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Optimal Resilience and Risk-Driven Strategies for Pre-Disaster Protection of Electric Power Systems against Uncertain Disaster Scenarios

Author

Listed:
  • Chen Wang

    (State Grid Shanghai Electric Power Research Institute, Shanghai 200437, China)

  • Chao Zhang

    (Shanghai Key Laboratory of Financial Information Technology, Shanghai University of Finance and Economics, Shanghai 200433, China)

  • Ling Luo

    (State Grid Shanghai Electric Power Research Institute, Shanghai 200437, China)

  • Xiaoman Qi

    (State Grid Shanghai Electric Power Research Institute, Shanghai 200437, China)

  • Jingjing Kong

    (School of Civil Engineering, Shanghai Normal University, Shanghai 201418, China)

Abstract

Pre-disaster protection strategies are essential for enhancing the resilience of electric power systems against natural disasters. Considering the budgets for protection strategies, the dependency of other infrastructure systems on electricity, and the uncertainty of disaster scenarios, this paper develops risk-neutral and risk management models of strategies for pre-disaster protection. The risk-neutral model is a stochastic model designed to maximize the expected value of resilience (EVR) of the integrated system. The risk management model is a multi-objective model prioritizing the minimization of risk metrics as a secondary goal alongside maximizing the EVR. A case study conducted on the energy infrastructure systems in the Greater Toronto Area (GTA) validates the effectiveness of the models. The findings reveal the following: (i) increasing the budget enhances the EVR of the integrated system; however, beyond a certain budget threshold, the incremental benefits to the EVR significantly diminish; (ii) reducing the value of the downside risk often results in an increase in the EVR, with the variation in Pareto-optimal solutions between the two objectives being non-linear; and (iii) whether for the risk-neutral or risk management protection strategies, there are reasonable budgets when considering disaster intensity and the cost of protection measures. The models can help decision-makers to select effective protection measures for natural disasters.

Suggested Citation

  • Chen Wang & Chao Zhang & Ling Luo & Xiaoman Qi & Jingjing Kong, 2024. "Optimal Resilience and Risk-Driven Strategies for Pre-Disaster Protection of Electric Power Systems against Uncertain Disaster Scenarios," Energies, MDPI, vol. 17(15), pages 1-24, July.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:15:p:3619-:d:1441288
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    References listed on IDEAS

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