{"paper":{"title":"Electricity Price-Aware Scheduling of Data Center Cooling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Arash Khojaste, Golbon Zakeri, Jonathan Pearce, Yuanrui Sang","submitted_at":"2025-08-05T07:06:47Z","abstract_excerpt":"Data centers are becoming a major consumer of electricity on the grid, with cooling accounting for about 40\\% of that energy. As electricity prices vary throughout the day and year, there is a need for cooling strategies that adapt to these fluctuations to reduce data center cooling costs. In this paper, we present a model for electricity price-aware cooling scheduling using a Markov Decision Process(MDP) framework to reliably estimate the cooling system operational costs and facilitate investment-phase decision-making. We utilize Quantile Fourier Regression (QFR) fits to classify electricity "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.03160","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2508.03160/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}