CN116961217A - Power equipment multistage cooperative early warning method and system based on state monitoring - Google Patents

Abstract

The invention discloses a multi-level collaborative early warning method and system for power equipment based on status monitoring, and belongs to the technical field of power equipment status assessment. The method of the present invention includes: determining the risk value and risk warning level of a single power equipment in the substation, and generating a report for any single power equipment in the substation based on the status monitoring data, risk value and risk warning level. Information; obtain the whole network operation information in the substation and the meteorological information in the substation area, and determine the early warning information in the substation based on the reported information, the whole network operation information and the meteorological information; based on the early warning information, generate Share early warning information and deliver the shared early warning information to the power equipment in the substation to complete multi-level collaborative fault early warning for the power equipment in the substation. The invention improves the accuracy and macroscopicity of substation equipment early warning.

Description

Multi-level collaborative early warning method and system for power equipment based on condition monitoring

Technical field

The present invention relates to the technical field of power equipment condition assessment, and more specifically, to a multi-level collaborative early warning method and system for power equipment based on condition monitoring.

Background technique

At present, the source of early warning information for primary substation equipment is basically limited to the status information of a single equipment itself. Power grid companies share equipment risk information throughout the network through simple methods such as reporting equipment family defects across the network and inspecting equipment status before special working conditions or extreme weather. Not only is there a lack of risk information sharing between equipment within the substation, but there is also a lack of risk information sharing between multiple substations in the regional power grid, resulting in incomplete early warning information and inaccurate early warning results.

In addition, the current early warning objects are limited to single equipment, and there is a lack of early warning for macro-targets such as entire station equipment and regional power grid equipment, making it difficult to meet the needs for different levels of reliability in the intelligent operation of the power grid.

Contents of the invention

In response to the above problems, the present invention proposes a multi-level collaborative early warning method for power equipment based on condition monitoring, including:

Perform condition monitoring on a single power equipment in the substation to obtain status monitoring data. Calculate the failure probability of the single power equipment based on the status monitoring data and the probability density function of the historical single power equipment failure. Based on the failure probability , the historical importance coefficient and family defect analysis data of the substation are used to determine the risk value and risk warning level of a single power equipment in the substation, and based on the condition monitoring data, risk value and risk warning level, generate a Report information of any single power equipment;

Obtain the entire network operation information in the substation and the meteorological information in the substation area, and determine the early warning information in the substation based on the reported information, the entire network operation information and the meteorological information;

Based on the early warning information, shared early warning information is generated and sent to the power equipment in the substation to complete multi-level collaborative fault early warning for the power equipment in the substation.

Optional, the reported information of a single power equipment includes the following: the fault location, fault type, fault status quantity, ledger, load current, and dissolved gas content information in the equipment oil at the time of the fault.

Optional, early warning information includes the following: faulty equipment, fault location of the faulty equipment, and fault status quantity of the faulty equipment.

Optionally, based on the early warning information, generate shared early warning information, including:

Based on the early warning information, the probability density distribution function when a single power equipment in the substation fails is determined, and based on the reported information, the load current coefficient of the single power equipment in the substation is calculated, as well as the family defect analysis data of the substation. , based on the calculation results of the load current coefficient, the family defect analysis data and the probability density distribution function, generate shared early warning information.

Optional, shared early warning information includes the following: importance coefficient, risk threshold, family defect, load current coefficient, and probability density distribution function.

Optionally, the method further includes: sending the shared early warning information to other substations within a preset range except the current substation.

On the other hand, the present invention also proposes a multi-level collaborative early warning system for power equipment based on condition monitoring, including:

An information acquisition unit is used to perform status monitoring on a single power equipment in the substation to obtain status monitoring data, and calculate the failure probability of a single power equipment based on the status monitoring data and the probability density function of historical single power equipment failures. , based on the failure probability, the historical importance coefficient of the substation and the family defect analysis data, determine the risk value and risk warning level of a single power equipment in the substation, and based on the condition monitoring data, risk value and risk warning level , generate reporting information for any single power equipment in the substation;

A computing unit configured to obtain the entire network operation information in the substation and the meteorological information in the substation area, and determine the early warning information in the substation based on the reported information, the entire network operation information and the meteorological information;

An early warning unit is configured to generate shared early warning information based on the early warning information and deliver the shared early warning information to the power equipment in the substation to complete multi-level collaborative fault early warning for the power equipment in the substation.

Optional, the reported information of a single power equipment includes the following: the fault location, fault type, fault status quantity, ledger, load current, and dissolved gas content information in the equipment oil at the time of the fault.

Optional, early warning information includes the following: faulty equipment, fault location of the faulty equipment, and fault status quantity of the faulty equipment.

Optionally, based on the early warning information, generate shared early warning information, including:

Based on the early warning information, the probability density distribution function when a single power equipment in the substation fails is determined, and based on the reported information, the load current coefficient of the single power equipment in the substation is calculated, as well as the family defect analysis data of the substation. , based on the calculation results of the load current coefficient, the family defect analysis data and the probability density distribution function, generate shared early warning information.

Optional, shared early warning information includes the following: importance coefficient, risk threshold, family defect, load current coefficient, and probability density distribution function.

Optionally, the early warning unit is also configured to send the shared early warning information to other substations within the preset range except the current substation.

In yet another aspect, the present invention also provides a computing device, including: one or more processors;

Processor, used to execute one or more programs;

When the one or more programs are executed by the one or more processors, the method as described above is implemented.

On the other hand, the present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed, the method as described above is implemented.

Compared with the prior art, the beneficial effects of the present invention are:

The present invention provides a multi-level collaborative early warning method for power equipment based on status monitoring, which includes: performing status monitoring on a single power equipment in the substation to obtain status monitoring data, based on the status monitoring data and history The probability density function of a single power equipment failure is calculated to obtain the failure probability of a single power equipment. Based on the failure probability, the historical importance coefficient of the substation and the family defect analysis data, the risk value and risk value of a single power equipment in the substation are determined. Risk warning level, and based on the status monitoring data, risk value and risk warning level, generate reporting information for any single power equipment in the substation; obtain the entire network operation information in the substation and meteorological information in the substation area , based on the reported information, the entire network operation information and meteorological information, determine the early warning information in the substation; based on the early warning information, generate shared early warning information and send the shared early warning information to the electric power in the substation equipment to complete multi-level collaborative fault early warning for the power equipment in the substation. The present invention overcomes the previous shortcomings of single-equipment early warning, realizes multi-level early warning and risk information sharing across the entire network, and improves the accuracy and macroscopicity of substation equipment early warning.

Description of the drawings

Figure 1 is a flow chart of the method of the present invention;

Figure 2 is a schematic flow chart of an embodiment of the method of the present invention;

Figure 3 is a structural diagram of the system of the present invention.

Detailed ways

Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided so that this disclosure will be thorough and complete. invention, and fully convey the scope of the invention to those skilled in the art. The terminology used in the exemplary embodiments represented in the drawings does not limit the invention. In the drawings, identical units/elements use the same reference numerals.

Unless otherwise defined, the terms (including scientific and technical terms) used herein have the commonly understood meaning to one of ordinary skill in the art. In addition, it is understood that terms defined in commonly used dictionaries should be understood to have consistent meanings in the context of their relevant fields and should not be understood as having an idealized or overly formal meaning.

Example 1:

At present, the source of early warning information for primary substation equipment is basically limited to the status information of a single equipment itself. Not only is there a lack of risk information sharing between equipment within the substation, but there is also a lack of risk information sharing between multiple substations in the regional power grid, making it difficult to Meet the requirements for different levels of reliability in the intelligent operation of the power grid.

The present invention aims to establish a hierarchical collaborative early warning method system, clarify the division of labor and collaborative methods of collaborative early warning tasks between the station and the centralized control station, overcome the shortcomings of only a single device early warning in the past, realize multi-level early warning and risk information sharing throughout the network, and improve The present invention proposes a multi-level collaborative early warning method for power equipment based on condition monitoring, as shown in Figure 1, which includes:

Step 1. Perform condition monitoring on a single power equipment in the substation to obtain status monitoring data. Calculate the failure probability of a single power equipment based on the status monitoring data and the historical probability density function of a single power equipment failure. Based on the The failure probability, the historical importance coefficient of the substation and the family defect analysis data are used to determine the risk value and risk warning level of a single power equipment in the substation, and based on the condition monitoring data, risk value and risk warning level, generate all Report information of any single power equipment in the substation;

Step 2: Obtain the entire network operation information in the substation and the meteorological information in the substation area, and determine the early warning information in the substation based on the reported information, the entire network operation information and the meteorological information;

Step 3: Based on the early warning information, generate shared early warning information and deliver the shared early warning information to the power equipment in the substation to complete multi-level collaborative fault early warning for the power equipment in the substation.

Among them, the reported information of a single power equipment includes the following: the fault location, fault type, fault status quantity, ledger, load current and dissolved gas content information in the equipment oil at the time of the fault.

Among them, the early warning information includes the following: faulty equipment, fault location of the faulty equipment, and fault status quantity of the faulty equipment.

Wherein, based on the early warning information, shared early warning information is generated, including:

Based on the early warning information, the probability density distribution function when a single power equipment in the substation fails is determined, and based on the reported information, the load current coefficient of the single power equipment in the substation is calculated, as well as the family defect analysis data of the substation. , based on the calculation results of the load current coefficient, the family defect analysis data and the probability density distribution function, generate shared early warning information.

Among them, the shared early warning information includes the following: importance coefficient, risk threshold, family defect, load current coefficient and probability density distribution function.

The method further includes: sending the shared early warning information to other substations within a preset range except the current substation.

The following is a further explanation of this busyness based on specific applications:

The present invention can be specifically applied to station ends, centralized control stations and regional substations. Its specific application process is shown in Figure 2, which specifically includes the following:

Based on the series model and common cause failure theory in reliability, and taking common meteorological conditions, common power grid operating conditions, common manufacturing processes and other factors as starting points, a station-centralized control station collaborative early warning method system was established. The station is responsible for the early warning of individual equipment in the substation, and reports the early warning information (including equipment at risk of failure, fault location, fault type, etc.) to the centralized control station; the centralized control station processes the information reported from the station and the entire network operation Comprehensive analysis of information and regional meteorological information, perform whole-station equipment warning and multi-station equipment warning, and send necessary shared warning information to each station (for example, equipment family defect warning, etc.), and even send alarm thresholds to the station Adjust the information to convey the macro risk information of the power grid. At the same time, the centralized control station carries out statistical analysis and equipment importance assessment of the entire network equipment, and issues basic data such as statistical probability distribution and importance of equipment required for early warning to the station.

Among them, the centralized control station and regional substations jointly guide the station to calculate the risk value of individual equipment.

Collaborative methods mainly include the following:

Site end:

Calculate the failure probability of a single device;

Report station equipment fault information, fault status quantity, fault location, equipment ledger, and load current to the centralized control station;

Central control station:

Adjustment of importance coefficients;

Calculation of load current coefficient;

familial defect analysis;

Issue information such as importance coefficient, risk threshold, family defects, load current coefficient, and probability density distribution function to the station;

Upload faulty equipment information to regional substations;

Regional substation:

Statistically analyze the probability density distribution function under fault conditions;

Issue the probability density distribution function to the centralized control station.

The specific implementation steps of the above-mentioned specific applications include the following:

Step 1: Station-side transformers C ₁ , C ₂ ,..., C _n-1 , C _n upload basic information such as fault equipment ledger information, fault location, fault content x ₀ and other basic information to centralized control stations B ₁ and B ₂ ,…,B _k-1 ,B _k (k<n), and then each centralized control station uploads the above information to the regional substation.

Step 2: Regional substation A collects the dissolved gas data in oil of all transformers in the area under fault conditions, statistically calculates the transformer fault probability density distribution function f _D (y), and sends it to centralized control stations B ₁ , B ₂ , …,B _k-1 ,B _k .

Step 3: The centralized control station B ₁ , B ₂ ,…, B _k-1 , B _k receives the statistical probability density distribution function f _D (y) from the regional substation A, and sends it to the station-side transformer C ₁ , C ₂ ,…,C _n-1 ,C _n .

Step 4: The station-side transformers C ₁ , C ₂ ,…, C _n-1 , C _n calculate the failure probability F of each equipment based on the online monitored dissolved gas in the oil, and combine the failure probability F of each equipment and the dissolved gas in the oil The gas value x ₀ and load current I are uploaded to the centralized control station B ₁ , B ₂ ,..., B _k-1 , B _k . The calculation method of failure probability refers to patent 202211466906.3. The specific process is as follows:

Assume that the probability density distribution function f _D (y) obtained statistically by regional substation A is in the form of a lognormal distribution. The dissolved gas content in the oil of the transformer measured at a certain time is x ₀ , and the failure probability of the transformer is the probability density function. The definite integral value of f _D (y) under x ₀ is shown in equation (1).

Among them, y is the dissolved gas content in the oil under fault, σ is the standard deviation of the probability density distribution function f _D (y), μ is the mean value of the probability density distribution function f _D (y), and x ₀ is the online monitoring at a certain time Dissolved gas content in oil.

Step 5: The centralized control station B ₁ , B ₂ ,..., B _k-1 , B _k allocates the important coefficient Q of the equipment according to the station equipment asset P and the operating load current eta _i (t), where the asset factor P includes the equipment There are three aspects: value P ₁ , y user level P ₂ , and equipment status P ₃ . The calculation method is as follows:

Q(t)＝P×η _i (t) (2)

Among them, i=1-3, 1 is the equipment value, 2 is the user level, and 3 is the equipment status; W _Pi is the asset factor; P _i is a certain asset factor; P is the asset. See Table 1 for the description of asset level division.

Table 1

The load current coefficient calculation formula is as follows:

Among them, i(t) is the load current, I _min is 0.4 times of the rated current _IN , and I _max is 0.8 times of the rated current _IN .

Step 6: Centralized control stations B ₁ , B ₂ ,…, B _k-1 , B _k analyze whether there are family defects in the equipment based on the fault information uploaded by station C ₁ , C ₂ ,…, C _n-1 , C _n , if the same manufacturer's transformer fails multiple times during a maintenance cycle, it is judged that the manufacturer's equipment has a family fault. At this time, the family defect information and adjustment coefficient T need to be sent to the corresponding station equipment. The family defect adjustment coefficient The setting value of T is shown in Table 2 below.

Table 2

Step 7: Central control stations B ₁ , B ₂ ,…, B _k-1 , B _k set the early warning thresholds for each early warning level. Level I early warning equipment can continue to operate but should strengthen monitoring during operation. The risk threshold is 3%; Level II early warning equipment should focus on monitoring the operation and promptly arrange power outage maintenance, the risk threshold is 9%; Level III early warning equipment should arrange power outage maintenance as soon as possible, the risk threshold is 27%; IV early warning equipment should immediately arrange power outage maintenance, the risk threshold is 81%.

Step 8: Station side C ₁ , C ₂ ,…, C _n-1 , C _n are based on the importance coefficient Q and family defects issued by the centralized control station B ₁ , B ₂ ,…, B _k-1 , B _k Adjust the coefficient T to calculate the equipment risk value R(t). The calculation formula is as follows. Compare it with the risk threshold and output the early warning level of the station equipment, and upload the risk value and early warning level to the centralized control station for reference by maintenance personnel;

R(t)＝F(t)×Q(t)×T (5)

Among them, R(t) is the equipment risk value at a certain time, F(t) is the failure probability of the equipment at a certain time, and Q(t) is the failure probability at a certain time.

The present invention overcomes the previous shortcomings of single-equipment early warning, realizes multi-level early warning and risk information sharing across the entire network, and improves the accuracy and macroscopicity of substation equipment early warning.

Example 2:

The present invention also proposes a multi-level collaborative early warning system 200 for power equipment based on condition monitoring, as shown in Figure 3, including:

The information collection unit 201 is used to perform status monitoring on a single power equipment in the substation to obtain status monitoring data, and calculate the fault of a single power equipment based on the status monitoring data and the probability density function of historical single power equipment failures. Probability, based on the failure probability, the historical importance coefficient of the substation and family defect analysis data, determine the risk value and risk warning level of a single power equipment in the substation, and based on the condition monitoring data, risk value and risk warning Level, generate reporting information for any single power equipment in the substation;

The computing unit 202 is used to obtain the entire network operation information in the substation and the meteorological information in the substation area, and determine the early warning information in the substation based on the reported information, the entire network operation information and the meteorological information;

The early warning unit 203 is configured to generate shared early warning information based on the early warning information and deliver the shared early warning information to the power equipment in the substation to complete multi-level collaborative fault early warning for the power equipment in the substation.

Among them, the reported information of a single power equipment includes the following: the fault location, fault type, fault status quantity, ledger, load current and dissolved gas content information in the equipment oil at the time of the fault.

Among them, the early warning information includes the following: faulty equipment, fault location of the faulty equipment, and fault status quantity of the faulty equipment.

Wherein, based on the early warning information, shared early warning information is generated, including:

Based on the early warning information, the probability density distribution function when a single power equipment in the substation fails is determined, and based on the reported information, the load current coefficient of the single power equipment in the substation is calculated, as well as the family defect analysis data of the substation. , based on the calculation results of the load current coefficient, the family defect analysis data and the probability density distribution function, generate shared early warning information.

Among them, the shared early warning information includes the following: importance coefficient, risk threshold, family defect, load current coefficient and probability density distribution function.

Among them, the early warning unit 203 is also used to send the shared early warning information to other substations within the preset range except the current substation.

The present invention overcomes the previous shortcomings of single-equipment early warning, realizes multi-level early warning and risk information sharing across the entire network, and improves the accuracy and macroscopicity of substation equipment early warning.

Example 3:

Based on the same inventive concept, the present invention also provides a computer device. The computer device includes a processor and a memory. The memory is used to store a computer program. The computer program includes program instructions. The processor is used to execute the Program instructions stored on computer storage media. The processor may be a central processing unit (Central Processing Unit, CPU), or other general-purpose processor, digital signal processor (Digital Signal Processor, DSP), application specific integrated circuit (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate array ( Field-Programmable GateArray (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., which are the computing core and control core of the terminal. It is suitable for implementing one or more instructions, specifically suitable for loading. And execute one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function to implement the steps of the method in the above embodiment.

Example 4:

Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in a computer device and is used to store programs and data. It can be understood that the computer-readable storage medium here may include a built-in storage medium in the computer device, and of course may also include an extended storage medium supported by the computer device. The computer-readable storage medium provides storage space, and the storage space stores the operating system of the terminal. Furthermore, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space. These instructions may be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory. One or more instructions stored in the computer-readable storage medium can be loaded and executed by the processor to implement the steps of the method in the above embodiments.

Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the literal scripting language JavaScript.

The invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce a use A device for realizing the functions specified in one process or multiple processes of the flowchart and/or one block or multiple blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory that causes a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction means, the instructions The device implements the functions specified in a process or processes of the flowchart and/or a block or blocks of the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device, causing a series of operating steps to be performed on the computer or other programmable device to produce computer-implemented processing, thereby executing on the computer or other programmable device. Instructions provide steps for implementing the functions specified in a process or processes of a flowchart diagram and/or a block or blocks of a block diagram.

Although the preferred embodiments of the present invention have been described, those skilled in the art will be able to make additional changes and modifications to these embodiments once the basic inventive concepts are apparent. Therefore, it is intended that the appended claims be construed to include the preferred embodiments and all changes and modifications that fall within the scope of the invention.

Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the invention. In this way, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims (14)

1. A multi-level collaborative early warning method for power equipment based on condition monitoring, characterized in that the method includes: Perform condition monitoring on a single power equipment in the substation to obtain status monitoring data. Calculate the failure probability of the single power equipment based on the status monitoring data and the probability density function of the historical single power equipment failure. Based on the failure probability , the historical importance coefficient and family defect analysis data of the substation are used to determine the risk value and risk warning level of a single power equipment in the substation, and based on the condition monitoring data, risk value and risk warning level, generate a Report information of any single power equipment; Obtain the entire network operation information in the substation and the meteorological information in the substation area, and determine the early warning information in the substation based on the reported information, the entire network operation information and the meteorological information; Based on the early warning information, shared early warning information is generated and sent to the power equipment in the substation to complete multi-level collaborative fault early warning for the power equipment in the substation. 2. The method according to claim 1, characterized in that the reported information of the single power equipment includes the following: fault location, fault type, fault status quantity, ledger, load current and fault of the single power equipment. Information on the content of dissolved gases in equipment oil at all times. 3. The method according to claim 1, characterized in that the early warning information includes the following: faulty equipment, fault location of the faulty equipment, and fault status quantity of the faulty equipment. 4. The method according to claim 1, characterized in that generating shared early warning information based on the early warning information includes: Based on the early warning information, the probability density distribution function when a single power equipment in the substation fails is determined, and based on the reported information, the load current coefficient of the single power equipment in the substation is calculated, as well as the family defect analysis data of the substation. , based on the calculation results of the load current coefficient, the family defect analysis data and the probability density distribution function, generate shared early warning information. 5. The method according to claim 1, characterized in that the shared early warning information includes the following: importance coefficient, risk threshold, family defect, load current coefficient and probability density distribution function. 6. The method according to claim 1, characterized in that the method further includes: sending the shared early warning information to other substations within a preset range except the current substation. 7. A multi-level collaborative early warning system for power equipment based on condition monitoring, characterized in that the system includes: An information acquisition unit is used to perform status monitoring on a single power equipment in the substation to obtain status monitoring data, and calculate the failure probability of a single power equipment based on the status monitoring data and the probability density function of historical single power equipment failures. , based on the failure probability, the historical importance coefficient of the substation and the family defect analysis data, determine the risk value and risk warning level of a single power equipment in the substation, and based on the condition monitoring data, risk value and risk warning level , generate reporting information for any single power equipment in the substation; A computing unit configured to obtain the entire network operation information in the substation and the meteorological information in the substation area, and determine the early warning information in the substation based on the reported information, the entire network operation information and the meteorological information; An early warning unit is configured to generate shared early warning information based on the early warning information and deliver the shared early warning information to the power equipment in the substation to complete multi-level collaborative fault early warning for the power equipment in the substation. 8. The system according to claim 7, characterized in that the reported information of the single power equipment includes the following: fault location, fault type, fault status quantity, ledger, load current and fault of the single power equipment. Information on the content of dissolved gases in equipment oil at all times. 9. The system according to claim 7, wherein the early warning information includes the following: faulty equipment, fault location of the faulty equipment, and fault status quantity of the faulty equipment. 10. The system according to claim 7, characterized in that generating shared early warning information based on the early warning information includes: Based on the early warning information, the probability density distribution function when a single power equipment in the substation fails is determined, and based on the reported information, the load current coefficient of the single power equipment in the substation is calculated, as well as the family defect analysis data of the substation. , based on the calculation results of the load current coefficient, the family defect analysis data and the probability density distribution function, generate shared early warning information. 11. The system according to claim 7, wherein the shared early warning information includes the following: importance coefficient, risk threshold, family defect, load current coefficient and probability density distribution function. 12. The system according to claim 7, wherein the early warning unit is further configured to send the shared early warning information to other substations within a preset range except the current substation. 13. A computer device, characterized by comprising: one or more processors; Processor, used to execute one or more programs; When the one or more programs are executed by the one or more processors, the method as claimed in any one of claims 1-6 is implemented. 14. A computer-readable storage medium, characterized in that a computer program is stored thereon, and when the computer program is executed, the method according to any one of claims 1-6 is implemented.