CN112858784A - Traction power supply system-regional power grid parallel harmonic resonance frequency identification method - Google Patents

Traction power supply system-regional power grid parallel harmonic resonance frequency identification method Download PDF

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CN112858784A
CN112858784A CN202110363959.1A CN202110363959A CN112858784A CN 112858784 A CN112858784 A CN 112858784A CN 202110363959 A CN202110363959 A CN 202110363959A CN 112858784 A CN112858784 A CN 112858784A
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harmonic
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power grid
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魏巍
徐琳
刘畅
靳旦
刘雪原
杨华
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Electric Power Research Institute of State Grid Sichuan Electric Power Co Ltd
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    • G01—MEASURING; TESTING
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Abstract

A method for identifying parallel harmonic resonant frequency of a traction power supply system-regional power grid is characterized in that an electric energy quality synchronous monitoring device is utilized to record the voltage waveform of any phase A, phase B or phase C of any bus of a regional power grid on the high-voltage side of a traction transformer and the voltage waveform of the locomotive side, so as to estimate the amplification factor of the phase A, phase B or phase C of the bus from a high-voltage circuit on the locomotive side to the regional power grid on the high-voltage side of the traction transformer by transmitting harmonic waves by a locomotive, and further judge whether the parallel harmonic resonant frequency exists in the regional power grid of the railway traction power supply. The method can identify whether the railway traction power supply system-regional power grid has parallel harmonic resonance frequency, and can quantitatively reflect the harmonic influence of the locomotive transmission harmonic on the regional power system; compared with a simulation analysis method, the method does not need to establish a traction power supply system-regional power grid harmonic model, and is simpler and accurate enough.

Description

Traction power supply system-regional power grid parallel harmonic resonance frequency identification method
Technical Field
The invention relates to the technical field of railway traction power supply system electric energy quality, in particular to a traction power supply system-regional power grid parallel harmonic resonance frequency identification method.
Background
By 7 months in 2020, the business mileage of the Chinese high-speed rail reaches more than 3.6 kilometers and exceeds two thirds of the total mileage of the world high-speed rail. According to the scheme of the advanced planning of new-era traffic compendium of the strong nation railways released by the state iron group in the day ahead: in the next 30 years, 20 kilometers of a national railway network are reached, wherein 7 kilometers of high-speed rails are reached, and the number of high-speed rails is more than 50 kilometers. In general, the current high-speed railways form large-scale and networked distribution in regional power grids, the development is more and more rapid in the future, and the load ratio is remarkably increased year by year. The traction power supply system with high power, variable working conditions (traction, coasting and regeneration), high-speed movement, high driving density and networking can lead the power supply pressure and the power quality of the regional power grid to be increased rapidly. Harmonics are one of the directions that have been of greatest interest in the field of electrical energy quality: the problems of harmonic amplification and harmonic resonance of the traction network are reported in many documents, and lightning arrester explosion and explosion of capacitive equipment such as a voltage transformer and a capacitor bank are often caused; meanwhile, the research for analyzing the harmonic influence of the railway locomotive transmitted harmonic on the high-voltage side area power grid of the traction transformer is also becoming one of the hot spots of the harmonic research.
The existing method for analyzing the parallel harmonic resonance frequency identification of the railway traction power supply system-regional power grid is mainly based on the system mathematical model analysis: the analysis is carried out by establishing a complete fundamental wave/harmonic wave model of 'regional power grid-traction power supply system-locomotive'. The analysis method comprises a harmonic transmission amplification method, a frequency spectrum analysis method, a resonance mode analysis method and an S-domain or frequency-domain transfer function method. However, these methods require obtaining accurate system components and structural parameters, the modeling process is complicated, and only qualitative judgment can be made on whether the resonant frequency exists, and the amplification factor of the railway locomotive transmitting harmonic to the high-voltage side of the traction transformer cannot be quantitatively given.
Disclosure of Invention
The invention aims to provide a method for identifying a parallel harmonic resonance frequency of a traction power supply system-regional power grid.
The technical scheme for realizing the purpose of the invention is as follows:
a method for identifying the parallel harmonic resonance frequency of a traction power supply system-regional power grid comprises the following steps,
step 1: selecting a time period in which only one locomotive runs, and acquiring voltage waveforms K of any one of A phase, B phase and C phase of any one bus of a traction transformer high-voltage side area power grid with an effective sampling rate larger than r x H x 50Hz, and voltage waveforms P of a locomotive grid side high-voltage circuit; wherein H is the highest harmonic number to be analyzed, and r is a multiple of the highest harmonic number;
step 2: and respectively carrying out fast Fourier transform on the voltage waveform K and the voltage waveform P to obtain: the square root mean time series of the fundamental voltage and the harmonic voltage of K, and the square root mean time series of the fundamental voltage and the harmonic voltage of P; further obtaining: time series of voltage content of each subharmonic of K
Figure BDA0003006648640000021
P subharmonic voltage content time series
Figure BDA0003006648640000022
Wherein H is the harmonic number, H is 2, …, H;
and step 3: for any h-th harmonic wave, a sliding time window with the window width of L and the sliding step length of L/2 is adopted, and
Figure BDA0003006648640000023
and
Figure BDA0003006648640000024
respectively dividing the voltage into N sub-time periods to obtain N corresponding harmonic voltage content sections; obtaining the relation Y between the h-order harmonic voltage content of K and P in the harmonic voltage content section by fitting a binary linear regression equationi＝λiXi+bi+εi(ii) a Wherein i is the serial number of the harmonic voltage content section, i is 1, …, N, YiIs a harmonic of K, XiIs a harmonic of P and is,λiis the slope of the regression line, i.e. the harmonic amplification of the h harmonic from P to K, biIs intercept, εiIs regression residual error;
and 4, step 4: performing linear relation significance test on the h-order harmonic voltage content of K and P in the harmonic voltage content section i to obtain linearity Fi：
Figure BDA0003006648640000025
Figure BDA0003006648640000031
Figure BDA0003006648640000032
wherein ,
Figure BDA0003006648640000033
is the jth value in the ith harmonic voltage content section of P,
Figure BDA0003006648640000038
is the jth value in the ith harmonic voltage content section of K;
and 5: selection with FiIncrease of lambda with consistent aggregation effectiLet these λ beiAverage value of (2)
Figure BDA0003006648640000034
Harmonic amplification from P to K as h harmonic; and if the amplification factor is more than 1, judging that the parallel harmonic resonant frequency of h times exists in the railway traction power supply system.
Further, in step 5, a selection is made that follows FiIncrease of lambda with consistent aggregation effectiThe method comprises the following steps:
5.1 mixing N FiSorting from big to small; let m be λ to be selectediThe number of (c) to the percentage of N;
5.2 calculate M% N, get M by rounding down;
5.3 calculate the first M FiVariance Var1 of and N FiVariance of (Var 2)
Figure BDA0003006648640000039
Namely, it is
Figure BDA0003006648640000035
5.4 if
Figure BDA0003006648640000036
Less than a threshold value delta, the selected lambda is determinediWith FiHas a consistent aggregation effect; otherwise, returning m to m-1 to step 5.2 for recalculation until m-1 is satisfied
Figure BDA0003006648640000037
Less than a threshold value delta.
Furthermore, in the 5.1, the method further includes setting the threshold Δ ═ m%.
Compared with the prior art, the invention has the advantages that,
1. the method can identify whether the railway traction power supply system-regional power grid has parallel harmonic resonance frequency, and can quantitatively reflect the harmonic influence of the locomotive transmission harmonic on the regional power system.
2. Compared with a simulation analysis method, the method does not need to establish a traction power supply system-regional power grid harmonic model, and is simpler and accurate enough.
Drawings
Fig. 1 is a schematic diagram of a railway traction power supply system-regional power grid structure.
Detailed Description
The following further describes the embodiments of the present invention with reference to the drawings.
As shown in fig. 1, the power quality synchronous monitoring device is used to record the voltage waveform of any phase a, B or C of the bus of the high-voltage side regional power grid of the traction transformer and the voltage waveform of the locomotive side to estimate the amplification factor of the phase a, B or C of the bus from the high-voltage side circuit of the locomotive to the high-voltage side regional power grid of the traction transformer by the harmonic emitted by the locomotive, so as to judge whether the parallel harmonic resonant frequency exists in the regional power grid of the railway traction power supply system. Taking phase a of the bus 1 in fig. 1 as an example, the steps are:
a) and selecting a time period in which only one locomotive runs in the power supply interval, and acquiring the voltage waveform of the phase A of the traction transformer high-voltage side regional power grid bus 1 and the voltage waveform of a locomotive grid side high-voltage circuit (measured by a voltage transformer between a pantograph and a main circuit breaker) with effective sampling rates larger than r H50 Hz (H is the highest harmonic frequency to be analyzed, and r is a multiple of the highest harmonic frequency), wherein the voltage waveforms are respectively marked as K and P.
b) A fundamental voltage and 2 to H harmonic voltages of a voltage waveform K of an A phase of a bus 1 and a voltage waveform P of a high-voltage circuit on a locomotive grid side are extracted by a Fast Fourier Transform (FFT) method. And obtaining the root mean square time sequence of the A phase of the regional power grid bus 1, the fundamental voltage of the locomotive grid side high-voltage circuit and the 2-H harmonic voltage. Dividing the harmonic amplitude of h 2 or above by the fundamental amplitude (h 1) 100% to obtain the harmonic voltage content rate, and obtaining the time sequence of the harmonic voltage content rate of K
Figure BDA0003006648640000041
P subharmonic voltage content time series
Figure BDA0003006648640000042
Wherein H is the harmonic order, H is 2, …, H.
c) For any h-th harmonic, dividing the harmonic voltage content time sequence of K and P into sub-time periods with the widths of up and the sliding step length of L/2 by adopting a sliding time window, and obtaining N-section data in total. The window width L can be 100-. For the ith data segment, fitting the relation between the h harmonic of P and the h harmonic of K by using a binary linear regression equation, wherein the expression of the obtained equation is Yi＝λiXi+bi+εi，XiI-th harmonic data segment, Y, representing PiI-th harmonic data segment, λ, representing KiThe slope of the regression line, i.e. the amplification of the corresponding h harmonic from P to K, i-1, …, N, biIs intercept, εiIs the regression residual.
d) And c, respectively carrying out linear relation significance test on the h-th harmonic voltage content of each segment of P and K according to the N segments of data in the step c to obtain corresponding linearity Fi，i＝1，…，N。
Figure BDA0003006648640000051
Figure BDA0003006648640000052
Figure BDA0003006648640000053
wherein ,
Figure BDA0003006648640000054
is the jth value in the ith harmonic data segment of P,
Figure BDA0003006648640000055
is the jth value in the ith harmonic data segment of K.
e) Selection with FiIncrease of lambda with consistent aggregation effectiλ of theseiAverage value of (2)
Figure BDA0003006648640000056
Is the true harmonic amplification of the h harmonic from P to K. And if the amplification factor is more than 1, judging that the parallel harmonic resonant frequency of h times exists in the railway traction power supply system.
In step e, a first step is selected following FiIs increased by oneLambda leading to an aggregation effectiThe invention provides a specific method for obtaining the real harmonic amplification factor. The following were used:
calculating an integer M rounded down by M%. about.N (M usually takes 10), and dividing N FiSorting from big to small, taking the first M FiThe variance Var1 is calculated, and then the variance Var1 is calculated together with N FiVariance of (Var 2)
Figure BDA0003006648640000057
Namely, it is
Figure BDA0003006648640000058
If it is
Figure BDA0003006648640000059
If the value is less than the threshold value delta (delta can be M%), M lambda are determinediMagnification estimate from P to K with FiHas a consistent aggregating effect. If it is
Figure BDA00030066486400000510
If the value is larger than or equal to the threshold delta, then m-1, m-2, m-3, m-4 and m-5 are taken in sequence for repeated calculation until the value meets the requirement
Figure BDA0003006648640000061
Less than a threshold value delta. If m-5 is not satisfied
Figure BDA0003006648640000062
If the value is smaller than the threshold value delta, the selected data cannot be used for accurately identifying the parallel harmonic resonance frequency of the traction power supply system-regional power grid, and the data needs to be selected again.

Claims (3)

1. A method for identifying the parallel harmonic resonance frequency of a traction power supply system-regional power grid is characterized by comprising the following steps,
step 1: selecting a time period in which only one locomotive runs, and acquiring voltage waveforms K of any one of A phase, B phase and C phase of any one bus of a traction transformer high-voltage side area power grid with an effective sampling rate larger than r x H x 50Hz, and voltage waveforms P of a locomotive grid side high-voltage circuit; wherein H is the highest harmonic number to be analyzed, and r is a multiple of the highest harmonic number;
step 2: and respectively carrying out fast Fourier transform on the voltage waveform K and the voltage waveform P to obtain: the square root mean time series of the fundamental voltage and the harmonic voltage of K, and the square root mean time series of the fundamental voltage and the harmonic voltage of P; further obtaining: time series of voltage content of each subharmonic of K
Figure FDA0003006648630000011
P subharmonic voltage content time series
Figure FDA0003006648630000012
Wherein H is the harmonic frequency, H is 2.
And step 3: for any h-th harmonic wave, a sliding time window with the window width of L and the sliding step length of L/2 is adopted, and
Figure FDA0003006648630000013
and
Figure FDA0003006648630000014
respectively dividing the voltage into N sub-time periods to obtain N corresponding harmonic voltage content sections; obtaining the relation Y between the h-order harmonic voltage content of K and P in the harmonic voltage content section by fitting a binary linear regression equationi＝λiXi+bi+εi(ii) a Wherein i is the serial number of the harmonic voltage content section, i is 1, …, N, YiIs a harmonic of K, XiIs a harmonic of P, λiIs the slope of the regression line, i.e. the harmonic amplification of the h harmonic from P to K, biIs intercept, εiIs regression residual error;
and 4, step 4: performing linear relation significance test on the h-order harmonic voltage content of K and P in the harmonic voltage content section i to obtain linearity Fi：
Figure FDA0003006648630000015
Figure FDA0003006648630000016
Figure FDA0003006648630000017
wherein ,
Figure FDA0003006648630000018
is the jth value, Y, in the ith harmonic voltage content section of Pi jIs the jth value in the ith harmonic voltage content section of K;
and 5: selection with FiIncrease of lambda with consistent aggregation effectiLet these λ beiAverage value of (2)
Figure FDA0003006648630000021
Harmonic amplification from P to K as h harmonic; and if the amplification factor is more than 1, judging that the parallel harmonic resonant frequency of h times exists in the railway traction power supply system.
2. A traction power supply system-regional power grid parallel harmonic resonance frequency identification method as claimed in claim 1, characterized in that in step 5, the selection is followed by FiIncrease of lambda with consistent aggregation effectiThe method comprises the following steps:
5.1 mixing N FiSorting from big to small; let m be λ to be selectediThe number of (c) to the percentage of N;
5.2 calculate M% N, get M by rounding down;
5.3 calculate the first M FiVariance Var1 of and N FiVariance of (Var 2)
Figure FDA0003006648630000022
Namely, it is
Figure FDA0003006648630000023
5.4 if
Figure FDA0003006648630000024
Less than a threshold value delta, the selected lambda is determinediWith FiHas a consistent aggregation effect; otherwise, returning m to m-1 to step 5.2 for recalculation until m-1 is satisfied
Figure FDA0003006648630000025
Less than a threshold value delta.
3. A traction power supply system-regional power grid parallel harmonic resonance frequency identification method as claimed in claim 2, wherein in said 5.1, further comprising setting the threshold Δ m%.
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CN116106672A (en) * 2023-04-13 2023-05-12 西南交通大学 Vehicle network resonance detection method and device based on data driving and engineering knowledge
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CN114113783A (en) * 2021-12-03 2022-03-01 通号（长沙）轨道交通控制技术有限公司 Harmonic amplification factor estimation method for electric locomotive
CN116106672A (en) * 2023-04-13 2023-05-12 西南交通大学 Vehicle network resonance detection method and device based on data driving and engineering knowledge
CN116106672B (en) * 2023-04-13 2023-08-18 西南交通大学 Vehicle network resonance detection method and device based on data driving and engineering knowledge
CN116865269A (en) * 2023-09-01 2023-10-10 山东泰开电力电子有限公司 Wind turbine generator system high harmonic compensation method and system
CN116865269B (en) * 2023-09-01 2023-11-21 山东泰开电力电子有限公司 Wind turbine generator system high harmonic compensation method and system

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