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.
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- Creators: Tylavsky, Daniel J.
As more non-dispatchable renewable resources are integrated into the grid, it will become increasingly difficult to predict the transfer capabilities and the network congestion. At the same time, renewable resources require operators to acquire more operating reserves. With existing deterministic reserve requirements unable to ensure optimal reserve locations, the importance of reserve location and reserve deliverability will increase. While stochastic programming can be used to determine reserve by explicitly modelling uncertainties, there are still scalability as well as pricing issues. Therefore, new methods to improve existing deterministic reserve requirements are desired.
One key barrier of improving existing deterministic reserve requirements is its potential market impacts. A metric, quality of service, is proposed in this thesis to evaluate the price signal and market impacts of proposed hourly reserve zones.
Three main goals of this thesis are: 1) to develop a theoretical and mathematical model to better locate reserve while maintaining the deterministic unit commitment and economic dispatch structure, especially with the consideration of renewables, 2) to develop a market settlement scheme of proposed dynamic reserve policies such that the market efficiency is improved, 3) to evaluate the market impacts and price signal of the proposed dynamic reserve policies.
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.