河南理工大学学报（自然科学版）2025，Vol.44Issue(1)：124-133,10.DOI:10.16186/j.cnki.1673-9787.2023010028
基于改进粒子群算法的光伏逆变器控制参数辨识
Parameter identification of photovoltaic inverter based on improved particle swarm optimization algorithm
摘要
Abstract
Accurate grid-connected photovoltaic(PV)inverter model is an important tool to study the fault characteristics of power system under large-scale PV access.Objectives In order to solve the problem that the characteristics of the existing PV inverter simulation model are quite different from those of the actual PV inverter,Methods this paper presented the method of parameter identification to construct the identifi-cation model of inverter.Taking a 1MW photovoltaic power station in Yunyang,Chongqing as the actual reference model,the working interval of the inverter was divided into three stages according to the actual working conditions,and the high and low sensitivity levels of the parameters to be identified in the three stages were divided by mathematical disturbance method.Then,the actual working data of photovoltaic power station was collected in stages,and the initial value range of each parameter to be identified was ob-tained after the data was analyzed and processed,and the synchronous identification parameter experiment was designed as a reference.Finally,an improved chaos genetic algorithm of particle swarm optimization(CGAPSO)was proposed as an identification algorithm to identify the relevant parameters step by step.The ad-vantages of the proposed method can be obtained by comparing the synchronous identification results of the pa-rameters,and the identification results were substituted into the simulation model.Results The error of syn-chronous identification results of low sensitivity parameters was far beyond the acceptable range,and the error of relevant parameters identified by CGAPSO step by step was less than 1.1%,which was much higher than the accuracy of synchronous identification results.Conclusions The output data of the identification model based on the improved particle swarm optimization algorithm had a high agreement with the actual inverter working data,which could accurately reflect the actual working characteristics of the inverter.关键词
光伏并网逆变器/逆变器控制策略/参数辨识/数学扰动法/改进粒子群优化算法Key words
photovoltaic grid-connected inverter/inverter control strategy/identification of parameter/mathe-matical perturbation method/improved particle swarm optimization分类
信息技术与安全科学引用本文复制引用
罗建,孙越,江丽娟..基于改进粒子群算法的光伏逆变器控制参数辨识[J].河南理工大学学报（自然科学版）,2025,44(1):124-133,10.基金项目
国家自然科学基金资助项目(52077017) （52077017）
国网重庆市电力公司重点科技项目(2021渝电科技10#) （2021渝电科技10#）
