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Impacts of cooling load calculation uncertainties on the design optimization of building cooling systems

机译:制冷负荷计算不确定性对建筑物制冷系统设计优化的影响

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Cooling load calculation is the basis for the design of building cooling systems. The current design Methods are usually based on deterministic cooling loads, which are obtained by using design parameters or information. However, these parameters contain uncertainties and they will be different from that used in the design calculation when the cooling system is put in use. The actual cooling load profile will deviate from that predicted in design. By considering uncertainties of these parameters, the sizing and configuration of the cooling system can be improved. In this study, a design optimization method is proposed by considering uncertainties related to the cooling load calculation. Impacts caused by the uncertainties of nine factors are considered, including the outdoor weather conditions, internal heat sources and indoor set-points. The cooling load distribution is analyzed. The oversize problem is explained from the viewpoint of uncertainties. By presenting the probability distribution of the cooling load and the potential capital cost, the proposed method can determine the cooling system capacity with quantified confidence. Comparison between the cooling systems with different configurations is also conducted. With the distributions of their energy consumption, decision makers can select the optimal configuration based on quantified confidence. (C) 2015 Elsevier B.V. All rights reserved.
机译:制冷负荷的计算是建筑制冷系统设计的基础。当前的设计方法通常基于确定性的冷却负荷,这些负荷是通过使用设计参数或信息获得的。但是,这些参数包含不确定性,并且与使用冷却系统时的设计计算中所使用的参数不同。实际的冷却负荷曲线将偏离设计中的预测。通过考虑这些参数的不确定性,可以改善冷却系统的尺寸和配置。在这项研究中,通过考虑与冷却负荷计算有关的不确定性,提出了一种设计优化方法。考虑了由九个因素的不确定性引起的影响,包括室外天气条件,内部热源和室内设定点。分析了冷却负荷分布。从不确定性的角度解释了超大问题。通过显示冷却负荷的概率分布和潜在的资本成本,所提出的方法可以量化的置信度确定冷却系统的容量。还对具有不同配置的冷却系统进行了比较。通过能耗的分布,决策者可以基于量化的置信度来选择最佳配置。 (C)2015 Elsevier B.V.保留所有权利。

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