DocumentCode
3474638
Title
Application of integrated weight method and support vector machine in the comprehensive evaluation of power quality
Author
Zhang, Xiaohua ; Chen, Xingying ; Liu, Haoming ; Zhao, Bo
Author_Institution
Coll. of Electr. Eng., Hohai Univ., Nanjing
fYear
2008
fDate
6-9 April 2008
Firstpage
2181
Lastpage
2186
Abstract
In this paper, a novel comprehensive strategy, consisting of an integrated weight method and support vector machine (SVM) method, is proposed to evaluate power quality. In integrated weight method, analysis hierarchy process (AHP) is employed to determine the subjective weights, and improved scatter degree (ISD) is employed to determine the objective weights, then the comprehensive weights could be fixed based on addition principle. Since SVM could deal with small samples and nonlinear problems effectively, it is introduced into the comprehensive evaluation of power quality. Test results show that the proposed strategy is feasible to PQ evaluation problems. At the same time it can obtain reasonable evaluation results quickly. The obtained model has so good generalization performance that it is fit for large practical samples.
Keywords
power engineering computing; power supply quality; support vector machines; PQ evaluation problems; SVM; analysis hierarchy process; improved scatter degree; integrated weight method; power quality; support vector machine; Analytical models; Artificial neural networks; Electricity supply industry; Mathematics; Power quality; Radial basis function networks; Scattering; Support vector machine classification; Support vector machines; Testing; analysis hierarchy process; comprehensive evaluation; improved scatter degree; integrated weight method; power quality; support vector machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Electric Utility Deregulation and Restructuring and Power Technologies, 2008. DRPT 2008. Third International Conference on
Conference_Location
Nanjuing
Print_ISBN
978-7-900714-13-8
Electronic_ISBN
978-7-900714-13-8
Type
conf
DOI
10.1109/DRPT.2008.4523772
Filename
4523772
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