A short-circuit fault direction discrimination method and system for wind farm sending-out lines

Abstract

A short-circuit fault direction discrimination method and system for a wind farm sending line, comprising the following steps: collecting positive sequence voltage and current signals of the wind power side sending line; pre-processing the positive sequence voltage and current signal data, calculating the positive sequence impedance amplitude using the pre-processed positive sequence voltage and current; judging whether the fault starting condition is met according to the positive sequence impedance amplitude; calculating the positive sequence impedance amplitude fluctuation function, and counting the proportion of the number of points meeting the positive direction fault criterion; obtaining the proportional setting value affected by the measurement error and abnormal data; comparing the proportion of the number of points meeting the positive direction fault criterion K with the proportional setting value to judge the fault direction. The present application can effectively distinguish the positive and negative direction faults of the wind farm sending line, measure the impedance fluctuation degree by using the DFA method, and form the line fault direction criterion. It is not affected by the operation condition of the wind farm and system oscillation, has strong resistance to transition resistance and abnormal data, is suitable for wind power integrated system, and has application prospect.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of wind farm sending-out line protection, and particularly relates to a short-circuit fault direction discrimination method and system for a wind farm sending-out line. BACKGROUND

[0002] Under the driving of energy transformation and the increasing maturity of power electronic technology, large-scale wind power is connected to power systems, and the fault characteristics of the wind power are different from those of conventional power grids, so that the power frequency quantity protection has an adaptation problem. The fault component direction element is widely applied in power systems. The fault component direction element is applicable to linear networks and systems with equal positive and negative sequence impedances, while the large-scale wind power connection changes the linear network of the power system into a nonlinear network, and the positive and negative sequence impedances of the wind farm are not equal and have fluctuation characteristics, so that the traditional short-circuit fault direction discrimination method based on the fault component direction element is not applicable to the wind farm sending-out line, and the traditional short-circuit fault direction discrimination method for the wind farm sending-out line is unreliable due to the frequency deviation characteristics and impedance fluctuation. SUMMARY

[0003] The application aims to provide a short-circuit fault direction discrimination method and system for a wind farm sending-out line, so as to solve the problem of the unreliability of the traditional short-circuit fault direction discrimination method for the wind farm sending-out line due to the frequency deviation characteristics and impedance fluctuation.

[0004] To achieve the above-mentioned purpose, the application adopts the following technical solutions:

[0005] A short-circuit fault direction discrimination method for a wind farm sending-out line, comprising the following steps:

[0006] When a fault occurs in the wind farm sending-out line, the positive sequence voltage and current signals of the wind farm sending-out line are collected;

[0007] The extracted positive sequence voltage and current signal data are preprocessed, and the positive sequence impedance amplitude is calculated by using the preprocessed positive sequence voltage and current;

[0008] Whether the fault starting condition is met is determined according to the positive sequence impedance amplitude;

[0009] The positive sequence impedance amplitude fluctuation function is calculated, and the proportion of the number of points meeting the positive direction fault criterion is calculated;

[0010] The proportional setting value affected by the measurement error and abnormal data is obtained;

[0011] The proportion of the number of points meeting the positive direction fault criterion is compared with the proportional setting value, and the fault direction is determined.

[0012] Further, the positive sequence voltage and current signals of the wind farm sending-out line protection installation are collected, and the data window is one cycle.

[0013] Further, the data preprocessing is: using a band-pass filter to filter out the data outside 35Hz-65Hz in the extracted signal, and using Prony algorithm to extract the power frequency signal in the filtered data; the positive sequence impedance is calculated by the ratio of voltage fault component and current fault component, and the positive sequence impedance amplitude calculation method is:

[0014]

[0015] In the formula: U M1 , I M1 are respectively the positive sequence voltage and current signals collected during the fault transient period of the wind power side sending-out line, U M1|0| , I M1|0| are respectively the positive sequence voltage and current signals collected before the fault of the wind power side sending-out line.

[0016] Further, it is judged whether the fault starting condition is met, and the steps are specifically:

[0017] The positive sequence impedance amplitude difference under positive and negative direction faults of the wind power side sending-out line is used to set the fault starting condition as the positive sequence impedance amplitude |Z M1 | being greater than or equal to the positive sequence impedance amplitude |Z L1 | of the wind power plant sending-out line, if it is met, the subsequent steps are performed, and if it is not met, the detection is continued.

[0018] Further, the positive sequence impedance amplitude fluctuation function is calculated, and the proportion K of the number of points meeting the positive direction fault criterion is calculated, and the steps are specifically:

[0019] Taking |Z M1 | as a non-stationary time series, the cumulative deviation of |Z M1 | time series is calculated to obtain a new profile sequence Y(n), and the calculation formula of Y(n) is:

[0020]

[0021] In the formula: is the average value of |Z M1 | time series;

[0022] The new sequence Y(n) is divided into N h groups of h discrete points, and N h = [N / h]; the number of discrete points of Y(n) is not always an integer multiple of h, and there is a small part of discrete points not in N h subintervals, and the inverse sequence of Y(n) is also divided into N h non-overlapping equal-length subintervals, and a total of 2N h equal-length subintervals v are obtained; each equal-length subinterval data v, v = 1, 2, ···, N h; the least square fitting is used to obtain the local trend function y v (n) of the sub-interval v (n) to obtain the local detrended result of each sub-interval, and the local detrended result of each sub-interval is also the fluctuation value of each sub-interval:

[0023]

[0024] The local detrended result of the sub-interval of the reverse division is:

[0025]

[0026] |Z M1 The time series fluctuation function calculation formula is:

[0027]

[0028] According to the positive and reverse direction faults of the wind power side sending out line |Z M1 The time series fluctuation function difference gets the line fault direction judgment condition: under the positive direction fault, α(h) = log h F(h)>0, the proportion K of the number of points satisfying α(h)>0 is counted.

[0029] Further, the proportion setting value affected by the measurement error and abnormal data is obtained, and the steps are specifically:

[0030] When the wind power side sending out line occurs positive direction fault, the proportion K of the number of points satisfying α(h)>0 is 100% under ideal state, considering the influence of CT, PT measurement error and abnormal data factors, the reliable coefficient is introduced to avoid the influence of the above factors, and the proportion setting value is set as follows:

[0031] K set =K1K2

[0032] In the formula: K1 is the reliable coefficient considering the CT, PT measurement error factor, which is 0.95; K2 is the reliable coefficient considering the abnormal data factor, which is 0.95. The proportion setting value K set =90%.

[0033] Further, when the proportion K of the number of points satisfying α(h)>0 is greater than the proportion setting value K set =90%, the wind power side sending out line occurs positive direction fault, otherwise the wind power side sending out line occurs reverse direction fault.

[0034] Further, a short-circuit fault direction discrimination system for a wind farm sending out line comprises:

[0035] A data acquisition module is used to acquire positive sequence voltage and current signals of the wind power side sending out line when the wind farm sending out line occurs fault.

[0036] a positive sequence impedance amplitude obtaining module, configured to pre-process the extracted positive sequence voltage and current signal data, and calculate the positive sequence impedance amplitude by using the pre-processed positive sequence voltage and current;

[0037] a judging module, configured to determine whether the fault starting condition is met according to the positive sequence impedance amplitude;

[0038] a judging data obtaining module, configured to calculate a positive sequence impedance amplitude fluctuation function, count the proportion of the number of points meeting the positive direction fault criterion, and obtain a proportional setting value affected by measurement error and abnormal data;

[0039] a comparing module, configured to compare the proportion of the number of points meeting the positive direction fault criterion with the proportional setting value, and determine the fault direction.

[0040] Compared with the prior art, the present application has the following technical effects:

[0041] The present application provides a short-circuit fault direction determination method for a wind farm sending line, which can effectively distinguish the positive and negative direction faults of the wind farm sending line, measure the impedance fluctuation degree by using the DFA method, form a line fault direction criterion, and is not affected by the operation condition of the wind farm and system oscillation, has strong resistance to transition resistance and abnormal data, is suitable for wind power integrated system, and has application prospect. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 The flow chart of the present application;

[0043] Figure 2 The structure topology of the large-scale wind turbine integrated power system in the embodiment of the present application;

[0044] Figure 3 The positive sequence impedance fluctuation function of the wind farm sending line when the ABG fault occurs at the main transformer T1 in the present application;

[0045] Figure 4 The positive sequence impedance fluctuation function of the wind farm sending line when the ABG fault occurs at the wind farm sending line in the present application. DETAILED DESCRIPTION

[0046] The present application will be further described below in combination with the drawings and specific embodiments.

[0047] The technical scheme of the present application is: a short-circuit fault direction discrimination method for a wind farm sending-out line is provided, when a fault occurs in the wind farm sending-out line, firstly, the positive sequence voltage and current of the wind power side sending-out line are sampled, secondly, the sampled data is preprocessed, the positive sequence impedance amplitude is calculated, and whether the fault starting condition is met is judged, then the positive sequence impedance fluctuation function is calculated, and the proportion K of the number of points satisfying α(h)>0 is counted. Finally, the proportion K of the number of points satisfying α(h)>0 is compared with the proportional setting value to judge the fault direction.

[0048] The specific steps are:

[0049] Step 1. Extract the positive sequence voltage and current signals at the protection installation of the wind power side sending-out line, pre-process the extracted positive sequence voltage and current signal data, and calculate the positive sequence impedance amplitude using the pre-processed positive sequence voltage and current;

[0050] Step 2. Determine whether the fault starting condition is met according to the positive sequence impedance amplitude;

[0051] Step 3. Calculate the positive sequence impedance amplitude fluctuation function, and count the proportion of the number of points satisfying the positive direction fault criterion;

[0052] Step 4. Set the proportional setting value considering the influence of measurement error and abnormal data;

[0053] Step 5. Compare the proportion K of the number of points satisfying the positive direction fault criterion with the proportional setting value to judge the fault direction.

[0054] The protection installation is usually in the indoor distribution cabinet, outdoor transformer station (usually local protection), power transmission line, etc.

[0055] Example 1: A large-scale wind turbine connected to a power system as shown in the accompanying Figure 2 is established as a simulation model. The wind farm is composed of 33 1.5MW double-fed wind turbines. The equivalent positive sequence impedance of the main transformer T1 is Z T1 =j0.12; the equivalent positive sequence impedance of the wind farm sending-out line is Z L1 =0.164+j0.479; and the equivalent positive sequence impedance of the power grid system is Z S1 =j0.065. The system reference voltage is 220kV, and the reference capacity is 1000MWA. The wind farm operating condition is set to super-synchronous operating state, the fault type is set to ABG fault, and the fault points are set at f1 and f2.

[0056] (1) When an ABG fault occurs at f1, the collected wind power side sending-out line positive sequence voltage and current signal data is pre-processed, the positive sequence impedance amplitude and its fluctuation function F(h) are calculated, and the fluctuation function F(h) max= 0.00043; by statistics to meet the proportion of points α(h) > 0 K = 0%, with the set value K set = 90% compared to K < K set , determined as the opposite direction fault, fluctuation function F(h) is shown in the attached Figure 3 .

[0057] (1) When f2 occurs ABG fault, the collected wind power side sending line positive sequence voltage, current signal data preprocessing, calculation of positive sequence impedance amplitude and its fluctuation function F(h), get the fluctuation function F(h) min = 49.2347; by statistics to meet the proportion of points α(h) > 0 K = 100%, with the set value K set = 90% compared to K > K set , determined as the positive direction fault, fluctuation function F(h) is shown in the attached Figure 4 .

[0058] Example 2: as shown in the attached Figure 2 Large-scale wind turbine access to the power system as a simulation model. Wind farm consists of 33 1.5MW double-fed wind turbine. Main transformer T1 equivalent positive sequence impedance is Z T1 = j0.12; wind farm sending line equivalent positive sequence impedance is Z L1 = 0.164 + j0.479; power system equivalent positive sequence impedance is Z S1 = j0.065. System reference voltage 220kV, the reference capacity is 1000MWA. When Figure 2 topology without fault occurs, set the power system occurs oscillation, set the two end power phase angle difference to 0° ~ 360° periodic change, oscillation time is 1 second.

[0059] (1) When Figure 2 topology without fault occurs, and wind farm operating condition is sub-synchronous operation state, after the power system occurs oscillation, the collected wind power side sending line positive sequence voltage, current signal data preprocessing, calculation of positive sequence impedance amplitude |Z M1 |. Can get |Z M1 | time series |Z M1 | max = 0.0040p.u., by fault starting condition criterion can get |Z M1 | max <|Z L1 | does not meet the fault starting condition.

[0060] (2) When Figure 2When the topology shown is fault-free and the wind farm is operating synchronously, after a power system oscillation, the positive sequence voltage and current signal data of the wind power side transmission line are preprocessed, and the positive sequence impedance amplitude |Z is calculated. M1 |。 We can obtain |Z M1 |Time series|Z M1 | max =0.0201 pu, which can be obtained through the fault start condition criterion |Z M1 | max <|Z L1 The fault start conditions are not met.

[0061] (3) When Figure 2 When the topology shown is fault-free and the wind farm is operating in a supersynchronous state, after the power system oscillates, the positive sequence voltage and current signal data of the wind power side transmission line are preprocessed, and the positive sequence impedance amplitude |Z is calculated. M1 |。 We can obtain |Z M1 |Time series|Z M1 | max =0.2110 pu, which can be obtained through the fault start condition criterion |Z M1 | max <|Z L1 The fault start conditions are not met.

[0062] Example 3: Create as shown in the attached document Figure 2 The large-scale wind turbine integration into the power system shown is used as a simulation model. The wind farm consists of 33 1.5MW doubly-fed wind turbines. The equivalent positive-sequence impedance of the main transformer T1 is Z. T1 =j0.12; The equivalent positive sequence impedance of the wind farm's transmission line is Z. L1 =0.164+j0.479; the equivalent positive sequence impedance of the power grid system is Z. S1 =j0.065. The system reference voltage is 220kV, and the reference capacity is 1000MWA. The fault type is set to ABG fault, the fault point is set at f2 of the wind farm's transmission line, and the voltage and current signals of the wind farm's transmission line are set to have a data loss or false pulse once every 5ms.

[0063] (1) To verify the data loss resistance of the proposed algorithm, Table 1 shows the verification results of the line fault direction discrimination method when data loss occurs under different transition resistances ABG faults in different operating states of the wind farm.

[0064] Table 1 Validation of the line fault direction determination method under missing data.

[0065]

[0066] From Table 1, it can be seen that the accuracy of the proposed line fault direction identification method is stable under different operating states of the wind farm and different transition resistances, and the method has strong anti-data loss ability under different operating states and transition resistances.

[0067] (2) To verify the anti-virtual impulse ability of the proposed algorithm, Table 2 gives the verification results of the line fault direction identification method when virtual impulses occur under ABG faults with different transition resistances under different operating states of the wind farm.

[0068] Table 2 Line fault direction identification method verification under virtual impulse

[0069]

[0070] From Table 2, it can be seen that the accuracy of the proposed line fault direction identification method is stable under different operating states of the wind farm and different transition resistances, and the method has strong anti-data loss ability under different operating states and transition resistances.

Claims

1. A short circuit fault direction discrimination method for a wind farm sending line, characterized in that, The method comprises the following steps: When the wind farm sending line fails, the positive sequence voltage and current signals of the wind power side sending line are collected; The extracted positive sequence voltage and current signal data are preprocessed, and the positive sequence impedance amplitude is calculated using the preprocessed positive sequence voltage and current; Whether the fault starting condition is met is determined according to the positive sequence impedance amplitude; The positive sequence impedance amplitude fluctuation function is calculated, and the proportion of the number of points meeting the positive direction fault criterion is counted; The proportional setting value affected by the measurement error and abnormal data is obtained; The proportion of the number of points meeting the positive direction fault criterion K is compared with the proportional setting value to determine the fault direction.

2. The short circuit fault direction discrimination method for a wind farm sending line according to claim 1, characterized in that, The positive sequence voltage and current signals at the installation position of the wind power side sending line protection are collected, and the data window is one cycle.

3. The short circuit fault direction discrimination method for wind farm sending line according to claim 1, characterized in that, The data preprocessing is as follows: the data other than 35Hz-65Hz in the extracted signal is filtered out using a band-pass filter, and the power frequency signal in the filtered data is extracted using the Prony algorithm; the positive sequence impedance is calculated by the ratio of the voltage fault component to the current fault component, and the positive sequence impedance amplitude calculation method is as follows: In the formula: U M1 , I M1 are respectively the positive sequence voltage and current signals collected during the transient period of the wind power side sending-out line fault, U M1|0| , I M1|0| are respectively the positive sequence voltage and current signals collected before the wind power side sending-out line fault.

4. The short circuit fault direction discrimination method for a wind farm sending line according to claim 1, characterized in that, Whether the fault starting condition is met is determined, and the specific steps are as follows: The positive sequence impedance amplitude difference under positive and reverse direction faults of the wind power side sending out line is used to set the fault starting condition as the positive sequence impedance amplitude |Z M1 | greater than or equal to the positive sequence impedance amplitude |Z L1 | of the wind farm sending out line. If the condition is met, the subsequent step is performed, and if the condition is not met, the detection is continued.

5. The short circuit fault direction discrimination method for wind farm sending line according to claim 1, characterized in that, The positive sequence impedance amplitude fluctuation function is calculated, and the proportion of the number of points satisfying the positive direction fault criterion is counted K The steps are specifically as follows: | as non-stationary time series, calculate Z M1 | as non-stationary time series, calculate Z M1 | as non-stationary time series, calculate Y ( n ), Y ( n ) In the formula: = |t| - |t-1| Z M1 |time series average; Put the new sequence Y ( n )by h Grouping discrete points into a set, dividing... N h There are three non-overlapping sub-intervals of equal length, among which N h =[ N / h ]; Y ( n The number of discrete points is not always h Integer multiples of, there exist a small number of discrete points that are not N h Phenomena within sub-intervals, Y ( n The reverse order is also performed. N h Divide the data into 2 non-overlapping subintervals of equal length, and obtain a total of 2... N h There are equal-length subintervals v; data for each equal-length subinterval v , v =1,2,···, N h The local trend function of this sub-interval is obtained by least squares fitting. y v ( n );use Y ( n )and y v ( n Perform local detrending; the local detrending result for each sub-interval is also the fluctuation value for that sub-interval. The local detrended results of the reverse divided sub-intervals are as follows: | Z M1 | The time series fluctuation function is calculated by the following formula: According to the wind power side sending out line positive and negative direction fault Z M1 |Time series fluctuation function difference line fault direction discrimination condition: positive direction fault α ( h )=log h F ( h )>0, the number of points satisfying α ( h )>0 point proportion K .

6. The short circuit fault direction discrimination method for a wind farm sending line according to claim 5, characterized in that, The proportional setting value affected by the measurement error and abnormal data is obtained, and the specific steps are as follows: When the wind power side sending line occurs positive direction fault, the ideal state meets α ( h )>0 point ratio K 100%, considering the CT, PT measurement error and abnormal data factors, the reliable coefficient is introduced to avoid the influence of the above factors, and the proportional setting value is as follows: In the formula: K 1 is a reliability coefficient taking into account the error factors of CT and PT measurement, and is 0.95; K 2 is a reliability coefficient taking into account the abnormal data factors, and is 0.95; the proportional setting value is calculated K set = 90%.

7. The short circuit fault direction discrimination method for a wind farm sending line according to claim 6, characterized in that, When the condition is met α ( h )>0 point proportion K Greater than the proportion setting value K set When the proportion is 90%, the wind power side sending line occurs positive direction fault, otherwise the wind power side sending line occurs negative direction fault.

8. A short circuit fault direction discrimination system for a wind farm sending line, characterized by, It comprises: A data collection module is configured to collect the positive sequence voltage and current signals of the wind power side sending line when the wind farm sending line fails; A positive sequence impedance amplitude acquisition module is configured to preprocess the extracted positive sequence voltage and current signal data, and calculate the positive sequence impedance amplitude using the preprocessed positive sequence voltage and current; A judgment module is configured to determine whether the fault starting condition is met according to the positive sequence impedance amplitude; A judgment data acquisition module is configured to calculate the positive sequence impedance amplitude fluctuation function, count the proportion of the number of points meeting the positive direction fault criterion, and obtain the proportional setting value affected by the measurement error and abnormal data; A comparison module is configured to compare the proportion of the number of points meeting the positive direction fault criterion K with the proportional setting value to determine the fault direction.

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