Measurement‐based correlation approach for power system dynamic response estimation. Issue 12 (1st September 2015)

• Record Type: Journal Article
• Authors: Bai, Feifei; Liu, Yong; Liu, Yilu; Sun, Kai; Bhatt, Navin; Del Rosso, Alberto; Farantatos, Evangelos; Wang, Xiaoru
• Is Part Of: IET generation, transmission & distribution. Volume 9:Issue 12(2015)
• Page Start: 1474
• Page End: 1484
• Publication Date: 2015-09-01
• Subjects: power system dynamic stability -- dynamic response -- power system identification -- phasor measurement -- autoregressive processes -- power system interconnection -- power system control -- correlation methods -- Global Positioning System; measurement‐based correlation approach -- power system dynamic response estimation -- online stability assessment -- Global Positioning System synchronised phasor measurement unit -- frequency disturbance recorder -- FDR -- correlation coefficient index -- autoregressive model -- exogenous input identification model -- US Eastern interconnection; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2014.1013
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : Understanding power system dynamics is essential for online stability assessment and control applications. Global positioning system‐synchronised phasor measurement units and frequency disturbance recorders (FDRs) make power system dynamics visible and deliver an accurate picture of the overall operation condition to system operators. However, in the actual field implementations, some measurement data can be inaccessible for various reasons, for example, most notably failure of communication. In this study, a measurement‐based approach is proposed to estimate the missing power system dynamics. Specifically, a correlation coefficient index is proposed to describe the correlation relationship between different measurements. Then, the auto‐regressive with exogenous input identification model is employed to estimate the missing system dynamic response. The US Eastern Interconnection is utilised in this study as a case study. The robustness of the correlation approach is verified by a wide variety of case studies as well. Finally, the proposed correlation approach is applied to the real FDR data for power system dynamic response estimation. The results indicate that the correlation approach could help select better input locations and thus improve the response estimation accuracy.