CN110672914A - Method and device for detecting traction net pressure - Google Patents

Abstract

The invention discloses a method for detecting traction network voltage. The method comprises: collecting primary-side voltage data and secondary-side current data of a vehicle-mounted transformer; processing the primary-side voltage data and the secondary-side current data to obtain voltage RMS data and power factor data of the on-board transformer; based on the voltage RMS data and power factor data, obtain a first oscillation frequency of the voltage RMS data and a second oscillation frequency of the power factor data; When both the first oscillation frequency and the second oscillation frequency are within a preset frequency range, it is determined that the traction net is in a low frequency oscillation state. The invention also discloses a detection device for traction net pressure at the same time.

Description

A kind of detection method and device of traction net pressure

technical field

The invention relates to a detection technology for traction network pressure, in particular to a detection method and device for traction network pressure.

Background technique

With the operation of new high-power high-speed trains, some complex system compatibility issues begin to emerge when the high-speed train and the traction power supply system interact dynamically. Among them, the phenomenon of low frequency oscillation is one of the important issues in the stable operation of the traction power supply system. When multiple trains are running at the same time with light loads, the voltage and current of the substation fluctuate greatly, and the phases are sometimes in the same phase, sometimes staggered, and sometimes completely reversed.

However, at present, it is impossible to effectively identify the low-frequency oscillation of the traction network voltage when the traction power supply system is running, and the following protection measures can only be adopted after the low-frequency fluctuation of the traction network voltage:

1) Improve the power supply environment and reduce the impedance of the traction network, such as increasing the capacity of the traction substation transformer; but this method often requires large investment, long construction period and poor flexibility;

2) Modify the control parameters of the grid-side rectifier of the electric locomotive. However, this method can only solve the problem temporarily, and it will still cause low-frequency oscillations in the future.

Therefore, it is necessary to study a method to effectively detect the low-frequency oscillation of the traction network voltage under the normal operation of the traction power supply system.

SUMMARY OF THE INVENTION

In view of this, the embodiments of the present invention are expected to provide a method and device for detecting the traction network pressure, which can effectively detect the low-frequency oscillation phenomenon of the traction network pressure under the condition of the normal operation of the traction power supply system, so as to detect the low frequency oscillation phenomenon of the traction network pressure effectively. When low-frequency oscillation occurs, the low-frequency oscillation should be suppressed in time to ensure the normal and stable operation of the traction power supply system.

The technical solution of the embodiment of the present invention is realized as follows:

According to an aspect of the embodiments of the present invention, a method for detecting traction network voltage is provided, which is applied to an electric locomotive, and the method includes:

Collect the primary side voltage data and secondary side current data of the on-board transformer;

processing the primary side voltage data and the secondary side current data to obtain the voltage RMS data and power factor data of the on-board transformer;

Based on the voltage RMS data and the power factor data, obtain a first oscillation frequency of the voltage RMS data and a second oscillation frequency of the power factor data;

When both the first oscillation frequency and the second oscillation frequency are within a preset frequency range, it is determined that the traction net is in a low frequency oscillation state.

In the above solution, after determining that the traction net is in a low-frequency oscillation state, the method further includes:

obtaining the duration that the traction net is in a low-frequency oscillation state;

Based on the duration of the low frequency oscillation of the traction grid, the current loop proportional coefficient of the grid-side converter is increased.

In the above solution, when the first oscillation frequency and/or the second oscillation frequency is outside the preset frequency range, it is determined that the traction net is not in a low frequency oscillation state.

In the above solution, after it is determined that the traction net is not in a low-frequency oscillation state, the method further includes:

Adjust the current loop proportional coefficient of the grid-side converter to the initial value.

In the above solution, the processing of the primary-side voltage data and the secondary-side current data to obtain the voltage RMS data and power factor data of the on-board transformer includes:

performing root mean square calculation on the primary side voltage data to obtain voltage RMS data of the primary side voltage data;

Use the local clock to obtain the sine reference signal and the cosine reference signal; calculate the sine reference signal, the cosine reference signal, the primary voltage data and the secondary current data to obtain the power factor data of the on-board transformer .

In the above solution, the obtaining of the first oscillation frequency of the voltage RMS data and the second oscillation frequency of the power factor data based on the voltage RMS data and the power factor data includes;

Construct a first Hankel matrix based on the voltage RMS data; perform singular value decomposition on the first Hankel matrix to obtain an orthogonal matrix of the first order in the first Hankel matrix, wherein, The orthogonal matrix corresponds to the subspace of the voltage RMS data; singular value decomposition is performed on the orthogonal matrix to obtain an invertible matrix; the invertible matrix is calculated by the overall least squares method to obtain the invertible matrix The eigenvalue of ; calculate the eigenvalue of the reversible matrix to obtain the first oscillation frequency of the RMS voltage;

Construct a second Hankel matrix based on the power factor data; perform singular value decomposition on the second Hankel matrix to obtain an orthogonal matrix of the first order in the second Hankel matrix, wherein the The orthogonal matrix corresponds to the subspace of the power factor; the singular value decomposition of the orthogonal matrix is performed to obtain an invertible matrix; the eigenvalue of the invertible matrix is obtained by calculating the invertible matrix by the overall least squares method ; Calculate the eigenvalues of the invertible matrix to obtain the second oscillation frequency of the power factor.

In the above solution, before the processing of the primary-side voltage data and the secondary-side current data, the method further includes:

Low-pass filtering with a cut-off frequency of 100 Hz is performed on the primary-side voltage data and secondary-side current data, respectively, to obtain low-frequency data of the primary-side voltage data and low-frequency data of the secondary-side current data.

The processing of the primary side voltage data and the secondary side current data includes:

The low-frequency data of the primary-side voltage data and the low-frequency data of the secondary-side current data are processed.

According to a second aspect of the embodiments of the present invention, there is provided a detection device for traction net pressure, the detection device comprising:

The voltage transformer is used to collect the primary voltage data of the on-board transformer;

a current transformer for collecting secondary current data of the on-board transformer;

a processor, configured to process the primary side voltage data and the secondary side current data to obtain voltage RMS data and power factor data of the on-board transformer; based on the voltage RMS data and power factor data, obtain The first oscillation frequency of the voltage RMS data and the second oscillation frequency of the power factor data; when both the first oscillation frequency and the second oscillation frequency are within the preset frequency range, determine the The traction net is in a low-frequency oscillation state.

In the above solution, the processor is further configured to: obtain the duration that the traction network is in a low-frequency oscillation state; and increase the current loop proportional coefficient of the grid-side converter based on the duration of the traction network being in a low-frequency oscillation state.

In the above solution, the processor is further configured to: when the first oscillation frequency and/or the second oscillation frequency are not within a preset frequency range, determine that the traction net is not in a low-frequency oscillation state .

In the above solution, the processor is further configured to adjust the current loop proportional coefficient of the grid-side converter to an initial value when the traction grid is not in a low-frequency oscillation state.

According to a third aspect of the embodiments of the present invention, there is provided a detection device for traction net pressure, the detection device comprising:

The acquisition unit is used to collect the primary voltage data and secondary current data of the on-board transformer;

a processing unit, configured to process the primary-side voltage data and the secondary-side current data to obtain voltage RMS data and power factor data of the on-board transformer, and based on the voltage RMS data and power factor data, obtaining the first oscillation frequency of the voltage RMS data and the second oscillation frequency of the power factor data;

A determination unit, configured to determine that the traction net is in a low-frequency oscillation state when both the first oscillation frequency and the second oscillation frequency are within a preset frequency range.

The method and device for detecting the traction grid voltage provided by the embodiments of the present invention collect primary voltage data and secondary current data of a vehicle-mounted transformer; and process the primary voltage data and the secondary current data to obtain The voltage RMS data and power factor data of the vehicle transformer, and based on the voltage RMS data and the power factor data, the first oscillation frequency of the voltage RMS data and the second oscillation frequency of the power factor data are obtained ; When the first oscillation frequency and the second oscillation frequency are both within the preset frequency range, it is determined that the traction net is in a low frequency oscillation state. In this way, the RMS voltage and power factor are given by fully considering the characteristics of the large voltage fluctuation and the constant change of the voltage and current phase when the low frequency oscillation occurs in the traction power supply system. Under the normal operation of the traction power supply system, the low-frequency oscillation phenomenon of the traction network pressure can be effectively detected, so as to improve the accuracy of the low-frequency oscillation phenomenon of the traction network pressure, so that when the low-frequency oscillation phenomenon of the traction network voltage occurs, the system can be carried out in time. Low-frequency oscillation suppression to ensure the safe and stable operation of the traction power supply system.

Description of drawings

Fig. 1 is the realization flow schematic diagram of the detection method of traction network pressure in the application;

Fig. 2 is the realization flow schematic diagram of the detection and suppression method of traction network pressure in the application;

Fig. 3 is the waveform schematic diagram of the traction grid voltage when the conventional current dq decoupling control is adopted in the prior art;

Fig. 4 is the waveform schematic diagram of the traction grid pressure when adopting the traction grid pressure detection and suppression method in the present application;

5 is a schematic diagram of the adaptive adjustment process of the current loop proportional coefficient of the grid-side converter in the application;

6 is a schematic diagram 1 of the structure and composition of the traction network pressure detection device in the application;

FIG. 7 is a second schematic diagram of the structure and composition of the traction network pressure detection device in the application.

Detailed ways

The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present invention, but not to limit the present invention.

Fig. 1 is the realization flow schematic diagram of the detection method of traction network pressure in the application, as shown in Fig. 1, the method comprises:

Step 101, collecting primary side voltage data and secondary side current data of the on-board transformer;

In this application, the detection method of the traction network voltage is mainly applied to electric locomotives. The electric locomotive includes an on-board transformer and an on-board converter. Because the low-frequency fluctuation of the traction network voltage generally occurs in the condition that multiple electric locomotives are raised and reconditioned at the same time in the same power supply interval, when the electric locomotive is raised and reconditioned, the electric locomotive can collect the on-board transformer through the voltage transformer. The primary side voltage data of the vehicle is collected, and the secondary side current data of the on-board transformer is collected through the current transformer.

Here, when the voltage transformer and the current transformer collect data, the data collection may be specifically performed according to the sampling period, for example, the collection period may be 50us or 10us, and so on.

In this application, after collecting the primary side voltage data and secondary side current data of the on-board transformer, the electric locomotive can also use a digital signal processor (DSP, Digital Signal Processor) or a Field Programmable Gate Array (FPGA, Filed Programmable Gate Array). ) The processor performs low-pass filtering with a cut-off frequency of 100Hz on the primary side voltage data and secondary side current data respectively to filter out the high frequency components contained in the collected signal and retain the effective low frequency components, so that the primary side voltage data can be obtained. the low frequency data of the secondary side current data and the low frequency data of the secondary side current data.

Step 102, processing the primary side voltage data and the secondary side current data to obtain the voltage RMS data and power factor data of the vehicle-mounted transformer;

In this application, after obtaining the low-frequency data of the primary-side voltage data and the low-frequency data of the secondary-side current data, the electric locomotive may process the low-frequency data of the primary-side voltage data and the low-frequency data of the secondary-side current data to obtain the The voltage RMS data and power factor data of the on-board transformer are described.

In the present application, when the electric locomotive processes the low-frequency data of the primary voltage data, specifically, a sliding window method with a period of 0.02s may be used to perform the root mean square calculation of the low-frequency data of the primary voltage data window by window to obtain The voltage RMS value of the primary voltage data.

Here, the voltage effective value of the primary voltage data is also referred to as the root mean square value of the primary voltage data.

Specifically, the mathematical expression for obtaining the root mean square value of the primary voltage data can be:

Among them, U _i is the i-th primary voltage data collected, and N is the number of primary voltage data collected within the sliding window time (0.02s).

In this application, when the electric locomotive processes the primary side voltage data and the secondary side current data, a local clock on the processor can also be used to obtain a sine reference signal and a cosine reference signal; The reference signal, the primary side voltage data and the secondary side current data are calculated to obtain the phase of the primary side voltage and the phase of the secondary side current.

Specifically, the phase of the primary voltage is calculated as:

Among them, sin(2πft) represents the sine reference signal, cos(2πft) represents the cosine reference signal; N is the number of primary side voltage data collected within the sliding window time (0.02s), and U _i is the ith primary side collected voltage data.

Calculate the phase of the secondary current as:

Among them, sin(2πft) represents the sine reference signal, cos(2πft) represents the cosine reference signal; N is the number of primary voltage data collected within the sliding window time (0.02s). I _i is the ith secondary current data collected.

Calculate the power factor of the on-board transformer as:

PF=cos(φU-φI);

Among them, φU is the phase of the voltage, and φI is the phase of the voltage. In an AC circuit, the cosine of the phase difference (Φ) between the voltage and the current is called the power factor, which is represented by the symbol cosΦ.

Step 103, based on the voltage RMS data and power factor data, obtain a first oscillation frequency of the voltage RMS data and a second oscillation frequency of the power factor data;

In this application, after obtaining the RMS voltage data and the power factor data of the on-board transformer, the electric locomotive can also use the signal parameter estimation algorithm of the total least squares method-rotation invariance technology to obtain the RMS voltage data and the power factor data, respectively. Identifying is performed to obtain a first oscillation frequency corresponding to the voltage RMS data and a second oscillation frequency corresponding to the power factor data.

Specifically, when the electric locomotive identifies the voltage RMS data and obtains the first oscillation frequency corresponding to the voltage RMS data, it may first construct a first Hankel matrix based on the voltage RMS data; Perform singular value decomposition on a Hankel matrix to obtain an orthogonal matrix of the first order in the first Hankel matrix, wherein the orthogonal matrix corresponds to the subspace of the voltage RMS data; Singular value decomposition to obtain an invertible matrix; then calculate the invertible matrix through the overall least squares method to obtain the eigenvalues of the invertible matrix; finally, calculate the eigenvalues of the invertible matrix to obtain the first oscillation frequency of the voltage RMS data .

The specific process of calculating the first oscillation frequency corresponding to the voltage RMS data is as follows:

(1) Record the data sequence as X=[x(0),x(1),...,x(n-1)];

Among them, X is the voltage RMS data, and n is the number of the obtained voltage RMS data;

(2) Construct an r×m-order Hankel matrix H based on the voltage RMS data:

Wherein, both r and m are orders, and r+m-1=n is satisfied. Here, the r and m orders may be determined according to the set fitting model order P, and r>p, m>p.

(3) Perform singular value decomposition on the Hankel matrix H:

U_n表示r×r阶矩阵，∑_s和∑_n表示Σ的对角元素。Among them, U is an r-order orthogonal matrix; Σ is an r×m-order diagonal matrix, and the diagonal elements of Σ are obtained by descending the singular values of the matrix H from large to small; V is an m-order orthogonal matrix, and V ^T is V The conjugate transpose of . U _s

U _n represents a matrix of order r×r, and ∑ _s and ∑ _n represent the diagonal elements of ∑.

Here, the singular values of the matrix H are denoted as the singular values of the matrix X ξ1, ξ2,...,ξp,ξp+1,...,ξmax(r,m). When the signal is only composed of p complex sinusoidal signal components, the rank of the Hankel matrix is p, at this time ξ1>ξ2>...>ξp>ξp+1=...=ξmax(r,m)=0, but when the signal When polluted by noise, the constructed Hankel matrix is full rank, and all singular values are no longer equal to zero.

In order to estimate the signal parameters from the noise-contaminated sampled data, V can be divided into two parts, namely V=[Vs, Vn], where Vs and Vn correspond to the signal subspace and noise subspace of the voltage RMS data, respectively. The column vector is the eigenvector corresponding to the p singular values with the largest magnitude of the matrix H, where s is the signal and n is the noise.

(4) Perform singular value decomposition on the orthogonal matrix V _s in the matrix H:

Among them, V ₁ represents the new matrix obtained by deleting the first row of the matrix V _s . V ₂ represents the new matrix obtained by deleting the last 1 row of the matrix V _s .

By performing singular value decomposition on the orthogonal matrix V _s , it can be known that there is an invertible matrix P such that:

V ₂ =V ₁ P

In this way, an invertible matrix P satisfying the relationship of V ₂ =V ₁ P can be obtained, and its eigenvalues can be used to calculate the frequency of the data signal.

Specifically, suppose that the oscillation signal x(n) can be expressed as a combination of a series of sinusoidal signals and white noise whose amplitude varies exponentially. At the sampling time n, its expression is as follows:

In the formula: T _s is the sampling period; since the sampling signal is usually a real signal, the model order P is usually twice the number of real sinusoidal components actually contained in the signal; a _p , φ _p , ω _p , σ _p are the first The amplitude, initial phase, angular frequency and attenuation coefficient of the p attenuation components; f _p is the frequency of the p-th attenuation component, f _p =ω _p /(2π); w is the white noise with mean 0.

则信号可简写为：make

Then the signal can be abbreviated as:

In the formula: z _p is called the signal pole.

Define the vector x(n)=[x(n),x(n+1),...,x(n+M-1)] ^T , where M>P, then

where:

c=[c ₁ c ₂ ... c _P ] ^T

Φ=diag(z ₁ z ₂ … z _P )

Γ _M = [τ _M (z ₁ ) τ _M (z ₂ ) … τ _M (z _P )]

w(n)=[w(n) w(n+1) ... w(n+M-1)] ^T

It can be found that: z _p (p=1,2,...,P) determines the frequency and damping coefficient of each component in the signal, and completely determines Φ, so we can try to indirectly obtain the signal pole through Φ, and then obtain each signal component. parameters such as frequency and damping coefficient.

For the convenience of expression, the symbols ↑ and ↓ are specified to represent the new matrix obtained by deleting the first row and the last row of the matrix, respectively. For example: S ^↓ represents a new matrix obtained by deleting the last row of matrix S, and S ^↑ means a new matrix obtained by deleting the first row of matrix S.

S ^↓ =Γ _M-1 Φ ⁿ c = J ₁ c

S ^↑ = Γ _M-1 Φ ⁿ⁺¹ c = J ₂ c

J ₂ =J ₁ Φ

Here, Φ is equivalent to the reversible matrix P in the above formula.

(5) Calculate the reversible matrix P by the total least squares method (TLS) to obtain the eigenvalue λ _i of the reversible matrix P, where the eigenvalue λ _i is used to estimate the oscillation frequency of the voltage effective value;

Specifically, let K=[V1, V2], and perform singular value (SVD) decomposition on K:

K=U ₃ ΣV ₃ ^T ;

Among them, U is an r-order orthogonal matrix; Σ is an r×m-order diagonal matrix, and the diagonal elements of Σ are obtained by decreasing the singular values of the matrix K from large to small; V is an m-order orthogonal matrix, V ^T is the conjugate transpose of V. The diagonal element Σ _i of Σ is the singular value of K.

Then, according to the set fitting model order p, the matrix V ₃ in the matrix K is divided into 4 sub-matrices of p × p:

Among them, V ₁₁ , V ₁₂ , V ₂ , and V ₂₂ respectively represent the positions of the corresponding four sub-matrices. For example, V ₁₁ represents 1 row and 1 column, V ₁₂ represents 1 row and 2 columns, V ₂₁ represents 2 rows and 1 column, and V ₂₁ means 2 rows and 2 columns.

The submatrix of matrix V ₃ is calculated by the overall least squares method, and the overall least squares solution of the invertible matrix P is obtained:

Then, find the eigenvalue λ _i (i=1,2,...,p) of the overall least squares solution P _tls of the invertible matrix P, and obtain the oscillation frequency of the sinusoidal component contained in the signal:

Among them, T _s is the sampling time of the voltage RMS, and λ _i is the characteristic value of P _tls .

Here, f _i is the first oscillation frequency of the RMS voltage, denoted as f _U .

In the present application, when the power factor data is identified and the second oscillation frequency of the power factor data is obtained, the power factor data can be obtained first, and then a second Hankel matrix can be constructed based on the obtained power factor data; Perform singular value decomposition on the second Hankel matrix to obtain an orthogonal matrix of the first order in the second Hankel matrix, where the orthogonal matrix corresponds to the subspace of the power factor data; Perform singular value decomposition to obtain an invertible matrix; then calculate the invertible matrix by the overall least squares method to obtain the eigenvalues of the invertible matrix; finally, calculate the eigenvalues of the invertible matrix to obtain the second oscillation frequency of the power factor data .

The specific process of calculating the second oscillation frequency of the power factor data is as follows:

(1) Record the data sequence as X=[x(0),x(1),...,x(n-1)];

Wherein, X is the power factor data, and n is the number of the obtained power factor data;

(2) Construct an r×m-order Hankel matrix H based on the power factor data:

Wherein, both r and m are orders, and r+m-1=n is satisfied. Here, the r and m orders are determined according to the set fitting model order P, and r>p, m>p.

(3) The singular value decomposition of the Hankel matrix H is:

U_n表示r×r阶矩阵，∑_s和∑_n表示Σ的对角元素。Among them, U is an r-order orthogonal matrix; Σ is an r×m-order diagonal matrix, and the diagonal elements of Σ are obtained by decreasing the singular values of the matrix H from large to small; V is an m-order orthogonal matrix, V ^T is the conjugate transpose of V. U _s

U _n represents a matrix of order r×r, and ∑ _s and ∑ _n represent the diagonal elements of ∑.

The singular values of the matrix H are denoted as the singular values of the matrix X ξ1, ξ2,...,ξp,ξp+1,...,ξmax(r,m). When the signal is only composed of p complex sinusoidal signal components, the rank of the Hankel matrix is p, at this time ξ1>ξ2>...>ξp>ξp+1=...=ξmax(r,m)=0, but when the signal When polluted by noise, the constructed Hankel matrix is full rank, and all singular values are no longer equal to zero.

In order to estimate the signal parameters from the noise-contaminated sampled data, V can be divided into two parts, namely V=[Vs, Vn], where Vs and Vn correspond to the signal subspace and noise subspace of the power factor data, respectively, and the column of Vs The vector is the eigenvector corresponding to the p singular values with the largest magnitude of the matrix H, where s is the signal and n is the noise.

(4) Perform singular value decomposition on the orthogonal matrix V _s :

Among them, V ₁ represents the new matrix obtained by deleting the first row of the matrix V _s . V ₂ represents the new matrix obtained by deleting the last 1 row of the matrix V _s .

By performing singular value decomposition of V _s , the invertible matrix P is determined such that:

V ₂ =V ₁ P

In this way, the eigenvalues of the matrix P satisfying the relationship V ₂ =V ₁ P can be used to calculate the frequency of the data signal.

(5) Calculate the reversible matrix P by the total least squares method (TLS) to obtain the eigenvalue λ _i of the reversible matrix P, and the eigenvalue λ _i is used for the subsequent estimation of the oscillation frequency of the power factor data;

Specifically, let K=[V1, V2], and perform singular value (SVD) decomposition on matrix K:

K=U ₃ ΣV ₃ ^T ;

Among them, U is an r-order orthogonal matrix; Σ is an r×m-order diagonal matrix, and the diagonal elements of Σ are obtained by decreasing the singular values of the matrix K from large to small; V is an m-order orthogonal matrix, V ^T is the conjugate transpose of V. The diagonal element Σ _i of Σ is the singular value of K.

Then, according to the set fitting model order p, the matrix V ₃ in the matrix K is divided into 4 sub-matrices of p × p:

Among them, V ₁₁ , V ₁₂ , V ₂ , and V ₂₂ respectively represent the positions of the corresponding four sub-matrices. For example, V ₁₁ represents 1 row and 1 column, V ₁₂ represents 1 row and 2 columns, V ₂₁ represents 2 rows and 1 column, and V ₂₁ means 2 rows and 2 columns.

The overall least squares solution of the invertible matrix P is obtained from the submatrices _of the matrix V:

_Find the eigenvalue λ _i (i=1, 2, .

Among them, T _s is the sampling time of the power factor, and λ _i is the characteristic value of P _tls .

Here, f _i is the second oscillation frequency of the power factor, denoted as f _PF .

Step 104, when both the first oscillation frequency and the second oscillation frequency are within a preset frequency range, determine that the traction net is in a low-frequency oscillation state.

In this application, after obtaining the first oscillation frequency f _U of the RMS voltage and the second oscillation frequency f _PF of the power factor, the electric locomotive can determine the first oscillation frequency f _U of the RMS voltage and the second oscillation frequency of the power factor. Whether the frequency f _PF is within the range of the interval [0.1, 20] Hz, the judgment result is obtained, if the judgment result indicates that the first oscillation frequency f _U and the second oscillation frequency f _PF are both within the range of the interval [0.1, 20] Hz , it means that the current traction network has low-frequency network pressure fluctuations, and the traction network pressure is currently in a low-frequency oscillation state. On the contrary, if the judgment result indicates that the first oscillation frequency f _U and/or the second oscillation frequency f _PF is outside the range of the interval [0.1, 20] Hz, it means that there is no low-frequency network pressure fluctuation phenomenon in the traction network, which means that the current traction network Not in a low frequency oscillation state.

In this way, through the traction grid voltage detection method provided by the present application, the characteristics of the primary side voltage and the secondary side current phase of the on-board transformer are constantly changing, the low frequency oscillation phenomenon in the traction power supply system is detected in real time, and the occurrence of traction grid voltage can be detected in time. The low-frequency oscillation phenomenon can be identified, so that the low-frequency oscillation phenomenon of the traction network pressure can be suppressed more effectively.

In this application, in the case of low-frequency oscillation in the traction network voltage, the electric locomotive can also obtain the duration of the low-frequency oscillation in the traction network; based on the duration of the low-frequency oscillation, increase the current loop proportional coefficient of the grid-side converter , namely: K _pi =α ^Δt K _pi0 .

Among them, the coefficient α takes a value greater than 1, preferably 1.1, Δt is the detected low-frequency oscillation duration, and K _pi0 is the initial value of the current loop proportional coefficient of the grid-side converter.

The present application may continue to perform steps 101 to 104 after correcting the current loop proportional coefficient of the grid-side converter until the low-frequency oscillation phenomenon is eliminated.

In the present application, the electric locomotive may also adjust the current loop proportional coefficient of the grid-side converter to an initial value, ie K _pi =K _pi0 , when it is determined that the traction grid is not in a low-frequency oscillation state.

In this way, through the online adaptive correction of the grid-side rectifier controller parameters of the electric locomotive, it is only necessary to properly correct the existing algorithm without additional investment, so that the effect of suppressing low-frequency oscillation can be achieved without affecting the normal operation of the traction power supply system. .

Fig. 2 is the realization flow schematic diagram of the detection and suppression method of traction network pressure in the application, as shown in Fig. 2:

Step 201 , collect the data of the primary side voltage and the secondary side current of the on-board transformer, and perform low-pass filtering processing with a cutoff frequency of 100 Hz on the collected data to filter out the high-frequency part and retain the low-frequency part.

Step 202, using the sliding window method to calculate the RMS voltage, and calculate the power factor of the on-board transformer.

Here, the method of the sliding window with a period of 0.02s is used to obtain the root mean square value (RMS) of the voltage data window by window to obtain the voltage RMS data U _rms ; then, the sine reference signal and the cosine reference signal generated by the local clock are used. Signal, primary side voltage data, secondary side current data to calculate the power factor PF of the on-board transformer.

Step 203 , use the signal parameter estimation algorithm based on the total least squares method-rotation invariant technology to identify the effective value of the traction network voltage U _rms and the power factor PF to obtain the oscillation frequencies f _U and f _PF .

Specifically, when the low-frequency oscillation occurs, the grid voltage amplitude and grid current phase fluctuate, and the effective value of the traction grid voltage U _rms and the power factor PF are identified by using the signal parameter estimation algorithm based on the overall least squares method-rotation invariant technology. Obtain the oscillation frequency f _U corresponding to the voltage effective value U _rms and the oscillation frequency f PF corresponding to the power factor _PF .

Step 204, determine whether the oscillation frequency f _U of the RMS voltage and the oscillation frequency f _PF of the power factor are within the interval [0.1, 20] Hz, if both are within the range of [0.1, 20] Hz, it is judged as a low frequency oscillation phenomenon, and step 205 is executed, if at least one is not , it is judged as normal, and step 206 is executed.

Specifically, the low-frequency oscillation frequency of the domestic traction power supply system is within 20 Hz. Therefore, it is determined whether the voltage RMS oscillation frequency f _U and the power factor oscillation frequency f _PF are within the interval [0.1, 20] Hz. If both are satisfied, the traction power supply system is determined. If low frequency oscillation occurs, go to step 205, if not, it is judged as normal, set the current loop proportional coefficient of the EMU grid-side converter to the initial value K _pi0 , and return to step 201 to continue the detection.

Step 205 , low frequency oscillation occurs in the traction power supply system, and the proportional coefficient of the current loop of the grid-side converter is adjusted to be: K _pi =α ^Δt K _pi0 .

Among them, the coefficient α takes a value greater than 1, preferably 1.1, Δt is the detected low-frequency oscillation duration, and K _pi0 is the initial value of the current loop proportional coefficient of the grid-side converter.

Specifically, according to the analysis and research conclusions of the low-frequency oscillation stability of the existing vehicle-to-grid coupling system, it can be seen that when the EMU grid-side rectifier adopts the current loop dq decoupling control, the current loop proportional coefficient can be appropriately increased, which can effectively suppress the low-frequency oscillation. effect. Therefore, when it is judged to be a low-frequency oscillation state, the proportional coefficient of the current loop of the EMU grid-side converter is adaptively corrected online every fixed time as: K _pi =α ^Δt K _pi0 . After correcting the coefficient, return to step 201, and continue to detect until the low frequency oscillation is eliminated.

Step 206 , the traction power supply system does not have low frequency oscillation, and the proportional coefficient of the current loop of the grid-side converter is adjusted to be: K _pi =K _pi0 .

After the correction, return to step 201 to continue detection.

Fig. 3 is the waveform schematic diagram of the traction grid voltage when the conventional current dq decoupling control is adopted in the prior art; as shown in Fig. 3:

If the traction power supply system has a total of 5 trains running lightly at the same time, when the traditional current dq decoupling control is adopted for the rectifier on the EMU grid side, the collected primary voltage and secondary current of the on-board transformer will fluctuate greatly, resulting in continuous low frequency oscillation. Phenomenon.

Fig. 4 is the waveform schematic diagram of traction grid pressure when adopting traction grid pressure detection and suppression method in the present application; as shown in Fig. 4:

If the traction power supply system has a total of 5 trains running lightly at the same time, when the EMU grid-side rectifier adopts the traction grid voltage detection and suppression method proposed in this application, the collected on-board transformer primary side voltage and secondary side current The oscillation phenomenon is significantly suppressed. .

FIG. 5 is a schematic diagram of the adaptive adjustment process of the current loop proportional coefficient of the grid-side converter in the application, as shown in FIG. 5 :

The dotted line indicates the _Kpi parameter value; the rectangular line indicates whether LFO is detected, 0 indicates not detected, and 1 indicates detected. When low-frequency oscillation is not detected, the K _pi parameter is a fixed initial value K _pi0 . When low-frequency oscillation is detected, the K _pi parameter is adaptively adjusted to α ^Δt K _pi0 to increase the current loop proportional coefficient of the EMU grid-side converter.

FIG. 6 is a schematic diagram 1 of the structure of the traction network pressure detection device in the application; as shown in FIG. 6 , the traction network pressure detection device 600 may be an electric locomotive or an EMU. The traction grid voltage detection device 600 shown in FIG. 6 includes: a voltage transformer 601, a current transformer 602, an on-board transformer 603, at least one processor 604 and a grid-side transformer 605, a voltage transformer 601, a current transformer 602, The on-board transformer 603 , the at least one processor 604 and the grid-side converter 605 may be coupled together through a bus system 606 . It will be appreciated that the bus system 606 is used to implement the connection communication between these components. In addition to the data bus, the bus system 606 also includes a power bus, a control bus, and a status signal bus. For clarity, however, the various buses are labeled as bus system 606 in FIG. 6 .

The methods disclosed in the above embodiments of the present invention may be applied to the processor 604 or implemented by the processor 604 . The processor 604 may be an integrated circuit chip with signal processing capability. In the implementation process, each step of the above-mentioned method may be completed by an integrated logic circuit of hardware in the processor 604 or an instruction in the form of software. The above-mentioned processor 604 may be a general-purpose processor, a digital signal processor (DSP, Digital Signal Processor), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like. The processor 604 may implement or execute the methods, steps, and logical block diagrams disclosed in the embodiments of the present invention. A general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed in combination with the embodiments of the present invention can be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor.

In an exemplary embodiment, the traction grid voltage detection device 600 may be implemented by one or more Application Specific Integrated Circuit (ASIC, Application Specific Integrated Circuit), DSP, Programmable Logic Device (PLD, Programmable Logic Device), complex programmable logic Device (CPLD, Complex Programmable LogicDevice), Field Programmable Gate Array (FPGA, Field-Programmable Gate Array), General Purpose Processor, Controller, Microcontroller (MCU, Micro Controller Unit), Microprocessor (Microprocessor), or Other electronic components are implemented for performing the aforementioned method.

Specifically, the voltage transformer 601 is used to collect the primary voltage data of the on-board transformer 603;

The current transformer 602 is used to collect secondary current data of the on-board transformer 603;

The processor 604 is configured to process the primary side voltage data and the secondary side current data to obtain the voltage RMS data and power factor data of the on-board transformer; and based on the voltage RMS data and power factor data to obtain the first oscillation frequency of the voltage RMS data and the second oscillation frequency of the power factor data; when both the first oscillation frequency and the second oscillation frequency are within the preset frequency range Next, it is determined that the traction net is in a low-frequency oscillation state.

As a preferred solution of the embodiment of the present application, the processor 604 is further configured to: obtain the duration that the traction network is in the low-frequency oscillation state; and increase the grid-side converter 605 based on the duration that the traction network is in the low-frequency oscillation state The current loop scaling factor.

As a preferred solution of the embodiment of the present application, the processor 604 is further configured to, when the first oscillation frequency and/or the second oscillation frequency are outside the preset frequency range, determine that the traction net is not in the In the low frequency oscillation state, and in the low frequency oscillation state, the current loop proportional coefficient of the grid-side converter 605 is adjusted to the initial value.

As a preferred solution of the embodiment of the present application, the processor 604 is specifically configured to perform root mean square calculation on the primary voltage data to obtain the voltage RMS data of the primary voltage data; obtain the sinusoidal reference signal by using the local clock and cosine reference signal; calculate the sine reference signal, the cosine reference signal, the primary side voltage data and the secondary side current data to obtain the power factor data of the on-board transformer 603 .

As a preferred solution of the embodiment of the present application, the processor 604 is further configured to: construct a first Hankel matrix based on the voltage RMS data; perform singular value decomposition on the first Hankel matrix to obtain the an orthogonal matrix of the first order in the first Hankel matrix, wherein the orthogonal matrix corresponds to the subspace of the voltage RMS data; perform singular value decomposition on the orthogonal matrix to obtain an invertible matrix ; Calculate the invertible matrix by the overall least squares method to obtain the eigenvalues of the invertible matrix; calculate the eigenvalues of the invertible matrix to obtain the first oscillation frequency of the voltage effective value.

As a preferred solution of the embodiment of the present application, the processor 604 is further configured to: construct a second Hankel matrix based on the power factor data; perform singular value decomposition on the second Hankel matrix to obtain the The orthogonal matrix of the first order in the second Hankel matrix, wherein the orthogonal matrix corresponds to the subspace of the power factor data; perform singular value decomposition on the orthogonal matrix to obtain an invertible matrix; The total least squares method calculates the invertible matrix to obtain the eigenvalues of the invertible matrix; and calculates the eigenvalues of the invertible matrix to obtain the second oscillation frequency of the power factor.

As a preferred solution of the embodiment of the present application, the processor 604 is further configured to: perform low-pass filtering with a cut-off frequency of 100 Hz on the primary-side voltage data and secondary-side current data, respectively, to obtain the primary-side voltage data low frequency data and low frequency data of the secondary side current data.

FIG. 7 is a schematic diagram 2 of the structure of the traction network pressure detection device in the application; as shown in FIG. 7 , in an exemplary embodiment, the detection device includes:

The collection unit 701 is used to collect the primary side voltage data and the secondary side current data of the on-board transformer;

A processing unit 702, configured to process the primary side voltage data and the secondary side current data to obtain the voltage RMS data and power factor data of the on-board transformer, and based on the voltage RMS data and power factor data , obtain the first oscillation frequency of the voltage RMS data and the second oscillation frequency of the power factor data;

A determination unit 703, configured to determine that the traction net is in a low-frequency oscillation state when both the first oscillation frequency and the second oscillation frequency are within a preset frequency range.

In a preferred embodiment, the detection device further includes: an acquisition unit 704 and an adjustment unit 705;

The obtaining unit 704 is configured to obtain the duration that the traction net is in a low-frequency oscillation state;

The adjustment unit 705 is configured to increase the current loop proportional coefficient of the grid-side converter based on the duration of the low-frequency oscillation of the traction grid.

In a preferred embodiment, the determining unit 703 is further configured to determine that the traction net is not in low frequency oscillation when the first oscillation frequency and/or the second oscillation frequency is outside the preset frequency range state.

In a preferred embodiment, the adjusting unit 705 is further configured to adjust the current loop proportional coefficient of the grid-side converter to an initial value when it is determined that the traction grid is not in a low-frequency oscillation state.

In a preferred embodiment, the processing unit 702 is specifically configured to perform root mean square calculation on the primary voltage data to obtain voltage RMS data of the primary voltage data;

Use the local clock to obtain the sine reference signal and the cosine reference signal; calculate the sine reference signal, the cosine reference signal, the primary voltage data and the secondary current data to obtain the power factor data of the on-board transformer .

In a preferred embodiment, the processing unit 702 is further configured to construct a first Hankel matrix based on the voltage RMS data; perform singular value decomposition on the first Hankel matrix to obtain the first Hankel matrix an orthogonal matrix of the first order in the Kerr matrix, wherein the orthogonal matrix corresponds to the subspace of the voltage RMS data; perform singular value decomposition on the orthogonal matrix to obtain an invertible matrix; through the overall minimum The square method calculates the invertible matrix to obtain the eigenvalue of the invertible matrix; calculates the eigenvalue of the invertible matrix to obtain the first oscillation frequency of the voltage effective value;

Construct a second Hankel matrix based on the power factor data; perform singular value decomposition on the second Hankel matrix to obtain an orthogonal matrix of the first order in the second Hankel matrix, wherein the The orthogonal matrix corresponds to the subspace of the power factor data; singular value decomposition is performed on the orthogonal matrix to obtain an invertible matrix; the invertible matrix is calculated by the overall least squares method to obtain the characteristics of the invertible matrix value; calculate the eigenvalues of the invertible matrix to obtain the second oscillation frequency of the power factor.

In a preferred embodiment, the processing unit 702 is further configured to perform low-pass filtering with a cut-off frequency of 100 Hz on the primary-side voltage data and the secondary-side current data, respectively, to obtain the low-frequency data of the primary-side voltage data and all The low-frequency data of the secondary side current data. The low-frequency data of the primary-side voltage data and the low-frequency data of the secondary-side current data are processed.

It should be noted that: when the traction network pressure detection device provided above realizes the detection of traction network pressure, only the division of the above program modules is used as an example. The module is completed, that is, the internal structure of the traction network pressure detection device is divided into different program modules, so as to complete all or part of the processing described above. In addition, the traction network pressure detection device provided above and the traction network pressure detection method described above belong to the same concept, and the specific implementation process thereof is detailed in the method embodiment, which will not be repeated here.

The methods disclosed in the several method embodiments provided in this application can be arbitrarily combined under the condition of no conflict to obtain new method embodiments.

The features disclosed in the several product embodiments provided in this application can be combined arbitrarily without conflict to obtain a new product embodiment.

The features disclosed in several method or device embodiments provided in this application can be combined arbitrarily without conflict to obtain new method embodiments or device embodiments.

The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention. should be included within the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims (10)

1. a detection method of traction net pressure, is characterized in that, described method comprises: Collect the primary side voltage data and secondary side current data of the on-board transformer; processing the primary side voltage data and the secondary side current data to obtain the voltage RMS data and power factor data of the on-board transformer; Based on the voltage RMS data and the power factor data, obtain a first oscillation frequency of the voltage RMS data and a second oscillation frequency of the power factor data; When both the first oscillation frequency and the second oscillation frequency are within a preset frequency range, it is determined that the traction net is in a low frequency oscillation state. 2 . The method according to claim 1 , wherein after the determining that the traction net is in a low-frequency oscillation state, the method further comprises: 2 . obtaining the duration that the traction net is in a low-frequency oscillation state; Based on the duration of the low frequency oscillation of the traction grid, the current loop proportional coefficient of the grid-side converter is increased. 3. The method according to claim 1, wherein, when the first oscillation frequency and/or the second oscillation frequency is outside a preset frequency range, it is determined that the traction net is not in low frequency oscillation state. 4. The method according to claim 3, wherein after the determining that the traction net is not in a low frequency oscillation state, the method further comprises: Adjust the current loop proportional coefficient of the grid-side converter to the initial value. 5 . The method according to claim 1 , wherein the processing of the primary side voltage data and the secondary side current data to obtain the voltage RMS data and power factor data of the on-board transformer, comprising: 6 . : performing root mean square calculation on the primary side voltage data to obtain voltage RMS data of the primary side voltage data; Use the local clock to obtain the sine reference signal and the cosine reference signal; calculate the sine reference signal, the cosine reference signal, the primary voltage data and the secondary current data to obtain the power factor data of the on-board transformer . 6 . The method according to claim 1 , wherein the first oscillation frequency of the voltage RMS data and the second oscillation frequency of the power factor data are obtained based on the voltage RMS data and the power factor data. 7 . Oscillation frequency, including; Construct a first Hankel matrix based on the voltage RMS data; perform singular value decomposition on the first Hankel matrix to obtain an orthogonal matrix of the first order in the first Hankel matrix, wherein, The orthogonal matrix corresponds to the subspace of the voltage RMS data; singular value decomposition is performed on the orthogonal matrix to obtain an invertible matrix; the invertible matrix is calculated by the overall least squares method to obtain the invertible matrix The eigenvalue of ; calculate the eigenvalue of the reversible matrix to obtain the first oscillation frequency of the RMS voltage; Construct a second Hankel matrix based on the power factor data; perform singular value decomposition on the second Hankel matrix to obtain an orthogonal matrix of the first order in the second Hankel matrix, wherein the The orthogonal matrix corresponds to the subspace of the power factor data; singular value decomposition is performed on the orthogonal matrix to obtain an invertible matrix; the invertible matrix is calculated by the overall least squares method to obtain the characteristics of the invertible matrix value; calculate the eigenvalues of the invertible matrix to obtain the second oscillation frequency of the power factor. 7 . The method according to claim 1 , wherein before the processing of the primary-side voltage data and the secondary-side current data, the method further comprises: 8 . Low-pass filtering with a cut-off frequency of 100 Hz is performed on the primary-side voltage data and secondary-side current data, respectively, to obtain low-frequency data of the primary-side voltage data and low-frequency data of the secondary-side current data. The processing of the primary side voltage data and the secondary side current data includes: The low-frequency data of the primary-side voltage data and the low-frequency data of the secondary-side current data are processed. 8. A detection device for traction net pressure, wherein the detection device comprises: The voltage transformer is used to collect the primary voltage data of the on-board transformer; a current transformer for collecting secondary current data of the on-board transformer; a processor, configured to process the primary side voltage data and the secondary side current data to obtain voltage RMS data and power factor data of the on-board transformer; based on the voltage RMS data and power factor data, obtain The first oscillation frequency of the voltage RMS data and the second oscillation frequency of the power factor data; when both the first oscillation frequency and the second oscillation frequency are within the preset frequency range, determine the The traction net is in a low frequency oscillation state. 9 . The detection device according to claim 8 , wherein the processor is further configured to: obtain the duration that the traction net is in a low-frequency oscillation state; based on the duration that the traction net is in a low-frequency oscillation, increase 9 . The current loop scaling factor of the grid-side converter. 10. A detection device for traction net pressure, characterized in that the detection device comprises: The acquisition unit is used to collect the primary voltage data and secondary current data of the on-board transformer; a processing unit, configured to process the primary-side voltage data and the secondary-side current data to obtain voltage RMS data and power factor data of the on-board transformer, and based on the voltage RMS data and power factor data, obtaining the first oscillation frequency of the voltage RMS data and the second oscillation frequency of the power factor data; A determination unit, configured to determine that the traction net is in a low-frequency oscillation state when both the first oscillation frequency and the second oscillation frequency are within a preset frequency range.

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