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Model-based space temperature cascade control for constant air volume air-conditioning system

机译:定风量空调系统的基于模型的空间温度级联控制

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摘要

Constant air volume (CAV) air-conditioning system is still widely used for cooling/heating buildings because of the requirement of air changes in many occasions and its simple system design as well as low primary cost. The space temperature of the CAV air-conditioning system is usually controlled by using conventional proportional-integral (PI) control algorithm, which tracks the space temperature by regulating the opening of the water valve directly. However, the control performance of the space temperature is usually unsatisfactory because of the significant thermal inertia of the building mass and the large volume of the indoor air. This paper proposes a model-based cascade control method for the space temperature control of the CAV system aiming to improve the control robustness and accuracy. A supply air temperature prediction model is developed to predict the system demand supply air temperature based on the real-time load condition and space temperature. The prediction is used as the set-point, and the space temperature is well controlled by regulating the water valve opening. The proposed control method was validated in a simulation CAV system as well as on an experimental platform. The validation results show that the proposed model-based cascade control method achieves better space temperature control performance than the conventional PI control. This control method may well track the space temperature directly both in the virtual CAV system and the real experimental system.
机译:恒定风量(CAV)空调系统由于在许多场合需要换气且其系统设计简单且初级成本较低,因此仍广泛用于制冷/制热建筑物。 CAV空调系统的空间温度通常通过使用常规的比例积分(PI)控制算法来控制,该算法通过直接调节水阀的开度来跟踪空间温度。然而,由于建筑物体的热惯性很大且室内空气量很大,因此对空间温度的控制性能通常不能令人满意。提出一种基于模型的级联控制方法,用于CAV系统的空间温度控制,以提高控制的鲁棒性和准确性。建立了供气温度预测模型,以基于实时负载条件和空间温度来预测系统需求供气温度。将该预测用作设定点,并通过调节水阀开度很好地控制空间温度。所提出的控制方法在模拟CAV系统以及实验平台上得到了验证。验证结果表明,所提出的基于模型的级联控制方法比常规的PI控制具有更好的空间温度控制性能。这种控制方法可以很好地直接在虚拟CAV系统和实际实验系统中跟踪空间温度。

著录项

  • 来源
    《Building and Environment》 |2018年第11期|308-318|共11页
  • 作者单位

    Huazhong Univ Sci & Technol, Dept Bldg Environm & Energy Engn, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Dept Bldg Environm & Energy Engn, Wuhan 430074, Hubei, Peoples R China;

    Dalian Univ Technol, Sch Municipal & Environm Engn, Dalian 116000, Peoples R China;

    Dalian Univ Technol, Sch Municipal & Environm Engn, Dalian 116000, Peoples R China;

    Huazhong Univ Sci & Technol, Dept Bldg Environm & Energy Engn, Wuhan 430074, Hubei, Peoples R China;

    Huazhong Univ Sci & Technol, Dept Bldg Environm & Energy Engn, Wuhan 430074, Hubei, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    CAV system; Model prediction; Model-based cascade control; Space temperature control; Robust control;

    机译:CAV系统;模型预测;基于模型的级联控制;空间温度控制;鲁棒控制;

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