Prediction control method of LCL filtering type three-phase photovoltaic grid-connected inverter system

Abstract

The invention discloses a prediction control method of an LCL filtering type three-phase photovoltaic grid-connected inverter system, and belongs to the field of power electronic control. Comprising the following steps: establishing a continuous domain state equation of an LCL filtering type three-phase photovoltaic grid-connected inverter system by using sampling information, and calculating an inductive current and a capacitor voltage given value through a steady-state value to establish a discrete prediction model; calculating a prediction control instruction integrated with resonance suppression by combining a resonance component obtained by subtracting a capacitor voltage prediction value from a capacitor voltage given value; determining an optimal vector; constructing a performance function of prediction control instruction synthesis tracking errors, and calculating optimal vector action time capable of minimizing the performance function; symmetrical four-section type control pulse signals are designed to act on an inverter switching tube for predictive control. According to the method, the resonant oscillation of the LCL filtering type three-phase photovoltaic grid-connected inverter system can be effectively suppressed, the fixed switching frequency is realized, and the stability and the steady-state performance are improved.

Description

Technical Field

[0001] The invention relates to a prediction control method for an LCL filtering type three-phase photovoltaic grid-connected inverter system, and belongs to the field of power electronics and electric power transmission. Background Art

[0002] With the increasing problems of energy exhaustion and environmental pollution, new energy power generation systems have ushered in rapid development, especially the installed capacity of distributed photovoltaics has increased year by year. Photovoltaic new energy transmits the generated electricity to the power grid through grid-connected operation. Distributed photovoltaic grid-connected systems are mostly installed on carriers such as building roofs. They are small in scale, simple and flexible, and have low line losses. As a key interface device between distributed photovoltaic power sources and the power grid, the performance of photovoltaic grid-connected inverters will directly affect the quality of grid connection and the stability of the power grid. Since photovoltaic grid-connected inverters are composed of power electronic devices, the switching frequency of photovoltaic grid-connected inverters is high when they work normally, so high-frequency harmonics will be injected into the power grid, affecting the power quality and operation stability of the power grid. In order to obtain satisfactory high-order harmonic suppression capabilities, LCL filters are usually installed between photovoltaic grid-connected inverters and the power grid. However, the introduction of LCL filters will not only increase the control order, but also cause resonance problems of grid-connected currents, which seriously threaten the stability and reliability of photovoltaic grid-connected systems.

[0003] In recent years, the model predictive control method has attracted widespread attention in the field of LCL filter type three-phase photovoltaic grid-connected inverter system control due to its simple structure, excellent dynamic performance and optimal control characteristics. At present, in order to suppress the resonance problem of LCL, the predictive control of the existing photovoltaic grid-connected inverter is a multi-objective finite set predictive model control, which requires the inverter current, capacitor voltage and grid-connected current to be predicted at the same time, and the optimal vector can be obtained by traversing the objective function multiple times. Therefore, there are many control parameters (2), difficult parameter setting (experience trial and error) and large amount of calculation (multiple traversal calculations), which aggravates the complexity of the control method. At the same time, the existing predictive control method only acts on a single vector in one control cycle, resulting in large steady-state harmonics and ripples and non-fixed switching frequency in the LCL filter type three-phase photovoltaic grid-connected inverter system. This is not only not conducive to the design of the LCL filter, but also greatly hinders the application of predictive control in the field of photovoltaic grid-connected inverters. Summary of the invention

[0004] In view of the limitations of the prior art, a predictive control method for an LCL filter type three-phase photovoltaic grid-connected inverter system is provided. This method extracts the resonant component by subtracting the capacitor voltage given value from the capacitor voltage predicted value, and feeds it back to the photovoltaic grid-connected inverter control instruction to obtain the photovoltaic grid-connected inverter control instruction with integrated resonance suppression, which effectively solves the resonance problem of the LCL filter type three-phase photovoltaic grid-connected inverter system, is simple to implement and enhances the stability of the LCL filter type three-phase photovoltaic grid-connected inverter system; this method has only the damping coefficient K r There is only one parameter to be designed, and the optimization process of cyclic traversal is eliminated, so the workload and complexity of parameter setting are greatly reduced; the symmetrical 4-segment pulse generation of this method does not use zero vector, so the common-mode voltage and leakage current of the LCL filter type three-phase photovoltaic grid-connected inverter system can be reduced; this method realizes a fixed switching frequency, which is beneficial to the parameter design of the LCL filter.

[0005] To achieve the above technical objectives, the present invention provides a predictive control method for an LCL filter type three-phase photovoltaic grid-connected inverter system, comprising the following steps:

[0006] Step 1: By sampling the inductor current, capacitor voltage, grid current and grid voltage of the LCL filter type three-phase photovoltaic grid-connected inverter system, the continuous domain state equation of the LCL filter type three-phase photovoltaic grid-connected inverter system in the dq coordinate system is established, and the inductor current given value i is calculated through the steady-state value of the state variable fd,k * 、i fq,k * and capacitor voltage given value u cd,k * 、u cq,k * ;

[0007] Step 2: Based on the continuous time domain state equation of the LCL filter type three-phase photovoltaic grid-connected inverter system, a discrete prediction model of the LCL filter type three-phase photovoltaic grid-connected inverter system is established using the forward Euler method;

[0008] Step 3: According to the given values ​​of inductor current, capacitor voltage and the discrete prediction model of LCL filter type three-phase photovoltaic grid-connected inverter system, the basic prediction control instruction v is calculated based on the principle that the predicted value of inductor current tracks the given value of inductor current within one sampling period. d,k * and v q,k * , using the resonance component obtained by the difference between the capacitor voltage prediction value and the capacitor voltage set value, calculate the prediction control command v for integrated resonance suppression rd,k * and v rq,k *, and integrate the predictive control command v with resonance suppression rd,k * and v rq,k * Perform Park inverse transformation to obtain the predictive control command v for integrated resonance suppression in the αβ coordinate system rα,k * and v rβ,k * ;

[0009] Step 4: Obtain the predicted control command v for integrated resonance suppression rα,k * and v rβ,k * The spatial position angle γ is used to determine the predictive control command v that can optimally synthesize integrated resonance suppression. rα,k * and v rβ,k * The two optimal vectors v p,1 and v p,2 ;

[0010] Step 5: With the help of two optimal vectors and two optimal vector action times that can optimally synthesize the integrated resonance suppression predictive control command, a performance function of the synthetic tracking error of the predictive control command based on integrated resonance suppression is constructed, and the optimal vector action time T that can minimize the performance function is calculated using the Lagrange multiplier method. i ;

[0011] Step 6: Design a symmetrical 4-segment control pulse signal generation strategy S and apply the strategy S to the inverter switch tube to achieve predictive control of the LCL filter type three-phase photovoltaic grid-connected inverter system.

[0012] Further, the step 1 specifically includes: establishing a continuous time domain state equation of the sampling LCL filter type three-phase photovoltaic grid-connected inverter system in the dq coordinate system as follows:

[0013]

[0014] In the formula, i fd 、i fq represents the dq axis inductor current, u cd 、u cq represents the dq axis capacitor voltage, i gd 、i gq Indicates the dq axis grid-connected current, v d 、v q Indicates the dq-axis inverter output voltage, u gd 、u gq Indicates the dq axis grid voltage; L f and R fRepresents the filter inductance and inverter side parasitic resistance, L g and R g represents the grid-side filter inductance and grid-side parasitic resistance, C is the filter capacitor, ω e is the grid voltage fundamental angular frequency;

[0015] Considering that the steady-state value of the state variable of the LCL filter type three-phase photovoltaic grid-connected inverter system no longer changes and the steady-state value of the grid-connected current is equal to the grid-connected current reference value: i gd =i gd,k * ,i gq =i gq,k * , the capacitor voltage given value u of the LCL filter type three-phase photovoltaic grid-connected inverter system can be calculated cd,k * 、u cq,k * With the given value of inductor current i fd,k * 、i fq,k * for:

[0016]

[0017] In the formula, i gd,k * and i gq,k * is the given value of the dq-axis grid-connected current.

[0018] Further, the step 2 specifically includes: assuming that the sampling period of the LCL filter type three-phase photovoltaic grid-connected inverter system is T s , the forward Euler method is used to discretize the continuous time domain state equation (1), and the prediction model of the inductor current and capacitor voltage of the LCL filter type three-phase photovoltaic grid-connected inverter system is established as follows:

[0019]

[0020] Wherein, the subscripts “k” and “k+1” represent the current k-th sampling moment and the predicted value of the k+1th step in the future, respectively.

[0021] Further, the step 3 specifically includes: based on the principle of tracking the inductor current reference value within a sampling period based on the inductor current prediction value, that is, according to the inductor current and capacitor voltage given values ​​of the LCL filter type three-phase photovoltaic grid-connected inverter system and the inductor current and capacitor voltage prediction model, let i fd,k+1 =i fd,k * ,i fq,k+1 =i fq,k *, calculate the basic predictive control command v of the LCL filter type three-phase photovoltaic grid-connected inverter system d,k * and v q,k * for:

[0022]

[0023] In order to suppress the de-resonant oscillation and improve the stability of the LCL filter type three-phase photovoltaic grid-connected inverter system, considering that the capacitor voltage prediction value contains both fundamental and resonant components, while the reference value only contains the fundamental component, the resonant component can be obtained by subtracting the capacitor voltage prediction value from the capacitor voltage given value, and the resonant component is taken from the basic prediction control instruction v d,k * and v q,k * Subtract from the original value to obtain the predictive control command v with integrated resonance suppression rd,k * and v rq,k * :

[0024]

[0025] In the formula, K r >0 is the adjustable resonance suppression gain, obtained through simulation or experimental trial;

[0026] Finally, through the Park inverse transform The predictive control command v of integrated resonance suppression in the αβ coordinate system is obtained rα,k * and v rβ,k * :

[0027]

[0028] Further, the step 4 specifically includes: obtaining the prediction control instruction v of the integrated resonance suppression by the inverse tangent function rα,k * and v rβ,k * The spatial position angle is as follows:

[0029]

[0030] According to the spatial sector where γ is located, the predictive control command v that can optimally synthesize integrated resonance suppression is determined rα,k * and v rβ,k * The two optimal vectors v p,1 =[v pα,1 v pβ,1 ] and vp,2 =[v pα,2 v pβ,2 ].

[0031] Further, the step 5 specifically includes: based on the two optimal vectors that can optimally synthesize the integrated resonance suppression prediction control instruction determined in step 4, combining the action time of the two optimal vectors to construct a performance function of the integrated resonance suppression prediction control instruction synthesis tracking error as follows:

[0032]

[0033] Where T1 and T2 are the action times of the two optimal vectors, respectively, satisfying T1+T2=T s Constraints of and They are the tracking errors between the two optimal vectors and the predictive control command with integrated resonance suppression in the αβ coordinate system.

[0034] Furthermore, in order to solve T1+T2=T s The action time of the optimal vector that can minimize the performance function G under the equality constraint is first constructed using the Lagrange multiplier method as follows:

[0035] f(T1,T2,λ)=G+λ(T1+T2-T s ) (9)

[0036] Where λ is the Lagrangian operator;

[0037] Secondly, let the partial derivatives of the Lagrangian function f with respect to the action time of the two optimal vectors be equal to 0, and we get:

[0038]

[0039] Combine equation (10) with the equality constraint T1+T2=T s Combined, we get the expression of the Lagrangian operator λ:

[0040]

[0041] Derived the action time T of the two optimal vectors i (i=1, 2) is:

[0042]

[0043] Furthermore, the step 6 specifically includes: in order to achieve a fixed switching frequency and a low common mode voltage, the following symmetrical 4-segment pulse mode is designed to generate a control pulse signal S:

[0044]

[0045] Finally, the pulse signal S is applied to the switch tube of the inverter to realize the predictive control of the LCL filter type three-phase photovoltaic grid-connected inverter system.

[0046] A computer device comprising: a processor, a memory and a network interface;

[0047] The processor is connected to the memory and the network interface, wherein the network interface is used to provide a network communication function, the memory is used to store program code, and the processor is used to call the program code to execute the predictive control method of the LCL filter-type three-phase photovoltaic grid-connected inverter system according to any one of claims 1-8.

[0048] A computer-readable storage medium having a computer program stored therein, wherein the computer program is suitable for being loaded by a processor and executing the predictive control method for an LCL filter-type three-phase photovoltaic grid-connected inverter system as described in any one of claims 1 to 8.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] 1. The method provided by the present invention adopts the capacitor voltage predicted value minus the capacitor voltage set value to extract the resonant component, which effectively solves the resonance problem of the LCL filter type three-phase photovoltaic grid-connected inverter system and enhances the stability of the LCL filter type three-phase photovoltaic grid-connected inverter system.

[0051] 2. The method provided by the present invention only includes one damping coefficient K r The design parameters do not require a cyclic optimization process, which greatly reduces the workload of parameter setting and the complexity of control method implementation.

[0052] 3. The optimal vector action time calculation and pulse signal generation method used in the method provided by the present invention can effectively improve the steady-state performance of the LCL filter-type three-phase photovoltaic grid-connected inverter system, reduce the common-mode voltage / leakage current, and achieve a fixed switching frequency, which is beneficial to the design of the LCL filter. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a schematic block diagram of a predictive control method of an LCL filter type three-phase photovoltaic grid-connected inverter system of the present invention;

[0054] Figure 2 is a basic voltage space vector diagram in an embodiment of the present invention;

[0055] Figure 3 A transient waveform diagram of the grid voltage and grid-connected current and a schematic diagram of the grid-connected current harmonic spectrum in an embodiment of the present invention;

[0056] Figure 4It is a schematic diagram of transient waveforms of grid voltage and grid-connected current and harmonic spectrum of grid-connected current in a traditional embodiment. DETAILED DESCRIPTION

[0057] The following drawings further illustrate the embodiments of the present invention:

[0058] like Figure 1 As shown, the present invention provides an LCL filter type three-phase photovoltaic grid-connected inverter system using a predictive control method of the LCL filter type three-phase photovoltaic grid-connected inverter system, wherein a DC bus voltage source is converted into an AC voltage square wave signal through a three-phase voltage source inverter, and then connected to the grid through an output LCL filter; and three-phase inductor current, three-phase capacitor voltage, three-phase grid-connected current and three-phase grid voltage are sampled in sequence.

[0059] Figure 1 In, V dc Indicates DC bus voltage; L f and R f Represents the filter inductance and parasitic resistance at the inverter output side, L g and R g represents the grid-side filter inductance and parasitic resistance, and C represents the filter capacitor. f,abc Represents the three-phase filter inductor current; u c,abc Represents the three-phase filter capacitor voltage; i g,abc Indicates the grid-connected current; u g,abc Indicates the grid voltage; i g,k * is the given value of grid-connected current; i g,k 、u g,k 、u c,k and i f,k They represent the grid-connected current, grid voltage, capacitor voltage and inductor current in the dq coordinate system at time k respectively; the sampled grid voltage is sent to the phase-locked loop to obtain the grid voltage phase θ; S represents the switching state of the inverter upper arm switch tube.

[0060] A predictive control method for an LCL filter type three-phase photovoltaic grid-connected inverter system comprises the following steps:

[0061] Step 1: Establish the continuous time domain state equation of the system in the dq coordinate system as follows:

[0062]

[0063] In the formula, i fd 、i fq represents the dq axis inductor current, u cd 、u cq represents the dq axis capacitor voltage, i gd 、i gq Indicates the dq axis grid-connected current, vd 、v q Indicates the dq-axis inverter output voltage, u gd 、u gq Indicates the dq axis grid voltage; L f and R f Represents the filter inductance and inverter side parasitic resistance, L g and R g is the grid-side filter inductance and grid-side parasitic resistance, C is the filter capacitor, ω e is the fundamental angular frequency of the grid voltage.

[0064] Considering that the steady-state value of the state variable of the LCL filter type three-phase photovoltaic grid-connected inverter system no longer changes, and the steady-state value of the grid-connected current is equal to the grid-connected current reference value: i gd =i gd,k * ,i gq =i gq,k * , the capacitor voltage given value u can be calculated cd,k * 、u cq,k * With the given value of inductor current i fd,k * 、i fq,k * for:

[0065]

[0066] In the formula, i gd,k * and i gq,k * is the given value of the dq-axis grid-connected current.

[0067] Step 2: In order to realize the predictive control of the inverter side current reference tracking, the sampling period of the LCL filter type three-phase photovoltaic grid-connected inverter system is set to T s , the continuous domain state equation in step 1 is discretized using the forward Euler method, and the prediction model of the inductor current and capacitor voltage of the LCL filter type three-phase photovoltaic grid-connected inverter system can be established as follows:

[0068]

[0069] Wherein, the subscripts “k” and “k+1” represent the current k-th sampling moment and the predicted value of the k+1th step in the future, respectively.

[0070] Step 3: Based on the principle that the predicted value of the inductor current tracks the reference value of the inductor current within a sampling period, that is, according to the given values ​​of the inductor current and capacitor voltage and the prediction model of the inductor current and capacitor voltage, let ifd,k+1 =i fd,k * ,i fq,k+1 =i fq,k * , the basic predictive control instruction v of the LCL filter type three-phase photovoltaic grid-connected inverter system can be calculated d,k * and v q,k * :

[0071]

[0072] Then, in order to suppress the resonant oscillation and improve the stability of the LCL filter type three-phase photovoltaic grid-connected inverter system, considering that the capacitor voltage prediction value contains both fundamental and resonant components, while the reference value only contains the fundamental component, the resonant component can be obtained by subtracting the capacitor voltage prediction value from the capacitor voltage given value, and the resonant component is taken from the basic prediction control instruction v d,k * and v q,k * Subtracting from the above, we can get the predictive control command v with integrated resonance suppression. rd,k * and v rq,k * :

[0073]

[0074] In the formula, K r >0 is an adjustable resonance suppression gain, which can be obtained through simulation or experimental trial and error.

[0075] Finally, through the Park inverse transform The predictive control command v for integrated resonance suppression in the αβ coordinate system can be obtained rα,k * and v rβ,k * :

[0076]

[0077] Step 4: Obtain the predicted control command v for integrated resonance suppression using the inverse tangent function rα,k * and v rβ,k * The spatial position angle is as follows:

[0078]

[0079] like Figure 2 As shown, v αβ,1 to v αβ,6is the basic voltage vector, and according to the spatial sector l where γ is located, the predictive control command v that can optimally synthesize integrated resonance suppression is determined rα,k * and v rβ,k * The two optimal vectors v p,1 =[v pα,1 v pβ,1 ] and v p,2 =[v pα,2 v pβ,2 ].

[0080] Step 5: Based on the two optimal vectors that can optimally synthesize the integrated resonance suppression prediction control command determined in step 4, the performance function of the integrated resonance suppression prediction control command synthesis tracking error is constructed by combining the action time of the two optimal vectors as follows:

[0081] G=(T1e α,1 ) 2 +(T1e β,1 ) 2 +(T2e α,2 ) 2 +(T2e β,2 ) 2

[0082] Where T1 and T2 are the action times of the two optimal vectors, respectively, satisfying T1+T2=T s Constraints of and They are the tracking errors between the two optimal vectors and the predictive control command with integrated resonance suppression in the αβ coordinate system.

[0083] In order to solve T1+T2=T s The action time of the optimal vector that can minimize the performance function G under the equality constraint is first constructed using the Lagrange multiplier method as follows:

[0084] f(T1,T2,λ)=G+λ(T1+T2-T s )

[0085] Where λ is the Lagrangian operator.

[0086] Secondly, let the partial derivatives of the Lagrangian function f with respect to the action time of the two optimal vectors be equal to 0, and we can get:

[0087]

[0088] Combine the above equation with the equality constraint T1+T2=T s Combined, the expression of the Lagrangian operator λ can be obtained as:

[0089]

[0090] The action time T of the two optimal vectors can be derived i (i=1, 2) is:

[0091]

[0092] Step 6: To achieve a fixed switching frequency and low common-mode voltage, design the following symmetrical 4-segment pulse pattern to generate the control pulse signal S:

[0093]

[0094] Finally, the pulse signal S is applied to the switch tube of the inverter to realize the predictive control of the LCL filter type three-phase photovoltaic grid-connected inverter system.

[0095] Each vector represents the switching state of the inverter upper bridge arm switch tube. Figure 2 As shown in the figure (1 means on, 0 means off), the switching state of the lower bridge arm switch tube is opposite to that of the upper bridge arm. Finally, the pulse signal is applied to the inverter switch tube to realize the predictive control of the LCL photovoltaic grid-connected inverter.

[0096] In order to verify the predictive control method of a LCL filter type three-phase photovoltaic grid-connected inverter system provided by the present invention, the method provided by the present invention is applied to the LCL filter type three-phase photovoltaic grid-connected inverter system, and the parameters are given in Table 1.

[0097] Table 1

[0098]

[0099] Figure 3 and Figure 4 They are respectively the transient waveform diagrams of the grid voltage and grid current and the schematic diagram of the grid current harmonic spectrum under the method of the present invention and the traditional multi-objective finite set prediction model control method. The given value of the grid current suddenly changes from 10A to 30A at 0.1s and suddenly changes to 20A at 0.15s.

[0100] Grid voltage u under two control methods g and grid current i gBoth can quickly follow the given reference when the grid-connected current reference amplitude suddenly changes, and both can complete the smooth transition of the grid-connected current without resonance, so the dynamic performance of the two control methods is equivalent. Nevertheless, compared with the method of the present invention, the total harmonic distortion rate of the grid-connected current under the traditional control method is larger. On the contrary, the proposed control method has better steady-state performance, and it can be seen from the harmonic spectrum that the method of the present invention achieves a fixed switching frequency of 10kHz. Therefore, the method provided by the present invention can effectively improve the steady-state performance and operating stability of the LCL filter-type three-phase photovoltaic grid-connected inverter system.

Claims

1. A predictive control method for an LCL filter type three-phase photovoltaic grid-connected inverter system, characterized in that: The steps include: Step 1: By sampling the inductor current, capacitor voltage, grid current and grid voltage of the LCL filter type three-phase photovoltaic grid-connected inverter system, the continuous domain state equation of the LCL filter type three-phase photovoltaic grid-connected inverter system in the dq coordinate system is established, and the inductor current given value i is calculated through the steady-state value of the state variable fd,k * 、i fq,k * and capacitor voltage given value u cd,k * 、u cq,k * ; Step 2: Based on the continuous time domain state equation of the LCL filter type three-phase photovoltaic grid-connected inverter system, a discrete prediction model of the LCL filter type three-phase photovoltaic grid-connected inverter system is established using the forward Euler method; Step 3: According to the given values ​​of inductor current, capacitor voltage and the discrete prediction model of LCL filter type three-phase photovoltaic grid-connected inverter system, the basic prediction control instruction v is calculated based on the principle that the predicted value of inductor current tracks the given value of inductor current within one sampling period. d,k * and v q,k * The predicted control command v of integrated resonance suppression is calculated by using the capacitor voltage resonance component obtained by making a difference between the capacitor voltage prediction value and the capacitor voltage given value. rd,k * and v rq,k * , and integrate the predictive control command v with resonance suppression rd,k * and v rq,k * Perform Park inverse transformation to obtain the predictive control command v for integrated resonance suppression in the αβ coordinate system rα,k * and v rβ,k * ; Step 4: Obtain the predicted control command v for integrated resonance suppression rα,k * and v rβ,k * The spatial position angle γ is used to determine the predictive control command v that can optimally synthesize integrated resonance suppression. rα,k * and v rβ,k * The two optimal vectors v p,1 and v p,2 ; Step 5: With the help of two optimal vectors and two optimal vector action times that can optimally synthesize the predictive control command with integrated resonance suppression, a performance function of the synthetic tracking error of the predictive control command based on integrated resonance suppression is constructed, and the optimal vector action time T that can minimize the performance function is calculated using the Lagrange multiplier method. i ; Step 6: Design a symmetrical 4-segment control pulse signal generation strategy S and apply the strategy S to the inverter switch tube to achieve predictive control of the LCL filter type three-phase photovoltaic grid-connected inverter system.

2. The predictive control method of a LCL filter type three-phase photovoltaic grid-connected inverter system according to claim 1, characterized in that: The step 1 specifically includes: The continuous time domain state equation of the sampling LCL filter type three-phase photovoltaic grid-connected inverter system in the dq coordinate system is established as follows: In the formula, the state variable i fd 、i fq represents the dq axis inductor current, the state variable u cd 、u cq represents the dq axis capacitor voltage, the state variable i gd 、i gq Indicates the dq axis grid-connected current; v d 、v q Indicates the dq-axis inverter output voltage, u gd 、u gq Indicates the dq axis grid voltage; L f and R f Represents the filter inductance and inverter side parasitic resistance, L g and R g represents the grid-side filter inductance and grid-side parasitic resistance, C is the filter capacitor, ω e is the grid voltage fundamental angular frequency; Considering that the steady-state value of the state variable of the LCL filter type three-phase photovoltaic grid-connected inverter system no longer changes, and the steady-state value of the grid-connected current is equal to the grid-connected current reference value: i gd =i gd,k * ,i gq =i gq,k * , the capacitor voltage given value u of the LCL filter type three-phase photovoltaic grid-connected inverter system can be calculated cd,k * 、u cq,k * With the given value of inductor current i fd,k * 、i fq,k * They are: In the formula, i gd,k * and i gq,k * is the given value of the dq-axis grid-connected current.

3. The predictive control method of a LCL filter type three-phase photovoltaic grid-connected inverter system according to claim 1, characterized in that: The step 2 specifically includes: Assume that the sampling period of the LCL filter type three-phase photovoltaic grid-connected inverter system is T s , the forward Euler method is used to discretize the continuous time domain state equation (1), and the prediction model of the inductor current and capacitor voltage of the LCL filter type three-phase photovoltaic grid-connected inverter system is established as follows: Wherein, the subscripts "k" and "k+1" represent the current k-th sampling moment and the future k+1-th step prediction value, respectively.

4. The predictive control method of a LCL filter type three-phase photovoltaic grid-connected inverter system according to claim 3, characterized in that: The step 3 specifically includes: Based on the principle that the predicted value of the inductor current tracks the reference value of the inductor current within a sampling period, that is, according to the given values ​​of the inductor current and capacitor voltage and the prediction model of the inductor current and capacitor voltage, let i fd,k+1 =i fd,k * ,i fq,k+1 =i fq,k * , the basic predictive control instruction v can be calculated d,k * and v q,k * for: In order to suppress resonant oscillation and improve the stability of the LCL filter type three-phase photovoltaic grid-connected inverter system, considering that the capacitor voltage prediction value contains both fundamental and resonant components, while the reference value only contains the fundamental component, the resonant component can be obtained by subtracting the capacitor voltage prediction value from the capacitor voltage given value, and the resonant component is taken from the basic prediction control instruction v d,k * and v q,k * Subtract from the original value to get the predictive control command v with integrated resonance suppression rd,k * and v rq,k * : In the formula, K r >0 is an adjustable resonance suppression gain, which is obtained through simulation or experimental trial and error. Finally, through the Park inverse transform The predictive control command v of integrated resonance suppression in the αβ coordinate system is obtained rα,k * and v rβ,k * :

5. The predictive control method of a LCL filter type three-phase photovoltaic grid-connected inverter system according to claim 4, characterized in that: The step 4 specifically includes: According to the prediction control command v obtained by the inverse tangent function for integrated resonance suppression rα,k * and v rβ,k * The spatial position angle is as follows: According to the spatial sector where γ is located, the predictive control command v that can optimally synthesize integrated resonance suppression is determined rα,k * and v rβ,k * The two optimal vectors v p,1 =[v pα,1 v pβ,1 ] and v p,2 =[v pα,2 v pβ,2 ].

6. The predictive control method of a LCL filter type three-phase photovoltaic grid-connected inverter system according to claim 5, characterized in that: The step 5 specifically includes: Based on the two optimal vectors that can optimally synthesize the integrated resonance suppression prediction control command determined in step 4, the performance function of the integrated resonance suppression prediction control command synthesis tracking error is constructed by combining the action time of the two optimal vectors as follows: G=(T1e α,1 ) 2 +(T1e β,1 ) 2 +(T2e α,2 ) 2 +(T2e β,2 ) 2 (8) Where T1 and T2 are the action times of the two optimal vectors, respectively, satisfying T1+T2=T s Constraints of and They are the tracking errors between the two optimal vectors and the integrated resonance suppression predictive control instructions in the αβ coordinate system.

7. The predictive control method of a LCL filter type three-phase photovoltaic grid-connected inverter system according to claim 6, characterized in that: In order to solve T1+T2=T s The action time of the optimal vector that can minimize the performance function G under the equality constraint is first constructed using the Lagrange multiplier method as follows: f(T1,T2,λ)=G+λ(T1+T2-T s ) (9) Where λ is the Lagrangian operator; Secondly, let the partial derivatives of the Lagrangian function f with respect to the action time of the two optimal vectors be equal to 0, and we get: Combine equation (10) with the equality constraint T1+T2=T s Combined, we get the expression of the Lagrangian operator λ: Derived the action time T of the two optimal vectors i (i=1, 2) is:

8. The predictive control method of a LCL filter type three-phase photovoltaic grid-connected inverter system according to claim 7, characterized in that: The step 6 specifically includes: In order to achieve a fixed switching frequency and low common-mode voltage, the following symmetrical 4-segment pulse pattern is designed to generate the control pulse signal S: Finally, the pulse signal S is applied to the switch tube of the inverter to realize the predictive control of the LCL filter type three-phase photovoltaic grid-connected inverter system.

9. A computer device, characterized in that: include: Processor, memory, and network interface; The processor is connected to the memory and the network interface, wherein the network interface is used to provide a network communication function, the memory is used to store program code, and the processor is used to call the program code to execute the predictive control method of the LCL filter-type three-phase photovoltaic grid-connected inverter system according to any one of claims 1-8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which is suitable for being loaded by a processor and executing the predictive control method of the LCL filter-type three-phase photovoltaic grid-connected inverter system according to any one of claims 1 to 8.

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