Abstract
Faced with the power system operation data set which has the characteristics of massive amounts of data and multiple numerical types, how to achieve a rapid and accurate network loss evaluation in power system will become an important issue. In accord with the data mining and typical scenario simulation method, a novel network loss evaluation method based on hybrid clustering analysis is proposed. The clustering attributes associated with network loss are determined from the power system operation data set first. Based on the division of different numerical types of clustering attributes, the original clustering problem is divided into two clustering sub-problems. In consideration of the characteristic of power data, the partitioning clustering method and hierarchical clustering method are adopted respectively to deal with the two clustering sub-problems. The clustering ensemble technique is further employed to achieve a mixed clustering result, which is finally utilized to generate a typical power system operation data set for the evaluation of network loss. The numerical result shows the proposed network loss evaluation method has good evaluation precision and computational efficiency, which can be effectively applied to engineering practice.
| Original language | English |
|---|---|
| Pages (from-to) | 60-65 |
| Number of pages | 6 |
| Journal | Dianli Xitong Zidonghua/Automation of Electric Power Systems |
| Volume | 40 |
| Issue number | 1 |
| DOIs | |
| State | Published - 10 Jan 2016 |
Keywords
- Clustering analysis
- Data mining
- Network loss evaluation
- Typical scenario
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