Coordinated Planning With Predetermined Renewable Energy Generation Targets Using Extended Two-Stage Robust Optimization

被引:20
|
作者
Tian, Kunpeng [1 ]
Sun, Weiqing [2 ]
Han, Dong [2 ]
Yang, Ce [1 ]
机构
[1] Univ Shanghai Sci & Technol, Dept Control Sci & Engn, Shanghai 200093, Peoples R China
[2] Univ Shanghai Sci & Technol, Dept Elect Engn, Shanghai 200093, Peoples R China
来源
IEEE ACCESS | 2020年 / 8卷
基金
中国国家自然科学基金;
关键词
Coordinated planning; renewable target; two-stage robust optimization; multiple uncertain sets; data-driven; column-and-constraint generation algorithm; POWER-SYSTEMS; WIND FARM; EXPANSION; TRANSMISSION; STORAGE; FLEXIBILITY; PENETRATION; INTEGRATION; CAPACITY;
D O I
10.1109/ACCESS.2019.2962841
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Coordinated planning is an effective method to balance investment costs and benefits in achieving high renewable target under the renewable-driven power system expansion wave. This paper proposes a coordinated planning model to support the efficient achievement of renewable target considering economy of the system by accounting for the interaction among source, grid, and energy storage system. An adaptive two-stage min-max-min robust optimization model is formulated to take into account renewable target as well as the uncertainty associated with renewable production and load demand. To reduce the conservatism of robust optimization, uncertain budget, multiple uncertain sets, and data-driven method are used to design uncertain sets. The resulting model is transformed into a tractable bi-level programming through strong duality theory and big-M method. A customized column-and-constraint generation algorithm is used to solve the bi-level programming. Simulation results presented for the modified IEEE 30-bus test system corroborates the effectiveness of the methodology, which finds siting and sizing of renewable energy sources and energy storage systems as well as transmission expansion schemes. It is capable to provide a fiexible planning tool driven by renewable target under a reasonable computational burden.
引用
收藏
页码:2395 / 2407
页数:13
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