CN104090159B - Electric energy measuring method and device - Google Patents

Abstract

The present application provides a method and device for measuring electric energy. The method includes: low-pass filtering the electrical signal to obtain an analog signal; performing A/D sampling on the analog signal to obtain a plurality of discrete signals; Improve the generalized fast S transform to obtain the first result matrix corresponding to each discrete signal; use the linear characteristics of the improved generalized fast S transform to linearly decompose each first result matrix to obtain the second result matrix corresponding to each frequency component of each discrete signal Result matrix; each second result matrix is carried out inversely improving the generalized fast S-transform according to the inversion lossless property respectively, obtains the reconstructed time-domain signal of each frequency component of each discrete signal; Obtains in described A/D sampling interval time Electric energy consumption value, so as to obtain the electric energy consumption value within the preset time. The present application can realize that the shape of the Gaussian window can be adjusted according to the actual situation, and the calculation efficiency is improved.

Description

Electric energy metering method and device

technical field

The present application relates to the field of electric power technology, in particular to an electric energy metering method and device.

Background technique

Electric energy is an indispensable and important energy commodity in the production and life of modern society. Its production, sales and use depend on the system composed of power plants, power supply parts and users. Therefore, the accuracy and rationality of electric energy measurement directly affect the economic interests of the power generation, supply, and consumption parties and the fairness of transactions.

At present, the existing electric energy meters at home and abroad can only measure the electric energy of the steady-state distortion signal, but are powerless for the electric energy measurement of the transient distortion signal. However, the frequent start-up of motors and the input of loads in industrial sites will generate huge transient power, but the energy meter cannot achieve measurement, which will cause huge losses to the power sector. Therefore, it is of great theoretical and practical significance to deeply study the influence of power grid signal distortion on electric energy metering and how to realize accurate and reasonable electric energy metering under this background.

At present, the commonly used electric energy measurement algorithm has S transformation (Stockwell Transform). S-transform is an algorithm proposed by R.G.Stockwell in 1996 and used for seismic wave signal detection. It is a reversible time-frequency analysis method. However, the S-transform has the disadvantage that the shape of the Gaussian window cannot be adjusted according to the actual situation, and because the time-frequency matrix of the S-transform algorithm has a huge amount of information, the operation takes a long time and the operation efficiency is low.

Contents of the invention

In order to solve the above technical problems, the embodiment of the present application provides an electric energy measurement method and device to achieve the purpose of adjusting the shape of the Gaussian window according to the actual situation and improving the calculation efficiency. The technical solution is as follows:

A method for measuring electric energy, comprising:

Perform low-pass filtering on the electric signal in the power grid that needs to be measured for electric energy to obtain an analog signal;

A/D sampling is performed on the analog signal to obtain a plurality of discrete signals;

The improved generalized fast S transform is performed on each discrete signal respectively to obtain the first result matrix corresponding to each discrete signal. The improved generalized fast S transform introduces a Gaussian window width adjustment factor and a Gaussian window at the DC component on the basis of the S transform. The width adjustment factor and the idea of using a fast algorithm are obtained;

Using the linear characteristics of the improved generalized fast S-transform, each first result matrix is linearly decomposed to obtain a second result matrix corresponding to each frequency component of each discrete signal;

Carrying out an inverse improved generalized fast S-transform on each second result matrix according to the inverse lossless property, to obtain the reconstructed time-domain signal of each frequency component of each discrete signal;

According to the requirements of electric energy measurement, multiply the corresponding points of each reconstructed time-domain signal and accumulate the product results, add the accumulated values of the multiplication results of each reconstructed time-domain signal to obtain the cumulative sum, and multiply the cumulative sum by A/ D sampling interval time, to obtain the power consumption value within the A/D sampling interval time, so as to obtain the power consumption value within the preset time.

Preferably, the process of improving the generalized fast S-transformation for each discrete signal to obtain the respective first result matrix corresponding to each discrete signal includes:

Improving Generalized Fast S-Transform Expression Using Discrete Performing improved generalized fast S-transformation on each discrete signal to obtain the respective first result matrix corresponding to each discrete signal, said Improved generalized fast S-transform expressions for the discretization of the AC part, the For the discrete improvement of the DC part, the generalized fast S-transform expression, a=0,1,...N-1, n=1,...n _max -1, p=-width(n ),..., 0,...width(n)-1, said N is the number of sampling points of the electrical signal to be analyzed, said Δt is the sampling time interval of the electrical signal to be analyzed, and said h(kΔt) is The sampled values at each sampling instant.

Preferably, the discrete improved generalized fast S-transform expression is obtained by discretely transforming the improved generalized fast S-transform formula, and the improved generalized fast S-transform formula is , the h(τ) is the electrical signal to be analyzed, t is the time shift variable, f is the frequency, τ is the time, α and β are the Gaussian window width adjustment factors, γ is the Gaussian window width adjustment factor at the DC component, w _m (t- τ, α, β, γ) are improved generalized Gaussian windows;

Among them, the process of discretely transforming the improved generalized fast S-transform formula is:

A: Use the formula Calculate the frequency domain radius of the improved generalized Gaussian window, the is the frequency domain radius;

B: Calculate the number of frequency sampling points and the frequency value of the central frequency point, the number of the frequency sampling points is denoted as n _max , the frequency value of the central frequency point is denoted as f _n , and the central frequency point is the frequency sampling point;

C: Calculate the discrete radius of the improved generalized Gaussian window at each center frequency point as The improved generalized Gaussian window discrete radius for width _n (n), is rounding symbol;

D: Calculate the displacement distance of the spectrum of each center frequency point as The center _n is the displacement distance;

E: Calculate the coverage of each frequency domain of the improved generalized Gaussian window, the coverage is characterized by f _start (n) and f _end (n), wherein, f _start (0)=0, f _start (n+1) =centre _n (n)+width _n (n)+width _n (n+1), n=0,..., n _max -1, f _end (n)=f _start (n)+2width _n (n) ;

F: Calculate the FFT result of the fast Fourier transform of the electrical signal to be analyzed, and shift the FFT result to obtain the first FFT result, denoted as H[p], in the spectrum information in the first FFT result The DC result of is located in the center, and the negative and positive frequency components are located on both sides;

G: Calculate the time-domain radius of the improved generalized Gaussian window at each center frequency point as p=-width _n (n),-width _n (n)+1,...,0,...,width _n (n)-1;

H: adding the first FFT result to the displacement distance of the frequency spectrum of each center frequency point, respectively, to obtain the second FFT result corresponding to each center frequency point, denoted as H[p+centre _n (n)];

I: Multiply the second FFT results of each center frequency point with the time domain radius of their respective improved generalized Gaussian windows to obtain the calculation results of each center frequency point, and arrange each calculation result according to the distribution position in the FFT spectrum to obtain The results are arranged, and an IFFT operation is performed on the arranged results to obtain a discrete improved generalized fast S-transform expression of the AC part.

Preferably, said step B includes:

B11: Let the frequency of the nth frequency sampling point be f _n (n starts from 0), then the relationship between two adjacent center frequencies:

B12: Let the first frequency center point be the DC point, i.e. f ₀ =0, and according to Obtain the frequency value f _n of each center frequency point, n=0,...,n _max -1;

B13: Solving Inequalities The number n _max of frequency sampling points is obtained, and the f _s is the sampling frequency of the electrical signal to be analyzed.

Preferably, utilizing the linear characteristics of the improved generalized fast S transform, each first result matrix is linearly decomposed, and the process of obtaining the second result matrix corresponding to each frequency component of each discrete signal includes:

Using the linear characteristic S[h(t)]=S[x(t)+y(t)]=S[x(t)]+S[y(t)] of the improved generalized fast S-transform, when calculating each For a certain frequency component of a result matrix, only the part corresponding to the frequency component in the first result matrix is reserved, and the part corresponding to the frequency component other than the frequency component in the first result matrix is assigned a value of 0;

The h(t), x(t) and y(t) are signals to be analyzed and h(t)=x(t)+y(t).

Preferably, the inversion losslessness is:

The principle of the inverse improved generalized fast S-transform is

H(v+f)=α(v,f)/W _m (v),

The a(v, f) is the Fourier transform result of the time shift variable t and the Fourier transform result of the time τ, and the v is the Fourier transform result of the time shift variable t transform, the f is the Fourier transform of the τ, and H(v+f) is the Fourier transform result of the electrical signal to be analyzed.

Preferably, according to the requirements of electric energy measurement, the process of multiplying corresponding points of any reconstructed time-domain signal and accumulating the product results includes:

Separate the reconstructed time-domain signal to obtain discrete signals of harmonic voltage and current, which are denoted as u _n [k] and i _n [k] respectively;

According to the formula The electric energy consumed per unit time of the reconstructed time-domain signal is calculated.

An electric energy metering device, comprising:

The filter module is used to low-pass filter the electric signal in the power grid that needs to be measured for electric energy to obtain an analog signal;

A sampling module, configured to perform A/D sampling on the analog signal to obtain multiple discrete signals;

The first transformation module is used to perform improved generalized fast S-transform on each discrete signal respectively to obtain the first result matrix corresponding to each discrete signal. The improved generalized fast S-transform introduces Gaussian window width adjustment on the basis of S-transform factor and the Gaussian window width adjustment factor at the DC component and the idea of using a fast algorithm;

Decomposition module, for utilizing the linear characteristic of improved generalized fast S transform, carry out linear decomposition to each first result matrix, obtain the second result matrix corresponding to each frequency component of each discrete signal;

The second transformation module is used to perform an inverse improved generalized fast S-transform on each second result matrix according to the inverse lossless property, so as to obtain the reconstructed time-domain signal of each frequency component of each discrete signal;

The calculation module is used to multiply corresponding points of each reconstructed time-domain signal according to the requirements of electric energy measurement and accumulate the product results, add the accumulated values of the multiplication results of each reconstructed time-domain signal to obtain an accumulated sum, and calculate the accumulated and multiplied by the A/D sampling interval time to obtain the power consumption value within the A/D sampling interval time, so as to obtain the power consumption value within the preset time.

Preferably, the first transformation module includes:

The first transformation unit is used to adopt the discrete improved generalized fast S-transform expression

Performing improved generalized fast S-transformation on each discrete signal to obtain the respective first result matrix corresponding to each discrete signal, said Improved generalized fast S-transform expressions for the discretization of the AC part, the For the discrete improvement of the DC part, the generalized fast S-transform expression, a=0, 1, ... N-1, n = 1, ... n _max -1, p = -width (n), ..., 0, ... width(n)-1, the N is the number of sampling points of the electrical signal to be analyzed, the Δt is the sampling time interval of the electrical signal to be analyzed, and the h(kΔt) is each sampling The sampling value at time;

The discrete improved generalized fast S-transform expression is obtained by discretely transforming the improved generalized fast S-transform formula, and the improved generalized fast S-transform formula is , the h(τ) is the electrical signal to be analyzed, t is the time shift variable, f is the frequency, τ is the time, α and β are the Gaussian window width adjustment factors, γ is the Gaussian window width adjustment factor at the DC component, w _m (t- τ, α, β, γ) are modified generalized Gaussian windows.

Preferably, it also includes:

The third transformation module is used to carry out discrete transformation to the improved generalized fast S transformation formula;

The third conversion module includes:

The first calculation unit is used to utilize the formula Calculate the frequency domain radius of the improved generalized Gaussian window, the is the frequency domain radius;

The second calculation unit is used to calculate the number of frequency sampling points and the frequency value of the central frequency point, the number of frequency sampling points is denoted as n _max , the frequency value of the central frequency point is denoted as f _n , and the central frequency point is Frequency sampling point;

The third calculation unit is used to calculate the discrete radius of the improved generalized Gaussian window of each center frequency point as The improved generalized Gaussian window discrete radius for width _n (n), is rounding symbol;

The fourth calculation unit is used to calculate the displacement distance of the frequency spectrum of each center frequency point as The center _n is the displacement distance;

The fifth calculation unit is used to calculate the coverage of each frequency domain of the improved generalized Gaussian window, the coverage is characterized by f _start (n) and f _end (n), wherein f _start (0)=0, f _start (n+1)=centre _n (n)+width _n (n)+width _n (n+1), n=0,..., n _max -1, f _end (n)=f _start (n)+ 2width _n (n);

The sixth calculation unit is used to calculate the FFT result of the electrical signal to be analyzed, and shift the FFT result to obtain the first FFT result, denoted as H[p], and the spectrum information in the first FFT result The DC result in is at the center, and the negative and positive frequency components are at the two sides, respectively;

The seventh calculation unit is used to calculate the time domain radius of the improved generalized Gaussian window of each center frequency point as p=-width _n (n),-width _n (n)+1,...,0,...,width _n (n)-1;

The eighth calculation unit is used to add the first FFT result to the displacement distance of the frequency spectrum of each center frequency point respectively, to obtain the second FFT result corresponding to each center frequency point, denoted as H[p+centre _n ( n)];

The ninth calculation unit is used to multiply the second FFT results of each center frequency point with the time domain radius of their respective improved generalized Gaussian windows to obtain the operation results of each center frequency point, and distribute each operation result according to the FFT spectrum The positions are arranged to obtain the arrangement result, and the IFFT operation is performed on the arrangement result to obtain the discrete improved generalized fast S-transform expression of the AC part.

Preferably, the second calculation unit includes: a first calculation subunit, the frequency used for the nth frequency sampling point is f _n (n starts from 0), then the relationship between two adjacent center frequencies:

The second calculation subunit is used for the first frequency center point to be the direct current point, that is, f ₀ =0, and according to Obtain the frequency value f _n of each center frequency point, n=0,...,n _max -1;

The third calculation subunit is used to solve the inequality The number n _max of frequency sampling points is obtained, and the f _s is the sampling frequency of the electrical signal to be analyzed.

Preferably, the decomposition module is specifically used to utilize the linear property S[h(t)]=S[x(t)+y(t)]=S[x(t)]+S[ y(t)], when calculating a certain frequency component, only keep the part corresponding to the frequency component in the first result matrix, so that the part corresponding to the frequency component other than the frequency component in the first result matrix assign a value of 0;

The h(t), x(t) and y(t) are signals to be analyzed and h(t)=x(t)+y(t).

Preferably, the calculation module includes:

A separation unit is used to separate the reconstructed time-domain signal to obtain discrete harmonic voltage and current signals, which are denoted as u _n [k] and i _n [k] respectively;

The tenth calculation unit is used to base the formula The electric energy consumed per unit time of the reconstructed time-domain signal is calculated.

Compared with the prior art, the beneficial effects of the present application are:

In this application, since the improved generalized fast S-transform introduces the Gaussian window width adjustment factor and the Gaussian window width adjustment factor at the DC component on the basis of the S-transformation, the shape of the Gaussian window can be adjusted according to the actual situation.

Since the improved generalized fast S transform is based on a fast algorithm, the calculation speed is increased when the improved generalized fast S transform is used, and the linear decomposition is performed by using the linear characteristics of the improved generalized fast S transform, which reduces the amount of calculation and improves the calculation efficiency.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings that need to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application. For those skilled in the art, other drawings can also be obtained based on these drawings without any creative effort.

Fig. 1 is a kind of flow chart of the electric energy metering method based on improved generalized fast S transformation provided by the present application;

Fig. 2 is a structural schematic diagram of an improved generalized fast S-transform electric energy metering device provided by the present application.

detailed description

The following will clearly and completely describe the technical solutions in the embodiments of the application with reference to the drawings in the embodiments of the application. Apparently, the described embodiments are only some of the embodiments of the application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

Embodiment one

Please refer to Fig. 1, which shows a flow chart of the electric energy metering method based on the improved generalized fast S-transformation provided by the present application, which may include the following steps:

Step S11: performing low-pass filtering on the electric signal in the power grid that needs to be measured for electric energy to obtain an analog signal.

In this embodiment, the electrical signal includes a current signal and a voltage signal.

In this embodiment, the highest frequency value of the electric signal that can be processed is determined according to the actual measurement requirements and the setting of the A/D sampling rate, and then the electric signal is filtered by an analog filter circuit.

Step S12: Perform A/D sampling on the analog signal to obtain multiple discrete signals.

Step S13: Perform the improved generalized fast S transform on each discrete signal respectively to obtain the first result matrix corresponding to each discrete signal. The improved generalized fast S transform introduces the Gaussian window width adjustment factor and the DC component on the basis of the S transform Gaussian window width adjustment factor and the idea of using a fast algorithm are obtained.

Step S14: Using the linear characteristic of the improved generalized fast S-transform, linearly decompose each first result matrix to obtain a second result matrix corresponding to each frequency component of each discrete signal.

Step S15 : performing an inverse improved generalized fast S-transform on each of the second result matrices according to the inverse lossless property, to obtain reconstructed time-domain signals of each frequency component of each discrete signal.

Step S16: According to the requirements of electric energy measurement, multiply the corresponding points of each reconstructed time-domain signal and accumulate the product results, add the accumulated values of the multiplication results of each reconstructed time-domain signal to obtain a cumulative sum, and multiply the accumulated sum Using the A/D sampling interval time, the power consumption value within the A/D sampling interval time is obtained, so as to obtain the power consumption value within a preset time.

In this embodiment, the preset time is divided by the A/D sampling interval time, and the obtained value is multiplied by the power consumption value within the A/D sampling interval time to obtain the power consumption value within the preset time period.

In this application, since the improved generalized fast S-transform introduces the Gaussian window width adjustment factor and the Gaussian window width adjustment factor at the DC component on the basis of the S-transformation, the shape of the Gaussian window can be adjusted according to the actual situation.

Since the improved generalized fast S transform is based on a fast algorithm, the calculation speed is increased when the improved generalized fast S transform is used, and the linear decomposition is performed by using the linear characteristics of the improved generalized fast S transform, which reduces the amount of calculation and improves the calculation efficiency.

Embodiment two

another embodiment

In this embodiment, it shows the process of performing the improved generalized fast S-transform on each discrete signal respectively to obtain the first result matrix corresponding to each discrete signal.

Since the improved generalized fast S-transform is performed on each discrete signal, the process of obtaining the first result matrix corresponding to each discrete signal is the same, so in this embodiment, only an improved generalized fast S-transform is performed on any discrete signal to obtain the discrete signal corresponding to The procedure for the first result matrix is described.

In this embodiment, the improved generalized fast S-transformation is performed on the discrete signal, and the specific process of obtaining the first result matrix corresponding to the discrete signal is as follows:

Improving Generalized Fast S-Transform Expression Using Discrete An improved generalized fast S-transform is performed on the discrete signal to obtain a first result matrix, and the Improved generalized fast S-transform expressions for the discretization of the AC part, the For the discrete improvement of the DC part, the generalized fast S-transform expression, a=0,1,...N-1, n=1,...n _max -1, p=-width(n ),..., 0,...width(n)-1, said N is the number of sampling points of the electrical signal to be analyzed, said Δt is the sampling time interval of the electrical signal to be analyzed, and said h(kΔt) is The sampled values at each sampling instant.

In this embodiment, by The discrete improved generalized fast transformation is performed on the AC component of the electric signal, and the first result matrix of the AC component is obtained.

Depend on The discrete improved generalized fast transformation is performed on the DC component of the electric signal to obtain the first result matrix of the DC component.

Wherein, the discrete improved generalized fast S-transform expression is obtained by performing discrete transformation on the improved generalized fast S-transform formula, and the improved generalized fast S-transform formula is , the h(τ) is the electrical signal to be analyzed, t is the time shift variable, f is the frequency, τ is the time, α and β are the Gaussian window width adjustment factors, γ is the Gaussian window width adjustment factor at the DC component, w _m (t- τ, α, β, γ) are modified generalized Gaussian windows.

Improved generalized fast S-transform formula compared to the S-transform formula in the prior art Added α, β, and γ.

In this embodiment, the process of discretely transforming the improved generalized fast S-transform formula is:

Step A: Use the formula Calculate the frequency domain radius of the improved generalized Gaussian window, the is the frequency domain radius.

Step B: Calculate the number of frequency sampling points and the frequency value of the central frequency point, the number of frequency sampling points is denoted as n _max , the frequency value of the central frequency point is denoted as f _n , and the central frequency point is the frequency sampling point.

In this embodiment, step B includes:

B11: Let the frequency of the nth frequency sampling point be f _n (n starts from 0), then the relationship between two adjacent center frequencies:

B12: Let the first frequency center point be the DC point, i.e. f ₀ =0, and according to The frequency values f _n of each center frequency point are obtained, n=0, . . . , n _max -1.

B13: Solving Inequalities The number n _max of frequency sampling points is obtained, and the f _s is the sampling frequency of the electrical signal to be analyzed.

Step C: Calculate the discrete radius of the improved generalized Gaussian window of each center frequency point as The improved generalized Gaussian window discrete radius for width _n (n), is the rounding symbol.

Step D: Calculate the displacement distance of the spectrum of each center frequency point as The center _n is the displacement distance.

Step E: Calculate the coverage of each frequency domain of the improved generalized Gaussian window, the coverage is characterized by f _start (n) and f _end (n), wherein, f _start (0)=0, f _start (n+1 )=centre _n (n)+width _n (n)+width _n (n+1), n=0,..., n _max -1, f _end (n)=f _start (n)+2width _n (n ).

Step F: Calculate the FFT (Fast Fourier Transformation) result of the electrical signal to be analyzed, and shift the FFT result to obtain the first FFT result, denoted as H[p], the first The DC result in the spectral information in the FFT result is located in the center, and the negative and positive frequency components are located on both sides.

Step G: Calculate the time-domain radius of the improved generalized Gaussian window of each center frequency point as

.

Step H: add the first FFT result to the displacement distance of the frequency spectrum of each center frequency point respectively to obtain the second FFT result corresponding to each center frequency point, denoted as H[p+centre _n (n)].

Step 1: multiply the second FFT result of each central frequency point and its respective time-domain radius of the improved generalized Gaussian window, obtain the calculation result of each central frequency point, arrange each calculation result according to the distribution position in the FFT spectrum, The permutation result is obtained, the IFFT operation is performed on the permutation result, and the discrete improved generalized fast S-transform expression of the AC part is obtained.

Embodiment Three

In this embodiment, the process of linearly decomposing each first result matrix to obtain a second result matrix corresponding to each frequency component of each discrete signal is shown by using the linear characteristic of the improved generalized fast S-transform.

Since the process of linearly decomposing each first result matrix to obtain the second result matrix corresponding to each frequency component of each discrete signal is the same, in this embodiment, only any first result matrix is linearly decomposed to obtain the first The process of the second result matrix corresponding to each frequency component of the discrete signal to which the result matrix belongs is described.

In this embodiment, the process of linearly decomposing the first result matrix to obtain the second result matrix corresponding to each frequency component of the discrete signal to which the first result matrix belongs is:

Using the linear characteristic S[h(t)]=S[x(t)+y(t)]=S[x(t)]+S[y(t)] of the improved generalized fast S-transform, when calculating a When the frequency component is used, only the part corresponding to the frequency component in the first result matrix is reserved, and the part corresponding to the frequency component other than the frequency component in the first result matrix is assigned a value of 0.

The h(t), x(t) and y(t) are signals to be analyzed and h(t)=x(t)+y(t).

Now give an example to illustrate the process of linear decomposition, such as the first result matrix S[a,n] of the signal to be analyzed h(t), where a is time and n is frequency, when it is necessary to calculate the _n0 frequency component of the signal to be analyzed, only It is necessary to keep the S[a, n ₀ ] part of the first result matrix, and the part corresponding to the other frequency components except the n ₀ frequency component is assigned a value of 0, and the obtained second result matrix of the n ₀ frequency component is:

Embodiment Four

In this embodiment, it shows the process of performing an inverse improved generalized fast S-transform on each of the second result matrices according to the inverse lossless property to obtain the reconstructed time-domain signal of each frequency component of each discrete signal.

Since the inverse improved generalized fast S-transform is performed on each second result matrix according to the inverse lossless property, the process of obtaining the reconstructed time-domain signal of each frequency component of each discrete signal is the same, so in this embodiment, only any one of the first The process of inversely improving the generalized fast S-transformation for the second result matrix to obtain the reconstructed time-domain signal of each frequency component of the discrete signal to which the second result matrix belongs is described.

Perform an inverse improved generalized fast S-transform on any second result matrix according to the inverse lossless property, and obtain the inverse lossless property based on the reconstructed time-domain signal of each frequency component of the discrete signal to which the second result matrix belongs:

Perform inverse improved generalized fast S transform on any second result matrix according to the inverse lossless property, and obtain the inverse improved generalized fast S transform based on the reconstructed time domain signal of each frequency component of the discrete signal to which the second result matrix belongs The principle is:

H(v+f)=α(v,f)/W _m (v)

The a(v, f) is the Fourier transform result of the time shift variable t and the Fourier transform result of the time τ, and the v is the Fourier transform result of the time shift variable t transform, the f is the Fourier transform of the τ, and H(v+f) is the Fourier transform result of the electrical signal to be analyzed.

In this embodiment, H(v+f) is shifted to obtain H(v), and then an IFFT operation is performed on H(v) to obtain h(τ).

In this embodiment, the specific process of reconstructing the time-domain signal of a certain discrete signal may include the following steps:

1) Create a length of array and where the array Store the improved generalized fast S-transform results of the DC component and the positive frequency component (the number of the array starts from 0), then the corresponding frequency range is Among them, the element numbered i (that is, the i-th element) corresponds to the frequency In addition, an array H[N] with a length of N is established to store the FFT result of the signal;

2) For n=0, 2, 3, ..., n _max -1:

Perform FFT operation on pos_spe[f _start (n)+1] to pos_spe[f _end (n)], a total of 2width _n (n) elements, and multiply by the coefficient And the result is still stored between pos_spe[f _start (n)+1] to pos_spe[f _end (n)];

At this time, the frequency domain improved generalized Gaussian window sequence is

p=-width _n (n),...,0,...,width _n (n)-1,

Put it between gauss[f _start (n)+1] to gauss[f _end (n)];

End of For.

3) the array Elements divided by corresponding elements in the , and place the result in the middle.

4) the array The elements in the array are placed in the corresponding positions in the array H[N].

5) For :

Take the conjugate of element H[i] and place it in H[N-i]; End of For.

6) Perform IFFT operation on H[N] and multiply by coefficient N to finally obtain the reconstructed time-domain signal.

It should be noted that the method provided by the present invention is applicable to electric energy metering occasions under common steady-state and non-steady-state signals. In order to illustrate the specific implementation process of the method provided by the present invention, the following analysis will focus on electric energy measurement under harmonic and inter-harmonic signals.

Let the signal sampling frequency be 6.4kHz, and the simulation time be 0.2s. The voltage and current signals for energy metering include harmonics and interharmonics. Then, the following points are included in the electric energy measurement: first, low-pass filter processing is performed on the voltage and current signals to obtain analog signals, and prepare for A/D sampling; then, A/D sampling is performed on the analog signals to obtain discrete signals for the following One-step signal processing lays the foundation; after that, the voltage and current are respectively processed by the improved generalized fast S transform to obtain the result matrix of voltage and current, and then the result matrix is separated by linear characteristics, so as to obtain the fundamental components and other components respectively The resulting matrix, and then inversely improve the generalized fast S transform on the separated result matrix to obtain the fundamental wave signal and distortion signal of the voltage and current respectively; finally, according to the formula Solve for various energy values. The measurement results are shown in Table 1 and Table 2. Table 1 is the analysis of the simulation results of electric energy measurement for harmonic and interharmonic signals, and Table 2 is the comparison of the calculation time between traditional S-transform and fast S-transform.

Where the voltage signal is:

The current signal is:

Table 1

Table 2

Table 1 and Table 2 show that the electric energy metering method based on the improved generalized fast S-transform can realize accurate metering of electric energy and the metering accuracy is higher than that of wavelet packet transform.

Embodiment five

In this embodiment, the electric energy metering device based on the improved generalized fast S-transform provided by the present application is provided, please refer to FIG. 2 , which shows a structural schematic diagram of the improved generalized fast S-transformed electric energy metering device provided by the present application , the electric energy metering device based on the improved generalized fast S-transform includes: a filtering module 21 , a sampling module 22 , a first transformation module 23 , a decomposition module 24 , a second transformation module 25 and a calculation module 26 .

The filtering module 21 is configured to perform low-pass filtering on electrical signals in the power grid that need to be measured for electric energy to obtain analog signals.

The sampling module 22 is configured to perform A/D sampling on the analog signal to obtain multiple discrete signals.

The first transformation module 23 is used to perform an improved generalized fast S-transform on each discrete signal respectively to obtain a first result matrix corresponding to each discrete signal. The improved generalized fast S-transform introduces a Gaussian window width on the basis of the S-transform The adjustment factor and the Gaussian window width adjustment factor at the DC component and the idea of using a fast algorithm are obtained.

In this embodiment, the first transformation module 23 includes: a first transformation unit for adopting the discrete improved generalized fast S-transform expression

Performing improved generalized fast S-transformation on each discrete signal to obtain the respective first result matrix corresponding to each discrete signal, said For the discrete improvement of the AC part, the generalized fast S-transform expression, a=0, 1,...N-1, n=1,...n _max -1, p=-width(n ),...,0,...width(n)-1, the is the discrete improved generalized fast S-transform expression of the DC part, the N is the number of sampling points of the electrical signal to be analyzed, the Δt is the sampling time interval of the electrical signal to be analyzed, and the h(kΔt) is the sampling time at each sampling moment value;

The discrete improved generalized fast S-transform expression is obtained by discretely transforming the improved generalized fast S-transform formula, and the improved generalized fast S-transform formula is , the h(τ) is the electrical signal to be analyzed, t is the time shift variable, f is the frequency, τ is the time, α and β are the Gaussian window width adjustment factors, γ is the Gaussian window width adjustment factor at the DC component, w _m (t- τ, α, β, γ) are modified generalized Gaussian windows.

The decomposition module 24 is configured to linearly decompose each first result matrix by utilizing the linear characteristic of the improved generalized fast S transform, to obtain a second result matrix corresponding to each frequency component of each discrete signal.

The second transformation module 25 is configured to perform an inverse improved generalized fast S-transform on each second result matrix according to the inverse lossless property, so as to obtain the reconstructed time-domain signal of each frequency component of each discrete signal.

The calculation module 26 is used to multiply the corresponding points of each reconstructed time-domain signal according to the requirements of electric energy measurement and accumulate the product results, and add the accumulated values of the multiplication results of each reconstructed time-domain signal to obtain a cumulative sum. Accumulate and multiply by the A/D sampling interval time to obtain the power consumption value within the A/D sampling interval time, so as to obtain the power consumption value within the preset time.

In this embodiment, the first transformation module 23 , the decomposition module 24 , the second transformation module 25 and the calculation module 26 can be integrated into the same digital signal processor.

The electric energy metering device based on the improved generalized fast S-transform shown in FIG. 2 may further include: a third transformation module, configured to perform discrete transformation on the improved generalized fast S-transform formula.

Wherein, the third transformation module includes: a first computing unit, a second computing unit, a third computing unit, a fourth computing unit, a fifth computing unit, a sixth computing unit, a seventh computing unit, an eighth computing unit and a ninth computing unit computing unit.

The first calculation unit is used to utilize the formula Calculate the frequency domain radius of the improved generalized Gaussian window, the is the frequency domain radius.

The second calculation unit is used to calculate the number of frequency sampling points and the frequency value of the central frequency point, the number of frequency sampling points is denoted as n _max , the frequency value of the central frequency point is denoted as f _n , and the central frequency point is Frequency sampling point.

In this embodiment, the second calculation unit specifically includes: a first calculation subunit, a second calculation subunit, and a third calculation subunit.

The first calculation subunit is used for the frequency of the nth frequency sampling point is f _n (n starts from 0), then the relationship between two adjacent center frequencies:

The second calculation subunit is used for the first frequency center point to be the direct current point, that is, f ₀ =0, and according to The frequency values f _n of each center frequency point are obtained, n=0, . . . , n _max -1.

The third calculation subunit is used to solve the inequality The number n _max of frequency sampling points is obtained, and the f _s is the sampling frequency of the electrical signal to be analyzed.

The third calculation unit is used to calculate the discrete radius of the improved generalized Gaussian window of each center frequency point as The improved generalized Gaussian window discrete radius for width _n (n), is the rounding symbol.

The fourth calculation unit is used to calculate the displacement distance of the frequency spectrum of each center frequency point as The center _n is the displacement distance.

The fifth calculation unit is used to calculate the coverage of each frequency domain of the improved generalized Gaussian window, the coverage is characterized by f _start (n) and f _end (n), wherein f _start (0)=0, f _start (n+1)=centre _n (n)+width _n (n)+width _n (n+1), n=0,..., n _max -1, f _end (n)=f _start (n)+ 2width _n (n).

The sixth calculation unit is used to calculate the FFT result of the electrical signal to be analyzed, and shift the FFT result to obtain the first FFT result, denoted as H[p], and the spectrum information in the first FFT result The DC result in is in the center, with negative and positive frequency components on the sides, respectively.

The seventh calculation unit is used to calculate the time domain radius of the improved generalized Gaussian window of each center frequency point as

.

The eighth calculation unit is used to add the first FFT result to the displacement distance of the frequency spectrum of each center frequency point respectively, to obtain the second FFT result corresponding to each center frequency point, denoted as H[p+centre _n ( n)].

The ninth calculation unit is used to multiply the second FFT results of each center frequency point with the time domain radius of their respective improved generalized Gaussian windows to obtain the operation results of each center frequency point, and distribute each operation result according to the FFT spectrum The positions are arranged to obtain the arrangement result, and the IFFT operation is performed on the arrangement result to obtain the discrete improved generalized fast S-transform expression of the AC part.

In this embodiment, the decomposition module 24 is specifically used to utilize the linear characteristic S[h(t)]=S[x(t)+y(t)]=S[x(t) of the improved generalized fast S-transform ]+S[y(t)], when calculating a certain frequency component, only keep the part corresponding to the frequency component in the first result matrix, so that the frequencies other than the frequency component in the first result matrix The part corresponding to the component is assigned a value of 0;

The h(t), x(t), and y(t) are signals to be analyzed and h(t)=x(t)+y(t)

In this embodiment, the calculation module 26 specifically includes: a separation unit and a tenth calculation unit.

The separation unit is used to separate the reconstructed time-domain signal to obtain discrete signals of harmonic voltage and current of each order, which are denoted as _un [ _k ] and in [k] respectively.

The tenth calculation unit is used to base the formula The electric energy consumed per unit time of the reconstructed time-domain signal is calculated.

It should be noted that each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the difference from other embodiments. For the same and similar parts in each embodiment, refer to each other, that is, Can. As for the device-type embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and for related parts, please refer to part of the description of the method embodiments.

Finally, it should also be noted that in this text, relational terms such as first and second etc. are only used to distinguish one entity or operation from another, and do not necessarily require or imply that these entities or operations, any such actual relationship or order exists. Furthermore, the term "comprises", "comprises" or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus comprising a set of elements includes not only those elements, but also includes elements not expressly listed. other elements of or also include elements inherent in such a process, method, article, or device. Without further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article or apparatus comprising said element.

The electric energy metering method and device provided by this application have been introduced in detail above. In this paper, specific examples have been used to illustrate the principle and implementation of this application. The description of the above embodiments is only used to help understand the method and its implementation of this application. core idea; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation and application scope. In summary, the content of this specification should not be construed as limiting the application .

Claims (13)

1. A method for measuring electric energy, comprising: Perform low-pass filtering on the electric signal in the power grid that needs to be measured for electric energy to obtain an analog signal; A/D sampling is performed on the analog signal to obtain a plurality of discrete signals; The improved generalized fast S transform is performed on each discrete signal respectively to obtain the first result matrix corresponding to each discrete signal. The improved generalized fast S transform introduces a Gaussian window width adjustment factor and a Gaussian window at the DC component on the basis of the S transform. The width adjustment factor and the idea of using a fast algorithm are obtained; Using the linear characteristics of the improved generalized fast S-transform, each first result matrix is linearly decomposed to obtain a second result matrix corresponding to each frequency component of each discrete signal; Carrying out an inverse improved generalized fast S-transform on each second result matrix according to the inverse lossless property, to obtain the reconstructed time-domain signal of each frequency component of each discrete signal; According to the requirements of electric energy measurement, multiply the corresponding points of each reconstructed time-domain signal and accumulate the product results, add the accumulated values of the multiplication results of each reconstructed time-domain signal to obtain the cumulative sum, and multiply the accumulated sum by A/ D sampling interval time, to obtain the power consumption value within the A/D sampling interval time, so as to obtain the power consumption value within the preset time. 2. method according to claim 1, it is characterized in that, carry out improved generalized fast S transformation to each discrete signal respectively, obtain the process of the first corresponding first result matrix of each discrete signal respectively, comprising: Improving Generalized Fast S-Transform Expression Using Discrete Performing improved generalized fast S-transformation on each discrete signal to obtain the respective first result matrix corresponding to each discrete signal, said Improved generalized fast S-transform expressions for the discretization of the AC part, the Improve the generalized fast S-transform expression for the discrete improvement of the DC part, a=0,1,...N-1,n=1,...n _max -1, p=-width(n ),...,0,...width(n)-1, the N is the number of sampling points of the electrical signal to be analyzed, the Δt is the sampling time interval of the electrical signal to be analyzed, and the h(kΔt) is The sampling value at each sampling moment, the width _n (n) is the improved generalized Gaussian window discrete radius of the nth center frequency point, and the center _n (n) is the displacement distance of the frequency spectrum of the nth center frequency point; Wherein, the discrete improved generalized fast S-transform expression is obtained by performing discrete transformation on the improved generalized fast S-transform formula, and the improved generalized fast S-transform formula is , the h(τ) is the electrical signal to be analyzed, t is the time shift variable, f is the frequency, τ is the time, α and β are the Gaussian window width adjustment factors, γ is the Gaussian window width adjustment factor at the DC component, w _m (t- τ,α,β,γ) is the improved generalized Gaussian window. 3. method according to claim 2, is characterized in that, described discrete improved generalized fast S transform expression obtains by carrying out discrete transformation to improved generalized fast S transform formula, and described improved generalized fast S transform formula is said h(τ) is the electrical signal to be analyzed, t is the time shift variable, f is the frequency, τ is the time, α and β are the Gaussian window width adjustment factors, γ is the Gaussian window width adjustment factor at the DC component, w _m (t- τ,α,β,γ) is an improved generalized Gaussian window; Among them, the process of discretely transforming the improved generalized fast S-transform formula is: A: Use the formula Calculate the frequency domain radius of the improved generalized Gaussian window, the is the frequency domain radius; B: Calculate the number of frequency sampling points and the frequency value of the central frequency point, the number of the frequency sampling points is denoted as n _max , the frequency value of the central frequency point is denoted as f _n , and the central frequency point is the frequency sampling point; C: Calculate the discrete radius of the improved generalized Gaussian window at each center frequency point as The improved generalized Gaussian window discrete radius for width _n (n), is rounding symbol; D: Calculate the displacement distance of the spectrum of each center frequency point as The center _n is the displacement distance; E: Calculate the coverage of each frequency domain of the improved generalized Gaussian window, the coverage is characterized by f _start (n) and f _end (n), wherein, f _start (0)=0, f _start (n+1) =centre _n (n)+width _n (n)+width _n (n+1), n=0,...,n _max -1, f _end (n)=f _start (n)+2width _n (n) ; F: Calculate the FFT result of the fast Fourier transform of the electrical signal to be analyzed, and shift the FFT result to obtain the first FFT result, denoted as H[p], in the spectrum information in the first FFT result The DC result of is located in the center, and the negative and positive frequency components are located on both sides; G: Calculate the time-domain radius of the improved generalized Gaussian window at each center frequency point as ; H: adding the first FFT result to the displacement distance of the frequency spectrum of each center frequency point, respectively, to obtain the second FFT result corresponding to each center frequency point, denoted as H[p+centre _n (n)]; I: Multiply the second FFT results of each center frequency point with the time domain radius of their respective improved generalized Gaussian windows to obtain the calculation results of each center frequency point, and arrange each calculation result according to the distribution position in the FFT spectrum to obtain The results are arranged, and an IFFT operation is performed on the arranged results to obtain a discrete improved generalized fast S-transform expression of the AC part. 4. The method according to claim 3, wherein said step B comprises: B11: Let the frequency of the nth frequency sampling point be f _n (n starts from 0), then the relationship between two adjacent center frequencies: B12: Let the first frequency center point be the DC point, i.e. f ₀ =0, and according to Obtain the frequency value f _n of each center frequency point, n=0,...,n _max -1; B13: Solving Inequalities The number n _max of frequency sampling points is obtained, and the f _s is the sampling frequency of the electrical signal to be analyzed. 5. method according to claim 3, is characterized in that, utilizes the linear characteristic of improving generalized fast S transformation, carries out linear decomposition to each first result matrix, obtains the corresponding second result matrix of each frequency component of each discrete signal process, including: Using the linear characteristic S[h(t)]=S[x(t)+y(t)]=S[x(t)]+S[y(t)] of the improved generalized fast S-transform, when calculating each For a certain frequency component of a result matrix, only the part corresponding to the frequency component in the first result matrix is reserved, and the part corresponding to the frequency component other than the frequency component in the first result matrix is assigned a value of 0; The h(t), x(t) and y(t) are signals to be analyzed and h(t)=x(t)+y(t). 6. The method according to claim 3, characterized in that, the inversion lossless property is: The principle of the inverse improved generalized fast S-transform is H(υ+f)=α(υ,f)/W _m (υ), The a(v, f) is the Fourier transform result of the time shift variable t and the Fourier transform result of the time τ, and the v is the Fourier transform result of the time shift variable t transform, the f is the Fourier transform of the τ, and H(υ+f) is the Fourier transform result of the electrical signal to be analyzed. 7. The method according to claim 6, characterized in that, according to the requirements of electric energy measurement, the process of multiplying corresponding points of any reconstructed time-domain signal and accumulating the product results includes: Separate the reconstructed time-domain signal to obtain discrete signals of harmonic voltage and current, which are denoted as u _n [k] and i _n [k] respectively; According to the formula The electric energy consumed per unit time of the reconstructed time-domain signal is calculated. 8. An electric energy metering device, characterized in that it comprises: The filter module is used to low-pass filter the electric signal in the power grid that needs to be measured for electric energy to obtain an analog signal; A sampling module, configured to perform A/D sampling on the analog signal to obtain multiple discrete signals; The first transformation module is used to perform improved generalized fast S-transform on each discrete signal respectively to obtain the first result matrix corresponding to each discrete signal. The improved generalized fast S-transform introduces Gaussian window width adjustment on the basis of S-transform factor and the Gaussian window width adjustment factor at the DC component and the idea of using a fast algorithm; Decomposition module, for utilizing the linear characteristic of improved generalized fast S transform, carry out linear decomposition to each first result matrix, obtain the second result matrix corresponding to each frequency component of each discrete signal; The second transformation module is used to perform an inverse improved generalized fast S-transform on each second result matrix according to the inverse lossless property, so as to obtain the reconstructed time-domain signal of each frequency component of each discrete signal; The calculation module is used to multiply corresponding points of each reconstructed time-domain signal according to the requirements of electric energy measurement and accumulate the product results, add the accumulated values of the multiplication results of each reconstructed time-domain signal to obtain an accumulated sum, and calculate the accumulated and multiplied by the A/D sampling interval time to obtain the power consumption value within the A/D sampling interval time, so as to obtain the power consumption value within the preset time. 9. The device according to claim 8, wherein the first conversion module comprises: The first transformation unit is used to adopt the discrete improved generalized fast S-transform expression Performing an improved generalized fast S-transform on each discrete signal to obtain the respective first result matrix corresponding to each discrete signal, said Improved generalized fast S-transform expressions for the discretization of the AC part, the For the discrete improvement of the DC part, the generalized fast S-transform expression, a=0,1,...N-1,n=1,...n _max -1, p=-width(n ),...,0,...width(n)-1, the N is the number of sampling points of the electrical signal to be analyzed, the Δt is the sampling time interval of the electrical signal to be analyzed, and the h(kΔt) is The sampling value at each sampling moment, the width _n (n) is the improved generalized Gaussian window discrete radius of the nth center frequency point, and the center _n (n) is the displacement distance of the frequency spectrum of the nth center frequency point; The discrete improved generalized fast S-transform expression is obtained by discretely transforming the improved generalized fast S-transform formula, and the improved generalized fast S-transform formula is , the h(τ) is the electrical signal to be analyzed, t is the time shift variable, f is the frequency, τ is the time, α and β are the Gaussian window width adjustment factors, γ is the Gaussian window width adjustment factor at the DC component, w _m (t- τ,α,β,γ) is the improved generalized Gaussian window. 10. The device according to claim 9, further comprising: The third transformation module is used to carry out discrete transformation to the improved generalized fast S transformation formula; The third conversion module includes: The first calculation unit is used to utilize the formula Calculate the frequency domain radius of the improved generalized Gaussian window, the is the frequency domain radius; The second calculation unit is used to calculate the number of frequency sampling points and the frequency value of the central frequency point, the number of frequency sampling points is denoted as n _max , the frequency value of the central frequency point is denoted as f _n , and the central frequency point is Frequency sampling point; The third calculation unit is used to calculate the discrete radius of the improved generalized Gaussian window of each center frequency point as The improved generalized Gaussian window discrete radius for width _n (n), is rounding symbol; The fourth calculation unit is used to calculate the displacement distance of the frequency spectrum of each center frequency point as The center _n is the displacement distance; The fifth calculation unit is used to calculate the coverage of each frequency domain of the improved generalized Gaussian window, the coverage is characterized by f _start (n) and f _end (n), wherein f _start (0)=0, f _start (n+1)=centre _n (n)+width _n (n)+width _n (n+1), n=0,...,n _max -1, f _end (n)=f _start (n)+ 2width _n (n); The sixth calculation unit is used to calculate the FFT result of the electrical signal to be analyzed, and shift the FFT result to obtain the first FFT result, denoted as H[p], and the spectrum information in the first FFT result The DC result in is at the center, and the negative and positive frequency components are at the two sides, respectively; The seventh calculation unit is used to calculate the time domain radius of the improved generalized Gaussian window of each center frequency point as ; The eighth calculation unit is used to add the first FFT result to the displacement distance of the frequency spectrum of each center frequency point respectively, to obtain the second FFT result corresponding to each center frequency point, denoted as H[p+centre _n ( n)]; The ninth calculation unit is used to multiply the second FFT results of each center frequency point with the time domain radius of their respective improved generalized Gaussian windows to obtain the operation results of each center frequency point, and distribute each operation result according to the FFT spectrum The positions are arranged to obtain the arrangement result, and the IFFT operation is performed on the arrangement result to obtain the discrete improved generalized fast S-transform expression of the AC part. 11. The device according to claim 10, wherein the second calculation unit comprises: a first calculation subunit, configured to make the frequency of the nth frequency sampling point be f _n (n starts from 0), Then the relationship between two adjacent center frequencies: The second calculation subunit is used to make the first frequency center point be a DC point, that is, f ₀ =0, and according to Obtain the frequency value f _n of each center frequency point, n=0,...,n _max -1; The third calculation subunit is used to solve the inequality The number n _max of frequency sampling points is obtained, and the f _s is the sampling frequency of the electrical signal to be analyzed. 12. The device according to claim 9, wherein the decomposition module is specifically used to utilize the linear property S[h(t)]=S[x(t)+y(t) of the improved generalized fast S-transform ]=S[x(t)]+S[y(t)], when calculating a certain frequency component, only keep the part corresponding to the frequency component in the first result matrix, so that in the first result matrix The part corresponding to the frequency component other than the frequency component is assigned a value of 0; The h(t), x(t) and y(t) are signals to be analyzed and h(t)=x(t)+y(t). 13. The device according to claim 12, wherein the calculation module comprises: A separation unit is used to separate the reconstructed time-domain signal to obtain discrete signals of harmonic voltage and current, which are denoted as u _n [k] and i _n [k] respectively; The tenth calculation unit is used to base the formula The electric energy consumed per unit time of the reconstructed time-domain signal is calculated.