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Transient performance improvement of power system by optimal design of SVC controller employing genetic algorithm

机译:基于遗传算法的SVC控制器优化设计提高电力系统暂态性能。

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With the increase of loading of long transmission line, transient stability of power system on the occurrence of a fault become one of the major concern for power engineers. Instability problem of power system on occurrence of the fault can be solved with the use of Static VAR Compensator (SVC) controller. Assessing the transient stability of a large inter connected power network very much nonlinear and tremendously complicated. To mitigate this complication and nonlinearity, a substantial research with SVC controller has been done in the power industry. To improve the system stability for dynamic and transient disturbances SVC plays a very important role, which is a shunt connected FACTS devices. In this work, genetic algorithm based optimal design of SVC controller to improve the transient performance of power system is proposed. The parameters of the damping controller by optimal selection of damping ratio of the critical eigenvalue employing genetic algorithm are tuned. The effectiveness of the developed optimal controller is investigated by simulating different abnormal conditions of a single machine infinite bus (SMIB) system using MATLAB based PST.
机译:随着长输电线路负荷的增加,发生故障时电力系统的暂态稳定成为电力工程师关注的重点之一。通过使用静态VAR补偿器(SVC)控制器,可以解决发生故障时电力系统的不稳定性问题。评估大型互联电网的暂态稳定性非常非线性,而且非常复杂。为了减轻这种复杂性和非线性,SVC控制器已在电力行业中进行了大量研究。为了提高动态和瞬态干扰的系统稳定性,SVC起着非常重要的作用,它是并联连接的FACTS装置。在这项工作中,提出了基于遗传算法的SVC控制器的优化设计,以提高电力系统的暂态性能。通过采用遗传算法对关键特征值的阻尼比进行最优选择,对阻尼控制器的参数进行了调整。通过使用基于MATLAB的PST模拟单机无限总线(SMIB)系统的不同异常情况,研究了开发的最优控制器的有效性。

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