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Related Experiment Video

Updated: Oct 1, 2025

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
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Bio-inspired negotiation approach for smart-grid colocation datacenter operation.

Santiago Iturriaga1, Jonathan Muraña1, Sergio Nesmachnow1

  • 1Department of Computer Science, Universidad de la República, Julio Herrera y Reissig 565, Montevideo, Uruguay.

Mathematical Biosciences and Engineering : MBE
|March 4, 2022
PubMed
Summary

This study introduces a bio-inspired method for colocation datacenters in smart grids to manage demand response events. It optimizes datacenter costs and tenant profits through negotiation and efficient scheduling, achieving significant improvements.

Keywords:
colocation datacenterdemand responseevolutionary negotiationsmart grid

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Optimization

Background:

  • Demand response programs are crucial for smart grid stability, enabling consumers to adjust energy use.
  • Colocation datacenters present unique challenges and opportunities for grid participation due to their significant energy demands.
  • Existing approaches may not adequately balance the economic incentives for both datacenters and their tenants during demand response events.

Purpose of the Study:

  • To propose a bio-inspired, hierarchical approach for colocation datacenters to participate in demand response programs.
  • To optimize the negotiation process between datacenters and tenants for demand response events.
  • To minimize datacenter costs while maximizing tenant profits.

Main Methods:

  • A two-level hierarchical model was developed, separating datacenter planning and tenant task scheduling.
  • Two bio-inspired algorithms were designed and compared for the datacenter planning level.
  • An efficient greedy scheduling heuristic was employed for tenant task scheduling.

Main Results:

  • The proposed bio-inspired approach demonstrated significant improvements compared to traditional methods.
  • Average improvements ranged from 72.9% to 82.2% over the business-as-usual scenario.
  • The hierarchical model effectively balanced the competing objectives of the datacenter and its tenants.

Conclusions:

  • The bio-inspired, hierarchical strategy is effective for integrating colocation datacenters into demand response programs.
  • The approach successfully optimizes economic outcomes for both datacenters and tenants.
  • This research offers a scalable and efficient solution for smart grid management involving large energy consumers.