CN-122000977-A - Residual drive window length self-adaption-based converter station harmonic parameter identification method and device

Abstract

The invention relates to the technical field of flexible direct current transmission, in particular to a residual drive window length self-adaptive converter station harmonic parameter identification method and device, comprising the steps of acquiring data of harmonic voltage and harmonic current of a converter station in a data window length; and identifying harmonic impedance of the converter station in the data window length by utilizing a pre-fitted complex domain regression equation based on the harmonic voltage and harmonic current data of the converter station in the data window length, wherein the data window length is adaptively adjusted based on the harmonic impedance of the converter station in the data window length. The technical scheme provided by the invention can adaptively adjust the window length, respond to system changes in real time, has stronger anti-interference capability, and has important and urgent practical significance for improving the reliability, accuracy and engineering practicability of the background harmonic impedance measurement of the alternating current side of the converter station.

Inventors

• LI ZHAOLIANG
• ZHOU SHENGJUN
• ZHAO LEI
• ZHANG JIN
• LI FANGYI
• LI YAQIONG
• LIU HAIJUN
• MU XIAOBIN
• WANG ZHIKAI
• WANG TONGXUN

Assignees

• 中国电力科学研究院有限公司
• 国家电网有限公司

Dates

Publication Date

20260508

Application Date

20251203

Claims (13)

1. 1. The method for identifying the harmonic parameters of the converter station based on the residual drive window length self-adaption is characterized by comprising the following steps: Acquiring harmonic voltage and harmonic current data of a converter station in a data window length; Identifying harmonic impedance of the converter station in the data window length by utilizing a complex domain regression equation fitted in advance based on the harmonic voltage and the harmonic current data of the converter station in the data window length; The data window length is adaptively adjusted based on the harmonic impedance of the converter station in the data window length.
2. 2. The method of claim 1, wherein the initial value of the data window length is as follows: In the above formula, N 0 is an initial value of the data window length, N max is a maximum value of the data window length, and N min is a minimum value of the data window length.
3. 3. The method of claim 1, wherein the pre-fitted complex domain regression equation is as follows: in the above formula, y is the independent variable column vector, A is the parameter matrix to be fitted, x is the independent variable column vector, Is a residual matrix.
4. 4. A method according to claim 3, wherein the dependent variable column vectors are as follows: the argument list vector is as follows: The parameter matrix to be fitted is as follows: In the above-mentioned method, the step of, For the h-th converter station harmonic voltage measurement value of the nth sampling point in the monitoring point data window length, n is the total number of sampling points in the data window length, T is a transposed symbol, For the h-th harmonic current measurement value of the converter station at the nth sampling point in the monitoring point data window length, For the background harmonic impedance of the ac side of the converter station, Is the background harmonic voltage on the alternating current side of the converter station.
5. 5. The method of claim 1, wherein adaptively adjusting the data window length based on the converter station harmonic impedance within the data window length comprises: Determining a standard residual index of the harmonic impedance of the converter station based on the harmonic impedance of the converter station in the data window length; And adjusting the data window length based on the harmonic impedance standardized residual index of the converter station.
6. 6. The method of claim 5, wherein the station harmonic impedance normalized residual index is as follows: In the above description, mu n is a standard residual error index of harmonic impedance of the converter station, And s is the residual scale, which is the harmonic impedance sequence value of the converter station in the data window length.
7. 7. The method of claim 6, wherein the residual scale is as follows: In the above equation, median is a function that takes the Median of the variables.
8. 8. The method of claim 7, wherein said adjusting a data window length based on said converter station harmonic impedance normalized residual index comprises: The data window length is adjusted as follows: In the above-mentioned method, the step of, In order to adjust the length of the data window, For the current data window length, For the first constant value of the first constant value, Is a weight coefficient.
9. 9. The method of claim 8, wherein the weight coefficients are as follows: In the above-mentioned method, the step of, Is a second constant.
10. 10. The method of claim 9, wherein the first constant is 2 and the second constant is 5.
11. 11. An apparatus based on the residual drive window length adaptive converter station harmonic parameter identification method of any one of claims 1-10, characterized in that the apparatus comprises: The acquisition module is used for acquiring harmonic voltage and harmonic current data of the converter station in the data window length; the analysis module is used for identifying harmonic impedance of the converter station in the data window length by utilizing a complex domain regression equation fitted in advance based on the harmonic voltage and the harmonic current data of the converter station in the data window length; The data window length is adaptively adjusted based on the harmonic impedance of the converter station in the data window length.
12. 12. A computer device, comprising: one or more processors; the processor is used for executing one or more programs; a method of converter station harmonic parameter identification based on residual drive window length adaptation as claimed in any one of claims 1 to 10, when said one or more programs are executed by said one or more processors.
13. 13. A computer readable storage medium, characterized in that a computer program is stored thereon, which computer program, when executed, implements the method for identifying converter station harmonic parameters based on residual drive window length adaptation according to any of claims 1 to 10.

Description

Residual drive window length self-adaption-based converter station harmonic parameter identification method and device Technical Field The invention relates to the technical field of flexible direct current transmission, in particular to a method and a device for identifying harmonic parameters of a converter station based on residual drive window length self-adaption. Background As large-scale new energy power generation and high-proportion power electronic equipment are connected into a power grid, the harmonic environment at the alternating-current side of a converter station is increasingly complicated and deteriorated. The harmonic pollution threatens the safe and stable operation of the equipment in the station and can permeate into all levels of power grids to cause the problem of wide power quality, so that accurate identification of the background harmonic parameters of the power grids becomes a key premise for guaranteeing the safety and the power quality of the system. The traditional identification method is mostly dependent on a regression analysis method, and background harmonic impedance is calculated by adopting least square algorithm and the like according to harmonic voltage and current data in a fixed time window. However, in actual operation, the harmonic state of the alternating-current side of the converter station has obvious randomness, volatility and time variability, the fixed window length is difficult to adapt to the dynamic change, namely, in a data stationary period, a shorter window cannot fully utilize effective information, so that the identification precision is limited, and when the data severely fluctuates or transient interference exists, a large amount of abnormal data is introduced into the fixed long window, so that the pollution of the inferior data to a parameter identification result cannot be effectively restrained by the traditional method, and the estimation deviation is increased and the accuracy is reduced. The prior art generally relies on manually setting a threshold or a fixed criterion as a data screening mechanism, and lacks the capability of on-line perception of data quality and autonomous optimization of a window length structure. Disclosure of Invention In order to overcome the defects, the invention provides a harmonic parameter identification method and device for a converter station based on residual drive window length self-adaption. In a first aspect, a method for identifying harmonic parameters of a converter station based on residual drive window length adaptation is provided, where the method for identifying harmonic parameters of a converter station based on residual drive window length adaptation includes: Acquiring harmonic voltage and harmonic current data of a converter station in a data window length; Identifying harmonic impedance of the converter station in the data window length by utilizing a complex domain regression equation fitted in advance based on the harmonic voltage and the harmonic current data of the converter station in the data window length; The data window length is adaptively adjusted based on the harmonic impedance of the converter station in the data window length. Preferably, the initial value of the data window length is as follows: In the above formula, N 0 is an initial value of the data window length, N max is a maximum value of the data window length, and N min is a minimum value of the data window length. Preferably, the pre-fitted complex domain regression equation is as follows: in the above formula, y is the independent variable column vector, A is the parameter matrix to be fitted, x is the independent variable column vector, Is a residual matrix. Further, the dependent variable column vectors are as follows: the argument list vector is as follows: The parameter matrix to be fitted is as follows: In the above-mentioned method, the step of, For the h-th converter station harmonic voltage measurement value of the nth sampling point in the monitoring point data window length, n is the total number of sampling points in the data window length, T is a transposed symbol,For the h-th harmonic current measurement value of the converter station at the nth sampling point in the monitoring point data window length,For the background harmonic impedance of the ac side of the converter station,Is the background harmonic voltage on the alternating current side of the converter station. Preferably, the adaptive adjustment of the data window length based on the harmonic impedance of the converter station in the data window length includes: Determining a standard residual index of the harmonic impedance of the converter station based on the harmonic impedance of the converter station in the data window length; And adjusting the data window length based on the harmonic impedance standardized residual index of the converter station. Further, the standard residual index of the harmonic impedance of the converter station is as