CN112231305A - Digital power grid system and method based on digital twinning - Google Patents
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Abstract
The invention belongs to the technical field of electric power, and particularly relates to a digital twin-based digital power grid system and a method. The system comprises: the acquisition part is configured to acquire the operation data of the power grid; the data preprocessing part is configured to perform data processing on the running data, and comprises the following steps: data cleaning, data specification, data standardization and data transformation; and the model part is configured for carrying out model analysis based on the data after data processing, defining data types and relations, defining data attributes, carrying out model reasoning, completing model creation, constructing a power grid graph based on the created model, carrying out data association on the data after data processing, and generating associated data. A power grid model is established based on data, the power grid is completely digitalized, the topological structure of the power grid is accurately reproduced, analysis of the digital power grid is facilitated, and the energy efficiency ratio of power grid management is improved.
Description
Technical Field
The invention belongs to the technical field of electric power, and particularly relates to a digital twin-based digital power grid system and a method.
Background
The concept prototype of the digital twin is firstly proposed in 2003 by the teaching of Grieves of the university of michigan, gradually developed and perfected, and the concept model is proposed in 2011 and comprises a physical product of a physical space, a virtual product of a virtual space and a data and information interaction interface between the physical product and the virtual product. The definition of the digital twin is to fully utilize data such as a physical model, sensor updating, operation history and the like, integrate a multidisciplinary, multi-physical quantity, multi-scale and multi-probability simulation process, complete mapping in a virtual space and reflect the full life cycle process of corresponding entity equipment. The digital twin is a real-time mirror image of a physical entity created in a virtual space in a digital mode, is a simulation model of the physical entity in the virtual space, completes complete and accurate digital description of the physical entity through data and information interaction between the physical entity and a digital twin, and can be used for simulating, monitoring, diagnosing, predicting and controlling the behavior and the state of the physical entity in a physical environment.
In the prior art, a digital twin conceptual model is proposed in 2011 to have a three-dimensional structure, which includes a physical model of a physical space and a virtual model of a virtual space, and data and information interaction therebetween. The three-dimensional structure model is a digital twin basic model, and the construction core is data connection between a virtual model and a physical space and a virtual space. The key problem in deployment is that the inheritance and connection between the two are not realized, but the virtual model is used as a reference, and a person serves as the connection between the two. In this technical solution, a scholars proposes to implement a connection function between two Unified Repositories (URs) by constructing the URs. Thereafter, the trainee extended the digital twin three-dimensional structure to a five-dimensional structure model, including physical entities, virtual models, service systems, twin data, and connections. In addition, in the aspect of the construction process of the digital twins, a scholars proposes to use an automated modeling language (AutomationML) to model data transmission between different systems connected with the digital twins and realize mapping of physical entities in a digital space.
In the prior art, the development of a power system improves the operation complexity of the power system, further causes a mode professional work task to be pushed to a first line of dispatching production, and the requirements of power grid simulation analysis based on online data are more and more strong.
Patent No. CN201410829988.2A discloses a digital power grid construction method based on online data, which includes power grid basic data construction, power grid graph construction and power grid simulation calculation data construction based on online data, that is, power grid basic data, graphs and simulation calculation data of a digital power grid for simulation analysis are generated by converting power grid model data, graph data and state-estimated power grid data maintained and generated by an online SCADA/EMS system. The technical scheme provided by the invention solves the problem of constructing the power grid simulation data consistent with the actual condition of online operation, and realizes the construction of the digital power grid based on the online data, thereby providing a data basis for the simulation analysis of the online operation power grid. Although the method is used for carrying out simulation construction on the power grid, the method is lack of integration processing on power grid data, and the constructed simulation network has low accuracy and cannot accurately restore the topological structure of the power grid system.
Disclosure of Invention
In view of the above, the present invention provides a digital grid system and a method based on digital twins, which utilize data processing and digital twins to perform data preprocessing on collected grid data, perform abstract classification and attribute definition on the data, and then combine with the topological relation of the original grid equipment corresponding to each data to establish a model of a grid based on the data, thereby completely digitizing the grid, accurately reproducing the topological structure of the grid, facilitating analysis of the digital grid, and further improving the energy efficiency ratio of grid management.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a digital twin based digital power grid system, the system comprising: the acquisition part is configured to acquire the operation data of the power grid; the data preprocessing part is configured to perform data processing on the running data, and comprises the following steps: data cleaning, data specification, data standardization and data transformation; the model part is configured for carrying out model analysis based on the data after data processing, defining data types and relations, defining data attributes, carrying out model reasoning, completing model creation, constructing a power grid graph based on the created model, carrying out data association on the data after the data processing, and generating associated data; and the data part is configured for storing the operation data, the data after data processing and the associated data, and simultaneously, the data part is respectively provided for the acquisition part, the data preprocessing part and the model part to call the data.
Further, the acquisition part at least comprises: the system comprises a sensor group, a user terminal, a control center, electric equipment and a routing part; the sensor group, the user terminal, the control center, the electric equipment and the routing part can carry out mirror image copying on running data of the sensor group, send the data after mirror image copying to the data part for storage and send the data after mirror image copying to the data preprocessing part in the running process.
Further, the data preprocessing part comprises: the method comprises the following steps: the data cleaning unit is configured for removing the unique attribute, processing missing values and abnormal values, detecting and processing the running data; the data specification unit is configured to perform data specification processing on the data after the data cleaning, and comprises: mean value removing, covariance matrix calculation, eigenvalue and eigenvector calculation of covariance matrix, sorting eigenvalues from large to small, and preservingReserving the largest feature vector, and converting the data into a new space constructed by the feature vector; finally, new processed data are obtained, and the data are irrelevant pairwise, but the original information is kept; the data standardization unit is configured for carrying out data standardization processing on the data subjected to the data specification processing, and scaling the data in proportion to enable the data to fall into a small specific interval; in which the data is linearly transformed using a transfer function such that the result falls to [0,1 ]]Interval, the transfer function is as follows:
wherein x is*The result is the result after data standardization processing; x is data to be processed; min is the minimum value in the data; max is the maximum value in the data; and the data conversion unit is configured to perform periodic sampling on the data subjected to the data standardization processing, further realize data discretization processing and convert continuous data into discrete data.
Further, the model part performs model analysis based on the data after data processing, defines data types and relationships, defines data attributes, performs model reasoning, and completes the model creation by executing the following steps: obtaining a function coupling relation, nodes and directed edges among all functional units in the power grid system through structural analysis, and establishing a topological coupling network of the power grid system; defining data types and data relations, defining data attributes at the same time, obtaining the coupling connection relation among multiple attributes of data of a topological mode in a topological coupling network of a power grid system through a multicolor set, and establishing an information processing model based on the multicolor set; constructing a topological graph for searching all topological propagation paths according to the information processing model based on the multicolor set, and establishing a topological traceability mathematical model; acquiring design requirement information of a power grid system, and building a visual simulation model of a digital twin body of the power grid system on a simulation platform; establishing an information channel and an instruction channel of a digital twin body and a real object twin body in the power grid system by using a digital twin technology, and establishing a digital twin model of the power grid system; model reasoning is carried out on a digital twin model based on a power grid system to obtain topological information, all topological propagation paths in the information processing model based on the multicolor set are searched through a breadth-first root search algorithm, a topological root is found, and topology tracing is completed.
Further, the method for obtaining the coupling connection relationship among the multiple attributes of the topological mode in the topological coupling network of the power grid system through the multi-color set and establishing the information processing model based on the multi-color set performs the following steps: classifying the data by the data category and the relationship to obtain the classification result of each data, and respectively calculating the mapping rule of each data and the attribute according to the corresponding relationship between each classification result and the data attribute by the following processes: extracting data characteristics according to the data categories and the relations, and counting the times of the data characteristics conforming to each data category by using the following formula:
wherein N is the number of times of conforming to the category, S is the number of data, and lambdaiIs the weight of the ith data, M is the number of features in each class, countjThe characteristic number of the ith data; according to the counted times that the data conforms to each category, setting the priority of the category of the corresponding data from high to low according to the number of the data from high to low, and finishing the data category training; and according to the corresponding relation between the classification result of each known data and the real classification result thereof, counting and analyzing the mapping rule between the category and the attribute.
A digital twin based digital power grid method, the method performing the steps of: step 1: acquiring operation data of a power grid; step 2: and performing data processing on the operation data, wherein the data processing comprises the following steps: data cleaning, data specification, data standardization and data transformation; and step 3: performing model analysis based on the data after data processing, defining data types and relationships, defining data attributes, performing model reasoning, completing model creation, constructing a power grid graph based on the created model, performing data association on the data after data processing, and generating associated data; and 4, step 4: storing the operation data, the data after data processing and the associated data, and simultaneously respectively providing the step 1, the step 2 and the step 3 for data calling.
Further, the step 1: acquiring the operation data of the power grid comprises the following steps: and (3) carrying out mirror image copying on the running data of the sensor group, the user terminal, the control center, the electric equipment and the routing part in real time in the running process, sending the data after mirror image copying to the step (4) for storage, and sending the data after mirror image copying to the step (2).
Further, the step 2: and performing data processing on the operation data, wherein the data processing comprises the following steps: the method for cleaning data, stipulating data, standardizing data and transforming data comprises the following steps: detecting and processing the running data by removing the unique attribute and processing the missing value and the abnormal value; the data protocol processing is carried out on the data after the data cleaning, and the data protocol processing method comprises the following steps: removing an average value, calculating a covariance matrix, calculating an eigenvalue and an eigenvector of the covariance matrix, sorting the eigenvalues from large to small, reserving the largest eigenvector, and converting data into a new space constructed by the eigenvector; finally, new processed data are obtained, and the data are irrelevant pairwise, but the original information is kept; carrying out data standardization processing on the data subjected to the data specification processing, and scaling the data in proportion to enable the data to fall into a small specific interval; in which the data is linearly transformed using a transfer function such that the result falls to [0,1 ]]Interval, the transfer function is as follows:
wherein x is*The result is the result after data standardization processing; x is data to be processed; min is the minimum value in the data; max is the maximum value in the data; and carrying out periodic sampling on the data subjected to the data standardization processing, further realizing data discretization processing, and converting continuous data into discrete data.
Further, the model part performs model analysis based on the data after data processing, defines data types and relationships, defines data attributes, performs model reasoning, and completes the model creation by executing the following steps: obtaining a function coupling relation, nodes and directed edges among all functional units in the power grid system through structural analysis, and establishing a topological coupling network of the power grid system; defining data types and data relations, defining data attributes at the same time, obtaining the coupling connection relation among multiple attributes of data of a topological mode in a topological coupling network of a power grid system through a multicolor set, and establishing an information processing model based on the multicolor set; constructing a topological graph for searching all topological propagation paths according to the information processing model based on the multicolor set, and establishing a topological traceability mathematical model; acquiring design requirement information of a power grid system, and building a visual simulation model of a digital twin body of the power grid system on a simulation platform; establishing an information channel and an instruction channel of a digital twin body and a real object twin body in the power grid system by using a digital twin technology, and establishing a digital twin model of the power grid system; model reasoning is carried out on a digital twin model based on a power grid system to obtain topological information, all topological propagation paths in the information processing model based on the multicolor set are searched through a breadth-first root search algorithm, a topological root is found, and topology tracing is completed.
Further, the method for obtaining the coupling connection relationship among the multiple attributes of the topological mode in the topological coupling network of the power grid system through the multi-color set and establishing the information processing model based on the multi-color set performs the following steps: classifying the data by the data category and the relationship to obtain the classification result of each data, and respectively calculating the mapping rule of each data and the attribute according to the corresponding relationship between each classification result and the data attribute by the following processes: extracting data characteristics according to the data categories and the relations, and counting the times of the data characteristics conforming to each data category by using the following formula:
wherein N is the number of times of conforming to the category, S is the number of data, and lambdaiIs the weight of the ith data,m is the number of features in each class, countjThe characteristic number of the ith data; according to the counted times that the data conforms to each category, setting the priority of the category of the corresponding data from high to low according to the number of the data from high to low, and finishing the data category training; and according to the corresponding relation between the classification result of each known data and the real classification result thereof, counting and analyzing the mapping rule between the category and the attribute.
The digital power grid system and method based on the digital twin have the following beneficial effects: after data processing and digital twins are utilized to carry out data preprocessing on collected power grid data, abstract classification and attribute definition are carried out on the data, and then a power grid model is established based on the data by combining the topological relation of original power grid equipment corresponding to each data, so that the power grid is completely digitalized, the topological structure of the power grid is accurately reproduced, the analysis of the digital power grid is facilitated, and the energy efficiency ratio of power grid management is further improved. The method is mainly realized by the following steps: 1. in the data preprocessing process, the data preprocessing is carried out on the power grid operation data acquired by the mirror image copying of the acquired part, so that data errors generated when the power grid equipment acquires the data and copies the mirror image are avoided, and the accuracy of the data is improved; 2. the method comprises the steps of firstly carrying out model analysis, defining data types and relationships, defining data attributes, carrying out model reasoning and completing model creation in the process of establishing a model of the digital power grid, wherein the process obtains functional coupling relationships, nodes and directed edges among all functional units in the power grid system through structural analysis and establishes a topological coupling network of the power grid system; defining data types and data relations, defining data attributes at the same time, obtaining the coupling connection relation among multiple attributes of data of a topological mode in a topological coupling network of a power grid system through a multicolor set, and establishing an information processing model based on the multicolor set; constructing a topological graph for searching all topological propagation paths according to the information processing model based on the multicolor set, and establishing a topological traceability mathematical model; compared with the existing model analysis process of the digital power grid, the method can accurately establish the topological model of the digital power grid, can better analyze the problem of the power grid when performing digital power grid analysis and power grid management, and improves the energy efficiency ratio of power grid operation.
Drawings
Fig. 1 is a schematic system structure diagram of a digital twin-based digital power grid system according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a method of a digital twin-based digital power grid method according to an embodiment of the present invention.
Fig. 3 is a schematic structural diagram of a data preprocessing portion of a system of a digital twin-based digital power grid system according to an embodiment of the present invention;
fig. 4 is a digital power grid topology schematic diagram of a system and method of a digital twin-based digital power grid system according to an embodiment of the present invention.
Fig. 5 is a graph of an experimental curve of a change of a grid energy efficiency ratio with operation time of the system and method of the digital twin-based digital grid system according to the embodiment of the present invention, and a graph of a comparison experimental effect in the prior art.
Detailed Description
The method of the present invention will be described in further detail below with reference to the accompanying drawings and embodiments of the invention.
Example 1
As shown in fig. 1, a digital twin-based digital power grid system, the system comprising: the acquisition part is configured to acquire the operation data of the power grid; the data preprocessing part is configured to perform data processing on the running data, and comprises the following steps: data cleaning, data specification, data standardization and data transformation; the model part is configured for carrying out model analysis based on the data after data processing, defining data types and relations, defining data attributes, carrying out model reasoning, completing model creation, constructing a power grid graph based on the created model, carrying out data association on the data after the data processing, and generating associated data; and the data part is configured for storing the operation data, the data after data processing and the associated data, and simultaneously, the data part is respectively provided for the acquisition part, the data preprocessing part and the model part to call the data.
By adopting the technical scheme, the collected power grid data is subjected to data preprocessing by utilizing data processing and digital twins, the data is subjected to abstract classification and attribute definition, and then a power grid model is established based on the data by combining the topological relation of the original power grid equipment corresponding to each data, so that the power grid is completely digitalized, the topological structure of the power grid is accurately reproduced, the analysis of the digital power grid is facilitated, and the energy efficiency ratio of power grid management is further improved. The method is mainly realized by the following steps: 1. in the data preprocessing process, the data preprocessing is carried out on the power grid operation data acquired by the mirror image copying of the acquired part, so that data errors generated when the power grid equipment acquires the data and copies the mirror image are avoided, and the accuracy of the data is improved; 2. the method comprises the steps of firstly carrying out model analysis, defining data types and relationships, defining data attributes, carrying out model reasoning and completing model creation in the process of establishing a model of the digital power grid, wherein the process obtains functional coupling relationships, nodes and directed edges among all functional units in the power grid system through structural analysis and establishes a topological coupling network of the power grid system; defining data types and data relations, defining data attributes at the same time, obtaining the coupling connection relation among multiple attributes of data of a topological mode in a topological coupling network of a power grid system through a multicolor set, and establishing an information processing model based on the multicolor set; constructing a topological graph for searching all topological propagation paths according to the information processing model based on the multicolor set, and establishing a topological traceability mathematical model; compared with the existing model analysis process of the digital power grid, the method can accurately establish the topological model of the digital power grid, can better analyze the problem of the power grid when performing digital power grid analysis and power grid management, and improves the energy efficiency ratio of power grid operation.
Example 2
On the basis of the above embodiment, the acquisition part at least includes: the system comprises a sensor group, a user terminal, a control center, electric equipment and a routing part; the sensor group, the user terminal, the control center, the electric equipment and the routing part can carry out mirror image copying on running data of the sensor group, send the data after mirror image copying to the data part for storage and send the data after mirror image copying to the data preprocessing part in the running process.
By adopting the technical scheme, the acquired data is not directly transmitted in real time through the self operating data, but is copied through a mirror image, so that the data can be reserved in the local acquisition part, and the power grid fault tracing and power grid management are facilitated.
Example 3
On the basis of the above embodiment, the data preprocessing section includes: the method comprises the following steps: the data cleaning unit is configured for removing the unique attribute, processing missing values and abnormal values, detecting and processing the running data; the data specification unit is configured to perform data specification processing on the data after the data cleaning, and comprises: removing an average value, calculating a covariance matrix, calculating an eigenvalue and an eigenvector of the covariance matrix, sorting the eigenvalues from large to small, reserving the largest eigenvector, and converting data into a new space constructed by the eigenvector; finally, new processed data are obtained, and the data are irrelevant pairwise, but the original information is kept; the data standardization unit is configured for carrying out data standardization processing on the data subjected to the data specification processing, and scaling the data in proportion to enable the data to fall into a small specific interval; in which the data is linearly transformed using a transfer function such that the result falls to [0,1 ]]Interval, the transfer function is as follows:
wherein x is*The result is the result after data standardization processing; x is data to be processed; min is the minimum value in the data; max is the maximum value in the data; and the data conversion unit is configured to perform periodic sampling on the data subjected to the data standardization processing, further realize data discretization processing and convert continuous data into discrete data.
By adopting the technical scheme, the data reduction means that the data volume is reduced to the maximum extent on the premise of keeping the original appearance of the data as much as possible. There are two main approaches to data reduction: attribute selection and data sampling, for attributes and records in the original dataset, respectively. Assume that data is selected for analysis at the company's data warehouse. So that the data set will be very large. Complex data analysis buckle mining on massive data would take a long time, making such analysis impractical or infeasible. Data reduction techniques may be used to obtain a reduced representation of a data set that, while small, substantially maintains the integrity of the original data. In this way, mining on the reduced data set will be more efficient and produce the same (or nearly the same) analysis results.
And (5) carrying out data analysis by using the normalized data. Data normalization is the indexing of statistical data. The data standardization processing mainly comprises two aspects of data chemotaxis processing and dimensionless processing. The data homochemotaxis processing mainly solves the problem of data with different properties, directly sums indexes with different properties and cannot correctly reflect the comprehensive results of different acting forces, and firstly considers changing the data properties of inverse indexes to ensure that all the indexes are homochemotactic for the acting forces of the evaluation scheme and then sum to obtain correct results. The data dimensionless process mainly addresses the comparability of data. There are many methods for data normalization, and the methods are commonly used, such as "min-max normalization", "Z-score normalization", and "normalization on a decimal scale". Through the standardization processing, the original data are all converted into non-dimensionalized index mapping evaluation values, namely, all index values are in the same quantity level, and comprehensive evaluation analysis can be carried out.
Example 4
On the basis of the previous embodiment, the model part performs model analysis based on the data after data processing, defines data types and relationships, defines data attributes, performs model reasoning, and completes the model creation method to execute the following steps: obtaining a function coupling relation, nodes and directed edges among all functional units in the power grid system through structural analysis, and establishing a topological coupling network of the power grid system; defining data types and data relations, defining data attributes at the same time, obtaining the coupling connection relation among multiple attributes of data of a topological mode in a topological coupling network of a power grid system through a multicolor set, and establishing an information processing model based on the multicolor set; constructing a topological graph for searching all topological propagation paths according to the information processing model based on the multicolor set, and establishing a topological traceability mathematical model; acquiring design requirement information of a power grid system, and building a visual simulation model of a digital twin body of the power grid system on a simulation platform; establishing an information channel and an instruction channel of a digital twin body and a real object twin body in the power grid system by using a digital twin technology, and establishing a digital twin model of the power grid system; model reasoning is carried out on a digital twin model based on a power grid system to obtain topological information, all topological propagation paths in the information processing model based on the multicolor set are searched through a breadth-first root search algorithm, a topological root is found, and topology tracing is completed.
Specifically, the digital twin is a full life cycle process of reflecting corresponding entity equipment by fully utilizing data such as a physical model, sensor updating, operation history and the like, integrating a multidisciplinary, multi-physical quantity, multi-scale and multi-probability simulation process and completing mapping in a virtual space. Digital twinning is an beyond-realistic concept that can be viewed as a digital mapping system of one or more important, interdependent equipment systems.
The goal of digital twinning is to make a more realistic virtual model of the product to bridge the gap between design and manufacturing and to reflect the real and virtual worlds, while at the present stage no one-to-one, complete mapping between the digital world and the physical world is possible.
The current digital twin system generally uses a computer 3D model which is built in advance as a digital entity in the digital twin system, a combined use case of the digital twin system and a virtual imaging technology is lacked, the application of the virtual imaging technology can directly improve the user impression and immersion of the digital twin system, and for a large-scene digital twin system such as space exploration, a digital factory, a virtual city and the like, the traditional computer 3D model cannot provide more detailed description at the same time due to single user visual angle.
At present, strong information mapping cannot be realized between a digital entity and a physical entity, that is, a large amount of valuable information is lost in the tracking process of the digital entity on the information of the physical entity. On one hand, the range of the acquired information is limited due to the bandwidth limitation of the sensor acquisition equipment, and on the other hand, the terminal processor has limited computing capacity and cannot carry analysis processing of mass data.
The current information transmission mode aiming at the digital twin system is not suitable for the virtual imaging technology which needs a large amount of data flow support, and especially when long-distance information transmission is needed between the digital twin bodies, the requirement of real-time processing and large amount of information transmission is generally insufficient for the current digital twin system, and the system is difficult to consider both real-time performance and information integrity.
Example 5
On the basis of the above embodiment, the method for obtaining the coupling connection relationship between the multiple attributes of the topological modes in the topological coupling network of the power grid system through the multi-color set performs the following steps: classifying the data by the data category and the relationship to obtain the classification result of each data, and respectively calculating the mapping rule of each data and the attribute according to the corresponding relationship between each classification result and the data attribute by the following processes: extracting data characteristics according to the data categories and the relations, and counting the times of the data characteristics conforming to each data category by using the following formula:
wherein N is the number of times of conforming to the category, S is the number of data, and lambdaiIs the weight of the ith data, M is the number of features in each class, countjThe characteristic number of the ith data; setting the priority of the corresponding data from high to low according to the number of times that the counted data conforms to each category and the number of the data from high to low, completing the data category trainingRefining; and according to the corresponding relation between the classification result of each known data and the real classification result thereof, counting and analyzing the mapping rule between the category and the attribute.
Example 6
A digital twin based digital power grid method, the method performing the steps of: step 1: acquiring operation data of a power grid; step 2: and performing data processing on the operation data, wherein the data processing comprises the following steps: data cleaning, data specification, data standardization and data transformation; and step 3: performing model analysis based on the data after data processing, defining data types and relationships, defining data attributes, performing model reasoning, completing model creation, constructing a power grid graph based on the created model, performing data association on the data after data processing, and generating associated data; and 4, step 4: storing the operation data, the data after data processing and the associated data, and simultaneously respectively providing the step 1, the step 2 and the step 3 for data calling.
Specifically, after data processing and digital twins are utilized to carry out data preprocessing on collected power grid data, abstract classification and attribute definition are carried out on the data, and then a power grid model is established based on the data by combining the topological relation of original power grid equipment corresponding to each data, so that the power grid is completely digitalized, the topological structure of the power grid is accurately reproduced, the analysis of the digital power grid is facilitated, and the energy efficiency ratio of power grid management is further improved.
Example 7
On the basis of the above embodiment, the step 1: acquiring the operation data of the power grid comprises the following steps: and (3) carrying out mirror image copying on the running data of the sensor group, the user terminal, the control center, the electric equipment and the routing part in real time in the running process, sending the data after mirror image copying to the step (4) for storage, and sending the data after mirror image copying to the step (2).
Example 8
On the basis of the above embodiment, the step 2: and performing data processing on the operation data, wherein the data processing comprises the following steps: the method for cleaning data, stipulating data, standardizing data and transforming data comprises the following steps: removing unique attribute and processing defect from operation dataLoss value and abnormal value detection and processing; the data protocol processing is carried out on the data after the data cleaning, and the data protocol processing method comprises the following steps: removing an average value, calculating a covariance matrix, calculating an eigenvalue and an eigenvector of the covariance matrix, sorting the eigenvalues from large to small, reserving the largest eigenvector, and converting data into a new space constructed by the eigenvector; finally, new processed data are obtained, and the data are irrelevant pairwise, but the original information is kept; carrying out data standardization processing on the data subjected to the data specification processing, and scaling the data in proportion to enable the data to fall into a small specific interval; in which the data is linearly transformed using a transfer function such that the result falls to [0,1 ]]Interval, the transfer function is as follows:
wherein x is*The result is the result after data standardization processing; x is data to be processed; min is the minimum value in the data; max is the maximum value in the data; and carrying out periodic sampling on the data subjected to the data standardization processing, further realizing data discretization processing, and converting continuous data into discrete data.
Specifically, the method and the device perform data preprocessing on the power grid operating data acquired by the mirror image copying of the acquired part, avoid data errors generated when the power grid equipment acquires the data and copies the mirror image, and improve the accuracy of the data.
Example 9
On the basis of the previous embodiment, the model part performs model analysis based on the data after data processing, defines data types and relationships, defines data attributes, performs model reasoning, and completes the model creation method to execute the following steps: obtaining a function coupling relation, nodes and directed edges among all functional units in the power grid system through structural analysis, and establishing a topological coupling network of the power grid system; defining data types and data relations, defining data attributes at the same time, obtaining the coupling connection relation among multiple attributes of data of a topological mode in a topological coupling network of a power grid system through a multicolor set, and establishing an information processing model based on the multicolor set; constructing a topological graph for searching all topological propagation paths according to the information processing model based on the multicolor set, and establishing a topological traceability mathematical model; acquiring design requirement information of a power grid system, and building a visual simulation model of a digital twin body of the power grid system on a simulation platform; establishing an information channel and an instruction channel of a digital twin body and a real object twin body in the power grid system by using a digital twin technology, and establishing a digital twin model of the power grid system; model reasoning is carried out on a digital twin model based on a power grid system to obtain topological information, all topological propagation paths in the information processing model based on the multicolor set are searched through a breadth-first root search algorithm, a topological root is found, and topology tracing is completed.
Specifically, in the process of establishing the model of the digital power grid, firstly, model analysis is carried out, data types and relations are defined, data attributes are defined, then, model reasoning is carried out, model establishment is completed, in the process, the functional coupling relations, the nodes and the directed edges among all functional units in the power grid system are obtained through structural analysis, and a topological coupling network of the power grid system is established; defining data types and data relations, defining data attributes at the same time, obtaining the coupling connection relation among multiple attributes of data of a topological mode in a topological coupling network of a power grid system through a multicolor set, and establishing an information processing model based on the multicolor set; constructing a topological graph for searching all topological propagation paths according to the information processing model based on the multicolor set, and establishing a topological traceability mathematical model; compared with the existing model analysis process of the digital power grid, the method can accurately establish the topological model of the digital power grid, can better analyze the problem of the power grid when performing digital power grid analysis and power grid management, and improves the energy efficiency ratio of power grid operation.
Example 10
On the basis of the above embodiment, the method for obtaining the coupling connection relationship between the multiple attributes of the topological modes in the topological coupling network of the power grid system through the multi-color set performs the following steps: classifying the data by data category and relation to obtain classification result of each data, and classifying each data according to eachAnd respectively calculating the mapping rule of each data and attribute according to the corresponding relation between the classification result and the data attribute by the following processes: extracting data characteristics according to the data categories and the relations, and counting the times of the data characteristics conforming to each data category by using the following formula:
wherein N is the number of times of conforming to the category, S is the number of data, and lambdaiIs the weight of the ith data, M is the number of features in each class, countjThe characteristic number of the ith data; according to the counted times that the data conforms to each category, setting the priority of the category of the corresponding data from high to low according to the number of the data from high to low, and finishing the data category training; and according to the corresponding relation between the classification result of each known data and the real classification result thereof, counting and analyzing the mapping rule between the category and the attribute.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process and related description of the system described above may refer to the corresponding process in the foregoing method embodiments, and will not be described herein again.
It should be noted that, the system provided in the foregoing embodiment is only illustrated by dividing the functional modules, and in practical applications, the functions may be distributed by different functional modules according to needs, that is, the modules or steps in the embodiment of the present invention are further decomposed or combined, for example, the modules in the foregoing embodiment may be combined into one module, or may be further split into multiple sub-modules, so as to complete all or unit functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the modules or steps, and are not to be construed as unduly limiting the present invention.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes and related descriptions of the storage device and the processing device described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Those of skill in the art would appreciate that the various illustrative modules, method steps, and modules described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that programs corresponding to the software modules, method steps may be located in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. To clearly illustrate this interchangeability of electronic hardware and software, various illustrative components and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as electronic hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The terms "first," "second," and the like are used for distinguishing between similar elements and not necessarily for describing or implying a particular order or sequence.
The terms "comprises," "comprising," or any other similar term are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention.
Claims (10)
1. A digital twin based digital power grid system, the system comprising: the acquisition part is configured to acquire the operation data of the power grid; the data preprocessing part is configured to perform data processing on the running data, and comprises the following steps: data cleaning, data specification, data standardization and data transformation; the model part is configured for carrying out model analysis based on the data after data processing, defining data types and relations, defining data attributes, carrying out model reasoning, completing model creation, constructing a power grid graph based on the created model, carrying out data association on the data after the data processing, and generating associated data; and the data part is configured for storing the operation data, the data after data processing and the associated data, and simultaneously, the data part is respectively provided for the acquisition part, the data preprocessing part and the model part to call the data.
2. The system of claim 1, wherein the acquisition portion comprises at least: the system comprises a sensor group, a user terminal, a control center, electric equipment and a routing part; the sensor group, the user terminal, the control center, the electric equipment and the routing part can carry out mirror image copying on running data of the sensor group, send the data after mirror image copying to the data part for storage and send the data after mirror image copying to the data preprocessing part in the running process.
3. The system of claim 2, wherein the data pre-processing portion comprises: the method comprises the following steps: the data cleaning unit is configured for removing the unique attribute, processing missing values and abnormal values, detecting and processing the running data; the data specification unit is configured to perform data specification processing on the data after the data cleaning, and comprises: mean value removing, covariance matrix calculation, eigenvalue and eigenvector of covariance matrix calculation, and eigenvalue pair calculationSorting from big to small, reserving the largest feature vector, and converting the data into a new space constructed by the feature vectors; finally, new processed data are obtained, and the data are irrelevant pairwise, but the original information is kept; the data standardization unit is configured for carrying out data standardization processing on the data subjected to the data specification processing, and scaling the data in proportion to enable the data to fall into a small specific interval; in which the data is linearly transformed using a transfer function such that the result falls to [0,1 ]]Interval, the transfer function is as follows:
wherein x is*The result is the result after data standardization processing; x is data to be processed; min is the minimum value in the data; max is the maximum value in the data; and the data conversion unit is configured to perform periodic sampling on the data subjected to the data standardization processing, further realize data discretization processing and convert continuous data into discrete data.
4. The system of claim 3, wherein the model part performs model analysis based on the data after data processing, defines data categories and relationships, defines data attributes, and performs model inference, and the method for completing model creation performs the following steps: obtaining a function coupling relation, nodes and directed edges among all functional units in the power grid system through structural analysis, and establishing a topological coupling network of the power grid system; defining data types and data relations, defining data attributes at the same time, obtaining the coupling connection relation among multiple attributes of data of a topological mode in a topological coupling network of a power grid system through a multicolor set, and establishing an information processing model based on the multicolor set; constructing a topological graph for searching all topological propagation paths according to the information processing model based on the multicolor set, and establishing a topological traceability mathematical model; acquiring design requirement information of a power grid system, and building a visual simulation model of a digital twin body of the power grid system on a simulation platform; establishing an information channel and an instruction channel of a digital twin body and a real object twin body in the power grid system by using a digital twin technology, and establishing a digital twin model of the power grid system; model reasoning is carried out on a digital twin model based on a power grid system to obtain topological information, all topological propagation paths in the information processing model based on the multicolor set are searched through a breadth-first root search algorithm, a topological root is found, and topology tracing is completed.
5. The system according to claim 4, wherein the method for obtaining the coupling connection relationship between the multiple attributes of the topological mode in the topological coupling network of the power grid system through the polychrome set performs the following steps: classifying the data by the data category and the relationship to obtain the classification result of each data, and respectively calculating the mapping rule of each data and the attribute according to the corresponding relationship between each classification result and the data attribute by the following processes: extracting data characteristics according to the data categories and the relations, and counting the times of the data characteristics conforming to each data category by using the following formula:
wherein N is the number of times of conforming to the category, S is the number of data, and lambdaiIs the weight of the ith data, M is the number of features in each class, countjThe characteristic number of the ith data; according to the counted times that the data conforms to each category, setting the priority of the category of the corresponding data from high to low according to the number of the data from high to low, and finishing the data category training; and according to the corresponding relation between the classification result of each known data and the real classification result thereof, counting and analyzing the mapping rule between the category and the attribute.
6. A digital twin based digital power grid method based on the system of one of claims 1 to 5, characterized in that the method performs the following steps: step 1: acquiring operation data of a power grid; step 2: and performing data processing on the operation data, wherein the data processing comprises the following steps: data cleaning, data specification, data standardization and data transformation; and step 3: performing model analysis based on the data after data processing, defining data types and relationships, defining data attributes, performing model reasoning, completing model creation, constructing a power grid graph based on the created model, performing data association on the data after data processing, and generating associated data; and 4, step 4: storing the operation data, the data after data processing and the associated data, and simultaneously respectively providing the step 1, the step 2 and the step 3 for data calling.
7. The method of claim 6, wherein the step 1: acquiring the operation data of the power grid comprises the following steps: and (3) carrying out mirror image copying on the running data of the sensor group, the user terminal, the control center, the electric equipment and the routing part in real time in the running process, sending the data after mirror image copying to the step (4) for storage, and sending the data after mirror image copying to the step (2).
8. The method of claim 7, wherein the step 2: and performing data processing on the operation data, wherein the data processing comprises the following steps: the method for cleaning data, stipulating data, standardizing data and transforming data comprises the following steps: detecting and processing the running data by removing the unique attribute and processing the missing value and the abnormal value; the data protocol processing is carried out on the data after the data cleaning, and the data protocol processing method comprises the following steps: removing an average value, calculating a covariance matrix, calculating an eigenvalue and an eigenvector of the covariance matrix, sorting the eigenvalues from large to small, reserving the largest eigenvector, and converting data into a new space constructed by the eigenvector; finally, new processed data are obtained, and the data are irrelevant pairwise, but the original information is kept; carrying out data standardization processing on the data subjected to the data specification processing, and scaling the data in proportion to enable the data to fall into a small specific interval; in which the data is linearly transformed using a transfer function such that the result falls to [0,1 ]]Interval, the transfer function is as follows:
wherein x is*The result is the result after data standardization processing; x is data to be processed; min is numberAccording to the minimum value; max is the maximum value in the data; and carrying out periodic sampling on the data subjected to the data standardization processing, further realizing data discretization processing, and converting continuous data into discrete data.
9. The method of claim 8, wherein the model is based in part on data processed for model analysis, defining data classes and relationships, defining data attributes, and performing model inference to complete model creation, wherein the method comprises the steps of: obtaining a function coupling relation, nodes and directed edges among all functional units in the power grid system through structural analysis, and establishing a topological coupling network of the power grid system; defining data types and data relations, defining data attributes at the same time, obtaining the coupling connection relation among multiple attributes of data of a topological mode in a topological coupling network of a power grid system through a multicolor set, and establishing an information processing model based on the multicolor set; constructing a topological graph for searching all topological propagation paths according to the information processing model based on the multicolor set, and establishing a topological traceability mathematical model; acquiring design requirement information of a power grid system, and building a visual simulation model of a digital twin body of the power grid system on a simulation platform; establishing an information channel and an instruction channel of a digital twin body and a real object twin body in the power grid system by using a digital twin technology, and establishing a digital twin model of the power grid system; model reasoning is carried out on a digital twin model based on a power grid system to obtain topological information, all topological propagation paths in the information processing model based on the multicolor set are searched through a breadth-first root search algorithm, a topological root is found, and topology tracing is completed.
10. The method according to claim 9, wherein the obtaining of the coupling connection relationship between the multiple attributes of the topological pattern in the topologically coupled network of the power grid system through the polychrome ensemble, the method of building the polychrome ensemble based information processing model performs the steps of: classifying the data by data category and relation to obtain classification result of each data, and determining the classification result and data attribute according to each classification resultAnd respectively calculating the mapping rule of each data and attribute through the following processes: extracting data characteristics according to the data categories and the relations, and counting the times of the data characteristics conforming to each data category by using the following formula:
wherein N is the number of times of conforming to the category, S is the number of data, and lambdaiIs the weight of the ith data, M is the number of features in each class, countjThe characteristic number of the ith data; according to the counted times that the data conforms to each category, setting the priority of the category of the corresponding data from high to low according to the number of the data from high to low, and finishing the data category training; and according to the corresponding relation between the classification result of each known data and the real classification result thereof, counting and analyzing the mapping rule between the category and the attribute.
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