Recovery strategy of distribution network based on dynamic island rescue under extreme weather

IF 1.6 Q4 ENERGY & FUELS IET Energy Systems Integration Pub Date : 2024-03-02 DOI:10.1049/esi2.12140
Xinrui Liu, Qingkun Meng, Rui Wang, Chaoyu Dong, Qiuye Sun
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Abstract

The frequent occurrence of various extreme weather has a great influence on the normal and stable operation of the distribution network. In order to minimise the large‐scale power loss of the distribution network caused by extreme weather, considering that most of the practical disasters are concurrent with various weather types, and each disaster is independent of each other. A unified failure rate calculation model is proposed, which includes line break, short circuit, tower fall, insulator flashover etc., to realise disaster scenario prediction. Secondly, a resilience evaluation index of island rescue based on mobile energy storage system (IR‐MESS) is proposed. Thirdly, considering the flexibility of MESS, the pre‐disaster scheduling of MESS is carried out according to the predicted disaster scenario. After the disaster occurs, a spatio‐temporal optimisation scheduling model based on the rescue state and charge state of MESS is proposed, and a dynamic IR‐MESS is formed to provide power supply for important loads in out‐of‐load areas of the distribution network. Finally, taking the actual ice disaster in northeast China as an example, the results show that the rescue strategy based on IR‐MESS proposed in this paper can effectively elevate the resilience of the distribution network.
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极端天气下基于动态孤岛救援的配电网恢复策略
各种极端天气的频繁出现,对配电网的正常稳定运行影响极大。考虑到实际灾害大多与各种天气类型同时发生,且各灾害之间相互独立,为了最大限度地降低极端天气对配电网造成的大面积电能损失。提出了统一的故障率计算模型,包括断线、短路、倒塔、绝缘子闪络等,实现灾害场景预测。其次,提出了基于移动储能系统(IR-MESS)的孤岛救援恢复力评价指标。第三,考虑到 MESS 的灵活性,根据预测的灾害场景对 MESS 进行灾前调度。灾害发生后,提出基于 MESS 救援状态和充电状态的时空优化调度模型,形成动态 IR-MESS,为配电网失载区域的重要负荷提供电力供应。最后,以中国东北地区的实际冰灾为例,结果表明本文提出的基于 IR-MESS 的救援策略能够有效提升配电网的抗灾能力。
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来源期刊
IET Energy Systems Integration
IET Energy Systems Integration Engineering-Engineering (miscellaneous)
CiteScore
5.90
自引率
8.30%
发文量
29
审稿时长
11 weeks
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