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

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    基于監(jiān)測(cè)點(diǎn)數(shù)據(jù)分析的風(fēng)電場(chǎng)電壓暫降預(yù)警研究

    來(lái)源:電工電氣發(fā)布時(shí)間:2016-04-06 10:06 瀏覽次數(shù):22

    基于監(jiān)測(cè)點(diǎn)數(shù)據(jù)分析的風(fēng)電場(chǎng)電壓暫降預(yù)警研究 

    柏晶晶1,袁曉冬2,張帥1,柳偉1,陳兵2,顧偉1 
    1 東南大學(xué) 電氣工程學(xué)院,江蘇 南京 210096;
    2 江蘇省電力公司電力科學(xué)研究院,江蘇 南京 210036
     
     

    摘 要:對(duì)風(fēng)電場(chǎng)電壓暫降指標(biāo)進(jìn)行深入數(shù)據(jù)挖掘并給出適當(dāng)預(yù)警,可及時(shí)發(fā)現(xiàn)電網(wǎng)中已存在或潛在的電能質(zhì)量問(wèn)題并加以改善。利用改進(jìn)的AHP法確定電壓暫降各個(gè)特征量的權(quán)重,結(jié)合改進(jìn)的歐氏距離法計(jì)算出風(fēng)電場(chǎng)并網(wǎng)點(diǎn)電壓暫降監(jiān)測(cè)數(shù)據(jù)、自設(shè)等級(jí)限值以及前一段時(shí)間電壓暫降均值的距離系數(shù),進(jìn)而快速準(zhǔn)確地對(duì)風(fēng)電場(chǎng)電壓暫降干擾的真實(shí)水平做出及時(shí)預(yù)警。通過(guò)實(shí)例分析,證明了所提方法的實(shí)用性和高效率,可將其有效應(yīng)用于電能質(zhì)量異常數(shù)據(jù)預(yù)警系統(tǒng)。
    關(guān)鍵詞:風(fēng)電場(chǎng);電壓暫降;預(yù)警;改進(jìn)的歐氏距離法
    中圖分類(lèi)號(hào):TM614;TM712 文獻(xiàn)標(biāo)識(shí)碼:A 文章編號(hào):1007-3175(2014)04-0008-04


    Research on Early Warning of Wind Farm Voltage Sag Based on Monitored Data Analysis 

    BAI Jing-jing1, YUAN Xiao-dong2, ZHANG Shuai1, LIU Wei1, CHEN Bin2, GU Wei1 
    1 School of Electrical Engineering, Southeast University, Nanjing 210096, China;
    2 Jiangsu Electric Power Research Institute, Nanjing 210036, China
     
     

    Abstract: Further mining voltage sag index of wind farm and suitable early warning could make it possible to timely find the existed and potential power quality problems and to give warning prompts. The improved analytic hierarchy process (AHP) was used to determine the different characteristic weights of voltage sag. Combined with the improved Euclidean distance method, this paper calculate voltage sag monitoring data at wind farm grid points and disposed grading limited values and the distance coefficient of early voltage sag mean to carry out early warning quickly and correctly for the real level of voltage sag disturbance of wind farm. The cases analysis verifies that the proposed approach is useful and high efficient and it is possible to timely conduct power quality early warning for abnormal data.
                Key words: wind farm; voltage sag; early warning; improved Euclidean distance method


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