Three-phase alternating current barostat control method for industrial big data electric energy optimization

Abstract

The invention relates to the technical field of electric energy optimization control, in particular to a three-phase alternating current barostat control method for industrial big data electric energy optimization, which comprises the following steps of: receiving a historical load harmonic data set covering multiple dimensions in an industrial big data platform, the historical load harmonic data set is classified and divided in a two-dimensional mode to form refined data subsets; a suppression target interval corresponding to each refined data subset is analyzed, and corresponding target harmonic waves are set; training an equivalent impedance model of each refined data subset; the equivalent impedance model is used for inputting current load harmonic data, outputting optimal impedance estimation corresponding to target harmonic and then calculating corresponding harmonic compensation current; and receiving a plurality of continuous harmonic voltages after outputting the harmonic compensation current, constructing a plurality of harmonic voltage sequences, analyzing a plurality of disorderly changing harmonic voltage sequences, and adjusting the target harmonic based on the harmonic voltage sequences.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric energy optimization control, in particular to a three-phase alternating current constant voltage controller control method for industrial big data electric energy optimization. BACKGROUND

[0002] In the industrial big data scene, due to the presence of frequency converters, rectifiers, electric arc furnaces and other various types of electrical equipment in the factory, the nonlinear characteristics of these devices will cause 3, 5, 7 and other different times of harmonic voltage in the power grid, and the presence of harmonic voltage will cause problems such as increased device heating, accelerated insulation aging, decreased precision of precision instruments, and even failure shutdown; Therefore, the existing means sets the corresponding harmonic suppression target interval through the system parameter configuration module based on the power quality national standard requirements of the industrial power grid, the harmonic tolerance threshold of the electrical equipment and the load characteristics of the actual production scene, and the harmonic suppression target interval clearly defines the allowed peak value, the upper limit of the effective value and the total harmonic distortion (THD) control standard of the harmonic voltage of each characteristic frequency (such as 3, 5, 7, etc.); Then compare this harmonic suppression target interval with the real-time harmonic data of the power grid collected at present, to determine whether there is an abnormal situation where the harmonic voltage exceeds the suppression interval; After the harmonic voltage is abnormal, further collect and analyze the real-time operation data of the power grid through the harmonic detection algorithm (such as the fast Fourier transform FFT algorithm, the synchronous phasor measurement algorithm or the detection algorithm based on the instantaneous reactive power theory), accurately extract the amplitude, phase, frequency and harmonic component ratio of each characteristic frequency harmonic voltage Key parameters, and then according to the set suppression target interval and harmonic component measured data, through the compensation current calculation model (including phase cancellation strategy, amplitude matching algorithm and dynamic adjustment coefficient) iterative operation, finally determine the accurate value of the harmonic compensation current corresponding to each characteristic frequency, and then output accurate compensation current parameters and equipment adjustment instructions, so as to instruct the staff to adjust the operating parameters of the harmonic control equipment (such as active power filter APF) in a targeted manner, so as to control the harmonic voltage within the national standard allowed range, ensure the stability of the power quality of the power grid and the safe and efficient operation of the equipment, and achieve the effect of However, although the harmonic suppression target interval is set through the above process, in the actual operation of the industrial power grid, the load mutation caused by the start-stop switching of the power equipment, the dynamic operation characteristics of the nonlinear devices such as frequency converters, the real-time fluctuations of the grid impedance parameters, the external electromagnetic interference, and the mutual coupling of harmonic components of different characteristic frequencies will cause deviations between the preset harmonic suppression target interval and the actual harmonic state of the power grid (including the specific cases of mismatch between the interval threshold and the actual harmonic amplitude, phase compensation reference offset, dynamic response lag, etc.), further causing the harmonic compensation current calculated based on the deviation interval to have insufficient precision, slow dynamic response, excessive or insufficient compensation, etc., which is specifically manifested in the reduction of the amplitude matching degree of the compensation current and the target harmonic component, incomplete phase cancellation, lagging tracking and adjustment of sudden harmonic fluctuations, and even harmonic amplification and other abnormal situations. Therefore, field personnel usually manually adjust the amplitude correction coefficient of the compensation current, the phase compensation offset, and the dynamic response speed parameters, etc. based on the harmonic compensation current output by the system and combined with long-term accumulated field operation experience to further optimize the harmonic compensation current, so as to accurately cancel the actual harmonic components of the power grid and control the harmonic voltage within the range allowed by the national standard. Although this manual experience adjustment method can compensate for the deficiencies of the system calculation to a certain extent and temporarily improve the harmonic control effect, it still has significant limitations, including that the adjustment process relies on the professional skills and experience accumulation of the personnel, the subjective nature leads to uneven adjustment accuracy, the adaptability to complex harmonic coupling scenarios is insufficient, the adjustment efficiency is low and cannot respond to the dynamic changes of the power grid in real time, and excessive adjustment may cause new power grid voltage fluctuations, thereby affecting the operation stability of the harmonic control equipment and the power quality of the entire power grid system. To effectively avoid the problems of insufficient harmonic compensation current precision, slow dynamic response, excessive or insufficient compensation caused by the deviation between the preset harmonic suppression target interval and the actual harmonic state of the power grid, and the subjective nature, uneven accuracy, poor adaptability, low efficiency and easy to cause new power grid voltage fluctuations of the manual experience adjustment method, and to ensure the stable and standard power quality of the industrial power grid and the safe and efficient operation of the power equipment, the present application provides an intelligent control method for a three-phase alternating current constant voltage regulator based on industrial big data. SUMMARY

[0003] The present application aims to solve the problem of harmonic compensation current precision reduction, unstable harmonic suppression effect, and even exceeding the national standard limit in the dynamic operating conditions of the power grid caused by the fixed target harmonic and insufficient adaptability of the suppression interval in the existing harmonic control scheme.

[0004] To achieve the above-mentioned purpose, the present application provides a three-phase alternating current constant voltage regulator control method for industrial big data power optimization, comprising the following steps: S1, receiving a multi-dimensional historical load harmonic dataset in an industrial big data platform , two-dimensional classification and division of historical load harmonic dataset , forming a refined data subset ; and analyzing each refined data subset corresponding to the suppression target interval , setting the corresponding target harmonic ; S2, receiving the refined data subset of the nth harmonic voltage in step S1 , establishing the equivalent impedance model corresponding to the nth harmonic voltage by the least square method; After establishing the equivalent impedance model, if the corresponding refined data subset is matched by receiving the current load harmonic data, the corresponding suppression target interval in step S1 is called out, if the harmonic voltage in the current load harmonic data is not in the suppression target interval , the corresponding equivalent impedance model is called out; the current load harmonic data is input into the corresponding equivalent impedance model, and the equivalent impedance model outputs the target harmonic corresponding to the optimal impedance estimation , and then the corresponding harmonic compensation current is calculated; Step S3, receiving a plurality of continuous harmonic voltages after outputting the harmonic compensation current , setting a fixed window with a length of , and sequentially selecting harmonic voltages consistent with the fixed window length to form a plurality of harmonic voltage sequences ; and analyzing the change trend of each harmonic voltage sequence, when the latest harmonic voltage is not in the suppression interval , adjusting the target harmonic through a plurality of disordered harmonic voltage sequences .

[0005] As a further improvement of the technical solution, in the historical load harmonic dataset , represents the load working condition category, represents the harmonic number, represents the harmonic voltage corresponding to the working condition and the number; As a further improvement of the technical solution, the historical load harmonic dataset is divided into a refined data subset in step S1 : for each load working condition category and each harmonic number , extract the historical load harmonic dataset Simultaneously satisfy and All data (with the same harmonic order) are used to form a refined data subset. .

[0006] As a further improvement to this technical solution, in step S1, after retrieving each refined data subset to determine the harmonic voltage anomaly, the input harmonic compensation current... and input harmonic compensation current The harmonic voltage after Then through harmonic voltage Analyze the adjustment patterns and ranges corresponding to the refined data subsets, and set the suppression target interval for each refined data subset. Specifically, the harmonic compensation current input each time is retrieved. The first harmonic voltage after Select the maximum and minimum values ​​and set them as the target suppression interval. .

[0007] As a further improvement to this technical solution, step S1 calculates the suppression target interval. The mean value is set as the target harmonic. : .

[0008] As a further improvement to this technical solution, the specific steps for establishing the equivalent impedance model in step S2 are as follows: S2. Filter out multiple refined data subsets middle Harmonic voltage phasors acquired synchronously by the group With harmonic current phasor As sample data; S2. Based on linear circuit theory, the first... The equivalent impedance of the power grid to subharmonics It is a constant, that is, the first Under the first harmonic, the power grid affects the first harmonic. The blocking capability of subharmonics does not change abruptly with time or operating conditions; specifically... For harmonic resistors, For harmonic reactance, For phase shift; and measurement and system disturbance errors For zero-mean white noise, an equivalent impedance model is established to describe the first... The relationship between subharmonic voltage, current and equivalent impedance; S2. Minimize the sum of squared errors for all sample data, and define the objective function. The sum of squares of the error moduli for each sample data: ; For the objective function Regarding the equivalent impedance of the power grid conjugate Find the partial derivatives (due to complex number operations, the conjugate derivative is needed to ensure the validity of the extremum), and set the partial derivatives to zero to calculate the value that makes the objective function... Minimum optimal impedance estimate : ; in This represents the complex conjugate and simultaneously performs joint estimation of the harmonic impedance amplitude and phase, resulting in the optimal impedance estimate. Equivalent impedance of the power grid The unbiased optimal estimate; S2.4. Organize the harmonic currents and voltages of all samples into a matrix form, where the current sample matrix is... Voltage sample matrix Then the matrix for the optimal impedance estimation is: ; in: Current sample matrix The conjugate transpose, through the current sample matrix Performing the conjugate transpose yields: ; Represents the complex conjugate, with a matrix dimension of N rows × 1 column, where each row is the complex conjugate of the original sample current; matrix multiplication The inverse matrix; S2.5 Repeat the above steps for all characteristic harmonics and non-characteristic harmonics to finally establish an equivalent impedance model with a linear voltage-current relationship corresponding to all harmonic orders. That is, each refined data subset in step S1 The corresponding equivalent impedance model.

[0009] As a further improvement to this technical solution, the equivalent impedance model in step S2 is as follows: ; in: , For the first The first sample Second harmonic voltage amplitude For the corresponding phase; , For the first The first sample Second harmonic current amplitude For the corresponding phase; For the first Error term for each sample.

[0010] As a further improvement to this technical solution, step S2 calls up the first... Target range for suppressing subharmonic voltage Based on Ohm's law and employing optimal impedance estimation Calculate harmonic compensation current ,in For the current measurement of the first Subharmonic voltage The target harmonic.

[0011] As a further improvement to this technical solution, the analysis in step S3 is as follows: Harmonic voltage sequence Is it ordered? Establish a linear fitting model ,in The slope reflects the harmonic voltage sequence. The intensity of the changing trend; The intercept represents the harmonic voltage sequence. The baseline level; Calculate goodness of fit ,in For the first Harmonic voltage sequence The mean.

[0012] Set a goodness-of-fit threshold If the goodness of fit ≤ goodness-of-fit threshold and Then determine the harmonic voltage sequence. If it is disordered, it is judged as ordered.

[0013] As a further improvement to this technical solution, step S3 retrieves multiple harmonic voltages from multiple disordered harmonic voltage sequences to form a harmonic voltage set. ,in The harmonic voltage is not in the suppression range The number of subsequent harmonic voltage sequences; and the selection of harmonic voltage sets. The median is set as the target harmonic. .

[0014] Beneficial effects: By step S1, the historical load harmonic data set is classified into multiple refined data subsets according to the load working condition category C and the harmonic order h, so that the system can accurately select and focus on the massive and chaotic historical harmonic data, extract the targeted data under specific working conditions and specific harmonic orders, and provide high-quality basic data for subsequent step S2 equivalent impedance modeling and target harmonic selection, avoiding the deviation of the equivalent impedance model caused by irrelevant data interference; Further, by setting the suppression target interval corresponding to each refined data subset, the pain points of the traditional method of presetting the suppression target interval and the deviation of the actual harmonic state of the power grid (such as the mismatch between the interval threshold and the harmonic amplitude, and the phase compensation reference deviation) are avoided, and the suppression target interval is accurately adapted to the actual operating characteristics of different working conditions and different harmonic orders through data subdivision and interval customization, replacing the traditional unified and fixed interval setting mode. Through step S2, the equivalent impedance model of all harmonic orders is established based on the linear circuit theory and the least squares method, the harmonic voltage is quantified, and then the equivalent impedance of each harmonic is accurately obtained through the unbiased optimal estimation formula based on the internal correlation between current and impedance, breaking through the precision limitation of traditional impedance estimation and providing a scientific basis for the quantitative calculation of harmonic compensation current, making the harmonic control quantitative from qualitative. Step S3 judges the ordered and unordered harmonic voltage sequences by analyzing the multiple consecutive harmonic voltages after outputting the harmonic compensation current, and then selects the mode of the unordered harmonic voltage sequence again to adjust the target harmonic in step S1, thereby effectively avoiding the repeated misoperation of the compensation strategy caused by the continuous small amplitude fluctuation of the harmonic voltage, avoiding the deviation of the preset suppression target interval and the actual harmonic state, and the strong subjectivity and low efficiency of manual adjustment, so that the target harmonic always fits the real operating characteristics of the power grid, ensuring the accuracy and dynamic response of the harmonic compensation current calculation, and further improving the stability and long-term effectiveness of the harmonic control.

[0015] In addition to the purposes, features and advantages described above, the present application has other purposes, features and advantages. The present application will be further described in detail below with reference to the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 The overall working steps of the present application are shown in the figure. DETAILED DESCRIPTION

[0017] The technical solutions in the embodiments of the present application will be described in detail below with reference to the drawings in the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0018] refer to Figure 1 As shown, a three-phase AC constant voltage regulator control method for industrial big data power optimization includes the following steps: S1. Receives a multi-dimensional historical load harmonic dataset from the industrial big data platform. Historical load harmonic dataset is classified into two dimensions. To form a refined subset of data And analyze each refined subset of data. Corresponding suppression target range Set the corresponding target harmonics ; S2, receiving step S1 is the first Refined data subset of subharmonic voltage Establish the first by least squares method Equivalent impedance model corresponding to subharmonic voltage; After establishing the equivalent impedance model, if the current load harmonic data is received, the corresponding refined data subset can be matched. And retrieve the corresponding suppression target region from step S1. If the harmonic voltage in the current load harmonic data is not within the suppression target range Within the range, the corresponding equivalent impedance model is retrieved; the current load harmonic data is input into the corresponding equivalent impedance model, and the equivalent impedance model outputs the target harmonic. Corresponding optimal impedance estimation Then calculate the corresponding harmonic compensation current. ; Step S3: Receive the output harmonic compensation current The subsequent multiple consecutive harmonic voltages, with a set length of For a fixed window, select the window with the specified length in sequence. Consistent harmonic voltages form multiple harmonic voltage sequences. ; And analyze the changing trend of each harmonic voltage sequence, when the latest harmonic voltage is not in the suppression range. Subsequently, the target harmonic is adjusted using multiple randomly varying harmonic voltage sequences. .

[0019] In the implementation of the above embodiments, in one embodiment, the specific implementation process of step S1 is as follows: The present example further considers that after the worker optimizes the harmonic compensation current again on the basis of the system calculation output, the corresponding harmonic voltage will present a change rule strongly associated with manual optimization operation at this time, and the change rule strictly meets the limit value requirements of the national standard for power quality of industrial power grids on harmonic voltage and the harmonic tolerance characteristics of long-term safe operation of equipment, thereby providing sufficient experience data support for correcting the setting deviation of the harmonic suppression target interval, improving the calculation accuracy of the harmonic compensation current based on data driving, and then realizing dynamic adaptation of the harmonic control effect to the actual working conditions; Step S1 receives a historical load harmonic data set covering multiple dimensions in the industrial big data platform , the historical load harmonic data set is classified and divided into two dimensions , a refined data subset is formed , and then the corresponding suppression target interval of each refined data subset is set , and the corresponding target harmonic is set , specifically: The working principle of dividing the historical load harmonic data set into a refined data subset in step S1 is as follows: In the historical load harmonic data set , represents the load working condition category, represents the harmonic order, represents the harmonic voltage under the corresponding working condition and order; For each load working condition category and each harmonic order , all data in the historical load harmonic data set that simultaneously satisfy (the load working condition categories are the same) and (the harmonic orders are the same) are extracted to form a refined data subset , in step S1, the massive historical load harmonic data is accurately subdivided according to the load working condition and the harmonic order through two-dimensional classification and division, so that each refined data subset focuses on harmonic data of a specific working condition and a specific order, thereby providing accurate and targeted basic data support for subsequent step S2 of establishing an equivalent impedance model for different working conditions and different order harmonics, The working principle of step S1 for setting the corresponding suppression target interval of each refined data subset is as follows: after each refined data subset judges the harmonic voltage anomaly, the input harmonic compensation current (specifically, the harmonic compensation current corrected manually by the on-site worker) and the input harmonic compensation current The harmonic voltage after Then through harmonic voltage Analyze the adjustment patterns and ranges corresponding to the refined data subsets, and set the suppression target interval for each refined data subset. Specifically, the harmonic compensation current input each time is retrieved. The first harmonic voltage after Select the maximum and minimum values ​​and set them as the target suppression interval. ; And due to the above-mentioned suppression target interval The reasonable fluctuation range of harmonic voltage is determined based on historical manual optimization. Its upper and lower limits fully cover the on-site operating condition adaptation requirements and national standard limits. Therefore, the target suppression range is calculated. The mean value is set as the target harmonic. This provides a clear and stable reference for calculating the harmonic compensation current in the subsequent step S2.

[0020] In one embodiment, the specific implementation process of step S2 is as follows: receiving the first... Refined data subset of subharmonic voltage Establish the first by least squares method The equivalent impedance model corresponding to the subharmonic voltage provides theoretical support for the subsequent calculation of harmonic compensation current. After establishing the equivalent impedance model, if the current load harmonic data is received, the corresponding refined data subset can be matched. And retrieve the corresponding suppression target region from step S1. If the harmonic voltage in the current load harmonic data is not within the suppression target range Within the range, the corresponding equivalent impedance model is retrieved; the current load harmonic data is input into the corresponding equivalent impedance model, and the equivalent impedance model outputs the target harmonic. Corresponding optimal impedance estimation Then calculate the corresponding harmonic compensation current. Specifically: retrieve the first Target range for suppressing subharmonic voltage Based on Ohm's law and employing optimal impedance estimation Calculate harmonic compensation current ,in For the current measurement of the th Subharmonic voltage For target harmonics; Harmonic compensation current By offsetting harmonic voltage / current in the power grid and controlling the total harmonic distortion (THD) within the national standard range (e.g., ≤1.5% in industrial scenarios), closed-loop control of harmonic mitigation is achieved, enabling the system to suppress harmonic voltage deviations from the target suppression range. Timely response and accurate impedance estimation ensure the accuracy of compensation current calculations, effectively suppressing harmonic voltage fluctuations and guaranteeing the stability of power grid quality. The specific steps for establishing the equivalent impedance model in step S2 are as follows: To ensure the synchronization and relevance of the sample data, S2. selected several refined data subsets. middle Harmonic voltage phasors acquired synchronously by the group With harmonic current phasor As sample data ( (sample number); S2. Based on linear circuit theory, the first... The equivalent impedance of the power grid to subharmonics ( For harmonic resistors, For harmonic reactance, (where the phase shift is constant, i.e., the first...) Under the first harmonic, the power grid affects the first harmonic. The blocking capability of subharmonics does not change abruptly with time or operating conditions; and the measurement and system disturbance errors... Using zero-mean white noise (with no systematic error bias and independent errors between different samples), an equivalent impedance model is established to describe the first... The relationship between the subharmonic voltage, current, and equivalent impedance is expressed by the following formula: ; in: , For the first The first sample Second harmonic voltage amplitude For the corresponding phase; , For the first The first sample Second harmonic current amplitude For the corresponding phase; For the first Error term for each sample.

[0021] S2. To achieve the first The equivalent impedance of the power grid corresponding to the subharmonic. The optimal estimate is obtained by minimizing the sum of squared errors across all sample data, and the objective function is defined. The sum of squares of the magnitudes of the errors (the magnitudes of the complex errors) for each sample data: ; For the objective function Regarding the equivalent impedance of the power grid conjugate Find the partial derivatives (due to complex number operations, the conjugate derivative is needed to ensure the validity of the extremum), and set the partial derivatives to zero to calculate the value that makes the objective function... Minimum optimal impedance estimate : ; in This represents the complex conjugate and simultaneously performs joint estimation of the harmonic impedance amplitude and phase, resulting in the optimal impedance estimate. Equivalent impedance of the power grid The unbiased optimal estimate; S2.4 To adapt to large-scale batch processing scenarios, the harmonic currents and voltages of all samples are organized into a matrix form, where the current sample matrix is... Voltage sample matrix Then the matrix for the optimal impedance estimation is: ; in: Current sample matrix The conjugate transpose, through the current sample matrix Performing the conjugate transpose yields: ; Represents the complex conjugate, with a matrix dimension of N rows × 1 column, where each row is the complex conjugate of the original sample current; matrix multiplication The inverse matrix; S2.5 Repeat the above steps (S2.1 to S2.4) for all characteristic harmonics and non-characteristic harmonics to finally establish the equivalent impedance model with a linear voltage-current relationship corresponding to all harmonic orders. That is, each refined data subset in step S1 The corresponding equivalent impedance model.

[0022] In the current industrial power grid scenario, the core cause of external harmonic source intrusion lies in the superposition of the grid interconnection attribute and the nonlinear nature of the equipment. The industrial power grid forms an electrical connection with multiple entities such as surrounding factories and new energy power plants through public distribution networks and tie lines. The power consumption / generation equipment of these external entities (such as electric arc furnaces, frequency converters, and photovoltaic inverters) generally have nonlinear characteristics. During operation, the non-sinusoidal energy conversion will inevitably generate harmonic currents. These harmonic currents can intrude into the local power grid through power grid conduction paths such as transmission lines and transformer windings, forming a continuous external harmonic source intrusion. When external harmonic sources intrude (such as load fluctuations caused by production adjustments in surrounding factories, or random changes in output of new energy power plants due to natural conditions) and internal equipment switching (such as inverter start-up and shutdown, and electric arc furnace operating condition adjustments) occur simultaneously, the harmonic impedance of the industrial power grid is not a constant value. It is jointly determined by the parameters of equipment such as transformers, transmission lines, and capacitor banks, and will continuously change dynamically due to factors such as grid topology adjustments (such as standby line switching, transformer paralleling / disconnection), and equipment aging (such as capacitor capacitive reactance decay, and transformer winding resistance drift with temperature). The formation of harmonic voltage follows... ( For harmonic voltage, For harmonic impedance, The core coupling relationship (for harmonic current) involves the triple effect of external fluctuating harmonic current, changes in internal harmonic sources, and dynamic harmonic impedance. This causes the harmonic voltage after output harmonic compensation current to fluctuate continuously and irregularly with the intrusion of external harmonic sources, thus affecting the output harmonic compensation current. The resulting harmonic voltage will fluctuate continuously and irregularly as external harmonic sources intrude, causing the output harmonic compensation current to... The subsequent harmonic voltage undergoes continuous changes, which in turn affects the stability of harmonic mitigation. This example further considers that if step S2 is again based on the target harmonic at this point... Calculate the corresponding harmonic compensation current Afterwards, the changing harmonic voltage will be within the suppression range. However, it will still fluctuate. In order to reduce this fluctuation and achieve a more stable harmonic control effect, therefore, in one embodiment, the specific implementation process of the above step S2 is as follows: Receive output harmonic compensation current The subsequent multiple consecutive harmonic voltages, with a set length of For a fixed window, select the window with the specified length in sequence. Consistent harmonic voltages form multiple harmonic voltage sequences. ; And analyze the changing trend of each harmonic voltage sequence, when the latest harmonic voltage is not in the suppression range. Subsequently, the target harmonics are adjusted using multiple randomly varying harmonic voltage sequences. , avoid the harmonic compensation current caused by output, and then cause the situation, the specific working principle is as follows: call out a plurality of harmonic voltages in a plurality of disordered changing harmonic voltage sequences to form a harmonic voltage set , wherein is not in the suppression interval the number of harmonic voltage sequences after select the harmonic voltage set mode (i.e. the harmonic voltage with the most occurrences) is set as the target harmonic , to avoid irregular fluctuations caused by harmonic voltage intrusion by external sources, equipment switching and other factors, the specific reasons are as follows: In industrial power grid, due to the continuous interference of the above external intrusion and internal switching factors, it will cause the output harmonic compensation current a plurality of continuous harmonic voltages after small amplitude fluctuations will continue to occur; In the process of small amplitude fluctuations will lead to the failure to achieve stable harmonic control effect, and then by setting the mode of the harmonic voltage set as the target harmonic , the harmonic voltage can be anchored in the most stable state on the statistical level, so that the harmonic compensation current is focused on this representative control target, thereby avoiding the repeated misoperation of the compensation strategy caused by the disordered fluctuation of the harmonic voltage, and finally realizing the stability and long-term effectiveness of the harmonic control, and ensuring the safe and efficient operation of the power grid power quality and electrical equipment.

[0023] Step S3 analyzes whether the harmonic voltage sequence is ordered or not, and the working principle is as follows: establish a linear fitting model , wherein is the slope, reflecting the change trend strength of the harmonic voltage sequence ; is the intercept, representing the baseline level of the harmonic voltage sequence ; calculate the goodness of fit , wherein is the mean of the harmonic voltage sequence .

[0024] set the goodness of fit threshold , if the goodness of fit ≤ goodness of fit threshold and , then the harmonic voltage sequence is disordered, otherwise it is ordered.

[0025] The above shows and describes the basic principles, main features and advantages of the present application. It should be understood by those skilled in the art that the present application is not limited to the above-mentioned embodiments, and the above-mentioned embodiments and descriptions in the specification are only preferred examples of the present application and are not intended to limit the present application. Various changes and improvements can be made to the present application without departing from the spirit and scope of the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A three-phase AC constant voltage regulator control method for industrial big data power optimization, characterized in that, Includes the following steps: S1. Receives a multi-dimensional historical load harmonic dataset from the industrial big data platform. Historical load harmonic dataset is classified into two dimensions. To form a refined subset of data ; And analyze each refined subset of data Corresponding suppression target interval Set the corresponding target harmonics ; S2, receiving step S1 is the first Refined data subset of subharmonic voltage Establish the first by least squares method Equivalent impedance model corresponding to subharmonic voltage; After establishing the equivalent impedance model, if the current load harmonic data is received, the corresponding refined data subset can be matched. And retrieve the corresponding suppression target region from step S1. If the harmonic voltage in the current load harmonic data is not within the suppression target range Within the range, the corresponding equivalent impedance model is retrieved; the current load harmonic data is input into the corresponding equivalent impedance model, and the equivalent impedance model outputs the target harmonic. Corresponding optimal impedance estimation Then calculate the corresponding harmonic compensation current. ; Step S3: Receive the output harmonic compensation current The subsequent multiple consecutive harmonic voltages, with a set length of For a fixed window, select the window with the specified length in sequence. Consistent harmonic voltages form multiple harmonic voltage sequences. ; And analyze the changing trend of each harmonic voltage sequence, when the latest harmonic voltage is not in the suppression range. Subsequently, the target harmonics are adjusted using multiple randomly varying harmonic voltage sequences. .

2. The three-phase AC constant voltage regulator control method for industrial big data power optimization according to claim 1, characterized in that: The historical load harmonic dataset middle, Indicates the load condition category. Indicates the harmonic order. This indicates the harmonic voltage under the corresponding operating condition and harmonic order.

3. The three-phase AC constant voltage regulator control method for industrial big data power optimization according to claim 1, characterized in that: In step S1, the historical load harmonic dataset is divided into a refined data subset. For each load condition category and each harmonic number Extracting historical load harmonic datasets Simultaneously satisfy and All data (with the same harmonic order) are used to form a refined data subset. .

4. The three-phase AC constant voltage regulator control method for industrial big data power optimization according to claim 3, characterized in that: In step S1, after retrieving each refined data subset to determine harmonic voltage anomalies, the input harmonic compensation current... and input harmonic compensation current The harmonic voltage after Then through harmonic voltage Analyze the adjustment patterns and ranges corresponding to the refined data subsets, and set the suppression target interval for each refined data subset. Specifically, the harmonic compensation current input each time is retrieved. The first harmonic voltage after Select the maximum and minimum values ​​and set them as the target suppression interval. .

5. The three-phase AC constant voltage regulator control method for industrial big data power optimization according to claim 4, characterized in that: S1 calculates the suppression target region. The mean value is set as the target harmonic. : 。 6. The three-phase AC constant voltage regulator control method for industrial big data power optimization according to claim 3, characterized in that: The specific steps for establishing the equivalent impedance model in step S2 are as follows: S2. Filter out multiple refined data subsets middle Harmonic voltage phasors acquired synchronously by the group With harmonic current phasor As sample data; S2. Based on linear circuit theory, the first... The equivalent impedance of the power grid to subharmonics It is a constant, that is, the first Under the first harmonic, the power grid affects the first harmonic. The blocking capability of subharmonics does not change abruptly with time or operating conditions; specifically... For harmonic resistors, For harmonic reactance, For phase shift; and measurement and system disturbance errors For zero-mean white noise, an equivalent impedance model is established to describe the first... The relationship between subharmonic voltage, current and equivalent impedance; S2. Minimize the sum of squared errors for all sample data, and define the objective function. The sum of squares of the error moduli for each sample data: ； For the objective function Regarding the equivalent impedance of the power grid conjugate Find the partial derivatives (due to complex number operations, the conjugate derivative is needed to ensure the validity of the extremum), and set the partial derivatives to zero to calculate the value that makes the objective function... Minimum optimal impedance estimate : ； in This represents the complex conjugate and simultaneously performs joint estimation of the harmonic impedance amplitude and phase, resulting in the optimal impedance estimate. Equivalent impedance of the power grid The unbiased optimal estimate; S2.

4. Organize the harmonic currents and voltages of all samples into a matrix form, where the current sample matrix is... Voltage sample matrix Then the matrix for the optimal impedance estimation is: ; in: Current sample matrix The conjugate transpose, through the current sample matrix Performing the conjugate transpose yields: ； Represents the complex conjugate, with a matrix dimension of N rows × 1 column, where each row is the complex conjugate of the original sample current; matrix multiplication The inverse matrix; S2.5 Repeat the above steps for all characteristic harmonics and non-characteristic harmonics to finally establish an equivalent impedance model with a linear voltage-current relationship corresponding to all harmonic orders. That is, each refined data subset in step S1 The corresponding equivalent impedance model.

7. The three-phase AC constant voltage regulator control method for industrial big data power optimization according to claim 6, characterized in that: The equivalent impedance model in step S2 is: ； in: , For the first The first sample Second harmonic voltage amplitude For the corresponding phase; , For the first The first sample Second harmonic current amplitude For the corresponding phase; For the first Error term for each sample.

8. The three-phase AC constant voltage regulator control method for industrial big data power optimization according to claim 1, characterized in that: The step S2 calls up the first Target range for suppressing subharmonic voltage Based on Ohm's law and employing optimal impedance estimation Calculate harmonic compensation current ,in For the current measurement of the first Subharmonic voltage The target harmonic.

9. A three-phase AC constant voltage regulator control method for industrial big data power optimization according to claim 8, characterized in that: In step S3, the analysis of the first Harmonic voltage sequence Is it ordered? Establish a linear fitting model ,in The slope reflects the harmonic voltage sequence. The intensity of the changing trend; The intercept represents the harmonic voltage sequence. The baseline level; Calculate goodness of fit ,in For the first Harmonic voltage sequence The mean; Set a goodness-of-fit threshold If the goodness of fit ≤ goodness-of-fit threshold and Then determine the harmonic voltage sequence If it is disordered, it is judged as ordered.

10. A three-phase AC constant voltage regulator control method for industrial big data power optimization according to claim 9, characterized in that: Step S3 retrieves multiple harmonic voltages from multiple disordered harmonic voltage sequences to form a harmonic voltage set. ,in The harmonic voltage is not in the suppression range The number of subsequent harmonic voltage sequences; and the selection of harmonic voltage sets. The median is set as the target harmonic. .

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