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标题：ANN Model for Estimation of Capacitance Requirements to Maintain Constant Air-Gap Voltage of Self-Excited Induction Generator with Variable Load
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作者：Raja Singh Khela ; K. S. Sandhu
期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2011
卷号：2
期号：4Ver1
出版社：Ayushmaan Technologies
摘要：It is essential to supply electric power at rated voltage and frequency to the consumers for efficient and safe operation of electric equipment or other appliances under varying conditions of load connected in power system. The dependence of output voltage and frequency of Self-Excited Induction Generator (SEIG) on its speed, load and terminal capacitance poses limitations on its use in public sector utilities for power generation. In power systems, the utility of SEIG as stand alone machine has started gaining importance when power engineers encountered difficult situations for installation of transmission and distribution lines in the remote areas due to difficult geographical conditions. The probability of reduced terminal voltage at rated or near full load become more pronounced when power is supplied from an isolated generator. Thus, to keep the load voltages at rated level under vide range of load variations, it is necessary to regulate the terminal capacitance to generate constant airgap voltage (E1 = 1.00 pu). In this paper an attempt is made to model the behavior of SEIG to maintain constant air-gap voltage using Artificial Neural Networks (ANN). The results are in good agreement with the analytical solution and are verified experimentallyml+xml,
关键词：Self-excited induction generator; artificial neural networks;terminal capacitance.n.l