A Decomposition and Coordination Approach for Large-Scale Security Constrained Unit Commitment Problems with Combined Cycle Units

被引:0
作者
Sun, Xiaorong [1 ]
Luh, Peter B. [1 ]
Bragin, Mikhail A. [1 ]
Chen, Yonghong [2 ]
Wang, Fengyu [2 ]
Wan, Jie [3 ]
机构
[1] Univ Connecticut, Elect & Comp Engn, Storrs, CT 06269 USA
[2] MISO, Market Serv, Carmel, IN 46032 USA
[3] GE Energy Solut, Market Applicat, Redmond, WA 98052 USA
来源
2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING | 2017年
基金
美国国家科学基金会;
关键词
Branch-and-cut; large-scale mixed integer programming; security constrained unit commitment; surrogate augmented Lagrangian Relaxation;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
MISO faces one of the most challenging Day-ahead Security Constrained Unit Commitment (SCUC) problems in view of its large number of units (including many virtual transactions) and complicated transmission capacity constraints. When combined cycle units with complicated state transitions are present, branch-and-cut shows poor performance in terms of solution quality and solving times. In this paper, a synergistic combination of Surrogate Augmented Lagrangian Relaxation and branch-and-cut is presented. With system coupling constraints relaxed and quadratic penalties on constraint violations added, the augmented Lagrangian is innovatively linearized and decomposed into subproblems to be solved by branch-and-cut. Subproblem solutions are then effectively coordinated based on Surrogate subgradients with much reduced computation requirements and multiplier zigzagging, and accelerated reduction of constraint violations. Numerical testing of a complicated MISO SCUC case demonstrates that our method generates near-optimal solutions in short solving times and significantly outperforms branch-and-cut.
引用
收藏
页数:5
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