An integrated performance analysis framework for HVAC systems using heterogeneous data models and building automation systems
An integrated performance analysis framework for HVAC systems using heterogeneous data models and building automation systems
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使用异构数据模型和楼宇自动化系统的 HVAC 系统集成性能分析框架
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
J. Garrett
中科院分区：
文献类型：
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作者：
Xuesong Liu;B. Akinci;M. Berges;J. Garrett
供暖、通风和空调（HVAC）系统消耗的能源中有20%以上是由于这些系统中未检测到的故障而浪费的。在过去的三十年里，研究人员开发了数百种计算机算法来自动和连续地分析其能源性能。然而，由于这些算法所需的复杂信息，设施运营商很难将它们部署在现实世界的建筑物中。本文提出了一种集成性能分析框架（IPAF），可用于集成异构数据模型的建筑和暖通空调系统和嵌入式传感器和控制器的动态数据。该框架通过自动提供所需的信息，促进了在不同建筑物和HVAC系统中部署性能分析算法。我们开发和测试我们提出的框架，使用四种不同类型的算法在现实世界的设施。IPAF能够集成三个异构数据模型，准确率为85%，召回率为91%。四种不同类型的算法所要求的检索数据的准确率和召回率均为100%。
More than 20% of the energy consumed by heating, ventilation and air-conditioning (HVAC) systems is wasted due to undetected faults in these systems. In the past three decades, researchers have developed hundreds of computer algorithms to automatically and continuously analyze their energy performance. However, due to the complex information required by these algorithms, it is very difficult for facilities operators to deploy them in real-world buildings. This paper presents an integrated performance analysis framework (IPAF) that can be used to integrate heterogeneous data models of the building and HVAC systems and the dynamic data from embedded sensors and controllers. This framework facilitates the deployment of performance analysis algorithms in different buildings and HVAC systems by automatically providing the required information. We developed and tested our proposed framework using four different types of algorithms in a real-world facility. The IPAF is able to integrate three heterogeneous data models with 85% of precision and 91% recall. The precision and recall for retrieving data required by the four different types of algorithms are both 100%.