Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/14183
Title: Energy performance of data centres in Singapore
Authors: SUN HANSONG
Keywords: Data centre, Energy performance, Energy consumption and power demand, Energy efficiency, Over-designing, Neuro-fuzzy network modeling
Issue Date: 30-Aug-2004
Source: SUN HANSONG (2004-08-30). Energy performance of data centres in Singapore. ScholarBank@NUS Repository.
Abstract: This thesis describes the study on the energy performance of data centres in Singapore. The primary objectives of this study are to determine an empirical energy usage pattern of data centres under tropical climate and to develop whole-system based models of data centre energy performance. Case studies and field measurements were conducted in six data centres in Singapore. The energy performances of various energy consuming systems and overall data centre are examined. Firstly, this study reveals that data centres are greatly high energy consuming facilities. Power demands and energy consumptions per unit gross floor area of data centres are significantly higher than those of commercial office spaces in Singapore. Secondly, over-designed power demands, over-sizing of HVAC and UPS systems, low occupancy rate of gross floor area, poor layout of IT equipment and supporting systems, and unreasonable environmental conditions are universal problems of data centre facilities. Significant potential of energy saving can be expected. Thirdly, there are significant variations among the six data centres investigated, with respect to the energy consumptions, power demands, operational energy efficiencies of systems, as well as the design and operation strategies. These reflect the lack of design standard and guidelines for data centres. Lastly, based on the results of case studies and field measurements, whole-system based models of data centre energy performance are developed using neuro-fuzzy network. The models incorporate various energy consuming systems and variables affecting energy performance of data centres. The quantitative prediction of energy saving potential of data centres can be performed.
URI: http://scholarbank.nus.edu.sg/handle/10635/14183
Appears in Collections:Master's Theses (Open)

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