Maximization of the annual energy production of wind power plants by optimization of layout and yaw‐based wake control

This paper presents a wind plant modeling and optimization tool that enables the maximization of wind plant annual energy production (AEP) using yaw-based wake steering control and layout changes. The tool is an extension of a wake engineering model describing the steady-state effects of yaw on wake velocity profiles and power productions of wind turbines in a wind plant. To make predictions of a wind plant's AEP, necessary extensions of the original wake model include coupling it with a detailed rotor model and a control policy for turbine blade pitch and rotor speed. This enables the prediction of power production with wake effects throughout a range of wind speeds. We use the tool to perform an example optimization study on a wind plant based on the Princess Amalia Wind Park. In this case study, combined optimization of layout and wake steering control increases AEP by 5%. The power gains from wake steering control are highest for region 1.5 inflow wind speeds, and they continue to be present to some extent for the above-rated inflow wind speeds. The results show that layout optimization and wake steering are complementary because significant AEP improvements can be achieved with wake steering in a wind plant layout that is already optimized to reduce wake losses. Copyright © 2016 John Wiley & Sons, Ltd.

[1]  Douglas DeVoto.  Performance and Reliability of Bonded Interfaces for High-Temperature Packaging; NREL (National Renewable Energy Laboratory) , 2015 .

[2]  Krystel K. Castillo-Villar,et al.  A Review of Methodological Approaches for the Design and Optimization of Wind Farms , 2014 .

[3]  Yingchen Zhang,et al.  Computational fluid dynamics simulation study of active power control in wind plants , 2016, 2016 American Control Conference (ACC).

[4]  E. Migoya,et al.  Application of a LES technique to characterize the wake deflection of a wind turbine in yaw , 2009 .

[5]  Joaquim R. R. A. Martins,et al.  Extensions to the design structure matrix for the description of multidisciplinary design, analysis, and optimization processes , 2012, Structural and Multidisciplinary Optimization.

[6]  J. Jonkman,et al.  Definition of a 5-MW Reference Wind Turbine for Offshore System Development , 2009 .

[7]  Jason R. Marden,et al.  Wind plant power optimization through yaw control using a parametric model for wake effects—a CFD simulation study , 2016 .

[8]  Andrew Ning,et al.  Comparison of two wake models for use in gradient-based wind farm layout optimization , 2015, 2015 IEEE Conference on Technologies for Sustainability (SusTech).

[9]  J. W. Wagenaar,et al.  Database of measurements on the offshore wind farm Egmond aan Zee , 2012 .

[10]  Laurent Hascoët,et al.  The Tapenade automatic differentiation tool: Principles, model, and specification , 2013, TOMS.

[11]  Thomas Bak,et al.  Survey of wind farm control - power and fatigue optimization , 2015 .

[12]  Jan-Willem van Wingerden,et al.  Comparison of actuation methods for wake control in wind plants , 2015, 2015 American Control Conference (ACC).

[13]  Michael A. Saunders,et al.  SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization , 2002, SIAM J. Optim..

[14]  M Maarten Steinbuch,et al.  Optimal control of wind power plants , 1988 .

[15]  Andrew Ning,et al.  Wind plant system engineering through optimization of layout and yaw control , 2016 .

[16]  N. Jensen.  A note on wind generator interaction , 1983 .