Return to search

Critical Substation Risk Assessment and Mitigation

Substations are joints in the power system that represent nodes that are vital to stable and reliable operation of the power system. They contrast the rest of the power system in that they are a dense combination of critical components causing all of them to be simultaneously vulnerable to one isolated incident: weather, attack, or other common failure modes. Undoubtedly, the loss of these vital links will have a severe impact to the to the power grid to varying degrees.

This work creates a cascading model based on protection system misoperations to estimate system risk from loss-of-substation events in order to assess each substation's criticality. A continuation power flow method is utilized for estimating voltage collapse during cascades. Transient stability is included through the use of a supervised machine learning algorithm called random forests. These forests allow for fast, robust and accurate prediction of transient stability during loss-of-substation initiated cascades.

Substation risk indices are incorporated into a preventative optimal power flow (OPF) to reduce the risk of critical substations. This risk-based dispatch represents an easily scalable, robust algorithm for reducing risk associated with substation losses. This new dispatch allows operators to operate at a higher cost operating point for short periods in which substations may likely be lost, such as large weather events, likely attacks, etc. and significantly reduce system risk associated with those losses.

System risk is then studied considering the interaction of a power grid utility trying to protect their critical substations under a constrained budget and a potential attacker with insider information on critical substations. This is studied under a zero-sum game theoretic framework in which the utility is trying to confuse the attacker. A model is then developed to analyze how a utility may create a robust strategy of protection that cannot be heavily exploited while taking advantage of any mistakes potential attackers may make. / Ph. D. / Substations are key components to the continued and reliable operation of the power system. Their removal from the power system would severely hinder the system’s ability to transport power from power producers to end consumers. As larger weather events and potential threats to the power system are being considered, power system engineers to start considering the impact that losing substations would cause on the system. This work studies the impact on the system associated with losing substation and ranks them to find the most important ones. A probabilistic model is created based on incorrect operations in power system protection elements that historically have exacerbated large events in the power system.

Mitigation of this impact is then studied through two preventative means: changing the operating condition of the current system and adding protection to the substations. This is in order to secure the system before potentially losing the operation of a substation. The operating point change is formulated as a new optimization problem that helps alleviate stress on the system close to the most critical substations found in the earlier model. Protection of these substations is analyzed through game-theoretic means where the utility tries to confuse any potential attackers on which substations actually have true, rigid protection on them. In doing so, on expectation, the damage done to the system may be reduced significantly.

Identiferoai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/83444
Date01 June 2018
CreatorsDelport, Jacques
ContributorsElectrical Engineering, Centeno, Virgilio A., Abbott, A. Lynn, Phadke, Arun G., De La Ree, Jaime, Marathe, Madhav Vishnu, Bernabeu, Emanuel Ernesto, Thorp, James S.
PublisherVirginia Tech
Source SetsVirginia Tech Theses and Dissertation
Detected LanguageEnglish
TypeDissertation
FormatETD, application/pdf
RightsIn Copyright, http://rightsstatements.org/vocab/InC/1.0/

Page generated in 0.0014 seconds