Effectively using multifidelity optimization for wind turbine design
-
Published:2022-05-11
Issue:3
Volume:7
Page:991-1006
-
ISSN:2366-7451
-
Container-title:Wind Energy Science
-
language:en
-
Short-container-title:Wind Energ. Sci.
Author:
Jasa JohnORCID, Bortolotti PietroORCID, Zalkind Daniel, Barter GarrettORCID
Abstract
Abstract. Wind turbines are complex multidisciplinary systems that are challenging to design because of the tightly coupled interactions between different subsystems. Computational modeling attempts to resolve these couplings so we can efficiently explore new wind turbine systems early in the design process. Low-fidelity models are computationally efficient but make assumptions and simplifications that limit the accuracy of design studies, whereas high-fidelity models capture more of the actual physics but with increased computational cost. This paper details the use of multifidelity methods for optimizing wind turbine designs by using information from both low- and high-fidelity models to find an optimal solution at reduced cost. Specifically, a trust-region approach is used with a novel corrective function built from a nonlinear surrogate model. We find that for a diverse set of design problems – with examples given in rotor blade geometry design, wind turbine controller design, and wind power plant layout optimization – the multifidelity method finds the optimal design using 38 %–58 % of the computational cost of the high-fidelity-only optimization. The success of the multifidelity method in disparate applications suggests that it could be more broadly applied to other wind energy or otherwise generic applications.
Funder
Advanced Research Projects Agency - Energy
Publisher
Copernicus GmbH
Subject
Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment
Reference65 articles.
1. Abbas, N. J., Zalkind, D. S., Pao, L., and Wright, A.: A reference open-source controller for fixed and floating offshore wind turbines, Wind Energ. Sci., 7, 53–73, https://doi.org/10.5194/wes-7-53-2022, 2022. a 2. Abdallah, I., Lataniotis, C., and Sudret, B.: Parametric hierarchical kriging
for multi-fidelity aero-servo-elastic simulators – Application to extreme
loads on wind turbines, Probabil. Eng. Mech., 55, 67–77, 2019. a 3. Alexandrov, N. M., Dennis, J., Lewis, R. M., and Torczon, V.: A trust-region
framework for managing the use of approximation models in optimization,
Struct. Optimiz., 15, 16–23, 1998. a 4. Alexandrov, N. M., Lewis, R. M., Gumbert, C. R., Green, L. L., and Newman, P. A.: Approximation and model management in aerodynamic optimization with
variable-fidelity models, J. Aircraft, 38, 1093–1101, 2001. a 5. Allen, C., Viselli, A., Dagher, H., Goupee, A., Gaertner, E., Abbas, N., Hall, M., and Barter, G.: Definition of the UMaine VolturnUS-S Reference
Platform Developed for the IEA Wind 15-Megawatt Offshore Reference Wind
Turbine, Tech. Rep. NREL/TP-76773, International Energy Agency, https://doi.org/10.2172/1660012, 2020. a
Cited by
9 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|