区域综合能源系统响应-恢复融合阶段弹性提升策略

doi:10.1007/s12204-024-2742-z

摘要/Abstract

摘要： 综合能源系统的建设有助于提高用能效率，推动全球能源转型。然而，近年来极端自然灾害事件发生给综合能源系统安全稳定运行带来了一定的威胁，有必要提高综合能源系统抵御灾害、降低灾害损失并尽快恢复能源供应的能力，即提高其弹性。本文针对灾中响应和灾后恢复两个具有较强关联性的阶段展开研究，建立了弹性导向的综合能源系统灾中响应和灾后恢复融合阶段主从优化模型。主模型形成最优故障抢修计划，子模型确定最优供能恢复方案，并以元件修复状态和元件运行状态为耦合变量，构建了协同优化框架。将主-从模型融合为一个两阶段鲁棒优化模型进行迭代求解，以制定最优的综合能源系统故障恢复策略，提升系统在灾中响应和灾后恢复融合阶段的弹性。

关键词: 综合能源系统, 自然灾害, 灾中响应, 灾后恢复, 弹性提升, 主从优化

Abstract: Deployment of integrated energy system is conducive to improving energy efficiency and achieving the transformation of the global energy system. However, recent appearance of extreme natural disasters poses a great challenge to the safe and stable operation of the integrated energy system. Therefore, the resilience of the integrated energy system, namely the ability to anticipate, withstand, respond to and recover to normal state, is to be enhanced urgently. This paper proposes a master-slave optimization model for the resilience enhancement of integrated energy system in the integrated stage of disaster response and post-disaster recovery, in view of the strong correlation between the two stages. The master model develops the optimal fault repair plan, and the sub model determines the optimal energy supply recovery scheme. Based on the master-slave model, which adopts the repair and operation state of the component as coupling variables, a coordinated optimization framework is constructed. Then, the master-slave model is merged into a two-stage robust optimization model for iterative solution in order to develop the optimal fault repair strategy and energy supply recovery scheme of the integrated energy system, enhancing its resilience in the integrated stage of disaster response and post-disaster recovery.

中图分类号:

TM732

. 区域综合能源系统响应-恢复融合阶段弹性提升策略[J]. J Shanghai Jiaotong Univ Sci, 2026, 31(2): 515-527.

You Minghao, Gu Jie, Liu Shuqi. Regional Integrated Energy System Resilience Enhancement Strategy at the Integrated Stage of Disaster Response and Post-Disaster Recovery[J]. J Shanghai Jiaotong Univ Sci, 2026, 31(2): 515-527.

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