Adaptive Particle Swarm Optimization for Simultaneous Design of UPFC Damping Controllers

• An adaptive particle swarm optimization based on non-linear time varying acceleration coefficients is proposed.
• The proposed algorithm is applied for numerical optimization and damping of oscillations in power system stability analysis.
• Experimental results confirm superior performance of the new method compared with other similar methods.

An adaptive particle swarm optimization based on nonlinear time-varying acceleration coefficients (NTVAC-PSO) is proposed for solving global optimization problems and damping of power system oscillations. The new method aims to control the global exploration ability of the original PSO algorithm and to increase its convergence rate with an acceptable solution in less iteration. A set of 10 well-known benchmark optimization problems is utilized to validate the performance of the NTVAC-PSO as a global optimization algorithm and to compare with similar methods. The numerical experiments show that the proposed algorithm leads to a significantly more accurate final solution for a variety of benchmark test functions faster. In addition, the simultaneous coordinated design of unified power flow controller-based damping controllers is presented to illustrate the feasibility and effectiveness of the new method. The performance of the proposed algorithm is compared with other methods through eigenvalue analysis and nonlinear time-domain simulation. The simulation studies show that the controllers designed using NTVAC-PSO performed better than controllers designed by other methods. Moreover, experimental results confirm superior performance of the new method compared with other methods.