Keywords

vertical axis wind turbine, VAWT, wake model, wind farm optimization, computational fluid dynamics, reduced order model

Abstract

Analyzing or optimizing wind farm layouts often requires reduced-order wake models to estimate turbine wake interactions and wind velocity. We propose a wake model for vertical-axis wind turbines (VAWTs) in streamwise and crosswind directions. Using vorticity data from computational fluid dynamic (CFD) simulations and cross-validated Gaussian distribution fitting, we produced a wake model that can estimate normalized wake velocity deficits of an isolated VAWT using normalized downstream and lateral positions, tip-speed ratio, and solidity. Compared to CFD, taking over a day to run one simulation, our wake model predicts a velocity deficit in under a second with an appropriate accuracy and computational cost necessary for wind farm optimization. The model agreed with two experimental studies producing percent differences of the maximum wake deficit of 6.3% and 14.6%. The wake model includes multiple wake interactions and blade aerodynamics to calculate power, allowing its use in wind farm layout analysis and optimization.

Original Publication Citation

Tingey, E., and Ning, A., “Development of a Parameterized Reduced-Order Vertical-Axis Wind Turbine Wake Model,” Wind Engineering, Jun. 2019. doi:10.1177/0309524X19849864

Document Type

Peer-Reviewed Article

Publication Date

2019-6

Publisher

Sage

Language

English

College

Ira A. Fulton College of Engineering and Technology

Department

Mechanical Engineering

University Standing at Time of Publication

Assistant Professor

Included in

Engineering Commons

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