A Fast Clustering Algorithm for Power Data
Shuqin Zeng, Haizhou Du, Tingting Dou · International Journal of Power Engineering and Engineering Thermophysics · 2017
Energy conservation is an urgent issue to solve on a global scale. A more and more widely used method for energy saving and emission reduction is the applications of data mining technology including data clustering in power system. However, power data has characteristics of large volume, high dimensions, discrete and complex datasets which lead to poor clustering results when we choose common classic clustering algorithm. In our paper, we proposed D-CFSFDP algorithm which is suitable for power data clustering. We do experiments compared with DBSCAN algorithm and K-means algorithm. We demonstrate the power of the algorithm on the power data from Shanghai Energy Conservation Supervision Center.