James E. Braun

Load Control Using Building Thermal Mass

This paper provides an overview of research related to use of building thermal mass for shifting and reducing peak cooling loads in commercial buildings. The paper presents background on the concept and the problem of optimizing zone temperature setpoints and provides specific results that have been obtained through simulations, controlled laboratory testing, and field studies. The studies have demonstrated significant savings potential for use of building thermal mass in commercial buildings. However, the savings are sensitive to many factors, including utility rates, type of equipment, occupancy schedule, building construction, climate conditions, and control strategy. The paper also attempts to provide an assessment of the state of the art in load control using building thermal mass and to identify the steps necessary to achieve widespread application of appropriate control strategies.

An Inverse Gray-Box Model for Transient Building Load Prediction

Lower costs and improved performance of sensors, controllers, and networking is leading to the development of smart building features, such as continuous performance monitoring, automated diagnostics, and optimal supervisory control. For some of these applications, it is important to be able to predict transient cooling and heating requirements for the building using inverse models that are trained using on-site data. Existing inverse models for transient building loads range from purely empirical or “black-box” models to purely physical or “white-box” models. Generally, black-box (e.g., neural network) models require a significant amount of training data and may not always reflect the actual physical behavior, whereas white-box (e.g., finite difference) models require specification of many physical parameters. This paper presents a hybrid or “gray-box” modeling approach that uses a transfer function with parameters that are constrained to satisfy a simple physical representation for energy flows in the building structure. A robust method is also presented for training parameters of the constrained model, wherein initial values of and bounds on physical parameters are estimated from a rough building description, better estimates are obtained using a global direct search algorithm, and optimal parameters are identified using a nonlinear regression algorithm. The model and training method were extensively tested for different buildings and locations using data generated from a detailed simulation program. The approach was also tested using data from a field site located near Chicago, Illinois. It was found that one to two weeks of data are sufficient to train a model so that it can accurately predict transient cooling or heating requirements.

A Statistical, Rule-Based Fault Detection and Diagnostic Method for Vapor Compression Air Conditioners

This paper presents a method for automated detection and diagnosis of faults in vapor compression air conditioners that only requires temperature measurements, and one humidity measurement. The differences between measured thermodynamic states and predicted states obtained from models for normal performance (residuals) are used as performance indices for both fault detection and diagnosis. For fault detection, statistical properties of the residuals for current and normal operation are used to classify the current operation as faulty or normal. A diagnosis is performed by comparing the directional change of each residual with a generic set of rules unique to each fault. This diagnostic technique does not require equipment-specific learning, is capable of detecting about a 5% loss of refrigerant, and can distinguish between refrigerant leaks, condenser fouling, evaporator fouling, liquid line restrictions, and compressor valve leakage.

Evaluating the Performance of Building Thermal Mass Control Strategies

A tool was developed that allows evaluation of thermal mass control strategies using HVAC utility costs as the baseline for comparison. Inverse models are used to represent the behavior of the building, cooling plant, and air distribution system. Inverse models use measured data to “learn” system behavior and provide relatively accurate site-specific performance predictions. Based on weather and solar inputs, as well as occupancy and internal gains schedules and utility rates, the evaluation tool predicts the total HVAC utility cost for a specified control strategy. Intelligent thermal mass control strategies can then be identified in a simulation environment using this analysis tool. The evaluation tool was validated using data collected from a field site located near Chicago, Illinois. The tool predicted HVAC utility costs for a summer month billing period that were within approximately 5% of actual costs. Additional studies were performed to examine the utility savings potential for summertime operations at the field site using various thermal mass control strategies. The best strategy resulted in approximately a 40% reduction in total cooling costs as compared with night setup control. Simulation studies were also used to analyze the overall impact of location on the savings potential for use of building thermal mass. Representative utility rates for five locations (Boston, Chicago, Miami, Phoenix, and Seattle) were used along with the models obtained for the field site. Significant savings were achieved in all locations except Seattle.

Mathematical modeling of scroll compressors—part I: compression process modeling

This paper presents a detailed model for the compression process of a scroll compressor, which is used for investigating a compressors performance under different operating conditions and subject to design changes. Upon defining the compressor chambers as suction chambers, compression chambers and discharge chambers, a geometry study was conducted and the governing mass and energy conservation equations were developed for each chamber. Models for the refrigerant flow in the suction and discharge processes, radial and flank leakage, and heat transfer between the gas and scroll wraps were combined with the conservation equations. The state of the refrigerant changes with a period of angle 2π, and thousands of step are used to solve the governing differential equations during each period. It is assumed that in each step the compressor is in steady state. Since the differential equations for the different chambers are coupled, all these equations are solved simultaneously using a nonlinear equation solver. A description of the corresponding computer code and some results are included in this paper. Verification of the compression process model can be referred to that of the overall model, which is described in Chen et al. [Chen Y, Halm N, Braun J, Groll E. Mathematical modeling of scroll compressors—part II: overall scroll compressor modeling. International Journal of Refrigeration 2002;25(6):751–764.].

Common faults and their impacts for rooftop air conditioners

This paper identifies important faults and their performance impacts for rooftop air conditioners. The frequencies of occurrence and the relative costs of service for different faults were estimated through analysis of service records. Several of the important and difficult to diagnose refrigeration cycle faults were simulated in the laboratory. Also, the impacts on several performance indices were quantified through transient testing for a range of conditions and fault levels. The transient test results indicated that fault detection and diagnostics could be performed using methods that incorporate steady-state assumptions and models. Furthermore, the fault testing led to a set of generic rules for the impacts of faults on measurements that could be used for fault diagnoses. The average impacts of the faults on cooling capacity and coefficient of performance (COP) were also evaluated. Based upon the results, all of the faults are significant at the levels introduced, and should be detected and diagnosed ...

Energy efficiency analysis of air cycle heat pump dryers

In this paper, the feasibility of an air heat pump (reversed Brayton) cycle for tumbler clothes dryers is investigated. The goal is to increase the energy efficiency as compared to conventional electrically heated driers. Relatively simple models were used to compare the energy efficiency of the heat pump drier with that of a conventional air vented drier. The components were modeled using overall performance indices and thermodynamic relations. An air cycle heat pump dryer with practical components was found to be capable of significant efficiency improvements as compared with conventional dryers.

Evaluating the Performance of a Fault Detection and Diagnostic System for Vapor Compression Equipment

This paper presents a detailed evaluation of the performance of a statistical, rule-based fault detection and diagnostic (FDD) technique presented by Rossi and Braun (1997). Steady-state and transi...

A Methodology for Diagnosing Multiple Simultaneous Faults in Vapor-Compression Air Conditioners

Existing methods addressing automated fault detection and diagnosis (FDD) for vapor-compression air-conditioning equipment have good performance for faults that occur individually but have difficulty handling multiple simultaneous faults. In addition, these methods either require high-cost measurements or measurements over a wide range of conditions for training reference models, the development of which can be time consuming and cost prohibitive. This paper formulates model-based FDD in a generic way and demonstrates that decoupling is the key to handling multiple simultaneous faults. To eliminate a cost-prohibitive overall system model, an alternative physical decoupling methodology to mathematical decoupling is developed. During the mathematical development, a previously developed FDD method termed the statistical rule-based method is reexamined and cast within the general mathematical framework. The paper also includes an evaluation of the FDD method in terms of both sensitivity and robustness.

A Simplified Method for Determining Optimal Cooling Control Strategies for Thermal Storage in Building Mass

Previous simulations and experiments have shown that significant operating savings can be realized when cooling commercial buildings if the building structure is used for thermal storage. Research has also shown that the control strategy must be tailored to the application to achieve these savings while maintaining occupant comfort. Developing cooling control strategies which utilize the thermal mass of a building is a formidable optimization problem. By examining optimal cooling results covering a wide range of buildings, cooling plants, weather, utility rates, and internal gains, this study has reduced the dimensionality of the optimal control problem. Two simplified approaches were developed which each employ two control variables while the building is unoccupied, in conjunction with a set of rules for the occupied period. These rules were expressed in terms of occupant comfort. The simplified strategy achieved 95% and 97%, respectively, of the optimal savings relative to conventional control. Using ho...