Despite the many technological advancements made in upgrading wind-powered systems, finding a reliable way to assess competing technologies continues to be a challenge. In a new study, researchers at Texas A&M use advanced data science methods to compare the performance of different wind turbine designs.
“Currently, there is no method to validate if a newly created technology will increase wind energy production and efficiency by a certain amount,” said Dr. Yu Ding. “In this study, we provided a practical solution to a problem that has existed in the wind industry for quite some time.”
As of 2020, about 8.4% of all electricity produced in the United States came from wind energy. The Department of Energy plans to increase the footprint of wind energy to 20% in the coming decade.
As a result, there has been a surge of novel technologies, particularly to the blades. These upgrades promise an improvement in the performance of wind turbines and power production. However, testing whether these quantities will go up is arduous.
The team collaborated with an industry that owns inland wind farms to collect their data. These machines were fitted with sensors to track power produced, wind speeds, wind directions and temperature. The researchers collected data over four-and-a-half years, and the turbines received three technological upgrades.
Using an advanced data comparison methodology that Ding developed with Dr. Rui Tuo, the team reduced the uncertainty in quantifying improvements in wind turbine performance.