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Description
At present, almost 70% of the electric energy in the United States is produced utilizing fossil fuels. Combustion of fossil fuels contributes CO2 to the atmosphere, potentially exacerbating the impact on global warming. To make the electric power system (EPS) more sustainable for the future, there has been an emphasis

At present, almost 70% of the electric energy in the United States is produced utilizing fossil fuels. Combustion of fossil fuels contributes CO2 to the atmosphere, potentially exacerbating the impact on global warming. To make the electric power system (EPS) more sustainable for the future, there has been an emphasis on scaling up generation of electric energy from wind and solar resources. These resources are renewable in nature and have pollution free operation. Various states in the US have set up different goals for achieving certain amount of electrical energy to be produced from renewable resources. The Southwestern region of the United States receives significant solar radiation throughout the year. High solar radiation makes concentrated solar power and solar PV the most suitable means of renewable energy production in this region. However, the majority of the projects that are presently being developed are either residential or utility owned solar PV plants. This research explores the impact of significant PV penetration on the steady state voltage profile of the electric power transmission system. This study also identifies the impact of PV penetration on the dynamic response of the transmission system such as rotor angle stability, frequency response and voltage response after a contingency. The light load case of spring 2010 and the peak load case of summer 2018 have been considered for analyzing the impact of PV. If the impact is found to be detrimental to the normal operation of the EPS, mitigation measures have been devised and presented in the thesis. Commercially available software tools/packages such as PSLF, PSS/E, DSA Tools have been used to analyze the power network and validate the results.
ContributorsPrakash, Nitin (Author) / Heydt, Gerald T. (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The increasing popularity of Twitter renders improved trustworthiness and relevance assessment of tweets much more important for search. However, given the limitations on the size of tweets, it is hard to extract measures for ranking from the tweet's content alone. I propose a method of ranking tweets by generating a

The increasing popularity of Twitter renders improved trustworthiness and relevance assessment of tweets much more important for search. However, given the limitations on the size of tweets, it is hard to extract measures for ranking from the tweet's content alone. I propose a method of ranking tweets by generating a reputation score for each tweet that is based not just on content, but also additional information from the Twitter ecosystem that consists of users, tweets, and the web pages that tweets link to. This information is obtained by modeling the Twitter ecosystem as a three-layer graph. The reputation score is used to power two novel methods of ranking tweets by propagating the reputation over an agreement graph based on tweets' content similarity. Additionally, I show how the agreement graph helps counter tweet spam. An evaluation of my method on 16~million tweets from the TREC 2011 Microblog Dataset shows that it doubles the precision over baseline Twitter Search and achieves higher precision than current state of the art method. I present a detailed internal empirical evaluation of RAProp in comparison to several alternative approaches proposed by me, as well as external evaluation in comparison to the current state of the art method.
ContributorsRavikumar, Srijith (Author) / Kambhampati, Subbarao (Thesis advisor) / Davulcu, Hasan (Committee member) / Liu, Huan (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
Traditional approaches to modeling microgrids include the behavior of each inverter operating in a particular network configuration and at a particular operating point. Such models quickly become computationally intensive for large systems. Similarly, traditional approaches to control do not use advanced methodologies and suffer from poor performance and limited operating

Traditional approaches to modeling microgrids include the behavior of each inverter operating in a particular network configuration and at a particular operating point. Such models quickly become computationally intensive for large systems. Similarly, traditional approaches to control do not use advanced methodologies and suffer from poor performance and limited operating range. In this document a linear model is derived for an inverter connected to the Thevenin equivalent of a microgrid. This model is then compared to a nonlinear simulation model and analyzed using the open and closed loop systems in both the time and frequency domains. The modeling error is quantified with emphasis on its use for controller design purposes. Control design examples are given using a Glover McFarlane controller, gain sched- uled Glover McFarlane controller, and bumpless transfer controller which are compared to the standard droop control approach. These examples serve as a guide to illustrate the use of multi-variable modeling techniques in the context of robust controller design and show that gain scheduled MIMO control techniques can extend the operating range of a microgrid. A hardware implementation is used to compare constant gain droop controllers with Glover McFarlane controllers and shows a clear advantage of the Glover McFarlane approach.
ContributorsSteenis, Joel (Author) / Ayyanar, Raja (Thesis advisor) / Mittelmann, Hans (Committee member) / Tsakalis, Konstantinos (Committee member) / Tylavsky, Daniel (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Today, more and more substations are created and reconstructed to satisfy the growing electricity demands for both industry and residence. It is always a big concern that the designed substation must guarantee the safety of persons who are in the area of the substation. As a result, the safety metrics

Today, more and more substations are created and reconstructed to satisfy the growing electricity demands for both industry and residence. It is always a big concern that the designed substation must guarantee the safety of persons who are in the area of the substation. As a result, the safety metrics (touch voltage, step voltage and grounding resistance), which should be considered at worst case, are supposed to be under the allowable values. To improve the accuracy of calculating safety metrics, at first, it is necessary to have a relatively accurate soil model instead of uniform soil model. Hence, the two-layer soil model is employed in this thesis. The new approximate finite equations with soil parameters (upper-layer resistivity, lower-layer resistivity and upper-layer thickness) are used, which are developed based on traditional infinite expression. The weighted- least-squares regression with new bad data detection method (adaptive weighted function) is applied to fit the measurement data from the Wenner-method. At the end, a developed error analysis method is used to obtain the error (variance) of each parameter. Once the soil parameters are obtained, it is possible to use a developed complex images method to calculate the mutual (self) resistance, which is the induced voltage of a conductor/rod by unit current form another conductor/rod. The basis of the calculation is Green's function between two point current sources, thus, it can be expanded to either the functions between point and line current sources, or the functions between line and line current sources. Finally, the grounding system optimization is implemented with developed three-step optimization strategy using MATLAB solvers. The first step is using "fmincon" solver to optimize the cost function with differentiable constraint equations from IEEE standard. The result of the first step is set as the initial values to the second step, which is using "patternsearch" solver, thus, the non-differentiable and more accurate constraint calculation can be employed. The final step is a backup step using "ga" solver, which is more robust but lager time cost.
ContributorsWu, Xuan (Author) / Tylavsky, Daniel (Thesis advisor) / Undrill, John (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Automating aspects of biocuration through biomedical information extraction could significantly impact biomedical research by enabling greater biocuration throughput and improving the feasibility of a wider scope. An important step in biomedical information extraction systems is named entity recognition (NER), where mentions of entities such as proteins and diseases are located

Automating aspects of biocuration through biomedical information extraction could significantly impact biomedical research by enabling greater biocuration throughput and improving the feasibility of a wider scope. An important step in biomedical information extraction systems is named entity recognition (NER), where mentions of entities such as proteins and diseases are located within natural-language text and their semantic type is determined. This step is critical for later tasks in an information extraction pipeline, including normalization and relationship extraction. BANNER is a benchmark biomedical NER system using linear-chain conditional random fields and the rich feature set approach. A case study with BANNER locating genes and proteins in biomedical literature is described. The first corpus for disease NER adequate for use as training data is introduced, and employed in a case study of disease NER. The first corpus locating adverse drug reactions (ADRs) in user posts to a health-related social website is also described, and a system to locate and identify ADRs in social media text is created and evaluated. The rich feature set approach to creating NER feature sets is argued to be subject to diminishing returns, implying that additional improvements may require more sophisticated methods for creating the feature set. This motivates the first application of multivariate feature selection with filters and false discovery rate analysis to biomedical NER, resulting in a feature set at least 3 orders of magnitude smaller than the set created by the rich feature set approach. Finally, two novel approaches to NER by modeling the semantics of token sequences are introduced. The first method focuses on the sequence content by using language models to determine whether a sequence resembles entries in a lexicon of entity names or text from an unlabeled corpus more closely. The second method models the distributional semantics of token sequences, determining the similarity between a potential mention and the token sequences from the training data by analyzing the contexts where each sequence appears in a large unlabeled corpus. The second method is shown to improve the performance of BANNER on multiple data sets.
ContributorsLeaman, James Robert (Author) / Gonzalez, Graciela (Thesis advisor) / Baral, Chitta (Thesis advisor) / Cohen, Kevin B (Committee member) / Liu, Huan (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This thesis concerns the flashover issue of the substation insulators operating in a polluted environment. The outdoor insulation equipment used in the power delivery infrastructure encounter different types of pollutants due to varied environmental conditions. Various methods have been developed by manufacturers and researchers to mitigate the flashover problem. The

This thesis concerns the flashover issue of the substation insulators operating in a polluted environment. The outdoor insulation equipment used in the power delivery infrastructure encounter different types of pollutants due to varied environmental conditions. Various methods have been developed by manufacturers and researchers to mitigate the flashover problem. The application of Room Temperature Vulcanized (RTV) silicone rubber is one such favorable method as it can be applied over the already installed units. Field experience has already showed that the RTV silicone rubber coated insulators have a lower flashover probability than the uncoated insulators. The scope of this research is to quantify the improvement in the flashover performance. Artificial contamination tests were carried on station post insulators for assessing their performance. A factorial experiment design was used to model the flashover performance. The formulation included the severity of contamination and leakage distance of the insulator samples. Regression analysis was used to develop a mathematical model from the data obtained from the experiments. The main conclusion drawn from the study is that the RTV coated insulators withstood much higher levels of contamination even when the coating had lost its hydrophobicity. This improvement in flashover performance was found to be in the range of 20-40%. A much better flashover performance was observed when the coating recovered its hydrophobicity. It was also seen that the adhesion of coating was excellent even after many tests which involved substantial discharge activity.
ContributorsGholap, Vipul (Author) / Gorur, Ravi S (Thesis advisor) / Karady, George G. (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
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Description
As renewable energy becomes more prevalent in transmission and distribution systems, it is vital to understand the uncertainty and variability that accompany these resources. Microgrids have the potential to mitigate the effects of resource uncertainty. With the ability to exist in either an islanded mode or maintain connections with the

As renewable energy becomes more prevalent in transmission and distribution systems, it is vital to understand the uncertainty and variability that accompany these resources. Microgrids have the potential to mitigate the effects of resource uncertainty. With the ability to exist in either an islanded mode or maintain connections with the main-grid, a microgrid can increase reliability, defer T&D; infrastructure and effectively utilize demand response. This study presents a co-optimization framework for a microgrid with solar photovoltaic generation, emergency generation, and transmission switching. Today unit commitment models ensure reliability with deterministic criteria, which are either insufficient to ensure reliability or can degrade economic efficiency for a microgrid that uses a large penetration of variable renewable resources. A stochastic mixed integer linear program for day-ahead unit commitment is proposed to account for uncertainty inherent in PV generation. The model incorporates the ability to trade energy and ancillary services with the main-grid, including the designation of firm and non-firm imports, which captures the ability to allow for reserve sharing between the two systems. In order to manage the computational complexities, a Benders' decomposition approach is utilized. The commitment schedule was validated with solar scenario analysis, i.e., Monte-Carlo simulations are conducted to test the proposed dispatch solution. For this test case, there were few deviations to power imports, 0.007% of solar was curtailed, no load shedding occurred in the main-grid, and 1.70% load shedding occurred in the microgrid.
ContributorsHytowitz, Robin Broder (Author) / Hedman, Kory W (Thesis advisor) / Heydt, Gerald T (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This thesis presents a new technique to develop an air-conditioner (A/C) compressor single phase induction motor model for use in an electro-magnetic transient program (EMTP) simulation tool. The method developed also has the capability to represent multiple units of the component in a specific three-phase distribution feeder and investigate the

This thesis presents a new technique to develop an air-conditioner (A/C) compressor single phase induction motor model for use in an electro-magnetic transient program (EMTP) simulation tool. The method developed also has the capability to represent multiple units of the component in a specific three-phase distribution feeder and investigate the phenomenon of fault-induced delayed voltage recovery (FIDVR) and the cause of motor stalling. The system of differential equations representing the single phase induction motor model is developed and formulated. Implicit backward Euler method is applied to numerically integrate the stator currents that are to be drawn from the electric network. The angular position dependency of the rotor shaft is retained in the inductance matrix associated with the model to accurately capture the dynamics of the motor loads. The equivalent circuit of the new model is interfaced with the electric network in the EMTP. The dynamic response of the motor when subjected to faults at different points on voltage waveform has been studied using the EMTP simulator. The mechanism and the impacts of motor stalling need to be explored with multiple units of the detailed model connected to a realistic three-phase distribution system. The model developed can be utilized to assess and improve the product design of compressor motors by air-conditioner manufacturers. Another critical application of the model would be to examine the impacts of asymmetric transmission faults on distribution systems to investigate and develop mitigation measures for the FIDVR problem.
ContributorsLiu, Yuan (Author) / Vittal, Vijay (Thesis advisor) / Undrill, John (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Battery energy storage has shown a lot of potential in the recent past to be effective in various grid services due to its near instantaneous ramp rates and modularity. This thesis aims to determine the commercial viability of customer premises and substation sited battery energy storage systems. Five different types

Battery energy storage has shown a lot of potential in the recent past to be effective in various grid services due to its near instantaneous ramp rates and modularity. This thesis aims to determine the commercial viability of customer premises and substation sited battery energy storage systems. Five different types of services have been analyzed considering current market pricing of Lithium-ion batteries and power conditioning equipment. Energy Storage Valuation Tool 3.0 (Beta) has been used to exclusively determine the value of energy storage in the services analyzed. The results indicate that on the residential level, Lithium-ion battery energy storage may not be a cost beneficial option for retail tariff management or demand charge management as only 20-30% of the initial investment is recovered at the end of 15 year plant life. SRP's two retail Time-of-Use price plans E-21 and E-26 were analyzed in respect of their ability to increase returns from storage compared to those with flat pricing. It was observed that without a coupled PV component, E-21 was more suitable for customer premises energy storage, however, its revenue stream reduces with addition to PV. On the grid scale, however, with carefully chosen service hierarchy such as distribution investment deferral, spinning or balancing reserve support, the initial investment can be recovered to an extent of about 50-70%. The study done here is specific to Salt River Project inputs and data. Results for all the services analyzed are highly location specific and are only indicative of the overall viability and returns from them.
ContributorsNadkarni, Aditya (Author) / Karady, George G. (Thesis advisor) / Ayyanar, Raja (Committee member) / Hedman, Kory (Committee member) / Arizona State University (Publisher)
Created2013