2023/09/28 by Vladimir Dvorkin, Dvorkin, Vladimir · 1 citation
Computer Science · #Blockchain Technology Applications and Security #Data Stream Mining Techniques #FOS: Electrical engineering #FOS: Mathematics #Optimization and Control (math.OC) #Privacy-Preserving Technologies in Data #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2309.16792
openalex publication_date 2023/09/28 · openalex created_date 2023/10/03 · openalex updated_date 2026/07/28
A network of spatially distributed data centers can provide operational flexibility to power systems by shifting computing tasks among electrically remote locations. However, harnessing this flexibility in real-time through the standard optimization techniques is challenged by the need for sensitive operational datasets and substantial computational resources. To alleviate the data and computational requirements, this paper introduces a coordination mechanism based on contextual regression. This mechanism, abbreviated as AgentCONCUR, associates cost-optimal task shifts with public and trusted contextual data (e.g., real-time prices) and uses regression on this data as a coordination policy. Notably, regression-based coordination does not learn the optimal coordination actions from a labeled dataset. Instead, it exploits the optimization structure of the coordination problem to ensure feasible and cost-effective actions. A NYISO-based study reveals large coordination gains and the optimal features for the successful regression-based coordination.