Buildings are the primary user of energy in the USA. Within homes, the heating, ventilation, and air condition (HVAC) system is the largest energy consumer. This study: (i) developed a new methodology for simulating filter loading in-situ; (ii) observed the impact of filter loading on AC performance in-situ; and (iii) provided a greater understanding of when a filter is “dirty” and should be replaced. Six central AC systems in the Atlanta metro-region were evaluated. Filter loading was simulated by installing the TrueFlow® airflow metering device and partially taping off the face at 3 different increments. This resulted in measurements at 5 discrete static pressures (no filter, TrueFlow, TrueFlow Taped one, TrueFlow Taped two, and TrueFlow Taped three). The pilot study found that as filter pressure drop increased, airflow rates generally decreased, resulting in higher differences in temperature across the evaporator coil (∆T). There was no observed correlation between absolute humidity across the evaporator coil and either filter pressure drop or system airflow. Overall, as airflow decreased so did sensible, latent, and total capacity. This research can inform decisions about filter replacement and be used to evaluate computer simulation models of HVAC performance.

Adverse health effects of human exposure to particulate matter (PM) in indoor environments and the associated costs have been of interest in recent studies conducted outside Canada. It was, therefore, necessary to investigate these effects in a Canadian environment. This study investigated the effects of building construction and Heating, Ventilation, and Air Conditioning (HVAC) systems on the indoor concentration of airborne PM of outdoor origin and the related health impacts and cost savings in Ontario. Due to the complexity of the investigation, the study has been limited to the metropolitan areas of Toronto and Hamilton which represent much of the population of Ontario and a significant portion of all Canada. The main objective of the cost-benefit analysis (CBA) was to analyze and evaluate the effects of pollution in monetary equivalents. The modeling integrated the various models using the Impact Pathway Approach. The approach consisted of four steps: First, identify the sources and emissions of PM. Although the study focused on indoor environments, outdoor sources such as incomplete combustion from rush hour traffic were identified for the geographical areas of the study. Secondly, evaluate the dispersion or the concentration of PM on the site of interest. In order to achieve this goal, building modeling was first established that was applicable to Ontario. There were three homes and two commercial building scenarios: Existing homes (resExist), new homes constructed under minimum building code requirements (resBC), and under R2000 standard (resR2000); commercial buildings with 40% (school40) and 85% (school85) ASHRAE air filters. Air flow rates were calculated from building and HVAC sizing calculations. These flow rates were used to calculate input parameters for well-established mass balanced indoor PM concentration models. In addition, indoor exposure needed to account for time activity in each micro-environment in Ontario. This was accomplished by using time-weighted exposure modeling. Thirdly and lastly in the Impact Pathway Approach, evaluate the health impact and its monetary equivalent, respectively. In order to evaluate the health effects and monetary equivalents, the study considered fourteen retrofit cases which consisted of improving factors such as building construction, distribution system, and air filtration efficiency. Because input parameters were selected from data applicable to Ontario, the study provided a model setup that could be applied to future work in Canada. The study demonstrated that Canadian building construction provided significant protection from time-weighted PM exposure (Toronto, ambient vs. resExist/school40win, PM2.5 10.00 vs. 4.20 μg/m3). For this scenario, the prevented attributable number of cases (ANCs) was 721 for Toronto related to equivalent PM10. Cost savings due to building envelope protection of mortality alone much outweighed costs in investment scenario for new home construction (Toronto, $1,671 million vs. $21.6 million). Therefore, recommendations were made to invest in home construction. Similarly, the morbidity effects were very significant, especially for chronic bronchitis endpoints which were along the same magnitude as mortality for most of the cases. Similar results were obtained for Hamilton in proportion to their relative population at risk. In addition, Canadian building construction and HVAC systems showed larger time-weighted PM exposure in the summer compared to the winter conditions due to the various HVAC operating conditions such as air flow rates (Toronto, resExist/school40sum, PM2.5 5.18 μg/m3 ; resExist/school40win, PM2.5 4.20 μg/m3). Furthermore, cost savings from retrofits from existing home to forced air with air filtration were very significant. It was demonstrated that the cost savings related to reduction of equivalent PM10 exposure due to mortality alone much outweighed costs in retrofit investment scenarios (R2000, Toronto, $574 million vs. $4.96 million). Therefore, the government would be wise to promote more energy efficient homes by offering more incentive programs. Factors such as wall insulation, air flow rate changes of less than 600cfm, and HRV installation type did not played a major role. In addition, the effect of air filtration was more intense in homes compared to commercial buildings. Similarly, the impact of simultaneously retrofitting both, homes and commercial buildings, where children and adults spent most of the daily activities produced the greatest reduction of outdoor PM exposure. Installing high efficient air filtration in both homes and commercial buildings resulted in optimal reduced effects. The cost savings from the retrofit due to mortality alone much outweighed the investment scenario costs justifying the retrofit (Toronto, $470 million vs. $1.8 million). This demonstrated that PM concentration exposure reduction is a collective effort that needed to be regulated not only in ambient air level but in the work environment and in homes as well. It was identified that results were limited to model assumptions and input parameter data used. Since some of the parameters used, such as ambient PM concentrations, were average values, the results may not represent the exact actual conditions. Nevertheless, they provided a starting point since they were tailored to Ontario. Therefore, this study provided model simulation data that related to the Canadian environment having many factors in common such as weather, building construction, building systems, and government regulations. Therefore, the results are part of useful data for policy decisions as well as a starting point for future related work.

This study models the HVAC system of a power plant. It involved Computer simulations to study the energy demand by the HVAC system of the power plant as well as the energy demand of the system with modifications on the plant such as the building materials, use of energy efficient lighting, etc. Further studies on the energy demand of the system with the power plant located at different regions of the country were done to understand the effects of climate and locations. It is important to have an understanding of how a plant generating energy uses it for Heating, Ventilating and Air conditioning within the power plant building itself. This study has provided a better understanding of the energy use and how the HVAC system use in the offices and other areas located in the power plant building operates. The study included implementation of energy efficient measures in the choice of building materials for the building. The U.S. Department of Energy (DOE) EnergyPlus program was used to model the HVAC system of the power plant making use of the parameters and modified parameters of the power plant. The results of this study show that the energy demand of the HVAC system of a power plant is significantly affected by the choice of materials for the building. It was found that there is a reduction in the power demand of the HVAC system of the plant by about an average of about 21.7 % at the different the locations. It was also found that this resulted in the amount of energy saved per year of about 87,600 kWh. This gives an average cost savings per year of about $10,512.

Building designers aim to create buildings with high quality internal environments which are energy and cost efficient in their use. Failure to attain these objectives simultaneously can lead to reduced building occupant productivities. An important aspect of the building services system which can have a major effect on the provision of occupant comfort within a building is the adopted control strategy. The research project investigated the use of fuzzy control strategies as a means of achieving good standards of comfort provision for occupants while maintaining or improving energy and cost efficiencies for the operation of the building HVAC services. This represented a multi-variant controls objective which was capable of being fulfilled by a fuzzy controller. A one zone building computer model was developed using Matlab and Simulink software as a platform for the development of fuzzy control strategies. The model incorporated building services Heating Ventilating and Air-Conditioning (HVAC) system models. A Proportional + Integral + Derivative (PID) control strategy was used as a benchmark control methodology against which to compare the developed fuzzy control strategies. Three types of fuzzy controller were developed during the course of the research project. These were a Proportional Derivative Fuzzy Controller (PDFC), a Fuzzy Ventilation Controller, and the Fuzzy High Level Controller. The PDFC used the inputs of error and rate of change of error from a specified zone environmental condition set point in much the same way as a PID controller would to control the HVAC plant. Simulation results indicated that the PDFC control strategy was capable of achieving performance levels equal to the conventional PID control strategy. The Fuzzy Ventilation Controller was used to control the rate of fresh outside air entering the building zone through the mechanical ventilation system in order to make use of the 'free' cooling and dehumidification available by purging the indoor air when possible. Simulation results showed improvements in the indoor environmental quality provided, and the energy efficiency and cost efficiency of running the HVAC plant. Finally, the Fuzzy High Level Controller used a fuzzy supervisor to control the actions of the fuzzy ventilation controllers. Simulation results showed that the fuzzy supervisor was able to improve the comfort conditions provided and the energy and cost efficiencies of the operation of the HVAC plant when compared to the use of the fuzzy ventilation control strategies alone.

Master of Science / Department of Mechanical and Nuclear Engineering / Donald L. Fenton / Today air cooled chillers are often used in industrial applications where chilled water is pumped through processes or laboratory equipment. Industrial chillers are used for the controlled cooling of products, mechanisms and factory machinery in a wide range of industries. However, there is limited information on condenser coil design for a simulated model that uses R407c in a process chiller system with a focus on the finned tube condenser design. Therefore, a simulation tool that evaluates the performance of a condenser design, e.g. frontal area, cost, and overall system efficiency would be very useful. An optimization calculator for the air cooled fin-tube condenser design was developed. This calculator allows a user to specifically select the condenser geometric design parameters including the overall condenser length and height, number of rows, number of circuits, row and tube spacing, fin thickness, fin density, tube inner and outer diameters, and the quantity and power of the fan motors. This study applied the calculator finding an optimum condenser design for various frontal areas and cost constraints. The calculator developed is appropriate for engineering designers for use in the process chiller industry.

As the cost of hardware decreases and software technology advances, building automation systems (BAS) have been widely deployed to new buildings or as part of the retrofit to replace the old control systems. Though they are becoming more prevalent and promise important benefits to the society, such as improved energy-efficiency and occupants’ comfort, many of their benefits remain unreachable. Research suggests that this is because of the heterogeneous, fragmented and nonstandardized nature of existing BASs. One of the purported benefits of these systems is the ability to reduce energy consumption through the application of automated approaches such as fault detection and diagnosis (FDD) algorithms. Savings of up to 0.16 quadrillion BTUs per year could be obtained in the US alone through the use of these approaches, which are just software applications running on BAS hardware. However, deployment of these applications for buildings remains a challenge due to the non-trivial efforts of organizing, managing and extracting metadata associated with sensors (e.g., information about their type, function, etc.), which is required by them. One of the reasons leading to the problem is that varying conventions, acronyms, and standards are used to define this metadata. Though standards and governmentmandated policies may lift these obstacles and enable these softwarebased improvements to our building stock, this effort could take years to come to fruition and there are alternative technical solutions, such as automated metadata inference techniques, that could help reign in on the non-standardized nature of today’s BASs. This thesis sheds light on the visibility of this alternative approach by answering three key questions, which are then validated using data from more than 400 buildings in the US: (a) What is the specific operational information required by FDD approaches for secondary heating, ventilation, and air conditioning (HVAC) systems found in existing literature? (b) How is the performance of existing metadata inference approaches affected by changes in building characteristics, weather conditions, building usage patterns, and geographical locations? (c) What is an approach that can provide physical interpretations in the case of incorrect metadata being inferred? We find that: (a) The BAS points required by more than 30% of FDD approaches include six sensors in AHUs monitoring supply air temperature, outside air temperature, chilled water valve position, return air temperature, supply air flow rate, and mixed air temperature; (b) The average performance of existing inference approaches in terms of accuracy is similar across building sites, though there is significant variance, and the expected accuracy of classifying the type of points required by a particular FDD application for a new unseen building is, on average, 75%; (c) A new approach based on physical models is developed and validated on both the simulation data and the real-world data to infer the point types confused by data-driven models with an accuracy ranging from 73% to 100%, and this approach can provide physical interpretations in the case of incorrect inference. Our results provide a foundation and starting point to infer the metadata required by FDD approaches and minimize the implementation cost of deploying FDD applications on multiple buildings.

Balancing an air distribution system consists primarily of measuring airflow and adjusting volume control devices to get specified airflow. Flow calculation methods are not accurate enough to ensure proper balancing by duct design alone. To assure proper balancing, dampers within an air distribution system must be adjusted until design flows are met throughout the system to within + 10%. By properly balancing an air distribution system, operating costs in the system will be reduced, comfort for the occupants in the building will be increased, and the life of the HVAC equipment will be improved. Existing balancing techniques are iterative methods that require several measurements and damper adjustments. The flows and pressures are first measured, and then the dampers are adjusted to match design airflow. The flows are measured again and the measuring and adjusting process is repeated on a trial-and-error process until design flow is achieved. This iterative process is time consuming and expensive. The proposed new balancing technique is to use a computer program that, based on a few measurements, determines damper adjustments that will achieve design airflow throughout the system. Each terminal damper is adjusted only once to a specified flowrate that is determined by the computer program, making the balancing process quicker and less expensive. No iteration is required. / Master of Science

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Energy efficiency of industrial systems is of great concern to many. Modeling and optimization of industrial systems has been an active research area aiming at improvement of energy efficiency of these systems. Traditional analytical and physics-based methods, reported in literature, limit modeling industrial systems, which are complex, nonlinear, and dynamic. Due to progress in data collection techniques, large volume of data has been collected and stored for analysis. Although much valuable information is contained in such data, utilization of the data in modeling industrial systems is lagging. Data mining is a novel science, providing a platform and techniques to model complex systems and processes. Data mining techniques have been widely applied in modeling various systems. In this Thesis, two energy intensive industrial systems are investigated, a pump system in wastewater treatment plants, and an HVAC system in commercial buildings. Data mining is utilized to derive models describing the relationship between target, operational cost of systems, and system control variables. An optimization model is constructed to minimize operational cost of a system, and intelligent algorithms are employed to solve the optimization models. The study demonstrates a considerable energy saving by applying the proposed control strategy. The approach developed in this Thesis can be applied to industrial systems other than the pump and HVAC systems.

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