中国电力 ›› 2018, Vol. 51 ›› Issue (4): 27-32.DOI: 10.11930/j.issn.1004-9649.20160024

• 电网 • 上一篇    下一篇

基于灰色经验融合的电网故障研判模型

吕小红, 张敏, 曹文忠, 熊来红   

  1. 国网重庆市电力公司, 重庆 400014
  • 收稿日期:2016-05-21 修回日期:2017-10-27 出版日期:2018-04-05 发布日期:2018-04-12
  • 作者简介:吕小红(1981-),女,四川广安人,高级工程师,从事智能电网管理研究,E-mail:lvxiaohong198108@sina.com。
  • 基金资助:
    重庆国电科技基金项目(ZD2015072)。

Research on Power Grid Fault Judgment Model Based on Gray Experience Fusion

LV Xiaohong, ZHANG Min, CAO Wenzhong, XIONG Laihong   

  1. State Grid Chongqing Electric Power Company, Chongqing 400014, China
  • Received:2016-05-21 Revised:2017-10-27 Online:2018-04-05 Published:2018-04-12
  • Supported by:
    This work is supported by Chongqing Science and Technology Fund Project of Electric Power (No.ZD2015072).

摘要: 针对电网故障检测系统中既有专家经验与处置方案难以充分利用的问题,提出了基于灰色经验融合的电网故障研判模型,并给出了该模型的框架结构、处理流程以及主要算法。该模型采用灰色信息融合方法实现专家经验与现场数据的融合,使用灰色聚类匹配算法抽取与现场数据高度相似的专家经验,实现当前故障的研判,并将最终的研判结果、处置方案与检测数据融合,促进专家经验库的优化。对比试验结果表明,该模型具有较高的研判精度、较为全面的故障覆盖度以及良好的时效性。

关键词: 故障检测, 电网, 灰色关联, 信息融合, 研判模型

Abstract: In order to deal with the difference between power grid fault judgment experience and field data, a novel model is proposed for power grid fault judgment based on gray experience fusion, and its frameworks, processing flow and main algorithms are presented. The model utilizes the gray information fusion method to integrate the expert experience and field data. Then the cluster matching method is used to extract the expert experience that is highly similar to the field data and to realize the judgment of present faults. In the end, the expertise database is optimized through integration of the final judgment results, disposal schemes and field data. Comparative experiment illustrates that the model has high fault judgment accuracy, comprehensive fault coverage and better time effectiveness.

Key words: fault judgment, power grid, gray correlation, information fusion, judgment model

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