Systematic review on deep reinforcement learning-based energy management for different building types
A Shaqour, A Hagishima - Energies, 2022 - mdpi.com
Owing to the high energy demand of buildings, which accounted for 36% of the global share
in 2020, they are one of the core targets for energy-efficiency research and regulations …
in 2020, they are one of the core targets for energy-efficiency research and regulations …
Electric vehicle charging modes, technologies and applications of smart charging
The rise of the intelligent, local charging facilitation and environmentally friendly aspects of
electric vehicles (EVs) has grabbed the attention of many end-users. However, there are still …
electric vehicles (EVs) has grabbed the attention of many end-users. However, there are still …
[HTML][HTML] Physically consistent neural networks for building thermal modeling: theory and analysis
Due to their high energy intensity, buildings play a major role in the current worldwide
energy transition. Building models are ubiquitous since they are needed at each stage of the …
energy transition. Building models are ubiquitous since they are needed at each stage of the …
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 …
Multi-agent reinforcement learning dealing with hybrid action spaces: A case study for off-grid oriented renewable building energy system
With the application of renewable energy in building energy systems (BES), an increasing
number of power grids require building energy systems coupled to realize off-grid operation …
number of power grids require building energy systems coupled to realize off-grid operation …
[HTML][HTML] Experimental data-driven model predictive control of a hospital HVAC system during regular use
ET Maddalena, SA Mueller, RM dos Santos… - Energy and …, 2022 - Elsevier
Herein we report a multi-zone, heating, ventilation and air-conditioning (HVAC) control case
study of an industrial plant responsible for cooling a hospital surgery center. The adopted …
study of an industrial plant responsible for cooling a hospital surgery center. The adopted …
Dyna-PINN: Physics-informed deep dyna-q reinforcement learning for intelligent control of building heating system in low-diversity training data regimes
This paper introduces Dyna-PINN, a novel physics-informed Deep Dyna-Q (DDQ)
reinforcement learning (RL) approach, designed to address the data-intensive training …
reinforcement learning (RL) approach, designed to address the data-intensive training …
[HTML][HTML] Towards scalable physically consistent neural networks: An application to data-driven multi-zone thermal building models
With more and more data being collected, data-driven modeling methods have been gaining
in popularity in recent years. While physically sound, classical gray-box models are often …
in popularity in recent years. While physically sound, classical gray-box models are often …
[HTML][HTML] Data-driven adaptive building thermal controller tuning with constraints: A primal–dual contextual Bayesian optimization approach
We study the problem of tuning the parameters of a room temperature controller to minimize
its energy consumption, subject to the constraint that the daily cumulative thermal discomfort …
its energy consumption, subject to the constraint that the daily cumulative thermal discomfort …
Towards more accurate and explainable supervised learning-based prediction of deliverability for underground natural gas storage
Numerous subsurface factors, including geology and fluid properties, can affect the
connectivity of the storage spaces in depleted reservoirs; hence, fluid flow simulations …
connectivity of the storage spaces in depleted reservoirs; hence, fluid flow simulations …