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AI Tool Could Help Plan NYS's Transition to Clean Electrical Power

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New York, which has committed to producing 100% clean electricity by 2040, is using technological, environmental, and economic data to determine the best policy and investment choices for integrating more renewable energy into the electrical grid.


Cornell University's Fengqi You and Ning Zhao have designed an artificial intelligence tool that could help New York state plan its switch to clean electricity by combining machine learning and multi-scale, bottom-up optimization modeling.

The researchers compiled case-studies on the state's electric power decarbonization, optimizing annual capacity planning and hourly systems operations while embedding data from the technology, capacity, and age of electricity generation/storage facilities statewide.

One transition model that considered expanded electricity storage capacity suggested total generation capacity was 39% higher than in a non-storage scenario, which would demand 200% more generation capacity based on nonintermittent energy.

Hourly simulations showed offshore wind, hydroelectric, and solar would be the optimal power sources by 2040, while nuclear would be required to replace solar energy absent a 10-fold expansion of power storage capacity.

From Cornell Chronicle
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Abstracts Copyright © 2022 SmithBucklin, Washington, DC, USA


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