CN105653882A - Method for identifying magnetizing inrush current by utilizing current waveform characteristics - Google Patents

Abstract

The invention discloses a method for identifying the excitation inrush current by using the characteristics of the current waveform, which is specifically implemented according to the following steps: Step 1: Collect the three-phase current of the transformer winding in, And carry out differential processing on the current of each phase; Step 2: Calculate the three-phase current change rate in the power frequency period T Then determine the maximum value of the rate of change of the three-phase current with the minimum sampling point Then calculate the time interval of the extreme value of the three-phase current change rate Step 3: Use criteria to identify inrush currents and internal faults. The invention discloses a method for identifying the excitation inrush current by utilizing the characteristics of the current waveform, which reduces the influence of the direct current component, and has a simple method and a small amount of calculation, thereby reducing the misoperation of the differential protection.

Description

A Method for Identifying Magnetizing Inrush Current Using Current Waveform Features

technical field

The invention belongs to the technical field of relay protection for electric power system transformers, and in particular relates to a method for identifying excitation inrush current by using current waveform characteristics.

Background technique

Transformers are important equipment in power plants and substations, and their safe and reliable operation is of great significance to the continuous and stable operation of the entire power system. The longitudinal differential protection is one of the main protections of the transformer protection, and the excitation inrush current of the transformer is the main source of the maloperation of the transformer differential protection. The excitation inrush current is not the fault state of the transformer, so how to accurately identify the inrush current and internal faults and ensure the safe and stable operation of the transformer is of great significance.

How to accurately identify inrush current and internal fault is the most difficult and critical problem faced by transformer differential protection. In recent years, relevant scholars and experts at home and abroad have proposed many new principles and new methods for identifying inrush currents, which can be roughly divided into the following three categories: identification methods for inrush currents using current quantities, identification methods for inrush currents using voltage quantities, and current-voltage quantity phase identification methods. Combined discriminant method.

① Identification method of excitation inrush current using current quantity

It mainly includes the second harmonic amplitude ratio, discontinuity angle characteristics, waveform characteristics and so on. The principle of the second harmonic method is simple, the calculation amount is small, and it is easy to implement, but it is greatly affected by the transient current characteristics and the magnetization characteristics of the transformer, and it is difficult to set the second harmonic braking threshold. The discontinuous angle feature is affected by the near-zero current amplitude and weak discontinuous angle characteristics at the discontinuous angle of the excitation inrush current, which increases the requirements for hardware. Waveform symmetry faces the problem of threshold selection and symmetry range (symmetry angle) selection.

②Voltage-based excitation inrush current identification method

It mainly includes voltage ratio method and voltage harmonic restraint method. In the voltage ratio method, when the transformer is air-dropped to an internal minor fault such as a slight inter-turn short circuit, the voltage at both sides of the transformer changes slightly, which may also cause a misjudgment of the criterion, which in turn leads to the rejection of the differential protection. The voltage harmonic braking method is less affected by resonance, but the voltage braking setting is greatly affected by the system impedance.

③ Identification method of excitation inrush current based on transformer current and voltage

It mainly includes magnetic flux characteristics, power differential principle, etc. Due to the difficulty in obtaining the residual magnetism of the transformer, the ψ- _id curve obtained in the case of inrush current will deviate from the magnetization curve, which will lead to misjudgment of the magnetic flux characteristic method. At the same time, there are difficulties in partitioning and complex setting of the braking coefficient threshold. The power differential method needs to avoid the charging process of the transformer in the first cycle of the inrush current, which leads to a delay in discrimination; it is difficult to accurately calculate the copper loss during the excitation inrush current, so it is difficult to use this principle to identify the threshold value setting of the inrush current.

In addition, intelligent methods including fuzzy logic, wavelet transform, and neural network have been successively introduced into the research on the identification of transformer inrush current. Effectively applied to industrial sites.

Aiming at the insufficiency of transformer inrush identification, the present invention proposes to use the time interval between the maximum value and minimum value of the current after differential processing to identify inrush current and fault based on the current discontinuity and peak characteristics during inrush current, which is expected to improve the inrush current identification of transformer differential protection ability.

Contents of the invention

The purpose of the present invention is to provide a method for identifying the excitation inrush current by using the characteristics of the current waveform, which solves the problem of differential protection misoperation in the prior art.

The technical solution adopted in the present invention is a method for identifying the excitation inrush current using the characteristics of the current waveform, which is specifically implemented according to the following steps:

Step 1: Collect the three-phase current of the transformer winding in, And perform differential processing on each phase current;

Step 2: Calculate the rate of change of the three-phase current in the power frequency period T Then determine the maximum value of the rate of change of the three-phase current with the minimum sampling point Then calculate the time interval of the extreme value of the three-phase current change rate

Step 3: Use criteria to identify inrush currents and internal faults.

The present invention is also characterized in that:

Step 1 is specifically: collect the three-phase currents i _A (k), i _B (k), and i _C (k) of the transformer, and calculate the differential current of each phase i _dA (k)=i _A (k)-i _A (k-1), i _dB (k)=i _B (k)-i _B (k-1), i _dC (k)=i _C (k)-i _C (k-1), where k= 2,3,4….

Step 2 is specifically:

Calculate the current change rate of each phase differential current i _dA (k), i _dB (k), i _dC (k) in a power frequency calculation cycle T Determine the maximum value of the three-phase current change rate with the minimum sampling point which is

Among them, k ₀ is the initial sampling point for inrush current discrimination, N is the number of sampling points in the power frequency period, and T _s is the sampling period;

According to the sampling points corresponding to the maximum value and minimum value of the three-phase current change rate Calculate the corresponding extreme time interval which is

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; A</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; A</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; A</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}\\ {\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; B</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; B</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; B</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}\\ {\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; C</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; C</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; C</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}\end{array}\right.$

in, In order to calculate the sampling points corresponding to the maximum value and the minimum value in the data window.

Step 3 is specifically:

According to the time interval of the extreme value of the three-phase current change rate in step 2 Inrush currents and internal faults are identified according to the following inrush current identification criteria:

Among them, T is the power frequency cycle, and ρ is the setting threshold coefficient that comprehensively considers the influence of current harmonic components and calculation errors when internal faults occur;

When at least one phase of the three-phase current meets the above inrush identification criteria, it is judged as an inrush current and the transformer differential protection is blocked; otherwise, it is judged as an internal fault.

Threshold coefficient ρ takes 0.2 to 0.3.

In order to improve the reliability of inrush current discrimination, on the basis of the discrimination results in step 3, N/4 data windows are shifted sequentially, and the process of steps 1-3 is repeated N times, and the inrush current identification criterion is confirmed multiple times.

The beneficial effects of the present invention are: a method for identifying excitation inrush current by using current waveform characteristics of the present invention, based on differential waveform characteristics of transformer inrush current and internal fault current, using extreme value characteristics of current change rate to provide a method for identifying excitation inrush current and fault current New, simple and reliable method. The invention only needs to perform differential processing on the current waveforms of each phase, and judge the time interval between the maximum value and the minimum value of the differential waveform of each phase to distinguish the excitation inrush current and the internal fault current. Compared with other excitation inrush current identification principles, the present invention has the following significant advantages:

(1) Utilizing the discontinuity angle and cusp composite characteristics of transformer excitation inrush current, the applicability of identifying excitation inrush current by using current characteristics is improved;

(2) The characteristics of the current change rate are used to reduce the influence of the DC component and highlight the inrush current characteristics in the case of weak discontinuity angles.

Description of drawings

FIG. 1 is a flow chart of a method for identifying a magnetizing inrush current using current waveform features in the present invention.

detailed description

The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

The excitation circuit of the transformer is equivalent to the fault branch of the internal fault of the transformer. When the iron core of the transformer is saturated, a large excitation inrush current will be generated and flow into the differential relay, causing the differential protection to malfunction. Since the excitation current is very large, if the action current is used to avoid its influence, the sensitivity of the differential protection will be very low when the transformer internal fault occurs. In view of this, the present invention uses the characteristics of the current waveform to identify the excitation inrush current and prevent the excitation inrush current from causing differential protection. Malfunction of protection. Due to the existence of transformer excitation inrush current discontinuity angle and peak wave, the time interval between the maximum value and the minimum value of the inrush current differential waveform is less than half a cycle; while the differential waveform of the internal fault current is approximately a sine wave, and its maximum value and pole The time interval of the small value is approximately half a cycle. Therefore, by judging the time interval between the maximum value and the minimum value of the current differential waveform, the excitation inrush current and the fault current can be distinguished.

The present invention is a method for identifying the excitation inrush current by using the characteristics of the current waveform, the process flow is shown in Figure 1,

Specifically follow the steps below:

Step 1: Collect the three-phase current of the transformer winding in, That is i _A (k), i _B (k), i _C (k), calculate the differential current of each phase i _dA (k) = i _A (k)-i _A (k-1), i _dB (k) = i _B (k)-i _B (k-1), i _dC (k)=i _C (k)-i _C (k-1), where k=2,3,4...;

Since the transformer winding is inductive, both the excitation inrush current and the internal fault current contain some non-periodic components, and differential processing is used to reduce the influence of non-periodic components.

Step 2: Calculate the rate of change of the three-phase current in the power frequency period T Then determine the maximum value of the rate of change of the three-phase current with the minimum sampling point Then calculate the time interval of the extreme value of the three-phase current change rate Specifically:

Calculate the current change rate of each phase differential current i _dA (k), i _dB (k), i _dC (k) in a power frequency calculation cycle T Determine the maximum value of the three-phase current change rate with the minimum sampling point which is

Among them, k ₀ is the initial sampling point for inrush current discrimination, N is the number of sampling points in the power frequency period, and T _s is the sampling period;

According to the sampling points corresponding to the maximum value and minimum value of the three-phase current change rate Calculate the corresponding extreme time interval which is

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; A</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; A</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; A</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}\\ {\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; B</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; B</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; B</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}\\ {\mathrm{<span\; class="notranslate">\; t</span>}}_{\mathrm{<span\; class="notranslate">\; C</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; |</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; C</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; k</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; C</span>}}<span\; class="notranslate">\; |</span><span\; class="notranslate">\; \&Center\; Dot;</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}\end{array}\right.$

in, In order to calculate the sampling points corresponding to the maximum value and the minimum value in the data window.

Step 3: Identify inrush currents and internal faults using the criteria:

According to the time interval of the extreme value of the three-phase current change rate in step 2 Inrush currents and internal faults are identified according to the following inrush current identification criteria:

Among them, T is the power frequency cycle, ρ is the setting threshold coefficient that comprehensively considers the influence of current harmonic components and calculation errors when internal faults occur, and ρ is taken as 0.2 to 0.3;

Extreme time due to inrush current less than half a cycle, while the extreme time of internal fault It is approximately half a cycle, so when at least one phase of the three-phase current meets the above inrush identification criteria, it is judged as an inrush current, and the transformer differential protection is blocked; otherwise, it is judged as an internal fault.

Step 4: Move the data window, calculate the extreme value and interval time of the three-phase current in sequence, and confirm the inrush current identification result several times. In order to improve the reliability of inrush current discrimination, on the basis of the discrimination results in step 4, N/4 data windows are sequentially shifted, and the aforementioned process is repeated N times, and the inrush current criterion is confirmed multiple times, so as to realize the reliable confirmation of transformer inrush current.

Example

Assuming that the number of sampling points in the power frequency cycle is N, use the data window of one power frequency cycle to calculate the first group of maximum and minimum values. If the inrush current criterion is satisfied, count Num=1; in order to improve the reliability of inrush current discrimination, Then move N/4 data windows point by point sequentially, and continuously calculate the maximum value and minimum value group of the current change rate that satisfies the inrush current criterion in the data window, and then count Num when the time difference is satisfied. The inrush current can be reliably confirmed when the criterion is met for the first time, and the reliable blocking of the transformer differential protection can be realized.

The method of the invention utilizes the waveform characteristics of the three-phase current change rate of the transformer winding, and proposes an excitation inrush current identification method utilizing the time interval characteristics of the maximum value and the minimum value of the current differential waveform. This method not only highlights the weak discontinuity angle characteristics of the excitation inrush current and reduces the influence of the DC component, but also has a simple method, a small amount of calculation, and is easy to apply to engineering. At the same time, it is conducive to improving the universality and applicability of waveform characteristics.

Claims (6)

1. A method for identifying magnetizing inrush current by using current waveform characteristics is characterized by comprising the following steps:

step 1: collecting three-phase current of transformer windingWherein,and carrying out differential processing on each phase current;

step 2: calculating the three-phase current change rate in the power frequency period TThen determining the maximum value of the three-phase current change rateAnd minimum valueSampling point ofFurther calculating the time interval of the three-phase current change rate extreme value

And step 3: and identifying inrush current and internal faults by using criteria.

2. The method for identifying the magnetizing inrush current by using the current waveform characteristics as claimed in claim 1, wherein the step 1 specifically comprises: three-phase current i to transformer_A(k)、i_B(k)、i_C(k) Collecting and calculating differential current i of each phase_dA(k)＝i_A(k)-i_A(k-1)、i_dB(k)＝i_B(k)-i_B(k-1)、i_dC(k)＝i_C(k)-i_C(k-1), wherein k is 2,3,4 ….

3. The method for identifying the magnetizing inrush current by using the current waveform characteristics as claimed in claim 2, wherein the step 2 is specifically as follows:

calculating differential current i of each phase_dA(k)、i_dB(k)、i_dC(k) Rate of change of current within a power frequency calculation period TDetermining maximum value of three-phase current change rateAnd minimum valueSampling point ofNamely, it is

Rate of change of current:

maximum value:

minimum value:

wherein k is₀Judging an initial sampling point for inrush current, wherein N is the number of sampling points in a power frequency period, T_sIs a sampling period;

according to the maximum value and the sampling point corresponding to the minimum value of the three-phase current change rateCalculating the corresponding extremum time intervalNamely, it is

$\left\{\begin{array}{c}{t}_A=\left|k_{1A}-k_{2A}\right|\&CenterDot;T_s\\ t_B=\left|k_{1B}-k_{2B}\right|\&CenterDot;T_s\\ t_C=\left|k_{1C}-k_{2C}\right|\&CenterDot;T_s\end{array}\right.$

Wherein,the sampling points corresponding to the maximum value and the minimum value in the data window are calculated.

4. The method for identifying a magnetizing inrush current by using the current waveform characteristics as claimed in claim 1, wherein the step 3 is specifically:

time interval of three-phase current change rate extremum according to step 2Inrush and internal faults are identified according to the following inrush identification criteria:

wherein T is a power frequency period, and rho is a setting threshold value coefficient which comprehensively considers the current harmonic component and the calculation error influence during the internal fault;

when at least one phase of the three-phase current meets the inrush current identification criterion, the three-phase current is judged to be inrush current, and the transformer differential protection is locked; otherwise, the internal fault is judged.

5. The method for identifying the magnetizing inrush current by using the current waveform characteristics as claimed in claim 4, wherein the threshold coefficient p is 0.2-0.3.

6. The method for identifying magnetizing inrush current by using current waveform characteristics as claimed in any one of claims 1 to 4, wherein in order to improve the reliability of inrush current identification, N/4 data windows are sequentially shifted on the basis of the identification result of step 3, and the process of steps 1 to 3 is repeated N times, and the identification criterion of inrush current is determined multiple times.