A Nonlinear Shunt Distributed Compensation Method for Grid-Connected Synchronous Control System

Abstract

The present invention discloses a nonlinear parallel distributed compensation method for a grid-connected synchronous control system, belonging to the technical field of grid-connected synchronous control. First, a large-signal model of the system is established, its Jacobian matrix is obtained, a linearization point is selected, and its state space A is determined. i , membership function ω i , and an open-loop T-S fuzzy model of the system is established; then, corresponding to each state space A in the open-loop T-S fuzzy model i , a corresponding state feedback F i x is added, and its input column vector B is determined, so that the state space A of the system after adding the state feedback i -BF i has negative eigenvalues, where x is the system state column vector; the fuzzy rules and the closed-loop T-S fuzzy model of the system are determined. The present invention performs nonlinear control on the nonlinear grid-connected synchronous control system, enabling the grid-connected synchronous control system to be stable at any phase angle operating point, improving the ability of the grid-connected synchronous control system to cope with grid faults, and enabling the traditional phase-locked loop to have a faster phase-locking speed.

Description

Technical Field

[0001] The present invention relates to the technical field of grid-connected synchronization control, and particularly relates to a non-linear parallel distributed compensation method for a grid-connected synchronization control system. Background Art

[0002] With the rapid development of human society, the energy problem has become an obstacle on the development path. Therefore, people have turned their attention to renewable energy (solar energy, wind energy) to solve the energy problem. In the future, renewable energy will be widely utilized, and large-scale renewable energy will be connected to the grid. Then, the stability of the grid-connected converter as its interface plays a crucial role in this process.

[0003] Nowadays, grid faults cause the instability of the grid-connected synchronization control system. In order to improve the stability of the grid-connected synchronization control system when dealing with grid faults, there are currently 5 main methods to improve stability: (1) Freeze the phase-locked loop integrator when the grid fault occurs. Although this method can keep the grid-connected synchronization control system stable during the fault, it cannot correctly track the grid phase; (2) By changing the phase-locked loop structure, the phase-locked loop becomes first-order during the grid fault, but it still has the ability to track the grid, avoiding the adverse phase angle overshoot caused by the second-order loop. If there is no equilibrium point in the system during the grid fault, the phase-locked loop will still diverge and the system will be unstable; (3) Increase the damping of the phase-locked loop. This adjustment method is similar to the existing proportional-integral adjustment, but the introduction of damping avoids the reverse adjustment of the sine function within a half cycle. This method also depends on the existence of the equilibrium point in the system during the grid fault; (4) During the grid fault, quickly estimate the impedance to obtain the short-circuit ratio, and re-give the references of the active current and reactive current according to the short-circuit ratio. However, this method is only applicable to single converters; (5) Adjust the output of the active current according to the phase-locked loop frequency deviation. Although this method can make the system stable, it should be noted that the use of this method cannot determine the operating point of the system during steady-state operation. Among these control methods for improving stability, they all need to be enabled during grid faults, resulting in the inability to quickly recover from system faults, and in severe cases, it will cause large-scale paralysis of the grid-connected synchronization control system. The above problems need to be solved urgently. For this reason, a non-linear parallel distributed compensation method for a grid-connected synchronization control system is proposed. Summary of the Invention

[0004] The technical problem to be solved by the present invention is: how to make all state spaces of the grid-connected synchronization control system stable through non-linear parallel distributed compensation, so that the grid-connected synchronization control system can converge at any initial phase angle point and the system remains stable, and a non-linear parallel distributed compensation method for a grid-connected synchronization control system is provided.

[0005] The present invention solves the above technical problems through the following technical solutions, and the present invention includes the following steps:

[0006] S1: Establish a large-signal model of the grid-connected synchronous control system;

[0007] S2: Obtain its Jacobian matrix J according to the large-signal model of the grid-connected synchronous control system in step S1;

[0008] S3: Select its linearization point according to the Jacobian matrix J of the grid-connected synchronous control system determined in step S2;

[0009] S4: Determine the state space A of the grid-connected synchronous control system according to the linearization point selected in step S3 i and the membership function ω i , where i = 1, 2, 3, 4, 5, and in order for the membership function to work correctly, the state variable δ is processed so that δ″ ∈ (-π + δ0, π + δ0);

[0010] S5: According to the state space A in step S4 i , the membership function ω i , establish an open-loop T-S fuzzy model of the grid-connected synchronous control system with multi-point linearization;

[0011] S6: According to the open-loop T-S fuzzy model of the grid-connected synchronous control system in step S5, add the state feedback F i x to V pccq after that, where x is the system state, determine the input matrix B, and V pccq is the q-axis component of the grid-connected common coupling point voltage V pcc after Park transformation;

[0012] S7: Design the state feedback row vector F i according to step S6, so that A i - BF i has negative eigenvalues;

[0013] S8: Determine the fuzzy rules and the closed-loop T-S fuzzy model of the grid-connected synchronous control system according to the above steps.

[0014] Furthermore, in the step S1, the large-signal model of the grid-connected synchronous control system is as follows:

[0015]

[0016] where the state variable δ = θ pll - ω s t, θ pll is the phase angle output by the phase-locked loop, ω s is the grid angular velocity, α is the output of the phase-locked loop integrator, k pis the proportional coefficient of the phase-locked loop, k i is the integral coefficient of the phase-locked loop, L g is the line inductive reactance, V g is the amplitude of the grid voltage, is the initial phase angle of the grid voltage.

[0017] Furthermore, in the step S2, the Jacobian matrix J is as follows:

[0018]

[0019] Furthermore, in the step S3, in order to make the initial operating points within 2π of the output phase angle of a phase-locked loop stable in one cycle, the linearization points are selected as δ1 = -π + δ0, δ2 = -0.5π + δ0, δ3 = δ0, δ4 = 0.5π + δ0, δ5 = π + δ0, where δ0 is the steady-state value of δ.

[0020] Furthermore, in the step S4, the state space A i is expressed as follows:

[0021]

[0022] The membership function ω i is expressed as follows:

[0023]

[0024] Furthermore, in the step S4, the state variable δ is processed as shown in the following formula:

[0025]

[0026] where δ' is the remainder of δ divided by 2π.

[0027] Furthermore, in the step S5, the open-loop T-S fuzzy model of the grid-connected synchronization control system is as shown in the following formula:

[0028]

[0029] where x = [δα] T , γ = [k p L g I c ω s / (1 - k p L g I c )k i L g I c ω s / (1 - k p Lg I c )] T 。

[0030] Furthermore, in the step S6, the state feedback F i x is added to V pccq After that, the input matrix B = [k p k i T 。

[0031] Furthermore, in the step S7, design the state feedback row vector F i , such that all the eigenvalues of the new state matrix A i - BF i have negative real parts, and make the first element of the F3 row vector be 0.

[0032] Furthermore, in the step S8, the fuzzy rules are as follows:

[0033] If δ″ = -π + δ0, then the state matrix A = A1 and the state feedback row vector F = F1;

[0034] If δ″ = -0.5π + δ0, then the state matrix A = A2 and the state feedback row vector F = F2;

[0035] If δ″ = δ0, then the state matrix A = A3 and the state feedback row vector F = F3;

[0036] If δ″ = 0.5π + δ0, then the state matrix A = A4 and the state feedback row vector F = F4;

[0037] If δ″ = π + δ0, then the state matrix A = A5 and the state feedback row vector F = F5;

[0038] The closed-loop T-S fuzzy model of the grid-connected synchronization control system is as follows:

[0039]

[0040] The present invention has the following advantages compared with the prior art: The traditional phase-locked loop will diverge and become unstable due to the working point shift during the grid fault. The present invention designs the PDC of the grid-connected synchronization control system to perform nonlinear control on the nonlinear grid-connected synchronization control system, so that the grid-connected synchronization control system can be stable at any phase angle working point, greatly improving the ability of the grid-connected synchronization control system to cope with grid faults. And with the addition of PDC, the traditional phase-locked loop can have a faster phase-locking speed at the originally stable working point. Therefore, the addition of PDC is of great significance for improving the stability of the grid-connected synchronization control system. Description of the Drawings ​

[0041] Figure 1 This is the topology diagram of the grid-connected synchronization control system in the embodiment of the present invention;

[0042] Figure 2 This is the structure diagram of the grid-connected synchronization control system in the embodiment of the present invention;

[0043] Figure 3 This is the schematic diagram of the membership function of the T-S fuzzy model in the embodiment of the present invention;

[0044] Figure 4 This is the PDC control block diagram of the grid-connected synchronization control system in the embodiment of the present invention;

[0045] Figure 5 (a) These are the system waveforms before and after the PDC control is not added when the initial phase angle working point is 0 in the embodiment of the present invention;

[0046] Figure 5 (b) These are the system waveforms before and after the PDC control is added when the initial phase angle working point is 0 in the embodiment of the present invention;

[0047] Figure 6 (a) These are the system waveforms before and after the PDC control is not added when the initial phase angle working point is 0.6π in the embodiment of the present invention;

[0048] Figure 6 (b) These are the system waveforms before and after the PDC control is added when the initial phase angle working point is 0.6π in the embodiment of the present invention;

[0049] Figure 7 (a) These are the system waveforms before and after the PDC control is not added when the initial phase angle working point is 0.9π in the embodiment of the present invention;

[0050] Figure 7 (b) These are the system waveforms before and after the PDC control is added when the initial phase angle working point is 0.9π in the embodiment of the present invention;

[0051] Figure 8 This is the design flow chart of the non-linear parallel distributed compensation method (PDC) of the grid-connected synchronization control system in the embodiment of the present invention. Detailed implementation manners

[0052] The following makes a detailed description of the embodiments of the present invention. These embodiments are implemented on the premise of the technical solution of the present invention, and detailed implementation manners and specific operation processes are given. However, the protection scope of the present invention is not limited to the following embodiments.

[0053] This embodiment provides a technical solution: a non-linear parallel distributed compensation method (PDC) for a grid-connected synchronous control system. Based on the open-loop T-S fuzzy model of the grid-connected synchronous control system, non-linear parallel distributed compensation is designed to stabilize all state spaces of the grid-connected synchronous control system, enabling the grid-connected synchronous control system to converge at any initial phase angle point and the system to remain stable. The method includes the following steps (see Figure 8 ):

[0054] Step 1: First, establish a large-signal model of the grid-connected synchronous control system;

[0055] Step 2: Calculate the Jacobian matrix J of the grid-connected synchronous control system based on the large-signal model determined in Step 1;

[0056] Step 3: Select the linearization point based on the Jacobian matrix J of the grid-connected synchronous control system determined in Step 2;

[0057] Step 4: Determine the state space A of the grid-connected synchronous control system based on the linearization point determined in Step 3 i , the membership function ω i , where i = 1, 2, 3, 4, 5, and to ensure the correct operation of the membership function, the state variable δ is processed so that δ″ ∈ (-π + δ0, π + δ0);

[0058] Step 5: Based on the state space A i and the membership function ω i determined in Step 4, establish an open-loop T-S fuzzy model of the grid-connected synchronous control system with multi-point linearization;

[0059] Step 6: According to the open-loop T-S fuzzy model of the grid-connected synchronous control system determined in Step 5, add the state feedback F i x to V pccq after that, where x is the system state, determine the input matrix B, and V pccq is the q-axis component of the grid-connected common coupling point voltage V pcc after PARK transformation;

[0060] Step 7: According to the row vector F of the state feedback designed in Step 6 i , make A i - BF i have negative eigenvalues;

[0061] Step 8: Finally, determine the fuzzy rules and the closed-loop T-S fuzzy model of the grid-connected synchronous control system according to the above steps.

[0062] In this embodiment, since the time scales of the current loop (several kilohertz) and the phase-locked loop (several tens of hertz) in the grid-connected synchronization control system differ greatly, the influence of the current loop on the phase-locked loop is ignored, and the grid-connected converter is equivalent to an ideal current source. Its topology diagram is as shown in Figure 1 shown, where I c is the reference current amplitude, θ pll is the phase angle output by the phase-locked loop, L g is the grid parasitic inductance, V g is the grid voltage amplitude, θ g is the grid voltage phase angle. The structure diagram of the grid-connected synchronization control system is as shown in Figure 2 shown.

[0063] In this embodiment, the grid-connected reference current amplitude I c of the grid-connected synchronization control system is 1512 A, the grid voltage amplitude V g is 220 V, the grid voltage angular velocity ω s is 100π, the grid parasitic inductance L g is 0.3 mH, the proportionality coefficient k p is 0.7, the integral coefficient k i is 78.4, and the initial phase angle of the grid voltage is

[0064] According to Figure 2 the state equation (large-signal model) of the grid-connected synchronization control system is written as follows:

[0065]

[0066] Its Jacobian matrix J is shown as follows:

[0067]

[0068] Select the linearization points δ1 = -π + δ0, δ2 = -0.5π + δ0, δ3 = δ0, δ4 = 0.5π + δ0, δ5 = π + δ0, where δ0 is the steady-state value of δ. In this embodiment, δ0 = 0.868.

[0069] By selecting the linearization points, its state space A i can be determined as shown in the following formula:

[0070]

[0071] where i = 1, 2, 3, 4, 5, and the state variable δ is processed as shown in the following formula:

[0072]

[0073] where δ' is the remainder of δ divided by 2π.

[0074] The membership functions of the T-S fuzzy model are as follows and Figure 3 shown as follows:

[0075]

[0076] The open-loop T-S fuzzy model of the grid-connected synchronization control system is shown as follows:

[0077]

[0078] where i = 1, 2, 3, 4, 5, x = [δα] T , γ = [k p L g I c ω s / (1 - k p L g I c )k i L g I c ω s / (1 - k p L g I c )] T .

[0079] Adding state feedback to the position as Figure 4 shown, the input matrix B = [k p k i . According to the state matrix A i and the input matrix B, design the state feedback row vector F i such that the eigenvalues of A i - BF i have negative real parts. To ensure that the addition of PDC has no impact on V pccq and thus achieve perfect tracking of the grid phase, the first element of F3 should be 0. In this embodiment, the selection of F i and the eigenvalues are as follows:

[0080]

[0081] The fuzzy rules are:

[0082] 1) If δ″ = -π + δ0, then the state matrix A = A1 and the state feedback row vector F = F1;

[0083] 2) If δ″ = -0.5π + δ0, then the state matrix A = A2 and the state feedback row vector F = F2;

[0084] 3) If δ″ = δ0, then the state matrix A = A3 and the state feedback row vector F = F3;

[0085] 4) If δ″ = 0.5π + δ0, then the state matrix A = A4, and the state feedback row vector F = F4;

[0086] 5) If δ″ = π + δ0, then the state matrix A = A5, and the state feedback row vector F = F5;

[0087] The closed-loop T-S fuzzy model of the grid-connected synchronization control system is shown as follows:

[0088]

[0089] where i = 1, 2, 3, 4, 5, x = [δα] T , γ = [k p L g I c ω s / (1 - k p L g I c )k i L g I c ω s / (1 - k p L g I c )] T .

[0090] The obtained T-S fuzzy model is simulated and compared with the traditional phase-locked loop without PDC by giving different initial phase angles. The initial phase angles are given as 0, 0.6π, and 0.9π respectively. The simulation results are shown as Figure 5 (a)-(b), 6(a)-(b), 7(a)-(b). It can be seen that the phase-locked loop with PDC has a faster adjustment speed when the initial phase angle is 0 and successfully locks the phase near 0.03 s, while the traditional phase-locked loop takes 0.04 s to successfully lock the phase. When the initial phase angle of the phase-locked loop is 0.6π, the traditional phase-locked loop loses the phase-locking ability and is unstable, while the phase-locked loop with PDC can continue to work stably. When the initial phase angle of the phase-locked loop is 0.9π, the traditional phase-locked loop loses the phase-locking ability and is unstable, while the phase-locked loop with PDC can continue to work stably.

[0091] In summary, for the nonlinear parallel distributed compensation method of the grid-connected synchronization control system in the above embodiments, after adding PDC to the traditional phase-locked loop, the phase-locked loop can have a faster phase-locking speed at the original stable operating point and can continue to maintain stable phase-locking at the unstable operating point. Therefore, the proposed phase-locked loop with PDC is of great significance for improving the stability of the grid-connected synchronization control system.

[0092] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A non-linear parallel distributed compensation method for a grid-connected synchronization control system, characterized in that, It includes the following steps: S1: Establish a large-signal model of the grid-connected synchronization control system; In the step S1, the large-signal model of the grid-connected synchronization control system is as follows: Among them, the state variable δ = θ pll - ω s t, θ pll is the phase angle output by the phase-locked loop, ω s is the angular velocity of the power grid, α is the output of the phase-locked loop integrator, k p is the proportional coefficient of the phase-locked loop, k i is the integral coefficient of the phase-locked loop, L g is the line inductive reactance, V g is the amplitude of the power grid voltage, is the initial phase angle of the power grid voltage; S2: Obtain its Jacobian matrix J according to the large-signal model of the grid-connected synchronization control system in step S1; In the step S2, the Jacobian matrix J is as follows: S3: Select its linearization point according to the Jacobian matrix J of the grid-connected synchronization control system determined in step S2; S4: Determine the state space A of the grid-connected synchronization control system according to the linearization points selected in step S3 i and the membership function ω i , where i = 1, 2, 3, 4, 5, and process the state variable δ so that δ″ ∈ (-π + δ0, π + δ0); S5: According to the state space A in step S4 i , membership function ω i , establish an open-loop T-S fuzzy model of the grid-connected synchronization control system with multi-point linearization; S6: According to the open-loop T-S fuzzy model of the grid-connected synchronization control system in step S5, add the state feedback F i x to V pccq after that, where x is the system state, determine the input matrix B, and V pccq is the q-axis component of the grid-connected point of common coupling voltage V pcc after Park transformation; S7: Design the state feedback row vector F according to step S6 i , such that A i - BF i has negative eigenvalues; S8: Determine the fuzzy rules and the closed-loop T-S fuzzy model of the grid-connected synchronization control system according to the above steps.

2. The non-linear parallel distributed compensation method for a grid-connected synchronization control system according to claim 1, characterized in that: In the step S3, in order to enable the initial operating points within 2π of one cycle of the output phase angle of a phase-locked loop to be stable, the linearization points are selected as δ1 = -π + δ0, δ2 = -0.5π + δ0, δ3 = δ0, δ4 = 0.5π + δ0, δ5 = π + δ0, where δ0 is the steady-state value of δ.

3. A non-linear parallel distributed compensation method for a grid-connected synchronization control system according to claim 1, characterized in that: In the step S4, the state space A i The expression is as follows: Membership function ω i The expression is as follows:

4. A non-linear parallel distributed compensation method for a grid-connected synchronization control system according to claim 3, characterized in that: In the step S4, the state variable δ is processed as shown in the following formula: where δ' is the remainder of δ divided by 2π.

5. A non-linear parallel distributed compensation method for a grid-connected synchronous control system according to claim 4, characterized in that: In the step S5, the open-loop T-S fuzzy model of the grid-connected synchronization control system is as shown in the following formula: where x = [δα] T , γ = [k p L g I c ω s / (1 - k p L g I c )k i L g I c ω s / (1 - k p L g I c )] T .

6. A non-linear parallel distributed compensation method for a grid-connected synchronization control system according to claim 5, characterized in that: In the step S6, the state feedback F i x is added to V pccq After that, the input matrix B = [k p k i T .​ 7. A non-linear parallel distributed compensation method for a grid-connected synchronization control system according to claim 6, characterized in that: In the step S7, design the state feedback row vector F i such that all the eigenvalues of the new state matrix A i - BF i have negative real parts, and make the first element in the row vector F3 be 0.

8. A non-linear parallel distributed compensation method for a grid-connected synchronization control system according to claim 7, characterized in that: In the step S8, the fuzzy rules are as follows: If δ″ = -π + δ0, then the state matrix A = A1 and the state feedback row vector F = F1; If δ″ = -0.5π + δ0, then the state matrix A = A2 and the state feedback row vector F = F2; If δ″ = δ0, then the state matrix A = A3 and the state feedback row vector F = F3; If δ″ = 0.5π + δ0, then the state matrix A = A4 and the state feedback row vector F = F4; If δ″ = π + δ0, then the state matrix A = A5 and the state feedback row vector F = F5; The closed-loop T-S fuzzy model of the grid-connected synchronization control system is as follows:

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