引用本文:杨白洁,刘洪,葛少云,李俊锴,张世达.基于分布鲁棒机会约束的高韧性配电网多类型储能配置[J].电力自动化设备,2024,44(7):45-53
YANG Baijie,LIU Hong,GE Shaoyun,LI Junkai,ZHANG Shida.Configuration of multi-type energy storage system in high resilience distribution network based on distributionally robust chance constraints[J].Electric Power Automation Equipment,2024,44(7):45-53
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基于分布鲁棒机会约束的高韧性配电网多类型储能配置
杨白洁, 刘洪, 葛少云, 李俊锴, 张世达
天津大学 智能电网教育部重点实验室,天津 300072
摘要:
针对当前多类型储能系统(ESS)配置尚未充分计及正常工况与极端灾害等多元场景下源、网、荷多重不确定性复杂耦合影响的问题,提出了一种兼顾配电网韧性和经济性的多类型ESS配置方法。提出了面向多元场景差异化需求的多类型ESS优化配置框架,建立了以配电网韧性和经济性最优为目标的配置模型。考虑元件故障、源荷出力等多重不确定性,将原模型构建为两阶段分布鲁棒机会约束模型。提出了基于Big-M和条件风险价值理论的系统化线性方法,基于列和约束生成算法对线性化模型求解。在改进的IEEE 33节点配电网与43节点交通网算例上验证,结果表明,所提方法可显著降低负荷损失及投资,提升配电网韧性和经济性。
关键词:  配电网  韧性  多类型储能系统  条件风险价值  分布鲁棒机会约束
DOI:10.16081/j.epae.202405025
分类号:TM715
基金项目:天津市自然科学基金资助项目(22JCZDJC00820);国家自然科学基金资助项目(72361033)
Configuration of multi-type energy storage system in high resilience distribution network based on distributionally robust chance constraints
YANG Baijie, LIU Hong, GE Shaoyun, LI Junkai, ZHANG Shida
Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
Abstract:
Addressing the complex coupling effects of multi-dimensional uncertainties arising from various scenarios such as normal operating conditions and extreme disasters of source-network-load interactions, a configuration method for multi-type energy storage system(ESS) is proposed, which considers both the resilience and economic efficiency of the distribution network. A multi-type ESS optimization configuration framework tailored to diverse demands across multiple scenarios is introduced, a model is established aiming at optimizing the resilience and economic efficiency of the distribution network. Considering multiple uncertainties such as component failure and source-load output, the original model is constructed as a two-stage distributionally robust chance-constrained model. A systematic linear approach based on Big-M and conditional value-at-risk theory is proposed, and the linearized model is solved using column-and-constraint generation algorithm. The case study of the improved IEEE 33-bus distribution network and 43-node transportation network demonstrates that the proposed method significantly reduces load losses and investment while enhancing the resilience and economy of the distribution network.
Key words:  distribution network  resilience  multi-type energy storage system  conditional value at risk  distributionally robust chance constraints

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