IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v41y2012i1p56-64.html
   My bibliography  Save this article

Fuel cell-based cogeneration system covering data centers’ energy needs

Author

Listed:
  • Guizzi, Giuseppe Leo
  • Manno, Michele

Abstract

The Information and Communication Technology industry has gone in the recent years through a dramatic expansion, driven by many new online (local and remote) applications and services. Such growth has obviously triggered an equally remarkable growth in energy consumption by data centers, which require huge amounts of power not only for IT devices, but also for power distribution units and for air-conditioning systems needed to cool the IT equipment.

Suggested Citation

  • Guizzi, Giuseppe Leo & Manno, Michele, 2012. "Fuel cell-based cogeneration system covering data centers’ energy needs," Energy, Elsevier, vol. 41(1), pages 56-64.
  • Handle: RePEc:eee:energy:v:41:y:2012:i:1:p:56-64
    DOI: 10.1016/j.energy.2011.07.030
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544211004786
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2011.07.030?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.

    References listed on IDEAS

    as
    1. Mitchell-Jackson, J. & Koomey, J.G. & Nordman, B. & Blazek, M., 2003. "Data center power requirements: measurements from Silicon Valley," Energy, Elsevier, vol. 28(8), pages 837-850.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Najafi, Behzad & Haghighat Mamaghani, Alireza & Rinaldi, Fabio & Casalegno, Andrea, 2015. "Long-term performance analysis of an HT-PEM fuel cell based micro-CHP system: Operational strategies," Applied Energy, Elsevier, vol. 147(C), pages 582-592.
    2. 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).
    3. Ahmad Baroutaji & Arun Arjunan & John Robinson & Tabbi Wilberforce & Mohammad Ali Abdelkareem & Abdul Ghani Olabi, 2021. "PEMFC Poly-Generation Systems: Developments, Merits, and Challenges," Sustainability, MDPI, vol. 13(21), pages 1-31, October.
    4. Daeho Kim & Jimin Kim & Choongwan Koo & Taehoon Hong, 2014. "An Economic and Environmental Assessment Model for Selecting the Optimal Implementation Strategy of Fuel Cell Systems—A Focus on Building Energy Policy," Energies, MDPI, vol. 7(8), pages 1-22, August.
    5. Oró, Eduard & Depoorter, Victor & Garcia, Albert & Salom, Jaume, 2015. "Energy efficiency and renewable energy integration in data centres. Strategies and modelling review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 429-445.
    6. Haghighat Mamaghani, Alireza & Najafi, Behzad & Casalegno, Andrea & Rinaldi, Fabio, 2017. "Predictive modelling and adaptive long-term performance optimization of an HT-PEM fuel cell based micro combined heat and power (CHP) plant," Applied Energy, Elsevier, vol. 192(C), pages 519-529.
    7. Ji, Haoran & Chen, Sirui & Yu, Hao & Li, Peng & Yan, Jinyue & Song, Jieying & Wang, Chengshan, 2022. "Robust operation for minimizing power consumption of data centers with flexible substation integration," Energy, Elsevier, vol. 248(C).
    8. Rostirolla, G. & Grange, L. & Minh-Thuyen, T. & Stolf, P. & Pierson, J.M. & Da Costa, G. & Baudic, G. & Haddad, M. & Kassab, A. & Nicod, J.M. & Philippe, L. & Rehn-Sonigo, V. & Roche, R. & Celik, B. &, 2022. "A survey of challenges and solutions for the integration of renewable energy in datacenters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    9. Depoorter, Victor & Oró, Eduard & Salom, Jaume, 2015. "The location as an energy efficiency and renewable energy supply measure for data centres in Europe," Applied Energy, Elsevier, vol. 140(C), pages 338-349.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Yingbo & Shan, Kui & Li, Xiuming & Li, Hangxin & Wang, Shengwei, 2023. "Research and Technologies for next-generation high-temperature data centers – State-of-the-arts and future perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    2. Zimmermann, Severin & Meijer, Ingmar & Tiwari, Manish K. & Paredes, Stephan & Michel, Bruno & Poulikakos, Dimos, 2012. "Aquasar: A hot water cooled data center with direct energy reuse," Energy, Elsevier, vol. 43(1), pages 237-245.
    3. Lei, Nuoa & Masanet, Eric, 2020. "Statistical analysis for predicting location-specific data center PUE and its improvement potential," Energy, Elsevier, vol. 201(C).
    4. Jin, Chaoqiang & Bai, Xuelian & Yang, Chao & Mao, Wangxin & Xu, Xin, 2020. "A review of power consumption models of servers in data centers," Applied Energy, Elsevier, vol. 265(C).
    5. Sauer, Ildo L. & Tatizawa, Hédio & Salotti, Francisco A.M., 2012. "Power quality and energy efficiency assessment and the need for labelling and minimum performance standard of uninterruptible power systems (UPS) in Brazil," Energy Policy, Elsevier, vol. 41(C), pages 885-892.
    6. Cullenward, Danny & Koomey, Jonathan G., 2016. "A critique of Saunders' ‘historical evidence for energy efficiency rebound in 30 us sectors’," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 203-213.
    7. Asha-Dee N. Celestine & Martin Sulic & Marika Wieliczko & Ned T. Stetson, 2021. "Hydrogen-Based Energy Storage Systems for Large-Scale Data Center Applications," Sustainability, MDPI, vol. 13(22), pages 1-16, November.
    8. Cheung, Howard & Wang, Shengwei & Zhuang, Chaoqun & Gu, Jiefan, 2018. "A simplified power consumption model of information technology (IT) equipment in data centers for energy system real-time dynamic simulation," Applied Energy, Elsevier, vol. 222(C), pages 329-342.
    9. Lee, Yee-Ting & Wen, Chih-Yung & Shih, Yang-Cheng & Li, Zhengtong & Yang, An-Shik, 2022. "Numerical and experimental investigations on thermal management for data center with cold aisle containment configuration," Applied Energy, Elsevier, vol. 307(C).

    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:energy:v:41:y:2012:i:1:p:56-64. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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/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.