Input Signals Selection for Measurement-based Power System ARX Dynamic Model Response Estimation
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Liu, Yilu
Sun, Kai
Bhatt, Navin
Del Rosso, Alberto
Farantatos, Evangelos
Wang, Xiaoru
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Chicago, Illinois, USA
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Abstract
This paper proposes a measurement-based approach to optimize the inputs of Auto-Regressive with eXogenous input (ARX) model identification in large power systems. Correlation Coefficient Index (CCI) is defined in this paper and Correlation Coefficient Map (CCM) is developed for the US Eastern Interconnection (EI) to show the correlation between any two power system output measurement signals visually. This approach is verified with EI system simulation data and applied to Frequency Disturbance Recorder (FDR) measurement data to estimate system dynamic response. The verification result shows that the number of ARX model inputs can be decreased and the estimation accuracy can be ensured by using the proposed approach.
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2014 IEEE PES T&D Conference and Exposition
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© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Science & Technology
Engineering, Electrical & Electronic
Engineering
Correlation coefficient index
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Bai, F; Liu, Y; Sun, K; Bhatt, N; Del Rosso, A; Farantatos, E; Wang, X, Input Signals Selection for Measurement-based Power System ARX Dynamic Model Response Estimation, 2014 IEEE PES T&D Conference and Exposition, 2014