WO2023092783A1 - Fan fuzzy adaptive variable pitch control method capable of suppressing multiple disturbance factors - Google Patents

Fan fuzzy adaptive variable pitch control method capable of suppressing multiple disturbance factors Download PDF

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WO2023092783A1
WO2023092783A1 PCT/CN2021/140650 CN2021140650W WO2023092783A1 WO 2023092783 A1 WO2023092783 A1 WO 2023092783A1 CN 2021140650 W CN2021140650 W CN 2021140650W WO 2023092783 A1 WO2023092783 A1 WO 2023092783A1
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fuzzy
wind turbine
transfer function
pitch control
adaptive
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PCT/CN2021/140650
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French (fr)
Chinese (zh)
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邵宜祥
刘剑
胡丽萍
过亮
方渊
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南瑞集团有限公司
国网湖北省电力有限公司
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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 
    • 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
    • F03D7/0224—Adjusting blade pitch
    • 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
    • F03D7/044—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic with PID control
    • 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
    • F03D7/046—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic with learning or adaptive control, e.g. self-tuning, fuzzy logic or neural network
    • 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
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P70/00—Climate change mitigation technologies in the production process for final industrial or consumer products
    • Y02P70/50—Manufacturing or production processes characterised by the final manufactured product

Definitions

  • the invention relates to the technical field of pitch control of wind turbines, in particular to a fuzzy self-adaptive pitch control method for wind turbines capable of suppressing multiple disturbance factors.
  • the pitch control strategy of traditional wind turbines only considers a single wind speed disturbance, and does not comprehensively consider the initial parameter errors caused by installation and manufacturing, and environmental changes during the operation of wind turbines (such as Turbulent wind speed, snow accumulation, frost accumulation, etc.) and wind turbine blade changes (such as blade bending, deformation, etc.) Balance, causing blade flapping vibrations and torque fluctuations.
  • the purpose of the present invention is to propose a fan fuzzy adaptive pitch control method that can suppress multiple disturbance factors, establish a closed-loop transfer function of the wind turbine pitch control system that takes into account multiple disturbance factors, and design a fuzzy adaptive PID algorithm based on
  • the advanced wind turbine pitch control method realizes adaptive and rapid response to disturbances caused by various factors, ensures that the pitch angle of wind turbines is properly adjusted, maintains system stability, and achieves optimal capture of wind energy.
  • the invention provides a fan fuzzy self-adaptive pitch control method capable of suppressing multiple disturbance factors, including:
  • fuzzy adaptive PID control parameters based on the closed-loop transfer function and fuzzy rules
  • the fuzzy adaptive PID control is used to adjust the pitch control system of the wind turbine considering multiple disturbance factors, and output the pitch angle of the wind turbine.
  • the disturbance factors include the blade change disturbance during the operation of the wind turbine, the initial parameter error disturbance of the wind turbine installation and the environment change disturbance during the operation of the wind turbine;
  • k 1 and k 2 are disturbance coefficients
  • k 3 , k 4 , k 5 are disturbance coefficients
  • D(s) D 1 (s)+D 2 (s)+D 3 (s)
  • K P , K I , K D are the adaptive parameters of the PID controller
  • G ⁇ is the transfer function of the pitch controller
  • G c is the transfer function of the pitch actuator
  • T ⁇ is the time constant
  • G p is the transfer function of the wind turbine
  • J is the moment of inertia
  • ⁇ V(s) V(s)-V 0 (s)
  • ⁇ (s) ⁇ (s)- ⁇ 0 (s)
  • V 0 is the initial wind speed
  • ⁇ (s) is the pitch angle
  • ⁇ 0 is the pitch angle at the working point of the wind turbine
  • ⁇ , ⁇ and ⁇ are all linear coefficients.
  • determining fuzzy adaptive PID control parameters based on the closed-loop transfer function and fuzzy rules includes:
  • the initial value of the parameters of the fuzzy adaptive PID control is adjusted
  • the fuzzy adaptive PI control parameters are obtained by combining the adjustment amount of the fuzzy adaptive PID controller parameters with the initial value of the parameters.
  • the reduced-order closed-loop transfer function is:
  • ⁇ (s) is the reduced-order closed-loop transfer function
  • ⁇ is the damping ratio
  • ⁇ n is the natural frequency
  • ⁇ and ⁇ n are obtained from the dominant poles
  • the dominant pole is determined as follows:
  • the determination of the adjustment amount of fuzzy adaptive PID control parameters based on fuzzy rules includes:
  • Fuzzify the input quantity and use the Mamdani fuzzy reasoning method to obtain fuzzy subsets according to the preset fuzzy rules;
  • the output of the fuzzy controller is obtained by defuzzifying the fuzzy subset as the adjustment values ⁇ K P , ⁇ K I , ⁇ K D of the adaptive parameters of the PID controller.
  • the fuzzy controller adopts a two-dimensional fuzzy controller.
  • the fuzzy controller adopts a triangular membership function.
  • the output of the fuzzy controller is obtained by defuzzifying the fuzzy subsets using the center of gravity method.
  • the invention considers various disturbance factors in the control process of the wind turbine, establishes the closed-loop transfer function of the pitch control system of the wind turbine considering multi-factor disturbance, determines the fuzzy control rules, and realizes the self-adaptive and fast response to the disturbance caused by various factors, ensuring The pitch angle of the wind turbine is properly adjusted to maintain system stability and achieve optimal capture of wind energy.
  • the present invention applies the fuzzy control to the pitch control system.
  • the fuzzy control has robustness and strong self-adaptive ability, and can realize good control effect without establishing an accurate system dynamic model.
  • Fig. 1 is a schematic diagram of a fan fuzzy adaptive pitch control method capable of suppressing multiple disturbance factors of the present invention
  • Fig. 2 is a fuzzy control rule table preset in the present invention.
  • the present invention designs a wind turbine pitch control strategy based on the fuzzy self-adaptive PID algorithm by establishing a wind turbine pitch control system closed-loop transfer function that takes into account multi-factor disturbances, and realizes Adaptive and fast response to disturbances caused by various factors to ensure that the pitch angle of wind turbines is properly adjusted, maintain system stability, and achieve optimal capture of wind energy.
  • a fan fuzzy adaptive pitch control method capable of suppressing multiple disturbance factors, comprising:
  • the disturbance factors include blade change disturbances during wind turbine operation, wind turbine installation initial parameter error disturbances, and wind turbine environment change disturbances during operation;
  • the wind turbine pitch control system considering multiple disturbance factors is adjusted, and the pitch angle of the wind turbine is output.
  • Blade variation factors include blade bending, deformation, etc., and the disturbance can be approximately expressed by the transfer function D 1 (s) as:
  • k 1 and k 2 are the disturbance coefficients, and their values are taken according to the errors of wind turbine installation and manufacture, which are known quantities, and V(s) is the external wind speed.
  • the environmental changes during the operation of the wind turbine include turbulent wind speed, snow accumulation, frost accumulation, etc.
  • the disturbance can be expressed approximately by the transfer function D 3 (s) as:
  • k 3 , k 4 , k 5 are the disturbance coefficients, and their values are taken according to the changes of the operating environment, which are known quantities; V(s) is the external wind speed.
  • D(s) D 1 (s)+D 2 (s)+D 3 (s)
  • K P , K I , K D are the adaptive parameters of the PID controller
  • G ⁇ , G c , G p are the transfer functions of each part of the fan system
  • G ⁇ is the transfer function of the pitch controller
  • G c is the variable paddle actuator transfer function
  • T ⁇ is the time constant
  • the unit is s
  • G p is the transfer function of the wind turbine
  • J is the moment of inertia
  • ⁇ V(s) V(s)-V 0 (s)
  • ⁇ (s) ⁇ (s)- ⁇ 0 (s)
  • V 0 is the initial wind speed
  • ⁇ (s) is the pitch angle
  • ⁇ 0 is the pitch angle at the working point of the wind turbine
  • ⁇ , ⁇ and ⁇ are all linear coefficients.
  • p i is the quantity with respect to K P , K I , K D .
  • the second-order system obtained after order reduction has the following expression:
  • ⁇ is the damping ratio
  • ⁇ n is the natural frequency
  • ⁇ and ⁇ n need to be obtained from the dominant poles, so ⁇ and ⁇ n are quantities related to K P , KI , and K D .
  • the fuzzy controller is used to determine the adjustment amount of the PID controller parameter based on the fuzzy rules, and the adjustment amount of the PID controller parameter output by the fuzzy controller and the adjusted initial parameter of the PID controller Combined to obtain the adaptive parameters K P , KI , K D of the PI controller.
  • the fuzzy controller adopts a two-dimensional fuzzy controller, and the difference e between the theoretical value ⁇ ref and the actual value of the wind turbine speed and its error variation ec are used as the input of the fuzzy controller, and ⁇ ref is the wind turbine
  • the speed given value is generally set as the rated value of the fan speed, and then the input quantity is fuzzified, and then the fuzzy subset is obtained by using Mamdani fuzzy inference method according to the corresponding fuzzy rules. See Figure 2 for the fuzzy control rules, and finally the fuzzy subset is solved Fuzzy obtains the output of the fuzzy controller, which is the adjustment of the parameters of the PID controller ⁇ K P , ⁇ K I , ⁇ K D .
  • the fuzzy controller adopts the triangular membership function, and determines the fuzzy control rules according to the adjustment requirements of the fan.
  • the input quantity of the fuzzy controller is converted into the corresponding fuzzy language variable value to realize fuzzification.
  • the output of the fuzzy controller is obtained by defuzzifying the fuzzy subset using the center of gravity method.
  • the adaptive parameters K P , K I , and K D of the PI controller can be obtained by integrating the output of the fuzzy controller and the initial parameters of the PID controller.
  • the calculation formula is as follows:
  • K P K P0 + ⁇ K P
  • K I K I0 + ⁇ K I
  • K D K D0 + ⁇ K D
  • ⁇ ref and ⁇ ref are the given value of the speed of the wind turbine and the given value of the pitch angle respectively.
  • the PID controller Based on the adaptive parameters K P , K I , K D of the PID controller, the PID controller is used to adjust the pitch control system of the wind turbine considering multiple disturbance factors, and the pitch angle of the wind turbine is output.
  • the wind turbine variable pitch control method proposed in the present invention comprehensively considers various disturbance factors in the control process of the wind turbine, and realizes the self-adaptive and rapid response to the disturbance caused by various factors, ensures that the pitch angle of the wind turbine is properly adjusted, and maintains system stability , to achieve optimal capture of wind energy.
  • the embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
  • computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions
  • the device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

Abstract

A fan fuzzy adaptive variable pitch control method capable of suppressing multiple disturbance factors. The method comprehensively considers common multiple disturbance factors in actual operation of a wind turbine generator, and the factors comprise initial parameter errors during mounting and manufacturing of the wind turbine generator, environment changes during operation of the wind turbine generator, blade changes of the wind turbine generator, etc.; a closed-loop transfer function of a wind turbine generator variable pitch control system considering multi-factor disturbance is established; the wind turbine generator variable pitch control system considering multiple disturbance factors is adjusted on the basis of fuzzy adaptive PID control; and the pitch angle of the wind turbine generator is output. Adaptive quick response to disturbance caused by multiple factors is achieved, it is ensured that the pitch angle of the wind turbine generator is properly adjusted, the system stability is maintained, and optimal capture of wind energy is achieved.

Description

一种可抑制多扰动因素的风机模糊自适应变桨距控制方法A fuzzy adaptive pitch control method for wind turbines that can suppress multiple disturbance factors 技术领域technical field
本发明涉及风力机组变桨距控制技术领域，具体的说是涉及一种可抑制多扰动因素的风机模糊自适应变桨距控制方法。The invention relates to the technical field of pitch control of wind turbines, in particular to a fuzzy self-adaptive pitch control method for wind turbines capable of suppressing multiple disturbance factors.
背景技术Background technique
经济社会的持续快速发展，离不开有力的能源保障。风能作为一种绿色可再生能源，分布广泛，发电成本相对较低，而且安全性、可靠性较高。正是因为这些独特的优点，风力发电具有良好的社会效益和经济效益，因此风力发电技术越来越受到国家的重视。Sustained and rapid economic and social development is inseparable from a strong energy security. As a kind of green renewable energy, wind energy is widely distributed, the cost of power generation is relatively low, and its safety and reliability are high. It is precisely because of these unique advantages that wind power generation has good social and economic benefits, so wind power technology has attracted more and more attention from the state.
由于风力机组在实际运行中不确定因素较多，传统风机的桨距控制策略仅考虑单一的风速扰动，并未综合考虑安装与制造时造成的初始参数误差、风力机组运行期间的环境变化(例如湍流风速、积雪、积霜等)以及风力机组叶片变化(例如叶片的弯曲、变形等)等多因素扰动，因此影响风力机的输出功率以及电能质量，另外还同时造成桨叶上的载荷不平衡，引起桨叶的拍打振动和扭矩波动。Due to the many uncertain factors in the actual operation of wind turbines, the pitch control strategy of traditional wind turbines only considers a single wind speed disturbance, and does not comprehensively consider the initial parameter errors caused by installation and manufacturing, and environmental changes during the operation of wind turbines (such as Turbulent wind speed, snow accumulation, frost accumulation, etc.) and wind turbine blade changes (such as blade bending, deformation, etc.) Balance, causing blade flapping vibrations and torque fluctuations.
发明内容Contents of the invention
本发明的目的在于提出一种可抑制多扰动因素的风机模糊自适应变桨距控制方法，建立计及多因素扰动的风电机组变桨控制系统闭环传递函数，设计一种基于模糊自适应PID算法的风力发电机组变桨距控制方法，实现对多种因素引起的扰动自适应快速响应，确保风电机组桨距角得到恰当调整，维持系统稳定，实现对风能的最优捕获。The purpose of the present invention is to propose a fan fuzzy adaptive pitch control method that can suppress multiple disturbance factors, establish a closed-loop transfer function of the wind turbine pitch control system that takes into account multiple disturbance factors, and design a fuzzy adaptive PID algorithm based on The advanced wind turbine pitch control method realizes adaptive and rapid response to disturbances caused by various factors, ensures that the pitch angle of wind turbines is properly adjusted, maintains system stability, and achieves optimal capture of wind energy.
为达到上述目的，本发明采用的技术方案如下：In order to achieve the above object, the technical scheme adopted in the present invention is as follows:
本发明提供一种可抑制多扰动因素的风机模糊自适应变桨距控制方法，包括：The invention provides a fan fuzzy self-adaptive pitch control method capable of suppressing multiple disturbance factors, including:
建立考虑多扰动因素的风力机组变桨距控制系统的闭环传递函数；Establish the closed-loop transfer function of the wind turbine pitch control system considering multiple disturbance factors;
基于所述闭环传递函数和模糊规则确定模糊自适应PID控制参数；determining fuzzy adaptive PID control parameters based on the closed-loop transfer function and fuzzy rules;
采用模糊自适应PID控制对所述考虑多扰动因素的风力机组变桨距控制系统进行调节，输出风力机组桨距角。The fuzzy adaptive PID control is used to adjust the pitch control system of the wind turbine considering multiple disturbance factors, and output the pitch angle of the wind turbine.
进一步的，所述扰动因素包括风力机组运行期间叶片变化扰动，风力机组安装初始参数误差扰动和风力机组运行期间环境变化扰动；Further, the disturbance factors include the blade change disturbance during the operation of the wind turbine, the initial parameter error disturbance of the wind turbine installation and the environment change disturbance during the operation of the wind turbine;
建立考虑多扰动因素的风力机组变桨距控制系统的闭环传递函数，包括：Establish the closed-loop transfer function of the wind turbine pitch control system considering multiple disturbance factors, including:
建立风力机组运行期间叶片变化扰动的传递函数：Set up the transfer function for the blade change disturbance during wind turbine operation:
Figure PCTCN2021140650-appb-000001
Figure PCTCN2021140650-appb-000001
其中，
Figure PCTCN2021140650-appb-000002
为叶根拍打弯矩M对桨距角β的线性化系数，
Figure PCTCN2021140650-appb-000003
为叶片的空气动力阻尼系数，ω z为叶片拍打振动模态的自然角频率，V(s)为外界风速； in,
Figure PCTCN2021140650-appb-000002
is the linearization coefficient of the flapping moment M of the blade root to the pitch angle β,
Figure PCTCN2021140650-appb-000003
is the aerodynamic damping coefficient of the blade, ω z is the natural angular frequency of the flapping vibration mode of the blade, and V(s) is the external wind speed;
建立风力机组安装初始参数误差扰动的传递函数：Establish the transfer function of the initial parameter error disturbance of the wind turbine installation:
Figure PCTCN2021140650-appb-000004
Figure PCTCN2021140650-appb-000004
其中，k 1，k 2为扰动系数； Among them, k 1 and k 2 are disturbance coefficients;
建立风力机组运行期间环境变化扰动的传递函数：Establish the transfer function for the disturbance of environmental changes during the operation of the wind turbine:
Figure PCTCN2021140650-appb-000005
Figure PCTCN2021140650-appb-000005
其中，k 3，k 4，k 5为扰动系数； Among them, k 3 , k 4 , k 5 are disturbance coefficients;
综合上述传递函数，得到风力机组变桨距控制系统的闭环传递函数：Combining the above transfer functions, the closed-loop transfer function of the wind turbine pitch control system is obtained:
Figure PCTCN2021140650-appb-000006
Figure PCTCN2021140650-appb-000006
其中，D(s)＝D 1(s)+D 2(s)+D 3(s)，
Figure PCTCN2021140650-appb-000007
K P、K I、K D为PID控制器的自适应参数，G θ为变桨控制器传递函数，G c为变桨执行器传递函数，
Figure PCTCN2021140650-appb-000008
T β为时间常数，G p为风力机的传递函数，
Figure PCTCN2021140650-appb-000009
J为转动惯量，ΔV(s)＝V(s)-V 0(s)，Δβ(s)＝β(s)-β 0(s)，V 0为初始风速，β(s)为桨距角，β 0是风力机工作点处的浆距角，
Figure PCTCN2021140650-appb-000010
μ、ξ和γ均为线性系数。 Wherein, D(s)=D 1 (s)+D 2 (s)+D 3 (s),
Figure PCTCN2021140650-appb-000007
K P , K I , K D are the adaptive parameters of the PID controller, G θ is the transfer function of the pitch controller, G c is the transfer function of the pitch actuator,
Figure PCTCN2021140650-appb-000008
T β is the time constant, G p is the transfer function of the wind turbine,
Figure PCTCN2021140650-appb-000009
J is the moment of inertia, ΔV(s)=V(s)-V 0 (s), Δβ(s)=β(s)-β 0 (s), V 0 is the initial wind speed, β(s) is the pitch angle, β 0 is the pitch angle at the working point of the wind turbine,
Figure PCTCN2021140650-appb-000010
μ, ξ and γ are all linear coefficients.
进一步的，基于所述闭环传递函数和模糊规则确定模糊自适应PID控制参数，包括：Further, determining fuzzy adaptive PID control parameters based on the closed-loop transfer function and fuzzy rules includes:
对所述闭环传递函数进行降阶处理，并基于降阶处理后的闭环传递函数计算风力机组变桨距控制系统的超调量和调节时间；Perform order reduction processing on the closed-loop transfer function, and calculate the overshoot and adjustment time of the pitch control system of the wind turbine based on the closed-loop transfer function after the order reduction processing;
根据超调量和调节时间整定模糊自适应PID控制的参数初值；According to the overshoot and adjustment time, the initial value of the parameters of the fuzzy adaptive PID control is adjusted;
基于模糊规则确定模糊自适应PID控制参数的调整量；Determine the adjustment amount of fuzzy adaptive PID control parameters based on fuzzy rules;
将模糊自适应PID控制器参数的调整量与整定的参数初值相结合得到模糊自适应PI控制参数。The fuzzy adaptive PI control parameters are obtained by combining the adjustment amount of the fuzzy adaptive PID controller parameters with the initial value of the parameters.
进一步的，further,
降阶后的闭环传递函数为：The reduced-order closed-loop transfer function is:
Figure PCTCN2021140650-appb-000011
Figure PCTCN2021140650-appb-000011
其中，φ(s)为降阶后的闭环传递函数，ζ为阻尼比，ω n为自然频率，ζ和ω n根据主导极点得到， Among them, φ(s) is the reduced-order closed-loop transfer function, ζ is the damping ratio, ω n is the natural frequency, ζ and ω n are obtained from the dominant poles,
所述主导极点确定如下：The dominant pole is determined as follows:
分别令传递函数G(s)的分子、分母等于零得到零点z i和极点p i，在复平面内寻找出距离虚轴最近且附近无闭环零点的极点，即为主导极点。 Make the numerator and denominator of the transfer function G(s) equal to zero respectively to get the zero z i and the pole p i , and find the pole closest to the imaginary axis in the complex plane without closed-loop zero nearby, which is the dominant pole.
进一步的，所述计算风力机组变桨距控制系统的超调量和调节时间如下：Further, the calculation of the overshoot and adjustment time of the wind turbine pitch control system is as follows:
当0＜ζ＜1时，超调量σ为：When 0<ζ<1, the overshoot σ is:
Figure PCTCN2021140650-appb-000012
Figure PCTCN2021140650-appb-000012
以误差带Δ＝0.05为标准，调节时间t s为： Taking the error band Δ=0.05 as the standard, the adjustment time t s is:
Figure PCTCN2021140650-appb-000013
Figure PCTCN2021140650-appb-000013
当ζ＞1时，不存在超调量；以误差带Δ＝0.05为标准，调节时间t s为： When ζ>1, there is no overshoot; with the error band Δ=0.05 as the standard, the adjustment time t s is:
Figure PCTCN2021140650-appb-000014
Figure PCTCN2021140650-appb-000014
Figure PCTCN2021140650-appb-000015
Figure PCTCN2021140650-appb-000015
Figure PCTCN2021140650-appb-000016
Figure PCTCN2021140650-appb-000016
进一步的，所述基于模糊规则确定模糊自适应PID控制参数的调整量，包括：Further, the determination of the adjustment amount of fuzzy adaptive PID control parameters based on fuzzy rules includes:
将风力机组的转速理论值ω ref与实际值间的差值e以及误差变化量ec作为模糊控制器的输入量； The difference e between the theoretical value ω ref and the actual value of the wind turbine speed and the error variation ec are used as the input of the fuzzy controller;
将输入量模糊化，根据预设定的模糊规则运用Mamdani模糊推理法得到模糊子集；Fuzzify the input quantity, and use the Mamdani fuzzy reasoning method to obtain fuzzy subsets according to the preset fuzzy rules;
将模糊子集解模糊得到模糊控制器的输出量作为PID控制器自适应参数的调整量ΔK P、ΔK I、ΔK D。 The output of the fuzzy controller is obtained by defuzzifying the fuzzy subset as the adjustment values ΔK P , ΔK I , ΔK D of the adaptive parameters of the PID controller.
进一步的，所述模糊控制器采用二维模糊控制器。Further, the fuzzy controller adopts a two-dimensional fuzzy controller.
进一步的，所述模糊控制器采用三角形隶属度函数。Further, the fuzzy controller adopts a triangular membership function.
进一步的，采用重心法对模糊子集解模糊得到模糊控制器的输出量。Furthermore, the output of the fuzzy controller is obtained by defuzzifying the fuzzy subsets using the center of gravity method.
本发明具有如下有益效果：The present invention has following beneficial effects:
本发明考虑到风力机组控制过程中各种扰动因素，建立计及多因素扰动的风电机组变桨控制系统闭环传递函数，确定模糊控制规则，实现对多种因素引起的扰动自适应快速响应，确保风电机组桨距角得到恰当调整，维持系统稳定，实现对风能的最优捕获。The invention considers various disturbance factors in the control process of the wind turbine, establishes the closed-loop transfer function of the pitch control system of the wind turbine considering multi-factor disturbance, determines the fuzzy control rules, and realizes the self-adaptive and fast response to the disturbance caused by various factors, ensuring The pitch angle of the wind turbine is properly adjusted to maintain system stability and achieve optimal capture of wind energy.
本发明将模糊控制应用在变桨距控制系统中，模糊控制具有鲁棒性和自适应能力强以及不需要建立精确的系统动态模型就能够实现很好的控制效果。The present invention applies the fuzzy control to the pitch control system. The fuzzy control has robustness and strong self-adaptive ability, and can realize good control effect without establishing an accurate system dynamic model.
附图说明Description of drawings
图1为本发明的一种可抑制多扰动因素的风机模糊自适应变桨距控制方法原理图；Fig. 1 is a schematic diagram of a fan fuzzy adaptive pitch control method capable of suppressing multiple disturbance factors of the present invention;
图2为本发明预设的模糊控制规则表。Fig. 2 is a fuzzy control rule table preset in the present invention.
具体实施方式Detailed ways
下面对本发明作进一步描述。以下实施例仅用于更加清楚地说明本发明的技术方案，而不能以此来限制本发明的保护范围。The present invention will be further described below. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.
风力机组在实际运行中不确定因素较多，包括风电机组在安装与制造时的初始参数误差、风力机组运行期间的环境变化(例如湍流风速、积雪、积霜等)，以及叶片变化(例如叶片的弯曲、变形等)等因素，本发明通过建立计及多因素扰动的风电机组变桨控制系统闭环传递函数，设计一种基于模糊自适应PID算法的风力发电机组变桨距控制策略，实现对多种因素引起的扰动自适应快速响应，确保风电机组桨距角得到恰当调整，维持系统稳定，实现对风能的最优捕获。There are many uncertain factors in the actual operation of wind turbines, including initial parameter errors during installation and manufacture of wind turbines, environmental changes during the operation of wind turbines (such as turbulent wind speed, snow accumulation, frost accumulation, etc.), and blade changes (such as blade bending, deformation, etc.), the present invention designs a wind turbine pitch control strategy based on the fuzzy self-adaptive PID algorithm by establishing a wind turbine pitch control system closed-loop transfer function that takes into account multi-factor disturbances, and realizes Adaptive and fast response to disturbances caused by various factors to ensure that the pitch angle of wind turbines is properly adjusted, maintain system stability, and achieve optimal capture of wind energy.
一种可抑制多扰动因素的风机模糊自适应变桨距控制方法，包括：A fan fuzzy adaptive pitch control method capable of suppressing multiple disturbance factors, comprising:
建立考虑多扰动因素的风力机组变桨距控制系统的闭环传递函数；所述扰动因素包括风力机组运行期间叶片变化扰动，风力机组安装初始参数误差扰动和风力机组运行期间环境变化扰动；Establishing a closed-loop transfer function of a wind turbine pitch control system considering multiple disturbance factors; the disturbance factors include blade change disturbances during wind turbine operation, wind turbine installation initial parameter error disturbances, and wind turbine environment change disturbances during operation;
基于模糊自适应PID控制对考虑多扰动因素的风力机组变桨距控制系统进行调节，输出风力机组桨距角。Based on the fuzzy adaptive PID control, the wind turbine pitch control system considering multiple disturbance factors is adjusted, and the pitch angle of the wind turbine is output.
作为一种优选的实施方式，本实施例中，建立考虑多扰动因素的风力机组变桨距控制系统的闭环传递函数参见图1，具体如下：As a preferred implementation, in this embodiment, the closed-loop transfer function of the wind turbine pitch control system considering multiple disturbance factors is established as shown in Figure 1, as follows:
建立风力机组运行期间叶片变化扰动的传递函数，Establish the transfer function of the blade change disturbance during the operation of the wind turbine,
叶片变化因素包括叶片的弯曲、变形等，可将该扰动用传递函数D 1(s)近似表述为： Blade variation factors include blade bending, deformation, etc., and the disturbance can be approximately expressed by the transfer function D 1 (s) as:
Figure PCTCN2021140650-appb-000017
Figure PCTCN2021140650-appb-000017
式中：
Figure PCTCN2021140650-appb-000018
为叶根拍打弯矩M对桨距角β的线性化系数，
Figure PCTCN2021140650-appb-000019
为叶片的空气动力阻尼系数，ω z为叶片拍打振动模态的自然角频率，
Figure PCTCN2021140650-appb-000020
和ω z均为已知量，V(s)为外界风速，s为传递函数参数。 In the formula:
Figure PCTCN2021140650-appb-000018
is the linearization coefficient of the flapping moment M of the blade root to the pitch angle β,
Figure PCTCN2021140650-appb-000019
is the aerodynamic damping coefficient of the blade, ω z is the natural angular frequency of the flapping vibration mode of the blade,
Figure PCTCN2021140650-appb-000020
and ω z are known quantities, V(s) is the external wind speed, and s is the transfer function parameter.
建立风力机组安装初始参数误差扰动的传递函数，Establish the transfer function of the initial parameter error disturbance of the wind turbine installation,
风力机组在安装与制造时存在初始参数误差，可将该扰动用传递函数D 2(s)近似表述为： There is an error in the initial parameters of the wind turbine during installation and manufacture, and the disturbance can be approximately expressed by the transfer function D 2 (s) as:
Figure PCTCN2021140650-appb-000021
Figure PCTCN2021140650-appb-000021
式中：k 1，k 2为扰动系数，其值根据风力机安装与制造时的误差取值，为已知量，V(s)为外界风速。 In the formula: k 1 and k 2 are the disturbance coefficients, and their values are taken according to the errors of wind turbine installation and manufacture, which are known quantities, and V(s) is the external wind speed.
建立风力机组运行期间环境变化扰动的传递函数，Establish the transfer function of the environmental change disturbance during the operation of the wind turbine,
风力机组运行期间的环境变化包括湍流风速、积雪、积霜等，可将该扰动用传递函数D 3(s)近似表述为： The environmental changes during the operation of the wind turbine include turbulent wind speed, snow accumulation, frost accumulation, etc. The disturbance can be expressed approximately by the transfer function D 3 (s) as:
Figure PCTCN2021140650-appb-000022
Figure PCTCN2021140650-appb-000022
式中：k 3，k 4，k 5为扰动系数，其值根据运行时环境的变化取值，为已知量；V(s)为外界风速。 In the formula: k 3 , k 4 , k 5 are the disturbance coefficients, and their values are taken according to the changes of the operating environment, which are known quantities; V(s) is the external wind speed.
综合以上各扰动因素，建立风力机组变桨距控制系统的闭环传递函数如下所示：Based on the above disturbance factors, the closed-loop transfer function of the wind turbine pitch control system is established as follows:
Figure PCTCN2021140650-appb-000023
Figure PCTCN2021140650-appb-000023
式中，D(s)＝D 1(s)+D 2(s)+D 3(s)，
Figure PCTCN2021140650-appb-000024
K P、K I、K D为PID控制器的自适应参数，G θ、G c、G p均为组成风机系统各部分的传递函数，G θ为变桨控制器传递函数，G c为变桨执行器传递函数，
Figure PCTCN2021140650-appb-000025
T β为时间常数，单位为s；G p为风力机的传递函数，
Figure PCTCN2021140650-appb-000026
J为转动惯量，ΔV(s)＝V(s)-V 0(s)，Δβ(s)＝β(s)-β 0(s)，V 0为初始风速，β(s)为桨距角，β 0是风力机工作点处的浆距角，
Figure PCTCN2021140650-appb-000027
μ、ξ和γ均为线性系数。 In the formula, D(s)=D 1 (s)+D 2 (s)+D 3 (s),
Figure PCTCN2021140650-appb-000024
K P , K I , K D are the adaptive parameters of the PID controller, G θ , G c , G p are the transfer functions of each part of the fan system, G θ is the transfer function of the pitch controller, and G c is the variable paddle actuator transfer function,
Figure PCTCN2021140650-appb-000025
T β is the time constant, the unit is s; G p is the transfer function of the wind turbine,
Figure PCTCN2021140650-appb-000026
J is the moment of inertia, ΔV(s)=V(s)-V 0 (s), Δβ(s)=β(s)-β 0 (s), V 0 is the initial wind speed, β(s) is the pitch angle, β 0 is the pitch angle at the working point of the wind turbine,
Figure PCTCN2021140650-appb-000027
μ, ξ and γ are all linear coefficients.
作为一种优选的实施方式，本实施例中，通过令传递函数G(s)的分子、分母等于零以求解出系统零、极点z i、p i(i＝1,2,3…)，p i是关于K P、K I、K D的量。 As a preferred implementation, in this embodiment, by making the numerator and denominator of the transfer function G(s) equal to zero to solve the system zero, pole z i , p i (i=1,2,3...), p i is the quantity with respect to K P , K I , K D .
在复平面内，寻找出距离虚轴最近且附近无闭环零点的极点，这些极点就是主导极点。从而进行等效简化实现对计及多因素扰动控制系统闭环传递函数的降阶，对于降阶后得到的二阶系统有如下表达式：In the complex plane, find the poles that are closest to the imaginary axis and have no closed-loop zeros nearby. These poles are the dominant poles. Therefore, the equivalent simplification is carried out to realize the order reduction of the closed-loop transfer function of the multi-factor disturbance control system. The second-order system obtained after order reduction has the following expression:
Figure PCTCN2021140650-appb-000028
Figure PCTCN2021140650-appb-000028
式中，ζ为阻尼比，ω n为自然频率，ζ和ω n需根据主导极点得到，因此ζ和ω n是关于K P、K I、K D的量。当0＜ζ＜1时，系统超调量σ为： In the formula, ζ is the damping ratio, ω n is the natural frequency, and ζ and ω n need to be obtained from the dominant poles, so ζ and ω n are quantities related to K P , KI , and K D . When 0<ζ<1, the system overshoot σ is:
Figure PCTCN2021140650-appb-000029
Figure PCTCN2021140650-appb-000029
以误差带Δ＝0.05为标准，调节时间t s为： Taking the error band Δ=0.05 as the standard, the adjustment time t s is:
Figure PCTCN2021140650-appb-000030
Figure PCTCN2021140650-appb-000030
当ζ＞1时,不存在超调量；以误差带Δ＝0.05为标准，调节时间t s为： When ζ>1, there is no overshoot; with the error band Δ=0.05 as the standard, the adjustment time t s is:
Figure PCTCN2021140650-appb-000031
Figure PCTCN2021140650-appb-000031
上式中，
Figure PCTCN2021140650-appb-000032
In the above formula,
Figure PCTCN2021140650-appb-000032
系统超调量和调节时间越小越好，因为ζ和ω n是关于K P、K I、K D的量，所以σ和t s也是关于K P、K I、K D的量，因此可根据超调量σ和调节时间t s的计算公式指导整定模糊自适应PID控制器的参数初值K P0、K I0、K D0使超调量和调节时间尽可能小。 The smaller the system overshoot and adjustment time, the better, because ζ and ω n are related to K P , KI , K D , so σ and t s are also related to K P , KI , K D , so it can be According to the calculation formula of overshoot σ and adjustment time t s , the initial parameters K P0 , K I0 , K D0 of the fuzzy adaptive PID controller are adjusted to make the overshoot and adjustment time as small as possible.
作为一种优选的实施方式，本实施例中，采用模糊控制器基于模糊规则确定PID控制器参数的调整量，将模糊控制器输出的PID控制器参数的调整量与整定的PID控制器初始参数结合得到PI控制器的自适应参数K P、K I、K D。 As a preferred implementation, in this embodiment, the fuzzy controller is used to determine the adjustment amount of the PID controller parameter based on the fuzzy rules, and the adjustment amount of the PID controller parameter output by the fuzzy controller and the adjusted initial parameter of the PID controller Combined to obtain the adaptive parameters K P , KI , K D of the PI controller.
参见图1，模糊控制器采用二维模糊控制器，将风力机组的转速理论值ω ref与实际值间 的差值e及其误差变化量ec作为模糊控制器的输入量，ω ref为风力机转速给定值，一般设定为风机转速额定值，然后将输入量模糊化，再根据相应的模糊规则运用Mamdani模糊推理法得到模糊子集，模糊控制规则参见图2，最后将模糊子集解模糊得到模糊控制器的输出量，该输出量为PID控制器参数的调整量ΔK P、ΔK I、ΔK D。 Referring to Figure 1, the fuzzy controller adopts a two-dimensional fuzzy controller, and the difference e between the theoretical value ω ref and the actual value of the wind turbine speed and its error variation ec are used as the input of the fuzzy controller, and ω ref is the wind turbine The speed given value is generally set as the rated value of the fan speed, and then the input quantity is fuzzified, and then the fuzzy subset is obtained by using Mamdani fuzzy inference method according to the corresponding fuzzy rules. See Figure 2 for the fuzzy control rules, and finally the fuzzy subset is solved Fuzzy obtains the output of the fuzzy controller, which is the adjustment of the parameters of the PID controller ΔK P , ΔK I , ΔK D .
本实施例中，模糊控制器采用三角形隶属度函数，并根据风机调节要求，确定模糊控制规则。In this embodiment, the fuzzy controller adopts the triangular membership function, and determines the fuzzy control rules according to the adjustment requirements of the fan.
本实施例中，将模糊控制器输入量转换为相应的模糊语言变量值以实现模糊化。In this embodiment, the input quantity of the fuzzy controller is converted into the corresponding fuzzy language variable value to realize fuzzification.
本实施例中，采用重心法对模糊子集解模糊得到模糊控制器的输出量。In this embodiment, the output of the fuzzy controller is obtained by defuzzifying the fuzzy subset using the center of gravity method.
综合模糊控制器输出量与PID控制器初始参数可以得到PI控制器的自适应参数K P、K I、K D，计算公式如下： The adaptive parameters K P , K I , and K D of the PI controller can be obtained by integrating the output of the fuzzy controller and the initial parameters of the PID controller. The calculation formula is as follows:
K P＝K P0+ΔK P K P ＝K P0 +ΔK P
K I＝K I0+ΔK I K I =K I0 +ΔK I
K D＝K D0+ΔK D K D ＝K D0 +ΔK D
参见图1，ω ref和β ref分别为风力机转速的给定值和浆距角的给定值。基于得到PID控制器的自适应参数K P、K I、K D，采用PID控制器对考虑多扰动因素的风力机组变桨距控制系统进行调节，输出风力机组桨距角。 Referring to Fig. 1, ω ref and β ref are the given value of the speed of the wind turbine and the given value of the pitch angle respectively. Based on the adaptive parameters K P , K I , K D of the PID controller, the PID controller is used to adjust the pitch control system of the wind turbine considering multiple disturbance factors, and the pitch angle of the wind turbine is output.
本发明所提风机变桨距控制方法综合考虑到风力机组控制过程中各种扰动因素，实现了对多种因素引起的扰动自适应快速响应，确保风力机组桨距角得到恰当调整，维持系统稳定，实现对风能的最优捕获。The wind turbine variable pitch control method proposed in the present invention comprehensively considers various disturbance factors in the control process of the wind turbine, and realizes the self-adaptive and rapid response to the disturbance caused by various factors, ensures that the pitch angle of the wind turbine is properly adjusted, and maintains system stability , to achieve optimal capture of wind energy.
本领域内的技术人员应明白，本申请的实施例可提供为方法、系统、或计算机程序产品。因此，本申请可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。Those skilled in the art should understand that the embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
本发明是参照根据本申请实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一 个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow diagram procedure or procedures and/or block diagram procedures or blocks.
最后应当说明的是：以上实施例仅用以说明本发明的技术方案而非对其限制，尽管参照上述实施例对本发明进行了详细的说明，所属领域的普通技术人员应当理解：依然可以对本发明的具体实施方式进行修改或者等同替换，而未脱离本发明精神和范围的任何修改或者等同替换，其均应涵盖在本发明的权利要求保护范围之内。Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: the present invention can still be Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall fall within the protection scope of the claims of the present invention.

Claims (9)

  1. 一种可抑制多扰动因素的风机模糊自适应变桨距控制方法，其特征在于，包括：A fan fuzzy adaptive pitch control method capable of suppressing multiple disturbance factors, characterized in that it includes:
    建立考虑多扰动因素的风力机组变桨距控制系统的闭环传递函数；Establish the closed-loop transfer function of the wind turbine pitch control system considering multiple disturbance factors;
    基于所述闭环传递函数和模糊规则确定模糊自适应PID控制参数；determining fuzzy adaptive PID control parameters based on the closed-loop transfer function and fuzzy rules;
    采用模糊自适应PID控制对所述考虑多扰动因素的风力机组变桨距控制系统进行调节，输出风力机组桨距角。The fuzzy adaptive PID control is used to adjust the pitch control system of the wind turbine considering multiple disturbance factors, and output the pitch angle of the wind turbine.
  2. 根据权利要求1所述的一种可抑制多扰动因素的风机模糊自适应变桨距控制方法，其特征在于，所述扰动因素包括风力机组运行期间叶片变化扰动，风力机组安装初始参数误差扰动和风力机组运行期间环境变化扰动；A fuzzy adaptive pitch control method for wind turbines capable of suppressing multiple disturbance factors according to claim 1, wherein the disturbance factors include blade change disturbance during wind turbine operation, wind turbine installation initial parameter error disturbance and Environmental changes and disturbances during wind turbine operation;
    建立考虑多扰动因素的风力机组变桨距控制系统的闭环传递函数，包括：Establish the closed-loop transfer function of the wind turbine pitch control system considering multiple disturbance factors, including:
    建立风力机组运行期间叶片变化扰动的传递函数：Set up the transfer function for the blade change disturbance during wind turbine operation:
    Figure PCTCN2021140650-appb-100001
    Figure PCTCN2021140650-appb-100001
    其中，
    Figure PCTCN2021140650-appb-100002
    为叶根拍打弯矩M对桨距角β的线性化系数，
    Figure PCTCN2021140650-appb-100003
    为叶片的空气动力阻尼系数，ω z为叶片拍打振动模态的自然角频率，V(s)为外界风速；     in,
    Figure PCTCN2021140650-appb-100002
    is the linearization coefficient of the flapping moment M of the blade root to the pitch angle β,
    Figure PCTCN2021140650-appb-100003
    is the aerodynamic damping coefficient of the blade, ω z is the natural angular frequency of the flapping vibration mode of the blade, and V(s) is the external wind speed;
    建立风力机组安装初始参数误差扰动的传递函数：Establish the transfer function of the initial parameter error disturbance of the wind turbine installation:
    Figure PCTCN2021140650-appb-100004
    Figure PCTCN2021140650-appb-100004
    其中，k 1，k 2为扰动系数； Among them, k 1 and k 2 are disturbance coefficients;
    建立风力机组运行期间环境变化扰动的传递函数：Establish the transfer function for the disturbance of environmental changes during the operation of the wind turbine:
    Figure PCTCN2021140650-appb-100005
    Figure PCTCN2021140650-appb-100005
    其中，k 3，k 4，k 5为扰动系数； Among them, k 3 , k 4 , k 5 are disturbance coefficients;
    综合上述传递函数，得到风力机组变桨距控制系统的闭环传递函数：Combining the above transfer functions, the closed-loop transfer function of the wind turbine pitch control system is obtained:
    Figure PCTCN2021140650-appb-100006
    Figure PCTCN2021140650-appb-100006
    其中，D(s)＝D 1(s)+D 2(s)+D 3(s)，
    Figure PCTCN2021140650-appb-100007
    K P、K I、K D为PID控制器的自适应参数，G θ为变桨控制器传递函数，G c为变桨执行器传递函数，
    Figure PCTCN2021140650-appb-100008
    T β为时间常数，G p为风力机的传递函数，
    Figure PCTCN2021140650-appb-100009
    J为转动惯量， ΔV(s)＝V(s)-V 0(s)，Δβ(s)＝β(s)-β 0(s)，V 0为初始风速，β(s)为桨距角，β 0是风力机工作点处的浆距角，
    Figure PCTCN2021140650-appb-100010
    μ、ξ和γ均为线性系数。     Wherein, D(s)=D 1 (s)+D 2 (s)+D 3 (s),
    Figure PCTCN2021140650-appb-100007
    K P , K I , K D are the adaptive parameters of the PID controller, G θ is the transfer function of the pitch controller, G c is the transfer function of the pitch actuator,
    Figure PCTCN2021140650-appb-100008
    T β is the time constant, G p is the transfer function of the wind turbine,
    Figure PCTCN2021140650-appb-100009
    J is the moment of inertia, ΔV(s)=V(s)-V 0 (s), Δβ(s)=β(s)-β 0 (s), V 0 is the initial wind speed, β(s) is the pitch angle, β 0 is the pitch angle at the working point of the wind turbine,
    Figure PCTCN2021140650-appb-100010
    μ, ξ and γ are all linear coefficients.
  3. 根据权利要求2所述的一种可抑制多扰动因素的风机模糊自适应变桨距控制方法，其特征在于，基于所述闭环传递函数和模糊规则确定模糊自适应PID控制参数，包括：The fuzzy adaptive pitch control method for wind turbines capable of suppressing multiple disturbance factors according to claim 2, wherein determining fuzzy adaptive PID control parameters based on the closed-loop transfer function and fuzzy rules includes:
    对所述闭环传递函数进行降阶处理，并基于降阶处理后的闭环传递函数计算风力机组变桨距控制系统的超调量和调节时间；Perform order reduction processing on the closed-loop transfer function, and calculate the overshoot and adjustment time of the pitch control system of the wind turbine based on the closed-loop transfer function after the order reduction processing;
    根据超调量和调节时间整定模糊自适应PID控制的参数初值；According to the overshoot and adjustment time, the initial value of the parameters of the fuzzy adaptive PID control is adjusted;
    基于模糊规则确定模糊自适应PID控制参数的调整量；Determine the adjustment amount of fuzzy adaptive PID control parameters based on fuzzy rules;
    将模糊自适应PID控制器参数的调整量与整定的参数初值相结合得到模糊自适应PI控制参数。The fuzzy adaptive PI control parameters are obtained by combining the adjustment amount of the fuzzy adaptive PID controller parameters with the initial value of the parameters.
  4. 根据权利要求3所述的一种可抑制多扰动因素的风机模糊自适应变桨距控制方法，其特征在于，A fuzzy adaptive pitch control method for wind turbines capable of suppressing multiple disturbance factors according to claim 3, characterized in that,
    降阶后的闭环传递函数为：The reduced-order closed-loop transfer function is:
    Figure PCTCN2021140650-appb-100011
    Figure PCTCN2021140650-appb-100011
    其中，φ(s)为降阶后的闭环传递函数，ζ为阻尼比，ω n为自然频率，ζ和ω n根据主导极点得到， Among them, φ(s) is the reduced-order closed-loop transfer function, ζ is the damping ratio, ω n is the natural frequency, ζ and ω n are obtained from the dominant poles,
    所述主导极点确定如下：The dominant pole is determined as follows:
    分别令传递函数G(s)的分子、分母等于零得到零点z i和极点p i，在复平面内寻找出距离虚轴最近且附近无闭环零点的极点，即为主导极点。 Make the numerator and denominator of the transfer function G(s) equal to zero respectively to get the zero z i and the pole p i , and find the pole closest to the imaginary axis in the complex plane without closed-loop zero nearby, which is the dominant pole.
  5. 根据权利要求4所述的一种可抑制多扰动因素的风机模糊自适应变桨距控制方法，其特征在于，所述计算风力机组变桨距控制系统的超调量和调节时间如下：A fuzzy adaptive pitch control method for wind turbines capable of suppressing multiple disturbance factors according to claim 4, wherein the calculation of the overshoot and adjustment time of the pitch control system of the wind turbine is as follows:
    当0＜ζ＜1时，超调量σ为：When 0<ζ<1, the overshoot σ is:
    Figure PCTCN2021140650-appb-100012
    Figure PCTCN2021140650-appb-100012
    以误差带Δ＝0.05为标准，调节时间t s为： Taking the error band Δ=0.05 as the standard, the adjustment time t s is:
    Figure PCTCN2021140650-appb-100013
    Figure PCTCN2021140650-appb-100013
    当ζ＞1时，不存在超调量；以误差带Δ＝0.05为标准，调节时间t s为： When ζ>1, there is no overshoot; with the error band Δ=0.05 as the standard, the adjustment time t s is:
    Figure PCTCN2021140650-appb-100014
    Figure PCTCN2021140650-appb-100014
    Figure PCTCN2021140650-appb-100015
    Figure PCTCN2021140650-appb-100015
    Figure PCTCN2021140650-appb-100016
    Figure PCTCN2021140650-appb-100016
  6. 根据权利要求3所述的一种可抑制多扰动因素的风机模糊自适应变桨距控制方法，其特征在于，所述基于模糊规则确定模糊自适应PID控制参数的调整量，包括：A kind of wind turbine fuzzy adaptive pitch control method capable of suppressing multiple disturbance factors according to claim 3, wherein said determining the adjustment amount of fuzzy adaptive PID control parameters based on fuzzy rules includes:
    将风力机组的转速理论值ω ref与实际值间的差值e以及误差变化量ec作为模糊控制器的输入量； The difference e between the theoretical value ω ref and the actual value of the wind turbine speed and the error variation ec are used as the input of the fuzzy controller;
    将输入量模糊化，根据预设定的模糊规则运用Mamdani模糊推理法得到模糊子集；Fuzzify the input quantity, and use the Mamdani fuzzy reasoning method to obtain fuzzy subsets according to the preset fuzzy rules;
    将模糊子集解模糊得到模糊控制器的输出量作为PID控制器自适应参数的调整量ΔK P、ΔK I、ΔK D。 The output of the fuzzy controller is obtained by defuzzifying the fuzzy subset as the adjustment values ΔK P , ΔK I , ΔK D of the adaptive parameters of the PID controller.
  7. 根据权利要求6所述的一种可抑制多扰动因素的风机模糊自适应变桨距控制方法，其特征在于，所述模糊控制器采用二维模糊控制器。The fuzzy adaptive pitch control method for wind turbines capable of suppressing multiple disturbance factors according to claim 6, wherein the fuzzy controller is a two-dimensional fuzzy controller.
  8. 根据权利要求6所述的一种可抑制多扰动因素的风机模糊自适应变桨距控制方法，其特征在于，所述模糊控制器采用三角形隶属度函数。The fuzzy adaptive pitch control method for wind turbines capable of suppressing multiple disturbance factors according to claim 6, wherein the fuzzy controller adopts a triangular membership function.
  9. 根据权利要求6所述的一种可抑制多扰动因素的风机模糊自适应变桨距控制方法，其特征在于，采用重心法对模糊子集解模糊得到模糊控制器的输出量。The fuzzy adaptive pitch control method for wind turbines capable of suppressing multiple disturbance factors according to claim 6, characterized in that the output of the fuzzy controller is obtained by defuzzifying the fuzzy subsets using the center of gravity method.
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