Articles | Volume 10, issue 7
https://doi.org/10.5194/wes-10-1231-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/wes-10-1231-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Jul 2025
Research article |
| 03 Jul 2025
| 03 Jul 2025
A parcel-level evaluation of distributed wind opportunity in the contiguous United States
National Renewable Energy Laboratory, Golden, Colorado, USA
Paula Pérez
National Renewable Energy Laboratory, Golden, Colorado, USA
Slater Podgorny
National Renewable Energy Laboratory, Golden, Colorado, USA
Michaela Sizemore
National Renewable Energy Laboratory, Golden, Colorado, USA
Paritosh Das
National Renewable Energy Laboratory, Golden, Colorado, USA
Jeffrey D. Laurence-Chasen
National Renewable Energy Laboratory, Golden, Colorado, USA
Paul Crook
National Renewable Energy Laboratory, Golden, Colorado, USA
Caleb Phillips
National Renewable Energy Laboratory, Golden, Colorado, USA
Related authors
No articles found.
Lindsay M. Sheridan, Dmitry Duplyakin, Caleb Phillips, Heidi Tinnesand, Raj K. Rai, Julia E. Flaherty, and Larry K. Berg
Wind Energ. Sci., 10, 1451–1470, https://doi.org/10.5194/wes-10-1451-2025, https://doi.org/10.5194/wes-10-1451-2025, 2025
Short summary
Short summary
A total of 12 months of onsite wind measurement is standard for correcting model-based long-term wind speed estimates for utility-scale wind farms; however, the time and capital investment involved in gathering onsite measurements must be reconciled with the energy needs and funding opportunities for distributed wind projects. This study aims to answer the question of how short you can go in terms of the observational time period needed to make impactful improvements to long-term wind speed estimates.
Lindsay M. Sheridan, Jiali Wang, Caroline Draxl, Nicola Bodini, Caleb Phillips, Dmitry Duplyakin, Heidi Tinnesand, Raj K. Rai, Julia E. Flaherty, Larry K. Berg, Chunyong Jung, and Ethan Young
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-115, https://doi.org/10.5194/wes-2024-115, 2024
Revised manuscript accepted for WES
Short summary
Short summary
Three recent wind resource datasets are assessed for their skills in representing annual average wind speeds and seasonal, diurnal, and inter-annual trends in the wind resource to support customers interested in small and midsize wind energy.
Caleb Phillips, Lindsay M. Sheridan, Patrick Conry, Dimitrios K. Fytanidis, Dmitry Duplyakin, Sagi Zisman, Nicolas Duboc, Matt Nelson, Rao Kotamarthi, Rod Linn, Marc Broersma, Timo Spijkerboer, and Heidi Tinnesand
Wind Energ. Sci., 7, 1153–1169, https://doi.org/10.5194/wes-7-1153-2022, https://doi.org/10.5194/wes-7-1153-2022, 2022
Short summary
Short summary
Adoption of distributed wind turbines for energy generation is hindered by challenges associated with siting and accurate estimation of the wind resource. This study evaluates classic and commonly used methods alongside new state-of-the-art models derived from simulations and machine learning approaches using a large dataset from the Netherlands. We find that data-driven methods are most effective at predicting production at real sites and new models reliably outperform classic methods.
Lindsay M. Sheridan, Caleb Phillips, Alice C. Orrell, Larry K. Berg, Heidi Tinnesand, Raj K. Rai, Sagi Zisman, Dmitry Duplyakin, and Julia E. Flaherty
Wind Energ. Sci., 7, 659–676, https://doi.org/10.5194/wes-7-659-2022, https://doi.org/10.5194/wes-7-659-2022, 2022
Short summary
Short summary
The small wind community relies on simplified wind models and energy production simulation tools to obtain energy generation expectations. We gathered actual wind speed and turbine production data across the US to test the accuracy of models and tools for small wind turbines. This study provides small wind installers and owners with the error metrics and sources of error associated with using models and tools to make performance estimates, empowering them to adjust expectations accordingly.
Mike Optis, Jordan Perr-Sauer, Caleb Philips, Anna E. Craig, Joseph C. Y. Lee, Travis Kemper, Shuangwen Sheng, Eric Simley, Lindy Williams, Monte Lunacek, John Meissner, and M. Jason Fields
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-12, https://doi.org/10.5194/wes-2019-12, 2019
Preprint withdrawn
Short summary
Short summary
As global wind capacity continues to grow, the need for accurate operational analyses of a rapidly growing fleet of wind power plants has increased in proportion. To address this need, the National Renewable Energy Laboratory has released OpenOA, an open-source codebase for operational analysis of wind farms. It is envisioned that OpenOA will evolve into a widely used codebase supported by a large group of global wind energy experts. This paper provides a summary of OpenOA.
Related subject area
Thematic area: Wind technologies | Topic: Design concepts and methods for plants, turbines, and components
Probabilistic cost modeling as a basis for optimizing inspection and maintenance of turbine support structures in offshore wind farms
Wind Turbine Gearbox Operation Monitoring Using High-Resolution Distributed Fiber Optic Sensing
Semi-analytical methodology for fretting wear evaluation of unlubricated pitch bearing raceways under operative and non-operative periods
Effect of blade inclination angle for straight-bladed vertical-axis wind turbines
Full-scale wind turbine performance assessment: a customised, sensor-augmented aeroelastic modelling approach
Challenges in detecting wind turbine power loss: the effects of blade erosion, turbulence, and time averaging
Identification of operational deflection shapes of a wind turbine gearbox using fiber-optic strain sensors on a serial production end-of-line test bench
Investigation into Instantaneous Centre of Rotation for Enhanced Design of Floating Offshore Wind Turbines
Wind farm layout optimization with alignment constraints
One-to-one aeroservoelastic validation of operational loads and performance of a 2.8 MW wind turbine model in OpenFAST
State-of-the-art efficiency determination of a wind turbine drivetrain on a nacelle test bench
Identification of electro-mechanical interactions in wind turbines
A sensitivity-based estimation method for investigating control co-design relevance
Validation of aeroelastic dynamic model of active trailing edge flap system tested on a 4.3 MW wind turbine
Mesoscale modelling of North Sea wind resources with COSMO-CLM: model evaluation and impact assessment of future wind farm characteristics on cluster-scale wake losses
Gradient-based wind farm layout optimization with inclusion and exclusion zones
A novel techno-economical layout optimization tool for floating wind farm design
Hybrid-Lambda: a low-specific-rating rotor concept for offshore wind turbines
Speeding up large-wind-farm layout optimization using gradients, parallelization, and a heuristic algorithm for the initial layout
Nonlinear vibration characteristics of virtual mass systems for wind turbine blade fatigue testing
Extreme wind turbine response extrapolation with the Gaussian mixture model
The effect of site-specific wind conditions and individual pitch control on wear of blade bearings
A neighborhood search integer programming approach for wind farm layout optimization
Enabling control co-design of the next generation of wind power plants
Offshore wind farm optimisation: a comparison of performance between regular and irregular wind turbine layouts
A data-driven reduced-order model for rotor optimization
Grand challenges in the design, manufacture, and operation of future wind turbine systems
Computational fluid dynamics (CFD) modeling of actual eroded wind turbine blades
Grand Challenges: wind energy research needs for a global energy transition
Current status and grand challenges for small wind turbine technology
CFD-based curved tip shape design for wind turbine blades
Impacts of wind field characteristics and non-steady deterministic wind events on time-varying main-bearing loads
Muhammad Farhan, Ronald Schneider, Sebastian Thöns, and Max Gündel
Wind Energ. Sci., 10, 461–481, https://doi.org/10.5194/wes-10-461-2025, https://doi.org/10.5194/wes-10-461-2025, 2025
Short summary
Short summary
This paper presents a probabilistic cost model for inspection and maintenance (I&M) of turbine support structures in offshore wind farms. It provides the basis for decision-theoretical optimization of I&M strategies and accounts for uncertainties in the costs. The model can be used to optimize I&M strategies at the component, structural system, and wind farm level. Additionally, a simplified method is provided for I&M optimization for individual turbine support structures.
Linqing Luo, Unai Gutierrez Santiago, and Yuxin Wu
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2025-1, https://doi.org/10.5194/wes-2025-1, 2025
Revised manuscript accepted for WES
Short summary
Short summary
We introduced a new method to monitor wind turbine gearboxes using distributed fiber optic technology. By attaching a single optical fiber to the gearbox, we tracked strain changes at high resolution, capturing gear movement, torque, and temperature in real time. This study demonstrated the link between torque and strain, enabling early fault detection. The approach offers a cost-effective way to improve gearbox reliability and reduce downtime, supporting more sustainable wind energy operations.
David Cubillas, Mireia Olave, Iñigo Llavori, Ibai Ulacia, Jon Larrañaga, Aitor Zurutuza, and Arkaitz Lopez
Wind Energ. Sci., 10, 401–415, https://doi.org/10.5194/wes-10-401-2025, https://doi.org/10.5194/wes-10-401-2025, 2025
Short summary
Short summary
A methodology for evaluating fretting in wind turbine pitch bearing raceways is presented, and a case study is evaluated. The methodology considers the coupled effects of radial fretting and rotational fretting. As result, critical locations based on the dissipated energy are identified for the different wind speeds and the contributions of operational and non-operational times, as well as the prediction of damage shapes on the raceway for both cases, are evaluated independently and compared.
Laurence Morgan, Abbas Kazemi Amiri, William Leithead, and James Carroll
Wind Energ. Sci., 10, 381–399, https://doi.org/10.5194/wes-10-381-2025, https://doi.org/10.5194/wes-10-381-2025, 2025
Short summary
Short summary
This paper presents a systematic study of the effect of blade inclination angle, chord distribution, and blade length on vertical-axis wind turbine performance. It shows that, for rotors of identical power production, both blade volume and rotor torque can be significantly reduced through the use of aerodynamically optimised inclined rotor blades. This demonstrates the potential of vertical rotors to reduce the cost of energy for offshore wind when compared to horizontal rotors.
Tahir H. Malik and Christian Bak
Wind Energ. Sci., 10, 269–291, https://doi.org/10.5194/wes-10-269-2025, https://doi.org/10.5194/wes-10-269-2025, 2025
Short summary
Short summary
This research integrates custom sensors into wind turbine simulation models for improved performance monitoring utilising a turbine performance integral (TPI) method developed here. Real-world data validation demonstrates that appropriate sensor selection improves wind turbine performance monitoring. This approach addresses the need for precise performance assessments in the evolving wind energy sector, ultimately promoting sustainability and efficiency.
Tahir H. Malik and Christian Bak
Wind Energ. Sci., 10, 227–243, https://doi.org/10.5194/wes-10-227-2025, https://doi.org/10.5194/wes-10-227-2025, 2025
Short summary
Short summary
This study investigates how wind turbine blades damaged by erosion, along with changing wind conditions, affect power output. Even minor blade damage can lead to significant energy losses, especially in turbulent winds. Using simulations, it was discovered that standard power data analysis methods, including time averaging, can hide these losses. This research highlights the need for better blade damage detection and careful wind data analysis to optimise wind farm performance.
Unai Gutierrez Santiago, Aemilius A. W. van Vondelen, Alfredo Fernández Sisón, Henk Polinder, and Jan-Willem van Wingerden
Wind Energ. Sci., 10, 207–225, https://doi.org/10.5194/wes-10-207-2025, https://doi.org/10.5194/wes-10-207-2025, 2025
Short summary
Short summary
Knowing the loads applied to wind turbine gearboxes throughout their service life is becoming increasingly important as maintaining reliability with higher torque density demands is proving to be challenging. Operational deflection shapes identified from fiber-optic strain measurements have enabled the estimation of input torque, improving the assessment of the consumed life. Tracking operational deflection shapes recursively over time can potentially be used as an indicator of fault detection.
Katarzyna Patryniak, Maurizio Collu, Jason Jonkman, Matthew Hall, Garrett Barter, Daniel Zalkind, and Andrea Coraddu
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-167, https://doi.org/10.5194/wes-2024-167, 2025
Revised manuscript accepted for WES
Short summary
Short summary
This paper studies the Instantaneous Centre of Rotation (ICR) of Floating Offshore Wind Turbines (FOWTs). We present a method for computing the ICR and examine the correlations between the external loading, design features, ICR statistics, motions, and loads. We demonstrate how to apply the new insights to successfully modify the designs of the spar and semisubmersible FOWTs to reduce the loads in the moorings, the tower, and the blades, improving the ultimate strength and fatigue properties.
Paul Malisani, Tristan Bartement, and Pauline Bozonnet
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-118, https://doi.org/10.5194/wes-2024-118, 2024
Revised manuscript accepted for WES
Short summary
Short summary
Maritime authorities often impose turbine alignment constraints on developers to secure the navigation of boats within the wind farm, potentially creating substantial wake losses. The proposed contribution is a new Wind Farm Layout Optimization (WFLO) algorithm that considers these constraints. The proposed method optimizes the grid-alignment parameters and the turbines' location on this grid. We illustrate the algorithm's performances on a challenging example.
Kenneth Brown, Pietro Bortolotti, Emmanuel Branlard, Mayank Chetan, Scott Dana, Nathaniel deVelder, Paula Doubrawa, Nicholas Hamilton, Hristo Ivanov, Jason Jonkman, Christopher Kelley, and Daniel Zalkind
Wind Energ. Sci., 9, 1791–1810, https://doi.org/10.5194/wes-9-1791-2024, https://doi.org/10.5194/wes-9-1791-2024, 2024
Short summary
Short summary
This paper presents a study of the popular wind turbine design tool OpenFAST. We compare simulation results to measurements obtained from a 2.8 MW land-based wind turbine. Measured wind conditions were used to generate turbulent flow fields through several techniques. We show that successful validation of the tool is not strongly dependent on the inflow generation technique used for mean quantities of interest. The type of inflow assimilation method has a larger effect on fatigue quantities.
Hongkun Zhang, Paula Weidinger, Christian Mester, Zihang Song, Marcel Heller, Alexander Dubowik, Bernd Tegtmeier, and Karin Eustorgi
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-70, https://doi.org/10.5194/wes-2024-70, 2024
Revised manuscript accepted for WES
Short summary
Short summary
Drivetrain efficiency is a wind turbine’s fundamental behaviour in the energy conversion. To determine the efficiency, input and output powers need to be measured with sufficient accuracy. However, this is a very challenging task due to high complexity and lack of proper calibrated torque measurement. In cooperation with the German and Swiss national metrology institutes, the efficiency determination with state-of-the art instrumentations is demonstrated here with test processes and results.
Fiona Dominique Lüdecke, Martin Schmid, and Po Wen Cheng
Wind Energ. Sci., 9, 1527–1545, https://doi.org/10.5194/wes-9-1527-2024, https://doi.org/10.5194/wes-9-1527-2024, 2024
Short summary
Short summary
Large direct-drive wind turbines, with a multi-megawatt power rating, face design challenges. Moving towards a more system-oriented design approach could potentially reduce mass and costs. Exploiting the full design space, though, may invoke interaction mechanisms, which have been neglected in the past. Based on coupled simulations, this work derives a better understanding of the electro-mechanical interaction mechanisms and identifies potential for design relevance.
Jenna Iori, Carlo Luigi Bottasso, and Michael Kenneth McWilliam
Wind Energ. Sci., 9, 1289–1304, https://doi.org/10.5194/wes-9-1289-2024, https://doi.org/10.5194/wes-9-1289-2024, 2024
Short summary
Short summary
The controller of a wind turbine has an important role in regulating power production and avoiding structural failure. However, it is often designed after the rest of the turbine, and thus its potential is not fully exploited. An alternative is to design the structure and the controller simultaneously. This work develops a method to identify if a given turbine design can benefit from this new simultaneous design process. For example, a higher and cheaper turbine tower can be built this way.
Andrea Gamberini, Thanasis Barlas, Alejandro Gomez Gonzalez, and Helge Aagaard Madsen
Wind Energ. Sci., 9, 1229–1249, https://doi.org/10.5194/wes-9-1229-2024, https://doi.org/10.5194/wes-9-1229-2024, 2024
Short summary
Short summary
Movable surfaces on wind turbine (WT) blades, called active flaps, can reduce the cost of wind energy. However, they still need extensive testing. This study shows that the computer model used to design a WT with flaps aligns well with measurements obtained from a 3month test on a commercial WT featuring a prototype flap. Particularly during flap actuation, there were minimal differences between simulated and measured data. These findings assure the reliability of WT designs incorporating flaps.
Ruben Borgers, Marieke Dirksen, Ine L. Wijnant, Andrew Stepek, Ad Stoffelen, Naveed Akhtar, Jérôme Neirynck, Jonas Van de Walle, Johan Meyers, and Nicole P. M. van Lipzig
Wind Energ. Sci., 9, 697–719, https://doi.org/10.5194/wes-9-697-2024, https://doi.org/10.5194/wes-9-697-2024, 2024
Short summary
Short summary
Wind farms at sea are becoming more densely clustered, which means that next to individual wind turbines interfering with each other in a single wind farm also interference between wind farms becomes important. Using a climate model, this study shows that the efficiency of wind farm clusters and the interference between the wind farms in the cluster depend strongly on the properties of the individual wind farms and are also highly sensitive to the spacing between the wind farms.
Javier Criado Risco, Rafael Valotta Rodrigues, Mikkel Friis-Møller, Julian Quick, Mads Mølgaard Pedersen, and Pierre-Elouan Réthoré
Wind Energ. Sci., 9, 585–600, https://doi.org/10.5194/wes-9-585-2024, https://doi.org/10.5194/wes-9-585-2024, 2024
Short summary
Short summary
Wind energy developers frequently have to face some spatial restrictions at the time of designing a new wind farm due to different reasons, such as the existence of protected natural areas around the wind farm location, fishing routes, and the presence of buildings. Wind farm design has to account for these restricted areas, but sometimes this is not straightforward to achieve. We have developed a methodology that allows for different inclusion and exclusion areas in the optimization framework.
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.
Daniel Ribnitzky, Frederik Berger, Vlaho Petrović, and Martin Kühn
Wind Energ. Sci., 9, 359–383, https://doi.org/10.5194/wes-9-359-2024, https://doi.org/10.5194/wes-9-359-2024, 2024
Short summary
Short summary
This paper provides an innovative blade design methodology for offshore wind turbines with very large rotors compared to their rated power, which are tailored for an increased power feed-in at low wind speeds. Rather than designing the blade for a single optimized operational point, we include the application of peak shaving in the design process and introduce a design for two tip speed ratios. We describe how enlargement of the rotor diameter can be realized to improve the value of wind power.
Rafael Valotta Rodrigues, Mads Mølgaard Pedersen, Jens Peter Schøler, Julian Quick, and Pierre-Elouan Réthoré
Wind Energ. Sci., 9, 321–341, https://doi.org/10.5194/wes-9-321-2024, https://doi.org/10.5194/wes-9-321-2024, 2024
Short summary
Short summary
The use of wind energy has been growing over the last few decades, and further increase is predicted. As the wind energy industry is starting to consider larger wind farms, the existing numerical methods for analysis of small and medium wind farms need to be improved. In this article, we have explored different strategies to tackle the problem in a feasible and timely way. The final product is a set of recommendations when carrying out trade-off analysis on large wind farms.
Aiguo Zhou, Jinlei Shi, Tao Dong, Yi Ma, and Zhenhui Weng
Wind Energ. Sci., 9, 49–64, https://doi.org/10.5194/wes-9-49-2024, https://doi.org/10.5194/wes-9-49-2024, 2024
Short summary
Short summary
This paper explores the nonlinear influence of the virtual mass mechanism on the test system in blade biaxial tests. The blade theory and simulation model are established to reveal the nonlinear amplitude–frequency characteristics of the blade-virtual-mass system. Increasing the amplitude of the blade or decreasing the seesaw length will lower the resonance frequency and load of the system. The virtual mass also affects the blade biaxial trajectory.
Xiaodong Zhang and Nikolay Dimitrov
Wind Energ. Sci., 8, 1613–1623, https://doi.org/10.5194/wes-8-1613-2023, https://doi.org/10.5194/wes-8-1613-2023, 2023
Short summary
Short summary
Wind turbine extreme response estimation based on statistical extrapolation necessitates using a small number of simulations to calculate a low exceedance probability. This is a challenging task especially if we require small prediction error. We propose the use of a Gaussian mixture model as it is capable of estimating a low exceedance probability with minor bias error, even with limited simulation data, having flexibility in modeling the distributions of varying response variables.
Arne Bartschat, Karsten Behnke, and Matthias Stammler
Wind Energ. Sci., 8, 1495–1510, https://doi.org/10.5194/wes-8-1495-2023, https://doi.org/10.5194/wes-8-1495-2023, 2023
Short summary
Short summary
Blade bearings are among the most stressed and challenging components of a wind turbine. Experimental investigations using different test rigs and real-size blade bearings have been able to show that rather short time intervals of only several hours of turbine operation can cause wear damage on the raceways of blade bearings. The proposed methods can be used to assess wear-critical operation conditions and to validate control strategies as well as lubricants for the application.
Juan-Andrés Pérez-Rúa, Mathias Stolpe, and Nicolaos Antonio Cutululis
Wind Energ. Sci., 8, 1453–1473, https://doi.org/10.5194/wes-8-1453-2023, https://doi.org/10.5194/wes-8-1453-2023, 2023
Short summary
Short summary
With the challenges of ensuring secure energy supplies and meeting climate targets, wind energy is on course to become the cornerstone of decarbonized energy systems. This work proposes a new method to optimize wind farms by means of smartly placing wind turbines within a given project area, leading to more green-energy generation. This method performs satisfactorily compared to state-of-the-art approaches in terms of the resultant annual energy production and other high-level metrics.
Andrew P. J. Stanley, Christopher J. Bay, and Paul Fleming
Wind Energ. Sci., 8, 1341–1350, https://doi.org/10.5194/wes-8-1341-2023, https://doi.org/10.5194/wes-8-1341-2023, 2023
Short summary
Short summary
Better wind farms can be built by simultaneously optimizing turbine locations and control, which is currently impossible or extremely challenging because of the size of the problem. The authors present a method to determine optimal wind farm control as a function of the turbine locations, which enables turbine layout and control to be optimized together by drastically reducing the size of the problem. In an example, a wind farm's performance improves by 0.8 % when optimized with the new method.
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.
Nicholas Peters, Christopher Silva, and John Ekaterinaris
Wind Energ. Sci., 8, 1201–1223, https://doi.org/10.5194/wes-8-1201-2023, https://doi.org/10.5194/wes-8-1201-2023, 2023
Short summary
Short summary
Wind turbines have increasingly been leveraged as a viable approach for obtaining renewable energy. As such, it is essential that engineers have a high-fidelity, low-cost approach to modeling rotor load distributions. In this study, such an approach is proposed. This modeling approach was shown to make high-fidelity predictions at a low computational cost for rotor distributed-pressure loads as rotor geometry varied, allowing for an optimization of the rotor to be completed.
Paul Veers, Carlo L. Bottasso, Lance Manuel, Jonathan Naughton, Lucy Pao, Joshua Paquette, Amy Robertson, Michael Robinson, Shreyas Ananthan, Thanasis Barlas, Alessandro Bianchini, Henrik Bredmose, Sergio González Horcas, Jonathan Keller, Helge Aagaard Madsen, James Manwell, Patrick Moriarty, Stephen Nolet, and Jennifer Rinker
Wind Energ. Sci., 8, 1071–1131, https://doi.org/10.5194/wes-8-1071-2023, https://doi.org/10.5194/wes-8-1071-2023, 2023
Short summary
Short summary
Critical unknowns in the design, manufacturing, and operation of future wind turbine and wind plant systems are articulated, and key research activities are recommended.
Kisorthman Vimalakanthan, Harald van der Mijle Meijer, Iana Bakhmet, and Gerard Schepers
Wind Energ. Sci., 8, 41–69, https://doi.org/10.5194/wes-8-41-2023, https://doi.org/10.5194/wes-8-41-2023, 2023
Short summary
Short summary
Leading edge erosion (LEE) is one of the most critical degradation mechanisms that occur with wind turbine blades. A detailed understanding of the LEE process and the impact on aerodynamic performance due to the damaged leading edge is required to optimize blade maintenance. Providing accurate modeling tools is therefore essential. This novel study assesses CFD approaches for modeling high-resolution scanned LE surfaces from an actual blade with LEE damages.
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.
Alessandro Bianchini, Galih Bangga, Ian Baring-Gould, Alessandro Croce, José Ignacio Cruz, Rick Damiani, Gareth Erfort, Carlos Simao Ferreira, David Infield, Christian Navid Nayeri, George Pechlivanoglou, Mark Runacres, Gerard Schepers, Brent Summerville, David Wood, and Alice Orrell
Wind Energ. Sci., 7, 2003–2037, https://doi.org/10.5194/wes-7-2003-2022, https://doi.org/10.5194/wes-7-2003-2022, 2022
Short summary
Short summary
The paper is part of the Grand Challenges Papers for Wind Energy. It provides a status of small wind turbine technology in terms of technical maturity, diffusion, and cost. Then, five grand challenges that are thought to be key to fostering the development of the technology are proposed. To tackle these challenges, a series of unknowns and gaps are first identified and discussed. Improvement areas are highlighted, within which 10 key enabling actions are finally proposed to the wind community.
Mads H. Aa. Madsen, Frederik Zahle, Sergio González Horcas, Thanasis K. Barlas, and Niels N. Sørensen
Wind Energ. Sci., 7, 1471–1501, https://doi.org/10.5194/wes-7-1471-2022, https://doi.org/10.5194/wes-7-1471-2022, 2022
Short summary
Short summary
This work presents a shape optimization framework based on computational fluid dynamics. The design framework is used to optimize wind turbine blade tips for maximum power increase while avoiding that extra loading is incurred. The final results are shown to align well with related literature. The resulting tip shape could be mounted on already installed wind turbines as a sleeve-like solution or be conceived as part of a modular blade with tips designed for site-specific conditions.
Edward Hart, Adam Stock, George Elderfield, Robin Elliott, James Brasseur, Jonathan Keller, Yi Guo, and Wooyong Song
Wind Energ. Sci., 7, 1209–1226, https://doi.org/10.5194/wes-7-1209-2022, https://doi.org/10.5194/wes-7-1209-2022, 2022
Short summary
Short summary
We consider characteristics and drivers of loads experienced by wind turbine main bearings using simplified models of hub and main-bearing configurations. Influences of deterministic wind characteristics are investigated for 5, 7.5, and 10 MW turbine models. Load response to gusts and wind direction changes are also considered. Cubic load scaling is observed, veer is identified as an important driver of load fluctuations, and strong links between control and main-bearing load response are shown.
Cited articles
Buster, G., Rossol, M., Pinchuk, P., Benton, B. N., Spencer, R., Bannister, M., and Williams, T.: NREL/reV: reV 0.8.0 (v0.8.0), Zenodo [code], https://doi.org/10.5281/zenodo.8247528, 2023.
DOE (U.S. Department of Energy Office of Energy Efficiency and Renewable Energy): Renewable energy resource assessment information for the United States, https://www.energy.gov/eere/analysis/renewable-energy-resource-assessment-information-united-states (last access: 20 October 2024), 2024.
Gagnon, P., Frazier, W., Hale, E., and Cole, W.: Cambium data for 2020 Standard Scenarios, National Renewable Energy Laboratory Scenario Viewer [data set], https://cambium.nrel.gov (last access: 1 November 2024), 2020.
Garcia-Castellanos, D. and Lombardo, U.: Poles of inaccessibility: A calculation algorithm for the remotest places on earth, Scott. Geogr. J., 123, 227–233, https://doi.org/10.1080/14702540801897809, 2007.
HIFLD (Homeland Infrastructure Foundation-Level Data): Parcels of the United States, LightBox [data set], https://www.lightboxre.com/data/ (last access: 1 November 2024), 2019.
Lantz, E., Sigrin, B., Gleason, M., Preus, R., and Baring-Gould, I.: Assessing the future of distributed wind: Opportunities for behind-the-meter projects. National Renewable Energy Laboratory, Golden, CO, NREL/TP-6A20-67337, https://www.nrel.gov/docs/fy17osti/67337.pdf (last access: 16 September 2024), 2016.
Lopez, A., Mai, T., Lantz, E., Harrison-Atlas, D., Williams, T., and Maclaurin, G.: Land use and turbine technology influences on wind potential in the United States, Energy, 223, 120044, https://doi.org/10.1016/j.energy.2021.120044, 2021.
Maclaurin, G., Draxl, C., Hodge, B., and Rossol, M.: Wind Integration National Dataset (WIND) Toolkit, Open Energy Data Initiative (OEDI), National Renewable Energy Laboratory [data set], https://doi.org/10.25984/1822195, 2014.
Maclaurin, G. J., Grue, N. W., Lopez, A., J., Heimiller, D. M., Rossol, M., Buster, G., and Williams, T.: The renewable energy potential (reV) model: A geospatial platform for technical potential and supply curve modeling, National Renewable Energy Laboratory, Golden, CO, NREL/TP-6A20-73067, https://doi.org/10.2172/1563140, 2019.
McCabe, K., Prasanna, A., Lockshin, J., Bhaskar, P., Bowen, T., Baranowski, R., Sigrin, B., and Lantz, E.: Distributed wind energy futures study, National Renewable Energy Laboratory, Golden, CO, NREL/TP-7A40-82519, https://www.nrel.gov/docs/fy22osti/82519.pdf (last access: 1 November 2024), 2022.
McDermott, T. E., McKenna, K., Heleno, M., Bhatti, B. A., Emmanuel, M., and Forrester, S.: Distribution system research roadmap: energy efficiency and renewable energy, Pacific Northwest National Laboratory, Richland, WA, PNNL-31580, https://www.osti.gov/servlets/purl/1843579 (last access: 20 October 2024), 2022.
Microsoft: U.S. Building Footprints, GitHub [data set], https://github.com/microsoft/USBuildingFootprints (last access: 1 November 2024), 2019.
NASA (National Aeronautics and Space Administration): Shuttle Radar Topography Mission, Earth Observing System Project Science Office [data set], https://eospso.nasa.gov/missions/shuttle-radar-topography-mission (last access: 1 November 2024), 2018.
NASS (National Agricultural Statistics Service): CroplandCROS (Cropland Data Layer), United States Department of Agriculture [data set]: https://croplandcros.scinet.usda.gov/ (last access: 1 November 2024), 2023.
NCSU (North Carolina State University): Database of State Incentives for Renewables & Efficiency (DSIRE), NC Clean Energy Technology Center [data set], https://www.dsireusa.org/ (last access: 1 November 2024), 2021.
Ong, S. and Clark, N.: Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States, Open Energy Data Initiative (OEDI), National Renewable Energy Laboratory [data set], https://doi.org/10.25984/1788456, 2014.
Phillips, C. and Lockshin, J.: Distributed wind, U.S. Department of Energy Atmosphere to Electrons, Wind Data Hub [data set], https://wdh.energy.gov/project/dw (last access: 27 June 2025), 2024.
Rickerson, W., Gillis, J., and Bulkeley, M.: The value of resilience for distributed energy resources: an overview of current analytical practices, National Renewable Energy Laboratory, Golden, CO, NREL/SR-7A40-90139, https://www.nrel.gov/docs/fy24osti/90139.pdf (last access: 24 September 2024), 2024.
Sheridan, L., Kazimierczuk, K., Garbe, J., and Preziuso, D.: Distributed wind market report: 2024 edition, Pacific Northwest National Laboratory, Richland, WA, PNNL-36057, https://www.pnnl.gov/main/publications/external/technical_reports/PNNL-36057.pdf (last access: 24 November 2024), 2024.
Sigrin, B., Gleason, M., Preus, R., Baring-Gould, I., and Margolis, R.: The distributed generation market demand model (dGen): Documentation. National Renewable Energy Laboratory, Golden, CO, NREL/TP-6A20-65231, http://www.nrel.gov/docs/fy16osti/65231.pdf (last access: 1 September 2024), 2016.
Stehly, T. and Duffy, P.: 2021 cost of wind energy review, National Renewable Energy Laboratory, Golden, CO, NREL/PR-5000-84774, https://doi.org/10.2172/1907623, 2022.
U.S. Census Bureau: TIGER/Line Shapefiles, U.S. Department of Commerce [data set], https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.html (last access: 1 November 2024), 2020.
USDA (United States Department of Agriculture): Rural Energy for America Program (REAP), Rural Development [data set], https://eligibility.sc.egov.usda.gov/eligibility/ (last access: 1 November 2024), 2023.
USGS (United States Geological Survey): NLCD Tree Canopy Cover of CONUS, Multi-Resolution Land Characteristics Consortium [data set], https://mrlc.gov/data/nlcd-2011-tree-canopy-cover-conus (last access: 1 November 2024), 2011.
Ventyx: Energy Velocity Suite, Hitachi Energy [data set], https://www.hitachienergy.com/us/en/products-and-solutions/energy-portfolio-management/market-intelligence-services/velocity-suite (last access: 1 November 2024), 2020.
Zimny-Schmitt, D. and Huggins, J.: Utility Rate Database (URDB), Open Energy Data Initiative (OEDI), National Renewable Energy Laboratory [data set], https://openei.org/wiki/Utility_Rate_Database (last access: 1 November 2024), 2020.
Short summary
This study examines the potential for distributed wind energy across the contiguous United States by leveraging a novel modeling approach that utilizes a high-resolution dataset and analyzes over 150 million parcels. Modeling results reveal substantial opportunities for energy generation using distributed wind technologies. Additionally, findings reveal a substantial increase from prior modeling results in estimated technical and economic potential for distributed wind.
This study examines the potential for distributed wind energy across the contiguous United...
Special issue
Altmetrics
Final-revised paper
Preprint