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Deterministic Scheduling for Transmission-Constrained Power Systems Amid Uncertainty


Abstract This research develops heuristics for scheduling electric power production amid uncertainty. Reliability is becoming more difficult to manage due to growing uncertainty from renewable resources. This challenge is compounded by the risk of resource outages, which can occur any time and without warning. Stochastic optimization is a promising tool but remains computationally intractable for large systems. The models used in industry instead schedule for the forecast and withhold generation reserve for scenario response, but they are blind to how this reserve may be constrained by network congestion. This dissertation investigates more effective heuristics to improve economics and reliability in power systems where congestion is a concern.

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Created Date 2015
Contributor Lyon, Joshua (Author) / Zhang, Muhong (Advisor) / Hedman, Kory W (Advisor) / Askin, Ronald G (Committee member) / Mirchandani, Pitu (Committee member) / Arizona State University (Publisher)
Subject Operations research / Industrial engineering / Electrical engineering / ancillary services / energy markets / optimization / uncertainty / unit commitment
Type Doctoral Dissertation
Extent 260 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Industrial Engineering 2015
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis