Nowadays, many organizations choose to increasingly implement the cloud computing approach. More specifically, as customers, these organizations are outsourcing the management of their physical infrastructure to data centers (or cloud computing platforms). Energy consumption is a primary concern for datacenter (DC) management. Its cost represents about 80% of the total cost of ownership and it is estimated that in 2020, the US DCs alone will spend about $13 billion on energy bills. Generally, the datacenter servers are manufactured in such a way that they achieve high energy efficiency at high utilizations. Thereby for a low cost per computation all datacenter servers should push the utilization as high as possible. In order to fight the historically low utilization, cloud computing adopted server virtualization. The latter allows a physical server to execute multiple virtual servers (called virtual machines) in an isolated way. With virtualization, the cloud provider can pack (consolidate) the entire set of virtual machines (VMs) on a small set of physical servers and thereby, reduce the number of active servers. Even so, the datacenter servers rarely reach utilizations higher than 50% which means that they operate with sets of longterm unused resources (called 'holes'). My first contribution is a cloud management system that dynamically splits/fusions VMs such that they can better fill the holes. This solution is effective only for elastic applications, i.e. applications that can be executed and reconfigured over an arbitrary number of VMs. However the datacenter resource fragmentation stems from a more fundamental problem. Over time, cloud applications demand more and more memory but the physical servers provide more an more CPU. In nowadays datacenters, the two resources are strongly coupled since they are bounded to a physical sever. My second contribution is a practical way to decouple the CPU-memory tuple that can simply be applied to a commodity server. Thereby, the two resources can vary independently, depending on their demand. My third and my forth contribution show a practical system which exploit the second contribution. The underutilization observed on physical servers is also true for virtual machines. It has been shown that VMs consume only a small fraction of the allocated resources because the cloud customers are not able to correctly estimate the resource amount necessary for their applications. My third contribution is a system that estimates the memory consumption (i.e. the working set size) of a VM, with low overhead and high accuracy. Thereby, we can now consolidate the VMs based on their working set size (not the booked memory). However, the drawback of this approach is the risk of memory starvation. If one or multiple VMs have an sharp increase in memory demand, the physical server may run out of memory. This event is undesirable because the cloud platform is unable to provide the client with the booked memory. My fourth contribution is a system that allows a VM to use remote memory provided by a different rack server. Thereby, in the case of a peak memory demand, my system allows the VM to allocate memory on a remote physical server.

he Department of Energy names executing and integrating high-performance sustainable design and green building best practices a Strategic Sustainability Performance Plan goal under the Executive Order 13514 (U.S DOE, 2009). As sustainability becomes a primary goal for engineers, a decision making framework is needed to guide their choice of materials and processes; and then to carry out the evaluation of their chosen design. Sustainable design process, and the products developed through its application, work concurrently with functionality and sustainability evaluation methodologies to cultivate a continuous loop of design, implementation, assessment and improvement. In this context, an alternative insulation prototype exploring the use of evacuated packets of pyrogenic silica substituting for conventional insulation for refrigeration applications was developed and assessed. Assessment criteria included experimental comparison of heat transfer characteristics and the energy efficiency of the new insulation as well as its life cycle as it related to environmental sustainability. Results indicate that by utilizing alternative insulation design, heat flux decreased by an average of 36%, and energy efficiency improved by 5.1% over a 24 hour period. The new insulation design also resulted in improved environmental sustainability, resulting in a savings of 0.257 metric tons of CO2e over 20 years for a single unit. Results provide an alternative insulation design for use in commercial insulation applications, and a framework by which to assess the efficiency and environmental performance of similar products.

Researchers are in broad agreement that energy-conserving actions produce economic as well as energy savings. Household energy rating systems (HERS) have been established in many countries to inform households of their house’s current energy performance and to help reduce their energy consumption and greenhouse gas emissions. In Canada, the national EnerGuide for Houses (EGH) program is delivered by many local delivery agents, including non-profit green community organizations. Waterloo Region Green Solutions is the local non-profit that offers the EGH residential energy evaluation service to local households. The purpose of this thesis is to explore the determinants of household’s participation in the residential energy efficiency program (REEP) in Waterloo Region, to explain the relationship between the explanatory variables and REEP participation, and to propose ways to improve this kind of program. A spatial (trend) analysis was conducted within a geographic information system (GIS) to determine the spatial patterns of the REEP participation in Waterloo Region from 1999 to 2006. The impact of sources of information on participation and relationships between participation rates and explanatory variables were identified. GIS proved successful in presenting a visual interpretation of spatial patterns of the REEP participation. In general, the participating households tend to be clustered in urban areas and scattered in rural areas. Different sources of information played significant roles in reaching participants in different years. Moreover, there was a relationship between each explanatory variable and the REEP participation rates. Statistical analysis was applied to obtain a quantitative assessment of relationships between hypothesized explanatory variables and participation in the REEP. The Poisson regression model was used to determine the relationship between hypothesized explanatory variables and REEP participation at the CDA level. The results show that all of the independent variables have a statistically significant positive relationship with REEP participation. These variables include level of education, average household income, employment rate, home ownership, population aged 65 and over, age of home, and number of eligible dwellings. The logistic regression model was used to assess the ability of the hypothesized explanatory variables to predict whether or not households would participate in a second follow-up evaluation after completing upgrades to their home. The results show all the explanatory variables have significant relationships with the dependent variable. The increased rating score, average household income, aged population, and age of home are positively related to the dependent variable. While the dwelling size and education has negative relationships with the dependent variable. In general, the contribution of this work provides a practical understanding of how the energy efficiency program operates, and insight into the type of variables that may be successful in bringing about changes in performance in the energy efficiency project in Waterloo Region. Secondly, with the completion of this research, future residential energy efficiency programs can use the information from this research and emulate or expand upon the efforts and lessons learned from the Residential Energy Efficiency Project in Waterloo Region case study. Thirdly, this research also contributes to practical experience on how to integrate different datasets using GIS.

Researchers are in broad agreement that energy-conserving actions produce economic as well as energy savings. Household energy rating systems (HERS) have been established in many countries to inform households of their house’s current energy performance and to help reduce their energy consumption and greenhouse gas emissions. In Canada, the national EnerGuide for Houses (EGH) program is delivered by many local delivery agents, including non-profit green community organizations. Waterloo Region Green Solutions is the local non-profit that offers the EGH residential energy evaluation service to local households. The purpose of this thesis is to explore the determinants of household’s participation in the residential energy efficiency program (REEP) in Waterloo Region, to explain the relationship between the explanatory variables and REEP participation, and to propose ways to improve this kind of program. A spatial (trend) analysis was conducted within a geographic information system (GIS) to determine the spatial patterns of the REEP participation in Waterloo Region from 1999 to 2006. The impact of sources of information on participation and relationships between participation rates and explanatory variables were identified. GIS proved successful in presenting a visual interpretation of spatial patterns of the REEP participation. In general, the participating households tend to be clustered in urban areas and scattered in rural areas. Different sources of information played significant roles in reaching participants in different years. Moreover, there was a relationship between each explanatory variable and the REEP participation rates. Statistical analysis was applied to obtain a quantitative assessment of relationships between hypothesized explanatory variables and participation in the REEP. The Poisson regression model was used to determine the relationship between hypothesized explanatory variables and REEP participation at the CDA level. The results show that all of the independent variables have a statistically significant positive relationship with REEP participation. These variables include level of education, average household income, employment rate, home ownership, population aged 65 and over, age of home, and number of eligible dwellings. The logistic regression model was used to assess the ability of the hypothesized explanatory variables to predict whether or not households would participate in a second follow-up evaluation after completing upgrades to their home. The results show all the explanatory variables have significant relationships with the dependent variable. The increased rating score, average household income, aged population, and age of home are positively related to the dependent variable. While the dwelling size and education has negative relationships with the dependent variable. In general, the contribution of this work provides a practical understanding of how the energy efficiency program operates, and insight into the type of variables that may be successful in bringing about changes in performance in the energy efficiency project in Waterloo Region. Secondly, with the completion of this research, future residential energy efficiency programs can use the information from this research and emulate or expand upon the efforts and lessons learned from the Residential Energy Efficiency Project in Waterloo Region case study. Thirdly, this research also contributes to practical experience on how to integrate different datasets using GIS.

The economic development, environmental sustainability and energy security stay on the top of government agenda, which guarantee the citizen¡¦s standards of living . EU's indigenous energy production is depleting, and each states has different priorities. The European Union push new European energy policies improving security of energy supply ,which are aiming at reducing the risks being dependent on external supply. Those new european energy policies transform Europe into a highly energy efficiency and low CO2 economy,creating an internal energy market and diversifying energy supplies. The EU¡¦s internal policies include enhancing powers and independence of regulatory authorities at Community level, improving the integrated and flexible energy networks,establishing adequate minimum security of gas supply standards and emergency measures and executing the Action Plan for energy efficiency. The EU¡¦s external policies include enhancing energy partnership and continuing energy dialogue with Russia, Central Asia and Mediterranean area, improving investment and growth, developing common trade,transit and environment rules, building the energy supply chain and diversifying energy supplies. In this thesis the security of EU¡¦s energy supply will be examined by the perspective of neo-functionalism.

While transistor size continues to shrink every technology generation increasing the amount of transistors on a die, the reduction in energy consumption is less significant. Furthermore, newer technologies induce fabrication challenges resulting in uncertainties in transistor and wire properties. Therefore to ensure correctness, design margins are introduced resulting in significantly sub-optimal energy efficiency. While increasing parallelism and the use of gating methods contribute to energy consumption reduction, ultimately, more radical changes to the architecture and better integration of architectural and circuit techniques will be necessary. This dissertation explores one such approach, combining a highly-efficient massively-parallel processor architecture with a design methodology that reduces energy by trimming design margins. Using a massively-parallel GPU-like (graphics processing unit) base- line architecture, we discuss the different components of process variation and design microarchitectural approaches supporting efficient margins reduction. We evaluate our design using a cycle-based GPU simulator, describe the conditions where efficiency improvements can be obtained, and explore the benefits of decoupling across a wide range of parameters. We architect a test-chip that was fabricated and show these mechanisms to work. We also discuss why previously developed related approaches fall short when process variation is very large, such as in low-voltage operation or as expected for future VLSI technology. We therefore develop and evaluate a new approach specifically for high-variation scenarios. To summarize, in this work, we address the emerging challenges of modern massively parallel architectures including energy efficient, reliable operation and high process variation. We believe that the results of this work are essential for breaking through the energy wall, continuing to improve the efficiency of future generations of the massively parallel architectures. / text

The purpose of this study is to determine the energy impacts of daylighing through toplights in a hot humid climate. Daylight in the working environment improves the quality of the space, and productivity of employees. In addition, natural light is a free energy resource. On one hand, a proper design of daylight such as distributed toplights can reduce the electrical lighting consumption. On the other hand, in a hot climate like Austin heat gain is a major concern. Therefore, this thesis is shaped around this question: Can toplighting strategies save energy in Austin despite the fact that buildings receive more direct heat gain through toplights? The importance of daylighting is more revealed since electrical lighting takes up a significant portion of the total building energy use (21%). In this thesis I investigated the reduction of lighting electricity and compared that with the total effects of toplights on external conductance, lighting heat gain and solar gain. The results of my thesis show that regarding the site energy a proper toplighting strategy can save electrical lighting up to (70%) with smaller impact on heating and cooling loads. This means that toplights generally can be energy efficient alternatives for a one storey office building. Developing my research I studied which toplights are more efficient: north sawtooth roofs, south sawtooth roofs, monitor roofs or very simple skylights. I compared different toplighting strategies and provided a design guide containing graphs of site energy, source energy, annual cost saving per square feet, as well as light distribution of each toplight. I believe this can accelerate implementation of efficient toplighting strategies in the design process. Concluding how significantly efficient daylighting is over heat gain, I finalized my research by comparison of skylights with different visible transmission (VT) and solar heat gain coefficient (SHGC). The major result of this thesis is that proper toplighting strategies can save energy despite the increased solar gain. It is anticipated that the thesis findings will promote the implementation of toplighting strategies and higher VT glass type in the energy efficient building industry. / text

Energy and water resources share an important interdependency. Large quantities of energy are required to move, purify, heat, and pressurize water, while large volumes of water are necessary to extract primary energy, refine fuels, and generate electricity. This relationship, commonly referred to as the energy-water nexus, can introduce vulnerabilities to energy and water services when insufficient access to either resource inhibits access to the other. It also creates areas of opportunity, since water conservation can lead to energy conservation and energy conservation can reduce water demand. This dissertation analyzes both sides of the energy-water nexus by (1) quantifying the extent of the relationship between these two resources and (2) identifying strategies for synergistic conservation. It is organized into two prevailing themes: the energy consumed for water services and the water used in the power sector. In Chapter 2, a national assessment of United States' energy consumption for water services is described. This assessment is the first to quantify energy embedded in water at the national scale with a methodology that differentiates consistently between primary and secondary uses of energy for water. The analysis indicates that energy use in the residential, commercial, industrial, and power sectors for direct water and steam services was approximately 12.3 quadrillion BTU or 12.6% of 2010 annual primary energy consumption in the United States. Additional energy was used to generate steam for indirect process heating, space heating, and electricity generation. Chapter 3 explores the potential energy and emissions reductions that might follow regional shifts in residential water heating technologies. Results suggest that the scale of energy and emissions benefits derived from shifts in water heating technologies depends on regional characteristics such as climate, electricity generation mix, water use trends, and population demographics. The largest opportunities for energy and emissions reductions through changes in water heating approaches are in locations with carbon dioxide intensive electricity mixes; however, these are generally areas that are least likely to shift toward more environmentally advantageous devices. In Chapter 4, water withdrawal and consumption rates for 310 electric generation units in Texas are incorporated into a unit commitment and dispatch model of ERCOT to simulate water use at the grid scale for a baseline 2011 case. Then, the potential for water conservation in the power generation sector is explored. Results suggest that the power sector might be a viable target for cost-effective reductions in water withdrawals, but reductions in water consumption are more difficult and more expensive to target. / text

ITC/USA 2013 Conference Proceedings / The Forty-Ninth Annual International Telemetering Conference and Technical Exhibition / October 21-24, 2013 / Bally's Hotel & Convention Center, Las Vegas, NV / A substantial amount of the energy usage in developed countries is consumed by climate control of residential and commercial structures. Collecting information on the usage patterns of heating, ventilation and air conditioning (HVAC) systems can allow a consumer to better understand the cost and effectiveness of these systems, and allow landlords and others to monitor their use. This paper describes a system which can easily be retrofitted onto legacy HVAC systems to monitor their activity, and then transmit the information over a wireless radio network for archiving and analysis

This thesis explored the opportunities to reduce energy demand and renewable energy feasibility at an off-grid science “community” called the Experimental Lakes Area (ELA) in Ontario. Being off-grid, ELA is completely dependent on diesel and propane fuel supply for all its electrical and heating needs, which makes ELA vulnerable to fluctuating fuel prices. As a result ELA emits a large amount of greenhouse gases (GHG) for its size. Energy efficiency and renewable energy technologies can reduce energy consumption and consequently energy cost, as well as GHG. Energy efficiency was very important to ELA due to the elevated fuel costs at this remote location. Minor upgrades to lighting, equipment and building envelope were able to reduce energy costs and reduce load. Efficient energy saving measures were recommended that save on operating and maintenance costs, namely, changing to LED lights, replacing old equipment like refrigerators and downsizing of ice makers. This resulted in a 4.8% load reduction and subsequently reduced the initial capital cost for biomass by $27,000, by $49,500 for wind power and by $136,500 for solar power. Many alternative energies show promise as potential energy sources to reduce the diesel and propane consumption at ELA including wind energy, solar heating and bio-mass. A biomass based CHP system using the existing diesel generators as back-up has the shortest pay back period of the technologies modeled. The biomass based CHP system has a pay back period of 4.1 years at $0.80 per liter of diesel, as diesel price approaches $ 2.00 per liter the pay back period reduces to 0.9 years, 50% the generation cost compared to present generation costs. Biomass has been successfully tried and tested in many off-grid communities particularly in a small-scale off-grid setting in North America and internationally. Also, the site specific solar and wind data show that ELA has potential to harvest renewable resources and produce heat and power at competitive rates compared to diesel and propane.