الفهرس 
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Abstract
The thesis presents advanced techniques to solve the Voltage Swell problem. The main subject of the thesis deals with enhancing the steady-state and dynamicperformance of the power grids by Advanced Flexible AC Transmission System (AFACTS) based on computational intelligence. Control of the electric power system can be achieved by using the AFACTS controller, where the new trends as Artificial Intelligence can be applied to this subject to enhance the characteristics of controller performance. This thesis studies and analyzes Advanced Flexible AC Transmission System (AFACTS) concerns of voltage swell mitigation in the power networks.
The contributions of this thesis start with formatting, deriving, coding and programming the network equations required to link new proposed idea. This is namely Advanced Flexible AC Transmission System AFACTS during steady-state and dynamic behavior to the power systems. One of the other contributions of the thesis is deriving new trends Evolutionary Computing methods as Particle Swarm Optimization (PSO) and Adaptive Acceleration Coefficients based PSO (AACPSO) applications on AFACTS to achieve real criteria on a real world transmission network.The AFACTS device, is used in this thesis, is the most promising one, which known as Advanced Thyristor Controlled Series Reactors (ATCSRs), and Advanced Static VAR Compensator (ASVC) were utilized in this thesis to mitigate the voltage swell performance aiming to achieve good power quality. This thesis focuses on the operation of the FACTS devices under turning off heavy load that may cause transformer damage, which is considering a novel approach. Particle Swarm Optimization and Adaptive Acceleration Coefficients based PSO is used to determine the value of series inductor connected to the AFACTS.The thesis achieves the optimization of the type, the location and the size of the power andcontrol elements for AFACTS to optimize the system performance.
The thesis derives thecriteria to install the AFACTS in an optimal location with optimal parameters and then designsa(PSO) and (AACPSO) based damping controller for enhancing power system dynamic performance. In thisthesis, for every operating point PSO is used to search for controller’s parameters. Such that Parametersfound at certain operating point are different from those found at others.