暴雨灾害下考虑多重不确定性的配电系统应急资源韧性规划(网络首发)

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  • 国网山西省电力公司经济技术研究院

网络出版日期: 2024-01-15

基金资助

国网山西省电力公司科技项目(520533220007)


Resilience Planning of Power Distribution System Emergency Resources Considering Multiple Uncertainties Under Heavy Rain Disasters

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  • (Economic and Technical Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030000, China)

Online published: 2024-01-15

摘要

近年来,暴雨灾害对配电网可靠供电的影响日益突出,在大范围多点严重故障等情况下,重要负荷保供极具挑战。合理部署应急资源,有助于减少系统重要负荷损失,进而提升配电系统韧性。本文提出了一种暴雨灾害下考虑多重不确定性的配电系统应急资源韧性规划方法,考虑应急电源和应急储能,建立了配电系统韧性提升的双层规划模型,上层模型以投资成本与负荷损失的净费用最小为目标,下层模型以多种孤岛场景下的综合负荷损失最小为目标。此外,提出了暴雨灾害下配网多孤岛场景的随机模拟生成方法,并基于每个场景的概率和严重程度,提出了基于聚类算法的场景缩减方法,服务于下层优化模型的场景筛选。最后,基于配电网62节点系统进行算例分析,结果表明本文所提方法能够在兼顾投资经济性的同时,有效降低系统在灾中的负荷损失量,提高配电网对重要负荷的保供能力。

本文引用格式

申泽渊, 赵海波, 王超, 李佳, 王尧, 李琦 . 暴雨灾害下考虑多重不确定性的配电系统应急资源韧性规划(网络首发)[J]. 上海交通大学学报, 0 : 0 . DOI: 10.16183/j.cnki.jsjtu.2023.594

Abstract

In recent years, the impact of heavy rain disasters on the reliable power supply of distribution networks has become increasingly prominent, and it is extremely challenging to ensure the supply of important loads in the case of large-scale and multi-point serious faults. Rational deployment of emergency resources can help reduce the loss of important loads in the system, thereby improving the resilience of the distribution system. In this paper, a resilience planning method for emergency resources in the distribution system considering multiple uncertainties under heavy rain disasters is proposed, and a two-tier planning model for the resilience improvement of the distribution system is established considering the emergency power supply and emergency energy storage, with the upper model aiming to minimize the net cost of investment cost and load loss, and the lower model aiming to minimize the comprehensive load loss under multiple island scenarios. In addition, a stochastic simulation generation method for multi-island scenarios in distribution network under heavy rain disasters is proposed, and based on the probability and severity of each scenario, a scene reduction method based on clustering algorithm is proposed to serve the scene screening of the lower-level optimization model. Finally, through the analysis of the actual 62-node system of China's distribution network, it is shown that the method proposed in this paper can effectively improve the supply capacity of the distribution network for important loads while taking into account the economy.
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