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基于全息時(shí)標量測數據挖掘的配電網(wǎng)設備健康狀態(tài)診斷分析
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南瑞集團(國網(wǎng)電力科學(xué)研究院)有限公司 、江蘇瑞中數據股份有限公司,

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HEALTH DIAGNOSIS METHOD OF POWER DISTRIBUTION EQUIPMENT BASED ON HOLOGRAPHIC TIME-SCALAR MEASUREMENT DATA
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    摘要:

    大數據、數據挖掘等新技術(shù)的出現和進(jìn)步,為建設智能配電網(wǎng)提供了新的技術(shù)手段。為實(shí)現對配電網(wǎng)運行狀態(tài)的真實(shí)還原、精細分析和精準預測,詳實(shí)有效的配電網(wǎng)設備運行數據記錄和支撐是關(guān)鍵,研究了配電網(wǎng)全息時(shí)標量測數據的變化即存儲技術(shù),基于全息時(shí)標量測數據研究了配電網(wǎng)設備健康狀態(tài)診斷的方法,對配電網(wǎng)歷史數據以及模型信息等進(jìn)行了深入的數據挖掘,通過(guò)聚類(lèi)分析、線(xiàn)性回歸算法、熵權法等建立了設備狀態(tài)診斷模型和評價(jià)體系,實(shí)現了對設備故障評估和預警分析等,為及時(shí)發(fā)現配電網(wǎng)的薄弱環(huán)節,保障配電網(wǎng)設備的安全穩定運行提供了有效手段。系統已在地市供電公司的配電網(wǎng)診斷方法研究與實(shí)現項目中得到實(shí)際應用,很好地滿(mǎn)足了地市供電公司的配電網(wǎng)精益化管理需求。

    Abstract:

    The emergence and progress of new technology, big data, data mining, provide a new technical means for building intelligent distribution network. In order to realize the real reduction, fine analysis and accurate prediction of the distribution network operation state, the real, detailed and effective distribution network equipment running data recording and support is the key. The technology of storing all changed data of holographic time-scalar measurement data of the distribution network is studied. On the basis of data recording, health diagnosis method of power distribution equipment is studied and in-depth data mining on the distribution history data and model information is carried out. The equipment state diagnosis model and the evaluation system are established by cluster analysis, linear regression algorithm and entropy method, and the equipment fault assessment and early warning analysis are realized. The weak links in distribution network can be found in time to ensure the safe and stable operation of the distribution equipment. The system has been applied in the construction project of research and implementation of distribution network diagnosis method based on big data technology of district power supply company. It can well meet the demand of lean management needs of distribution network of district power supply company.

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張珂珩,彭晨輝,趙康.基于全息時(shí)標量測數據挖掘的配電網(wǎng)設備健康狀態(tài)診斷分析計算機測量與控制[J].,2018,26(3):29-34.

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  • 收稿日期:2017-10-27
  • 最后修改日期:2018-02-02
  • 錄用日期:2017-11-24
  • 在線(xiàn)發(fā)布日期: 2018-03-29
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