High-voltage level intelligent substation ac-dc integrated power supply monitoring system

Abstract

The application relates to the technical field of intelligent substation power supply monitoring, in particular to a high-voltage-grade intelligent substation AC / DC integrated power supply monitoring system. The system comprises an equipment abnormality reason analysis unit, an abnormality reason classification unit and a parameter data information comparison unit. In the application, the parameter data information comparison unit extracts fault reason parameter data information, compares each parameter data information, classifies fault reasons with the same parameter data information, shows that the two parameter data that are compared and coincided belong to the same data type and correspond to the same fault reason, merges the fault reasons corresponding to the parameter data that are compared and coincided, only retains the parameter data corresponding to one fault reason in the later period, and the remaining same parameter data is eliminated, so that the control system can avoid storing too much redundant data, system storage overload is avoided, and the normal operation of the system is affected.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent substation power supply monitoring, in particular to a high-voltage grade intelligent substation AC / DC integrated power supply monitoring system. BACKGROUND

[0002] The power AC / DC intelligent integrated power supply monitoring system is a complete set of equipment that combines AC power supply, DC power supply, power UPS, communication DC conversion power supply and emergency lighting devices into one, shares the battery pack of the DC power supply, and is uniformly monitored. The intelligent integrated power supply system adopts intelligent modular design and is monitored by a unified microcomputer monitoring system: various analog signals and switch signals of the DC power supply, power UPS, AC power supply, communication power supply and emergency lighting, and can automatically convert equal charging and floating charging according to the actual operation of the battery pack, completely realizing intelligent management of the battery.

[0003] In the existing power AC / DC intelligent integrated power supply monitoring system, there are many reasons for circuit failure, and the circuit failures occurring at different time points may be caused by the same reason. However, when analyzing, the circuit failure information caused by the same reason is repeatedly stored, the storage end redundant data is easy to overload, and in the later stage, when calling the storage end data to obtain a solution, secondary screening is needed, which greatly reduces the efficiency of calling data. Therefore, there is an urgent need for a high-voltage grade intelligent substation AC / DC integrated power supply monitoring system. SUMMARY

[0004] The present application relates to the technical field of intelligent substation power supply monitoring, in particular to a high-voltage grade intelligent substation AC / DC integrated power supply monitoring system.

[0005] To achieve the above object, the high voltage level intelligent substation AC / DC integrated power supply monitoring system is provided, comprising an AC / DC line simulation unit, the AC / DC line simulation unit is used for on-line simulation processing of the substation AC / DC line, the device running state monitoring unit is connected to the output end of the AC / DC line simulation unit, the device running state monitoring unit is used for monitoring and processing the state of each device in the substation AC / DC line, the device abnormal fault point identification unit is connected to the output end of the device running state monitoring unit, the device abnormal fault point identification unit is used for identifying and processing the fault point of the fault device, the device abnormal reason analysis unit is also connected to the output end of the device running state monitoring unit, the device abnormal reason analysis unit is used for analyzing the fault reason of the fault device, the abnormal reason classification unit is connected to the output end of the device abnormal reason analysis unit, the abnormal reason classification unit classifies and processes each fault reason according to different device fault reasons, the parameter data information comparison unit is connected to the output end of the abnormal reason classification unit, the parameter data information comparison unit is used for extracting fault reason parameter data information and comparing each parameter data information, and the fault reasons with the same parameter data information are classified.

[0006] As a further improvement of the technical solution, the AC / DC line simulation unit comprises a current flow direction simulation module, the current flow direction simulation module is used for defining the current flow direction in the on-line simulation line, and the predetermined position current size defining module is connected to the output end of the current flow direction simulation module.

[0007] As a further improvement of the technical solution, the predetermined position current size defining module is connected to the output end of the current size change amplitude defining module, and the current size change amplitude defining module is used for determining the current size range that each device can allow to pass under normal circumstances.

[0008] As a further improvement of the technical solution, the current size change amplitude defining module adopts an amplitude determination algorithm, and the algorithm formula is as follows:

[0009] A=[a1,a2,…,a n ];

[0010]

[0011] Wherein, A is a set of each current amount that the device in the on-line line can allow, a1 to a n is each current amount that the device in the on-line line can allow, a is the current amount measured by the device at present, f(a) is the current amount measured by the device at present, and a minThe minimum current among the currents allowed by the device in the online circuit, a max The maximum current among the currents allowed by the device in the online circuit, when a min ≤a≤a max , f(a) outputs 1, indicating that the current a measured by the device is in the normal range, when a>a max or a min , f(a) outputs 0, indicating that the current a measured by the device is out of the normal range, and the device has a fault point.

[0012] As a further improvement of the technical solution, the parameter data information comparison unit comprises a data cluster extraction module, which is used to extract data clusters of each parameter data in sequence according to a data cluster arrangement order; the data cluster extraction module is connected with a data cluster comparison module at the output end; the data cluster comparison module is used to compare and process the data clusters of each parameter data; and the data cluster comparison module is connected with a coincidence threshold value preset module at the output end, which is used to preset the coincidence threshold value of the data clusters in advance.

[0013] As a further improvement of the technical solution, the parameter data information comparison unit adopts a data cluster comparison algorithm, and the algorithm formula is as follows:

[0014] B=[b1,b2,…,b m ];

[0015] C=[c1,c2,…,c p ];

[0016] B∩C=[d1,d2,…,d y ];

[0017]

[0018] Wherein, B is a set of data clusters of one parameter data, b1 to b m are data clusters of one parameter data, C is a set of data clusters of another parameter data, c1 to c p are data clusters of another parameter data, d1 to d y are coincident data clusters, f(D) is a data cluster coincidence rate judgment function, y is the number of coincident data clusters, is a coincidence threshold value, when the number of coincident data clusters y is less than the coincidence threshold value , f(D) outputs 0, indicating that the two parameter data are not the same parameter data at this time, when the number of coincident data clusters y is not less than the coincidence threshold value , f(D) outputs 1, indicating that the two parameter data are the same parameter data at this time.

[0019] As a further improvement of the technical solution, the abnormal reason classifying unit is connected with a same data merging unit at the output end, the input end of the same data merging unit is connected with the parameter data information comparing unit at the output end, and the same data merging unit is used for merging the same parameter data.

[0020] As a further improvement of the technical solution, the abnormal reason classifying unit is connected with a different data classification identification unit at the output end, the input end of the different data classification identification unit is connected with the parameter data information comparing unit at the output end, and the different data classification identification unit is used for classifying the different parameter data.

[0021] As a further improvement of the technical solution, the different data classification identification unit is connected with a parent data storage unit at the output end, the input end of the parent data storage unit is connected with the same data merging unit at the output end, and the parent data storage unit is used for copying the parent data of each parameter data, identifying the same parameter data, performing single parent data replication, and generating parent data information.

[0022] Compared with the prior art, the present application has the following advantages:

[0023] 1. In the high-voltage level intelligent substation AC-DC integrated power supply monitoring system, the parameter data information comparing unit extracts the fault reason parameter data information, compares each parameter data information, classifies the fault reasons with the same parameter data information, indicates that the two parameter data compared and coincided belong to the same data type and correspond to the same fault reason, merges the fault reasons corresponding to the parameter data compared and coincided, and only retains the parameter data corresponding to the fault reason in the later period, and the remaining same parameter data is excluded, thereby avoiding that the control system stores too much redundant data, causing system storage overload and affecting normal operation of the system.

[0024] 2. In the high-voltage level intelligent substation AC-DC integrated power supply monitoring system, the current size change amplitude specification module determines the current size range that each device can allow under normal conditions, when the current changes when the online line output current passes through the device, as long as the current change is within the range specified by the current size change amplitude specification module, it indicates that the device is still in a normal state, and the device does not need to be detected for fault points.

[0025] 3. In the high-voltage level intelligent substation AC-DC integrated power supply monitoring system, the abnormal reason classification unit classifies and processes each fault reason according to different device fault causes, generates classification processing information, and transmits the classification processing information to the same data merging unit, the same data merging unit merges and processes the same parameter data, and packs the same parameter data, which is convenient for storage in the later stage. BRIEF DESCRIPTION OF DRAWINGS

[0026] Fig. 1 is the overall flowchart of the present application;

[0027] Fig. 2 is the AC-DC line simulation unit flowchart of the present application;

[0028] Fig. 3 is the parameter data information comparison unit flowchart of the present application.

[0029] The meanings of various labels in the figure are as follows:

[0030] 10. AC-DC line simulation unit; 110. Current flow direction simulation module; 120. Predetermined position current size specification module; 130. Current size change amplitude specification module;

[0031] 20. Device operation state monitoring unit;

[0032] 30. Device abnormal fault point identification unit;

[0033] 40. Device abnormal reason analysis unit;

[0034] 50. Abnormal reason classification unit;

[0035] 60. Parameter data information comparison unit; 610. Data cluster extraction module; 620. Data cluster comparison module; 630. Coincidence threshold value specification module;

[0036] 70. Same data merging unit;

[0037] 80. Different data classification identification unit;

[0038] 90. Maternal data storage unit. DETAILED DESCRIPTION

[0039] The technical solutions in the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0040] Please refer toFigs. 1-3 As shown, a high-voltage level intelligent substation AC / DC integrated power supply monitoring system is provided, which comprises an AC / DC line simulation unit 10, the AC / DC line simulation unit 10 is used for online simulation processing of the substation AC / DC line, the output end of the AC / DC line simulation unit 10 is connected with a device running state monitoring unit 20, the device running state monitoring unit 20 is used for monitoring and processing the state of each device in the substation AC / DC line, the output end of the device running state monitoring unit 20 is connected with a device abnormal fault point identification unit 30, the device abnormal fault point identification unit 30 is used for identifying and processing the fault point of the fault device, the output end of the device running state monitoring unit 20 is also connected with a device abnormal reason analysis unit 40, the device abnormal reason analysis unit 40 is used for analyzing the fault reason of the fault device, the output end of the device abnormal reason analysis unit 40 is connected with an abnormal reason classification unit 50, the abnormal reason classification unit 50 classifies each fault reason according to different fault reasons of the device, the output end of the abnormal reason classification unit 50 is connected with a parameter data information comparison unit 60, the parameter data information comparison unit 60 is used for extracting fault reason parameter data information, comparing each parameter data information, and classifying fault reasons with the same parameter data information.

[0041] In specific use, the AC-DC line simulation unit 10 simulates the AC-DC line of the substation to simulate the current flow direction in the AC-DC line of the substation and the real-time display of various data in the line, generates online simulation information, and transmits the online simulation information to the equipment operation state monitoring unit 20. The equipment operation state monitoring unit 20 monitors the state of each device in the AC-DC line of the substation, determines whether the operation data of each device is abnormal, generates real-time monitoring information, and transmits the real-time monitoring information to the equipment abnormal fault point identification unit 30. The equipment abnormal fault point identification unit 30 infers the equipment fault point according to the real-time monitoring information. At the same time, the equipment abnormal reason analysis unit 40 receives the real-time monitoring information, analyzes the fault reason of the faulty equipment, determines the reason for the fault of the equipment fault point, generates judgment information, and transmits the judgment information to the abnormal reason classification unit 50. The abnormal reason classification unit 50 classifies similar reasons for the fault of the equipment fault point and generates classification information, transmits the classification information to the parameter data information comparison unit 60, extracts fault reason parameter data information, and compares various parameter data information. The fault reasons with the same parameter data information are classified, indicating that the two parameter data that coincide belong to the same data type and correspond to the same fault reason. The fault reasons corresponding to the parameter data that coincide are merged. In the later stage, only the parameter data corresponding to one of the fault reasons is retained, and the remaining same parameter data is excluded, thereby avoiding the control system storing too much redundant data, causing system storage overload, and affecting the normal operation of the system.

[0042] In addition, the AC-DC line simulation unit 10 includes a current flow direction simulation module 110 for specifying the current flow direction in the online simulation line. The output end of the current flow direction simulation module 110 is connected to a predetermined position current size specification module 120 for specifying the current size that each device in the online simulation line can allow to pass through. In specific use, the current flow direction simulation module 110 specifies the current flow direction in the online simulation line, analyzes the current flow direction in the entire line, and marks the direction in the online line. The predetermined position current size specification module 120 specifies the current size that each device in the online simulation line can allow to pass through. When the line fails, the current flow direction may change at this time. The fault point position can be determined according to the current size change, and the fault point can be determined by observing whether the current passing through each device is a normal value, helping the detection personnel to determine the offline circuit fault point through the online line real-time simulation result, and improving the detection efficiency.

[0043] Furthermore, the output terminal of the predetermined position current magnitude specification module 120 is connected to a current magnitude change amplitude specification module 130. The current magnitude change amplitude specification module 130 is used to determine the range of current magnitudes that each device can pass under normal conditions. In practical use, since current changes may occur in the line under normal conditions, and this range of current changes is within the normal range, the current magnitude change amplitude specification module 130 determines the range of current magnitudes that each device can pass under normal conditions. When the line output current passes through the device and causes a current change, as long as this current change is within the range specified by the current magnitude change amplitude specification module 130, it indicates that the device is still in a normal state, and there is no need to detect fault points in the device.

[0044] Furthermore, the current magnitude change amplitude specification module 130 employs an amplitude determination algorithm, the formula of which is as follows:

[0045] A = [a1, a2, ..., a] n ];

[0046]

[0047] Where A represents the set of all allowable current quantities for the equipment in the online line, a1 to a... n Let 'a' represent the allowable current quantities of the equipment in the online circuit, 'a' represent the current quantity measured by the equipment, and 'f(a)' represent the current quantity judgment function measured by the equipment. min a is the minimum current among all the allowable currents of the equipment in the online circuit. max The maximum current among all the allowable currents of the equipment in the online circuit, when a min ≤a≤a max The output of f(a) is 1, indicating that the current a measured by the device is within the normal range. When a > a max or a<a min If f(a) outputs 0, the current a measured by the device is outside the normal range, indicating a fault in the device.

[0048] Specifically, the parameter data information comparison unit 60 comprises a data cluster extraction module 610, which is configured to sequentially extract data clusters of each parameter data according to a data cluster arrangement order. The data cluster extraction module 610 is connected to a data cluster comparison module 620 at the output end. The data cluster comparison module 620 is configured to perform comparison processing on the data clusters of each parameter data. The data cluster comparison module 620 is connected to a coincidence threshold value preset module 630 at the output end. The coincidence threshold value preset module 630 is configured to preset a coincidence threshold value of the data clusters. In specific use, the data cluster extraction module 610 sequentially extracts data clusters of each parameter data according to a data cluster arrangement order, generates data cluster extraction information, and transmits the data cluster extraction information to the data cluster comparison module 620. The data cluster comparison module 620 performs comparison processing on the data clusters of each parameter data, compares the coincidence rate of the data clusters of two parameter data, generates comparison information, and transmits the comparison information to the coincidence threshold value preset module 630. The coincidence threshold value preset module 630 presets a coincidence threshold value of the data clusters. When the coincidence rate of the data clusters of two parameter data exceeds the coincidence threshold value, it indicates that the two parameter data are the same parameter data. When the coincidence rate of the data clusters of two parameter data does not exceed the coincidence threshold value, it indicates that the two parameter data are not the same parameter data.

[0049] In addition, the parameter data information comparison unit 60 adopts a data cluster comparison algorithm, and the algorithm formula is as follows:

[0050] B = [b1, b2, …, b m ];

[0051] C = [c1, c2, …, c p ];

[0052] B∩C = [d1, d2, …, d y ];

[0053]

[0054] Wherein, B is a set of each data cluster of one parameter data, b1 to b m are each data cluster of one parameter data, C is a set of each data cluster of another parameter data, c1 to c p are each data cluster of another parameter data, d1 to d y are each coincident data cluster, f(D) is a data cluster coincidence rate judgment function, y is the number of coincident data clusters, is a coincidence threshold value, when the number of coincident data clusters y is less than the coincidence threshold value , f(D) outputs 0, indicating that the two parameter data are not the same parameter data, when the number of coincident data clusters y is not less than the coincidence threshold value When f(D) outputs 1, it indicates that the two parameter data are the same parameter data at this time.

[0055] Further, the output end of the abnormal reason classification unit 50 is connected with the same data merging unit 70, the input end of the same data merging unit 70 is connected with the output end of the parameter data information comparison unit 60, and the same data merging unit 70 is used for merging the same parameter data. In specific use, the abnormal reason classification unit 50 classifies the various fault reasons according to the different equipment fault causes, generates classification processing information, and transmits the classification processing information to the same data merging unit 70. The same data merging unit 70 merges the same parameter data, packages the same parameter data for storage in the later stage.

[0056] Further, the output end of the abnormal reason classification unit 50 is connected with the different data classification identification unit 80, the input end of the different data classification identification unit 80 is connected with the output end of the parameter data information comparison unit 60, and the different data classification identification unit 80 is used for classifying the different parameter data. In specific use, the different data classification identification unit 80 classifies the different parameter data, and identifies the parameter data of different types according to the classification type.

[0057] In addition, the output end of the different data classification identification unit 80 is connected with the parent data storage unit 90, the input end of the parent data storage unit 90 is connected with the output end of the same data merging unit 70, and the parent data storage unit 90 is used for copying the parent data of each parameter data, identifying the same parameter data, and performing single parent data replication to generate parent data information. In specific use, the parent data storage unit 90 is used for copying the parent data of each parameter data, identifying the same parameter data, and performing single parent data replication to generate parent data information, removing the same parameter information for storage in the later stage, and preventing the generation of redundant data.

[0058] The basic principle, 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-mentioned embodiments, and the above-mentioned embodiments and descriptions in the specification are only preferred examples of the present application and are not intended 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 claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A high-voltage-level intelligent substation AC-DC integrated power supply monitoring system, comprising an AC-DC line simulation unit (10), the AC-DC line simulation unit (10) is used for on-line simulation processing of the AC-DC line of the substation, characterized in that: The device running state monitoring unit (20) is connected with an equipment abnormal fault point identification unit (30) at the output end, the equipment abnormal fault point identification unit (30) is used for identifying the fault point of the fault equipment, the device running state monitoring unit (20) is also connected with an equipment abnormal reason analysis unit (40) at the output end, the equipment abnormal reason analysis unit (40) is used for analyzing the fault reason of the fault equipment, the equipment abnormal reason analysis unit (40) is connected with an abnormal reason classification unit (50) at the output end, the abnormal reason classification unit (50) classifies each fault reason according to different equipment fault reasons, the abnormal reason classification unit (50) is connected with a parameter data information comparison unit (60) at the output end, the parameter data information comparison unit (60) is used for extracting the fault reason parameter data information, and comparing each parameter data information, and the fault reasons with the same parameter data information are classified; ​ The abnormal reason classification unit (50) is connected with a same data merging unit (70) at the output end, the same data merging unit (70) is connected with the parameter data information comparison unit (60) at the input end, and the same data merging unit (70) is used for merging the same parameter data; The abnormal reason classification unit (50) is connected with a different data classification identification unit (80) at the output end, the different data classification identification unit (80) is connected with the parameter data information comparison unit (60) at the input end, and the different data classification identification unit (80) is used for classifying different parameter data. 2.The high-voltage-level intelligent substation AC-DC integrated power supply monitoring system according to claim 1, characterized in that: The alternating current line simulation unit (10) comprises a current flow direction simulation module (110), the current flow direction simulation module (110) is used for defining the current flow direction in the simulation line on the line, and the current flow direction simulation module (110) is connected with a predetermined position current size definition module (120) at the output end, the predetermined position current size definition module (120) is used for defining the current size allowed to pass through each equipment in the simulation line on the line. 3.The high-voltage-level intelligent substation AC-DC integrated power supply monitoring system according to claim 2, characterized in that: The predetermined position current size definition module (120) is connected with a current size change amplitude definition module (130) at the output end, the current size change amplitude definition module (130) is used for determining the current size range allowed to pass through each equipment under normal circumstances.

4. The high-voltage-level intelligent substation AC / DC integrated power supply monitoring system of claim 3, characterized in that: The current size change amplitude definition module (130) adopts an amplitude determination algorithm, and the algorithm formula is as follows: ； ； Wherein, A is the set of current that the device in the online circuit can allow, To A is the set of current that the device in the online circuit can allow, A is the current that the device measures at present, A is the current that the device measures at present, A is the minimum current in the set of current that the device in the online circuit can allow, A is the maximum current in the set of current that the device in the online circuit can allow, when , The output is 1, the current that the device measures at present is in the normal range, when , The output is 0, the current that the device measures at present is out of the normal range, and the device has a fault point.

5. The high-voltage-level intelligent substation AC / DC integrated power supply monitoring system of claim 1, characterized in that: The parameter data information comparison unit (60) comprises a data cluster extraction module (610) for extracting data clusters of each parameter data in sequence according to a data cluster arrangement order, and the data cluster extraction module (610) is connected with a data cluster comparison module (620) at an output end, the data cluster comparison module (620) is used for comparing and processing the data clusters of each parameter data, and the data cluster comparison module (620) is connected with a coincidence threshold value preset module (630) at an output end, and the coincidence threshold value preset module (630) is used for presetting a coincidence threshold value of the data clusters in advance. 6.The high-voltage-level intelligent substation AC / DC integrated power supply monitoring system according to claim 5, characterized in that: The parameter data information comparison unit (60) adopts a data cluster comparison algorithm, and an algorithm formula is as follows: ； ； ； ； wherein, is a set of individual data clusters of one parameter data, is a set of individual data clusters of one parameter data, is a set of individual data clusters of one parameter data, is a set of individual data clusters of another parameter data, is a set of individual data clusters of another parameter data, is a set of individual data clusters of another parameter data, is a set of individual data clusters of another parameter data, is a set of individual data clusters of another parameter data, is a data cluster coincidence rate judging function, y is the number of coincident data clusters, is a coincidence threshold, when the number of coincident data clusters y is less than the coincidence threshold , the output is 0, indicating that the two parameter data are not the same parameter data at this time, when the number of coincident data clusters y is not less than the coincidence threshold , the output is 1, indicating that the two parameter data are the same parameter data at this time. 7.The high-voltage-level intelligent substation AC / DC integrated power supply monitoring system of claim 1, characterized in that: The different data classification identification unit (80) is connected with a parent data storage unit (90) at an output end, the parent data storage unit (90) is connected with the same data merging unit (70) at an input end, and the parent data storage unit (90) is used for copying parent data of each parameter data, identifying the same parameter data, copying the parent data once, and generating parent data information.

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