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Energy system digitization in the era of AI: A three-layered approach toward carbon neutrality
Le Xie1, Tong Huang2, Xiangtian Zheng1
1Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.
Abstract:
The transition toward carbon-neutral electricity is one of the biggest game changers in addressing climate change since it addresses the dual challenges of removing carbon emissions from the two largest sectors of emitters: electricity and transportation. The transition to a carbon-neutral electric grid poses significant challenges to conventional paradigms of modern grid planning and operation. Much of the challenge arises from the scale of the decision-making and the uncertainty associated with the energy supply and demand. Artificial intelligence (AI) could potentially have a transformative impact on accelerating the speed and scale of carbon-neutral transition, as many decision-making processes in the power grid can be cast as classic, though challenging, machine-learning tasks. We point out that to amplify AI's impact on carbon-neutral transition of the electric energy systems, the AI algorithms originally developed for other applications should be tailored in three layers of technology, markets, and policy.
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