A power equipment data governance method and device

Abstract

The application discloses a power equipment data management method and device, wherein the method comprises the following steps: defining multiple states for power equipment switch values according to event types concerned by a user side, and setting transition rules between the states; using a mark deduplication method on a high-frequency sampling device side to accurately capture a sudden event; using a sampling integral point period mark method in a time interval of a minimum query time span to achieve the target of high-frequency sampling on the high-frequency sampling device side and low-frequency recording, while retaining the user side readability of the minimum time query span; using the mark deduplication method on a data access layer to accurately capture the sudden event; and using a sampling mark period method in the time interval of the minimum query time span to achieve the target of high-frequency sampling on the high-frequency sampling device side and low-frequency continuous recording reporting, while retaining the continuous readability requirement of the minimum time query span on the user side. The application improves the lean management and operation and maintenance level of massive data.

Description

Technical Field

[0001] This invention belongs to the field of power distribution network technology, and specifically relates to a method and apparatus for power equipment data management. Background Technology

[0002] In recent years, with the rise of the Internet of Things (IoT), researchers have begun to use intelligent edge computing devices on the device side combined with cloud platform applications to achieve layered and hierarchical processing technology for real-time computing tasks. The basic idea is a cloud-edge-device architecture, forming a system architecture of "high-frequency device status acquisition device - data access layer gateway - cloud data storage center - application display system." High-frequency monitoring at the bottom layer, data governance in the middle layer, and application display at the top layer effectively shield users from excessive reliance on the underlying logic, allowing them to focus more on the value of the data application itself. The value of switching quantities in power equipment is mainly reflected in the following aspects:

[0003] 1. Real-time and accurate data sampling time, with event occurrence time accurate to within 20 milliseconds.

[0004] 2. The integrity and continuity of switch data, accident reconstruction and review, require complete and continuous time series.

[0005] 3. The speed and continuity of user-side data extraction enable a complete and accurate understanding of the event process.

[0006] In the industry, switch quantities are usually classified into two states: on or off, corresponding to the digital quantities 0 or 1. There are only these two states, either on (1) or off (0), and there are no other states. Switch quantity acquisition simply refers to acquiring these two states to convert input or output.

[0007] First, for the business characteristic of a large number of repeated values ​​appearing in the interval of the switch quantity within its life cycle, the industry's general solution is to solve the high frequency and low transmission problem on the sampling device side based on similar mutation events + duration. However, it is usually deeply bound to the embedded hardware device on the edge side and only handles the 0 and 1 states, lacking the extension and handling of states in subsequent processes.

[0008] In addition, in power application systems, to more conveniently and accurately distinguish other forms of switch quantities, two-point semaphores are sometimes used to extend the difference between steady-state and transient states, namely: steady-state power outage, steady-state power supply, transient power outage, and transient power supply. However, due to various external factors throughout the entire lifecycle of switch quantities—from sampling, transmission, storage, to application—data acquisition interruptions, data transmission delays, or data loss can occur. The observable states presented to end users in application systems should be closer to user understanding and displayed in a more easily readable way.

[0009] Meanwhile, similar tagging schemes exist in the industry, but they only tag sudden events and do not take into account the problem of excessively long time intervals between sudden events. Due to the low randomness and long time span of sudden events, these industry solutions lack the continuity of time series, cannot meet the user's query requirements for the minimum time span, or require the user to set a very long time query span to retrieve valid records, making it inconvenient for the user to set the start time period for the query. Summary of the Invention

[0010] This invention provides a power equipment data governance method and apparatus to solve the problems of incomplete switch status description indicators, high numerical repetition within time intervals, and minimum query span on the user side derived from the tagging and deduplication algorithm.

[0011] To address the aforementioned technical problems, this invention provides a method for power equipment data governance, comprising:

[0012] Step S1: Define multiple states for the switching quantities of power equipment according to the event types that the user side is concerned about, and set the transition rules between each state;

[0013] Step S2: On the high-frequency sampling device side of the equipment, a marking and deduplication method is used to accurately capture sudden events; and within the time interval of the minimum query time span, the sampling is marked on the hourly cycle to achieve the goal of high-frequency sampling and low-frequency recording on the high-frequency sampling device side, while preserving the readability of the user side of the minimum time query span.

[0014] Step S3: At the data access layer, a marking deduplication method is used to accurately capture sudden events; and within the time interval of the minimum query time span, a sampling marking period is used to achieve the goal of high-frequency sampling on the high-frequency sampling device side and continuous recording and reporting of the second-lowest frequency, while preserving the continuous readability requirements of the minimum time query span on the user side.

[0015] Furthermore, in step S1, the switching quantities of the power equipment are defined as six states: 0, 1, 2, 3 and 5, according to the event types that the user side is concerned about.

[0016] Further, step S2 specifically includes:

[0017] Step S21: Create measurement point information and activate the measurement points when data writing begins;

[0018] Step S22: The high-frequency sampling device starts monitoring the on / off status of the high-frequency monitoring equipment to determine whether the sampling data obtained by the high-frequency sampling device is normal.

[0019] Step S23: If the acquired sampling data is abnormal, mark the event as the fifth state according to the optional process;

[0020] Step S24: If the sampled data is obtained normally, compare the sampled value with the previous cached value at the measurement point. If it is a new value, immediately mark it as an emergency and record it; if it is a duplicate value, process it according to the hourly cycle procedure, discarding it or marking it at the hour.

[0021] Step S25: Determine whether the measurement point is write-prohibited. If not, process it according to the hourly cycle, discard or mark it as an hourly point, and then continue the cycle of acquiring sampling data for the next time. If yes, write data is prohibited for the measurement point and the measurement point is deleted, and the process ends.

[0022] Furthermore, the hourly period is the natural time during data sampling, which is equal to the minimum query time span on the user side.

[0023] Furthermore, step S3 specifically includes:

[0024] Step S31: Create measurement point information and activate the measurement points when data writing begins.

[0025] Step S32: The data access layer begins to receive high-frequency and sub-high-frequency sampling data from the high-frequency sampling device in real time, and determines whether the received sampling data is normal.

[0026] Step S33: If there is a delay in receiving the sampled data, mark the event as the sixth state according to the optional procedure;

[0027] Step S34: If the received sampling data is normal, compare the sampled value with the previous buffered value of the measurement point. If it is a new value, mark it as a sudden event and record it immediately. If it is a duplicate value, process it according to the marking period process, discarding or marking the period point value.

[0028] Step S35: Determine whether the measurement point is write-prohibited. If not, process according to the marking cycle procedure, discard or mark the record, and then continue the loop process of receiving sampled data. If yes, write data is prohibited for the measurement point and the measurement point is deleted, and the process ends.

[0029] Furthermore, the marking period = data sampling frequency × number of consecutive records, and the marking period is equal to the minimum query time span on the user side.

[0030] Furthermore, the power equipment data governance method also includes a user-side switch quantity data query process, which is used to process the conversion of the minimum time span. Specifically, it queries the continuous records of the marker of the sudden event and the minimum user query interval, and determines the value of the query time point according to the principle of taking the value at the lower edge.

[0031] The present invention also provides a power equipment data governance device, comprising:

[0032] The configuration module is used to define multiple states for the switching quantities of power equipment according to the event types that the user side is concerned about, and to set the transition rules between each state.

[0033] The first deduplication and hourly cycle marking module is used to use a deduplication method on the high-frequency sampling device side of the equipment to accurately capture sudden events; and to use an hourly cycle marking method within the time interval of the minimum query time span to achieve the goal of high-frequency sampling and low-frequency recording on the high-frequency sampling device side, while preserving the readability of the user side of the minimum time query span.

[0034] The second deduplication and hourly cycle marking module is used to use the marking deduplication method at the data access layer to accurately capture sudden events; and to use the sampling marking cycle method within the time interval of the minimum query time span to achieve the goal of high-frequency sampling and continuous recording and reporting of high-frequency and second-low-frequency data on the high-frequency sampling device side, while preserving the continuous readability requirements of the minimum time query span on the user side.

[0035] Furthermore, the first deduplication and hourly cycle marking module is specifically used for:

[0036] Create measurement point information and activate the measurement points when data writing begins;

[0037] The high-frequency sampling device starts monitoring the on / off status of the high-frequency monitoring equipment to determine whether the sampling data acquired by the high-frequency sampling device is normal.

[0038] If the acquired sampling data is abnormal, the event will be marked as the fifth state according to the optional procedure;

[0039] If the sampled data is obtained normally, the sampled value is compared with the previous cached value at the measurement point. If it is a new value, it is immediately marked as an emergency and recorded; if it is a duplicate value, it is processed according to the hourly cycle procedure, either discarded or marked on the hour.

[0040] Determine if the measurement point is write-prohibited. If not, process it according to the hourly cycle, discard or mark it as an hourly point, and then continue the cycle of acquiring sampling data for the next time. If it is write-prohibited, then the measurement point is deleted.

[0041] Furthermore, the second marker deduplication and hourly cycle marker module is specifically used for:

[0042] Create measurement point information and activate the measurement points when you start writing data.

[0043] The data access layer begins to receive high-frequency and sub-high-frequency sampling data from the high-frequency sampling device in real time, and determines whether the received sampling data is normal.

[0044] If there is a delay in receiving the sampled data, the event will be marked as the sixth state according to the optional procedure;

[0045] If the received sampling data is normal, the sampled value is compared with the previous buffered value at the measurement point. If it is a new value, it is immediately marked as a sudden event and recorded. If it is a duplicate value, it is processed according to the marking cycle process, either discarding or marking the cycle point value.

[0046] Determine whether the measurement point is write-prohibited. If not, process it according to the marking cycle procedure, discard or mark the record, and then continue the cycle of receiving sampled data. If it is write-prohibited, then the measurement point is deleted.

[0047] Implementing this invention has the following beneficial effects: This invention provides data querying from the equipment side to the sampling device and then to the user side. The sampling accuracy of the marked events is at the 20-millisecond level. While ensuring no loss of sampling accuracy, the repeated values ​​of switching quantities within the time interval are effectively denoised and filtered. Furthermore, according to the minimum query requirements of the user side, hourly markers are added to effectively guarantee data continuity and readability. Simultaneously, the event types are expanded from the conventional 0 and 1 states to six more readable and understandable descriptions: 0, 1, 2, 3, 5, and 6. This provides a foundation for real-time processing, subsequent storage, and rapid retrieval of power equipment switching quantities, effectively supporting the lean governance and operation and maintenance level of large-scale, massive data in the power system, and overall improving the intelligent data governance service level of the system. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a schematic diagram of the hierarchical flow of the switching quantities of power equipment throughout its entire life cycle, as described in this embodiment of the invention.

[0050] Figure 2 This is a flowchart illustrating a power equipment data governance method according to an embodiment of the present invention.

[0051] Figure 3 This is a full-process state transition diagram of the switching quantity of power equipment in an embodiment of the present invention.

[0052] Figure 4 This is a schematic diagram of the marking and deduplication process of power equipment switching quantities on the high-frequency sampling device side in an embodiment of the present invention.

[0053] Figure 5 This is a schematic diagram of the marking and deduplication process of power equipment switching quantities at the data access layer in an embodiment of the present invention.

[0054] Figure 6 This is a flowchart of the data access layer for the full-quantity marking algorithm of power equipment switching quantities.

[0055] Figure 7 This is a schematic diagram of the switch quantity query and extraction process based on the minimum time span in an embodiment of the present invention. Detailed Implementation

[0056] The following description of the embodiments is taken with reference to the accompanying drawings, which illustrate specific embodiments in which the invention can be implemented.

[0057] As mentioned earlier, due to various external factors, the state of switch signals throughout their entire lifecycle—from sampling, transmission, storage, to application—can experience data acquisition interruptions, data transmission delays, or loss. Therefore, to present the observable state to the end user in the application system, it should be more user-friendly and displayed in a more easily understandable way. This requires: First, from the user's perspective, expanding the definition of the entire switch signal's state process to ensure completeness and accuracy. Second, by combining an event tagging deduplication algorithm with a periodic tagging method, the high-frequency, precise, continuous switch signal events acquired by the acquisition device are significantly reduced in order to minimize the number of records transmitted and stored. Furthermore, a falling edge extraction algorithm within a controllable time interval with a minimum span ensures the accuracy, completeness, and continuity of the data extraction process.

[0058] In power grid systems, numerous monitoring devices of various switching quantities exist during the operation of power equipment, responsible for high-frequency acquisition of various switching status information of the power equipment. For example... Figure 1 The diagram illustrates the layered flow of power equipment switching signals throughout their entire lifecycle. The entire lifecycle of switching signals roughly includes four layered processing stages: high-frequency acquisition devices and data access gateways on the equipment side, a cloud-based data storage center, and a data application and display system. These are organized together through a comprehensive data network to form a complete closed-loop ecosystem. Given the massive scale and high frequency of data collection from switching monitoring devices, and the fact that a large number of duplicate values ​​exist within a certain time interval during the acquisition, transmission, and storage phases throughout the system's lifecycle, processing data in real-time at a 1:1 ratio would result in an excessively large data base, leading to excessive storage and query volumes, which would severely impact the rapid retrieval of data.

[0059] from Figure 1It is easy to see that the accuracy of an event is determined by the initial sampling period. Taking real-time data transmission at a sampling frequency of 20 milliseconds in a 1:1 manner as an example, even the simplest 01 encoding method of sampling is difficult to offset the huge data volume impact brought about by high-frequency sampling, resulting in inefficient data utilization efficiency for data transmission, storage, and query, and seriously affecting the utilization value of the data.

[0060] Therefore, this invention addresses the characteristic of switching signals being repeated extensively within a certain time interval by providing a power equipment data governance method to improve the utilization efficiency of massive amounts of data. Please refer to... Figure 2 As shown, the power equipment data governance method includes:

[0061] Step S1: Define multiple states for the switching quantities of power equipment according to the event types that the user side is concerned about, and set the transition rules between each state;

[0062] Step S2: On the high-frequency sampling device side of the equipment, a marking deduplication algorithm is used to accurately capture sudden events; and within the time interval of the minimum query time span, the sampling is marked on the hourly cycle to achieve the goal of high-frequency sampling and low-frequency recording on the high-frequency sampling device side, while preserving the readability of the user side of the minimum time query span.

[0063] Step S3: At the data access layer, a marking deduplication algorithm is used to accurately capture sudden events; and within the time interval of the minimum query time span, the sampling marking period is used to achieve the goal of high-frequency sampling and continuous recording and reporting of the second-lowest frequency on the high-frequency sampling device side, while preserving the continuous readability requirements of the minimum time query span on the user side.

[0064] Specifically, such as Figure 3 As shown in the full-process state transition diagram of power equipment switching quantities, in this embodiment, the power equipment switching quantities are defined into six states: 0, 1, 2, 3 and 5, 6, according to the event types that the user side is concerned about, and transition rules between each state are set.

[0065] Step S2 uses a combination of switch-to-signature deduplication and hourly-period signage. The signage deduplication algorithm is used on the high-frequency sampling device side to accurately capture sudden events and sample hourly-period signs within the time interval of the minimum query time span. This achieves the goal of high-frequency sampling and low-frequency recording while preserving the readability of the user side within the minimum time query span.

[0066] Please refer to again Figure 4 As shown, step S2 specifically includes:

[0067] Step S21: Create measurement point information and activate the measurement points when data writing begins;

[0068] Step S22: The high-frequency sampling device starts monitoring the on / off status of the high-frequency monitoring device to determine whether the sampling data obtained by the high-frequency sampling device is normal. The sampling period is configurable and defaults to 20 milliseconds.

[0069] Step S23: If the acquired sampling data is abnormal, the event is marked as the fifth state (state 5) according to the optional process, indicating that the sampling is abnormal;

[0070] Step S24: If the sampled data is obtained normally, compare the sampled value with the previous cached value at the measurement point. If it is a new value, immediately mark it as a sudden event (i.e., mark the event) and record it; if it is a duplicate value, process it according to the hourly cycle process, discard it or mark it at the hour.

[0071] Step S25: Determine whether the measurement point is write-prohibited. If not, process it according to the hourly cycle, discard or mark it as an hourly point, and then continue the cycle of acquiring sampling data for the next time. If yes, write data is prohibited for the measurement point and the measurement point is deleted, and the process ends.

[0072] The above process of sudden events + interval deduplication + hourly periodic marking can be used to represent low-frequency records as follows:

[0073] D = {F1, d1, ..., d} m1 ,...,d m2 ,...,d m3 ,...}

[0074] Wherein, the hourly period = the natural time when data is sampled, and the hourly period = the minimum query time span on the user side. This value is configurable and defaults to 1 second (it can be configured to 5 seconds depending on network bandwidth). D represents the sampled data record set after a sudden event at a certain moment; F1 represents the sudden event record at a certain moment; d1 represents the first duplicate event value after a sudden event at a certain moment, and subsequent duplicate event data records will be discarded; d m1 d m2 d m3 ...represent the data records of the natural cycle, the m1st time, the m2nd time, the m3rd time, ..., until the next sudden event occurs.

[0075] The high-frequency sampling device-side deduplication method of this invention satisfies both the high-frequency sampling period of 20 milliseconds on the device side and the continuity requirements of data reporting records and minimum time query span of 1 to 5 seconds on the device side.

[0076] It should be noted that the marking period method differs from the hourly marking method in that the marking period method focuses on solving the functional defect of the hourly marking method in that the data transmission delay causes the incorrect marking of state 6. The marking period method can ensure that the algorithm can handle the backlog of delayed data, and increase the robustness of the algorithm in such scenarios.

[0077] In step S3, the same marking and deduplication algorithm is used in the data access layer to accurately capture sudden events; and within the time interval of the minimum query time span, the sampling and marking cycle is used to achieve the goal of high-frequency sampling and continuous recording and reporting of the device side, while also preserving the continuous readability requirements of the minimum time query span on the user side.

[0078] Please refer to again Figure 5 As shown, step S3 specifically includes:

[0079] Step S31: Create measurement point information and activate the measurement points when data writing begins.

[0080] Step S32: The data access layer begins to receive high-frequency and sub-high-frequency sampling data from the high-frequency sampling device in real time, and determines whether the received sampling data is normal.

[0081] Step S33: If there is a delay in receiving the sampled data, the event is marked as the sixth state (state 6) according to the optional procedure, indicating that the sampled data delay timeout has occurred;

[0082] Step S34: If the received sampling data is normal, compare the sampled value with the previous buffered value of the measurement point. If it is a new value, immediately mark it as a sudden event (i.e., a marked event) and record it. If it is a duplicate value, process it according to the marking cycle process, discarding or marking the cycle point value.

[0083] Step S35: Determine whether the measurement point is write-prohibited. If not, process according to the marking cycle procedure, discard or mark the record, and then continue the loop process of receiving sampled data. If yes, write data is prohibited for the measurement point and the measurement point is deleted, and the process ends.

[0084] The process of receiving high-frequency sampled values ​​at the data access layer can be summarized as a process of sudden events + interval deduplication + marking periodic point values, which can be represented by low-frequency records as follows:

[0085] S = {D1,S1,...,S} m1 ,...,S m2 ,...,S m3 ,...}

[0086] Wherein, the marking period = data sampling frequency × number of consecutive records, and the marking period = minimum query time span on the user side, this value is configurable, the default is 1 minute (which can be configured to 5 seconds depending on network bandwidth). S represents the set of data records received at a certain moment in the data access layer; D1 represents the data record at a certain moment; S1 represents the first duplicate value of the data record at a certain moment, and subsequent duplicate data records will be discarded; S m1 S m2 Sm3 ...represent the data records for the marking period, m1, m2, m3, ..., until the next sudden event.

[0087] The data access side marking and deduplication method of this invention satisfies both the high-frequency sampling period of 20 milliseconds on the device side and the continuity requirements of the data reporting records of 1 to 5 seconds on the sampling device side and the minimum time query span of 1 to 5 minutes on the user side.

[0088] In addition, for process comparison, the following is a similar business processing flow for full recording, such as... Figure 6 The algorithm flow diagram of the full-scale marking algorithm for power equipment switching quantities in the data access layer is shown in the flowchart. Taking the data access layer as an example, the algorithm flow of full-scale sampling data recording is also adopted in the data access layer to achieve the goal of reporting high-frequency sampling and secondary low-frequency continuous recording on the device side. However, no deduplication processing is performed within the interval, resulting in the storage of a large number of duplicate values ​​within the time interval, which brings huge query challenges to queries based on massive data.

[0089] Figure 6 The process described below is as follows:

[0090] First, create the measurement point information and activate the measurement points when you start writing data.

[0091] The data access layer begins to receive high-frequency and sub-high-frequency sampling data from the sampling device in real time. If there is a delay in receiving the sampling data, an optional process is followed, and the event is marked as state 6 (6), indicating that the sampling data delay has timed out. If the received sampling data is normal, the real-time sampled values ​​are recorded, resulting in the storage of duplicate values ​​within a large number of time intervals.

[0092] Finally, determine whether the measurement point is write-prohibited. If not, continue the loop of receiving sampled data; if so, disable write data for that measurement point, delete the measurement point, and end the process.

[0093] The process of the data access layer receiving high-frequency sampled values ​​can be summarized as a process of sudden events + full sampling of the recording interval, which can be represented as:

[0094] P={D1,D2,D3,...,S1,S2,S3,...}

[0095] Wherein, the recording period = 1 / data sampling frequency, and the recording period = the minimum query time span on the user side. This value is not configurable and depends entirely on the reporting speed on the device side. P represents a continuous set of full high-frequency data records;

[0096] D1, D2, D3... represent continuous normal state data records starting from a certain moment; S1, S2, S3... represent continuous abnormal state sudden event records starting from a certain moment.

[0097] As can be seen from the above, this type of real-time recording processing algorithm can meet the high-frequency sampling period of 20 milliseconds on the device side and the data reporting record of 1 to 5 seconds on the sampling device side. However, there are a large number of duplicate recorded values, which leads to huge data utilization challenges in storage and querying.

[0098] Furthermore, embodiments of the present invention also propose a user-side switch quantity data query service processing flow, such as... Figure 7 The diagram illustrates the switch quantity query extraction process based on the minimum time span. User-side data queries are mainly divided into two scenarios: real-time queries and historical queries.

[0099] In the user-side data query process, the main issue to be addressed is the conversion of the minimum time span. The specific process is illustrated below:

[0100] Query the continuous records of the markers of sudden events and the minimum user query interval, and determine the value of the query time point according to the principle of taking the value at the lower edge.

[0101] Taking historical queries as an example, by converting the start and end times of the query into the minimum query span, it can be guaranteed that continuous status records can be retrieved.

[0102] Based on the process of receiving high-frequency sampled values ​​at the data access layer described above, it can be summarized as a process of sudden events + interval deduplication + marking periodic point values. Therefore, the query result can represent low-frequency records as follows:

[0103] S = {D1,S1,...,S} m1 ,...,S m2 ,...,S m3 ,...}

[0104] Where, the marking period = data sampling frequency × number of consecutive records, and the marking period = minimum query time span on the user side, this value is configurable, the default is 1 minute (which can be configured to 5 seconds depending on network bandwidth). S represents the set of data records queried on the user side; D1 represents the data record at a certain moment; S1 represents the first duplicate value of the data record at a certain moment, and subsequent duplicate data records will be discarded; S m1 S m2 S m3 ...represent the data records for the marking period, m1, m2, m3, ..., until the next sudden event.

[0105] The data access side marking and deduplication method of the present invention satisfies both the high-frequency sampling period of 20 milliseconds on the device side and the continuity requirements of data reporting records of 1 to 5 seconds on the sampling device side and the minimum time query span of 1 to 5 minutes on the user side.

[0106] Corresponding to the power equipment data governance method described in Embodiment 1 of the present invention, Embodiment 2 of the present invention also provides a power equipment data governance device, comprising:

[0107] The configuration module is used to define multiple states for the switching quantities of power equipment according to the event types that the user side is concerned about, and to set the transition rules between each state.

[0108] The first deduplication and hourly cycle marking module is used to use a deduplication method on the high-frequency sampling device side of the equipment to accurately capture sudden events; and to use an hourly cycle marking method within the time interval of the minimum query time span to achieve the goal of high-frequency sampling and low-frequency recording on the high-frequency sampling device side, while preserving the readability of the user side of the minimum time query span.

[0109] The second deduplication and hourly cycle marking module is used to use the marking deduplication method at the data access layer to accurately capture sudden events; and to use the sampling marking cycle method within the time interval of the minimum query time span to achieve the goal of high-frequency sampling and continuous recording and reporting of high-frequency and second-low-frequency data on the high-frequency sampling device side, while preserving the continuous readability requirements of the minimum time query span on the user side.

[0110] Furthermore, the first deduplication and hourly cycle marking module is specifically used for:

[0111] Create measurement point information and activate the measurement points when data writing begins;

[0112] The high-frequency sampling device starts monitoring the on / off status of the high-frequency monitoring equipment to determine whether the sampling data acquired by the high-frequency sampling device is normal.

[0113] If the acquired sampling data is abnormal, the event will be marked as the fifth state according to the optional procedure;

[0114] If the sampled data is obtained normally, the sampled value is compared with the previous cached value at the measurement point. If it is a new value, it is immediately marked as an emergency and recorded; if it is a duplicate value, it is processed according to the hourly cycle procedure, either discarded or marked on the hour.

[0115] Determine if the measurement point is write-prohibited. If not, process it according to the hourly cycle, discard or mark it as an hourly point, and then continue the cycle of acquiring sampling data for the next time. If it is write-prohibited, then the measurement point is deleted.

[0116] Furthermore, the second marker deduplication and hourly cycle marker module is specifically used for:

[0117] Create measurement point information and activate the measurement points when you start writing data.

[0118] The data access layer begins to receive high-frequency and sub-high-frequency sampling data from the high-frequency sampling device in real time, and determines whether the received sampling data is normal.

[0119] If there is a delay in receiving the sampled data, the event will be marked as the sixth state according to the optional procedure;

[0120] If the received sampling data is normal, the sampled value is compared with the previous buffered value at the measurement point. If it is a new value, it is immediately marked as a sudden event and recorded. If it is a duplicate value, it is processed according to the marking cycle process, either discarding or marking the cycle point value.

[0121] Determine whether the measurement point is write-prohibited. If not, process it according to the marking cycle procedure, discard or mark the record, and then continue the cycle of receiving sampled data. If it is write-prohibited, then the measurement point is deleted.

[0122] For the working principle and process of this embodiment, please refer to the description of Embodiment 1 of the present invention, which will not be repeated here.

[0123] As explained above, compared with the prior art, the beneficial effects of this invention are as follows: This invention provides data querying from the equipment side to the sampling device and then to the user side. The sampling accuracy of the marked events is at the 20-millisecond level. While ensuring no loss of sampling accuracy, the repeated values ​​of switching quantities within the time interval are effectively denoised and filtered. Furthermore, according to the minimum query requirements of the user side, hourly markers are added to effectively guarantee data continuity and readability. Simultaneously, the event types are expanded from the conventional 0 and 1 states to six more readable and understandable descriptions: 0, 1, 2, 3, 5, and 6. This provides a foundation for real-time processing, subsequent storage, and rapid retrieval of power equipment switching quantities, effectively supporting the lean governance and operation and maintenance level of large-scale, massive data in the power system, and overall improving the intelligent data governance service level of the system.

[0124] The above description is merely a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. Therefore, any equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for managing power equipment data, characterized in that, include: Step S1: Define the switching quantities of power equipment into six states, namely 0, 1, 2, 3 and 5, according to the event types that the user side is concerned about, and set the transition rules between each state. Step S2: On the high-frequency sampling device side of the equipment, a marking and deduplication method is used to accurately capture sudden events; and within the time interval of the minimum query time span, a full-hour periodic marking method is used to achieve the goal of high-frequency sampling and low-frequency recording on the high-frequency sampling device side, while preserving the readability of the user side of the minimum time query span. Step S3: Use a tagging and deduplication method at the data access layer to accurately capture sudden events; In addition, within the time interval of the minimum query time span, the received sampled data is continuously recorded and reported at a low frequency using a marking period method, while preserving the user's requirement for continuous readability within the minimum time query span. Step S2 specifically includes: Step S21: Create measurement point information and activate the measurement points when data writing begins; Step S22: The high-frequency sampling device starts monitoring the on / off status of the high-frequency monitoring equipment to determine whether the sampling data obtained by the high-frequency sampling device is normal. Step S23: If the acquired sampling data is abnormal, mark the event as the fifth state; Step S24: If the sampled data is obtained normally, compare the sampled value with the previous cached value at the measurement point. If it is a new value, immediately mark it as an emergency and record it; if it is a duplicate value, process it according to the hourly cycle procedure, discarding it or marking it at the hour. Step S25: Determine whether the measurement point is write-prohibited. If not, process it according to the hourly cycle, discard or mark it as an hourly point, and then continue the loop process of acquiring sampling data. If it is write-prohibited, the measurement point is deleted and the process ends. Step S3 specifically includes: Step S31: Create measurement point information and activate the measurement points when data writing begins; Step S32: The data access layer begins to receive data from the high-frequency sampling device in real time and determines whether the received data is normal. Step S33: If there is a delay in receiving data, mark the event as the sixth state; Step S34: If the received data is normal, compare the sampled value with the previous buffered value of the measurement point. If it is a new value, mark it as a sudden event and record it immediately. If it is a duplicate value, process it according to the marking period process, discarding or marking the period point value. Step S35: Determine whether the measurement point is write-prohibited. If not, process according to the marking cycle procedure, discard or mark the record, and then continue the data receiving loop. If yes, the measurement point is write-prohibited and the measurement point is deleted, and the process ends.

2. The power equipment data governance method according to claim 1, characterized in that, The hourly cycle uses the natural time when the data is sampled as the marker node, and its duration is equal to the minimum query time span on the user side.

3. The power equipment data governance method according to claim 1, characterized in that, Marking period = number of consecutive records The data sampling frequency and marking period are equal to the minimum query time span on the user side.

4. The power equipment data governance method according to claim 1, characterized in that, It also includes a user-side switch data query process, used to handle the conversion of the minimum time span. Specifically, it queries the continuous records of the markers of sudden events and the minimum user query interval, and determines the value of the query time point according to the principle of taking the value at the lower edge.

5. A power equipment data management device, characterized in that, include: The setting module is used to define the switching quantities of power equipment into six states, namely 0, 1, 2, 3 and 5, according to the event types that the user side is concerned about, and to set the transition rules between each state. The first deduplication and hourly periodic marking module is used to execute the deduplication method on the high-frequency sampling device side of the equipment to achieve accurate capture of sudden events; and to use the hourly periodic marking method within the time interval of the minimum query time span to achieve the goal of high-frequency sampling and low-frequency recording on the high-frequency sampling device side, while preserving the readability of the user side of the minimum time query span. The second tag deduplication and tag period tagging module is used to execute the tag deduplication method at the data access layer to complete the accurate capture of sudden events; In addition, within the time interval of the minimum query time span, the sampling period is used to record and report the received sampled data continuously at the second lowest frequency, while preserving the user's requirement for continuous readability within the minimum time query span. The first deduplication and integer periodic marking module is specifically used for: Create measurement point information and activate the measurement points when data writing begins; The high-frequency sampling device starts monitoring the on / off status of the high-frequency monitoring equipment to determine whether the sampling data acquired by the high-frequency sampling device is normal. If the acquired sampling data is abnormal, mark the event as the fifth state; If the sampled data is obtained normally, the sampled value is compared with the previous cached value at the measurement point. If it is a new value, it is immediately marked as an emergency and recorded. If it is a duplicate value, it will be processed according to the hourly cycle, either discarded or marked on the hour. Determine if the measurement point is write-prohibited. If not, process it according to the hourly cycle procedure, discard or mark it as an hourly point, and then continue the loop process of acquiring sampling data. If it is write-prohibited, then the measurement point is deleted. The second deduplication and periodic marking module is specifically used for: Create measurement point information and activate the measurement points when data writing begins; The data access layer begins to receive high-frequency and sub-high-frequency sampling data from the high-frequency sampling device in real time, and determines whether the received data is normal. If there is a delay in receiving data, mark the event as the sixth state; If the received data is normal, the sampled value is compared with the previous buffered value at the measurement point. If it is a new value, it is immediately marked as a sudden event and recorded. If it is a duplicate value, it is processed according to the marking cycle process, either discarding or marking the cycle point value. Determine if the measurement point is write-prohibited. If not, process according to the marking cycle procedure, discard or mark the record, and then continue the data receiving cycle. If so, then writing data to this measurement point is prohibited, and the measurement point should be deleted.

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