Available transfer capability based on hybrid continuous ant colony optimization

被引：0
|
作者：
Li, Guo-Qing [1 ]
Lv, Zhi-Yuan [1 ]
Qi, Wei-Fu [2 ]
机构：
[1] Electrical Engineering College, Northeast Dian Li University
[2] Shenyang Power Supply Co. Ltd.
来源：
Zhejiang Daxue Xuebao(Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2009年 / 43卷 / 11期
关键词：
Ant colony optimization; Available transfer capability; Forced searching; Genetic algorithm; Penalty function;
D O I：
10.3785/j.issn.1008-973X.2009.11.024
中图分类号：
学科分类号：
摘要：
A new computation method of available transfer capability (ATC) was presented. This algorithm combines the positive feedback of ant colony optimization (ACO) with the evolutionary strategy of float genetic algorithm (GA), and introduces the pattern search method as eugenic strategy, thus enhances the optimization efficiency, global convergence performance and stability of result. Meanwhile, according to the amount overrunning the limit of inequality constraints during the computing process, this algorithm uses the non-stationary multi-stage assignment penalty function to simplify the inequality constrains, and adopts the forced searching strategy to further increase the convergence speed and improve the global optimization results. Compared with the other algorithms, the verification results by IEEE 30-bus system showed the rationality, availability, and superiority of this algorithm.
引用
收藏
页码：2073 / 2078
页数：5
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