Study on Aggregation of Inductive Motor Loads Based on Differential Evolution Algorithm

被引:0
|
作者
Zhang, Baozhen [1 ]
Fan, Chenxi [2 ]
机构
[1] Hainan Univ, Sch Mech & Elect Engn, Haikou, Hainan, Peoples R China
[2] South China Univ Technol, ySch Elect Power, Guangzhou, Guangdong, Peoples R China
来源
PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON APPLIED MATHEMATICS, MODELLING AND STATISTICS APPLICATION (AMMSA 2017) | 2017年 / 141卷
关键词
power system; estimation dynamic equivalence; inductive-motor load; differential evolution; parameter identification;
D O I
暂无
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In order to simplify enormous inductive-motor loads in online estimation dynamic equivalence for large-scale power systems, it is presented identification strategy based on the algorithm of differential evolution algorithm (DE) to acquired the parameter of equivalent motor loads. It presented to dynamic aggregate motors into an equivalent motor based on same or similar dynamic characteristic, the parameter of equivalent motor is identified to use modified Differential Evolution algorithm (DE) which has unique advantage in nonlinear parameter optimization, in order to solve premature convergence problem of DE, double evolution swarm which adopt different variation are formed. Simulated results indicate that it is high accuracy for identified the parameter of equivalent motors, equivalent system can preserve dynamic characteristics of original system well. The method can be used to simplify mass inductive motor loads in online estimation dynamic equivalence for large-scale power systems.
引用
收藏
页码:365 / 368
页数:4
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