Review on deep learning applications in frequency analysis and control of modern power system
The penetration of renewable energy resources (RES) generation and the interconnection of
regional power grids in wide area and large scale have led the modern power system to …
regional power grids in wide area and large scale have led the modern power system to …
Reinforcement learning and its applications in modern power and energy systems: A review
With the growing integration of distributed energy resources (DERs), flexible loads, and
other emerging technologies, there are increasing complexities and uncertainties for …
other emerging technologies, there are increasing complexities and uncertainties for …
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 …
Electric vehicle charging management based on deep reinforcement learning
A time-variable time-of-use electricity price can be used to reduce the charging costs for
electric vehicle (EV) owners. Considering the uncertainty of price fluctuation and the …
electric vehicle (EV) owners. Considering the uncertainty of price fluctuation and the …
[HTML][HTML] Reinforcement learning for industrial process control: A case study in flatness control in steel industry
Highlights•A new learning controller is developed for an industrial control system.•An
ensemble learning based reinforcement learning method is proposed.•A real industrial strip …
ensemble learning based reinforcement learning method is proposed.•A real industrial strip …
Deep reinforcement learning for smart grid operations: algorithms, applications, and prospects
With the increasing penetration of renewable energy and flexible loads in smart grids, a
more complicated power system with high uncertainty is gradually formed, which brings …
more complicated power system with high uncertainty is gradually formed, which brings …
[PDF][PDF] Reinforcement learning for decision-making and control in power systems: Tutorial, review, and vision
With large-scale integration of renewable generation and distributed energy resources
(DERs), modern power systems are confronted with new operational challenges, such as …
(DERs), modern power systems are confronted with new operational challenges, such as …
Data-driven resilient automatic generation control against false data injection attacks
With the advancement of communication technologies and the development of the smart
grid, today's physical power systems present an ever-growing dependency on cyber …
grid, today's physical power systems present an ever-growing dependency on cyber …
Multi-energy net load forecasting for integrated local energy systems with heterogeneous prosumers
The rapid development of distributed generators and demand response management
programs are transforming the traditional consumers to emerging prosumers. While, it is …
programs are transforming the traditional consumers to emerging prosumers. While, it is …
Load altering attack-tolerant defense strategy for load frequency control system
Cyber attacks become emerging threats to every information-oriented energy management
system. By violating the cyber systems, the hacker can disrupt the security and stability due …
system. By violating the cyber systems, the hacker can disrupt the security and stability due …