A grid-connected inverter control method based on a parametric variational method

Abstract

The application discloses a grid-connected inverter control method based on a parameter variation method. Wherein, the method comprises: establishing a synchronization optimal objective function based on Hamilton action minimum for grid-forming inverters and grid-following inverters respectively; obtaining a regular equation of a system functional extreme condition based on the parameter variation method according to the optimal objective function; constructing an optimal synchronization strategy of the grid-forming inverters and the grid-following inverters respectively according to the regular equation, and adjusting corresponding optimal parameters to control the grid-connected inverters. The technical scheme solves the synchronization stability problem of the grid-connected inverters in the current power system.

Description

Technical Field

[0001] This application relates to the field of new energy power generation, and in particular to the stability control of grid-connected inverters. Background Technology

[0002] In traditional power systems, the constitutive relationship of power regulation of synchronous generators is constrained by the fundamental theorem of macroscopic electrodynamics at the power frequency scale. Power supply or distribution circuits and systems are receiving increasing attention, especially with the development of new energy technologies and the integration of more power supply types into the grid. When multiple inverters are connected in parallel, system instability is prone to occur in practice due to variations in grid impedance in distributed systems and the mutual coupling between multiple inverters. Currently, grid-connected inverters in power systems exhibit poor synchronization stability. Summary of the Invention

[0003] This application provides a grid-connected inverter control method based on parametric variational method, which can solve the synchronization stability problem of grid-connected inverters in the current power system.

[0004] In a first aspect, embodiments of this application provide a grid-connected inverter control method based on the parametric variational method, including:

[0005] Step 1: Establish the synchronization optimal objective function based on minimizing Hamiltonian action for both grid-connected inverters and follow-up inverters;

[0006] Step 2: Based on the optimal objective function, obtain the regularity conditions for the extremum conditions of the system functional based on the parametric variational method;

[0007] Step 3: Construct optimal synchronization strategies for grid-connected inverters and grid-linked inverters respectively based on regularity conditions, and set the corresponding optimal parameters to control the grid-connected inverters.

[0008] Preferably, establishing the synchronization optimal objective function based on minimizing Hamiltonian action for both grid-connected and grid-linked inverters includes:

[0009] Step 1.1: Construct the optimal objective function for a first-order power point tracking inverter based on minimizing the Hamiltonian action using the time-domain integral of the Lagrange function; the Lagrange equation for the non-conservative system is as follows:

[0010] In the formula, q k Let Q be the generalized coordinate, where is the generalized velocity. k Let L represent the projection of the nonconservative forces of the system onto the generalized coordinate system; L represents the Lagrange energy function of the system, which is defined as the difference between the system's kinetic and potential energy.

[0011] L = TV (2)

[0012] In the formula, T is the kinetic energy. It is a function of generalized velocity; V is potential energy, a function of generalized position; construct the kinetic / potential energy expression for first-order power tracking control based on Hooke's elasticity law:

[0013]

[0014] Define the optimal objective function as the time-domain integral of the Lagrange function:

[0015]

[0016] Step 1.2: Construct the optimal objective function for a second-order grid-type inverter, i.e., a second-order power point tracking inverter; construct the kinetic / potential energy expression for second-order power point tracking control based on Newton's second law for a simple pendulum system:

[0017]

[0018] Define the optimal objective function as the time-domain integral of the Lagrange function:

[0019]

[0020] Step 1.3: Construct the optimal objective function for the voltage tracking inverter;

[0021] By employing the time-domain integral of the Lagrange function, an optimal objective function for a voltage tracking inverter based on minimizing the Hamiltonian action is constructed. Kinetic energy characterizes the tracking error between the converter output frequency and the grid voltage frequency, while potential energy characterizes the q-axis voltage v at the PCC. PCCq The difference between it and its reference value:

[0022]

[0023] Where C represents the voltage tracking error weighting factor in the optimal function, and the objective function is defined as the time-domain integral of the Lagrange function:

[0024]

[0025] Preferably, the canonical equations for obtaining the extremum conditions of the system functional based on the parametric variational method, according to the optimal objective function, include:

[0026] Step 2.1: Construct the regularization conditions for a first-order grid-type inverter;

[0027] Based on the fundamental principle of parametric variation, the regularity condition corresponding to the minimum Hamiltonian action of the system can be determined:

[0028]

[0029] Combining (3)-(4) and (9), we can obtain the first canonical condition for a first-order grid inverter:

[0030]

[0031] Step 2.2: Construct the regularity conditions for optimal synchronization control of the second-order grid inverter;

[0032] Based on the fundamental principle of parametric variation, the regularity condition corresponding to the minimum Hamiltonian action of the system can be determined:

[0033]

[0034] Combining (5)-(6) and (11), we can obtain the second regularity condition for optimal synchronization control of a second-order grid inverter:

[0035]

[0036] Step 2.3: Construct the regularization conditions for the grid-connected inverter;

[0037] Based on the fundamental principle of parametric variation, the regularity condition corresponding to the minimum Hamiltonian action of the system can be determined:

[0038]

[0039] Combining (7)-(8) and (13), we can obtain the regularity condition for optimal synchronization control of the grid-connected inverter:

[0040]

[0041] Preferably, the step of constructing optimal synchronization strategies for grid-connected inverters and grid-linked inverters based on canonical equations, and adjusting the corresponding optimal parameters to control the grid-connected inverters, includes:

[0042] Step 3.1 Construct the optimal control strategy and set the optimal parameters for the first-order grid-type inverter;

[0043] Further simplification and derivation from (10) yields the optimal control strategy for a first-order grid-type inverter as follows:

[0044]

[0045] Where the optimal sagging coefficient m p for:

[0046]

[0047] Step 3.2 Derivation of the optimal control strategy and tuning of the optimal parameters for the second-order grid inverter. Further simplification of (12) yields the optimal control strategy for the second-order grid inverter as follows:

[0048]

[0049] Step 3.3: Set the optimal control strategy and optimal parameters for the grid-type inverter.

[0050] Further simplification and derivation from (14) yields the optimal control strategy for the grid-connected inverter as follows:

[0051] ω=+K p v PCCq +K i ∫v PCCq [v PCCd +(ω+ω g )L g I g ]dt (18)

[0052] The optimal proportionality coefficient K p =CL g I g / M, optimal integration coefficient K i =C / M.

[0053] The optimal control strategy and corresponding optimal parameters are applied to the grid-connected inverter control.

[0054] The beneficial effects of the technical solutions provided in some embodiments of this application include at least the following: establishing optimal synchronization objective functions based on minimizing Hamiltonian action for both grid-connected and grid-linked inverters; obtaining canonical equations for the system functional extremum conditions based on parametric variational methods according to the optimal objective functions; constructing optimal synchronization strategies for grid-connected and grid-linked inverters respectively based on the canonical equations, and tuning the corresponding optimal parameters to control the grid-connected inverters. This technical solution addresses the synchronization stability problem existing in grid-connected inverters in current power systems. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 This is a flowchart illustrating a grid-connected inverter control method based on parametric variational method, provided in an embodiment of this application. Detailed Implementation

[0057] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0058] The terms "first," "second," "third," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0059] To achieve the above objectives, the present invention employs a method for deriving the optimal synchronization mechanism of a grid-connected inverter based on the parametric variational method, comprising the following steps:

[0060] Step 1: Establish the synchronization optimal objective function based on minimizing Hamiltonian action for both grid-connected inverters and follow-up inverters.

[0061] Step 2: Based on the optimal objective function, obtain the canonical equations for the system functional extremum conditions based on the parametric variational method. For both grid-connected and grid-linked inverters, derive methods for the system functional extremum (optimal synchronous control) conditions (canonical equations) based on the parametric variational method are proposed.

[0062] Step 3: Construct optimal synchronization strategies for grid-connected inverters and grid-linked inverters respectively based on the canonical equations, and tune the corresponding optimal parameters to control the grid-connected inverters. Using the canonical conditions proposed in Step 2, derive the optimal synchronization strategies for grid-connected inverters and grid-linked inverters respectively, and tune the corresponding optimal parameters.

[0063] The purpose of this invention is based on the parametric variational principle to construct a power balance control mechanism for power-electronic power systems, establish a synchronization mechanism theory and method for grid-connected inverters, and reveal the coordination law under the action of the synchronization mechanism during the dynamic stability process of power-electronic power systems. This research can provide a new theoretical basis for the connection of grid-connected inverters in power-electronic power systems, and is expected to further develop new grid-connected inverter synchronization mechanisms, laying a solid theoretical foundation for overcoming current problems such as synchronization stability and wideband oscillations.

[0064] In the above derivation method of the optimal synchronization mechanism for grid-connected inverters based on the parametric variational method, the implementation of step 1 includes:

[0065] Step 1.1: Derive the optimal objective function for a first-order grid-type inverter, i.e., a first-order power point tracking inverter. Considering the synchronicity of the power conversion relationship, the time-domain integral of the Lagrange function is used to study the construction of the system functional variational problem based on minimizing the Hamiltonian action. The Lagrange equations for the non-conservative system are as follows:

[0066]

[0067] In the formula, q k Let Q be the generalized coordinate, where is the generalized velocity. k Let L represent the projection of the nonconservative forces of the system onto the generalized coordinate system. Let L represent the Lagrange energy function of the system, defined as the difference between the system's kinetic and potential energy.

[0068] L = TV (2)

[0069] In the formula, T represents kinetic energy, a function of generalized velocity; V represents potential energy, a function of generalized position. Generally, both the kinetic and potential energies of a system are related to the system's state or state trajectory and change dynamically with time. For power point-of-care control, kinetic energy represents the tracking error between the converter output frequency and the grid voltage frequency, while potential energy represents the difference between the output power and the power reference value. The kinetic / potential energy expression for first-order power point-of-care control is constructed based on Hooke's law of elasticity:

[0070]

[0071] Define the objective function as the time-domain integral of the Lagrange function:

[0072]

[0073] Step 1.2: Derive the optimal objective function for a second-order grid-type inverter, i.e., a second-order power point tracking inverter. Construct the kinetic / potential energy expression for second-order power point tracking control based on Newton's second law for a simple pendulum system:

[0074]

[0075] Define the objective function as the time-domain integral of the Lagrange function:

[0076]

[0077] Step 1.3: Derive the optimal objective function for the grid-following inverter, i.e., the voltage-tracking inverter. Kinetic energy is represented by the tracking error between the converter output frequency and the grid voltage frequency, and potential energy is represented by the q-axis voltage v at the PCC. pccq The difference between it and its reference value (usually 0).

[0078]

[0079] Where C represents the voltage tracking error weighting factor in the optimal function, also known as the virtual capacitance acting on the calculation of electric field energy. The objective function is defined as the time-domain integral of the Lagrangian function:

[0080]

[0081] In the above derivation method of the optimal synchronization mechanism for grid-connected inverters based on the parametric variational method, step 2 includes the following:

[0082] 2.1 Derivation of the regularity conditions for first-order grid inverters.

[0083] Based on the fundamental principles of parametric variation, the regularization condition corresponding to the minimum Hamiltonian action (optimal synchronization) of the system can be determined:

[0084]

[0085] Combining (3)-(4) and (9), we can obtain the canonical conditions for a first-order grid inverter:

[0086]

[0087] 2.2 Derivation of the regularity conditions for optimal synchronization control of second-order grid inverters.

[0088] Based on the fundamental principles of parametric variation, the regularization condition corresponding to the minimum Hamiltonian action (optimal synchronization) of the system can be determined:

[0089]

[0090] Combining (5)-(6) and (11), we can obtain the regularity condition for optimal synchronization control of a second-order grid inverter:

[0091]

[0092] 2.3 Derivation of the regularity conditions for grid-connected inverters.

[0093] Based on the fundamental principles of parametric variation, the regularization condition corresponding to the minimum Hamiltonian action (optimal synchronization) of the system can be determined:

[0094]

[0095] Combining (7)-(8) and (13), we can obtain the regularity condition for optimal synchronization control of the grid-connected inverter:

[0096]

[0097] Based on the above-mentioned optimal synchronization strategies for grid-connected and grid-linked inverters constructed according to canonical equations, and by tuning the corresponding optimal parameters to control the grid-connected inverters, the following are achieved:

[0098] Step 3.1 Derivation of the optimal control strategy and optimal parameter tuning for the first-order grid inverter.

[0099] Further simplification and derivation from (10) yields the optimal control strategy for a first-order grid-type inverter as follows:

[0100]

[0101] Where the optimal sagging coefficient m p for:

[0102]

[0103] Step 3.2 Derivation of the optimal control strategy and optimal parameter tuning for the second-order grid inverter.

[0104] Further simplification and derivation from (12) yields the optimal control strategy for a second-order grid-type inverter as follows:

[0105]

[0106] Step 3.3 involves deriving the optimal control strategy and tuning the optimal parameters for the grid-type inverter.

[0107] Further simplification and derivation from (14) yields the optimal control strategy for the grid-connected inverter as follows:

[0108] ω=+K p v PCCq +K i ∫v PCCq [v PCCd +(ω+ω g )L g I g ]dt (18)

[0109] The optimal proportionality coefficient K p =CL g I g / M, optimal integration coefficient K i =C / M.

[0110] The optimal control strategy and corresponding optimal parameters are applied to the grid-connected inverter control.

[0111] The embodiments described above are merely preferred embodiments of this application and are not intended to limit the scope of this application. Any modifications and improvements made by those skilled in the art to the technical solutions of this application without departing from the spirit of this application should fall within the protection scope defined by the claims of this application.

Claims

1. A grid-connected inverter control method based on parametric variational method, characterized in that, include: Step 1: Establish the synchronization optimal objective function based on minimizing Hamiltonian action for both grid-connected inverters and follow-up inverters; Step 2: Based on the optimal objective function, obtain the regularity conditions for the extremum conditions of the system functional based on the parametric variational method; Step 3: Construct optimal synchronization strategies for grid-connected inverters and grid-linked inverters respectively based on regularity conditions, and set the corresponding optimal parameters to control the grid-connected inverters; The establishment of the synchronization optimal objective function based on minimizing Hamiltonian action for grid-connected inverters and grid-linked inverters includes: Step 1.1: Construct the optimal objective function for a first-order power point tracking inverter based on minimizing the Hamiltonian action using the time-domain integral of the Lagrange function; the Lagrange equation for the non-conservative system is as follows: (1) In the formula, q k For generalized coordinates, For generalized speed, Q k Let L represent the projection of the nonconservative forces of the system onto the generalized coordinate system; L represents the Lagrange energy function of the system, which is defined as the difference between the system's kinetic and potential energy. (2) In the formula, T represents kinetic energy, a function of generalized velocity; V represents potential energy, a function of generalized position; the kinetic / potential energy expression for first-order power tracking control is constructed based on Hooke's law of elasticity: (3) Define the optimal objective function as the time-domain integral of the Lagrange function: (4) Step 1.2: Construct the optimal objective function for a second-order grid-type inverter, i.e., a second-order power point tracking inverter; construct the kinetic / potential energy expression for second-order power point tracking control based on Newton's second law for a simple pendulum system: (5) Define the optimal objective function as the time-domain integral of the Lagrange function: (6) Step 1.3: Construct the optimal objective function for the voltage tracking inverter; By employing the time-domain integral of the Lagrange function, an optimal objective function for a voltage tracking inverter based on minimizing the Hamiltonian action is constructed. Kinetic energy characterizes the tracking error between the converter output frequency and the grid voltage frequency, while potential energy characterizes the q-axis voltage v at the PCC. PCCq The difference between it and its reference value: (7) Where C represents the voltage tracking error weighting factor in the optimal function, and the objective function is defined as the time-domain integral of the Lagrange function: (8) Among them, the canonical equations for obtaining the system functional extremum conditions based on the parametric variational method, according to the optimal objective function, include: Step 2.1: Construct the regularization conditions for a first-order grid-type inverter; Based on the fundamental principle of parametric variation, the regularity condition corresponding to the minimum Hamiltonian action of the system can be determined: (9) Combining (3)-(4) and (9), we can obtain the first canonical condition for a first-order grid inverter: (10) Step 2.2: Construct the regularity conditions for optimal synchronization control of the second-order grid inverter; Based on the fundamental principle of parametric variation, the regularity condition corresponding to the minimum Hamiltonian action of the system can be determined: (11) Combining (5)-(6) and (11), we can obtain the second regularity condition for optimal synchronization control of a second-order grid inverter: (12) Step 2.3: Construct the regularization conditions for the grid-connected inverter; Based on the fundamental principle of parametric variation, the regularity condition corresponding to the minimum Hamiltonian action of the system can be determined: (13) Combining (7)-(8) and (13), we can obtain the regularity condition for optimal synchronization control of the grid-connected inverter: (14) 2. The method as described in claim 1, characterized in that, The step of constructing optimal synchronization strategies for grid-connected inverters and grid-linked inverters based on canonical equations, and adjusting the corresponding optimal parameters to control the grid-connected inverters includes: Step 3.1 Construct the optimal control strategy and set the optimal parameters for the first-order grid-type inverter; Further simplification and derivation from (10) yields the optimal control strategy for a first-order grid-type inverter as follows: (15) Where the optimal droop coefficient m p for: (16) Step 3.2 Derivation of the optimal control strategy and tuning of the optimal parameters for the second-order grid inverter; Further simplification and derivation from (12) yields the optimal control strategy for a second-order grid-type inverter as follows: (17) Step 3.3: Set the optimal control strategy and optimal parameters for the grid-connected inverter; Further simplification and derivation from (14) yields the optimal control strategy for the grid-connected inverter as follows: (18) The optimal proportionality coefficient K p =CL g I g / M, optimal integration coefficient K i =C / M; The optimal control strategy and corresponding optimal parameters are applied to the grid-connected inverter control.

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