A review of recent literature on systems and methods for the control of thermal comfort in buildings
B Grassi, EA Piana, AM Lezzi, M Pilotelli - Applied Sciences, 2022 - mdpi.com
Thermal comfort in indoor environments is perceived as an important factor for the well-
being and productivity of the occupants. To practically create a comfortable environment, a …
being and productivity of the occupants. To practically create a comfortable environment, a …
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 …
Mitigating an adoption barrier of reinforcement learning-based control strategies in buildings
Reinforcement learning (RL) algorithms have shown great promise in controlling building
systems to minimize energy use, operational cost, and occupant discomfort. RL agents learn …
systems to minimize energy use, operational cost, and occupant discomfort. RL agents learn …
Addressing data inadequacy challenges in personal comfort models by combining pretrained comfort models
Occupant thermal-comfort complaints are the biggest operational headache of facilities
managers. Many of the complaints can be attributed to the diverse nature of individuals' …
managers. Many of the complaints can be attributed to the diverse nature of individuals' …
Diversity for transfer in learning-based control of buildings
The application of reinforcement learning to the optimal control of building systems has
gained traction in recent years as it can cut the building energy consumption and improve …
gained traction in recent years as it can cut the building energy consumption and improve …
Efficacy of temporal and spatial abstraction for training accurate machine learning models: A case study in smart thermostats
Smart thermostats are increasingly popular in homes and buildings as they improve
occupant comfort, lower energy use in heating and cooling systems, and reduce utility bills …
occupant comfort, lower energy use in heating and cooling systems, and reduce utility bills …
The impact of forecast characteristics on the forecast value for the dispatchable feeder
Transforming the energy system to decentralised, renewable energy sources requires
measures to balance their fluctuating nature and stabilise the energy system. One such …
measures to balance their fluctuating nature and stabilise the energy system. One such …
Addressing partial observability in reinforcement learning for energy management
Automatic control of energy systems is affected by the uncertainties of multiple factors,
including weather, prices and human activities. The literature relies on Markov-based …
including weather, prices and human activities. The literature relies on Markov-based …
Investigating the Impact of Space Allocation Strategy on Energy-Comfort Trade-off in Office Buildings
T Zhang, O Ardakanian - Companion Proceedings of the 14th ACM …, 2023 - dl.acm.org
With the global push to decarbonize the building sector and growing interest in occupant-
centric building controls, numerous simulation and field studies have been conducted to …
centric building controls, numerous simulation and field studies have been conducted to …
Control Policy Correction Framework for Reinforcement Learning-based Energy Arbitrage Strategies
SSK Madahi, G Gokhale, MS Verwee… - arXiv preprint arXiv …, 2024 - arxiv.org
A continuous rise in the penetration of renewable energy sources, along with the use of the
single imbalance pricing, provides a new opportunity for balance responsible parties to …
single imbalance pricing, provides a new opportunity for balance responsible parties to …