Transforming US energy infrastructure through Artificial Intelligence

One hundred experts from the fields of clean energy and artificial intelligence convened at Argonne for two days to discuss strategies for securing America’s energy future and leadership.

Their discussions culminated in the AI for Energy report, which outlines their vision.

The AI for Energy Report presents a framework for utilizing AI to expedite the decarbonization of the U.S. economy.

This initiative comes as the U.S. endeavors to achieve net zero carbon emissions by 2050 in response to the escalating threat of climate change. Meeting this ambitious goal will necessitate a widespread adoption of clean energy technologies and a substantial overhaul of the nation’s energy infrastructure.

Although the task ahead is formidable and multifaceted, leveraging the transformative capabilities of artificial intelligence (AI) can make it achievable.

Leading energy researchers and scientists from America’s national laboratories have issued a groundbreaking new report titled AI for Energy, presenting an innovative framework for leveraging AI to accelerate the nation’s clean energy transformation, according to the report.

Rick Stevens, associate laboratory director for the Computing, Environment, and Life Sciences directorate at DOE’s Argonne National Laboratory, highlighted the potential of AI in managing complexity and facilitating connections across various scientific and engineering disciplines, model and data types, and outcome priorities.

This capability, he noted, enables AI to devise solutions for the ‘grand challenges’ of large-scale and rapid clean energy deployment, surpassing conventional methods.

The report outlines grand challenges in five areas of the U.S. energy infrastructure: nuclear power, the power grid, carbon management, energy storage, and energy materials.

It underscores three common needs across these challenges: the imperative for swift and highly reliable computer-aided design and testing of materials and systems, the enhancement of scientists’ capacity to identify uncertainties in their predictions and system performance, and the integration of data from diverse sources and formats using AI.

“AI’s capacity to navigate complexity and establish connections across various disciplines, models, and data types presents an opportunity to address the ‘grand challenges’ of clean energy deployment beyond the capabilities of traditional methods,” stated Rick Stevens, associate laboratory director for the Computing, Environment, and Life Sciences directorate at Argonne.

“If the U.S. can surmount these challenges, the potential benefits could be substantial. AI has the potential to slash the costs associated with designing, licensing, deploying, operating, and maintaining energy infrastructure by hundreds of billions of dollars,” noted Kirsten Laurin-Kovitz, associate laboratory director for the Nuclear Technologies and National Security directorate at Argonne.

“Moreover, it can expedite the design, deployment, and licensing processes, which often consume up to 50% of the time required for a new technology to enter the market.”

Realizing this potential demands closer collaboration among scientists, industry stakeholders, and policymakers than ever before.

The AI for Energy report marks a significant initial stride. Around 100 experts specializing in AI, machine learning, and energy convened at Argonne for a two-day conference in December 2023. Their objective was to outline the optimal utilization of AI in addressing U.S. energy challenges. Subsequently, participants collaborated for three months to produce the report.