CN117291554B - Cloud network collaborative operation method and system in power industry - Google Patents

Abstract

The present invention provides a cloud-network collaborative operation method and system for the electric power industry, the method comprising: receiving an instruction to add a target transmission line to a cloud-network collaborative management platform; the cloud-network collaborative management platform comprises a first cloud resource pool, a second cloud resource pool and a data operation layer; the cloud-network collaborative management platform receives basic information and extended information of the target transmission line; the basic information is uploaded to the first cloud resource pool, and the physical trust is obtained by calculation in the first cloud resource pool; the extended information is uploaded to the second cloud resource pool, and the external trust is obtained by calculation in the second cloud resource pool; the physical trust and the external trust are input into the data operation layer, and the physical trust and the external trust are integrated to obtain the operation data of the target transmission line; the operation data is compared with a preset threshold value, and if it is greater than the preset threshold value, the target transmission line is added to the cloud-network collaborative management platform. The present invention can improve the accuracy of the operation evaluation of the transmission line.

Description

A cloud network collaborative operation method and system for the power industry

Technical Field

The present invention relates to the field of data processing technology, and in particular to a cloud-network collaborative operation method and system for the electric power industry.

Background technique

The expansion of the power grid has led to an increase in transmission lines, which are distributed in complex and remote areas and are vulnerable to natural disasters, causing failures and power accidents. In order to improve the operational service capabilities of power grid companies, before incorporating transmission lines into the cloud-network collaborative management platform, it is necessary to solve the urgent problem of how to accurately evaluate the operation of transmission lines.

Therefore, it is necessary to propose a cloud-network collaborative operation method and system for the power industry to solve this technical problem.

Summary of the invention

The purpose of the embodiment of the present invention is to provide a cloud-network collaborative operation method and system for the power industry. The embodiment of the present invention can improve the accuracy of operation evaluation of transmission lines. The specific technical solution is as follows:

In a first aspect of an embodiment of the present invention, a cloud-network collaborative operation method for the electric power industry is provided, the method comprising:

Receiving an instruction to add a target transmission line to a cloud-network collaborative management platform; the cloud-network collaborative management platform includes a first cloud resource pool, a second cloud resource pool, and a data operation layer;

The cloud-network collaborative management platform receives basic information and extended information of the target transmission line;

Uploading the basic information to a first cloud resource pool, and obtaining a physical trust degree through calculation in the first cloud resource pool;

Uploading the extended information to a second cloud resource pool, and obtaining an external trust degree through calculation in the second cloud resource pool;

Inputting the physical trust and the external trust into the data operation layer, fusing the physical trust and the external trust to obtain the operation data of the target transmission line;

The operation data is compared with a preset threshold value. If the operation data is greater than the preset threshold value, the target transmission line is added to the cloud-network collaborative management platform.

Furthermore, the basic information includes: target tower coordinates, target tower height and target tower structure.

Furthermore, the extended information includes: meteorological parameters, air humidity, wind speed and geographical area type.

Furthermore, uploading the basic information to the first cloud resource pool and obtaining the physical trust by calculation in the first cloud resource pool includes:

According to the target tower structure, obtaining an existing transmission line in the first cloud resource pool that is similar to the target tower structure;

Querying the historical operation data of the existing transmission line;

Screening out high-quality existing transmission lines according to the historical operation data, and querying average tower coordinates and average tower heights corresponding to the high-quality existing transmission lines;

The physical trust degree is obtained according to the numerical relationship between the target tower coordinates, the target tower height and the average tower coordinates, the average tower height.

Further, acquiring, according to the target tower structure, an existing transmission line in the first cloud resource pool that is similar to the target tower structure, includes:

Acquire a first structural image of the target tower;

Acquire a second structural image of any one of the existing transmission lines;

Using the SSIM algorithm to compare the similarity between the first structural image and the second structural image;

If the similarity is higher than the similarity threshold, the corresponding existing transmission line is an existing transmission line with a structure similar to that of the target tower.

Further, obtaining the physical trust according to the numerical relationship between the target tower coordinates, the target tower height and the average tower coordinates, the average tower height, includes:

The physical trust Q1 is calculated according to the following formula:

;

in,( , ) represents the target tower coordinates, represents the target tower height, ( , ) represents the average tower coordinates, represents the average tower height, and α and β are weight parameters.

Further, uploading the extended information to the second cloud resource pool, and obtaining the external trust through calculation in the second cloud resource pool, includes:

According to the geographical area type, obtaining an existing power transmission line corresponding to the geographical area type in the second cloud resource pool;

Querying the historical fault data of the existing power transmission line; the historical fault data includes the fault type and fault frequency;

The fault type, the fault frequency, and the meteorological parameter are input into a neural network model to obtain external trust.

Furthermore, the inputting the fault type, the fault frequency, and the meteorological parameter into a neural network model to obtain external trustworthiness includes:

Inputting the meteorological parameters into a deep learning model to obtain a model output result;

The fault type, the fault frequency and the model output result are input into a multilayer perceptron to obtain external trust.

Further, the inputting the physical trust and the external trust into the data operation layer, fusing the physical trust and the external trust, and obtaining the operation data of the target transmission line includes:

The operating data S is calculated according to the following formula:

S = Q1·Q2;

Among them, Q1 represents physical trust and Q2 represents external trust.

In another aspect of the embodiment of the present invention, a cloud network collaborative operation system for the electric power industry is provided, the system comprising:

An instruction collection module, used to receive an instruction to add a target transmission line to a cloud-network collaborative management platform; the cloud-network collaborative management platform includes a first cloud resource pool, a second cloud resource pool and a data operation layer;

An information receiving module, used for the cloud-network collaborative management platform to receive basic information and extended information of the target transmission line;

A first calculation module, used for uploading the basic information to a first cloud resource pool, and obtaining the physical trust through calculation in the first cloud resource pool;

A second calculation module, used for uploading the extended information to a second cloud resource pool, and obtaining an external trust degree through calculation in the second cloud resource pool;

A third calculation module, used for inputting the physical trust and the external trust into the data operation layer, fusing the physical trust and the external trust, and obtaining the operation data of the target transmission line;

The data processing module is used to compare the operating data with a preset threshold value. If the operating data is greater than the preset threshold value, the target transmission line is added to the cloud-network collaborative management platform.

It can be seen from the above that the implementation of the present invention brings at least the following beneficial effects:

(1) The present invention receives an instruction to add a target transmission line to a cloud-network collaborative management platform; the cloud-network collaborative management platform includes a first cloud resource pool, a second cloud resource pool, and a data operation layer; the cloud-network collaborative management platform receives basic information and extended information of the target transmission line; the basic information and extended information are uploaded to the first and second cloud resource pools, respectively, and external trust and external trust are obtained through calculation; the physical trust and the external trust are input into the data operation layer for fusion to obtain the operation data of the target transmission line; and whether to add the target transmission line to the cloud-network collaborative management platform is determined based on the operation data. The efficiency of cloud-network collaborative operation management and the safety of power grid operation are improved by fusion calculation of relevant data of the target transmission line.

(2) Obtain high-quality existing transmission lines with similar tower structures to the target towers, and calculate the physical trust of the target transmission lines based on the numerical relationship between the average tower coordinates and average tower heights corresponding to the high-quality existing transmission lines and the target tower coordinates and heights, thereby improving the accuracy of the operation data calculation.

(3) Obtain the external data of the target transmission line and the historical fault data of the existing transmission lines, introduce deep learning models and multi-layer perceptrons, and calculate the external trust of the target transmission line, thereby improving the accuracy of operation data calculation.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

FIG1 is a schematic diagram of an application scenario of a cloud-network collaborative operation system for the power industry provided by an embodiment of the present invention;

FIG2 is a flow chart of a cloud-network collaborative operation method for the power industry provided by an embodiment of the present invention;

3 is a schematic diagram of the structure of a cloud-network collaborative operation system for the power industry provided by an embodiment of the present invention;

FIG. 4 is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention.

Detailed ways

The embodiment of the present invention provides a cloud-network collaborative operation method and system for the power industry. Please refer to Figure 1, which is a schematic diagram of an application scenario of the cloud-network collaborative operation system for the power industry provided by the embodiment of the present invention. The system may include a terminal and a server. The cloud-network collaborative operation method for the power industry provided by the present invention can be implemented through a terminal or a server.

As shown in FIG1 , the terminal and the server are connected via a network, such as a wired or wireless network connection. The terminal may include but is not limited to portable terminals such as mobile phones and tablets installed with various network platform applications, as well as fixed terminals such as computers, query machines, and advertising machines. The server provides users with various business services, including service push servers, user recommendation servers, etc.

It should be noted that the application scenario diagram of the cloud-network collaborative operation system for the power industry shown in Figure 1 is merely an example. The terminals, servers, and application scenarios described in the embodiments of the present invention are intended to more clearly illustrate the technical solutions of the embodiments of the present invention, and do not generate limitations on the technical solutions provided by the embodiments of the present invention. Ordinary technicians in this field can know that with the evolution of the system and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present invention are also applicable to similar technical problems.

Among them, the terminal can be used for:

Receiving an instruction to add a target transmission line to a cloud-network collaborative management platform; the cloud-network collaborative management platform includes a first cloud resource pool, a second cloud resource pool, and a data operation layer;

The cloud-network collaborative management platform receives basic information and extended information of the target transmission line;

Uploading the basic information to a first cloud resource pool, and obtaining a physical trust degree through calculation in the first cloud resource pool;

Uploading the extended information to a second cloud resource pool, and obtaining an external trust degree through calculation in the second cloud resource pool;

Inputting the physical trust and the external trust into the data operation layer, fusing the physical trust and the external trust to obtain the operation data of the target transmission line;

The operation data is compared with a preset threshold value. If the operation data is greater than the preset threshold value, the target transmission line is added to the cloud-network collaborative management platform.

It should be noted that the steps of the cloud-network collaborative operation method for the power industry executed by the above-mentioned terminal can also be executed by the server.

FIG2 shows a flow chart of a cloud-network collaborative operation method and system for the power industry provided by an embodiment of the present invention. As shown in FIG2 , a cloud-network collaborative operation method and system for the power industry includes the following steps:

Step 201: Receive an instruction to add a target transmission line to a cloud-network collaborative management platform.

Among them, the cloud-network collaborative management platform may include a first cloud resource pool, a second cloud resource pool and a data operation layer.

In some embodiments, the system or operator may receive commands or instructions from the outside, the purpose of which is to incorporate a specific transmission line into the power operation management system of the cloud-network collaborative management platform.

In some embodiments, the cloud-network collaborative management platform is divided into three main components:

First Cloud Resource Pool: It is a cloud computing resource pool used to process the basic information of the target transmission line and perform calculations to obtain physical trust. In the first cloud resource pool, data processing and analysis of the transmission line will be carried out to evaluate its physical reliability.

Second cloud resource pool: is another cloud computing resource pool used to process the extended information of the target transmission line and perform calculations to obtain external trust. The second cloud resource pool involves the processing of meteorological data, geographic information and other external factors to evaluate the external environmental conditions and trust of the transmission line.

Data operation layer: It is the core part of the entire collaborative management platform. It receives and integrates the trust data from the first cloud resource pool and the second cloud resource pool. In the data operation layer, physical trust and external trust will be combined to generate comprehensive operation data about the target transmission line. The above data can be used to make decisions, such as whether to include the transmission line in the cloud network collaborative management platform.

In summary, receiving the instruction to add the target transmission line to the cloud-network collaborative management platform initiates a series of calculation and data processing processes to evaluate and manage the operating status and reliability of the specific transmission line, which helps to improve the operational efficiency of the power industry and the reliability of the power grid.

Step 202: The cloud-network collaborative management platform receives basic information and extended information of the target transmission line.

Among them, the basic information may include target tower coordinates, target tower height, and target tower structure. In some embodiments, it is core information about the target transmission line, which is usually used to evaluate the physical condition and reliability of the line. The target tower coordinates are the geographic coordinates of the tower or supporting structure on the transmission line, usually expressed in longitude and latitude. This information can be used to determine the location of the tower. The target tower height indicates the height of the tower or supporting structure on the transmission line, which is important when considering the physical trust of the line. The target tower structure describes the type, shape, and material of the tower or supporting structure, which is critical to determining the physical reliability and carrying capacity of the line.

Among them, the extended information may include meteorological parameters, air humidity, wind force, and geographic region type. In some embodiments, the extended information is generally used to consider external environmental factors of the transmission line to more comprehensively evaluate the reliability of the line. In some embodiments, meteorological parameters include meteorological conditions such as temperature, humidity, and air pressure, which can affect the performance of the transmission line, especially under severe weather conditions. Air humidity can affect electrical equipment on the transmission line, such as insulators. The strength and direction of wind force can affect the stability of the towers and conductors of the transmission line. The geographic region type represents the geographical environment where the transmission line is located, such as cities, mountains, deserts, etc. Different geographical regions have different effects on the maintenance and reliability of the line.

Step 203: Upload the basic information to the first cloud resource pool, and obtain the physical trust through calculation in the first cloud resource pool.

Optionally, step 203 may further include:

According to the target tower structure, obtaining an existing transmission line in the first cloud resource pool that is similar to the target tower structure;

Querying the historical operation data of the existing transmission line;

Screening out high-quality existing transmission lines according to the historical operation data, and querying average tower coordinates and average tower heights corresponding to the high-quality existing transmission lines;

The physical trust degree is obtained according to the numerical relationship between the target tower coordinates, the target tower height and the average tower coordinates, the average tower height.

In some embodiments, basic information about the target transmission line (such as target tower coordinates, target tower height, and target tower structure) can be uploaded to a first cloud resource pool. This resource pool is a cloud computing environment for storing and processing data related to the transmission line. Once the basic information is uploaded to the first cloud resource pool, the next operation involves calculating the physical trust. This trust reflects the physical reliability or health status of the target transmission line. The calculation of the physical trust can be based on different factors, depending on the target tower structure.

In some embodiments, the system may try to find existing transmission lines with similar structures to the target tower. This can help the system better understand the physical characteristics of the target line. The system will also query the historical operation data of the existing transmission lines, which include the past performance of the line, fault conditions, etc. These data help to assess the health of the line. The system will screen out high-quality lines from the existing transmission lines, which have performed well in the past or have been better maintained. Finally, the system will use the target tower coordinates, target tower height, and the numerical relationship between the average tower coordinates and the average tower height to calculate the physical trust of the target transmission line. This trust can help decision makers understand the health of the line so that they can make corresponding operational decisions. In the above way, the operational safety and efficiency of the power grid can be improved.

Optionally, the step of acquiring, according to the target tower structure, an existing transmission line in the first cloud resource pool that is similar to the target tower structure includes:

Acquire a first structural image of the target tower;

Acquire a second structural image of any one of the existing transmission lines;

Using the SSIM algorithm to compare the similarity between the first structural image and the second structural image;

If the similarity is higher than the similarity threshold, the corresponding existing transmission line is an existing transmission line with a structure similar to that of the target tower.

In some embodiments, a structural image of a target tower in a target transmission line may be obtained. This image is a photograph or drawing showing the appearance and structural details of the tower. Next, a transmission line in an existing transmission line needs to be selected and a structural image of the line is obtained. This line is considered to be similar in structure to the target tower, but not necessarily exactly the same line.

In some embodiments, a structural similarity index (SSIM) algorithm may be used to compare the first structural image (target tower) and the second structural image (existing transmission line). SSIM is an image quality assessment method used to measure the similarity between two images. If the SSIM value is high enough, it means that the two images are very similar in structure.

In some embodiments, a similarity threshold may be set, which is used to determine when two structural images are considered sufficiently similar. If the SSIM value is higher than the threshold, then the structure of the target tower may be considered to be very similar to the structure of the selected existing transmission line.

Finally, by comparing the calculated SSIM value with the similarity threshold, it can be determined whether the selected existing transmission line is structurally similar to the target tower. If the similarity is higher than the threshold, it can be concluded that the selected existing transmission line is structurally similar to the target tower.

Determining whether the existing transmission line has similar characteristics to the target tower structure in the above way helps to evaluate the physical trustworthiness of the target transmission line and can be used as an indicator for decision-making to improve the reliability of the power system.

Optionally, the step of obtaining the physical trust according to the numerical relationship between the target tower coordinates, the target tower height and the average tower coordinates, the average tower height, includes:

The physical trust Q1 is calculated according to the following formula:

;

in, is the physical trust, which indicates the physical reliability of the target transmission line, ( , ) represents the target tower coordinates, represents the target tower height, ( , ) represents the average tower coordinates, represents the average tower height, and α and β are weight parameters used to balance the importance of coordinates and height in the calculation. They determine the contribution of coordinates and height to physical confidence. Usually, the values of these parameters are determined according to the needs of specific applications.

The purpose of this formula is to calculate the physical trust based on the numerical difference between the coordinates and height of the target tower and the average coordinates and average height of the known existing transmission lines. Specifically:

A measure of the difference between the target tower coordinates and the known average coordinates. This is expressed as the Euclidean distance, which takes into account the deviation between longitude and latitude. The difference between the target tower height and the known average height is measured.

It can be understood that the combination of these two items is used to comprehensively consider the deviation of coordinates and height to calculate the physical trust of the target transmission line. If the value of Q1 is higher, it means that the physical characteristics of the target transmission line are closer to the known average characteristics, so that it can be operated and maintained more reliably. The selection of weight parameters α and β can be adjusted according to the needs of specific applications to reflect the relative importance of different factors. Step 204, upload the extended information to the second cloud resource pool, and obtain the external trust through calculation in the second cloud resource pool.

Optionally, step 204 may include:

According to the geographical area type, obtaining an existing power transmission line corresponding to the geographical area type in the second cloud resource pool;

Querying the historical fault data of the existing power transmission line; the historical fault data includes the fault type and the fault frequency;

The fault type, the fault frequency, and the meteorological parameter are input into a neural network model to obtain external trust.

In some embodiments, the system may obtain existing power transmission lines corresponding to the geographic region type from the second cloud resource pool according to the geographic region type, which means that the system will select power transmission lines that already exist in the geographic region and operate under similar environmental conditions.

In some embodiments, the system queries historical fault data for selected existing transmission lines. These historical fault data include the types and frequencies of faults that occurred on these lines in the past. This information helps to understand the performance and reliability of these lines in the past.

In some embodiments, the system inputs the acquired fault type, fault frequency and meteorological parameters into a neural network model. The neural network model is a computational model that can be used to analyze and process complex data relationships.

In some embodiments, the neural network model processes the input data and outputs an external confidence value. This value represents the reliability of the target transmission line in a specific geographical area type, subject to historical fault data and meteorological parameters. The value of the external confidence can be determined based on the output of the model, and a higher value generally indicates higher reliability.

Optionally, the step of inputting the fault type, the fault frequency, and the meteorological parameter into a neural network model to obtain an external trustworthiness includes:

Inputting the meteorological parameters into a deep learning model to obtain a model output result;

The fault type, the fault frequency and the model output result are input into a multilayer perceptron to obtain external trust.

In some embodiments, the system can input the collected meteorological parameters into a deep learning model. A deep learning model is an artificial neural network that is used to learn and understand complex data relationships. In this scenario, the task of the deep learning model is to predict some relevant results based on the input meteorological parameters, which can be information related to the reliability of the transmission line.

In some embodiments, the deep learning model processes the input meteorological parameters and generates a model output result. This result is a numerical value representing a prediction based on the meteorological parameters, or a probability distribution representing the probability of different results. This output reflects the impact of meteorological conditions on the reliability of the target transmission line.

In some embodiments, the fault type, fault frequency, and model output results can be input into a multi-layer perceptron (MLP): Next, the system inputs the fault type and fault frequency in the historical fault data and the output results obtained by the previous deep learning model into a multi-layer perceptron (MLP). MLP is a common neural network structure used to process and fuse different types of data.

In some embodiments, the MLP processes the input data and generates an external confidence result. This external confidence reflects the combined influence of multiple factors, including historical failure data, meteorological conditions, and the prediction results of the deep learning model. The value of the external confidence can be determined based on the output of the MLP, and generally a higher value indicates higher reliability.

In summary, this process uses deep learning models and MLP to comprehensively consider meteorological parameters, historical fault data, and the model's prediction results to calculate the external trust value. The value of the external trust value helps to evaluate the reliability of the target transmission line under external environmental conditions.

Step 205: input the physical trust and the external trust into the data operation layer, integrate the physical trust and the external trust, and obtain the operation data of the target transmission line.

Optionally, step 205 may include:

The operating data S is calculated according to the following formula:

S = Q1·Q2;

Among them, Q1 represents physical trust and Q2 represents external trust.

In some embodiments, the system can pass the previously calculated physical trust (Q1) and external trust (Q2) to the data operation layer. The data operation layer is a computing and decision-making environment used to integrate various information to support operational decisions.

In some embodiments, in the data operation layer, physical trust and external trust will be integrated. This integration process can be done in different ways, depending on specific business needs and algorithm design. The goal is to comprehensively consider the impact of physical characteristics and external environmental factors on the target transmission line to more fully understand the operation status of the line.

Finally, by integrating physical trust and external trust, the system can obtain the operation data of the target transmission line. This operation data reflects the line status and reliability after comprehensive consideration of physical and external factors.

In some embodiments, in the calculation formula of the operation data S, S represents the operation data, Q1 represents the physical trust, and Q2 represents the external trust. This formula is used to multiply the physical trust and the external trust to obtain the final operation data. This formula can be designed according to specific business needs to determine the weight and influence of physical and external factors in the operation data.

In summary, through the above methods, physical trust and external trust can be comprehensively considered to calculate the operating data of the target transmission line, helping power companies to better understand the status and reliability of the line, thereby supporting operational decisions.

Step 206: compare the operating data with a preset threshold value. If the operating data is greater than the preset threshold value, add the target transmission line to the cloud-network collaborative management platform.

In some embodiments, the system can obtain operation data, which reflects the operation status and reliability of the target transmission line by integrating physical trust and external trust, and then compare the operation data with a pre-set threshold.

In some embodiments, during the comparison process, the system checks whether the operating data is greater than a preset threshold. This preset threshold is set according to specific business needs and operating standards, and usually represents the lower limit of an acceptable reliability level. If the operating data exceeds this threshold, it means that the operating status of the target transmission line has reached or exceeded the expected reliability standard.

In some embodiments, if the operating data is greater than a preset threshold, the system will decide to add the target transmission line to the cloud network collaborative management platform. This means that the line will be included in the management and monitoring system so that the power company can track and manage its operating status in real time and take necessary maintenance and repair measures.

In summary, the calculated operating data is compared with the preset thresholds in the above way to help the power company determine the reliability status of the target transmission line. If the reliability of the line meets or exceeds the expected standards, it will be included in the collaborative management platform to ensure the stable and reliable operation of the power system.

In summary, this solution can improve the efficiency of cloud-network collaborative operation management and the safety of power grid operation, and accurately evaluate the operating status of the target transmission line.

To implement the above method embodiments, the present invention further provides a cloud-network collaborative operation system for the power industry. FIG3 shows a schematic diagram of the structure of a cloud-network collaborative operation system for the power industry provided by the present invention. The system includes:

The instruction collection module 301 is used to receive an instruction to add a target transmission line to a cloud-network collaborative management platform; the cloud-network collaborative management platform includes a first cloud resource pool, a second cloud resource pool and a data operation layer;

An information receiving module 302 is used for the cloud-network collaborative management platform to receive basic information and extended information of the target transmission line;

A first calculation module 303 is used to upload the basic information to a first cloud resource pool, and obtain the physical trust through calculation in the first cloud resource pool;

A second calculation module 304 is used to upload the extended information to a second cloud resource pool, and obtain an external trust degree through calculation in the second cloud resource pool;

A third calculation module 305 is used to input the physical trust and the external trust into the data operation layer, and integrate the physical trust and the external trust to obtain the operation data of the target transmission line;

The data processing module 306 is used to compare the operating data with a preset threshold value. If the operating data is greater than the preset threshold value, the target transmission line is added to the cloud-network collaborative management platform.

In some embodiments, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in FIG4. The computer device includes a processor, a memory, and a network interface connected via 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, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store relevant data of the image acquisition device. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a cloud network collaborative operation method and system for the power industry is realized.

In some embodiments, a computer device is provided, which may be a terminal, and its internal structure diagram may be shown in FIG4. The computer device includes a processor, a memory, a communication interface, a display screen, and an input system connected via 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 implemented through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a cloud network collaborative operation method and system for the power industry is implemented. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input system of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

Those skilled in the art will understand that the structure shown in FIG. 4 is merely a block diagram of a partial structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

In some embodiments, a computer device is also provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

In some embodiments, a computer-readable storage medium is provided, storing a computer program, which implements the steps in the above-mentioned method embodiments when executed by a processor.

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 computer program can be stored in a non-volatile computer-readable storage medium. When the computer 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 by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all feasible combinations of the technical features in the above 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 invention patent. 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.

In summary, the present invention provides a cloud-network collaborative operation method for the power industry, the method comprising:

Receiving an instruction to add a target transmission line to a cloud-network collaborative management platform; the cloud-network collaborative management platform includes a first cloud resource pool, a second cloud resource pool, and a data operation layer;

The cloud-network collaborative management platform receives basic information and extended information of the target transmission line;

Uploading the basic information to a first cloud resource pool, and obtaining a physical trust degree through calculation in the first cloud resource pool;

Uploading the extended information to a second cloud resource pool, and obtaining an external trust degree through calculation in the second cloud resource pool;

Inputting the physical trust and the external trust into the data operation layer, fusing the physical trust and the external trust, and obtaining the operation data of the target transmission line;

The operating data is compared with a preset threshold value. If the operating data is greater than the preset threshold value, the target transmission line is added to the cloud-network collaborative management platform.

Claims (4)

1. The cloud network collaborative operation method in the power industry is characterized by comprising the following steps of:

Receiving an instruction for adding a target power transmission line into a cloud network collaborative management platform; the cloud network collaborative management platform comprises a first cloud resource pool, a second cloud resource pool and a data operation layer;

the cloud network collaborative management platform receives basic information and extension information of the target power transmission line; the basic information includes: target tower coordinates, target tower height, and target tower structure; the extension information includes: meteorological parameters, air humidity, wind and geographic region type;

Uploading the basic information to a first cloud resource pool, and obtaining the physical trust degree in the first cloud resource pool through calculation, wherein the method comprises the following steps: acquiring an existing power transmission line similar to the target tower structure in the first cloud resource pool according to the target tower structure; inquiring historical operation data of the existing transmission line; screening out high-quality existing power transmission lines according to the historical operation data, and inquiring average tower coordinates and average tower heights corresponding to the high-quality existing power transmission lines; obtaining the physical trust degree according to the numerical relation between the target tower coordinates and the target tower heights, the average tower coordinates and the average tower heights, wherein the physical trust degree comprises the following steps: the physical confidence level Q1 is calculated according to the following formula: Where (x _D,y_D) represents the target tower coordinates, h _D represents the target tower height,/> Representing average tower coordinates,/>Representing the average tower height, wherein alpha and beta are weight parameters;

Uploading the expansion information to a second cloud resource pool, and obtaining external trust through calculation in the second cloud resource pool, wherein the method comprises the following steps: acquiring an existing power transmission line corresponding to the geographic region type in the second cloud resource pool according to the geographic region type; querying historical fault data of the existing transmission line; the historical fault data comprises fault types and fault frequencies; inputting the fault type, the fault frequency and the meteorological parameters into a neural network model to obtain external trust, wherein the method comprises the following steps of: inputting the meteorological parameters into a deep learning model to obtain a model output result; inputting the fault type, the fault frequency and the model output result into a multi-layer perceptron to obtain external trust;

Inputting the physical trust degree and the external trust degree into the data operation layer, and fusing the physical trust degree and the external trust degree to obtain operation data of the target transmission line;

And comparing the operation data with a preset threshold, and if the operation data is larger than the preset threshold, adding the target power transmission line into the cloud network collaborative management platform.

2. The method for cloud network co-operation in the power industry according to claim 1, wherein the obtaining, according to the target tower structure, an existing power transmission line in the first cloud resource pool similar to the target tower structure includes:

acquiring a first structural image of the target tower;

acquiring a second structural image of any one of the existing power transmission lines;

Comparing the similarity between the first structural image and the second structural image by adopting an SSIM algorithm;

And if the similarity is higher than a similarity threshold, the corresponding existing transmission line is an existing transmission line similar to the target tower structure.

3. The cloud network collaborative operation method of the power industry according to claim 1, wherein the inputting the physical trust and the external trust to the data operation layer, fusing the physical trust and the external trust, obtaining operation data of the target transmission line, includes:

the operation data S is calculated according to the following formula:

S＝Q1·Q2

Where Q1 represents physical confidence and Q2 represents external confidence.

4. The cloud network collaborative operation system of the power industry is characterized in that the system comprises:

the instruction acquisition module is used for receiving an instruction for adding the target transmission line into the cloud network collaborative management platform; the cloud network collaborative management platform comprises a first cloud resource pool, a second cloud resource pool and a data operation layer;

The information receiving module is used for receiving basic information and extension information of the target power transmission line by the cloud network collaborative management platform; the basic information includes: target tower coordinates, target tower height, and target tower structure; the extension information includes: meteorological parameters, air humidity, wind and geographic region type;

The first computing module is used for uploading the basic information to a first cloud resource pool, obtaining physical trust through computing in the first cloud resource pool, and is also used for: acquiring an existing power transmission line similar to the target tower structure in the first cloud resource pool according to the target tower structure; inquiring historical operation data of the existing transmission line; screening out high-quality existing power transmission lines according to the historical operation data, and inquiring average tower coordinates and average tower heights corresponding to the high-quality existing power transmission lines; obtaining the physical trust degree according to the numerical relation between the target tower coordinates and the target tower heights, the average tower coordinates and the average tower heights, wherein the physical trust degree comprises the following steps: the physical confidence level Q1 is calculated according to the following formula: Where (x _D,y_D) represents the target tower coordinates, h _D represents the target tower height,/> Representing average tower coordinates,/>Representing the average tower height, wherein alpha and beta are weight parameters;

The second computing module is used for uploading the extension information to a second cloud resource pool, and obtaining external trust through computing in the second cloud resource pool, and is also used for: acquiring an existing power transmission line corresponding to the geographic region type in the second cloud resource pool according to the geographic region type; querying historical fault data of the existing transmission line; the historical fault data comprises fault types and fault frequencies; inputting the fault type, the fault frequency and the meteorological parameters into a neural network model to obtain external trust, wherein the method comprises the following steps of: inputting the meteorological parameters into a deep learning model to obtain a model output result; inputting the fault type, the fault frequency and the model output result into a multi-layer perceptron to obtain external trust;

The third calculation module is used for inputting the physical trust degree and the external trust degree into the data operation layer, and fusing the physical trust degree and the external trust degree to obtain operation data of the target power transmission line;

And the data processing module is used for comparing the operation data with a preset threshold value, and if the operation data is larger than the preset threshold value, adding the target power transmission line into the cloud network collaborative management platform.