CN112433127A - Fault type identification method and device based on platform area intelligent fusion terminal - Google Patents
Fault type identification method and device based on platform area intelligent fusion terminal Download PDFInfo
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- CN112433127A CN112433127A CN202011272175.XA CN202011272175A CN112433127A CN 112433127 A CN112433127 A CN 112433127A CN 202011272175 A CN202011272175 A CN 202011272175A CN 112433127 A CN112433127 A CN 112433127A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/086—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/088—Aspects of digital computing
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S10/52—Outage or fault management, e.g. fault detection or location
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Abstract
The invention relates to a fault type identification method and a fault type identification device based on a transformer area intelligent fusion terminal, which are used for acquiring normal state data and transient state data of a low-voltage transformer area switch node and identifying fault types through edge calculation to obtain fault types under various conditions, and uploading the fault types to a power distribution management background in time, thereby realizing comprehensive analysis of power failure fault types from local data of the transformer area terminal, and improving the efficiency of power management and maintenance units for fault shaping and emergency repair preparation.
Description
Technical Field
The invention relates to the technical field of low-voltage distribution network correlation, in particular to a fault type identification method and device based on a transformer area intelligent fusion terminal.
Background
The low-voltage distribution station area is the tail end of a distribution network and is connected with an end user, and the low-voltage distribution station area is characterized in that: the method has the advantages of multiple points, wide range, complex environment, multiple faults and difficult identification. The fault rush-repair of the distribution transformer area brings huge workload to power management and maintenance units, and particularly long-time power failure caused by line faults is often complained or compensated by users.
From 2017, the national grid company carries out intelligent transformation and upgrading on a power distribution station: the intelligent transformer substation comprises a substation area intelligent fusion terminal, a substation area original line protection switch and an electrical sensing device, wherein the substation area intelligent fusion terminal is additionally arranged on the low-voltage side of a substation area distribution transformer, the substation area original line protection switch is kept unchanged (the fault automatic cutting function is exerted), the electrical sensing device is additionally arranged at the node of the substation area original line protection switch, and the substation area intelligent fusion terminal is used as the substation area device and is responsible for being connected with the electrical sensing device and the line protection switch and directly collecting substation area distribution transformer main incoming line electrical data. Under the condition, the station area intelligent fusion terminal can only collect the power failure information reported by the electrical sensing equipment through communication so as to identify the power failure of the fault, but cannot obtain the specific type (grounding or short circuit) of the power failure fault at this time, so that the power management and maintenance unit is not favorable for setting the fault and preparing for emergency repair.
Disclosure of Invention
Based on the above situation in the prior art, the invention aims to provide a method for comprehensively analyzing the type of the power failure fault and reporting the type to a background master station by using a station area intelligent fusion terminal as an edge computing center, distributing and transforming the total incoming line electrical quantity data through a high-frequency wave recording station area and combining the power failure message/electrical quantity data reported by an electrical sensing device at the line side of the station area.
In order to achieve the above object, according to an aspect of the present invention, there is provided a method for identifying a fault type based on a platform area intelligent convergence terminal, including the steps of:
acquiring signal data of each acquisition point, wherein the signal data comprises transient state quantity data and normal state quantity data; identifying fault types through edge calculation based on the acquired signal data;
and uploading the fault type identification result to a power distribution management background.
Further, the fault type identification includes transient data fault type identification and normal data acquisition fault type identification.
Further, the transient data fault type identification comprises short circuit type identification, open-phase analysis identification, electric leakage analysis identification and fault removal duration calculation.
Further, the short circuit type identification includes the steps of:
when any phase voltage at the incoming line end is less than 50V and the fault phase current is greater than 6 times of a rated value, the single-phase ground fault is identified;
when the voltage of any two phases at the incoming line end is less than 50V and the fault phase current is greater than 6 times of a rated value, the fault phase is identified as an interphase short circuit or a two-phase ground fault;
and when the three-phase voltage of the incoming line end is less than 50V and the fault phase current is greater than 6 times of the rated value, identifying the three-phase short circuit or the ground fault.
Further, the phase-defect analysis and identification comprises the following steps:
when the voltage of any one phase or two phases at the incoming line end is less than 50V and the three-phase current is less than 1.2 times of the rated value and lasts for 0.2s, the phase-missing fault of the high-voltage side of the distribution transformer is identified.
Further, the electric leakage analysis and identification comprises the following steps:
when the leakage current of the inlet wire end is larger than 50mA and lasts for 0.2s, the leakage fault is identified.
The calculation of the fault clearing time comprises the following steps:
and calculating the time from the beginning of the disturbance of the incoming line electrical quantity to the tripping of the circuit breaker, and judging the accuracy of the action of the circuit breaker by combining a delay fixed value.
Furthermore, the normal quantity data acquisition fault type identification comprises voltage quality monitoring, load rate monitoring, three-phase load monitoring, power factor monitoring, phase loss monitoring, temperature and humidity monitoring, pole tower inclination monitoring and low-voltage zero line disconnection monitoring.
Further, the signal data of each acquisition point is acquired,
when the transient state quantity data is collected, the collection frequency is 20 ms/time;
when normal data is collected, the collection frequency is 10 min/time.
According to another aspect of the invention, a fault type identification device based on a platform area intelligent fusion terminal is provided, which comprises a data acquisition module, a fault type identification module and an uploading module; wherein the content of the first and second substances,
the data acquisition module acquires signal data of each acquisition point, wherein the signal data comprises transient state quantity data and normal state quantity data;
the fault type identification module identifies the fault type through edge calculation based on the acquired signal data;
and the uploading module uploads the fault type identification result to a power distribution management background.
In summary, the invention provides a fault type identification method and a fault type identification device based on a transformer area intelligent fusion terminal, which are used for acquiring normal data and transient data of a low-voltage transformer area terminal and identifying fault types through edge calculation to obtain fault types under various conditions, and uploading the fault types to a power distribution management background in time, so that the comprehensive analysis of local data of the transformer area terminal on power failure fault types is realized, and the efficiency of power management and maintenance units for fault shaping and emergency repair preparation is improved.
Drawings
FIG. 1 is an electrical diagram of a typical device of a low voltage distribution substation;
FIG. 2 is an overall block diagram of the power distribution grid data collection and analysis of the present invention;
FIG. 3 is a flow chart of the fault type identification method based on the intelligent convergence terminal of the station area according to the present invention;
fig. 4 is a schematic diagram of fault type identification based on transient data in the fault type identification method based on the intelligent convergence terminal of the distribution room according to the present invention;
fig. 5 is a schematic diagram of fault type identification based on normal data in the fault type identification method based on the intelligent convergence terminal in the distribution room.
Fig. 6 is an overall configuration diagram of the fault type recognition apparatus based on the intelligent convergence terminal of the station area according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
The technical solution of the present invention will be described in detail below with reference to the accompanying drawings. First, a structure of a low-voltage power distribution station is described, and fig. 1 shows a typical device configuration manner of the low-voltage power distribution station, in which a data acquisition point is set, including: the distribution transformer incoming line is configured with an acquisition point of an intelligent distribution transformer terminal (or a fusion terminal); the distribution transformer outlet is provided with a collection point of the intelligent residual current protection device; a low-voltage middle section node is provided with a collection point of a monitoring device LTU; configuring a collection point of a monitoring device LTU by the drainage and irrigation node; configuring a collection point of a monitoring device LTU by a low-voltage end user; the distribution transformer rack is provided with a temperature and humidity sensor and the tower is provided with a collecting point of an inclination angle sensor. The invention realizes power failure analysis and abnormal monitoring by collecting transient state quantity data and normal state quantity data, and the overall block diagram of the collection and analysis is shown in figure 2. The method comprises the items of electric quantity timing acquisition, transient data recording, electric quantity normal state acquisition, temperature and humidity acquisition, tower inclination acquisition and the like, and uploads an analysis result to a main station after monitoring and analysis.
According to an embodiment of the present invention, a method for identifying a fault type based on a zone intelligent convergence terminal is provided, an implementation flowchart of the method is shown in fig. 3, and the method includes the steps of:
acquiring signal data of each acquisition point, wherein the signal data comprises transient state quantity data and normal state quantity data; identifying fault types through edge calculation based on the acquired signal data;
and uploading the fault type identification result to a power distribution management background.
Fig. 4 shows a schematic diagram of fault type identification based on transient data in the fault type identification method, the transformer substation intelligent fusion terminal monitors the electric quantities such as current, voltage and the like of the low-voltage side of the distribution transformer once every 20 milliseconds through an electric quantity wiring terminal of the TTU, and after receiving an outgoing line leakage protection tripping message, records and analyzes the electric quantities of incoming lines and disconnected equipment in 2 seconds before and after the disconnection time point, and judges the power failure type, including 6 items of single-phase grounding, two-phase grounding, inter-phase short circuit, three-phase short circuit and the like.
Single-phase grounding: any phase voltage of the inlet wire is less than 50V and the fault phase current is more than 6 times of a rated value.
The phases or two phases are grounded: the voltage of any two phases of the inlet wire is less than 50V, and the fault phase current is more than 6 times of a rated value.
Three-phase short circuit or grounding: the incoming line three-phase voltage is less than 50V and the fault phase current is greater than 6 times of a rated value.
Phase loss: the voltage of any one phase or two phases is less than 50V, and the three-phase current is less than 1.2 times of rated value.
And (3) zero line breaking: the voltage of the low-voltage zero line to ground is more than 150V.
Electric leakage: the inlet leakage current is greater than 50 mA.
Overload: and the load rate of each breaker port is greater than x times of rated current.
Specifically, each type of fault identification can be performed by:
short circuit type identification: when any phase voltage at the incoming line end is less than 50V and the fault phase current is greater than 6 times of a rated value, the single-phase ground fault is identified;
when the voltage of any two phases at the incoming line end is less than 50V and the fault phase current is greater than 6 times of a rated value, the fault phase is identified as an interphase short circuit or a two-phase ground fault;
and when the three-phase voltage of the incoming line end is less than 50V and the fault phase current is greater than 6 times of the rated value, identifying the three-phase short circuit or the ground fault.
Phase loss analysis and identification: when the voltage of any one phase or two phases at the incoming line end is less than 50V and the three-phase current is less than 1.2 times of the rated value and lasts for 0.2s, the phase-missing fault of the high-voltage side of the distribution transformer is identified.
Electric leakage analysis and identification: when the leakage current of the inlet wire end is larger than 50mA and lasts for 0.2s, the leakage fault is identified.
Calculating the fault removal time: and calculating the time from the beginning of the disturbance of the incoming line electrical quantity to the tripping of the circuit breaker, and judging the accuracy of the action of the circuit breaker by combining a delay fixed value.
Fig. 5 shows a schematic diagram of fault type identification based on normal data in the fault type identification method, and normal data acquisition fault type identification includes voltage quality monitoring, load rate monitoring, three-phase load monitoring, power factor monitoring, phase loss monitoring, temperature and humidity monitoring, tower inclination monitoring, and low-voltage zero line disconnection monitoring.
According to the transient data records, the intelligent distribution transformer terminal realizes short circuit type analysis (including single-phase grounding, interphase short circuit or two-phase grounding, three-phase short circuit or grounding trip judgment), open-phase analysis (open-phase trip input), leakage analysis, fault removal duration calculation and the like through edge calculation and uploads the short circuit type analysis, the open-phase short circuit or the two-phase grounding, the three-phase short circuit or the grounding trip judgment), the leakage analysis, the fault removal duration calculation and the like.
And the system generates and displays the power failure event record according to the power failure analysis result sent by the intelligent distribution transformer terminal. Master station system demonstration example: station area branch power failure, fault type: single-phase grounding/interphase short circuit or two-phase grounding/three-phase short circuit or grounding/phase loss/electric leakage/overload, the breaker acts correctly, and the fault cutting time is ms.
According to another embodiment of the present invention, there is provided a fault type identification apparatus based on a zone intelligent convergence terminal, and an overall structure diagram of the apparatus is shown in fig. 6. The device includes: the device comprises a data acquisition module, a fault type identification module and an uploading module. The data acquisition module acquires signal data of each acquisition point, wherein the signal data comprises transient state quantity data and normal state quantity data; the fault type identification module is used for identifying the fault type based on the collected signal data; and the uploading module uploads the fault type identification result to a power distribution management background. In the fault type identification module, the specific steps of each fault type identification are the same as those in the method provided by the first embodiment of the present invention, and are not described herein again.
In summary, the invention relates to a fault type identification method and a fault type identification device based on a transformer substation intelligent fusion terminal, which are based on the acquisition of normal state data and transient state data of a low-voltage transformer substation terminal, obtain fault types under various conditions through edge calculation and analysis, and timely upload the fault types to a power distribution management background, thereby realizing the comprehensive analysis of power failure fault types (including ground fault, short-circuit fault, leakage fault and the like) by using local data of the transformer substation terminal, and powerfully supporting the power management/emergency repair unit to process the fault and recover the power supply efficiency.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (10)
1. A fault type identification method based on a platform area intelligent fusion terminal is characterized by comprising the following steps:
acquiring signal data of each acquisition point, wherein the signal data comprises transient state quantity data and normal state quantity data;
identifying fault types through edge calculation based on the acquired signal data;
and uploading the fault type identification result to a power distribution management background.
2. The identification method according to claim 1, wherein the fault type identification is carried out, and comprises transient data fault type identification and normal data acquisition fault type identification.
3. The identification method according to claim 2, wherein the transient data fault type identification comprises short circuit type identification, open-phase analysis identification, leakage current analysis identification and fault clearing duration calculation.
4. The identification method according to claim 3, characterized in that said short circuit type identification comprises the steps of:
when any phase voltage at the incoming line end is less than 50V and the fault phase current is greater than 6 times of a rated value, the single-phase ground fault is identified;
when the voltage of any two phases at the incoming line end is less than 50V and the fault phase current is greater than 6 times of a rated value, the fault phase is identified as an interphase short circuit or a two-phase ground fault;
and when the three-phase voltage of the incoming line end is less than 50V and the fault phase current is greater than 6 times of the rated value, identifying the three-phase short circuit or the ground fault.
5. The identification method according to claim 3, characterized in that the open-phase analysis identification comprises the steps of:
when the voltage of any one phase or two phases at the incoming line end is less than 50V and the three-phase current is less than 1.2 times of the rated value and lasts for 0.2s, the phase-missing fault of the high-voltage side of the distribution transformer is identified.
6. The identification method according to claim 4, wherein the electric leakage analysis identification comprises the steps of:
when the leakage current of the inlet wire end is larger than 50mA and lasts for 0.2s, the leakage fault is identified.
7. The identification method according to claim 5, wherein said calculation of fault clearing duration comprises the steps of:
and calculating the time from the beginning of the disturbance of the incoming line electrical quantity to the tripping of the circuit breaker, and judging the accuracy of the action of the circuit breaker by combining a delay fixed value.
8. The identification method according to claim 2, wherein the normal data collection fault type identification comprises voltage quality monitoring, load rate monitoring, three-phase load monitoring, power factor monitoring, open-phase monitoring, temperature and humidity monitoring, tower inclination monitoring and low-voltage zero line disconnection monitoring.
9. The identification method according to any of claims 2-8, wherein the collecting of signal data for each collection point,
when the transient state quantity data is collected, the collection frequency is 20 ms/time;
when normal data is collected, the collection frequency is 10 min/time.
10. A fault type identification device based on a platform area intelligent fusion terminal is characterized by comprising a data acquisition module, a fault type identification module and an uploading module; wherein the content of the first and second substances,
the data acquisition module acquires signal data of each acquisition point, wherein the signal data comprises transient state quantity data and normal state quantity data;
the fault type identification module identifies the fault type through edge calculation based on the acquired signal data;
and the uploading module uploads the fault type identification result to a power distribution management background.
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