Please use this identifier to cite or link to this item: https://accedacris.ulpgc.es/jspui/handle/10553/161397
Title: Determination of the Weekly Profile of the Residential Electricity Consumption in Gran Canaria Island: A Survey-Based Approach
Authors: Brey-García, Adrián
Vega-Fuentes, Eduardo
Mazorra-Aguiar, Luis
Déniz, Fabián
UNESCO Clasification: 3306 Ingeniería y tecnología eléctricas
Keywords: Demand-Side Management
Machine Learning
Neural Networks
Residential Load Curve
Survey
Issue Date: 2025
Journal: IEEE Pes Innovative Smart Grid Technologies Conference Europe
Conference: 2025 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT Europe 2025
Abstract: The transition to a more sustainable energy system requires a better understanding of residential electricity consumption. This study reviews existing methodologies for analyzing household energy use and examines the weekly load profile of households in Gran Canaria by combining surveys and neural networks. While real responses are being collected, synthetic data generated with artificial intelligence w ere used to train a predictive model. The goal is to estimate residential consumption from socio-economic data and offer insights into household load curves in the Canary Islands, supporting energy policies and demand-side management strategies.
URI: https://accedacris.ulpgc.es/jspui/handle/10553/161397
ISBN: 9798331525033
ISSN: 2165-4816
DOI: 10.1109/ISGTEurope64741.2025.11305656
Source: IEEE PES Innovative Smart Grid Technologies Conference Europe [ISSN 2165-4816], (Enero 2025)
Appears in Collections:Actas de congresos
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