Wind energy: The feasible path to sustainable energy

By Samuel Moss

As the world continually seeks alternatives to large carbon footprint energy sources, the demand for efficient renewable energy continues to increase. In the United States, 7% of current energy comes from wind power, and Dr. Paul Veers, a chief engineer at the National Renewable Energy Lab (NREL), believes that wind power can feasibly increase over 50%. Veers discussed the current status of acquiring energy from wind as well as its future directions in his seminar “Wind Energy Modeling and Simulation: the amazing interrelationships of physics and engineering in wind plant design” on February 7, 2020 at the University of Wisconsin–Madison’s Mechanics Seminar.

One common misconception about wind energy is that it cannot compete with other sources of renewable energy such as solar power. In reality, wind energy is currently outperforming solar energy in the U.S. market as solar power only accounts for 2% of total energy production. Wind energy can be harvested around the clock and, by analyzing wind patterns created by geographical and meteorological features, wind turbine plants can be set up to efficiently generate energy. This is commonly done with mesosphere modeling where a large area of terrain interacts with common weather patterns in the region.

Simulations are also run on single turbines by modeling the air as a fluid mesh around the rotating turbine. These mesh sizes become extremely fine in the areas nearest the turbine, on the scale of less than a meter. One large gap in knowledge, identified by Veers, is the information on a scale between these two types of simulations. This is where Veers and NREL are focusing the majority of their research. They believe that the key to making wind energy more efficient is to understand how wind turbines in proximity to each other can benefit the total energy output of a wind turbine plant.

For example, using consensus control monitoring, the wind turbine controllers can make decisions as a collective group instead of as individual. They do this by sharing their information with each other and collaborating to form a general consensus. This collective decision making allows for easy detection of broken sensors, more accurate determination of wind directions, as well as prediction of when and where the wind will change directions allowing for the more optimal harvesting of wind energy.

The relative placement of wind turbines to each other can also affect the energy output from a wind plant. Using computer simulations, it was discovered that by slightly offsetting a series of wind turbines, the overall wind capturing ability of the series increased in comparison to a series of wind turbines that are in line with the dominant wind direction. This increase in the wind harvesting ability was not the same across each turbine, and some of the individual turbines decreased in energy output, but the series of turbines as a whole increased their output because of the offset.

By utilizing various simulation software, wind turbines can be analyzed and optimized as a collective instead of as individual machines. Combine this data with mesosphere and single wind turbine simulations, wind turbines can be optimized on an environmental, collective, and individual scale. This collaboration of data will allow for wind energy to propel itself forward and grow in its ability to meet energy needs in the United States.