Energy demand attributable to the operation of supermarkets on-site is thought to be responsible for 1% of UK greenhouse gas emissions. In use data show a performance gap approaching a factor of three for overall energy use, with a gap of a factor of six in energy demand for heating. This performance gap indicates significant faults in the conventional modelling route. Current building regulations in the UK require the "building related" energy use of new commercial buildings to comply with particular requirements. Supermarket buildings are therefore modelled according to these protocols to establish their predicted energy demand. The impact on this predicted energy demand of the exclusion of process energy (eg for refrigeration) from these protocols is explored by modelling a supermarket retail floor with heat transfers related to refrigerated cabinets, and comparing the sensitivities of such models with those of models compliant with regulatory protocols. Whereas models compliant with regulatory protocols indicate an advantage of limiting the level of insulation and airtightness, and allowing stratification, to facilitate heat loss through the store envelope; models that include heat transfers around the refrigerated cabinets are found to show that energy demand may be decreased by up to 40% by doubling both insulation and airtightness, and by destratification. This will, however, only apply if rates of air change in buildings in use match those modelled. This shows the importance of including heat transfers around refrigerated cabinets in design modelling, so that appropriate decisions may be taken with respect to building envelope parameters. Compliance modelling protocols should be changed to reflect this. In order to facilitate this change and enable modelling of refrigerated cabinets within a compliance model through a few simple inputs, a set of data and associated algorithms is derived and offered for inclusion in compliance modelling tools.

Climate change projections estimate a rise of approximately 3 °C by the 2080‘s for most of the UK (under a medium emissions scenario at 50% probability level, 1961-1990 baseline). Warming is of particular concern for urban areas due to the issues of urban densification and the Urban Heat Island (UHI) effect. To combat warming, one adaptation strategy that has been suggested for urban areas is increasing the proportion of greenspace, such as parks, gardens, street tree plantings, and green roofs. While a number of studies have investigated the cooling effect of greenspace in terms of park size, proximity to a park, or area covered by tree canopy, little is yet known about the specific types of greenspace that contribute to its cooling effectiveness and how this relates to building energy demand. This thesis employs an interdisciplinary approach to model fine-scale changes to greenspace for a temperate northern UK city, linking the resulting microclimate changes to building energy consumption in commercial buildings. Using the urban microclimate model ENVI-met, two study areas (one urban one suburban) were modelled with seven different greenspace scenarios (a base case representing current field conditions, +5% new trees, +5% mature trees, +5% hedges, addition of a green roof on the largest building, changing all current greenspace to grass only, and changing all current greenspace to asphalt only) for a summer day in July 2010. The models were calibrated based on measured air temperature data and then analysed for microclimate changes due to each greenspace scenario. Both the modelled and measured microclimate data were then used to inform a series of building energy models using IES-VE 2012 for three commercial building types, estimating summer cooling and winter heating trade-offs due to greenspace effects. For the most effective scenario of adding 5% mature trees to the urban case study, the microclimate modelling estimates a maximum hourly air temperature reduction of nearly 0.7 °C at 5 pm and surface temperature reductions up to 1.7 °C at 3 pm. In the suburban case study, a 5% increase in mature deciduous trees can reduce mean hourly surface temperatures by 1 °C between 10 am and 5 pm, while the worst case scenario of replacing all current vegetation (20% of the study area) with asphalt results in increased air temperature of 3.2 °C at mid-day. The building energy modelling estimates a reduction of 2.7% in July chiller energy due to the combination of reduced UHI peak hours and eight additional trees (four on the north side and four on the south side) of a three-storey shallow plan building. These energy savings increase to 4.8% under a three-day period of peak UHI conditions. While winter boiler energy usage shows large reductions for a building in an urban location with a low proportion of greenspace (as compared to a suburban location), this benefit is marginal when analysed in terms of carbon trade-offs between summer cooling and winter heating requirements.

A modeling tool was developed capable of evaluating the thermal performance of a commercial building, for the purpose of objectively quantifying the impacts of both operational changes and technological retrofits. The modeling tool was created using a steady state energy balance approach, discretized into half hour time steps to capture the time varying characteristics of the rate of heat transfer through the building envelope, the ventilation systems, appliance heat gains, heat generated by electricity consumption, solar energy transfer and space heating through exhaust gas energy recovery with the TEG POWER system. Several experimental facilities were used to validate the modeling tool, and to provide inputs to the case studies presented. Data from two separate commercial baking operations was collected, and was shown to be in agreement with the model predictions with a 7% error. Several energy conservation measures were simulated, including switching to idealized methods of exhaust ventilation, sealing and insulating appliances, shutting down appliances during unoccupied hours, and the inclusion of exhaust gas energy harvesting. Implementing all four conservation measures at a single restaurant had the effect of reducing electricity consumption by 14% or approximately 17,700 kWh (64 GJ), and reducing natural gas consumption by 60% or approximately 18,200 m3 (608 GJ) annually. In contrast, proceeding directly to the energy harvesting solution, and bypassing other conservation measures, only allowed for 20% of the total potential energy savings to be realized. If the concepts identified are implemented across 2000 comparable restaurants in Ontario, there is a potential to reduced electricity consumption by 44.4 million kWh and natural gas consumption by 33.7 million cubic meters annually. The measures would effectively eliminate 65,500 metric tonnes of CO2 emissions every year. / Thesis / Master of Applied Science (MASc)

There is interest concerning the energy performance of buildings in the United States. Buildings, whether residential, commercial or institutional, generally underperform in terms of energy efficiency when compared to buildings that are constructed following sustainably and energy efficiency standards. A substantial percentage of energy loss in these buildings is associated with the thermal efficiency of its envelope (exterior walls, windows roof, floors and doors). The objective of this study will evaluate the results of three energy modeling techniques developed to investigate the energy transfer through the envelope of existing campus buildings. The techniques employed are solving the heat transfer calculations using spreadsheets, using a stand-alone modeling software (OpenStudio) and using an integrated building energy modeling software (eQuest) employed in Autodesk Revit. The first technique is somewhat different from the other two because it does not require a 3D representation of the building to be generated as the first step in the modeling process. It is the application of a mathematical methodology employing heat transfer algorithms entered into the spreadsheet’s cells to estimate the heat transfer through the building envelope. Data needed for this technique are weather data of the buildings location, surface area of the building envelope, and the overall heat transfer coefficient (U-value) of each component of the building envelope. The OpenStudio technique involves a 3D representation of the building. The building is drawn on a 3D modeling computer program called SketchupPro, which communicates directly to the OpenStudio energy modelling interface. The building operations as well as the building characteristics, such as the composition and type of the elements that made up the building envelop, the thermal zone, occupancy schedule and the space type was inputted in the OpenStudio engine. The OpenStudio engine runs the simulation and generates a detail result about the energy usage and energy transfer in the building. The third method that employs AutoCAD Revit software is a standalone technique that does not require an external software for sketching the building model. Revit the ability to draw the model as well as perform the energy analysis at the same time with the aid of inbuilt eQuest modeling engine. The model in Revit is generated with the right building envelope characteristics as the existing building and the weather file. The process is somewhat similar to the OpenStudio technique; the main difference is the level of detail and limitation provided by both the energy modeling engine (eQuest and EnergyPlus). At the end of the simulation, the building energy modeling using Autodesk Revit presents a detailed result of the energy usage and energy flow in the building. The underlying reason of the comparison of three techniques is to understand the simplest, most efficient, accurate method to quantify heat transfer through the building envelope. By the end of this study, the most efficient technique for investigating the building envelope will be expected to be the EnergyPlus technique because of the usage simplicity, ability to take in a lot of details required for simulation and the periodical software updates.

To help solve the climate crisis, municipalities are increasingly modifying their building codes and offering incentives to create greener buildings in their cities. But, city planners find it difficult to set and assess these policies, as most municipalities do not have the types of data used in urban building energy modelling (UBEM) that would allow their planners to forecast the impacts of various building policies. This thesis offers techniques for operating in this data-poor environment, presenting best practices for developing data-driven archetypes with machine learning, demonstrating inference of parameter values to improve archetypes by using surrogate modelling and genetic algorithms, and a demonstration of techniques for assessing residential retrofit impact in a data-limited environment, where data is neither detailed enough to create an in-depth single archetype study, nor broad enough to create an UBEM model. It will be shown that inference techniques have potential, but need a certain amount of detailed data to work, though far less than traditional UBEM techniques. For performing residential retrofit, it will be shown the lack of ideal detailed data does not present an overwhelming obstacle to drawing useful conclusions and that meaningful insight can be extracted despite the lack of precision. Overall, this thesis shows a data-poor environment, while challenging, is a viable environment for both research and policy modelling. / Graduate

Buildings and the built environment account for a significant portion of the global energy use and greenhouse gas emissions, and reducing the energy demand in this sector is crucial for a sustainable energy transition. This highlights the need for accurate and large-scale estimations and predictions of the future energy demand in buildings. Urban building energy modeling (UBEM) is an analytical tool for precise and high-quality energy modelling of city-scale building stocks, which is growing in interest as a useful tool for researchers and decision-makers worldwide. This thesis contributes to the understanding and future development in the field of UBEM and multi-variate cluster analysis. Based on a review of contemporary literature, possible improvements and knowledge gaps regarding UBEM are identified. The majority of UBEM studies are developed for similar applications, and some challenges are close to universal. Difficulties in data acquisition and the identification and characterisation of building archetypes are frequently addressed. Drawing on conclusions from the review, a clustering methodology for identifying building archetypes for hybrid UBEM was developed. The methodology utilised the k-means cluster analysis algorithm for multiple diverse parameters, including socio-economic indicators, and is based on open data sets which eliminates data acquisition issues and allows for easy adaptation. Building archetypes were successfully identified for two large data sets, and proved to be representative of the sample building stock. The results of the analysis also show that the error metric values diverge after a certain number of clusters, for multiple runs of the algorithm. This property of the algorithm in combination with the use of both existing and novel error metrics provide a reliable method for determining the optimal number of clusters. The methodology developed in this thesis enables for an improved modelling process, as a part of a complete UBEM.

Liquid desiccant air conditioning (LDAC) has received much attention in recent years. This is mainly because LDAC systems are able to control latent loads in a more energy efficient way than conventional air conditioning systems. Although many research studies have been conducted on LDAC technologies, the following gaps in the scientific literature are addressed in this thesis: (1) carryover of desiccant droplets in air streams, (2) direct comparisons between different configurations of LDAC systems, (3) fundamentals of capacity matching in heat-pump LDAC systems, (4) optimal-control strategies for heat-pump LDAC systems, and (5) importance of transients in evaluating the performance of a LDAC system. Items (1) to (4) are addressed using TRNSYS simulations, and item (5) is addressed using data collected from a field test. The use of liquid-to-air membrane energy exchangers (LAMEEs) as dehumidifiers and regenerators in LDAC systems eliminate the desiccant droplets carryover problem in air streams. This is because LAMEE separate the air and solution streams using semi-permeable membranes, which allow the transfer of heat and moisture but do not allow the transfer of the liquid desiccant. A preliminary configuration for a membrane LDAC system, which uses LAMEEs as the dehumidifier and regenerator, is proposed and investigated under fixed operating conditions in this thesis. The influences of key design and operating parameters on the heat and mass transfer performances of the membrane LDAC system are evaluated. Results show that the membrane LDAC technology is able to effectively remove latent loads in applications that the humidity to be controlled. A comprehensive evaluation is conducted in this thesis for the thermal, economic and environmental performances of several configurations of membrane LDAC systems. The solution cooling load is covered using a cooling heat pump in all systems studied, while the solution heating load is covered using one of the following five different heating systems: (1) a gas boiler, (2) a heating heat pump, (3) a solar thermal system with gas boiler backup, (4) a solar thermal system with heat pump backup, and (5) the condenser of the solution cooling heating pump. Each of the membrane LDAC systems studied is evaluated with/without an energy recovery ventilator (ERV) installed in the air handling system. The influence of operating the ERV under balanced/unbalanced operating conditions is studied. It is found that the most economic membrane LDAC system is the one which uses the evaporator and condenser of the same heat pump to cover the solution cooling and heating loads, respectively (i.e. heat-pump membrane LDAC system). No clear guidance was found in the literature for sizing the evaporator and condenser in a heat-pump LDAC system to simultaneously meet the solution cooling and heating loads. When the heating and cooling provided by the heat pump exactly match the heating and cooling requirements of the solution, the system is “capacity matched”. A parametric study is conducted on a heat-pump membrane LDAC system to identify the influence of key operating and design parameters on achieving capacity matching. It is concluded that the solution inlet temperatures to the dehumidifier and regenerator are the most influential parameters on the moisture removal rate, capacity matching and coefficient of performance (COP). Three control strategies are developed for heat-pump membrane LDAC systems, where these strategies meet the latent loads and achieve one of the following three objectives: (1) meet the sensible loads, (2) achieve capacity matching, or (3) optimize the COP. Results show that the COP of a heat-pump LDAC system can be doubled by selecting the right combination of solution inlet temperatures to the regenerator and dehumidifier. The importance of transients in evaluating the performance of a LDAC system is addressed in the thesis using a data collected from a field test on a solar LDAC system. It is found that the sensible, latent and total cooling energy, and the total primary energy consumption of the LDAC system are changed by less than 10% during an entire test day when transients are considered. Thus, it can be concluded that steady-state models are reliable to evaluate the energy performances of LDAC systems.

<p>With increasing concerns about the global warming effects of HFC refrigerants, low-GWP refrigerants and non-vapor compression heat pumps are investigated as potential mid- and long-term replacements for current vapor compression heat pump systems that rely on high-GWP refrigerants. To address the need for more environmentally friendly space cooling and heating, and water heating solutions. the U.S. Department of Energy (DOE) Office of Energy Efficiency & Renewable Energy (EERE) is supporting the development of smarter, more efficient, and affordable heat pumping systems operating with low- or near-zero GWP refrigerants through different programs including the Energy, Emissions, and Equity (E3) Initiative. In addition, the Emerging Technologies (ET) Program within the Building Technologies Office (BTO) emphasized the research and development efforts needed to support new technologies that could reduce energy usage in residential and commercial buildings by 50\% over the next decades. In the literature, limited studies were found that systematically investigated different combinations of conventional and emerging space conditioning and water heating technologies while accounting for real building loads, different climate zones, utility structures, and current state-of-the-art equipment. Existing literature primarily focused on thermodynamic performance evaluations at fixed boundary conditions. In addition, separate sensible latent cooling (SSLC) and other novel cooling and dehumidification systems (e.g., membrane-based systems) can significantly reduce the electricity usage for space conditioning. To compare the performance of conventional and emerging technologies several figures-of-merit such as the second law efficiency, are often used. However, limitations exist in previous studies to define the thermodynamic reversible limits and second law efficiency for cooling and dehumidification systems.</p><p>This study developed a comprehensive modeling framework to evaluate both current state-of-the-art vapor compression systems and emerging HVAC\&R technologies in real-world scenarios. The platform will be used to assess potential energy savings, scalability issues, and the effectiveness of combined technologies for different buildings, climate conditions, and utility structures.</p><p>To compare HVAC technologies, a new physics-based definition for the reversible limit and the second law efficiencies for cooling and dehumidification systems with air recirculation has been developed. The new framework is then extended to define a novel performance metric, the seasonal second law efficiency, to form a universal benchmark for assessing various cooling and dehumidification systems. Five cooling and dehumidification systems including magnetocaloric cooling, solid desiccant dehumidification, and membrane dehumidification are evaluated using this benchmark. Steady-state thermodynamic models are constructed for each system. Second law efficiency for each system under various outdoor temperatures and indoor sensible heat ratios (SHR) are calculated. The annual electricity usage of the five systems is used to justify the seasonal second law efficiency definition. The results show that compared to conventional vapor compression systems with mechanical dehumidification, the membrane-based AMX-R cycle can reduce annual electricity use by 12.2%-22.2% and increase the seasonal second law efficiency by 36%.</p><p>The advancements of nine not-in-kind (defined as non-vapor compression systems, solid-state, and chemical-based systems) technologies, i.e. magnetocaloric, thermoelectric, elastocaloric, electrocaloric, membrane-based, Vuilleumier, sorption, chemical looping, and desiccant, were reviewed in detail and compared with the state-of-the-art vapor compression systems. Suitable figures-of-merit were defined to compare the different technologies from a thermodynamic standpoint as well as technology readiness level. As a result of the thorough literature review, a roadmap was created to track the development of emerging HVAC&R technologies and future developments. More importantly, the roadmap enabled the identification of several case studies to evaluate potential energy savings both for space conditioning and water heating. Techno-economic studies for eight HVAC configurations for space heating, cooling, and water heating were conducted for a realistic building scenario under various climate conditions. Different combinations of advanced equipment such as heat pump water heater (HPWH), ground-source heat pumps (GSHP), cold-climate heat pumps (CCHP), and membrane-heat pumps were compared with traditional vapor compression heat pumps and gas furnaces. A building model was developed in EnergyPlus and validated with historical data from the DC Nanogrid House at the Purdue University campus. A total of eleven climate zones were considered, and both local weather conditions and utility pricing were implemented in the simulations. Moreover, future SEER2/HSPF2 equipment ratings and E3 Initiative targets were also included in the analyses.</p><p>The initial simulation results provided climate-based equipment selection guidelines and quantitative techno-economic assessments. For instance, CCHPs with two-stage compression in heating mode save 10%-20% in annual heating cost compared with single-stage VCHPs in Climate Zone 4A, 4C, 5A, 5B, 6A, and 6B. Membrane evaporative air-conditioners could provide cooling cost savings in places where is a significant cooling load, such as Zone 1A, 2A, 2B, 3A, 3C, 4A, 5A, and 6A. Gas furnaces should only be used in cold places where the electricity price per kWh to gas price ratio is higher than 3. GSHP has the lowest HVAC annual energy cost in six out of eleven climate zones in the U.S. Dual fuel heat pumps are not always the most economical option but yield better average cost savings among the eleven locations. HPWHs should be recommended in areas where the electricity price to gas price ratio is below 3. </p><p>The developed simulation framework will be instrumental to continue in-depth investigations of current and next-generation heat pump technologies. The ultimate goal of this research is to provide future guidelines on the selection of building-specific and climate-specific equipment solutions that will enable energy savings and future decarbonization strategies (e.g., geospatially-resolved simulations).</p>

Complying with the Paris agreements requires substantial efforts in the building sector, and especially within the existing building stock which is responsible for a considerable amount of emissions and energy consumption. This master thesis focuses on the residential district of Minneberg, located in the west of Stockholm in Bromma. The urban building energy modelling (UBEM) approach is used to model the situation of the current district. This method uses real-life data provided by the district, as well as information found in energy performance certificates and in public databases. Based on that, a virtual archetype building representing the whole district is modelled and calibrated. Suitable energy-efficient solutions that can contribute to reducing the energy consumption are identified and applied in two different scenarios. The first scenario consists in retrofitting the current building stock, while the second represents the case where the building has to be designed from scratch today to comply with Boverket’s requirements on nearly zero-energy buildings ("New Minneberg" scenario). The aggregation of the results shows that the current district is already quite energy-efficient, with the installation of solar panels seeming to be the only economically viable retrofitting option. As for the "New Minneberg" scenario, it is possible to comply with the requirements and achieve a C-class building by reducing the primary energy consumption, but that comes at the expense of a higher actual energy consumption. / Att följa Parisavtalen kräver stora ansträngningar inom byggsektorn, och särskilt inom det befintliga byggnadsbeståndet som står för en betydande mängd växthusgasutsläpp och energianvändning. Examensarbetet fokuserar på det svenska bostadsområdet av Minneberg, som ligger i västra Stockholm i Bromma. UBEM-metoden (urban building energy modelling) används för att modellera situationen i det nuvarande distriktet. Metoden använder verkliga data från fastighetsområdet, liksom information som finns i energideklarationer och offentliga databaser. Därefter modelleras och kalibreras en virtuell arketypsbyggnad som representerar hela distriktet. Lämpliga energieffektiva lösningar som kan bidra till att minska energiförbrukningen identifieras och tillämpas i två olika scenarier. Det första scenariot består i renovering av det nuvarande byggnadsbeståndet, medan det andra representerar fallet om byggnaden hade designats från grunden idag, för att uppfylla Boverkets krav på nollenergihus ("New Minneberg" scenario). Resultaten visar att det nuvarande distriktet redan är ganska energieffektivt, där installation av solpaneler verkar vara den enda ekonomiskt lönsamma åtgärden. Gällande "New Minneberg" scenariot är det möjligt att uppfylla kraven och uppnå en C-klass byggnad genom att minska primärenergitalet, men det resulterar i en högre verklig energiförbrukning.