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[HTML][HTML] Energetics Systems and artificial intelligence: Applications of industry 4.0
Industrial development with the growth, strengthening, stability, technical advancement,
reliability, selection, and dynamic response of the power system is essential. Governments …
reliability, selection, and dynamic response of the power system is essential. Governments …
[HTML][HTML] Energy modelling and control of building heating and cooling systems with data-driven and hybrid models—A review
Implementing an efficient control strategy for heating, ventilation, and air conditioning
(HVAC) systems can lead to improvements in both energy efficiency and thermal …
(HVAC) systems can lead to improvements in both energy efficiency and thermal …
A data-driven DRL-based home energy management system optimization framework considering uncertain household parameters
With the rise in household computing power and the increasing number of smart devices,
more and more residents are able to participate in demand response (DR) management …
more and more residents are able to participate in demand response (DR) management …
[HTML][HTML] A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems
Different fields have been thriving with the advents in mobile communication systems in
recent years. These fields reap benefits of data collected by Internet of Things (IoT) in next …
recent years. These fields reap benefits of data collected by Internet of Things (IoT) in next …
A review of deep reinforcement learning for smart building energy management
Global buildings account for about 30% of the total energy consumption and carbon
emission, raising severe energy and environmental concerns. Therefore, it is significant and …
emission, raising severe energy and environmental concerns. Therefore, it is significant and …
Reinforcement learning for selective key applications in power systems: Recent advances and future challenges
With large-scale integration of renewable generation and distributed energy resources,
modern power systems are confronted with new operational challenges, such as growing …
modern power systems are confronted with new operational challenges, such as growing …
[HTML][HTML] Real-time energy scheduling for home energy management systems with an energy storage system and electric vehicle based on a supervised-learning …
With rising energy costs and concerns about environmental sustainability, there is a growing
need to deploy Home Energy Management Systems (HEMS) that can efficiently manage …
need to deploy Home Energy Management Systems (HEMS) that can efficiently manage …
Multi-agent deep reinforcement learning for HVAC control in commercial buildings
In commercial buildings, about 40%-50% of the total electricity consumption is attributed to
Heating, Ventilation, and Air Conditioning (HVAC) systems, which places an economic …
Heating, Ventilation, and Air Conditioning (HVAC) systems, which places an economic …
Dynamic energy dispatch strategy for integrated energy system based on improved deep reinforcement learning
Dynamic energy dispatch is an integral part of the operation optimization of integrated
energy systems (IESs). Most existing dynamic dispatch schemes depend heavily on explicit …
energy systems (IESs). Most existing dynamic dispatch schemes depend heavily on explicit …
Smart building energy management and monitoring system based on artificial intelligence in smart city
In the present scenario, the fastest-growing environmental concerns are energy
management and monitoring. In-efficient energy recycling, energy consumption, energy …
management and monitoring. In-efficient energy recycling, energy consumption, energy …