A method and system for establishing a power grid measurement database

Abstract

The present invention provides a method and system for establishing a power grid measurement database, the method comprising: determining a multi-source measurement data index based on at least one power grid measurement data dimension; wherein the at least one power grid measurement data dimension comprises: a time dimension, a space dimension, an application dimension, an attribute dimension and a physical dimension; reorganizing the power grid measurement data in the power grid measurement database based on the multi-source measurement data index; retrieving the input business requirements in the power grid measurement database to obtain corresponding business requirement data; wherein the business requirements comprise: a field value or a field range corresponding to a specified dimension field in the multi-source measurement data index. The present invention achieves high-speed data retrieval from different dimensions of time, space, application and equipment by establishing a power grid measurement database, meets the differentiated data requirements of different application scenarios, and can accurately and quickly store and access multi-source heterogeneous data.

Description

Technical Field

[0001] The present invention relates to the field of data access, and in particular to a method and a system for establishing a power grid measurement database. Background Art

[0002] With the rapid construction and development of smart grids, the power industry has entered the era of big data. In the context of smart grid construction, the control center has put forward higher requirements for the intelligence of power grid monitoring. Objectively, it is necessary to further improve the underlying data model of dispatching data, establish a power grid operation big data model suitable for big data analysis, support power grid operation big data analysis based on monitoring data, and thus improve the ability to analyze and make decisions on power grid control operations.

[0003] The operation status of complex AC and DC power grids is in a rapid and dynamic change process, which objectively puts forward higher requirements for online analysis and urgently needs to improve the quality of power grid data. Power grid data has the characteristics of large scale, complex types, delay differences, and cross-business platforms. The multi-source measurement data of the dispatching system includes power grid operation data based on the SCADA system, power grid fault signals and equipment monitoring signals, PMU data based on the WAMS system, fault recording data based on the fault recording management system, and electric energy data based on the electric energy management system, which makes the power grid measurement data required for various applications of the dispatching system contain a large amount of redundant and error information. Due to the problems of low quality and poor synchronization of power grid measurement data, it is impossible to accurately map the actual operation status of the power grid. At the same time, there are many types of power grid measurement data and the heterogeneity of the acquisition system is large, which makes the cross-system data matching low and the correlation poor, and cannot support the multi-scale information fusion analysis and online application of various applications.

[0004] Therefore, it is necessary to provide a technical solution to overcome the shortcomings of the prior art. Summary of the invention

[0005] In order to overcome the above-mentioned deficiencies of the prior art, the present invention provides a method and system for establishing a power grid measurement database. The technical solution of the present invention is as follows.

[0006] A method for establishing a power grid measurement database, comprising: determining a multi-source measurement data index based on at least one power grid measurement data dimension; wherein the at least one power grid measurement data dimension comprises: a time dimension, a space dimension, an application dimension, an attribute dimension, and a physical dimension;

[0007] Reorganizing the power grid measurement data in the power grid measurement database based on the multi-source measurement data index;

[0008] Retrieving the inputted business demand in the power grid measurement database to obtain corresponding business demand data;

[0009] The business requirement includes: a field value or a field range corresponding to a specified dimension field in the multi-source measurement data index.

[0010] Based on the power grid measurement data dimensions, determine the multi-source measurement data index, including:

[0011] Based on the time dimension and space dimension, the grid measurement data of the same grid equipment in different grid systems are temporally correlated and spatially mapped;

[0012] Using globally unique identifiers to identify power grid measurement data after time association and spatial mapping;

[0013] The multi-source measurement data index is determined based on the time characteristics, spatial characteristics, application characteristics, attribute characteristics and physical characteristics of the power grid measurement data corresponding to the globally unique identifier.

[0014] The physical dimension index includes: busbars, AC line terminals, generators, transformers, capacitors, reactors, converters, DC lines, switches, and knife switches of power grid equipment;

[0015] The attribute dimension index includes: active power of power grid equipment,

[0016] Reactive power, three-phase voltage amplitude, three-phase voltage phase angle, three-phase current amplitude, three-phase current phase angle, remote signal status, quality code;

[0017] The spatial dimension index includes: the area where the power grid equipment is located;

[0018] The application dimension index includes: determining the supervisory control and data acquisition system (SCADA), wide area phasor measurement system (WAMS), and fault recording system (FRS) of the power grid measurement data;

[0019] The time dimension index includes: different time scales of power grid equipment.

[0020] The method further includes: retrieving and accessing required data from the power grid measurement database based on a preset strategy-driven manner.

[0021] The preset strategy-driven method includes: measurement point query: obtaining the measurement data of the power grid equipment within a preset time, determining the time characteristics and attribute characteristics of the multi-source measurement data index, and obtaining the corresponding business demand data according to the measurement data association relationship;

[0022] Section query: obtain the measurement data of all power grid equipment in a specific area at a specified time point, determine the time characteristics and spatial characteristics of the multi-source measurement data index, and merge and output the corresponding business demand data according to the correlation of the measurement data.

[0023] A system for establishing a power grid measurement database comprises: a determination module, configured to determine a multi-source measurement data index based on at least one power grid measurement data dimension; wherein the at least one power grid measurement data dimension comprises: a time dimension, a space dimension, an application dimension, an attribute dimension, and a physical dimension;

[0024] A reorganization module, used for reorganizing the power grid measurement data in the power grid measurement database based on the multi-source measurement data index;

[0025] An acquisition module, used for retrieving the inputted business demand in the power grid measurement database to obtain corresponding business demand data;

[0026] The business requirement includes: a field value or a field range corresponding to a specified dimension field in the multi-source measurement data index.

[0027] The determining module comprises:

[0028] An association mapping unit, used for performing time association and space mapping on the power grid measurement data of the same power grid equipment in different power grid systems based on the time dimension and the space dimension;

[0029] An identification unit, used for identifying the power grid measurement data after time association and space mapping by using a globally unique identifier;

[0030] The determination unit is used to determine the multi-source measurement data index based on the time characteristics, spatial characteristics, application characteristics, attribute characteristics and physical characteristics of the power grid measurement data corresponding to the global unique identifier.

[0031] The physical dimension index includes: busbars, AC line terminals, generators, transformers, capacitors, reactors, converters, DC lines, switches, and knife switches of power grid equipment;

[0032] The attribute dimension index includes: active power, reactive power, three-phase voltage amplitude, three-phase voltage phase angle, three-phase current amplitude, three-phase current phase angle, remote signaling status, and quality code of power grid equipment;

[0033] The spatial dimension index includes: the area where the power grid equipment is located;

[0034] The application dimension index includes: determining the supervisory control and data acquisition system (SCADA), wide area phasor measurement system (WAMS), and fault recording system (FRS) of the power grid measurement data;

[0035] The time dimension index includes: different time scales of power grid equipment.

[0036] The system also includes: a retrieval module, which is used to retrieve and access the corresponding business demand data from the power grid measurement database based on a preset policy-driven manner.

[0037] Preset policy-driven methods include:

[0038] Measurement point query: obtain the measurement data of the specified power grid equipment within the preset time, determine the time characteristics and attribute characteristics of the multi-source measurement data index, and obtain the corresponding business demand data according to the measurement data association relationship;

[0039] Section query: obtain the measurement data of all power grid equipment in a specific area at a specified time point, determine the time characteristics and spatial characteristics of the multi-source measurement data index, and merge and output the corresponding business demand data according to the correlation of the measurement data.

[0040] Compared with the closest prior art, the technical solution provided by the present invention has the following beneficial effects:

[0041] The method for constructing a multidimensional index of the present invention realizes high-speed data retrieval from different dimensions of time, space, application, and equipment by establishing a power grid measurement database, meets the differentiated data requirements of different application scenarios, can accurately and quickly store and access multi-source heterogeneous data, improves the utilization rate of power grid measurement data, thereby improving the quality of basic power grid measurement data, and provides effective support for accurate data analysis and evaluation of the power grid. Through the multidimensional index, multi-source heterogeneous data can be quickly stored and accessed, and each application of the dispatching system can use the multidimensional index to call all measurement data of the same section or multiple section data of a measurement point, thereby improving the utilization rate of data. In addition, the multidimensional index constructed by the present invention has adaptability, and a secondary index can be defined according to business needs, further accelerating the storage and access speed of multi-source heterogeneous data, and improving data retrieval efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic diagram of the dimension structure of power grid measurement data of the present invention;

[0043] Figure 2 It is a schematic diagram of the multi-dimensional index structure of multi-source measurement data of the present invention. DETAILED DESCRIPTION

[0044] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0045] like Figure 1 As shown, the dimensions of the power grid measurement data of the present invention include:

[0046] 1) Physical dimension: corresponds to a specific device, including: busbar, AC line terminal, generator, transformer, capacitor, reactor, converter, DC line, switch, and knife switch.

[0047] 2) Attribute dimension: used to distinguish the measurement data type, including: active power, reactive power, three-phase voltage amplitude, three-phase voltage phase angle, three-phase current amplitude, three-phase current phase angle, telesignaling status, and quality code.

[0048] 3) Spatial dimension: corresponds to the area where the device is located.

[0049] 4) Application dimension: used to clarify data sources, including: Supervisory Control and Data Acquisition (SCADA), Wide Area Phase Measurement System (WAMS), and Fault Recording System (FRS).

[0050] 5) Time dimension: corresponds to different time scales of measurement.

[0051] 6) Provide consistent description of multi-dimensional power grid measurement data by associating data sets of the same data object with a data object ID that has a globally unique identifier. The data object is the power grid equipment, and the power grid equipment is identified by the same ID in different systems. In this way, all data of a data object are associated in time and space.

[0052] 7) Establish a multi-dimensional index of multi-source data of the power grid, which mainly consists of the following five parts:

[0053] ① Physical characteristics represent data objects, which are represented by the English name of the measurement object, and are recorded as Type = {T m / m=1,2,…,M}, where T m Represents the mth physical feature, with a total of M physical features.

[0054] ② Attribute characteristics are mainly about the description of the data object itself, recorded as Field = {F n / n=1,2,…,N}, where F n Indicates the nth attribute feature, with a total of N attribute features. The attribute feature values ​​are separated by padding bits and then concatenated into a string as the attribute feature part of the index.

[0055] ③ The spatial feature represents the location of the multi-source measurement data object, recorded as KeyID = {K l / l=1,2,…,L}, where K l Indicates the lth spatial feature, with a total of L spatial features. Contains the region and device serial number;

[0056] ④ Application characteristics represent the source of multi-source measurement data, denoted as App = {A j |j=1,2,…,J},where A jIndicates the jth application feature, with a total of J application features. The application feature value App is the application feature part of the multi-dimensional index, including: SCADA, PMU, FRS;

[0057] ⑤The time feature represents the generation time of multi-source measurement data, recorded as Time = {T k / k=1,2,…,K}, where T k Indicates the kth time feature, with a total of K time features. The time feature value describes the Greenwich time in the form of a String, which can effectively shorten the retrieval time;

[0058] The final generated multidimensional index is: App:Time:KeyID:Type:Field.

[0059] Figure 2 This is a schematic diagram of the multidimensional index architecture of the present invention. The power grid measurement data in each heterogeneous system is reorganized and stored in a multidimensional index format. According to the data utilization scenario, the required data can be quickly retrieved and accessed from the database in a policy-driven manner. The reorganization and storage is because the data format of each measurement is different, including CIME format and CSV format. However, the present invention reorganizes and stores the data according to the multidimensional index to facilitate data retrieval, which is an application of multidimensional index.

[0060] The strategy driving methods of the present invention mainly include the following two types:

[0061] 1) Measurement point query: Get the relevant measurement data of the specified device within a period of time. Determine the time characteristic value and attribute characteristic value of the multi-dimensional index, and obtain the target data based on the correlation relationship of the measurement data.

[0062] 2) Section query: Obtain relevant measurement data of all equipment in a specific area at a specified time point. Determine the time feature value and spatial feature value of the multi-dimensional index, and merge and output the target data according to the correlation of the measurement data.

[0063] Furthermore, when retrieving the measurement data of all loads at 16:32:56:020 under the SCADA application, the multidimensional index feature value App=SCADA, Properties={LOAD, P_Q} is determined according to the measurement point query strategy drive, that is, the multidimensional index and the corresponding target data are quickly output, meeting the differentiated data requirements of different application scenarios.

[0064] Based on the method of the present invention, the present invention also includes a system for establishing a power grid measurement database, including: a determination module, used to determine a multi-source measurement data index based on at least one power grid measurement data dimension; wherein the at least one power grid measurement data dimension includes: a time dimension, a space dimension, an application dimension, an attribute dimension, and a physical dimension;

[0065] A reorganization module, used for reorganizing the power grid measurement data in the power grid measurement database based on the multi-source measurement data index;

[0066] An acquisition module, used for retrieving the inputted business demand in the power grid measurement database to obtain corresponding business demand data;

[0067] The business requirement includes: a field value or a field range corresponding to a specified dimension field in the multi-source measurement data index.

[0068] The determining module comprises:

[0069] An association mapping unit, used for performing time association and space mapping on the power grid measurement data of the same power grid equipment in different power grid systems based on the time dimension and the space dimension;

[0070] An identification unit, used for identifying the power grid measurement data after time association and space mapping by using a globally unique identifier;

[0071] The determination unit is used to determine the multi-source measurement data index based on the time characteristics, spatial characteristics, application characteristics, attribute characteristics and physical characteristics of the power grid measurement data corresponding to the global unique identifier.

[0072] The physical dimension index includes: busbars, AC line terminals, generators, transformers, capacitors, reactors, converters, DC lines, switches, and knife switches of power grid equipment;

[0073] The attribute dimension index includes: active power, reactive power, three-phase voltage amplitude, three-phase voltage phase angle, three-phase current amplitude, three-phase current phase angle, remote signaling status, and quality code of power grid equipment;

[0074] The spatial dimension index includes: the area where the power grid equipment is located;

[0075] The application dimension index includes: determining the supervisory control and data acquisition system (SCADA), wide area phasor measurement system (WAMS), and fault recording system (FRS) of the power grid measurement data;

[0076] The time dimension index includes: different time scales of power grid equipment.

[0077] The system also includes: a retrieval module, which is used to retrieve and access the corresponding business demand data from the power grid measurement database based on a preset policy-driven manner.

[0078] Preset policy-driven methods include:

[0079] Measurement point query: obtain the measurement data of the specified power grid equipment within the preset time, determine the time characteristics and attribute characteristics of the multi-source measurement data index, and obtain the corresponding business demand data according to the measurement data association relationship;

[0080] Section query: obtain the measurement data of all power grid equipment in a specific area at a specified time point, determine the time characteristics and spatial characteristics of the multi-source measurement data index, and merge and output the corresponding business demand data according to the correlation of the measurement data.

[0081] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0082] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes 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 generate 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.

[0083] These computer program instructions may also be stored in a computer or other programmable data processing device that can direct the computer.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Ordinary technicians in the relevant field can still modify or make equivalent substitutions to the specific implementation methods of the present invention with reference to the above embodiments. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention are within the scope of protection of the claims of the present invention to be approved.

Claims

1. A method for establishing a power grid measurement database, characterized in that: include: Determine a multi-source measurement data index based on at least one power grid measurement data dimension; wherein the at least one power grid measurement data dimension includes: a time dimension, a space dimension, an application dimension, an attribute dimension, and a physical dimension; Reorganizing the power grid measurement data in the power grid measurement database based on the multi-source measurement data index; Retrieving the inputted business demand in the power grid measurement database to obtain corresponding business demand data; Wherein, the business requirements include: field values ​​or field ranges corresponding to the specified dimension fields in the multi-source measurement data index; The step of determining the multi-source measurement data index based on the power grid measurement data dimension includes: Based on the time dimension and space dimension, the grid measurement data of the same grid equipment in different grid systems are temporally correlated and spatially mapped; Using globally unique identifiers to identify power grid measurement data after time association and spatial mapping; The multi-source measurement data index is determined based on the time characteristics, spatial characteristics, application characteristics, attribute characteristics and physical characteristics of the power grid measurement data corresponding to the globally unique identifier.

2. The method according to claim 1, characterized in that The physical dimension index includes: busbar, AC line terminal, generator, transformer, capacitor, reactor, converter, DC line, switch, and knife switch of power grid equipment; The attribute dimension index includes: active power, reactive power, three-phase voltage amplitude, three-phase voltage phase angle, three-phase current amplitude, three-phase current phase angle, remote signaling status, and quality code of power grid equipment; The spatial dimension index includes: the area where the power grid equipment is located; The application dimension index includes: determining the data acquisition and monitoring control system, wide area phasor measurement system, and fault recording system of the power grid measurement data; The time dimension index includes: different time scales of power grid equipment.

3. The method according to claim 2, characterized in that Also includes: Based on a preset policy-driven approach, required data is retrieved and accessed from the power grid measurement database.

4. The method according to claim 3, characterized in that The preset strategy driving method includes: Measurement point query: obtain the measurement data of the power grid equipment within the preset time, determine the time characteristics and attribute characteristics of the multi-source measurement data index, and obtain the corresponding business demand data according to the measurement data association relationship; Section query: obtain the measurement data of all power grid equipment in a specific area at a specified time point, determine the time characteristics and spatial characteristics of the multi-source measurement data index, and merge and output the corresponding business demand data according to the correlation of the measurement data.

5. A system for establishing a power grid measurement database, characterized in that: include: A determination module, configured to determine a multi-source measurement data index based on at least one power grid measurement data dimension; wherein the at least one power grid measurement data dimension comprises: a time dimension, a space dimension, an application dimension, an attribute dimension, and a physical dimension; A reorganization module, used for reorganizing the power grid measurement data in the power grid measurement database based on the multi-source measurement data index; An acquisition module, used for retrieving the inputted business demand in the power grid measurement database to obtain corresponding business demand data; Wherein, the business requirements include: field values ​​or field ranges corresponding to the specified dimension fields in the multi-source measurement data index; The determining module comprises: An association mapping unit, used for performing time association and space mapping on the power grid measurement data of the same power grid equipment in different power grid systems based on the time dimension and the space dimension; An identification unit, used for identifying the power grid measurement data after time association and space mapping by using a globally unique identifier; The determination unit is used to determine the multi-source measurement data index based on the time characteristics, spatial characteristics, application characteristics, attribute characteristics and physical characteristics of the power grid measurement data corresponding to the global unique identifier.

6. The system according to claim 5, characterized in that The physical dimension index includes: busbar, AC line terminal, generator, transformer, capacitor, reactor, converter, DC line, switch, and knife switch of power grid equipment; The attribute dimension index includes: active power, reactive power, three-phase voltage amplitude, three-phase voltage phase angle, three-phase current amplitude, three-phase current phase angle, remote signaling status, and quality code of power grid equipment; The spatial dimension index includes: the area where the power grid equipment is located; The application dimension index includes: determining the data acquisition and monitoring control system, wide area phasor measurement system, and fault recording system of the power grid measurement data; The time dimension index includes: different time scales of power grid equipment.

7. The system according to claim 6, characterized in that Also includes: The retrieval module is used to retrieve and access the corresponding business demand data from the power grid measurement database based on a preset policy-driven manner.

8. The system according to claim 7, characterized in that The preset strategy driving method includes: Measurement point query: obtain the measurement data of the specified power grid equipment within the preset time, determine the time characteristics and attribute characteristics of the multi-source measurement data index, and obtain the corresponding business demand data according to the measurement data association relationship; Section query: obtain the measurement data of all power grid equipment in a specific area at a specified time point, determine the time characteristics and spatial characteristics of the multi-source measurement data index, and merge and output the corresponding business demand data according to the correlation of the measurement data.

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