LCL type three-phase grid-connected inverter double-closed-loop control method based on variable universe fuzzy PI control and grid-connected inverter system

Abstract

The invention discloses an LCL type three-phase grid-connected inverter double-closed-loop control method based on variable universe fuzzy PI control and a grid-connected inverter system, and relates to the field of automatic control. D-axis and q-axis actual currents of the current control inner ring and actual power and actual voltage of the power and voltage control outer ring are calculated according to the inverter output current and the grid-connected point voltage; inputting the difference value between the actual power and the reference power into a power control outer ring, and obtaining a d-axis reference current by adopting variable universe fuzzy PI control; the difference value of the actual voltage and the reference voltage is input into a voltage control outer ring, and q-axis reference current is obtained through a voltage control outer ring PI controller; the difference values of the d-axis and q-axis actual currents and the d-axis and q-axis reference currents are input into a current control inner ring, and d-axis and q-axis reference voltages are obtained; the d-axis reference voltage and the q-axis reference voltage are subjected to inverse Park conversion and sine pulse width modulation to generate PWM signals, switching of the LCL type three-phase grid-connected inverter is controlled, and the dynamic response performance and the steady-state control precision of the system can be improved.

Description

Technical Field

[0001] The present application relates to the field of automatic control technology, and in particular to a dual closed-loop control method for an LCL-type three-phase grid-connected inverter based on variable universe fuzzy PI control and a grid-connected inverter system. Background Art

[0002] With the development of renewable energy power generation technology, wind power generation, photovoltaic power generation and other renewable energy power generation methods have been widely used around the world. These power generation methods usually require the use of grid-connected inverters to convert direct current into alternating current so that they can be connected to the power grid. As the core equipment in the renewable energy power generation system, the quality of the control method of the grid-connected inverter directly affects the power quality, system stability and power generation efficiency.

[0003] In the design of grid-connected inverters, LCL filters are widely used to filter high-frequency harmonics, reduce electromagnetic interference, and improve the quality of grid-connected power. However, due to the complexity of the LCL filter structure, the design of its control strategy also faces many challenges. The traditional proportional integral (PI) control strategy is difficult to achieve good dynamic response and steady-state performance under actual working conditions due to fixed parameters. Therefore, how to optimize the parameters of the PI controller so that it can adapt to the changing operating environment has become a hot issue in current research.

[0004] Fuzzy control has gradually become an effective method to improve the performance of PI controllers because it does not rely on accurate mathematical models and can handle nonlinearity and uncertainty. However, traditional fuzzy control strategies have problems such as low control accuracy and slow response speed when dealing with large-scale operating conditions. Summary of the invention

[0005] In response to the problems pointed out in the background technology, the purpose of this application is to provide a dual closed-loop control method and a grid-connected inverter system for an LCL type three-phase grid-connected inverter based on variable domain fuzzy PI control, so as to improve the dynamic response performance and steady-state control accuracy of the system.

[0006] To achieve the above objectives, this application provides the following solutions.

[0007] In a first aspect, the present application provides a dual closed-loop control method for an LCL-type three-phase grid-connected inverter based on variable universe fuzzy PI control, comprising:

[0008] Collect the inverter output current and grid connection point voltage of LCL type three-phase grid-connected inverter;

[0009] Calculate the actual current of the d-axis and q-axis of the inner loop of current control and the actual power and actual voltage of the outer loop of power and voltage control according to the inverter output current and the grid connection point voltage;

[0010] The difference between the actual power and the reference power is input into the outer loop of power control, and the d-axis reference current is obtained by using variable universe fuzzy PI control;

[0011] The difference between the actual voltage and the reference voltage is input into the voltage control outer loop, and the q-axis reference current is obtained through the voltage control outer loop PI controller;

[0012] The difference between the actual current of the d-axis and q-axis and the reference current of the d-axis and q-axis is input into the current control inner loop to obtain the reference voltage of the d-axis and q-axis;

[0013] The d-axis and q-axis reference voltages are transformed by inverse Park transformation and sinusoidal pulse width modulation to generate PWM signals to control the switches of the LCL type three-phase grid-connected inverter.

[0014] Optionally, the calculating of the actual d-axis and q-axis currents of the inner current control loop and the actual power and actual voltage of the outer power and voltage control loops according to the inverter output current and the grid connection point voltage specifically includes:

[0015] The inverter output current i cabc The actual current i of the d-axis of the current control inner loop is obtained by Park transformation cd and the actual q-axis current i cq ;

[0016] The grid voltage v oabc The d-axis voltage component v of the grid connection point voltage is obtained by Park transformation od and the q-axis voltage component v oq ;

[0017] Using the formula P = 1.5 (v od i cd +v oq i cq ) Calculate the actual power P of the power control outer loop;

[0018] Using formula Calculate the actual voltage V of the voltage control outer loop.

[0019] Optionally, before inputting the difference between the actual power and the reference power into the power control outer loop and adopting the variable universe fuzzy PI control to obtain the d-axis reference current, the method further includes:

[0020] Establish the linear state space equation of LCL type three-phase grid-connected inverter;

[0021] Determine the PI parameter stability threshold of the power control outer loop under different output powers according to the characteristic root distribution of the linear state space equation; the output power is the actual power P;

[0022] According to the PI parameter stability threshold of the power control outer loop under different output powers, K in the variable domain fuzzy PI control p and K i The correspondence table between the domain and the output power P is used as the variable domain fuzzy PI control table.

[0023] Optionally, in the variable domain fuzzy PI control table, when the actual power P is less than 0.4, K p The domain of K is

[16] , i The domain of K is [0.54]; when the actual power P is between 0.4 and 0.7, p The domain of discourse is [13.5], K i The domain of K is [0.52]; when the actual power P is greater than 0.7, p The domain of K is [1.53], i The domain of is [0.51.5].

[0024] Optionally, before inputting the difference between the actual power and the reference power into the power control outer loop and adopting the variable universe fuzzy PI control to obtain the d-axis reference current, the method further includes:

[0025] The actual power P of the LCL three-phase grid-connected inverter is compared with the reference power P ref The difference E and the difference change rate EC are taken as input, and the PI parameters of the power control outer loop are taken as output. According to the characteristics of the grid-connected inverter system and the PI adjustment law, a fuzzy control rule table is formulated.

[0026] Optionally, the step of inputting the difference between the actual power and the reference power into the power control outer loop and adopting variable universe fuzzy PI control to obtain the d-axis reference current specifically includes:

[0027] Firstly, the difference E between the actual power and the reference power and the difference change rate EC are divided into 7 levels {NB, NM, NS, ZO, PS, PM, PB}, corresponding to large negative, medium negative, small negative, zero, small positive, medium positive, and large positive respectively;

[0028] Then, the levels of the difference value E and the difference change rate EC are input into the fuzzy rule controller, and fuzzy reasoning is performed according to the formulated fuzzy control rule table to obtain the fuzzy value of the PI parameter after fuzzy reasoning, and the fuzzy value is clarified to obtain the unadjusted PI parameter output value;

[0029] According to the variable domain fuzzy PI control table, the domain corresponding to the PI parameter output value under the current actual power is obtained, so as to calculate the domain adjustment value α of the PI parameter kp and α ki ;

[0030] Multiply the PI parameter output values ​​by the corresponding domain adjustment values ​​to obtain the PI parameter K of the power control outer loop. p_P and K i_P ;

[0031] Using the power control outer loop differential equation i cdref =K p_P (P ref -P)+K i_P Int p Calculate the d-axis reference current i cdref ; where Int P is the integrator state variable in the power control outer loop.

[0032] Optionally, the difference E between the actual power and the reference power and the difference change rate EC are divided into 7 levels {NB, NM, NS, ZO, PS, PM, PB}, specifically including:

[0033] When the range of E and EC is between [-1, -0.75], it is classified as NB;

[0034] When the range of E and EC is between [-1, -0.5], it is divided into NM;

[0035] When the range of E and EC is between [-0.75, -0.25], it is divided into S;

[0036] When the range of E and EC is between [-0.5, 0.5], it is divided into ZO;

[0037] When the range of E and EC is between [0.25, 0.75], it is classified as PS;

[0038] When the range of E and EC is between [0.5, 1], it is classified as PM;

[0039] When the range of E and EC is between [0.75, 1], it is classified as PB.

[0040] Optionally, the step of inputting the difference between the actual voltage and the reference voltage into a voltage control outer loop and obtaining a q-axis reference current through a voltage control outer loop PI controller specifically includes:

[0041] Compare the actual voltage V with the reference voltage V ref The difference input voltage controls the outer loop, using the voltage control outer loop differential equation i cqref =K p_V (VV ref )+K i_V Int V Calculate the q-axis reference current i cqref ; where K p_V and K i_Vare the proportional parameter and integral parameter of the voltage control outer loop PI controller respectively; Int V is the integrator state variable in the voltage control outer loop.

[0042] Optionally, the step of inputting the difference between the actual current of the d-axis and the q-axis and the reference current of the d-axis and the q-axis into the current control inner loop to obtain the reference voltage of the d-axis and the q-axis specifically includes:

[0043] Using the current control inner loop differential equation Calculate the d-axis reference voltage v cdref and q-axis reference voltage v cqref ; where K p_I and K i_I They are the proportional parameter and integral parameter of the inner loop PI controller of the current control; Int id and Int iq are the d-axis and q-axis integrator state variables in the current control inner loop; ω is the rated angular frequency of the grid-connected inverter system; L f is the filter inductor.

[0044] On the other hand, the present application also provides a grid-connected inverter system, including: an LCL-type three-phase grid-connected inverter and a grid-connected inverter controller, wherein the LCL-type three-phase grid-connected inverter is connected to a power grid, and the grid-connected inverter controller executes the LCL-type three-phase grid-connected inverter dual closed-loop control method based on variable domain fuzzy PI control.

[0045] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0046] The present application provides a dual closed-loop control method for an LCL-type three-phase grid-connected inverter based on variable universe fuzzy PI control and a grid-connected inverter system. By introducing a variable universe fuzzy PI control strategy, the PI parameters of the power control outer loop can be dynamically adjusted under different operating conditions, so that the grid-connected inverter system can still maintain excellent control accuracy and fast dynamic response performance under different output power conditions, providing a more stable and efficient control means for the grid-connected operation of the new energy power generation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] Figure 1This is a flow chart of a dual closed-loop control method for an LCL-type three-phase grid-connected inverter based on variable universe fuzzy PI control in this application;

[0049] Figure 2 It is a schematic diagram of the main circuit and double closed-loop control circuit structure of the LCL type three-phase grid-connected inverter;

[0050] Figure 3 It is a schematic diagram of the structure of the inner loop of current control;

[0051] Figure 4 Schematic diagram of the power control outer loop structure;

[0052] Figure 5 It is a schematic diagram of the voltage control outer loop structure;

[0053] Figure 6 It is a schematic diagram of the eigenvalue root locus when the output power increases;

[0054] Figure 7 K is the power outer loop control parameter p_P Schematic diagram of eigenvalue root locus when increasing;

[0055] Figure 8 It is a schematic diagram of the distribution of system characteristic roots under different output active powers and different power outer loop control parameters;

[0056] Fig. 9 K is the power control outer loop PI parameter of the inverter at different output powers p_P and K i_P Schematic diagram of the system stability domain when changing;

[0057] Fig.10 This is the variable domain fuzzy PI control block diagram of the power control outer loop;

[0058] Fig.11 It is the actual output power waveform diagram of the inverter output power increasing from 0.5 times the rated power to 0.9 times the rated power;

[0059] Fig.12 Schematic diagram of the voltage harmonic content at the grid connection point under the traditional PI control strategy;

[0060] Fig.13 Schematic diagram of the harmonic content of the grid connection point voltage under the variable domain fuzzy PI control strategy used in this application. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0062] In view of the defects existing in the prior art, this application proposes a dual closed-loop control method and a grid-connected inverter system for an LCL-type three-phase grid-connected inverter based on variable domain fuzzy PI control, so as to improve the dynamic response performance and steady-state control accuracy of the system, and provide a more stable and efficient control means for the grid-connected operation of the new energy power generation system.

[0063] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0064] In an exemplary embodiment, Figure 1 As shown, a dual closed-loop control method for an LCL type three-phase grid-connected inverter based on variable universe fuzzy PI control is provided, including the following steps 1 to 6.

[0065] Step 1: Collect the inverter output current and grid connection point voltage of the LCL type three-phase grid-connected inverter.

[0066] The main circuit and double closed-loop control circuit structure of the LCL type three-phase grid-connected inverter (referred to as inverter) studied in this application are as follows Figure 2 The LCL type three-phase grid-connected inverter is connected to the power grid to form a grid-connected inverter system. f , L f and R f are the filter capacitor, inductor and resistor respectively. g and L g are the equivalent resistance and inductance of the grid side line respectively. dc is the inverter input voltage. c 、v o 、v g They are the inverter output voltage, grid connection point voltage and grid voltage respectively. Since they are all abc three-phase voltages, they are also written as v cabc 、v oabc 、v gabc θ c ,θ o ,θ g are the phase angles corresponding to the inverter output voltage, grid connection point voltage and grid voltage respectively. c 、i o 、i gThey are the inverter output current, grid connection point current and grid current respectively. Since they are all abc three-phase currents, they are also written as i cabc 、i oabc 、i gabc 、v cd 、v cq 、v od 、v oq 、v gd 、v gq The inverter output voltage v c , grid connection point voltage v o and grid voltage v g The voltage components of the d-axis and q-axis in the dq coordinate system. cd 、i cq 、i od 、i oq They are the inverter output current i c and grid-connected current i o The current components of the d-axis and q-axis in the dq coordinate system are also called actual currents. ω is the rated angular frequency of the system. P is the output power of the system, also called actual power. ref is the set reference power. V is the output voltage of the system, also known as the actual voltage. ref is the set reference voltage.

[0067] The dual closed-loop control loop used in this application refers to the current control inner loop (referred to as the current inner loop) and the power and voltage control outer loop. The power and voltage control outer loop can be further divided into the power control outer loop (referred to as the power outer loop) and the voltage control outer loop (referred to as the voltage outer loop). The structure of the current control inner loop is as follows: Figure 3 As shown, the corresponding current control inner loop differential equation is:

[0068]

[0069] Among them, i cdref and i cqref are the d-axis reference current and q-axis reference current input to the current control inner loop respectively; v cd,ref and v cqref are the d-axis reference voltage and q-axis reference voltage output by the current control inner loop respectively; K p_I and K i_I They are the proportional parameter and integral parameter of the inner loop PI controller of the current control; Int id and Int iq are the d-axis and q-axis integrator state variables in the current control inner loop; ω is the rated angular frequency of the grid-connected inverter system; L f is the filter inductor.

[0070] The power control outer loop structure is as follows: Figure 4As shown, it is used to compare the actual power P with the reference power P ref The difference between the two is taken as input, and the variable universe fuzzy PI control is used to obtain the d-axis reference current i cdref .

[0071] The voltage control outer loop structure is as follows Figure 5 As shown, the corresponding voltage control outer loop differential equation is:

[0072]

[0073] Among them, v od and v oq They are the grid connection point voltage v o The d-axis voltage component and the q-axis voltage component in the dq coordinate system. cqref is the q-axis reference current output by the voltage control outer loop. V is the actual voltage. ref is the set reference voltage. K p_V and K i_V Int are the proportional parameter and integral parameter of the voltage control outer loop PI controller respectively. V is the integrator state variable in the voltage control outer loop.

[0074] Step 2: Calculate the actual d-axis and q-axis currents of the inner current control loop and the actual power and actual voltage of the outer power and voltage control loops according to the inverter output current and the grid-connected point voltage.

[0075] like Figure 2 As shown, first the inverter output current i cabc The actual current i of the d-axis of the current control inner loop is obtained by Park transformation cd and the actual q-axis current i cq The Park transformation projects the stator's three-phase currents abc onto the direct axis (d axis), quadrature axis (q axis) and zero axis (0 axis) perpendicular to the dq plane that rotate with the rotor, that is, transforms from the abc coordinate system to the dq coordinate system, thereby achieving the diagonalization of the stator inductance matrix and simplifying the operation analysis of the synchronous motor. Similarly, the grid-connected voltage v oabc The d-axis voltage component v of the grid connection point voltage is obtained by Park transformation od and the q-axis voltage component v oq .

[0076] Then, using the formula P = 1.5 (v od i cd +v oq i cq )Calculate the actual power P of the power control outer loop.

[0077] Using formula Calculate the actual voltage V of the voltage control outer loop.

[0078] Step 3: Input the difference between the actual power and the reference power into the power control outer loop, and use variable domain fuzzy PI control to obtain the d-axis reference current.

[0079] The power control outer loop structure is as follows: Figure 4 As shown, before inputting the difference between the actual power and the reference power into the power control outer loop and using the variable domain fuzzy PI control to obtain the d-axis reference current, it is necessary to first establish the linear state space equation of the LCL type three-phase grid-connected inverter, and according to the distribution of the characteristic roots of the equation, find the power control outer loop parameter range that keeps the system stable under different output powers of the inverter, determine the fuzzy control domain according to the parameter range, formulate the variable domain fuzzy PI control table, and formulate the fuzzy control rule table. Therefore, before executing step 3, it is also necessary to execute the following steps 3.1 to 3.4.

[0080] Step 3.1: Establish the linear state space equation of the LCL type three-phase grid-connected inverter.

[0081] The main circuit is in ab c The equation in the three-phase coordinate system is:

[0082]

[0083] In formulas (3)-(5), v cabc 、v oabc 、v gabc are the inverter output voltage, grid connection point voltage and grid voltage respectively; i cabc and i oabc They are the inverter output current and the grid-connected point current respectively. After abc-dq coordinate transformation, the differential equation of the main circuit can be expressed as:

[0084]

[0085]

[0086] Among them, v cd 、v cq 、v od 、v oq 、v gd 、v gq are the voltage components of the output voltage, grid connection point voltage and grid voltage on the d-axis and q-axis in the dq coordinate system respectively; i cd 、i cq 、i od 、i oq are the current components of the inverter output current and the grid-connected point current on the d-axis and q-axis in the dq coordinate system respectively; ω is the rated angular frequency of the system. The linearized equations of equations (6)-(7) can be expressed as equations (9)-(11):

[0087]

[0088] The Δ before each parameter indicates the change of the parameter, which is applicable to all the parameters in the formula.

[0089] The small signal model of the dual closed-loop control loop is established as follows.

[0090] like Figure 1 and Figure 3 As shown, the differential equation of the inner current loop can be expressed as:

[0091]

[0092] In formulas (12) and (13), Int id and Int iq are the d-axis and q-axis integrator state variables in the inner current control loop, K p_I and K i_I are the proportional parameter and integral parameter of the inner loop PI controller of the current control, respectively. The linearized equations of equations (12)-(13) can be expressed as (14)-(15):

[0093]

[0094]

[0095] The differential equations of the power and voltage control outer loop are shown in equations (16)-(17):

[0096]

[0097] In formulas (16)-(17), Int P and Int V are the integrator state variables in the power and voltage control outer loops, respectively, K p_P , K i_P , K p_V , K i_V are the proportional and integral parameters of the outer loop PI controller for power and voltage control, respectively. The linearized equations of (16)-(17) are:

[0098]

[0099] The linearized equations for power and voltage calculation in the dual closed-loop control loop are:

[0100]

[0101] The complete small signal model of the LCL type three-phase grid-connected inverter is constructed as follows.

[0102] According to equations (9)-(11), (14)-(15), (18)-(20), the linear state space equation of the LCL type three-phase grid-connected inverter (or grid-connected inverter system) can be derived as follows:

[0103]

[0104] where Δx 12×1 =[Δv od , Δv oq , Δv cd , Δv cq , Δi cd , Δi cq , ΔInt id , ΔInt iq , ΔInt P , ΔInt V , ΔP, ΔV] T . = Δx 12×1 The derivative of A. 12×12 is the state space matrix of the grid-connected inverter system, and the system matrix A 12×12 The characteristic root of determines the stability of the system. If the system matrix A 12×12 If the real part of all the characteristic roots of is less than zero, the system is stable. If the real part of at least one characteristic root is greater than or equal to zero, the system is unstable.

[0105] Step 3.2: Determine the PI parameter stability threshold of the power control outer loop under different output powers P according to the distribution of the characteristic roots of the linear state space equation, that is, the control parameter K p_P and K i_P The stability threshold.

[0106] The stability analysis is performed by characteristic root analysis method, and the characteristic root locus obtained is as follows Figure 6 As shown. Figure 6 It can be seen that when the control parameter K p_P and K i_P When the inverter output power increases, the system gradually changes from a stable state to an unstable state. Figure 7 The relationship between the power control outer loop PI parameter and the system characteristic root distribution is shown when the output active power is equal to 0.6pu. The real part of the characteristic root λ1 increases with the power outer loop control parameter K p_P According to the above analysis, the changes of the inverter's output active power and the power outer loop control parameters will cause the risk of system instability.

[0107] Figure 8The three-dimensional distribution diagram of the system characteristic value under different output active power of the inverter and different power outer loop control parameters is shown. The x-axis coordinate and the y-axis coordinate are the power outer loop PI parameter K p_P and K i_P , the z-axis coordinate is the real part of the most unstable characteristic root of the system, the area below the z=0 plane is the stable area, and the area above the z=0 plane is the unstable area. This application divides the inverter output active power area into a low power segment (output power less than 0.4pu), a medium power segment (output power between 0.4pu and 0.7pu) and a high power segment (output power greater than 0.4pu and less than or equal to 1p.u.), and analyzes the system stability when the active power is equal to 0.4pu, 0.7pu, and 1p.u in the three power segments. The stability domain of the power outer loop PI parameters under three different powers is as follows Fig. 9 As shown by Fig. 9 It can be seen that: 1) when K p_P When it is in a smaller value range, for any power, K i_P The larger the value, the greater the risk of system instability. p_P The larger the value, the smaller the risk of system instability; 2) But when K p_P When K increases to a certain value, the system stability trend shows an inflection point. p_P When K is greater than this value, p_P Entering a larger value range, at this time for any power, K i_P The larger the value, the greater the risk of system instability. p_P The larger the active power, the greater the risk of system instability; 3) The increase in active power will increase the risk of system instability. The stable area (stable domain) refers to the working range or conditions in which the inverter can maintain stable operation when connected to the grid. In this area, the inverter can normally and reliably transmit electrical energy to the grid area, and the output of the inverter will not cause system oscillation, overload or other instability.

[0108] Step 3.3: According to the PI parameter stability threshold of the power control outer loop under different output powers, K in the variable domain fuzzy PI control is determined. p and K i The correspondence table between the domain and the output power P is used as the variable domain fuzzy PI control table.

[0109] according to Fig. 9 The stability domain in the variable domain fuzzy PI control method is obtained by determining the PI parameter range of the power control outer loop under different powers P. p and K i The corresponding relationship table between the domain and the output power P is the variable domain fuzzy PI control table described in this application, as shown in Table 1 below.

[0110] Table 1 Variable universe fuzzy PI control table

[0111]

[0112] In the variable domain fuzzy PI control table, when the actual power P is less than 0.4, K p The domain of K is

[16] , i The domain of K is [0.54]; when the actual power P is between 0.4 and 0.7, p The domain of discourse is [13.5], K i The domain of K is [0.52]; when the actual power P is greater than 0.7, p The domain of K is [1.53], i The domain of is [0.51.5]. Based on this variable domain fuzzy PI control table, K in the variable domain fuzzy PI control can be adjusted according to the inverter output power P. p and K i The domain is the PI parameter K of the power control outer loop p_P and K i_P The domain of discussion.

[0113] Step 3.4: Compare the actual power P and reference power P of LCL three-phase grid-connected inverter ref The difference E and the difference change rate EC are taken as input, and the PI parameters of the power control outer loop are taken as output. According to the characteristics of the grid-connected inverter system and the PI adjustment law, a fuzzy control rule table is formulated.

[0114] The actual value P of the inverter active power output is compared with the reference power P ref The deviation (difference) E and the deviation change rate EC are used as input, and the PI parameter K of the power control outer loop is used. p_P and K i_P The fuzzy value (also denoted as K p and K i ) as the output, and formulate the fuzzy control rule table according to the characteristics of the grid-connected inverter system and the PI regulation law. When the deviation E is too large, select a larger proportional parameter K p To increase the response speed and reduce K i Avoid excessive overshoot; when the deviation E is small, select a smaller proportional parameter K p , reduce the response of the controller to avoid overreaction, and increase K i Eliminate steady-state error. When the deviation change rate EC is too large, increase the proportional parameter K p , enhance the controller's ability to respond to rapid changes so as to correct deviations more quickly, while reducing the integral coefficient K i Prevent overcorrection. When the deviation change rate EC is small, reduce the proportional parameter K pAvoid over-adjustment while increasing K i Strengthen the integral action to eliminate small errors. The fuzzy control rule tables are shown in Tables 2 and 3 below.

[0115] Table 2K p Fuzzy control rule table

[0116]

[0117] Table 3K i Fuzzy control rule table

[0118]

[0119]

[0120] The seven levels {NB, NM, NS, ZO, PS, PM, PB} in the above fuzzy control rule table correspond to large negative, medium negative, small negative, zero, small positive, medium positive, and large positive, respectively.

[0121] On the basis of formulating the above variable universe fuzzy PI control table and fuzzy control rule table, the variable universe fuzzy PI control of the power control outer loop can be carried out. The control block diagram is as follows: Fig.10 See Fig.10 In step 3, the difference between the actual power and the reference power is input into the power control outer loop, and the d-axis reference current is obtained by using variable domain fuzzy PI control, which specifically includes:

[0122] Step 3.5: First, compare the actual power P with the reference power P ref The difference E and the difference change rate EC are divided into 7 fuzzy levels {NB, NM, NS, ZO, PS, PM, PB}, corresponding to large negative, medium negative, small negative, zero, small positive, medium positive, and large positive, respectively.

[0123] Specifically, the range of E and EC is between [-1, 1], and their fuzzy levels are divided as follows:

[0124] When the range of E and EC is between [-1, -0.75], it is classified as NB;

[0125] When the range of E and EC is between [-1, -0.5], it is divided into NM;

[0126] When the range of E and EC is between [-0.75, -0.25], it is divided into S;

[0127] When the range of E and EC is between [-0.5, 0.5], it is divided into ZO;

[0128] When the range of E and EC is between [0.25, 0.75], it is classified as PS;

[0129] When the range of E and EC is between [0.5, 1], it is classified as PM;

[0130] When the range of E and EC is between [0.75, 1], it is classified as PB.

[0131] Each fuzzy level is represented by a triangular membership function, where the central point corresponds to a membership of 1 and the two sides gradually decrease toward zero. The specific membership function is defined as follows:

[0132] NB (Negative Large): The center point is -1, the coverage range is [-1, -0.75], and it gradually decreases to 0 to the right.

[0133] NM (Negative Middle): The center point is -0.75, the coverage range is [-1, -0.5], and it decreases on both sides.

[0134] NS (Negative Small): The center point is -0.5, the coverage range is [-0.75, -0.25], and it decreases on both sides.

[0135] ZO (zero): center point 0, coverage range [-0.5, 0.5], symmetrically decreasing.

[0136] PS (positive small): the center point is 0.5, the coverage range is [0.25, 0.75], and it decreases on both sides.

[0137] PM (middle): The center point is 0.75, the coverage range is [0.5, 1], and it decreases on both sides.

[0138] PB (positive and large): The center point is 1, the coverage range is [0.75, 1], and decreases to 0 to the left.

[0139] Assuming the values ​​of E and EC are x, the membership degree of each fuzzy level M(x) is calculated as follows:

[0140] NB:

[0141]

[0142] NM:

[0143]

[0144] NS:

[0145]

[0146] ZO:

[0147]

[0148] PS:

[0149]

[0150] PM:

[0151]

[0152] PB:

[0153]

[0154] Step 3.6: Then, the levels of the difference E and the difference change rate EC are input into the fuzzy rule controller, and fuzzy reasoning is performed according to the formulated fuzzy control rule table (Table 2 and Table 3) to obtain the fuzzy value K of the PI parameter after fuzzy reasoning. p and K i , the fuzzy value K p and K i After clarification, the unadjusted PI parameter output value is obtained.

[0155] Fuzzy value K p and K i Determine according to the corresponding rules in Table 2 and Table 3, for example, if E = NS and EC = PS, then K p The fuzzy value of is ZO. Fuzzy value clarification is to convert the fuzzy result obtained by fuzzy reasoning into a clear and executable output value. The unadjusted PI parameter output value refers to the output value obtained by fuzzy reasoning.

[0156] Step 3.7: According to the variable domain fuzzy PI control table, the domain corresponding to the PI parameter output value under the current actual power is obtained, so as to calculate the domain adjustment value α of the PI parameter kp and α ki .

[0157] Using the corresponding relationship between power P and domain in Table 1, we can get K under the current power p and K i The output domain of , thereby calculating the corresponding domain adjustment value α kp and α ki , multiplying the unadjusted output value by the domain adjustment value gives K p and K i The actual value of the power control outer loop PI parameter K p_P and K i_P .

[0158] Domain adjustment value α kp and α ki According to the current system state, the adjustment value is used to adjust the output domain range. The unadjusted output value is within the standard domain [-1, 1]. After adjustment, the restricted domain range in Table 1 can be obtained. At the same time, the power P can also be used to determine the K that stabilizes the system. pand K i The limit value is used to limit the PI parameter K obtained by variable domain fuzzy control p_P and K i_P The value of .

[0159] Step 3.8: Multiply the PI parameter output values ​​by the corresponding domain adjustment value α kp and α ki , we can get the PI parameter K of the power control outer loop p_P and K i_P By dynamically adjusting the domain of fuzzy control rules, the controller can achieve better control effects under different working conditions.

[0160] Step 3.9: If Figure 2 and Figure 4 As shown, the power control outer loop differential equation i cdref =K p_P (P ref -P)+K i_P Int p The d-axis reference current i can be calculated cdref ; where Int P is the integrator state variable in the power control outer loop.

[0161] Step 4: Input the difference between the actual voltage and the reference voltage into the voltage control outer loop, and obtain the q-axis reference current through the voltage control outer loop PI controller.

[0162] like Figure 2 and Figure 5 As shown, the actual voltage V is compared with the reference voltage V ref The difference input voltage controls the outer loop, using the voltage control outer loop differential equation i cqref =K p_V (VV ref )+K i_V Int V The q-axis reference current i can be calculated cqref ; where K p_V and K i_V are the proportional parameter and integral parameter of the voltage control outer loop PI controller respectively; Int V is the integrator state variable in the voltage control outer loop.

[0163] Step 5: Input the difference between the actual current of the d-axis and q-axis and the reference current of the d-axis and q-axis into the current control inner loop to obtain the reference voltage of the d-axis and q-axis.

[0164] like Figure 2 and Figure 3 As shown, the actual current i of the d-axis and q-axis is cd 、i cqWith the d-axis and q-axis reference current i cdref 、i cqref The difference input current control inner loop adopts the current control inner loop differential equation The d-axis reference voltage v can be calculated cdref and q-axis reference voltage v cqref . Where K p_I and K i_I They are the proportional parameter and integral parameter of the inner loop PI controller of the current control; Int id and Int iq are the d-axis and q-axis integrator state variables in the current control inner loop; ω is the rated angular frequency of the grid-connected inverter system; L f is the filter inductor.

[0165] Step 6: Generate PWM signals from the d-axis and q-axis reference voltages through inverse Park transformation and sinusoidal pulse width modulation to control the switches of the LCL-type three-phase grid-connected inverter.

[0166] like Figure 2 As shown, the d-axis and q-axis reference voltages v cdref 、v cqref The PWM signal is generated by inverse Park transformation and sine pulse width modulation (SPWM) to control the switch of the LCL type three-phase grid-connected inverter, thereby realizing the control of the inverter.

[0167] In an exemplary embodiment, the present application also provides a grid-connected inverter system, comprising: an LCL-type three-phase grid-connected inverter and a grid-connected inverter controller, wherein the LCL-type three-phase grid-connected inverter is connected to a power grid, and the grid-connected inverter controller executes the LCL-type three-phase grid-connected inverter dual closed-loop control method based on variable domain fuzzy PI control.

[0168] Fig.11 Part (a) and part (b) of FIG. 1 respectively show the power waveform of the traditional PI control strategy and the power waveform of the variable domain fuzzy PI control used in this application. Fig.11 It can be seen that the overshoot of the variable universe fuzzy PI control used in this application (within 0.702) is smaller than the overshoot of the traditional PI control strategy (within 0.708).

[0169] Fig.12 and Fig.13 The total harmonic distortion (THD) of the grid-connected point voltage of the system using the traditional PI control strategy power waveform and the variable universe fuzzy PI control used in this application are shown respectively after the output power reaches a stable value (3.5s-5s). Fig.12 and Fig.13 The horizontal axis is frequency (Frequency); the vertical axis Mag represents the amplitude, and Fundamental means the basic, which means the fundamental amplitude here; then Fig.12 and Fig.13 The vertical axis represents the percentage of the harmonic amplitude to the fundamental amplitude. Fig.12 It can be seen that the traditional PI control strategy THD = 0.28%. Fig.13 It can be seen that the THD of the present application is 0.02%. It can be seen that the present application can reduce the harmonic content value of the grid connection point.

[0170] The present application provides a dual closed-loop control method for an LCL-type three-phase grid-connected inverter based on variable universe fuzzy PI control, which has the following significant technical advantages and effects compared with the prior art:

[0171] 1. Improve control accuracy and dynamic response performance: By introducing the variable domain fuzzy PI control strategy, the present application can dynamically adjust the control parameters under different operating conditions, so that the grid-connected inverter system can still maintain excellent control accuracy and fast dynamic response under different output power conditions.

[0172] 2. Enhance the robustness and stability of the system: The variable domain fuzzy PI control method can effectively cope with the uncertainty of system parameters and grid fluctuations, enhance the robustness of the grid-connected inverter system, reduce the risk of system oscillation or instability, and improve the system's stable operation capability.

[0173] 3. Significantly reduce harmonic distortion (THD): This application optimizes the design and adjustment of the LCL filter in the control strategy. By effectively filtering out the high-order harmonic components in the grid-connected current, the total harmonic distortion (THD) is significantly reduced, thereby improving the quality of the output power.

[0174] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0175] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A dual closed-loop control method for LCL type three-phase grid-connected inverter based on variable universe fuzzy PI control, characterized in that: include: Collect the inverter output current and grid connection point voltage of LCL type three-phase grid-connected inverter; Calculate the actual current of the d-axis and q-axis of the inner loop of current control and the actual power and actual voltage of the outer loop of power and voltage control according to the inverter output current and the grid connection point voltage; The difference between the actual power and the reference power is input into the outer loop of power control, and the d-axis reference current is obtained by using variable universe fuzzy PI control; The difference between the actual voltage and the reference voltage is input into the voltage control outer loop, and the q-axis reference current is obtained through the voltage control outer loop PI controller; The difference between the actual current of the d-axis and q-axis and the reference current of the d-axis and q-axis is input into the current control inner loop to obtain the reference voltage of the d-axis and q-axis; The d-axis and q-axis reference voltages are transformed by inverse Park transformation and sinusoidal pulse width modulation to generate PWM signals to control the switches of the LCL type three-phase grid-connected inverter.

2. The LCL type three-phase grid-connected inverter double closed-loop control method based on variable universe fuzzy PI control according to claim 1 is characterized in that: The method of calculating the actual current of the d-axis and q-axis of the inner loop of the current control and the actual power and actual voltage of the outer loop of the power and voltage control according to the inverter output current and the grid connection point voltage specifically includes: The inverter output current i cabc The actual current i of the d-axis of the current control inner loop is obtained by Park transformation cd and the actual q-axis current i cq ; The grid voltage v oabc The d-axis voltage component v of the grid connection point voltage is obtained by Park transformation od and the q-axis voltage component v oq ; Using the formula P = 1.5 (v od i cd +v oq i cq ) Calculate the actual power P of the power control outer loop; Using formula Calculate the actual voltage V of the voltage control outer loop.

3. The LCL type three-phase grid-connected inverter double closed-loop control method based on variable universe fuzzy PI control according to claim 2 is characterized in that: Before inputting the difference between the actual power and the reference power into the power control outer loop and obtaining the d-axis reference current by using the variable universe fuzzy PI control, the method further includes: Establish the linear state space equation of LCL type three-phase grid-connected inverter; Determine the PI parameter stability threshold of the power control outer loop under different output powers according to the characteristic root distribution of the linear state space equation; the output power is the actual power P; According to the PI parameter stability threshold of the power control outer loop under different output powers, K in the variable domain fuzzy PI control p and K i The correspondence table between the domain and the output power P is used as the variable domain fuzzy PI control table.

4. The LCL type three-phase grid-connected inverter double closed-loop control method based on variable universe fuzzy PI control according to claim 3 is characterized in that: In the variable domain fuzzy PI control table, when the actual power P is less than 0.4, K p The domain of K is [16], i The domain of K is [0.54]; when the actual power P is between 0.4 and 0.7, p The domain of discourse is [13.5], K i The domain of K is [0.52]; when the actual power P is greater than 0.7, p The domain of K is [1.53], i The domain of is [0.51.5].

5. The LCL type three-phase grid-connected inverter double closed-loop control method based on variable universe fuzzy PI control according to claim 4 is characterized in that: Before inputting the difference between the actual power and the reference power into the power control outer loop and obtaining the d-axis reference current by using the variable universe fuzzy PI control, the method further includes: The actual power P of the LCL three-phase grid-connected inverter is compared with the reference power P ref The difference E and the difference change rate EC are taken as input, and the PI parameters of the power control outer loop are taken as output. According to the characteristics of the grid-connected inverter system and the PI adjustment law, a fuzzy control rule table is formulated.

6. The LCL type three-phase grid-connected inverter double closed-loop control method based on variable universe fuzzy PI control according to claim 5 is characterized in that: The difference between the actual power and the reference power is input into the power control outer loop, and the d-axis reference current is obtained by using the variable universe fuzzy PI control, which specifically includes: Firstly, the difference E between the actual power and the reference power and the difference change rate EC are divided into 7 levels {NB, NM, NS, ZO, PS, PM, PB}, corresponding to large negative, medium negative, small negative, zero, small positive, medium positive, and large positive respectively; Then, the levels of the difference value E and the difference change rate EC are input into the fuzzy rule controller, and fuzzy reasoning is performed according to the formulated fuzzy control rule table to obtain the fuzzy value of the PI parameter after fuzzy reasoning, and the fuzzy value is clarified to obtain the unadjusted PI parameter output value; According to the variable domain fuzzy PI control table, the domain corresponding to the PI parameter output value under the current actual power is obtained, so as to calculate the domain adjustment value α of the PI parameter kp and α ki ; Multiply the PI parameter output values ​​by the corresponding domain adjustment values ​​to obtain the PI parameter K of the power control outer loop. p_P and K i_P ; Using the power control outer loop differential equation i cdref =K p_P (P ref -P)+K i_P Int p Calculate the d-axis reference current i cdref ; where Int P is the integrator state variable in the power control outer loop.

7. The LCL type three-phase grid-connected inverter double closed-loop control method based on variable universe fuzzy PI control according to claim 6 is characterized in that: The difference E between the actual power and the reference power and the difference change rate EC are divided into 7 levels {NB, NM, NS, ZO, PS, PM, PB}, specifically including: When the range of E and EC is between [-1, -0.75], it is classified as NB; When the range of E and EC is between [-1, -0.5], it is divided into NM; When the range of E and EC is between [-0.75, -0.25], it is divided into S; When the range of E and EC is between [-0.5, 0.5], it is divided into ZO; When the range of E and EC is between [0.25, 0.75], it is classified as PS; When the range of E and EC is between [0.5, 1], it is classified as PM; When the range of E and EC is between [0.75, 1], it is classified as PB.

8. The LCL type three-phase grid-connected inverter double closed-loop control method based on variable universe fuzzy PI control according to claim 7 is characterized in that: The difference between the actual voltage and the reference voltage is input into the voltage control outer loop, and the q-axis reference current is obtained through the voltage control outer loop PI controller, which specifically includes: Compare the actual voltage V with the reference voltage V ref The difference input voltage controls the outer loop, using the voltage control outer loop differential equation i cqref =K p_V (VV ref )+K i_V Int V Calculate the q-axis reference current i cqref ; where K p_V and K i_V are the proportional parameter and integral parameter of the voltage control outer loop PI controller respectively; Int V is the integrator state variable in the voltage control outer loop.

9. The LCL type three-phase grid-connected inverter double closed-loop control method based on variable universe fuzzy PI control according to claim 8, characterized in that: The difference between the actual current of the d-axis and the q-axis and the reference current of the d-axis and the q-axis is input into the current control inner loop to obtain the reference voltage of the d-axis and the q-axis, specifically including: Using the current control inner loop differential equation Calculate the d-axis reference voltage V cdref and q-axis reference voltage v cqref ; where K p_I and K i_I They are the proportional parameter and integral parameter of the inner loop PI controller of the current control; Int id and Int iq are the d-axis and q-axis integrator state variables in the current control inner loop; ω is the rated angular frequency of the grid-connected inverter system; L f is the filter inductor.

10. A grid-connected inverter system, comprising: An LCL type three-phase grid-connected inverter and a grid-connected inverter controller, wherein the LCL type three-phase grid-connected inverter is connected to a power grid, and wherein the grid-connected inverter controller executes a LCL type three-phase grid-connected inverter double closed-loop control method based on variable domain fuzzy PI control as described in any one of claims 1 to 9.

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