CN-115809418-B - Frequency response characteristic processing method and device and computer equipment

CN115809418BCN 115809418 BCN115809418 BCN 115809418BCN-115809418-B

Abstract

The present application relates to the field of power systems, and in particular, to a method and apparatus for processing frequency response characteristics, and a computer device. The method comprises the steps of obtaining running states of all wind turbines, clustering all the wind turbines according to the running states of the wind turbines to obtain a plurality of target wind turbine clusters, determining aggregate straight-axis current of the target wind turbines at all moments according to the running states of all the wind turbines in any one target wind turbine cluster and a preset frequency time sequence curve, and determining actual active power curves of the target wind turbines according to straight-axis components of voltage at a machine end and the aggregate straight-axis current of the target wind turbines at all moments for any one target wind turbine cluster. The method can reduce the calculated amount, thereby improving the processing speed of the frequency response characteristic.

Inventors

LU ZONGXIANG
YU HAOYANG
WANG DAN
GU PAN
JIANG JIHENG
QIAO YING
XIE HUAN
XIA XUE
WANG ZESEN
ZHAO TIANQI
LIU DONG
LIU ZHONGJIAN

Assignees

清华大学
国网冀北电力有限公司电力科学研究院
国网经济技术研究院有限公司

Dates

Publication Date: 20260505
Application Date: 20221114

Claims (10)

1. A method of processing frequency response characteristics, the method comprising: acquiring the running state of each wind turbine generator; according to the running state of each wind turbine, clustering each wind turbine in a clustering way to obtain a plurality of target wind turbine clusters; For any one of the target wind turbine clusters, determining state quantity and input quantity of the target wind turbine cluster according to the running states of all the wind turbines in the target wind turbine cluster; Determining an aggregation parameter corresponding to the target wind turbine cluster according to the state quantity and the input quantity of the target wind turbine cluster; Acquiring a main shaft motion equation of the wind turbine and an active reference value model of a machine side converter of the wind turbine; Processing the state quantity, the input quantity, the aggregation parameter and a preset frequency time sequence curve corresponding to the target wind turbine cluster based on the main shaft motion equation and the active reference value model to obtain active reference values of the target wind turbine cluster at all moments, wherein the input quantity comprises an aggregation reactive reference value, and the aggregation parameter comprises an aggregation current limit value; determining the direct axis current of the target wind turbine generator cluster at each moment according to the active reference value of the target wind turbine generator cluster at each moment and the direct axis component of the machine end voltage; determining quadrature current according to the aggregate reactive reference value and the direct axis component of the machine terminal voltage; Determining the aggregate direct axis current of the target wind turbine generator cluster at each moment according to the quadrature axis current, the aggregate current limit value and the direct axis current of the target wind turbine generator cluster at each moment; And determining an actual active power curve of the target wind turbine generator cluster according to the direct axis component of the machine end voltage and the aggregate direct axis current of the target wind turbine generator cluster at each moment aiming at any target wind turbine generator cluster.
2. The method according to claim 1, wherein clustering each of the wind turbines into a plurality of target wind turbine clusters according to the operation state of each wind turbine includes: Normalizing the running states of each wind turbine to obtain normalized running states of each wind turbine; And clustering each wind turbine based on the normalized running state of each wind turbine by adopting a hierarchical clustering method to obtain a plurality of target wind turbine clusters.
3. The method of claim 1, wherein the operating conditions include machine side wind speed, main shaft rotational speed, pitch angle, active power, reactive power.
4. The method according to claim 1, wherein the processing the state quantity, the input quantity, the aggregation parameter, and a preset frequency time sequence curve corresponding to the target wind turbine cluster based on the principal axis motion equation and the active reference value model to obtain active reference values of the target wind turbine cluster at each moment includes: Determining the mechanical power of the target wind turbine generator cluster according to the calculation coefficient of the mechanical power, the state quantity corresponding to the target wind turbine generator cluster and the input quantity; And processing the state quantity, the aggregation parameter, the mechanical power and a preset frequency time sequence curve corresponding to the target wind turbine cluster based on the main shaft motion equation and the active reference value model to obtain active reference values of the target wind turbine cluster at all moments.
5. A frequency response characteristic processing apparatus, characterized in that the apparatus comprises: The state acquisition module is used for acquiring the running state of each wind turbine generator; the clustering module is used for clustering each wind turbine according to the running state of each wind turbine to obtain a plurality of target wind turbine clusters; The current calculation module is used for determining state quantity and input quantity of the target wind turbine generator cluster according to the running state of each wind turbine generator in the target wind turbine generator cluster, determining aggregation parameters corresponding to the target wind turbine generator cluster according to the state quantity and the input quantity of the target wind turbine generator cluster, acquiring a main shaft motion equation of the wind turbine generator and an active reference value model of a machine side converter of the wind turbine generator, processing the state quantity, the input quantity and the aggregation parameters corresponding to the target wind turbine generator cluster and a preset frequency time sequence curve corresponding to the target wind turbine generator cluster based on the main shaft motion equation and the active reference value model to obtain active reference values of the target wind turbine generator cluster at each moment, wherein the input quantity comprises an aggregation reactive reference value, the aggregation parameters comprise an aggregation current limit value, determining an aggregation axis component of a wind turbine generator terminal voltage according to the active reference values of the target wind turbine generator cluster at each moment, determining an aggregation axis current of the target wind turbine generator at each moment, determining a direct axis component of the wind turbine generator at each moment according to the aggregation axis current of the direct axis of the target wind turbine generator cluster at each moment, and the current of the direct axis of the target wind turbine generator at each moment; the power calculation module is used for determining an actual active power curve of the target wind turbine generator cluster according to the direct axis component of the machine end voltage and the aggregate direct axis current of the target wind turbine generator cluster at each moment.
6. The device of claim 5, wherein the clustering module is further configured to normalize the operation states of each of the wind turbines to obtain normalized operation states of each of the wind turbines, and perform clustering on each of the wind turbines to obtain a plurality of target wind turbine clusters based on the normalized operation states of each of the wind turbines by using a hierarchical clustering method.
7. The device of claim 5, wherein the current calculation module is further configured to determine a mechanical power of the target wind turbine cluster according to a calculation coefficient of the mechanical power, the state quantity corresponding to the target wind turbine cluster, and the input quantity, and process the state quantity corresponding to the target wind turbine cluster, the aggregation parameter, the mechanical power, and a preset frequency time sequence curve based on the principal axis motion equation and the active reference value model to obtain active reference values of the target wind turbine cluster at each moment.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 4 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 4.
10. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the method of any of claims 1 to 4.

Description

Frequency response characteristic processing method and device and computer equipment Technical Field The present application relates to the field of power systems, and in particular, to a method and apparatus for processing frequency response characteristics, and a computer device. Background After wind power is connected into a power system in a large scale, the duty ratio of the traditional synchronous unit is reduced, the inertia and frequency modulation capacity of a power end are reduced, and the frequency instability risk after the power system is disturbed is increased. In order to enhance the frequency stability, the wind turbine generator is modified through a control strategy, so that the wind turbine generator has frequency response capabilities such as inertia response and primary frequency modulation, and the frequency instability problem of the disturbed system is relieved to a certain extent. However, as the frequency response characteristics of the wind turbine generator are affected by multiple factors such as a control strategy and an operation state, the active support characteristics of the wind turbine generator show time-varying characteristics, and the wind turbine generator is difficult to describe through a low-order model similar to a synchronous machine set, and the frequency response characteristics of the wind turbine generator are analyzed and need to keep detailed models of a plurality of control links. However, the control parameters and the running states of different wind turbines in the wind power plant are obviously different, if detailed models of all the turbines are reserved to participate in the system frequency analysis, the calculated amount is increased suddenly, and quick calculation and quick analysis are difficult to realize. Therefore, the existing frequency response characteristic analysis method of the wind power plant has the problems of large calculated amount and low frequency response characteristic analysis speed. Disclosure of Invention Based on the foregoing, it is necessary to provide a method, an apparatus, a computer device, a computer readable storage medium and a computer program product for processing frequency response characteristics, so as to implement analysis of overall frequency response characteristics of a plurality of wind turbines in different control parameters and different running states in a wind farm, and improve analysis speed of wind power frequency response characteristics. In a first aspect, the present application provides a method for processing frequency response characteristics, the method comprising: acquiring the running state of each wind turbine generator; according to the running state of each wind turbine, clustering each wind turbine in a clustering way to obtain a plurality of target wind turbine clusters; Aiming at any one target wind turbine cluster, determining the aggregation straight-axis current of the target wind turbine cluster at each moment according to the running state of each wind turbine in the target wind turbine cluster and a preset frequency time sequence curve; And determining an actual active power curve of the target wind turbine generator cluster according to the direct axis component of the machine end voltage and the aggregate direct axis current of the target wind turbine generator cluster at each moment aiming at any target wind turbine generator cluster. In one embodiment, the clustering the wind turbines according to the running state of each wind turbine to obtain a plurality of target wind turbine clusters includes: Normalizing the running states of each wind turbine to obtain normalized running states of each wind turbine; And clustering each wind turbine based on the normalized running state of each wind turbine by adopting a hierarchical clustering method to obtain a plurality of target wind turbine clusters. In one embodiment, the determining, according to the running states of the wind turbines in the target wind turbine cluster and a preset frequency timing curve, the aggregate direct axis current of the target wind turbine cluster at each moment includes: Determining state quantity and input quantity of the target wind turbine generator cluster according to the running states of the wind turbine generators in the target wind turbine generator cluster; Determining an aggregation parameter corresponding to the target wind turbine cluster according to the state quantity and the input quantity of the target wind turbine cluster; And determining the aggregation straight-axis current of the target wind turbine generator cluster at each moment according to the aggregation parameter corresponding to the target wind turbine generator cluster, the state quantity and the input quantity of the target wind turbine generator cluster and a preset frequency time sequence curve. In one embodiment, the determining the aggregate straight-axis current of the target wind turbine cluster at each momen