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中国管理科学 ›› 2022, Vol. 30 ›› Issue (12): 86-95.doi: 10.16381/j.cnki.issn1003-207x.2019.1887

• 论文 • 上一篇    

基于线性分段恢复函数的基础设施韧性分析模型——以C县电力系统网络为例

高蕾, 龚晶   

  1. 暨南大学公共管理学院/应急管理学院,广东 广州510632
  • 收稿日期:2019-11-19 修回日期:2020-04-24 发布日期:2023-01-10
  • 通讯作者: 龚晶(1976-),女(汉族),湖北荆门人,暨南大学公共学院/应急管理学院,副教授,硕士生导师,研究方向:应急决策理论与方法、弹性应急网络管理,Email:tgongjing@jnu.edu.cn. E-mail:tgongjing@jnu.edu.cn
  • 基金资助:
    国家自然科学基金资助青年项目(G010301);广东省自然科学基金资助项目(S2013010014179)

Analysis Model for Infrastructure Resilience Based on Linear Piecewise Recovery Function——A Case Study of C County Power Network

GAO Lei, GONG Jing   

  1. School of Public Administration & Emergency Management, Jinan University, Guangzhou 510632, China
  • Received:2019-11-19 Revised:2020-04-24 Published:2023-01-10
  • Contact: 龚晶 E-mail:tgongjing@jnu.edu.cn

摘要: 针对近年来一系列突发事件冲击和破坏着城市关键基础设施系统的正常运行,并造成了较为严重的社会后果的现实问题,提出了如何保护关键基础设施系统的研究问题,以使基础设施系统能够对灾害情景做出迅速的响应,并迅速地处理以恢复到常态。本研究基于三种典型的恢复函数提出了线性分段恢复函数,构建了关键基础设施系统韧性分析模型,并用蒙特卡洛模拟的方法应用到C县的电力系统网络加以验证,得到了该韧性分析模型不仅可以帮助决策者在灾害情境下权衡预算成本和韧性的关系,也可以识别关键基础设施系统网络中需要保护的关键节点,从而实现对关键基础设施系统的针对性保护的结论。本研究构建的韧性分析模型有为灾害情境下对电力系统采取针对性保护的现实价值,和开拓了对基础设施系统进行保护研究的分析模型的理论价值。

关键词: 网络韧性;关键基础设施系统;网络流优化;应急管理;数学规划

Abstract: Recent disasters,such as earthquakes, typhoons, and terrorist attacks, disrupted operations of critical infrastructure systems and even destroyed functions of our society. Therefore, it is necessary and important to maintain critical infrastructure systems which are not only cost-effective but also able to respond quickly, handle smoothly, and recover promptly from disruptions. To achieve this goal, a linear piece-wise recovery function is proposed based on three other recovery functions and then develops a resilience analysis model. The proposed model is applied to the decision-making processes of improving the resilience of the power system in C county. C county is a coastal area vulnerable to hurricanes and its power network consists of 958 arcs and 939 nodes, including 4 supply nodes and 56 transfer nodes. In addition, to estimate the probability of nodes being disrupted and identify the critical nodes that require priority protection, different disaster scenarios are simulated according to the type, severity, and extent of the disaster in C county. The results show that: (1) this linear piece-wise recovery function enables tradeoff between a cost minimum system and a resilient system; (2) this resilience analysis model can distinguish the critical nodes in infrastructure systems and give the best and highly individualized approach to protect critical infrastructure systems. Overall, a new analysis model is developed for the protection of the critical infrastructure systems and therefore the targeted strategies and suggestions can be provided to protect the critical infrastructure systems.

Key words: network resilience; critical infrastructure systems; network flow optimization; emergency management; mathematic programming

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