Artificial Intelligence for the Modeling of Energy Systems
A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".
Deadline for manuscript submissions: 25 March 2027 | Viewed by 181
Special Issue Editors
Interests: magnetic equivalent circuits; electrical machines; PEM fuel cells; PEM electrolyzers
Special Issues, Collections and Topics in MDPI journals
Interests: quasi-3D analytical modelling FEM; electromagnetic analysis; permanent magnet machines; multiphysics simulation technological innovation and artificial intelligence; AI solutions for industry and energy
Special Issue Information
Dear Colleagues,
The deployment of artificial intelligence (AI) has the potential to profoundly transform the way models for energy systems are developed. Today, the development of these models relies mainly on the advanced mathematical knowledge of a limited number of scientific experts in electrical engineering. Depending on the assumptions made and the complexity of the studied energy system, model development is often time-consuming, and equation building can be difficult. The use of AI could facilitate the development, automatic generation, improvement, or adaptation of multiphysics models while significantly reducing the time required for their development. Such progress would provide researchers with the freedom to focus on scientific innovation related to the optimization, design, and management of energy systems.
The objective of this Special Issue is to explore the current potential of AI for the generation or enhancement of models of varying complexity in electrical engineering, as well as for parameter identification from experimental or simulated data. Topics of interest include (but are not limited to) the following:
- Applications in energy systems for production, conversion, storage or use (e.g., electric machines, fuel cells, electrolyzers, liquefiers, batteries, supercapacitors);
- Automatic model generation, parameter identification and calibration;
- Solving open problems in the energy field;
- Derivation of empirical energy equations from data;
- Development of AI-based digital twins for energy systems.
Numerical methods and experimental tests are encouraged for the comparison or validation of AI-based models.
Dr. Frédéric Dubas
Guest Editor
Dr. Huguette Tiegna
Dr. Antony Plait
Co-Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- artificial intelligence
- energy systems
- multiphysics modeling
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