Power grid cloud edge data interaction method

Abstract

The invention provides a power grid cloud edge data interaction method. The method comprises the following steps: acquiring power grid line operation state monitoring data and network equipment configuration parameter data; determining line load data, data transmission delay data and error rate data based on the operation state monitoring data and the network equipment configuration parameter data; in response to determining that the line load data exceeds the first preset threshold value, determining that the line fault is overload; in response to determining that the line transmission data exceeds a second preset threshold value, determining that a line fault is data transmission delay; in response to determining that the bit error rate data exceeds a third preset threshold value, determining that the line fault is an error code; and obtaining a power grid line transmission demand, and switching a standby cloud side transmission path corresponding to the line fault type to carry out data transmission based on the power grid line transmission demand and the line fault type. The data transmitted by using the interaction method is stable, efficient and safe, and the transmission efficiency is high.

Description

Technical Field

[0001] This application relates to the technical field of data interaction, and more particularly to a power grid cloud-edge data interaction method. Background Technology

[0002] The power grid has a wide coverage area, but communication infrastructure in some remote areas, such as mountainous regions and rural areas, is weak. Unstable network signals in these areas can easily lead to data transmission interruptions or delays between cloud and edge computing devices. Furthermore, the power grid environment is subject to significant electromagnetic interference, which can affect wireless communication, reduce communication quality, and cause data errors, thus impacting normal communication between edge computing nodes and the cloud. With the continuous improvement of power grid intelligence, the demand for data transmission from various monitoring and control services is exploding. However, the communication infrastructure in remote areas was designed with relatively limited capacity and bandwidth resources, making it difficult to adapt to the rapidly increasing volume of business data. These factors significantly hinder the effective implementation and stable operation of intelligent power grid applications in remote areas. Summary of the Invention

[0003] In view of this, the purpose of this application is to propose a power grid cloud-edge data interaction method to solve the problems of unstable data transmission, bit error rate, and limited carrying capacity between the power grid and cloud-edge and edge computing devices in remote areas.

[0004] To achieve the above objectives, this application provides a power grid cloud-edge data interaction method, comprising:

[0005] Acquire power grid line operation status monitoring data and network equipment configuration parameter data;

[0006] Based on the operational status monitoring data and the network device configuration parameter data, determine the line load data, data transmission delay data, and bit error rate data;

[0007] In response to determining that the line load data exceeds a first preset threshold, the line fault is determined to be an overload;

[0008] In response to determining that the data transmitted on the line exceeds a second preset threshold, the line fault is determined to be a data transmission delay;

[0009] In response to determining that the bit error rate data exceeds a third preset threshold, the line fault is determined to be a bit error;

[0010] The system acquires the power grid line transmission requirements and, based on these requirements and the line fault type, switches to the backup cloud-edge transmission path corresponding to the line fault type for data transmission.

[0011] Optionally, the step of obtaining the power grid line transmission demand and, based on the power grid line transmission demand and the line fault type, switching to the backup cloud-edge transmission path corresponding to the line fault type for data transmission includes:

[0012] In response to the determination of a line failure, the backup cloud-edge transmission path corresponding to the line failure is switched for data transmission;

[0013] In response to the determination of multiple line faults, the backup cloud-edge transmission path corresponding to the line fault is switched for data transmission based on the power grid line transmission requirements.

[0014] Optionally, in response to determining that multiple line faults have occurred, the step of switching to a backup cloud-edge transmission path corresponding to the line fault for data transmission, based on the power grid line transmission requirements, includes:

[0015] In response to determining that multiple line faults have occurred, the system determines whether the power grid line transmission demand is related to each line fault.

[0016] In response to determining that the power grid line transmission demand is associated with a line fault, the backup cloud-edge transmission path corresponding to the line fault is switched first for data transmission.

[0017] Optionally, the step of responding to the determination of multiple line faults by switching to the backup cloud-edge transmission path corresponding to the line fault for data transmission, based on the power grid line transmission demand, further includes:

[0018] In response to determining that no line fault is associated with the transmission demand of the power grid line, it is then determined whether an overload fault exists on the line;

[0019] In response to the determination that an overload fault exists on the line, the backup cloud-edge transmission path corresponding to the overload fault is switched for data transmission.

[0020] Optionally, the operating status monitoring data includes current, voltage, received data information, and transmitted data information, and the network device configuration parameter data includes the rated transmission power of the line.

[0021] Optionally, determining the line load data, data transmission delay data, and bit error rate data based on the operational status monitoring data and the network device configuration parameter data includes:

[0022] Based on the current and voltage data in the operational status monitoring data, the line transmission power per unit time is determined.

[0023] The line load data is determined based on the rated transmission power of the line in the network device configuration parameter data.

[0024] Optionally, determining the line load data, data transmission delay data, and bit error rate data based on the operational status monitoring data and the network device configuration parameter data includes:

[0025] Obtain the data transmission timestamp and the data reception timestamp from the operation status monitoring data;

[0026] The data transmission delay data is determined based on the data transmission timestamp and the data reception timestamp.

[0027] Based on the same inventive concept, this disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor implements the method described above when executing the computer program.

[0028] Based on the same inventive concept, this disclosure also provides a non-transitory computer-readable storage medium that stores computer instructions for causing a computer to perform the method described above.

[0029] As described above, the power grid cloud-edge data interaction method provided in this application determines line load data, data transmission delay data, and bit error rate data by acquiring power grid line operation status monitoring data and network device configuration parameter data. Based on this data, it identifies the line fault type and initiates a switching mechanism for backup cloud-edge transmission paths according to the fault type. This ensures that data transmission between cloud-edge computing devices and edge computing devices in remote power grids is not affected by faulty lines, thus maintaining normal data transmission. Furthermore, this solution dynamically invokes backup cloud-edge transmission paths based on both fault type and power grid transmission needs. This dynamic invocation mechanism can flexibly adapt to different power grid transmission requirements, ensuring efficient and reliable power grid data transmission, thereby providing strong support for the intelligent operation of the power grid. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a flowchart illustrating a power grid cloud-edge data interaction method according to an embodiment of this application;

[0032] Figure 2 This is a schematic diagram showing the hardware structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with specific embodiments and the accompanying drawings.

[0034] It should be noted that, unless otherwise defined, the technical or scientific terms used in the embodiments of this application should have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms "first," "second," and similar terms used in the embodiments of this application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are only used to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0035] As mentioned in the background, while the coverage of power grids in modern power systems continues to expand, communication infrastructure development lags behind in some remote areas, such as mountainous regions and rural areas. These areas have complex terrains, with natural barriers like mountains and dense forests severely hindering signal transmission and resulting in highly unstable network signals. This leads to frequent interruptions or excessively high latency in data transmission between cloud and edge computing devices, seriously affecting the real-time performance and reliability of power grid data and hindering the advancement of intelligent power grid management in these regions.

[0036] Meanwhile, the power grid operating environment itself is subject to significant electromagnetic interference, becoming another major obstacle to communication quality. Both high-voltage equipment in substations and electromagnetic fields generated by transmission lines can interfere with wireless communication. Under such interference, communication signals experience attenuation and distortion, and data transmission frequently encounters bit errors, severely hindering normal communication between edge computing nodes and the cloud, making real-time status feedback and precise control of power grid equipment difficult to achieve.

[0037] With the continuous improvement of power grid intelligence, the demand for data transmission from various monitoring and control services is experiencing explosive growth. From the status monitoring of power grid equipment to the accurate prediction of power load, massive amounts of data need to be transmitted to the cloud for analysis and processing in a timely and stable manner. However, due to limitations in technology and funding, the communication infrastructure in remote areas was designed with relatively limited capacity and bandwidth resources, making it difficult to meet the current rapidly growing demand for business data. During peak electricity consumption periods or concentrated monitoring periods of power grid equipment, communication links are easily overloaded, resulting in a significant reduction in data transmission speed and even data loss or transmission failure. This not only exacerbates the instability of data transmission but also makes it difficult for intelligent power grid applications to be effectively implemented and operate stably in remote areas, failing to fully realize their role in improving power grid operating efficiency and ensuring power supply reliability.

[0038] As can be seen from the above, the quality of power grid communication in remote areas exhibits a multi-dimensional deterioration. First, the unstable network signals caused by terrain directly lead to the loss of real-time data transmission. Frequent transmission interruptions or extremely high latency occur between cloud-edge and edge computing devices, preventing timely synchronization of critical monitoring data and rendering the real-time power grid monitoring system ineffective in these areas. Second, electromagnetic interference causes signal distortion and a surge in bit error rate, compromising the accuracy of data transmission. Deviations in equipment status feedback may lead to misinterpretations of cloud control commands, affecting the safety and reliability of power grid dispatching. Third, the contradiction between the explosive growth of business data volume and the carrying capacity of communication infrastructure results in frequent overload and congestion of communication links, a significant decrease in data transmission efficiency, and even packet loss, further exacerbating communication instability. These three factors combine to create a vicious cycle of "high transmission latency, numerous data errors, and easy link interruptions" in the communication quality of power grids in remote areas, severely restricting the implementation of intelligent power grid applications and failing to meet the basic requirements of modern power systems for "real-time, accurate, and stable" communication networks.

[0039] The following is in conjunction with the appendix Figure 1-2 The embodiments of this application will be described in detail below.

[0040] A power grid cloud-edge data interaction method includes:

[0041] S100: Acquire power grid line operation status monitoring data and network equipment configuration parameter data;

[0042] Specifically, operational status monitoring data is mainly used to reflect the operating status of power grid lines and equipment, including electrical parameters and line operation data. Among them, electrical parameter data includes line current, voltage, power, power factor, etc., which can intuitively reflect the power transmission status of the power grid; line operation data is used to measure the data transmission status, which can be obtained by deploying network traffic monitoring tools on edge computing devices or network nodes. These tools can count the amount of data received and sent by the devices in real time, data rate, etc., to help determine whether there are any abnormalities in data transmission.

[0043] Network device configuration parameters are the parameters set for related equipment in a communication network, and are crucial for ensuring the stability and efficiency of data transmission. Among these, the rated transmission power of a line is a key network device configuration parameter. It specifies the maximum power a line can transmit under safe and stable operating conditions and is typically recorded in the power grid line design documents or equipment parameter configuration files. By interfacing with the power grid asset information management system, the rated transmission power data of the line can be obtained for subsequent line load assessment and fault diagnosis. In the power grid communication architecture, the network management system is generally deployed in the cloud for centralized management and acquisition of configuration parameter data for all network devices. Lightweight agent programs also run on edge computing devices to interact with the cloud management system and upload configuration information of local network devices.

[0044] S200: Based on the operational status monitoring data and the network device configuration parameter data, determine the line load data, data transmission delay data, and bit error rate data;

[0045] Specifically, line load data is the ratio of the actual data flow carried by a power grid line during operation to its rated carrying capacity, used to assess the load level of the power grid line. Data transmission delay data is the time required for data to be transmitted from the sending end (such as an edge computing device) to the receiving end (such as a cloud platform), usually measured in milliseconds (ms), used to assess the real-time performance of the communication link. Bit error rate (BER) data refers to the ratio of the number of erroneous bits during data transmission to the total number of bits transmitted, usually expressed in scientific notation, for example, a BER of one in a million is 10^ ... - 6. Used to measure the reliability of communication links.

[0046] S300: In response to determining that the line load data exceeds a first preset threshold, determine that the line fault is an overload;

[0047] S400: In response to determining that the data transmitted on the line exceeds a second preset threshold, determine that the line fault is a data transmission delay;

[0048] S500: In response to determining that the bit error rate data exceeds a third preset threshold, determine that the line fault is a bit error;

[0049] S600: Obtain the power grid line transmission requirements, and based on the power grid line transmission requirements and the line fault type, switch to the backup cloud-edge transmission path corresponding to the line fault type for data transmission.

[0050] Specifically, the three types of line faults mentioned above can occur simultaneously on a single power grid line or on different power grid lines. When a power grid line experiences an overload fault, the data transmission is switched to the backup cloud-edge transmission path corresponding to the overload fault. This backup cloud-edge transmission path is a line with a lower load and sufficient transmission capacity. For example, in a power grid communication network, there are multiple parallel fiber optic transmission lines. When a line responsible for real-time monitoring data transmission becomes overloaded due to a large influx of data, it can be switched to a backup fiber optic line of the same type that is currently mainly used for non-real-time data transmission and has a lighter load, ensuring that data transmission can continue stably. When a power grid line experiences a data transmission delay fault, the data transmission is switched to the backup cloud-edge transmission path corresponding to the data transmission delay fault. This cloud-edge transmission path is a backup line with low latency characteristics. This line has an independent frequency band and less interference, enabling fast data transmission and meeting the strict real-time requirements of dispatch commands. When a power grid line experiences a bit error fault, the data transmission is switched to the backup cloud-edge transmission path corresponding to the bit error fault. This backup cloud-edge transmission path has strong anti-interference capabilities and data error correction capabilities, improving the accuracy and integrity of the data.

[0051] In addition, power grid transmission requirements include: real-time power grid monitoring data and dispatch instructions, which have extremely high requirements for transmission latency; power metering data and equipment status monitoring data, which have stringent requirements for transmission accuracy; distributed power source control signals and wide-area measurement system data, which have extremely high requirements for transmission stability; and equipment inspection images and power grid simulation analysis, which have high requirements for transmission bandwidth. When a line fault occurs, alternative cloud-edge transmission paths should also be considered to meet different power grid transmission needs.

[0052] In this embodiment, by acquiring power grid line operation status monitoring data and network device configuration parameter data, line load data, data transmission delay data, and bit error rate data are determined. Based on this data, the fault type of the line is identified, and a switching mechanism for backup cloud-edge transmission paths is initiated according to the fault type. This ensures that data transmission between cloud-edge computing devices and edge computing devices in remote power grids is not affected by the faulty line, thereby maintaining normal data transmission. Furthermore, this solution dynamically calls backup cloud-edge transmission paths based on both fault type and power grid transmission needs. This dynamic calling mechanism can flexibly adapt to different power grid transmission requirements, ensuring efficient and reliable power grid data transmission, thus providing strong support for the intelligent operation of the power grid.

[0053] In some embodiments, in S600, obtaining the power grid line transmission demand and, based on the power grid line transmission demand and the line fault type, switching to the backup cloud-edge transmission path corresponding to the line fault type for data transmission includes:

[0054] S601: In response to determining that a line fault has occurred, switch to the backup cloud-edge transmission path corresponding to the line fault for data transmission;

[0055] S602: In response to the determination that multiple line faults have occurred, the backup cloud-edge transmission path corresponding to the line fault is switched for data transmission based on the power grid line transmission requirements.

[0056] Additionally, in S602, the step of responding to the determination of multiple line faults by switching to the backup cloud-edge transmission path corresponding to the line fault for data transmission, based on the power grid line transmission requirements, includes:

[0057] S602a: In response to determining that multiple line faults have occurred, it is determined whether the power grid line transmission demand is related to each line fault;

[0058] S602b: In response to determining that the power grid line transmission demand is associated with a line fault, the backup cloud-edge transmission path corresponding to the line fault is switched first for data transmission.

[0059] Specifically, when only one line fails, the data transmission is switched to the backup cloud-edge transmission path corresponding to that line failure, without considering the power grid line's transmission requirements. When multiple power grid lines experience simultaneous failures, the priority of handling these failures must be allocated based on the power grid line's transmission needs. For example, when a real-time power grid monitoring line experiences both excessive transmission delay and line overload, the low-latency backup cloud-edge transmission path is prioritized to avoid misjudgments or omissions due to delays, ensuring timely and accurate data transmission, given the extremely high latency requirements of real-time monitoring data. Similarly, when the power grid is transmitting electricity metering data and a line experiences both excessive error rate and transmission delay, the backup cloud-edge transmission path associated with the error rate failure is prioritized to reduce the error rate to 10%, as electricity metering data directly affects electricity billing and has stringent accuracy requirements. Any error could lead to metering errors and economic disputes. -7 For electricity at levels below the designated level, ensure zero-error transmission of metering data to guarantee the fairness and accuracy of electricity billing.

[0060] In this embodiment, different processing methods are set for single-fault and multi-fault scenarios, achieving efficient fault handling: in the case of a single fault, the corresponding backup path is directly switched to quickly restore data transmission; in the case of multiple faults, faults related to power grid transmission needs are prioritized based on "demand-fault" correlation analysis, avoiding core business interruptions caused by incorrect processing order, thereby improving the overall reliability, fault handling accuracy and resource utilization efficiency of the power grid communication network.

[0061] In some embodiments, in S602, the step of switching the backup cloud-edge transmission path corresponding to the line fault for data transmission in response to determining that multiple line faults have occurred, based on the power grid line transmission demand, further includes:

[0062] S602c: In response to determining that no line fault is associated with the transmission demand of the power grid line, determine whether there is an overload fault in the line;

[0063] S602d: In response to determining that there is an overload fault on the line, the backup cloud-edge transmission path corresponding to the overload fault is switched for data transmission.

[0064] Furthermore, in S602, the step of responding to determining that multiple line faults have occurred, and then switching to the backup cloud-edge transmission path corresponding to the line fault for data transmission based on the power grid line transmission requirements, further includes:

[0065] S602e: In response to determining that there is no overload fault on the line, the backup cloud-edge transmission path corresponding to the transmission delay fault and the bit error fault is switched in turn to transmit data.

[0066] In this embodiment, line faults are handled according to the following priority: overload faults, transmission delay faults, and bit error faults. This is mainly because line overloads can cause a sharp increase in equipment temperature, accelerate insulation aging, and even lead to line fires or tripping, causing regional communication outages. For example, if an overloaded 500kV transmission line causes equipment burnout, resulting in a two-hour interruption of monitoring data for three surrounding substations, prioritizing overload faults can prevent cascading effects and ensure the physical integrity of the power grid communication network. Power grid dispatch commands (such as AGC automatic generation control) require millisecond-level responses. Delays exceeding 100ms will cause mismatches between control commands and power grid status, potentially leading to frequency fluctuations or even system collapse. Therefore, prioritizing delay faults ensures the effectiveness of the real-time control system. Bit errors can cause deviations in energy metering data (e.g., a bit error rate of 10⁻³ can cause a settlement error of more than 0.1%) or distort equipment status monitoring data (e.g., misjudgment of circuit breaker mechanical characteristics). Although these affect accuracy, they usually do not immediately endanger the safety of power grid operation. The aforementioned priority ranking essentially addresses risks that could trigger systemic collapse upfront, following a progressive principle of "preserving life → controlling the situation → correcting deviations," ensuring the safe and stable operation of the power grid to the greatest extent possible with limited backup resources.

[0067] In some embodiments, the operating status monitoring data includes current, voltage, received data information, and transmitted data information, and the network device configuration parameter data includes the rated transmission power of the line.

[0068] Additionally, in S200, determining line load data, data transmission delay data, and bit error rate data based on the operational status monitoring data and the network device configuration parameter data includes:

[0069] S201: Based on the current and voltage data in the operation status monitoring data, determine the line transmission power per unit time;

[0070] S202: Determine the line load data based on the rated transmission power of the line in the network device configuration parameter data.

[0071] Also includes:

[0072] S203: Obtain the data transmission timestamp and the data reception timestamp from the operation status monitoring data;

[0073] S204: Determine the data transmission delay data based on the data transmission timestamp and the data reception timestamp.

[0074] Also includes:

[0075] S205: Obtain the total number of bits of transmitted data and the total number of bits of received data from the operation status monitoring data;

[0076] S206: Determine the bit error rate data based on the total number of bits of transmitted data and the total number of bits of received data.

[0077] Specifically, based on the current and voltage data from the operational status monitoring data, the transmission power of the line per unit time is obtained as P1, the rated transmission power from the network device configuration parameter data is P2, and the line load data is Load, expressed using the formula: Load = P1 / P2 × 100%. The data transmission timestamp T1 and data reception timestamp T2 are obtained from the operational status monitoring data. The data transmission delay can be represented by ΔT, expressed using the formula: ΔT = T2 - T1. The number of erroneous bits N1 and the total number of received data bits N2 are obtained from the operational status monitoring data. The bit error rate (BER) can be calculated using the formula: BER = N1 / N2.

[0078] Additionally, in response to determining that the line load data exceeds a first preset threshold, a line fault is determined to be an overload; for example, the first preset threshold is 85%. In response to determining that the line transmission data exceeds a second preset threshold, a line fault is determined to be a data transmission delay; for example, the second preset threshold is 100ms. In response to determining that the bit error rate data exceeds a third preset threshold, a line fault is determined to be a bit error; for example, the third preset threshold is 1×10⁻⁶. -6 The aforementioned preset thresholds are not fixed and can be flexibly adjusted according to different control networks and network requirements.

[0079] In this embodiment, the line transmission power is calculated using current and voltage data, and compared with the rated transmission power to determine the load, enabling timely detection of line overload risks. Data transmission delay is calculated based on transmission and reception timestamps to assess the network's real-time response performance. The bit error rate is determined by the total number of bits transmitted and received, effectively detecting the accuracy of data transmission. This embodiment, through the combination of multi-faceted data monitoring and analysis, helps to comprehensively understand the network's operating status, providing strong data support for network optimization, fault early warning, and maintenance.

[0080] It should be noted that the method in this embodiment can be executed by a single device, such as a computer or server. The method can also be applied in a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method in this embodiment, and the multiple devices will interact with each other to complete the method described.

[0081] It should be noted that the above description describes some embodiments of this application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0082] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the cloud-edge data interaction method described in any of the above embodiments.

[0083] Figure 2 This embodiment illustrates a more specific hardware structure of an electronic device, which may include a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, memory 1020, input / output interface 1030, and communication interface 1040 are interconnected internally via the bus 1050.

[0084] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0085] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0086] The input / output interface 1030 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components within the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices may include displays, speakers, vibrators, indicator lights, etc.

[0087] The communication interface 1040 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0088] Bus 1050 includes a pathway for transmitting information between various components of the device, such as processor 1010, memory 1020, input / output interface 1030, and communication interface 1040.

[0089] It should be noted that although the above-described device only shows the processor 1010, memory 1020, input / output interface 1030, communication interface 1040, and bus 1050, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0090] The electronic devices described above are used to implement the corresponding cloud-edge data interaction methods in any of the foregoing embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0091] Based on the same inventive concept, corresponding to the methods of any of the above embodiments, this application also provides a non-transitory computer-readable storage medium that stores computer instructions for causing the computer to execute the cloud-edge data interaction method as described in any of the above embodiments.

[0092] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0093] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the cloud-edge data interaction method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0094] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this application is limited to these examples; under the concept of this application, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the embodiments of this application as described above, which are not provided in detail for the sake of brevity.

[0095] Additionally, to simplify the description and discussion, and to avoid obscuring the embodiments of this application, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Furthermore, the apparatus may be shown in block diagram form to avoid obscuring the embodiments of this application, and this also takes into account the fact that the details of the implementation of these block diagram apparatuses are highly dependent on the platform on which the embodiments of this application will be implemented (i.e., these details should be fully understood by those skilled in the art). While specific details (e.g., circuits) have been set forth to describe exemplary embodiments of this application, it will be apparent to those skilled in the art that the embodiments of this application can be implemented without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0096] Although this application has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0097] The embodiments of this application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the claims of this application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the embodiments of this application should be included within the protection scope of this application.

Claims

1. A method for data interaction between power grid cloud and edge, characterized in that, include: Acquire power grid line operation status monitoring data and network equipment configuration parameter data; Based on the operational status monitoring data and the network device configuration parameter data, determine the line load data, data transmission delay data, and bit error rate data; In response to determining that the line load data exceeds a first preset threshold, the line fault is determined to be an overload; In response to determining that the data transmitted on the line exceeds a second preset threshold, the line fault is determined to be a data transmission delay; In response to determining that the bit error rate data exceeds a third preset threshold, the line fault is determined to be a bit error; The system acquires the power grid line transmission requirements and, based on these requirements and the line fault type, switches to the backup cloud-edge transmission path corresponding to the line fault type for data transmission.

2. The power grid cloud-edge data interaction method according to claim 1, characterized in that, The step of acquiring the power grid line transmission requirements and, based on the power grid line transmission requirements and line fault types, switching to the backup cloud-edge transmission path corresponding to the line fault type for data transmission includes: In response to the determination of a line failure, the backup cloud-edge transmission path corresponding to the line failure is switched for data transmission; In response to the determination of multiple line faults, the backup cloud-edge transmission path corresponding to the line fault is switched for data transmission based on the power grid line transmission requirements.

3. The power grid cloud-edge data interaction method according to claim 2, characterized in that, In response to the determination of multiple line faults, the method involves switching to a backup cloud-edge transmission path corresponding to the line fault for data transmission, based on the power grid line transmission requirements. This includes: In response to determining that multiple line faults have occurred, the system determines whether the power grid line transmission demand is related to each line fault. In response to determining that the power grid line transmission demand is associated with a line fault, the backup cloud-edge transmission path corresponding to the line fault is switched first for data transmission.

4. The power grid cloud-edge data interaction method according to claim 3, characterized in that, The step of responding to the determination of multiple line faults by switching to the backup cloud-edge transmission path corresponding to the line fault for data transmission, based on the power grid line transmission demand, further includes: In response to determining that no line fault is associated with the transmission demand of the power grid line, it is then determined whether an overload fault exists on the line; In response to the determination that an overload fault exists on the line, the backup cloud-edge transmission path corresponding to the overload fault is switched for data transmission.

5. The power grid cloud-edge data interaction method according to claim 1, characterized in that, The operational status monitoring data includes current, voltage, received data information, and transmitted data information, while the network device configuration parameter data includes the rated transmission power of the line.

6. The power grid cloud-edge data interaction method according to claim 5, characterized in that, The determination of line load data, data transmission delay data, and bit error rate data based on the operational status monitoring data and the network device configuration parameter data includes: Based on the current and voltage data in the operational status monitoring data, the line transmission power per unit time is determined. The line load data is determined based on the rated transmission power of the line in the network device configuration parameter data.

7. The power grid cloud-edge data interaction method according to claim 5, characterized in that, The determination of line load data, data transmission delay data, and bit error rate data based on the operational status monitoring data and the network device configuration parameter data includes: Obtain the data transmission timestamp and the data reception timestamp from the operation status monitoring data; The data transmission delay data is determined based on the data transmission timestamp and the data reception timestamp.

8. A power grid cloud-edge data interaction method according to claim 5, characterized in that, The determination of line load data, data transmission delay data, and bit error rate data based on the operational status monitoring data and the network device configuration parameter data includes: Obtain the total number of bits of transmitted data and the total number of bits of received data from the operation status monitoring data; The bit error rate data is determined based on the total number of bits of data sent and the total number of bits of data received.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 8.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1 to 8.

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