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Title: Electricity demand profile prediction based on household characteristics
Authors: Melicio, Rui
Keywords: Data mining
Machine learning
Smart meter data
Household energy consumption
Issue Date: 22-May-2015
Publisher: 12th International Conference on the European Energy Market — EEM 2015
Citation: 12th International Conference on the European Energy Market — EEM 2015, pp. 1–5, Lisbon, Portugal, 20–22 May 2015
Abstract: This work proposes a methodology for predicting the typical daily load profile of electricity usage based on static data obtained from surveys. The methodology intends to: (1) determine consumer segments based on the metering data using the k-means clustering algorithm, (2) correlate survey data to the segments, and (3) develop statistical and machine learning classification models to predict the demand profile of the consumers. The developed classification models contribute to make the study and planning of demand side management programs easier, provide means for studying the impact of alternative tariff setting methods and generate useful knowledge for policy makers.
Type: lecture
Appears in Collections:FIS - Comunicações - Em Congressos Científicos Internacionais

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