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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
Building Envelope includes walls, roofs and openings, which react to the outdoor environmental condition. Today, with the increasing use of glass in building envelope, the energy usage of the buildings is increasing, especially in the offices and commercial buildings. Use of right glass type and control triggers helps to optimize

Building Envelope includes walls, roofs and openings, which react to the outdoor environmental condition. Today, with the increasing use of glass in building envelope, the energy usage of the buildings is increasing, especially in the offices and commercial buildings. Use of right glass type and control triggers helps to optimize the energy use, by tradeoff between optical and thermal properties. The part of the research looks at the different control triggers and its range that governs the use of electrochromic glass to regulate the energy usage in building. All different control trigger that can be possibly used for regulating the clear and tint state of glass were analyzed with most appropriate range. Its range was triggered such that 80% time of the glass is trigger between the ranges. The other building parameters like window wall ratio and orientations were also investigated. The other half of the research study looks into the feasibility of using the Electrochromic windows, as it is ought to be the main factor governing the market usage of Electrochromic windows and to investigate the possible ways to make it feasible. Different LCC parameters were studied to make it market feasible product. This study shows that installing this technology with most appropriate trigger range can reduce annual building energy consumption from 6-8% but still cost of the technology is 3 times the ASHRAE glass, which results in 70-90 years of payback. This study concludes that south orientation saves up to 3-5% of energy and 4-6% of cooling tons while north orientation gives negligible saving using EC glass. LCC parameters show that there is relative change in increasing the net saving for different parameters but none except 50% of the present glass cost is the possible option where significant change is observed.
ContributorsMunshi, Kavish Prakash (Author) / Bryan, Harvey (Thesis advisor) / Reddy, Agami (Committee member) / Addison, Marlin (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Dynamic loading is the term used for one way of optimally loading a transformer. Dynamic loading means the utility takes into account the thermal time constant of the transformer along with the cooling mode transitions, loading profile and ambient temperature when determining the time-varying loading capability of a transformer. Knowing

Dynamic loading is the term used for one way of optimally loading a transformer. Dynamic loading means the utility takes into account the thermal time constant of the transformer along with the cooling mode transitions, loading profile and ambient temperature when determining the time-varying loading capability of a transformer. Knowing the maximum dynamic loading rating can increase utilization of the transformer while not reducing life-expectancy, delaying the replacement of the transformer. This document presents the progress on the transformer dynamic loading project sponsored by Salt River Project (SRP). A software application which performs dynamic loading for substation distribution transformers with appropriate transformer thermal models is developed in this project. Two kinds of thermal hottest-spot temperature (HST) and top-oil temperature (TOT) models that will be used in the application--the ASU HST/TOT models and the ANSI models--are presented. Brief validations of the ASU models are presented, showing that the ASU models are accurate in simulating the thermal processes of the transformers. For this production grade application, both the ANSI and the ASU models are built and tested to select the most appropriate models to be used in the dynamic loading calculations. An existing application to build and select the TOT model was used as a starting point for the enhancements developed in this work. These enhancements include:  Adding the ability to develop HST models to the existing application,  Adding metrics to evaluate the models accuracy and selecting which model will be used in dynamic loading calculation  Adding the capability to perform dynamic loading calculations,  Production of a maximum dynamic load profile that the transformer can tolerate without acceleration of the insulation aging,  Provide suitable output (plots and text) for the results of the dynamic loading calculation. Other challenges discussed include: modification to the input data format, data-quality control, cooling mode estimation. Efforts to overcome these challenges are discussed in this work.
ContributorsLiu, Yi (Author) / Tylavksy, Daniel J (Thesis advisor) / Karady, George G. (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2011
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Description
This thesis pursues a method to deregulate the electric distribution system and provide support to distributed renewable generation. A locational marginal price is used to determine prices across a distribution network in real-time. The real-time pricing may provide benefits such as a reduced electricity bill, decreased peak demand, and lower

This thesis pursues a method to deregulate the electric distribution system and provide support to distributed renewable generation. A locational marginal price is used to determine prices across a distribution network in real-time. The real-time pricing may provide benefits such as a reduced electricity bill, decreased peak demand, and lower emissions. This distribution locational marginal price (D-LMP) determines the cost of electricity at each node in the electrical network. The D-LMP is comprised of the cost of energy, cost of losses, and a renewable energy premium. The renewable premium is an adjustable function to compensate `green' distributed generation. A D-LMP is derived and formulated from the PJM model, as well as several alternative formulations. The logistics and infrastructure an implementation is briefly discussed. This study also takes advantage of the D-LMP real-time pricing to implement distributed storage technology. A storage schedule optimization is developed using linear programming. Day-ahead LMPs and historical load data are used to determine a predictive optimization. A test bed is created to represent a practical electric distribution system. Historical load, solar, and LMP data are used in the test bed to create a realistic environment. A power flow and tabulation of the D-LMPs was conducted for twelve test cases. The test cases included various penetrations of solar photovoltaics (PV), system networking, and the inclusion of storage technology. Tables of the D-LMPs and network voltages are presented in this work. The final costs are summed and the basic economics are examined. The use of a D-LMP can lower costs across a system when advanced technologies are used. Storage improves system costs, decreases losses, improves system load factor, and bolsters voltage. Solar energy provides many of these same attributes at lower penetrations, but high penetrations have a detrimental effect on the system. System networking also increases these positive effects. The D-LMP has a positive impact on residential customer cost, while greatly increasing the costs for the industrial sector. The D-LMP appears to have many positive impacts on the distribution system but proper cost allocation needs further development.
ContributorsKiefer, Brian Daniel (Author) / Heydt, Gerald T (Thesis advisor) / Shunk, Dan (Committee member) / Hedman, Kory (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Arizona has an abundant solar resource and technologically mature systems are available to capture it, but solar energy systems are still considered to be an innovative technology. Adoption rates for solar and wind energy systems rise and fall with the political tides, and are relatively low in most rural areas

Arizona has an abundant solar resource and technologically mature systems are available to capture it, but solar energy systems are still considered to be an innovative technology. Adoption rates for solar and wind energy systems rise and fall with the political tides, and are relatively low in most rural areas in Arizona. This thesis tests the hypothesis that a consumer profile developed to characterize the adopters of renewable energy technology (RET) systems in rural Arizona is the same as the profile of other area residents who performed renovations, upgrades or additions to their homes. Residents of Santa Cruz and Cochise Counties who had obtained building permits to either install a solar or wind energy system or to perform a substantial renovation or upgrade to their home were surveyed to gather demographic, psychographic and behavioristic data. The data from 133 survey responses (76 from RET adopters and 57 from non-adopters) provided insights about their decisions regarding whether or not to adopt a RET system. The results, which are statistically significant at the 99% level of confidence, indicate that RET adopters had smaller households, were older and had higher education levels and greater income levels than the non-adopters. The research also provides answers to three related questions: First, are the energy conservation habits of RET adopters the same as those of non-adopters? Second, what were the sources of information consulted and the most important factors that motivated the decision to purchase a solar or wind energy system? And finally, are any of the factors which influenced the decision to live in a rural area in southeastern Arizona related to the decision to purchase a renewable energy system? The answers are provided, along with a series of recommendations that are designed to inform marketers and other promoters of RETs about how to utilize these results to help achieve their goals.
ContributorsPorter, Wayne Eliot (Author) / Reddy, T. Agami (Thesis advisor) / Pasqualetti, Martin (Committee member) / Larson, Kelli (Committee member) / Kennedy, Linda (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Due to economic and environmental reasons, several states in the United States of America have a mandated renewable portfolio standard which requires that a certain percentage of the load served has to be met by renewable resources of energy such as solar, wind and biomass. Renewable resources provide energy at

Due to economic and environmental reasons, several states in the United States of America have a mandated renewable portfolio standard which requires that a certain percentage of the load served has to be met by renewable resources of energy such as solar, wind and biomass. Renewable resources provide energy at a low variable cost and produce less greenhouse gases as compared to conventional generators. However, some of the complex issues with renewable resource integration are due to their intermittent and non-dispatchable characteristics. Furthermore, most renewable resources are location constrained and are usually located in regions with insufficient transmission facilities. In order to deal with the challenges presented by renewable resources as compared to conventional resources, the transmission network expansion planning procedures need to be modified. New high voltage lines need to be constructed to connect the remote renewable resources to the existing transmission network to serve the load centers. Moreover, the existing transmission facilities may need to be reinforced to accommodate the large scale penetration of renewable resource. This thesis proposes a methodology for transmission expansion planning with large-scale integration of renewable resources, mainly solar and wind generation. An optimization model is used to determine the lines to be constructed or upgraded for several scenarios of varying levels of renewable resource penetration. The various scenarios to be considered are obtained from a production cost model that analyses the effects that renewable resources have on the transmission network over the planning horizon. A realistic test bed was created using the data for solar and wind resource penetration in the state of Arizona. The results of the production cost model and the optimization model were subjected to tests to ensure that the North American Electric Reliability Corporation (NERC) mandated N-1 contingency criterion is satisfied. Furthermore, a cost versus benefit analysis was performed to ensure that the proposed transmission plan is economically beneficial.
ContributorsHariharan, Sruthi (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald (Committee member) / Hedman, Kory (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Among the various end-use sectors, the commercial sector is expected to have the second-largest increase in total primary energy consump¬tion from 2009 to 2035 (5.8 quadrillion Btu) with a growth rate of 1.1% per year, it is the fastest growing end-use sectors. In order to make major gains in reducing

Among the various end-use sectors, the commercial sector is expected to have the second-largest increase in total primary energy consump¬tion from 2009 to 2035 (5.8 quadrillion Btu) with a growth rate of 1.1% per year, it is the fastest growing end-use sectors. In order to make major gains in reducing U.S. building energy use commercial sector buildings must be improved. Energy benchmarking of buildings gives the facility manager or the building owner a quick evaluation of energy use and the potential for energy savings. It is the process of comparing the energy performance of a building to standards and codes, to a set target performance or to a range of energy performance values of similar buildings in order to help assess opportunities for improvement. Commissioning of buildings is the process of ensuring that systems are designed, installed, functionally tested and capable of being operated and maintained according to the owner's operational needs. It is the first stage in the building upgrade process after it has been assessed using benchmarking tools. The staged approach accounts for the interactions among all the energy flows in a building and produces a systematic method for planning upgrades that increase energy savings. This research compares and analyzes selected benchmarking and retrocommissioning tools to validate their accuracy such that they could be used in the initial audit process of a building. The benchmarking study analyzes the Energy Use Intensities (EUIs) and Ratings assigned by Portfolio Manager and Oak Ridge National Laboratory (ORNL) Spreadsheets. The 90.1 Prototype models and Commercial Reference Building model for Large Office building type were used for this comparative analysis. A case-study building from the DOE - funded Energize Phoenix program was also benchmarked for its EUI and rating. The retrocommissioning study was conducted by modeling these prototype models and the case-study building in the Facility Energy Decision System (FEDS) tool to simulate their energy consumption and analyze the retrofits suggested by the tool. The results of the benchmarking study proved that a benchmarking tool could be used as a first step in the audit process, encouraging the building owner to conduct an energy audit and realize the energy savings potential. The retrocommissioning study established the validity of FEDS as an accurate tool to simulate a building for its energy performance using basic inputs and to accurately predict the energy savings achieved by the retrofits recommended on the basis of maximum LCC savings.
ContributorsAgnihotri, Shreya Prabodhkumar (Author) / Reddy, T Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2011
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Description
In recent years environmental life-cycle assessments (LCA) have been increasingly used to support planning and development of sustainable infrastructure. This study demonstrates the application of LCA to estimate embedded energy use and greenhouse gas (GHG) emissions related to materials manufacturing and construction processes for low and high density single-family neighborhoods

In recent years environmental life-cycle assessments (LCA) have been increasingly used to support planning and development of sustainable infrastructure. This study demonstrates the application of LCA to estimate embedded energy use and greenhouse gas (GHG) emissions related to materials manufacturing and construction processes for low and high density single-family neighborhoods typically found in the Southwest. The LCA analysis presented in this study includes the assessment of more than 8,500 single family detached units, and 130 miles of related roadway infrastructure. The study estimates embedded and GHG emissions as a function of building size (1,500 - 3000 square feet), number of stories (1 or 2), and exterior wall material composition (stucco, brick, block, wood), roof material composition (clay tile, cement tile, asphalt shingles, built up), and as a function of roadway typology per mile (asphalt local residential roads, collectors, arterials). While a hybrid economic input-out life-cycle assessment is applied to estimate the energy and GHG emissions impacts of the residential units, the PaLATE tool is applied to determine the environmental effects of pavements and roads. The results indicate that low density single family neighborhoods are 2 - 2.5 X more energy and GHG intensive, per residential dwelling (unit) built, than high density residential neighborhoods. This relationship holds regardless of whether the functional unit is per acre or per capita. The results also indicate that a typical low density neighborhood (less than 2 dwellings per acre) requires 78 percent more energy and resource in roadway infrastructure per residential unit than a traditional small lot high density (more than 6 dwelling per acre). Also, this study shows that new master planned communities tend to be more energy intensive than traditional non master planned residential developments.
ContributorsFrijia, Stephane (Author) / Guhathakurta, Subhrajit (Committee member) / Williams, Eric D. (Committee member) / Pijawka, David K (Committee member) / Arizona State University (Publisher)
Created2011
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Description
The use of energy-harvesting in a wireless sensor network (WSN) is essential for situations where it is either difficult or not cost effective to access the network's nodes to replace the batteries. In this paper, the problems involved in controlling an active sensor network that is powered both by batteries

The use of energy-harvesting in a wireless sensor network (WSN) is essential for situations where it is either difficult or not cost effective to access the network's nodes to replace the batteries. In this paper, the problems involved in controlling an active sensor network that is powered both by batteries and solar energy are investigated. The objective is to develop control strategies to maximize the quality of coverage (QoC), which is defined as the minimum number of targets that must be covered and reported over a 24 hour period. Assuming a time varying solar profile, the problem is to optimally control the sensing range of each sensor so as to maximize the QoC while maintaining connectivity throughout the network. Implicit in the solution is the dynamic allocation of solar energy during the day to sensing and to recharging the battery so that a minimum coverage is guaranteed even during the night, when only the batteries can supply energy to the sensors. This problem turns out to be a non-linear optimal control problem of high complexity. Based on novel and useful observations, a method is presented to solve it as a series of quasiconvex (unimodal) optimization problems which not only ensures a maximum QoC, but also maintains connectivity throughout the network. The runtime of the proposed solution is 60X less than a naive but optimal method which is based on dynamic programming, while the peak error of the solution is less than 8%. Unlike the dynamic programming method, the proposed method is scalable to large networks consisting of hundreds of sensors and targets. The solution method enables a designer to explore the optimal configuration of network design. This paper offers many insights in the design of energy-harvesting networks, which result in minimum network setup cost through determination of optimal configuration of number of sensors, sensing beam width, and the sampling time.
ContributorsGaudette, Benjamin (Author) / Vrudhula, Sarma (Thesis advisor) / Shrivastava, Aviral (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Plasmon resonance in nanoscale metallic structures has shown its ability to concentrate electromagnetic energy into sub-wavelength volumes. Metal nanostructures exhibit a high extinction coefficient in the visible and near infrared spectrum due to their large absorption and scattering cross sections corresponding to their surface plasmon resonance. Hence, they can serve

Plasmon resonance in nanoscale metallic structures has shown its ability to concentrate electromagnetic energy into sub-wavelength volumes. Metal nanostructures exhibit a high extinction coefficient in the visible and near infrared spectrum due to their large absorption and scattering cross sections corresponding to their surface plasmon resonance. Hence, they can serve as an attractive candidate for solar energy conversion. Recent papers have showed that dielectric core/metallic shell nanoparticles yielded a plasmon resonance wavelength tunable from visible to infrared by changing the ratio of core radius to the total radius. Therefore it is interesting to develop a dispersion of core-shell multifunctional nanoparticles capable of dynamically changing their volume ratio and thus their spectral radiative properties. Nanoparticle suspensions (nanofluids) are known to offer a variety of benefits for thermal transport and energy conversion. Nanofluids have been proven to increase the efficiency of the photo-thermal energy conversion process in direct solar absorption collectors (DAC). Combining these two cutting-edge technologies enables the use of core-shell nanoparticles to control the spectral and radiative properties of plasmonic nanofluids in order to efficiently harvest and convert solar energy. Plasmonic nanofluids that have strong energy concentrating capacity and spectral selectivity can be used in many high-temperature energy systems where radiative heat transport is essential. In this thesis,the surface plasmon resonance effect and the wavelength tuning ranges for different metallic shell nanoparticles are investigated, the solar-weighted efficiencies of corresponding core-shell nanoparticle suspensions are explored, and a quantitative study of core-shell nanoparticle suspensions in a DAC system is provided. Using core-shell nanoparticle dispersions, it is possible to create efficient spectral solar absorption fluids and design materials for applications which require variable spectral absorption or scattering.
ContributorsLv, Wei (Author) / Phelan, Patrick E (Thesis advisor) / Dai, Lenore (Committee member) / Prasher, Ravi (Committee member) / Arizona State University (Publisher)
Created2012