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考虑电力-信息-交通网络耦合的配电网韧性提升策略分析

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韧性是评估系统在极端灾害下吸收抵御扰动并恢复至正常状态的能力指标.基于电力-信息-交通网络之间紧密耦合的特性,提出考虑多网络耦合特性的多阶段配电网韧性提升策略.首先,在灾前预防阶段提出考虑网络抗毁性与电力信息风险价值的最优线路加固策略,并对应急中心进行优化布点.其次,基于网络损毁导致的拓扑变化对分布式电源与联络开关进行动态联合调控,最小化灾害抵御阶段的负荷损失价值.然后,结合耦合网络间的关联制约属性,提出灾后阶段多网协同恢复策略.最后,建立组合式评估框架对系统韧性进行多时段精细化分析.基于IEEE33节点系统搭建三网耦合系统算例进行仿真,所得结果表明所提策略可有效提高灾害下系统的抵御力并提升恢复效率.
Analysis of Distribution Network Resilience Improvement Strategy Considering Power-information-transportation Network Coupling
Resilience is an ability index of a system to absorb and withstand disturbances until returning to a normal state under extreme disasters.Based on the characteristics of the tight coupling between the Power-Information-Transportation Networks,the strategy for a multi-stage distribution network to improve its resilience considering the coupling characteristics of multiple networks is proposed.First of all,in the prevention stage before a disarster,the optimal line reinforcement strategy considering the network survivability and the risk value of the power information is proposed,and the emergency centers are set optimally.Secondly,based on the topology changes caused by the network damages,the distributed power generation and the tie switch are dynamically and jointly scheduled to minimize the load loss value in the disaster resistance stage.Then,combined with the associated constraints between the coupled networks,a multi-network collaborative recovery strategy is proposed in the post-disaster phase.Finally,a combined evaluation framework is established to conduct a multi-period refined analysis of the system resilience.Based on the IEEE33 node system to build a three-network coupling system example,the results show that the proposed strategy is able to effectively improve the resilience of the system under disasters and improve the recovery efficiency.

resiliencemultiple network couplingline reinforcejoint schedulecollaborative recoverycombined evaluation

张巍、罗浩

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上海理工大学机械工程学院,上海市 杨浦区 200093

韧性 多网络耦合 线路加固 联合调控 协同恢复 组合式评估

2024

电网技术
国家电网公司

电网技术

CSTPCD北大核心
影响因子:2.821
ISSN:1000-3673
年,卷(期):2024.48(1)
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