Energy System Digitization in the Era of AI: A Three-Layered Approach towards Carbon Neutrality
This addresses the problem of decarbonizing electricity and transportation sectors for climate change mitigation, but it is incremental as it adapts existing AI methods.
The paper tackles the challenge of transitioning to a carbon-neutral electric grid by proposing a three-layered approach (technology, markets, policy) to tailor AI algorithms, aiming to accelerate the transition, though no concrete results or numbers are provided.
The transition towards 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.