Data Quality Assessment for Power Equipment Condition Based on Combination Weighing Method and Fuzzy Synthetic Evaluation

被引：0
|
作者：
Ji R. [1 ]
Hou H. [2 ]
Sheng G. [2 ]
Zhang L. [2 ]
Shu B. [2 ]
Jiang X. [2 ]
机构：
[1] College of Smart Energy, Shanghai Jiao Tong University, Shanghai
[2] Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai
来源：
Gaodianya Jishu/High Voltage Engineering | 2024年 / 50卷 / 01期
关键词：
data quality assessment; electrical equipment; entropy weight method; fuzzy analytic hierarchy process; fuzzy comprehensive evaluation; ig data;
D O I：
10.13336/j.1003-6520.hve.20221976
中图分类号：
学科分类号：
摘要：
With the increasing expansion of power network and the rapid development of industrial informatization, the amount of data collected and to be processed in the field of electric power shows explosive growth. Data loss, redundancy, exception, conflict and other problems are becoming increasingly prominent, affecting the quality of data. As a key part of ensuring data quality, data quality assessment plays an important role. In this paper, a data quality evaluation method is proposed for electrical equipment monitoring data. Five evaluation indexes including completeness, accuracy, uniqueness, consistency and timeliness are selected to construct a quality evaluation system, and evaluation rules for quantitative calculation are set up. The fuzzy analytic hierarchy process and entropy weight method are combined to determine the weight of each dimension, raising the scientificity of the data quality evaluation. Then the method of fuzzy comprehensive evaluation is used to determine the level of data quality based on membership function. Finally, the above method is used to evaluate the quality of oil chromatographic data in a local power grid. The score of data quality calculated by this method is 77.15, rated “medium”. The assessment result is consistent with the actual application situation and verifies that the method proposed in this paper is applicable to the data quality assessment of power equipment condition. © 2024 Science Press. All rights reserved.
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页码：274 / 282
页数：8
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