Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4943311 | Expert Systems with Applications | 2017 | 10 Pages |
Abstract
Clustering in energy markets is a top topic with high significance on expert and intelligent systems. The main impact of is paper is the proposal of a new clustering framework for the automatic classification of electricity customers' loads. An automatic selection of the clustering classification algorithm is also highlighted. Finally, new customers can be assigned to a predefined set of clusters in the classification phase. The computation time of the proposed framework is less than that of previous classification techniques, which enables the processing of a complete electric company sample in a matter of minutes on a personal computer. The high accuracy of the predicted classification results verifies the performance of the clustering technique. This classification phase is of significant assistance in interpreting the results, and the simplicity of the clustering phase is sufficient to demonstrate the quality of the complete mining framework.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Félix Biscarri, Iñigo Monedero, Antonio GarcÃa, Juan Ignacio Guerrero, Carlos León,