Design of Decentralized PSSs for Multimachine Power System via Reduced Order Model

Abstract

The Power System Stabilizer (PSS) is added to excitation system to enhance the damping during low frequency oscillations. In this paper, the design of decentralized PSSs for 10 machines with 39 buses using fast output sampling method via reduced order model is proposed. In multi-machine power system the order of the states matrix is very large. The main objectives of order reduction is to design a controller of lower order which can effectively control the original high order system so that the overall system is of lower order and easy to understand. The state space matrices of the reduced order system are chosen such that the dominant eigenvalues of the full order system are unchanged. The other system parameters are chosen using the particle swarm optimization with objective function to minimize the mean squared errors between the outputs of the full order system and the outputs of the reduced order model when the inputs are unit step. Design of fast output sampling controllers via reduced order model using Particle Swarm Optimization (PSO) method is proposed for good damping enhancement for various operating points of multi-machine power systems. In fast output sampling technique, the nonlinear model of 10 machine and 39 bus system is linearized at different operating point and a linear model is obtained. A robust fast output sampling feedback gain which realizes output injection gain is obtained using LMI approach. This robust fast output sampling control is applied to non-linear model of a Multi-machine system at different operating points. This method gives very good results in the design of Power System Stabilizers and takes less computation time in operation of power system.