Hogan Lovells 2024-2025 AI Trends Guide - Flipbook - Page 47
Energy
AI-driven Carbon Capture and Storage (CCS) optimization. The continued development and application of AI in the
In parallel with energy storage advancements, AI-driven CCS
optimization is becoming a critical component for reducing
emissions in sectors that are difficult to decarbonize, such
as heavy industrials and facilities with significant energy
consumption. AI enhances the capture process by optimizing
variables like temperature and pressure, increasing capture
rates and reducing the energy required for CO2 capture.
Through predictive maintenance, AI also helps monitor
CCS infrastructure, such as pipelines and storage wells,
minimizing the risk of leaks and ensuring long-term storage
integrity. These improvements help position CCS as a viable
and cost-effective tool in emissions-reduction strategies.
AI in nuclear energy optimization.
Nuclear energy holds immense promise as the zerocarbon, high-output solution to the world’s growing energy
demands and the urgent need to combat climate change.
AI technologies are increasingly optimizing nuclear energy
systems by enhancing efficiency, safety, and operational
performance. Machine learning algorithms are being used to
predict maintenance needs, detect anomalies, and optimize
reactor operations, leading to reduced downtime and more
reliable energy production. AI is also playing a crucial role
in improving the design and simulation of nuclear reactors,
enabling more precise modeling of complex systems, and
supporting the development of next-generation reactors.
Additionally, AI aids in managing the vast amounts of data
generated by nuclear plants, streamlining decision-making
processes, and helping to ensure compliance with safety
regulations. As AI continues to evolve, its integration into
nuclear energy systems promises to drive innovations that
improve both the sustainability and safety of the industry.
Additional
resources
Spotlight
Energy Transition Hub
energy sector is critical in accelerating the transition to a
cleaner, more reliable, and cost-effective energy landscape.
Our experienced team is dedicated to assisting clients in
understanding and addressing the legal complexities of
integrating AI into their energy infrastructure and projects.
By working with leading companies in the energy sector, we
support the development of smarter, more resilient assets,
helping businesses stay ahead in an increasingly AI-driven
energy landscape.
