Optimal Selection of SSSC Based Damping Controller Parameters
Optimal Selection of SSSC Based Damping Controller Parameters for Improving Power System Dynamic Stability Using Genetic Algorithm
Abstract: This paper proposes a new genetic-based approach for optimal selection of the Static Synchronous Series Compensator (SSSC) based 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. For simultaneous improvement of objective function (system stability) and constraints (limits of controller gains), their combination is used as the fitness function. The work relies on Genetic Algorithms (to capture the near global solution), analysis of mode abservability (to select the effective feedback signal of the damping controller) and the theoretical analysis of a general Single-Machine Infinite-Bus (SMIB) power system, using its modified linearized Phillips-Heffron model installed with SSSC. Simulation results are presented to show the excellent performance of the proposed SSSC controller in damping the critical modes without significantly deteriorating the damping characteristics of other modes
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