Typhoon-resistant soft cut-out method and system for offshore wind turbines based on control parameter planning

Abstract

The present invention discloses a typhoon-resistant soft cut-out method and system for offshore wind turbines with control parameter planning. The method adopts a hierarchical control framework, including a controller and a planner. The planner consists of a soft cut-out reference curve and a nonlinear model prediction algorithm, which is used to give control parameters to the controller. The reference curve maintains a rated value below the cut-out wind speed, and follows a hyperbolic attenuation law after exceeding the cut-out wind speed. As the wind speed increases, the wind rotor speed and the power generation reference value are gradually reduced, thereby extending the actual shutdown wind speed of the offshore wind turbine. The nonlinear model prediction algorithm compensates the reference value according to the control target. The method of the present invention can reduce the structural load of the offshore wind turbine and increase the power generation under high wind speed conditions, effectively ensure the reliability and safety of the operation of the offshore wind turbine, reduce costs and increase efficiency, and has important engineering application value.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind turbine control, and relates to a typhoon-resistant control method for offshore wind turbines, and in particular to a typhoon-resistant soft cut-out method and system for offshore wind turbines with control parameter planning. Background Art

[0002] Global offshore wind energy capacity has experienced significant growth, becoming one of the fastest-growing renewable energy technologies. Due to their unique operating environment, offshore wind turbines present significant challenges in operation and maintenance, making structural safety crucial for ensuring their long-term stable operation. Strong winds are a major factor in offshore wind turbine failures. Extreme weather events, such as typhoons and tornadoes, can not only disrupt power supply to wind farms but also place offshore wind turbines at high risk. This risk is particularly acute for wind farms without backup power sources, as a power outage prevents real-time monitoring and adjustment of offshore wind turbine operating conditions, increasing the likelihood of safety incidents. Existing standard wind-power curves divide wind speeds into three zones: cut-in speed, rated speed, and cut-out speed. These wind speed points represent the minimum wind speed at which offshore wind turbines begin generating power, the wind speed at which they reach rated power, and the wind speed at which they are cut out to ensure structural safety. However, in an environment with sustained strong winds, frequent switching on and off of offshore wind turbines not only causes grid stability issues but can also have long-term negative impacts on the equipment itself, including reduced reliability, safety, and overall power generation efficiency. Specifically:

[0003] Under high wind speed conditions, offshore wind turbines must strike a balance between power generation and structural safety. Active shutdown protection mechanisms are designed to mitigate the risk of excessive structural loads, but in complex sea conditions, their effectiveness is limited due to the loss of aerodynamic damping caused by shutdown. Furthermore, shutdowns can prevent the full utilization of high wind speed resources, resulting in power loss. Industry-standard controllers frequently switch on and off during intermittent periods of strong winds, hindering the effective utilization of transient high wind speeds and causing significant energy losses. They also subject the turbine structure to shock loads, further compromising its stability. Furthermore, coupled wind-wave-soil-pile excitation exacerbates the risk of structural instability, simultaneously triggering complex dynamic responses in the turbine's fore-aft and lateral directions. Current industry-standard controllers struggle to effectively address these dynamic responses, exacerbating the risk of instability. Furthermore, since industry-standard controllers have been extensively validated in engineering, any modifications to their architecture could introduce system uncertainties and increase the risk of operational failure, further limiting the scope for optimizing offshore wind turbine operating strategies for typhoon conditions.

[0004] Therefore, developing control strategies for high wind speed sea conditions is the key to improving the operating efficiency and safety of wind turbines.

[0005] To design control strategies for offshore wind turbines operating at high wind speeds, CN117846872A proposed a storm control strategy. This strategy, by presetting reference values for rotor speed and active power, establishes a soft-cut-out control mechanism that guides the wind turbine's operating state as wind speed increases. To further optimize structural load control during the soft-cut-out process, active tower damping and feedforward-feedback control have been successively applied. However, these advanced control strategies have limitations in the practical application of offshore wind turbines. This is because existing industry-standard controllers have mature architectures, while the implementation of these innovative control strategies requires additional control loops. This architectural modification may introduce unforeseen operational risks. To address the limitations of the controller architecture, CN118092147A proposed a hierarchical "planning-control" strategy that decouples the planner and controller. This strategy uses nonlinear model predictive control as the planner and significantly enhances the overall controller performance by dynamically optimizing 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, the strategy will immediately execute the industrial standard controller to cut out, which cannot provide optimization for operating performance.

[0006] With the rapid growth of offshore wind power installed capacity, achieving safe soft-cutout operation of wind turbine structures in typhoon-like sea conditions while maintaining compatibility with existing standard controllers is crucial for the reliability and safety of offshore wind resource development. However, this area is understudied and urgently requires further research. Summary of the Invention

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

[0008] In order to solve the above technical problems, the present invention adopts the following technical solutions:

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

[0010] Step 1: Establish a universal hierarchical control framework for fixed and floating offshore wind turbines, including a controller and a planner. The controller is an industry-standard controller consisting of a blade pitch control system and a generator torque control system. The planner consists of a soft-cutout reference curve and a nonlinear model prediction algorithm to provide control parameters to the controller.

[0011] Step 2: Based on the external operating environment of the offshore wind turbine, a soft cut-out reference curve is designed in the planner to achieve the following: when the wind speed exceeds the cut-out wind speed threshold, the rotor speed and power generation are steadily reduced as the average wind speed increases, thereby achieving soft cut-out of the rotor speed and power generation and expanding 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 a dynamic model of the transmission system and a tower-foundation system dynamic model applicable to fixed and floating wind turbines, respectively; establish state equations associating the state variables of the offshore wind turbine transmission system, tower-foundation system, and controller with the given control parameters;

[0013] Step 4: discretize the state equation to realize multi-step prediction of the operating state of the offshore wind turbine, and at the same time design the nonlinear model prediction algorithm to compensate the control parameters obtained by the soft cut-out reference curve; iteratively solve the nonlinear model prediction algorithm based on the multi-step predicted state value solved by the discretized state equation to determine the optimal compensation value of the control parameter.

[0014] In the above technical solution, further, the control parameter is a wind wheel speed reference value used for the blade pitch control system , and a power generation reference value for the generator torque control system ; In the planner:

[0015] 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 after exceeding the cut-out wind speed, the cut-out wind speed is gradually reduced as the wind speed increases, thereby extending the actual shutdown wind speed of the offshore wind turbine;

[0016] 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 for the next N planning cycles is obtained through iterative solution of the model prediction algorithm. , ,…, , where the vector , The wind wheel speed setting value The compensation value, Set the power generation value Compensation value of vector The control parameters of the controller are obtained by compensating the set value with the obtained compensation value. and .

[0017] Furthermore, in step 2, the design of the soft cut-out reference curve adopts a hyperbola soft cut-out method, that is, the average wind speed is calculated using a 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 generation rating ; When it exceeds the cut-out wind speed When the wind wheel speed setting value Press the formula to change , power generation setting value Press the formula to change ,in: represents the hyperbolic tangent function; The actual shutdown wind speed is set.

[0018] Furthermore, in step 3, the dynamic model of the transmission system adopts the torque balance equation of the single mass model.

[0019] Furthermore, 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.

[0020] Furthermore, in step 3, for the floating offshore wind turbine, the tower-foundation structure system dynamics model thereof adopts a second-order ordinary differential dynamics equation for controlling the motion angle of the floating body of the system with decoupling in the pitch and roll directions.

[0021] Furthermore, 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 (Fixed wind turbines , floating wind turbines ), wind turbine structure stability optimization items (Fixed wind turbines , floating wind turbines ), pitch angle and its compensation value The magnitude of the change caused , generator torque and its compensation value The magnitude of the change caused Construct the wind turbine state vector ; Discretize the state equation using a first-order Tate expansion method;

[0022] The discretized state prediction equation is:

[0023]

[0024] 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 during 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 vectors during the planning period; 、 and They are 、 ,and The matrix is Matrix for discretization of planning period ,matrix and matrix , for A matrix is a matrix composed of variables related to the state of the wind turbine in the wind turbine dynamics mathematical model; for A matrix is a matrix composed of variables related to control parameters in the wind turbine dynamics mathematical model; for The matrix is a matrix composed of variables related to the wind turbine wind and wave environment in the wind turbine dynamics mathematical model;

[0025] 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 ,

[0026]

[0027] in, The execution cycle of the planner.

[0028] Furthermore, 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 structure damping and limiting the actuator action, 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, 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 that the compensation value and Do not exceed their respective rated values and The present invention also provides an electronic device, comprising:

[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 the above-mentioned method for soft switching out of offshore wind turbines against typhoons with control parameter planning.

[0033] The present invention also provides a computer-readable storage medium having computer instructions stored thereon, wherein the computer instructions are used to enable a computer to execute the above-mentioned typhoon-resistant soft cut-out method for offshore wind turbines with control parameter planning.

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

[0035] The proposed method for soft typhoon-resistant offshore wind turbine cutout, using control parameter planning, addresses the limitations of industry-standard controllers, which often fail to effectively reduce structural loads due to full cutout in high wind speeds. This strategy employs a dual-loop architecture: the inner loop uses an industry-standard controller to regulate blade pitch and generator torque, while the outer loop incorporates a planner to optimize control parameters. Without changing the existing controller architecture, this strategy achieves progressive cutout, reducing structural loads and increasing power generation in high wind speeds.

[0036] Specifically, the planner consists of a soft cut-out reference curve for rotor speed and power generation corresponding to average wind speed, as well as a nonlinear model prediction algorithm. The reference curve maintains its rated value below the cut-out wind speed. Beyond this threshold, it follows a hyperbolic attenuation law, gradually reducing the rotor speed and power generation reference values as wind speed increases, thereby extending the actual shutdown wind speed of the offshore wind turbine. The nonlinear model prediction algorithm compensates the reference value based on control objectives, including suppressing tower deformation speed, adjusting virtual active damping, and limiting actuator action. This allows for structural damping adjustment and load reduction in both the fore-aft and lateral directions.

[0037] This strategy effectively prevents the loss of aerodynamic damping caused by offshore wind turbine shutdown, suppresses structural bending moment fluctuations caused by wave loads, and increases power generation beyond cut-out wind speeds. This effectively improves the reliability and safety of offshore wind turbine operation and has significant engineering application value for reducing costs and increasing efficiency in typhoon-resistant environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a diagram of the structure safety soft cut-out strategy for offshore wind turbines based on control parameter planning according to the present invention;

[0039] Figure 2 Wind speed-power curve for safe soft cut-out strategy of offshore wind turbine structure;

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

[0041] Figure 4 A timing diagram of the comparison curves used for the actuator (blade pitch angle);

[0042] Figure 5 A timing diagram of the comparison curve used for the actuator (generator torque);

[0043] Figure 6 It is a timing diagram of the comparison curve of the power generation;

[0044] Figure 7 It is a time series diagram of the comparison curve of the tower bending moment load (the front-back bending moment load of the tower);

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

[0046] Figure 9 This is a performance comparison chart considering the use of actuators (blade pitch angle) under all wind speed conditions;

[0047] Figure 10This is a performance comparison chart considering the use of actuators (generator torque) under all wind speed conditions;

[0048] Figure 11 This is a performance comparison chart of power generation under all wind speed conditions;

[0049] Figure 12 This is a performance comparison chart considering tower bending moment load (forward and backward bending moment load of the tower) under full wind speed conditions;

[0050] Figure 13 This is a performance comparison chart considering the tower bending moment load (tower lateral bending moment load) under full wind speed conditions. DETAILED DESCRIPTION

[0051] The specific embodiments of the present invention are further described below in conjunction with the accompanying drawings to make the technical solutions of the present invention easier to understand and grasp.

[0052] An embodiment of the present invention provides a typhoon-resistant soft cut-out strategy for offshore wind turbines with control parameter planning, so as to achieve structural load reduction and power generation improvement under high wind speed conditions. First, the control parameters are dynamically adjusted to improve the performance of offshore wind turbines under high wind speed conditions, while keeping the existing controller architecture unchanged. The strategy adopts a hierarchical decoupling framework, which consists of a planner and a controller. Among them, the controller adopts an industrial standard controller to ensure the basic operation of the offshore wind turbine, while the planner is responsible for calculating the reference control parameters of the wind rotor speed and power output, so as to achieve progressive cut-out and delay the shutdown wind speed threshold; secondly, under complex wind and wave coupling conditions, the forward and backward and lateral structural damping are adjusted to ensure structural safety. The strategy integrates a nonlinear model prediction algorithm in the planner, so that it can dynamically compensate for the reference parameters of the wind rotor speed and power output to reduce the aerodynamic-hydrodynamic load effects in complex wind and wave environments. This compensation process is driven by three optimization objectives: suppressing tower deformation velocity, adjusting virtual active structural damping, and limiting actuator motion. Finally, this strategy prevents the loss of aerodynamic damping caused by offshore wind turbine shutdown, while simultaneously suppressing fluctuations in structural bending moment loads caused by aerodynamic and hydrodynamic loads and increasing power generation beyond cut-out wind speeds. This effectively improves the operational reliability and safety of offshore wind turbines and has significant engineering application value for reducing costs and increasing efficiency in typhoon-resistant environments.

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

[0054] Step 1: Establish a typhoon-resistant soft cut-out strategy for both fixed and floating offshore wind turbines based on control parameter planning. This strategy involves a controller and a planner. The controller is an industry-standard controller comprised of a blade pitch control system and a generator torque control system. The planner comprises a soft cut-out reference curve corresponding to average wind speed and a nonlinear model prediction algorithm for given control parameters (rotor speed reference and power generation reference).

[0055] Step 2: Design a soft cut-out reference curve for the planner based on the specific external operating environment of the offshore wind turbine. When the wind speed exceeds the cut-out wind speed threshold, the rotor speed and power generation are steadily reduced as the average wind speed increases, thereby achieving soft cut-out of the rotor speed and power generation, thereby expanding the operating range of the offshore wind turbine.

[0056] Step 3: Construct a reduced-order dynamic model to describe the dynamic response of the offshore wind turbine, including a nonlinear dynamic mathematical model of the transmission system and a nonlinear dynamic mathematical model of the tower-foundation system applicable to both fixed and floating wind turbines. State equations are established to relate the state variables of the offshore wind turbine transmission system, tower-foundation system, and controller to the given control parameters (rotor speed reference value, generated power reference value).

[0057] Step 4: Discretize the state equation to achieve multi-step prediction of the offshore wind turbine's operating status. A nonlinear model prediction algorithm is designed to compensate for the comprehensive optimization objective function of the soft-cutout reference curve control parameters (rotor speed reference value, power generation reference value). This objective function is used to suppress tower-support structure deformation, adjust virtual active damping, and limit actuator motion. Based on the multi-step predicted state values obtained from the discretized state equation, the comprehensive optimization objective function of the nonlinear model prediction algorithm in the planner is iteratively solved to determine the optimal compensation values for the control parameters.

[0058] Furthermore, the typhoon-resistant soft cut-out strategy and wind-power theoretical curve of the offshore wind turbine proposed in step 1 are respectively as follows: Figure 1 and Figure 2 As shown, further comprising:

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

[0060] Step 1-2, for the inner loop of the industrial standard controller, it is composed of the blade pitch control system and the 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 wheel speed Run at set value For existing standard controllers, the value is set to the rated speed of the wind wheel 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 of the floating platform in the pitch direction. The generator torque control system outputs a torque reference value , above the rated wind speed, a constant power control mode is used, and the power is maintained at the set value by adjusting the torque value. , for existing standard controllers, its value is set to the rated power of the power generation ; The controller uses a sampling period For the working range above the rated value, 、 The calculation formula is as follows:

[0061] (1)

[0062] (2)

[0063] in, and are the proportional coefficient and integral coefficient of the pitch controller respectively; is the damping gain coefficient of the floating body, which is taken when the supporting structure is fixed. ; is the measured value of the wind wheel speed; is the transmission chain gearbox ratio; is the energy conversion efficiency of the generator. The dynamic process from the reference value output of the controller to the pitch and torque actuator can be expressed as:

[0064] (3)

[0065] (4)

[0066] in, and are the first-order derivatives of pitch angle and generator torque with respect to time, respectively; and are the time constants of blades and generators, respectively;

[0067] Steps 1-3, the planner is the outer loop, and a variety of algorithms can be used to solve the optimal control parameters and In order to be compatible with the computing performance of the hardware device, the execution cycle of the planner is set to , this value is greater than or equal to the controller cycle of the industrial controller , defined as: That is, the wind turbine performs After a control cycle, the control parameters of the industrial standard controller are updated.

[0068] In the present invention, the planner is based on the average wind speed corresponding to 、 The soft cut-out reference curve and nonlinear model prediction algorithm are composed of the soft cut-out reference curve. The rated value is maintained below the threshold, and the rotor speed setting value is gradually reduced as the wind speed increases after exceeding the threshold. and power generation setting value , thereby extending the actual shutdown wind speed of the offshore wind turbine. The soft cut-out reference curve is designed based on the actual operating environment and operating status of the wind turbine. The nonlinear model prediction algorithm dynamically compensates the set value. and , to adjust the structural damping and reduce the load. The input of the model prediction algorithm is the real-time operating status of the unit and the wind-wave-current environmental parameters measured by the sensor. The core control parameter vector sequence of the next N planner cycles is obtained through the iterative solution of the model prediction algorithm. , ,…, , and the first vector As output, it is finally used to obtain the control parameters of the industrial controller and , specifically:

[0069] (5)

[0070] (6)

[0071] Furthermore, the step 2 includes:

[0072] The design of the soft cut-out reference curve for the rotor speed and power generation needs to take into account the external operating environment of the offshore wind turbine, such as wind, waves, piles and soil, and there is no unique design method. The present invention provides a hyperbola soft cut-out method, that is, in strong wind areas, the hyperbola soft cut-out steadily reduces the rotor speed and power generation as the average wind speed increases, thereby expanding the operating range of the offshore wind turbine. Compared with the direct cut-out method, the hyperbola soft cut-out method has the following advantages: smoother unit operation transition, longer operation time, optimized structural protection and reduced downtime losses. Rotor speed setting reference value based on hyperbola soft cut-out and power generation setting reference value The calculation formula is as follows (the cut-in stage is not considered, and the present invention is only designed for the cut-out):

[0073] (7)

[0074] (8)

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

[0076] Furthermore, the step 3 includes:

[0077] Step 3-1, wind wheel speed Aerodynamic torque and generator torque Among them, By pneumatic thrust Produced, and The control system actively adjusts the torque to achieve the power generation target. In order to describe the dynamic characteristics of the transmission system, the torque balance equation of the single mass model is used, as shown below:

[0078] (9)

[0079] in, is the total inertial mass of the rotor, transmission system and generator; is the gearbox ratio; Indicates wind speed , wind wheel speed and pitch angle Pneumatic torque under .

[0080] In step 3-2, for fixed wind turbines, a dynamic model of the tower-fixed foundation structure is constructed. The displacement of the tower top 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] in, is the tower's forward and backward deformation acceleration, is the lateral deformation acceleration of the tower; is the tower's forward and backward deformation velocity, is the lateral deformation velocity of the tower; is the front-to-back deformation displacement of the tower, is the lateral deformation displacement of the tower; 、 and are the mass, structural damping and stiffness coefficients of the tower respectively; The thrust on the rotor surface is related to the rotor speed. , blade pitch angle , wind speed at hub function; is the height of the tower;

[0084] For floating wind turbines, a dynamic model of the tower-floating foundation structure is established, and the second-order ordinary differential dynamic equation of the control system's floating body motion angle is used with decoupling of pitch and roll directions:

[0085] (12)

[0086] (13)

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

[0088] Step 3-3, construct the state equation between the control parameters and the state of the wind turbine, and convert the dynamic model of the transmission system, the tower-support structure dynamic model, and the industrial controller model into the state equation, which is expressed as:

[0089] (14)

[0090] in, is the wind turbine state vector, and are blade pitch angle and generator torque respectively, and The compensation values are and The magnitude of the change caused, and For structural stability optimization (fixed wind turbine , floating wind turbines ); yes First derivative with respect to time; is the control parameter vector, which is used to compensate and ; is the wind turbine wind and wave environment parameter vector; for A matrix is a matrix composed of variables related to the state of the wind turbine in the wind turbine dynamics mathematical model; for A matrix is a matrix composed of variables related to control parameters in the wind turbine dynamics mathematical model; for The matrix is a matrix composed of variables related to the wind turbine wind and wave environment in the wind turbine dynamics mathematical model.

[0091] Furthermore, the step 4 further comprises:

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

[0093] (15)

[0094] 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 during the planning period, For the Wind turbine wind and wave environment vectors during the planning period; 、 and They are 、 ,and The matrix is Matrix for discretization of planning period ,matrix and matrix .

[0095] Based on the Euler forward method and combined with formula (15), the future The predicted state vector of the planning period , its formula can be expressed as:

[0096] (16)

[0097] in, represents the predicted state vector of the first step. In the multi-step prediction process, Step-length prediction state Used to update the matrix in formula (15) and further used to predict the Step-length prediction state .

[0098] Step 4-2, in a specific planning cycle The nonlinear model prediction algorithm is based on suppressing the deformation of the tower-support structure ( Structural stability term with a prediction step length and ), adjust the virtual active damping ( and , and are the virtual active damping gains for blade pitch and generator torque, respectively) and limiting actuator action ( and ) to determine the compensation value based on the comprehensive optimization goal and The optimization objective function of the planner is not unique and can be defined as shown in the following example:

[0099] (17)

[0100] in, is the value of the cost function; 、 、 、 、 、 is the weight factor, and the value of the weight factor is adjusted based on the Pareto optimal theory according to the real-time external environment characteristics; and It is the maximum allowable value within the safe working range; and are the maximum motion rates of the pitch and torque actuators respectively; is the contribution ratio of the additional controlled variable to the actuator motion.

[0101] In step 4-3, the state variables and input variables are intrinsically linked through the state space model, so state and input constraints need to be imposed to ensure safe operation:

[0102] (18)

[0103] (19)

[0104] (20)

[0105] (twenty one)

[0106] (twenty two)

[0107] (twenty three)

[0108] Among them, the state constraints are designed to prevent overload and operation risks: The predicted value of the generator torque Limited to the torque rating The predicted value of the rate of change is within 110% of Need to be less than To reduce the risk of overload; blade pitch prediction value of step length Must not be greater than the maximum value of the blade pitch angle , its change rate prediction value Restricted to To prevent aerodynamic stall. Input constraints are mainly used to adjust the changes in control parameters to ensure that the compensation variables and Do not exceed their respective rated values and 10% of.

[0109] Step 4-4, based on the state prediction model of offshore wind turbines (15-16), optimization objectives and constraints (17-23), use a solution algorithm such as quadratic programming, exhaustive method, gradient descent method, intelligent optimization algorithm, etc. to iteratively solve the objective function, and iteratively solve the N planning cycle control parameter vectors , ,…, Get the minimum cost function value . The sequence The first element of As the wind wheel speed setting value and power generation setting value Dynamic compensation value.

[0110] Application Examples

[0111] The typhoon-resistant soft cut-out method of offshore wind turbines with control parameter planning is applied to the DTU-10MW fixed wind turbine. A wind-wave environment time sequence diagram that exceeds the cut-out wind speed of the offshore wind turbine is set as follows: Figure 3 As shown, the specific parameters are: IEC standard Class A turbulent wind of 30m / s, wave peak height of 4.46m, and wave period of 8.86s.

[0112] Figures 4 to 8 Shows the corresponding Figure 3 Under working conditions, the performance comparison curve timing diagram of the industrial standard controller and the strategy proposed in this invention in terms of actuator use, power generation power, and tower bending moment load: Figure 4 The timing diagrams of blade pitch angles above the cut-out wind speed are compared. The standard industrial controller maintains the pitch angle at 90 degrees, while the proposed strategy fluctuates within the range of [20, 40] degrees. Figure 5 The comparison of the timing diagrams of the generator torque above the cut-out wind speed is shown. 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 The timing diagrams for cutting out the power generation above wind speed are compared. The standard industrial controller generates 0kW of power, while the proposed strategy generates approximately 80% of the rated power. Figure 7 A comparison of the time series of the tower's fore-aft bending moment load at wind speeds above the cut-out speed is shown. The standard industrial controller significantly exacerbates bending moment fluctuations under hydrodynamic forces due to the loss of aerodynamic damping. Figure 8 The time series diagrams of the tower lateral bending moment load above the cut-out wind speed are compared. Compared with the case of the forward and backward bending moment load, the strategy proposed in this invention effectively suppresses the structural load fluctuation by adjusting the structural damping.

[0113] Figures 9 to 13 The performance comparison between the industrial standard controller and the proposed strategy in terms of actuator usage, power generation, and tower bending moment load is shown under conditions with average wind speeds ranging from 2m / s to 40m / s: Figure 9 The performance comparison of blade pitch angle under all wind speed conditions is shown. Within the normal operating range, the two strategies have little difference in the mean and standard deviation of the pitch actuator used. Within the cut-out range, the mean pitch angle gradually approaches 90 degrees as the average wind speed increases, and the standard deviation is within a reasonable range. Figure 10 The performance comparison of generator torque under all wind speed conditions is shown. Within the normal operating range, the two strategies have little difference in the mean and standard deviation of the torque actuator used. Within the cut-out range, the mean torque gradually approaches 0 kNm with increasing average wind speed, and the standard deviation is within a reasonable range. Figure 11 The performance comparison of power generation under all wind speed conditions is shown. Within the normal operating range, the power generation characteristics of the two strategies are similar, with small differences in average and standard deviation. Within the cut-out range, the strategy of the present invention shows a significant advantage, not only effectively improving the average power generation, but also keeping the standard deviation within an acceptable range. Figure 12 The performance comparison of the tower's fore-aft bending moment loads under all wind speed conditions is demonstrated. Within the normal operating range, especially at wind speeds above rated, the proposed strategy achieves lower fore-aft structural fatigue damage compared to the industry standard control, with no significant difference in average bending moment values. Within the cut-out range, the proposed strategy achieves higher average bending moment values compared to the industry standard control, but the increased structural damping effectively reduces fore-aft fatigue damage. Figure 13 The performance comparison of tower lateral bending moment loads under all wind speed conditions is presented. Within the normal operating range, the proposed strategy achieves lower lateral structural fatigue damage compared to the industry standard control, with insignificant differences in average bending moment values. Within the cut-out range, the proposed strategy achieves higher average bending moment values compared to the industry standard control, but the increased structural damping effectively reduces lateral fatigue damage.

[0114] The above are only typical examples of the present invention. In addition, the present invention may have many other specific implementations. Any technical solutions formed by equivalent replacement or equivalent transformation fall within the scope of protection required by the present invention.

[0115] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0116] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic 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 is considered to be illustrative and not restrictive, and it should be understood that the claims (including all equivalents) are intended to limit the spirit and scope of the present invention. These embodiments above should be understood to be only for illustrating the present invention and not for limiting the scope of protection of the present invention. After reading the content of the record of the present invention, the technician can make various changes or modifications to the present invention, and these equivalent variations and modifications fall into the scope limited by the claims of the present invention equally.

Claims

1. A method for soft cut-out of offshore wind turbines against typhoons using control parameter planning, characterized in that: The steps include: Step 1: Establish a universal hierarchical control framework for fixed and floating offshore wind turbines, including a controller and a planner. The controller is an industry-standard controller consisting of a blade pitch control system and a generator torque control system. The planner consists of a soft-cutout reference curve and a nonlinear model prediction algorithm to provide control parameters to the controller. Step 2: Based on the external operating environment of the offshore wind turbine, a soft cut-out reference curve is designed in the planner to achieve the following: when the wind speed exceeds the cut-out wind speed threshold, the rotor speed and power generation are steadily reduced as the average wind speed increases, thereby achieving soft cut-out of the rotor speed and power generation and expanding the operating range of the offshore wind turbine; Step 3: construct 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; establish state equations associating the state variables of the offshore wind turbine transmission system, tower-foundation system, and controller with the given control parameters; Step 4: discretize the state equation to achieve multi-step prediction of the operating state of the offshore wind turbine, and design the nonlinear model prediction algorithm to compensate for the control parameters obtained from the soft cut-out reference curve; Iteratively solving the nonlinear model prediction algorithm based on the multi-step predicted state value obtained by solving the discretized state equation to determine the optimal compensation value of the control parameter; 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 ; 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 , using the hyperbola soft cut-out method: using the sliding window method to calculate the average wind speed , 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 generation rating ; When it exceeds the cut-out wind speed When the wind wheel speed setting value Press the formula to change , power generation setting value Press the formula to change ,in: represents the hyperbolic tangent function; is the actual shutdown wind speed set; 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 for the next N planning cycles is obtained through iterative solution of the model prediction algorithm. , ,…, , where the vector , The wind wheel speed setting value The compensation value, Set the power generation value Compensation value of vector The control parameters of the controller are obtained by compensating the set value with the obtained compensation value. and .

2. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 1, characterized in that: In step 3, the dynamic model of the transmission system adopts the torque balance equation of the single mass model.

3. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 1, characterized in that: In step 3, for a fixed offshore wind turbine, the tower-foundation structure system dynamics model is constructed in the following way: the fore-aft and lateral displacements of the tower top are modeled as a standard mass-spring-damper system.

4. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 1, 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 system with decoupling in the pitch and roll directions.

5. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 1, 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 and its compensation value The magnitude of the change caused , generator torque and its compensation value The magnitude of the change caused Construct the state vector of the wind turbine ; 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 during 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 vectors during 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.

6. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 1, 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 structure damping and limiting the actuator action, and designs a comprehensive optimization objective function to determine the compensation value. and .

7. The method for soft cut-out of offshore wind turbines against typhoons with control parameter planning according to claim 6, 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.

8. 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 7.

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