Robust Decentralized Fast Output Sampling Technique via reduced order models based Power System Stabilizer for Multimachine Power System

Power System Stabilizers (PSSs) are added to excitation systems 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 feedback 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 PSO 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 feedback controllers via reduced order model using PSO method is proposed for good damping enhancement for various operating points of multi-machine power systems. This paper also presents a comparatively study of design of fast output sampling feedback controllers via reduced order model using Particle PSO method, and Davison method technique for multi-machine system. Particle swarm optimization (PSO) order reduction method based fast output sampling feedback controller gives very good results, less complexity and also economic in designing of PSSs comparatively Davison method and balance truncation technique.