CN115390827A - Power grid digital twin body construction method and platform for supporting debugging operation - Google Patents
Power grid digital twin body construction method and platform for supporting debugging operation Download PDFInfo
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Abstract
The invention discloses a power grid digital twin body construction method and a platform for supporting debugging operation, which comprise the following steps: acquiring power grid online data and offline data for constructing a power grid digital twin; according to the characteristics of the online data and the offline data of the power grid, different file adapters are constructed, and the file adapters are adapted to the online data and the offline data of the power grid; and analyzing the power grid online data and the power grid offline data through the file adapter, adapting the power grid online data and the power grid offline data into corresponding power grid models through the file adapter, mapping data to a power grid digital twin body, and constructing the power grid digital twin body. The problem that the scheduling service lacks real-time flexible and agile decision support is solved.
Description
Technical Field
The invention relates to the field of power grid operation scheduling control, in particular to a power grid digital twin body construction method and a power grid digital twin body platform for supporting debugging operation.
Background
With the advance of extra-high voltage construction work, the scale of interconnected large power grids in China is continuously enlarged, alternating current and direct current are mutually influenced, and large-area power grids are mutually influenced, so that extra-high voltage lines, new energy plants and large-capacity variable loads are rapidly increased; meanwhile, due to the gradual increase of the proportion of renewable energy sources, the gradual enhancement of the trend of power electronic and information acquisition diversification of the power grid, the large power grid can present more complex nonlinear random characteristics, multi-source large data characteristics and multi-time scale dynamic characteristics. The developments provide serious challenges for the safe and stable operation of the power grid, provide more detailed requirements for power dispatching, and objectively require that the power grid analysis has more accurate state perception, more efficient simulation means and more intelligent analysis and evaluation.
At present, the power grid dispatching has the problems that:
(1) The dispatching service needs to improve the automation and intelligence level
In the process of developing scheduling daily business, a scheduler still needs to make a manual decision according to past experiences when monitoring the operation of a power grid in the face of multi-source complicated data viewing and analyzing time-consuming and time-consuming processes, the judgment and decision often cannot be made systematically, accurately, timely and scientifically, and some automatic and intelligent technical means and application tools are lacked, for example, at present, a regulation and control person needs to frequently look over the stable regulations of various text forms to guide the operation of the power grid, so that the omission is easy and the efficiency is low.
(2) Lack of real-time performance for scheduling traffic
D5000 and a new generation platform are built according to function modularization, excessively subdivided module division often causes multiple links of data acquisition links of application, and is limited by the performance of database and file I/O access, service application cannot achieve real-time performance, a simulation calculation mode of periodic scanning and event triggering is adopted in current online analysis, time is consumed for 5-15 minutes, and when potential safety hazards exist, a system or a dispatcher cannot take measures in time to prevent the problems in the bud.
(3) Lack of agility in scheduling services
The D5000 and a new generation platform have strong and complex functions, and when supporting the development of a new scheduling service, the problems of different interfaces, complex integration, difficult coordination and the like are often faced, so that the method cannot adapt to agile development requirements of small-step fast running, fast iteration and fast response scheduling service in product research and development.
Disclosure of Invention
In order to solve the problems, the invention provides a power grid digital twin body construction method for supporting debugging operation, which comprises the following steps:
the method comprises the following steps:
acquiring power grid online data and offline data for constructing a power grid digital twin;
according to the characteristics of the online data and the offline data of the power grid, different file adapters are constructed, and the file adapters are adapted to the online data and the offline data of the power grid;
and analyzing the power grid online data and the power grid offline data through the file adapter, adapting the power grid online data and the power grid offline data into corresponding power grid models through the file adapter, realizing the mapping of the data to the power grid digital twin, and constructing the power grid digital twin.
Further, the grid online data includes: QS files for power grid state estimation and power grid operation real-time data; the power grid offline data comprises: and future state data and power flow files of the power grid.
Further, the different file adapters include:
the system comprises a QS file adapter for power grid state estimation, a real-time library adapter for power grid operation real-time data, a power grid future state data and power flow file PSASP/BPA file adapter.
Further, the method for mapping the power grid digital twin body to the power grid digital twin body is realized by adapting the online data and the offline data of the power grid to corresponding power grid models through the file adapter, and comprises the following steps:
importing topological correlation and simulation parameter data in a power grid model into a power grid calculation model and importing physical equipment data into a full-grid model of a power grid digital twin through a QS file adapter for power grid state estimation;
the real-time database adapter of the power grid operation real-time data is used for adapting the power grid operation real-time data to a physical equipment model object of a power grid digital twin;
the method comprises the steps of performing enumeration modeling on a power grid calculation model in a power grid digital twin and corresponding equipment types in a power grid future state data and power flow file equipment model through model information enumeration contained in a defined equipment model through a power grid future state data and power flow file PSASP/BPA file adapter, and establishing an association relation with a digital twin enumeration model in an enumeration definition of the power grid future state data and power flow file model in a mode of adding labels.
Further, the QS file adapter for grid state estimation includes: the file analysis, data caching and model mapping three-layer structure;
the file analysis layer carries out data analysis on the whole network model to generate entity equipment corresponding to the data table;
converting the entity class into a data structure readable by a computer to generate data analysis;
the data caching layer caches the data in the data table;
and the model mapping layer establishes corresponding types of objects in the power grid calculation model of the digital twin according to the logical relation of QS files estimated by the power grid state of the entity equipment corresponding to the data table based on the data analysis, so as to realize model mapping.
Further, the method for adapting the real-time data of the power grid operation to the physical equipment model object of the digital twin body of the power grid through the real-time library adapter of the real-time data of the power grid operation comprises the following steps:
acquiring data of an alternating current line segment, an alternating current line terminal, a transformer winding, a circuit breaker, a bus section and a transformer substation from a power grid real-time library through a data interface;
for each type of acquired data, establishing a key-value pair object, specifically comprising: for an alternating current line section, a transformer, a breaker, a bus section and a transformer substation, a key is a specific equipment name, and a value is actual measurement data corresponding to the equipment; for the alternating current line, the key is a specific alternating current line name, and measurement values corresponding to the station on the I side and the station on the J side of the line are respectively stored; for the transformer winding, the key is a specific transformer winding name, and the values respectively store actual measurement data corresponding to the high voltage side, the medium voltage side and the low voltage side of the transformer.
Further, the power grid future state data and power flow file PSASP/BPA file adapter comprises a three-layer structure of file analysis, data caching and model mapping, and the incidence relation among all layers is realized through enumeration and marking;
the file analysis layer is used for respectively establishing key value pair objects of the single equipment aiming at different equipment; aiming at the equipment of the same type, forming an entity class of a single type model by using the established key value pair objects of all the single equipment; combining entity classes of a plurality of single type models together to form a set as an information class of the single type model; forming a key-value pair set by the information classes of different types of model information;
the data cache layer is used for caching the data of the file analysis layer;
the model mapping layer obtains digital twin model enumeration information by analyzing model information enumeration of the future state data and the power flow file of the power grid, different devices are taken out from the data cache layer according to the digital twin model enumeration information, and corresponding objects are established in the digital twin model according to the logical relationship.
Further, the method also comprises the following steps:
and updating the constructed power grid digital twin body by adopting a complex event processing engine.
The invention also provides a power grid digital twin platform for supporting dispatching operation, which comprises:
the data module is used for acquiring online data and offline data of a power grid;
the modeling calculation core module is used for reading online data and offline data of the power grid from the data module; analyzing the power grid online data and the power grid offline data through the file adapter, adapting the power grid online data and the power grid offline data to corresponding power grid models through the file adapter, realizing mapping of data to power grid digital twins, and constructing power grid digital twins;
the advanced application module provides power grid load flow information through the power grid digital twin body constructed by the modeling calculation core module; and after the digital twin of the power grid is updated, providing simulation analysis for the support scheduling of the power grid based on artificial intelligence application, power grid short-circuit current calculation and static safety analysis.
Further, the method also comprises the following steps:
and updating the constructed power grid digital twin body by adopting a complex event processing engine.
The invention provides a power grid digital twin body construction method and a platform for supporting debugging operation, which are suitable for a large power grid dispatching operation application scene, and the digital twin body mirrors the real-time operation state of a physical power grid in a high-fidelity manner, and supports real-time analysis and rolling deduction. Aiming at the characteristics of complex stability rules, multiple control dimensions, hidden monitoring blind areas and the like of an extra-high voltage power grid, the platform can be used for assisting the day-ahead, day-in and real-time operation safety monitoring and checking of the power grid, assisting in achieving power grid dispatching stable and specified full life cycle management, operation risk dead-angle-free rolling monitoring, marketized multi-scene safety checking and assistant decision making, providing a brand-new application platform-level solution for real-time support of dispatching operation monitoring, analysis and decision making, improving the real-time performance of power grid dispatching decision making, improving the intelligent rapid assistant decision making capability in the field of large power grid safety operation, and solving the problem that dispatching services lack real-time flexible and quick decision making support.
Drawings
FIG. 1 is a schematic flow chart of a method for constructing a digital twin of a power grid for supporting debugging operation, provided by the invention;
fig. 2 is a structural diagram of a grid digital twin according to the present invention;
FIG. 3 is a device connection relationship in a SCADA real-time library model according to the present invention;
FIG. 4 is a diagram of device connections in a state estimation model according to the present invention;
FIG. 5 is a mapping of a state estimation file model to a computational model to which the present invention relates;
FIG. 6 is a diagram of the construction of a digital twin based on PSASP/BPA data in accordance with the present invention;
FIG. 7 is a real-time updating sequence diagram of a grid digital twin according to the present invention;
FIG. 8 is a flow chart of a real-time grid digital twin update stored on a memory data grid according to the present invention;
fig. 9 is a structural diagram of a power grid digital twin platform supporting commissioning according to the present invention.
Detailed Description
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather construed as limited to the embodiments set forth herein.
Example 1
The invention provides a power grid digital twin body construction method for supporting debugging operation, which can be used for realizing integrated mapping of offline data and online data involved in scheduling and realizing high-fidelity and sub-second level mirroring of a power grid, and the flow of the method is shown in figure 1, and comprises the following steps:
and step S101, acquiring power grid online data and offline data for constructing the power grid digital twin body.
The off-line data and the on-line data can be selectively utilized according to requirements, wherein the off-line data of the power grid comprises the following steps: a power flow file in a power system analysis integrated program (PSASP) format and future state data of a power grid (comprising system load prediction, bus load prediction, a tie line plan, a power generation plan and an overhaul plan); the power grid online data comprises: QS files in CIM/E format for power grid state estimation and power grid operation real-time data (including real-time data information during power grid operation, including line state, breaker state, generator active power and reactive power, load active power and reactive power, stability control device state, line power, node voltage and the like).
And S102, constructing different file adapters according to the characteristics of the online data and the offline data of the power grid, and adapting the file adapters with the online data and the offline data of the power grid.
The file adapter specifically comprises: the system comprises a QS file adapter for power grid state estimation, a real-time library adapter for power grid operation real-time data, a power grid future state data and power flow file PSASP/BPA file adapter.
And step S103, analyzing the power grid online data and the power grid offline data through the file adapter, adapting the power grid online data and the power grid offline data to corresponding power grid models through the file adapter, realizing mapping of data to power grid digital twins, and constructing the power grid digital twins.
Importing topological correlation and simulation parameter data in a power grid model into a power grid calculation model and importing physical equipment data into a full-grid model of a power grid digital twin through a QS file adapter for power grid state estimation;
the QS file adapter for grid state estimation comprises: the file analysis, data caching and model mapping three-layer structure;
the file analysis layer carries out data analysis on the whole network model to generate entity equipment corresponding to the data table;
converting the entity class into a data structure readable by a computer to generate data analysis;
the data caching layer caches the data in the data table;
and the model mapping layer establishes corresponding types of objects in the power grid calculation model of the digital twin according to the logical relation of QS files estimated by the power grid state of the entity equipment corresponding to the data table based on the data analysis, so as to realize model mapping.
The real-time database adapter of the power grid operation real-time data is used for adapting the power grid operation real-time data to a physical equipment model object of a power grid digital twin; specifically, data of an alternating current line segment, an alternating current line endpoint, a transformer winding, a circuit breaker, a bus segment and a transformer substation are obtained from a power grid real-time library through a data interface;
for each type of acquired data, establishing a key-value pair object, specifically comprising: for an alternating current line section, a transformer, a breaker, a bus section and a transformer substation, a key is a specific equipment name, and a value is actual measurement data corresponding to the equipment; for the alternating current line, the key is a specific alternating current line name, and measurement values corresponding to the station on the I side and the station on the J side of the line are respectively stored; for the transformer winding, the key is a specific transformer winding name, and the values respectively store actual measurement data corresponding to the high voltage side, the medium voltage side and the low voltage side of the transformer.
The method comprises the steps of performing enumeration modeling on a power grid computing model in a power grid digital twin and corresponding equipment types in the power grid future state data and power flow file equipment model through model information enumeration contained in a defined equipment model through a power grid future state data and power flow file PSASP/BPA file adapter, and establishing an association relation with a digital twin enumeration model in an adding and labeling mode in the enumeration definition of the power grid future state data and power flow file model.
The PSASP/BPA file adapter comprises a three-layer structure of file analysis, data caching and model mapping, and the association relationship among all layers is realized by enumeration and marking;
the file analysis layer is used for respectively establishing key value pair objects of the single equipment aiming at different equipment; aiming at the equipment of the same type, forming an entity class of a single type model by using the established key value pair objects of all the single equipment; combining entity classes of a plurality of single type models together to form a set which is used as an information class of the single type model; forming a key-value pair set by the information classes of different types of model information;
the data cache layer is used for caching the data of the file analysis layer;
the model mapping layer obtains digital twin model enumeration information by analyzing model information enumeration of the future state data and the power flow file of the power grid, different devices are taken out from the data cache layer according to the digital twin model enumeration information, and corresponding objects are established in the digital twin model according to the logical relationship.
The structure of the established grid digital twin is shown in fig. 2:
the key point of the power grid digital twin is that the power grid digital twin is compatible with multiple data sources, and effective integration and integration of offline data (including PSASP and BPA flow files) and online data (including power grid real-time operation data SCADA and state estimation QS files) can be realized. In the digital twin body shown in the figure, a full-grid model and a physical equipment model relate to a conventional element model of a power system, and a power grid calculation model is mainly used for establishing a general power grid calculation model object by importing power grid information into an algorithm program by utilizing an InterPSS. The invention mainly provides a constructed power grid digital twin body, and how to uniformly be compatible with different offline and online data sources.
Example 2
The process of establishing the corresponding grid digital twin based on the corresponding file adapter includes:
1. the specific process of constructing different file adapters is as follows:
1) QS file adapter for power grid state estimation
The QS file adapter has the functions of importing data such as topological relation and simulation parameters of a power grid model in the QS file into a power grid calculation model of a power grid digital twin body, and importing specific physical equipment data into a full-network model (CIM/E). The QS file adapter comprises a file analysis layer, a data cache and a model mapping three-layer structure, firstly, data analysis is carried out through CIM/E table definition of the CIM/E file, and entity classes corresponding to the CIM/E tables are generated and comprise a reference value, a transformer substation, a bus, an alternating current circuit, a generator, a transformer, a load, series compensation, parallel compensation, a current converter, a direct current circuit, a topological node, a breaker and a disconnecting link; secondly, the entity classes are changed into a data structure which can be read by a computer, a data analysis Parser is generated, and a single device in a certain CIM/E table is cached; and finally, based on the data analysis, establishing objects of corresponding types in the power grid calculation model of the digital twin according to the logical relation of QS files for the entity type equipment corresponding to the CIM/E table, and realizing model mapping.
2) Real-time library adapter for power grid operation real-time data
And (4) adapting the real-time operation new information SCADA data to a physical equipment model object of the power grid digital twin. Firstly, calling a data reading interface provided by a D5000 platform, and acquiring data of an alternating current line segment, an alternating current line terminal, a transformer winding, a circuit breaker, a bus segment and a transformer substation from a real-time library. Secondly, for each type of acquired data, a key-value pair object is established. For an alternating current line section, a transformer, a breaker, a bus section and a transformer substation, a key is a specific equipment name, and a value is actual measurement data corresponding to the equipment; for the alternating current line, the key is a specific alternating current line name, and measurement values corresponding to the station on the I side and the station on the J side of the line are respectively stored; for the transformer winding, the key is a specific transformer winding name, and the values respectively store actual measurement data corresponding to the high voltage side, the medium voltage side and the low voltage side of the transformer.
3) Power grid future state data and power flow file PSASP/BPA file adapter
The power grid future state data PSASP and the power flow file BPA file PSASP/BPA file adapter area comprise three layers of structures including file analysis, data cache and model mapping. Taking an equipment model as an example, firstly defining model information enumeration contained in the equipment model, and adopting a mode that certain information of one model corresponds to one enumeration, wherein the model information enumeration runs through the modeling process of the whole digital twin body; then, performing enumeration modeling on a power grid calculation model in the power grid digital twin and a corresponding device type in a PSASP/BPA device model; and finally, establishing an association relation with the digital twin enumeration model by adopting a mode of increasing labels in the enumeration definition of the PSASP/BPA file model.
(1) A file analysis layer: after the file of the PSASP/BPA is obtained, a key value pair object of a single device is established aiming at different devices, such as a generator, a bus, a transformer, a load, an alternating current line, a direct current line, parallel compensation, series compensation and the like, wherein a specific device is taken as an example, the key of the object is model information, and the value is a model information value; secondly, aiming at the equipment of the same type, forming a single type model entity class by using all the established single equipment key value pair objects; then, continuously combining the entity classes of the plurality of single type models together to form a List set as all information classes of the single type models; and finally, storing all information classes of a single type model of all different types of model information in the MAP, wherein the model type of the PSASP/BPA file model is used as a MAP key value.
(2) Data caching: the data caching layer is used as a data source of the model mapping layer, and the file analyzing layer is used as a data source of the data caching layer.
(3) Model mapping: the model mapping layer obtains digital twin model enumeration information by analyzing model information enumeration of the PSASP/BPA, different devices are taken out from the data cache according to the digital twin model enumeration information, and corresponding objects are established in the digital twin model according to the logical relationship.
2. According to different data sources, establishing a corresponding power grid digital twin body based on a corresponding file adapter:
1) Reading real-time operation data of a power grid, and constructing a digital twin body of the power grid:
and (2) analyzing the SCADA real-time library structure file by utilizing the SCADA real-time library adapter established in the step (1) according to the SCADA real-time library structure file (. H file comprising the real-time library table name, the field data type and the field name), acquiring the table name, the field name and the field data type of each real-time library table, and forming a power grid digital twin body according to the equipment connection relation shown in the figure 3. The fast index relationship of fig. 3 mainly includes: 1) A plant contains a number of devices including ac line terminals, transformers, transformer windings (of a particular transformer), series/parallel capacitors/reactors, generators, switches, etc.; 2) Each device belongs to a reference voltage; 3) The line comprises 2 alternating current line terminals, and the terminals belong to a specific line; 4) The equipment comprises two types, wherein one type has two end point numbers belonging to the 'side' type and comprises a switch and a disconnecting link, and only one end point belongs to the 'point' type and comprises a transformer winding, a parallel capacitor/reactor, a generator and the like.
2) Reading a state estimation QS file, and constructing a power grid digital twin body:
reading a QS file of online state estimation, analyzing fields contained in a CIM/E table according to the CIM/E table structure of the state estimation file by utilizing an established QS file adapter, and generating an entity class, a data analysis tool and a data mapping tool corresponding to the CIM/E table by virtue of an automatic code generation technology. The entity class is used for attribute definition of a CIM/E table; the data analysis tool is used for analyzing the file records; the data mapping tool is used to map the parsed data to file records. According to the device connection relationship in the state estimation model and the object-oriented modeling method shown in fig. 4, modeling is performed in a model-driven manner to form a physical object model of the power grid. The established fast index relationship mainly comprises: 1) A plant contains a number of devices including ac line terminals, transformers, transformer windings (of a particular transformer), series/parallel capacitors/reactors, generators, switches, etc.; 2) Each device belongs to a reference voltage; 3) The line comprises 2 alternating current line terminals, and the terminals belong to a specific line; 4) The equipment comprises two types, wherein one type has two end points belonging to the side type and comprises a switch and a disconnecting link, and only one end point belongs to the point type and comprises a transformer winding, a parallel capacitor/reactor, a generator and the like.
The mapping of the state estimation file model to the grid computing model is shown in fig. 5, and comprises the following steps:
(1) the state estimation model file content is imported into a state estimation model information adapter.
(2) And establishing a bus node (AclfBus) in the InterPSS power grid calculation model by using the reference value, the station, the island information and the physical bus information in the model adapter.
(3) And establishing a generator (AclfGen) in the InterPSS power grid computing model by using the reference value, the station, the island information and the generator information in the model adapter.
(4) And establishing a load (Aclfload) in the InterPSS power grid computing model by using the reference value, the station, the island information and the load information in the model adapter.
(5) And establishing a parallel compensation alternating current branch (AclfBranch) in the InterPSS power grid calculation model by using the reference value, the station, the island information and the parallel compensation device information in the model adapter.
(6) And establishing a series compensation alternating current branch (AclfBranch) in the InterPSS power grid calculation model by using the reference value, the station, the island separation information and the series compensation device information in the model adapter.
(7) And establishing an alternating current line alternating current branch (AclfBranch) in the InterPSS power grid calculation model by using the reference value, the station, the island separation information and the alternating current line information in the model adapter.
(8) And establishing a transformer alternating current branch (AclfBranch) in the InterPSS power grid calculation model by using the reference value, the station, the island information and the transformer information in the model adapter.
(9) And establishing a direct current line branch (HvdcLine 2 LCC) in the InterPSS power grid calculation model by using the reference value, the station, the island information, the direct current line and the converter information in the model adapter.
3) Reading a PSASP/BPA data file, and establishing a power grid digital twin:
and reading the PSASP/BPA data file, and constructing a power grid digital twin body according to the relation of the figure 6 by utilizing the established corresponding file adapter.
(1) And importing the PASAP/BPA model and the parameter file content into a PASAP/BPA file adapter.
(2) And establishing a bus node (AclfBus) in the InterPSS power grid computing model by using the bus information in the model adapter.
(3) And establishing a generator (AclfGen) in the InterPSS power grid computing model by using the generator information in the model adapter.
(4) And establishing a load (Aclfload) in the InterPSS power grid computing model by using the load information in the model adapter.
(5) And establishing a parallel compensation alternating current branch (AclfBranch) in the InterPSS power grid computing model by using the parallel compensation device information in the model adapter.
(6) And establishing a series compensation alternating current branch (AclfBranch) in the InterPSS power grid computing model by using the information of the series compensation device in the model adapter.
(7) And establishing an alternating current line alternating current branch (AclfBranch) in the InterPSS power grid computing model by using the alternating current line information in the model adapter.
(8) And establishing a transformer alternating current branch (AclfBranch) in the InterPSS power grid calculation model by using the transformer information in the model adapter.
(9) And establishing a direct current line branch (HvdcLine 2 LCC) in the InterPSS power grid computing model by using a direct current line in the model adapter.
And controlling the updating of the grid digital twin by adopting a Complex Event Processing (CEP) engine.
And replacing the memory of the CEP engine by using an external memory data grid, putting the constructed power grid digital twin into the memory data grid, storing the power grid digital twin into the memory, and distributing the power grid digital twin onto a plurality of servers. In the running process of a power grid, when the system has large changes or disturbances, a CEP system subscribes changes and disturbance events from a high-speed data bus, updates a calculation model in real time (millisecond level), and informs a CEP engine of the updating changes by the model to trigger the rule evaluation of the CEP rule engine. The real-time change events (information) of the power grid come from the SCADA system. As shown in fig. 7, taking power change of a certain section of a power grid digital twin as an example, a D5000 bus receiver receives a power grid change event such as a process 1, a cep engine receives a node power change event sent by the D5000 bus receiver such as a process 2, and sends a power grid node update task such as a process 3, a node object such as a process 4 is formed by deserializing a calculation model in a data grid, then updating is performed according to the task such as a process 5, and finally, the node update is serialized and stored in a distributed container such as a process 6, so as to complete node update.
The grid digital twin stored in the memory data grid has the following functions, as shown in fig. 8:
1) The digital twin cycle synchronization of the power grid: pass [ 2 ]
]And carrying out periodic synchronization of the models by the adapters of data sources of the real-time library, the QS file and the LF file.
2) Updating the digital twin of the power grid in real time: there are two scenarios: 1) The system full model is observable in real time; 2) The system model part is observable in real time. In the interval of the cycle synchronization, by
]Processing the remote signaling telemetry information (
) And finally updated to the grid calculation model (
) Real-time updating of a considerable model of the whole model is realized; in the interval of the cycle synchronization, by
]First, local telemetry is processed (
) Update to data exchange model (A)
) Then carrying out model splicing and updating to the global power grid calculation model (
) And the model updating with locally observable data model and model splicing is realized.
3) The grid digital twins support the following 3 levels of parallel computation:
and l, multi-virtual machine level parallel computing, wherein a power grid analysis model can be distributed to a plurality of Java virtual machines, and parallel computing is realized on a plurality of JVMs. If the Java virtual machines are managed by the memory data grid, the distribution of the grid digital twin in the computer cluster is automatically completed.
And l, performing multi-case level parallel computation, wherein each simulation computation case can be represented by one power grid analysis model object, a plurality of analysis model objects can be stored in the Java virtual machine, and a plurality of analysis model objects can be processed in parallel.
And (3) algorithm level parallel computation, wherein certain specific power grid simulation algorithms can be designed to enable simulation objects to be in a read-only mode in the whole algorithm execution process, and the algorithms have the characteristics of ensuring the multithread safety of the simulation objects and being well suitable for the parallel execution of the simulation algorithms.
Example 3
The grid digital twin platform based on the support scheduling operation established above, as shown in fig. 9, includes:
the data module is used for acquiring online data and offline data of a power grid;
the modeling calculation core module is used for reading online data and offline data of the power grid from the data module; analyzing the power grid online data and the power grid offline data through the file adapter, adapting the power grid online data and the power grid offline data to corresponding power grid models through the file adapter, realizing mapping of data to power grid digital twins, and constructing power grid digital twins;
the advanced application module provides power grid load flow information through the power grid digital twin body constructed by the modeling calculation core module; and after the digital twin of the power grid is updated, providing simulation analysis for the support scheduling of the power grid based on artificial intelligence application, power grid short-circuit current calculation and static safety analysis.
The power grid digital twin body platform adopts a complex event processing engine to update the constructed power grid digital twin body.
And the data module is used for storing data required by constructing the digital twin body, including offline data and online data. The power grid online data comprises: QS files used for power grid state estimation and power grid operation real-time data; the power grid offline data comprises: future state data and tide files of the power grid.
And the modeling calculation core module consists of the constructed power grid digital twin and a complex event processing engine. The complex event processing engine monitors the power grid digital twin, and after the digital twin is updated, the complex event processing engine starts a function module in the advanced application platform to provide auxiliary decision support for the power grid, so that information interaction and cooperative control between a physical power grid and a twin system can be realized.
And the high-level application module is a modeling calculation core module and provides power grid load flow information, namely the power grid load flow information obtained by the power grid digital twin model. In the modeling calculation core module, after the digital twin body is updated, the complex event processing engine starts a function module in the advanced application module, the function module comprises various artificial intelligence-based power grid analysis applications, traditional power grid short-circuit current calculation and static safety analysis applications, and power grid digital twin body tide current information in the modeling calculation core module is transmitted to each function module of the advanced application module for further power grid analysis.
Example 4
Example 1: the model updating speed in the digital twin platform of the power grid is tested by adopting the scale data of the current provincial power grid and 1000 nodes: starting from the acquisition of the real-time operation data of the power grid, the equipment is updated in less than 0.1s, and a calculation model is formed through mapping, wherein the time consumption is less than 0.1s, and the total time consumption is less than 0.2s.
Example 2: the computing performance of the digital twin platform of the power grid is tested by adopting an online data model (about 4 ten thousand nodes directly derived from EMS) of the current state-regulated DSA dispatching automation system as a case.
1) Test data, environment
At present, online DSA analysis application in a D5000 system adopts Sanhua + northwest online data as basic data of analysis except for a northeast power grid. The test data model includes: 41219 nodes, 34028 branches and 12 direct current systems. The test computer was a laptop (Intel Core i 7-6820.70 GHz CPU/4 Core, 8 MB Cache). The test data model is stored in a PSASP format.
2) Future state power flow test
And taking the power grid digital twin body tidal current result in the internal storage data grid as an initial value, changing the output and load of generators of certain nodes in the network, simulating future state tidal current change, and performing tidal current calculation performance test. The calculation method adopts a cow pulling method, and an alternating current and direct current system adopts alternate iteration to solve.
Future state 1: the Wu Jiangsu Wuqiao transformer/220 kV. #2 main transformer-high voltage side equivalent load is increased by 50 MW, and the Huadong Yangcheng factory/21 kV. # 1 generator is used for carrying out all power regulation. The consumption was calculated to be 0.358 s.
Future state 2: the power regulation of the power of 25 MW, 15 MW and 10 MW is respectively shared by the Wu Jiangsu, wu Qiao transform/220 kV. #2 main transform-high voltage side equivalent load, the Yangcheng factory/21 kV. # 1 machine, the Qinshan second factory/20 kV.1 machine and the Huadong Fangjiashan nuclear power plant/24 kV.1 machine. The consumption is calculated to be 0.346 s.
3) Sensitivity calculation
Based on the grid digital twin stored in the memory data grid, the node and branch sensitivity can be rapidly calculated, and decision support can be provided for grid operation scheduling. The performance test results of all the power nodes (1579) of the test network and the branches (1593) connected to the power nodes on the sensitivity calculation of the power control line "east China, east Yang line" are shown in Table 1.
TABLE 1 sensitivity calculation results
And configuring a plurality of sets of power grid models in the memory data grid, and performing parallel computation on a plurality of power flows. The parallel power flow calculation test results are shown in table 2. The computing test environment is a computer with 4 cores and 8 Hyper-threads (Hyper-threads). The total calculation time and acceleration ratio when processing 1 to 32 parallel load flow calculation tasks are listed in the table. The test result shows that the parallel power flow calculation based on the memory calculation technology developed by the project has good linear horizontal expansibility, and when the parallel calculation task is more than 8, the acceleration ratio is close to the theoretical limit 4. It should be noted that when parallel power grid simulation calculation is performed on the in-memory data grid, the power grid model and the corresponding algorithm must have the Multi-thread safety (Multi-thread Safe) characteristic.
TABLE 2 test results of parallel memory computations
And starting a memory data grid consisting of a plurality of JVMs based on 2 servers to test. The computational test environment was 2 servers (4 × CPU: intel Xeon E7-4830 v2.0 GHz, CPU/10 cores, 40 cores total). The total calculation time and acceleration ratio when processing 1 to 128 parallel load flow calculation tasks are listed in table 3. The test result shows that the parallel power flow calculation based on the memory calculation technology developed by the project has good linear horizontal expansibility when being expanded on a physical machine, and the processing time of one server for processing the same number of tasks is increased and reduced by half. The parallel power flow calculation of a single server is further optimized.
TABLE 3 test results of parallel memory calculation of multiple servers
Parallel computing at the algorithm level has been implemented in static security and stability analysis, and the parallel case of the algorithm is shown in table 4. Performance test model: thirty-one plus 4 million nodes in the northwest (1.3 million effective nodes); the content of the performance test is as follows: the sensitivity is calculated to be 1.2 ten thousand, and the number of scanning faults of the whole network N-1 is 13884; and (3) testing environment: 4 CPU Intel Xeon E7-4830 v2.0 GHz, CPU/10 cores, for a total of 40 cores. The test results are shown in the table below, with an overall acceleration ratio of about 29x.
Table 4 test results of algorithm parallelism level
The invention provides a power grid digital twin body construction method and a platform for supporting debugging operation, which are suitable for a large power grid dispatching operation application scene, and the digital twin body mirrors the real-time operation state of a physical power grid in a high-fidelity manner, and supports real-time analysis and rolling deduction. Aiming at the characteristics of complex stability rules, multiple control dimensions, hidden monitoring blind areas and the like of an extra-high voltage power grid, the platform can be used for assisting the day-ahead, day-in and real-time operation safety monitoring and checking of the power grid, assisting in achieving power grid dispatching stable and specified full life cycle management, operation risk dead-angle-free rolling monitoring, marketized multi-scene safety checking and assistant decision making, providing a brand-new application platform-level solution for real-time support of dispatching operation monitoring, analysis and decision making, improving the real-time performance of power grid dispatching decision making, improving the intelligent rapid assistant decision making capability in the field of large power grid safety operation, and solving the problem that dispatching services lack real-time flexible and quick decision making support.
The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the invention.
Claims (10)
1. A power grid digital twin body construction method for supporting debugging operation is characterized by comprising the following steps:
acquiring power grid online data and offline data for constructing a power grid digital twin;
according to the characteristics of the online data and the offline data of the power grid, different file adapters are constructed, and the file adapters are adapted to the online data and the offline data of the power grid;
and analyzing the power grid online data and the power grid offline data through the file adapter, adapting the power grid online data and the power grid offline data to corresponding power grid models, mapping data to a power grid digital twin body, and constructing the power grid digital twin body.
2. The method of claim 1, wherein the grid online data comprises: QS files for power grid state estimation and power grid operation real-time data; the power grid offline data comprises: and future state data and power flow files of the power grid.
3. The method according to claim 1 or 2, wherein the different file adapter comprises:
the system comprises a QS file adapter for power grid state estimation, a real-time library adapter for power grid operation real-time data, a power grid future state data and power flow file PSASP/BPA file adapter.
4. The method according to claim 1, wherein the adapting the grid online data and the offline data into corresponding grid models through the file adapter to achieve mapping of data to grid digital twins comprises:
introducing topological correlation and simulation parameter data in a power grid model into a power grid calculation model and introducing physical equipment data into a full-grid model of a power grid digital twin through a QS file adapter for power grid state estimation;
the real-time database adapter of the power grid operation real-time data is used for adapting the power grid operation real-time data to a physical equipment model object of a power grid digital twin;
the method comprises the steps of performing enumeration modeling on a power grid computing model in a power grid digital twin and corresponding equipment types in the power grid future state data and power flow file equipment model through model information enumeration contained in a defined equipment model through a power grid future state data and power flow file PSASP/BPA file adapter, and establishing an association relation with a digital twin enumeration model in an adding and labeling mode in the enumeration definition of the power grid future state data and power flow file model.
5. The method according to claim 4, wherein the QS file adapter of grid state estimation comprises: the file analysis, data caching and model mapping three-layer structure;
the file analysis layer carries out data analysis on the whole network model to generate entity equipment corresponding to the data table;
converting the entity class into a computer-readable data structure to generate data analysis;
the data caching layer caches the data in the data table;
and the model mapping layer establishes corresponding types of objects in the power grid calculation model of the digital twin according to the logical relation of QS files estimated by the power grid state of the entity equipment corresponding to the data table based on the data analysis, so as to realize model mapping.
6. The method of claim 4, wherein fitting the grid operation real-time data into the physical equipment model object of the grid digital twin through a real-time library adaptor of the grid operation real-time data comprises:
acquiring data of an alternating current line segment, an alternating current line terminal, a transformer winding, a circuit breaker, a bus section and a transformer substation from a power grid real-time library through a data interface;
for each type of acquired data, establishing a key-value pair object, which specifically comprises: for an alternating current line section, a transformer, a breaker, a bus section and a transformer substation, a key is a specific equipment name, and a value is actual measurement data corresponding to the equipment; for the alternating current line, the key is a specific alternating current line name, and measurement values corresponding to the station on the I side and the station on the J side of the line are respectively stored; for the transformer winding, the key is a specific transformer winding name, and the values respectively store actual measurement data corresponding to the high voltage side, the medium voltage side and the low voltage side of the transformer.
7. The method according to claim 4, wherein the PSASP/BPA file adapter comprises three layers of structures of file parsing, data caching and model mapping, and the association relationship among the layers is realized through enumeration and labeling;
the file analysis layer is used for respectively establishing key value pair objects of the single equipment aiming at different equipment; aiming at the equipment of the same type, forming an entity class of a single type model by using the established key value pair objects of all the single equipment; combining entity classes of a plurality of single type models together to form a set as an information class of the single type model; forming a key-value pair set by the information classes of different types of model information;
the data caching layer is used for caching the data of the file analysis layer;
the model mapping layer obtains digital twin model enumeration information by analyzing model information enumeration of the future state data and the power flow file of the power grid, different devices are taken out from the data cache layer according to the digital twin model enumeration information, and corresponding objects are established in the digital twin model according to the logical relationship.
8. The method of claim 1, further comprising:
and updating the constructed power grid digital twin body by adopting a complex event processing engine.
9. A grid digital twin platform supporting scheduled operation, comprising:
the data module is used for acquiring online data and offline data of a power grid;
the modeling calculation core module is used for reading online data and offline data of the power grid from the data module; analyzing the power grid online data and the power grid offline data through a file adapter, adapting the power grid online data and the power grid offline data to corresponding power grid models, mapping data to a power grid digital twin body, and constructing the power grid digital twin body;
the advanced application module provides power grid load flow information through the power grid digital twin body constructed by the modeling calculation core module; and after the digital twin of the power grid is updated, providing simulation analysis for the support scheduling of the power grid based on artificial intelligence application, power grid short-circuit current calculation and static safety analysis.
10. The platform of claim 9, further comprising:
and updating the constructed power grid digital twin body by adopting a complex event processing engine.
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