DocumentCode :
2938696
Title :
Load Identification Modeling with Improved Model
Author :
Liu Shujun ; Li Xianshan
Author_Institution :
Electr. Eng. & Renewable Energy Sch., Three Gorges Univ., Yichang, China
fYear :
2011
fDate :
25-28 March 2011
Firstpage :
1
Lastpage :
4
Abstract :
The running state of different induction motor in the load group will be moved toward two directions when it was occurred the large disturbance in the power system, one is to keep on the rotor speed running, another is to decelerate to zero, that is stall state. If the quantity or proportion of stall induction motor in the group is a large number, the dynamic of stall motor has great impacts on the results of power system analysis. So it is necessary to adopt the detailed load model to simulate the complicated dynamic characteristic of the load group. An improved synthesis load model which combines two kinds of induction motor is proposed in this paper, and the improved genetic algorithm is used to solve the optimization problem. The case is studied to illustrate the efficiency and comprehensive capability of proposed identification model.
Keywords :
genetic algorithms; induction motors; power systems; genetic algorithm; induction motor; load identification modeling; optimization problem; power system analysis; stall motor; Data models; Induction motors; Load modeling; Mathematical model; Power system dynamics; Rotors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2011 Asia-Pacific
Conference_Location :
Wuhan
ISSN :
2157-4839
Print_ISBN :
978-1-4244-6253-7
Type :
conf
DOI :
10.1109/APPEEC.2011.5748978
Filename :
5748978
Link To Document :
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