TY - JOUR
T1 - Energy system digitization in the era of AI
T2 - A three-layered approach toward carbon neutrality
AU - Xie, Le
AU - Huang, Tong
AU - Zheng, Xiangtian
AU - Liu, Yan
AU - Wang, Mengdi
AU - Vittal, Vijay
AU - Kumar, P. R.
AU - Shakkottai, Srinivas
AU - Cui, Yi
N1 - Funding Information:
This material is based upon work partially supported by the US Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Solar Energy Technologies Office award number DE-EE0009031 and by the US National Science Foundation under the grants CMMI-2130945 and ECCS-2038963 . The views expressed herein and the conclusions contained in this document are those of the authors and should not be interpreted as representing the views or official policies, either expressed or implied, of the Department of Energy or the United States government.
Publisher Copyright:
© 2022 The Authors
PY - 2022/12/9
Y1 - 2022/12/9
N2 - 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.
AB - 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.
KW - DSML2: Proof-of-concept: Data science output has been formulated, implemented, and tested for one domain/problem
KW - artificial intelligence
KW - carbon neutrality
KW - electric energy systems
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U2 - 10.1016/j.patter.2022.100640
DO - 10.1016/j.patter.2022.100640
M3 - Review article
C2 - 36569552
AN - SCOPUS:85145586270
SN - 2666-3899
VL - 3
JO - Patterns
JF - Patterns
IS - 12
M1 - 100640
ER -