Dynamic Stability of Power Systems Using UPFC: Bat-Inspired Search and Gravitational Search Algorithms

Abstract

In this paper, the bat-inspired algorithm and the Gravitational Search Algorithm (GSA) based optimal location and ca pacity of UPFC are proposed to improve the dynamic stability of power systems. The novelty of the proposed method is in improved searching ability, random reduction and reduced complexity. Here, the GSA is used to optimize the location of the UPFC if a generator fault occurs. The GSA selects the maximum power loss line as the optimum location to place UPFC as per the objective function, since the generator fault violates the system equality and inequality constraints from the secure limit. From the UPFC control parameters, the minimum voltage deviation is optimized using the bat algorithm. The minimum voltage deviation has been used to find the optimum capacity of the UPFC. Then the optimum UPFC capacity is applied in the optimum location, which enhances the dynamic stability of the system. The proposed method is implemented in the MATLAB/Simulink platform and the performance is evaluated by means of comparison with the different techniques like GSA and bat-inspired algorithm. The comparison results demonstrate the superiority of the proposed approach and confirm its potential to solve the problem