Resilience enhancement of cyber–physical distribution systems via mobile power sources and unmanned aerial vehicles

IF 11 1区 工程技术 Q1 ENGINEERING, INDUSTRIAL Reliability Engineering & System Safety Pub Date : 2025-02-01 Epub Date: 2024-11-05 DOI:10.1016/j.ress.2024.110603
Meng Tian , Ziyang Zhu , Zhengcheng Dong , Le Zhao , Hongtai Yao
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Abstract

Mobile power sources (MPS) and unmanned aerial vehicles (UAV) are critical and flexible resources to enhance the resilience of cyber–physical distribution systems. However, they are usually independently planned and dispatched. In this paper, considering the cyber–physical interdependence, topology reconfiguration and planned distribution generator islanding, an allocation and dispatch strategy of MPSs and UAVs is proposed. Before an event, a two-stage stochastic optimization based allocation model is built to pre-position MPSs and UAVs considering the uncertainty of events. After the event, a dispatch model is proposed to identify routings of MPSs and UAVs to restore electricity services. Note that both the models are mixed-integer nonlinear three-dimensional (3D) problems. As the optimal service radius and height of a UAV are independent with other variables, these two models are decomposed into two parts, i.e., one part to calculate the optimal service radius and height, and the other to identify resilience enhancement strategy. Then the two models are transformed into a mixed-integer convex programming solved by Progressive Hedging algorithm and a mixed-integer second-order cone programming, respectively. The effectiveness is verified on the modified IEEE 33-node and 123-node test systems. Numerical results highlight the necessity of co-optimizing MPSs and UAVs on cyber–physical distribution systems.
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通过移动电源和无人驾驶飞行器增强网络物理分配系统的弹性
移动电源(MPS)和无人机(UAV)是增强网络物理配电系统弹性的关键和灵活资源。然而,它们通常是独立计划和调度的。本文考虑网络物理相互依赖、拓扑重构和规划配电发电机孤岛等问题,提出了一种mps和无人机的分配调度策略。在事件发生前,考虑事件的不确定性,建立了基于两阶段随机优化的分配模型,对mps和无人机进行了预先定位。在事件发生后,提出了一种调度模型来确定mps和无人机的路由以恢复电力服务。注意,这两个模型都是混合整数非线性三维(3D)问题。由于无人机的最优服务半径和高度与其他变量无关,因此将这两个模型分解为两部分,一部分用于计算最优服务半径和高度,另一部分用于识别弹性增强策略。然后将这两个模型分别转化为用渐进式套期保值算法求解的混合整数凸规划和混合整数二阶锥规划。在改进的IEEE 33节点和123节点测试系统上验证了该方法的有效性。数值计算结果强调了网络物理配送系统中mps和无人机协同优化的必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Reliability Engineering & System Safety
Reliability Engineering & System Safety 管理科学-工程:工业
CiteScore
15.20
自引率
39.50%
发文量
621
审稿时长
67 days
期刊介绍: Elsevier publishes Reliability Engineering & System Safety in association with the European Safety and Reliability Association and the Safety Engineering and Risk Analysis Division. The international journal is devoted to developing and applying methods to enhance the safety and reliability of complex technological systems, like nuclear power plants, chemical plants, hazardous waste facilities, space systems, offshore and maritime systems, transportation systems, constructed infrastructure, and manufacturing plants. The journal normally publishes only articles that involve the analysis of substantive problems related to the reliability of complex systems or present techniques and/or theoretical results that have a discernable relationship to the solution of such problems. An important aim is to balance academic material and practical applications.
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