[HTML][HTML] Energetics Systems and artificial intelligence: Applications of industry 4.0

T Ahmad, H Zhu, D Zhang, R Tariq, A Bassam, F Ullah… - Energy Reports, 2022 - Elsevier
Industrial development with the growth, strengthening, stability, technical advancement,
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

Y Balali, A Chong, A Busch, S O'Keefe - Renewable and Sustainable …, 2023 - Elsevier
Implementing an efficient control strategy for heating, ventilation, and air conditioning
(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

K Ren, J Liu, Z Wu, X Liu, Y Nie, H Xu - Applied Energy, 2024 - Elsevier
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 …

[HTML][HTML] A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems

İ Yazici, I Shayea, J Din - … Science and Technology, an International Journal, 2023 - Elsevier
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 …

A review of deep reinforcement learning for smart building energy management

L Yu, S Qin, M Zhang, C Shen, T Jiang… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
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 …

Reinforcement learning for selective key applications in power systems: Recent advances and future challenges

X Chen, G Qu, Y Tang, S Low… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With large-scale integration of renewable generation and distributed energy resources,
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 …

THB Huy, HT Dinh, DN Vo, D Kim - Energy Conversion and Management, 2023 - Elsevier
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 …

Multi-agent deep reinforcement learning for HVAC control in commercial buildings

L Yu, Y Sun, Z Xu, C Shen, D Yue… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
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 …

Dynamic energy dispatch strategy for integrated energy system based on improved deep reinforcement learning

T Yang, L Zhao, W Li, AY Zomaya - Energy, 2021 - Elsevier
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 …

Smart building energy management and monitoring system based on artificial intelligence in smart city

R Selvaraj, VM Kuthadi, S Baskar - Sustainable Energy Technologies and …, 2023 - Elsevier
In the present scenario, the fastest-growing environmental concerns are energy
management and monitoring. In-efficient energy recycling, energy consumption, energy …