Television usage recommendations for energy efficiency: A probabilistic methodology based on the Wasserstein distance

Francisco Rodríguez-Cuenca, Eugenio Francisco Sánchez-Úbeda, José Portela, Antonio Muñoz, Víctor Guizien, Andrea Veiga Santiago and Alicia Mateo González

Energy, 2025, vol. 322, issue C

Abstract: This paper presents a general and interpretable methodology for delivering personalized energy-saving recommendations to household televisions. TVs, though often overlooked, account for 7% of household energy consumption, ranking as the fourth most costly category. The methodology extracts five easy-to-understand scalar features from historical TV energy consumption data, each representing a key usage aspect: OFF consumption, ON consumption, Daily Consumption, Session Duration, and Schedule of Consumption. It then employs a probabilistic approach based on the Wasserstein Distance to compare these features across TVs. Based on this comparison, two methods—percentage and elbow— are introduced for identifying TVs with significant deviations by feature, accompanied by tailored recommendations.

Keywords: Recommender system; Energy saving; Occupant behavior; Household appliances; Wasserstein distance; Data-driven (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:322:y:2025:i:c:s0360544225010527

DOI: 10.1016/j.energy.2025.135410

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