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Date of Award

4-1985

Degree Type

Thesis

Degree Name

Doctor of Philosophy (PhD)

Department

Electrical and Computer Engineering

Supervisor

Professor Mohamed A. El-Kady

Co-Supervisor

Professor Naresh K. Sinhu

Abstract

The major effort in this thesis has been directed towards the performance modelling and reliability estimation of large-scale power systems subject to probable single or multiple contingencies. A scheme for performance data pooling is introduced, which overcomes the problems of the limited available performance history and manipulation of large numbers of data sets associated with various components of a power system. A simulation technique which adopts a Monte-Carlo scheme is developed-to estimate component reliability measures and to select the probable contingency states of the system. A combined optimization/reliability formulation is introduced which provides improved reliability figures of the power system. In this formulation the system control parameters are manipulated to simulate practical contingency situations in which suitable system controls are invoked to preserve as much as possible, the continuity of supply. An efficient network partitioning scheme based on Ward equivalence has been developed. Only those parts of the system which are mostly affected by a contingency are retained for detailed analysis while the rest of the system is modelled by network equivalents. It is demonstrated that the use of such a partitioning scheme yields significant reduction in computational time and storage for contingency analysis while maintaining sufficiently accurate solutions. The partitioning scheme is subsequently combined with the optimization/reliability formulation which adds to the efficiency of both approaches. A technique is developed to guide the partitioning scheme via predicting the change in a performance index due to a contingency. The predicted changes are efficiently calculated using either a perturbed matrix inversion scheme or a suitable nth order derivative formulation. Using these predicted changes, a generalized contingency ranking methodology is introduced, for generation and/or transmission contingencies. The contingency ranking scheme is based on an important class of line loading functions representing system security constraints. A novel and computationally efficient technique for fast linear contingency analysis and ranking is introduced. This technique utilizes a bilinear-based formulation to calculate efficiently, the changes of individual bus voltage angles after the occurrence of a transmission contingency. An alternative equivalent formulation of the technique is aIso presented. It adopts reduced gradients of system states and provides the post-contingency exact changes of these states with significantly reduced online computations.

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