Haohan Cui, P. Chao, Xiao-dong Cui, Xinyuan Liu, Weixin Li
{"title":"Identification Method for LVRT Control Parameters of Type-3 wind turbine Based on Short-Circuit Fault Frequency Model","authors":"Haohan Cui, P. Chao, Xiao-dong Cui, Xinyuan Liu, Weixin Li","doi":"10.1109/CIEEC58067.2023.10166085","DOIUrl":null,"url":null,"abstract":"Accurately modeling the low voltage ride through (LVRT) fault characteristics of type-3 wind turbine is crucial for ensuring the safety and stability of high-proportion new energy power systems. However, identifying the controller parameters of the main external characteristics of type-3 wind turbine presents a significant engineering challenge, given the black box of manufacturer converter controller parameters. Existing identification methods have several limitations, including low identification accuracy and unrealistic identification scenarios. This paper proposes a new step identification method based on the short-circuit fault frequency model. The LVRT control strategy parameters are identified based on the output dynamic characteristics of type-3 wind turbine and the generalized LVRT control strategy. The short-circuit fault frequency model proposed in this paper is used to identify the controller parameters. Finally, the accuracy of the proposed method is verified by simulation examples. The results indicate that the proposed method has high accuracy and is suitable for practical engineering applications.","PeriodicalId":185921,"journal":{"name":"2023 IEEE 6th International Electrical and Energy Conference (CIEEC)","volume":"165 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 6th International Electrical and Energy Conference (CIEEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIEEC58067.2023.10166085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Accurately modeling the low voltage ride through (LVRT) fault characteristics of type-3 wind turbine is crucial for ensuring the safety and stability of high-proportion new energy power systems. However, identifying the controller parameters of the main external characteristics of type-3 wind turbine presents a significant engineering challenge, given the black box of manufacturer converter controller parameters. Existing identification methods have several limitations, including low identification accuracy and unrealistic identification scenarios. This paper proposes a new step identification method based on the short-circuit fault frequency model. The LVRT control strategy parameters are identified based on the output dynamic characteristics of type-3 wind turbine and the generalized LVRT control strategy. The short-circuit fault frequency model proposed in this paper is used to identify the controller parameters. Finally, the accuracy of the proposed method is verified by simulation examples. The results indicate that the proposed method has high accuracy and is suitable for practical engineering applications.