【摘要】：PSD-BPA在中國電力系統(tǒng)仿真計(jì)算中被廣泛應(yīng)用,但由于其數(shù)據(jù)格式的特殊性,往往容易出現(xiàn)許多人為原因的數(shù)據(jù)錯(cuò)誤,這給仿真計(jì)算結(jié)果的準(zhǔn)確性與可靠性帶來了極大的隱患。首先,在給出變壓器不良漏抗參數(shù)辨識(shí)步驟的基礎(chǔ)上,結(jié)合PSD-BPA潮流數(shù)據(jù)中變壓器參數(shù)數(shù)據(jù)的特點(diǎn),提出了考慮特征相似度的具有噪聲的基于密度的聚類(DBSCAN)改進(jìn)算法。其次,基于各類參數(shù)向量簇的各屬性最大相似系數(shù),計(jì)算獲得各類參數(shù)向量簇的典型特征向量。然后,基于各類的典型特征向量,針對(duì)聚類結(jié)果中的噪聲簇,提出了基于離群系數(shù)的可疑不良數(shù)據(jù)分布模型;在此基礎(chǔ)上,結(jié)合分布規(guī)律,提出了基于可疑度的不良參數(shù)判別方法。最后,通過實(shí)際算例驗(yàn)證了所述模型與方法的有效性。
[Abstract]:PSD-BPA is widely used in power system simulation calculation in China, but because of the particularity of its data format, it is prone to many man-made data errors, which brings great hidden trouble to the accuracy and reliability of simulation results. Firstly, based on the identification steps of transformer bad leakage reactance parameters and considering the characteristics of transformer parameter data in PSD-BPA power flow data, an improved (DBSCAN) clustering algorithm with noise based on density is proposed, which takes into account the similarity of features. Secondly, based on the maximum similarity coefficient of each attribute of all kinds of parameter vector clusters, the typical characteristic vectors of various parameter vector clusters are obtained. Then, based on the typical feature vectors, the distribution model of suspicious bad data based on outlier coefficients is proposed for the noise clusters in the clustering results. On this basis, combined with the distribution law, a method of identifying bad parameters based on the degree of doubt is proposed. Finally, the effectiveness of the proposed model and method is verified by a practical example.
【作者單位】： 華北電力大學(xué)電氣與電子工程學(xué)院;國網(wǎng)江蘇省電力公司;國網(wǎng)北京經(jīng)濟(jì)技術(shù)研究院輸電網(wǎng)規(guī)劃中心;
【分類號(hào)】：TM41
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本文編號(hào)：2424401