Maximum Power Tracking Control Method for Offshore Wind Turbines Based on Position Sensors

Abstract

The present invention discloses a maximum power tracking control method for an offshore wind turbine based on a position sensor, comprising the following steps: S1, establishing a mathematical model of a wind turbine; S2, establishing a mathematical model of a permanent magnet synchronous generator; S3, designing a sliding mode controller; S4, designing an aerodynamic torque observer; S5, designing a control strategy for a grid-side converter. According to the optimal tip speed ratio, the reference speed is obtained and substituted into the sliding mode controller, so that maximum wind energy tracking can be achieved under the condition of wind speed change; in addition, an extended state observer is used to estimate the aerodynamic mechanical torque of the wind turbine, and a feedforward compensation is performed on the q-axis current, so that the sliding mode controller has a better effect.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind turbine control, and particularly relates to a maximum power tracking control method for an offshore wind turbine based on a position sensor. Background Art

[0002] Behind the great prosperity and development of human material life and cultural life, the energy resources supporting its growth are becoming increasingly scarce. However, the fossil energy we rely on is non-renewable energy. Fossil fuels such as coal, natural gas, and oil will eventually be exhausted, and the combustion of fossil energy has damaged the earth's ecological environment. The air, water, and vegetation on which we depend for survival will be polluted due to the use of fossil fuels. Therefore, this has led to the opposition between economic development and environmental protection. To achieve the goal of both economic development and environmental protection, some clean and renewable energies such as wind energy, solar energy, geothermal energy, and tidal energy have begun to be utilized.

[0003] According to the wind speed, the operating area of a wind turbine is usually divided into four parts: the part where the wind speed is lower than the cut-in wind speed, the area where the wind speed is between the cut-in wind speed and the rated wind speed (low wind speed area), the area where the wind speed is close to the rated wind speed, and the area where the wind speed is higher than the rated wind speed (high wind speed area). Among them, the low wind speed area is one of the typical working areas of the system operation. Its main control objective is to control the wind turbine rotor speed to track the optimal speed determined by the real-time wind speed, so as to capture more wind energy and maximize the power output of the wind turbine. Therefore, obtaining better control effects depends on both the accurate measurement of the real-time wind speed and the reasonable design of the optimized control algorithm.

[0004] In terms of wind speed measurement, traditional sensors such as anemometers and wind vanes are generally located in the upwind area of the wind turbine. Affected by the tower shadow effect and wake effect, there is a certain difference from the real wind speed reaching the wind turbine rotor. At the same time, due to the randomness and time-variability of turbulent wind, the wind speed continuously changes across the entire wind turbine swept area, and mechanical instruments have inertia, so it is impossible to ensure the real-time and accuracy of wind speed measurement. The control strategy designed based on it is difficult to ensure the optimal. In addition, the harsh natural environment of the wind farm will shorten the service life of the sensor. Therefore, most of the existing research estimates the wind speed according to the output characteristics of the wind turbine, which has a relatively high estimation accuracy. However, it is undeniable that the estimated wind speed has a lag compared with the actual wind speed, and the control law adopted according to it cannot control the wind turbine in real time, resulting in a significant reduction in control performance.

[0005] Due to the unique dynamic properties of wind power generation, its control system must be designed in combination with these properties. Variability, non-linearity, strong coupling, and complexity are the inherent properties of megawatt-level high-power wind turbine generators. At the same time, due to the variable terrain of wind farms, the wind speed is unstable, strongly interfered, and unpredictable. It can be seen that the environment where the wind turbine is located is very harsh. The wind speed and direction are unpredictable by people and change in real time. In wind turbines connected to the grid for power generation, changes in grid parameters will also pose requirements for the control of the wind turbine. Therefore, the control of the wind turbine requires stability and high efficiency.

[0006] In terms of control strategies, the optimal torque method, which is most widely used in engineering, has the characteristics of simplicity and easy implementation. However, when the wind speed is low or the moment of inertia of the wind turbine generator is large, the response speed of the wind turbine rotor speed to track the real-time wind speed will decrease, leading to a reduction in the wind energy conversion efficiency. Conventional sliding mode control has great advantages in dealing with non-linearity, uncertain disturbances, etc., and can make the system move along the specified state trajectory under certain characteristics, with a simple structure and fast response. However, it will generate chattering. Summary of the Invention

[0007] The purpose of the present invention is to provide a maximum power tracking control method for offshore wind turbine generators based on position sensors in view of the problems existing in the prior art.

[0008] To achieve the above purpose, the technical solution adopted by the present invention is:

[0009] A maximum power tracking control method for offshore wind turbine generators based on position sensors includes the following steps:

[0010] S1. Establish a mathematical model of the wind turbine;

[0011] S2. Establish a mathematical model of the permanent magnet synchronous generator;

[0012] S3. Design a sliding mode controller;

[0013] S4. Design an aerodynamic torque observer;

[0014] S5. Design a grid-side converter control strategy.

[0015] Specifically, in step S1, the mathematical model of the wind turbine includes the following mathematical models, where

[0016] The mechanical energy captured by the wind turbine is expressed as:

[0017]

[0018] The tip speed ratio is the ratio of the tip linear speed of the wind turbine impeller to the real-time wind speed, and is expressed as:

[0019]

[0020] The mechanical torque on the wind turbine rotor is expressed as:

[0021]

[0022] where P is the output power of the wind turbine; ρ is the air density; r is the impeller radius; v wind is the actual wind speed through the wind turbine; β is the pitch angle; λ is the tip speed ratio; C P is the wind energy utilization coefficient; ω is the angular velocity of the motor rotor.

[0023] Specifically, in step S2, the mathematical model of the permanent magnet synchronous generator includes the following mathematical models, where

[0024] The voltage equation of the permanent magnet synchronous generator is expressed as:

[0025]

[0026]

[0027] The motion equation of the permanent magnet synchronous generator is expressed as:

[0028]

[0029]

[0030] where u sd 、u sq are the voltages on the d-axis and q-axis respectively; i sd 、i sq are the currents on the d-axis and q-axis respectively; L s 、R s are the stator inductance and stator resistance respectively; J is the moment of inertia; P n is the number of pole pairs; ψ f is the magnetic flux linkage between the permanent magnet and the stator; T e is the electromagnetic torque.

[0031] Specifically, in step S3, the method for designing the sliding mode controller is:

[0032] Define the state variables of the permanent magnet synchronous generator as:

[0033]

[0034] where ω ref is the reference speed of the motor; ω is the angular velocity of the motor rotor;

[0035]

[0036] Let The state equation of the system is obtained as follows:

[0037]

[0038] Define the system sliding mode surface as:

[0039] s = cx 1 + x 2

[0040] It can be obtained that:

[0041]

[0042] where c is a system parameter;

[0043] Then the expression of the sliding mode controller is:

[0044]

[0045] The q-axis reference current is obtained as:

[0046]

[0047] where J is the moment of inertia; T L is the mechanical torque on the wind turbine rotor; P n is the number of pole pairs; ψ f is the magnetic flux linkage between the permanent magnet and the stator.

[0048] Specifically, in step S4, the method for designing the aerodynamic torque observer is:

[0049] The state equation of the observer is:

[0050]

[0051] where, u = T e ; y = ω;

[0052] To simplify the observer structure, the above equation is reduced in order to obtain:

[0053]

[0054] where, l is the observer gain and z is the intermediate state variable;

[0055] Discretizing the above equation gives:

[0056]

[0057] where i = 0, 1, 2, 3…, the absolute value of the eigenvalue λ of the observation equation is less than 1; the eigenvalue λ of the observation equation can be expressed as:

[0058]

[0059] The observed value of the reduced-order disturbance torque is:

[0060]

[0061] Input the true measured values of the rotational speed ω and the current i q into the observer, and obtain:

[0062]

[0063] Introduce a low-pass filter at the output end of the observer to reduce interference, then there is:

[0064]

[0065] where δ 1 , δ 2 is the cut-off frequency of the low-pass filter, and K t is the motor torque constant;

[0066] Convert the torque obtained by the torque observer into current, and combine it with the above formula as the feed-forward compensation amount of the anti-disturbance torque to obtain the reference current:

[0067]

[0068] where J is the moment of inertia; T L is the mechanical torque on the wind turbine rotor; P n is the number of pole pairs; ψ f is the magnetic flux linkage between the permanent magnet and the stator.

[0069] Specifically, in step S5, the method for designing the grid-side converter control strategy is:

[0070] In the steady state, assuming that the DC bus voltage is stable and there is no power fluctuation, the active power output by the motor-side rectifier is:

[0071] P s = u sd i sd + u sq i sq = u dc i dc

[0072] P g = u gd i gd = u dc i g

[0073]

[0074] Among them, P s is the active power output of the motor; P g is the active power transmitted to the power grid; i g is the current input from the DC side to the grid-side inverter; i dc is the current value input from the machine-side rectifier to the DC side; u dc is the DC bus voltage;

[0075] When the active power output of the generator changes with the wind speed, the grid-side control is coordinated with the machine-side control to correct the control quantity on the grid side;

[0076] Under the condition of grid stability, u gd is constant, then:

[0077]

[0078] Among them, u gd is the d-axis component of the input voltage of the grid-side converter; i gd is the d-axis component of the input current of the grid-side converter; u sd , u sq are the components of the grid-connected voltage on the d-axis and q-axis respectively; i sd , i sq are the components of the grid-connected current on the d-axis and q-axis respectively;

[0079] is used as a feed-forward compensation amount to compensate the d-axis current given value of the current inner loop of the grid-side converter.

[0080] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention obtains the reference speed according to the optimal tip speed ratio and substitutes it into the sliding mode controller, so as to achieve maximum wind energy tracking under the condition of wind speed change; in addition, the extended state observer is used to estimate the aerodynamic mechanical torque of the wind turbine, and the q-axis current is feed-forward compensated, so that the sliding mode controller has better effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 is a flowchart of the maximum power tracking control method for an offshore wind turbine based on a position sensor according to the present invention.

[0082] Figure 2 is a schematic structural diagram of the observer in the embodiment of the present invention.

[0083] Figure 3 is a control block diagram of the machine-side system in the embodiment of the present invention.

[0084] Figure 4 is a control block diagram of the grid-side converter in the embodiment of the present invention.

[0085] Figure 5 This is the control block diagram of the MPPT system in the embodiment of the present invention.

[0086] Figure 6 This is the wind speed graph of Shanghai in 2019 in the embodiment of the present invention.

[0087] Figure 7 This is the constant wind speed graph used in the simulation in the embodiment of the present invention.

[0088] Figure 8 This is the comparison graph of tip speed ratios after simulation using SMC control, PI control, and ESO+SMC control methods respectively at constant wind speed in the embodiment of the present invention.

[0089] Figure 9 This is the comparison graph of maximum wind energy utilization coefficients after simulation using SMC control, PI control, and ESO+SMC control methods respectively at constant wind speed in the embodiment of the present invention.

[0090] Figure 10 This is the comparison graph of angular velocity tracking response effects after simulation using SMC control, PI control, and ESO+SMC control methods respectively at constant wind speed in the embodiment of the present invention.

[0091] Figure 11 This is the comparison graph of wind turbine output powers after simulation using SMC control, PI control, and ESO+SMC control methods respectively at constant wind speed in the embodiment of the present invention.

[0092] Figure 12 This is the random wind speed graph used in the simulation in the embodiment of the present invention.

[0093] Figure 13 This is the comparison graph of tip speed ratios after simulation using SMC control, PI control, and ESO+SMC control methods respectively at random wind speed in the embodiment of the present invention.

[0094] Figure 14 This is the comparison graph of maximum wind energy utilization coefficients after simulation using SMC control, PI control, and ESO+SMC control methods respectively at random wind speed in the embodiment of the present invention.

[0095] Figure 15 This is the comparison graph of angular velocity tracking response effects after simulation using SMC control, PI control, and ESO+SMC control methods respectively at random wind speed in the embodiment of the present invention.

[0096] Figure 16 This is the comparison graph of wind turbine output powers after simulation using SMC control, PI control, and ESO+SMC control methods respectively at random wind speed in the embodiment of the present invention.

[0097] Figure 17 This is a comparison chart of the average values of the maximum wind energy utilization coefficients obtained by using the SMC control method, the PI control method, and the ESO+SMC control method respectively in the embodiments of the present invention.

[0098] Figure 18 This is a comparison chart of the standard deviations of the maximum wind energy utilization coefficients obtained by using the SMC control method, the PI control method, and the ESO+SMC control method respectively in the embodiments of the present invention.

[0099] Figure 19 This is a schematic diagram of the observation results of the pneumatic torque observer in the embodiments of the present invention.

[0100] Figure 20 This is a schematic diagram of the DC-side voltage curve under random wind speeds in the embodiments of the present invention. Detailed implementation manners

[0101] Next, the technical solutions of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0102] As Figure 1 shown, this embodiment provides a maximum power tracking control method for an offshore wind turbine based on a position sensor, including the following steps:

[0103] S1. Establish a mathematical model of the wind turbine;

[0104] The mathematical model of the wind turbine includes the following mathematical models, where

[0105] The mechanical energy captured by the wind turbine is expressed as:

[0106]

[0107] The tip speed ratio is the ratio of the tip linear speed of the wind turbine impeller to the real-time wind speed, and is expressed as:

[0108]

[0109] The mechanical torque on the wind turbine rotor is expressed as:

[0110]

[0111] where P is the output power of the wind turbine; ρ is the air density; r is the impeller radius; v wind is the actual wind speed passing through the rotor; β is the pitch angle; λ is the tip speed ratio; C Pis the wind energy utilization coefficient; ω is the angular velocity of the motor rotor.

[0112] S2. Establish the mathematical model of the permanent magnet synchronous generator;

[0113] To simplify the system analysis process, the following assumptions are made when building the PMSG mathematical model:

[0114] It is assumed that the rotor permanent magnet magnetic field is sinusoidally distributed in the air gap space, and the induced electromotive force in the stator armature winding is also sinusoidal;

[0115] The saturation of the stator iron core is ignored, and the magnetic circuit is considered linear with unchanged inductance parameters;

[0116] The core eddy current and hysteresis losses are not considered;

[0117] There is no damping winding on the rotor;

[0118] The mathematical model of the permanent magnet synchronous generator includes the following mathematical models, where

[0119] The voltage equation of the permanent magnet synchronous generator is expressed as:

[0120]

[0121]

[0122] The motion equation of the permanent magnet synchronous generator is expressed as:

[0123]

[0124]

[0125] where, u sd , u sq are the voltages of the d-axis and q-axis respectively; i sd , i sq are the currents of the d-axis and q-axis respectively; L s , R s are the stator inductance and stator resistance respectively; J is the moment of inertia; P n is the number of pole pairs; ψ f is the magnetic flux linkage between the permanent magnet and the stator; T e is the electromagnetic torque.

[0126] In this embodiment, the maximum torque control strategy is adopted to achieve the vector control of the permanent magnet synchronous motor; the maximum torque control is also called the maximum torque per unit current output control. It is a current control strategy often used for salient pole permanent magnet synchronous motors. For surface-mounted permanent magnet synchronous motors, the inductance values of the direct axis and the quadrature axis are equal, and its maximum torque control is equivalent to I d = 0 control.

[0127] S3. Design a sliding mode controller;

[0128] Due to the parameter uncertainty of the WECS and other factors not involved in the modeling, it often leads to the inaccuracy of the mathematical model of the real system. Therefore, it is necessary to control the robustness of the system to maintain the stability of the system performance. In this embodiment, SMC is used to design the controller of the system.

[0129] The design of the sliding mode controller mainly includes two parts: the selection of the switching function and the design of the control law. The overall goal of the design is to achieve three elements:

[0130] All state points of the system can reach the sliding surface within a finite time;

[0131] There is a sliding mode region near the sliding surface;

[0132] The sliding mode is asymptotically stable and has good dynamic response quality.

[0133] Among them, the switching function determines the stability and dynamic quality of the sliding mode motion. The control law ensures the reachability of the system state and the existence of the sliding mode. However, due to the chattering phenomenon of SMC, in order to solve the problem of the contradiction between the chattering of SMC and the anti-interference performance, an extended state observer is used to observe the disturbance in real time, and then the observed value is used for feedforward compensation, so as to weaken the system chattering while realizing the rapid suppression of the disturbance.

[0134] The SMC method replaces an n-order system with a first-order system, and can easily control the first-order system by selecting an appropriate function of the tracking error (called the sliding surface or sliding manifold). It can move the system trajectory from its initial point to the sliding surface within a finite time, and then constrain the variable near the sliding surface through the control law. To illustrate the SMC theory, consider a second-order nonlinear system with the following state equation:

[0135]

[0136] where x is the system state variable, u is the system input; f and g are respectively bounded nonlinear matrix functions of the system, and it is assumed that the function g is continuous and invertible. The purpose of control is to obtain the state vector to track the preset state vector in the presence of disturbances and uncertainties. Let e = x - x d be the trajectory error in the state vector x, where x d is the preset state vector. Usually, the time-varying sliding surface of the n-order system is selected as:

[0137]

[0138] where α is a positive number, and for a second-order system:

[0139]

[0140] Therefore, the tracking preset value can be equivalent to ensuring that the value of S is always zero. The error vector can be kept on the sliding mode surface all the time by defining the control law, and its stability condition is:

[0141]

[0142] To ensure the dynamic performance of the PMSG system, the method of adaptive reaching law is adopted. The adaptive reaching rate overcomes the shortcomings of the exponential reaching rate. When the system approaches the sliding mode surface, the exponential term approaches zero, and the variable speed term of -εh(x)sgn(s) plays a key role. When the state variable x enters the sliding mode and moves towards the zero point, the value of the control term sgn(s) continuously decreases due to the continuous decrease of its value, and finally it can reach the stable point.

[0143]

[0144]

[0145] It is easy to prove The system tends to the sliding mode surface in the entire state space and asymptotically reaches the steady state with the selected reaching law after entering the sliding mode.

[0146]

[0147]

[0148] It can be seen that the system can converge to the sliding mode surface in a finite time and the reaching rate is variable;

[0149] Define the state variables of the permanent magnet synchronous generator as:

[0150]

[0151] where, ω ref is the reference speed of the motor; ω is the angular velocity of the motor rotor;

[0152]

[0153] Let The state equation of the system is obtained as:

[0154]

[0155] Define the system sliding mode surface as:

[0156] s = cx 1 +x 2

[0157] It can be obtained that:

[0158]

[0159] Among them, c is a system parameter;

[0160] Then the expression of the sliding mode controller is:

[0161]

[0162] The q-axis reference current is obtained as:

[0163]

[0164] Among them, J is the moment of inertia; T L is the mechanical torque on the wind turbine rotor; P n is the number of pole pairs; ψ f is the magnetic flux linkage between the permanent magnet and the stator.

[0165] S4. Design an aerodynamic torque observer;

[0166] Sliding mode control uses discontinuous switching terms to suppress the influence of external disturbances. When the aerodynamic torque of the WECS changes, to overcome the change of the aerodynamic torque disturbance using sliding mode control, a large switching gain needs to be selected. However, this will exacerbate the chattering in the steady state of the system. In addition, it will also generate transient fluctuations in the rotational speed and reduce the performance of the control system. Therefore, for the stability and accuracy of the control effect, the disturbance torque value obtained by observing with an extended state observer is used to obtain the torque current compensation amount, and feedforward compensation is performed on the reference current to modify and enhance the dynamic response of the system.

[0167] Since the current sampling period is very small, the motion equation of the PMSG is simplified, and the aerodynamic torque T L can be regarded as constant within one period, and the following formula is obtained:

[0168]

[0169] Combining the above formulas, the state equation of the observer can be obtained as:

[0170]

[0171] Among them, u = T e ; y = ω;

[0172] To simplify the observer structure, the above formula is reduced in order to obtain:

[0173]

[0174] Among them, l is the observer gain, and z is the intermediate state variable;

[0175] Discretizing the above equation gives:

[0176]

[0177] where \(i = 0, 1, 2, 3,\cdots\), and the absolute value of the eigenvalue \(\lambda\) of the observation equation is less than 1; the eigenvalue \(\lambda\) of the observation equation can be expressed as:

[0178]

[0179] The reduced-order disturbance torque observation value is:

[0180]

[0181] Input the true measurement values of the rotational speed \(\omega\) and the current \(i\) q into the observer, and we get:

[0182]

[0183] The motor current is the input of the torque observer. Due to some hardware problems such as the encoder accuracy, the actual feedback signal will generate relatively large noise. Therefore, a low-pass filter is introduced at the output end of the observer to reduce interference. The structure of the observer is as Figure 2 shown, then we have:

[0184]

[0185] where \(\delta\) 1 , \(\delta\) 2 is the cut-off frequency of the low-pass filter, and \(K\) t is the motor torque constant;

[0186] The overall structure diagram of the machine side system is as Figure 3 shown. Convert the torque obtained by the torque observer into current, and combine it with the above formula as the feed-forward compensation amount of the anti-disturbance torque to obtain the reference current:

[0187]

[0188] where \(J\) is the moment of inertia; \(T\) L is the mechanical torque on the wind turbine rotor; \(P\) n is the number of pole pairs; \(\psi\) f is the magnetic flux linkage between the permanent magnet and the stator.

[0189] S5. Design the control strategy of the grid-side converter.

[0190] The grid-side converter needs to convert the DC electrical energy output from the machine side into AC and transmit it to the grid. Therefore, it needs to ensure the power quality of the electrical energy transmitted to the grid and, at the same time, play a role in stabilizing the DC bus voltage. Since the fluctuation of the DC bus voltage is very unfavorable for the grid-connected operation of the wind power system, the grid-side converter must have a good control method.

[0191] The main functions that the grid-side conversion device needs to achieve are as follows:

[0192] Stabilize the DC bus voltage, that is, keep the DC voltage output by the machine-side converter stable;

[0193] Implement the inversion function, invert the DC power into AC power, and transmit all the DC electrical energy to the grid;

[0194] Ensure the power quality, that is, the frequency, phase sequence, phase, and waveform of the output AC power should be synchronized with the grid side.

[0195] The grid-side converter and the machine-side converter have the same structure, and it is easy to obtain the mathematical model of the grid-side converter:

[0196]

[0197] In the formula, i gd , i gq respectively represent the d-axis and q-axis components of the grid-side grid-connected current; e d , e q respectively represent the d-axis and q-axis components of the grid-side voltage; u gd , u gq respectively represent the d-axis and q-axis components of the input voltage of the grid-side converter; u dc is the DC bus voltage;

[0198] By using the vector control oriented to the grid voltage, we can obtain:

[0199]

[0200] According to the law of conservation of energy, the power balance relationship between the power input to the DC side and the power transmitted to the grid directly determines the stability of the DC bus voltage: that is, when the power input to the DC side is greater than the power input to the grid, the excess energy will first be stored in the bus capacitor, resulting in an increase in the bus voltage; conversely, it will cause the voltage to decrease. Therefore, the magnitude of the active power transmitted by the grid side determines the stability of the DC bus voltage. As long as the active current component i gd output by the grid side can be quickly controlled, the active power balance can be controlled, and the stability of the DC bus voltage can be achieved.

[0201] In the steady state, assuming that the DC bus voltage is stable and there is no power fluctuation, the active power output by the motor-side rectifier is:

[0202] P s = u sd i sd + u sq i sq = u dc i dc

[0203] P g = u gd i gd = u dc i g

[0204]

[0205] Wherein, P s is the active power output of the motor; P g is the active power transmitted to the power grid; i g is the current input from the DC side to the grid-side inverter; i dc is the current value input from the machine-side rectifier to the DC side; u dc is the DC bus voltage;

[0206] When the active power output by the generator varies with the wind speed, if the active power output from the grid-side converter to the power grid can always be equal to the output power of the machine-side converter, the power on both sides of the DC side capacitor can reach dynamic balance, there is no energy buffer on the DC side, and the DC bus voltage reaches stability. Therefore, the grid-side control is coordinated with the motor-side control to correct the control quantity on the grid side. This method can improve the tracking ability of the grid-side current given value to the output power of the machine side of the system and improve the stability of the DC side bus voltage.

[0207] Under the condition of grid stability, u gd is constant, then:

[0208]

[0209] Wherein, u gd is the d-axis component of the input voltage of the grid-side converter; i gd is the d-axis component of the input current of the grid-side converter; u sd , u sq are the components of the grid-connected voltage on the d-axis and q-axis respectively; i sd , i sq are the components of the grid-connected current on the d-axis and q-axis respectively;

[0210] The above formula shows that the DC side capacitor voltage is simultaneously affected by the active power output by the PMSG and the d-axis current component i gdThe influence. Therefore, the mapped quantity of the control information of the system grid-side converter is incorporated into the control of the grid-side converter to achieve coordinated control on the grid side, making the control performance of the DC-side capacitor voltage more stable.

[0211] The direct cause of the DC-side voltage fluctuation is that there is a certain lag between the given value and the actual value of the d-axis current component generated by the voltage outer loop of the grid-side converter. Therefore, combined with the above formula, is used as a feedforward compensation quantity. This value is used to compensate the given value of the d-axis current of the current inner loop of the grid-side converter, so that a new given value of the d-axis current of the current inner loop of the grid-side converter can be obtained

[0212] From Figure 4 it can be seen that the improved control strategy of the grid-side converter still adopts the traditional vector control based on grid voltage orientation. The difference lies in the given value output by the d-axis speed outer loop, where a change amount representing the change in the active power output of the permanent magnet generator is added. The control target is single and easy to achieve. Therefore, when the wind speed changes and causes the power output by the generator to change, the given value of the current inner loop of the grid-side converter can promptly feedback this change, and then through the current inner loop control, the d-axis current can quickly track the given value, so that the active power input by the grid-side converter to the grid and the active power input by the machine-side converter to the DC side reach balance, reducing the fluctuation of the DC-side voltage, and finally achieving the stability of the DC-side bus voltage.

[0213] To verify the correctness of the load torque observer and the feasibility of the feedforward compensation scheme, in this embodiment, Matlab / Simulink is used to establish a PMSG wind power generation system for simulation. Among them, the PMSG is controlled by the field-oriented decoupling strategy with zero d-axis current. The control block diagram of the entire system is as Figure 5 shown, the main parameters of the system are shown in Table 1, and the controller parameters and load torque observer parameters are shown in Table 2.

[0214] Table 1 Main parameters of the permanent magnet wind power generation system

[0215]

[0216] Table 2 Main parameters of the controller

[0217]

[0218] Figure 6 is the wind speed map of the coastal area of Shanghai from January to November 2019. It can be seen that its average wind speed is about 10 m / s. Therefore, the control effects of different controllers under the condition of constant wind speed (10 m / s) are compared. The control effects are as Figures 7 to 11 shown.

[0219] It can be seen that under a constant wind speed, the MPPT control effects of the three control methods adopted on the WECS are not very different. This is because the PI parameters are well designed under a constant wind speed, and the system has high stability. However, it can still be observed that there is a certain overshoot in the system under PI control, which is somewhat insufficient compared to the control strategy proposed in this embodiment. At the same time, the system response rapidity under SMC is slightly insufficient, but the addition of the load torque observer significantly compensates for the shortcoming of the slow system response. Therefore, the control strategy proposed in this embodiment is effective and has good control effects. Figures 7 to 11

[0220] Figure 12 To better demonstrate the control effects, the white noise module in Simulink is used to simulate random wind speeds, as Figure 12 shown. Under random wind speeds, the PI controller, the sliding mode controller, and the sliding mode controller with an aerodynamic torque observer are respectively used to simulate the system, and the obtained results are as Figures 13 to 16 shown.

[0221] Figure 12 This is the random wind speed graph used for simulation, and its value fluctuates around a wind speed of 10 m / s. It can be seen from Figure 13 and 14 that under the simulated random wind speed fluctuations, due to the robustness advantages of SMC, the fluctuations of the tip speed ratio and the maximum wind energy utilization coefficient are significantly weakened when the wind speed changes, while the PI control is prone to obvious fluctuations under fluctuating wind speeds. At the simulation time of 1 - 1.5 s, the maximum wind energy utilization coefficient under PI control is as low as 0.44, which has a large gap with the reference value of 0.48. At the same time, it can be observed in Figure 13 that when only SMC is used, the λ value of the WECS has obvious chattering. After adding the observer, due to the feed-forward compensation of the aerodynamic torque observer, the rising speed of the system is much faster than that when only SMC is used, and its chattering is also relatively reduced.

[0222] It can be seen from Figure 15 that the speed of the SMC with an observer approaches the green reference value very quickly after the system runs, while when only SMC is used, the speed approaches the reference value at about 1.5 s. In addition, the speed under PI control follows the wind speed fluctuations and it is very difficult to reach stability. It is not difficult to see that the control strategy adopted in this embodiment is very effective for the speed control of the PMSG.

[0223] It can be seen from Figure 16It can be seen that the output power of the wind turbine under PI control has been significantly reduced compared to that under SMC. It can be seen that under PI control, the utilization of wind energy is far from sufficient. Therefore, it can be seen that the performance of PI control in dealing with random inputs of complex systems is poor, while the anti-interference performance of the system with SMC has been significantly improved. In addition, from the local enlarged view, it can be seen that the SMC method with an observer has improved in terms of response speed, and the output power from 0 to 1 s far exceeds the other two control methods.

[0224] Figure 17 and Figure 18 are the average value and standard deviation of the wind energy utilization coefficient of different control strategies under random wind speed. It is not difficult to see that the control strategy proposed in this embodiment has better performance compared to SMC and PI, and its average value is closer to the reference value C P of 0.48, and the standard deviation is reduced by about 10% compared to PI, which greatly improves the performance of the WECS.

[0225] In summary, the control method proposed in this embodiment greatly improves the performance of the entire control system in terms of chattering suppression, response speed, anti-disturbance, etc.

[0226] Figure 19 is the observation result of the pneumatic torque observer. The green dashed line in it is the reference torque. It can be seen that the observed torque is very close to the reference value and meets the standard. Therefore, the effect of the observer is good and its performance is stable in the system, which plays an important role in the accurate operation of the control method proposed in this embodiment.

[0227] Figure 20 is the DC-side voltage curve under random wind speed. It can be seen that U dc quickly enters the stable state after the initial overshoot. Under the condition of large wind speed fluctuations, U dc can still be stabilized at 800V. Therefore, the overall control strategy proposed is proven to be effective, which can balance the power on the machine side and the grid side and maintain the stability of the DC bus voltage.

[0228] The simulation results show that due to the feedback of the torque estimation value, the sign function gain in the proposed sliding mode control law has the self-adjusting ability based on the random wind speed condition. Therefore, it helps to eliminate chattering and ensure the reliability of the MPPT sliding mode control signal. Compared with only using the SMC method, the proposed observer can help improve the response speed of the system. At the same time, its anti-interference performance is significantly improved compared with using the PI method under random wind speed.

[0229] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A maximum power tracking control method for an offshore wind turbine based on a position sensor, characterized in that, it includes the following steps: S1. Establish a mathematical model of the wind turbine; in step S1, the mathematical model of the wind turbine includes the following mathematical models, where, the mechanical energy captured by the wind turbine is expressed as: the tip speed ratio is the ratio of the tip linear speed of the wind turbine impeller to the real-time wind speed, expressed as: the mechanical torque on the wind turbine rotor is expressed as: Wherein, P is the output power of the wind turbine; ρ is the air density; r is the impeller radius; v wind is the actual wind speed passing through the wind wheel; β is the pitch angle; λ is the tip speed ratio; C P is the wind energy utilization coefficient; ω is the angular velocity of the motor rotor S2. Establish a mathematical model of the permanent magnet synchronous generator; S3. Design a sliding mode controller; in step S3, the method for designing the sliding mode controller is: define the state variables of the permanent magnet synchronous generator as: where ω ref is the reference speed of the motor; ω is the angular velocity of the motor rotor; Let The state equation of the system is obtained as follows: define the system sliding mode surface as: s = cx 1 + x 2 it can be obtained that: where c is a system parameter; then the expression of the sliding mode controller is: obtain the q-axis reference current as: where, J is the moment of inertia; T L is the mechanical torque on the wind turbine rotor; P n is the number of pair stages; ψ f is the magnetic flux linkage between the permanent magnet and the stator S4. Design an aerodynamic torque observer; S5. Design a grid-side converter control strategy; in step S5, the method for designing the grid-side converter control strategy is: in the steady state, assuming that the DC bus voltage is stable and there is no power fluctuation, the active power output by the motor-side rectifier is: P s = u sd i sd + u sq i sq = u dc i dc P g = u gd i gd = u dc i g Among them, P s is the active power output by the motor; P g is the active power transmitted to the power grid; i g is the current input from the DC side to the grid-side inverter; i dc is the current value input from the machine-side rectifier to the DC side; u dc is the DC bus voltage; when the active power output by the generator changes with the wind speed, coordinate the grid-side control and the motor-side control, and correct the control quantity of the grid side; Under the condition of power grid stability, u gd is constant, then: where, u gd is the d-axis component of the input voltage of the grid-side converter; i gd is the d-axis component of the input current of the grid-side converter; u sd , u sq are the components of the grid-connected voltage on the d-axis and q-axis respectively; i sd , i sq are the components of the grid-connected current on the d-axis and q-axis respectively; It is used as a feed-forward compensation amount to compensate the d-axis current given value of the inner current loop of the grid-side converter.

2. A maximum power tracking control method for an offshore wind turbine based on a position sensor according to claim 1, characterized in that, in step S2, the mathematical model of the permanent magnet synchronous generator includes the following mathematical models, where, the voltage equation of the permanent magnet synchronous generator is expressed as: the motion equation of the permanent magnet synchronous generator is expressed as: Among them, u sd , u sq are the voltages on the d-axis and q-axis respectively; i sd , i sq are the currents on the d-axis and q-axis respectively; L s , R s are the stator inductance and stator resistance respectively; J is the moment of inertia; P n is the number of pole pairs; ψ f is the magnetic flux linkage between the permanent magnet and the stator; T e is the electromagnetic torque.

3. A maximum power tracking control method for an offshore wind turbine based on a position sensor according to claim 1, characterized in that, in step S4, the method for designing the aerodynamic torque observer is: the state equation of the observer is: Among them, u = T e ; y = ω; in order to simplify the observer structure, perform a reduced-order processing on the above formula to obtain: wherein, l is the observer gain, and z is the intermediate state variable; discretize the above formula to obtain: where i = 0, 1, 2, 3…, the absolute value of the eigenvalue λ of the observation equation is less than 1; the eigenvalue λ of the observation equation can be expressed as: the reduced-order disturbance torque observation value is: Input the true measured values of the rotational speed ω and the current i q into the observer to obtain: introduce a low-pass filter at the output end of the observer to reduce interference, then there is: Among them, δ 1 , δ 2 is the cut-off frequency of the low-pass filter, and K t is the motor torque constant; convert the torque obtained by the torque observer into current, and combine it with the above formula as the feedforward compensation amount of the anti-disturbance torque to obtain the reference current: Among them, J is the moment of inertia; T L is the mechanical torque on the wind turbine rotor; P n is the number of pair stages; ψ f is the magnetic flux linkage between the permanent magnet and the stator.

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