Intelligent control method and system for high voltage switch cabinet

Abstract

The present invention discloses an intelligent control method and system for a high-voltage switch cabinet, and relates to the technical field of switch cabinet control. The system discloses a switch cabinet monitoring module, a control intervention analysis module, a control rationality analysis module, and a control instruction execution module. The switch cabinet monitoring module and the control intervention analysis module are set, and the analysis sequence of the monitoring data of the high-voltage switch cabinet can be dynamically customized according to the characteristics and requirements of the high-voltage switch cabinet, so as to ensure that the key data of the high-voltage switch cabinet is analyzed first, and it is no longer necessary to analyze all the monitoring data of the high-voltage switch cabinet at the same time, so as to reasonably reduce the data analysis intensity of the control system, and deeply analyze the correlation and independence of the monitoring data, so as to ensure efficient and accurate analysis of whether the high-voltage switch cabinet needs intervention control.

Description

Technical Field

[0001] The present invention relates to the technical field of switch cabinet control, and more specifically, to an intelligent control method and system for a high-voltage switch cabinet. Background Art

[0002] In the power system, high-voltage switchgear is a key power distribution and control equipment, and its stability and reliability are crucial to ensure the normal operation of the power system. Traditional high-voltage switchgear control mainly relies on manual operation and simple automatic control systems. These systems often have problems such as slow response speed, inaccurate control and insufficient safety when dealing with complex and changing power environments and fault conditions.

[0003] First, traditional high-voltage switchgear monitoring systems usually collect and analyze all monitoring data indiscriminately. This method not only has a large amount of data processing, but also easily ignores the real-time and importance of key data, resulting in inaccurate and in-time judgment of the status of the high-voltage switchgear. Especially when the high-voltage switchgear is operating abnormally or fails, if the key data cannot be quickly located and analyzed, it will seriously affect the speed of fault discovery and processing.

[0004] Secondly, traditional control systems often lack intelligent control strategies when facing abnormalities or failures in high-voltage switchgear. Manual operation is not only time-consuming and laborious, but also easily affected by human factors, resulting in unreasonable and inefficient selection of control instructions. At the same time, simple automated control systems can often only execute preset fixed control processes and cannot be flexibly adjusted according to the real-time status of the high-voltage switchgear, thus limiting the accuracy and effectiveness of control.

[0005] Therefore, the present invention proposes an intelligent control method and system for a high-voltage switch cabinet. Summary of the invention

[0006] In view of the deficiencies in the prior art, an object of the present invention is to provide an intelligent control method and system for a high-voltage switch cabinet.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] An intelligent control system for a high-voltage switch cabinet, comprising a switch cabinet monitoring module, a control intervention analysis module, a control rationality analysis module, and a control instruction execution module;

[0009] The switch cabinet monitoring module is used to collect various types of monitoring data of the high-voltage switch cabinet in real time;

[0010] The manipulation intervention analysis module Time, update the sensor monitoring sequence of the high-voltage switchgear, analyze each type of monitoring data in turn according to the sensor monitoring sequence, obtain the data analysis index of each type of monitoring data after completing the data analysis, and synchronously update the control intervention value of the high-voltage switchgear. Based on the comparison result between the control intervention value and the control intervention threshold value, determine whether the high-voltage switchgear needs to be intervened and controlled;

[0011] When the high-voltage switchgear needs to be controlled, the control rationality analysis module constructs a switchgear control simulation model, and the switchgear control simulation model performs simulated control on the high-voltage switchgear. Each time a simulated control is completed, a control rationality value of the simulated control is obtained, and based on the comparison result between the control rationality value and the control rationality limit value, it is determined whether to send the control instruction of the simulated control to the control instruction execution module;

[0012] The control instruction execution module is used to execute the control instruction to control the high-voltage switch cabinet.

[0013] Furthermore, the sensor monitoring sequence update steps of the high-voltage switchgear are as follows: obtain the sensor monitoring prominent value of each type of monitoring data, sort each type of monitoring data in descending order according to the value of the sensor monitoring prominent value, and generate the sensor monitoring sequence of the high-voltage switchgear according to the sorting result.

[0014] Furthermore, the sensor monitoring prominent value is obtained as follows: obtain i data analysis indexes of a type of monitoring data obtained before the current time of the system, sort all data analysis indexes in the order of acquisition, mark the data analysis index as Datacs, c=1, 2, ..., C, c is the sorting number of the data analysis index, C is the total number of data analysis indexes, set the data analysis coefficient to Hbs, s=1, 2, ..., s, calculate the difference between two adjacent data analysis indexes after sorting and take the absolute value to obtain the data analysis floating value, sum all data analysis floating values ​​and take the average to obtain the floating mean AVfoa, and use the formula Get the sensor monitoring prominent value Prod of this type of monitoring data.

[0015] Furthermore, the data analysis index is obtained as follows: A type of monitoring data collected within a period of time is preprocessed, and then a monitoring analysis model for the type of monitoring data is obtained, the type of monitoring data is input into the monitoring analysis model, and the monitoring analysis model outputs a data analysis index for the type of monitoring data.

[0016] Furthermore, based on the comparison result between the control intervention value and the control intervention threshold value, it is determined whether the high-voltage switchgear needs to be intervened and controlled. Specifically, the control intervention threshold value is set. When the control intervention value of the high-voltage switchgear is greater than or equal to the control intervention threshold value, it is determined that the high-voltage switchgear needs to be intervened and controlled, and the data analysis of subsequent types of monitoring data in the sensor monitoring sequence is stopped simultaneously. When the control intervention value of the high-voltage switchgear is less than the control intervention threshold value, it is determined that the high-voltage switchgear does not need to be intervened and control, and the data analysis of the next type of monitoring data in the sensor monitoring sequence is continued.

[0017] Furthermore, the control intervention value of the high-voltage switchgear is updated as follows: all types of monitoring data that have completed data analysis in the sensor monitoring sequence are marked as control data, the data analysis index of the control data is obtained, the monitoring data influence diagram is obtained, all control data are matched in pairs, and when the two matched control data have an influence relationship line in the monitoring data influence diagram, the data analysis indexes of the two control data are summed and averaged to obtain the influence analysis index; when the two matched control data do not have an influence relationship line in the monitoring data influence diagram, the data analysis indexes of the two control data are difference calculated and the absolute value is taken to obtain the salient analysis index; all the influence analysis indices are summed and averaged to obtain the shadow score mean Effj; all the salient analysis indices are summed and averaged to obtain the convex score mean Minj; and the formula is used. The control intervention value Contp of the high-voltage switchgear is obtained, where u1 is the shadow coefficient and u2 is the convex coefficient.

[0018] Furthermore, a switch cabinet control simulation model is constructed, specifically: collecting high-voltage switch cabinet The real data of various types of monitoring data generated within a certain period of time can determine the high-voltage switchgear The expected data of various types of monitoring data within a certain period of time, and the switch cabinet control simulation model is built based on the real data and expected data.

[0019] Furthermore, based on the comparison result between the reasonable control value and the reasonable control limit, it is determined whether to send the control instruction of this simulated control to the control instruction execution module, specifically: setting the reasonable control limit, when the reasonable control value is greater than or equal to the reasonable control limit, the control instruction of this simulated control is sent to the control instruction execution module, when the reasonable control value is less than the reasonable control limit, the switch cabinet control simulation model performs the next simulated control on the high-voltage switch cabinet.

[0020] Furthermore, the reasonable control value of the simulation control is obtained as follows: During the simulation control process, each The duration of the simulation is to obtain the comprehensive state value of the high-voltage switchgear until the end of the simulation operation. All the comprehensive state values ​​of the high-voltage switchgear are sorted in the order of acquisition. The previous adjacent comprehensive state value after sorting is compared with the next comprehensive state value. When the previous comprehensive state value is greater than the next comprehensive state value, the effective operation times are increased once, and the total number of effective operation times is marked as Eive, and the total number of comprehensive state values ​​is marked as Statg. The formula is used The reasonable control value Rsean of the simulated control is obtained, where wa is the effective control coefficient and wb is the comprehensive state coefficient;

[0021] The comprehensive status value of the high-voltage switchgear is obtained as follows: The data analysis index of each type of monitoring data within the time period is summed and averaged to obtain the comprehensive status value of the high-voltage switchgear.

[0022] Furthermore, a method for intelligently controlling a high-voltage switch cabinet includes the following steps:

[0023] Step S1: collecting various types of monitoring data of high-voltage switchgear in real time;

[0024] Step S2: Time, update the sensor monitoring sequence of the high-voltage switchgear, and analyze each type of monitoring data in sequence according to the sensor monitoring sequence;

[0025] Step S3: when data analysis is completed for each type of monitoring data, the data analysis index of the type of monitoring data is obtained, the control intervention value of the high-voltage switchgear is updated synchronously, and based on the comparison result between the control intervention value and the control intervention threshold value, it is determined whether the high-voltage switchgear needs intervention control;

[0026] Step S4: When the high-voltage switchgear needs to be controlled, a switchgear control simulation model is constructed;

[0027] Step S5: the switch cabinet control simulation model performs simulated control on the high-voltage switch cabinet, and obtains a reasonable control value of the simulated control each time the simulated control is completed, and determines whether to send a control instruction of the simulated control to the control instruction execution module based on a comparison result between the reasonable control value and the reasonable control limit value;

[0028] Step S6: Execute the control instruction to control the high-voltage switch cabinet.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. The method of the present invention deeply analyzes the correlation and independence of the monitoring data, ensures efficient and accurate analysis of whether the high-voltage switchgear needs to be intervened and controlled, quickly and accurately selects appropriate control instructions to control the high-voltage switchgear, comprehensively considers the stability and efficiency of the high-voltage switchgear during the control process, and ensures the safety and reliability of the high-voltage switchgear;

[0031] 2. The system of the present invention can dynamically customize the analysis order of the high-voltage switchgear monitoring data according to the characteristics and requirements of the high-voltage switchgear by setting up a switchgear monitoring module and a control intervention analysis module, thereby ensuring that the key data of the high-voltage switchgear is analyzed first, and there is no need to analyze all the monitoring data of the high-voltage switchgear at the same time. The data analysis intensity of the control system can be reasonably reduced, and a reasonable control analysis module and a control instruction execution module can be set. When an abnormality occurs in the high-voltage switchgear, the high-voltage switchgear can be simulated and controlled in time, and the instructions of the simulated control can be deeply and comprehensively analyzed. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A method flow chart of an intelligent control method for a high-voltage switchgear;

[0033] Figure 2 It is a system module diagram of an intelligent control system for a high-voltage switchgear;

[0034] Figure 3 A determination flow chart for determining whether to send a control instruction of a simulated control to a control instruction execution module;

[0035] Figure 4 A flow chart for determining whether high-voltage switchgear requires intervention and control. DETAILED DESCRIPTION

[0036] Example 1: Reference Figure 1 , an intelligent control method for a high-voltage switch cabinet, comprising the following steps:

[0037] Step S1: Collect various types of monitoring data of high-voltage switchgear in real time.

[0038] Step S2: Duration, update the sensor monitoring sequence of the high-voltage switchgear, and analyze each type of monitoring data in turn according to the sensor monitoring sequence.

[0039] Step S3: When data analysis is completed for each type of monitoring data, the data analysis index of the type of monitoring data is obtained, and the control intervention value of the high-voltage switchgear is synchronously updated. Based on the comparison result between the control intervention value and the control intervention threshold value, it is determined whether the high-voltage switchgear needs intervention control.

[0040] Step S4: When the high-voltage switchgear needs to be controlled, a switchgear control simulation model is constructed.

[0041] Step S5: The switch cabinet control simulation model performs simulated control on the high-voltage switch cabinet. Each time a simulated control is completed, a reasonable control value of the simulated control is obtained. Based on the comparison result between the reasonable control value and the reasonable control limit, it is determined whether to send the control instruction of the simulated control to the control instruction execution module.

[0042] Step S6: Execute the control instruction to control the high-voltage switch cabinet.

[0043] The above method is used to deeply analyze the correlation and independence of the monitoring data, ensuring efficient and accurate analysis of whether the high-voltage switchgear needs to be controlled, quickly and accurately selecting appropriate control instructions to control the high-voltage switchgear, and comprehensively considering the stability and efficiency of the high-voltage switchgear during the control process to ensure the safety and reliability of the high-voltage switchgear.

[0044] Example 2: Reference Figure 2-Figure 4 , an intelligent control system for a high-voltage switchgear, including a switchgear monitoring module, a control intervention analysis module, a control rationality analysis module, and a control instruction execution module.

[0045] Switchgear monitoring module: real-time collection of various types of monitoring data of high-voltage switchgear (the monitoring data types of high-voltage switchgear include but are not limited to temperature data, current and voltage data, pressure data, insulation data, vibration data, gas composition data, partial discharge data, and the above types of monitoring data are collected in real time through corresponding sensors).

[0046] Operation intervention analysis module: Time duration, update the sensor monitoring sequence of the high-voltage switchgear (the sensor monitoring sequence contains various types of monitoring data that need to be collected by the high-voltage switchgear, and arranges the various types of monitoring data of the high-voltage switchgear in order. For example, the high-voltage switchgear needs to monitor five types of data: temperature data, current and voltage data, pressure data, insulation data, and vibration data. If the sensor monitoring sequence is 1, pressure data; 2, insulation data; 3, temperature data; 4, current and voltage data; 5, vibration data, it means that the pressure data is analyzed first, and the vibration data is analyzed last), analyze each type of monitoring data in turn according to the sensor monitoring sequence, and obtain the data analysis index of each type of monitoring data when the data analysis is completed for each type of monitoring data , synchronously update the control intervention value of the high-voltage switchgear, set the control intervention threshold value (the control intervention threshold value is the system preset value, and the preset value size is customized by the system). When the control intervention value of the high-voltage switchgear is greater than or equal to the control intervention threshold value, it is determined that the high-voltage switchgear needs to intervene in the control, and the data analysis of subsequent types of monitoring data in the sensor monitoring sequence is synchronously stopped. When the control intervention value of the high-voltage switchgear is less than the control intervention threshold value, it is determined that the high-voltage switchgear does not need to intervene in the control, and continue to perform data analysis on the next type of monitoring data in the sensor monitoring sequence (if all types of monitoring data in the sensor monitoring sequence are analyzed, and the control intervention value of the high-voltage switchgear is less than the control intervention threshold value, it means that there is no need to intervene in the control of the high-voltage switchgear).

[0047] The steps for updating the sensor monitoring sequence of the high-voltage switchgear are as follows: obtain the sensor monitoring prominent values ​​of each type of monitoring data, sort each type of monitoring data in descending order according to the values ​​of the sensor monitoring prominent values, and generate the sensor monitoring sequence of the high-voltage switchgear according to the sorting results.

[0048] The method for obtaining the prominent value of sensor monitoring is as follows: obtain i data analysis indexes of a type of monitoring data obtained before the current time of the system, sort all data analysis indexes in the order of acquisition, mark the data analysis index as Datacs, c=1, 2,…, C, c is the sorting number of the data analysis index, C is the total number of data analysis indexes, set the data analysis coefficient to Hbs, s=1, 2,…, s, Hb1<Hb2<…<Hbs, each data analysis index range corresponds to a data analysis coefficient, where the range of the data analysis index includes (0, Datac1], (Datac1, Datac2],…, (Datacs-1, Datacs], if the data analysis index Datacs∈(Datac1, Datac2], the data analysis coefficient is Hb2, calculate the difference between the two adjacent data analysis indexes after sorting and take the absolute value to obtain the data analysis floating value, sum and average all data analysis floating values ​​to obtain the floating mean AVfoa, and use the formula Get the sensor monitoring prominent value Prod of this type of monitoring data.

[0049] The data analysis index is obtained as follows: Preprocess a type of monitoring data collected within a certain period of time (taking pressure data as an example, The pressure data collected within the time period is preprocessed, and the preprocessing methods include data cleaning, data normalization, etc. The preprocessing method is not specifically limited in this embodiment), and then a monitoring and analysis model for this type of monitoring data is obtained, and this type of monitoring data is input into the monitoring and analysis model, and the monitoring and analysis model outputs a data analysis index for this type of monitoring data.

[0050] For high-voltage switchgear, different types of monitoring data correspond to different monitoring and analysis models. The difference between different monitoring and analysis models lies in the difference in training data. This embodiment takes pressure data as an example to disclose the construction process of the monitoring and analysis model: collect L groups of pressure data, each group of pressure data is limited to The pressure data can be collected within a certain period of time. The pressure data can be historically collected or virtually set for model training. A neural network model is constructed, and the pressure data is used as the training data of the neural network model (if it is a monitoring and analysis model for insulation data, L groups of insulation data are collected). A data analysis index is assigned to each training data. The value range of the data analysis index is (1~3). The closer the value of the data analysis index is to 3, the more abnormal the pressure data of the high-voltage switchgear is, and the closer the value of the data analysis index is to 1, the more normal the pressure data of the high-voltage switchgear is (if it is a monitoring and analysis model for insulation data, the closer the value of the data analysis index is to 3, the more abnormal the insulation data of the high-voltage switchgear is, and the closer the value of the data analysis index is to 1, the more normal the insulation data of the high-voltage switchgear is). The training data is divided into a training set, a validation set, and a test set according to the set ratio of 3:2:2. The neural network is iteratively trained on the training data. After the training is completed, a monitoring and analysis model for pressure data is constructed.

[0051] The updating method of the control intervention value of the high-voltage switchgear is as follows: mark all types of monitoring data that have completed data analysis in the sensor monitoring sequence as control data, obtain the data analysis index of the control data, obtain the monitoring data influence diagram, match all the control data in pairs, and when the two matched control data have an influence relationship line in the monitoring data influence diagram, sum and average the data analysis indexes of the two control data to obtain the influence analysis index; when the two matched control data do not have an influence relationship line in the monitoring data influence diagram, calculate the difference between the data analysis indexes of the two control data and take the absolute value to obtain the salient analysis index; sum and average all the influence analysis indexes to obtain the shadow score mean Effj; sum and average all the salient analysis indexes to obtain the convex score mean Minj; use the formula The control intervention value Contp of the high-voltage switchgear is obtained, where u1 is the shadow coefficient, u2 is the convex coefficient, the value of u1 is 0.57, and the value of u2 is 0.45.

[0052] The monitoring data influence diagram includes all types of monitoring data of the high-voltage switchgear, and displays the direct influence relationship between various types of monitoring data in the form of a relationship diagram. For example, partial discharge is a local electrical breakdown phenomenon occurring inside or on the surface of the insulating medium, which directly leads to a decrease in insulation performance. The decrease in insulation performance may increase the probability and intensity of partial discharge, indicating that there is a direct influence relationship between the insulation data and the partial discharge data. In this case, there is an influence relationship line between the insulation data and the partial discharge data in the monitoring data influence diagram. The vibration data reflects the movement state of the mechanical components inside the switchgear, and the gas composition data reflects the chemical state of the gas inside the switchgear. In this case, there is no influence relationship line between the vibration data and the gas composition data in the monitoring data influence diagram.

[0053] By setting up a switchgear monitoring module and a control intervention analysis module, the analysis order of the high-voltage switchgear monitoring data can be dynamically customized according to the characteristics and requirements of the high-voltage switchgear, ensuring that the key data of the high-voltage switchgear are analyzed first. It is no longer necessary to analyze all the monitoring data of the high-voltage switchgear at the same time, and the data analysis intensity of the control system can be reasonably reduced. The correlation and independence of the monitoring data can be deeply analyzed to ensure efficient and accurate analysis of whether the high-voltage switchgear needs to be intervened.

[0054] Reasonable control analysis module: When the high-voltage switchgear needs to be controlled, collect the high-voltage switchgear The real data of various types of monitoring data generated within a certain period of time can determine the high-voltage switchgear The expected data of various types of monitoring data within the time period (the expected data are various types of monitoring data of the high-voltage switchgear under ideal and normal conditions set by the system or humans), and the switchgear control simulation model is constructed based on the real data and the expected data. The switchgear control simulation model simulates the control of the high-voltage switchgear. After each simulated control, the reasonable control value of the simulated control is obtained, and the reasonable control limit is set (the reasonable control limit is the system preset value, and the preset value size is customized by the system). When the reasonable control value is greater than or equal to the reasonable control limit, the control instruction of the simulated control is sent to the control instruction execution module. When the reasonable control value is less than the reasonable control limit, the switchgear control simulation model performs the next simulated control on the high-voltage switchgear.

[0055] A switchgear operation simulation model is constructed based on real data and expected data. Specifically, a three-dimensional physical model of the high-voltage switchgear is established using software such as Solidworks and ANSYS, including its internal structure, material properties, contact resistance, etc. The electromagnetic field and thermal field inside the high-voltage switchgear are modeled using numerical methods such as the finite element method and the finite difference method. Factors such as the current distribution, voltage distribution, and temperature distribution inside the switchgear, as well as their interactions and influences, are considered. A contact resistance model between the components inside the switchgear is established, and the influence of contact resistance on current and voltage is considered, thereby completing the construction of the switchgear operation simulation model.

[0056] The reasonable control value of simulation control is obtained as follows: During the simulation control process, each duration, obtain the comprehensive status value of the high-voltage switchgear until the simulation control is completed (in order to ensure that there are multiple comprehensive status values ​​for analysis during the entire simulation control process, The duration will be set to be smaller to meet the requirement of multiple comprehensive status values ​​in the simulation control process). All comprehensive status values ​​of the high-voltage switchgear are sorted in the order of acquisition, and the previous adjacent comprehensive status value after sorting is compared with the next comprehensive status value. When the current comprehensive status value is greater than the next comprehensive status value, the effective control times are increased once. When the current comprehensive status value is less than or equal to the next comprehensive status value, no further processing is performed. The total number of effective control times is marked as Eive, and the total number of comprehensive status values ​​is marked as Statg. Using the formula The reasonable control value Rsean of the simulated control is obtained, where wa is the effective control coefficient, wb is the comprehensive state coefficient, the value of wa is 1.28, and the value of wb is 1.19.

[0057] The comprehensive status value of the high-voltage switchgear is obtained as follows: The data analysis index of each type of monitoring data within the time period is summed and averaged to obtain the comprehensive status value of the high-voltage switchgear.

[0058] Control instruction execution module: executes control instructions to control the high-voltage switchgear.

[0059] A reasonable control analysis module and a control instruction execution module are set up. When an abnormality occurs in the high-voltage switchgear, the high-voltage switchgear is simulated and controlled in time, and the simulated control instructions are deeply and comprehensively analyzed. The appropriate control instructions are selected quickly and accurately to control the high-voltage switchgear. The stability and efficiency of the high-voltage switchgear during the control process are comprehensively considered to ensure the safety and reliability of the high-voltage switchgear.

[0060] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0061] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0062] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0063] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0064] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0065] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0066] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0067] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An intelligent control system for a high-voltage switch cabinet, characterized in that: Including switch cabinet monitoring module, control intervention analysis module, control rationality analysis module, and control instruction execution module; The switch cabinet monitoring module is used to collect various types of monitoring data of the high-voltage switch cabinet in real time; The manipulation intervention analysis module is cabinet Time, update the sensor monitoring sequence of the high-voltage switchgear, analyze each type of monitoring data in turn according to the sensor monitoring sequence, obtain the data analysis index of each type of monitoring data after completing the data analysis, and synchronously update the control intervention value of the high-voltage switchgear. Based on the comparison result between the control intervention value and the control intervention threshold value, determine whether the high-voltage switchgear needs to be intervened and controlled; When the high-voltage switchgear needs to be controlled, the control rationality analysis module constructs a switchgear control simulation model, and the switchgear control simulation model performs simulated control on the high-voltage switchgear. Each time a simulated control is completed, a control rationality value of the simulated control is obtained, and based on the comparison result between the control rationality value and the control rationality limit value, it is determined whether to send the control instruction of the simulated control to the control instruction execution module; The control instruction execution module is used to execute the control instruction to control the high-voltage switch cabinet; The method for obtaining the outstanding value of sensor monitoring is as follows: obtain i data analysis indexes of a type of monitoring data obtained before the current time of the system, sort all data analysis indexes in the order of acquisition, mark the data analysis index as Datacs, c = 1, 2, ..., C, c is the sorting number of the data analysis index, C is the total number of data analysis indexes, set the data analysis coefficient to Hbs, calculate the difference between the two adjacent data analysis indexes after sorting and take the absolute value to obtain the data analysis floating value, sum up all data analysis floating values ​​and take the average to obtain the floating mean AVfoa, and use the formula Get the sensor monitoring outstanding value Prod of this type of monitoring data; The updating method of the control intervention value of the high-voltage switchgear is as follows: mark all types of monitoring data that have completed data analysis in the sensor monitoring sequence as control data, obtain the data analysis index of the control data, obtain the monitoring data influence diagram, match all the control data in pairs, and when the two matched control data have an influence relationship line in the monitoring data influence diagram, sum and average the data analysis indexes of the two control data to obtain the influence analysis index; when the two matched control data do not have an influence relationship line in the monitoring data influence diagram, calculate the difference between the data analysis indexes of the two control data and take the absolute value to obtain the salient analysis index; sum and average all the influence analysis indexes to obtain the shadow score mean Effj; sum and average all the salient analysis indexes to obtain the convex score mean Minj; use the formula The control intervention value Contp of the high-voltage switchgear is obtained, where u1 is the shadow coefficient and u2 is the convex coefficient.

2. The intelligent control system of a high-voltage switch cabinet according to claim 1 is characterized in that: The steps for updating the sensor monitoring sequence of the high-voltage switchgear are as follows: obtain the sensor monitoring prominent values ​​of each type of monitoring data, sort each type of monitoring data in descending order according to the values ​​of the sensor monitoring prominent values, and generate the sensor monitoring sequence of the high-voltage switchgear according to the sorting results.

3. The intelligent control system of a high-voltage switch cabinet according to claim 1 is characterized in that: The data analysis index is obtained as follows: cabinet A type of monitoring data collected within a period of time is preprocessed, and then a monitoring analysis model for the type of monitoring data is obtained, the type of monitoring data is input into the monitoring analysis model, and the monitoring analysis model outputs a data analysis index for the type of monitoring data.

4. The intelligent control system of a high-voltage switch cabinet according to claim 1 is characterized in that: Based on the comparison result between the control intervention value and the control intervention threshold value, determine whether the high-voltage switchgear needs to be intervened and controlled. Specifically, set the control intervention threshold value. When the control intervention value of the high-voltage switchgear is greater than or equal to the control intervention threshold value, determine that the high-voltage switchgear needs to be intervened and control, and simultaneously stop data analysis of subsequent types of monitoring data in the sensor monitoring sequence. When the control intervention value of the high-voltage switchgear is less than the control intervention threshold value, determine that the high-voltage switchgear does not need to be intervened and control, and continue to perform data analysis on the next type of monitoring data in the sensor monitoring sequence.

5. The intelligent control system for high-voltage switchgear according to claim 1, characterized in that: Construct a switch cabinet control simulation model, specifically: collect the high-voltage switch cabinet at T cabinet The real data of various types of monitoring data generated within T cabinet The expected data of various types of monitoring data within a certain period of time, and the switch cabinet control simulation model is built based on the real data and expected data.

6. The intelligent control system of a high-voltage switch cabinet according to claim 1, characterized in that: Based on the comparison result between the reasonable control value and the reasonable control limit, determine whether to send the control instruction of this simulated control to the control instruction execution module, specifically: set the reasonable control limit, when the reasonable control value is greater than or equal to the reasonable control limit, send the control instruction of this simulated control to the control instruction execution module, when the reasonable control value is less than the reasonable control limit, the switch cabinet control simulation model performs the next simulated control on the high-voltage switch cabinet.

7. The intelligent control system of a high-voltage switch cabinet according to claim 1, characterized in that: The reasonable control value of simulation control is obtained as follows: During the simulation control process, each T cabinet The duration of the simulation is to obtain the comprehensive state value of the high-voltage switchgear until the end of the simulation operation. All the comprehensive state values ​​of the high-voltage switchgear are sorted in the order of acquisition. The previous adjacent comprehensive state value after sorting is compared with the next comprehensive state value. When the previous comprehensive state value is greater than the next comprehensive state value, the effective operation times are increased once, and the total number of effective operation times is marked as Eive, and the total number of comprehensive state values ​​is marked as Statg. The formula is used The reasonable control value Rsean of the simulated control is obtained, where wa is the effective control coefficient and wb is the comprehensive state coefficient; The comprehensive status value of the high-voltage switchgear is obtained as follows: Get T cabinet The data analysis index of each type of monitoring data within the time period is summed up and averaged to obtain the comprehensive status value of the high-voltage switchgear.

8. An intelligent control method for a high-voltage switch cabinet, applied to execute an intelligent control system for a high-voltage switch cabinet according to any one of claims 1 to 7, characterized in that: The steps include: Step S1: collecting various types of monitoring data of high-voltage switchgear in real time; Step S2: Every T cabinet Time, update the sensor monitoring sequence of the high-voltage switchgear, and analyze each type of monitoring data in sequence according to the sensor monitoring sequence; Step S3: when data analysis is completed for each type of monitoring data, the data analysis index of the type of monitoring data is obtained, the control intervention value of the high-voltage switchgear is updated synchronously, and based on the comparison result between the control intervention value and the control intervention threshold value, it is determined whether the high-voltage switchgear needs intervention control; Step S4: When the high-voltage switchgear needs to be controlled, a switchgear control simulation model is constructed; Step S5: the switch cabinet control simulation model performs simulated control on the high-voltage switch cabinet, and obtains a reasonable control value of the simulated control each time the simulated control is completed, and determines whether to send a control instruction of the simulated control to the control instruction execution module based on a comparison result between the reasonable control value and the reasonable control limit value; Step S6: Execute the control instruction to control the high-voltage switch cabinet.

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