Deep reinforcement learning in smart manufacturing: A review and prospects
To facilitate the personalized smart manufacturing paradigm with cognitive automation
capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by …
capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by …
[HTML][HTML] A critical review of improved deep learning methods for the remaining useful life prediction of lithium-ion batteries
As widely used for secondary energy storage, lithium-ion batteries have become the core
component of the power supply system and accurate remaining useful life prediction is the …
component of the power supply system and accurate remaining useful life prediction is the …
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 …
[HTML][HTML] Demand-side management in industrial sector: A review of heavy industries
H Golmohamadi - Renewable and Sustainable Energy Reviews, 2022 - Elsevier
The penetration of renewable energies is increasing in power systems all over the world.
The volatility and intermittency of renewable energies pose real challenges to energy …
The volatility and intermittency of renewable energies pose real challenges to energy …
Deep reinforcement learning in production systems: a systematic literature review
Shortening product development cycles and fully customisable products pose major
challenges for production systems. These not only have to cope with an increased product …
challenges for production systems. These not only have to cope with an increased product …
Turning waste into wealth: A systematic review on echelon utilization and material recycling of retired lithium-ion batteries
With the increasing production and marketing of global electric vehicles (EVs), a large
quantity of lithium ion battery (LIB) raw materials are demanded, and massive LIBs will be …
quantity of lithium ion battery (LIB) raw materials are demanded, and massive LIBs will be …
Applications of reinforcement learning for building energy efficiency control: A review
Q Fu, Z Han, J Chen, Y Lu, H Wu, Y Wang - Journal of Building Engineering, 2022 - Elsevier
The wide variety of smart devices equipped in modern intelligent buildings and the
increasing comfort requirements of occupants for the environment make the control of …
increasing comfort requirements of occupants for the environment make the control of …
A scalable privacy-preserving multi-agent deep reinforcement learning approach for large-scale peer-to-peer transactive energy trading
Peer-to-peer (P2P) transactive energy trading has emerged as a promising paradigm
towards maximizing the flexibility value of prosumers' distributed energy resources (DERs) …
towards maximizing the flexibility value of prosumers' distributed energy resources (DERs) …
Scalable coordinated management of peer-to-peer energy trading: A multi-cluster deep reinforcement learning approach
The increasing penetration of small-scale distributed energy resources (DER) has the
potential to support cost-efficient energy balancing in emerging electricity systems, but is …
potential to support cost-efficient energy balancing in emerging electricity systems, but is …
Key technologies for smart energy systems: Recent developments, challenges, and research opportunities in the context of carbon neutrality
Energy crisis and environmental pollution have expedited the transition of the energy
system. Global use of low-carbon energy has increased from 1: 6.16 to 1: 5.37. Smart energy …
system. Global use of low-carbon energy has increased from 1: 6.16 to 1: 5.37. Smart energy …