Multi-characteristic electric energy metering method, device, terminal and storage medium

Abstract

The present invention relates to the field of electric power metering technology, and in particular to a method, device, terminal and storage medium for electric energy metering with multiple characteristic quantities. The method of the present invention first obtains the waveform at the feeder end. Then, the waveform is sampled to obtain a waveform data set. Next, the waveform is Fourier transformed based on the waveform data set to obtain a fundamental wave and multiple higher harmonics. Finally, multiple characteristic quantity operations are performed on the fundamental wave and the multiple higher harmonics to obtain metering data of multiple characteristic quantities. The embodiment of the present invention can determine a reasonable sampling rate through the waveform, which can ensure the accuracy of each harmonic after the transformation and reduce the complexity of sampling and calculation, thereby achieving a balance between the two. After the harmonics obtained by transformation, metering data such as harmonic active power, harmonic reactive power, power factor, harmonic factor, main harmonics, etc. can be calculated based on the harmonics, and the accuracy of the metering data is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power metering, and in particular to a method, device, terminal and storage medium for measuring electric energy with multiple characteristic quantities. Background Art

[0002] Electricity is an essential energy commodity in modern production and life. Its production, distribution, and use rely on a system consisting of power plants, power suppliers, and users. Therefore, the accuracy and rationality of electricity metering directly impact the economic benefits and fairness of transactions among all three parties involved. With the increasing popularity of wind and solar power generation, distributed power sources are distributed throughout transmission lines, bringing greater complexity and diversity to electricity metering.

[0003] Currently, existing electricity meters, both domestically and internationally, lack effective measurement methods for multiple characteristic quantities and various power supply modes, and are particularly incapable of measuring energy from transient distorted signals. However, frequent motor startups, load switching, and fluctuations in distributed generation in power supply applications all generate enormous transient power that electricity meters are unable to measure, resulting in significant losses for the power sector.

[0004] Therefore, it is of great theoretical and practical significance to conduct in-depth research on the impact of various characteristics of renewable energy access to the power grid and how to achieve accurate and reasonable electricity metering in this context.

[0005] Based on this, it is necessary to develop and design a multi-characteristic electric energy metering method. Summary of the Invention

[0006] The embodiments of the present invention provide a multi-characteristic electric energy metering method, device, terminal and storage medium, which are used to solve the problem in the prior art of lacking means for accurately metering multi-characteristic quantities of a power grid.

[0007] In a first aspect, an embodiment of the present invention provides a multi-characteristic electric energy metering method, comprising: obtaining a waveform at a feeder end, wherein the feeder is used to connect to a load and / or a power supply, and the waveform is used to represent the waveform of electric energy transmitted by the feeder;

[0008] Sampling the waveform to obtain a waveform data set;

[0009] Performing Fourier transform on the waveform based on the waveform data set to obtain a fundamental wave and a plurality of higher harmonics;

[0010] Multiple characteristic quantity operations are performed on the fundamental wave and the multiple higher harmonics to obtain metering data of the multiple characteristic quantities, wherein the metering data represents attribute characteristics of electric energy.

[0011] In one possible implementation, the sampling rate is determined based on the waveform, including:

[0012] Acquire a plurality of sample waveforms, wherein the sample waveforms correspond to a target capacity level, and the target capacity level is determined based on the capacity of input power and / or the capacity of output power;

[0013] For each of the plurality of sample waveforms, a sampling rate corresponding to a target capacity level is obtained by performing the following steps:

[0014] Sampling the sample waveform at a sample sampling rate to obtain a sample waveform data set;

[0015] Performing Fourier transform on the sample waveform based on the sample waveform data set to obtain a sample fundamental wave and a plurality of sample higher harmonics;

[0016] determining a deviation rate after transformation according to the sample waveform, the sample fundamental wave, and the plurality of sample higher harmonics;

[0017] If the deviation rate is lower than a threshold, a plurality of harmonics having a harmonic rate higher than the threshold are screened out from the plurality of sample higher harmonics as typical harmonics, wherein the harmonic rate is a ratio of the amplitude of the sample higher harmonic to the amplitude of the sample fundamental wave;

[0018] A target sampling rate is determined according to the frequency of the highest-order harmonic among the typical harmonics, and the target sampling rate is used as the sampling rate of the sample waveform corresponding to the target capacity level.

[0019] In one possible implementation, determining the deviation rate after transformation based on the sample waveform, the sample fundamental wave, and the plurality of sample higher harmonics includes:

[0020] Sampling the sample fundamental wave and the plurality of sample higher harmonics respectively according to the sample sampling rate to obtain a plurality of transformation sets, wherein the plurality of transformation sets correspond to a plurality of sampling points, and the transformation sets include sampling values of the fundamental wave and sampling values of the plurality of sample higher harmonics;

[0021] For each of the multiple transformation sets, the following steps are performed to obtain deviation rates of multiple sampling points:

[0022] Accumulating the sampling values of the fundamental wave and the sampling values of the plurality of higher harmonic samples in the transformation set to obtain an accumulated sum;

[0023] Finding the waveform data value in the sample waveform data set according to the sampling position corresponding to the transformation set;

[0024] Calculating a deviation rate between the accumulated sum and the waveform data value as a deviation rate of a sampling point;

[0025] An average value of the deviation rates of the plurality of sampling points is calculated as the transformed deviation rate.

[0026] In one possible implementation, the sampling adopts a dynamic sampling rate, and the sampling of the waveform to obtain the waveform data set includes:

[0027] Obtain a time pane, wherein the time pane includes a time period;

[0028] Extracting a section of the waveform from the waveform according to the time window;

[0029] Flipping the waveform to obtain a flipped waveform, wherein the flipping is to flip the negative half cycle of the waveform to the positive half cycle in an amplitude mirroring manner;

[0030] Integrating the inverted waveform to obtain an effective value of the waveform;

[0031] According to the effective value, a dynamic sampling rate is selected, the waveform is sampled, and a waveform data set is obtained, wherein the dynamic sampling rate is obtained based on a sampling rate set, and the sampling rate set includes sampling rates of multiple target capacity files, and the sampling rates of the target capacity files correspond to the target capacity files.

[0032] In one possible implementation, performing Fourier transform on the waveform based on the waveform data set to obtain a fundamental wave and a plurality of higher harmonics includes:

[0033] Obtaining a sampling rate corresponding to the waveform data set;

[0034] Determining a conversion target frequency according to the sampling rate, wherein the conversion target frequency is the frequency of the highest harmonic among the multiple high-order harmonics obtained by Fourier transform;

[0035] The fundamental wave and multiple higher harmonics are calculated based on the conversion target frequency, the waveform data set, and the first formula, where the first formula is:

[0036]

[0037] Where X[k] is the kth wave after transformation, x[n] is the nth element in the waveform dataset, and N is the total number of data in the waveform dataset.

[0038] In one possible implementation, the metering data of the multiple feature quantities includes: active power corresponding to multiple harmonics and reactive power corresponding to multiple harmonics, the fundamental wave and the multiple higher harmonics include the fundamental wave of voltage, multiple higher harmonics of voltage, the fundamental wave of current, and the higher harmonics of current, and performing multiple feature quantity operations on the fundamental wave and the multiple higher harmonics to obtain the metering data of the multiple feature quantities includes:

[0039] Pairing the fundamental wave of voltage, multiple higher harmonics of voltage, the fundamental wave of current, and higher harmonics of current according to the frequencies of the fundamental wave and higher harmonics to generate multiple voltage-current pairs;

[0040] Performing a dot product operation and a cross product operation on the multiple voltage-current pairs to obtain active power of multiple harmonics and reactive power of multiple harmonics;

[0041] The active powers of the multiple harmonics and the reactive powers of the multiple harmonics are accumulated respectively to obtain a total active power and a total reactive power.

[0042] In one possible implementation, the metering data of the multiple feature quantities includes: power factors corresponding to multiple harmonics, the fundamental wave and the multiple higher harmonics include the fundamental wave of voltage, multiple higher harmonics of voltage, the fundamental wave of current, and the higher harmonics of current, and performing multiple feature quantity operations on the fundamental wave and the multiple higher harmonics to obtain the metering data of the multiple feature quantities includes:

[0043] Pairing the fundamental wave of voltage, multiple higher harmonics of voltage, the fundamental wave of current, and higher harmonics of current according to the frequencies of the fundamental wave and higher harmonics to generate multiple voltage-current pairs;

[0044] The power factors of the plurality of harmonics are determined based on the plurality of voltage-current pairs and a second formula, wherein the second formula is:

[0045]

[0046] Where cos k (θ) is the power factor of the kth harmonic, X u (k) is the kth harmonic of voltage, X i (k) is the kth harmonic of the current.

[0047] In a second aspect, an embodiment of the present invention provides a multi-characteristic electric energy metering device, comprising:

[0048] A waveform acquisition module, configured to acquire a waveform at a feeder end, wherein the feeder is configured to be connected to a load and / or a power source, and the waveform is configured to characterize a waveform of electric energy transmitted by the feeder;

[0049] A waveform sampling module, used to sample the waveform and obtain a waveform data set;

[0050] A Fourier transform module, configured to perform Fourier transform on the waveform based on the waveform data set to obtain a fundamental wave and a plurality of higher harmonics;

[0051] as well as,

[0052] The multi-feature quantity metering module is used to perform multiple feature quantity operations on the fundamental wave and the multiple higher harmonics to obtain metering data of the multiple feature quantities, wherein the metering data represents the attribute characteristics of the electric energy.

[0053] In a third aspect, an embodiment of the present invention provides a terminal comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, it implements the steps of the method described in the first aspect or any possible implementation of the first aspect.

[0054] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the method described in the first aspect or any possible implementation of the first aspect.

[0055] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0056] The embodiment of the present invention discloses a multi-feature quantity electric energy metering method, which first obtains the waveform at the feeder end, wherein the feeder is used to connect to a load and / or a power supply, and the waveform is used to characterize the waveform of the electric energy transmitted by the feeder. Then, the waveform is sampled to obtain a waveform data set. Next, the waveform is Fourier transformed based on the waveform data set to obtain a fundamental wave and multiple higher harmonics. Finally, multiple feature quantity operations are performed on the fundamental wave and the multiple higher harmonics to obtain metering data of multiple feature quantities, wherein the metering data characterizes the attribute characteristics of the electric energy. The embodiment of the present invention can determine a reasonable sampling rate through the waveform, which can ensure the accuracy of each harmonic after the transformation and reduce the complexity of sampling and calculation, achieving a balance between the two. After the harmonics obtained by transformation, metering data such as harmonic active power, harmonic reactive power, power factor, harmonic factor, main harmonics, etc. can be calculated based on the harmonics, and the accuracy of the metering data is guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0058] Figure 1 This is a flow chart of a multi-feature electric energy metering method provided by an embodiment of the present invention;

[0059] Figure 2 This is a schematic diagram of a power transmission line with a distributed power supply provided by an embodiment of the present invention;

[0060] Figure 3 It is a time domain diagram after waveform sampling and Fourier transformation provided by an embodiment of the present invention;

[0061] Figure 4 This is a functional block diagram of a multi-feature electric energy metering device provided by an embodiment of the present invention;

[0062] Figure 5 This is a functional block diagram of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0063] In the following description, specific details such as particular system structures and techniques are provided for purposes of illustration, not limitation, to facilitate a thorough understanding of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in alternative embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0064] In order to make the objectives, technical solutions and advantages of the present invention more clear, the following will be described through specific implementation methods in conjunction with the accompanying drawings.

[0065] The following is a detailed description of an embodiment of the present invention. This example is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiment.

[0066] Figure 1 This is a flow chart of a method for measuring electric energy with multiple characteristic quantities provided by an embodiment of the present invention.

[0067] like Figure 1 As shown, it shows a flowchart of the implementation method of the multi-feature quantity electric energy metering method provided by an embodiment of the present invention, which is detailed as follows:

[0068] In step 101, a waveform at a feeder end is obtained, wherein the feeder is used to connect to a load and / or a power source, and the waveform is used to represent a waveform of electric energy transmitted by the feeder.

[0069] For example, Figure 2 As shown, Figure 2 The schematic diagram of a power transmission line with distributed power supply provided by an embodiment of the present invention is shown. In the prior art, a power transmission network bus 201 has multiple feeders 202, and the feeders have both loads 203 and possibly distributed power supplies 204. There are many forms of distributed power supplies, such as wind power generation, solar power generation, etc.

[0070] In the above application scenarios, the loads and / or distributed power sources connected to the feeders make electric energy metering very complex. For example, in some feeders, during certain periods, they generate electricity connected to the bus 201, while during other periods, they consume electricity through the bus 201. For such scenarios, embodiments of the present invention achieve feeder electric energy metering by acquiring waveforms on the feeder 201. The waveforms may be voltage waveforms, current waveforms, or both, depending on the specific situation and are not limited here.

[0071] In step 102, the waveform is sampled to obtain a waveform data set.

[0072] In some implementations, the sampling rate is determined based on a waveform, including:

[0073] Acquire a plurality of sample waveforms, wherein the sample waveforms correspond to a target capacity level, and the target capacity level is determined based on the capacity of input power and / or the capacity of output power;

[0074] For each of the plurality of sample waveforms, a sampling rate corresponding to a target capacity level is obtained by performing the following steps:

[0075] Sampling the sample waveform at a sample sampling rate to obtain a sample waveform data set;

[0076] Performing Fourier transform on the sample waveform based on the sample waveform data set to obtain a sample fundamental wave and a plurality of sample higher harmonics;

[0077] determining a deviation rate after transformation according to the sample waveform, the sample fundamental wave, and the plurality of sample higher harmonics;

[0078] If the deviation rate is lower than a threshold, a plurality of harmonics having a harmonic rate higher than the threshold are screened out from the plurality of sample higher harmonics as typical harmonics, wherein the harmonic rate is a ratio of the amplitude of the sample higher harmonic to the amplitude of the sample fundamental wave;

[0079] A target sampling rate is determined according to the frequency of the highest-order harmonic among the typical harmonics, and the target sampling rate is used as the sampling rate of the sample waveform corresponding to the target capacity level.

[0080] In some embodiments, determining the deviation rate after transformation based on the sample waveform, the sample fundamental wave, and the plurality of sample higher harmonics includes:

[0081] Sampling the sample fundamental wave and the plurality of sample higher harmonics respectively according to the sample sampling rate to obtain a plurality of transformation sets, wherein the plurality of transformation sets correspond to a plurality of sampling points, and the transformation sets include sampling values of the fundamental wave and sampling values of the plurality of sample higher harmonics;

[0082] For each of the multiple transformation sets, the following steps are performed to obtain deviation rates of multiple sampling points:

[0083] Accumulating the sampling values of the fundamental wave and the sampling values of the plurality of higher harmonic samples in the transformation set to obtain an accumulated sum;

[0084] Finding the waveform data value in the sample waveform data set according to the sampling position corresponding to the transformation set;

[0085] Calculating a deviation rate between the accumulated sum and the waveform data value as a deviation rate of a sampling point;

[0086] An average value of the deviation rates of the plurality of sampling points is calculated as the transformed deviation rate.

[0087] In some implementations, the sampling uses a dynamic sampling rate, and step 102 includes:

[0088] Obtain a time pane, wherein the time pane includes a time period;

[0089] Extracting a section of the waveform from the waveform according to the time window;

[0090] Flipping the waveform to obtain a flipped waveform, wherein the flipping is to flip the negative half cycle of the waveform to the positive half cycle in an amplitude mirroring manner;

[0091] Integrating the inverted waveform to obtain an effective value of the waveform;

[0092] According to the effective value, a dynamic sampling rate is selected, the waveform is sampled, and a waveform data set is obtained, wherein the dynamic sampling rate is obtained based on a sampling rate set, and the sampling rate set includes sampling rates of multiple target capacity files, and the sampling rates of the target capacity files correspond to the target capacity files.

[0093] For example, for the transformation of the waveform, one transformation form used is discrete Fourier transform, that is, the waveform is sampled to obtain multiple sampling data points, and Fourier transform is performed based on the multiple data points to obtain the fundamental wave and higher harmonics of the waveform.

[0094] However, due to the uncertainty of electricity consumption and power generation in reality, the number of harmonics is uncertain. For example, for a certain feeder, when it obtains electricity from the busbar, when the electricity consumption is relatively high, the more harmonics it has, the more higher-order harmonics need to be decomposed. When the electricity consumption is relatively low, the electricity consumption is relatively stable, the fewer harmonics there are, and the fewer harmonics need to be decomposed.

[0095] Correspondingly, Shannon's theorem indicates that the sampling rate should be at least twice the target frequency being sampled. Once the highest harmonic order is determined, the sampling rate can also be determined. The sampling rate, along with the accuracy of the transformed data and data processing speed, is crucial for ensuring the accuracy of multi-feature measurement.

[0096] Based on the above derivation process, in an embodiment of the present invention, historical waveforms are sorted and a plurality of sample waveforms are collected, and the sample waveforms correspond to corresponding capacity levels.

[0097] Then, the sampling rate of each sample of the above-mentioned multiple sample waveforms is determined. First, sampling is performed according to the sample sampling rate. Usually, the sample sampling rate has a high frequency, which can provide sufficient conditions for the subsequent Fourier transform. Then, Fourier transform is performed on the sampled data to transform the fundamental wave and higher harmonics. Among them, the frequency of the higher harmonics obtained here is set at a very high order. Then, the higher harmonics are screened according to the ratio of the amplitude to the fundamental wave. Those with a smaller amplitude than the fundamental wave are discarded, and only those with a higher ratio to the fundamental wave amplitude are retained. Then, according to Figure 3 In the manner shown, these fundamental waves 302 and the retained multiple higher harmonics 303 are resampled and accumulated, and then compared with the waveform 301 sampled data at the same moment. If the comparison result shows that the deviation between the two is very small, it means that the currently obtained decomposed higher harmonics meet the requirements. Finally, the highest harmonic among the multiple harmonics is used as the highest harmonic after transformation. The frequency of this highest harmonic is multiplied by two, and a certain margin is added to serve as the sample waveform sampling rate, that is, the sampling rate of the target capacity level. It should be noted that in some embodiments, the deviation between the above-mentioned cumulative sum and the waveform data sampling value is obtained by averaging the deviations of multiple simultaneous points. This average value may be an arithmetic mean or an average value calculated by other calculation methods, which is not limited here.

[0098] In terms of applying the above-mentioned dynamic sampling rate, the present invention provides a method for determining the sampling rate through the current waveform. Specifically, we take out the current waveform of a time window each time, and this time window spans a time period. Then, we take out a waveform and mirror the lower half of the waveform to the upper half with the horizontal axis as the mirror axis. Then, this waveform is integrated to obtain the effective value of the current waveform. According to the size of the effective value, the sampling rate of the corresponding capacity is selected.

[0099] In step 103, Fourier transform is performed on the waveform based on the waveform data set to obtain a fundamental wave and a plurality of higher harmonics.

[0100] In some embodiments, step 103 includes:

[0101] Obtaining a sampling rate corresponding to the waveform data set;

[0102] Determining a conversion target frequency according to the sampling rate, wherein the conversion target frequency is the frequency of the highest harmonic among the multiple high-order harmonics obtained by Fourier transform;

[0103] The fundamental wave and multiple higher harmonics are calculated based on the conversion target frequency, the waveform data set, and the first formula, where the first formula is:

[0104]

[0105] Where X[k] is the kth wave after transformation, x[n] is the nth element in the waveform dataset, and N is the total number of data in the waveform dataset.

[0106] For example, after determining the target sampling rate, we can determine the frequency of the highest harmonic after the change based on the target sampling rate (according to Shannon's theorem, the frequency of the highest harmonic should be 1 / 2 of the sampling rate). Thus, the fundamental wave and higher harmonics of the waveform can be obtained through the discrete Fourier transform formula. The transformation formula is:

[0107]

[0108] Where X[k] is the kth wave after transformation, x[n] is the nth element in the waveform dataset, and N is the total number of data in the waveform dataset.

[0109] In step 104, multiple characteristic quantity operations are performed on the fundamental wave and the multiple higher harmonics to obtain metering data of the multiple characteristic quantities, wherein the metering data represents the attribute characteristics of the electric energy.

[0110] In some embodiments, the metering data of the multiple characteristic quantities includes: active power corresponding to multiple harmonics and reactive power corresponding to multiple harmonics, the fundamental wave and the multiple higher harmonics include the fundamental wave of voltage, multiple higher harmonics of voltage, the fundamental wave of current, and higher harmonics of current, and step 104 includes:

[0111] Pairing the fundamental wave of voltage, multiple higher harmonics of voltage, the fundamental wave of current, and higher harmonics of current according to the frequencies of the fundamental wave and higher harmonics to generate multiple voltage-current pairs;

[0112] Performing a dot product operation and a cross product operation on the multiple voltage-current pairs to obtain active power of multiple harmonics and reactive power of multiple harmonics;

[0113] The active powers of the multiple harmonics and the reactive powers of the multiple harmonics are accumulated respectively to obtain a total active power and a total reactive power.

[0114] In some embodiments, the metering data of the multiple characteristic quantities includes: power factors corresponding to multiple harmonics, the fundamental wave and the multiple higher harmonics include the fundamental wave of voltage, multiple higher harmonics of voltage, the fundamental wave of current, and higher harmonics of current, and step 104 includes:

[0115] Pairing the fundamental wave of voltage, multiple higher harmonics of voltage, the fundamental wave of current, and higher harmonics of current according to the frequencies of the fundamental wave and higher harmonics to generate multiple voltage-current pairs;

[0116] The power factors of the plurality of harmonics are determined based on the plurality of voltage-current pairs and a second formula, wherein the second formula is:

[0117]

[0118] Where cos k (θ) is the power factor of the kth harmonic, X u (k) is the kth harmonic of voltage, X i (k) is the kth harmonic of the current.

[0119] For example, the voltage waveform and current waveform are sampled and transformed at the same time, and the fundamental wave and higher harmonics obtained are very important for obtaining multiple characteristics of electric energy. For example, the active power, reactive power or power factor of each harmonic can be obtained. Some application scenarios are explained below.

[0120] For the active or reactive aspects of each harmonic, since the different frequency waveforms of the fundamental wave and higher harmonics are orthogonal (the length of the waveform taken out of the time window ensures orthogonality), to calculate the active and reactive aspects, it is only necessary to pair the voltage harmonics and current harmonics according to the frequency. After pairing, the active power at the harmonic frequency is obtained by dot product of the voltage harmonics and the current harmonics, and the reactive power at the harmonic frequency is obtained by cross product of the voltage harmonics and the current harmonics. The total active power is obtained by adding up the active powers at multiple harmonic frequencies. Similarly, the total reactive power is obtained by adding up the reactive powers at multiple harmonic frequencies.

[0121] Regarding the power factor, after pairing the voltage harmonics and current harmonics according to their frequencies, the power factor under the harmonics can be calculated using the following formula:

[0122]

[0123] Where cos k (θ) is the power factor of the kth harmonic, X u (k) is the kth harmonic of voltage, X i (k) is the kth harmonic of the current.

[0124] The embodiment of the electric energy metering method with multiple characteristic quantities of the present invention first obtains the waveform at the feeder end, wherein the feeder is used to connect to a load and / or a power supply, and the waveform is used to characterize the waveform of the electric energy transmitted by the feeder. Then, the waveform is sampled to obtain a waveform data set. Next, the waveform is Fourier transformed based on the waveform data set to obtain a fundamental wave and multiple higher harmonics. Finally, multiple characteristic quantity operations are performed on the fundamental wave and the multiple higher harmonics to obtain metering data of multiple characteristic quantities, wherein the metering data characterizes the attribute characteristics of the electric energy. The embodiment of the present invention can determine a reasonable sampling rate through the waveform, which can ensure the accuracy of each harmonic after the transformation and reduce the complexity of sampling and calculation, achieving a balance between the two. After the harmonics obtained by transformation, metering data such as harmonic active power, harmonic reactive power, power factor, harmonic factor, main harmonics, etc. can be calculated based on the harmonics, and the accuracy of the metering data is guaranteed.

[0125] It should be understood that the size of the serial numbers of each step in the above embodiment does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0126] The following is an embodiment of the device of the present invention. For details not described in detail, please refer to the corresponding method embodiment described above.

[0127] Figure 4This is a functional block diagram of a multi-feature electric energy metering device provided by an embodiment of the present invention, referring to Figure 4 The multi-feature quantity electric energy metering device 4 includes: a waveform acquisition module 401 , a waveform sampling module 402 , a Fourier transform module 403 and a multi-feature quantity metering module 404 .

[0128] The waveform acquisition module 401 is used to acquire a waveform at a feeder end, wherein the feeder is used to connect to a load and / or a power source, and the waveform is used to represent the waveform of the electric energy transmitted by the feeder;

[0129] The waveform sampling module 402 is used to sample the waveform to obtain a waveform data set;

[0130] A Fourier transform module 403 is configured to perform Fourier transform on the waveform based on the waveform data set to obtain a fundamental wave and multiple higher harmonics;

[0131] The multi-feature quantity metering module 404 is configured to perform multiple feature quantity operations on the fundamental wave and the multiple higher harmonics to obtain metering data of the multiple feature quantities, wherein the metering data represents attribute characteristics of electric energy.

[0132] Figure 5 This is a functional block diagram of a terminal provided by an embodiment of the present invention. Figure 5 As shown, the terminal 5 of this embodiment includes: a processor 500 and a memory 501, wherein the memory 501 stores a computer program 502 that can be run on the processor 500. When the processor 500 executes the computer program 502, the steps in the above-mentioned multi-feature quantity electric energy metering method and embodiment are implemented, such as Figure 1 Steps 101 to 104 are shown.

[0133] Illustratively, the computer program 502 may be divided into one or more modules / units, and the one or more modules / units are stored in the memory 501 and executed by the processor 500 to implement the present invention.

[0134] The terminal 5 can be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal 5 can include, but is not limited to, a processor 500 and a memory 501. Those skilled in the art will understand that Figure 5 It is only an example of terminal 5 and does not constitute a limitation on terminal 5. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal may also include input and output devices, network access devices, buses, etc.

[0135] The processor 500 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0136] The memory 501 may be an internal storage unit of the terminal 5, such as a hard disk or memory of the terminal 5. The memory 501 may also be an external storage device of the terminal 5, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal 5. Furthermore, the memory 501 may include both an internal storage unit of the terminal 5 and an external storage device. The memory 501 is used to store the computer program and other programs and data required by the terminal. The memory 501 may also be used to temporarily store data that has been output or is about to be output.

[0137] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the implementation method can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method implementation method, and will not be repeated here.

[0138] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0139] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0140] In the embodiments provided herein, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For example, the division of modules or units is merely a logical functional division. In actual implementation, there may be other division methods, such as multiple units or components being combined or integrated into another system, or some features being ignored or not implemented. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interface, or the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0141] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of this embodiment.

[0142] In addition, the functional units in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0143] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned implementation method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, it can implement the steps of the above-mentioned various methods and device implementation methods. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0144] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A method for measuring electric energy with multiple characteristic quantities, characterized in that: include: Acquire a waveform at a feeder end, wherein the feeder is used to connect to a load and / or a power source, and the waveform is used to represent a waveform of electric energy transmitted by the feeder; Sampling the waveform at a dynamic sampling rate to obtain a waveform data set; Performing Fourier transform on the waveform based on the waveform data set to obtain a fundamental wave and a plurality of higher harmonics; Performing multiple characteristic quantity operations on the fundamental wave and the multiple higher harmonics to obtain metering data of the multiple characteristic quantities, wherein the metering data represents attribute characteristics of electric energy; in, The sampling rate is determined based on the waveform, including: Acquire a plurality of sample waveforms, wherein the sample waveforms correspond to a target capacity level, and the target capacity level is determined based on the capacity of input power and / or the capacity of output power; For each of the plurality of sample waveforms, a sampling rate corresponding to a target capacity level is obtained by performing the following steps: Sampling the sample waveform at a sample sampling rate to obtain a sample waveform data set; Performing Fourier transform on the sample waveform based on the sample waveform data set to obtain a sample fundamental wave and a plurality of sample higher harmonics; determining a deviation rate after transformation according to the sample waveform, the sample fundamental wave, and the plurality of sample higher harmonics; If the deviation rate is lower than a threshold, a plurality of harmonics having a harmonic rate higher than the threshold are screened out from the plurality of sample higher harmonics as typical harmonics, wherein the harmonic rate is a ratio of the amplitude of the sample higher harmonic to the amplitude of the sample fundamental wave; Determining a target sampling rate according to the frequency of the highest-order harmonic among the typical harmonics, and using the target sampling rate as the sampling rate of the sample waveform corresponding to the target capacity level; in, The step of sampling the waveform at a dynamic sampling rate to obtain a waveform data set includes: Obtain a time pane, wherein the time pane includes a time period; Extracting a section of the waveform from the waveform according to the time window; Flipping the waveform to obtain a flipped waveform, wherein the flipping is to flip the negative half cycle of the waveform to the positive half cycle in an amplitude mirroring manner; Integrating the inverted waveform to obtain an effective value of the waveform; According to the effective value, a dynamic sampling rate is selected, the waveform is sampled, and a waveform data set is obtained, wherein the dynamic sampling rate is obtained based on a sampling rate set, and the sampling rate set includes sampling rates of multiple target capacity files, and the sampling rates of the target capacity files correspond to the target capacity files.

2. The multi-characteristic electric energy measurement method according to claim 1, characterized in that: The step of determining the deviation rate after transformation according to the sample waveform, the sample fundamental wave, and the plurality of sample higher harmonics includes: Sampling the sample fundamental wave and the plurality of sample higher harmonics respectively according to the sample sampling rate to obtain a plurality of transformation sets, wherein the plurality of transformation sets correspond to a plurality of sampling points, and the transformation sets include sampling values of the fundamental wave and sampling values of the plurality of sample higher harmonics; For each of the multiple transformation sets, the following steps are performed to obtain deviation rates of multiple sampling points: Accumulating the sampling values of the fundamental wave and the sampling values of the plurality of higher harmonic samples in the transformation set to obtain an accumulated sum; Finding the waveform data value in the sample waveform data set according to the sampling position corresponding to the transformation set; Calculating a deviation rate between the accumulated sum and the waveform data value as a deviation rate of a sampling point; An average value of the deviation rates of the plurality of sampling points is calculated as the transformed deviation rate.

3. The multi-characteristic electric energy measurement method according to claim 1, characterized in that: The performing Fourier transform on the waveform based on the waveform data set to obtain a fundamental wave and a plurality of higher harmonics includes: Obtaining a sampling rate corresponding to the waveform data set; Determining a conversion target frequency according to the sampling rate, wherein the conversion target frequency is the frequency of the highest harmonic among the multiple high-order harmonics obtained by Fourier transform; The fundamental wave and multiple higher harmonics are calculated based on the conversion target frequency, the waveform data set and a first formula, where the first formula is: Where, After transformation Second wave, The first elements, is the total number of data in the waveform dataset.

4. The multi-characteristic electric energy measurement method according to any one of claims 1 to 3, characterized in that: The measurement data of the multiple feature quantities includes: active power corresponding to multiple harmonics and reactive power corresponding to multiple harmonics, the fundamental wave and the multiple higher harmonics include the fundamental wave of voltage, multiple higher harmonics of voltage, the fundamental wave of current, and higher harmonics of current, and performing multiple feature quantity operations on the fundamental wave and the multiple higher harmonics to obtain the measurement data of the multiple feature quantities includes: Pairing the fundamental wave of voltage, multiple higher harmonics of voltage, the fundamental wave of current, and higher harmonics of current according to the frequencies of the fundamental wave and higher harmonics to generate multiple voltage-current pairs; Performing a dot product operation and a cross product operation on the multiple voltage-current pairs to obtain active power of multiple harmonics and reactive power of multiple harmonics; The active powers of the multiple harmonics and the reactive powers of the multiple harmonics are accumulated respectively to obtain a total active power and a total reactive power.

5. The multi-characteristic electric energy measurement method according to any one of claims 1 to 3, characterized in that: The measurement data of the multiple feature quantities includes: power factors corresponding to multiple harmonics, the fundamental wave and the multiple higher harmonics include the fundamental wave of voltage, multiple higher harmonics of voltage, the fundamental wave of current, and the higher harmonics of current, and performing multiple feature quantity operations on the fundamental wave and the multiple higher harmonics to obtain the measurement data of the multiple feature quantities includes: Pairing the fundamental wave of voltage, multiple higher harmonics of voltage, the fundamental wave of current, and higher harmonics of current according to the frequencies of the fundamental wave and higher harmonics to generate multiple voltage-current pairs; The power factors of the plurality of harmonics are determined based on the plurality of voltage-current pairs and a second formula, wherein the second formula is: Where, For the The power factor of the subharmonics, The voltage subharmonics, The first Subharmonics.

6. A multi-characteristic electric energy metering device, characterized in that: For implementing the multi-feature quantity electric energy metering method according to any one of claims 1 to 5, the multi-feature quantity electric energy metering device comprises: A waveform acquisition module, configured to acquire a waveform at a feeder end, wherein the feeder is configured to be connected to a load and / or a power source, and the waveform is configured to characterize a waveform of electric energy transmitted by the feeder; A waveform sampling module, used to sample the waveform and obtain a waveform data set; A Fourier transform module, configured to perform Fourier transform on the waveform based on the waveform data set to obtain a fundamental wave and a plurality of higher harmonics; as well as, The multi-feature quantity metering module is used to perform multiple feature quantity operations on the fundamental wave and the multiple higher harmonics to obtain metering data of the multiple feature quantities, wherein the metering data represents the attribute characteristics of the electric energy.

7. A terminal comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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