電力系統(tǒng)諧波電流檢測的研究

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摘 要
本課題為黑龍江省教育廳科學(xué)技術(shù)研究項(xiàng)目。項(xiàng)目名稱為電氣系統(tǒng)高效低諧波系統(tǒng)優(yōu)化設(shè)計(jì)的研究，項(xiàng)目編號為：10551012
目前隨著電力電子技術(shù)的飛速發(fā)展，采用有源電力濾波器動(dòng)態(tài)抑制諧波成為重要的發(fā)展方向，它能克服傳統(tǒng)LC濾波器的缺陷。在我國有源電力濾波器的研究和開發(fā)正處于起始階段，至今還沒有大容量的有源電力濾波器的成熟產(chǎn)品問世，因此進(jìn)行有源電力濾波器的研究和開發(fā)工作有著非常重要的意義。
本文對有源電力濾波器的關(guān)鍵環(huán)節(jié)——主電路參數(shù)計(jì)算、諧波電流檢測和方法進(jìn)行了分析。重點(diǎn)是對諧波檢測的幾種方法進(jìn)行比較分析，提出了將神經(jīng)網(wǎng)絡(luò)與基于噪聲對消原理的自適應(yīng)諧波電流監(jiān)測方法相結(jié)合，應(yīng)用神經(jīng)網(wǎng)絡(luò)檢測快的特點(diǎn)，構(gòu)成神經(jīng)網(wǎng)絡(luò)諧波檢測方法，用于檢測總諧波電流。
同時(shí)，提出利用徑向基函數(shù)具有運(yùn)算量小、收斂快、無局部極小值等優(yōu)點(diǎn)，應(yīng)用徑向基函數(shù)神經(jīng)網(wǎng)絡(luò)，代替?zhèn)鹘y(tǒng)的BP神經(jīng)網(wǎng)絡(luò)，構(gòu)成一種新型的諧波檢測方法——基于徑向基函數(shù)神經(jīng)網(wǎng)絡(luò)的諧波電流監(jiān)測方法。分析了這種諧波檢測法的濾波原理，徑向基函數(shù)神經(jīng)網(wǎng)絡(luò)的結(jié)構(gòu)和權(quán)值調(diào)整的算法。
通過本文的研究工作，對有源電力濾波器實(shí)驗(yàn)系統(tǒng)的開發(fā)起到了一定的指導(dǎo)和參考作用。

關(guān)鍵詞：諧波，有源電力濾波器，徑向基函數(shù)神經(jīng)網(wǎng)絡(luò)，滯環(huán)電流控制方法，諧波電流檢測

Abstract
This topic for Heilongjiang Province education department science and technology research project. The project name for the electrical system highly effective low overtone system optimization design research, the project serial number is: 10551012
Recently，with the quickly development of power electronic technology，Active power Filter(APF) is being an important way to eliminate harmonic dynamically. in china，the studies and exploitations in APF are at its beginning stage，and large capacity mature products have not been coming out yet，so the studies in APF have important significance.
In this paper，we analyze the keys of APF-----calculating the parameter of main circuit，harmonic current detecting and current tracking controlling. Neural network(NN) have the characteristic of detecting quickly，the emphasis is bring forward combining the neural network and auto adaptive harmonic current detecting based on the principle of noise each other eliminating----the detecting method of neural network，it is applied detecting the total harmonic current.
At the same time，because of Redial Basis Function is (RBF)characteristics----small calculative quantity，fast convergence，without local minimal point，we apply RBF neural network to replace the traditional Basis Propagation neural network，consisting assort of new method for harmonic detecting----RBFNN is harmonic current detecting，and analyzing its principle of filter，the structure of RBFNN and the arithmetic of adjective weights.
The studies in this paper have some guidance and references on the exploitation of the active power filter experimental system.

Key Words：harmonic；APF；RBF；the controlling method of feed beat current；Harmonic current examination

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