Advances in Offshore Wind and Wave Energies—2nd Edition
A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".
Deadline for manuscript submissions: 30 August 2024 | Viewed by 3510
Special Issue Editors
2. IDMEC—Mechanical Engineering Institute, Avenida Rovisco Pais, 1049-001 Lisbon, Portugal
Interests: wave energy; modeling; control; PLC programming; equipment development
Special Issues, Collections and Topics in MDPI journals
2. CENTEC—Centre for Marine Technology and Ocean Engineering, University of Lisbon, Instituto Superior Técnico (IST), Avenida Rovisco Pais, 1049-001 Lisbon, Portugal
Interests: renewable energy; wave energy converters; fault-tolerant control systems; multi-agent systems; soft robotics; digital factories
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The Journal of Marine Science and Engineering is pleased to announce a Special Issue entitled "Advances in Offshore Wind and Wave Energies—2nd Edition" based on the great success of our previous Special Issue with the same title. The aim of this Special Issue is to collate and publish original research articles covering the latest developments in the field of offshore wind and wave energy. Some potential topics might include, but are not limited to, technological aspects, such as new devices and their designs, modeling, control algorithms and simulation approaches, power optimization, energy harnessing, storage, management and grid connection. The Guest Editors of this Special Issue, together with the Editors of the Journal of Marine Science and Engineering will provide a high-quality reviewing process and ensure efficient publication of original research and review articles.
Dr. Pedro Beirão
Dr. Mário J. G. C. Mendes
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 100 words) can be sent to the Editorial Office for announcement on this website.
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. Journal of Marine Science and Engineering 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 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
- renewable energy
- wind energy
- wave energy
- offshore wind devices
- offshore wave energy converters
- modeling
- control
- wind and wave energy management
Related Special Issue
Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title:
Abstract: This study explores the potential of sustainable energy generation by integrating Floating Offshore Wind Turbines (FOWTs) with Oscillating Water Columns (OWCs), addressing the inherent dynamic complexities and uncertainties. A novel dual approach is introduced, combining regressive modeling of the aero-hydro-elasto-servo-mooring coupled system with a deep data-driven network and proportional-integral-derivative (PID) control mechanism to enhance system control stability. Utilizing data-driven models trained on OpenFAST datasets, real-time predictive behavior analysis and decision-making are facilitated. Advanced computational learning methods, particularly Artificial Neural Networks (ANNs), are employed to replicate the dynamics of FOWT-OWCs numerical models. Subsequently, a sophisticated PID control system is implemented to address structural vibrations, ensuring effective control. Comparative analysis with traditional barge-based FOWT systems demonstrates the efficacy of the enhanced modeling and control approaches. The study reveals the promise of ANN-driven modeling as an alternative to the intricate non-linear dynamics of NREL 5MW FOWT models and highlights the significant improvement in system stability across diverse operational scenarios through tailored PID gain scheduling. Furthermore, this research underscores the importance of cutting-edge control strategies in advancing the stability and efficiency of offshore renewable energy systems, marking a significant step towards a sustainable energy future and inaugurating a new phase for research in feedback control methodologies.