Intelligent Energy Arbitration in Edge Networks with Distributed Digital Twins

Data centers currently account for <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{2 - 3 \%}$</tex> of global electricity consumption and may reach <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$3-4 \%$</tex> by 2030 as artificial intelligence and cloud workloads surge. In the U.S., data centers are projected to use up to 8% of national electricity by 2030. Meanwhile, power grids integrate growing shares of intermittent renewables, complicating real-time balancing. This paper presents a hierarchical multi-agent framework for energy arbitration at the Edge, based on Intelligent Digital Twins (IDTs) that control individual devices and a Distributed Intelligent Twin (DIT) that coordinates a site or mesh of Edges. The approach enables autonomous, fine-grained energy optimization and resilient operation. We detail architecture and AI decision mechanisms and evaluate three representative use cases: distributed Edge data centers, drone swarms, and smart buildings. Simulations indicate energy savings up to 50% in certain scenarios, while improving scalability and robustness.