Researchers create better method to predict offshore wind power
Published 2021-06-30 · Original archive entry · Explore research explainers
New Brunswick, N.J. (June 28, 2021) - Rutgers researchers have developed a machine learning model using a physics-based simulator and real-world meteorological data to better predict offshore wind power.
The findings appear in the journal Applied Energy.
Offshore wind is rapidly maturing into a major source of renewable energy worldwide and is projected to grow by 13% in the next two decades and 15-fold by 2040 to become a $1 trillion industry, matching capital spending on gas- and coal-fired power generation. In the United States, for instance, New York and New Jersey recently awarded two offshore wind energy contracts to help achieve their targets of renewable energy integration.
"We're entering a new age of the offshore wind energy revolution," said senior author END
The findings appear in the journal Applied Energy.
Offshore wind is rapidly maturing into a major source of renewable energy worldwide and is projected to grow by 13% in the next two decades and 15-fold by 2040 to become a $1 trillion industry, matching capital spending on gas- and coal-fired power generation. In the United States, for instance, New York and New Jersey recently awarded two offshore wind energy contracts to help achieve their targets of renewable energy integration.
"We're entering a new age of the offshore wind energy revolution," said senior author END