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Study on the Performance of Wave Energy Converters
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Study on the Performance of Wave Energy Converters

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: 10 June 2024 | Viewed by 1804

Special Issue Editors

Dr. Elizaldo Domingues Dos Santos

E-Mail Website
Guest Editor
Escola de Engenharia, Conselho Departamental, Universidade Federal do Rio Grande - FURG, Rio Grande, Brazil
Interests: fluid mechanics; heat transfer; design; renewable energy; computational fluid dynamics
Special Issues, Collections and Topics in MDPI journals
Dr. Liércio André Isoldi

E-Mail Website
Guest Editor
Escola de Engenharia, Universidade Federal do Rio Grande - FURG, Rio Grande, Brazil
Interests: solid mechanics; geometrical investigation; renewable energy; numerical approach

Special Issue Information

Dear Colleagues,

Ocean wave energy converters (WECs) have emerged as a promising technology for harnessing renewable energy from the vast resources of the ocean. As the world seeks to transition toward clean and sustainable energy sources, understanding the performance of WECs becomes crucial for optimizing their efficiency and reliability. This Special Issue aims to explore various aspects related to the performance of ocean wave energy converters. We invite researchers and experts from academia and industry to contribute their original research articles, reviews and case studies on this topic.

The topics of interest include, but are not limited to:

  • Design and optimization of WECs: novel design concepts, modeling techniques and optimization strategies for improving the performance of WECs;
  • Performance evaluation and monitoring: experimental and numerical methods for assessing the performance of WECs, including power generation, energy conversion efficiency and reliability;
  • Wave resource assessment: studies focusing on characterizing and predicting the wave resource at different coastal regions and its impact on the performance of WECs;
  • Control and operation strategies: advanced control algorithms and operational strategies for enhancing the performance and survivability of WECs under varying wave conditions;
  • Environmental impact assessment: investigations on the potential environmental impacts of WECs, including their effects on marine ecosystems and mitigation measures.

Dr. Elizaldo Domingues Dos Santos
Dr. Liércio André Isoldi
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

  • ocean wave energy converters
  • WEC
  • performance evaluation
  • ocean wave energy
  • wave resource assessment
  • marine renewable energy

Published Papers (2 papers)

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Research

21 pages, 5753 KiB  
Article
Enhancing Wave Energy Conversion Efficiency through Supervised Regression Machine Learning Models
by Sunny Kumar Poguluri and Yoon Hyeok Bae
J. Mar. Sci. Eng. 2024, 12(1), 153; https://doi.org/10.3390/jmse12010153 - 12 Jan 2024
Cited by 1 | Viewed by 743
Abstract
The incorporation of machine learning (ML) has yielded substantial benefits in detecting nonlinear patterns across a wide range of applications, including offshore engineering. Existing ML works, specifically supervised regression models, have not undergone exhaustive scrutiny, and there are no potential or concurrent models [...] Read more.
The incorporation of machine learning (ML) has yielded substantial benefits in detecting nonlinear patterns across a wide range of applications, including offshore engineering. Existing ML works, specifically supervised regression models, have not undergone exhaustive scrutiny, and there are no potential or concurrent models for improving the performance of wave energy converter (WEC) devices. This study employs supervised regression ML models, including multi-layer perceptron, support vector regression, and XGBoost, to optimize the geometric aspects of an asymmetric WEC inspired by Salter’s duck, based on key parameters. These important parameters, the ballast weight and its position, vary along a guided line within the available geometric resilience of the asymmetric WEC. Each supervised regression ML model was fine-tuned through hyperparameter optimization using Grid cross-validation. When evaluating the performance of each ML model, it became evident that the tuned hyperparameters of XGBoost led to predictions that strongly aligned with the actual values compared to other models. Furthermore, the study extended to assess the performance of the optimized WEC at the designated deployment test site location. Full article
(This article belongs to the Special Issue Study on the Performance of Wave Energy Converters)
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27 pages, 15963 KiB  
Article
Numerical and Experimental Investigation of the Dynamics of a U-Shaped Sloshing Tank to Increase the Performance of Wave Energy Converters
by Marco Fontana, Giuseppe Giorgi, Massimiliano Accardi, Ermanno Giorcelli, Stefano Brizzolara and Sergej Antonello Sirigu
J. Mar. Sci. Eng. 2023, 11(12), 2339; https://doi.org/10.3390/jmse11122339 - 11 Dec 2023
Viewed by 721
Abstract
In this investigation, a comprehensive study was conducted on a U-shaped sloshing tank, based on reversing the classical treatment of such devices as motion stabilizers and using them instead to improve the performance of wave energy converters. The modeling encompasses a comparative analysis [...] Read more.
In this investigation, a comprehensive study was conducted on a U-shaped sloshing tank, based on reversing the classical treatment of such devices as motion stabilizers and using them instead to improve the performance of wave energy converters. The modeling encompasses a comparative analysis between a linear model and Computational Fluid Dynamics (CFD) simulations. The validation of the CFD methodology was rigorously executed via a series of experimental tests, subsequently enhancing the linear model. The refined linear model demonstrates a notable alignment with rigorously verified results, thus establishing itself as a reliable tool for advanced research, indicating promise for various applications. Furthermore, this novelty is addressed by simulating the integration of a U-tank device with a pitch-based wave energy converter, displaying a broadening of the operational bandwidth and a substantial performance improvement, raising the pitch motion of the floater to about 850% in correspondence with the new secondary peak over extended periods, effectively addressing previously identified limitations. This achievement contributes to the system’s practical relevance in marine energy conversion. Full article
(This article belongs to the Special Issue Study on the Performance of Wave Energy Converters)
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