This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.

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Description
Due to restructuring and open access to the transmission system, modern electric power systems are being operated closer to their operational limits. Additionally, the secure operational limits of modern power systems have become increasingly difficult to evaluate as the scale of the network and the number of transactions between utilities

Due to restructuring and open access to the transmission system, modern electric power systems are being operated closer to their operational limits. Additionally, the secure operational limits of modern power systems have become increasingly difficult to evaluate as the scale of the network and the number of transactions between utilities increase. To account for these challenges associated with the rapid expansion of electric power systems, dynamic equivalents have been widely applied for the purpose of reducing the computational effort of simulation-based transient security assessment. Dynamic equivalents are commonly developed using a coherency-based approach in which a retained area and an external area are first demarcated. Then the coherent generators in the external area are aggregated and replaced by equivalenced models, followed by network reduction and load aggregation. In this process, an improperly defined retained area can result in detrimental impacts on the effectiveness of the equivalents in preserving the dynamic characteristics of the original unreduced system. In this dissertation, a comprehensive approach has been proposed to determine an appropriate retained area boundary by including the critical generators in the external area that are tightly coupled with the initial retained area. Further-more, a systematic approach has also been investigated to efficiently predict the variation in generator slow coherency behavior when the system operating condition is subject to change. Based on this determination, the critical generators in the external area that are tightly coherent with the generators in the initial retained area are retained, resulting in a new retained area boundary. Finally, a novel hybrid dynamic equivalent, consisting of both a coherency-based equivalent and an artificial neural network (ANN)-based equivalent, has been proposed and analyzed. The ANN-based equivalent complements the coherency-based equivalent at all the retained area boundary buses, and it is designed to compensate for the discrepancy between the full system and the conventional coherency-based equivalent. The approaches developed have been validated on a large portion of the Western Electricity Coordinating Council (WECC) system and on a test case including a significant portion of the eastern interconnection.
ContributorsMa, Feng (Author) / Vittal, Vijay (Thesis advisor) / Tylavsky, Daniel (Committee member) / Heydt, Gerald (Committee member) / Si, Jennie (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2011
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Description
The Smart Grid initiative describes the collaborative effort to modernize the U.S. electric power infrastructure. Modernization efforts incorporate digital data and information technology to effectuate control, enhance reliability, encourage small customer sited distributed generation (DG), and better utilize assets. The Smart Grid environment is envisioned to include distributed generation, flexible

The Smart Grid initiative describes the collaborative effort to modernize the U.S. electric power infrastructure. Modernization efforts incorporate digital data and information technology to effectuate control, enhance reliability, encourage small customer sited distributed generation (DG), and better utilize assets. The Smart Grid environment is envisioned to include distributed generation, flexible and controllable loads, bidirectional communications using smart meters and other technologies. Sensory technology may be utilized as a tool that enhances operation including operation of the distribution system. Addressing this point, a distribution system state estimation algorithm is developed in this thesis. The state estimation algorithm developed here utilizes distribution system modeling techniques to calculate a vector of state variables for a given set of measurements. Measurements include active and reactive power flows, voltage and current magnitudes, phasor voltages with magnitude and angle information. The state estimator is envisioned as a tool embedded in distribution substation computers as part of distribution management systems (DMS); the estimator acts as a supervisory layer for a number of applications including automation (DA), energy management, control and switching. The distribution system state estimator is developed in full three-phase detail, and the effect of mutual coupling and single-phase laterals and loads on the solution is calculated. The network model comprises a full three-phase admittance matrix and a subset of equations that relates measurements to system states. Network equations and variables are represented in rectangular form. Thus a linear calculation procedure may be employed. When initialized to the vector of measured quantities and approximated non-metered load values, the calculation procedure is non-iterative. This dissertation presents background information used to develop the state estimation algorithm, considerations for distribution system modeling, and the formulation of the state estimator. Estimator performance for various power system test beds is investigated. Sample applications of the estimator to Smart Grid systems are presented. Applications include monitoring, enabling demand response (DR), voltage unbalance mitigation, and enhancing voltage control. Illustrations of these applications are shown. Also, examples of enhanced reliability and restoration using a sensory based automation infrastructure are shown.
ContributorsHaughton, Daniel Andrew (Author) / Heydt, Gerald T (Thesis advisor) / Vittal, Vijay (Committee member) / Ayyanar, Raja (Committee member) / Hedman, Kory W (Committee member) / Arizona State University (Publisher)
Created2012
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Description
The past decades have seen a significant shift in the expectations and requirements re-lated to power system analysis tools. Investigations into major power grid disturbances have suggested the need for more comprehensive assessment methods. Accordingly, sig-nificant research in recent years has focused on the development of better power system models

The past decades have seen a significant shift in the expectations and requirements re-lated to power system analysis tools. Investigations into major power grid disturbances have suggested the need for more comprehensive assessment methods. Accordingly, sig-nificant research in recent years has focused on the development of better power system models and efficient techniques for analyzing power system operability. The work done in this report focusses on two such topics

1. Analysis of load model parameter uncertainty and sensitivity based pa-rameter estimation for power system studies

2. A systematic approach to n-1-1 analysis for power system security as-sessment

To assess the effect of load model parameter uncertainty, a trajectory sensitivity based approach is proposed in this work. Trajectory sensitivity analysis provides a sys-tematic approach to study the impact of parameter uncertainty on power system re-sponse to disturbances. Furthermore, the non-smooth nature of the composite load model presents some additional challenges to sensitivity analysis in a realistic power system. Accordingly, the impact of the non-smooth nature of load models on the sensitivity analysis is addressed in this work. The study was performed using the Western Electrici-ty Coordinating Council (WECC) system model. To address the issue of load model pa-rameter estimation, a sensitivity based load model parameter estimation technique is presented in this work. A detailed discussion on utilizing sensitivities to improve the ac-curacy and efficiency of the parameter estimation process is also presented in this work.

Cascading outages can have a catastrophic impact on power systems. As such, the NERC transmission planning (TPL) standards requires utilities to plan for n¬-1-1 out-ages. However, such analyses can be computationally burdensome for any realistic pow-er system owing to the staggering number of possible n-1-1 contingencies. To address this problem, the report proposes a systematic approach to analyze n-1-1 contingencies in a computationally tractable manner for power system security assessment. The pro-posed approach addresses both static and dynamic security assessment. The proposed methods have been tested on the WECC system.
ContributorsMitra, Parag (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald T (Committee member) / Ayyanar, Raja (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2016