Energy Consumption
Energy consumption research focuses on understanding and optimizing energy use across various sectors, from individual households and smart grids to large-scale AI systems and data centers. Current research emphasizes developing energy-efficient machine learning models (e.g., using transformers, convolutional neural networks, and recurrent neural networks) and employing techniques like federated learning to improve privacy while training models on distributed data. This work is crucial for mitigating the environmental impact of increasing energy demands and for improving the efficiency and sustainability of numerous technological applications.
Papers
Occupancy Detection Based on Electricity Consumption
Thomas Brilland, Guillaume Matheron, Laetitia Leduc, Yukihide Nakada
A multi-sourced data and agent-based approach for complementing Time Use Surveys in the context of residential human activity and load curve simulation
Mathieu Schumann, Quentin Reynaud, François Sempé, Julien Guibourdenche, Jean-Baptiste Ly, Nicolas Sabouret