Advanced controls on energy reliability, flexibility, resilience, and occupant-centric control for smart and energy-efficient buildings—a state-of-the-art review
Advanced controls have attracted increasing interests due to the high requirement on smart
and energy-efficient (SEE) buildings and decarbonization in the building industry with …
and energy-efficient (SEE) buildings and decarbonization in the building industry with …
A systematic study on reinforcement learning based applications
We have analyzed 127 publications for this review paper, which discuss applications of
Reinforcement Learning (RL) in marketing, robotics, gaming, automated cars, natural …
Reinforcement Learning (RL) in marketing, robotics, gaming, automated cars, natural …
A data-driven output voltage control of solid oxide fuel cell using multi-agent deep reinforcement learning
J Li, T Yu, B Yang - Applied Energy, 2021 - Elsevier
To effectively control the output voltage of solid oxide fuel cells (SOFCs) and improve the
operating efficiency of SOFC systems, an SOFC output voltage data-driven controller based …
operating efficiency of SOFC systems, an SOFC output voltage data-driven controller based …
A new multi-data-driven spatiotemporal PM2. 5 forecasting model based on an ensemble graph reinforcement learning convolutional network
X Liu, M Qin, Y He, X Mi, C Yu - Atmospheric Pollution Research, 2021 - Elsevier
Spatiotemporal PM2. 5 forecasting technology plays an important role in urban traffic
environment management and planning. In order to establish a satisfactory high-precision …
environment management and planning. In order to establish a satisfactory high-precision …
A multi-step predictive deep reinforcement learning algorithm for HVAC control systems in smart buildings
The development of the building energy management systems (BEMS) enable users to
intelligently control Heating, Ventilation, Air-conditioning and Cooling (HVAC) systems …
intelligently control Heating, Ventilation, Air-conditioning and Cooling (HVAC) systems …
A new ensemble deep graph reinforcement learning network for spatio-temporal traffic volume forecasting in a freeway network
Spatio-temporal traffic volume forecasting technologies can effectively improve freeway
traffic efficiency and the travel comfort of humans. To construct a high-precision traffic …
traffic efficiency and the travel comfort of humans. To construct a high-precision traffic …
Dynamics analysis of a novel hybrid deep clustering for unsupervised learning by reinforcement of multi-agent to energy saving in intelligent buildings
The heating, ventilating and air conditioning (HVAC) systems energy demand can be
reduced by manipulating indoor conditions within the comfort range, which relates to control …
reduced by manipulating indoor conditions within the comfort range, which relates to control …
Deep reinforcement learning control for co-optimizing energy consumption, thermal comfort, and indoor air quality in an office building
With the recent demand for decarbonization and energy efficiency, advanced HVAC control
using Deep Reinforcement Learning (DRL) becomes a promising solution. Due to its flexible …
using Deep Reinforcement Learning (DRL) becomes a promising solution. Due to its flexible …
[HTML][HTML] Ai-driven innovations in building energy management systems: A review of potential applications and energy savings
Despite the tightening of energy performance standards for buildings in various countries
and the increased use of efficient and renewable energy technologies, it is clear that the …
and the increased use of efficient and renewable energy technologies, it is clear that the …
[HTML][HTML] A review of reinforcement learning for controlling building energy systems from a computer science perspective
D Weinberg, Q Wang, TO Timoudas… - Sustainable cities and …, 2023 - Elsevier
Energy efficient control of energy systems in buildings is a widely recognized challenge due
to the use of low temperature heating, renewable electricity sources, and the incorporation of …
to the use of low temperature heating, renewable electricity sources, and the incorporation of …