Title page for ETD etd-09112009-151520

Type of Document Dissertation
Author Cheng, Danling
URN etd-09112009-151520
Title Integrated System Model Reliability Evaluation and Prediction for Electrical Power Systems: Graph Trace Analysis Based Solutions
Degree PhD
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Broadwater, Robert P. Committee Chair
Abbott, A. Lynn Committee Member
Liu, Yilu Committee Member
Nachlas, Joel A. Committee Member
Tam, Kwa-Sur Committee Member
  • Real-Time Monitoring and Analysis
  • Monte Carlo Simulation
  • Distributed Generation
  • Time-Varying Load
  • Cascading Effect
  • Dependent Failure
  • Adverse Weather Effect
  • Reliability Analysis
Date of Defense 2009-09-09
Availability unrestricted
A new approach to the evaluation of the reliability of electrical systems is presented. In this approach a Graph Trace Analysis based approach is applied to integrated system models and reliability analysis. The analysis zones are extended from the traditional power system functional zones. The systems are modeled using containers with iterators, where the iterators manage graph edges and are used to process through the topology of the graph. The analysis provides a means of computationally handling dependent outages and cascading failures. The effects of adverse weather, time-varying loads, equipment age, installation environment, operation conditions are considered. Sequential Monte Carlo simulation is used to evaluate the reliability changes for different system configurations, including distributed generation and transmission lines. Historical weather records and loading are used to update the component failure rates on-the-fly. Simulation results are compared against historical reliability field measurements.

Given a large and complex plant to operate, a real-time understanding of the networks and their situational reliability is important to operational decision support. This dissertation also introduces using an Integrated System Model in helping operators to minimize real-time problems. A real-time simulation architecture is described, which predicts where problems may occur, how serious they may be, and what is the possible root cause.

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