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Dynamic modeling, intelligent control and diagnostics of hot water heating systems.

机译:热水加热系统的动态建模,智能控制和诊断。

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摘要

Heating, ventilating and air-conditioning (HVAC) systems have been extensively used to provide desired indoor environment in buildings. It is well acknowledged that 25-35% of the total energy use is consumed by buildings, and space heating systems account for 50-60% of the building energy consumption. Furthermore, roughly half of the energy consumed goes to operation of heating systems. In the past few years the energy use has shown rapid growth. Therefore, it is necessary to design and operate HVAC systems to reduce energy consumption and improve occupant comfort. To improve energy efficiency, HVAC systems should be optimally controlled and operated.;The contributions of this study include the development of a large scale dynamic model of a HWH system for a high-rise building; design of fuzzy logic adaptive control strategies to improve energy efficiency of heating systems and design of model-based FTC systems by using FDD information.;This study focuses on developing advanced control strategies and fault tolerant control (FTC) using information from fault detection and diagnosis (FDD) for hot water heating (HWH) systems. To begin with, HWH system dynamic models are developed based on mass, momentum and energy balance principles. Then, embedded intelligent control strategies: fuzzy logic control and fuzzy logic adaptive control are designed for the overall system to achieve better performance and energy efficiency. Moreover, in designing the advanced control strategies, the parameter uncertainty and noise from measurement and process are taken into account. The extended Kalman filter (EKF) technique is utilized to handle system uncertainty and measurement noise, and to improve system control performance. After that, a supervisory control strategy for the HWH system is designed and simulated to achieve optimal operation. Finally, model-based FDD methods were developed by using fuzzy logic to detect and isolate measurement and process faults occurring in HWH systems. The FDD information was employed to design model-based FTC systems for various faults and to extend the operating range under failure situations.
机译:采暖,通风和空调(HVAC)系统已广泛用于在建筑物中提供所需的室内环境。众所周知,建筑物消耗的能源总量占总能源消耗的25-35%,而空间供暖系统占建筑物能源消耗的50-60%。此外,大约一半的能量消耗用于加热系统的运行。在过去的几年中,能源使用量显示出快速增长。因此,有必要设计和操作HVAC系统以减少能耗并改善乘员舒适度。为了提高能源效率,应该对HVAC系统进行最佳控制和操作。这项研究的成果包括为高层建筑开发HWH系统的大型动态模型。利用FDD信息设计提高供热系统能效的模糊逻辑自适应控制策略,并设计基于模型的FTC系统。本研究的重点是利用故障检测和诊断信息开发先进的控制策略和容错控制(FTC)。 (FDD)用于热水(HWH)系统。首先,基于质量,动量和能量平衡原理开发HWH系统动力学模型。然后,针对整个系统设计了嵌入式智能控制策略:模糊逻辑控制和模糊逻辑自适应控制,以实现更好的性能和能效。此外,在设计高级控制策略时,还要考虑参数不确定性以及测量和过程产生的噪声。扩展卡尔曼滤波器(EKF)技术用于处理系统不确定性和测量噪声,并改善系统控制性能。之后,设计并模拟了HWH系统的监控策略,以实现最佳运行。最后,通过使用模糊逻辑来检测和隔离HWH系统中发生的测量和过程故障,开发了基于模型的FDD方法。 FDD信息用于针对各种故障设计基于模型的FTC系统,并扩展故障情况下的工作范围。

著录项

  • 作者

    Li, Lian Zhong.;

  • 作者单位

    Concordia University (Canada).;

  • 授予单位 Concordia University (Canada).;
  • 学科 Engineering Architectural.;Energy.;Engineering Civil.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 226 p.
  • 总页数 226
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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