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A robust PSSs design using PSO in a multi-machine environment

机译：在多机器环境中使用PSO进行强大的PSS设计

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In this paper, multi-objective design of multi-machine power system stabilizers (PSSs) using particle swarm optimization (PSO) is proposed. The potential of the proposed approach for optimal setting of the widely used conventional lead-lag PSSs has been investigated. The stabilizers are tuned to simultaneously shift the lightly damped and undamped electromechanical modes of all machines to a prescribed zone in the s-plane. The PSSs parameters tuning problem is converted to an optimization problem with the eigenvalue-based multi-objective function comprising the damping factor, and the damping ratio of the lightly damped electromechanical modes, which is solved by a PSO algorithm which has a strong ability to find the most optimistic results. The robustness of the proposed PSO-based PSSs (PSOPSS) is verified on a multi-machine power system under different operating conditions and disturbances. The results of the proposed PSOPSS are compared with the genetic algorithm based tuned PSS and classical PSSs through eigenvalue analysis, nonlinear time-domain simulation and some performance indices to illustrate its robust performance for a wide range of loading conditions.
机译：本文提出了基于粒子群算法的多机电力系统稳定器多目标设计方法。已经研究了所提出的方法对广泛使用的常规超前滞后PSS进行最佳设置的潜力。调整稳定器可将所有机器的轻度阻尼和无阻尼的机电模式同时移至s平面中的指定区域。通过基于特征值的多目标函数将PSSs参数调整问题转换为优化问题，该函数包括阻尼因子和轻度阻尼机电模式的阻尼比，并通过具有强大发现能力的PSO算法解决了该问题最乐观的结果。提出的基于PSO的PSS（PSOPSS）的鲁棒性已在多机电源系统上的不同操作条件和干扰下得到了验证。通过特征值分析，非线性时域仿真和一些性能指标，将拟议的PSOPSS的结果与基于遗传算法的调谐PSS和经典PSS进行比较，以说明其在各种载荷条件下的鲁棒性能。

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