Article(id=1205158463295959817, tenantId=1146029695717560320, journalId=1189987059142926344, issueId=1205158458619306387, articleNumber=null, orderNo=null, doi=10.19457/j.1001-2095.dqcd24937, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1675612800000, receivedDateStr=2023-02-06, revisedDate=1678377600000, revisedDateStr=2023-03-10, acceptedDate=null, acceptedDateStr=null, onlineDate=1765261768411, onlineDateStr=2025-12-09, pubDate=1721404800000, pubDateStr=2024-07-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1765261768411, onlineIssueDateStr=2025-12-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1765261768411, creator=13701087609, updateTime=1765261768411, updator=13701087609, issue=Issue{id=1205158458619306387, tenantId=1146029695717560320, journalId=1189987059142926344, year='2024', volume='54', issue='7', pageStart='3', pageEnd='96', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1765261767296, creator=13701087609, updateTime=1765261938922, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1205159178575782323, tenantId=1146029695717560320, journalId=1189987059142926344, issueId=1205158458619306387, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1205159178575782324, tenantId=1146029695717560320, journalId=1189987059142926344, issueId=1205158458619306387, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=86, endPage=92, ext={EN=ArticleExt(id=1205158463576978198, articleId=1205158463295959817, tenantId=1146029695717560320, journalId=1189987059142926344, language=EN, title=Adaptive Active Arc Suppression Method for Single Phase Grounding in Distribution Network Based on S-transform Correlation Degree, columnId=null, journalTitle=Electric Drive, columnName=null, runingTitle=null, highlight=null, articleAbstract=

An adaptive active arc suppression method based on S-transform correlation degree for distribution network unidirectional grounding was proposed to effectively eliminate single-phase grounding fault arc in distribution network and improve power system stability. The time series data of zero-sequence current of distribution network lines were collected,the time-frequency information matrix of zero-sequence current through S-transformation was obtained,the correlation matrix of time-frequency information matrix between each line was calculated and obtained. Input the convolution neural network model,and output the single-phase grounding fault line selection results;the double closed-loop adaptive control method based on fuzzy quasi-PR and PI control was adopted in the fault line to inject zero-sequence current into the neutral point of the fault line of the distribution network,effectively control the phase and amplitude of the injected current,force the voltage value of the phase of the fault line of the distribution network to be 0,and complete the adaptive active arc suppression. The experimental results show that this method can effectively identify the single-phase grounding fault lines in the distribution network,realize the single-phase grounding adaptive active arc suppression,and complete the single-phase grounding adaptive active arc suppression work as soon as possible to ensure the safe and stable operation of the distribution network.

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提出了基于S变换相关度的配电网单向接地自适应有源消弧法,有效消除了配电网单相接地故障电弧,提升了电力系统稳定性。采集配电网线路零序电流时序数据,经S变换获取零序电流时频信息矩阵后,计算并获取各线路间时频信息矩阵相关度矩阵,输入卷积神经网络模型,输出单相接地故障选线结果;在故障线路采用基于模糊准PR与PI控制的双闭环自适应控制方法,向配电网故障线路中性点注入零序电流,有效控制注入电流相位以及幅值,迫使配电网故障线路所在相的电压值为0,完成自适应有源消弧。实验结果表明:该方法可有效识别配电网单相接地故障线路,实现配电网单相接地自适应有源消弧,且可尽快完成单相接地自适应有源消弧工作,保证配电网安全稳定运行。

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李运旺(1992—),男,硕士,工程师,主要研究方向为配电网继电保护与馈线自动化技术、城区配电自动化技术,Email:

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李运旺(1992—),男,硕士,工程师,主要研究方向为配电网继电保护与馈线自动化技术、城区配电自动化技术,Email:

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李运旺(1992—),男,硕士,工程师,主要研究方向为配电网继电保护与馈线自动化技术、城区配电自动化技术,Email:

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Single phase grounding fault line selection vector of distribution network

, figureFileSmall=null, figureFileBig=null, tableContent=
出线 元素值 出线 元素值
L1 0.036 9 L10 0.023 6
L2 0.826 9 L11 0.000 6
L3 0.365 4 L12 0.001 5
L4 0.006 5 L13 0.039 8
L5 0.012 3 L14 0.635 4
L6 0.023 1 L15 0.225 8
L7 0.000 9 L16 0.302 1
L8 0.008 9 L17 0.006 6
L9 0.008 9 L18 0.000 8
), ArticleFig(id=1205208443033465522, tenantId=1146029695717560320, journalId=1189987059142926344, articleId=1205158463295959817, language=CN, label=表1, caption=

配电网单相接地故障选线向量

, figureFileSmall=null, figureFileBig=null, tableContent=
出线 元素值 出线 元素值
L1 0.036 9 L10 0.023 6
L2 0.826 9 L11 0.000 6
L3 0.365 4 L12 0.001 5
L4 0.006 5 L13 0.039 8
L5 0.012 3 L14 0.635 4
L6 0.023 1 L15 0.225 8
L7 0.000 9 L16 0.302 1
L8 0.008 9 L17 0.006 6
L9 0.008 9 L18 0.000 8
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基于S变换相关度的配电网单相接地自适应有源消弧法
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李运旺 , 陈俊德 , 张大平 , 桑云 , 韩晓蕾
电气传动 | 可靠性与诊断 2024,54(7): 86-92
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电气传动 | 可靠性与诊断 2024, 54(7): 86-92
基于S变换相关度的配电网单相接地自适应有源消弧法
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李运旺 , 陈俊德, 张大平, 桑云, 韩晓蕾
作者信息
  • 国网西宁供电公司,青海 西宁 810003
  • 李运旺(1992—),男,硕士,工程师,主要研究方向为配电网继电保护与馈线自动化技术、城区配电自动化技术,Email:

Adaptive Active Arc Suppression Method for Single Phase Grounding in Distribution Network Based on S-transform Correlation Degree
Yunwang LI , Junde CHEN, Daping ZHANG, Yun SANG, Xiaolei HAN
Affiliations
  • State Grid Xining Power Supply Company,Xining 810003,Qinghai,China
出版时间: 2024-07-20 doi: 10.19457/j.1001-2095.dqcd24937
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提出了基于S变换相关度的配电网单向接地自适应有源消弧法,有效消除了配电网单相接地故障电弧,提升了电力系统稳定性。采集配电网线路零序电流时序数据,经S变换获取零序电流时频信息矩阵后,计算并获取各线路间时频信息矩阵相关度矩阵,输入卷积神经网络模型,输出单相接地故障选线结果;在故障线路采用基于模糊准PR与PI控制的双闭环自适应控制方法,向配电网故障线路中性点注入零序电流,有效控制注入电流相位以及幅值,迫使配电网故障线路所在相的电压值为0,完成自适应有源消弧。实验结果表明:该方法可有效识别配电网单相接地故障线路,实现配电网单相接地自适应有源消弧,且可尽快完成单相接地自适应有源消弧工作,保证配电网安全稳定运行。

S变换  /  相关度  /  配电网  /  单相接地故障  /  自适应  /  有源消弧

An adaptive active arc suppression method based on S-transform correlation degree for distribution network unidirectional grounding was proposed to effectively eliminate single-phase grounding fault arc in distribution network and improve power system stability. The time series data of zero-sequence current of distribution network lines were collected,the time-frequency information matrix of zero-sequence current through S-transformation was obtained,the correlation matrix of time-frequency information matrix between each line was calculated and obtained. Input the convolution neural network model,and output the single-phase grounding fault line selection results;the double closed-loop adaptive control method based on fuzzy quasi-PR and PI control was adopted in the fault line to inject zero-sequence current into the neutral point of the fault line of the distribution network,effectively control the phase and amplitude of the injected current,force the voltage value of the phase of the fault line of the distribution network to be 0,and complete the adaptive active arc suppression. The experimental results show that this method can effectively identify the single-phase grounding fault lines in the distribution network,realize the single-phase grounding adaptive active arc suppression,and complete the single-phase grounding adaptive active arc suppression work as soon as possible to ensure the safe and stable operation of the distribution network.

S-transformation  /  correlation degree  /  distribution network  /  single phase grounding fault  /  adaptive  /  active arc suppression
李运旺, 陈俊德, 张大平, 桑云, 韩晓蕾. 基于S变换相关度的配电网单相接地自适应有源消弧法. 电气传动, 2024 , 54 (7) : 86 -92 . DOI: 10.19457/j.1001-2095.dqcd24937
Yunwang LI, Junde CHEN, Daping ZHANG, Yun SANG, Xiaolei HAN. Adaptive Active Arc Suppression Method for Single Phase Grounding in Distribution Network Based on S-transform Correlation Degree[J]. Electric Drive, 2024 , 54 (7) : 86 -92 . DOI: 10.19457/j.1001-2095.dqcd24937
电力系统中线路状况错综复杂,加之一些不合理接地方式的应用,导致配电网单相接地故障时有发生[1-3]。故障电流的不断增大,使得配电网接地故障消弧能力难以满足实际工作需求,电弧不能有效消除的直接后果是引起大面积的停电事故,由此带来的经济损失不可估量[4-5]。基于此,非常有必要研究一种行之有效的配电网单相接地消弧方法,有效消除配电网单相接地故障电弧,保障电力系统稳定运行。
近年来,国内外诸多学者针对该问题,进行了大量研究,成果相当显著。颇受青睐的如李晖等[6]提出的基于故障距离的配电网单相接地有源消弧法、荣飞等[7]提出的基于混合补偿的配电网单相接地有源消弧法。前者使用二分法估计故障距离,并在获取合理的电压参考值后,以二分法所获距离估计值以及负荷阻抗为可靠依据,对电压参考值实施合理调整,最终利用逆变器对调整后参考电压进行有效跟踪,合理抑制配电网单相接地故障电流并且恢复电压,完成配电网单相接地故障有源消弧;后者使用线相变换器在中性点中反向植入配电网单相接地故障相电动势,并通过有源补偿装置对线相变换器左右量测产生的电压偏差执行补偿操作以及合理跟踪调控,最终使得有源装置处获得的总电压等同于配电网单相接地故障相电源处产生的相反电动势,完成配电网单相接地故障有源消弧。二者均可实现配电网单相接地故障有源消弧,但是没有对配电网单相接地故障线路的识别问题作相关论述,并且在实际的消弧控制过程中,需要对配电网中大量的参数进行测量,才能使消弧工作得以完成,在配电网单相接地有源消弧工作中,具有一定的局限性。
S变换方法能够有效依据相关度提取配电网电流的能量以及相位等特征,在配电网单相接地故障线路识别方面具有明显优势;模糊准双闭环控制方法可更高效、稳定与准确地对有源消弧装置执行控制操作,从而使配电网单相接地有源消弧工作得以顺利完成。为此,本文提出基于S变换相关度的配电网单相接地自适应有源消弧法,更为高效准确地完成配电网单相接地故障有源消弧工作。
应用S变换方法不仅可获取配电网在出现单相接地故障时所有配电线路中包含的暂态零序电流时频信息,就连发生、未发生单相接地故障配电线路中零序电流互反的特性也可被完整保留下来[8-9],因而,将S变换方法应用于配电网单相接地故障选线工作中,对于故障选线工作的完成大有裨益;卷积神经网络是一种拥有超强深度特征提取与学习能力的学习网络模型,将其应用于接地故障选线工作中,可完美呈现接地线路故障特征与故障线路间的有效关联,更好完成配电网单相接地故障选线工作[10]。为此,本文在故障选线工作过程中,充分利用二者优势,合理准确识别配电网单相接地故障线路,具体的选线过程可归结如下:
1)在单向接地故障出现后,在一定的时间范围内,应用有效的采集技术采集全部线路中包含的零序电流时序数据,并对所获结果使用必要的手段执行归一化操作[11-12]。需要注意的是,采集的时间范围通常状况下为1周期。
2)对步骤1)中采集并归一化处理后的零序电流时序数据实施S变换获取零序电流时频信息矩阵,S变换过程可用公式表示为
s x ( τ ,   f ) = - x t ω ( t - τ ,   f ) e - j 2 π f t d t ω ( t - τ ,   f ) = f × 1 2 π e - f 2 τ - t 2 2
式中: x t为零序电流时序数据; s x ( τ ,   f ) x t经S变换获得的零序电流时频信息矩阵; f t分别为频率以及时间轴; τ为在 t上的高斯窗控制参数; ω ( t - τ ,   f )为高斯窗函数; e为指数函数。
3)计算配电网中各线路间时频信息矩阵的相关度。用 x y代表两条配电线路,分别将二者的零序电流数据标记成 x n × 1 y n × 1,在利用式(1)获得各自的时频信息矩阵后,对各自的时频信息矩阵实施欧式距离计算操作,将获得的欧式距离标记为 δ,那么 1 - δ即二者通过S变换获得的相关度,用 s x y代表。
4)根据步骤3)中获得的配电网线路时频信息矩阵相关度,构建相关度矩阵,构建的相关度矩阵用公式可表示为
$\boldsymbol{S}_{\mathrm{sel}}=\left[\begin{array}{ccc} \boldsymbol{s}_{11} & \ldots & \boldsymbol{s}_{1 n} \\ \vdots & \ddots & \vdots \\ \boldsymbol{s}_{n 1} & \ldots & \boldsymbol{s}_{n n} \end{array}\right] $
式中: S s e l为配电网线路时频信息相关度矩阵; s 1 n为所处行数是1、列数是 n的配电网线路时频信息相关度矩阵向量; s n 1 s n n分别为所处列数是1、以及第 n列配电网线路时频信息相关度矩阵向量。
5)S变换相关度与卷积神经网络配电网单相接地故障选线模型构建。构建的配电网单相接地故障选线模型如图1所示。
在构建的S变换相关度与卷积神经网络的配电网单相接地故障选线模型中,两个卷积层与两个池化层共同构成深层特征提取层。该层是模型的核心部分,其主要作用表现为:运用拥有 k 1 × k 1阶的卷积核对输入到网络中的配电网线路时频信息相关度矩阵通过下式执行滑步卷积操作:
Z o u t l = f Z i n l - 1 K c o r e l
式中: l为网络层序号; Z o u t l K c o r e l分别为所处网络层数序号为 l时的输出特征面以及卷积核矩阵; Z i n l - 1为所处网络层数序号为 l - 1时输出特征面; 为滑步卷积运算; f ·为激活函数。
与此同时,使用激活函数经过无数次的迭代,最终得到一次特征面;模型中的池化操作是由拥有 k 2 × k 2阶数的池化核通过下式完成的:
Z o u t l + 1 = f m e a n ( Z i n l K 1 k 2 )
式中: f m e a n 为均值函数。
池化核运用有效手段在降分辨率条件下,对经第一层卷积操作获取特征面,执行合理的采样操作,可得到二次特征面。
最终,通过模型中的全连接网络有效整合输出的最终特征面,可获得用于完成配电网单相接地故障选线工作的选线向量,将其标记为 O L,则 O L中的各元素便是配电线路发生单相接地故障可能性的代表,元素数值的高低代表各配电线路发生单相接地故障可能性的大小,在模型的Softmax层挑选 O L中元素值最高对应的配电线路,当作最终的配电网单相接地故障选线结果。
6)配电网单相接地选线结果获取。对步骤5)中构建的配电网接地故障选线模型实施有效的训练操作便可获取较为精确的配电网单相接地选项结果。具体的操作过程为:卷积核与池化核参数初始化。对两种参数执行初始化操作的目的是增强该网络模型的深度学习能力;在向前传播阶段,将配电网线路时频信息相关度矩阵样本输入到网络中,依次执行有效的特征获取以及分类等操作,最终获得实际的配电网单相接地故障选线向量 O L;在向后传播阶段,将模型输出结果、输入的配电网线路时频信息相关度矩阵训练样本标签误差进行合理的比较,并通过下式执行反向传播操作,以减小误差为主要目的,实施核参数调整,公式如下:
X i j ' = X i j + F B p ( α J 12 )
式中: X i j X i j '分别为经有效调整前、后获得的核参数; J 12为真实输出、模型训练样本数据标签产生的误差; α F B p ·分别为学习效率与反向传播运算。
利用脉宽调制有源逆变器完成配电网单相接地有源消弧工作的实质是:利用脉宽调制有源逆变器,将能够对幅值、相位实施有效控制的某一零序电流向配电网中性点执行合理注入操作,从而合理控制零序电压,有效抑制配电网单相接地故障点所处位置电流,使电弧无法具备重燃标准,最终将电弧去除的过程[13-15]。配电网单相接地有源电压消弧原理图如图2所示。
图2中, U S为电源输出电压;UT为变压器调整输出电压; U D C C D C分别为直流母线的电压、电容; R D C为直流母线电阻; L L p为获得的滤波电感以及消弧线圈电感; E A E B E C分别为有关 U S的电动势; U A U B U C以及 U N分别为三相电压以及中性点电压; r A r B r C分别为三个对地泄露电阻; R f为单相接地故障电阻; C A C B C C为三个对地电容。
根据基尔霍夫电流定律中的相关描述,有:
I = E A Y A + U N Y A + E B Y B + U N Y B + E C Y C + E C R f + U N Y C + U N R f + U N Y 0
其中
Y A = 1 r A + j ϑ C A Y B = 1 r B + j ϑ C B Y C = 1 r C + j ϑ C C Y 0 = - j ϑ L p
式中: I为向配电网注入的电流; Y A Y B Y C分别为三相对地参数导纳; Y 0为中性点对地导纳; ϑ为配电网基波电压角频率。
为了更好地完成配电网单向接地故障有源消弧工作,应使故障相电压 U C等于0,又由于 U C满足 U C = U N + E C,故有 U N = - E C。基于此,式(6)可转化为
I = E A Y A + E B Y B - E C ( Y A + Y B + Y 0 )
根据式(8)可得: I R f间并无相关性,而与 Y A Y B Y C Y 0以及相电压存在相关性。因而,在配电网单相接地有源消弧工作中,使用电流注入的方式,完成有源消弧切实可行。
根据2.1节对配电网单向接地故障有源消弧原理的分析可知,利用脉宽调制有源逆变器在配电网中注入的电流要受到配电网多种参数的影响,而在实际的工作中想要对各项参数进行准确测量难度系数十分大,几乎很难实现。为此,本文使用基于模糊准PR(比例谐振)与PI(比例积分)控制的双闭环自适应控制方法,充分利用双闭环控制技术的优势,在无需进行各项参数测量的状况下,使用反馈控制的方式,对单相接地故障线路的注入电流的相位以及幅值实施有效控制,迫使配电网故障所在相的电压值为0,从而自适应完成单相接地故障的有源消弧。
该控制方法的控制方式隶属串级控制,并将PI、模糊PR控制器分别作为内、外环控制装置,模糊准PR控制器主要是用来完成中性点电压控制工作,并将有效的参考电流向电流内环输送。模糊准PR控制器可有效抑制电压谐波,稳态性能较好;PI控制器在实施电流控制时具有高效率,可迅速做出控制响应。双闭环控制框图如图3所示。
图3中, Δ U 0 + ' Δ U 0分别为给定信号与真实状况下检测出的中性电压发生的变化量; I i * I i 分别为向有源消弧装置中注入的参考电流值与真实状况下检测出的真实注入电流值; Q 1 h Q 2 h分别为电流内、外环控制器传递函数; U为有源消弧装置交流侧电压值; Q I N V h为逆变器传递函数; Q R h为有关输出电压、注入电流的传递函数; Q h h为与配电网中性电压以及注入电流相关的传递函数; U 00为扰动信号; g为逆变侧的变压器变比。
在采用PI对电流内环实施控制进行消弧时,用到的传递函数用公式可表示为
Q 1 h = Q p I h = Ψ p + Ψ I Ψ p / h
式中: Ψ p Ψ I分别为PI控制比例系数以及积分系数; Q p I h Q 1 h为电流内环传递函数; h为传递速度。
用公式将有关逆变器注入到配电网中性点的零序电流以及内环参考电流的传递函数 I i h表示为
I i h = g Q P I h Q I N V h Q R h I i * h 1 + g Q P I h Q I N V h Q R h - Q R h U 00 h 1 + g Q P I h Q I N V h Q R h
式中: I i * h为有源消弧装置注入电流值以及内环参考电流间的传递函数; U 00 h为利用逆变器向中性点实施电流注入后扰动中性点电压与参考扰动电压间的传递函数。
为提高分析效率,在刚发生配电网单相接地故障时,可将该时刻的中性点电压做忽略处理,原因是此时的中性点电压大致等同于该系统内存在的扰动,该时刻的电流内环开环传递函数可描述为
R i n h = g Q P I h Q I N V h Q R h
式中: R i n h为刚发生配电网单向接地故障时电流内环开环的传递函数。
根据式(9)可进一步将式(11)描述为
R i n h = [ ( g Ψ p w m Ψ p + n Ψ p w m Ψ p Ψ I ) × ( L p C e q h 2 + R e p L p h + 1 ) ] ÷ h [ h L ( L p C e q h 2 + R e p L p h + 1 ) + L p h ]
式中: Ψ p w m R e p C e q分别为有源逆变器的比例系数、三相对地等效泄漏电阻与电容。
根据上述分析,用公式可将电流内环闭环传递函数描述成:
Q i n h = R i n h × 1 R i n h = [ ( g Ψ p w m Ψ p + n Ψ p w m Ψ p Ψ I ) × ( L p C e q h 2 + R e p L p h + 1 ) ] ÷ [ h 2 L ( L p C e q h 2 + R e p L p h + 1 ) + L p h 2 + ( g Ψ p w m Ψ p + n Ψ p w m Ψ p Ψ I ) × ( L p C e q h 2 + R e p L p h + 1 ) ]
用公式可将用于消弧的PR控制的传递函数表示为
Q 2 h = Q P R h = Ψ p + 2 Ψ r ϕ c h h 2 + 2 ϕ c h + ϕ 0 2
式中: Ψ r为谐振系数; ϕ c ϕ 0分别为截止频率与基波频率; Q 2 h Q P R h均为PR控制传递函数。
用公式将电压外环控制的闭环传递函数描述为
Q o u t h = Q P R h Q i n h Q h h 1 + Q P R h Q i n h Q h h
将对电压外环实施有效控制时用到的开环传递函数用公式表示为
R o u t h = Q P R h Q i n h Q h h
式中: Q o u t h R o u t h分别为双闭环控制系统闭环传递函数与电压外环控制开环传递函数; Q i n h为电流内环闭环传递函数。
结合PI,PR控制传递函数,将故障刚发生时产生的扰动因素忽略不计,将模糊准PR与PI控制双闭环自适应控制系统在闭环时使用的传递函数用公式描述为
Z = [ g Q 1 h Q 2 h Q I N V h Q h h ] ÷ [ 1 + g Q 1 h Q I N V h Q R h + g Q 1 h Q 2 h Q I N V h Q R h Q h h ]
通过式(17)完成单相接地故障线路的自适应有缘消弧。
在确定配电网以及PI控制器的参数后,需对 ϕ c Ψ p Ψ r三个PR控制参数执行有效的整定操作。 ϕ c是由配电网中能够容纳的最高波动频率决定的。在实际的工作中,配电网中的频率波动最高值约0.2 Hz左右,因此,通常设定 ϕ c的值为1.25 rad/s。 Ψ p Ψ r的取值是由系统的比例增益以及峰值增益决定的。 Ψ p Ψ r的取值是否合理,决定了能否更稳定准确地实施PR控制。通常状况下,当 Ψ p Ψ r的取值较大时,可提高PR控制的稳态精度,但是若出现取值过大的情况,则会使系统的稳定性产生一定程度的下降。在利用模糊准PR对电压外环实施有效控制时,向其输入的是给定的以及真实的中性点电压变化量间的误差 E以及误差变化率 E c,在将 E E c输入至模糊准PR电压外环控制系统后,输出的是与 Ψ p Ψ r相关的变化量,在本文中将二者的变化量标记为 Δ Ψ p Δ Ψ r。为有效提升电压外环模糊准PR控制效果, Ψ p Ψ r初值按专家模糊准PR参数调整规则自适应调整,用公式可将该过程表示为
Ψ p = Ψ p ' + Δ Ψ p Ψ r = Ψ r ' + Δ Ψ r
式中: Ψ p ' Ψ r '分别为给定的比例系数与谐振系数参考值。
综上,通过参数整定后的基于模糊准PR与PI控制的双闭环自适应控制方法实现单相接地故障线路的自适应有缘消弧,以降低单相接地故障对配电网的影响。
为验证本文方法在配电网单向接地有源消弧方面的有效性,以华东地区某一大型电力公司的配电网为实验对象,该配电网中包含编号为L1~L18的出线共18条。应用Matlab软件模拟使用本文方法对该配电网进行单向接地有源消弧时的控制过程,并进行相关的数据分析。控制过程中,将截止频率 ϕ c的值设置为1.25 rad/s,实施准比例谐振控制操作时用到的比例系数 Ψ p以及谐振系数 Ψ r初值按专家模糊准PR参数调整规则自适应调整。系统发生接地故障时,设定故障点的过渡电阻与中性点给定电压值分别为180 Ω和6 543 V,利用有源消弧装置对零序电流执行系统注入操作的时间为0.03 s。
表1是应用本文方法进行单相接地故障选线获得的配电网单相接地故障选线向量。
表1可以看出,出线L2的向量元素值最高,为应用本文方法进行单相接地故障选线获得的选线结果。实验证明:本文方法可以实现配电网单相接地故障选线,为实现配电网单相接地自适应有源消弧提供可靠参考与依据。
图4是应用本文方法对该配电网实施配电网单相接地自适应有源消弧获得的控制效果图。
分析图4a可知,在约0.03 s时,利用有源消弧装置将零序电流注入到系统后,系统迅速做出了反应,并在经过约0.06 s的响应后,中性点电压波形呈现出与零序电流注入前一样的平滑波形;在图4b的故障相母线电压图中,可观察到零序电流注入到系统后,有效钳制了故障相电压,电压值几乎为零。实验证明:应用本文方法可以实现配电网接地自适应有源消弧,有效消除配电网单相接地故障电弧,保障电力系统的稳定运行。
图5显示的是应用本文方法进行配电网单相接地故障自适应有源消弧后,获得的逆变器输出电流真实情况。
图5可以看出,本文方法在利用有源装置向故障线路注入零序电流初期,电流输出值比较大,这样可使中性点电压在最短时间内能够达到或者接近给定的电压参考值,从而达到快速完成配电网单相接地故障有源消弧工作的目的,实验结果表明,本文方法的应用效果较好,可尽快促使逆变器输出稳定电流。
应用本文方法可以实现配电网单相接地有源消弧,并且有源消弧效果较好,但是由于时间与条件有限,并未使用有源消弧装置与实际配电网完成对所提方法有效性的现场测试验证。下一阶段,在对本文方法的研究中,将对该方法进行现场测试,进一步验证本文方法在配电网单相接地有源消弧工作方面的优势。
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2024年第54卷第7期
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doi: 10.19457/j.1001-2095.dqcd24937
  • 接收时间:2023-02-06
  • 首发时间:2025-12-09
  • 出版时间:2024-07-20
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  • 收稿日期:2023-02-06
  • 修回日期:2023-03-10
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    国网西宁供电公司,青海 西宁 810003
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
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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
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