.png){kind=icon}
返回
Transmission Constraint Filtering in Large-Scale Security-Constrained Unit Commitment
.png){kind=icon}
OA
AI
DOI：10.1109/TPWRS.2019.2892620.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
When solving the security-constrained unit commitment problem, one of the most complicating factors is handling the large number of transmission constraints, corresponding to both base case and N - 1 line contingency scenarios. Although it is well known that only a few of these constraints need to be enforced, identifying this critical subset of constraints efficiently remains a challenge. In this letter, we propose a novel and simple iterative contingency-screening procedure that is able to eliminate 99.4% of the constraints selected by existing iterative methods, allowing for the solution of much larger-scale problems. We report computational results in realistic instances with up to 6468 buses and 9000 transmission lines. The method was also independently implemented and evaluated at MISO, where it performed faster than alternative methods.
Keyword:
Mixed-integer linear programming (MIP)
security constrained unit commitment (SCUC)
contingency screening
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.2
论文数:
1.1W
被引数:
5.0W
机构
引用论文
.png){kind=icon}
Tight and Compact MILP Formulation for the Thermal Unit Commitment Problem用于热单元承诺问题的紧密而紧凑的MILP公式
PREAI
分享收藏MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and EducationMATPOWER: 用于电力系统研究和教育的稳态操作，规划和分析工具
OAAI
OAAI分享收藏 没有更多内容
没有更多内容