Article(id=1241699532724040569, tenantId=1146029695717560320, journalId=1227999626482147330, issueId=1241699531444769296, articleNumber=null, orderNo=null, doi=10.16579/j.issn.1001.9669.2025.04.016, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1693411200000, receivedDateStr=2023-08-31, revisedDate=1695830400000, revisedDateStr=2023-09-28, acceptedDate=null, acceptedDateStr=null, onlineDate=1773973838263, onlineDateStr=2026-03-20, pubDate=1744646400000, pubDateStr=2025-04-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773973838263, onlineIssueDateStr=2026-03-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773973838263, creator=13701087609, updateTime=1773973838263, updator=13701087609, issue=Issue{id=1241699531444769296, tenantId=1146029695717560320, journalId=1227999626482147330, year='2025', volume='47', issue='4', pageStart='1', pageEnd='157', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773973837957, creator=13701087609, updateTime=1773974092709, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241700600002433947, tenantId=1146029695717560320, journalId=1227999626482147330, issueId=1241699531444769296, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241700600006628252, tenantId=1146029695717560320, journalId=1227999626482147330, issueId=1241699531444769296, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=131, endPage=138, ext={EN=ArticleExt(id=1241699532979893116, articleId=1241699532724040569, tenantId=1146029695717560320, journalId=1227999626482147330, language=EN, title=Structural stochastic reliability of testing transformers with impulse current under short-circuit condition based on the magnetic field-circuit coupling, columnId=1241699532912784251, journalTitle=Journal of Mechanical Strength, columnName=∙Optimization∙Reliability∙, runingTitle=null, highlight=null, articleAbstract=

Impulse current under short-circuit condition is the key factor for the structural reliability of the testing transformer. Therefore, the structural reliability analysis model of transformers was proposed based on the probability density evolution theory. Firstly, the basic principle of probability density evolution theory was introduced, and the analysis method of electromagnetic force field for windings was given considering the coupling effects of magnetic and electric fields. On the basis,the numerical analysis model of transformers structure was constructed by using the Abaqus software finite element analysis method. Taking an AGF 20 kV testing transformer as an example, the above model was validated. The longitudinal Mises stress of windings was chosen as the control variable, and the stress distribution and probability density evolution characteristics were given. Then, the structural reliability index was calculated, and the extreme mechanical response and the corresponding distribution zones of windings and iron cores were discussed. The results show that the stress of windings increases significantly under the action of short-circuit impulse current. The maximum value of windings’stress reaches 82%of the threshold, and plays the key role in structural reliability, the increase of impedance has obvious influence on the reliability of transformers.

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CHEN Zhiwei, E-mail:
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短路工况下的冲击电流是影响试验变压器结构可靠性的关键因素。因此,提出了基于概率密度演化理论的变压器结构可靠性分析模型。首先,介绍了概率密度演化理论的基本原理,给出了磁-电耦合下短路工况绕组电磁力场分析方法。以此为基础,利用Abaqus软件有限元分析方法构建了变压器结构力学数值分析模型。以某AGF型20 kV试验变压器为例,对上述模型进行了论证,选取绕组纵向Mises应力为模型控制变量,给出了结构的应力分布特征和概率密度演化特征,计算了可靠度指标,并进一步讨论了铁芯和绕组的力学极值响应和分布区域。结果表明,短路冲击电流作用下绕组应力显著提升,可达阈值的82%左右,是影响可靠性的控制因素,提高变压器阻抗对于提升可靠性有显著影响。

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陈志伟,男,1981年生,浙江磐安人,工程师;主要研究方向为变电运行维护检修、设备可靠性分析等;E-mail:

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陈志伟,男,1981年生,浙江磐安人,工程师;主要研究方向为变电运行维护检修、设备可靠性分析等;E-mail:

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陈志伟,男,1981年生,浙江磐安人,工程师;主要研究方向为变电运行维护检修、设备可靠性分析等;E-mail:

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Mechanical Science and Technology for Aerospace Engineering201029(5):690-694.(In Chinese), articleTitle=A study of the mechanism kinematic accuracy reliability by probability density evolution method, refAbstract=null)], funds=[Fund(id=1241699548876304740, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, awardId=51777119, language=EN, fundingSource=National Natural Science Foundation of China(51777119), fundOrder=null, country=null), Fund(id=1241699548955996521, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, awardId=51777119, language=CN, fundingSource=国家自然科学基金项目(51777119), fundOrder=null, country=null), Fund(id=1241699549060854124, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, awardId=CF058713002022002, language=EN, fundingSource=State Grid Zhejiang Electric Power Co., Ltd. Technology Project(CF058713002022002), fundOrder=null, country=null), Fund(id=1241699549161517425, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, awardId=CF058713002022002, language=CN, fundingSource=国网浙江省电力有限公司科技项目(CF058713002022002), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241699539967602703, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, xref=null, ext=[AuthorCompanyExt(id=1241699539971797008, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, companyId=1241699539967602703, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=State Grid Zhejiang Electric Power Co, Ltd Jinhua Power Supply Company, Jinhua 321000, China), AuthorCompanyExt(id=1241699539980185618, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, companyId=1241699539967602703, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=国网浙江省电力有限公司金华供电公司,金华 321000)])], figs=[ArticleFig(id=1241699544291930302, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, language=EN, label=Fig. 1, caption=Dynamic coupling field analysis model of windings, figureFileSmall=jZT+2Vukai2S71ONNANCpw==, figureFileBig=aAXJF1N3KNxHX51jJza9OQ==, tableContent=null), ArticleFig(id=1241699544371622084, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, language=CN, label=图1, caption=绕组动态耦合场分析模型, figureFileSmall=jZT+2Vukai2S71ONNANCpw==, figureFileBig=aAXJF1N3KNxHX51jJza9OQ==, tableContent=null), ArticleFig(id=1241699544602308814, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, language=EN, label=Fig. 2, caption=Numerical analysis model of transformer structural components, 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label=图10, caption=阻抗提高对可靠性的影响曲线, figureFileSmall=EOTgS8k2Kr7Dmba8O1/vSA==, figureFileBig=ywsI/hgWOVEpIcs2oU/vYw==, tableContent=null), ArticleFig(id=1241699548138107204, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, language=EN, label=Tab. 1, caption=

Basic random variable and its distribution

, figureFileSmall=null, figureFileBig=null, tableContent=
变量Variable分布类型
Distribution type
均值
Mean
变异系数
Coefficient of variation/%
绕组短路阻抗
Windings’ short-circuit impedance/Ω
正态分布
Normal distribution
0.082
绕组电阻率
Windings’ resistivity /(Ω/m)
正态分布
Normal distribution
0.0182
铁芯电阻率
Core resistivity /(Ω/m)
正态分布
Normal distribution
0.2202
绕组弹性模量
Modulus of elasticicity of windings /MPa
正态分布
Normal distribution
1.17×10115
铁芯弹性模量
Modulus of elasticicity of cores /MPa
正态分布
Normal distribution
2×10115
高压绕组横截面积
Cross-section area of high voltage windings /mm2
正态分布
Normal distribution
56.335
低压绕组横截面积
Cross-section area of low voltage windings/mm2
正态分布
Normal distribution
15.545
铁芯中心距Center distance of cores /mm正态分布
Normal distributio
755
), ArticleFig(id=1241699548297490765, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, language=CN, label=表1, caption=

基本随机变量及其分布

, figureFileSmall=null, figureFileBig=null, tableContent=
变量Variable分布类型
Distribution type
均值
Mean
变异系数
Coefficient of variation/%
绕组短路阻抗
Windings’ short-circuit impedance/Ω
正态分布
Normal distribution
0.082
绕组电阻率
Windings’ resistivity /(Ω/m)
正态分布
Normal distribution
0.0182
铁芯电阻率
Core resistivity /(Ω/m)
正态分布
Normal distribution
0.2202
绕组弹性模量
Modulus of elasticicity of windings /MPa
正态分布
Normal distribution
1.17×10115
铁芯弹性模量
Modulus of elasticicity of cores /MPa
正态分布
Normal distribution
2×10115
高压绕组横截面积
Cross-section area of high voltage windings /mm2
正态分布
Normal distribution
56.335
低压绕组横截面积
Cross-section area of low voltage windings/mm2
正态分布
Normal distribution
15.545
铁芯中心距Center distance of cores /mm正态分布
Normal distributio
755
), ArticleFig(id=1241699548523983186, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, language=EN, label=Tab. 2, caption=

Value range for relevant physical variables under short-circuit conditions

, figureFileSmall=null, figureFileBig=null, tableContent=
物理量Variable部件Component均值Mean变异性
Variability /%
分布范围Distribution range
横向拉应力
Transverse tensile stress/MPa
铁芯Core12.65.4两端连接处Connection at both ends
绕组Winding56.24.6下端底部Bottom of the lower end
纵向拉应力
Longitudinal tensile stress /MPa
铁芯Core14.56.6两端连接处Connection at both ends
绕组Winding82.67.2上下两端Two ends
变形量
Deformation /m
铁芯Core3.4×10-53.6顶端连接处Top connection
绕组Winding4.6×10-44.5外表面中部Middle of the outer surface
), ArticleFig(id=1241699548691755356, tenantId=1146029695717560320, journalId=1227999626482147330, articleId=1241699532724040569, language=CN, label=表2, caption=

短路工况下相关物理量的取值范围

, figureFileSmall=null, figureFileBig=null, tableContent=
物理量Variable部件Component均值Mean变异性
Variability /%
分布范围Distribution range
横向拉应力
Transverse tensile stress/MPa
铁芯Core12.65.4两端连接处Connection at both ends
绕组Winding56.24.6下端底部Bottom of the lower end
纵向拉应力
Longitudinal tensile stress /MPa
铁芯Core14.56.6两端连接处Connection at both ends
绕组Winding82.67.2上下两端Two ends
变形量
Deformation /m
铁芯Core3.4×10-53.6顶端连接处Top connection
绕组Winding4.6×10-44.5外表面中部Middle of the outer surface
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基于场路耦合的试验变压器短路冲击电流下结构随机可靠性
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陈志伟 , 吴雪峰 , 厉晓伟 , 潘仲达 , 吴胥阳
机械强度 | ·优化·可靠性· 2025,47(4): 131-138
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机械强度 | ·优化·可靠性· 2025, 47(4): 131-138
基于场路耦合的试验变压器短路冲击电流下结构随机可靠性
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陈志伟 , 吴雪峰, 厉晓伟, 潘仲达, 吴胥阳
作者信息
  • 国网浙江省电力有限公司金华供电公司,金华 321000
  • 陈志伟,男,1981年生,浙江磐安人,工程师;主要研究方向为变电运行维护检修、设备可靠性分析等;E-mail:

Structural stochastic reliability of testing transformers with impulse current under short-circuit condition based on the magnetic field-circuit coupling
Zhiwei CHEN , Xuefeng WU, Xiaowei LI, Zhongda PAN, Xuyang WU
Affiliations
  • State Grid Zhejiang Electric Power Co, Ltd Jinhua Power Supply Company, Jinhua 321000, China
出版时间: 2025-04-15 doi: 10.16579/j.issn.1001.9669.2025.04.016
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短路工况下的冲击电流是影响试验变压器结构可靠性的关键因素。因此,提出了基于概率密度演化理论的变压器结构可靠性分析模型。首先,介绍了概率密度演化理论的基本原理,给出了磁-电耦合下短路工况绕组电磁力场分析方法。以此为基础,利用Abaqus软件有限元分析方法构建了变压器结构力学数值分析模型。以某AGF型20 kV试验变压器为例,对上述模型进行了论证,选取绕组纵向Mises应力为模型控制变量,给出了结构的应力分布特征和概率密度演化特征,计算了可靠度指标,并进一步讨论了铁芯和绕组的力学极值响应和分布区域。结果表明,短路冲击电流作用下绕组应力显著提升,可达阈值的82%左右,是影响可靠性的控制因素,提高变压器阻抗对于提升可靠性有显著影响。

试验变压器  /  结构可靠性  /  绕组  /  概率密度演化  /  短路

Impulse current under short-circuit condition is the key factor for the structural reliability of the testing transformer. Therefore, the structural reliability analysis model of transformers was proposed based on the probability density evolution theory. Firstly, the basic principle of probability density evolution theory was introduced, and the analysis method of electromagnetic force field for windings was given considering the coupling effects of magnetic and electric fields. On the basis,the numerical analysis model of transformers structure was constructed by using the Abaqus software finite element analysis method. Taking an AGF 20 kV testing transformer as an example, the above model was validated. The longitudinal Mises stress of windings was chosen as the control variable, and the stress distribution and probability density evolution characteristics were given. Then, the structural reliability index was calculated, and the extreme mechanical response and the corresponding distribution zones of windings and iron cores were discussed. The results show that the stress of windings increases significantly under the action of short-circuit impulse current. The maximum value of windings’stress reaches 82%of the threshold, and plays the key role in structural reliability, the increase of impedance has obvious influence on the reliability of transformers.

Testing transformer  /  Structural reliability  /  Winding  /  Probability density evolution  /  Short-circuit
陈志伟, 吴雪峰, 厉晓伟, 潘仲达, 吴胥阳. 基于场路耦合的试验变压器短路冲击电流下结构随机可靠性. 机械强度, 2025 , 47 (4) : 131 -138 . DOI: 10.16579/j.issn.1001.9669.2025.04.016
Zhiwei CHEN, Xuefeng WU, Xiaowei LI, Zhongda PAN, Xuyang WU. Structural stochastic reliability of testing transformers with impulse current under short-circuit condition based on the magnetic field-circuit coupling[J]. Journal of Mechanical Strength, 2025 , 47 (4) : 131 -138 . DOI: 10.16579/j.issn.1001.9669.2025.04.016
试验变压器是电力预防性试验不可或缺的基础仪器,随着轻量化设计的要求日益提高,如何在轻量化结构设计下满足设备可靠性要求是一个重要课题[1-2]。铁芯和绕组是变压器内部的两个重要部件,两者通过电磁感应原理实现电压转换。正常情况下,磁场电磁力较小,对变压器结构产生的形变可忽略。然而,在发生短路时,绕组瞬时电流可达平时的数十倍,电磁力可达平时的数百倍,导致绕组在高温情形下产生变形[3-4],并进一步在铁芯和油箱外壳等部位造成应力集中,降低使用寿命。因此,提高短路故障下变压器的结构可靠性是一个重要课题。
近年来,诸多学者开始关注冲击电流下变压器内部结构的安全问题,尤其是试验变压器领域,由于设备小型轻量化需求,变压器绕组铁芯与固定件体积要求日益严苛,极易出现短路电流下结构机械强度不足而损伤的情形。经调研,现有研究主要集中于电磁力作用下绕组的受力分析层面,包括数值模拟分析和短路能力测试,根据分析结果给出结构的应力场,并提出优化措施。例如,张冰倩等[5]分析了匝间短路故障时的绕组多物理场特征,利用Ansys软件进行了场路耦合分析模型,揭示了故障时电磁、机械和温度等参数的分布规律。类似地,咸日常等[6-7]利用有限元分析方法建立了磁场-电路耦合分析模型,研究了不同工况下绕组的漏磁通密度与匝间短路故障时的电磁力。陈忠贤等[8]利用分布式光纤传感技术监测绕组变形,并进行了变形试验,实现了变形的初步定位。此外,近年来部分学者针对绕组故障诊断进行了研究,利用机器学习算法进行故障诊断,提高了智能运行维护水平,这类方法不仅包括设备振动等结构响应信息,还包括机电信号等信息,属于大数据分析方法[9-10]。然而,短路故障下的绕组结构安全分析涉及较多的不确定因素,包括结构形式、材料机械强度、磁场分布等,考虑随机性的结构可靠性分析目前基本处于空白状态。
上述问题的复杂性涉及两个方面,分别是可靠性分析算法和电磁场、应力场耦合动态分析模型。对于可靠性分析算法,由于多种不确定因素的存在,传统的分析方法(如蒙特卡洛模拟法、代理法等)存在组合爆炸问题,且在计算成本和分析精度之间存在难以协调的矛盾[11-12]。对于多场耦合动态分析模型,现有研究多将绕组视为静态组件,忽略了短路电流下的结构变形以及由此产生的磁动势不平衡问题,分析结果偏保守[13-15]
为此,本文将概率密度演化理论引入可靠性分析,并利用Abaqus软件有限元分析模型进行多场耦合下的结构数值模拟,给出短路工况下的结构最不利位置的概率密度函数,研究成果可为试验变压器结构设计和运行维护提供支撑。
LI等[16]提出了具有一般物理意义的工程结构广义概率密度演化方程,为随机非线性系统的可靠性分析提供了新思路。本文基于广义概率密度演化理论,考虑短路故障下结构机械强度和应力的一般性关系,建立概率密度演化方程。
对于任一随机动力系统,其应力控制方程可表达为
根据概率密度演化理论,结构应力Δσ随时间T的演化速度为
若Δσθ的联合概率密度函数为fΔσΘ(Δσθ),考虑到Δσ的随机性完全取决于基本随机变量θ,因此,系统增广矩阵(Δσθ)为保守系统。换言之,在演化过程中,该系统无随机变量的消失,也无其他随机变量的引入,是概率守恒系统。其概率密度演化方程的数学表达式为
系统初始条件为
式中,δ(·)为Dirac函数;fΘθ)为基本随机变量的概率密度函数。
系统边界条件为
联合式(3)~式(5),即可获得结构应力的概率密度函数,数学表达式为
式中,Ωθ为基本随机变量的可行域。
概率密度演化方程是1阶偏微分方程,可通过点演化方法进行求解,基本步骤[17]如下:
1)概率区间剖分及赋得概率。在Ωθ内取代表点θr=(θ1rθ2r,…,θnr),n为基本随机变量维度,r=1、2、…、RR为代表点个数。此时,概率密度函数可写为
式中,Ωi为离散区间,且满足∑Ωi = Ωθ
每组代表点的赋得概率为
2)点演化率。对于θr=(θ1rθ2r,…,θnr,)和T,联合式(2)可得点演化速度hθrT)。
3)概率密度演化方程求解。可利用有限差分法对概率密度演化方程进行求解,采用Lax-Wendroff差分格式,差分表达式为
4)代表点求和。对所有代表点进行累积求和,即可得到目标变量的概率密度函数,即
短路工况下,试验变压器所受电磁力受短路电流和漏磁通分布两者的共同影响,是一个多场耦合问题。由于变压器漏磁场有轴向和纵向之分,所以绕组结构受力也是双向的。根据Biot-Savart定律,绕组单元的电磁力荷载可表示为[18]
式中,FxFy分别为单元横向力和纵向力,N;Bx、By分别为横向和纵向平均漏磁场强度,A/m;j为电流密度,A/m2v为单元体积,m3m为计算区域内的单元数。
计算时,取三相短路对应的稳态电流,表达式为
式中,Kd为短路电流的冲击系数;U为阻抗电压,V;IN为额定电流,A;K为短路电流系数。
前已述及,短路时绕组在冲击电流作用下发生形变和位移,影响磁感应强度分布。根据式(11),电磁力大小与磁场强度B成正相关,因此,磁场分布的改变会进一步影响电磁力大小和绕组变形。换言之,绕组的应力场和磁场是动态耦合的。这一过程可用弹簧阻尼系统表示,如图1所示。对于第i个线饼而言,假设运动方向为zi,其动力学控制方程可表达为
式中,c为阻尼系数,N·s/m;t为时间,s;ki为刚度系数,N/m;mi为线饼质量,kg;Fi为电磁力,N。
求解上述微分方程即可获得任意时刻的绕组位移,由此修正电磁场及所受变形,从而解决多场耦合问题。
选取某20 kV试验变压器为研究对象,其主要部件包括器身、油箱、冷却装置、保护装置和出线装置等。由于本文关注变压器的受力行为,所以,选取主要绕组和铁芯等受力部件进行分析。其中,绕组材料为紫铜,并用聚脂漆包线,电导率为2.1×10-8 Ω·m。铁芯为芯式结构,硅钢片型号为30ZH110,厚度为0.4 mm,含硅量为5.4%。
短路时,一次绕组和二次绕组间的辐向力会向内压缩低压绕组,向外拉伸高压绕组,由此产生的轴向电磁力主要由铁芯承担。关于铁芯的受力规则目前尚无统一的分析方法,且考虑到模型较为复杂,本文采用Abaqus软件建立结构的数值分析模型,识别结构最不利位置。
根据部件几何形式,铁芯采用线性减缩积分单元(C3D8R),铁芯上下夹件采用壳体单元(S8R),绕组采用桁架单元(T2D2)。网格划分时,铁芯和夹件采用结构化网格划分法,绕组采用曲面逼近的自适应网格划分法,并利用中性轴算法提高网格质量[19]。在保障精度的同时,为降低计算成本,将绕组建模为饼式结构,将铁芯及夹件作为整体建模,并在网格划分时在不同部件处进行网格尺寸调节,总体布种间距控制在3~6 cm。图2为模型网格划分示意图。
数值仿真模型中工况模拟的关键在于确定高压绕组和低压绕组的自身电阻值及外接电阻值。以低压绕组为例,其接线形式如图3所示。根据技术手册可知,绕组的电阻率为0.018 Ω·mm2/m,横截面积为15.54 mm2,114匝,线圈总长为213 m。自身电阻值表达式为
式中,ρlA分别为低压绕组的电阻率、长度和截面积。
高压绕组自身电阻计算方式类似,不再赘述。对于外接电阻,为模拟短路工况,这里将其设置为0。短路工况模拟时间为0.25 s,时间步长为0.001 s。忽略不同铁芯绕组间的影响以及绕组谐波的影响。
尽管变压器的基本参数可根据铭牌确定,但实际运行过程中不可避免地存在随机性的影响,包括负载、出力、拓扑结构、材质等[20]。根据概率密度演化理论,需确定系统的基本随机变量,这里考虑3类随机性因素:①运行功能类,包括绕组短路阻抗、绕组电阻率、铁芯电阻率;②材质强度类,包括绕组弹性模量和铁芯弹性模量;③几何尺寸类,包括高压绕组横截面积、低压绕组横截面积和铁芯中心距。各变量的分布类型、均值和变异系数如表1所示。
表1中共有8个基本随机变量,需在8维概率空间进行选点。根据点演化方法需选取代表点[式(7)],需选取代表点108个。图4给出了高压绕组横截面积选点结果分布图。
图5给出了根据概率密度演化原理进行短路故障下变压器结构可靠性分析流程,该流程主要分为以下三步:①选取一组代表点,生成确定性系统,包括变压器设备几何尺寸、强度特征和荷载输入,荷载输入根据第2节内容确定;②利用Abaqus软件进行确定性系统有限元分析,提取结构应力应变信息;③对所有代表点进行上述分析,然后将所有分析结果代入概率密度演化方程[式(3)],即可获得短路工况下的结构可靠度。
以往研究表明,短路冲击电流下的绕组和铁芯的受力分布形式与正常工况下的基本相同,但幅值显著提升,薄弱环节出现在铁芯端部结构边缘部位和绕组两端底部。本文选取绕组的应力响应作为目标变量,主要原因包括两方面:①绕组是承受冲击电流的直接载体,容易产生过载并发生损伤;②与铁芯相比,绕组的弹性模量较低,同等应力水平下产生的变形量要更大[21-22]。为此,本文选取绕组的纵向Mises应力作为概率密度演化分析的目标函数,即式(1)中取Δσ=σMises
需要指出,根据国家标准GB 1094.5—2008,芯式变压器绕组导线的环形拉伸应力应不高于0.9Re,环形压缩应力不高于0.35Re,其中Re为屈服强度,根据铭牌获得,本例为150 MPa。因此,可靠性分析时应同时考虑纵向拉伸和纵向压缩两个方向的Mises应力,对应的应力阈值分别为135、52.5 MPa。图6给出了某次确定性分析时绕组纵向拉伸方向的应力分布云图。此外,尽管短路时绕组变形会增大,但尚在可接受范围内(图7),因此,也不作为分析的目标函数。
对108组确定性分析工况进行统计分析,短路工况下的绕组纵向Mises应力是正常工况下的5.6~7.8倍(均值7. 1倍),可到阈值的72%~104%(均值82%),存在失效风险。铁芯环向应力也有所增加,为阈值的25%~37%(均值29%),不会超过允许范围。此外,绕组应变增加幅值为35%~67%(均值45%),但极值小于1 mm,在可接受范围。
由于Mises应力为随机变量,并非式(3)中要求的随机过程,所以无法直接进行概率密度演化。为此,构造虚拟时间过程σMisesθτ)=σMisesθ)sin(0.1πτ),其中,τ为虚拟时间[23]。将该式代入式(3)进行概率密度演化,即可获得σMises的概率密度演化曲面。令τ=5 s,即可获得此时刻的概率密度曲线,最终积分可获得结构的可靠度。图8图9分别给出了σMises的概率密度曲面和等值线信息。经计算,此工况下的可靠度指标为0.954。此外,模型总体分析用时为67 min,涉及108个确定性系统的数值分析和概率密度演化分析,可见,该方法的分析效率较高。
除绕组纵向应力外,其他物理量虽然不是本案例中的目标变量,但分析其极值变化过程对运行维护亦是有益的。为此,对所有分析工况下的物理量取值进行了汇总,相关信息汇总于表2
表2可知,与绕组相比,铁芯的受力较小,且纵向应力较横向应力更高,进一步证实了所选择的目标变量的合理性。此外,铁芯的最不利位置主要集中在底部与部件连接部位,此处几何形式突变,容易产生应力集中现象,在运行维护过程中应予以关注和防护。此外,从变形量可知,短路工况下电磁力产生的变形主要集中在绕组部分,且最高值接近肉眼可见的程度,若考虑其他不确定性因素的影响,如电源电压、拓扑结构等,该因素可能成为可靠性分析的控制变量,应予以关注。
工程经验表明,采用高阻抗变压器或在变压器低压侧串联限流电抗器等措施可以降低短路失效风险,提高可靠性。这些措施的本质在于提高短路阻抗。因此,这里简要分析短路阻抗的提高对于可靠性的影响。共增加6组工况,阻抗提高幅度均为5%,分析结果如图10所示。由图10可知,随着阻抗的提高,试验变压器的结构可靠性不断提高,初期增长较快,后期增长较慢。当阻抗提高20%以后,变压器可靠性几乎不再变化,基本维持在0.995左右。
提出了短路冲击电流下试验变压器结构可靠性分析方法,得到主要结论如下:
1)利用概率密度演化理论,通过点演化方法可实现变压器结构可靠性的高效分析。
2)短路工况下,绕组Mises应力提高幅度较大,可达阈值的72%~104%,铁芯环向应力可达阈值的25%~37%,绕组变形量提高幅值35%~67%,不超过1 mm。
3)绕组的纵向Mises应力是变压器结构短路工况下的控制变量,可靠性指标为0.954。
4)铁芯和绕组的横向应力及变形量在短路工况下都有不同幅度的提高,主要分布在铁芯端部与结构连接处和绕组中部,运行维护时应予以重点关注。
5)短路阻抗的提高对于可靠性是有益的,后续可通过工程性措施提高变压器短路阻抗,例如绕组匝数和横截面积的增加、原材料的优化、采用磁屏蔽措施等。
  • 国家自然科学基金项目(51777119)
  • 国网浙江省电力有限公司科技项目(CF058713002022002)
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2025年第47卷第4期
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doi: 10.16579/j.issn.1001.9669.2025.04.016
  • 接收时间:2023-08-31
  • 首发时间:2026-03-20
  • 出版时间:2025-04-15
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  • 收稿日期:2023-08-31
  • 修回日期:2023-09-28
基金
National Natural Science Foundation of China(51777119)
国家自然科学基金项目(51777119)
State Grid Zhejiang Electric Power Co., Ltd. Technology Project(CF058713002022002)
国网浙江省电力有限公司科技项目(CF058713002022002)
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    国网浙江省电力有限公司金华供电公司,金华 321000
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Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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