Optimization Under Uncertainty for Wake Steering Strategies

Quick, Julian; Annoni, Jennifer; King, Ryan N.; Dykes, Katherine L.; Fleming, Paul A.; Ning, Andrew

doi:10.1088/1742-6596/854/1/012036

Optimization Under Uncertainty for Wake Steering Strategies

Journal Article · Tue Jun 13 00:00:00 EDT 2017 · Journal of Physics. Conference Series

DOI:https://doi.org/10.1088/1742-6596/854/1/012036· OSTI ID:1373674

Quick, Julian ^[1]; Annoni, Jennifer ^[1]; King, Ryan N. ^[1]; Dykes, Katherine L. ^[1]; Fleming, Paul A. ^[1]; Ning, Andrew ^[2]

National Renewable Energy Lab. (NREL), Golden, CO (United States)
Brigham Young Univ., Provo, UT (United States)

Here, wind turbines in a wind power plant experience significant power losses because of aerodynamic interactions between turbines. One control strategy to reduce these losses is known as 'wake steering,' in which upstream turbines are yawed to direct wakes away from downstream turbines. Previous wake steering research has assumed perfect information, however, there can be significant uncertainty in many aspects of the problem, including wind inflow and various turbine measurements. Uncertainty has significant implications for performance of wake steering strategies. Consequently, the authors formulate and solve an optimization under uncertainty (OUU) problem for finding optimal wake steering strategies in the presence of yaw angle uncertainty. The OUU wake steering strategy is demonstrated on a two-turbine test case and on the utility-scale, offshore Princess Amalia Wind Farm. When we accounted for yaw angle uncertainty in the Princess Amalia Wind Farm case, inflow-direction-specific OUU solutions produced between 0% and 1.4% more power than the deterministically optimized steering strategies, resulting in an overall annual average improvement of 0.2%. More importantly, the deterministic optimization is expected to perform worse and with more downside risk than the OUU result when realistic uncertainty is taken into account. Additionally, the OUU solution produces fewer extreme yaw situations than the deterministic solution.

Research Organization:: National Renewable Energy Lab. (NREL), Golden, CO (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)

Grant/Contract Number:: AC36-08GO28308

OSTI ID:: 1373674

Alternate ID(s):: OSTI ID: 1357097
OSTI ID: 1374526
OSTI ID: 1374530

Report Number(s):: NREL/JA--5000-68984

Journal Information:: Journal of Physics. Conference Series, Journal Name: Journal of Physics. Conference Series Vol. 854; ISSN 1742-6588

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: United States

Language:: English

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Active Subspaces for Wind Plant Surrogate Modeling King, Ryan; Quick, Julian; Adcock, Christiane 2018 Wind Energy Symposium https://doi.org/10.2514/6.2018-2019	conference	January 2018
Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization Munters, Wim; Meyers, Johan Energies, Vol. 11, Issue 1, p. 177 https://doi.org/10.3390/en11010177	journal	January 2018
A Study on the Effect of Closed-Loop Wind Farm Control on Power and Tower Load in Derating the TSO Command Condition Kim, Hyungyu; Kim, Kwansu; Paek, Insu Energies, Vol. 12, Issue 10 https://doi.org/10.3390/en12102004	journal	May 2019
Detection of wakes in the inflow of turbines using nacelle lidars Held, Dominique P.; Mann, Jakob Wind Energy Science Discussions https://doi.org/10.5194/wes-2018-78	posted_content	January 2019
Robust active wake control in consideration of wind direction variability and uncertainty Rott, Andreas; Doekemeijer, Bart; Seifert, Janna Kristina Wind Energy Science, Vol. 3, Issue 2 https://doi.org/10.5194/wes-3-869-2018	journal	January 2018
Detection of wakes in the inflow of turbines using nacelle lidars Held, Dominique P.; Mann, Jakob Wind Energy Science, Vol. 4, Issue 3 https://doi.org/10.5194/wes-4-407-2019	journal	January 2019
Robust active wake control in consideration of wind direction variability and uncertainty Rott, Andreas; Doekemeijer, Bart; Seifert, Janna Kristina Zenodo https://doi.org/10.5281/zenodo.2556506	text	January 2018

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