Ruiqi Deng, Gang Chen, Bo Li, Jianping Wu, Guangyong Zheng, Jinhong Chen
{"title":"基于多源数据融合技术和PMU测量的配电网状态估计研究","authors":"Ruiqi Deng, Gang Chen, Bo Li, Jianping Wu, Guangyong Zheng, Jinhong Chen","doi":"10.1109/ICoPESA56898.2023.10141507","DOIUrl":null,"url":null,"abstract":"With the introduction of phasor measurement units (PMUs), multi-source measurements with different time scales and accuracy coexist in distribution networks. The efficient utilization of multi-source measurements to accurately estimate the state of distribution network is an important prerequisite for operational decision-making. In this paper, a state estimation method based on multi-source measurement data was proposed for distribution networks. The time scale, synchronization and accuracy of multi-source measurements were considered. The integration of PMU data into state estimation model was discussed. The measurement functions were linearized by equivalent conversion of multi-source measurements. The data fusion strategy for different data types was presented to improve the estimation accuracy and shorten the estimation period. Case studies on an actual engineering example was performed to show the effectiveness of the proposed method. The improvements in network observability and estimation accuracy under different measurement conditions were verified.","PeriodicalId":127339,"journal":{"name":"2023 International Conference on Power Energy Systems and Applications (ICoPESA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on State Estimation of Distribution Networks Based on Multi-source Data Fusion Technology with PMU Measurement\",\"authors\":\"Ruiqi Deng, Gang Chen, Bo Li, Jianping Wu, Guangyong Zheng, Jinhong Chen\",\"doi\":\"10.1109/ICoPESA56898.2023.10141507\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the introduction of phasor measurement units (PMUs), multi-source measurements with different time scales and accuracy coexist in distribution networks. The efficient utilization of multi-source measurements to accurately estimate the state of distribution network is an important prerequisite for operational decision-making. In this paper, a state estimation method based on multi-source measurement data was proposed for distribution networks. The time scale, synchronization and accuracy of multi-source measurements were considered. The integration of PMU data into state estimation model was discussed. The measurement functions were linearized by equivalent conversion of multi-source measurements. The data fusion strategy for different data types was presented to improve the estimation accuracy and shorten the estimation period. Case studies on an actual engineering example was performed to show the effectiveness of the proposed method. The improvements in network observability and estimation accuracy under different measurement conditions were verified.\",\"PeriodicalId\":127339,\"journal\":{\"name\":\"2023 International Conference on Power Energy Systems and Applications (ICoPESA)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Power Energy Systems and Applications (ICoPESA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICoPESA56898.2023.10141507\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Power Energy Systems and Applications (ICoPESA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICoPESA56898.2023.10141507","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on State Estimation of Distribution Networks Based on Multi-source Data Fusion Technology with PMU Measurement
With the introduction of phasor measurement units (PMUs), multi-source measurements with different time scales and accuracy coexist in distribution networks. The efficient utilization of multi-source measurements to accurately estimate the state of distribution network is an important prerequisite for operational decision-making. In this paper, a state estimation method based on multi-source measurement data was proposed for distribution networks. The time scale, synchronization and accuracy of multi-source measurements were considered. The integration of PMU data into state estimation model was discussed. The measurement functions were linearized by equivalent conversion of multi-source measurements. The data fusion strategy for different data types was presented to improve the estimation accuracy and shorten the estimation period. Case studies on an actual engineering example was performed to show the effectiveness of the proposed method. The improvements in network observability and estimation accuracy under different measurement conditions were verified.