Stability Analysis of LCL Grid-Connected Inverter Based on Neural Network

doi:10.16183/j.cnki.jsjtu.2023.653

Abstract

Abstract: The parameter uncertainty of LCL-type grid-connected inverter can significantly affect the power quality of renewable energy, so it is necessary to analyze the stability of the inverter under the parameter inception. Facing the above problems, the paper firstly establishes the state space model of LCL-type single-phase grid-connected inverter and proposes the neural network modeling method based on the parameter model. Through the parameter characterization, the training dataset based on the parameter distribution is obtained. This dataset is trained in the neural network to output the stability discrimination results. Finally, the effectiveness of the proposed method is verified by MATLAB/Simulink simulation and the experimental platform.

Key words: LCL type single-phased grid connected inverter, stability analysis, neural network, back propagation, binary classification

CLC Number:

TM464
TP183

HAN Hualing1, JIA Yichao1, MA Zihan2, 3, DENG Jun4, HUANG Meng2, 3. Stability Analysis of LCL Grid-Connected Inverter Based on Neural Network[J]. Journal of Shanghai Jiao Tong University, doi: 10.16183/j.cnki.jsjtu.2023.653.

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Stability Analysis of LCL Grid-Connected Inverter Based on Neural Network

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