State Evaluation Based on Feature Identification of Measurement Data: for Resilient Power System

Hongxia Wang; Bo Wang; Peng Luo; Fuqi Ma; Yinyu Zhou; Mohamed A. Mohamed

doi:10.17775/CSEEJPES.2021.01270

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State Evaluation Based on Feature Identification of Measurement Data: for Resilient Power System

Regular Papers | 更新时间：2026-10-15

- State Evaluation Based on Feature Identification of Measurement Data: for Resilient Power System
- CSEE Journal of Power and Energy Systems Vol. 8, Issue 4, Pages: 983-992(2022)
- 作者机构：
  
  1. School of Electrical Engineering and Automation, Wuhan University,Wuhan,China
  2. Huizhou Power Supply Bureau Co., Ltd.,Guangdong Province,Huizhou,China
  3. Electrical Engineering Department, Faculty of Engineering, Minia University, Minia,Egypt
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2021.01270
  CLC：
- Published：01 July 2022
- 稿件说明：
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Hongxia Wang, Bo Wang, Peng Luo, et al. State Evaluation Based on Feature Identification of Measurement Data: for Resilient Power System[J]. CSEE Journal of Power and Energy Systems, 2022, 8(4): 983-992.
DOI：

Hongxia Wang, Bo Wang, Peng Luo, et al. State Evaluation Based on Feature Identification of Measurement Data: for Resilient Power System[J]. CSEE Journal of Power and Energy Systems, 2022, 8(4): 983-992. DOI： 10.17775/CSEEJPES.2021.01270.

摘要

Abstract

Resilient power systems urgently need real-time evaluation of their operational states. By mining the characteristics of the grid operational data and mapping them to the operational state

this paper proposes a method to evaluate the real-time state and the evolution direction of power systems. First

the state evaluation matrix is constructed using nodal voltages. Then

from the data-driven perspective

the grid state is embodied in the operational data change. Furthermore

four indicators are proposed to characterize the power grid state-from inherent physical and operating characteristics perspectives. Finally

through the simulations of a real power grid in China

it is shown that the method proposed in this paper can adequately characterize the power grid state

and is robust against bad data.

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