A grid-connected control method and controller for reducing harmonic noise

Abstract

The application provides a grid-connected control method and a controller for reducing harmonic noise, and relates to the technical field of grid-connected control.The method comprises the following steps: collecting amplitude information and phase information of each harmonic component, which is recorded as first information; then calculating compensation data according to the first information; then establishing a mathematical model of an inverter to obtain grid-connected parameter information of the inverter; then generating a control instruction based on the compensation data; then adjusting the grid-connected parameter information according to the control instruction, generating an output current, and injecting the output current into a power grid; and calculating corresponding compensation data for each harmonic component, thereby improving the suppression effect on different orders of harmonics.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of grid-connected control, in particular to a grid-connected control method and a controller for reducing harmonic noise. BACKGROUND

[0002] In a power system, a grid-connected inverter serves as an interface device between a distributed power source and a power grid, and its performance directly affects the stability of the power grid and the power quality. However, during the grid connection process, the harmonic noise generated by the inverter is a problem that cannot be ignored. The harmonic noise mainly comes from the nonlinear characteristics of the switching devices of the inverter, and these harmonic components will be injected into the power grid, causing the waveform distortion of the voltage and current of the power grid, and further negatively affecting the stability of the power grid and the power quality. Traditional harmonic suppression methods mostly adopt a passive filtering method, that is, a filter is installed at the output end of the inverter to filter out the harmonic components. However, this method has the disadvantages of large filter size, high cost, and difficult maintenance, and the filtering effect is limited, which is difficult to meet the growing requirements of power quality.

[0003] In order to overcome the shortcomings of the traditional harmonic suppression method, in recent years, active harmonic suppression technology has gradually attracted attention. The active harmonic suppression technology monitors the harmonic components in the power grid in real time, calculates the corresponding compensation data, and then controls the inverter to output a compensation current opposite to the harmonic components, so as to effectively suppress the harmonic noise. However, the existing active harmonic suppression technology still has some problems, and some technologies can only suppress harmonics of specific frequencies, and have poor effect on harmonics of other frequencies. SUMMARY

[0004] In order to provide a certain suppression effect on harmonics of different frequencies, the application provides a grid-connected control method and a controller for reducing harmonic noise.

[0005] In a first aspect, the application provides a grid-connected control method for reducing harmonic noise, which adopts the following technical solution:

[0006] A grid-connected control method for reducing harmonic noise, comprising the following steps:

[0007] First acquisition: acquiring the harmonic components of the current in the power grid, obtaining the amplitude information and phase information of each harmonic component, denoted as first information;

[0008] First calculation: calculating compensation data according to the first information, and the calculation model of the compensation data is as follows:

[0009] ;

[0010] Wherein, is the compensation data; is amplitude information of the nth harmonic component; n is a harmonic number of the harmonic component; is a fundamental angular frequency of the grid-connected current; t is time; is phase information of the nth harmonic component;

[0011] First modeling: a mathematical model of the inverter in a three-phase stationary coordinate system is established to obtain grid-connected parameter information of the inverter;

[0012] Generating instructions: control instructions are generated based on the compensation data;

[0013] Generating signals: the inverter adjusts the grid-connected parameter information according to the control instructions, generates an output current, and injects the output current into the power grid.

[0014] By adopting the technical solutions, the harmonic components of the current in the power grid are collected, and the amplitude information and the phase information of each harmonic component are obtained, so that the harmonic conditions in the power grid can be comprehensively understood. According to the collected harmonic information, compensation data are calculated by a calculation model. The calculation model of the application considers the amplitude, the harmonic number, the fundamental angular frequency, the time, and the phase information of the harmonic component, so that accurate compensation data can be generated. These compensation data will be used to guide the output of the inverter to offset different harmonic numbers in the power grid. The controller generates control instructions based on the calculated compensation data. These control instructions will directly guide the operation of the inverter, so that the inverter can output a current with the same phase and opposite amplitude as the harmonic amplitude in the power grid, thereby realizing harmonic compensation. The inverter adjusts its grid-connected parameter information according to the control instructions, generates an output current, and injects the current into the power grid. Through accurate control of the inverter, effective compensation of the harmonic in the power grid is realized.

[0015] Optionally, after the step of performing the first modeling is performed, before the step of generating the instructions is performed, the method further comprises:

[0016] Coordinate transformation: the mathematical model in the three-phase stationary coordinate system is converted into a mathematical model in a two-phase rotating coordinate system by using Clarke transformation algorithm and Park transformation algorithm;

[0017] Second calculation: the current rate of change of the power grid under the action of zero voltage is calculated, denoted as a first current rate of change; the current rate of change of the power grid under the action of non-zero voltage is calculated, denoted as a second current rate of change;

[0018] First prediction: the prediction data of the power grid current is calculated based on the first current rate of change and the second current rate of change, denoted as first data;

[0019] Third calculation: the difference between the first data and the real current data is calculated, denoted as second data;

[0020] Difference judgment: judge whether the difference between the second data and the compensation data is less than a preset difference threshold, if yes, execute the step of generating an instruction; if no, execute the step of second calculation.

[0021] By adopting the above technical solutions, the Clarke transformation algorithm and the Park transformation algorithm are adopted to convert the mathematical model in the three-phase stationary coordinate system into the mathematical model in the two-phase rotating coordinate system, which is helpful to simplify the mathematical model of the inverter, so that the subsequent calculation is more efficient and accurate. Calculating the current change rate of the power grid under the action of zero voltage and non-zero voltage is helpful to understand the response characteristics of the power grid under different voltage conditions. The current change rate is an important indicator of the dynamic performance of the power grid, which can reflect the stability and response speed of the power grid. The first current change rate and the second current change rate are used to calculate the prediction data of the power grid current. This step uses the known current change rate to predict the future current value, and then calculates the difference between the predicted current value and the real current value, and compares the difference with the compensation data to determine whether the difference meets the expectation. If yes, it means that the harmonic components in the power grid can be well suppressed, and then the step of generating an instruction is executed; otherwise, it means that there is a calculation error or the harmonic components in the power grid are not well suppressed (the compensation data is problematic or new harmonic components appear), and the step of second calculation needs to be re-executed to verify whether the phenomenon is caused by calculation error.

[0022] Optionally, after the step of difference judgment and before the step of generating an instruction, it further includes:

[0023] Fourth calculation: calculating the prediction data of the power grid voltage based on the first data;

[0024] Inverse Park transformation: performing inverse Park transformation on the prediction data of the power grid voltage to obtain voltage data in the two-phase stationary coordinate system, denoted as the third data;

[0025] Calculating voltage phase: calculating the voltage phase based on the third data;

[0026] Output control: adding the voltage phase to the original compensation data as new compensation data.

[0027] By adopting the above technical solutions, the prediction data of the power grid voltage is calculated based on the first data (prediction data of the power grid current), which can more effectively manage the stability and performance of the power grid. The prediction data of the power grid voltage is converted into a more easily processed and applied format through inverse Park transformation, improving the applicability and practicality of the data. The voltage phase is calculated and the compensation data is updated, and the new process optimizes the voltage control process, improving the stability and performance of the power grid.

[0028] Optionally, after the step of performing the inverse Park transformation, before the step of calculating the voltage phase, further comprising:

[0029] Second acquisition: acquiring active power in the power grid, denoted as first power; acquiring reactive power in the power grid, denoted as second power;

[0030] Fifth calculation: calculating active power based on the first data and the third data, denoted as third power; calculating reactive power based on the first data and the third data, denoted as fourth power;

[0031] Sixth calculation: calculating the difference between the first power and the third power, denoted as fourth data; calculating the difference between the second power and the fourth power, denoted as fifth data;

[0032] Power judgment: judging whether the fourth data and the fifth data meet the expectation, if yes, performing the step of calculating the voltage phase; if no, performing the step of the second calculation.

[0033] By adopting the above technical solution, in the step of the second acquisition, the active power and the reactive power are acquired in real time, then in the step of the fifth calculation, the active power and the reactive power under the predicted data are calculated based on the predicted current data and the voltage data (converted coordinates), then in the step of the sixth calculation, the difference between the active power real-time data and the predicted data is calculated respectively, then in the step of the power judgment, whether the difference meets the expectation is judged, if yes, it means that the difference is within an acceptable range, then the step of calculating the voltage phase is performed, otherwise, the step of the second calculation is performed, whether there is a calculation error in the verification process.

[0034] Optionally, after the step of calculating the voltage phase, before the step of outputting the control, further comprising:

[0035] First filtering: inputting the fourth data into a low-pass filter to obtain new fourth data;

[0036] Seventh calculation: multiplying the new fourth data with a preset adjustment coefficient to obtain an active frequency adjustment amount, converting the active frequency adjustment amount into a voltage phase adjustment amount, denoted as sixth data;

[0037] First summation: summing the voltage phase and the sixth data to obtain a new voltage phase.

[0038] By adopting the technical scheme, the fourth data is input into the low-pass filter, and the fourth data is smoothed and high-frequency components are filtered out, then the fourth data after the smoothing is multiplied by a preset adjustment coefficient to obtain an active power adjustment amount, and the adjustment amount is converted to obtain a voltage phase adjustment amount, then the voltage phase obtained in the step of calculating the voltage phase is summed with the voltage phase adjustment amount to obtain a more accurate new voltage phase, the whole step is based on real-time data and dynamic changes of the power system, which helps to maintain the stability and power factor of the power system.

[0039] Optionally, after the step of performing the seventh calculation, before the step of performing the first summation, further comprising:

[0040] Second filtering: inputting the fifth data into a low-pass filter to obtain new fifth data;

[0041] Eighth calculation: multiplying the new fifth data by a preset adjustment coefficient to obtain a reactive power adjustment amount, and converting the reactive frequency adjustment amount into a voltage phase adjustment amount, denoted as seventh data;

[0042] Second summation: summing the sixth data and the seventh data to obtain new sixth data.

[0043] By adopting the technical scheme, the fifth data is input into the low-pass filter, and the fifth data is smoothed, then the fifth data after the smoothing is multiplied by a preset adjustment coefficient to obtain a reactive power adjustment amount, and the adjustment amount is converted to obtain a voltage phase adjustment amount, then the sixth data and the seventh data are summed to obtain a voltage phase more accurate than the sixth data.

[0044] Optionally, after the step of generating the signal, further comprising:

[0045] Third acquisition: acquiring current data in the power grid after the output current is injected, denoted as eighth data;

[0046] Second modeling: establishing a neural network model;

[0047] Second prediction: inputting the eighth data and the compensation data into the neural network model to output a current adjustment amount;

[0048] Adjustment: adjusting the compensation data based on the current adjustment amount, and taking the adjusted compensation data as new compensation data;

[0049] Judgment of adjustment amount: judging whether the current adjustment amount is less than a preset threshold, if yes, outputting a weight coefficient of the neural network model; if no, performing the step of second prediction;

[0050] Parameter replacement: the weight coefficients of the neural network model are used as parameters of the controller.

[0051] By adopting the technical scheme, the neural network model is established, the relationship between the grid current and the inverter output current is learned and simulated by using the neural network model, and the current regulation amount is outputted, so that the accurate control of the grid current is realized. The compensation data is adjusted based on the current regulation amount. By adjusting the compensation data, the output current of the inverter can be further corrected to be closer to the target value. In the whole process, the neural network model essentially replaces the controller, realizes the adjustment of the inverter output current data, and then the weight coefficients of the neural network model and the parameters of the controller are optimized. The weight coefficients of the neural network model are used as the parameters of the controller, the learning ability of the neural network is utilized, the parameters of the controller are adjusted in real time, and more accurate and flexible control of the grid current or voltage is realized.

[0052] Optionally, after the step of performing the second prediction, before the step of adjusting, further comprising:

[0053] Online learning: the neural network model uses an online learning algorithm to adjust the internal weight coefficients by reducing the current regulation amount.

[0054] By adopting the technical scheme, the grid state and the inverter load may change at any time during actual operation. The neural network model uses an online learning algorithm to continuously adjust the internal weight coefficients, aiming to reduce the current regulation amount until it is lower than the preset regulation amount threshold. This process is essentially a real-time optimization of the neural network model, making its prediction output more accurate, thereby generating a more accurate current regulation amount. The performance of the inverter is improved by this scheme, which can maintain excellent current control ability under various working conditions, providing a strong guarantee for the stable operation of the power system.

[0055] Optionally, after the step of performing the third collection, before the step of performing the second modeling, further comprising:

[0056] Harmonic judgment: judging whether the even harmonics are included in the eighth data, if yes, performing the checking step; if no, performing the second modeling step.

[0057] Checking: checking the wiring.

[0058] By adopting the technical scheme, the application can identify whether there is an even harmonic component in the power grid in advance before the neural network model is established through the harmonic judgment step. Since the even harmonic exists only when the wiring error / contact failure occurs, the existence of the even harmonic in the eighth data means that there is a wiring error, and the checking step needs to be performed. Through the harmonic judgment step, the existence of the even harmonic can be detected sensitively before modeling, thereby effectively reducing the complexity and errors that may be introduced in the modeling process due to harmonic interference, which improves the accuracy of the model and provides early warning information for subsequent harmonic control.

[0059] In a second aspect, the application provides a controller, comprising a processor and a memory, the memory storing machine executable instructions executable by the processor, and the processor executes the machine executable instructions to implement the method.

[0060] In summary, the application has at least one of the following beneficial technical effects:

[0061] 1. The application can comprehensively understand the harmonic condition in the power grid by collecting the harmonic components of the current in the power grid and obtaining the amplitude information and phase information of each harmonic component. According to the collected harmonic information, the application calculates compensation data through a calculation model. The calculation model of the application considers the amplitude of the harmonic component, the harmonic order, the fundamental angular frequency, the time, and the phase information, so that accurate compensation data can be generated. These compensation data will be used to guide the output of the inverter to offset the different orders of harmonics in the power grid. The controller generates control instructions based on the calculated compensation data, which directly guide the operation of the inverter, so that the inverter can output current with the same phase and opposite amplitude of the harmonic in the power grid, thereby realizing harmonic compensation. The inverter adjusts its grid-connected parameter information according to the control instructions to generate output current and injects the current into the power grid. Through the accurate control of the inverter, the effective compensation of the harmonics in the power grid is realized.

[0062] 2. The application calculates the predicted data of the power grid voltage based on the first data (predicted data of the power grid current), which can more effectively manage the stability and performance of the power grid. The application can convert the predicted power grid voltage data into a format that is easier to process and apply through inverse Park transformation, thereby improving the applicability and practicality of the data. The application optimizes the voltage control process by calculating the voltage phase and updating the compensation data, thereby improving the stability and performance of the power grid.

[0063] 3. In the second acquisition step, active power and reactive power are acquired in real time. Then, in the fifth calculation step, active power and reactive power under the predicted data are calculated based on the predicted current data and voltage data (after coordinate transformation). Then, in the sixth calculation step, the difference between the real-time active power data and the predicted data is calculated respectively. Then, in the power judgment step, it is determined whether these differences meet the expectations. If they do, it means that the difference is within an acceptable range. Then, the step of calculating the voltage phase is executed. Otherwise, the second calculation step is executed to verify whether there are any calculation errors in the process. Attached Figure Description

[0064] Figure 1 This is a flowchart of the process from S1 (first acquisition) to S5 (signal generation) in Embodiment 1 of this application;

[0065] Figure 2 This is the circuit topology diagram of the inverter in this application;

[0066] Figure 3 This is a flowchart of the S3 first modeling to S4 generation instructions in Embodiment 2 of this application;

[0067] Figure 4 This is a flowchart of the process from S68 calculating the voltage phase to S69 output control in Embodiment 2 of this application;

[0068] Figure 5 This is a flowchart of Embodiment 3 of this application. Detailed Implementation

[0069] The following combination Figures 1 to 5 This application will be described in further detail.

[0070] Example 1: This example discloses a grid-connected control method for reducing harmonic noise, referring to... Figure 1 The method includes: S1 first acquisition, S2 first calculation, S3 first modeling, S4 generating instructions, and S5 generating signals. First, the amplitude and phase information of each harmonic component are acquired and recorded as the first information. Then, compensation data is calculated based on the first information. Next, a mathematical model of the inverter is established to obtain the grid-connected parameter information of the inverter. Then, control instructions are generated based on the compensation data. Finally, the inverter adjusts the grid-connected parameter information according to the control instructions, generates an output current, and injects the output current into the grid. This embodiment includes the following steps:

[0071] S1 First Acquisition: Acquire the harmonic components of the current in the power grid, and obtain the amplitude and phase information of each harmonic component, denoted as the first information. The harmonics are all other frequency components in the power grid except the fundamental frequency, including odd harmonics and even harmonics.

[0072] S2 first calculation, according to the first information, the compensation data is calculated to offset the harmonic component in the power grid, the calculation model of the compensation data is as follows:

[0073] ;

[0074] Wherein, is the compensation data (i.e. the compensation current at time t); is the amplitude information of the nth harmonic component; n is the harmonic number of the harmonic component (from 2, because n = 1 corresponds to the fundamental wave, the fundamental wave is not regarded as a harmonic, when n is odd, corresponds to the odd harmonic, when n is even, corresponds to the even harmonic); is the fundamental angular frequency of the grid-connected current; t is time; is the phase information of the nth harmonic component.

[0075] S3 first modeling, the mathematical model of the inverter in the three-phase stationary coordinate system (a, b, c) is established, and the grid-connected parameter information of the inverter is obtained.

[0076] The mathematical model of the inverter in the three-phase stationary coordinate system is derived based on Kirchhoff's law, in which the inverter is regarded as a three-phase alternating current time-varying system, and the switch function mode reflects the working state of the inverter.

[0077] Referring to Figure 2 , the direction of the grid current into the inverter is positive, and the mathematical model of the inverter is as follows:

[0078] ;

[0079] Wherein, L is the equivalent inductance; R is the equivalent resistance; C is the equivalent capacitance; is the current of the three-phase grid in phase a; is the voltage of the three-phase grid in phase a; is the output voltage of the three-phase grid-side inverter in phase a; is the current of the three-phase grid in phase b; is the voltage of the three-phase grid in phase b; is the output voltage of the three-phase grid-side inverter in phase b; is the current of the three-phase grid in phase c; is the voltage of the three-phase grid in phase c; is the output voltage of the three-phase grid-side inverter in phase c; is the DC bus capacitor voltage; is the DC side output current.

[0080] a phase bridge arm switch function; b phase bridge arm switch function; c phase bridge arm switch function; the calculation model of the three is:

[0081] .

[0082] The inverter is a power electronic device that can convert DC power into AC power and can adjust the frequency, amplitude and phase of the output current by controlling its switching state. Through the establishment of a mathematical model, the grid-connected parameter information of the inverter can be obtained, such as output voltage, current, power, etc., wherein the power is further calculated by voltage and current.

[0083] S4 generates instructions to generate control instructions based on compensation data, which will be used to adjust the switching state of the inverter, so that its output can offset the compensation current of the harmonic component in the grid.

[0084] The control instructions described in this embodiment are PWM signals generated using pulse width modulation technology. The PWM signal precisely controls the current waveform and amplitude of the inverter output by adjusting the switching frequency and duty cycle of the inverter.

[0085] S5 generates signals, and the inverter adjusts the grid-connected parameter information according to the control instructions, that is, the inverter quickly switches its switching state according to the received PWM signal. When the PWM signal is high, the inverter outputs current; when the PWM signal is low, the inverter stops outputting current. By adjusting the duty cycle of the PWM signal, the average value of the inverter output current can be controlled, so as to accurately match the required compensation current. The output current will contain compensation data for offsetting the harmonic component in the grid, and then the output current will be injected into the grid.

[0086] This embodiment first collects the harmonic component of the current from the grid and obtains its amplitude and phase information, then calculates the compensation data for offsetting the harmonic based on this information, then establishes a mathematical model of the inverter in the three-phase stationary coordinate system to obtain the grid-connected parameter, then generates control instructions according to the compensation data, and then the inverter adjusts the grid-connected parameter according to these instructions and generates output current to accurately offset the harmonic component in the grid, thereby improving power quality.

[0087] Embodiment 2, refer to Figure 3 The difference between this embodiment and embodiment 1 is that after performing S3 first modeling, before performing S4 generating instructions, it further includes:

[0088] S6 voltage control, including S61 coordinate transformation, S62 second calculation, S63 first prediction, S64 third calculation, S65 difference judgment, S66 fourth calculation, S67 inverse Park transformation, S7 power check, S68 calculation of voltage phase and S69 output control.

[0089] S61 coordinate transformation, using Clarke transformation algorithm to convert the mathematical model under three-phase static coordinate system into the mathematical model under two-phase static coordinate system, and then using Park transformation algorithm to convert the mathematical model under two-phase static coordinate system into the mathematical model under two-phase rotating coordinate system, the mathematical model under two-phase rotating coordinate system is as follows:

[0090] ;

[0091] Wherein, L is equivalent inductance; R is equivalent resistance; C is equivalent capacitance; is the grid angular frequency; is the grid voltage d-axis component; is the grid voltage q-axis component; is the grid-side current d-axis component; is the grid-side current q-axis component; is the DC-side output current.

[0092] is the switching function of the bridge arm on the k-axis, and the calculation model is:

[0093] .

[0094] S62 second calculation, calculate the current rate of change of the grid under the action of zero voltage, recorded as the first current rate of change, and the first current rate of change calculation model is as follows:

[0095] ;

[0096] ;

[0097] Wherein, represents the current rate of change under the action of zero voltage on the d-axis; represents the current rate of change under the action of zero voltage on the q-axis

[0098] Calculate the current rate of change of the grid under the action of non-zero voltage, recorded as the second current rate of change, and the calculation model of the second current rate of change is as follows:

[0099] ;

[0100] ;

[0101] ;

[0102] ;

[0103] wherein, represents the rate of change of current under the action of a non-zero voltage ; represents the rate of change of current under the action of a non-zero voltage ; represents the rate of change of current under the action of a non-zero voltage ; represents the rate of change of current under the action of a non-zero voltage .

[0104] S63 First prediction, calculate the prediction data of the grid current based on the first rate of change of current and the second rate of change of current, denoted as the first data, the calculation model of the first data is as follows:

[0105] ;

[0106] ;

[0107] wherein, is the length of time under the action of zero voltage; , is the length of time under the action of corresponding non-zero voltage ( ), ( ). is the d-axis reference current data; is the q-axis reference current data. is the current data at the mth iteration under the action of non-zero voltage ; is the current data at the m+1th iteration under the action of non-zero voltage ; is the current data at the mth iteration under the action of non-zero voltage ; is the current data at the m+1th iteration under the action of non-zero voltage .

[0108] After that, inverse Park transformation is performed on and , the process is as follows:

[0109] ;

[0110] wherein, is the rotor position angle.

[0111] After that, conversion is made from the two-phase stationary coordinate system to the three-phase stationary coordinate system, the process is as follows:

[0112] .

[0113] S64 Third calculation, calculate the difference between the first data and the true current data, denoted as second data.

[0114] S65 Difference judgment, judge whether the difference between the second data and the compensation data is less than the preset difference threshold, if yes, it means that the predicted data is close enough to the true data, then execute S66 fourth calculation; if not, it means that there is an error in the calculation process, or the harmonic component in the power grid is not well suppressed (the compensation data is problematic or a new harmonic component appears), it is necessary to re-execute S62 second calculation to verify whether this phenomenon is caused by calculation error.

[0115] After re-executing S62 second calculation, execute this step again to find that the difference between the second data and the compensation data is still greater than the preset difference threshold, which means that a new harmonic appears in the power grid, execute S1 first collection.

[0116] S66 Fourth calculation, calculate the predicted data of the power grid voltage based on the first data, the calculation process is as follows:

[0117] ;

[0118] ;

[0119] ;

[0120] Wherein, T is the control period of the controller; is the zero voltage action time; , is the time length of the corresponding non-zero voltage ( ), ( ) action; is the d-axis component of the power grid voltage; is the q-axis component of the power grid voltage.

[0121] S67 inverse Park transformation, inverse Park transformation is performed on the predicted data of the power grid voltage to obtain the voltage data in the two-phase stationary coordinate system, denoted as third data, the calculation process is as follows:

[0122] ;

[0123] Wherein, is the voltage component on the axis; is the voltage component on the axis; for the rotor position angle.

[0124] This step converts the voltage data in the two-phase rotating coordinate system back to the two-phase stationary coordinate system for comparison and control with the actual output of the inverter.

[0125] S7 power verification, including S71 second acquisition, S72 fifth calculation, S73 sixth calculation and S74 power judgment.

[0126] S71 second acquisition, acquiring active power in the power grid, denoted as first power, active power is the actual work done in the power grid, and is the basis for stable operation of the power grid. The reactive power in the power grid is collected and denoted as the second power. Although the reactive power does not do work in the power grid, it is crucial for maintaining voltage stability and current balance of the power grid.

[0127] S72 fifth calculation, calculating active power based on first data and third data, denoted as third power; calculating reactive power based on first data and third data, denoted as fourth power. This step calculates the predicted value of active power and the predicted value of reactive power based on the predicted value of current data and the predicted value of voltage data.

[0128] S73 sixth calculation, calculating the difference between the first power and the third power, denoted as the fourth data; calculating the difference between the second power and the fourth power, denoted as the fifth data. This step calculates the difference between the real-time collected active power / reactive power and the predicted active power / reactive power.

[0129] S74 power judgment, judging whether the fourth data and the fifth data meet the expectation, if yes, it means that the fourth data and the fifth data are caused by measurement error or calculation error, then S68 calculates the voltage phase is executed; if not, it means that there is a big gap between the real active power / reactive power and the predicted active power / reactive power, which may be caused by calculation error or new harmonic components in the power grid, so S62 second calculation is executed to verify whether this phenomenon is caused by calculation error.

[0130] After re-executing S62 second calculation, this step is executed again to find that the fourth data and the fifth data still do not meet the expectation, which means that new harmonics appear in the power grid, so S1 first acquisition is executed.

[0131] S68 calculates the voltage phase, calculates the voltage phase based on the third data, and the calculation model is as follows:

[0132] ;

[0133] wherein, is the voltage phase.

[0134] S69 output control, increase the voltage phase to the original compensation data as new compensation data. This step increases the voltage phase to the original compensation data, in order to consider the change of voltage phase in the compensation data, so as to more accurately control the output of the inverter, realize accurate harmonic compensation.

[0135] The embodiment increases S6 voltage control and S7 power verification on the basis of the technical solutions provided in embodiment 1. Compared with the current control used alone in embodiment 1, the output of the inverter can be accurately controlled, and effective compensation of grid harmonics can be realized.

[0136] Reference Figure 4 In other embodiments, when one of the fourth data or the fifth data does not meet the expectation or both do not meet the expectation in S74 power judgment, that is, the calculation is wrong and the predicted data of the current and the predicted data of the voltage are recalculated, after performing S62 second calculation until performing S68 calculation of voltage phase, before performing S69 output control, it further includes:

[0137] S681 first filtering, input the fourth data into a low-pass filter, the function of the low-pass filter is to remove the high-frequency component in the signal and retain the low-frequency component, so as to smooth the data and reduce noise interference. After filtering, new fourth data is obtained, which is more stable and can better reflect the actual state of the power grid.

[0138] S682 seventh calculation, multiply the new fourth data by a preset adjustment coefficient to obtain an active frequency adjustment amount, convert the active frequency adjustment amount into a voltage phase adjustment amount, denoted as sixth data, the sixth data represents the voltage phase amount that needs to be adjusted to compensate for the active power deviation.

[0139] The process of converting the active frequency adjustment amount into the voltage phase adjustment amount is as follows:

[0140] 1. According to the active frequency Calculate the cycle time :

[0141] .

[0142] 2. According to the active frequency adjustment amount Obtain the time change amount , calculate the proportion of the time change amount in the cycle time :

[0143] .

[0144] 3. Multiply the proportion by ​Obtaining voltage phase adjustment amount

[0145] .

[0146] The adjustment coefficient is set according to the operating characteristics and control targets of the power grid, and is used to adjust the adjustment intensity of active power, and has a value range of 0-10. The closer to 0, the smaller the adjustment intensity, and vice versa, the greater the adjustment intensity.

[0147] S683 Second filtering, input the fifth data into a low-pass filter to obtain new fifth data.

[0148] S684 Eighth calculation, the new fifth data is multiplied by a preset adjustment coefficient to obtain a reactive power adjustment amount, and the reactive frequency adjustment amount is converted into a voltage phase adjustment amount (the same as the seventh calculation in S682), recorded as the seventh data. The seventh data represents the amount of voltage phase adjustment needed to compensate for the reactive power deviation.

[0149] S685 Second summation, the sixth data and the seventh data are summed to obtain new sixth data. The new sixth data integrates the effects of active and reactive power adjustment on voltage phase and is the final basis for subsequent voltage phase adjustment.

[0150] S686 First summation, summing the voltage phase and the sixth data to obtain a new voltage phase.

[0151] This embodiment focuses on the accurate adjustment of voltage phase. First, the deviation data of active power and reactive power is smoothed by a low-pass filter to reduce noise interference. Then, the preset adjustment coefficient is used to calculate the active frequency adjustment amount and the reactive power adjustment amount, and convert them into the corresponding voltage phase adjustment amount. Then, the two voltage phase adjustment amounts are summed to obtain the comprehensive voltage phase adjustment amount. Finally, the adjustment amount is added to the original voltage phase to obtain the optimized voltage phase, aiming to realize fine regulation of power balance and stability of the power grid, and improve the overall performance and power supply quality of the power grid.

[0152] Embodiment 3: Refer to Figure 5 The difference between this embodiment and embodiment 1 is that after performing S5 to generate a signal, it further includes:

[0153] S81 Third acquisition, acquiring current data in the power grid after injecting output current, recorded as eighth data, the eighth data reflects the state of the power grid after adding compensation current.

[0154] S82 harmonic judgment, the eighth data is subjected to harmonic analysis to determine whether the eighth data contains even harmonics, if yes, it indicates that there is a wiring error or poor contact in the wiring, S83 check needs to be performed; if not, it indicates that the power grid state is relatively good, S84 second modeling is performed.

[0155] S83 check, check whether the wiring is incorrect or has poor contact, and adjust the part where the wiring is incorrect or has poor contact.

[0156] S84 second modeling, if the eighth data does not contain even harmonics, or after checking and correcting the wiring problem, a neural network model is established.

[0157] S85 second prediction, the eighth data and the compensation data are input into the neural network model, the neural network model will analyze and predict according to the input data (the eighth data and the compensation data), and then output a current regulation amount.

[0158] This current regulation amount represents the amount of adjustment that needs to be made to the compensation data in order to make the power grid reach or approach the ideal state.

[0159] S86 online learning, in order to improve the prediction accuracy and adaptability of the neural network model, the weight coefficients of the neural network model are adjusted using an online learning algorithm, specifically: the weight coefficients of the neural network model are adjusted by reducing the current regulation amount until the current regulation amount is less than a preset regulation amount threshold.

[0160] S87 adjustment, the compensation data is adjusted based on the current regulation amount, and the adjusted compensation data is used as new compensation data.

[0161] S88 judgment of regulation amount, determine whether the current regulation amount is less than a preset threshold, if yes, it indicates that the adjustment is effective, and the weight coefficients of the neural network model are output as parameters for subsequent control; if not, it indicates that the adjustment is not sufficient, and S84 second prediction needs to be performed.

[0162] S89 parameter replacement, the weight coefficients of the neural network model are used as parameters of the controller, the controller can accurately adjust and control according to the actual situation of the power grid, by using the weight coefficients of the neural network model as parameters of the controller, the dynamic changes of the power grid can be adapted, and the harmonic compensation effect and stability of the power grid can be further improved.

[0163] In this embodiment, the controller includes three parameters: proportional gain Kp, integral time Ti and differential time Td, so the neural network model uses three neurons to correspond to the three parameters of the controller.

[0164] In other embodiments, if the controller includes multiple parameters, the neural network model employs the same number of neurons as the number of controller parameters to achieve a corresponding number.

[0165] The embodiment first collects power grid current data after injecting compensation current, and determines whether the data contains even harmonics. If yes, the connection is checked, otherwise a neural network model is established. Then the collected current data and compensation data are input into the neural network model for prediction, and the current adjustment amount is output. The model weight coefficient is adjusted through an online learning algorithm to reduce the adjustment amount to below a preset threshold. Based on the obtained current adjustment amount, the compensation data is adjusted, and it is determined whether the adjusted current adjustment amount meets the requirements. If yes, the weight coefficient of the neural network model is applied as the parameter of the quasi-PR controller to achieve accurate compensation and adjustment of power grid harmonics.

[0166] Embodiment 4: The embodiment discloses a controller, characterized in that the controller includes a processor and a memory, the memory stores machine executable instructions executable by the processor, and the processor executes the machine executable instructions to implement the method.

[0167] The above are preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Therefore, any equivalent changes made on the basis of the structure, shape and principle of the present application shall be covered within the protection scope of the present application.

Claims

1. A grid-connected control method for reducing harmonic noise, characterized in that, include: First acquisition: Acquire the harmonic components of the current in the power grid, obtain the amplitude and phase information of each harmonic component, and record it as the first information; First calculation: Based on the first information, calculate the compensation data. The calculation model for the compensation data is as follows: ； in, To compensate for the data; This represents the amplitude information of the nth harmonic component; n is the harmonic order of the harmonic component. ω is the fundamental angular frequency of the grid-connected current; t is time. This represents the phase information of the nth harmonic component; First modeling: Establish a mathematical model of the inverter in a three-phase stationary coordinate system to obtain the grid connection parameter information of the inverter; Generate instructions: Generate control instructions based on compensation data; Signal generation: The inverter adjusts the grid connection parameter information according to the control command, generates output current, and injects the output current into the grid; After performing the first modeling step and before performing the generation instruction step, the process also includes: Coordinate transformation: The Clarke transformation algorithm and the Park transformation algorithm are used to transform the mathematical model in the three-phase stationary coordinate system into a mathematical model in the two-phase rotating coordinate system; The second calculation: calculate the rate of change of current in the power grid under zero voltage, denoted as the first rate of change of current; calculate the rate of change of current in the power grid under non-zero voltage, denoted as the second rate of change of current. First prediction: The predicted data of the grid current calculated based on the first current change rate and the second current change rate is denoted as the first data; Third calculation: Calculate the difference between the first data and the actual current data, and record it as the second data; Difference judgment: Determine whether the difference between the second data and the compensation data is less than the preset difference threshold. If yes, execute the generation instruction step; if no, execute the second calculation step. After the step of performing the difference judgment and before the step of performing the generation instruction, the following steps are also included: Fourth calculation: Calculate the predicted grid voltage based on the first data; Inverse Park Transform: Perform an inverse Park transform on the predicted grid voltage data to obtain voltage data in a two-phase stationary coordinate system, denoted as the third data. Calculate voltage phase: Calculate voltage phase based on third-party data; Output control: The voltage phase is added to the original compensation data as new compensation data; After performing the inverse Park transform step and before performing the voltage phase calculation step, the following steps are also included: Second data collection: Collect the active power in the power grid, denoted as the first power; collect the reactive power in the power grid, denoted as the second power; Fifth calculation: Calculate the active power based on the first and third data, and record it as the third power; calculate the reactive power based on the first and third data, and record it as the fourth power; Sixth calculation: Calculate the difference between the first power and the third power, and record it as the fourth data; calculate the difference between the second power and the fourth power, and record it as the fifth data; Power determination: Determine whether the fourth and fifth data meet the expectations. If yes, proceed to the step of calculating the voltage phase; otherwise, proceed to the second calculation step.

2. The grid-connected control method for reducing harmonic noise according to claim 1, characterized in that, After performing the step of calculating the voltage phase and before performing the step of output control, the following steps are also included: First filtering: Input the fourth data into the low-pass filter to obtain a new fourth data; The seventh calculation: multiply the new fourth data with the preset adjustment coefficient to obtain the active frequency adjustment amount, and convert the active frequency adjustment amount into the voltage phase adjustment amount, which is recorded as the sixth data. First summation: Summing the voltage phase with the sixth data to obtain a new voltage phase.

3. The grid-connected control method for reducing harmonic noise according to claim 2, characterized in that, After performing the seventh calculation step and before performing the first summation step, the following steps are also included: Second filtering: Input the fifth data into the low-pass filter to obtain a new fifth data; Eighth calculation: Multiply the new fifth data with the preset adjustment coefficient to obtain the reactive frequency adjustment amount, and convert the reactive frequency adjustment amount into the voltage phase adjustment amount, which is recorded as the seventh data. Second summation: Summing the sixth data with the seventh data yields a new sixth data.

4. The grid-connected control method for reducing harmonic noise according to any one of claims 1-3, characterized in that, After performing the signal generation step, the following is also included: Third acquisition: Acquire the current data in the power grid after the injected output current is collected, and record it as the eighth data; Second modeling: Establishing a neural network model; Second prediction: Input the eighth data and compensation data into the neural network model to output the current regulation amount; Adjustment: The compensation data is adjusted based on the current adjustment amount, and the adjusted compensation data is used as the new compensation data; Determine the adjustment amount: Determine whether the current adjustment amount is less than a preset threshold. If yes, output the weight coefficients of the neural network model; if no, execute the second prediction step. Parameter substitution: The weight coefficients of the neural network model are used as parameters of the controller.

5. The grid-connected control method for reducing harmonic noise according to claim 4, characterized in that, After the second prediction step and before the adjustment step, the following steps are also included: Online learning: The neural network model uses an online learning algorithm to adjust the internal weight coefficients by reducing the current regulation amount.

6. The grid-connected control method for reducing harmonic noise according to claim 5, characterized in that, The process, which follows the third data acquisition step and precedes the second modeling step, also includes: Harmonic detection: Determine whether the eighth data contains even harmonics. If yes, proceed with the checking step; otherwise, proceed with the second modeling step. Inspection: Check the wiring.

7. A controller, characterized in that, The controller includes a processor and a memory, the memory storing machine-executable instructions that can be executed by the processor, the processor executing the machine-executable instructions to implement the method as claimed in any one of claims 1-6.

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