Articles | Volume 5, issue 1
https://doi.org/10.5194/wes-5-413-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-5-413-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Mar 2020
Research article |
| 30 Mar 2020
| 30 Mar 2020
Wake steering optimization under uncertainty
University of Colorado, Boulder, CO, USA
National Renewable Energy Laboratory, Golden, CO, USA
Jennifer King
National Renewable Energy Laboratory, Golden, CO, USA
Ryan N. King
National Renewable Energy Laboratory, Golden, CO, USA
Peter E. Hamlington
University of Colorado, Boulder, CO, USA
Katherine Dykes
National Renewable Energy Laboratory, Golden, CO, USA
Related authors
Andrew Clifton, Sarah Barber, Andrew Bray, Peter Enevoldsen, Jason Fields, Anna Maria Sempreviva, Lindy Williams, Julian Quick, Mike Purdue, Philip Totaro, and Yu Ding
Wind Energ. Sci., 8, 947–974, https://doi.org/10.5194/wes-8-947-2023, https://doi.org/10.5194/wes-8-947-2023, 2023
Short summary
Short summary
Wind energy creates huge amounts of data, which can be used to improve plant design, raise efficiency, reduce operating costs, and ease integration. These all contribute to cheaper and more predictable energy from wind. But realising the value of data requires a digital transformation that brings
grand challengesaround data, culture, and coopetition. This paper describes how the wind energy industry could work with R&D organisations, funding agencies, and others to overcome them.
Julian Quick, Ryan N. King, Garrett Barter, and Peter E. Hamlington
Wind Energ. Sci., 7, 1941–1955, https://doi.org/10.5194/wes-7-1941-2022, https://doi.org/10.5194/wes-7-1941-2022, 2022
Short summary
Short summary
Wake steering is an emerging wind power plant control strategy where upstream turbines are intentionally yawed out of alignment with the incoming wind, thereby steering wakes away from downstream turbines. Trade-offs between the gains in power production and fatigue loads induced by this control strategy are the subject of continuing investigation. In this study, we present an optimization approach for efficiently exploring the trade-offs between power and loading during wake steering.
Shadan Mozafari, Paul Veers, Jennifer Rinker, and Katherine Dykes
Wind Energ. Sci., 9, 799–820, https://doi.org/10.5194/wes-9-799-2024, https://doi.org/10.5194/wes-9-799-2024, 2024
Short summary
Short summary
Turbulence is one of the main drivers of fatigue in wind turbines. There is some debate on how to model the turbulence in normal wind conditions in the design phase. To address such debates, we study the fatigue load distribution and reliability following different models of the International Electrotechnical Commission 61400-1 standard. The results show the lesser importance of load uncertainty due to turbulence distribution compared to the uncertainty of material resistance and Miner’s rule.
Amalia Ida Hietanen, Thor Heine Snedker, Katherine Dykes, and Ilmas Bayati
Wind Energ. Sci., 9, 417–438, https://doi.org/10.5194/wes-9-417-2024, https://doi.org/10.5194/wes-9-417-2024, 2024
Short summary
Short summary
The layout of a floating offshore wind farm was optimized to maximize the relative net present value (NPV). By modeling power generation, losses, inter-array cables, anchors and operational costs, an increase of EUR 34.5 million in relative NPV compared to grid-based layouts was achieved. A sensitivity analysis was conducted to examine the impact of economic factors, providing valuable insights. This study contributes to enhancing the efficiency and cost-effectiveness of floating wind farms.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
Short summary
Short summary
Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Lena Kitzing, David Rudolph, Sophie Nyborg, Helena Solman, Tom Cronin, Gundula Hübner, Elizabeth Gill, Katherine Dykes, Suzanne Tegen, and Julia Kirch Kirkegaard
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2023-174, https://doi.org/10.5194/wes-2023-174, 2024
Manuscript not accepted for further review
Short summary
Short summary
Social aspects are gaining traction in wind energy. A recent publication by Kirkegaard et al. lays out social grand challenges. We discuss them for a more technologically focused audience. We describe the role of social sciences in wind energy research, showing insights, topics, and value-added for public engagement and planning, just ownership and value-based design. We reflect how social and technical sciences can jointly advance wind energy research into a new interdisciplinary era.
Mark O’Malley, Hannele Holttinen, Nicolaos Cutululis, Til Kristian Vrana, Jennifer King, Vahan Gevorgian, Xiongfei Wang, Fatemeh Rajaei-Najafabadi, and Andreas Hadjileonidas
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2023-179, https://doi.org/10.5194/wes-2023-179, 2024
Preprint under review for WES
Short summary
Short summary
The rising share of wind power poses challenges to cost-effective integration while ensuring reliability. Balancing the needs and contributions of wind power is crucial for long-term value. Research should prioritize its advantages over competitors, focusing on internal challenges like control and coordination. Collaboration with other technologies is essential for addressing fundamental objectives of power systems—maintaining reliable supply-demand balance at least cost.
Maaike Sickler, Bart Ummels, Michiel Zaaijer, Roland Schmehl, and Katherine Dykes
Wind Energ. Sci., 8, 1225–1233, https://doi.org/10.5194/wes-8-1225-2023, https://doi.org/10.5194/wes-8-1225-2023, 2023
Short summary
Short summary
This paper investigates the effect of wind farm layout on the performance of offshore wind farms. A regular farm layout is compared to optimised irregular layouts. The irregular layouts have higher annual energy production, and the power production is less sensitive to wind direction. However, turbine towers require thicker walls to counteract increased fatigue due to increased turbulence levels in the farm. The study shows that layout optimisation can be used to maintain high-yield performance.
Andrew Clifton, Sarah Barber, Andrew Bray, Peter Enevoldsen, Jason Fields, Anna Maria Sempreviva, Lindy Williams, Julian Quick, Mike Purdue, Philip Totaro, and Yu Ding
Wind Energ. Sci., 8, 947–974, https://doi.org/10.5194/wes-8-947-2023, https://doi.org/10.5194/wes-8-947-2023, 2023
Short summary
Short summary
Wind energy creates huge amounts of data, which can be used to improve plant design, raise efficiency, reduce operating costs, and ease integration. These all contribute to cheaper and more predictable energy from wind. But realising the value of data requires a digital transformation that brings
grand challengesaround data, culture, and coopetition. This paper describes how the wind energy industry could work with R&D organisations, funding agencies, and others to overcome them.
Christopher J. Bay, Paul Fleming, Bart Doekemeijer, Jennifer King, Matt Churchfield, and Rafael Mudafort
Wind Energ. Sci., 8, 401–419, https://doi.org/10.5194/wes-8-401-2023, https://doi.org/10.5194/wes-8-401-2023, 2023
Short summary
Short summary
This paper introduces the cumulative-curl wake model that allows for the fast and accurate prediction of wind farm energy production wake interactions. The cumulative-curl model expands several existing wake models to make the simulation of farms more accurate and is implemented in a computationally efficient manner such that it can be used for wind farm layout design and controller development. The model is validated against high-fidelity simulations and data from physical wind farms.
Paul Veers, Katherine Dykes, Sukanta Basu, Alessandro Bianchini, Andrew Clifton, Peter Green, Hannele Holttinen, Lena Kitzing, Branko Kosovic, Julie K. Lundquist, Johan Meyers, Mark O'Malley, William J. Shaw, and Bethany Straw
Wind Energ. Sci., 7, 2491–2496, https://doi.org/10.5194/wes-7-2491-2022, https://doi.org/10.5194/wes-7-2491-2022, 2022
Short summary
Short summary
Wind energy will play a central role in the transition of our energy system to a carbon-free future. However, many underlying scientific issues remain to be resolved before wind can be deployed in the locations and applications needed for such large-scale ambitions. The Grand Challenges are the gaps in the science left behind during the rapid growth of wind energy. This article explains the breadth of the unfinished business and introduces 10 articles that detail the research needs.
Johan Meyers, Carlo Bottasso, Katherine Dykes, Paul Fleming, Pieter Gebraad, Gregor Giebel, Tuhfe Göçmen, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 2271–2306, https://doi.org/10.5194/wes-7-2271-2022, https://doi.org/10.5194/wes-7-2271-2022, 2022
Short summary
Short summary
We provide a comprehensive overview of the state of the art and the outstanding challenges in wind farm flow control, thus identifying the key research areas that could further enable commercial uptake and success. To this end, we have structured the discussion on challenges and opportunities into four main areas: (1) insight into control flow physics, (2) algorithms and AI, (3) validation and industry implementation, and (4) integrating control with system design
(co-design).
Julian Quick, Ryan N. King, Garrett Barter, and Peter E. Hamlington
Wind Energ. Sci., 7, 1941–1955, https://doi.org/10.5194/wes-7-1941-2022, https://doi.org/10.5194/wes-7-1941-2022, 2022
Short summary
Short summary
Wake steering is an emerging wind power plant control strategy where upstream turbines are intentionally yawed out of alignment with the incoming wind, thereby steering wakes away from downstream turbines. Trade-offs between the gains in power production and fatigue loads induced by this control strategy are the subject of continuing investigation. In this study, we present an optimization approach for efficiently exploring the trade-offs between power and loading during wake steering.
Charles Tripp, Darice Guittet, Jennifer King, and Aaron Barker
Wind Energ. Sci., 7, 697–713, https://doi.org/10.5194/wes-7-697-2022, https://doi.org/10.5194/wes-7-697-2022, 2022
Short summary
Short summary
Hybrid solar and wind plant layout optimization is a difficult, complex problem. In this paper, we propose a parameterized approach to wind and solar hybrid power plant layout optimization that greatly reduces problem dimensionality while guaranteeing that the generated layouts have a desirable regular structure. We demonstrate that this layout method that generates high-performance, regular layouts which respect hard constraints (e.g., placement restrictions).
Andrew P. J. Stanley, Jennifer King, Christopher Bay, and Andrew Ning
Wind Energ. Sci., 7, 433–454, https://doi.org/10.5194/wes-7-433-2022, https://doi.org/10.5194/wes-7-433-2022, 2022
Short summary
Short summary
In this paper, we present a computationally inexpensive model to calculate wind turbine blade fatigue caused by waking and partial waking. The model accounts for steady state on the blade, as well as wind turbulence. The model is fast enough to be used in wind farm layout optimization, which has not been possible with more expensive fatigue models in the past. The methods introduced in this paper will allow for farms with increased energy production that maintain turbine structural reliability.
Ethan Young, Jeffery Allen, John Jasa, Garrett Barter, and Ryan King
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2022-7, https://doi.org/10.5194/wes-2022-7, 2022
Preprint withdrawn
Short summary
Short summary
In this study, we present ways to measure the phenomenon of wind plant blockage, or the the velocity slowdown upstream from a farm, and carry out turbine layout optimizations to reduce this effect. We find that farm-wide measurements provide a better characterization of blockage compared to more localized measurements and that, in the absence of any constraint on total power output, layouts which minimize the effect of blockage are frequently characterized by streamwise alignment of turbines.
Paul Fleming, Michael Sinner, Tom Young, Marine Lannic, Jennifer King, Eric Simley, and Bart Doekemeijer
Wind Energ. Sci., 6, 1521–1531, https://doi.org/10.5194/wes-6-1521-2021, https://doi.org/10.5194/wes-6-1521-2021, 2021
Short summary
Short summary
The paper presents a new validation campaign of wake steering at a commercial wind farm. The campaign uses fixed yaw offset positions, rather than a table of optimal yaw offsets dependent on wind direction, to enable comparison with engineering models of wake steering. Additionally, by applying the same offset in beneficial and detrimental conditions, we are able to collect important data for assessing second-order wake model predictions.
Andrew P. J. Stanley, Owen Roberts, Jennifer King, and Christopher J. Bay
Wind Energ. Sci., 6, 1143–1167, https://doi.org/10.5194/wes-6-1143-2021, https://doi.org/10.5194/wes-6-1143-2021, 2021
Short summary
Short summary
Wind farm layout optimization is an essential part of wind farm design. In this paper, we present different methods to determine the number of turbines in a wind farm, as well as their placement. Also in this paper we explore the effect that the objective function has on the wind farm design and found that wind farm layout is highly sensitive to the objective. The optimal number of turbines can vary greatly, from 15 to 54 for the cases in this paper, depending on the metric that is optimized.
Alayna Farrell, Jennifer King, Caroline Draxl, Rafael Mudafort, Nicholas Hamilton, Christopher J. Bay, Paul Fleming, and Eric Simley
Wind Energ. Sci., 6, 737–758, https://doi.org/10.5194/wes-6-737-2021, https://doi.org/10.5194/wes-6-737-2021, 2021
Short summary
Short summary
Most current wind turbine wake models struggle to accurately simulate spatially variant wind conditions at a low computational cost. In this paper, we present an adaptation of NREL's FLOw Redirection and Induction in Steady State (FLORIS) wake model, which calculates wake losses in a heterogeneous flow field using local weather measurement inputs. Two validation studies are presented where the adapted model consistently outperforms previous versions of FLORIS that simulated uniform flow only.
Jennifer King, Paul Fleming, Ryan King, Luis A. Martínez-Tossas, Christopher J. Bay, Rafael Mudafort, and Eric Simley
Wind Energ. Sci., 6, 701–714, https://doi.org/10.5194/wes-6-701-2021, https://doi.org/10.5194/wes-6-701-2021, 2021
Short summary
Short summary
This paper highlights the secondary effects of wake steering, including yaw-added wake recovery and secondary steering. These effects enhance the value of wake steering especially when applied to a large wind farm. This paper models these secondary effects using an analytical model proposed in the paper. The results of this model are compared with large-eddy simulations for several cases including 2-turbine, 3-turbine, 5-turbine, and 38-turbine cases.
Katherine M. Smith, Skyler Kern, Peter E. Hamlington, Marco Zavatarelli, Nadia Pinardi, Emily F. Klee, and Kyle E. Niemeyer
Geosci. Model Dev., 14, 2419–2442, https://doi.org/10.5194/gmd-14-2419-2021, https://doi.org/10.5194/gmd-14-2419-2021, 2021
Short summary
Short summary
We present a newly developed reduced-order biogeochemical flux model that is complex and flexible enough to capture open-ocean ecosystem dynamics but reduced enough to incorporate into highly resolved numerical simulations with limited additional computational cost. The model provides improved correlations between model output and field data, indicating that significant improvements in the reproduction of real-world data can be achieved with a small number of variables.
Luis A. Martínez-Tossas, Jennifer King, Eliot Quon, Christopher J. Bay, Rafael Mudafort, Nicholas Hamilton, Michael F. Howland, and Paul A. Fleming
Wind Energ. Sci., 6, 555–570, https://doi.org/10.5194/wes-6-555-2021, https://doi.org/10.5194/wes-6-555-2021, 2021
Short summary
Short summary
In this paper a three-dimensional steady-state solver for flow through a wind farm is developed and validated. The computational cost of the solver is on the order of seconds for large wind farms. The model is validated using high-fidelity simulations and SCADA.
Paul Fleming, Jennifer King, Eric Simley, Jason Roadman, Andrew Scholbrock, Patrick Murphy, Julie K. Lundquist, Patrick Moriarty, Katherine Fleming, Jeroen van Dam, Christopher Bay, Rafael Mudafort, David Jager, Jason Skopek, Michael Scott, Brady Ryan, Charles Guernsey, and Dan Brake
Wind Energ. Sci., 5, 945–958, https://doi.org/10.5194/wes-5-945-2020, https://doi.org/10.5194/wes-5-945-2020, 2020
Short summary
Short summary
This paper presents the results of a field campaign investigating the performance of wake steering applied at a section of a commercial wind farm. It is the second phase of the study for which the first phase was reported in a companion paper (https://wes.copernicus.org/articles/4/273/2019/). The authors implemented wake steering on two turbine pairs and compared results with the latest FLORIS model of wake steering, showing good agreement in overall energy increase.
Eric Simley, Paul Fleming, and Jennifer King
Wind Energ. Sci., 5, 451–468, https://doi.org/10.5194/wes-5-451-2020, https://doi.org/10.5194/wes-5-451-2020, 2020
Short summary
Short summary
Wind farm wake losses occur when turbines operate in the wakes of upstream turbines. However, wake steering control can be used to deflect wakes away from downstream turbines. A method for including wind direction variability in wake steering simulations is presented here. Controller performance is shown to improve when wind direction variability is accounted for. Furthermore, the importance of wind direction variability is shown for different turbine spacings and atmospheric conditions.
Jennifer Annoni, Christopher Bay, Kathryn Johnson, Emiliano Dall'Anese, Eliot Quon, Travis Kemper, and Paul Fleming
Wind Energ. Sci., 4, 355–368, https://doi.org/10.5194/wes-4-355-2019, https://doi.org/10.5194/wes-4-355-2019, 2019
Short summary
Short summary
Typically, turbines do not share information with nearby turbines in a wind farm. Relying on a single turbine sensor on the back of a turbine nacelle can lead to large errors in yaw misalignment or excessive yawing due to noisy sensor measurements. The wind farm consensus control approach in this paper shows the benefits of sharing information between nearby turbines by computing a robust estimate of the wind direction using noisy sensor information from these neighboring turbines.
Paul Fleming, Jennifer King, Katherine Dykes, Eric Simley, Jason Roadman, Andrew Scholbrock, Patrick Murphy, Julie K. Lundquist, Patrick Moriarty, Katherine Fleming, Jeroen van Dam, Christopher Bay, Rafael Mudafort, Hector Lopez, Jason Skopek, Michael Scott, Brady Ryan, Charles Guernsey, and Dan Brake
Wind Energ. Sci., 4, 273–285, https://doi.org/10.5194/wes-4-273-2019, https://doi.org/10.5194/wes-4-273-2019, 2019
Short summary
Short summary
Wake steering is a form of wind farm control in which turbines use yaw offsets to affect wakes in order to yield an increase in total energy production. In this first phase of a study of wake steering at a commercial wind farm, two turbines implement a schedule of offsets. For two closely spaced turbines, an approximate 14 % increase in energy was measured on the downstream turbine over a 10° sector, with a 4 % increase in energy production of the combined turbine pair.
Christopher J. Bay, Jennifer King, Paul Fleming, Rafael Mudafort, and Luis A. Martínez-Tossas
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-19, https://doi.org/10.5194/wes-2019-19, 2019
Preprint withdrawn
Short summary
Short summary
This work details a new low-fidelity wake model to be used in determining operational strategies for wind turbines. With the additional physics that this model captures, optimizations have found new control strategies that provide greater increases in performance than previously determined, and these performance increases have been confirmed in high-fidelity simulations. As such, this model can be used in the design and optimization of future wind farms and operational schemes.
Luis A. Martínez-Tossas, Jennifer Annoni, Paul A. Fleming, and Matthew J. Churchfield
Wind Energ. Sci., 4, 127–138, https://doi.org/10.5194/wes-4-127-2019, https://doi.org/10.5194/wes-4-127-2019, 2019
Short summary
Short summary
A new control-oriented model is developed to compute the wake of a wind turbine under yaw. The model uses a simplified version of the Navier–Stokes equation with assumptions. Good agreement is found between the model-proposed and large eddy simulations of a wind turbine in yaw.
Jennifer Annoni, Paul Fleming, Andrew Scholbrock, Jason Roadman, Scott Dana, Christiane Adcock, Fernando Porte-Agel, Steffen Raach, Florian Haizmann, and David Schlipf
Wind Energ. Sci., 3, 819–831, https://doi.org/10.5194/wes-3-819-2018, https://doi.org/10.5194/wes-3-819-2018, 2018
Short summary
Short summary
This paper addresses the modeling aspect of wind farm control. To implement successful wind farm controls, a suitable model has to be used that captures the relevant physics. This paper addresses three different wake models that can be used for controls and compares these models with lidar field data from a utility-scale turbine.
Jan Häfele, Rick R. Damiani, Ryan N. King, Cristian G. Gebhardt, and Raimund Rolfes
Wind Energ. Sci., 3, 553–572, https://doi.org/10.5194/wes-3-553-2018, https://doi.org/10.5194/wes-3-553-2018, 2018
Short summary
Short summary
The present work provides a technical basis for the design of jacket structures used as substructures for offshore wind turbines. This involves models for the geometry, costs, and structural design code checks. An example application is shown in this paper, in which three different structural designs are compared. This work may lead to improved design approaches and finally to a cost reduction of offshore substructures.
Paul Fleming, Jennifer Annoni, Matthew Churchfield, Luis A. Martinez-Tossas, Kenny Gruchalla, Michael Lawson, and Patrick Moriarty
Wind Energ. Sci., 3, 243–255, https://doi.org/10.5194/wes-3-243-2018, https://doi.org/10.5194/wes-3-243-2018, 2018
Short summary
Short summary
This paper investigates the role of flow structures in wind farm control through yaw misalignment. A pair of counter-rotating vortices is shown to be important in deforming the shape of the wake. Further, we demonstrate that the vortex structures created in wake steering can enable a greater change power generation than currently modeled in control-oriented models. We propose that wind farm controllers can be made more effective if designed to take advantage of these effects.
Rick Damiani, Scott Dana, Jennifer Annoni, Paul Fleming, Jason Roadman, Jeroen van Dam, and Katherine Dykes
Wind Energ. Sci., 3, 173–189, https://doi.org/10.5194/wes-3-173-2018, https://doi.org/10.5194/wes-3-173-2018, 2018
Short summary
Short summary
The paper discusses load effects on wind turbines operating under misaligned-flow operations, which is part of a strategy to optimize wind-power-plant power production, where upwind turbines can be rotated off the wind axis to redirect their wakes. Analytical simplification, aeroelastic simulations, and field data from an instrumented turbine are compared and interpreted to provide an informed picture on the loads for various components.
Paul Fleming, Jennifer Annoni, Jigar J. Shah, Linpeng Wang, Shreyas Ananthan, Zhijun Zhang, Kyle Hutchings, Peng Wang, Weiguo Chen, and Lin Chen
Wind Energ. Sci., 2, 229–239, https://doi.org/10.5194/wes-2-229-2017, https://doi.org/10.5194/wes-2-229-2017, 2017
Short summary
Short summary
In this paper, a field test of wake-steering control is presented. In the campaign, an array of turbines within an operating commercial offshore wind farm have the normal yaw controller modified to implement wake steering according to a yaw control strategy. Results indicate that, within the certainty afforded by the data, the wake-steering controller was successful in increasing power capture.
Ryan N. King, Katherine Dykes, Peter Graf, and Peter E. Hamlington
Wind Energ. Sci., 2, 115–131, https://doi.org/10.5194/wes-2-115-2017, https://doi.org/10.5194/wes-2-115-2017, 2017
Short summary
Short summary
This paper demonstrates optimization of wind turbine locations within a utility-scale wind plant using a nonlinear flow model and gradient-based optimization techniques made possible through the use of adjoints. This represents a groundbreaking improvement in model fidelity and optimization efficiency for wind energy applications. The optimized wind farms demonstrate significant improvements in annual energy production with turbine layouts that take advantage of nonlinear flow curvature effects.
Related subject area
Design methods, reliability and uncertainty modelling
Effectively using multifidelity optimization for wind turbine design
Efficient Bayesian calibration of aerodynamic wind turbine models using surrogate modeling
Fast yaw optimization for wind plant wake steering using Boolean yaw angles
A simplified, efficient approach to hybrid wind and solar plant site optimization
Influence of wind turbine design parameters on linearized physics-based models in OpenFAST
Input torque measurements for wind turbine gearboxes using fiber-optic strain sensors
A model to calculate fatigue damage caused by partial waking during wind farm optimization
A fully integrated optimization framework for designing a complex geometry offshore wind turbine spar-type floating support structure
Land-based wind turbines with flexible rail-transportable blades – Part 2: 3D finite element design optimization of the rotor blades
Local-thermal-gradient and large-scale-circulation impacts on turbine-height wind speed forecasting over the Columbia River Basin
Evaluation of the impact of active wake control techniques on ultimate loads for a 10 MW wind turbine
Assessing boundary condition and parametric uncertainty in numerical-weather-prediction-modeled, long-term offshore wind speed through machine learning and analog ensemble
What are the benefits of lidar-assisted control in the design of a wind turbine?
Design procedures and experimental verification of an electro-thermal deicing system for wind turbines
Land-based wind turbines with flexible rail-transportable blades – Part 1: Conceptual design and aeroservoelastic performance
Objective and algorithm considerations when optimizing the number and placement of turbines in a wind power plant
Aeroelastic loads on a 10 MW turbine exposed to extreme events selected from a year-long large-eddy simulation over the North Sea
Optimal scheduling of the next preventive maintenance activity for a wind farm
A method for preliminary rotor design – Part 1: Radially Independent Actuator Disc model
A method for preliminary rotor design – Part 2: Wind turbine Optimization with Radial Independence
Wind farm layout optimization using pseudo-gradients
On the scaling of wind turbine rotors
Reducing cost uncertainty in the drivetrain design decision with a focus on the operational phase
Feature selection techniques for modelling tower fatigue loads of a wind turbine with neural networks
Wind tunnel comparison of four VAWT configurations to test load-limiting concept and CFD validation
Redesign of an upwind rotor for a downwind configuration: design changes and cost evaluation
Fatigue lifetime calculation of wind turbine blade bearings considering blade-dependent load distribution
Reliability analysis of offshore wind turbine foundations under lateral cyclic loading
Operational-based annual energy production uncertainty: are its components actually uncorrelated?
Change-point detection in wind turbine SCADA data for robust condition monitoring with normal behaviour models
Augmented Kalman filter with a reduced mechanical model to estimate tower loads on a land-based wind turbine: a step towards digital-twin simulations
A surrogate model approach for associating wind farm load variations with turbine failures
New strategies for optimized structural monitoring of wind farms: experimental campaign
Differences in damping of edgewise whirl modes operating an upwind turbine in a downwind configuration
Assessment of a rotor blade extension retrofit as a supplement to the lifetime extension of wind turbines
Is the Blade Element Momentum theory overestimating wind turbine loads? – An aeroelastic comparison between OpenFAST's AeroDyn and QBlade's Lifting-Line Free Vortex Wake method
Development and feasibility study of segment blade test methodology
Analytical model for the power–yaw sensitivity of wind turbines operating in full wake
Radar-derived precipitation climatology for wind turbine blade leading edge erosion
WESgraph: a graph database for the wind farm domain
Reliability-based design optimization of offshore wind turbine support structures using analytical sensitivities and factorized uncertainty modeling
Optimal relationship between power and design-driving loads for wind turbine rotors using 1-D models
Digitalization of scanning lidar measurement campaign planning
Massive simplification of the wind farm layout optimization problem
System-level design studies for large rotors
Sensitivity analysis of the effect of wind characteristics and turbine properties on wind turbine loads
Performance of non-intrusive uncertainty quantification in the aeroservoelastic simulation of wind turbines
Polynomial chaos to efficiently compute the annual energy production in wind farm layout optimization
Multipoint high-fidelity CFD-based aerodynamic shape optimization of a 10 MW wind turbine
Comparison between upwind and downwind designs of a 10 MW wind turbine rotor
John Jasa, Pietro Bortolotti, Daniel Zalkind, and Garrett Barter
Wind Energ. Sci., 7, 991–1006, https://doi.org/10.5194/wes-7-991-2022, https://doi.org/10.5194/wes-7-991-2022, 2022
Short summary
Short summary
Using highly accurate simulations within a design cycle is prohibitively computationally expensive. We implement and present a multifidelity optimization method and showcase its efficacy using three different case studies. We examine aerodynamic blade design, turbine controls tuning, and a wind plant layout problem. In each case, the multifidelity method finds an optimal design that performs better than those obtained using simplified models but at a lower cost than high-fidelity optimization.
Benjamin Sanderse, Vinit V. Dighe, Koen Boorsma, and Gerard Schepers
Wind Energ. Sci., 7, 759–781, https://doi.org/10.5194/wes-7-759-2022, https://doi.org/10.5194/wes-7-759-2022, 2022
Short summary
Short summary
An accurate prediction of loads and power of an offshore wind turbine is needed for an optimal design. However, such predictions are typically performed with engineering models that contain many inaccuracies and uncertainties. In this paper we have proposed a systematic approach to quantify and calibrate these uncertainties based on two experimental datasets. The calibrated models are much closer to the experimental data and are equipped with an estimate of the uncertainty in the predictions.
Andrew P. J. Stanley, Christopher Bay, Rafael Mudafort, and Paul Fleming
Wind Energ. Sci., 7, 741–757, https://doi.org/10.5194/wes-7-741-2022, https://doi.org/10.5194/wes-7-741-2022, 2022
Short summary
Short summary
In wind plants, turbines can be yawed to steer their wakes away from downstream turbines and achieve an increase in plant power. The yaw angles become expensive to solve for in large farms. This paper presents a new method to solve for the optimal turbine yaw angles in a wind plant. The yaw angles are defined as Boolean variables – each turbine is either yawed or nonyawed. With this formulation, most of the gains from wake steering can be reached with a large reduction in computational expense.
Charles Tripp, Darice Guittet, Jennifer King, and Aaron Barker
Wind Energ. Sci., 7, 697–713, https://doi.org/10.5194/wes-7-697-2022, https://doi.org/10.5194/wes-7-697-2022, 2022
Short summary
Short summary
Hybrid solar and wind plant layout optimization is a difficult, complex problem. In this paper, we propose a parameterized approach to wind and solar hybrid power plant layout optimization that greatly reduces problem dimensionality while guaranteeing that the generated layouts have a desirable regular structure. We demonstrate that this layout method that generates high-performance, regular layouts which respect hard constraints (e.g., placement restrictions).
Jason M. Jonkman, Emmanuel S. P. Branlard, and John P. Jasa
Wind Energ. Sci., 7, 559–571, https://doi.org/10.5194/wes-7-559-2022, https://doi.org/10.5194/wes-7-559-2022, 2022
Short summary
Short summary
This paper summarizes efforts done to understand the impact of design parameter variations in the physical system (e.g., mass, stiffness, geometry, aerodynamic, and hydrodynamic coefficients) on the linearized system using OpenFAST in support of the development of the WEIS toolset to enable controls co-design of floating offshore wind turbines.
Unai Gutierrez Santiago, Alfredo Fernández Sisón, Henk Polinder, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 505–521, https://doi.org/10.5194/wes-7-505-2022, https://doi.org/10.5194/wes-7-505-2022, 2022
Short summary
Short summary
The gearbox is one of the main contributors to the overall cost of wind energy, and it is acknowledged that we still do not fully understand its loading. The study presented in this paper develops a new alternative method to measure input rotor torque in wind turbine gearboxes, overcoming the drawbacks related to measuring on a rotating shaft. The method presented in this paper could make measuring gearbox torque more cost-effective, which would facilitate its adoption in serial wind turbines.
Andrew P. J. Stanley, Jennifer King, Christopher Bay, and Andrew Ning
Wind Energ. Sci., 7, 433–454, https://doi.org/10.5194/wes-7-433-2022, https://doi.org/10.5194/wes-7-433-2022, 2022
Short summary
Short summary
In this paper, we present a computationally inexpensive model to calculate wind turbine blade fatigue caused by waking and partial waking. The model accounts for steady state on the blade, as well as wind turbulence. The model is fast enough to be used in wind farm layout optimization, which has not been possible with more expensive fatigue models in the past. The methods introduced in this paper will allow for farms with increased energy production that maintain turbine structural reliability.
Mareike Leimeister, Maurizio Collu, and Athanasios Kolios
Wind Energ. Sci., 7, 259–281, https://doi.org/10.5194/wes-7-259-2022, https://doi.org/10.5194/wes-7-259-2022, 2022
Short summary
Short summary
Floating offshore wind technology has high potential but still faces challenges for gaining economic competitiveness to allow commercial market uptake. Hence, design optimization plays a key role; however, the final optimum floater obtained highly depends on the specified optimization problem. Thus, by considering alternative structural realization approaches, not very stringent limitations on the structure and dimensions are required. This way, more innovative floater designs can be captured.
Ernesto Camarena, Evan Anderson, Josh Paquette, Pietro Bortolotti, Roland Feil, and Nick Johnson
Wind Energ. Sci., 7, 19–35, https://doi.org/10.5194/wes-7-19-2022, https://doi.org/10.5194/wes-7-19-2022, 2022
Short summary
Short summary
The length of rotor blades of land-based wind turbines is currently constrained by logistics. Turbine manufacturers currently propose segmented solutions to overcome these limits, but blade joints come with extra masses and costs. This work investigates an alternative solution, namely the design of ultra-flexible blades that can be transported on rail via controlled bending. The results show that this is a promising pathway to further increasing the size of land-based wind turbines.
Ye Liu, Yun Qian, and Larry K. Berg
Wind Energ. Sci., 7, 37–51, https://doi.org/10.5194/wes-7-37-2022, https://doi.org/10.5194/wes-7-37-2022, 2022
Short summary
Short summary
Uncertainties in initial conditions (ICs) decrease the accuracy of wind speed forecasts. We find that IC uncertainties can alter wind speed by modulating the weather system. IC uncertainties in local thermal gradient and large-scale circulation jointly contribute to wind speed forecast uncertainties. Wind forecast accuracy in the Columbia River Basin is confined by initial uncertainties in a few specific regions, providing useful information for more intense measurement and modeling studies.
Alessandro Croce, Stefano Cacciola, and Luca Sartori
Wind Energ. Sci., 7, 1–17, https://doi.org/10.5194/wes-7-1-2022, https://doi.org/10.5194/wes-7-1-2022, 2022
Short summary
Short summary
In recent years, research has focused on the development of wind farm controllers with the aim of minimizing interactions between machines and thus improving the production of the wind farm.
In this work we have analyzed the effects of these recent technologies on a single wind turbine, with the aim of understanding the impact of these controllers on the design of the machine itself.
The analyses have shown there are non-negligible effects on some components of the wind turbine.
Nicola Bodini, Weiming Hu, Mike Optis, Guido Cervone, and Stefano Alessandrini
Wind Energ. Sci., 6, 1363–1377, https://doi.org/10.5194/wes-6-1363-2021, https://doi.org/10.5194/wes-6-1363-2021, 2021
Short summary
Short summary
We develop two machine-learning-based approaches to temporally extrapolate uncertainty in hub-height wind speed modeled by a numerical weather prediction model. We test our approaches in the California Outer Continental Shelf, where a significant offshore wind energy development is currently being planned, and we find that both provide accurate results.
Helena Canet, Stefan Loew, and Carlo L. Bottasso
Wind Energ. Sci., 6, 1325–1340, https://doi.org/10.5194/wes-6-1325-2021, https://doi.org/10.5194/wes-6-1325-2021, 2021
Short summary
Short summary
Lidar-assisted control (LAC) is used to redesign the rotor and tower of three turbines, differing in terms of wind class, size, and power rating. The load reductions enabled by LAC are used to save
mass, increase hub height, or extend lifetime. The first two strategies yield reductions in the cost of energy only for the tower of the largest machine, while more interesting benefits are obtained for lifetime extension.
David Getz and Jose Palacios
Wind Energ. Sci., 6, 1291–1309, https://doi.org/10.5194/wes-6-1291-2021, https://doi.org/10.5194/wes-6-1291-2021, 2021
Short summary
Short summary
A methodology to design electrothermal deicing protection for wind turbines is presented. The method relies on modeling and experimental testing to determine the critical ice thickness. The critical ice thickness needed is dependent on the ice tensile strength, which varies with icing conditions. The ice tensile strength must be overcome by the stress that a de-bonded ice structure exerts under centrifugal force at its root region, where it attaches to a non-de-bonded ice region.
Pietro Bortolotti, Nick Johnson, Nikhar J. Abbas, Evan Anderson, Ernesto Camarena, and Joshua Paquette
Wind Energ. Sci., 6, 1277–1290, https://doi.org/10.5194/wes-6-1277-2021, https://doi.org/10.5194/wes-6-1277-2021, 2021
Short summary
Short summary
The length of rotor blades of land-based wind turbines is currently constrained by logistics. Turbine manufacturers currently propose segmented solutions to overcome these limits, but blade joints come with extra masses and costs. This work investigates an alternative solution, namely the design of ultra-flexible blades that can be transported on rail via controlled bending. The results show that this is a promising pathway for further increasing the size of land-based wind turbines.
Andrew P. J. Stanley, Owen Roberts, Jennifer King, and Christopher J. Bay
Wind Energ. Sci., 6, 1143–1167, https://doi.org/10.5194/wes-6-1143-2021, https://doi.org/10.5194/wes-6-1143-2021, 2021
Short summary
Short summary
Wind farm layout optimization is an essential part of wind farm design. In this paper, we present different methods to determine the number of turbines in a wind farm, as well as their placement. Also in this paper we explore the effect that the objective function has on the wind farm design and found that wind farm layout is highly sensitive to the objective. The optimal number of turbines can vary greatly, from 15 to 54 for the cases in this paper, depending on the metric that is optimized.
Gerard Schepers, Pim van Dorp, Remco Verzijlbergh, Peter Baas, and Harmen Jonker
Wind Energ. Sci., 6, 983–996, https://doi.org/10.5194/wes-6-983-2021, https://doi.org/10.5194/wes-6-983-2021, 2021
Short summary
Short summary
In this article the aeroelastic loads on a 10 MW turbine in response to unconventional wind conditions selected from a year-long large-eddy simulation on a site at the North Sea are evaluated. Thereto an assessment is made of the practical importance of these wind conditions within an aeroelastic context based on high-fidelity wind modelling. Moreover the accuracy of BEM-based methods for modelling such wind conditions is assessed.
Quanjiang Yu, Michael Patriksson, and Serik Sagitov
Wind Energ. Sci., 6, 949–959, https://doi.org/10.5194/wes-6-949-2021, https://doi.org/10.5194/wes-6-949-2021, 2021
Short summary
Short summary
There are two ways to maintain a multi-component system: corrective maintenance, when a broken component is replaced with a new one, and preventive maintenance (PM), when some components are replaced in a planned manner before they break down. This article proposes a mathematical model for finding an optimal time to perform the next PM activity and selecting the components which should be replaced. The model is fast to solve, and it can be used as a key module in a maintenance scheduling app.
Kenneth Loenbaek, Christian Bak, Jens I. Madsen, and Michael McWilliam
Wind Energ. Sci., 6, 903–915, https://doi.org/10.5194/wes-6-903-2021, https://doi.org/10.5194/wes-6-903-2021, 2021
Short summary
Short summary
We present a model for assessing the aerodynamic performance of a wind turbine rotor through a different parametrization of the classical blade element momentum model. The model establishes an analytical relationship between the loading in the flow direction and the power along the rotor span. The main benefit of the model is the ease with which it can be applied for rotor optimization and especially load constraint power optimization.
Kenneth Loenbaek, Christian Bak, and Michael McWilliam
Wind Energ. Sci., 6, 917–933, https://doi.org/10.5194/wes-6-917-2021, https://doi.org/10.5194/wes-6-917-2021, 2021
Short summary
Short summary
A novel wind turbine rotor optimization methodology is presented. Using an assumption of radial independence it is possible to obtain the Pareto-optimal relationship between power and loads through the use of KKT multipliers, leaving an optimization problem that can be solved at each radial station independently. Combining it with a simple cost function it is possible to analytically solve for the optimal power per cost with given inputs for the aerodynamics and the cost function.
Erik Quaeghebeur, René Bos, and Michiel B. Zaaijer
Wind Energ. Sci., 6, 815–839, https://doi.org/10.5194/wes-6-815-2021, https://doi.org/10.5194/wes-6-815-2021, 2021
Short summary
Short summary
We present a technique to support the optimal layout (placement) of wind turbines in a wind farm. It efficiently determines good directions and distances for moving turbines. An improved layout reduces production losses and so makes the farm project economically more attractive. Compared to most existing techniques, our approach requires less time. This allows wind farm designers to explore more alternatives and provides the flexibility to adapt the layout to site-specific requirements.
Helena Canet, Pietro Bortolotti, and Carlo L. Bottasso
Wind Energ. Sci., 6, 601–626, https://doi.org/10.5194/wes-6-601-2021, https://doi.org/10.5194/wes-6-601-2021, 2021
Short summary
Short summary
The paper analyzes in detail the problem of scaling, considering both the steady-state and transient response cases, including the effects of aerodynamics, elasticity, inertia, gravity, and actuation. After a general theoretical analysis of the problem, the article considers two alternative ways of designing a scaled rotor. The two methods are then applied to the scaling of a 10 MW turbine of 180 m in diameter down to three different sizes (54, 27, and 2.8 m).
Freia Harzendorf, Ralf Schelenz, and Georg Jacobs
Wind Energ. Sci., 6, 571–584, https://doi.org/10.5194/wes-6-571-2021, https://doi.org/10.5194/wes-6-571-2021, 2021
Short summary
Short summary
Making wind turbines more reliable over their lifetime is an important goal for improving wind turbine technology. The wind turbine drivetrain has a major influence on turbine reliability. This paper presents an approach that will help to identify holistically better drivetrain concepts in an early product design phase from an operational perspective as it is able to estimate and assess drivetrain-concept-specific inherent risks in the operational phase.
Artur Movsessian, Marcel Schedat, and Torsten Faber
Wind Energ. Sci., 6, 539–554, https://doi.org/10.5194/wes-6-539-2021, https://doi.org/10.5194/wes-6-539-2021, 2021
Short summary
Short summary
The assessment of the structural condition and technical lifetime extension of a wind turbine is challenging due to lack of information for the estimation of fatigue loads. This paper demonstrates the modelling of damage-equivalent loads of the fore–aft bending moments of a wind turbine tower, highlighting the advantage of using the neighbourhood component analysis. This feature selection technique is compared to correlation analysis, stepwise regression, and principal component analysis.
Jan Wiśniewski, Krzysztof Rogowski, Konrad Gumowski, and Jacek Szumbarski
Wind Energ. Sci., 6, 287–294, https://doi.org/10.5194/wes-6-287-2021, https://doi.org/10.5194/wes-6-287-2021, 2021
Short summary
Short summary
The article describes results of experimental wind tunnel and CFD testing of four different straight-bladed vertical axis wind turbine model configurations. The experiment tested a novel concept of vertically dividing and azimuthally shifting a turbine rotor into two parts with a specific uneven height division in order to limit cycle amplitudes and average cycle values of bending moments at the bottom of the turbine shaft to increase product lifetime, especially for industrial-scale turbines.
Gesine Wanke, Leonardo Bergami, Frederik Zahle, and David Robert Verelst
Wind Energ. Sci., 6, 203–220, https://doi.org/10.5194/wes-6-203-2021, https://doi.org/10.5194/wes-6-203-2021, 2021
Short summary
Short summary
This article regards a rotor redesign for a wind turbine in upwind and in downwind rotor configurations. A simple optimization tool is used to estimate the aerodynamic planform, as well as the structural mass distribution of the rotor blade. The designs are evaluated in full load base calculations according to the IEC standard with the aeroelastic tool HAWC2. A scaling model is used to scale turbine and energy costs from the design loads and compare the costs for the turbine configurations.
Oliver Menck, Matthias Stammler, and Florian Schleich
Wind Energ. Sci., 5, 1743–1754, https://doi.org/10.5194/wes-5-1743-2020, https://doi.org/10.5194/wes-5-1743-2020, 2020
Short summary
Short summary
Blade bearings of wind turbines experience unusual loads compared to bearings in other industrial applications, which adds some difficulty to the application of otherwise well-established calculation methods, like fatigue lifetime. As a result, different methods for such calculations can be found in the literature. This paper compares three approaches of varying complexity and comes to the conclusion that the simplest of the methods is very inaccurate compared to the more complex methods.
Gianluca Zorzi, Amol Mankar, Joey Velarde, John D. Sørensen, Patrick Arnold, and Fabian Kirsch
Wind Energ. Sci., 5, 1521–1535, https://doi.org/10.5194/wes-5-1521-2020, https://doi.org/10.5194/wes-5-1521-2020, 2020
Short summary
Short summary
Storms, typhoons or seismic actions are likely to cause permanent rotation of offshore wind turbine foundations. Excessive rotation jeopardizes the operation of the wind turbine. In this study geotechnical, loads and probabilistic modelling are used to develop a reliability framework for predicting the rotation of the foundation under cyclic lateral loading.
Nicola Bodini and Mike Optis
Wind Energ. Sci., 5, 1435–1448, https://doi.org/10.5194/wes-5-1435-2020, https://doi.org/10.5194/wes-5-1435-2020, 2020
Short summary
Short summary
Calculations of annual energy production (AEP) and its uncertainty are critical for wind farm financial transactions. Standard industry practice assumes that different uncertainty categories within an AEP calculation are uncorrelated and can therefore be combined through a sum of squares approach. In this project, we show the limits of this assumption by performing operational AEP estimates for over 470 wind farms in the United States and propose a more accurate way to combine uncertainties.
Simon Letzgus
Wind Energ. Sci., 5, 1375–1397, https://doi.org/10.5194/wes-5-1375-2020, https://doi.org/10.5194/wes-5-1375-2020, 2020
Short summary
Short summary
One of the major challenges when working with wind turbine sensor data in practice is the presence of systematic changes in signal behaviour induced by malfunctions or maintenance actions. We found that approximately every third signal is affected by such change points and introduce an algorithm which reliably detects them in a highly automated fashion. The algorithm enables the application of data-driven techniques to monitor wind turbine components using data from commonly installed sensors.
Emmanuel Branlard, Dylan Giardina, and Cameron S. D. Brown
Wind Energ. Sci., 5, 1155–1167, https://doi.org/10.5194/wes-5-1155-2020, https://doi.org/10.5194/wes-5-1155-2020, 2020
Short summary
Short summary
The paper presents an application of the Kalman filtering technique to estimate loads on a wind turbine. The approach combines a mechanical model and a set of measurements to estimate signals that are not available in the measurements, such as wind speed, thrust, tower position, and tower loads. The model is severalfold faster than real time and is intended to be run online, for instance, to evaluate real-time fatigue life consumption of a field turbine using a digital twin.
Laura Schröder, Nikolay Krasimirov Dimitrov, and David Robert Verelst
Wind Energ. Sci., 5, 1007–1022, https://doi.org/10.5194/wes-5-1007-2020, https://doi.org/10.5194/wes-5-1007-2020, 2020
Short summary
Short summary
We suggest a methodology for correlating loads with component reliability of turbines in wind farms by combining physical modeling with machine learning. The suggested approach is demonstrated on an offshore wind farm for comparing performance, loads and lifetime estimations against recorded main bearing failures from maintenance reports. It is found that turbines positioned at the border of the wind farm with a higher expected AEP are estimated to experience earlier main bearing failures.
João Pacheco, Silvina Guimarães, Carlos Moutinho, Miguel Marques, José Carlos Matos, and Filipe Magalhães
Wind Energ. Sci., 5, 983–996, https://doi.org/10.5194/wes-5-983-2020, https://doi.org/10.5194/wes-5-983-2020, 2020
Short summary
Short summary
This paper introduces the Tocha wind farm, presents the different layouts adopted in the instrumentation of the wind turbines and shows initial results. At this preliminary stage, the capabilities of the very extensive monitoring layout are demonstrated. The results presented demonstrate the ability of the different monitoring components to track the modal parameters of the system, composed of tower and rotor, and to characterize the internal loads at the tower base and blade roots.
Gesine Wanke, Leonardo Bergami, and David Robert Verelst
Wind Energ. Sci., 5, 929–944, https://doi.org/10.5194/wes-5-929-2020, https://doi.org/10.5194/wes-5-929-2020, 2020
Short summary
Short summary
Converting an upwind wind turbine into a downwind configuration is shown to come with higher edgewise loads due to lower edgewise damping. The study shows from modal displacements of a reduced-order turbine model that the interaction between the forces on the rotor, the rotor motion, and the tower torsion is the main reason for the observed damping decrease.
Malo Rosemeier and Matthias Saathoff
Wind Energ. Sci., 5, 897–909, https://doi.org/10.5194/wes-5-897-2020, https://doi.org/10.5194/wes-5-897-2020, 2020
Short summary
Short summary
A huge number of wind turbines have reached their designated lifetime of 20 years.
Most of the turbines installed were overdesigned.
In practice, these turbines could potentially operate longer to increase the energy yield.
For the use case turbine considered in this work, a simple lifetime extension of 8.7 years increases the energy yield by 43.5 %. When the swept rotor area is increased by means of a blade tip extension, the yield is increased by an additional 2.3 %.
Sebastian Perez-Becker, Francesco Papi, Joseph Saverin, David Marten, Alessandro Bianchini, and Christian Oliver Paschereit
Wind Energ. Sci., 5, 721–743, https://doi.org/10.5194/wes-5-721-2020, https://doi.org/10.5194/wes-5-721-2020, 2020
Short summary
Short summary
Aeroelastic design load calculations play a key role in determining the design loads of the different wind turbine components. This study compares load estimations from calculations using a Blade Element Momentum aerodynamic model with estimations from calculations using a higher-order Lifting-Line Free Vortex Wake aerodynamic model. The paper finds and explains the differences in fatigue and extreme turbine loads for power production simulations that cover a wide range of turbulent wind speeds.
Kwangtae Ha, Moritz Bätge, David Melcher, and Steffen Czichon
Wind Energ. Sci., 5, 591–599, https://doi.org/10.5194/wes-5-591-2020, https://doi.org/10.5194/wes-5-591-2020, 2020
Short summary
Short summary
This paper outlines a novel segment test methodology for wind turbine rotor blades. It mainly aims at improving the efficiency of the fatigue test as a future test method at Fraunhofer IWES. The numerical simulation reveals that this method has a significant time savings of up to 43 % and 52 % for 60 and 90 m blades, while improving test quality within an acceptable range of overload. This test methodology could be a technical solution for future offshore rotor blades longer than 100 m.
Jaime Liew, Albert M. Urbán, and Søren Juhl Andersen
Wind Energ. Sci., 5, 427–437, https://doi.org/10.5194/wes-5-427-2020, https://doi.org/10.5194/wes-5-427-2020, 2020
Short summary
Short summary
In wind farms, the interaction between neighboring turbines can cause notable power losses. The focus of the paper is on how the combination of turbine yaw misalignment and wake effects influences the power loss in a wind turbine. The results of the paper show a more notable power loss due to turbine misalignment when turbines are closely spaced. The presented conclusions enable better predictions of a turbine's power production, which can assist the wind farm design process.
Frederick Letson, Rebecca J. Barthelmie, and Sara C. Pryor
Wind Energ. Sci., 5, 331–347, https://doi.org/10.5194/wes-5-331-2020, https://doi.org/10.5194/wes-5-331-2020, 2020
Short summary
Short summary
Wind turbine blade leading edge erosion (LEE) is potentially a significant source of energy loss and expense for wind farm operators. This study presents a novel approach to characterizing LEE potential from precipitation across the contiguous USA based on publicly available National Weather Service dual-polarization RADAR data. The approach is described in detail and illustrated using six locations distributed across parts of the USA that have substantial wind turbine deployments.
Erik Quaeghebeur, Sebastian Sanchez Perez-Moreno, and Michiel B. Zaaijer
Wind Energ. Sci., 5, 259–284, https://doi.org/10.5194/wes-5-259-2020, https://doi.org/10.5194/wes-5-259-2020, 2020
Short summary
Short summary
The design and management of an offshore wind farm involve expertise in many disciplines. It is hard for a single person to maintain the overview needed. Therefore, we have created WESgraph, a knowledge base for the wind farm domain, implemented as a graph database. It stores descriptions of the multitude of domain concepts and their various interconnections. It allows users to explore the domain and search for relationships within and across disciplines, enabling various applications.
Lars Einar S. Stieng and Michael Muskulus
Wind Energ. Sci., 5, 171–198, https://doi.org/10.5194/wes-5-171-2020, https://doi.org/10.5194/wes-5-171-2020, 2020
Short summary
Short summary
We present a framework for reducing the cost of support structures for offshore wind turbines that takes into account the many uncertainties that go into the design process. The results demonstrate how an efficient new approach, tailored for support structure design, allows the state of the art for design without uncertainties to be used within a framework that does include these uncertainties. This allows more realistic, and less conservative, design methods
to be used for practical design.
Kenneth Loenbaek, Christian Bak, Jens I. Madsen, and Bjarke Dam
Wind Energ. Sci., 5, 155–170, https://doi.org/10.5194/wes-5-155-2020, https://doi.org/10.5194/wes-5-155-2020, 2020
Short summary
Short summary
From the basic aerodynamic theory of wind turbine rotors, it is a well-known fact that there is a relationship between the loading of the rotor and power efficiency. It shows that there is a loading that maximizes the power efficiency, and it is common to target this maximum when designing rotors. But in this paper it is found that for rotors constrained by a load, the maximum power is found by decreasing the loading and increasing the rotor radius. Max power efficiency is therefore not optimal.
Nikola Vasiljević, Andrea Vignaroli, Andreas Bechmann, and Rozenn Wagner
Wind Energ. Sci., 5, 73–87, https://doi.org/10.5194/wes-5-73-2020, https://doi.org/10.5194/wes-5-73-2020, 2020
Short summary
Short summary
A WindScanner system consisting of two synchronized scanning lidars potentially represents a cost-effective solution for multipoint measurements. However, the lidar limitations and the site limitations are detrimental to the installation of lidars and number and location of measurement positions. To simplify the process of finding suitable measurement positions and lidar installation locations, a campaign planning workflow was devised. The paper describes the workflow and how it was digitalized.
Andrew P. J. Stanley and Andrew Ning
Wind Energ. Sci., 4, 663–676, https://doi.org/10.5194/wes-4-663-2019, https://doi.org/10.5194/wes-4-663-2019, 2019
Short summary
Short summary
When designing a wind farm, one crucial step is finding the correct location or optimizing the location of the wind turbines to maximize power production. In the past, optimizing the turbine layout of large wind farms has been difficult because of the large number of interacting variables. In this paper, we present the boundary-grid parameterization method, which defines the layout of any wind farm with only five variables, allowing people to study and design wind farms regardless of the size.
Daniel S. Zalkind, Gavin K. Ananda, Mayank Chetan, Dana P. Martin, Christopher J. Bay, Kathryn E. Johnson, Eric Loth, D. Todd Griffith, Michael S. Selig, and Lucy Y. Pao
Wind Energ. Sci., 4, 595–618, https://doi.org/10.5194/wes-4-595-2019, https://doi.org/10.5194/wes-4-595-2019, 2019
Short summary
Short summary
We present a model that both (1) reduces the computational effort involved in analyzing design trade-offs and (2) provides a qualitative understanding of the root cause of fatigue and extreme structural loads for wind turbine components from the blades to the tower base. We use this model in conjunction with design loads from high-fidelity simulations to analyze and compare the trade-offs between power capture and structural loading for large rotor concepts.
Amy N. Robertson, Kelsey Shaler, Latha Sethuraman, and Jason Jonkman
Wind Energ. Sci., 4, 479–513, https://doi.org/10.5194/wes-4-479-2019, https://doi.org/10.5194/wes-4-479-2019, 2019
Short summary
Short summary
This paper identifies the most sensitive parameters for the load response of a 5 MW wind turbine. Two sets of parameters are examined: one set relating to the wind excitation characteristics and a second related to the physical properties of the wind turbine. The two sensitivity analyses are done separately, and the top most-sensitive parameters are identified for different load outputs throughout the structure. The findings will guide future validation campaigns and measurement needs.
Pietro Bortolotti, Helena Canet, Carlo L. Bottasso, and Jaikumar Loganathan
Wind Energ. Sci., 4, 397–406, https://doi.org/10.5194/wes-4-397-2019, https://doi.org/10.5194/wes-4-397-2019, 2019
Short summary
Short summary
The paper studies the effects of uncertainties in aeroservoelastic
wind turbine models. Uncertainties are associated with the wind
inflow characteristics and the blade surface state, and they are propagated
by means of two non-intrusive methods throughout the
aeroservoelastic model of a large conceptual offshore wind
turbine. Results are compared with a brute-force extensive Monte
Carlo sampling to assess the convergence characteristics of the
non-intrusive approaches.
Andrés Santiago Padrón, Jared Thomas, Andrew P. J. Stanley, Juan J. Alonso, and Andrew Ning
Wind Energ. Sci., 4, 211–231, https://doi.org/10.5194/wes-4-211-2019, https://doi.org/10.5194/wes-4-211-2019, 2019
Short summary
Short summary
We propose the use of a new method to efficiently compute the annual energy production (AEP) of a wind farm by properly handling the uncertainties in the wind direction and wind speed. We apply the new ideas to the layout optimization of a large wind farm. We show significant computational savings by reducing the number of simulations required to accurately compute and optimize the AEP of different wind farms.
Mads H. Aa. Madsen, Frederik Zahle, Niels N. Sørensen, and Joaquim R. R. A. Martins
Wind Energ. Sci., 4, 163–192, https://doi.org/10.5194/wes-4-163-2019, https://doi.org/10.5194/wes-4-163-2019, 2019
Short summary
Short summary
The wind energy industry relies heavily on CFD to analyze new designs. This paper investigates a way to utilize CFD further upstream the design process where lower-fidelity methods are used. We present the first comprehensive 3-D CFD adjoint-based shape optimization of a 10 MW modern offshore wind turbine. The present work shows that, with the right tools, we can model the entire geometry, including the root, and optimize modern wind turbine rotors at the cost of a few hundred CFD evaluations.
Pietro Bortolotti, Abhinav Kapila, and Carlo L. Bottasso
Wind Energ. Sci., 4, 115–125, https://doi.org/10.5194/wes-4-115-2019, https://doi.org/10.5194/wes-4-115-2019, 2019
Short summary
Short summary
The paper compares upwind and downwind three-bladed configurations
for a 10 MW wind turbine in terms of power and loads. For the
downwind case, the study also considers a load-aligned solution
with active coning. Results indicate that downwind solutions are
slightly more advantageous than upwind ones, although improvements
are small. Additionally, pre-alignment is difficult to achieve in
practice, and the active coning solution is associated with very
significant engineering challenges.
Cited articles
Adams, B. M., Ebeida, M. S., Eldred, M. S., Geraci, G., Jakeman, J. D., Maupin,
K. A., Monschke, J. A., Stephens, J. A., Swiler, L. P., Vigil, D. M., Wildey,
T. M., Bohnhoff, W. J., Dalbey, K. R., Eddy, J. P., Frye, J. R., Hooper,
R. W., Hu, K. T., Hough, P. D., Khalil, M., Ridgway, E. M., Winokur, J. G.,
and Rushdi, A.: Dakota, A Multilevel Parallel Object-Oriented Framework for
Design Optimization, Parameter Estimation, Uncertainty Quantification, and
Sensitivity Analysis: Version 6.8 Theory Manual, 2014. a, b, c, d
Annoni, J., Fleming, P., Scholbrock, A., Roadman, J., Dana, S., Adcock, C., Porte-Agel, F., Raach, S., Haizmann, F., and Schlipf, D.: Analysis of control-oriented wake modeling tools using lidar field results, Wind Energ. Sci., 3, 819–831, https://doi.org/10.5194/wes-3-819-2018, 2018. a, b, c
Bastankhah, M. and Porté-Agel, F.: Experimental and theoretical study of
wind turbine wakes in yawed conditions, J. Fluid Mech., 806,
506–541, https://doi.org/10.1017/jfm.2016.595, 2016. a
Birge, J. R. and Louveaux, F.: Introduction to stochastic programming, Springer
Science & Business Media, https://doi.org/10.1007/978-1-4614-0237-4, 2011. a
Bossanyi, E. and Jorge, T.: Optimisation of wind plant sector management for
energy and loads, in: Control Conference (ECC), 2016 European, Aalborg, Denmark,
IEEE, 922–927, https://doi.org/10.1109/ECC.2016.7810407, 29 June–1 July 2016. a
Chen, L. and MacDonald, E.: Effects of uncertain land availability, wind shear,
and cost on wind farm layout, in: Proceedings of the International Design
Engineering Technical Conferences & Computers and Information in Engineering
Conference IDETC/CIE, Portland, OR, USA, 4–7,
https://doi.org/10.1115/DETC2013-13433, 2013. a
Clifton, A., Smith, A., and Fields, M.: Wind plant preconstruction energy
estimates: current practice and opportunities, National Renewable Energy
Laboratory, NREL/TP–5000-64735, https://doi.org/10.2172/1248798, 2016. a
Damiani, R., Dana, S., Annoni, J., Fleming, P., Roadman, J., van Dam, J., and Dykes, K.: Assessment of wind turbine component loads under yaw-offset conditions, Wind Energ. Sci., 3, 173–189, https://doi.org/10.5194/wes-3-173-2018, 2018. a, b, c
Eldred, M. S. and Elman, H. C.: Design under uncertainty employing stochastic
expansion methods, Int. J. Uncertain. Quan., 1, 119–146,
https://doi.org/10.1615/Int.J.UncertaintyQuantification.v1.i2.20, 2011. a
Fleming, P., Churchfield, M., Scholbrock, A., Clifton, A., Schreck, S.,
Johnson, K., Wright, A., Gebraad, P., Annoni, J., Naughton, B., Berg, J., Herges, T., White, J., Mikkelsen, T., Sjöholm, M., and Angelou, N.:
Detailed field test of yaw-based wake steering, J. Phys.
Conf. Ser., 753, 052003,
https://doi.org/10.1088/1742-6596/753/5/052003, 2016a. a
Fleming, P., Ning, A., Gebraad, P. M., and Dykes, K.: Wind plant system
engineering through optimization of layout and yaw control, Wind Energy, 19,
329–344, https://doi.org/10.1002/we.1836, 2016b. a, b
Fleming, P., Annoni, J., Shah, J. J., Wang, L., Ananthan, S., Zhang, Z., Hutchings, K., Wang, P., Chen, W., and Chen, L.: Field test of wake steering at an offshore wind farm, Wind Energ. Sci., 2, 229–239, https://doi.org/10.5194/wes-2-229-2017, 2017. a
Fleming, P., Annoni, J., Martínez-Tossas, L. A., Raach, S., Gruchalla, K.,
Scholbrock, A., Churchfield, M., and Roadman, J.: Investigation into the
shape of a wake of a yawed full-scale turbine, J. Phys.
Conf. Ser., 1037, 032010,
https://doi.org/10.1088/1742-6596/1037/3/032010, 2018. a, b
Fleming, P., King, J., Dykes, K., Simley, E., Roadman, J., Scholbrock, A., Murphy, P., Lundquist, J. K., Moriarty, P., Fleming, K., van Dam, J., Bay, C., Mudafort, R., Lopez, H., Skopek, J., Scott, M., Ryan, B., Guernsey, C., and Brake, D.: Initial results from a field campaign of wake steering applied at a commercial wind farm – Part 1, Wind Energ. Sci., 4, 273–285, https://doi.org/10.5194/wes-4-273-2019, 2019. a
Gaumond, M., Réthoré, P.-E., Ott, S., Pena, A., Bechmann, A., and
Hansen, K. S.: Wind Energy, 17, 1169–1178, https://doi.org/10.1002/we.1625, 2014. a, b
Gebraad, P., Teeuwisse, F., Van Wingerden, J., Fleming, P. A., Ruben, S.,
Marden, J., and Pao, L.: Wind plant power optimization through yaw control
using a parametric model for wake effects – a CFD simulation study, Wind
Energy, 19, 95–114, https://doi.org/10.1002/we.1822, 2016. a, b
Gebraad, P., Thomas, J. J., Ning, A., Fleming, P., and Dykes, K.: Maximization
of the annual energy production of wind power plants by optimization of
layout and yaw-based wake control, Wind Energy, 20, 97–107,
https://doi.org/10.1002/we.1993, 2017. a
Gonzalez, J. S., Payan, M. B., and Riquelme-Santos, J. M.: Optimization of wind
farm turbine layout including decision making under risk, IEEE Syst.
J., 6, 94–102, https://doi.org/10.1109/JSYST.2011.2163007, 2012. a
Johnson, K. E. and Thomas, N.: Wind farm control: Addressing the aerodynamic
interaction among wind turbines, in: American Control Conference,
ACC'09, IEEE, 2104–2109, https://doi.org/10.1109/ACC.2009.5160152, 2009. a
Jonkman, J., Butterfield, S., Musial, W., and Scott, G.: Definition of a 5-MW
reference wind turbine for offshore system development, National Renewable
Energy Laboratory, Golden, CO, Technical Report No. NREL/TP-500-38060,
https://doi.org/10.2172/947422, 2009. a, b
Marden, J. R., Ruben, S. D., and Pao, L. Y.: A model-free approach to wind farm
control using game theoretic methods, IEEE T. Contr. Syst.
T., 21, 1207–1214, https://doi.org/10.1109/TCST.2013.2257780, 2013. a
Mittelmeier, N. and Kühn, M.: Determination of optimal wind turbine alignment into the wind and detection of alignment changes with SCADA data, Wind Energ. Sci., 3, 395–408, https://doi.org/10.5194/wes-3-395-2018, 2018. a, b
Mittelmeier, N., Blodau, T., and Kühn, M.: Monitoring offshore wind farm power performance with SCADA data and an advanced wake model, Wind Energ. Sci., 2, 175–187, https://doi.org/10.5194/wes-2-175-2017, 2017. a
Munters, W. and Meyers, J.: Dynamic strategies for yaw and induction control of
wind farms based on large-eddy simulation and optimization, Energies, 11,
177, https://doi.org/10.3390/en11010177, 2018. a
NWTC Information Portal: (NWTC 135-m Meteorological Towers Data
Repository), available at: https://nwtc.nrel.gov/135mData, last access: 13 September 2019. a
Nygaard, N. G.: Systematic quantification of wake model uncertainty, in: EWEA
Offshore conference, 10–12, 2015. a
Padrón, A. S., Thomas, J., Stanley, A. P. J., Alonso, J. J., and Ning, A.: Polynomial chaos to efficiently compute the annual energy production in wind farm layout optimization, Wind Energ. Sci., 4, 211–231, https://doi.org/10.5194/wes-4-211-2019, 2019. a
Quick, J., Dykes, K., Graf, P., and Zahle, F.: Optimization Under Uncertainty
of Site-Specific Turbine Configurations, J. Phys. Conf.
Ser., 753, 062012, https://doi.org/10.1088/1742-6596/753/6/062012,
2016. a
Quick, J., Annoni, J., King, R., Dykes, K., Fleming, P., and Ning, A.:
Optimization Under Uncertainty for Wake Steering Strategies, J.
Phys. Conf. Ser., 854, 012036,
https://doi.org/10.1088/1742-6596/854/1/012036,
2017. a
Raach, S., Schlipf, D., Borisade, F., and Cheng, P. W.: Wake redirecting using
feedback control to improve the power output of wind farms, in: American
Control Conference (ACC), IEEE, 1387–1392,
https://doi.org/10.1109/ACC.2016.7525111, 2016. a
Rott, A., Doekemeijer, B., Seifert, J. K., van Wingerden, J.-W., and Kühn, M.: Robust active wake control in consideration of wind direction variability and uncertainty, Wind Energ. Sci., 3, 869–882, https://doi.org/10.5194/wes-3-869-2018, 2018. a, b, c
Simley, E., Fleming, P., and King, J.: Design and Analysis of a Wake Steering Controller with Wind Direction Variability, Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-35, in review, 2019.
a, b, c
Wharton, S. and Lundquist, J.: Assessing atmospheric stability and the impacts
on wind characteristics at an onshore wind farm, Tech. rep., Lawrence
Livermore National Laboratory (LLNL), Livermore, CA, USA,
https://doi.org/10.1002/we.483, 2010. a
Short summary
We investigate the trade-offs in optimization of wake steering strategies, where upstream turbines are positioned to deflect wakes away from downstream turbines, with a probabilistic perspective. We identify inputs that are sensitive to uncertainty and demonstrate a realistic optimization under uncertainty for a wind power plant control strategy. Designing explicitly around uncertainty yielded control strategies that were generally less aggressive and more robust to the uncertain input.
We investigate the trade-offs in optimization of wake steering strategies, where upstream...
Altmetrics
Final-revised paper
Preprint