An Efficient Enhancement of Rotor Angle Stability using a Hybrid BBO-DE Approach

Abstract

Power System Stabilizers (PSS) are mainly used as add-on controllers to damp out the low frequency oscillations in the power system stability operation. The tuning of Conventional Power System Stabilizer (CPSS) parameters for a system should be robust such that overall system stability phenomena can be improved. In the recent decades, various population based heuristic algorithms are available to sort out the stability problem in the electric Power System (PS). In this paper presents a new heuristic optimization algorithm named as hybrid Biogeography Based Optimization adapted Differential Evolution (BBO-DE) algorithm for finding the optimal CPSS parameters for Single Machine Infinite Bus (SMIB) and multi-machine system under various operating conditions. The location of the PSS has been carried by participation factor and optimal design of PSS parameters have been obtained by its eigen value approach. Simulations are carried out for the SMIB and three machine nine bus systems. The proposed hybrid BBO-DE technique is robust and highly efficient as compared with its related heuristic algorithms such as Biogeography Based Optimization involved Power System Stabilizer (BBOPSS) and Differential Evolution based Power System Stabilizer (DEPSS). From the simulation results the proposed method enhances the dynamic stability of the system remarkably, especially when the system operating condition changes.