Networking type inverter field station distributed cooperative control method based on passivity

Abstract

The invention discloses a passivity-based distributed cooperative control method for a network-building type inverter field station, and belongs to the field of electrical engineering. According to the distributed cooperative control method, a port controlled Hamiltonian method is utilized to design inner ring controllers of network-building type inverters, a nonlinear observer is introduced to ensure the stability of a new energy station, and in addition, a pole assignment method is utilized to determine ideal injection damping parameters of the network-building type inverters in different power grid states. And the dynamic performance of the network-building type inverter station is improved. The method is not only simple to implement, but also solves the problem that the overall dynamic performance of the field station is difficult to consider under the traditional passive control of the inverters in a multi-inverter scene in the network construction type inverter field station, and effectively improves the dynamic performance of the inverter field station under the complex power grid change.

Description

Technical Field

[0001] The present invention belongs to the field of electrical engineering and relates to a distributed collaborative control method for grid-type inverter stations based on passivity. Background Art

[0002] As the key interface for grid-connected renewable energy generation, the control performance of grid-connected inverters is crucial for multi-inverter power plants. Currently, many researchers have proposed grid-connected inverter control. These inverters are capable of supporting both grid frequency and voltage, making them a prominent area of current research and a key trend in the development of large-scale renewable energy integration. Currently, these inverters typically employ linear controllers, such as proportional-integral control, which are designed based on linear theory. However, when nonlinear changes occur in the grid due to the instability and volatility of renewable energy sources, such as the plug-and-play of inverters in multi-inverter power plants, large fluctuations in grid impedance, and random variations in inverter operating points, the structure and parameters of the grid vary randomly. In such cases, control schemes based on linear theory may fail to ensure system stability. Previous research has shown that problems such as broadband oscillations in the nonlinear frequency domain can arise, posing significant stability challenges.

[0003] The article entitled "A Review of Hybrid Control of Grid-following / Grid-forming Modes for Grid-connected Converters with High Penetration Renewable Energy Generation" (Zhang Xing, Zhan Xiangdui, Wu Mengze, et al. A Review of Hybrid Control of Grid-following / Grid-forming Modes for Grid-connected Converters with High Penetration Renewable Energy Generation [J]. Automation of Electric Power Systems, 2024, 48(21): 1-15.) introduces the characteristics of inverter control using grid-following and grid-forming modes. Among them, in the context of high penetration of new energy, new energy stations are often in a weak power grid environment at the end. The stability of traditional grid-following control of inverters is poor, while grid-forming control has better stability. However, when the grid structure and parameters change randomly and over a large range, it still faces the challenge of maintaining stable operation. The resonance and instability problems of multi-inverter power stations in the station still exist. Multi-inverter power stations using conventional grid-forming control are prone to nonlinear oscillation problems and cannot guarantee stability under nonlinear disturbances.

[0004] To address high grid impedance and nonlinear grid structure / parameter changes, existing research has proposed passive control based on nonlinear control theory. However, this approach is not suitable for the distributed coordinated control of multiple inverters within a grid-connected inverter station. For example:

[0005] 1) In the paper entitled “Distributed Coordinated Control for Stabilization of Multi-Inverter Power Plant” (M. Li, H. Geng and X. Zhang, “Distributed Coordinated Control for Stabilization of Multi-Inverter Power Plant,” in IEEE Transactions on Industrial Electronics, vol. 70, no. 12, pp. 12421-12430, Dec. 2023), a passive controller was designed for grid-following inverters, achieving distributed coordinated and stable operation of grid-following inverter stations and adapting to changes in nonlinear grid structure / parameters. However, there is still a gap in the design of passive controllers for grid-following inverter control.

[0006] 2) Invention patent: Data-driven grid-connected inverter grid-connected passive control parameter optimization method (publication number CN118264144A) designs a passive controller for grid-connected inverters and a method for optimizing injection damping parameters using a particle swarm algorithm. However, its design only involves the control parameters of a single inverter and cannot be applied to a grid-connected inverter station composed of multiple grid-connected inverters, nor can it guarantee the synergistic effect between multiple grid-connected inverters.

[0007] 3) Invention patent: A control parameter optimization method and optimization device for a grid-type new energy power generation system (publication number CN116404691A) designs a passive controller for a grid-type inverter and uses the D-splitting method to design parameters. However, it also only involves the design of control parameters for a single inverter and cannot be applied to grid-type inverter stations.

[0008] In summary, the existing technology has the following problems:

[0009] (1) The existing grid-type inverter control technology lacks the ability to cope with nonlinear grid states and parameter changes, especially in multi-inverter sites, where it is difficult to take into account the control performance of each inverter;

[0010] (2) The nonlinear distributed passive control strategy for multi-inverter stations proposed in the prior art only involves grid-following inverters, while there is still a gap in the passive control design corresponding to grid-forming inverters. Summary of the Invention

[0011] The technical problem to be solved by the present invention is that traditional grid-type control is difficult to cope with the nonlinear changes in grid status and parameters, and the dynamic performance between multiple inverters within the station is difficult to coordinate. Therefore, it is necessary to propose a nonlinear grid-type distributed collaborative control.

[0012] The object of the present invention is achieved as follows. The present invention provides a distributed collaborative control method for a grid-type inverter station based on passivity, wherein the grid-type inverter station refers to a power generation station composed of n grid-type inverters with the same structure, wherein each grid-type inverter includes a DC side power supply, a three-phase inverter, and an LC filter connected in series in sequence, and the output ends of the n grid-type inverters are connected in parallel to the three-phase grid via a grid inductor; the steps of the collaborative control method are as follows:

[0013] Step 1: Establish a mathematical model of the voltage and current inner loop of the grid-type inverter and record it as the inner loop mathematical model;

[0014] Step 2: Based on the inner loop mathematical model described in step 1, establish a controlled Hamiltonian model of the inner loop port of the grid-type inverter and record it as the inner loop Hamiltonian model; define the interconnection matrix J(x), the damping matrix R(x) and the Hamiltonian function H(x), where x is the state variable matrix;

[0015] Step 3, define a nonlinear observer loop based on the port-controlled Hamiltonian form, denoted as nonlinear observer;

[0016] Step 4: Establish the desired interconnection matrix J d (x) and the expected damping matrix R d (x) is:

[0017]

[0018] Among them, J a (x) is the injection interconnection matrix, R a (x) is the injection damping matrix, the injection damping matrix R a (x) is related to the voltage loop injection damping r1 and the current loop injection damping r2, which are unknown parameters.

[0019] Step 5: Define the state variable matrix x and the expected state variable matrix x respectively. d and the closed-loop Hamiltonian function H d (xx d );

[0020] Step 6: Based on the inner-loop Hamiltonian model, the nonlinear observer and the closed-loop Hamiltonian function, the expected closed-loop Hamiltonian model is established, and its expression is:

[0021]

[0022] in, is the differential of the state variable matrix, is the differential of the expected state variable matrix;

[0023] The voltage and current inner loop passive controller of the grid-type inverter is designed based on the expected closed-loop Hamiltonian model, so that the grid-type inverter station meets the passivity and ensures the stable operation of the grid-type inverter station.

[0024] Step 7: Use the pole placement method to design parameter adaptive laws for the voltage loop injection damping r1 and the current loop injection damping r2 to achieve distributed collaborative control among multiple grid-type inverters in the grid-type inverter station and optimize the dynamic performance of the grid-type inverter station.

[0025] Preferably, the expression of the inner loop mathematical model in step 1 is:

[0026]

[0027] Among them, L is the inductance of the filter inductor, C is the capacitance of the filter capacitor, i d is the d-axis component of the inverter output current, i q is the q-axis component of the inverter output current, is the time derivative of the d-axis component of the inverter output current, is the time derivative of the q-axis component of the inverter output current, v Cd is the d-axis component of the inverter output voltage, v Cq is the q-axis component of the inverter output voltage, is the time derivative of the d-axis component of the inverter output voltage, is the time derivative of the q-axis component of the inverter output voltage, ω is the angular frequency, i gd is the d-axis component of the grid-side current, i gq is the q-axis component of the grid-side current, r f is the parasitic resistance of the filter inductor, v d is the d-axis component of the inverter modulation voltage, v q is the q-axis component of the inverter modulation voltage, γ vd is the d-axis component of the voltage loop disturbance, γ vq is the q-axis component of the voltage loop disturbance, γ id is the d-axis component of the current loop disturbance, γ iq is the q-axis component of the current loop disturbance.

[0028] Preferably, the expression of the inner loop Hamiltonian model in step 2 is:

[0029]

[0030] Among them, u c is the control input matrix, g c is the control input matrix coefficient matrix, u e is the external input matrix, g e is the external input matrix coefficient matrix, p is the unknown perturbation matrix, g p is the unknown perturbation matrix coefficient matrix, H(x) is the Hamiltonian function, J(x) is the interconnection matrix, and R(x) is the damping matrix;

[0031] The expressions of the interconnection matrix J(x) and the damping matrix R(x) are:

[0032]

[0033] Define the Hamiltonian function H(x) as:

[0034]

[0035] Preferably, the expression of the nonlinear observer in step 3 is:

[0036]

[0037] in, is the observation value of the state variable matrix, is the differential of the observation value of the state variable matrix, is the observed value of the unknown perturbation matrix, is the differential of the observation value of the unknown disturbance matrix, k1 is the first observer gain coefficient, k2 is the second observer gain coefficient, J d (x) is the desired interconnection matrix, R d (x) is the desired damping matrix.

[0038] Preferably, the injection interconnection matrix J in step 4 a (x) and the injection damping matrix R a (x) is defined as:

[0039]

[0040] Preferably, the state variable matrix x and the expected state variable matrix x in step 5 are d and the closed-loop Hamiltonian function H d (xx d ) are defined as follows:

[0041]

[0042] in, is the desired inverter output current d-axis component, is the desired inverter output current q-axis component, is the desired inverter output voltage d-axis component, is the q-axis component of the desired inverter output voltage, the superscript T represents the matrix transpose; Q is the filter parameter matrix, Q = diag(L, L, C, C).

[0043] Preferably, the specific steps of step 7 are as follows:

[0044] Step 7.1: Establish the voltage loop open loop continuous domain transfer function G of the voltage and current inner loop passive controller v (s) and the current loop open-loop continuous domain transfer function G c (s), the expressions are:

[0045]

[0046] Where s is the Laplace operator;

[0047] According to G v (s) and G c (s), and multiply them to obtain the overall open-loop continuous domain transfer function G of the voltage and current inner loop passive controller. i (s), whose expression is:

[0048] G i (s)=G v (s)·G c (s)=r1r2+(r1L+r2C)s+LCs 2 ;

[0049] Step 7.2, calculate the overall open-loop continuous domain transfer function G of the voltage and current inner loop passive controller i (s) The overall open-loop discrete domain transfer function G of the voltage and current inner loop passive controller is obtained by using the backward Euler method. i (z), its expression is:

[0050]

[0051] Among them, T s is the sampling period, z is the discrete domain variable, s is the Laplace operator;

[0052] Step 7.3: Establish the discrete domain transfer function G of the inverter side current to the inverter output voltage LCL (z), its expression is:

[0053]

[0054] Among them, ω r is the resonant frequency, a is the first simplification coefficient, b is the second simplification coefficient, L g is the inductance value of the grid;

[0055] Step 7.4: According to the overall open-loop discrete domain transfer function G of the voltage and current inner loop passive controller described in step 7.2, i (z) and the discrete domain transfer function GL of the inverter side current to the inverter output voltage described in step 7.3 CL (z), calculate the closed-loop discrete domain transfer function G(z) of the controller, which is expressed as:

[0056] G(z)=z -1 G i (z)G LCL (z) / [1+z -1 G i (z)G LCL (z)];

[0057] Step 7.5: Based on the controller closed-loop discrete domain transfer function G(z), obtain the controller closed-loop discrete domain characteristic equation A c (z -1 )for:

[0058]

[0059] Step 7.6: Select the desired poles of the closed-loop discrete domain characteristic equation of the controller, and define the dominant pole z1, dominant pole z2, non-dominant pole z3, non-dominant pole z4, non-dominant pole z5, and non-dominant pole z6, respectively. The expressions are:

[0060]

[0061] Where ξ is the damping ratio, ω n is the natural frequency, j is the imaginary unit, and m is the non-dominant pole coefficient;

[0062] Step 7.7, based on the expected poles of the discrete domain characteristic equation in step 7.6, obtain the controller's expected closed-loop discrete domain characteristic equation A m (z -1 ), the expression is:

[0063]

[0064] Step 7.8: According to the closed-loop discrete domain characteristic equation of the controller described in step 7.5 and the expected closed-loop discrete domain characteristic equation of the controller described in step 7.7, set A m (z -1 )=A c (z -1 ), realize pole configuration, establish voltage loop injection damping r1 and current loop injection damping r2 and grid inductance L g The mathematical relationship between

[0065] Assume that the current loop injection damping r2 and the grid inductance L g As a known quantity, find two types of constraint relationships of voltage loop injection damping with respect to r1. Define the first constraint relationship as r1=f(r2,L g ), whose expression is:

[0066]

[0067] Define the second constraint relationship as r1=g(r2,L g ), whose expression is:

[0068]

[0069] Step 7.9: According to the two types of constraint relations r1=f(r2, L g ) and r1=g(r2,L g ), and obtain the grid inductance L corresponding to each inverter in the grid-type inverter station. g The corresponding values of r1 and r2 that meet the expected dynamic performance are determined to achieve distributed collaborative control among the inverters.

[0070] Compared with the prior art, the present invention has the following beneficial effects:

[0071] 1. The grid-type inverter control method provided by the present invention is simple to implement. It only requires adaptively adjusting the injection damping according to the grid impedance after designing the controller to improve the dynamic performance of the grid-type inverter.

[0072] 2. The passive controller designed based on nonlinear theory can keep the inverter stable under complex nonlinear changes in grid conditions and parameters. Its stability in high-penetration new energy grids is superior to controllers designed under traditional linear frameworks.

[0073] 3. The present invention introduces a nonlinear state observer into the voltage and current inner loop controller of the grid-type inverter, which can effectively deal with unknown external disturbances of the inverter and achieve error-free tracking of the inverter output. At the same time, the nonlinear state observer is based on a passive design and remains stable.

[0074] 4. The passive controller and injection damping adaptive adjustment method designed in the present invention are designed from a multi-machine perspective. In an inverter station containing a large number of meshed inverters, distributed collaborative control of each inverter can be implemented, thereby reducing mutual interference between the inverters and ensuring that the station as a whole has good dynamic performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 This is the structural diagram of the grid-type inverter station described in the present invention.

[0076] Figure 2 This is the control block diagram of the distributed collaborative control method described in the present invention.

[0077] Figure 3 This is a curve diagram showing the relationship between the injection damping value and the grid inductance according to the present invention.

[0078] Figure 4 This is the simulation waveform diagram using the fixed injection damping control method.

[0079] Figure 5 This is a simulation waveform diagram of the distributed collaborative control method of the present invention. DETAILED DESCRIPTION

[0080] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0081] Figure 1 This is the structural diagram of the grid-type inverter station described in the present invention, consisting of Figure 1 It can be seen that the grid-type inverter station refers to a power generation station composed of n grid-type inverters with the same structure, wherein each grid-type inverter includes a DC side power supply, a three-phase inverter and an LC filter connected in series in sequence, and the output ends of the n grid-type inverters are connected in parallel to the three-phase grid through the grid inductor.

[0082] exist Figure 1 In, V DC is the DC side voltage, 1# is the number of the first inverter, 2# is the number of the second inverter, and n# is the number of the nth inverter.

[0083] Figure 2 This is the control block diagram of the distributed collaborative control method of the present invention. Figure 2 It can be seen that the present invention provides a distributed cooperative control method for grid-type inverter stations based on passivity, which includes the following steps. Steps 1, 2 and 6 are the establishment of the voltage and current inner loop passive controller, steps 3 to 5 are the establishment of the nonlinear observer, step 7 is the adaptive damping cooperative link, u e As a control signal input to Figure 1In the corresponding three-phase inverter, control of the three-phase inverter is realized.

[0084] Step 1: Establish a mathematical model of the voltage and current inner loop of the grid-type inverter and record it as the inner loop mathematical model.

[0085] In this embodiment, the inner loop mathematical model is expressed as:

[0086]

[0087] Among them, L is the inductance of the filter inductor, C is the capacitance of the filter capacitor, i d is the d-axis component of the inverter output current, i q is the q-axis component of the inverter output current, is the time derivative of the d-axis component of the inverter output current, is the time derivative of the q-axis component of the inverter output current, v Cd is the d-axis component of the inverter output voltage, v Cq is the q-axis component of the inverter output voltage, is the time derivative of the d-axis component of the inverter output voltage, is the time derivative of the q-axis component of the inverter output voltage, ω is the angular frequency, i gd is the d-axis component of the grid-side current, i gq is the q-axis component of the grid-side current, r f is the parasitic resistance of the filter inductor, v d is the d-axis component of the inverter modulation voltage, v q is the q-axis component of the inverter modulation voltage, γ vd is the d-axis component of the voltage loop disturbance, γ vq is the q-axis component of the voltage loop disturbance, γ id is the d-axis component of the current loop disturbance, γ iq is the q-axis component of the current loop disturbance.

[0088] Step 2: Based on the inner loop mathematical model described in step 1, establish a controlled Hamiltonian model of the inner loop port of the meshed inverter and record it as the inner loop Hamiltonian model; define the interconnection matrix J(x), the damping matrix R(x) and the Hamiltonian function H(x), where x is the state variable matrix.

[0089] In this embodiment, the expression of the inner loop Hamiltonian model is:

[0090]

[0091] Among them, x represents the state variable matrix, u c is the control input matrix, g c is the control input matrix coefficient matrix, u e is the external input matrix, ge is the external input matrix coefficient matrix, p is the unknown perturbation matrix, g p is the unknown perturbation matrix coefficient matrix, H(x) is the Hamiltonian function, J(x) is the interconnection matrix, and R(x) is the damping matrix.

[0092] The expressions of the interconnection matrix J(x) and the damping matrix R(x) are:

[0093]

[0094] Define the Hamiltonian function H(x) as:

[0095]

[0096] Step 3: Define a nonlinear observer loop based on the port-controlled Hamiltonian form, denoted as the nonlinear observer.

[0097] In this embodiment, the expression of the nonlinear observer is:

[0098]

[0099] in, is the observation value of the state variable matrix, is the differential of the observation value of the state variable matrix, is the observed value of the unknown perturbation matrix, is the differential of the observed value of the unknown disturbance matrix, k1 is the first observer gain coefficient, k2 is the second observer gain coefficient, x d is the expected state variable matrix, H d (xx d ) is the closed-loop Hamiltonian function, J d (x) is the desired interconnection matrix, R d (x) is the desired damping matrix.

[0100] Step 4: Establish the desired interconnection matrix J d (x) and the expected damping matrix R d (x) is:

[0101]

[0102] Among them, J a (x) is the injection interconnection matrix, R a (x) is the injection damping matrix, the injection damping matrix R a (x), voltage loop injection damping r1 and current loop injection damping r2 are related, and voltage loop injection damping r1 and current loop injection damping r2 are unknown parameters;

[0103] In this embodiment, the injection interconnection matrix Ja (x) and the injection damping matrix R a (x) is defined as:

[0104]

[0105] Step 5: Define the state variable matrix x and the expected state variable matrix x respectively. d and the closed-loop Hamiltonian function H d (xx d ).

[0106] In this embodiment, the state variable matrix x and the expected state variable matrix x d and the closed-loop Hamiltonian function H d (xx d ) are defined as follows:

[0107]

[0108]

[0109] in, is the desired inverter output current d-axis component, is the desired inverter output current q-axis component, is the desired inverter output voltage d-axis component, is the q-axis component of the desired inverter output voltage, the superscript T represents the matrix transpose; Q is the filter parameter matrix, Q = diag(L, L, C, C).

[0110] Step 6: Based on the inner-loop Hamiltonian model, the nonlinear observer and the closed-loop Hamiltonian function, the expected closed-loop Hamiltonian model is established, and its expression is:

[0111]

[0112] in, is the differential of the state variable matrix, is the differential of the expected state variable matrix;

[0113] The voltage and current inner loop passive controller of the grid-type inverter is designed based on the expected closed-loop Hamiltonian model, so that the grid-type inverter station meets the passivity and ensures the stable operation of the grid-type inverter station.

[0114] Step 7: Use the pole placement method to design parameter adaptive laws for the voltage loop injection damping r1 and the current loop injection damping r2 to achieve distributed collaborative control among multiple grid-type inverters in the grid-type inverter station and optimize the dynamic performance of the grid-type inverter station.

[0115] In this embodiment, the specific steps of step 7 are as follows:

[0116] Step 7.1: Establish the voltage loop open loop continuous domain transfer function G of the voltage and current inner loop passive controller v (s) and the current loop open-loop continuous domain transfer function G c (s), the expressions are:

[0117]

[0118] Where s is the Laplace operator;

[0119] According to G v (s) and G c (s), and multiply them to obtain the overall open-loop continuous domain transfer function G of the voltage and current inner loop passive controller. i (s), whose expression is:

[0120] G i (s)=G v (s)·G c (s)=r1r2+(r1L+r2C)s+LCs 2 ;

[0121] Step 7.2, calculate the overall open-loop continuous domain transfer function G of the voltage and current inner loop passive controller i (s) The overall open-loop discrete domain transfer function G of the voltage and current inner loop passive controller is obtained by using the backward Euler method. i (z), its expression is:

[0122]

[0123] Among them, T s is the sampling period, z is the discrete domain variable, s is the Laplace operator;

[0124] Step 7.3: Establish the discrete domain transfer function G of the inverter side current to the inverter output voltage LCL (z), its expression is:

[0125]

[0126] Among them, ω r is the resonant frequency, a is the first simplification coefficient, b is the second simplification coefficient, L g is the inductance value of the grid;

[0127] Step 7.4: According to the overall open-loop discrete domain transfer function G of the voltage and current inner loop passive controller described in step 7.2, i(z) and the discrete domain transfer function G of the inverter side current to the inverter output voltage described in step 7.3 LCL (z), calculate the closed-loop discrete domain transfer function G(z) of the controller, which is expressed as:

[0128] G(z)=z -1 G i (z)G LCL (z) / [1+z -1 G i (z)G LCL (z)];

[0129] Step 7.5: Based on the controller closed-loop discrete domain transfer function G(z), obtain the controller closed-loop discrete domain characteristic equation A c (z -1 )for:

[0130]

[0131] Step 7.6: Select the desired poles of the closed-loop discrete domain characteristic equation of the controller, and define the dominant pole z1, dominant pole z2, non-dominant pole z3, non-dominant pole z4, non-dominant pole z5, and non-dominant pole z6, respectively. The expressions are:

[0132]

[0133] Where ξ is the damping ratio, ω n is the natural frequency, j is the imaginary unit, and m is the non-dominant pole coefficient;

[0134] Step 7.7, based on the expected poles of the discrete domain characteristic equation in step 7.6, obtain the controller's expected closed-loop discrete domain characteristic equation A m (z -1 ), the expression is:

[0135]

[0136] Step 7.8: According to the closed-loop discrete domain characteristic equation of the controller described in step 7.5 and the expected closed-loop discrete domain characteristic equation of the controller described in step 7.7, set A m (z -1 )=A c (z -1 ), realize pole configuration, establish voltage loop injection damping r1 and current loop injection damping r2 and grid inductance L g The mathematical relationship between

[0137] Assume that the current loop injection damping r2 and the grid inductance L gAs a known quantity, find two types of constraint relationships of voltage loop injection damping with respect to r1. Define the first constraint relationship as r1=f(r2,L g ), whose expression is:

[0138]

[0139] Define the second constraint relationship as r1=g(r2,L g ), whose expression is:

[0140]

[0141] Step 7.9: According to the two types of constraint relations r1=f(r2, L g ) and r1=g(r2,L g ), and obtain the grid inductance L corresponding to each inverter in the grid-type inverter station. g The corresponding values of r1 and r2 that meet the expected dynamic performance are determined to achieve distributed collaborative control among the inverters.

[0142] In order to verify the passivity-based distributed collaborative control method of grid-type inverter stations provided by the present invention, simulation was carried out.

[0143] In this simulation, n=2 is used, that is, two three-phase inverters are used for verification, which are respectively denoted as inverter 1 and inverter 2.

[0144] The relevant electrical parameters of this simulation are set as follows: Active power reference value P1 of inverter 1 * =20kW, active power reference value of inverter 2 Damping ratio ξ=0.707, natural frequency ω n =314rad / s, non-dominant pole coefficient m=10.

[0145] Figure 3 Figure 2 is a relationship curve between the injection damping values of inverter 1 and inverter 2 and the grid inductance under corresponding parameters. Different grid inductances correspond to different values of voltage loop injection damping r1 and current loop injection damping r2.

[0146] Figure 4 The power waveform when the same fixed injection damping parameters are used for the injection damping of inverter 1 and inverter 2. Figure 4 It can be seen that at time 1 second, the active power reference values of inverter 1 and inverter 2 increase the simulated disturbance, and the active power waveform has obvious oscillation.

[0147] Figure 5 The distributed cooperative control method of the present invention is used to inject damping into inverter 1 and inverter 2 to adaptively generate the power waveform at a given time. Figure 5It can be seen that at time 1 second, the active power reference values of inverter 1 and inverter 2 increase the simulated disturbance, and the active power waveform oscillation is effectively suppressed.

[0148] In summary, Figure 4 、 Figure 5 The simulation waveform shown is consistent with the results of the present invention, which effectively suppresses the active power oscillation under system disturbance conditions and improves the dynamic performance of the system.

Claims

1. A distributed collaborative control method for a grid-type inverter station based on passivity, wherein the grid-type inverter station refers to a power generation station composed of n grid-type inverters of the same structure, wherein each grid-type inverter includes a DC side power supply, a three-phase inverter, and an LC filter connected in series in sequence, and the output ends of the n grid-type inverters are connected in parallel to a three-phase grid via a grid inductor; characterized in that: The steps of the collaborative control method are as follows: Step 1: Establish a mathematical model of the voltage and current inner loop of the grid-type inverter and record it as the inner loop mathematical model; Step 2: Based on the inner loop mathematical model described in step 1, establish a controlled Hamiltonian model of the inner loop port of the grid-type inverter and record it as the inner loop Hamiltonian model; define the interconnection matrix J(x), the damping matrix R(x) and the Hamiltonian function H(x), where x is the state variable matrix; Step 3, define a nonlinear observer loop based on the port-controlled Hamiltonian form, denoted as nonlinear observer; Step 4: Establish the desired interconnection matrix J d (x) and the expected damping matrix R d (x) is: Among them, J a (x) is the injection interconnection matrix, R a (x) is the injection damping matrix, the injection damping matrix R a (x) is related to the voltage loop injection damping r1 and the current loop injection damping r2, which are unknown parameters. Step 5: Define the state variable matrix x and the expected state variable matrix x respectively. d and the closed-loop Hamiltonian function H d (xx d ); Step 6: Based on the inner-loop Hamiltonian model, the nonlinear observer and the closed-loop Hamiltonian function, the expected closed-loop Hamiltonian model is established, and its expression is: in, is the differential of the state variable matrix, is the differential of the expected state variable matrix; The voltage and current inner loop passive controller of the grid-type inverter is designed based on the expected closed-loop Hamiltonian model, so that the grid-type inverter station meets the passivity and ensures the stable operation of the grid-type inverter station. Step 7: Use the pole placement method to design parameter adaptive laws for the voltage loop injection damping r1 and the current loop injection damping r2 to achieve distributed collaborative control among multiple grid-type inverters in the grid-type inverter station and optimize the dynamic performance of the grid-type inverter station.

2. The distributed collaborative control method of grid-type inverter stations based on passivity according to claim 1 is characterized in that: The expression of the inner loop mathematical model in step 1 is: Among them, L is the inductance of the filter inductor, C is the capacitance of the filter capacitor, i d is the d-axis component of the inverter output current, i q is the q-axis component of the inverter output current, is the time derivative of the d-axis component of the inverter output current, is the time derivative of the q-axis component of the inverter output current, v Cd is the d-axis component of the inverter output voltage, v Cq is the q-axis component of the inverter output voltage, is the time derivative of the d-axis component of the inverter output voltage, is the time derivative of the q-axis component of the inverter output voltage, ω is the angular frequency, i gd is the d-axis component of the grid-side current, i gq is the q-axis component of the grid-side current, r f is the parasitic resistance of the filter inductor, v d is the d-axis component of the inverter modulation voltage, v q is the q-axis component of the inverter modulation voltage, γ vd is the d-axis component of the voltage loop disturbance, γ vq is the q-axis component of the voltage loop disturbance, γ id is the d-axis component of the current loop disturbance, γ iq is the q-axis component of the current loop disturbance.

3. The distributed collaborative control method of grid-type inverter stations based on passivity according to claim 2 is characterized in that: The expression of the inner loop Hamiltonian model in step 2 is: Among them, u c is the control input matrix, g c is the control input matrix coefficient matrix, u e is the external input matrix, g e is the external input matrix coefficient matrix, p is the unknown perturbation matrix, g p is the unknown perturbation matrix coefficient matrix, H(x) is the Hamiltonian function, J(x) is the interconnection matrix, and R(x) is the damping matrix; The expressions of the interconnection matrix J(x) and the damping matrix R(x) are: Define the Hamiltonian function H(x) as:

4. The distributed collaborative control method of grid-type inverter stations based on passivity according to claim 3 is characterized in that: The expression of the nonlinear observer in step 3 is: in, is the observed value of the state variable matrix, is the differential of the observation value of the state variable matrix, is the observed value of the unknown perturbation matrix, is the differential of the observation value of the unknown disturbance matrix, k1 is the first observer gain coefficient, k2 is the second observer gain coefficient, J d (x) is the desired interconnection matrix, R d (x) is the desired damping matrix.

5. The distributed collaborative control method of grid-type inverter stations based on passivity according to claim 4 is characterized in that: Step 4 injects the interconnection matrix J a (x) and the injection damping matrix R a (x) is defined as:

6. The distributed collaborative control method of grid-type inverter stations based on passivity according to claim 5 is characterized in that: The state variable matrix x and the expected state variable matrix x in step 5 are d and the closed-loop Hamiltonian function H d (xx d ) are defined as follows: in, is the desired inverter output current d-axis component, is the desired inverter output current q-axis component, is the desired inverter output voltage d-axis component, is the q-axis component of the desired inverter output voltage, the superscript T represents the matrix transpose; Q is the filter parameter matrix, Q = diag(L, L, C, C).

7. The distributed collaborative control method of grid-type inverter stations based on passivity according to claim 6 is characterized in that: The specific steps of step 7 are as follows: Step 7.1: Establish the voltage loop open loop continuous domain transfer function G of the voltage and current inner loop passive controller v (s) and the current loop open-loop continuous domain transfer function G c (s), the expressions are: Where s is the Laplace operator; According to G v (s) and G c (s), and multiply them to obtain the overall open-loop continuous domain transfer function G of the voltage and current inner loop passive controller. i (s), whose expression is: G i (s)=r1r2+(r1L+r2C)s+LCs 2 ; Step 7.2, calculate the overall open-loop continuous domain transfer function G of the voltage and current inner loop passive controller i (s) The overall open-loop discrete domain transfer function G of the voltage and current inner loop passive controller is obtained by using the backward Euler method. i (z), its expression is: Among them, T s is the sampling period, z is the discrete domain variable, s is the Laplace operator; Step 7.3: Establish the discrete domain transfer function G of the inverter side current to the inverter output voltage LCL (z), its expression is: Among them, ω r is the resonant frequency, a is the first simplification coefficient, b is the second simplified coefficient, L g is the inductance value of the grid; Step 7.4: According to the overall open-loop discrete domain transfer function G of the voltage and current inner loop passive controller described in step 7.2, i (z) and the discrete domain transfer function G of the inverter side current to the inverter output voltage described in step 7.3 LCL (z), calculate the closed-loop discrete domain transfer function G(z) of the controller, which is expressed as: G(z)=z -1 G i (z)G LCL (z) / [1+z -1 G i (z)G LCL (z)]; Step 7.5: Based on the controller closed-loop discrete domain transfer function G(z), obtain the controller closed-loop discrete domain characteristic equation A c (z -1 )for: Step 7.6: Select the desired poles of the closed-loop discrete domain characteristic equation of the controller, and define the dominant pole z1, dominant pole z2, non-dominant pole z3, non-dominant pole z4, non-dominant pole z5, and non-dominant pole z6, respectively. The expressions are: Where ξ is the damping ratio, ω k is the natural frequency, j is the imaginary unit, and m is the non-dominant pole coefficient; Step 7.7, based on the expected poles of the discrete domain characteristic equation in step 7.6, obtain the controller's expected closed-loop discrete domain characteristic equation A m (z -1 ), the expression is: Step 7.8: According to the closed-loop discrete domain characteristic equation of the controller described in step 7.5 and the expected closed-loop discrete domain characteristic equation of the controller described in step 7.7, set A m (z -1 )=A c (z -1 ), realize pole configuration, establish voltage loop injection damping r1 and current loop injection damping r2 and grid inductance L g The mathematical relationship between Assume that the current loop injection damping r2 and the grid inductance L g For v, we can find two types of constraints on voltage loop injection damping with respect to r1. The first constraint is defined as r1 = f(r2, L g ), whose expression is: Define the second constraint relationship as r1=g(r2,L g ), whose expression is: Step 7.9: According to the two types of constraint relations r1=f(r2,L g ) and r1=g(r2,L g ), and obtain the grid inductance L corresponding to each inverter in the grid-type inverter station. g The corresponding values of r1 and r2 that meet the expected dynamic performance are determined to achieve distributed collaborative control among the inverters.

Images