【摘要】：為預(yù)測電網(wǎng)諧波,改進供電品質(zhì),本文根據(jù)電網(wǎng)諧波特性,建立了BP神經(jīng)網(wǎng)絡(luò)算法,對電網(wǎng)諧波樣本點進行了誤差訓(xùn)練,得到了諧波幅值變化特性。通過與標(biāo)準(zhǔn)值比較,表明:采用BP神經(jīng)網(wǎng)絡(luò)算法對諧波進行擬合能夠達(dá)到較高的準(zhǔn)確度。
[Abstract]:In order to predict the harmonics and improve the power supply quality, according to the harmonic characteristics of the power network, the BP neural network algorithm is established, and the error training of the harmonic sample points is carried out, and the variation characteristics of the harmonic amplitudes are obtained. By comparing with the standard values, it is shown that the BP neural network algorithm can achieve high accuracy in harmonic fitting.
【作者單位】： 鄭州大學(xué)體育學(xué)院;
【基金】：河南省教育廳科學(xué)技術(shù)研究重點項目(13B520253);河南省教育廳科學(xué)技術(shù)研究重點項目(13B890250)
【分類號】：TP183;U674.703.3
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本文編號：2461233