Quantitative Evaluation of Data Centers’ Participation in Demand Side Management
In recent years, the rapid increase in the number of internet users and widespread usage of internet applications have obliged large servers and networking equipment to manage large data stack and optimize the instantaneous transmission of digital information. The COVID-19 Pandemic has also caused a...
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doaj-ebf155e99875493cabc7e4084612fb8e2021-03-30T15:14:57ZengIEEEIEEE Access2169-35362021-01-019148831489610.1109/ACCESS.2021.30522049328111Quantitative Evaluation of Data Centers’ Participation in Demand Side ManagementMehmet Turker Takci0https://orcid.org/0000-0002-5417-6621Tuba Gozel1https://orcid.org/0000-0003-4798-0635Mehmet Hakan Hocaoglu2https://orcid.org/0000-0001-6528-3812Department of Electronics Engineering, Gebze Technical University, Kocaeli, TurkeyDepartment of Electronics Engineering, Gebze Technical University, Kocaeli, TurkeyDepartment of Electronics Engineering, Gebze Technical University, Kocaeli, TurkeyIn recent years, the rapid increase in the number of internet users and widespread usage of internet applications have obliged large servers and networking equipment to manage large data stack and optimize the instantaneous transmission of digital information. The COVID-19 Pandemic has also caused an increase in data exchanges and digital information generation. In order to manage large-scale data, there is a need for gigantic data centers (DCs) which are tremendous energy consumers and have relatively flexible loads that are easier to control by means of shifting in time and space. Therefore, DCs can be regarded as dispatchable loads and are considered good candidates for participating in demand side management (DSM) programs for power curve smoothing and compensation of power fluctuation in electrical power systems. In this paper, the question of why DCs should participate in DSM has been investigated rather than the technical methods used in DSM. The amount of DCs' participation energy is used by peak shaving/shifting method for power curve smoothing using actual data. The possible environmental and financial effects of it for Turkey and all the world have been carried out. The study results show that DCs' participation in DSM for Turkey decreases peak load by up to 2.18%, defers up to 34% of the installed power plants launched in 2019, and improves load and loss factors by up to 2.2% and 4.3% respectively. Additionally, global DC's participation in DSM decreases the peak point by up to 0.77% and reduces CO<sub>2</sub> emission by 0.03%.https://ieeexplore.ieee.org/document/9328111/Demand side managementelectricity marketdata centerenergy efficiencypeak shaving<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">CO</italic>₂ emission reduction |
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language |
English |
format |
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sources |
DOAJ |
author |
Mehmet Turker Takci Tuba Gozel Mehmet Hakan Hocaoglu |
spellingShingle |
Mehmet Turker Takci Tuba Gozel Mehmet Hakan Hocaoglu Quantitative Evaluation of Data Centers’ Participation in Demand Side Management IEEE Access Demand side management electricity market data center energy efficiency peak shaving <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">CO</italic>₂ emission reduction |
author_facet |
Mehmet Turker Takci Tuba Gozel Mehmet Hakan Hocaoglu |
author_sort |
Mehmet Turker Takci |
title |
Quantitative Evaluation of Data Centers’ Participation in Demand Side Management |
title_short |
Quantitative Evaluation of Data Centers’ Participation in Demand Side Management |
title_full |
Quantitative Evaluation of Data Centers’ Participation in Demand Side Management |
title_fullStr |
Quantitative Evaluation of Data Centers’ Participation in Demand Side Management |
title_full_unstemmed |
Quantitative Evaluation of Data Centers’ Participation in Demand Side Management |
title_sort |
quantitative evaluation of data centers’ participation in demand side management |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
In recent years, the rapid increase in the number of internet users and widespread usage of internet applications have obliged large servers and networking equipment to manage large data stack and optimize the instantaneous transmission of digital information. The COVID-19 Pandemic has also caused an increase in data exchanges and digital information generation. In order to manage large-scale data, there is a need for gigantic data centers (DCs) which are tremendous energy consumers and have relatively flexible loads that are easier to control by means of shifting in time and space. Therefore, DCs can be regarded as dispatchable loads and are considered good candidates for participating in demand side management (DSM) programs for power curve smoothing and compensation of power fluctuation in electrical power systems. In this paper, the question of why DCs should participate in DSM has been investigated rather than the technical methods used in DSM. The amount of DCs' participation energy is used by peak shaving/shifting method for power curve smoothing using actual data. The possible environmental and financial effects of it for Turkey and all the world have been carried out. The study results show that DCs' participation in DSM for Turkey decreases peak load by up to 2.18%, defers up to 34% of the installed power plants launched in 2019, and improves load and loss factors by up to 2.2% and 4.3% respectively. Additionally, global DC's participation in DSM decreases the peak point by up to 0.77% and reduces CO<sub>2</sub> emission by 0.03%. |
topic |
Demand side management electricity market data center energy efficiency peak shaving <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">CO</italic>₂ emission reduction |
url |
https://ieeexplore.ieee.org/document/9328111/ |
work_keys_str_mv |
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