AI is accelerating the transition to clean energy
Through AI-driven research and collaboration, the energy sector can better forecast infrastructure needs and respond to climate-related challenges.
AI is playing an increasingly vital role in supporting the transition to clean energy. AI helps optimise power grid operations, plan infrastructure investments, and accelerate the discovery of novel materials for energy generation, storage, and conversion.
While energy-hungry data centres can increase electricity demand, AI applications are helping reduce energy consumption across buildings, transport, and industry.
On electric grids, AI algorithms enhance efficiency, integrate renewable energy sources, and predict maintenance needs to prevent power outages. Grid operators can utilise AI to forecast supply and demand, optimise energy storage, and manage resources in real-time.
Technologies such as smart thermostats, electric vehicle batteries, and AI-managed data centres provide additional flexibility to balance peak demand and supply.
AI also aids long-term planning by helping utilities forecast future infrastructure needs amid growing renewable deployment and climate-related risks. Additionally, AI accelerates the discovery of materials for energy technologies.
At MIT, researchers use AI-guided experiments and robotics to design and test new materials, significantly shortening development times from decades to years.
Through research, modelling, and collaboration, AI is being applied to fusion reactor management, solar cell optimisation, and energy-efficient data centre design. MIT Energy Initiative programmes unite academics, industry, and policymakers to harness AI for a resilient and sustainable energy future.
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