Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.7
2.9
Journals
JMSE
Special Issues
Renewable Energy Applications: Wind Turbines, Marine Current Turbines, Hybrid Generation...
share announcement

Renewable Energy Applications: Wind Turbines, Marine Current Turbines, Hybrid Generation Systems, and Smart Grids

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: closed (10 April 2022) | Viewed by 2345

Special Issue Editors

Prof. Dr. Yassine Amirat

E-Mail Website1 Website2
Guest Editor
L@bISEN, ISEN Yncréa Ouest, Brest, France
Interests: electric machines and drives; tidal and wave power; wind power; fault detection and diagnosis; fault-tolerant control; microgrids; smart grids
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Tianzhen Wang

E-Mail Website
Guest Editor
Department of Electrical Engineering, Shanghai Maritime University, Shanghai 201306, China
Interests: fault diagnosis; fault tolerance fault detection; control systems; control theory; tidal and wave power
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Climate change due to greenhouse emissions and the depletion risk of traditional fossil energy resources are two great challenges faced by human society. The use of renewable energy sources in energy supply has been indexed as a solution and has been growing rapidly in recent years. Despite the massive deployment of renewables, they still face major barriers to wider adoption. Some are associated with renewable energy technologies, while others are due to the modern energy market and regulatory and infrastructure realities.

This Special Issue aims to collect high-quality papers in renewable energy applications and thus create a space where readers can find renewable energies engineering critical reviews on methods, solutions, and applications, helping to strengthen cross-field cooperation mechanisms to boost the deployment of enabling renewable energy technologies. In this context, researchers are encouraged to submit manuscripts on innovative technical developments, reviews, case studies, and analytical as well as assessment papers from different disciplines, which are relevant to renewable energy applications and the renewable energy market: marine current turbines, wave energies, offshore wind turbine technologies, sensing and monitoring systems, subsea engineering, hybrid generation systems, and smart grids.

Prof. Dr. Yassine Amirat
Prof. Dr. Tianzhen 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 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

  • marine renewable energies
  • offshore wind turbine
  • energy management
  • hybrid power generation
  • renewable energy market

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

16 pages, 5350 KiB  
Article
A Layering Linear Discriminant Analysis-Based Fault Diagnosis Method for Grid-Connected Inverter
by Guangfeng Jin, Tianzhen Wang, Yassine Amirat, Zhibin Zhou and Tao Xie
J. Mar. Sci. Eng. 2022, 10(7), 939; https://doi.org/10.3390/jmse10070939 - 08 Jul 2022
Cited by 5 | Viewed by 1501
Abstract
Grid-connected inverters are the core equipment for connecting marine energy power generation systems to the public electric utility. The variation of current sensor fault severity will make fault samples multimodal. However, linear discriminant analysis assumes that the same fault is independent and identically [...] Read more.
Grid-connected inverters are the core equipment for connecting marine energy power generation systems to the public electric utility. The variation of current sensor fault severity will make fault samples multimodal. However, linear discriminant analysis assumes that the same fault is independent and identically distributed. To solve this problem, this paper proposes a layering linear discriminant analysis method based on traditional linear discriminant analysis. The proposed method divides the historical fault data based on the sensor fault severity layer-by-layer until the distribution of the same fault category in each subset is very close. Linear discriminant analysis is used to analyze historical fault data in each subgroup, and the kappa coefficient is applied as the basis for ending the training process. A BP neural network is employed to estimate the fault severity during the testing process, and the fault diagnosis sub-model is selected. The proposed method enables the accurate diagnosis of faults with different distributions in the same category and provides an accurate estimate of the sensor’s fault severity degree. The estimated value of the sensor’s fault degree can provide critical information for the maintenance of the equipment and can be used to correct the sensor’s output. Full article
(This article belongs to the Special Issue Renewable Energy Applications: Wind Turbines, Marine Current Turbines, Hybrid Generation Systems, and Smart Grids)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop