基于最优路径的配电网弹性恢复力提升策略

张新宇,姚方,文福拴,岳文全,薛栋烽

分布式能源 ›› 2023, Vol. 8 ›› Issue (6) : 20-26.

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分布式能源 ›› 2023, Vol. 8 ›› Issue (6) : 20-26. DOI: 10.16513/j.2096-2185.DE.2308603
学术研究

基于最优路径的配电网弹性恢复力提升策略

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A Strategy for Enhancing the Elastic Resilience of Distribution Networks Based on Optimal Path

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摘要

针对极端天气下配网系统的弹性恢复力提升问题,提出长短时间尺度的两阶段电力系统弹性恢复力提升策略。灾害发生后短时间内通过布置分布式电源和联络开关,对配电网进行孤岛划分和网络重构以恢复短时供电;考虑极端天气对交通网的影响,极端灾害发生一段时间后由检修小组在最短时间内完成维修以最小化负荷削减成本。通过协同优化建立长短时间故障演变分析的鲁棒优化(robust optimization,RO)模型,并采用列与约束生成(column-and-constraint generation, C&CG)算法进行求解;最后进行算例分析,验证所提模型对提升配电网弹性能力的有效性。

Abstract

This article proposes a two-stage strategy for improving the elastic resilience of distribution network systems under extreme weather conditions, with a long and short time scale. After a disaster occurs, the distribution network is isolated and reconstructed to restore short-term power supply by arranging distributed power sources and interconnection switches in a short period of time. Considering the impact of extreme weather on the transportation network after an extreme disaster occurs, the maintenance team needs to complete maintenance in the shortest possible time to minimize load reduction costs. For analyzing the evolution of long and short-term faults, a robust optimization (RO) model is established through collaborative optimization, which is solved using column and constraint generation (C&CG) algorithm. Finally, case studies are conducted to verify the effectiveness of the proposed model in improving the elastic resilience of distribution networks.

关键词

极端天气 / 电力系统弹性 / 两阶段鲁棒优化模型 / 列与约束生成(C&CG)算法

Key words

extreme weather / power system elasticity / two-stage robust optimization model / column-and-constraint (C&CG) generation

引用本文

导出引用
张新宇, 姚方, 文福拴, . 基于最优路径的配电网弹性恢复力提升策略[J]. 分布式能源. 2023, 8(6): 20-26 https://doi.org/10.16513/j.2096-2185.DE.2308603
Xinyu ZHANG, Fang YAO, Fushuan WEN, et al. A Strategy for Enhancing the Elastic Resilience of Distribution Networks Based on Optimal Path[J]. Distributed Energy Resources. 2023, 8(6): 20-26 https://doi.org/10.16513/j.2096-2185.DE.2308603
中图分类号: TK01; TM76   

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基金

山西省回国留学人员科研教研资助项目(2022-005)

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