Power system dynamic state estimation considering correlation of measurement error from PMU and SCADA. (3rd October 2018)

• Record Type: Journal Article
• Authors: Lu, Zigang; Wei, Zhinong; Sun, Yonghui
• Other Names: Manogaran Gunasekaran guestEditor.; Chilamkurti Naveen guestEditor.; Hsu Ching‐Hsien guestEditor.; Vijayakumar V. guestEditor.
• Is Part Of: Concurrency and computation. Volume 31:Number 10(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-10-03
• Subjects: CEKF -- correlation of measurement error -- dynamic state estimation -- PMU -- SCADA; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.4726
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: It is well known that measurements from phasor measurement unit (PMU) or supervisory control and data acquisition (SCADA) are not generally independent. Since the correlation of measurement error is a very representative feature of the actual measurement system, traditional assumptions on error independency are not adequate. In this paper, taking the correlation of measurement error of both PMU and SCADA measurements into consideration, a novel correlated extended Kalman filter (CEKF) is proposed. The actual measurement configurations are analyzed with the consideration of measurement error transfer characteristics. Then, the modified measurement error covariance matrix is calculated by using the point estimation method, which will replace the traditional diagonal variance matrix. At last, IEEE 14‐bus system and 57‐bus system are provided to illustrate the effectiveness and superiority of the method, respectively.