LAPSE:2023.10579
Published Article
LAPSE:2023.10579
On State Estimation Modeling of Smart Distribution Networks: A Technical Review
Junjun Xu, Yulong Jin, Tao Zheng, Gaojun Meng
February 27, 2023
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.
Keywords
Big Data, distribution generation, energy internet, smart distribution network, smart meter, state estimation, uncertainty
Suggested Citation
Xu J, Jin Y, Zheng T, Meng G. On State Estimation Modeling of Smart Distribution Networks: A Technical Review. (2023). LAPSE:2023.10579
Author Affiliations
Xu J: State Key Laboratory of Smart Grid Protection and Control, Nanjing 211106, China; College of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
Jin Y: NARI Technology Co., Ltd., Nanjing 211106, China; NARI Group Corporation (State Grid Electric Power Research Institute), Nanjing 211106, China
Zheng T: NARI Technology Co., Ltd., Nanjing 211106, China; NARI Group Corporation (State Grid Electric Power Research Institute), Nanjing 211106, China
Meng G: Jiangsu Collaborative Innovation Center for Smart Distribution Network, Nanjing 211167, China
Journal Name
Energies
Volume
16
Issue
4
First Page
1891
Year
2023
Publication Date
2023-02-14
Published Version
ISSN
1996-1073
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PII: en16041891, Publication Type: Review
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LAPSE:2023.10579
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doi:10.3390/en16041891
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Feb 27, 2023
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