Can whole building energy models outperform numerical models, when forecasting performance of indirect evaporative cooling systems?
Can whole building energy models outperform numerical models, when forecasting performance of indirect evaporative cooling systems?
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在预测间接蒸发冷却系统的性能时,整个建筑能源模型能否优于数值模型?
DOI:
10.1016/j.enconman.2020.112886
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发表时间:
2020
影响因子:
10.4
通讯作者:
Badiei A
中科院分区:
文献类型:
--
作者:
Badiei A
This paper presents a whole building energy modelling work incorporating a state-of-the-art indirect evaporative cooling system. The model is calibrated and validated with real-life empirical data, and is capable of representing actual performance of the system with high reliability. The investigated system is a novel super-performance Dew Point Cooler (DPC) with a guideless and corrugated Heat and Mass Exchanger (HMX). The DPC is modelled as part of the whole building energy model through detailed description of system and building characteristics at source code level. The developed model has been simulated in all different climates that an Indirect Evaporative Cooling (IEC) system can be operated, namely: subtropical hot desert, humid continental, Mediterranean, and hot desert climates. The performance predictions has been tested against experiments and numerical model of the same system, and a detailed investigation of modelling approaches to efficiently and effectively model aforementioned systems has been provided.The calibrated and empirically validated whole building energy model predicted the key performance parameters of the dew point evaporative cooling system with mean error values limited to 4.1%. The highest COP values recorded by experiments and whole building energy simulations were 51.1 and 49, respectively. The whole building energy model proved to better predict the performance of dew point evaporative cooler, when compared to numerical models, by incorporating the building-side parameters into the model. This modelling work paves the way toward detailed investigation of the advanced cooling systems within building context to achieve optimised performance of the system in wide range of buildings and operating conditions.
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影响因子:
6.7
作者:
Badiei A
通讯作者:
Badiei A
影响因子:
2.9
作者:
Moustris, K. P.;Nastos, P. T.;Paliatsos, A. G.
通讯作者:
Paliatsos, A. G.
影响因子:
9
作者:
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通讯作者:
Li, Junming
DOI:
--
发表时间:
2014
期刊:
影响因子:
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作者:
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通讯作者:
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