Power system frequency measurement method and system based on squeeze theorem

Abstract

The application provides a power system frequency measurement method and system based on the squeeze theorem, which comprises the following steps: sampling the system voltage signal in real time at a fixed sampling frequency fs; determining whether there is a zero-crossing interval according to the positive and negative signs of the sampling value; when the zero-crossing interval exists, calculating the difference value of adjacent points and judging whether the difference value of adjacent points meets a preset similarity condition; when the preset similarity condition is met, determining that the zero-crossing interval is valid based on the squeeze theorem, and calculating the accurate zero-crossing time Tn by linear interpolation; and calculating the system frequency according to the current zero-crossing time Tn and the previous zero-crossing time T0. The sine wave signal of the zero-crossing point is replaced by a linear signal by using the squeeze theorem, so that the influence of the following situations on the frequency calculation can be avoided, and abnormal situations such as burrs, jumps, communication errors, missing points and repeated points caused by electromagnetic interference can be avoided.

Description

Technical Field

[0001] This invention relates to the field of power system automation technology, and in particular to a power system frequency measurement method and system based on the squeeze theorem. Background Technology

[0002] In power system operation, frequency is one of the key indicators, affecting the safe and stable operation of the system. Therefore, reliable measurement of system frequency is crucial. Conventional power automation equipment and intelligent primary equipment all require system frequency measurement. The traditional approach is to detect the zero-crossing point of the voltage signal to obtain the period, and then convert it into the system frequency. This method is simple in principle and convenient to implement, but it has the following drawbacks:

[0003] 1. When electromagnetic interference such as surges, fast transients, and oscillating waves is present, the measuring device may experience signal sampling errors due to insufficient anti-interference capability. These errors may include jumps, non-singular values, glitches, zero-crossing detection errors, or insufficient calculation accuracy. (See attached diagram.) Figure 2 Appendix Figure 3 As shown;

[0004] 2. Abnormal situations such as lost or duplicated points caused by communication anomalies can also affect the accuracy of frequency calculation. When a large number of power electronic loads are connected, especially at the moment of connection or disconnection, the harmonic signals superimposed on the fundamental voltage can adversely affect the detection of the zero-crossing point of the frequency, resulting in a decrease in calculation accuracy. Summary of the Invention

[0005] The purpose of this invention is to at least address one of the aforementioned technical deficiencies.

[0006] Therefore, one objective of this invention is to propose a power system frequency measurement method based on the squeeze theorem. Based on the calculus limit theory, a linear function is replaced with a sine function to enhance the judgment of the validity of the zero crossing point and improve the accuracy of the algorithm.

[0007] To achieve the above objectives, one aspect of the present invention provides a power system frequency measurement method based on the squeeze theorem, comprising the following steps:

[0008] S1. The system voltage signal is sampled in real time at a fixed sampling frequency fs;

[0009] S2. Define the sample value corresponding to the current sampling point as y(k), then the previous sample value is y(k-1), the previous two sample values ​​are y(k-2), and so on; determine whether there is a zero-crossing interval based on the sign of the sample value;

[0010] S3. When a zero-crossing interval exists, calculate the difference between adjacent points and determine whether the difference between adjacent points meets the preset similarity condition. When the preset similarity condition is met, the zero-crossing interval is determined to be valid based on the squeeze theorem, and linear interpolation is used to calculate the precise zero-crossing time Tn.

[0011] S4. Calculate the system frequency based on the current zero-crossing time Tn and the previous zero-crossing time T0:

[0012]

[0013] Furthermore, in S2, determining whether a zero-crossing interval exists based on the sign of the sampled values ​​includes:

[0014] When y(k-3) and y(k-2) ≤ 0 and y(k-1) and y(k) ≥ 0, it is determined that there is a zero-crossing interval.

[0015] Furthermore, in S3, when a zero-crossing interval exists, calculating the difference between adjacent points and determining whether the difference between adjacent points satisfies the preset similarity condition includes:

[0016] 1) Calculate the difference between adjacent points:

[0017] DiffY(1)=y(k)-y(k-1)

[0018] DiffY(2)=y(k-1)-y(k-2)

[0019] DiffY(3)=y(k-2)-y(k-3)

[0020] 2) Determine whether DiffY(1), DiffY(2), and DiffY(3) satisfy the following preset similarity conditions:

[0021] DiffY(1)≈DiffY(2)≈DiffY(3).

[0022] Furthermore, in S3, when a preset similarity condition is met, the zero-crossing interval is determined to be valid based on the squeeze theorem, including:

[0023] When the preset similarity condition is met, based on the squeeze theorem:

[0024]

[0025] If we replace the sine function with a linear function, x approaches 0, sinx also approaches 0, and y(k-1) and y(k) also approach 0. Then the interval [k-1,k] is a valid zero-crossing interval.

[0026] Furthermore, the zero-crossing time Tn is calculated using the linear interpolation method described below.

[0027] An interpolation algorithm is used to calculate the precise zero-crossing time:

[0028] T n =k-2+[-y(k-1)] / [y(k)-y(k-1)]

[0029] Furthermore, the previous zero-crossing time T0 is a confirmed valid zero-crossing time, and Tn > T0.

[0030] The present invention also provides a power system frequency measurement device based on the squeeze theorem, which is used to implement the above-mentioned power system frequency measurement method based on the squeeze theorem, including:

[0031] The data acquisition module is installed in the power system to sample the system voltage signal in real time at a fixed sampling frequency fs;

[0032] The data processing module defines the current sampling point as y(k), the previous sampling point as y(k-1), the two previous sampling points as y(k-2), and so on. Based on the sign of the sampling value, it determines whether a zero-crossing interval exists. When a zero-crossing interval exists, it calculates the difference between adjacent points and determines whether the difference satisfies a preset similarity condition. If the preset similarity condition is met, it determines that the zero-crossing interval is valid based on the squeeze theorem and uses linear interpolation to calculate the precise zero-crossing time Tn. Based on the current zero-crossing time Tn and the previous zero-crossing time T0, it calculates the system frequency.

[0033] According to the embodiments of the present invention, based on real-time sampling information of the device and the squeeze theorem of the calculus limit theory, the validity of zero-crossing points is enhanced, avoiding the influence of electromagnetic interference, communication errors and system harmonics on the frequency algorithm, thus ensuring the correctness of the calculation and the frequency algorithm.

[0034] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0035] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0036] Figure 1 This is a flowchart of a power system frequency measurement method based on the squeeze theorem;

[0037] Figure 2 This is a schematic diagram illustrating the error in zero-crossing detection when conventional methods are used in the event of electromagnetic interference.

[0038] Figure 3This is a schematic diagram illustrating the decrease in accuracy of calculation results when conventional methods are used in the presence of electromagnetic interference.

[0039] Figure 4 This is a diagram illustrating how the accuracy of calculation results decreases when communication errors occur using conventional methods.

[0040] Figure 5 This is a schematic diagram illustrating the decrease in accuracy of calculation results when harmonic signals are present in the system using conventional methods. Detailed Implementation

[0041] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0042] like Figure 1 As shown in the figure, an embodiment of the present invention provides a power system frequency measurement method based on the squeeze theorem, comprising the following steps:

[0043] S1. The system voltage signal is sampled in real time at a fixed sampling frequency fs;

[0044] S2. Define the sample value corresponding to the current sampling point as y(k), then the previous sample value is y(k-1), the previous two sample values ​​are y(k-2), and so on; determine whether there is a zero-crossing interval based on the sign of the sample value;

[0045] Furthermore, in S2, determining whether a zero-crossing interval exists based on the sign of the sampled values ​​includes:

[0046] When y(k-3) and y(k-2) ≤ 0 and y(k-1) and y(k) ≥ 0, it is determined that there is a zero-crossing interval.

[0047] Finding the initial zero-crossing interval is exactly the same process as the regular algorithm. However, unlike the regular algorithm, this zero-crossing interval needs further validation, including whether it is a true zero-crossing interval and whether the sampled values ​​before and after the zero-crossing point can be used for calculation.

[0048] S3. When a zero-crossing interval exists, calculate the difference between adjacent points and determine whether the difference between adjacent points satisfies a preset similarity condition. If the preset similarity condition is met, the zero-crossing interval is determined to be valid based on the squeeze theorem, and linear interpolation is used to calculate the precise zero-crossing time Tn. Further, in S3, when a zero-crossing interval exists, calculating the difference between adjacent points and determining whether the difference between adjacent points satisfies the preset similarity condition includes:

[0049] 1) Calculate the difference between adjacent points:

[0050] DiffY(1)=y(k)-y(k-1)

[0051] DiffY(2)=y(k-1)-y(k-2)

[0052] DiffY(3)=y(k-2)-y(k-3)

[0053] 2) Determine whether DiffY(1), DiffY(2), and DiffY(3) satisfy the following preset similarity conditions:

[0054] DiffY(1)≈DiffY(2)≈DiffY(3).

[0055] In practice, since the data acquisition device samples at equal intervals, the sampling interval does not change with time. The difference in sampling interval is represented by DiffX, meaning DiffX is a constant. If the values ​​of DiffY(1), DiffY(2), and DiffY(3) are nearly identical, then the sine function can be considered to be replaced by a linear function.

[0056] Furthermore, in S3, when a preset similarity condition is met, the zero-crossing interval is determined to be valid based on the squeeze theorem, including:

[0057] When the preset similarity condition is met, based on the squeeze theorem:

[0058]

[0059] If we replace the sine function with a linear function, x approaches 0, sinx also approaches 0, and y(k-1) and y(k) also approach 0. Then the interval [k-1,k] is a valid zero-crossing interval.

[0060] Furthermore, the zero-crossing time Tn is calculated using the linear interpolation method described below.

[0061] An interpolation algorithm is used to calculate the precise zero-crossing time:

[0062] T n =k-2+[-y(k-1)] / [y(k)-y(k-1)]

[0063] S4. Calculate the system frequency based on the current zero-crossing time Tn and the previous zero-crossing time T0:

[0064]

[0065] Furthermore, the previous zero-crossing time T0 is a confirmed valid zero-crossing time, and Tn > T0.

[0066] The present invention also provides a power system frequency measurement device based on the squeeze theorem, which is used to implement the above-mentioned power system frequency measurement method based on the squeeze theorem, including:

[0067] The data acquisition module is used to sample the system voltage signal in real time at a fixed sampling frequency fs; the data acquisition module is...

[0068] The data processing module defines the current sampling point as y(k), the previous sampling point as y(k-1), the two previous sampling points as y(k-2), and so on. Based on the sign of the sampling value, it determines whether a zero-crossing interval exists. When a zero-crossing interval exists, it calculates the difference between adjacent points and determines whether the difference satisfies a preset similarity condition. If the preset similarity condition is met, it determines that the zero-crossing interval is valid based on the squeeze theorem and uses linear interpolation to calculate the precise zero-crossing time Tn. Based on the current zero-crossing time Tn and the previous zero-crossing time T0, it calculates the system frequency.

[0069] The enhancement criteria for zero-crossing are mainly to avoid the influence of electromagnetic interference, communication errors and system harmonics on the frequency algorithm. The consequences mainly include misjudgment of zero-crossing, insufficient calculation accuracy, and improper selection of zero-crossing.

[0070] See attached for cases of misjudgment at zero point. Figure 2 Appendix Figure 2 This is because the measurement equipment has insufficient anti-interference capability, resulting in glitch sampling and a pseudo-zero-crossing interval. In this case, if this patent is used, the calculated DiffY(1), DiffY(2), and DiffY(3) values ​​of the four samples in this pseudo-zero-crossing interval have large differences, which does not conform to the squeeze theorem. Therefore, this interval is not considered a true zero-crossing interval.

[0071] Figure 3 and Figure 4 This reflects situations where the calculation accuracy is insufficient. The former represents glitches caused by electromagnetic interference, while the latter is the key area where communication errors occur. In both cases, although the zero-crossing interval is not problematic, the zero-crossing time calculated based on the interpolation of the sampled values ​​has a deviation, which will eventually lead to a decrease in frequency accuracy and have a negative impact on subsequent applications. Similarly, using this patent, the differences between DiffY(1), DiffY(2), and DiffY(3) obtained from the zero-crossing interval sampled values ​​are also large, which does not conform to the squeeze theorem.

[0072] Appendix Figure 5 This is due to the superposition of the 3rd and 5th harmonics in the system. Although the zero-crossing interval and zero-crossing time that appear in this case are indeed present in the system, since the frequency specifically refers to the fundamental frequency, the frequency calculated based on the zero-crossing time is also very large because of the superimposed harmonic signal. In this case, the identified zero-crossing interval, being a composite signal of the fundamental frequency and harmonics, does not meet the squeeze theorem and can also be discarded.

[0073] When judging the similarity between DiffY(1), DiffY(2), and DiffY(3), the judgment criteria or basis can be determined as needed based on factors such as system characteristics, sensing links, and application requirements.

[0074] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0075] Although embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention without departing from the principles and spirit of the invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A power system frequency measurement method based on the squeeze theorem, characterized in that, Includes the following steps: S1, using a fixed sampling frequency fs Real-time sampling of system voltage signals; S2. Define the sampled value corresponding to the current sampling point. y(k) The previous sample value is y(k-1) The first two sample values ​​are y (k-2) And so on; determine whether there is a zero-crossing interval based on the sign of the sampled values; S3. When a zero-crossing interval exists, calculate the difference between adjacent points and determine whether the difference between adjacent points meets the preset similarity condition. If the preset similarity condition is met, the zero-crossing interval is determined to be valid based on the squeeze theorem, and linear interpolation is used to calculate the precise zero-crossing time. Tn ; In S3, when a zero-crossing interval exists, calculating the difference between adjacent points and determining whether the difference between adjacent points satisfies the preset similarity condition includes: 1) Calculate the difference between adjacent points: DiffY(1) = y(k) - y(k-1) ； DiffY(2) = y(k-1) - y(k-2) ； DiffY(3) = y(k-2) - y(k-3) ； 2) Judgment DiffY(1), DiffY(2), DiffY(3) Does it meet the following preset similarity conditions: DiffY(1) ≈DiffY(2)≈DiffY(3) ； When a preset similarity condition is met, the zero-crossing interval is determined to be valid based on the squeeze theorem, including: When the preset similarity condition is met, based on the squeeze theorem: ； Replace the sine function with a linear function. x Approaching 0, sinx It also approaches 0. y(k-1), y(k) If the zero-crossing interval also tends to 0, then the interval [k-1,k] is a valid zero-crossing interval; S4. Based on the current zero-crossing time Tn Compared to the previous zero crossing moment T0， Calculate the system frequency; 。 2. The power system frequency measurement method based on the squeeze theorem according to claim 1, characterized in that, In S2, determining whether a zero-crossing interval exists based on the sign of the sampled values ​​includes: when y(k-3), y(k-2)≤0 and y(k-1), y(k)≥0 When the zero-crossing interval exists, it is determined that there is a zero-crossing interval.

3. The power system frequency measurement method based on the squeeze theorem according to claim 1, characterized in that, The zero-crossing time is calculated using the linear interpolation method described below. Tn ; An interpolation algorithm is used to calculate the precise zero-crossing time: T n = k-2 + [-y(k-1)] / [y(k)-y(k-1)].

4. The power system frequency measurement method based on the squeeze theorem according to claim 1, characterized in that, The previous zero-crossing moment T0， For confirmed valid zero-crossing moments, and Tn>T0.

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