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SELF TUNING CONTROLLERS FOR DAMPING LOW FREQUENCY OSCILLATIONS

机译:用于阻尼低频振荡的自调谐控制器

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This paper presents a new control methods based on adaptive Neuro-Fuzzy damping controller and adaptive Artificial Neural Networks damping controller techniques to control a Unified Power Flow controller (UPFC) installed in a single machine infinite bus Power System. The objective of Neuro-Fuzzy and ANN based UPFC controller is to damp power system oscillations.Phillips-Herffron model of a single machine power system equipped with a UPFC is used to model the system. In order to damp power system oscillations, adaptive neuro-fuzzy damping controller and adaptive ANN damping controller for UPFC are designed and simulated. Simulation is performed for various types of loads and for different disturbances. Simulation results demonstrate that the developed adaptive ANN damping controller has an excellent capability in damping electromechanical oscillations which exhibits a superior damping performance in comparison to the neuro-fuzzy damping controller as well as conventional lead-lag controller.
机译:本文介绍了一种基于自适应神经模糊阻尼控制器和自适应人工神经网络阻尼控制器技术的新控制方法,以控制安装在单机无限总线电力系统中的统一电流控制器(UPFC)。神经模糊和基于ANN的UPFC控制器的目的是潮湿的电力系统振荡。赫弗斯 - 赫克斯·赫弗斯模型配备了UPFC的单机电力系统来建模系统。为了潮湿的电力系统振荡,设计和模拟了用于UPFC的自适应神经模糊阻尼控制器和自适应ANN阻尼控制器。为各种类型的负载和不同干扰进行仿真。仿真结果表明,开发的自适应ANN阻尼控制器在阻尼机电振荡中具有优异的能力,该机电振荡能够与神经模糊阻尼控制器以及传统的引线滞后控制器相比具有出色的阻尼性能。

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