WO2019127974A1 - Method and apparatus for optimizing loads of wind turbine - Google Patents

Method and apparatus for optimizing loads of wind turbine Download PDF

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Publication number
WO2019127974A1
WO2019127974A1 PCT/CN2018/082347 CN2018082347W WO2019127974A1 WO 2019127974 A1 WO2019127974 A1 WO 2019127974A1 CN 2018082347 W CN2018082347 W CN 2018082347W WO 2019127974 A1 WO2019127974 A1 WO 2019127974A1
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Prior art keywords
load
value
control parameter
predetermined
wind turbine
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PCT/CN2018/082347
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French (fr)
Chinese (zh)
Inventor
马羽龙
彭柳
赵树椿
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新疆金风科技股份有限公司
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Publication of WO2019127974A1 publication Critical patent/WO2019127974A1/en

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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
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/386—
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • 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
    • 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
    • Y02E10/76—Power conversion electric or electronic aspects

Definitions

  • the present application relates generally to the field of wind power generation technology and, more particularly, to a method and apparatus for optimizing the load of a wind turbine.
  • the design of a wind turbine is usually started from the load calculation. To do this, it is necessary to establish a mathematical model of the wind turbine and determine the control strategy. The adjustment of the parameters related to the control strategy will obviously affect the results of the load calculation.
  • a method for optimizing a load of a wind power generator comprising the steps of: acquiring at least one control parameter of a wind power generator, wherein the plurality of wind power generator sets The load of the position is affected by the at least one control parameter; acquiring a load value of the plurality of positions of the wind turbine set corresponding to the at least one control parameter; loading the plurality of positions using a predetermined evaluation model The value is quantized into a single evaluation value; determining whether the evaluation value satisfies a predetermined condition; when the evaluation value does not satisfy the predetermined condition, the predetermined optimization algorithm is used to optimize the at least one control parameter based on the evaluation value to update the at least one control parameter, And performing the step of acquiring at least one control parameter of the wind power generator again, wherein the optimization problem of optimizing the control parameter is such that the evaluation value corresponding to the updated control parameter satisfies a predetermined condition; when the evaluation value satisfies the predetermined condition
  • an apparatus for optimizing a load of a wind power generator comprising: a control parameter acquisition module that acquires at least one control parameter of a wind power generator, wherein the wind power generation The load of the plurality of positions of the unit is affected by the at least one control parameter; the load acquisition module acquires a load value of the plurality of positions of the wind power generator corresponding to the at least one control parameter; a load quantization module, The load value of the plurality of locations is quantized into a single evaluation value using a predetermined evaluation model; the evaluation value judging module judges whether the evaluation value satisfies a predetermined condition; and the control parameter update module uses a predetermined optimization algorithm when the evaluation value does not satisfy the predetermined condition Updating the at least one control parameter based on the evaluation value to update the at least one control parameter, and the control parameter obtaining module acquires the at least one control parameter again, wherein the optimization problem of optimizing the control parameter is such that after updating The evaluation value corresponding
  • a computer readable storage medium storing a computer program that, when executed by a processor, implements the method for optimizing a load of a wind turbine.
  • a control system for a wind power generator set comprising: a processor; a memory storing a computer program, when the computer program is executed by the processor, implementing the above A method for optimizing the load of a wind turbine.
  • the method and apparatus for optimizing the load of a wind power generator can quantify multiple loads of the wind power generator and optimize the parameters of the wind turbine generator controller model based on the quantized values using an optimization algorithm. To help get optimized load results.
  • FIG. 1 shows a flow chart of a method for optimizing a load of a wind power plant according to an embodiment of the present application
  • FIG. 2 is a block diagram showing the structure of an apparatus for optimizing the load of a wind power generator according to an embodiment of the present application.
  • FIG. 1 shows a flow chart of a method for optimizing the load of a wind turbine according to an embodiment of the present application.
  • step S10 at least one control parameter of the wind turbine may be acquired, and loads of the plurality of locations of the wind turbine are affected by the at least one control parameter.
  • control parameters affecting the loads of the plurality of locations of the wind turbine and related to the control strategy of the wind turbine may be obtained as at least one control parameter.
  • a control parameter of a predetermined controller model of the wind turbine may be obtained as at least one control parameter. It should be noted that when the control parameter of the predetermined controller model is acquired as the at least one control parameter, the acquired at least one control parameter may be a control parameter of the same controller model, or may be a control parameter of different multiple controller models. This application does not limit this.
  • the predetermined controller model may be a pitch controller model, a torque controller model, or a filter model.
  • the optimization may take into account multiple loads among the fatigue load and the ultimate load at various locations of the wind turbine.
  • the load at a plurality of positions may include a fatigue load of a bending moment Mx in a first direction of the bottom of the tower, a fatigue load of a bending moment My in the second direction of the bottom of the tower, and a fatigue load of a bending moment My in the second direction of the blade root.
  • the loads at multiple locations may be two or more of the above loads, as well as other types of loads.
  • the predetermined controller model may be a pitch controller model for the above loads.
  • the control parameters of the pitch controller model can be KPPS and KIPS.
  • acquiring the control parameter may refer to acquiring the current value of the control parameter.
  • any value within the range of values of the control parameter can be obtained as the current value.
  • the range of values of the control parameters can be set in advance according to experience.
  • the method illustrated in FIG. 1 may also include the step of initializing at least one control parameter.
  • a control parameter of a predetermined controller model may be initialized, and an initialization value of the control parameter may be acquired as a current value.
  • step S20 load values of a plurality of locations of the wind turbine set corresponding to at least one control parameter may be acquired.
  • the load at a plurality of positions in one embodiment of the present application may be the fatigue load of the bottom Mx, the fatigue load of the bottom My, the fatigue load of the blade root My, the ultimate load of the bottom My, and the limit of the blade root My.
  • the overall model of the wind turbine may be simulated based on the current value of the acquired control parameters to obtain the plurality of load values corresponding to the control parameters.
  • the whole machine model of the wind power generator is simulated based on the acquired at least one control parameter, and the value of the predetermined operating parameter of the wind power generator set is also obtained. This will be described in more detail below.
  • step S30 the plurality of load values are quantized into a single evaluation value using a predetermined evaluation model.
  • a plurality of load values may be quantized to an evaluation value associated with the minimum load using a predetermined evaluation model to perform subsequent optimization based thereon.
  • the predetermined evaluation model may be various functions capable of implementing the evaluation function of an embodiment, and the quantized evaluation value is a value of the function.
  • the predetermined evaluation model may be a fitness function.
  • the predetermined evaluation model may be the product of the sum of the plurality of loads (eg, the accumulated value) and the constraint value.
  • the predetermined evaluation model may be a product of a weighted sum (eg, an accumulated weighting value) of the plurality of loads respectively weighted and a constraint value.
  • respective weights may be applied to a plurality of loads in the evaluation model according to different degrees of attention to the plurality of loads, and different weights may be applied to the plurality of loads in consideration of different magnitudes between the plurality of loads, but the application is not limited thereto. this.
  • the constraint values as described above may reflect constraints for predetermined operational parameters that need to be met for normal operation of the wind turbine.
  • the constraint value can be determined based on constraints required for the predetermined operational parameters to be met by the normal operation of the wind turbine.
  • the predetermined operational parameter may include at least one of a generator rotational speed and a cabin vibration acceleration, but the application is not limited thereto.
  • the constraints described above may include the generator speed being within a predetermined range of generator speeds and the cabin vibration acceleration being within a predetermined range of cabin vibration acceleration.
  • the value of the predetermined operational parameter can be obtained by simulation based on the current value of the acquired at least one control parameter in step S20. Therefore, the constraint value can be determined by judging whether the value of the predetermined operational parameter obtained by the simulation satisfies the above constraint condition.
  • the determining the constraint value according to the constraint condition for the predetermined operational parameter that is required to be met by the normal operation of the wind power generator may include: setting the constraint value to a predetermined value when the predetermined operational parameter satisfies the constraint condition; When the predetermined operational parameter does not satisfy the constraint, the constraint value is set to a value greater than the predetermined value.
  • the predetermined value can be set in advance.
  • the constraint value may be determined to be greater than the predetermined value according to the degree to which the abnormality of the predetermined operating parameter can be accepted (or the magnitude of the abnormality). degree.
  • the constraint value when the generator rotational speed obtained by simulation according to the current value of the control parameter exceeds a predetermined range of the generator rotational speed, the constraint value may be set to a value greater than a predetermined value, thereby increasing the sum of the load values as the quantized evaluation values.
  • the product of the constraint value is merely an example, and the case where the predetermined control parameter of the present application does not satisfy the constraint and the setting of the constraint value are not limited thereto.
  • step S40 it is judged whether or not the evaluation value satisfies the predetermined condition.
  • step S50 the control parameter is updated based on the evaluation value to update the control parameter using the predetermined optimization algorithm, and returns to step S10 to acquire the control parameter again.
  • the optimization problem of optimizing the control parameters is such that the evaluation value corresponding to the updated control parameter (that is, the evaluation value obtained by the steps S20 and S30 for the updated control parameter) satisfies the predetermined condition.
  • the predetermined condition may mean that the evaluation value reaches a minimum value.
  • the predetermined condition may mean that the evaluation value corresponding to the acquired at least one control parameter reaches a minimum value.
  • the evaluation value may be determined to be reached. Minimum value.
  • control parameters can be optimized based on the quantized evaluation values to update the control parameters using various existing optimization algorithms.
  • the optimization algorithm used may be a genetic algorithm or a simplex method, but the application is not limited thereto.
  • the evaluation value corresponding to the acquired at least one control parameter may be The minimum values of all the previous evaluation values are compared, and based on the comparison result, according to the correspondence relationship between the evaluation values and the control parameters, the optimization direction and the amplitude at which the control parameters are to be adjusted next are determined, thereby updating the control parameters. Then, returning to step S10, the at least one control parameter is acquired again.
  • the number of predetermined thresholds may be set for the number of the at least one control parameter.
  • the difference between the first control parameters (eg, KPPS) acquired twice before and after may be referred to as a first difference
  • the difference between the second control parameters (eg, KIPS) acquired twice before and after may be referred to as a second difference.
  • a first predetermined threshold and a second predetermined threshold may be set for the first difference and the second difference, respectively.
  • the same predetermined threshold may be set for the first difference and the second difference. It should be understood that the number of control parameters and predetermined thresholds is not limited thereto.
  • step S60 when the evaluation value satisfies the predetermined condition, the acquired at least one control parameter is taken as the final control parameter.
  • control parameters can be used in the design, simulation and actual operation of subsequent wind turbines to conveniently and efficiently optimize the corresponding loads.
  • Table 1 shows an example of comparing the loads of the above-described plurality of positions before and after the method as described in FIG. 1 and the values of the control parameters.
  • the optimization algorithm is used to update the control parameters of the pitch controller model, so that the fatigue load of the bottom Mx, the fatigue load of the bottom of the tower My, the fatigue load of the blade root My, The ultimate load of the bottom of My Tower has been reduced to some extent. Although the ultimate load of the blade root My is slightly higher than that before the optimization, the load of the wind turbine is generally optimized from the system point of view.
  • FIG. 2 is a block diagram showing the structure of an apparatus for optimizing the load of a wind power generator according to an embodiment of the present application.
  • the apparatus for optimizing the load of a wind power generator includes: a control parameter acquisition module 10, a load acquisition module 20, a load quantization module 30, an evaluation value judgment module 40, and a control parameter update module. 50 and control parameter providing module 60.
  • the control parameter obtaining module 10 acquires at least one control parameter of the wind power generator set, and the loads of the plurality of positions of the wind power generator set are affected by the at least one control parameter.
  • control parameters related to the control strategy of the wind turbine ie, for setting the control strategy
  • a control parameter of a predetermined controller model of the wind turbine may be obtained as at least one control parameter.
  • the control parameter of the predetermined controller model is a control parameter of the wind turbine associated with a plurality of loads of the wind turbine, the plurality of loads being affected by the control parameter.
  • control parameter obtaining module 10 acquires the control parameter of the predetermined controller model as the at least one control parameter
  • the acquired at least one control parameter may be the control parameter of the same controller model, or may be different controllers.
  • the control parameters of the model are not limited in this application.
  • the predetermined controller model may be a pitch controller model, a torque controller model, or a filter model.
  • control parameter acquisition module 10 may obtain the current value of the control parameter.
  • the control parameter acquisition module 10 may obtain any value within the range of values of the control parameter as the current value.
  • the apparatus may further include an initialization module (not shown) for initializing the at least one control parameter.
  • the initialization module can initialize control parameters of a predetermined controller model.
  • the control parameter acquisition module may obtain an initialization value of the control parameter as the current value.
  • the load acquisition module 20 may acquire load values for a plurality of locations of the wind turbine set corresponding to the at least one control parameter.
  • the load acquisition module 20 may simulate a complete machine model of the wind turbine based on the current value of the acquired at least one control parameter, thereby obtaining load values for the plurality of locations corresponding to the at least one control parameter.
  • the load acquisition module 20 may also simulate the overall model of the wind turbine based on the acquired at least one control parameter to obtain a value of a predetermined operational parameter of the wind turbine.
  • the load quantification module 30 quantizes the plurality of load values into a single evaluation value using a predetermined evaluation model.
  • the load quantification module 30 may quantize the plurality of load values into one of the evaluation values associated with the minimum load using a predetermined evaluation model to perform subsequent optimizations based thereon.
  • the predetermined evaluation model may be various functions capable of implementing the evaluation function in some embodiments of the present application, and the quantized evaluation value is a value of the function.
  • the predetermined evaluation model may be a fitness function.
  • the predetermined evaluation model may be the product of the sum of the plurality of loads (eg, the accumulated value) and the constraint value.
  • the predetermined evaluation model may be a product of a weighted sum (eg, an accumulated weighting value) of the plurality of loads respectively weighted to the constraint value.
  • the load quantification module 30 may apply respective weights to a plurality of loads in the evaluation model according to different degrees of attention to the plurality of loads, and may also apply respective weights to the plurality of loads in consideration of different magnitudes between the plurality of loads, but This application is not limited to this.
  • the constraint values as described above may reflect constraints for predetermined operational parameters that need to be met for normal operation of the wind turbine.
  • the load quantification module 30 may determine the constraint value based on constraints for the predetermined operational parameters that need to be met for normal operation of the wind turbine.
  • the predetermined operational parameter may include at least one of a generator rotational speed and a cabin vibration acceleration, but the application is not limited thereto.
  • the constraints described above may include the generator speed being within a predetermined range of generator speeds and the cabin vibration acceleration being within a predetermined range of cabin vibration acceleration.
  • the value of the predetermined operational parameter of the wind turbine can be simulated by the load acquisition module 20 based on the acquired at least one control parameter. Therefore, the constraint value can be determined by the load quantization module 30 by determining whether the value of the simulated predetermined operational parameter satisfies the above constraint.
  • the step of determining the constraint value by the load quantification module 30 may include: when the predetermined operational parameter satisfies the constraint condition, the load quantization module 30 sets the constraint value to a predetermined value; when the predetermined operational parameter does not satisfy the constraint condition The load quantization module 30 sets the constraint value to a value greater than a predetermined value.
  • the predetermined value may be preset by the load quantization module 30.
  • the load quantization module 30 may determine the constraint value according to the degree to which the abnormality of the predetermined operational parameter can be accepted (or the magnitude of the abnormality). A degree greater than a predetermined value.
  • the load quantification module 30 may set the constraint value to a value greater than a predetermined value, thereby increasing the The product of the weighted value of the quantized evaluation value and the product of the constraint value.
  • this is merely an example, and the application is not limited thereto.
  • the evaluation value determination module 40 determines whether the evaluation value satisfies a predetermined condition.
  • the control parameter update module 50 updates the control parameter based on the evaluation value to update the control parameter using a predetermined optimization algorithm, and the control parameter acquisition module 10 acquires the control parameter again.
  • the optimization problem of optimizing the control parameters is such that the evaluation value corresponding to the updated control parameter satisfies a predetermined condition.
  • the predetermined condition may mean that the evaluation value reaches a minimum value.
  • the predetermined condition may mean that the evaluation value quantized by the load quantization module 30 corresponding to the at least one control parameter acquired by the control parameter acquisition module 10 reaches a minimum value.
  • the evaluation value determining module 40 may determine that the evaluation value reaches a minimum value.
  • the control parameter update module 50 may optimize the control parameters based on the quantized evaluation values using existing various optimization algorithms to update the control parameters.
  • the optimization algorithm used by the control parameter update module 50 may be a genetic algorithm or a simplex method, but the application is not limited thereto.
  • the control parameter update module 50 may select at least one acquired by the control parameter acquisition module 10 in the predetermined optimization algorithm.
  • the evaluation value quantized by the load quantization module 30 corresponding to the control parameter is compared with the minimum value of all the previous evaluation values, and based on the comparison result, according to the correspondence relationship between the evaluation value and the control parameter, it is determined that the control parameter is next.
  • the direction and magnitude of the adjustment are optimized to update the control parameters.
  • control parameter acquisition module 10 acquires the at least one control parameter
  • the load acquisition module 20 acquires the load values of the plurality of locations corresponding to the at least one control parameter
  • the load quantization module 30 uses the predetermined evaluation model to the plurality of locations.
  • the load value of the position is quantized into a single evaluation value
  • the evaluation value judging module 40 judges whether the evaluation value satisfies a predetermined condition.
  • the control parameter update module 50 uses the predetermined optimization algorithm to calculate the at least one control parameter based on the evaluation value. optimize.
  • the evaluation value judging module 40 may set the number of predetermined thresholds for the number of the at least one control parameter.
  • the difference between the first control parameters acquired twice before and after may be referred to as the first difference
  • the difference between the second control parameters acquired twice before and after may be referred to as the second difference.
  • a first predetermined threshold and a second predetermined threshold may be set for the first difference and the second difference, respectively.
  • the same predetermined threshold may be set for the first difference and the second difference. It should be understood that the number of control parameters and predetermined thresholds is not limited thereto.
  • the control parameter providing module 60 when the evaluation value judging module 40 judges that the evaluation value satisfies the predetermined condition, the control parameter providing module 60 provides at least one control parameter acquired by the control parameter obtaining module 10 as the final control parameter.
  • the control parameter providing module 60 can provide the control parameters for design, simulation, and actual operation of the subsequent wind turbine to conveniently and efficiently optimize the corresponding load.
  • Embodiments of the present application also provide a control system.
  • the control system includes a processor and a memory.
  • the memory is used to store computer programs.
  • the computer program is executed by a processor such that the processor executes a computer program for the method of optimizing the load of the wind turbine as described above.
  • Embodiments of the present application also provide a computer readable storage medium storing a computer program.
  • the computer readable storage medium stores a computer program that, when executed by a processor, causes the processor to perform the method described above for optimizing the load of the wind turbine.
  • the computer readable recording medium is any data storage device that can store data read by a computer system. Examples of the computer readable recording medium include read only memory, random access memory, read-only optical disk, magnetic tape, floppy disk, optical data storage device, and carrier wave (such as data transmission via the Internet via a wired or wireless transmission path).
  • the above method and apparatus for optimizing the load of a wind power generator using the embodiment of the present application can automatically update the control parameters based on the controller model of the wind turbine using an optimization algorithm, instead of based on the overall model of the wind turbine
  • the linearized data analyzes the time domain and frequency domain and manually adjusts the control parameters, thereby greatly saving labor and resource costs in the design process of the wind turbine.
  • the above method and apparatus for optimizing the load of the wind power generator according to the embodiment of the present application can flexibly select a plurality of optimization algorithms, and the method and the device can be extended not only to the load but also to the power generation amount, the power curve, and the like. Optimization of various indicators and update of related control parameters.

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Abstract

A method for optimizing the loads of a wind turbine, comprising: obtaining at least one control parameter of a wind turbine; obtaining load values at multiple positions of the wind turbine; quantifying the load values at the multiple positions into individual assessment values; determining whether the assessment values satisfy a predetermined condition; if the assessment values do not satisfy the predetermined condition, optimizing the at least one control parameter by using a predetermined optimization algorithm; and if the assessment values satisfy the predetermined condition, using the at least one control parameter as a final control parameter. By using the method and apparatus, multiple loads of a wind turbine can be quantified, and on the basis of quantified values, the controller parameters of the wind turbine are optimized by using an optimization algorithm, to obtain an optimized load result.

Description

用于优化风力发电机组的载荷的方法和装置Method and apparatus for optimizing the load of a wind turbine 技术领域Technical field
本申请总体说来涉及风力发电技术领域，更具体地讲，涉及一种用于优化风力发电机组的载荷的方法和装置。The present application relates generally to the field of wind power generation technology and, more particularly, to a method and apparatus for optimizing the load of a wind turbine.
背景技术Background technique
风力发电机组的设计通常是从载荷计算开始的，为此需要建立风力发电机组数学模型并确定控制策略，而控制策略相关的参数的调整会明显影响载荷计算的结果。The design of a wind turbine is usually started from the load calculation. To do this, it is necessary to establish a mathematical model of the wind turbine and determine the control strategy. The adjustment of the parameters related to the control strategy will obviously affect the results of the load calculation.
在设计阶段，由于风力发电机组是一个复杂的***，设计人员针对某个载荷指标调整控制器模型的参数可能会导致其他多个载荷指标出现不可预期的波动，因此很难便捷地得到相对较优的参数。In the design stage, because the wind turbine is a complex system, the designer adjusts the parameters of the controller model for a certain load index, which may cause unpredictable fluctuations of other multiple load indicators, so it is difficult to get relatively convenient and convenient. Parameters.
发明内容Summary of the invention
根据本申请实施例的一方面，提供一种用于优化风力发电机组的载荷的方法，所述方法包括以下步骤：获取风力发电机组的至少一个控制参数，其中，所述风力发电机组的多个位置的载荷受到所述至少一个控制参数的影响；获取与所述至少一个控制参数对应的所述风力发电机组的所述多个位置的载荷值；使用预定评价模型将所述多个位置的载荷值量化为单个评价值；判断评价值是否满足预定条件；当评价值不满足预定条件时，使用预定优化算法，基于评价值对所述至少一个控制参数进行优化来更新所述至少一个控制参数，并再次执行获取所述风力发电机组的至少一个控制参数的步骤，其中，对控制参数进行优化的优化问题为使得更新后的控制参数所对应的评价值满足预定条件；当评价值满足预定条件时，将获取的所述至少一个控制参数作为最终的控制参数。According to an aspect of an embodiment of the present application, a method for optimizing a load of a wind power generator is provided, the method comprising the steps of: acquiring at least one control parameter of a wind power generator, wherein the plurality of wind power generator sets The load of the position is affected by the at least one control parameter; acquiring a load value of the plurality of positions of the wind turbine set corresponding to the at least one control parameter; loading the plurality of positions using a predetermined evaluation model The value is quantized into a single evaluation value; determining whether the evaluation value satisfies a predetermined condition; when the evaluation value does not satisfy the predetermined condition, the predetermined optimization algorithm is used to optimize the at least one control parameter based on the evaluation value to update the at least one control parameter, And performing the step of acquiring at least one control parameter of the wind power generator again, wherein the optimization problem of optimizing the control parameter is such that the evaluation value corresponding to the updated control parameter satisfies a predetermined condition; when the evaluation value satisfies the predetermined condition Determining the acquired at least one control parameter as a final System parameters.
根据本申请实施例的另一方面，提供一种用于优化风力发电机组的载荷的装置，所述装置包括：控制参数获取模块，获取风力发电机组的至少一个控制参数，其中，所述风力发电机组的多个位置的载荷受到所述至少一个控 制参数的影响；载荷获取模块，获取与所述至少一个控制参数对应的所述风力发电机组的所述多个位置的载荷值；载荷量化模块，使用预定评价模型将所述多个位置的载荷值量化为单个评价值；评价值判断模块，判断评价值是否满足预定条件；控制参数更新模块，当评价值不满足预定条件时，使用预定优化算法，基于评价值对所述至少一个控制参数进行优化来更新所述至少一个控制参数，并且控制参数获取模块再次获取所述至少一个控制参数，其中，对控制参数进行优化的优化问题为使得更新后的控制参数所对应的评价值满足预定条件；控制参数提供模块，当评价值满足预定条件时，将获取的所述至少一个控制参数提供作为最终的控制参数。According to another aspect of an embodiment of the present application, there is provided an apparatus for optimizing a load of a wind power generator, the apparatus comprising: a control parameter acquisition module that acquires at least one control parameter of a wind power generator, wherein the wind power generation The load of the plurality of positions of the unit is affected by the at least one control parameter; the load acquisition module acquires a load value of the plurality of positions of the wind power generator corresponding to the at least one control parameter; a load quantization module, The load value of the plurality of locations is quantized into a single evaluation value using a predetermined evaluation model; the evaluation value judging module judges whether the evaluation value satisfies a predetermined condition; and the control parameter update module uses a predetermined optimization algorithm when the evaluation value does not satisfy the predetermined condition Updating the at least one control parameter based on the evaluation value to update the at least one control parameter, and the control parameter obtaining module acquires the at least one control parameter again, wherein the optimization problem of optimizing the control parameter is such that after updating The evaluation value corresponding to the control parameter satisfies the predetermined a condition; a control parameter providing module that provides the acquired at least one control parameter as a final control parameter when the evaluation value satisfies a predetermined condition.
根据本申请实施例的另一方面，提供一种存储有计算机程序的计算机可读存储介质，当所述计算机程序在被处理器执行时实现上述的用于优化风力发电机组的载荷的方法。According to another aspect of an embodiment of the present application, there is provided a computer readable storage medium storing a computer program that, when executed by a processor, implements the method for optimizing a load of a wind turbine.
根据本申请实施例的另一方面，提供一种风力发电机组的控制***，所述控制***包括：处理器；存储器，存储有计算机程序，当所述计算机程序被处理器执行时，实现上述的用于优化风力发电机组的载荷的方法。According to another aspect of an embodiment of the present application, there is provided a control system for a wind power generator set, the control system comprising: a processor; a memory storing a computer program, when the computer program is executed by the processor, implementing the above A method for optimizing the load of a wind turbine.
采用本申请实施例的用于优化风力发电机组的载荷的方法和装置，能够针对风力发电机组的多个载荷进行量化，并使用优化算法基于量化值对风力发电机组的控制器模型的参数进行优化，以有助于获得优化的载荷结果。The method and apparatus for optimizing the load of a wind power generator according to an embodiment of the present application can quantify multiple loads of the wind power generator and optimize the parameters of the wind turbine generator controller model based on the quantized values using an optimization algorithm. To help get optimized load results.
附图说明DRAWINGS
为了更清楚地说明本申请实施例的技术方案，下面将对本申请实施例中所需要使用的附图作简单地介绍。In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings to be used in the embodiments of the present application will be briefly described below.
图1示出本申请一实施例的用于优化风力发电机组的载荷的方法的流程图；1 shows a flow chart of a method for optimizing a load of a wind power plant according to an embodiment of the present application;
图2示出本申请一实施例的用于优化风力发电机组的载荷的装置的结构框图。2 is a block diagram showing the structure of an apparatus for optimizing the load of a wind power generator according to an embodiment of the present application.
具体实施方式Detailed ways
图1示出本申请一实施例的用于优化风力发电机组的载荷的方法的流程图。1 shows a flow chart of a method for optimizing the load of a wind turbine according to an embodiment of the present application.
参考图1，在步骤S10中，可获取风力发电机组的至少一个控制参数， 风力发电机组的多个位置的载荷受到该至少一个控制参数的影响。根据一个实施例，可获取影响风力发电机组的多个位置的载荷的，并且与风力发电机组的控制策略有关的控制参数作为至少一个控制参数。作为示例，可获取风力发电机组的预定控制器模型的控制参数作为至少一个控制参数。应注意，当获取预定控制器模型的控制参数作为至少一个控制参数时，获取的至少一个控制参数可以是同一个控制器模型的控制参数，也可以是不同的多个控制器模型的控制参数，本申请对此不做限制。作为示例，针对特定载荷的优化，预定控制器模型可以是变桨控制器模型、转矩控制器模型或者滤波器模型。优化时可考虑风力发电机组的各个位置处的疲劳载荷和极限载荷之中的多个载荷。例如，多个位置的载荷可包括塔底的第一方向的弯矩Mx的疲劳载荷、塔底的第二方向的弯矩My的疲劳载荷、叶根的第二方向的弯矩My的疲劳载荷、塔底的第二方向的弯矩My的极限载荷以及叶根的第二方向的弯矩My的极限载荷。应理解，多个位置的载荷可以是以上载荷之中的两个或更多个，也可以包括其他类型的载荷。Referring to FIG. 1, in step S10, at least one control parameter of the wind turbine may be acquired, and loads of the plurality of locations of the wind turbine are affected by the at least one control parameter. According to one embodiment, control parameters affecting the loads of the plurality of locations of the wind turbine and related to the control strategy of the wind turbine may be obtained as at least one control parameter. As an example, a control parameter of a predetermined controller model of the wind turbine may be obtained as at least one control parameter. It should be noted that when the control parameter of the predetermined controller model is acquired as the at least one control parameter, the acquired at least one control parameter may be a control parameter of the same controller model, or may be a control parameter of different multiple controller models. This application does not limit this. As an example, for a particular load optimization, the predetermined controller model may be a pitch controller model, a torque controller model, or a filter model. The optimization may take into account multiple loads among the fatigue load and the ultimate load at various locations of the wind turbine. For example, the load at a plurality of positions may include a fatigue load of a bending moment Mx in a first direction of the bottom of the tower, a fatigue load of a bending moment My in the second direction of the bottom of the tower, and a fatigue load of a bending moment My in the second direction of the blade root. The ultimate load of the bending moment My in the second direction of the tower bottom and the ultimate load of the bending moment My in the second direction of the blade root. It should be understood that the loads at multiple locations may be two or more of the above loads, as well as other types of loads.
在本申请的一些实施例中，针对上述载荷，预定控制器模型可以是变桨控制器模型。例如，变桨控制器模型的控制参数可以是KPPS和KIPS。但这仅为示例，本申请不限于此。In some embodiments of the present application, the predetermined controller model may be a pitch controller model for the above loads. For example, the control parameters of the pitch controller model can be KPPS and KIPS. However, this is merely an example, and the application is not limited thereto.
在步骤S10中，优选地，获取控制参数可以指获取控制参数的当前值。作为示例，可获取控制参数的取值范围内的任意值作为当前值。作为示例，可根据经验预先设置控制参数的取值范围。In step S10, preferably, acquiring the control parameter may refer to acquiring the current value of the control parameter. As an example, any value within the range of values of the control parameter can be obtained as the current value. As an example, the range of values of the control parameters can be set in advance according to experience.
在本申请的一些实施例中，图1所示的方法还可包括初始化至少一个控制参数的步骤。作为示例，可初始化预定控制器模型的控制参数，可获取控制参数的初始化值作为当前值。In some embodiments of the present application, the method illustrated in FIG. 1 may also include the step of initializing at least one control parameter. As an example, a control parameter of a predetermined controller model may be initialized, and an initialization value of the control parameter may be acquired as a current value.
在步骤S20中，可获取与至少一个控制参数对应的所述风力发电机组的多个位置的载荷值。In step S20, load values of a plurality of locations of the wind turbine set corresponding to at least one control parameter may be acquired.
如上所述，本申请一实施例的多个位置的载荷可以是塔底Mx的疲劳载荷、塔底My的疲劳载荷、叶根My的疲劳载荷、塔底My的极限载荷以及叶根My的极限载荷。作为示例，可基于获取的控制参数的当前值，对风机的整机模型进行仿真，从而得到与控制参数对应的上述多个载荷值。As described above, the load at a plurality of positions in one embodiment of the present application may be the fatigue load of the bottom Mx, the fatigue load of the bottom My, the fatigue load of the blade root My, the ultimate load of the bottom My, and the limit of the blade root My. Load. As an example, the overall model of the wind turbine may be simulated based on the current value of the acquired control parameters to obtain the plurality of load values corresponding to the control parameters.
在本申请一些实施例中，基于获取的至少一个控制参数，对风力发电机组的整机模型进行仿真，还可得到风力发电机组的预定运行参数的值。这将 在以下进行更详细的描述。In some embodiments of the present application, the whole machine model of the wind power generator is simulated based on the acquired at least one control parameter, and the value of the predetermined operating parameter of the wind power generator set is also obtained. This will be described in more detail below.
在步骤S30中，使用预定评价模型将上述多个载荷值量化为单个评价值。In step S30, the plurality of load values are quantized into a single evaluation value using a predetermined evaluation model.
基于优化载荷的目的，可使用预定评价模型将多个载荷值量化为与其中最小载荷关联的一个评价值，以便基于此进行后续优化。例如，预定评价模型可以是能够实现一实施例的评价功能的各种函数，量化的评价值为函数的值。例如，预定评价模型可以是适应度函数。作为示例，预定评价模型可以是上述多个载荷的和(例如，累加值)与约束值的乘积。作为另一示例，预定评价模型可以是上述多个载荷分别被加权后的加权和(例如，累加加权值)与约束值的乘积。例如，可根据对多个载荷的不同关注程度向评价模型中的多个载荷施加各自的权重，还可考虑多个载荷之间的不同数量级向多个载荷施加各自的权重，但本申请不限于此。Based on the purpose of optimizing the load, a plurality of load values may be quantized to an evaluation value associated with the minimum load using a predetermined evaluation model to perform subsequent optimization based thereon. For example, the predetermined evaluation model may be various functions capable of implementing the evaluation function of an embodiment, and the quantized evaluation value is a value of the function. For example, the predetermined evaluation model may be a fitness function. As an example, the predetermined evaluation model may be the product of the sum of the plurality of loads (eg, the accumulated value) and the constraint value. As another example, the predetermined evaluation model may be a product of a weighted sum (eg, an accumulated weighting value) of the plurality of loads respectively weighted and a constraint value. For example, respective weights may be applied to a plurality of loads in the evaluation model according to different degrees of attention to the plurality of loads, and different weights may be applied to the plurality of loads in consideration of different magnitudes between the plurality of loads, but the application is not limited thereto. this.
如上所述的约束值可反映风力发电机组正常运行所需要满足的针对预定运行参数的约束条件。优选地，可根据风力发电机组正常运行所需要满足的针对预定运行参数的约束条件来确定约束值。The constraint values as described above may reflect constraints for predetermined operational parameters that need to be met for normal operation of the wind turbine. Preferably, the constraint value can be determined based on constraints required for the predetermined operational parameters to be met by the normal operation of the wind turbine.
作为示例，预定运行参数可包括发电机转速和机舱振动加速度中的至少一个，但本申请不限于此。例如，如上所述的约束条件可包括发电机转速在发电机转速的预定范围内以及机舱振动加速度在机舱振动加速度的预定范围内。As an example, the predetermined operational parameter may include at least one of a generator rotational speed and a cabin vibration acceleration, but the application is not limited thereto. For example, the constraints described above may include the generator speed being within a predetermined range of generator speeds and the cabin vibration acceleration being within a predetermined range of cabin vibration acceleration.
如上所述，预定运行参数的值可通过在步骤S20中基于获取的至少一个控制参数的当前值通过仿真得到。因此，可通过判断经仿真得到的预定运行参数的值是否满足上述的约束条件来确定约束值。As described above, the value of the predetermined operational parameter can be obtained by simulation based on the current value of the acquired at least one control parameter in step S20. Therefore, the constraint value can be determined by judging whether the value of the predetermined operational parameter obtained by the simulation satisfies the above constraint condition.
在本申请一些实施例中，根据风力发电机组正常运行所需要满足的针对预定运行参数的约束条件确定约束值的步骤可包括：当预定运行参数满足约束条件时，将约束值设置为预定值；当预定运行参数不满足约束条件时，将约束值设置为大于预定值的值。例如，预定值可被预先设置。这里，当预定运行参数不满足约束条件(即，预定运行参数存在异常)时，可根据预定运行参数的异常所能被接受的程度(或该异常的量级)，确定约束值大于预定值的程度。In some embodiments of the present application, the determining the constraint value according to the constraint condition for the predetermined operational parameter that is required to be met by the normal operation of the wind power generator may include: setting the constraint value to a predetermined value when the predetermined operational parameter satisfies the constraint condition; When the predetermined operational parameter does not satisfy the constraint, the constraint value is set to a value greater than the predetermined value. For example, the predetermined value can be set in advance. Here, when the predetermined operating parameter does not satisfy the constraint condition (ie, the predetermined operating parameter has an abnormality), the constraint value may be determined to be greater than the predetermined value according to the degree to which the abnormality of the predetermined operating parameter can be accepted (or the magnitude of the abnormality). degree.
例如，当根据控制参数的当前值通过仿真得到的发电机转速超过发电机转速的预定范围时，可将约束值设置为大于预定值的值，从而增大作为量化的评价值的载荷值的和与约束值的乘积。但这仅为示例，本申请的预定控制 参数不满足约束条件的情况以及约束值的设置不限于此。For example, when the generator rotational speed obtained by simulation according to the current value of the control parameter exceeds a predetermined range of the generator rotational speed, the constraint value may be set to a value greater than a predetermined value, thereby increasing the sum of the load values as the quantized evaluation values. The product of the constraint value. However, this is merely an example, and the case where the predetermined control parameter of the present application does not satisfy the constraint and the setting of the constraint value are not limited thereto.
在步骤S40中，判断评价值是否满足预定条件。In step S40, it is judged whether or not the evaluation value satisfies the predetermined condition.
当评价值不满足预定条件时，在步骤S50中，使用预定优化算法，基于评价值对控制参数进行优化来更新控制参数，并返回步骤S10再次获取控制参数。这里，对控制参数进行优化的优化问题为使得更新后的控制参数所对应的评价值(即，针对更新后的控制参数通过步骤S20和S30得到的评价值)满足预定条件。When the evaluation value does not satisfy the predetermined condition, in step S50, the control parameter is updated based on the evaluation value to update the control parameter using the predetermined optimization algorithm, and returns to step S10 to acquire the control parameter again. Here, the optimization problem of optimizing the control parameters is such that the evaluation value corresponding to the updated control parameter (that is, the evaluation value obtained by the steps S20 and S30 for the updated control parameter) satisfies the predetermined condition.
在本申请一些实施例中，预定条件可指评价值达到最小值。例如，预定条件可指获取的至少一个控制参数所对应的评价值达到最小值。优选地，当获取的至少一个控制参数与前一次(即，在当前方法的上一次迭代中执行步骤S10时)获取的该至少一个控制参数之间的差小于预定阈值时，可确定评价值达到最小值。In some embodiments of the present application, the predetermined condition may mean that the evaluation value reaches a minimum value. For example, the predetermined condition may mean that the evaluation value corresponding to the acquired at least one control parameter reaches a minimum value. Preferably, when the obtained at least one control parameter is less than a predetermined threshold from the previous one (ie, when the step S10 is performed in the last iteration of the current method), the evaluation value may be determined to be reached. Minimum value.
可使用现有的各种优化算法基于量化的评价值对控制参数进行优化，以更新控制参数。例如，所使用的优化算法可以是遗传算法或单纯形法，但本申请不限于此。The control parameters can be optimized based on the quantized evaluation values to update the control parameters using various existing optimization algorithms. For example, the optimization algorithm used may be a genetic algorithm or a simplex method, but the application is not limited thereto.
例如，当量化的评价值不满足预定条件(即，量化的评价值未达到最小值)时，可在步骤S50中，在预定优化算法中，将获取的至少一个控制参数所对应的评价值与所有之前的评价值中的最小值进行比较，并基于比较的结果，根据评价值与控制参数的对应关系，确定控制参数接下来将被调节的优化方向和幅度，从而更新控制参数。然后，返回步骤S10，再次获取该至少一个控制参数。For example, when the quantized evaluation value does not satisfy the predetermined condition (that is, the quantized evaluation value does not reach the minimum value), in step S50, in the predetermined optimization algorithm, the evaluation value corresponding to the acquired at least one control parameter may be The minimum values of all the previous evaluation values are compared, and based on the comparison result, according to the correspondence relationship between the evaluation values and the control parameters, the optimization direction and the amplitude at which the control parameters are to be adjusted next are determined, thereby updating the control parameters. Then, returning to step S10, the at least one control parameter is acquired again.
应注意，可针对该至少一个控制参数的数量设置预定阈值的数量。例如，前后两次获取的第一控制参数(例如，KPPS)之间的差可称为第一差，前后两次获取的第二控制参数(例如，KIPS)之间的差可称为第二差。作为示例，可针对第一差和第二差分别设置第一预定阈值和第二预定阈值。作为另一示例，可针对第一差和第二差设置相同的预定阈值。应该理解，控制参数和预定阈值的数量不限于此。It should be noted that the number of predetermined thresholds may be set for the number of the at least one control parameter. For example, the difference between the first control parameters (eg, KPPS) acquired twice before and after may be referred to as a first difference, and the difference between the second control parameters (eg, KIPS) acquired twice before and after may be referred to as a second difference. As an example, a first predetermined threshold and a second predetermined threshold may be set for the first difference and the second difference, respectively. As another example, the same predetermined threshold may be set for the first difference and the second difference. It should be understood that the number of control parameters and predetermined thresholds is not limited thereto.
在步骤S60中，当评价值满足预定条件时，将获取的至少一个控制参数作为最终的控制参数。In step S60, when the evaluation value satisfies the predetermined condition, the acquired at least one control parameter is taken as the final control parameter.
例如，当在步骤S40中判断评价值达到最小值(即，前后两次获取的控制参数之间的差小于预定阈值)时，说明本次获取的至少一个控制参数可认 为是作为优化结果的最终的控制参数，可将其用于后续风力发电机组的设计、仿真和实际运行中，以便捷有效地优化相应的载荷。For example, when it is determined in step S40 that the evaluation value reaches the minimum value (that is, the difference between the control parameters acquired twice before and after is less than a predetermined threshold), it indicates that the at least one control parameter acquired this time may be considered as the final result of the optimization result. The control parameters can be used in the design, simulation and actual operation of subsequent wind turbines to conveniently and efficiently optimize the corresponding loads.
表1示出对比执行如图1所述的方法前后的上述多个位置的载荷以及控制参数的值的示例。Table 1 shows an example of comparing the loads of the above-described plurality of positions before and after the method as described in FIG. 1 and the values of the control parameters.
表1Table 1
Figure PCTCN2018082347-appb-000001
Figure PCTCN2018082347-appb-000001
通过表1可见，针对上述多个位置的载荷，采用优化算法对变桨控制器模型的控制参数进行更新，使得塔底Mx的疲劳载荷、塔底My的疲劳载荷、叶根My的疲劳载荷、塔底My的极限载荷均有不同程度的降低，虽然叶根My的极限载荷比优化前略微上升，但是从***角度来说，风力发电机组的载荷总体上得到了较好的优化效果。It can be seen from Table 1 that, for the loads of the above multiple positions, the optimization algorithm is used to update the control parameters of the pitch controller model, so that the fatigue load of the bottom Mx, the fatigue load of the bottom of the tower My, the fatigue load of the blade root My, The ultimate load of the bottom of My Tower has been reduced to some extent. Although the ultimate load of the blade root My is slightly higher than that before the optimization, the load of the wind turbine is generally optimized from the system point of view.
图2示出本申请一实施例的用于优化风力发电机组的载荷的装置的结构框图。2 is a block diagram showing the structure of an apparatus for optimizing the load of a wind power generator according to an embodiment of the present application.
如图2所示，本申请一实施例的用于优化风力发电机组的载荷的装置包括：控制参数获取模块10、载荷获取模块20、载荷量化模块30、评价值判断模块40、控制参数更新模块50和控制参数提供模块60。As shown in FIG. 2, the apparatus for optimizing the load of a wind power generator according to an embodiment of the present application includes: a control parameter acquisition module 10, a load acquisition module 20, a load quantization module 30, an evaluation value judgment module 40, and a control parameter update module. 50 and control parameter providing module 60.
其中，控制参数获取模块10获取风力发电机组的至少一个控制参数，风力发电机组的多个位置的载荷受到该至少一个控制参数的影响。在本申请一些实施例中，可获取与风力发电机组的控制策略有关(即，用于设置控制策略)的控制参数作为至少一个控制参数。作为示例，可获取风力发电机组的预定控制器模型的控制参数作为至少一个控制参数。这里，该预定控制器模型的控制参数是风力发电机组的与风力发电机组的多个载荷相关联的控制参 数，该多个载荷受到该控制参数的影响。应注意，当控制参数获取模块10获取预定控制器模型的控制参数作为至少一个控制参数时，获取的至少一个控制参数可以是同一个控制器模型的控制参数，也可以是不同的多个控制器模型的控制参数，本申请对此不做限制。The control parameter obtaining module 10 acquires at least one control parameter of the wind power generator set, and the loads of the plurality of positions of the wind power generator set are affected by the at least one control parameter. In some embodiments of the present application, control parameters related to the control strategy of the wind turbine (ie, for setting the control strategy) may be obtained as at least one control parameter. As an example, a control parameter of a predetermined controller model of the wind turbine may be obtained as at least one control parameter. Here, the control parameter of the predetermined controller model is a control parameter of the wind turbine associated with a plurality of loads of the wind turbine, the plurality of loads being affected by the control parameter. It should be noted that when the control parameter obtaining module 10 acquires the control parameter of the predetermined controller model as the at least one control parameter, the acquired at least one control parameter may be the control parameter of the same controller model, or may be different controllers. The control parameters of the model are not limited in this application.
作为示例，针对特定载荷的优化，预定控制器模型可以是变桨控制器模型、转矩控制器模型或者滤波器模型。As an example, for a particular load optimization, the predetermined controller model may be a pitch controller model, a torque controller model, or a filter model.
在本申请一些实施例中，控制参数获取模块10可获取控制参数的当前值。作为示例，控制参数获取模块10可获取控制参数的取值范围内的任意值作为当前值。In some embodiments of the present application, the control parameter acquisition module 10 may obtain the current value of the control parameter. As an example, the control parameter acquisition module 10 may obtain any value within the range of values of the control parameter as the current value.
在本申请一些实施例中，装置还可包括初始化模块(未示出)，初始化模块用于初始化至少一个控制参数。例如，初始化模块可初始化预定控制器模型的控制参数。作为示例，控制参数获取模块可获取控制参数的初始化值作为当前值。In some embodiments of the present application, the apparatus may further include an initialization module (not shown) for initializing the at least one control parameter. For example, the initialization module can initialize control parameters of a predetermined controller model. As an example, the control parameter acquisition module may obtain an initialization value of the control parameter as the current value.
在本申请一些实施例中，载荷获取模块20可获取与至少一个控制参数对应的风力发电机组的多个位置的载荷值。作为示例，载荷获取模块20可基于获取的至少一个控制参数的当前值，对风机的整机模型进行仿真，从而得到与该至少一个控制参数对应的该多个位置的载荷值。In some embodiments of the present application, the load acquisition module 20 may acquire load values for a plurality of locations of the wind turbine set corresponding to the at least one control parameter. As an example, the load acquisition module 20 may simulate a complete machine model of the wind turbine based on the current value of the acquired at least one control parameter, thereby obtaining load values for the plurality of locations corresponding to the at least one control parameter.
在本申请一些实施例中，载荷获取模块20还可基于获取的至少一个控制参数，对风力发电机组的整机模型进行仿真，得到风力发电机组的预定运行参数的值。In some embodiments of the present application, the load acquisition module 20 may also simulate the overall model of the wind turbine based on the acquired at least one control parameter to obtain a value of a predetermined operational parameter of the wind turbine.
在本申请一些实施例中，载荷量化模块30使用预定评价模型将该多个载荷值量化为单个评价值。In some embodiments of the present application, the load quantification module 30 quantizes the plurality of load values into a single evaluation value using a predetermined evaluation model.
基于优化载荷的目的，载荷量化模块30可使用预定评价模型将多个载荷值量化为与其中最小载荷关联的一个评价值，以便基于此进行后续优化。例如，预定评价模型可以是能够实现本申请一些实施例中的评价功能的各种函数，量化的评价值为函数的值。例如，预定评价模型可以是适应度函数。作为示例，预定评价模型可以是该多个载荷的和(例如，累加值)与约束值的乘积。作为另一示例，预定评价模型可以是该多个载荷分别被加权后的加权和(例如，累加加权值)与约束值的乘积。例如，载荷量化模块30可根据对多个载荷的不同关注程度向评价模型中的多个载荷施加各自的权重，还可考虑多个载荷之间的不同数量级向多个载荷施加各自的权重，但本申请不限于 此。Based on the purpose of optimizing the load, the load quantification module 30 may quantize the plurality of load values into one of the evaluation values associated with the minimum load using a predetermined evaluation model to perform subsequent optimizations based thereon. For example, the predetermined evaluation model may be various functions capable of implementing the evaluation function in some embodiments of the present application, and the quantized evaluation value is a value of the function. For example, the predetermined evaluation model may be a fitness function. As an example, the predetermined evaluation model may be the product of the sum of the plurality of loads (eg, the accumulated value) and the constraint value. As another example, the predetermined evaluation model may be a product of a weighted sum (eg, an accumulated weighting value) of the plurality of loads respectively weighted to the constraint value. For example, the load quantification module 30 may apply respective weights to a plurality of loads in the evaluation model according to different degrees of attention to the plurality of loads, and may also apply respective weights to the plurality of loads in consideration of different magnitudes between the plurality of loads, but This application is not limited to this.
如上所述的约束值可反映风力发电机组正常运行所需要满足的针对预定运行参数的约束条件。优选地，载荷量化模块30可根据风力发电机组正常运行所需要满足的针对预定运行参数的约束条件来确定约束值。The constraint values as described above may reflect constraints for predetermined operational parameters that need to be met for normal operation of the wind turbine. Preferably, the load quantification module 30 may determine the constraint value based on constraints for the predetermined operational parameters that need to be met for normal operation of the wind turbine.
作为示例，预定运行参数可包括发电机转速和机舱振动加速度中的至少一个，但本申请不限于此。例如，如上所述的约束条件可包括发电机转速在发电机转速的预定范围内以及机舱振动加速度在机舱振动加速度的预定范围内。As an example, the predetermined operational parameter may include at least one of a generator rotational speed and a cabin vibration acceleration, but the application is not limited thereto. For example, the constraints described above may include the generator speed being within a predetermined range of generator speeds and the cabin vibration acceleration being within a predetermined range of cabin vibration acceleration.
如上所述，风力发电机组的预定运行参数的值可由载荷获取模块20基于获取的至少一个控制参数，对风力发电机组的整机模型进行仿真得到。因此，可由载荷量化模块30通过判断经仿真得到的预定运行参数的值是否满足上述的约束条件来确定约束值。As described above, the value of the predetermined operational parameter of the wind turbine can be simulated by the load acquisition module 20 based on the acquired at least one control parameter. Therefore, the constraint value can be determined by the load quantization module 30 by determining whether the value of the simulated predetermined operational parameter satisfies the above constraint.
在本申请一些实施例中，载荷量化模块30确定约束值的步骤可包括：当预定运行参数满足约束条件时，载荷量化模块30将约束值设置为预定值；当预定运行参数不满足约束条件时，载荷量化模块30将约束值设置为大于预定值的值。例如，预定值可由载荷量化模块30预先设置。这里，当预定运行参数不满足约束条件(即，预定运行参数存在异常)时，载荷量化模块30可根据预定运行参数的异常所能被接受的程度(或该异常的量级)，确定约束值大于预定值的程度。In some embodiments of the present application, the step of determining the constraint value by the load quantification module 30 may include: when the predetermined operational parameter satisfies the constraint condition, the load quantization module 30 sets the constraint value to a predetermined value; when the predetermined operational parameter does not satisfy the constraint condition The load quantization module 30 sets the constraint value to a value greater than a predetermined value. For example, the predetermined value may be preset by the load quantization module 30. Here, when the predetermined operational parameter does not satisfy the constraint condition (ie, there is an abnormality in the predetermined operational parameter), the load quantization module 30 may determine the constraint value according to the degree to which the abnormality of the predetermined operational parameter can be accepted (or the magnitude of the abnormality). A degree greater than a predetermined value.
例如，当载荷量化模块30判断根据控制参数的当前值通过仿真得到的发电机转速超过发电机转速的预定范围时，载荷量化模块30可将约束值设置为大于预定值的值，从而增大作为量化的评价值的载荷值的和与约束值的乘积。但这仅为示例，本申请不限于此。For example, when the load quantification module 30 determines that the generator rotational speed obtained by simulation according to the current value of the control parameter exceeds a predetermined range of the generator rotational speed, the load quantization module 30 may set the constraint value to a value greater than a predetermined value, thereby increasing the The product of the weighted value of the quantized evaluation value and the product of the constraint value. However, this is merely an example, and the application is not limited thereto.
在本申请一些实施例中，评价值判断模块40判断评价值是否满足预定条件。In some embodiments of the present application, the evaluation value determination module 40 determines whether the evaluation value satisfies a predetermined condition.
在本申请一些实施例中，当评价值不满足预定条件时，控制参数更新模块50使用预定优化算法，基于评价值对控制参数进行优化来更新控制参数，并且控制参数获取模块10再次获取控制参数。这里，对控制参数进行优化的优化问题为使得更新后的控制参数所对应的评价值满足预定条件。In some embodiments of the present application, when the evaluation value does not satisfy the predetermined condition, the control parameter update module 50 updates the control parameter based on the evaluation value to update the control parameter using a predetermined optimization algorithm, and the control parameter acquisition module 10 acquires the control parameter again. . Here, the optimization problem of optimizing the control parameters is such that the evaluation value corresponding to the updated control parameter satisfies a predetermined condition.
在本申请一些实施例中，预定条件可指评价值达到最小值。例如，预定条件可指由控制参数获取模块10获取的至少一个控制参数所对应的由载荷 量化模块30量化的评价值达到最小值。优选地，当控制参数获取模块10获取的至少一个控制参数与前一次获取的该至少一个控制参数之间的差小于预定阈值时，评价值判断模块40可确定评价值达到最小值。In some embodiments of the present application, the predetermined condition may mean that the evaluation value reaches a minimum value. For example, the predetermined condition may mean that the evaluation value quantized by the load quantization module 30 corresponding to the at least one control parameter acquired by the control parameter acquisition module 10 reaches a minimum value. Preferably, when the difference between the at least one control parameter acquired by the control parameter obtaining module 10 and the at least one control parameter acquired previously is less than a predetermined threshold, the evaluation value determining module 40 may determine that the evaluation value reaches a minimum value.
控制参数更新模块50可使用现有的各种优化算法基于量化的评价值对控制参数进行优化，以更新控制参数。例如，控制参数更新模块50所使用的优化算法可以是遗传算法或单纯形法，但本申请不限于此。The control parameter update module 50 may optimize the control parameters based on the quantized evaluation values using existing various optimization algorithms to update the control parameters. For example, the optimization algorithm used by the control parameter update module 50 may be a genetic algorithm or a simplex method, but the application is not limited thereto.
例如，当载荷量化模块30量化的评价值不满足预定条件(即，量化的评价值未达到最小值)时，控制参数更新模块50可在预定优化算法中将由控制参数获取模块10获取的至少一个控制参数所对应的由载荷量化模块30量化的评价值与所有之前的评价值中的最小值进行比较，并基于比较的结果，根据评价值与控制参数的对应关系，确定控制参数接下来将被调节的优化方向和幅度，从而更新控制参数。然后，再一次地，控制参数获取模块10获取该至少一个控制参数，载荷获取模块20获取与该至少一个控制参数对应的多个位置的载荷值，载荷量化模块30使用预定评价模型将该多个位置的载荷值量化为单个评价值，评价值判断模块40判断评价值是否满足预定条件，当评价值不满足预定条件时，控制参数更新模块50使用预定优化算法基于评价值对该至少一个控制参数进行优化。For example, when the evaluation value quantized by the load quantization module 30 does not satisfy the predetermined condition (ie, the quantized evaluation value does not reach the minimum value), the control parameter update module 50 may select at least one acquired by the control parameter acquisition module 10 in the predetermined optimization algorithm. The evaluation value quantized by the load quantization module 30 corresponding to the control parameter is compared with the minimum value of all the previous evaluation values, and based on the comparison result, according to the correspondence relationship between the evaluation value and the control parameter, it is determined that the control parameter is next The direction and magnitude of the adjustment are optimized to update the control parameters. Then, again, the control parameter acquisition module 10 acquires the at least one control parameter, the load acquisition module 20 acquires the load values of the plurality of locations corresponding to the at least one control parameter, and the load quantization module 30 uses the predetermined evaluation model to the plurality of locations. The load value of the position is quantized into a single evaluation value, and the evaluation value judging module 40 judges whether the evaluation value satisfies a predetermined condition. When the evaluation value does not satisfy the predetermined condition, the control parameter update module 50 uses the predetermined optimization algorithm to calculate the at least one control parameter based on the evaluation value. optimize.
应注意，评价值判断模块40可针对该至少一个控制参数的数量设置预定阈值的数量。例如，前后两次获取的第一控制参数之间的差可称为第一差，前后两次获取的第二控制参数之间的差可称为第二差。作为示例，可针对第一差和第二差分别设置第一预定阈值和第二预定阈值。作为另一示例，可针对第一差和第二差设置相同的预定阈值。应该理解，控制参数和预定阈值的数量不限于此。It should be noted that the evaluation value judging module 40 may set the number of predetermined thresholds for the number of the at least one control parameter. For example, the difference between the first control parameters acquired twice before and after may be referred to as the first difference, and the difference between the second control parameters acquired twice before and after may be referred to as the second difference. As an example, a first predetermined threshold and a second predetermined threshold may be set for the first difference and the second difference, respectively. As another example, the same predetermined threshold may be set for the first difference and the second difference. It should be understood that the number of control parameters and predetermined thresholds is not limited thereto.
在本申请一些实施例中，当评价值判断模块40判断评价值满足预定条件时，控制参数提供模块60将由控制参数获取模块10获取的至少一个控制参数提供作为最终的控制参数。In some embodiments of the present application, when the evaluation value judging module 40 judges that the evaluation value satisfies the predetermined condition, the control parameter providing module 60 provides at least one control parameter acquired by the control parameter obtaining module 10 as the final control parameter.
例如，当评价值判断模块40判断评价值达到最小值(即，控制参数获取模块10前后两次获取的控制参数之间的差小于预定阈值)时，说明本次获取的至少一个控制参数可认为是作为优化结果的最终的控制参数。此时，控制参数提供模块60可将该控制参数提供用于后续风力发电机组的设计、仿真和实际运行中，以便捷有效地优化相应的载荷。For example, when the evaluation value judging module 40 judges that the evaluation value reaches the minimum value (that is, the difference between the control parameters acquired twice before and after the control parameter acquisition module 10 is less than a predetermined threshold), it indicates that the at least one control parameter acquired this time can be considered as It is the final control parameter as an optimization result. At this time, the control parameter providing module 60 can provide the control parameters for design, simulation, and actual operation of the subsequent wind turbine to conveniently and efficiently optimize the corresponding load.
本申请的实施例还提供一种控制***。该控制***包括处理器和存储器。存储器用于存储计算机程序。所述计算机程序被处理器执行使得处理器执行如上所述的用于优化风力发电机组的载荷的方法的计算机程序。Embodiments of the present application also provide a control system. The control system includes a processor and a memory. The memory is used to store computer programs. The computer program is executed by a processor such that the processor executes a computer program for the method of optimizing the load of the wind turbine as described above.
本申请的实施例还提供一种存储有计算机程序的计算机可读存储介质。该计算机可读存储介质存储有当被处理器执行时使得处理器执行上述用于优化风力发电机组的载荷的方法的计算机程序。该计算机可读记录介质是可存储由计算机***读出的数据的任意数据存储装置。计算机可读记录介质的示例包括：只读存储器、随机存取存储器、只读光盘、磁带、软盘、光数据存储装置和载波(诸如经有线或无线传输路径通过互联网的数据传输)。Embodiments of the present application also provide a computer readable storage medium storing a computer program. The computer readable storage medium stores a computer program that, when executed by a processor, causes the processor to perform the method described above for optimizing the load of the wind turbine. The computer readable recording medium is any data storage device that can store data read by a computer system. Examples of the computer readable recording medium include read only memory, random access memory, read-only optical disk, magnetic tape, floppy disk, optical data storage device, and carrier wave (such as data transmission via the Internet via a wired or wireless transmission path).
采用本申请实施例的上述用于优化风力发电机组的载荷的方法和装置，能够使用优化算法基于风力发电机组的控制器模型进行控制参数的自动更新，而不是基于风力发电机组的整机模型的线性化数据进行时域和频域的分析和手动调节控制参数，从而大大节省风力发电机组的设计过程中的人力和资源成本。The above method and apparatus for optimizing the load of a wind power generator using the embodiment of the present application can automatically update the control parameters based on the controller model of the wind turbine using an optimization algorithm, instead of based on the overall model of the wind turbine The linearized data analyzes the time domain and frequency domain and manually adjusts the control parameters, thereby greatly saving labor and resource costs in the design process of the wind turbine.
采用本申请实施例的上述用于优化风力发电机组的载荷的方法和装置，可灵活地选用多种优化算法，并且所述方法和装置可不仅针对载荷，还可推广到发电量、功率曲线等各种指标的优化和相关控制参数的更新。The above method and apparatus for optimizing the load of the wind power generator according to the embodiment of the present application can flexibly select a plurality of optimization algorithms, and the method and the device can be extended not only to the load but also to the power generation amount, the power curve, and the like. Optimization of various indicators and update of related control parameters.
尽管已经参照本申请实施例具体显示和描述了本申请，但是本领域的技术人员应该理解，在不脱离权利要求所限定的本申请的精神和范围的情况下，可以对其进行形式和细节上的各种改变。While the present invention has been particularly shown and described with respect to the embodiments of the present invention, it will be understood by those skilled in the art Various changes.

Claims (22)

  1. 一种用于优化风力发电机组的载荷的方法，所述方法包括以下步骤：A method for optimizing a load of a wind turbine, the method comprising the steps of:
    获取风力发电机组的至少一个控制参数，其中，所述风力发电机组的多个位置的载荷受到所述至少一个控制参数的影响；Obtaining at least one control parameter of the wind turbine, wherein loads of the plurality of locations of the wind turbine are affected by the at least one control parameter;
    获取与所述至少一个控制参数对应的所述风力发电机组的所述多个位置的载荷值；Obtaining a load value of the plurality of locations of the wind turbine set corresponding to the at least one control parameter;
    使用预定评价模型将所述多个位置的载荷值量化为单个评价值；The load values of the plurality of locations are quantized into a single evaluation value using a predetermined evaluation model;
    判断评价值是否满足预定条件；Determining whether the evaluation value satisfies a predetermined condition;
    当评价值不满足预定条件时，使用预定优化算法，基于评价值对所述至少一个控制参数进行优化来更新所述至少一个控制参数，并再次执行获取所述风力发电机组的至少一个控制参数的步骤；When the evaluation value does not satisfy the predetermined condition, the predetermined optimization algorithm is used, the at least one control parameter is optimized based on the evaluation value to update the at least one control parameter, and the acquiring at least one control parameter of the wind power generator is performed again step;
    当评价值满足预定条件时，将获取的所述至少一个控制参数作为最终的控制参数。When the evaluation value satisfies a predetermined condition, the acquired at least one control parameter is taken as a final control parameter.
  2. 根据权利要求1所述的方法，其中，所述预定评价模型为适应度函数。The method of claim 1 wherein said predetermined evaluation model is a fitness function.
  3. 根据权利要求1所述的方法，其中，获取与所述至少一个控制参数对应的所述风力发电机组的多个位置的载荷值的步骤包括：基于获取的所述至少一个控制参数，对所述风力发电机组的整机模型进行仿真得到所述多个位置的载荷值和所述风力发电机组的预定运行参数的值。The method of claim 1 wherein obtaining a load value for a plurality of locations of said wind turbine set corresponding to said at least one control parameter comprises: said said at least one control parameter based on said acquired The overall model of the wind turbine is simulated to obtain the load values of the plurality of locations and the values of the predetermined operational parameters of the wind turbine.
  4. 根据权利要求3所述的方法，其中，所述预定评价模型为所述多个位置的载荷值的和与约束值的乘积或者所述多个位置的载荷值分别被加权后的加权和与约束值的乘积。The method according to claim 3, wherein said predetermined evaluation model is a weighted sum and constraint of a product of a sum of load values of said plurality of positions and a value of a constraint value or a load value of said plurality of positions, respectively The product of the values.
  5. 根据权利要求4所述的方法，其中，根据所述风力发电机组正常运行所需要满足的针对预定运行参数的约束条件确定约束值。The method of claim 4 wherein the constraint value is determined based on constraints required for predetermined operational parameters to be met by said wind turbine for normal operation.
  6. 根据权利要求5所述的方法，其中，确定约束值的步骤包括：The method of claim 5 wherein the step of determining the constraint value comprises:
    当预定运行参数满足所述约束条件时，将约束值设置为预定值；When the predetermined operating parameter satisfies the constraint condition, the constraint value is set to a predetermined value;
    当预定运行参数不满足所述约束条件时，将约束值设置为大于预定值的值。When the predetermined operational parameter does not satisfy the constraint, the constraint value is set to a value greater than the predetermined value.
  7. 根据权利要求1所述的方法，其中，预定条件是指评价值达到最小值。The method according to claim 1, wherein the predetermined condition means that the evaluation value reaches a minimum value.
  8. 根据权利要求7所述的方法，其中，当获取的所述至少一个控制参数与前一次获取的所述至少一个控制参数之间的差小于预定阈值时，确定评价 值达到最小值。The method of claim 7, wherein the evaluation value is determined to be at a minimum when a difference between the acquired at least one control parameter and the previously acquired at least one control parameter is less than a predetermined threshold.
  9. 根据权利要求6所述的方法，其中，预定运行参数包括发电机转速和机舱振动加速度中的至少一个。The method of claim 6 wherein the predetermined operational parameter comprises at least one of a generator speed and a cabin vibration acceleration.
  10. 根据权利要求1所述的方法，其中，所述多个位置的载荷包括塔底的第一方向的弯矩的疲劳载荷、塔底的第二方向的弯矩的疲劳载荷、叶根的第二方向的弯矩的疲劳载荷、塔底的第二方向的弯矩的极限载荷以及叶根的第二方向的弯矩的极限载荷中的两个或更多个。The method according to claim 1, wherein the load of the plurality of positions comprises a fatigue load of a bending moment of a first direction of the bottom of the tower, a fatigue load of a bending moment of a second direction of the tower bottom, and a second load of the blade root Two or more of the fatigue load of the direction bending moment, the ultimate load of the bending moment of the second direction of the tower bottom, and the ultimate load of the bending moment of the blade root in the second direction.
  11. 一种用于优化风力发电机组的载荷的装置，所述装置包括：A device for optimizing the load of a wind turbine, the device comprising:
    控制参数获取模块，获取风力发电机组的至少一个控制参数，其中，所述风力发电机组的多个位置的载荷受到所述至少一个控制参数的影响；Controlling a parameter acquisition module, acquiring at least one control parameter of the wind power generator, wherein a load of the plurality of positions of the wind power generator is affected by the at least one control parameter;
    载荷获取模块，获取与所述至少一个控制参数对应的所述风力发电机组的所述多个位置的载荷值；a load acquisition module acquiring a load value of the plurality of locations of the wind power generator corresponding to the at least one control parameter;
    载荷量化模块，使用预定评价模型将所述多个位置的载荷值量化为单个评价值；a load quantification module that quantizes load values of the plurality of locations into a single evaluation value using a predetermined evaluation model;
    评价值判断模块，判断评价值是否满足预定条件；The evaluation value judging module judges whether the evaluation value satisfies a predetermined condition;
    控制参数更新模块，当评价值不满足预定条件时，使用预定优化算法，基于评价值对所述至少一个控制参数进行优化来更新所述至少一个控制参数，并且控制参数获取模块再次获取所述至少一个控制参数；Controlling a parameter update module, when the evaluation value does not satisfy the predetermined condition, using a predetermined optimization algorithm, optimizing the at least one control parameter based on the evaluation value to update the at least one control parameter, and the control parameter acquisition module acquiring the at least a control parameter;
    控制参数提供模块，当评价值满足预定条件时，将获取的所述至少一个控制参数提供作为最终的控制参数。The control parameter providing module provides the acquired at least one control parameter as a final control parameter when the evaluation value satisfies a predetermined condition.
  12. 根据权利要求11所述的装置，其中，所述预定评价模型为适应度函数。The apparatus of claim 11 wherein said predetermined evaluation model is a fitness function.
  13. 根据权利要求11所述的装置，其中，载荷获取模块基于获取的所述至少一个控制参数，对所述风力发电机组的整机模型进行仿真得到所述多个位置的载荷值和所述风力发电机组的预定运行参数的值。The apparatus according to claim 11, wherein the load acquisition module simulates the whole machine model of the wind power generator based on the acquired at least one control parameter to obtain load values of the plurality of positions and the wind power generation The value of the scheduled operating parameters of the unit.
  14. 根据权利要求13所述的装置，其中，所述预定评价模型为所述多个位置的载荷值的和与约束值的乘积或者所述多个位置的载荷值分别被加权后的加权和与约束值的乘积。The apparatus according to claim 13, wherein said predetermined evaluation model is a weighted sum and constraint of a product of a sum of load values of said plurality of positions and a value of said constraint value or a load value of said plurality of positions, respectively The product of the values.
  15. 根据权利要求14所述的装置，其中，载荷量化模块根据所述风力发电机组正常运行所需要满足的针对预定运行参数的约束条件确定约束值。The apparatus of claim 14 wherein the load quantification module determines the constraint value based on constraints required for the predetermined operational parameter to be satisfied by the normal operation of the wind turbine.
  16. 根据权利要求15所述的装置，其中，The device according to claim 15, wherein
    当预定运行参数满足所述约束条件时，载荷量化模块将约束值设置为预定值；The load quantification module sets the constraint value to a predetermined value when the predetermined operational parameter satisfies the constraint condition;
    当预定运行参数不满足所述约束条件时，载荷量化模块将约束值设置为大于预定值的值。The load quantization module sets the constraint value to a value greater than a predetermined value when the predetermined operational parameter does not satisfy the constraint.
  17. 根据权利要求11所述的装置，其中，预定条件是指评价值达到最小值。The apparatus according to claim 11, wherein the predetermined condition means that the evaluation value reaches a minimum value.
  18. 根据权利要求17所述的装置，其中，当获取的所述至少一个控制参数与前一次获取的所述至少一个控制参数之间的差小于预定阈值时，评价值判断模块确定评价值达到最小值。The apparatus according to claim 17, wherein the evaluation value judging module determines that the evaluation value reaches a minimum value when a difference between the acquired at least one control parameter and the at least one control parameter acquired last time is less than a predetermined threshold value .
  19. 根据权利要求16所述的装置，其中，预定运行参数包括发电机转速和机舱振动加速度中的至少一个。The apparatus of claim 16 wherein the predetermined operating parameter comprises at least one of a generator speed and a cabin vibration acceleration.
  20. 根据权利要求11所述的装置，其中，所述多个位置的载荷包括塔底的第一方向的弯矩的疲劳载荷、塔底的第二方向的弯矩的疲劳载荷、叶根的第二方向的弯矩的疲劳载荷、塔底的第二方向的弯矩的极限载荷以及叶根的第二方向的弯矩的极限载荷中的两个或更多个。The apparatus according to claim 11, wherein the load of the plurality of positions comprises a fatigue load of a bending moment of a first direction of the tower bottom, a fatigue load of a bending moment of a second direction of the tower bottom, and a second root of the blade root Two or more of the fatigue load of the direction bending moment, the ultimate load of the bending moment of the second direction of the tower bottom, and the ultimate load of the bending moment of the blade root in the second direction.
  21. 一种存储有计算机程序的计算机可读存储介质，当所述计算机程序在被处理器执行时实现权利要求1至10中的任一项所述的用于优化风力发电机组的载荷的方法。A computer readable storage medium storing a computer program that, when executed by a processor, implements the method for optimizing a load of a wind turbine set according to any one of claims 1 to 10.
  22. 一种风力发电机组的控制***，所述控制***包括：A control system for a wind power generator, the control system comprising:
    处理器；processor;
    存储器，存储有计算机程序，当所述计算机程序被处理器执行时，实现权利要求1至10中的任一项所述的用于优化风力发电机组的载荷的方法。The memory, stored with a computer program, when the computer program is executed by the processor, implements the method for optimizing the load of the wind turbine set according to any one of claims 1 to 10.
PCT/CN2018/082347 2017-12-25 2018-04-09 Method and apparatus for optimizing loads of wind turbine WO2019127974A1 (en)

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