Wind Energy Assessment Based on CFD Simulations and Analytical Techniques

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: 30 July 2024 | Viewed by 1091

Special Issue Editors


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Guest Editor
Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja 86400, Johor, Malaysia
Interests: CFD simulations; wind energy; wind turbine design; renewable energy technologies

E-Mail Website
Guest Editor
Faculty of Mechanical and Manufacturing Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja 86400, Johor, Malaysia
Interests: computational fluid dynamics; aeroacoustics

Special Issue Information

Dear Colleagues,

Today, the quest for clean and sustainable energy is rising globally at a rapid pace with the current technological advances, an increase in the world's population, and a recurring need to reduce CO2 emissions. Wind energy stands to play a crucial role in ensuring sustainable energy development in the world as its potential is abundant across the globe. However, the conversion capability of the existing wind turbines is still unsatisfactory and far from the Betz limit. This inability stems from both technological constraints such as an efficient design of the wind turbine rotor, generator/alternator and gearbox and environmental issues such as appropriate site selection (micrositing) and wind regime characteristics.

This Special Issue aims to address recent developments on wind turbine rotor design improvement through CFD simulations as well as analytical assessment on site siting and wind regime characteristics. Topics include, but are not limited to:

  • CFD simulations;
  • Wind turbine design;
  • Fluid flow characterizations;
  • Wind power assessment;
  • Site siting;
  • Wind regime characteristics.

Dr. Djamal Hissein Didane
Dr. Bukhari Bin Manshoor
Guest Editors

Manuscript Submission Information

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Keywords

  • CFD simulations
  • rotor design
  • aerodynamics performance
  • VAWT
  • HAWT
  • micrositing
  • wind power

Published Papers (1 paper)

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Research

15 pages, 8628 KiB  
Article
Wind Shear Model Considering Atmospheric Stability to Improve Accuracy of Wind Resource Assessment
by Hongpeng Liu, Guanjin Chen, Zejia Hua, Jingang Zhang and Qing Wang
Processes 2024, 12(5), 954; https://doi.org/10.3390/pr12050954 - 8 May 2024
Viewed by 345
Abstract
An accurate wind shear model is an important prerequisite in extrapolating the wind resource from lower heights to the increasing hub height of wind turbines. Based on the 1-year dataset (collected in 2014) consisting of 15-minute intervals collected at heights of 2, 10, [...] Read more.
An accurate wind shear model is an important prerequisite in extrapolating the wind resource from lower heights to the increasing hub height of wind turbines. Based on the 1-year dataset (collected in 2014) consisting of 15-minute intervals collected at heights of 2, 10, 50, 100, and 150 m on an anemometer tower in northern China, the present study focuses on the time-varying relationship between the wind shear coefficient (WSC) and atmospheric stability and proposes a wind shear model considering atmospheric stability. Through the relationship between Monin–Obukhov (M-O) length and gradient Richardson number, the M-O length is directly calculated by wind data, and the WSC is calculated by combining the Panofsky and Dutton (PD) models, which enhances the engineering practicability of the model. Then, the performance of the model is quantified and compared with two alternative methods: the use of annual average WSC and the use of stability change WSC extrapolation. The analysis demonstrates that the proposed model outperforms the other approaches in terms of normal root mean square error (NRMSE) and normal bias (NB). More specifically, this method reduces the NRMSE and NB by 24–29% and 76–95%, respectively. Meanwhile, it reaches the highest extrapolation accuracy under unstable and stable atmospheric conditions. The results are verified using the Weibull distribution. Full article
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