Matching Items (17)
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Distributed estimation uses many inexpensive sensors to compose an accurate estimate of a given parameter. It is frequently implemented using wireless sensor networks. There have been several studies on optimizing power allocation in wireless sensor networks used for distributed estimation, the vast majority of which assume linear radio-frequency amplifiers. Linear

Distributed estimation uses many inexpensive sensors to compose an accurate estimate of a given parameter. It is frequently implemented using wireless sensor networks. There have been several studies on optimizing power allocation in wireless sensor networks used for distributed estimation, the vast majority of which assume linear radio-frequency amplifiers. Linear amplifiers are inherently inefficient, so in this dissertation nonlinear amplifiers are examined to gain efficiency while operating distributed sensor networks. This research presents a method to boost efficiency by operating the amplifiers in the nonlinear region of operation. Operating amplifiers nonlinearly presents new challenges. First, nonlinear amplifier characteristics change across manufacturing process variation, temperature, operating voltage, and aging. Secondly, the equations conventionally used for estimators and performance expectations in linear amplify-and-forward systems fail. To compensate for the first challenge, predistortion is utilized not to linearize amplifiers but rather to force them to fit a common nonlinear limiting amplifier model close to the inherent amplifier performance. This minimizes the power impact and the training requirements for predistortion. Second, new estimators are required that account for transmitter nonlinearity. This research derives analytically and confirms via simulation new estimators and performance expectation equations for use in nonlinear distributed estimation. An additional complication when operating nonlinear amplifiers in a wireless environment is the influence of varied and potentially unknown channel gains. The impact of these varied gains and both measurement and channel noise sources on estimation performance are analyzed in this paper. Techniques for minimizing the estimate variance are developed. It is shown that optimizing transmitter power allocation to minimize estimate variance for the most-compressed parameter measurement is equivalent to the problem for linear sensors. Finally, a method for operating distributed estimation in a multipath environment is presented that is capable of developing robust estimates for a wide range of Rician K-factors. This dissertation demonstrates that implementing distributed estimation using nonlinear sensors can boost system efficiency and is compatible with existing techniques from the literature for boosting efficiency at the system level via sensor power allocation. Nonlinear transmitters work best when channel gains are known and channel noise and receiver noise levels are low.
ContributorsSantucci, Robert (Author) / Spanias, Andreas (Thesis advisor) / Tepedelenlioðlu, Cihan (Committee member) / Bakkaloglu, Bertan (Committee member) / Tsakalis, Kostas (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Energy consumption of the data centers worldwide is rapidly growing fueled by ever-increasing demand for Cloud computing applications ranging from social networking to e-commerce. Understandably, ensuring energy-efficiency and sustainability of Cloud data centers without compromising performance is important for both economic and environmental reasons. This dissertation develops a cyber-physical multi-tier

Energy consumption of the data centers worldwide is rapidly growing fueled by ever-increasing demand for Cloud computing applications ranging from social networking to e-commerce. Understandably, ensuring energy-efficiency and sustainability of Cloud data centers without compromising performance is important for both economic and environmental reasons. This dissertation develops a cyber-physical multi-tier server and workload management architecture which operates at the local and the global (geo-distributed) data center level. We devise optimization frameworks for each tier to optimize energy consumption, energy cost and carbon footprint of the data centers. The proposed solutions are aware of various energy management tradeoffs that manifest due to the cyber-physical interactions in data centers, while providing provable guarantee on the solutions' computation efficiency and energy/cost efficiency. The local data center level energy management takes into account the impact of server consolidation on the cooling energy, avoids cooling-computing power tradeoff, and optimizes the total energy (computing and cooling energy) considering the data centers' technology trends (servers' power proportionality and cooling system power efficiency). The global data center level cost management explores the diversity of the data centers to minimize the utility cost while satisfying the carbon cap requirement of the Cloud and while dealing with the adversity of the prediction error on the data center parameters. Finally, the synergy of the local and the global data center energy and cost optimization is shown to help towards achieving carbon neutrality (net-zero) in a cost efficient manner.
ContributorsAbbasi, Zahra (Author) / Gupta, Sandeep K. S. (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Shrivastava, Aviral (Committee member) / Wu, Carole-Jean (Committee member) / Arizona State University (Publisher)
Created2014
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Description
In the U.S., high-speed passenger rail has recently become an active political topic, with multiple corridors currently being considered through federal and state level initiatives. One frequently cited benefit of high-speed rail proposals is that they offer a transition to a more sustainable transportation system with reduced greenhouse gas emissions

In the U.S., high-speed passenger rail has recently become an active political topic, with multiple corridors currently being considered through federal and state level initiatives. One frequently cited benefit of high-speed rail proposals is that they offer a transition to a more sustainable transportation system with reduced greenhouse gas emissions and fossil energy consumption. This study investigates the feasibility of high-speed rail development as a long-term greenhouse gas emission mitigation strategy while considering major uncertainties in the technological and operational characteristics of intercity travel. First, I develop a general model for evaluating the emissions impact of intercity travel modes. This model incorporates aspects of life-cycle assessment and technological forecasting. The model is then used to compare future scenarios of energy and greenhouse gas emissions associated with the development of high-speed rail and other intercity travel technologies. Three specific rail corridors are evaluated and policy guidelines are developed regarding the emissions impacts of these investments. The results suggest prioritizing high-speed rail investments on short, dense corridors with fewer stops. Likewise, less emphasis should be placed on larger investments that require long construction times due to risks associated with payback of embedded emissions as competing technology improves.
ContributorsBurgess, Edward (Author) / Williams, Eric (Thesis advisor) / Fink, Jonathan (Thesis advisor) / Yaro, Robert (Committee member) / Arizona State University (Publisher)
Created2011
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Description
A major problem faced by electric utilities is the need to meet electric loads during certain times of peak demand. One of the widely adopted and promising programs is demand response (DR) where building owners are encouraged, by way of financial incentives, to reduce their electric loads during a few

A major problem faced by electric utilities is the need to meet electric loads during certain times of peak demand. One of the widely adopted and promising programs is demand response (DR) where building owners are encouraged, by way of financial incentives, to reduce their electric loads during a few hours of the day when the electric utility is likely to encounter peak loads. In this thesis, we investigate the effect of various DR measures and their resulting indoor occupant comfort implications, on two prototype commercial buildings in the hot and dry climate of Phoenix, AZ. The focus of this study is commercial buildings during peak hours and peak days. Two types of office buildings are modeled using a detailed building energy simulation program (EnergyPlus V6.0.0): medium size office building (53,600 sq. ft.) and large size office building (498,600 sq. ft.). The two prototype buildings selected are those advocated by the Department of Energy and adopted by ASHRAE in the framework of ongoing work on ASHRAE standard 90.1 which reflect 80% of the commercial buildings in the US. After due diligence, the peak time window is selected to be 12:00-18:00 PM (6 hour window). The days when utility companies require demand reduction mostly fall during hot summer days. Therefore, two days, the summer high-peak (15th July) and the mid-peak (29th June) days are selected to perform our investigations. The impact of building thermal mass as well as several other measures such as reducing lighting levels, increasing thermostat set points, adjusting supply air temperature, resetting chilled water temperature are studied using the EnergyPlus building energy simulation program. Subsequently the simulation results are summarized in tabular form so as to provide practical guidance and recommendations of which DR measures are appropriate for different levels of DR reductions and the associated percentage values of people dissatisfied (PPD). This type of tabular recommendations is of direct usefulness to the building owners and operators contemplating DR response. The methodology can be extended to other building types and climates as needed.
ContributorsKhanolkar, Amruta (Author) / Reddy, T Agami (Thesis advisor) / Addison, Marlin (Committee member) / Bryan, Harvey (Committee member) / Arizona State University (Publisher)
Created2012
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Description
This study aims to teach the reader about the process of making a building more energy efficient at ASU. In this study the importance of energy efficiency in buildings will be discussed as well as how building efficiency is important for the three tiers of sustainability. The case of energy

This study aims to teach the reader about the process of making a building more energy efficient at ASU. In this study the importance of energy efficiency in buildings will be discussed as well as how building efficiency is important for the three tiers of sustainability. The case of energy efficiency in the environment, economy, and society will be outlined with the intent of creating urgency for the implementation of energy efficiency. Environment, economy, and society, the three tiers of sustainability fit the model of energy efficiency because efficient energy is a principle of sustainability. Efficient energy can fill the gap between our energy system at present and the energy system of the future. This document outlines the steps that ASU goes through when there is an energy upgrade to a building on campus. It also includes a mock audit of the Psychology North building at ASU. This mock audit serves as an example to justify how the steps outlined in this document can be used to initiate an energy retrofit. A person who reads this document will be able to understand the energy retrofit process. The main argument is that there is room for student inclusion in this process, by giving students the knowledge on how to initiate an energy retrofit they have the tools to be included. Practicing building efficiency on campus will help ASU to succeed in accomplishing numbers two and four of their sustainability goals: "1) Carbon Neutrality, 2) Zero Solid/Water Waste, 3) Active Engagement, and 4) Principled Practice" (ASU, 2011).
ContributorsCladianos, Bradley Pete (Author) / Kelman, Jonathan (Thesis director) / Richter, Jennifer (Committee member) / School of Sustainability (Contributor, Contributor) / School of Earth and Space Exploration (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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The research analyzes the transformation of wasted thermal energy into a usable form through thermogalvanic devices. This technology helps mitigate international growing energy demands. Building energy efficiency is a critical research topic, since the loads account for 40% of all energy demand in developed nations, and 30% in less developed

The research analyzes the transformation of wasted thermal energy into a usable form through thermogalvanic devices. This technology helps mitigate international growing energy demands. Building energy efficiency is a critical research topic, since the loads account for 40% of all energy demand in developed nations, and 30% in less developed nations. A significant portion of the energy consumed for heating and cooling, where a majority is dissipated to the ambient as waste heat. This research answers how much power output (µW·cm-2) can the thermogalvanic brick experimentally produce from an induced temperature gradient? While there are multiple avenues for the initial and optimized prototype design, one key area of interest relating to thermogalvanic devices is the effective surface area of the electrodes. This report highlights the experimental power output measurements of a Cu/Cu2+ thermogalvanic brick by manipulating the effective surface area of the electrodes. Across three meshes, the maximum power output normalized for temperature was found to be between 2.13-2.87 x 10-3 μWcm-2K-2. The highest normalized power output corresponded to the mesh with the highest effective surface area, which was classified as the fine mesh. This intuitively aligned with the theoretical understanding of surface area and maximum power output, where decreasing the activation resistance also reduces the internal resistance, which increases the theoretical maximum power.
ContributorsKiracofe, Ryan Moore (Author) / Phelan, Patrick (Thesis director) / El Asmar, Mounir (Committee member) / Mechanical and Aerospace Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Energy performance and efficiency plays of major role in the operations of K-12 schools, as it is a significant expense and a source of budgetary pressure upon schools. Energy performance is tied to the physical infrastructure of schools, as well as the operational and behavioral patterns they accommodate. Little documentation

Energy performance and efficiency plays of major role in the operations of K-12 schools, as it is a significant expense and a source of budgetary pressure upon schools. Energy performance is tied to the physical infrastructure of schools, as well as the operational and behavioral patterns they accommodate. Little documentation exists within the existing literature on the measured post-occupancy performance of schools once they have begun measuring and tracking their energy performance. Further, little is known about the patterns of change over time in regard to energy performance and whether there is differentiation in these patterns between school districts.

This paper examines the annual Energy Use Intensity (EUI) of 28 different K-12 schools within the Phoenix Metropolitan Region of Arizona over the span of five years and presents an analysis of changes in energy performance resulting from the measurement of energy use in K-12 schools. This paper also analyzes the patterns of change in energy use over time and provides a comparison of these patterns by school district.

An analysis of the energy performance data for the selected schools revealed a significant positive impact on the ability for schools to improve their energy performance through ongoing performance measurement. However, while schools tend to be able to make energy improvements through the implementation of energy measurement and performance tracking, deviation may exist in their ability to maintain ongoing energy performance over time. The results suggest that implementation of ongoing measurement is likely to produce positive impacts on the energy performance of schools, however further research is recommended to enhance and refine these results.
ContributorsThurston, Anna (Author) / Sullivan, Kenneth (Thesis advisor) / Okamura, Patrick (Committee member) / Slife, Curtis (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Energy use within urban building stocks is continuing to increase globally as populations expand and access to electricity improves. This projected increase in demand could require deployment of new generation capacity, but there is potential to offset some of this demand through modification of the buildings themselves. Building

Energy use within urban building stocks is continuing to increase globally as populations expand and access to electricity improves. This projected increase in demand could require deployment of new generation capacity, but there is potential to offset some of this demand through modification of the buildings themselves. Building stocks are quasi-permanent infrastructures which have enduring influence on urban energy consumption, and research is needed to understand: 1) how development patterns constrain energy use decisions and 2) how cities can achieve energy and environmental goals given the constraints of the stock. This requires a thorough evaluation of both the growth of the stock and as well as the spatial distribution of use throughout the city. In this dissertation, a case study in Los Angeles County, California (LAC) is used to quantify urban growth, forecast future energy use under climate change, and to make recommendations for mitigating energy consumption increases. A reproducible methodological framework is included for application to other urban areas.

In LAC, residential electricity demand could increase as much as 55-68% between 2020 and 2060, and building technology lock-in has constricted the options for mitigating energy demand, as major changes to the building stock itself are not possible, as only a small portion of the stock is turned over every year. Aggressive and timely efficiency upgrades to residential appliances and building thermal shells can significantly offset the projected increases, potentially avoiding installation of new generation capacity, but regulations on new construction will likely be ineffectual due to the long residence time of the stock (60+ years and increasing). These findings can be extrapolated to other U.S. cities where the majority of urban expansion has already occurred, such as the older cities on the eastern coast. U.S. population is projected to increase 40% by 2060, with growth occurring in the warmer southern and western regions. In these growing cities, improving new construction buildings can help offset electricity demand increases before the city reaches the lock-in phase.
ContributorsReyna, Janet Lorel (Author) / Chester, Mikhail V (Thesis advisor) / Gurney, Kevin (Committee member) / Reddy, T. Agami (Committee member) / Rey, Sergio (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Residential air conditioning systems represent a critical load for many electric

utilities, especially for those who serve customers in hot climates. In hot and dry

climates, in particular, the cooling load is usually relatively low during night hours and

early mornings and hits its maximum in the late afternoon. If electric loads could

Residential air conditioning systems represent a critical load for many electric

utilities, especially for those who serve customers in hot climates. In hot and dry

climates, in particular, the cooling load is usually relatively low during night hours and

early mornings and hits its maximum in the late afternoon. If electric loads could be

shifted from peak hours (e.g., late afternoon) to off-peak hours (e.g., late morning), not

only would building operation costs decrease, the need to run peaker plants, which

typically use more fossil fuels than non-peaker plants, would also decrease. Thus, shifting

electricity consumption from peak to off-peak hours promotes economic and

environmental savings. Operational and technological strategies can reduce the load

during peak hours by shifting cooling operation from on-peak hours to off-peak hours.

Although operational peak load shifting strategies such as precooling may require

mechanical cooling (e.g., in climates like Phoenix, Arizona), this cooling is less

expensive than on-peak cooling due to demand charges or time-based price plans.

Precooling is an operational shift, rather than a technological one, and is thus widely

accessible to utilities’ customer base. This dissertation compares the effects of different

precooling strategies in a Phoenix-based utility’s residential customer market and

assesses the impact of technological enhancements (e.g., energy efficiency measures and

solar photovoltaic system) on the performance of precooling. This dissertation focuses on

the operational and technological peak load shifting strategies that are feasible for

residential buildings and discusses the advantages of each in terms of peak energy

savings and residential electricity cost savings.
ContributorsArababadi, Reza (Author) / Parrish, Kristen (Thesis advisor) / Reddy, T A (Committee member) / Jackson, Roderick K (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Integrated circuits must be energy efficient. This efficiency affects all aspects of chip design, from the battery life of embedded devices to thermal heating on high performance servers. As technology scaling slows, future generations of transistors will lack the energy efficiency gains as it has had in previous generations. Therefore,

Integrated circuits must be energy efficient. This efficiency affects all aspects of chip design, from the battery life of embedded devices to thermal heating on high performance servers. As technology scaling slows, future generations of transistors will lack the energy efficiency gains as it has had in previous generations. Therefore, other sources of energy efficiency will be much more important. Many computations have the potential to be executed for extreme energy efficiency but are not instigated because the platforms they run on are not optimized for efficient execution. ASICs improve energy efficiency by reducing flexibility and leveraging the properties of a specific computation. However, ASICs are fixed in function and therefore have incredible opportunity cost. FPGAs offer a reconfigurable solution but are 25x less energy efficient than ASIC implementation. Spatially programmable architectures (SPAs) are similar in design and structure to ASICs and FPGAs but are able bridge the ASIC-FPGA energy efficiency gap by trading flexibility for efficiency. However, SPAs are difficult to program because they do not share the same programming model as normal architectures that execute in time. This work addresses compiler challenges for coarse grained, locally interconnected SPA for domain efficiency (SPADE). A novel SPADE topology, called the wave pipeline, is introduced that is designed for the image signal processing domain that is both efficient and simple to compile to. A compiler for the wave pipeline is created that solves for maximum energy and area efficiency using low complexity, greedy methods. The wave pipeline topology and compiler allow for us to investigate and experiment with image signal processing applications to prove the feasibility of SPADE compilers.
ContributorsMackay, Curtis (Author) / Brunhaver, John (Thesis advisor) / Karam, Lina J (Committee member) / Seo, Jae-Sun (Committee member) / Arizona State University (Publisher)
Created2016