A Data Mining Approach for Real-time Corrective Switching

被引：0

作者：

Shi, Jiaying ^{[1
]}

Oren, Shmuel S. ^{[1
]}

机构：

[1] Univ Calif Berkeley, Dept Ind Engn & Operat Res, Berkeley, CA 94720 USA

来源：

2015 IEEE POWER & ENERGY SOCIETY GENERAL MEETING | 2015年

关键词：

Power system; corrective switching; contingency; corrective control;

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：

Corrective transmission switching can improve the flexibility of power system. To avoid the computational complexity, a data mining approach for real-time corrective switching is proposed in this paper. A factorized expression that measures the approximate switching effects is first derived. The expression can be utilized to generate candidate transmission switching lists. Based on the factorized expression, an algorithm is proposed. The algorithm can be used to generate rank list of candidate switching actions. Since the algorithm bypasses the need to solve complex mixed integer optimization problems, it can provide candidate switching actions for real-time corrective control efficiently. The validity of the presented approach is demonstrated by tests conducted on IEEE RTS96 system.

引用

页数：5

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