DocumentCode :
1777716
Title :
Minimum frequency prediction of power system after disturbance based on the v-support vector regression
Author :
Qibin Bo ; Xiaoru Wang ; Ketian Liu
Author_Institution :
Sch. of Electr. Eng., Southwest Jiaotong Univ., Chengdu, China
fYear :
2014
fDate :
20-22 Oct. 2014
Firstpage :
614
Lastpage :
619
Abstract :
The prediction of power system minimum frequency after disturbance is the main content of power system measures. This paper presents a method based on the v-SVR to predict the minimum frequency and the frequency dynamic rapidly after disturbance. Several conditions which have effects on the power system frequency dynamic, such as the maximum output limit of the generator, spinning reserve levels and its distribution, turbine-governor, load et al. The method presented in this paper is accurate and quick enough to predict the frequency dynamic and its minimum value, and the method is based on support vector regression which is of good generalization ability and extension. Furthermore, the method presented in this paper can be used online for power system frequency stability assessment.
Keywords :
frequency stability; load forecasting; power system stability; regression analysis; support vector machines; frequency prediction; power system frequency stability; power system measures; v-SVR; v-support vector regression; Frequency measurement; Generators; Load modeling; Power system dynamics; Power system stability; Predictive models; Support vector machines; Frequency dynamic; Power system; Support Vector Regression; WAMS;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power System Technology (POWERCON), 2014 International Conference on
Conference_Location :
Chengdu
Type :
conf
DOI :
10.1109/POWERCON.2014.6993789
Filename :
6993789
Link To Document :
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