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author:

Song, Wenchao (Song, Wenchao.) [1] | Lu, Chao (Lu, Chao.) [2] | Ling, Xiaobo (Ling, Xiaobo.) [3] | Gu, Jun (Gu, Jun.) [4] | Tu, Mingquan (Tu, Mingquan.) [5] | Lin, Junjie (Lin, Junjie.) [6]

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Abstract:

In this paper, a forecasting-aided state estimation (FASE) method based on Vector Autoregression (VAR) for power system prediction is proposed, which makes full use of the time correlation of dynamic power systems and the space correlation based on physical constraints of massive synchronous phasor measurement data. The real-time states of power systems can be accurately estimated by the proposed method. The effectiveness and accuracy of the proposed VAR-FASE method are verified by the simulation results. © 2022 IEEE.

Keyword:

Forecasting Phase measurement Phasor measurement units Real time systems Regression analysis State estimation Value engineering Vector spaces

Community:

  • [ 1 ] [Song, Wenchao]Tsinghua University, Department of Electrical Engineering, Beijing, China
  • [ 2 ] [Lu, Chao]Tsinghua University, Department of Electrical Engineering, Beijing, China
  • [ 3 ] [Ling, Xiaobo]State Grid Shanghai Municipal Electric Power Company, Shanghai, China
  • [ 4 ] [Gu, Jun]State Grid Shanghai Municipal Electric Power Company, Shanghai, China
  • [ 5 ] [Tu, Mingquan]Fuzhou University, College of Electrical Engineering and Automation, Fuzhou, China
  • [ 6 ] [Lin, Junjie]Fuzhou University, College of Electrical Engineering and Automation, Fuzhou, China

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Year: 2022

Page: 1784-1788

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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