Any way the wind blows

Los Alamos scientists develop computer modeling capabilities to predict wind turbine success.

By Jill Gibson | November 29, 2023

Nss Winter 2023   Wind Blows   Body
Los Alamos research helps predict whether wind turbines, such as this one located close to a building, can be effective despite possible obstructions. Dreamstime

Los Alamos National Laboratory research and development engineer Matt Nelson wouldn’t say his job is a breeze, but he does spend a great deal of time considering which way the wind blows. That’s because Nelson’s work focuses on predicting the viability of small wind turbines so that individuals, businesses, and communities can make informed decisions about where such turbines will work to serve on-site energy needs.

Nelson is part of a project team led by the National Renewable Energy Laboratory (NREL). “We have developed tools that help people predict the potential for small-scale wind projects,” Nelson says. Using a computer modeling program called Quick Urban & Industrial Complex (QUIC) integrated into NREL’s Tools for Assessing Performance (TAP) framework, Nelson can determine whether any obstructions, such as buildings or trees, will slow wind before it reaches a turbine. “By repurposing code originally developed for counterterrorism, we have created an affordable tool for the wind industry that can run in a few minutes on a laptop,” he says. “There are definite challenges for the wind industry, and often you are dependent on whatever Mother Nature gives you. We are trying to prevent bad information and bad decisions to make wind energy more predictable and affordable.”

Nelson notes that TAP is used for “distributed wind” projects, which are typically small in size, number of turbines, and budget. Distributed wind turbines are usually located close to where the energy is used and can be situated alone or grouped to meet larger energy needs. Individuals and companies considering small wind turbines rarely have the funds to construct meteorological towers to measure wind speeds. That’s where TAP comes in. 

“We’re using machine learning to train our fast-running models based on a suite of high-fidelity simulations and validating it with field experiments,” notes Nelson. “When it comes to wind modeling, there are lots of variables and many parameters that must be addressed to include varying speeds, directions, and thermal conditions.”

Nelson points out that the Lab has drawn on its computational and atmospheric science expertise, supercomputing capabilities, and ongoing work with wind flow and contaminant dispersal to develop what will become an online portal that will provide the wind industry with much-needed data. “Our work in national security has helped develop new tools for energy security,” says Nelson, adding that “energy security ensures national security, too.”

“If we can find an economically viable way to harness the wind, it’s a piece of solving the energy puzzle that we shouldn’t blow off.” ★