Method and device for determining control parameters of grid-connected inverter

Abstract

This disclosure provides a method and apparatus for determining control parameters of a grid-connected inverter, which can be applied to the field of new energy grid-connected application technology. The method includes: inputting a preset frequency disturbance into the grid-connected inverter through a first disturbance injection point to collect the angular velocity data sequence output by the phase-locked loop (PLL) of the grid-connected inverter under the preset frequency disturbance; using Newton's method, performing recursive iteration based on the angular velocity data sequence to obtain the PLL parameters; using the d-axis current reference value of the current loop of the grid-connected inverter as the input of a frequency sweep method and the d-axis component of the output current of the grid-connected inverter as the output of the frequency sweep method, determining the frequency response of the current loop based on a preset frequency sweep interval; and processing the frequency response of the current loop based on the transfer function of the current loop to obtain the current loop parameters.

Description

Technical Field

[0001] The present disclosure relates to the fields of computer technology, Internet technology, warehousing and logistics, and electronic technology, and in particular to a method and device for determining control parameters of a grid-connected inverter. Background Art

[0002] Since the storage capacity of non-renewable energy is limited and the consumption of non-renewable energy will damage the natural environment, the development of renewable energy such as photovoltaic and wind energy is of great significance to environmental protection and economic development. When using the above renewable energy to generate electricity, it is necessary to use a grid-connected inverter to convert DC into AC before using it. Therefore, the safe operation of the grid-connected inverter is crucial to the grid connection of new energy.

[0003] Different from the physical characteristics of generator sets, the characteristics of new energy grid-connected inverters are dominated by control characteristics, which will bring a series of problems to the power system, such as broadband oscillation, voltage fluctuation, high-order harmonics, etc. In order to solve the above problems, large-scale simulation is needed to obtain the specific parameters of the grid-connected inverter and establish an accurate inverter model. However, in practical applications, it is difficult to obtain the specific parameters of the grid-connected inverter and verify the correctness of the parameters of the grid-connected inverter.

[0004] Existing research usually uses optimization algorithms such as particle swarm optimization and genetic algorithm to identify the control parameters of the current loop of the grid-connected inverter. Since the grid-connected inverter system is jointly affected by the current loop and the phase-locked loop, the existing technology ignores the verification of the phase-locked loop parameters, so it is difficult to ensure the verification accuracy of the control parameters. Summary of the invention

[0005] In view of this, the present disclosure provides a method and device for determining control parameters of a grid-connected inverter.

[0006] One aspect of the present disclosure provides a method for determining control parameters of a grid-connected inverter, comprising: inputting a preset frequency disturbance into the grid-connected inverter through a first disturbance injection point to collect an angular velocity data sequence output by a phase-locked loop of the grid-connected inverter under the preset frequency disturbance; using Newton's method to perform recursive iteration based on the angular velocity data sequence to obtain phase-locked loop parameters; using a d-axis current reference value of the current loop of the grid-connected inverter as an input of a frequency sweeping method and a d-axis component of the output current of the grid-connected inverter as an output of the frequency sweeping method, and determining the frequency response of the current loop based on a preset frequency sweeping interval; and processing the frequency response of the current loop based on a transfer function of the current loop to obtain current loop parameters.

[0007] According to an embodiment of the present disclosure, Newton's method is used to perform recursive iteration based on the angular velocity data sequence to obtain phase-locked loop parameters, including: obtaining time domain responses corresponding to each of the multiple angular velocity data based on a transfer function of the phase-locked loop, the acquisition moments of each of the multiple angular velocity data included in the angular velocity data sequence, and the angular velocity frequency domain response of the power grid in which the grid-connected inverter is located; constructing a recursive iterative model based on Newton's method based on the angular velocity data sequence and the time domain responses corresponding to each of the multiple angular velocity data; and iteratively optimizing the initial parameters of the phase-locked loop using the recursive iterative model based on Newton's method to obtain the phase-locked loop parameters.

[0008] According to an embodiment of the present disclosure, based on a transfer function of a phase-locked loop, the acquisition moments of each of the multiple angular velocity data included in the angular velocity data sequence, and the angular velocity frequency domain response of the power grid in which the grid-connected inverter is located, a time domain response corresponding to each of the multiple angular velocity data is obtained, including: obtaining a frequency domain response function of the phase-locked loop based on the angular velocity frequency domain response of the power grid and the transfer function of the phase-locked loop; performing a time domain conversion on the frequency domain response function of the phase-locked loop to obtain a time domain response function of the phase-locked loop; and sampling the time domain response function of the phase-locked loop based on the acquisition moments of each of the multiple angular velocity data to obtain a time domain response corresponding to each of the multiple angular velocity data.

[0009] According to an embodiment of the present disclosure, a recursive iterative model based on Newton's method is constructed based on an angular velocity data sequence and a time domain response corresponding to each of the multiple angular velocity data, including: obtaining a residual function corresponding to each of the multiple angular velocity data based on the angular velocity data sequence and the time domain response corresponding to each of the multiple angular velocity data; obtaining a cost function based on the residual function corresponding to each of the multiple angular velocity data; constructing the gradient of the cost function for each of the multiple parameters to be identified included in the phase-locked loop parameters, to obtain a gradient model and a Hessian matrix model of the phase-locked loop; and obtaining a recursive iterative model based on Newton's method based on the gradient model and the Hessian matrix model.

[0010] According to an embodiment of the present disclosure, the initial parameters of a phase-locked loop are iteratively optimized using a recursive iterative model based on Newton's method to obtain the phase-locked loop parameters, including: substituting the initial parameters into a gradient model and a Hessian matrix model respectively to obtain gradient values ​​and Hessian matrices corresponding to the initial parameters; determining errors corresponding to the initial parameters based on the gradient values ​​and Hessian matrices corresponding to the initial parameters; iteratively optimizing the initial parameters based on the errors corresponding to the initial parameters to obtain iterated parameters; and determining the iterated parameters as the phase-locked loop parameters when the errors are less than an error threshold.

[0011] According to an embodiment of the present disclosure, the control parameter determination method of the grid-connected inverter further includes: when the error is greater than or equal to the error threshold, iteratively optimizing the iterated parameters using a recursive iteration model based on Newton's method to obtain phase-locked loop parameters.

[0012] According to an embodiment of the present disclosure, a d-axis current reference value of a current loop of a grid-connected inverter is used as an input of a frequency sweeping method, and a d-axis component of an output current of the grid-connected inverter is used as an output of the frequency sweeping method. Based on a preset frequency sweeping interval, a frequency response of the current loop is determined, including: sampling the preset frequency sweeping interval to obtain a plurality of sampling frequencies; for each sampling frequency, generating a disturbance signal based on the sampling frequency; superimposing the disturbance signal with the d-axis current reference value of the current loop and the d-axis component of the output current of the grid-connected inverter through a second disturbance injection point to obtain a current signal corresponding to the sampling frequency; using a frestimate function to process the current signal corresponding to the sampling frequency to obtain a frequency response corresponding to the sampling frequency; and merging the frequency responses corresponding to each of the plurality of sampling frequencies to obtain the frequency response of the current loop.

[0013] According to an embodiment of the present disclosure, for each sampling frequency, a disturbance signal is generated based on the sampling frequency, including: determining a period value based on the frequency range in which the sampling frequency is located; and generating a sine wave using the sampling frequency as the signal frequency, the period value as the number of periods of the signal, and the preset amplitude as the signal amplitude to obtain a disturbance signal.

[0014] According to an embodiment of the present disclosure, the frequency response of the current loop is processed based on the transfer function of the current loop to obtain the current loop parameters, including: based on the transfer function of the current loop, using the tfest function to identify the frequency response of the current loop to obtain an identification result; and based on the identification result, obtaining the current loop parameters.

[0015] Another aspect of the present disclosure provides a control parameter determination device for a grid-connected inverter, including:

[0016] A sequence acquisition module, used for inputting a preset frequency disturbance to the grid-following type grid-connected inverter through a first disturbance injection point, so as to acquire an angular velocity data sequence output by a phase-locked loop of the grid-following type grid-connected inverter under the preset frequency disturbance;

[0017] A sequence iteration module is used to perform recursive iteration based on the angular velocity data sequence using Newton's method to obtain phase-locked loop parameters;

[0018] a response determination module, configured to determine the frequency response of the current loop based on a preset frequency sweep interval by using a d-axis current reference value of the current loop of the grid-connected inverter as an input of the frequency sweep method and a d-axis component of the output current of the grid-connected inverter as an output of the frequency sweep method; and

[0019] The parameter determination module is used to process the frequency response of the current loop based on the transfer function of the current loop to obtain the current loop parameters.

[0020] Another aspect of the present disclosure provides an electronic device, comprising:

[0021] one or more processors;

[0022] a memory for storing one or more programs,

[0023] When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described above.

[0024] Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the above method when executed.

[0025] Another aspect of the present disclosure provides a computer program product, which includes computer executable instructions, and when the instructions are executed, are used to implement the method as described above.

[0026] According to an embodiment of the present disclosure, a disturbance is input to a grid-connected inverter through a first disturbance injection point, and an angular velocity data sequence output by a phase-locked loop is collected, and the angular velocity data sequence is processed using the Newton method to determine the phase-locked loop parameters. Iteration through the Newton method can improve the convergence speed, improve the stability of the simulation, and thus improve the accuracy of parameter determination. According to the d-axis current of the grid-connected inverter, the input and output of the sweep frequency method are determined to determine the frequency response of the current loop, and the current loop parameters are determined based on the frequency response of the current loop and the transfer function of the current loop. Since the sweep frequency method is a non-invasive measurement method, the frequency response of the current loop is determined by the sweep frequency method, and no additional test equipment is required, which reduces the load of the simulation system. In addition, the sweep frequency method can quickly determine the response of the system at different frequencies, which improves the efficiency of parameter determination. By simultaneously determining the phase-locked loop parameters and the current loop parameters, the influencing factors of the grid-connected inverter can be comprehensively considered, thereby improving the effect of the simulation and further ensuring the accuracy of the control parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0028] Figure 1 A circuit topology diagram showing a method and device for determining control parameters of a grid-connected inverter according to an embodiment of the present disclosure;

[0029] Figure 2 A flow chart of a method for determining control parameters of a grid-connected inverter according to an embodiment of the present disclosure is shown;

[0030] Figure 3A schematic diagram of disturbance injection of a phase-locked loop of a grid-connected inverter according to an embodiment of the present disclosure is shown;

[0031] Figure 4 A schematic diagram of disturbance injection of a current loop of a grid-connected inverter according to an embodiment of the present disclosure is shown;

[0032] Figure 5 A schematic diagram showing the dynamic response of a phase-locked loop of a real system after a disturbance is applied and a phase-locked loop of a parameter determination result according to an embodiment of the present disclosure;

[0033] Figure 6 A schematic diagram showing the dynamic response of the d-axis current of a real system after a disturbance is applied and the d-axis current of a parameter determination result according to another embodiment of the present disclosure;

[0034] Figure 7 A block diagram of a control parameter determination device for a grid-connected inverter according to an embodiment of the present disclosure is shown;

[0035] Figure 8 A block diagram of an electronic device suitable for implementing the method described above according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0036] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0037] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0038] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0039] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0040] In the embodiments of the present disclosure, the collection, updating, analysis, processing, use, transmission, provision, disclosure, storage, etc. of the data involved (for example, including but not limited to user personal information) are in compliance with the provisions of relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures are taken for user personal information to prevent illegal access to user personal information data and maintain the security of user personal information, network security, and national security.

[0041] In the embodiments of the present disclosure, the user's authorization or consent is obtained before obtaining or collecting the user's personal information.

[0042] An embodiment of the present disclosure provides a method for determining control parameters of a grid-connected inverter, comprising: inputting a preset frequency disturbance into the grid-connected inverter through a first disturbance injection point to collect an angular velocity data sequence output by a phase-locked loop of the grid-connected inverter under the preset frequency disturbance; using Newton's method to perform recursive iteration based on the angular velocity data sequence to obtain phase-locked loop parameters; using a d-axis current reference value of the current loop of the grid-connected inverter as an input of a frequency sweeping method and using a d-axis component of the output current of the grid-connected inverter as an output of the frequency sweeping method, and determining the frequency response of the current loop based on a preset frequency sweeping interval; and processing the frequency response of the current loop based on a transfer function of the current loop to obtain current loop parameters.

[0043] Figure 1 A circuit topology diagram of a method and device for determining control parameters of a grid-connected inverter according to an embodiment of the present disclosure is shown.

[0044] like Figure 1 As shown, the circuit 100 may include a DC power supply 101, a bridge inverter circuit 102, an L-type filter 103, a current sensor 104, and a voltage sensor 105. One end of the bridge inverter circuit 102 is connected to the DC power supply 101, and the other end is connected to the L-type filter 103. The other end of the L-type filter 103 is connected to a common grid connection point (Point of Common Coupling, PCC). The outlet of the L-type filter 103 is connected to a circuit sensor 104, and a voltage sensor 105 is provided at the common grid connection point PCC.

[0045] The DC power generated by the DC power supply 101 is inverted into AC power after passing through the bridge inverter circuit 102, and is input into the L-type filter 103 for filtering processing, and is connected to the public grid connection point PCC. The information of the AC power is collected by the current sensor 104 and the voltage sensor 105. The voltage collected by the voltage sensor 105 can be used as the voltage of the power grid.

[0046] The voltage of the public grid connection point PCC is input into the phase-locked loop, and then the voltage and current of PCC are input into the current loop after coordinate transformation. According to the voltage and current after coordinate transformation, the phase angle θ of the phase-locked loop is determined. PLL , the voltage and current of the current loop are transformed, and the voltage and current of the current loop after the coordinate transformation are adjusted using the phase angle of the phase-locked loop, and then pulse width modulation (PWM) is performed, and the result of PWM is input to the bridge inverter circuit 102.

[0047] It should be understood that Figure 1 The number of DC power supplies, bridge inverter circuits, L-type filters, current sensors, and voltage sensors in the embodiment is only for illustration. Any number of DC power supplies, bridge inverter circuits, L-type filters, current sensors, and voltage sensors may be provided as required.

[0048] Figure 2 A flow chart of a method for determining control parameters of a grid-connected inverter according to an embodiment of the present disclosure is shown.

[0049] like Figure 2 As shown, the method includes operations S210 to S240.

[0050] In operation S210, a preset frequency disturbance is input to the grid-connected inverter through a first disturbance injection point to collect an angular velocity data sequence output by a phase-locked loop of the grid-connected inverter under the preset frequency disturbance.

[0051] According to an embodiment of the present disclosure, the control parameters of the grid-connected inverter include phase-locked loop parameters and current loop parameters, wherein the phase-locked loop is used to synchronize the frequency and phase of the inverter output with the grid voltage, and the current loop is used to control the amplitude and phase of the inverter output current to achieve synchronization with the grid.

[0052] According to an embodiment of the present disclosure, the first disturbance injection point may be a node in the same loop as the grid-connected inverter. After a preset frequency disturbance is input into the first disturbance injection point, the disturbance will affect the grid-connected inverter through the loop, thereby causing the output result of the phase-locked loop of the grid-connected inverter to change.

[0053] According to an embodiment of the present disclosure, a current sensor or a voltage sensor is used to collect an angular velocity data sequence output by a phase-locked loop of a grid-connected inverter under a preset frequency disturbance, wherein the angular velocity data sequence includes a plurality of corresponding angular velocity data, and each angular velocity data includes a collection time and an angular velocity value at the collection time.

[0054] In operation S220, Newton's method is used to perform recursive iteration based on the angular velocity data sequence to obtain phase-locked loop parameters.

[0055] According to an embodiment of the present disclosure, Newton's method is an iterative method for solving the zero point of a function in the real number domain and the complex number domain, and the root of the equation can be gradually approximated by using the tangent of the function curve through multiple iterations. Therefore, the phase-locked loop parameters can be obtained by recursively iterating the angular velocity data sequence using Newton's method.

[0056] In operation S230, the d-axis current reference value of the current loop of the grid-connected inverter is used as the input of the sweep frequency method, and the d-axis component of the output current of the grid-connected inverter is used as the output of the sweep frequency method, and the frequency response of the current loop is determined based on a preset sweep frequency interval.

[0057] According to an embodiment of the present disclosure, the current loop of the grid-connected inverter includes a d-axis and a q-axis, which are established based on a rotating coordinate system, wherein the d-axis is in phase with the grid voltage, and the q-axis current is used to control the reactive power output by the grid-connected inverter.

[0058] According to an embodiment of the present disclosure, the current loop parameters can be fitted using a sweep frequency method. Since the sweep frequency method needs to inject sine waves of different frequencies separately to determine the amplitude and frequency response of the sine waves of different frequencies, the frequency range of the sine waves of different frequencies can be determined as the preset sweep frequency interval of the sweep frequency method.

[0059] According to an embodiment of the present disclosure, the d-axis current reference value of the current loop of the grid-connected inverter is used as the input of the sweeping frequency method, and the d-axis component of the output current of the grid-connected inverter is used as the output of the sweeping frequency method, so that the frequency response of the current loop is determined by the sweeping frequency method based on a preset sweeping frequency interval.

[0060] In operation S240 , the frequency response of the current loop is processed based on the transfer function of the current loop to obtain current loop parameters.

[0061] According to an embodiment of the present disclosure, the frequency response of the current loop is processed based on the transfer parameter of the current loop, so that the current loop parameter is inversely deduced according to the transfer function.

[0062] According to an embodiment of the present disclosure, a disturbance is input to a grid-connected inverter through a first disturbance injection point, and an angular velocity data sequence output by a phase-locked loop is collected, and the angular velocity data sequence is processed using the Newton method to determine the phase-locked loop parameters. Iteration through the Newton method can improve the convergence speed, improve the stability of the simulation, and thus improve the accuracy of parameter determination. According to the d-axis current of the grid-connected inverter, the input and output of the sweep frequency method are determined to determine the frequency response of the current loop, and the current loop parameters are determined based on the frequency response of the current loop and the transfer function of the current loop. Since the sweep frequency method is a non-invasive measurement method, the frequency response of the current loop is determined by the sweep frequency method, and no additional test equipment is required, which reduces the load of the simulation system. In addition, the sweep frequency method can quickly determine the response of the system at different frequencies, which improves the efficiency of parameter determination. By simultaneously determining the phase-locked loop parameters and the current loop parameters, the influencing factors of the grid-connected inverter can be comprehensively considered, thereby improving the effect of the simulation and further ensuring the accuracy of the control parameters.

[0063] According to an embodiment of the present disclosure, Newton's method is used to perform recursive iteration based on the angular velocity data sequence to obtain phase-locked loop parameters, including: obtaining time domain responses corresponding to each of the multiple angular velocity data based on a transfer function of the phase-locked loop, the acquisition moments of each of the multiple angular velocity data included in the angular velocity data sequence, and the angular velocity frequency domain response of the power grid in which the grid-connected inverter is located; constructing a recursive iterative model based on Newton's method based on the angular velocity data sequence and the time domain responses corresponding to each of the multiple angular velocity data; and iteratively optimizing the initial parameters of the phase-locked loop using the recursive iterative model based on Newton's method to obtain the phase-locked loop parameters.

[0064] According to an embodiment of the present disclosure, after the grid voltage is input into a phase-locked loop, a time domain response corresponding to each of the multiple angular velocity data is obtained based on the transfer function of the phase-locked loop, the collection time of each of the multiple angular velocity data included in the angular velocity data sequence, and the angular velocity frequency domain response of the grid in which the grid-connected inverter is located, wherein the time domain response corresponding to each of the multiple angular velocity data can be determined according to the real time domain response of the phase-locked loop corresponding to the collection time of each of the multiple angular velocity data.

[0065] According to an embodiment of the present disclosure, based on the angular velocity data sequence and the time domain responses corresponding to each of the multiple angular velocity data, a residual function and a cost function are constructed to construct a recursive iterative model based on Newton's method, and the recursive iterative model based on Newton's method is used to iteratively optimize the initial parameters of the phase-locked loop to obtain the phase-locked loop parameters.

[0066] According to the embodiments of the present disclosure, the time domain response is determined based on the transfer function of the phase-locked loop, the collection moments of the multiple angular velocity data included in the angular velocity data sequence, and the angular velocity frequency domain response of the power grid in which the grid-connected inverter is located. The simulation effect of the parameters can be improved according to the real data. A recursive iterative model based on Newton's method is constructed based on the angular velocity data sequence and the time domain response. The recursive iterative model based on Newton's method is used to perform iterative optimization to obtain the phase-locked loop parameters. The fast convergence and strong adaptability of the Newton's method can be used to improve the optimization efficiency and accuracy of the phase-locked loop parameters.

[0067] According to an embodiment of the present disclosure, based on a transfer function of a phase-locked loop, the acquisition moments of each of the multiple angular velocity data included in the angular velocity data sequence, and the angular velocity frequency domain response of the power grid in which the grid-connected inverter is located, a time domain response corresponding to each of the multiple angular velocity data is obtained, including: obtaining a frequency domain response function of the phase-locked loop based on the angular velocity frequency domain response of the power grid and the transfer function of the phase-locked loop; performing a time domain conversion on the frequency domain response function of the phase-locked loop to obtain a time domain response function of the phase-locked loop; and sampling the time domain response function of the phase-locked loop based on the acquisition moments of each of the multiple angular velocity data to obtain a time domain response corresponding to each of the multiple angular velocity data.

[0068] According to an embodiment of the present disclosure, based on the angular velocity frequency domain response of the power grid and the transfer function of the phase-locked loop , and obtain the frequency domain response function of the phase-locked loop , where the transfer function of the phase-locked loop is shown in formula (1):

[0069] (1)

[0070] in, is the phase-locked loop output angular velocity, is the actual angular velocity of the power grid, v is the amplitude of the power grid voltage, s is the Laplace operator, is the proportional coefficient of the PID controller of the phase-locked loop, is the integral coefficient of the PID controller of the phase-locked loop.

[0071] According to an embodiment of the present disclosure, the frequency domain response function of the phase-locked loop Perform time domain conversion to obtain the time domain response function of the phase-locked loop , where the time domain conversion can be performed by means of inverse Laplace transform.

[0072] According to an embodiment of the present disclosure, the acquisition time of each of the plurality of angular velocity data is substituted into the time domain response function , so as to sample the time domain response function of the phase-locked loop and obtain the time domain response corresponding to each of the multiple angular velocity data.

[0073] According to the embodiments of the present disclosure, based on the angular velocity frequency domain response and the transfer function of the phase-locked loop, the frequency domain response function of the phase-locked loop is determined, and the frequency domain response function of the phase-locked loop is converted into the time domain to obtain the time domain response function of the phase-locked loop, and the frequency domain is converted into the time domain to meet the subsequent use requirements of the time domain data, thereby reducing the amount of calculation and improving efficiency. The time domain response function of the phase-locked loop is sampled based on multiple acquisition moments to obtain the time domain response corresponding to each of the multiple angular velocity data. Since the time domain response is consistent with the acquisition moment of the angular velocity data, the correctness of the data can be ensured, thereby further improving the accuracy of determining the parameters of the phase-locked loop.

[0074] According to an embodiment of the present disclosure, a recursive iterative model based on Newton's method is constructed based on an angular velocity data sequence and a time domain response corresponding to each of the multiple angular velocity data, including: obtaining a residual function corresponding to each of the multiple angular velocity data based on the angular velocity data sequence and the time domain response corresponding to each of the multiple angular velocity data; obtaining a cost function based on the residual function corresponding to each of the multiple angular velocity data; constructing the gradient of the cost function for each of the multiple parameters to be identified included in the phase-locked loop parameters, to obtain a gradient model and a Hessian matrix model of the phase-locked loop; and obtaining a recursive iterative model based on Newton's method based on the gradient model and the Hessian matrix model.

[0075] According to an embodiment of the present disclosure, based on the angular velocity data sequence and the time domain response corresponding to each of the plurality of angular velocity data, a residual function corresponding to each of the plurality of angular velocity data is obtained, wherein for the angular velocity data at time k The time domain response corresponding to the angular velocity data at time k , the residual function is shown in formula (2):

[0076] (2)

[0077] According to an embodiment of the present disclosure, based on the residual functions corresponding to the plurality of angular velocity data, a cost function J is obtained, as shown in formula (3):

[0078] (3)

[0079] Wherein, m is the number of angular velocity data included in the angular velocity data sequence.

[0080] According to an embodiment of the present disclosure, after the cost function J is determined, the gradient of the cost function J can be constructed. For the kth angular velocity data, the gradient of the cost function is as shown in formula (4):

[0081] grad[J(α k )]= ∂ J ∂ α k (4)

[0082] in, is the kth parameter to be identified, k∈[1,n], preferably, n can be 2.

[0083] According to an embodiment of the present disclosure, the gradient model of the phase-locked loop can be determined according to the gradient of the cost function, as shown in formula (5):

[0084] grad[J] = [ grad[J(α 1 )] grad[J(α 2 )] ⋯ grad[J(α n )] ] (5)

[0085] According to an embodiment of the present disclosure, the Hessian matrix model of the phase-locked loop can also be determined according to the gradient of the cost function, as shown in formula (6):

[0086] H(α)= [ ∂ 2 J ∂ α 1 2 ∂ 2 J ∂ α 1 α 2 ⋯ ∂ 2 J ∂ α 1 α n ∂ 2 J ∂ α 2 α 1 ∂ 2 J ∂ α 2 2 ⋯ ∂ 2 J ∂ α 2 α n ⋮ ⋮ ⋱ ⋮ ∂ 2 J ∂ α n α 1 ∂ 2 J ∂ α n α 2 ⋯ ∂ 2 J ∂ α n 2 ] (6)

[0087] According to an embodiment of the present disclosure, a recursive iterative model based on Newton's method may be determined according to a gradient model and a Hessian matrix model of a phase-locked loop.

[0088] According to the embodiment of the present disclosure, the cost function is determined by the residual function, and the Hessian matrix model and the gradient model of the phase-locked loop are further determined. Since the cost function is the square of the error, the idea of ​​minimizing the square of the error by Newton's method is adopted to establish the Hessian matrix model and the gradient model of the phase-locked loop, and further determine the optimal solution of the phase-locked loop parameters, which can reduce the randomness of parameter determination and improve the accuracy of the phase-locked loop parameters.

[0089] According to an embodiment of the present disclosure, the initial parameters of a phase-locked loop are iteratively optimized using a recursive iterative model based on Newton's method to obtain the phase-locked loop parameters, including: substituting the initial parameters into a gradient model and a Hessian matrix model respectively to obtain gradient values ​​and Hessian matrices corresponding to the initial parameters; determining errors corresponding to the initial parameters based on the gradient values ​​and Hessian matrices corresponding to the initial parameters; iteratively optimizing the initial parameters based on the errors corresponding to the initial parameters to obtain iterated parameters; and determining the iterated parameters as the phase-locked loop parameters when the errors are less than an error threshold.

[0090] According to an embodiment of the present disclosure, the initial parameters are substituted into the gradient model and the Hessian matrix model respectively to obtain the gradient value and the Hessian matrix corresponding to the initial parameters. For example, the initial parameters can be taken as ,Will Substitute into the gradient model to get the gradient value corresponding to the initial parameters grad[J(α * )] ,Will Substitute into the Hessian matrix model to obtain the Hessian matrix corresponding to the initial parameters .

[0091] According to an embodiment of the present disclosure, based on the gradient value and the Hessian matrix corresponding to the initial parameters, the error corresponding to the initial parameters is determined. , as shown in formula (7):

[0092] Δα= [ H(α * ) ] − 1 grad[J(α * )] (7)

[0093] in,[·] -1 Represents the inverse of a matrix.

[0094] According to an embodiment of the present disclosure, based on the error , optimize the initial parameters and obtain the iterative parameters, as shown in formula (8):

[0095] α * = α * − [ H(α * ) ] − 1 grad[J(α * )] (8)

[0096] Among them, the left side of the equation is the parameter value after iteration, and the right side of the equation is the parameter value before iteration.

[0097] According to an embodiment of the present disclosure, the above operation is repeatedly performed until the error Less than the error threshold After that, the error Less than the error threshold The iterated parameters are determined as the phase-locked loop parameters.

[0098] According to the embodiments of the present disclosure, the magnitude relationship between the error and the error threshold is used as a condition for stopping iteration, so that the error of the phase-locked loop parameters can be quantitatively controlled, thereby ensuring the effect of iterative optimization and the accuracy of the phase-locked loop parameters.

[0099] According to an embodiment of the present disclosure, the control parameter determination method of the grid-connected inverter further includes: when the error is greater than or equal to the error threshold, iteratively optimizing the iterated parameters using a recursive iteration model based on Newton's method to obtain phase-locked loop parameters.

[0100] According to an embodiment of the present disclosure, in the error Greater than the error threshold In the case of , continue to use formula (7) to calculate the error, and iteratively optimize the parameters based on the error to obtain the parameters after the latest iteration.

[0101] According to the embodiments of the present disclosure, when the error is greater than the error threshold, iterative optimization is continued to ensure that the optimal solution is obtained by iterative optimization using the Newton method, thereby improving the accuracy of the phase-locked loop parameters.

[0102] Figure 3 A schematic diagram of disturbance injection of a phase-locked loop of a grid-connected inverter according to an embodiment of the present disclosure is shown.

[0103] like Figure 3 As shown, at the first disturbance injection point, the injection frequency of the grid-connected inverter is The original frequency is , and then Laplace transform is performed after superposition, and the phase angle of the grid voltage is Superimpose to obtain the data before grid connection, and determine the q-axis voltage after passing through the public grid connection point PCC , and use the phase-locked loop proportional coefficient , Phase-locked loop integral coefficient And Laplace operator s is processed to obtain the phase-locked loop angular velocity , after Laplace transformation, the phase angle of the phase-locked loop is determined , use the phase angle of the phase-locked loop to adjust the data before grid connection.

[0104] According to an embodiment of the present disclosure, a d-axis current reference value of a current loop of a grid-connected inverter is used as an input of a frequency sweeping method, and a d-axis component of an output current of the grid-connected inverter is used as an output of the frequency sweeping method. Based on a preset frequency sweeping interval, a frequency response of the current loop is determined, including: sampling the preset frequency sweeping interval to obtain a plurality of sampling frequencies; for each sampling frequency, generating a disturbance signal based on the sampling frequency; superimposing the disturbance signal with the d-axis current reference value of the current loop and the d-axis component of the output current of the grid-connected inverter through a second disturbance injection point to obtain a current signal corresponding to the sampling frequency; using a frestimate function to process the current signal corresponding to the sampling frequency to obtain a frequency response corresponding to the sampling frequency; and merging the frequency responses corresponding to each of the plurality of sampling frequencies to obtain the frequency response of the current loop.

[0105] According to an embodiment of the present disclosure, the preset frequency sweep interval can be [ , ], that is, [100 Hz, 100000 Hz], and perform equally spaced sampling in the preset sweep frequency interval to obtain multiple sampling frequencies. For example, 100 equally spaced points are taken on [100 Hz, 100000 Hz], and the frequency at each point is determined as the sampling frequency.

[0106] According to an embodiment of the present disclosure, for each sampling frequency, a sinusoidal wave with a frequency equal to the sampling frequency is generated as a disturbance signal, and the disturbance signal is superimposed with the d-axis current reference value of the current loop and the d-axis component of the output current of the grid-connected inverter through a second disturbance injection point to obtain a current signal corresponding to the sampling frequency.

[0107] According to an embodiment of the present disclosure, a frestimate function is used to process a current signal corresponding to a sampling frequency to obtain a frequency response corresponding to the sampling frequency, wherein the frestimate function can be used to estimate a system frequency response by injecting a designed input signal into a model and recording it, and then estimating the frequency response using the recorded signal, and the return value of the frestimate function is a frequency response data object.

[0108] According to an embodiment of the present disclosure, after obtaining multiple frequency responses corresponding to each sampling frequency, the frequency responses corresponding to each of the multiple sampling frequencies are merged to obtain the frequency response of the current loop, wherein merging the multiple frequency responses can combine the frequency response characteristics of multiple different systems to obtain a comprehensive frequency response that characterizes the overall system characteristics, and the merging of frequency responses can be achieved through means such as cascade frequency response, parallel frequency response, and feedback frequency response.

[0109] According to an embodiment of the present disclosure, a preset frequency sweep interval is sampled and processed to obtain multiple sampling frequencies, and a disturbance signal is generated for each sampling frequency. After the disturbance signal is injected through a second disturbance injection point, a current signal corresponding to the sampling frequency is obtained. Since the disturbance signal corresponds to the sampling frequency, a variety of different disturbances and different current signals can be injected, which improves the diversity of the disturbance, thereby making the current signal corresponding to the sampling frequency obtained more comprehensive. By using the frestimate function to process the current signal corresponding to the sampling frequency, the frequency response corresponding to the sampling frequency can be efficiently determined, and multiple frequency responses are combined to obtain the frequency response of the current loop, so that the frequency response can characterize the overall characteristics, thereby ensuring that the frequency response is more comprehensive and accurate.

[0110] According to an embodiment of the present disclosure, for each sampling frequency, a disturbance signal is generated based on the sampling frequency, including: determining a period value based on the frequency range in which the sampling frequency is located; and generating a sine wave using the sampling frequency as the signal frequency, the period value as the number of periods of the signal, and the preset amplitude as the signal amplitude to obtain a disturbance signal.

[0111] According to an embodiment of the present disclosure, for each sampling frequency, the frequency range in which it is located is determined, thereby determining a period value, wherein the period value is the number of periods of the disturbance signal generated based on the sampling frequency. For example, when there are 100 sampling frequencies, the period number of the 1st to 20th sampling frequencies can be set to 10, the period number of the 21st to 50th sampling frequencies can be set to 30, the period number of the 51st to 70th sampling frequencies can be set to 70, and the period number of the 71st to 100th sampling frequencies can be set to 100.

[0112] According to an embodiment of the present disclosure, a preset amplitude is determined. Preferably, the preset amplitude can be 5. A sine wave is generated with the sampling frequency as the signal frequency, the period value as the number of periods of the signal and the preset amplitude as the signal amplitude to obtain a disturbance signal corresponding to the sampling frequency.

[0113] According to an embodiment of the present disclosure, different period values ​​are determined for sampling frequencies in different frequency ranges using the same predicted amplitude, and a sine wave is generated based on the period value, predicted amplitude and sampling frequency to determine a disturbance signal. This can increase the difference between multiple disturbance signals generated by different sampling frequencies, thereby using multiple disturbance signals with large differences for disturbance, making the frequency response more comprehensive and improving the accuracy of the determined current loop parameters.

[0114] According to an embodiment of the present disclosure, the frequency response of the current loop is processed based on the transfer function of the current loop to obtain the current loop parameters, including: based on the transfer function of the current loop, using the tfest function to identify the frequency response of the current loop to obtain an identification result; and based on the identification result, obtaining the current loop parameters.

[0115] According to an embodiment of the present disclosure, based on the transfer function of the current loop , use the tfest function to identify the frequency response of the current loop and get the identification result , where the transfer parameters of the current loop can be obtained by simulating the Bode diagram. The transfer parameters of the current loop are shown in formula (9):

[0116] (9)

[0117] in, is the proportional coefficient of the PID controller of the current loop, is the integral coefficient of the PID controller of the current loop, R is the resistance value of the L-type filter, and L is the inductance value of the L-type filter.

[0118] According to an embodiment of the present disclosure, since the tfest function can be used to estimate the transfer function model of the system, that is, to estimate the parameters of the transfer function according to the input and output data, the current loop parameters can be calculated based on the identification results.

[0119] According to the embodiments of the present disclosure, the transfer function is fitted by means of a Bode diagram, without the need for time domain derivation, thereby reducing the amount of calculation and improving the calculation efficiency. The transfer function model is estimated using the tfest function, thereby improving the calculation efficiency and accuracy of the current loop parameters.

[0120] Figure 4 A schematic diagram of disturbance injection into the current loop of a grid-connected inverter according to an embodiment of the present disclosure is shown.

[0121] like Figure 4 As shown, after the disturbance signal is determined, the disturbance signal is injected at the second disturbance injection point, which is consistent with the d-axis component of the original output current. and d-axis reference value Superposition is performed using the current loop proportional coefficient , current loop integral coefficient and Laplace operator s, and then compared with the q-axis component of the original output current The inductive reactance through the inductor L The processed results are used to compare the d-axis current with the d-axis reference value. The difference between Make adjustments to determine the current loop parameters .

[0122] The q-axis component of the original output current and q-axis reference value Superposition is performed using the current loop proportional coefficient , current loop integral coefficient and Laplace operator s, and then combined with the d-circular component of the original output current The inductive reactance through the inductor L The processed results are used to compare the q-axis current with the q-axis reference value. Difference Make adjustments to determine the current loop parameters .

[0123] According to an embodiment of the present disclosure, circuit parameters of a simulation experiment of a control parameter determination method for a grid-connected inverter are shown in Table 1.

[0124] Table 1

[0125] Circuit system parameters Numeric DC voltage source voltage Vdc / V 700 Switching frequency / kHz 10 Grid voltage effective value / V 380 Filter inductance L / mH 1.8 Equivalent resistance R / #timg# 0.5 Grid frequency f / hz 50

[0126] According to an embodiment of the present disclosure, control parameters of a simulation experiment of a control parameter determination method for a grid-connected inverter are shown in Table 2.

[0127] Table 2

[0128] Control system parameters Numeric PLL scaling factor#timg# 1.364 PLL integral coefficient #timg# 289.3 Current loop proportionality factor #timg# 2 Current loop integral coefficient #timg# 250

[0129] The d-axis reference value of the output current of the grid-connected inverter is set to 50A, and the q-axis reference value is set to 0A.

[0130] According to an embodiment of the present disclosure, a control parameter determination method for a grid-connected inverter is used to identify the simulation system set up as shown in Tables 1 and 2, and iterative optimization is performed until the error is less than the error threshold. The identification results obtained are shown in Table 3.

[0131] Table 3

[0132] PLL scaling factor#timg# PLL integral coefficient #timg# Current loop proportionality factor #timg# Current loop integral coefficient #timg# True value 1.364 289.3 2 250 Identification value 1.3113 281.9681 1.9602 246.6215

[0133] According to Table 3, it can be determined that the error rates between the identified values ​​and the true values ​​of the PLL proportional coefficient, PLL integral coefficient, current loop proportional coefficient and current loop integral coefficient determined by the control parameter determination method of the grid-following type grid-connected inverter are 3.863%, 2.534%, 1.99% and 1.3514% respectively. The error rate is low and the parameter determination result is highly accurate.

[0134] Figure 5 A schematic diagram showing the dynamic response of a phase-locked loop of a real system after a disturbance is applied and a phase-locked loop of a parameter determination result according to an embodiment of the present disclosure is shown.

[0135] like Figure 5 As shown in the figure, a 5Hz disturbance is applied to the grid frequency at 0.05 seconds, and the actual response of the phase-locked loop of the real system is shown as the dotted line. The dynamic response of the phase-locked loop of the parameter determination result obtained by the control parameter determination method of the grid-connected inverter is shown as the solid line. It can be determined that the trends of the two dynamic response results are consistent and the error rate is low.

[0136] Figure 6 A schematic diagram showing the dynamic response of the d-axis current of a real system after a disturbance is applied and the d-axis current of a parameter determination result according to another embodiment of the present disclosure is shown.

[0137] like Figure 6 As shown in the figure, a 10A disturbance is applied to the grid frequency at 0.1 second, and the actual response of the d-axis current of the real system is shown as the dotted line. The dynamic response of the d-axis current of the parameter determination result obtained by the control parameter determination method of the grid-connected inverter is shown as the solid line. It can be determined that the trends of the two dynamic response results are consistent and the error rate is low.

[0138] Figure 7 A block diagram of a control parameter determination device for a grid-connected inverter according to an embodiment of the present disclosure is shown.

[0139] like Figure 7 As shown, the control parameter determination device 700 of the grid-connected inverter includes a sequence acquisition module 710 , a sequence iteration module 720 , a response determination module 730 and a parameter determination module 740 .

[0140] The sequence acquisition module 710 is used to input a preset frequency disturbance to the grid-connected inverter through the first disturbance injection point to collect the angular velocity data sequence output by the phase-locked loop of the grid-connected inverter under the preset frequency disturbance. In one embodiment, the sequence acquisition module 710 can be used to perform the operation S210 described above, which will not be repeated here.

[0141] The sequence iteration module 720 is used to perform recursive iteration based on the angular velocity data sequence using Newton's method to obtain phase-locked loop parameters. In one embodiment, the sequence iteration module 720 can be used to perform the operation S220 described above, which will not be described in detail here.

[0142] The response determination module 730 is used to determine the frequency response of the current loop based on a preset frequency sweep interval, using the d-axis current reference value of the current loop of the grid-connected inverter as the input of the frequency sweep method and the d-axis component of the output current of the grid-connected inverter as the output of the frequency sweep method. In one embodiment, the response determination module 730 can be used to perform the operation S230 described above, which will not be described in detail here.

[0143] The parameter determination module 740 is used to process the frequency response of the current loop based on the transfer function of the current loop to obtain the current loop parameters. In one embodiment, the parameter determination module 740 can be used to perform the operation S270 described above, which will not be described in detail here.

[0144] According to an embodiment of the present disclosure, the sequence iteration module 720 includes a response determination submodule, a model construction submodule and a parameter iteration submodule.

[0145] The response determination submodule is used to obtain the time domain response corresponding to each of the multiple angular velocity data based on the transfer function of the phase-locked loop, the collection time of each of the multiple angular velocity data included in the angular velocity data sequence, and the angular velocity frequency domain response of the power grid where the grid-connected inverter is located.

[0146] The model building submodule is used to build a recursive iterative model based on Newton's method based on the angular velocity data sequence and the time domain responses corresponding to each of the plurality of angular velocity data.

[0147] The parameter iteration submodule is used to iteratively optimize the initial parameters of the phase-locked loop using a recursive iteration model based on Newton's method to obtain the phase-locked loop parameters.

[0148] According to an embodiment of the present disclosure, the response determination submodule includes a first function determination unit, a function conversion unit, and a function sampling unit.

[0149] The first function determination unit is used to obtain the frequency domain response function of the phase-locked loop based on the angular velocity frequency domain response of the power grid and the transfer function of the phase-locked loop.

[0150] The function conversion unit is used to perform time domain conversion on the frequency domain response function of the phase-locked loop to obtain the time domain response function of the phase-locked loop.

[0151] The function sampling unit is used to sample the time domain response function of the phase-locked loop based on the respective acquisition moments of the multiple angular velocity data to obtain the time domain response corresponding to the respective multiple angular velocity data.

[0152] According to an embodiment of the present disclosure, the model construction submodule includes a second function determination unit, a third function determination unit, a gradient construction unit and a model construction unit.

[0153] The second function determination unit is used to obtain a residual function corresponding to each of the plurality of angular velocity data based on the angular velocity data sequence and the time domain response corresponding to each of the plurality of angular velocity data.

[0154] The third function determination unit is used to obtain a cost function based on the residual functions corresponding to each of the plurality of angular velocity data.

[0155] The gradient construction unit is used to construct the gradient of the cost function for the multiple parameters to be identified included in the phase-locked loop parameters, and obtain the gradient model and Hessian matrix model of the phase-locked loop.

[0156] The model building unit is used to obtain a recursive iterative model based on Newton's method based on the gradient model and the Hessian matrix model.

[0157] According to an embodiment of the present disclosure, the parameter iteration submodule includes a parameter substitution unit, an error determination unit, a parameter iteration unit and a parameter determination unit.

[0158] The parameter substitution unit is used to substitute the initial parameters into the gradient model and the Hessian matrix model respectively to obtain the gradient value and the Hessian matrix corresponding to the initial parameters.

[0159] The error determination unit is used to determine the error corresponding to the initial parameters based on the gradient value and the Hessian matrix corresponding to the initial parameters.

[0160] The parameter iteration unit is used to iteratively optimize the initial parameters based on the errors corresponding to the initial parameters to obtain the iterated parameters.

[0161] The parameter determination unit is used to determine the iterated parameter as the phase-locked loop parameter when the error is less than the error threshold.

[0162] According to an embodiment of the present disclosure, a control parameter determination device 700 for a grid-connected inverter includes a parameter iteration module.

[0163] The parameter iteration module is used to iteratively optimize the iterated parameters by using a recursive iteration model based on Newton's method when the error is greater than or equal to the error threshold, so as to obtain the phase-locked loop parameters.

[0164] According to an embodiment of the present disclosure, the response determination module 730 includes an interval sampling submodule, a signal generation submodule, a signal superposition submodule, a signal processing submodule and a frequency merging submodule.

[0165] The interval sampling submodule is used to perform sampling processing on the preset frequency sweep interval to obtain multiple sampling frequencies.

[0166] The signal generation submodule is used to generate a disturbance signal based on the sampling frequency for each sampling frequency.

[0167] The signal superposition submodule is used to superimpose the disturbance signal with the d-axis current reference value of the current loop and the d-axis component of the output current of the grid-connected inverter through the second disturbance injection point to obtain a current signal corresponding to the sampling frequency.

[0168] The signal processing submodule is used to process the current signal corresponding to the sampling frequency using the frestimate function to obtain the frequency response corresponding to the sampling frequency.

[0169] The frequency merging submodule is used to merge the frequency responses corresponding to the multiple sampling frequencies to obtain the frequency response of the current loop.

[0170] According to an embodiment of the present disclosure, the signal generation submodule includes a value determination unit and a sine wave generation unit.

[0171] The value determination unit is used to determine the period value based on the frequency range in which the sampling frequency is located.

[0172] The sine wave generating unit is used to generate a sine wave by taking the sampling frequency as the signal frequency, the period value as the number of periods of the signal and the preset amplitude as the signal amplitude, so as to obtain a disturbance signal.

[0173] According to an embodiment of the present disclosure, the parameter determination module 740 includes a frequency identification submodule and a parameter determination submodule.

[0174] The frequency identification submodule is used to identify the frequency response of the current loop based on the transfer function of the current loop using the tfest function to obtain the identification result.

[0175] The parameter determination submodule is used to obtain the current loop parameters based on the identification results.

[0176] According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits, or at least part of the functions of any one of them can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be at least partially implemented as hardware circuits, such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems on chips, systems on substrates, systems on packages, application specific integrated circuits (ASICs), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging circuits, or can be implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules, submodules, units, and subunits can be at least partially implemented as computer program modules, and when the computer program modules are run, the corresponding functions can be performed.

[0177] For example, any multiple of the sequence acquisition module 710, the sequence iteration module 720, the response determination module 730, and the parameter determination module 740 can be combined in one module / unit / sub-unit for implementation, or any one of the modules / units / sub-units can be split into multiple modules / units / sub-units. Alternatively, at least part of the functions of one or more of these modules / units / sub-units can be combined with at least part of the functions of other modules / units / sub-units and implemented in one module / unit / sub-unit. According to an embodiment of the present disclosure, at least one of the sequence acquisition module 710, the sequence iteration module 720, the response determination module 730, and the parameter determination module 740 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or by any one of the three implementation methods of software, hardware, and firmware, or by a suitable combination of any of them. Alternatively, at least one of the sequence acquisition module 710, the sequence iteration module 720, the response determination module 730 and the parameter determination module 740 may be at least partially implemented as a computer program module, and when the computer program module is executed, the corresponding function may be performed.

[0178] It should be noted that the control parameter determination system part of the grid-connected inverter in the embodiment of the present disclosure corresponds to the control parameter determination method part of the grid-connected inverter in the embodiment of the present disclosure. The description of the control parameter determination system part of the grid-connected inverter specifically refers to the control parameter determination method part of the grid-connected inverter, which will not be repeated here.

[0179] Figure 8 A block diagram of an electronic device suitable for implementing the method described above according to an embodiment of the present disclosure is shown. Figure 8 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0180] like Figure 8 As shown, the electronic device 800 according to an embodiment of the present disclosure includes a processor 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory ROM 802 or a program loaded from a storage part 808 to a random access memory RAM 803. The processor 801 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a dedicated microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 801 may also include an onboard memory for caching purposes. The processor 801 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0181] In RAM 803, various programs and data required for the operation of electronic device 800 are stored. Processor 801, ROM 802 and RAM 803 are connected to each other via bus 804. Processor 801 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 802 and / or RAM 803. It should be noted that the program can also be stored in one or more memories other than ROM 802 and RAM 803. Processor 801 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0182] According to an embodiment of the present disclosure, the electronic device 800 may further include an input / output (I / O) interface 805, which is also connected to the bus 804. The electronic device 800 may further include one or more of the following components connected to the input / output (I / O) interface 805: an input portion 806 including a keyboard, a mouse, etc.; an output portion 807 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 808 including a hard disk, etc.; and a communication portion 809 including a network interface card such as a LAN card, a modem, etc. The communication portion 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the input / output (I / O) interface 805 as needed. A removable medium 811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 810 as needed, so that the computer program read therefrom is installed into the storage portion 808 as needed.

[0183] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 809, and / or installed from the removable medium 811. When the computer program is executed by the processor 801, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0184] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0185] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0186] For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 802 and / or the RAM 803 described above and / or one or more memories other than the ROM 802 and the RAM 803 .

[0187] The embodiments of the present disclosure also include a computer program product, which includes a computer program, and the computer program contains program code for executing the method provided by the embodiments of the present disclosure. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the control parameter determination method of the grid-connected inverter provided by the embodiments of the present disclosure.

[0188] When the computer program is executed by the processor 801, the above functions defined in the system / device of the embodiment of the present disclosure are executed. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0189] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 809, and / or installed from a removable medium 811. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0190] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0191] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It can be understood by those skilled in the art that the features recorded in the various embodiments of the present disclosure can be combined and / or combined in a variety of ways, even if such a combination or combination is not explicitly recorded in the present disclosure. In particular, without departing from the spirit and teaching of the present disclosure, the features described in the various embodiments of the present disclosure may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0192] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A method for determining control parameters of a grid-connected inverter, characterized in that: The control parameters of the grid-connected inverter include phase-locked loop parameters and current loop parameters, and the method includes: Inputting a preset frequency disturbance to the grid-connected inverter through a first disturbance injection point to collect an angular velocity data sequence output by a phase-locked loop of the grid-connected inverter under the preset frequency disturbance; Using Newton's method, recursively iterate based on the angular velocity data sequence to obtain the phase-locked loop parameters; Using a d-axis current reference value of the current loop of the grid-connected inverter as an input of the frequency sweeping method and using a d-axis component of the output current of the grid-connected inverter as an output of the frequency sweeping method, and determining a frequency response of the current loop based on a preset frequency sweeping interval; and Processing the frequency response of the current loop based on the transfer function of the current loop to obtain the current loop parameters; The method of using Newton's method to perform recursive iteration based on the angular velocity data sequence to obtain the phase-locked loop parameters includes: Based on the transfer function of the phase-locked loop, the collection time of each of the multiple angular velocity data included in the angular velocity data sequence, and the angular velocity frequency domain response of the power grid where the grid-connected inverter is located, a time domain response corresponding to each of the multiple angular velocity data is obtained; constructing a recursive iterative model based on Newton's method based on the angular velocity data sequence and the time domain responses corresponding to each of the plurality of angular velocity data; and The initial parameters of the phase-locked loop are iteratively optimized using a recursive iterative model based on Newton's method to obtain the phase-locked loop parameters.

2. The method according to claim 1, characterized in that: The method of obtaining a time domain response corresponding to each of the plurality of angular velocity data based on the transfer function of the phase-locked loop, the respective acquisition moments of the plurality of angular velocity data included in the angular velocity data sequence, and the angular velocity frequency domain response of the power grid in which the grid-connected inverter is located comprises: Based on the angular velocity frequency domain response of the power grid and the transfer function of the phase-locked loop, a frequency domain response function of the phase-locked loop is obtained; Performing time domain conversion on the frequency domain response function of the phase-locked loop to obtain the time domain response function of the phase-locked loop; and The time domain response function of the phase-locked loop is sampled based on the respective acquisition moments of the plurality of angular velocity data to obtain the time domain responses corresponding to the respective plurality of angular velocity data.

3. The method according to claim 1, characterized in that: The constructing of a recursive iterative model based on Newton's method based on the angular velocity data sequence and the time domain responses corresponding to each of the plurality of angular velocity data comprises: Based on the angular velocity data sequence and the time domain responses corresponding to the plurality of angular velocity data respectively, obtaining a residual function corresponding to each of the plurality of angular velocity data respectively; Obtaining a cost function based on the residual functions corresponding to each of the plurality of angular velocity data; constructing the gradient of the cost function for each of the plurality of parameters to be identified included in the phase-locked loop parameters, and obtaining a gradient model and a Hessian matrix model of the phase-locked loop; and Based on the gradient model and the Hessian matrix model, the recursive iterative model based on Newton's method is obtained.

4. The method according to claim 3, characterized in that The iterative optimization of the initial parameters of the phase-locked loop using a recursive iterative model based on Newton's method to obtain the phase-locked loop parameters includes: Substituting the initial parameters into the gradient model and the Hessian matrix model respectively, to obtain the gradient value and the Hessian matrix corresponding to the initial parameters; Determine an error corresponding to the initial parameter based on a gradient value and a Hessian matrix corresponding to the initial parameter; Iteratively optimizing the initial parameters based on errors corresponding to the initial parameters to obtain iterated parameters; and When the error is less than an error threshold, the iterated parameter is determined as the phase-locked loop parameter.

5. The method according to claim 4, characterized in that The method further comprises: When the error is greater than or equal to the error threshold, the iterative parameters are iteratively optimized using a recursive iteration model based on Newton's method to obtain the phase-locked loop parameters.

6. The method according to claim 1, characterized in that The method uses the d-axis current reference value of the current loop of the grid-connected inverter as the input of the frequency sweeping method, uses the d-axis component of the output current of the grid-connected inverter as the output of the frequency sweeping method, and determines the frequency response of the current loop based on a preset frequency sweeping interval, including: Performing sampling processing on the preset frequency sweeping interval to obtain multiple sampling frequencies; For each sampling frequency, generating a disturbance signal based on the sampling frequency; The disturbance signal is superimposed with the d-axis current reference value of the current loop and the d-axis component of the output current of the grid-connected inverter through the second disturbance injection point to obtain a current signal corresponding to the sampling frequency; Using a frestimate function to process a current signal corresponding to the sampling frequency to obtain a frequency response corresponding to the sampling frequency; and The frequency responses corresponding to the multiple sampling frequencies are combined to obtain the frequency response of the current loop.

7. The method according to claim 6, characterized in that For each sampling frequency, generating a disturbance signal based on the sampling frequency comprises: Determining a period value based on the frequency range in which the sampling frequency is located; and The disturbance signal is obtained by generating a sine wave using the sampling frequency as the signal frequency, the period value as the number of periods of the signal and the preset amplitude as the signal amplitude.

8. The method according to claim 1, characterized in that The step of processing the frequency response of the current loop based on the transfer function of the current loop to obtain the current loop parameter includes: Based on the transfer function of the current loop, using the tfest function to identify the frequency response of the current loop to obtain an identification result; and Based on the identification result, the current loop parameter is obtained.

9. A control parameter determination device for a grid-connected inverter, characterized in that: The device comprises: A sequence acquisition module, used for inputting a preset frequency disturbance to the grid-connected inverter through a first disturbance injection point, so as to acquire an angular velocity data sequence output by a phase-locked loop of the grid-connected inverter under the preset frequency disturbance; A sequence iteration module, used for performing recursive iteration based on the angular velocity data sequence using Newton's method to obtain the phase-locked loop parameters; a response determination module, configured to determine the frequency response of the current loop based on a preset frequency sweep interval by using a d-axis current reference value of the current loop of the grid-connected inverter as an input of a frequency sweep method and a d-axis component of an output current of the grid-connected inverter as an output of the frequency sweep method; and A parameter determination module, configured to process the frequency response of the current loop based on the transfer function of the current loop to obtain the current loop parameters; Wherein, the sequence iteration module includes: a response determination submodule, configured to obtain a time domain response corresponding to each of the plurality of angular velocity data based on a transfer function of the phase-locked loop, a collection time of each of the plurality of angular velocity data included in the angular velocity data sequence, and an angular velocity frequency domain response of the power grid in which the grid-connected inverter is located; a model building submodule, configured to build a recursive iterative model based on Newton's method based on the angular velocity data sequence and the time domain responses corresponding to each of the plurality of angular velocity data; and The parameter iteration submodule is used to iteratively optimize the initial parameters of the phase-locked loop using a recursive iteration model based on Newton's method to obtain the phase-locked loop parameters.

Images