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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Mahmoudi-Kohan, N. Moghaddam, M.P. Bidaki, S.M. |
| Copyright Year | 2009 |
| Description | Author affiliation: Department of Computer Engineering, Shiraz University, Iran (Bidaki, S.M.) || Department of Electrical Engineering, Tarbiat Modares University (TMU), Tehran, Iran (Mahmoudi-Kohan, N.; Moghaddam, M.P.) |
| Abstract | Clustering is a process that partitions a set of feature vectors into clusters. There are different applications of load curves clustering in regulated and deregulated environment such as system analysis, load and price forecasting, distributed resource selection, better tariff design, etc. In this paper we evaluate performances of two clustering methods (WFA (Weighted Fuzzy Average) K-means and Modified Follow the Leader) for load curves classification. For evaluation and comparison we use two adequacy measures (Mean Index Adequacy and Clustering Dispersion Indicator) that show distinction and compactness of clusters, respectively. A novel feature of this paper is that we evaluate performances of clustering algorithms on the basis of different applications on power system. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 1508618 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424438105 |
| DOI | 10.1109/PSCE.2009.4840115 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-03-15 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Performance evaluation Energy consumption Clustering methods Modified Follow the Leader Cleaning Pattern recognition Load forecasting Mean Index Adequacy Clustering Dispersion Indicator Clustering algorithms Power system analysis computing Voltage Electricity supply industry Load Curve Clustering Electricity Market WFA K-means |
| Content Type | Text |
| Resource Type | Article |
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