Mixed Air Temperature Research Articles

Optimal Control of Air-Side Economizer

The economizer system is a method of improving energy efficiency through the operating method, which introduces outdoor air through dampers when the outdoor air temperature or enthalpy is lower than the that of the indoor air. The set values used for economizer control include the mixed air temperature and high and low limits. The set values are presented as fixed values in the relevant standards and are controlled to be fixed during actual operation, which may lead to issues such as indoor discomfort, poor indoor air quality, and energy wastage. Therefore, it is necessary to optimize economizer control by determining appropriate set values considering the indoor and outdoor environments. To this end, this paper reviewed the economizer system, control method, control set values, and prediction models in buildings. As a result, it was concluded that optimal economizer control is possible by utilizing a prediction model.

Spatio-Temporal Heterogeneity of the Urban Heat Effect and Its Socio-Ecological Drivers in Yangzhou City, China

Rapid urbanization and land-use changes may affect the intensity of urban heat islands (UHIs). However, research on the eastern Chinese city of Yangzhou is lacking. Using land cover data and the InVest Urban Cooling model, this study evaluated the spatiotemporal heterogeneity of the UHI effect from 1990 to 2020 and its socioecological drivers in Yangzhou City. Landscape pattern indices such as patch area (CA), percentage of landscape (PLAND), number of patches, patch density, and aggregation index were created using Fragstats 4.2 software. Several social indicators, such as gross domestic product (GDP), night-light index, and population density, were considered to explore their correlation with UHI indicators. During the past three decades, rapid urbanization in Yangzhou has intensified the UHI effect, with the cooling capacity (cc park) and heat mitigation index (HMI) decreasing by ~9.6%; however, the mixed air temperature (T air) has increased by 0.14 °C. The main heat island areas are concentrated in southern Yangzhou, including the Hanjiang and Guangling districts, and have expanded over time. T air was positively correlated with GDP, night-light index, and population density. Moreover, for the impervious land use type, cc park and HMI were negatively correlated with CA and PLAND (p < 0.01). This study contributes to a deeper understanding of the dynamics of UHIs and provides valuable insights for policymakers, urban planners, and researchers striving to create sustainable and climate-resilient cities in Yangzhou.

Mixed air temperature reset by data-driven model for optimal economizer control

An economizer system means that outside air is introduced to reduce energy consumption when the outdoor air is sufficient to be used for cooling, and adjusts the outdoor, ventilation, and exhaust damper to maintain the mixed air temperature set value during heating, ventilation and air conditioning control. The set values for economizer control include high and low limit that determine whether to operate economizer, and mixed air temperature. At this time, the mixed air temperature is set to a fixed value. Such a fixed set value may cause problems such as energy waste because it does not consider changes in indoor and outdoor environments. Therefore, in this study, an optimal economizer control was developed that produces the maximum economizer effect by resetting the mixed air temperature set value considering the indoor and outdoor conditions. For this, a data-driven prediction model was developed, and based on the prediction model, an optimal economizer control was developed that resetting the mixed air temperature set value. And the developed control was evaluated by TRNSYS-Matlab co-simulator, and as a result, the mixed air temperature set value was changed in real time, and energy consumption was reduced by about 20% compared to the dry-bulb temperature control.

Optimal Economizer Control of VAV System using Machine Learning

Energy efficiency of the HVAC system can be improved through system renovation and operating method improvement. Economizer control, one of the energy efficient measures through improvement of operating method, introduces outdoor air when outdoor air is sufficient for cooling. There are high/low limit that determine the range of economizer control and mixed air temperature as control set-points. Economizer is controlled with the user's or manager's experience, and the set-point is operated fixed. This causes problems energy waste because it does not consider indoor and outdoor environments. Therefore, the purpose of this study is to develop an optimal economizer control of VAV system that resetting the set-point considering the indoor and outdoor environments. To this, a machine learning model was used to develop a model that predicts the future state based on the current state. Based on the developed prediction model, the optimal economizer control of VAV system that resets the mixed air temperature set-point in real time was developed and the control method was evaluated through simulation. As a result, it was confirmed that the mixed air temperature set-point changed in real time, and that about 20% of energy consumption was saved compared to the existing dry- bulb temperature control.

Predictive Model for the Optimized Mixed-Air Temperature of a Single-Duct VAV System

As global warming accelerates due to greenhouse gas emissions, more efforts are required to reduce greenhouse gas emissions. One of the methods used to save building energy is the efficient management of building mechanical systems. The economizer control of HVAC systems is an energy-efficient measure that improves operating methods by introducing outdoor air to save cooling energy when the outdoor-air temperature is sufficiently low. When the HVAC system is operated using economizer control, cooling energy can be saved, and the set-point of the mixed-air temperature is kept constant. Several studies are being conducted on the saving of energy using economizers. Although various studies have been conducted on the control of economizers, there is insufficient research dealing with the optimal control of mixed-air temperature in economizers that consider real-time changes. Therefore, in this study, predictive model-based mixed-air temperature optimization for a single-duct VAV system was constructed. For this, an ANN (Artificial Neural Network) that could be analyzed regardless of the variables was applied to predict the load and energy consumption and a simulator was constructed for the optimized mixed air temperature of the system. The predictive model-based control was evaluated in terms of its thermal comfort and energy, along with the existing economizer control. According to the application of the optimal economizer control, the energy consumption of the building was reduced by 28.9% compared to the existing dry-bulb temperature control, and was within ±1 °C of the indoor-air temperature set point.

Gray-box virtual sensor of the supply air temperature of air handling units

Building automation system uses several networks of sensors for continuous monitoring of building control systems for energy-efficient operation. Physical sensors are costly and need frequent calibration. The accurate measurement of supply air temperature from the air handling units (AHUs) has an important effect on the control of cooling coil, supply air temperature and supply airflow rate delivered to rooms. In the case when such a sensor gives erroneous measurements, a virtual sensor can replace temporarily the faulty sensor, and it can also be used for automated fault detection of HVAC systems. This article proposes two different gray-box (models A and B) for predicting the supply air temperature of air handling units that were developed and tested using the measurements from two buildings. The models require the measurement of three variables (mixed air temperature, cooling coil valve signal, and chilled water inlet temperature). The results of both models are discussed and compared. A sliding window approach for cross-validation of the models was also carried out. The developed gray-box models A and B could be integrated into BAS for virtual measurement, virtual calibration, and fault detection in HVAC systems.

이코노마이저 제어 시 공조기 혼합온도 센서 오차에 따른 냉방 에너지 소요량 비교 분석

The purpose of this study is to analyze the cooling energy consumption according to the error of the mixing temperature sensor in economizer control. When controlling the economizer, the outside air and the return air volume are controlled according to the mixed air temperature setpoint. Since it must be mixed and supplied to the room, accuracy of measuring the mixing temperature is required. However, in existing air conditioners, the mixing temperature sensor is mostly installed in one place in the mixing chamber. In addition, the installation position of the mixing temperature sensor is different depending on the automatic control construction company and the site situation. This results in low accuracy of the mixing temperature sensor. In this study, in order to examine the reliability of the mixing temperature sensor during economizer control, the measurement error of the air conditioning mixing temperature sensor was measured and the cooling energy requirements were compared. In addition, the mixing temperature correction model is proposed to improve the reliability of the existing mixing temperature sensor. And the outdoor air intake rate before and after mixing temperature correction model was compared. The existing mixing temperature sensor was found to have an error of about -0.4 °C compared with the measurement result. In addition, the cooling energy requirements were analyzed according to the error of the mixing temperature sensor, and it was confirmed that up to about 10,000MJ of cooling energy could be wasted according to the mixing temperature setpoint. In addition, additional outdoor air intake rate of up to 3% is required after temperature sensor correction.

Development of Economizer Control Method with Variable Mixed Air Temperature

Achieving energy efficiency by improving the operating method of the system used in existing buildings is attracting considerable attention. The Building Design Criteria for Energy Saving was established to induce energy saving design in the domestic construction field, and the introduction of a free-cooling system, such as an economizer system, as an item of the mechanical sector, was evaluated. The economizer is an energy saving method that reduces the building load by introducing outdoor air through damper control according to the indoor and outdoor conditions. The system consists of dry-bulb temperature control and enthalpy control and the mixed air temperature is kept constant in the conventional economizer controls. On the other hand, in dry-bulb temperature control, when the set value of the mixed air temperature is changed according to the load, additional energy savings are expected compared to the conventional control method. Therefore, this paper proposes an economizer control that makes the mixed air temperature variable according to the load in a Constant Air Volume single duct system. For this, a load prediction is needed and an Artificial Neural Network is used for the load prediction. In addition, the relationship between the mixed air temperature and energy were analyzed using the BIN method and TRNSYS 17. Based on the results of previous analysis, a control method which predicting the load using Artificial Neural Network and controlling the mixed air temperature according to the predicted load in the dry-bulb temperature control of a Constant Air Volume single duct system is proposed and the proposed control was applied to the dynamic simulation program and compared with the conventional control. The results show that the temperature of each room was 21–23 °C in summer and 22.5–26 °C in winter when the economizer was controlled using the proposed control method and the energy consumption analysis showed that 19% of the energy was reduced compared to the conventional method when the proposed method was controlled.

Cooling energy performance analysis depending on the economizer cycle control methods in an office building

The current building tends to pursue high air-tightness for the reduction of the outside air supply to prevent an increase in the energy consumption of air conditioning, resulting in high dependency on mechanical ventilation and adverse effects on indoor air quality, occupant health and productivity. In this circumstance, many developed countries improved the ventilation regulation, but mere increase in the outdoor air introduction without considering the outdoor condition elevated the cooling energy. Therefore, study of the economizer cycle system that can cause fresh outside air introduction and energy saving has been actively conducted. In this study, we analyzed different economizer control methods, addressing mixed air temperature, outdoor air fraction and cooling demand according to the outdoor air temperature. Also, we analyzed the energy consumption of the three control types of the economizer cycle through detailed EnergyPlus simulation modeling under a variety of climatic conditions. As a result, differential enthalpy control method showed the greatest energy saving by around 10% under Korean climatic conditions compared to other methods. Differential dry-bulb control method showed 12.7% lower energy consumption than no economizer method in an intermediate period, but it did show 7.1% more energy usage during the summer period under a humid region. When properly considering the latent load, it was found that the resultant energy saving potential due to economizer operation is significant.

Virtual sensors for rooftop unit air-side diagnostics

In this article, virtual sensors for air-side diagnostics are developed and validated for rooftop air conditioners. The virtual air-side sensors require indoor fan differential pressure and speed measurements. Experimental data from laboratory measurements are used to evaluate the accuracy of the virtual sensors. Methodologies for improving the accuracy of air-side temperature sensors often used for outdoor-air economizer diagnostics have also been developed and evaluated. Outdoor-air temperature correction correlations improve single-point temperature inaccuracy caused by exhaust-air recirculation. A model correcting a single-point mixed-air temperature measurement for inaccuracy caused by thermal stratification and non-uniform velocity distributions at the evaporator inlet has also been described and validated. Finally, methods for estimating outdoor ventilation air fraction are presented and compared to measurements.

Simulation of the HCCI Combustion Based on Single-Zone Combustion Model

A single-zone HCCI combustion model coupled with chemical reaction kinetics mechanisms was set up by AVL-BOOST and CHEMKIN module based on a variable lift and timing (VLT) gasoline. In order to achieve HCCI combustion, the negative valve overlap (NVO) strategy was used to raise the temperature of mixed air in the simulation. In this paper, the HCCI combustion was compared with the conventional SI combustion, then the feasibility of using single-zone model to simulate the HCCI combustion was verified and the HCCI operation region was predicted under specific speed, compression ratio, air-fuel ratio conditions by this model.

Transient Analysis of Inlet Fogging Process for Gas Turbine Systems

Gas turbine inlet fogging is a method of cooling intake air by injecting demineralized water in the duct through the special atomizing nozzles. Gas turbine cycles with inlet fogging could offer enhanced efficiency with low complexity, so the inlet air-cooling is considered the most cost-effective way to increase the power output as well as thermal efficiency of gas turbines. In this work the inlet fogging process is modeled based on the evaporation of droplets. Transient behaviors of the process are investigated with analytic expressions obtained by considering heat and mass transfer and thermodynamic relations. Effects of water injection ratio on the transient behaviors of temperature of mixed air, mass of liquid droplets, mass flux and heat transfer from the droplets are thoroughly investigated. Results show also the dependencies of system parameters on the critical injection ratio and evaporation time.

Temperature and humidity control inside an automobile during heating period

This article investigates a control strategy for the automobile climate control problem; in particular, the heating mode in winter is considered when the initial car compartment temperature and outside temperature are colder than comfortable. By analyzing the air-conditioning processes involving the automobile air-handling unit operating in various weather conditions on a psychrometric chart, a control strategy is developed based upon the concept of conservation of sensible heat and latent heat. Irrespective of the car compartment's initial condition, the control strategy is to control air flow and mixed air temperature such that the compartment conditions in terms of temperature and humidity reach a set condition. The proposed strategy is composed of two parts. The first is to adjust air mass flow rate by balancing the latent heat transfer between ventilation and automobile compartment. Meanwhile, the second part is to control the percentage of heating air flow rate such that a precise temperature can be maintained. In short, balancing the sensible heat transfer among the air condition processes is essential to achieving temperature control, as variation in the net sensible heat will lead to changes in temperature. The proposed control strategy is evaluated in a Matlab/Simulink simulation environment. The results suggest that the proposed control strategy results in an improved indoor humidity level when compared to traditional fuzzy control.

A Smart Mixed-Air Temperature Sensor

Accurate mixed-air temperature (MAT) measurements are notoriously difficult to obtain in packaged air-conditioning equipment for small commercial applications because of space constraints and the use of small mixing chambers. However, MAT is important for control of economizers and in diagnostic algorithms for both economizers and vapor compression equipment. This paper demonstrates that a single-point measurement of MAT can provide accurate results when combined with a correlation for bias error that depends on damper control signal and difference between outdoor and return-air temperature. The correlation could be determined using a self-calibration procedure with measurements of mixed, outdoor, return, and supply air temperatures. A system was tested in a laboratory over a wide range of outdoor conditions and damper positions, and the single-point measurement errors were reduced by about a factor of five when using the bias correction. Furthermore, errors in outdoor air fraction (OAF) determined from temperature measurements were reduced by about a factor of four.

Model-based Fault Detection and Diagnosis of HVAC systems using Support Vector Machine method

Preventive maintenance plays a very important role in the modern Heating, Ventilation and Air Conditioning (HVAC) systems for guaranteeing the thermal comfort, energy saving and reliability. Its key is a cost-effective Fault Detection and Diagnosis (FDD) method. To achieve this goal, this paper proposes a new method by combining the model-based FDD method and the Support Vector Machine (SVM) method. A lumped-parameter model of a single zone HVAC system is developed first, and then the characteristics of three major faults, including the recirculation damper stuck, cooling coil fouling/block and supply fan speed decreasing, are investigated by computer simulation. It is found that the supply air temperature, mixed air temperature, outlet water temperature and control signal are sensitive to the faults and can be selected as the fault indicators. Based on the variations of the system states under the normal and faulty conditions of different degrees, the faults can be detected efficiently by using the residual analysis method. Furthermore, a multi-layer SVM classifier is developed, and the diagnosis results show that this classifier is effective with high accuracy. As a result, the presented Model-Based Fault Detection and Diagnosis (MBFDD) method can help to maintain the health of the HVAC systems, reduce energy consumption and maintenance cost.

A fuzzy sensor for measuring the mixed air temperature in air-handling units

The paper describes the development of a fuzzy sensor for measuring the average temperature of the air leaving the mixing-box of an air-handling unit. This measurement is often required by schemes for automatically detecting the presence of faults in air-conditioning systems. The measurement of the mixed air temperature is notoriously difficult because of spatial variations in the air temperature and velocity immediately downstream of the mixing-box. Variations in the sensor bias are investigated using a computer simulation of a typical mixing-box based on computational fluid dynamics. The simulation data are used to train a fuzzy relational model that relates the measured temperature to the average temperature of the air. The resulting fuzzy sensor takes bias errors into account and provides an indication of the uncertainties associated with the estimated average temperature at the current operating conditions. Results are presented that show how auxiliary information can be used to reduce the measurement uncertainties.

A comparison of CFD-simulations and measurements of the temperature stratification in a mixing box of an air-handling unit

This paper presents a comparison between CFD-simulations and measurements of the temperature stratification in a mixing box of an air-handling unit. We have used data from field measurements during a period of over a year for different outside temperatures. We performed two-dimensional CFD-simulations for four different outside temperatures with commercially available software. The measurements as well as the simulations show that the temperature difference between the upper part and the lower part of the duct downstream of the mixing box is considerable. It increases, as the outside temperature decreases. However, the discrepancies between the measurements and the simulations are large. The reasons for this are uncertain boundary conditions and modelling errors leading to an inaccurate simulation result. The stratification downstream of the mixing box implies large sensor errors and the use of the mixed air temperature for control and fault detection must therefore be questioned. Averaging sensors, which take a mean value over the duct section, can be used but do not consider differences in velocities and are therefore not accurate either. In order to, for example, use CFD as a tool to decide the optimal sensor location a more accurate model and more information regarding the boundary conditions is needed. Copyright © 2001 John Wiley & Sons, Ltd.

96/04259 How much air mixing is enough?

The three charts presented in this article are intended to provide the HVAC system designer with a method that can be used to select the type of mixing system needed for each particular HVAC system. These charts are based on an economizer control strategy wherein 100% outside air is introduced into a system when the outside air temperature is equal to the mixed air temperature set point. As the outside air temperature drops below this set point, the control dampers reduce the amount of outside air to maintain the desired mixed air temperature.