一種新的電壓暫降事故源識(shí)別方法研究
蔣小偉，呂干云，武陽(yáng)
（南京工程學(xué)院 電力工程學(xué)院，江蘇 南京 211167）
摘 要：電壓暫降發(fā)生頻率高、影響范圍廣、造成危害大。針對(duì)電力監(jiān)測(cè)系統(tǒng)中帶有事故源信息的電壓暫降監(jiān)測(cè)數(shù)據(jù)非常有限且不易獲得的問題，提出了一種基于半監(jiān)督支持向量機(jī)的電壓暫降源識(shí)別方法。分析了各種電壓暫降事故源，利用短時(shí)傅里葉變換（STFT）對(duì)電壓暫降信號(hào)進(jìn)行時(shí)頻分析，提取出各類暫降特性參數(shù)，運(yùn)用半監(jiān)督支持向量機(jī)對(duì)其進(jìn)行訓(xùn)練與識(shí)別，實(shí)現(xiàn)在少量帶事故源標(biāo)簽電壓暫降監(jiān)測(cè)數(shù)據(jù)下電壓暫降源的可靠識(shí)別。算例結(jié)果顯示，在少量標(biāo)簽數(shù)據(jù)下半監(jiān)督支持向量機(jī)比傳統(tǒng)支持向量機(jī)具有更高的暫降源識(shí)別精度。
關(guān)鍵詞：電壓暫降；電壓暫降源識(shí)別；短時(shí)傅里葉變換；半監(jiān)督支持向量機(jī)；標(biāo)簽數(shù)據(jù)
中圖分類號(hào)：TM714 文獻(xiàn)標(biāo)識(shí)碼：A 文章編號(hào)：1007-3175(2018)05-0023-04
A New Kind of Method for Identification of Voltage Sags Accident Source
JIANG Xiao-wei, LV Gan-yun, WU Yang
（School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167 , China）
Abstract: Voltage sag has the characteristics of high frequency, wide influence and great harm, etc. This paper proposed a voltage sag source identification method based on the semi-supervised support vector machine (SVM) in view of the situation that the labeled data with accident source information was very limited and not easy to obtain in the power monitoring system. All kinds of voltage sag sources were analyzed. The short time Fourier transform (STFT) was used for time-frequency analysis. All kinds of voltage sag characteristic parameters were extracted and the semi-supervised SVM was adopted for training and identification to realize the reliable identification of voltage sag sources under the conditions that there was a small number of labeled voltage sag monitoring data. Example results show that the semisupervised SVM has higher identification accuracy than the traditional SVM in the case of a small number of labeled data.
Key words: voltage sag; identification of voltage sags source; short time Fourier transform; semi-supervised support vector machine; labeled data
參考文獻(xiàn)
[1] ZHANG Lidong, BOLLEN M H J.Characteristic of voltage dips in power system[J]. IEEE Transactions on Power Delivery，2000，15：827-832.
[2] 張波. 電壓暫降特征提取與擾動(dòng)原因分析[D]. 北京：中國(guó)電力科學(xué)研究院，2005.
[3] 劉奇，周雒維，盧偉國(guó). 基于廣義S變換的暫態(tài)電能質(zhì)量擾動(dòng)定位與識(shí)別[J]. 電力系統(tǒng)保護(hù)與控制，2012，40(7)：60-65.
[4] 呂干云，方奇品，蔡秀珊. 基于多分類支持向量機(jī)的電壓暫降源識(shí)別[J]. 電力系統(tǒng)保護(hù)與控制，2010，38(22)：151-155．
[5] 李國(guó)棟，丁寧，徐永海. 基于Mamdani型模糊推理的電壓暫降源識(shí)別[J]. 華北電力大學(xué)學(xué)報(bào)，2010，37(2)：43-48.
[6] 劉建偉，劉媛，羅雄麟. 半監(jiān)督學(xué)習(xí)方法[J]. 計(jì)算機(jī)學(xué)報(bào)，2015，38(8)：1592-1617.
[7] 王世旭，呂干云．基于標(biāo)簽傳播半監(jiān)督學(xué)習(xí)的電壓暫降源識(shí)別[J]. 電力系統(tǒng)及其自動(dòng)化學(xué)報(bào)，2013，25(4)：34-38．
[8] 徐志超，楊玲君，李曉明. 基于聚類改進(jìn)S變換與直接支持向量機(jī)的電能質(zhì)量擾動(dòng)識(shí)別[J]. 電力自動(dòng)化設(shè)備，2015，35(7)：50-58.
[9] 王學(xué)偉，張宏財(cái). 基于S變換和最小二乘支持向量機(jī)的電能質(zhì)量擾動(dòng)識(shí)別[J]. 電測(cè)與儀表，2009，46(8)：1-4.
[10] MELHORN C J, DAVIS T D, BEAM G E.Voltage sags：their impact on the utility and industrial customers[J]. IEEE Transactions on Industry Applications，1998，34(2)：549-558.
[11] 李昆侖，張偉，代運(yùn)娜. 基于Tri-training的半監(jiān)督SVM[J]. 計(jì)算機(jī)工程與應(yīng)用，2009，45(22)：103-106.
[12] CHEN K, WANG S.Semi-supervised learning via regularized boosting working on multiple semisupervised assumptions[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence，2011，33(1)：129-143.
[13] WANG Fei, ZHANG Changshui.Label propagation through linear neighborhoods[J]. IEEE Transactions on Knowledge and Date Engineering，2008，20(1)：55-67.
[14] 徐健，張語勍，李彥斌. 短時(shí)傅里葉變換和S變換用于檢測(cè)電壓暫降的對(duì)比研究[J]. 電力系統(tǒng)保護(hù)與控制，2014，42(24)：44-48.
