Symmetry/Asymmetry in Applied Machine Learning and Neural Networks for Hybrid Energy Ship Power System
A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".
Deadline for manuscript submissions: 30 May 2025 | Viewed by 1039
Special Issue Editors
Interests: optimization strategies for hybrid energy systems; detection of malicious attacks in power systems; power system; state estimation; smart grid
Interests: high-power multilevel converter technology; photovoltaic grid-connected technology; power quality assessment and management; flexible dc transmission; distribution technology
Special Issue Information
Dear Colleagues,
As the main carrier of maritime transportation and trade, more than 90% of traditional ships’ main propulsion power units are currently diesel engines that burn heavy oil. The single energy structure of a traditional ship system results in a large amount of greenhouse gases during navigation, which cannot achieve efficient energy utilization. To achieve the global greenhouse gas emission reduction strategy, new energy technologies such as wind energy, solar energy, and fuel cells have been widely applied in new energy ships. However, the intermittent, fluctuating, and uncertain characteristics of new energy power generation devices, as well as the voltage and frequency fluctuations of ship power grids under different operating conditions, have caused difficulties in characterizing the dynamic model of large-scale ship energy power systems as well as coordinating the output of multiple energy sources under different sea conditions. In combination with increasingly mature AI technology, solving the collaborative optimization and control problems of ship energy power systems under dual carbon constraints is critical to ensure the stable operation of ships.
Topics in this Special Issue may include (but are not limited to) the following:
- Symmetry in the characterization of the dynamic model of ship energy power systems under different time scales;
- Application of emerging technologies in ship energy power systems such as federated machine learning, digital twins, and blockchain;
- Collaborative control for new cyber–physical–energy fusion ship energy power systems;
- Life prediction and evaluation of energy storage systems for new ship energy power systems;
- Symmetry in the coordination control and optimization of scheduling strategies by considering multi-objective scenarios;
- Key technologies for the panoramic situational awareness of new ship energy power systems;
- Symmetry in the detection and localization of voltage and frequency fault/attack for new ship energy power systems;
- Key technologies for the elastic defense of new ship energy power systems in extreme disasters.
Dr. Xinyu Wang
Dr. Shuzheng Wang
Dr. Shaoping Chang
Guest Editors
Manuscript Submission Information
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Keywords
- symmetry in ship energy power systems
- symmetry in coordination control and optimization
- life prediction and evaluation of energy storage systems
- security mechanism under extreme disaster conditions
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