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Robust tuning of multimachine power system Stabilizer via Cuckoo Search Optimization Algorithm

机译:多机动力系统稳定器通过CUCKOO搜索优化算法进行强大调整

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In this paper, Cuckoo Search Optimization (CSO) algorithm is presented for robust tuning of Power System Stabilizer (PSS) parameters in multimachine power system. In this work, a conventional speed-based lead-lag PSS is used. A damping ratio based objective function is formulated to optimize the damping of all electromechanical modes. The parameters of the CSO based PSS (CSOPSS) are optimized to shift the unstable or poorly damped eigenvalues associated with all electromechanical modes to a wedge-shape zone in left half of the s-plane. The eigenvalue analysis, time domain simulation results and performance indices show the effectives of CSOPSS by exhibiting better damping ratio than Genetic Algorithm based PSS (GAPSS) and Particle Swarm Optimization based PSO (PSOPSS). It is observed that CSOPSS exhibits improved damping performance compared to GAPSS and PSOPSS. The performance of proposed PSS is tested on Kundur 2-area 4-machine power system for wide range of operating conditions and severe disturbances.1
机译:本文在多机动力系统中的电力系统稳定器(PSS)参数的鲁棒调谐中,提出了Cuckoo搜索优化(CSO)算法。在这项工作中,使用传统的速度基引线PSS。配制基于阻尼比的目标函数以优化所有机电模式的阻尼。优化CSOX的PSS(CSOPS)的参数优化以将与所有机电模式相关联的不稳定或不良的特征值转移到S平面的左半部分的楔形区域。特征值分析,时域仿真结果和性能指标显示CSOPS通过表现出比基于遗传算法的PSS(空隙)和基于粒子群优化的PSO(PSOPS)的PSS(PSOPS)的效果。观察到,与间隙和PSOPS相比,CSOPS表现出改善的阻尼性能。建议PSS的性能在昆医2区4机电力系统上进行测试,可用于广泛的操作条件和严重的扰动.1

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