Application of self-organizing maps for classification and filtering of electrical customer load patterns
- Valero, S. 4
- Ortiz, M. 4
- Senabre, C. 4
- Álvarez, C. 3
- García Franco, F.J. 3
- Encinas, N. 3
- Gabaldón, A. 1
- Fuentes, J.A. 1
- Ramírez-Rosado, I.J. 2
- Fernández-Jiménez, L.A. 2
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1
Universidad Politécnica de Cartagena
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2
Universidad de La Rioja
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3
Universidad Politécnica de Valencia
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4
Universidad Miguel Hernández de Elche
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Publisher: 92
ISBN: 0-88986-326-1
Year of publication: 2004
Pages: 87-92
Type: Book chapter
Abstract
The objective of this paper is to show the capability of the Self-Organizing Maps (SOMs) to organize, to filter, to classify and to extract patterns from distributor, commercializer, aggregator or customer electrical demand databases -objective known as data mining-. This approach basically uses -to reach the above mentioned objectives- the historic load demand curves of each user. In our case, and for simplicity, we will study two typical medium users: an industry and a university located both in Spain. The results clearly show the suitability of SOM approach to improve data management and to find easily coherent clusters between electrical users.