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CSEE Journal of Power and Energy Systems 2022, 8(4): 983-992 https://doi.org/10.17775/CSEEJPES.2021.01270
Open Access | Issue | Published: 25 June 2021

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

Show Author's Information Hongxia Wang,  Bo Wang( ),  Peng Luo,  Fuqi Ma,  Yinyu Zhou,  Mohamed A. Mohamed
School of Electrical Engineering and Automation, Wuhan University, Wuhan 430074, China
Huizhou Power Supply Bureau Co., Ltd., Huizhou 516001, Guangdong Province, China
Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61519, Egypt
Keywords:
random matrix theory, Data characteristics, evolution direction, real-time evaluation, resilient power system
Cite this article:
Wang H, Wang B, Luo P, et al. State Evaluation Based on Feature Identification of Measurement Data: for Resilient Power System. CSEE Journal of Power and Energy Systems, 2022, 8(4): 983-992. https://doi.org/10.17775/CSEEJPES.2021.01270
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Abstract Full text About this article

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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About this article

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

Show Author's information Hongxia Wang, Bo Wang( ), Peng Luo, Fuqi Ma, Yinyu Zhou, Mohamed A. Mohamed
School of Electrical Engineering and Automation, Wuhan University, Wuhan 430074, China
Huizhou Power Supply Bureau Co., Ltd., Huizhou 516001, Guangdong Province, China
Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61519, Egypt

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.

Keywords: random matrix theory, Data characteristics, evolution direction, real-time evaluation, resilient power system

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Received: 19 February 2021
Revised: 01 April 2021
Accepted: 11 May 2021
Published: 25 June 2021
Issue date: July 2022

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© 2021 CSEE

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Acknowledgements

This paper is supported by National Natural Science Foundation of China under Grant No. 51907096.

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