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ABC algorithm for estimation of dynamic parameters in radial power system transfer path

机译:径向电力系统传输路径中动态参数估计ABC算法

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摘要

In this paper, the artificial bee colony algorithm (ABC) is used to predict the stability of the power system and is evaluated the aggregated machine reactance and inertias in the transfer path. The proposed method is used for estimating the dynamic parameters of the aggregated machines for each area utilising the amplitudes of voltage oscillations measured at any three intermediate points on the transfer path. Two types of voltage control equipment are considered, namely, a static var compensator (SVC) and a thyristor controlled series capacitor (TCSC) including the purpose of voltage support and reducing the disturbance in the system. The proposed methods employ bus voltage phasor data at several buses including the voltage control bus and the line currents on the power transfer path. Here, the three phase fault is applied in the power system. Based on the estimation, the dynamics of the power system is improved and the proposed strategy is utilised for improving the overall dynamic security. The proposed technique is implemented in MATLAB/simulink working platform and the output performance is evaluated and compared with the existing methods such as without facts devices, SVC based controller and genetic algorithm (GA) based TCSC controller respectively.
机译:在本文中,人造蜂菌落算法(ABC)用于预测电力系统的稳定性,并在传送路径中评估聚集机电抗和惯性。所提出的方法用于估计利用在传送路径上的任何三个中间点处测量的电压振荡幅度的每个区域的聚合机器的动态参数。考虑两种类型的电压控制设备,即静态VAR补偿器(SVC)和晶闸管控制串联电容器(TCSC),包括电压支撑的目的并降低系统中的干扰。所提出的方法在包括电压控制总线和电力传输路径上的线路电流的若干总线上使用总线电压量程数据。这里,三相故障应用于电力系统。基于估计,提高了电力系统的动态,并且所提出的策略用于提高整体动态安全性。所提出的技术在MATLAB / SIMULINK工作平台中实现,并与现有方法进行评估,并将其与基于事实设备,基于SVC的控制器和遗传算法(GA)基于TCSC控制器的TCSC控制器进行评估。

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