CN112526208B - Electric energy quality measurement system and method based on high-coupling-degree iteration model - Google Patents

Abstract

A power quality measurement system and method based on a high-coupling iterative model are based on a programmable digital logic platform and are used for measuring the power quality of multichannel input signals. The rapid iterative computation module tightly integrates four complex operations of sine solving, arcsine solving, division dividing and square root opening which are necessary in the electric energy quality computation process into one module through a high-coupling program algorithm, and different operations are switched through operation types, so that the expenditure of logic resources is effectively reduced. The main calculation module designs digital logic of recursive DFT, recursive average filtering, synchronous sampling, harmonic amplitude calculation, positive and negative zero calculation and state machine control, and realizes calculation of power quality and output result by calling the iterative calculation module. The invention is used for complex operation in the multichannel electric energy quality measurement and calculation process, has the advantages of simple external interface, rich operation result, small application space limitation and good multifunctional intelligent integration optimization, and can effectively reduce the consumption of operation resources of a processor.

Description

Electric energy quality measurement system and method based on high-coupling-degree iteration model

Technical Field

The invention relates to the field of power quality measurement, in particular to a power quality measurement system and method based on a high-coupling iterative model.

Background field

With the development of long-distance direct-current transmission, the application range of the micro-grid is expanded, the micro-grid has wide application of new energy sources with volatility, randomness and intermittence, and the electric power quality of the power grid is deteriorated due to the fact that the power grid structure is changed, the load characteristics tend to be complex due to the fact that the electric vehicles, charging piles of the electric vehicles, the operation of charging stations and other factors are increased increasingly. The reduction of the electric energy quality reduces the service life of household appliances and the life quality of residents; the heavy load can interfere with the control circuit, which in turn causes serious problems such as product quality degradation, even power failure, production stoppage, etc. The deterioration of the electric energy quality also can cause the problems of increasing the line loss, reducing the service life of equipment such as a transformer, and the like, causing malfunction of relay protection equipment caused by electromagnetic interference, and the like, which has negative effects on the safe and stable operation of the power system.

The monitoring and analysis of the electric energy quality are beneficial to evaluating the running state of the power grid, improving and managing the power grid, defining the responsibility of both power supply and power consumption parties and solving the contradiction and dispute of both power supply and power consumption parties, and meanwhile, the electric energy quality monitoring problem is a research hotspot of the general relation of the electric power departments and related scientific researches. Currently, there is still a lack of a generally accepted and consistent measurement and evaluation algorithm for transient power quality disturbances, which combines rapidity and accuracy. The problem of compression, analysis and utilization of massive power quality data by a large power grid still needs further research. The index parameters of the electric energy quality are few, and the comprehensive evaluation problem of the multi-index electric energy quality is also urgently needed to be further broken through at present of rapid development of artificial intelligence.

The power quality monitoring device is an actual carrier for power quality detection, and has undergone four stages of development from a simple instrument, an analog circuit-based, a large-scale integrated circuit, and an intelligent instrument based on virtual technology. In the power quality calculation, the optimization problem of complex calculation is not bypassed. DFT-based power quality computation is most widely used. In the calculation process, a large number of complex algorithms such as square root solving, arcsine solving, sine solving and division solving are involved, and an embedded processor is adopted for carrying out the calculation, so that a large amount of calculation resources of a computer processor are required to be occupied. If the multi-channel requirement exists, the operation burden is more serious; if a processor with stronger computing capability is selected, hardware cost and equipment volume are likely to be increased, such as special application occasions like some ship power monitoring systems, not only are very severe restrictions on the equipment volume, but also higher requirements on the functions of the power quality detection equipment are also provided. The power quality monitoring equipment not only has the function of measurement, but also often needs to take into account the functions of data transmission, monitoring the safe running state judgment, protection control and the like of the regional power grid. If the power quality measurement algorithm does not perform optimization processing, occupied computing resources are more, and interaction transmission of intermediate data during operation needs to be frequently occupied and interrupted, so that not only can data flow transmission be blocked, but also the complexity of data processing is further increased, the whole monitoring system is easily unstable, and other functions of the whole monitoring system are affected.

Disclosure of Invention

Aiming at the problem that a complex operation model is not optimized in the electric energy quality measurement and calculation process, the electric energy quality measurement system and method based on the high-coupling iterative model are designed, and are used for solving the problems that a large number of complex algorithms such as solving square root, arcsine, sine and division are involved in the electric energy quality measurement of a multi-channel alternating current-direct current signal, the calculation is carried out by an embedded processor, a large amount of operation resources of the computer processor are occupied, the interactive transmission of intermediate data during the operation is frequently interrupted, the transmission of data streams is blocked, the complexity of data processing is increased, and the instability of the whole monitoring system is easily caused.

The technical scheme of the application is as follows: the utility model provides a power quality measuring method based on a high coupling degree iterative model, which is based on a programmable digital logic platform and is used for measuring parameters of power quality of a multichannel AC/DC electric signal, and comprises the following steps: and collecting the related data of the electric energy, sampling the data, calculating the electric energy based on the sampled data, and outputting the calculated electric energy quality result.

In any one of the above technical solutions, further, the method includes:

S1: collecting analog voltage u and/or current i signals by utilizing a plurality of parallel channels, wherein the signals are sequentially transmitted to a power quality calculation module through AD conversion and AD driving of a programmable logic device, the AD conversion is used for converting the input analog voltage u and/or current i signals of the plurality of parallel channels into digital voltage u and/or current i signals, and the AD driving is used for driving and transmitting digital voltage u and/or current i signal data to the power quality calculation module;

s2: in the power quality calculation module, the input digital voltage and/or current signals are converted into 2kHz data streams after the 24 channels of 100kHz sampling serial data streams are subjected to data sampling by the main calculation module; for an alternating current signal with the rated frequency of 50Hz, sampling 1 cycle wave by a sampling rate of 2kHz for 40 sampling points, reading sampling data by a calculation model of a main calculation module, continuously and circularly storing the sampling data in a RAM, performing basic operation once by a recursive DFT (discrete Fourier transform) for each 1kHz sampling point to obtain phasors a+bj of 24 channels, and circularly storing continuous sampling values corresponding to 90 points for each channel to serve as a data stream calculated by the main calculation module; the vector value a+bj of each channel is subjected to evolution and arcsine through an iterative calculation module to obtain amplitude c and phase P, phase difference deltap is obtained through phase difference calculation, and deltap is obtained through multi-order average filtering calculation _avg A frequency f;

setting the duration of 1Cyc for every 50 sampling points with continuous 2kHz frequency, synchronously sampling the data stream obtained by sampling 24 channels at 2kHz with frequency f, and resampling the signal X on the basis of every 1kHz operation _r Performing high-precision DFT calculation once to obtain the DC amplitude value c of each channel of 24 channels ₀ Fundamental phasor a ₁ +b _1j And 2-19 harmonic vector a ₂ +b _2j To a ₁₉ +b _19j Obtaining fundamental wave amplitude c through open square ₁ And 2-19 harmonic vector magnitude c ₂ To c ₁₉ The method comprises the steps of carrying out a first treatment on the surface of the Every 8 Cyc, the sum of harmonic amplitude of the same frequency of each channel in 24 channels is added up and c _{2_s1} 、c _{3_s1} 、...c _{19_s1} Respectively carrying out an average operation, and respectively obtaining harmonic amplitude accumulated sum c by accumulated summation after squaring _{2_sum} 、c _{3_sum} 、...c _{19_sum} And storing; negative sequence imbalance summation e for three-phase channels _{2_s1} Zero sequence imbalance sum e _{0_s1} Carrying out one-time averaging operation, squaring, accumulating and summing, and storing;

the direct current amplitude addition is performed once every 15bounch time periods 3s (c _{0_sum} ) Sum of fundamental wave amplitude accumulation (c) _{1_sum} ) Frequency accumulated sum (f) _{_sum} ) Carrying out average operation to obtain a power quality calculation result;

to accumulate the sum (e _{2_sum} ) Zero sequence imbalance sum (e) _{0_sum} ) The cumulative summed dc magnitude (c _{0_sum} ) Fundamental frequency (f) _{_sum} ) And the fundamental amplitude c1_sum are arithmetically averaged over 120 Cyc cycles, and then the harmonic amplitude is summed up (c _{2_sum} 、c _{3__sum} 、...c _{19_ssum} ) Root mean square operation is carried out and then the fundamental wave amplitude c is compared _1R Obtaining the amplitude (c) of each harmonic _2R 、c _3R 、...c _19R ) Harmonic content (HR) ₂ 、HR ₃ 、...HR ₁₉ ) The root mean square of the sum of the squares of the amplitude of each harmonic is used for obtaining the amplitude c of the fundamental wave _1R The ratio of (2) to obtain the total fundamental wave distortion rate THR;

the main calculation module carries out high-coupling iterative calculation on the vector value and the amplitude of each signal as well as the solution of the input operation data a, b and c and the required operation types 1 square, 2 arcsine, 3 sine and 4 division thereof to the iterative calculation module, reprocesses the calculation result fed back by the iterative calculation module to obtain the amplitude c, the phase P and the frequency f of each component of the signal, and carries out operation by the main calculation module to obtain the total fundamental wave distortion rate THR of the electric energy quality calculation result; cumulative sum of negative sequence imbalances e _{2_sum} Sum zero sequence imbalance cumulative sum e _{0_sum} The arithmetic square root of 15 bounch cycles respectively gives the negative sequence imbalance degree e _2R And zero sequence imbalance degree e _0R Outputting to a programmable logic device;

s3: the output power quality measurement result is externally communicated and output through the programmable logic device.

In any of the above solutions, further, step S2 includes:

The iterative calculation module comprises the following iterative steps:

s221: initializing signal data according to the operation type transmitted by the main calculation module;

s222: the iterative computation module performs iterative computation according to the operation type;

s223: selecting a subsequent calculation module according to the operation type;

s224: and outputting a calculation result.

In any of the above solutions, further, step S22 includes: iterative calculation module the iterative calculation module step

S221: initializing signal data according to the operation type transmitted by the main calculation module;

s222: the iterative computation module performs iterative computation according to the operation type;

s223: carrying out subsequent conversion treatment according to the operation type;

s224: and outputting a calculation result.

In any of the above embodiments, further, step S222 includes:

and carrying out at least three identical iterative calculation models with different iterative times through the operation data of the iterative calculation module, wherein the solving process of the iterative method comprises the following steps:

iteration 1, let u _n＞ u _0＞0 Wherein u is _n And (3) rounding the values of the power quality data related to the iterative calculation type and the calculation process of the iterative calculation module.

n is an integer not less than 3;

Establishing array A ₁ In order to achieve this, the first and second,

A ₁ ＝[u ₀ u ₀ +Δs u ₀ +2·Δs … u ₀ +n·Δs]

＝[u ₀ u ₁ u ₂ … u _n ]

if the target value a and A ₁ The numerical value of the relation is that,

f(u _i )<a<f(u _i+1 )

and the function f is in interval [ u ] ₀ ，u _n ]For a monotonically increasing function, determining the numerical range of result as:

u _i <result<u _i+1 ，0<i<n

iteration 2, let u ₀ ＝u _i And u _n ＝u _i+1

Obtaining an array A ₂ Is that

A ₂ ＝[u _i u _i +Δs u _i +2·Δs … u _i+1 ]，0<j<n＝[u _i +v ₀ u _i +v ₁ u _i +v ₂ … u _i +v _n ]

If the target value a and A ₂ The numerical value of the relation is that,

f(u _i +v _j )<a<f(u _i +v _j+1 )

and the function f is in interval [ u ] ₀ ,u _n ]A more accurate result range is the monotonically increasing function:

u _i +v _j <result<u _i +v _j+1

after the 3 rd iteration, a more accurate numerical range of result is obtained:

u _i +v _j +w _k <result<u _i +v _j +w _k+1 ，0<k<n

output result is approximately equal to u _i +v _j +w _k The result is a solution of the function f (result) =a.

In any of the above embodiments, further, step S223 includes: the operation type is selected and different functions f (result) are switched to solve through the operation type input and state selection logic of the iterative calculation module,

when the operation type input is 1SQRT (square of opening), the result1 is obtained, and the result is closest to a; the final calculation result is result=result;

when the operation type input is 2ASIN (arcsine), the result2 is obtained, so that sin (result) is closest to a; if a and/or b are not 0 and are not equal, exchanging the values of a and b if a is less than b, and obtaining a phase result after iterative calculation, wherein the result=90-result is the final arcsine calculation result; otherwise, the final calculation result is that,

When the operation type input is 3SIN (sine), obtaining a result3, and enabling arcsin (result) to be closest to a; the final result of the calculation is that,

when the operation type input is 4DIV (division), obtaining a result4, and enabling result×b to be closest to a; the final calculation result is result=i ₀ ·10 ⁵ +i ₁ ·10 ⁴ +i ₂ ·10 ³ +i ₃ ·10 ² +i ₄ ·10 ¹ +i ₅ 。

In any of the above technical solutions, further, the calculation process of the main calculation module divides the calculation of the main calculation module into three processes of basic operation, data calculation and power quality calculation results respectively with a cycle period of 1Cyc small cycle period per 50 consecutive 2kHz sampling points, a cycle period of 1bounch single cycle period per 8Cyc consecutive 2kHz sampling points, and a cycle period of 3s per 15bounch corresponding time.

In any of the above technical solutions, further, wherein the calculation result of the basic operation is stored in a RAM of the power quality module, and based on a recursive DFT algorithm, the calculation steps thereof are,

Stcp_1：

Step_2：

Step_3：

Step_4：

Step_5：

/>

Step_6：

5t8p_7：

g_c is the cosine value reduced by n times, g_s is the sine value reduced by n times, m_a ' is the vector of the g_c sampling point amplified by m times according to step_2, m_b ' is the vector of the g_s sampling point amplified by m times according to step_2, c is the signal amplitude, θ ' is the current signal phase, θ _old′ For the recursion of the previously input signal phase, f is the signal frequency.

In any of the above technical solutions, further, the recursive DFT algorithm further includes a recursive mean filtering algorithm, and the calculating steps are:

first order filtering

Second order filtering

……

k-order filtering

Wherein SUM ₁ …SUM _k Respectively, the k-order recursive average filtering result, A _k (n+1) is the n+1 value after the n value of the k-order recursive mean filter band, A _k 1 is the 1 st value (k.ltoreq.n) of the k-th order recursive mean filter band.

The application also provides a power quality measurement system based on the high-coupling-degree iteration model, which is characterized in that the power quality measurement method of the high-coupling-degree iteration model is realized when the computer program is executed by a processor, the power quality measurement system of the high-coupling-degree iteration model comprises one or more programmable digital logic platforms, one or more programmable digital logic platforms comprises an iteration calculation module, a calculation module, digital selection logic, a multiplier, a RAM, a ROM, an input and output interface and one or more AD conversion modules, and the power quality measurement system comprises the one or more programmable digital logic platforms, wherein the one or more programmable digital logic platforms comprise an iteration calculation module, a calculation module, digital selection logic, a multiplier, a RAM, a ROM, an input and output interface and one or more AD conversion modules which are connected internally.

The beneficial effects of this application are:

1. the invention tightly integrates the four operations of sine, arcsine, division and square opening necessary in the electric energy quality calculation, and the operation types are switched only through different input values, so that the design greatly multiplexes the digital logic, and the cost of logic resources is effectively reduced.

2. The invention is used for complex operation in the multichannel power quality measurement and calculation process, has the requirement of multiple channels, solves the complex operation problem in the multichannel power quality measurement and calculation process, has less occupied logic resources, meets the requirement of multiple channel operation, realizes the measurement of the power quality of multichannel input signals, has simple external interface and rich operation result, can effectively reduce the consumption of the operation resources of a processor, saves soft and hard resources, can be used for designing higher-level analysis functions, improves the intelligent degree of an instrument, and has good multifunctional intelligent integration optimization.

3. The power quality measurement system and the power quality measurement method designed by the invention have the advantages of less occupied calculation resources, less frequent occupied interruption during the interactive transmission of intermediate data during operation, avoiding the blockage caused by the data stream transmission during the calculation, greatly reducing the complexity of data processing and enhancing the stability of the whole monitoring system.

4. The system and the method for measuring the electric energy quality of the high-coupling iterative model improve the calculation performance of a processor by optimizing the digital logic design and the multiplexing method of the digital logic design in the programmable logic device of the electric energy quality measuring algorithm, have small application space limit, and can be applied to application occasions with very severe limit on the volume of equipment such as ship electric power monitoring.

Drawings

FIG. 1 is a simplified block diagram of a power quality measurement module based on high coupling digital logic according to the present application;

FIG. 2 is a computational flow diagram of an iterative computation module according to an embodiment of the present application;

FIG. 3 is an arcsine function calculation preprocessing partition map according to an embodiment of the present application;

FIG. 4 is a multi-channel power quality calculation timing diagram according to an embodiment of the present application;

FIG. 5 is a flowchart of basic calculation in the power quality calculation step according to an embodiment of the present application;

FIG. 6 is a high precision DC, AC, harmonic component calculation flow chart according to an embodiment of the present application;

FIG. 7 is a flow chart of the accumulation operation per Cyc for amplitude and frequency in accordance with an embodiment of the present application;

FIG. 8 is a flowchart of a squaring accumulation operation per 8Cyc for harmonic amplitudes in an embodiment according to the present application;

FIG. 9 is a flow chart of an accumulation per Cyc imbalance operation in accordance with one embodiment of the present application;

FIG. 10 is a flow chart of zero sequence imbalance and negative sequence imbalance accumulation operations in an embodiment of the present application;

fig. 11 is a flow chart of power quality measurement output calculation in accordance with one embodiment of the present application.

Detailed Description

The invention mainly aims at solving the measurement problem of the electric energy quality, designs an electric energy quality measurement method based on high-coupling digital logic, is based on a programmable digital logic platform, is used for solving the problem that a complex operation model is not optimized in the electric energy quality measurement and calculation process of a multi-channel alternating-current/direct-current signal, and solves the problem that the complex algorithm of solving square root, arcsine, sine and division is involved in the electric energy quality measurement of the multi-channel alternating-current/direct-current signal, the calculation is carried out in an embedded processor, a large amount of operation resources of a computer processor are occupied, the interactive transmission of intermediate data is required to frequently occupy interruption, the transmission of data flow is blocked and the complexity of data processing is increased, and the whole monitoring system is easy to be unstable.

The algorithm of the electric energy quality measurement model designed by the application mainly comprises a main calculation module and an iterative calculation module, and a high-coupling iterative calculation module is designed by depending on a programmable logic device, wherein the high-coupling iterative calculation module is digital logic in the programmable logic device, four operations of sine, arcsine, division and square opening which are necessary in the calculation of electric energy quality measurement are tightly integrated, and the operation types are switched only through input quantity, so that the design greatly multiplexes the digital logic, and the cost of logic resources is effectively reduced.

On the basis, digital logic such as recursive DFT, recursive average filtering, synchronous sampling, harmonic calculation, positive and negative zero sequence calculation, state control and the like is integrated in the main logic, so that the measurement and output of the electric energy quality of the multichannel input signals are realized.

Therefore, the complex operation in the power quality measurement model algorithm is optimally designed, so that the resource consumption can be reduced, the cost of the power quality monitoring equipment system resource can be reduced, the volume of the power quality monitoring equipment can be reduced, the saved soft and hard resources can be used for designing higher-level analysis functions, the intelligent degree of the instrument can be improved, and the power quality measurement model algorithm has great significance in application.

In order that the above-recited objects, features and advantages of the present application will be more clearly understood, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, however, the present application may be practiced otherwise than as described herein, and thus the scope of the present application is not limited to the specific embodiments disclosed below.

The iterative computation module of one embodiment of the principles of the iterative computation module of the present application is shown in fig. 2, where the iterative computation module is digital logic in a programmable logic device, and is used for performing four complex operations of sine, arcsine, division, and square of opening, which are necessary in power quality computation. For the four problems, an iterative calculation mode is adopted, and because the four problems have similar structures, high coupling integration is performed, and resource multiplexing is performed as much as possible, so that the purpose of reducing the consumption of ROM, RAM and digital logic is achieved.

For the calculation problems of open Square (SQRT), arcsine (ASIN), sine (SIN), division (DIV), the problem is described as: solving result, bringing into the corresponding function such that f (result) is closest to the target value a.

Further specifically, for solving the square root problem (SQRT, i.e., solving

) The problem can be described as: result is found such that result×result is closest to a.

For solving the arcsine problem (ASIN, i.e., solving result=arcsin (a)), the problem can be described as: result is obtained so that sin (result) is closest to a.

For solving a sine problem (SIN), i.e., result=sin (a)), the problem can be described as: result was found to be the closest to a for arcsin (result).

For solving the division problem (DIV, i.e., result=a/b), the problem can be described as: result is calculated such that result×b is closest to a.

After the above description is made for the problem SQRT, ASIN, SIN, DIV, the iterative method can be used for solving. The general process is as follows:

iteration 1, let u _n＞ u _0＞0 ，

n is an integer not less than 3;

u ₀ and u _n The values of (2) are related to the type of calculation and the range of minimum and maximum values that may be involved in the calculation process, respectively.

In practical design, since the number of bits of the AD is limited, the calculation module is not intended to solve the calculation problem of all numbers in plus or minus infinity. But rather to solve the data calculation problem that the calculation does not exceed the maximum calculation range. u (u) _n The value of (2) is a little greater than or equal to the possible maximum value in the calculation process, and the data range, the precision and the iteration algebra are taken into consideration.

Establishing array A ₁ For let u _n＞ u _0＞0 ，

A ₁ ＝[u ₀ u ₀ +Δs u ₀ +2·Δs … u ₀ +n·Δs]＝[u ₀ u ₁ u ₂ … u _n ]

If the target value a and A ₁ The medium-number values have the following relationship,

f(u _i )<a<f(u _i+1 )

and the function f is in interval [ u ] ₀ ,u _n ]Is a monotonically increasing function, there is,

u _i <result<u _i+1 ，0<i<n

this completes the iterative calculation of the first cycle and approximately determines the range of values for result.

The 2 nd iteration, the order,

establishing array A ₂ Is that

A ₂ ＝[u _i u _i +Δs u _i +2·Δs … u _i+1 ]，0<j<n＝[u _i +v ₀ u _i +v ₁ u _i +v ₂ … u _i +v _n ]

If the target value a and A ₂ The medium-number values have the following relationship,

f(u _i +v _j )<a<f(u _i +v _j+1 )

And the function f is in interval [ u ] ₀ ,u _n ]Is a monotonically increasing function, there is,

u _i +v _j <result<u _i +v _j+1

this completes the iterative calculation of cycle 2 and results in a more accurate range of values than the first time.

After 3 iterations are set, a relation is obtained,

u _i +v _j +w _k <result<u _i +v _j +w _k+1 ，0<k<n

it can be considered that result is approximately u _i +v _j +w _k An approximate solution result of the function f (result) =a. The more the iteration times are, the more accurate the calculation result is, and meanwhile, the more operation steps are, the longer the time consumption is. The iteration times in the algorithm are properly selected according to the electric energy quality precision.

For the SQRT, ASIN, SIN, DIV problem, the iteration process is consistent, but the function f is different, the iteration times are different, and the preprocessing and post-stage processes are different. The different parts can be selected and switched by the operation type input and state selection logic of the iteration module. Therefore, the solving problem of the SQRT, ASIN, SIN, DIV four complex operations can be completed by one iterative calculation digital logic.

Iterative computation converts complex operations into multiplication, addition and subtraction, and magnitude comparison operations. The multiplier is embedded in the programmable logic device, and multiplexing of the multiplier is carried out through the data selector according to the operation steps, so that hardware resources can be saved to a great extent. In the digital logic of the power quality calculation of the invention, only 4 signed 64-bit multipliers are applied, and the multipliers are formed into a multiplier module for multiplexing. The operation formula of the multiplier module is as follows:

The multiplier module is designed as the formula above, so as to facilitate the two angles and calculation in the trigonometric function:

if only two numbers are calculated to multiply, c can be made ₁ 、d ₁ Equal to 0.

Considering implementation in digital logic, the number of interval divisions n in each iteration is a power of 2, typically n takes a value of 8.

After discussing the iterative calculation principles, specific steps for solving SQRT, ASIN, SIN, DIV are described below. In the iterative comparison, once the calculation results are equal and a and/or b are equal to 0, the calculation results can be directly known without entering a round of iteration. The case of comparative equality will not be discussed further below.

The technical scheme of the invention is described in more detail below with reference to the accompanying drawings.

As shown in fig. 1, the external multichannel analog signal stream is sequentially input into an AD converter, and the AD conversion module converts the analog signal stream into a digital signal stream and then transmits the digital signal stream to an AD driving module of a connected programmable logic device to drive different data streams to be transmitted to each calculation module of the power quality calculation module.

As shown in fig. 4, in the main calculation module of the power quality calculation module, the received 100Hz sampled data stream is data-sampled to obtain a 2kHz data stream. The whole calculation process of the electric energy quality measurement is mainly divided into four parts of data sampling, basic operation, data statistics and electric energy quality calculation results. Wherein, the duration of each 50 continuous 2kHz sampling points is defined as 1Cyc; every 8Cyc is defined as 1 bound, which is equal to the duration of 10 cycles of a 50Hz AC signal; the corresponding time period is 3s every 15 bounch.

As shown in fig. 1, a storage module in the main computing module sequentially performs a cyclic storage step on each data point of the received 2kHz sampling points in the storage chip, and sequentially stores the collected data in RAM and/or ROM of the power quality computing module, where the data sampling process is as follows: the 24-channel 100kHz sampled serial data stream is converted to a 2kHz data stream after data sampling. For an ac signal rated at 50Hz, there are 40 samples of 1 cycle when the sampling rate is 2 kHz. The calculation model reads the sampled data and performs continuous cyclic storage. Each channel cycle stores samples of 90 consecutive points.

That is, as shown in fig. 5, the steps of the basic operation include, in order: carrying out serial calculation on 24 channels at each 1kHz to obtain phasors, amplitude values, phases, phase differences and frequencies (f) corresponding to the input waveforms of each channel at the moment; in which, as shown in FIG. 6, every 1kHz, the next channel is resampled at 2kHz according to the first frequency calculation result (f) in the Cyc, and then DFT operation is performed to obtain phasors (a+bi), amplitude (c 1), DC amplitude (c 0) and harmonic amplitude (c) ₂ 、c ₃ 、...c ₁₉ ) And calculating results, wherein the K value is the ratio of each channel to the last sampling frequency when the 24 channels are resampled at 2kHz according to the first frequency calculation result (f) in the Cyc, and the resampling starting point of each channel is the same so as to ensure that the calculation results are synchronous data.

Further specifically, the basic operation process is: every 1Cyc, the time is calibrated according to the sampling rate of 2kHz, and then 1, 2 to 50 sampling moments are provided. Let time t be identified as 1, 2, … …, 50. The basis operation is performed every 1 data sampling instant (i.e., t=2, 4, 6, … …, 50). The basic operation aims at obtaining phasors, amplitude values, phases, phase differences (phase differences for short) in unit time and frequencies of input signals of each channel, and calculation results in the basic operation are all stored in a RAM. The basic operation is based on a recursive DFT algorithm, the calculation steps of which are,

Step_1:

Step_2:

Step_3:

phasors of m times/amplified

Step_4:

Step_5:

Signal amplitude value

Step_6:

Phase of the signals

Step_7:

Frequency of signals

g_c is the cosine value reduced by n times, g_s is the sine value reduced by n times, m_a ' is the vector of the g_c sampling point amplified by m times according to step_2, m_b ' is the vector of the g_s sampling point amplified by m times according to step_2, c is the signal amplitude, θ ' is the current signal phase, θ _old′ For the recursion of the previously input signal phase, f is the signal frequency.

In order to eliminate the measurement error problem caused by the frequency deviation rated signal, a recursive average filtering algorithm is performed, so as to obtain a high-precision frequency measurement result, the calculation formula is as follows,

First order filtering

Second order filtering

_… ……

k-order filtering

As shown in fig. 4 and 6, in every 1Cyc, after the basic operation is completed, a high-precision operation is required. The operation content comprises: synchronous sampling, DFT direct current and harmonic component calculation. When t=2, 4, 6, … …, 48, the channels involved in the operation are chn_1, chn_2, chn_3, … …, chn_24, respectively. The calculation formula of the synchronous sampling operation is as follows,

and performing DFT operation to obtain direct current components and harmonic amplitudes. Defining n resample points x obtained by a resample algorithm _i For resampling sequence X _r . The h-degree component DFT coefficients (amplified g-degree genotyping) are defined as,

the h-degree component DFT phasor calculation formula is (m times amplified),

the calculation formula of the magnitude of the h-degree component is as follows,

wherein, the basic operation is a recursive DFT algorithm, a recursive average filtering algorithm, a synchronous sampling operation, a definition of the DFT coefficient of the h-order component and the h-order componentThe function calculation of the main calculation module used for the DFT phasor calculation and the h-time component amplitude calculation is performed, and in the calculation process of the main calculation module, division operation is required to be converted into multiplication operation through the data selection logic module, multiplier calculation multiplication operation is selectively called, and a result is transmitted back to the main calculation module, as shown in fig. 1. The problem SQRT, ASIN, SIN, DIV in the above operation is solved by the calculation of the operation data in the main module and the operation type input iterative calculation module, wherein the operation type inputs 1), SQRT (open square), 2), ASIN (arcsine), 3), SIN (sine), 4), DIV (division) and the inputs a, b and c of the operation data are respectively calculated by the iterative calculation module through S221: initializing signal data according to the operation type transmitted by the main calculation module; s222: the iterative computation module performs iterative computation according to the operation type; s223: selecting a subsequent calculation module according to the operation type; s224: outputting a calculation result 1:

2:result=arcsin (b/c), 3:result=sin (a), and 4:result=a/b.

The high-coupling iterative computation module comprises the following specific contents that the solution to SQRT is specifically as follows:

the main calculation module inputs the operation type input 1), SQRT (open square) and operation data a, b and c into the iterative calculation module with high coupling degree:

first, iteration is carried out in the 1 st round to construct an array A ₁ ，

A ₁ ＝[02 ⁰ ·Δs 2 ¹ ·Δs … 2 ⁿ ·Δs]

＝[u ₀ u ₁ u ₂ … u _n ]

Wherein let u _n＞ u _0＞0 N is an integer greater than zero, the maximum value range which can be represented in the calculation process is determined according to the AD bit number acquired by the signal of the system, the calculation is performed,

find out the interval satisfies

Then the first time period of the first time period,

u _i <result<u _i+1

iteration of the 2 nd round, construct array A ₂ ，

Order the

The calculation is performed such that,

the satisfaction of the interval is found out,

then the first time period of the first time period,

through multiple iterations, the range can be reduced, thereby determining the value of result, and enabling

More specifically, as shown in FIG. 3, the general arcsin calculation is to solve the arcsin (a) problem. In the present invention, ASIN is performed to obtain signal phase after DFT obtains signal phasor to be a+bj, and signal amplitude is made to be

The ASIN problem in the present invention is therefore referred to as solving the arcsin (b/c) problem.

The solution to ASIN is specifically: the main calculation module inputs the operation type input 2), ASIN (arcsine) and operation data a, b and c into the iterative calculation module with high coupling degree:

Data preprocessing is required before solving the ASIN.

First, if (a, b) is located at the x-axis, y-axis or center, the result can be directly obtained, and the result is found to be 0 ° (including the center), 90 °, 180 °, 270 ° or 360 ° according to the position information, so that iterative calculation is not necessary. If (a, b) is not the axis area or the center of the circle, quadrant information of a+bj needs to be saved,

then, an absolute value operation is performed.

For the y=sin (x) function, the rate of change of the y value is smaller as x is closer to 90 °. Thus, as x approaches 90 °, the calculation error increases. According to the operational relation of the trigonometric function,

the problem that the calculation error of the iterative algorithm is larger when x is closer to 90 degrees can be solved by using the formula. As shown in fig. 2, the section is divided into two regions. When a=b, result=45°, the iterative calculation process is also skipped, and the result is directly known. Otherwise, if a is less than b, the values of a and b are interchanged, and the phase result is obtained after iterative calculation, so that the result=90-result is the final arcsine calculation result. After the logic is added, all arcsine operations are in the interval of 0-45 degrees, so that the problem of precision reduction caused by approaching 90 degrees is avoided. Normal iteration logic is entered below.

When calculating the arcsine, use 2 ¹² =4096 denotes 90 °, u _n Is 4096 and n is 8,u ₀ 4096/8=512. Each iteration, the range of evaluation is thinned by 1/n, namely 1/8, and after 4 iterations, the data range can be thinned to 4096/(8) ⁴ ) The accuracy of the arcsine calculation is 90 °/4096= 0.0219 °.

Iteration 1, construct array A ₁ ，

Wherein g is a power of 2 number, which is used for scaling up the value and avoiding floating point operation. A is that ₁ The member values of the table are known values, stored in ROM, and obtained by directly accessing ROM when performing calculation.

Calculation, B ₁ ＝cA ₁ ＝[c·g·sin(α ₀ ) c·g·sin(α ₁ ) c·g·sin(α ₂ ) … c·g·sin(α ₈ )]

Where, as previously mentioned, c is the magnitude of the signal phasor a + bj, which is,

the interval is obtained by means of a comparison,

c·g·sin(α _i )<g·b<c·g·sin(α _i+1 )

so that the number of the components in the product,

α _i <result<α _i+1

iteration of the 2 nd round, construct array A ₂ ，

The calculation is performed such that,

B ₂ ＝c·A ₂

it is assumed that by means of the comparison,

c·g·sin(α _i +β _j )<g·b<c·g·sin(α _i +β _j+1 )

so that the number of the components in the product,

α _i +β _j <result<α _i +β _j+1

iteration 3, construct array A ₃ ，

The same algorithm is adopted, and the method is obtained,

c·g·sin(α _i +β _j +γ _k )<g·b<c·g·sin(α _i +β _j +γ _k+1 )

it can be approximated that,

and finally, correcting the result. The values of a and b are interchanged, so that result=90-result, otherwise result is unchanged. Correcting result according to the quadrant position of (a ', b'),

in this way, only 24 sinusoidal values need to be stored at most, and the effective resolution is,

more specifically, the solution to SIN is specifically: the sine calculation is an inverse process of the arcsine calculation, and the value range of the angle a in the solving problem result=sin (a) is as follows 0～360°/m*k _m . Where m is the number of points per cycle when performing DFT operations on a signal of a nominal frequency (typically 50Hz for a power system). k (k) _m Leaving a margin for frequency fluctuations. The sine function is solved without covering the range of 0-90 deg. because the algorithm guarantees a range of values for a in relation to synchronous sampling algorithms. The algorithm can be simplified. Here, m=20, k _m For example, =1.5, the iterative computation process of SIN is described. The maximum angle can be calculated to be 360 °/20 x 1.5=27°.

Specifically, the main calculation module inputs the operation type 3) SIN (sine) and operation data a, b and c into the iterative calculation module with high coupling degree:

first, iteration is carried out in the 1 st round to construct an array A ₁ ，

It is assumed that by means of the comparison,

u _i <a<u _i+1

iteration of the 2 nd round, construct array A ₂ ，

It is assumed that by means of the comparison,

u _i +v _j <a<u _i +v _j+1

iteration 3, construct array A ₃ ，

It is assumed that by means of the comparison,

u _i +v _j +w _k <a<u _i +v _j +w _k+1

there is a case where the number of the group,

finally, calculating according to the two angles of the trigonometric function and the formula to obtain a sine calculation result,

such a calculation method is sampled, and 3*8 =24 sine values only need to be stored in the ROM. The consumption of ROM is effectively reduced.

Further specifically, the solution to DIV is specifically: the design choice of this application is for 16-bit AD, so the maximum is 2ζ5=32768. The division result does not exceed 99999, and is therefore the division operation.

For division, it is assumed that the signal acquisition of the system adopts 14-bit AD, and the maximum value of the signal amplitude after the symbol removal is 2 ¹³ =8192 (four digits), so when calculating the discrete division, u _n The initial value set to 10000 (five digits) can certainly meet the calculation requirement. If u is _n Setting 100000 (six digits) is not indispensable, but only one iteration is needed to obtain the calculation result with the same precision, so that u is unnecessary according to the current practical situation _n Set to 100000 (six digits).

The solution to DIV is specifically: the main calculation module inputs the operation type input 2), DIV (division) and operation data a, b and c into the iterative calculation module with high coupling degree:

first, in iteration 1, let u _n＞ u _0＞0 Constructing array A ₁ Is that

A ₁ ＝[0 1·10 ⁵ ·b 2·10 ⁵ ·b … 9·10 ⁵ ·b]＝[u ₀ u ₁ u ₂ … u ₉ ]

The comparison is carried out by the device,

u _i0 <a<u _i0+1

then the first time period of the first time period,

i ₀ ·10 ⁵ <result<(i ₀ +1)·10 ⁵

iteration of the 2 nd round, construct array A ₂ Is that

A ₂ ＝[u _i0 +0u _i0 +1·10 ⁴ ·b u _i0 +2·10 ⁴ ·b … u _i0 +9·10 ⁴ ·b]

＝[u _i0 +v ₀ u _i0 +v ₁ u _i0 +v ₂ … u _i0 +v _n ]

The comparison is carried out by the device,

u _i0 +v _i1 <a<u _i0 +v _i1+1

then the first time period of the first time period,

i ₀ ·10 ⁵ +i ₁ ·10 ⁴ <result<i ₀ ·10 ⁵ +(i ₁ +1)·10 ⁴

similarly, the 3 rd round of iteration and the 6 th round of iteration are carried out again, and i can be confirmed in turn ₀ 、i ₁ 、i ₂ 、i ₃ 、i ₄ 、i ₅ The numerical value. Finally, the calculation result is obtained as a result of calculation,

result＝i ₀ ·10 ⁵ +i ₁ ·10 ⁴ +i ₂ ·10 ³ +i ₃ ·10 ² +i ₄ ·10 ¹ +i ₅

as shown in fig. 1, when the high-coupling-degree iterative computation module performs computation, the high-coupling-degree iterative computation module transmits operation data to the multiplier module for operation through the data selection logic when multiplication operation is needed, and the result is fed back to the iterative computation module after the multiplier operation is finished.

The data statistics operation is used for completing the measurement of the electric energy quality and giving out a calculation result, and the steps are as follows: every 1Cyc (as shown in FIG. 6 and FIG. 8) or every 8Cyc (as shown in FIG. 7 and FIG. 9) a statistical operation is required. And carrying out statistical operation every 120Cyc (namely 15 bound and 3s duration) to obtain a final power quality calculation result, wherein the calculation schematic diagrams are shown in fig. 10 and 11. The electric energy quality operation result comprises voltage deviation, fundamental wave frequency, harmonic wave content, total harmonic wave distortion rate, positive and negative zero sequence components, negative sequence unbalance degree and zero sequence unbalance degree.

The method comprises the following steps of: every 1 sampling point of 1kHz, basic operation needs to be carried out once; each 1Cyc carries out high-precision calculation on the basis of each 1kHz operation, as shown in fig. 4, each 1Cyc carries out data statistics, the specific step process is shown as 6, and the phasor, amplitude, frequency (f) and direct-current amplitude (c) of 24 channels for serial calculation are obtained ₀ ) Amplitude of fundamental wave (c ₁ ) Harmonic amplitude (c) ₂ 、c ₃ 、.....c ₁₉ ) Accumulating and summing up and storing; as shown in fig. 9, the three-phase channels are calculated to obtain positive and negative zero sequence components, and the negative sequence imbalance (e ₁ ) Zero sequence imbalance (e) ₀ ) And calculating the results, and simultaneously summing and accumulating the necessary operation results.

Each 1bounch comprises 8Cyc which is equal to the duration of 10 cycles of 50Hz alternating current signals; as shown in FIG. 8, the data statistics continues with the sum of the harmonic amplitudes per channel (c) for 24 channels per 1bounch (i.e., per 8 Cyc) _{2_s1} 、c _{3_s1} 、.c _{19_s1} ) Performing an average operation, squaring, accumulating and summing, and storing; as shown in fig. 10, the negative sequence imbalance sum (e _{2_s1} ) Zero sequence imbalance sum (e) _{0_s1} ) And carrying out one-time averaging operation, squaring, accumulating and summing, and storing.

Every 15bounch, according to the electric energy quality calculation requirement, carry out necessary and calculate the mean value or calculate the root mean square, and finally get the electric energy quality operation result. The specific process is as follows: every 120Cyc (i.e. 3 s), as shown in FIG. 1, a power quality calculation result is obtained and stored in a memory ROM or RAM in the power quality calculation module for calling and transmitting internal data, so that input data can be transmitted to more functional modules designed subsequently, and meanwhile, the calculated power quality calculation result is communicated to the outside and output. As shown in fig. 7, the dc amplitude is summed (c _{0_sum} ) Sum of fundamental wave amplitude accumulation (c) _{1_sum} ) Frequency accumulated sum (f) _{_sum} ) And carrying out average operation to obtain a power quality calculation result:

As shown in fig. 9, the sum is further accumulated for negative sequence imbalances(e _{2_sum} ) Zero sequence imbalance sum (e) _{0_sum} ) As shown in fig. 10, the dc amplitude (c _{0_sum} ) Fundamental frequency (f) _{1_sum} ) And fundamental wave amplitude c _{1_sum} Arithmetic averaging over 120 Cyc cycles, and then summing the harmonic amplitudes (c _{2_sum} 、c _{3__sum} 、...c _{19_sum} ) Root mean square operation is carried out and then the fundamental wave amplitude c is compared _1R Obtaining the amplitude (c) of each harmonic _2R 、c _3R 、...c _19R ) Harmonic content (HR) ₂ 、HR ₃ 、...HR ₁₉ ) The root mean square of the sum of the squares of the amplitude of each harmonic is used for obtaining the amplitude c of the fundamental wave _1R And obtaining the total fundamental wave distortion rate THR of the power quality calculation result.

Cumulative sum of negative sequence imbalances e _{2_sum} Sum zero sequence imbalance cumulative sum e _{0_sum} The arithmetic square root of 15 bounch cycles respectively gives the negative sequence imbalance degree e _2R And zero sequence imbalance degree e _0R The power quality calculation module is stored in a memory ROM or RAM in the power quality calculation module and used for calling and transmitting internal data, and can transmit input data to more functional modules designed subsequently, and simultaneously, the calculated power quality calculation result is communicated to the outside and output.

The steps in the present application may be sequentially adjusted, combined, and pruned according to actual requirements.

The units in the device can be combined, divided and pruned according to actual requirements.

Although the present application is disclosed in detail with reference to the accompanying drawings, it is to be understood that such descriptions are merely illustrative and are not intended to limit the application of the present application. The scope of the present application is defined by the appended claims and may include various modifications, alterations, and equivalents to the invention without departing from the scope and spirit of the application.

Claims (5)

1. The power quality measuring method based on the high-coupling iterative model is characterized by comprising the following steps of: collecting power related data, sampling the data, calculating power based on the sampled data, and outputting a calculated power quality result, wherein the method comprises the following steps:

s1: collecting analog voltage u and/or current i signals by utilizing a plurality of parallel channels, wherein the signals are sequentially transmitted to a power quality calculation module through AD conversion and AD driving of a programmable logic device, the AD conversion is used for converting the input analog voltage u and/or current i signals of the plurality of parallel channels into digital voltage u and/or current i signals, and the AD driving is used for driving and transmitting digital voltage u and/or current i signal data to the power quality calculation module;

S2: in the power quality calculation module, the input digital voltage and/or current signals are converted into 2kHz data streams after the 24 channels of 100kHz sampling serial data streams are subjected to data sampling by the main calculation module; for an alternating current signal with the rated frequency of 50Hz, sampling 1 cycle wave by a sampling rate of 2kHz for 40 sampling points, reading sampling data by a calculation model of a main calculation module, continuously and circularly storing the sampling data in a RAM, performing basic operation once by a recursive DFT (discrete Fourier transform) for each 1kHz sampling point to obtain phasors a+bj of 24 channels, and circularly storing continuous sampling values corresponding to 90 points for each channel to serve as a data stream calculated by the main calculation module; the vector value a+bj of each channel is subjected to evolution and arcsine through an iterative calculation module to obtain amplitude c and phase P, phase difference deltap is obtained through phase difference calculation, and deltap is obtained through multi-order average filtering calculation _avg A frequency f;

setting the duration of 1Cyc for every 50 sampling points with continuous 2kHz frequency, synchronously sampling the data stream obtained by sampling 24 channels at 2kHz with frequency f, and resampling the signal X on the basis of every 1kHz operation _r Performing high-precision DFT calculation once to obtain a direct current amplitude value c0 and a fundamental wave phasor a of each channel of 24 channels ₁ +b _1j And 2-19 harmonic vector a ₂ +b _2j To a ₁₉ +b _19j Obtaining fundamental wave amplitude c through open square ₁ And 2-19 harmonic vector magnitude c ₂ To c ₁₉ The method comprises the steps of carrying out a first treatment on the surface of the Every 8 Cyc, the harmonic amplitude of each channel in 24 channels with the same frequency is accumulatedSummation c _{2_s1} 、c _{3_s1} 、...c _{19_s1} Respectively carrying out an average operation, and respectively obtaining harmonic amplitude accumulated sum c by accumulated summation after squaring _{2_sum} 、c _{3_sum} 、...c _{19_sum} And storing; negative sequence imbalance summation e for three-phase channels _{2_s1} Zero sequence imbalance sum e _{0_s1} Carrying out one-time averaging operation, squaring, accumulating and summing, and storing;

serial calculation is carried out on 24 channels of each 1Cyc to obtain the direct current amplitude value c of each channel ₀ Amplitude c of fundamental wave ₁ And frequency f, DC amplitude c for 24 channels ₀ Amplitude c of fundamental wave ₁ Respectively accumulating and summing the sum frequency f to obtain a DC amplitude accumulated sum c _{0_sum} Sum of fundamental wave amplitude summation c _{1_sum} Sum frequency accumulated sum f _{_sum} ，

The direct current amplitude value is accumulated and summed every 3s _{0_sum} Sum of fundamental wave amplitude summation c _{1_sum} Frequency accumulated sum f _{_sum} Obtaining a power quality calculation result by the average operation of (a);

accumulating the sum e for negative sequence imbalance _{2_sum} Zero sequence imbalance accumulated sum e _{0_sum} For the direct current amplitude value accumulated sum c _{0_sum} Frequency accumulated sum f _{_sum} Sum of fundamental wave amplitude accumulated sum c _{1_sum} Arithmetic average over 120 Cyc cycles, and then sum up the harmonic amplitude _{2_sum} 、c _{3_sum} 、...c _{19_sum} Root mean square operation is carried out and then the fundamental wave amplitude c is compared _1R Obtaining the amplitude value c of each harmonic _2R 、c _3R 、...c _19R Harmonic content HR of (2) ₂ 、HR ₃ 、...HR ₁₉ The root mean square of the sum of the squares of the amplitude of each harmonic is used for obtaining the amplitude c of the fundamental wave _1R The ratio of (2) to obtain the total fundamental wave distortion rate THR;

wherein the main calculation module solves the vector value and the amplitude of each signal, the input operation data a, b and c and the required operation type thereof, and outputs to an iterative computation module to perform high-coupling iterative computation, and reprocesses the computation result fed back by the iterative computation module to obtain the amplitude c of each component of the signal,The phase P and the frequency f are calculated by a main calculation module to obtain the total fundamental wave distortion rate THR of the electric energy quality calculation result; cumulative sum of negative sequence imbalances e _{2_sum} Sum zero sequence imbalance cumulative sum e _{0_sum} Respectively obtaining the negative sequence unbalance e2R and the zero sequence unbalance e0R at the arithmetic square root of 15 bounch periods, and outputting the negative sequence unbalance e2R and the zero sequence unbalance e0R to a programmable logic device, wherein the required operation types comprise open square, arcsine, sine and division;

s3: the output power quality measurement result is externally communicated and output through the programmable logic device.

2. The power quality measurement method of a high coupling degree iterative model according to claim 1, wherein the iterative calculation module iterates steps including:

S221: initializing signal data according to the operation type transmitted by the main calculation module;

s222: the iterative computation module performs iterative computation according to the operation type;

s223: selecting a subsequent calculation module according to the operation type;

s224: and outputting a calculation result.

3. The power quality measurement method of the high-coupling iterative model according to claim 1, wherein the principle of iterative calculation by the iterative calculation module is as follows: and carrying out at least three identical iterative calculation models with different iterative times through the operation data of the iterative calculation module, wherein the solving process of the iterative method comprises the following steps:

iteration 1, let u _n＞ u _0＞0 Wherein u is _n Is rounded up with the iterative calculation type of the iterative calculation module and the maximum value of the power quality data involved in the calculation process,

n is an integer not less than 3;

establishing array A ₁ In order to achieve this, the first and second,

A ₁ ＝[u ₀ u ₀ +Δs u ₀ +2·Δs …u ₀ +n·Δs]

＝[u ₀ u ₁ u ₂ … u _n ]

if the target value a and A ₁ The numerical value of the relation is that,

f(u _i )<a<f(u _i+1 )

and the function f is in interval [ u ] ₀ ，u _n ]For a monotonically increasing function, determining the numerical range of result as:

u _i <result<u _i+1 ，0<i<n

iteration 2, let u ₀ ＝u _i And u _n ＝u _i+1

Obtaining an array A ₂ Is that

If the target value a and A ₂ The numerical value of the relation is that,

f(u _i +v _j )<a<f(u _i +v _j+1 )

and the function f is in interval [ u ] ₀ ,u _n ]A more accurate result range is the monotonically increasing function:

u _i +v _j <result<u _i +v _j+1

After the 3 rd iteration, a more accurate numerical range of result is obtained:

u _i +v _j +w _k <result<u _i +v _j +w _k+1 ，0<k<n

output result is approximately equal to u _i +v _j +w _k The result is a solution of the function f (result) =a.

4. The power quality measurement method of the high coupling degree iterative model according to claim 1, wherein the calculation process of the main calculation module is divided into three processes of basic operation, data calculation and power quality calculation result respectively by using a period of 1 cycle small cycle per 50 continuous 2kHz sampling points, a period of 1 bound single cycle per 8 continuous 2kHz sampling points and a corresponding period of 3s per 15 bound as a round cycle period.

5. A power quality measurement system based on a high-coupling iterative model, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements a power quality measurement method of the high-coupling iterative model according to any one of claims 1 to 4, the power quality measurement system of the high-coupling iterative model comprising one or more programmable digital logic platforms according to any one of claims 1 to 4, comprising an iterative calculation module, a digital selection logic, a multiplier, a RAM, a ROM, an input and output interface and one or more AD conversion modules connected between the interiors for measuring power quality parameters of the high-coupling iterative model.

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