Intelligent substation real-time monitoring system and method based on data analysis

Abstract

The invention discloses an intelligent substation real-time monitoring system and method based on data analysis, and belongs to the technical field of intelligent power grids. The system comprises an equipment management module, a data real-time acquisition module, an integrated analysis platform, a model management module, an intelligent calculation module and a monitoring display module, the equipment management module is used for determining associated electric equipment in a monitoring area; the data real-time acquisition module is used for acquiring parameter data of electric equipment; the integrated analysis platform is used for analyzing the collected parameter data; the model management module is used for establishing a risk analysis model, and analyzing the influence of different parameter data on the fault of the electric equipment according to a historical parameter data analysis result; the intelligent calculation module is used for calculating the safety risk degree of the electric equipment in each sub-region and dynamically allocating supervision resources of each sub-region; and the monitoring display module is used for providing an interactive display platform and carrying out digital display.

Description

Technical Field

[0001] The present invention relates to the technical field of smart power grids, and in particular to a real-time monitoring system and method for a smart substation based on data analysis. Background Art

[0002] A smart substation is a new type of power network that deeply integrates traditional power grids with modern information and communication technologies. Through the Internet of Things technology, it interconnects various devices, nodes and systems in the substation to achieve real-time data collection, transmission and processing, which significantly improves the information level of the substation and provides strong technical support for real-time monitoring. However, with the expansion of the scale of substations, the number of devices that need to be monitored is also increasing, resulting in tight monitoring resources. The existing technology has an unbalanced allocation of monitoring resources, and it is difficult for substations to reasonably allocate monitoring resources based on real-time data, which results in the system's response to faults not being timely enough, affecting the monitoring effect. Summary of the invention

[0003] The purpose of the present invention is to provide a smart substation real-time monitoring system and method based on data analysis to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: a real-time monitoring method for a smart substation based on data analysis, the method comprising the following steps:

[0005] S1. Determine the monitoring area of ​​the smart substation, divide the monitoring area into different sub-areas, determine the associated power-consuming equipment in the monitoring area, and collect parameter data of the power-consuming equipment, store the collected parameter data in the database as historical data and continuously update it; the parameter data includes the operation cycle, fault record and maintenance record of the power-consuming equipment;

[0006] S2. Analyze the collected parameter data, determine the total working time of the electrical equipment according to the operating cycle of the electrical equipment; determine the number of failures of the electrical equipment according to the failure record of the electrical equipment; determine the number of maintenance of the electrical equipment and the cycle length of each maintenance interval according to the maintenance record of the electrical equipment; wherein the parameter data is divided into historical parameter data and real-time parameter data;

[0007] S3. Establish a risk analysis model and analyze the impact of different parameter data on power equipment failures based on historical parameter data analysis results;

[0008] S4. Determine the electrical equipment currently operating in each sub-area, calculate the safety risk level of the electrical equipment in each sub-area based on the electrical equipment currently operating in each sub-area, the established risk analysis model and the real-time parameter data analysis results, and dynamically allocate regulatory resources to each sub-area based on the calculation results.

[0009] A real-time monitoring system for a smart substation based on data analysis, the system includes an equipment management module, a real-time data acquisition module, an integrated analysis platform, a model management module, an intelligent computing module and a monitoring display module;

[0010] The equipment management module is used to determine the monitoring area of ​​the smart substation, divide the monitoring area into different sub-areas, and determine the associated power-consuming equipment in the monitoring area;

[0011] The real-time data acquisition module is used to collect parameter data of the related electrical equipment in the monitoring area of ​​the equipment management module, store the collected parameter data in the database as historical data and continuously update it; the parameter data includes the operation cycle, fault record and maintenance record of the electrical equipment; provide a sensor, the sensor is used to send the collected parameter data to the integrated analysis platform;

[0012] The integrated analysis platform is used to receive and analyze parameter data sent by sensors in the real-time data acquisition module, determine the total working time of the electrical equipment according to the operating cycle of the electrical equipment; determine the number of failures of the electrical equipment according to the failure records of the electrical equipment; determine the number of maintenance of the electrical equipment and the cycle length of each maintenance interval according to the maintenance records of the electrical equipment; wherein the parameter data is divided into historical parameter data and real-time parameter data; the analysis results of the historical parameter data are sent to the model management module, and the analysis results of the real-time parameter data are sent to the intelligent computing module and the monitoring and display module;

[0013] The model management module is used to establish a risk analysis model and analyze the impact of different parameter data on power equipment failures based on the historical parameter data analysis results in the integrated analysis platform;

[0014] The intelligent calculation module is used to determine the electrical equipment currently working in each sub-area, calculate the safety risk level of the electrical equipment in each sub-area based on the electrical equipment currently working in each sub-area, the established risk analysis model and the real-time parameter data analysis results in the integrated analysis platform, and dynamically allocate the supervision resources of each sub-area based on the calculation results; send the calculated safety risk level of the electrical equipment in each sub-area to the monitoring and display module;

[0015] The monitoring and display module is used to provide an interactive display platform to digitally display the real-time parameter data analysis results and the calculated safety risk levels of electrical equipment in each sub-area.

[0016] Compared with the prior art, the beneficial effects achieved by the present invention are: providing a real-time monitoring system and method for a smart substation based on data analysis, by collecting and analyzing parameter data of electrical equipment, establishing a risk analysis model, and analyzing the impact of different parameter data on electrical equipment failures, thereby providing data support for the safety risk level analysis of each sub-area, improving the system's ability to analyze data generated in the smart substation and the accuracy of safety judgments; by calculating the safety risk level of electrical equipment in each sub-area, and dynamically allocating regulatory resources for each sub-area based on the calculation results, the problem of unbalanced monitoring resource allocation in the smart substation is solved, thereby improving the timeliness of the system's response to failures and enhancing the monitoring effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the steps of a real-time monitoring method of a smart substation based on data analysis of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] See also Figure 1 , the present invention provides a technical solution:

[0020] See also Figure 1 In the first embodiment, a real-time monitoring method for a smart substation based on data analysis is provided. In the method, parameter data of power equipment in the substation is monitored in real time. By analyzing the parameter data, the supervision resources in the substation are dynamically allocated according to the analysis results, thereby improving the timeliness of the system's response to power equipment failures and enhancing the monitoring effect. The method includes the following steps:

[0021] S1. Determine the monitoring area of ​​the smart substation, divide the monitoring area into different sub-areas, determine the associated electrical equipment in the monitoring area, and collect parameter data of the electrical equipment. The collected parameter data is stored in the database as historical data and continuously updated; the parameter data includes the operation cycle, fault record and maintenance record of the electrical equipment.

[0022] In this embodiment, the monitoring area is the substation area; the sub-areas are divided according to the distribution of electrical equipment in the substation area; the electrical equipment has different types of equipment, including but not limited to electronic mutual inductors, transformers, and high-voltage circuit breakers.

[0023] Furthermore, the monitoring area is divided into different sub-areas, the number n of divided sub-areas is determined, and the number m of associated electrical devices in the monitoring area is determined; wherein each electrical device has a corresponding device number; the electrical devices used in each parameter data analysis are devices of the same type; a sensor is installed on each associated electrical device; the sensor is used to send the collected parameter data to an integrated analysis platform, and the integrated analysis platform is used to receive the parameter data and perform analysis.

[0024] In this embodiment, when the electrical equipment starts to work, parameter data of the electrical equipment is collected, and the sensor sends the collected parameter data to the integrated analysis platform. The integrated analysis platform analyzes the parameter data after receiving the parameter data sent by the sensor.

[0025] It should be noted that the collected parameter data are analyzed, wherein the electrical equipment analyzed each time is of the same type. By analyzing the same type of equipment, the differences between different equipment types are avoided, thereby improving the accuracy of the analysis of the impact of electrical equipment failures.

[0026] S2. Analyze the collected parameter data, determine the total working time of the electrical equipment according to the operating cycle of the electrical equipment; determine the number of failures of the electrical equipment according to the fault records of the electrical equipment; determine the number of maintenance of the electrical equipment and the cycle duration of each maintenance interval according to the maintenance records of the electrical equipment; wherein the parameter data is divided into historical parameter data and real-time parameter data.

[0027] It should be noted that electrical equipment failure means that the current and voltage of the electrical equipment are abnormal, resulting in the inability to operate normally.

[0028] S3. Establish a risk analysis model and analyze the impact of different parameter data on power equipment failures based on historical parameter data analysis results.

[0029] Specifically, the method steps are:

[0030] S31. Establish a risk analysis model, take the total working time T of the electrical equipment, the number of maintenance times S and the period length t of the interval under the corresponding maintenance times as independent variables, take the number of maintenance times Y of the electrical equipment as the dependent variable, analyze the influence of different parameter data on the failure of the electrical equipment, and calculate according to the formula:

[0031]

[0032] Among them, t grepresents the cycle duration of the electrical equipment in the g-th maintenance interval; α1 represents the influence of the total working time of the electrical equipment on the failure of the electrical equipment; α2 represents the influence of the cycle duration of the maintenance interval on the failure of the electrical equipment; a and b are both constant terms;

[0033] S32, selecting historical parameter data of electrical equipment failure from the database for analysis; determining the total working time T1, T2, ..., T of different electrical equipment respectively according to the operating cycle of the electrical equipment. m ; According to the fault records of the electrical equipment, determine the fault times Y1, Y2, ..., Y m ; According to the maintenance records of electrical equipment, determine the maintenance times S1, S2, ..., S of different electrical equipment respectively m , and determine the set H1, H2, ..., H consisting of the cycle duration of each maintenance interval of different electrical equipment m ;in, H j represents the set consisting of the cycle duration of each maintenance interval of the j-th electrical equipment; Respectively represent the cycle length of each maintenance interval of the jth electrical equipment; j = 1, 2, ..., m; S j represents the maintenance times of the jth electrical equipment;

[0034] S33, substituting the historical parameter data analysis results in step S32 as training parameters into the calculation formula of step S31 for fitting, and determining the values ​​of α1, α2, a and b.

[0035] It should be noted that the total working time of the electrical equipment is obtained by accumulating the operating cycle time of the electrical equipment; by establishing a risk analysis model, according to the historical parameter data analysis results, T1, T2, ..., T m As the training parameters of the total working time T, S1, S2, ..., S m As the training parameter of the maintenance number S, As the training parameters of the period length t of the interval corresponding to the number of maintenance times, Y1, Y2, ..., Y m As the training parameters of the maintenance times Y, they are substituted into the calculation formula of step S32 respectively, and the curve is fitted according to the least squares method to determine the values ​​of α1, α2, a and b; by analyzing the impact of different parameter data on the failure of electrical equipment, data support is provided for the safety risk level analysis of each sub-area, thereby improving the system's ability to analyze the data generated in the smart substation and the accuracy of safety judgment.

[0036] S4. Determine the electrical equipment currently operating in each sub-area, calculate the safety risk level of the electrical equipment in each sub-area based on the electrical equipment currently operating in each sub-area, the established risk analysis model and the real-time parameter data analysis results, and dynamically allocate regulatory resources to each sub-area based on the calculation results.

[0037] Specifically, the method steps are:

[0038] S41, analyzing the collected real-time parameter data, respectively determining the total working time, number of failures, number of maintenances and the period length of each maintenance interval of different current electrical equipment; according to the parameter data received by the integrated analysis platform, respectively determining the electrical equipment currently working in each sub-area, and obtaining the device number set P1, P2, ..., P corresponding to the electrical equipment currently working in each sub-area n ;

[0039] S42, according to P1, P2, ..., P n , the established risk analysis model and real-time parameter data analysis results are used to calculate the safety risk level F1, F2, ..., F of electrical equipment in each sub-area. n , according to the calculation formula:

[0040]

[0041] Among them, F i represents the security risk level of the i-th sub-area; i = 1, 2, ..., n; P i Indicates the device number set corresponding to the electrical devices currently working in the i-th sub-area; Indicates the total working time of the current r-th electrical equipment; Indicates the duration of the maintenance interval of the current r-th electrical equipment; Indicates the maintenance times of the current r-th electrical equipment; Indicates the number of failures of the current r-th electrical equipment;

[0042] S43. Calculate the safety risk level of different types of electrical equipment in each sub-area and assign weights. After accumulation, obtain the total safety risk level of electrical equipment in each sub-area. According to the total safety risk level of each sub-area, dynamically allocate regulatory resources to each sub-area.

[0043] It should be noted that, since each electrical device has a corresponding device number, each associated electrical device is equipped with a sensor. When the sensor sends parameter data, it carries the device number corresponding to the electrical device, so that the set P1, P2, ..., P nThe equipment number in is updated in real time with the operating status of the power-consuming equipment; where r and j are the numbers of the power-consuming equipment; since the data selected for analysis by the risk analysis model are historical parameter data with power-consuming equipment failures, in actual calculations, Therefore, the above calculation formula can reflect the degree of safety risk of electrical equipment in each sub-area; the supervision resources of each sub-area are dynamically allocated according to the calculation results, which solves the problem of unbalanced allocation of monitoring resources in smart substations.

[0044] It should be noted that steps S2-S4 are a process for calculating the safety risk level of electrical equipment of the same type in each sub-area. At this time, different types of equipment are determined according to the associated electrical equipment in the monitoring area, and steps S2-S4 are repeated to calculate the safety risk level of each type of electrical equipment in each sub-area. The management personnel set the corresponding weights for the safety risk level of each type of electrical equipment, and accumulate the weighted safety risk levels of each type of electrical equipment to obtain the total safety risk level of the electrical equipment in each sub-area, thereby dynamically allocating the supervision resources of each sub-area. For example: in one embodiment, the supervision resources are intelligent inspection robots, and the number of intelligent inspection robots is greater than n; at this time, the parameter data of the electrical equipment is collected and analyzed, and steps S2-S4 are repeated to calculate the safety risk level of each type of electrical equipment in each sub-area, and the calculated safety risk levels of each type of electrical equipment in each sub-area are weighted and accumulated to obtain the total safety risk level of each type of electrical equipment in each sub-area. according to The intelligent inspection robots are dispatched so that the number of intelligent inspection robots in each sub-area meets the requirements. At this time, when there is a equipment failure, the intelligent inspection robot can promptly check it, which improves the timeliness of the system's response to the failure and enhances the monitoring effect.

[0045] Furthermore, an interactive display platform is provided to digitally display the real-time parameter data analysis results and the calculated safety risk levels of electrical equipment in each sub-area; wherein, management personnel can manually allocate regulatory resources to each sub-area through the interactive display platform; wherein, when management personnel manually allocate regulatory resources to each sub-area through the interactive display platform, the regulatory resources to each sub-area are directly allocated according to the manual allocation results of the management personnel.

[0046] In the second embodiment: a real-time monitoring system for a smart substation based on data analysis is provided, the system comprising an equipment management module, a real-time data acquisition module, an integrated analysis platform, a model management module, an intelligent computing module and a monitoring display module;

[0047] The equipment management module is used to determine the monitoring area of ​​the smart substation, divide the monitoring area into different sub-areas, and determine the associated power-consuming equipment in the monitoring area;

[0048] The real-time data acquisition module is used to collect parameter data of the related electrical equipment in the monitoring area of ​​the equipment management module, store the collected parameter data in the database as historical data and continuously update it; the parameter data includes the operation cycle, fault record and maintenance record of the electrical equipment; provide a sensor, the sensor is used to send the collected parameter data to the integrated analysis platform;

[0049] The integrated analysis platform is used to receive and analyze parameter data sent by sensors in the real-time data acquisition module, determine the total working time of the electrical equipment according to the operating cycle of the electrical equipment; determine the number of failures of the electrical equipment according to the failure records of the electrical equipment; determine the number of maintenance of the electrical equipment and the cycle length of each maintenance interval according to the maintenance records of the electrical equipment; wherein the parameter data is divided into historical parameter data and real-time parameter data; the analysis results of the historical parameter data are sent to the model management module, and the analysis results of the real-time parameter data are sent to the intelligent computing module and the monitoring and display module;

[0050] The model management module is used to establish a risk analysis model and analyze the impact of different parameter data on power equipment failures based on the historical parameter data analysis results in the integrated analysis platform;

[0051] The intelligent calculation module is used to determine the electrical equipment currently working in each sub-area, calculate the safety risk level of the electrical equipment in each sub-area based on the electrical equipment currently working in each sub-area, the established risk analysis model and the real-time parameter data analysis results in the integrated analysis platform, and dynamically allocate the supervision resources of each sub-area based on the calculation results; send the calculated safety risk level of the electrical equipment in each sub-area to the monitoring and display module;

[0052] The monitoring and display module is used to provide an interactive display platform to digitally display the real-time parameter data analysis results and the calculated safety risk levels of electrical equipment in each sub-area.

[0053] Furthermore, the model management module includes a historical data analysis unit and a model training unit;

[0054] The historical data analysis unit is used to select historical parameter data of electrical equipment failure from the database for analysis; determine the total working hours of different electrical equipment according to the operating cycle of the electrical equipment; determine the number of failures of different electrical equipment according to the fault records of the electrical equipment; determine the number of maintenance of different electrical equipment according to the maintenance records of the electrical equipment, and determine a set consisting of the cycle duration of each maintenance interval of different electrical equipment; and send the analysis results to the model training unit;

[0055] The model training unit is used to establish a risk analysis model to analyze the impact of different parameter data on electrical equipment failures.

[0056] Furthermore, the intelligent computing module includes a real-time data analysis unit, a security risk degree calculation unit and a resource allocation unit;

[0057] The real-time data analysis unit is used to analyze the collected real-time parameter data to determine the total working time, number of failures, number of maintenances and the period length of each maintenance interval of different current electrical equipment; determine the electrical equipment currently working in each sub-area according to the parameter data received by the integrated analysis platform, and obtain the device number set corresponding to the electrical equipment currently working in each sub-area; and send the real-time parameter data analysis results to the safety risk degree calculation unit;

[0058] The safety risk degree calculation unit is used to calculate the safety risk degree of the electric equipment in each sub-area according to the electric equipment currently working in each sub-area, the established risk analysis model and the real-time parameter data analysis result; and send the calculated safety risk degree of the electric equipment in each sub-area to the resource allocation unit;

[0059] The resource allocation unit is used to dynamically allocate the supervision resources to each sub-area according to the calculated safety risk level of the electrical equipment in each sub-area.

[0060] In this embodiment:

[0061] Real-time monitoring of parameter data of electrical equipment in smart substations; the equipment management module determines the monitoring area of ​​the smart substation, divides the monitoring area into different sub-areas, and determines the associated electrical equipment in the monitoring area;

[0062] The real-time data acquisition module collects parameter data of electrical equipment, stores the collected parameter data in the database as historical data and continuously updates it; and provides sensors to send the collected parameter data to the integrated analysis platform;

[0063] The integrated analysis platform receives and analyzes the collected parameter data, sends the historical parameter data analysis results to the model management module, and sends the real-time parameter data analysis results to the intelligent computing module and the monitoring display module;

[0064] The historical data analysis unit in the model management module selects historical parameter data of power equipment failure from the database for analysis, and sends the analysis results to the model training unit; the model training unit establishes a risk analysis model to analyze the impact of different parameter data on power equipment failure;

[0065] The real-time data analysis unit in the intelligent computing module analyzes the collected real-time parameter data and sends the real-time parameter data analysis results to the safety risk degree calculation unit; the safety risk degree calculation unit calculates the safety risk degree of the electrical equipment in each sub-area and sends the calculated safety risk degree of the electrical equipment in each sub-area to the resource allocation unit; the resource allocation unit dynamically allocates the supervision resources of each sub-area according to the calculated safety risk degree of the electrical equipment in each sub-area; and sends the calculated safety risk degree of the electrical equipment in each sub-area to the monitoring and display module;

[0066] The monitoring and display module provides an interactive display platform to digitally display the real-time parameter data analysis results and the calculated safety risk level of electrical equipment in each sub-area. When the management personnel manually allocate the supervision resources of each sub-area through the interactive display platform, the monitoring and display module sends the management personnel's control signal to the intelligent computing module to directly and dynamically allocate the supervision resources of each sub-area.

[0067] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A real-time monitoring method for a smart substation based on data analysis, characterized in that: The method comprises the following steps: S1. Determine the monitoring area of ​​the smart substation, divide the monitoring area into different sub-areas, determine the associated power-consuming equipment in the monitoring area, and collect parameter data of the power-consuming equipment, store the collected parameter data in the database as historical data and continuously update it; the parameter data includes the operation cycle, fault record and maintenance record of the power-consuming equipment; S2. Analyze the collected parameter data, determine the total working time of the electrical equipment according to the operating cycle of the electrical equipment; determine the number of failures of the electrical equipment according to the failure record of the electrical equipment; determine the number of maintenance of the electrical equipment and the cycle length of each maintenance interval according to the maintenance record of the electrical equipment; wherein the parameter data is divided into historical parameter data and real-time parameter data; S3. Establish a risk analysis model and analyze the impact of different parameter data on power equipment failures based on historical parameter data analysis results; S4. Determine the electrical equipment currently operating in each sub-area, calculate the safety risk level of the electrical equipment in each sub-area based on the electrical equipment currently operating in each sub-area, the established risk analysis model and the real-time parameter data analysis results, and dynamically allocate regulatory resources to each sub-area based on the calculation results.

2. The method for real-time monitoring of a smart substation based on data analysis according to claim 1 is characterized in that: The monitoring area is divided into different sub-areas, the number of divided sub-areas n is determined, and the number of associated electrical devices m in the monitoring area is determined; wherein each electrical device has a corresponding device number; the electrical devices used in each parameter data analysis are devices of the same type; a sensor is installed on each associated electrical device; the sensor is used to send the collected parameter data to an integrated analysis platform, and the integrated analysis platform is used to receive the parameter data and perform analysis.

3. The method for real-time monitoring of a smart substation based on data analysis according to claim 2 is characterized in that: The method steps of step S3 are: S31. Establish a risk analysis model, take the total working time T of the electrical equipment, the number of maintenance times S and the period length t of the interval under the corresponding maintenance times as independent variables, take the number of maintenance times Y of the electrical equipment as the dependent variable, analyze the influence of different parameter data on the failure of the electrical equipment, and calculate according to the formula: Among them, t g represents the cycle duration of the electrical equipment in the g-th maintenance interval; α1 represents the influence of the total working time of the electrical equipment on the failure of the electrical equipment; α2 represents the influence of the cycle duration of the maintenance interval on the failure of the electrical equipment; a and b are both constant terms; S32, selecting historical parameter data of electrical equipment failure from the database for analysis; determining the total working time T1, T2, ..., T of different electrical equipment respectively according to the operating cycle of the electrical equipment. m ; According to the fault records of the electrical equipment, determine the fault times Y1, Y2, ..., Y m ; According to the maintenance records of electrical equipment, determine the maintenance times S1, S2, ..., S of different electrical equipment respectively m , and determine the set H1, H2, ..., H consisting of the cycle duration of each maintenance interval of different electrical equipment m ;in, H j represents the set of cycle durations of each maintenance interval of the jth electrical equipment; t j1 ,t j2 ,..., Respectively represent the cycle length of each maintenance interval of the jth electrical equipment; j = 1, 2, ..., m; S j represents the maintenance times of the jth electrical equipment; S33, substituting the historical parameter data analysis results in step S32 as training parameters into the calculation formula of step S31 for fitting, and determining the values ​​of α1, α2, a and b.

4. The method for real-time monitoring of a smart substation based on data analysis according to claim 3 is characterized in that: The method steps of step S4 are: S41, analyzing the collected real-time parameter data to determine the total working time, number of failures, number of maintenances and the cycle length of each maintenance interval of different current electrical equipment; According to the parameter data received by the integrated analysis platform, the electrical equipment currently working in each sub-area is determined respectively, and the device number set P1, P2, ..., P corresponding to the electrical equipment currently working in each sub-area is obtained. n ; S42, according to P1, P2, ..., P n , the established risk analysis model and real-time parameter data analysis results are used to calculate the safety risk level F1, F2, ..., F of electrical equipment in each sub-area. n , according to the calculation formula: Among them, F i represents the security risk level of the i-th sub-area; i = 1, 2, ..., n; P i Indicates the device number set corresponding to the electrical devices currently working in the i-th sub-area; Indicates the total working time of the current r-th electrical equipment; Indicates the duration of the maintenance interval of the current r-th electrical equipment; Indicates the maintenance times of the current r-th electrical equipment; Indicates the number of failures of the current r-th electrical equipment; S43. Calculate the safety risk level of different types of electrical equipment in each sub-area and assign weights. After accumulation, obtain the total safety risk level of electrical equipment in each sub-area. According to the total safety risk level of each sub-area, dynamically allocate regulatory resources to each sub-area.

5. The method for real-time monitoring of a smart substation based on data analysis according to claim 4 is characterized in that: An interactive display platform is provided to digitally display the real-time parameter data analysis results and the safety risk level of the calculated electrical equipment in each sub-area; managers can manually allocate regulatory resources to each sub-area through the interactive display platform.

6. A real-time monitoring system for smart substations based on data analysis, characterized in that: The system includes equipment management module, real-time data acquisition module, integrated analysis platform, model management module, intelligent computing module and monitoring display module; The equipment management module is used to determine the monitoring area of ​​the smart substation, divide the monitoring area into different sub-areas, and determine the associated power-consuming equipment in the monitoring area; The real-time data acquisition module is used to collect parameter data of the related electrical equipment in the monitoring area of ​​the equipment management module, store the collected parameter data in the database as historical data and continuously update it; the parameter data includes the operation cycle, fault record and maintenance record of the electrical equipment; provide a sensor, the sensor is used to send the collected parameter data to the integrated analysis platform; The integrated analysis platform is used to receive and analyze parameter data sent by sensors in the real-time data acquisition module, and determine the total working time of the electrical equipment according to the operating cycle of the electrical equipment; According to the fault records of the electrical equipment, the number of faults of the electrical equipment is determined; according to the maintenance records of the electrical equipment, the number of maintenance times of the electrical equipment and the period length of each maintenance interval are determined; wherein the parameter data is divided into historical parameter data and real-time parameter data; the historical parameter data analysis results are sent to the model management module, and the real-time parameter data analysis results are sent to the intelligent computing module and the monitoring display module; The model management module is used to establish a risk analysis model and analyze the impact of different parameter data on power equipment failures based on the historical parameter data analysis results in the integrated analysis platform; The intelligent calculation module is used to determine the electrical equipment currently working in each sub-area, calculate the safety risk level of the electrical equipment in each sub-area based on the electrical equipment currently working in each sub-area, the established risk analysis model and the real-time parameter data analysis results in the integrated analysis platform, and dynamically allocate the supervision resources of each sub-area based on the calculation results; send the calculated safety risk level of the electrical equipment in each sub-area to the monitoring and display module; The monitoring and display module is used to provide an interactive display platform to digitally display the real-time parameter data analysis results and the calculated safety risk levels of electrical equipment in each sub-area.

7. The real-time monitoring system for smart substations based on data analysis according to claim 6 is characterized in that: The model management module includes a historical data analysis unit and a model training unit; The historical data analysis unit is used to select historical parameter data of electrical equipment failure from the database for analysis; and determine the total working time of different electrical equipment according to the operating cycle of the electrical equipment; According to the fault records of the electrical equipment, the number of faults of different electrical equipment is determined respectively; according to the maintenance records of the electrical equipment, the number of maintenance times of different electrical equipment is determined respectively, and a set consisting of the period duration of each maintenance interval of different electrical equipment is determined; Send the analysis results to the model training unit; The model training unit is used to establish a risk analysis model to analyze the impact of different parameter data on electrical equipment failures.

8. The real-time monitoring system for smart substations based on data analysis according to claim 7 is characterized in that: The intelligent computing module includes a real-time data analysis unit, a security risk degree calculation unit and a resource allocation unit; The real-time data analysis unit is used to analyze the collected real-time parameter data to determine the total working time, number of failures, number of maintenances and the cycle length of each maintenance interval of different current electrical equipment; According to the parameter data received by the integrated analysis platform, the electrical equipment currently working in each sub-area is determined respectively, and a set of equipment numbers corresponding to the electrical equipment currently working in each sub-area is obtained; Sending the real-time parameter data analysis results to the safety risk degree calculation unit; The safety risk degree calculation unit is used to calculate the safety risk degree of the electrical equipment in each sub-area according to the electrical equipment currently working in each sub-area, the established risk analysis model and the real-time parameter data analysis results; Sending the calculated safety risk level of the electrical equipment in each sub-area to the resource allocation unit; The resource allocation unit is used to dynamically allocate the supervision resources to each sub-area according to the calculated safety risk level of the electrical equipment in each sub-area.

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