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可控串联补偿神经网络广义逆系统控制方法的数字仿真研究
引用本文:曹路,李海峰,陈珩,曹然.可控串联补偿神经网络广义逆系统控制方法的数字仿真研究[J].电力系统及其自动化学报,2000,12(6):4-8.
作者姓名:曹路  李海峰  陈珩  曹然
作者单位:东南大学电气工程系,南京,210096
基金项目:国家自然科学基金委员会重点资助项目! (项目号 :5 963 70 5 0 )
摘    要:本文介绍了提高电力系统暂态稳定性的可控串联补偿(TCSC)神经网络广义逆系统控制方法,以及该方法在数字仿真软件NETOMAC中的实现过程,并对含有TCSC的实际多机电力系统进行了数字仿真。结果表明,这种方法具有良好的暂态稳定控制效果,而NETOMAC可以实现这类复杂的控制策略。

关 键 词:电力系统  可控串联补偿  数字仿真  神经网络
修稿时间:2000-02-27

STUDY OF ANN-BASED GENERALIZED INVERSE-SYSTEM CONTROL FOR THYRISTOR CONTROLLED SERIES COMPENSATION BY DIGITAL SIMRLATION
Cao Lu,Li Haifeng,Chen Heng,Cao Ran.STUDY OF ANN-BASED GENERALIZED INVERSE-SYSTEM CONTROL FOR THYRISTOR CONTROLLED SERIES COMPENSATION BY DIGITAL SIMRLATION[J].Proceedings of the CSU-EPSA,2000,12(6):4-8.
Authors:Cao Lu  Li Haifeng  Chen Heng  Cao Ran
Affiliation:Department of Electrical Engineering Southeast University Nanjing 210096
Abstract:This paper introduces the ANN-based generalized inverse-system control strategy for Thyristor Controlled Series Compensation (TCSC) to enhance the transient stability of power systems. The techniques of applying the controller to the digital simulation program NETOMAC are given and a practical multi-machine power system with TCSC is taken as an example. The simulation results show that the ANN-based generalized inverse-system performs good effect in transient stability control and NETOMAC is a powerful tool for complicated control strategy studies.
Keywords:power system  transient stability  thyristor controlled series compensation (TCSC)  digital simulation  artificial neural network  inverse-system
本文献已被 CNKI 维普 万方数据 等数据库收录!
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