How AI Can Solve the Green Energy Challenge

Argonne National Laboratory has a plan for big data teamed with artificial intelligence.

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The creation of a carbon free energy infrastructure by 2050 is a widely sought goal for Western economies, and America is no exception. Achieving both green energy production and grid distribution at scale, however, is a problem almost impossible to resolve in only 25 years with current technology. 

Argonne National Laboratory has published a report which presents a roadmap toward a clean energy future, driven by artificial intelligence. According to the laboratory, the key will be to harness very large data sets from laboratories, government, and the private sector, to enable AI systems to develop new materials, new technologies and deployment strategies using established techniques such as the digital twin. If regulators will accept artificial intelligence results at face value, timelines for certification of new technologies could be compressed by at least 20%.

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Written by

James Anderton

Jim Anderton is the Director of Content for ENGINEERING.com. Mr. Anderton was formerly editor of Canadian Metalworking Magazine and has contributed to a wide range of print and on-line publications, including Design Engineering, Canadian Plastics, Service Station and Garage Management, Autovision, and the National Post. He also brings prior industry experience in quality and part design for a Tier One automotive supplier.