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Generalized model-based predictive weather control for the control of free cooling by enhanced night-time ventilation

机译:基于通用模型的预测性天气控制,可通过增强的夜间通风来控制自然冷却

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摘要

Free cooling by enhanced night-time ventilation could be an efficient technique for decreasing the energy demand for the cooling of buildings. Such systems use the ambient cold of surrounding air, which is transported into buildings by mechanical fan-driven ventilation systems. Only carefully designed and operated systems can be efficient enough to compete with other free-cooling techniques, such as evaporative cooling or even compressor-driven mechanical cooling systems. The efficiency of free cooling by enhanced night-time ventilation could be significantly improved if a model-based predictive weather control algorithm is used for operation control. The aim of this article is to present a generalized model-based predictive weather control (G-MPWC) algorithm that was developed with a detailed short time step numerical simulation of the thermal response of the building and free cooling system and simplified weather forecast data. The result of the G-MWPC is a set of control matrixes that includes data on the forecast required night-time air exchange rate and forecast daily coefficient of the performance of the free cooling system regarding the forecast daily average ambient air temperature and amplitude and the pre-set free cooling system on/off temperature difference. An additional matrix that includes data on forecast maximum indoor air temperature is developed for the case of the free cooling system being unable to fulfil pre-set thermal comfort requirements. A unique set of G-MWPS control matrixes must be developed for specific buildings and building operation conditions; afterwards, that control matrix can be used for the predicted controlling of the free cooling system by night time ventilation for the whole range of summer time meteorological conditions. In this article, the method and numerical model for developing a G-MPWC algorithm is presented as well as an example of a control matrix developed for a typical office room. The G-MPWC algorithm was validated for the case of a free-cooled office room. (C) 2016 Elsevier Ltd. All rights reserved.
机译:通过增强夜间通风来进行免费制冷可能是减少建筑物制冷能源需求的有效技术。这种系统利用周围空气的周围冷气,通过机械风扇驱动的通风系统将其输送到建筑物中。只有精心设计和运行的系统才能有效地与其他自然冷却技术(例如蒸发冷却或压缩机驱动的机械冷却系统)竞争。如果将基于模型的预测天气控制算法用于操作控制,则可以通过提高夜间通风来实现自然冷却的效率得到显着提高。本文的目的是提出一种基于通用模型的预测天气预报(G-MPWC)算法,该算法是通过对建筑物和自然冷却系统的热响应进行详细的短时数值模拟以及简化的天气预报数据而开发的。 G-MWPC的结果是一组控制矩阵,其中包括有关预测的所需夜间空气交换率的数据以及有关自然冷却系统性能的每日预测系数,该系数与每日预测的平均环境空气温度和振幅以及预设的自由冷却系统开/关温差。对于自然冷却系统无法满足预设的热舒适性要求的情况,还开发了一个额外的矩阵,其中包含有关预测的室内最高气温的数据。必须为特定建筑物和建筑物运行条件开发一套独特的G-MWPS控制矩阵;之后,该控制矩阵可以用于整个夏季气象条件范围内夜间通风对自然冷却系统的预测控制。在本文中,将介绍开发G-MPWC算法的方法和数值模型,以及为典型办公室开发的控制矩阵的示例。 G-MPWC算法已针对自然冷却的办公室空间进行了验证。 (C)2016 Elsevier Ltd.保留所有权利。

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