Analysis of design parameters of large-sized wind turbines by non-dimensional model
Armando Lúcio Ramos de Medeiros,
Alex Maurício Araújo,
Oyama Douglas Queiroz de Oliveira Filho,
Janardan Rohatgi and
Maurílio José dos Santos
Energy, 2015, vol. 93, issue P1, 1146-1154
Abstract:
This paper presents a simplified non-dimensional model to estimate capacity factor for megawatt-sized VSVP (variable speed variable pitch) wind turbines. Instead of cut-in (Vin), rated (Vr) and cut-out (Vout) speeds of a wind turbine a non-dimensional speed parameter (x) defined as the ratio of the wind speed to the mean wind speed (Vm) is employed. Then the non-dimensional speed parameters become: xin (=Vin/Vm), xr (=Vr/Vm), and xout (=Vout/Vm). The wind speed distribution is characterized by Weibull shape parameter k. It is shown that the CF (capacity factor) depends only on k and Vr. In this way the model is independent of the mean wind speed of the site. However, these simplifications does introduce small error in the estimation of the capacity factor, but of little significance. The model shows three important points: 1) There is an optimum relation between xr and k represented by a six-degree polynomial indicating optimum value of the CF. This implies that the design parameters of a wind turbine should be selected on the basis of k; 2) The capacity factor increases with the decreasing value of the xr. This decrease in xr can either be achieved by increasing Vm or by decreasing Vr.
Keywords: Megawatt-sized wind turbines; Weibull shape parameter; Non-dimensional rated wind speed; Capacity factor (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544215013419
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:energy:v:93:y:2015:i:p1:p:1146-1154
DOI: 10.1016/j.energy.2015.09.118
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().