發(fā)布時(shí)間：2018-06-17 21:07

  本文選題：風(fēng)電輸出功率 + 自適應(yīng)神經(jīng)模糊推理系統(tǒng)　； 參考：《電力系統(tǒng)自動(dòng)化》2014年19期

【摘要】：風(fēng)電場(chǎng)風(fēng)電輸出功率數(shù)據(jù)的完整性在風(fēng)能利用中具有重要意義。利用相鄰風(fēng)機(jī)法、持續(xù)法、平均插值法、標(biāo)準(zhǔn)功率曲線對(duì)應(yīng)法均可以對(duì)風(fēng)電缺失功率數(shù)據(jù)進(jìn)行補(bǔ)齊,但都有各自的優(yōu)缺點(diǎn)及適用范圍;在單一補(bǔ)齊數(shù)據(jù)方法的基礎(chǔ)上,文中采用自適應(yīng)神經(jīng)模糊推理系統(tǒng)(ANFIS)模型對(duì)丟失數(shù)據(jù)進(jìn)行補(bǔ)齊和優(yōu)化。對(duì)實(shí)測(cè)數(shù)據(jù)的仿真計(jì)算結(jié)果表明,用所提出的方法進(jìn)行數(shù)據(jù)補(bǔ)齊后風(fēng)電輸出功率的計(jì)算結(jié)果平均相對(duì)誤差降低,準(zhǔn)確率提高。
[Abstract]:The integrity of wind power output data is of great significance in wind power utilization. By using adjacent fan method, continuous method, average interpolation method and standard power curve correspondence method, the missing power data of wind power can be compensated, but all of them have their own advantages and disadvantages and applicable range. In this paper, the adaptive neural fuzzy inference system (ANFIS) model is used to correct and optimize the lost data. The simulation results of the measured data show that the average relative error of the wind power output power is reduced and the accuracy is improved after the proposed method is used to correct the data.
【作者單位】： 東北電力大學(xué)電氣工程學(xué)院;
【基金】：國(guó)家重點(diǎn)基礎(chǔ)研究發(fā)展計(jì)劃(973計(jì)劃)資助項(xiàng)目(2013CB228201) 國(guó)家自然科學(xué)基金資助項(xiàng)目(51307017) 吉林省科技發(fā)展計(jì)劃資助項(xiàng)目(20140520129JH) 吉林省教育廳“十二五”科學(xué)技術(shù)研究項(xiàng)目(吉教科合字[2014]第474號(hào)) 吉林市科技發(fā)展計(jì)劃資助項(xiàng)目(2013625004)~~
【分類號(hào)】：TM614
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本文編號(hào)：2032453