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计及灵活性资源的交直流混合配电网双层优化 被引量:15

Bi-level Optimization of AC/DC Hybrid Distribution Network Considering Flexible Resources
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摘要 如何引导灵活性资源参与电网优化运行是智能电网面临的重要问题,而交直流混合配电网的分区化和多元化也给优化运行带来新的挑战。提出了一种考虑灵活性资源参与的交直流混合配电网双层优化方法。首先,分析了供需两侧灵活性资源模型,通过对负荷聚类划分峰谷时段并制定合理分时电价,并从供需平衡的角度定义运行灵活性评价指标;其次,综合考虑需求响应、风光不确定性等因素,建立兼顾灵活性和经济性的交直流混合配电网双层优化模型,其中,上层模型以柔性负荷调度策略为决策主体,下层模型侧重于灵活性供给资源的运行策略,并利用分布鲁棒优化方法进行求解。最后,算例仿真结果验证了本文所提优化方法的合理性和有效性。 It is an important problem for smart grid to guide flexible resources participating in the optimal operation of the power grid,and the zoning and diversifying of the AC/DC hybrid distribution network also bring about new challenges.A two-level optimization for the AC/DC hybrid distribution network considering the participation of flexible resources is proposed.Firstly,the flexible resources model on both the supply and demand sides is analysed.The peak and valley periods are divided and a reasonable TOU price is formulated by clustering the loads.The operation flexibility evaluation index is defined from the perspective of supply and demand balance.Secondly,considering the demand response,wind &solar uncertainty and other factors,a two-level optimization model of the AC/DC hybrid distribution network considering flexibility and economy is established.In this model,the upper level takes the flexible load scheduling strategy as the decision-making unit,and the lower focuses on the operation strategy of flexible supply resources and solves it by using the distributed robust optimization.Finally,the simulation results of an example verify the rationality and effectiveness of the proposed optimization.
作者 胡戎 邱晓燕 张志荣 HU Rong;QIU Xiaoyan;ZHANG Zhirong(Key Laboratory of Intelligent Electric Power Grid in Sichuan Province(Sichuan University),Chengdu 610065,Sichuan Province,China)
出处 《电网技术》 EI CSCD 北大核心 2022年第6期2259-2267,共9页 Power System Technology
基金 四川省成都市重点研发项目(2019-YF05-02107-SN)。
关键词 交直流混合配电网 灵活性资源 分时电价 双层优化 分布鲁棒 AC/DC hybrid distribution network flexible resources time-of-use price bi-level optimization distributed robustness
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