Pitch angle control for a small-scale Darrieus vertical axis wind turbine with straight blades (H-Type VAWT)

Gebreel Abdalrahman, William Melek and Fue-Sang Lien

Renewable Energy, 2017, vol. 114, issue PB, 1353-1362

Abstract: Unlike horizontal axis wind turbines (HAWTs), the Darrieus vertical axis wind turbine (H-type VAWT) has been the subject of only a few recent studies directed at improving its self-starting capability and/or aerodynamic performance. The technique currently used for improving the performance of this type of turbine is pitch angle control. This paper presents intelligent blade pitch control for enhancing the performance of H-type VAWTs with respect to power output. To determine the optimum pitch angles, ANSYS Fluent Computational Fluid Dynamics (CFD) software was used for a study of the aerodynamic performance of a 2D variable pitch angle H-type VAWT at a variety of tip speed ratios (TSRs). For each case examined, the power coefficient (Cp) was calculated and compared to published experimental and CFD findings. The results obtained from the CFD model were then applied for the construction of an aerodynamic model of an H-type VAWT rotor, which constituted a prerequisite for designing an intelligent pitch angle controller using a multilayer perceptron artificial neural network (MLP-ANN) method. The performance of the MLP-ANN blade pitch controller was compared to that of a conventional controller (PID). The findings demonstrate that for an H-type VAWT, compared to a conventional PID controller, an MLP-ANN results in superior power output.

Keywords: Darrieus vertical axis wind turbine (H-type VAWT); Computational fluid dynamics (CFD); Variable pitch angle control; Multilayer perceptron artificial neural network (MLP-ANN) (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148117306961
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:114:y:2017:i:pb:p:1353-1362

DOI: 10.1016/j.renene.2017.07.068

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().