Knowledge extraction from medium voltage load diagrams to support the definitio...

• Author(s): Ramos, Sérgio ; Figueiredo, Vera ; Rodrigues, Fátima ; Pinheiro, Raul ; Vale, Zita
• Date: 2007
• Persistent ID: http://hdl.handle.net/10400.22/1517
• Origin: Repositório Científico do Instituto Politécnico do Porto
• Subject(s): Electricity markets; Load profiles; Data mining; Hierarchical clustering; Classification
• Document Type: Article
• Language: English

Description

With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.