Implementation of MPPT technique for solar PV system using ANN

Suman Kumar Roy, Shoeb Hussain, M. A. Bazaz
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引用次数: 19

Abstract

This paper presents the use of two different methods of implementing Perturb and observe (P&O) algorithm for Maximum power point tracking (MPPT) of a Solar photovoltaic system (PV). One method includes the use of MATLAB FUNCTION BLOCK and other is by ANN (Artificial neural network). The system used comprises of a PV panel, MPPT algorithm and boost converter. The two control methods are used to provide the duty cycle to DC/DC boost converter. The simulation modelling is done in MATLAB and the corresponding results of two methods are presented. The fluctuations in output Voltage and Current of PV panel are minimized using Artificial neural network technique.
利用神经网络实现太阳能光伏系统的MPPT技术
针对太阳能光伏系统的最大功率点跟踪(MPPT)问题,提出了两种不同的扰动与观测(P&O)算法的实现方法。一种方法是利用MATLAB函数块,另一种方法是利用人工神经网络。该系统由光伏板、MPPT算法和升压变换器组成。这两种控制方法用于提供DC/DC升压变换器的占空比。在MATLAB中进行了仿真建模,并给出了两种方法的相应结果。采用人工神经网络技术对光伏板输出电压和电流的波动进行最小化。
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