A hybrid EPSO for power system stabilizers design

This paper presents a hybrid optimization method to solve the robust and coordinated design of power system stabilizers problem. The tuning procedure is posed as an optimization problem aiming at maximizing the damping ratio coefficients in closed-loop operation taking several scenarios into account to ensure robustness. The hybrid proposed method combines the global search and self-adaptive ability of the Evolutionary Particle Swarm Optimization (EPSO) with the local search capability of the Quasi-Newton optimization method (BFGS). The method is successfully applied to the well-known New England Test System and overcomes the results provided by the standard EPSO, PSO and Genetic Algorithm.

[1]  A.P. Alves da Silva,et al.  Applications of evolutionary computation in electric power systems , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[2]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[3]  David G. Luenberger,et al.  Linear and Nonlinear Programming: Second Edition , 2003 .

[4]  P. Kundur,et al.  Power system stability and control , 1994 .

[5]  Vladimiro Miranda,et al.  EPSO-evolutionary particle swarm optimization, a new algorithm with applications in power systems , 2002, IEEE/PES Transmission and Distribution Conference and Exhibition.

[6]  Ivo Chaves da Silva Junior,et al.  Gradient based hybrid metaheuristics for robust tuning of power system stabilizers , 2018 .

[7]  K. R. Padiyar,et al.  ENERGY FUNCTION ANALYSIS FOR POWER SYSTEM STABILITY , 1990 .