The Challenge
Wind energy, particularly offshore wind, needs to radically scale up to meet renewable energy needs. As this scale up is happening, the sustainability, equity, efficiency, and reliability of these new wind farms also needs to be assured. Large improvements in efficiency can radically increase the amount of reliance society places in these new power sources, while even small advancements can lead to big savings in terms of embodied carbon. How can we support rapid adoption, while embracing societal equity issues in that adoption in parallel with improved engineering solutions for efficiency, reliability, and sustainability? These inter-connected issues drive ROSEI’s efforts in the wind energy field.
An Initiative Completed
On May 21, 2025 a free, comprehensive, public wind farm database developed through ROSEI was released.
A multi-year effort led by two of ROSEI’s leaders in its wind pillar Dennice Gayme and Charles Meneveau, the Johns Hopkins Turbulence Databases – Wind (JHTDB-wind) provides massive amounts of data from computer simulations of turbulent flow in wind turbine arrays to help in wind farm design, analysis and operational increases to power output. The publicly available resource supports everything from academic studies to practical wind farm planning and development projects.
The Datasets
JHTDB-wind is currently comprised of two datasets. The first, titled “LES of large wind farm under conventionally neutral atmospheric conditions,” simulates a large wind farm under conditions where temperature differences across different heights in the atmosphere are negligibly small such as during sunset or on cloudy days. It functions as a baseline in terms of the atmospheric conditions.
“This set serves as a good general baseline so users can see how wind turbines in a big farm interact with each other under minimal effects from atmospheric stability conditions,” said Gayme.
The second dataset, titled “LES of large wind farm during a diurnal cycle,” simulates a smaller wind farm over 24 hours. During daylight, the sun heats the ground, creating convective conditions with rising air plumes that generate turbulence and interact with wind farms. At nighttime, temperatures drop, causing colder air to drift downward, reducing turbulence.
“If someone is particularly interested in a warm or cold part of the day, they can pinpoint those times and find the information they want,” Meneveau said.
Fostering Collaboration
JHTDB-wind enables people to study wind farm flows and run small programs that calculate averages or extreme conditions, plotting data points without needing to keep data locally or downloading files. Being able to do all of this work on a publicly available database will also help foster collaborations that have previously been challenging in the research area.
“One of the problems in this field has been that people run massive computer simulations of turbulent flow in wind farms; a couple of papers get written by the people doing the simulations, and little else is done. These datasets are so large that it is difficult to share with others via traditional methods, limiting the potential broader impact of the data,” said Meneveau. “What we are doing instead is storing the data in a database, so that anyone can access it through the JHTDB-wind website using tools that we have developed to enable the data to stream directly into analysis programs. We’re hoping this will help bridge the previous gaps in shared knowledge that have plagued this research area.”
JHTDB-wind itself is a collaboration, as the site was created in tandem with the Institute for Data Intensive Engineering and Science (IDIES). The access tools leverage those currently in use to access over a petabyte of data for fundamental studies of turbulent flows.
Looking Ahead to Offshore Wind with Further Support from ROSEI
Meneveau and Gayme are collaborating with Julie Lundquist, the Bloomberg Distinguished Professor of Atmospheric Science and Wind Energy, to add datasets to JHTDB-wind that involve offshore wind farms, which bring complicating factors such as wave motions, and possibly turbine motion if they are placed on floating platforms. They will also explore the effect of very large turbines that reach high up and span various regions of the atmosphere.
“Including offshore options is essential for the next generation of wind farms because there is so much potential for wind and space in open waters,” Gayme said. “Charles, Julie and I are still very early in creating the set for that one, but the work is being supported by a new ROSEI SPARK award, and we are considering including a dataset that mimics conditions of a specific site off the coast of New England that has been targeted for a potential offshore wind farm.”
Key Partnerships
- Institute for Data Intensive Engineering and Science (IDIES)
- Department of Mechanical Engineering
- European Academy of Wind Energy (EAWE)
- Business Network for Offshore Wind (BNOW)
Press
The Streaming Service for Wind Energy: Hopkins Database Powers Wind Farm Research, ROSEI Website
New Project will Lay Groundwork for Open Access to Massive Windfarm Simulations, The Hub
ROSEI Affiliated Researcher Q&A: Dennice Gayme, ROSEI Website
Additional ROSEI Efforts in Wind Energy
In addition to the fundamental fluid mechanics and control, ROSEI researchers are working on grid integration of wind energy, unique carbon capture ideas utilizing wind farms, operational reliability of offshore wind farms, and fundamental efficiency and reliability of wind turbine structures. Along with our partners, ROSEI aims to be a key contributor to the equitable and successful adoption of wind energy.
