Research

Research, white papers, reports, and presentations on data centers, energy, and modern infrastructure from around the world.

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Power & Energy Supply 8 Cooling & Thermal 2 Facility Design & Construction 2 IT & AI Infrastructure 1 Operations & Efficiency 1 Market, Policy & Sustainability 5

Grid connection 4 On-site generation 5 Energy storage (BESS) 2 Microgrids & flexibility 5 Power distribution (AC/DC) 1

Academic PaperarXiv (preprint)30 September 2026Power & Energy Supply

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

The paper introduces FissionReady, a scheduler for data centers supplied by a multi-module small modular reactor (SMR) plant. It jointly manages the output of each reactor module, deferrable batch workloads, and grid purchases while accounting for fuel age, iodine-xenon dynamics, and reactivity margin. In simulations, the approach eliminates forced outages and missed batch-job deadlines while reducing water use and grid-electricity costs relative to a comparable baseline configuration.

Small Modular Reactors (SMRs)Data Center Power SupplyGeneration Load FollowingData Center Microgrids

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Academic PaperarXiv (preprint)29 September 2026Power & Energy Supply

Grid Demand Flexibility Assessment of AI Data Centers via Batch Workload Temporal Shifting

This research paper presents a method for quantifying the electricity-demand flexibility that AI data centers can provide to the power system. The approach reschedules batch computing workloads subject to constraints on delay, uninterrupted execution, and available CPU, GPU, and memory resources. Task-scheduling decisions are translated into a server power profile, which is then used to assess peak-shaving potential and the duration for which a load reduction can be sustained, using real GPU-cluster traces.

AI Data CentersDemand FlexibilityLoad ManagementBatch Workload Shifting

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Academic PaperarXiv (preprint)28 September 2026Power & Energy Supply

Long-Term Operational Planning Using Scenario-Based System Load Forecasting

This technical paper from Dominion Energy examines how scenario-based system-load forecasts at different time granularities can support long-term assessment of planned transmission outages. It is set against rapid growth in hyperscale data-center and AI load in Northern Virginia, which requires new and reinforced grid infrastructure. The authors compare the conventional use of monthly or seasonal peak demand with coordinated daily, weekly, and monthly forecasts, finding that the latter can enable more outage coordination without weakening the N-1 reliability criterion.

AI data-center loadLarge-load interconnectionPlanned grid outagesTransmission grid

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