Time-frequency data management system and method based on cloud computing and multi-source data fusion

Abstract

The invention discloses a time-frequency data management system and method based on cloud computing and multi-source data fusion, and belongs to the technical field of power system metering and time synchronization. The system comprises a system data flow design unit used for classifying key data of a power system into time-frequency synchronization data and command and monitoring data; the data fusion design unit is used for fusing the classified multi-source time-frequency synchronization data and command and monitoring data; and the data standardization design unit is used for performing standardization calculation processing on the data obtained by fusion based on cloud calculation to obtain standardized data, and storing the standardized data in a pre-formulated adaptive time-frequency incremental data structure and a storage mode. According to the invention, the intelligent level and the operation efficiency of the power system are comprehensively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system metering and time synchronization, and more specifically, to a time-frequency data management system and method based on cloud computing and multi-source data fusion. Background Art

[0002] At present, in modern power systems, time and frequency measurement standards are an important basis for ensuring the safety of power grid operation and fair transactions in the power market. However, the power system has problems such as low time synchronization accuracy, inaccurate transmission of time and frequency values, and lack of real-time monitoring and intelligent diagnosis methods. Traditional time synchronization technology has low timing accuracy and cannot meet high-precision requirements. In addition, the sources of time and frequency data are diverse and complex, and heterogeneous data management faces challenges.

[0003] To solve these problems, a new time-frequency data management system that integrates modern information technology and advanced algorithms is urgently needed. The system should have high-precision time synchronization capabilities, provide powerful data processing and analysis functions, and achieve real-time monitoring and intelligent diagnosis. The introduction of cloud computing platforms provides support for large-scale data processing and storage, and multi-source data fusion technology improves data accuracy and consistency, thereby improving the safety, reliability and intelligence level of power grid operation, ensuring fairness and justice in power market transactions, and promoting the sustainable development of the power industry.

[0004] In the prior art:

[0005] A distribution network fault identification method and system based on intelligent data fusion analysis, which obtains multiple electrical characteristic quantities of acquisition nodes through sensors and performs fault identification with high reliability; at the same time, the present invention sequentially performs regional differential processing, expansion and dimension reduction on the acquired electrical characteristic quantities, determines outliers based on the LOF algorithm to predict whether a fault occurs, and determines the fault location if a fault occurs, and then calculates the wavelet singular entropy value of the three-phase voltage at the fault location, inputs the calculation result into an SVM fault identification model, and obtains the distribution network fault phase identification result, without complex setting calculation, and with high speed.

[0006] This invention mainly provides a distribution network fault identification method based on intelligent data fusion analysis, and does not involve related technologies for multi-source data fusion.

[0007] A multi-source information fusion environment monitoring device and system thereof, comprising a terminal application module, an edge gateway module, a cloud monitoring module, a LoRa communication module and an NB-IoT communication module. The terminal application module is used to collect, pre-process and fuse multi-source homogeneous data for environmental monitoring data, and the data is uploaded to the edge gateway module through the LoRa communication module; then, the edge gateway module processes the received data, realizes task decomposition and allocation according to dynamic perception task drive, schedules the corresponding terminal application module to complete multi-source heterogeneous data fusion, and uploads the decision result to the cloud monitoring module through the NB-IoT communication module for display and real-time monitoring of the current environment status, and reports abnormal information to the corresponding department, adopts information fusion technology to reduce network congestion, effectively saves energy consumption, and prolongs the service life of the network system.

[0008] The invention mainly includes a multi-source information fusion environment monitoring device, which does not involve how to analyze and process a large amount of multi-source data. Summary of the invention

[0009] In view of the above problems, the present invention proposes a time-frequency data management system based on cloud computing and multi-source data fusion, comprising:

[0010] System data flow design unit, used to classify the key data of the power system into time-frequency synchronization data and command and monitoring data;

[0011] A data fusion design unit, used for fusing the classified multi-source time-frequency synchronization data and command and monitoring data;

[0012] The data standardization design unit is used to perform standardized calculation processing on the fused data based on cloud computing to obtain standardized data, and store the standardized data in a pre-defined adaptive time-frequency incremental data structure and storage mode.

[0013] Optionally, the time-frequency synchronization data is used for time-frequency value transfer.

[0014] Optionally, commands and monitoring data are used for remote command control and transmission of node status monitoring data.

[0015] Optionally, a data fusion design unit integrates the archival information of the time-frequency value synchronization modules at each level according to the timing scheme and hierarchical relationship;

[0016] The hierarchical relationship includes: a one-to-many or one-to-one hierarchical topological relationship and its associated relationship.

[0017] Optionally, the data standardization design unit formulates the most compatible time-frequency data recording parameter specifications for different levels of data accuracy;

[0018] The parameter specifications include: data format, data length, data attributes, data uniqueness and data standard requirements.

[0019] Optional data attributes, including: device type of nodes at each level.

[0020] On the other hand, the present invention also proposes a time-frequency data management method based on cloud computing and multi-source data fusion, comprising:

[0021] Classify the key data of the power system into time-frequency synchronization data and command and monitoring data;

[0022] fusing the classified multi-source time-frequency synchronization data and command and monitoring data;

[0023] The fused acquired data is subjected to standardized computational processing based on cloud computing to obtain standardized data, which is then stored in a pre-defined adaptive time-frequency incremental data structure and storage mode.

[0024] Optionally, the time-frequency synchronization data is used for time-frequency value transfer.

[0025] Optionally, commands and monitoring data are used for remote command control and transmission of node status monitoring data.

[0026] Optionally, the method further includes:

[0027] Integrate the archival information of the time-frequency value synchronization modules at each level according to the timing scheme and hierarchical relationship;

[0028] The hierarchical relationship includes: a one-to-many or one-to-one hierarchical topological relationship and its associated relationship.

[0029] Optionally, the method further includes:

[0030] Formulate the most compatible time and frequency data recording parameter specifications for different levels of data accuracy;

[0031] The parameter specifications include:

[0032] Data format, data length, data attributes, data uniqueness and data standard requirements.

[0033] Optional data attributes, including:

[0034] Device type of nodes at each level.

[0035] In yet another aspect, the present invention further provides a computing device, comprising: one or more processors;

[0036] a processor for executing one or more programs;

[0037] When the one or more programs are executed by the one or more processors, the above-described method is implemented.

[0038] In yet another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, the method described above is implemented.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The present invention provides a time-frequency data management system based on cloud computing and multi-source data fusion, including: a system data flow design unit, used to classify the key data of the power system into time-frequency synchronization data and command and monitoring data; a data fusion design unit, used to fuse the classified multi-source time-frequency synchronization data and command and monitoring data; a data standardization design unit, used to perform standardized calculation processing on the fused data based on cloud computing to obtain standardized data, and store the standardized data in a pre-established adaptive time-frequency incremental data structure and storage mode. The present invention realizes high-precision time synchronization of nodes at all levels in the power system through cloud computing and multi-source data fusion technology, significantly improving the safety and reliability of power grid operation; the system can monitor the time-frequency data in real time throughout the entire chain, and quickly identify and handle abnormal situations through an intelligent diagnosis module to ensure the stable operation of the power system; through the efficient fusion and management of multi-source heterogeneous time-frequency data, a unified data standard and format are provided, which facilitates data storage, processing and analysis, thereby comprehensively improving the intelligence level and operation efficiency of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a structural diagram of the system of the present invention;

[0042] Figure 2 It is the principle diagram of the system of the present invention;

[0043] Figure 3 This is a schematic diagram of the data standard system of the present invention;

[0044] Figure 4 Flow chart of the method of the present invention. DETAILED DESCRIPTION

[0045] Now, exemplary embodiments of the present invention are described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0046] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0047] Embodiment 1:

[0048] The present invention proposes a time-frequency data management system 100 based on cloud computing and multi-source data fusion, such as Figure 1 As shown, including:

[0049] A system data flow design unit 101, for classifying key data of the power system into time-frequency synchronization data and command and monitoring data;

[0050] A data fusion design unit 102, configured to fuse the classified multi-source time-frequency synchronization data and command and monitoring data;

[0051] The data standardization design unit 103 is used to perform standardized calculation processing on the fused data based on cloud computing to obtain standardized data, and store the standardized data in a pre-defined adaptive time-frequency incremental data structure and storage mode.

[0052] Among them, the time-frequency synchronization data is used for time-frequency value transmission.

[0053] Among them, commands and monitoring data are used for remote command control and the return of node status monitoring data.

[0054] Among them, the data fusion design unit integrates the archival information of the time-frequency value synchronization modules at each level according to the timing scheme and hierarchical relationship;

[0055] The hierarchical relationship includes: a one-to-many or one-to-one hierarchical topological relationship and its associated relationship.

[0056] Among them, the data standardization design unit formulates the most compatible time-frequency data recording parameter specifications for different levels of data accuracy;

[0057] The parameter specifications include: data format, data length, data attributes, data uniqueness and data standard requirements.

[0058] The data attributes include: device types of nodes at each level.

[0059] The system principle is as follows Figure 2 As shown, the following is an explanation based on the principle:

[0060] System data flow design: System key data is divided into time-frequency traceability data and command and monitoring data;

[0061] Time-frequency synchronization data is mainly used for the transmission of time-frequency values, and has real-time requirements for data interaction. Generally, real-time data is required to be interacted within 2 minutes. Command and monitoring data is mainly used for remote command control and node status monitoring data feedback. This part of data has lower real-time requirements and is subject to a maximum delay of 1 day.

[0062] Data fusion design: Based on the above system data flow design, in the design and research of the time and frequency traceability system, the archive information of the time and frequency value synchronization modules at each level is integrated and designed for the timing scheme and hierarchical relationship, and the necessary attributes such as synchronization accuracy requirements, hierarchy and communication method are investigated. The hierarchical relationship design research includes one-to-many or one-to-one hierarchical topological relationships and their associations, and the investigation information includes synchronization methods and hierarchical attributes. The business fusion relationship research designs the association and mapping relationship between the on-site acquisition terminal and the main time and frequency synchronization unit of the substation, and the electric energy meter and the terminal time and frequency synchronization unit of the substation. Based on the above investigation results, the digital model design of heterogeneous data fusion is carried out to ensure data standardization.

[0063] Data standardization design: In the data parameter design research of the time-frequency traceability system, an adaptive time-frequency incremental data structure and storage mode are formulated based on the data and business characteristics of the system. According to the data accuracy of different levels, the time-frequency data recording parameter specifications with maximum compatibility are formulated, including necessary information such as data format and data length. In the data attribute design, it is necessary to distinguish and design the equipment types of nodes at each level, such as the network provincial clock source node, the user server clock node, the low-voltage concentrator carrier module master clock node, the electric energy meter carrier module slave clock node, etc., to ensure that the node type is clear.

[0064] In terms of data uniqueness design, for archival data, according to the principle of data uniqueness or one number and one source, a unique identifier for archival data is formulated to ensure the logical uniqueness and data requirements of later data applications. In terms of data source requirements, in order to ensure the uniqueness and traceability of data sources, the same type of data must have a clear unique data source to avoid difficulties in tracing abnormal data in the later stage.

[0065] In terms of data standard requirements, for the target data structure, various field information is mapped and maintained to meet the constraints of subject definition, information items, and standard codes. In terms of business mapping interpretation, for external source data, the defined data standards are associated with business systems and business applications to provide business explanations. In terms of data expansion requirements, the scalability of the data structure is guaranteed to reserve sufficient space for subsequent new business data or time-frequency data.

[0066] According to the data type and source of the traceability system digital platform, the data standards are as follows: Figure 3 As shown in the figure, it is divided into basic archives, platform increments and external access. The basic archive data records the relevant equipment information of all nodes accessed by the platform, including unique identification, address information and type. The platform increment data is built based on the time and frequency traceability system, including node operation status, timing results and time and frequency freezing data, etc., to meet the real-time online monitoring and intelligent diagnosis requirements of the time and frequency traceability platform. The external access data is synchronized through basic business application systems such as MDS and electricity consumption information collection system, including meter clock data, terminal clock data and marketing industry expansion packaging process.

[0067] Embodiment 2:

[0068] The present invention also proposes a time-frequency data management method based on cloud computing and multi-source data fusion, such as Figure 4 As shown, including:

[0069] Step 1: Classify the key data of the power system into time-frequency synchronization data and command and monitoring data;

[0070] Step 2: fusing the classified multi-source time-frequency synchronization data and command and monitoring data;

[0071] Step 3: Perform standardized calculation processing on the fused data based on cloud computing to obtain standardized data, and store the standardized data in a pre-defined adaptive time-frequency incremental data structure and storage mode.

[0072] Among them, the time-frequency synchronization data is used for time-frequency value transmission.

[0073] Among them, commands and monitoring data are used for remote command control and the return of node status monitoring data.

[0074] The method further includes:

[0075] Integrate the archival information of the time-frequency value synchronization modules at each level according to the timing scheme and hierarchical relationship;

[0076] The hierarchical relationship includes: a one-to-many or one-to-one hierarchical topological relationship and its associated relationship.

[0077] The method further includes:

[0078] Formulate the most compatible time and frequency data recording parameter specifications for different levels of data accuracy;

[0079] The parameter specifications include:

[0080] Data format, data length, data attributes, data uniqueness and data standard requirements.

[0081] The data attributes include:

[0082] Device type of nodes at each level.

[0083] The present invention realizes high-precision time synchronization of nodes at all levels in the power system through cloud computing and multi-source data fusion technology, significantly improving the safety and reliability of power grid operation; the system can monitor the time-frequency data in real time throughout the entire chain, and quickly identify and handle abnormal situations through intelligent diagnosis modules to ensure the stable operation of the power system; through the efficient fusion and management of multi-source heterogeneous time-frequency data, a unified data standard and format is provided to facilitate data storage, processing and analysis, thereby comprehensively improving the intelligence level and operation efficiency of the power system.

[0084] Embodiment 3:

[0085] Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding functions, so as to implement the steps of the method in the above embodiment.

[0086] Embodiment 4:

[0087] Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It is understandable that the computer-readable storage medium here can include both a built-in storage medium in a computer device and an extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiment.

[0088] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0089] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0090] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0091] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0092] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0093] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A time-frequency data management system based on cloud computing and multi-source data fusion, characterized in that: include: System data flow design unit, used to classify the key data of the power system into time-frequency synchronization data and command and monitoring data; A data fusion design unit, used for fusing the classified multi-source time-frequency synchronization data and command and monitoring data; The data standardization design unit is used to perform standardized calculation processing on the fused data based on cloud computing to obtain standardized data, and store the standardized data in a pre-defined adaptive time-frequency incremental data structure and storage mode.

2. The time-frequency data management system according to claim 1, characterized in that: The time-frequency synchronization data is used for time-frequency value transmission.

3. The time-frequency data management system according to claim 1, characterized in that: The commands and monitoring data are used for remote command control and the return of node status monitoring data.

4. The time-frequency data management system according to claim 1, characterized in that: The data fusion design unit integrates the archive information of the time-frequency value synchronization modules at each level according to the timing scheme and the hierarchical relationship; The hierarchical relationship includes: a one-to-many or one-to-one hierarchical topological relationship and its associated relationship.

5. The time-frequency data management system according to claim 1, characterized in that: The data standardization design unit formulates the most compatible time-frequency data recording parameter specifications for different levels of data accuracy; The parameter specifications include: data format, data length, data attributes, data uniqueness and data standard requirements.

6. The time-frequency data management system according to claim 5, characterized in that: The data attributes include: device types of nodes at each level.

7. A time-frequency data management method based on cloud computing and multi-source data fusion, characterized in that: include: Classify the key data of the power system into time-frequency synchronization data and command and monitoring data; fusing the classified multi-source time-frequency synchronization data and command and monitoring data; The fused acquired data is subjected to standardized computational processing based on cloud computing to obtain standardized data, which is then stored in a pre-defined adaptive time-frequency incremental data structure and storage mode.

8. The time-frequency data management method according to claim 7, characterized in that: The time-frequency synchronization data is used for time-frequency value transmission.

9. The time-frequency data management method according to claim 7, characterized in that: The commands and monitoring data are used for remote command control and the return of node status monitoring data.

10. The time-frequency data management method according to claim 7, characterized in that: The method further comprises: Integrate the archival information of the time-frequency value synchronization modules at each level according to the timing scheme and hierarchical relationship; The hierarchical relationship includes: a one-to-many or one-to-one hierarchical topological relationship and its associated relationship.

11. The time-frequency data management method according to claim 7, characterized in that: The method further comprises: Formulate the most compatible time and frequency data recording parameter specifications for different levels of data accuracy; The parameter specifications include: Data format, data length, data attributes, data uniqueness and data standard requirements.

12. The time-frequency data management method according to claim 11, characterized in that: The data attributes include: Device type of nodes at each level.

13. A computer device, characterized in that: include: one or more processors; a processor for executing one or more programs; When the one or more programs are executed by the one or more processors, the method according to any one of claims 7 to 12 is implemented.

14. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed, the method according to any one of claims 7 to 12 is implemented.

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