A multi-service converged data risk assessment method and system

Abstract

The present application relates to the technical field of big data analysis, and discloses a multi-service integrated data risk assessment method and system, comprising: a global heterogeneous data acquisition module, a risk category comprehensive judgment module, a solid risk first analysis module, a running risk second analysis module, and a risk assessment and early warning output module; the risk categories in a target region are comprehensively judged based on the environmental data of the target region; a first data calling layer calling instruction is sent based on the risk category comprehensive judgment result of the target region, and low-load solid risk analysis of the target region is carried out according to the data output by the first data calling layer; a second data calling layer calling instruction is sent based on the risk category comprehensive judgment result of the target region, and high-load running risk analysis of the target region is carried out according to the data output by the second data calling layer; the change of the risk level is monitored in real time, and it is ensured that the risk can be responded to in time and effectively.

Description

Technical Field

[0001] This invention relates to the field of big data analytics, and more specifically to a data risk assessment method and system that integrates multiple business functions. Background Technology

[0002] Throughout the development of the power industry, data risk assessment has always been a crucial link for power supply companies to ensure the stable operation of their businesses. In the early days, power supply business was relatively simple, mainly focusing on power supply and basic equipment maintenance. Data volume was small and the structure was simple. Risk assessment methods, primarily based on manual statistics and experience, were generally sufficient. Power supply companies only needed to periodically check the operating data of a few key pieces of equipment, relying on engineers' experience to identify potential risks, lacking systematic and scientific data processing methods. With the advancement of smart grid construction and the deepening of digital transformation, the business scope of power supply companies has expanded significantly. Data generation is extremely rapid; for example, smart meters generate electricity consumption data every minute or even every second, and power equipment sensors continuously output equipment operating status information. This data is not only massive in quantity but also complex in structure, covering multi-dimensional information from basic power supply data to environmental parameters. Traditional risk assessment methods are inadequate when faced with such large-scale data, making it difficult to accurately and efficiently identify potential risks.

[0003] Currently, most power supply companies' data risk assessment methods for multi-service integration focus on the power business data itself, such as equipment operating parameters and user electricity consumption data, while neglecting the significant impact of environmental parameters on power system operation and business development. Environmental factors such as meteorological conditions, air quality, and geographical environment are closely related to power equipment performance, user electricity consumption behavior, and grid operational stability. Furthermore, existing data risk assessment methods often conduct general assessments of the entire power supply area, lacking refined regional division and targeted analysis, making it difficult to accurately reflect the risk status under different characteristics. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a multi-service integrated data risk assessment system to solve the problems existing in the background art.

[0005] This invention provides the following technical solution: a multi-service integrated data risk assessment system, comprising: a global heterogeneous data acquisition module, a risk category comprehensive judgment module, a solid risk first analysis module, an operational risk second analysis module, and a risk assessment and early warning output module;

[0006] The global heterogeneous data acquisition module includes an environmental data acquisition layer and a power supply data acquisition layer. The power supply data acquisition layer includes a first data retrieval layer and a second data retrieval layer, which acquires heterogeneous data within the target area through sensors.

[0007] The risk category comprehensive judgment module comprehensively judges the risk category within the target area based on the environmental data of the target area output by the environmental data acquisition layer and the active power of the target area output by the power supply data acquisition layer.

[0008] The solid-state risk first analysis module, based on the comprehensive judgment result of the risk category of the target area, issues a call instruction to the first data call layer, and performs low-load solid-state risk analysis on the target area according to the data output by the first data call layer;

[0009] The second operational risk analysis module, based on the comprehensive judgment result of the risk category of the target area, issues a call instruction to the second data call layer, and performs a high-load operational risk analysis on the target area based on the data output by the second data call layer;

[0010] The risk assessment and early warning output module performs risk assessment based on the solid risk analysis results and operational risk analysis results of the target area, and sends early warning information to the device terminal based on the assessment results.

[0011] Preferably, the global heterogeneous data acquisition module includes an environmental data acquisition layer and a power supply data acquisition layer, the specific contents of which are as follows:

[0012] The environmental data acquisition layer collects environmental data of the target area of ​​the power supply company through temperature and humidity sensors. The environmental data includes temperature data and humidity data of the target area.

[0013] The power supply data acquisition layer collects the active power output value of the power supply company when transmitting power to the target area through an active power transmitter. The power supply data acquisition layer includes a first data call layer and a second data call layer.

[0014] When the target area is detected as having a low load, the first data calling layer receives the calling instruction and outputs the calling data of the first data calling layer.

[0015] When the target area is detected as having a high load, the second data calling layer receives the calling instruction and outputs the calling data of the second data calling layer.

[0016] Preferably, the specific content of the risk category comprehensive determination module is as follows:

[0017] Based on historical data, preset temperature correction coefficients for different temperature ranges and humidity correction coefficients for different humidity ranges;

[0018] The system receives temperature and humidity data of the target area from the environmental data acquisition layer. The temperature and humidity data represent the temperature and humidity values ​​at different times at preset n sampling points. The system projects the temperature and humidity data into preset different temperature ranges and different humidity ranges to obtain the corresponding temperature correction coefficients and humidity correction coefficients. The system then calculates the average temperature correction coefficient and average humidity correction coefficient of the target area.

[0019] The active power of the target area is received from the power supply data acquisition layer. The active power represents the active power value at different times obtained at n preset sampling points. The average active power of the target area is obtained by averaging.

[0020] The average active power of the target area is combined with the average temperature correction factor and the average humidity correction factor to obtain the output value of the risk category comprehensive judgment module. When the output value is less than the minimum value of the preset normal power range, the risk category comprehensive judgment result is low load. When the output value is greater than the maximum value of the preset normal power range, the risk category comprehensive judgment result is high load.

[0021] Preferably, the specific content of the first solid-state risk analysis module is as follows:

[0022] When the comprehensive risk category assessment result of the target area is low load, a call instruction is issued to the first data call layer to obtain the data output by the first data call layer;

[0023] The actual load rate of the lines and the actual operating capacity of the substations under low load conditions in the target area are weighted and allocated, respectively, as follows: and ;

[0024] The load mismatch degree under low load conditions is obtained by comparing the ratio of the actual load rate of the line to the ideal load rate of the line under low load conditions in the target area.

[0025] The first difference is obtained by performing a difference analysis between the actual operating capacity of the substation under low load conditions and the reasonable operating capacity under low load conditions. The second difference is obtained by performing a difference analysis between the maximum capacity of the substation and the actual operating capacity of the substation under low load conditions. The capacity mismatch degree under low load conditions is obtained based on the ratio of the first difference and the second difference.

[0026] Based on weight allocation, load mismatch, and capacity mismatch, a low-load solid-state risk analysis is performed on the target area to obtain the low-load solid-state risk analysis results, which are then sent to the risk assessment and early warning output module.

[0027] Preferably, the specific content of the second operational risk analysis module is as follows:

[0028] When the comprehensive risk category assessment result of the target area is high load, a call instruction for the second data call layer is issued to obtain the data output by the second data call layer;

[0029] The actual operating voltage and frequency of the line under high load conditions in the target area are weighted and allocated, respectively, as follows: and ;

[0030] The voltage non-uniformity under high load conditions is calculated by taking the difference between the actual operating voltage and the rated voltage of the line under high load conditions as the numerator and the difference between the highest and lowest allowable voltages of the line as the denominator.

[0031] The frequency non-uniformity under high load conditions is obtained by taking the difference between the actual operating frequency and the rated frequency of the line under high load conditions as the numerator and the difference between the highest and lowest allowable frequencies of the line as the denominator.

[0032] Based on weight allocation, voltage non-uniformity, and frequency non-uniformity, a high-load operation risk analysis is performed on the target area to obtain the high-load operation risk analysis results, which are then sent to the risk assessment and early warning output module.

[0033] Preferably, the specific contents of the risk assessment and early warning output module are as follows:

[0034] When the load is low, a risk assessment is performed based on the solid-state risk analysis results of the target area. When the solid-state risk analysis result is greater than or equal to the preset low-load analysis threshold, the assessment result is that the target area is at risk, and a warning message is sent to the device terminal based on the assessment result. Conversely, when the solid-state risk analysis result is less than the preset low-load analysis threshold, the assessment result is that the target area is not at risk, and no warning message is sent.

[0035] When under high load, risk assessment is performed based on the operational risk analysis results of the target area. If the operational risk analysis result is greater than or equal to the preset high load analysis threshold, the assessment result is that the target area is at risk, and a warning message is sent to the equipment terminal based on the assessment result. Conversely, if the operational risk analysis result is less than the preset high load analysis threshold, the assessment result is that the target area is not at risk, and no warning message is sent.

[0036] A data risk assessment method for multi-service integration includes the following steps:

[0037] Step S01: Collect heterogeneous data within the target area using sensors;

[0038] Step S02: Based on the environmental data and active power of the target area, comprehensively determine the risk category within the target area;

[0039] Step S03: Based on the comprehensive judgment result of the risk category of the target area, issue a call instruction for the first data call layer, and perform low-load solid-state risk analysis on the target area according to the data output by the first data call layer;

[0040] Step S04: Based on the comprehensive judgment result of the risk category of the target area, issue a call instruction for the second data call layer, and perform a high-load operation risk analysis on the target area based on the data output by the second data call layer;

[0041] Step S05: Conduct a risk assessment based on the solid-state risk analysis results and operational risk analysis results of the target area, and send the early warning information to the equipment terminal based on the assessment results.

[0042] The technical effects and advantages of this invention are as follows:

[0043] This invention comprehensively determines the risk category within the target area based on environmental data and active power of the target area. It combines conventional power supply parameters with environmental parameters of the target area to achieve the integration of multiple services, breaking through the limitations of a single data dimension. This provides a more comprehensive and accurate decision-making basis for the planning, operation, maintenance and energy efficiency optimization of the power system, and realizes a comprehensive assessment of the risks in the target area.

[0044] Through low-load solid-state risk analysis and high-load operation risk analysis, a detailed assessment of the potential risks in the target area under different load conditions was conducted. Under low load conditions, the focus was mainly on the matching of line load rate and substation operating capacity to avoid risks caused by idle resources or improper configuration. Under high load conditions, the emphasis was placed on the stability of line operating voltage and frequency to ensure the quality and reliability of power supply. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of the structure of a multi-business integrated data risk assessment system.

[0046] Figure 2 This is a flowchart illustrating a data risk assessment method that integrates multiple business functions. Detailed Implementation

[0047] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. In addition, the forms of the various structures described in the following embodiments are merely illustrative. The multi-service converged data risk assessment method and system involved in the present invention are not limited to the structures described in the following embodiments. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] like Figure 1 As shown, the present invention provides a multi-service integrated data risk assessment system, including: a global heterogeneous data acquisition module, a risk category comprehensive judgment module, a solid risk first analysis module, an operational risk second analysis module, and a risk assessment and early warning output module;

[0049] The global heterogeneous data acquisition module includes an environmental data acquisition layer and a power supply data acquisition layer. The power supply data acquisition layer includes a first data retrieval layer and a second data retrieval layer, which acquires heterogeneous data within the target area through sensors.

[0050] The risk category comprehensive judgment module comprehensively judges the risk category within the target area based on the environmental data of the target area output by the environmental data acquisition layer and the active power of the target area output by the power supply data acquisition layer.

[0051] The solid-state risk first analysis module, based on the comprehensive judgment result of the risk category of the target area, issues a call instruction to the first data call layer, and performs low-load solid-state risk analysis on the target area according to the data output by the first data call layer;

[0052] The second operational risk analysis module, based on the comprehensive judgment result of the risk category of the target area, issues a call instruction to the second data call layer, and performs a high-load operational risk analysis on the target area based on the data output by the second data call layer;

[0053] The risk assessment and early warning output module performs risk assessment based on the solid risk analysis results and operational risk analysis results of the target area, and sends early warning information to the device terminal based on the assessment results.

[0054] In this embodiment, it should be specifically noted that the global heterogeneous data acquisition module includes an environmental data acquisition layer and a power supply data acquisition layer, the specific contents of which are as follows:

[0055] The environmental data acquisition layer collects environmental data of the target area of ​​the power supply company through temperature and humidity sensors. The environmental data includes temperature data and humidity data of the target area.

[0056] The power supply data acquisition layer collects the active power output value of the power supply company when transmitting power to the target area through an active power transmitter. The power supply data acquisition layer includes a first data call layer and a second data call layer.

[0057] When the target area is monitored as having a low load, the first data calling layer receives a calling instruction and outputs the calling data of the first data calling layer. The calling data includes: the actual load rate of the line under the low load state of the target area, the ideal load rate of the line, the actual operating capacity of the substation, the reasonable operating capacity, and the maximum capacity of the substation.

[0058] When the target area is monitored as being under high load, the second data calling layer receives a calling instruction and outputs the calling data of the second data calling layer. The calling data includes: the actual operating voltage of the line under high load conditions, the rated voltage, the maximum and minimum voltages that the line can pass, the actual operating frequency of the line, the rated frequency, and the maximum and minimum frequencies that the line can pass.

[0059] In this embodiment, it should be specifically explained that the specific content of the risk category comprehensive determination module is as follows:

[0060] Based on historical data, preset temperature correction coefficients for different temperature ranges and humidity correction coefficients for different humidity ranges;

[0061] The system receives temperature and humidity data of the target area from the environmental data acquisition layer. The temperature and humidity data represent the temperature and humidity values ​​at different times at preset n sampling points. The system projects the temperature and humidity data into preset different temperature ranges and different humidity ranges to obtain the corresponding temperature correction coefficients and humidity correction coefficients. The system then calculates the average temperature correction coefficient and average humidity correction coefficient of the target area.

[0062] In this embodiment, the correction factor is set to 1 when the temperature is between 25℃ and 30℃; when the temperature is above 30℃, the correction factor increases by 0.05 for every 1℃ increase; when the temperature is below 25℃, the correction factor decreases by 0.03 for every 1℃ decrease; when the humidity is between 40% and 60%, the correction factor is 1; when the humidity is above 60%, the correction factor increases by 0.02 for every 10% increase; when the humidity is below 40%, the correction factor decreases by 0.01 for every 10% decrease.

[0063] The active power of the target area is received from the power supply data acquisition layer. The active power represents the active power value at different times obtained at n preset sampling points. The average active power of the target area is obtained by averaging.

[0064] The average active power of the target area is combined with the average temperature correction factor and the average humidity correction factor to obtain the output value of the risk category comprehensive judgment module. When the output value is less than the minimum value of the preset normal power range, the risk category comprehensive judgment result is low load. When the output value is greater than the maximum value of the preset normal power range, the risk category comprehensive judgment result is high load.

[0065] In this embodiment, it should be specifically explained that the specific content of the first solid-state risk analysis module is as follows:

[0066] When the comprehensive risk category assessment result of the target area is low load, a call instruction is issued to the first data call layer to obtain the data output by the first data call layer;

[0067] The actual load rate of the lines and the actual operating capacity of the substations under low load conditions in the target area are weighted and allocated, respectively, as follows: and ,in ;

[0068] The load mismatch degree under low load conditions is obtained by comparing the ratio of the actual load rate of the line to the ideal load rate of the line under low load conditions in the target area.

[0069] The first difference is obtained by performing a difference analysis between the actual operating capacity of the substation under low load conditions and the reasonable operating capacity under low load conditions. The second difference is obtained by performing a difference analysis between the maximum capacity of the substation and the actual operating capacity of the substation under low load conditions. The capacity mismatch degree under low load conditions is obtained based on the ratio of the first difference and the second difference.

[0070] Based on weight allocation, load mismatch, and capacity mismatch, a low-load solid-state risk analysis is performed on the target area, yielding the results. The calculation formula is as follows: Where D represents the result of the low-load solid-state risk analysis, This indicates the degree of load mismatch under low load conditions. It represents the capacity mismatch under low load conditions and sends the low load solid-state risk analysis results to the risk assessment and early warning output module. By weighted summation, the two key influencing factors of load and capacity are integrated into a comprehensive risk value according to their respective impact weights on risk.

[0071] In this embodiment, it should be specifically explained that the specific content of the second operational risk analysis module is as follows:

[0072] When the comprehensive risk category assessment result of the target area is high load, a call instruction for the second data call layer is issued to obtain the data output by the second data call layer;

[0073] The actual operating voltage and frequency of the line under high load conditions in the target area are weighted and allocated, respectively, as follows: and ,in ;

[0074] The voltage non-uniformity under high load conditions is calculated by taking the difference between the actual operating voltage and the rated voltage of the line under high load conditions as the numerator and the difference between the highest and lowest allowable voltages of the line as the denominator.

[0075] The frequency non-uniformity under high load conditions is obtained by taking the difference between the actual operating frequency and the rated frequency of the line under high load conditions as the numerator and the difference between the highest and lowest allowable frequencies of the line as the denominator.

[0076] Based on weight allocation, voltage non-uniformity, and frequency non-uniformity, a high-load operation risk analysis is conducted on the target area, yielding the high-load operation risk analysis results. The calculation formula is as follows: Where W represents the result of the high-load operation risk analysis, This indicates voltage non-uniformity under high load conditions. It represents the frequency non-uniformity under high load conditions and sends the high load operation risk analysis results to the risk assessment and early warning output module. Through weighted summation, the two key influencing factors of voltage and frequency are integrated into a comprehensive risk value according to their respective impact weights on risk.

[0077] In this embodiment, it should be specifically explained that the specific content of the risk assessment and early warning output module is as follows:

[0078] When the load is low, a risk assessment is performed based on the solid-state risk analysis results of the target area. When the solid-state risk analysis result is greater than or equal to the preset low-load analysis threshold, the assessment result is that the target area is at risk, and a warning message is sent to the device terminal based on the assessment result. Conversely, when the solid-state risk analysis result is less than the preset low-load analysis threshold, the assessment result is that the target area is not at risk, and no warning message is sent.

[0079] When under high load, risk assessment is performed based on the operational risk analysis results of the target area. If the operational risk analysis result is greater than or equal to the preset high load analysis threshold, the assessment result is that the target area is at risk, and a warning message is sent to the equipment terminal based on the assessment result. Conversely, if the operational risk analysis result is less than the preset high load analysis threshold, the assessment result is that the target area is not at risk, and no warning message is sent.

[0080] like Figure 2 As shown in this embodiment, it should be specifically explained that a data risk assessment method for multi-service integration includes the following steps:

[0081] Step S01: Collect heterogeneous data within the target area using sensors;

[0082] Step S02: Based on the environmental data and active power of the target area, comprehensively determine the risk category within the target area;

[0083] Step S03: Based on the comprehensive judgment result of the risk category of the target area, issue a call instruction for the first data call layer, and perform low-load solid-state risk analysis on the target area according to the data output by the first data call layer;

[0084] Step S04: Based on the comprehensive judgment result of the risk category of the target area, issue a call instruction for the second data call layer, and perform a high-load operation risk analysis on the target area based on the data output by the second data call layer;

[0085] Step S05: Conduct a risk assessment based on the solid-state risk analysis results and operational risk analysis results of the target area, and send the early warning information to the equipment terminal based on the assessment results.

[0086] In this embodiment, it should be specifically noted that the main difference between this embodiment and the prior art is that this embodiment comprehensively determines the risk category in the target area based on the environmental data and active power of the target area, combines the conventional power supply parameters and environmental parameters of the target area, completes the integration of multiple services, breaks through the limitations of a single data dimension, and provides a more comprehensive and accurate decision-making basis for the planning, operation, maintenance and energy efficiency optimization of the power system, and realizes a comprehensive assessment of the risk in the target area.

[0087] Through low-load solid-state risk analysis and high-load operation risk analysis, a detailed assessment of the potential risks in the target area under different load conditions was conducted. Under low load conditions, the focus was mainly on the matching of line load rate and substation operating capacity to avoid risks caused by idle resources or improper configuration. Under high load conditions, the emphasis was placed on the stability of line operating voltage and frequency to ensure the quality and reliability of power supply.

[0088] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0089] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A multi-service integrated data risk assessment system, characterized in that: include: The system includes a global heterogeneous data acquisition module, a risk category comprehensive judgment module, a solid-state risk first analysis module, an operational risk second analysis module, and a risk assessment and early warning output module. The global heterogeneous data acquisition module includes an environmental data acquisition layer and a power supply data acquisition layer. The power supply data acquisition layer includes a first data retrieval layer and a second data retrieval layer, which acquires heterogeneous data within the target area through sensors. The environmental data acquisition layer collects environmental data of the target area of ​​the power supply company through temperature and humidity sensors. The environmental data includes temperature data and humidity data of the target area. The power supply data acquisition layer collects the active power output value of the power supply company when transmitting power to the target area through an active power transmitter. The power supply data acquisition layer includes a first data call layer and a second data call layer. When the target area is monitored as having a low load, the first data calling layer receives a calling instruction and outputs the calling data of the first data calling layer, including: the actual load rate of the line under the low load state of the target area, the ideal load rate of the line, the actual operating capacity of the substation, the reasonable operating capacity, and the maximum capacity of the substation. When the target area is monitored as being under high load, the second data calling layer receives a calling instruction and outputs the calling data of the second data calling layer, including: the actual operating voltage of the line under high load conditions, the rated voltage, the maximum and minimum voltages that the line can pass, the actual operating frequency of the line, the rated frequency, and the maximum and minimum frequencies that the line can pass. The risk category comprehensive determination module comprehensively determines the risk category within the target area based on the environmental data of the target area output by the environmental data acquisition layer and the active power of the target area output by the power supply data acquisition layer. When the comprehensive judgment result of the risk category of the target area is low load, the solid-state risk first analysis module issues a call instruction to the first data call layer and performs low load solid-state risk analysis on the target area based on the data output by the first data call layer. When the comprehensive judgment result of the risk category of the target area is high load, the second operation risk analysis module issues a call instruction to the second data call layer and performs high load operation risk analysis on the target area based on the data output by the second data call layer. The risk assessment and early warning output module performs risk assessment based on the solid risk analysis results and operational risk analysis results of the target area, and sends early warning information to the device terminal based on the assessment results.

2. The data risk assessment system for multi-service integration according to claim 1, characterized in that: The specific content of the risk category comprehensive determination module is as follows: Based on historical data, preset temperature correction coefficients for different temperature ranges and humidity correction coefficients for different humidity ranges; The system receives temperature and humidity data of the target area from the environmental data acquisition layer. The temperature and humidity data represent the temperature and humidity values ​​at different times obtained at n preset sampling points. The system projects the temperature and humidity data into different preset temperature ranges and different humidity ranges to obtain the corresponding temperature correction coefficients and humidity correction coefficients. The system then calculates the average temperature correction coefficient and average humidity correction coefficient of the target area. The active power of the target area is received from the power supply data acquisition layer. The active power represents the active power value at different times obtained at n preset sampling points. The average active power of the target area is obtained by averaging. The average active power of the target area is combined with the average temperature correction factor and the average humidity correction factor to obtain the output value of the risk category comprehensive judgment module. When the output value is less than the minimum value of the preset normal power range, the risk category comprehensive judgment result is low load. When the output value is greater than the maximum value of the preset normal power range, the risk category comprehensive judgment result is high load.

3. The data risk assessment system for multi-service integration according to claim 1, characterized in that: The specific content of the first solid-state risk analysis module is as follows: When the comprehensive risk category assessment result of the target area is low load, a call instruction is issued to the first data call layer to obtain the data output by the first data call layer; The actual load rate of the lines and the actual operating capacity of the substations under low load conditions in the target area are weighted and allocated, respectively, as follows: and ; The load mismatch degree under low load conditions is obtained by comparing the ratio of the actual load rate of the line to the ideal load rate of the line under low load conditions in the target area. The first difference is obtained by performing a difference analysis between the actual operating capacity of the substation under low load conditions and the reasonable operating capacity under low load conditions. The second difference is obtained by performing a difference analysis between the maximum capacity of the substation and the actual operating capacity of the substation under low load conditions. The capacity mismatch degree under low load conditions is obtained based on the ratio of the first difference and the second difference. Based on weight allocation, load mismatch, and capacity mismatch, a low-load solid-state risk analysis is performed on the target area to obtain the low-load solid-state risk analysis results, which are then sent to the risk assessment and early warning output module.

4. The data risk assessment system for multi-service integration according to claim 1, characterized in that: The specific content of the second operational risk analysis module is as follows: When the comprehensive risk category assessment result of the target area is high load, a call instruction for the second data call layer is issued to obtain the data output by the second data call layer; The actual operating voltage and frequency of the line under high load conditions in the target area are weighted and allocated, respectively, as follows: and ; The voltage non-uniformity under high load conditions is calculated by taking the difference between the actual operating voltage and the rated voltage of the line under high load conditions as the numerator and the difference between the highest and lowest allowable voltages of the line as the denominator. The frequency non-uniformity under high load conditions is obtained by taking the difference between the actual operating frequency and the rated frequency of the line under high load conditions as the numerator and the difference between the highest and lowest allowable frequencies of the line as the denominator. Based on weight allocation, voltage non-uniformity, and frequency non-uniformity, a high-load operation risk analysis is performed on the target area to obtain the high-load operation risk analysis results, which are then sent to the risk assessment and early warning output module.

5. The data risk assessment system for multi-service integration according to claim 1, characterized in that: The specific contents of the risk assessment and early warning output module are as follows: When the load is low, a risk assessment is performed based on the solid-state risk analysis results of the target area. When the solid-state risk analysis result is greater than or equal to the preset low-load analysis threshold, the assessment result is that the target area is at risk, and a warning message is sent to the device terminal based on the assessment result. Conversely, when the solid-state risk analysis result is less than the preset low-load analysis threshold, the assessment result is that the target area is not at risk, and no warning message is sent. When under high load, risk assessment is performed based on the operational risk analysis results of the target area. If the operational risk analysis result is greater than or equal to the preset high load analysis threshold, the assessment result is that the target area is at risk, and a warning message is sent to the equipment terminal based on the assessment result. Conversely, if the operational risk analysis result is less than the preset high load analysis threshold, the assessment result is that the target area is not at risk, and no warning message is sent.

6. A data risk assessment method for multi-service integration, used in conjunction with the data risk assessment system for multi-service integration as described in any one of claims 1-5, characterized in that: Includes the following steps: Step S01: Collect heterogeneous data within the target area using sensors; Step S02: Based on the environmental data and active power of the target area, comprehensively determine the risk category within the target area; Step S03: When the comprehensive judgment result of the risk category of the target area is low load, issue a call instruction of the first data call layer, and perform low load solid risk analysis on the target area based on the data output by the first data call layer; Step S04: When the comprehensive judgment result of the risk category of the target area is high load, issue a call instruction for the second data call layer, and perform a high load operation risk analysis on the target area based on the data output by the second data call layer; Step S05: Conduct a risk assessment based on the solid-state risk analysis results and operational risk analysis results of the target area, and send the early warning information to the equipment terminal based on the assessment results.

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