Electricity clustering framework for automatic classification of customer loads

•An automatic clustering of electricity customers’ loads is proposed.•A new set of clustering features satisfies company electricity experts.•The importance of the clustering algorithm selection is highlighted.•The final solution is discussed with domain experts. Clustering in energy markets is a to...

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Veröffentlicht in:Expert systems with applications 2017-11, Vol.86, p.54-63
Hauptverfasser: Biscarri, Félix, Monedero, Iñigo, García, Antonio, Guerrero, Juan Ignacio, León, Carlos
Format: Artikel
Sprache:eng
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Zusammenfassung:•An automatic clustering of electricity customers’ loads is proposed.•A new set of clustering features satisfies company electricity experts.•The importance of the clustering algorithm selection is highlighted.•The final solution is discussed with domain experts. 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.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2017.05.049