| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 689.33 KB | Adobe PDF |
Advisor(s)
Abstract(s)
This paper consists in the characterization of medium voltage (MV) electric power consumers based on a data clustering approach. It is intended to identify typical load profiles by selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The best partition is selected using several cluster validity indices. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers’ behavior. The data-mining-based methodology presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partitions. To validate our approach, a case study with a real database of 1.022 MV consumers was used.
Description
Keywords
Data mining Clustering Smart Grid Typical load profiles
Citation
Publisher
IEEE