From graph theory to graph neural networks (GNNs): The opportunities of GNNs in power electronics
Graph theory within power electronics, developed over a 50-year span, is continually
evolving, necessitating ongoing research endeavors. Facing with the never-been-seen …
evolving, necessitating ongoing research endeavors. Facing with the never-been-seen …
Liquid hydrogen superconducting transmission based super energy pipeline for Pacific Rim in the context of global energy sustainable development
The global energy issue is undergoing transformation owing to various factors, such as
climate change and geopolitics. In the long term, the primary pathways to achieve …
climate change and geopolitics. In the long term, the primary pathways to achieve …
Embedded scenario clustering for wind and photovoltaic power, and load based on multi-head self-attention
L Liu, X Hu, J Chen, R Wu… - Protection and Control of …, 2024 - ieeexplore.ieee.org
The source and load uncertainties arising from increased applications of renewable energy
sources such as wind and photovoltaic energy in the power system have had adverse …
sources such as wind and photovoltaic energy in the power system have had adverse …
Modeling and control of nuclear–renewable integrated energy systems: Dynamic system model for green electricity and hydrogen production
The need for decarbonization and diversification of energy resources has led to the
development of integrated energy systems (IESs), where multiple resources supply more …
development of integrated energy systems (IESs), where multiple resources supply more …
Generative design for resilience of interdependent network systems
Interconnected complex systems usually undergo disruptions due to internal uncertainties
and external negative impacts such as those caused by harsh operating environments or …
and external negative impacts such as those caused by harsh operating environments or …
Post-Disaster Microgrid Formation for Enhanced Distribution System Resilience
This paper proposes a deep reinforcement learning (DRL) based approach for post-disaster
critical load restoration in active distribution systems to form microgrids through network …
critical load restoration in active distribution systems to form microgrids through network …
Leveraging graph clustering techniques for cyber‐physical system analysis to enhance disturbance characterisation
N Jacobs, S Hossain‐McKenzie, S Sun… - IET Cyber‐Physical …, 2024 - Wiley Online Library
Cyber‐physical systems have behaviour that crosses domain boundaries during events
such as planned operational changes and malicious disturbances. Traditionally, the cyber …
such as planned operational changes and malicious disturbances. Traditionally, the cyber …
Network reconfiguration for enhanced operational resilience using reinforcement learning
M Abdelmalak, M Gautam, S Morash… - … on Smart Energy …, 2022 - ieeexplore.ieee.org
This paper proposes a reinforcement learning-based approach for distribution network
reconfiguration (DNR) to enhance the resilience of the electric power supply. Resilience …
reconfiguration (DNR) to enhance the resilience of the electric power supply. Resilience …
Post-disaster generation dispatching for enhanced resilience: A multi-agent deep deterministic policy gradient learning approach
M Abdelmalak, H Hosseinpour… - 2022 North …, 2022 - ieeexplore.ieee.org
This paper proposes a reinforcement learning-based approach for dispatching distributed
generators (DGs) to enhance operational resilience of electric distribution systems after a …
generators (DGs) to enhance operational resilience of electric distribution systems after a …
Topology-based Clustering Techniques for Graph Partitioning Applied to the Italian Transmission Network
As renewable energy sources are integrated into power systems, the complexity of their
management increases. For the analysis of modern power systems, clustering algorithms …
management increases. For the analysis of modern power systems, clustering algorithms …