Method and system for solving short circuit abnormity in network construction type control

Abstract

The invention relates to the technical field of power grids, and particularly discloses a method and a system for solving short circuit abnormity in network construction type control. The method comprises the steps of firstly obtaining node current information, node frequency information and node harmonic information, then obtaining a current surge value according to the node current information, then obtaining a power grid node fluctuation difference value according to the node frequency information, then obtaining a harmonic increment value according to the node harmonic information, and finally obtaining a power grid node fluctuation difference value according to the harmonic increment value. Calculating a fluctuation load value according to the current surge value, the power grid node fluctuation difference value and the harmonic increment value, judging whether the fluctuation load value is greater than a preset threshold value or not, if so, judging that the connection between the distributed new energy and the power grid node has a short-circuit risk, and searching a target node according to the fluctuation load value, and the distributed new energy is controlled to be connected with the target node, and the access positions of the power grid nodes are paired in advance, so that the problem of short circuit of the power grid caused by overlarge load can be avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of power grids, and in particular to a method and system for solving short-circuit abnormalities in network-building control. Background Art

[0002] Grid-based control refers to a control strategy for power electronic converters that enables the converter to connect distributed renewable energy to the grid without an external synchronization signal and form a stable local grid.

[0003] In the process of connecting distributed new energy (such as solar photovoltaic, wind energy, etc.) to the power grid, because distributed new energy converts natural energy (light energy and wind energy, etc.) into electrical energy, when affected by the weather, the electrical energy connected to the power grid will produce serious fluctuating loads, and then cause a short circuit to the power grid when the load is too large. Therefore, a short-circuit anomaly solution in network control is needed to solve the above problem. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for solving the short-circuit abnormality problem in network-type control, so as to solve the technical problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for solving short circuit anomaly in network control, comprising:

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

[0008] Acquire a current amplitude and a current phase according to the node current information, acquire a current waveform according to the current amplitude and the current phase, acquire a plurality of current peak values ​​within a preset time according to the current waveform, and acquire a current surge value according to the plurality of current peak values;

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

[0010] Acquire multiple nonlinear load harmonic values ​​within a preset time according to 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 ​​according to the multiple harmonic high-frequency component values;

[0011] Calculate the fluctuating load value according to the current surge value, the grid node fluctuation difference and the harmonic wave increment value;

[0012] Determining whether the fluctuating load value is greater than a preset threshold;

[0013] 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 and the grid node and a danger warning instruction is generated. The target node is searched according to the fluctuating load value, and the distributed renewable energy is controlled to connect to the target node.

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

[0015] Comparing the multiple current peak values ​​with a preset standard peak value to obtain multiple abnormal current peak values;

[0016] Acquire corresponding abnormal times according to the plurality of abnormal current peak values;

[0017] Calculating the difference between the plurality of abnormal current peak values ​​and the preset standard peak values ​​in sequence to obtain a plurality of abnormal current difference values;

[0018] The current surge value is calculated according to the number of abnormalities and the difference between multiple abnormal currents, wherein the calculation formula is:

[0019]

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

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

[0022] Obtaining node loads of power grid nodes, wherein the node loads include active node load values ​​and reactive node load values;

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

[0024]

[0025] Among them, 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 when the fluctuation frequency falls back to the preset reference fluctuation frequency within the preset time is obtained, 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, wherein the calculation formula is:

[0027]

[0028] Among them, S(L) represents the grid load change rate, b(d) represents the fluctuation frequency, j(b) represents the preset benchmark 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 a preset fundamental value by integer multiples to obtain a plurality of harmonic high-frequency component values, and obtaining a harmonic increment value according to the plurality of harmonic high-frequency component values ​​comprises:

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

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

[0032] Grouping the plurality of harmonic high-frequency component values ​​adjacently according to a time series to obtain a plurality of harmonic high-frequency component groups;

[0033] Performing difference calculation on 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;

[0034] The difference values ​​of the multiple harmonic high-frequency components are summed to obtain the harmonic increment value, wherein the calculation formula is:

[0035]

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

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

[0038] Acquire a corresponding first weight value according to the current surge value;

[0039] Acquire a corresponding second weight value according to the power grid node fluctuation difference;

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

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

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

[0043] The comprehensive abnormal value is taken as the fluctuating load value.

[0044] Preferably, the step of searching for a target node according to the fluctuating load value and controlling the connection between the distributed new energy and the target node further includes:

[0045] Obtaining a load fluctuation threshold value of a plurality of grid nodes in the grid;

[0046] Acquire a current grid node corresponding to the fluctuating load value, and acquire multiple transmission distances from the current grid node to multiple grid nodes, and establish a transmission distance table according to the multiple transmission distances;

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

[0048]

[0049] in, represents the load similarity value from the gth to the pth, z(h) represents the fluctuating load value, and Y(S) g represents the g-th load fluctuation threshold, Y(S) p represents the pth load fluctuation threshold;

[0050] Acquire a corresponding plurality of matching docking nodes according to a plurality of the load similarity values;

[0051] According to the transmission distance table, the shortest transmission distance is screened for multiple matching docking nodes to obtain the matching docking node with the shortest transmission distance, and the matching docking node with the shortest transmission distance is used as the target node, and the distributed new energy is controlled to connect with the target node.

[0052] The present invention also provides a short circuit abnormality solution system in a networked control, comprising:

[0053] The first acquisition module is used to acquire node access information of distributed new energy and power grid nodes, wherein the node access information includes node current information, node frequency information and node harmonic information;

[0054] A second acquisition module is used to acquire a current amplitude and a current phase according to the node current information, acquire a current waveform according to the current amplitude and the current phase, acquire a plurality of current peak values ​​within a preset time according to the current waveform, and acquire a current surge value according to the plurality of current peak values;

[0055] A third acquisition module is used to acquire the fluctuation frequency of the power grid node within a preset time, and acquire the load change rate of the power grid node according to the fluctuation frequency, and acquire the power grid node fluctuation difference according to the load change rate of the power grid node and a preset normal change rate;

[0056] A fourth acquisition module is used to acquire a plurality of nonlinear load harmonic values ​​within a preset time according to the node harmonic information, and compare the plurality of nonlinear load harmonic values ​​with a preset fundamental value by integer multiples to 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;

[0057] A first calculation module, used for calculating a fluctuating load value according to the current surge value, the grid node fluctuation difference and the harmonic wave increment value;

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

[0059] 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 and the grid node and a danger warning instruction is generated. The target node is searched according to the fluctuating load value, and the distributed renewable energy is controlled to connect to the target node.

[0060] Preferably, the second acquisition module includes:

[0061] Comparing the multiple current peak values ​​with a preset standard peak value to obtain multiple abnormal current peak values;

[0062] Acquire corresponding abnormal times according to the plurality of abnormal current peak values;

[0063] Calculating the difference between the plurality of abnormal current peak values ​​and the preset standard peak values ​​in sequence to obtain a plurality of abnormal current difference values;

[0064] The current surge value is calculated according to the number of abnormalities and the difference between multiple abnormal currents, wherein the calculation formula is:

[0065]

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

[0067] The present invention also 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 above method when executing the computer program.

[0068] The present invention also provides a computer-readable storage medium on which a computer program is stored, and the computer program implements the steps of the above method when executed by a processor.

[0069] The beneficial effects of the present invention are as follows: the present invention first obtains node access information of distributed new energy and power grid nodes, wherein the node access information includes node current information, node frequency information and node harmonic information, and then obtains the current surge value according to the node current information, and then obtains the power grid node fluctuation difference according to the node frequency information, and then obtains the harmonic increment value according to the node harmonic information, and finally, calculates the fluctuating load value according to the current surge value, the power grid node fluctuation difference and the harmonic increment value, and then judges whether the fluctuating load value is greater than a preset threshold value. If the fluctuating load value is greater than the preset threshold value, it is determined that there is a short-circuit risk in the connection between the distributed new energy and the power grid node, and searches for the target node according to the fluctuating load value, and controls the connection between the distributed new energy and the target node. In this way, by judging in advance whether the power grid node can withstand the fluctuating load generated by the distributed new energy caused by the weather, the access location of the power grid node can be paired in advance, thereby avoiding the problem of short circuit caused by excessive load on the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 The figure is a schematic diagram of a method flow according to an embodiment of the present invention.

[0071] Figure 2 FIG. 1 is a schematic diagram of a system structure according to an embodiment of the present invention.

[0072] Figure 3 The figure is a schematic diagram of the internal structure of a computer device according to an embodiment of the present invention.

[0073] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

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

[0075] like Figure 1-3 As shown, the present invention provides a solution to short circuit anomaly in network control, including:

[0076] S1. Obtain node access information of distributed new energy and power grid nodes, wherein the node access information includes node current information, node frequency information and node harmonic information;

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

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

[0079] S4. Acquire multiple nonlinear load harmonic values ​​within a preset time according to the node harmonic information, compare the multiple nonlinear load harmonic values ​​with a preset fundamental value by integer multiples to obtain multiple harmonic high-frequency component values, and acquire a harmonic increment value according to the multiple harmonic high-frequency component values;

[0080] S5, calculating the fluctuating load value according to the current surge value, the grid node fluctuation difference and the harmonic wave increment value;

[0081] S6. Determine whether the fluctuating load value is greater than a preset threshold;

[0082] 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 and the grid node and a danger warning instruction is generated. The target node is searched according to the fluctuating load value, and the distributed renewable energy is controlled to connect to the target node.

[0083] As described in the above steps S1-S6, in the process of connecting distributed new energy (such as solar photovoltaic, wind energy, etc.) to the power grid, because distributed new energy converts natural energy (light energy and wind energy, etc.) into electrical energy, when affected by the weather, the electrical energy connected to the power grid will produce serious fluctuating loads, and then cause a short circuit to the power grid when the load is too large. Therefore, it is necessary to detect in advance whether the connected power grid node can withstand the fluctuating load 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 first obtained, wherein the node access information includes node current information, node frequency information and node harmonic information, and the power grid node is the entrance for connecting the power grid with the distributed new energy, and plays the role of receiving electric energy. In this way, The node current information, node frequency information and node harmonic information can provide comprehensive data support for the fluctuating load analysis, and can also comprehensively judge the state of the node through various data to provide a basis for the subsequent calculation of the fluctuating load value, and then obtain the current amplitude and current phase according to the node current information, so that the current fluctuation characteristics can be understood through the current amplitude and current phase, and the current waveform can be obtained according to the current amplitude and current phase. The current change can be intuitively displayed through the current waveform, and multiple current peak values ​​within a preset time can be obtained according to the current waveform, and the current surge value can be obtained according to the multiple current peak values. After calculating the current surge value, the transient change of the current can be evaluated through the current surge value. It can identify potential short-circuit risks and use the current surge value as one of the factors for evaluating short-circuit risks. It then obtains the fluctuation frequency of the power grid node within a preset time. 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 there is a short-circuit risk at the power grid node. Since the load carried by the power grid node has a rated upper limit, and the load change rate can reflect the dynamic changes of the load at the power grid node, the load change rate of the power grid node can be obtained according to the fluctuation frequency, and the power grid node fluctuation difference can be obtained according to the power grid node load change rate and the preset normal change rate. The power grid node fluctuation difference can evaluate whether the load change of the power grid exceeds the normal range. When the load change exceeds the normal range, the load change rate can be used to evaluate whether the load change of the power grid exceeds the normal range. After the preset range, the power grid will have a certain short-circuit risk. Therefore, the power grid node fluctuation difference is also one of the factors for judging whether the power grid has a short-circuit risk. The harmonic content in the power grid node determines whether the power grid has harmonic pollution, and the power grid polluted by harmonics has a short-circuit risk. Then, multiple nonlinear load harmonic values ​​within a preset time are obtained according to the node harmonic information. Since the nonlinear load harmonic value is less than an integer multiple of the preset fundamental value, it has little effect on the power grid node. Therefore, it is necessary to compare the multiple nonlinear load harmonic values ​​with the preset fundamental value by integer multiples to obtain multiple harmonic high-frequency component values, and obtain the harmonic increment value according to the multiple harmonic high-frequency component values. In this way, the harmonic increment value can be used to accurately judge whether the power grid node is polluted.Therefore, the harmonic increment value can be used as one of the factors to determine whether there is a short circuit in the power grid node. Then, the fluctuating load value is calculated according to the current surge value, the power grid node fluctuation difference and the harmonic increment value. The fluctuating load value calculated in this way can comprehensively and comprehensively evaluate the fluctuating load situation of the power grid node, and then determine whether the fluctuating load value is greater than the preset threshold. If the fluctuating load value is greater than the preset threshold, it is determined that there is a short circuit risk in the connection between the distributed new energy and the power grid node. The target node is found according to the fluctuating load value, and the distributed new energy is controlled to connect with the target node. In this way, by judging in advance whether the power grid node can withstand the fluctuating load generated by the distributed new energy caused by the weather, the access location of the power grid node can be paired in advance, thereby avoiding the problem of short circuit caused by excessive load on the power grid.

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

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

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

[0087] S203, calculating the difference between the plurality of abnormal current peak values ​​and the preset standard peak values ​​in sequence to obtain a plurality of abnormal current difference values;

[0088] S204, calculating the current surge value according to the number of abnormalities and the multiple abnormal current differences, wherein the calculation formula is:

[0089]

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

[0091] As described in the above steps S201-S204, since the current surge value is an important indicator for evaluating whether there is a short circuit risk at a power grid node, based on this, the present invention first compares the multiple current peaks with the preset standard peaks to obtain multiple abnormal current peaks. By comparing, it is possible to identify which current peaks exceed the preset standard peaks. These peaks are considered to be abnormal current peaks. At the same time, the abnormal current peaks are screened out, which can provide a data basis for further analysis. Then, the corresponding abnormal times are obtained according to the multiple abnormal current peaks. According to the abnormal times, the frequency of current fluctuations can be preliminarily evaluated, providing a basis for the subsequent calculation of current surge values. Then, the difference between the multiple abnormal current peaks and the preset standard peaks is calculated in turn to obtain multiple abnormal current differences. The multiple abnormal current differences obtained in this way can quantitatively reflect the degree of each abnormality. Finally, the current surge value is calculated according to the abnormal times and the multiple abnormal current differences. In this way, the transient change of the current can be evaluated through the current surge value. At the same time, 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 acquiring the grid load change rate according to the fluctuation frequency includes:

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

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

[0095]

[0096] Among them, 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 when the fluctuation frequency falls back to the preset reference fluctuation frequency within the preset time, and calculating the 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] Among them, S(L) represents the grid load change rate, b(d) represents the fluctuation frequency, j(b) represents the preset benchmark fluctuation frequency, T represents the fluctuation time, and X(s) represents the load influence coefficient.

[0100] As described in the above steps S301-S303, the present invention first obtains the node load of the power grid node, wherein the node load includes an active node load value and a reactive node load value, so that the load characteristics can be fully understood and the integrity and accuracy of the data can be ensured. 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 of the fluctuation frequency falling back to the preset reference fluctuation frequency within the preset time is obtained, 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 grid nodes can be known through the grid load change rate, and provide a basis for short-circuit judgment.

[0102] In one embodiment, the step S4 of comparing the plurality of nonlinear load harmonic values ​​with a preset fundamental value by integer multiples to obtain a plurality of harmonic high-frequency component values, and obtaining harmonic increment values ​​according to the plurality of harmonic high-frequency component values ​​comprises:

[0103] S401, determining in sequence whether a plurality of harmonic values ​​of the nonlinear loads are integer multiples of a preset fundamental value;

[0104] If the nonlinear load harmonic value is an integer multiple of the preset fundamental value, then a plurality of the nonlinear load harmonic values ​​are used as a plurality of harmonic high-frequency component values;

[0105] S402, grouping the plurality of harmonic high-frequency component values ​​adjacently according to a time series to obtain a plurality of harmonic high-frequency component groups;

[0106] S403, performing difference calculation on 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;

[0107] S404, summing up the difference values ​​of the multiple harmonic high-frequency components to obtain a harmonic increment value, wherein the calculation formula is:

[0108]

[0109] Among them, X(B) represents the harmonic increment value, F(l) represents the harmonic high-frequency component difference, and i represents the number of harmonic high-frequency component differences, i=1, 2, 3...k.

[0110] As described in the above steps S401-S404, since the harmonics that cause short-circuit effects on power grid nodes must be integer multiples of preset fundamental values, based on this, the present invention needs to first determine in turn whether the multiple nonlinear load harmonic values ​​are integer multiples of preset fundamental values. If the nonlinear load harmonic value is an integer multiple of the preset fundamental value, the multiple nonlinear load harmonic values ​​are used as multiple harmonic high-frequency component values. In this way, the content of harmonics in the power grid node can be determined by the multiple harmonic high-frequency component values, and a basis is provided for determining whether the power grid node is short-circuited. Subsequently, the difference between two harmonic high-frequency component values ​​of the multiple harmonic high-frequency component groups is calculated to obtain multiple harmonic high-frequency component differences, and then the multiple harmonic high-frequency component differences are summed to obtain a harmonic increment value. In this way, the severity of harmonic changes can be evaluated by the harmonic increment value, which is beneficial to identifying potential risks in power grid nodes and providing risk avoidance for power grid node short circuits.

[0111] In one embodiment, the step S5 of calculating the fluctuating load value according to the current surge value, the grid node fluctuation difference and the harmonic wave increment value comprises:

[0112] S501, obtaining a corresponding first weight value according to the current surge value;

[0113] S502, obtaining a corresponding second weight value according to the power grid node fluctuation difference;

[0114] S503, calculating a comprehensive abnormal value according to the current surge value, the grid node fluctuation difference, the harmonic increment value, the first weight value and the second weight value, wherein the calculation formula is:

[0115] z(h)=[J(Z)*a+F(H)*b+X(B)*(1-ab)];

[0116] Wherein, z(h) represents the comprehensive abnormal value, J(Z) represents the current surge value, F(H) represents the grid node fluctuation difference, X(B) represents the harmonic increment value, a represents the first weight value, and b represents the second weight value;

[0117] The comprehensive abnormal value is taken as the fluctuating load value.

[0118] As described in the above steps S501-S503, by monitoring the current surge value, transient anomalies in the power grid can be discovered in time, and by calculating the fluctuation difference of the power grid node, it is possible to evaluate whether the load change of the power grid node exceeds the normal range and identify potential risk points. By calculating the harmonic increment value, the harmonic pollution degree of the power grid node can be evaluated and the impact of harmonics on the power grid can be identified. On this basis, the present invention first obtains the corresponding first weight value according to the current surge value, and then obtains the corresponding second weight value according to the power grid node fluctuation difference, and then calculates the comprehensive abnormal value according to the current surge value, the power grid node fluctuation difference, the harmonic increment value, the first weight value and the second weight value. In this way, the overall fluctuating load of the power grid node can be comprehensively evaluated through the comprehensive abnormal value, which provides a basis for identifying potential short-circuit risks, and then by judging in advance whether the power grid node can withstand the fluctuating load generated by the distributed new energy caused by the weather, the access location of the power grid node can be paired in advance, thereby avoiding the problem of short circuit caused by excessive load on the power grid.

[0119] In one embodiment, the step S6 of searching for a target node according to the fluctuating load value and controlling the connection between the distributed new energy and the target node further includes:

[0120] S601, obtaining a load fluctuation threshold of a plurality of grid nodes in a grid;

[0121] S602, obtaining a current grid node corresponding to a fluctuating load value, and obtaining a plurality of transmission distances from the current grid node to a plurality of the grid nodes, and establishing a transmission distance table according to the plurality of the transmission distances;

[0122] S603: traverse and match the fluctuating load value with the plurality of fluctuating load thresholds based on a similarity model to obtain a plurality of load similarity values, wherein the function of the similarity model is:

[0123]

[0124] in, represents the load similarity value from the gth to the pth, z(h) represents the fluctuating load value, and Y(S) g represents the g-th load fluctuation threshold, Y(S) p represents the pth load fluctuation threshold;

[0125] S604, acquiring corresponding multiple matching docking nodes according to the multiple load similarity values;

[0126] S605. Screen the multiple matching docking nodes for the shortest transmission distance according to the transmission distance table to obtain the matching docking node with the shortest transmission distance, use the matching docking node with the shortest transmission distance as the target node, and control the distributed new energy to connect with the target node.

[0127] As described in the above steps S601-S605, the present invention first obtains the carrying capacity of multiple grid nodes in the power grid, so that the carrying capacity of each docking node can be understood, and whether they can withstand the fluctuating load brought by the access of new distributed new energy sources can be evaluated. Then, the current grid node corresponding to the fluctuating load value is obtained, and multiple transmission distances from the current grid node to multiple grid nodes are obtained. A transmission distance table is established based on the multiple transmission distances. In this way, the distance from the risky grid node to each docking node can be understood, providing a basis for selecting the nearest docking node. At the same time, docking nodes with shorter distances can reduce transmission losses and improve transmission efficiency. Then, the fluctuating load value is traversed and matched with multiple carrying fluctuating load thresholds based on a similarity model to obtain multiple load phases. Similarity value, and then obtain corresponding multiple matching docking nodes according to multiple load similarity values, so that the docking nodes that can withstand the fluctuating load of the newly connected distributed new energy can be screened out to ensure that the selected docking nodes have sufficient carrying capacity, and provide a basis for avoiding subsequent short-circuit risks. Then, according to the transmission distance table, the multiple matching docking nodes are screened for the shortest transmission distance to obtain the matching docking node with the shortest transmission distance, and the matching docking node with the shortest transmission distance is used as the target node, and the distributed new energy is controlled to be connected to the target node. In this way, it is possible to judge in advance whether the power grid node can withstand the fluctuating load generated by the distributed new energy caused by the weather, and then the access location of the power grid node can be paired in advance, thereby avoiding the problem of short circuit of the power grid caused by excessive load.

[0128] The present invention also provides a short circuit abnormality solution system in a networked control, comprising:

[0129] The first acquisition module 1 is used to acquire node access information of distributed new energy and power grid nodes, wherein the node access information includes node current information, node frequency information and node harmonic information;

[0130] A second acquisition module 2, used for acquiring a current amplitude and a current phase according to the node current information, acquiring a current waveform according to the current amplitude and the current phase, acquiring a plurality of current peak values ​​within a preset time according to the current waveform, and acquiring a current surge value according to the plurality of current peak values;

[0131] The third acquisition module 3 is used to obtain the fluctuation frequency of the power grid node within a preset time, and obtain the load change rate of the power grid node according to the fluctuation frequency, and obtain the power grid node fluctuation difference according to the load change rate of the power grid node and a preset normal change rate;

[0132] A fourth acquisition module 4 is used to acquire a plurality of nonlinear load harmonic values ​​within a preset time according to the node harmonic information, and compare the plurality of nonlinear load harmonic values ​​with a preset fundamental value by integer multiples to 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;

[0133] A first calculation module 5, used for calculating a fluctuating load value according to the current surge value, the grid node fluctuation difference and the harmonic wave increment value;

[0134] A first judging module 6, used to judge whether the fluctuating load value is greater than a preset threshold;

[0135] 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 and the grid node and a danger warning instruction is generated. The target node is searched according to the fluctuating load value, and the distributed renewable energy is controlled to connect to the target node.

[0136] In one embodiment, the second acquisition module includes:

[0137] Comparing the multiple current peak values ​​with a preset standard peak value to obtain multiple abnormal current peak values;

[0138] Acquire corresponding abnormal times according to the plurality of abnormal current peak values;

[0139] Calculating the difference between the plurality of abnormal current peak values ​​and the preset standard peak values ​​in sequence to obtain a plurality of abnormal current difference values;

[0140] The current surge value is calculated according to the number of abnormalities and the difference between multiple abnormal currents, wherein the calculation formula is:

[0141]

[0142] Wherein, J(Z) represents the current surge value, j(l) represents the abnormal current difference, and C represents the number of abnormalities, C=1, 2, 3...n.

[0143] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned short-circuit anomaly solution in the networking-oriented control are implemented.

[0144] 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 the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided by the present invention 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 and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double-speed 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).

[0145] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0146] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for solving short circuit anomaly in network control, characterized in that: include: Obtaining node access information of distributed new energy and power grid nodes, wherein the node access information includes node current information, node frequency information and node harmonic information; Acquire a current amplitude and a current phase according to the node current information, acquire a current waveform according to the current amplitude and the current phase, acquire a plurality of current peak values ​​within a preset time according to the current waveform, and acquire a current surge value according to the plurality of current peak values; Obtaining a fluctuation frequency of a power grid node within a preset time, and obtaining a load change rate of the power grid node according to the fluctuation frequency, and obtaining a power grid node fluctuation difference according to the load change rate of the power grid node and a preset normal change rate; Acquire multiple nonlinear load harmonic values ​​within a preset time according to 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 ​​according to the multiple harmonic high-frequency component values; Calculate the fluctuating load value according to the current surge value, the grid node fluctuation difference and the harmonic wave increment value; Determining 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 the target node is searched according to the fluctuating load value, and the distributed renewable energy source is controlled to be connected to the target node.

2. The method for solving the short circuit abnormality in the network control according to claim 1 is characterized in that: The step of obtaining a current surge value according to the multiple current peak values ​​comprises: Comparing the multiple current peak values ​​with a preset standard peak value to obtain multiple abnormal current peak values; Acquire corresponding abnormal times according to the plurality of abnormal current peak values; Calculating the difference between the plurality of abnormal current peak values ​​and the preset standard peak values ​​in sequence to obtain a plurality of abnormal current difference values; The current surge value is calculated according to the number of abnormalities and the difference between multiple abnormal currents, wherein the calculation formula is: Wherein, J(Z) represents the current surge value, j(l) represents the abnormal current difference, and C represents the number of abnormalities, C=1, 2, 3...n.

3. The short circuit abnormality solution in the network control according to claim 1 is characterized in that: The step of obtaining the grid load change rate according to the fluctuation frequency comprises: Acquire a node load value of a power grid node based on a mutual inductor, wherein the node load includes an active node load value and a reactive node load value; The load influence coefficient is calculated according to the active node load value and the reactive node load value, wherein the calculation formula is: Among them, 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 when the fluctuation frequency falls back to the preset reference fluctuation frequency within the preset time is obtained, 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, wherein the calculation formula is: Among them, S(L) represents the grid load change rate, b(d) represents the fluctuation frequency, j(b) represents the preset benchmark fluctuation frequency, T represents the fluctuation time, and X(s) represents the load influence coefficient.

4. The method for solving the short circuit abnormality in the network control according to claim 1 is characterized in that: The step of comparing the plurality of nonlinear load harmonic values ​​with a preset fundamental value by integer multiples to obtain a plurality of harmonic high-frequency component values, and obtaining a harmonic increment value according to the plurality of harmonic high-frequency component values ​​comprises: sequentially determining whether a plurality of harmonic values ​​of the nonlinear loads are integer multiples of a preset fundamental value; If the nonlinear load harmonic value is an integer multiple of the preset fundamental value, then a plurality of the nonlinear load harmonic values ​​are used as a plurality of harmonic high-frequency component values; Grouping the plurality of harmonic high-frequency component values ​​adjacently according to a time series to obtain a plurality of harmonic high-frequency component groups; Performing difference calculation on 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; The difference values ​​of the plurality of harmonic high frequency components are summed to obtain a harmonic increment value.

5. The method for solving the short circuit abnormality in the network control according to claim 1 is characterized in that: The step of calculating the fluctuating load value according to the current surge value, the grid node fluctuation difference and the harmonic wave increment value comprises: Acquire a corresponding first weight value according to the current surge value; Acquire a corresponding second weight value according to the power grid node fluctuation difference; A comprehensive abnormal value is calculated according to 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 abnormal value is used as the fluctuating load value.

6. The method for solving the short circuit abnormality in the network control according to claim 1 is characterized in that: The step of searching for a target node according to the fluctuating load value and controlling the connection between the distributed new energy source and the target node also includes: Obtaining a load fluctuation threshold value of a plurality of grid nodes in the grid; Acquire a current grid node corresponding to the fluctuating load value, and acquire multiple transmission distances from the current grid node to multiple grid nodes, and establish a transmission distance table according to the multiple transmission distances; The fluctuating load value is traversed and matched with a plurality of the fluctuating load thresholds based on a similarity model to obtain a plurality of load similarity values, wherein the function of the similarity model is: in, represents the load similarity value from the gth to the pth, z(h) represents the fluctuating load value, and Y(S) g represents the g-th load fluctuation threshold, Y(S) p represents the pth load fluctuation threshold; Acquire a corresponding plurality of matching docking nodes according to a plurality of the load similarity values; According to the transmission distance table, the shortest transmission distance is screened for multiple matching docking nodes to obtain the matching docking node with the shortest transmission distance, and the matching docking node with the shortest transmission distance is used as the target node, and the distributed new energy is controlled to connect with the target node.

7. A short circuit abnormality resolution system in a networked control, characterized in that: include: The first acquisition module is used to acquire node access information of distributed new energy and power grid nodes, wherein the node access information includes node current information, node frequency information and node harmonic information; A second acquisition module is used to acquire a current amplitude and a current phase according to the node current information, acquire a current waveform according to the current amplitude and the current phase, acquire a plurality of current peak values ​​within a preset time according to the current waveform, and acquire a current surge value according to the plurality of current peak values; A third acquisition module is used to acquire the fluctuation frequency of the power grid node within a preset time, and acquire the load change rate of the power grid node according to the fluctuation frequency, and acquire the power grid node fluctuation difference according to the load change rate of the power grid node and a preset normal change rate; A fourth acquisition module is used to acquire a plurality of nonlinear load harmonic values ​​within a preset time according to the node harmonic information, and compare the plurality of nonlinear load harmonic values ​​with a preset fundamental value by integer multiples to 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; A first calculation module, used for calculating a fluctuating load value according to the current surge value, the grid node fluctuation difference and the harmonic wave increment value; A first judging module, used to judge 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 and the grid node and a danger warning instruction is generated. The target node is searched according to the fluctuating load value, and the distributed renewable energy is controlled to connect to the target node.

8. A short circuit abnormality resolution system in a networked control according to claim 7, characterized in that: The second acquisition module includes: Comparing the multiple current peak values ​​with a preset standard peak value to obtain multiple abnormal current peak values; Acquire corresponding abnormal times according to the plurality of abnormal current peak values; Calculating the difference between the plurality of abnormal current peak values ​​and the preset standard peak values ​​in sequence to obtain a plurality of abnormal current difference values; The current surge value is calculated according to the number of abnormalities and the difference between multiple abnormal currents, wherein the calculation formula is: Wherein, J(Z) represents the current surge value, j(l) represents the abnormal current difference, 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, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

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

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