电子器件2024，Vol.47Issue(1)：201-208,8.DOI:10.3969/j.issn.1005-9490.2024.01.034
基于长短期记忆网络-模糊控制的光伏最大功率点跟踪算法
Photovoltaic Maximum Power Point Tracking Algorithm Based on LSTM-FLC
摘要
Abstract
Photovoltaic array features nonlinear performance,and its maximum power point(MPP)will shift with environmental changes.Although the maximum power point tracking(MPPT)algorithm is widely used to track and predict the MPP of photovoltaic systems,it still faces challenges such as low dynamic quality and poor control accuracy of fuzzy logic control(FLC).To solve the problems men-tioned,a photovoltaic maximum power point tracking algorithm based on long-short term memory-flC(LSTM-FLC)is proposed.Firstly,the LSTM network predicts the MPP voltage by a time series method based on the light intensity and temperature datasets.Secondly,the deviation between the predicted voltage and the photovoltaic array voltage,as well as its derivative,are used as the input of FLC,and thus FLC is used to direct adjust the duty cycle of the boost converter.At the same time,the maximum and minimum duty ratios are pre-set to prevent the switch from being normally turned on.Simulation verification is carried out using MATLAB/Simulink under four varia-ble atmospheric conditions.Experimental results show that compared with LSTM,conductance incremental method,and genetic algo-rithm,the proposed MPPT algorithm has good tracking performance,stable accuracy,and efficiency,and takes the advantages of smoother waveform and smaller amplitude.关键词
长短期记忆网络/最大功率点跟踪算法/光伏系统/模糊控制/Boost变换器Key words
LSTM/MPPT/photovoltaic system/FLC/Boost converter分类
信息技术与安全科学引用本文复制引用
张秘源,蔡希彪,王新凯,张严,李洋洋,孙福明..基于长短期记忆网络-模糊控制的光伏最大功率点跟踪算法[J].电子器件,2024,47(1):201-208,8.基金项目
国家自然科学基金项目(61572244) （61572244）
辽宁省教育厅基本科研项目青年项目(LJKQZ2021142) （LJKQZ2021142）
