Building as a virtual power plant, magnitude and persistence of deferrable loads and human comfort implications

Building as a virtual power plant, magnitude and persistence of deferrable loads and human comfort implications
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DOI:
10.1016/j.enbuild.2020.109794
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发表时间:
2020-02
影响因子:
6.7
通讯作者:
M. Royapoor;Mehdi Pazhoohesh;P. Davison;C. Patsios;S. Walker
M. Royapoor;Mehdi Pazhoohesh;P. Davison;C. Patsios;S. Walker
中科院分区:
工程技术2区
文献类型:
--
作者:
M. Royapoor;Mehdi Pazhoohesh;P. Davison;C. Patsios;S. Walker

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这项工作使用高分辨率的数据,从130个电力分表,以12,500平方米的商业建筑作为一个虚拟的发电厂(VPP),通过评估大小和持续时间的电力负荷适合需求响应(DR)。2018年,该建筑的高峰小时需求为48 W/m2,其耗电量(183.2 kWh/m2/yr.)是在低到中等范围内的空调英国投资组合。来自热泵、空气处理机组、电梯、照明、循环泵和干燥空气冷却器的可推迟负荷被用来说明建筑物的DR能力,每个DR周期的最大持续时间为4小时。平均而言,可推迟负荷占建筑物总耗电量的46.4%,在4小时DR循环中,可推迟负荷的特征在于,在100%、41.5%和24.6%的时间内,初始功率(和储存能量)分别为28 kW(401 ± 117 kWh)、109 kW(571±82 kWh)和最终138 kW(625±18 kWh)。在DR事件之后,发现HVAC恢复原始室内气候的能力至少是事件期间气候漂移的两倍。一个线性回归模型被发现是弱在使用外部温度来预测聚合的可延期负荷的大小。
This work uses high resolution data from 130 electricity sub-meters to characterise a 12,500m2commercial building as a virtual power plant (VPP) by assessing magnitude and duration of electrical loads suitable for demand response (DR). In 2018, the building had a peak hourly demand of 48 W/m2and its electricity consumption (183.2 kWh/m2/yr.) was within low to medium range of air-conditioned UK portfolio. Deferrable loads from heat pumps, air handling units, lifts, lighting, circulating pumps and dry air coolers were used to illustrate building's DR capability over a maximum duration of 4 h per DR cycle. On average, deferrable loads form 46.4% of total building electricity consumption and across a 4-hour DR cycle can be characterised as having an initial power (and stored energies) of 28 kW (401 ± 117 kWh); 109 kW (571±82 kWh); and finally 138 kW (625±18 kWh) for 100%, 41.5% and 24.6% of time respectively. Following a DR event, the HVAC ability to restore original indoor climate was found to be at least twice as fast as climatic drift during the event. A linear regression model was found to be weak in using external temperature to predict the magnitude of aggregated deferrable loads.