The use of environmental control systems has significantly increased in the building sector in order to reduce the energy consumption of heating, ventilation, and air-conditioning (HVAC) systems [1
]. Air handling units (AHUs) are one of the most complex building service systems [2
], and can include heating, cooling, humidifier, mixing element, and heat recovery units, in order to provide the required indoor air quality and thermal comfort in conditioned spaces [3
In a typical AHU, chilled water in the cooling coils cools the air, and hot water (or steam) in the heating coils heats the air, in order to maintain the desired temperature of the supply [4
]. The supply and return fans assist in moving the air for heat exchange, as well as circulating it in the HVAC system at the required flow rate [5
]. Several components are part of a typical system, i.e., the chiller, the boiler, the supply and return fans, and the water pump that consumes a lot of energy [6
Direct expansion ventilation units are becoming more commonly used central air-conditioning technical solutions, in which a refrigerant is directly delivered to the cooling (and heating) coil [7
]. These systems have the potential to save cooling and heating energy use, since they do not require any water pumps for their operation, compared to water-based central air conditioning systems [8
Developers are working really hard to minimalize the energy consumption of their developed devices; however, there are many imperfections in the actual available product catalogues, technical data, and technical support service systems, especially for the annual energy designing provided by the ventilation producers for building service and energy design engineers [10
]. Therefore, it would be particularly significant to have measured and recorded data obtained from field studies [12
], which may be utilized in the course of design work, and which would allow a proper estimation of the expected realizable annual energy consumption of air handling elements in the function of the temperature and relative humidity of ambient and indoor air and operating parameters [14
Stamatescu et. al [15
] presented the implementation and evaluation of a data mining methodology based on collected data from a more than one-year operation. The case study was carried out on four AHUs of a modern campus building for preliminary decision support for facility managers. The results are useful for deriving the behavior of each piece of equipment in various mode of operation and can be built upon for fault detection or energy efficiency applications. The imperfection of their work is the missing data for air condition parameters (temperature and humidity) between the coils and mixing box; before and after the fans, which cannot be neglected, since the electrical motor of the fans increases the air temperature and decreases the relative humidity; and the air volume flow rate, which changes during the operation. All these missing parameters have a significant effect on the energy efficiency of the ventilation system.
Hong et. al [16
] conducted a case study on a running AHU for data-driven predictive model development. In order to develop the optimal model, input variables, the number of neurons and hidden layers, and the period of the training data set were considered. The results and conclusions presented for the one-year field study could have much better reflected the reality from the view point of energy performance, if further temperature and relative humidity sensors had been placed between the coils and humidifier element, before and after the fans. Only focusing on energy performance data recording is not enough, since the desired indoor air quality and thermal comfort are also significant parameters that need to be considered. To draw a more exact conclusion from this point of view, the CO2
parameter should also have been monitored and recorded in the outdoor air inlet (OA) and supply air outlet (SA) sections in the investigated AHU.
Based on a literature review of the field, there are some case studies in which the heat recovery unit has also been considered in the ventilation system. Noussan et. al [17
] presented results obtained from an operation data analysis of an AHU serving a large university classroom. The main drivers of 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 allowed a comparison of the actual operation of the AHU and the expected performance from nominal parameters to be performed. Calculations were made considering the operation analysis of the heat recovery unit over different years; however, the existing system does not include any heat or energy recovery devices, so there are no exact measured data from this point of view.
Bareschino et. al [18
] compared three alternative hygroscopic materials for desiccant wheels considering the operation of the air handling unit they are installed in. Their results demonstrated that a primary energy saving of about 20%, 29%, and 15% can be reached with silica-gel, milgo, and zeolite-rich tuff desiccant wheel-based air handling units, respectively. The results were given based on a simulation and there is no exact measured data, which would be significant for making precise and clear energetic conclusions.
In this work, a field study is carried out on an existing, operating ventilation system that includes an air-to-air rotary heat wheel, a mixing box element, and a direct expansion cooling coil connected to a variable refrigerant volume outdoor unit. One of the main objectives of the present paper is to investigate the cooling energy performance and thermal behavior of each air handling component separately. To achieve this, an advanced data recording and remote monitoring system was considerately developed by building management system-based software. The system includes an electricity energy meter installed in the outdoor unit, as well as temperature, humidity, air velocity, and CO2 sensors placed in the inlet and outlet section of all the air handling elements that have an effect on the cooling process. The purpose of the CO2 measurements was to investigate the CO2 cross-contamination, which occurs from the exhaust air flow to the supply air flow in the air-to-air rotary heat wheel, resulting in indoor air quality degradation. The novelty of this research is the accurate determination of the seasonal effectiveness and the energy saving impact of the heat wheel on the electric energy consumption of the outdoor unit. Moreover, the relative average and maximum value of CO2 cross-contamination in the rotary heat recovery using the developed measurement system in the cooling period are presented. A further innovation in this study is the analytical evaluation method developed, which shows a good agreement between the calculated and measured energy consumption.
4. Results and Discussion
The reference period of the study is the year 2019, more specifically, the cooling period from June 1st to August 31st for a total of 92 days and 25,296 data samples for each of the used measurement points. The AHU is intermittently operated 12 h/day from 8:00 till 20:00 7 days/week. Since this research work focused on the ventilation energy saving of the heat recovery unit’s DX cooling coil, the mixing box was shut off during the data recording.
The air handling parameters obtained from the field study for the investigated AHU are illustrated in Figure 5
, Figure 6
and Figure 7
with a monthly timescale. Since the ambient air temperature was the highest in June during the whole cooling season, this relevant month was selected to present the measured data resulting from the data collection.
shows the temperature of the outdoor air (to
), the air in the supply outlet sections of the heat wheel (tHWS
) and DX coil (tDX
), and the exhaust inlet section of the heat wheel (tHWE
) over time at hourly intervals in June.
Considering the hottest periods in the cooling season, the ambient air temperature decreased by about 4–5 °C due to the pre-cooling effect of the heat wheel, and by an additional 18–20 °C, provided by air cooling of the DX coil.
shows the measured relative humidity of the outdoor air (RHo
), the air in the supply outlet sections of the heat wheel (RHHWS
) and DX coil (RHDX
), and the exhaust inlet section of the heat wheel (RHHWE
) over time at hourly intervals in June.
The ambient air relative humidity decreased by about 60% due to the air cooling process. In this way, the supplied air relative humidity was around 90%.
shows the enthalpy of the outdoor air (ho
), the air in the supply outlet sections of the heat wheel (hHWS
) and DX coil (hDX
), and the exhaust inlet section of the heat wheel (hHWE
) over time at hourly intervals in June.
Considering the hottest periods in the cooling season, the ambient air enthalpy decreased by about 8–10 kJ/kg due to the pre-cooling effect of the heat wheel, and by an additional 30–35 kJ/kg, provided by air cooling of the DX coil.
shows the sensible effectiveness data (εs
) for the outdoor air temperature in June.
Based on the results, the average sensible effectiveness of the heat wheel was 79.6% during the whole cooling season and the maximum value of 97.6% was recorded in June.
shows the energy saving of the air-to-air rotary heat wheel (QHW_saved
) in terms of the energy consumption of the DX coil, and the cooling energy consumption of the DX coil with the heat wheel operation (QDX_HW
) and without the heat wheel operation (QDX_WO_HW
), when the DX coil directly cools the hot ambient outdoor air to the supply air conditions during the cooling season.
Based on the results, the energy saving of the heat wheel was 2491 kWh in terms of the energy consumption of the DX coil, the cooling energy consumption of the DX coil with the heat wheel operation was 7434 kWh, and that without the heat wheel operation was 9926 kWh.
shows the electric energy consumption of the outdoor unit based on the direct real electric energy consumption measurements (PVRV_HW_M
) and the calculations made using the recorded air condition parameters with (PVRV_HW
) and without the heat wheel operation (PVRV_WO_HW
) for the whole cooling period.
The real electric energy consumption of the outdoor unit based on the measurements was 1889 kWh and the calculations resulted in 1863 kWh consumption with and 2488 kWh consumption without the heat wheel operation for the whole cooling period.
Since the difference (ΔPVRV_HW
) is only 26 kWh and rate of deviation (ΔPVRV_HW_REL
) is 1.36% between the values of the measured and calculated electric energy consumption of the variable refrigerant volume (VRV) outdoor unit with the heat wheel operation, Figure 10
shows very good agreement between the experimental and numerical results. The evaluated energy efficiency ratio is 3.94 based on the measurements (EERM
) conducted for the whole investigated cooling season, which is only 0.05 less than the value of 3.99 given by the producer. The energy impact of the heat wheel results in 624 kWh energy being saved (ΔPVRV_HW_saved
), which is equivalent to a 25.1% energy saving rate (ΔPVRV_HW_saved_REL
) in terms of the electric energy consumption of the outdoor unit for the whole cooling period, compared to the system without the heat wheel operation.
shows the measured CO2
concentration of the outdoor air (CCO2_o
), the air in the supply outlet section of the heat wheel (CCO2_HWS
), and the exhaust inlet section of the heat wheel (CCO2_HWE
) over time at hourly intervals in June. There are a few hours in Figure 11
when the recorded CO2
values of the air were lower in the supply outlet section than in the exhaust inlet section of the heat wheel, probably due to the uncertainties and transient response characteristics of the CO2
Having completed the measurements of the whole cooling period, the average CO2 cross-contamination value () was 63.9 ppm. The average value of the CO2 concentration in the exhaust inlet section of the heat wheel () was 390.1 ppm. Based on the results, the relative average of CO2 cross-contamination () was 16.4% and the maximum value () was recorded as 30.1%, considering the whole cooling season. To determine how the obtained values influence the indoor air quality inside of the conditioned spaces, further indoor air quality measurements are necessary (with the use of further measurement devices and questionnaires), which can act as a continuation of this research work, but exceed the limitation of this recent ongoing research project.
In this research work, a field study was carried out on the cooling energy performance of an existing, operating ventilation system under the operation of an air-to-air rotary heat wheel and direct expansion cooling coil, connected to a variable refrigerant volume outdoor unit. The major findings obtained from the study can be summarized as follows:
1. The operation of the heat wheel has a significant cooling energy saving impact on the electric energy consumption of the outdoor unit. Comparing the measured ventilation system with an air handling unit without a heat wheel operation, the cooling energy consumption is 25.1% higher;
2. Based on the measurements, the real sensible effectiveness and the CO2 cross-contamination of the heat wheel are not in accordance with the design assumptions for the cooling period;
3. The sensible effectiveness of the heat wheel performed 4.7% higher than the data (74.9%) given in the technical data book of the producer;
4. Having completed the measurements for the whole cooling period, the amount of CO2 cross-contamination in the heat wheel was much higher (with 16.4% relative average and 30.1% maximum values) than predicted during the designing phase.
Future work will focus on heating and annual energy performance investigations by conducting further field studies on the system. Moreover, simulation model development will also be considered for an annual energy consumption investigation of the existing ventilation system and model validation is planned based on data given by an annual field study. The long-term goal is to develop a simulation model which is suitable for determination of the energy consumption of ventilation systems in the design phase with a high accuracy.