Hogan Lovells 2024-2025 AI Trends Guide - Flipbook - Page 47
Energy
• AI-driven Carbon Capture and Storage (CCS) optimization.
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
The continued development and application of AI in the
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.
