基于NSGA-Ⅱ的冷源机房设备运行参数多目标优化
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TU831.3

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广东省科技计划项目(2016B090918105);广东省自然科学基金资助项目(2017A030310162, 2018A030313352)


Multi-objective Optimization of Operating Parameters of Central Air Conditioning Cold Source Equipment Room Based on NSGA-Ⅱ
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the Science and Technology Planning Project of Guangdong Province, China (2016B090918105) and the Natural Science Foundation of Guangdong Province (2017A030310162, 2018A030313352)

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    摘要:

    中央空调冷源机房设备系统运行参数优化是提高空调运行性能的重要途径之一,但由于机房设备种类繁多,运行工况复杂,运行参数诸多,参数之间耦合作用较强,其优化问题是学者们广泛关注的重点和难点。为此,本文提出一种基于非支配排序遗传算法Ⅱ(NSGA-Ⅱ)的冷源机房设备运行参数多目标优化方法。以制冷量最大和能耗最低为目标函数,以冷冻出水温度、冷冻回水温度、冷却回水温度、冷冻水流量和冷却水流量五个变量为决策变量,根据实际运行工况设定其约束条件,建立了系统运行参数优化模型。此外,以负荷率、室外环境温度和室外环境湿度作为划分工况的依据,采用等宽离散化方法并结合k-means聚类方法划分出了32种运行工况。最后仿真结果表明,在四种典型运行工况下,多目标优化方法相对于普通优化方式,能得到更高的COP值;同时,多目标优化方法能够使系统能效提升14.35%,能耗降低12.52%。因此,本文提出的优化方法适用于空调领域,并能为工程应用时的参数设置提供一定的指导作用。

    Abstract:

    The optimization of the operating parameters of the equipment system of the central air-conditioning cold source computer room is one of the important ways to improve the operating performance of the air conditioner. However, due to the variety of equipment in the computer room, the complicated operating conditions, the numerous operating parameters and the strong coupling between the parameters, the problem of optimization is the key points and difficulties that the scholars widely concerned about. To this end, it is presented a multi-objective optimization method for operating parameters of cold source equipment room which is based on non-dominated sorting genetic algorithm II (NSGA-Ⅱ). Setting the maximum cooling capacity and the lowest energy consumption as the objective function while the frozen outlet water temperature, frozen return water temperature, cooling return water temperature, frozen water flow rate and cooling water flow rate were decision variables, established a system optimization model of operating parameters, which constraints were set according to the actual operating conditions. In addition, based on the load rate, outdoor ambient temperature and outdoor ambient humidity, 32 working conditions according to the method of constant width discretization and the k-means clustering were divided. The final simulation results show that under four typical operating conditions, the multi-objective optimization method can obtain a higher COP which compares to the ordinary optimization method; at the same time, the energy efficiency could be increased by 14.35% while the energy consumption decreased by 12.52%. In conclusion, the optimization method proposed is not only applicable to the field of air conditioning, but also provide a certain guidance for the parameter setting in engineering applications.

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闫军威,卢泽东,周璇. 基于NSGA-Ⅱ的冷源机房设备运行参数多目标优化[J]. 科学技术与工程, 2021, 21(7): 2896-2903.
Yan Junwei, Lu Zedong, Zhou Xuan. Multi-objective Optimization of Operating Parameters of Central Air Conditioning Cold Source Equipment Room Based on NSGA-Ⅱ[J]. Science Technology and Engineering,2021,21(7):2896-2903.

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  • 收稿日期:2020-06-28
  • 最后修改日期:2020-12-05
  • 录用日期:2020-08-10
  • 在线发布日期: 2021-03-31
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