A Method and System for Synchronizing WAMS Time-Series Data Across Security Zones Based on Stream-Based Parallel Processing

Abstract

A method and system for synchronizing WAMS time-series data across security zones based on parallel processing and traffic splitting is proposed. In Security Zone I, the WAMS time-series data synchronization master service dynamically groups all PMU measurement points connected to the WAMS master station. Based on the grouping, multiple time-series data synchronization instances are automatically started in parallel processing to generate WAMS time-series data files containing grouping information. These files are then transmitted synchronously across security zones using different communication channels. In Security Zone III, the file parsing master service automatically determines and starts multiple file parsing instances based on the grouping information in the WAMS time-series data file names, achieving split parsing of data files and parallel submission and saving of WAMS time-series data. This invention, based on the automatic dynamic loading of multiple time-series data synchronization instances in Security Zone I and the parallel processing of multiple file parsing instances in Security Zone III, improves the cross-security zone WAMS data synchronization capability, ensures the sampling rate and integrity of WAMS time-series data in Security Zone III, and provides strong data support for ensuring the safe and stable operation of the power grid.

Description

Technical Field

[0001] This invention relates to the field of power system dispatch automation, and in particular to a method for synchronizing WAMS time-series data across security zones based on parallel processing of split-flow data. Background Technology

[0002] In my country, most provincial-level and above power grid companies have built wide-area measurement systems (WAMS), which consist of a WAMS master station located in the power dispatch and control center and PMU substations located at the power plant and substation ends. The WAMS master station collects and receives phasor data sent by the PMU substations in real time through the power dispatch data network. After processing and storage by the real-time time series database and the time series history database, high-density WAMS time series data is formed for online monitoring and offline analysis applications, enabling the perception and evaluation of the dynamic characteristics of the power grid and ensuring the safe and stable operation of the power grid.

[0003] According to the security protection principles of power secondary systems, WAMS belongs to the real-time control zone (Security Zone I). Time-series data stored in the WAMS master station can only be exported from Security Zone I under the premise of adhering to security protection principles. Offline analysis and refined research of power grid events are usually conducted in the production management zone (Security Zone III). With the rapid changes in my country's power grid structure and the increasing complexity of power grid operation characteristics, the scenarios in which operation analysts in power dispatch and control centers use WAMS time-series data for research in Security Zone III are gradually expanding and increasing in frequency, creating an urgent need for convenient access to WAMS time-series data across security zones.

[0004] Synchronization of WAMS time-series data across security zones requires transmission from Security Zone I to Security Zone III via a power system forward isolation device. While reducing the sampling rate of high-density WAMS time-series data decreases the amount of data to be transmitted, which can to some extent meet the needs of the increasing number of PMU measurement points at the WAMS master station, the transmitted data only satisfies the needs of some analysis scenarios and is insufficient for in-depth analysis of complex power grid faults. Using single-file compression transmission can fully preserve the high-density sampling characteristics of WAMS time-series data, but as the number of PMU substations connected to the WAMS master station increases, file transmission latency gradually increases, and file parsing efficiency gradually decreases. This makes it difficult to guarantee the timeliness and reliability of WAMS time-series data synchronization across security zones, hindering large-scale power grid characteristic analysis research conducted by operational analysts in Security Zone III. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method for synchronizing WAMS time-series data across security zones based on parallel processing. In Security Zone I, PMU measurement points connected to the WAMS master station are dynamically grouped. The grouped PMU measurement point data is then cached and compressed using multiple instances in parallel to generate multiple WAMS time-series data files. These files are transmitted to a designated directory in Security Zone III via different communication channels and a power system forward isolation device. In Security Zone III, based on the grouping information in the WAMS time-series data file names, the corresponding parsing service instance is automatically activated to perform parallel parsing of the WAMS time-series data files. The data is then submitted and saved to the WAMS time-series history database in Security Zone III. This achieves reliable and stable synchronization of high-density WAMS time-series data across security zones, providing convenient WAMS time-series data consistent with that in Security Zone I for operation and analysis personnel in Security Zone III. This comprehensively supports the refined analysis of complex power grid faults and improves the level of power grid dynamic characteristic analysis.

[0006] In view of this, the present invention discloses a method for synchronizing WAMS time-series data across security zones based on split parallel processing.

[0007] The present invention adopts the following technical solution:

[0008] At the WAMS master station in Security Zone I of the power dispatch control center, the WAMS time-series data synchronization master service obtains all connected PMU measurement point information from the real-time database. It dynamically groups the PMU measurement points according to the set number of grouped measurement points. Based on the grouping, multiple time-series data synchronization instances are automatically started, receiving data from PMU substations cyclically from the message bus and performing cache processing. When a set period is reached, each instance extracts PMU data from the cache, generates corresponding WAMS time-series data files using a set compression algorithm, and transmits them to a designated directory in Security Zone III through the designated communication channel of the cross-security zone synchronization service. The Security Zone III file parsing master service periodically scans the WAMS time-series data files in the designated directory. When a new group of WAMS time-series data files is generated, the corresponding parsing service instance is automatically started, parsing the WAMS time-series data files of different groups in parallel. After decompression, the data is cached in each parsing service instance. When a set retention period is reached, the Security Zone III WAMS time-series history database write interface is called to complete the WAMS time-series data submission and storage, achieving reliable and stable synchronization of high-density WAMS time-series data across security zones.

[0009] A method for synchronizing WAMS time-series data across security zones based on split-flow parallel processing includes the following steps:

[0010] In Security Zone I, the WAMS time-sequential data synchronization master service dynamically groups all PMU measurement points accessed by the WAMS master station, automatically starts multiple time-sequential data synchronization instances for parallel processing according to the grouping situation, generates WAMS time-sequential data files containing grouping information, and uses different communication channels to shunt and synchronously transmit across security zones; in Security Zone III, the file parsing master service automatically determines and starts multiple file parsing instances according to the grouping information in the name of the WAMS time-sequential data file, realizing the shunt parsing of data files and the parallel submission and saving of WAMS time-sequential data.

[0011] Specifically, it includes the following steps:

[0012] Step 1, in the WAMS master station in Security Zone I, the WAMS time-sequential data synchronization master service obtains all n PMU measurement points accessed from the real-time database, and dynamically groups the PMU measurement point information according to the set number k of grouped measurement points, forming m groups.

[0013] Step 2, according to the number of groups, the WAMS time-sequential data synchronization master service automatically starts time-sequential data synchronization instances.

[0014] Step 3, each instance circularly receives and analyzes the data packets sent by the PMU substation from the message bus and performs caching processing.

[0015] Step 4, when the set processing period is reached, each instance extracts PMU data from the cache, generates corresponding WAMS time-sequential data files using a compression algorithm, and transmits them to the specified directory in Security Zone III through the specified communication channel of the cross-security zone synchronous transmission service.

[0016] Step 5, the file parsing master service in Security Zone III regularly queries the WAMS time-sequential data files in the specified directory according to the set scanning period. When a new grouped WAMS time-sequential data file is generated, the file parsing master service in Security Zone III automatically starts the corresponding parsing service instance.

[0017] Step 6, shunt and parallelly parse the WAMS time-sequential data files of different groups, and cache them in each parsing service instance after decompression.

[0018] Step 7, when the set saving period is reached, call the write interface of the WAMS time-sequential history database in Security Zone III to complete the submission and storage of WAMS time-sequential data.

[0019] Preferably, step 2 specifically includes:

[0020] Step 2.1, according to the number of groups m, the WAMS time-sequential data synchronization master service performs traversal loop processing on group i, 0 ≤ i < m, and the initial value of i is 0.

[0021] Step 2.2: Calculate the maximum PMU measurement point address \(i\) included in the \(i\)-th group according to the number of grouped measurement points \(k\). max , \(i\) max = \((i + 1) * k\);

[0022] Step 2.3: Use \(i\) max and the number of grouped measurement points \(k\) as startup parameters to start the \(i\)-th PMU data receiving instance;

[0023] Step 2.4: Let \(i = i + 1\). When \(i < m\), repeat Steps 2.2 to 2.4.

[0024] Preferably, Step 3 specifically includes:

[0025] Step 3.1: Each instance is started in the manner described in Step 2.3;

[0026] Step 3.2: According to the startup parameters \(i\) max , \(k\), calculate the range of PMU measurement point addresses processed by each instance \([i\) start , \(i\) end , \(i\) start = \(i\) max – \(k + 1\), \(i\) end = \(i\) max ;

[0027] Step 3.3: Load and start the PMU data receiving thread and the WAMS timing data file generation thread inside each instance;

[0028] Step 3.4: The PMU data receiving thread continuously receives the data packets sent by the PMU substation from the message bus and resolves the PMU measurement point address \(i\) curr ;

[0029] Step 3.5: When the PMU measurement point address \(i\) curr is within the range of PMU measurement point addresses processed by this instance \([i\) start , \(i\) end , save the data of the PMU measurement point address \(i\) curr in the memory buffer.

[0030] Preferably, Step 4 specifically includes:

[0031] Step 4.1: The WAMS timing data file generation thread extracts data from the memory buffer according to the set processing cycle threshold;

[0032] Step 4.2: The WAMS timing data file generation thread compresses the extracted data according to the set compression algorithm type and generates a WAMS timing data file corresponding to the instance;

[0033] Step 4.3: The WAMS time-series data file generation thread calls the transmission interface of the cross-security zone synchronization transmission service to synchronize the WAMS time-series data file generated in step 4.2 to the specified directory in security zone III through the specified communication channel.

[0034] Preferably, step 5 specifically includes:

[0035] Step 5.1: The Security Zone III file parsing main service queries the generation time of WAMS time-series data files in the specified directory of Security Zone III according to the set scan cycle threshold;

[0036] Step 5.2: When the generation time is later than the last query time of the Security Zone III file parsing main service, the Security Zone III file parsing main service parses the maximum PMU measurement point address i contained in the WAMS time series data file name. max Number of measurement points in each group, k.

[0037] Preferably, step 5 further includes, when a new grouped WAMS timing data file is generated, the Security Zone III file parsing master service, based on the maximum PMU measurement point address i obtained in step 5.2, performs parsing. max 1. Calculate the number of test points in the group, k, and determine if a corresponding parsing service instance already exists. If no corresponding parsing service instance exists, the Security Zone III file parsing main service will parse the maximum PMU test point address i using step 5.2. max The number of measurement points in a group, k, is used as a startup parameter to automatically start a new parsing service instance.

[0038] Preferably, step 6 specifically includes:

[0039] Step 6.1, parse the service instance and load the startup parameter i max 、k;

[0040] Step 6.2: The WAMS time-series data file parsing thread and the WAMS time-series data saving thread are loaded and started within the parsing service instance;

[0041] Step 6.3: The WAMS timing data file parsing thread periodically parses the WAMS timing data files in the directory specified in Step 4.3, and obtains the maximum PMU measurement point address i from the file name. maxj Number of measurement points in groups k j Data time;

[0042] Step 6.4, when i in step 6.3 maxj k j Each of the steps in step 6.1 is related to i. max If k is equal to 0, and the data time in step 6.3 is greater than the previous parsing time of the parsing service instance, then parse the WAMS time-series data file and read the data.

[0043] Step 6.5: Decompress the read data and store it in a memory buffer.

[0044] Preferably, step 7 specifically includes:

[0045] Step 7.1: The WAMS time-series data saving thread reads data from the memory buffer in step 6.5 according to the set saving period threshold.

[0046] Step 7.2: The WAMS time series data saving thread calls the WAMS time series history library write interface in Security Zone III to complete the submission and storage of WAMS time series data.

[0047] A WAMS time-series data synchronization system across security zones based on split-stream parallel processing, the system includes:

[0048] The data acquisition and preprocessing module is used to obtain all n connected PMU measurement points from the real-time database and dynamically group the PMU measurement point information according to the set number of grouped measurement points; and automatically start the time series data synchronization instance according to the number of groups.

[0049] The data caching module is used to receive and parse data packets sent by the PMU substation from the message bus and perform caching processing.

[0050] The data transmission module is used to extract PMU data from the cache, generate corresponding WAMS timing data files using a compression algorithm, and transmit them to the specified directory in Security Zone III through the designated communication channel of the cross-security zone synchronous transmission service.

[0051] The data parsing module is used to periodically query WAMS time-series data files in a specified directory according to a set scanning cycle. When a new group of WAMS time-series data files is generated, the corresponding parsing service instance is automatically started.

[0052] The decompression module is used to split and parse WAMS time-series data files in different groups in parallel, and cache the decompressed data in each parsing service instance.

[0053] The data storage module is used to call the WAMS time-series history library write interface in Security Zone III to complete the submission and storage of WAMS time-series data when the set retention period is reached.

[0054] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0055] This invention employs a WAMS time-series data synchronization master service in Safety Zone I to dynamically group all PMU measurement points connected to the WAMS master station. Based on the grouping, multiple time-series data synchronization instances are automatically launched, generating WAMS time-series data files containing grouping information. This enables the parallel, distributed, and synchronous transmission of WAMS time-series data across safety zones. In Safety Zone III, a file parsing master service automatically determines and launches multiple file parsing instances based on the grouping information in the WAMS time-series data file names. This achieves distributed parsing of data files and parallel submission and saving of WAMS time-series data. Through the automatic dynamic loading of multiple time-series data synchronization instances in Safety Zone I and the parallel processing of multiple file parsing instances in Safety Zone III, this invention greatly adapts to the ever-increasing number of PMU measurement points in power dispatch control centers, significantly improves the cross-safety-zone WAMS data synchronization processing capability, reduces operation and maintenance costs, ensures the sampling accuracy and integrity of WAMS time-series data in Safety Zone III, and enhances the work efficiency of operation analysts conducting power grid characteristic analysis in Safety Zone III, providing strong data support for ensuring the safe and stable operation of the power grid. Attached Figure Description

[0056] Figure 1 This is a method for synchronizing WAMS time-series data across security zones based on split parallel processing. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, other embodiments obtained by those skilled in the art without creative effort are all within the protection scope of this invention.

[0058] Figure 1 Flowchart of a method for synchronizing WAMS time-series data across security zones based on split parallel processing.

[0059] The proposed method for synchronizing WAMS time-series data across security zones based on parallel processing operates at the WAMS master station in Security Zone I and the dispatch master station in Security Zone III of the power dispatch control center. The networks of Security Zone I and Security Zone III are connected through a dedicated forward isolation device for the power system. The WAMS master station in Security Zone I receives data from PMU substations in real time via a message bus, with a data density typically of 50 frames / second, and stores it in the WAMS time-series history database of Security Zone I. The dispatch master station in Security Zone III deploys the WAMS time-series history database to store and manage the WAMS time-series data synchronized to Security Zone III.

[0060] Taking a power dispatch control center with 130,000 PMU measurement points connected to the WAMS master station in Safety Zone I as an example, this invention illustrates a method for synchronizing WAMS time-series data across safety zones based on parallel processing. The method specifically includes the following steps:

[0061] Step 1: At the WAMS master station in Security Zone I, the WAMS time series data synchronization master service retrieves all connected PMU measurement points from the real-time database, with a number of n = 130,000.

[0062] Step 2: According to the set number of group measurement points k = 100000, dynamically group the PMU measurement point information from Step 1 to form a group of m = 2;

[0063] In practice, the number of group measurement points k can be modified through the database.

[0064] Based on the number of groups m=2, the WAMS time series data synchronization master service automatically starts 2 time series data synchronization instances; Step 2 includes: based on the number of measurement points k in the group, calculate the maximum PMU measurement point address included in group i, based on the maximum PMU measurement point address and the number of measurement points in the group, start the i-th PMU data receiving instance, and based on the number of groups m, the WAMS time series data synchronization master service iterates through group i until all groups are traversed.

[0065] Step 2.1: Based on the number of groups m=2, the WAMS time-series data synchronization master service iterates through group i in a loop, where 0≤i<2, and the initial value of i is 0;

[0066] Step 2.2: Based on the number of measurement points k = 100000 in Step 2, calculate the maximum PMU measurement point address i included in group i. max i max = (i+1)*100000;

[0067] Step 2.3, using i from step 2.2 max The number of measurement points k in the group is used as the startup parameter to start the i-th PMU data receiving instance;

[0068] Step 2.4: Let i = i + 1. When i < 2, repeat steps 2.2 to 2.4.

[0069] Step 3: In Step 2, each instance receives and parses the data packets sent by the PMU substation from the message bus in a loop and performs buffering processing.

[0070] Step 3.1: Each instance is started in the manner described in Step 2.3;

[0071] Step 3.2, based on the startup parameter i from step 3.3 max, k = 100000, calculate the PMU measurement point address range processed by each instance [i start i end ], i start =i max -100000+1, i end =i max ;

[0072] Step 3.3: Each instance internally loads and starts the PMU data receiving thread and the WAMS timing data file generation thread;

[0073] In steps 3.4 and 3.3, the PMU data receiving thread continuously receives data packets from the PMU substation via the message bus and parses the PMU measurement point address i from the data packets. curr ;

[0074] Step 3.5, when the PMU measurement point address i in step 3.4... curr In this instance, the PMU measurement point address range [i start i end [When], the PMU measurement point address i curr The data is stored in a memory buffer.

[0075] Step 4: When the set processing cycle is reached, each instance in Step 2 extracts PMU data from the cache, generates the corresponding WAMS timing data file using the set compression algorithm, and transmits it to the specified directory in Security Zone III through the designated communication channel of the cross-security zone synchronous transmission service.

[0076] In steps 4.1 and 3.3, the WAMS time-series data file generation thread extracts data from the memory buffer in step 4.4 according to the set processing cycle threshold.

[0077] In steps 4.2 and 3.3, the WAMS time-series data file generation thread compresses the extracted data in step 4.1 according to the set compression algorithm type to generate the WAMS time-series data file corresponding to the instance.

[0078] In step 4.3, the WAMS time-series data file generation thread in step 3.3 calls the transmission interface of the cross-security zone synchronization sending service to synchronize the WAMS time-series data file generated in step 4.2 to the specified directory in security zone III through the specified communication channel.

[0079] In practice, in step 4.1, the processing cycle threshold is configured or modified through the database, preferably 1 minute.

[0080] In specific implementation, in step 4.2, the compression algorithm type is configured or modified through the database, preferably the zstd compression algorithm.

[0081] In practice, step 4.3 involves configuring or modifying the specified communication channel through the database.

[0082] Step 5: The Security Zone III file parsing main service periodically queries the WAMS time-series data files in the directory specified in Step 4 according to the set scanning cycle.

[0083] Step 5.1: The Security Zone III file parsing main service queries the generation time of the WAMS time-series data file in the specified directory in Step 4.3 according to the set scan cycle threshold;

[0084] Step 5.2: When the generation time is later than the last query time of the Security Zone III file parsing main service, the Security Zone III file parsing main service parses the maximum PMU measurement point address i contained in the WAMS time series data file name. max The number of measurement points in each group is k = 100,000.

[0085] In specific implementation, in step 5.1, the scan cycle threshold is configured or modified through the database, preferably 10 seconds.

[0086] Step 5 also includes automatically starting the corresponding parsing service instance of the Security Zone III file parsing main service when a new packet WAMS time series data file is generated: when a new packet WAMS time series data file is generated, the Security Zone III file parsing main service uses the maximum PMU measurement point address i obtained in step 5.2 to parse the data. max 1. Calculate the number of test points in the group, k, and determine if a corresponding parsing service instance already exists. If no corresponding parsing service instance exists, the Security Zone III file parsing main service will parse the maximum PMU test point address i using step 5.2. max The number of measurement points in a group, k, is used as a startup parameter to automatically start a new parsing service instance.

[0087] Specifically, the Security Zone III file parsing main service parses the maximum PMU test point address i according to step 5.2. max 1. If the number of measurement points in the group is k = 100000, determine whether a corresponding parsing service instance already exists;

[0088] When no corresponding parsing service instance exists, the Security Zone III file parsing main service parses the maximum PMU test point address i using step 5.2. max The number of group measurement points k = 100000 is used as the startup parameter to automatically start a new parsing service instance.

[0089] Step 6: In step 5, each parsing service instance performs parallel parsing of WAMS time-series data files from different groups, and caches the decompressed data in each parsing service instance.

[0090] Step 6.1: Parse the service instance and load the startup parameter i from step 5. max k = 100000;

[0091] Step 6.2: The WAMS time-series data file parsing thread and the WAMS time-series data saving thread are loaded and started within the parsing service instance;

[0092] Step 6.3, the WAMS timing data file parsing thread in step 6.2 periodically parses the WAMS timing data file in the directory specified in step 4.3, and obtains the maximum PMU measurement point address i from the file name. maxj Number of measurement points in groups k j Data time;

[0093] Step 6.4, when i in step 6.3 maxj k j Each of the steps in step 6.1 is related to i. max When k = 100000 is equal, and the data time in step 6.3 is greater than the previous parsing time of the parsing service instance, the WAMS time-series data file is parsed and the data is read.

[0094] Step 6.5: Decompress the read data and store it in a memory buffer.

[0095] Step 7: When the set retention period is reached, each parsing service instance in Step 5 calls the WAMS time series history library write interface in Security Zone III to complete the submission and storage of WAMS time series data, thereby achieving reliable and stable synchronization of high-density WAMS time series data across security zones based on split parallel processing.

[0096] In steps 7.1 and 6.2, the WAMS time-series data saving thread reads data from the memory buffer in step 6.5 according to the set saving period threshold.

[0097] In step 7.2, the WAMS timing data saving thread in step 6.2 calls the WAMS timing history library write interface in security zone III to complete the submission and storage of WAMS timing data.

[0098] In practice, in step 7.1, the retention period threshold is configured or modified in the database, preferably 1 minute.

[0099] Example 2: A WAMS time-series data synchronization system across security zones based on split-stream parallel processing. The system includes:

[0100] The data acquisition and preprocessing module is used to obtain all n connected PMU measurement points from the real-time database and dynamically group the PMU measurement point information according to the set number of grouped measurement points; and automatically start the time series data synchronization instance according to the number of groups.

[0101] The data caching module is used to receive and parse data packets sent by the PMU substation from the message bus and perform caching processing.

[0102] The data transmission module is used to extract PMU data from the cache, generate corresponding WAMS timing data files using a compression algorithm, and transmit them to the specified directory in Security Zone III through the designated communication channel of the cross-security zone synchronous transmission service.

[0103] The data parsing module is used to periodically query WAMS time-series data files in a specified directory according to a set scanning cycle. When a new group of WAMS time-series data files is generated, the corresponding parsing service instance is automatically started.

[0104] The decompression module is used to split and parse WAMS time-series data files in different groups in parallel, and cache the decompressed data in each parsing service instance.

[0105] The data storage module is used to call the WAMS time-series history library write interface in Security Zone III to complete the submission and storage of WAMS time-series data when the set retention period is reached.

[0106] The beneficial effects of this invention are as follows: Compared with the prior art, this invention employs a dynamic grouping method in Security Zone I, where the WAMS time-series data synchronization master service dynamically groups all PMU measurement points connected to the WAMS master station. Based on the grouping, multiple time-series data synchronization instances are automatically launched to generate WAMS time-series data files containing grouping information, achieving parallel cross-security zone synchronous transmission of WAMS time-series data. In Security Zone III, the file parsing master service automatically determines and launches multiple file parsing instances based on the grouping information in the WAMS time-series data file names, achieving split parsing of data files and parallel submission and saving of WAMS time-series data. Through the automatic dynamic loading of multiple time-series data synchronization instances in Security Zone I and the parallel processing of multiple file parsing instances in Security Zone III, this invention greatly adapts to the ever-increasing number of PMU measurement points in power dispatch control centers, significantly improves the cross-security zone WAMS data synchronization processing capability, reduces operation and maintenance costs, ensures the sampling accuracy and integrity of WAMS time-series data in Security Zone III, and enhances the work efficiency of operation analysts conducting power grid characteristic analysis in Security Zone III, providing strong data support for ensuring the safe and stable operation of the power grid.

[0107] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for synchronizing WAMS time-series data across security zones based on split-flow parallel processing, characterized in that: In Security Zone I, the WAMS time series data synchronization master service dynamically groups all PMU measurement points connected to the WAMS master station. Based on the grouping, it automatically starts multiple time series data synchronization instances for parallel processing, generates WAMS time series data files containing grouping information, and uses different communication channels to distribute and transmit synchronously across security zones. In Security Zone III, the file parsing master service automatically determines and starts multiple file parsing instances based on the grouping information in the WAMS time series data file name, realizing the split parsing of data files and the parallel submission and saving of WAMS time series data. Step 1: At the WAMS master station in Security Zone I, the WAMS time-series data synchronization master service retrieves all connected data from the real-time database. n Each PMU measurement point, and according to the set number of measurement points in groups. k The PMU measurement point information is dynamically grouped to form... m One group; Step 2: Based on the number of groups, the WAMS time-series data synchronization master service automatically starts the time-series data synchronization instance; Step 2 specifically includes: Step 2.1, based on the number of groups m WAMS time-series data synchronization master service for groups i Perform iterative processing, 0 ≤ i < m , i The initial value is 0; Step 2.2, based on the number of measurement points in each group. k Calculate grouping i Includes the largest PMU measurement point address i max , i max = ( i + 1)* k ; Step 2.3, with i max Number of measurement points in groups k As a startup parameter, start the... i One PMU data receiving instance; Step 2.4, let i = i +1, when i < m Repeat steps 2.2 to 2.

4. Step 3: Each instance receives and parses the data packets sent by the PMU substation from the message bus in a loop, and performs buffering processing. Step 4: When the set processing cycle is reached, each instance extracts PMU data from the cache, uses a compression algorithm to generate the corresponding WAMS time-series data file, and transmits it to the specified directory in Security Zone III through the designated communication channel of the cross-security zone synchronous transmission service. Step 5: The Security Zone III file parsing main service periodically queries the WAMS time-series data files in the specified directory according to the set scanning cycle. When a new group of WAMS time-series data files is generated, the Security Zone III file parsing main service automatically starts the corresponding parsing service instance. Step 5 specifically includes: Step 5.1: The Security Zone III file parsing main service queries the generation time of WAMS time-series data files in the specified directory of Security Zone III according to the set scan cycle threshold; Step 5.2: When the generation time is later than the last query time of the Security Zone III file parsing main service, the Security Zone III file parsing main service parses the WAMS time series data file name containing the maximum PMU measurement point address. i max Number of measurement points in groups k ; Step 6: Split and parse the WAMS time-series data files of different groups in parallel, and cache them in each parsing service instance after decompression; Step 7: When the set retention period is reached, call the WAMS time series history library write interface in Security Zone III to complete the submission and storage of WAMS time series data.

2. The method for synchronizing WAMS time-series data across security zones based on split-flow parallel processing as described in claim 1, characterized in that: Step 3 specifically includes: Step 3.1: Each instance is started in the manner described in Step 2.3; Step 3.2, according to the startup parameters i max , k The address range of the PMU measurement points processed by each instance was calculated. i start , i end ], i start = i max – k +1, i end = i max ; Step 3.3: Each instance internally loads and starts the PMU data receiving thread and the WAMS timing data file generation thread; Step 3.4: The PMU data receiving thread continuously receives data packets sent by the PMU substation from the message bus and parses the PMU measurement point address from the data packets. i curr ; Step 3.5, when the PMU measurement point address i curr The range of PMU measurement point addresses processed in this instance [ i start , i end [Within], the PMU measurement point address i curr The data is stored in a memory buffer.

3. The method for synchronizing WAMS time-series data across security zones based on split-flow parallel processing as described in claim 2, characterized in that: Step 4 specifically includes: Step 4.1: The WAMS time-series data file generation thread extracts data from the memory buffer according to the set processing cycle threshold; Step 4.2: The WAMS time-series data file generation thread compresses the extracted data according to the set compression algorithm type to generate a WAMS time-series data file corresponding to the instance. Step 4.3: The WAMS time-series data file generation thread calls the transmission interface of the cross-security zone synchronization transmission service to synchronize the WAMS time-series data file generated in step 4.2 to the specified directory in security zone III through the specified communication channel.

4. The method for synchronizing WAMS time-series data across security zones based on split-flow parallel processing according to claim 3, characterized in that: Step 5 also includes the Security Zone III file parsing master service resolving the maximum PMU measurement point address obtained in step 5.2 when a new grouped WAMS timing data file is generated. i max Number of measurement points in groups k The system checks if a corresponding parsing service instance already exists. If no such instance exists, the Security Zone III file parsing main service uses step 5.2 to parse and obtain the address of the maximum PMU test point. i max Number of measurement points in groups k As a startup parameter, a new DNS service instance will be started automatically.

5. The method for synchronizing WAMS time-series data across security zones based on split-flow parallel processing according to claim 4, characterized in that: Step 6 specifically includes: Step 6.1: Parse the service instance and load startup parameters. i max , k ; Step 6.2: The WAMS time-series data file parsing thread and the WAMS time-series data saving thread are loaded and started within the parsing service instance; Step 6.3: The WAMS timing data file parsing thread periodically parses the WAMS timing data files in the directory specified in Step 4.3, and obtains the maximum PMU measurement point address from the file name. i maxj Number of measurement points in groups k j Data time; Step 6.4, when in step 6.3 i maxj , k j In step 6.1 respectively i max , k If the timestamps are equal and the data time in step 6.3 is greater than the previous parsing time of the parsing service instance, then parse the WAMS time-series data file and read the data. Step 6.5: Decompress the read data and store it in a memory buffer.

6. The method for synchronizing WAMS time-series data across security zones based on split-flow parallel processing according to claim 5, characterized in that: Step 7 specifically includes: Step 7.1: The WAMS time-series data saving thread reads data from the memory buffer in step 6.5 according to the set saving period threshold. Step 7.2: The WAMS time series data saving thread calls the WAMS time series history library write interface in Security Zone III to complete the submission and storage of WAMS time series data.

7. A WAMS time-series data cross-security zone synchronization system based on split-parallel processing, executing the WAMS time-series data cross-security zone synchronization method based on split-parallel processing as described in any one of claims 1 to 6, characterized in that: The system includes: The data acquisition and preprocessing module is used to obtain all accessed data from the real-time database. n There are 10 PMU measurement points, and the PMU measurement point information is dynamically grouped according to the set number of grouped measurement points; the time series data synchronization instance is automatically started according to the number of groups; The data caching module is used to receive and parse data packets sent by the PMU substation from the message bus and perform caching processing. The data transmission module is used to extract PMU data from the cache, generate corresponding WAMS timing data files using a compression algorithm, and transmit them to the specified directory in Security Zone III through the designated communication channel of the cross-security zone synchronous transmission service. The data parsing module is used to periodically query WAMS time-series data files in a specified directory according to a set scanning cycle. When a new group of WAMS time-series data files is generated, the corresponding parsing service instance is automatically started. The decompression module is used to split and parse WAMS time-series data files in different groups in parallel, and the decompressed data is cached in each parsing service instance. The data storage module is used to call the WAMS time-series history library write interface in Security Zone III to complete the submission and storage of WAMS time-series data when the set retention period is reached.

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