1.三峡大学电气与新能源学院,湖北省宜昌市 443002
2.清华大学电机工程与应用电子技术系,北京市 100084
3.清华四川能源互联网研究院,四川省成都市 610213
王长明(2001—),男,硕士研究生,主要研究方向:主动配电网优化运行。E-mail:1504329751@qq.com
蔺晨晖(1995—),男,通信作者,助理研究员,主要研究方向:电力系统调控、主动配电网。E-mail:linchenhui@tsinghua.edu.cn
刘道兵(1974—),男,副教授,高级工程师,主要研究方向:电力系统安全性与稳定性。E-mail:liudb@ctgu.edu.cn
收稿:2025-05-15,
修回:2025-08-03,
网络首发:2025-09-25,
纸质出版:2026-02-10
移动端阅览
王长明,蔺晨晖,刘道兵等.面向并网灵活性提升的微电网网络重构方法[J].电力系统自动化,2026,50(3):57-66.
WANG Changming,LIN Chenhui,LIU Daobing,et al.Microgrid Network Reconfiguration Method for Grid-connected Flexibility Enhancement[J].Automation of Electric Power Systems,2026,50(3):57-66.
王长明,蔺晨晖,刘道兵等.面向并网灵活性提升的微电网网络重构方法[J].电力系统自动化,2026,50(3):57-66. DOI: 10.7500/AEPS20250515001.
WANG Changming,LIN Chenhui,LIU Daobing,et al.Microgrid Network Reconfiguration Method for Grid-connected Flexibility Enhancement[J].Automation of Electric Power Systems,2026,50(3):57-66. DOI: 10.7500/AEPS20250515001.
随着分布式能源海量接入,微电网已成为支撑源-网-荷-储协同运行的重要载体。微电网通过公共耦合点(PCC)提供的调节灵活性,是电力系统中一项重要的调节资源。然而,受内部电压安全、支路容量等约束,分布式能源的灵活性无法在PCC得到充分体现,且不同网络重构策略下所能提供的灵活性也差异显著。为此,文中提出一种基于网络重构的并网灵活性提升方法。首先,建立了基于微电网聚合的并网灵活性表征模型,进而构建了两阶段鲁棒优化框架:第1阶段通过拓扑优化聚合微电网PCC的最大灵活性,第2阶段验证解聚合的可行性。然后,采用强对偶理论和列与约束生成算法进行高效求解。最后,算例分析表明,所提方法能够通过网络重构实现对分布式能源灵活性的充分挖掘,显著提升微电网并网灵活性。
With the massive integration of distributed energy resources
microgrids have become a critical platform for supporting the coordinated operation of source-grid-load-storage systems. The regulation flexibility provided by microgrids at the point of common coupling (PCC) serves as an important adjustable resource for power systems. However
due to constraints such as internal voltage stability and branch capacity limitations
the flexibility of distributed resources cannot be fully manifested at the PCC
and the available flexibility varies significantly under various network reconfiguration strategies. To address this challenge
this paper proposes a network reconfiguration based method for grid-connected flexibility enhancement. First
a characterization model for grid-connection flexibility based on microgrid aggregation is established
and a two-stage robust optimization framework is developed
in which the first stage maximizes the aggregated flexibility at the PCC through topology optimization
while the second stage verifies the feasibility of disaggregation. The strong duality theory and the column and constraint generation algorithm are employed to efficiently solve the model. Case studies demonstrate that the proposed method can fully tap into the flexibility of distributed energy resources through network reconfiguration
significantly improving the grid-connected flexibility of microgrids.
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