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Wind Energy Exploitation: Design and Modeling of Wind Turbines and Wind Farms

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Resources and Sustainable Utilization".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 8566

Special Issue Editors

Dr. Fabio Famoso

E-Mail Website
Guest Editor
Engineering Department, University of Messina, 98166 Mesina, Italy
Interests: GIS-based models for advanced energy systems; wind turbines; simulation and optimization of renewable energy systems; environmental impact; air pollutant dispersion modeling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Sebastian Brusca

E-Mail Website
Guest Editor
Department of Engineering, University of Messina, 1, 98166 Messina, Italy
Interests: VAWT; HAWT; wind farms; wind turbine wakes; optimal placement; ducted turbines
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Nowadays, the use and consumption of fossil fuels has dramatically increased with serious consequences regarding the emission of pollutants and climate change. For these reasons, renewable energy systems, in anticipation of the depletion of fossil fuels, represent the best solution to these environmental problems. Among renewable sources, wind energy plays a key role in providing clean energy around the world. Wind power capacity has considerably increased in the last 10 years, with around 840 GW of the total installed capacity in 2021. Therefore, the design and modeling of wind farms and wind turbines are of crucial importance to accurately assess the impact of wind on power systems. Several aspects, such as the estimation of wind energy potential in the presence of obstacles, wake losses induced by upstream and/or downstream turbines, the diagnosis of faults, optimization of wind farm layout, and reliability of wind generators under adverse weather conditions, could require the application and modeling of several approaches, such as computational fluid dynamics (CFD) methods, artificial intelligence (AI) techniques or deterministic models. The aim of this Special Issue is to collect and disseminate novel contributions to the field of wind energy exploitation. Topics of interest for this Special Issue include but are not limited to:

  • Performance analysis of wind turbines or wind farms;
  • Physics-based and/or data-driven modeling;
  • Wind energy source assessment;
  • Wind rotor aerodynamics modeling;
  • Wake dynamics modeling;
  • Onshore and offshore wind farms;
  • Novel wind turbines designs and modeling;
  • Optimal wind farm placement modeling;
  • Maintenance criteria for wind turbines or wind farms;
  • Forecasting models;
  • Wind integration studies.

Dr. Fabio Famoso
Prof. Dr. Sebastian Brusca
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 energy
  • aerogenerators
  • renewable systems
  • modeling
  • wind farms
  • energy exploitation

Published Papers (2 papers)

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Research

12 pages, 3462 KiB  
Article
Short-Term Interval Prediction of Wind Power Based on KELM and a Universal Tabu Search Algorithm
by Qiang Zhou, Yanhong Ma, Qingquan Lv, Ruixiao Zhang, Wei Wang and Shiyou Yang
Sustainability 2022, 14(17), 10779; https://doi.org/10.3390/su141710779 - 29 Aug 2022
Cited by 5 | Viewed by 1342
Abstract
Installed wind power has significantly grown in recent years to synchronize with the ever-increasing demand for environment-friendly and renewable energy. However, wind energy has significant uncertainty or random futures, and will give rise to destructive effects on the safety operations of the power [...] Read more.
Installed wind power has significantly grown in recent years to synchronize with the ever-increasing demand for environment-friendly and renewable energy. However, wind energy has significant uncertainty or random futures, and will give rise to destructive effects on the safety operations of the power system. In this respect, an accurate and reliable wind power prediction is of great significance for improving the power system stability and optimizing the dispatch plan. Compared with traditionally deterministic point forecast techniques, probabilistic forecasting approaches can provide more stochastic information to quantify the random characteristics of wind power and to estimate its impacts on the power system. Moreover, the interval of the output power is a key stochastic information on wind power. In general, an interval prediction needs to compromise the calibration and the average width of the predicted interval. To find the best combination of these two metrics, a methodology based on a kernel extreme learning machine (KELM) and an improved universal tabu search algorithm is proposed. In the proposed methodology, to eliminate the inherent randomness on the weights between the input and hidden lays in the commonly used extreme learning machine, a radial-basis-function-based kernel extreme learning machine is proposed, and an improved tabu search method is introduced to optically compromise the calibration and the average width of the predicted interval to overcome the deficiency of existing algorithms, such as the insufficient global search ability of a particle swarm optimization. A prototype wind farm is utilized as a case study to verify the efficiency and advantage of the proposed methodology. Full article
(This article belongs to the Special Issue Wind Energy Exploitation: Design and Modeling of Wind Turbines and Wind Farms)
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26 pages, 14394 KiB  
Article
On the Performance of a Modified Triple Stack Blade Savonius Wind Turbine as a Function of Geometrical Parameters
by Reza Norouztabar, Seyed Soheil Mousavi Ajarostaghi, Seyed Sina Mousavi, Payam Nejat, Seyed Saeid Rahimian Koloor and Mohamed Eldessouki
Sustainability 2022, 14(16), 9816; https://doi.org/10.3390/su14169816 - 9 Aug 2022
Cited by 9 | Viewed by 6702
Abstract
The Savonius wind turbine is one of the most well-known vertical axis wind turbines with insensitivity to wind direction, flow turbulence, and high torque generation. These turbines can extract up to 20% of the energy from the wind. This study numerically analyzes the [...] Read more.
The Savonius wind turbine is one of the most well-known vertical axis wind turbines with insensitivity to wind direction, flow turbulence, and high torque generation. These turbines can extract up to 20% of the energy from the wind. This study numerically analyzes the performance of a modified Savonius wind turbine equipped with secondary blades and slots. The k-ε standard method is used to simulate the turbulence flow around the turbine, and the simulation is performed using the ANSYS FLUENT 18.2 commercial code. The effects of distance between the main blade and the secondary blade, position of the secondary blade, the width of the main blade’s slot, and the profile of the secondary blade on the produced torque are studied and analyzed. The simulation is performed at four wind velocities: 3, 4, 5, and 6 m/s. The results showed that the output torque at the secondary blade angular position β = 130 is higher than other angles. Furthermore, by increasing the radius of the additional blade from R = 25 to 43 mm, the torque is improved, and the area below the output torque curve is increased. Moreover, the results showed that creating a slot on the main blade equipped with a secondary blade has a significant impact on the produced torque; however, the geometrical parameters of the proposed rotors should be adjusted accurately to find the best case in terms of the produced torque. Full article
(This article belongs to the Special Issue Wind Energy Exploitation: Design and Modeling of Wind Turbines and Wind Farms)
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