NREL&#8217;s Steve Hammond, director of the Computational Science Center, and Kenny Gruchalla, senior scientist, discuss a 3D model of wind plant



An industry-wide concern


The market for wind energy continues to grow -- and so do the wind turbines and farms themselves. Unfortunately, the power production of these energy plants has, in many cases, been lower than initially predicted. Wind plant underperformance has become a concern throughout the wind industry and could potentially cost developers millions of dollars over the life of a wind plant because of reduced power generation and increased maintenance costs.

"The wind industry is increasingly concerned with these underperformance issues," said Pat Moriarty, senior engineer at NREL's National Wind Technology Center. "The average underperformance is about 10 percent, with some seeing underperformance as high as 30 percent to 40 percent. This adds up to a lot of lost energy and high cost for the industry over the life of a wind plant and presents us with a big opportunity to improve wind plant efficiencies."

Models enhance understanding of performance issues



"Previous models were very simple and don't capture a lot of the physics -- how the atmosphere behaves and how wind turbines respond to changing conditions in the field," Moriarty said. "It was clear that we needed better models, specifically understanding issues around wake-turbine and atmosphere-turbine interactions."

Good models need good data. Data from operating wind farms provides validation for the models. So the project has been collecting data from offshore and onshore wind farms in both Europe and the United States to compare to the simulations. "We're comparing the data from actual wind turbine performance in the field to the predictions from our models," Moriarty said. "The models have been very accurate and very close to what is actually happening in the field."

Big computers facilitating big ideas


Researchers are currently using RedMesa, NREL's most powerful high-performance computing system, located at DOE's Sandia National Laboratories and managed in collaboration with Sandia. Peak computational capability of RedMesa is about 180 teraflops, which means it can process 180 trillion floating point operations (flops) per second. For comparison, a basic calculator requires only 10 flops.

NREL will be adding additional high-performance computing capability in the next year with a new supercomputer on the lab's Golden, Colorado, campus. The supercomputer in NREL's new Energy Systems Integration Facility (ESIF) will be nearly a petaflop in scale (a petaflop is 1,000 teraflops) and will be the fastest computer system in the world dedicated to renewable energy and energy efficiency technologies.

Building a better wind farm

One anticipated outcome of this enhanced simulation and modeling capability is improved understanding by wind plant developers of how to lay out their projects to achieve maximum performance from individual turbines. Issues to consider include placement of turbines in a wind farm, spacing between turbines, and how terrain and other location-specific conditions might impact turbine performance. Improved tools for wind plant design will enable improved physical understanding of turbine interactions and ultimately lead to plant designs with higher energy production and lower maintenance costs.


A wind turbine getting beat up by wakes may have higher maintenance costs. This increases costs for the wind plant operator as well as the cost of wind energy in general."

The wind farm as a system, not the sum of its parts

Another benefit to using these tools is in the area of "wind farm controls." This concept -- a hot topic of discussion in the industry today -- involves looking at a wind farm as a total system rather than just a collection of wind turbines. It explores how to best operate that system in a manner that leads to maximum efficiency for the wind farm as a whole.



The concept is to view wind farms from a global controls perspective and to seek ways to operate the wind farm as a total system. These types of controls improvements hold great potential for making wind farms more efficient and more productive. Modeling capabilities can be used to study how to operate a wind farm to optimize the energy capture of the entire plant instead of just looking at individual turbines. This capability could be applied to both onshore and offshore wind plants already in operation, as well as new developments.

Leading the way to lower-cost wind energy

This work will create a better understanding of wind farm performance and will allow wind developments to be designed to maximize performance through increased energy capture and reduced maintenance costs -- all of which leads to lower-cost wind energy.

"This capability is of significant importance for various segments of the wind industry -- manufacturers, developers, and operators," Moriarty said. "It provides science behind wind energy that is beneficial to all in their roles toward expanding the deployment of wind energy and reducing costs."