Power System Dynamic State Estimation: Motivations, Definitions, Methodologies and Future Work

Journal Article · Wed Jan 23 00:00:00 UTC 2019 · IEEE Transactions on Power Systems

DOI: https://doi.org/10.1109/TPWRS.2019.2894769 · OSTI ID:1491863

Zhao, Junbo ^[1]; Gomez-Exposito, Antonio ^[2]; Netto, Marcos ^[1]; Mili, Lamine ^[1]; Abur, Ali ^[3]; Terzija, Vladimir ^[4]; Kamwa, Innocent ^[5]; Pal, Bikash Chandra ^[6]; Singh, Abhinav Kumar ^[7]; Qi, Junjian ^[8]; Huang, Zhenyu ^[9]; Meliopoulos, A. P. Sakis ^[10]

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1. Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)
2. Univ. of Sevilla Spain, Sevilla (Spain)
3. Northeastern Univ., Boston, MA (United States)
4. The Univ. of Manchester, Manchester (United Kingdom of Great Britain and Northern Ireland)
5. IREQ, Varennes, QC (Canada)
6. Imperial College of Science, Technology and Medicine, London (United Kingdom of Great Britain and Northern Ireland)
7. Univ. of Lincoln College of Science, Lincoln (United Kingdom of Great Britain and Northern Ireland)
8. Univ. of Central Florida, Orlando, FL (United States)
9. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
10. Georgia Inst. of Technology, Atlanta, GA (United States)

This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Univ. of Central Florida, Orlando, FL (United States)
• Sponsoring Organization: USDOE
• Grant/Contract Number: AC05-76RL01830; EE0007327
• OSTI ID: 1491863
• Journal Information: IEEE Transactions on Power Systems, Journal Name: IEEE Transactions on Power Systems Journal Issue: 4 Vol. 34; ISSN 0885-8950
• Publisher: IEEECopyright Statement
• Country of Publication: United States
• Language: English