Optimal selection of SSSC based damping controller parameters for improving power system dynamic stability using genetic algorithm

A new genetic-based approach is proposed for optimal selection of the static synchronous series compensator (SSSC) damping controller parameters in order to shift the closed loop eigenvalues toward the desired stability region. Controller design is formulated as a nonlinear constrained optimization problem. As the combination of objective function (system stability) and constraints (limits of controller gains) is used as the fitness function, their simultaneous improvement is achieved. The work relies on genetic algorithm (to capture the near global solution), analysis of mode observability (to select the effective feedback signal of the damping controller) and the theoretical analysis of a single-machine infinite-bus (SMIB), using its modified linearized Phillips-Heffron model installed with SSSC. It is shown that the results can be easily extended for multi machine power systems. Simulation results are presented to show the fine performance of the proposed SSSC controller in damping the critical modes without significantly deteriorating the damping characteristics of other modes in a SMIB power system.