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Description
The ability to design high performance buildings has acquired great importance in recent years due to numerous federal, societal and environmental initiatives. However, this endeavor is much more demanding in terms of designer expertise and time. It requires a whole new level of synergy between automated performance prediction with the

The ability to design high performance buildings has acquired great importance in recent years due to numerous federal, societal and environmental initiatives. However, this endeavor is much more demanding in terms of designer expertise and time. It requires a whole new level of synergy between automated performance prediction with the human capabilities to perceive, evaluate and ultimately select a suitable solution. While performance prediction can be highly automated through the use of computers, performance evaluation cannot, unless it is with respect to a single criterion. The need to address multi-criteria requirements makes it more valuable for a designer to know the "latitude" or "degrees of freedom" he has in changing certain design variables while achieving preset criteria such as energy performance, life cycle cost, environmental impacts etc. This requirement can be met by a decision support framework based on near-optimal "satisficing" as opposed to purely optimal decision making techniques. Currently, such a comprehensive design framework is lacking, which is the basis for undertaking this research. The primary objective of this research is to facilitate a complementary relationship between designers and computers for Multi-Criterion Decision Making (MCDM) during high performance building design. It is based on the application of Monte Carlo approaches to create a database of solutions using deterministic whole building energy simulations, along with data mining methods to rank variable importance and reduce the multi-dimensionality of the problem. A novel interactive visualization approach is then proposed which uses regression based models to create dynamic interplays of how varying these important variables affect the multiple criteria, while providing a visual range or band of variation of the different design parameters. The MCDM process has been incorporated into an alternative methodology for high performance building design referred to as Visual Analytics based Decision Support Methodology [VADSM]. VADSM is envisioned to be most useful during the conceptual and early design performance modeling stages by providing a set of potential solutions that can be analyzed further for final design selection. The proposed methodology can be used for new building design synthesis as well as evaluation of retrofits and operational deficiencies in existing buildings.
ContributorsDutta, Ranojoy (Author) / Reddy, T Agami (Thesis advisor) / Runger, George C. (Committee member) / Addison, Marlin S. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This thesis addresses the issue of making an economic case for energy storage in power systems. Bulk energy storage has often been suggested for large scale electric power systems in order to levelize load; store energy when it is inexpensive and discharge energy when it is expensive; potentially defer transmission

This thesis addresses the issue of making an economic case for energy storage in power systems. Bulk energy storage has often been suggested for large scale electric power systems in order to levelize load; store energy when it is inexpensive and discharge energy when it is expensive; potentially defer transmission and generation expansion; and provide for generation reserve margins. As renewable energy resource penetration increases, the uncertainty and variability of wind and solar may be alleviated by bulk energy storage technologies. The quadratic programming function in MATLAB is used to simulate an economic dispatch that includes energy storage. A program is created that utilizes quadratic programming to analyze various cases using a 2010 summer peak load from the Arizona transmission system, part of the Western Electricity Coordinating Council (WECC). The MATLAB program is used first to test the Arizona test bed with a low level of energy storage to study how the storage power limit effects several optimization out-puts such as the system wide operating costs. Very high levels of energy storage are then added to see how high level energy storage affects peak shaving, load factor, and other system applications. Finally, various constraint relaxations are made to analyze why the applications tested eventually approach a constant value. This research illustrates the use of energy storage which helps minimize the system wide generator operating cost by "shaving" energy off of the peak demand.
ContributorsRuggiero, John (Author) / Heydt, Gerald T (Thesis advisor) / Datta, Rajib (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Current policies subsidizing or accelerating deployment of photovoltaics (PV) are typically motivated by claims of environmental benefit, such as the reduction of CO2 emissions generated by the fossil-fuel fired power plants that PV is intended to displace. Existing practice is to assess these environmental benefits on a net life-cycle basis,

Current policies subsidizing or accelerating deployment of photovoltaics (PV) are typically motivated by claims of environmental benefit, such as the reduction of CO2 emissions generated by the fossil-fuel fired power plants that PV is intended to displace. Existing practice is to assess these environmental benefits on a net life-cycle basis, where CO2 benefits occurring during use of the PV panels is found to exceed emissions generated during the PV manufacturing phase including materials extraction and manufacture of the PV panels prior to installation. However, this approach neglects to recognize that the environmental costs of CO2 release during manufacture are incurred early, while environmental benefits accrue later. Thus, where specific policy targets suggest meeting CO2 reduction targets established by a certain date, rapid PV deployment may have counter-intuitive, albeit temporary, undesired consequences. Thus, on a cumulative radiative forcing (CRF) basis, the environmental improvements attributable to PV might be realized much later than is currently understood. This phenomenon is particularly acute when PV manufacture occurs in areas using CO2 intensive energy sources (e.g., coal), but deployment occurs in areas with less CO2 intensive electricity sources (e.g., hydro). This thesis builds a dynamic Cumulative Radiative Forcing (CRF) model to examine the inter-temporal warming impacts of PV deployments in three locations: California, Wyoming and Arizona. The model includes the following factors that impact CRF: PV deployment rate, choice of PV technology, pace of PV technology improvements, and CO2 intensity in the electricity mix at manufacturing and deployment locations. Wyoming and California show the highest and lowest CRF benefits as they have the most and least CO2 intensive grids, respectively. CRF payback times are longer than CO2 payback times in all cases. Thin film, CdTe PV technologies have the lowest manufacturing CO2 emissions and therefore the shortest CRF payback times. This model can inform policies intended to fulfill time-sensitive CO2 mitigation goals while minimizing short term radiative forcing.
ContributorsTriplican Ravikumar, Dwarakanath (Author) / Seager, Thomas P (Thesis advisor) / Fraser, Matthew P (Thesis advisor) / Chester, Mikhail V (Committee member) / Sinha, Parikhit (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Recent trends in the electric power industry have led to more attention to optimal operation of power transformers. In a deregulated environment, optimal operation means minimizing the maintenance and extending the life of this critical and costly equipment for the purpose of maximizing profits. Optimal utilization of a transformer can

Recent trends in the electric power industry have led to more attention to optimal operation of power transformers. In a deregulated environment, optimal operation means minimizing the maintenance and extending the life of this critical and costly equipment for the purpose of maximizing profits. Optimal utilization of a transformer can be achieved through the use of dynamic loading. A benefit of dynamic loading is that it allows better utilization of the transformer capacity, thus increasing the flexibility and reliability of the power system. This document presents the progress on a software application which can estimate the maximum time-varying loading capability of transformers. This information can be used to load devices closer to their limits without exceeding the manufacturer specified operating limits. The maximally efficient dynamic loading of transformers requires a model that can accurately predict both top-oil temperatures (TOTs) and hottest-spot temperatures (HSTs). In the previous work, two kinds of thermal TOT and HST models have been studied and used in the application: the IEEE TOT/HST models and the ASU TOT/HST models. And, several metrics have been applied to evaluate the model acceptability and determine the most appropriate models for using in the dynamic loading calculations. In this work, an investigation to improve the existing transformer thermal models performance is presented. Some factors that may affect the model performance such as improper fan status and the error caused by the poor performance of IEEE models are discussed. Additional methods to determine the reliability of transformer thermal models using metrics such as time constant and the model parameters are also provided. A new production grade application for real-time dynamic loading operating purpose is introduced. This application is developed by using an existing planning application, TTeMP, as a start point, which is designed for the dispatchers and load specialists. To overcome the limitations of TTeMP, the new application can perform dynamic loading under emergency conditions, such as loss-of transformer loading. It also has the capability to determine the emergency rating of the transformers for a real-time estimation.
ContributorsZhang, Ming (Author) / Tylavsky, Daniel J (Thesis advisor) / Ayyanar, Raja (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
According to the U.S. Energy Information Administration, commercial buildings represent about 40% of the United State's energy consumption of which office buildings consume a major portion. Gauging the extent to which an individual building consumes energy in excess of its peers is the first step in initiating energy efficiency improvement.

According to the U.S. Energy Information Administration, commercial buildings represent about 40% of the United State's energy consumption of which office buildings consume a major portion. Gauging the extent to which an individual building consumes energy in excess of its peers is the first step in initiating energy efficiency improvement. Energy Benchmarking offers initial building energy performance assessment without rigorous evaluation. Energy benchmarking tools based on the Commercial Buildings Energy Consumption Survey (CBECS) database are investigated in this thesis. This study proposes a new benchmarking methodology based on decision trees, where a relationship between the energy use intensities (EUI) and building parameters (continuous and categorical) is developed for different building types. This methodology was applied to medium office and school building types contained in the CBECS database. The Random Forest technique was used to find the most influential parameters that impact building energy use intensities. Subsequently, correlations which were significant were identified between EUIs and CBECS variables. Other than floor area, some of the important variables were number of workers, location, number of PCs and main cooling equipment. The coefficient of variation was used to evaluate the effectiveness of the new model. The customization technique proposed in this thesis was compared with another benchmarking model that is widely used by building owners and designers namely, the ENERGY STAR's Portfolio Manager. This tool relies on the standard Linear Regression methods which is only able to handle continuous variables. The model proposed uses data mining technique and was found to perform slightly better than the Portfolio Manager. The broader impacts of the new benchmarking methodology proposed is that it allows for identifying important categorical variables, and then incorporating them in a local, as against a global, model framework for EUI pertinent to the building type. The ability to identify and rank the important variables is of great importance in practical implementation of the benchmarking tools which rely on query-based building and HVAC variable filters specified by the user.
ContributorsKaskhedikar, Apoorva Prakash (Author) / Reddy, T. Agami (Thesis advisor) / Bryan, Harvey (Committee member) / Runger, George C. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The smart grid initiative is the impetus behind changes that are expected to culminate into an enhanced distribution system with the communication and control infrastructure to support advanced distribution system applications and resources such as distributed generation, energy storage systems, and price responsive loads. This research proposes a distribution-class analog

The smart grid initiative is the impetus behind changes that are expected to culminate into an enhanced distribution system with the communication and control infrastructure to support advanced distribution system applications and resources such as distributed generation, energy storage systems, and price responsive loads. This research proposes a distribution-class analog of the transmission LMP (DLMP) as an enabler of the advanced applications of the enhanced distribution system. The DLMP is envisioned as a control signal that can incentivize distribution system resources to behave optimally in a manner that benefits economic efficiency and system reliability and that can optimally couple the transmission and the distribution systems. The DLMP is calculated from a two-stage optimization problem; a transmission system OPF and a distribution system OPF. An iterative framework that ensures accurate representation of the distribution system's price sensitive resources for the transmission system problem and vice versa is developed and its convergence problem is discussed. As part of the DLMP calculation framework, a DCOPF formulation that endogenously captures the effect of real power losses is discussed. The formulation uses piecewise linear functions to approximate losses. This thesis explores, with theoretical proofs, the breakdown of the loss approximation technique when non-positive DLMPs/LMPs occur and discusses a mixed integer linear programming formulation that corrects the breakdown. The DLMP is numerically illustrated in traditional and enhanced distribution systems and its superiority to contemporary pricing mechanisms is demonstrated using price responsive loads. Results show that the impact of the inaccuracy of contemporary pricing schemes becomes significant as flexible resources increase. At high elasticity, aggregate load consumption deviated from the optimal consumption by up to about 45 percent when using a flat or time-of-use rate. Individual load consumption deviated by up to 25 percent when using a real-time price. The superiority of the DLMP is more pronounced when important distribution network conditions are not reflected by contemporary prices. The individual load consumption incentivized by the real-time price deviated by up to 90 percent from the optimal consumption in a congested distribution network. While the DLMP internalizes congestion management, the consumption incentivized by the real-time price caused overloads.
ContributorsAkinbode, Oluwaseyi Wemimo (Author) / Hedman, Kory W (Thesis advisor) / Heydt, Gerald T (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The Solid State Transformer (SST) is an essential component in the FREEDM system. This research focuses on the modeling of the SST and the controller hardware in the loop (CHIL) implementation of the SST for the support of the FREEDM system demonstration. The energy based control strategy for a three-stage

The Solid State Transformer (SST) is an essential component in the FREEDM system. This research focuses on the modeling of the SST and the controller hardware in the loop (CHIL) implementation of the SST for the support of the FREEDM system demonstration. The energy based control strategy for a three-stage SST is analyzed and applied. A simplified average model of the three-stage SST that is suitable for simulation in real time digital simulator (RTDS) has been developed in this study. The model is also useful for general time-domain power system analysis and simulation. The proposed simplified av-erage model has been validated in MATLAB and PLECS. The accuracy of the model has been verified through comparison with the cycle-by-cycle average (CCA) model and de-tailed switching model. These models are also implemented in PSCAD, and a special strategy to implement the phase shift modulation has been proposed to enable the switching model simulation in PSCAD. The implementation of the CHIL test environment of the SST in RTDS is described in this report. The parameter setup of the model has been discussed in detail. One of the dif-ficulties is the choice of the damping factor, which is revealed in this paper. Also the grounding of the system has large impact on the RTDS simulation. Another problem is that the performance of the system is highly dependent on the switch parameters such as voltage and current ratings. Finally, the functionalities of the SST have been realized on the platform. The distributed energy storage interface power injection and reverse power flow have been validated. Some limitations are noticed and discussed through the simulation on RTDS.
ContributorsJiang, Youyuan (Author) / Ayyanar, Raja (Thesis advisor) / Holbert, Keith E. (Committee member) / Chowdhury, Srabanti (Committee member) / Arizona State University (Publisher)
Created2014
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Description
This study evaluates two photovoltaic (PV) power plants based on electrical performance measurements, diode checks, visual inspections and infrared scanning. The purpose of this study is to measure degradation rates of performance parameters (Pmax, Isc, Voc, Vmax, Imax and FF) and to identify the failure modes in a "hot-dry desert"

This study evaluates two photovoltaic (PV) power plants based on electrical performance measurements, diode checks, visual inspections and infrared scanning. The purpose of this study is to measure degradation rates of performance parameters (Pmax, Isc, Voc, Vmax, Imax and FF) and to identify the failure modes in a "hot-dry desert" climatic condition along with quantitative determination of safety failure rates and reliability failure rates. The data obtained from this study can be used by module manufacturers in determining the warranty limits of their modules and also by banks, investors, project developers and users in determining appropriate financing or decommissioning models. In addition, the data obtained in this study will be helpful in selecting appropriate accelerated stress tests which would replicate the field failures for the new modules and would predict the lifetime for new PV modules. The study was conducted at two, single axis tracking monocrystalline silicon (c-Si) power plants, Site 3 and Site 4c of Salt River Project (SRP). The Site 3 power plant is located in Glendale, Arizona and the Site 4c power plant is located in Mesa, Arizona both considered a "hot-dry" field condition. The Site 3 power plant has 2,352 modules (named as Model-G) which was rated at 250 kW DC output. The mean and median degradation of these 12 years old modules are 0.95%/year and 0.96%/year, respectively. The major cause of degradation found in Site 3 is due to high series resistance (potentially due to solder-bond thermo-mechanical fatigue) and the failure mode is ribbon-ribbon solder bond failure/breakage. The Site 4c power plant has 1,280 modules (named as Model-H) which provide 243 kW DC output. The mean and median degradation of these 4 years old modules are 0.96%/year and 1%/year, respectively. At Site 4c, practically, none of the module failures are observed. The average soiling loss is 6.9% in Site 3 and 5.5% in Site 4c. The difference in soiling level is attributed to the rural and urban surroundings of these two power plants.
ContributorsMallineni, Jaya Krishna (Author) / Govindasamy, Tamizhmani (Thesis advisor) / Devarajan, Srinivasan (Committee member) / Narciso, Macia (Committee member) / Arizona State University (Publisher)
Created2013
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Description
A robust, fast and accurate protection system based on pilot protection concept was developed previously and a few alterations in that algorithm were made to make it faster and more reliable and then was applied to smart distribution grids to verify the results for it. The new 10 sample window

A robust, fast and accurate protection system based on pilot protection concept was developed previously and a few alterations in that algorithm were made to make it faster and more reliable and then was applied to smart distribution grids to verify the results for it. The new 10 sample window method was adapted into the pilot protection program and its performance for the test bed system operation was tabulated. Following that the system comparison between the hardware results for the same algorithm and the simulation results were compared. The development of the dual slope percentage differential method, its comparison with the 10 sample average window pilot protection system and the effects of CT saturation on the pilot protection system are also shown in this thesis. The implementation of the 10 sample average window pilot protection system is done to multiple distribution grids like Green Hub v4.3, IEEE 34, LSSS loop and modified LSSS loop. Case studies of these multi-terminal model are presented, and the results are also shown in this thesis. The result obtained shows that the new algorithm for the previously proposed protection system successfully identifies fault on the test bed and the results for both hardware and software simulations match and the response time is approximately less than quarter of a cycle which is fast as compared to the present commercial protection system and satisfies the FREEDM system requirement.
ContributorsIyengar, Varun (Author) / Karady, George G. (Thesis advisor) / Ayyanar, Raja (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2014
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Description
GaAs-based solar cells have attracted much interest because of their high conversion efficiencies of ~28% under one sun illumination. The main carrier recombination mechanisms in the GaAs-based solar cells are surface recombination, radiative recombination and non-radiative recombination. Photon recycling reduces the effect of radiative recombination and is an approach to

GaAs-based solar cells have attracted much interest because of their high conversion efficiencies of ~28% under one sun illumination. The main carrier recombination mechanisms in the GaAs-based solar cells are surface recombination, radiative recombination and non-radiative recombination. Photon recycling reduces the effect of radiative recombination and is an approach to obtain the device performance described by detailed balance theory. The photon recycling model has been developed and was applied to investigate the loss mechanisms in the state-of-the-art GaAs-based solar cell structures using PC1D software. A standard fabrication process of the GaAs-based solar cells is as follows: wafer preparation, individual cell isolation by mesa, n- and p-type metallization, rapid thermal annealing (RTA), cap layer etching, and anti-reflection coating (ARC). The growth rate for GaAs-based materials is one of critical factors to determine the cost for the growth of GaAs-based solar cells. The cost for fabricating GaAs-based solar cells can be reduced if the growth rate is increased without degrading the crystalline quality. The solar cell wafers grown at different growth rates of 14 μm/hour and 55 μm/hour were discussed in this work. The structural properties of the wafers were characterized by X-ray diffraction (XRD) to identify the crystalline quality, and then the as-grown wafers were fabricated into solar cell devices under the same process conditions. The optical and electrical properties such as surface reflection, external quantum efficiency (EQE), dark I-V, Suns-Voc, and illuminated I-V under one sun using a solar simulator were measured to compare the performances of the solar cells with different growth rates. Some simulations in PC1D have been demonstrated to investigate the reasons of the different device performances between fast growth and slow growth structures. A further analysis of the minority carrier lifetime is needed to investigate into the difference in device performances.
ContributorsZhang, Chaomin (Author) / Honsberg, Christiana (Thesis advisor) / Goodnick, Stephen (Committee member) / Faleev, Nikolai (Committee member) / Arizona State University (Publisher)
Created2014