Artificial Intelligence in Wind Energy Optimization Design
A Special Issue of Machines (ISSN 2075-1702) belonging to the section "Turbomachinery".
Deadline for manuscript submissions: 31 January 2027 | Viewed by 244
Editors
Interests: mechanical signal processing; noise and vibration; diagnostic and prognostics; sensors; design optimisation; wind energy; failure analysis; condition monitoring
Interests: artificial intelligence for fluid mechanics and energy systems; wind and tidal energy technologies; wake dynamics and flow control; condition monitoring and intelligent fault diagnosis of rotating machinery; data-driven modeling and digital twin technologies
Special Issue Information
Dear Colleagues,
The rapid expansion of wind energy places increasing demands on the design, operation, and power optimization. Wind energy optimization is a multidisciplinary problem involving turbine layout, wake interaction, aerodynamic performance, control strategy, structural reliability, operation and maintenance, and energy conversion efficiency. Recent advances in artificial intelligence, including machine learning, physics-informed neural networks, surrogate modeling, reinforcement learning, and digital twins, are creating new opportunities to accelerate design exploration and improve the performance, reliability, and economic viability of wind energy systems. In addition, operation and maintenance of the wind turbine, rotating system and power generator play a critical role in achieving its economic viability.
We are pleased to invite contributions to this Special Issue on “Artificial Intelligence in Wind Energy Optimization Design”. This Special Issue aims to present recent theoretical, computational, and experimental developments in AI-enabled wind turbine/farm energy optimization, with particular emphasis on methods related to machinery design, turbomachinery, electromechanical energy conversion, automation and control, condition monitoring, and intelligent machines.
Original research articles and review papers are welcome. Topics may include, but are not limited to, AI-based wind farm layout optimization; wake modeling and prediction; CFD-assisted surrogate models; physics-informed learning; reinforcement learning for farm-level control; digital-twin-based design and operation; optimization of floating and offshore wind farms; uncertainty quantification; multi-objective optimization of power production, loads, and cost; intelligent monitoring, diagnosis, and maintenance for wind turbines and wind farms.
We look forward to receiving your contributions.
Prof. Dr. Andy Chit Tan
Prof. Dr. Longyan Wang
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly 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 2400 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
- wind farm optimization
- wind turbine layout design
- wake modeling
- surrogate modeling
- physics-informed machine learning
- reinforcement learning
- digital twins
- farm-level control
- machine condition monitoring
- diagnostics
- failure detection
- reliability
- rotating machines
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
