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Review | Open Access

Perspectives of Vertical Axis Wind Turbines in Cluster Configurations

Ryan Randall1Chunmei Chen1( )Mesfin Belayneh Ageze2,3Muluken Temesgen Tigabu4
College of Automation, Qingdao University, Qingdao, 266071, China
Center for Renewable Energy, Addis Ababa Institute of Technology, Addis Ababa University, Addis Ababa, 1000, Ethiopia
BTeQ R&D Labs, Addis Ababa, 1000, Ethiopia
Bahir Dar Energy Center, Bahir Dar Institute of Technology, Bahir Dar University, Bahir Dar, 6000, Ethiopia
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Abstract

Vertical Axis Wind Turbines (VAWTs) offer several advantages over horizontal axis wind turbines (HAWTs), including quieter operation, ease of maintenance, and simplified construction. Surprisingly, despite the prevailing belief that HAWTs outperform VAWTs as individual units, VAWTs demonstrate higher power density when arranged in clusters. This phenomenon arises from positive wake interactions downstream of VAWTs, potentially enhancing the overall wind farm performances. In contrast, wake interactions negatively impact HAWT farms, reducing their efficiency. This paper extensively reviews the potential of VAWT clusters to increase energy output and reduce wind energy costs. A precise terminology is introduced to clarify ambiguous terms researchers use to quantify cluster parameters. While examining commonly studied and proposed VAWT cluster configurations, several aspects are discussed such as aerodynamic interactions, wake characteristics, structural dynamics, and performance metrics. Additionally, the current state-of-the-art and research gaps are critically described. The review also covers computational modeling, optimization techniques, advanced control strategies, machine learning applications, economic considerations, and the influence of terrain and application locations.

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Fluid Dynamics & Materials Processing
Pages 2657-2691

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Cite this article:
Randall R, Chen C, Ageze MB, et al. Perspectives of Vertical Axis Wind Turbines in Cluster Configurations. Fluid Dynamics & Materials Processing, 2024, 20(12): 2657-2691. https://doi.org/10.32604/fdmp.2024.058169

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Received: 06 September 2024
Accepted: 19 November 2024
Published: 31 December 2024
© The Author 2024.

This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.