Insulation Condition Assessment Method of Power Transformer Based on Improved Extension Cloud Theory With Optimal Cloud Entropy

被引：0
|
作者：
Liu Y. [1 ,2 ]
Xu Z. [1 ]
Fu H. [1 ]
Li G. [3 ]
Gao S. [4 ]
机构：
[1] Hebei Provincial Key Laboratory of Power Transmission Equipment Security Defense, North China Electric Power University, Baoding
[2] State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing
[3] School of Computer and Control Engineering, North China Electric Power University, Baoding
[4] State Grid Hebei Electric Power Research Institute, Shijiazhuang
来源：
Gaodianya Jishu/High Voltage Engineering | 2020年 / 46卷 / 02期
关键词：
Combination weight; Extension cloud theory; Insulation condition assessment; Optimal cloud entropy; Transformer;
D O I：
10.13336/j.1003-6520.hve.20190215004
中图分类号：
学科分类号：
摘要：
Condition assessment is the key link in the condition maintenance and health management of the power equipment. Taking 220 kV oil-immersed transformers as the research object, we proposed an insulation condition assessment method based on improved extension cloud theory with optimal cloud entropy. Firstly, aiming at the randomness and fuzziness problem of insulation condition level boundary information, we constructed a basic theoretical framework of condition assessment based on extension cloud theory. Afterwards, considering the clarity and ambiguity of the grade division, we proposed a calculation method of optimal cloud entropy that can be adaptive to the evaluation object, and realized the improvement of the traditional extension cloud theory. Finally, in view of the shortcomings of subjective weighting method and objective weighting method, a combination weighting model based on fuzzy set-valued statistical method and entropy weight method was constructed to realize the dynamic adjustment of the index weight based on the degree of information change. Case studies and comparison analysis with traditional methods show that the proposed method can be adopted to effectively deal with the uncertainty factors in the insulation condition assessment, and its evaluation results are closer to the actual state of equipment, so the proposed method has a certain application feasibility. © 2020, High Voltage Engineering Editorial Department of CEPRI. All right reserved.
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页码：397 / 405
页数：8
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