern search technology
particle swarm optimization algorithm
Cauchy mutation
local search
global optimization
