ETDs

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.

Displaying 1 - 1 of 1
Filtering by

Clear all filters

161246-Thumbnail Image.png

Power System Modeling Under Uncertainty With Controllable Demand

Description
With demand for increased efficiency and smaller carbon footprint, power system operators are striving to improve their modeling, down to the individual consumer device, paving the way for higher production and consumption efficiencies and increased renewable generation without sacrificing system reliability. This dissertation explores two lines of research. The first…

With demand for increased efficiency and smaller carbon footprint, power system operators are striving to improve their modeling, down to the individual consumer device, paving the way for higher production and consumption efficiencies and increased renewable generation without sacrificing system reliability. This dissertation explores two lines of research. The first part looks at stochastic continuous-time power system scheduling, where the goal is to better capture system ramping characteristics to address increased variability and uncertainty. The second part of the dissertation starts by developing aggregate population models for residential Demand Response (DR), focusing on storage devices, Electric Vehicles (EVs), Deferrable Appliances (DAs) and Thermostatically Controlled Loads (TCLs). Further, the characteristics of such a population aggregate are explored, such as the resemblance to energy storage devices, and particular attentions is given to how such aggregate models can be considered approximately convex even if the individual resource model is not. Armed with an approximately convex aggregate model for DR, how to interface it with present day energy markets is explored, looking at directions the market could go towards to better accommodate such devices for the benefit of not only the prosumer itself but the system as a whole.
ContributorsHreinsson, Kári (Author) / Scaglione, Anna (Thesis advisor) / Hedman, Kory (Committee member) / Zhang, Junshan (Committee member) / Alizadeh, Mahnoosh (Committee member) / Arizona State University (Publisher)
Created2020