Efficient wind farm layout optimization with the FLOWERS AEP model and analytic gradients

LoCascio, Michael J.; Bay, Christopher J.; Martínez-Tossas, Luis A.; Thomas, Jared J.; Gorlé, Catherine

doi:10.1063/5.0237778

Efficient wind farm layout optimization with the FLOWERS AEP model and analytic gradients

Journal Article · Mon Jan 13 23:00:00 EST 2025 · Journal of Renewable and Sustainable Energy

DOI:https://doi.org/10.1063/5.0237778· OSTI ID:2500407

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Wind farm layout optimization (WFLO) studies often aim to maximize the annual energy production (AEP) of a wind farm by choosing an arrangement of turbines that minimizes wake interactions. One way to reduce the cost of WFLO studies is by using more computationally efficient AEP models. The cost of standard AEP modeling approaches, based on the numerical integration of low-fidelity engineering wake models, scales poorly with the number of simulated discrete wind conditions. A second way to reduce cost when using a gradient-based algorithm is to supply exact gradient information instead of finite-difference estimates. However, analytical functions for the derivatives of AEP with respect to turbine positions are not always available in the conventional modeling approach. FLOWERS is a computationally inexpensive, analytical model for wind farm AEP that is specifically developed for WFLO applications. In this paper, we analyze the performance of the FLOWERS AEP model with analytic gradients in a layout optimization study compared with a reference optimization framework across three wind farm case studies. We find that the FLOWERS-based approach reduces computation time by a factor of 50–4000 and improves optimal AEP by about 0.3% with less than half of the variability in AEP across instances with randomized initial conditions. We also find the optimal layouts to be insensitive to model parameter tuning, making FLOWERS-based layout optimization a streamlined, user-friendly approach.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: NONE; AC36-08GO28308

OSTI ID:: 2500407

Alternate ID(s):: OSTI ID: 2530902

Journal Information:: Journal of Renewable and Sustainable Energy, Journal Name: Journal of Renewable and Sustainable Energy Journal Issue: 1 Vol. 17; ISSN 1941-7012

Publisher:: American Institute of PhysicsCopyright Statement

Country of Publication:: United States

Language:: English

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FLOWERS AEP: An Analytical Model for Wind Farm Layout Optimization

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