Contribution on the Combination of Artificial Neural Network and Incremental Conductance Method to MPPT Control Approach

Noureddine Akoubi, J. B. Salem, L. El Amraoui
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引用次数: 4

Abstract

This paper proposes a robust approach to design a maximum power point tracking (MPPT) controller based on artificial neural networks (ANN). This approach is developed by combining the incremental conductance (IC) method and ANN. The first step presents the MPPT control system using the conventional IC method (MPPT_IC). Then, a second step proposes an algorithm exploiting the IC method to generate the appropriate training data for the ANN. The results show the ability of the ANN controller (MPPT_ANN) to provide the best control performance under various solar irradiance and temperature values. Its effectiveness of tracking has been compared to the traditional MPPT_IC controller. The test results presented show the performance of the proposed MPPT_ANN controller. The study results are simulated and validated by MATLAB/Simulink software.
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人工神经网络与增量电导法相结合对MPPT控制方法的贡献
提出了一种基于人工神经网络(ANN)的最大功率点跟踪(MPPT)控制器的鲁棒设计方法。该方法是将增量电导(IC)法与人工神经网络相结合而发展起来的。第一步介绍了采用传统集成电路方法(MPPT_IC)的MPPT控制系统。然后,第二步提出了一种利用IC方法为人工神经网络生成适当训练数据的算法。结果表明,该神经网络控制器(MPPT_ANN)在不同的太阳辐照度和温度下都能提供最佳的控制性能。并与传统的MPPT_IC控制器进行了跟踪效果的比较。实验结果表明了所提出的MPPT_ANN控制器的性能。利用MATLAB/Simulink软件对研究结果进行了仿真验证。
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