基于多预测模型融合的电力变压器安全预判

doi:10.11930/j.issn.1004-9649.201907172

中国电力 ›› 2020, Vol. 53 ›› Issue (1): 72-80.DOI: 10.11930/j.issn.1004-9649.201907172

• 信息物理电力系统(CPPS)专栏 • 上一篇下一篇

基于多预测模型融合的电力变压器安全预判

李典阳^1,2, 张育杰¹, 王善渊¹, 冯健¹, 王洪哲², 秦领²

1. 东北大学信息科学与工程学院, 辽宁沈阳 110819;
2. 国网辽宁省电力有限公司, 辽宁沈阳 110006

收稿日期:2019-07-22 修回日期:2019-11-29 发布日期:2020-01-15
通讯作者: 李典阳(1987-),男,通信作者,博士研究生,高级工程师,从事电网运行及电力调度控制技术与应用等研究,E-mail:2824804703@qq.com
作者简介:张育杰(1996-),男,硕士研究生,从事电力设备故障诊断与状态预判等研究,E-mail:2841385779@qq.com;王善渊(1994-),男,硕士研究生,从事综合能源系统及电力输配网络自动化研究,E-mail:wsyneu@163.com
基金资助:
国家自然科学基金资助项目(61673093)

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

LI Dianyang^1,2, ZHANG Yujie¹, WANG Shanyuan¹, FENG Jian¹, WANG Hongzhe², QIN Ling²

1. College of Information Science and Engineering, Northeastern University, Shenyang 110819, China;
2. State Grid Shenyang Electric Power Co., Ltd., Shenyang 110004, China

Received:2019-07-22 Revised:2019-11-29 Published:2020-01-15
Supported by:
This work is supported by the National Natural Science Foundation of China (No. 61673093)

摘要/Abstract

摘要： 为解决传统分析措施未能将多源异类的数据信息纳入电网设备故障征兆分析及基于小样本单一算法难以较好应对多种故障类型设备诊断的问题，构建一种不同类型电网设备相关数据的统一化、标准化方法。采用卡方分布算法通过对数据相关性挖掘进行特定故障类型征兆集的选择，以避免层次分析法、格林兰验证等故障征兆集分析方法存在人工经验干扰。构建了一种多算法融合决策方法来避免单一算法决策的弊端。通过实例验证了对电力设备的单一故障类型寻找故障征兆集比针对设备选择故障征兆集具有更好的简约效果与预判准确率。实例还验证了所提融合算法效果好于单一算法。

关键词: 电力数据, 数据规范化, 征兆集选择, 融合决策, 事件模型

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

李典阳, 张育杰, 王善渊, 冯健, 王洪哲, 秦领. 基于多预测模型融合的电力变压器安全预判[J]. 中国电力, 2020, 53(1): 72-80.

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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链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.201907172

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

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基于多预测模型融合的电力变压器安全预判

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

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

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