CN111425347B - Wind turbine generator maximum power point tracking control method based on torque gain coefficient optimization - Google Patents

Wind turbine generator maximum power point tracking control method based on torque gain coefficient optimization Download PDF

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CN111425347B
CN111425347B CN202010205696.7A CN202010205696A CN111425347B CN 111425347 B CN111425347 B CN 111425347B CN 202010205696 A CN202010205696 A CN 202010205696A CN 111425347 B CN111425347 B CN 111425347B
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torque gain
gain coefficient
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CN111425347A (en
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殷明慧
张欢
周连俊
陈载宇
彭云
杨炯明
卜京
邹云
顾伟
徐畅
李阳
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Nanjing University of Science and Technology
Jiangsu Goldwind Science and Technology Co Ltd
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Jiangsu Goldwind Science and Technology Co Ltd
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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    • F05B2270/30—Control parameters, e.g. input parameters
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Abstract

The invention discloses a wind turbine generator maximum power point tracking control method based on torque gain coefficient optimization, which is characterized in that on the basis of an MPPT control method for reducing torque gain, wind energy capture efficiency of a wind turbine generator operated under a PSF method is used as a comprehensive measurement index of the influence of turbulent wind speed on MPPT, and the functional relation between an optimal torque gain coefficient and the index is traversed off line; when the online operation is carried out, the comprehensive measurement index is periodically obtained, and the optimal set value of the torque gain coefficient is estimated and updated according to the function; the acquisition of the corresponding wind energy capturing efficiency of the PSF method is realized by constructing a means that a virtual wind turbine generator set operating the PSF method and an actual wind turbine generator set operate synchronously in a unit master control PLC. The invention can realize the single index depiction of the comprehensive influence of a plurality of indexes on MPPT, and simplify the construction complexity of direct quantity relationship; the wind energy capture efficiency is ensured, and meanwhile, the computational resource requirement is greatly reduced.

Description

Wind turbine generator maximum power point tracking control method based on torque gain coefficient optimization
Technical Field
The invention belongs to the field of wind turbine generator control, and particularly relates to a wind turbine generator maximum power point tracking control method based on torque gain coefficient optimization.
Background
In order to improve the Maximum Power Point Tracking (MPPT) performance of the wind turbine generator facing turbulent wind speed, an improved PSF method based on two ideas of torque gain and tracking interval adjustment is developed on the basis of applying the most extensive Power Signal Feedback (PSF) method. The two ideas are that the tracking performance of the high-energy wind speed area is improved by sacrificing the wind energy capturing efficiency of the low-energy wind speed area, and key adjusting parameters need to be reasonably set to balance loss and lifting amount, so that the maximization of the overall efficiency is realized. Research shows that the optimal value of the key adjusting parameter is influenced by wind condition characteristics (average wind speed, turbulence intensity and turbulence frequency) and factors such as unit aerodynamics and structural parameters. How to periodically estimate and update the optimal setting of the key parameters during operation based on the above mentioned changes of the influencing factors becomes a focus issue.
The problem currently exists in Adaptive Torque Control (ATC) and two types of solutions for constructing a quantitative relation between an optimal value of a key parameter and an influencing factor and guiding online operation. The self-adaptive torque control determines the direction and the magnitude of the disturbance of the next period according to the change of the wind energy capture efficiency after the key parameter of the disturbance on the basis of the method for reducing the torque gain. And the latter directly constructs a definite nonlinear function relation between the optimal torque curve adjustment quantity and three wind condition characteristics and unit parameters in an off-line traversal mode aiming at a specific unit. When the system runs online, the optimal set value of the key parameter can be estimated according to the wind condition information and the functional relation.
The self-adaptive algorithm does not need to know the parameters of the wind turbine generator in advance, has the advantages of strong universality and capability of being quickly implemented in batches, but has the problems of search non-convergence and search direction error in partial wind condition change scenes, so that the MPPT performance of the method is limited in practical application. The method for directly constructing the function relationship between the optimal torque curve adjustment quantity and the three wind condition characteristics to guide parameter online optimization avoids an iterative search process, can obtain higher wind energy capture efficiency and good wind condition adaptability, but the method consumes a large amount of time and calculation force to perform offline traversal work, is not easy to implement quickly in batches, and limits the engineering practicability. Therefore, how to combine high wind energy capture efficiency and quick implementation is a problem that needs to be further solved by the current MPPT control method.
Disclosure of Invention
The invention aims to provide a wind turbine generator maximum power point tracking control method based on torque gain coefficient optimization, and the wind turbine generator maximum power point tracking control method can obtain higher wind energy capture efficiency on the premise of paying less calculation power and time cost.
The technical solution for realizing the purpose of the invention is as follows: a wind turbine generator maximum power point tracking control method based on torque gain coefficient optimization comprises the following steps:
(1) offline construction of functional relationships
Step 1-1: aiming at a wind turbine generator to which the method is applied, acquiring pneumatic and structural parameters required for constructing a FAST model of the wind turbine generator;
step 1-2: in FAST software, finishing the construction of a wind turbine generator simulation model according to parameters;
step 1-3: a turbulent wind speed simulation method is adopted, and three characteristic indexes representing turbulent wind conditions are changed in sequence: mean wind speed
Figure BDA0002420997560000021
Generating a turbulent wind speed sequence corresponding to different characteristic index combinations by using the turbulent intensity TI and the turbulent integral scale L;
step 1-4: wind turbine generator optimal torque gain coefficient corresponding to each wind speed sequence based on FAST software traversal
Figure BDA0002420997560000022
And wind energy capture efficiency when applying the PSF method
Figure BDA0002420997560000023
Step 1-5: fitting the result obtained by traversing as sample data to obtain an optimal torque gain coefficient
Figure BDA0002420997560000024
And the average wind energy capture efficiency under the PSF method
Figure BDA0002420997560000025
Functional relationship of
Figure BDA0002420997560000026
(2) Building virtual wind turbine generator
Step 2-1: embedding a FAST model of a wind turbine generator set to which the method is applied into an actual master control PLC (programmable logic controller) of the wind turbine generator set, and constructing a virtual machine set capable of synchronously operating with the actual machine set;
step 2-2: embedding a PSF method code for MPPT control of a virtual wind turbine generator in a master control PLC;
(3) on-line operation
Step 3-1: setting the torque gain factor optimization period to TwInitializing the torque gain coefficient K of the actual wind turbine generator operationdInitializing initial rotation speed omega of virtual wind turbine generator and actual wind turbine generatorbgnSetting the current time interval as n to be 1 for the lowest rotating speed of the MPPT stage;
step 3-2: reading a current actually measured wind speed value, carrying out MPPT control on an actual wind turbine generator by adopting a torque gain reduction method optimized by a torque gain coefficient, carrying out MPPT control on a virtual wind turbine generator in the PLC by adopting a PSF method, and synchronously operating the actual wind turbine generator and the virtual wind turbine generator;
step 3-3: recording the operating data of the virtual wind turbine, including the rotor speed ωrAcceleration of rotor
Figure BDA0002420997560000027
Electromagnetic torque T of generatore；
Step 3-4: judging the nth TwWhether the time interval runs over; if yes, calculating the current time interval according to the recorded operation dataAverage wind energy capture efficiency corresponding to PSF method applied to pseudo wind turbine generator
Figure BDA0002420997560000031
And substituting into the function relation constructed off-line
Figure BDA0002420997560000032
In the process of pre-estimating the optimal torque gain coefficient
Figure BDA0002420997560000033
Otherwise, returning to execute the step 3-2;
step 3-5: the optimal torque gain coefficient given in the step 3-4 is obtained
Figure BDA0002420997560000034
Setting a torque gain coefficient of an n +1 th time period of an actual wind turbine generator;
step 3-6: and n is n +1, jumping to the step 3-2, and entering the next operation period.
Compared with the prior art, the invention has the following remarkable advantages: (1) the invention directly establishes the relation between the optimal gain coefficient and the wind condition characteristics, avoids the self-adaptive iterative search process and the possible problem of search non-convergence, and has strong adaptability to the wind condition change; (2) the invention introduces a power curve method to correspond to the wind energy capture efficiency
Figure BDA0002420997560000035
The method has the advantages that three wind condition characteristic indexes of average wind speed, turbulence intensity and turbulence frequency are replaced, the functional relation between the wind condition characteristic indexes and the optimal torque gain coefficient of the wind turbine generator in the MPPT stage is established, and compared with the existing off-line traversal and on-line optimization algorithms such as a neural network and a response surface model, the wind energy capturing efficiency is guaranteed, meanwhile, the requirements of computational resources and traversal time are greatly reduced, and the method has high engineering practicability.
The present invention is described in further detail below with reference to the attached drawing figures.
Drawings
Fig. 1 is a flowchart of a wind turbine maximum power point tracking control method based on torque gain coefficient optimization according to the present invention.
FIG. 2 is a schematic diagram of a statistical relationship between an optimal gain coefficient of an NREL CART3 wind turbine generator and an average wind energy capture efficiency corresponding to the application of a PSF method.
FIG. 3 is a graph comparing the performance of the method of the present invention with other methods.
Detailed Description
The invention belongs to the type of a method for constructing a direct quantitative relation between optimal adjustment parameters and MPPT influence factor description indexes to guide parameter online optimization, and has higher wind energy capture performance. The invention further realizes the single index depiction of the comprehensive influence of a plurality of indexes on MPPT, simplifies the construction difficulty of direct quantity relation, can obtain higher wind energy capture efficiency on the premise of paying less calculation resources and time cost, and has more engineering application value.
With reference to fig. 1, the method of the invention firstly establishes a functional relationship between the optimal torque gain coefficient and the corresponding wind energy capture efficiency of the PSF method offline, and periodically adjusts the torque curve gain coefficient of the wind turbine generator during the actual operation process according to the functional relationship. Aiming at the problem that the wind energy capture efficiency corresponding to the PSF method cannot be directly obtained by improving the MPPT control method in the actual operation of the wind turbine generator, the problem is solved by constructing a virtual wind turbine generator applying the PSF method in a controller and synchronously operating the virtual wind turbine generator and the actual wind turbine generator.
The method comprises the following steps of offline construction of a functional relation:
step 1-1: aiming at a wind turbine generator to which the method is applied, acquiring pneumatic and structural parameters required for constructing a FAST model of the wind turbine generator;
step 1-2: in FAST software, the construction of a wind turbine generator simulation model is completed according to parameters;
step 1-3: three characteristic indexes representing turbulent wind conditions are changed in sequence by adopting a turbulent wind speed simulation method, wherein the three characteristic indexes are respectively mean wind speeds
Figure BDA0002420997560000041
And generating a turbulent wind speed sequence corresponding to different characteristic index combinations by using the turbulent intensity TI and the turbulent integral scale L.Wherein the content of the first and second substances,
Figure BDA0002420997560000042
the variation range of (2) is 4-9 m/s, the step length is 1m/s, the turbulence intensity TI is changed according to A, B, C turbulence level, the variation range of the integral scale L is 100-500 m, and the step length is 50 m. A total of 162 parameter setting combined wind conditions are obtained, and 10 wind speed sequences are generated corresponding to each wind condition;
step 1-4: wind turbine generator optimal torque gain coefficient corresponding to each wind speed sequence based on FAST software traversal
Figure BDA0002420997560000043
And wind energy capture efficiency when applying the PSF method
Figure BDA0002420997560000044
Wherein
Figure BDA0002420997560000045
In the formula, PcapRepresenting actual captured power, P, of the wind turbinewyIs the maximum wind power in the air, v is the wind speed, ngFor gear ratio, T, of the gearboxeRepresenting electromagnetic torque, omegarIndicates the rotational speed JtRepresenting the moment of inertia, ρ representing the air density, and R the rotor radius. Optimum torque gain factor
Figure BDA0002420997560000046
I.e. K corresponding to the maximum efficiency of the average wind energy captured；
Step 1-5: fitting an optimal torque gain coefficient by using 1620 sets of results obtained by traversing as sample data
Figure BDA0002420997560000047
And the average wind energy capture efficiency under the PSF method
Figure BDA0002420997560000048
Functional relationship of
Figure BDA0002420997560000049
The virtual wind turbine generator set is constructed by the following steps:
step 2-1: embedding a FAST model of a wind turbine generator set to which the method is applied into an actual master control PLC (programmable logic controller) of the wind turbine generator set, and constructing a virtual machine set capable of synchronously operating with the actual machine set;
step 2-2: and embedding a PSF method code for MPPT control of the virtual wind turbine generator set in the master control PLC.
The online operation steps are as follows:
step 3-1: setting the torque gain factor optimization period to TwInitializing the torque gain coefficient K of the actual wind turbine generator operationdInitializing initial rotation speed omega of virtual wind turbine generator and actual wind turbine generatorbgnSetting the current time interval as n to be 1 for the lowest rotating speed of the MPPT stage; wherein the torque gain factor optimizes the period TwSetting the value to be 10 min-1 h, and initializing the torque gain coefficient K of the actual wind turbine generator operationdIs 0.9Kopt～0.98Kopt，KoptA torque gain factor for the PSF method;
step 3-2: reading a current actually measured wind speed value, carrying out MPPT control on an actual wind turbine generator by adopting a torque gain reduction method optimized by a torque gain coefficient, carrying out MPPT control on a virtual wind turbine generator in the PLC by adopting a PSF method, and synchronously operating the actual wind turbine generator and the virtual wind turbine generator;
step 3-3: recording the operating data of the virtual wind turbine, including the rotor speed ωrAcceleration of rotor
Figure BDA0002420997560000051
Electromagnetic torque T of generatore；
Step 3-4: judging the nth TwWhether the session is running over. If so, calculating the average wind energy capture efficiency corresponding to the PSF method applied to the virtual wind turbine generator set at the current time period according to the recorded operation data
Figure BDA0002420997560000052
And substituting into the function relation constructed off-line
Figure BDA0002420997560000053
In the process of pre-estimating the optimal torque gain coefficient
Figure BDA0002420997560000054
Otherwise, returning to execute the step 3-2;
step 3-5: the optimal torque gain coefficient given in the step 3-4 is obtained
Figure BDA0002420997560000055
Setting a torque gain coefficient of an n +1 th time period of an actual wind turbine generator;
step 3-6: and n is n +1, jumping to the step 3-2, and entering the next operation period.
The invention belongs to the type of a method for constructing a direct quantitative relation between optimal adjustment parameters and MPPT influence factor characterization indexes to guide parameter online optimization, and can avoid efficiency reduction caused by non-convergence or direction error of iterative search of a self-adaptive algorithm. In addition, the invention realizes the single index depiction of the comprehensive influence of a plurality of indexes on the MPPT, and can simplify the construction complexity of the direct quantity relationship. Therefore, the wind energy capture efficiency can be ensured, the computational resource requirement is greatly reduced, and the engineering practicability is high.
The present invention is described in further detail below with reference to examples:
examples
The method takes a 0.6MW CART3 model of renewable energy laboratory (NREL) of the national department of energy as an application object, and compares wind energy capture efficiency of a wind turbine generator maximum power point tracking control method based on torque gain coefficient optimization, a traditional power curve method and self-adaptive torque control and a method for online application of function relation of offline constructed optimal torque curve adjustment quantity and three wind condition characteristics to consume calculation resources and compare fast implementation through simulation calculation and statistical analysis of a simulated wind speed sequence so as to verify effectiveness and superiority of the method.
Simulation model
The simulation model adopts open-source professional wind turbine simulation software FAST provided by renewable energy laboratory (NREL) of the national department of energy. The wind turbine model corresponds to the 0.6MW CART3 model developed by NREL, with the relevant parameters as follows.
TABLE 1 NREL 0.6MW CART3 wind turbine principal parameters
Figure BDA0002420997560000061
(II) simulation implementation
According to the steps in the invention, the method comprises the following steps:
and (3) offline construction of a functional relation:
step 1-1: aiming at a CRAT3 wind turbine generator to be applied, acquiring pneumatic and structural parameters required for constructing a FAST model of the CRAT3 wind turbine generator, as shown in Table 1;
step 1-2: in FAST software, the construction of a wind turbine generator simulation model is completed according to parameters;
step 1-3: three characteristic indexes (average wind speed) for representing the wind condition of the turbulent flow are changed in sequence by adopting a turbulent flow wind speed simulation method
Figure BDA0002420997560000062
Turbulence intensity TI and turbulence integral scale L), a sequence of turbulent wind speeds corresponding to different combinations of characteristic indicators is generated. Wherein the content of the first and second substances,
Figure BDA0002420997560000063
the variation range of (2) is 4-9 m/s, the step length is 1m/s, the turbulence intensity TI is changed according to A, B, C turbulence level, the variation range of the integral scale L is 100-500 m, and the step length is 50 m. A total of 162 parameter setting combined wind conditions are obtained, and 10 wind speed sequences are generated corresponding to each wind condition;
step 1-4: wind turbine generator optimal torque gain coefficient corresponding to each wind speed sequence based on FAST software traversal
Figure BDA0002420997560000064
And wind energy capture efficiency when applying the PSF method
Figure BDA0002420997560000065
Wherein
Figure BDA0002420997560000071
In the formula, PcapRepresenting actual captured power, P, of the wind turbinewyIs the maximum wind power in the air, v is the wind speed, ngFor gear ratio, T, of the gearboxeRepresenting electromagnetic torque, omegarIndicates the rotational speed JtRepresenting the moment of inertia. Optimum torque gain factor
Figure BDA0002420997560000072
I.e. K corresponding to the maximum efficiency of the average wind energy captured；
Step 1-5: fitting an optimal torque gain coefficient by using 1620 sets of results obtained by traversing as sample data
Figure BDA0002420997560000073
And the average wind energy capture efficiency under the PSF method
Figure BDA0002420997560000074
Functional relationship of
Figure BDA0002420997560000075
Optimal torque gain coefficient corresponding to CART3 wind turbine generator
Figure BDA0002420997560000076
And the average wind energy capture efficiency under the PSF method
Figure BDA0002420997560000077
The relationship of (c) is as shown in FIG. 2.
Figure BDA0002420997560000078
The specific expression of (A) is as follows:
Figure BDA0002420997560000079
constructing a virtual wind turbine generator:
step 2-1: embedding a FAST model of a wind turbine generator set to which the method is applied into an actual master control PLC (programmable logic controller) of the wind turbine generator set, and constructing a virtual machine set capable of synchronously operating with the actual machine set;
step 2-2: and embedding a PSF method code for MPPT control of the virtual wind turbine generator set in the master control PLC.
And (3) online operation:
step 3-1: setting the torque gain factor optimization period to TwInitializing a torque gain coefficient K of the actual wind turbine generator operation in 10mind＝0.9KoptInitializing initial rotation speed omega of virtual wind turbine generator and actual wind turbine generatorbgnSetting the current time interval as n to be 1 for the lowest rotating speed of the MPPT stage;
step 3-2: reading a current actually measured wind speed value, carrying out MPPT control on an actual wind turbine generator by adopting a torque gain reduction method optimized by a torque gain coefficient, carrying out MPPT control on a virtual wind turbine generator in the PLC by adopting a PSF method, and synchronously operating the actual wind turbine generator and the virtual wind turbine generator;
step 3-3: recording the operating data of the virtual wind turbine, including the rotor speed ωrAcceleration of rotor
Figure BDA00024209975600000710
Electromagnetic torque T of generatore；
Step 3-4: judging the nth TwWhether the time interval runs over; if so, calculating the average wind energy capture efficiency corresponding to the PSF method applied to the virtual wind turbine generator set at the current time period according to the recorded operation data
Figure BDA0002420997560000081
And substituting into the function relation constructed off-line
Figure BDA0002420997560000082
In the process of pre-estimating the optimal torque gain coefficient
Figure BDA0002420997560000083
Otherwise, returning to execute the step 3-2;
step 3-5: the optimal torque gain coefficient given in the step 3-4 is obtained
Figure BDA0002420997560000084
Setting a torque gain coefficient of an n +1 th time period of an actual wind turbine generator;
step 3-6: and n is n +1, jumping to the step 3-2, and entering the next operation period.
(III) consumed computing resources
And if the same sample fineness is required to be obtained (namely the wind energy capture efficiency obtained in a statistical level is the same after application), the sample scale required by the relation between the optimal torque gain coefficient and the corresponding wind energy capture efficiency of the PSF method is constructed, namely the calculation resource is only 1 percent. For the embodiment, a common i7 quad-core workstation is adopted to perform offline scanning on the sample size required by the invention, and the scanning can be completed only by consuming about 2 days.
(IV) comparative analysis of wind energy capture efficiency
The method aims at 50 actually measured turbulent wind speed sequences with the duration of 4 hours, and a PSF method, adaptive torque control and the improved method provided by the invention are respectively applied to simulation. Corresponding to each wind speed sequence, calculating P of different MPPT methods relative to PSF methodfavgThe percentage is increased. Table 2 gives the statistical average of 50 examples.
Table 2 comparison of different MPPT control methods
Figure BDA0002420997560000085
As can be seen from table 2, compared with the conventional PSF method and the adaptive torque method, the MPPT method for the wind turbine generator provided by the invention can improve the wind energy capture efficiency.
The torque gain coefficient, the theoretically optimal torque gain coefficient and the change of the average wind energy capture efficiency given by each method at each 10min period are shown in detail below with reference to a specific calculation example, as shown in fig. 3. It can be seen that the adaptive torque method has the phenomenon of search non-convergence and can give a gain coefficient prediction with a large deviation from the optimal value. In comparison, the gain coefficient estimated value provided by the invention is closer to the optimal value, and higher wind energy capture efficiency can be obtained. Specifically, the adaptive torque control is improved by 1.29% compared with the traditional PSF method, and on the basis, the efficiency of the method provided by the invention is further improved by 0.70% compared with the efficiency of the adaptive torque. The embodiment compares the wind energy capture efficiency and the computational resource consumption of the method with other existing MPPT control methods, and verifies the effectiveness and superiority of the method.

Claims (4)

1. A wind turbine generator maximum power point tracking control method based on torque gain coefficient optimization is characterized by comprising the following steps:
(1) offline construction of functional relationships
Step 1-1: acquiring pneumatic and structural parameters required by constructing a FAST model of a wind turbine generator to be applied;
step 1-2: in FAST software, finishing the construction of a wind turbine generator simulation model according to parameters;
step 1-3: a turbulent wind speed simulation method is adopted, and three characteristic indexes representing turbulent wind conditions are changed in sequence: mean wind speed
Figure FDA0003365338990000018
Generating a turbulent wind speed sequence corresponding to different characteristic index combinations by using the turbulent intensity TI and the turbulent integral scale L;
step 1-4: wind turbine generator optimal torque gain coefficient corresponding to each wind speed sequence based on FAST software traversal
Figure FDA0003365338990000011
And wind energy capture efficiency when applying the PSF method
Figure FDA0003365338990000012
Wherein
Figure FDA0003365338990000013
In the formula, PcapRepresenting actual power captured by the wind turbine, PwyIs the maximum wind power in the air, v is the wind speed, ngFor gear ratio of gear box, TeRepresenting electromagnetic torque, ωrDenotes the rotational speed, JtRepresenting the moment of inertia, rho representing the air density, and R representing the radius of the wind wheel; optimum torque gain factor
Figure FDA0003365338990000014
I.e. K corresponding to the maximum efficiency of the average wind energy captured；
Step 1-5: fitting the result obtained by traversing as sample data to obtain an optimal torque gain coefficient
Figure FDA0003365338990000015
And the average wind energy capture efficiency under the PSF method
Figure FDA0003365338990000016
Functional relationship of
Figure FDA0003365338990000017
(2) Virtual wind turbine generator system construction
Step 2-1: embedding a FAST model of a wind turbine generator to be applied into an actual master control PLC of the wind turbine generator, and constructing a virtual generator which can synchronously run with the actual generator;
step 2-2: embedding a PSF method code for MPPT control of a virtual wind turbine generator in a master control PLC;
(3) on-line operation
Step 3-1: setting the torque gain factor optimization period to TwInitializing the torque gain coefficient K of the actual wind turbine generator operationdInitializing initial rotation speed omega of virtual wind turbine generator and actual wind turbine generatorbgnSetting the current time interval as n to be 1 for the lowest rotating speed of the MPPT stage;
step 3-2: reading a current actually measured wind speed value, carrying out MPPT control on an actual wind turbine generator by adopting a torque gain reduction method optimized by a torque gain coefficient, carrying out MPPT control on a virtual wind turbine generator in the PLC by adopting a PSF method, and synchronously operating the actual wind turbine generator and the virtual wind turbine generator;
step 3-3: recording the operating data of the virtual wind turbine, including the rotor speed ωrAcceleration of rotor
Figure FDA0003365338990000021
Electromagnetic torque T of generatore；
Step 3-4: judging the nth TwWhether the time interval runs over; if so, calculating the average wind energy capture efficiency corresponding to the PSF method applied to the virtual wind turbine generator set at the current time period according to the recorded operation data
Figure FDA0003365338990000022
And substituting into the function relation constructed off-line
Figure FDA0003365338990000023
In the process of pre-estimating the optimal torque gain coefficient
Figure FDA0003365338990000024
Otherwise, returning to execute the step 3-2;
step 3-5: the optimal torque gain coefficient given in the step 3-4 is obtained
Figure FDA0003365338990000025
Setting a torque gain coefficient of an n +1 th time period of an actual wind turbine generator;
step 3-6: and n is n +1, jumping to the step 3-2, and entering the next operation period.
2. Wind turbine generator maximization based on torque gain factor optimization according to claim 1A power point tracking control method, characterized in that, in step 1-3,
Figure FDA0003365338990000026
the variation range of (2) is 4-9 m/s, the step length is 1m/s, the turbulence intensity TI is changed according to A, B, C turbulence level, the variation range of the integral scale L is 100-500 m, and the step length is 50 m; a total of 162 parameter sets are available to combine wind conditions, generating a sequence of 10 wind speeds for each wind condition.
3. The wind turbine generator maximum power point tracking control method based on torque gain coefficient optimization according to claim 2, wherein in steps 1-5, the optimal torque gain coefficient is fitted by using 1620 sets of results obtained by traversal as sample data
Figure FDA0003365338990000027
And the average wind energy capture efficiency under the PSF method
Figure FDA0003365338990000028
Functional relationship of
Figure FDA0003365338990000029
4. The wind turbine generator maximum power point tracking control method based on torque gain coefficient optimization according to claim 1, wherein the torque gain coefficient optimization period T in step 3-1wSetting the value to be 10 min-1 h, and initializing the torque gain coefficient K of the actual wind turbine generator operationdIs 0.9Kopt～0.98KoptIn which K isoptIs the torque gain factor of the PSF method.
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