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.
- Wu, Teresa
- 1 Arizona State University
- 1 Hedman, Kory W
- 1 Li, Chao
- 1 Mirchandani, Pitu B
- 1 Zhang, Muhong
- 1 Public
- Operations research
- Unit commitment
- Electrical engineering
- 1 Energy markets
- 1 Operations reserch
- 1 Power system scheduling
- 1 Statistics
- Dwarf Galaxies as Laboratories of Protogalaxy Physics: Canonical Star Formation Laws at Low Metallicity
- Evolutionary Genetics of CORL Proteins
- Social Skills and Executive Functioning in Children with PCDH-19
- Deep Domain Fusion for Adaptive Image Classification
- Software Defined Pulse-Doppler Radar for Over-The-Air Applications: The Joint Radar-Communications Experiment
This dissertation carries out an inter-disciplinary research of operations research, statistics, power system engineering, and economics. Specifically, this dissertation focuses on a special power system scheduling problem, a unit commitment problem with uncertainty. This scheduling problem is a two-stage decision problem. In the first stage, system operator determines the binary commitment status (on or off) of generators in advance. In the second stage, after the realization of uncertainty, the system operator determines generation levels of the generators. The goal of this dissertation is to develop computationally-tractable methodologies and algorithms to solve large-scale unit commitment problems with uncertainty. In the first …
- Contributors
- Li, Chao, Hedman, Kory W, Zhang, Muhong, et al.
- Created Date
- 2016