A system and method for centralized processing of synchronized phasor data

Abstract

This invention relates to a system and method for centralized processing of synchronous phasor data, belonging to the field of synchronous phasor measurement technology. This invention integrates a synchronous phasor data acquisition board onto an intelligent remote control unit (RTU), utilizing the hardware resources of the RTU already present in the intelligent substation to acquire synchronous phasor data, thereby reducing hardware resource investment. Simultaneously, it utilizes the storage resources configured on the monitoring server to store data acquired by the synchronous phasor data acquisition board that exceeds a certain time frame, achieving optimized long-term storage and providing data assurance for operation and maintenance analysis.

Description

Technical Field

[0001] This invention relates to a system and method for centralized processing of synchronous phasor data, belonging to the field of synchronous phasor measurement technology. Background Technology

[0002] With the advancement of smart substation construction, new application requirements have been placed on synchronous phasor measurement devices. Synchronous phasor data acquisition systems must be installed in substations with voltage levels of 220kV and above. Traditional synchronous phasor data acquisition systems employ… Figure 1 The architecture shown comprises a phasor data concentrator (PDC), a synchronous phasor measurement unit (PMU), and a master station (WAMS). The PDC adopts the technical standard of "GB / T26865.2-2011 Real-time Dynamic Monitoring System for Power Systems Part 2: Data Transmission Protocol," employing a GPS / BeiDou clock synchronization mechanism. It receives dynamic data from the PMU at a rate of 10 / 25 / 50 / 100 frames per second, including voltage and current phasor data, as well as real-time information such as switching quantities, frequency, rate of frequency change, power, and power angle. Finally, it forwards the real-time dynamic data, transient filtering, and continuous filtering files to the master station (WAMS) at a rate of 10 / 20 / 50 / 100 frames per second. The PDC's built-in local storage can retain at least 14 days of data, which is automatically deleted after this period. For example, Chinese patent application CN108614187A discloses a power system oscillation tracing method and system based on multimodal synchronous phasors, including multiple multimodal phasor measurement units, a multimodal phasor concentrator, and a multimodal oscillation wide-area monitoring / analysis and tracing platform. The multimodal phasor concentrator 200 is used to communicate with the multiple multimodal phasor measurement units and store phasor data. However, this architecture has the following problems: 1) Rigid hierarchical architecture: The three-level architecture adopted by the system, namely the Dispatch Master Station (WAMS), Phasor Data Concentrator (PDC), and Synchronous Phasor Measurement Unit (PMU), requires the PDC to be deployed as dedicated hardware. This creates a redundant configuration with the original remote motors in the substation in terms of data transmission to the master station, resulting in repeated investment in hardware resources and thus increasing hardware costs.

[0003] 2) Storage stability: Due to the limited local hard drive capacity, the PDC storage module is difficult to meet the long-term storage needs of various types of data such as dynamic data, transient waveforms / continuous data, and configuration files in the synchronous phasor device. It usually adopts a periodic (e.g., every 14 days) deletion method for storage optimization. When maintenance is required, the periodic deletion of data may lead to insufficient data, which will affect the maintenance analysis.

[0004] 3) When new PMU devices or communication protocols are added, hardware and software modifications are required, which reduces the flexibility of the system. Summary of the Invention

[0005] The purpose of this invention is to provide a system and method for centralized processing of synchronous phasor data, so as to solve the problems of high hardware cost and insufficient storage in current centralized processing of synchronous phasor data.

[0006] To address the aforementioned technical problems, this invention provides a centralized processing system for synchronized phasor data. The system includes a synchronized phasor data acquisition board and a monitoring server. The synchronized phasor data acquisition board is integrated into an intelligent telemetry unit (MTU). The MTU connects to a synchronized phasor measurement unit via the integrated synchronized phasor data acquisition board to acquire data measured by the synchronized phasor measurement unit. The monitoring server is equipped with computing and storage resources to store data acquired by the synchronized phasor data acquisition board that exceeds a certain time period.

[0007] Furthermore, the synchronous phasor data acquisition board is equipped with a synchronous data acquisition module. The synchronous data acquisition module adopts a containerized architecture, including a data acquisition container group and a real-time processing container group. The data acquisition container group is used to realize the acquisition and secure isolation of PMU data, and the real-time processing container group is used to realize the pre-allocation and processing of computing resources.

[0008] Furthermore, the data acquisition container group includes N data acquisition containers, each of which is configured with a hardware channel identifier, an electrical interval description, and a resource quota. The hardware channel identifier is used to specify the physical channel address between the hardware and the synchronous phasor measurement unit, the electrical interval description is used to associate the specific equipment location in the substation, and the resource quota is used to describe the size of its memory buffer.

[0009] Furthermore, the real-time processing container group adopts a three-level container based on data type to realize the pre-allocation and processing of computing resources. The first-level container is used to realize real-time dynamic processing, the second-level container is used to realize data preprocessing, and the third-level container is used to realize steady-state analysis of data.

[0010] Furthermore, the first-level container, the second-level container, and the third-level container are all configured with corresponding computing threads and bound CPU physical cores. The first-level container is used to collect data from the synchronization phasor measurement unit and calculate the effective value. The second-level container is used to perform data format verification, timestamp alignment, and quality identifier injection on the data collected by the first-level container. The third-level container is used for data waveform recording.

[0011] Furthermore, the synchronous phasor data acquisition board integrated in the intelligent telemetry machine is also used for communication connection with the master station. The synchronous data acquisition module also includes a master station communication container group. The master station communication container group adopts an extensible protocol parsing plug-in framework to support multiple communication protocols and protocol changes between the synchronous phasor data acquisition board and the master station.

[0012] Furthermore, the synchronous data acquisition module also includes a monitoring storage container group, which includes a hot data storage container and a cold data storage container. The hot data storage container is used to store data that needs to be accessed frequently in the recent period of time collected by the synchronous data acquisition module, while the cold data storage container is used to store data that does not need to be accessed frequently in the recent period of time collected by the synchronous data acquisition module, as well as data beyond that recent period of time.

[0013] Furthermore, the intelligent telecontrol unit adopts a master-slave redundancy configuration, and each intelligent telecontrol unit is equipped with a synchronization phasor data acquisition board.

[0014] Furthermore, the synchronous phasor data acquisition board integrated in the intelligent telemetry unit has multiple Ethernet channels for communication with the synchronous phasor measurement unit.

[0015] This invention also provides a method for centralized processing of synchronized phasor data. The system used in this method includes a monitoring server and an intelligent telemetry unit. The intelligent telemetry unit integrates a synchronized phasor data acquisition board, which is used to connect to a synchronized phasor measurement unit to acquire data measured by the synchronized phasor measurement unit. The monitoring server is configured with computing and storage resources to store data acquired by the synchronized phasor data acquisition board that exceeds a certain time period.

[0016] Furthermore, the synchronous phasor data acquisition board is equipped with a synchronous data acquisition module. The synchronous data acquisition module adopts a containerized architecture, including a data acquisition container group and a real-time processing container group. The data acquisition container group is used to realize the acquisition and secure isolation of PMU data, and the real-time processing container group is used to realize the pre-allocation and processing of computing resources.

[0017] Furthermore, the data acquisition container group includes N data acquisition containers, each of which is configured with a hardware channel identifier, an electrical interval description, and a resource quota. The hardware channel identifier is used to specify the physical channel address between the hardware and the synchronous phasor measurement unit, the electrical interval description is used to associate the specific equipment location in the substation, and the resource quota is used to describe the size of its memory buffer.

[0018] Furthermore, the real-time processing container group adopts a three-level container based on data type to realize the pre-allocation and processing of computing resources. The first-level container is used to realize real-time dynamic processing, the second-level container is used to realize data preprocessing, and the third-level container is used to realize steady-state analysis of data.

[0019] Furthermore, the first-level container, the second-level container, and the third-level container are all configured with corresponding computing threads and bound CPU physical cores. The first-level container is used to collect data from the synchronization phasor measurement unit and calculate the effective value. The second-level container is used to perform data format verification, timestamp alignment, and quality identifier injection on the data collected by the first-level container. The third-level container is used for data waveform recording.

[0020] Furthermore, the synchronous phasor data acquisition board integrated in the intelligent telemetry machine is also used for communication connection with the master station. The synchronous data acquisition module also includes a master station communication container group. The master station communication container group adopts an extensible protocol parsing plug-in framework to support multiple communication protocols and protocol changes between the synchronous phasor data acquisition board and the master station.

[0021] Furthermore, the synchronous data acquisition module also includes a monitoring storage container group, which includes a hot data storage container and a cold data storage container. The hot data storage container is used to store data that needs to be accessed frequently in the recent period of time collected by the synchronous data acquisition module, while the cold data storage container is used to store data that does not need to be accessed frequently in the recent period of time collected by the synchronous data acquisition module, as well as data beyond that recent period of time.

[0022] Furthermore, the intelligent telecontrol unit adopts a master-slave redundancy configuration, and each intelligent telecontrol unit is equipped with a synchronization phasor data acquisition board.

[0023] Furthermore, the synchronous phasor data acquisition board integrated in the intelligent telemetry unit has multiple Ethernet channels for communication with the synchronous phasor measurement unit.

[0024] The beneficial effects of this invention are as follows: This invention integrates the synchronization phasor data acquisition board into the intelligent remote motor, and uses the hardware resources of the intelligent remote motor that already exists in the intelligent substation to realize the acquisition of synchronization phasor data, thereby reducing the investment of hardware resources. At the same time, it uses the storage resources configured in the monitoring server to store the data collected by the synchronization phasor data acquisition board that exceeds a certain period of time, thereby optimizing long-term storage and providing data security for operation and maintenance analysis. Attached Figure Description

[0025] Figure 1 This is a system architecture diagram of a traditional synchronous phasor device; Figure 2 This is a diagram of the containerized synchronous phasor data centralized processing system architecture of the present invention; Figure 3 This is a functional deployment logic diagram of the container group of this invention; Figure 4 This is an easy example of YAML file configuration in the embodiments of the present invention. Detailed Implementation

[0026] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings.

[0027] Implementation of a Synchronous Phasor Data Centralized Processing System This invention deploys a synchronous data acquisition module in an intelligent telemetry unit (TMU). The synchronous data acquisition board deployed in the TMU receives the data stream from the PMU, and the storage resources configured on the monitoring server are used to store the data acquired by the synchronous phasor data acquisition board that exceeds a certain time. A lightweight container platform is used to divide the software system in the synchronous data acquisition board and the monitoring server into four major container groups: data acquisition, real-time processing, master station communication, and monitoring storage. The data acquisition container group, real-time processing container group, and master station communication container group are part of the synchronous data acquisition module deployed in the intelligent TMU, while the monitoring storage container group is part of the monitoring server.

[0028] Specifically, such as Figure 2 As shown, the synchronous phasor data centralized processing system of the present invention includes an intelligent remote control unit (RTU) and a monitoring server. The monitoring server is an existing device in the substation and is mainly used to realize functions such as monitoring the status of substation equipment and remote control operation. The RTU is equipped with a synchronous data acquisition board, which is used to communicate with each synchronous phasor measurement unit (PMU) in the substation. The PMU is used to collect phasor data and other related data within the substation, such as voltage, current, phase angle, frequency, power, and power angle data of substation transformers, high-voltage lines, capacitors, etc. The synchronous data acquisition board deployed in the RTU receives PMU data streams through an Ethernet physical channel; that is, each PMU transmits the collected data to the synchronous data acquisition board through an Ethernet physical channel. The monitoring server is communicatively connected to the synchronous data acquisition board and each PMU, providing long-term storage and monitoring capabilities based on its configured high-performance computing and storage resources. The RTU can be configured with primary and backup redundancy as needed, and each RTU is equipped with a synchronous phasor data acquisition board.

[0029] like Figure 3As shown, the software system (i.e., the synchronous phasor data acquisition module) deployed in the intelligent remote sensing machine adopts a containerized architecture, including a data acquisition container group, a real-time processing container group, and a master station communication container group. The software system in the monitoring server also adopts a containerized architecture, including a monitoring storage container group. This containerized architecture can solve the problems of resource conflicts, inefficient deployment, and fault propagation in traditional architectures. The core effects include: First, resource isolation and security assurance. Each container group is independently bound to a CPU core group and memory buffer through a YAML configuration file (e.g., the data acquisition container is bound to 0-3 CPU cores and 2MB of memory). Data tasks in different electrical intervals (e.g., the high-voltage side of #1 main transformer and 220kV line 1) do not compete for resources, and a single container failure (e.g., an abnormality in a PMU acquisition container) only affects the corresponding channel and will not cause the entire synchronous data acquisition module to be paralyzed. Second, elastic expansion and efficient operation and maintenance: When adding a new PMU device, only a new container instance needs to be added and the hardware channel identifier needs to be configured, without the need for downtime and hardware modification.

[0030] The data acquisition container group, real-time processing container group, main station communication container group, and monitoring storage container group are all equipped with platform standardized interfaces. Each container group can exchange information by calling the platform standardized interface service through its own platform standardized interface. The standardized interface of this platform is a custom interface defined by this system, and its specific design is as follows: ① Interface Functions: Supports three types of interactions: "data upload," "command issuance," and "status feedback." For example, the data acquisition container group uploads raw PMU data to the real-time processing container group through the interface, and the monitoring and storage container group receives storage commands from the real-time processing container group through the interface; ② Data Format: Encapsulated in JSON format, it must contain the fields "Device ID (e.g., PMU-01)," "Data Type (e.g., voltage phasor)," "Timestamp (accurate to ms)," "Data Value," and "Check Code." Example: {"deviceID":"PMU-01","dataType":"voltagePhasor","timestamp":"20260129100000123","dataValue":"110kV","checkCode":"A3F2"}; ③ Communication Mechanism: Based on TCP / IP to achieve reliable transmission, with a 100ms interval. Timeout retransmission; automatic logging and triggering of local alarms (such as indicator light flashing) when the interface call fails; ④ Access control: each container group is assigned a unique access token, and only authorized containers can call the interface to prevent unauthorized data tampering.

[0031] The data acquisition container group is used to acquire and securely isolate PMU data. The group consists of N data acquisition containers, where N is typically the number of PMU devices in the substation, and N is greater than or equal to 2. Each data acquisition container is first instantiated using a predefined structured configuration file (such as YAML format). Figure 4 As shown, a mapping relationship is established between container instances, hardware channels, and electrical isolation. Key parameters are assigned to each container, including a hardware channel identifier, electrical bay description, and resource quota. The hardware channel identifier specifies the physical channel address (e.g., channel:1001, indicating network port 1); the electrical bay description associates the specific equipment location in the substation (e.g., "#1 main transformer high-voltage side"); and the resource quota describes the memory buffer size (e.g., 2MB) and the bound CPU core group (e.g., cpu-set0-3, indicating CPU cores 0-3). This allows each container instance to independently allocate CPU core groups and memory quotas, locking resources through configuration files to ensure physical isolation of data from different electrical bays and prevent resource contention. When the data acquisition container group starts, it obtains the physical network card channel address through the "channel" field in the configuration file. The user-space program calls the recv() function to read packets in batches, mapping the network card buffer to the container memory space, enabling direct data read / write between the hardware channel and container memory. Parallel and secure acquisition of multi-channel data is achieved through multi-container isolation.

[0032] The real-time processing container group employs a three-tiered container architecture based on data types to pre-allocate and process computing resources. The first-tier container handles real-time dynamic processing, the second-tier container handles data preprocessing, and the third-tier container handles steady-state data analysis. Each of the first, second, and third-tier containers is configured with corresponding computing threads and bound CPU physical cores. The first-tier container acquires data from the synchronous phasor measurement unit and calculates its effective value. The second-tier container performs data format verification, timestamp alignment, and quality identifier injection on the data acquired by the first-tier container. The third-tier container performs data waveform recording.

[0033] Specifically, the first-level container is defined through a structured configuration file, similar to... Figure 4The system can be structured in several ways. For example, a dedicated computing thread can be defined and bound to a CPU physical core. The parameter `cpu_shares:600` indicates that 60% of the computer resources are allocated to dynamically acquire PMU data, including voltage and current phasor data, as well as real-time information such as switching quantities, frequency, rate of change of frequency, power, and power angle, for effective value calculation. A second-level container, defined through a structured configuration file, defines a dedicated computing thread and binds it to a CPU physical core, allocating 30% of the computer resources to complete data format verification, timestamp alignment, and quality identifier injection. A third-level container, also defined through a structured configuration file, defines a dedicated computing thread and binds it to a CPU physical core, allocating 10% of the computer resources to execute offline data such as waveform recordings triggered by disturbances or manually. As another implementation method, the computing resources allocated to each level of container can be adjusted according to actual needs.

[0034] The master station communication container group is set up to realize communication between the intelligent remote machine and the master station (WAMS). In this embodiment, the master station communication container group adopts an extensible protocol parsing plugin framework, which supports dynamic loading of various standard protocol plugins such as IEC 61850, Modbus, and TCP. The protocol parsing plugin framework follows a unified interface specification, including data parsing functions, communication port binding methods, and exception handling interfaces. When adding a new protocol, it is only necessary to write the plugin code and deploy it to the specified directory of the container. The protocol extension can be completed by restarting the container without modifying the underlying hardware or system code.

[0035] The monitoring server has data storage capabilities, implemented using a monitoring storage container group. This container stores data collected by the synchronization phasor data acquisition board that has exceeded a certain time frame. To achieve effective management of PMU data, this invention employs a "hot storage-cold storage" system for the monitoring storage container group. This embodiment divides the monitoring storage container group into hot data storage containers and cold data storage containers. Hot data refers to data that requires frequent access in the recent period, while cold data refers to data that does not require frequent access in the recent period and data exceeding that period. The hot data storage container uses high-speed storage devices (such as SSDs) deployed locally on the monitoring server to store frequently accessed data (such as real-time data like voltage and phase) in the recent period (e.g., 1 hour), meeting the needs of real-time monitoring and rapid fault backtracking. The storage duration can be set via a configuration file according to actual needs. The cold data storage container uses a distributed storage cluster. A time window algorithm is used to migrate data exceeding a set duration (e.g., 15 minutes) from the synchronization data acquisition module to this cold data storage container in batches. This supports the retention of historical data for more than 60 days. The migration task execution time can be set via a configuration file according to actual needs, solving the problem of insufficient storage capacity in traditional PDCs. Meanwhile, the monitoring server also has monitoring capabilities, equipped with a runtime monitoring module for communicating with each phasor measurement unit (PMU) to achieve real-time monitoring of each PMU. The implementation logic for real-time monitoring of each PMU consists of three stages: communication link establishment, multi-dimensional status acquisition, and anomaly alarm. Communication Link Construction: The monitoring server's operation monitoring module establishes a dedicated TCP / IP communication link with each PMU based on the GB / T 26865.2-2011 protocol through the synchronization phasor data acquisition board of the intelligent remote motor. A heartbeat packet is sent every 500ms to maintain link connectivity. Multi-dimensional Status Acquisition: Real-time acquisition of PMU hardware status (CPU load, memory usage, power supply voltage), acquisition status (sampling frequency, time synchronization deviation, data integrity identifier), and communication status (link latency, data packet loss rate). Anomaly Alarm Trigger: When an anomaly is detected where the PMU sampling frequency deviates from the preset value (e.g., preset 50 frames / second, actual value is lower than 48 frames / second), the time synchronization deviation exceeds 1ms, or the link interruption exceeds 3 seconds, an alarm message is immediately generated and pushed to the main station system, while simultaneously triggering local audible and visual alarms.

[0036] To better illustrate the synchronous phasor data centralized processing system of the present invention, the deployment and implementation process of the synchronous phasor data centralized processing system will be described below using a 200kV smart substation as an example.

[0037] 1) Hardware configuration The hardware configuration of the synchronous phasor data centralized processing system includes an intelligent remote control monitoring server. In this example, two intelligent remote control units are deployed, redundantly, one as the primary and one as the backup. Each remote control unit has a 16-channel Ethernet (the hardware design of the board is fixed at 16 channels) synchronous phasor data acquisition board. This acquisition board supports synchronous phasor measurement unit (PMU) access and SNTP time synchronization, meeting the needs of multi-bay data synchronous acquisition in substations. The monitoring server is equipped with integrated high-speed storage devices (such as 1TB SSDs) and a large-capacity hard disk array (6×2TB), supporting distributed storage cluster deployment and providing data storage and computing capabilities. Eight synchronous phasor measurement units (PMUs) are configured, capable of acquiring data such as voltage, current, phase angle, frequency, power, and power angle from substation transformers, 220kV lines, 110kV lines, and capacitors.

[0038] 2) Software Function Deployment Data acquisition container group: Based on the number of electrical bays in the substation, 16 container instances are created. Each instance binds one PMU channel data through a predefined YAML configuration file. User-space programs call the recv() function to read packets in batches, mapping the physical channel memory to the container's virtual address space to achieve data acquisition.

[0039] Real-time processing container group: Construct three-level containers and allocate resources. Level 1 containers (cores 0-3, 60% CPU) calculate the effective values ​​of voltage / current; Level 2 containers (cores 4-5, 30% CPU) verify data integrity and inject quality codes; Level 3 containers (cores 6-7, 10% CPU) process waveform files. Resource quotas are controlled through container parameters to improve data processing efficiency.

[0040] The main station communication container group loads the protocol plugin of "GB / T 26865.2-2011 Real-time Dynamic Monitoring System for Power Systems Part 2: Data Transmission Protocol" to realize communication and transmission with the WAMS main station.

[0041] Monitoring storage container group: Deploy hot storage management containers and cold storage archiving containers. Hot storage management containers are responsible for data scheduling of high-speed storage devices, with 1TB SSDs as the storage medium; cold storage archiving containers realize the automatic migration of data from hot storage to cold storage and from cold storage to archiving through scheduled tasks, with 6×2TB hard disk arrays as the storage medium.

[0042] Implementation of the method for centralized processing of synchronized phasor data This invention also provides a method for centralized processing of synchronized phasor data. The system used in this method includes a monitoring server and an intelligent telemetry unit. The intelligent telemetry unit integrates a synchronized phasor data acquisition board, which is used to connect to a synchronized phasor measurement unit to acquire data measured by the synchronized phasor measurement unit. The monitoring server is configured with computing and storage resources to store data acquired by the synchronized phasor data acquisition board that exceeds a certain time period.

[0043] like Figure 2 As shown, the synchronous phasor data centralized processing system used in the synchronous phasor data centralized processing method of this invention includes an intelligent remote motor and a monitoring server. The intelligent remote motor is equipped with a synchronous data acquisition board, which is used to communicate with each synchronous phasor measurement unit (PMU) within the substation. The PMU is used to collect phasor data and other related data within the substation, such as voltage, current, phase angle, frequency, power, and power angle data of transformers, high-voltage lines, and capacitors in the substation. The synchronous data acquisition board deployed in the intelligent remote motor receives PMU data streams through an Ethernet physical channel; that is, each PMU transmits its collected data to the synchronous data acquisition board through an Ethernet physical channel. The monitoring server is communicatively connected to the synchronous data acquisition board and each PMU, providing long-term storage and monitoring capabilities based on its configured high-performance computing and storage resources. The intelligent remote motor can be configured with primary and backup redundancy as needed, and each intelligent remote motor is equipped with a synchronous phasor data acquisition board.

[0044] like Figure 3 As shown, the software system (i.e., the synchronous phasor data acquisition module) deployed in the intelligent telemetry machine adopts a containerized architecture, including a data acquisition container group, a real-time processing container group, and a master station communication container group. The software system in the monitoring server also adopts a containerized architecture, including a monitoring storage container group. Each of the data acquisition container group, real-time processing container group, master station communication container group, and monitoring storage container group has a standardized platform interface. Each container group interacts with information by calling the standardized platform interface service through its own standardized platform interface.

[0045] The data acquisition container group is used to acquire and securely isolate PMU data. The group consists of N data acquisition containers, where N is greater than or equal to 2. Each data acquisition container is first instantiated using a predefined structured configuration file (such as YAML format), for example... Figure 4As shown, a mapping relationship is established between container instances, hardware channels, and electrical isolation. Key parameters are assigned to each container, including a hardware channel identifier, electrical bay description, and resource quota. The hardware channel identifier specifies the physical channel address (e.g., channel:1001, indicating network port 1); the electrical bay description associates the specific equipment location in the substation (e.g., "#1 main transformer high-voltage side"); and the resource quota describes the memory buffer size (e.g., 2MB) and the bound CPU core group (e.g., cpu-set0-3, indicating CPU cores 0-3). This allows each container instance to independently allocate CPU core groups and memory quotas, locking resources through configuration files to ensure physical isolation of data from different electrical bays and prevent resource contention. When the data acquisition container group starts, it obtains the physical network card channel address through the "channel" field in the configuration file. The user-space program calls the recv() function to read packets in batches, mapping the network card buffer to the container memory space, enabling direct data read / write between the hardware channel and container memory. Parallel and secure acquisition of multi-channel data is achieved through multi-container isolation.

[0046] The real-time processing container group employs a three-tiered container architecture based on data types to pre-allocate and process computing resources. The first-tier container handles real-time dynamic processing, the second-tier container handles data preprocessing, and the third-tier container handles steady-state data analysis. Each of the first, second, and third-tier containers is configured with corresponding computing threads and bound CPU physical cores. The first-tier container acquires data from the synchronous phasor measurement unit and calculates its effective value. The second-tier container performs data format verification, timestamp alignment, and quality identifier injection on the data acquired by the first-tier container. The third-tier container performs data waveform recording.

[0047] Specifically, the first-level container is defined through a structured configuration file, similar to... Figure 4 The system can be structured in several ways. For example, a dedicated computing thread can be defined and bound to a CPU physical core. The parameter `cpu_shares:600` indicates that 60% of the computer resources are allocated to dynamically acquire PMU data, including voltage and current phasor data, as well as real-time information such as switching quantities, frequency, rate of change of frequency, power, and power angle, for effective value calculation. A second-level container, defined through a structured configuration file, defines a dedicated computing thread and binds it to a CPU physical core, allocating 30% of the computer resources to complete data format verification, timestamp alignment, and quality identifier injection. A third-level container, also defined through a structured configuration file, defines a dedicated computing thread and binds it to a CPU physical core, allocating 10% of the computer resources to execute offline data such as waveform recordings triggered by disturbances or manually. As another implementation method, the computing resources allocated to each level of container can be adjusted according to actual needs.

[0048] The main station communication container group adopts an extensible protocol parsing plugin framework, which supports dynamic loading of various standard protocol plugins such as IEC 61850, Modbus, and TCP. The protocol parsing plugin framework follows a unified interface specification, including data parsing functions, communication port binding methods, and exception handling interfaces. When adding a new protocol, you only need to write the plugin code and deploy it to the specified directory of the container. The protocol extension can be completed by restarting the container without modifying the underlying hardware or system code.

[0049] The monitoring server has data storage capabilities, implemented using a monitoring storage container group. This container stores data collected by the synchronization phasor data acquisition board that has exceeded a certain time frame. To achieve effective management of PMU data, this invention employs a "hot storage-cold storage" system for the monitoring storage container group. This embodiment divides the monitoring storage container group into hot data storage containers and cold data storage containers. Hot data refers to data that requires frequent access in the recent period, while cold data refers to data that does not require frequent access in the recent period and data exceeding that period. The hot data storage container uses high-speed storage devices (such as SSDs) deployed locally on the monitoring server to store frequently accessed data (such as real-time data like voltage and phase) in the recent period (e.g., 1 hour), meeting the needs of real-time monitoring and rapid fault backtracking. The storage duration can be set via a configuration file according to actual needs. The cold data storage container uses a distributed storage cluster. A time window algorithm is used to migrate data exceeding a set duration (e.g., 15 minutes) from the synchronization data acquisition module to this cold data storage container in batches. This supports the retention of historical data for more than 60 days. The migration task execution time can be set via a configuration file according to actual needs, solving the problem of insufficient storage capacity in traditional PDCs. Meanwhile, the monitoring server also has monitoring functions, with a running monitoring module for communicating with each synchronous phasor measurement unit (PMU) to achieve real-time monitoring of each synchronous phasor measurement unit (PMU).

[0050] In summary, this invention utilizes the hardware resources of the intelligent remote actuators and monitoring servers within the intelligent substation itself, thereby reducing hardware investment. At the software level, a lightweight container platform is built on the intelligent remote actuators and monitoring servers, dividing the system into four container groups: data acquisition, real-time processing, master station communication, and monitoring storage. By replacing traditional PDC hardware with a containerized architecture, the rigidity, storage limitations, and poor scalability of the traditional architecture are solved.

Claims

1. A system for centralized processing of synchronized phasor data, characterized in that, The system includes a synchronization phasor data acquisition board and a monitoring server. The synchronization phasor data acquisition board is integrated on the intelligent telemetry unit. The intelligent telemetry unit connects to the synchronization phasor measurement unit through the integrated synchronization phasor data acquisition board to acquire the data measured by the synchronization phasor measurement unit. The monitoring server is configured with computing resources and storage resources to store data acquired by the synchronization phasor data acquisition board that exceeds a certain period of time.

2. The synchronous phasor data centralized processing system according to claim 1, characterized in that, The synchronous phasor data acquisition board is equipped with a synchronous data acquisition module. The synchronous data acquisition module adopts a containerized architecture, including a data acquisition container group and a real-time processing container group. The data acquisition container group is used to acquire and securely isolate PMU data, and the real-time processing container group is used to pre-allocate and process computing resources.

3. The synchronous phasor data centralized processing system according to claim 2, characterized in that, The data acquisition container group includes N data acquisition containers. Each data acquisition container is configured with a hardware channel identifier, an electrical interval description, and a resource quota. The hardware channel identifier is used to specify the physical channel address between the container and the synchronous phasor measurement unit. The electrical interval description is used to associate the specific equipment location in the substation. The resource quota is used to describe the size of its memory buffer.

4. The synchronous phasor data centralized processing system according to claim 2, characterized in that, The real-time processing container group adopts a three-level container based on data type to realize the pre-allocation and processing of computing resources. The first-level container is used to realize real-time dynamic processing, the second-level container is used to realize data preprocessing, and the third-level container is used to realize steady-state analysis of data.

5. The synchronous phasor data centralized processing system according to claim 4, characterized in that, The first-level container, second-level container, and third-level container are all configured with corresponding computing threads and bound CPU physical cores. The first-level container is used to collect data from the synchronization phasor measurement unit and calculate the effective value. The second-level container is used to perform data format verification, timestamp alignment, and quality identifier injection on the data collected by the first-level container. The third-level container is used for data waveform recording.

6. The synchronous phasor data centralized processing system according to claim 2, characterized in that, The integrated synchronous phasor data acquisition board of the intelligent telemetry machine is also used for communication connection with the master station. The synchronous data acquisition module also includes a master station communication container group. The master station communication container group adopts an extensible protocol parsing plug-in framework to support multiple communication protocols and protocol changes between the synchronous phasor data acquisition board and the master station.

7. The synchronous phasor data centralized processing system according to claim 2, characterized in that, The synchronous data acquisition module also includes a monitoring storage container group, which includes a hot data storage container and a cold data storage container. The hot data storage container is used to store data that needs to be accessed frequently in the recent period of time collected by the synchronous data acquisition module, while the cold data storage container is used to store data that does not need to be accessed frequently in the recent period of time collected by the synchronous data acquisition module, as well as data beyond that recent period of time.

8. The synchronous phasor data centralized processing system according to claim 1, characterized in that, The intelligent telecontrol unit adopts a master-slave redundancy configuration, and each intelligent telecontrol unit is equipped with a synchronous phasor data acquisition board.

9. The synchronous phasor data centralized processing system according to claim 7, characterized in that, The intelligent telemetry unit integrates a synchronous phasor data acquisition board with multiple Ethernet channels for communication with the synchronous phasor measurement unit.

10. A method for centralized processing of synchronized phasor data, characterized in that, The processing method employs the synchronous phasor data centralized processing system as described in any one of claims 1-9.

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