LAPSE:2018.0581
Published Article
LAPSE:2018.0581
Parameter Estimation of Electromechanical Oscillation Based on a Constrained EKF with C&I-PSO
Yonghui Sun, Yi Wang, Linquan Bai, Yinlong Hu, Denis Sidorov, Daniil Panasetsky
September 21, 2018
By combining together the extended Kalman filter with a newly developed C&I particle swarm optimization algorithm (C&I-PSO), a novel estimation method is proposed for parameter estimation of electromechanical oscillation, in which critical physical constraints on the parameters are taken into account. Based on the extended Kalman filtering algorithm, the constrained parameter estimation problem is formulated via the projection method. Then, by utilizing the penalty function method, the obtained constrained optimization problem could be converted into an equivalent unconstrained optimization problem; finally, the C&I-PSO algorithm is developed to address the unconstrained optimization problem. Therefore, the parameters of electromechanical oscillation with physical constraints can be successfully estimated and better performed. Finally, the effectiveness of the obtained results has been illustrated by several test systems.
Keywords
C&, constrained parameter estimation, extended Kalman filter, I particle swarm optimization, power systems, ringdown detection
Suggested Citation
Sun Y, Wang Y, Bai L, Hu Y, Sidorov D, Panasetsky D. Parameter Estimation of Electromechanical Oscillation Based on a Constrained EKF with C&I-PSO. (2018). LAPSE:2018.0581
Author Affiliations
Sun Y: College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, China
Wang Y: College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, China
Bai L: ABB Inc., Raleigh, NC 27606, USA
Hu Y: College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, China
Sidorov D: Melentiev Energy Systems Institute, Russian Academy of Sciences, Irkutsk 664033, Russia
Panasetsky D: Melentiev Energy Systems Institute, Russian Academy of Sciences, Irkutsk 664033, Russia
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Journal Name
Energies
Volume
11
Issue
8
Article Number
E2059
Year
2018
Publication Date
2018-08-08
Published Version
ISSN
1996-1073
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PII: en11082059, Publication Type: Journal Article
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LAPSE:2018.0581
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doi:10.3390/en11082059
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Sep 21, 2018
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Calvin Tsay
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