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 …
A comprehensive review of predictive control strategies in heating, ventilation, and air-conditioning (HVAC): Model-free VS model
X **n, Z Zhang, Y Zhou, Y Liu, D Wang… - Journal of Building …, 2024 - Elsevier
Predictive control offers significant advantages in nonlinear control, high thermal inertia, and
dynamic control. This article uses a Systematic Reviews and Meta-Analyses methodology to …
dynamic control. This article uses a Systematic Reviews and Meta-Analyses methodology to …
Data-driven predictive control for smart HVAC system in IoT-integrated buildings with time-series forecasting and reinforcement learning
Optimising HVAC operations towards human wellness and energy efficiency is a major
challenge for smart facilities management, especially amid COVID situations. Although IoT …
challenge for smart facilities management, especially amid COVID situations. Although IoT …
High spatial granularity residential heating load forecast based on Dendrite net model
With the application of smart meters, more information is available from residential buildings
for support heat load forecast. Yet, there is still a lack of an effective method to exploit the …
for support heat load forecast. Yet, there is still a lack of an effective method to exploit the …
[HTML][HTML] AI-Driven Innovations in Building Energy Management Systems: A Review of Potential Applications and Energy Savings
Despite the tightening of energy performance standards for buildings in various countries
and the increased use of efficient and renewable energy technologies, it is clear that the …
and the increased use of efficient and renewable energy technologies, it is clear that the …
Real-time automatic control of multi-energy system for smart district community: A coupling ensemble prediction model and safe deep reinforcement learning
Energy system autonomous control is influenced by day-ahead forecasting, despite being
carried out independently in the literature. This paper develops an energy management …
carried out independently in the literature. This paper develops an energy management …
Prospects and challenges of reinforcement learning-based HVAC control
Increasing worldwide energy demand and the resulting escalations in greenhouse gas
emissions require a reassessment of energy usage in many sectors. The building industry …
emissions require a reassessment of energy usage in many sectors. The building industry …
Sustainable residential building energy consumption forecasting for smart cities using optimal weighted voting ensemble learning
In recent times, smart-built environments have gone through an incessant transformation,
becoming more independent and sensitive ecosystems which can balance energy …
becoming more independent and sensitive ecosystems which can balance energy …
[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 …
A review on enhancing energy efficiency and adaptability through system integration for smart buildings
The increasing need for reducing carbon emissions and promoting smart, energy-saving
buildings is fueling the rising trend of sophisticated control systems. This study provides …
buildings is fueling the rising trend of sophisticated control systems. This study provides …