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[HTML][HTML] An overview of machine learning applications for smart buildings
The efficiency, flexibility, and resilience of building-integrated energy systems are
challenged by unpredicted changes in operational environments due to climate change and …
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 …
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
Occupant Behavior (OB) is one of the major drivers of building energy consumption.
However, OB is usually oversimplified in Building Performance Simulation (BPS), resulting …
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
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 …
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 …
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 …
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
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 …
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 …
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
Currently, the indoor thermal environment in many buildings is controlled by conventional
control techniques that maintain the indoor temperature within a prescribed deadband. The …
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
Room occupancy prediction based on indoor environmental quality may be the
breakthrough to ensure energy efficiency and establish an interior ambience tailored to each …
breakthrough to ensure energy efficiency and establish an interior ambience tailored to each …