Public computing support system for power station control system

Abstract

The invention provides a public computing support system for a power station control system, and belongs to the technical field of power generation control, and the system comprises a computing module which is used for operating an application program in the power station control system and providing computing resources for the application program; the data processing module is in communication connection with the calculation module and is used for processing the operation data from the power station control system; the storage module is in communication connection with the data processing module and is used for storing the operation data; the KVM management module is used for performing centralized management and resource scheduling on the calculation module, the data processing module and the storage module; and the exchange module is used for connecting the modules to form a high-speed network so as to ensure real-time data transmission and information synchronization among the modules. Through a public computing support system integrating computing, data processing, storage, management and a high-speed network, efficient processing, real-time transmission, flexible resource scheduling and high-reliability operation of data in a power station control system are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of power generation control, and in particular to a public computing support system for a power station control system. Background Art

[0002] As the automation level of power plant control systems continues to increase, the amount and type of data involved in these systems are also rapidly increasing. Traditional power plant control systems primarily rely on separate computing devices, storage devices, and independent data processing modules. These modules are interconnected via communication protocols and gradually complete the collection, processing, and storage of data. However, as power plants grow in size and complexity, traditional single-piece hardware systems are gradually exposing various limitations.

[0003] In traditional power plant control systems, each functional module often relies on an independent computer or controller for operation. These systems typically adopt a "decentralized" structure, where each module independently handles a specific task and uses standard communication protocols (such as Modbus, CAN, and RS485) for data transmission and coordination. However, this architecture has significant limitations: the limited computing resources of a single controller make it difficult to run complex applications; data exchange between modules relies on low-speed or non-real-time networks, which affects the timeliness of data transmission and system responsiveness. Furthermore, the independent operation of each module and the fragmented data storage make it difficult to centrally manage data and lack redundant backups. This can lead to data loss in the event of system failures or emergencies, seriously affecting system stability.

[0004] In summary, the computing, data processing, storage, and management architectures within traditional power plant control systems are no longer able to effectively address the comprehensive demands of today's power plant control systems for efficient computing, real-time data processing and transmission, flexible resource scheduling, and high system reliability. Therefore, building a public computing support system that supports efficient data processing, flexible resource management, and high reliability has become a pressing technical challenge in the field of power plant control systems. Summary of the Invention

[0005] The present invention provides a public computing support system, method, electronic equipment and storage medium for a power plant control system, which are used to address the defects in the existing technology and realize efficient processing, real-time transmission, flexible resource scheduling and high-reliability operation of data in the power plant control system.

[0006] The present invention provides a public computing support system for a power plant control system, comprising the following modules: A computing module, configured to run applications in the power plant control system and provide computing resources for the applications; a data processing module, in communication with the computing module, for processing operating data from the power station control system; a storage module, communicatively connected to the data processing module, and configured to store the operating data; A KVM management module is used to centrally manage and schedule resources for the computing module, the data processing module, and the storage module; The switching module is used to connect the computing module, the data processing module and the storage module to form a high-speed network to ensure real-time data transmission and information synchronization among the computing module, the data processing module, the storage module and the KVM management module.

[0007] According to a public computing support system for a power plant control system provided by the present invention, the computing module includes multiple physical servers and virtual machine instances. A hot standby redundancy mode is adopted between the physical servers, and the virtual machine instances support dynamic migration and elastic expansion to adapt to the resource requirements of different computing tasks.

[0008] According to a public computing support system for a power plant control system provided by the present invention, the data processing module implements data processing based on a relational database and a distributed computing framework; The relational database is used to store structured historical operation data and supports transaction processing and concurrency control; The distributed computing framework is used to process unstructured data and large-scale real-time data streams to achieve data mining, model training and predictive analysis tasks; The data processing module is also used to support automatic scheduling of tasks and fault-tolerant recovery functions to ensure the continuity and accuracy of data processing.

[0009] According to a public computing support system for a power plant control system provided by the present invention, the storage module is used to analyze the operating data to determine the data type of the operating data; The storage module is further configured to determine a storage method for the operating data based on the data type; The storage module is also used to implement redundant backup functions and supports automatic switching between hot backup and cold backup of data. The hot backup is used to protect critical data in real time to ensure that data is not lost when the main storage fails; the cold backup is used to regularly back up system operation data.

[0010] According to a public computing support system for a power plant control system provided by the present invention, the storage methods include: high-frequency storage, compressed storage, distributed storage and secure storage.

[0011] According to a public computing support system for a power plant control system provided by the present invention, the switching module adopts a redundant ring network design, wherein the redundant ring network design supports automatic path switching to ensure that data transmission is not affected when any network node fails; The switching module also supports network partitioning and access control mechanisms to ensure the real-time and security of data transmission.

[0012] According to a public computing support system for a power plant control system provided by the present invention, the switching module includes a plurality of switching units; and the redundant ring network is formed by cascading all of the switching units.

[0013] The present invention also provides a public computing support method for a power plant control system, comprising the following steps: Run applications in the power plant control system through the computing module and provide computing resources for the applications; Processing the operating data from the power plant control system through a data processing module; storing the operating data based on the data type of the operating data by a storage module; Centrally manage and schedule resources for the computing module, the data processing module, and the storage module through the KVM management module; The computing module, the data processing module and the storage module are connected through a switching module to form a high-speed network to ensure real-time data transmission and information synchronization among the computing module, the data processing module, the storage module and the KVM management module.

[0014] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the public computing support method for a power station control system when executing the program.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which implements the public computing support method for a power plant control system when executed by a processor.

[0016] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the common computing support method for a power plant control system is implemented.

[0017] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: By employing a collaborative approach involving computing modules, data processing modules, storage modules, KVM management modules, and switching modules, the power plant control system achieves efficient application execution, real-time data processing and storage, centralized resource management and scheduling, and overall system stability and reliability. After data processing is complete, operational data is categorized and stored. The storage module not only addresses the need for large-scale data storage but also, through rational data management, avoids resource waste and improves overall system efficiency. The KVM management module centrally manages and manages resource scheduling and monitoring for the computing, data processing, and storage modules, achieving efficient utilization of system resources. To ensure real-time and stable data transmission and information synchronization between modules, the switching module connects the computing, data processing, storage, and KVM management modules via a high-speed network, forming an efficient data channel. This high-speed switching network ensures rapid data transmission and synchronization between modules, avoiding system operational disruptions caused by data latency. In summary, by integrating computing, data processing, storage, management, and a high-speed network into a common computing support system, the power plant control system achieves efficient data processing, real-time transmission, flexible resource scheduling, and highly reliable operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 This is an overall architecture diagram of the public computing support system for a power plant control system provided by the present invention.

[0020] Figure 2 This is a working principle diagram of the KVM management module provided by the present invention.

[0021] Figure 3 This is a data storage flow chart provided by the present invention.

[0022] Figure 4 This is a schematic diagram of the software and hardware resource sharing principle of the control system provided by the present invention.

[0023] Figure 5 It is a flow chart of the public computing support method for a power plant control system provided by the present invention.

[0024] Figure 6 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0025] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0026] It should be noted that, in the description of the present invention, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. The orientation or positional relationship indicated by the terms "upper", "lower", etc. is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the system or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.

[0027] The following combination Figures 1-6 The present invention describes a public computing support system, method, electronic device and storage medium for a power plant control system.

[0028] Reference Figure 1 , Figure 1 This is the overall architecture diagram of the public computing support system for power plant control systems provided by the present invention. The system includes the following modules: The computing module is used to run the applications in the power plant control system and provide computing resources for the applications; A data processing module, in communication with the computing module, for processing operating data from the power station control system; A storage module, connected to the data processing module for storing the operation data; KVM management module, used for centralized management and resource scheduling of computing modules, data processing modules, and storage modules; The switching module is used to connect the computing module, data processing module and storage module to form a high-speed network to ensure real-time data transmission and information synchronization between the computing module, data processing module, storage module and KVM management module.

[0029] The present invention provides a public computing support system for a power plant control system. The system integrates a computing module, a data processing module, a storage module, a KVM management module, and a switching module. Real-time data transmission and efficient resource management are achieved between the modules through a high-speed network to meet the high-performance computing needs, massive data processing needs, and reliability assurance needs of the power plant control system in a complex operating environment.

[0030] In this embodiment, the computing module assumes the core task of running the applications in the power plant control system and provides the required computing resources for these applications. Considering the complexity of applications in the power plant system and the dynamic changes in task load, the computing module utilizes a combination of multiple physical servers and virtual machine instances. The physical servers operate in hot standby redundancy mode. If a server fails, the other servers can seamlessly take over the task, ensuring continuous system operation. Furthermore, virtual machine instances support dynamic migration and elastic expansion, allowing flexible resource allocation based on the needs of different computing tasks, thereby avoiding resource waste and performance bottlenecks.

[0031] The data processing module communicates with the computing module and is used to process and analyze large amounts of data generated during power plant operation. By combining a relational database with a distributed computing framework, this module enables efficient processing of structured and unstructured data. The relational database is used to store structured historical operating data and supports transaction processing and concurrency control to ensure the accuracy and consistency of data management. The distributed computing framework is responsible for processing unstructured data and large-scale data streams generated in real time, supporting tasks such as data mining, model training, and predictive analysis. In addition, to ensure the continuity of the data processing process, the data processing module also has automatic task scheduling and fault-tolerant recovery functions, ensuring that the system can quickly recover and continue to execute data processing tasks in the event of an unexpected failure.

[0032] The storage module is in communication with the data processing module and is responsible for storing the processed operation data and selecting an appropriate storage method according to the data type. The specific storage module storage method for the operation data will be described in detail in subsequent embodiments, so it will not be described in detail here.

[0033] The KVM management module is responsible for the centralized management and resource scheduling of the computing module, data processing module, and storage module. During the operation of the system, the KVM management module uses virtualization technology to achieve unified monitoring and dynamic scheduling of the resources of each module. When the system load increases, the KVM management module can automatically start backup resources to participate in the calculation, and optimize the allocation of resources according to the task priority. In addition, the module also supports the system's permission management and logging functions to help administrators control the system status in real time, and provide detailed operation records to ensure the security and traceability of the system. Further, the working principle of the KVM management module can refer to Figure 2 , Figure 2 This is a working principle diagram of the KVM management module provided by the present invention.

[0034] The switching module connects the computing module, data processing module, storage module and KVM management module through a high-speed network, forming a data transmission channel with high reliability and high bandwidth.

[0035] In addition, the switching module can also support network partitioning and access control mechanisms, and can set different transmission priorities and access rights according to different data transmission requirements to ensure the timeliness of critical data transmission and the overall security of the system.

[0036] Through the above solution, the public computing support system achieves efficient integration of computing, data processing, and storage resources. It also centrally schedules and manages these resources through the KVM management module, ensuring smooth system operation under various operating conditions. The introduction of high-speed switching modules further improves the efficiency and reliability of data transmission between modules. Compared to traditional single-controller or standalone computer systems, the system provided by this invention significantly improves the computing performance, data processing capabilities, and scalability of the power plant control system, reduces hardware resource waste, and enhances the system's real-time performance and reliability.

[0037] In one possible implementation, the computing module includes multiple physical servers and virtual machine instances. A hot standby redundancy mode is used between the physical servers, and the virtual machine instances support dynamic migration and elastic expansion to adapt to the resource requirements of different computing tasks.

[0038] Specifically, to accommodate the diverse computing needs of complex power plant control systems, the computing module utilizes a hybrid architecture consisting of multiple physical servers and virtual machine instances. Physical servers utilize hot standby redundancy, while virtual machine instances support dynamic migration and elastic expansion. This design aims to improve system stability, flexibility, and resource utilization.

[0039] In traditional power plant control systems, computing resources typically rely on a single server or controller. Failure of a single device can disrupt ongoing tasks, impacting system stability and the normal operation of the power plant. However, by integrating multiple physical servers into the computing module and employing hot standby redundancy, we can ensure that if any server fails, other servers can seamlessly take over its tasks, ensuring continuous system operation and the stable execution of critical tasks. This hot standby redundancy design not only enhances the system's fault tolerance but also improves the power plant's ability to respond to emergencies.

[0040] In order to further enhance the flexibility of the computing module, the computing module in this solution also deploys multiple virtual machine instances, each of which runs a specific application or computing task. The introduction of virtual machines realizes resource virtualization, so that computing resources are no longer dependent on specific physical servers. During system operation, the KVM management module can dynamically adjust the resource allocation of each virtual machine according to changes in task load, achieving elastic expansion and dynamic migration. For example, when the load of a certain computing task increases, the system can automatically allocate more computing resources to the corresponding virtual machine to ensure the timely completion of the task. When a physical server needs maintenance, the virtual machine instance can be migrated to another server without affecting the operation of the application, avoiding task interruption due to hardware downtime.

[0041] This design effectively improves the resource utilization efficiency of the computing module. In traditional systems, computing resources are often statically configured, and the computing power of some servers may remain idle for long periods of time, resulting in resource waste. However, through the elastic scaling of virtual machine instances, the system can automatically adjust resource allocation based on current task requirements, maximizing computing resource utilization. Furthermore, the isolation between virtual machine instances enhances system security, ensuring that different applications running on the same physical server will not interfere with each other.

[0042] Furthermore, the computing module in this solution offers excellent scalability. When power plant control requirements increase or new applications need to be deployed, simply add new physical servers or virtual machine instances, eliminating the need for large-scale modifications to the existing system. This not only simplifies system expansion but also reduces system operation and maintenance costs.

[0043] By employing hot standby redundancy across multiple physical servers and dynamic migration and elastic expansion of virtual machine instances, this solution's computing module achieves a good balance between performance, reliability, and flexibility. The redundant design of physical servers ensures stable system operation under high load and fault conditions, while the dynamic management of virtual machines ensures efficient resource utilization and flexible task scheduling, providing reliable and efficient computing support for power plant control system applications.

[0044] In one possible implementation, the data processing module implements data processing based on a relational database and a distributed computing framework; Relational databases are used to store structured historical operational data and support transaction processing and concurrency control; The distributed computing framework is used to process unstructured data and large-scale real-time data streams to implement data mining, model training, and predictive analysis tasks; The data processing module is also used to support automatic task scheduling and fault-tolerant recovery functions to ensure the continuity and accuracy of data processing.

[0045] Specifically, a large amount of data is generated during the operation of a power plant control system. This data includes both structured historical operating data and unstructured real-time data streams. In traditional systems, the methods for processing and managing this data are relatively simple, which can easily lead to low data processing efficiency, especially for the analysis and prediction of large-scale data, where there are obvious bottlenecks. Therefore, this solution uses a relational database to manage structured data, such as the power plant's operation logs, equipment status, and operation records. The accuracy and consistency of this data are crucial to the normal operation of the power plant. Therefore, a relational database provides transaction processing and concurrency control capabilities to ensure the consistency and reliability of data when multiple tasks are accessed concurrently, avoiding errors caused by data conflicts.

[0046] However, power plant control systems rely not only on structured data but also on analyzing unstructured data and large-scale real-time data streams. This data, sourced from various sensors, real-time monitoring systems, and condition monitoring equipment, is massive and diverse in format. To address this issue, the data processing module in this solution integrates a distributed computing framework to process these unstructured and real-time data streams in parallel. This distributed computing framework can split data processing tasks into multiple subtasks and execute them simultaneously on different nodes, significantly improving data processing efficiency. This framework not only supports the monitoring and analysis of real-time data, but also enables data mining, model training, and predictive analysis, providing reliable data support for power plant operation optimization and fault warning.

[0047] Furthermore, power plant control systems place extremely high demands on the continuity and accuracy of data processing. To ensure that data processing tasks are not interrupted by individual node failures during system operation, the data processing module features automatic task scheduling and fault-tolerant recovery capabilities. Specifically, if a node fails to function properly due to a failure, the system automatically reallocates tasks on that node to other nodes, ensuring uninterrupted data processing. Furthermore, the task scheduling mechanism dynamically adjusts task allocation based on current data load and computing resource usage to optimize resource utilization and reduce processing latency.

[0048] Through this design, the data processing module of the present invention effectively solves the problems of low data processing efficiency and insufficient flexibility in traditional power plant control systems. The introduction of relational databases makes structured data management more standardized and reliable, and the distributed computing framework improves the ability of large-scale data analysis, providing strong support for predictive analysis and intelligent operation of power plants. The automatic scheduling and fault-tolerant mechanism of tasks further enhance the robustness and stability of the system. Even in the event of equipment failure, the system can still maintain the continuity and accuracy of data processing. This comprehensive design enables the power plant control system to operate efficiently in complex environments, meet the data processing requirements in different scenarios, and lay a solid foundation for the intelligent management and operation optimization of the system.

[0049] In a possible implementation, the storage module is configured to analyze the operation data to determine a data type of the operation data; The storage module is further used to determine the storage method of the operation data based on the data type; The storage module is also used to implement redundant backup functions and supports automatic switching between hot and cold backups. Hot backup is used to protect critical data in real time to ensure that data is not lost when the primary storage fails; cold backup is used to regularly back up system operation data.

[0050] In a possible implementation, the storage methods include: high-frequency storage, compressed storage, distributed storage, and secure storage.

[0051] Specifically, refer to Figure 3 , Figure 3 This is the data storage flow chart provided by the present invention. When the operating data enters the storage module, the storage module will first analyze the data based on the data analysis algorithm to identify the type of the data. The system will first perform a primary classification of the data type based on a data sampling algorithm that combines simple random sampling and stratified sampling, and identify data that is accessed frequently (such as real-time monitoring data) as high-frequency data, and identify data that is stored for a long time but has a low access frequency (such as historical operation logs) as archived data. In addition, for the raw data of the sensor or the model analysis data, the system will identify it as unstructured data and select a suitable storage solution. The identification of data types is a key step for the storage module to optimize storage efficiency and performance, ensuring that different types of data can be managed using the optimal storage method.

[0052] After determining the data type, the storage module will select a storage method that matches it. For high-frequency data, the system will store it on high-performance storage media such as memory and solid-state drives to ensure fast data access. For archived data, the system uses a combination of lossy and lossless compression storage technology. For data with higher sampling accuracy, lossless compression algorithms such as run-length encoding and Huffman coding are used. For general data, a lossy compression algorithm based on discrete cosine transform (DCT) combined with quantization is used to save storage space and reduce costs. For distributed or unstructured data, the storage module will choose a distributed storage solution, distributing the data across multiple storage nodes to increase access speed. In addition, for parts involving sensitive information or critical data, the storage module uses a secure storage solution, including data encryption, hot standby redundancy, and access control to ensure data security.

[0053] To further enhance data reliability and the system's disaster recovery capabilities, the storage module also features redundant backup functionality, supporting automatic switching between hot and cold backups. When the system detects critical data, the storage module automatically initiates hot backup, synchronizing that data to the redundant storage device. This ensures data protection even in the event of a primary storage failure. Hot backup operates in real time and is particularly suitable for critical data generated during power plant operations, such as equipment status data and alarm logs. For large-scale historical or non-critical data, the system utilizes cold backup, regularly backing up the data to remote storage devices or offline storage media. This design ensures real-time protection of critical data while avoiding excessive consumption of storage resources.

[0054] In one possible implementation, the switching module adopts a redundant ring network design, wherein the redundant ring network design supports automatic path switching to ensure that data transmission is not affected when any network node fails; The switching module also supports network partitioning and access control mechanisms to ensure the real-time and security of data transmission.

[0055] In a possible implementation, the switching module includes multiple switching units; and the redundant ring network is formed by cascading all the switching units.

[0056] Specifically, the various modules within the power plant control system require frequent data exchange and information synchronization. To ensure reliable and real-time system operation, the switching modules utilize a redundant ring network design. This design aims to improve the system's fault resistance and data transmission stability. This redundant ring network design enables the system to automatically switch data transmission paths if any network node fails, ensuring uninterrupted data transmission and preventing system stalls caused by network failures.

[0057] The switching module is composed of multiple switching units, which are cascaded to form a ring network structure. In traditional star or bus networks, data transmission may be interrupted if a node or path fails. However, with a redundant ring network design, if a node or connection in the ring fails, the system automatically identifies the failure and switches to an alternate path to continue data transmission. Because both ends of the ring network are connected to different switching units, data can be routed in opposite directions around the failed node, ensuring that data transmission is not affected by any single point of failure.

[0058] Furthermore, power plant control systems require high real-time and secure data transmission. To meet these requirements, the switch modules also support network partitioning and access control mechanisms. Network partitioning allows different types of data streams to be allocated to independent virtual networks. For example, real-time control data, condition monitoring data, and management data can be transmitted within separate network partitions, preventing interference between different data streams. This partitioning approach not only optimizes network resource utilization but also improves data transmission stability. Access control mechanisms safeguard network security, ensuring that only authorized modules and devices can access specific data channels, thereby preventing unauthorized data access or tampering.

[0059] The switching module design not only enhances the system's structural resilience and transmission stability, but also improves the real-time and security of data transmission through partitioning and control mechanisms. In actual system operation, the switching module dynamically configures network paths and access permissions based on data transmission requirements, providing optimized transmission channels for different business scenarios. Furthermore, the cascading nature of the switching units facilitates network expansion. When a power plant needs to add new modules or data channels, simply add the corresponding switching units and connect them to the existing ring network, without requiring major modifications to the system architecture.

[0060] Through this design, the switching modules ensure efficient data transmission while also enhancing network resiliency and security. Redundant ring networks and automatic path switching mechanisms enhance the system's ability to operate continuously under high load and fault conditions. Network partitioning and access control mechanisms ensure secure and reliable data transmission, laying a solid foundation for the stable operation of the power plant control system.

[0061] It should be noted that, in the public computing support system of the present invention, in order to achieve efficient utilization and management of resources, a design is adopted that abstracts the physical form of hardware computing resources into logical operation resources. Figure 4 , Figure 4This is a schematic diagram of the control system software and hardware resource sharing principles provided by the present invention. This design virtualizes various hardware resources through management and scheduling software, forming a flexibly configurable resource pool to accommodate the dynamic demands for computing, storage, and network resources by different business system tasks. The diagram illustrates the specific structure of this resource abstraction and management, where the resource pool consists of different types of resources, including resource type 1 (e.g., computing resources), resource type 2 (e.g., storage resources), resource type 3 (e.g., network resources), and resource type 4 (e.g., redundant backup resources). These resources are logically allocated to different resource sets and dynamically added or removed from resource sets based on the business system's task requirements.

[0062] During system operation, business systems utilize management and scheduling software to allocate the required resource sets based on the current mission requirements. For example, if business system 1 needs to perform a complex computational analysis task at a certain moment, the scheduling software will dynamically allocate computing resources (e.g., resource type 1) from the resource pool to resource set 1 based on the task's priority and importance to ensure sufficient computing support for the task. Simultaneously, the scheduling software monitors the system's resource usage in real time and flexibly adjusts the composition of resource sets based on task progress and resource load levels to avoid resource waste and bottlenecks.

[0063] Dynamic management of resource sets not only includes resource inclusion but also supports resource removal and reallocation. When a business system completes its computing task, the allocated computing resources are automatically released and returned to the resource pool for use by other tasks. This allows resources within each resource set to flow in and out freely based on task requirements, enabling efficient resource sharing and flexible configuration. The figure illustrates how different business systems use resource sets. The system balances resource allocation across multiple business systems, ensuring that each task receives the necessary resources within the appropriate timeframe.

[0064] Furthermore, to ensure the integrity of data processing and computing tasks, the system uses management and scheduling software to perform task integrity checks. The scheduling software checks and records task execution status, ensuring data consistency and integrity for each task despite dynamic resource changes. If resource shortages or node failures are detected during task execution, the system dynamically incorporates redundant resources from the resource pool into the current resource set, ensuring uninterrupted tasks and ensuring system continuity.

[0065] By decoupling applications from specific hardware resources, the present invention achieves low-coupling encapsulation of software and hardware modules. Business systems no longer need to interact directly with specific hardware devices, but instead interact with resource sets through logical resources. This not only simplifies the system's operation and maintenance management, but also enhances the system's flexibility and scalability. When adding new applications or adjusting the system architecture, only the configuration of the resource set needs to be modified, without the need for large-scale changes to the underlying hardware. As a result, the present invention greatly improves the scalability of the system and reduces overall operation and maintenance costs.

[0066] Reference Figure 5 , Figure 5 : is a flow chart of a public computing support method for a power plant control system provided by the present invention, the method comprising the following steps: Step 1: Run the application in the power plant control system through the computing module and provide computing resources for the application; Step 2: Processing the operating data from the power plant control system through the data processing module; Step 3: storing the operation data based on the data type of the operation data through the storage module; Step 4: Centrally manage and schedule resources for the computing module, data processing module, and storage module through the KVM management module; Step 5: Connect the computing module, data processing module and storage module through the switching module to form a high-speed network to ensure real-time data transmission and information synchronization between the computing module, data processing module, storage module and KVM management module.

[0067] Figure 6 Schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 6As shown, the electronic device may include: a processor 610, a communications interface 620, a memory 630, and a communications bus 640. The processor 610, the communications interface 620, and the memory 630 communicate with each other via the communications bus 640. The processor 610 may invoke logic instructions in the memory 630 to execute a common computing support method for a power plant control system. The method includes: running applications in the power plant control system through a computing module and providing computing resources for the applications; processing operating data from the power plant control system through a data processing module; storing the operating data based on its data type through a storage module; centrally managing and scheduling resources for the computing module, data processing module, and storage module through a KVM management module; and connecting the computing module, data processing module, and storage module through a switching module to form a high-speed network to ensure real-time data transmission and information synchronization among the computing module, data processing module, storage module, and KVM management module.

[0068] Furthermore, the logic instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes instructions for enabling a computer device (such as a personal computer, server, or network device) to perform all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, read-only memory 630 (ROM), random access memory 630 (RAM), a magnetic disk, or an optical disk.

[0069] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the common computing support method for a power plant control system provided in the above-mentioned embodiments, the method including: running an application in the power plant control system through a computing module and providing computing resources for the application; processing operating data from the power plant control system through a data processing module; storing operating data based on the data type of the operating data through a storage module; centrally managing and scheduling resources for the computing module, data processing module and storage module through a KVM management module; connecting the computing module, data processing module and storage module through a switching module to form a high-speed network to ensure real-time data transmission and information synchronization between the computing module, data processing module, storage module and KVM management module.

[0070] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by the processor 610, is implemented to execute the common computing support method for a power plant control system provided in the above-mentioned embodiments, the method comprising: running an application in the power plant control system through a computing module and providing computing resources for the application; processing operating data from the power plant control system through a data processing module; storing operating data based on the data type of the operating data through a storage module; centrally managing and scheduling resources for the computing module, the data processing module and the storage module through a KVM management module; and connecting the computing module, the data processing module and the storage module through a switching module to form a high-speed network to ensure real-time data transmission and information synchronization between the computing module, the data processing module, the storage module and the KVM management module.

[0071] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units. That is, they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0072] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods of each embodiment or certain portions of the embodiments.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A public computing support system for a power plant control system, characterized in that: include: A computing module, configured to run applications in the power plant control system and provide computing resources for the applications; a data processing module, in communication with the computing module, for processing operating data from the power station control system; a storage module, communicatively connected to the data processing module, and configured to store the operating data; A KVM management module is used to centrally manage and schedule resources for the computing module, the data processing module, and the storage module; The switching module is used to connect the computing module, the data processing module and the storage module to form a high-speed network to ensure real-time data transmission and information synchronization among the computing module, the data processing module, the storage module and the KVM management module.

2. The public computing support system for a power plant control system according to claim 1, characterized in that: The computing module includes multiple physical servers and virtual machine instances. The physical servers adopt a hot standby redundancy mode, and the virtual machine instances support dynamic migration and elastic expansion to adapt to the resource requirements of different computing tasks.

3. The public computing support system for a power plant control system according to claim 1, characterized in that: The data processing module realizes data processing based on a relational database and a distributed computing framework; The relational database is used to store structured historical operation data and supports transaction processing and concurrency control; The distributed computing framework is used to process unstructured data and large-scale real-time data streams to achieve data mining, model training and predictive analysis tasks; The data processing module is also used to support automatic scheduling of tasks and fault-tolerant recovery functions to ensure the continuity and accuracy of data processing.

4. The public computing support system for a power plant control system according to claim 1, characterized in that: The storage module is configured to analyze the operation data to determine a data type of the operation data; The storage module is further configured to determine a storage method for the operating data based on the data type; The storage module is also used to implement redundant backup functions and supports automatic switching between hot backup and cold backup of data. The hot backup is used to protect critical data in real time to ensure that data is not lost when the main storage fails; the cold backup is used to regularly back up system operation data.

5. The public computing support system for a power plant control system according to claim 4, characterized in that: The storage methods include: high-frequency storage, compressed storage, distributed storage and secure storage.

6. The public computing support system for a power plant control system according to claim 1, characterized in that: The switching module adopts a redundant ring network design, wherein the redundant ring network design supports automatic path switching to ensure that data transmission is not affected when any network node fails; The switching module also supports network partitioning and access control mechanisms to ensure the real-time and security of data transmission.

7. The public computing support system for a power plant control system according to claim 6, characterized in that: The switching module includes a plurality of switching units; the redundant ring network is formed by cascading all the switching units.

8. A public computing support method for a power plant control system, characterized in that: include: Run applications in the power plant control system through the computing module and provide computing resources for the applications; Processing the operating data from the power plant control system through a data processing module; storing the operating data based on the data type of the operating data by a storage module; Centrally manage and schedule resources for the computing module, the data processing module, and the storage module through the KVM management module; The computing module, the data processing module and the storage module are connected through a switching module to form a high-speed network to ensure real-time data transmission and information synchronization among the computing module, the data processing module, the storage module and the KVM management module.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the public computing support method for a power plant control system as claimed in claim 8 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the public computing support method for a power plant control system as claimed in claim 8 is implemented.

11. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the public computing support method for a power plant control system as claimed in claim 8 is implemented.

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