Hogan Lovells 2024-2025 AI Trends Guide - Flipbook - Page 46
Energy
AI innovations shaping tomorrow’s energy landscape
AI is playing a critical, transformative role in the energy
sector. In addition to the continued growth of the AI
industry driving future energy needs, there have been
significant advancements and additional opportunities
remain regarding AI’s role in optimizing energy generation,
distribution, and consumption. From enhancing the
intelligence of smart grids to advancing battery storage,
AI solutions are driving critical progress across a range of
technologies. This shift is not only helping energy providers
manage demand fluctuations and renewable integration
more effectively but is also opening new avenues for
decentralized energy solutions and emissions reductions in
traditionally challenging sectors.
Key AI innovations are transforming every stage of the energy
value chain. Here’s a quick look at the most impactful areas
where AI is shaping the future of energy:
• Smart grids, renewable energy forecasting, and demand
response.
AI-powered smart grids are transforming energy systems
by optimizing the real-time balance of supply and demand,
a critical function for incorporating variable renewable
energy sources like wind and solar. With AI’s advanced
forecasting abilities, providers can more accurately predict
renewable energy generation using weather and historical
data, allowing for better generation planning and grid
stability as renewable energy generation fluctuates. AIdriven demand response programs also adjust or reduce
consumer energy use during peak periods, reducing grid
loads and minimizing reliance on backup fossil-fuel
sources. Additionally, AI is driving decentralized energy
management, empowering local or “edge” resources such
as rooftop solar, community wind projects, and residential
battery storage and energy projects to contribute to the
grid independently. By integrating these decentralized
resources, AI-enabled smart grids can dynamically
coordinate and manage localized generation and storage,
and optimize energy flow within microgrids, or between
microgrids and the utility grid. This decentralized approach
supports resilience by reducing grid congestion and
transmission losses, and improving response during grid
disruptions. These smart grid capabilities create more
resilient and adaptive microgrids, and allow for sustainable
energy infrastructure as renewable energy resources
continue to grow.
• Predictive maintenance and asset management.
AI-driven predictive maintenance is essential for keeping
critical energy infrastructure - like turbines, transmission
lines, transformers, and generators - operational with
minimal downtime. By analyzing sensor data in real time,
AI can assess equipment health, predicting potential issues
and preventing failures before they occur. These systems
use machine learning to identify failure patterns that
might not be visible to human operators, leading to fewer
unplanned outages and longer asset life. For asset-heavy
industries such as utilities, oil and gas pipeline companies,
and generation companies, predictive maintenance reduces
repair, replacement, and insurance costs, ultimately
enhancing both operational efficiency and safety.
• Battery and energy storage optimization.
As clean energy becomes a larger portion of the energy
generation mix, energy storage systems are essential to
maintaining a steady power supply for variable energy
resources. AI-driven optimization transforms storage
management, ensuring that battery systems operate
efficiently, sustainably, and at optimal cost. By analyzing
demand forecasts and renewable energy output, AI can
strategically manage charging and discharging cycles,
improving storage efficiency and extending battery life.
Additionally, AI powers Virtual Power Plants (VPPs) that
aggregate distributed storage assets, such as electric
vehicles and residential batteries, allowing these resources
to function as a unified, flexible power source for the grid,
enhancing reliability and flexibility.
Authors
Darcy Bisset
Partner
Baltimore
Brian Chappell
Partner
Baltimore
Niki Roberts
Partner
Houston
Amy Roma
Partner
Washington, D.C.
Ben Sulaiman
Partner
London
