Method, device and processor for predicting properties of current in a conducting medium

Abstract

The application discloses a current attribute prediction method and device in a conductive medium and a processor. The method comprises the following steps: obtaining a conductive medium to which a leakage current in a power system flows; determining a target difference model of a node in at least one branch of the conductive medium, wherein the target difference model is used to represent a mapping relationship between currents flowing through the branches and voltages of the branches; and predicting an attribute of the leakage current in the process of flowing to the conductive medium by using the target difference model to obtain an attribute prediction result, wherein the attribute prediction result at least comprises a circuit range passed by the leakage current in the process of flowing to the conductive medium and an influence result of the leakage current on the power system in the process of flowing to the conductive medium. The application solves the technical problem of low accuracy of current attribute prediction in a conductive medium.

Description

Technical Field

[0001] This invention relates to the field of electric power, and more specifically, to a method, apparatus, and processor for predicting the properties of current in a conductive medium. Background Technology

[0002] In power systems, leakage current can occur when current flows into conductive media such as water due to equipment insulation failure or external factors. This leakage current can cause varying degrees of damage to the power supply system; therefore, analyzing the propagation path and impact range of leakage current in conductive media is crucial.

[0003] However, in related technologies, it is often impossible to accurately capture the true characteristics of current in conductive media, resulting in the technical problem of low accuracy in predicting the properties of current in conductive media.

[0004] There is currently no effective solution to the technical problem of low accuracy in predicting the properties of current in conductive media. Summary of the Invention

[0005] This invention provides a method, apparatus, and processor for predicting the properties of current in a conductive medium, to at least solve the technical problem of low accuracy in predicting the properties of current in a conductive medium.

[0006] According to one aspect of the present invention, a method for predicting the properties of current in a conductive medium is provided. The method includes: obtaining the conductive medium to which leakage current flows in a power system; determining a target differential model of a node based on at least one node in a plurality of impedance branches to which the leakage current flows, wherein the target differential model is used to at least represent the mapping relationship between the current flowing through each of the plurality of impedance branches and the voltage of each of the plurality of impedance branches; and using the target differential model to predict the properties of the leakage current during its flow to the conductive medium, thereby obtaining a property prediction result, wherein the property prediction result includes at least the circuit range traversed by the leakage current during its flow to the conductive medium and the impact of the leakage current on the power system during its flow to the conductive medium.

[0007] Optionally, based on at least one node among multiple impedance branches of the conductive medium flow direction, a target differential model of the node is determined, including: determining the type of the node; and determining the target differential model based on the type.

[0008] Optionally, determining the target differential model based on the type includes: determining target boundary information that matches the type, wherein the target boundary information is used to represent the electrical characteristics at the node; and determining the target differential model based on the target boundary information.

[0009] Optionally, the target difference model is determined based on the target boundary information, including: adjusting the initial difference model according to the target boundary information to obtain the target difference model.

[0010] Optionally, the properties of leakage current during its flow to the conductive medium are predicted using a target differential model, and the property prediction results are obtained, including: determining the resistance and capacitance in the power system; inputting the resistance and capacitance into the target differential model; and predicting the properties in the target differential model to obtain the property prediction results.

[0011] Optionally, the impedance branch includes: a first impedance branch, a second impedance branch, and a third impedance branch, wherein the direction of the first impedance branch is perpendicular to the direction of the second impedance branch and the direction of the third impedance branch, the direction of the second impedance branch is perpendicular to the direction of the first impedance branch and the direction of the third impedance branch, and the direction of the third impedance branch is perpendicular to the direction of the first impedance branch and the direction of the second impedance branch.

[0012] According to one aspect of the present invention, a device for predicting the properties of current in a conductive medium is provided. The device may include: an acquisition unit for acquiring the conductive medium to which leakage current flows in a power system; a determination unit for determining a target differential model of a node based on at least one node among multiple impedance branches to which the conductive medium flows, wherein the target differential model is used to at least represent the mapping relationship between the current flowing through each of the multiple impedance branches and the voltage of each of the multiple impedance branches; and a prediction unit for predicting the properties of the leakage current as it flows into the conductive medium using the target differential model, and obtaining a property prediction result, wherein the property prediction result includes at least the circuit range through which the leakage current flows into the conductive medium and the impact of the leakage current on the power system as it flows into the conductive medium.

[0013] According to another aspect of the present invention, a processor is also provided. The processor is used to run a program, wherein the program, when run by the processor, performs the current property prediction method in a conductive medium according to the embodiments of the present invention.

[0014] According to another aspect of the embodiments of the present invention, an electronic device is also provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the current property prediction method in a conductive medium according to various embodiments of the present invention during runtime.

[0015] According to another aspect of the present invention, a computer-readable storage medium is also provided. The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the battery charging method for a vehicle according to the embodiments of the present invention.

[0016] According to another aspect of the present invention, a computer program product is also provided, the computer program product including a computer program, wherein the computer program, when executed by a processor, implements the current property prediction method in a conductive medium according to the embodiments of the present invention.

[0017] According to another aspect of the present invention, a computer program product is also provided, including a non-volatile computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the current property prediction method in a conductive medium according to the present invention.

[0018] According to another aspect of the embodiments of the present invention, the embodiments of this application also provide a computer program, which, when executed by a processor, implements the current property prediction method in a conductive medium described in the above embodiments of the present invention.

[0019] In this embodiment of the invention, when predicting the properties of current in a conductive medium, the conductive medium to which the leakage current in the power system flows can be obtained. Based on at least one node among multiple impedance branches to which the conductive current flows, a target differential model for the node can be determined. Using the determined target differential model, the properties of the leakage current during its flow to the conductive medium are predicted, yielding property prediction results. In other words, the circuit range traversed by the leakage current during its flow to the conductive medium, and the impact of the leakage current on the power system during its flow to the conductive medium, are obtained. This achieves the goal of accurately capturing the true characteristics of current in the conductive medium, thus solving the technical problem of low accuracy in predicting the properties of current in a conductive medium, and ultimately improving the technical effect of improving the accuracy of predicting the properties of current in a conductive medium. Attached Figure Description

[0020] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0021] Figure 1 This is a flowchart of a method for predicting the properties of current in a conductive medium according to an embodiment of the present invention;

[0022] Figure 2(a) is a schematic diagram of a three-dimensional network node connection according to an embodiment of the present invention;

[0023] Figure 2(b) is a schematic diagram of the basic unit of an equivalent model according to an embodiment of the present invention;

[0024] Figure 3(a) is a schematic diagram of an impedance branch model according to an embodiment of the present invention;

[0025] Figure 3(b) is a schematic diagram of an internal node in an impedance branch according to an embodiment of the present invention;

[0026] Figure 3(c) is a schematic diagram of the upper boundary node in an impedance branch according to an embodiment of the present invention;

[0027] Figure 3(d) is a schematic diagram of the upper boundary grounding node in an impedance branch according to an embodiment of the present invention;

[0028] Figure 3(e) is a schematic diagram of the upper boundary insulation node in an impedance branch according to an embodiment of the present invention;

[0029] Figure 3(f) is a schematic diagram of the lower boundary insulation node in an impedance branch according to an embodiment of the present invention;

[0030] Figure 4 This is a schematic diagram of a current property prediction device in a conductive medium according to an embodiment of the present invention. Detailed Implementation

[0031] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0033] According to an embodiment of the present invention, a method for predicting the properties of current in a conductive medium is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0034] Figure 1 This is a flowchart of a method for predicting the properties of current in a conductive medium according to an embodiment of the present invention. The method may include the following steps:

[0035] Step S101: Obtain the conductive medium to which the leakage current in the power system flows.

[0036] In the technical solution provided by step S101 of the present invention, the leakage current may be caused by the insulation failure of equipment in the power system. For example, the equipment may include: switches, cables, generators, transformers, distributors, and inverters, etc., which are only examples and are not specifically limited here.

[0037] In this embodiment, the conductive medium may include at least one of the following media: ground and water, etc., which are only examples and are not specifically limited.

[0038] In this embodiment, the conductive medium to which the leakage current flows in the power system is obtained. Optionally, in the event of equipment insulation failure, this embodiment can detect the leakage current in the power system and trace the direction of the leakage current to obtain the conductive medium to which the leakage current flows, for example, the body of water to which the leakage current flows. This is only an example and is not a specific limitation.

[0039] Step S102: Determine the target differential model of the node based on at least one node among multiple impedance branches of the conductive medium flow direction.

[0040] In the technical solution provided by step S102 of the present invention, the target differential model can be used to at least represent the mapping relationship between the current flowing through each of the multiple impedance branches and the voltage of each of the multiple impedance branches.

[0041] In this embodiment, the number of the plurality of impedance branches is not limited. For example, there can be three impedance branches, which can be represented by coordinate axes in a three-dimensional coordinate system. This is only an example and is not a specific limitation.

[0042] In this embodiment, after obtaining the conductive medium to which the leakage current flows in the power system, a target differential model for the node is determined based on at least one node among multiple impedance branches to which the conductive current flows. Optionally, this embodiment, based on obtaining the conductive medium to which the leakage current flows, traces the flow direction of the conductive medium to obtain multiple impedance branches to which the conductive current flows. According to the type of at least one node among the multiple impedance branches, a target differential model can be determined; that is, the mapping relationship between the current flowing through each of the multiple impedance branches and the voltage in each of the multiple impedance branches can be determined.

[0043] Step S103: Using the target difference model, predict the properties of the leakage current as it flows into the conductive medium, and obtain the property prediction results.

[0044] In the technical solution provided by step S103 of the present invention, the attribute prediction result may at least include the circuit range through which the leakage current flows to the conductive medium, and the impact of the leakage current on the power system during the process of flowing to the conductive medium. For example, the attribute prediction result may be the circuit range through which the leakage current flows to the water body, and the impact of the leakage current on the power system during the process of flowing to the water body. This is only an example and is not specifically limited.

[0045] In this embodiment, the circuit range can include the propagation path of the leakage current as it flows into the conductive medium. The resulting impact can include the extent to which the leakage current affects the power supply of the power system as it flows into the conductive medium.

[0046] In this embodiment, after determining the target differential model of at least one node in multiple impedance branches based on the direction of conductive medium flow, the properties of the leakage current during its flow into the conductive medium are predicted using the target differential model, resulting in property prediction results. Optionally, in this embodiment, based on the determined target differential model, the current flowing through each of the multiple impedance branches and the voltage of each of the multiple impedance branches are input into the target differential model. Then, using the target differential model with the input current and voltage, the properties of the leakage current during its flow into the conductive medium are predicted, resulting in property prediction results. For example, the circuit range traversed by the leakage current during its flow into the conductive medium and the impact of the leakage current on the power system during its flow into the conductive medium can be obtained. This is only an example and is not a specific limitation.

[0047] In steps S101 to S103 of this application, when predicting the properties of current in a conductive medium, the conductive medium to which the leakage current in the power system flows can be obtained. Based on at least one node among multiple impedance branches to which the conductive medium flows, a target differential model of the node can be determined. Using the determined target differential model, the properties of the leakage current during its flow to the conductive medium are predicted, and the property prediction results can be obtained. That is, the circuit range traversed by the leakage current during its flow to the conductive medium and the impact of the leakage current on the power system during its flow to the conductive medium can be obtained. This achieves the goal of accurately capturing the true characteristics of current in a conductive medium, thereby solving the technical problem of low accuracy in predicting the properties of current in a conductive medium, and thus achieving the technical effect of improving the accuracy of predicting the properties of current in a conductive medium.

[0048] The method described in this embodiment will be further described below.

[0049] As an optional embodiment, step S102, based on at least one node among multiple impedance branches of the conductive medium flow direction, determines the target differential model of the node, including: determining the type of the node; and determining the target differential model based on the type.

[0050] In this embodiment, the types of the nodes mentioned above may include at least the following types: internal nodes, upper boundary nodes, and lower boundary nodes. This is only for illustrative purposes and is not a specific limitation.

[0051] In this embodiment, the aforementioned internal nodes can be used to represent nodes located within the network. Depending on their state, these internal nodes can be categorized as: internal passive nodes (also known as ordinary nodes), internal active nodes, and internal grounded nodes.

[0052] In this embodiment, the aforementioned upper boundary node can be used to represent an edge node located where the network label (e.g., represented by i, j, or k) has a maximum value. Depending on the state, the aforementioned upper boundary node can be divided into upper boundary grounded nodes and upper boundary insulated nodes.

[0053] In this embodiment, the lower boundary node can be used to represent an edge node located at the minimum value of the network label (e.g., denoted by i, j, or k). Depending on the state, the lower boundary node can be divided into a lower boundary ground node and a lower boundary insulated node.

[0054] In this embodiment, after obtaining the conductive medium to which the leakage current flows in the power system, the type of node is determined. Optionally, based on obtaining the conductive medium to which the leakage current flows, this embodiment traces the flow direction of the conductive medium to obtain multiple impedance branches. Among the obtained multiple impedance branches, the type of node can be determined. That is, classifying at least one node among the multiple impedance branches yields a classification result. The classification result can be used to represent the type to which at least one node among the multiple impedance branches belongs.

[0055] In this embodiment, after determining the type of the node, the target difference model is determined based on the type. Optionally, based on the determined node type, this embodiment further specifies the target differential model if the determined node type is an internal passive node, satisfies the differential model of an internal passive node, and is determined as the target differential model; if the determined node type is an internal active node, satisfies the differential model of an internal active node, and is determined as the target differential model; if the determined node type is an internal ground node, satisfies the differential model of an internal ground node, and is determined as the target differential model; if the determined node type is an upper boundary ground node, satisfies the differential model of an upper boundary ground node, and is determined as the target differential model; if the determined node type is an upper boundary insulated node, satisfies the differential model of an upper boundary insulated node, and is determined as the target differential model; if the determined node type is a lower boundary ground node, satisfies the differential model of a lower boundary ground node, and is determined as the target differential model; if the determined node type is a lower boundary insulated node, satisfies the differential model of a lower boundary insulated node, and is determined as the target differential model. This is merely an illustrative example and not a specific limitation.

[0056] As an optional implementation method, determining the target difference model based on type includes: determining target boundary information that matches the type; and determining the target difference model based on the target boundary information.

[0057] In this embodiment, the aforementioned target boundary information can be used to represent the electrical characteristics at the node. These electrical characteristics may include voltage and / or current at the node, etc., but this is only illustrative and not specifically limited.

[0058] In this embodiment, after determining the node type, target boundary information matching the type is determined. Optionally, based on the determined node type, if the determined node type is an internal passive node, the boundary information matching the internal passive node is determined as the target boundary information; if the determined node type is an internal active node, the differential model satisfying the internal active node is determined as the target differential model; if the determined node type is an internal ground node, the boundary information matching the internal ground node is determined as the target boundary information; if the determined node type is an upper boundary ground node, the boundary information matching the upper boundary ground node is determined as the target boundary information; if the determined node type is an upper boundary insulated node, the boundary information matching the upper boundary insulated node is determined as the target boundary information; if the determined node type is a lower boundary ground node, the boundary information matching the lower boundary ground node is determined as the target boundary information; if the determined node type is a lower boundary insulated node, the boundary information matching the lower boundary insulated node is determined as the target boundary information. This is only an example and is not a specific limitation.

[0059] In this embodiment, after determining the target boundary information that matches the type, a target differential model is determined based on the target boundary information. Optionally, based on the determined target boundary information, if the target boundary information is boundary information matching internal passive nodes, then the differential model satisfying the internal passive node condition is determined as the target differential model; if the target boundary information is boundary information matching internal active nodes, then the differential model satisfying the internal active node condition is determined as the target differential model; if the target boundary information is boundary information matching internal grounding nodes, then the differential model satisfying the internal grounding node condition is determined as the target differential model; if the target boundary information is boundary information matching the upper boundary grounding node condition... The differential model that satisfies the upper boundary grounding node is determined as the target differential model. If the target boundary information is the boundary information that matches the upper boundary insulation node, the differential model that satisfies the upper boundary insulation node is determined as the target differential model. If the target boundary information is the boundary information that matches the lower boundary grounding node, the differential model that satisfies the lower boundary grounding node is determined as the target differential model. If the target boundary information is the boundary information that matches the lower boundary insulation node, the differential model that satisfies the lower boundary insulation node is determined as the target differential model. This is only an example and is not specifically limited.

[0060] As an optional implementation method, determining the target difference model based on the target boundary information includes: adjusting the initial difference model according to the target boundary information to obtain the target difference model.

[0061] In this embodiment, after determining the target boundary information that matches the type, the initial differential model is adjusted according to the target boundary information to obtain the target differential model. Optionally, based on the determined target boundary information, if the target boundary information is boundary information matching internal passive nodes, the initial differential model is adjusted to obtain a differential model that satisfies internal passive nodes, and this differential model is determined as the target differential model; if the target boundary information is boundary information matching internal active nodes, the initial differential model is adjusted to obtain a differential model that satisfies internal active nodes, and this differential model is determined as the target differential model; if the target boundary information is boundary information matching internal ground nodes, the initial differential model is adjusted to obtain a differential model that satisfies internal ground nodes, and this differential model is determined as the target differential model; if the target boundary information is boundary information matching the upper boundary ground node, the initial differential model is adjusted... If the target boundary information is the boundary information matching the upper boundary insulation node, then the initial differential model is adjusted to obtain a differential model that satisfies the upper boundary insulation node, and this differential model is determined as the target differential model. If the target boundary information is the boundary information matching the lower boundary grounding node, then the initial differential model is adjusted to obtain a differential model that satisfies the lower boundary grounding node, and this differential model is determined as the target differential model. If the target boundary information is the boundary information matching the lower boundary insulation node, then the initial differential model is adjusted to obtain a differential model that satisfies the lower boundary insulation node, and this differential model is determined as the target differential model. This is only an example and is not specifically limited.

[0062] Optionally, the initial difference model described above can be determined by equations (1) to (10). Substituting equation (6) into equations (2), (3), and (4), we obtain the three difference equations for the nodes shown in equations (7), (8), and (9). Transforming equation (5), we obtain equation (10):

[0063]

[0064]

[0065] I x(i,j,k) (t)+I y(i,j,k) (t)+I z(i,j,k) (t)=I x(i-1,j,k) (t)+I y(i,j-1,k) (t)+I z(i,j,k-1) (t)+I in (t) (5)

[0066]

[0067] I x(i,j,k) [n]+I y(i,j,k) [n]+I z(i,j,k) [n] = I x(i-1,j,k) [n]+I y(i,j-1,k) [n]+I z(i,j,k-1) [n]+I in [n] (10)

[0068] Among them, U (i,j,k) It can be used to represent the voltage at a node, I x(i,j,k) I y(i,j,k) and I z(i,j,k) It can be used to represent the current flowing into three impedance branches. It can be used to represent the basic operators of fractional calculus, where 'a' represents the upper bound of the operator, 't' represents the lower bound, 'α' represents the order of differentiation / integration, 'R' represents the resistance of the mesh, 'C' represents the capacitance of the mesh, and 'U' represents the capacitance of the mesh. (i+1,j,k) U (i,j+1,k) and U (i,j,k+1) It can be used to represent the node voltage of adjacent cells, I x(i-1,j,k) I y(i,j-1,k) and I z(i,j,k-1) It can be used to represent the impedance branch current of adjacent units, I in It can be used to represent the current injected into the node from the outside; if the node is a passive node, then I in (t) = 0. z can be used to represent a complex variable. n can be used to represent the count of sampling time points.

[0069] Optionally, if the target boundary information is the boundary information matched by the internal active nodes, the initial difference model can be adjusted to obtain a difference model that satisfies the internal active nodes, and this difference model can be determined as the target difference model. This can be achieved by the following equation (11), that is, the boundary information represented by the above equation (10) is adjusted to the boundary information represented by the following equation (11):

[0070] U (i,j,k) [n] = U in [n] (11)

[0071] Optionally, if the target boundary information is the boundary information matching the internal grounding node, the initial differential model can be adjusted to obtain a differential model that satisfies the internal grounding node, and this differential model can be determined as the target differential model. This can be achieved by the following equation (12), that is, the boundary information represented by the above equation (10) is adjusted to the boundary information represented by the following equation (12):

[0072] U (i,j,k) [n] = 0 (12)

[0073] Optionally, if the target boundary information is the boundary information matching the upper boundary grounding node, the initial differential model is adjusted to obtain a differential model that satisfies the upper boundary grounding node, and this differential model is determined as the target differential model. This can be achieved through formulas (1), (13), (8), (9) and (10), or through formulas (1), (7), (14), (9) and (10), or through formulas (1), (7), (8), (15) and (10). That is, based on adjusting the boundary information represented by the above formula (10) to the boundary information represented by the above formula (12), if the node is located on the x-axis boundary, i.e., i = M, then there exists a boundary condition U. (i+1,j,k) (t)=0, transform the above equation (7) into the following equation (13), where, considering U (i,j,k) (t)=0, the following equation (13) is actually equivalent to I x(i,j,k) (t) = 0. If the node is located on the y-axis boundary, i.e., j = N, then the boundary condition U exists. (i,j+1,k) (t) = 0, transforming equation (8) into equation (14). If the node is located on the z-axis boundary, i.e., k = L, then the boundary condition U exists. (i,j,k+1) =0, transform the above equation (9) into the following equation (15):

[0074]

[0075]

[0076] Optionally, if the target boundary information is the boundary information matching the upper boundary insulation node, the initial difference model is adjusted to obtain a difference model that satisfies the upper boundary insulation node, and this difference model is determined as the target difference model. This can be achieved through formulas (1), (16), (8), (9), and (10), or through formulas (1), (7), (17), (9), and (10), or through formulas (1), (7), (8), (18), and (10). That is, if the node is located on the x-axis boundary, i.e., i = M, then there exists boundary condition I. x(M,j,k) (t) = 0, transforming equation (7) into equation (16). If the node is located on the y-axis boundary, i.e., j = N, then the boundary condition I exists. y(M,j,k) (t) = 0, transforming equation (8) into equation (17). If the node is located on the z-axis boundary, i.e., k = L, then the boundary condition I exists. z(M,j,k)(t)=0, transforming equation (9) into equation (18), and thus using the target difference model, the properties of the leaked current during its flow to the conductive medium can be predicted, and the property prediction results can be obtained:

[0077] I x(i,j,k) [n] = 0 (16)

[0078] I y(i,j,k) [n] = 0 (17)

[0079] I z(i,j,k) [n] = 0 (18)

[0080] Optionally, if the target boundary information is the boundary information matching the lower boundary grounding node, the initial differential model is adjusted to obtain a differential model that satisfies the lower boundary grounding node, and this differential model is determined as the target differential model, which can be achieved by the above equations (12), (7), (8) and (9).

[0081] Optionally, if the target boundary information is the boundary information matching the lower boundary insulation node, the initial differential model can be adjusted to obtain a differential model that satisfies the lower boundary insulation node, and this differential model can be determined as the target differential model. This can be achieved through equations (7), (8), (9), and (10) above. Wherein, if the node is the lower bound of the x-axis element (i=1), then the current flowing into the (1, j, k) node is only I. y(1,j-1,k) and I z(1,j,k-1) Since this node is insulated and has no externally injected current, the boundary conditions of this node include I. x(i-1,j,k) (t) = 0, so I in equation (10) above needs to be changed. x(i-1,j,k) [n] is set to 0; if the node is the lower bound of the y-axis element (j=1), then the boundary conditions of the node include I. y(i,j-1,k) (t) = 0, so I in equation (10) above needs to be changed. y(i,j-1,k) [n] is set to 0; if the node is the lower bound of the z-axis element (k=1), then the boundary conditions of the node include I. z(i,j,k-1) (t) = 0, so I in equation (10) above needs to be changed. z(i,j,k-1) [n] is set to 0.

[0082] As an optional embodiment, step S103 involves using a target differential model to predict the properties of the leakage current as it flows into the conductive medium, and obtaining property prediction results. This includes: determining the resistance and capacitance in the power system; inputting the resistance and capacitance into the target differential model; and predicting the properties in the target differential model to obtain property prediction results.

[0083] In this embodiment, after determining the target differential model of at least one node in a plurality of impedance branches based on the direction of conductive medium flow, the resistance and capacitance in the power system are determined. Optionally, this embodiment determines the resistance and capacitance in the power system by detecting the resistance and capacitance in the power system based on the determined target differential model.

[0084] In this embodiment, after determining the resistance and capacitance in the power system, the resistance and capacitance are input into the target differential model. Optionally, in this embodiment, based on determining the resistance and capacitance in the power system, the current flowing through each of the multiple impedance branches, the voltage of each of the multiple impedance branches, and the determined resistance and capacitance are all input into the target differential model.

[0085] In this embodiment, after the resistance and capacitance are input into the target differential model, the attributes are predicted in the target differential model to obtain attribute prediction results. Optionally, this embodiment uses the target differential model after inputting the above-mentioned current, voltage, resistance, and capacitance to predict the attributes of the leakage current during its flow to the conductive medium, and can obtain attribute prediction results. For example, it can obtain the circuit range through which the leakage current flows to the conductive medium, and the impact of the leakage current on the power system during its flow to the conductive medium. This is only an example and is not specifically limited.

[0086] As an optional embodiment, the impedance branch includes: a first impedance branch, a second impedance branch, and a third impedance branch, wherein the direction of the first impedance branch is perpendicular to the direction of the second impedance branch and the direction of the third impedance branch, the direction of the second impedance branch is perpendicular to the direction of the first impedance branch and the direction of the third impedance branch, and the direction of the third impedance branch is perpendicular to the direction of the first impedance branch and the direction of the second impedance branch.

[0087] In this embodiment, the direction of the first impedance branch can be perpendicular to the direction of the second impedance branch, and the direction of the first impedance branch can be perpendicular to the direction of the third impedance branch. The direction of the second impedance branch can be perpendicular to the direction of the first impedance branch, and the direction of the second impedance branch can be perpendicular to the direction of the third impedance branch. The direction of the third impedance branch can be perpendicular to the direction of the first impedance branch, and the direction of the third impedance branch can be perpendicular to the direction of the second impedance branch.

[0088] In this embodiment, the first impedance branch, the second impedance branch, and the third impedance branch can be represented using a three-dimensional coordinate system. Specifically, the first impedance branch can be represented by the x-axis, the second impedance branch by the y-axis, and the third impedance branch by the z-axis. This is merely an illustrative example and not a specific limitation.

[0089] In this embodiment of the invention, when predicting the properties of current in a conductive medium, the conductive medium to which the leakage current in the power system flows can be obtained. Based on at least one node among multiple impedance branches to which the conductive current flows, a target differential model for the node can be determined. Using the determined target differential model, the properties of the leakage current during its flow to the conductive medium are predicted, yielding property prediction results. In other words, the circuit range traversed by the leakage current during its flow to the conductive medium, and the impact of the leakage current on the power system during its flow to the conductive medium, are obtained. This achieves the goal of accurately capturing the true characteristics of current in the conductive medium, thus solving the technical problem of low accuracy in predicting the properties of current in a conductive medium, and ultimately improving the technical effect of improving the accuracy of predicting the properties of current in a conductive medium.

[0090] The technical solutions of the embodiments of the present invention will be illustrated below with reference to preferred embodiments.

[0091] In power systems, leakage current can occur when current flows into conductive media such as water due to equipment insulation failure or external factors. This leakage current can cause varying degrees of damage to the power supply system; therefore, analyzing the propagation path and impact range of leakage current in conductive media is crucial.

[0092] However, in related technologies, it is often impossible to accurately capture the true characteristics of current in conductive media, resulting in the technical problem of low accuracy in predicting the properties of current in conductive media.

[0093] To address the aforementioned technical problems, this invention proposes a method for predicting the properties of current in a conductive medium. Based on at least one node among multiple impedance branches of the conductive medium to which the leaked current flows in the power system, a target differential model of the node can be determined. Using this target differential model, the properties of the leaked current during its flow into the conductive medium are predicted, yielding the property prediction results. This achieves the goal of accurately capturing the true characteristics of current in the conductive medium, thus solving the technical problem of low accuracy in predicting the properties of current in a conductive medium, and ultimately improving the accuracy of current property prediction in a conductive medium.

[0094] In this embodiment, a tetrahedron can be represented by a three-dimensional network node, and the basic unit of water can be the aforementioned tetrahedron. For example, Figure 2(a) is a schematic diagram of a three-dimensional network node connection according to an embodiment of the present invention. As shown in Figure 2(a), the smallest tetrahedron is the basic unit of water, and each unit is labeled (i, j, k). The positive directions of the x, y, and z coordinate axes are the labels, and i, j, and k are the directions of increase.

[0095] In this embodiment, the state vector of each unit can be as shown in Figure 2(b). Figure 2(b) is a schematic diagram of the basic unit of an equivalent model according to an embodiment of the present invention. Each node is connected to three resistors, and the state vector of each unit can be represented by θ(t) = [U (i,j,k) (t),I x(i,j,k) (t),I y(i,j,k) (t),I z(i,j,k) (t)] T To express.

[0096] In this embodiment, the impedance branch model can be as shown in Figure 3(a). Figure 3(a) is a schematic diagram of an impedance branch model according to an embodiment of the present invention, which uses a parallel combination of resistors and fractional capacitors to represent the impedance branch model.

[0097] In this embodiment, the internal nodes in the impedance branch can be as shown in Figure 3(b). Figure 3(b) is a schematic diagram of the internal nodes in an impedance branch according to an embodiment of the present invention. The internal nodes can be used to represent nodes located inside the network. The internal nodes are the parts selected by the dashed box.

[0098] In this embodiment, the internal passive nodes in the impedance branch can be implemented by the above equations (1), (7), (8), (9) and (10) to predict the properties of the leaked current as it flows into the conductive medium.

[0099] In this embodiment, the internal grounding node in the impedance branch can be implemented by the above equations (1), (7), (8), (9) and (11) to predict the properties of the leaked current as it flows into the conductive medium.

[0100] In this embodiment, the internal grounding node in the impedance branch can be implemented by the above equations (1), (7), (8), (9) and (12) to predict the properties of the leaked current as it flows into the conductive medium.

[0101] Optionally, fractional differential operators Unifying fractional integrals and differentials, when Re(α) > 0, It can represent fractional differentials. When Re(α) < 0, It can represent fractional integrals. When α is a positive integer n, It can represent the nth derivative of a function f(t). Therefore, integer-order calculus is a special case of fractional-order calculus.

[0102] In this embodiment, the upper boundary node in the impedance branch can be as shown in Figure 3(c). Figure 3(c) is a schematic diagram of the upper boundary node in an impedance branch according to an embodiment of the present invention. The upper boundary node can be used to represent the edge node located at the maximum value of the network label (e.g., represented by i, j or k). The upper boundary node is the part selected by the dashed box.

[0103] In this embodiment, the upper boundary grounding node in the impedance branch can be as shown in Figure 3(d). Figure 3(d) is a schematic diagram of the upper boundary grounding node in an impedance branch according to an embodiment of the present invention. The upper boundary grounding node is the part selected by the dashed box. Based on adjusting the boundary information expressed by formula (10) to the boundary information expressed by formula (12), if the node is located on the x-axis boundary, i.e., i = M, then there exists a boundary condition U. (i+1,j,k) (t)=0, transforming formula (7) into formula (13), where, considering U (i,j,k) (t)=0, formula (13) is actually equivalent to I x(i,j,k) (t) = 0. If the node is located on the y-axis boundary, i.e., j = N, then the boundary condition U exists. (i,j+1,k) (t) = 0, transforming equation (8) into equation (14). If the node is located on the z-axis boundary, i.e., k = L, then the boundary condition U exists. (i,j,k+1) =0, convert formula (9) into formula (15).

[0104] In this embodiment, the upper boundary insulation node in the impedance branch can be as shown in Figure 3(e). Figure 3(e) is a schematic diagram of the upper boundary insulation node in an impedance branch according to an embodiment of the present invention. The upper boundary insulation node is the part selected by the dashed box. Wherein, if the node is located on the x-axis boundary, i.e., i = M, then a boundary condition exists.

[0105] I x(M,j,k) (t) = 0, transforming formula (7) into formula (16). If the node is located on the y-axis boundary, i.e., j = N, then the boundary condition I exists. y(M,j,k) (t) = 0, transforming formula (8) into formula (17). If the node is located on the z-axis boundary, i.e., k = L, then the boundary condition I exists. z(M,j,k) (t)=0, transforming formula (9) into formula (18), and thus using the target difference model, the properties of the leaked current during its flow to the conductive medium can be predicted, and the property prediction results can be obtained.

[0106] In this embodiment, the lower boundary grounding node in the impedance branch can be implemented by the above equations (12), (7), (8) and (9) to pre-determine the properties of the leaked current as it flows into the conductive medium.

[0107] In this embodiment, the lower boundary insulating node in the impedance branch can be as shown in Figure 3(f). Figure 3(f) is a schematic diagram of the lower boundary insulating node in an impedance branch according to an embodiment of the present invention. The lower boundary insulating node is the part selected by the dashed box. Wherein, if this node is the lower boundary of the x-axis element (i=1), then the current flowing into the (1, j, k) node is only I. y(1,j-1,k) and I z(1,j,k-1) Since this node is insulated and has no externally injected current, the boundary conditions of this node include I. x(i-1,j,k) (t) = 0, so I in equation (10) above needs to be changed. x(i-1,j,k) [n] is set to 0; if the node is the lower bound of the y-axis element (j=1), then the boundary conditions of the node include I. y(i,j-1,k) (t) = 0, so I in equation (10) above needs to be changed. y(i,j-1,k) [n] is set to 0; if the node is the lower bound of the z-axis element (k=1), then the boundary conditions of the node include I. z(i,j,k-1) (t) = 0, so I in equation (10) above needs to be changed. z(i,j,k-1) [n] is set to 0.

[0108] In this embodiment, based on at least one node among multiple impedance branches of the conductive medium to which the leaked current in the power system flows, a target differential model of the node can be determined. Using the target differential model, the properties of the leaked current during its flow into the conductive medium can be predicted, thereby obtaining the property prediction results. This achieves the goal of accurately capturing the true characteristics of the current in the conductive medium, thus solving the technical problem of low accuracy in predicting the properties of the current in the conductive medium, and further achieving the technical effect of improving the accuracy of predicting the properties of the current in the conductive medium.

[0109] In this embodiment, each node in the impedance network has a state vector θ with 8 states to be determined. Based on the category of each node, 8 equations (basic equations + boundary conditions) can be formulated for each node. Solving the equations of each node simultaneously yields the linear equation system AX = Y for the entire impedance network. Here, X can be formed by arranging and connecting the state vectors of each node, X = [θ]. (1,1,1) T ,θ (2,1,1) T ,…,θ (M,1,1) T ,θ (1,2,1) T ,…,θ (1,N,1) T,…,θ (M,N,1) T ,θ (1,1,2) T ,…,θ (M,N,L) T ] T The system has 8×M×N×L rows. A is a matrix (8MNL×8MNL) consisting of the coefficients of the linear equations. Since the state of each node is only related to the states of its neighboring nodes, matrix A is a sparse matrix. Y can be a vector composed of terms from the linear equations other than the state vector. Y can include node voltages, branch currents, external power supply voltages, etc., at past time points. Solving the linear equations AX=Y yields a unique solution for the states of each node.

[0110] In this embodiment, the active node and the ground node may be subject to externally injected current I. in(i,j,k) After calculating the state variables of each node (t), the external injection current of each node can be calculated according to the following formula (19):

[0111] I x(i,j,k) [n]+I y(i,j,k) [n]+I z(i,j,k) [n]-I x(i-1,j,k) [n]-I y(i,j-1,k) [n]-I z(i,j,k-1) [n] = I in [n](19)

[0112] According to embodiments of the present invention, an apparatus for predicting the properties of current in a conductive medium is also provided. It should be noted that this apparatus for predicting the properties of current in a conductive medium can be used to execute one of the current property prediction methods in a conductive medium described in the embodiments.

[0113] Figure 4 This is a schematic diagram of a current property prediction device in a conductive medium according to an embodiment of the present invention. Figure 4 As shown, the current property prediction device 400 in a conductive medium may include: an acquisition unit 401, a determination unit 402, and a prediction unit 403.

[0114] The acquisition unit 401 is used to acquire the conductive medium to which the leakage current in the power system flows.

[0115] The determining unit 402 is used to determine the target differential model of at least one node among multiple impedance branches based on the direction of the conductive medium flow, wherein the target differential model is used to at least represent the mapping relationship between the current flowing through each of the multiple impedance branches and the voltage of each of the multiple impedance branches.

[0116] The prediction unit 403 is used to predict the properties of the leakage current as it flows into the conductive medium using a target difference model, and obtain the property prediction results. The property prediction results include at least the circuit range through which the leakage current flows into the conductive medium, and the impact of the leakage current on the power system during the process of flowing into the conductive medium.

[0117] Optionally, the determining unit 402 may include: a first determining module for determining the type of the node; and a second determining module for determining the target difference model based on the type.

[0118] Optionally, the second determining module may include: a first determining submodule for determining target boundary information that matches the type, wherein the target boundary information is used to represent the electrical characteristics at the node; and a second determining submodule for determining the target differential model based on the target boundary information.

[0119] Optionally, the second determining submodule can determine the target difference model based on the target boundary information by performing the following steps: adjusting the initial difference model according to the target boundary information to obtain the target difference model.

[0120] Optionally, the prediction unit 403 may include: a third determining module for determining the resistance and capacitance in the power system; an input module for inputting the resistance and capacitance into the target differential model; and a prediction module for predicting the attributes in the target differential model to obtain attribute prediction results.

[0121] Optionally, the impedance branch may include: a first impedance branch, a second impedance branch, and a third impedance branch, wherein the direction of the first impedance branch is perpendicular to the direction of the second impedance branch and the direction of the third impedance branch, the direction of the second impedance branch is perpendicular to the direction of the first impedance branch and the direction of the third impedance branch, and the direction of the third impedance branch is perpendicular to the direction of the first impedance branch and the direction of the second impedance branch.

[0122] In this embodiment, the acquisition unit is used to acquire the conductive medium to which the leakage current flows in the power system; the determination unit is used to determine the target differential model of the node based on at least one node among multiple impedance branches to which the conductive medium flows, wherein the target differential model is used to at least represent the mapping relationship between the current flowing through each of the multiple impedance branches and the voltage of each of the multiple impedance branches; the prediction unit is used to predict the attributes of the leakage current in the process of flowing into the conductive medium using the target differential model, and obtain the attribute prediction result, wherein the attribute prediction result includes at least the circuit range through which the leakage current flows into the conductive medium, and the impact of the leakage current on the power system in the process of flowing into the conductive medium. This achieves the purpose of accurately capturing the true characteristics of the current in the conductive medium, thereby solving the technical problem of low accuracy in the prediction of the attributes of the current in the conductive medium, and thus achieving the technical effect of improving the accuracy of the prediction of the attributes of the current in the conductive medium.

[0123] According to an embodiment of the present invention, a processor is also provided for running a program, wherein the program is executed by the processor to perform the current property prediction method in the conductive medium of the embodiment.

[0124] According to an embodiment of the present invention, an electronic device is also provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the method for predicting the properties of current in a conductive medium as described in the embodiment.

[0125] According to another aspect of the present invention, a computer-readable storage medium is also provided. The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the computer-readable storage medium to perform the current property prediction method in the conductive medium described in the embodiments.

[0126] According to an embodiment of the present invention, a computer program product is also provided, the computer program product including a computer program, wherein when the computer program is executed by a processor, it implements the method for predicting the properties of current in a conductive medium in the embodiments.

[0127] According to an embodiment of the present invention, a computer program product is also provided, including a non-volatile computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the method for predicting the properties of current in a conductive medium as described in the embodiments.

[0128] According to an embodiment of the present invention, a computer program is also provided, which, when executed by a processor, implements the method for predicting the properties of current in a conductive medium as described in the embodiments.

[0129] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0130] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0131] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0132] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0133] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0134] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to related technologies, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0135] The above are merely preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method of predicting properties of an electric current in a conducting medium, characterized by, The method comprises: obtaining a conductive medium to which a leakage current in a power system flows; determining a target differential model of at least one node in a plurality of impedance branches through which the conductive medium flows, wherein the target differential model is used to at least represent a mapping relationship between a current flowing through each of the plurality of impedance branches and a voltage of each of the plurality of impedance branches; using the target differential model to predict a property of the leakage current in a process of flowing to the conductive medium, to obtain a property prediction result, wherein the property prediction result at least includes a circuit range passed by the leakage current in the process of flowing to the conductive medium, and an influence result of the leakage current on the power system in the process of flowing to the conductive medium; wherein, based on at least one node in a plurality of impedance branches through which the conductive medium flows, determining a target differential model of the node comprises: determining a type of the node; determining target boundary information matched with the type, wherein the target boundary information is used to represent an electrical characteristic at the node; and adjusting an initial differential model according to the target boundary information to obtain the target differential model, wherein the initial differential model is determined by the following formulas (1) to (10), substituting formula (6) into formulas (2), (3) and (4) to obtain three differential equations of the node shown in formulas (7), (8) and (9), and converting formula (5) to obtain formula (10): I x(i,j,k) (t)+I y(i,j,k) (t)+I z(i,j,k) (t)=I x(i-1,j,k) (t)+I y(i,j-1,k) (t)+I z(i,j,k-1) (t)+I in (t)(5) I x(i,j,k) [n]+I y(i,j,k) [n]+I z(i,j,k) [n]=I x(i-1,j,k) [n]+I y(i,j-1,k) [n]+I z(i,j,k-1) [n]+I in [n](10) where U (i,j,k) I x(i,j,k) , I y(i,j,k) , and I z(i,j,k) are used to represent the current flowing into three impedance branches, where a (i+1,j,k) , U (i,j+1,k) , and U (i,j,k+1) are used to represent the node voltage of the adjacent cell, I x(i-1,j,k) , I y(i,j-1,k) , and I z(i,j,k-1) are used to represent the impedance branch current of the adjacent cell, I in is used to represent the current injected from outside into this node, if this node is a passive node, then I in (t) = 0; z is used to represent a complex variable; n is used to represent the count of sampling time points.

2. The method of claim 1, wherein, using the target differential model to predict a property of the leakage current in a process of flowing to the conductive medium, to obtain a property prediction result, comprises: determining a resistance and a capacitance in the power system; inputting the resistance and the capacitance into the target differential model; predicting the property in the target differential model to obtain the property prediction result.

3. The method of any one of claims 1-2, wherein, The impedance branches comprise: a first impedance branch, a second impedance branch and a third impedance branch, a direction in which the first impedance branch is located is perpendicular to a direction in which the second impedance branch is located and perpendicular to a direction in which the third impedance branch is located, the direction in which the second impedance branch is located is perpendicular to the direction in which the first impedance branch is located and perpendicular to the direction in which the third impedance branch is located, and the direction in which the third impedance branch is located is perpendicular to the direction in which the first impedance branch is located and perpendicular to the direction in which the second impedance branch is located.

4. An attribute prediction device of a current in a conductive medium, characterized by, The method comprises: an obtaining unit configured to obtain a conductive medium to which a leakage current in a power system flows; a determining unit configured to determine a target differential model of at least one node in a plurality of impedance branches through which the conductive medium flows, wherein the target differential model is used to at least represent a mapping relationship between a current flowing through each of the plurality of impedance branches and a voltage of each of the plurality of impedance branches; A prediction unit is configured to predict, by using the target differential model, an attribute of the leakage current in a process of flowing to the conductive medium, to obtain an attribute prediction result, wherein the attribute prediction result at least includes a circuit range passed by the leakage current in the process of flowing to the conductive medium, and an influence result of the leakage current on the power system in the process of flowing to the conductive medium. The prediction unit is configured to determine the target differential model of at least one node in the plurality of impedance branches of the conductive medium based on the node by performing the following steps, including: determining a type of the node; determining target boundary information matched with the type, wherein the target boundary information is used to represent an electrical characteristic at the node; and adjusting an initial differential model according to the target boundary information to obtain the target differential model, wherein the initial differential model is determined by the following formulas (1) to (10), the formula (6) is substituted into the formulas (2), (3) and (4) to obtain three differential equations of the node shown in the following formulas (7), (8) and (9), and the formula (5) is converted to obtain the following formula (10): I x(i,j,k) (t)+I y(i,j,k) (t)+I z(i,j,k) (t)=I x(i-1,j,k) (t)+I y(i,j-1,k) (t)+I z(i,j,k-1) (t)+I in (t)(5) I x(i,j,k) [n]+I y(i,j,k) [n]+I z(i,j,k) [n]=I x(i-1,j,k) [n]+I y(i,j-1,k) [n]+I z(i,j,k-1) [n]+I in [n](10) where U (i,j,k) I x(i,j,k) , I y(i,j,k) and I z(i,j,k) are used to represent the current flowing into three impedance branches, where a (i+1,j,k) , U (i,j+1,k) and U (i,j,k+1) are used to represent the node voltage of adjacent cells, I x(i-1,j,k) , I y(i,j-1,k) and I z(i,j,k-1) are used to represent the impedance branch current of adjacent cells, I in is used to represent the current injected from outside into this node, if this node is a passive node, then I in (t) = 0; z is used to represent a complex variable; n is used to represent the count of sampling time points.

5. A processor, comprising: The processor is configured to run a program, wherein the program is executed by the processor to perform the attribute prediction method of the current in the conductive medium.

6. An electronic device, comprising: Comprise: A memory storing an executable program; The processor is configured to run a program, wherein the program is executed by the processor to perform the attribute prediction method of the current in the conductive medium.

7. A computer-readable storage medium, characterized in that, The computer readable storage medium comprises a stored executable program, wherein the executable program controls the device where the storage medium is located to perform the attribute prediction method of the current in the conductive medium when the executable program is run.

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