A Cyber-Secured Operation for Water-Energy Nexus

Pengfei Zhao, Chenghong Gu, Zhidong Cao, Da Xie, Fei Teng

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12 Citations (SciVal)
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The wide implementation of information and communication technologies (ICT) cause power system operations exposed to cyber-attacks. Meanwhile, the tendency of integrated multi energy vectors has worsened this issue with multiple energy coupled. This paper proposes a two-stage risk-averse mitigation strategy for water-energy systems (WESs), incorporating power, natural gas and water systems against false data injection attacks (FDIA) under water-energy nexus. The FDIA on individual sub-systems is modelled through hampering false data integrity to the systems. An innovative two-stage risk-averse distributionally robust optimization (RA-DRO) is proposed to mitigate uneconomic operation and provides a coordinated optimal load shedding scheme for the nexus system security. A coherent risk measure, Conditional Value-at-Risk is incorporated into the RA-DRO to model risk. A Benders decomposition method is used to solve the original NP-hard RA-DRO problem. Case studies are demonstrated on a WES under water-energy nexus and results show that the effectiveness of the method to mitigate risks from potential FDIA and renewable uncertainties. This research provides WES operators an economic system operation tool by optimally coordinating energy infrastructures and implementing reasonable load shedding to enhance cybersecurity.
Original languageEnglish
Article number9290107
Pages (from-to)3105 - 3117
Number of pages13
JournalIEEE Transactions on Power Systems
Issue number4
Early online date10 Dec 2020
Publication statusPublished - 31 Jul 2021

Bibliographical note

Funding Information:
Manuscript received April 11, 2020; revised August 20, 2020 and November 30, 2020; accepted December 5, 2020. Date of publication December 10, 2020; date of current version June 18, 2021. This work was supported by the National Science Fund for Distinguished Young Scholars, 72025404. This work was supported by the National Natural Science Foundation of China under Grants 72042018 and 71621002. Paper no. TPWRS-00599-2020. (Corresponding author: Zhidong Cao.) Pengfei Zhao and Zhidong Cao are with the Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China, and also with the School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100190, China (e-mail: [email protected]; [email protected]).

Publisher Copyright:
© 1969-2012 IEEE.


  • Distributionally robust optimization
  • False data injection attacks
  • Integrated energy system
  • Mitigation strategy
  • Risk aversion
  • Water-energy nexus

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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