WO2022021740A1 - 基于区间斜率的配电网弧光高阻故障区段定位方法 - Google Patents
基于区间斜率的配电网弧光高阻故障区段定位方法 Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/086—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/088—Aspects of digital computing
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S10/52—Outage or fault management, e.g. fault detection or location
Definitions
- the invention relates to a distribution network fault location method, in particular to a distribution network arc high resistance fault location method based on interval slope.
- Arc high-resistance fault is a common form of distribution network fault.
- the overhead line is disconnected/dropped to the ground, or a tree barrier occurs, so that it contacts with a high-impedance grounding medium, resulting in a single-phase grounding fault.
- Common high-impedance grounding media include cement, sand, soil, rubber, asphalt, and trees. It is difficult to detect it with traditional overcurrent protection devices. Since a reliable connection cannot be formed between the wire and the grounding medium, the air gap always exists (except for water resistance), so the high-resistance fault often realizes the electrical connection between the line conductor and the grounding medium by arc.
- High-resistance faults are generally caused by the disconnection of overhead lines or tree barriers, and the contact between the conductor and the high-impedance grounding medium is generally unreliable. Air gaps generally exist between the conductor and the grounding medium or inside the grounding medium. Therefore, when a high-resistance grounding fault occurs, the electrical connection between the network and the earth is generally formed by an arc, so that both the fault current and the zero-sequence current will produce nonlinear waveform distortion.
- the waveform distortion of the zero-sequence current can be described by the slope. However, calculating the slope directly by derivation or difference is obviously highly susceptible to signal noise, which may come from background noise, measurement errors, or invalid distortion caused by arcing.
- the purpose of the present invention is to provide a reliable and effective method for locating arc high-resistance fault section of distribution network based on interval slope in order to overcome the above-mentioned defects of the prior art.
- a method for locating arc high-resistance fault sections in distribution network based on interval slope includes a fault detection process and a fault location process,
- the absolute value of the corresponding interval slope is obtained according to the collected zero-sequence current, and based on the absolute value of the interval slope, it is sequentially judged whether each cycle of the zero-sequence current has the arc high resistance fault feature, and will have the arc high resistance fault.
- the period of the fault feature is recorded as the fault period, and when the consecutive number of fault periods is greater than the set value, the fault location process is started;
- the fault section location is performed based on the synchronous zero-sequence current and zero-sequence voltage waveforms of each measurement point.
- the fault detection process includes the following steps:
- K set1 is the sensitivity coefficient
- Num c1 and Num c2 are the sampling points n c1 and n satisfying the following formulas respectively The number of c2 :
- K set2 is the sensitivity coefficient
- step 12 In the half-cycle interval [N 1 , N 2 ], the judgment process as in step 12) is adopted. If both half-cycle intervals satisfy the two criteria, it is judged that the cycle has arc high resistance fault characteristics, and record is the failure period;
- an improved robust local regression smoothing method based on the Grubbs criterion is used to process the sampled zero-sequence current.
- the improved robust local regression smoothing method based on the Grubbs criterion is specifically:
- the zero-sequence current is fitted to a polynomial according to the set fitting error, and the iterative screening idea and outlier screening principle of Grubbs method are introduced to iteratively update the fitting error weight coefficient wi and fitting coefficient ⁇ .
- step 2) a minimum value point n min is obtained in the interval [N 0 +d, N 1 -d], where d is an oscillation elimination parameter.
- the value range of the sensitivity coefficient K set1 is 0.80-0.85.
- the value range of the sensitivity coefficient K set2 is 0.08-0.12.
- the fault location process includes the following steps:
- the value of the coefficient c dir is determined according to different neutral point grounding methods, and is calculated from the u 0b interval slope curve:
- u 0b is the zero-sequence voltage at the bus.
- the present invention has the following beneficial effects:
- the present invention uses the absolute value of the interval slope as the judgment basis for the arc high resistance fault characteristics, which can overcome the influence of noise on the description of the distortion characteristics and improve the fault detection accuracy.
- the present invention is based on the least squares linear fitting, combined with the Grubbs rule and the robust local regression smoothing theory, to further eliminate the influence of noise.
- the present invention further determines the fault section from the original fault detection and line selection, realizes accurate and fast section location of the fault, and provides information support for section selection tripping and fault recovery.
- Fig. 1 is the absolute value curve of interval slope of the present invention, wherein, (1a) is under non-fault condition, and (1b) is under fault condition;
- Figure 2 is a schematic diagram of the effectiveness of LLSF and Grubbs-RLRS in describing the characteristics of the interval slope curve, where (2a) is the zero-sequence current waveform of the measured high resistance fault, (2b) is the derivative curve, and (2c) is the interval slope curve. (non-absolute value), (2d) is the absolute value curve of interval slope and distortion detection;
- FIG. 3 is a schematic flow chart of the present invention.
- this embodiment provides a method for locating arc high-resistance fault sections of distribution network based on interval slope.
- the method includes a fault detection process and a fault location process.
- the fault detection process according to the collected zero Obtain the absolute value of the corresponding interval slope of the sequence current. Based on the absolute value of the interval slope, it is judged whether each cycle of the zero sequence current has the arc high resistance fault characteristic, and the cycle with the arc high resistance fault characteristic is recorded as the fault cycle.
- the fault location process is started; in the fault location process, the fault segment location is performed based on the synchronous zero-sequence current and zero-sequence voltage waveforms of each measurement point.
- the high-resistance fault is generally caused by the disconnection of the overhead line or the tree barrier, and the conductor contacts with the high-impedance grounding medium. This contact is generally unreliable, and air gaps generally exist between the conductor and the grounding medium or inside the grounding medium. Therefore, when a high-resistance grounding fault occurs, the electrical connection between the network and the ground is generally formed by an arc, so that both the fault current and the zero-sequence current will produce nonlinear waveform distortion.
- the waveform distortion of the zero-sequence current can be described by the slope.
- calculating the slope directly by derivation or difference is obviously highly susceptible to signal noise, which may come from background noise, measurement errors, or invalid distortion caused by arcing.
- the interval slope is calculated based on the least squares linear fit.
- j 0, 1, ..., m ⁇ , so that ⁇ is the smallest.
- ⁇ ′ 0, so the calculated ⁇ can be expressed as:
- G p, N represents the threshold when the confidence coefficient is p, and p generally takes 90% to 99.5%.
- the absolute value curve of the interval slope can be calculated point by point And, it can also be calculated once every few points And use interpolation to obtain the curve to reduce the amount of calculation.
- Figure 2a shows the derivative curve of the zero-sequence current. It can be seen from the comparison that the interval slope curve calculated based on the linear least squares has better resistance to noise fluctuations, as shown in Figure (2c).
- Figure (2c) also proves the effect of Grubbs-RLRS method in eliminating the influence of impulse noise, so that the absolute value curve of the interval slope can correctly show the "double M" shape characteristic.
- the high-resistance fault detection can adopt the following process:
- Step 1 As shown in Figure (2d), for each cycle of the zero-sequence current, calculate the maximum and minimum points through FFT, and locate the minimum points N 1 and N 2 of the absolute value of the interval slope in the vicinity thereof.
- N 0 is the N 2 point of the previous cycle.
- the maximum and minimum values of the current are located to the minimum points N 1 and N 2 of the absolute value of the interval slope corresponding to the cycle to form an interval [N 1 , N 2 ], and the point N 2 obtained in the previous cycle is used.
- the interval [N 0 , N 1 ] is formed with the point N 1 of the current cycle. Therefore, each cycle can be bounded by the maximum and minimum values to obtain two intervals of about half-cycle length.
- Step 2 For the half-period interval [N 0 , N 1 ], n min is the minimum value point in the interval [N 0 +d, N 1 -d], and 2d is to avoid the calculation of the absolute value. There may be repeated oscillations around the zero-crossing point of .
- the half-period interval [N 0 , N 1 ] can be said to have nonlinear characteristics of high-resistance faults if and only if the following two criteria are established:
- K set1 is the sensitivity coefficient and is usually set to 0.80-0.85 to ensure the sensitivity and safety of detection at the same time.
- Num c1 and Num c2 are the numbers of sampling points n c1 and n c2 that satisfy formulas (7) and (8), respectively.
- K set2 is also a sensitivity coefficient, which is usually set to 0.10.
- Step 3 In the half-period interval [N 1 , N 2 ], adopt the same judgment process as the half-period interval [N 0 , N 1 ]. If both half-cycle intervals are judged to have nonlinear characteristics of high-resistance faults, the cycle is recorded as "fault cycle".
- Step 4 Perform the judgments in steps 1 to 3 cycle by cycle. If multiple consecutive cycles are recorded as "fault cycles”, it is determined that a high resistance fault occurs, and the fault location process is started.
- the zero-sequence voltage u 0b at the bus is used as the reference voltage to locate the fault section.
- the zero-sequence current i 0i of a certain measurement point its positioning feature in a certain "half cycle interval" is expressed as:
- c dir is a coefficient, and is calculated from the slope curve of the u 0b interval:
- cdir is further divided by or The maximum value of d is normalized, and d is the differential.
- d is the differential.
- u 0b is the zero-sequence voltage at the busbar; represents the interval slope of the zero-sequence voltage u 0b at the bus at n min , and The calculation method is exactly the same.
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Abstract
一种基于区间斜率的配电网弧光高阻故障区段定位方法,包括:故障检测流程和故障定位流程,故障检测流程中,根据采集的零序电流获取对应的区间斜率绝对值,基于区间斜率绝对值依次判断零序电流的每个周期是否具备弧光高阻故障特征,将具备弧光高阻故障特征的周期记为故障周期,当故障周期的连续个数大于设定值时,启动故障定位流程;故障定位流程中,基于各量测点的同步零序电流和零序电压波形进行故障区段定位。
Description
本发明涉及一种配电网故障定位方法,尤其是涉及一种基于区间斜率的配电网弧光高阻故障区段定位方法。
弧光高阻故障是一种常见的配电网故障形式,一般是架空线路因断线/下垂坠地,或发生树障从而与高阻抗的接地介质发生接触,形成单相接地故障。常见的高阻抗接地介质包括水泥、沙地、土壤、橡胶、沥青和树木等,故障电阻从几百欧到几十千欧不等,故障电流极其微弱,甚至在1安培以内,因此配电网的传统过流保护装置等难以对其实现检测。由于导线和接地介质之间无法形成可靠连接,空气间隙始终存在(除水阻),因此高阻故障常以电弧实现线路导体和接地介质的电气连接。弧光高阻故障的长期存在容易引发火灾,并对人员和设施的安全带来重大威胁。而故障的极弱特征、负荷电流和背景噪声的干扰、电弧的非线性以及非线性在不同接地介质下的差异等,均给故障的可靠检测和准确定位带来挑战。
高阻故障一般由架空线路断线或树障引起的导体与高阻抗的接地介质发生接触,这种接触一般是不可靠的,空气隙普遍存在于导体与接地介质之间或接地介质的内部。因此,当高阻接地故障发生时,一般都是通过电弧形成网络与大地的电气连接,从而故障电流和零序电流均会产生非线性的波形畸变。零序电流的波形畸变可以通过斜率进行描述。然而,直接通过求导或差分计算斜率显然极易受到信号噪声的影响,这个噪声可能来自于背景噪声、量测误差或燃熄弧引起的无效畸变等。
因此,故障的准确、快速区段定位,是提高配电网供电可靠性的重要方面。
发明内容
本发明的目的就是为了克服上述现有技术存在的缺陷而提供一种可靠有效的基于区间斜率的配电网弧光高阻故障区段定位方法。
本发明的目的可以通过以下技术方案来实现:
一种基于区间斜率的配电网弧光高阻故障区段定位方法,该方法包括故障检测流程和故障定位流程,
所述故障检测流程中,根据采集的零序电流获取对应的区间斜率绝对值,基于所述区间斜率绝对值依次判断零序电流的每个周期是否具备弧光高阻故障特征,将具备弧光高阻故障特征的周期记为故障周期,当故障周期的连续个数大于设定值时,启动所述故障定位流程;
所述故障定位流程中,基于各量测点的同步零序电流和零序电压波形进行故障区段定位。
进一步地,所述故障检测流程包括以下步骤:
11)采集零序电流,对于零序电流的每个周期,获得电流最大最小值,基于所述电流最大最小值定位至与该周期对应的区间斜率绝对值的最小值点N
1和N
2,并将上一周期的点N
2作为N
0组成区间[N
0,N
2];
12)对于半周期区间[N
0,N
1],获取其中的极小值点n
min,判断极小值点是否同时满足以下两个判据,若是,则执行步骤13),若否,返回步骤11)进行下一周期的判断:
a)标定第一个n
min为n
min0,其满足:
b)除n
min0外,其余极小值点n
min满足:
其中,K
set2为灵敏度系数;
13)在半周期区间[N
1,N
2]中采用如步骤12)的判断流程,若两个半周期区间均满足所述两个判据,则判断该周期具备弧光高阻故障特征,记为故障周期;
14)当故障周期的连续个数大于设定值时,启动所述故障定位流程。
进一步地,所述区间斜率绝对值表示为:
进一步地,在计算所述区间斜率绝对值前,采用基于格拉布斯准则的改进鲁棒局部回归平滑方法对的采样的零序电流进行处理。
进一步地,所述基于格拉布斯准则的改进鲁棒局部回归平滑方法具体为:
按设定拟合误差将零序电流拟合为多项式,并引入Grubbs法的迭代筛选思想和异常值筛选原则,对拟合误差权重系数w
i和拟合系数α进行迭代更新。
进一步地,步骤2)中,在区间[N
0+d,N
1-d]中获取极小值点n
min,其中,d为振荡消除参数。
优选地,所述灵敏度系数K
set1的取值范围为0.80~0.85。
优选地,所述灵敏度系数K
set2的取值范围为0.08~0.12。
进一步地,所述故障定位流程包括以下步骤:
21)对于某量测点的零序电流i
0i,其在某一个半周期区间的定位特征量:
进一步地,所述系数c
dir的取值根据不同中性点接地方式确定,并由u
0b区间斜率曲线计算而得:
其中,u
0b为母线处零序电压。
与现有技术相比,本发明具有如下有益效果:
1、本发明采用区间斜率绝对值作为弧光高阻故障特征的判断依据,能够克服噪声对畸变特征描述的影响,提高故障检测准确率。
2、本发明在计算区间斜率绝对值时,基于最小二乘线性拟合,并结合格拉布斯法则和鲁棒局部回归平滑理论,进一步消除噪声影响。
3、本发明将弧光高阻故障从原来的故障检测和选线,进一步确定故障区段,实现故障的准确、快速区段定位,为选段跳闸和故障恢复提供信息支撑。
图1为本发明的区间斜率绝对值曲线,其中,(1a)为非故障下,(1b)为故障下;
图2为LLSF和Grubbs-RLRS在描述区间斜率曲线特征上的有效性示意图,其中,(2a)为实测高阻故障的零序电流波形,(2b)为导数曲线,(2c)为区间斜率曲线(非绝对值),(2d)为区间斜率绝对值曲线及畸变检测;
图3为本发明的流程示意图。
下面结合附图和具体实施例对本发明进行详细说明。本实施例以本发明技术方案为前提进行实施,给出了详细的实施方式和具体的操作过程,但本发明的保护范围不限于下述的实施例。
如图3所示,本实施例提供一种基于区间斜率的配电网弧光高阻故障区段定位方法,该方法包括故障检测流程和故障定位流程,所述故障检测流程中,根据采集的零序电流获取对应的区间斜率绝对值,基于所述区间斜率绝对值依次判断零序电流的每个周期是否具备弧光高阻故障特征,将具备弧光高阻故障特征的周期记为故障周期,当故障周期的连续个数大于设定值时,启动所述故障定位流程;所述故障定位流程中,基于各量测点的同步零序电流和零序电压波形进行故障区段定位。
一、区间斜率曲线
高阻故障一般由架空线路断线或树障引起的导体与高阻抗的接地介质发生接触,这种接触一般是不可靠的,空气隙普遍存在于导体与接地介质之间或接地介质的内部。因此,当高阻接地故障发生时,一般都是通过电弧形成网络与大地的电气 连接,从而故障电流和零序电流均会产生非线性的波形畸变。
零序电流的波形畸变可以通过斜率进行描述。然而,直接通过求导或差分计算斜率显然极易受到信号噪声的影响,这个噪声可能来自于背景噪声、量测误差或燃熄弧引起的无效畸变等。为了克服这种噪声对畸变特征描述的影响,基于最小二乘线性拟合,计算区间斜率。
其中,
为在n
s点的区间斜率,
表示计算
所采用的一段零序电流区间,该区间长度为l并以n
s为中点,n表示该区间中的点,i
0(n)为点n处的零序电流;令l=N
T/8且N
T表示一个工频周期中的采样点个数。n为区间
中的点,即
n实际上表示为
n或
n,
i
0(n)同理。
对于零序电流的正弦波形,区间斜率绝对值
在电流最大和最小值时达到极小值点,如图(1a),在每个周期表现出“双Λ”形。对于畸变波形,如图(1b),
还会在最大畸变点附近达到极小值点,从而使得畸变波形的区间斜率绝对值曲线在一个工频周期中表现出“双M”形。这一特征可以用来区分大多数的故障事件和非故障事件。
然而,由于故障过程中存在燃熄弧现象,并且高阻故障电流幅值有时远小于有效量程而存在严重量测误差,零序电流波形会受到诸如脉冲噪声等短时不规则畸变的影响,这种畸变很难被传统低通滤波器或小波滤波器有效滤除。因此,优选地,在计算区间斜率之前,一种基于格拉布斯(Grubbs)准则的改进鲁棒局部回归平滑(robust local regression smoothing,RLRS)方法被用于对区间
中的采样数据进行处理。
其中,w
i表示权重系数,初始设为1;基于RLRS,即需找到一组α={α
j|j=0,1,…,m},使得ξ最小。令ξ′=0,从而计算得到的α可以表示为:
α=(N
TWN)
-1N
TWI (3)
相对于故障“零休期”的非线性畸变波形,诸如脉冲噪声等影响较大的无效畸变均有变化较快,持续时间较短的特点。引入Grubbs法的迭代筛选思想和异常值筛选原则,对w
i和α迭代更新。Grubbs准则的归一化残差表示为:
其中,G
p,N表示置信系数为p时的阈值,p一般取90%~99.5%。在本方法中,p设为90%;N表示当前区间中w
i=1的采样点个数。G
p,i取不同p和N时的值可参考格拉布斯表。当经过(2)-(5)的计算之后无w
i从1置为0时,用
计算
最终,区间斜率绝对值曲线可通过逐点计算
而得,也可以隔数个点计算一次
并利用插值获得曲线从而降低计算量。整个LLSF-Grubbs-RLRS方法的应用效果可通过图2进行说明。如图(2a)所示,若仅采用低通滤波器,当截止频率f
c较大时不能完全滤除脉冲噪声,当截止频率较低时,反而会扩大脉冲噪声带来的影响,因此不能仅利用低通滤波器来解决此问题。图(2b)展示了零序电流的导数曲线,对比可见,基于线性最小二乘而计算的区间斜率曲线具有更好抗噪声波动能力,如图(2c)所示。此外,图(2c)也证明Grubbs-RLRS法在消除脉冲噪声影响上的作用,从而使得区间斜率绝对值曲线能够正确地展示“双M”形特征。
二、故障检测
在区间斜率计算的基础上,高阻故障检测可以采用以下流程:
步骤一:如图(2d),对于零序电流的每个周期,通过FFT计算最大最小值点,并分别定位至其附近的区间斜率绝对值的最小值点N
1和N
2。N
0为上一周期的N
2点。具体为基于所述电流最大最小值定位至与该周期对应的区间斜率绝对值的最小值点N
1和N
2,组成区间[N
1,N
2],并将上一周期获得的点N
2作为N
0,与本周期的点N
1组成区间[N
0,N
1]。因此,每个周期均能以最大最小值为边界得到两个约半周期长度的区间。
步骤二:对于半周期区间[N
0,N
1],n
min为区间[N
0+d,N
1-d]中的极小值点,2d是为了规避因绝对值的计算导致在
的过零点附近可能存在的反复振荡。当且仅当以下两个判据成立时,可称半周期区间[N
0,N
1]具备高阻故障的非线性特征:
1)标定第一个n
min为n
min0,其应满足:
其中,
且
和
为区间(N
0,n
min)和(n
min,N
1)内的极大值(如图(2d));
为零序电流i
0在n
min的区间斜率;K
set1为灵敏度系数且通常设为0.80~0.85从而同时保证检测的灵敏性和安全性。Num
c1和Num
c2分别为满足公式(7)、(8)的采样点n
c1和n
c2的个数。
2)考虑在极强噪声情况下的Grubbs-RLRS滤波残余,[N
0+d,N
1-d]中可能存在超过一个n
min。此时,除了n
min0,其余n
min应满足:
其中,K
set2也为灵敏度系数,通常设为0.10。
步骤三:在半周期区间[N
1,N
2]中,采取与半周期区间[N
0,N
1]相同的判断流程。如果两个半周期区间均判断为具备高阻故障的非线性特征,该周期记为“故障周期”。
步骤四:逐周期进行步骤一至三的判断,若连续多个周期被记为“故障周期”,则判断高阻故障发生,并启动故障定位流程。
三、故障定位
当检测到高阻故障后,基于各量测点的同步零序电流和零序电压波形,若无零序电压,则采用母线处零序电压u
0b作为参考电压,进行故障区段定位流程。对于某量测点的零序电流i
0i,其在某一个“半周期区间”的定位特征量表示为:
其中,c
dir进一步通过除以
或
的最大值而进行归一化处理,d表示微分。此外,当一个周期并没有被记为“故障周期”时,其两个“半周期”的
均为0。其中,u
0b为母线处零序电压;
表示母线处零序电压u
0b在n
min的区间斜率,
和
的计算方式完全一致。
基于上述特征量,对于三种中性点接地方式,故障点前的
远大于0,故障点后的
等于或小于0。当过渡电阻极大,零序电流极小时,有功分量的占比和影响将会发生变化,此时故障点后的
会略大于0,但大多数情况下依然远小于故障点前的
则可以通过相邻半周期的定位特征量
的关系确定故障位置。
需要指出的是,在谐振接地系统中,当故障电流极小时,各量测点的零序电流受到系统中有功分量的影响而相位关系出现变化。在这种情况下,
更适用,因此,对于谐振接地系统来说,区段定位需要采用两种c
dir进行判定。
以上详细描述了本发明的较佳具体实施例。应当理解,本领域的普通技术人员无需创造性劳动就可以根据本发明的构思作出诸多修改和变化。因此,凡本技术领域中技术人员依本发明的构思在现有技术的基础上通过逻辑分析、推理或者有限的实验可以得到的技术方案,皆应在由权利要求书所确定的保护范围内。
Claims (10)
- 一种基于区间斜率的配电网弧光高阻故障区段定位方法,其特征在于,该方法包括故障检测流程和故障定位流程,所述故障检测流程中,根据采集的零序电流获取对应的区间斜率绝对值,基于所述区间斜率绝对值依次判断零序电流的每个周期是否具备弧光高阻故障特征,将具备弧光高阻故障特征的周期记为故障周期,当故障周期的连续个数大于设定值时,启动所述故障定位流程;所述故障定位流程中,基于各量测点的同步零序电流和零序电压波形进行故障区段定位。
- 根据权利要求1所述的基于区间斜率的配电网弧光高阻故障区段定位方法,其特征在于,所述故障检测流程包括以下步骤:11)采集零序电流,对于零序电流的每个周期,获得电流最大最小值,基于所述电流最大最小值定位至与该周期对应的区间斜率绝对值的最小值点N 1和N 2,并将上一周期的点N 2作为N 0组成区间[N 0,N 2];12)对于半周期区间[N 0,N 1],获取其中的极小值点n min,判断极小值点是否同时满足以下两个判据,若是,则执行步骤13),若否,返回步骤11)进行下一周期的判断:a)标定第一个n min为n min0,其满足:b)除n min0外,其余极小值点n min满足:其中,K set2为灵敏度系数;13)在半周期区间[N 1,N 2]中采用如步骤12)的判断流程,若两个半周期区间均满足所述两个判据,则判断该周期具备弧光高阻故障特征,记为故障周期;14)当故障周期的连续个数大于设定值时,启动所述故障定位流程。
- 根据权利要求2所述的基于区间斜率的配电网弧光高阻故障区段定位方法,其特征在于,在计算所述区间斜率绝对值前,采用基于格拉布斯准则的改进鲁棒局部回归平滑方法对的采样的零序电流进行处理。
- 根据权利要求4所述的基于区间斜率的配电网弧光高阻故障区段定位方法,其特征在于,所述基于格拉布斯准则的改进鲁棒局部回归平滑方法具体为:按设定拟合误差将零序电流拟合为多项式,并引入Grubbs法的迭代筛选思想和异常值筛选原则,对拟合误差权重系数w i和拟合系数α进行迭代更新。
- 根据权利要求2所述的基于区间斜率的配电网弧光高阻故障区段定位方法,其特征在于,步骤2)中,在区间[N 0+d,N 1-d]中获取极小值点n min,其中,d为振荡消除参数。
- 根据权利要求2所述的基于区间斜率的配电网弧光高阻故障区段定位方法,其特征在于,所述灵敏度系数K set1的取值范围为0.80~0.85。
- 根据权利要求2所述的基于区间斜率的配电网弧光高阻故障区段定位方法,其特征在于,所述灵敏度系数K set2的取值范围为0.08~0.12。
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