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
Q Zhou, M Shahidehpour, A Paaso… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
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 …
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 …
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 …
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 …
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] Interval type-2 fuzzy sets and systems: Overview and outlook
WU Dongrui, Z Zhi-Gang, MO Hong, W Fei-Yue - ACTA Autom. Sin, 2020 - aas.net.cn
Type-1 fuzzy sets can model the linguistic uncertainty from a single user, ie, intra-personal
uncertainty. Type-1 fuzzy systems have been widely used in controls and machine learning …
uncertainty. Type-1 fuzzy systems have been widely used in controls and machine learning …
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 …
Aggregation of EVs for primary frequency control of an industrial microgrid by implementing grid regulation & charger controller
After nearly a century with internal combustion engines dominating the transportation sector,
it now appears that electric vehicles (EVs) are on the brink of enjoying rapid development …
it now appears that electric vehicles (EVs) are on the brink of enjoying rapid development …