Distributed Wind Aeroelastic Modeling

Through the Distributed Wind Aeroelastic Modeling (dWAM) project, NREL researchers are helping provide the distributed wind energy industry with better tools to model, validate, and certify improved wind turbine designs.

A small wind turbine towers over a field, forest, and barn on a farm.
The Distributed Wind Aeroelastic Modeling project helps improve the tools used to design small-scale wind turbines for distributed energy systems at farms, communities, or homes, like this one in Kansas. Photo from Eocycle Technologies

To ensure distributed wind turbines are resilient, stable, and high performing, new designs undergo an evaluation to check loads on the turbine components and results of field testing. Before building a costly prototype for testing, turbine designers can use aeroelastic modeling to see how a turbine will function when subjected to winds over its lifetime. Aeroelastic models simulate airflow and turbine behavior for land-based and offshore wind turbine designs. These models have been modified for small- and medium-sized wind turbines used in distributed wind energy applications, providing on-site power for farms, houses, and communities.

Through the dWAM project, which is funded by the U.S. Department of Energy's Wind Energy Technologies Office, NREL researchers, along with collaborators at Sandia National Laboratories and several industry companies, are working to improve aeroelastic modeling for distributed wind turbines. Their goal is to provide the tools turbine suppliers need to design and certify optimized and reliable small- and medium-sized wind turbines with competitive costs of energy.

Project Approach

In this 2-year project, researchers will work to improve the physics of models for several types of distributed wind turbine designs (called archetypes), including both horizontal- and vertical-axis wind turbines, many of which are part of the NREL Competitiveness Improvement Project.

Passive-yaw, upwind, stall horizontal-axis wind turbine wind turbine model

A: Bergey Excel 15
Passive-yaw, upwind, stall-regulated, horizontal-axis wind turbine. Photo from Bergey WIndpower Co.

Passive-yaw, downwind, stall horizontal-axis wind turbine wind turbine by ocean

B: Eocycle EOX M-26
Passive yaw, downwind, stall-regulated, horizontal-axis wind turbine. Photo from Eocycle Technologies

Active-yaw, upwind, stall horizontal-axis wind turbine wind turbine in field

Active-yaw, upwind, stall-regulated, horizontal-axis wind turbine. Photo from QED Wind Power

Three modern distributed wind turbines (A, B, and C), 
coming to NREL's Distributed Integrated Energy Laboratory at Flatirons Campus under the Flatirons Distributed Wind Turbine Installation project, will serve as the baseline for new reference turbines and for model validation.

Pika T701 wind turbine model

D: Pika T701
NREL has reinstalled the Pika T701 at Flatirons Campus as a second turbine for tail-vane modeling validation. Photo from Pika Energy, Inc.

Xflow turbine prototype in field

E: XFlow Energy
XFlow has installed a prototype 25-kW vertical-axis wind turbine at Windward Engineering's test facility in Spanish Fork, Utah, for vertical-axis wind turbine model validation. Photo from XFlow Energy

They will then create validated advanced reference turbines for the top archetypes used in distributed applications.

Once validated, the team will update the tools for improved user experience (such as by revising documentation for NREL's OpenFAST).

Through this project, researchers hope to enable industry adoption of the upgraded modeling tools to develop certified wind turbines that perform better, are more reliable, and generate energy at a lower cost, with the goal of accelerating distributed wind energy deployment across the United States.

Project Components

To reach the project's goals throughout 2023 and 2024, researchers will:

Models of horizontal- and vertical-axis wind turbines
NREL and Sandia National Laboratories researchers are working with industry partners to improve modeling tools to validate better-performing, more reliable, and lower-cost distributed wind turbines. Images by Besiki Kazaishvili, NREL
  • Focus on modern, horizontal-axis archetypes
  • Improve OpenFAST code
  • Validate code improvements using research turbines at NREL's Flatirons Campus
  • Verify that the results from different modeling tools agree
  • Develop guidance documents and improved user manuals.

To address vertical-axis wind turbine modeling, the team will:

  • Improve modeling code and user experience in collaboration with Sandia National Laboratories
  • Couple Sandia National Laboratories' Offshore Wind Energy Simulator code and NREL's OpenFAST and AeroDyn software tools.

To improve automated Campbell diagram capabilities, the team will:

  • Develop a streamlined, documented, and automated procedure to generate a Campbell diagram (which charts the turbine's response to vibration stress at various levels of operation)
  • Aid in turbines meeting the certification requirements in International Electrotechnical Commission standards.

And finally, to launch the improved tools, the team will:

  • Develop guidance on distributed wind turbine modeling
  • Host an industry workshop to better understand real-world field failures of distributed wind turbines.


Modeling the Yaw Behavior of Tail Fins for Small Wind Turbines: November 22, 2021–May 21, 2024, NREL Technical Report (2023)

Distributed Wind Aeroelastic Modeling Fact Sheet, NREL Fact Sheet (2023)

Distributed Wind Aeroelastic Modeling Presentation, Distributed Wind National Laboratory–Industry Discussion (2023)

Aeroelastic Modeling for Distributed Wind Turbines, NREL Technical Report (2022)


Partners on this project include:

  • Sandia National Laboratories
  • Technical University of Denmark
  • RRD Engineering
  • Windward Engineering
  • Advanced Renewable Technology
  • Bergey Windpower Co.
  • QED Wind Power
  • Eocycle Americas
  • XFlow Energy Co.
  • University of Calgary
  • University of Massachusetts Amherst.


Brent Summerville

Distributed Wind Energy Systems Engineer