220kV protection limit risk assessment system based on industrial internet

Abstract

The invention discloses a 220kV protection limit risk assessment system based on an industrial internet, and belongs to the technical field of power system relay protection. The 220kV protection limit risk assessment system comprises a data acquisition module used for acquiring related data of a power grid of a target area, the related data comprises a group of power grid lines with the maximum fault occurrence frequency in the target area and factors corresponding to fault occurrence; marking a group of power grid lines with the highest fault occurrence frequency as a reference group of power grid lines; and the data distinguishing module is used for distinguishing factors corresponding to each line in the reference group power grid line when the fault occurs from the factors corresponding to the fault, and the factors comprise power frequency overvoltage, operation overvoltage and resonance overvoltage. According to the invention, through a data-driven risk assessment method, in combination with multi-dimensional analysis and a dynamic early warning mechanism, accurate management and control of 220kV power grid protection limit risks are realized, and a powerful technical guarantee is provided for safe operation of a power grid.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power system relay protection, and particularly to a 220kV protection limit risk assessment system based on industrial internet. BACKGROUND

[0002] Due to the large scale of modern power systems, involving numerous power equipment and complex control logic, the uncertainty of power systems in the grid is increased.

[0003] For this research, the application number CN202411298163.2 provides a power grid limit intelligent alarm method and system based on risk assessment model, which collects the performance parameters of each power equipment corresponding to each power node, so that the multi-dimensional information of material aging, component loosening and component corrosion in the power equipment is more accurately understood, the performance influence value of each power equipment corresponding to each power node is analyzed, and the influence degree of the equipment in the power grid is accurately known, and the operation risk assessment degree of each power node in the power grid is obtained through the risk assessment model, which helps to quantify the complexity of power grid limit and the uncertainty of risk, and ensures the safe and stable operation of power system in the power grid.

[0004] Another application number CN202110690951.6 provides an intelligent alarm system for power grid operation risk based on big data analysis, which includes data acquisition layer, data analysis layer and data display layer. The data acquisition layer is used to acquire dispatching data and real-time operation information of power grid supporting dispatching decision, the data analysis layer is used to evaluate the existing operation risk through big data analysis according to the data acquired by the data acquisition layer, and the data display layer is used to display the evaluation data analyzed by the data analysis layer. This technical scheme improves the operation risk control level of power grid and reduces the electricity loss of power transmission and transformation equipment.

[0005] However, the existing system usually processes protection device operation data, primary equipment state data and environmental data in isolation, lacks multi-source data fusion analysis mechanism, and cannot realize real-time perception of power grid operation state change, resulting in that the risk assessment result lags behind the actual working condition, affecting the timeliness of early warning. SUMMARY

[0006] In view of the above problems existing in the prior art of power system relay protection, the present application is proposed.

[0007] Therefore, one object of the present application is to provide a 220kV protection limit risk assessment system based on industrial internet, which realizes precise control of 220kV power grid protection limit risk through data-driven risk assessment method combined with multi-dimensional analysis and dynamic early warning mechanism, and provides strong technical support for safe operation of power grid.

[0008] To solve the above-mentioned technical problems, the present invention provides the following technical solution: This invention provides a 220kV protection limit risk assessment system based on the Industrial Internet, comprising: The data acquisition module is used to collect relevant data of the power grid in the target area. The relevant data includes the group of power grid lines with the most frequent faults in the target area and the factors corresponding to the faults. The group of power grid lines with the most frequent faults is marked as the reference group of power grid lines. The data differentiation module is used to distinguish the factors corresponding to each line in the reference group power grid when the fault occurs from the factors corresponding to the occurrence of the fault. The factors include power frequency overvoltage, switching overvoltage and resonant overvoltage. The data construction module is used to construct faults for each line in the reference group power grid. The fault construction includes constructing fault zones on each line. The fault zones are constructed by factors corresponding to the occurrence of faults on each line. There are no fewer than 6 fault zones constructed on each line. The data fusion processing module is used to analyze and process the changes in fault areas on each line, including fault changes; the data fusion processing module includes a statistical unit, an analysis unit, an acquisition unit, and a calculation unit. The statistical unit is used to count the number of times a fault occurs due to different factors in each fault zone. The analysis unit is used to analyze the voltage variation patterns of adjacent fault zones on each of the lines during each fault occurrence. The acquisition unit responds to the change pattern and is used to acquire the voltage at the starting location of each fault zone; the starting location is a length range within one meter at the beginning of the fault zone.

[0009] In a preferred embodiment of the present invention, the calculation unit is used to calculate the time required for the fault to occur based on the voltage of the starting location under the condition of the factors corresponding to the fault that caused the fault zone; and to issue an early warning based on the time.

[0010] In a preferred embodiment of the present invention, the analysis unit analyzes the voltage variation patterns of adjacent fault zones on each line during each fault occurrence. The analysis method includes correlation factor analysis, which includes combining the factors corresponding to the fault occurrence to analyze whether there are differences in the voltage variation patterns under different factors. The differences include calculating the average value and standard deviation of the voltage variation in faults caused by different factors.

[0011] In a preferred embodiment of the present invention, the calculation unit calculates the time required for a fault to occur based on the voltage at the starting location, taking into account the factors mentioned above, using the following formula: ; In the formula, Indicates elapsed time Voltage at the initial location, in V; Indicates the magnitude of the operational overvoltage, in volts (V). This indicates the time elapsed since the fault occurred, in seconds. The angular frequency of the operating overvoltage is expressed in radians per second. This represents the initial phase angle, expressed in radians.

[0012] In a preferred embodiment of the present invention, the average value of the voltage change is calculated according to the following formula: ; In the formula, The average value of the change in voltage, expressed in V; The total number of failures is a positive integer. Indicates the first The voltage change during the fault, in units of V, is determined by the first... Initial voltage at the starting location of the secondary fault and the voltage at a certain moment after the fault occurs Calculated; Indicates the first The initial voltage at the starting location of the secondary fault, in V; Indicates the first In a fault, the voltage at the starting location after a certain moment when the fault occurs is expressed in V.

[0013] In a preferred embodiment of the present invention, the standard deviation of the voltage variation is calculated according to the following formula: ; In the formula, The standard deviation of voltage variation, expressed in V; The total number of failures is a positive integer. Indicates the first The voltage change during the fault, in units of V, is determined by the first... Initial voltage at the starting location of the secondary fault and the voltage at a certain moment after the fault occurs Calculated; The average value representing the change in voltage; Indicates the first The initial voltage at the starting location of the secondary fault, in V; Indicates the first In a fault, the voltage at the starting location after a certain moment when the fault occurs is expressed in V.

[0014] In a preferred embodiment of the present invention: a safety threshold is preset based on the calculated average value; a fault point corresponding to the occurrence of a historical fault is obtained in the fault zone; the distance between the fault point and the starting point of the fault zone is obtained; if the voltage exceeds the safety threshold within the distance, the system issues a warning; otherwise, no warning is issued.

[0015] In a preferred embodiment of the present invention, if the voltage does not exceed the safety threshold within the distance, the voltage change is monitored in the monitoring area from the fault point to the end of the fault zone. If the voltage shows an increasing trend, the system issues an early warning; otherwise, no early warning is issued.

[0016] In a preferred embodiment of the present invention, if the voltage does not show an increasing trend, the voltage monitored at the endpoint is used as the reference voltage. At the beginning of the next fault zone, if the voltage at the beginning is higher than the reference voltage, the system issues an early warning; otherwise, no early warning is issued.

[0017] Beneficial effects: 1. This invention collects detailed data on the power grid in the target area, including lines with high failure rates and corresponding factors (such as power frequency overvoltage, switching overvoltage, and resonant overvoltage), and performs in-depth data differentiation and construction, which can accurately identify risk points in the power grid and provide a solid data foundation for risk assessment. 2. This invention performs multi-dimensional analysis of fault zones on each line, including counting the number of faults caused by different factors and analyzing the voltage change patterns of adjacent fault zones. Furthermore, through a calculation unit, it accurately calculates the time required for a fault to occur based on the voltage at the starting point and the corresponding factors of the fault, and issues an early warning accordingly. This early warning mechanism can detect potential fault risks in advance and provide strong protection for the safe operation of the power grid. 3. Through correlation factor analysis, the differences in voltage change patterns under different factors are explored in depth, including calculating the average value and standard deviation of voltage change and other statistical characteristics. Based on the calculated average value of voltage change, a safety threshold is preset, and voltage changes are dynamically monitored in the fault area. Once the voltage exceeds the safety threshold or shows an increasing trend, the system issues an early warning. This dynamic safety threshold setting method improves the flexibility and accuracy of power grid safety monitoring. 4. The system not only monitors voltage changes at the beginning of the fault zone, but also continuously monitors the area from the fault point to the end of the fault zone. If the voltage shows an increasing trend or the voltage at the beginning of the next fault zone is higher than the reference voltage, the system will issue an early warning. This comprehensive monitoring and early warning mechanism ensures the all-round and timely nature of power grid safety monitoring. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. 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 effort. Wherein: Fig. 1 This is a schematic diagram of the modular structure of a 220kV protection limit risk assessment system based on the Industrial Internet, according to an embodiment of the present invention. Fig. 2 This is a schematic diagram of the process structure of an embodiment of the present invention; The diagram is labeled as follows: 110 - Data acquisition module; 120 - Data differentiation module; 130 - Data construction module; 140 - Data fusion and processing module; 1401 - Statistical unit; 1402 - Analysis unit; 1403 - Acquisition unit; 1404 - Calculation unit. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention are within the scope of protection of the present invention.

[0020] Because existing technologies lack a multi-source data fusion and analysis mechanism, they cannot perceive changes in the power grid's operating status in real time, resulting in risk assessment results lagging behind actual operating conditions and affecting the timeliness of early warnings.

[0021] Based on this, the present invention proposes a 220kV protection limit risk assessment system based on the Industrial Internet. Through a data-driven risk assessment method, combined with multi-dimensional analysis and dynamic early warning mechanism, it achieves precise control over the protection limit risk of the 220kV power grid, providing strong technical support for the safe operation of the power grid.

[0022] The present solution will be further described in detail below through embodiments and in conjunction with the accompanying drawings.

[0023] Reference Figs. 1-2 As one embodiment of the present invention, this embodiment provides a 220kV protection limit risk assessment system based on the Industrial Internet, including: Data acquisition module 110 is used to collect relevant data of the power grid in the target area. The relevant data includes the group of power grid lines with the most frequent faults in the target area and the factors corresponding to the faults. The group of power grid lines with the most frequent faults is marked as the reference group of power grid lines. In this embodiment, the fault refers to the voltage of the power grid line being higher than the rated value or the standard allowable range; The data collection methods include collecting data from the power supply bureau in the target area to obtain relevant data; When the voltage of a power grid line exceeds the rated value or the standard allowable range, it will have a variety of impacts on power grid equipment, user equipment, system stability, and personnel safety. This impact includes effects on power grid equipment, such as: Damaged transformer insulation can lead to accelerated insulation aging, core saturation and increased losses, and winding deformation or breakdown. This will also increase losses in power transmission lines; The data acquisition module is responsible for collecting relevant data of the power grid in the target area, including the fault-prone line groups and the factors corresponding to the fault occurrence (power frequency overvoltage, switching overvoltage and resonant overvoltage), and marking the line groups with the most faults as the reference group of power grid lines; This method, by accurately collecting data on lines with high failure rates and key influencing factors, provides a reliable raw data foundation for subsequent analysis, ensuring the relevance and accuracy of risk assessment. The data differentiation module 120 is used to distinguish the factors corresponding to the fault occurrence from the factors corresponding to each line in the reference group power grid line at the time of the fault occurrence. The factors include power frequency overvoltage, switching overvoltage and resonant overvoltage. It should be noted that the data differentiation module separates the specific factors (power frequency overvoltage, switching overvoltage, and resonant overvoltage) of each line of the reference group power grid from the fault-related factors when the fault occurs. This can clearly identify the causes of failures on different lines, provide a basis for subsequent differentiated analysis, help to accurately locate the source of risk, and improve the level of precision in risk assessment; The data construction module 130 is used to construct faults for each line in the reference group power grid. Fault construction includes constructing fault areas on each line. The fault areas are constructed by each line based on the factors corresponding to the occurrence of the fault. There are no less than 6 fault areas constructed on each line. In this embodiment, the data construction module constructs fault zones on each line of the reference group power grid. Each fault zone is generated based on the corresponding factors (such as overvoltage type) when the line fault occurs, and no less than 6 fault zones are constructed for each line. This method enhances the system's ability to identify complex fault modes and improves the comprehensiveness of risk assessment by simulating multiple fault zones and covering voltage change characteristics under different fault conditions. The data fusion processing module 140 is used to analyze and process the changes in the fault areas on each line, including changes in faults; the data fusion processing module 140 includes a statistical unit 1401, an analysis unit 1402, an acquisition unit 1403, and a calculation unit 1404. The statistics unit 1401 is used to count the number of times a fault occurs due to different factors in each fault zone; In this embodiment, the statistics unit counts the number of times a fault occurs due to different factors (power frequency overvoltage, switching overvoltage, and resonant overvoltage) in each fault zone; This quantification of the contribution of each factor to the failure provides data support for subsequent correlation analysis, helps to prioritize the identification of high-risk factors, and optimize resource allocation; Analysis unit 1402 is used to analyze the voltage change pattern of adjacent fault areas on each line during each fault occurrence. The analysis methods include correlation factor analysis, which combines the factors corresponding to the occurrence of the fault (power frequency overvoltage, switching overvoltage, and resonant overvoltage) to analyze whether there are differences in the voltage change patterns under different factors; the differences include calculating the average and standard deviation of the voltage change in faults caused by different factors; In this embodiment, the magnitude relationship between them is compared to determine the degree of influence of different factors on voltage changes; The analysis unit studies the voltage change patterns of adjacent fault areas on each line when a fault occurs, performs correlation analysis in conjunction with fault factors, and calculates the average value and standard deviation of voltage change. This method, through multi-dimensional correlation analysis, reveals the differences in voltage changes under different factors, providing a quantitative basis for risk assessment and enhancing the scientific rigor of the assessment results; The response change pattern of the acquisition unit 1403 is used to obtain the voltage at the starting location of each fault zone; the starting location is the length range within one meter at the beginning of the fault zone. In this embodiment, the acquisition unit acquires the voltage at the starting location of each fault zone (within 1 meter of the fault initiation point) based on the voltage change pattern; This precise capture of voltage characteristics in the initial stage of a fault provides crucial data for subsequent time calculations and early warnings, improving the timeliness of early warnings.

[0024] The calculation unit 1404 calculates the time required for the fault to occur based on the voltage of the starting location, according to the factors corresponding to the fault that caused the fault area, and provides an early warning based on the time. In this embodiment, the calculation unit calculates the time from the occurrence of the fault based on the fault factors and the initial location voltage, and triggers an early warning. It enables quantitative prediction and early warning of fault risks, giving maintenance personnel more time to handle the situation and reducing the risk of fault spread.

[0025] In the calculation unit, considering various factors, the time required for a fault to occur is calculated based on the voltage at the starting location, using the following formula: ; In the formula, Indicates elapsed time Voltage at the initial location, in V; Indicates the magnitude of the operational overvoltage, in volts (V). This indicates the time elapsed since the fault occurred, in seconds. The angular frequency of the operating overvoltage is expressed in radians per second (rad / s). This represents the initial phase angle, expressed in radians (rad).

[0026] The average value of the voltage change is calculated using the following formula: ; In the formula, It represents the average value of the voltage change, expressed in volts (V); it reflects the average level of voltage change under the influence of this type of overvoltage factor. The total number of faults is a positive integer; it represents the number of times a fault caused by a certain overvoltage factor has been detected. Subsequent monitoring and recording Indicates the first The voltage change during the fault, in units of V, is determined by the first... Initial voltage at the starting location of the secondary fault and the voltage at a certain moment after the fault occurs Calculated; Indicates the first The initial voltage at the starting location of the secondary fault, in volts (V), i.e., the voltage at the starting location at the instant the fault occurs. Indicates the first In a fault, the voltage at the starting location after a certain moment when the fault occurs is expressed in V.

[0027] The standard deviation of the voltage variation is calculated using the following formula: ; In the formula, The standard deviation of voltage variation, measured in volts (V), measures the dispersion of voltage variation around its average value under the influence of an overvoltage factor. A larger standard deviation indicates greater fluctuation in voltage variation, while a smaller standard deviation indicates more concentrated voltage variation. The total number of failures is a positive integer. Indicates the first The voltage change during the fault, in units of V, is determined by the first... Initial voltage at the starting location of the secondary fault and the voltage at a certain moment after the fault occurs Calculated; The average value representing the change in voltage; Indicates the first The initial voltage at the starting location of the secondary fault, in V; Indicates the first In this fault, the voltage at the starting location after a certain moment when the fault occurs, in V; In the two calculation formulas above, when comparing average values, if the average value of voltage change under a certain overvoltage factor is larger, it indicates that the average level of voltage change under the influence of that factor is higher, meaning that the influence of this factor on voltage is relatively greater. For example, if the average value of voltage change under switching overvoltage is greater than the average value under power frequency overvoltage and resonant overvoltage, it can be preliminarily considered that the average influence of switching overvoltage on voltage is greater. When comparing standard deviations, if the standard deviation of voltage change under a certain overvoltage factor is large, it indicates that the voltage fluctuation is large under the influence of that factor, meaning that this factor leads to higher uncertainty in voltage change. For example, if the standard deviation of voltage change under resonant overvoltage is greater than the standard deviation under power frequency overvoltage and switching overvoltage, it can be considered that the voltage fluctuation caused by resonant overvoltage is more severe. By calculating the average value and standard deviation of voltage changes, the central tendency and dispersion of voltage changes under different factors are quantified. This can reveal the significance and stability of the effects of various factors on voltage, providing data support for optimizing protection strategies and improving system adaptability; The two calculation formulas mentioned above are used to calculate the average value and standard deviation of voltage change, respectively. They are logically related and work together to quantify the risk of power grid faults. The first formula reflects the average voltage change caused by a certain type of overvoltage factor (such as operational overvoltage) by statistically averaging the voltage changes in all fault events. Its function is to quantify the overall trend of voltage change under specific factors, providing a benchmark value for subsequent standard deviation calculation; Used to set a dynamic safety threshold (as described below, "preset safety threshold based on average value"), which triggers an alarm when the voltage deviates from the average value; The second formula measures the dispersion of voltage fluctuations by calculating the root mean square of the sum of squares of the deviations between the voltage change and the average value. Its function is to reflect the stability of voltage changes under a certain type of overvoltage factor. The larger the standard deviation, the more severe the voltage fluctuation and the higher the risk of failure. By combining the average value, it is possible to distinguish whether the system is affected by persistent factors (high mean) or occasional disturbances (high standard deviation), providing a basis for differentiated protection strategies; The two formulas have a data dependency relationship; Standard deviation calculations must be based on the mean, meaning the formula includes... ; Both are based on the same set of fault event data ( and This ensures consistency in the analysis; The average value reveals the "typical value" of voltage variation, which is used to determine the overall risk level (such as whether it exceeds the safety threshold). Standard deviation reveals the "volatility" of voltage changes and is used to assess the uncertainty of risk (such as whether drastic fluctuations are caused by unforeseen factors). For example, if the average value of a certain type of overvoltage is close to the threshold but the standard deviation is small, it indicates that the risk is controllable; if the average value is low but the standard deviation is extremely large, then sudden failures should be guarded against. Based on the calculated average value, a safety threshold is preset. The fault point corresponding to the occurrence of the historical fault is obtained in the fault area. The distance between the fault point and the starting point of the fault area is obtained. If the voltage exceeds the safety threshold within the distance, the system issues an early warning; otherwise, no early warning is issued. Within a certain distance, if the voltage does not exceed the safety threshold, the monitoring area from the fault point to the end of the fault zone is used to monitor voltage changes. If the voltage shows an increasing trend, the system will issue an early warning; otherwise, no warning will be issued. If the voltage does not show an increasing trend, the voltage monitored at the end point is used as the reference voltage. At the beginning of the next fault zone, if the voltage at the beginning is higher than the reference voltage, the system will issue a warning; otherwise, no warning will be issued. The system presets a safety threshold based on the average voltage change and dynamically monitors the voltage in the fault area: if the voltage exceeds the threshold or shows an upward trend, or if the starting voltage of the next fault area is higher than the reference value, an early warning is triggered. This multi-level dynamic monitoring enables accurate identification and timely handling of fault risks, significantly improving the safety and reliability of power grid operation.

[0028] In summary, this application, through a data-driven risk assessment method combined with multi-dimensional analysis and a dynamic early warning mechanism, achieves precise control over the risk of 220kV power grid protection limits, providing strong technical support for the safe operation of the power grid.

[0029] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A 220kV protection limit risk assessment system based on the Industrial Internet, characterized in that, include: The data acquisition module is used to collect relevant data of the power grid in the target area. The relevant data includes the group of power grid lines with the most frequent faults in the target area and the factors corresponding to the faults. The group of power grid lines with the most frequent faults is designated as the reference group of power grid lines; The data differentiation module is used to distinguish the factors corresponding to each line in the reference group power grid when the fault occurs from the factors corresponding to the occurrence of the fault. The factors include power frequency overvoltage, switching overvoltage and resonant overvoltage. The data construction module is used to construct faults for each line in the reference group power grid. The fault construction includes constructing fault zones on each line. The fault zones are constructed by factors corresponding to the occurrence of faults on each line. There are no fewer than 6 fault zones constructed on each line. The data fusion processing module is used to analyze and process the changes in fault areas on each line, including fault changes; the data fusion processing module includes a statistical unit, an analysis unit, an acquisition unit, and a calculation unit. The statistical unit is used to count the number of times a fault occurs due to different factors in each fault zone. The analysis unit is used to analyze the voltage variation patterns of adjacent fault zones on each of the lines during each fault occurrence. The acquisition unit responds to the change pattern and is used to acquire the voltage at the starting location of each fault zone; the starting location is a length range within one meter at the beginning of the fault zone.

2. The 220kV protection limit risk assessment system based on the Industrial Internet as described in claim 1, characterized in that, The calculation unit, based on the factors corresponding to the faults that caused the fault zone, calculates the time required for the fault to occur based on the voltage at the starting location under the conditions of the factors; and issues an early warning based on the time.

3. The 220kV protection limit risk assessment system based on the Industrial Internet as described in claim 1, characterized in that, In the analysis unit, the voltage change pattern of adjacent fault areas on each line is analyzed at each fault occurrence. The analysis method includes correlation factor analysis, which includes combining the factors corresponding to the fault occurrence to analyze whether there are differences in the voltage change pattern under different factors. The difference includes calculating the average value and standard deviation of the voltage change in faults caused by different factors.

4. The 220kV protection limit risk assessment system based on the Industrial Internet as described in claim 2, characterized in that, In the calculation unit, the time required for a fault to occur is calculated based on the voltage at the starting location, taking into account the factors mentioned above, using the following formula: ； In the formula, Indicates elapsed time Voltage at the initial location, in V; Indicates the magnitude of the operational overvoltage, in volts (V). This indicates the time elapsed since the fault occurred, in seconds. The angular frequency of the operating overvoltage is expressed in radians per second. This represents the initial phase angle, expressed in radians.

5. The 220kV protection limit risk assessment system based on the Industrial Internet as described in claim 3, characterized in that, The average value of the voltage change is calculated using the following formula: ； In the formula, The average value of the change in voltage, expressed in V; The total number of failures is a positive integer. Indicates the first The voltage change during the fault, in units of V, is determined by the first... Initial voltage at the starting location of the secondary fault and the voltage at a certain moment after the fault occurs Calculated; Indicates the first The initial voltage at the starting location of the secondary fault, in V; Indicates the first In a fault, the voltage at the starting location after a certain moment when the fault occurs is expressed in V.

6. The 220kV protection limit risk assessment system based on the Industrial Internet as described in claim 3, characterized in that, The standard deviation of the voltage variation is calculated using the following formula: ； In the formula, The standard deviation of voltage variation, expressed in V; The total number of failures is a positive integer. Indicates the first The voltage change during the fault, in units of V, is determined by the first... Initial voltage at the starting location of the secondary fault and the voltage at a certain moment after the fault occurs Calculated; The average value representing the change in voltage; Indicates the first The initial voltage at the starting location of the secondary fault, in V; Indicates the first In a fault, the voltage at the starting location after a certain moment when the fault occurs is expressed in V.

7. The 220kV protection limit risk assessment system based on the Industrial Internet as described in claim 5, characterized in that, Based on the calculated average value, a safety threshold is preset. The fault point corresponding to the occurrence of the historical fault is obtained in the fault area. The distance between the fault point and the starting point of the fault area is obtained. If the voltage exceeds the safety threshold within the distance, the system issues an early warning. Conversely, no warning will be issued.

8. The 220kV protection limit risk assessment system based on the Industrial Internet as described in claim 7, characterized in that, Within the specified distance, if the voltage does not exceed the safety threshold, the voltage change is monitored within the monitoring area from the fault point to the end of the fault zone. If the voltage shows an increasing trend, the system issues an early warning. Conversely, no warning will be issued.

9. The 220kV protection limit risk assessment system based on the Industrial Internet as described in claim 8, characterized in that, If the voltage does not show an increasing trend, the voltage monitored at the endpoint is used as the reference voltage. At the beginning of the next fault zone, if the voltage at the beginning is higher than the reference voltage, the system issues a warning; otherwise, no warning is issued.

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