Automatic reactive power control of wind-diesel-micro-hydro autonomous hybrid power systems using ANN tuned static VAr compensator

R. Bansal, T. Bhatti, D. Kothari
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引用次数: 25

Abstract

This paper presents an artificial neural network (ANN) based approach to tune the parameters of the SVC reactive power controller over a wide range of typical load model parameters. The multi-layer feed-forward ANN with the error back-propagation training is employed to tune the static VAr compensator (SVC) controller for controlling the reactive power of variable slip/speed isolated wind-diesel-micro-hydro hybrid power systems. Transient responses of sample hybrid power system have been presented.
基于人工神经网络调谐静态无功补偿器的风-柴-微水电自主混合电力系统无功自动控制
本文提出了一种基于人工神经网络(ANN)的SVC无功控制器在大范围典型负荷模型参数下的参数整定方法。采用带误差反向传播训练的多层前馈神经网络对静态无功补偿器(SVC)控制器进行整定,以控制变转差/转速隔离型风-柴-微水电混合动力系统的无功功率。给出了典型混合动力系统的暂态响应。
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