NDLI: A reliability forecasting method for distribution systems based on support vector machine with chaotic particle swarm optimization algorithm

Content Provider	IEEE Xplore Digital Library
Author	Li, Z.Y. Xu, Z.Y. Ye, H.C. Wang, Z.Q.
Copyright Year	2013
Description	Author affiliation: Guizhou Power Grid Corp., China (Ye, H.C.) \|\| Zhejiang Univ., Hangzhou, China (Li, Z.Y.; Xu, Z.Y.; Wang, Z.Q.)
Abstract	In this paper, support vector machine (SVM) technique is applied to predict the reliability of power distribution system. To determine the SVM models' optimal parameters for regression, particle swarm optimization algorithm is improved by combination with chaotic searching method (CPSO). The implementation approach of SVM for regression with CPSO (CPSO-SVR) is detailedly given. The CPSO-SVR models are first trained to learn the relationship between the influential factors of historical reliability and the corresponding reliability targets, and then future reliability can be predicted. In addition, a single but comprehensive index for distribution reliability is defined as IPSR. To examine the effectiveness of the proposed method, numerical experiments for the reliability forecasting of a city's power distribution system in Southern China are conducted. The results reveal that CPSO-SVR outperforms the existing with higher forecasting accuracy and more robust performance. Hence, the proposed CPSO-SVR method is a proper alternative for forecasting power distribution system reliability. Furthermore, sensitivity analyses of input influential factors are demonstrated.
Sponsorship	EPRC
Starting Page	1
Ending Page	5
File Size	360809
Page Count	5
File Format	PDF
ISBN	9781479932542
DOI	10.1109/UPEC.2013.6714983
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-09-02
Publisher Place	Ireland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines support vector machine Interrupters forecasting performance sensitivity analysis Predictive models particle swarm optimization Reliability Indexes distribution system reliability Forecasting Particle swarm optimization
Content Type	Text
Resource Type	Article

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