CN118092147B - Industrial planning controller design method for offshore wind turbine generator - Google Patents
Industrial planning controller design method for offshore wind turbine generator Download PDFInfo
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Abstract
The invention discloses a design method of an industrial planning controller of an offshore wind turbine, which comprises the following steps: 1) Constructing a planning controller architecture, wherein the planning controller adopts a double closed loop architecture: the inner ring is a standard industrial controller of the wind turbine generator, and the outer ring is a parameter planner; 2) Establishing a prediction model between core parameters of an industrial controller and the state of the wind turbine by using a nonlinear dynamics mathematical model of the wind turbine; 3) Determining an objective function and a state constraint of a parameter planner according to a rotating speed stability, power and load control target of the wind turbine generator in the running process based on a prediction model; 4) And (5) based on the incoming wind speed, the waves and the state of the wind turbine generator set, iteratively solving an objective function of the parameter planner, and updating parameters of a standard industrial controller of the wind turbine generator set. According to the method, under the condition that the existing industrial controller architecture is not changed, the running stability of the wind turbine generator can be comprehensively improved by dynamically adjusting the parameters of the industrial controller.
Description
Technical Field
The invention relates to an industrial controller design method, in particular to an industrial planning controller design method of an offshore wind turbine generator.
Background
The large-scale offshore wind turbine structure has remarkable flexible characteristics and is subjected to more extreme environmental load. According to data investigation, actual parameters and theoretical design values of running wind-power curves, wind-thrust curves and the like of the wind turbine generator are greatly different. The wind turbine generator system faces great uncertainty in actual operation, and challenges are brought to the power generation quality, the structural load and the stable control of the wind turbine generator system. Therefore, a wind turbine running controller architecture needs to be developed to improve the running of the existing offshore wind turbine and improve the running performance of the wind turbine.
The existing industrial controller architecture of the wind turbine generator is based on a single-input-single-output Proportional-integral (PI) controller, namely, a torque controller tracks an optimal rotating speed reference value to capture maximum wind power in a low wind speed region, and a torque and pitch controller respectively maintain the operation of the wind turbine generator at rated active power output and rated wind wheel rotating speed values in a high wind speed region. In order to optimize the running performance of the unit, the actual running performance of the unit is close to a theoretical design value, and a parameter setting control algorithm, such as fuzzy self-adaptive control, sliding mode variable structure control and model reference self-adaptive control strategy, is provided successively. However, such parameter tuning control changes the architecture of existing industrial controllers, with the potential risk of operational failure of the wind turbines, which is difficult to accept by the complete machine manufacturers and owners.
The offshore wind turbine is provided with a large number of sensors for monitoring the external wind-wave-current environment and the running state of the turbine, so that research content for improving the comprehensive running performance of the wind turbine on the premise of not changing the original industrial controller architecture is deficient by utilizing the data information of the external environment and the running state of the turbine, and deep research is needed.
Disclosure of Invention
The invention provides a design method of an industrial planning controller of an offshore wind turbine, which aims to solve the problem that the existing industrial controller has deviation between a theoretical design value and an actual operation value in the operation process and cannot meet the performance requirements of stable operation, power generation quality, structural load and the like of the turbine; in addition, the offshore wind turbine is provided with a large number of sensors, and the running performance of the offshore wind turbine is comprehensively optimized by designing an industrial planning controller capable of dynamically adjusting core control parameters on the premise of not changing the original industrial controller architecture.
In order to solve the technical problems, the invention adopts the following technical scheme:
an industrial planning controller design method of an offshore wind turbine generator set comprises the following steps:
Step 1, building an industrial planning controller architecture of a wind turbine, wherein the planning controller adopts a double closed-loop architecture: the inner ring is a standard industrial controller of the wind turbine generator, and the outer ring is a parameter planner;
Step 2, establishing a prediction model between core parameters of a standard industrial controller of the wind turbine and the state of the wind turbine by using a nonlinear dynamics mathematical model of the wind turbine; the core parameters of the standard industrial controller of the wind turbine generator comprise a proportional coefficient of pitch and yaw, an integral coefficient of pitch and yaw and a torque optimal coefficient;
step 3, determining an objective function and a state constraint of the parameter planner according to a rotating speed stability, power and load control target of the wind turbine in the running process based on a prediction model between core parameters of the standard industrial controller of the wind turbine and the state of the wind turbine;
And 4, iteratively solving an objective function of the parameter planner based on the incoming wind speed, the wave and the wind turbine generator system state, determining an optimal parameter sequence of the standard industrial controller of the wind turbine generator system, and taking a first vector of the optimal parameter sequence as a parameter of the standard industrial controller of the wind turbine generator system.
In the above technical solution, further, in step 1:
The existing industrial controller of the wind turbine generator is used as an inner ring of a planning controller, the input of the inner ring comprises the core parameters of the controller, set real-time running states and wind-wave-current environment parameters, which are given by a parameter planner, and the output of the inner ring is a blade pitch reference value Reference value of generator torqueYaw angle of engine roomAnd the control unit is used for executing control of the wind turbine generator.
The parameter planner is used as an outer ring of the planning controller, the input of the parameter planner is the real-time running state and the wind-wave-current environment parameters of the wind turbine measured by the sensor, the output is a core control parameter vector sequence of N periods in the future obtained by iterative solution of a model prediction algorithm, and the first vector is used for setting the core parameters of the standard industrial controller of the wind turbine;
execution cycle of parameter planner Controller cycle of greater than or equal to industrial controllerThe definition is: . That is, after the wind turbine generator system executes control for n periods, the industrial controller is updated with the core control parameters once.
Further, the nonlinear dynamics mathematical model of the wind turbine comprises a dynamics model of a wind wheel-transmission chain-generator of the wind turbine, a dynamics model of a tower-supporting structure of the wind turbine and a control dynamics model of variable pitch of blades, torque of the generator and yaw of a cabin of the wind turbine; the step 2 further comprises:
step 2-1, constructing a kinetic model of a wind wheel-transmission chain-generator of the wind turbine, wherein the formula is as follows:
(1)
(2)
(3)
Wherein, 、AndRespectively represent the rotational speed of the wind wheelRotation speed of generatorTorsion angle of transmission chainFirst derivative with respect to time; the power captured by the wind wheel relates to the rotation speed of the wind wheel Blade pitch angleWind speed at hubIs a function of (2); And The rotational inertia of the wind wheel and the generator are respectively; And Damping coefficient and rigidity coefficient of the transmission chain respectively; The gear box is a gear box transformation ratio; is the electromagnetic torque of the generator.
2-2, Constructing a dynamic model of the tower-supporting structure of the wind turbine, wherein the model mainly considers the forward-backward deformation and the lateral deformation of the tower top, and the model is expressed as follows:
(4)
(5)
Wherein, For the forward and backward deformation acceleration of the tower barrel,Lateral deformation acceleration of the tower barrel is achieved; For the deformation speed of the tower drum in the front-back direction, The lateral deformation speed of the tower barrel is set; for the deformation displacement of the tower drum in the front-back direction, The tower barrel is laterally deformed and displaced;、 And Respectively the mass, the structural damping and the rigidity coefficient of the tower; the thrust force born by the wind wheel surface relates to the rotation speed of the wind wheel Blade pitch angleWind speed at hubIs a function of (2); Is the height of the tower.
And 2-3, constructing a control dynamics model of blade pitch, generator torque and cabin yaw of the wind turbine. The model is expressed as:
(6)
(7)
(8)
Wherein, 、AndThe first derivatives of pitch angle, generator torque and yaw angle with respect to time, respectively;、 And Time constants of the blade, the generator and the engine room;、 And Respectively 3 blade pitch reference values, a generator torque reference value and a cabin yaw angle reference value;
、 And The calculation formula of (2) is as follows:
(9)
(10)
(11)
Wherein, 、、AndThe proportional coefficient of the variable pitch controller, the proportional coefficient of the yaw controller, the integral coefficient of the variable pitch controller and the integral coefficient of the yaw controller are respectively; An optimal torque coefficient below the rated wind speed; 、 And Rated wind speed, rated generator speed and rated power respectively; Is a measurement of generator rotational speed; And Respectively, incoming wind direction and measured cabin angle.
Step 2-4, the construction method of the prediction model between the core parameters of the standard industrial controller of the wind turbine and the states of the wind turbine is that a wind wheel-driving chain-generator, a tower-supporting structure and a controlled dynamic model are converted into a state prediction equation, which is expressed as:
(12)
Wherein, Is thatWith respect to the first derivative of time,Is a state vector of the wind turbine generator,、AndRespectively 3 blades, namely a variable pitch angle, generator torque and cabin yaw angle; Is the core parameter vector; Is the wind wave environment vector of the wind turbine generator; the matrix is composed of variables related to the states of the wind turbine in the nonlinear dynamics mathematical model of the wind turbine; the matrix is composed of variables related to core parameters in the nonlinear dynamics mathematical model of the wind turbine generator; The matrix is composed of variables related to wind wave environments of the wind turbine in the nonlinear dynamics mathematical model of the wind turbine.
Still further, the step 3 further includes:
Step 3-1, converting the state prediction equation of step 2-4 from continuous time state to discrete time state, wherein the discrete period is a specific planning period The discretized state prediction equation is expressed as:
(13)
Wherein, Is the firstThe state vector of the wind turbine generator set at the moment,Is the firstThe state vector of the wind turbine generator set at the moment,Is the firstA core parameter vector of the moment; Is the first Wind wave environment vectors of the wind turbine generator at moment;、 And Respectively the firstMatrix with discretized timeMatrixSum matrix。
Step 3-2, during a specific programming cycleIn the method, the parameter planner aims at comprehensive optimization of power capture quality improvement and load reduction of the wind turbine generator, and an objective function can be expressed by the following cost function:
(14)
Wherein, A value that is a cost function;、、、、、、、 the method comprises the steps of respectively obtaining weight factors of rotor rotating speed, generator rotating speed, transmission chain torsion angle, tower forward and backward deformation speed, tower lateral deformation speed, blade pitch, generator torque and cabin yaw, wherein the weight factors are based on the pareto theory of power generation quality and structural load reduction, and setting according to real-time external environment characteristics; is a normalized function of the variables.
Step 3-3, the state constraint of the parameter planner is as follows:
Limiting variable pitch of candidate given blades of the wind turbine generator, generator torque, a limited control set of yaw and a generator rotating speed value:
(15)
(16)
(17)
(18)
(19)
(20)
(21)
Wherein, 、、And、、The minimum and maximum limits of blade pitch amplitude, torque amplitude and nacelle yaw amplitude are respectively;、、 And 、、Maximum and minimum limits for blade pitch rate, torque rate, yaw rate, respectively; for the cut-in rotational speed, Is the rated rotation speed value of the generator.
Still further, the step 4 further includes:
At each execution cycle of the parameter planner And (3) based on the actually measured incoming wind speed and wave, the forecast and the actually measured wind turbine generator set state, iteratively solving an objective function of the parameter planner by using an intelligent optimization algorithm or a quadratic programming solution algorithm, and updating an optimal sequence of core parameters of the standard industrial controller of the wind turbine generator set. The principle of the quadratic programming solving algorithm is a gradient descent method; the intelligent solving algorithm, such as a particle swarm algorithm, can quickly solve the multi-step prediction problem and find the global optimal solution.
Furthermore, the intelligent optimization algorithm is a particle swarm algorithm, and the particle swarm algorithm is adopted to iteratively solve the objective function of the parameter planner, which comprises the following specific steps:
1) From the following components The group of particles is searched in space, through the firstFirst iterationThe core parameters of the wind turbine standard industrial controller characterized by the particles and the vector of the parameter change rate are respectively expressed asAndIn the jth round of iterationCost function of individual particlesThe vector corresponding to the minimum of (2) is expressed asThe global optimum through which all particles within a population pass is expressed asIn the first placeSecond timeThe iterative equations for the velocity and position of the individual particles are:
(22)
(23)
Wherein, AndIs a factor of the learning process,AndIs uniformly distributedTwo random numbers in between are used for the control of the data,For inertial weights, the value depends on inheritance of the current speed.
2) When the iteration times reach a set value, obtaining a predicted parameter sequence of a standard industrial controller of the wind turbine generator according to a particle swarm algorithm,, ,…, . The sequence is subjected toIs the first vector of (2)As a parameter of a standard industrial controller of the wind turbine.
The present invention also provides an electronic device including:
one or more processors;
A memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement an industrial planning controller design method for an offshore wind turbine as described above.
The invention also provides a computer readable storage medium, on which computer instructions are stored, the computer instructions being for causing a computer to perform the steps of the above-described method for designing an industrial planning controller for an offshore wind turbine.
The invention has the beneficial effects that:
The invention provides a design method of a planning controller of an offshore wind turbine generator system for improving running performance. The industrial planning controller of the offshore wind turbine adopts a double closed loop architecture, and the inner loop is the standard industrial controller of the existing wind turbine, so that the scheme of the mature controller of the existing complete machine plant/owner is not changed; the parameter planner of the outer ring dynamically adjusts the core parameters of the industrial controller to realize multi-objective optimization.
And establishing a state prediction equation between core parameters of the industrial controller and states of the wind turbine based on a wind wheel-transmission chain-generator of the wind turbine, a tower-supporting structure and a controlled dynamic model for the prediction model in the planner. And determining an objective function and a state constraint of the parameter planner according to the rotation speed stability, the power and the load control targets of the wind turbine generator in the operation process. And (3) based on the actually measured incoming wind speed and wave, the prediction and the actually measured wind turbine generator set state, iteratively solving an objective function, determining an optimal sequence of optimal industrial controller parameters, and taking a first vector of the optimal sequence as a controller parameter.
According to the invention, under the condition of not changing the architecture of the existing industrial controller, the running stability of the wind turbine can be comprehensively improved, the power output quality is optimized, the structural load of the component is reduced, and the running reliability and the high energy efficiency of the wind turbine are improved by dynamically adjusting the parameters of the industrial controller, so that the method has important engineering application value.
Drawings
FIG. 1 is a diagram of an industrial planning controller architecture for an offshore wind turbine of the present invention;
FIG. 2 is a non-linear cost function solver based on a fast particle swarm algorithm;
FIG. 3 is a graph of wind speed versus wave external environment operating conditions for an offshore wind turbine;
FIG. 4 is a graph showing real-time comparison of parameter changes of a pitch and torque sub-control system;
FIG. 5 is a graph of real-time comparison of rotational speed, power, blade root load, and tower bottom load optimization effects for corresponding operating conditions.
Detailed Description
The following detailed description of the invention is provided in connection with the accompanying drawings to facilitate understanding and grasping of the technical scheme of the invention.
The embodiment of the invention provides a design method of an industrial planning controller of an offshore wind turbine, and an architecture diagram of the industrial planning controller is shown in fig. 1.
The design method of the industrial planning controller comprises the following specific steps:
Step 1, building an industrial planning controller architecture of a wind turbine, wherein the planning controller adopts a double closed-loop architecture: the inner ring is a standard industrial controller of the wind turbine generator, and the outer ring is a parameter planner;
Step 2, establishing a prediction model between core parameters of a standard industrial controller of the wind turbine and the state of the wind turbine by using a nonlinear dynamics mathematical model of the wind turbine; the core parameters of the standard industrial controller of the wind turbine generator comprise a proportional coefficient of pitch and yaw, an integral coefficient of pitch and yaw and a torque optimal coefficient;
step 3, determining an objective function and a state constraint of the parameter planner according to a rotating speed stability, power and load control target of the wind turbine in the running process based on a prediction model between core parameters of the standard industrial controller of the wind turbine and the state of the wind turbine;
And 4, iteratively solving an objective function of the parameter planner based on the incoming wind speed, the wave and the wind turbine generator system state, determining an optimal parameter sequence of the standard industrial controller of the wind turbine generator system, and taking a first vector of the optimal parameter sequence as a parameter of the standard industrial controller of the wind turbine generator system.
In step 1: the input of the standard industrial controller of the wind turbine generator comprises a controller core parameter given by a parameter planner, the real-time running state of the wind turbine generator and wind-wave-flow environment parameters, and the output comprises a blade pitch reference value, a generator torque reference value and a cabin yaw angle reference value; the input of the parameter planner is the real-time running state of the wind turbine and the wind wave-current environment parameters, the output is the predicted core parameter vector sequence of the future N periods, and the first vector is utilized to set the core parameters of the standard industrial controller of the wind turbine; execution cycle of the parameter plannerThe control period of the standard industrial controller of the wind turbine generator is greater than or equal to that of the standard industrial controller of the wind turbine generatorThe definition is:。
In the step 2, the nonlinear dynamics mathematical model of the wind turbine comprises a dynamics model of a wind wheel-transmission chain-generator of the wind turbine, a dynamics model of a tower-supporting structure of the wind turbine and a control dynamics model of variable pitch of blades, torque of the generator and yaw of a cabin of the wind turbine; the step 2 specifically comprises the following steps:
step 2-1, constructing a kinetic model of a wind wheel-transmission chain-generator of the wind turbine, wherein the formula is as follows:
(1)
(2)
(3)
Wherein, 、AndRespectively represent the rotational speed of the wind wheelRotation speed of generatorTorsion angle of transmission chainFirst derivative with respect to time; the power captured by the wind wheel relates to the rotation speed of the wind wheel Blade pitch angleWind speed at hubIs a function of (2); And The rotational inertia of the wind wheel and the generator are respectively; And Damping coefficient and rigidity coefficient of the transmission chain respectively; The gear box is a gear box transformation ratio; is the electromagnetic torque of the generator.
2-2, Constructing a dynamic model of the tower-supporting structure of the wind turbine, wherein the model mainly considers the forward-backward deformation and the lateral deformation of the tower top, and the model is expressed as follows:
(4)
(5)
Wherein, For the forward and backward deformation acceleration of the tower barrel,Is the lateral deformation acceleration; For the deformation speed of the tower drum in the front-back direction, The lateral deformation speed of the tower barrel is set; for the deformation displacement of the tower drum in the front-back direction, The tower barrel is laterally deformed and displaced;、 And Respectively the mass, the structural damping and the rigidity coefficient of the tower; the thrust force born by the wind wheel surface relates to the rotation speed of the wind wheel Blade pitch angleWind speed at hubIs a function of (2); Is the height of the tower.
And 2-3, constructing a control dynamics model of blade pitch, generator torque and cabin yaw of the wind turbine. The model is expressed as:
(6)
(7)
(8)
Wherein, 、AndThe first derivatives of pitch angle, generator torque and yaw angle with respect to time, respectively;、 And Time constants of the blade, the generator and the engine room;、 And Respectively a blade pitch reference value, a generator torque reference value and a cabin yaw angle reference value;
、 And The calculation formula of (2) is as follows:
(9)
(10)
(11)
Wherein, 、、AndThe proportional coefficient of the variable pitch controller, the proportional coefficient of the yaw controller, the integral coefficient of the variable pitch controller and the integral coefficient of the yaw controller are respectively; An optimal torque coefficient below the rated wind speed; 、 And Rated wind speed, rated generator speed and rated power respectively; Is a measurement of generator rotational speed; And Respectively, incoming wind direction and measured cabin angle.
Step 2-4, the construction method of the prediction model between the core parameters of the standard industrial controller of the wind turbine and the states of the wind turbine is that a wind wheel-driving chain-generator, a tower-supporting structure and a controlled dynamic model are converted into a state prediction equation, which is expressed as:
(12)
Wherein, Is a state vector of the wind turbine generator,、AndRespectively 3 blades, namely a variable pitch angle, generator torque and cabin yaw angle; Is that First derivative with respect to time; Is the core parameter vector; Is the wind wave environment vector of the wind turbine generator; the matrix is composed of variables related to the states of the wind turbine in the nonlinear dynamics mathematical model of the wind turbine; the matrix is composed of variables related to core parameters in the nonlinear dynamics mathematical model of the wind turbine generator; The matrix is composed of variables related to wind wave environments of the wind turbine in the nonlinear dynamics mathematical model of the wind turbine.
Step 3 comprises the following steps:
Step 3-1, converting the state prediction equation from a continuous time state to a discrete time state, wherein the discrete period is a specific planning period The discretized state prediction equation is expressed as:
(13)
Wherein, Is the firstThe state vector of the wind turbine generator set at the moment,Is the firstThe state vector of the wind turbine generator set at the moment,Is the firstA core parameter vector of the moment; Is the first Wind wave environment vectors of the wind turbine generator at moment;、 And Respectively the firstMatrix with discretized timeMatrixSum matrix；
Step 3-2, during a specific programming cycleIn this, the objective function of the parameter planner is represented by the following cost function:
(14)
Wherein, A value that is a cost function;、、、、、、、 The weight factors of rotor rotating speed, generator rotating speed, transmission chain torsion angle, tower forward and backward deformation speed, tower lateral deformation speed, blade pitch, generator torque and cabin yaw are respectively; a normalization function for the variables;
step 3-3, the state constraint of the parameter planner is as follows:
Limiting a limited control set of pitch, generator torque and nacelle yaw of candidate given blades of the wind turbine generator, and restraining the value of the generator rotation speed:
(15)
(16)
(17)
(18)
(19)
(20)
(21)
Wherein, 、、And、、The minimum and maximum limits of blade pitch amplitude, torque amplitude and nacelle yaw amplitude are respectively;、、 And 、、Minimum and maximum limits for blade pitch rate, torque rate, nacelle yaw rate, respectively; for the cut-in rotational speed, Is the rated rotation speed value of the generator.
Step 4 comprises the steps of:
At each execution cycle of the parameter planner And (3) based on the actually measured incoming wind speed and wave, the forecast and the actually measured wind turbine generator set state, iteratively solving an objective function of the parameter planner by using an intelligent optimization algorithm or a quadratic programming solution algorithm, and updating an optimal sequence of core parameters of the standard industrial controller of the wind turbine generator set.
The intelligent optimization algorithm is a particle swarm algorithm, the particle swarm algorithm is adopted to iteratively solve the objective function of the parameter planner, a flow chart of the algorithm is shown in fig. 2, and the specific steps are as follows:
1) From the following components The group of particles is searched in space, through the firstFirst iterationThe core parameters of the wind turbine standard industrial controller characterized by the particles and the vector of the parameter change rate are respectively expressed asAndIn the jth round of iterationCost function of individual particlesThe vector corresponding to the minimum of (2) is expressed asThe global optimum through which all particles within a population pass is expressed asIn the first placeSecond timeThe iterative equations for the velocity and position of the individual particles are:
(22)
(23)
Wherein, AndIs a factor of the learning process,AndIs uniformly distributedTwo random numbers in between are used for the control of the data,Is an inertial weight;
2) When the iteration number reaches a set value, obtaining a predicted parameter sequence of a standard industrial controller of the wind turbine generator according to a particle swarm algorithm , ,…, ; The sequence is subjected toIs the first vector of (2)As a parameter of a standard industrial controller of the wind turbine.
The present invention also provides an electronic device including: one or more processors; a memory for storing one or more programs; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement an industrial planning controller design method for an offshore wind turbine as described above.
The present invention further provides a computer readable storage medium having stored thereon computer instructions for causing a computer to perform the steps of the above-described method for designing an industrial planning controller for an offshore wind turbine.
Example 1
And applying the designed industrial planning controller of the offshore wind turbine to a DTU-10MW wind turbine model considering the p-y-M- Θ pile soil structure. The environmental parameters are set as follows: (a) 8m/s turbulent wind of IEC standard, turbulent intensity 20.30%, wave peak height 1.31m, wave period 5.67s, and included angle of wind and wave 90deg; (b) IEC standard 20m/s turbulent wind, turbulent intensity 14.42%, wave peak height 2.76m, wave period 6.99s, and included angle of wind and wave 90deg.
FIG. 3 shows a time sequence diagram of wind speed and external wave environment conditions of the offshore wind turbine corresponding to the environment parameters (a) and (b). Fig. 4 shows real-time comparison curves of a standard controller and a planning controller for parameter variation of a pitch and torque sub-control system, wherein (a) is a time sequence variation comparison diagram of a torque optimal parameter corresponding to an environment parameter (a), and (b) is a time sequence variation comparison diagram of a pitch proportion parameter and an integral parameter corresponding to the environment parameter (b), and the planning controller provided by the invention adopts a parameter planner to adjust parameters of an industrial controller. Fig. 5 shows real-time comparison curves of a standard controller and a planning controller of active power, rotor rotating speed, blade root waving bending moment, forward and backward bending moment at the bottom of a tower and lateral bending moment at the bottom of the tower, which correspond to the environmental parameters (a) and (b), so that the planning controller provided by the invention can effectively inhibit power and rotating speed fluctuation, reduce structural loads of key components such as blades and towers, and comprehensively improve the operation performance of the offshore wind turbine.
The foregoing is only exemplary of the invention, and many other embodiments of the invention are possible, and all modifications and variations of the invention are intended to fall within the scope of the invention.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
While the 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 invention. It is therefore intended that the foregoing detailed description be regarded as illustrative rather than limiting, and that it be understood that it is the following claims, including all equivalents, that are intended to define the spirit and scope of this invention. The above examples should be understood as illustrative only and not limiting the scope of the invention. Various changes and modifications to the present invention may be made by one skilled in the art after reading the teachings herein, and such equivalent changes and modifications are intended to fall within the scope of the invention as defined in the appended claims.
Claims (7)
1. The design method of the industrial planning controller of the offshore wind turbine generator is characterized by comprising the following steps of:
Step 1, building an industrial planning controller architecture of a wind turbine, wherein the planning controller adopts a double closed-loop architecture: the inner ring is a standard industrial controller of the wind turbine generator, and the outer ring is a parameter planner;
Step 2, establishing a prediction model between core parameters of a standard industrial controller of the wind turbine and the state of the wind turbine by using a nonlinear dynamics mathematical model of the wind turbine; the core parameters of the standard industrial controller of the wind turbine generator comprise a proportional coefficient of pitch and yaw, an integral coefficient of pitch and yaw and a torque optimal coefficient;
step 3, determining an objective function and a state constraint of the parameter planner according to a rotating speed stability, power and load control target of the wind turbine in the running process based on a prediction model between core parameters of the standard industrial controller of the wind turbine and the state of the wind turbine;
Step 4, iteratively solving an objective function of the parameter planner based on the incoming wind speed, the wave and the wind turbine generator system state, determining an optimal parameter sequence of the standard industrial controller of the wind turbine generator system, and taking a first vector of the optimal parameter sequence as a parameter of the standard industrial controller of the wind turbine generator system;
in the step 2, the nonlinear dynamics mathematical model of the wind turbine comprises a dynamics model of a wind wheel-transmission chain-generator of the wind turbine, a dynamics model of a tower-supporting structure of the wind turbine and a control dynamics model of variable pitch of blades of the wind turbine, generator torque and cabin yaw; the step 2 specifically comprises the following steps:
step 2-1, constructing a kinetic model of a wind wheel-transmission chain-generator of the wind turbine, wherein the formula is as follows:
Wherein, AndRespectively representing the first derivative of wind wheel rotating speed omega r, generator rotating speed omega g and transmission chain torsion angle delta with respect to time; p r is the wind wheel capturing power, and is a function of the wind wheel rotating speed omega r, the blade pitch angle beta and the wind speed V wind at the hub; j r and J g are the rotor and generator moment of inertia, respectively; d s and K s are the damping coefficient and stiffness coefficient of the drive chain, respectively; n g is the gear box transformation ratio; t g is the electromagnetic torque of the generator;
step 2-2, constructing a dynamic model of a wind turbine tower-supporting structure, wherein the dynamic model is expressed as follows:
Wherein, For the forward and backward deformation acceleration of the tower barrel,Lateral deformation acceleration of the tower barrel is achieved; For the deformation speed of the tower drum in the front-back direction, The lateral deformation speed of the tower barrel is set; x fa is the forward and backward deformation displacement of the tower, and x ss is the lateral deformation displacement of the tower; m t、Dt and K t are respectively the mass, structural damping and stiffness coefficients of the tower; f t is the thrust borne by the wind wheel surface and is a function of the wind wheel rotating speed omega r, the blade pitch angle beta and the wind speed V wind at the hub; h is the height of the tower;
2-3, constructing a control dynamics model of blade pitch, generator torque and cabin yaw of the wind turbine; the model is expressed as:
Wherein, AndThe first derivatives of pitch angle, generator torque and yaw angle with respect to time, respectively; t au,pitch、tau,torque and t au,yaw are time constants of the blade, the generator and the nacelle respectively; And Respectively 3 blade pitch reference values, a generator torque reference value and a cabin yaw angle reference value;
And The calculation formula of (2) is as follows:
wherein, K p,bla、Kp,yaw、Ki,bla and K i,yaw are the proportional coefficient of the pitch controller, the proportional coefficient of the yaw controller, the integral coefficient of the pitch controller and the integral coefficient of the yaw controller respectively; k opt is the optimal torque coefficient below the rated wind speed; And Rated wind speed, rated generator speed and rated power respectively; Is a measurement of generator rotational speed; theta wind Respectively measuring the incoming wind direction and the cabin angle;
2-4, the construction method of the prediction model between the core parameters of the standard industrial controller of the wind turbine and the states of the wind turbine is that a wind wheel-driving chain-generator, a tower-supporting structure and a controlled dynamic model are converted into a state prediction equation, and the state prediction equation is expressed as follows:
Wherein, Is a wind turbine generator set state vector, and beta 1,2,3、TGen and theta yaw are respectively 3 blades pitch angles, generator torque and cabin yaw angles; Is the first derivative of x with respect to time; u= [ K p_bla,Ki_bla,Kopt,Kp_yaw,Ki_yaw]T ] is the core parameter vector; d= [ v wind,θwind]T ] is wind wave environment vector of the wind turbine generator; a is a matrix formed by variables related to the state of the wind turbine in the nonlinear dynamics mathematical model of the wind turbine; b is a matrix formed by variables related to core parameters in the nonlinear dynamics mathematical model of the wind turbine generator; b d is a matrix formed by variables related to wind wave environment of the wind turbine in the nonlinear dynamics mathematical model of the wind turbine.
2. The method for designing an industrial planning controller for an offshore wind turbine according to claim 1, wherein in step 1: the input of the standard industrial controller of the wind turbine generator comprises a controller core parameter given by a parameter planner, the real-time running state of the wind turbine generator and wind-wave-flow environment parameters, and the output comprises a blade pitch reference value, a generator torque reference value and a cabin yaw angle reference value; the input of the parameter planner is the real-time running state of the wind turbine and the wind wave-current environment parameters, the output is the predicted core parameter vector sequence of the future N periods, and the first vector is utilized to set the core parameters of the standard industrial controller of the wind turbine; the execution period T plan of the parameter planner is greater than or equal to the control period T ctrl of the standard industrial controller of the wind turbine, and is defined as: t plan＝n*Tctrl.
3. The method for designing an industrial planning controller for an offshore wind turbine according to claim 1, wherein the step 3 comprises the steps of:
Step 3-1, converting the state prediction equation from a continuous time state to a discrete time state, wherein the discrete period is a specific planning period T plan, and the discretized state prediction equation is expressed as follows:
Wherein, As a state vector of the wind turbine at the kth moment, x k+1 is a state vector of the wind turbine at the (k+1) th moment ,uk＝[Kp_bla k,Ki_bla k,Kopt k,Kp_yaw k,Ki_yaw k]T is a core parameter vector at the kth moment; d k＝[vwind k,θwind k]T is the wind wave environment vector of the wind turbine at the kth moment; a k、Bk The matrix A, the matrix B and the matrix B d are discretized at the kth moment respectively;
Step 3-2, during a particular planning period T plan, the objective function of the parameter planner is represented by the following cost function:
Wherein J CF is the value of the cost function; q 1、Q2、Q3、Q4、Q5、Q6、Q7、Q8 is the weight factors of rotor speed, generator speed, transmission chain torsion angle, tower forward and backward deformation speed, tower lateral deformation speed, blade pitch, generator torque and cabin yaw respectively; norm (·) is the normalized function of the variable;
step 3-3, the state constraint of the parameter planner is as follows:
Limiting a limited control set of pitch, generator torque and nacelle yaw of candidate given blades of the wind turbine generator, and restraining the value of the generator rotation speed:
βmin≤β1,2,3≤βmax (15)
TGenMin≤TGen≤TGenMax (16)
θYawMin≤θYaw≤θYawMax (17)
Wherein, beta min、TGenMin、θYawMin and beta max、TGenMax、θYawMax are the minimum and maximum limits of blade pitch amplitude, torque amplitude, nacelle yaw amplitude, respectively; And Minimum and maximum limits for blade pitch rate, torque rate, nacelle yaw rate, respectively; for the cut-in rotational speed, Is the rated rotation speed value of the generator.
4. An industrial planning controller design method for an offshore wind turbine according to claim 3, wherein the step 4 comprises the steps of:
And in the execution period T plan of each parameter planner, iteratively solving an objective function of the parameter planners by using an intelligent optimization algorithm or a quadratic programming solution algorithm based on the actually measured incoming wind speed and wave, the prediction and the actually measured wind turbine generator state, and updating an optimal sequence of core parameters of the standard industrial controller of the wind turbine generator.
5. The method for designing an industrial planning controller for an offshore wind turbine according to claim 4, wherein the intelligent optimization algorithm is a particle swarm algorithm, and the objective function of the parameter planner is iteratively solved by using the particle swarm algorithm, and the specific steps are as follows:
1) Searching a group consisting of m particles in space, wherein the vectors of the core parameters and the parameter change rates of the core parameters of the standard industrial controller of the wind turbine generator set, which are characterized by the ith particle of the jth iteration, are respectively expressed as U i j and U i j The vector corresponding to the minimum of cost function J CF for the ith particle in the jth iteration is expressed asThe global optimum through which all particles pass within a population is expressed asThe velocity and position iterative equation for the ith particle at the j+1th time is:
wherein c 1 and c 2 are learning factors, r 1 and r 2 are two random numbers uniformly distributed and [0,1], and ω is an inertial weight;
2) When the iteration number reaches a set value, obtaining a predicted parameter sequence of a standard industrial controller of the wind turbine generator according to a particle swarm algorithm The first vector of the sequence U * As a parameter of a standard industrial controller of the wind turbine.
6. An electronic device, comprising:
one or more processors;
A memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-5.
7. A computer readable storage medium having stored thereon computer instructions for causing a computer to perform the steps of the method according to any of claims 1-5.
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