A power grid resonance identification and suppression method fusing correlation coefficient and sensitivity

Abstract

The present application relates to power grid resonance suppression, in particular to a kind of power grid resonance identification and suppression method fusing correlation coefficient and sensitivity, the correlation coefficient of the effective value array of each line h harmonic current and the effective value array of power bus h harmonic voltage is calculated, and all target lines are selected based on correlation coefficient;The coupling harmonic impedance array of each target line is calculated, the first position greater than the average value of coupling harmonic impedance array in coupling harmonic impedance array is determined respectively, and the second position not greater than the average value of coupling harmonic impedance array;The average value of the coupling harmonic impedance corresponding to the first position and the second position is respectively calculated, and the harmonic voltage of the power bus corresponding to the first position and the second position is respectively calculated;The sensitivity index of each target line is calculated;The technical scheme provided by the present application can effectively overcome the defect that sensitive resonance branch cannot be accurately identified in the case of lack of phase information of monitoring data, and effectively suppress power grid resonance.

Description

Technical Field

[0001] This invention relates to power grid resonance suppression, and more specifically to a method for identifying and suppressing power grid resonance by integrating correlation coefficient and sensitivity. Background Technology

[0002] Currently, most resonance analysis methods for power systems are based on harmonic impedance models. These models establish the state equations or admittance matrix of the entire system, and then employ methods such as the eigenvalue method, state-space method, and modal analysis to comprehensively analyze the resonance risk of the power grid. While these methods offer high computational accuracy and relatively comprehensive analysis results, the final analysis outcome largely depends on the accuracy of the power grid parameters.

[0003] With the widespread application of power electronics technology, the interaction and coupling between power sources, grids, and loads have intensified, making it difficult to accurately obtain actual grid parameters and thus hindering the accurate establishment of state equations or admittance matrices. Furthermore, due to the dynamic changes in grid operating conditions, resonance analysis based on specific harmonic impedance models cannot completely avoid the occurrence of resonance.

[0004] With the vigorous construction of new power systems and the continuous development of smart grids, a large amount of monitoring data has been accumulated in the power grid, providing a data foundation for resonance analysis based on monitoring data. However, current monitoring data often lack phase information, making it impossible to accurately identify harmonic power flow and resonance paths through harmonic impedance characteristics. Therefore, how to accurately identify sensitive resonant branches and effectively suppress grid resonance when monitoring data lacks phase information is a key technical challenge that urgently needs to be solved. Summary of the Invention

[0005] (a) Technical problems to be solved

[0006] In view of the above-mentioned shortcomings of the existing technology, the present invention provides a grid resonance identification and suppression method that integrates correlation coefficient and sensitivity, which can effectively overcome the shortcomings of the existing technology that cannot accurately identify sensitive resonance branches and effectively suppress grid resonance when the monitoring data lacks phase information.

[0007] (II) Technical Solution

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A method for identifying and suppressing grid resonance by integrating correlation coefficient and sensitivity includes the following steps:

[0010] S1. Obtain the array of effective values ​​of the h-th harmonic voltage of the power supply bus and the array of effective values ​​of the h-th harmonic current of each line at the same time.

[0011] S2. Calculate the correlation coefficient between the effective value array of the h-th harmonic current of each line and the effective value array of the h-th harmonic voltage of the power supply bus, and select all target lines based on the correlation coefficient.

[0012] S3. Calculate the coupled harmonic impedance array for each target line, and determine the first position in the coupled harmonic impedance array that is greater than the average value of the coupled harmonic impedance array, and the second position that is not greater than the average value of the coupled harmonic impedance array.

[0013] S4. Calculate the average value of the coupling harmonic impedance corresponding to the first position and the second position respectively, and calculate the average value of the harmonic voltage of the power supply bus corresponding to the first position and the second position respectively;

[0014] S5. Calculate the sensitivity index of each target route;

[0015] S6. Based on the sensitivity index, sort the target lines to determine the degree of influence of each target line on the power grid resonance, and prioritize the adjustment of target lines with higher sensitivity index when suppressing power grid resonance.

[0016] Preferably, in S1, obtaining the effective value array of the h-th harmonic voltage of the power supply bus and the effective value array of the h-th harmonic current of each line within the same time period includes:

[0017] The effective value array of the h-th harmonic voltage of the power supply bus is U h =(U h,1 U h,2 , ..., U h,n The effective values ​​of the h-th harmonic currents of each line are arrayed as I. h,i =(I h,i,1 I h,i,2 , ..., I h,i,n ), where n is the data index in the array, h is the harmonic order, and i is the line number.

[0018] Preferably, in S2, the correlation coefficient between the effective value array of the h-th harmonic current of each line and the effective value array of the h-th harmonic voltage of the power supply bus is calculated, and all target lines are selected based on the correlation coefficient, including:

[0019] The correlation coefficient r between the effective values ​​of the h-th harmonic current of each line and the effective values ​​of the h-th harmonic voltage of the power supply bus is calculated using the following formula. h,i :

[0020]

[0021] in, This represents the mean of the array of effective values ​​of the h-th harmonic voltage of the power supply bus. The mean of the effective values ​​of the h-th harmonic current for each line is denoted by N, where N is the number of data points in the array.

[0022] Filter out the correlation coefficient r h,i All target lines with a value greater than 0.9.

[0023] Preferably, in S3, the coupled harmonic impedance arrays of each target line are calculated, and the first position in the coupled harmonic impedance array that is greater than the average value of the coupled harmonic impedance array, and the second position that is not greater than the average value of the coupled harmonic impedance array, are determined, including:

[0024] The coupling harmonic impedance array Z of each target line is calculated using the following formula. h,i :

[0025]

[0026] The coupling harmonic impedance array Z of the i-th target line h,i Average value of the coupled harmonic impedance array As dividing points, we determine the values ​​greater than the average value of the coupled harmonic impedance array. First position and not greater than the average value of the coupled harmonic impedance array Second position

[0027] Here, find(·) is used to find the array position that satisfies the inequality · condition.

[0028] Preferably, in S4, the average values ​​of the coupling harmonic impedances corresponding to the first position and the second position are calculated respectively, and the average values ​​of the harmonic voltages of the power supply bus corresponding to the first position and the second position are calculated respectively, including:

[0029] The following formula is used for the first position P h1,i Calculate the average value of the corresponding coupled harmonic impedance.

[0030]

[0031] The following formula is used for the second position P h2,i Calculate the average value of the corresponding coupled harmonic impedance.

[0032]

[0033] The following formula is used for the first position P h1,i Calculate the average value of the harmonic voltage of the corresponding power supply bus.

[0034]

[0035] The following formula is used for the second position P h2i Calculate the average value of the harmonic voltage of the corresponding power supply bus.

[0036]

[0037] Where, length(P) h1,i ) is the first position P h1,i The corresponding array length, length(P) h2,i ) is the second position P h2,i The corresponding array length.

[0038] Preferably, in S5, the sensitivity index of each target line is calculated, including:

[0039] The sensitivity index S of the i-th target line is calculated using the following formula. i :

[0040]

[0041] Preferably, in step S6, the target lines are sorted based on sensitivity indices to determine the degree of influence of each target line on grid resonance, and when suppressing grid resonance, the target lines with higher sensitivity indices are adjusted first, including:

[0042] According to the sensitivity index S i The target routes are sorted in descending order of sensitivity index S. i The larger the target line, the greater its impact on grid resonance. When suppressing grid resonance by changing the grid operation mode, the sensitivity index S should be adjusted first. i A relatively large target route.

[0043] (III) Beneficial Effects

[0044] Compared with existing technologies, the grid resonance identification and suppression method integrating correlation coefficient and sensitivity provided by this invention has the following beneficial effects:

[0045] 1) Combining correlation coefficients and sensitivity indices to judge sensitive resonant branches can effectively improve the accuracy of sensitive resonant branch identification;

[0046] 2) The accurate identification of sensitive resonant branches can be achieved solely by the effective value of the h-th harmonic voltage of the power supply bus and the effective value of the h-th harmonic current of each line. No phase information of the harmonics is required, and it can be directly applied to existing online power quality monitoring systems.

[0047] 3) By accurately identifying sensitive resonant branches, priority guidance is provided for resonance transfer based on grid operation mode adjustment, effectively supporting the efficient suppression of grid resonance. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0049] Figure 1 This is a schematic diagram of the process of the present invention;

[0050] Figure 2 This is a schematic diagram illustrating an example of the present invention;

[0051] Figure 3 For the present invention Figure 2 Scatter plots of the h-th harmonic currents of lines 1, 2, 3 and 6 versus the h-th harmonic voltage of the power supply bus. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0053] A method for identifying and suppressing grid resonances that integrates correlation coefficients and sensitivity, such as... Figure 1 As shown, S1 involves obtaining the effective value array of the h-th harmonic voltage of the power supply bus and the effective value array of the h-th harmonic current of each line within the same time period, specifically including:

[0054] The effective value array of the h-th harmonic voltage of the power supply bus is U h =(U h,1 U h,2 , ..., U h,n The effective values ​​of the h-th harmonic currents of each line are arrayed as I. h,i =(I h,i,1 I h,i,2 , ..., I h,i,n ), where n is the data index in the array, h is the harmonic order, and i is the line number.

[0055] S2. Calculate the correlation coefficient between the effective values ​​of the h-th harmonic current of each line and the effective values ​​of the h-th harmonic voltage of the power supply bus, and select all target lines based on the correlation coefficient, specifically including:

[0056] The correlation coefficient r between the effective values ​​of the h-th harmonic current of each line and the effective values ​​of the h-th harmonic voltage of the power supply bus is calculated using the following formula. h,i :

[0057]

[0058] in, This represents the mean of the array of effective values ​​of the h-th harmonic voltage of the power supply bus. The mean of the effective values ​​of the h-th harmonic current for each line is denoted by N, where N is the number of data points in the array.

[0059] Filter out the correlation coefficient r h,i All target lines with a value greater than 0.9.

[0060] S3. Calculate the coupled harmonic impedance array for each target line, and determine the first position in the coupled harmonic impedance array that is greater than the average value of the coupled harmonic impedance array, and the second position that is not greater than the average value of the coupled harmonic impedance array. Specifically, this includes:

[0061] The coupling harmonic impedance array Z of each target line is calculated using the following formula. h,i :

[0062]

[0063] The coupling harmonic impedance array Z of the i-th target line h,i Average value of the coupled harmonic impedance array As dividing points, we determine the values ​​greater than the average value of the coupled harmonic impedance array. First position and not greater than the average value of the coupled harmonic impedance array Second position

[0064] Here, find(·) is used to find the array position that satisfies the inequality · condition.

[0065] S4. Calculate the average value of the coupling harmonic impedance corresponding to the first position and the second position, and calculate the average value of the harmonic voltage of the power supply bus corresponding to the first position and the second position, specifically including:

[0066] The following formula is used for the first position P h1,i Calculate the average value of the corresponding coupled harmonic impedance.

[0067]

[0068] The following formula is used for the second position P h2,i Calculate the average value of the corresponding coupled harmonic impedance.

[0069]

[0070] The following formula is used for the first position P h1,i Calculate the average value of the harmonic voltage of the corresponding power supply bus.

[0071]

[0072] The following formula is used for the second position P h2,i Calculate the average value of the harmonic voltage of the corresponding power supply bus.

[0073]

[0074] Where, length(P) h1,i ) is the first position P h1,i The corresponding array length, length(P) h2,i ) is the second position P h2,i The corresponding array length.

[0075] S5. Calculate the sensitivity index of each target line, specifically including:

[0076] The sensitivity index S of the i-th target line is calculated using the following formula. i :

[0077]

[0078] S6. Based on sensitivity indices, rank the target lines to determine their impact on grid resonance, and prioritize adjusting target lines with higher sensitivity indices when suppressing grid resonance. Specifically, this includes:

[0079] According to the sensitivity index S i The target routes are sorted in descending order of sensitivity index S. i The larger the target line, the greater its impact on grid resonance. When suppressing grid resonance by changing the grid operation mode, the sensitivity index S should be adjusted first. i A relatively large target route.

[0080] To better illustrate the technical solution of this application, a specific example will be used for detailed explanation below:

[0081] like Figure 2As shown, a substation has 5 outgoing lines, numbered Line 1, Line 2, Line 3, Line 4, and Line 5, with the total incoming line numbered Line 6. The substation's low-voltage system experienced 5th harmonic parallel resonance. Based on synchronous monitoring of the effective values ​​of the 5th harmonic voltage on the power supply bus and the effective values ​​of the 5th harmonic current on the 6 lines, with data recorded every 3 seconds for a total monitoring time of 19 hours, the following arrays were obtained: U5 (effective value array of the 5th harmonic voltage on the power supply bus) and I (effective value array of the 5th harmonic current on each line at the same time). 5,i ,i=1,2,...,6, U5 and I 5,i The array length (data size) is 22800.

[0082] Calculate the correlation coefficients between the effective values ​​of the 5th harmonic currents of each line and the effective values ​​of the 5th harmonic voltages of the power supply bus. The results of the correlation coefficient calculations are shown in the table below:

[0083] Table 1. Calculation Results of Correlation Coefficients and Sensitivity Indicators for Each Line

[0084] line Correlation coefficient Sensitivity index Sensitive Resonant Branch Sequencing Line 1 0.995 3.26 2 Line 2 0.982 3.59 1 Line 3 0.907 0.58 4 Line 4 0.522 / / Line 5 0.318 / / Line 6 0.959 1.10 3

[0085] like Figure 3 As shown in Table 1, the correlation coefficients of lines 1, 2, 3 and 6 are all greater than 0.9.

[0086] For lines with a correlation coefficient greater than 0.9, calculate the coupled harmonic impedance array for each line, and determine the first position in the coupled harmonic impedance array that is greater than the average value of the coupled harmonic impedance array, and the second position that is not greater than the average value of the coupled harmonic impedance array.

[0087] The average values ​​of the coupling harmonic impedances corresponding to the first and second positions were calculated, as were the average values ​​of the harmonic voltages of the power supply buses corresponding to the first and second positions. Then, the sensitivity index of each line was calculated. As shown in Table 1, the sensitivity index of line 2 is 3.59, ranking first in its impact on the 5th harmonic resonance; the sensitivity index of line 1 is 3.6, ranking second in its impact on the 5th harmonic resonance; the sensitivity index of line 6 is 1.10, ranking third in its impact on the 5th harmonic resonance; and the sensitivity index of line 3 is 0.58, ranking fourth in its impact on the 5th harmonic resonance. Therefore, when suppressing grid resonance by changing the grid operation mode, lines 2 and 1 should be adjusted first.

[0088] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying and suppressing power grid resonance by integrating correlation coefficient and sensitivity, characterized in that: Includes the following steps: S1. Obtain the array of effective values ​​of the h-th harmonic voltage of the power supply bus and the array of effective values ​​of the h-th harmonic current of each line at the same time. S2. Calculate the correlation coefficient between the effective value array of the h-th harmonic current of each line and the effective value array of the h-th harmonic voltage of the power supply bus, and select all target lines based on the correlation coefficient. S3. Calculate the coupled harmonic impedance array for each target line, and determine the first position in the coupled harmonic impedance array that is greater than the average value of the coupled harmonic impedance array, and the second position that is not greater than the average value of the coupled harmonic impedance array. S4. Calculate the average value of the coupling harmonic impedance corresponding to the first position and the second position respectively, and calculate the average value of the harmonic voltage of the power supply bus corresponding to the first position and the second position respectively; S5. Calculate the sensitivity index of each target line, including: The sensitivity index of the i-th target line is calculated using the following formula. : ； in, , The first position Second position The corresponding average harmonic voltage of the power supply bus , The first position Second position The corresponding average value of the coupled harmonic impedance; S6. Based on the sensitivity index, sort the target lines to determine the degree of influence of each target line on the power grid resonance, and prioritize the adjustment of target lines with higher sensitivity index when suppressing power grid resonance.

2. The method for identifying and suppressing power grid resonance by integrating correlation coefficient and sensitivity according to claim 1, characterized in that: S1 obtains the array of effective values ​​of the h-th harmonic voltage of the power supply bus and the array of effective values ​​of the h-th harmonic current of each line at the same time, including: The effective values ​​of the h-th harmonic voltage of the power supply bus are as follows: The effective values ​​of the h-th harmonic current for each line are arrayed as follows: n is the data index in the array, h is the harmonic order, and i is the line number.

3. The method for identifying and suppressing power grid resonance by integrating correlation coefficient and sensitivity according to claim 2, characterized in that: In S2, the correlation coefficient between the effective values ​​of the h-th harmonic current of each line and the effective values ​​of the h-th harmonic voltage of the power supply bus is calculated, and all target lines are selected based on the correlation coefficient, including: The correlation coefficient between the effective values ​​of the h-th harmonic current of each line and the effective values ​​of the h-th harmonic voltage of the power supply bus is calculated using the following formula. : ； in, This represents the mean of the array of effective values ​​of the h-th harmonic voltage of the power supply bus. The mean of the effective values ​​of the h-th harmonic current for each line is denoted by N, where N is the number of data points in the array. Filter out correlation coefficients All target lines with a value greater than 0.

9.

4. The grid resonance identification and suppression method integrating correlation coefficient and sensitivity according to claim 3, characterized in that: In S3, the coupled harmonic impedance arrays for each target line are calculated. The first position in the coupled harmonic impedance array that is greater than the average value of the coupled harmonic impedance array, and the second position that is not greater than the average value of the coupled harmonic impedance array, are determined, including: The coupling harmonic impedance array of each target line is calculated using the following formula. : ； The coupling harmonic impedance array of the i-th target line Average value of the coupled harmonic impedance array As dividing points, we determine the values ​​greater than the average value of the coupled harmonic impedance array. First position and not greater than the average value of the coupled harmonic impedance array Second position ; in, To find the inequality The array position of the condition.

5. The grid resonance identification and suppression method integrating correlation coefficient and sensitivity according to claim 4, characterized in that: In S4, the average values ​​of the coupling harmonic impedances corresponding to the first and second positions are calculated respectively, and the average values ​​of the harmonic voltages of the power supply bus corresponding to the first and second positions are calculated respectively, including: The following formula is used for the first position Calculate the average value of the corresponding coupled harmonic impedance. : ； Use the following formula for the second position Calculate the average value of the corresponding coupled harmonic impedance. : ； The following formula is used for the first position Calculate the average value of the harmonic voltage of the corresponding power supply bus. : ； Use the following formula for the second position Calculate the average value of the harmonic voltage of the corresponding power supply bus. : ； in, First position The corresponding array length, For the second position The corresponding array length.

6. The method for identifying and suppressing power grid resonance by integrating correlation coefficient and sensitivity according to claim 1, characterized in that: S6 sorts target lines based on sensitivity indices to determine the degree of influence of each target line on grid resonance, and prioritizes adjusting target lines with higher sensitivity indices when suppressing grid resonance, including: According to sensitivity index The target routes are sorted in descending order of sensitivity index. The larger the target line, the greater its impact on grid resonance. When suppressing grid resonance by changing the grid operation mode, the sensitivity index should be adjusted first. A relatively large target route.

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