CN117748745B - A method and system for optimizing and enhancing the reliability of a distribution network - Google Patents

Abstract

The present invention belongs to the technical field of data transmission, and specifically relates to a method and system for optimizing and enhancing the reliability of a power distribution network, wherein the method includes respectively setting different data acquisition modules on different power distribution equipment, for collecting monitoring data of the power distribution equipment, storing main characteristic values, first characteristic values up to the Nth characteristic value, and first password values up to the Nth password value respectively corresponding to the first characteristic value up to the Nth characteristic value; each data acquisition module encrypts and transmits the collected monitoring data to the first data acquisition module through several other data acquisition modules, and the first data acquisition module sends the monitoring data to a remote server module; the remote server module uses a machine learning algorithm to analyze and process the monitoring data to obtain an analysis result, and in the case of an abnormality in the analysis result, promptly pushes a reminder message to a relevant contact person. The present invention can enhance the reliability of the power distribution network.

Description

A method and system for optimizing and enhancing the reliability of a distribution network

Technical Field

The present invention belongs to the technical field of data transmission, and in particular relates to a method and system for optimizing and enhancing the reliability of a distribution network.

Background technique

A distribution network refers to an electric power grid that receives electrical energy from a transmission network or a regional power plant and distributes it locally or step by step according to voltage to various types of users through different distribution equipment. With the continuous development of computer application technology, there are more and more methods that monitor the operating data of distribution equipment, predict the probability of failure of distribution equipment, and take timely response measures to enhance the reliability of distribution networks by reducing the duration of power outages caused by failures of distribution equipment.

Similar to the prior art is an invention with publication number CN110572261A, which relates to a data encryption transmission method, the method comprising: S1, a data sending end generates a first part of the data key, and sends the first part of the data key to a data receiving end; S2, a data receiving end generates a second part of the data key, and sends the second part of the data key to the data sending end; S3, an encryption key and a decryption key are generated from the first part of the data key and the second part of the data key; S4, the data sending end uses the encryption key to encrypt the data to be transmitted, and sends the generated encrypted data to the data receiving end; S5, the data receiving end uses the decryption key to decrypt the received encrypted data to obtain the data to be transmitted, but the key used in the invention is not dynamically updated and is not secure enough. Similar to the prior art, there is an invention with publication number CN110943832B, which relates to a data encryption transmission method, which specifically generates a master key, and obtains a first key and a second key according to the master key; generates a first process key using the first device identification information, and then calculates the second process key using the first key and the first process key; calculates the third key using the second key and the second process key; calculates the session key using the third key; and then uses the session key to encrypt data. However, when the first device of the invention is invaded, it will not be able to generate a key, and the reliability is not high. Therefore, the present invention provides a method and system for optimizing and enhancing the reliability of the distribution network.

Summary of the invention

The present invention respectively sets data acquisition modules on the power distribution equipment. Each data acquisition module encrypts and transmits the collected monitoring data to the first data acquisition module through other data acquisition modules. The first data acquisition module sends the monitoring data to the remote server module, and the remote server module pushes reminder messages to relevant contacts in time. The purpose of the present invention is to reliably generate a highly secure password value for encrypting and transmitting monitoring data while enhancing the reliability of the distribution network.

In order to achieve the above-mentioned object of the invention, the present invention provides a method for optimizing and enhancing the reliability of a distribution network as described below, which mainly includes the following steps:

Different data acquisition modules are respectively arranged on different power distribution equipment, and the data acquisition modules are used to collect monitoring data of the power distribution equipment. At the same time, communication connection is established between different data acquisition modules, and main characteristic values, first characteristic values to N-th characteristic values, and first password values to N-th password values respectively corresponding to the first characteristic values to N-th characteristic values are stored in the data acquisition modules, and the first password values to N-th password values stored are updated once after each pre-set first time interval.

Each of the data acquisition modules encrypts and transmits the collected monitoring data to the first data acquisition module through a number of other data acquisition modules, and after receiving the monitoring data sent by each of the data acquisition modules, the first data acquisition module sends the monitoring data to the remote server module;

After receiving the monitoring data collected by different data acquisition modules from the first data acquisition module, the remote server module uses a machine learning algorithm to analyze and process the monitoring data to obtain an analysis result, and if the analysis result is abnormal, a reminder message is promptly pushed to relevant contacts.

As a preferred technical solution of the present invention, among the different data acquisition modules, there is a first data acquisition module, and a second data acquisition module up to the Nth data acquisition module, and the first data acquisition module, and the second data acquisition module up to the Nth data acquisition module complete a change after each preset first time interval.

As a preferred technical solution of the present invention, the first data acquisition module, and the second data acquisition module until the Nth data acquisition module complete a change after each predetermined first time interval, comprising the following steps:

Divide the first time interval into N second time intervals, namely, second time interval 1, second time interval 2, and second time interval N;

Before the end of the second time interval 1, each of the data acquisition modules randomly generates a notification message. If the notification message is generated, the notification message is sent to each of the other data acquisition modules, which represents the intention of the data acquisition module sending the notification message to become the target data acquisition module. When the second time interval 1 ends, if the data acquisition module sending the notification message does not receive the notification message from other data acquisition modules, the data acquisition module sending the notification message is regarded as the target data acquisition module. Otherwise, the data acquisition module with the highest priority among all the data acquisition modules sending the notification messages is regarded as the target data acquisition module, and the target data acquisition module is regarded as the first data acquisition module.

During the second time interval 2 until the end of the second time interval N, the same method as the method for determining the first data acquisition module is repeated to respectively determine the second data acquisition module until the Nth data acquisition module.

As a preferred technical solution of the present invention, after each preset first time interval, the first password value to the Nth password value stored in the data acquisition module is updated once, including the following steps:

Each of the other data acquisition modules sends the first characteristic value stored in itself to the first data acquisition module, and the first data acquisition module generates a first password value using the main characteristic value stored in itself and the received first characteristic value, and the first data acquisition module transmits the generated first password value to the corresponding other data acquisition modules for storage;

Each of the other data acquisition modules sends the Kth characteristic value stored in itself to the Kth data acquisition module, and the Kth data acquisition module uses the main characteristic value stored in itself and the received Kth characteristic value to generate the Kth password value, and the Kth data acquisition module transmits the generated Kth password value to the corresponding other data acquisition modules for storage, where K is any integer greater than or equal to two and less than or equal to N.

As a preferred technical solution of the present invention, among the different data acquisition modules, there is a first data acquisition module, and a second data acquisition module up to an Nth data acquisition module, wherein N is the same as the total number of secret levels corresponding to the monitoring data collected by the data acquisition module.

As a preferred technical solution of the present invention, in the process in which the data acquisition module encrypts and transmits the collected monitoring data to the first data acquisition module through several other data acquisition modules, the following steps are included:

The first data acquisition module sets the tag value to zero and pre-sets a tag value threshold;

The first data acquisition module sends a first request message to the data acquisition module other than itself, and after receiving the first request message, the data acquisition module sends a first reply message to the first data acquisition module, wherein the first reply message includes the ID value of the data acquisition module and the ID values of other data acquisition modules adjacent to the data acquisition module;

In the case where the position of the first data acquisition module has not changed, all steps are terminated. In the case where the position of the first data acquisition module has changed, the first data acquisition module sends a second request message to the adjacent data acquisition module. After receiving the second request message, the adjacent data acquisition module sends a second reply message to the first data acquisition module. The second reply message includes the ID value of the adjacent data acquisition module, and the first data acquisition module determines the category to which the adjacent data acquisition module belongs according to the second reply message.

In the case where the adjacent data acquisition module belongs to category D, regenerate the transmission path of the monitoring data to the first data acquisition module, set the tag value to zero, and jump to the step of the first data acquisition module sending the first request information;

In the case where the adjacent data acquisition module does not belong to category D, determining whether the tag value is greater than the tag value threshold, and if so, regenerating the transmission path of the monitoring data to the first data acquisition module, setting the tag value to zero, and skipping the step of the first data acquisition module sending the first request information;

When the tag value is less than or equal to the tag value threshold, a new transmission path for the monitoring data to the first data acquisition module is generated based on the transmission path for the monitoring data to the first data acquisition module before the position of the first data acquisition module is changed, the tag value is accumulated, and the step of the first data acquisition module sending the first request information is jumped.

The present invention also provides a system for optimizing and enhancing the reliability of a power distribution network, comprising the following modules:

A data acquisition module, which is arranged on different power distribution equipment, collects monitoring data of the power distribution equipment, stores main characteristic values, first characteristic values to N-th characteristic values, and first password values to N-th password values respectively corresponding to the first characteristic values to N-th characteristic values, completes an update of the stored first password values to N-th password values after each pre-set first time interval, and is used to encrypt and transmit the collected monitoring data to the first data acquisition module through a plurality of other data acquisition modules, and the first data acquisition module sends the monitoring data to the remote server module after receiving the monitoring data sent by the data acquisition module;

An external network module, used for data transmission between the first data acquisition module and the remote server module;

The remote server module is used to use a machine learning algorithm to analyze and process the monitoring data after receiving the monitoring data collected by different data acquisition modules from the first data acquisition module to obtain analysis results, and in the event that the analysis results are abnormal, promptly push reminder messages to relevant contacts.

Compared with the prior art, the beneficial effects of the present invention are at least as follows:

In the present invention, firstly, different data acquisition modules are respectively arranged on different power distribution equipment to collect monitoring data of the power distribution equipment, store main characteristic values, first characteristic values up to the Nth characteristic value, and first password values corresponding to the first characteristic value up to the Nth characteristic value respectively up to the Nth password value; secondly, each data acquisition module encrypts and transmits the collected monitoring data to the first data acquisition module through several other data acquisition modules, and the first data acquisition module sends the monitoring data to the remote server module; finally, the remote server module uses a machine learning algorithm to analyze and process the monitoring data to obtain an analysis result, and in the case of an abnormality in the analysis result, promptly pushes a reminder message to the relevant contact person. While enhancing the reliability of the power distribution network, the present invention can also reliably generate a highly secure password value for encrypting and transmitting monitoring data.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of a method for optimizing and enhancing the reliability of a power distribution network according to the present invention;

FIG2 is a schematic diagram of category A of the present invention;

FIG3 is a schematic diagram of category B of the present invention;

FIG4 is a schematic diagram of category C of the present invention;

FIG5 is a structural diagram of a system for optimizing and enhancing the reliability of a distribution network according to the present invention.

Detailed ways

In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script.

The present invention provides a method for optimizing and enhancing the reliability of a distribution network as shown in FIG1 , which is mainly implemented by executing the following steps:

Step 1, respectively setting different data acquisition modules on different power distribution equipment, the data acquisition modules are used to collect monitoring data of the power distribution equipment, and at the same time, communication connection is established between different data acquisition modules, and main characteristic values, first characteristic values to N-th characteristic values, and first password values to N-th password values respectively corresponding to the first characteristic values to N-th characteristic values are stored in the data acquisition modules, and the first password values to N-th password values stored are updated once after each pre-set first time interval;

Step 2, each data acquisition module encrypts and transmits the collected monitoring data to the first data acquisition module through several other data acquisition modules, and after receiving the monitoring data sent by each data acquisition module, the first data acquisition module sends the monitoring data to the remote server module;

Step 3: After receiving the monitoring data collected by different data acquisition modules from the first data acquisition module, the remote server module uses a machine learning algorithm to analyze and process the monitoring data to obtain analysis results, and if the analysis results are abnormal, promptly push reminder messages to relevant contacts.

Specifically, firstly, different data acquisition modules are respectively arranged on different power distribution equipment, and the data acquisition modules are responsible for collecting monitoring data of the power distribution equipment, and the monitoring data refers to the operating data of the power distribution equipment, wherein two different data acquisition modules can communicate with each other, and the data acquisition module also stores main characteristic values, the first characteristic value to the Nth characteristic value, and the first password value to the Nth password value corresponding to the first characteristic value to the Nth characteristic value, respectively. The main characteristic value, the first characteristic value to the Nth characteristic value are pre-generated, and the generation method of the first password value to the Nth password value will be introduced below, and after each first time interval, the data acquisition module completes an update of the first password value to the Nth password value, that is, the first password value to the Nth password value stored in the data acquisition module is not fixed, but dynamically updated, and the security of the first password value to the Nth password value is enhanced, and secondly, each data acquisition module encrypts and transmits the collected monitoring data to the first data acquisition module through several other data acquisition modules, that is, for each data acquisition module, there is a path through several The transmission path of the monitoring data from other data acquisition modules to the first data acquisition module, for example, there are two adjacent data acquisition modules A and data acquisition module B on the transmission path, after data acquisition module A securely transmits a stored password value to data acquisition module B, it can use this password value to encrypt and transmit the monitoring data to data acquisition module B, thereby ensuring the security of the monitoring data, and then the first data acquisition module receives the monitoring data sent by each data acquisition module, and sends the monitoring data to the remote server module, and finally, after receiving the monitoring data collected by different data acquisition modules from the first data acquisition module, the remote server module uses a machine learning algorithm to analyze and process the monitoring data to obtain analysis results, and in the event that the analysis results are abnormal, for example, the analysis results show that the probability of failure of the distribution equipment can reach 90%, a reminder message is pushed to the relevant contacts in time, so that the distribution equipment can be briefly repaired in advance, or the distribution equipment can be directly and quickly replaced, thereby avoiding the power outage time caused by the need to locate the faulty distribution equipment in the future, thereby improving the reliability of the distribution network.

Further, among different data acquisition modules, there is a first data acquisition module, and a second data acquisition module up to an Nth data acquisition module, and the first data acquisition module, and the second data acquisition module up to an Nth data acquisition module complete a change after each preset first time interval.

Further, the first data acquisition module, and the second data acquisition module until the Nth data acquisition module complete a change after each preset first time interval, including the following steps:

Step 1: divide the first time interval into N second time intervals, namely, second time interval 1, second time interval 2, and second time interval N;

Step 2: Before the end of the second time interval 1, each data acquisition module randomly generates a notification message. If a notification message is generated, the notification message is sent to each other data acquisition module, which represents the intention of the data acquisition module sending the notification message to become the target data acquisition module. When the second time interval 1 ends, if the data acquisition module sending the notification message does not receive a notification message from other data acquisition modules, the data acquisition module sending the notification message is regarded as the target data acquisition module. Otherwise, the data acquisition module with the highest priority among all the data acquisition modules sending the notification messages is regarded as the target data acquisition module, and the target data acquisition module is regarded as the first data acquisition module.

Step 3: During the second time interval 2 until the end of the second time interval N, the same method as the method for determining the first data acquisition module is repeated to respectively determine the second data acquisition module until the Nth data acquisition module.

Specifically, in step 1, the first time interval is divided into N second time intervals, namely second time interval 1, second time interval 2 and second time interval N. In step 2, before the end of second time interval 1, each data acquisition module randomly generates a notification message, that is, each data acquisition module may generate a notification message or may not generate a notification message. If a notification message is generated, the notification message is sent to each other data acquisition module, which means that the data acquisition module sending the notification message wants to become the target data acquisition module, and at the end of second time interval 1, if the data acquisition module sending the notification message does not receive a notification message from other data acquisition modules, it means that no other data acquisition module also wants to become the target data acquisition module, and the notification message is sent. The data collection module is regarded as the target data collection module. Otherwise, the data collection module with the highest priority among all the data collection modules that send notification messages is regarded as the target data collection module. The priority of the data collection module can be set according to whether the data collection module has been invaded and the number of times it has been invaded. For example, the data collection module that has not been invaded has the highest priority, and the data collection module with fewer invasions has a higher priority. Then the target data collection module is regarded as the first data collection module. In step 3, before the end of the second time interval 2, before the end of the second time interval 3, and until the end of the second time interval N, the same method as in step 2 is repeated to respectively determine the second data collection module, the third data collection module, and until the Nth data collection module. It should be noted that in different data collection modules, the first generation of the first data collection module, and the second data collection module until the Nth data collection module can also use the above-mentioned methods of step 1 to step 3.

The above content says that the first data acquisition module, and the second data acquisition module until the Nth data acquisition module complete a change after each first time interval. In addition, when the total number of data acquisition modules changes, the first data acquisition module, and the second data acquisition module until the Nth data acquisition module also complete a change through the above steps 1 to 3, for example, adding a new data acquisition module, or abandoning a faulty data acquisition module. In addition, when any one of the first data acquisition module, the second data acquisition module, until the Nth data acquisition module is invaded, the first data acquisition module, and the second data acquisition module until the Nth data acquisition module also complete a change through the above steps 1 to 3. This change is to set the invaded data acquisition module not to send a notification message, so that the invaded data acquisition module is not used as one of the new first data acquisition module, the new second data acquisition module, until the new Nth data acquisition module. Through the above steps 1 to 3, the data acquisition module that generates the password value is not fixed, but dynamically changes, which can improve reliability. Even if the data acquisition module that generates the password value is invaded, the password value can still be generated by other data acquisition modules.

Furthermore, after each preset first time interval, the first password value to the Nth password value stored in the data acquisition module is updated once, including the following steps:

Step 1: Each other data acquisition module sends the first characteristic value stored in itself to the first data acquisition module, and the first data acquisition module uses the main characteristic value stored in itself and the received first characteristic value to generate a first password value, and the first data acquisition module transmits the generated first password value to the corresponding other data acquisition modules for storage;

Step 2. Each other data acquisition module sends the Kth characteristic value stored in itself to the Kth data acquisition module. The Kth data acquisition module uses the main characteristic value stored in itself and the received Kth characteristic value to generate the Kth password value, and the Kth data acquisition module transmits the generated Kth password value to the corresponding other data acquisition modules for storage, where K is any integer greater than or equal to two and less than or equal to N.

Specifically, according to the above content, after each first time interval, the first data acquisition module, and the second data acquisition module until the Nth data acquisition module complete a change, and at the same time, the first password value stored in the data acquisition module until the Nth password value can also be updated. In step 1, each other data acquisition module sends its own stored first characteristic value to the first data acquisition module, and the first data acquisition module uses its own stored main characteristic value and the received first characteristic value to generate the first password value. The specific generation method can be to encrypt the main characteristic value stored by itself and the received first characteristic value. Then the first data acquisition module transmits the generated first password value to each other data acquisition module to which the first characteristic value is transmitted. In step 2, each other data acquisition module sends its own stored Kth characteristic value to the Kth data acquisition module by repeating the method in step 1 to obtain the Kth password value. K refers to any integer greater than or equal to two and less than or equal to N. It should be noted that the first data acquisition module, and the second data acquisition module until the Nth data acquisition module can use the main characteristic value stored by itself and any characteristic value to generate their own corresponding password values. Through the above method, the first password value to the Nth password value stored in the data acquisition module are dynamically changed, and when the password value is used to encrypt and transmit the monitoring data, the security can be improved.

Furthermore, among different data acquisition modules, there is a first data acquisition module, and a second data acquisition module up to an Nth data acquisition module, wherein N is the same as the total number of secret levels corresponding to the monitoring data collected by the data acquisition module.

Specifically, N is the same as the total number of secret levels corresponding to the monitoring data collected by the data acquisition module, and is also the same as the total number of password values stored in the data acquisition module. According to the above content, the generation of the password value is related to the main eigenvalue and the eigenvalue. Different main eigenvalues and eigenvalues will produce different password values, and the complexity of different password values is also different. When the data acquisition module encrypts and transmits the monitoring data through the password value, it can select different password values according to the secret level corresponding to the monitoring data. The higher the secret level, the more complex the password value used. For example, if the secret level corresponding to the monitoring data is the highest, the first password value is selected to use, because the first password value has the highest complexity among all password values. In this way, for the corresponding monitoring data with a higher secret level, the encrypted transmission is safer, because the higher the complexity of the password value, the more difficult it is to crack. For the corresponding monitoring data with a lower secret level, the efficiency of the encrypted transmission can be improved, because the lower the complexity of the password value, the less time is spent on encryption and decryption.

Furthermore, in the process where the data acquisition module encrypts and transmits the collected monitoring data to the first data acquisition module through several other data acquisition modules, the following steps are included:

Step 1: The first data acquisition module sets the tag value to zero and pre-sets a tag value threshold;

Step 2: The first data acquisition module sends a first request message to the data acquisition modules other than itself. After receiving the first request message, the data acquisition module sends a first reply message to the first data acquisition module. The first reply message includes the ID value of the data acquisition module and the ID values of other data acquisition modules adjacent to the data acquisition module.

Step 3: When the position of the first data acquisition module does not change, all steps are terminated. When the position of the first data acquisition module changes, the first data acquisition module sends a second request message to the adjacent data acquisition module. After receiving the second request message, the adjacent data acquisition module sends a second reply message to the first data acquisition module. The second reply message includes the ID value of the adjacent data acquisition module, and the first data acquisition module determines the category to which the adjacent data acquisition module belongs according to the second reply message.

Step 4: if the adjacent data acquisition module belongs to category D, regenerate the transmission path of the monitoring data to the first data acquisition module, set the tag value to zero, and jump to the step of the first data acquisition module sending the first request information;

Step 5: If the adjacent data acquisition module does not belong to category D, determine whether the tag value is greater than the tag value threshold. If so, regenerate the transmission path of the monitoring data to the first data acquisition module, set the tag value to zero, and jump to the step of the first data acquisition module sending the first request information.

Step 6. When the tag value is less than or equal to the tag value threshold, a new transmission path for the monitoring data to the first data acquisition module is generated based on the transmission path for the monitoring data to the first data acquisition module before the position of the first data acquisition module is changed, the tag value is accumulated, and the step of the first data acquisition module sending the first request information is jumped.

Specifically, in the process where the data acquisition module encrypts and transmits the collected monitoring data to the first data acquisition module through several other data acquisition modules, the position of the first data acquisition module may change due to changes in power load and other reasons. At this time, a new transmission path for the monitoring data to the first data acquisition module needs to be generated. Generally, the entire transmission path will be regenerated, but this will take a long time and delay the transmission of the monitoring data, thereby affecting the reliability of the distribution network. In order to solve this problem, the above steps 1 to 6 are proposed;

For ease of understanding, the above categories are first explained. Referring to Figure 2, the data acquisition module with an ID value of 56 belongs to category A, the dotted box represents the first data acquisition module before the position changes, and the solid box represents the first data acquisition module after the position changes. The first data acquisition module changes from the position of the dotted box to the position of the solid box, that is, it changes to the vicinity of the data acquisition module with an ID value of 56. The data acquisition module with an ID value of 56 is separated from the dotted box by two communication distances. At this time, the new path length is reduced by one communication distance, and so on. When the first data acquisition module changes to the vicinity of the data acquisition module that was originally separated from it by P communication distances, where P is greater than or equal to 2, the new path length is reduced by P-1 communication distances. Referring to Figure 3, the data acquisition module with an ID value of 60 belongs to category B. The dotted box represents the first data acquisition module before the position changes, and the solid box represents the first data acquisition module after the position changes. The first data acquisition module The block changes from the position of the dotted box to the position of the solid box, that is, it changes to the vicinity of the data acquisition module with an ID value of 60. The data acquisition module with an ID value of 60 is an adjacent data acquisition module that is originally separated from the dotted box by two communication distances. At this time, the new path length remains unchanged; as shown in FIG4 , the data acquisition module with an ID value of 62 belongs to category C, the dotted box represents the first data acquisition module before the position is changed, and the solid box represents the first data acquisition module after the position is changed. The first data acquisition module changes from the position of the dotted box to the position of the solid box, that is, it changes to the vicinity of the data acquisition module with an ID value of 62. The data acquisition module with an ID value of 62 is an adjacent data acquisition module that is originally separated from the dotted box by a communication distance. At this time, the new path length increases by one communication distance. In addition, when the data acquisition module does not belong to any of category A, category B, and category C, the data acquisition module belongs to category D;

Next, the above-mentioned step 1 to step 6 are explained. In step 1, because the transmission path may become complicated by executing the generation of a new transmission path based on the transmission path before the position of the first data acquisition module is changed for multiple times, the first data acquisition module sets the tag value to zero and pre-sets the tag value threshold. In step 2, the first data acquisition module sends a first request message to the data acquisition modules other than itself. After receiving the first request message, the data acquisition module sends a first reply message to the first data acquisition module. The first reply message includes the ID value of the data acquisition module and the ID values of other data acquisition modules adjacent to the data acquisition module. Adjacent means separated by a communication distance. Through step 2, the first data acquisition module can grasp the positional relationship between all data acquisition modules. In step 3, if the position of the first data acquisition module has not changed, all steps are terminated. Otherwise, the first data acquisition module sends a second request message to the adjacent data acquisition module. After receiving the second request message, the adjacent data acquisition module sends a second reply message to the first data acquisition module. The second reply message includes the ID value of the adjacent data acquisition module. The first data acquisition module determines the positional relationship between all data acquisition modules before the position change according to the second reply message. , it is possible to determine the category to which the adjacent data acquisition module belongs. It should be noted that category A has a higher priority than category B and higher than category C. When there are multiple adjacent data acquisition modules belonging to the same category, a random adjacent data acquisition module is determined. In step 4, if the adjacent data acquisition module belongs to category D, the transmission path of the monitoring data to the first data acquisition module is regenerated, the tag value is set to zero, and the second step is jumped. In step 5, if the adjacent data acquisition module does not belong to category D, it is determined whether the tag value is greater than the tag value threshold. If it is, the transmission path of the monitoring data to the first data acquisition module is regenerated, and the tag value is set to zero. is zero, jump to step 2. Since the transmission path has become too complicated at this time, the transmission path should be regenerated. In step 6, if the tag value is less than or equal to the tag value threshold, based on the transmission path of the monitoring data to the first data acquisition module before the position of the first data acquisition module is changed, and the category of the determined adjacent data acquisition module, a new transmission path for the monitoring data to the first data acquisition module is generated using a corresponding method, and the tag value is accumulated, and jump to step 2. If the adjacent data acquisition module belongs to category A, 0 is accumulated, if the adjacent data acquisition module belongs to category B, 1 is accumulated, and if the adjacent data acquisition module belongs to category C, 2 is accumulated.

According to another aspect of an embodiment of the present invention, as shown in FIG5 , a system for optimizing and enhancing the reliability of a distribution network is also provided, which is used to implement the above-mentioned method for optimizing and enhancing the reliability of a distribution network, including a data acquisition module, an external network module, and a remote server module, and the functions of each module are as follows:

A data acquisition module, which is arranged on different power distribution equipment, collects monitoring data of the power distribution equipment, stores main characteristic values, first characteristic values to N-th characteristic values, and first password values to N-th password values respectively corresponding to the first characteristic values to N-th characteristic values, completes an update of the stored first password values to N-th password values after each pre-set first time interval, and is used to encrypt and transmit the collected monitoring data to the first data acquisition module through a plurality of other data acquisition modules, and the first data acquisition module sends the monitoring data to the remote server module after receiving the monitoring data sent by the data acquisition module;

An external network module, used for data transmission between the first data acquisition module and the remote server module;

The remote server module is used to use a machine learning algorithm to analyze and process the monitoring data after receiving the monitoring data collected by different data acquisition modules from the first data acquisition module to obtain analysis results, and in the event that the analysis results are abnormal, promptly push reminder messages to relevant contacts.

It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have strict order restrictions, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the above-mentioned program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and/or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims (5)

1. A method for optimizing and enhancing the reliability of a distribution network, characterized in that it comprises the following steps: Different data acquisition modules are respectively arranged on different power distribution equipment, and the data acquisition modules are used to collect monitoring data of the power distribution equipment. At the same time, communication connection is established between different data acquisition modules, and main characteristic values, first characteristic values to N-th characteristic values, and first password values to N-th password values respectively corresponding to the first characteristic values to N-th characteristic values are stored in the data acquisition modules, and the first password values to N-th password values stored are updated once after each pre-set first time interval. Each of the data acquisition modules encrypts and transmits the collected monitoring data to the first data acquisition module through a number of other data acquisition modules, and after receiving the monitoring data sent by each of the data acquisition modules, the first data acquisition module sends the monitoring data to the remote server module; After receiving the monitoring data collected by different data collection modules from the first data collection module, the remote server module uses a machine learning algorithm to analyze and process the monitoring data to obtain an analysis result, and in the event that the analysis result is abnormal, promptly pushes a reminder message to the relevant contact person; Among the different data acquisition modules, there is a first data acquisition module, and a second data acquisition module until an Nth data acquisition module, and the first data acquisition module, and the second data acquisition module until the Nth data acquisition module complete a change after each first preset time interval; The first data acquisition module, and the second data acquisition module until the Nth data acquisition module complete a change after each predetermined first time interval, comprising the following steps: Divide the first time interval into N second time intervals, namely, second time interval 1, second time interval 2, and second time interval N; Before the end of the second time interval 1, each of the data acquisition modules randomly generates a notification message. If the notification message is generated, the notification message is sent to each of the other data acquisition modules, which represents the intention of the data acquisition module sending the notification message to become the target data acquisition module. When the second time interval 1 ends, if the data acquisition module sending the notification message does not receive the notification message from other data acquisition modules, the data acquisition module sending the notification message is regarded as the target data acquisition module. Otherwise, the data acquisition module with the highest priority among all the data acquisition modules sending the notification messages is regarded as the target data acquisition module, and the target data acquisition module is regarded as the first data acquisition module. During the second time interval 2 until the end of the second time interval N, the same method as the method for determining the first data acquisition module is repeated to respectively determine the second data acquisition module until the Nth data acquisition module. 2. A method for optimizing and enhancing the reliability of a distribution network according to claim 1, characterized in that after each predetermined first time interval, the first password value to the Nth password value stored in the data acquisition module is updated once, comprising the following steps: Each of the other data acquisition modules sends the first characteristic value stored in itself to the first data acquisition module, and the first data acquisition module generates a first password value using the main characteristic value stored in itself and the received first characteristic value, and the first data acquisition module transmits the generated first password value to the corresponding other data acquisition modules for storage; Each of the other data acquisition modules sends the Kth characteristic value stored in itself to the Kth data acquisition module, and the Kth data acquisition module uses the main characteristic value stored in itself and the received Kth characteristic value to generate the Kth password value, and the Kth data acquisition module transmits the generated Kth password value to the corresponding other data acquisition modules for storage, where K is any integer greater than or equal to two and less than or equal to N. 3. A method for optimizing and enhancing the reliability of a distribution network according to claim 2, characterized in that, among the different data acquisition modules, there is a first data acquisition module, and a second data acquisition module up to an Nth data acquisition module, wherein N is the same as the total number of confidentiality levels corresponding to the monitoring data collected by the data acquisition module. 4. A method for optimizing and enhancing the reliability of a power distribution network according to claim 3, characterized in that, in the process in which the data acquisition module encrypts and transmits the collected monitoring data to the first data acquisition module through a plurality of other data acquisition modules, the method comprises the following steps: The first data acquisition module sets the tag value to zero and pre-sets a tag value threshold; The first data acquisition module sends a first request message to the data acquisition module other than itself, and after receiving the first request message, the data acquisition module sends a first reply message to the first data acquisition module, wherein the first reply message includes the ID value of the data acquisition module and the ID values of other data acquisition modules adjacent to the data acquisition module; In the case where the position of the first data acquisition module has not changed, all steps are terminated. In the case where the position of the first data acquisition module has changed, the first data acquisition module sends a second request message to the adjacent data acquisition module. After receiving the second request message, the adjacent data acquisition module sends a second reply message to the first data acquisition module. The second reply message includes the ID value of the adjacent data acquisition module, and the first data acquisition module determines the category to which the adjacent data acquisition module belongs according to the second reply message. In the case where the adjacent data acquisition module belongs to category D, regenerate the transmission path of the monitoring data to the first data acquisition module, set the tag value to zero, and jump to the step of the first data acquisition module sending the first request information; In the case where the adjacent data acquisition module does not belong to category D, determining whether the tag value is greater than the tag value threshold, and if so, regenerating the transmission path of the monitoring data to the first data acquisition module, setting the tag value to zero, and skipping the step of the first data acquisition module sending the first request information; When the tag value is less than or equal to the tag value threshold, a new transmission path for the monitoring data to the first data acquisition module is generated based on the transmission path for the monitoring data to the first data acquisition module before the position of the first data acquisition module is changed, the tag value is accumulated, and the step of the first data acquisition module sending the first request information is jumped. 5. A system for optimizing and enhancing the reliability of a distribution network, used to implement the method according to any one of claims 1 to 4, characterized in that it comprises the following modules: A data acquisition module, which is arranged on different power distribution equipment, collects monitoring data of the power distribution equipment, stores main characteristic values, first characteristic values to N-th characteristic values, and first password values to N-th password values respectively corresponding to the first characteristic values to N-th characteristic values, completes an update of the stored first password values to N-th password values after each pre-set first time interval, and is used to encrypt and transmit the collected monitoring data to the first data acquisition module through a plurality of other data acquisition modules, and the first data acquisition module sends the monitoring data to the remote server module after receiving the monitoring data sent by the data acquisition module; An external network module, used for data transmission between the first data acquisition module and the remote server module; The remote server module is used to use a machine learning algorithm to analyze and process the monitoring data after receiving the monitoring data collected by different data acquisition modules from the first data acquisition module to obtain analysis results, and in the event that the analysis results are abnormal, promptly push reminder messages to relevant contacts.