Insulation performance optimization system for distribution transformer full-enclosed transformer area

Abstract

The application relates to the technical field of insulation performance optimization, in particular to an insulation performance optimization system for a full-closed distribution transformer area. The system comprises a parameter acquisition module and a parameter processing module. The parameter acquisition module identifies an insulation performance aging parameter monitoring device, acquires corresponding aging parameters, divides aging correlation parameters in cooperation with the parameter processing module, divides response emergency parameters according to emergency quantities, and serves as an aging parameter monitoring device for real-time response starting. The corresponding aging parameter values are acquired in real time, the aging parameter values are evaluated, each group of correlated aging parameters is started in sequence after responding to abnormal values, and the aging parameter value combination uploaded through the planned response evaluation time serves as a parameter for aging state evaluation. The aging parameter monitoring device for real-time response starting can be reduced, the load of the full-closed distribution transformer area can be reduced, and meanwhile, the coverage monitoring can be realized, so that the aging parameter emergency acquisition effect is ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of insulation performance optimization, in particular to an insulation performance optimization system for a full-closed distribution transformer substation. BACKGROUND

[0002] In specific use, the full-closed distribution transformer substation is a compact power distribution system in which transformers, high-low voltage switch devices, protection devices and other power distribution devices are integrated in a closed metal box. The metal shell has an IP54 or above protection level, effectively isolating external environmental interference. It is mainly applied to urban core areas, rail transit, data centers and other scenes with high power supply reliability requirements.

[0003] The insulation performance of the full-closed distribution transformer substation can be affected by different aging parameters, such as temperature, humidity, oxygen content and smoke concentration. High temperature promotes molecular chain rupture, resulting in an increase in dielectric loss tangent and a decrease in volume resistivity, thereby affecting the insulation performance of the full-closed distribution transformer substation. When the relative humidity exceeds a certain range, the surface leakage current of the power distribution equipment increases exponentially, and the creepage distance effectiveness decreases, thereby affecting the insulation performance of the full-closed distribution transformer substation.

[0004] In order to respond to the influence of aging parameters on insulation performance in a timely manner, the existing processing method is to configure different aging parameter monitoring devices in the full-closed distribution transformer substation, and to collect the change state of each aging parameter in real time. Since different combinations of aging parameters can affect the insulation performance to varying degrees, the insulation performance result fed back by a single aging parameter is not accurate. At the same time, if each aging parameter monitoring device is continuously started, although real-time data collection can be performed, the corresponding load in the full-closed distribution transformer substation will also increase, which will also affect the insulation performance of the full-closed distribution transformer substation to some extent. Irregularly starting a few aging parameter monitoring devices will also reduce the monitoring feedback effect and fail to obtain parameter changes in the full-closed distribution transformer substation in a timely manner.

[0005] In order to solve the above problems, there is an urgent need for an insulation performance optimization system for a full-closed distribution transformer substation that responds to monitoring in sequence. SUMMARY

[0006] The purpose of the present application is to provide an insulation performance optimization system for a full-closed distribution transformer substation to solve the problems raised in the background.

[0007] To achieve the above purpose, an insulation performance optimization system for a full-closed distribution transformer substation is provided, which includes a device monitoring end, a parameter acquisition module, a parameter processing module, an associated item parameter value change feedback module and an insulation performance response optimization module.

[0008] The device monitoring end is used for configuring insulation performance aging parameter monitoring devices to monitor and process aging parameters of the full-enclosed transformer substation;

[0009] The parameter acquisition module is used for identifying the insulation performance aging parameter monitoring devices and acquiring corresponding aging parameters;

[0010] The parameter processing module combines historical insulation performance optimization evaluation information, divides aging correlation parameters, and calculates emergency quantities of each aging correlation parameter, divides response emergency parameters through the emergency quantities, and plans starting sequences of each insulation performance aging parameter monitoring device according to the emergency quantities and the aging correlation parameters;

[0011] The correlation parameter value change feedback module acquires aging parameter values in different time periods and binds and feeds back the aging correlation parameters;

[0012] The insulation performance response optimization module is used for establishing an insulation performance optimization mechanism, responding to the aging correlation parameters of the binding feedback, and matching corresponding optimization schemes according to the insulation performance optimization mechanism.

[0013] As a further improvement of the technical solution, the corresponding aging parameters in the device monitoring end include temperature, humidity, SF6 gas concentration, oxygen content, ozone concentration, smoke concentration, water level or water immersion information, and space noise in the enclosed substation;

[0014] The parameter monitoring device for temperature is a resistance temperature detector;

[0015] The parameter monitoring device for humidity is a humidity sensor, which is used for measuring the moisture content in the enclosed substation;

[0016] The parameter monitoring device for SF6 gas concentration is an SF6 gas detector;

[0017] The parameter monitoring device for oxygen content is an electrochemical oxygen sensor, which monitors the oxygen percentage in the air in the enclosed substation;

[0018] The parameter monitoring device for ozone concentration is a fixed ozone sensor;

[0019] The parameter monitoring device for smoke concentration is a photoelectric sensor, which is used for detecting the particulate matter concentration in the air in the enclosed substation;

[0020] The parameter monitoring device for water level or water immersion information is a pressure sensor, which monitors the water level;

[0021] The parameter monitoring device for space noise in the enclosed substation is a sound level meter measuring sound pressure level sensor.

[0022] As a further improvement of the technical solution, the method for dividing the aging correlation parameters in the parameter processing module comprises the following steps:

[0023] S301, obtaining each aging state, and collecting each aging parameter in the aging state by cooperating with the parameter monitoring device;

[0024] S302, dividing the normal value range of each aging parameter in the full-enclosed distribution transformer area in the normal state;

[0025] S303, marking the aging parameter value in the aging state, and comparing with the corresponding normal value range;

[0026] The aging parameter value exceeding the normal value range is marked as an abnormal aging parameter value, each abnormal aging parameter causing the same aging state is marked as an aging correlation parameter, and the change trend of the aging correlation parameter is marked;

[0027] The aging parameter value not exceeding the normal value range is marked as a normal aging parameter value.

[0028] As a further improvement of the technical solution, the emergency quantity in the parameter processing module comprises a correlation rate and a change rate.

[0029] As a further improvement of the technical solution, the method for calculating the emergency quantity of each aging correlation parameter in the parameter processing module comprises the following steps:

[0030] S3010, calculating the correlation rate of each aging correlation parameter, wherein the algorithm formula of the correlation rate is as follows:

[0031] ;

[0032] Wherein is the correlation rate, is the number of aging correlation parameter groups associated with the current aging parameter, is the total number of aging correlation parameters;

[0033] S3011, calculating the change rate of each aging parameter, and the corresponding algorithm formula is as follows:

[0034] ;

[0035] Wherein is the change rate, to is the value exceeding the normal value range in the historical detection process, n is the total number of detection statistics, is the unit detection quantity;

[0036] S3012, according to the correlation rate and the change rate The final emergency quantity is calculated, and the corresponding algorithm formula is as follows:

[0037] ;

[0038] Wherein is the emergency quantity, is the correlation rate is the weight coefficient of the correlation rate, is the weight coefficient of the change rate .

[0039] As a further improvement of the technical solution, the method steps of dividing the response emergency parameters by the emergency quantity in the parameter processing module are as follows:

[0040] S3020, respectively calculating the emergency quantity of each aging parameter, and sequentially dividing each aging parameter according to the emergency quantity;

[0041] S3021, using the division order to select the emergency parameter, and feeding back the coverage range of the emergency parameter in real time until the selected emergency parameter covers all the aging correlation parameters of the group.

[0042] As a further improvement of the technical solution, the method of planning the starting order of each insulation performance aging parameter monitoring device in the parameter processing module is as follows:

[0043] S3030, determining the correlation state of each emergency parameter;

[0044] Marking only one group of aging correlation parameters as a single correlation emergency parameter;

[0045] Marking multiple groups of aging correlation parameters as multiple group correlation emergency parameters;

[0046] S3031, for the single correlation emergency parameter, each aging parameter in the associated aging correlation parameter corresponds to the aging parameter monitoring device which starts at the same time;

[0047] S3032, for the multiple group correlation emergency parameter, each aging parameter in the associated aging correlation parameter corresponds to the aging parameter monitoring device which starts according to the emergency quantity order, and if the first aging parameter monitoring device of one group of aging correlation parameters does not monitor abnormal data, the aging parameter monitoring device corresponding to the aging parameter with the highest order in another group of aging correlation parameters starts;

[0048] When all the aging parameter monitoring devices of the emergency quantity in all groups of aging correlation parameters do not monitor abnormal data, the aging parameters of each group of aging correlation parameters which are not monitored are sequentially monitored again;

[0049] S3033, according to the above steps, the monitoring work is carried out in turn until the monitoring work of all aging parameters in each group of aging associated parameters is completed.

[0050] As a further improvement of the technical solution, the method for binding feedback according to the aging associated parameters in the parameter value change feedback module comprises the following steps:

[0051] S401, obtaining the unit monitoring time of the aging parameter monitoring device corresponding to each emergency parameter;

[0052] S402, selecting the longest unit monitoring time as the response evaluation time, and uploading the parameter values corresponding to all emergency parameters every interval response evaluation time;

[0053] S403, when an abnormal parameter value appears, mark the emergency parameter therein, and respond to start the aging parameter monitoring device corresponding to the aging parameter in the aging associated parameter associated with the emergency parameter, and perform associated judgment;

[0054] When the emergency parameter is a single associated emergency parameter, the longest unit monitoring time of the aging parameter monitoring device therein is the response upload time;

[0055] When the emergency parameter is a plurality of groups of associated emergency parameters, the sum of the unit monitoring time of the aging parameter monitoring device corresponding to each group of aging parameters is the response upload time.

[0056] As a further improvement of the technical solution, the insulation performance response optimization module establishes an insulation performance optimization mechanism, which comprises the following steps:

[0057] S501, obtaining various types of emergency parameters, and matching the corresponding response evaluation time;

[0058] S502, according to the aging parameter value combination uploaded by the response evaluation time, the aging state is evaluated;

[0059] S503, according to the historical detection information, matching the optimization scheme of each aging state.

[0060] Compared with the prior art, the beneficial effects of the present application are:

[0061] In the insulation performance optimization system of the fully-enclosed distribution transformer area, the insulation performance aging parameter monitoring equipment is identified through the parameter acquisition module, the corresponding aging parameters are acquired, the aging correlation parameters are divided in cooperation with the parameter processing module, the emergency parameters are divided according to the emergency quantity, the aging parameter monitoring equipment is started in real time, the corresponding aging parameter values are acquired in real time, the aging parameter values are evaluated, the abnormal values are responded, the aging parameters of each group are started in sequence, and the aging parameter value combination uploaded through the planned response evaluation time is taken as the parameter of the aging state evaluation, which can reduce the aging parameter monitoring equipment started in real time, reduce the load of the fully-enclosed distribution transformer area, and realize covering monitoring and ensure the emergency acquisition effect of the aging parameters. BRIEF DESCRIPTION OF DRAWINGS

[0062] Figure 1 The figure is a whole structure diagram of the application.

[0063] The meanings of various signs in the figure are as follows:

[0064] 10, equipment monitoring end;

[0065] 20, parameter acquisition module;

[0066] 30, parameter processing module;

[0067] 40, correlation parameter value change feedback module;

[0068] 50, insulation performance response optimization module. DETAILED DESCRIPTION

[0069] The technical solutions in the embodiments of the application will be described clearly and completely in combination with the drawings in the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the application.

[0070] Please refer to Figure 1 As shown in the figure, the insulation performance optimization system of the fully-enclosed distribution transformer area is provided, which comprises an equipment monitoring end 10, a parameter acquisition module 20, a parameter processing module 30, a correlation parameter value change feedback module 40 and an insulation performance response optimization module 50.

[0071] The equipment monitoring end 10 is used for configuring the insulation performance aging parameter monitoring equipment, and monitoring and processing the aging parameters of the fully-enclosed distribution transformer area.

[0072] The parameter acquisition module 20 is used for identifying the insulation performance aging parameter monitoring equipment and acquiring the corresponding aging parameters.

[0073] The parameter processing module 30 combines the historical insulation performance optimization evaluation information, divides the aging correlation parameters, and calculates the emergency quantities of each aging correlation parameter. The response emergency parameters are divided by the emergency quantities, and the starting order of each insulation performance aging parameter monitoring device is planned according to the emergency quantities and the aging correlation parameters.

[0074] The correlation parameter value change feedback module 40 collects the aging parameter values at different time periods and binds the feedback according to the aging correlation parameters.

[0075] The insulation performance response optimization module 50 is used to establish an insulation performance optimization mechanism, respond to the aging correlation parameters of the binding feedback, and match the corresponding optimization scheme according to the insulation performance optimization mechanism.

[0076] The specific content is as follows:

[0077] First, the insulation performance aging parameter monitoring device is configured through the device monitoring end 10 to monitor the aging parameters of the full-enclosed transformer substation. The corresponding aging parameters include temperature, humidity, SF6 gas concentration, oxygen content, ozone concentration, smoke concentration, water level or water immersion information, and space noise in the enclosed substation.

[0078] The parameter monitoring device for temperature is a resistance temperature detector, such as a PT100 RTD detector, which can provide high-precision temperature measurement and is suitable for a detection range of -200℃ to 850℃.

[0079] The parameter monitoring device for humidity is a humidity sensor used to measure the moisture content in the enclosed substation.

[0080] The parameter monitoring device for SF6 gas concentration is an SF6 gas detector, specifically an infrared absorption type detector.

[0081] The parameter monitoring device for oxygen content is an electrochemical oxygen sensor that monitors the oxygen percentage in the air in the enclosed substation.

[0082] The parameter monitoring device for ozone concentration is a fixed ozone sensor that measures ozone concentration based on ultraviolet absorption.

[0083] The parameter monitoring device for smoke concentration is a photoelectric sensor used to detect the particulate matter concentration in the air in the enclosed substation.

[0084] The parameter monitoring device for water level or water immersion information is a pressure sensor that monitors water level height.

[0085] The parameter monitoring device for space noise in the enclosed substation is a sound level meter that measures sound pressure level sensors, providing real-time decibel values and frequency spectrum analysis.

[0086] After completing the configuration of the parameter monitoring device, each parameter monitoring device is marked with a serial number, such as parameter monitoring device 1, parameter monitoring device 2, and parameter monitoring device N, as the basis for subsequent response initiation.

[0087] Further, the parameter monitoring device for identifying the insulation performance aging parameter is identified by the parameter acquisition module 20, i.e., the corresponding serial number mark, and the corresponding aging parameters are collected. Since the distribution transformer full-closed area is in a normal state under normal circumstances, the real-time start of each parameter monitoring device will cause the load of the entire distribution transformer full-closed area to increase, and will also interfere with the later optimization. In order to reduce the load and interference, the parameter processing module 30 combines historical insulation performance optimization evaluation information to divide the aging correlation parameters. The specific division method is as follows:

[0088] First, collect the historical insulation performance optimization evaluation information to obtain each aging state, and collect each aging parameter under the aging state in cooperation with the parameter monitoring device, i.e., divide the normal value range of each aging parameter in the distribution transformer full-closed area under normal conditions. After the aging state occurs, the real-time aging parameters are obtained and compared with the corresponding normal value range. The aging parameters that exceed the normal value range are marked as abnormal aging parameters. Each abnormal aging parameter that causes the same aging state is marked as an aging correlation parameter, and the change trend of the aging correlation parameter is marked, such as a decrease in SF6 gas concentration, an increase in corresponding ozone concentration, and an increase in space noise decibels in the closed area. The aging state caused by the simultaneous abnormality of these three aging correlation parameters is: the power frequency withstand voltage value decreases, and the reason is that the discharge decomposition product reduces the SF6 insulation strength, thereby causing the power frequency withstand voltage value to decrease.

[0089] Further, after completing the aging correlation parameter division work, some aging parameters will have a higher change frequency. This aging parameter will form different groups of aging correlation parameters with other different aging parameters, such as humidity, temperature, and water immersion abnormalities, which will cause the ground shielding layer to be damaged and the electric field distortion to be aggravated. When humidity and smoke anomalies cause the equivalent distance of the surface creepage to be shortened, therefore, in this scheme, the parameter processing module 30 calculates the emergency quantity of each aging correlation parameter, and divides the response emergency parameters by the emergency quantity. The emergency quantity includes the correlation rate and the change rate. The corresponding division steps are as follows:

[0090] First, the correlation rate of each aging correlation parameter is calculated, and the algorithm formula of the correlation rate is as follows:

[0091] ;

[0092] wherein is the correlation rate, is the number of aging correlation parameter groups associated with the current aging parameter, is the total number of aging correlation parameters;

[0093] The change rate of each aging parameter is then calculated, and the corresponding algorithm formula is as follows:

[0094]

[0095] wherein is the change rate, to is the number of values exceeding the normal value range in the historical detection process, n is the total number of detection statistics, is the unit detection amount, that is, the minimum change amount in the corresponding detection equipment;

[0096] Finally, the final emergency amount is calculated according to the correlation rate and the change rate , and the corresponding algorithm formula is as follows:

[0097]

[0098] wherein is the emergency amount, is the weight coefficient of the correlation rate , and is the weight coefficient of the change rate ;

[0099] After the calculation of the emergency amount is completed, the response emergency parameter is divided by the emergency amount, and the specific method is as follows:

[0100] First, the emergency amount of each aging parameter is calculated, and the aging parameters of each aging correlation parameter group are obtained according to the order division of the aging parameters. The emergency parameter is selected by using the order division, and the coverage range of the emergency parameter is fed back in real time until the selected emergency parameter covers all the aging correlation parameters of the group, that is, in the process of selecting the emergency parameter, one or more of the aging correlation parameters in each group need to be selected for real-time feedback monitoring. When data anomalies occur in the emergency parameter during monitoring, the remaining aging parameters in the feedback aging correlation parameters are started in turn for order detection. Therefore, each aging parameter in the aging correlation parameter group is also started in response to the emergency amount, for example, the aging correlation parameter group composed of humidity, temperature and water immersion, the emergency amount of humidity > the emergency amount of temperature > the emergency amount of water immersion, and the corresponding humidity aging parameter is the emergency parameter in the aging correlation parameter group, that is, the aging parameter monitoring equipment for monitoring the change of humidity is monitored in real time, and the aging parameter monitoring equipment for monitoring temperature and the aging parameter monitoring equipment for monitoring water immersion are started in response, and the starting order is to start the aging parameter monitoring equipment for monitoring temperature first, and then start the aging parameter monitoring equipment for monitoring water immersion.

[0101] ​​It is worth mentioning that when one of the emergency parameters represents a plurality of groups of aging correlation parameters for real-time monitoring and monitoring abnormalities occur, the corresponding group of aging correlation parameters of each aging parameter is still according to the order of the emergency amount to start the response, but if one of the first group of aging correlation parameters of the aging parameter monitoring device does not monitor abnormal data, the order of the aging parameter monitoring device corresponding to the aging parameter with the highest priority in the other group of aging correlation parameters is responded, for example, by In the first group, the corresponding emergency parameter is A, and the aging correlation parameters consisting of A, M, N and L are marked as the first group. In the second group, the corresponding emergency parameter is also A, and the aging correlation parameters consisting of A, X and Y are marked as the third group, and the corresponding emergency parameter is A. At this time, the aging parameter monitoring device corresponding to the emergency parameter starts real-time monitoring. When the value is abnormal, the aging parameter monitoring device corresponding to the aging parameter with the highest emergency amount in each group needs to be started in response to the emergency amount. The aging parameter M in the second group has the highest emergency amount, and the aging parameter monitoring device corresponding to the aging parameter M is started in response to the emergency amount. If no abnormalities are found, skip the monitoring work of the second group, compare the emergency amount of the remaining aging parameters in the first group and the third group, and the aging parameter B in the first group is in the highest value. At this time, the aging parameter monitoring device corresponding to the aging parameter B is continued to be started in response to the emergency amount. If no abnormalities are found, the aging parameter monitoring device corresponding to the aging parameter with the highest emergency amount in the third group is directly started in response to the emergency amount. If abnormalities occur, the aging parameter monitoring device corresponding to the remaining aging parameters in the group is sequentially responded, and vice versa. If no abnormalities still occur, the aging parameters in each group of aging correlation parameters that have not been monitored are monitored in order according to the above steps, and the monitoring work of all aging parameters in each group of aging correlation parameters is completed.

[0102] In the specific monitoring process, the aging parameter value in different time periods is collected by the correlation item parameter value change feedback module 40, and the aging correlation parameters are bound and fed back. The unit monitoring time of the aging parameter monitoring equipment corresponding to each emergency parameter needs to be obtained, that is, the time consumed from monitoring to uploading the value. The longest unit monitoring time is selected as the response evaluation time by comparing each unit monitoring time. The parameter values corresponding to all emergency parameters are uploaded every interval of the response evaluation time. When an abnormal parameter value appears, the emergency parameter is marked, and the aging parameter monitoring equipment corresponding to the aging parameter in the aging correlation parameter associated with the emergency parameter is started in response, and the correlation is determined. When the emergency parameter is single correlation, that is, the emergency parameter is only associated with a group of aging correlation parameters, the response upload time is also the longest unit monitoring time consumed by the aging parameter monitoring equipment in it. When the emergency parameter is multi-group correlation, the response upload time is the sum of the unit monitoring time of the aging parameter monitoring equipment corresponding to each group of aging parameters. For example, there are four groups of aging correlation parameters, which are , , and , wherein , and are emergency parameters, the emergency parameter corresponding to the aging parameter monitoring equipment consumes 6 minutes of unit monitoring time, the emergency parameter corresponding to the aging parameter monitoring equipment consumes 10 minutes of unit monitoring time, and the emergency parameter corresponding to the aging parameter monitoring equipment consumes 9 minutes of unit monitoring time. At this time, the response evaluation time is 10 minutes, that is, the parameter values corresponding to the emergency parameter , the parameter values corresponding to the emergency parameter and the parameter values corresponding to the emergency parameter are uploaded every 10 minutes. When the parameter value corresponding to the emergency parameter is abnormal, the aging parameter monitoring equipment corresponding to the aging parameter in each group of aging correlation parameters is started in the order of emergency quantity, and the sum of the unit monitoring time of the corresponding aging parameter monitoring equipment is obtained as the response evaluation time. When the parameter value corresponding to the emergency parameter is abnormal, the and The unit monitoring time of the aging parameter monitoring device is compared, and the unit monitoring time with the highest value is selected as the response evaluation time.

[0103] Finally, the insulation performance optimization mechanism is established by the insulation performance response optimization module 50, the aging associated parameters of the binding feedback are responded, the corresponding optimization scheme is matched according to the insulation performance optimization mechanism, and the specific method is as follows:

[0104] Firstly, the emergency parameters of various association types, i.e., single association and multiple groups of association, are obtained, the corresponding response evaluation time is matched, the aging state is evaluated according to the aging parameter value combination uploaded according to the response evaluation time, the optimization scheme of each aging state is matched according to the historical detection information.

[0105] The insulation performance aging parameter monitoring device is identified by the parameter acquisition module 20, the corresponding aging parameters are collected, the aging associated parameters are divided by the parameter processing module 30, and the response emergency parameters are divided according to the emergency quantity, which are the aging parameter monitoring devices for real-time response start, the corresponding aging parameter values are obtained in real time, the aging parameter values are evaluated, each group of associated aging parameters is started in order after responding to abnormal values, and the aging parameter value combination uploaded through the planned response evaluation time is used as the parameter for aging state evaluation, which can reduce the aging parameter monitoring devices for real-time response start, reduce the load of the full-closed distribution transformer area, and realize the coverage monitoring, and ensure the aging parameter emergency collection effect.

[0106] The basic principles, main features and advantages of the present application are shown and described above. It should be understood by those skilled in the art that the present application is not limited by the above examples, and the above examples and descriptions in the specification are only preferred examples of the present application, and are not used to limit the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. An insulation performance optimization system for fully enclosed distribution transformer areas, characterized in that: It includes an equipment monitoring terminal (10), a parameter acquisition module (20), a parameter processing module (30), a correlation parameter value change feedback module (40), and an insulation performance response optimization module (50); The equipment monitoring terminal (10) is used to configure insulation performance aging parameter monitoring equipment to monitor and process the aging parameters of the fully enclosed distribution transformer area; The parameter acquisition module (20) is used to identify the insulation performance aging parameter monitoring equipment and collect and classify the corresponding aging parameters; The parameter processing module (30) combines historical insulation performance optimization evaluation information to divide aging-related parameters and calculate the emergency quantity of each aging-related parameter. It divides the emergency response parameters based on the emergency quantity and plans the start-up order of each insulation performance aging parameter monitoring device according to the emergency quantity and aging-related parameters. The method for planning the startup sequence of each insulation performance aging parameter monitoring device in the parameter processing module (30) is as follows: S3030, Determine the correlation status of each emergency parameter; Mark aging parameters that are associated with only one group as single-association emergency parameters; Mark multiple sets of aging-related parameters as multiple sets of associated emergency parameters; S3031. For a single associated emergency parameter, the aging parameter monitoring devices corresponding to each aging parameter in the associated aging associated parameters are activated simultaneously. S3032. For multiple sets of associated emergency parameters, the aging parameter monitoring devices corresponding to each aging parameter in the associated aging parameters are started in order of emergency quantity. If the aging parameter monitoring device that is started first in one set of aging parameters does not detect abnormal data, the aging parameter monitoring device corresponding to the aging parameter that is started first in another set of aging parameters will be started in order. If the monitoring equipment for the aging parameters with the highest emergency response value in all aging-related parameters of all groups does not detect abnormal data, then the aging parameters that were not monitored in each group of aging-related parameters will be re-monitored according to the emergency response value. S3033. Follow the above steps to perform the monitoring work in sequence until all aging parameters in each group of aging-related parameters have been monitored. The correlation parameter value change feedback module (40) collects aging parameter values ​​under different time periods and performs binding feedback based on aging correlation parameters. The insulation performance response optimization module (50) is used to establish an insulation performance optimization mechanism, respond to the aging-related parameters of the feedback, and match the corresponding optimization scheme according to the insulation performance optimization mechanism.

2. The insulation performance optimization system for fully enclosed distribution transformer areas according to claim 1, characterized in that: The aging parameters corresponding to the equipment monitoring terminal (10) include temperature, humidity, SF6 gas concentration, oxygen content, ozone concentration, smoke concentration, water level or water immersion information, and spatial noise in the enclosed area. The device used for monitoring temperature parameters is a resistance temperature detector; The humidity monitoring device is a humidity sensor, used to measure the moisture content within the enclosed area. The equipment for monitoring parameters related to SF6 gas concentration is an SF6 gas detector; The equipment for monitoring oxygen content is an electrochemical oxygen sensor, which monitors the percentage of oxygen in the air within the enclosed area. The equipment used for monitoring ozone concentration parameters is a fixed ozone sensor; The parameter monitoring equipment for smoke concentration is a photoelectric sensor, which is used to detect the concentration of particulate matter in the air within the enclosed area. The parameter monitoring equipment for water level or flooding information is a pressure sensor, which monitors the water level height. The equipment for monitoring parameters of noise in the enclosed area is a sound level meter, which is a sound pressure level sensor.

3. The insulation performance optimization system for fully enclosed distribution transformer areas according to claim 1, characterized in that: The method for dividing aging-related parameters in the parameter processing module (30) includes the following steps: S301. Obtain various aging states and collect various aging parameters under the aging state in conjunction with parameter monitoring equipment; S302. Define the normal value range of various aging parameters in the fully enclosed distribution transformer area under normal conditions; S303. Mark the aging parameter values ​​under aging conditions and compare them with the corresponding normal value range; Aging parameters that exceed the normal range are marked as abnormal aging parameter values. All abnormal aging parameters that cause the same aging state are marked as aging-related parameters, and the changing trend of aging-related parameters is marked. Aging parameters that do not exceed the normal range are marked as normal aging parameter values.

4. The insulation performance optimization system for fully enclosed distribution transformer areas according to claim 3, characterized in that: The emergency quantities in the parameter processing module (30) include correlation rate and change rate.

5. The insulation performance optimization system for fully enclosed distribution transformer areas according to claim 4, characterized in that: The method for calculating the emergency quantities of various aging-related parameters in the parameter processing module (30) includes the following steps: S3010. Calculate the correlation rate of each aging-related parameter. The algorithm formula for the correlation rate is as follows: ； in For correlation rate, This represents the number of aging-related parameter groups associated with the current aging parameter. This represents the total number of aging-related parameter groups. S3011. Calculate the rate of change of each aging parameter. The corresponding algorithm formula is as follows: ； in For the rate of change, to This represents values ​​that exceeded the normal range during historical testing, where n is the total number of tests. Unit testing quantity; S3012, Based on the correlation rate and rate of change The final emergency response amount is calculated using the following algorithm formula: ； in For emergency use only. For correlation rate The weighting coefficients, rate of change The weighting coefficients.

6. The insulation performance optimization system for fully enclosed distribution transformer areas according to claim 5, characterized in that: The method steps for dividing emergency response parameters by emergency quantity in the parameter processing module (30) are as follows: S3020. Calculate the emergency quantity for each aging parameter separately, and classify the aging parameters according to the emergency quantity. S3021. Emergency parameters are selected based on the order of division, and the coverage of emergency parameters is fed back in real time until the selected emergency parameters cover the aging-related parameters of all groups.

7. The insulation performance optimization system for fully enclosed distribution transformer areas according to claim 1, characterized in that: The method for binding feedback based on aging-related parameters in the joint parameter value change feedback module (40) includes the following steps: S401. Obtain the unit monitoring time of the aging parameter monitoring equipment corresponding to each emergency parameter; S402. Select the longest unit monitoring time as the response assessment time, and upload the parameter values ​​corresponding to all emergency parameters at each response assessment time interval. S403. When an abnormal parameter value occurs, mark the emergency parameter and activate the aging parameter monitoring device corresponding to the aging parameter in the aging-related parameters associated with the emergency parameter, and perform association determination. When the emergency parameter is a single associated emergency parameter, the response upload time is the unit monitoring time that the aging parameter monitoring device consumes the longest. When the emergency parameter consists of multiple sets of associated emergency parameters, the response upload time is the sum of the unit monitoring times of the aging parameter monitoring devices corresponding to each set of aging parameters.

8. The insulation performance optimization system for fully enclosed distribution transformer areas according to claim 1, characterized in that: The insulation performance optimization mechanism established by the insulation performance response optimization module (50) includes the following steps: S501. Obtain emergency parameters of various related types and match their corresponding response assessment times; S502. Perform an aging status assessment based on the combination of aging parameter values ​​uploaded at the response assessment time. S503. Based on historical testing information, match optimization schemes for each aging state.

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