<dd id="mimiw"><samp id="mimiw"></samp></dd>

<address id="mimiw"><nav id="mimiw"><delect id="mimiw"></delect></nav></address>

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

    Article retrieval

    文章檢索

    首頁 >> 文章檢索 >> 往年索引

    一種基于ARMA模型的配電網(wǎng)饋線負(fù)荷預(yù)測方法

    來源:電工電氣發(fā)布時間:2017-01-24 14:24 瀏覽次數(shù):5
    一種基于ARMA模型的配電網(wǎng)饋線負(fù)荷預(yù)測方法
     
    李曉東1,陳中顯2
    (1 國網(wǎng)無錫供電公司,江蘇 無錫 214062;2 國網(wǎng)合肥供電公司,安徽 合肥 230022)
     
        摘 要:為了提高配電網(wǎng)系統(tǒng)的運行效率和穩(wěn)定性,在建立ARMA 模型的基礎(chǔ)上,對配電網(wǎng)饋線負(fù)荷進行預(yù)測和分析。建立了配電網(wǎng)饋線負(fù)荷數(shù)據(jù)序列及ARMA 模型,對饋線負(fù)荷數(shù)據(jù)序列的差分運算、標(biāo)準(zhǔn)化、自相關(guān)系數(shù)和偏相關(guān)系數(shù)進行分析,并采用ARMA 模型對未來某一時間段內(nèi)的配電網(wǎng)饋線負(fù)荷數(shù)據(jù)序列進行預(yù)測。算例結(jié)果分析表明,ARMA 模型預(yù)測值與實際值相符。
        關(guān)鍵詞:配電網(wǎng);饋線負(fù)荷預(yù)測;數(shù)據(jù)序列;ARMA 模型
        中圖分類號:TM715     文獻標(biāo)識碼:A     文章編號:1007-3175(2017)01-0035-03
     
    A Kind of Distribution Grid Feeder Load Forecasting Method Based on
    Auto-Regressive and Moving Average Model
     
    LI Xiao-dong1, CHEN Zhong-xian2
    (1 State Grid Wuxi Power Supply Company, Wuxi 214062, China; 2 State Grid Hefei Power Supply Company, Hefei 230022, China)
     
        Abstract: In order to improve the operational efficiency and stability of distribution grid system, this paper carried out prediction and analysis for distribution grid feeder load, based on the establishment of auto-regressive and moving average (ARMA) model. The distribution grid feeder load data series and the ARMA model were established to analyze the difference operation, standardization, autocorrelation coefficient and partial correlation coefficient of feeder load data series. The ARMA model was adopted to predict the distribution grid feeder load data series in certain period of time. The analysis results of calculation examples show that the prediction value of the ARMA model conforms to the actual value.
        Key words: distribution grid; feeder load forecasting; data series; auto-regressive and moving average model
     
    參考文獻
    [1] 游亞戈, 李偉, 劉偉民, 等. 海洋能發(fā)電技術(shù)的發(fā)展現(xiàn)狀與前景[J]. 電力系統(tǒng)自動化,2010,34(14):1-12.
    [2] 謝小偉. 地理信息系統(tǒng)在配電網(wǎng)中的應(yīng)用研究[D]. 杭州:浙江大學(xué),2010.
    [3] 萬國成,王漢華. 最小二乘法在配網(wǎng)饋線年度負(fù)荷預(yù)測中的應(yīng)用[J]. 電氣應(yīng)用,2008,27(9):32-34.
    [4] 張善文,雷英杰,馮有前.MATLAB 在時間序列分析中的應(yīng)用[M]. 西安:西安電子科技大學(xué)出版社,2007.
    [5] 亓四華,費業(yè)泰. 應(yīng)用時間序列移動平均模型預(yù)測加工精度的研究[J]. 計量與測試技術(shù),2002,29(2):12-13.
    亚洲无码av成人在线,亚洲影院AV无码一区二区,亚洲无码第二页,成人无码AV网站在线观看不卡 (function(){ var bp = document.createElement('script'); var curProtocol = window.location.protocol.split(':')[0]; if (curProtocol === 'https') { bp.src = 'https://zz.bdstatic.com/linksubmit/push.js'; } else { bp.src = 'http://push.zhanzhang.baidu.com/push.js'; } var s = document.getElementsByTagName("script")[0]; s.parentNode.insertBefore(bp, s); })();