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Most air conditioning and refrigeration systems that employ the vapor compression cycle rely on oil circulating with refrigerant to lubricate the bearings and other contact surfaces in the compressor. The lubricant acts as a sealant to reduce leakage losses during the compression process and it also helps to absorb some of the excess heat that is generated in the compression chamber. However, this oil circulation results in oil retention in various other components outside the compressor depending on the physical interaction between lubricant and refrigerant and their transport properties. Other factors, such as the geometry and orientation of connecting lines, and the system operating conditions, such as refrigerant flow rate and oil circulation ratio, also impact the oil retention. Because of oil retention, the efficiency of heat exchangers (evaporators and condensers) decreases. In addition, the oil level in the compressor reduces, which may ultimately affect its efficiency and life span. The current line sizing rules reported in the ASHRAE Handbook Refrigeration have only limited consideration of the effects of oil in the system. With the increasing development of variable-speed systems as well as future use of newer HFO refrigerants, there is a need in the industry for upgrading the line sizing recommendations, especially the connecting gas lines of unitary split systems, which consider the effects of oil retention. To develop these rules, measuring oil retention at different operating conditions is important. A test setup has been built to measure oil retention in horizontal and vertical lines of different diameters at different refrigerant and oil flow conditions. Initial results for R134a-POE32 are presented in this paper. Based on the collected data, the final goal is to build a model, which can predict oil retention in gas lines for some of the commonly used refrigerant-lubricant combinations in the HVAC&R industry. [ABSTRACT FROM AUTHOR]

Gray-box or black-box models that are trained using onsite data typically do a better job of capturing actual system performance than forward models that are based on physical parameters due to deviations from design assumptions or uncertainties. However, accurate, site-specific models are needed for developing optimal control strategies for existing systems. In this study, two different gray-box, quasi-steadystate modeling approaches for multistage direct-expansion (DX) units with variable air volume (VAV) were developed and compared for application to supervisory control optimization. Firstly, the ASHRAE Toolkit model was modified for multistage DX units and trained using data from afield site. Secondly, a component-based, gray-box modeling approach was developed and trained using on-site data. The models were validated using measured data not included in the training data set. The advantage of the component-based approach is that it requires less data for training and provides better extrapolating performance. However, it requires significantly more computation. Therefore, a metamodel that correlates outputs from the gray-box model was developed for application to supervisory control optimization. This overall approach provides good accuracy over a wide range of conditions with limited training data and computational requirements. In order to test the application potential, optimization of supply air temperature setpoints was performed for the case study using both the metamodel and modified Toolkit model. Although the two different modeling approaches gave some differences, both indicate significant energy savings potential. [ABSTRACT FROM AUTHOR]

This paper describes extensive tests performed on a 3-ton R-22 split heat pump in heating mode. The tests contain 150 steady-state performance tests, 18 cyclic tests, and 18 defrost tests. During the testing work, the refrigerant charge level was varied from 70% to 130%, relative to the nominal value; the outdoor temperature was altered by three levels at 17°F (--8.3°C), 35°F (1.7°C) and 47°F (8.3°C); indoor airflow rates ranged from 60% to 150% of the rated airflow rate; and the expansion device was switched from a fixed-orifice to a thermal expansion value. Detailed performance data from the extensive steady-state cyclic and defrost testing performed were presented and compared. [ABSTRACT FROM AUTHOR]

Lee and Braun (2008b) developed a simple approach, termed the weighted-averaging (WA) method, that estimates building zone temperature set-point variations that minimize peak cooling demand during critical demand periods. The current paper extends this approach to air conditioning power demand and presents the results of a field evaluation for a small commercial building. The WA method uses data from two or more test days to determine a near-optimal setpoint trajectory for minimizing peak demand during a demand-limiting period. Evaluation of the method was performed over a two-week test period at a small bank building located in Palm Desert, California. The first week of testing was used to collect baseline data for conventional control and data for estimating the optimal setpoint trajectory. The second week of testing was used to evaluate demand reduction and energy savings for application of trajectories determined using the WA method. [ABSTRACT FROM AUTHOR]

Dynamic cooling coil models are useful in the development and evaluation of feedback controllers and fault detection and diagnostics algorithms. Existing models in the literature are forward models, which require detailed specification of physical parameters such as geometry and material properties. On the other hand, inverse models typically require measurements and parameter estimation techniques to identify unknown parameters and are particularly useful for online applications where models are part of a control and/or diagnostic algorithm. This paper develops a simplified distributed inverse model for transient performance of cooling coils that is based on a forward model recently presented in the literature. The inverse model employs lumped parameters for conductances and capacitances. Simple empirical forms are employed for characterizing the impact of flow rates on airside and water-side conductances. Unknown parameters are determined using a two-step approach that requires a small amount of steady-state and transient training data. Dividing the parameter estimation process into two separate steps greatly reduces the training data requirements. A case study is presented for an 8-row cooling coil that was tested in a laboratory environment. The case study highlights the ability of the model to extrapolate performance when trained with a limited amount of data. [ABSTRACT FROM AUTHOR]

Typically, catalog information for cooling towers is available only for a limited range of operating conditions for sea level applications. The information is often not suitable for the selection of a tower at other operating conditions (e.g., high altitude, different ambient temperatures), the evaluation of measured performance, or the simulation over a wide operating range. The analogy approach (Braun et al., 1989) provides a general method for representing the performance of cooling towers over a wide range of conditions. The accuracy of this methodology is 2% compared to catalog values. The methodology is able to extend catalog information to other operating conditions, including water inlet and entering temperatures, wet bulb temperature, air and water flow rates, and altitude. [ABSTRACT FROM AUTHOR]

A simple control method was developed by Braun (2007) for cool storage systems having real-time pricing (RTP) of electricity and shown to yield annual operating costs that are within about 2% of those determined for optimal control. The primary goal of the work described in this paper was to evaluate the operating cost savings associated with employing the strategy developed by Braun (2007) as compared with using chiller-priority control. In addition, operating cost savings associated with employing ice storage in combination with RTP rates were evaluated for both the near-optimal and chiller-priority strategies. For a range of systems employing ice storage with RTP rates, the cost savings associated with the near-optimal strategy compared to chiller-priority control were found to be as high as 60% with typical savings between 25% and 30%. These savings are much more significant than savings associated with employing near-optimal control for cool storage systems when typical time-of-use utility rates are employed with demand charges. A similar level of savings was determined when comparing costs for the near-optimal control strategy applied to ice storage systems with costs for systems not employing cool storage. However, relatively small savings were determined for use of ice storage when chiller-priority control is utilized. In many situations, the use of storage with chiller-priority control can actually result in higher costs than without storage. It can be concluded that chiller-priority control should not be employed in combination with RTP rate structures for cool storage systems. [ABSTRACT FROM AUTHOR]

In contrast to critical systems, one of the primary consequences of faults in HVAC&R systems is economic rather than safety related. Therefore, fault detection and diagnosis (FDD) systems applied to HVAC systems should be assessed based on economic considerations. However, existing FDD research in HVAC applications has mainly focused on technique development and validation. This paper addresses the economics of FDD application to rooftop air-conditioning units (RTUs). Two major aspects of savings associated with FDD application to RTUs are investigated qualitatively and quantitatively: service and operating cost savings. Automated FDD reduces service costs due to reduced preventive maintenance inspections, fault prevention, lower-cost FDD, better scheduling of multiple service activities, and shifting service to low season. Operating cost savings consist of utility cost and equipment life savings. Based on these two major savings, a methodology is presented for evaluating the cost savings for application of automated FDD to RTU. Application of this methodology to a number of sites in California showed that $30/kW year, around 70% of the original service costs, can be saved, and the operating cost savings range from $5 to $51/kW year depending on the location and application. The savings are significant, and the payback period for an FDD technique presented by Li and Braun (2007a, 2007b) that relies on low-cost sensors is less than one year. [ABSTRACT FROM AUTHOR]

A methodology for calibrating simulation models for use in evaluating demand-controlled ventilation (DCV) retrofits in small commercial buildings was developed. The method uses a calibrated building simulation model developed through the process of tuning individual component models (such as HVAC equipment performance) from field data. Specific parameters tuned using field-collected data were the occupancy schedules for weekday and weekend periods, ones that characterize the heating, ventilating, and air-conditioning (HVAC) equipment performance, and several key parameters characterizing the building thermal performance. The tuning of parameters associated with the CO2 modeling and occupancy included in this evaluation was described in separate publications. The tuning parameters were chosen because they were found through parametric studies to have a large influence on the economics of DCV and because they are difficult to determine from site inspections. The method was applied to several small commercial buildings located in different climates within California. The influence of the amount of training data was studied, and it was found that only a few days of training data are sufficient to develop models for evaluation of DCV retrofits. Overall improvement in the root mean square error (RMSE) of predicted hourly cooling system energy usage resulting from calibrated simulation models compared to using an untuned model with best engineering estimates ranged from 0.13 to 1.2 kWh for the test sites, with an average improvement of 27.6%. Economic benefits of DCV were evaluated against the case where outdoor airflow rates equaled those specified in ASHRAE Standard 62.1. Estimated simple economic paybacks for retrofit of DCV at the field test sites ranged from less than one year to about five years. Key factors in determining the economic benefits were the climate type and the number of HVAC units installed at a site. [ABSTRACT FROM AUTHOR]

This paper evaluates the potential for cost savings associated with the use of a near-optimal control strategy for electrical demand limiting in hybrid chiller plants. The control strategy includes the effects of electrical and gas energy, electrical demand, and chiller maintenance costs. A demand constraint is set for each month based upon a heuristic strategy, and an energy/maintenance cost optimal strategy that attempts to satisfy the demand constraint is applied for cooling tower and chiller control at each decision interval (e.g., every five minutes) throughout the month. Evaluation of the strategy was performed using a simulation tool that predicts the utility costs associated with hybrid plants. Annual cost savings associated with employing demand-limiting control for hybrid cooling plants were evaluated for a wide range of conditions. Costs can be reduced by up to 50% compared to a strategy that is just based on minimizing energy costs. The cost savings for demand-limiting control generally increase with increasing ratio of demand to total utility costs. In addition to depending on utility rates, the ratio of demand to total costs depends on the load profile. In general, the use of hybrid cooling plants with demand-limiting control is more beneficial for buildings with shorter occupancy periods having high demand charges. Buildings with shorter occupancy have a higher ratio of peak load to integrated load. [ABSTRACT FROM AUTHOR]

This paper presents results from experimental testing and comfort surveys designed to evaluate peak demand-limiting strategies that utilize adjustments of zone temperature setpoints. The testing was performed at a building that is representative of small commercial buildings. In addition, an inverse model was developed to allow extrapolation to ambient and control conditions not encountered during testing. The testing consisted of two phases. During phase 1 two kinds of control strategies were considered: conventional night setup control and a model-based demand-limiting strategy that involved precooling during the morning and nonlinear setpoint adjustments during an afternoon demand-limiting period. The demand-limiting strategy resulted in greater than 30% reductions in peak cooling loads compared to night setup control for a five-hour demand-limiting period. The phase 1 comfort surveys revealed some occupant discomfort in the morning under the demand-limiting control strategy. Therefore, the major objective of phase 2 testing was to investigate less aggressive strategies. In phase 2, comfort conditions were much improved and occupants were generally satisfied with their environment. Furthermore, daily load shifting from the demand-limiting period during the phase 2 tests was similar to that obtained during phase 1. The inverse model was used to extrapolate the study to hotter conditions with similar results for peak load reduction. This study also demonstrated that the shape of the load profile is very sensitive to the shape of the temperature variation during the demand-limiting period. Linear and step changes in setpoints did not result in satisfactory load shapes for minimizing peak demand. [ABSTRACT FROM AUTHOR]

This paper describes the development and evaluation of a simple algorithm for limiting peak electrical demand in buildings using building thermal mass. The control algorithm is intended to reduce electrical demand in response to utility critical peak pricing (CPP) signals or similar incentives and involves adjustment of zone temperature setpoints within comfort bounds. The demand-limiting potential and impact on utility costs for CPP rates were evaluated through simulation for representative small commercial buildings throughout California. In general, it is possible to achieve between 1 and 2 W/ft² (10.76 and 21.53 W/m²) of demand reduction for a four-hour demand-limiting period while keeping zone temperatures between 70°F and 78°F (21.1°C and 25.6°C). This represents a 30%–100% reduction in peak electrical requirements for air conditioning depending on the climate. For typical CPP utility rates, the impact of the demand-limiting strategy on operating costs is relatively small, with less than about $50 in annual savings per 1000 ft² (92.9 m²). Greater incentives may be necessary to encourage customers to respond to critical capacity shortages. Furthermore, CPP super-peak energy rates do not encourage customers to minimize their demand during CPP periods but, rather, encourage them to reduce their integrated energy usage over this period. A better incentive would involve imposing a high peak demand charge for CPP periods. [ABSTRACT FROM AUTHOR]

Air-to-air energy recovery can be used to reduce ventilation loads for small commercial buildings. Enthalpy exchangers are one approach to energy recovery that is commonly employed. An alternative technology involves the use of a heat pump that operates between the ventilation and exhaust streams. In this paper, the performance of a ventilation heat pump heat recovery unit was studied through simulation. A model of the heat pump was developed and validated using manufacturers' and laboratory test data. This component model was then incorporated within a system simulation to investigate operating cost savings for the heat pump relative to a base case that does not employ energy recovery but utilizes fixed minimum ventilation rates with an enthalpy economizer. The operating costs were found to be greater than the base case in moderate climates with relatively small savings in more extreme climates (hot or cold). The performance is not competitive with the performance of enthalpy exchangers or demand-controlled ventilation. The breakeven ambient conditions for positive savings utilizing a ventilation heat pump were also investigated. The primary performance penalties associated with the use of a heat pump are added fan and compressor power consumption, along with lost economizer savings. [ABSTRACT FROM AUTHOR]

The ventilation airstream required to maintain acceptable indoor air quality is typically a .significant contributor to the total heating and cooling load in commercial buildings. Demand-controlled ventilation (DCV) and enthalpy exchangers are two technologies that can be used to reduce ventilation loads and overall operating costs. This paper evaluates the operating cost savings and overall economics associated with these two different ventilation load reduction technologies for a variety of small commercial building types and climates. A specialized simulation tool was developed and utilized to perform the evaluations. Both demand-controlled ventilation and enthalpy exchangers were shown to result in significant operational cost savings as compared with fixed ventilation and no energy recovery in a number of small commercial buildings and locations. For both technologies, the savings potential and economic payback are better in more extreme climates. The opportunities are particularly great in cold climates because the ventilation load is a larger portion of the overall toad. For retrofit applications, demand-controlled ventilation (DCV) with an economizer was found to give the greatest savings in utility costs for all the buildings and climates considered. Air-conditioning utility cost savings for DCV of up to 52% were found for offices and restaurants. Payback ranged from about one to six years for most locations. Although utility cost savings were found to be less for enthalpy exchangers, they have the advantages of allowing smaller primary cooling and heating equipment for new applications and providing better indoor air quality. The operating cost savings for both DCV and enthalpy exchangers are dependent on assumptions concerning occupancy. The impact of occupancy schedules on cost savings for DCV and enthalpy exchanger systems should be considered in more detail in future studies. [ABSTRACT FROM AUTHOR]

Dynamic models of heat pumps are useful in developing feedback controllers and fault-detection-diagnostic (FDD) studies. Several system models have been documented in the literature, but few are for centrifugal chillers. Existing publications focus on model development and validation, providing minimal detail on the numerical aspects of the solution. The solution of the PDEs that are obtained to model the heat exchangers is critical in terms of accuracy and execution speed. This paper presents the development of a centrifugal chiller system model, using the finite-volume (FV) approach for shell-and-tube heat exchangers and aspects such as mesh dependence, integration order, and step size. Sufficient and necessary mesh sizes for accurate steady-state prediction are determined for the heat exchangers. Execution speeds with integration algorithms of the first, second, and fourth order are compared for equivalent accuracy. The model is based on first principles, allowing it to be used over a wide range of operating conditions and transients. The model is validated using data from a 90-ton R-134a centrifugal chiller. [ABSTRACT FROM AUTHOR]

In the U.S., the current testing and rating procedure for residential air-conditioning and heat-pumping equipment (e.g., AHRI 210/240) is based on a steady-state performance measurement approach with a degradation coefficient to account for cycling losses at part-load conditions. The test equipment performance is measured at different ambient conditions with different compressor and fan speeds, which is then propagated through a temperature-bin method to estimate seasonal performance. Though the current rating approach provides a standard performance metric for comparing different equipment relative performances, it is a steady-state testing approach that involves overriding the native controls and therefore does not consider the effect of test unit integrated controls and their dynamic interactions with representative building loads. As an alternative, a load-based testing methodology has been developed in which the dynamic performance of equipment is measured in a test facility by allowing it to respond to a simulated virtual building model. Hjortland and Braun (2019), Patil et al. (2018), and Cheng et al. (2021) describe the load-based testing methodology in detail which forms the basis for CSA standard draft EXP07 (2019). In this paper, a comparison of the steady-state and load-based approaches is performed for seasonal performance estimation of a heat pump in heating mode. Here, a 5-ton heat pump system performance was measured based on the two testing approaches, and heating seasonal performance was estimated and compared for different climate zones. The differences in the two test methodologies' performance evaluation results for different ambient conditions are discussed, along with their ability in capturing equipment performance that is representative of field application. [ABSTRACT FROM AUTHOR]

In this paper, we present MySmartE, a cloud-based smart home energy application (app) that aims to promote heating and cooling energy efficiency in multi-unit residential communities. The platform is designed to help residents easily apply personalized energy-saving tips to their setpoint schedule and form sustainable energy-saving habits. To induce users' behavioral change, our energy app provides three major attributes: 1) smart thermostat control capability implemented in visual and voice user interfaces (i.e., wall-mounted tablet and Amazon Alexa); 2) personalized feedback that provides a custom metric and action recommendations based on households' thermostat profiles; 3) a collaborative social energy game to facilitate community-inspired user engagement. MySmartE was implemented in an affordable housing community that includes two multi-unit residential buildings with 44 households in IN to evaluate the effect of the app on occupant behaviors during the cooling season by addressing the following research questions: 1) how do occupant behaviors change after using the MySmartE app? Does it improve households' thermostat settings and setpoint selections?; 2) how do users interact with our energy app?; 3) how can we improve user experience with the developed system? Despite the heterogeneous characteristics of households, the results from the field study show the positive effect of the intervention for all participating units during the cooling season. [ABSTRACT FROM AUTHOR]

Current rating standards for residential, electric-driven vapor compression systems determine seasonal energy efficiency (e.g., SEER) using a bin method along with equipment performance data from steady-state tests at different operating conditions. These standards were originally developed for equipment with single or two-stage thermostat control but have been incrementally updated to include equipment with advanced controls and variable-speed compressors and fans. However, the controls are overridden during equipment testing and therefore the rated performance does not consider the interaction of the integrated controls, equipment, and building dynamics. As a result, the standard ratings do not fully capture the characteristics of part-load operation and do not necessarily reward equipment with superior controllers. To address these issues, a load-based testing methodology has recently been developed for estimating the seasonal performance of variable-capacity cooling and heating equipment. The load-based testing methodology emulates the response of building sensible and latent loads to the equipment controls in a psychrometric test chamber by continuously updating the room temperature and humidity based on a virtual building model. The test unit thermostat naturally responds to the dynamic temperature variation and controls the equipment capacity in response to a deviation from its setpoint. The test unit thermostat is installed in a thermostat environment emulator to provide a standardized environment to the thermostat in order to ensure realistic and reproducible conditions for the thermostat. This enables the load-based testing procedure to capture realistic control interactions and performance of a heat pump in a laboratory using psychrometric test chambers. However, to adopt the developed methodology for nextgeneration rating standards, it is crucial to assess the repeatability and reproducibility of the load-based testing approach. In this paper, the assessment of the repeatability of the load-based testing methodology for a 3-ton variable-speed heat-pump operating in cooling mode is presented. The test unit performance was measured multiple times in the same psychrometric facility based on the load-based testing approach. A comparison of the test equipment estimated seasonal performance for different sets of tests is presented along with a discussion of the causes for the differences. [ABSTRACT FROM AUTHOR]

Model Predictive Control (MPC) has gained attention in recent years for application to building automation and controls because of significant potential for energy consumption and/or energy cost savings. MPC utilizes dynamic building and HVAC equipment models and input forecasts to estimate future energy usage and employs optimization to determine control inputs that minimize an integrated cost function for a specified prediction horizon. A dynamic model with reasonable prediction performance (e.g., accuracy and simulation speed) is crucial for a practical implementation of MPC. One modeling approach is to use whole-building energy simulation programs such as EnergyPlus, TRNSYS and ESPr, etc. However, the computational and set up costs for these models are significant and they do not appear to be suitable for on-line implementation. This paper presents the development of control-oriented models for the thermal zones in buildings. Low-order state-space models are identified from the designed input-output responses of thermal zones with disturbances from ambient conditions and internal heat gains . A high-fidelity TRNSYS model of an office building was used as a virtual testbed to generate data for system identification, parameter estimation, and validation of the proposed model structures. This paper concludes with evaluations of the state-space model in terms of model accuracy for predictive control design. [ABSTRACT FROM AUTHOR]

This paper presents a semi-empirical modeling approach that involves the use of physical representations and parameter tuning to enable predictions of steady-state performance for variable refrigerant flow heat pumps systems that incorporate multiple indoor units having variable-speed fans. The system model is based on the use of semi-empirical component models where parameters are tuned using data. The semi-empirical models are built based on first principles but are simplified to speed up the computation. Deviations of the model from experimental data due to model simplification are corrected by tuning the heat transfer coefficients and charge at the system level with the experimental data. Control algorithms for the electronic expansion valve are also estimated based on experimental observation. The model is built in modules to allow the flexibility to add components such as more indoor units or to change the control algorithms easily without a significant change in the solver. A case study was carried out using data from a ductless heat pump system having two indoor units and results show that the model can accurately simulate performance at conditions not used for tuning. [ABSTRACT FROM AUTHOR]

This paper describes steady-state performance simulations performed on a 3-ton R-22 split heat pump in heating mode. In total, 150 steady-state points were simulated, which covers refrigerant charge levels from 70% to 130% relative to the nominal value, the outdoor temperatures at 17°F (--8.3°C), 357°F (1.7°C) and 47°F (8.3°C), indoor air flow rates from 60% to 150% of the rated air flow rate, and two types of expansion devices (fixed orifice and thermostatic expansion valve [TXV]). A charge tuning method, which is to calibrate the charge inventory model based on measurements at two operation conditions, was applied and shown to improve the system simulation accuracy significantly over an extensive range of charge levels. In addition, we discuss the effects of using a suction line accumulator in modeling a heat pump system using either a fixed orifice or thermal expansion valve. Last, we identify the issue of refrigerant mass flow mal-distribution at low charge levels and propose an improved modeling approach. [ABSTRACT FROM AUTHOR]

An experimental study was conducted to investigate the impacts of air-side fouling and cleaning on the performance of various condenser coils used in unitary air-conditioning systems. A total of six condenser coils with different fin geometries and depths were tested. Performance tests were conducted at three different conditions: clean-as-received, after fouling, and after cleaning. In all cases, it was observed that fouling was mostly confined to the frontal face of the heat exchanger as reported in previous investigations. The amount of deposited dust was more dependent on fin geometry for single-row heat exchangers than for double-row heat exchangers. The predominant effect of fouling was to cause a more significant increase in air-side pressure drop than degradation in heat transfer performance. For the single-row heat exchangers, the pressure drop increased by 28% to 31%, while the heat transfer performance decreased by 7% to 12% at the standard air face velocity of 1.53 m/s depending on fin shape. For the double-row heat exchangers, the pressure drop increased by 22% to 3 7%, and heat transfer performance decreased by only 4% to 5% at the same air face velocity. Once the contaminated coils were cleaned according to a manufacturer-specified cleaning procedure, the original performance of the heat exchangers was recovered almost completely. The pressure drop was restored to within 1% to 7% and the heat transfer performance could be recovered to within 1% to 5% of the originally clean heat exchangers. Therefore, it is concluded that a periodic application of .specified cleaning procedures will be effective in maintaining the thermal performance of condenser coils. [ABSTRACT FROM AUTHOR]

The growing applications of variable-speed and tandem compressors, coupled with emerging refrigerant-oil combinations, can lead to higher levels of oil retention in vaporcompression systems, especially at lower refrigerant mass flow rates. To develop better designs and mitigation strategies, it is important to have methods for accurately measuring oil circulation ratio (OCR). High levels of OCR reduce the efficiency of heat exchangers (i.e., evaporators and condensers) and cause the compressor’s oil level to reduce, which may ultimately affect its efficiency and life span. However, measuring OCR within a vapor-compression cycle is challenging due to various factors, such as the phase change of the working fluid at different locations, miscibility between the oil and refrigerant, and varying flow regimes. The objective of this study was to develop a noninvasive, in-situ method to measure OCR in real time, which involves minimal human intervention. An OCR measurement method is presented using an oil separator and a level measurement sensor. The approach has been validated with two different methods, one of which is an ASHRAE standard. The relative differences in the OCR measurement between the liquid level probe and ASHRAE standard methods are less than 12%. [ABSTRACT FROM AUTHOR]

This paper discusses a method of generating generic equipment models that capture the performance of families of similar equipment. Mapping was carried out for a family of three similar residential split systems with central air distribution and the correlations have been implemented as components for an hourly building simulation program. The units mapped ranged from 3 to 5 tons (10.6-17.6 kW) in nominal cooling capacity. The performance mapping predicts the power consumption of the units based on indoor and outdoor environmental conditions, building heating or cooling load and an indoor air flow rate. The equipment models were based on and use a similar approach to the ASHRAE secondary toolkit direct expansion model (Brandemuehl et. al 1993), the DOE-2 model (Winkelmann et al 1993) and EnergyPlus variable refrigerant flow model (DOE 2012). Single sets of correction factor equations were found for each unit in heating mode and cooling mode by first aggregating the performance data of all the units in each family and then performing a single fit. These models are based on data generated from finite volume simulation of modern equipment on the market and are a useful update to available standard direct expansion air conditioner models in building simulation programs. [ABSTRACT FROM AUTHOR]