Improved Time Variant PSO Based Design of Multiple Power System Stabilizer

摘要

The effective device for damping of the inter-area and intra-area low frequency oscillations is the Power System Stabilizers (PSSs) to enhance power system stability and optimal power flow. Optimal setting of the PSS parameters is importance and a challenging task to accommodate variations in the power system dynamics, particularly when several PSSs are used. Because, it is a multimodal optimization problem. In this paper, in order to reduce the PSS design effort and find the best possible solution a bio-inspired algorithm which called Particle Swarm Optimization with Time-Varying Acceleration Coefficients (PSO-TVAC) is presented for optimal tuning of multiple PSSs parameters, simultaneously. The non-linear time domain-based objective function under multiple operating conditions is used to determine the optimal parameters of PSSs. The PSO-TVAC uses a new parameter automation strategy to control both global and local search for considerable increasing the probability of finding the global optimum solution within a reasonable computation effort. The effectiveness of the proposed method is investigated on a two-area four machine power system in comparison with the classical PSO, bacterial foraging algorithm and conventional method based designed PSSs through the nonlinear time domain simulation and some performance indices for a wide range of loading condition. The results analysis reveals that the PSO-TVAC based PSSs is effective and provides good low frequency oscillations damping ability. Moreover, it is superior that of the other PSO method in terms of accuracy, convergence and computational effort.