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电力大数据:2019,22(11):-
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数据挖掘在变电站设备运维中的应用
张萌
(国网保定供电公司)
Application of data mining in operation and maintenance of substation equipment
zhangmeng
(State Grid BaoDing Power Supply Company)
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投稿时间:2019-06-19    修订日期:2019-08-05
中文摘要: 为解决变电运维工作中所获得的大量设备数据未能得到充分利用的问题,本文在搭建变电站云平台已成为可能的条件下,主要结合数据挖掘技术对运行人员从现场获得的数据进行分析处理。这些数据包括设备压力、泄漏电流、动作次数、以及设备台账等,可以用来提高工作效率和质量、进行业务决策,避免形成数据孤岛,提高变电运维的智能化水平。一是利用了趋势外推法进行数据拟合来指导设备巡视维护工作,二是采用多元线性回归法分析设备状态的影响因素并进行缺陷预测和故障诊断,三是通过人工神经网络深度学习进行电网停电承载力分析。合理利用大数据技术将推动变电站向集约化管控、专业化运维方向转变,通过数据挖掘技术可以极大地提升变电运维工作的智能化水平,从而优化人力配置,使工作更精准高效。
Abstract:In order to solve the problem that a large amount of equipment data obtained in the work of substation operation and maintenance is not fully utilized, in this paper, under the condition that the substation cloud platform has become possible, the data mining technology is mainly used to analyze and process the data obtained by the operators from the site. These data include equipment pressure, leakage current, number of actions, and equipment ledgers, which can be used to improve work efficiency and quality, make business decisions, avoid data islands, and improve the intelligent level of substation operation and maintenance. First, the trend extrapolation method is used for data fitting to guide the equipment inspection and maintenance work. Secondly, multiple linear regression method is used to analyze the influencing factors of equipment state and defect prediction and fault diagnosis. Thirdly, the artificial neural network is used for the analysis of power failure capacity. The rational use of data mining technology will promote the transformation of substation to the direction of intensive management and specialized operation and maintenance. Through data mining technology, the intelligent level of substation operation and maintenance work can be greatly improved, thereby optimizing manpower allocation and making work more precise and efficient.
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