卡尔曼滤波在电力系统动态估计中的研究综述

2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) Pub Date : 2021-06-18 DOI:10.1109/IMCEC51613.2021.9482112

Zili Yang, Ran Gao, Weihua He

{"title":"卡尔曼滤波在电力系统动态估计中的研究综述","authors":"Zili Yang, Ran Gao, Weihua He","doi":"10.1109/IMCEC51613.2021.9482112","DOIUrl":null,"url":null,"abstract":"Firstly, the problems and common methods of power system dynamic state estimation are briefly introduced, and then the basic principles of Kalman filtering are introduced. Based on this principle, the common methods of power system dynamic state estimation problems are derived: extended Kalman filter, unscented Kalman filter and cubature Kalman filter, which are introduced respectively. The advantages and disadvantages of these methods and their applications in power system dynamic state estimation are compared and analyzed. Finally, the development trend of Kalman filter in dynamic state estimation is prospected.","PeriodicalId":240400,"journal":{"name":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Review of The Research on Kalman Filtering in Power System Dynamic State Estimation\",\"authors\":\"Zili Yang, Ran Gao, Weihua He\",\"doi\":\"10.1109/IMCEC51613.2021.9482112\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Firstly, the problems and common methods of power system dynamic state estimation are briefly introduced, and then the basic principles of Kalman filtering are introduced. Based on this principle, the common methods of power system dynamic state estimation problems are derived: extended Kalman filter, unscented Kalman filter and cubature Kalman filter, which are introduced respectively. The advantages and disadvantages of these methods and their applications in power system dynamic state estimation are compared and analyzed. Finally, the development trend of Kalman filter in dynamic state estimation is prospected.\",\"PeriodicalId\":240400,\"journal\":{\"name\":\"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMCEC51613.2021.9482112\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMCEC51613.2021.9482112","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

摘要

首先简要介绍了电力系统动态估计存在的问题和常用方法，然后介绍了卡尔曼滤波的基本原理。在此基础上，导出了电力系统动态估计问题的常用方法:扩展卡尔曼滤波、无气味卡尔曼滤波和培养卡尔曼滤波，并分别对它们进行了介绍。对这些方法的优缺点及其在电力系统动态估计中的应用进行了比较和分析。最后，展望了卡尔曼滤波在动态估计中的发展趋势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A Review of The Research on Kalman Filtering in Power System Dynamic State Estimation

Firstly, the problems and common methods of power system dynamic state estimation are briefly introduced, and then the basic principles of Kalman filtering are introduced. Based on this principle, the common methods of power system dynamic state estimation problems are derived: extended Kalman filter, unscented Kalman filter and cubature Kalman filter, which are introduced respectively. The advantages and disadvantages of these methods and their applications in power system dynamic state estimation are compared and analyzed. Finally, the development trend of Kalman filter in dynamic state estimation is prospected.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2021 IEEE 4th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)

自引率

0.00%

发文量