FissionReady: Joint Workload and Power Scheduling for Data Centers Powered by Small Modular Reactors

2026-09-30

AI Summary

This study addresses the nuclear physics load-following challenges in small modular reactor (SMR)-powered data centers caused by workload fluctuations. We propose a novel dual-timescale optimization framework that integrates nuclear physics constraints with computational scheduling. By tracking fuel and xenon states to determine safe operating envelopes, the method employs a two-stage algorithm that synergizes reactor state modeling with workload-aware scheduling, enabling joint optimization of load following, task latency, and electricity procurement. Experimental results demonstrate that the proposed framework achieves zero unplanned downtime and zero task deadline violations, while reducing water consumption by approximately one-third and grid electricity costs by nearly half.

Abstract

Data centers are increasingly exploring small modular nuclear reactors (SMRs) as a carbon-free power source, but variable datacenter demand and negative grid prices require the SMR plant to load-follow rather than run at constant output. Load following is uniquely challenging and complex for SMR plants due to underlying nuclear physics. We propose FissionReady, a datacenter scheduler that tracks each module's fuel age, xenon state, and remaining flexibility to determine per-module operating envelopes, then coordinates load-following, batch deferral, and grid purchasing through a two-timescale optimization. FissionReady achieves zero involuntary shutdowns and zero batch deadline misses while reducing water consumption by roughly one-third and grid cost by roughly half compared to a same-sized base configuration.

Problem

• Small Modular Reactors
• Load Following
• Data Center Scheduling
• Power Management
• Nuclear Physics Constraints

Innovation

• Small Modular Reactors
• Joint Scheduling
• Load Following
• Two-timescale Optimization
• Data Center