WO2023245866A1 - 一种基于全时域突变信息的故障识别方法、系统、电子设备及计算机可读存储介质 - Google Patents

一种基于全时域突变信息的故障识别方法、系统、电子设备及计算机可读存储介质 Download PDF

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WO2023245866A1
WO2023245866A1 PCT/CN2022/116214 CN2022116214W WO2023245866A1 WO 2023245866 A1 WO2023245866 A1 WO 2023245866A1 CN 2022116214 W CN2022116214 W CN 2022116214W WO 2023245866 A1 WO2023245866 A1 WO 2023245866A1
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fault
phase
current
wind farm
fault current
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PCT/CN2022/116214
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English (en)
French (fr)
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王聪博
杨国生
余越
蒋帅
曹虹
窦雪薇
薛志英
王剑锋
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中国电力科学研究院有限公司
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/08Locating faults in cables, transmission lines, or networks
    • G01R31/081Locating faults in cables, transmission lines, or networks according to type of conductors
    • G01R31/085Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution lines, e.g. overhead
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/08Locating faults in cables, transmission lines, or networks
    • G01R31/088Aspects of digital computing
    • YGENERAL 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
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS 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
    • Y04S10/00Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • Y04S10/52Outage or fault management, e.g. fault detection or location

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  • This application relates to the technical field of power system protection, and involves but is not limited to a fault identification method, system, electronic equipment and computer-readable storage media based on full time domain mutation information.
  • Full time domain information protection uses cosine similarity, Spearman rank correlation coefficient and Pearson correlation coefficient to characterize the difference in current transient waveforms between new energy stations and power grids.
  • this type of method completely relies on the voltage and current on both sides of the line.
  • the output of the new energy station is small, or it is integrated into a weak power grid, the overall current amplitude is small at this time, and the protection performance is degraded, or even fails to operate. risks of.
  • the traditional protection method using power frequency information requires extracting the power frequency information from the post-fault current and voltage sampling values to form protection criteria.
  • the line fault information used by this type of method is mainly power frequency, it is easily affected by the characteristics of new energy stations such as limited short-circuit current amplitude, controlled phase angle, and frequency offset, resulting in a decline in protection performance. Therefore, when a fault occurs in a high-voltage AC line, a new fault identification method is urgently needed.
  • a fault identification method based on full time domain mutation information includes:
  • a multi-order matrix is constructed according to the fault current of each phase of the wind farm side and the compliance side, and the fault current of each phase of the wind farm side and the compliance side is calculated according to the multi-order matrix.
  • the fault current of each phase on the flexible side is:
  • E f is the internal potential of the converter
  • Z eq is the equivalent impedance
  • ⁇ and ⁇ - represent the angular frequencies of the positive and negative sequence currents respectively
  • m is the proportional coefficient related to the short-circuit type; is the initial phase angle of the negative sequence current.
  • a multi-order matrix is constructed according to the fault current of each phase of the wind farm side and the compliance side, and the wind farm side and the wind farm side are respectively calculated according to the multi-order matrix. Describe the mutation characteristic values corresponding to the fault current of each phase on the flexible side, including:
  • the fault current sampling value of any phase is determined as a one-dimensional array.
  • the multi-order matrix is:
  • I T ⁇ I 1 , I 2 , I 3 ,..., I N ⁇
  • I 1 ⁇ i 1 ,i 2 ,i 3 ,...,i N ⁇ T
  • Calculating the longitudinal gradient matrix corresponding to the multi-order matrix of the row vector expression includes:
  • G is the sudden change characteristic value corresponding to the fault current of each phase;
  • Gx and Gy are the transverse gradient matrix and the longitudinal gradient matrix respectively;
  • Gx(i,j) is the i-th row in the transverse gradient matrix The element in the j-th column;
  • Gy(i,j) is the element in the i-th row and j-th column in the longitudinal gradient matrix.
  • the fault type is determined based on the mutation characteristic value corresponding to the fault current of each phase of the wind farm side and the compliance side and a preset criterion, including:
  • the sudden change characteristic value corresponding to the fault current; G set is the preset setting value.
  • This application provides a fault identification system based on full time domain mutation information.
  • the system includes:
  • a sudden change characteristic value calculation unit configured to construct a multi-order matrix according to the fault current of each phase of the wind farm side and the flexible side, and calculate the wind farm side and the flexible side respectively according to the multi-order matrix.
  • the mutation characteristic value calculation unit is also used to operate the fault current of each phase of the wind farm side and the compliance side in the following manner to obtain the wind farm side respectively.
  • the sudden change characteristic value corresponding to the fault current of each phase on the flexible side includes:
  • Calculating the longitudinal gradient matrix corresponding to the multi-order matrix of the row vector expression includes:
  • G is the sudden change characteristic value corresponding to the fault current of each phase;
  • Gx and Gy are the transverse gradient matrix and the longitudinal gradient matrix respectively;
  • Gx(i,j) is the i-th row in the transverse gradient matrix The element in the j-th column;
  • Gy(i,j) is the element in the i-th row and j-th column in the longitudinal gradient matrix.
  • the fault type determination unit is also configured to determine, for any phase, if the fault current of any corresponding wind farm side and compliance side satisfies the preset criterion,
  • the fault type of any phase is an intra-zone fault
  • the fault type of any phase is determined to be an out-of-area fault
  • the sudden change characteristic value corresponding to the fault current; G set is the preset setting value.
  • the fault type determination unit is also used to determine that the phase whose fault type is an intra-zone fault is a fault phase, and to protect the outlet according to the number of the fault phases;
  • the present application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor.
  • the processor executes the computer program, the above method is implemented. step.
  • the present application provides a computer-readable storage medium that stores a computer program.
  • the computer program is executed by a processor, the steps of the above method are implemented.
  • the mutation characteristic value corresponding to the fault current of each phase is determined according to the mutation characteristic value corresponding to the fault current of each phase on the wind farm side and the compliance side and the preset criteria; the method of this application uses each phase on both sides of the line Multi-order matrices are constructed from the current signals respectively.
  • the characteristics of the multi-order matrix that can quickly amplify the proportion of mutation signals and the advantage of the matrix gradient that can accurately represent the degree of data mutation are used to construct protection criteria to achieve high-speed and reliable identification of faults, thereby solving the problem.
  • This application can adapt to scenarios where a variety of new energy power sources are connected and sent out, and does not rely on power frequency.
  • Figure 1 is a flow chart of a fault identification method based on full time domain mutation information provided by an embodiment of the present application
  • Figure 2 is a protection flow chart provided by the embodiment of the present application.
  • Figure 4 is a schematic diagram of the protection action when different fault types occur at F2 in the area provided by the embodiment of the present application;
  • Figure 5 is a schematic diagram of the protection action when different fault types occur at F3 in the area provided by the embodiment of the present application;
  • Figure 6 is a schematic diagram of the protection action when different fault types occur at F4 in the area provided by the embodiment of the present application;
  • Figure 7 is a schematic diagram of the protection action when different fault types occur at F1 outside the area provided by the embodiment of the present application.
  • Figure 8 is a comparison diagram of the protection effects of the protection method provided by the embodiment of the present application and the traditional protection method;
  • Figure 9 is a schematic structural diagram of a fault identification system based on full time domain mutation information provided by an embodiment of the present application.
  • FIG. 10 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.
  • FIG. 1 is a flow chart of a fault identification method 100 based on full time domain mutation information according to an embodiment of the present application.
  • the fault identification method based on full time domain mutation information uses the current signals of each phase on both sides of the line to construct a multi-order matrix.
  • the comprehensive use of the multi-order matrix can quickly amplify the proportion of mutation signals.
  • Characteristics, and the advantage that the matrix gradient can accurately represent the degree of data mutation, protection criteria can be constructed to achieve high-speed and reliable identification of faults, thereby solving the risk of reduced sensitivity of traditional protection and incorrect actions in new power systems.
  • This application can adapt to scenarios where a variety of new energy power sources are connected and sent out, and does not rely on power frequency. It has the ability to withstand transition resistance and noise, and has good quickness. It is useful for the high proportion of new energy consumption and safe operation of the power grid in the future. It has important engineering significance and provides a prerequisite and guarantee for the further development of high-proportion new energy power electronic systems in the future.
  • the fault identification method 100 based on full time domain mutation information provided by the embodiment of the present application, as shown in Figure 1, can be implemented through the following steps:
  • Step 101 When a fault occurs on the high-voltage AC line, collect the current signals on the wind farm side and the flexible side to obtain the fault current of each phase on the wind farm side and the flexible side.
  • the fault current of each phase on the wind farm side can be expressed by the following formula 1,
  • E f is the internal potential of the converter
  • Z eq is the equivalent impedance
  • ⁇ and ⁇ - represent the angular frequencies of the positive and negative sequence currents respectively
  • m is the proportional coefficient related to the short-circuit type; is the initial phase angle of the negative sequence current.
  • the fault characteristics of faults inside and outside the area of AC lines sent by new energy through flexible and straight-side grid connection are first analyzed to clarify the characteristics of fault currents inside and outside the area, and then the single-phase current signals collected in the time window on both sides are constructed as Multi-order matrix.
  • the wind power converter is the only power outlet of the permanent magnet wind turbine. Due to the limited overcurrent capability, in order to protect the power electronic devices of the converter, the control system mainly uses limiting control and negative sequence current control.
  • the short-circuit current of each phase on the wind farm side can be expressed by the above formula 1.
  • the short-circuit current of the wind farm is controlled by the reference value of the dq-axis current of the converter control system, and the wind farm is equivalent to a controlled current source. Due to the limited overcurrent capability of the converter, the short-circuit current is generally 1.5-2 times the maximum rated current. Therefore, wind farms have the characteristics of limited fault current amplitude.
  • the fault current amplitude of the converter is limited and lacks a sustained and stable power frequency component, which seriously affects the correct identification of faults by the traditional current differential protection principle, and will occur during the calculation process of the protection device.
  • different converter controls reflect different control response characteristics, which determines the mutation characteristics of the short-circuit current after a fault are different and different from traditional synchronous machines.
  • Step 102 Construct a multi-order matrix according to the fault current of each phase on the wind farm side and the compliance side, and calculate the mutation characteristic value corresponding to the fault current of each phase on the wind farm side and the compliance side according to the multi-order matrix.
  • I T ⁇ I 1 , I 2 , I 3 ,..., I N ⁇
  • I 1 ⁇ i 1 ,i 2 ,i 3 ,...,i N ⁇ T
  • the transverse gradient matrix can be obtained by the following formula 4,
  • the mutation characteristic value is calculated according to the horizontal gradient matrix and the longitudinal gradient matrix.
  • the mutation characteristic value can be obtained by the following formula 6,
  • the obtained current signals of N sampling points constitute one-dimensional data I and are improved as follows to obtain a multi-order matrix IT .
  • the improvement method is as follows:
  • Matrix gradients are divided into horizontal gradients and vertical gradients, which mainly reflect the degree of change between adjacent elements in the matrix. Taking the multi-order matrix I T as an example, convert it into the expression form of a column vector:
  • the difference between the first column vector of the current matrix and the next column vector is divided by 1 to obtain the first column vector of the transverse gradient matrix; the average value of the difference between the nth column vector in the middle and the current column vectors on both sides is The nth column vector of the transverse gradient matrix; the difference between the last column vector and the previous column vector is used as the next column vector of the transverse gradient matrix.
  • the expression of the transverse gradient matrix Gx is:
  • the mutation characteristic value G of each time window is taken to reflect the mutation characteristic value of this signal;
  • G is the mutation characteristic value corresponding to the fault current of each phase;
  • Gx and Gy are the transverse gradient matrix and the longitudinal gradient matrix respectively;
  • Gx(i,j) is the element in the i-th row and j-th column in the horizontal gradient matrix;
  • Gy(i,j) is the element in the i-th row and j-th column in the longitudinal gradient matrix.
  • Step 103 Determine the fault type according to the mutation characteristic value corresponding to the fault current of each phase on the wind farm side and the compliance side and the preset criteria.
  • the fault type is determined based on the mutation characteristic value corresponding to the fault current of each phase on the wind farm side and the compliance side and the preset criteria, including:
  • the fault type of any phase is determined to be an intra-zone fault
  • the fault type of any phase is determined to be an outside fault
  • the phase whose fault type is an intra-zone fault is determined to be a faulty phase, and the protection outlet is performed according to the number of faulty phases.
  • the control relay protection device issues a faulty phase trip command, controls the faulty phase to trip, and controls the normal operation of the non-faulty phases; if the number of faulty phases is greater than the preset number, the control relay The protection device issues a three-phase trip command and controls all three phases to trip.
  • the wind farm power flows completely through the line to the flexible side. At this time, all through-currents flow in the line.
  • the AC current collected on both sides of the line is the same sine wave. Then, the collected AC currents on both sides of the line are collected in the same time window.
  • the mutation characteristic value G of the current signal should also be basically the same.
  • the fault current on both sides will undergo a large adjustment in a short time after the fault occurs.
  • the mutation characteristic value of the entire time window will be due to the collected fault point. Changes occur in a short period of time, and the changes in the current signals collected on both sides are different, and the calculated mutation characteristic value G value will also be greatly different.
  • the protection criterion can be constructed as:
  • G 1 and G 2 respectively represent the mutation characteristic values corresponding to the current signals at both ends of the line,
  • G set is the setting value of the main criterion of protection, which is based on the maximum value when avoiding external faults.
  • Amplitude error setting considering that the maximum transmission error of the current transformer (CT) is ⁇ 10%, and the capacitance has a small impact on the fault current, set the maximum amplitude error on both sides to 20%, while taking into account special circumstances. There is a certain margin.
  • the time window the higher the sampling frequency required.
  • the fault type is identified by comparing the size relationship between the actual operation value
  • the specific process is: when the protection is started, each set of protection devices is divided into phases to judge the fault, extract the differential current data 10ms after the fault moment, and calculate according to the proposed protection criteria. For any phase, if the formula protection criterion is met, that is, the difference between the multi-dimensional mutation characteristic values is greater than a fixed value, then the fault type is determined to be an internal fault, and the outlet is protected; otherwise, the fault type is determined to be an external fault, and the protection Return.
  • the phase whose fault type is an intra-zone fault is determined to be the faulty phase. If the faulty phase is a single phase, the relay protection device issues a tripping command for the faulty phase, and the non-faulty phase continues to operate. If two or three phases meet the criteria, the relay protection device will issue a three-phase trip command and control all three phases to trip.
  • the transition resistance has strong tolerance, and the protection can still operate correctly under a 100 ⁇ transition resistance.
  • the wind farm is connected to the grid via a ⁇ 500kV flexible direct transmission line, with a system capacity of 200 megavolt-ampere (MVA).
  • the wind farm is equivalent to a single wind turbine, with a single wind turbine unit capacity of 5 MW (million watt, MW).
  • the length of the AC line from the wind farm transformer to the flexible direct transmission end converter is set to 20 kilometers (kilometre, km).
  • F1 and F5 are fault points outside the area.
  • Internal faults in the area include the F2 wind farm side protection line outlet, the F4 flexible side line outlet, and the F3 line. Midpoint failure.
  • the sampling frequency of the current signal is 4kHz, and the time window is selected as 10ms.
  • the tuning settings should avoid maximum amplitude errors in the event of external faults.
  • the current transformer (CT) has a maximum transmission error of ⁇ 10% and a maximum amplitude error of 20% on both sides.
  • CT current transformer
  • an adjustable margin is used to avoid the impact of the capacitor current. This article sets the margin to 20% and can be adjusted according to actual system parameters.
  • the difference G between the mutation characteristic values increases to 30 during external faults. Therefore, set the constant value of G set to 30.
  • Figure 4 shows a schematic diagram of the corresponding protection action situation after different fault types occur at F2 in the area.
  • Figure 5 shows a schematic diagram of the corresponding protection action situation after different fault types occur at F3 in the area.
  • Figure 6 shows a schematic diagram of the protection action situation after different fault types occur at F4 in the area, and
  • Figure 7 shows a schematic diagram of the protection action situation after different fault types occur at F1 outside the area.
  • Table 1 shows the difference in protection characteristic values of different types of faults at F2, F3, F4 in the 5ms time zone and F1 and F5 outside the zone.
  • the fault type determination unit 903 is also used to determine that the phase whose fault type is an intra-zone fault is a fault phase, and to protect the outlet according to the number of fault phases;
  • FIG. 10 is a schematic structural diagram of the electronic device 1000 according to an embodiment of the present application. It includes: a memory 1001, a processor 1002, and a memory 1001.
  • the computer program runs on 1002.
  • the processor 1002 executes the computer program, the steps of the fault identification method shown in Figure 1 are implemented.
  • embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment that combines software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
  • computer-usable storage media including, but not limited to, disk storage, CD-ROM, optical storage, etc.
  • These computer program instructions may also be stored in a computer-readable memory that causes a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction means, the instructions
  • the device implements the functions specified in a process or processes of the flowchart and/or a block or blocks of the block diagram.
  • the mutation characteristic value corresponding to the fault current of each phase is determined according to the mutation characteristic value corresponding to the fault current of each phase on the wind farm side and the compliance side and the preset criteria; the method of this application uses each phase on both sides of the line Multi-order matrices are constructed from the current signals respectively.
  • the characteristics of the multi-order matrix that can quickly amplify the proportion of mutation signals and the advantage of the matrix gradient that can accurately represent the degree of data mutation are used to construct protection criteria to achieve high-speed and reliable identification of faults, thereby solving the problem.
  • This application can adapt to scenarios where a variety of new energy power sources are connected and sent out, and does not rely on power frequency.

Abstract

一种基于全时域突变信息的故障识别方法(100)、系统、电子设备及计算机可读存储介质,当高压交流线路出现故障时,进行风电场侧和柔直侧的电流信号的采集,获取风电场侧和柔直侧的每相的故障电流(101);根据风电场侧和柔直侧的每相的故障电流分别构造多阶矩阵,并根据多阶矩阵分别计算风电场侧和柔直侧的每相的故障电流对应的突变特征值(102);根据风电场侧和柔直侧的每相的故障电流对应的突变特征值以及预设判据,确定故障类型(103)。

Description

一种基于全时域突变信息的故障识别方法、系统、电子设备及计算机可读存储介质
相关申请的交叉引用
本申请要求在2022年06月23日提交中国专利局、申请号为202210717823.0、申请名称为“一种基于全时域突变信息的故障识别方法及系统”的中国专利申请的优先权,其全部内容通过引用结合在本申请中。
技术领域
本申请涉及电力系统保护技术领域,涉及但不限于一种基于全时域突变信息的故障识别方法、系统、电子设备及计算机可读存储介质。
背景技术
随着风电、光伏等新能源占比日益提高,电网规模持续扩大,我国新型电力系统安全面临严峻挑战。高占比新能源成为新型电力系统的一个重要特性。在新型电力系统中,由于大量采用电力电子换流器并入电网,故障暂态过程与电力电子设备控制策略及其参数密切相关,短路电流幅值受限、相角受控,且非特征谐波含量显著增大。这会导致传统以工频量为基础的继电保护可靠性与灵敏性受到一定威胁,使得传统差动保护存在性能下降,严重影响新能源电力系统的安全运行。目前针对现有保护原理,根据故障信息种类的不同,可细分为全时域信息保护和频域信息保护。全时域信息量保护通过利用余弦相似度、斯皮尔曼等级相关系数和皮尔逊相关系数等方式来表征新能源场站和电网之间的电流暂态波形的差异。然而,该类方法完全依赖线路两侧的电压电流,当新能源场站出力较小时,或并入弱电网的场景下,此时电流幅值整体较小,保护存在性能下降,甚至出现拒动的风险。关于频域信息的保护,传统利用工频量信息保护方法,需要提取故障后电流电压采样值中的工频量信息,从而形成保护判据。但此类方法由于利用的线路故障信息均以工频量为主,易受到新能源场站短路电流幅值受限、相角受控、频率偏移等特性的影响,导致保护性能下降。因此,针对高压交流线路出现故障时,目前亟需一种新的故障识别方法。
申请内容
本申请提出一种基于全时域突变信息的故障识别方法及系统,以解决如何高效地实现高压交流线路故障识别,从而提高电力系统保护能力的问题。
为了解决上述问题,根据本申请的一个方面,提供了一种基于全时域突变信息的故障识别方法,所述方法包括:
当高压交流线路出现故障时,进行风电场侧和柔直侧的电流信号的采集,获取所述风电场侧和所述柔直侧的每相的故障电流;
根据所述风电场侧和所述柔直侧的每相的故障电流分别构造多阶矩阵,并根据所述多阶矩阵分别计算所述风电场侧和所述柔直侧的每相的故障电流对应的突变特征值;
根据所述风电场侧和所述柔直侧的每相的故障电流对应的突变特征值以及预设判据,确定故障类型。
在一些实施例中,其中,所述风电场侧的每相的故障电流为:
Figure PCTCN2022116214-appb-000001
所述柔直侧的每相的故障电流为:
Figure PCTCN2022116214-appb-000002
其中,
Figure PCTCN2022116214-appb-000003
为所述风电场侧的
Figure PCTCN2022116214-appb-000004
相的故障电流;
Figure PCTCN2022116214-appb-000005
分别为预设的d轴和q轴的电流参考值;ω PLL为基频角频率;
Figure PCTCN2022116214-appb-000006
为初始相位角;ξ为二阶系统的阻尼比,ξ=k ip/2×(L×k ii) 1/2;ω d为阻尼固有频率,ω d=ω n(1-ξ 2) 1/2,ω n为二阶系统阻尼为零时的自然振荡角频率,ω n=(k ii/L) 1/2;β为系统阻尼角,β=arctan((1-ξ 2) 1/2/ξ);P为单相输出有功功率;u d为d轴电压;i d0为d轴初始电流;t为故障时间;k ip为电流控制环比例;k ii为积分时间常数;L为桥臂电感;
其中,
Figure PCTCN2022116214-appb-000007
为所述柔直侧的
Figure PCTCN2022116214-appb-000008
相的故障电流;E f为换流器内电势;Z eq为等效阻抗;ω和ω -分别表示正、负序电流的角频率;m为与短路类型有关的比例系数;
Figure PCTCN2022116214-appb-000009
为负序电流初始相角。
在一些实施例中,其中,所述根据所述风电场侧和所述柔直侧的每相的故障电流分别构造多阶矩阵,并根据所述多阶矩阵分别计算所述风电场侧和所述柔直侧的每相的故障电流对应的突变特征值,包括:
对所述风电场侧和所述柔直侧的每相的故障电流,均按照如下方式操作,以分别获取所述风电场侧和所述柔直侧的每相的故障电流对应的所述突变特征值,包括:
将任一相的故障电流采样值确定为一个一维的数组,在采样时间内N个采样点构成的电流信号记作I={i 1,i 2,i 3,…,i N},则多阶矩阵为:
Figure PCTCN2022116214-appb-000010
将多阶矩阵I T转化为行向量和列向量的表达形式,列向量表达形式为:I T={I 1,I 2,I 3,…,I N},其中,第一个列向量内部元素为:I 1={i 1,i 2,i 3,…,i N} T;行向量表达形式为:I T={I 1 T,I 2 T,I 3 T,…,I N T} T,其中第一个行向量内部元素为: I 1 T={i 1,i 2,i 3,…,i N};
计算所述列向量表达形式的多阶矩阵对应的横向梯度矩阵,包括:
Figure PCTCN2022116214-appb-000011
计算所述行向量表达形式的多阶矩阵对应的纵向梯度矩阵,包括:
Figure PCTCN2022116214-appb-000012
根据所述横向梯度矩阵和所述纵向梯度矩阵计算所述突变特征值,包括:
Figure PCTCN2022116214-appb-000013
其中,G为所述每相的故障电流对应的突变特征值;Gx和Gy分别为所述横向梯度矩阵和所述纵向梯度矩阵;Gx(i,j)为所述横向梯度矩阵中第i行第j列的元素;Gy(i,j)为所述纵向梯度矩阵中第i行第j列的元素。
在一些实施例中,其中,所述根据所述风电场侧和所述柔直侧的每相的故障电流对应的突变特征值以及预设判据,确定故障类型,包括:
对于任一相,若所述任一相对应的风电场侧和柔直侧的故障电流满足所述预设判据,确定所述任一相的故障类型为区内故障;
若所述任一相对应的风电场侧和柔直侧的故障电流不满足所述预设判据,确定所述任一相的故障类型为区外故障;
所述预设判据包括ΔG=|G 1-G 2|>G set,其中,G 1和G 2分别为所述风电场侧的每相的故障电流和所述柔直侧的每相的故障电流对应的突变特征值;G set为预设整定值。
在一些实施例中,确定所述故障类型为区内故障的相为故障相,并根据所述故障相的数量进行保护出口;
其中,若所述故障相的数量小于或等于预设数量,控制继电保护装置发出故障相跳闸指令,控制所述故障相跳闸,控制非故障相正常运行;若所述故障相的数量大于所述预设数量,控制所述继电保护装置发出三相跳闸指令,控制三相全部跳闸。
本申请提供一种基于全时域突变信息的故障识别系统,所述系统包括:
故障电流获取单元,用于当高压交流线路出现故障时,进行风电场侧和柔直侧的电流信号的采集,获取所述风电场侧和所述柔直侧的每相的故障电流;
突变特征值计算单元,用于根据所述风电场侧和所述柔直侧的每相的故障电流分别构造多阶矩阵,并根据所述多阶矩阵分别计算所述风电场侧和所述柔直侧的每相的故障电流对应的突变特征值;
故障类型确定单元,用于根据所述风电场侧和所述柔直侧的每相的故障电流对应的突变特征值以及预设判据,确定故障类型。
在一些实施例中,在所述故障电流获取单元,所述风电场侧的每相的故障电流为:
Figure PCTCN2022116214-appb-000014
所述柔直侧的每相的故障电流为:
Figure PCTCN2022116214-appb-000015
其中,
Figure PCTCN2022116214-appb-000016
为所述风电场侧的
Figure PCTCN2022116214-appb-000017
相的故障电流;
Figure PCTCN2022116214-appb-000018
分别为预设的d轴和q轴的电流参考值;ω PLL为基频角频率;
Figure PCTCN2022116214-appb-000019
为初始相位角;ξ为二阶系统的阻尼比,ξ=k ip/2×(L×k ii) 1/2;ω d为阻尼固有频率,ω d=ω n(1-ξ 2) 1/2,ω n为二阶系统阻尼为零时的自然振荡角频率,ω n=(k ii/L) 1/2;β为系统阻尼角,β=arctan((1-ξ 2) 1/2/ξ);P为单相输出有功功率;u d为d轴电压;i d0为d轴初始电流;t为故障时间;k ip为电流控制环比例;k ii为积分时间常数;L为桥臂电感;
其中,
Figure PCTCN2022116214-appb-000020
为所述柔直侧的
Figure PCTCN2022116214-appb-000021
相的故障电流;E f为换流器内电势;Z eq为等效阻抗;ω和ω -分别表示正、负序电流的角频率;m为与短路类型有关的比例系数;
Figure PCTCN2022116214-appb-000022
为负序电流初始相角。
在一些实施例中,所述突变特征值计算单元,还用于对所述风电场侧和所述柔直侧的每相的故障电流,均按照如下方式操作,以分别获取所述风电场侧和所述柔直侧的每相的故障电流对应的所述突变特征值,包括:
将任一相的故障电流采样值确定为一个一维的数组,在采样时间内N个采样点构成的电流信号记作I={i 1,i 2,i 3,…,i N},则多阶矩阵为:
Figure PCTCN2022116214-appb-000023
将多阶矩阵I T转化为行向量和列向量的表达形式,列向量表达形式为:I T={I 1,I 2,I 3,…,I N},其中,第一个列向量内部元素为:I 1={i 1,i 2,i 3,…,i N} T;行向量表达形式为:I T={I 1 T,I 2 T,I 3 T,…,I N T} T,其中第一个行向量内部元素为:I 1 T={i 1,i 2,i 3,…,i N};
计算所述列向量表达形式的多阶矩阵对应的横向梯度矩阵,包括:
Figure PCTCN2022116214-appb-000024
计算所述行向量表达形式的多阶矩阵对应的纵向梯度矩阵,包括:
Figure PCTCN2022116214-appb-000025
根据所述横向梯度矩阵和所述纵向梯度矩阵计算所述突变特征值,包括:
Figure PCTCN2022116214-appb-000026
其中,G为所述每相的故障电流对应的突变特征值;Gx和Gy分别为所述横向梯度 矩阵和所述纵向梯度矩阵;Gx(i,j)为所述横向梯度矩阵中第i行第j列的元素;Gy(i,j)为所述纵向梯度矩阵中第i行第j列的元素。
在一些实施例中,所述故障类型确定单元,还用于对于任一相,若所述任一相对应的风电场侧和柔直侧的故障电流满足所述预设判据,确定所述任一相的故障类型为区内故障;
若所述任一相对应的风电场侧和柔直侧的故障电流不满足所述预设判据,确定所述任一相的故障类型为区外故障;
所述预设判据包括ΔG=|G 1-G 2|>G set,其中,G 1和G 2分别为所述风电场侧的每相的故障电流和所述柔直侧的每相的故障电流对应的突变特征值;G set为预设整定值。
在一些实施例中,所述故障类型确定单元,还用于确定所述故障类型为区内故障的相为故障相,并根据所述故障相的数量进行保护出口;
其中,若所述故障相的数量小于或等于预设数量,控制继电保护装置发出故障相跳闸指令,控制所述故障相跳闸,控制非故障相正常运行;若所述故障相的数量大于所述预设数量,控制所述继电保护装置发出三相跳闸指令,控制三相全部跳闸。
本申请提供一种电子设备,包括:存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序,所述处理器执行所述计算机程序时实现上述所述方法的步骤。
本申请提供一种计算机可读存储介质,所述计算机可读存储介质存储有计算机程序,所述计算机程序被处理器执行时实现上述所述方法的步骤。
本申请提供了一种基于全时域突变信息的故障识别方法、系统、电子设备及计算机可读存储介质,当高压交流线路出现故障时,进行风电场侧和柔直侧的电流信号的采集,获取风电场侧和柔直侧的每相的故障电流;根据风电场侧和柔直侧的每相的故障电流分别构造多阶矩阵,并根据多阶矩阵分别计算风电场侧和柔直侧的每相的故障电流对应的突变特征值;根据风电场侧和柔直侧的每相的故障电流对应的突变特征值以及预设判据,确定故障类型;本申请的方法利用线路两侧各相的电流信号分别构造多阶矩阵,综合利用多阶矩阵能快速放大突变信号占比的特性,以及矩阵梯度可以精准表征数据突变程度的优势构建保护判据,以实现故障的高速可靠判别,从而解决新型电力系统中传统保护灵敏性降低以及不正确动作的风险问题。本申请可适应多种新能源电源接入送出的场景,且不依赖工频量,具有耐受过渡电阻及噪声的能力,速动性好,对于未来新能源高比例消纳、电网安全运行具有重要的工程意义,为未来进一步发展高比例的新能源电力电子系统提供前提与保障。
附图说明
通过参考下面的附图,可以更为完整地理解本申请的示例性实施方式:
图1为本申请实施方式提供的一种基于全时域突变信息的故障识别方法的流程图;
图2为本申请实施方式提供的一种保护流程图;
图3为本申请实施方式提供的风机并入交流系统的示意图;
图4为本申请实施方式提供的在区内F2处出现不同故障类型的故障时保护动作情况的示意图;
图5为本申请实施方式提供的在区内F3处出现不同故障类型的故障时保护动作情况的示意图;
图6为本申请实施方式提供的在区内F4处出现不同故障类型的故障时保护动作情况的示意图;
图7为本申请实施方式提供的在区外F1处出现不同故障类型的故障时保护动作情况的示意图;
图8为本申请实施方式提供的保护方法与传统保护方法的保护效果对比图;
图9为本申请实施方式提供的一种基于全时域突变信息的故障识别系统的结构示意图;
图10为本申请实施方式提供的一种电子设备的结构示意图。
具体实施方式
现在参考附图介绍本申请的示例性实施方式,然而,本申请可以用许多不同的形式来实施,并且不局限于此处描述的实施例,提供这些实施例是为了详尽地且完全地公开本申请,并且向所属技术领域的技术人员充分传达本申请的范围。对于表示在附图中的示例性实施方式中的术语并不是对本申请的限定。在附图中,相同的单元/元件使用相同的附图标记。
除非另有说明,此处使用的术语(包括科技术语)对所属技术领域的技术人员具有通常的理解含义。另外,可以理解的是,以通常使用的词典限定的术语,应当被理解为与其相关领域的语境具有一致的含义,而不应该被理解为理想化的或过于正式的意义。
在新型电力系统中,由于故障特性受电力电子装置控制策略的影响,会使短路电流呈现幅值受限、频率非工频、相角受控等与同步发电机截然不同的特性,导致传统的差动保护在短路电流受控的场景下难以快速提取持续且稳定的工频分量,进而会出现灵敏度降低甚至不正确动作的风险,影响电力系统的安全运行。因此研究适用于不受电力电子装置控制影响的保护新原理,对此后规模化新能源并网的安全稳定运行具有重要意义。图1为根据本申请实施方式的基于全时域突变信息的故障识别方法100的流程图。如图1所示,本申请实施方式提供的基于全时域突变信息的故障识别方法,利用线路两侧各相的电流信号分别构造多阶矩阵,综合利用多阶矩阵能快速放大突变信号占比的特性,以及矩阵梯度可以精准表征数据突变程度的优势构建保护判据,以实现故障的高速可靠判别,从而解决新型电力系统中传统保护灵敏性降低以及不正确动作的风险问题。本申请可适应多种新能源电源接入送出的场景,且不依赖工频量,具有耐受过渡电阻及噪声的能力,速动性好,对于未来新能源高比例消纳、电网安全运行具有重要的工程意义,为未来进一步发展高比例的新能源电力电子系统提供前提与保障。
本申请实施方式提供的基于全时域突变信息的故障识别方法100,参照图1所示,可以通过如下步骤实现:
步骤101、当高压交流线路出现故障时,进行风电场侧和柔直侧的电流信号的采集,获取风电场侧和柔直侧的每相的故障电流。
本申请实施例中,风电场侧的每相的故障电流可以通过如下公式1表示,
Figure PCTCN2022116214-appb-000027
柔直侧的每相的故障电流可以通过如下公式2表示,
Figure PCTCN2022116214-appb-000028
其中,
Figure PCTCN2022116214-appb-000029
为风电场侧的
Figure PCTCN2022116214-appb-000030
相的故障电流;
Figure PCTCN2022116214-appb-000031
分别为预设的d轴和q轴的电流参考值;ω PLL为基频角频率;
Figure PCTCN2022116214-appb-000032
为初始相位角;ξ为二阶系统的阻尼比,ξ=k ip/2×(L×k ii) 1/2;ω d为阻尼固有频率,ω d=ω n(1-ξ 2) 1/2,ω n为二阶系统阻尼为零时的自然振荡角频率,ω n=(k ii/L) 1/2;β为系统阻尼角,β=arctan((1-ξ 2) 1/2/ξ);P为单相输出有功功率;u d为d轴电压;i d0为d轴初始电流;t为故障时间;k ip为电流控制环比例;k ii为积分时间常数;L为桥臂电感;
其中,
Figure PCTCN2022116214-appb-000033
为柔直侧的
Figure PCTCN2022116214-appb-000034
相的故障电流;E f为换流器内电势;Z eq为等效阻抗;ω和ω -分别表示正、负序电流的角频率;m为与短路类型有关的比例系数;
Figure PCTCN2022116214-appb-000035
为负序电流初始相角。
在本申请实施例中,首先分析新能源经柔直侧并网送出交流线路区内外故障的故障特性,明确区内外故障电流的特征,然后将两侧时间窗内采集的单相电流信号构造成多阶矩阵。风电换流器是永磁风机的唯一功率出口。由于过流能力有限,为保护换流器电力电子器件,控制系统主要选用限幅控制和负序电流控制。风电场侧每相的短路电流可通过上述公式1表示。
如上述公式1所示,风电场的短路电流受换流器控制系统的dq轴电流的参考值控制,风电场相当于一个受控电流源。由于换流器的耐受过电流能力有限,短路电流一般为最大额定电流电流的1.5-2倍。因此,风电场具有故障电流幅值受限的特性。
在一些实施例中,柔直侧的送端换流器由于与受控电流源连接,一般选用交流电压-频率控制,等效为受控电压源。柔直送端换流器闭锁前的故障电流可以通过如上公式2表示。
由上述公式2可知,故障发生时柔直换流器提供的短路电流同时具有正序分量和负序分量。换流器相当于受控电压源,其短路电流幅值取决于柔直换流器的的等效内电位和等效阻抗。
根据以上对换流器的故障特征分析可知,换流器故障电流幅值受限且缺少持续且稳定的工频分量,严重影响传统电流差动保护原理正确识别故障,保护装置计算过程中会出现灵敏度降低的问题,存在不正确动作的风险。同时不同的换流器控制体现出不同的控制响应特征,从而决定了故障后短路电流的突变特性不同且均与传统同步机不同。
步骤102、根据风电场侧和柔直侧的每相的故障电流分别构造多阶矩阵,并根据多阶矩阵分别计算风电场侧和柔直侧的每相的故障电流对应的突变特征值。
本申请实施例中,根据风电场侧和柔直侧的每相的故障电流分别构造多阶矩阵,并根据多阶矩阵分别计算风电场侧和柔直侧的每相的故障电流对应的突变特征值,包括:
对风电场侧和柔直侧的每相的故障电流,均按照如下方式操作,以分别获取风电场侧和柔直侧的每相的故障电流对应的突变特征值,包括:
将任一相的故障电流采样值确定为一个一维的数组,在采样时间内N个采样点构成的电流信号记作I={i 1,i 2,i 3,…,i N},则多阶矩阵可以通过如下公式3表示:
Figure PCTCN2022116214-appb-000036
将多阶矩阵I T转化为行向量和列向量的表达形式,列向量表达形式为:I T={I 1,I 2,I 3,…,I N},其中,第一个列向量内部元素为:I 1={i 1,i 2,i 3,…,i N} T;行向量表达形式为:I T={I 1 T,I 2 T,I 3 T,…,I N T } T,其中第一个行向量内部元素为:I 1 T={i 1,i 2,i 3,…,i N};
计算列向量表达形式的多阶矩阵对应的横向梯度矩阵,横向梯度矩阵可以通过如下公式4得到,
Figure PCTCN2022116214-appb-000037
计算行向量表达形式的多阶矩阵对应的纵向梯度矩阵,纵向梯度矩阵可以通过如下公式5得到,
Figure PCTCN2022116214-appb-000038
根据横向梯度矩阵和纵向梯度矩阵计算突变特征值,突变特征值可以通过如下公式6得到,
Figure PCTCN2022116214-appb-000039
其中,G为每相的故障电流对应的突变特征值;Gx和Gy分别为横向梯度矩阵和纵向梯度矩阵;Gx(i,j)为横向梯度矩阵中第i行第j列的元素;Gy(i,j)为纵向梯度矩阵中第i行第j列的元素。
在本申请实施例中,线路两侧任一相的电流采样值可以视作一个一维的数组,即一段时间内N个采样点的电流信号构成一维数据I,记作:I={i 1,i 2,i 3,…,i N}
对得到的N个采样点的电流信号构成一维数据I进行如下改进,得到多阶矩阵I T,改进方式如下:
构建一个N×N的空矩阵,将矩阵中所有的信号元素第一行按照时间顺序从i 0开始顺序排列,由于矩阵对称,第一列和第一行一样从i 0开始顺序排列。第二行开始,每个位置的元素和其左上角的元素相同,直至排满整个N×N矩阵。矩阵采用对称构型,这使得其及符合对称矩阵的定义I T=I T T,同时每一个元素都与其左上角的元素相同。当矩阵中所有信号元素均已按照规则排列,进而得到多阶矩阵I T
需要说明的是,当发生故障时,电流会出现短时间的突变,那么故障后的电流信号相对于之前的信号会出现一个较大的阶跃性跳变。进一步的为了将这种突变程度用具体的数值表示,引入矩阵梯度的概念。
矩阵梯度分为横向梯度和纵向梯度,主要反映的矩阵内相邻元素间的变化程度。以多阶矩阵I T为例,将其转化为列向量的表达形式:
列向量表达形式为:I T={I 1,I 2,I 3,…,I N},其中第一个列向量内部元素为:I 1={i 1,i 2,i 3,…,i N} T。其中,电流矩阵第一个列向量和下一个列向量作差除以1得到横向梯度矩阵的第一个列向量;中间的第n个列向量与两侧的电流列向量作差的平均值作为横向梯度矩阵的第n个列向量;最后一列列向量与前一列向量之差作为横向梯度矩阵的对后一个列向量。横向梯度矩阵Gx表达式为:
Figure PCTCN2022116214-appb-000040
同理,行向量表达形式为:I T={I 1 T,I 2 T,I 3 T,…,I N T} T,其中第一个行向量内部元素为:I 1 T={i 1,i 2,i 3,…,i N}。则有电流矩阵第一个行向量和下一个行向量作差除以1得到纵向梯度矩阵的第一个行向量;中间的第n个行向量与两侧的电流行向量作差的平均值作为纵向梯度矩阵的第n个行向量;最后一行行向量与前一行向量之差作为纵向梯度矩阵的对后一个行向量。纵向梯度矩阵Gy表达式为:
Figure PCTCN2022116214-appb-000041
对于任一相,在获取到横向梯度矩阵Gx和纵向梯度矩阵Gy后,将求得的横向梯度矩阵Gx和纵向梯度矩阵Gy取绝对值,求二者内部所有元素之和,作为该时间窗内采集信号的突变特征值,即可得到任一相的电流信号对应的突变特征值G,表达式为:
Figure PCTCN2022116214-appb-000042
即取每个时间窗的突变特征值G用于反映这段信号的突变特征值;其中,G为每相的故障电流对应的突变特征值;Gx和Gy分别为横向梯度矩阵和纵向梯度矩阵;Gx(i,j)为横向梯度矩阵中第i行第j列的元素;Gy(i,j)为纵向梯度矩阵中第i行第j列的元素。
在本申请实施例中,风电场侧和柔直侧的每相的故障电流均对应一个突变特征值。
步骤103、根据风电场侧和柔直侧的每相的故障电流对应的突变特征值以及预设判据,确定故障类型。
本申请实施例中,根据风电场侧和柔直侧的每相的故障电流对应的突变特征值以及预设判据,确定故障类型,包括:
对于任一相,若任一相对应的风电场侧和柔直侧的故障电流满足预设判据,确定任一相的故障类型为区内故障;
若任一相对应的风电场侧和柔直侧的故障电流不满足预设判据,确定任一相的故障类型为区外故障;
预设判据包括ΔG=|G 1-G 2|>G set,其中,G 1和G 2分别为风电场侧的每相的故障电流和柔直侧的每相的故障电流对应的突变特征值;G set为预设整定值。
本申请其他实施例中,确定故障类型为区内故障的相为故障相,并根据故障相的数量进行保护出口。
其中,若故障相的数量小于或等于预设数量,控制继电保护装置发出故障相跳闸指令,控制故障相跳闸,控制非故障相正常运行;若故障相的数量大于预设数量,控制继电保护装置发出三相跳闸指令,控制三相全部跳闸。
本申请实施例中,需要利用区内故障时电流信号的多维度突变特征值不同,构建判),再通过比较判据中的实际运算值与整定值之间的大小关系来识别故障类型,进而根据故障类型启用相应的保护措施。
在正常稳态运行时,风电场功率完全经线路流向柔直侧,此时线路中全部流过穿越性电流,线路两侧采集到的交流电流是相同的正弦波,那么相同时间窗两侧采集的电流信号的突变特征值G也应该基本相同。
区内故障时,由于控制策略以及调节速度的差异,两侧的故障电流会在故障发生后的短时间内出现较大幅度的调整,整个时间窗的突变特征值都会因为采集到的故障点在短时间内出现变化,且两侧采集的电流信号的变化不同,计算得到的突变特征值G值也会存在较大差异。
区外故障时,被保护线路同样流过穿越性电流,故两侧的同相电流信号的多阶矩阵梯度的突变特征值G应该相同,理论上两侧采集的电流信号的突变特征值G值差应该趋近于零。
因此,根据以上故障特征分析可以构造保护判据为:
ΔG=|G 1-G 2|>G set
其中,G 1、G 2分别表示线路两端电流信号对应的突变特征值,|·|表示取绝对值;G set为保护的主判据的整定值,该值按躲过外部故障时的最大振幅误差整定,考虑电流互感器(Current transformer,CT)的最大传输误差为±10%,且电容对故障电流的影响较小,将两侧的最大振幅误差设为20%,同时考虑特殊情况留有一定裕度。在本申请实施例中,为了保证采样点数满足计算要求,越短的时间窗要求的采样频率越高,但工业应用难以达到较高的采样频率,所以此处采用10ms时间窗内的电流信号构造多阶矩阵,再求矩阵梯度的绝对值之和,从而确定多突变特征值。
结合图2所示,在本申请实施例中通过比较判据实际运算值|G1-G2|与整定值Gset之间的大小关系来识别故障类型,进而根据故障类型启用相应的保护措施。具体流程为:当保护启动后,每套保护装置分相进行故障的判断,提取故障时刻后10ms的差动电流数据,并根据所提保护判据进行计算。对于任一相,如果满足公式保护判据,即多维度突变特征值之差大于定值,则确定故障类型为区内故障,此时保护出口;反之,则确定故障类型为区外故障,保护复归。
值得注意的是,在确定了故障类型后,确定故障类型为区内故障的相为故障相,若故障相为单相,则继电保护装置发出故障相跳闸命令,非故障相仍继续运行。若两相或三相满足判据,则继电保护装置发出三相跳闸指令,控制三相全部跳闸。
规模化新能源并入电网后,传统保护灵敏性下降,为了保证系统安全可靠的运行,本方法通过理论分析与仿真验证证实了区内外故障时突变特征值存在明显差异,最终提出了一种采用多维突变信息的高压交流线路保护方法,本申请实施例提供的方法解决了传统保护因故障电流受控无法提供持续且稳定的工频分量导致的灵敏性降低以及不正确动作的风险问题,适用不同类型新能源场站,本申请实施例提供的方法具有如下特点:
1)速动性强,保护的出口时间在5ms以内;
2)可靠性强,保护利用区故障后两侧短路电流的多维度突变特征值的不同构造保护判据,不受两侧电源特性的影响,且在大于30dB的噪声下仍可正确动作;与传统差动保护相比,在新能源接入柔直系统的双侧受控场景下仍然可以保证较高的灵敏度实现可靠动作。
3)过渡电阻耐受能力强,100Ω过渡电阻下保护仍可正确动作。
以下具体举例说明本申请的实施方式
在电磁暂态仿真软件(Power Systems Computer Aided Design,PSCAD)/直流电磁暂态计算程序软件(Electromagnetic Transients including DC,EMTDC)中搭建图3所示的额定电压220千伏(kilovolt,kV)直驱风电场经±500kV柔直输电线路并网系统,系统容量为200兆伏安(megavolt-ampere,MVA)。风电场采用单个风机进行等 效,风电机组单机容量5兆瓦(million watt,MW)。风电场变压器到柔直送端换流器交流线路长度定为20千米(kilometre,km)。
如图3所示,在交流线路上设置了五个故障点,其中F1、F5为区外故障点,区内内部故障包括F2风场侧保护线路出口、F4柔直侧线路出口处以及F3线路中点故障。电流信号采样频率为4kHz,时间窗选择为10ms。
整定设置应避免出现外部故障时的最大振幅误差。电流互感器(CT)的最大传输误差为±10%,两侧的最大振幅误差为20%。虽然电容电流的影响很小,但采用可调容余度来避免电容电流的影响。本文将裕度设置为20%,并可根据实际系统参数进行调整。当两侧存在20%的振幅误差时,外部故障时突变特征值之差G增加到30。因此,将G set的常数值设置为30。
图4示出了在区内F2处出现不同故障类型的故障后对应的保护动作情况的示意图,图5示出了在区内F3处出现不同故障类型的故障后对应的保护动作情况的示意图,以及图6示出了在区内F4处出现不同故障类型的故障后保护动作情况的示意图,图7示出了在区外F1处出现不同故障类型的故障后保护动作情况的示意图。另外,表1给出了5ms时区内F2、F3、F4,区外F1、F5位置处不同类型故障的保护特变特征值之差。
由图4至图7可以看出,所提出的保护原理在不同场景下(不同故障类型、不同故障位置)均具有良好的动作性能:区内故障时,故障相的突变特征值之差在5ms之内均大于保护判据整定值,保护可靠动作;区外故障时,故障相与非故障相均未越过定值,保护可靠不动作,验证了所提保护的有效性。
为验证所提保护对过渡电阻的适应性,以F3处发生区内故障为例,分别对过渡电阻25Ω、50Ω、75Ω、100Ω的A相接地故障及BC相间故障进行分析。表2分别给出了经过渡电阻时单相接地故障及两相相间故障下,所提保护的突变特征值差动量。
从表2可以看出,随着过渡电阻的增大,电流信号的突变程度逐渐减小,两侧电流信号突变特征值的差异减小,所以突变特征值差动量减小。尽管存在灵敏性下降的趋势,但所提保护在100Ω的高阻故障场景下仍然能够可靠地反映故障,考虑到220kV系统最大过渡电阻为100Ω,因此以上结果基本可以满足所提保护在高阻故障场景下具有良好的性能。
表3给出的了F3处发生故障时不同噪声场景下5ms后的保护动作性能。从表3可以知,噪声增大对故障相的影响较小,保护能够正确反映故障;对于非故障相来说,噪声增大,会导致两侧电流出现差异,进而导致奇异值差动量有增加的趋势,但仍远低于整定值。在30dB的高噪声场景下,保护仍然能够正确区分故障类型,可以证明所提方法具有较好的抗噪能力。
Figure PCTCN2022116214-appb-000043
表1
Figure PCTCN2022116214-appb-000044
表2
Figure PCTCN2022116214-appb-000045
表3
为了测试所提保护的优越性,如图8所示,将本申请实施例提出的保护方法如图8中的A与传统差动保护方法如图8中的B进行动作性能对比。当三相相间故障时,传统基于工频量的差动保护保护在5ms时间内保护启动速度慢,并且在5ms时A相存在明显的回落趋势,保护出口的差动电流与制动电流的比值勉强超过整定值,灵敏度严重下降,存在拒动的风险。而本文所提出的保护新原理在5ms内故障响应更为迅速,灵敏度更高,可以快速识别故障,且在噪声和电阻接地场景下仍能保证正常的性能。
本申请提出了电流采样数据多阶矩阵变换概念,多阶矩阵变换能快速放大故障电流突变信号的占比,从根本上解决了电力电子器件故障特征“弱”的问题;提出了利用矩阵梯度可以精准表征数据突变程度的优势构建保护判据,以实现故障的高速可靠判别,从而解决新型电力系统中传统保护灵敏性降低的问题。图9为根据本申请实施方式的基于全时域突变信息的故障识别系统900的结构示意图。如图9所示,本申请实施方式提供的基于全时域突变信息的故障识别系统900,包括:故障电流获取单元901、突变特征值计算单元902和故障类型确定单元903。
故障电流获取单元901,用于当高压交流线路出现故障时,进行风电场侧和柔直侧的电流信号的采集,获取风电场侧和柔直侧的每相的故障电流;
突变特征值计算单元902,用于根据风电场侧和柔直侧的每相的故障电流分别构造多阶矩阵,并根据多阶矩阵分别计算风电场侧和柔直侧的每相的故障电流对应的突变特征值;
故障类型确定单元903,用于根据风电场侧和柔直侧的每相的故障电流对应的突变特征值以及预设判据,确定故障类型。
在一些实施例中,在故障电流获取单元901,风电场侧的每相的故障电流为:
Figure PCTCN2022116214-appb-000046
柔直侧的每相的故障电流为:
Figure PCTCN2022116214-appb-000047
其中,
Figure PCTCN2022116214-appb-000048
为风电场侧的
Figure PCTCN2022116214-appb-000049
相的故障电流;
Figure PCTCN2022116214-appb-000050
分别为预设的d轴和q轴的电流参考值;ω PLL为基频角频率;
Figure PCTCN2022116214-appb-000051
为初始相位角;ξ为二阶系统的阻尼比,ξ=k ip/2×(L×k ii) 1/2;ω d为阻尼固有频率,ω d=ω n(1-ξ 2) 1/2,ω n为二阶系统阻尼为零时的自然振荡角频率,ω n=(k ii/L) 1/2;β为系统阻尼角,β=arctan((1-ξ 2) 1/2/ξ);P为单相输出有功功率;u d为d轴电压;i d0为d轴初始电流;t为故障时间;k ip为电流控制环比例;k ii为积分时间常数;L为桥臂电感;
其中,
Figure PCTCN2022116214-appb-000052
为柔直侧的
Figure PCTCN2022116214-appb-000053
相的故障电流;E f为换流器内电势;Z eq为等效阻抗;ω和ω -分别表示正、负序电流的角频率;m为与短路类型有关的比例系数;
Figure PCTCN2022116214-appb-000054
为负序电流初始相角。
在一些实施例中,突变特征值计算单元902,还用于对风电场侧和柔直侧的每相的故障电流,均按照如下方式操作,以分别获取风电场侧和柔直侧的每相的故障电流对应的突变特征值,包括:
将任一相的故障电流采样值确定为一个一维的数组,在采样时间内N个采样点构成的电流信号记作I={i 1,i 2,i 3,…,i N},则多阶矩阵为:
Figure PCTCN2022116214-appb-000055
将多阶矩阵I T转化为行向量和列向量的表达形式,列向量表达形式为:I T={I 1,I 2,I 3,…,I N},其中,第一个列向量内部元素为:I 1={i 1,i 2,i 3,…,i N} T;行向量表达形式为:I T={I 1 T,I 2 T,I 3 T,…,I N T} T,其中第一个行向量内部元素为:I 1 T={i 1,i 2,i 3,…,i N};
计算列向量表达形式的多阶矩阵对应的横向梯度矩阵,包括:
Figure PCTCN2022116214-appb-000056
计算行向量表达形式的多阶矩阵对应的纵向梯度矩阵,包括:
Figure PCTCN2022116214-appb-000057
根据横向梯度矩阵和纵向梯度矩阵计算突变特征值,包括:
Figure PCTCN2022116214-appb-000058
其中,G为每相的故障电流对应的突变特征值;Gx和Gy分别为横向梯度矩阵和纵向梯度矩阵;Gx(i,j)为横向梯度矩阵中第i行第j列的元素;Gy(i,j)为纵向梯度矩阵中第i行第j列的元素。
在一些实施例中,故障类型确定单元903,还用于对于任一相,若任一相对应的风电场侧和柔直侧的故障电流满足预设判据,确定任一相的故障类型为区内故障;
若任一相对应的风电场侧和柔直侧的故障电流不满足预设判据,确定任一相的故障类型为区外故障;
预设判据包括ΔG=|G 1-G 2|>G set,其中,G 1和G 2分别为风电场侧的每相的故障电流和柔直侧的每相的故障电流对应的突变特征值;G set为预设整定值。
在一些实施例中,故障类型确定单元903,还用于确定故障类型为区内故障的相为故障相,并根据故障相的数量进行保护出口;
其中,若故障相的数量小于或等于预设数量,控制继电保护装置发出故障相跳闸指令,控制故障相跳闸,控制非故障相正常运行;若故障相的数量大于预设数量,控制继电保护装置发出三相跳闸指令,控制三相全部跳闸。
本申请提供一种电子设备1000,参照图10所示,图10为根据本申请实施方式的电子设备1000的结构示意图,包括:存储器1001、处理器1002以及存储在存储器1001中并可在处理器1002上运行的计算机程序,处理器1002执行计算机程序时实现上述图1所示的故障识别的方法的步骤。
本申请提供一种计算机可读存储介质,计算机可读存储介质存储有计算机程序,计算机程序被处理器执行时实现上述图1所示的故障识别的方法的步骤。
已经通过参考少量实施方式描述了本申请。然而,本领域技术人员所公知的,正如附带的专利权利要求所限定的,除了本申请以上公开的其他的实施例等同地落在本申请的范围内。
通常地,在权利要求中使用的所有术语都根据他们在技术领域的通常含义被解释,除非在其中被另外明确地定义。所有的参考“一个//该[装置、组件等]”都被开放地解释为装置、组件等中的至少一个实例,除非另外明确地说明。这里公开的任何方法的步骤都没必要以公开的准确的顺序运行,除非明确地说明。
本领域内的技术人员应明白,本申请的实施例可提供为方法、系统、或计算机程序产品。因此,本申请可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且,本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本申请是参照根据本申请实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备 的处理器以产生一个机器,使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中,使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品,该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上,使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理,从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
最后应当说明的是:以上实施例仅用以说明本申请的技术方案而非对其限制,尽管参照上述实施例对本申请进行了详细的说明,所属领域的普通技术人员应当理解:依然可以对本申请的具体实施方式进行修改或者等同替换,而未脱离本申请精神和范围的任何修改或者等同替换,其均应涵盖在本申请的权利要求保护范围之内。
工业实用性
本申请提供了一种基于全时域突变信息的故障识别方法、系统、电子设备及计算机可读存储介质,当高压交流线路出现故障时,进行风电场侧和柔直侧的电流信号的采集,获取风电场侧和柔直侧的每相的故障电流;根据风电场侧和柔直侧的每相的故障电流分别构造多阶矩阵,并根据多阶矩阵分别计算风电场侧和柔直侧的每相的故障电流对应的突变特征值;根据风电场侧和柔直侧的每相的故障电流对应的突变特征值以及预设判据,确定故障类型;本申请的方法利用线路两侧各相的电流信号分别构造多阶矩阵,综合利用多阶矩阵能快速放大突变信号占比的特性,以及矩阵梯度可以精准表征数据突变程度的优势构建保护判据,以实现故障的高速可靠判别,从而解决新型电力系统中传统保护灵敏性降低以及不正确动作的风险问题。本申请可适应多种新能源电源接入送出的场景,且不依赖工频量,具有耐受过渡电阻及噪声的能力,速动性好,对于未来新能源高比例消纳、电网安全运行具有重要的工程意义,为未来进一步发展高比例的新能源电力电子系统提供前提与保障。

Claims (12)

  1. 一种基于全时域突变信息的故障识别方法,所述方法包括:
    当高压交流线路出现故障时,进行风电场侧和柔直侧的电流信号的采集,获取所述风电场侧和所述柔直侧的每相的故障电流;
    根据所述风电场侧和所述柔直侧的每相的故障电流分别构造多阶矩阵,并根据所述多阶矩阵分别计算所述风电场侧和所述柔直侧的每相的故障电流对应的突变特征值;
    根据所述风电场侧和所述柔直侧的每相的故障电流对应的突变特征值以及预设判据,确定故障类型。
  2. 根据权利要求1所述的方法,其中,所述风电场侧的每相的故障电流为:
    Figure PCTCN2022116214-appb-100001
    所述柔直侧的每相的故障电流为:
    Figure PCTCN2022116214-appb-100002
    其中,
    Figure PCTCN2022116214-appb-100003
    为所述风电场侧的
    Figure PCTCN2022116214-appb-100004
    相的故障电流;
    Figure PCTCN2022116214-appb-100005
    分别为预设的d轴和q轴的电流参考值;ω PLL为基频角频率;
    Figure PCTCN2022116214-appb-100006
    为初始相位角;ξ为二阶系统的阻尼比,ξ=k ip/2×(L×k ii) 1/2;ω d为阻尼固有频率,ω d=ω n(1-ξ 2) 1/2,ω n为二阶系统阻尼为零时的自然振荡角频率,ω n=(k ii/L) 1/2;β为系统阻尼角,β=arctan((1-ξ 2) 1/2/ξ);P为单相输出有功功率;u d为d轴电压;i d0为d轴初始电流;t为故障时间;k ip为电流控制环比例;k ii为积分时间常数;L为桥臂电感;
    其中,
    Figure PCTCN2022116214-appb-100007
    为所述柔直侧的
    Figure PCTCN2022116214-appb-100008
    相的故障电流;E f为换流器内电势;Z eq为等效阻抗;ω和ω -分别表示正、负序电流的角频率;m为与短路类型有关的比例系数;
    Figure PCTCN2022116214-appb-100009
    为负序电流初始相角。
  3. 根据权利要求1所述的方法,其中,所述根据所述风电场侧和所述柔直侧的每相的故障电流分别构造多阶矩阵,并根据所述多阶矩阵分别计算所述风电场侧和所述柔直侧的每相的故障电流对应的突变特征值,包括:
    对所述风电场侧和所述柔直侧的每相的故障电流,均按照如下方式操作,以分别获取所述风电场侧和所述柔直侧的每相的故障电流对应的所述突变特征值,包括:
    将任一相的故障电流采样值确定为一个一维的数组,在采样时间内N个采样点构成的电流信号记作I={i 1,i 2,i 3,…,i N},则多阶矩阵为:
    Figure PCTCN2022116214-appb-100010
    将多阶矩阵I T转化为行向量和列向量的表达形式,列向量表达形式为:I T={I 1,I 2,I 3,…,I N},其中,第一个列向量内部元素为:I 1={i 1,i 2,i 3,…,i N} T;行向量表达形式为:I T={I 1 T,I 2 T,I 3 T,…,I N T} T,其中第一个行向量内部元素为:I 1 T={i 1,i 2,i 3,…,i N};
    计算所述列向量表达形式的多阶矩阵对应的横向梯度矩阵,包括:
    Figure PCTCN2022116214-appb-100011
    计算所述行向量表达形式的多阶矩阵对应的纵向梯度矩阵,包括:
    Figure PCTCN2022116214-appb-100012
    根据所述横向梯度矩阵和所述纵向梯度矩阵计算所述突变特征值,包括:
    Figure PCTCN2022116214-appb-100013
    其中,G为所述每相的故障电流对应的突变特征值;Gx和Gy分别为所述横向梯度矩阵和所述纵向梯度矩阵;Gx(i,j)为所述横向梯度矩阵中第i行第j列的元素;Gy(i,j)为所述纵向梯度矩阵中第i行第j列的元素。
  4. 根据权利要求1所述的方法,其中,所述根据所述风电场侧和所述柔直侧的每相的故障电流对应的突变特征值以及预设判据,确定故障类型,包括:
    对于任一相,若所述任一相对应的风电场侧和柔直侧的故障电流满足所述预设判据,确定所述任一相的故障类型为区内故障;
    若所述任一相对应的风电场侧和柔直侧的故障电流不满足所述预设判据,确定所述任一相的故障类型为区外故障;
    所述预设判据包括ΔG=|G 1-G 2|>G set,其中,G 1和G 2分别为所述风电场侧的每相的故障电流和所述柔直侧的每相的故障电流对应的突变特征值;G set为预设整定值。
  5. 根据权利要求1所述的方法,其中,所述方法还包括:
    确定所述故障类型为区内故障的相为故障相,并根据所述故障相的数量进行保护出口;
    其中,若所述故障相的数量小于或等于预设数量,控制继电保护装置发出故障相跳闸指令,控制所述故障相跳闸,控制非故障相正常运行;若所述故障相的数量大于所述预设数量,控制所述继电保护装置发出三相跳闸指令,控制三相全部跳闸。
  6. 一种基于全时域突变信息的故障识别系统,所述系统包括:
    故障电流获取单元,用于当高压交流线路出现故障时,进行风电场侧和柔直侧的电流信号的采集,获取所述风电场侧和所述柔直侧的每相的故障电流;
    突变特征值计算单元,用于根据所述风电场侧和所述柔直侧的每相的故障电流分别构造多阶矩阵,并根据所述多阶矩阵分别计算所述风电场侧和所述柔直侧的每相的故障电流对应的突变特征值;
    故障类型确定单元,用于根据所述风电场侧和所述柔直侧的每相的故障电流对应的突变特征值以及预设判据,确定故障类型。
  7. 根据权利要求6所述的系统,其中,在所述故障电流获取单元,所述风电场侧的每相的故障电流为:
    Figure PCTCN2022116214-appb-100014
    所述柔直侧的每相的故障电流为:
    Figure PCTCN2022116214-appb-100015
    其中,
    Figure PCTCN2022116214-appb-100016
    为所述风电场侧的
    Figure PCTCN2022116214-appb-100017
    相的故障电流;
    Figure PCTCN2022116214-appb-100018
    分别为预设的d轴和q轴的电流参考值;ω PLL为基频角频率;
    Figure PCTCN2022116214-appb-100019
    为初始相位角;ξ为二阶系统的阻尼比,ξ=k ip/2×(L×k ii) 1/2;ω d为阻尼固有频率,ω d=ω n(1-ξ 2) 1/2,ω n为二阶系统阻尼为零时的自然振荡角频率,ω n=(k ii/L) 1/2;β为系统阻尼角,β=arctan((1-ξ 2) 1/2/ξ);P为单相输出有功功率;u d为d轴电压;i d0为d轴初始电流;t为故障时间;k ip为电流控制环比例;k ii为积分时间常数;L为桥臂电感;
    其中,
    Figure PCTCN2022116214-appb-100020
    为所述柔直侧的
    Figure PCTCN2022116214-appb-100021
    相的故障电流;E f为换流器内电势;Z eq为等效阻抗;ω和ω -分别表示正、负序电流的角频率;m为与短路类型有关的比例系数;
    Figure PCTCN2022116214-appb-100022
    为负序电流初始相角。
  8. 根据权利要求6所述的系统,其中,所述突变特征值计算单元,还用于对所述风电场侧和所述柔直侧的每相的故障电流,均按照如下方式操作,以分别获取所述风电场侧和所述柔直侧的每相的故障电流对应的所述突变特征值,包括:
    将任一相的故障电流采样值确定为一个一维的数组,在采样时间内N个采样点构成的电流信号记作I={i 1,i 2,i 3,…,i N},则多阶矩阵为:
    Figure PCTCN2022116214-appb-100023
    将多阶矩阵I T转化为行向量和列向量的表达形式,列向量表达形式为:I T={I 1,I 2,I 3,…,I N},其中,第一个列向量内部元素为:I 1={i 1,i 2,i 3,…,i N} T; 行向量表达形式为:I T={I 1 T,I 2 T,I 3 T,…,I N T} T,其中第一个行向量内部元素为:I 1 T={i 1,i 2,i 3,…,i N};
    计算所述列向量表达形式的多阶矩阵对应的横向梯度矩阵,包括:
    Figure PCTCN2022116214-appb-100024
    计算所述行向量表达形式的多阶矩阵对应的纵向梯度矩阵,包括:
    Figure PCTCN2022116214-appb-100025
    根据所述横向梯度矩阵和所述纵向梯度矩阵计算所述突变特征值,包括:
    Figure PCTCN2022116214-appb-100026
    其中,G为所述每相的故障电流对应的突变特征值;Gx和Gy分别为所述横向梯度矩阵和所述纵向梯度矩阵;Gx(i,j)为所述横向梯度矩阵中第i行第j列的元素;Gy(i,j)为所述纵向梯度矩阵中第i行第j列的元素。
  9. 根据权利要求6所述的系统,其中,所述故障类型确定单元,还用于对于任一相,若所述任一相对应的风电场侧和柔直侧的故障电流满足所述预设判据,确定所述任一相的故障类型为区内故障;
    若所述任一相对应的风电场侧和柔直侧的故障电流不满足所述预设判据,确定所述任一相的故障类型为区外故障;
    所述预设判据包括ΔG=|G 1-G 2|>G set,其中,G 1和G 2分别为所述风电场侧的每相的故障电流和所述柔直侧的每相的故障电流对应的突变特征值;G set为预设整定值。
  10. 根据权利要求9所述的系统,其中,所述故障类型确定单元,还用于确定所述故障类型为区内故障的相为故障相,并根据所述故障相的数量进行保护出口;
    其中,若所述故障相的数量小于或等于预设数量,控制继电保护装置发出故障相跳闸指令,控制所述故障相跳闸,控制非故障相正常运行;若所述故障相的数量大于所述预设数量,控制所述继电保护装置发出三相跳闸指令,控制三相全部跳闸。
  11. 一种电子设备,包括:存储器、处理器以及存储在所述存储器中并可在所述处理器上运行的计算机程序,所述处理器执行所述计算机程序时实现如所述权利要求1-5任意一项所述方法的步骤。
  12. 一种计算机可读存储介质,所述计算机可读存储介质存储有计算机程序,所述计算机程序被处理器执行时实现如所述权利要求1-5中任一项所述方法的步骤。
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