Estimating the energy consumption and power demand of small power equipment in office buildings

被引:129
|
作者
Menezes, A. C. [1 ,2 ]
Cripps, A. [1 ]
Buswell, R. A. [2 ]
Wright, J. [2 ]
Bouchlaghem, D. [3 ]
机构
[1] AECOM, Sustainable Dev Grp, London WC1V 6QS, England
[2] Univ Loughborough, Dept Civil & Bldg Engn, Loughborough, Leics, England
[3] Nottingham Trent Univ, Sch Architecture, Nottingham, England
基金
英国工程与自然科学研究理事会;
关键词
Small power; Plug loads; Offices; Predictions; Estimates; Computers; Energy consumption; Power demand; Operational performance; LOADS;
D O I
10.1016/j.enbuild.2014.02.011
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Small power is a substantial energy end-use in office buildings in its own right, but also significantly contributes to internal heat gains. Technological advancements have allowed for higher efficiency computers, yet current working practices are demanding more out of digital equipment. Designers often rely on benchmarks to inform predictions of small power consumption, power demand and internal gains. These are often out of date and fail to account for the variability in equipment speciation and usage patterns in different offices. This paper details two models for estimating small power consumption in office buildings, alongside typical power demand profiles. The first model relies solely on the random sampling of monitored data, and the second relies on a 'bottom-up' approach to establish likely power demand and operational energy use. Both models were tested through a blind validation demonstrating a good correlation between metered data and monthly predictions of energy consumption. Prediction ranges for power demand profiles were also observed to be representative of metered data with minor exceptions. When compared to current practices, which often rely solely on the use of benchmarks, both proposed methods provide an improved approach to predicting the operational performance of small power equipment in offices. (C) 2014 The Authors. Published by Elsevier B.V.
引用
收藏
页码:199 / 209
页数:11
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