Daily typical load clustering of residential customers

Sathiracheewin, Supalak; Surapatana, Vichai

doi:10.1109/ecticon.2011.5947960

Cited by 11 publications

(1 citation statement)

References 6 publications

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“…Classical KM is one of the most used clustering algorithms to obtain energy consumption profiles. Both KM and FCM have already been successfully used for the case of smart metering electricity data [32][33][34][35][36][37][38][39][40][41] and natural gas data [26,30]. FCM allows gradual memberships to cluster, which offers the opportunity to deal with data that belong to more than one cluster simultaneously [31].…”

Section: Introductionmentioning

confidence: 99%

Segmentation of Residential Gas Consumers Using Clustering Analysis

et al. 2017

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Abstract:The growing environmental concerns and liberalization of energy markets have resulted in an increased competition between utilities and a strong focus on efficiency. To develop new energy efficiency measures and optimize operations, utilities seek new market-related insights and customer engagement strategies. This paper proposes a clustering-based methodology to define the segmentation of residential gas consumers. The segments of gas consumers are obtained through a detailed clustering analysis using smart metering data. Insights are derived from the segmentation, where the segments result from the clustering process and are characterized based on the consumption profiles, as well as according to information regarding consumers' socio-economic and household key features. The study is based on a sample of approximately one thousand households over one year. The representative load profiles of consumers are essentially characterized by two evident consumption peaks, one in the morning and the other in the evening, and an off-peak consumption. Significant insights can be derived from this methodology regarding typical consumption curves of the different segments of consumers in the population. This knowledge can assist energy utilities and policy makers in the development of consumer engagement strategies, demand forecasting tools and in the design of more sophisticated tariff systems.

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