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Wind Energy for Sustainable Development: Driving Factors and Future Outlook

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (2 November 2023) | Viewed by 3313

Special Issue Editors


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Guest Editor
School of Automation, China University of Geosciences, Wuhan 430074, China
Interests: intelligent system control; advanced control theory and applications for complex industrial process; robot control; information fusion; wind power prediction
School of Automation, China University of Geosciences, Wuhan 430074, China
Interests: advanced control theory; renewable energy generation; control of microgrids; wind power prediction

Special Issue Information

Dear Colleagues,

Energy is critical to economic development and social prosperity, as well as playing a key role in driving innovation. Rapidly increasing energy demand has brought the world to the brink of a global energy crisis. In addition, the widespread use of conventional energy sources is polluting the environment and contributing to global warming.

Wind and other renewable energy sources are viable and clean alternatives to fossil fuels. Low operating costs and widespread availability make wind one of the most beneficial and efficient renewable energy sources. This Special Issue will highlight the use of wind power and the importance of improving energy efficiency as key elements in achieving an economically and ecologically sustainable energy future.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Future prospects for innovative technologies in wind power generation;
  • Key elements driving the development of wind power;
  • Renewable energy integration in microgrids;
  • Distributed energy generation;
  • Wind power prediction;
  • Application of energy storage system in wind power;
  • Application of data analysis in wind power systems;
  • Integration of wind power with regional and microgrids;
  • Application of advanced technology in wind power generation system;
  • The impact of wind power on the grid.

We look forward to receiving your contributions

Prof. Dr. Jianqi An
Dr. Min Ding
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

  • wind power
  • distributed generation
  • micro grid

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Published Papers (1 paper)

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Research

26 pages, 7866 KiB  
Article
Assessment of Correction Methods Applied to BEMT for Predicting Performance of Horizontal-Axis Wind Turbines
by Hércules Araújo Oliveira, José Gomes de Matos, Luiz Antonio de Souza Ribeiro, Osvaldo Ronald Saavedra and Jerson Rogério Pinheiro Vaz
Sustainability 2023, 15(8), 7021; https://doi.org/10.3390/su15087021 - 21 Apr 2023
Cited by 5 | Viewed by 2821
Abstract
Blade Element Momentum Theory (BEMT) is the most used method to design horizontal-axis wind turbines worldwide. This is because BEMT has a low computational cost and easy numerical implementation. Additionally, it is demonstrated in the literature that the prediction of output power using [...] Read more.
Blade Element Momentum Theory (BEMT) is the most used method to design horizontal-axis wind turbines worldwide. This is because BEMT has a low computational cost and easy numerical implementation. Additionally, it is demonstrated in the literature that the prediction of output power using BEMT agrees well with experimental data. Another important feature of the BEMT is its applicability to small, medium, and large-sized turbines. However, BEMT models are usually implemented and adjusted for a specific power range turbine, and they are not applied in a more general form. Thus, this article presents an analysis of additional correction methods for tip and root losses, high values of the axial induction factor, and high angle of attack to better represent horizontal-axis turbines in terms of numerical stability. The approach has the intention of combining several complementary correction methods strategically inserted in the BEMT in order to compile an algorithm that is more general, stable, and workable for any turbine size. The main contribution of this work is to propose a stable BEMT numerical algorithm through the assessment of the combination of the correction methods available in the literature, i.e., classical and modern ones. The algorithm ensures applicability for small, medium, and large-sized wind turbines, as well as being fast and easy to implement in any computer and extendable even to turbines with a diffuser. This approach is validated by comparing the results with experimental data from four turbines of different power ranges (1.9 kW to 7.3 MW). The results show the best approximations for performance power curves against the measured values of all turbines. Moreover, it is effective, less complex, and quick in analyzing the performance of those turbines. Furthermore, the need for high-performance computers to analyze the performance of horizontal-axis turbines is avoided. Full article
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