人工神经网络在停电事故下无功补偿预测中的应用

2013 International Conference on Power, Energy and Control (ICPEC) Pub Date : 2013-06-13 DOI:10.1109/ICPEC.2013.6527681

A. Rai, Dr. Suvanam Sasidhar Babu, P. S. Venkataramu, M. Nagaraja

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引用次数: 5

摘要

静态无功补偿器是一种可变阻抗装置，其中通过电抗器的电流是使用背靠背晶闸管连接阀来控制的。本文成功地设计了一种人工神经网络体系结构，该体系结构可以预测特定线路中断事故时向系统提供的补偿量，以提高系统性能。本文采用MATLAB软件对一个IEEE-30总线系统进行了研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Artificial neural network application for prediction of reactive power compensation under line outage contingency

Static VAR Compensator is a variable impedance device where the current through a reactor is controlled using back to back thyristor connected valves. In this paper a successful attempt has been made to design an ANN architecture which predicts the quantum of compensation to be provided to the system for a specific line outage contingency in order to improve the system performance. The study is carried out on an IEEE-30 bus system using MATLAB software.

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2013 International Conference on Power, Energy and Control (ICPEC)

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