REDUCED ORDER DYNAMIC MODELS FOR ELECTRIC POWER SYSTEMS

Abstract

Physical systems can be translated into mathematical models which are so high in dimensionsthat a direct simulation or design would be neither computationally desirable nor physically possible in many cases. A multiarea large-scale power system, for example is a very high dimensional system which physically and geographically is composed of several plants connected by tie lines. It is therefore required to reduce the system models. Traditionally simplification of mathematical models of dynamic systems rely heavily on the experience and acumen of the analyst. But in the last three decades tremendous work has been done to develop a general technique to reduce and simplify higher order dynamic system models. In this dissertation software for three methods namely Optimization, Routh Approximation and Mixed methods have been developed and tested for different system models. These reduction methods are then applied to excitation system of single machine connected to the infinite bus system and regulator problem. It has been shown in these two examples that reduced models of the respected systems can be successfully used in place of higher order models for optimal design of PID controller to improve their performance according to the requirements. i