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

Journal Article · Mon Jul 01 04:00:00 EDT 2019 · IEEE Transactions on Power Systems

DOI:https://doi.org/10.1109/TPWRS.2019.2894769· OSTI ID:1567197

Zhao, Junbo ^[1]; Gómez-Expósito, Antonio ^[2]; Netto, Marcos ^[3]; Mili, Lamine ^[3]; Abur, Ali ^[4]; Terzija, Vladimir ^[5]; Kamwa, Innocent ^[6]; Pal, Bikash ^[7]; Singh, Abhinav Kumar ^[8]; Qi, Junjian ^[9]; Huang, Zhenyu ^[10]; Meliopoulos, Sakis ^[11]

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1. Virginia Polytechnic Institute
2. University of Seville
3. Virginia Tech
4. Northeastern University
5. The University of Manchester
6. Hydro-Quebec Research Institute
7. Imperial College London
8. University of Southampton
9. University of Central Florida
10. BATTELLE (PACIFIC NW LAB)
11. Georgia Institute Of Technology

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)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1567197
• Report Number(s): PNNL-SA-147864
• Journal Information: IEEE Transactions on Power Systems, Journal Name: IEEE Transactions on Power Systems Journal Issue: 4 Vol. 34
• Country of Publication: United States
• Language: English

Related Subjects

task force
dynamic state estimation
Parameter Estimation
Electric Power Systems