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An energy-aware, agent-based maintenance-management framework for improving the satisfaction of occupantsCao, Yang 08 June 2015 (has links)
Nowadays, facility managers and related staffs are facing with much maintenance requests every day. The more complicated building system generates the more diverse and complex maintenance issues. With the limited budget and staff, not all the maintenance requests can be solved immediately. To schedule the maintenance work, facility managers first consider the impact of requested problem on system failure and life safety. Besides these two factors, the author proposed the importance of considering the energy efficiency and occupant satisfaction based on the former research for sustainability. This paper firstly tries to quantify the occupant satisfaction for normal daily maintenance requests which will provide the facility managers with suggestions on work prioritization. For a long time, it is a difficult task to quantify the occupant satisfaction, even though there are enough researches concerning the people satisfaction. In this research, author first designed a structured questionnaire including normal maintenance issues and they are measured by different factors such as thermal impact, acoustic impact, and so on. Then based on the classical disconfirmation theory, a framework was built to prioritize numerous works based on occupant satisfaction. For energy efficiency, due to the limitation of collecting real measured data, this paper referred the work from Lawrance Lab. They conducted the research to simulate the daily HVAC faults to quantify the energy impact through EnergyPlus, which provided the data of energy increase for some daily HVAC faults. An agent based model is proposed to both consider these two factors. Simulation was used to verify the framework and the result showed that the total satisfaction level and energy efficiency can be increased by 30% and 97% respectively.
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U.S. electricity end-use efficiency: policy innovation and potential assessmentWang, Yu 27 August 2014 (has links)
Electric end-use efficiency is attracting more and more attentions, but it remains unclear what factors are driving state policy innovations to improve energy efficiency. Controversy also exists over the effectiveness of energy efficiency programs. Several critical problems are facing the policymakers: what factors drive the states taking distinct strategies in policy innovation? Have state policies being able to improve energy efficiency in the past? And, will state policies remain relevant to future efficiency improvements?
This dissertation tries to answer these important questions and assumes that policy innovation is relevant to energy efficiency. It first explores the factors that influence the adoption of energy efficiency policies using Internal Determinants models. Results suggest that internal state factors affect policy innovation, including state socioeconomic factors, state fiscal capacity, ideology, and constituent pressure. Policy innovations are found to be correlated with each other. This dissertation also evaluates the impact of policy innovation on energy efficiency by decomposing electricity productivity into activity, structure, and efficiency effects. The findings suggest that financial incentives and building codes have significant impacts on state electricity productivity. Other regulations tend to have mixed effects. In addition, an estimation of the achievable potential of energy efficiency suggests that policies will cost-effectively drive significant electricity savings in the future.
Overall, this dissertation offers an in-depth diagnosis of the relationship between policy innovation and energy efficiency. It provides a rigorous statistical analysis covering the most important energy efficiency policies. It represents the first attempt to evaluate policy impact by decomposing electricity productivity. However, the statistical models and energy models are subject to limitations and future research is needed to improve the models.
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Energy-efficient mechanisms for managing on-chip storage in throughput processorsGebhart, Mark Alan 05 July 2012 (has links)
Modern computer systems are power or energy limited. While the number of transistors per chip continues to increase, classic Dennard voltage scaling has come to an end. Therefore, architects must improve a design's energy efficiency to continue to increase performance at historical rates, while staying within a system's power limit. Throughput processors, which use a large number of threads to tolerate
memory latency, have emerged as an energy-efficient platform for
achieving high performance on diverse workloads and are found in
systems ranging from cell phones to supercomputers. This work focuses
on graphics processing units (GPUs), which contain thousands of
threads per chip.
In this dissertation, I redesign the on-chip storage system of a
modern GPU to improve energy efficiency. Modern GPUs contain very large register files that consume between 15%-20% of the
processor's dynamic energy. Most values written into the register
file are only read a single time, often within a few instructions of
being produced. To optimize for these patterns, we explore various
designs for register file hierarchies. We study both a
hardware-managed register file cache and a software-managed operand register file. We evaluate the energy tradeoffs in varying the number of levels and the capacity of each level in the hierarchy. Our most efficient design reduces register file energy by 54%.
Beyond the register file, GPUs also contain on-chip scratchpad
memories and caches. Traditional systems have a fixed partitioning
between these three structures. Applications have diverse
requirements and often a single resource is most critical to
performance. We propose to unify the register file, primary data
cache, and scratchpad memory into a single structure that is
dynamically partitioned on a per-kernel basis to match the
application's needs.
The techniques proposed in this dissertation improve the utilization of on-chip memory, a scarce resource for systems with a large number of hardware threads. Making more efficient use of on-chip memory both improves performance and reduces energy. Future efficient systems will be achieved by the combination of several such techniques which
improve energy efficiency. / text
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Smart technology enabled residential building energy use and peak load reduction and their effects on occupant thermal comfortCetin, Kristen Sara 03 September 2015 (has links)
Residential buildings in the United States are responsible for the consumption of 38% of electricity, and for much of the fluctuations in the power demands on the electric grid, particularly in hot climates. Residential buildings are also where occupants spend nearly 69% of their time. As “smart” technologies, including electric grid-connected devices and home energy management systems are increasingly available and installed in buildings, this research focuses on the use of these technologies combined with available energy use data in accomplishing three main objectives. The research aims to: (a) better understand how residential buildings currently use electricity, (b) evaluate the use of these smart technologies and data to reduce buildings’ electricity use and their contribution to peak loads, and (c) develop a methodology to assess the impacts of these operational changes on occupant thermal comfort. Specifically this study focuses on two of the most significant electricity consumers in residential buildings: large appliances, including refrigerators, clothes washers, clothes dryers and dishwashers, and heating, ventilation and air conditioning (HVAC) systems. First, to develop an improved understanding of current electricity use patterns of large appliances and residential HVAC systems, this research analyzes a large set of field-collected data. This dataset includes highly granular electricity consumption information for residential buildings located in a hot and humid climate. The results show that refrigerators have the most reliable and consistent use, while the three user-dependent appliances varied more greatly among houses and by time-of-day. In addition, the daily use patterns of appliances vary in shape depending on a number of factors, particularly whether or not the occupants work from home, which contrasts with common residential building energy modeling assumptions. For the all-air central HVAC systems studied, the average annual HVAC duty cycle was found to be approximately 20%, and varied significantly depending on the season, time of day, and type of residential building. Duty cycle was also correlated to monthly energy use. This information provides an improvement to previously assumed values in indoor air modeling studies. Overall, the work presented here enhances the knowledge of how the largest consumers of residential buildings, large appliances and HVAC, operate and use energy, and identifies influential factors that affect these use patterns. The methodologies developed can be applied to determine use patterns for other energy consuming devices and types of buildings, to further expand the body of knowledge in this area. Expanding on this knowledge of current energy use, smart large appliances and residential HVAC systems are investigated for use in reducing peak electric grid loads, and building energy use, respectively. This includes a combination of laboratory testing, field-collected data, and modeling. For appliance peak load reduction, refrigerators are found to have a good demand response potential, in part due to the nearly 100% of residential buildings that have one or more of these appliances, and the predictability of their energy consumption behavior. Dryers provide less consistent energy use across all homes, but have a higher individual peak power demand during afternoon and evening peak use times. These characteristics also make dryers also a good candidate for demand response. The study of continuous commissioning of HVAC systems using energy data found that both runtime and energy use are increased, and cooling capacity and efficiency are reduced due to the presence of faults or inefficiencies. The correction of these faults have an estimated 1.4% to 5.7% annual impact on a residential building’s electricity use in a cooling-dominated climate such as the one studied. Overall, appliance peak load reduction results are useful for utility companies and policy makers in identifying what smart appliance may provide the most peak energy reduction potential through demand response programs. The results of the HVAC study provides a methodology that can be used with energy use data, to determine if an HVAC system has the characteristics implying an inefficiency may be present, and to quantify the annual savings resulting from its correction. The final aspect of this research focuses on the development of a tool to enable an assessment the effect of operational changes of a building associated with energy and peak load reduction on occupant comfort. This is accomplished by developing a methodology that uses the response surface methodology (RSM), combined with building performance data as input, and uncertainly analysis. A second-order RSM model constructed using a full-factorial design was generally found to provide strong agreement to in and out-of-sample building simulation data when evaluating the Average Percent of People Dissatisfied (PPD[subscript avg]). This 5-step methodology was applied to assess occupant thermal comfort in a residential building due to a 1-hour demand response event and a time-of-use pricing rate schedule for a variety of residential building characteristics. This methodology provides a model that can quickly assess, over a continuous range of values for each of the studied design variables, the effect on occupant comfort. This may be useful for building designers and operators who wish to quickly assess the effect of a change in building operations on occupants. / text
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Sustainability in the UK domestic sector : A review and analysis of the sustainable energy innovations available to homeownersHultgren, Elin January 2015 (has links)
The UK Government has set an ambitious legislative goal of reducing greenhouse gas emissions by 80 % by 2050. Of the total energy used in the UK, 31 % is used in the domestic sector. In the domestic sector energy is used for space and hot water heating, lighting, appliances and cooking. Space and hot water heating make up 82 % of the total energy used in the UK domestic sector. Almost all of the energy used in the UK domestic sector originates from depletable resources. In order for the UK to reach its goal of decreasing greenhouse gas emissions by 80 % by 2050, the way energy is used in the UK domestic sector needs to change dramatically. The aim of this study is to identify opportunities for homeowners to be more sustainable without compromising their standard of living, by changing the way they use and supply energy. Homeowners’ ways of using and supplying energy today will be reviewed followed by an identification of measures that can be taken to create a more sustainable home from an energy perspective. Identified measures not only include usage of small-scale energy technologies but also application of energy efficiency measures and changes in behaviour that result in homeowners using energy in a more efficient way. The aim has been achieved by conducting a literature review, collecting statistical data regarding energy use from the Department of Energy and Climate Change and the undertaking of a case study. The literature review revealed that air source and solar assisted heat pumps, solar photovoltaic (solar PV) and fuel cell micro combined heat and power (fuel cell mCHP) are the most promising and widely available microgeneration technologies on the market today. LED light bulbs, wall and loft insulation and energy efficient appliances are the energy efficiency measures identified as having the highest potential to decrease the amount of energy used. The literature review also proved that behaviour in relation to energy use is a key area to address in order to make homeowners use energy in a more efficient way. The case study consisted of six case houses, based on the most common house types in the UK. The reference heating system used in the case study was a gas boiler connected to a central heating system of the house. 80 % of the homes in the UK are heated with a gas boiler and that is why it was chosen as a reference scenario. The case study showed that all of the microgeneration technologies use resources and energy in a more efficient way than the reference scenario. But despite the financial support of governmental subsidies none of the microgeneration technologies were financially viable options compared to a gas boiler. Energy efficiency measures, especially LED lighting, wall and loft insulation, significantly lowered the amount of energy used, they lowered the influence on greenhouse gas emissions and were financially viable options without the support of governmental subsidies. It was identified that microgeneration technologies are impacted by behaviour and that they can enable demand-side management, especially as the number of supply-driven sources such as wind and solar PV increases. In summation microgeneration technologies and energy efficiency measures have a large potential to help make homeowners become more sustainable from an energy perspective. Governmental support has a determining role in making them financially viable and therefore accessible to the public.
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Understanding and influencing energy efficient renovation decisionsWilson, Charles 11 1900 (has links)
This thesis is an investigation of why and how homeowners decide to renovate their homes. Energy efficient renovations are of particular interest given their potential contribution to public policy goals including greenhouse gas emission reduction. Policies seeking to improve energy efficiency in existing homes have to influence homeowners’ decisions. This requires a psychologically and behaviourally realistic understanding of the renovation decision process. Different research traditions offer competing models. These are tested through a series of hypotheses on the form and content of the renovation decision. The empirical dataset used combines both stated and revealed preference data. 809 homeowners in British Columbia were surveyed at three different cross-sections of the renovation decision process. The sample included both energy efficient (e.g., windows, insulation) and amenity renovators (e.g., kitchens, bathrooms), and was broadly representative of the population of renovating homeowners in British Columbia. Survey responses were calibrated using actual energy consumption data, and a supplementary survey of realtors. Calibration allowed homeowners’ expectations of the financial costs and benefits of renovating to be evaluated. Firstly, sampled homeowners systematically over-estimated their energy costs. Secondly, these estimates were subject to common information processing and recall biases. Thirdly, even homeowners in the middle of energy efficient renovations had expectations of capital costs, energy cost savings, and property value impacts that were largely unknown or unreliable. More generally, sampled homeowners lacked the basic knowledge necessary to appraise energy efficient renovations as financial investments. Homeowners’ motivations for renovating were more likely to be emotional and aesthetic in the case of amenities, but related to functional outcomes like thermal comfort in the case of energy efficiency. Social norms were influential in both cases but were underreported by homeowners. This was consistent with rationalisation biases which help individuals maintain self-esteem by emphasizing instrumental explanations for their actions. This psychologically realistic characterisation of the renovation decision suggests a range of design criteria for policy, and questions the effectiveness of narrowly-targeted information and incentive policies in their current form. However, policy implications should be generalised with caution given the low energy price and appreciating real estate market characteristics of the study region.
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ENERGY EFFICIENT SECURITY FOR WIRELESS SENSOR NETWORKSMoh'd, Abidalrahman 18 June 2013 (has links)
This thesis presents two main achievements. The first is a novel link-layer encryption protocol for wireless sensor networks. The protocol design aims to reduce energy consumption by reducing security-related communication overhead. This is done by merging security-related data of consecutive packets. The merging is based on simple mathematical operations. It helps to reduce energy consumption by eliminating the requirement to transmit security-related fields in the packet. The protocol is named the Compact Security Protocol and is referred to as C-Sec. In addition to energy savings, the C-Sec protocol also includes a unique security feature of hiding the packet header information. This feature makes it more difficult to trace the flow of wireless communication, and helps to minimize the effect of replay attacks. The C-Sec protocol is rigorously tested and compared with well-known related protocols. Performance evaluations demonstrate that C-Sec protocol outperforms other protocols in terms of energy savings. The protocol is evaluated with respect to other performance metrics including queuing delay and error probability.
The C-Sec operation requires fast encryption, which leads to a second major contribution: The SN-Sec, a 32-bit RISC secure wireless sensor platform with hardware cryptographic primitives. The security vulnerabilities in current WSNs platforms are scrutinized and the main approaches to implementing their cryptographic primitives are compared in terms of security, time, and energy efficiency. The SN-Sec secures these vulnerabilities and provides more time and energy efficiency. The choice of cryptographic primitives for SN-Sec is based on their compatibility with the constrained nature of WSNs and their security. The AES implementation has the best data-path and S-Box design in the literature. All SHA family members are implemented and compared to choose the most compatible with WSN constraints. An efficient elliptic-curve processor design is proposed. It has the least mathematical operations compared to elliptic-curve processors proposed for WSNs in the literature. It also exploits parallelism among mathematical operations to compute elliptic-curve point multiplication with minimal amount of clock cycles. SN-Sec is implemented using VHDL. Experimental results using synthesis for Spartan-6 low-power FPGA shows that the proposed design has very reasonable computational time and energy consumption.
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Niedrigenergiesortimente bei TopfkulturenWartenberg, Stephan 26 March 2015 (has links) (PDF)
Von 2012 bis 2014 wurden Topfkulturen im Zierpflanzenbau auf Sortenunterschiede im Wärmebedarf untersucht. Hinsichtlich der Einsparung an Heizenergie durch Sortenwahl wurde bei Pelargonien ein Potenzial von 10 %, bei Neuguinea-Impatiens von 48 % und bei Poinsettien von 40 % ermittelt. Diese Potenziale sind wegen weiterer Kriterien für die Sortenwahl und Varianten der Kulturführung in der Praxis des Gartenbaus nicht in vollem Umfang nutzbar, aber die für jede Art ermittelten Niedrigenergiesortimente bieten gute Einsparmöglichkeiten. Die Ergebnisse sind auch ein starker Impuls für die stärkere Berücksichtigung des Wärmebedarfs bei der Neuzüchtung von Sorten.
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On Exploration of Mechanical Insights into Bipedal Walking: Gait Characteristics, Energy Efficiency, and ExperimentationAlghooneh, Mansoor January 2014 (has links)
Human walking is dynamic, stable, and energy efficient. To achieve such remarkable legged locomotion in robots, engineers have explored bipedal robots developed based on two paradigms: trajectory-controlled and passive-based walking. Trajectory-controlled bipeds often deliver energy-inefficient gaits. The reason is that these bipeds are controlled via high-impedance geared electrical motors to accurately follow predesigned trajectories. Such trajectories are designed to keep a biped locally balanced continually while walking.
On the other hand, passive-based bipeds provide energy-efficient gaits. The reason is that these bipeds adapt to their natural dynamics. Such gaits are stable limit-cycles through entire walking motion, and do not require being locally balanced at every instant during walking. However, passive-based bipeds are often of round/point foot bipeds that are not capable of achieving and experiencing standing, stopping, and some important bipedal gait phases and events, such as the double support phase. Therefore, the goals of this thesis are established such that the aforementioned limitations on trajectory-controlled and passive-based bipeds are resolved.
Toward the above goal, comprehensive simulation and experimental explorations into bipedal walking have been carried out. Firstly, a novel systematic trajectory-controlled gait-planning framework has been developed to provide mechanical insights into bipedal walking in terms of gait characteristics and energy efficiency. For the same purpose, a novel mathematical model of passive-based bipedal walking with compliant hip-actuation and compliant-ankle flat-foot has been developed. Finally, based on mechanical insights that have been achieved by the aforementioned passive-based model, a physical prototype of a passive-based bipedal robot has been designed and fabricated. The prototype experimentally validates the importance of compliant hip-actuation in achieving a highly dynamic and energy efficient gait.
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Efficient Kiln Drying of Quality Softwood TimberMcCurdy, Murray Charles January 2006 (has links)
This thesis is a study of the kiln drying of radiata pine with a primary focus on the change in wood colour that occurs during this process. The energy efficiency of the drying process has also been examined using computer modelling. The aim of this work was to develop guidelines for commercial wood dryers who wish to produce high quality appearance grade timber in a competitive commercial environment. The colour change in radiata pine wood during kiln drying is mainly caused by sap compounds accumulating at the wood surface and reacting to form coloured compounds. The initial research involved drying experiments designed to determine the relationship between this colour change and the kiln schedule and also measure the accumulation of colour forming compounds. The kinetics of the colour change reaction were also measured using two methods, one in-vitro and the other using small samples of wood. From these experiments a colour change equation was developed that predicts the rate of colour formation based on the drying conditions and this was incorporated into a kiln stack model along with an energy efficiency model. The combined model was used to simulate the drying process to find schedules optimised for energy use and wood quality. The model was also used to simulate the energy efficiency of different humidity control configurations for wood drying kilns. A kiln micro-sensor system was also developed for use in kiln diagnostics and control with the particular aim of identifying areas in wood drying kilns with adverse drying conditions. The recommendation to kiln operators wishing to reduce colour change is to not exceed 70? and to use lower relative humidity schedules with a wet bulb depression of 15-20?. Operating at lower humidity can increase the energy used by the kiln so it is also recommended that kiln designers incorporate heat recovery into the humidity control mechanisms of the kiln.
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