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A normalized neural network based controller for power quality improved grid connected solar PV systems

机译:基于归一化神经网络的控制器,用于改善电能质量的并网太阳能光伏系统

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This paper is aimed at normalized neural network based control scheme for power quality improved integration of solar PV and utility grid. In the proposed scheme the solar PV and grid are integrated using a three leg voltage source converter consists of six IGBTs, three interfacing inductors and a DC bus capacitor. The neural network based scheme is used for estimating fundamental real and reactive power components of the load current in all three phases independently therefore the three phase grid current remains balanced and sinusoidal under all type of loading conditions including unbalancing in load currents of three phases. The proposed controller mitigates the harmonic current, compensates reactive power need of the system, improves system power factor and regulates the system voltage at the point of common coupling (PCC).
机译:本文针对基于归一化神经网络的控制方案,以提高太阳能光伏发电和公用电网的电能质量。在提出的方案中,使用由六个IGBT,三个接口电感和一个DC总线电容器组成的三脚电压源转换器将太阳能PV和电网集成在一起。基于神经网络的方案用于独立估计所有三相负载电流的基本有功和无功分量,因此,在包括三相负载电流不平衡在内的所有类型的负载条件下,三相电网电流仍保持平衡和正弦曲线。所提出的控制器减轻了谐波电流,补偿了系统的无功功率需求,提高了系统功率因数,并在公共耦合点(PCC)上调节了系统电压。

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