On State Estimation Modeling of Smart Distribution Networks: A Technical Review

被引：3
|
作者：
Xu, Junjun [1 ,2 ,3 ]
Jin, Yulong [4 ,5 ]
Zheng, Tao [4 ,5 ]
Meng, Gaojun [6 ]
机构：
[1] State Key Lab Smart Grid Protect & Control, Nanjing 211106, Peoples R China
[2] Nanjing Univ Posts & Telecommun, Coll Automat, Nanjing 210023, Peoples R China
[3] Nanjing Univ Posts & Telecommun, Coll Artificial Intelligence, Nanjing 210023, Peoples R China
[4] NARI Technol Co Ltd, Nanjing 211106, Peoples R China
[5] NARI Grp Corp, State Grid Elect Power Res Inst, Nanjing 211106, Peoples R China
[6] Jiangsu Collaborat Innovat Ctr Smart Distribut Net, Nanjing 211167, Peoples R China
来源：
ENERGIES | 2023年 / 16卷 / 04期
关键词：
state estimation; smart distribution network; distribution generation; uncertainty; smart meter; big data; energy internet; LEARNING-BASED OPTIMIZATION; POWER DISTRIBUTION-SYSTEMS; INTERVAL OPTIMIZATION; NEURAL-NETWORKS; ALGORITHM; IDENTIFICATION; EFFICIENT; FLOW; UNCERTAINTY; VALIDATION;
D O I：
10.3390/en16041891
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
State estimation (SE) is regarded as an essential tool for achieving the secure and efficient operation of distribution networks, and extensive research on SE has been conducted over the past three decades. Nonetheless, the high penetration of distribution generations (DGs) is accompanied by uncertainties and dynamics, and the extensive application of intelligent electronic devices (IEDs) is associated with data processing issues, all of which raise new challenges, and these issues must be taken care of for further development of SE in smart distribution networks. This paper attempts to present a comprehensive literature review of numerous works that address various issues in SE, examining key technical research issues and future perspectives. Hopefully, it will be able to meet the needs for the development of smart distribution networks.
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页数：19
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