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Development of an optimal control method of chilled water temperature for constant-speed air-cooled water chiller air conditioning systems

机译:恒速空气冷却水冷空调系统的冷水温度最优控制方法

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摘要

Constant-speed air-cooled water chillers (CAWCs) are typically on-off controlled in accordance with a fixed set point of chilled water return temperature (T-wr), which seriously restricts their efficiency during part load conditions. To improve the performance of CAWC air conditioning (A/C) systems, this paper developed an optimal control method to reset the T-wr of CAWCs real time. Firstly, a simulation platform was established based on an actual office building with a CAWC A/C system using fan coil units (FCUs) as terminal devices in Beijing. Secondly, a dataset of optimal values of at different part load conditions was calculated by simulation. Thirdly, to enable the practical use of the dataset, a general regression neural network (GRNN) model was built to predict the optimal T-wr value according to three ambient parameters and one operation parameter. Finally, a GRNN based optimal control method was developed for the CAWC/FCU A/C system. The numerical results demonstrated that the proposed method can achieve a good control over indoor thermal environment, and lead to a reduced energy use for the A/C system by 11.0% over the cooling season. This study provided a promising control method of chilled water temperature for CAWC/FCU A/C systems in dry climates.
机译:恒速空气冷却水冷钻(CAWC)通常根据冷却水返回温度(T-W)的固定设定点的开关控制,这在部分负载条件下严重限制了它们的效率。为了提高CAWC空调(A / C)系统的性能,本文开发了一种最佳的控制方法,可以实时复位CAWCS的T-WR。首先,基于具有CAWC A / C系统的实际办公大楼建立了模拟平台,该建筑用CAWC A / C系统使用风扇线圈单元(FCU)作为北京的终端设备。其次,通过仿真计算不同部分负载条件的最佳值的数据集。第三,为了实现数据集的实际使用,建立了一般回归神经网络(GRNN)模型以根据三个环境参数和一个操作参数预测最佳T-WR值。最后,为CAWC / FCU A / C系统开发了基于GRNN的最优控制方法。数值结果表明,该方法可以实现对室内热环境的良好控制,并导致A / C系统的能量使用降低11.0%。冷却季节。本研究为干气中的CAWC / FCU A / C系统提供了有希望的冷冻水温控制方法。

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