Abstract. Using adjoint optimization and three-dimensional steady-state Reynolds-averaged Navier–Stokes (RANS) simulations, we present a new gradient-based approach for optimally siting wind turbines within utility-scale wind plants. By solving the adjoint equations of the flow model, the gradients needed for optimization are found at a cost that is independent of the number of control variables, thereby permitting optimization of large wind plants with many turbine locations. Moreover, compared to the common approach of superimposing prescribed wake deficits onto linearized flow models, the computational efficiency of the adjoint approach allows the use of higher-fidelity RANS flow models which can capture nonlinear turbulent flow physics within a wind plant. The steady-state RANS flow model is implemented in the Python finite-element package FEniCS and the derivation and solution of the discrete adjoint equations are automated within the dolfin-adjoint framework. Gradient-based optimization of wind turbine locations is demonstrated for idealized test cases that reveal new optimization heuristics such as rotational symmetry, local speedups, and nonlinear wake curvature effects. Layout optimization is also demonstrated on more complex wind rose shapes, including a full annual energy production (AEP) layout optimization over 36 inflow directions and 5 wind speed bins.
King, Ryan N., et al. "Optimization of wind plant layouts using an adjoint approach." Wind Energy Science (Online), vol. 2, no. 1, Mar. 2017. https://doi.org/10.5194/wes-2-115-2017
King, Ryan N., Dykes, Katherine, Graf, Peter, & Hamlington, Peter E. (2017). Optimization of wind plant layouts using an adjoint approach. Wind Energy Science (Online), 2(1). https://doi.org/10.5194/wes-2-115-2017
King, Ryan N., Dykes, Katherine, Graf, Peter, et al., "Optimization of wind plant layouts using an adjoint approach," Wind Energy Science (Online) 2, no. 1 (2017), https://doi.org/10.5194/wes-2-115-2017
@article{osti_1346445,
author = {King, Ryan N. and Dykes, Katherine and Graf, Peter and Hamlington, Peter E.},
title = {Optimization of wind plant layouts using an adjoint approach},
annote = {Abstract. Using adjoint optimization and three-dimensional steady-state Reynolds-averaged Navier–Stokes (RANS) simulations, we present a new gradient-based approach for optimally siting wind turbines within utility-scale wind plants. By solving the adjoint equations of the flow model, the gradients needed for optimization are found at a cost that is independent of the number of control variables, thereby permitting optimization of large wind plants with many turbine locations. Moreover, compared to the common approach of superimposing prescribed wake deficits onto linearized flow models, the computational efficiency of the adjoint approach allows the use of higher-fidelity RANS flow models which can capture nonlinear turbulent flow physics within a wind plant. The steady-state RANS flow model is implemented in the Python finite-element package FEniCS and the derivation and solution of the discrete adjoint equations are automated within the dolfin-adjoint framework. Gradient-based optimization of wind turbine locations is demonstrated for idealized test cases that reveal new optimization heuristics such as rotational symmetry, local speedups, and nonlinear wake curvature effects. Layout optimization is also demonstrated on more complex wind rose shapes, including a full annual energy production (AEP) layout optimization over 36 inflow directions and 5 wind speed bins.},
doi = {10.5194/wes-2-115-2017},
url = {https://www.osti.gov/biblio/1346445},
journal = {Wind Energy Science (Online)},
issn = {ISSN 2366-7451},
number = {1},
volume = {2},
place = {Germany},
publisher = {European Wind Energy Association - Copernicus},
year = {2017},
month = {03}}
ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Volume 3: 38th Design Automation Conference, Parts A and Bhttps://doi.org/10.1115/DETC2012-71478