Large-Scale Data Center Integration in Power Systems: Uncertainty and Multi-Scale Variation
eess.SY, cs.SY
Submitted: 2026-10-09
Updated: 2026-10-09
Comments: Accepted for publication in Proceedings of the IEEE. Copyright 2026 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses
Code: https://github.com/amitjena1992/LILAD
Project page: https://www.energy.gov/speed-to-power
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Electricity Demand and Grid Impacts of AI Data Centers: Challenges and Prospects
- Data Center Control Against Sub-Synchronous Resonance: A Data-Driven Approach
- Measurement of Generative AI Workload Power Profiles for Whole-Facility Data Center Infrastructure Planning
- A Gradient-Based Capacity Accreditation Framework in Resource Adequacy: Formulation, Computation, and Practical Implications
- Risk-Based Capacity Accreditation of Resource-Colocated Large Loads in Capacity Markets
- Power Stabilization for AI Training Datacenters
- Comparative Assessment of Look-Ahead Economic Dispatch and Ramp Products for Grid Flexibility
- Stochastic Long-Term Joint Decarbonization Planning for Power Systems and Data Centers: A Case Study in PJM
- From Liability to Asset: A Three-Mode Grid-Forming Control Framework for Centralized Data Center UPS Systems
- When Experimental Economics Meets Large Language Models: Evidence-based Tactics
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