Insulation Condition Assessment for Power Transformer Based on Normal Cloud Model with Optimal Variable Weights

ZHENG Like; LI Shuaibing; WANG Xiaodong; XIN Dongli; WU Guangning

doi:10.13296/j.1001-1609.hva.2016.02.014

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Insulation Condition Assessment for Power Transformer Based on Normal Cloud Model with Optimal Variable Weights

更新时间：2025-04-26

- Insulation Condition Assessment for Power Transformer Based on Normal Cloud Model with Optimal Variable Weights
- High VoltageApparatus Vol. 52, Issue 2, Pages: 85-92(2016)
- 作者机构：
  
  1. 国网四川省电力公司内江供电公司
  2. 西南交通大学电气工程学院
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2016.02.014
  CLC： TM855
- Published：2016
- 稿件说明：
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[1]郑理科,李帅兵,王晓东,辛东立,吴广宁.基于最优变权正态云模型的电力变压器绝缘状态评估[J].高压电器,2016,52(02):85-92.

ZHENG Like, LI Shuaibing, WANG Xiaodong, et al. Insulation Condition Assessment for Power Transformer Based on Normal Cloud Model with Optimal Variable Weights[J]. High voltageapparatus, 2016, 52(2): 85-92.
[1]郑理科,李帅兵,王晓东,辛东立,吴广宁.基于最优变权正态云模型的电力变压器绝缘状态评估[J].高压电器,2016,52(02):85-92. DOI： 10.13296/j.1001-1609.hva.2016.02.014.

ZHENG Like, LI Shuaibing, WANG Xiaodong, et al. Insulation Condition Assessment for Power Transformer Based on Normal Cloud Model with Optimal Variable Weights[J]. High voltageapparatus, 2016, 52(2): 85-92. DOI： 10.13296/j.1001-1609.hva.2016.02.014.

摘要

电力变压器整体绝缘状态评估过程中的主、客观因素并存

致使评价结果具有较大的随机性和不确定性。为此

笔者提出一种基于最优变权正态云模型的变压器绝缘状态评估策略。首先确定了绝缘状态评估指标体系

并基于复合二元语义实现了主观评估标度的定量转换

通过最优变权确定了各状态量的权重

在合理确定云模型数字特征的基础上

采用正态云模型描述绝缘状态评估中的模糊性与随机性

通过云运算确定绝缘状态及故障类型。实例分析验证了该方法的可行性

为针对性的变压器绝缘状态在线检修工作提供了一种新思路。

Abstract

In the condition assessment process of power transformers

the evaluation results have great randomness and uncertainty due to both subject and object factors coexist. An assessment strategy based on normal cloud model with optimal variable weights is proposed

which realizes the translation form qualitative to quantitative scale by using a compound two tuple method and optimal variable weights of each state quantity is determine

accordingly. A normal cloud model with reasonable digital characteristics is proposed to describe the fuzzy and random of the insulation condition. Then

the whole insulation condition and fault types of transformer are determined via cloud aggregation. Local case study proves the feasibility of the strategy proposed

which provides a new method for the targeted online insulation condition maintenance of power transformer.

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