AI’s Dual Role: Facilitating Renewable Energy and Straining Power Grids
Artificial intelligence is reshaping the energy landscape by enhancing utility infrastructure and accelerating renewable energy projects. However, this technology also poses challenges with increasing electricity demand due to AI-driven data centers.
The ongoing AI data center expansion could drive 44% of U.S. electricity load growth between 2023 and 2028. As reported in October by Bain & Company, utilities might need to increase annual generation by up to 26% by 2028 to meet the demand.
Neil Chatterjee, former chairman of the Federal Energy Regulatory Commission, highlighted the impending demand surge, stating, “We have had a period of relatively flat demand for electricity going on almost two decades now.” He expressed concern about the readiness of policymakers and the industry for this change.
Chatterjee, now on the advisory board of AiDash, a satellite analytics company, emphasized AI’s potential in aiding the clean energy transition. AiDash utilizes AI to tackle challenges like vegetation management, which costs utilities between $6 billion to $8 billion annually. “I really think the climate case for AI needs to be made,” he added.
Abhishek Singh, CEO of AiDash, noted the massive scale of U.S. power infrastructure, including 7 million miles of power lines and billions of trees, which face increased risks due to climate change. Recent advancements in generative AI have enabled AiDash to offer innovative solutions that were once impossible.
Chatterjee also addressed the complex issues arising from AI-driven electricity demand, such as data center co-location. Last month, FERC rejected a proposal to power a data center from an existing nuclear plant, which could have led to increased costs for ratepayers. Chatterjee called for leadership to navigate AI adaptation, emphasizing the need to balance demand, reliability, and decarbonization goals.
AI in Permitting and Risk Assessment
Following the release of ChatGPT in November 2022, the software company Paces resumed its efforts to build a permitting insights tool. Co-founder James McWalter explained that initial attempts were costly and inefficient but now leverage AI to support clean energy developers in permitting, siting, and risk assessment.
Paces’ AI tools facilitate data collection and report generation, allowing developers to focus on community engagement and utility relationships. McWalter anticipates that most desktop analysis will be automated within two years, enhancing project efficiency.
In September, McWalter participated in a White House roundtable discussing AI infrastructure and clean energy strategies. He emphasized Paces’ mission to transition the economy from fossil fuels to renewable energy, including AI data centers.
AI’s Role in Nuclear Fusion Development
AI is also advancing nuclear fusion research, as noted in a Clean Air Task Force report. Sehila Gonzales de Vicente, CATF’s global fusion director, highlighted AI’s critical role in overcoming fusion challenges, such as plasma stability.
DisruptionPy, an open-source library developed by MIT, exemplifies AI’s impact in fusion research by streamlining data analysis for plasma disruptions. Gonzales de Vicente noted AI’s ability to optimize operations, reducing the need for physical experiments and accelerating fusion development.
“Artificial intelligence is a tool which is quite transversal to basically everything,” said Gonzales de Vicente, optimistic about AI’s potential to enhance industrial processes and complex technologies like fusion over the next five years.
Original Story at www.esgdive.com