S evidence theory artificial neural network trend analysis n
本文關鍵詞:人工神經(jīng)網(wǎng)絡和信息融合技術在變壓器狀態(tài)評估中的應用,由筆耕文化傳播整理發(fā)布。
人工神經(jīng)網(wǎng)絡和信息融合技術在變壓器狀態(tài)評估中的應用
Application of Artificial Neural Network and Information Fusion Technology in Power Transformer Condition Assessment
[1] [2] [3] [4] [5] [6]
RUAN Ling, XIE Qijia, GAO Shengyou, NIE Dexin, LU Wenhua, ZHANG Hailong (1. State Grid Key Laboratory of On-site Test Technology on High Voltage Power Apparatus, State Grid
[1]國網(wǎng)湖北省電力公司電力科學研究院國家電網(wǎng)公司高壓電氣設備現(xiàn)場試驗教術重點實驗室,武漢430077; [2]清華大學電機工程與應用電子技術系電力系統(tǒng)及發(fā)電設備控制和仿真國家重點實驗室,北京100084; [3]國網(wǎng)電力科學研究院,武漢430074
文章摘要:為滿足電力系統(tǒng)對變壓器資產(chǎn)管理和風險評估的需求,提出了一種基于人工神經(jīng)網(wǎng)絡和信息融合技術的變壓器狀態(tài)評估方法。以預防性試驗數(shù)據(jù)和在線監(jiān)測數(shù)據(jù)為例,選擇具有代表意義的信息量作為開展評估的靜態(tài)狀態(tài)量,,除此之外還選取部分靜態(tài)狀態(tài)量的變化趨勢作為開展評估的漸變狀態(tài)量,采用非線性指標評價函數(shù)對狀態(tài)量進行歸一化處理,綜合應用人工神經(jīng)網(wǎng)絡(朋州)和Dempster-Shafer(D.s)證據(jù)理論構(gòu)建多信息融合的變壓器狀態(tài)評估模型。通過對某臺500kV變壓器數(shù)據(jù)的實例分析,驗證了該評估模型應用于變壓器狀態(tài)評估中的有效性。該方法將在線監(jiān)測數(shù)據(jù)與部分參數(shù)的變化趨勢緊密結(jié)合,有助于提高變壓器狀態(tài)評估的時效性和準確性。
Abstr:To meet the needs of assets management and risk assessment for power transformers in power systems, we proposed a condition assessment method of power transformer based on artificial neural network and information fusion technology. Taking preventative test parameters and on-line monitoring parameters as the example, we chose some repre- sentative part of them as static condition parameters, and chose the variation trends of parts of the static condition parameters as trend condition parameters. We normalized these condition parameters using a nonlinear index evaluation function, and established a model of multi-information fusion transformer condition assessment based on the artificial neuron network (ANN) and Dempster-Shafer (D-S) evidence theory. Moreover, we analyzed data of an example from a 500 kV power transformer, and the results verified the effectiveness of the proposed model. It is concluded that combining on-line monitoring parameters and their variation trends, the proposed method is helpful to improving the accuracy and timeliness of transformer condition assessment.
文章關鍵詞:
Keyword::transformer condition assessment multi-information fusion D-S evidence theory artificial neural network trend analysis nonlinear index evaluate function
課題項目:國家電網(wǎng)公司科技項目(SGl0028);國網(wǎng)湖北省電力公司科技項目(201110101).
本文關鍵詞:人工神經(jīng)網(wǎng)絡和信息融合技術在變壓器狀態(tài)評估中的應用,由筆耕文化傳播整理發(fā)布。
本文編號:125320
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