The Effect of Non-Uniform Velocity Distribution on the Performance of Tethered Coaxial Turbines
POSTER
Abstract
Tethered, coaxial, counter-rotating turbines offer the advantage of operating in zero net-torque mode, thereby avoiding tether twisting and entanglements. Low-order models of coaxial turbines operating under realistic conditions are required to estimate turbine performance, levelized cost of energy and to design optimization strategies for farm layouts. When operating in ocean currents, coaxial turbines may experience non-uniform velocity conditions from two sources, namely velocity shear present in the ambient flow and shear associated with the turbulent wake from an upstream turbine in a farm configuration. The assertion of a turbine experiencing background shear due to the ambient flow is reinforced by acoustic doppler current profiler data presented in [1]. We have performed high-resolution LES simulations aimed at developing insights into the evolution of the wake from a tethered turbine operating over a range of shear conditions. Our simulations reveal that when the wake parameters are scaled by the local inlet velocity, the turbine wake exhibits a self-similar behavior, approximated by a Gaussian function. By varying the magnitude of the shear gradient, we are able to establish a relationship between the turbine wake growth rate and the shear magnitude. Our simulations of coaxial, counter-rotating turbines show background shear enhances turbine wake vortices, leading to faster wake recovery and higher growth rate. The faster wake recovery will mean increased power performance of downstream turbines, informing optimization strategies for the turbine farm. Future work will focus on developing a low-order modification for the BEMT model introduced in [2] for coaxial turbine performance at different shear strengths.
References:
[1] M. Muglia, H. Seim, P. Taylor, Mar. Technol. Soc. J., 54 (6), 24-36, (2020).
[2] L. Chamorro et al., Wind Energy, vol. 16, no. 2, pp. 279–282 (2012).
References:
[1] M. Muglia, H. Seim, P. Taylor, Mar. Technol. Soc. J., 54 (6), 24-36, (2020).
[2] L. Chamorro et al., Wind Energy, vol. 16, no. 2, pp. 279–282 (2012).
Presenters
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Carson Ramm
University of North Carolina at Charlotte
Authors
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Carson Ramm
University of North Carolina at Charlotte
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Praveen K Ramaprabhu
University of North Carolina at Charlotte
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Kenneth Granlund
North Carolina State University
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Matthew Bryant
North Carolina State University
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Andre Mazzoleni
North Carolina State University