Advanced controls on energy reliability, flexibility, resilience, and occupant-centric control for smart and energy-efficient buildings—a state-of-the-art review
Advanced controls have attracted increasing interests due to the high requirement on smart
and energy-efficient (SEE) buildings and decarbonization in the building industry with …
and energy-efficient (SEE) buildings and decarbonization in the building industry with …
[HTML][HTML] A comprehensive review of the applications of machine learning for HVAC
Heating, ventilation and air-conditioning (HVAC) accounts for around 40% of the total
building energy consumption. It has therefore become a major target for reductions, in terms …
building energy consumption. It has therefore become a major target for reductions, in terms …
How to improve the application potential of deep learning model in HVAC fault diagnosis: Based on pruning and interpretable deep learning method
Automated fault detection and diagnosis (AFDD) plays a crucial role in enhancing the
energy efficiency of air conditioning systems. Deep learning has emerged as a promising …
energy efficiency of air conditioning systems. Deep learning has emerged as a promising …
[HTML][HTML] An integrated framework for sustainable and efficient building maintenance operations aligning with climate change, SDGs, and emerging technology
Improving the operation and maintenance of buildings can significantly reduce carbon
emissions, energy consumption, and other environmental challenges while promoting …
emissions, energy consumption, and other environmental challenges while promoting …
Novel transformer-based self-supervised learning methods for improved HVAC fault diagnosis performance with limited labeled data
Existing data-driven HVAC fault diagnosis methods mainly adopt supervised learning
paradigms, making them less feasible/implementable for individual buildings with limited …
paradigms, making them less feasible/implementable for individual buildings with limited …
Techniques and technologies to board on the feasible renewable and sustainable energy systems
This paper is the editorial for the virtual special issue (VSI) of Renewable and Sustainable
Energy Reviews (RSER) dedicated to the 16th Conference on Sustainable Development of …
Energy Reviews (RSER) dedicated to the 16th Conference on Sustainable Development of …
Integrating active learning and semi-supervised learning for improved data-driven HVAC fault diagnosis performance
Data-driven methods have drawn increasing interests in HVAC fault diagnosis tasks due to
their intrinsic advantages in making real-time automated decisions. To ensure the reliability …
their intrinsic advantages in making real-time automated decisions. To ensure the reliability …
A thermodynamic-law-integrated deep learning method for high-dimensional sensor fault detection in diverse complex HVAC systems
Abstract In building Heating, Ventilation and Air Conditioning (HVAC) systems, sensor
healthy operation is the foundation of the adopted control strategies to improve building …
healthy operation is the foundation of the adopted control strategies to improve building …
The impact of improved PCA method based on anomaly detection on chiller sensor fault detection
A Liang, Y Hu, G Li - International Journal of Refrigeration, 2023 - Elsevier
With the widespread use of building automation systems (BAS), a large amount of chiller
operating data is often readily available, which provides a good basis for optimizing the …
operating data is often readily available, which provides a good basis for optimizing the …
[HTML][HTML] Building thermal dynamics modeling with deep transfer learning using a large residential smart thermostat dataset
Understanding thermal dynamics and obtaining the computational model of residential
buildings enable its scaled application in energy retrofits, control optimization and …
buildings enable its scaled application in energy retrofits, control optimization and …