Energy consumption prediction of a smart home using non-intrusive appliance load monitoring

Lazhar Chabane (), Said Drid (), Larbi Chrifi-Alaoui () and Laurant Delahoche ()
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Lazhar Chabane: University of 8 Mai 1945 Geulma
Said Drid: University of Batna 2
Larbi Chrifi-Alaoui: University of Picardie Jules Verne, IUT de l’Aisne
Laurant Delahoche: University of Picardie Jules Verne, IUT de l’Aisne

International Journal of System Assurance Engineering and Management, 2024, vol. 15, issue 3, No 27, 1244 pages

Abstract: Abstract The increasing need for energy has been a major problem in recent years. In view of this problem, energy saving and reduction of energy consumption are strongly encouraged. The residential sector accounts an important part of final energy consumption and is therefore a major challenge for improving energy efficiency. In this work, individual energy consumption is determined from measurements taken downstream at the energy meter using a single current and a single voltage sensor, without a learning phase or knowledge of the equipment inside the home. This non-intrusive appliance load monitoring (NIALM) method has several advantages: it allows us to process the load curves and to extract useful information for the identification of the uses and to prevent the most energy consuming appliances. In addition, we will apply the Auto Regressive Moving Average with eXternal inputs (ARMAX) model to predict the energy consumption. These two approaches will allow us to better analyze the management, control, metering and billing system of consumption in order to ensure better energy efficiency in buildings.

Keywords: Energy consumption; Consumption prediction; Smart home; Non-intrusive appliance load monitoring; Data processing; ARMAX model (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13198-023-02209-3

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