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Communication Dans Un Congrès Année : 2023

Sensor-Aided NILM with Gaussian Mixture Models

Résumé

Energy disaggregation, also known as non-intrusive load monitoring (NILM), is the process of analyzing energy consumption in a building and identifying individual appliancelevel energy usage. This approach can provide valuable insights into energy consumption patterns and help reduce overall energy usage, costs, and carbon emissions. This paper proposes a new method for tackling the disaggregation problem by using data from low-cost wireless sensor networks. The proposed approach estimates appliance states using a GMM model and uses these states as features to improve energy disaggregation. The performance of the proposed method was evaluated on a real-world dataset called SmartSense deployed in our lab, and the results showed that it significantly improved the accuracy of conventional NILM disaggregation performance.
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Dates et versions

hal-04399811 , version 1 (17-01-2024)

Identifiants

Citer

Nidhal Balti, Baptiste Vrigneau, Pascal Scalart. Sensor-Aided NILM with Gaussian Mixture Models. 2023 31st European Signal Processing Conference (EUSIPCO), Sep 2023, Helsinki, France. pp.1529-1533, ⟨10.23919/EUSIPCO58844.2023.10289785⟩. ⟨hal-04399811⟩
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