[HTML][HTML] An overview of machine learning applications for smart buildings

K Alanne, S Sierla - Sustainable Cities and Society, 2022 - Elsevier
The efficiency, flexibility, and resilience of building-integrated energy systems are
challenged by unpredicted changes in operational environments due to climate change and …

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 …

[HTML][HTML] State-of-the-art review of occupant behavior modeling and implementation in building performance simulation

O Ahmed, N Sezer, M Ouf, LL Wang… - … and Sustainable Energy …, 2023 - Elsevier
Occupant Behavior (OB) is one of the major drivers of building energy consumption.
However, OB is usually oversimplified in Building Performance Simulation (BPS), resulting …

[HTML][HTML] Strategic potential of multi-energy system towards carbon neutrality: A forward-looking overview

TM Alabi, FD Agbajor, Z Yang, L Lu… - Energy and Built …, 2023 - Elsevier
Carbon neutrality is an ambitious goal that has been promulgated to be achieved on or
before 2060. However, most of the current energy policies focus more on carbon emission …

[HTML][HTML] Challenges and opportunities of occupant-centric building controls in real-world implementation: A critical review

A Soleimanijavid, I Konstantzos, X Liu - Energy and Buildings, 2024 - Elsevier
Over the past few decades, attention in buildings' design and operation has gradually shifted
from promoting only energy efficiency objectives to also addressing human comfort and well …

Energy-efficient heating control for nearly zero energy residential buildings with deep reinforcement learning

H Qin, Z Yu, T Li, X Liu, L Li - Energy, 2023 - Elsevier
Abstract Controlling Heating, Ventilation and Air Conditioning (HVAC) systems is critical to
improving energy efficiency of demand-side. In this paper, a model-free optimal control …

A guideline to document occupant behavior models for advanced building controls

B Dong, R Markovic, S Carlucci, Y Liu, A Wagner… - Building and …, 2022 - Elsevier
The availability of computational power, and a wealth of data from sensors have boosted the
development of model-based predictive control for smart and effective control of advanced …

Occupant behavior impact in buildings and the artificial intelligence-based techniques and data-driven approach solutions

B Yan, W Yang, F He, W Zeng - Renewable and Sustainable Energy …, 2023 - Elsevier
Occupant behavior in buildings might result into gap between predicted and actual energy
use and cause indoor thermal comfort fluctuations, due to its uncertainty and …

[HTML][HTML] Dynamic indoor thermal environment using reinforcement learning-based controls: Opportunities and challenges

A Chatterjee, D Khovalyg - Building and environment, 2023 - Elsevier
Currently, the indoor thermal environment in many buildings is controlled by conventional
control techniques that maintain the indoor temperature within a prescribed deadband. The …

[HTML][HTML] Energy efficiency through the implementation of an AI model to predict room occupancy based on thermal comfort parameters

SA Abdel-Razek, HS Marie, A Alshehri, OM Elzeki - Sustainability, 2022 - mdpi.com
Room occupancy prediction based on indoor environmental quality may be the
breakthrough to ensure energy efficiency and establish an interior ambience tailored to each …