A method for dynamic zero drift filtering of sampling values ​​of relay protection device

Abstract

The present invention discloses a method for dynamic zero drift filtering of sampling values ​​of a relay protection device. The present invention filters out abnormal sampling points based on the numerical distribution statistics of the sampling points of the analog quantity in each phase interval, and calculates the DC component of the sampling value in the sliding time window as the zero drift of the sampling value, and calibrates the sampling value in real time to achieve dynamic tracking and real-time filtering of the zero drift. The present invention improves the accuracy of zero drift measurement, has low requirements on working conditions and environment, has strong adaptability, and will not affect the zero drift calibration accuracy when the system protection is started or when abnormal mutation points appear in the analog quantity sampling value.

Description

Technical Field

[0001] The invention belongs to the technical field of power system protection. Background Art

[0002] In the field of relay protection, the existing zero drift filtering method generally measures or calibrates the zero drift value of the system sampling in advance, and then uses the zero drift value to calibrate the analog quantity when the system is running. In this method, when measuring the zero drift value of the analog channel, the channel input needs to be short-circuited, and the zero drift value used for analog quantity calibration during system operation is fixed. Due to the aging of electronic components, environmental changes such as temperature and humidity in the analog sensing and sampling links, the zero drift value often changes over time, and the error of zero drift calibration may become larger and larger, affecting the reliability of the relay protection system and the accuracy of the measurement system.

[0003] Another method to measure zero drift is to calculate the cumulative sum of sampling points in real time, and find the average zero drift value based on the sum of sampling point data. However, invalid points or abnormal sampling points are inevitable in the process of sampling value collection and transmission. When the system protection is activated or the measured analog quantity has a sudden change, there will also be a large number of sampling value sudden change points. These sampling value abnormal points and sudden change points make the zero drift value measured by the cumulative sum of sampling points have a large error.

[0004] Another method is to accumulate sampling points when the system is shut down, started without protection, and without sudden changes in analog quantities, and calculate the average zero drift value. The disadvantage of this method is that it has strict requirements on measurement conditions and cannot measure the zero drift value dynamically in real time. Summary of the invention

[0005] Purpose of the invention: In order to solve the problems existing in the above-mentioned prior art, the present invention provides a method for dynamic zero drift filtering of sampling values ​​of a relay protection device.

[0006] Technical solution: The present invention provides a method for dynamic zero drift filtering of sampling values ​​of a relay protection device, which specifically includes the following steps:

[0007] Step 1: Periodically sample the AC analog quantity with zero DC bias in the relay protection device to obtain the analog signal cycle; when the number of analog signal cycles reaches a preset threshold value N, establish a time window with a length of N*Tsig, and put the N analog signal cycles into the time window in chronological order, where Tsig is the period of the analog cycle; the total number of sampling points in each analog signal cycle is the same;

[0008] Step 2: Divide the nth analog signal cycle into Y time segments evenly in time, n=1, ..., N; so that each sampling point on the cycle falls into and only falls into one of the time segments;

[0009] Step 3: Preset a number of analog value intervals so that the analog sampling value corresponding to each sampling point in any analog signal cycle belongs to and only belongs to one of the analog value intervals;

[0010] Step 4: group the sampling points that fall in the same numbered time segment into a group; for the yth time segment, if the number of sampling points in a certain analog value interval is less than a preset threshold, delete the sampling points in the analog value interval; calculate the average value of the analog values ​​corresponding to the remaining sampling points, and use the average value as the typical sampling value of the yth time segment, y=1, ..., Y;

[0011] Step 5: Calculate the average value of Y typical sampling values, use the average value as the zero drift value of the analog quantity in the current time window, and use the zero drift value to calibrate the sampling value of the analog quantity in real time;

[0012] Step 6: When a new analog signal cycle is generated, slide the time window forward by one analog cycle, move the longest cycle in the time window out of the time window, put the new analog signal cycle into the time window, and divide the new analog signal cycle into Y time periods evenly in time, and return to step 4.

[0013] Furthermore, the value range of N is 10-100.

[0014] Furthermore, in step 2, Y=Tsig / Tsamp, where Tsamp is a sampling period.

[0015] Beneficial effects:

[0016] First, the present invention adopts the method of numerical distribution probability statistics to calculate the typical value of each sampling point in the analog frequency, effectively eliminating abnormal sampling values ​​caused by various situations during operation, and improving the accuracy of zero drift measurement.

[0017] Second, the present invention uses a sliding window to calculate the zero drift value in real time, improves the dynamic response of the zero drift value, quickly and effectively tracks the changes of the analog zero drift value over time, and improves the accuracy of the system analog measurement.

[0018] Third, the algorithm provided by the present invention can be implemented in any link of analog quantity sampling value acquisition, transmission and processing in the system, without short-circuiting the analog quantity channel input or shutting down the system. It can automatically calculate the zero drift and calibrate during the normal operation of the system, has low requirements on working conditions and environment, and has strong adaptability. When the system protection is started or abnormal mutation points occur in the analog quantity sampling value, the zero drift calibration accuracy will not be affected. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the process of the present invention;

[0020] Figure 2 It is a schematic diagram of the time segment division of analog quantity of the present invention;

[0021] Figure 3 It is a schematic diagram of the distribution of values ​​of sampling points falling within the same time segment number of the present invention. DETAILED DESCRIPTION

[0022] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0023] The present embodiment provides a method for dynamic zero drift filtering of sampling values ​​of a relay protection device. The method is applied to an analog zero drift calibration device with a zero DC component. The analog signal is evenly divided into a number of phase intervals, and the numerical distribution of the sampling points of each phase interval in a specified time window is counted. The sampling points with low numerical distribution probability in each phase interval are eliminated, and the remaining sampling points are averaged to obtain the DC component of the sampling value in the time window, which is used as the zero drift of the sampling value for filtering, such as Figure 1 As shown, the specific steps include:

[0024] Step 1: Divide a complete analog signal cycle into Tsig / Tsamp time segments. This embodiment takes a typical application scenario in the field of relay protection as an example. The cycle of the AC analog quantity is 20ms and the sampling frequency is 1.2KHz. Then, a complete analog signal cycle is divided into 24 time segments, numbered 1 to 24. Figure 2 As shown in the figure, time segments at the same position in different analog cycles are regarded as the same time segment and have the same number.

[0025] Step 2: preset several analog value intervals based on experience, so that the value of each sampling point belongs to and only belongs to one of the value segments.

[0026] Step 3: When the number of analog signal cycles reaches a preset threshold value N, a time window with a length of N*Tsig is established, and the N analog signal cycles are placed in the time window in chronological order. The total number of sampling points in each analog signal cycle is the same. In this embodiment, N=10~100.

[0027] Step 4: The window contains N analog cycles, each cycle contains 24 sampling points, each sampling point falls into and only falls into one of the time segments, and the sampling points falling into the same numbered time segment are grouped together to obtain 24 groups of data.

[0028] Step 5: For each group of data, the analog sampling values ​​corresponding to the sampling points in the numerical range in step 2 are distributed and counted, such as Figure 3 .

[0029] Step 6: For any time segment, if the number of sampling points in a certain analog value interval in the vertical axis is less than the preset threshold, the sampling points in the analog value interval are deleted; the average value of the analog values ​​corresponding to the remaining sampling points is calculated; this average value is used as the typical sampling value of the numbered time segment.

[0030] Step 7: Calculate the average value of the typical sampling values ​​of the 24 time segments, which is the zero drift value of the analog quantity, and use the latest zero drift value to calibrate the analog quantity sampling value in real time.

[0031] Step 8: When the number of analog sampling points newly arrived meets the number of sampling points of one cycle (that is, when a new complete analog signal cycle is generated), slide the window forward by one analog cycle, remove the longest cycle in the time window from the time window, and put the new analog signal cycle into the time window, repeat steps 4 to 7, and refresh the zero drift value. Similarly, update the zero drift value every 20ms.

[0032] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge scope of ordinary technicians in this field without departing from the purpose of the present invention.

Claims

1. A method for dynamic zero drift filtering of sampling values ​​of a relay protection device, characterized in that: The specific steps include: Step 1: Periodically sample the AC analog quantity with zero DC bias in the relay protection device to obtain the analog signal cycle; when the number of analog signal cycles reaches a preset threshold value N, establish a time window with a length of N*Tsig, and put the N analog signal cycles into the time window in chronological order, where Tsig is the period of the analog cycle; the total number of sampling points in each analog signal cycle is the same; Step 2: Divide the nth analog signal cycle into Y time segments evenly in time, n=1, ..., N; so that each sampling point on the cycle falls into and only falls into one of the time segments; Step 3: Preset a number of analog value intervals so that the analog sampling value corresponding to each sampling point in any analog signal cycle belongs to and only belongs to one of the analog value intervals; Step 4: group the sampling points that fall in the same numbered time segment into a group; for the yth time segment, if the number of sampling points in a certain analog value interval is less than a preset threshold, delete the sampling points in the analog value interval; calculate the average value of the analog values ​​corresponding to the remaining sampling points, and use the average value as the typical sampling value of the yth time segment, y=1, ..., Y; Step 5: Calculate the average value of Y typical sampling values, use the average value as the zero drift value of the analog quantity in the current time window, and use the zero drift value to calibrate the sampling value of the analog quantity in real time; Step 6: When a new analog signal cycle is generated, slide the time window forward by one analog cycle, move the longest cycle in the time window out of the time window, put the new analog signal cycle into the time window, and divide the new analog signal cycle into Y time periods evenly in time, and return to step 4.

2. A method for dynamic zero drift filtering of sampling values ​​of a relay protection device according to claim 1, characterized in that: The value range of N is 10-100.

3. A method for dynamic zero drift filtering of sampling values ​​of a relay protection device according to claim 1, characterized in that: In step 2, Y=Tsig / Tsamp, where Tsamp is the sampling period.

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