Santiago Bañales1,2,*, Raquel Dormido1, Natividad Duro1
CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 869-907, 2025, DOI:10.32604/cmes.2024.054946
- 17 December 2024
Abstract Customer segmentation according to load-shape profiles using smart meter data is an increasingly important application to vital the planning and operation of energy systems and to enable citizens’ participation in the energy transition. This study proposes an innovative multi-step clustering procedure to segment customers based on load-shape patterns at the daily and intra-daily time horizons. Smart meter data is split between daily and hourly normalized time series to assess monthly, weekly, daily, and hourly seasonality patterns separately. The dimensionality reduction implicit in the splitting allows a direct approach to clustering raw daily energy time series… More >
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