Suzhou Electric Appliance Research Institute
期刊號: CN32-1800/TM| ISSN1007-3175

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基于BP神經(jīng)網(wǎng)絡(luò)的低壓變頻器電壓暫降耐受能力評估

來源:電工電氣發(fā)布時間:2023-12-28 12:28 瀏覽次數(shù):151

基于BP神經(jīng)網(wǎng)絡(luò)的低壓變頻器電壓暫降耐受能力評估

郭微,楊家豪
(廈門大學(xué)嘉庚學(xué)院 機電工程與自動化學(xué)院,福建 漳州 363105)
 
    摘 要:針對電壓暫降在工程中對變頻調(diào)速系統(tǒng)有較大影響的問題,利用 BP 神經(jīng)網(wǎng)絡(luò)對低壓變頻器遭受電壓暫降后的直流側(cè)電壓進行預(yù)測,建立負載功率、直流側(cè)電容、暫降深度、持續(xù)時間 4 個參數(shù)與變頻器直流側(cè)電壓的非線性映射關(guān)系?;?MATLAB/Simulink 軟件建立仿真模型,調(diào)節(jié) 4 個參數(shù)進行批量化仿真,針對不同電壓暫降類型獲得充足的數(shù)據(jù)樣本,建立 BP 神經(jīng)網(wǎng)絡(luò)進行預(yù)測,通過將直流側(cè)電壓預(yù)測值與保護定值作比較,評估低壓變頻器的電壓暫降耐受能力。算例結(jié)果表明,BP 神經(jīng)網(wǎng)絡(luò)模型預(yù)測精度較高,能夠準確預(yù)測直流側(cè)電壓值,從而判斷低壓變頻器遭受電壓暫降后的保護動作情況。
    關(guān)鍵詞: 電壓暫降;BP 神經(jīng)網(wǎng)絡(luò);低壓變頻器;耐受能力
    中圖分類號:TM714 ;TN773     文獻標(biāo)識碼:A     文章編號:1007-3175(2023)12-0049-05
 
Assessment of Voltagesag Tolerance of Low-Voltage Convertor
Based on BP Neural Network
 
GUO Wei, YANG Jia-hao
(School of Mechanical and Electrical Engineering & Automation, Xiamen University Tan Kah Kee College, Zhangzhou 363105, China)
 
    Abstract: In view of the problem that voltagesag has a great impact on the frequency conversion speed regulation system in engineering,the BP neural network is used to predict the DC side voltage after voltagesag of low-voltage convertor, and the nonlinear mapping relationship of load power, DC side capacitor, depth of voltage dip, duration and the DC side voltage of the convertor is established. First, the simulation model was built based on MATLAB/Simulink, four parameters were adjusted for mass simulation, sufficient data samples were obtained for different types of voltagesag. Then, the BP neural network was established for prediction, the voltagesag tolerance of low-voltage convertor was evaluated by comparing the DC side voltage predicted and protecteed value. The results show that the BP neural network model has high prediction accuracy and can accurately predict the DC side voltage value, so as to judge the protection action of low-voltage convertor after voltage sag.
    Key words: voltagesag; BP neural network; low-voltage convertor; tolerance
 
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