Employing Federated Learning for Training Autonomous HVAC Systems

arXiv:2405.00389v1 Announce Type: cross
Abstract: Buildings account for 40 % of global energy consumption. A considerable portion of building energy consumption stems from heating, ventilation, and air conditioning (HVAC), and thus implementing smart, energy-efficient HVAC systems has the potential to significantly impact the course of climate change. In recent years, model-free reinforcement learning algorithms have been increasingly assessed for this purpose due to their ability to learn and adapt purely from experience. They have been shown to outperform classical controllers …

abstract air conditioning arxiv autonomous building buildings change climate climate change consumption course cs.lg cs.sy eess.sy energy federated learning free global hvac impact math.oc reinforcement smart systems training type