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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 …
Distributed control and communication strategies in networked microgrids
Networked microgrids (NMGs) provide a promising solution for accommodating various
distributed energy resources (DERs) and enhancing the system performance in terms of …
distributed energy resources (DERs) and enhancing the system performance in terms of …
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 …
Knowledge-based reinforcement learning and estimation of distribution algorithm for flexible job shop scheduling problem
Y Du, J Li, X Chen, P Duan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Inthis study, a flexible job shop scheduling problem with time-of-use electricity price
constraint is considered. The problem includes machine processing speed, setup time, idle …
constraint is considered. The problem includes machine processing speed, setup time, idle …
On data-driven modeling and control in modern power grids stability: Survey and perspective
Modern power grids are fast evolving with the increasing volatile renewable generation,
distributed energy resources (DERs) and time-varying operating conditions. The DERs …
distributed energy resources (DERs) and time-varying operating conditions. The DERs …
Survey on microgrids frequency regulation: Modeling and control systems
The traditional power system structure is constantly changing due to the application of
renewable energy sources (RESs) and microgrids (MGs) into the power system network …
renewable energy sources (RESs) and microgrids (MGs) into the power system network …
Fusion of microgrid control with model-free reinforcement learning: Review and vision
Challenges and opportunities coexist in microgrids as a result of emerging large-scale
distributed energy resources (DERs) and advanced control techniques. In this paper, a …
distributed energy resources (DERs) and advanced control techniques. In this paper, a …
A comprehensive review: study of artificial intelligence optimization technique applications in a hybrid microgrid at times of fault outbreaks
The use of fossil-fueled power stations to generate electricity has had a damaging effect
over the years, necessitating the need for alternative energy sources. Microgrids consisting …
over the years, necessitating the need for alternative energy sources. Microgrids consisting …
[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 …
Navigating the landscape of deep reinforcement learning for power system stability control: A review
The widespread penetration of inverter-based resources has profoundly impacted the
electrical stability of power systems (PSs). Deepening grid integration of photovoltaic and …
electrical stability of power systems (PSs). Deepening grid integration of photovoltaic and …