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上海理工大学机械工程学院,上海市 200093
孙伟卿(1985—),男,博士,副教授,博士生导师,主要研究方向:智能电网、电力系统储能、需求响应。E-mail:sidswq@163.com
刘唯(1997—),男,通信作者,硕士研究生,主要研究方向:移动式储能、需求响应。E-mail:15800987750@163.com
张婕(1997—),女,硕士研究生,主要研究方向:人工智能与大数据在电力系统中的应用、需求响应。E-mail:zhangjieeeze@163.com
收稿日期:2021-01-20,
修回日期:2021-04-19,
网络出版日期:2021-06-28,
纸质出版日期:2021-10-10
移动端阅览
孙伟卿,刘唯,张婕.高比例可再生能源背景下配电网动态重构与移动储能协同优化[J].电力系统自动化,2021,45(19):80-90.
SUN Weiqing,LIU Wei,ZHANG Jie.Collaborative Optimization for Dynamic Reconfiguration of Distribution Network and Mobile Energy Storage in Background of High Proportion of Renewable Energy[J].Automation of Electric Power Systems,2021,45(19):80-90.
孙伟卿,刘唯,张婕.高比例可再生能源背景下配电网动态重构与移动储能协同优化[J].电力系统自动化,2021,45(19):80-90. DOI: 10.7500/AEPS20210120007.
SUN Weiqing,LIU Wei,ZHANG Jie.Collaborative Optimization for Dynamic Reconfiguration of Distribution Network and Mobile Energy Storage in Background of High Proportion of Renewable Energy[J].Automation of Electric Power Systems,2021,45(19):80-90. DOI: 10.7500/AEPS20210120007.
随着可再生能源在配电网中渗透率的不断提升,其出力不确定性导致的弃风、弃光现象日趋严重。针对该问题,在高比例可再生能源背景下提出一种配电网动态重构与移动储能协同优化方法。首先
为缩减问题规模,融合时序负荷先验信息并采用模糊C均值算法划分重构时段,同时避免多余的开关操作。其次,考虑到可再生能源出力的不确定性,构建计及时空相关性且对稀疏离群点具有鲁棒性的不确定集合。然后,建立配电网动态重构策略与移动储能经济调度的两阶段鲁棒协同优化模型,第1阶段选择关键开关与充放电站,第2阶段对重构开关与移动储能进行协同优化以评估第1阶段选择方案的经济性。针对模型多层结构的复杂性,采用嵌套的列约束生成算法进行求解。最后,通过测试系统中的仿真计算,验证所提模型和算法的有效性。
With the increasing penetration of renewable energy in the distribution network
the phenomenon of curtailment caused by its output uncertainty is becoming more and more serious. To solve this problem
a collaborative optimization method for dynamic reconfiguration of the distribution network and mobile energy storage is proposed in the background of high proportion of renewable energy. Firstly
in order to reduce the scale of the problem
the prior information of time series load is fused
and the fuzzy C-means algorithm is used to divide the reconstruction period
while avoiding redundant switching operation. Secondly
considering the uncertainty of renewable energy output
an uncertain set with spatiotemporal correlation and robustness to sparse outliers is constructed. Then
a two-stage robust collaborative optimization model of dynamic reconfiguration strategy and economic dispatch of mobile energy storage is established. In the first stage
the key switch and charging and discharging power stations are selected. In the second stage
the reconfiguration of switches and mobile energy storage are co-optimized to evaluate the economy of the scheme selected in the first stage. Aiming at the complexity of the multi-layer structure of the model
a nested column constraint generation algorithm is used to solve the problem. Finally
the effectiveness of the proposed model and algorithm is verified by simulation in the test system.
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