CN113685314B - Pitch control method, system and readable storage medium - Google Patents

Pitch control method, system and readable storage medium Download PDF

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Publication number
CN113685314B
CN113685314B CN202110975943.6A CN202110975943A CN113685314B CN 113685314 B CN113685314 B CN 113685314B CN 202110975943 A CN202110975943 A CN 202110975943A CN 113685314 B CN113685314 B CN 113685314B
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control
pitch
pitch angle
target
rotating speed
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CN113685314A (en
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吴立建
郑松岳
史婷娜
宋鹏
刘嘉明
王思奇
许移庆
朱志权
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Zhejiang University ZJU
Shanghai Electric Wind Power Group Co Ltd
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Zhejiang University ZJU
Shanghai Electric Wind Power Group 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
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/022—Adjusting aerodynamic properties of the blades
    • 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
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/0276—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor controlling rotor speed, e.g. variable speed
    • 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
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/04—Automatic control; Regulation
    • F03D7/042—Automatic control; Regulation by means of an electrical or electronic controller
    • F03D7/043—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic
    • F03D7/045—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic with model-based controls
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/30—Control parameters, e.g. input parameters
    • F05B2270/328—Blade pitch angle
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/72—Wind turbines with rotation axis in wind direction

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  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Fluid Mechanics (AREA)
  • Wind Motors (AREA)

Abstract

The application provides an independent variable pitch control method and system of a fan and a readable storage medium. The independent variable pitch control method comprises the steps of determining an objective function and a data driving model, wherein an independent variable of the objective function comprises a load reduction control target, a dependent variable of the objective function is used for representing the size of a structural load of a fan in variable pitch control, an independent variable of the data driving model comprises a pitch angle rotating speed of the fan, and the data driving model is used for determining the functional relation between at least part of the load reduction control target and the pitch angle rotating speed; determining a corresponding target pitch angle rotating speed when the value of the target function is minimum according to the target function and the data driving model; and carrying out variable pitch control on the fan according to the target pitch angle rotating speed. The load reduction effect is good.

Description

Pitch control method, system and readable storage medium
Technical Field
The invention relates to the field of wind power, in particular to a variable pitch control method, a variable pitch control system and a readable storage medium.
Background
The variable pitch system is one of the core parts of the unit control system, and plays an important role in safe, stable and efficient operation of the wind turbine. On one hand, the pitch controller changes the resistance to the incoming flow wind speed by adjusting the pitch angle of the fan blades, and further controls the aerodynamic torque and power captured by the wind wheel. On the other hand, in the rotation process of the fan, due to the influences of factors such as horizontal and vertical wind shearing, tower shadow effect, wind turbulence, yaw misalignment and the like, the pneumatic load on the impeller surface of the fan is in an unbalanced state. Unbalanced aerodynamic loads can cause structural component loading of the fan wheel face, resulting in fan vibration. In some fan load reduction control strategies, a pitch angle of each fan blade is independently adjusted by a pitch control system of the fan, and the pneumatic load borne by each fan blade is changed to reduce the periodic load of the fan blade and the asymmetric load of the fan blade wheel surface.
However, as the single-machine capacity of the fan is increased and the fan blades are lengthened, the load reduction effect of the fan load reduction control strategies on the fan is reduced.
Disclosure of Invention
The application provides a variable pitch control method, a variable pitch control system and a readable storage medium, and the load shedding effect is good.
The application provides a variable pitch control method, which comprises the following steps:
determining an objective function and a data driving model, wherein the independent variable of the objective function comprises a load reduction control target, the dependent variable of the objective function is used for representing the structural load of a fan in pitch control, and the data driving model is used for determining the functional relation between at least part of the load reduction control target and the rotating speed of a pitch angle;
determining a corresponding target pitch angle rotating speed when the value of the target function is minimum according to the target function and the data driving model;
and carrying out variable pitch control on the fan according to the target pitch angle rotating speed.
The application provides a pitch control system, comprising one or more processors, for implementing a pitch control method as claimed in any one of the preceding claims
The present application provides a readable storage medium having stored thereon a program which, when executed by a processor, implements a pitch control method as defined in any one of the above.
The pitch control method determines a target function and a data driving model, determines a corresponding target pitch angle rotating speed when the structural load value is minimum according to the target function and the data driving model, and then performs pitch control on the fan based on the target pitch angle rotating speed. By controlling the rotating speed of the pitch angle, the fan runs at the rotating speed of the pitch angle when the structural load is minimized in the pitch changing process, the problem of effectiveness reduction of a pitch changing control strategy caused by constant rotating speed of the pitch angle is solved, and the load reduction effect of the fan in the pitch changing process is improved.
Drawings
FIG. 1 is a schematic view of a fan;
FIG. 2 is an enlarged partial cross-sectional view of the blower of FIG. 1;
FIG. 3 is a schematic pitch control flow diagram of the wind turbine of FIG. 1 in one technique;
FIG. 4a is a time series comparison of pitch angle and blade root moment of a wind turbine under one operating condition;
FIG. 4b is another time series comparison of pitch angle and blade root moment of the wind turbine under the same operating conditions as FIG. 4 a;
FIG. 5 is a flow chart of a pitch control method provided by an embodiment of the present application;
FIG. 6 is a sub-flowchart of step S52 in FIG. 5;
FIG. 7 is a block diagram of a pitch control system provided in an embodiment of the present application.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. The following description refers to the accompanying drawings in which the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the exemplary embodiments below do not represent all embodiments consistent with one or more embodiments of the specification. Rather, they are merely examples of apparatus and methods consistent with certain aspects of one or more embodiments of the specification, as detailed in the claims that follow.
It should be noted that: in other embodiments, the steps of the corresponding methods are not necessarily performed in the order shown and described in this specification. In some other embodiments, the methods may include more or fewer steps than those described herein. Moreover, a single step described in this specification may be broken down into multiple steps for description in other embodiments; multiple steps described in this specification may be combined into a single step in other embodiments.
Fig. 1 is a schematic structural diagram of a wind turbine 100. Referring to FIG. 1, a wind turbine 100 is a wind generator, or referred to as a wind turbine. Wind turbine 100 includes a tower 11 extending from a support system 14, a nacelle 12 mounted on tower 11, and a rotor 13 coupled to nacelle 12. The rotor 13 includes a rotatable hub 131 coupled to the nacelle 12 and at least one blade 132 coupled to the hub 131 and extending outwardly from the hub 131.
In some embodiments, if rotor 13 includes a plurality of blades 132, blades 132 are spaced about hub 131 to facilitate rotating rotor 13 to enable kinetic energy to be transferred from the wind energy into usable mechanical energy, and subsequently, electrical energy.
In the present embodiment, the rotor 13 includes three blades 132.
In other embodiments, the rotor 13 may include more or less than three blades 132.
Fig. 2 is an enlarged partial cross-sectional view of fan 100 of fig. 1. Referring to fig. 1 and 2, nacelle 12 includes a rotor shaft 122 (also referred to as either a main shaft or a low speed shaft), a gearbox 123, a high speed shaft 124, a coupling 125, and a motor 126. Hub 131 is rotatably coupled to an electric generator 126 within nacelle 12 via rotor shaft 122, gearbox 123, high speed shaft 124, and coupling 125. Blades 132 impart rotation to hub 131, which drives rotor shaft 122, and rotation of rotor shaft 122 drives gearbox 123, which gearbox 123 in turn drives high speed shaft 124. High speed shaft 124 drives generator 126 through coupling 125 to generate electricity. Thus, the conversion from wind energy to mechanical energy and then to electric energy is realized.
In some embodiments, hub 131 includes pitch assembly 130. Pitch assembly 130 includes a pitch drive system 135, and a pitch controller 134 operatively coupled to pitch drive system 135. Each pitch drive system 135 is coupled to a respective blade 132. Pitch controller 134 controls pitch drive system 135 to vary a pitch angle or blade pitch of respective blades 132 (i.e., an angle that determines a perspective (perspective) of blades 132 with respect to direction 17 of the wind) along pitch axis 133 to control loads and power generated by wind turbine 100. For example, during operation of wind turbine 100, pitch controller 134 may control rotation of blades 132 about pitch axis 133 by controlling pitch drive system 135 such that blades 132 are rotated to a feathered position, thereby facilitating a reduction in a rotational speed of rotor 13 and/or facilitating a stall of rotor 13. For another example, during operation of wind turbine 100, pitch controller 134 may control a rotational speed of rotor 13, and thus a power of generator 126, by controlling pitch drive system 135 to adjust a pitch angle of blades 132. Specifically, pitch assembly 130 includes at least one pitch bearing 136 coupled to hub 131 and to respective blade 132. Pitch drive system 135 includes pitch drive motor 137, pitch drive gearbox 138, and pitch drive pinion 139. Pitch drive motor 137 is coupled to pitch drive gearbox 138 such that pitch drive motor 137 imparts mechanical force to pitch drive gearbox 138. Pitch drive gearbox 138 is coupled to pitch drive pinion 139 such that pitch drive pinion 139 is rotated by pitch drive gearbox 138. Pitch bearing 136 is coupled to pitch drive pinion 139 such that rotation of pitch drive pinion 139 causes pitch bearing 136 to rotate, which in turn rotates blade 132 about pitch axis 133 in order to change the pitch angle or blade pitch of blade 132.
In some embodiments, pitch controller 134 may be a centralized pitch controller associated with a plurality of pitch drive systems 135. Each pitch controller 134 simultaneously controls multiple pitch drive systems 135 to control a pitch angle or blade pitch of blades 132 corresponding to the multiple pitch drive systems 135.
In other embodiments, pitch controller 134 includes a distributed plurality of individual pitch controllers. Each pitch controller 134 controls a corresponding one of pitch drive systems 135 to control a pitch angle or blade pitch of blade 132 corresponding to that pitch drive system 135.
In some embodiments, the nacelle 12 includes a master controller 121. Pitch controller 134 is communicatively coupled to main controller 121. Pitch controller 134 receives one or more control signals from main controller 121 and/or transmits signals indicative of operational information of blades 132 to pitch controller 134 to control the pitch angle or blade pitch of blades 132.
FIG. 3 is a schematic pitch control flow diagram of wind turbine 100 of FIG. 1 in one technique.
Referring to FIG. 3, pitch controller 134 includes a centralized pitch controller 1341 and an independent pitch controller 1342. The centralized pitch controller 1341 obtains a reference rotation speed w according to the current rotation speed w of the rotor 13 and the predicted wind speed refTo obtain the pitch angle β theoretically required for the three blades 132cFor controlling the aerodynamic torque and power captured by the wind turbine 100; the independent pitch controller 1342 obtains the pitch angle β theoretically required to be reached by the three blades 132 according to the current torques M1, M2 and M3 of the three blades 132 sensed by the sensors1、β2、β3And is used for load shedding control of the fan 100. The pitch controller 134 adjusts the pitch angle β according toc、β1、β2、β3The pitch control of the blades 132 is performed by controlling the pitch drive system 135, and the load shedding control of the wind turbine 100 is performed while controlling the aerodynamic torque and power captured by the wind turbine 100.
In fig. 3, the pitch control principle of the wind turbine 100 is: the pitch controller 134 controls the pitch drive system 135 to rotate the blades 132 to the corresponding angular positions at a constant pitch angle speed according to the pitch angle that each blade 132 theoretically needs to achieve. However, as fan technology develops, the single-machine capacity of fan 100 increases, blades 132 lengthen, the volume of fan 100 increases, and the inertia of blades 132 during rotation increases. The variable pitch control technology based on the constant rotating speed of the pitch angle has the problem that the load reduction control effect is reduced. Specifically, on the one hand, the pitch angle of blades 132 may not be accurately controlled. If the rotational speed of the pitch angle of the blade 132 is set too high, after the blade 132 rotates to the pitch angle position that theoretically needs to be reached, the blade 132 may not be braked in time due to too high inertia, so that the pitch angle position to which the blade 132 actually rotates and the pitch angle position that theoretically needs to be reached have a deviation, and the load shedding control effect of the fan 100 is reduced; on the other hand, the timeliness of the load reduction control is reduced. For example, when the pitch angle rotation speed of the blade 132 is small, the torque for driving the blade 132 to rotate is small, and the time for the blade 132 to change from the stopped state to the rotated state is long, which reduces the timeliness of the load shedding control and reduces the load shedding control effect. Therefore, in order to improve the load shedding control effect of wind turbine 100, it is necessary to perform pitch control on wind turbine 100 based on a pitch control strategy in which the rotational speed of the pitch angle is variable. For example, in the early stage of pitch control, the blades 132 are controlled to pitch at a higher pitch angle rotating speed, so that the timeliness of load shedding control is improved; in the later stage of pitch control, the blades 132 are controlled to pitch at a smaller pitch angle rotating speed, so that the pitch angle deviation caused by inertia is reduced.
Further, the inventors of the present application have found that under the same operating condition (that means the operating environment of the wind turbine 100 is the same, for example, the wind speed and the wind direction at the same position), different pitch angle rotational speed settings may affect the blade root torque of the blade 132. Referring to FIG. 4a and FIG. 4b, in combination, the wind turbine generator dynamics under the same operating condition, FIG. 4a is a time-series comparison of the pitch angle and blade root moment of wind turbine 100 when the rotational speed of blade 132 is set to [ -3.5, 3.5] deg/s. FIG. 4b is a time series comparison of a pitch angle of wind turbine 100 and a blade root moment at a rotational speed of blade 132 set to [ -5,5] deg/s. In fig. 4a and 4b, curves 132_1A, 132_1A represent the change over time of the pitch angle of the three blades 132, respectively, and based on the curves 132_1A, the pitch angle rotational speed can be determined for different periods of time. The curves 132_1B, 132_1B correspond to the curves 132_1A, 132_1A one to one, and respectively represent the change characteristics of the root moments of the three blades 132 with time. As can be seen from fig. 4a and 4b, at different pitch angle rotational speed settings, the position of the pitch angle of wind turbine 100 is influenced, further resulting in different blade root moments for the three blades 132. Different blade root moments can cause the unbalanced load moment of the impeller surface of the fan 100, and the unbalanced load moment of the impeller surface can aggravate the vibration of the fan 100, so that the structural load of the fan 100 is increased; conversely, if the blade face load moment is balanced, the vibration of fan 100 is small and the structural load of fan 100 is small.
In summary, when the wind turbine 100 is subjected to pitch control based on the pitch control strategy with the variable pitch angle rotation speed, the influence of the pitch angle rotation speed on the structural load needs to be considered. In order to achieve a better load reduction control effect, the corresponding pitch angle rotating speed when the structural load is minimum needs to be selected. Based on the above description, the present application proposes a pitch control method, whose basic idea is: in a control period of the variable pitch control, wind speed information in a future period (also called a prediction period corresponding to the control period) after the control period is predicted, and the rotating speed of the pitch angle in the prediction period is determined based on the predicted wind speed information, so that the variable pitch control is performed on the fan in the prediction period according to the predicted rotating speed of the pitch angle. Wherein the predicted pitch angle rotation speed satisfies the following conditions: the structural loading of wind turbine 100 during the prediction cycle may be minimized.
FIG. 5 is a flow chart of a pitch control method provided by an embodiment of the present application. The pitch control method may be applied to wind turbine 100 in FIG. 1, such as to a master controller 121 of wind turbine 100. The pitch control method includes steps S51 to S53.
Step S51, determining an objective function and a data driving model, wherein the independent variable of the objective function comprises a load reduction control target, the dependent variable of the objective function is used for representing the structural load of the fan in the pitch control, and the data driving model is used for determining the functional relation between at least part of the load reduction control target and the pitch angle rotating speed.
In some embodiments, the derating control objective refers to an influencing factor of the structural load of the wind turbine 100. Taking the stress value of the top of the tower 11 of the wind turbine 100 in the front-back direction as an example, the stress value of the top of the tower 11 in the front-back direction may affect the structural load of the wind turbine 100, and the change of the stress value of the top of the tower 11 in the front-back direction may affect the structural load of the wind turbine 100. The structural load of wind turbine 100 may be controlled by controlling the fore-aft force level at the top of tower 11 of wind turbine 100. Therefore, the fore-and-aft force value of the top of the tower 11 can be referred to as a load shedding control target. In the present embodiment, the load shedding control targets include, but are not limited to, a pitch angle speed change rate of the wind turbine 100 during the pitch control, a front-back direction force value of the top of the tower 11, and a blade root moment average value of the blades 132 and a blade root moment difference of each blade 132.
The objective function will be described below by taking as an example that the load shedding control target of the present application includes only the pitch angle speed change rate, the fore-and-aft direction force value of the top of the tower 11, and the blade root moment difference between the blade root moment average value of the blades 132 and each blade root moment of the blades 132.
In some embodiments, the expression of the objective function may be expressed as expression (1):
Figure BDA0003227619360000071
Where J represents an objective function value. The larger the value of J is, the larger the structural load of the wind turbine 100 in a future period (prediction period) after a control period is; conversely, this means that the structural load of wind turbine 100 is less for a future period of time (predicted period) after a control period. t is t0Indicating the starting time point of the prediction period, and n indicating the prediction step size of the prediction period; Δ t represents the duration of each prediction step;
Figure BDA0003227619360000072
representing the mean value of blade root moments of the three rotor blades 1, 2 and 3 in a prediction period; m is a group ofiRepresenting the blade root moment of the ith rotor blade in the z-th prediction step of the prediction period, wherein the value of z is 1, 2 … … and n;
Figure BDA0003227619360000073
representing the root moment mean of the blades 132 and the root moment difference of each blade 132; ffore-aftIndicates the predicted weekThe fore-and-aft stress value of the top of the tower 11 within the z-th predicted step length Δ t;
Figure BDA0003227619360000074
representing a pitch angle speed rate of change of the i-th rotor blade within a z-th prediction step Δ t of the prediction period; as can be seen from the above-mentioned related description,
Figure BDA0003227619360000075
Ffore-aft、
Figure BDA0003227619360000076
respectively representing load shedding control targets; w is a1(vwind)、w2(vwind)、w3(vwind) Respectively representing the weight values of the corresponding load reduction control targets. Wherein,
Figure BDA0003227619360000077
(Ffore-aft)2、
Figure BDA0003227619360000078
or in absolute value form, e.g.
Figure BDA0003227619360000079
And the value for ensuring the load reduction control target is positive.
In some embodiments, considering that the wind turbine PLC controller does not support the integral algorithm during execution, expression (1) may also be expressed as a discrete form in expression (2):
Figure BDA0003227619360000081
wherein k represents the kth control period, and j represents the jth prediction step length in the kth control period.
In some embodiments, the data-driven model may be built based on Kriging (Kriging) interpolation and operational data of the wind turbine 100. The operational data of the wind turbine 100 may be a wind turbineThe simulation data of 100 includes pitch angle rotation speed, wind direction, pitch angle of fan 100 at a plurality of sampling time points under different working conditions, blade root moment of blade 132, fore-and-aft direction stress value of the top of tower 11, and the like. The data-driven model takes the state of the fan as output and takes the independent variable parameters related to the state of the fan as input. Fan conditions include, but are not limited to, blade root moment M of blade 132iFore-and-aft force value F of the top of the tower 11fore-aft. The independent variable parameter related to the state of the fan includes the pitch angle rotation speed. And different fan states correspond to different data driving models. To reduce the load of the control target
Figure BDA0003227619360000082
For example, the data-driven model may determine the root moment M of the ith blade 132 iAnd the pitch angle rotating speed, and further determining the load shedding control target based on the function relation
Figure BDA0003227619360000083
A functional relationship with pitch angle rotational speed; then controlling the target F by load reductionfore-aftFor example, based on a data-driven model, the load shedding control target F can be directly determinedfore-aftAs a function of pitch angle speed. And substituting the functional relationship between the load reduction control target and the rotating speed of the pitch angle, which is determined according to the data driving model, into the expression (1) or (2), so as to establish the functional relationship between the target function value and the rotating speed of the pitch angle.
In some embodiments, the data-driven model built based on kriging interpolation may be expressed as expression (3):
Figure BDA0003227619360000084
according to the principle of the kriging method, the meaning of each parameter in the expression (3) is as follows:
y (x) represents a fan state; x represents an independent variable parameter vector related to the state of the fan;
Figure BDA0003227619360000085
a regression model representing a global approximation to y (x); f. ofp(x) Is a basis function of the regression model; c ═ c1,c2,…,cp]TA regression coefficient vector of the regression model; m represents the number of independent variable parameters related to the state of the fan; z (x) represents a regression model
Figure BDA0003227619360000091
The mean of the systematic deviation function of approximate y (x) is 0, and the covariance matrix can be expressed as expression (4):
Figure BDA0003227619360000092
Wherein,
Figure BDA0003227619360000093
the variance of z (x) is expressed,
Figure BDA0003227619360000094
and (3) representing the spatial correlation between the test points x and x' by using a correlation function taking theta as a hyper-parameter. In this embodiment, R (x)p,xp′,θp) And (3) taking a one-dimensional correlation function, specifically adopting a Gaussian function, and expressing as an expression (5):
Figure BDA0003227619360000095
it can be understood that x and y (x) in the expression (3) are different for different fan states, that is, the data driving models corresponding to different fan states are different. For example, when the fan state is the blade root moment of the blade 132, y (x) represents the value of the blade root moment, x represents the independent variable parameter vector related to the blade root moment, and m represents the number of the independent variable parameters related to the blade root moment; for another example, when the fan state is the front-rear direction stress value of the top of the tower 11, y (x) represents the value of the front-rear direction stress value of the tower 11, x represents the independent variable parameter vector related to the front-rear direction stress value of the top of the tower 11, and m represents the number of the independent variable parameters related to the front-rear direction stress value of the top of the tower 11. By performing regression analysis on the operation data of the fan 100, the regression coefficient vector c of the data driving model corresponding to each fan state can be determined, and then the data driving model corresponding to each fan state is determined. The data driving model will be described by taking the fan status as the blade root moment of the blade 132 and the fore-and-aft direction stress value of the top of the tower 11 as examples.
In some embodiments, the root moment of the blade 132 is the fan state, and the root moment is the associated argument vector of the root moment
Figure BDA0003227619360000096
Wherein, VwindA wind speed indicative of an environment in which wind turbine 100 is located; thetawindA wind direction indicating an environment in which fan 100 is located; sigmawindRepresenting the wind shear coefficient; thetaazimuthThe azimuth angle of the blade 132 during rotation is shown for describing the tower shadow effect; beta is aiRepresents the pitch angle of the ith blade 132;
Figure BDA0003227619360000097
representing the pitch angle rotational speed of the ith blade 132; omegarThe rotational speed of the rotor 13 of the i-th blade 132 is indicated. The root moment of the ith blade 132 may be expressed as expression (6):
Figure BDA0003227619360000098
in expression (6), MiIllustrating the blade root moment of the ith blade 132 of the wind turbine 100,
Figure BDA0003227619360000099
the argument parameter corresponding to the root moment of the ith blade 132 is represented.
Similarly, when the fan state is the fore-and-aft direction stress value of the top of the tower 11, the independent variable parameter vector related to the fore-and-aft direction stress value of the top of the tower 11
Figure BDA0003227619360000101
Wherein, VwindRepresenting wind speed; thetawindRepresents the wind direction; sigmawindRepresenting the wind shear coefficient; thetaazimuthThe azimuth angle of the blade 132 during rotation is shown for describing the tower shadow effect; beta is a1,β2,β3Representing the pitch angles of the three blades 132, respectively;
Figure BDA0003227619360000102
representing the pitch angle rotational speed of the three blades 132, respectively. The fore-and-aft direction stress value of the top of the tower 11 can be expressed by expression (7):
Figure BDA0003227619360000103
In expression (7), Ffore-aftIndicating fore and aft force values at the top of tower 11.
In expressions (6) and (7), the wind speed VwindWind direction θwindWind shear coefficient σwindThe predicted incoming wind information is represented as the wind speed V within any control period of the pitch control and predicted in a future period (namely a predicted period) by a laser radar and the likewindWind direction θwindWind shear coefficient σwind. The predicted incoming wind information can be directly substituted into the expression (6) or (7), and other parameters are converted into the rotating speed through the pitch angle
Figure BDA0003227619360000104
To establish the load shedding control target and the pitch angle rotation speed
Figure BDA0003227619360000105
The functional relationship of (a). By pitch angle beta and rotational speed omega of rotor 13rFor example, the following steps are carried out:
in one embodiment, the speed is rotated by the pitch angle
Figure BDA0003227619360000106
The expression to express the pitch angle β can be expressed as expression (8):
Figure BDA0003227619360000107
where t represents time.
In one embodiment, the speed is rotated by the pitch angle
Figure BDA0003227619360000108
To indicate the rotational speed ω of the rotor 13rThe expression (c) may be determined based on the following method:
according to the related knowledge of the wind turbine, the power calculation formula of the wind turbine 100 can be expressed as expression (9):
Figure BDA0003227619360000109
further, λ can be expressed again as expression (10):
Figure BDA00032276193600001010
wherein λ represents a reference tip speed ratio; ρ is the air density; r is the radius of the rotor 13, C P(λ, β) is the wind energy capture coefficient. Further, CP(λ, β) can be expressed as expression (11):
Figure BDA0003227619360000111
further, λiIt may again be determined based on expression (12):
Figure BDA0003227619360000112
in some embodiments, expression (11) and a in expression (12)1Is 0.5176, a2Is 116, a3Is 0.4, a4 Is 5, a5Is 21, a6Is 0.0068, b1Is 0.08, b2Is 0.035.
From expressions (9) to (12), the pitch angle rotation speed can be determined
Figure BDA0003227619360000113
To indicate the rotational speed ω of the rotor 13rIs described in (1).
In some embodiments, because the operating data of the wind turbine 100 is obtained through simulation, a wind turbine model needs to be established for the wind turbine 100, and the value ranges of the parameters in the data driving model are constrained based on the wind turbine model. In one embodiment, pitch angle rotation speed
Figure BDA0003227619360000114
Rotational speed ω of rotor 13rAnd the constraints on the effective power output of wind turbine 100 are as follows:
Figure BDA0003227619360000115
ωr_cut≤ωr≤ωr_rate
95％·Pref≤Pg≤105％·Pref
wherein,
Figure BDA0003227619360000116
represents a minimum pitch angle rotational speed of wind turbine 100;
Figure BDA0003227619360000117
represents a maximum pitch angle rotational speed of wind turbine 100;
ωr_cutindicates the cut-in rotational speed of the rotor 13; omegar_rateIndicates the rated rotational speed of the rotor 13;
Prefrepresenting an active power reference for wind turbine 100.
In addition, the expressions (1) and(2) in the method, the change rate of the pitch angle speed can be directly expressed as the pitch angle rotating speed of two predicted step lengths before and after
Figure BDA0003227619360000118
Difference of between, therefore, for a load shedding control target
Figure BDA0003227619360000119
Determining a load shedding control target without establishing a corresponding data-driven model
Figure BDA00032276193600001110
And pitch angle speed.
In some embodiments, considering that the wind conditions of the environment where the wind turbine 100 is located are in a changing process, on one hand, the weights of the load reduction control targets in the above expression (1) and expression (2) may be different under different operating conditions. For example, at a wind speed of 10m/s, the rate of change of pitch angle speed over the period is predicted
Figure BDA0003227619360000121
Weight w of3(vwind) Possibly 0.2, but at a wind speed of 18m/s, the rate of change of pitch angle speed over the period is predicted
Figure BDA0003227619360000122
Weight w of3(vwind) May need to be adjusted to 0.5. On the other hand, under different wind conditions, the predicted incoming flow wind information acquired in each control cycle may be different, in order to make the objective function and the data driving model have adaptivity and improve prediction accuracy, in some embodiments of the present application, for any control cycle, according to the predicted incoming flow wind information corresponding to the control cycle, weight values corresponding to a plurality of load shedding control targets in the objective function corresponding to the control cycle are determined, and meanwhile, the data driving model is used for determining a functional relationship between at least part of the load shedding control targets and the pitch angle rotation speed of the corresponding control cycle according to the predicted incoming flow wind information corresponding to each control cycle in the plurality of control cycles.
Further, the predicted incoming wind information for each control period may include predicted incoming wind information for a plurality of prediction steps after the corresponding control period. For any control cycle, according to the predicted incoming wind information in any prediction step length after the control cycle, the functional relationship between at least part of the off-load control targets corresponding to the prediction step length and the pitch angle rotating speed of the control cycle and the weight value of each off-load control target of the target function corresponding to the prediction step length of the control cycle can be determined. Based on this, the above expression (6) can be expressed again as expression (15):
Figure BDA0003227619360000123
wherein M isi(k + j) represents the root moment of the ith blade 132 at the jth predicted step of the kth control cycle.
Similarly, the above expression (7) can be expressed as expression (16):
Figure BDA0003227619360000124
wherein,
Figure BDA0003227619360000131
representing the fore-aft stress value of the tower 11 at the jth predicted step length of the kth control cycle.
With continued reference to FIG. 5, after determining the objective function and the data-driven model, step S52 may be performed.
And step S52, determining the corresponding target pitch angle rotating speed when the value of the objective function is minimum according to the objective function and the data driving model.
According to the related description, the data driving model is mainly used for determining the functional relationship between at least part of the load shedding control targets and the pitch angle rotating speed of each control period according to the predicted incoming wind information of each control period, and further determining the corresponding target pitch angle rotating speeds according to the functional relationship between the target function and the pitch angle rotating speed of at least part of the load shedding control targets determined by each control period. Referring to fig. 6 in combination, fig. 6 is a sub-flowchart of step S52 in fig. 5, including step S61 and step S62.
Step S61, for any control period, determining an objective function to be solved according to the objective function and the functional relationship between at least part of the load shedding control objective determined by the control period and the rotating speed of the pitch angle, wherein the independent variable of the objective function to be solved comprises the rotating speed of the pitch angle, and the dependent variable of the objective function to be solved is used for representing the size of the structural load of the fan in the pitch control.
In some embodiments, as can be seen from the above description, the functional relationship between at least part of the load shedding control target and the pitch angle rotation speed determined by the control period may be substituted into the objective function to obtain the objective function to be solved for the control period.
Further, for a control period including multiple prediction step lengths, an objective function to be solved corresponding to any prediction step length after the control period may be determined according to the objective function and a functional relationship between at least part of the load shedding control target corresponding to the prediction step length after the control period and the pitch angle rotation speed. Namely, the functional relationship between at least part of the load shedding control target corresponding to each prediction step length and the rotating speed of the pitch angle is substituted into the objective function to obtain the objective function to be solved corresponding to the prediction step length.
And step S62, solving the objective function to be solved based on the intelligent optimization solving algorithm so as to determine the corresponding target pitch angle rotating speed.
For a control cycle comprising a plurality of prediction step sizes, solving an objective function to be solved corresponding to each prediction step size of the control cycle based on an intelligent optimization solving algorithm to determine a corresponding target pitch angle rotating speed. In some embodiments, M particles may be searched in space to determine a sequence of target pitch angle rotational speeds for the control cycle corresponding to a plurality of predicted step sizes. Specifically, the iteration may be performed N times in the control period, and one pitch angle rotation speed corresponding to each prediction step length in the control period may be determined for each iteration for all prediction step lengths corresponding to the control period, that is, for each iteration. For example, if a control cycle corresponds to 10 prediction steps, the wind turbine 100 includes 3 blades 132, and each iteration is performed, 10 × 3 pitch angle rotation speeds may be determined, where the 10 × 3 pitch angle rotation speeds correspond to the 10 prediction steps, respectively, and are an optimal point at which the value of the objective function shown in expression (2) is minimized in the current iteration.
It is assumed here that in the ith iteration of the kth control cycle, the rotation speed of the pitch angle of the three blades 132 corresponding to the jth prediction step represented by the ith particle can be expressed as expression (17):
Figure BDA0003227619360000141
Where l is 1,2, …, M, i is 1,2, …, N, i _1, i _2, and i _3 are used to distinguish the three blades 132.
Then, at the ith iteration of the kth control cycle, the pitch angle rotation speeds of the three blades 132 corresponding to all the predicted step sizes represented by the ith particle can be expressed as expression (18):
Figure BDA0003227619360000142
where n represents the number of prediction steps.
When the target pitch angle rotating speed corresponding to the minimum value of the objective function is found, the ith particle can define the track in the parameter space according to an expression (19) and an expression (20):
Figure BDA0003227619360000143
Figure BDA0003227619360000144
Figure BDA0003227619360000145
representing the rotation speed of the pitch angle of the i +1 th iteration
Figure BDA0003227619360000146
Pitch angle rotation speed relative to ith iteration
Figure BDA0003227619360000147
The rate of change of (c);
Figure BDA0003227619360000148
represents the pitch angle rotation speed of the (i + 1) th time;
Figure BDA0003227619360000149
a local optimal point corresponding to the objective function value shown in the expression (2) in the ith iteration is obtained;
Figure BDA00032276193600001410
and (3) a global optimum point corresponding to the objective function with the minimum value shown in the expression (2) in all iterations from 1 to i.
c1And c2Is a learning factor;
r1and r2Is uniformly distributed with [0,1 ]]Two random numbers in between;
ω is the inertial weight, representing the pair
Figure BDA0003227619360000151
Inheritance of the rate of change of speed of (c).
Based on the above calculation, the pitch angle rotation speed of each predicted step length corresponding to the time when the value of the objective function in the objective function is minimized after N iterations in the k-th control period can be finally determined, and the pitch angle rotation speed is used as the target pitch angle rotation speed. Assuming herein that the target pitch angle rotation speed is
Figure BDA0003227619360000152
Then
Figure BDA0003227619360000153
Can be expressed as expression (20):
Figure BDA0003227619360000154
wherein,
Figure BDA0003227619360000155
representing the rotating speed of the pitch angle corresponding to the 1 st predicted step length of the kth control period;
in a similar manner, the first and second substrates are,
Figure BDA0003227619360000156
representing the pitch angle rotating speed corresponding to the 2 nd predicted step length of the kth control period;
in a similar manner, the first and second substrates are,
Figure BDA0003227619360000157
and the pitch angle rotating speed corresponding to the nth predicted step length in the kth control period is shown.
And solving the objective function to be solved based on the particle swarm algorithm, so that the solving speed is high and the convergence is better.
With continued reference to FIG. 5, in determining the target pitch angle speed, step S53 may continue to be performed.
Step S53, pitch control is performed on the wind turbine 100 according to the target pitch angle rotation speed.
In some embodiments, for any control period, the target pitch angle rotational speed determined during that control period is based on
Figure BDA0003227619360000158
The pitch control of the wind turbine 100 is performed in the next control period after the control period. Therefore, when the wind turbine 100 is subjected to pitch control in the next control period, the rotating speed of the pitch angle enables the structure load to be minimum.
Further, in some embodiments, the relationship between the control period, the prediction period, and the prediction step size may be such that: for example, assuming that each second is a control cycle, the prediction cycle corresponding to each control cycle is a period 10 seconds after the corresponding control cycle, and within the prediction cycle, every 1 second is a prediction step.
Based on the above assumptions, it is obvious that in the first control cycle (e.g. 1 st second), the target pitch angle rotation speed for each prediction step in the first prediction cycle (e.g. 2 nd to 11 th seconds) is determined, i.e. the target pitch angle rotation speeds for 2 nd, 3 rd, … … th, and 11 th seconds are determined respectively;
similarly, in the second control period (2 nd second), the target pitch angle rotation speed for each prediction step in the second prediction period (3 rd to 12 th seconds) is determined, i.e., the target pitch angle rotation speeds for the 3 rd, 4 th, … … th and 12 th seconds are determined, respectively.
According to the above example, in the first control period (1 st second), only the target pitch angle rotation speed of the first prediction step length (2 nd second) in the first prediction period needs to be output, so as to perform pitch control on the wind turbine 100 in the second control period (2 nd second); when the wind turbine 100 is operated for the 3 rd second, the second control period outputs the target pitch angle rotation speed for the 3 rd second already based on the latest predicted incoming wind information, and at this time, the pitch control of the wind turbine 100 may be performed based on the target pitch angle rotation speed for the first prediction period (3 rd second) output by the second control period (2 nd second). That is, for any control cycle, the target pitch angle rotational speed corresponding to the first predicted step according to the control cycle, that is, the target pitch angle rotational speed of the first column of expression 20
Figure BDA0003227619360000161
The wind turbine 100 is pitch controlled in a next control cycle after the control cycle. In this way, the structural load of the wind turbine 100 can be further reduced during the pitching process.
Based on the above description, in some embodiments of the present application, the pitch control method determines the target function and the data driving model, determines the target pitch angle rotation speed corresponding to the minimum target function value according to the target function and the data driving model, and then performs pitch control on the wind turbine 100 based on the target pitch angle rotation speed. By controlling the rotating speed of the pitch angle, the fan 100 runs at the rotating speed of the pitch angle when the structural load is minimized in the pitch changing process, the problem of effectiveness reduction of a pitch changing control strategy caused by constant rotating speed of the pitch angle is solved, and the load reduction effect of the fan 100 in the pitch changing process is improved.
FIG. 7 is a block diagram of pitch control system 800 provided by an embodiment of the present application.
The pitch control system 800 includes one or more processors 801 for implementing the pitch control method as described above. In some embodiments, pitch control system 800 may include a readable storage medium 809, where readable storage medium 809 may store a program that may be invoked by processor 801, which may include a non-volatile storage medium.
In some embodiments, pitch control system 800 may include a memory 808 and an interface 807.
In some embodiments, pitch control system 800 may also include other hardware depending on the application.
The readable storage medium 809 of the embodiments of the application has stored thereon a program for implementing the pitch control method as described above when executed by the processor 801.
This application may take the form of a computer program product embodied on one or more readable storage media 809 (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having program code embodied therein. Readable storage media 809 includes permanent and non-permanent, removable and non-removable media, and information storage may be accomplished by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of readable storage media 809 include, but are not limited to: phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technologies, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic tape storage or other magnetic storage devices, or any other non-transmission medium, may be used to store information that may be accessed by a computing device.
The above description is only a preferred embodiment of the present disclosure, and should not be taken as limiting the present disclosure, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
The above description is only a preferred embodiment of the present disclosure, and should not be taken as limiting the present disclosure, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.

Claims (11)

1. A pitch control method, comprising:
determining an objective function, wherein the independent variable of the objective function comprises a load shedding control target, the load shedding control target is an influence factor of the structural load of the fan in the variable pitch control, and the dependent variable of the objective function is used for expressing the structural load of the fan in the variable pitch control;
determining a data driving model according to the operating data of the fan, wherein the data driving model takes the fan state as output and takes the independent variable parameters related to the fan state as input, and is used for determining the functional relation between at least part of the load shedding control target and the rotating speed of the pitch angle;
determining a corresponding target pitch angle rotating speed when the value of the target function is minimum according to the target function and the data driving model;
and carrying out variable pitch control on the fan according to the target pitch angle rotating speed.
2. The pitch control method according to claim 1, wherein the data-driven model is configured to determine a functional relationship between at least part of the off-load control targets and a pitch angle rotation speed of each of a plurality of control periods according to predicted incoming wind information corresponding to each of the control periods;
The determining of the target pitch angle rotating speed corresponding to the minimum value of the target function comprises:
respectively determining corresponding target pitch angle rotating speeds according to the target function and the function relationship between at least part of the load shedding control target and the pitch angle rotating speed determined in each control period;
the pitch control of the fan comprises:
and for any control period, carrying out pitch control on the fan in the next control period after the control period according to the target pitch angle rotating speed determined in the control period.
3. The pitch control method of claim 2, wherein the arguments of the objective function include a plurality of the derating control targets, the pitch control method further comprising:
for any control period, determining weight values corresponding to a plurality of load shedding control targets in the target function corresponding to the control period according to the predicted incoming flow wind information corresponding to the control period.
4. The pitch control method according to claim 2, wherein said determining respective corresponding target pitch angle rotational speeds as a function of at least part of said off-load control targets and pitch angle rotational speeds determined from said objective function and each of said control cycles comprises:
For any control period, determining an objective function to be solved according to the objective function and a function relation between at least part of the load shedding control object and a pitch angle rotating speed determined by the control period, wherein the independent variable of the objective function to be solved comprises the pitch angle rotating speed, and the dependent variable of the objective function to be solved is used for representing the size of the structural load of the fan in pitch control;
and solving the objective function to be solved based on an intelligent optimization solving algorithm so as to determine the corresponding target pitch angle rotating speed.
5. The pitch control method of claim 4, wherein the smart optimization solution algorithm comprises a particle swarm algorithm.
6. The pitch control method of claim 4, wherein the predicted oncoming wind information for each of the control periods comprises predicted oncoming wind information for a plurality of prediction steps after the respective control period;
for any of the control cycles, said determining a functional relationship of at least a portion of the off-load control target and pitch angle rotational speed for the respective control cycle comprises:
determining a functional relation between at least part of the load shedding control target and the rotating speed of the pitch angle of the control period corresponding to the prediction step length according to the predicted incoming wind information in any prediction step length after the control period;
For any one control period, determining an objective function to be solved according to the objective function and the functional relationship between at least part of the load shedding control object and the rotating speed of the pitch angle determined by the control period, wherein the determining comprises the following steps:
determining the target function to be solved of the control period corresponding to the prediction step length according to the target function and the functional relationship between at least part of the load reduction control target corresponding to any prediction step length after the control period and the rotating speed of the pitch angle;
for any one of the control cycles, solving the objective function to be solved to determine the corresponding target pitch angle rotation speed includes:
and solving the objective function to be solved corresponding to each prediction step length in the control period based on an intelligent optimization solving algorithm so as to determine the corresponding target pitch angle rotating speed.
7. The pitch control method according to claim 6, wherein for any one of the control cycles, pitch controlling the wind turbine in a next control cycle after the control cycle according to the target pitch angle rotational speed determined in the control cycle comprises:
and carrying out variable pitch control on the fan in the next control period after the control period according to the target pitch angle rotating speed of the control period corresponding to the first predicted step length.
8. The pitch control method of claim 1, wherein the load shedding control objective comprises a rate of change of pitch angle speed of the wind turbine during pitch control.
9. The pitch control method of claim 1, wherein the data driven model is established based on kriging interpolation and operational data of the wind turbine.
10. A pitch control system, characterized by comprising one or more processors for implementing a pitch control method according to any of claims 1-9.
11. A readable storage medium, characterized in that a program is stored thereon, which program, when being executed by a processor, carries out the pitch control method according to any one of claims 1-9.
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