与抢修人员和移动电源协作,对不平衡配电系统进行多重叠灾难滚动恢复

IF 4.8 2区 工程技术 Q2 ENERGY & FUELS
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引用次数: 0

摘要

传统的配电系统恢复策略可以处理非重叠灾难,通常是单个 N-k 故障,而不是多重重叠灾难。多重重叠灾难指的是系统发生多个 N-k 故障,在系统完全恢复前又发生新的 N-k 故障的情况。为解决多重重叠灾难下的恢复问题,提出了一种同时考虑抢修人员(RC)和移动电源(MPS)的不平衡配电系统滚动恢复模型。所提出的滚动恢复模型可以根据电网拓扑结构和每次灾难重叠时刻每个弹性资源的状态,自动优化之前的恢复策略。在改进的 IEEE 33 节点测试系统上进行了案例研究,以演示多重叠灾难恢复的概念。与将多重叠灾害视为多个单独灾害的传统方法相比,案例研究表明,所提出的模型可减少约 6.91% 的甩负荷,这验证了所提出的方法在灾害重叠时刻更新恢复策略的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-overlapping disaster rolling recovery of unbalanced distribution systems collaborated with repair crews and mobile power sources

Traditional distribution system recovery strategies can handle non-overlapping disasters, typically a single N-k failure, rather than multi-overlapping disasters. Multi-overlapping disaster refers to a scenario in which a system experiences multiple N-k failures, with a new N-k failure occurring before the system has been fully restored from the previous one. To address the recovery problem under multi-overlapping disasters, a rolling recovery model for unbalanced distribution systems that considers both repair crews (RCs) and mobile power sources (MPSs) is proposed. The proposed rolling recovery model can automatically optimize preceding recovery strategies based on the grid topology and the state of each resilient resource at the overlapping moment of each disaster. Case studies are conducted on the modified IEEE 33-node test system to demonstrate the concept of multi-overlapping disaster recovery. Compared to traditional methods that treat multi-overlapping disasters as multiple individual disasters, the case studies demonstrate that the proposed model can reduce load shedding by about 6.91 %, which verifies the effectiveness of the proposed methodology for updating recovery strategies at overlapping moments of disasters.

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来源期刊
Sustainable Energy Grids & Networks
Sustainable Energy Grids & Networks Energy-Energy Engineering and Power Technology
CiteScore
7.90
自引率
13.00%
发文量
206
审稿时长
49 days
期刊介绍: Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.
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