[HTML][HTML] An overview of machine learning applications for smart buildings
The efficiency, flexibility, and resilience of building-integrated energy systems are
challenged by unpredicted changes in operational environments due to climate change and …
challenged by unpredicted changes in operational environments due to climate change and …
[HTML][HTML] A critical review of occupant energy consumption behavior in buildings: How we got here, where we are, and where we are headed
X Xu, H Yu, Q Sun, VWY Tam - Renewable and Sustainable Energy …, 2023 - Elsevier
Occupant behavior has been widely considered as one of the key influencing factors on
building energy consumption. The complexity of its formation mechanism and the dynamic …
building energy consumption. The complexity of its formation mechanism and the dynamic …
Prediction of heating and cooling loads based on light gradient boosting machine algorithms
J Guo, S Yun, Y Meng, N He, D Ye, Z Zhao, L Jia… - Building and …, 2023 - Elsevier
Abstract Machine learning models have been widely used to study the prediction of heating
and cooling loads in residential buildings. However, most of these methods use the default …
and cooling loads in residential buildings. However, most of these methods use the default …
Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings
In recent years, advanced control strategies based on Deep Reinforcement Learning (DRL)
proved to be effective in optimizing the management of integrated energy systems in …
proved to be effective in optimizing the management of integrated energy systems in …
Applications of reinforcement learning for building energy efficiency control: A review
Q Fu, Z Han, J Chen, Y Lu, H Wu, Y Wang - Journal of Building Engineering, 2022 - Elsevier
The wide variety of smart devices equipped in modern intelligent buildings and the
increasing comfort requirements of occupants for the environment make the control of …
increasing comfort requirements of occupants for the environment make the control of …
Scalable coordinated management of peer-to-peer energy trading: A multi-cluster deep reinforcement learning approach
The increasing penetration of small-scale distributed energy resources (DER) has the
potential to support cost-efficient energy balancing in emerging electricity systems, but is …
potential to support cost-efficient energy balancing in emerging electricity systems, but is …
Deep reinforcement learning optimal control strategy for temperature setpoint real-time reset in multi-zone building HVAC system
X Fang, G Gong, G Li, L Chun, P Peng, W Li… - Applied Thermal …, 2022 - Elsevier
Determining a proper trade-off between energy consumption and indoor thermal comfort is
important for HVAC system control. Deep Q-learning (DQN) based multi-objective optimal …
important for HVAC system control. Deep Q-learning (DQN) based multi-objective optimal …
[HTML][HTML] Advances of machine learning in multi-energy district communities‒mechanisms, applications and perspectives
Y Zhou - Energy and AI, 2022 - Elsevier
Energy paradigm transition towards the carbon neutrality requires combined and continuous
efforts in cleaner power production, advanced energy storages, flexible district energy …
efforts in cleaner power production, advanced energy storages, flexible district energy …
Multi-agent deep reinforcement learning optimization framework for building energy system with renewable energy
R Shen, S Zhong, X Wen, Q An, R Zheng, Y Li, J Zhao - Applied Energy, 2022 - Elsevier
Under the background of high global building energy consumption, meeting the ever-
growing energy consumption demand of building energy system (BES) through renewable …
growing energy consumption demand of building energy system (BES) through renewable …
Data-driven district energy management with surrogate models and deep reinforcement learning
Demand side management at district scale plays a crucial role in the energy transition
process, being an ideal candidate to balance the needs of both users and grid, by managing …
process, being an ideal candidate to balance the needs of both users and grid, by managing …