4.7 Article

Exploiting data centres energy flexibility in smart cities: Business scenarios

期刊

INFORMATION SCIENCES
卷 476, 期 -, 页码 392-412

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2018.07.010

关键词

Data centre; Electrical and thermal energy flexibility; Workload relocation; Business scenari-os; Optimization techniques

资金

  1. GEYSER pro-ject [609211]
  2. European Commission as part of the 7th Research Framework Programme (FP7-SMARTCITIES-2013)
  3. CATALYST project [768739]
  4. SPERO [PN-III-P2-2.1-SOL-2016-03-0046, 3So1/2017]
  5. ROBIN [PN-III-P1-1.2-PCCDI-2017-0734]
  6. NETIO ForestMon [53/05.09.2016, SMIS2014+ 105976]
  7. European Commission as part of the H2020 Framework Programme (H2020-EE-2016-2017)
  8. [PN 18 19 02 01]
  9. [9N/16.03.2018]

向作者/读者索取更多资源

In this paper, we have considered Data Centres (DCs) as computing facilities functioning at the crossroad of electrical, thermal and data networks and have defined optimisation techniques to exploit their energy flexibility. Our methods are leveraging on non-electrical cooling devices such as thermal storage and heat pumps for waste heat reuse and IT workload execution time shifting and spatial relocation in federated DCs. To trade energy flexibility we have defined an Energy Marketplace which allows DCs to act as active energy players integrated into the smart grid, contributing to smart city-level efficiency goals. Reinforcing this vision, we have proposed four innovative business scenarios that enable next generation smart Net-zero Energy DCs acting as energy prosumers at the interface with smart energy grids within smart city environments. Simulation experiments are conducted to determine the DCs potential electrical and thermal energy flexibility in meeting various network level goals and to assess the financial viability of the defined business scenarios. The results show that DCs have a significant amount of energy flexibility which may be shifted and traded to interested stakeholders thus allowing them to gain new revenue streams not foreseen before. (C) 2018 Elsevier Inc. All rights reserved.

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