Application of Multi-Objective Genetic Algorithm for Optimal Design of SSSC Based Robust Damping Controllers to Improve Small Signal Stability

A new genetic approach is proposed for optimal selection of the static synchronous series compensator (SSSC) based conventional lead-lag damping controller parameters. The parameters are tuned in order to shift the lightly damped and undamped modes under various loading conditions toward the prescribed stability region. The objective function includes system stability criteria (e.g., damping factor and damping ratio of the eigenvalues for all operating points under consideration) and boundaries of controller parameters (as constraints), enforcing their simultaneous improvement. The robustness is achieved by considering several loading conditions. The work relies on genetic algorithm (to capture the near global solution), analysis of mode observability (to select the effective feedback signal for 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 could easily be 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 under different loading conditions without significantly deteriorating damping characteristics of other modes in a SMIB power system