Energy flexibility of residential buildings: A systematic review of characterization and quantification methods and applications
With building electric demand becoming increasingly dynamic, and a growing percentage of
intermittent renewable power generation from solar photovoltaics and wind turbines, the …
intermittent renewable power generation from solar photovoltaics and wind turbines, the …
State of the art review on model predictive control (MPC) in Heating Ventilation and Air-conditioning (HVAC) field
Y Yao, DK Shekhar - Building and Environment, 2021 - Elsevier
Building systems are subject of dynamic system that have a general feature of non-linearity
and in turn, present us with different challenges for its optimized control of energy-saving …
and in turn, present us with different challenges for its optimized control of energy-saving …
All you need to know about model predictive control for buildings
It has been proven that advanced building control, like model predictive control (MPC), can
notably reduce the energy use and mitigate greenhouse gas emissions. However, despite …
notably reduce the energy use and mitigate greenhouse gas emissions. However, despite …
Reinforcement learning for building controls: The opportunities and challenges
Building controls are becoming more important and complicated due to the dynamic and
stochastic energy demand, on-site intermittent energy supply, as well as energy storage …
stochastic energy demand, on-site intermittent energy supply, as well as energy storage …
Building thermal load prediction through shallow machine learning and deep learning
Building thermal load prediction informs the optimization of cooling plant and thermal energy
storage. Physics-based prediction models of building thermal load are constrained by the …
storage. Physics-based prediction models of building thermal load are constrained by the …
State-of-the-art on research and applications of machine learning in the building life cycle
Fueled by big data, powerful and affordable computing resources, and advanced algorithms,
machine learning has been explored and applied to buildings research for the past decades …
machine learning has been explored and applied to buildings research for the past decades …
Field demonstration and implementation analysis of model predictive control in an office HVAC system
Abstract Model Predictive Control (MPC) is a promising technique to address growing needs
for heating, ventilation, and air-conditioning (HVAC) systems to operate more efficiently and …
for heating, ventilation, and air-conditioning (HVAC) systems to operate more efficiently and …
Data requirements and performance evaluation of model predictive control in buildings: A modeling perspective
Abstract Model predictive control (MPC) has shown great potential in improving building
performance and saving energy. However, after over 20 years of research, it is yet to be …
performance and saving energy. However, after over 20 years of research, it is yet to be …
Operational optimization for off-grid renewable building energy system using deep reinforcement learning
With the application of renewable energy in single office buildings, an increasing number of
power grids require building systems coupled with renewable energy to realize off-grid …
power grids require building systems coupled with renewable energy to realize off-grid …
Metadata schemas and ontologies for building energy applications: A critical review and use case analysis
Digital and intelligent buildings are critical to realizing efficient building energy operations
and a smart grid. With the increasing digitalization of processes throughout the life cycle of …
and a smart grid. With the increasing digitalization of processes throughout the life cycle of …