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Design Analysis and Performance Evaluation of a Data Center With Indirect Evaporative Cooling

[+] Author Affiliations
Fatemeh Tavakkoli, Siavash Ebrahimi, Xiaogang Sun, Yan Cui, Ali Heydari

Baidu USA LLC, Sunnyvale, CA

Paper No. IPACK2017-74295, pp. V001T02A012; 14 pages
  • ASME 2017 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems collocated with the ASME 2017 Conference on Information Storage and Processing Systems
  • ASME 2017 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems
  • San Francisco, California, USA, August 29–September 1, 2017
  • Conference Sponsors: Electronic and Photonic Packaging Division
  • ISBN: 978-0-7918-5809-7
  • Copyright © 2017 by ASME


With the rapid growth of data centers worldwide and the global shift towards energy sustainability, deploying new cooling technologies has an utmost importance. Conventional cooling systems such as chilled water system, usually have high capital costs and relatively low energy efficiency, leading to a high PUE and TCO values. Indirect evaporative cooling is a promising technology, which offers air cooling with high efficiency, hygiene air quality, and lower total cost. This paper details the design of a proof-of-concept data center with indirect evaporative cooling, which will be eventually deployed at megawatt-scale Baidu datacenters. BIN data analysis and CFD simulation are performed to optimize the physical design and operating conditions. CFD analysis of the data center room is established to optimize rack placement, air flow management, and cold aisle hot aisle configuration. A comprehensive TCO analysis is established, which shows a total savings of 9% using IDEC technology compared to chilled water system for cooling. In addition, TCO analysis indicates small to negligible effect of air supply temperature. Hence, air supply to the cold aisle is set to 27 °C to improve cooling performance. Finally, ROI sensitivity analysis is performed to measure the sensitivity of ROI on power usage effectiveness of the IDEC unit.

Copyright © 2017 by ASME



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