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Distributed security state estimation-based carbon emissions and economic cost analysis for cyber–physical power systems under hybrid attacks

Author

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  • Du, Dajun
  • Zhu, Minggao
  • Wu, Dakui
  • Li, Xue
  • Fei, Minrui
  • Hu, Yukun
  • Li, Kang

Abstract

Sustainable cyber–physical power systems (CPPSs) significantly reduce carbon emissions due to climate change. However, when the data exchange in CPPSs suffers from hybrid attacks, the distributed state estimation and optimal power flow (OPF) analysis will inevitably be compromised, leading to inadequate or faulty scheduling of clean energy and thermal power generations and further affecting the total carbon emissions and economic cost. To address these problems, this paper proposes a novel consensus-based distributed security state estimation (DSSE) method for CPPSs, which is used to analyze the impact of hybrid attacks on carbon emissions and economic cost. Firstly, the incomplete and non-authentic data features caused by hybrid attacks are described, and their influence on distributed state estimation model is analyzed. A new residual-based attack detection method is then constructed in each subregion, where secure and non-secure sets are employed to describe whether the subregion is attacked and the compensation mechanism is designed for the non-secure set. Secondly, considering data compensation, distributed state estimation model is reconstructed, and a distributed security state estimation method under hybrid attacks is proposed while its convergence condition is derived. Thirdly, the impacts of hybrid attacks on carbon emissions and economic costs are analyzed based on the proposed DSSE method. Finally, experimental results confirm the validity of the theoretic analysis.

Suggested Citation

  • Du, Dajun & Zhu, Minggao & Wu, Dakui & Li, Xue & Fei, Minrui & Hu, Yukun & Li, Kang, 2024. "Distributed security state estimation-based carbon emissions and economic cost analysis for cyber–physical power systems under hybrid attacks," Applied Energy, Elsevier, vol. 353(PA).
    • Handle: RePEc:eee:appene:v:353:y:2024:i:pa:s030626192301365x
    DOI: 10.1016/j.apenergy.2023.122001
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    as
    1. Wang, Huaizhi & Meng, Anjian & Liu, Yitao & Fu, Xueqian & Cao, Guangzhong, 2019. "Unscented Kalman Filter based interval state estimation of cyber physical energy system for detection of dynamic attack," Energy, Elsevier, vol. 188(C).
    2. Luo, Xiaoyuan & Wang, Xinyu & Zhang, Mingyue & Guan, Xinping, 2019. "Distributed detection and isolation of bias injection attack in smart energy grid via interval observer," Applied Energy, Elsevier, vol. 256(C).
    3. Wang, Rutian & Wen, Xiangyun & Wang, Xiuyun & Fu, Yanbo & Zhang, Yu, 2022. "Low carbon optimal operation of integrated energy system based on carbon capture technology, LCA carbon emissions and ladder-type carbon trading," Applied Energy, Elsevier, vol. 311(C).
    4. Prinsloo, Gerro & Dobson, Robert & Mammoli, Andrea, 2018. "Synthesis of an intelligent rural village microgrid control strategy based on smartgrid multi-agent modelling and transactive energy management principles," Energy, Elsevier, vol. 147(C), pages 263-278.
    5. Zhao, Haitao & Jiang, Peng & Chen, Zhe & Ezeh, Collins I. & Hong, Yuanda & Guo, Yishan & Zheng, Chenghang & Džapo, Hrvoje & Gao, Xiang & Wu, Tao, 2019. "Improvement of fuel sources and energy products flexibility in coal power plants via energy-cyber-physical-systems approach," Applied Energy, Elsevier, vol. 254(C).
    6. Qian, Tong & Tang, Wenhu & Wu, Qinghua, 2020. "A fully decentralized dual consensus method for carbon trading power dispatch with wind power," Energy, Elsevier, vol. 203(C).
    7. Tan, Qinliang & Ding, Yihong & Ye, Qi & Mei, Shufan & Zhang, Yimei & Wei, Yongmei, 2019. "Optimization and evaluation of a dispatch model for an integrated wind-photovoltaic-thermal power system based on dynamic carbon emissions trading," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    8. Wen Yang & Xiaofan Wang & Hongbo Shi, 2011. "Optimal consensus-based distributed estimation with intermittent communication," International Journal of Systems Science, Taylor & Francis Journals, vol. 42(9), pages 1521-1529.
    9. Zhang, Sufang & He, Yongxiu, 2013. "Analysis on the development and policy of solar PV power in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 393-401.
    10. Zeng, Jingjing & Bao, Rui & McFarland, Michael, 2022. "Clean energy substitution: The effect of transitioning from coal to gas on air pollution," Energy Economics, Elsevier, vol. 107(C).
    11. Saad, Ahmed A. & Faddel, Samy & Mohammed, Osama, 2019. "A secured distributed control system for future interconnected smart grids," Applied Energy, Elsevier, vol. 243(C), pages 57-70.
    12. Tan, Qinliang & Ding, Yihong & Zheng, Jin & Dai, Mei & Zhang, Yimei, 2021. "The effects of carbon emissions trading and renewable portfolio standards on the integrated wind–photovoltaic–thermal power-dispatching system: Real case studies in China," Energy, Elsevier, vol. 222(C).
    13. Zhang, Wei & Li, Guoxiang & Guo, Fanyong, 2022. "Does carbon emissions trading promote green technology innovation in China?," Applied Energy, Elsevier, vol. 315(C).
    14. Marania Hopuare & Tao Manni & Victoire Laurent & Keitapu Maamaatuaiahutapu, 2022. "Investigating Wind Energy Potential in Tahiti, French Polynesia," Energies, MDPI, vol. 15(6), pages 1-13, March.
    15. Tan, Zhongfu & Tan, Qingkun & Rong, Menglei, 2018. "Analysis on the financing status of PV industry in China and the ways of improvement," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 409-420.
    16. Xu, Jiuping & Wang, Fengjuan & Lv, Chengwei & Huang, Qian & Xie, Heping, 2018. "Economic-environmental equilibrium based optimal scheduling strategy towards wind-solar-thermal power generation system under limited resources," Applied Energy, Elsevier, vol. 231(C), pages 355-371.
    17. Lai, Kexing & Illindala, Mahesh & Subramaniam, Karthikeyan, 2019. "A tri-level optimization model to mitigate coordinated attacks on electric power systems in a cyber-physical environment," Applied Energy, Elsevier, vol. 235(C), pages 204-218.
    18. Anasis, John G. & Khalil, Mohammad Aslam Khan & Butenhoff, Christopher & Bluffstone, Randall & Lendaris, George G., 2019. "Optimal energy resource mix for the US and China to meet emissions pledges," Applied Energy, Elsevier, vol. 238(C), pages 92-100.
    Full references (including those not matched with items on IDEAS)

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