{"title":"径向和简单环路配电系统的前向/后向鲁棒状态估计算法","authors":"Wei Yan , Guanneng Xu , Xu Zhang , Ruifeng Zhao","doi":"10.1016/j.ijepes.2024.110366","DOIUrl":null,"url":null,"abstract":"<div><div>The data integration of high voltage (HV) and medium voltage (MV) distribution power grids is a development trend in future energy management systems. This integration brings about challenges such as handling large-scale networks and bad data, which can impact the speed and accuracy of state estimation. To address these issues, a forward/backward sweep (FBS) robust state estimation algorithm (FB-SE) is proposed, particularly suitable for simple loop and radial distribution systems. The algorithm consists of two stages: 1) Bad Data Pre-processing (BDP); and 2) Branch Power Flow State Estimation; Both stages follow the FBS strategy. The preprocessing of bad data only involves one FBS calculation, aiming to identify and rectify obvious bad data; The branch power flow state estimation introduces the weights of state estimation and uses a classification normalized residual index function to achieve weight allocation. The state estimation algorithm proposed in this paper avoids solving Jacobian matrices and linear equations. It can also handle simple ring networks by opening the loop and performing power compensation. The simulation results based on IEEE examples show that this algorithm has advantages in computation speed, robustness, and convergence.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"163 ","pages":"Article 110366"},"PeriodicalIF":5.0000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A forward/backward robust state estimation algorithm for radial and simple loop distribution systems\",\"authors\":\"Wei Yan , Guanneng Xu , Xu Zhang , Ruifeng Zhao\",\"doi\":\"10.1016/j.ijepes.2024.110366\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The data integration of high voltage (HV) and medium voltage (MV) distribution power grids is a development trend in future energy management systems. This integration brings about challenges such as handling large-scale networks and bad data, which can impact the speed and accuracy of state estimation. To address these issues, a forward/backward sweep (FBS) robust state estimation algorithm (FB-SE) is proposed, particularly suitable for simple loop and radial distribution systems. The algorithm consists of two stages: 1) Bad Data Pre-processing (BDP); and 2) Branch Power Flow State Estimation; Both stages follow the FBS strategy. The preprocessing of bad data only involves one FBS calculation, aiming to identify and rectify obvious bad data; The branch power flow state estimation introduces the weights of state estimation and uses a classification normalized residual index function to achieve weight allocation. The state estimation algorithm proposed in this paper avoids solving Jacobian matrices and linear equations. It can also handle simple ring networks by opening the loop and performing power compensation. The simulation results based on IEEE examples show that this algorithm has advantages in computation speed, robustness, and convergence.</div></div>\",\"PeriodicalId\":50326,\"journal\":{\"name\":\"International Journal of Electrical Power & Energy Systems\",\"volume\":\"163 \",\"pages\":\"Article 110366\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2024-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Electrical Power & Energy Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0142061524005891\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Electrical Power & Energy Systems","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0142061524005891","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
A forward/backward robust state estimation algorithm for radial and simple loop distribution systems
The data integration of high voltage (HV) and medium voltage (MV) distribution power grids is a development trend in future energy management systems. This integration brings about challenges such as handling large-scale networks and bad data, which can impact the speed and accuracy of state estimation. To address these issues, a forward/backward sweep (FBS) robust state estimation algorithm (FB-SE) is proposed, particularly suitable for simple loop and radial distribution systems. The algorithm consists of two stages: 1) Bad Data Pre-processing (BDP); and 2) Branch Power Flow State Estimation; Both stages follow the FBS strategy. The preprocessing of bad data only involves one FBS calculation, aiming to identify and rectify obvious bad data; The branch power flow state estimation introduces the weights of state estimation and uses a classification normalized residual index function to achieve weight allocation. The state estimation algorithm proposed in this paper avoids solving Jacobian matrices and linear equations. It can also handle simple ring networks by opening the loop and performing power compensation. The simulation results based on IEEE examples show that this algorithm has advantages in computation speed, robustness, and convergence.
期刊介绍:
The journal covers theoretical developments in electrical power and energy systems and their applications. The coverage embraces: generation and network planning; reliability; long and short term operation; expert systems; neural networks; object oriented systems; system control centres; database and information systems; stock and parameter estimation; system security and adequacy; network theory, modelling and computation; small and large system dynamics; dynamic model identification; on-line control including load and switching control; protection; distribution systems; energy economics; impact of non-conventional systems; and man-machine interfaces.
As well as original research papers, the journal publishes short contributions, book reviews and conference reports. All papers are peer-reviewed by at least two referees.