Paper Info
Title
Hierarchical Evaluation and Fault Diagnose Strategy for the Active Distribution Network Using the Incomplete Monitoring Information
Abstract
The cost of monitoring facilities for the whole active distribution network challenges the electric power companies. This paper proposes a hierarchical evaluation and fault diagnose strategy using the incomplete monitoring information to decrease the cost of the monitoring facilities. The proposed strategy consists of three levels: the primary level, the middle level and the output level. The K-means clustering algorithm is employed at the primary level. Considering the local incomplete history information and the history fault record information, the K-means clustering algorithm assesses the failure probability of the target area in each cluster. A regional composite failure probability calculation algorithm is proposed at the middle level. Considering the distance from the monitoring area real-time sampling data matrix to each cluster, the proposed algorithm calculates the probability of the real-time monitoring data belonging to each cluster. Combining the cluster belonging probability and the failure probability of each cluster, the proposed algorithm calculate the composite failure probability of the each target area in the active distribution network. An evaluation algorithm based on the maximum composite probability is proposed at the output level. The maximum composite failure probability of each region is used as the overall operation state evaluation coefficient to evaluate the operation status level of the active distribution network. The proposed strategy is tested by the Matlab/Simulink model of a distribution network in Nanjing. Test results show that the proposed strategy can effectively detect the weak areas of the active distribution network. The real-time operating state of the active distribution network is evaluated scientifically.
Year
DOI
Venue
2018
10.1109/ICCAIS.2018.8570325
2018 International Conference on Control, Automation and Information Sciences (ICCAIS)
Keywords
Field
DocType
Active distribution network,hierarchical evaluation,fault diagnose,incomplete information,K-means clustering algorithm
Electric power,Data mining,k-means clustering,MATLAB,Control theory,Distribution networks,Sampling (statistics),Engineering,Cluster analysis,Complete information
Conference
ISSN
ISBN
Citations 
2475-790X
978-1-5386-6021-8
0
PageRank 
References 
Authors
0.34
1
6
Name
Order
Citations
PageRank
Feilong Fan100.34
Nengling Tai223.71
Jiayun Ni300.34
Qiu Sun400.34
Zhoujun Ma500.34
Pei-yu Chen61138.79