Offshore wind turbine generator anti-typhoon soft cut-out method and system for controlling parameter planning

Abstract

The invention discloses an offshore wind turbine generator anti-typhoon soft cut-out method and system for controlling parameter planning, and the method employs a layered control framework which comprises a controller and a planner, the planner is composed of a soft cut-out reference curve and a nonlinear model prediction algorithm, and is used for giving control parameters to the controller, the reference curve is kept at a rated value below the cut-out wind speed and follows the hyperbolic attenuation law after exceeding the cut-out wind speed, the wind wheel rotating speed and the generated power reference value are gradually reduced along with increase of the wind speed, and therefore the actual shutdown wind speed of the offshore wind turbine generator is prolonged, and the reference value is compensated through a nonlinear model prediction algorithm according to a control target; by the adoption of the method, the structural load of the offshore wind turbine generator can be reduced, the generated power can be improved under the high-wind-speed condition, the operation reliability and safety of the offshore wind turbine generator can be effectively guaranteed, cost can be reduced, efficiency can be improved, and the method has important engineering application value.

Description

Technical Field

[0001] The present invention belongs to the technical field of fan control, and relates to an anti-typhoon control method for an offshore wind turbine, specifically to an anti-typhoon soft cut-out method and system for an offshore wind turbine unit with control parameter planning. Background Art

[0002] The global offshore wind energy capacity has experienced significant growth and has jumped to one of the fastest-growing renewable energy technologies. Due to its unique operating environment, the operation and maintenance of offshore wind turbine units are difficult, and structural safety is crucial for ensuring its long-term stable operation. For offshore wind turbine unit failures, strong winds are one of the main factors leading to the collapse of offshore wind turbine units. In particular, extreme weather events such as typhoons and tornadoes can not only cause power outages in wind farms but also put offshore wind turbine units in a high-risk state. For wind farms without backup power supplies, this risk is particularly prominent because once a power outage occurs, the operating state of offshore wind turbine units cannot be monitored and adjusted in real time, thus increasing the probability of safety accidents. The existing standard wind-power curve divides wind speed into three regions: cut-in wind speed, rated wind speed, and cut-out wind speed. These wind speed points respectively represent the minimum wind speed at which an offshore wind turbine unit starts generating electricity, the wind speed at which the rated power is reached, and the wind speed at which it cuts out to ensure structural safety. However, in an environment of continuous strong winds, frequent cut-in and cut-out operations of offshore wind turbine units will not only cause stability problems in the power grid but also may have long-term negative impacts on the equipment itself, including reducing its reliability, safety, and overall power generation efficiency. Specifically:

[0003] Under high wind speed conditions, an offshore wind turbine unit needs to balance power generation and structural safety. The active shutdown protection mechanism aims to reduce the risk of structural load overrun, but in complex sea conditions, due to the disappearance of aerodynamic damping caused by shutdown, its safety guarantee effect is limited. At the same time, shutdown will cause the high wind speed resources to not be fully utilized, resulting in power generation loss. Industrial standard controllers frequently cut in and cut out during intermittent strong winds, which not only makes it difficult to effectively utilize transient high wind speeds, resulting in significant energy losses, but also causes the unit structure to bear impact loads, further affecting its stability. In addition, the wind-wave-soil-pile coupling excitation will exacerbate the risk of structural instability, simultaneously stimulating complex dynamic responses of the wind turbine unit in the front-back and lateral directions, and the current industrial standard controllers are difficult to effectively respond to the dynamic responses caused by complex environments, thus exacerbating the instability risk. At the same time, since industrial standard controllers have been widely verified in engineering, any modification to their architecture may introduce system uncertainties and increase the risk of operation failure, thus further limiting the space for optimizing the operation strategy of offshore wind turbine units for typhoon environments.

[0004] Therefore, developing a control strategy for high wind speed sea conditions is the key to improving the operation efficiency and safety of wind turbine units.

[0005] Regarding the design of the control strategy for offshore wind turbines under high wind speeds, CN117846872A proposed a storm control strategy. This strategy constructs a soft cut-out control mechanism that guides the wind turbine to achieve an operating state with increasing wind speeds by presetting the reference values of the wind turbine speed and active power. To further optimize the structural load control during the soft cut-out process, tower active damping and feedforward-feedback are successively applied during the soft cut-out process. However, these advanced control strategies have limitations in the actual application of offshore wind turbines. This is because existing industrial standard controllers have a mature architecture, while the implementation of the above innovative control strategies requires an additional control loop, and such architecture modifications may introduce unforeseen operating risks. Regarding the limitations of the controller architecture, CN118092147A proposed a "planning-control" strategy with a hierarchical architecture, which decouples the planner and the controller. Nonlinear model predictive control is used as the planner, and the overall performance of the controller is significantly enhanced by dynamically optimizing the control parameters. However, this strategy is only applicable to the performance optimization of offshore wind turbines in the normal operating range. Since it does not have a soft cut-out function, when the wind speed exceeds the cut-out value, this strategy will execute an immediate cut-out of the industrial standard controller and cannot provide optimization for the operating performance.

[0006] With the leapfrog development of the installed capacity of offshore wind power, realizing the safe soft cut-out operation of the wind turbine structure under typhoon sea conditions while being compatible with existing standard controllers is of great significance for the reliability and safety of offshore wind resource development. However, this part of the research content is lacking and in urgent need of in-depth research. Summary of the Invention

[0007] The purpose of the present invention is to provide an anti-typhoon soft cut-out method for offshore wind turbines with control parameter planning in view of the deficiencies of the prior art, so as to reduce the structural load and increase the power generation of offshore wind turbines under high wind speed conditions, effectively ensure the reliability and safety of the operation of offshore wind turbines, reduce costs and increase efficiency, and have important engineering application value.

[0008] To solve the above technical problems, the present invention adopts the following technical solutions:

[0009] An anti-typhoon soft cut-out method for offshore wind turbines with control parameter planning includes the following steps:

[0010] Step 1, establish a general hierarchical control framework for fixed and floating offshore wind turbines, including a controller and a planner; the controller is an industrial standard controller, which consists of a blade pitch control system and a generator torque control system; the planner consists of a soft cut-out reference curve and a nonlinear model predictive algorithm, and is used to give control parameters to the controller;

[0011] Step 2: Design the soft cut-out reference curve described in the planner according to the external operating environment of the offshore wind turbine, so as to achieve: when the wind speed exceeds the cut-out wind speed threshold, smoothly reduce the wind turbine speed and power generation power as the average wind speed increases, realize the soft cut-out of the wind turbine speed and power generation power, and expand the operating range of the offshore wind turbine;

[0012] Step 3: Construct a reduced-order dynamic model describing the dynamic response of the offshore wind turbine, including the dynamic model of the drive train and the tower-foundation structure system dynamic models applicable to fixed and floating wind turbines respectively; establish the state equations of the drive train, tower-foundation structure system, and controller of the offshore wind turbine, which associate the state variables with the given control parameters;

[0013] Step 4: Discretize the state equations to realize the multi-step prediction of the operating state of the offshore wind turbine. At the same time, design the described nonlinear model predictive algorithm to compensate the control parameters obtained from the soft cut-out reference curve; iteratively solve the described nonlinear model predictive algorithm based on the multi-step prediction state values obtained by solving the discretized state equations to determine the optimal compensation value of the control parameters.

[0014] In the above technical solution, further, the control parameters are the reference value of the wind turbine speed for the blade pitch control system and the reference value of the power generation power for the generator torque control system ; in the planner:

[0015] The soft cut-out reference curve is designed according to the operating environment and its own operating state of the actual wind turbine, and is used to output the wind turbine speed set value corresponding to the average wind speed and the power generation power set value , which remains at the rated value below the cut-out wind speed and gradually decreases as the wind speed increases after exceeding the cut-out wind speed, thereby extending the actual shutdown wind speed of the offshore wind turbine;

[0016] The nonlinear model predictive algorithm dynamically compensates the set values output by the soft cut-out reference curve for structural damping adjustment and load reduction. Its input is the real-time operating state of the unit and the wind-wave-current environmental parameters, and the core control parameter vector sequence for the next N planning periods is obtained through iterative solution of this model predictive algorithm , ,…, , where the vector , is the compensation value for the wind turbine speed set value , is the compensation value for the power generation power set value ; with the vector The obtained compensation value is used to compensate the set value, and then the control parameter of the controller is obtained. and .

[0017] Further, in step 2, the soft cut-out reference curve is designed by using the hyperbolic soft cut-out method, that is: the average wind speed is calculated by using the sliding window method . When it does not exceed the cut-out wind speed , the set value of the wind turbine rotor speed remains the rated value of the standard wind turbine rotor speed , and the set value of the generated power remains the rated value of the standard generated power ; when it exceeds the cut-out wind speed , the set value of the wind turbine rotor speed changes according to the following formula , and the set value of the generated power changes according to the following formula , where: represents the hyperbolic tangent function; is the set actual shutdown wind speed.

[0018] Further, in step 3, the dynamic model of the drive system adopts the torque balance equation of the single-mass model.

[0019] Further, in step 3, for the fixed offshore wind turbine, the dynamic model of its tower-foundation structure system is constructed as follows: the displacements of the front-back and lateral directions at the top of the tower are modeled as a standard mass-spring-damper system.

[0020] Further, in step 3, for the floating offshore wind turbine, the dynamic model of its tower-foundation structure system adopts the second-order ordinary differential dynamic equation of the control system floating body motion angle decoupled in the pitch and roll directions.

[0021] Further, the dynamic model of the drive system and the dynamic model of the tower-foundation structure system are combined with the control parameters of the controller to construct the state equation, where the wind turbine speed , the structural stability optimization term of the wind turbine (fixed wind turbine , floating wind turbine ), the structural stability optimization term of the wind turbine (fixed wind turbine , floating wind turbine ), the pitch angle and the change amplitude caused by its compensation value , the generator torque and the change caused by its compensation value The change range caused constitutes the state vector of the wind turbine ; Discretize the state equation, and the discretization method is the first-order Taylor expansion method;

[0022] The discretized state prediction equation is:

[0023]

[0024] where is the estimated first-order differential vector of is the state vector of the wind turbine at the planning period, is the state vector of the wind turbine at the planning period; is the control parameter vector at the planning period, is the control parameter vector at the planning period; is the wind and wave environment vector of the wind turbine at the planning period, is the wind speed value at the th planning period, is the wind direction value at the th planning period, is the wind and wave environment vector of the wind turbine at the planning period; , and are respectively , , and matrices, which are the matrices discretized at the planning period matrix, matrix , is matrix, which is composed of variables related to the wind turbine state in the dynamic mathematical model of the wind turbine; is matrix, which is composed of variables related to the control parameters in the dynamic mathematical model of the wind turbine; is matrix, which is composed of variables related to the wind and wave environment of the wind turbine in the dynamic mathematical model of the wind turbine;

[0025] Based on the above discretized state prediction equation, the prediction state vector at the planning period can be obtained by using the Euler forward method ,​

[0026]

[0027] Among them, is the execution period of the planner.

[0028] Furthermore, the non-linear model predictive algorithm is based on the comprehensive optimization objectives of suppressing the deformation of the tower-barrel support structure, adjusting the virtual active structure damping, and restricting the actuator movement, and designs a comprehensive optimization objective function to determine the compensation value and .

[0029] Furthermore, state constraints and input constraints are imposed on the comprehensive optimization objective function, where the state constraints are aimed at preventing overload and operation risks, and the input constraints are used to adjust the change of control parameters to ensure that the compensation value and do not exceed 10% of their respective rated values and . The present invention also provides an electronic device, including:

[0030] One or more processors;

[0031] A memory for storing one or more programs;

[0032] When the one or more programs are executed by the one or more processors, the one or more processors implement a typhoon-resistant soft cut-out method for an offshore wind turbine with control parameter planning as described above.

[0033] The present invention also provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the above-mentioned typhoon-resistant soft cut-out method for an offshore wind turbine with control parameter planning.

[0034] The beneficial effects of the present invention are as follows:

[0035] The typhoon-resistant soft cut-out method for an offshore wind turbine with control parameter planning proposed by the present invention solves the limitations of industrial standard controllers, that is, the problem that the structural load cannot be effectively reduced due to complete cut-out under high wind speed conditions. This strategy adopts a dual-loop architecture: the inner loop uses an industrial standard controller to adjust the blade pitch and generator torque, while the outer loop introduces a planner to optimize the control parameters. Without changing the existing controller architecture, this strategy realizes a progressive cut-out, reduces the structural load and increases the power generation power under high wind speed conditions.

[0036] Specifically, the planner consists of a soft cut-out reference curve for the wind turbine rotor speed corresponding to the average wind speed and the generated power, and a non-linear model predictive algorithm. The reference curve maintains the rated value below the cut-out wind speed and follows the hyperbolic decay law above this threshold, gradually reducing the reference values of the wind turbine rotor speed and the generated power as the wind speed increases, thereby extending the actual cut-out wind speed of the offshore wind turbine. The non-linear model predictive algorithm compensates the reference values according to the control objectives, which include suppressing the deformation speed of the tower, adjusting the virtual active damping, and limiting the actuator actions. This enables structural damping adjustment and load reduction in both the fore-aft and lateral directions.

[0037] The strategy of the present invention can effectively prevent the disappearance of aerodynamic damping caused by the shutdown of the offshore wind turbine, and at the same time can suppress the structural bending moment fluctuations caused by wave loads and increase the generated power beyond the cut-out wind speed. It effectively improves the reliability and safety of the operation of the offshore wind turbine and has important engineering application value for cost reduction and efficiency improvement of the wind turbine in the typhoon sea state environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 is the architecture diagram of the structural safety soft cut-out strategy for the offshore wind turbine based on the control parameter planning of the present invention;

[0039] Figure 2 is the wind speed-power curve diagram of the structural safety soft cut-out strategy for the offshore wind turbine;

[0040] Figure 3 is the time series diagram of the wind-wave external environment condition curve at an average wind speed of 30 m / s;

[0041] Figure 4 is the time series comparison curve diagram of the actuator usage (blade pitch angle);

[0042] Figure 5 is the time series comparison curve diagram of the actuator usage (generator torque);

[0043] Figure 6 is the time series comparison curve diagram of the generated power;

[0044] Figure 7 is the time series comparison curve diagram of the tower bending moment load (fore-aft bending moment load of the tower);

[0045] Figure 8 is the time series comparison curve diagram of the tower bending moment load (lateral bending moment load of the tower);

[0046] Figure 9 is the performance comparison diagram of the actuator usage (blade pitch angle) considering the full wind speed condition;

[0047] Figure 10Performance comparison diagram for the actuator (generator torque) considering all wind speed conditions;

[0048] Figure 11 Performance comparison diagram for the generated power considering all wind speed conditions;

[0049] Figure 12 Performance comparison diagram for the tower bending moment load (front - back tower bending moment load) considering all wind speed conditions;

[0050] Figure 13 Performance comparison diagram for the tower bending moment load (lateral tower bending moment load) considering all wind speed conditions. Detailed implementation manners

[0051] The following further details the specific implementation manners of the present invention in conjunction with the accompanying drawings, so that the technical solutions of the present invention are easier to understand and master.

[0052] The embodiment of the present invention provides an anti - typhoon soft cut - out strategy for a wind turbine generator in the sea with control parameter planning to reduce structural loads and increase generated power under high - wind - speed conditions. First, the control parameters are dynamically adjusted to improve the performance of the wind turbine generator in the sea under high - wind - speed conditions while keeping the existing controller architecture unchanged. This strategy adopts a hierarchical decoupling framework, which consists of a planner and a controller. Among them, the controller uses an industrial standard controller to ensure the basic operation of the wind turbine generator in the sea, and the planner is responsible for calculating the reference control parameters of the wind turbine speed and power output, so as to achieve a progressive cut - out and delay the shutdown wind speed threshold. Secondly, under complex wind - wave coupling conditions, the front - back and lateral structural damping are adjusted to ensure structural safety. This strategy integrates a non - linear model predictive algorithm in the planner, enabling it to dynamically compensate the reference parameters of the wind turbine speed and power output to reduce the aero - hydrodynamic load effects in complex wind - wave environments. This compensation process is driven by three optimization objectives: suppressing the tower deformation speed, adjusting the virtual active structural damping, and limiting the actuator action. Finally, through this strategy, the disappearance of aerodynamic damping caused by the shutdown of the wind turbine generator in the sea can be avoided, and at the same time, the structural bending moment load fluctuations caused by aero - hydrodynamic loads can be suppressed, and the generated power beyond the cut - out wind speed can be increased. It effectively improves the reliability and safety of the operation of the wind turbine generator in the sea, and has important engineering application value for cost reduction and efficiency improvement of the unit facing typhoon sea conditions.

[0053] Specifically, the method includes the following steps:

[0054] Step 1: Establish an anti-typhoon soft cut-out strategy for offshore wind turbines based on control parameter planning, including fixed and floating types. Specifically, it includes a controller and a planner. The controller is an industrial standard controller, composed of a blade pitch control system and a generator torque control system; the planner consists of a soft cut-out reference curve corresponding to the average wind speed and a non-linear model predictive algorithm, which is used to give control parameters (reference value of wind turbine speed, reference value of power generation).

[0055] Step 2: Design the soft cut-out reference curve of the planner according to the external specific operating environment of the offshore wind turbine. When the wind speed exceeds the cut-out wind speed threshold, smoothly reduce the wind turbine speed and power generation as the average wind speed increases, so as to realize the soft cut-out of the wind turbine speed and power generation, and expand the operating range of the offshore wind turbine.

[0056] Step 3: Build a reduced-order dynamic model describing the dynamic response of the offshore wind turbine, including the non-linear dynamic mathematical model of the drive train and the non-linear dynamic mathematical model of the tower-foundation structure system applicable to fixed and floating wind turbines. Establish the state equations of the drive train, tower-foundation structure system, and controller of the offshore wind turbine, which are associated with the given control parameters (reference value of wind turbine speed, reference value of power generation).

[0057] Step 4: Discretize the state equations to realize the multi-step prediction of the operating state of the offshore wind turbine. Design a non-linear model predictive algorithm to compensate for the comprehensive optimization objective function of the soft cut-out reference curve control parameters (reference value of wind turbine speed, reference value of power generation), which is used to suppress the deformation of the tower-support structure, adjust the virtual active damping, and limit the actuator action. Iteratively solve the comprehensive optimization objective function of the non-linear model predictive algorithm in the planner based on the multi-step prediction state values obtained by solving the discretized state equations to determine the optimal compensation values of the control parameters.

[0058] Furthermore, the anti-typhoon soft cut-out strategy and the wind-power theoretical curve of the offshore wind turbine proposed in Step 1 are respectively as Figure 1 and Figure 2 shown, and further include:

[0059] Step 1-1: Use the existing industrial standard controller as the inner loop of the proposed control strategy, and operate the offshore wind turbine through the reference value of the blade pitch angle and the reference value of the generator torque output by the inner loop. One of the inputs of the inner loop is the reference value setting of the wind turbine speed used by the planner for the given blade pitch controller and the reference value setting of the power generation used by the generator torque controller ; Another input is the real-time operating state of the wind turbine and the wind-wave-current environmental parameters, which can be measured by sensors or obtained based on existing equivalent estimation algorithms;

[0060] Step 1-2, for the industrial standard controller of the inner loop, it consists of a blade pitch control system and a generator torque control system. The blade pitch control system uses Gain Scheduled Proportional-Integral (GSPI) to output the blade pitch reference value , to maintain the wind turbine speed running at the set value , for the existing standard controller, its value is set to the rated value of the wind turbine speed . The offshore wind turbine is installed on a floating support structure, and a proportional control loop ( ) needs to be added to the pitch controller to dynamically adjust the structural damping in the pitch direction of the floating platform. The generator torque control system outputs the torque reference value , and adopts a constant power control method above the rated wind speed, and adjusts the torque value to maintain the power at the set value , for the existing standard controller, its value is set to the rated value of the generated power ; The controller is updated and run with a sampling period . For the operating range above the rated value , , the calculation formulas are as follows:

[0061] (1)

[0062] (2)

[0063] Among them, and are the proportional coefficient and integral coefficient of the pitch controller respectively; is the floating body damping gain coefficient, and when the support structure is fixed, take ; is the measured value of the wind turbine speed; is the gear ratio of the drive chain gearbox; is the generator energy conversion efficiency. The dynamic process from the reference value output of the controller to the pitch and torque actuators can be expressed as:

[0064] (3)

[0065] (4)

[0066] Among them, and are the first-order derivatives of the pitch angle and the generator torque with respect to time, respectively; and are the time constants of the blade and the generator, respectively;

[0067] Steps 1-3, the planner serves as the outer loop of, and various algorithms can be used to solve for the optimal control parameters and . To be compatible with the computing performance of the hardware device, the execution period of the planner is set to , which is greater than or equal to the controller period of the industrial controller , defined as: . That is, after the wind turbine executes control cycles of control, the control parameters of the industrial standard controller are updated once.

[0068] In the present invention, the planner consists of a soft cut-out reference curve corresponding to the average wind speed , and a non-linear model predictive algorithm. The soft cut-out reference curve maintains the rated value below the cut-out wind speed , and after exceeding this threshold, the set values of the wind turbine speed and the set value of the generated power are gradually reduced as the wind speed increases, thereby extending the actual cut-out wind speed of the offshore wind turbine. The soft cut-out reference curve is designed based on the actual operating environment and the operating state of the wind turbine itself. The non-linear model predictive algorithm performs dynamic compensation on the set values and , and performs structural damping adjustment and load reduction. The input of the model predictive algorithm is the real-time operating state of the unit measured by the sensor and the wind-wave-current environmental parameters. Through the iterative solution of the model predictive algorithm, a sequence of core control parameter vectors for the next N planner cycles is obtained , ,…, , and the first vector is used as the output, and finally used to obtain the control parameters and of the industrial controller, specifically:

[0069] (5)

[0070] (6)

[0071] Furthermore, the step 2 includes:

[0072] The design of the soft cut-out reference curves for the wind turbine speed and the generated power needs to consider the external operating environments such as wind, waves, and pile-soil of the offshore wind turbine, and the design method is not unique. The present invention provides a hyperbolic soft cut-out method, that is, in a strong wind area, as the average wind speed increases, the hyperbolic soft cut-out smoothly reduces the wind turbine speed and the generated power, thereby expanding the operating range of the offshore wind turbine. Compared with the direct cut-out method, the hyperbolic soft cut-out method has the following advantages: the operation transition of the unit is smoother, the operation time is longer, the structural protection is optimized, and the shutdown loss is reduced. Based on the hyperbolic soft cut-out, the reference value of the rotor speed setting and the reference value of the generated power setting are calculated as follows (the cut-in stage is not considered, and the present invention is only designed for cut-out):

[0073] (7)

[0074] (8)

[0075] wherein, represents the 10-minute average wind speed calculated by the sliding window method; represents the hyperbolic tangent function; is the actual shutdown wind speed set in the soft cut-out method, and this wind speed exceeds the cut-out wind speed value of the standard industrial controller , and this value is usually set to 25 m / s; in addition, to prevent the generator torque from exceeding its rated capacity, the complete shutdown wind speed of the wind turbine speed is set to 1.1 times the corresponding value of the generated power.

[0076] Furthermore, the step 3 includes:

[0077] Step 3-1, the wind turbine speed is affected by the interaction between the aerodynamic torque and the generator torque . Among them, is generated by the aerodynamic thrust , and is actively adjusted by the control system to achieve the power generation target. In order to describe the dynamic characteristics of the drive system, the torque balance equation of the single-mass model is used as follows:

[0078] (9)

[0079] wherein, is the total inertia mass of the rotor, the drive system and the generator; is the gearbox ratio; represents the aerodynamic torque at the wind speed , the wind turbine speed and the pitch angle .

[0080] Step 3-2: For fixed wind turbines, construct a dynamic model of the tower-fixed foundation structure. The displacement at the top of the tower is modeled as a standard mass-spring-damper system. The first-order bending modes in the fore-aft and lateral directions can be approximately expressed as:

[0081] (10)

[0082] (11)

[0083] where, is the fore-aft deformation acceleration of the tower, is the lateral deformation acceleration of the tower; is the fore-aft deformation velocity of the tower, is the lateral deformation velocity of the tower; is the fore-aft deformation displacement of the tower, is the lateral deformation displacement of the tower; 、 and are the mass, structural damping, and stiffness coefficient of the tower respectively; is the thrust on the rotor plane, which is a function of the rotor speed , the blade pitch angle , and the wind speed at the hub ; is the height of the tower;

[0084] For floating wind turbines, establish a dynamic model of the tower-floating foundation structure, and adopt a control system with decoupling in the pitch and roll directions for the second-order ordinary differential dynamic equation of the floating body motion angle:

[0085] (12)

[0086] (13)

[0087] where, 、 、 are the moment of inertia, equivalent damping, and restoring coefficient of the floating body platform in the pitch direction respectively, 、 、 are the moment of inertia, equivalent damping, and restoring coefficient of the floating body platform in the roll direction respectively; 、 、 and 、 、 are the angular acceleration, angular velocity, and angle of the floating body platform in the pitch and roll directions respectively; and The moments caused by waves in the pitch and roll directions respectively; and The equivalent thrusts received by the platform in the pitch and roll directions respectively.

[0088] Step 3-3: Construct a state equation between the control parameters and the state of the wind turbine. Convert the dynamic models of the drive train, the tower-support structure dynamics model, and the industrial controller model into state equations, which are expressed as:

[0089] (14)

[0090] Wherein, is the wind turbine state vector, and are the blade pitch angle and the generator torque respectively, and are the change amplitudes caused by the compensation values and respectively; and are the structural stability optimization terms (for fixed wind turbines , floating wind turbines ); is the first derivative of with respect to time; and ; is the wind turbine wind-wave environment parameter vector; is matrix, which is a matrix composed of variables related to the wind turbine state in the wind turbine dynamic mathematical model; is matrix, which is a matrix composed of variables related to the control parameters in the wind turbine dynamic mathematical model; is matrix, which is a matrix composed of variables related to the wind turbine wind-wave environment in the wind turbine dynamic mathematical model.

[0091] Furthermore, the step 4 further includes:

[0092] Step 4-1: Convert the state prediction equation in step 3-3 from continuous time state to discrete time state. The discrete method adopts the first-order Taylor expansion, and the discrete period is the planner operation period , and the discretized state prediction equation is expressed as:

[0093] (15)

[0094] Among them, is the estimated first-order differential vector; is the wind turbine state vector of the th planning period, is the wind turbine state vector of the th planning period; is the wind turbine wind and wave environment vector of the th planning period, , and are respectively , , and matrices, which are the matrices discretized in the th planning period, matrix .

[0095] Based on the Euler forward method and combined with formula (15), the predicted state vector of the future th

[0096] (16)

[0097] Among them, represents the predicted state vector of the first step size. In the multi-step prediction process, the th step size predicted state is used to update the matrices in formula (15) and further used to predict the th

[0098] Step 4-2, within a specific planning period , the nonlinear model predictive algorithm is based on suppressing the deformation of the tower-bar support structure (the structural stability term of the th prediction step size) and adjusting the virtual active damping ( and , and are the virtual active damping gains of blade pitch and generator torque respectively) and restricting the actuator actions ( and to determine the compensation value based on the comprehensive optimization objective of ( and . The design of the optimizer's objective function is not unique and can be defined as shown in the following example:

[0099] (17)

[0100] where is the value of the cost function; , , , , , are weight factors, and the values of the weight factors are tuned based on the real-time external environment characteristics according to the Pareto optimality theory; and are the maximum allowable values within the safe operating range; and are the maximum values of the motion rates of the pitch and torque actuators respectively; is the contribution ratio of the additional control variable to the actuator motion.

[0101] Step 4-3: Since the state variables and input variables are inherently related through the state space model, state and input constraints need to be imposed to ensure safe operation:

[0102] (18)

[0103] (19)

[0104] (20)

[0105] (21)

[0106] (22)

[0107] (23)

[0108] where the state constraints are aimed at preventing overload and operation risks: the predicted value of the generator torque at the th time step is restricted to within 110% of the torque rating , and its predicted rate of change needs to be less than to reduce the overload risk; the predicted value of the blade pitch at the th time step shall not be greater than the maximum value of the blade pitch angle , and its predicted rate of change is restricted to To prevent aerodynamic stall. The input constraints are mainly used to regulate the changes of control parameters to ensure that the compensation variables and do not exceed 10% of their respective rated values and .

[0109] Step 4-4: Based on the state prediction model (15-16), optimization objectives and constraints (17-23) of the offshore wind turbine, use solution algorithms such as quadratic programming method, exhaustive method, gradient descent method, intelligent optimization algorithm, etc. to iteratively solve the objective function, and the N control parameter vectors of the planning period obtained by iterative solution , ,…, to obtain the minimum cost function value . Take the first element of the sequence as the set value of the wind turbine speed and the dynamic compensation value of the set value of the generated power .

[0110] Application example

[0111] Apply the anti-typhoon soft cut-out method for the offshore wind turbine with control parameter planning to the DTU-10MW fixed wind turbine. A time series diagram of the wind-wave environment exceeding the cut-out wind speed of the offshore wind turbine is set as Figure 3 shown, and the specific parameters are: Class A turbulent wind of 30 m / s according to the IEC standard, the peak wave height is 4.46 m, and the wave period is 8.86 s.

[0112] Figures 4 to 8 shows the time series diagram comparison of the performance of the industrial standard controller and the strategy proposed in the present invention in terms of actuator use, generated power, and tower barrel bending moment load under the Figure 3 working conditions: Figure 4 shows the time series diagram comparison of the blade pitch angle above the cut-out wind speed. The pitch angle value of the standard industrial controller remains at 90 deg, while the pitch angle of the proposed strategy fluctuates in the range of [20, 40] deg; Figure 5 shows the time series diagram comparison of the generator torque above the cut-out wind speed. The torque value of the standard industrial controller is 0 kNm, while the torque value of the proposed strategy is 84% of the rated torque; Figure 6 shows the time series diagram comparison of the generated power above the cut-out wind speed. The generated power of the standard industrial controller is 0 kW, while the generated power of the proposed strategy is about 80% of the rated power; Figure 7 shows the time series diagram comparison of the front and rear bending moment loads of the tower barrel above the cut-out wind speed. Due to the loss of aerodynamic damping, the standard industrial controller significantly exacerbates the bending moment fluctuation under the hydrodynamic action;Figure 8 It shows the comparison of the time - series diagrams of the lateral bending moment loads of the tower above the cut - out wind speed. Similar to the cases of the front - to - back bending moment loads, the strategy proposed by the present invention effectively suppresses the structural load fluctuations by adjusting the structural damping.

[0113] Figures 9 to 13 It shows the performance comparison of the industrial standard controller and the strategy proposed by the present invention in terms of actuator usage, power generation, and tower bending moment loads under the working conditions where the average wind speed ranges from 2 m / s to 40 m / s: Figure 9 It shows the performance comparison of the blade pitch angles under the full - wind - speed working conditions. In the normal operating range, the differences in the average value and standard deviation of the pitch actuator usage between the two strategies are relatively small. In the cut - out range, as the average wind speed increases, the average pitch value gradually approaches 90 deg, and the standard deviation is within a reasonable range; Figure 10 It shows the performance comparison of the generator torques under the full - wind - speed working conditions. In the normal operating range, the differences in the average value and standard deviation of the torque actuator usage between the two strategies are relatively small. In the cut - out range, as the average wind speed increases, the average torque value gradually approaches 0 kNm, and the standard deviation is within a reasonable range; Figure 11 It shows the performance comparison of the power generation under the full - wind - speed working conditions. In the normal operating range, the power generation characteristics of the two strategies are similar, with small differences in the average value and standard deviation. In the cut - out range, the strategy of the present invention shows significant advantages, not only effectively improving the average power generation, but also controlling the standard deviation within an acceptable range; Figure 12 It shows the performance comparison of the front - to - back bending moment loads of the tower under the full - wind - speed working conditions. In the normal operating range, especially under the working conditions above the rated wind speed, the strategy of the present invention has lower front - to - back structural fatigue damage compared with the industrial standard control, and the difference in the average bending moment is not obvious. In the cut - out range, compared with the industrial standard control, it has a higher average bending moment, but due to the increased structural damping, the front - to - back fatigue damage is effectively reduced; Figure 13 It shows the performance comparison of the lateral bending moment loads of the tower under the full - wind - speed working conditions. In the normal operating range, the strategy of the present invention has lower lateral structural fatigue damage compared with the industrial standard control, and the difference in the average bending moment is not obvious. In the cut - out range, compared with the industrial standard control, it has a higher average bending moment, but due to the increased structural damping, the lateral fatigue damage is effectively reduced.

[0114] The above are just typical examples of the present invention. In addition, the present invention can also have many other specific implementation manners. Any technical solutions formed by equivalent replacement or equivalent transformation fall within the scope protected by the present invention.

[0115] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, commodity or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, commodity or device comprising said element.

[0116] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0117] Although the present invention has been described above with reference to various embodiments, it should be understood that many changes and modifications can be made without departing from the scope of the present invention. Therefore, it is intended that the above detailed description be regarded as illustrative rather than restrictive, and it should be understood that the claims (including all equivalents) are intended to define the spirit and scope of the present invention. These embodiments should be understood as only illustrative of the present invention and not limiting the scope of protection of the present invention. After reading the content described in the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent changes and modifications also fall within the scope defined by the claims of the present invention.

Claims

1. A method for soft cut-out of offshore wind turbines against typhoons with control parameter planning, characterized in that: The steps include: Step 1, establishing a general hierarchical control framework for fixed and floating offshore wind turbines, including a controller and a planner; the controller is an industrial standard controller, which is composed of a blade pitch control system and a generator torque control system; the planner is composed of a soft cut-out reference curve and a nonlinear model prediction algorithm, which is used to give control parameters to the controller; Step 2, according to the external operating environment of the offshore wind turbine, design the soft cut-out reference curve described in the planner to achieve: when the wind speed exceeds the cut-out wind speed threshold, the wind rotor speed and power generation are steadily reduced as the average wind speed increases, so as to achieve soft cut-out of the wind rotor speed and power generation and expand the operating range of the offshore wind turbine; Step 3, constructing a reduced-order dynamic model describing the dynamic response of the offshore wind turbine, including a dynamic model of the transmission system and a tower-foundation system dynamic model applicable to fixed and floating wind turbines, respectively; establishing state equations associating the state variables of the offshore wind turbine transmission system, the tower-foundation system, and the controller with the given control parameters; Step 4, discretizing the state equation to realize multi-step prediction of the operating state of the offshore wind turbine, and designing the nonlinear model prediction algorithm to compensate for the control parameters obtained by the soft cut-out reference curve; The nonlinear model prediction algorithm is iteratively solved based on the multi-step predicted state value solved by the discretized state equation to determine the optimal compensation value of the control parameter.

2. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 1, characterized in that: The control parameter is the rotor speed reference value used in the blade pitch control system , and a power generation reference value for the generator torque control system ; In the planner: The soft cut-out reference curve is designed according to the actual operating environment and operating status of the wind turbine generator set and is used to output the rotor speed setting value corresponding to the average wind speed. and power generation setting value , which is at the cut-out wind speed The rated value is maintained below the cut-out wind speed, and the cut-out wind speed is gradually reduced as the wind speed increases after the cut-out wind speed is exceeded, thereby extending the actual shutdown wind speed of the offshore wind turbine; The nonlinear model prediction algorithm dynamically compensates the set value output by the soft cut-out reference curve to adjust the structural damping and reduce the load. Its input is the real-time operating status of the unit and the wind-wave-current environmental parameters. The core control parameter vector sequence of the next N planning cycles is obtained by iterative solution of the model prediction algorithm. , ,…, , where the vector , The wind rotor speed setting value The compensation value, To set the power generation value The compensation value of The control parameters of the controller are obtained by compensating the set value with the obtained compensation value. and .

3. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 2, characterized in that: In step 2, the design of the soft cut-out reference curve adopts the hyperbolic soft cut-out method, that is, the average wind speed is calculated using the sliding window method. , before it exceeds the cut-out wind speed When the wind wheel speed setting value Maintain standard rotor speed rating , power generation setting value Maintain standard power rating ; When it exceeds the cut-out wind speed When the wind wheel speed setting value Press the button to change , power generation setting value Press the button to change ,in: represents the hyperbolic tangent function; The actual shutdown wind speed is set.

4. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 2, characterized in that: In step 3, the dynamic model of the transmission system adopts the torque balance equation of the single mass model.

5. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 2, characterized in that: In step 3, for a fixed offshore wind turbine, the tower-foundation structure system dynamics model is constructed in the following manner: the fore-aft and lateral displacements of the tower top are modeled as a standard mass-spring-damper system.

6. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 2, characterized in that: In step 3, for floating offshore wind turbines, the tower-foundation structure system dynamics model adopts a second-order ordinary differential dynamics equation that controls the motion angle of the floating body of the control system with decoupling in pitch and roll directions.

7. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 2, characterized in that: The dynamic model of the transmission system and the tower-foundation system dynamic model are combined with the control parameters of the controller to construct the state equation, in which the wind turbine speed is , Wind turbine structure stability optimization items , Wind turbine structure stability optimization items , Pitch Angle Its compensation value The magnitude of the change caused , generator torque Its compensation value The magnitude of the change caused The wind turbine state vector ; Discretize the state equation using a first-order Tate expansion method; The discretized state prediction equation is: in, for The estimated first-order differential vector of ; For the The wind turbine state vector of the planning period, For the Wind turbine state vector during the planning period; For the The control parameter vector of the planning cycle, For the Control parameter vector of the planning cycle; For the Wind turbine wind and wave environment vector for the planning period, For the Wind speed value for the planning period, For the Wind direction value for a planning period, For the Wind turbine wind and wave environment vector for the planning period; , and They are Matrix for discretization of planning period ,matrix and matrix , A matrix composed of variables related to the state of the wind turbine generator set in the dynamic mathematical model of the wind turbine generator set; is a matrix composed of variables related to control parameters in the dynamic mathematical model of the wind turbine generator set; A matrix composed of variables related to the wind and wave environment of the wind turbine in the dynamic mathematical model of the wind turbine; Based on the above discretized state prediction equation, the Euler forward method can be used to obtain the The predicted state vector of the planning period , in, The execution cycle of the planner.

8. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 2, characterized in that: The nonlinear model prediction algorithm is based on the comprehensive optimization objectives of suppressing the deformation of the tower-support structure, adjusting the virtual active structural damping, and limiting the actuator action, and designs a comprehensive optimization objective function to determine the compensation value. and .

9. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 8, characterized in that: State constraints and input constraints are imposed on the comprehensive optimization objective function, wherein the state constraints are intended to prevent overload and operation risks, and the input constraints are used to adjust the changes in control parameters to ensure the compensation value and Do not exceed their respective rated values and 10% of.

10. A typhoon-resistant soft cut-out system for offshore wind turbines with control parameter planning, characterized in that: Used to implement the method according to any one of claims 1 to 9.

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