A method and system for solving mid-short circuit abnormality in network construction type control

Abstract

The application relates to the technical field of power grids, and particularly discloses a network-constructing type control short-circuit abnormality solving method and system. The application first acquires node current information, node frequency information and node harmonic information, then acquires a current surge value according to the node current information, next acquires a power grid node fluctuation difference value according to the node frequency information, then acquires a harmonic increment value according to the node harmonic information, and finally, calculates a fluctuation load value according to the current surge value, the power grid node fluctuation difference value and the harmonic increment value, and judges whether the fluctuation load value is greater than a preset threshold value; if yes, it is determined that a short-circuit risk exists in the connection of a distributed new energy and a power grid node, a target node is found according to the fluctuation load value, the distributed new energy is connected with the target node, and the position of the power grid node is paired in advance, so that the problem that a short circuit is caused in the power grid due to excessively large load can be avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid, and particularly relates to a method and system for solving short-circuit abnormality in grid-forming control. BACKGROUND

[0002] The grid-forming control refers to a control strategy of a power electronic converter, which can enable the converter to connect distributed new energy to a power grid and form a stable local power grid without external synchronization signals.

[0003] In the process of connecting distributed new energy (such as solar photovoltaic energy and wind energy) to the power grid, the distributed new energy converts natural energy (such as light energy and wind energy) into electric energy. When the weather changes, the electric energy connected to the power grid will have a serious fluctuating load, and when the load is too large, it will cause a short circuit in the power grid. Therefore, a method for solving short-circuit abnormality in grid-forming control is needed to solve the above problems. SUMMARY

[0004] The present application aims to provide a method and system for solving short-circuit abnormality in grid-forming control to solve the technical problems in the background.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0006] A method for solving short-circuit abnormality in grid-forming control, comprising:

[0007] Obtaining node access information of distributed new energy and a power grid node, wherein the node access information includes node current information, node frequency information and node harmonic information;

[0008] According to the node current information, the current amplitude and the current phase are obtained, the current waveform diagram is obtained according to the current amplitude and the current phase, and a plurality of current peak values within a preset time are obtained according to the current waveform diagram, and a current surge value is obtained according to a plurality of current peak values;

[0009] Obtaining the fluctuating frequency of the power grid node within a preset time, and obtaining the load change rate of the power grid node according to the fluctuating frequency, and obtaining the fluctuating difference value of the power grid node according to the load change rate of the power grid node and the preset normal change rate;

[0010] According to the node harmonic information, a plurality of nonlinear load harmonic values within a preset time are obtained, and a plurality of harmonic high-frequency component values are obtained by comparing a plurality of nonlinear load harmonic values with a preset fundamental wave value in integer multiple, and a harmonic increment value is obtained according to a plurality of harmonic high-frequency component values;

[0011] According to the current surge value, the fluctuating difference value of the power grid node and the harmonic increment value, the fluctuating load value is calculated;

[0012] determining whether the fluctuation load value is greater than a preset threshold value;

[0013] When the fluctuation load value is greater than the preset threshold value, it is determined that the connection of the distributed new energy and the grid node has a short-circuit risk, and a danger warning instruction is generated. The target node is found according to the fluctuation load value, and the distributed new energy is connected with the target node.

[0014] Preferably, the step of obtaining the current surge value according to the plurality of current peak values comprises:

[0015] The plurality of current peak values are compared with a preset standard peak value to obtain a plurality of abnormal current peak values.

[0016] The corresponding abnormal times are obtained according to the plurality of abnormal current peak values.

[0017] The plurality of abnormal current difference values are obtained by sequentially calculating the difference between the plurality of abnormal current peak values and the preset standard peak value.

[0018] The current surge value is calculated according to the abnormal times and the plurality of abnormal current difference values, and the calculation formula is:

[0019]

[0020] Wherein, J(Z) represents the current surge value, j(l) represents the abnormal current difference value, wherein C represents the abnormal times, C = 1, 2, 3...n.

[0021] Preferably, the step of obtaining the grid load change rate according to the fluctuation frequency comprises:

[0022] The node load of the grid node is obtained, wherein the node load includes the active node load value and the reactive node load value.

[0023] The load influence coefficient is calculated according to the active node load value and the reactive node load value, and the calculation formula is:

[0024]

[0025] Wherein, X(s) represents the load influence coefficient, F(y) represents the active node load value, F(e) represents the reactive node load value, and θ represents the load error coefficient.

[0026] The fluctuation time of the fluctuation frequency falling back to the preset reference fluctuation frequency within a preset time is obtained, and the grid load change rate is calculated according to the fluctuation frequency, the preset reference fluctuation frequency, the fluctuation time and the load influence coefficient, and the calculation formula is:

[0027]

[0028] Wherein, S(L) represents the grid load change rate, b(d) represents the fluctuation frequency, j(b) represents the preset reference fluctuation frequency, T represents the fluctuation time, and X(s) represents the load influence coefficient.

[0029] Preferably, the step of comparing the plurality of nonlinear load harmonic values with the preset fundamental harmonic value by an integer multiple, obtaining a plurality of harmonic high-frequency component values, and acquiring a harmonic increment value according to the plurality of harmonic high-frequency component values comprises:

[0030] sequentially determining whether the plurality of nonlinear load harmonic values are integer multiples of the preset fundamental harmonic value;

[0031] If the nonlinear load harmonic value is an integer multiple of the preset fundamental harmonic value, the plurality of nonlinear load harmonic values are taken as the plurality of harmonic high-frequency component values;

[0032] The plurality of harmonic high-frequency component values are sequentially grouped according to time sequence to obtain a plurality of harmonic high-frequency component groups;

[0033] The two harmonic high-frequency component values of the plurality of harmonic high-frequency component groups are subjected to difference calculation to obtain a plurality of harmonic high-frequency component differences;

[0034] The plurality of harmonic high-frequency component differences are summed to obtain a harmonic increment value, wherein the calculation formula is:

[0035]

[0036] Wherein, X(B) represents the harmonic increment value, and F(l) represents the harmonic high-frequency component difference, wherein i represents the number of harmonic high-frequency component differences, i = 1, 2, 3...k.

[0037] Preferably, the step of calculating the fluctuation load value according to the current surge value, the grid node fluctuation difference value, and the harmonic increment value comprises:

[0038] According to the current surge value, a corresponding first weight value is obtained;

[0039] According to the grid node fluctuation difference value, a corresponding second weight value is obtained;

[0040] According to the current surge value, the grid node fluctuation difference value, the harmonic increment value, the first weight value, and the second weight value, a comprehensive abnormal value is calculated, wherein the calculation formula is:

[0041] z(h) = [J(z)*a + F(h)*b + X(b)*(1-a-b)];

[0042] Wherein, z(h) represents a comprehensive abnormal value, J(z) represents a current surge value, F(h) represents a power grid node fluctuation difference value, X(b) represents a harmonic increment value, a represents a first weight value, and b represents a second weight value.

[0043] The comprehensive abnormal value is taken as a fluctuation load value.

[0044] As preferred, the step of searching a target node according to the fluctuation load value and controlling the distributed new energy to be connected with the target node further comprises:

[0045] A bearing fluctuation load threshold of each of the plurality of power grid nodes is acquired.

[0046] A current power grid node corresponding to the fluctuation load value is acquired, and a plurality of transmission distances from the current power grid node to the plurality of power grid nodes are acquired, and a transmission distance table is established according to the plurality of transmission distances.

[0047] The fluctuation load value is iteratively matched with the plurality of bearing fluctuation load thresholds based on a similarity model to obtain a plurality of load similarity values, wherein a function of the similarity model is:

[0048]

[0049] Wherein, represents the gth to pth load similarity value, z(h) represents the fluctuation load value, Y(S) g represents the gth bearing fluctuation load threshold, Y(S) p represents the pth bearing fluctuation load threshold.

[0050] A plurality of matching docking nodes corresponding to the plurality of load similarity values are acquired.

[0051] The plurality of matching docking nodes are screened according to the transmission distance table to obtain a matching docking node with a shortest transmission distance, and the matching docking node with the shortest transmission distance is taken as a target node, and the distributed new energy is controlled to be connected with the target node.

[0052] The application further provides a network-constructing type control short-circuit abnormality solving system, comprising:

[0053] A first acquisition module is configured to acquire node access information of a distributed new energy and a power grid node, wherein the node access information comprises node current information, node frequency information and node harmonic information.

[0054] a second obtaining module, configured to obtain a current amplitude and a current phase according to the node current information, obtain a current waveform diagram according to the current amplitude and the current phase, obtain a plurality of current peak values within a preset time according to the current waveform diagram, and obtain a current surge value according to the plurality of current peak values;

[0055] a third obtaining module, configured to obtain a fluctuation frequency of the power grid node within a preset time, obtain a power grid node load change rate according to the fluctuation frequency, and obtain a power grid node fluctuation difference value according to the power grid node load change rate and a preset normal change rate;

[0056] a fourth obtaining module, configured to obtain a plurality of nonlinear load harmonic values within a preset time according to the node harmonic information, compare the plurality of nonlinear load harmonic values with a preset fundamental wave value in an integer multiple manner to obtain a plurality of harmonic high-frequency component values, and obtain a harmonic increment value according to the plurality of harmonic high-frequency component values;

[0057] a first calculating module, configured to calculate a fluctuation load value according to the current surge value, the power grid node fluctuation difference value, and the harmonic increment value;

[0058] a first judging module, configured to judge whether the fluctuation load value is greater than a preset threshold value;

[0059] if the fluctuation load value is greater than the preset threshold value, it is determined that the connection of the distributed new energy and the power grid node has a short-circuit risk, a danger reminding instruction is generated, a target node is found according to the fluctuation load value, and the distributed new energy is connected with the target node.

[0060] Preferably, the second obtaining module comprises:

[0061] the plurality of current peak values are compared with a preset standard peak value to obtain a plurality of abnormal current peak values;

[0062] a corresponding abnormal number of times is obtained according to the plurality of abnormal current peak values;

[0063] a plurality of abnormal current difference values are obtained by sequentially performing difference calculation on the plurality of abnormal current peak values and the preset standard peak value;

[0064] the current surge value is calculated according to the abnormal number of times and the plurality of abnormal current difference values, and the calculation formula is:

[0065]

[0066] wherein, J(Z) represents the current surge value, j(l) represents the abnormal current difference value, C represents the abnormal number of times, and C = 1, 2, 3,..., n.

[0067] The application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method when executing the computer program.

[0068] The application further provides a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the method when executed by a processor.

[0069] The application has the beneficial effects that: the application first acquires node access information of a distributed new energy and a power grid node, wherein the node access information comprises node current information, node frequency information and node harmonic information, then acquires a current surge value according to the node current information, next acquires a power grid node fluctuation difference value according to the node frequency information, then acquires a harmonic increment value according to the node harmonic information, finally, calculates a fluctuation load value according to the current surge value, the power grid node fluctuation difference value and the harmonic increment value, next, judges whether the fluctuation load value is greater than a preset threshold value, and the fluctuation load value is greater than the preset threshold value, so that it is determined that the connection of the distributed new energy and the power grid node has a short circuit risk, the target node is found according to the fluctuation load value, and the distributed new energy is connected with the target node, so that whether the power grid node can bear the fluctuation load generated by the distributed new energy caused by weather influence is judged in advance, and then the position of the power grid node access can be paired in advance, so that the problem that the load is too large to cause a short circuit of the power grid can be avoided. BRIEF DESCRIPTION OF DRAWINGS

[0070] Fig. 1 It is a method flowchart of an embodiment of the application.

[0071] Fig. 2 It is a system structure schematic diagram of an embodiment of the application.

[0072] Fig. 3 It is an internal structure schematic diagram of a computer device of an embodiment of the application.

[0073] The implementation, functional features and advantages of the application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0074] It should be understood that the specific embodiments described herein are only used to explain the application, and are not used to limit the application.

[0075] As shown in the drawings, Figs. 1-3 The application provides a network construction type control short circuit exception solving method, which comprises:

[0076] S1, acquiring node access information of a distributed new energy and a power grid node, wherein the node access information comprises node current information, node frequency information and node harmonic information;

[0077] S2, obtain a current amplitude and a current phase according to the node current information, obtain a current waveform diagram according to the current amplitude and the current phase, obtain a plurality of current peak values within a preset time according to the current waveform diagram, and obtain a current surge value according to the plurality of current peak values;

[0078] S3, obtain a fluctuation frequency of a power grid node within a preset time, obtain a power grid node load change rate according to the fluctuation frequency, and obtain a power grid node fluctuation difference value according to the power grid node load change rate and a preset normal change rate;

[0079] S4, obtain a plurality of nonlinear load harmonic values within a preset time according to the node harmonic information, compare the plurality of nonlinear load harmonic values with a preset fundamental wave value by an integer multiple, obtain a plurality of harmonic high-frequency component values, and obtain a harmonic increment value according to the plurality of harmonic high-frequency component values;

[0080] S5, calculate a fluctuation load value according to the current surge value, the power grid node fluctuation difference value, and the harmonic increment value;

[0081] S6, determine whether the fluctuation load value is greater than a preset threshold value;

[0082] When the fluctuation load value is greater than the preset threshold value, it is determined that there is a short-circuit risk in the connection of the distributed new energy and the power grid node, a danger reminding instruction is generated, a target node is found according to the fluctuation load value, and the distributed new energy is connected with the target node.

[0083] In the process of connecting distributed new energy (such as solar photovoltaic, wind energy, etc.) to the power grid, the natural energy (light energy and wind energy, etc.) is converted into electric energy by the distributed new energy. When the weather is affected, the load fluctuation of the electric energy connected to the power grid is serious, and the power grid may be short-circuited when the load is too large. Therefore, it is necessary to detect in advance whether the connected power grid node can withstand the load fluctuation when the distributed new energy is connected. On this basis, the node access information of the distributed new energy and the power grid node is obtained, wherein the node access information includes node current information, node frequency information and node harmonic information. The power grid node is the entrance of the power grid and the distributed new energy, and plays a role in electric energy connection. The node current information, node frequency information and node harmonic information can provide comprehensive data support for fluctuation load analysis, and can also comprehensively judge the state of the node through various data to provide a basis for subsequent calculation of fluctuation load value. Then, the current amplitude and current phase are obtained according to the node current information. The fluctuation characteristics of the current can be understood through the current amplitude and current phase. The current waveform diagram is obtained according to the current amplitude and current phase. The change of the current can be intuitively displayed through the current waveform diagram. A plurality of current peak values in a preset time are obtained according to the current waveform diagram. The current surge value is obtained according to a plurality of current peak values. After calculating the current surge value, the transient change of the current can be evaluated through the current surge value, the potential short-circuit risk can be identified, and the current surge value can be used as one of the factors for evaluating the short-circuit risk. Then, the fluctuation frequency of the power grid node in a preset time is obtained. The frequency stability of the power grid node can be analyzed through the fluctuation frequency. The frequency stability of the power grid is also one of the factors for judging whether the power grid node has a short-circuit risk. Since the load bearing capacity of the power grid node has a rated upper limit, and the load change rate can reflect the dynamic change of the load of the power grid node, the load change rate of the power grid node can be obtained according to the fluctuation frequency. The fluctuation difference value of the power grid node is obtained according to the load change rate of the power grid node and the preset normal change rate. The fluctuation difference value of the power grid node can evaluate whether the load change of the power grid exceeds the normal range. When the load change exceeds the preset range, the power grid has a certain short-circuit risk. Therefore, the fluctuation difference value of the power grid node is also one of the factors for judging whether the power grid has a short-circuit risk. Since the harmonic content in the power grid node determines whether the power grid is polluted by harmonics, the power grid polluted by harmonics has a short-circuit risk. Then, a plurality of nonlinear load harmonic values in a preset time are obtained according to the node harmonic information. Since the nonlinear load harmonic value less than an integer multiple of the preset fundamental value has little effect on the power grid node, the plurality of nonlinear load harmonic values are compared with the integer multiple of the preset fundamental value to obtain a plurality of harmonic high-frequency component values. The harmonic increment value is obtained according to a plurality of harmonic high-frequency component values. The harmonic increment value can accurately judge whether the power grid node is polluted.Thus, the harmonic increment value can be used as one of the factors to determine whether the power grid node is short-circuited. Then, the fluctuation load value is calculated according to the current surge value, the power grid node fluctuation difference value and the harmonic increment value. The calculated fluctuation load value can comprehensively and comprehensively evaluate the fluctuation load condition of the power grid node. Then, it is determined whether the fluctuation load value is greater than the preset threshold value. If the fluctuation load value is greater than the preset threshold value, it is determined that the connection of the distributed new energy and the power grid node has a short-circuit risk. The target node is found according to the fluctuation load value, and the distributed new energy is connected with the target node. In this way, it can be determined in advance whether the power grid node can withstand the fluctuation load caused by the distributed new energy due to weather influence, and then the position of the power grid node connected can be matched in advance, so that the problem of short circuit caused by excessive load on the power grid can be avoided.

[0084] In one embodiment, the step S2 of obtaining the current surge value according to the plurality of current peak values comprises:

[0085] S201, comparing the plurality of current peak values with a preset standard peak value to obtain a plurality of abnormal current peak values;

[0086] S202, obtaining a corresponding abnormal number according to a plurality of abnormal current peak values;

[0087] S203, sequentially calculating the difference value of the plurality of abnormal current peak values and the preset standard peak value to obtain a plurality of abnormal current difference values;

[0088] S204, calculating the current surge value according to the abnormal number and the plurality of abnormal current difference values, wherein the calculation formula is:

[0089]

[0090] Wherein, J(Z) represents the current surge value, j(l) represents the abnormal current difference value, wherein C represents the abnormal number, C=1, 2, 3...n.

[0091] As described in steps S201-S204, since the current surge value is an important indicator for evaluating whether the power grid node has a short circuit risk, based on this, the application first compares the plurality of current peak values with the preset standard peak value to obtain a plurality of abnormal current peak values. In this way, by comparing, it is identified which current peak values exceed the preset standard peak value, and these peak values are considered to be abnormal current peak values. At the same time, screening out abnormal current peak values can provide a data basis for further analysis. Then, according to the plurality of abnormal current peak values, the corresponding abnormal times are obtained. Through the abnormal times, the frequency of current fluctuation can be preliminarily evaluated, which provides a basis for the calculation of the current surge value. Then, according to the plurality of abnormal current peak values, difference calculation is performed with the preset standard peak value in turn to obtain a plurality of abnormal current difference values. In this way, the plurality of abnormal current difference values obtained can quantitatively reflect the degree of each abnormality. Finally, the current surge value is calculated according to the abnormal times and the plurality of abnormal current difference values. In this way, the current surge value can be used to evaluate the transient change of the current, and the current surge value can also reflect the severity of the current fluctuation and provide a basis for subsequent short circuit judgment.

[0092] In one embodiment, the step S3 of obtaining the power grid load change rate according to the fluctuation frequency comprises:

[0093] S301, obtaining the node load of the power grid node, wherein the node load includes an active node load value and a reactive node load value;

[0094] S302, calculating a load influence coefficient according to the active node load value and the reactive node load value, wherein the calculation formula is:

[0095]

[0096] Wherein, X(s) represents the load influence coefficient, F(y) represents the active node load value, F(e) represents the reactive node load value, and θ represents the load error coefficient;

[0097] S303, obtaining the fluctuation time of the fluctuation frequency falling back to the preset reference fluctuation frequency within a preset time, and calculating the power grid load change rate according to the fluctuation frequency, the preset reference fluctuation frequency, the fluctuation time and the load influence coefficient, wherein the calculation formula is:

[0098]

[0099] Wherein, S(L) represents the power grid load change rate, b(d) represents the fluctuation frequency, j(b) represents the preset reference fluctuation frequency, T represents the fluctuation time, and X(s) represents the load influence coefficient.

[0100] As described in steps S301-S303, the application first acquires the node load of the power grid node, wherein the node load includes the active node load value and the reactive node load value, so that the load characteristics can be comprehensively understood, ensuring the completeness and accuracy of the data, then the load influence coefficient is calculated according to the active node load value and the reactive node load value, so that the degree of change of the current load relative to the baseline load can be understood, and important support is provided for the subsequent calculation of the power grid load change rate, then the fluctuation time in which the fluctuation frequency falls back to the preset reference fluctuation frequency within the preset time is acquired, and the power grid load change rate is calculated according to the fluctuation frequency, the preset reference fluctuation frequency, the fluctuation time and the load influence coefficient, for example: the active node load value is 100kw, the reactive node load value is 60kw, the load error coefficient is 0.05, the fluctuation frequency is 50.2Hz, the preset reference fluctuation frequency is 50Hz, and the fluctuation time is 2s, In this way, the dynamic response and stability of the power grid node can be known through the power grid load change rate, and a basis is provided for short-circuit judgment.

[0101] In one embodiment, the step S4 of comparing the plurality of non-linear load harmonic values with the preset fundamental wave value by an integer multiple to obtain a plurality of harmonic high-frequency component values, and acquiring a harmonic increment value according to the plurality of harmonic high-frequency component values, comprises:

[0102] S401, sequentially judging whether the plurality of non-linear load harmonic values are integer multiples of the preset fundamental wave value;

[0103] If the non-linear load harmonic value is an integer multiple of the preset fundamental wave value, the plurality of non-linear load harmonic values are taken as the plurality of harmonic high-frequency component values;

[0104] S402, grouping the plurality of harmonic high-frequency component values according to time sequence to obtain a plurality of harmonic high-frequency component groups;

[0105] S403, calculating the difference value of two harmonic high-frequency component values of the plurality of harmonic high-frequency component groups to obtain a plurality of harmonic high-frequency component difference values;

[0106] S404, summing the plurality of harmonic high-frequency component difference values to obtain a harmonic increment value, wherein the calculation formula is:

[0107]

[0108] Wherein, X(B) represents the harmonic increment value, F(l) represents the harmonic high-frequency component difference value, wherein i represents the number of harmonic high-frequency component difference values, i=1, 2, 3...k.

[0109] As described in steps S401-S404, since the harmonic affecting the short circuit of the power grid node must be an integer multiple of the preset fundamental value, based on this, the application needs to first judge whether the harmonic value of the nonlinear load is an integer multiple of the preset fundamental value, if the harmonic value of the nonlinear load is an integer multiple of the preset fundamental value, the harmonic value of the nonlinear load is taken as a plurality of harmonic high frequency component values, so that the content of the harmonic in the power grid node can be judged through the plurality of harmonic high frequency component values, and the basis for judging whether the power grid node is short-circuited is provided, then the difference value of the two harmonic high frequency component values of the plurality of harmonic high frequency component groups is calculated, the harmonic high frequency component difference value is obtained, then the harmonic high frequency component difference value is summed, the harmonic increment value is obtained, so that the severity of the harmonic change can be evaluated through the harmonic increment value, which is helpful to identify the potential risk in the power grid node, and to provide risk avoidance for the short circuit of the power grid node.

[0110] In one embodiment, the step S5 of calculating the fluctuation load value according to the current surge value, the power grid node fluctuation difference value and the harmonic increment value comprises:

[0111] S501, obtaining a corresponding first weight value according to the current surge value;

[0112] S502, obtaining a corresponding second weight value according to the power grid node fluctuation difference value;

[0113] S503, calculating a comprehensive abnormal value according to the current surge value, the power grid node fluctuation difference value, the harmonic increment value, the first weight value and the second weight value, wherein the calculation formula is:

[0114] z(h)=[J(Z)*a+F(H)*b+X(B)*(1-a-b)];

[0115] Wherein, z(h) represents the comprehensive abnormal value, J(Z) represents the current surge value, F(H) represents the power grid node fluctuation difference value, X(B) represents the harmonic increment value, a represents the first weight value, and b represents the second weight value;

[0116] Taking the comprehensive abnormal value as the fluctuation load value.

[0117] As described in steps S501-S503, since the transient abnormality in the power grid can be found in time by monitoring the current surge value, the load change of the power grid node can be evaluated whether it is beyond the normal range by calculating the power grid node fluctuation difference value, the potential risk point is identified, and the harmonic pollution degree of the power grid node can be evaluated by calculating the harmonic increment value, the influence of the harmonic on the power grid is identified, on this basis, the first weight value corresponding to the current surge value is obtained, then the second weight value corresponding to the power grid node fluctuation difference value is obtained, and then the comprehensive abnormal value is calculated according to the current surge value, the power grid node fluctuation difference value, the harmonic increment value, the first weight value and the second weight value, so that the overall fluctuation load condition of the power grid node can be comprehensively evaluated by the comprehensive abnormal value, which provides a basis for identifying potential short-circuit risks, and then whether the power grid node can withstand the fluctuation load caused by the weather influence of the distributed new energy is judged in advance, and then the position of the power grid node access can be paired in advance, so that the problem of short circuit caused by too large load to the power grid can be avoided.

[0118] In one embodiment, the step S6 of searching for a target node according to the fluctuation load value and controlling the distributed new energy to be connected with the target node further comprises:

[0119] S601, obtaining a fluctuation load bearing threshold of a plurality of power grid nodes in the power grid;

[0120] S602, obtaining a current power grid node corresponding to the fluctuation load value, and obtaining a plurality of transmission distances from the current power grid node to a plurality of power grid nodes, and establishing a transmission distance table according to the plurality of transmission distances;

[0121] S603, performing traversal matching between the fluctuation load value and a plurality of fluctuation load bearing thresholds based on a similarity model to obtain a plurality of load similarity values, wherein the function of the similarity model is:

[0122]

[0123] wherein, represents the gth to the pth load similarity value, z(h) represents the fluctuation load value, Y(S) g represents the gth fluctuation load bearing threshold, Y(S) p represents the pth fluctuation load bearing threshold;

[0124] S604, obtaining a plurality of matching docking nodes corresponding to a plurality of load similarity values;

[0125] S605, screening the matching docking nodes according to the transmission distance table to obtain the matching docking node with the shortest transmission distance, taking the matching docking node with the shortest transmission distance as a target node, and connecting the distributed new energy with the target node.

[0126] As described in steps S601-S605, the application first obtains the load fluctuation threshold of multiple power grid nodes in the power grid, so that the carrying capacity of each docking node can be understood, and it can be evaluated whether they can withstand the fluctuating load caused by the access of new distributed new energy. Then, the current power grid node corresponding to the fluctuating load value is obtained, and multiple transmission distances from the current power grid node to multiple power grid nodes are obtained. According to multiple transmission distances, a transmission distance table is established, so that the distance from the risk power grid node to each docking node can be understood, providing a basis for selecting the nearest docking node. At the same time, the docking node with shorter distance can reduce transmission loss and improve transmission efficiency. Then, the fluctuating load value is iteratively matched with multiple load fluctuation threshold values based on a similarity model to obtain multiple load similarity values. Then, multiple matching docking nodes corresponding to the multiple load similarity values are obtained, so that the docking nodes that can withstand the fluctuating load of the newly accessed distributed new energy are screened out. It can be ensured that the selected docking node has sufficient carrying capacity, providing a basis for avoiding short-circuit risk. Then, the transmission distance table is used to screen multiple matching docking nodes with the shortest transmission distance, and the matching docking node with the shortest transmission distance is taken as a target node. The distributed new energy is connected with the target node. In this way, it can be determined in advance whether the power grid node can withstand the fluctuating load caused by the distributed new energy affected by the weather, and the position of the power grid node can be paired in advance, so that the problem of short circuit caused by excessive load on the power grid can be avoided.

[0127] The application also provides a network construction type control short-circuit abnormality solving system, comprising:

[0128] The first acquisition module 1 is used for acquiring node access information of distributed new energy and a power grid node, wherein the node access information comprises node current information, node frequency information and node harmonic information.

[0129] The second acquisition module 2 is used for acquiring current amplitude and current phase according to the node current information, acquiring a current waveform diagram according to the current amplitude and the current phase, acquiring multiple current peak values within a preset time according to the current waveform diagram, and acquiring a current surge value according to multiple current peak values.

[0130] The third acquisition module 3 is configured to acquire a fluctuation frequency of the power grid node within a preset time, acquire a load change rate of the power grid node according to the fluctuation frequency, and acquire a fluctuation difference value of the power grid node according to the load change rate of the power grid node and a preset normal change rate.

[0131] The fourth acquisition module 4 is configured to acquire a plurality of non-linear load harmonic values within a preset time according to the node harmonic information, compare the plurality of non-linear load harmonic values with a preset fundamental wave value by an integer multiple, obtain a plurality of harmonic high-frequency component values, and acquire a harmonic increment value according to the plurality of harmonic high-frequency component values.

[0132] The first calculation module 5 is configured to calculate a fluctuation load value according to the current surge value, the fluctuation difference value of the power grid node and the harmonic increment value.

[0133] The first judgment module 6 is configured to judge whether the fluctuation load value is greater than a preset threshold value.

[0134] When the fluctuation load value is greater than the preset threshold value, it is determined that the connection of the distributed new energy and the power grid node has a short-circuit risk, a danger reminding instruction is generated, a target node is found according to the fluctuation load value, and the distributed new energy is connected with the target node.

[0135] In an embodiment, the second acquisition module comprises:

[0136] The plurality of current peak values are compared with a preset standard peak value to obtain a plurality of abnormal current peak values.

[0137] The corresponding abnormal times are acquired according to the plurality of abnormal current peak values.

[0138] The plurality of abnormal current peak values are sequentially compared with the preset standard peak value to obtain a plurality of abnormal current difference values.

[0139] The current surge value is calculated according to the abnormal times and the plurality of abnormal current difference values, and the calculation formula is:

[0140]

[0141] Wherein, J(Z) represents the current surge value, j(l) represents the abnormal current difference value, C represents the abnormal times, and C=1, 2, 3...n.

[0142] The application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the steps of the short-circuit abnormality solving method for network-oriented control.

[0143] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiment methods can be included. Any reference to memory, storage, database or other medium provided by the present application and used in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0144] It should be noted that in this document, the terms "comprising", "including", or any other variant thereof are intended to cover a non-exclusive inclusion, such that a process, device, article or method that comprises a list of elements does not only include those elements, but can also include other elements not expressly listed or inherent to such process, device, article or method. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, device, article or method that includes the element.

[0145] The above description is only the preferred embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation, or direct or indirect application in other related technical fields, which is made according to the content of the present application specification and drawings, is also included in the patent protection scope of the present application.

Claims

1. A method for resolving short-circuit anomalies in network-type control, characterized in that, include: Obtain node access information for distributed renewable energy and grid nodes, including node current information, node frequency information, and node harmonic information; The current amplitude and current phase are obtained based on the node current information. A current waveform is obtained based on the current amplitude and current phase. Multiple current peaks within a preset time period are obtained based on the current waveform. A current surge value is obtained based on the multiple current peaks. The fluctuation frequency of the power grid node within a preset time period is obtained, and the load change rate of the power grid node is obtained based on the fluctuation frequency. The fluctuation difference of the power grid node is obtained based on the load change rate of the power grid node and the preset normal change rate. Based on the node harmonic information, multiple nonlinear load harmonic values ​​within a preset time period are obtained, and the multiple nonlinear load harmonic values ​​are compared with the preset fundamental value by integer multiples to obtain multiple harmonic high-frequency component values, and harmonic increment values ​​are obtained based on the multiple harmonic high-frequency component values. The fluctuating load value is calculated based on the current surge value, the grid node fluctuation difference, and the harmonic increment value. Determine whether the fluctuating load value is greater than a preset threshold; If the fluctuating load value is greater than a preset threshold, it is determined that there is a short circuit risk in the connection between the distributed renewable energy source and the grid node. The target node is located based on the fluctuating load value, and the connection between the distributed renewable energy source and the target node is controlled.

2. The short-circuit anomaly solution in network-type control according to claim 1, characterized in that, The step of obtaining the current surge value based on the multiple current peaks includes: The multiple current peak values ​​are compared with preset standard peak values ​​to obtain multiple abnormal current peak values; The number of abnormalities is obtained based on the multiple abnormal current peak values; Multiple abnormal current differences are obtained by sequentially calculating the difference between the multiple abnormal current peak values ​​and the preset standard peak value; The current surge value is calculated based on the number of abnormal events and the difference between multiple abnormal current values. The calculation formula is as follows: Where J(Z) represents the current surge value, j(l) represents the abnormal current difference value, and C represents the number of abnormalities, C = 1, 2, 3...n.

3. The short-circuit anomaly solution in network-type control according to claim 1, characterized in that, The step of obtaining the power grid load change rate based on the fluctuation frequency includes: The node load values ​​of the power grid nodes are obtained based on the current transformers, where the node load includes active node load values ​​and reactive node load values. The load impact coefficient is calculated based on the active node load value and the reactive node load value, wherein the calculation formula is: Where X(s) represents the load influence coefficient, F(y) represents the active node load value, F(e) represents the reactive node load value, and θ represents the load error coefficient. The fluctuation time within which the fluctuation frequency falls back to the preset reference fluctuation frequency within a preset time is obtained, and the power grid load change rate is calculated based on the fluctuation frequency, the preset reference fluctuation frequency, the fluctuation time, and the load influence coefficient. The calculation formula is as follows: Where S(L) represents the rate of change of the power grid load, b(d) represents the fluctuation frequency, j(b) represents the preset reference fluctuation frequency, T represents the fluctuation time, and X(s) represents the load influence coefficient.

4. The method for resolving short-circuit anomalies in network-type control according to claim 1, characterized in that, The step of comparing multiple nonlinear load harmonic values ​​with a preset fundamental value as integer multiples to obtain multiple high-frequency harmonic component values, and obtaining harmonic increment values ​​based on the multiple high-frequency harmonic component values, includes: Sequentially determine whether the multiple nonlinear load harmonic values ​​are integer multiples of the preset fundamental value; If the nonlinear load harmonic value is an integer multiple of the preset fundamental value, then the multiple nonlinear load harmonic values ​​are taken as multiple harmonic high-frequency component values. The multiple harmonic high-frequency component values ​​are grouped adjacently according to the time sequence to obtain multiple harmonic high-frequency component groups; The difference between two harmonic high-frequency component values ​​in the multiple harmonic high-frequency component groups is calculated to obtain the multiple harmonic high-frequency component differences; The difference between multiple high-frequency harmonic components is summed to obtain the harmonic increment value.

5. The short-circuit anomaly solution in network-type control according to claim 1, characterized in that, The step of calculating the fluctuating load value based on the current surge value, the grid node fluctuation difference, and the harmonic increment value includes: The first weight value is obtained based on the current surge value; The corresponding second weight value is obtained based on the fluctuation difference of the power grid nodes; The comprehensive anomaly value is calculated based on the current surge value, the grid node fluctuation difference, the harmonic increment value, the first weight value, and the second weight value, and the comprehensive anomaly value is used as the fluctuating load value.

6. The short-circuit anomaly solution in network-type control according to claim 1, characterized in that, The step of locating the target node based on the fluctuating load value and controlling the connection between the distributed renewable energy source and the target node further includes: Obtain the load fluctuation threshold of multiple power grid nodes in the power grid; Obtain the current power grid node corresponding to the fluctuating load value, and obtain multiple transmission distances from the current power grid node to multiple power grid nodes, and establish a transmission distance table based on the multiple transmission distances; The fluctuating load value is matched against multiple load fluctuation thresholds based on a similarity model to obtain multiple load similarity values. The function of the similarity model is: in, Let represent the load similarity values ​​from the g-th to the p-th value, z(h) represent the fluctuating load value, and Y(S) represent the load similarity values. g Y(S) represents the g-th load fluctuation threshold. p This represents the threshold value for the p-th load fluctuation. Multiple matching nodes are obtained based on the multiple load similarity values; According to the transmission distance table, the shortest transmission distance is used to filter the multiple matching docking nodes to obtain the matching docking node with the shortest transmission distance. The matching docking node with the shortest transmission distance is then used as the target node, and the distributed new energy source is controlled to connect with the target node.

7. A short-circuit anomaly resolution system in a network-type control system, characterized in that, include: The first acquisition module is used to acquire node access information of distributed new energy and grid nodes, wherein the node access information includes node current information, node frequency information and node harmonic information; The second acquisition module is used to acquire the current amplitude and current phase based on the node current information, acquire the current waveform based on the current amplitude and current phase, acquire multiple current peaks within a preset time based on the current waveform, and acquire the current surge value based on the multiple current peaks. The third acquisition module is used to acquire the fluctuation frequency of the power grid node within a preset time, acquire the load change rate of the power grid node based on the fluctuation frequency, and acquire the fluctuation difference of the power grid node based on the load change rate of the power grid node and the preset normal change rate. The fourth acquisition module is used to acquire multiple nonlinear load harmonic values ​​within a preset time period based on the node harmonic information, compare the multiple nonlinear load harmonic values ​​with the preset fundamental value by integer multiples to obtain multiple harmonic high-frequency component values, and acquire harmonic increment values ​​based on the multiple harmonic high-frequency component values. The first calculation module is used to calculate the fluctuating load value based on the current surge value, the power grid node fluctuation difference value, and the harmonic increment value. The first judgment module is used to determine whether the fluctuating load value is greater than a preset threshold. If the fluctuating load value is greater than a preset threshold, it is determined that there is a short circuit risk in the connection between the distributed renewable energy source and the grid node, and a danger warning instruction is generated. The target node is located based on the fluctuating load value, and the connection between the distributed renewable energy source and the target node is controlled.

8. A short-circuit anomaly resolution system in a network-type control system according to claim 7, characterized in that, The second acquisition module includes: The multiple current peak values ​​are compared with preset standard peak values ​​to obtain multiple abnormal current peak values; The number of abnormalities is obtained based on the multiple abnormal current peak values; Multiple abnormal current differences are obtained by sequentially calculating the difference between the multiple abnormal current peak values ​​and the preset standard peak value; The current surge value is calculated based on the number of abnormal events and the difference between multiple abnormal current values. The calculation formula is as follows: Where J(Z) represents the current surge value, j(l) represents the abnormal current difference value, and C represents the number of abnormalities, C = 1, 2, 3...n.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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