Access Type

Open Access Embargo

Date of Award

January 2022

Degree Type

Dissertation

Degree Name

Ph.D.

Department

Electrical and Computer Engineering

First Advisor

Caisheng Wang

Second Advisor

Feng Lin

Abstract

A power system cascading failure can propagate through sequential tripping of components in the network. As a result, a complete or partial shutdown may occur. Many models were developed to understand the failure propagation mechanism at a higher abstract level and methods were implemented for failure mitigation. This work introduces a unified framework of modeling and mitigating cascading failures. Based on a Discrete Event Systems (DES) approach, a power system is modeled by an automaton via parallel composition of the sub-models of system components. A modified DES supervisory control (SC) strategies are introduced as a solution to mitigating cascading failures that is based on a regular off-line control. The proposed supervisory control strategy is then extended to an on-line based control to overcome the increased complexity of large scale systems. An evaluation method and a criterion for assessing cascading failure risk and identifying critical components during failure propagation in the DES framework are then proposed. The proposed on-line control was implemented and verified through joint simulations between continuous time power flow analysis and discrete events dynamics with supervisory control. An illustrative example of the proposed approach is presented. Simulation studies for the on-line approach are carried out for IEEE 6-bus, 30-bus and 118-bus systems systems to verify the effectiveness of the proposed approach. Modular supervisory control is then introduced and proposed to mitigate cascading failure for large scale power systems. A framework to implement modular control approach is then proposed. Similar to the on-line control approach, simulations based on case studies for the IEEE 6-bus and 30-bus systems are carried out to illustrate the effectiveness of the proposed approach.

Available for download on Tuesday, December 12, 2023

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