基于深度信念网络的变压器运行状态分析

Operation Condition Analysis of Transformer Based on Deep Belief Network

电力变压器作为整个电力系统的重要组成部分,承担着电网中电力传输和分配的工作,并且保证电压的有效转换,在电力服务中发挥着至关重要的作用。通过分析不同类型的运行状态下特征参量的特点,可以掌握变压器的运行变化,实现变压器故障的提前检测并做出相应预防性的措施,避免造成事故的发生。文中提出了一种基于深度信念网络的变压器运行状态分析方法。计算油中溶解气体的无编码特征比值,输入到深度信念网络中,挖掘数据信息与变压器运行状态之间的联系,判断变压器的运行状态。实验结果表明文中的方法具有较高的分析准确度。

The power transformer,as an important part of the entire power system,undertakes the work of powertransmission and distribution in the power grid,assures the effective conversion of voltage and therefore plays a vitalrole in power service.The operational variation of the transformer can be mastered by analyzing the feature of charac-teristic parameters at different types of operation conditions,the early detection on the fault of transformer is achievedand corresponding preventive measures are made so to avoid the occurrence of the fault.In this paper,a kind of opera-tion state analysis method of transformer based on deep belief network is proposed.The un-coded characteristic ratioof dissolved gases in the oil is calculated and input into the deep belief network so to explore the relationship betweenthe data information and the operation condition of transformer as well as judge the operation condition of the trans-former.It is shown by the experimental result that the method in this paper has higher analysis accuracy.