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
Under the framework of intelligent management of power grids by leveraging advanced information, communication and control technologies, a primary objective of this study is to develop novel data mining and data processing schemes for several critical applications that can enhance the reliability of power systems. Specifically, this study is broadly

Under the framework of intelligent management of power grids by leveraging advanced information, communication and control technologies, a primary objective of this study is to develop novel data mining and data processing schemes for several critical applications that can enhance the reliability of power systems. Specifically, this study is broadly organized into the following two parts: I) spatio-temporal wind power analysis for wind generation forecast and integration, and II) data mining and information fusion of synchrophasor measurements toward secure power grids. Part I is centered around wind power generation forecast and integration. First, a spatio-temporal analysis approach for short-term wind farm generation forecasting is proposed. Specifically, using extensive measurement data from an actual wind farm, the probability distribution and the level crossing rate of wind farm generation are characterized using tools from graphical learning and time-series analysis. Built on these spatial and temporal characterizations, finite state Markov chain models are developed, and a point forecast of wind farm generation is derived using the Markov chains. Then, multi-timescale scheduling and dispatch with stochastic wind generation and opportunistic demand response is investigated. Part II focuses on incorporating the emerging synchrophasor technology into the security assessment and the post-disturbance fault diagnosis of power systems. First, a data-mining framework is developed for on-line dynamic security assessment by using adaptive ensemble decision tree learning of real-time synchrophasor measurements. Under this framework, novel on-line dynamic security assessment schemes are devised, aiming to handle various factors (including variations of operating conditions, forced system topology change, and loss of critical synchrophasor measurements) that can have significant impact on the performance of conventional data-mining based on-line DSA schemes. Then, in the context of post-disturbance analysis, fault detection and localization of line outage is investigated using a dependency graph approach. It is shown that a dependency graph for voltage phase angles can be built according to the interconnection structure of power system, and line outage events can be detected and localized through networked data fusion of the synchrophasor measurements collected from multiple locations of power grids. Along a more practical avenue, a decentralized networked data fusion scheme is proposed for efficient fault detection and localization.
ContributorsHe, Miao (Author) / Zhang, Junshan (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Hedman, Kory (Committee member) / Si, Jennie (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This thesis addresses the design and control of three phase inverters. Such inverters are

used to produce three-phase sinusoidal voltages and currents from a DC source. They

are critical for injecting power from renewable energy sources into the grid. This is

especially true since many of these sources of energy are DC sources

This thesis addresses the design and control of three phase inverters. Such inverters are

used to produce three-phase sinusoidal voltages and currents from a DC source. They

are critical for injecting power from renewable energy sources into the grid. This is

especially true since many of these sources of energy are DC sources (e.g. solar

photovoltaic) or need to be stored in DC batteries because they are intermittent (e.g. wind

and solar). Two classes of inverters are examined in this thesis. A control-centric design

procedure is presented for each class. The first class of inverters is simple in that they

consist of three decoupled subsystems. Such inverters are characterized by no mutual

inductance between the three phases. As such, no multivariable coupling is present and

decentralized single-input single-output (SISO) control theory suffices to generate

acceptable control designs. For this class of inverters several families of controllers are

addressed in order to examine command following as well as input disturbance and noise

attenuation specifications. The goal here is to illuminate fundamental tradeoffs. Such

tradeoffs include an improvement in the in-band command following and output

disturbance attenuation versus a deterioration in out-of-band noise attenuation.

A fundamental deficiency associated with such inverters is their large size. This can be

remedied by designing a smaller core. This naturally leads to the second class of inverters

considered in this work. These inverters are characterized by significant mutual

inductances and multivariable coupling. As such, SISO control theory is generally not

adequate and multiple-input multiple-output (MIMO) theory becomes essential for

controlling these inverters.
ContributorsSarkar, Aratrik (Author) / Rodriguez, Armando A. (Thesis advisor) / Si, Jennie (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2015