[HTML][HTML] Applications of reinforcement learning in energy systems

ATD Perera, P Kamalaruban - Renewable and Sustainable Energy …, 2021 - Elsevier
Energy systems undergo major transitions to facilitate the large-scale penetration of
renewable energy technologies and improve efficiencies, leading to the integration of many …

Reinforcement learning for demand response: A review of algorithms and modeling techniques

JR Vázquez-Canteli, Z Nagy - Applied energy, 2019 - Elsevier
Buildings account for about 40% of the global energy consumption. Renewable energy
resources are one possibility to mitigate the dependence of residential buildings on the …

[HTML][HTML] Reinforcement learning for whole-building HVAC control and demand response

D Azuatalam, WL Lee, F De Nijs, A Liebman - Energy and AI, 2020 - Elsevier
This paper proposes a novel reinforcement learning (RL) architecture for the efficient
scheduling and control of the heating, ventilation and air conditioning (HVAC) system in a …

The use of artificial intelligence (AI) methods in the prediction of thermal comfort in buildings: Energy implications of AI-based thermal comfort controls

J Ngarambe, GY Yun, M Santamouris - Energy and Buildings, 2020 - Elsevier
Buildings consume about 40% of globally-produced energy. A notable amount of this energy
is used to provide sufficient comfort levels to the building occupants. Moreover, given recent …

State-of-the-art thermal comfort models for car cabin Environment

B Chen, Y Lian, L Xu, Z Deng, F Zhao, H Zhang… - Building and …, 2024 - Elsevier
The automotive industry has recently seen significant advancements, making cars a
dominant form of urban transportation. This development has led to increased focus on …

Energy-efficient heating control for smart buildings with deep reinforcement learning

A Gupta, Y Badr, A Negahban, RG Qiu - Journal of Building Engineering, 2021 - Elsevier
Buildings account for roughly 40% of the total energy consumption in the world, out of which
heating, ventilation, and air conditioning are the major contributors. Traditional heating …

Cabin and battery thermal management of connected and automated HEVs for improved energy efficiency using hierarchical model predictive control

MR Amini, H Wang, X Gong… - … on Control Systems …, 2019 - ieeexplore.ieee.org
Incorporating traffic information in power management optimization process for electrified
and connected vehicles offers opportunities for improving fuel economy. Integrating the …

Review of cabin thermal management for electrified passenger vehicles

A Lajunen, Y Yang, A Emadi - IEEE Transactions on Vehicular …, 2020 - ieeexplore.ieee.org
The technical maturity and rapidly increasing market share of electrified vehicles have given
more importance to the cabin thermal management. Efficient thermal management has a key …

Computer vision-based smart HVAC control system for university classroom in a subtropical climate

H Lan, HC Hou, Z Gou, MS Wong, Z Wang - Building and Environment, 2023 - Elsevier
To respond to the increasing demand for a comfortable, productive and energy efficient
study environment, the application of artificial intelligence technologies in the smart control …

[HTML][HTML] A review of reinforcement learning applications to control of heating, ventilation and air conditioning systems

S Sierla, H Ihasalo, V Vyatkin - Energies, 2022 - mdpi.com
Reinforcement learning has emerged as a potentially disruptive technology for control and
optimization of HVAC systems. A reinforcement learning agent takes actions, which can be …