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

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

摘要

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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic reactive power control of wind-diesel-micro-hydro autonomous hybrid power systems using ANN tuned static VAr compensator
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.
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