| 基于BP神经网络的SSSC的建模与仿真 |
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| 引用本文： | 林俊波,蒋程.基于BP神经网络的SSSC的建模与仿真[J].电气开关,2012,50(4):72-75. |
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| 作者姓名： | 林俊波 蒋程 |
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| 作者单位： | 1. 广西电网公司北海供电局,广西 北海,536000
2. 华北电力大学电气与电子工程学院,北京,102206 |
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| 摘 要： | SSSC的模型是分析其原理和设计其控制器的基础.由于SSSC是一个强非线性的系统,用传统的方法所建立的模型已不能达到人们的要求,利用具有非线性拟合能力的人工神经网络建立了逆变器电容电压和线路有效阻抗的神经网络模型.神经网络特有的非线性逼近、强化学习和自适应能力,使神经网络模型对变化的环境和参数具有自适应性.
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| 关 键 词： | 静止同步串联补偿器(SSSC) BP神经网络 非线性 自适应性 |
Model and Simulation of SSSC Based on BP Neural Network |
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| LIN Jun-bo
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JIANG Cheng.Model and Simulation of SSSC Based on BP Neural Network[J].Electric Switchgear,2012,50(4):72-75. |
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| Authors: | LIN Jun-bo JIANG Cheng |
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| Affiliation: | 1.Beihai Power Supply Bureau of Guangxi Power Grid Corporation,Beihai 536000,China;2.North China Electric Power University,Beijing 102206,China) |
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| Abstract: | The model of SSSC(Static Synchronous Series Compensator) is the key to analyze its principle and design its controller.Because of the SSSC’s strongly non-linearity,the model of SSSC using tradition method is not satisfied.In this paper,the neural network model of SSSC is built which contain the capacitor voltage model and the line impedance model.The neural network model with intensifying study,non-linear approach and adaptability could self-turn when the parameter of SSSC and the environment change. |
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| Keywords: | static synchronous series compensator(SSSC) BP neural network non-linearity adaptability |
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