阅读说明：本技术 一种基于高耦合度迭代模型的电能质量测量系统及方法 (Electric energy quality measurement system and method based on high-coupling-degree iterative model ) 是由 廖于翔 李可维 张正卿 吴浩伟 孔祥伟 帅骁睿 张鹏程 田杰 于 2020-12-23 设计创作，主要内容包括：一种基于高耦合度迭代模型的电能质量测量系统及方法,其基于可编程数字逻辑平台,用于多通道输入信号的电能质量的测量。快速迭代计算模块通过高耦合度程序算法,将电能质量计算过程中必须的求正弦、反正弦、除法、开平方根这四种复杂运算紧密集成于一个模块,通过运算类型切换不同运算,有效地减小了逻辑资源的开销。主计算模块设计了递归DFT、递归均值滤波、同步采样、谐波幅值计算、正负零计算及状态机控制的数字逻辑,通过调用迭代计算模块,实现电能质量的计算并输出结果。本发明用于多通道电能质量测量及计算过程中的复杂运算,具有对外接口简单、运算结果丰富、可有效减小处理器运算资源的消耗,应用空间限制小,多功能智能集成优化好。(A power quality measurement system and method based on a high-coupling-degree iterative model are based on a programmable digital logic platform and used for measuring the power quality of a multi-channel input signal. The fast iterative computation module closely integrates four complex operations of sine, arcsine, division and square root division which are necessary in the power quality computation process into one module through a high-coupling-degree program algorithm, and effectively reduces the expenditure of logic resources by switching different operations through operation types. The main calculation module designs digital logics of recursive DFT, recursive mean filtering, synchronous sampling, harmonic amplitude calculation, positive and negative zero calculation and state machine control, and realizes the calculation of the power quality and outputs the result by calling the iterative calculation module. The invention is used for the complex operation in the multi-channel power quality measurement and calculation process, has simple external interface, rich operation result, can effectively reduce the consumption of the operation resource of the processor, has small application space limitation and good multifunctional intelligent integration optimization.)

1. A power quality measurement method based on a high-coupling-degree iterative model is characterized in that the method is based on a programmable digital logic platform and is used for measuring parameters of power quality of a multi-channel alternating current-direct current signal, and the method comprises the following steps: collecting electric energy related data, sampling the data, calculating electric energy based on the sampled data, and outputting a calculated electric energy quality result.

2. The method for measuring the quality of electric energy based on the iterative model with high coupling degree of claim 1, wherein the method comprises the following steps:

s1: the method comprises the steps that a plurality of parallel channels are utilized to collect analog voltage u and/or current i signals, 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 electric energy quality computing module, an input digital voltage and/or current signal is converted into a 2kHz data stream after data sampling is carried out on 24 channels of 100kHz sampling serial data streams through a main computing module; for an alternating current signal with the rated frequency of 50Hz, sampling 40 sampling points for 1 cycle at the sampling rate of 2kHz, reading sampling data by a calculation model of a main calculation module and continuously and circularly storing the sampling data in an RAM, carrying out basic operation once by recursive DFT (discrete Fourier transform) on each 1kHz sampling point to obtain phasor a + bj of 24 channels, and circularly storing the sampling values corresponding to 90 continuous points in each channel for serving as a data stream calculated by the main calculation module; the vector value a + bj of each channel is subjected to evolution and arcsine by an iterative computation module to obtain an amplitude c and a phase P, the phase difference delta P is obtained by phase difference computation, and the delta P is obtained by multi-order average filtering computation_avgAnd a frequency f;

setting the time length of each 50 sampling points under the continuous 2kHz frequency to be 1Cyc, synchronously sampling data streams obtained by sampling 24 channels at 2kHz by adopting frequency f, and performing synchronous sampling on a re-sampling signal X on the basis of every 1kHz operation_rPerforming high-precision DFT calculation once to obtain the direct current amplitude c0 and the fundamental phasor a of each channel of 24 channels₁+b_1jAnd 2-19 subharmonic vectors a₂+b_2jTo a₁₉+b_19jObtaining the fundamental wave amplitude c by squaring₁And 2-19 subharmonic vector magnitude c₂To c₁₉(ii) a Sum of harmonic amplitudes per channel for 24 channels (c)_{2_s1}、c_{3_s1}、.c_{19_s1}) Carrying out primary average operation, and accumulating, summing and storing after squaring; cumulative sum of negative sequence imbalance of three phase channels (e)_{2_s1}) Zero sequence imbalance cumulative sum (e)_{0_s1}) Carrying out primary averaging operation, squaring, accumulating, summing and storing;

adding up the DC amplitude value once for every 15bounch duration 3s (c)_{0_sum}) Sum of fundamental amplitude values (c)_{1_sum}) Frequency sum (f)_{_sum}) Carrying out average operation to obtain a power quality calculation result;

adding up the sum (e) of the negative sequence unbalances_{2_sum}) Zero sequence imbalance accumulated sum (e)_{0_sum}) The DC amplitude (c) of the cumulative sum_{0_sum}) Fundamental frequency (f)_{1_sum}) And the amplitude c of the fundamental wave_{1_sum}Arithmetically averaging over 120Cyc cycles, and then summing the harmonic amplitudes (c)_{2_sum}、c_{3__sum}、...c_{19_sum}) Comparing the root mean square calculation with the fundamental wave amplitude c_1RObtaining the amplitude (c) of each harmonic_2R、c_3R、...c_19R) Harmonic content (HR)₂、HR₃、...HR₁₉) By root mean square of the sum of the squares of the amplitudes of the harmonics and the amplitude c of the fundamental wave_1RObtaining the total fundamental wave distortion rate THR according to the ratio;

the main calculation module solves input operation data a, b and c and required operation types 1 squaring, 2 arcsine, 3 sine and 4 division of vector values and amplitudes of each signal to the iterative calculation module to perform high coupling degree iterative calculation, reprocesses calculation results fed back by the iterative calculation module to obtain amplitudes c, phases P and frequencies f of all components of the signal, and obtains a total fundamental wave distortion rate THR of an electric energy quality calculation result through calculation of the main calculation module; cumulative sum of negative sequence imbalance e_{2_sum}Sum zero sequence imbalance cumulative sum e_{0_sum}Obtaining a negative sequence unbalance e2R and a zero sequence unbalance e0R from arithmetic square roots of 15 launch cycles respectively and outputting the negative sequence unbalance e2R and the zero sequence unbalance e0R to the programmable logic device;

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

3. The method for measuring the power quality of the iterative model with high coupling degree according to claim 2, wherein the iterative computation module comprises the iterative steps of:

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

s222: the iterative computation module carries out iterative computation according to the operation type;

s223: selecting and processing subsequent calculation modules according to the operation type;

s224: and outputting a calculation result.

4. The method for measuring the power quality of the iterative model with high coupling degree according to claim 2, wherein the iterative computation module iteratively computes the principles of: the same iterative computation model is carried out for at least three times with different iteration times through the operational data of the iterative computation module, wherein the process of solving by the iterative method is as follows:

iteration 1, order, u_n＞u₀＞₀Wherein u is_nAnd the value of (a) is rounded with the maximum value of the iterative computation type of the iterative computation module and the power quality data involved in the computation process.

n is an integer of not less than 3;

set up array A₁In order to realize the purpose,

A₁＝[u₀ u₀+Δs u₀+2·Δs … u₀+n·Δs]

＝[u₀ u₁ u₂ … u_n]

if the target values a and A are₁The medium numerical relationship is that,

f(u_i)＜a＜f(u_i+1)

and the function f is in the interval u₀，u_n]For a monotonically increasing function, the value range of result is determined as:

u_i＜result＜u_i+1，0<i<n

iteration 2, let u₀＝u_iAnd u and_n＝u_i

get the array A₂Is composed of

If the target values a and A are₂The medium numerical relationship is that,

f(u_i+v_j)＜a＜f(u_i+v_j+1)

and the function f is in the interval u₀，u_n]For a monotonically increasing function, the more accurate value range of result is:

u_i+v_j＜result＜u_i+v_j+1

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

u_i+v_j+w_k＜result＜u_i+v_j+w_k+1，0<k<n

the output result ≈ ui + vj + wk is the solution result of the function f (result) ═ a.

5. The power quality measurement method of the iterative model with high coupling degree according to claim 3, step S223 comprises: the selection of the operation type and the switching of different functions f (result) are carried out by the operation type input and the state selection logic of the iterative computation module,

when the operation type input is 1SQRT (square-on-square), finding result1 to make result × result closest to a; the final calculation result is that result is:

when the operation type input is 2ASIN (arcsine), finding result2, and making sin (result) closest to a; when a and/or b are not 0 and unequal, if a is less than b, interchanging the numerical values of a and b, obtaining a phase result after iterative calculation, and making the result be 90-result, which is a final arcsine calculation result; otherwise, the final calculation result is that,

when the operation type input is 3SIN (sine), finding result3 to make arcsin (result) closest to a; the final result of the calculation is that,

when the operation type input is 4DIV (division), finding result4 to make result x b closest to a; the final calculation result is that result is i₀·10⁵+i₁·10⁴+i₂·10³+i₃·10²+i₄·10¹+i₅。

6. The method for measuring the power quality of the iterative model with high coupling degree according to claim 1, wherein 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 by taking a round-robin period of 1Cyc short-circuiting period of time spent on every 50 continuous 2kHz sampling points, a single round-circuiting period of 1 round of time spent on every 8Cyc continuous 2kHz sampling points and a round-robin period of 3s corresponding to every 15 round.

7. The power quality measurement method of the high-coupling iterative model according to claim 2, wherein the calculation result of the basic operation is stored in a RAM of the power quality module, based on a recursive DFT algorithm, and the calculation steps are,

Step_1：

Step_2：

Step_3：

Step_4：

Step_5：

Step_6：

Step_7：

g _ c is a cosine value reduced by n times of angle, g _ s is a sine value reduced by n times of angle, m _ a ' is a vector of g _ c sampling point amplified by m times according to the proportion of step _2, m _ b ' is a vector of g _ s sampling point amplified by m times according to the proportion of step _2, c is signal amplitude, theta ' is current signal phase, theta_old′The phase of the input signal before recursion, f is the signal frequency.

8. The power quality measurement method of the high-coupling iterative model according to claim 7, wherein the recursive DFT algorithm further comprises a recursive mean filtering algorithm, and the calculation steps are as follows:

first order filtering

Second order filtering

……

k order filtering

Wherein the SUM₁...SUM_kRespectively, k order recursive mean filtering results, A_k(n +1) is the n +1 value after the n value of the k-order recursive mean filtering section, A_k(1) Is a step of kAnd (k is less than or equal to n) to the 1 st value of the average value filtering section.

9. A power quality measurement system based on a high-coupling iterative model, wherein a computer program is stored thereon, and when being executed by a processor, the power quality measurement system of the high-coupling iterative model is used for implementing the power quality measurement method of the high-coupling iterative model according to any one of claims 1 to 8, the power quality measurement system of the high-coupling iterative model comprises one or more programmable digital logic platforms according to any one of claims 1 to 8, and the one or more programmable digital logic platforms comprise an iterative computation module, a computation 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 with one another internally and are used for measuring power quality parameters of the high-coupling iterative 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-degree iterative model.

Background field of the invention

With the development of long-distance direct current transmission, the application range of the microgrid is expanded, the microgrid has wide application of new energy with volatility, randomness and intermittence, and the power grid structure is changed, the load characteristics tend to be complex and the problem of power quality deterioration of the power grid is brought due to the fact that the factors such as the operation of the electric vehicles, the charging piles and the charging stations are increased day by day. The reduction of the quality of electric energy reduces the service life of household appliances and the life quality of residents; the interference to the control circuit can cause the quality of the product to be reduced, even the serious problems of power failure, production stop and the like. The deterioration of the power quality also brings about the problems of increasing the line loss, reducing the service life of equipment such as a transformer and the like, causing misoperation of relay protection equipment due to electromagnetic interference and the like, and causing negative influence on the safe and stable operation of the power system.

The monitoring and analysis of the power quality are beneficial to the evaluation of the running state of the power grid, the improvement and the treatment of the power grid, the determination of the responsibility of both power supply and power utilization parties and the resolution of the contradiction disputes of both power supply and power utilization parties, and the power quality monitoring problem is a research hotspot of the general relation of power departments and related scientific researches. At present, for transient power quality disturbance, a generally-accepted and consistent measurement and evaluation algorithm with rapidity and accuracy is still lacked. The large power grid still needs further research on the problems of compression, analysis and utilization of mass power quality data. Index parameters of the power quality are few, and the comprehensive evaluation problem of the multi-index power quality is urgently needed to be further broken through at present when artificial intelligence is rapidly developed.

The power quality monitoring equipment is an actual carrier for power quality detection and goes through four development stages of simple instruments, analog circuit-based instruments, large-scale integrated circuits and virtual technology-based intelligent instruments. In the power quality calculation, the optimization problem of complex calculation cannot be avoided. DFT-based power quality calculations are most widely used. In the calculation process, a large number of complex algorithms of square root solving, arcsine solving, sine solving and division solving are involved, the embedded processor is adopted for carrying out the calculation, and a large number of operation resources of the computer processor are occupied. If the requirement of multiple channels is provided, the operation burden is more serious; if a processor with high computing power is selected, hardware cost and equipment volume are increased, and for special application occasions such as certain ship power monitoring systems, the equipment volume is severely limited, and the function of power quality detection equipment is also required to be higher. The power quality monitoring equipment not only has the function of measurement, but also has multiple functions of data transmission, judgment of the safe operation state of a monitored area power grid, protection control and the like. If the power quality measurement algorithm does not perform optimization processing, more computing resources are occupied, and the interactive transmission of intermediate data during operation needs to frequently occupy interruption, which not only can block the transmission of data streams, but also further increases the complexity of data processing, easily causes the instability of the whole monitoring system, and affects other functions of the whole monitoring system.

Disclosure of Invention

The system and the method are designed for solving the problem that complex arithmetic models are not optimized in the electric energy quality measurement and calculation processes, the electric energy quality measurement system and the method are based on a high-coupling-degree iterative model, the complex arithmetic of solving square roots, arcsine, sine and division in large quantities are involved in the electric energy quality measurement of multi-channel alternating current and direct current signals, the calculation is carried out in an embedded processor, a large quantity of arithmetic resources of a computer processor are occupied, interactive transmission of intermediate data during operation is frequently occupied and interrupted, transmission of data streams is blocked, complexity of data processing is increased, and the problem that the whole monitoring system is unstable is easily caused.

The technical scheme of the application is as follows: a power quality measurement method based on a high-coupling-degree iterative model is designed, is based on a programmable digital logic platform and is used for measuring parameters of the power quality of a multi-channel alternating current-direct current signal, and comprises the following steps: collecting electric energy related data, sampling the data, calculating electric energy based on the sampled data, and outputting a calculated electric energy quality result.

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

s1: the method comprises the steps that a plurality of parallel channels are utilized to collect analog voltage u and/or current i signals, 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 electric energy quality computing module, an input digital voltage and/or current signal is converted into a 2kHz data stream after data sampling is carried out on 24 channels of 100kHz sampling serial data streams through a main computing module; for an alternating current signal with the rated frequency of 50Hz, sampling 40 sampling points for 1 cycle at the sampling rate of 2kHz, reading sampling data by a calculation model of a main calculation module and continuously and circularly storing the sampling data in an RAM, carrying out basic operation once by recursive DFT (discrete Fourier transform) on each 1kHz sampling point to obtain phasor a + bj of 24 channels, and circularly storing the sampling values corresponding to 90 continuous points in each channel for serving as a data stream calculated by the main calculation module; the vector value a + bj of each channel is subjected to evolution and arcsine by an iterative computation module to obtain an amplitude c and a phase P, the phase difference delta P is obtained by phase difference computation, and the delta P is obtained by multi-order average filtering computation_avgAnd a frequency f;

setting the time length of each 50 sampling points under the continuous 2kHz frequency to be 1Cyc, synchronously sampling data streams obtained by sampling 24 channels at 2kHz by adopting frequency f, and performing one-time sampling on a re-sampling signal X on the basis of every 1kHz operationObtaining the direct current amplitude c of each channel of 24 channels by sub-high-precision DFT calculation₀Fundamental phasor a₁+b_1jAnd 2-19 subharmonic vectors a₂+b_2jTo a₁₉+b_19jObtaining the fundamental wave amplitude c by squaring₁And 2-19 subharmonic vector magnitude c₂To c₁₉(ii) a Sum of harmonic amplitudes per channel for 24 channels (c)_{2_s1}、c_{3_s1}、.c_{19_s1}) Carrying out primary average operation, and accumulating, summing and storing after squaring; cumulative sum of negative sequence imbalance of three phase channels (e)_{2_s1}) Zero sequence imbalance cumulative sum (e)_{0_s1}) Carrying out primary averaging operation, squaring, accumulating, summing and storing;

adding up the DC amplitude value once for every 15bounch duration 3s (c)_{0_sum}) Sum of fundamental amplitude values (c)_{1_sum}) Frequency sum (f)_{_sum}) Carrying out average operation to obtain a power quality calculation result;

adding up the sum (e) of the negative sequence unbalances_{2_sum}) Zero sequence imbalance accumulated sum (e)_{0_sum}) The DC amplitude (c) of the cumulative sum_{0_sum}) Fundamental frequency (f)_{1_sum}) And the fundamental amplitude c1_ sum is arithmetically averaged over 120Cyc cycles, and the harmonic amplitudes are summed up to a sum (c)_{2_sum}、c_{3__sum}、...c_{19_sum}) Comparing the root mean square calculation with the fundamental wave amplitude c_1RObtaining the amplitude (c) of each harmonic_2R、c_3R、...c_19R) Harmonic content (HR)₂、HR₃、...HR₁₉) By root mean square of the sum of the squares of the amplitudes of the harmonics and the amplitude c of the fundamental wave_1RObtaining the total fundamental wave distortion rate THR according to the ratio;

the main calculation module solves input operation data a, b and c and required operation types 1 squaring, 2 arcsine, 3 sine and 4 division of vector values and amplitudes of each signal to the iterative calculation module to perform high coupling degree iterative calculation, reprocesses calculation results fed back by the iterative calculation module to obtain amplitudes c, phases P and frequencies f of all components of the signal, and obtains a total fundamental wave distortion rate THR of an electric energy quality calculation result through calculation of the main calculation module;cumulative sum of negative sequence imbalance e_{2_sum}Sum zero sequence imbalance cumulative sum e_{0_sum}The negative sequence imbalance e is obtained at the arithmetic square root of 15 bound cycles_2RAnd the degree of unbalance of zero sequence e_0ROutputting the data to a programmable logic device;

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

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

the iterative computation module iterates the steps including:

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

s222: the iterative computation module carries out iterative computation according to the operation type;

s223: selecting and processing subsequent calculation modules according to the operation type;

s224: and outputting a calculation result.

In any one of the above technical solutions, further, step S22 includes: iterative computation Module procedure

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

s222: the iterative computation module carries out iterative computation according to the operation type;

s223: performing subsequent conversion treatment according to the operation type;

s224: and outputting a calculation result.

In any one of the above technical solutions, further, step S222 includes:

the same iterative computation model is carried out for at least three times with different iteration times through the operational data of the iterative computation module, wherein the process of solving by the iterative method is as follows:

iteration 1, let u_n＞u_0＞0Wherein u is_nAnd the value of (a) is rounded with the maximum value of the iterative computation type of the iterative computation module and the power quality data involved in the computation process.

n is an integer of not less than 3;

set up array A₁In order to realize the purpose,

A₁＝[u₀ u₀+Δs u₀+2·Δs … u₀+n·Δs]

＝[u₀ u₁ u₂ … u_n]

if the target values a and A are₁The medium numerical relationship is that,

f(u_i)＜a＜f(u_i+1)

and the function f is in the interval u₀，u_n]For a monotonically increasing function, the value range of result is determined as:

u_i＜result＜u_i+1，0<i<n

iteration 2, let u₀＝u_iAnd u and_n＝u_i

get the array A₂Is composed of

A₂＝[u_i u_i+Δs u_i+2·Δs … u_i+1]，0<j<n

＝[u_i+v₀ u_i+v₁ u_i+v₂ … u_i+v_n]

If the target values a and A are₂The medium numerical relationship is that,

f(u_i+v_j)＜a＜f(u_i+v_j+1)

and the function f is in the interval u₀,u_n]For a monotonically increasing function, the more accurate value range of result is:

u_i+v_j＜result＜u_i+v_j+1

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

u_i+v_j+w_k＜result＜u_i+v_j+w_k+1，0<k<n

the output result ≈ ui + vj + wk is the solution result of the function f (result) ═ a.

In any one of the above technical solutions, further, step S223 includes: the selection of the operation type and the switching of different functions f (result) are carried out by the operation type input and the state selection logic of the iterative computation module,

when the operation type input is 1SQRT (square-on-square), finding result1 to make result × result closest to a; the final calculation result is that result is result;

when the operation type input is 2ASIN (arcsine), finding result2, and making sin (result) closest to a; when a and/or b are not 0 and are not equal, if a < b, interchanging the numerical values of a and b, obtaining a phase result after iterative computation, and making the result be 90-result, which is a final arcsine computation result; otherwise, the final calculation result is that,

when the operation type input is 3SIN (sine), finding result3 to make arcsin (result) closest to a; the final result of the calculation is that,

when the operation type input is 4DIV (division), finding result4 to make result x b closest to a; the final calculation result is that result is i₀·10⁵+i₁·10⁴+i₂·10³+i₃·10²+i₄·10¹+i₅。

In any one of the above technical solutions, further, in the calculation process of the main calculation module, the calculation of the main calculation module is divided into three processes of basic operation, data calculation and electric energy quality calculation result by taking a round-robin period as a time duration of every 50 continuous 2k Hz sampling points is 1Cyc small-cycle period, a time duration of every 8Cyc continuous 2kHz sampling points is 1 round-cycle period, and a corresponding time duration of every 15 rounds is 3 s.

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 are,

g _ c is a cosine value reduced by n times of angle, g _ s is a sine value reduced by n times of angle, m _ a ' is a vector of g _ c sampling point amplified by m times according to the proportion of step _2, m _ b ' is a vector of g _ s sampling point amplified by m times according to the proportion of step _2, c is signal amplitude, theta ' is current signal phase, theta_old′For pre-recursionThe phase of the incoming signal, f is the frequency of the signal.

In any one of the above technical solutions, further, wherein the recursive DFT algorithm further includes a recursive mean filtering algorithm, and the calculating step includes:

first order filtering

Second order filtering

……

k order filtering

Wherein the SUM₁…SUM_kRespectively, k order recursive mean filtering results, A_k(n +1) is the n +1 value after the n value of the k-order recursive mean filtering section, A_k1 is the 1 st value of k-order recursive mean filtering segment (k is less than or equal to n).

Based on the same concept, the present application further provides a power quality measurement system based on a high-coupling iterative model, on which a computer program is stored, wherein the computer program, when executed by a processor, implements the power quality measurement method of the high-coupling iterative model according to any one of claims 1 to 8, the power quality measurement system of the high-coupling iterative model includes one or more programmable digital logic platforms according to any one of claims 1 to 8, including one or more programmable digital logic platforms including an iterative computation module, a digital selection logic, a multiplier, a RAM, a ROM, an interface for input and output, and one or more AD conversion modules connected between the internal components, for measuring a power quality parameter of the high-coupling iterative model.

The beneficial effect of this application is:

1. the invention integrates the sine, arcsine, division and square opening operations necessary in the power quality calculation, and only switches the operation types through different input values, so that the design can multiplex digital logic to a great extent, and the expenditure of logic resources is effectively reduced.

2. The invention is used for the complex operation in the multi-channel power quality measurement and calculation process, has the requirement of multiple channels, solves the problem of the complex operation in the multi-channel power quality measurement and calculation process, has the advantages of less occupied logic resources, meeting the requirement of the multi-channel operation, realizing the measurement of the power quality of multi-channel input signals, having simple external interfaces and rich operation results, effectively reducing the consumption of the operation resources of a processor, saving soft and hard resources which can be used for designing higher analysis functions, improving the intelligent degree of instruments and having good multi-functional intelligent integration and optimization.

3. The optimization processing of the power quality measurement system and the method designed by the invention occupies less computing resources, reduces frequent occupation and interruption of interactive transmission of intermediate data during operation, avoids blockage caused by data stream transmission in the computing process, greatly reduces the complexity of data processing and enhances the stability of the whole monitoring system.

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

Drawings

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

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

FIG. 3 is a diagram of arcsine function computation preprocessing partitions according to an embodiment of the present application;

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

fig. 5 is a flowchart of a basic operation 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 diagram according to an embodiment of the present application;

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

FIG. 8 is a flow chart of the operation of square accumulation of harmonic amplitude for every 8Cyc in an embodiment in accordance with the present application;

FIG. 9 is a flow chart of an operation for accumulating the degree of imbalance per Cyc according to an embodiment of the present application;

fig. 10 is a flowchart of an operation of accumulating zero sequence imbalance and negative sequence imbalance in the embodiment of the present application;

fig. 11 is a flow chart of power quality measurement output calculation according to an embodiment of the present application.

Detailed Description

The invention mainly aims to solve the problem of measuring the power quality, designs a power quality measuring method based on high-coupling-degree 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 power quality measurement and calculation process of a multi-channel alternating current and direct current signal, solves the problem that a large number of complex algorithms for solving square root, arcsine, sine and division are involved in the power quality measurement of the multi-channel alternating current and direct current signal, carries out the calculation in an embedded processor, occupies a large amount of operation resources of a computer processor, needs to frequently occupy interruption due to interactive transmission of intermediate data during operation, causes blockage to the transmission of data stream and increases the complexity of data processing, and easily causes the problem that the whole monitoring system is unstable.

The algorithm of the electric energy quality measurement model mainly comprises a main calculation module and an iterative calculation module, and the iterative calculation module with high coupling degree is designed by relying on a programmable logic device, wherein the iterative calculation module with high coupling degree 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 digital logic is multiplexed to a great extent by the design, and the expenditure of logic resources is effectively reduced.

On the basis, digital logics such as recursive DFT, recursive mean filtering, synchronous sampling, harmonic calculation, positive and negative zero sequence calculation, state control and the like are integrated in the main logic, and the measurement and the output of the power quality of the multi-channel input signal are realized.

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

In order that the above objects, features and advantages of the present application can be more clearly understood, the present application will be described in further detail with reference to the accompanying drawings and detailed description. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.

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 in other ways than those described herein, and therefore the scope of the present application is not limited by the specific embodiments disclosed below.

As shown in fig. 2, the iterative computation module is digital logic in a programmable logic device and is used for performing four complex operations, namely sine, arcsine, division and square opening, necessary for power quality computation. For the four problems, an iterative calculation mode is adopted, and due to the fact that the four problems have similar structures, high-coupling-degree integration is carried out, and resource reuse is carried out as much as possible, so that the purpose of reducing consumption of ROM, RAM and digital logic is achieved.

For the computation problems of square-open (SQRT), Arcsine (ASIN), Sine (SIN), and Division (DIV), the problem is described as: solve result, which is substituted into the corresponding function such that f (result) is closest to the target value a.

Further specifically, for solving the open square root problem (SQRT, i.e., solving) The problem can be described as: find result, make result × result closest to a.

For solving an arcsine problem (ASIN, i.e., finding result ═ arcsin (a)), the problem can be described as: result is calculated with sin (result) closest to a.

For solving the sine problem (SIN, i.e. finding result ═ SIN (a)), the problem can be described as: find result, make arcsin (result) closest to a.

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

The solving problems of SQRT, ASIN, SIN and DIV can be solved by an iterative method after being described above. The general process is as follows:

iteration 1, let u_n＞u_0＞0，

n is an integer of not less than 3;

u₀and u_nThe values of (a) are related to the type of computation and the range of minimum and maximum values that may be involved in the computation, respectively.

In actual design, the number of bits of the AD is limited, so the calculation module does not solve the calculation problem of all the numbers within plus and minus infinity. But to solve the problem of data calculation in which the maximum calculation range is not exceeded in the calculation. u. of_nThe value of (2) gives consideration to the data range, precision and iteration algebra, and is slightly larger than or equal to the maximum value possibly appearing in the calculation process.

Set up array A₁To make u_n＞u_0＞0，

A₁＝[u₀ u₀+Δs u₀+2·Δs … u₀+n·Δs]

＝[u₀ u₁ u₂ … u_n]

If the target values a and A are₁The median values have the following relationship,

f(u_i)＜a＜f(u_i+1)

and the function f is in the interval u₀,u_n]Is a monotonically increasing function, and then,

u_i＜result＜u_i+1，0<i<n

this completes the first cycle of iterative calculations and roughly determines the value range of result.

The 2 nd iteration, the order,

set up array A₂Is composed of

A₂＝[u_i u_i+Δs u_i+2·Δs … u_i+1]，0<j<n

＝[u_i+v₀ u_i+v₁ u_i+v₂ … u_i+v_n]

If the target values a and A are₂The median values have the following relationship,

f(u_i+v_j)＜a＜f(u_i+v_j+1)

and the function f is in the interval u₀,u_n]Is a monotonically increasing function, and then,

u_i+v_j＜result＜u_i+v_j+1

this completes the iteration calculation for cycle 2 and the value range of result is more accurate than for the first time.

After 3 iterations are set, a relationship is obtained,

u_i+v_j+w_k＜result＜u_i+v_j+w_k+1，0<k<n

then it can be considered that result ≈ u_i+v_j+w_kThe result of the approximate solution for the function f (result) ═ a. The more the iteration times, the more accurate the calculation result, and the more the operation steps and the longer the time consumption. The iteration times in the algorithm are properly selected according to the power quality precision.

For SQRT, ASIN, SIN and DIV problems, the iteration processes are consistent, and only the functions f are different, the iteration times are different, and the preprocessing and later processes are different. The different parts can be selected and switched by the operation type input and the state selection logic of the iteration module. Therefore, the solving problem of four complex operations of SQRT, ASIN, SIN and DIV can be completed by an iterative computation digital logic.

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

the multiplier module is designed as above formula for the convenience of the two-angle sum calculation in the trigonometric function:

if only two numbers need to be multiplied, let c₁、d₁Equal to 0.

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

After discussing the iterative computation principle, the 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 is equal to 0, the calculation results can be directly obtained without entering a round of iteration. The case of equality is not discussed further below.

The technical solution of the present invention will be described in more detail with reference to the accompanying drawings.

As shown in fig. 1, external multi-channel analog signal streams are sequentially input to the AD converter, and the AD conversion module converts the analog signals into digital signal streams and transmits the digital signal streams to the AD driver module of the connected programmable logic device to drive different data streams to be transmitted to each computing module of the power quality computing module.

As shown in fig. 4, in the main computing module of the power quality computing module, data sampling is performed on the received 100Hz sampling data stream to obtain a 2kHz data stream. The whole algorithm of the calculation process of the power quality measurement is mainly divided into four parts of data sampling, basic operation, data statistics and power quality calculation results. Wherein, the time length of every 50 continuous 2kHz sampling points is defined as 1 Cyc; every 8Cyc is defined as 1 bounce and is equal to the duration of 10 cycles of 50Hz alternating current signals; every 15 bounchs corresponds to a duration of 3 s.

As shown in fig. 1, the storage module in the main computing module sequentially performs a cyclic storage step on each data point of the received 2kHz sampling point in the storage chip, and sequentially stores the acquired data in the RAM and/or ROM of the power quality computing module, wherein the data sampling process is as follows: the 24 channels 100kHz sampled serial data stream is converted to a 2kHz data stream after being sampled by the data. For an AC signal with a nominal frequency of 50Hz, there are 40 samples for 1 cycle at a sampling rate of 2 kHz. And reading the sampling data and performing continuous cyclic storage by the calculation model. Each channel cycle stores 90 consecutive sample values.

That is, the basic operation steps are as shown in fig. 5, and sequentially include: performing serial calculation on each channel of 1kHz and 24 channels to obtain phasor, amplitude, phase difference and frequency (f) corresponding to input waveforms of each channel at the moment; wherein, as shown in FIG. 6, every 1kHz, the next channel is re-sampled at 2kHz according to the first frequency calculation result (f) in Cyc, and then DFT operation is performed to obtain the channel with higher precisionPhasor (a + bi), amplitude (c1), direct current amplitude (c0), harmonic amplitude (c0)₂、c₃、...c₁₉) And (3) calculating results, wherein the K value is the ratio of each channel to the last sampling frequency when 24 channels are re-sampled at 2kHz according to the first frequency calculation result (f) in Cyc at every 1kHz, and the re-sampling starting point of each channel is the same so as to ensure that the calculation result is synchronous data.

Further specifically, the basic operation process is: every 1Cyc, the time is calibrated according to the sampling rate of 2kHz, and 50 sampling moments are 1, 2 to 50. Let time t be denoted 1, 2, … …, 50. The base operation is performed every 1 data sample time (i.e., t2, 4, 6, … …, 50). The basic operation aims to obtain the phasor, amplitude, phase difference in unit time (phase difference for short) and frequency of each channel input signal, and the calculation result in the basic operation is stored in the RAM. The basic operation is based on a recursive DFT algorithm, which is calculated by,

g _ c is a cosine value reduced by n times of angle, g _ s is a sine value reduced by n times of angle, m _ a ' is a vector of g _ c sampling point amplified by m times according to the proportion of step _2, m _ b ' is a vector of g _ s sampling point amplified by m times according to the proportion of step _2, c is signal amplitude, theta ' is current signal phase, theta_old′The phase of the input signal before recursion, f is the signal frequency.

In order to eliminate the problem of measurement error caused by frequency deviation of rated signal, a recursive mean filtering algorithm is carried out to obtain a high-precision frequency measurement result, and the calculation formula is as follows,

first order filtering

Second order filtering

……

k order filtering

As shown in fig. 4 and 6, a high-precision calculation is performed once every 1Cyc after the basic calculation is completed. The operation content comprises the following steps: synchronous sampling, DFT direct current and harmonic component calculation. When t is 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 then performing DFT operation to obtain direct current components and harmonic amplitudes. Defining n resample points obtained by a resampling algorithmx_iFor resampling sequence X_r. Defining the h-component DFT coefficients (amplified by g times integer) as,

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

the amplitude of the h-th-order component is calculated by the formula,

the basic operation includes a recursive DFT algorithm, a recursive mean filtering algorithm, a synchronous sampling operation, a main calculation module function calculation for defining h-order component DFT coefficients, h-order component DFT phasor calculation and h-order component amplitude calculation, and in the main calculation module, in the calculation process, it is necessary to convert the operation of division into multiplication calculation through a data selection logic module, select and call a multiplier to calculate multiplication operation, and transmit the result back to the main calculation module, as shown in fig. 1. The above-mentioned SQRT, ASIN, SIN, DIV problems in the operation are solved by the iterative computation module for the operation data and operation type input in the main module, respectively, where the operation type input is 1), SQRT (square, 2), ASIN (arcsine), 3, SIN (sine), 4, DIV (division) and the input a, b, and c of the operation data, and the iterative computation module passes through S221: initializing signal data according to the operation type transmitted by the main calculation module; s222: the iterative computation module carries out iterative computation according to the operation type; s223: selecting and processing subsequent calculation modules according to the operation type; s224: outputting the calculation result2: result ═ arcsin (b/c), 3: result ═ sin (a) and 4: result ═ a/b.

The specific content of the high-coupling-degree iterative computation module is as follows, and further specifically, the solving of the SQRT is as follows:

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

first, iteration 1, constructing array A₁，

A₁＝[0 2⁰·Δs 2¹·Δs … 2ⁿ·Δs]

＝[u₀ u₁ u₂ … u_n]

Wherein, let u_n＞u_0＞0N is an integer larger than zero, the maximum value range which can be expressed in the calculation process according to the AD digit acquired by the system signal is determined and calculated,

finding out interval satisfaction

Then the process of the first step is carried out,

u_i＜result＜u_i+1

iteration 2, construct array A₂，

Order to

The calculation is carried out according to the calculation,

the found interval is satisfied with the result that,

then the process of the first step is carried out,

through multiple iterations, the range can be reduced, and the value of result is determined, so that

More specifically, as shown in FIG. 3, a general arcsine calculation is to solve the arcsin (a) problem. In the invention, ASIN is carried out to obtain the signal phase after the phasor of the signal is expressed as a + bj by DFT, and the signal amplitude is set asTherefore, the ASIN problem in the invention refers to solving arcsin (b/c) problem.

The solution to ASIN is specifically: the main calculation module inputs the operation type 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 for ASIN.

Firstly, if (a, b) is located at the x-axis, the y-axis or the center of the circle, the result can be directly obtained, and the result can be known to be 0 ° (including the center of the circle), 90 °, 180 °, 270 ° or 360 ° according to the position information, so that iterative calculation is not needed. If (a, b) is not the axis area or the center of the circle, the 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 approaches 90 °. Therefore, as x approaches 90 °, the calculation error increases. The operational relationship according to the trigonometric function is,

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 interval is divided into two regions. When a is b, result is 45 °, the iterative calculation process is also skipped, and the result is directly obtained. Otherwise, if a < b, interchanging the values of a and b, obtaining a phase result after iterative calculation, and making the phase result be 90-result, which is the final arcsine calculation result. After the logic of the section is added, all the arcsine operations are within the range of 0-45 degrees, and the problem of precision reduction caused by approaching 90 degrees is avoided. The normal iteration logic is entered below.

When calculating arcsine, use 2¹²4096 denotes 90 °, u_nIs 4096, n is 8, u₀4096/8-512. In each iteration, the evaluation range is refined by 1/n, namely 1/8, and after 4 iterations, the data range can be refined to 4096/(8)⁴) The accuracy of the arcsine calculation is 90 °/4096 — 0.0219 °.

Iteration 1, constructing array A₁，

Wherein g is a power of 2, and is used for scaling up numerical values and avoiding floating point operations. A. the₁Is a known value, is stored in the ROM, and is directly obtained by accessing the ROM when performing the calculation.

Calculation, B₁＝cA₁＝[c·g·sin(α₀) c·g·sin(α₁) c·g·sin(α₂) … c·g·sin(α₈)]

Where c is the amplitude of the signal phasor a + bj, as previously described, is,

the interval is obtained by the comparison and,

c·g·sin(α_i)＜g·b＜c·g·sin(α_i+1)

therefore, the temperature of the molten steel is controlled,

α_i＜result＜α_i+1

iteration 2, construct array A₂，

The calculation is carried out according to the calculation,

B₂＝c·A₂

if the result is obtained by comparison, the result is obtained,

c·g·sin(α_i+β_j)＜g·b＜c·g·sin(α_i+β_j+1)

therefore, the temperature of the molten steel is controlled,

α_i+β_j＜result＜α_i+β_j+1

iteration 3, construct array A₃，

The same algorithm is adopted to obtain the result,

c·g·sin(α_i+β_j+γ_k)＜g·b＜c·g·sin(α_i+β_j+γ_k+1)

it can be approximately assumed that,

and finally, correcting the result. and if the values of a and b are interchanged, making result equal to 90-result, otherwise, making result constant. According to the quadrant position of (a ', b'), correcting result,

with this approach, only a maximum of 24 sine values need to be stored, and the effective resolution is,

more specifically, solving for SIN specifically includes: the sine calculation is the reverse process of the sine inversion calculation, and the value range of the angle a in the solving problem result sin (a) is 0-360 degrees/m k_m. Here, m is the number of points per cycle when DFT computation is performed on a signal of a rated frequency (50 Hz in a general power system). k is a radical of_mA margin is left for frequency fluctuations. The sine function does not need to be solved in a range of 0-90 degrees, because the sine function is related to a synchronous sampling algorithm, and the algorithm ensures that the value of a has a certain range. The algorithm can be simplified. Where m is 20, k_mThe iterative calculation process of SIN is explained as 1.5. The maximum angle can be calculated as 360 °/20 × 1.5 — 27 °.

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

first, iteration 1, constructing array A₁，

[u₀ u₁ u₂ … u_n]

If the result is obtained by comparison, the result is obtained,

u_i＜a＜u_i+1

iteration 2, construct array A₂，

[u_i+v₀ u_i+v₁ u_i+v₂ … u_i+v_n]

If the result is obtained by comparison, the result is obtained,

u_i+v_j＜a＜u_i+v_j+1

iteration 3, construct array A₃，

If the result is obtained by comparison, the result is obtained,

u_i+v_j+w_k＜a＜u_i+v_j+w_k+1

then there is a change in the number of,

finally, the sine calculation result can be obtained by calculation according to two angles of the trigonometric function and a formula,

the calculation method just needs to store 3 × 8 — 24 sine values in the ROM. Effectively reducing the consumption of ROM.

More specifically, the solving of the DIV is specifically: the design choice of the present application is for 16-bit AD, so the maximum value is 2^15 ^ 32768. The division result does not exceed 99999, so the division result is obtained.

For division, it is assumed that the signal acquisition of the system adopts 14-bit AD, and the maximum value of the amplitude of the signal after symbol removal is 2¹³8192 (four-digit), so when calculating a discrete division, u_nThe initial value set to 10000 (five digits) is certain to satisfy the calculation requirement. If u is to be_nThe setting of 100000 (six digits) is not indispensable, and the calculation result with the same precision can be obtained only by one more iteration, so that u is not necessary according to the actual situation at present_nSet to 100000 (six digits).

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

first, in iteration 1, let u_n＞u_0＞0Construct array A₁Is composed of

A₁＝[0 1·10⁵·b 2·10⁵·b … 9·10⁵·b]

＝[u₀ u₁ u₂ … u₉]

If the comparison is successful, the result is that,

u_i0＜a＜u_i0+1

then the process of the first step is carried out,

i₀·10⁵＜result＜(i₀+1)·10⁵

iteration 2, construct array A₂Is composed of

A₂＝[u_i0+0 u_i0+1·10⁴·b u_i0+2·10⁴·b … u_i0+9·10⁴·b]

＝[u_i0+v₀ u_i0+v₁ u_i0+v₂ … u_i0+v_n]

If the comparison is successful, the result is that,

u_i0+v_i1＜a＜u_i0+v_i1+1

then the process of the first step is carried out,

i₀·10⁵+i₁·10⁴＜result＜i₀·10⁵+(i₁+1)·10⁴

similarly, the 3 rd to 6 th iteration is carried out again, and i can be confirmed in sequence₀、i₁、i₂、i₃、i₄、i₅Magnitude of the value. And finally, obtaining the result of the calculation that,

result＝i₀·10⁵+i₁·10⁴+i₂·10³+i₃·10²+i₄·10¹+i₅

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

The data statistics operation is used for finishing the electric energy quality measurement and giving a calculation result, and the method comprises the following steps: statistical calculations are required for every 1Cyc (as shown in FIGS. 6 and 8) or every 8Cyc (as shown in FIGS. 7 and 9). The statistical operation is performed every 120Cyc (i.e. 15 bounce, 3s duration) to obtain the final power quality calculation result, and the calculation schematic diagram is shown in FIG. 10 and FIG. 11. The electric energy quality operation result comprises voltage deviation, fundamental frequency, harmonic content, total harmonic distortion rate, positive and negative zero sequence components, negative sequence unbalance and zero sequence unbalance.

The further concrete calculation steps are as follows: every 1kHz sampling point needs to be subjected to basic operation; performing high-precision calculation once on the basis of every 1kHz operation every 1Cyc, performing data statistics once every 1Cyc as shown in FIG. 4, and obtaining phasor, amplitude, frequency (f) and direct current amplitude (c) of 24 channels for serial calculation as shown in 6 in the specific step process₀) Fundamental amplitude (c)₁) Harmonic amplitude (c)₂、c₃、.....c₁₉) Accumulating, summing and storing; as shown in fig. 9, the three-phase channel is calculated to obtain the positive and negative zero-sequence components, and the negative sequence imbalance (e) is calculated₁) Zero sequence unbalance (e)₀) And the calculation results are subjected to summation and accumulation at the same time.

Each 1 boot includes 8Cyc, equal to 10The duration of the 50Hz alternating current signal of each cycle; as shown in FIG. 8, the statistical data calculation is continued for 24 channels per channel harmonic amplitude cumulative sum (c) every 1bounch (i.e., every 8Cyc)_{2_s1}、c_{3_s1}、.c_{19_s1}) Carrying out primary average operation, and accumulating, summing and storing after squaring; as shown in fig. 10, the negative sequence imbalance cumulative sum (e) of the three-phase channels_{2_s1}) Zero sequence imbalance cumulative sum (e)_{0_s1}) And carrying out primary averaging operation, squaring, accumulating, summing and storing.

And performing necessary averaging or root mean square calculation according to the calculation requirement of the power quality every 15bounch, and finally obtaining a power quality calculation result. The specific process is as follows: every 120Cyc (namely 3s), as shown in FIG. 1, a power quality calculation result is obtained once and stored in a ROM or RAM in the power quality calculation module for calling and transmitting internal data, input data can be transmitted to more functional modules designed subsequently, and the calculated power quality calculation result is communicated and output externally. The sum (c) is accumulated for the DC amplitude values as shown in FIG. 7_{0_sum}) Sum of fundamental amplitude values (c)_{1_sum}) Frequency sum (f)_{_sum}) Carrying out average operation to obtain a power quality calculation result:

as shown in FIG. 9, the negative sequence imbalance is further summed up by a sum (e)_{2_sum}) Zero sequence imbalance accumulated sum (e)_{0_sum}) The cumulative summed DC amplitude (c) is shown in FIG. 10_{0_sum}) Fundamental frequency (f)_{1_sum}) And the amplitude c of the fundamental wave_{1_sum}Arithmetically averaging over 120Cyc cycles, and then summing the harmonic amplitudes (c)_{2_sum}、c_{3__sum}、...c_{19_sum}) Comparing the root mean square calculation with the fundamental wave amplitude c_1RObtaining the amplitude (c) of each harmonic_2R、c_3R、...c_19R) Harmonic content (HR)₂、HR₃、...HR₁₉) By root mean square of the sum of the squares of the amplitudes of the harmonics and the amplitude c of the fundamental wave_1RAnd obtaining the total fundamental wave distortion rate THR of the calculation result of the power quality.

Cumulative sum of negative sequence imbalance e_{2_sum}Sum zero sequence imbalance cumulative sum e_{0_sum}The negative sequence imbalance e is obtained at the arithmetic square root of 15 bound cycles_2RAnd the degree of unbalance of zero sequence e_0RThe power quality calculation module is stored in a memory ROM or RAM in the power quality calculation module, is used for calling and transmitting internal data, can transmit input data to more functional modules designed subsequently, and simultaneously carries out external communication and output on the calculated power quality calculation result.

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

The units in the device can be merged, divided and deleted according to actual requirements.

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