A steady-state analysis method and terminal for power quality data

Abstract

The present invention discloses a steady-state analysis method and terminal for power quality data. After collecting the power quality data of each monitoring point, the steady-state qualified rate of the power quality data within each regional range is calculated. Therefore, the steady-state qualified rate of the harmonic monitoring point can be displayed through the dimension of the power grid topology area, which is convenient for targeted data missing location or fault location. If the steady-state qualified rate reaches the qualified rate threshold, the collected power quality data is reliable data. Otherwise, the integrity index of the power quality data is calculated. When the integrity index falls within the integrity interval, the regional steady-state qualified rate is recalculated. When the integrity index does not fall within the integrity interval, the power quality data is supplemented. In this way, the problem of a decrease in the steady-state qualified rate due to incomplete power quality data collection can be reduced, the integrity of the power quality data can be guaranteed, and the steady-state qualified rate of the power quality data can be guaranteed to meet the standard.

Description

Technical Field

[0001] The present invention relates to the technical field of power quality data analysis, and in particular to a steady-state analysis method and terminal for power quality data. Background Art

[0002] As a system for monitoring power quality data, the power quality monitoring terminal has the characteristic of large data volume. Large data volume will bring a series of problems such as insufficient storage space, low query efficiency, and difficulty in handling abnormal data. One of the important problems is the integrity of power quality data.

[0003] Power quality data is the foundation for various subsequent power quality analyses. Incomplete data will lead to incomplete and unreliable power quality analysis results, resulting in a decrease in the pass rate of steady-state power quality indicators. In practical applications, power quality monitoring systems are prone to data loss due to their wide coverage area, complex network structure, and complex data interfaces. Data integrity has become a very important factor affecting the normal operation of power quality monitoring systems. However, there is currently no effective method to handle or recover missing power quality data. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a steady-state analysis method and terminal for power quality data, which can ensure the integrity of power quality data and process data when it is missing.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A method for steady-state analysis of power quality data, comprising the steps of:

[0007] S1. Collect power quality data of each monitoring point;

[0008] S2. Calculate the steady-state qualified rate of power quality data within each area;

[0009] S3. If the steady-state qualified rate reaches the qualified rate threshold, the collected power quality data is reliable data; otherwise, the integrity index of the power quality data is calculated. When the integrity index falls within the integrity interval, step S2 is re-executed. When the integrity index does not fall within the integrity interval, the power quality data is supplemented and the process returns to step S1.

[0010] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0011] A steady-state analysis terminal for power quality data includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, each step of the steady-state analysis method for power quality data is implemented.

[0012] The beneficial effect of the present invention is that after collecting the power quality data of each monitoring point, the steady-state qualified rate of the power quality data within each regional range is calculated. Therefore, the steady-state qualified rate of the harmonic monitoring point can be displayed through the dimension of the power grid topology area, which is convenient for targeted data missing location or fault location. If the steady-state qualified rate reaches the qualified rate threshold, the collected power quality data is reliable data. Otherwise, the integrity index of the power quality data is calculated. When the integrity index falls within the integrity interval, the regional steady-state qualified rate is recalculated. When the integrity index does not fall within the integrity interval, the power quality data is supplemented. In this way, the problem of a decrease in the steady-state qualified rate due to incomplete power quality data collection can be reduced, the integrity of the power quality data can be guaranteed, and data can be processed when it is missing, thereby ensuring that the steady-state qualified rate of the power quality data meets the standard. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is a flow chart of a method for steady-state analysis of power quality data according to an embodiment of the present invention;

[0014] Figure 2 Schematic diagram of a steady-state analysis terminal for power quality data according to an embodiment of the present invention;

[0015] Figure 3 A flowchart showing the specific steps of a method for steady-state analysis of power quality data according to an embodiment of the present invention;

[0016] Description of labels:

[0017] 1. A steady-state analysis terminal for power quality data; 2. A memory; 3. A processor. DETAILED DESCRIPTION

[0018] To illustrate the technical content, achieved objectives and effects of the present invention in detail, the following description is given in conjunction with the embodiments and accompanying drawings.

[0019] Please refer to Figure 1 , an embodiment of the present invention provides a method for steady-state analysis of power quality data, comprising the steps of:

[0020] S1. Collect power quality data of each monitoring point;

[0021] S2. Calculate the steady-state qualified rate of power quality data within each area;

[0022] S3. If the steady-state qualified rate reaches the qualified rate threshold, the collected power quality data is reliable data; otherwise, the integrity index of the power quality data is calculated. When the integrity index falls within the integrity interval, step S2 is re-executed. When the integrity index does not fall within the integrity interval, the power quality data is supplemented and the process returns to step S1.

[0023] From the above description, it can be seen that the beneficial effect of the present invention is that after collecting the power quality data of each monitoring point, the steady-state qualified rate of the power quality data within each regional range is calculated. Therefore, the steady-state qualified rate of the harmonic monitoring point can be displayed through the dimension of the power grid topology area, which is convenient for targeted data missing location or fault location. If the steady-state qualified rate reaches the qualified rate threshold, the collected power quality data is reliable data. Otherwise, the integrity index of the power quality data is calculated. When the integrity index falls within the integrity interval, the regional steady-state qualified rate is recalculated. When the integrity index does not fall within the integrity interval, the power quality data is supplemented. In this way, the problem of the steady-state qualified rate drop caused by incomplete power quality data collection can be reduced, the integrity of the power quality data can be guaranteed, and data can be processed when it is missing, thereby ensuring that the steady-state qualified rate of the power quality data can meet the standard.

[0024] Furthermore, step S2 includes:

[0025] Calculating a first steady-state pass rate of the power quality data based on the power quality data collected by each monitoring point in the first cycle;

[0026] Divide each monitoring point into regional hierarchies based on the power grid topology, and calculate the second steady-state qualified rate of power quality data in each regional range within the first cycle according to the first steady-state qualified rate of each monitoring point;

[0027] Calculating a third steady-state qualified rate of power quality data of each area within the second period according to the second steady-state qualified rate of each area;

[0028] The duration of the first cycle is shorter than the duration of the second cycle.

[0029] Furthermore, according to the first steady-state qualified rate of each monitoring point, the second steady-state qualified rate of the power quality data of each area within the first cycle is calculated, including:

[0030] The second steady-state qualified rate of each area is the weighted average of the second steady-state qualified rates of the next level areas of the area;

[0031] The second steady-state qualified rate within the minimum level area is the weighted average of the first steady-state qualified rates of all monitoring points in the area.

[0032] From the above description, we can see that recursively calculating the steady-state qualified rate of different areas layer by layer can provide an important basis for subsequent data missing location, data supplementation, and equipment fault location.

[0033] Furthermore, in step S3, calculating the integrity index of the power quality data includes:

[0034] Calculate the percentage ID of the data sent by each monitoring point and all the data contained in each monitoring point:

[0035]

[0036] Where VD i Indicates the number of data sent up by the i-th monitoring point, OD i It indicates the number of unsent data of the i-th monitoring point, and N indicates the number of monitoring points.

[0037] From the above description, it can be seen that calculating the integrity index of power quality data based on the ratio of uploaded data to all data can accurately and reasonably calculate the integrity of power quality data.

[0038] Furthermore, in step S3, the integrity interval includes:

[0039] Collect historical power quality data of each monitoring point, and perform linear regression analysis on the historical power quality data to obtain linear regression coefficients C1, ..., C i ,…,C N and R;

[0040] Estimate the integrity ID of the monitoring point based on the linear regression coefficient loss :

[0041]

[0042] The linear equation interval of the integrity of the monitoring point is used as the integrity interval.

[0043] From the above description, it can be seen that by estimating the integrity of the monitoring points through the linear regression coefficient and then using the linear equation interval as the integrity interval, a reasonable integrity interval can be obtained according to the historical situation of each monitoring point, further ensuring the accuracy of power quality data analysis.

[0044] Please refer to Figure 2 Another embodiment of the present invention provides a steady-state analysis terminal for power quality data, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, each step of the above-mentioned steady-state analysis method for power quality data is implemented.

[0045] The above-mentioned steady-state analysis method and terminal for power quality data of the present invention are suitable for ensuring the integrity of the collected power quality data and processing the data when it is missing, thereby ensuring that the steady-state qualified rate of the power quality data can meet the standard. The following is an explanation through specific implementation methods:

[0046] Example 1

[0047] Please refer to Figure 1 and Figure 3 , a steady-state analysis method for power quality data, comprising the steps of:

[0048] S1. Collect power quality data from each monitoring point.

[0049] S2. Calculate the steady-state pass rate of power quality data in each area.

[0050] S21. Calculate a first steady-state pass rate of the power quality data based on the power quality data collected by each monitoring point within a first period.

[0051] In this embodiment, the first cycle is daily. Specifically, a formula for calculating the first steady-state qualified rate of a single monitoring point is established:

[0052]

[0053] Where, CR s It indicates the daily qualified rate of harmonic power quality index s at the operation monitoring point, that is, the first steady-state qualified rate; CN s It indicates the number of data that do not exceed the standard in the data indicator s sent by the monitoring points put into operation on the day at the statistical time interval (1 minute or 3 minutes); OD indicates the number of data that should be sent by the monitoring points put into operation on the day at the statistical time interval (1 minute or 3 minutes).

[0054] Where s represents the type of harmonic power quality indicators, including: harmonic voltage (total harmonic distortion rate of voltage, content rate of each harmonic voltage), voltage deviation, three-phase voltage unbalance, interharmonic voltage content rate (each interharmonic voltage), harmonic current (each harmonic current), negative sequence current, frequency deviation, and flicker.

[0055] In this embodiment, statistics are collected daily at 1:00 AM each day for the daily steady-state indicator pass rate for the monitoring points put into operation the previous day. Data uploaded or supplemented thereafter will no longer be counted. According to the harmonic monitoring platform's indicator judgment principles, monitoring points above 330 kV do not determine the voltage total harmonic distortion rate, harmonic voltage content, negative sequence current, or harmonic current.

[0056] In this embodiment, the monthly pass rate of a single monitoring point also needs to be calculated:

[0057]

[0058] In the formula, CG s It represents the monthly qualified rate of the power grid harmonic power quality index s; H represents the number of statistical days in a month, CR sh represents the daily pass rate on day h.

[0059] Preferably, the monthly pass rate is calculated on a calendar month basis, and the monthly pass rate of the previous month is calculated starting at 24:00 on the 3rd of each month. Data uploaded or supplemented thereafter will no longer be included in the statistical scope.

[0060] S22. Divide each monitoring point into regional hierarchies based on the power grid topology, and calculate the second steady-state qualified rate of the power quality data in each regional range within the first cycle according to the first steady-state qualified rate of each monitoring point.

[0061] The second steady-state pass rate for each area is the weighted average of the second steady-state pass rates for the next level of areas within that area; the second steady-state pass rate for the minimum level area is the weighted average of the first steady-state pass rates for all monitoring points within that area. Therefore, the second steady-state pass rate in this embodiment is a weighted calculation of multi-point monitoring data.

[0062] Specifically, a recursive hierarchical approach is used to calculate the steady-state pass rates of different regions, providing a crucial basis for locating missing data, supplementing data, and locating equipment faults. The regions are divided based on the grid topology, which in this embodiment is a typical tree structure. When calculating the steady-state pass rate, the steady-state pass rate of the parent region is inferred from the steady-state pass rate of the monitoring point, resulting in a more accurate result. The parent region is the region one level above the current region.

[0063] In this embodiment, it is assumed that the power grid topology is: N first-level areas, M second-level areas, I third-level areas, and J fourth-level areas. The steady-state qualified rate of each regional level is obtained by weighted average of the steady-state qualified rates of its sub-levels to obtain the steady-state qualified rate of the region, where the sub-level is the region of the next level of the current region.

[0064] The steady-state qualified rate of the fourth-level area is the weighted average of the daily qualified rates of all monitoring points in the area:

[0065]

[0066] Where KR sj represents the daily qualified rate of the power quality index s of the monitoring point in the fourth-level area j; D represents the number of monitoring points in the fourth-level area; CR sd It represents the daily qualified rate of the power quality index s at the d-th monitoring point.

[0067] The steady-state pass rate of the third-level region is the weighted average of the steady-state pass rates of the fourth-level region:

[0068]

[0069] The steady-state pass rate of the second-level region is the weighted average of the steady-state pass rates of the third-level region:

[0070]

[0071] The steady-state pass rate of the first-level region is the weighted average of the steady-state pass rates of the second-level region:

[0072]

[0073] In this way, the relatively accurate steady-state qualified rate of each area can be more clearly and intuitively understood, and a basis can be provided for the rapid location of steady-state indicator problems.

[0074] S23. Calculate the third steady-state qualified rate of the power quality data of each area in the second period according to the second steady-state qualified rate of each area.

[0075] In this embodiment, the second cycle is monthly. Specifically, the formula for calculating the third steady-state qualified rate of the power quality data collected in each area within the second cycle is:

[0076]

[0077] Where KM s Indicates the monthly qualified rate of power quality index s of regional monitoring points, KR sh It represents the daily qualified rate of the power quality indicator s of the regional monitoring point on the hth day. It can be seen that the third steady-state qualified rate in this embodiment is also calculated by weighting the multi-point monitoring data.

[0078] Among them, the monthly pass rate is calculated in the natural month, and the monthly pass rate of the monitoring points of the previous month will be calculated starting at 24:00 on the 3rd of each month. Data uploaded or supplemented thereafter will no longer be included in the statistical scope.

[0079] S3. If the steady-state qualified rate reaches the qualified rate threshold, the collected power quality data is reliable data; otherwise, the integrity index of the power quality data is calculated. When the integrity index falls within the integrity interval, step S2 is re-executed. When the integrity index does not fall within the integrity interval, the power quality data is supplemented and the process returns to step S1.

[0080] First, determine whether the steady-state pass rate reaches the pass rate threshold. Sequentially determine the first, second, and third steady-state pass rates. In this embodiment, the three steady-state pass rates all meet the following criteria: a steady-state pass rate ≥ 90% for excellent, 60% ≤ a steady-state pass rate < 90% for qualified, and a steady-state pass rate < 60% for extremely poor. Therefore, the pass rate threshold is set at 60%. Therefore, when the three steady-state pass rates reach 60%, the collected power quality data is considered reliable, and the analysis ends.

[0081] When one of the three steady-state qualified rates does not reach 60%, the integrity index of the power quality data is calculated, including:

[0082] Calculate the percentage ID of the data sent by each monitoring point and all the data contained in each monitoring point:

[0083]

[0084] Where VD i Indicates the number of data sent up by the i-th monitoring point, OD i It indicates the number of unsent data of the i-th monitoring point, and N indicates the number of monitoring points.

[0085] The calculation method of the integrity interval is:

[0086] Collect historical power quality data of each monitoring point, and perform linear regression analysis on the historical power quality data to obtain linear regression coefficients C1, ..., C i ,…,C N and R;

[0087] Estimate the integrity ID of the monitoring point based on the linear regression coefficient loss :

[0088]

[0089] The linear equation interval of the integrity of the monitoring point is used as the integrity interval.

[0090] Determine whether the ID is in ID loss If the data is not within the linear equation interval, it means that the data sent by the monitoring point is incomplete and needs to be supplemented and sent again for analysis of the steady-state indicators. By improving the integrity of the data, the qualified rate of each steady-state indicator can be improved.

[0091] Example 2

[0092] Please refer to Figure 2A steady-state analysis terminal 1 for power quality data includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3. When the processor 3 executes the computer program, each step of a steady-state analysis method for power quality data in embodiment 1 is implemented.

[0093] In summary, the present invention provides a method and terminal for steady-state analysis of power quality data. After collecting the power quality data of each monitoring point, the steady-state qualified rate of the power quality data within each regional range is calculated. Therefore, the steady-state qualified rate of the harmonic monitoring point can be displayed through the dimension of the power grid topology area, which is convenient for targeted data missing location or fault location. If the steady-state qualified rate reaches the qualified rate threshold, the collected power quality data is reliable data. Otherwise, the integrity index of the power quality data is calculated. When the integrity index falls within the integrity interval, the regional steady-state qualified rate is recalculated. When the integrity index does not fall within the integrity interval, the power quality data is supplemented. In this way, the problem of a decrease in the steady-state qualified rate due to incomplete power quality data collection can be reduced, the integrity of the power quality data can be guaranteed, and data can be processed when it is missing, thereby ensuring that the steady-state qualified rate of the power quality data meets the standard.

[0094] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's description and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A steady-state analysis method for power quality data, characterized in that: Including steps: S1. Collect power quality data of each monitoring point; S2. Calculate the steady-state qualified rate of power quality data within each area; S3. If the steady-state qualified rate reaches the qualified rate threshold, the collected power quality data is reliable data; otherwise, the integrity index of the power quality data is calculated. When the integrity index falls within the integrity interval, step S2 is re-executed. When the integrity index does not fall within the integrity interval, the power quality data is supplemented and the process returns to step S1. Step S2 includes: calculating a first steady-state qualified rate of the power quality data based on the power quality data collected by each monitoring point in the first cycle; dividing each monitoring point into regional hierarchies based on the power grid topology, and calculating a second steady-state qualified rate of the power quality data of each regional range in the first cycle based on the first steady-state qualified rate of each monitoring point; calculating a third steady-state qualified rate of the power quality data of each regional range in the second cycle based on the second steady-state qualified rate of each regional range; the duration of the first cycle is less than the duration of the second cycle; Calculate the second steady-state qualified rate of the power quality data of each area within the first cycle based on the first steady-state qualified rate of each monitoring point, including: the second steady-state qualified rate of each area is the weighted average of the second steady-state qualified rates of the next level area in the area; the second steady-state qualified rate within the minimum level area is the weighted average of the first steady-state qualified rates of all monitoring points in the area; In step S3, calculating the integrity index of the power quality data includes: Calculate the percentage ID of the data sent by each monitoring point and all the data contained in each monitoring point: Where, VD i Indicates the number of data sent up by the i-th monitoring point, OD i Indicates the number of unsent data of the i-th monitoring point, N Indicates the number of monitoring points.

2. The method for steady-state analysis of power quality data according to claim 1, characterized in that: In step S3, the integrity interval includes: Collect historical power quality data from each monitoring point and perform linear regression analysis on the historical power quality data to obtain the linear regression coefficients C 1. ... C i 、…、 C N and R; Estimate the integrity of the monitoring points based on the linear regression coefficient ID loss : + + + The linear equation interval of the integrity of the monitoring point is used as the integrity interval.

3. A steady-state analysis terminal for power quality data, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the following steps are implemented: S1. Collect power quality data of each monitoring point; S2. Calculate the steady-state qualified rate of power quality data within each area; S3. If the steady-state qualified rate reaches the qualified rate threshold, the collected power quality data is reliable data; otherwise, the integrity index of the power quality data is calculated. When the integrity index falls within the integrity interval, step S2 is re-executed. When the integrity index does not fall within the integrity interval, the power quality data is supplemented and the process returns to step S1. Step S2 includes: calculating a first steady-state qualified rate of the power quality data based on the power quality data collected by each monitoring point in the first cycle; dividing each monitoring point into regional hierarchies based on the power grid topology, and calculating a second steady-state qualified rate of the power quality data of each regional range in the first cycle based on the first steady-state qualified rate of each monitoring point; calculating a third steady-state qualified rate of the power quality data of each regional range in the second cycle based on the second steady-state qualified rate of each regional range; the duration of the first cycle is less than the duration of the second cycle; Calculate the second steady-state qualified rate of the power quality data of each area within the first cycle based on the first steady-state qualified rate of each monitoring point, including: the second steady-state qualified rate of each area is the weighted average of the second steady-state qualified rates of the next level area in the area; the second steady-state qualified rate within the minimum level area is the weighted average of the first steady-state qualified rates of all monitoring points in the area; In step S3, calculating the integrity index of the power quality data includes: Calculate the percentage ID of the data sent by each monitoring point and all the data contained in each monitoring point: Where, VD i Indicates the number of data sent up by the i-th monitoring point, OD i Indicates the number of unsent data of the i-th monitoring point, N Indicates the number of monitoring points.

4. The steady-state analysis terminal for power quality data according to claim 3, characterized in that: In step S3, the integrity interval includes: Collect historical power quality data from each monitoring point and perform linear regression analysis on the historical power quality data to obtain the linear regression coefficients C 1. ... C i 、…、 C N and R; Estimate the integrity of the monitoring points based on the linear regression coefficient ID loss : + + + The linear equation interval of the integrity of the monitoring point is used as the integrity interval.

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