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Abstract

In light of the rapid growth of data centers around the world and their huge energy consumption, several researchers have focused on the task scheduling and resource allocation problem in order to minimize the energy consumed by the data center. Other initiatives focus on the implementation of green energy sources in order to minimize the consumption of fossil fuels and their emission of CO2. As part of the ANR DATAZERO project (Pierson et al. in IEEE Access 7, 2019. https://doi.org/10.1109/ACCESS.2019.2930368), several research teams have engaged in efforts at defining the main concepts of a full green data center, powered only by renewable energy. Achieving this goal necessitates a focus on the efficient management of an autonomous hybrid power system consisting of solar panels, wind turbines, batteries, and fuel cell systems. The purpose of this work is not to show that a stand-alone data center is economically viable, but rather is feasible. This paper proposes a set of models based on mixed integer linear programs capable of managing the energy commitment to address data center power demand. The approach takes the season and weather forecasts into account at the time of optimization.

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Title
Stand-alone renewable power system scheduling for a green data center using integer linear programming
Author
Haddad Maroua 1 ; Nicod Jean-Marc 1 ; Marie-Cécile, Péra 2 ; Varnier Christophe 1 

 Université Bourgogne Franche-Comté, FEMTO-ST Institute, Besançon, France (GRID:grid.493090.7) (ISNI:0000 0004 4910 6615) 
 Université Bourgogne Franche-Comté, FEMTO-ST Institute, Belfort, France (GRID:grid.493090.7) (ISNI:0000 0004 4910 6615) 
Publication title
Volume
24
Issue
5
Pages
523-541
Publication year
2021
Publication date
Oct 2021
Publisher
Springer Nature B.V.
Place of publication
New York
Country of publication
Netherlands
Publication subject
ISSN
10946136
e-ISSN
10991425
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2021-09-28
Milestone dates
2021-07-22 (Registration); 2021-07-07 (Accepted)
Publication history
 
 
   First posting date
28 Sep 2021
ProQuest document ID
2582283697
Document URL
https://www.proquest.com/scholarly-journals/stand-alone-renewable-power-system-scheduling/docview/2582283697/se-2?accountid=208611
Copyright
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.
Last updated
2024-11-15
Database
ProQuest One Academic