Heat pumps are a vital part of each building for their role in keeping the space conditioned for the occupant. This study focuses on developing a model for the ground-source heat pump at the Zero Energy lab at the University of North Texas, and finding the minimum data required for generating the model. The literature includes many models with different approaches to determine the performance of the heat pump. Each method has its pros and cons. In this research the equation-fit method was used to generate a model based on the data collected from the field. Two experiments were conducted for the cooling mode: the first one at the beginning of the season and the second one at the peak of the season to cover all the operation conditions. The same procedure was followed for the heating mode. The models generated based on the collected data were validated against the experiment data. The error of the models was within ±10%. The study showed that the error could be reduced by 20% to 42% when using the field data to generate the model instead of the manufacturer’s catalog data. Also it was found that the minimum period to generate the cooling mode model was two days and two hours from each experiment, while for the heating mode it was four days and two hours from each experiment.

This research work is focused on a conceptual combination of membrane-based energy recovery ventilator (ERV) and phase change material (PCM) to provide energy savings in building heating, ventilation & air-conditioning (HVAC) systems. An ERV can recover thermal energy and moisture between the outside fresh air (OFA) entering into the building and the exhaust air (EA) leaving from the building thus reducing the energy consumption of the HVAC system for cooling and heating the spaces inside the building. The membranes were stacked parallel to each other forming adjacent channels in a counter-flow arrangement for OFA and EA streams. Heat and moisture is diffused through the membrane core. Flat-plate encapsulated PCM is arranged in OFA duct upstream/downstream of the ERV thereby allowing for further reduction in temperature by virtue of free cooling. Paraffin-based PCMs with a melting point of 24°C and 31°C is used in two different configurations where the PCM is added either before or after the ERV. Computational fluid dynamics (CFD), and heat and mass transfer modeling is employed using COMSOL Multiphysics v5.3 to perform the heat and mass transfer analysis for the membrane-based ERV and flat-plate PCMs. An 8-story office building was considered to perform building energy simulation using eQUEST v3.65 from Department of Energy (DOE). Based on the heat and mass transfer analysis, it is found that the sensible effectiveness (heat recovery) stood in the range of 65%-97% while the latent effectiveness (moisture recovery) stood at 55%-80%. Also, the highest annual energy savings achieved were 72,700 kWh in electricity consumption and 358.45 MBtu in gas consumption.

The rapid urbanization of modern cities poses several economic challenges and questions, such as energy efficiency, environmental sustainability, and the distribution of businesses. These elements significantly shape the dynamics of housing markets and urban migration patterns. My dissertation explores the causal impacts of environmental amenities and informational transparency on housing market valuations and the interactions within business sectors. In the first chapter of this thesis, we study the equilibrium effects of building energy efficiency information on the housing market. Building energy efficiency is crucial for identifying energy-saving potential, yet such information was not publicly available in the past. We examine the equilibrium effects of a regulation in New York City that mandates increased public access to information on building energy efficiency. We find that the effectiveness of disclosure policies in achieving desired market outcomes hinges significantly on the salience of the information disclosed. Our findings suggest that enhancing the salience of building energy efficiency disclosures leads to the emergence of energy efficiency premiums and incentivizes buildings to make energy efficiency improvements. Particularly, luxury buildings exhibit more pronounced responses. We develop and estimate an equilibrium model of demand for homes and building energy efficiency, as well as buildings' choices of energy efficiency levels. The results indicate that the increase in housing prices attributable to energy efficiency improvements significantly exceeds the savings in energy bills. In the second chapter of this thesis, we the strengths of agglomeration spillovers in the local non-tradable service sector using a comprehensive list of grocery store openings in the U.S. in 2018 -- 2019. We combine deep learning tools with propensity score estimation to find counterfactual opening sites and compare business outcomes surrounding actual and counterfactual sites. We find openings of grocery stores lead to significant growth in foot traffic to their opening locations and a 39 percent increase in foot traffic to businesses within 0.1 miles. The spillovers of demand are strongest between new grocery stores and businesses in wholesale and retail and hospitality services. We also find that grocery store openings lead to a 6.9 percentage point higher growth in the number of businesses within 0.1 miles of the openings 0--3 years later. My third chapter investigates the economic impacts of cleaning up heavily polluted waterways in urban neighborhoods. We leverage the Black-and-Odorous Water Program, a major urban environmental campaign in China, as a natural experiment to identify the causal impact of cleaner waterways on local housing prices, housing supply, and business growth. Implemented in 2016, the program remediated heavily polluted waterways in China's 36 most developed cities. Using a difference-in-differences estimator, we find that the program mainly benefits properties within 1 mile of cleaned-up waterways: These properties saw a 2.3% appreciation in market value after the program. Beyond the impacts on the housing market, we identify two novel mechanisms associated with community revitalization following pollution management and examine their implications for housing prices. First, new real estate developments near treated waterways are more likely to offer high-end units after the program. Second, service businesses flourish in neighborhoods near cleaned waterways, indicating a commercial rejuvenation of these areas.

This thesis focuses on the design and implementation of a software tool able to achieve electricity grid optimal management in a dynamic pricing environment, at the residential level, and from a customer's perspective. The main drivers encouraging a development of energy management at the home level are analyzed, and a system architecture modeling power, thermodynamic and economic subsystems is proposed. The user behavior is also considered. A mathematical formulation of the related energy management optimization problem is proposed based on the linear programming theory. Several cases involving controllable and non-controllable domestic loads as well as renewable energy sources are presented and simulation scenarios illustrate the proposed optimization strategy in each case. The performance of the controller and the changes in energy use are analyzed, and ideas for possible future work are discussed.

Buildings are directly responsible for 40% of the final energy use in most developed economies and for much more if indirect requirements are considered. This results in huge impacts which affect the environmental balance of our planet.<p>However, most current building energy assessments focus solely on operational energy overlooking other energy uses such as embodied and transport energy. Embodied energy comprises the energy requirements for building materials production, construction and replacement. Transport energy represents the amount of energy required for the mobility of building users.<p>Decisions based on partial assessments might result in an increased energy demand during other life cycle stages or at different scales of the built environment. Recent studies have shown that embodied and transport energy demands often account for more than half of the total lifecycle energy demand of residential buildings. Current assessment tools and policies therefore overlook more than 50% of the life cycle energy use.<p>This thesis presents a comprehensive life cycle energy analysis framework for residential buildings. This framework takes into account energy requirements at the building scale, i.e. the embodied and operational energy demands, and at the city scale, i.e. the embodied energy of nearby infrastructures and the transport energy of its users. This framework is implemented through the development, verification and validation of an advanced software tool which allows the rapid analysis of the life cycle energy demand of residential buildings and districts. Two case studies, located in Brussels, Belgium and Melbourne, Australia, are used to investigate the potential of the developed framework.<p>Results show that each of the embodied, operational and transport energy requirements represent a significant share of the total energy requirements and associated greenhouse gas emissions of a residential building, over its useful life. The use of the developed tool will allow building designers, town planners and policy makers to reduce the energy demand and greenhouse gas emissions of residential buildings by selecting measures that result in overall savings. This will ultimately contribute to reducing the environmental impact of the built environment. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

This research investigates the bio-products/phase change material (PCM) composites for the building envelope application. Bio-products, such as wood and herb, are porous medium, which can be applied in the building envelope for thermal insulation purpose. PCM is infiltrated into the bio-product (porous medium) to form a composite material. The PCM can absorb/release large amount of latent heat of fusion from/to the building environment during the melting/solidification process. Hence, the PCM-based composite material in the building envelope can efficiently adjust the building interior temperature by utilizing the phase change process, which improves the thermal insulation, and therefore, reduces the load on the HVAC system. Paraffin wax was considered as the PCM in the current studies. The building energy savings were investigated by comparing the composite building envelope material with the conventional material in a unique Zero-Energy (ZØE) Research Lab building at University of North Texas (UNT) through building energy simulation programs (i.e., eQUEST and EnergyPlus). The exact climatic conditions of the local area (Denton, Texas) were used as the input values in the simulations. It was found that the EnergyPlus building simulation program was more suitable for the PCM based building envelope using the latent heat property. Therefore, based on the EnergyPlus simulations, when the conventional structure insulated panel (SIP) in the roof and wall structures were replaced by the herb panel or herb/PCM composite, it was found that around 16.0% of energy savings in heating load and 11.0% in cooling load were obtained by using PCM in the bio-product porous medium.

This study presents findings from survey and interview data investigating replication of green building measures by Commercial Building Partnership (CBP) partners that worked directly with the Pacific Northwest National Laboratory (PNNL). PNNL partnered directly with 12 organizations on new and retrofit construction projects, which represented approximately 28 percent of the entire U.S. Department of Energy (DOE) CBP program. Through a feedback survey mechanism, along with personal interviews, quantitative and qualitative data were gathered relating to replication efforts by each organization. These data were analyzed to provide insight into two primary research areas: 1) CBP partners' replication efforts of green building approaches used in the CBP project to the rest of the organization's building portfolio, and, 2) the market potential for technology diffusion into the total U.S. commercial building stock, as a direct result of the CBP program. The first area of this research focused specifically on replication efforts underway or planned by each CBP program participant. The second area of this research develops a diffusion of innovations model to analyze potential broad market impacts of the CBP program on the commercial building industry in the United States. Findings from this study provided insight into motivations and objectives CBP partners had for program participation. Factors that impact replication include motivation, organizational structure and objectives firms have for implementation of energy efficient technologies. Comparing these factors between different CBP partners revealed patterns in motivation for constructing energy efficient buildings, along with better insight into market trends for green building practices. The optimized approach to the CBP program allows partners to develop green building parameters that fit the specific uses of their building, resulting in greater motivation for replication. In addition, the diffusion model developed for this analysis indicates that this method of market prediction may be used to adequately capture cumulative construction metrics for a whole-building analysis as opposed to individual energy efficiency measures used in green building.

Currently, the public has a strong sense of the need for environment protection and the use of sustainable, or “green,” design in buildings and other civil structures. Since green design elements and technologies are different from traditional design, they probably have impacts on the building environment, such as vibration, lighting, noise, temperature, relative humidity, and overall comfort. Determining these impacts of green design on building environments is the primary objective of this study. The Zero Energy Research (ZOE) laboratory, located at the University of North Texas Discovery Park, is analyzed as a case study. Because the ZOE lab is a building that combines various green design elements and energy efficient technologies, such as solar panels, a geothermal heating system, and wind turbines, it provides an ideal case to study. Through field measurements and a questionnaire survey of regular occupants of the ZOE lab, this thesis analyzed and reported: 1) whether green design elements changed the building’s ability to meet common building environmental standards, 2) whether green design elements assisted in Leadership in Energy and Environmental Design (LEED) scoring, and 3) whether green design elements decreased the subjective comfort level of the occupants.

The goal of this dissertation is to demonstrate that data from a remotely located building can be utilized for energy modeling of a similar type of building and to demonstrate how to use this remote data without physically moving the data from one server to another using Virtual Information Fabric Infrastructure (VIFI). In order to achieve this goal, firstly an EnergyPlus model was created for Greek Life Center, a campus building located at University of North Texas campus at Denton in Texas, USA. Three thermal comfort models of Fanger model, Pierce two-node model and KSU two-node model were compared in order to find which one of these three models is most accurate to predict occupant thermal comfort. This study shows that Fanger's model is most accurate in predicting thermal comfort. Secondly, an experimental data pertaining to lighting usage and occupancy in a single-occupancy office from Carnegie Mellon University (CMU) has been implemented in order to perform energy analysis of Greek Life Center assuming that occupants in this building's offices behave similarly as occupants in CMU. Thirdly, different data types, data formats and data sources were identified which are required in order to develop a city-scale urban building energy model (CS-UBEM). Two workflows were created, one for an individual scale building energy model and another one for CS-UBEM. A new innovative infrastructure called as Virtual Information Fabric Infrastructure (VIFI) has been introduced in this dissertation. The workflows proposed in this study will demonstrate in the future work that by using VIFI infrastructure to develop building energy models there is a potential of using data for remote servers without actually moving the data. It has been successfully demonstrated in this dissertation that data located at remote location can be used credibly to predict energy consumption of a newly built building. When the remote experimental data of both lighting and occupancy are implemented, 4.57% energy savings was achieved in the Greek Life Center energy model.