Digital twin power grid component mapping method, device and electronic equipment

Abstract

The present application is applicable to the field of digital twin technology, and provides a digital twin power grid component mapping method, device and electronic device. The digital twin power grid component mapping method includes: dividing the business entity units of the smart grid; collecting the power consumption data of the smart grid power components, preprocessing the power consumption data, and obtaining the input data of the power components; based on the input data of the power components, constructing component models to obtain the voltage and state variables of the power components; according to the voltage and state variables of the power components, establishing a mapping of the power components in the physical space to the power components in the digital twin power grid. The present application realizes the dynamic mapping of corresponding power grid components driven by business. Through the flexible deployment of components, the components are mapped from the physical power grid to the digital twin power grid under the business drive, and the effective monitoring of the components under the specific business functions of the smart grid entity end is further realized.

Description

Technical Field

[0001] The present application belongs to the field of digital twin technology, and in particular to a digital twin power grid component mapping method, device and electronic equipment. Background Art

[0002] The power grid mainly provides services to people in the form of physical objects. Adding simulation systems to the power grid facilitates the calculation and planning of power flow in the transmission network. However, it is difficult to decouple the strong dependencies between components in the power grid, resulting in low efficiency in power grid business execution and high maintenance and management costs. In recent years, domestic and foreign scholars have mainly mapped power grid lines, mainly using elasticity theory to perform topological analysis on the network, lacking consideration of component relationships, and not fully considering business-driven mapping methods.

[0003] Existing research mainly applies simulation systems to business planning, and the technology of applying business drivers to component-level mapping does not exist yet. Summary of the invention

[0004] In order to overcome the problems existing in the related art, the embodiments of the present application provide a digital twin power grid component mapping method, device and electronic device.

[0005] This application is implemented through the following technical solutions:

[0006] In a first aspect, an embodiment of the present application provides a componentized mapping method for a digital twin power grid, comprising: dividing the business entity units of the smart grid; collecting power consumption data of the power consumption components of the smart grid, preprocessing the power consumption data, and obtaining input data of the power consumption components; constructing a component model based on the input data of the power consumption components to obtain the voltage and state variables of the power consumption components; and establishing a mapping of the power consumption components in the physical space to the power consumption components in the digital twin power grid according to the voltage and state variables of the power consumption components.

[0007] Based on the first aspect, in some possible implementations, the division of the business entity units of the smart grid includes: dividing the smart grid into power-consuming components, power transmission components and power generation components based on the business characteristics of the smart grid, and determining the power-consuming components of the smart grid and their arrangement order.

[0008] Based on the first aspect, in some possible implementations, the power consumption data of the power-consuming component includes: electric energy indication, voltage, current, power, device status and events of the power-consuming component.

[0009] Based on the first aspect, in some possible implementations, the preprocessing of the electricity usage data includes: performing data cleaning, data integration, data transformation and data reduction on the electricity usage data to obtain input data of the electricity usage component.

[0010] Based on the first aspect, in some possible implementations, constructing a component model based on the input data of the power-consuming component to obtain the voltage and state variables of the power-consuming component includes:

[0011]

[0012] The component model is constructed, wherein f1 and f2 are arbitrary vector functions, defining external equations and internal equations respectively, i is a vector of through variables, v is a vector of cross variables, y is a vector of internal state variables, and u is a vector of independent control.

[0013] Based on the first aspect, in some possible implementations, obtaining the voltage and state variables of the power-consuming component by constructing the component model includes:

[0014]

[0015] The voltage v(t) and state variable y(t) of the power-consuming component are obtained, where: v 0 (t), y 0 (t) is the value of the state variable at the previous iteration. m1 0 、m2 0 represents the misfit of the system equations from the previous iteration.

[0016] Based on the first aspect, in some possible implementations, the mapping of the power component in the physical space to the power component in the digital twin power grid is established based on the voltage and state variables of the power component, including: based on the voltage v(t) and state variable y(t) of the power component, using RT-LAB to perform real-time simulation of the voltage and state variables of the power component to obtain the mapping of the power component in the digital twin power grid.

[0017] The above-mentioned digital twin power grid component mapping method realizes the dynamic mapping of corresponding power grid components under business drive. Through the flexible deployment of components, the components are mapped from the physical power grid to the digital twin power grid under business drive, further realizing the effective monitoring of the components under the specific business functions of the smart grid entity.

[0018] In the second aspect, an embodiment of the present application provides a componentized mapping device for a digital twin power grid, comprising: a division module for dividing the business entity units of the smart grid; a collection and processing module for collecting the power consumption data of the power consumption component, preprocessing the power consumption data, and obtaining the input data of the power consumption component; a construction module for constructing a component model based on the input data of the power consumption component to obtain the voltage and state variables of the power consumption component; and a mapping module for establishing a mapping of the power consumption component in the physical space to the power consumption component in the digital twin power grid according to the voltage and state variables of the power consumption component.

[0019] In a third aspect, an embodiment of the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the digital twin power grid component mapping method as described in any one of the first aspects is implemented.

[0020] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the digital twin power grid component mapping method as described in any one of the first aspects.

[0021] It can be understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here.

[0022] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present specification. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0024] Figure 1 It is a schematic diagram of an application scenario of a digital twin power grid component mapping method provided in an embodiment of the present application;

[0025] Figure 2 This is a business-driven digital twin power grid framework diagram provided in an embodiment of the present application;

[0026] Figure 3 It is a flowchart of a componentized mapping method of a digital twin power grid provided in one embodiment of the present application;

[0027] Figure 4 It is a schematic diagram of the component structure provided by an embodiment of the present application;

[0028] Figure 5 It is a structural schematic diagram of a digital twin power grid component mapping device provided in one embodiment of the present application;

[0029] Figure 6 It is a structural schematic diagram of a digital twin power grid component mapping device provided in one embodiment of the present application;

[0030] Figure 7 It is a schematic diagram of the structure of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0031] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0032] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0033] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0034] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0035] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0036] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0037] The power grid mainly provides services to people in the form of physical objects. Adding simulation systems to the power grid facilitates the calculation and planning of power flow in the transmission network. However, it is difficult to decouple the strong dependencies between components in the power grid, resulting in low efficiency in power grid business execution and high maintenance and management costs. In recent years, domestic and foreign scholars have mainly mapped power grid lines, mainly using elasticity theory to perform topological analysis on the network, lacking consideration of component relationships, and not fully considering business-driven mapping methods.

[0038] Existing research mainly applies simulation systems to business planning, and the technology of applying business drivers to component-level mapping does not exist yet.

[0039] Based on the above problems, the digital twin power grid component mapping method in the embodiment of the present application divides the business entity units of the smart grid; collects power consumption data of the power consumption components of the smart grid, pre-processes the power consumption data, and obtains the input data of the power consumption components; based on the input data of the power consumption components, constructs a component model to obtain the voltage and state variables of the power consumption components; according to the voltage and state variables of the power consumption components, establishes a mapping of the power consumption components in the physical space to the power consumption components in the digital twin power grid.

[0040] For example, the embodiments of the present application can be applied to Figure 1 In the exemplary scenario shown. The scenario includes a smart grid 10, a collection device 20, an electronic device 30 and a digital twin grid 40. The smart grid 10 is divided into a transmission component 11, a power generation component 12 and a power consumption component 13. The collection device 20 is used to collect the power consumption data of the smart grid 10 and transmit the power consumption data to the electronic device 30. The electronic device 30 is used to construct a mapping of the smart grid 10 to the digital twin grid 40 based on the power consumption data. The digital twin grid 40 includes a transmission twin component 41, a power generation twin component 42 and a power consumption twin component 43, which correspond to each component of the smart grid 10 one by one.

[0041] For example, the electronic device 30 preprocesses the power consumption data to obtain the input data of the power component 11; based on the input data of the power component 11, a component model is constructed to obtain the voltage and state variables of the power component 11; according to the voltage and state variables of the power component 11, a mapping of the power component 11 in the physical space to the power component 41 in the digital twin power grid is established.

[0042] In this embodiment, the electronic device 30 may be a terminal such as a computer, a mobile phone, a tablet computer, a laptop computer, a netbook, a personal digital assistant (PDA), etc. The embodiment of the present application does not impose any limitation on the specific type of the electronic device.

[0043] In some embodiments, based on Figure 1 The embodiment shown, see Figure 2 The above-mentioned componentized mapping structure of the digital twin power grid may include: transmission components, power generation components and power consumption components in the physical power grid, which correspond one-to-one to the transmission twin components, power generation twin components and power consumption twin components in the digital twin power grid through componentized mapping and business drive.

[0044] The following combination Figure 1 The digital twin power grid component mapping method of the present application is described in detail.

[0045] Figure 2 is a schematic flow chart of a digital twin power grid component mapping method provided in an embodiment of the present application, with reference to Figure 2 , the componentized mapping method of the digital twin power grid is described as follows:

[0046] In step 101, business entity units of the smart grid are divided.

[0047] Exemplarily, based on the business characteristics of the smart grid, the smart grid is divided into power consumption components, power transmission components and power generation components, and the power consumption components of the smart grid and their arrangement order are determined.

[0048] In step 102, power consumption data of smart grid power consumption components are collected, and the power consumption data are preprocessed to obtain input data of the power consumption components;

[0049] The power consumption data of the power-consuming components include: the power indication, voltage, current, power, equipment status and events of the power-consuming components.

[0050] Optionally, the frequency of data collection is once every 5 minutes. To ensure the normal collection of large amounts of data, it is necessary to consider load balancing strategies and implement functions such as automatic collection and breakpoint resuming to ensure that data can be obtained in a timely and efficient manner. In addition, PostgreSQL or Oracle database connection pool technology and Redis local cache technology are also required.

[0051] Specifically, data collection also needs to realize the following functions:

[0052] (1) Efficient communication with different remote cluster devices. The data acquisition system needs to consider abnormal conditions of remote devices during communication with remote devices, such as power failure, network disconnection, memory overflow, etc. At the same time, the effectiveness of the cluster is tested to ensure timely processing of data during the acquisition process.

[0053] (2) Implement interface calling functions between different components.

[0054] (3) Support the implementation of clock functions between systems.

[0055] (4) Implementation of basic data functions, including data query, storage and data display functions.

[0056] (5) Supports switching between master and slave devices, and switches and activates other devices through the management end.

[0057] Exemplarily, preprocessing the electricity consumption data includes: performing data cleaning, data integration, data transformation and data reduction on the electricity consumption data to obtain input data of the electricity consumption component.

[0058] Specifically, for noise data such as errors, losses, duplications, etc. in electricity consumption data, different data cleaning methods are used to ensure data availability: for duplicate data, it is necessary to remove duplicate records and compare each instance with other instances; for numerical attributes in the instance, the mean and standard deviation are calculated respectively, and abnormal attributes are identified by setting confidence intervals, and duplicate records are deleted; for incomplete data in electricity consumption data, mainly including vacant or missing data, the cleaning methods for this type of data mainly include ignoring and missing value interpolation methods: the data execution efficiency can be effectively improved by deleting instances; for valuable data, filling technology is used to interpolate missing values.

[0059] Merge and process heterogeneous electricity consumption data to achieve data integration and solve conflicts, selection and data inconsistency problems of heterogeneous data.

[0060] In order to facilitate subsequent data processing, it is necessary to use dimensionality transformation or conversion to convert the data format, mainly using function transformation, data standardization and other methods to improve data availability.

[0061] The model input feature data is processed for dimensionality reduction through eigenvalue selection and spatial transformation technology to reduce irrelevant attributes and achieve efficient data processing.

[0062] In step 103, a component model is constructed based on the input data of the power-consuming component to obtain the voltage and state variables of the power-consuming component.

[0063] Specifically, through

[0064]

[0065] Construct a component model, where f1 and f2 are arbitrary vector functions, defining external equations and internal equations respectively, i is the vector of through variables, v is the vector of cross variables, y is the vector of internal state variables, and u is the vector of independent control.

[0066] pass

[0067]

[0068] Get the voltage v(t) and state variable y(t) of the power component, where: v 0 (t), y 0 (t) is the value of the state variable at the previous iteration. m1 0 、m2 0 represents the misfit of the system equations from the previous iteration.

[0069] For example, an electrical system component has multiple terminals, through which other components can be connected. Figure 4 Each terminal has an associated cross variable and a through variable. If the terminal is charged, the cross variable and the through variable are the voltage and the current flowing into the terminal, respectively. V represents voltage and I represents current.

[0070] This component can be

[0071]

[0072] Construct a component model, where f1 and f2 are arbitrary vector functions, defining external equations and internal equations respectively, i is the vector of through variables, v is the vector of cross variables, y is the vector of internal state variables, and u is the vector of independent control.

[0073] By integrating equation (1) over the simulation time step, we can approximate it with a quadratic expression. Assuming the simulation time step is h, then:

[0074]

[0075] Where G is the Jacobian matrix:

[0076]

[0077] b1(th), b2(th) are vectors that depend only on the past history of the through state, cross state or internal state, δ1, δ2 represent cubic terms and other high-order terms. Vectors q1, q2 represent quadratic terms that can be expressed by expression (4):

[0078]

[0079] Among them, the matrix Q i Has the following form:

[0080]

[0081] In (4) and (5), the vectors f and X are given by the following equations:

[0082]

[0083] If the quadratic term is omitted, the above equation corresponds to the resistive concomitant form model. The quadratic term improves the convergence speed and makes the numerical process more robust and stable. If the device equation (1) is linear, the quadratic term is zero.

[0084] The solution to the network is obtained by applying the law of conservation of energy at each node in the system. This process produces the following set of equations:

[0085]

[0086] Among them, I inj is the vector of node current injection, and is the component correlation matrix:

[0087]

[0088] In the formula, i k (t) is the terminal current of component k. Component k has variable v k (t) is related to the node vector across variables v(t) by:

[0089] v k (t)=(A k ) T v(t) (9)

[0090] When replacing the device equation (2), equation (7) becomes a set of quadratic equations. These equations are solved using Newton's method. The solution is to iteratively evaluate the following expression.

[0091]

[0092] Among them, v 0 (t), y0 (t) is the value of the state variable at the previous iteration. , represents the mismatch of the system equations at the previous iteration.

[0093] In step 104, a mapping of the power consumption components in the physical space to the power consumption components in the digital twin power grid is established based on the voltage and state variables of the power consumption components.

[0094] Specifically, according to the voltage v(t) and state variable y(t) of the power component, a mapping of the power component in the physical space to the power component in the digital twin power grid is established, including: according to the voltage and state variables of the power component, the voltage and state variables of the power component are simulated in real time by using RT-LAB to obtain the mapping of the power component in the digital twin power grid.

[0095] Optionally, by effectively modeling the power-consuming components in step C in the digital twin space, the power-consuming components in the physical space are mapped to the power-consuming twin components based on the voltage and state variables predicted in formula (9).

[0096] In the process of establishing the mapping, real-time simulation technology also needs to be considered. Due to the frequent conversion of business operations in the power grid, there are high requirements for the real-time performance of the mapping. RT-LAB is an industrial-grade system real-time simulation platform software package. It is fully integrated with MATLAB SIMULINK and includes a test application system for rapid control prototyping and hardware-in-the-loop. RT-LAB has a small operation step size and can be executed in real time. It also provides digital and analog signal input / output ports for high-speed data exchange with real devices. The power system model is changed by using SIMULINK. RT-LAB divides the model into three subsystems: SM module, SS module and SC module. The SM module contains all electrical models and electrical network topology. The SS module can interact frequently with the SM module, and the two modules run synchronously. The SC module can monitor various physical quantities in the system. After the subsystem is loaded, different computing nodes of RT-LAB perform parallel calculations to ensure the accuracy and speed of the simulation.

[0097] The above-mentioned digital twin power grid component mapping method realizes the dynamic mapping of corresponding power grid components under business drive. Through the flexible deployment of components, the components are mapped from the physical power grid to the digital twin power grid under business drive, further realizing the effective monitoring of the components under the specific business functions of the smart grid entity.

[0098] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0099] Corresponding to the digital twin power grid component mapping method described in the above embodiment, Figure 5 A structural block diagram of a digital twin power grid component mapping device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0100] See also Figure 5 The digital twin power grid component mapping device in the embodiment of the present application may include a division module 201, an acquisition and processing module 202, a construction module 203 and a mapping module 204.

[0101] Among them, the division module 201 is used to divide the business entity units of the smart grid; the collection and processing module 202 is used to collect the power consumption data of the power consumption components, pre-process the power consumption data, and obtain the input data of the power consumption components; the construction module 203 is used to construct a component model based on the input data of the power consumption components, and obtain the voltage and state variables of the power consumption components; the mapping module 204 is used to establish a mapping of the power consumption components in the physical space to the power consumption components in the digital twin power grid according to the voltage and state variables of the power consumption components.

[0102] In some embodiments, the division module 201 can be specifically used to: divide the smart grid into power-consuming components, power transmission components and power generation components based on the business characteristics of the smart grid, and determine the power-consuming components of the smart grid and their arrangement order.

[0103] In some embodiments, see Figure 6 ,based on Figure 5 In the illustrated embodiment, the acquisition and processing module 202 may specifically include an acquisition unit 2021 and a pre-processing unit 2022 .

[0104] The collecting unit 2021 is used to collect the power consumption data of the power-consuming components.

[0105] The pre-processing unit 2022 is used to perform data cleaning, data integration, data transformation and data reduction on the power consumption data to obtain input data of the power consumption component.

[0106] Exemplarily, the power consumption data of the power-consuming component includes: the electric energy indication, voltage, current, power, device status and events of the power-consuming component.

[0107] In some embodiments, the construction module 203 may be specifically used to:

[0108] pass

[0109]

[0110] The component model is constructed, wherein f1 and f2 are arbitrary vector functions, defining external equations and internal equations respectively, i is a vector of through variables, v is a vector of cross variables, y is a vector of internal state variables, and u is a vector of independent control.

[0111] The step of obtaining the voltage and state variables of the power-consuming component by constructing the component model includes:

[0112] pass

[0113]

[0114] The voltage v(t) and state variable y(t) of the power-consuming component are obtained, where: v 0 (t), y 0 (t) is the value of the state variable at the previous iteration. m1 0 、m2 0 represents the misfit of the system equations from the previous iteration.

[0115] In some embodiments, the mapping module 204 can be specifically used to: obtain the mapping of the power component in the digital twin power grid by performing real-time simulation of the voltage and state variables of the power component using RT-LAB according to the voltage v(t) and state variable y(t) of the power component.

[0116] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0117] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, 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. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0118] The present application also provides a terminal device, see Figure 7The electronic device 500 may include: at least one processor 510, a memory 520, and a computer program stored in the memory 520 and executable on the at least one processor 510. When the processor 510 executes the computer program, the steps in any of the above-mentioned method embodiments are implemented, for example: Figure 3 Steps 101 to 104 in the illustrated embodiment. Alternatively, when the processor 510 executes the computer program, the functions of each module / unit in the above-mentioned device embodiments are implemented, for example Figure 5 Functions of modules 201 to 204 are shown.

[0119] Exemplarily, the computer program may be divided into one or more modules / units, one or more modules / units are stored in the memory 520, and executed by the processor 510 to complete the present application. The one or more modules / units may be a series of computer program segments capable of completing specific functions, and the program segments are used to describe the execution process of the computer program in the electronic device 500.

[0120] Those skilled in the art will understand that Figure 7 These are merely examples of electronic devices and do not constitute a limitation on the terminal device. The terminal device may include more or fewer components than shown in the figure, or a combination of certain components, or different components, such as input and output devices, network access devices, buses, etc.

[0121] The processor 510 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0122] The memory 520 may be an internal storage unit of the terminal device, or an external storage device of the terminal device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. The memory 520 is used to store the computer program and other programs and data required by the terminal device. The memory 520 may also be used to temporarily store data that has been output or is to be output.

[0123] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0124] The digital twin power grid component mapping method provided in the embodiment of the present application can be applied to smart grids, computers, wearable devices, vehicle-mounted devices, tablet computers, laptops, mobile phones and other electronic devices. The embodiment of the present application does not impose any restrictions on the specific type of electronic devices.

[0125] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it can implement the steps in each embodiment of the above-mentioned digital twin power grid component mapping method.

[0126] An embodiment of the present application provides a computer program product. When the computer program product runs on a mobile terminal, the mobile terminal can implement the steps in each embodiment of the above-mentioned digital twin power grid component mapping method when executing.

[0127] If the integrated 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, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0128] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0129] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0130] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0131] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0132] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A digital twin power grid component mapping method, characterized in that: include: Divide the business entity units of smart grid; Collecting power consumption data of power consumption components of the smart grid, preprocessing the power consumption data, and obtaining input data of the power consumption components; Based on the input data of the power-consuming component, a component model is constructed to obtain the voltage and state variables of the power-consuming component; Establishing a mapping of the power consumption component in the physical space to the power consumption component in the digital twin power grid according to the voltage and state variables of the power consumption component; The step of constructing a component model based on the input data of the power-consuming component to obtain the voltage and state variables of the power-consuming component includes: pass Construct the component model, where f1 and f2 are arbitrary vector functions, defining external equations and internal equations respectively, i is a vector of through variables, v is a vector of cross variables, y is a vector of internal state variables, and u is a vector of independent control; pass The voltage v(t) and state variable y(t) of the power-consuming component are obtained, where: v 0 (t), y 0 (t) is the value of the state variable in the previous iteration, m1 0 、m2 0 represents the misfit of the system equations from the previous iteration.

2. The digital twin power grid component mapping method according to claim 1, characterized in that: The division of the business entity units of the smart grid includes: Based on the service characteristics of the smart grid, the smart grid is divided into power consumption components, power transmission components and power generation components, and the power consumption components of the smart grid and the arrangement order of the power consumption components are determined.

3. The digital twin power grid component mapping method according to claim 1, characterized in that: The power consumption data of the power consumption component includes: The electrical energy indication, voltage, current, power, device status and events of the electrical components.

4. The digital twin power grid component mapping method according to claim 1 or 3, characterized in that: The preprocessing of the electricity consumption data comprises: The power consumption data is cleaned, integrated, transformed and reduced to obtain input data of the power consumption component.

5. The digital twin power grid component mapping method according to claim 1, characterized in that: The mapping of the power consumption component in the physical space to the power consumption component in the digital twin power grid is established according to the voltage and state variable of the power consumption component, including: According to the voltage v(t) and the state variable y(t) of the power component, the voltage and the state variable of the power component are simulated in real time by using RT-LAB to obtain a mapping of the power component in the digital twin power grid.

6. A digital twin power grid component mapping device, characterized in that: include: A division module, used for dividing the business entity units of the smart grid; A collection and processing module, used to collect power consumption data of power consumption components of the smart grid, pre-process the power consumption data, and obtain input data of the power consumption components; A construction module, used to construct a component model based on the input data of the power-consuming component, and obtain the voltage and state variables of the power-consuming component; A mapping module, used to establish a mapping of the power consumption component in the physical space to the power consumption component in the digital twin power grid according to the voltage and state variables of the power consumption component; The building blocks can be used to: pass Construct the component model, where f1 and f2 are arbitrary vector functions, defining external equations and internal equations respectively, i is a vector of through variables, v is a vector of cross variables, y is a vector of internal state variables, and u is a vector of independent control; pass The voltage v(t) and state variable y(t) of the power-consuming component are obtained, where: v 0 (t), y 0 (t) is the value of the state variable in the previous iteration, m1 0 、m2 0 represents the misfit of the system equations from the previous iteration.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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