CN-122026483-A - Grid-connected converter control method, grid-connected converter control system, electronic equipment and storage medium

CN122026483ACN 122026483 ACN122026483 ACN 122026483ACN-122026483-A

Abstract

The application provides a grid-connected converter control method, a grid-connected converter control system, electronic equipment and a storage medium, and belongs to the technical field of power electronics. The method comprises the steps of obtaining output angular frequency deviation, output active power change rate and output angular frequency change rate of a virtual synchronous generator when a grid-connected converter is in a virtual synchronous generator control mode, obtaining an optimal initial value of a key parameter affecting the virtual synchronous generator control mode when the output angular frequency deviation and the output active power change rate meet preset threshold conditions, solving by adopting an improved white whale optimization algorithm introducing a chaos reverse learning strategy and a Gaussian disturbance variation strategy, carrying out fuzzy control analysis according to the output angular frequency deviation and the output angular frequency change rate to obtain a value adjustment quantity of the key parameter, and determining the optimal value of the key parameter according to the optimal initial value and the value adjustment quantity of the key parameter so as to adjust the virtual synchronous generator control mode. The application can improve the control performance.

Inventors

XIAO CHUN
ZHOU YULAI
CHEN JING
LU CHIHUA
ZHENG HAO
WANG YIFEI
DENG YI
CHEN JIALONG
Zhang Jiazili

Assignees

佛山仙湖实验室

Dates

Publication Date: 20260512
Application Date: 20260121

Claims (10)

1. A grid-tied inverter control method, wherein the grid-tied inverter is configured to implement bidirectional flow of energy between a micro grid and a main grid, the method comprising: When the grid-connected converter is in a virtual synchronous generator control mode, obtaining output angular frequency deviation, output active power change rate and output angular frequency change rate of the virtual synchronous generator; When the output angular frequency deviation and the output active power change rate meet preset threshold conditions, acquiring an optimal initial value of a key parameter affecting the control mode of the virtual synchronous generator, and carrying out fuzzy control analysis according to the output angular frequency deviation and the output angular frequency change rate to obtain a value adjustment quantity of the key parameter, wherein the optimal initial value of the key parameter is obtained by solving an improved white whale optimization algorithm introducing a chaos reverse learning strategy and a Gaussian disturbance variation strategy; And determining the optimal value of the key parameter according to the optimal initial value and the value adjustment quantity of the key parameter so as to adjust the control mode of the virtual synchronous generator.
2. The grid-tie inverter control method of claim 1, wherein the output angular frequency deviation and the output active power change rate satisfy a preset threshold condition comprising an absolute value of the output angular frequency deviation being greater than a first preset threshold and/or an absolute value of the output active power change rate being greater than a second preset threshold, wherein the first preset threshold is determined according to a rated angular frequency of the virtual synchronous generator and the second preset threshold is determined according to a rated power of the virtual synchronous generator.
3. The grid-connected inverter control method according to claim 1, wherein the optimal initial value of the key parameter is obtained by: Initializing the position of the white whale population by adopting a chaotic reverse learning strategy, wherein the position of each white whale individual refers to the value of the key parameter, and taking the initial position of the white whale population as the current position of the white whale population; Screening a current optimal white whale position from the current position of the white whale population according to a preset fitness function, wherein the fitness function is constructed by taking the integral of the absolute value of the output frequency error of the minimized virtual synchronous generator multiplied by time as a target, and the output frequency error is calculated after simulation analysis is carried out on a micro-grid model which is built in an MATLAB/Simulink environment and is fused with a virtual synchronous generator control model according to preset test working conditions and the values of the key parameters; Judging whether a preset algorithm ending condition is met or not; If not, determining a balance factor and a white whale falling probability, updating the current position of the white whale population according to the balance factor to obtain a first position of the white whale population, updating the first position of the white whale population by adopting a Gaussian disturbance variation strategy to obtain a second position of the white whale population when the balance factor is larger than the white whale falling probability, and returning to the step of screening the current optimal white whale position from the current position of the white whale population according to a preset fitness function; If yes, determining an optimal initial value of the key parameter according to the current optimal white whale position.
4. The grid-connected inverter control method of claim 3, wherein initializing the location of the white whale population using a chaotic reverse learning strategy comprises: generating a first candidate initial position of the white whale population by adopting a piecewise linear chaotic mapping mode according to the value range of the key parameter; according to the value range of the key parameter, performing reverse learning on the first candidate initial position of the white whale population to obtain a second candidate initial position of the white whale population; and screening the first candidate initial position and the second candidate initial position of the white whale population according to the fitness function to obtain the initial position of the white whale population.
5. The grid-tie inverter control method of claim 3, wherein updating the first location of the white whale population with the gaussian perturbation variation strategy to obtain the second location of the white whale population comprises: Dividing the white whale population into a first white whale subgroup meeting the condition and a second white whale subgroup not meeting the condition on the condition that the change rate of the fitness value corresponding to the white whale individual in the last continuous iteration process is smaller than a preset value; And performing Gaussian disturbance on the first position of the first white whale subgroup to obtain a second position of the first white whale subgroup, and taking the first position of the second white whale subgroup as the second position of the second white whale subgroup.
6. The grid-connected inverter control method according to claim 1, wherein determining the optimal value of the key parameter according to the optimal initial value and the value adjustment amount of the key parameter comprises: and superposing the optimal initial value of the key parameter and the value adjustment quantity to obtain the optimal value of the key parameter.
7. The grid-connected inverter control method according to claim 1, wherein the grid-connected inverter is in a virtual synchronous generator control mode by: obtaining the output active power of the virtual synchronous generator and the most recently determined optimal value of the key parameter, and analyzing the optimal value through a preset active frequency control strategy to obtain the output phase angle of the virtual synchronous generator; Obtaining output reactive power and output voltage of the virtual synchronous generator, and analyzing through a preset reactive voltage control strategy to obtain output virtual electromotive force of the virtual synchronous generator; determining the three-phase electromotive force of the virtual synchronous generator according to the output phase angle and the output virtual electromotive force, and analyzing through a preset voltage-current double closed-loop control strategy to obtain a control voltage; And carrying out pulse modulation on the control voltage to obtain a control signal so as to drive the grid-connected converter.
8. A grid-tie inverter control system for enabling bi-directional flow of energy between a micro-grid and a main grid, the system comprising: The first module is used for acquiring output angular frequency deviation, output active power change rate and output angular frequency change rate of the virtual synchronous generator when the grid-connected converter is in a virtual synchronous generator control mode; The second module is used for acquiring an optimal initial value of a key parameter affecting the control mode of the virtual synchronous generator when the output angular frequency deviation and the output active power change rate meet preset threshold conditions, and carrying out fuzzy control analysis according to the output angular frequency deviation and the output angular frequency change rate to obtain a value adjustment quantity of the key parameter, wherein the optimal initial value of the key parameter is obtained by solving an improved white whale optimization algorithm introducing a chaotic reverse learning strategy and a Gaussian disturbance variation strategy; and the third module is used for determining the optimal value of the key parameter according to the optimal initial value and the value adjustment quantity of the key parameter so as to adjust the control mode of the virtual synchronous generator.
9. An electronic device comprising a memory storing a computer program and a processor that when executing the computer program implements the grid-tie converter control method of any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the grid-tie converter control method of any one of claims 1 to 7.

Description

Grid-connected converter control method, grid-connected converter control system, electronic equipment and storage medium Technical Field The application relates to the technical field of power electronics, in particular to a grid-connected converter control method, a grid-connected converter control system, electronic equipment and a storage medium. Background In the prior art, a virtual synchronous generator control strategy is adopted to control the grid-connected converter, but in the implementation process, the value of a key parameter affecting the control mode of the virtual synchronous generator is usually set to a fixed value determined by experience, and the control performance is poor due to the difficulty in adapting to complex and variable working conditions. Disclosure of Invention The application mainly aims to provide a grid-connected converter control method, a grid-connected converter control system, electronic equipment and a storage medium, and control performance of the grid-connected converter can be improved through a proper parameter adjusting mode. To achieve the above object, an aspect of the present application provides a grid-connected inverter control method for implementing bidirectional energy flow between a micro grid and a main grid, the method comprising: When the grid-connected converter is in a virtual synchronous generator control mode, obtaining output angular frequency deviation, output active power change rate and output angular frequency change rate of the virtual synchronous generator; When the output angular frequency deviation and the output active power change rate meet preset threshold conditions, acquiring an optimal initial value of a key parameter affecting the control mode of the virtual synchronous generator, and carrying out fuzzy control analysis according to the output angular frequency deviation and the output angular frequency change rate to obtain a value adjustment quantity of the key parameter, wherein the optimal initial value of the key parameter is obtained by solving an improved white whale optimization algorithm introducing a chaos reverse learning strategy and a Gaussian disturbance variation strategy; And determining the optimal value of the key parameter according to the optimal initial value and the value adjustment quantity of the key parameter so as to adjust the control mode of the virtual synchronous generator. Further, the output angular frequency deviation and the output active power change rate meet a preset threshold condition, wherein the absolute value of the output angular frequency deviation is larger than a first preset threshold value and/or the absolute value of the output active power change rate is larger than a second preset threshold value, the first preset threshold value is determined according to the rated angular frequency of the virtual synchronous generator, and the second preset threshold value is determined according to the rated power of the virtual synchronous generator. Further, the optimal initial value of the key parameter is obtained by: Initializing the position of the white whale population by adopting a chaotic reverse learning strategy, wherein the position of each white whale individual refers to the value of the key parameter, and taking the initial position of the white whale population as the current position of the white whale population; Screening a current optimal white whale position from the current position of the white whale population according to a preset fitness function, wherein the fitness function is constructed by taking the integral of the absolute value of the output frequency error of the minimized virtual synchronous generator multiplied by time as a target, and the output frequency error is calculated after simulation analysis is carried out on a micro-grid model which is built in an MATLAB/Simulink environment and is fused with a virtual synchronous generator control model according to preset test working conditions and the values of the key parameters; Judging whether a preset algorithm ending condition is met or not; If not, determining a balance factor and a white whale falling probability, updating the current position of the white whale population according to the balance factor to obtain a first position of the white whale population, updating the first position of the white whale population by adopting a Gaussian disturbance variation strategy to obtain a second position of the white whale population when the balance factor is larger than the white whale falling probability, and returning to the step of screening the current optimal white whale position from the current position of the white whale population according to a preset fitness function; If yes, determining an optimal initial value of the key parameter according to the current optimal white whale position. Further, initializing the positions of the white whale population by adopting the chaotic reverse learning st