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Investigation and analysis of high performance green energy induction motor drive with intelligent estimator

机译:带有智能估计器的高性能绿色能源感应电动机驱动器的调查与分析

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This paper attempts to enhance the performance of a green energy induction motor drive. The electronic power converters become indispensable part of the renewable energy systems (RES). The solar photovoltaic (PV) system is efficiently operated with artificial neural network (ANN) based maximum power point tracking (MPPT) algorithm. The inverter topologies for the green drive scheme are analyzed. To improve the drive performance a reduced switch multilevel inverter (RSMLI) is employed. As indirect field oriented control (IFOC) is used, the drive demands on-line estimation of rotor resistance. A neural learning model reference adaptive scheme (NL-MRAS) based rotor resistance estimator is found to exhibit good dynamic performance. This work also investigates the performance of the green drive with an intelligent estimator. The performance enhancement of the green energy drive obtained by ANN based MPPT for the PV system, a reduced switch MLI and an intelligent estimator is presented. (C) 2015 Elsevier Ltd. All rights reserved.
机译:本文试图增强绿色能源感应电动机驱动器的性能。电子功率转换器成为可再生能源系统(RES)不可或缺的一部分。太阳能光伏(PV)系统可通过基于人工神经网络(ANN)的最大功率点跟踪(MPPT)算法有效运行。分析了绿色驱动方案的逆变器拓扑。为了提高驱动性能,采用了减少开关的多电平逆变器(RSMLI)。由于使用了间接磁场定向控制(IFOC),因此驱动器需要在线估算转子电阻。发现基于神经学习模型参考自适应方案(NL-MRAS)的转子电阻估算器具有良好的动态性能。这项工作还使用智能估算器研究了绿色驱动器的性能。提出了基于ANN的MPPT用于光伏系统的绿色能源驱动的性能增强,减少的开关MLI和智能估计器。 (C)2015 Elsevier Ltd.保留所有权利。

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