Large-scale power system planning using enhanced Benders decomposition

被引:0
|
作者
Skar, Christian [1 ]
Doorman, Gerard [1 ]
Tomasgard, Asgeir [2 ]
机构
[1] Norwegian Univ Sci & Technol, Dept Elect Power Engn, Trondheim, Norway
[2] Norwegian Univ Sci & Technol, Dept Ind Econ & Technol Management, Trondheim, Norway
来源
2014 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC) | 2014年
关键词
Benders decomposition; investments under uncertainty; large-scale power system planning; LINEAR-PROGRAMS;
D O I
暂无
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
An enhanced Benders decomposition algorithm for two-stage stochastic LPs is presented and applied to a large-scale dynamic generation and transmission expansion planning model for the European power system. The improved algorithm is a variation of the traditional multi-cut Benders decomposition algorithm where the scenario aggregation used for the optimality cuts is reduced at a given error threshold. Experimental results show that this technique improves convergence and reduces computation time. An analysis using the planning model to compute an optimal development of the European power sector under a global climate policy is also discussed.
引用
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页数:7
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