本文選題：神經(jīng)網(wǎng)絡(luò)　切入點：諧波　出處：《電測與儀表》2014年23期 　論文類型：期刊論文

【摘要】：為了提高諧波和間諧波分析的速度、精度和抗噪性能,將基于分段迭代的增強型Adaline神經(jīng)網(wǎng)絡(luò)應(yīng)用于電力系統(tǒng)諧波和間諧波分析。該網(wǎng)絡(luò)在加漢寧窗雙譜線插值FFT算法的基礎(chǔ)上,將采樣數(shù)據(jù)按采樣時間分段,依次用各段對應(yīng)的誤差信息來調(diào)整增強型Adaline神經(jīng)網(wǎng)絡(luò)的參數(shù)。該方法結(jié)合一點迭代法和全部點迭代法的優(yōu)點,既將各時段內(nèi)的誤差進行平均,減少噪聲對參數(shù)調(diào)整的影響,又充分保留誤差中包含的諧波和間諧波信息,提高網(wǎng)絡(luò)的精度。另外,根據(jù)參數(shù)估計誤差和頻率對誤差函數(shù)一階偏導(dǎo)之間的關(guān)系,提出修正信號幅值最大分量對應(yīng)的頻率調(diào)整量的處理方式,提高網(wǎng)絡(luò)的實時性和精度。仿真結(jié)果驗證了分析結(jié)論的正確性。
[Abstract]:In order to improve the speed, accuracy and anti-noise performance of harmonic and interharmonic analysis, an enhanced Adaline neural network based on piecewise iteration is applied to harmonic and interharmonic analysis of power system. The network is based on the FFT algorithm with double spectral lines interpolation. The parameters of the enhanced Adaline neural network are adjusted with the corresponding error information of each segment according to the sampling time segment. The method combines the advantages of the one-point iterative method and the all-point iterative method, and the errors in each period are averaged. The effect of noise on parameter adjustment is reduced, and the harmonic and interharmonic information contained in the error is fully preserved to improve the accuracy of the network. In addition, according to the relationship between the parameter estimation error and frequency to the first order partial derivative of the error function, In order to improve the real-time and accuracy of the network, the processing method of correcting the frequency adjuster corresponding to the maximum signal amplitude component is proposed. The simulation results verify the correctness of the analysis conclusion.
【作者單位】： 國網(wǎng)浙江建德市供電公司;重慶大學(xué)電氣工程學(xué)院輸配電裝備及系統(tǒng)安全與新技術(shù)國家重點實驗室;國網(wǎng)浙江杭州市余杭區(qū)供電公司;
【基金】：重慶市科技攻關(guān)資助項目(CSTC,2011AB3003) 國家“111”計劃資助項目(B08036)
【分類號】：TM711

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相關(guān)期刊論文 前5條

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本文編號：1595231