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

Le Xie, Tong Huang, Xiangtian Zheng, Yan Liu, Mengdi Wang, Vijay Vittal, P. R. Kumar, Srinivas Shakkottai, Yi Cui

Research output: Contribution to journalReview articlepeer-review

3 Scopus citations


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.

Original languageEnglish (US)
Article number100640
Issue number12
StatePublished - Dec 9 2022

All Science Journal Classification (ASJC) codes

  • General Decision Sciences


  • DSML2: Proof-of-concept: Data science output has been formulated, implemented, and tested for one domain/problem
  • artificial intelligence
  • carbon neutrality
  • electric energy systems


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