Metering method and system for high-accuracy dynamic electric energy

Abstract

The invention provides a metering method and system for high-accuracy dynamic electric energy. The metering method comprises the following steps: carrying out synchronization processing on sampling signals of voltage and current; dynamically adjusting the window length of each sampling signal according to the active power stability of the sampling signals based on an adaptive non-overlapping window algorithm, and calculating the real-time power of the sampling signals; and according to the accuracy grade of the electric energy meter and the fluctuation of the real-time power of the sampling signal, adaptively adjusting a power threshold, and realizing accurate metering of dynamic electric energy. The accuracy of electric energy metering is improved.

Description

Technical Field

[0001] The present invention relates to the technical fields of smart grid and electric energy metering, and particularly relates to a metering method and system for high-accuracy dynamic electric energy. Background Art

[0002] In recent years, with the large-scale grid connection of renewable energy sources such as wind energy and solar energy, and the rapid development of new types of loads such as electric vehicles and energy storage devices, the operating environment of the power system has shown significant dynamic and nonlinear characteristics. The intermittency and volatility of new energy power generation, as well as the wide access of power electronic devices, have led to an increase in the harmonic content of voltage and current signals in the power grid and frequent frequency offset phenomena. The accuracy of traditional electric energy metering algorithms under dynamic operating conditions faces severe challenges.

[0003] In traditional electric energy metering technologies, the sliding window algorithm and the non-overlapping algorithm are two mainstream methods. The sliding window algorithm calculates power by sliding a window of fixed length point by point. Although it can ensure the metering accuracy under steady-state signals, its fixed window design is difficult to adapt to the rapid changes of dynamic signals, resulting in principle errors in scenarios of power mutation or high-frequency harmonics. The non-overlapping algorithm reduces the calculation amount through a jumping window, but it is easy to ignore signal mutation information at the window boundary and has insufficient adaptability to non-stationary signals. In addition, existing algorithms generally rely on a fixed active power threshold for electric energy accumulation judgment. The static setting of the threshold is easily affected by noise interference or signal fluctuations, causing the accumulation of metering errors, especially in the low-power section, which may lead to creeping or missing metering problems.

[0004] In addition, in actual operation, due to factors such as power grid frequency fluctuations and sampling clock deviations, the sampling process of the electric energy meter often cannot be completely synchronized with the power grid signal, resulting in non-synchronous sampling errors. To meet the development needs of the new power system, there is an urgent need for a new electric energy metering algorithm that can comprehensively consider factors such as steady-state performance, dynamic response, threshold influence, and non-synchronous sampling. Summary of the Invention

[0005] In view of the above technical problems, the present invention provides a metering method and system for high-accuracy dynamic electric energy. The method includes: Synchronizing the sampling signals of voltage and current; Based on the adaptive non-overlapping window algorithm, dynamically adjusting the window length of each sampling signal according to the active power stability of the sampling signal, and calculating the real-time power of the sampling signal; Adaptive adjusting the power threshold according to the accuracy level of the electric energy meter and the fluctuation of the real-time power of the sampling signal to achieve accurate metering of dynamic electric energy.

[0006] Further, synchronizing the sampling signals of voltage and current includes: Adopt the second - order Lagrange interpolation algorithm to convert the frequency of the sampled signal into a signal sequence that is a multiple of the preset fundamental frequency and synchronized with the power grid signal. The specific expression for the synchronization process is as follows: Let the original sampling sequence be , and the corresponding time points be , the synchronization time is t,

[0007] Then the synchronized signal value x(t) is:

[0008] Among them, the value of n is:

[0009] is the sampling frequency of the signal.

[0010] Furthermore, based on the adaptive non - overlapping window algorithm, dynamically adjust the window length of each sampling signal according to the active power stability of the sampling signal, including: Keep no overlap between the sampling signal windows. Let the window length of the sampling signal be L(n). When the active power of the sampling signal fluctuates, adaptively shorten the window length L(n); When the active power of the sampling signal is relatively stable, adaptively extend the window length L(n); The expression for the adaptive adjustment of the window length L(n) is:

[0011] Among them, 256 is the number of sampling points within the fundamental wave period, is the mapping function of the window length L(n).

[0012] Furthermore, the mapping function of the window length L(n) has the following expression:

[0013] P is the average power of each window. Among them, K is related to the maximum window length, and the relationship between K and the maximum window length is as follows:

[0014] Among them, 256 is the number of sampling points within the fundamental wave period, is the maximum window length.

[0015] Furthermore, adaptively adjust the power threshold according to the accuracy level of the electricity meter and the fluctuation of the real - time power of the sampling signal, including: Determine the accuracy class of the electricity meter and determine the maximum threshold of the starting current ; When the dynamic change frequency of the real-time power of the sampling signal is greater than the preset fluctuation threshold, the power threshold is reduced; When the dynamic change frequency of the real-time power of the sampling signal is less than the preset fluctuation threshold, the power threshold is increased; Power threshold The expression of is:

[0016] Among them, is the variance of the real-time power signal output by the system, is the expected value of the real-time power signal output by the system.

[0017] The present invention also provides a metering system for high-accuracy dynamic electric energy, including: A synchronization processing module for synchronizing the sampling signals of voltage and current; An adaptive non-overlapping window processing module for dynamically adjusting the window length of each sampling signal based on the adaptive non-overlapping window algorithm according to the active power stability of the sampling signal and calculating the real-time power of the sampling signal; A power adaptive adjustment module for adaptively adjusting the power threshold according to the accuracy class of the electricity meter and the fluctuation of the real-time power of the sampling signal to achieve accurate measurement of dynamic electric energy.

[0018] Further, the synchronization processing module includes: A signal sequence synchronization sub-module for converting the frequency of the sampling signal into a signal sequence that is a multiple of the preset fundamental frequency and synchronized with the power grid signal by using the second-order Lagrange interpolation algorithm. The specific expression of the synchronization processing is: Let the original sampling sequence be , and the corresponding time point be , and the synchronization time be t,

[0019] Then the synchronized signal value x(t) is:

[0020] Among them, the value of n is:

[0021] is the sampling frequency of the signal.

[0022] Further, the adaptive non-overlapping window processing module includes: The first window length adaptive adjustment sub-module is used to keep no overlap between sampling signal windows. Let the window length of the sampling signal be L(n). When the active power of the sampling signal fluctuates, it adaptively shortens the window length L(n). The second window length adaptive adjustment sub-module is used to adaptively extend the window length L(n) when the active power of the sampling signal is relatively stable. The adaptive adjustment expression of the window length L(n) is:

[0023] where 256 is the number of sampling points within the fundamental wave period. is the mapping function of the window length L(n).

[0024] Furthermore, the mapping function of the window length L(n) has the following expression:

[0025] P is the average power of each window. Among them, K is related to the maximum window length, and the relationship between K and the maximum window length is as follows:

[0026] where 256 is the number of sampling points within the fundamental wave period. is the maximum window length.

[0027] Furthermore, the power adaptive adjustment module includes: The level and maximum threshold determination sub-module is used to determine the accuracy level of the electric energy meter and determine the maximum threshold of the starting current ; The first power threshold adjustment sub-module is used to reduce the power threshold when the dynamic change frequency of the real-time power of the sampling signal is greater than the preset fluctuation threshold; The first power threshold adjustment sub-module is used to increase the power threshold when the dynamic change frequency of the real-time power of the sampling signal is less than the preset fluctuation threshold; The power threshold has the following expression:

[0028] where is the variance of the real-time power signal output by the system, is the expected value of the real-time power signal output by the system.

[0029] A method and system for measuring high-accuracy dynamic electric energy provided by the present invention synchronize the sampling signals to reduce the measurement error caused by asynchronous sampling; on the basis of maintaining no overlap between windows, the improved adaptive non-overlapping window algorithm dynamically adjusts the length of each window according to the signal characteristics, can capture signal changes more accurately, and reduce dynamic errors; adjust the threshold according to the fluctuation of the real-time power of the power grid to achieve adaptive threshold adjustment, and solve the measurement error problem caused by the active power threshold. The accuracy of electric energy measurement is improved. Description of the Drawings

[0030] Figure 1 is a schematic flowchart of a method for measuring high-accuracy dynamic electric energy provided by an embodiment of the present invention; Figure 2 is a block diagram for implementing the measurement of a high-accuracy electric energy meter provided by an embodiment of the present invention; Figure 3 is a schematic structural diagram of a system for measuring high-accuracy dynamic electric energy provided by an embodiment of the present invention. Detailed Embodiments

[0031] Many specific details are set forth in the following description in order to provide a thorough understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0032] Embodiment 1 The present invention provides a method for improving the measurement of dynamic electric energy, which comprehensively considers various technical problems faced by electric energy measurement in the new power system environment, and makes systematic improvements and innovations on the basis of traditional measurement algorithms. The method provided by the present invention will be described in detail below with reference to the accompanying drawings. As Figure 1 shown, it specifically includes the following steps: Step S101, synchronize the sampling signals of voltage and current.

[0033] In order to reduce the measurement error caused by asynchronous sampling, the present invention first synchronizes the sampling signals of voltage and current. Specifically, the fundamental frequency f is obtained by zero-crossing detection of the voltage signal over a long period of time. Then, the second-order Lagrange interpolation algorithm is used to convert the frequency of the sampling signal into a signal sequence that is a multiple of the preset fundamental frequency and synchronized with the power grid signal. The multiple of the preset fundamental frequency can specifically take a value of 256 times.

[0034] The second-order Lagrange interpolation algorithm is a classic algorithm based on polynomial interpolation, which has the advantages of high accuracy and stable calculation, and can effectively improve the synchronization of signals. The expression of the synchronization process is specifically: Let the original sampling sequence be , and the corresponding time points be , the synchronization time is t,

[0035] Then the synchronized signal value x(t) is:[[]]

[0036] where the value of n is:[[]]

[0037] is the sampling frequency of the signal.[[]]

[0038] Step S102, based on the adaptive non-overlapping window algorithm, dynamically adjust the window length of each sampling signal according to the active power stability of the sampling signal, and calculate the real-time power of the sampling signal.[[]]

[0039] In the power system, power calculation usually uses the sliding window method for real-time processing. Although the traditional sliding window method has a simple process, it has a principle error for high-frequency signals when considering starting and creeping, and the calculation complexity is relatively high. The design of a fixed window length is also difficult to adapt to the characteristic changes of dynamic signals. Although the non-overlapping algorithm reduces the calculation amount through jump windows, it is easy to ignore signal mutation information at the window boundary, has poor adaptability to non-stationary signals, and the window length lacks a dynamic adjustment mechanism and cannot be flexibly changed according to the actual changes of the signal, resulting in difficulty in accurately calculating power in the complex and changeable power grid signal environment. Therefore, the present invention proposes an improved adaptive non-overlapping window algorithm, the core of which is to combine an adaptive variable window length with a non-overlapping window. On the basis of keeping no overlap between windows, dynamically adjust the length of each window according to the signal characteristics. Specifically, keep no overlap between the sampling signal windows, set the window length of the sampling signal as L(n), when the active power of the sampling signal fluctuates, adaptively shorten the window length L(n); when the active power of the sampling signal is relatively stable, adaptively extend the window length L(n); the adaptive adjustment expression of the window length L(n) is:[[]]

[0040] where 256 is the number of sampling points within the fundamental wave period, and the variance and second moment of the active power are used to adjust the window length. When the power grid signal is stable, the variance of the active power is close to 0, and the maximum window length is taken; when the power grid signal fluctuates the most, the variance of the active power is close to the second moment, and the minimum window length is taken as the number of sampling points within a single fundamental wave period.[[]]

[0041] The mapping function of the window length L(n)[[]] The expression is:

[0042] P is the average power of each window, where K is related to the maximum window length, and the relationship between K and the maximum window length is as follows:

[0043] Among them, 256 is the number of sampling points within the fundamental wave period, is the maximum window length.

[0044] Step S103: According to the accuracy level of the watt-hour meter and the fluctuation of the real-time power of the sampling signal, adaptively adjust the power threshold to achieve accurate measurement of dynamic electric energy.

[0045] Aiming at the problem that the fixed power threshold in the traditional algorithm may introduce errors, the present invention proposes an adaptive threshold judgment method. First, determine the accuracy level of the watt-hour meter and the starting current to determine the maximum threshold ; then adjust the threshold according to the fluctuation of the real-time power of the power grid to achieve adaptive power threshold adjustment. When the dynamic change frequency of the real-time power of the sampling signal is greater than the preset fluctuation threshold, the power threshold is reduced; when the dynamic change frequency of the real-time power of the sampling signal is less than the preset fluctuation threshold, the power threshold is increased; Power threshold The expression is:

[0046] Among them, is the variance of the real-time power signal output by the system, is the expected value of the real-time power signal output by the system, or the average value of the real-time power signal output by the system.

[0047] Generally, when the real-time power changes frequently, the threshold is reduced to avoid partial loss of electric energy measurement caused by the threshold. When the real-time power is relatively stable, the threshold is increased to minimize the error caused by the inclusion of thermal noise in the electric energy measurement as much as possible.

[0048] According to the above power threshold It can be seen that when the dynamic change frequency of the real-time power of the sampling signal is less than the preset fluctuation threshold, that is, when the real-time power is stable, the standard deviation of the power signal is close to 0, and the power threshold is close to the maximum value; When the dynamic change frequency of the real-time power of the sampling signal is greater than the preset fluctuation threshold, that is, when the real-time power fluctuates violently, the standard deviation of the real-time power is close to the expected value, and at this time the threshold is close to 0 to avoid losing the electric energy that needs to be measured.

[0049] Embodiment 2 Applying a method for measuring high-accuracy dynamic electric energy provided by the present invention, high-accuracy electric energy meter measurement is realized, such as Figure 2 shown. First, the fundamental frequency f of the sampled voltage signal is obtained by using the zero-crossing detection method. Then, an interpolation algorithm is adopted to synchronize the sampled voltage signal. Based on the adaptive non-overlapping window algorithm, according to the active power stability of the sampled signal, the window length of each sampled signal is dynamically adjusted, and the real-time power of the sampled signal is calculated. When the real-time power changes frequently, the threshold is reduced to avoid the loss of partial electric energy measurement caused by the threshold. When the real-time power is relatively stable, the threshold is increased to minimize the error caused by the inclusion of thermal noise in the electric energy measurement. Finally, the dynamic electric energy is calculated by processing the above sampled signal.

[0050] Embodiment 3 Based on the same inventive concept, the present invention also provides a metering system 300 for high-accuracy dynamic electric energy, such as Figure 3 shown, including: A synchronization processing module 310 for synchronizing the sampled signals of voltage and current; An adaptive non-overlapping window processing module 320 for dynamically adjusting the window length of each sampled signal and calculating the real-time power of the sampled signal based on the adaptive non-overlapping window algorithm according to the active power stability of the sampled signal; A power adaptive adjustment module 330 for adaptively adjusting the power threshold according to the accuracy level of the electric energy meter and the fluctuation of the real-time power of the sampled signal to achieve accurate measurement of dynamic electric energy.

[0051] Furthermore, the synchronization processing module includes: A signal sequence synchronization sub-module for converting the frequency of the sampled signal into a signal sequence that is a multiple of the preset fundamental frequency and synchronized with the power grid signal by using the second-order Lagrange interpolation algorithm. The specific expression of the synchronization processing is: Let the original sampled sequence be , the corresponding time point be , the synchronization moment be t,

[0052] Then the synchronized signal value x(t) is:

[0053] where the value of n is:

[0054] is the sampling frequency of the signal.

[0055] Furthermore, the adaptive non-overlapping window processing module includes: The first window length adaptive adjustment sub-module is used to keep the sampling signal windows non-overlapping. Let the window length of the sampling signal be L(n). When the active power of the sampling signal fluctuates, the window length L(n) is adaptively shortened; The second window length adaptive adjustment sub-module is used to adaptively extend the window length L(n) when the active power of the sampling signal is relatively stable; The adaptive adjustment expression of the window length L(n) is:

[0056] where 256 is the number of sampling points within the fundamental wave period, is the mapping function of the window length L(n).

[0057] Furthermore, the mapping function of the window length L(n) has the following expression:

[0058] P is the average power of each window. Here, K is related to the maximum window length, and the relationship between K and the maximum window length is as follows:

[0059] where 256 is the number of sampling points within the fundamental wave period, is the maximum window length.

[0060] Furthermore, the power adaptive adjustment module includes: The level and maximum threshold determination sub-module is used to determine the accuracy level of the electricity meter and determine the maximum threshold of the starting current ; The first power threshold adjustment sub-module is used to reduce the power threshold when the dynamic change frequency of the real-time power of the sampling signal is greater than the preset fluctuation threshold; The first power threshold adjustment sub-module is used to increase the power threshold when the dynamic change frequency of the real-time power of the sampling signal is less than the preset fluctuation threshold; The power threshold has the following expression:

[0061] where, is the variance of the real-time power signal output by the system, is the expected value of the real-time power signal output by the system, or the average value of the real-time power signal output by the system.

[0062] A metering method and system for high-accuracy dynamic electric energy provided by the present invention perform synchronization processing on sampling signals to reduce metering errors caused by asynchronous sampling; on the basis of keeping no overlap between windows through an improved adaptive non-overlapping window algorithm, the length of each window is dynamically adjusted according to signal characteristics, which can capture signal changes more accurately and reduce dynamic errors; the threshold is adjusted according to the fluctuation of the real-time power of the power grid to achieve adaptive threshold adjustment and solve the metering error problem caused by the active power threshold.

[0063] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0064] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0065] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including an instruction device, and the instruction device realizes the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0066] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0067] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that the specific implementation manners of the present invention can still be modified or equivalently replaced. Any modification or equivalent replacement without departing from the spirit and scope of the present invention shall be covered by the scope of the claims of the present invention.

Claims

1. A method for measuring dynamic electric energy with high accuracy, characterized in that: include: Synchronize the sampling signals of voltage and current; Based on an adaptive non-overlapping window algorithm, dynamically adjusting the window length of each sampling signal according to the active power stability of the sampling signal, and calculating the real-time power of the sampling signal; According to the accuracy level of the electric energy meter and the fluctuation of the real-time power of the sampling signal, the power threshold is adaptively adjusted to achieve accurate measurement of dynamic electric energy.

2. The method according to claim 1, characterized in that The sampling signals of voltage and current are processed synchronously, including: The second-order Lagrange interpolation algorithm is used to convert the frequency of the sampling signal into a signal sequence that is a multiple of the preset fundamental frequency and synchronized with the power grid signal. The specific expression of the synchronization processing is: Assume the original sampling sequence is , the corresponding time point is , the synchronization time is t, Then the synchronized signal value x(t) is: The value of n is: is the sampling frequency of the signal.

3. The method according to claim 1, characterized in that Based on an adaptive non-overlapping window algorithm, dynamically adjusting the window length of each sampling signal according to the active power stability of the sampling signal includes: Keep the sampling signal windows non-overlapping, assume that the window length of the sampling signal is L(n), and when the active power of the sampling signal fluctuates, adaptively shorten the window length L(n); When the active power of the sampling signal is relatively stable, adaptively extending the window length L(n); The adaptive adjustment expression of the window length L(n) is: Among them, 256 is the number of sampling points in the fundamental wave period. is the mapping function of the window length L(n).

4. The method according to claim 3, characterized in that The mapping function of the window length L(n) The expression is: P is the average power of each window, where K is related to the maximum window length. The relationship between K and the maximum window length is as follows: Among them, 256 is the number of sampling points in the fundamental wave period. is the maximum window length.

5. The method according to claim 1, characterized in that: According to the accuracy level of the electric energy meter and the fluctuation of the real-time power of the sampling signal, the power threshold is adaptively adjusted, including: Determine the accuracy level of the energy meter and the maximum threshold value for the starting current ; When the real-time power dynamic change frequency of the sampling signal is greater than a preset fluctuation threshold, the power threshold is reduced; When the real-time power dynamic change frequency of the sampling signal is less than the preset fluctuation threshold, the power threshold is increased; Power threshold The expression is: in, is the variance of the real-time power signal output by the system, It is the expected value of the real-time power signal output by the system.

6. A high-accuracy dynamic electric energy metering system, characterized in that: include: A synchronization processing module is used to perform synchronization processing on the sampling signals of voltage and current; An adaptive non-overlapping window processing module, used for dynamically adjusting the window length of each sampling signal according to the active power stability of the sampling signal based on an adaptive non-overlapping window algorithm, and calculating the real-time power of the sampling signal; The power adaptive adjustment module is used to adaptively adjust the power threshold according to the accuracy level of the electric energy meter and the fluctuation of the real-time power of the sampling signal to achieve accurate measurement of dynamic electric energy.

7. The system according to claim 6, characterized in that Synchronization processing module, including: The signal sequence synchronization submodule is used to convert the frequency of the sampling signal into a signal sequence that is a multiple of the preset fundamental frequency and synchronized with the power grid signal by using a second-order Lagrange interpolation algorithm. The specific expression of the synchronization processing is: Assume the original sampling sequence is , the corresponding time point is , the synchronization time is t, Then the synchronized signal value x(t) is: The value of n is: is the sampling frequency of the signal.

8. The system according to claim 6, characterized in that Adaptive non-overlapping window processing module, including: The first window length adaptive adjustment submodule is used to keep the sampling signal windows non-overlapping, assuming that the window length of the sampling signal is L(n), and when the active power of the sampling signal fluctuates, the window length L(n) is adaptively shortened; A second window length adaptive adjustment submodule, used for adaptively extending the window length L(n) when the active power of the sampling signal is relatively stable; The adaptive adjustment expression of the window length L(n) is: Among them, 256 is the number of sampling points in the fundamental wave period. is the mapping function of the window length L(n).

9. The system according to claim 8, characterized in that The mapping function of the window length L(n) The expression is: P is the average power of each window, where K is related to the maximum window length. The relationship between K and the maximum window length is as follows: Among them, 256 is the number of sampling points in the fundamental wave period. is the maximum window length.

10. The system according to claim 6, characterized in that Power adaptive adjustment module, including: The level and maximum threshold determination submodule is used to determine the accuracy level of the electric energy meter and the maximum threshold of the starting current ; A first power threshold adjustment submodule, used to reduce the power threshold when the real-time power dynamic change frequency of the sampling signal is greater than a preset fluctuation threshold; A first power threshold adjustment submodule, used to increase the power threshold when the real-time power dynamic change frequency of the sampling signal is less than a preset fluctuation threshold; Power threshold The expression is: in, is the variance of the real-time power signal output by the system, It is the expected value of the real-time power signal output by the system.

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