CN-119146003-B - Control method and system of wind turbine

Abstract

The invention belongs to the technical field of wind power generation, and provides a control method and a control system of a wind turbine, wherein the method comprises the steps of obtaining strain data of a whole blade on the wind turbine by using a fiber bragg grating sensor; the method comprises the steps of updating the geometric shape of the deformed blade by utilizing a blade and flow field analysis and prediction module according to strain data of the whole blade, inverting the inflow speed of the wind turbine according to the geometric shape, aerodynamic characteristics, SCADA data of the wind turbine and spatial positions of the wind turbine in a wind field, predicting flow field distribution data in the wind field according to the inflow speed of the wind turbine, and controlling the wind turbine in the wind field according to the flow field distribution data. The wake flow control method solves the problems that wake flow control technology in the prior art is mostly based on feedback control, has certain hysteresis for natural wind signals with randomness, and is unfavorable for achieving the optimal control effect.

Inventors

• ZHANG XIANFENG
• DAI WEIDONG
• MA LU
• QIN MING
• SHEN XIN
• YANG DINGHUA
• OUYANG HUA
• LEI XIAO
• DU CHAOHUI
• FU GUANGZE

Assignees

• 中国长江三峡集团有限公司
• 上海交通大学

Dates

Publication Date

20260508

Application Date

20240805

Claims (5)

1. 1.A method of controlling a wind turbine, comprising: strain data of the whole blade on the wind turbine are obtained by using a fiber bragg grating sensor; obtaining the geometric shape of the deformed blade according to the strain data of the whole blade; Inverting the inflow speed of the wind turbine according to the geometric shape, aerodynamic characteristics, SCADA data of the wind turbine and the spatial position of the wind turbine in a wind field; predicting flow field distribution data in a wind field according to the inflow speed of the wind turbine; Controlling the wind turbines in the wind field according to the flow field distribution data so as to maximize the overall power generation amount of the wind field; The inversion of the inflow speed of the wind turbine comprises the following steps: establishing and solving the following optimization inverse problem to invert the inflow speed of the wind turbine : Wherein, the Wind turbine load predicted for the aerodynamic model; SCADA data of the wind turbine; And Wind speeds of the wind turbine are cut in and cut out respectively; The solving of the optimization inverse problem includes: establishing a relation curve of wind speed and load in a wind speed section of fan operation, and realizing the linearization solution of the optimization inverse problem through piecewise linear fitting of the curve; the linear solving of the problem by piecewise linear fitting of the curve comprises: determining the running wind speed section of the fan, determining the wind speed range of the fan during normal running, In the running process of the fan, the wind speed and the corresponding load data are collected in real time, Drawing a relation curve of wind speed and load according to the acquired data, and establishing a relation between the wind speed and the load; dividing a wind speed and load relation curve into a plurality of sections, and performing linear fitting on the wind speed and load relation curve of each section; And approximating the nonlinear relation between the wind speed and the load as a combination of a plurality of linear segments by piecewise linear fitting, so as to realize the linearization solution of the optimization inverse problem.
2. 2. The method for controlling a wind turbine according to claim 1, wherein the obtaining strain data of the entire blade on the wind turbine by using the fiber bragg grating sensor comprises: selecting the root, middle and tip of the blade to mount fiber bragg grating sensors; and collecting strain data of the whole blade on the wind turbine according to the measurement result of the fiber bragg grating sensor.
3. 3. The method according to claim 1, wherein the step of obtaining the deformed blade geometry from the strain data of the entire blade comprises: Determining the magnitude and direction of strain at each location on the blade; Determining coordinates of each key point based on the geometric shape of the blade; According to the material characteristics and the strain data, calculating the deformation degree of each part of the blade by using a corresponding mechanical formula; according to the deformation degree obtained by calculation, the coordinates of each key point are adjusted; and constructing the geometric shape of the deformed blade by connecting the adjusted key points.
4. 4. The method for controlling a wind turbine according to claim 1, wherein the controlling the wind turbine in the wind farm according to the flow field distribution data so that the overall power generation amount of the wind farm is maximized comprises: enabling all wind turbines in the wind farm to maximize power of all wind turbines in the wind farm by controlling yaw angles of all wind turbines in the wind farm; the control objective function is as follows: Wherein T is time, T is total time, N is the number of wind turbines, N is the total number of wind turbines in the wind farm; is the yaw angle of the wind turbine, For the power of wind turbine n at time t, In order to achieve an air density of the air, In order to achieve the wind sweeping area, For the speed in the wind farm, Is an efficiency power coefficient.
5. 5. A control system for a wind turbine, characterized by implementing a control method for a wind turbine according to any of claims 1-4, comprising: The measuring module is used for acquiring strain data of the whole blade on the wind turbine by using the fiber bragg grating sensor; the geometric shape construction module is used for acquiring the geometric shape of the deformed blade according to the strain data of the whole blade; The inflow speed calculation module is used for inverting the inflow speed of the wind turbine according to the geometric shape and aerodynamic characteristics of the blade, SCADA data of the wind turbine and the spatial position of the wind turbine in the wind field; The flow field distribution calculation module is used for predicting flow field distribution data in a wind field according to the inflow speed of the wind turbine; And the control module is used for controlling the wind turbines in the wind field according to the flow field distribution data so as to maximize the overall power generation amount of the wind field.

Description

Control method and system of wind turbine Technical Field The disclosure belongs to the technical field of wind power generation, and particularly relates to a control method and a control system of a wind turbine. Background A wind power generator is an energy device that converts wind energy into kinetic energy through blades and generates electricity. The wind energy resources in China are rich, and the wind power generation is an ideal electric energy source for areas lacking resources such as water or fuel or the like. However, since the wind power level is often unstable, it is difficult to always maintain the wind power generator in an ideal operating state, thereby affecting the efficiency of wind power generation and the load condition and life of the blades. Furthermore, for fans in a wind farm, the power loss of the downstream units from wake effects may be such that the total generated power of the wind farm is not a maximum due to the nonlinearity of the wind energy capture characteristics of the wind turbines. The wake flow of the fan is closely related to the running state of the fan, the strength and the direction of the wake flow can be changed by adjusting the running parameters and the running state of the unit, so that the wake flow loss of a downstream unit is reduced, the total power of the wind power plant is improved, and the benefit of the wind power plant is improved as much as possible. Thus, in recent years, how to increase the power generation amount of the entire wind farm by wake control has become one of important problems in the field of wind power generation. The patent with publication number CN114169614A discloses a wind power plant optimization scheduling method and system based on wind turbine wake model optimization, and belongs to the technical field of wind power plant wake calculation. The SCADA data is used for correcting the analysis wake model, and the intelligent optimization algorithm is combined to optimize key parameters of the model with the aim of minimizing power calculation errors of the wind power plant, so that the actual situation of the wind power plant can be fully considered by the wake optimization method provided by the technology to customize the parameters of the model. After the wake model is optimized by the method, the calculation precision of the model in an actual wind power plant can be greatly improved, so that the wake effect in the wind power plant can be modeled more accurately, the power prediction precision of the wind power plant and the reliability of a wake control strategy can be remarkably improved, and the overall power generation efficiency and the overall power generation capacity of the wind power plant are improved by wake optimization control and the like based on the optimized wake model. The publication number CN115807734a discloses a wake tracking based offshore wind farm level cooperative control strategy comprising a cabin type laser radar wind measurement system, a wake tracking module, an optimizer and a farm level controller. The method comprises the steps of measuring original wind information by using a cabin type laser radar wind measuring system, carrying out wind field inversion by using a wake tracking module to finish parameter evaluation of environmental input wind and wake characteristic parameter identification, solving the optimal wake center positions under different environmental working conditions by using an intelligent optimization algorithm based on a marine wind power field pneumatic-hydraulic-servo-elastic dynamic simulation model, establishing a multi-dimensional intelligent decision database LUT and an optimizer, and realizing wake redirection and intelligent control by using a field level collaborative PI controller. However, the existing wake flow control technology is mostly based on feedback control, has a certain hysteresis for natural wind signals with randomness, and is not beneficial to achieving the optimal control effect. Disclosure of Invention In order to solve the problems, the present disclosure provides a control method and a system for a wind turbine, which adopt a fiber bragg grating blade load to monitor wind conditions and predict wake effects generated by an upstream wind turbine on a downstream so as to perform predictive control, so that an ideal control effect can be achieved. The following technical content is as follows: a method of controlling a wind turbine, comprising: strain data of the whole blade on the wind turbine are obtained by using a fiber bragg grating sensor; obtaining the geometric shape of the deformed blade according to the strain data of the whole blade; Inverting the inflow speed of the wind turbine according to the geometric shape, aerodynamic characteristics, SCADA data of the wind turbine and the spatial position of the wind turbine in a wind field; predicting flow field distribution data in a wind field according to the inflow speed of the wind tu