Transient Stability Optimization based on increasing the Critical Clearing Time using Particle Swarm Optimization
Keywords:Transient Stability Analysis, Fault condition, rotor swing angle, critical clearing time, Particle Swarm Optimization.
Transient stability Analysis under fault condition is one of the most important concept for a secure and reliable power system operation. Any delay time to cleared the fault and remove the line may be caused the system unstable. Increasing the clearing timetc leads to increase the rotor angle of the generator and go towards the instability system. The clearing time before the system become unstable is called the critical clearing time tcc. This article design a new architecture algorithm to improve the transient stability of the system under fault condition by increase the critical clearing time without adding any external dives. An artificial intelligence technique of Particle Swarm Optimization PSO has been used for this purpose. PSO technique minimize the maximum rotor angle of the generator according to optimize the control variable of the system such as the magnitude voltage of the generator. A load flow analysis based on Newton Raphson method has been used for the pre fault calculation. The two state equations for both during and post fault cases are solved using the modified Euler method to calculate the rotor angle of the generators. Different cases of clearing time are tested in this article to specified the system stability and access to the critical clearing time. The propose algorithm has been applied on the IEEE 9 bus system. This algorithm improve the system transient stability by increasing the critical clearing time by 28%. The propose algorithm are programming by author using matlab software.
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