With the expansion of electric power systems, the size and complexity of the network is increased. One of the most important drawbacks of network expansion is the reduction in the damping torque of the whole system. The lack of damping torque can lead to fluctuations and instability in the power system. With regard to this problem, power system stabilizers (PSSs) have been widely utilized to improve power system stability. However, due to some drawbacks of the conventional PSSs, the need for finding a better substitution still remains. Therefore, in this paper, the application of a static synchronous compensator (STATCOM) to improve dynamic stability of a multimachine electric power system is presented and a supplementary stabilizer based on the STATCOM is incorporated. Intelligence optimization methods such as particle swarm optimization and genetic algorithms are considered for tuning the parameters of the proposed stabilizer. Several nonlinear time-domain simulation tests visibly show the ability of the STATCOM in damping power system oscillations.
Power System Stabilizers (PSSs) are used to enhance damping of power system oscillations through excitation control of synchronous generator. The objective of the PSS is to generate a stabilizing signal, which produces a damping torque component on the generator shaft. Conventional PSSs are designed with the phase compensation technique in the frequency domain and include the lead-lag blocks whose parameters are determined according to a linearized power system model. The performance of Conventional PSSs (CPSSs) depends upon the generator operating point and the system parameters, but a reasonable level of robustness can be achieved depending on the tuning method. To overcome the drawbacks of CPSS, numerous techniques have been proposed in literatures. In this paper a robust method based on Quantitative Feedback Theory (QFT) Algorithm is used for tuning the PSS parameters. The proposed QFT-PSS is evaluated at a multi machine electric power system. The simulation results clearly indicate the effectiveness and validity of the proposed method.
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