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Title:Real-time power system operational reliability tools
Author(s):Van Horn, Kai Emerson
Director of Research:Dominguez-Garcia, Alejandro D; Sauer, Peter W
Doctoral Committee Chair(s):Dominguez-Garcia, Alejandro D; Sauer, Peter W
Doctoral Committee Member(s):Zhu, Hao; Veeravalli, Venugopal V
Department / Program:Electrical & Computer Engineering
Discipline:Electrical & Computer Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):electricity markets
phasor measurement unit (PMU)
reliability
economic dispatch
contingency analysis
injection shift factor
security-constrained economic dispatch
Abstract:The primary goal of power system operators is to effectively and economically maintain operational reliability---a power system is said to be in an operationally reliable state if the supply-demand balance is met, and the system can tolerate the failure of a small number of components without jeopardizing continued operation. In pursuit of this goal, operators rely on so-called operational reliability tools to schedule resources and manage uncertainty. Conventional operational reliability tools include market-scheduling tools, e.g., the real-time security-constrained economic dispatch (SCED), and system-monitoring tools, e.g., real-time contingency analysis (RTCA). Due to the stringent computational speed requirements of real-time operations, conventional operational reliability tools make extensive use of power flow sensitivities to simplify the mathematical representation of the physical electricity system. Moreover, the computation of such sensitivities requires a model of the system, which is typically obtained offline. As such, the effectiveness of these tools is highly dependent on the accuracy of the model from which such sensitivities are computed, which may be compromised due to erroneous input parameters, undetected topology changes, and changes in ambient conditions. Inaccurate sensitivities are an impediment to effective electricity market operation and price formation, as well as compromising system operational reliability. The 2011 San Diego blackout brought to light an additional shortcoming of conventional operational reliability tools: they do not provide system operators the ability to predict the angle of the voltage across the breaker of a transmission line that will arise in the event of the line's outage---which we refer to as the outage angle---or means by which to mitigate such angles. Indeed, the conventional SCED process does not include any means by which to bring outage angle considerations to bare on the generator dispatch, which determines if the system will be in an operationally reliable state. In this thesis, we address the aforementioned shortcomings of conventional operational reliability tools by formulating a set of measurement-based operational reliability tools and deriving a sensitivity-based approach to monitoring and mitigating line outage angles. To this end, we provide: (i) a measurement-based approach to marginal loss factor (LF) estimation, which harnesses phasor measurement unit (PMU) measurements to estimate the LFs online rather than computing them from a power flow model; (ii) a formulation of the line outage angle factor (LOAF), the computation of which requires only existing sensitivities, the angle factors (AFs) and injection shift factors (ISFs), and which can be deployed to formulate a tool for outage angle monitoring and an angle-constrained SCED; and (iii) a measurement-based formulation of the SCED, which utilizes the measurement-based LFs along with measurement-based ISFs to decouple the SCED process and underlying RTCA from the vulnerabilities associated with a system model. Our hope is that the proposed tools will enhance the real-time operational reliability process and contribute to more effective and efficient power system operations.
Issue Date:2015-11-10
Type:Thesis
URI:http://hdl.handle.net/2142/88983
Rights Information:Copyright 2015 Kai Van Horn
Date Available in IDEALS:2016-03-02
Date Deposited:2015-12


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