Low-order modeling of wind farm aerodynamics using leaky Rankine bodies
Author(s) -
Daniel Araya,
Anna Craig,
Matthias Kinzel,
John O. Dabiri
Publication year - 2014
Publication title -
journal of renewable and sustainable energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.475
H-Index - 43
ISSN - 1941-7012
DOI - 10.1063/1.4905127
Subject(s) - streamlines, streaklines, and pathlines , wake , turbine , aerodynamics , degree rankine , mechanics , vertical axis wind turbine , computational fluid dynamics , potential flow , heat sink , flow (mathematics) , engineering , physics , aerospace engineering , mechanical engineering , process engineering
We develop and characterize a low-order model of the mean flow through an array of vertical-axis wind turbines (VAWTs), consisting of a uniform flow and pairs of potential sources and sinks to represent each VAWT. The source and sink in each pair are of unequal strength, thereby forming a “leaky Rankine body” (LRB). In contrast to a classical Rankine body, which forms closed streamlines around a bluff body in potential flow, the LRB streamlines have a qualitatively similar appearance to a separated bluff body wake; hence, the LRB concept is used presently to model the VAWT wake. The relative strengths of the source and sink are determined from first principles analysis of an actuator disk model of the VAWTs. The LRB model is compared with field measurements of various VAWT array configurations measured over a 3-yr campaign. It is found that the LRB model correctly predicts the ranking of array performances to within statistical certainty. Furthermore, by using the LRB model to predict the flow around two-turbine and three-turbine arrays, we show that there are two competing fluid dynamic mechanisms that contribute to the overall array performance: turbine blockage, which locally accelerates the flow; and turbine wake formation, which locally decelerates the flow as energy is extracted. A key advantage of the LRB model is that optimal turbine array configurations can be found with significantly less computational expense than higher fidelity numerical simulations of the flow and much more rapidly than in experiments.
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