Reliability of Onshore and Offshore Wind Energy Generation Systems
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".
Deadline for manuscript submissions: 5 September 2024 | Viewed by 1791
Special Issue Editors
Interests: reliability of renewable energy systems; probabilistic design; probabilistic multibody dynamic analysis and (probabilistic) prognostics and health management
Interests: reliability of renewable energy systems; probabilistic design; (probabilistic) prognostics and health management; composite materials; infrared imaging; artificial intelligence
Special Issue Information
Dear Colleagues,
It is our pleasure to announce a new Special Issue, “Reliability of Onshore and Offshore Wind Energy Generation Systems”, of the journal Sustainability.
The search for new sources of energy to quench societal demand is a continuous process. One of these efforts is the use of wind turbines to harvest abundant wind energy to produce electricity. Currently, offshore and onshore wind farms satisfy more than 6% of electricity demand globally: more than 50% in Denmark, about 40% in Uruguay, about 35% in Ireland, more than 9% in the United States (over 50% in Iowa and South Dakota, and over 30% in Kansas, Oklahoma, and North Dakota (and growing)) and about 6% in China. At the same time, they face challenges such as the sudden failure of mechanical (e.g., gearboxes), structural (e.g., blades), and electrical components, which can result in expensive catastrophic failures and very long downtimes for maintenance. In order to predict such failures before their occurrence, real-time health monitoring, reliability analysis and the prediction of remaining useful life are significantly important to optimize maintenance. This reliability analysis can be specifically conducted for mechanical, structural, and electrical components, which can help avoid sudden failures and create effective maintenance plans.
This Special Issue aims to focus on the reliability studies of blades, foundations, gearboxes, main bearings, and other rotating components as well as electrical components such as generators, power electronics, and battery storage systems. These reliability studies can include, but are not limited to, advanced methodologies such as machine learning, artificial intelligence, digital twins, finite element analysis, signal processing, non-destructive and non-contact techniques, structural health monitoring, and Bayesian inference.
Original research articles and reviews are welcome on the following topics:
- (Probabilistic) prognostic and health management (PHM): sensing, diagnosis, and prognosis;
- Application of Bayesian Inference in PHM;
- Application of deep and machine learning in PHM;
- Uncertainty quantification;
- Risk and reliability analysis;
- Modeling: physics-based and data-driven;
- Development of effective and efficient damage precursor detection methods;
- Artificial intelligence and digital twins;
- Structural health monitoring.
Dr. Fisseha M. Alemayehu
Dr. Shweta Dabetwar
Dr. Shawn Sheng
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. Sustainability 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 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
- reliability
- wind turbines
- risk
- resilience
- health monitoring
- prognostics
- health management
- remaining useful life
