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Risk management for integrated power and natural gas systems against extreme weather: A coalitional insurance contract approach

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  • Xie, Haipeng
  • Sun, Xiaotian
  • Fu, Wei
  • Chen, Chen
  • Bie, Zhaohong

Abstract

Integrated power and natural gas systems (IPGSs) are vulnerable to extreme weather. The system operators are facing risks of huge economic losses. An insurance could be the appropriate approach for system operators to manage and transfer the risks of huge economic losses to the third-party entities. However, conventional standalone insurance design will induce the free-ride phenomenon and the missing of integration incentive in IPGSs. Thus, to bridge the gaps, we proposed a novel coalitional insurance design for the IPGSs against the extreme weather. To control the risk of insurer insolvency, the premium of the coalitional insurance is determined based on the resilience assessment-based actuarial framework. To provide appropriate incentive in inter-energy assistance, the indemnity is allocated by a combined damage-based and assistance-based policy. Asymmetric Nash bargaining is adopted to ensure the fair allocation of indemnity. Favorable properties include budget balanced, low safe loading cost, free-ride averse, and integration beneficial are theoretically and numerically proved. Numerical tests are conducted on the modified IEEE 39-bus Belgium 20-node IPGS to validate the effectiveness of the proposed coalitional insurance contract design.

Suggested Citation

  • Xie, Haipeng & Sun, Xiaotian & Fu, Wei & Chen, Chen & Bie, Zhaohong, 2023. "Risk management for integrated power and natural gas systems against extreme weather: A coalitional insurance contract approach," Energy, Elsevier, vol. 263(PB).
  • Handle: RePEc:eee:energy:v:263:y:2023:i:pb:s0360544222026366
    DOI: 10.1016/j.energy.2022.125750
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    1. Li, Xue & Du, Xiaoxue & Jiang, Tao & Zhang, Rufeng & Chen, Houhe, 2022. "Coordinating multi-energy to improve urban integrated energy system resilience against extreme weather events," Applied Energy, Elsevier, vol. 309(C).
    2. Malavasi, Matteo & Peters, Gareth W. & Shevchenko, Pavel V. & Trück, Stefan & Jang, Jiwook & Sofronov, Georgy, 2022. "Cyber risk frequency, severity and insurance viability," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 90-114.
    3. Cong, Di & Liang, Lingling & Jing, Shaoxing & Han, Yongming & Geng, Zhiqiang & Chu, Chong, 2021. "Energy supply efficiency evaluation of integrated energy systems using novel SBM-DEA integrating Monte Carlo," Energy, Elsevier, vol. 231(C).
    4. Kaivan Munshi & Mark Rosenzweig, 2016. "Networks and Misallocation: Insurance, Migration, and the Rural-Urban Wage Gap," American Economic Review, American Economic Association, vol. 106(1), pages 46-98, January.
    5. Tran, Trung Hieu & French, Simon & Ashman, Rhys & Kent, Edward, 2018. "Linepack planning models for gas transmission network under uncertainty," European Journal of Operational Research, Elsevier, vol. 268(2), pages 688-702.
    6. Matteo Malavasi & Gareth W. Peters & Pavel V. Shevchenko & Stefan Truck & Jiwook Jang & Georgy Sofronov, 2021. "Cyber Risk Frequency, Severity and Insurance Viability," Papers 2111.03366, arXiv.org, revised Mar 2022.
    7. Hasanzad, Fardin & Rastegar, Hasan, 2022. "Application of optimal hardening for improving resilience of integrated power and natural gas system in case of earthquake," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    8. Kshetri, Nir, 2020. "The evolution of cyber-insurance industry and market: An institutional analysis," Telecommunications Policy, Elsevier, vol. 44(8).
    9. Wang, Zekai & Ding, Tao & Jia, Wenhao & Huang, Can & Mu, Chenggang & Qu, Ming & Shahidehpour, Mohammad & Yang, Yongheng & Blaabjerg, Frede & Li, Li & Wang, Kang & Chi, Fangde, 2022. "Multi-stage stochastic programming for resilient integrated electricity and natural gas distribution systems against typhoon natural disaster attacks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    10. Wang, Han & Hou, Kai & Zhao, Junbo & Yu, Xiaodan & Jia, Hongjie & Mu, Yunfei, 2022. "Planning-Oriented resilience assessment and enhancement of integrated electricity-gas system considering multi-type natural disasters," Applied Energy, Elsevier, vol. 315(C).
    11. DE WOLF, Daniel & SMEERS, Yves, 2000. "The gas transmission problem solved by an extension of the simplex algorithm," LIDAM Reprints CORE 1489, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    12. Daniel De Wolf & Yves Smeers, 2000. "The Gas Transmission Problem Solved by an Extension of the Simplex Algorithm," Management Science, INFORMS, vol. 46(11), pages 1454-1465, November.
    13. Lv, Chaoxian & Liang, Rui & Jin, Wei & Chai, Yuanyuan & Yang, Tiankai, 2022. "Multi-stage resilience scheduling of electricity-gas integrated energy system with multi-level decentralized reserve," Applied Energy, Elsevier, vol. 317(C).
    14. Aldarajee, Ammar H.M. & Hosseinian, Seyed H. & Vahidi, Behrooz, 2020. "A secure tri-level planner-disaster-risk-averse replanner model for enhancing the resilience of energy systems," Energy, Elsevier, vol. 204(C).
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    1. Guo, Kun & Liu, Fengqi & Sun, Xiaolei & Zhang, Dayong & Ji, Qiang, 2023. "Predicting natural gas futures’ volatility using climate risks," Finance Research Letters, Elsevier, vol. 55(PA).

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