TY - JOUR A1 - Valero Verdú, Sergio AU - Ortiz García, Mario AU - Senabre Blanes, Carolina AU - Gabaldón Marín, Antonio AU - García Franco, Francisco J. T1 - Classification, filtering, and identification of electrical customer load patterns through the use of self-organizing maps Y1 - 2006 SN - 0885-8950 UR - http://hdl.handle.net/10317/7212 AB - Different methodologies are available for clustering purposes. The objective of this paper is to review the capacity of some of them and specifically to test the ability of self-organizing maps (SOMs) to filter, classify, and extract patterns from distributor, commercializer, or customer electrical demand databases. These market participants can achieve an interesting benefit through the knowledge of these patterns, for example, to evaluate the potential for distributed generation, energy efficiency, and demand-side response policies (market analysis). For simplicity, customer classification techniques usually used the historic load curves of each user. The first step in the methodology presented in this paper is anomalous data filtering: holidays, maintenance, and wrong measurements must be removed from the database. Subsequently, two different treatments (frequency and time domain) of demand data were tested to feed SOM maps and evaluate the advantages of each approach. Finally, the ability of SOM to classify new customers in different clusters is also examined. Both steps have been performed through a well-known technique: SOM maps. The results clearly show the suitability of this approach to improve data management and to easily find coherent clusters between electrical users, accounting for relevant information about weekend demand patterns. KW - Ingeniería e Infraestructura del Transporte KW - Ingeniería e Infraestructura del Transporte KW - Gestión de la demanda KW - Extracciónde datos KW - Segmentación de clientes KW - Patrones de carga KW - Libre organización de los mapas KW - Data mining KW - Demand management KW - Electrical customer segmentation KW - Load patterns KW - Self-organizing maps LA - eng PB - IEEE Power & Energy Society ER -