<p>The main objective of this thesis is to investigate the energetic, economic and environmental impact of utilizing a novel Run-Around Membrane Energy Exchanger (RAMEE) in building HVAC systems. The RAMEE is an energy recovery ventilator that transfers heat and moisture between the exhaust air and the fresh outdoor ventilation air to reduce the energy required to condition the ventilation air. The RAMEE consists of two exchangers made of water vapor permeable membranes coupled with an aqueous salt solution.</p> <p>In order to examine the energy savings with the RAMEE, two different buildings (an office building and a health-care facility) were simulated using TRNSYS computer program in four different climatic conditions, i.e., cold-dry, cool-humid, hot-humid and hot-dry represented by Saskatoon, Chicago, Miami and Phoenix, respectively. It was found that the RAMEE significantly reduces the heating energy consumption in cold climates (Saskatoon and Chicago), especially in the hospital where the required ventilation rate is much higher than in the office building. On the other hand, the results showed that the RAMEE must be carefully controlled in summer to minimize the cooling energy consumption.</p> <p>The application of the RAMEE in an office building reduces the annual heating energy by 30% to 40% in cold climates (Saskatoon and Chicago) and the annual cooling energy by 8% to 15% in hot climates (Miami and Phoenix). It also reduces the size of heating equipment by 25% in cold climates, and the size of cooling equipment by 5% to 10% in hot climates. The payback period of the RAMEE depends on the air pressure drop across the exchangers. For a practical pressure drop of 2 cm of water across each exchanger, the payback of the RAMEE is 2 years in cold climates and 4 to 5 years in hot climates. The total annual energy saved with the RAMEE (including heating, cooling and fan energy) is found to be 30%, 28%, 5% and 10% in Saskatoon, Chicago, Miami and Phoenix, respectively.</p> <p>In the hospital, the RAMEE reduces the annual heating energy by 58% to 66% in cold climates, and the annual cooling energy by 10% to 18% in hot climates. When a RAMEE is used, the heating system can be downsized by 45% in cold climates and the cooling system can be downsized by 25% in hot climates. For a practical range of air pressure drop across the exchangers, the payback of the RAMEE is immediate in cold climates and 1 to 3 years in hot climates. The payback period in the hospital is, on average, 2 years faster than in the office building). The total annual energy saved with RAMEE is found to be 48%, 45%, 8% and 17% in Saskatoon, Chicago, Miami and Phoenix, respectively. The emission of greenhouse gases (in terms of CO₂-equivalent) can be reduced by 25% in cold climates and 11% in hot climates due to the lower energy use when employing a RAMEE.</p>

Under the pressure of energy shortage, energy saving has become one of the most important topics. The world isseeking different ways to follow the sustainable development concept and to solve the energy shortage crisis.This thesis is based on the idea of improving energy efficiency in the building industry which is one of thebiggest energy consumption industries. The aim of this paper is to simulate a renovation of an existing oldbuilding in Sweden according to the concept of building a Swedish Passive House and to see how much energycould be saved after the renovation. The target building Taljstenen 7A-C was built in 1960 in Uppsala and itbelongs to the housing company Uppsalahem. The target building is facing extensive renovation due to its age.An energy consumption model of the present building was built by the software VIP-Energy after measurementsand calculations. Based on the model, three important improvements are made in a simulative renovation process.The three improvements are insulating building envelope, installing a new FTX ventilation system with highefficient heat recovery system and installing solar collectors for hot top water and space heating. The resultsshow a significant reduction of energy consumption of the renovated building compared to the original onewhich is from 516MWh per year decreased to 371MWh. Although the renovated building did not completelyfulfil the Passive House Standard in Sweden, it still has improved to be a low energy building. The purpose ofsaving energy can be achieved.

This study examines the use of building modeling and energy simulations in the design process  of  a  building.  The  take-off  point  is  the  notion  of  energy  simulations  being needed early and throughout the building design process, and that the lack of energy simulations may be explained by the fact that they are time consuming and therefore often too expensive. A greater interoperability between software tools used by relevant disciplines,  such  as  the  architect  and  the  energy  specialist,  would  create  smoother workflows, which would reduce this cost and open up for more frequent and iterative energy  simulation  processes.  The  study  is  an  assessment  of  the  modeling  tool  Revit and  the  simulation  tool  Virtual  Environment  and  whether  they  can  create  smoother workflows, and make leeway for a more frequent use of energy simulations throughout the  design  process.  It  also  investigates  the  limitations  of  what  can  be  examined  by simulations in Virtual Environment. This will hopefully help clarify the future role of energy  simulations  in  design  processes.  The  method  is  a  trial  by  error  approach  of testing the two software tools by building and simulating a model. The results of these tests  show  that  the  workflow  is  not  optimal  (and  therefore  time  consuming)  for frequent  and  iterative simulations  throughout the  design  process,  but  it  also  reveals some  great  possibilities  of  what  can  be  performed  with  these  two  powerful  tools  at hand.  Further  development  with  regards  on  platform  independency  of  the  building information  model,  including  seamless  exporting  and  importing,  seems  necessary  to strengthen the future role of energy simulations.

<p>The main objective of this thesis is to investigate the energetic, economic and environmental impact of utilizing a novel Run-Around Membrane Energy Exchanger (RAMEE) in building HVAC systems. The RAMEE is an energy recovery ventilator that transfers heat and moisture between the exhaust air and the fresh outdoor ventilation air to reduce the energy required to condition the ventilation air. The RAMEE consists of two exchangers made of water vapor permeable membranes coupled with an aqueous salt solution.</p> <p>In order to examine the energy savings with the RAMEE, two different buildings (an office building and a health-care facility) were simulated using TRNSYS computer program in four different climatic conditions, i.e., cold-dry, cool-humid, hot-humid and hot-dry represented by Saskatoon, Chicago, Miami and Phoenix, respectively. It was found that the RAMEE significantly reduces the heating energy consumption in cold climates (Saskatoon and Chicago), especially in the hospital where the required ventilation rate is much higher than in the office building. On the other hand, the results showed that the RAMEE must be carefully controlled in summer to minimize the cooling energy consumption.</p> <p>The application of the RAMEE in an office building reduces the annual heating energy by 30% to 40% in cold climates (Saskatoon and Chicago) and the annual cooling energy by 8% to 15% in hot climates (Miami and Phoenix). It also reduces the size of heating equipment by 25% in cold climates, and the size of cooling equipment by 5% to 10% in hot climates. The payback period of the RAMEE depends on the air pressure drop across the exchangers. For a practical pressure drop of 2 cm of water across each exchanger, the payback of the RAMEE is 2 years in cold climates and 4 to 5 years in hot climates. The total annual energy saved with the RAMEE (including heating, cooling and fan energy) is found to be 30%, 28%, 5% and 10% in Saskatoon, Chicago, Miami and Phoenix, respectively.</p> <p>In the hospital, the RAMEE reduces the annual heating energy by 58% to 66% in cold climates, and the annual cooling energy by 10% to 18% in hot climates. When a RAMEE is used, the heating system can be downsized by 45% in cold climates and the cooling system can be downsized by 25% in hot climates. For a practical range of air pressure drop across the exchangers, the payback of the RAMEE is immediate in cold climates and 1 to 3 years in hot climates. The payback period in the hospital is, on average, 2 years faster than in the office building). The total annual energy saved with RAMEE is found to be 48%, 45%, 8% and 17% in Saskatoon, Chicago, Miami and Phoenix, respectively. The emission of greenhouse gases (in terms of CO₂-equivalent) can be reduced by 25% in cold climates and 11% in hot climates due to the lower energy use when employing a RAMEE.</p>

The concern of increasing energy consumption with depleting energy resources is ever growing. Though the solution to this problem lies in part in renewable energies, it is becoming increasingly clear that sustainable building design also plays a critical role. Controlling solar gain, for example, can greatly reduce the cooling energy consumption and lowering the peak cooling load. Having the ability to model these effects can have a substantial impact on the sizing of equipment and further reduce operational costs of a building. As a result, renewed interest has been invested by researchers and industry to promote the development and use of building simulation tools to aid in the design process. Efforts at the University of Waterloo’s Advanced Glazing Systems Laboratory have resulted in a set of shading device models, with emphasis on generality and computational efficiency, tailored for use in building simulation. These models have been validated with measurements at the component level and with measurements performed at the National Solar Test Facility (NSTF) on a full scale window system, giving confidence to model validity. Continued research has resulted in the integration of these shading device models into ESP-r via the Complex Fenestration Construction (CFC) module, capable of modelling multi-layer glazing and shading layer systems and greatly improving the value of ESP-r as a design tool. The objective of the current research was to implement shading device models for roller blinds, pleated drapes and insect screens to the CFC module. These would be in addition to the venetian blind model which had previously been established. A Monte-Carlo ray tracing analysis of pleated drape geometry and incident angle dependent fabric characteristics gave further confidence to the view factor or net reduction method used by the implemented models. On model implementation, a preliminary comparison was performed between a high-slat angle venetian blind, a roller drape and drapery fabric, all given the same material properties, with similar results. Further comparison was then performed using EnergyPlus shading device models to establish further confidence in the functionality of the models. Though there was some discrepancy between the results, primarily due to convective models, good agreement was found, and the effect of the shading device models on building performance was demonstrated. The successful implementation of roller blind, pleated drape and insect screen shading models to the CFC module in ESP-r has been demonstrated in the current research. It should also be noted that the convective models for indoor shading attachments is a worthwhile topic for further research, at which point it would then be beneficial to conduct further empirical validation on the ESP-r simulation.

Increasing studies imply that predicted energy performance of buildings significantly deviates from actual measured energy use. This so-called "performance gap" may undermine one's confidence in energy-efficient buildings, and thereby the role of building energy efficiency in the national carbon reduction plan. Closing the performance gap becomes a daunting challenge for the involved professions, stimulating them to reflect on how to investigate and better understand the size, origins, and extent of the gap. The energy performance gap underlines the lack of prediction capability of current building energy models. Specifically, existing predictions are predominantly deterministic, providing point estimation over the future quantity or event of interest. It, thus, largely ignores the error and noise inherent in an uncertain future of building energy consumption. To overcome this, the thesis turns to a thriving area in engineering statistics that focuses on computation-based uncertainty quantification. The work provides theories and models that enable probabilistic prediction over future energy consumption, forming the basis of risk assessment in decision-making. Uncertainties that affect the wide variety of interacting systems in buildings are organized into five scales (meteorology - urban - building - systems - occupants). At each level both model form and input parameter uncertainty are characterized with probability, involving statistical modeling and parameter distributional analysis. The quantification of uncertainty at different system scales is accomplished using the network of collaborators established through an NSF-funded research project. The bottom-up uncertainty quantification approach, which deals with meta uncertainty, is fundamental for generic application of uncertainty analysis across different types of buildings, under different urban climate conditions, and in different usage scenarios. Probabilistic predictions are evaluated by two criteria: coverage and sharpness. The goal of probabilistic prediction is to maximize the sharpness of the predictive distributions subject to the coverage of the realized values. The method is evaluated on a set of buildings on the Georgia Tech campus. The energy consumption of each building is monitored in most cases by a collection of hourly sub-metered consumption data. This research shows that a good match of probabilistic predictions and the real building energy consumption in operation is achievable. Results from the six case buildings show that using the best point estimations of the probabilistic predictions reduces the mean absolute error (MAE) from 44% to 15% and the root mean squared error (RMSE) from 49% to 18% in total annual cooling energy consumption. As for monthly cooling energy consumption, the MAE decreases from 44% to 21% and the RMSE decreases from 53% to 28%. More importantly, the entire probability distributions are statistically verified at annual level of building energy predictions. Based on uncertainty and sensitivity analysis applied to these buildings, the thesis concludes that the proposed method significantly reduces the magnitude and effectively infers the origins of the building energy performance gap.

Within the design community, a growing number of researchers have shown interest in extending the value context to include design, such that designers focus on maximizing the 'value' of the product or service, rather than simply satisfying a set of requirements. Thus, by applying a value-driven approach to design, the design community hopes to show that the magnitude of cost and schedule overruns may be reduced, or even eliminated. However, a common criticism of value-driven approaches is that they are difficult to implement, and not sufficiently pragmatic to be used for large scale engineering problems. Further, some argue that less rigorous methods appear to provide reasonable results in practice, and so rigor is not necessary. To reconcile these disparate viewpoints, it must be shown that value-driven approaches contribute to the design process, and can be implemented in practice at a reasonable cost. In response, I propose that the cause for the lack of practicality in value-driven approaches is attributable to the lack of well established and verified methods and tools. This dissertation presents research that attempts to address this deficiency by first developing a better understanding of effectiveness for methods that seek to enable value-driven design. This investigation leads to a concise set of desired characteristics for methods for guiding the development of value-models which then motivate the creation of a Systematic Method for Developing Value Models (SMDVM). To evaluate the SMDVM, it is applied to the design and retrofit of buildings for energy efficiency. A simulation workbench is developed as a tool to automate the development and analysis of value models for building design and retrofit contexts. The workbench enables architects, engineers, and other practitioners to easily incorporate uncertainty into analyses of building energy consumption, as part of a value-driven approach to design and retrofit.

Building Simulation is widely used for understanding how a building consumes energy and for assessing design strategies aimed at improving building energy efficiency. The present research study uses eQUEST, a popular simulation software. Various simulations are done here to analyse and critically comment on the best design strategies to be used in order to vastly reduce the energy consumption of a recently constructed small (1800 m2 floor area) commercial building in Brampton, Ontario, which is a heating dominated region. The limitations faced with eQUEST while simulating the modified design are critiqued. A complete understanding of the building science and heat flow through the building envelope has been applied to modify the building in question. After all the changes applied, the overall heat load of the building was reduced to 15 kWh/m2/yr and the overall energy consumption reduced by 60 percent.

Building Simulation is widely used for understanding how a building consumes energy and for assessing design strategies aimed at improving building energy efficiency. The present research study uses eQUEST, a popular simulation software. Various simulations are done here to analyse and critically comment on the best design strategies to be used in order to vastly reduce the energy consumption of a recently constructed small (1800 m2 floor area) commercial building in Brampton, Ontario, which is a heating dominated region. The limitations faced with eQUEST while simulating the modified design are critiqued. A complete understanding of the building science and heat flow through the building envelope has been applied to modify the building in question. After all the changes applied, the overall heat load of the building was reduced to 15 kWh/m2/yr and the overall energy consumption reduced by 60 percent.

The concern of increasing energy consumption with depleting energy resources is ever growing. Though the solution to this problem lies in part in renewable energies, it is becoming increasingly clear that sustainable building design also plays a critical role. Controlling solar gain, for example, can greatly reduce the cooling energy consumption and lowering the peak cooling load. Having the ability to model these effects can have a substantial impact on the sizing of equipment and further reduce operational costs of a building. As a result, renewed interest has been invested by researchers and industry to promote the development and use of building simulation tools to aid in the design process. Efforts at the University of Waterloo’s Advanced Glazing Systems Laboratory have resulted in a set of shading device models, with emphasis on generality and computational efficiency, tailored for use in building simulation. These models have been validated with measurements at the component level and with measurements performed at the National Solar Test Facility (NSTF) on a full scale window system, giving confidence to model validity. Continued research has resulted in the integration of these shading device models into ESP-r via the Complex Fenestration Construction (CFC) module, capable of modelling multi-layer glazing and shading layer systems and greatly improving the value of ESP-r as a design tool. The objective of the current research was to implement shading device models for roller blinds, pleated drapes and insect screens to the CFC module. These would be in addition to the venetian blind model which had previously been established. A Monte-Carlo ray tracing analysis of pleated drape geometry and incident angle dependent fabric characteristics gave further confidence to the view factor or net reduction method used by the implemented models. On model implementation, a preliminary comparison was performed between a high-slat angle venetian blind, a roller drape and drapery fabric, all given the same material properties, with similar results. Further comparison was then performed using EnergyPlus shading device models to establish further confidence in the functionality of the models. Though there was some discrepancy between the results, primarily due to convective models, good agreement was found, and the effect of the shading device models on building performance was demonstrated. The successful implementation of roller blind, pleated drape and insect screen shading models to the CFC module in ESP-r has been demonstrated in the current research. It should also be noted that the convective models for indoor shading attachments is a worthwhile topic for further research, at which point it would then be beneficial to conduct further empirical validation on the ESP-r simulation.