Wind power is a source of energy that is both affordable and renewable.
McGill University
However, decision-makers have been reluctant to invest in
wind energy due to a perception that wind farms require a lot of land compared
to electric power plants driven by fossil fuels. Research led by McGill
University and based on the assessment of the land-use of close to 320 wind
farms in the U.S. (the largest study of its kind) paints a very different
picture.
Misplaced preconceptions about the land use of gas-fueled
electricity
The study, which was published recently in Environmental Science and Technology, shows that, when calculations are made, the entire wind farm area is usually considered as land given over to wind development.
The research also shows that if wind turbines are sited
in areas with existing roads and infrastructure, such as on agricultural land,
they can be approximately seven times more efficient, in terms of energy
produced per square metre of land directly impacted by the infrastructure, than
projects that are developed from scratch.
“The land use of wind farms has often been viewed as among the predominant challenges to wind development,” explains Sarah Jordaan, an associate professor in the Department of Civil Engineering at McGill and the senior author on the study.
“But, by
quantifying the land area used by nearly 16,000 wind turbines in the western
U.S., we found that gas-fired generation offers no real benefits in terms of
lesser land use when the infrastructures, including all the wells, pipelines,
and roads associated with the natural gas supply chain, are considered.”
A new approach to future energy technology assessments
It has been difficult to get a clear picture of the land
use associated with wind power in the U.S. until now because earlier studies
only looked at the infrastructure associated with wind energy and land use on a
relatively small scale, making it difficult to extrapolate from their results.
Other studies have relied on estimates of the entire wind farm, rather than the
land directly impacted by the infrastructure.
By combining information gathered through GIS (geographic information systems) with machine learning models developed using nearly 2000 images of wind farms from the American portion of the Western Interconnection (which provides electricity to 14 states in the U.S. as well as to portions of Canada and Mexico), the researchers were able to train a deep learning model to analyze land use in wind farms.
By doing so, they were able to assess a range
of factors (placement of turbines, pre-existing roads, age of turbines, etc.)
that contribute to the land directly impacted by wind infrastructure.
“The method we have developed is potentially useable for
future assessments of various energy technologies, whether in terms of
environmental impact analysis or energy systems planning for net zero
emissions,” adds Jordaan. “In fact, it sets the stage for the first consistent
comparisons of environmental sustainability across different energy
technologies in future.”
The study
“Land Resources for Wind Energy Development Requires
Regionalized Characterizations” by Tao Dai et al was
published in Environmental Science and Technology
DOI: 10.1021/acs.est.3c07908
Further reading from the same research team:
“The life cycle land use of natural gas-fired electricity in the US Western
interconnection” by Tao Dai et al was published in Environmental Science: Advances
DOI: 10.1039/D3VA00038A