ASU Electronic Theses and Dissertations
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.
and satisfactory dynamic performance. The integration of renewable resources in general, and photovoltaic resources in particular into the grid has created new engineering issues. A particularly problematic operating scenario occurs when conventional generation is operated at a low level but photovoltaic solar generation is at a high level. Significant solar photovoltaic penetration as a renewable resource is becoming a reality in some electric power systems. In this thesis, special attention is given to photovoltaic generation in an actual electric power system: increased solar penetration has resulted in significant strides towards meeting renewable portfolio standards. The impact of solar generation integration on power system dynamics is studied and evaluated.
This thesis presents the impact of high solar penetration resulting in potentially
problematic low system damping operating conditions. This is the case because the power system damping provided by conventional generation may be insufficient due to reduced system inertia and change in power flow patterns affecting synchronizing and damping capability in the AC system. This typically occurs because conventional generators are rescheduled or shut down to allow for the increased solar production. This problematic case may occur at any time of the year but during the springtime months of March-May, when the system load is low and the ambient temperature is relatively low, there is the potential that over voltages may occur in the high voltage transmission system. Also, reduced damping in system response to disturbances may occur. An actual case study is considered in which real operating system data are used. Solutions to low damping cases are discussed and a solution based on the retuning of a conventional power system stabilizer is given in the thesis.
This work puts forth a Hybrid Electromagnetic Transient-Transient Stability simulation method implemented using MATLAB and Simulink, to study power electronic based power systems. Hybrid Simulation enables detailed, accurate modeling, along with fast, efficient simulation, on account of the Electromagnetic Transient (EMT) and Transient Stability (TS) simulations respectively. A critical component of hybrid simulation is the interaction between the EMT and TS simulators, established through a well-defined interface technique, which has been explored in detail.
This research focuses on the boundary conditions and interaction between the two simulation models for optimum accuracy and computational efficiency.
A case study has been carried out employing the proposed hybrid simulation method. The test case used is the IEEE 9-bus system, modified to integrate it with a solar PV plant. The validation of the hybrid model with the benchmark full EMT model, along with the analysis of the accuracy and efficiency, has been performed. The steady-state and transient analysis results demonstrate that the performance of the hybrid simulation method is competent. The hybrid simulation technique suitably captures accuracy of EMT simulation and efficiency of TS simulation, therefore adequately representing the behavior of power systems with high penetration of converter interfaced generation.
In this thesis, we improve the intent classification and slot filling in the virtual voice agents by automatic data augmentation. Spoken Language Understanding systems face the issue of data sparsity. The reason behind this is that it is hard for a human-created training sample to represent all the patterns in the language. Due to the lack of relevant data, deep learning methods are unable to generalize the Spoken Language Understanding model. This thesis expounds a way to overcome the issue of data sparsity in deep learning approaches on Spoken Language Understanding tasks. Here we have described the limitations in the current intent classifiers and how the proposed algorithm uses existing knowledge bases to overcome those limitations. The method helps in creating a more robust intent classifier and slot filling system.
In the process of ground grid optimization, the touch potential and the step potential are introduced as nonlinear constraints in a two layer soil model whose parameters are set by the user. To obtain an accurate expression for these nonlinear constraints, the ground grid is discretized by using a ground-conductor (and ground-rod) segmentation method that breaks each conductor into reasonable-size segments. The leakage current on each segment and the ground potential rise (GPR) are calculated by solving a matrix equation involving the mutual resistance matrix. After the leakage current on each segment is obtained, the touch potential and the step potential can be calculated using the superposition principle.
A genetic algorithm is used in the optimization of the ground grid and a pattern search algorithm is used to accelerate the convergence. To verify the accuracy of the application, the touch potential and the step potential calculated by the MATLAB application are compared with those calculated by the commercialized grounding system analysis software, WinIGS.
The user's manual of the optimal ground grid application is also presented in this work.