Empirical variation in 24-h profiles of delivered power for a sample of UK dwellings: Implications for evaluating energy savings

Empirical variation in 24-h profiles of delivered power for a sample of UK dwellings: Implications for evaluating energy savings
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英国住宅样本 24 小时输送功率曲线的经验变化:对评估节能的影响

DOI:
10.1016/j.enbuild.2014.11.075
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发表时间:
2015
影响因子:
6.7
通讯作者:
Summerfield A
Summerfield A
中科院分区:
工程技术2区
文献类型:
--
作者:
Summerfield A

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建筑节能量化的改进方法需要实证措施的支持,而不是未来年度能源需求的模型估计。本文使用功率温度梯度(PTG,W/K)或功率需求的斜率来响应外部空气温度的变化;首先,根据每日能源数据(当室外温度为0-15 °C时)对住宅能源性能进行分类;其次,调查24小时输送功率曲线的变化。PTG的估计值来自567个英国住宅,有118,000天的天然气和电力数据。从多变量回归模型来看,PTG是由居住特征(卧室数量、楼层数量、居住类型和居住年龄类别(均P < 0.001))预测的,而不是由居住者数量预测的。当住宅被分为五分之一的PTG,平均PTG增加了三倍,从第一到第五个五分之一(188至563 W/K,分别)。这反映在输送功率的24小时曲线(30分钟间隔)中:在0 °C下,PTG每下降100 W/K对应于平均早晨和晚上峰值功率下降2.5 kW。使用PTG来估计峰值功率的减少,作为等效的“负瓦”重新定义了能源效率改造和电网弹性的潜在好处。
Improved methods for quantifying energy savings in buildings need to be supported by empirical measures rather than modeled estimates of future annual energy demand. This paper uses power temperature gradient (PTG, W/K), or the slope of power demand in response to changes in external air temperature; first, to categorise dwelling energy performance from daily energy data (when 0–15 °C outside); second, to investigate variations in 24-h profiles of delivered power. Estimates of PTG were obtained from 567 UK dwellings with 118,000 days of gas and electricity data. From a multivariable regression model, PTG was predicted by dwelling characteristics (number of bedrooms, number of floors, dwelling type, and dwelling age category (allp< 0.001)) but not by number of occupants. When dwellings were grouped into quintiles of PTG, mean PTG had threefold increase from the first to fifth quintile (188 to 563 W/K, respectively). This was reflected in 24-h profiles of delivered power (30 min intervals): at 0 °C, each 100 W/K decline in PTG corresponded to ∼2.5 kW decline in mean morning and evening peak power. Using PTG to estimate reductions in peak power as equivalent ‘negawatts’ reframes potential benefits of energy efficiency retrofits and for grid resilience.
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