CN116593769A - High-precision electric energy calculation method with wide dynamic range - Google Patents
High-precision electric energy calculation method with wide dynamic range Download PDFInfo
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Abstract
The invention discloses a high-precision electric energy calculation method with a wide dynamic range, and belongs to the field of measuring electric variables. The method comprises the following steps: step one, sampling voltage and current by using more than 2 AD; according to the sampling data of the AD selected currently, performing electric energy calculation by using a digital filter; judging whether AD switching is needed or not in real time according to the sampling data, and selecting the switched AD; step two, if switching is needed, respectively estimating the amplitude and the phase of the current signal for two AD before and after switching; and thirdly, adjusting the buffer memory of the digital filter based on the amplitude and phase estimation of the two AD, inputting the selected sampling data of the AD after switching into the digital filter, completing the switching of the AD, and continuing to perform electric energy calculation. The invention reduces the operation amount and avoids the data delay problem caused by switching on the premise of not influencing the electric energy calculation.
Description
Technical Field
The invention belongs to the field of measuring electric variables, and particularly relates to an electric energy calculation method.
Background
In modern electric energy meter metering technology, AD is used as a sampling device, and its numerical resolution is a very important parameter. The bit number of AD is generally 16 bits or 24 bits, and the corresponding resolution is 1/2 respectively 16 、1/2 24 Due to AD samplingThe quantization noise exists in the process, and the actual effective bit number of the AD is smaller than 16 bits and 24 bits.
Because the resolution is limited, the metering range and the metering precision of the electric energy meter show a trend of eliminating each other, namely, the metering range is wide, the metering precision cannot be very high, and the metering range cannot be very wide.
One solution, which simultaneously combines metering range and metering accuracy, is to use multiple ADs, sample the voltage and current signals simultaneously, and use different gains for different current ranges AD. For example: using two ADs, the first AD using 8-fold gain, mainly handling currents less than 0.1 Ib; the second AD uses a 4-fold gain, mainly handling currents greater than 0.1 Ib. Note that: the two ADs are sampled simultaneously, the first AD may have a truncated peak under high current conditions and the second AD may have excessive noise under low current conditions. In the last metering step, the calculation result of which AD is used is determined according to the current magnitude.
However, the above solution has the following drawbacks: modern electric energy meters are mostly realized by programming digital devices, and digital filter technology is used. In the electric energy calculation process, intermediate data of the digital filter need to be cached, the digital filter needs to perform multiply-add operation for a plurality of times point by point, and larger operation resources can be consumed. If the data of two ADs are calculated simultaneously, the computational power of the digital device presents a significant challenge. Taking the current mainstream Cortex-M3 kernel 200MHz main frequency singlechip as an example, assuming that the number of sampling points per cycle is 256, the power frequency is 50Hz, and the basic fundamental wave and full wave electric energy calculation takes about 15ms per cycle (20 ms). If data of two ADs are calculated simultaneously, the theory takes 30ms, and the calculation cannot be completed.
If a sequential calculation mode is adopted, that is, only data of one AD is calculated, and calculation of current AD data is stopped when the AD needs to be switched, and data of another AD is used instead, the problem of metering delay exists. Because many digital filters are involved in the power calculation process, and the digital filter output needs a certain time to stabilize, the longest may reach the second order. The need to use the calculation data of the last AD before the digital filter output stabilizes necessarily causes delays in the metering data, which is not acceptable in some situations where high-speed calculation is required.
Disclosure of Invention
The invention provides a high-precision electric energy calculation method with a wide dynamic range, which aims to: the method solves the problems of large operand and delay of metering data in the multi-AD sampling.
The technical scheme of the invention is as follows:
a high-precision electric energy calculation method with wide dynamic range comprises the following steps:
step one, sampling voltage and current by using more than 2 AD; according to the sampling data of the AD selected currently, performing electric energy calculation by using a digital filter; judging whether AD switching is needed or not in real time according to the sampling data, and selecting the switched AD;
step two, if switching is needed, respectively estimating the amplitude and the phase of the current signal for two AD before and after switching;
and thirdly, adjusting the buffer memory of the digital filter based on the amplitude and phase estimation of the two AD, inputting the selected sampling data of the AD after switching into the digital filter, completing the switching of the AD, and continuing to perform electric energy calculation.
As a further improvement of the wide dynamic range high-precision electric power calculation method: in the first step, a buffer area is respectively set for each AD, and the buffer areas are used for storing sampling data of the AD.
As a further improvement of the wide dynamic range high-precision electric power calculation method: the method for judging whether AD switching is needed or not in real time according to the sampling data comprises the following steps: the weekly wave respectively calculates the RMS value of the primary current based on the sampling data in the buffer area; and judging whether AD channel switching is needed or not based on the current RMS value.
As a further improvement of the wide dynamic range high-precision electric power calculation method: the current RMS value calculating method comprises the following steps: for a certain AD, the sampling frequency is F S The frequency of the voltage signal is 50Hz, and the sampling point number N=F of each cycle is then S /50，C i And (3) representing the value of the ith sampling point of the current channel in the corresponding buffer area, wherein the current RMS value is as follows:
。
as a further improvement of the wide dynamic range high-precision electric power calculation method: the step of judging whether AD channel switching is needed based on the current RMS value is as follows: the gains of the current channels of the AD are different, all the AD are ordered from small to large according to the gains of the current channels, the serial number of the AD currently selected in the ordering is j, and the current RMS value is RMS j Gain of current channel G j The current RMS value of the previous AD in the sequence is RMS j-1 Gain of current channel G j-1 The current RMS value of the next AD in the sequence is RMS j+1 Gain of current channel G j+1 ；
If G j ×RMS j >T j_j+1 Or G j+1 ×RMS j+1 >T j_j+1 ，T j_j+1 Switching from the current AD to the j+1th AD for a switching threshold value between the j-th AD and the j+1th AD;
if G j ×RMS j ≤ T j-1_j Or G j-1 ×RMS j-1 ≤ T j-1_j ，T j-1_j Switching from the current AD to the j-1 AD for a switching threshold value between the j-1 AD and the j-1 AD;
if there is no previous or next adjacent AD in the ranking, no judgment calculation of forward or backward switching is performed.
As a further improvement of the wide dynamic range high-precision electric power calculation method: in the second step, for a certain AD, the specific method for estimating the amplitude and the phase of the current signal is as follows:
step a-1, the latest N current sampling values in the AD buffer area are taken out; n is the sampling point number of a cycle; the index value of the current sampling value is marked as: 0,1,2 … N-1;
step a-2, an input vector X and an output vector Y are established:
X=[0,1/F S ,1/2F S ,…,1/(N-1)F S ]；
Y=[C 0 , C 1 , C 2 ,…, C N-1 ]；
wherein X is the time index vector of the current sampling value, F S Is the sampling frequency; c (C) i Is the i sampling value;
step a-3, establishing a current signal model:
；
wherein t is time, a is a current value when I (t) is t, a is an amplitude, ω is an electrical angular velocity, and Φ is a phase when t=0; the amplitude A and the phase phi are values to be solved;
step a-4, setting an initial value: let the initial estimated value of phi be 0, and the initial estimated value of A be the maximum value of the absolute value of the element in the output vector Y;
step a-5, defining a loss function as follows:
；
wherein A is es And phi es The estimated values of the amplitude A and the phase phi are respectively; y is Y i_es Is to make the current estimated value A es And phi is substituted into the current signal model, and the ith element value X in the input vector X is calculated i As the actual t, an output estimated value is obtained: y is Y i_es = A es sin(ωX i +φ es )；Y i The i element value in the output vector Y;
the loss function is derived to obtain the estimated value A of the amplitude A and the phase phi es And phi es The gradients at the points are respectively:
；
a-6, defining a learning rate as alpha, an iteration termination threshold as epsilon, and carrying out iteration solution on an amplitude A and a phase phi:
step a-6-1, setting the current as the mth iteration, and setting the current amplitude A and the current amplitude AThe estimated values of the phase phi are A respectively es_m And phi es_m Will A es_m And phi es_m Substituting the current signal model, and then solving the current loss function value;
a step a-6-2, stopping iteration if the current loss function value is smaller than the iteration termination threshold epsilon, and leading the current A to be es_m And phi es_m As a solution to the amplitude A and phase phi; otherwise, executing the step a-6-3;
step a-6-3, according to the current A es_m And phi es_m Obtaining the corresponding gradient to obtain the next estimated value A es_m+1 And phi es_m+1 ：
；
The iteration then continues back to step a-6-1.
As a further improvement of the wide dynamic range high-precision electric power calculation method: in the third step, the digital filter includes a digital filter F1 and a digital filter F2, the sampled data is input into the digital filter F1, the instantaneous power value is obtained according to the output of the digital filter F1, and then the instantaneous power value is input into the digital filter F2, so as to obtain the RMS value of the power.
As a further improvement of the wide dynamic range high-precision electric power calculation method: and step three, if fundamental wave electric energy calculation is currently carried out, the buffer memory of the digital filter F1 is adjusted, otherwise, the buffer memory of the digital filter F1 is not adjusted.
As a further improvement of the wide dynamic range high-precision electric power calculation method: the method for adjusting the buffer memory of the digital filter F1 comprises the following steps: let the digital filter F1 be a K-stage filter, before the AD switch, the digital filter F1 will calculate and output the nth output value according to the nth input value, and then the output buffer vector of the current channel of the digital filter F1 is: o (O) I =[y I (n-1),y I (n-2),…,y I (n-K)]Wherein y is I (n-k) represents a previous kth output value of the digital filter F1 with respect to the current output value; input buffering of current channel of digital filter F1The storage vector is as follows: i I =[x I (n-1),x I (n-2),…,x I (n-K)]Wherein x is I (n-k) represents the previous kth input value of the digital filter F1 relative to the current input value;
when the AD is switched, if the amplitude solution values obtained by the AD before and after the switching in the amplitude and phase estimation process of the current signal are respectively A1 and A2, the output buffer vector of the current channel of the adjusted digital filter F1 is O I ’= O I XA 2/A1, the input buffer vector of the current channel of the adjusted digital filter F1 is I I ’= I I ×A2/A1；
After switching, the digital filter F1 is based on the new output buffer vector O I ' sum input cache vector I I ' and an nth input value x I (n) calculating an nth output value y I (n) and continuing to complete the calculation of the subsequent output value based on the subsequent input value.
As a further improvement of the wide dynamic range high-precision electric power calculation method: the method for adjusting the buffer memory of the digital filter F2 comprises the following steps: let the digital filter F2 be a K-stage filter, before the AD switch, the digital filter F2 will calculate and output the nth output value according to the nth input value, and then the output buffer vector of the digital filter F2 is: o (O) P =[y P (n-1),y P (n-2),…,y P (n-K)]Wherein y is P (n-k) represents a previous kth output value of the digital filter F2 with respect to the current output value; the input buffer vector of the digital filter F2 is: i P =[x P (n-1),x P (n-2),…,x P (n-K)]Wherein x is P (n-k) represents the previous kth input value of the digital filter F2 relative to the current input value;
when the AD is switched, the amplitude solving values obtained by the AD before and after the switching in the amplitude and phase estimation process of the current signal are respectively A1 and A2, and the output buffer vector of the adjusted digital filter F2 is O P ’= O P X A2/A1, the input buffer vector of the adjusted digital filter F2 is I P ’= I P ×A2/A1；
After switching, the digital filter F2 is based on the new output bufferVector O P ' sum input cache vector I P ' and an nth input value x P (n) calculating an nth output value y P (n) and continuing to complete the calculation of the subsequent output value based on the subsequent input value.
Compared with the prior art, the invention has the following positive effects:
(1) The invention only needs to calculate the data of one AD at the same time, realizes the real-time conversion of the data by calculation when the AD is switched, and can realize seamless connection by conversion of the data before and after the switching, thereby reducing the operation amount and avoiding the data delay problem caused by the switching on the premise of not influencing the calculation of the electric energy.
(2) The invention accurately calculates the gain change during the AD channel switching by using an iterative mode, and lays a foundation for carrying out coefficient conversion on the filter during the AD switching.
(3) According to the invention, the buffer memory of the filter is converted, so that output mutation caused by switching of sampling data is avoided, lossless switching is realized, the problems of precision mutation and unstable output are avoided, and the filter is not required to be stabilized.
Detailed Description
The following describes the technical scheme of the invention in detail:
for simplicity of explanation, in the embodiment, the voltage and the current are single phases, and the single-phase calculation method is easily generalized to three-phase calculation. Meanwhile, all cases where the AD number is greater than or equal to 2 are also within the protection scope of the invention.
A high-precision electric energy calculation method with wide dynamic range comprises the following steps:
step one, voltage and current are sampled using more than 2 ADs. And according to the sampling data of the AD selected currently, performing electric energy calculation by using a digital filter. And judging whether AD switching is needed or not in real time according to the sampling data, and selecting the switched AD.
Specifically, a buffer area is respectively set for each AD, and the buffer areas are used for storing sampling data of the AD. The depth of the data stored in the buffer areas is at least one week of data points, each buffer area contains data of two channels of voltage and current, the gains of the voltage channels of all AD are the same, and the gains of the current channels are different. Note that the sampled data of all ADs must be strictly synchronized. The method for realizing the synchronization of the plurality of AD data has simpler hardware proposal, uses the AD chips with the same model, and can realize the synchronous sampling of the AD by connecting the control pins of the AD chips to the pins of the same singlechip, and the detailed description is omitted here.
The method for judging whether AD switching is needed or not in real time according to the sampling data comprises the following steps: the weekly wave respectively calculates the RMS value of the primary current based on the sampling data in the buffer area; and judging whether AD channel switching is needed or not based on the current RMS value.
The current RMS value calculating method comprises the following steps: for a certain AD, the sampling frequency is F S The frequency of the voltage signal is 50Hz, and the sampling point number N=F of each cycle is then S /50，C i And (3) representing the value of the ith sampling point of the current channel in the corresponding buffer area, wherein the current RMS value is as follows:
。
the step of judging whether AD channel switching is needed based on the current RMS value is as follows: the gains of the current channels of the AD are different, all the AD are ordered from small to large according to the gains of the current channels, the serial number of the AD currently selected in the ordering is j, and the current RMS value is RMS j Gain of current channel G j The current RMS value of the previous AD in the sequence is RMS j-1 Gain of current channel G j-1 The current RMS value of the next AD in the sequence is RMS j+1 Gain of current channel G j+1 。
If G j ×RMS j >T j_j+1 Or G j+1 ×RMS j+1 >T j_j+1 ，T j_j+1 Switching from the current AD to the j+1th AD for a switching threshold value between the j-th AD and the j+1th AD;
if G j ×RMS j ≤ T j-1_j Or G j-1 ×RMS j-1 ≤ T j-1_j ，T j-1_j Switching from the current AD to the j-1 AD for a switching threshold value between the j-1 AD and the j-1 AD;
if there is no previous or next adjacent AD in the ranking, no judgment calculation of forward or backward switching is performed.
Taking 3 ADs as an example here, the switching threshold should be two, assuming T 1_2 、T 2_3 ，T 1_2 An AD sampling value corresponding to a current of 0.1Ib, T 2_3 An AD sample value corresponding to a current of 0.5Ib may be considered.
And step two, if switching is needed, respectively estimating the amplitude and the phase of the current signal for the two AD before and after switching.
Specifically, for an AD, the specific method for estimating the amplitude and phase of the current signal is:
step a-1, the latest N current sampling values in the AD buffer area are taken out; n is the sampling point number of a cycle; the index value of the current sampling value is marked as: 0,1,2 … N-1.
Step a-2, an input vector X and an output vector Y are established:
；
wherein X is the time index vector of the current sampling value, F S Is the sampling frequency; c (C) i Is the i-th sampled value taken.
Step a-3, establishing a current signal model:
；
wherein t is time, a is a current value when I (t) is t, a is an amplitude, ω is an electrical angular velocity, and Φ is a phase when t=0; the amplitude a and the phase phi are values to be solved.
Step a-4, setting an initial value: let the initial estimate of phi be 0 and the initial estimate of A be the maximum of the absolute value of the element in the output vector Y.
Step a-5, defining a loss function as follows:
；
wherein A is es And phi es The estimated values of the amplitude A and the phase phi are respectively; y is Y i_es Is to make the current estimated value A es And phi is substituted into the current signal model, and the ith element value X in the input vector X is calculated i As the actual t, an output estimated value is obtained: y is Y i_es = A es sin(ωX i +φ es )；Y i Is the i-th element value in the output vector Y.
The loss function is derived to obtain the estimated value A of the amplitude A and the phase phi es And phi es The gradients at the points are respectively:
；
and a step a-6, defining the learning rate as alpha, the iteration termination threshold as epsilon, and carrying out iteration solution on the amplitude A and the phase phi.
Step a-6-1, setting the current iteration as the mth iteration, wherein the estimated values of the current amplitude A and the phase phi are respectively A es_m And phi es_m Will A es_m And phi es_m Substituting the current signal model, and then obtaining the current loss function value.
A step a-6-2, stopping iteration if the current loss function value is smaller than the iteration termination threshold epsilon, and leading the current A to be es_m And phi es_m As a solution to the amplitude A and phase phi; otherwise, step a-6-3 is performed.
Step a-6-3, according to the current A es_m And phi es_m Obtaining the corresponding gradient to obtain the next estimated value A es_m+1 And phi es_m+1 ：
；
The iteration then continues back to step a-6-1.
And thirdly, adjusting the buffer memory of the digital filter based on the amplitude and phase estimation of the two AD, inputting the selected sampling data of the AD after switching into the digital filter, completing the switching of the AD, and continuing to perform electric energy calculation.
For digital filters, practical engineering applications are typically implemented using differential equations, and the general representation of the K-order filter is:
y(n)=a 1 y(n-1)+a 2 y(n-2)+…+a k y(n-K)+b 0 x(n)+b 1 x(n-1)+b 2 x(n-2)+…+b k x(n-K)；
where y (n) represents the nth output value of the filter, x (n) represents the nth input value of the filter, y (n-K) represents the upper K output values relative to the current output value, x (n-K) represents the upper K input values relative to the current input value, k=1, 2,3, …, K. a, a 1 ,a 2 ,a 3 ,…,a K ,b 1 ,b 2 ,b 3 ,…,b K Representing the filter coefficients.
The output buffer vector of the filter is expressed as:
O=[y(n-1),y(n-2),…,y(n-K)]；
the input buffer vector of the filter is expressed as:
I=[x(n-1),x(n-2),…,x(n-K)]；
the filter coefficient vectors M and N are:
M=[a 1 ,a 2 ,a 3 ,…,a K ], N=[b 1 ,b 2 ,b 3 ,…,b K ]；
the nth output of the filter can be expressed as: y (n) =om+in.
In the power calculation, the digital filter includes a digital filter F1 and a digital filter F2. Typically, both are low pass filters. The cut-off frequency of the digital filter F1 is 1.5 times the power frequency, and the filter type can be considered as a butterworth low-pass filter of order 6. The digital filter F2 is used for filtering out the frequency content except the direct current component in the instantaneous power signal, and the direct current component of the instantaneous power is the RMS value of the power. In general, to consider both the filtering effect and the filter response time, the parameters of the digital filter F2 can be considered as: the second-order chebyshev type II low-pass digital filter has a filter cut-off frequency of 1.5 times of the power frequency. Since the instantaneous power frequency is 2 times the power frequency and the cut-off frequency is typically 0.75 times the instantaneous power frequency, the cut-off frequency of the filter is 0.75x2=1.5 times the power frequency.
The sampled data is input into the digital filter F1, an instantaneous power value is obtained according to the output of the digital filter F1, and then the instantaneous power value is input into the digital filter F2, so as to obtain the RMS value of the power.
Specifically, if fundamental wave power calculation is currently performed, the buffer memory of the digital filter F1 is adjusted, otherwise, the buffer memory of the digital filter F1 is not adjusted.
The method for adjusting the buffer memory of the digital filter F1 comprises the following steps: let the digital filter F1 be a K-stage filter, before the AD switch, the digital filter F1 will calculate and output the nth output value according to the nth input value, and then the output buffer vector of the current channel of the digital filter F1 is: o (O) I =[y I (n-1),y I (n-2),…,y I (n-K)]Wherein y is I (n-k) represents a previous kth output value of the digital filter F1 with respect to the current output value; the input buffer vector of the current channel of the digital filter F1 is: i I =[x I (n-1),x I (n-2),…,x I (n-K)]Wherein x is I (n-k) represents the previous kth input value of the digital filter F1 relative to the current input value.
When the AD is switched, if the amplitude solution values obtained by the AD before and after the switching in the amplitude and phase estimation process of the current signal are respectively A1 and A2, the output buffer vector of the current channel of the adjusted digital filter F1 is O I ’= O I XA 2/A1, the input buffer vector of the current channel of the adjusted digital filter F1 is I I ’= I I ×A2/A1。
After switching, the digital filter F1 is based on the new output buffer vector O I ' sum input cache vector I I ' and an nth input value x I (n) calculating an nth output value y I (n) and continuing to complete the calculation of the subsequent output value based on the subsequent input value.
Note that: for the voltage channels, since the sampling is synchronous and the gains of the voltage channels are the same, when the AD channel switching occurs, the buffer vectors of the voltage channels do not need to be switched.
The instantaneous power value can be calculated by the current output value u (n) of the digital filter F1 voltage channel and the current output value of the current channel i (n): p (n) =u (n) ×i (n).
The method for adjusting the buffer memory of the digital filter F2 comprises the following steps: let the digital filter F2 be a K-stage filter, before the AD switch, the digital filter F2 will calculate and output the nth output value according to the nth input value, and then the output buffer vector of the digital filter F2 is: o (O) P =[y P (n-1),y P (n-2),…,y P (n-K)]Wherein y is P (n-k) represents a previous kth output value of the digital filter F2 with respect to the current output value; the input buffer vector of the digital filter F2 is: i P =[x P (n-1),x P (n-2),…,x P (n-K)]Wherein x is P (n-k) represents the previous kth input value of the digital filter F2 relative to the current input value.
When the AD is switched, the amplitude solving values obtained by the AD before and after the switching in the amplitude and phase estimation process of the current signal are respectively A1 and A2, and the output buffer vector of the adjusted digital filter F2 is O P ’= O P X A2/A1, the input buffer vector of the adjusted digital filter F2 is I P ’= I P ×A2/A1。
After switching, the digital filter F2 is based on the new output buffer vector O P ' sum input cache vector I P ' and an nth input value x P (n) calculating an nth output value y P (n) and continuing to complete the calculation of the subsequent output value based on the subsequent input value. The output value of the digital filter F2 is the RMS value P of the power RMS . To further improve the stability of the power, it is also possible to consider an averaging operation of the output value of the digital filter F2.
Further, assuming that the power value between two adjacent sampling points is unchanged, according to P RMS And sampling frequency F S The power value for each sampling interval can be found: e=p RMS /F S 。
Claims (10)
1. A high-precision electric energy calculation method with wide dynamic range is characterized in that:
step one, sampling voltage and current by using more than 2 AD; according to the sampling data of the AD selected currently, performing electric energy calculation by using a digital filter; judging whether AD switching is needed or not in real time according to the sampling data, and selecting the switched AD;
step two, if switching is needed, respectively estimating the amplitude and the phase of the current signal for two AD before and after switching;
and thirdly, adjusting the buffer memory of the digital filter based on the amplitude and phase estimation of the two AD, inputting the selected sampling data of the AD after switching into the digital filter, completing the switching of the AD, and continuing to perform electric energy calculation.
2. The wide dynamic range high precision power calculation method as set forth in claim 1, wherein: in the first step, a buffer area is respectively set for each AD, and the buffer areas are used for storing sampling data of the AD.
3. The wide dynamic range high precision power calculation method as set forth in claim 2, wherein: the method for judging whether AD switching is needed or not in real time according to the sampling data comprises the following steps: the weekly wave respectively calculates the RMS value of the primary current based on the sampling data in the buffer area; and judging whether AD channel switching is needed or not based on the current RMS value.
4. A wide dynamic range high precision electrical energy computing method as set forth in claim 3, wherein: the current RMS value calculating method comprises the following steps: for a certain AD, the sampling frequency is F S The frequency of the voltage signal is 50Hz, and the sampling point number N=F of each cycle is then S /50，C i And (3) representing the value of the ith sampling point of the current channel in the corresponding buffer area, wherein the current RMS value is as follows:。
5. a wide dynamic range high precision electrical energy computing method as set forth in claim 3, wherein: the step of judging whether AD channel switching is needed based on the current RMS value is as follows: the gains of the current channels of the AD are different, all the AD are ordered from small to large according to the gains of the current channels, the serial number of the AD currently selected in the ordering is j, and the current RMS value is RMS j Gain of current channel G j The current RMS value of the previous AD in the sequence is RMS j-1 Gain of current channel G j-1 The current RMS value of the next AD in the sequence is RMS j+1 Gain of current channel G j+1 ；
If G j ×RMS j >T j_j+1 Or G j+1 ×RMS j+1 >T j_j+1 ，T j_j+1 Switching from the current AD to the j+1th AD for a switching threshold value between the j-th AD and the j+1th AD;
if G j ×RMS j ≤ T j-1_j Or G j-1 ×RMS j-1 ≤ T j-1_j ，T j-1_j Switching from the current AD to the j-1 AD for a switching threshold value between the j-1 AD and the j-1 AD;
if there is no previous or next adjacent AD in the ranking, no judgment calculation of forward or backward switching is performed.
6. The wide dynamic range high precision power calculation method as set forth in claim 2, wherein: in the second step, for a certain AD, the specific method for estimating the amplitude and the phase of the current signal is as follows:
step a-1, the latest N current sampling values in the AD buffer area are taken out; n is the sampling point number of a cycle; the index value of the current sampling value is marked as: 0,1,2 … N-1;
step a-2, an input vector X and an output vector Y are established:
X=[0,1/F S ,1/2F S ,…,1/(N-1)F S ]；
Y=[C 0 , C 1 , C 2 ,…, C N-1 ]；
wherein X is the time index vector of the current sampling value, F S Is the sampling frequency; c (C) i Is the i sampling value;
step a-3, establishing a current signal model: i (t) =asin (ωt+Φ);
wherein t is time, a is a current value when I (t) is t, a is an amplitude, ω is an electrical angular velocity, and Φ is a phase when t=0; the amplitude A and the phase phi are values to be solved;
step a-4, setting an initial value: let the initial estimated value of phi be 0, and the initial estimated value of A be the maximum value of the absolute value of the element in the output vector Y;
step a-5, defining a loss function as follows:
;
wherein A is es And phi es The estimated values of the amplitude A and the phase phi are respectively; y is Y i_es Is to make the current estimated value A es And phi is substituted into the current signal model, and the ith element value X in the input vector X is calculated i As the actual t, an output estimated value is obtained: y is Y i_es = A es sin(ωX i +φ es )；Y i The i element value in the output vector Y;
the loss function is derived to obtain the estimated value A of the amplitude A and the phase phi es And phi es The gradients at the points are respectively:
;
a-6, defining a learning rate as alpha, an iteration termination threshold as epsilon, and carrying out iteration solution on an amplitude A and a phase phi:
step a-6-1, setting the current iteration as the mth iteration, wherein the estimated values of the current amplitude A and the phase phi are respectively A es_m And phi es_m Will A es_m And phi es_m Substituted into current signalIn the number model, then the current loss function value is calculated;
a step a-6-2, stopping iteration if the current loss function value is smaller than the iteration termination threshold epsilon, and leading the current A to be es_m And phi es_m As a solution to the amplitude A and phase phi; otherwise, executing the step a-6-3;
step a-6-3, according to the current A es_m And phi es_m Obtaining the corresponding gradient to obtain the next estimated value A es_m+1 And phi es_m+1 ：
;
The iteration then continues back to step a-6-1.
7. The wide dynamic range high precision power calculation method as set forth in claim 2, wherein: in the third step, the digital filter includes a digital filter F1 and a digital filter F2, the sampled data is input into the digital filter F1, the instantaneous power value is obtained according to the output of the digital filter F1, and then the instantaneous power value is input into the digital filter F2, so as to obtain the RMS value of the power.
8. The wide dynamic range high precision power calculation method as set forth in claim 7, wherein: and step three, if fundamental wave electric energy calculation is currently carried out, the buffer memory of the digital filter F1 is adjusted, otherwise, the buffer memory of the digital filter F1 is not adjusted.
9. The wide dynamic range high precision power calculation method as set forth in claim 7 or 8, wherein: the method for adjusting the buffer memory of the digital filter F1 comprises the following steps: let the digital filter F1 be a K-stage filter, before the AD switch, the digital filter F1 will calculate and output the nth output value according to the nth input value, and then the output buffer vector of the current channel of the digital filter F1 is: o (O) I =[y I (n-1),y I (n-2),…,y I (n-K)]Wherein y is I (n-k) represents a digital filterF1 is the kth previous output value relative to the current output value; the input buffer vector of the current channel of the digital filter F1 is: i I =[x I (n-1),x I (n-2),…,x I (n-K)]Wherein x is I (n-k) represents the previous kth input value of the digital filter F1 relative to the current input value;
when the AD is switched, if the amplitude solution values obtained by the AD before and after the switching in the amplitude and phase estimation process of the current signal are respectively A1 and A2, the output buffer vector of the current channel of the adjusted digital filter F1 is O I ’= O I XA 2/A1, the input buffer vector of the current channel of the adjusted digital filter F1 is I I ’= I I ×A2/A1；
After switching, the digital filter F1 is based on the new output buffer vector O I ' sum input cache vector I I ' and an nth input value x I (n) calculating an nth output value y I (n) and continuing to complete the calculation of the subsequent output value based on the subsequent input value.
10. The wide dynamic range high precision power calculation method as set forth in claim 7 or 8, wherein: the method for adjusting the buffer memory of the digital filter F2 comprises the following steps: let the digital filter F2 be a K-stage filter, before the AD switch, the digital filter F2 will calculate and output the nth output value according to the nth input value, and then the output buffer vector of the digital filter F2 is: o (O) P =[y P (n-1),y P (n-2),…,y P (n-K)]Wherein y is P (n-k) represents a previous kth output value of the digital filter F2 with respect to the current output value; the input buffer vector of the digital filter F2 is: i P =[x P (n-1),x P (n-2),…,x P (n-K)]Wherein x is P (n-k) represents the previous kth input value of the digital filter F2 relative to the current input value;
when the AD is switched, the amplitude solving values obtained by the AD before and after the switching in the amplitude and phase estimation process of the current signal are respectively A1 and A2, and the output buffer vector of the adjusted digital filter F2 is O P ’= O P X A2/A1, adjustmentThe input buffer vector of the digital filter F2 is I P ’= I P ×A2/A1；
After switching, the digital filter F2 is based on the new output buffer vector O P ' sum input cache vector I P ' and an nth input value x P (n) calculating an nth output value y P (n) and continuing to complete the calculation of the subsequent output value based on the subsequent input value.
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