A distributed power source harmonic compensation control method and related device

Abstract

The embodiment of the application discloses a kind of distributed power harmonic compensation control method and related equipment, the method includes: based on Kirchhoff theorem, the mathematical model of LCL type inverter connected with distributed power is established, and the current signal of the LCL type inverter is obtained;The current signal is filtered, and the parameter estimation error of the LCL type inverter is obtained;The virtual control rate and parameter estimation value of the LCL type inverter are determined based on the current signal and the parameter estimation error;According to the virtual control rate and the parameter estimation value, the control parameter of the LCL type inverter is adjusted, and the harmonic compensation of distributed power is completed.Parameter estimation value is associated with the control parameter of the LCL type inverter, and the control parameter of the LCL type inverter is adjusted in real time, to improve the performance of controller.

Description

Technical Field

[0001] This invention relates to the field of grid-connected converter management technology, and in particular to a method and related equipment for harmonic compensation control of distributed power sources. Background Technology

[0002] Harmonic currents and unbalanced voltages in the power grid, caused by various factors, pose significant challenges to the safe and stable operation of distributed generation grid-connected inverters. In distributed generation grid-connected inverters, the current controller is used to control the grid-connected current, and its control performance directly affects the power quality and grid-connected stability of the distributed generation.

[0003] Current controller design for harmonic compensation is divided into selective harmonic compensation control methods and non-selective harmonic compensation control methods. Selective harmonic compensation control methods mainly include proportional-integral (PI) control and proportional-resonant (PR) control, or parallel PR controllers designed for several harmonic frequencies with severe harmonic pollution. However, the design and computational burden of designing a separate controller for each harmonic component is significant, and the suppression effect is poor when harmonic components change.

[0004] Non-selective harmonic compensation strategies include repetitive control, deadbeat current predictive control, and adaptive control methods. These strategies effectively suppress harmonic components without requiring separate controllers for each component. However, repetitive control has a slow response to varying harmonics and cannot guarantee robustness under system parameter fluctuations, unmodeled dynamics, and disturbances. Deadbeat current predictive control offers better dynamic response but is highly sensitive to system parameter uncertainties. Adaptive control methods can estimate uncertain parameters in the system in real time by designing an adaptive rate and adjust controller parameters accordingly to achieve high-performance harmonic suppression. Traditional robust parameter estimation methods in adaptive control, such as the σ-correction method and the e-correction method, can guarantee system parameter convergence. However, the introduction of damping terms affects the accuracy and rate of parameter convergence, which directly impacts the overall grid-connected control performance. Summary of the Invention

[0005] In view of this, the present invention provides a distributed power source harmonic compensation control method and related equipment to solve the problem that the introduction of damping terms in the existing adaptive control technology will affect the accuracy and convergence rate of parameter convergence, and thus affect the overall grid-connected control performance.

[0006] To achieve one or more of the above objectives or other objectives, the present invention proposes a distributed power source harmonic compensation control method, comprising: establishing a mathematical model of an LCL inverter connected to a distributed power source based on Kirchhoff's theorem, and acquiring the current signal of the LCL inverter;

[0007] The current signal is filtered, and the parameter estimation error of the LCL inverter is obtained;

[0008] The virtual control law and parameter estimate of the LCL inverter are determined based on the current signal and the parameter estimation error.

[0009] The control parameters of the LCL inverter are adjusted according to the virtual control law and the parameter estimate to complete the harmonic compensation of the distributed power source.

[0010] Optionally, the step of establishing a mathematical model of an LCL-type inverter connected to a distributed power source based on Kirchhoff's theorem includes:

[0011] The grid-connected state equations for an LCL inverter connected to distributed power sources are established based on Kirchhoff's theorem.

[0012] By analyzing the three phases of the LCL inverter separately and defining state variables, the grid-connected state equations are used to obtain the state-space expression of the LCL inverter.

[0013] The state-space expression is simplified to the form of a regression matrix multiplied by an unknown parameter matrix to obtain the target mathematical model of the LCL inverter.

[0014] Optionally, the step of acquiring the current signal of the LCL inverter includes:

[0015] Using i p -i q The detection method separates the harmonic / interharmonic current components from the current flowing through the nonlinear load in the LCL inverter;

[0016] The target current signal of the LCL inverter is obtained by integrating the harmonic / interharmonic current components and the original reference current.

[0017] Optionally, the step of filtering the current signal and obtaining the parameter estimation error of the LCL inverter includes:

[0018] The target current signal of the LCL inverter is filtered to obtain the filtered state variables.

[0019] An auxiliary matrix is ​​constructed based on the filtered state variables, and the parameter estimation error of the LCL inverter is obtained based on the auxiliary matrix.

[0020] Optionally, the step of determining the virtual control law and parameter estimate of the LCL inverter based on the current signal and the parameter estimation error includes:

[0021] The Lyapunov function is used to determine the first-order virtual control law and the first-order adaptive law, the second-order virtual control law and the second-order adaptive law, and the third-order virtual control law and the third-order adaptive law of the LCL inverter based on the current signal and the parameter estimation error.

[0022] The first-order parameter estimate of the LCL inverter is determined based on the first-order adaptive rate.

[0023] The second-order parameter estimate of the LCL inverter is determined based on the second-order adaptive rate.

[0024] The estimated values ​​of the third-order parameters of the LCL inverter are determined based on the third-order adaptive rate.

[0025] Optionally, the step of adjusting the control parameters of the LCL inverter based on the virtual control law and the parameter estimate includes:

[0026] Track the differential signals of the first-order virtual control law and the second-order virtual control law;

[0027] The actual control rate of the LCL inverter is obtained based on the differential signal.

[0028] The control parameters of the LCL inverter are adjusted based on the actual control rate and the parameter estimate.

[0029] Optionally, before the step of tracking the differential signals of the first-order virtual control law and the second-order virtual control law, the method further includes:

[0030] A preset high-order sliding mode differentiator is constructed. The preset high-order sliding mode differentiator is used to track the first derivative of the virtual control law. The preset high-order sliding mode differentiator includes a first high-order sliding mode differentiator and a second high-order sliding mode differentiator. The first high-order sliding mode differentiator has an order of 3, and the second high-order sliding mode differentiator has an order of 2.

[0031] Secondly, this application provides a distributed power source harmonic compensation control device, the device comprising:

[0032] The model building module is used to establish a mathematical model of an LCL inverter connected to a distributed power source based on Kirchhoff's theorem, and to obtain the current signal of the LCL inverter.

[0033] A filtering module is used to filter the current signal and obtain the parameter estimation error of the LCL inverter.

[0034] The calculation module is used to determine the virtual control law and parameter estimate of the LCL inverter based on the current signal and the parameter estimation error;

[0035] The adjustment module is used to adjust the control parameters of the LCL inverter according to the virtual control law and the parameter estimate, so as to complete the harmonic compensation of the distributed power source.

[0036] Thirdly, this application provides an electronic device, including: a processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the memory through the bus, and when the machine-readable instructions are executed by the processor, the steps of the distributed power supply harmonic compensation control method described above are performed.

[0037] Fourthly, this application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the distributed power supply harmonic compensation control method described above.

[0038] Implementing the embodiments of the present invention will have the following beneficial effects:

[0039] A mathematical model of an LCL-type inverter connected to a distributed generation source is established based on Kirchhoff's theorem, and the current signal of the LCL-type inverter is obtained. The current signal is filtered, and the parameter estimation error of the LCL-type inverter is obtained. Based on the current signal and the parameter estimation error, the virtual control law and parameter estimate of the LCL-type inverter are determined. The control parameters of the LCL-type inverter are adjusted according to the virtual control law and the parameter estimate to complete the harmonic compensation of the distributed generation source. This method can estimate various electrical parameters in the power grid system online, accurately, and quickly, and can improve control performance in real time, improve the power quality of distributed generation source grid connection, and suppress harmonics / interharmonics. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] in:

[0042] Figure 1This is a flowchart of a distributed power supply harmonic compensation control method provided in an embodiment of this application;

[0043] Figure 2 This is a schematic diagram of the structure of a distributed power supply harmonic compensation control device provided in an embodiment of this application;

[0044] Figure 3 This is a schematic diagram of the structure of a distributed power supply harmonic compensation control system provided in an embodiment of this application;

[0045] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application;

[0046] Figure 5 This is a schematic diagram of the structure of a storage medium provided in an embodiment of this application. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] like Figure 1 As shown in the figure, this application provides a distributed power source harmonic compensation control method, including:

[0049] S101. Establish a mathematical model of the LCL inverter connected to the distributed power source based on Kirchhoff's theorem, and obtain the current signal of the LCL inverter.

[0050] S102. Filter the current signal and obtain the parameter estimation error of the LCL inverter;

[0051] S103. Determine the virtual control law and parameter estimate of the LCL inverter based on the current signal and the parameter estimation error;

[0052] S104. Adjust the control parameters of the LCL inverter according to the virtual control law and the parameter estimate to complete the harmonic compensation of the distributed power source.

[0053] A mathematical model of an LCL-type inverter connected to a distributed generation source is established based on Kirchhoff's theorem, and the current signal of the LCL-type inverter is obtained. The current signal is filtered, and the parameter estimation error of the LCL-type inverter is obtained. Based on the current signal and the parameter estimation error, the virtual control law and parameter estimate of the LCL-type inverter are determined. The control parameters of the LCL-type inverter are adjusted according to the virtual control law and the parameter estimate to complete the harmonic compensation of the distributed generation source. This method can estimate various electrical parameters in the power grid system online, accurately, and quickly, and can improve control performance in real time, improve the power quality of distributed generation source grid connection, and suppress harmonics / interharmonics.

[0054] In one possible implementation, the step of establishing a mathematical model of an LCL-type inverter connected to a distributed power source based on Kirchhoff's theorem includes:

[0055] The grid-connected state equations for an LCL inverter connected to distributed power sources are established based on Kirchhoff's theorem.

[0056] By analyzing the three phases of the LCL inverter separately and defining state variables, the grid-connected state equations are used to obtain the state-space expression of the LCL inverter.

[0057] The state-space expression is simplified to the form of a regression matrix multiplied by an unknown parameter matrix to obtain the target mathematical model of the LCL inverter.

[0058] For example, the grid-connected state equation of an LCL inverter connected to a distributed power source in the static abc coordinate system can be obtained from Kirchhoff's laws, as follows:

[0059]

[0060] in, It is the three-phase inverter side current with reference to the neutral point n. Let v be the grid-side current with reference to n. abc (t)=[v a (t), v b (t), v c (t)] T ∈R 3 The capacitor voltage of the LCL filter is referenced to n. Let u be the grid voltage referenced to n. abc (t)=[u a u b u c ] T ∈R 3This refers to the output voltage of the three-phase inverter-side current controller with reference to n. The three-phase microgrid includes an electrical neutral point n. To facilitate controller design, each phase is analyzed separately, and variables are defined. in v a (t), and u a (t) represents the single-phase grid current, single-phase capacitor voltage, single-phase inverter current, single-phase grid voltage, and single-phase current controller input voltage, respectively. Therefore, formula (1) can be rewritten as:

[0061]

[0062] Let α1 = [-R] i2 / L i2 -1 / L i2 ] T ∈R 2 α2=-1 / C *1 ∈R, α3=[-1 / L1, -R1 / L1] T ∈R 2 ;φ1=[x1,V g ] T ∈R 2 ,φ2=x1∈Rφ3=[x2,x3] T ∈R 2 And [θ1, θ2, θ3] = [1 / L i2 , 1 / C i1 1 / L i1 After simplification, we get:

[0063]

[0064] Next, we define W1 = [α1; θ1] ∈ R 3 W2=[α2;θ2]∈R 3 W3 = [α3; θ3] ∈ R 3 And Ψ1=[φ1;x2]∈R 3 Ψ2=[φ2;x3]∈R 3 Ψ3=[φ3;u]∈R 3 We can obtain:

[0065]

[0066] In one possible implementation, the step of acquiring the current signal of the LCL inverter includes:

[0067] Using i p -i qThe detection method separates the harmonic / interharmonic current components from the current flowing through the nonlinear load in the LCL inverter;

[0068] The target current signal of the LCL inverter is obtained by integrating the harmonic / interharmonic current components and the original reference current.

[0069] For example, using i p -i q The detection method first uses a phase-locked loop (PLL) to generate a sinusoidal signal sinωt in phase with the grid voltage and a corresponding cosine signal -cosωt. The three-phase current i on the grid side... i2abv The active component of the current, i, is obtained after the Park-Clark transformation. i2p and reactive component i i2q Next, i i2p and i i2q After filtering by a low-pass filter, the DC components of the active and reactive currents are obtained. and The fundamental component i can be obtained by performing an inverse Clark-Park transform on the DC component. if2abc Then the grid-side current i i2abc with i if2abc Harmonic current components can be extracted by subtraction. Finally, the original current reference signal With harmonic current components By superimposing these signals, the overall current reference signal can be obtained.

[0070] In one possible implementation, the step of filtering the current signal and obtaining the parameter estimation error of the LCL inverter includes:

[0071] The target current signal of the LCL inverter is filtered to obtain the filtered state variables.

[0072] An auxiliary matrix is ​​constructed based on the filtered state variables, and the parameter estimation error of the LCL inverter is obtained based on the auxiliary matrix.

[0073] For example, a first-order low-pass filter operation is performed on both sides of the simplified model formula (5).

[0074] A first-order low-pass filter (·) is introduced on both sides of equation (4). f =(·) / (ks+1), to reduce the interference of high-frequency measurement noise on the extraction of parameter estimation error and to avoid differential signals. Direct use, after filtering, variable x nf Ψ nf (n = 1, 2, 3) is defined as follows:

[0075]

[0076] Where κ>0 is the filter parameter.

[0077] Substituting the filter variables obtained from formulas (5) and (6) into formulas (4) and (4) yields:

[0078]

[0079] Based on the filtered state variables, design an auxiliary matrix P. n Q n and H n , (where n = 1, 2, 3) to extract parameter estimation error.

[0080] In order to extract the parameter estimation error through simple algebraic calculations, an auxiliary matrix P is designed. n and auxiliary matrix Q n Where n = 1, 2, 3, as follows:

[0081]

[0082] In formula (8), l > 0, which is to ensure that the auxiliary matrix P n and Q n The solution to the bounded differential equation formula (8) is as follows:

[0083]

[0084] Next, by designing the auxiliary matrix H n (n = 1, 2, 3) allows us to extract the parameter estimation error, as follows:

[0085]

[0086] in, These are the electrical parameters to be estimated.

[0087] In one possible implementation, the step of determining the virtual control law and parameter estimate of the LCL inverter based on the current signal and the parameter estimation error includes:

[0088] The Lyapunov function is used to determine the first-order virtual control law and the first-order adaptive law, the second-order virtual control law and the second-order adaptive law, and the third-order virtual control law and the third-order adaptive law of the LCL inverter based on the current signal and the parameter estimation error.

[0089] The first-order parameter estimate of the LCL inverter is determined based on the first-order adaptive rate.

[0090] The second-order parameter estimate of the LCL inverter is determined based on the second-order adaptive rate.

[0091] The estimated values ​​of the third-order parameters of the LCL inverter are determined based on the third-order adaptive rate.

[0092] For example, the steps of determining the first-order virtual control law and the first adaptive law using Lyapunov functions based on the current signal and the parameter estimation error include:

[0093] The grid-side output current tracking error is defined as follows:

[0094] e1 = x1 - x 1d (11)

[0095] Design the Lyapunov function based on the current tracking error e1 and the parameter estimation error W1:

[0096]

[0097] The first-order virtual control law can be obtained, where Γ1>0∈R 3×3 Estimate the gain for the parameters;

[0098]

[0099] Where c1 > 0 is the control gain. as well as These are the parameters to be estimated.

[0100] Similarly, according to formula (12), the first adaptive rate can be designed as:

[0101]

[0102] Where σ1>0 is the gain, the unknown parameters can be realized through the adaptive rate formula (14). and The online real-time update, and through the virtual control law formula (13) and the adaptive law (14), can ensure that the first-order tracking error and parameter estimation error can converge exponentially to zero at the same time.

[0103] Design a second-order virtual control law and a second adaptive law.

[0104] Based on the backstepping method, a second-order virtual control law is designed to ensure that the actual x2 tracks the desired signal x. 2d The second-order error is defined as:

[0105] e² = x² - x 2d (15)

[0106] Based on the tracking error e2 and parameter estimation error Design a Lyapunov function:

[0107]

[0108] Where Γ2>0∈R 2×2 To estimate the gain matrix for the parameters, the second-order virtual control law x can be obtained from formula (16). 3d for:

[0109]

[0110] Where c2 > 0 is the control gain. as well as These are the parameters to be estimated.

[0111] Similarly, from formula (16), the second adaptive rate can be obtained as:

[0112]

[0113] Where σ2>0 is the gain, the tracking errors e1 and e2 and the parameter estimation error can be realized through the virtual control law formula (13) and the virtual control law formula (17), the adaptive law formula (14) and the adaptive law formula (18). and At the same time, the exponent converges to zero, that is, x1, x2. and The exponents converge to x. 1d x 2d W1 and W2 can achieve the unknown parameters by using the adaptive rate formula (18). Real-time updates and will obtain the updates Incorporating this into the controller will improve its overall control performance.

[0114] Design the third-order actual control law and the third adaptive law.

[0115] The current controller is designed with an actual control rate u to ensure that x3 can track x. 3d This enables the actual grid-side current x1 to track the reference current x. 1d Define the error:

[0116] e3 = x3 - x 3d (19)

[0117] Based on the tracking error e3 and the parameter estimation error Lyapunov function:

[0118]

[0119] Where Γ3>0∈R 3×3 To estimate the gain matrix for the parameters, the actual control law u can be obtained according to formula (20):

[0120]

[0121] Where c3 > 0 is the control gain. and These are the parameters to be estimated.

[0122] According to formula (20), the third adaptive rate can be designed as follows:

[0123]

[0124] Where σ3>0 is the gain, and according to the Lyapunov stability criterion, when using the actual control law formula (21), the virtual control law formula (17) and formula (13), and the adaptive control law formula (14), formula (18) and (22), the tracking errors e1, e2 and e3 and the parameter estimation error can be reduced. and It can simultaneously converge exponentially to zero. Traditional robust control methods, such as the σ-correction method, can only converge the parameter estimation error and control error to a compact concentration near zero. Furthermore, the transient response of the controller may degrade control performance due to the slow parameter convergence caused by the traditional adaptive rate. However, directly using H... n The design of the adaptive rate (n=1, 2, 3) can ensure that the parameter estimation error exponent converges to zero, thereby improving the parameter estimation performance and thus improving the control performance of the current controller.

[0125] In one possible implementation, the step of adjusting the control parameters of the LCL inverter based on the virtual control law and the parameter estimate includes:

[0126] Track the differential signals of the first-order virtual control law and the second-order virtual control law;

[0127] The actual control rate of the LCL inverter is obtained based on the differential signal.

[0128] The control parameters of the LCL inverter are adjusted based on the actual control rate and the parameter estimate.

[0129] In one possible implementation, prior to the step of tracking the differential signals of the first-order virtual control law and the second-order virtual control law, the method further includes:

[0130] A preset high-order sliding mode differentiator is constructed. The preset high-order sliding mode differentiator is used to track the first derivative of the virtual control law. The preset high-order sliding mode differentiator includes a first high-order sliding mode differentiator and a second high-order sliding mode differentiator. The first high-order sliding mode differentiator has an order of 3, and the second high-order sliding mode differentiator has an order of 2.

[0131] For example, a high-order sliding mode differentiator is designed to track the virtual control law (23) and the differential signal of the virtual control law (24).

[0132] From formulas (12)(13), (17)(16), and (21)(20), the measurable disturbance term V can be found. g / L i2 Existing in virtual control law x 2d In the first derivative of the virtual control law Existing in virtual control law x 3d In, and the first derivative of the virtual control law The differential signal of the disturbance term, present in the actual control law u, is highly sensitive to noise. Direct differentiation would reduce the robustness of the controller; therefore, a differentiator is needed to observe the differential signal. A high-order sliding mode differentiator conforms to the separation principle, meaning the differentiator and controller can be designed separately, and this differentiator guarantees convergence of the observed value within a finite time. Therefore, a high-order sliding mode differentiator is used to track the differential of the virtual control law.

[0133] Design a high-order sliding mode differentiator to observe signals. Set the order of the high-order sliding mode differentiator to 3, and assume |x 2d (r) If |≤L1, the specific design of the differentiator is as follows:

[0134]

[0135] Where z r (r = 1, 2, 3) are the observed variables, λ1 > 0, λ2 > 0, and λ3 > 0 are the differentiator gains, and sign(·) is the sign function. A higher-order sliding mode differentiator can be used to make z... r →x 2d (r) That is, z1 can track the target within a finite time. Will The derivative signal of the virtual control law can be input into the controller. Compensation will be provided.

[0136] In addition, a higher-order sliding mode observer of order 2 is designed to observe the signal. And assume |x 3d (r)|≤L2, as follows:

[0137]

[0138] Among them, z r1 (r = 1, 2), λ1 > 0 and λ2 > 0 are the differentiator gains, and this high-order sliding mode differentiator can make z equal to the gain of the differentiator in a finite time. r1 →x 2d (r1) That is, within a finite time z 11 Tracking the signal By compensating the observed differential signal into the controller, the actual control law u can be obtained as:

[0139]

[0140] like Figure 3 As shown, the controller in the LCL inverter is a backstepping controller, including virtual control law formulas (17) and (13) and actual control law formula (24). Unknown electrical parameters are estimated online using adaptive control law formulas (14), (18), and (22), and the estimated parameters are introduced into the controller to adjust the controller parameters in real time, thereby improving controller performance. The required differential signal in the backstepping controller is observed using high-order sliding mode differentiator formulas (22) and (23). and Thus, the controller design is completed. Using the proposed controller, the tracking error and parameter estimation error can be exponentially converged to zero.

[0141] In one possible implementation, such as Figure 2 As shown, this application provides a distributed power source harmonic compensation control device, the device comprising:

[0142] The model building module 201 is used to establish a mathematical model of an LCL inverter connected to a distributed power source based on Kirchhoff's theorem, and to obtain the current signal of the LCL inverter.

[0143] The filtering module 202 is used to filter the current signal and obtain the parameter estimation error of the LCL inverter.

[0144] Calculation module 203 is used to determine the virtual control law and parameter estimate of the LCL inverter based on the current signal and the parameter estimation error;

[0145] The adjustment module 204 is used to adjust the control parameters of the LCL inverter according to the virtual control law and the parameter estimate, so as to complete the harmonic compensation of the distributed power source.

[0146] In one possible implementation, such as Figure 3 As shown, the distributed power source harmonic compensation control system includes a distributed power source, an LCL-type grid-connected inverter, a nonlinear load, a harmonic / interharmonic current detection module, a parameter estimation module, a current controller based on the adaptive backstepping method, and a PWM modulation module. The overall workflow is as follows: the distributed power source provides DC power to the three-phase grid-connected inverter. The three-phase grid-connected inverter, acting as the grid interface, converts the DC power to AC power through the modulation signal of the PWM modulation module. After filtering by an LCL-type filter, the AC power is connected to the microgrid to obtain the grid-side current i. gabc To achieve grid-connected power supply, microgrids often contain localized nonlinear unbalanced loads and numerous power electronic devices, which can degrade power quality at the microgrid's point of common coupling (PCC). To eliminate the adverse effects of harmonics / interharmonics on the grid, a harmonic / interharmonic current detection module extracts the harmonic / interharmonic currents caused by the nonlinear loads based on the three-phase voltage and load current at the PCC point and provides a reference current i that is equal in magnitude but opposite in direction. href , and the original reference current i ref The integrated current provides a general reference current to the current controller; subsequently, the current controller outputs a control signal u based on the provided general reference current. abc However, factors such as processing technology, manufacturing errors, temperature changes, and component aging can cause parameter fluctuations in LCL filters. These electrical parameters are directly used in the design of the current controller, and inaccurate parameters will directly affect the robustness and response speed of the controller, thereby affecting the power quality of distributed power grid connection. Therefore, a parameter estimation module was designed to extract the parameter estimation error of the LCL filter in real time, and use this error to adjust the parameters of the adaptive backstepping current controller in real time, thereby improving the performance of the current controller and improving the overall grid connection performance.

[0147] One possible implementation, such as Figure 4 As shown, this application embodiment provides an electronic device 300, including: a memory 310, a processor 320, and a computer program 311 stored in the memory 310 and executable on the processor 320. When the processor 320 executes the computer program 311, it performs the following steps: establishing a mathematical model of an LCL-type inverter connected to a distributed power source based on Kirchhoff's theorem, and acquiring the current signal of the LCL-type inverter; filtering the current signal and acquiring the parameter estimation error of the LCL-type inverter; determining the virtual control law and parameter estimation value of the LCL-type inverter based on the current signal and the parameter estimation error; and adjusting the control parameters of the LCL-type inverter according to the virtual control law and the parameter estimation value to complete the harmonic compensation of the distributed power source.

[0148] In one possible implementation, such as Figure 5 As shown, this application embodiment provides a computer-readable storage medium 400 storing a computer program 411. When executed by a processor, the computer program 411 performs the following steps: establishing a mathematical model of an LCL-type inverter connected to a distributed power source based on Kirchhoff's theorem, and acquiring the current signal of the LCL-type inverter; filtering the current signal and acquiring the parameter estimation error of the LCL-type inverter; determining the virtual control law and parameter estimation value of the LCL-type inverter based on the current signal and the parameter estimation error; and adjusting the control parameters of the LCL-type inverter according to the virtual control law and the parameter estimation value to complete the harmonic compensation step of the distributed power source.

[0149] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0150] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0151] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0152] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0153] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computing device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0154] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

[0155] The above description discloses only preferred embodiments of the present invention and should not be construed as limiting the scope of the present invention. Therefore, equivalent variations made in accordance with the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for harmonic compensation control of distributed power sources, characterized in that, include: A mathematical model of an LCL inverter connected to a distributed power source is established based on Kirchhoff's theorem, and the current signal of the LCL inverter is obtained. The current signal is filtered, and the parameter estimation error of the LCL inverter is obtained; The virtual control law and parameter estimate of the LCL inverter are determined based on the current signal and the parameter estimation error. The control parameters of the LCL inverter are adjusted according to the virtual control law and the parameter estimate to complete the harmonic compensation of the distributed power source. The step of acquiring the current signal of the LCL inverter includes: use The detection method separates the harmonic / interharmonic current components from the current flowing through the nonlinear load in the LCL inverter; The target current signal of the LCL inverter is obtained by integrating the harmonic / interharmonic current components and the original reference current. The step of filtering the current signal and obtaining the parameter estimation error of the LCL inverter includes: The target current signal of the LCL inverter is filtered to obtain the filtered state variables. An auxiliary matrix is ​​constructed based on the filtered state variables, and the parameter estimation error of the LCL inverter is obtained based on the auxiliary matrix. The formula for the filtered state variables is as follows: in, These are the filter parameters. The filtered state variables; Substitute the obtained filter variables into the formula We can obtain: Design an auxiliary matrix based on the filtered state variables. , as well as : in, The electrical parameter to be estimated is the parameter estimation error.

2. The distributed power source harmonic compensation control method as described in claim 1, characterized in that, The steps for establishing a mathematical model of an LCL-type inverter connected to distributed power sources based on Kirchhoff's theorem include: The grid-connected state equations for an LCL inverter connected to distributed power sources are established based on Kirchhoff's theorem. By analyzing the three phases of the LCL inverter separately and defining state variables, the grid-connected state equations are used to obtain the state-space expression of the LCL inverter. The state-space expression is simplified to the form of a regression matrix multiplied by an unknown parameter matrix to obtain the target mathematical model of the LCL inverter.

3. The distributed power source harmonic compensation control method as described in claim 1, characterized in that, The step of determining the virtual control law and parameter estimate of the LCL inverter based on the current signal and the parameter estimation error includes: The Lyapunov function is used to determine the first-order virtual control law and the first-order adaptive law, the second-order virtual control law and the second-order adaptive law, and the third-order virtual control law and the third-order adaptive law of the LCL inverter based on the current signal and the parameter estimation error. The first-order parameter estimate of the LCL inverter is determined based on the first-order adaptive rate. The second-order parameter estimate of the LCL inverter is determined based on the second-order adaptive rate. The estimated values ​​of the third-order parameters of the LCL inverter are determined based on the third-order adaptive rate.

4. The distributed power source harmonic compensation control method as described in claim 3, characterized in that, The step of adjusting the control parameters of the LCL inverter based on the virtual control law and the parameter estimate includes: Track the differential signals of the first-order virtual control law and the second-order virtual control law; The actual control rate of the LCL inverter is obtained based on the differential signal. The control parameters of the LCL inverter are adjusted based on the actual control rate and the parameter estimate.

5. The distributed power source harmonic compensation control method as described in claim 4, characterized in that, Before the step of tracking the differential signals of the first-order virtual control law and the second-order virtual control law, the method further includes: A preset high-order sliding mode differentiator is constructed. The preset high-order sliding mode differentiator is used to track the first derivative of the virtual control law. The preset high-order sliding mode differentiator includes a first high-order sliding mode differentiator and a second high-order sliding mode differentiator. The first high-order sliding mode differentiator has an order of 3, and the second high-order sliding mode differentiator has an order of 2.

6. A distributed power source harmonic compensation control device, applied to the distributed power source harmonic compensation control method as described in claim 1, characterized in that, The device includes: The model building module is used to establish a mathematical model of an LCL inverter connected to a distributed power source based on Kirchhoff's theorem, and to obtain the current signal of the LCL inverter. A filtering module is used to filter the current signal and obtain the parameter estimation error of the LCL inverter. The calculation module is used to determine the virtual control law and parameter estimate of the LCL inverter based on the current signal and the parameter estimation error; The adjustment module is used to adjust the control parameters of the LCL inverter according to the virtual control law and the parameter estimate, so as to complete the harmonic compensation of the distributed power source.

7. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, they perform the steps of the distributed power supply harmonic compensation control method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the steps of the distributed power supply harmonic compensation control method as described in any one of claims 1 to 5.

Images