IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v222y2024ics0960148123017809.html
   My bibliography  Save this article

Analysis on data center power supply system based on multiple renewable power configurations and multi-objective optimization

Author

Listed:
  • He, Wei
  • Xu, Qing
  • Liu, Shengchun
  • Wang, Tieying
  • Wang, Fang
  • Wu, Xiaohui
  • Wang, Yulin
  • Li, Hailong

Abstract

With rapid development of data center industry, achieving low energy consumption and costs become important. How to provide an optimal configuration on renewable distributed energy systems combining data centers is challenging. This work discussed possible hybrid configurations by combining diesel, photovoltaic, wind, and battery capacity in data center. For each mode, renewable penetration (RP) and the Levelized Cost of Electricity (LCOE) were used to evaluate the performance of system. A multi-objective optimization analysis of the case is performed based on the entropy weighted-TOPSIS method, genetic algorithm, and NSGA-II aiming to obtain both a high RP and a low LCOE. Then, comparative research on optimal power configuration with conventional or renewable energy was conducted. The results show that it is recommended to take a high-rated PV power. When wind power is taken, it is only meaningful when combined with PV power system. For the hybrid renewable power system without an energy storage unit, it's easy to realize a lower LCOE compared to Diesel mode, and its realizable maximum RP is 28.31 %. When battery energy storage is taken in the hybrid system, six optimal configurations are recommended which can achieve the lowest cost of 0.21 $/kWh and the highest RP of 44.5 %.

Suggested Citation

  • He, Wei & Xu, Qing & Liu, Shengchun & Wang, Tieying & Wang, Fang & Wu, Xiaohui & Wang, Yulin & Li, Hailong, 2024. "Analysis on data center power supply system based on multiple renewable power configurations and multi-objective optimization," Renewable Energy, Elsevier, vol. 222(C).
  • Handle: RePEc:eee:renene:v:222:y:2024:i:c:s0960148123017809
    DOI: 10.1016/j.renene.2023.119865
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148123017809
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2023.119865?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:222:y:2024:i:c:s0960148123017809. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.