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]

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1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
2. 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 Laboratory (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
• Report Number(s): NREL/JA-5000-68984
• Journal Information: Journal of Physics. Conference Series, Vol. 854; ISSN 1742-6588
• Publisher: IOP Publishing
• Country of Publication: United States
• Language: English

Related Subjects

17 WIND ENERGY
wake steering
wind energy
optimization under uncertainty
yaw
control