Substation multi-physics field digital reconstruction modeling method and system

Abstract

The invention discloses a substation multi-physics field digital reconstruction modeling method and system, and the method comprises the steps: completing the point location measurement based on radial basis function interpolation, restoring an inversion model of a multi-physics field region value, and taking a point location measurement result of power equipment as the input of the multi-physics field inversion model; meanwhile, performing inversion calculation on internal parameter distribution of the power equipment by combining the three-dimensional reconstruction model of the point cloud data of the transformer substation; and constructing a power equipment full-space information three-dimensional model, inputting an inversion calculation result into the three-dimensional model to realize substation multi-physics field digital reconstruction, and performing zoning and grading evaluation on the state of the power equipment through the power equipment full-space information three-dimensional model.

Description

Background Art

[0002] In the field of power equipment, due to the complex spatial structure and large number of power equipment, the method of manual regular inspection is mostly used to collect the operation data of the equipment at present. However, with the manual inspection method, it is very difficult to monitor and diagnose the problems of the equipment in real time. Moreover, when the equipment has abnormalities or failures, due to the slow acquisition and transmission speed, it is impossible to determine the area and specific location where the fault occurs in time, which will have a great impact on the maintenance and reliability of the power system. Timely monitoring of the temperature field, humidity field, electromagnetic field, and voltage field in the substation plays an important role in avoiding serious accidents. At present, a large number of sensing devices usually need to be arranged for parameters such as the ambient temperature and humidity of the substation, which is not convenient for installation and maintenance. The traditional detection method cannot realize spatial positioning of the measured data points and can only reflect the information on the surface of the equipment, and cannot reflect the spatial distribution characteristics of the internal temperature distribution field, electric field distribution, etc. of the equipment. At the same time, there are dynamic interaction effects among the temperature field, humidity field, electromagnetic field, and voltage field reflected by the power equipment. The traditional measurement method can only measure the temperature field, humidity field, electromagnetic field, and voltage field independently in sequence and is difficult to measure simultaneously. For this reason, a digital reconstruction modeling method for multi-physical fields in a substation is proposed. Based on the accurate three-dimensional reconstruction of the substation, a reconstruction model of multi-physical parameters is established to obtain the multi-physical field distribution of the substation, and then the environmental physical field distribution of the substation is comprehensively monitored.

[0003] Due to the complex structure of the substation, the traditional 3D mapping technology requires specialized operation and maintenance personnel to manually collect data, with a large data fusion difficulty and very low efficiency, requiring manual intervention and being difficult to accurately discover potential hidden dangers and fault problems. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a digital reconstruction modeling method and system for multi-physical fields in a substation in view of the above-mentioned deficiencies in the prior art, to solve the technical problems of electromagnetic interference and poor environmental reliability in the substation, improve the working stability of sensors and sensor networks, and draw a digital twin map of the substation according to the multi-physical fields in the substation by zoning and grading.

[0005] The present invention adopts the following technical solutions: A digital reconstruction modeling method for multi-physical fields in a substation includes the following steps: S1. Establish a coupled calculation model for power equipment, and obtain the field distribution of physical quantities through coupled calculation; S2. Based on the field distribution of physical quantities obtained in step S1, establish a multi-physical scene inversion model for restoring the quantity values of multi-physical field regions by radial basis function interpolation, and perform inversion calculation on the internal parameter distribution of power equipment in combination with the three-dimensional reconstruction model of the substation point cloud data; S3. Construct a three-dimensional model of the full-space information of power equipment; S4. Input the results of the inversion calculation in step S2 into the three-dimensional model of the full-space information of power equipment constructed in step S3 to achieve the digital reconstruction of the multi-physical fields of the substation, and perform zonal and hierarchical assessment of the state of the power equipment through the three-dimensional model of the full-space information of power equipment.

[0006] Preferably, in step S1, the specific method for establishing the coupled calculation model of power equipment is as follows: Build a coupling model that characterizes the multi-physical field characteristics for the characteristic parameters of power equipment, and at the same time extract the corresponding multi-physical field information based on this model to establish a database; then based on the substation electrical model and measured signals, input the time-series data of the measurement points into the established coupling model and / or database by establishing boundary conditions; finally, use the coupling model for calculation to obtain the physical quantity field distribution.

[0007] Preferably, in step S2, introduce the Hermite-type radial basis function for data interpolation and inversion calculation, specifically as follows: First, obtain the point measurement parameters of the key area through on-site measurement, including power frequency electromagnetic fields and various electromagnetic transient signals. Based on the radial basis function, perform surface interpolation calculation on the measured point data to inversely obtain the surface distribution based on the point measurement parameters; Finally, combine the three-dimensional reconstruction model of the substation point cloud data and the electrical model to perform simulation calculations on the power frequency electromagnetic fields and transient electromagnetic signals in the substation area.

[0008] Preferably, the solution of the differential equation based on the radial basis function collocation is specifically as follows: Basis function setting: According to the specific situation of the complex electromagnetic environment of the substation, determine the number of basis functions, and set the RBF center and shape parameters; Determine the weights: According to the interpolation conditions and basis functions, use the least squares method to obtain the weight coefficients of each point measurement value; Interpolation process: After obtaining the interpolation equation, calculate the interpolation at any place according to the calculation to obtain the regional quantity value, and obtain the distribution and magnitude of each characteristic parameter through mathematical fitting means.

[0009] Preferably, the RBF center is set at the interpolation nodes or randomly distributed in the interpolation area. Let the number of interpolation nodes be N and the number of RBFs be M.

[0010] Preferably, in step S2, the three-dimensional reconstruction model of the substation point cloud data is specifically as follows: First, divide the substation area according to the voltage level and the types of in-service equipment; Then select the scanning points. When the radius of the scanning area is greater than the point measurement step size, directly model, otherwise re-divide the area and then model; Finally, after denoising and stitching the substation point cloud data, the reconstruction of the three-dimensional reconstruction model is completed.

[0011] Preferably, for the three-dimensional point cloud recognition of substation equipment, the subspaces are divided according to the characteristics of the points, and the characteristics of the subspaces are extracted to form feature vectors. The cosine value of the angle between the line connecting the centroid of the entire point cloud and the centroid of each subspace point cloud relative to the positive direction of the Z-axis is used as the subspace feature of the point cloud; kNN is used to obtain the classification result, and the PSO algorithm is used to optimize the coefficient weights of each subspace feature.

[0012] Preferably, the specific optimization of the coefficient weights of each subspace feature using the PSO algorithm is as follows: First, initialize the example, calculate the classification error rate, update the particle position and velocity. When the maximum number of iterations is reached, output the subspace weights of the optimal solution. When the maximum number of iterations is not reached, return to recalculate the classification error rate.

[0013] Preferably, when using the PSO algorithm to optimize the feature weights, the classification error rate is defined as the fitness function, and the final position of the particle represents the weight of the corresponding feature.

[0014] In a second aspect, an embodiment of the present invention provides a substation multi-physical field digital reconstruction modeling system, including: A coupling module that establishes a coupling calculation model for power equipment and obtains the physical quantity field distribution through coupling calculation; An inversion module that establishes a multi-physical scenario inversion model for restoring the multi-physical field region values of point position measurements based on the obtained physical quantity field distribution using radial basis function interpolation, and performs inversion calculation on the internal parameter distribution of power equipment in combination with the three-dimensional reconstruction model of substation point cloud data; A construction module that constructs a three-dimensional model of the full-space information of power equipment; A reconstruction module that inputs the results of the inversion calculation into the constructed three-dimensional model of the full-space information of power equipment to achieve the digital reconstruction of the substation multi-physical field, and performs zoning and grading evaluation on the state of power equipment through the three-dimensional model of the full-space information of power equipment.

[0015] In a third aspect, a computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned substation multi-physical field digital reconstruction modeling method are implemented.

[0016] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium including a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned substation multi-physical field digital reconstruction modeling method are implemented.

[0017] Compared with the prior art, the present invention has at least the following beneficial effects: A digital reconstruction modeling method for multi-physical fields in a substation, based on coupled simulation and point measurements, and at the same time, through inversion, the simulation calculation is compared with the measured values, and the physical quantity field distribution is gradually corrected and iterated to obtain a more accurate one.

[0018] Furthermore, since the point measurement values obtained from distributed sensing are limited, establishing a coupled calculation model of power equipment is the basis and comparison object for correcting and iterating the inversion calculation results of the measured values, that is, on the basis of the quantity value distribution obtained from the simulation calculation of the established coupled calculation model of power equipment, the inversion calculation is carried out through point measurements for correction, and finally a more credible physical quantity field distribution is obtained.

[0019] Furthermore, common RBFs include Gauss function, Multiquadric (MQ) function and thin plate spline function. To avoid the singularity problem caused by using polynomial basis interpolation method, the radial basis function is used to form the shape function of the radial point interpolation method (RPIM) for the meshless method. Radial basis function interpolation can be divided into interpolation with polynomial basis and interpolation without polynomial basis. When using the above radial basis function interpolation to solve differential equations with Neumman boundary conditions (giving the function values at nodes and the first derivative values at boundary nodes), large errors will occur, and at this time, Hermite-type radial basis function interpolation can be used.

[0020] Furthermore, on the basis of Hermite-type radial basis function interpolation, set the RBF center and shape parameters, including the number of basis functions (corresponding to the number of terms of the basis function in the approximation formula), the setting of the center position and shape parameters; the collocation point setting mainly refers to the selection of the node positions used in the collocation method. Usually in the implementation process, appropriate nodes are first set in the solution domain and on the boundary, and then these nodes are used as both the center points and collocation points of the basis function, and the interpolation calculation is carried out by determining the weights to make the whole process converge quickly.

[0021] Furthermore, due to the diverse structures and types of substation equipment, and at the same time, transformers, switch-type equipment all have their own different sensing equipment, so only through reasonable area division, site selection and recording can the operation process be ensured to proceed orderly and effectively. As the basis of the whole link, model reconstruction is to realize efficient modeling of the substation, and at the same time, the physical quantity field distribution needs to be combined with the actual model of the in-service power equipment. Based on the substation point cloud data, the power equipment model can be obtained, and on this basis, the three-dimensional reconstruction of the physical quantity field distribution is carried out.

[0022] Furthermore, the PSO algorithm is a heuristic algorithm based on swarm intelligence and a global evolutionary algorithm used to solve multi-objective, non-linear, and multi-variable problems. The PSO algorithm iteratively initializes particles, updates the positions and velocities of the particles, and tracks the optimal particles in the space to find the optimal solution. The condition for stopping the iteration is usually whether the target iteration number is reached. When using the PSO algorithm to optimize the weights of features in each subspace, the classification error rate is defined as the fitness function, and the final position of the particle represents the weight of the corresponding feature.

[0023] It can be understood that the beneficial effects of the second aspect can be referred to the relevant descriptions in the first aspect above, and will not be elaborated here.

[0024] In summary, the present invention establishes a coupled calculation model of power equipment based on the finite volume strategy to perform coupled calculations on the multi-physical fields of power equipment; establishes a multi-physical field inversion model according to the coupled calculation results, and uses the surface temperature of the power equipment as the input of the multi-physical field inversion model to perform parameter inversion on the electromagnetic, fluid, and temperature fields of the power equipment; performs inversion calculations on the internal parameter distribution of the power equipment according to the parameter inversion results and corrects the coupled calculation results; constructs a three-dimensional model of the full-space information of the power equipment based on the three-dimensional automatic reconstruction technology, inputs the inversion calculation results into the three-dimensional model of the full-space information of the power equipment, and evaluates the state of the power equipment through the three-dimensional model of the full-space information of the power equipment.

[0025] The technical solutions of the present invention will be further described in detail below with reference to the drawings and embodiments. Description of the Drawings

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings to be used in the following description of the embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0027] Figure 1 It is a flowchart of the particle swarm optimization algorithm; Figure 2 It is a flowchart of the three-dimensional model reconstruction of the substation; Figure 3 It is a flowchart of the method for digital reconstruction and modeling of the multi-physical fields of the substation; Figure 4 It is a schematic diagram of the development plan of the digital reconstruction and sub-region and sub-level evaluation system of the multi-physical fields of the substation; Figure 5Schematic diagram of a computer device provided by an embodiment of the present invention; Figure 6 Block diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0028] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0029] In the description of the present invention, it should be understood that the terms "include" and "comprise" indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0030] It should also be understood that the terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0031] It should be further understood that the term " / and" as used in the specification of the present invention and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in the present invention generally represents an "or" relationship between the contextually related objects.

[0032] It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present invention to describe preset ranges, etc., these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0033] Depending on the context, as used herein, the word "if" can be interpreted as "when" or "while" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detecting (stated condition or event)" can be interpreted as "when determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)".

[0034] Various schematic structural diagrams according to the disclosed embodiments of the present invention are shown in the accompanying drawings. These figures are not drawn to scale, where for the purpose of clear expression, some details are enlarged and some details may be omitted. The shapes of various regions and layers shown in the figures, as well as their relative sizes and positional relationships, are merely exemplary and may deviate in practice due to manufacturing tolerances or technical limitations. And those skilled in the art can design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0035] The present invention provides a method for digital reconstruction and modeling of multi - physical fields in a substation. Based on radial basis function interpolation, an inversion model for multi - physical scenarios that restores the "regional" quantity values of multi - physical fields from "point - position" measurements is completed, and the measurement results of the power equipment point - positions are used as the input of the multi - physical field inversion model. At the same time, combined with the three - dimensional reconstruction model of the substation point cloud data, the inversion calculation of the internal parameter distribution of the power equipment is carried out; Construct a three - dimensional model of the full - space information of the power equipment, input the results of the inversion calculation into the three - dimensional model of the full - space information of the power equipment, realize the digital reconstruction of the multi - physical fields in the substation, and evaluate the state of the power equipment in a zoned and hierarchical manner through the three - dimensional model of the full - space information of the power equipment.

[0036] Please refer to Figure 3 , a method for digital reconstruction and modeling of multi - physical fields in a substation according to the present invention, includes the following steps: S1. Establish a coupled calculation model for the power equipment, and obtain the distribution of the physical quantity field through coupled calculation; First, build a coupled model that characterizes the multi - physical field characteristics for the characteristic parameters of the power equipment, and at the same time extract the multi - physical field information based on this model to establish a database; Then, based on the substation electrical model and measured signals, input the time - series data of the measurement points into the established coupled model and / or database by establishing boundary conditions; Finally, use the coupled model for calculation to obtain the coupled calculation model of the power equipment.

[0037] S2. Based on the physical quantity field distribution obtained in step S1, establish a multi-physical scenario inversion model for restoring the quantity values in the multi-physical field region by radial basis function interpolation, and perform inversion calculations on the internal parameter distribution of power equipment in combination with the three-dimensional reconstruction model of substation point cloud data; Based on the actual working conditions of the substation, introduce the Hermite-type radial basis function for data interpolation and inversion calculations; the specific method is as follows: First, obtain the "point" position measurement parameters of the key area through on-site measurement, including power frequency electromagnetic fields and various electromagnetic transient signals. Based on the radial basis function, the measured "point" data is calculated by surface interpolation. The solution of the differential equation based on the collocation points of the radial basis function and the RBF surface interpolation method can be summarized as the following steps: Basis function setting: According to the specific situation of the complex electromagnetic environment in the substation, determine the number of basis functions, and set the RBF center and shape parameters. The RBF center can be set at the interpolation nodes or randomly distributed within the interpolation area. To illustrate the principle and process of radial basis function interpolation, assume the number of interpolation nodes is N and the number of RBFs is M.

[0038] Determine the weights: According to the interpolation conditions and basis functions, use the least squares method to obtain the weight coefficients of each position measurement value.

[0039] Interpolation process: After obtaining the interpolation equation, the interpolation at any point can be calculated. Obtain the regional quantity values, and obtain the distribution and magnitude of each characteristic parameter through mathematical fitting means.

[0040] Finally, in combination with the three-dimensional reconstruction model and electrical model of the substation point cloud data, perform simulation calculations on the power frequency electromagnetic field and transient electromagnetic signals in the substation area. At the same time, substitute the restored regional quantity values into the substation electrical model, correct the numerical values of the substation electrical model, and perform simulation calculations on the power frequency electromagnetic field and transient electromagnetic signals in the substation area again to obtain the distribution of characteristic quantity values.

[0041] To check whether the model quality is qualified, it is necessary to evaluate the quality of the three-dimensional reconstruction model of the substation point cloud data.

[0042] The reconstruction quality evaluation of the three-dimensional reconstruction model of substation point cloud data is mainly divided into 4 aspects: Appearance similarity, model integrity, dimension accuracy, and operability of simplification.

[0043] Based on the completion of point cloud data recognition and extraction, a 3D reconstruction of the substation is carried out. For the 3D point cloud recognition of substation equipment, the subspaces are divided according to the characteristics of the points, and the characteristics of the subspaces are extracted to form feature vectors. The cosine value of the angle between the line connecting the centroid of the entire point cloud and the centroid of each subspace point cloud relative to the positive direction of the Z-axis is selected as the subspace feature of the point cloud. The kNN is used to obtain the classification result, and the PSO algorithm is used to optimize the coefficient weights of each subspace feature. The process is as Figure 1 shown: First, initialize the example, calculate the classification error rate, update the particle position and velocity. When the maximum number of iterations is reached, output the optimal solution, which is the subspace weight. When the maximum number of iterations is not reached, return to recalculate the classification error rate.

[0044] Among them, by adjusting the coefficient weights of each subspace feature, the accuracy of feature recognition and classification is improved. When using PSO to optimize the feature weights, the classification error rate is defined as the fitness function, and the final position of the particle represents the weight of the corresponding feature.

[0045] Due to the diverse structures and types of substation equipment, and at the same time, transformers, switches and other equipment all have their own different sensing equipment, only through reasonable area division, site selection and recording can the operation process be ensured to proceed orderly and effectively.

[0046] Please refer to Figure 2 , as the basis of the whole link, for the realization of efficient substation modeling, the process and method of model reconstruction are determined as follows: First, divide the substation area according to the voltage level and the types of in-service equipment; Among them, substations are divided into low-voltage substations, medium-voltage substations and high-voltage substations according to the voltage level. Substations with different voltage levels have different safety requirements and management measures. According to the types of in-service equipment, such as transformers, circuit breakers, disconnectors, the substation is divided into different functional areas.

[0047] Then select the scanning points, and judge whether the radius of the scanning area is greater than the point measurement step. If it is greater, directly model; otherwise, carry out area division and then model; Among them, the radius of the scanning area is the maximum distance from the scanning point that can effectively collect data. The point measurement step is the distance between each measurement point during the data collection process. If the radius of the scanning area is greater than the point measurement step, it means that the entire scanning area can be covered by fewer measurement points; conversely, if the radius of the scanning area is less than the point measurement step, more measurement points are required to ensure the integrity of the data.

[0048] Finally, after noise reduction processing and stitching processing of the data, the model reconstruction is completed.

[0049] Remove noise and outliers in the model through noise reduction processing to improve the accuracy and aesthetics of the model. Common noise reduction methods include: filtering algorithms and morphological operations.

[0050] Stitch multiple local models into a complete model through stitching processing. Since in practical applications, the substation area may be large, data needs to be collected and models constructed at multiple scanning points respectively. The key to stitching processing lies in finding the corresponding relationships between local models and accurately stitching them together. Common stitching methods include: feature-based stitching and optimization-based stitching.

[0051] S3. Construct a three-dimensional model of the full-space information of power equipment; divide the calculation area into grids and ensure that each grid point has a non-overlapping control volume around it; integrate the differential equation to be solved (control equation) for each control volume to obtain a set of discrete equations; the unknowns are the dependent variables at the grid points; in order to calculate the integral of the control volume, the variation law of the dependent variable values between grid points must be assumed. In short, the subdomain method plus discretization is the finite volume strategy. Through the finite volume method, the multi-physical fields of power equipment are coupled and calculated to increase the coupling relationship, and the internal state of power equipment is accurately evaluated by performing inversion calculations on the unobservable operating parameters inside the power equipment. Finally, a three-dimensional model of the full-space information of power equipment is constructed based on the three-dimensional automatic reconstruction technology.

[0052] S4. Input the results of the inversion calculation in step S2 into the three-dimensional model of the full-space information of power equipment constructed in step S3 to realize the digital reconstruction of the multi-physical fields of the substation, and evaluate the state of the power equipment in zones and levels through the three-dimensional model of the full-space information of power equipment.

[0053] Obtain the topological information and component types of the substation by parsing the SCD file. After obtaining the topological information and component types of the substation, input the simulation model of each component through Excel; use the topological information, component types, and simulation models of the components of the substation to automatically generate a simulation file according to the syntax rules of the simulation file, and call the kernel of each physical field module to run the simulation file to realize the automatic modeling and simulation of the multi-physical fields of the substation.

[0054] Judge the fault type according to the equipment state evaluation results, quickly locate the fault point and evaluate the fault risk through the digital reconstruction model of the multi-physical fields of the substation; perform regional and hierarchical modeling on the equipment of the digital model of the multi-physical fields of the substation; perform hierarchical modeling on the modeling object and then perform refined modeling on the key parts.

[0055] Those skilled in the art can understand that various aspects of the present invention can be implemented as a system, a method, or a program product. Therefore, various aspects of the present invention can be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation combining hardware and software aspects, which can be collectively referred to as "circuits", "modules", or "platforms".

[0056] In another embodiment of the present invention, a substation multi-physical field digital reconstruction and modeling system is provided. This system can be used to implement the above-mentioned substation multi-physical field digital reconstruction and modeling method. Specifically, the substation multi-physical field digital reconstruction and modeling system includes a coupling module, an inversion module, a construction module, and a reconstruction module.

[0057] Among them, the coupling module establishes a coupling calculation model for power equipment, and obtains the physical quantity field distribution through coupling calculation. The inversion module establishes a multi-physical scenario inversion model for restoring the quantity values of multi-physical field areas based on point position measurement by radial basis function interpolation based on the obtained physical quantity field distribution, and performs inversion calculation on the internal parameter distribution of power equipment in combination with the three-dimensional reconstruction model of substation point cloud data. The construction module constructs a three-dimensional model of the full-space information of power equipment. The reconstruction module inputs the result of the inversion calculation into the constructed three-dimensional model of the full-space information of power equipment to realize the digital reconstruction of the substation multi-physical field, and evaluates the state of power equipment in a partitioned and hierarchical manner through the three-dimensional model of the full-space information of power equipment.

[0058] In another embodiment of the present invention, a terminal device is provided. The terminal device includes a processor and a memory. The memory is used to store a computer program, and the computer program includes program instructions. The processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of the substation multi-physical field digital reconstruction and modeling method, including: Establish a coupled calculation model for power equipment, and obtain the distribution of the physical quantity field through coupled calculation; based on the obtained distribution of the physical quantity field, establish an inversion model for multi-physical scenarios to restore the quantity values of multi-physical fields at points through radial basis function interpolation, and perform inversion calculation on the internal parameter distribution of power equipment in combination with the three-dimensional reconstruction model of substation point cloud data; construct a three-dimensional model of the full-space information of power equipment; input the results of the inversion calculation into the constructed three-dimensional model of the full-space information of power equipment to realize the digital reconstruction of multi-physical fields in the substation, and perform zonal and hierarchical evaluation of the state of power equipment through the three-dimensional model of the full-space information of power equipment.

[0059] In another embodiment of the present invention, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in a terminal device, used to store programs and data. It can be understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device, and of course, can also include the extended storage medium supported by the terminal device. It can be any tangible medium containing or storing a program, and this program can be used by or in combination with an instruction execution system, device or component. The computer-readable storage medium provides a storage space, and this storage space stores the operating system of the terminal. And, in this storage space, one or more instructions suitable for being loaded and executed by the processor are also stored, and these instructions can be one or more computer programs (including program codes). It should be noted that more specific examples (non-exhaustive list) of the computer-readable storage medium here include: electrical connections with one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0060] The computer-readable storage medium also includes data signals propagated in the baseband or as part of a carrier wave, which carry the readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium can also be any readable medium other than the readable storage medium, and this readable medium can send, propagate or transmit a program for use by or in combination with an instruction execution system, device or component. The program code contained on the readable storage medium can be transmitted by any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination of the above.

[0061] The program code for performing the operations of the present invention can be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., and also including conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, executed as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., by connecting through the Internet using an Internet service provider).

[0062] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the substation multi-physical field digital reconstruction modeling method in the above embodiments; the one or more instructions in the computer-readable storage medium are loaded and executed by the processor to perform the following steps: Establish a coupled calculation model of power equipment, and obtain the physical quantity field distribution through coupled calculation; based on the obtained physical quantity field distribution, establish a multi-physical scene inversion model for restoring the quantity values of multi-physical field areas based on radial basis function interpolation, and perform inversion calculation on the internal parameter distribution of power equipment in combination with the three-dimensional reconstruction model of substation point cloud data; construct a three-dimensional model of the full-space information of power equipment; input the results of the inversion calculation into the constructed three-dimensional model of the full-space information of power equipment to realize the digital reconstruction of the substation multi-physical field, and perform zoning and grading evaluation of the state of power equipment through the three-dimensional model of the full-space information of power equipment.

[0063] Please refer to Figure 5 , the terminal device is a computer device. The computer device 60 in this embodiment includes: a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When the computer program 63 is executed by the processor 61, it implements the substation multi-physical field digital reconstruction modeling method in the embodiment. To avoid repetition, it will not be elaborated here one by one. Alternatively, when the computer program 63 is executed by the processor 61, it implements the functions of each model / unit in the substation multi-physical field digital reconstruction modeling system in the embodiment. To avoid repetition, it will not be elaborated here one by one.

[0064] The computer device 60 can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The computer device 60 can include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art can understand that Figure 5This is only an example of the computer device 60, which does not constitute a limitation on the computer device 60. It may include more or fewer components than those shown in the figure, or combine certain components, or have different components. For example, the computer device may also include input / output devices, network access devices, buses, etc.

[0065] The so-called processor 61 may be a central processing unit (CPU), or may also be other general-purpose processors, central processors, graphics processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, data processing logic devices based on quantum computing, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0066] The memory 62 may be an internal storage unit of the computer device 60, such as the hard disk or memory of the computer device 60. The memory 62 may also be an external storage device of the computer device 60, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device 60.

[0067] Furthermore, the memory 62 may also include both an internal storage unit and an external storage device of the computer device 60. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 may also be used to temporarily store data that has been output or is to be output.

[0068] In each of the embodiments provided in the present application, any reference to a memory, a database, or other media may include at least one of non-volatile and volatile memories. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0069] In each of the embodiments provided in the present application, the database involved may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., without limitation. In each of the embodiments provided in the present application, the processor involved may be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without limitation.

[0070] Please refer to Figure 6 , the terminal device is an electronic device 600, and the electronic device is presented in the form of a general computing device. The components of the electronic device may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including the storage unit 620 and the processing unit 610), a display unit 640, etc.

[0071] Among them, the storage unit stores program code, and the program code can be executed by the processing unit 610, so that the processing unit 610 executes the steps according to various exemplary embodiments of the present invention described in the above method part of this specification. For example, the processing unit 610 can execute steps as shown in Figure 3 .

[0072] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 6201 and / or a cache storage unit 6202, and may further include a read-only storage unit (ROM) 6203.

[0073] The storage unit 620 may also include a program / utilities 6204 having a set (at least one) of program modules 6205. Such program modules 6205 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment.

[0074] The bus 630 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of a variety of bus structures.

[0075] The electronic device 600 may also communicate with one or more external devices 700 (such as a keyboard, a pointing device, a Bluetooth device, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 600, and / or may communicate with any device that enables the electronic device 600 to communicate with one or more other computing devices (such as a router, a modem, etc.). Such communication may be through an input / output (I / O) interface 650. Also, the electronic device 600 may communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 through the bus 630. It should be understood that although not shown in the figures, other hardware and / or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0076] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Generally, the components described and shown in the accompanying drawings here may be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0077] Please refer to Figure 4 , based on the digital reconstruction modeling method of multi - physical fields in substations and the typical multi - physical field feature zoning and grading method, construct a multi - physical field zoning and grading model for substations; study the evaluation method of the impact of multi - physical fields in substations on in - service equipment under different zoning and grading; develop a multi - physical field feature zoning and grading evaluation system for substations to achieve the zoning and grading evaluation of multi - physical fields in substations.

[0078] 1) Substation multi - physical field zoning and grading model.

[0079] Establish a modular circuit model of substation equipment, study the digital construction and connection methods of the circuit model of substation equipment, combine the propagation algorithm of multi - physical fields in and around substation equipment, study the construction method of the multi - physical field zoning and grading mathematical model of modular substation equipment, and establish a modular - docking building - block - type multi - physical field zoning and grading model for substations according to different on - site equipment connection methods.

[0080] 2) Evaluation methods for different in - service equipment in substations under multi - physical field zoning and grading.

[0081] First, according to the distribution of different physical fields on and near different in - service equipment in substations, combined with the functions and types of sensors, systematically sort out the positions suitable for installing sensors on and near in - service equipment.

[0082] Combined with the existing industry standards for the limit values of electric field intensity and magnetic field intensity of electronic equipment under different industrial grades, further divide and limit the sensor installation positions.

[0083] Finally, under the framework of the digital reconstruction model of multi - physical fields in substations, predict the intensity thresholds of typical characteristic quantities of multi - physical fields in substations, and propose equipment - level evaluation methods and bases for in - service equipment under multi - physical field zoning and grading.

[0084] 3) Development of the multi - physical field feature zoning and grading evaluation system for substations First, conduct intelligent simulation processing on the modular - docking building - block - type multi - physical field zoning and grading model of substations, and process the simulation results: compare the simulation results of different working modes to obtain the characteristic quantities of typical multi - physical field parameters; Conduct time - frequency analysis on the simulation results to obtain the time - frequency spectrum, and obtain the amplitude, frequency distribution, energy contained in the typical parameters and the corresponding physical field influence sources by comparing the time - frequency spectra; Then, for the actual working conditions of different types of substations, carry out research on the zoning and grading evaluation methods and bases for station - level multi - physical field characteristics, and develop a multi - physical field feature zoning and grading evaluation system integrating equipment - level and station - level for substations.

[0085] In summary, for a method and system for digital reconstruction and modeling of multiple physical fields in a substation, aiming at the pain points of reliability assessment of sensors and sensor networks in the construction process of smart substations, first, taking the in-operation equipment in the substation as the research object, a coupled simulation model based on the characteristic distribution, magnitude, coupling relationship, and correlation analysis of multiple physical fields is constructed; then, based on the measured values of the distributed synchronous measurements at the substation, the inversion calculation of the multiple physical fields in the substation is completed and the coupled simulation results are corrected; finally, based on the 3D model of the substation, the zonal and hierarchical assessment of the physical quantity field distribution in the substation is carried out.

[0086] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above-mentioned division of each functional unit and module is used as an example. In actual applications, the above-mentioned functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working processes of the units and modules in the above system can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0087] In the above embodiments, the descriptions of the various embodiments have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0088] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this invention can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this invention.

[0089] In the embodiments provided by the present invention, it should be understood that the disclosed device / terminal and method can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in electrical, mechanical or other forms.

[0090] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0091] In addition, each functional unit in various embodiments of the present invention can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0092] If the integrated module / unit is implemented in the form of 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, to implement all or part of the processes in the above method embodiments of the present invention, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0093] This application is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices produce a means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or a means for implementing the functions specified in multiple blocks.

[0094] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufactured article including an instruction means that implements the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or a means for implementing the functions specified in multiple blocks.

[0095] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operating steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or a means for implementing the functions specified in multiple blocks.

[0096] The above content is only for explaining the technical idea of the present invention and cannot be used to limit the protection scope of the present invention. Any modification made on the basis of the technical solution according to the technical idea proposed by the present invention falls within the protection scope of the claims of the present invention.

Claims

1. A multi-physics field digital reconstruction modeling method for a substation, characterized in that: The following steps are involved: S1. Establish a coupling calculation model for power equipment and obtain the field distribution of physical quantities through coupling calculation; S2. Based on the field distribution of physical quantities obtained in step S1, a multi-physics scenario inversion model is established to complete point measurement and restore multi-physics field regional values ​​based on radial basis function interpolation, and the internal parameter distribution of power equipment is inverted and calculated in combination with the three-dimensional reconstruction model of substation cloud data; S3. Construct a three-dimensional model of the full spatial information of power equipment; S4. Input the result of the inversion calculation in step S2 into the three-dimensional model of the full-space information of the power equipment constructed in step S3, realize the digital reconstruction of the multi-physical field of the substation, and conduct a partitioned and graded assessment of the status of the power equipment through the three-dimensional model of the full-space information of the power equipment.

2. The substation multi-physics field digital reconstruction modeling method according to claim 1 is characterized in that: In step S1, the power equipment coupling calculation model is established as follows: A coupling model is built to characterize the multi-physical field characteristics of the characteristic parameters of the power equipment. At the same time, the corresponding multi-physical field information is extracted based on this model to establish a database. Then, based on the substation electrical model and the measured signal, the time series data of the measuring points are input into the established coupling model and / or database by establishing boundary conditions. Finally, the coupling model is used for calculation to obtain the field distribution of physical quantities.

3. The substation multi-physics field digital reconstruction modeling method according to claim 1 is characterized in that: In step S2, the Hermite radial basis function is introduced to perform data interpolation and inversion calculation, specifically: First, the point measurement parameters of the key areas are obtained through field measurements, including power frequency electromagnetic fields and various electromagnetic transient signals. The measured point data are calculated through surface interpolation based on radial basis functions, and the surface distribution based on the point measurement parameters is inverted. Finally, combined with the three-dimensional reconstruction model and electrical model of the substation site cloud data, the power frequency electromagnetic field and transient electromagnetic signals in the substation area are simulated and calculated.

4. The substation multi-physics field digital reconstruction modeling method according to claim 3 is characterized in that: The solution of the differential equation based on radial basis function collocation is as follows: Basis function setting: according to the specific situation of the complex electromagnetic environment of the substation, determine the number of basis functions, set the RBF center and shape parameters; Determine the weight: According to the interpolation conditions and basis functions, the least square method is used to obtain the weight coefficient of each point measurement value; Interpolation process: After obtaining the interpolation equation, the interpolation value at any point is calculated to obtain the regional value, and the distribution and value of each characteristic parameter are obtained through mathematical fitting.

5. The method for digital reconstruction and modeling of multi-physical fields of a substation according to claim 4 is characterized in that: The RBF centers are set at the interpolation nodes or randomly distributed in the interpolation area. Let the number of interpolation nodes be N and the number of RBFs be M.

6. The substation multi-physics field digital reconstruction modeling method according to claim 1 is characterized in that: In step S2, the three-dimensional reconstruction model of the substation cloud data is specifically: First, the substation area is divided according to the voltage level and the type of equipment in operation; Then select the scanning points. If the scanning area radius is larger than the point measurement step length, directly model the model. Otherwise, re-divide the area before modeling. Finally, the substation cloud data is subjected to noise reduction and splicing to complete the reconstruction of the three-dimensional reconstruction model.

7. The method for digital reconstruction and modeling of multi-physical fields of a substation according to claim 6, characterized in that: The three-dimensional point cloud recognition of substation equipment divides the subspace according to the characteristics of the points and extracts the characteristics of the subspace to form a feature vector. The cosine value of the angle between the centroid of the entire point cloud and the centroid of each subspace point cloud relative to the positive direction of the Z axis is selected as the subspace feature of the point cloud; the kNN is used to obtain the classification result, and the PSO algorithm is used to optimize the coefficient weight of each subspace feature.

8. The method for digital reconstruction and modeling of multi-physical fields of a substation according to claim 7, characterized in that: The PSO algorithm is used to optimize the coefficient weight of each subspace feature as follows: First, initialize the example, calculate the classification error rate, update the particle position and velocity, and when the maximum number of iterations is reached, output the subspace weight of the optimal solution. When the maximum number of iterations is not reached, return to recalculate the classification error rate.

9. The method for digital reconstruction and modeling of multi-physical fields of a substation according to claim 7, characterized in that: When using the PSO algorithm to optimize feature weights, the classification error rate is defined as the fitness function, and the final position of the particle represents the weight of the corresponding feature.

10. A multi-physics field digital reconstruction modeling system for a substation, characterized in that: include: The coupling module establishes a coupling calculation model for power equipment and obtains the field distribution of physical quantities through coupling calculation; The inversion module establishes a multi-physics scenario inversion model based on radial basis function interpolation to complete point measurement and restore multi-physics field regional values ​​based on the obtained physical quantity field distribution, and combines the three-dimensional reconstruction model of the substation cloud data to perform inversion calculation on the internal parameter distribution of the power equipment; Construct modules to build a three-dimensional model of the full space information of power equipment; The reconstruction module inputs the results of the inversion calculation into the constructed three-dimensional model of the full-space information of the power equipment, realizes the digital reconstruction of the multi-physical fields of the substation, and conducts a partitioned and graded assessment of the status of the power equipment through the three-dimensional model of the full-space information of the power equipment.

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