Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/1505
Título: Data mining contributions to characterize MV consumers and to improve the suppliers-consumers settlements
Autor: Ramos, Sérgio
Vale, Zita
Santana, João
Duarte, Jorge
Palavras-chave: Classification
Clustering
Data mining
Electricity markets
Load management
New tariff structures
Data: 2007
Editora: IEEE
Resumo: This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.
URI: http://hdl.handle.net/10400.22/1505
ISBN: 1-4244-1296-X
1-4244-1298-6
ISSN: 1932-5517
Versão do Editor: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4275762
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

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