How Monitoring the Behavior of HVAC Systems Can Support Filter Performance Assessment

A ducted air system is a common way to heat and cool an occupied building. Most devices in such systems - fans, ductwork, coils, chillers, etc. - have well-described relations to building thermal requirements and thermal characteristics. However, for one device category, air filters, the relation to thermal and other factors is poorly developed. Thermal requirements change filter airflows by season, but filter performance depends primarily on the combination of outdoor aerosol size distribution and concentration, the desired indoor air quality, and the numbers and activities of people in the building spaces. Filter pressure drop normally increases during its operating life, which complicates filter performance and affects other system elements. Fully instrumented studies of actual filter-containing systems over extended time periods are needed to develop the relationships between characteristics of a system and its energy usage, capital costs and operating costs. This includes the characteristics of indoor and outdoor particles affecting the performance of the air filters in the system

Operational performance of an Air Handling Unit: insights from a data analysis

Space heating and cooling is one of the most relevant causes of energy consumption in both residential and tertiary sector buildings. In particular, service buildings and offices are mostly served by all-air HVAC systems in which control logics are fundamental to guarantee reliability and performance. Building automation systems are therefore becoming more and more relevant as a support tool for reducing the energy consumption in these contexts. For this reason, the detailed analysis of operational data from real units can help in understanding the main variables that affect the performance and functioning of all-air systems. This paper presents some results from operation data analysis of an Air Handling Unit (AHU) serving a large university classroom. The main drivers of the energy consumption are highlighted, and the classroom occupancy is found to have a significant importance in the energy balance of the system. The availability of historical operation data allows performing a comparison between the actual operation of the AHU and the expected performance from nominal parameters. An example of fault detection is proposed, considering the operation analysis of the heat recovery unit over different years