[HTML][HTML] A quasi-oppositional learning of updating quantum state and Q-learning based on the dung beetle algorithm for global optimization
Z Wang, L Huang, S Yang, D Li, D He… - Alexandria Engineering …, 2023 - Elsevier
There are many tricky optimization problems in real life, and metaheuristic algorithms are the
most effective way to solve optimization problems at a lower cost. The dung beetle …
most effective way to solve optimization problems at a lower cost. The dung beetle …
Decomposition prediction fractional-order PID reinforcement learning for short-term smart generation control of integrated energy systems
L Yin, D Zheng - Applied Energy, 2024 - Elsevier
With the continuous development of integrated energy systems (IESs), various distributed
power is continuously connected to IESs. Uncertainty and volatility of renewable energy …
power is continuously connected to IESs. Uncertainty and volatility of renewable energy …
Data-driven load frequency cooperative control for multi-area power system integrated with VSCs and EV aggregators under cyber-attacks
This paper proposes a cooperative load frequency control (LFC) strategy based on a multi-
agent deep reinforcement learning (MADRL) framework for the multi-area power system in …
agent deep reinforcement learning (MADRL) framework for the multi-area power system in …
Quantum-inspired distributed policy-value optimization learning with advanced environmental forecasting for real-time generation control in novel power systems
L Yin, X Cao - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
With the increasing weight of wind and photovoltaic power (WPP) in grids, the uncertainty of
WPP has an increasing impact on power systems. The access to WPP raises the difficulty of …
WPP has an increasing impact on power systems. The access to WPP raises the difficulty of …
Synergy of Human-Centered AI and Cyber-Physical-Social Systems for Enhanced Cognitive Situation Awareness: Applications, Challenges and Opportunities
This paper explores the convergence of Human-Centered AI (HCAI) and Cyber-Physical
Social Systems (CPSS) in pursuing advanced Cognitive Situation Awareness (CSA) …
Social Systems (CPSS) in pursuing advanced Cognitive Situation Awareness (CSA) …
A Robust V2G Voltage Control Scheme for Distribution Networks Against Cyber Attacks and Customer Interruptions
A decent vehicle-to-grid (V2G) control scheme improves voltage stability and grid reliability
of distribution networks (DNs) by providing reactive power and ancillary services. However …
of distribution networks (DNs) by providing reactive power and ancillary services. However …
Lazy deep Q networks for unified rotor angle stability framework with unified time-scale of power systems with mass distributed energy storage
L Yin, N Mo, Y Lu - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
The addition of increasing numbers of new energy sources can lead to challenges to the
security and stability of power systems. The combined rotor angle stability (RAS) framework …
security and stability of power systems. The combined rotor angle stability (RAS) framework …
Adaptive cyber-tolerant finite-time frequency control framework for renewable-integrated power system under deception and periodic denial-of-service attacks
AK Chaudhary, S Roy, D Guha, R Negi, S Banerjee - Energy, 2024 - Elsevier
This work concentrates on designing and applying an adaptive cyber-tolerant finite-time
frequency control framework for smart power systems under state-dependent sensor …
frequency control framework for smart power systems under state-dependent sensor …
Fractional-order transfer Q-learning based on modal decomposition and convolutional neural networks for voltage control of smart grids
L Yin, N Mo - Advanced Engineering Informatics, 2024 - Elsevier
Extensive distributed energy connected to smart grids (SGs) poses a huge challenge to the
voltage regulation of power systems. Conventional automatic voltage control (AVC) …
voltage regulation of power systems. Conventional automatic voltage control (AVC) …
Fractional-order Q-learning based on modal decomposition and convolutional neural networks for voltage control of smart grids
L Yin, N Mo - Applied Soft Computing, 2024 - Elsevier
To maintain uniformity in the time scale of the control system, a coordinated first-level
voltage control (FVC) framework is proposed for the voltage controller of three-state energy …
voltage control (FVC) framework is proposed for the voltage controller of three-state energy …