الفهرس يوجد فقط 14 صفحة متاحة للعرض العام
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المستخلص
Static Var Compensators (SVCs) are being increasingly employed in modern powe systems. They improve power system stability and reduce losses by compensating reactive power of fluctuating heavy industrial loads and regulating terminal. As SVC essentially consists of a capacitor to supply reactive power to the system and a Thyristor Controllec Reactor (TCR) to absorb reactive power from the system, however, operation of SVC introduce harmonic culTents into the power system. These harmonics are generall removed using external filters. This work presents the application of SVC for compensation and stahilit’ enhancement in power system using intelligent control techniques. First, the developnien of an artificial neural network (ANN) controller for a Static VAR Compensator (SVC) i proposed. The objectives of this controller are to balance the line cunents improve the:power factor to unity and to minimize power line loss by controlling the firing angles c the Thvristor Controlled Reactors (TCR) of the SVC. Secondly, an indirect adaptive fuzzy excitation control (IAFLC) to enhanc transient stability for the power system is proposed. The dynamic interaction between tl generator excitation and the SVC in controller design is considered in this work. TI proposed IAFI C is applied to a single generator connected to an infinite bus where ti SVC is located at midpoint of transmission line. The coordinated generator excitatk control and the SVC can enhance the transient stability of the power system under lar, sudden faults, which may occur nearly at the generator bus terminal. An indirect adaptive fuzzy excitation control for multi-machine power systems considered. The main goal is to improve the transient stability. The proposed algoritin have been implemented in technical MATLAB package and tested on the theoreth system.