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Review
. 2022 Dec 9;3(12):100640.
doi: 10.1016/j.patter.2022.100640.

Energy system digitization in the era of AI: A three-layered approach toward carbon neutrality

Le Xie  1 , Tong Huang  2 , Xiangtian Zheng  1 , Yan Liu  3 , Mengdi Wang  4   5   6 , Vijay Vittal  7 , P R Kumar  1 , Srinivas Shakkottai  1 , Yi Cui  8
Affiliations
Review

Energy system digitization in the era of AI: A three-layered approach toward carbon neutrality

Le Xie et al. Patterns (N Y). .

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.

Keywords: artificial intelligence; carbon neutrality; electric energy systems.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
A layered vision of energy system digitization
Figure 2
Figure 2
Decision-making modules of power (transmission) system operation
See this image and copyright information in PMC

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