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基于Morris灵敏度分析的储能变流器故障穿越控制参数辨识方法

伍阳阳 文天舒 王庆 张彩强 袁华宇 王思维 黄永章

高压电器2025,Vol.61Issue(11):109-117,128,10.
高压电器2025,Vol.61Issue(11):109-117,128,10.DOI:10.13296/j.1001-1609.hva.2025.11.010

基于Morris灵敏度分析的储能变流器故障穿越控制参数辨识方法

Fault Ride-through Control Parameters Identification Method for Energy Storage Power Conversion System Based on Morris Sensitivity Analysis

伍阳阳 1文天舒 1王庆 2张彩强 1袁华宇 1王思维 3黄永章4

作者信息

  • 1. 云南电力试验研究院(集团)有限公司,昆明 650217
  • 2. 云南电网有限责任公司丽江供电局,云南 丽江 674100
  • 3. 国网老河口供电公司,湖北 襄阳 441800
  • 4. 华北电力大学新能源电力系统国家重点实验室,北京 102206
  • 折叠

摘要

Abstract

For improving the accuracy of ault ride-through(FRT)control parameters of power conversion system and enhancing the accuracy of simulation analysis,a FRT control parameter identification method based on Morris sensitivity analysis is proposed.First,a hardware-in-the-loop simulation platform for the power conversion system is set up using RT-LAB,and FRT operation conditions under different fault conditions are used as the identification data set.Then,the Morris method is used to analyze the sensitivity of the parameters to be identified under each con-trol mode,providing a theoretical basis for the stepwise strategy.Finally,the cuckoo search algorithm is improved by combining dynamic parameters and dynamic step size strategies,and the identification of high-sensitivity and low-sensitivity FRT control parameters is completed in sequence.The simulation results show that compared with the CS algorithm,the average parameter error of the proposed dynamic CS algorithm is reduced by up to 15%,the si-multion accuracy is effectively improved and the optimization efficiency is increased by more than 40%.

关键词

储能变流器/电压穿越/参数辨识/布谷鸟搜索

Key words

energy storage power conversion system/voltage ride-through/parameter identification/cuckoo search

引用本文复制引用

伍阳阳,文天舒,王庆,张彩强,袁华宇,王思维,黄永章..基于Morris灵敏度分析的储能变流器故障穿越控制参数辨识方法[J].高压电器,2025,61(11):109-117,128,10.

基金项目

云南省新型电力系统技术创新中心资助项目(202405AK340007) (202405AK340007)

新能源电力系统全国重点实验室2024年开放课题(LAPS24006) (LAPS24006)

宁夏自然科学基金(2023AAC03857). Project Supported by Funding Project of Yunnan Province New-type Power System Technology Innovation Center(202405AK340007),2024 Open Project of the National Key Laboratory of New Energy Power Systems(LAPS24006),Ningxia Natural Science Foundation(2023AAC03857). (2023AAC03857)

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1001-1609

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