A Novel Power System Reliability Predicting Model Based on PCA and RVM
Joint Authors
Zheng, Yuping
Zhao, Feifei
Wei, Zhinong
Sun, Yonghui
Sun, Guoqiang
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-03-19
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
The power system reliability is an important index to evaluate the ability of power supply.
According to thecharacteristics of the practical grid operation, this paper trains and sets up power grid reliability predicting model,based on relevance vector machine, taking the load supplying capacity of power grid and natural calamities asinput variables, and the outage time of power grid failure affecting the reliability of the power supply as outputvariables.
In the modeling process, through principal component analysis of the training sample set of relevancevector machine, the input factor number of sample is improved, the input number of network is reduced, thenetwork structure is simplified, and the predicting accuracy is increased.
Simulation results are provided to verifythe effectiveness of the proposed algorithm, which show that it provides a new way for power system reliabilitypredicting.
American Psychological Association (APA)
Zheng, Yuping& Sun, Guoqiang& Wei, Zhinong& Zhao, Feifei& Sun, Yonghui. 2013. A Novel Power System Reliability Predicting Model Based on PCA and RVM. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1032054
Modern Language Association (MLA)
Zheng, Yuping…[et al.]. A Novel Power System Reliability Predicting Model Based on PCA and RVM. Mathematical Problems in Engineering No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-1032054
American Medical Association (AMA)
Zheng, Yuping& Sun, Guoqiang& Wei, Zhinong& Zhao, Feifei& Sun, Yonghui. A Novel Power System Reliability Predicting Model Based on PCA and RVM. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1032054
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1032054