A partial discharge monitoring system and method for GIS gas insulated switchgear

Abstract

The present application discloses a partial discharge monitoring system and method for GIS gas-insulated switchgear, the system comprising: a GIS equipment related information collection module, used to collect environmental data and equipment service life of GIS gas-insulated switchgear; a GIS equipment detection requirement determination module, used to obtain the preset requirements of the power facilities used by the GIS gas-insulated switchgear for the accuracy of identifying partial discharge conditions of the GIS gas-insulated switchgear; a GIS equipment detection method determination module, used to obtain the detection method that meets the preset requirements of the accuracy of identifying partial discharge conditions of the GIS gas-insulated switchgear under the conditions of current environmental data and equipment service life and has the lowest operating cost; a GIS equipment partial discharge detection module, used to complete the monitoring of the current GIS gas-insulated switchgear using the selected detection method and obtain the partial discharge condition. The present application can realize the dynamic adjustment of the partial discharge detection method considering the application scenario and detection requirements, and improve the accuracy and efficiency of monitoring.

Description

Technical Field

[0001] The present application relates to the technical field of GIS partial discharge monitoring, and in particular to a partial discharge monitoring system and method for GIS gas insulated switchgear. Background Art

[0002] GIS gas insulated switchgear is a high-voltage electrical equipment that combines circuit breakers, disconnectors, grounding switches, voltage transformers, current transformers, lightning arresters, busbars, cable terminals, inlet and outlet bushings and other components. It has been widely used in power systems for its high insulation strength, small footprint, low operating cost, high reliability and strong environmental adaptability. GIS gas insulated switchgear may be damaged by partial discharge due to various defects during the equipment manufacturing and installation, transportation and actual use. Therefore, partial discharge monitoring of GIS gas insulated switchgear is of great significance to ensure the safe and stable operation of power systems.

[0003] In the prior art, there are many ways to detect partial discharge of GIS gas insulated switchgear, such as pulse current detection method, ultrasonic detection method, ultra-high frequency (UHF) detection method, infrared detection method, chemical detection method, etc. Although these monitoring methods have their own advantages and disadvantages, the above methods mainly rely on single data for feature mining to analyze and obtain the laws and characteristics of partial discharge, which may lead to underreporting of partial discharge detection; in order to further comprehensively grasp the inherent laws of GIS partial discharge occurrence and development, there are multi-modal perception data obtained by combining multiple detection methods in the existing monitoring system to realize partial discharge detection of GIS gas insulated switchgear based on multi-parameter combination to improve the accuracy of GIS insulation status assessment.

[0004] However, these existing systems do not take into account the actual application scenarios. The partial discharge detection methods of different GIS gas insulated switchgear used in different environments and different years have relative advantages and disadvantages, and do not take into account the accuracy requirements of partial discharge detection of gas insulated switchgear in the actual application systems of each GIS gas insulated switchgear. Therefore, it is necessary to dynamically adjust the partial discharge detection method in combination with the actual application scenarios and the actual partial discharge detection accuracy requirements, so as to improve the accuracy and efficiency of monitoring and ensure the safe and stable operation of the power system. Summary of the invention

[0005] In order to dynamically adjust the partial discharge detection method in consideration of application scenarios and detection requirements, improve the accuracy and efficiency of monitoring, and ensure the safe and stable operation of the power system, the present application provides a partial discharge monitoring system and method for GIS gas insulated switchgear.

[0006] In a first aspect, the present application provides a partial discharge monitoring system for a GIS gas insulated switchgear, comprising:

[0007] GIS equipment related information collection module, used to collect environmental data of GIS gas insulated switchgear, equipment service life and geographical location data of GIS gas insulated switchgear; the environmental data includes: electromagnetic interference, temperature, humidity, pressure and ambient light intensity;

[0008] The GIS equipment detection requirement determination module is used to determine the power facilities where the GIS gas-insulated switchgear is applied according to the geographical location data of the GIS gas-insulated switchgear, and obtain the preset requirements of the power facilities where the GIS gas-insulated switchgear is installed for the accuracy of identifying partial discharge conditions of the GIS gas-insulated switchgear;

[0009] The GIS equipment detection method determination module is used to use a deep learning algorithm to obtain the accuracy of identifying the partial discharge of GIS gas insulated switchgear using different detection methods under different environmental data and equipment service life conditions; the different detection methods include: ultrasonic detection method, pulse current detection method, ultra-high frequency detection method, chemical detection method, optical detection method and a combined detection method of at least two of the above detection methods; obtain a detection method that meets the preset requirements for the accuracy of identifying the partial discharge of GIS gas insulated switchgear under the current environmental data and equipment service life conditions; combine the operating costs of different detection methods, and select the detection method with the lowest operating cost from all the obtained detection methods;

[0010] The GIS equipment partial discharge detection module is used to complete the monitoring of the current GIS gas-insulated switchgear by using the selected detection method and obtain the partial discharge situation of the GIS gas-insulated switchgear.

[0011] By adopting the above scheme and using a deep learning algorithm, the accuracy of identifying partial discharge conditions of GIS gas insulated switchgear using different detection methods under different environments and service life conditions is determined, thereby dynamically adjusting the detection method according to the actual environment and equipment service life to improve the accuracy of identifying partial discharge conditions of GIS gas insulated switchgear; at the same time, considering the recognition accuracy requirements of power facilities actually used by GIS equipment and the operating costs of different detection methods, a detection method that meets the requirements and is low-cost is selected to reduce the partial discharge monitoring cost of GIS gas insulated switchgear.

[0012] Preferably, it also includes:

[0013] A GIS equipment detection mode adjustment module is used to obtain the GIS gas insulated switchgear associated with the current GIS gas insulated switchgear when the local discharge condition of the GIS gas insulated switchgear is severe local discharge and lasts for a first preset time, and adaptively adjust the preset requirement of its local discharge condition recognition accuracy within a second preset time to improve the adjusted local discharge condition recognition accuracy; obtain the detection method of the local discharge condition of the associated GIS gas insulated switchgear according to the adjusted preset requirement; wherein the severe local discharge includes: the discharge amount of the local discharge is greater than the preset discharge amount or the discharge frequency of the local discharge is greater than the preset discharge frequency; the associated GIS gas insulated switchgear is a GIS gas insulated switchgear that is directly electrically connected to the current GIS gas insulated switchgear or is less than a preset distance from the geographical location of the current GIS gas insulated switchgear.

[0014] By adopting the above solution, considering that when a serious partial discharge is detected in a GIS device, it may affect the associated GIS devices; the recognition accuracy requirements of the associated GIS devices are adaptively increased within a period of time since the abnormality of a certain GIS device, so as to further ensure the accurate identification of the partial discharge of the associated GIS devices.

[0015] Preferably, the GIS equipment detection method determination module is also used to obtain the existing detection conditions of the GIS gas insulated switchgear, and select the detection method that meets the existing detection conditions and has the lowest operating cost from all acquired detection methods based on the operating costs of different detection methods and the existing detection conditions of the GIS gas insulated switchgear; the existing detection conditions are detection methods that can be supported by the existing conditions.

[0016] By adopting the above scheme, considering that some GIS gas insulated switchgear in power facilities where GIS gas insulated switchgear is used is not installed with detection equipment corresponding to all detection methods, the specific GIS equipment detection method is determined in combination with actual detection conditions to ensure the successful operation of partial discharge monitoring of GIS gas insulated switchgear.

[0017] Preferably, the GIS equipment detection method determination module is also used to use a deep learning algorithm to determine the duration for completing the identification of partial discharge conditions of GIS gas insulated switchgear using different detection methods under different environmental data and equipment service life conditions; receive the requirements for the identification time of partial discharge conditions of GIS gas insulated switchgear sent by the monitoring personnel and verify that the monitoring personnel is an authorized monitoring personnel; if yes, obtain the detection method that meets the preset requirements for the identification accuracy and identification time of partial discharge conditions of GIS gas insulated switchgear under the current environmental data and equipment service life conditions.

[0018] By adopting the above scheme, taking into account the different recognition times of partial discharge conditions for different detection methods, the detection method is selected in combination with the recognition time requirement to meet the recognition time requirements of monitoring personnel in some application scenarios.

[0019] Preferably, it also includes:

[0020] The GIS equipment detection method determination module is also used to receive the monitoring personnel's request for obtaining the partial discharge situation of the GIS gas insulated switchgear and determine the current acquisition request type, which includes online real-time detection, periodic detection or simulation detection corresponding to a specific detection method; according to the obtained request type, the corresponding preset prohibited detection method is searched, and the prohibited detection method found is eliminated from the detection methods that meet the preset requirements for the accuracy of identifying the partial discharge situation of the GIS gas insulated switchgear under the conditions of obtaining the current environmental data and the service life of the equipment.

[0021] By adopting the above scheme, taking into account that some detection methods are not suitable for real-time online detection, or the monitoring personnel need to simulate the detection of some detection methods, the type of the monitoring personnel's request for obtaining partial discharge conditions is received in real time, and some unsuitable or unnecessary detection methods are prohibited from completing subsequent detection according to the specific type, thereby meeting the needs of the monitoring personnel and ensuring the normal operation of the partial discharge condition identification of the GIS gas insulated switchgear.

[0022] Preferably, it also includes:

[0023] The GIS equipment partial discharge detection feedback module is used to regularly receive the average feedback score of the monitoring personnel on the partial discharge conditions of the GIS gas insulated switchgear. If the average feedback score is lower than the preset score, the parameters of the deep learning algorithm are updated to re-determine the accuracy of identifying the partial discharge conditions of the GIS gas insulated switchgear using different detection methods under different environments and equipment service life conditions.

[0024] By adopting the above solution, the parameters of the deep learning algorithm are updated according to the scoring results fed back by the monitoring personnel, so as to obtain the recognition accuracy more accurately and obtain a more appropriate detection method.

[0025] Preferably, the GIS equipment-related information collection module is also used to collect environmental data of the GIS gas-insulated switchgear, and analyze whether the environmental data currently collected of the GIS gas-insulated switchgear undergoes a mutation compared to the environmental data collected at the previous moment. If a mutation occurs, the collection data of the current environmental data by the backup environmental data collection device is obtained. If the environmental data collected by the backup environmental data collection device still undergoes a mutation compared to the environmental data collected at the previous moment, the currently collected environmental data is retained. Otherwise, the environmental data collected by the backup environmental data collection device is used as the currently collected environmental data.

[0026] By adopting the above scheme, considering the sudden change of environmental data due to the erroneous collection of the sensor, the adjustment of the erroneous detection method is performed. In order to further ensure the accuracy of the adjustment of the detection method, the mutated environmental data is verified.

[0027] In a second aspect, the present application provides a partial discharge monitoring method for a GIS gas insulated switchgear, comprising:

[0028] Collect environmental data of GIS gas insulated switchgear, equipment service life and geographical location data of GIS gas insulated switchgear; the environmental data include: electromagnetic interference, temperature, humidity, pressure and ambient light intensity;

[0029] Determine the power facilities where the GIS gas insulated switchgear is used based on the geographical location data of the GIS gas insulated switchgear, and obtain the preset requirements of the power facilities where the GIS gas insulated switchgear is used for the accuracy of identifying partial discharge conditions of the GIS gas insulated switchgear;

[0030] Using deep learning algorithms, the accuracy of identifying partial discharge conditions of GIS gas insulated switchgear using different detection methods under different environmental data and equipment service life conditions is obtained; the different detection methods include: ultrasonic detection method, pulse current detection method, ultra-high frequency detection method, chemical detection method, optical detection method and a combined detection method of at least two of the above detection methods; obtaining a detection method that meets the preset requirements for the accuracy of identifying partial discharge conditions of GIS gas insulated switchgear under the current environmental data and equipment service life conditions; combining the operating costs of different detection methods, selecting the detection method with the lowest operating cost from all the obtained detection methods;

[0031] The selected detection method is used to complete the monitoring of the current GIS gas-insulated switchgear and obtain the partial discharge situation of the GIS gas-insulated switchgear.

[0032] By adopting the above scheme, the partial discharge detection method is dynamically adjusted considering the application scenario and detection requirements, and the detection method is selected based on the operating cost of each detection method, which improves the accuracy and efficiency of monitoring, reduces the monitoring cost, and ensures the safe and stable operation of the power system.

[0033] In a third aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the method as described above.

[0034] In a fourth aspect, the present application provides a computer device, comprising a memory, a processor, and a program stored and executable on the memory, wherein the program implements the steps of the above method when executed by the processor.

[0035] In summary, this application has the following beneficial effects:

[0036] 1. Use deep learning algorithms to determine the accuracy of identifying partial discharges of GIS gas-insulated switchgear using different detection methods under different environments and service life conditions, so as to dynamically adjust the detection method according to the actual environment and service life to improve the accuracy of identifying partial discharges of GIS gas-insulated switchgear. At the same time, consider the recognition accuracy requirements of power facilities actually used by GIS equipment and the operating costs of different detection methods, select a detection method that meets the requirements and is low-cost, and reduce the partial discharge monitoring cost of GIS gas-insulated switchgear.

[0037] 2. Considering the impact of severe partial discharge of a certain GIS device on the associated GIS devices, the recognition accuracy requirements of the associated GIS devices are adaptively increased within a period of time after the abnormality of a certain GIS device, so as to further ensure the accurate recognition of the partial discharge of the associated GIS devices;

[0038] 3. Considering that GIS gas-insulated switchgear is not equipped with detection equipment corresponding to all detection methods, the specific GIS equipment detection method is determined in combination with actual detection conditions to ensure the successful operation of partial discharge monitoring of GIS gas-insulated switchgear. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a structural schematic diagram of a partial discharge monitoring system for a GIS gas insulated switchgear in a specific embodiment;

[0040] Figure 2 It is a flow chart of the partial discharge monitoring method of GIS gas insulated switchgear described in a specific embodiment. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0042] Example 1

[0043] like Figure 1 As shown, an embodiment of the present application discloses a partial discharge monitoring system for GIS gas insulated switchgear, which specifically includes: a GIS equipment related information collection module 1, a GIS equipment detection requirement determination module 2, a GIS equipment detection method determination module 3 and a GIS equipment partial discharge detection module 4.

[0044] The GIS equipment related information collection module 1 is used to collect GIS gas insulated switch equipment related information such as environmental data of the GIS gas insulated switch equipment, equipment service life and geographical location data of the GIS gas insulated switch equipment.

[0045] Specifically, the GIS gas insulated switchgear related information can be collected in real time or regularly according to actual needs. The environmental data of the GIS gas insulated switchgear includes: electromagnetic interference, temperature, humidity, pressure, and ambient light intensity, among which electromagnetic interference mainly measures the electromagnetic noise in the environment.

[0046] Taking into account the importance of the collected environmental data for the subsequent determination of the GIS equipment detection method, the collected environmental data is prevented from being erroneous due to damage to the collection device or other factors; the GIS equipment related information collection module 2 is also used to collect the current environmental data of the GIS gas insulated switchgear, and analyze whether the environmental data currently collected for the GIS gas insulated switchgear is mutated compared with the environmental data collected at the previous moment, and the mutation is that the change value of any type of environmental data (such as temperature) compared with the environmental data collected at the previous moment is greater than the corresponding preset environmental data difference (such as preset temperature difference); if a mutation occurs, the collection data of the current environmental data by the standby environmental data collection device is obtained, and if the environmental data collected by the standby environmental data collection device is still mutated compared with the environmental data collected at the previous moment, the currently collected environmental data is retained, otherwise, the environmental data collected by the standby environmental data collection device is used as the currently collected environmental data.

[0047] The GIS equipment detection requirement determination module 2 is used to obtain the preset requirements of the power facilities where the GIS gas insulated switchgear is applied for the accuracy of identifying the partial discharge of the GIS gas insulated switchgear.

[0048] Specifically, GIS gas-insulated switchgear (GIS equipment for short) is widely used in various power facilities and power systems, such as substations, distribution equipment, etc. Some power facilities or power systems have preset corresponding requirements for the installed GIS gas-insulated switchgear itself and its detection indicators, such as: The preset requirements for the accuracy of identifying partial discharge conditions of GIS gas-insulated switchgear can be determined based on the geographical location data of the GIS gas-insulated switchgear and directly obtained.

[0049] Taking into account that some power facilities or power systems do not directly set corresponding requirements, the power facilities where the GIS gas insulated switchgear is located can be determined based on the geographical location data of the GIS gas insulated switchgear, and the proportion of the power supply of the power facility in the power supply of the area where the power facility is located can be determined. The importance of the power facility can be determined by comparing the proportion with the preset proportion threshold, such as: important, generally important, and unimportant; power facilities of different importance correspond to different levels of preset requirements, that is, corresponding to different partial discharge situation identification accuracy ranges (such as: important power facilities, the partial discharge situation identification accuracy range is required to reach 95%, generally important power facilities, the partial discharge situation identification accuracy range is required to reach 90%, and unimportant power facilities, the partial discharge situation identification accuracy range is required to reach 80%), and then the preset requirements for the accuracy of partial discharge situation identification of the gas insulated switchgear can be obtained by indirect matching based on the geographical location data of the GIS gas insulated switchgear.

[0050] The GIS equipment detection method determination module 3 is used to use a deep learning algorithm to obtain the accuracy of identifying the partial discharge situation of the GIS gas insulated switchgear using different detection methods under different environmental data and equipment service life conditions; obtain a detection method that meets the preset requirements for the accuracy of identifying the partial discharge situation of the GIS gas insulated switchgear under the current environmental data and equipment service life conditions; and combine the operating costs of different detection methods to select the detection method with the lowest operating cost from all the acquired detection methods.

[0051] Specifically, the different detection methods include: ultrasonic detection method, pulse current detection method, ultra-high frequency detection method, chemical detection method, optical detection method and a combined detection method of at least two of the above detection methods, such as: a combined detection method of ultrasonic detection method and ultra-high frequency detection method. Among them, the combined detection method can choose to fuse multiple parameters (such as: using ultrasonic detection to obtain the acoustic emission signal inside the equipment, and using ultra-high frequency detection to capture high-frequency electromagnetic wave data, etc.), and use the fused parameters and the fused parameter training to generate a neural network model to complete the detection.

[0052] Taking into account different environments and different equipment service life, the accuracy of partial discharge identification of GIS gas insulated switchgear using different detection methods is different. For example, in a high humidity environment, the ultra-high frequency signal is less affected by humidity, and the accuracy of partial discharge identification of GIS gas insulated switchgear using the ultra-high frequency detection method will be higher; or the accuracy of partial discharge identification of GIS gas insulated switchgear using the chemical detection method will be higher for GIS gas insulated switchgear that has been in operation for many years. Therefore, using the deep learning algorithm, the first deep learning neural network model can be selected to be constructed. The input of the model is the environmental data and service life of the GIS gas insulated switchgear, and the specific detection method used. The output of the model is the accuracy of partial discharge identification of GIS gas insulated switchgear using the corresponding detection method; the model can complete the model training through the accuracy of partial discharge identification of GIS gas insulated switchgear under historical environmental data, historical service life, historical specific detection methods, and historical corresponding detection methods.

[0053] By choosing to build the first deep learning neural network model, the current environmental conditions, equipment age and specific detection methods can be input to obtain the accuracy of the corresponding detection method in completing the identification of partial discharge conditions of GIS gas-insulated switchgear, thereby obtaining a detection method that meets the preset requirements for the accuracy of identifying partial discharge conditions of GIS gas-insulated switchgear under the conditions of current environmental data and equipment age. In addition, once there is a detection method that cannot meet the preset requirements, a prompt message that the detection method that cannot meet the preset requirements is generated, and the model of the joint detection method is updated until a detection method that meets the preset requirements is obtained.

[0054] Considering that different detection methods have different operating costs, the operating costs of the different detection methods can be obtained based on the historical operating costs of GIS gas-insulated switchgear for detection under different environments and different equipment service life conditions (including: the cost of purchasing, operating and maintaining the corresponding detection equipment, the cost of hiring or training the corresponding detection equipment operators, etc.); therefore, combined with the operating costs of different detection methods, the detection method with the lowest operating cost is selected from all the aforementioned detection methods as the final detection method. Among them, if the operating costs are the same, they can be selected randomly.

[0055] The GIS equipment partial discharge detection module 4 is used to complete the monitoring of the current GIS gas insulated switchgear by using the selected detection method, and obtain the partial discharge situation of the GIS gas insulated switchgear.

[0056] Specifically, the partial discharge condition of the GIS gas insulated switchgear includes whether there is partial discharge in the GIS gas insulated switchgear, the severity of the partial discharge, and the health status of the GIS gas insulated switchgear, and a fault reminder is generated according to the health status of the GIS gas insulated switchgear.

[0057] In addition, in order to further meet the monitoring personnel's requirements for identifying partial discharge conditions of GIS gas insulated switchgear, the system described in this embodiment also includes:

[0058] The GIS equipment partial discharge detection feedback module 5 is used to regularly receive the average feedback score of the monitoring personnel on the partial discharge situation of the GIS gas insulated switchgear; specifically, the monitoring personnel can give corresponding feedback scores based on the partial discharge situation of the IS gas insulated switchgear obtained, combined with the monitoring personnel's own observation of the actual partial discharge situation of the IS gas insulated switchgear, such as: a satisfaction feedback score with a full score of 100 points. If the average feedback score of the monitoring personnel is lower than the preset score, it means that the current monitoring personnel is not satisfied with the partial discharge situation identification result of the current GIS gas insulated switchgear, and the parameters of the constructed first deep learning neural network model can be further updated to re-determine the accuracy of the partial discharge situation identification of the GIS gas insulated switchgear using different detection methods under different environments and service life conditions, so as to improve the accuracy of the partial discharge situation identification of the GIS gas insulated switchgear.

[0059] Example 2

[0060] The difference from the first embodiment is that the present embodiment adds a module for determining the detection requirements of GIS equipment to further ensure the accuracy of identifying the partial discharge situation of the GIS gas insulated switchgear. Specifically, the system further includes:

[0061] The GIS equipment detection mode adjustment module 6 is used to obtain the local discharge situation of the GIS gas insulated switchgear as severe local discharge and the severe local discharge situation lasts for a first preset time; wherein, the first preset time can be manually preset, and the severe local discharge includes: the discharge amount of the local discharge is greater than the preset discharge amount or the discharge frequency of the local discharge is greater than the preset discharge frequency, etc.

[0062] Obtain the GIS gas insulated switchgear associated with the current GIS gas insulated switchgear; wherein the associated GIS gas insulated switchgear is a GIS gas insulated switchgear that is directly electrically connected to the current GIS gas insulated switchgear or is located at a geographical location less than a preset distance from the current GIS gas insulated switchgear; or when statistics show that the GIS gas insulated switchgear has a history of severe partial discharge and the severe partial discharge situation lasts for a first preset time period, obtain the GIS gas insulated switchgear that has a simultaneous partial discharge situation as the associated GIS gas insulated switchgear.

[0063] Since the local discharge situation of the GIS gas insulated switchgear is severe local discharge and the severe local discharge situation lasts for a first preset time period, the preset requirement for the local discharge situation recognition accuracy of the associated GIS gas insulated switchgear is adaptively adjusted within a second preset time period to improve the adjusted local discharge situation recognition accuracy; the specific adjustment amount can be preset, such as: adjusting the recognition accuracy to increase by 5%.

[0064] According to the adjusted preset requirements, the detection method of the partial discharge condition of the associated GIS gas-insulated switchgear is obtained, so as to better ensure the detection of the partial discharge condition of the associated GIS gas-insulated switchgear.

[0065] Example 3

[0066] The difference from Example 1 is that this embodiment further takes into account that some actual power facilities or power systems cannot provide all the detection equipment to support a comprehensive detection method for the detection of the GIS equipment installed therein, in order to ensure the operation of the GIS equipment detection method.

[0067] The GIS equipment detection method determination module 3 described in the present system is also used to obtain the existing detection conditions of the GIS gas-insulated switchgear, and select the detection method that meets the existing detection conditions and has the lowest operating cost from all the acquired detection methods in combination with the operating costs of different detection methods and the existing detection conditions of the GIS gas-insulated switchgear; wherein, the existing detection conditions are detection methods that can be supported by the existing conditions, such as: an ultrasonic sensor is installed on the existing GIS equipment, which can support the ultrasonic detection method.

[0068] And you can set the time to obtain the current test conditions of the GIS gas-insulated switchgear to ensure that the latest test conditions are obtained.

[0069] Example 4

[0070] The difference from Example 1 is that this implementation further considers and meets the time limit requirements of the monitoring personnel for obtaining the partial discharge conditions of the GIS gas insulated switchgear. The GIS equipment detection method determination module 3 in the system is also used to use a deep learning algorithm to determine the time required to complete the identification of the partial discharge conditions of the GIS gas insulated switchgear using different detection methods under different environmental data and equipment service life conditions; receive the time requirement for identifying the partial discharge conditions of the GIS gas insulated switchgear sent by the monitoring personnel and verify that the monitoring personnel is an authorized monitoring personnel; if yes, obtain a detection method that meets the preset requirements for the accuracy of identifying the partial discharge conditions of the GIS gas insulated switchgear and the identification time requirements under the current environmental data and equipment service life.

[0071] Specifically, you can choose to build a second deep learning neural network model. The input of the model is the environmental data, service life, and specific detection method of the GIS gas insulated switchgear. The output of the model is the duration of identifying the partial discharge of the GIS gas insulated switchgear using the corresponding detection method. The model can complete model training by using historical environmental data, historical service life, historical specific detection methods, and historical corresponding detection methods to complete the duration of identifying the partial discharge of the GIS gas insulated switchgear.

[0072] By choosing to build a second deep learning neural network model, the current environmental conditions, equipment service life and specific detection methods can be input to obtain the time required to complete the identification of partial discharge conditions of GIS gas insulated switchgear under the corresponding detection method. Combined with the accuracy of partial discharge identification of GIS gas insulated switchgear under the corresponding detection method obtained by the first deep learning network model, the detection method that meets the preset requirements for the accuracy of partial discharge identification of GIS gas insulated switchgear and the identification time requirements under the current environmental data and equipment service life conditions is obtained.

[0073] Example 5

[0074] The difference from Example 1 is that this embodiment is to further ensure the monitoring personnel's need to obtain the partial discharge situation of the GIS gas insulated switchgear.

[0075] The GIS equipment detection method determination module 3 is also used to receive the monitoring personnel's request for obtaining the local discharge status of the GIS gas insulated switchgear and determine the current acquisition request type, wherein the acquisition request type includes online real-time detection, periodic detection or simulation detection corresponding to a specific detection method; wherein the specific detection method is at least any one of the different detection methods in the above-mentioned embodiment 1.

[0076] Search for the corresponding preset prohibited detection method according to the obtained request type; specifically, when the obtained request type is online real-time detection, the corresponding preset prohibited detection methods include: the remaining detection types except ultrasonic detection method, ultra-high frequency detection method, and joint detection method of ultrasonic detection method and ultra-high frequency detection method; when the obtained request type is periodic detection, the corresponding prohibited detection method is: no prohibited detection method; when the obtained request type is time-delay simulation detection corresponding to a specific detection method, the corresponding prohibited detection method is: the remaining detection methods except the specific detection method.

[0077] Under the conditions of obtaining current environmental data and equipment service life, the prohibited detection methods found are eliminated from the detection methods that meet the preset requirements for the accuracy of identifying partial discharge conditions of GIS gas-insulated switchgear.

[0078] like Figure 2 As shown, the embodiment of the present application discloses a partial discharge monitoring method for GIS gas insulated switchgear, and the specific steps are as follows:

[0079] S1. Collect environmental data, equipment service life and geographical location data of GIS gas insulated switchgear.

[0080] Specifically, when collecting environmental data of GIS gas insulated switchgear, it is analyzed whether the environmental data currently collected of GIS gas insulated switchgear undergoes a mutation compared to the environmental data collected at the previous moment. If a mutation occurs, the collection data of the current environmental data by the backup environmental data collection device is obtained. If the environmental data collected by the backup environmental data collection device still undergoes a mutation compared to the environmental data collected at the previous moment, the currently collected environmental data is retained. Otherwise, the environmental data collected by the backup environmental data collection device is used as the currently collected environmental data.

[0081] S2. Obtain the preset requirements of the power facilities where GIS gas insulated switchgear is used for the accuracy of identifying partial discharge conditions of GIS gas insulated switchgear.

[0082] S3. Obtain a detection method that meets the preset requirements for the accuracy of identifying partial discharge conditions of GIS gas-insulated switchgear under the conditions of current environmental data and equipment service life and has the lowest operating cost.

[0083] Specifically, a deep learning algorithm is used to obtain the accuracy of identifying partial discharge conditions of GIS gas insulated switchgear using different detection methods under different environmental data and equipment service life conditions; a detection method that meets the preset requirements for accuracy of identifying partial discharge conditions of GIS gas insulated switchgear under current environmental data and equipment service life conditions is obtained; and the operating costs of different detection methods are combined to select the detection method with the lowest operating cost from all the obtained detection methods.

[0084] S4. Use the selected detection method to complete the monitoring of the current GIS gas insulated switchgear and obtain the partial discharge situation of the GIS gas insulated switchgear.

[0085] In addition, the method also includes:

[0086] S5. Receive feedback from monitoring personnel and re-obtain the accuracy of partial discharge identification.

[0087] Specifically, the average feedback score of the partial discharge of GIS gas insulated switchgear obtained by monitoring personnel is regularly received. If the average feedback score is lower than the preset score, the parameters of the deep learning algorithm are updated to re-determine the accuracy of partial discharge identification of GIS gas insulated switchgear using different detection methods under different environments and equipment service life conditions.

[0088] In a specific embodiment, the method further includes: when the local discharge condition of the GIS gas insulated switch device is obtained as severe local discharge and lasts for a first preset time period, the GIS gas insulated switch device associated with the current GIS gas insulated switch device is obtained, and the preset requirements for its local discharge condition recognition accuracy are adaptively adjusted within a second preset time period so that the adjusted local discharge condition recognition accuracy is improved; according to the adjusted preset requirements, a detection method for the local discharge condition of the associated GIS gas insulated switch device is obtained.

[0089] In a specific embodiment, step S3 of the method also includes: using a deep learning algorithm to determine the time required to complete the identification of partial discharge conditions of GIS gas insulated switchgear using different detection methods under different environmental data and equipment service life conditions; receiving the time requirement for the identification of partial discharge conditions of GIS gas insulated switchgear sent by the monitoring personnel and verifying that the monitoring personnel is an authorized monitoring personnel; if so, obtaining a detection method that meets the preset requirements for the accuracy of identification of partial discharge conditions of GIS gas insulated switchgear and the identification time requirement under the current environmental data and equipment service life conditions.

[0090] In a specific embodiment, step S3 of the method also includes: receiving a request from a monitoring personnel to obtain the partial discharge condition of a GIS gas insulated switchgear and determining the current acquisition request type; searching for a corresponding preset prohibited detection method according to the acquired request type, and eliminating the found prohibited detection method from the detection methods that meet the preset requirements for the accuracy of identifying the partial discharge condition of the GIS gas insulated switchgear under the conditions of obtaining the current environmental data and the service life of the equipment.

[0091] The embodiment of the present application also discloses a computer-readable storage medium.

[0092] Specifically, the computer-readable storage medium stores a computer program that can be loaded by a processor and executed such as the local discharge monitoring method of the above-mentioned GIS gas-insulated switchgear. The computer-readable storage medium includes, for example: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0093] The embodiment of the present application also discloses a computer device.

[0094] Specifically, the computer device includes a memory and a processor, and the memory stores a computer program that can be loaded by the processor and execute the above-mentioned partial discharge monitoring method for GIS gas insulated switchgear.

[0095] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A partial discharge monitoring system for GIS gas insulated switchgear, characterized in that: include: GIS equipment related information collection module, used to collect environmental data of GIS gas insulated switchgear, equipment service life and geographical location data of GIS gas insulated switchgear; the environmental data includes: electromagnetic interference, temperature, humidity, pressure and ambient light intensity; The GIS equipment detection requirement determination module is used to determine the power facilities used by the GIS gas-insulated switchgear according to the geographical location data of the GIS gas-insulated switchgear, and obtain the preset requirements of the power facilities used by the GIS gas-insulated switchgear for the accuracy of identifying partial discharge conditions of the GIS gas-insulated switchgear; The GIS equipment detection method determination module is used to use a deep learning algorithm to obtain the accuracy of identifying the partial discharge of GIS gas insulated switchgear using different detection methods under different environmental data and equipment service life conditions; the different detection methods include: ultrasonic detection method, pulse current detection method, ultra-high frequency detection method, chemical detection method, optical detection method and a combined detection method of at least two of the above detection methods; obtain a detection method that meets the preset requirements for the accuracy of identifying the partial discharge of GIS gas insulated switchgear under the current environmental data and equipment service life conditions; combine the operating costs of different detection methods, and select the detection method with the lowest operating cost from all the obtained detection methods; The GIS equipment partial discharge detection module is used to complete the monitoring of the current GIS gas-insulated switchgear by using the selected detection method and obtain the partial discharge situation of the GIS gas-insulated switchgear.

2. The partial discharge monitoring system for GIS gas insulated switchgear according to claim 1 is characterized in that: Also includes: The GIS equipment detection mode adjustment module is used to obtain the GIS gas insulated switchgear associated with the current GIS gas insulated switchgear when the partial discharge condition of the GIS gas insulated switchgear is severe partial discharge and lasts for a first preset time, and adaptively adjust the preset requirement of its partial discharge condition recognition accuracy within a second preset time so that the adjusted partial discharge condition recognition accuracy is improved; According to the adjusted preset requirements, a detection method for the local discharge situation of the associated GIS gas insulated switchgear is obtained; wherein, the severe local discharge includes: the discharge amount of the local discharge is greater than the preset discharge amount or the discharge frequency of the local discharge is greater than the preset discharge frequency; the associated GIS gas insulated switchgear is a GIS gas insulated switchgear that is directly electrically connected to the current GIS gas insulated switchgear or is located at a geographical location less than a preset distance from the current GIS gas insulated switchgear.

3. The partial discharge monitoring system for GIS gas insulated switchgear according to claim 1, characterized in that: The GIS equipment detection method determination module is also used to obtain the existing detection conditions of the GIS gas-insulated switchgear, and combine the operating costs of different detection methods with the existing detection conditions of the GIS gas-insulated switchgear to select the detection method that meets the existing detection conditions and has the lowest operating cost from all the acquired detection methods; the existing detection conditions are the detection methods that can be supported by the existing conditions.

4. The partial discharge monitoring system for GIS gas insulated switchgear according to claim 1, characterized in that: The GIS equipment detection method determination module is also used to use a deep learning algorithm to determine the time required to complete the identification of partial discharge conditions of GIS gas insulated switchgear using different detection methods under different environmental data and equipment service life conditions; receive the time requirement for identifying partial discharge conditions of GIS gas insulated switchgear sent by the monitoring personnel and verify that the monitoring personnel is an authorized monitoring personnel; if yes, obtain the detection method that meets the preset requirements for the accuracy of identifying partial discharge conditions of GIS gas insulated switchgear and the identification time requirement under the current environmental data and equipment service life conditions.

5. The partial discharge monitoring system for GIS gas insulated switchgear according to claim 1, characterized in that: Also includes: The GIS equipment detection method determination module is also used to receive the monitoring personnel's request for obtaining the partial discharge situation of the GIS gas insulated switchgear and determine the current acquisition request type, which includes online real-time detection, periodic detection or simulation detection corresponding to a specific detection method; according to the obtained request type, the corresponding preset prohibited detection method is searched, and the prohibited detection method found is eliminated from the detection methods that meet the preset requirements for the accuracy of identifying the partial discharge situation of the GIS gas insulated switchgear under the conditions of obtaining the current environmental data and the service life of the equipment.

6. The partial discharge monitoring system for GIS gas insulated switchgear according to claim 1, characterized in that: Also includes: The GIS equipment partial discharge detection feedback module is used to regularly receive the average feedback score of the monitoring personnel on the partial discharge conditions of the GIS gas insulated switchgear. If the average feedback score is lower than the preset score, the parameters of the deep learning algorithm are updated to re-determine the accuracy of identifying the partial discharge conditions of the GIS gas insulated switchgear using different detection methods under different environments and equipment service life conditions.

7. The partial discharge monitoring system for GIS gas insulated switchgear according to claim 1, characterized in that: The GIS equipment related information collection module is also used to collect environmental data of the GIS gas insulated switchgear, and analyze whether the environmental data currently collected of the GIS gas insulated switchgear is mutated compared with the environmental data collected at the previous moment. If a mutation occurs, the collection data of the current environmental data by the backup environmental data collection device is obtained. If the environmental data collected by the backup environmental data collection device is still mutated compared with the environmental data collected at the previous moment, the currently collected environmental data is retained. Otherwise, the environmental data collected by the backup environmental data collection device is used as the currently collected environmental data.

8. A partial discharge monitoring method for GIS gas insulated switchgear using the system described in any one of claims 1 to 7, characterized in that: include: Collect environmental data, equipment service life and geographical location data of GIS gas insulated switchgear; The environmental data include: electromagnetic interference, temperature, humidity, pressure and ambient light intensity; Determine the power facilities where the GIS gas insulated switchgear is used based on the geographical location data of the GIS gas insulated switchgear, and obtain the preset requirements of the power facilities where the GIS gas insulated switchgear is used for the accuracy of identifying partial discharge conditions of the GIS gas insulated switchgear; Using deep learning algorithms, the accuracy of identifying partial discharge conditions of GIS gas insulated switchgear using different detection methods under different environmental data and equipment service life conditions is obtained; the different detection methods include: ultrasonic detection method, pulse current detection method, ultra-high frequency detection method, chemical detection method, optical detection method and a combined detection method of at least two of the above detection methods; obtaining a detection method that meets the preset requirements for the accuracy of identifying partial discharge conditions of GIS gas insulated switchgear under the current environmental data and equipment service life conditions; combining the operating costs of different detection methods, selecting the detection method with the lowest operating cost from all the obtained detection methods; The selected detection method is used to complete the monitoring of the current GIS gas-insulated switchgear and obtain the partial discharge situation of the GIS gas-insulated switchgear.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to claim 8.

10. A computer device, characterized in that: The computer device comprises a memory, a processor and a program stored and executable on the memory, and the program implements the steps of the method according to claim 8 when executed by the processor.

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