Active and Reactive Power Coordinated Two-Stage MG Scheduling for Resilient Distribution Systems Under Uncertainties

被引:30
|
作者
Cai, Sheng [1 ]
Xie, Yunyun [1 ]
Wu, Qiuwei [2 ]
Zhang, Menglin [3 ]
Jin, Xiaolong [4 ]
Xiang, Zhengrong [1 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Peoples R China
[2] Tsinghua Univ, Tsinghua Shenzhen Int Grad Sch, Tsinghua Berkeley Shenzhen Inst, Shenzhen 518055, Peoples R China
[3] China Univ Geosci, Sch Automat, Wuhan 430074, Peoples R China
[4] Tianjin Univ, Key Lab Smart Grid, Minist Educ, Tianjin 30072, Peoples R China
关键词
Uncertainty; Reactive power; Renewable energy sources; Load modeling; Resilience; Computational modeling; Static VAr compensators; Microgrid scheduling; resilience enhancement; two-stage optimization; uncertainties; disjunctive programming; SERVICE RESTORATION; ROBUST OPTIMIZATION; WIND; MICROGRIDS; RESOURCES; FLOW;
D O I
10.1109/TSG.2022.3149816
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper proposes a two-stage microgrid (MG) scheduling approach that considers the dynamic MG formation and the coordinated optimization of active and reactive powers to enhance the distribution system resilience after blackouts. It aims to dispatch multiple devices operating in different timescales to sectionalize the distribution system into self-supplied MGs and supply the critical loads continuously with reliable power. In the hour-ahead operation stage, switches, capacitor banks and energy storage charging/discharging decisions are optimized based on hour-ahead interval predictions of renewable energy generations and load demands. In the intra-hour operation stage, the output of distributed energy resources and static Var compensators are redispatched to compensate the hour-ahead operation decisions after the uncertainty realization. Compared with the existing methods, the proposed MG scheduling method can restore more critical loads and sustain secure operation under random renewable energy generation and load demand. In addition, to address uncertainties, the MG scheduling problem is modeled as a robust optimization model, which is decomposed into a master problem and a subproblem by adopting the column-and-constraint generation algorithm. Furthermore, the subproblem is reformulated via the disjunctive programming method to reduce the computational complexity. The effectiveness of the proposed method is verified on the modified IEEE test systems.
引用
收藏
页码:2986 / 2998
页数:13
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