Performance Analysis of Three Phase Grid Connected PV Array with ANN Controlled SAPF

Shivansh Gautam, S. Agrawal
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引用次数: 1

Abstract

Three phase Shunt Active Power Filters (SAPF) are widely used to inject required amount of compensating current to eliminate current harmonics generated by Non-Linear Loads (NLL) and restore sinusoidal waveform of the supply. This paper analyze the development of a three phase grid connected PV array generating a P&O algorithm based MPPT tracked DC power, converted to AC power by PLL controlled VSI supplying a NLL connected with SAPF constituting of series inductor, ANN based self-supported DC link capacitor connected to IGBT based Current controlled VSI compensating for load induced current harmonics in the line. The developed SAPF works on instantaneous active and reactive power measurements to calculate the reference current for the HBCC to produce the gate pulse for the inverter. The proposed model is developed in MATLAB 17a Simulink and Levenberg Marquardt training algorithm based ANN is implemented to regulate DC link capacitor voltage. Simulated results approves the proposed control technique for a fast and flexible dynamic response of the solar to three phase compensated grid system and Total Harmonic Distortion of supply current is found to be satisfactory as per the IEEE-519 standards.
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基于神经网络控制的三相并网光伏阵列性能分析
三相并联有源电力滤波器(SAPF)被广泛用于注入所需的补偿电流,以消除非线性负载产生的电流谐波,恢复电源的正弦波形。本文分析了一种三相并网光伏阵列的开发,产生基于P&O算法的MPPT跟踪直流电,由锁相环控制的VSI提供与串联电感组成的SAPF连接的NLL,基于ANN的自支撑直流链路电容连接到基于IGBT的电流控制VSI补偿线路中负载感应电流谐波。开发的SAPF工作于瞬时有功和无功功率测量,以计算HBCC的参考电流,从而为逆变器产生门脉。在MATLAB 17a Simulink中开发了该模型,并实现了基于神经网络的Levenberg Marquardt训练算法来调节直流链路电容电压。仿真结果表明,所提出的控制技术能够快速灵活地对三相补偿电网系统进行动态响应,并且供电电流的总谐波失真符合IEEE-519标准。
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