Intelligent monitoring method and system for improving self-healing reliable operation

Abstract

The invention relates to the technical field of distribution network OCS system self-healing, in particular to an intelligent monitoring method and system for improving self-healing reliable operation, and the method comprises the steps: selecting a target feeder group for self-healing; obtaining related information of the target feeder group; and judging whether the self-healing action is influenced or not according to the relevant information in combination with a preset rule. And processing according to a judgment result. The method has the beneficial effects that the checking efficiency of the self-healing signal of the power distribution network is remarkably improved through an automatic means, the original time-consuming and manual-dependent process is converted into a rapid and efficient automatic process, and meanwhile, an advanced signal identification and filtering mechanism is introduced, so that the influence of an interference signal on self-healing logic is effectively reduced, and the self-healing reliability of the power distribution network is improved. And the stability and the reliability of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of self-healing technology of distribution network OCS system, and in particular to an intelligent monitoring method and system for improving reliable operation of self-healing. Background Art

[0002] In the context of the rapid development of distribution networks, self-healing technology, as a key technology to improve the stability and reliability of power grids, has become increasingly important. However, with the rapid increase in the number of self-healing lines, existing technologies have exposed a series of significant shortcomings in self-healing signal troubleshooting, interference signal processing, automation tool support, and system scalability. Specifically, the efficiency of self-healing signal troubleshooting is low, and manual troubleshooting is particularly inefficient when facing large-scale lines and massive information points; self-healing logic is susceptible to interference from multiple signals, and existing technologies lack effective signal recognition and filtering mechanisms, making it difficult to accurately distinguish and eliminate interference signals, affecting the stability and reliability of the self-healing system; there is a lack of integrated automation tool support in the market, and automation professionals need to rely on multiple decentralized systems or tools during troubleshooting, which increases the complexity and difficulty of operations and reduces work efficiency; the existing system has obvious deficiencies in scalability and adaptability, making it difficult to quickly adapt to the access requirements of new lines and equipment, and lacks sufficient flexibility and configurability, which limits the further promotion and application of self-healing technology. Summary of the invention

[0003] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides an intelligent monitoring method and system for improving the reliable operation of self-healing, which can solve the problems mentioned in the background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides an intelligent monitoring method for improving reliable operation of self-healing, comprising selecting a target feeder group for self-healing;

[0008] Obtain relevant information of the target feeder group;

[0009] Determine whether the self-healing action will be affected based on relevant information and preset rules;

[0010] Take action based on the determination result.

[0011] As a preferred solution of the intelligent monitoring method for improving the reliable operation of self-healing of the present invention, wherein: the target feeder group selected for self-healing includes:

[0012] Each group of self-healing feeders has a corresponding self-healing feeder group ID, and the feeder is selected according to the ID.

[0013] As a preferred solution of the intelligent monitoring method for improving the self-healing reliable operation of the present invention, the acquisition of relevant information of the target feeder group includes:

[0014] Obtain the basic information and terminal information of the target feeder group.

[0015] As a preferred solution of the intelligent monitoring method for improving self-healing reliable operation of the present invention, the terminal information includes terminal basic information and terminal signal status information.

[0016] As a preferred solution of the intelligent monitoring method for improving the reliable operation of self-healing of the present invention, the processing according to the determination result includes:

[0017] If the result of the determination is yes, the terminal information is sorted and a report is generated.

[0018] If the result is no, the self-healing process is performed.

[0019] As a preferred solution of the intelligent monitoring method for improving self-healing reliable operation of the present invention, the basic information includes but is not limited to IP information, device name information, telemetry information and telesignaling information.

[0020] As a preferred solution of the intelligent monitoring method for improving self-healing reliable operation of the present invention, wherein: the basic information of the terminal includes but is not limited to the real-time status, signal strength and communication status of the terminal device;

[0021] The terminal signal status information includes but is not limited to the type, frequency and phase parameters of the signal.

[0022] In a second aspect, the present invention provides an intelligent monitoring system for improving the reliable operation of self-healing, including: a selection module for selecting a target feeder group for self-healing;

[0023] An acquisition model is used to acquire relevant information of a target feeder group;

[0024] A determination module, used to determine whether the self-healing action will be affected based on relevant information and preset rules;

[0025] The processing module is used to perform processing according to the determination result.

[0026] In a third aspect, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0027] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above method when the computer program is executed by a processor.

[0028] Compared with the prior art, the beneficial effects of the present invention are as follows: the efficiency of troubleshooting self-healing signals of the distribution network is significantly improved through automation means, and the original time-consuming and manually dependent process is transformed into a fast and efficient automated process. At the same time, advanced signal recognition and filtering mechanisms are introduced, which effectively reduces the impact of interference signals on the self-healing logic and improves the stability and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0030] Figure 1 Flow chart of intelligent monitoring method to improve self-healing reliable operation Figure 1 .

[0031] Figure 2 Flow chart of intelligent monitoring method to improve self-healing reliable operation Figure 2 .

[0032] Figure 3 A schematic diagram of the internal structure of a computer device. DETAILED DESCRIPTION

[0033] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0034] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0035] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0036] Example 1

[0037] Reference Figure 1-2 , which is the first embodiment of the present invention, provides an intelligent monitoring method for improving self-healing reliable operation, which includes:

[0038] S1. Select a target feeder group for self-healing.

[0039] Furthermore, the target feeder group selected for self-healing includes:

[0040] Each group of self-healing feeders has a corresponding self-healing feeder group ID, and the feeder is selected according to the ID.

[0041] It should be noted that the system selects the feeder group that needs to be self-healed as the operation object according to the corresponding self-healing feeder group ID, and this step is the basis of the self-healing process.

[0042] S2. Obtain relevant information of the target feeder group.

[0043] Further, the relevant information of the target feeder group is obtained including:

[0044] Obtain the basic information and terminal information of the target feeder group.

[0045] Furthermore, the terminal information includes terminal basic information and terminal signal status information.

[0046] Furthermore, basic information includes but is not limited to IP information, device name information, telemetry information and telesignaling information, among which telemetry information includes but is not limited to power side line phase voltage Uab [YC4], load side line phase voltage Uab [YC8], and telesignaling information includes but is not limited to spring no energy storage [YX1], switch handle remote [YX2]), switch lock total [YX16], Y time limit lock [YX20], X time limit lock [YX21], post-closing fault lock [YX22], continuous opening lock [YX26], three-stage overcurrent protection working mode [YX27], segmented working mode [YX29], terminal fault alarm [YX32], battery undervoltage [YX34], automation function soft pressure plate [YX41], automation function hard pressure plate [YX42], opening hard pressure plate [YX43], closing hard pressure plate [YX44].

[0047] It should be noted that by using the unique codes of the devices at both ends of the device connected to the switch, search for distribution automation switch equipment downstream along the feeder starting from the switch in the station, obtain the IP information and device name information of the distribution automation terminal, obtain the telemetry information and telesignaling information in the real-time database, and obtain the corresponding real-time values ​​respectively, and read the self-healing line self-healing input type [differential type, voltage type]. This information is an important basis for subsequent judgment.

[0048] Furthermore, the basic terminal information includes, but is not limited to, the real-time status, signal strength, and communication status of the terminal device;

[0049] The terminal signal status information includes but is not limited to the type, frequency and phase parameters of the signal.

[0050] It should be noted that these parameters will be used to determine whether the signal status will affect the self-healing action. Specifically, if [YC4][YC8] is abnormal, the distribution terminal on the self-healing feeder group cannot operate correctly, resulting in the failure of the self-healing action; if [YX1][YX2][YX34] is abnormal, the remote control will fail when the self-healing action automatically transfers power, resulting in the failure of the self-healing action; if [YX16][YX20][YX21][YX22][YX26] is abnormal, the self-healing will not be able to locate the faulty section, resulting in the failure of self-healing; if [YX27][YX29] is abnormal, the terminal cannot operate correctly, resulting in the failure of self-healing to locate the faulty section, resulting in the failure of self-healing; if [YX41][YX42][YX43][YX44] is abnormal, the terminal cannot be correctly separated or combined, resulting in the failure of self-healing.

[0051] S3. Determine whether the self-healing action will be affected based on the relevant information and preset rules.

[0052] It should be noted that the system determines whether the current signal status will affect the self-healing action based on the signal status information it reads and the preset rules. The specific rules are as follows:

[0053] (1) Differential type

[0054] If Uab>0 and YX1=0 and YX2=1 and YX27=1 and YX29=0 and YX32=0 and YX34=0 and YX41=1 and YX42=1 and YX43=1 and YX44=1, the terminal is normal; otherwise, the terminal is abnormal and outputs abnormal information.

[0055] (2) Voltage type

[0056] If YC4>0 and YC8>0 and YX1=0 and YX2=1 and YX16=0 and YX20=0 and YX21=0 and YX22=0 and YX26=0 and YX27=1 and YX29=1 and YX32=0 and YX34=0 and YX41=1 and YX42=1 and YX43=1 and YX44=1, the terminal is normal; otherwise, the terminal is abnormal and outputs abnormal information.

[0057] It should be noted that, except for YC4\YC8, the other signals have two states, 0 or 1, 0 means reset, 1 means initiate. Only when these signal states meet the above rules are they considered normal, otherwise they are abnormal.

[0058] S4. Perform processing according to the determination result.

[0059] Further, processing according to the determination result includes:

[0060] If the result of the determination is yes, the terminal information is sorted and a report is generated.

[0061] If the result of the determination is no, a self-healing process or other processing is performed.

[0062] It should be noted that the system will organize and record terminal information including but not limited to fault information and device status changes, and generate detailed reports that can be used for subsequent analysis, troubleshooting and performance evaluation.

[0063] In summary, the beneficial effect of the intelligent monitoring method for improving the reliable operation of self-healing in the present invention is that it significantly improves the efficiency of troubleshooting self-healing signals in the distribution network through automated means, transforming the original time-consuming and manually dependent process into a fast and efficient automated process, while introducing advanced signal recognition and filtering mechanisms, effectively reducing the impact of interference signals on the self-healing logic, and improving the stability and reliability of the system.

[0064] Example 2

[0065] This embodiment provides an intelligent monitoring system for improving the reliable operation of self-healing, which includes a selection module for selecting a target feeder group for self-healing;

[0066] An acquisition model is used to acquire relevant information of a target feeder group;

[0067] A determination module, used to determine whether the self-healing action will be affected based on relevant information and preset rules;

[0068] The processing module is used to perform processing according to the determination result.

[0069] The above-mentioned unit modules may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above-mentioned modules.

[0070] Example 3

[0071] This embodiment provides a computer device, which may be a terminal, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, an intelligent monitoring method for improving the reliable operation of self-healing is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse.

[0072] This embodiment also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it is implemented to: select a target feeder group for self-healing; obtain relevant information of the target feeder group; determine whether the self-healing action will be affected according to the relevant information combined with preset rules, and process according to the determination result.

[0073] 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 preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An intelligent monitoring method for improving self-healing reliable operation, characterized by: include, Select a target feeder group for self-healing; Acquire relevant information of the target feeder group; Determine whether the self-healing action will be affected based on the relevant information and preset rules; Take action based on the determination result.

2. The intelligent monitoring method for improving self-healing reliable operation according to claim 1, characterized in that: The target feeder group selected for self-healing includes: Each group of self-healing feeders has a corresponding self-healing feeder group ID, and the feeder is selected according to the ID.

3. The intelligent monitoring method for improving self-healing reliable operation according to claim 2, characterized in that: The obtaining of the relevant information of the target feeder group includes: Obtain basic information and terminal information of the target feeder group.

4. The intelligent monitoring method for improving self-healing reliable operation according to claim 3, characterized in that: The terminal information includes terminal basic information and terminal signal status information.

5. The intelligent monitoring method for improving self-healing reliable operation according to claim 4, characterized in that: The processing according to the determination result includes: If the result of the determination is yes, the terminal information is sorted and a report is generated. If the result is no, the self-healing process is performed.

6. The intelligent monitoring method for improving self-healing reliable operation according to claim 5, characterized in that: The basic information includes but is not limited to IP information, device name information, telemetry information and telesignaling information.

7. The intelligent monitoring method for improving self-healing reliable operation according to claim 6, characterized in that: The terminal basic information includes but is not limited to the real-time status, signal strength and communication status of the terminal device; The terminal signal status information includes but is not limited to the type, frequency and phase parameters of the signal.

8. An intelligent monitoring system for improving self-healing reliable operation, characterized in that: include: A selection module, used for selecting a target feeder group for self-healing; An acquisition model is used to acquire relevant information of the target feeder group; A determination module, used to determine whether the self-healing action will be affected based on the relevant information combined with preset rules; The processing module is used to perform processing according to the determination result.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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