Safety Prejudging Method for Power Transformer Based on Multi-Prediction Model Fusion

doi:10.11930/j.issn.1004-9649.201907172

Abstract

Abstract: Fault diagnosis and pre-judgment of power grid equipment is an important guarantee for safe operation of power grids. There are many related factors for grid equipment faults. The conventional analytical measures have not considered integrating multi-source heterogeneous data into grid equipment fault cause analysis, and the small sample-based unitary algorithm cannot well deal with diagnosis of multi-type fault equipment. A unified and standardized method is presented in this paper for relevant data of different types of power grid equipment. To avoid the artificial experience interference of such fault cause analysis methods as the analytic hierarchy process and Greenland verification, the Chi-Square distribution algorithm is used to select the specific-type fault cause set through mining data correlation. A new multi-algorithm fusion decision method is proposed to avoid the drawback of unitary algorithm decision. It is verified through case study that the proposed fuse algorithm is better than the unitary algorithm in simpleness and pre-judgment accuracy.

Key words: power system data, data normalization, event-causes selection, multi-information fusion, event model

LI Dianyang, ZHANG Yujie, WANG Shanyuan, FENG Jian, WANG Hongzhe, QIN Ling. Safety Prejudging Method for Power Transformer Based on Multi-Prediction Model Fusion[J]. Electric Power, 2020, 53(1): 72-80.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.201907172

https://www.electricpower.com.cn/EN/Y2020/V53/I1/72

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