Wind turbine generator inertia process load optimization control method based on wind speed estimator

Abstract

The invention discloses a wind turbine generator inertia process load optimization control method based on a wind speed estimator, and the method comprises the steps: employing the wind speed estimator and a feedforward controller to calculate the feedforward pitch angle of a wind turbine generator according to the current wind speed, and the wind speed estimator is generated through training of a width learning algorithm; adopting a feedback controller to calculate a feedback pitch angle of the wind turbine generator according to the generator rotating speed of the wind turbine generator and the current wind speed; calculating the pitch angle deviation of the wind turbine generator according to the frequency monitoring value of the wind turbine generator; according to the feed-forward pitch angle, the feedback pitch angle and the pitch angle deviation, the active power of the wind turbine generator is calculated; and performing active power control on the wind turbine generator according to the active power.

Description

Technical Field

[0001] The present invention relates to the technical field of power system optimization control, and more specifically, to a method for optimizing the inertia process load of a wind turbine generator set based on a wind speed estimator. Background Art

[0002] As the proportion of wind power connected to the grid continues to rise, the proportion of wind power in local areas of my country has exceeded 70% of the power supply. High-proportion wind power systems show low anti-interference, weak inertia and weak frequency / voltage support characteristics, and grid disturbances such as fault voltage drop, inertia response, and frequency fluctuations occur from time to time. Especially in the context of the development of new energy of "carbon peak and carbon neutrality", the penetration rate of wind power is getting higher and higher, the equivalent inertia of the power system is constantly decreasing, and the frequency of grid disturbances will also become higher and higher. The frequency regulation capability of traditional thermal power units alone can no longer fully meet the needs of maintaining the stability of the grid frequency. It is necessary to require new energy units such as wind power to have frequency response characteristics and frequency regulation control capabilities similar to conventional thermal power units.

[0003] However, in order to pursue the best wind energy utilization efficiency, the generator speed and grid frequency are completely decoupled, which makes it difficult for wind turbines to respond promptly to fluctuations in grid frequency. This puts forward corresponding requirements on the ability of wind turbines to actively support the grid, so that they have inertial response capabilities similar to conventional thermal power units. That is, when the grid frequency drops due to a surge in load or power outage, the wind turbines can quickly increase active power output and inject active power into the grid to support and raise the grid frequency.

[0004] At present, existing literature has proposed a series of practical methods for the strategy and implementation of inertia response control of wind turbines, and has also verified them from a simulation perspective. However, they have not considered the coordination and linkage between the realization of the primary frequency regulation function of the wind turbine and the power output loss and the fatigue load control of the mechanical system. For wind turbines that switch between normal power generation mode and inertia response mode for a long time, their power generation loss and the fatigue load of the mechanical system structure itself are often ignored. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a method for optimizing the control of inertia process load of a wind turbine set based on a wind speed estimator.

[0006] According to one aspect of the present invention, a method for optimizing control of inertia process load of a wind turbine generator system based on a wind speed estimator is provided, comprising:

[0007] A wind speed estimator and a feedforward controller are used to calculate the feedforward pitch angle of the wind turbine according to the current wind speed, wherein the wind speed estimator is trained and generated using a width learning algorithm;

[0008] A feedback controller is used to calculate the feedback pitch angle of the wind turbine according to the generator speed of the wind turbine and the current wind speed;

[0009] Calculate the pitch angle deviation of the wind turbine generator set according to the frequency monitoring value of the wind turbine generator set;

[0010] Calculate the active power of the wind turbine according to the feedforward pitch angle, feedback pitch angle and pitch angle deviation;

[0011] Active power control is performed on the wind turbine according to the active power.

[0012] Optionally, a wind speed estimator and a feedforward controller are used to calculate the feedforward pitch angle of the wind turbine according to the current wind speed, including:

[0013] A wind speed estimator is used to predict the incoming wind speed of the wind turbine according to the current wind speed, and the predicted incoming wind speed of the wind turbine is obtained;

[0014] A feedforward controller is used to calculate the feedforward pitch angle of the wind turbine according to the blade pitch angle matched with the incoming flow prediction wind speed.

[0015] Optionally, a feedback controller is used to calculate a feedback pitch angle of the wind turbine according to a generator speed of the wind turbine and a current wind speed, including:

[0016] Estimate the rotation speed of the wind turbine generator set according to the current rotation speed of the wind turbine generator set and the current wind speed, and output the estimated rotation speed of the wind turbine generator set;

[0017] A feedback controller is used to calculate the feedback pitch angle based on the estimated rotational speed.

[0018] Optionally, estimating the rotation speed of the wind turbine generator set according to the current rotation speed of the wind turbine generator set and the current wind speed, and outputting the estimated rotation speed of the wind turbine generator set, includes:

[0019] The current speed is input to the feedforward controller, and the initial estimated speed of the wind turbine is output;

[0020] Input the current wind speed to the wind speed estimator, and output the initial estimated wind speed of the wind turbine;

[0021] A pitch command of the wind turbine generator set is determined according to an initial estimated rotational speed and an initial estimated wind speed, and an estimated rotational speed that meets the pitch command is determined iteratively.

[0022] Optionally, calculating the pitch angle deviation of the wind turbine generator set according to the frequency monitoring value of the wind turbine generator set includes:

[0023] Compare the frequency monitoring value with the grid set power frequency 50Hz to obtain the frequency deviation;

[0024] Calculate the power difference of the wind turbine according to the frequency deviation;

[0025] The pitch angle deviation of the wind turbine is calculated based on the power difference.

[0026] According to another aspect of the present invention, there is provided a wind turbine inertia process load optimization control device based on a wind speed estimator, comprising:

[0027] A first calculation module is used to calculate the feedforward pitch angle of the wind turbine according to the current wind speed by using a wind speed estimator and a feedforward controller, wherein the wind speed estimator is generated by training using a width learning algorithm;

[0028] A second calculation module is used to calculate a feedback pitch angle of the wind turbine generator set according to a generator speed of the wind turbine generator set and a current wind speed by using a feedback controller;

[0029] A third calculation module is used to calculate the pitch angle deviation of the wind turbine generator set according to the frequency monitoring value of the wind turbine generator set;

[0030] A fourth calculation module, used to calculate the active power of the wind turbine according to the feedforward pitch angle, the feedback pitch angle and the pitch angle deviation;

[0031] The control module is used to control the active power of the wind turbine according to the active power.

[0032] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and the computer program is used to execute the method described in any one of the above aspects of the present invention.

[0033] According to another aspect of the present invention, an electronic device is provided, comprising: a processor; a memory for storing instructions executable by the processor; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of the above aspects of the present invention.

[0034] Therefore, the present invention is based on a wind speed estimator and focuses on studying how to achieve the coordination between the inertia response function of the unit and the power generation loss and fatigue load control. A wind turbine inertia response control strategy based on a width learning estimator is proposed. The width learning algorithm is used to accurately predict and perceive the incoming flow characteristics of the unit. Combined with the perceived incoming flow characteristics, the wind turbine blade pitch angle is adjusted in a timely manner. While achieving the inertia support control of the wind turbine, the power generation loss caused by excessive pitch angle reservation is reduced, the wind turbine load control is optimized, and the fatigue load of the main structural components of the wind turbine is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] A more complete understanding of exemplary embodiments of the present invention may be obtained by referring to the following drawings:

[0036] Figure 1It is a flow chart of a method for optimizing the control of inertia process load of a wind turbine set based on a wind speed estimator provided by an exemplary embodiment of the present invention;

[0037] Figure 2 It is a schematic diagram of active power-frequency droop characteristics of a wind turbine generator set with fast frequency response provided by an exemplary embodiment of the present invention;

[0038] Figure 3 is a schematic diagram of a blade pitch change process (different pitch change rates) provided by an exemplary embodiment of the present invention;

[0039] Figure 4 is a schematic diagram of tower bottom load under different blade pitch rate conditions provided by an exemplary embodiment of the present invention;

[0040] Figure 5 is a schematic diagram of a relationship curve between tip speed ratio and power coefficient under different pitch angles provided by an exemplary embodiment of the present invention;

[0041] Figure 6 is a schematic diagram of power curves under different pitch angle conditions provided by an exemplary embodiment of the present invention;

[0042] Figure 7 is a schematic diagram of the principle of a width learning estimator provided by an exemplary embodiment of the present invention;

[0043] Figure 8a and Figure 8b They are respectively schematic diagrams of a rotation speed and pitch angle feedforward control strategy based on a width learning algorithm wind speed estimator provided by an exemplary embodiment of the present invention;

[0044] Fig. 9 is a schematic diagram of an inertia response control strategy based on a wind speed estimator provided by an exemplary embodiment of the present invention;

[0045] Fig.10 is a structural schematic diagram of a wind turbine inertia process load optimization control device based on a wind speed estimator provided by an exemplary embodiment of the present invention;

[0046] Fig.11 This is a structure of an electronic device provided by an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0047] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described here.

[0048] It should be noted that the relative arrangement of components and steps, the numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

[0049] Those skilled in the art can understand that the terms "first" and "second" in the embodiments of the present invention are only used to distinguish different steps, devices or modules, etc., and neither represent any specific technical meaning nor indicate the necessary logical order between them.

[0050] It should also be understood that, in the embodiments of the present invention, “plurality” may refer to two or more than two, and “at least one” may refer to one, two or more than two.

[0051] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more, unless explicitly limited or otherwise indicated in the context.

[0052] In addition, the term "and / or" in the present invention is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in the present invention generally indicates that the associated objects before and after are in an "or" relationship.

[0053] It should also be understood that the description of the various embodiments of the present invention focuses on the differences between the various embodiments, and the same or similar aspects thereof can be referenced to each other, and for the sake of brevity, they will not be described one by one.

[0054] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0055] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0056] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0057] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0058] Embodiments of the present invention can be applied to electronic devices such as terminal devices, computer systems, servers, etc., which can operate with many other general or special computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, servers, etc. include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, large computer systems, and distributed cloud computing technology environments including any of the above systems, etc.

[0059] Electronic devices such as terminal devices, computer systems, servers, etc. can be described in the general context of computer system executable instructions (such as program modules) executed by computer systems. Generally, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in a distributed cloud computing environment, where tasks are performed by remote processing devices linked through a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media including storage devices.

[0060] Exemplary Methods

[0061] Figure 1 FIG. 1 is a flow chart of a method for optimizing the control of the inertia process load of a wind turbine set based on a wind speed estimator provided by an exemplary embodiment of the present invention. This embodiment can be applied to electronic devices, such as Figure 1 As shown, the wind turbine inertia process load optimization control method 100 based on the wind speed estimator includes the following steps:

[0062] Step 101, using a wind speed estimator and a feedforward controller to calculate a feedforward pitch angle of a wind turbine according to a current wind speed, wherein the wind speed estimator is generated by training using a width learning algorithm;

[0063] Step 102, using a feedback controller to calculate a feedback pitch angle of the wind turbine according to a generator speed of the wind turbine and a current wind speed;

[0064] Step 103, calculating the pitch angle deviation of the wind turbine generator set according to the frequency monitoring value of the wind turbine generator set;

[0065] Step 104, calculating the active power of the wind turbine according to the feedforward pitch angle, the feedback pitch angle and the pitch angle deviation;

[0066] Step 105: performing active power control on the wind turbine generator set according to the active power.

[0067] Specifically, the impact and fatigue load of the grid frequency disturbance process on the unit are inevitable. The present invention focuses on how to use corresponding control strategies and methods to reduce the impact load and fatigue damage of the grid frequency disturbance process on the mechanical structure of the wind turbine as much as possible while achieving the inertia response of the unit. Based on the double-fed wind turbine, the patent of this invention designs a wind speed estimator based on the width learning method. Based on the wind speed estimator, the real-time pre-prediction and perception of the incoming flow characteristics of the wind turbine are used to advance the pitch action, so as to achieve frequency and active power support while weakening the impact load and fatigue damage of the disturbance process on the mechanical system of the unit.

[0068] With the continuous expansion of wind power installed capacity, the impact of wind power grid connection on the power system continues to emerge. The inertia response capability of wind turbines has become one of the technical indicators for wind turbine grid connection. It requires that wind turbines can maintain grid-connected operation without being disconnected from the grid under a certain degree of grid frequency disturbance. That is, when the grid frequency is within the operating range required by GB / T 19963 "Technical Regulations for Wind Farm Access to Power System", wind turbines should be able to operate normally.

[0069] In view of the inertia response characteristics of wind turbines, wind turbines use their own active power control system, stand-alone or additional independent control devices to complete active power-frequency droop characteristic control, so that they have the ability to participate in the rapid adjustment of grid frequency at the grid connection point. The fast frequency response active power-frequency droop characteristic is achieved by setting the frequency and active power broken line function, that is:

[0070]

[0071] Where: f d is the fast frequency response dead zone, Hz; f n is the system rated frequency, 50Hz; P n is the rated power of the wind turbine, MW; δ% is the fast frequency response adjustment rate of the wind turbine; P0 is the initial value of the active power of the wind turbine, MW.

[0072] That is, Figure 2 As shown in the figure, under different frequency amplitude fluctuation conditions, the grid requires different active power supported by the unit. When the grid frequency drops below 49.8Hz, the unit needs to be able to support 10% of the rated power injected into the grid to maintain the safe and stable operation of the unit and the grid. At present, there are relevant specifications for frequency deviation adaptability testing of wind turbines. The specific test requirements are shown in Table 1.

[0073] Table 1 Wind turbine frequency deviation adaptability test content

[0074]

[0075] Since the wind turbine is a traditional power electronic grid-connected unit, the inverter monitors the grid system frequency in real time. When the grid system frequency is disturbed due to sudden changes in the grid system load, the inverter tracks and adjusts the frequency of the unit's output power in real time. This adjustment process will cause the electromagnetic torque of the wind turbine generator to oscillate. The electromagnetic torque oscillation will destroy the dynamic load balance of the wind turbine transmission chain system, cause transmission chain torsional vibration, and significantly increase the fatigue and impact load of key wind turbine components such as the transmission chain and tower, thereby causing the transmission chain shaft system torsional vibration instability and causing safety accidents; in addition, since the electromagnetic torque disturbance will cause the wind turbine to change the pitch violently (to suppress the increase in generator speed and generator power), the wind rotor aerodynamic torque changes, thereby significantly increasing the load on the root of the wind turbine blade and the front and rear directions of the tower. Especially for doubly fed wind turbines that have a strong coupling effect with the grid, the impact load and fatigue damage of the unit mechanical system caused by grid frequency disturbance are more significant.

[0076] On the one hand, the electromagnetic torque oscillation of the wind turbine generator excites the transmission chain shaft system or a certain order mode in the left and right directions of the tower to resonate, which in turn causes a large impact load, posing a threat to the structural safety of the wind turbine itself. On the other hand, a grid frequency disturbance process not only causes an impact load on the mechanical system of the wind turbine, but also causes a fatigue damage accumulation process on the mechanical system components of the unit. During the entire life cycle, frequent grid disturbance processes cannot be ignored for the cumulative fatigue load and damage to the unit.

[0077] For a wind turbine, when the airflow flows through the rotating swept surface of the wind turbine blade, it generates a huge thrust on the blade, which is then transmitted to the bottom of the tower through the wind turbine transmission chain. Existing research literature shows that during the change of the blade pitch angle, the blade pitch rate has a great influence on the load characteristics of the unit. In order to facilitate the analysis of the relationship between the blade pitch rate and the load characteristics of the wind turbine structural components, the present invention simplifies the mechanical model of each structural component of the wind turbine. The simplified linear model of the wind turbine can be expressed as:

[0078]

[0079] In the formula, Ω r is the wind rotor speed; J is the moment of inertia of the wind turbine; M r is the impeller torque. According to the blade element theory, the relationship between the blade root swing bending moment, flapping bending moment, wind speed and pitch angle can be expressed as:

[0080]

[0081] Where M zi represents the flapping moment of the i-th blade; F xi represents the force in the flapping direction of the i-th blade; M xirepresents the swing bending moment of the i-th blade; F zi Indicates the force on the ith blade in the swing direction; h Mz ,h Fx ,h Mx ,h Fz , k Mz , k Fx , k Mx , k Fz It represents the coefficient after linearization near the working point, which can be expressed as:

[0082]

[0083] The aerodynamic torque of the impeller is T a , axial force F a , Tower pitch bending moment M tilt , Tower overturning moment M roll It can be expressed as:

[0084]

[0085] In the formula, φ i represents the impeller azimuth angle of the i-th blade; T a Indicates the impeller aerodynamic torque; F a Indicates the impeller axial force; M tilt Represents the tower pitch bending moment; M roll Represents the tower overturning bending moment.

[0086] At present, most wind turbines use independent pitch control, collect the bending moment signals at the roots of the three blades at the same time, and obtain the pitching moment and overturning moment of the wind turbine through Kellermann coordinate transformation. Then, the pitching moment and overturning moment are inversely transformed by Kellermann to obtain the blade angles that need to be adjusted for the three blades, and then the pitch angles of the three blades are obtained.

[0087]

[0088] In order to control the load on the unit, it is necessary to continuously adjust the pitch angles of the three blades, i.e. the pitch change process. Figure 3 Considering the structural inertia, time constant and other factors, the speed of pitch angle adjustment, that is, the blade pitch rate, will have an important impact on the load of the unit mechanical system, such as Figure 4 shown.

[0089] At present, according to different energy sources, the methods for wind turbines to participate in frequency regulation mainly include rotor kinetic energy control, power reserve control, and wind-storage joint control. The power reserve mode can be summarized into two modes: variable pitch angle control and overspeed control. The frequency regulation control of wind turbines using variable pitch angle control is to control the active power output of the wind turbine by increasing the pitch angle of the wind turbine blades to make it lower than the power output in the maximum power output tracking operation mode, and use the difference in active power output as reserve power to support the frequency adjustment process of the power grid. Based on the traditional delayed signal elimination phase-locking principle, Wang Jisong et al. proposed a specific delayed signal elimination phase-locking method that takes into account the frequency change of the system. Taking the doubly fed wind turbine as the research object, under the premise that the wind turbine has reserve power, the primary frequency regulation function of the wind turbine is realized by combining virtual inertia with variable pitch control. The active power output of the wind turbine can be expressed as:

[0090] P(v i )=0.5ρAv i 3 C p (λ,β) (7)

[0091]

[0092] Where, ρ is the air density, kg / m3; A is the impeller projected area to the wind, m2; v i is the wind speed in the ith interval, m / s; C p (λ,β) is the power coefficient of the ith interval; λ is the tip speed ratio; β is the blade pitch angle, rad; R is the radius of the wind turbine blade, m; ω is the impeller speed, rad / s. The wind turbine blade pitch angle is the key variable of the power coefficient. The power coefficient curve of the wind turbine under different pitch angle settings is as follows Figure 5 shown.

[0093] Under different tip speed ratio conditions, the larger the pitch angle of the wind turbine blades, the smaller the active power output of the unit. Under most working conditions, controlling the pitch angle change can reduce the load of the wind turbine, but it includes mechanical control components, which causes the inertia of the pitch angle change to be large, so variable pitch control is generally suitable for medium and high wind speed conditions. Variable pitch control can participate in power system frequency adjustment for a long time, but it is not suitable for the full wind speed range. When the wind speed changes drastically, variable pitch control will rapidly reduce the service life of the wind turbine.

[0094] like Figure 6 As shown, at a certain wind speed v i Under the condition, when the wind turbine blade pitch angle β a Increase to β b When the power coefficient of the wind turbine is p (λa ,β a ) changes to C p (λ b ,β b ), resulting in a power output difference, namely the reserve power, which can be expressed as:

[0095] ΔP(v i )=0.5ρAv i 3 (C p (λ a ,β a )-C p (λ b ,β b )) (10)

[0096] In the formula, C p (λ a ,β a ) is the power coefficient of the wind turbine before the change, C p (λ b ,β b ) is the power coefficient of the wind turbine after the change.

[0097] The impact and fatigue load of the grid frequency disturbance process on the unit are inevitable. The present invention focuses on how to use corresponding control strategies and methods to reduce the impact load and fatigue damage of the grid frequency disturbance process on the mechanical structure of the wind turbine as much as possible while achieving the inertia response of the unit. For the doubly fed wind turbine, the present invention patent is based on the width learning method and designs a wind speed estimator. Based on the real-time pre-prediction and perception of the incoming flow characteristics of the wind turbine by the wind speed estimator, the pitch action is changed in advance, and the impact load and fatigue damage of the disturbance process on the mechanical system of the unit are weakened, while achieving frequency and active power support.

[0098] The present invention proposes a load optimization control strategy for the inertia response process of a wind turbine based on a wind speed estimator. The control algorithm based on the wind speed estimator mainly adopts a width learning method to establish a wind speed prediction model, accurately predict the wind speed in the incoming flow direction, and calculate the wind speed and wind direction changes at the hub center in advance through frequency domain analysis and Kalman filtering. A feedforward control algorithm is designed and combined with conventional pitch control to give pitch instructions in advance and perform pitch actions in advance, which not only ensures the stability of speed control, but also reduces the changes in the thrust of the wind rotor plane, thereby reducing the fatigue load at the root of the blades and the bottom of the tower.

[0099] Among them, the principle of width learning estimator is as follows Figure 7The basic strategy logic of the wind turbine feedforward control based on the wind speed estimator is shown in Figure 8. By predicting the incoming wind speed, estimating the appropriate blade pitch angle, and comparing the pitch angle with the current wind speed conditions, the pitch angle of the unit is adjusted in advance, and the pitch rate can be based on the following formula:

[0100]

[0101] In the formula, is the pitch rate, β(v(t)) represents the pitch angle when the wind speed is v(t); β(v(t+τ)) represents the pitch angle when the wind speed is v(t+τ); τ represents the prediction time.

[0102] The basic assumption of the present invention is that during the grid frequency drop process, the wind turbine adopts the pitch angle standby mode for inertia support. This inertia support control scheme is conservative. Although it can achieve the effect of inertia response and active support of the grid, it loses power generation and cannot predict the incoming wind conditions to achieve active control of the unit to reduce the load. This paper designs a wind speed estimator based on a width learning algorithm. According to the wind speed predicted by the estimator and the actual demand for the current reserved pitch angle, the pitch angle of the wind turbine blades is adjusted in real time and dynamically. While ensuring a certain amount of active power reserve to support the grid frequency, it reduces the loss of power generation and reduces the fatigue load of the unit.

[0103] The inertia response control strategy logic based on the wind speed estimator is as follows Fig. 9 As shown in the figure. Based on the inertia response control strategy of the wind speed estimator, a grid frequency monitor and a corresponding reserved pitch angle feedback calculation module are introduced on the basis of wind speed estimation and prediction. The grid frequency monitor monitors the grid frequency in real time and converts the monitored grid frequency f M Compared with the power grid set frequency of 50Hz, the frequency deviation Δf is calculated; combined with Figure 2 In response to the relevant needs of wind turbine frequency regulation, the active power ΔP that the wind turbine needs to support in the current state is calculated. Based on the active power support shortage required for a frequency regulation process, the wind turbine controller calculates the pitch angle of the wind turbine under the current wind speed conditions.

[0104] At a certain wind speed v i Under this condition, the pitch angle of the wind turbine blade is β FF Change to β FB When the backup power is:

[0105] ΔP(v i )=0.5ρAv i 3 (C p (λ i ,β FF )-Cp (λ i ,β FB )) (12)

[0106] Therefore, the present invention takes into account that the existing inertia response control strategy of wind turbines ignores the power output loss of wind turbines and the load constraints of the mechanical system of the wind turbines, and proposes a load optimization control strategy for the inertia response process of wind turbines based on a wind speed estimator. While realizing the inertia response control of the wind turbines, the active output loss in the frequency modulation process and the fatigue load of the mechanical components of the wind turbines are reduced, which is of great significance for optimizing the load design of wind turbines, improving the "grid-friendly" characteristics of wind turbines, and ensuring the safe and stable operation of the wind turbines and the power grid.

[0107] Exemplary Devices

[0108] Fig.10 FIG. 1 is a schematic diagram of a wind turbine inertia process load optimization control device based on a wind speed estimator provided by an exemplary embodiment of the present invention. Fig.10 As shown, the device 1000 includes:

[0109] A first calculation module 1010 is used to calculate the feedforward pitch angle of the wind turbine according to the current wind speed by using a wind speed estimator and a feedforward controller, wherein the wind speed estimator is generated by training using a width learning algorithm;

[0110] A second calculation module 1020 is used to calculate a feedback pitch angle of the wind turbine according to a generator speed of the wind turbine and a current wind speed using a feedback controller;

[0111] A third calculation module 1030 is used to calculate the pitch angle deviation of the wind turbine generator set according to the frequency monitoring value of the wind turbine generator set;

[0112] A fourth calculation module 1040, configured to calculate the active power of the wind turbine according to the feedforward pitch angle, the feedback pitch angle and the pitch angle deviation;

[0113] The control module 1050 is used to control the active power of the wind turbine generator set according to the active power.

[0114] Optionally, the first computing module includes:

[0115] A prediction submodule, used to use a wind speed estimator to predict the incoming wind speed of the wind turbine according to the current wind speed, and obtain the predicted incoming wind speed of the wind turbine;

[0116] The matching submodule is used to calculate the feedforward pitch angle of the wind turbine set by using a feedforward controller to match the blade pitch angle with the incoming flow predicted wind speed.

[0117] Optionally, the second computing module includes:

[0118] An estimation submodule, used to estimate the rotation speed of the wind turbine generator set according to the current rotation speed of the wind turbine generator set and the current wind speed, and output the estimated rotation speed of the wind turbine generator set;

[0119] The first calculation submodule is used to calculate the feedback pitch angle according to the estimated rotation speed using a feedback controller.

[0120] Optionally, the estimation submodule includes:

[0121] A first output unit, used to input the current rotation speed into the feedforward controller and output an initial estimated rotation speed of the wind turbine;

[0122] A second output unit is used to input the current wind speed into the wind speed estimator and output an initial estimated wind speed of the wind turbine;

[0123] The determination unit is used to determine the pitch command of the wind turbine according to the initial estimated rotation speed and the initial estimated wind speed, and iteratively determine the estimated rotation speed that meets the pitch command.

[0124] Optionally, the third computing module includes:

[0125] The comparison submodule is used to compare the frequency monitoring value with the power grid set frequency of 50Hz to obtain the frequency deviation;

[0126] The second calculation submodule is used to calculate the power difference of the wind turbine generator set according to the frequency deviation;

[0127] The third calculation submodule is used to calculate the pitch angle deviation of the wind turbine generator set according to the power difference.

[0128] Exemplary Electronic Devices

[0129] Fig.11 This is a structure of an electronic device provided by an exemplary embodiment of the present invention. Fig.11 As shown, the electronic device 110 includes one or more processors 111 and a memory 112 .

[0130] The processor 111 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0131] The memory 112 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 111 may run the program instructions to implement the methods of the software programs of the various embodiments of the present invention described above and / or other desired functions. In one example, the electronic device may also include: an input device 113 and an output device 114, which are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0132] In addition, the input device 113 may also include, for example, a keyboard, a mouse, etc.

[0133] The output device 114 can output various information to the outside, and can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto.

[0134] Of course, to simplify, Fig.11 Only some of the components related to the present invention in the electronic device are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, the electronic device may further include any other appropriate components according to specific application conditions.

[0135] Exemplary computer program products and computer-readable storage media

[0136] In addition to the above-mentioned methods and devices, an embodiment of the present invention may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present invention described in the above-mentioned "Exemplary Method" section of this specification.

[0137] The computer program product may be written in any combination of one or more programming languages ​​to write program code for performing the operations of the embodiments of the present invention, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0138] In addition, an embodiment of the present invention may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present invention described in the above “Exemplary Method” section of this specification.

[0139] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, system or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0140] The basic principle of the present invention is described above in conjunction with specific embodiments. However, it should be pointed out that the advantages, strengths, effects, etc. mentioned in the present invention are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. must be possessed by each embodiment of the present invention. In addition, the specific details disclosed above are only for the purpose of illustration and facilitation of understanding, rather than limitation, and the above details do not limit the present invention to being implemented by adopting the above specific details.

[0141] Each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system embodiment, since it basically corresponds to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0142] The block diagrams of the devices, systems, equipment, and systems involved in the present invention are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, systems, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The word "such as" used here refers to the phrase "such as but not limited to", and can be used interchangeably with it.

[0143] The method and system of the present invention may be implemented in many ways. For example, the method and system of the present invention may be implemented by software, hardware, firmware or any combination of software, hardware, firmware. The above order of steps for the method is only for illustration, and the steps of the method of the present invention are not limited to the order specifically described above, unless otherwise specifically stated. In addition, in some embodiments, the present invention may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.

[0144] It should also be noted that in the system, device and method of the present invention, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. The above description of the disclosed aspects is provided to enable any technician in the field to make or use the present invention. Various modifications to these aspects are very obvious to those skilled in the art, and the general principles defined here can be applied to other aspects without departing from the scope of the present invention. Therefore, the present invention is not intended to be limited to the aspects shown here, but in accordance with the widest range consistent with the principles and novel features disclosed here.

[0145] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present invention to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A method for optimizing the inertia process load of a wind turbine generator system based on a wind speed estimator, characterized in that: include: A wind speed estimator and a feedforward controller are used to calculate the feedforward pitch angle of the wind turbine according to the current wind speed, wherein the wind speed estimator is generated by training using a width learning algorithm; Using a feedback controller to calculate a feedback pitch angle of the wind turbine generator set according to the generator speed of the wind turbine generator set and the current wind speed; Calculating the pitch angle deviation of the wind turbine generator set according to the frequency monitoring value of the wind turbine generator set; Calculating the active power of the wind turbine generator set according to the feedforward pitch angle, the feedback pitch angle and the pitch angle deviation; Active power control is performed on the wind turbine generator set according to the active power.

2. The method according to claim 1, characterized in that The wind speed estimator and the feedforward controller are used to calculate the feedforward pitch angle of the wind turbine according to the current wind speed, including: Using the wind speed estimator to predict the incoming wind speed of the wind turbine generator set according to the current wind speed, and obtaining the predicted incoming wind speed of the wind turbine generator set; The feedforward controller is used to calculate the feedforward pitch angle of the wind turbine set according to the blade pitch angle that matches the incoming flow predicted wind speed.

3. The method according to claim 1, characterized in that The feedback controller is used to calculate the feedback pitch angle of the wind turbine generator set according to the generator speed of the wind turbine generator set and the current wind speed, including: estimating the rotation speed of the wind turbine generator set according to the current rotation speed of the wind turbine generator set and the current wind speed, and outputting the estimated rotation speed of the wind turbine generator set; A feedback controller is used to calculate the feedback pitch angle according to the estimated rotation speed.

4. The method according to claim 3, characterized in that The method of estimating the rotation speed of the wind turbine generator set according to the current rotation speed of the wind turbine generator set and the current wind speed, and outputting the estimated rotation speed of the wind turbine generator set, comprises: Inputting the current rotation speed into a feedforward controller to output an initial estimated rotation speed of the wind turbine generator set; Inputting the current wind speed into the wind speed estimator, and outputting the initial estimated wind speed of the wind turbine generator set; A pitch command of the wind turbine generator system is determined according to the initial estimated rotational speed and the initial estimated wind speed, and an estimated rotational speed that meets the pitch command is determined iteratively.

5. The method according to claim 1, characterized in that Calculating the pitch angle deviation of the wind turbine generator set according to the frequency monitoring value of the wind turbine generator set includes: The frequency monitoring value is compared with the power grid set frequency of 50 Hz to obtain the frequency deviation; Calculating the power difference of the wind turbine generator set according to the frequency deviation; The pitch angle deviation of the wind turbine generator set is calculated according to the power difference.

6. A wind turbine inertia process load optimization control device based on a wind speed estimator, characterized in that: include: A first calculation module is used to calculate the feedforward pitch angle of the wind turbine according to the current wind speed by using a wind speed estimator and a feedforward controller, wherein the wind speed estimator is generated by training using a width learning algorithm; A second calculation module, configured to calculate a feedback pitch angle of the wind turbine generator set according to a generator speed of the wind turbine generator set and the current wind speed by using a feedback controller; A third calculation module, used for calculating the pitch angle deviation of the wind turbine generator set according to the frequency monitoring value of the wind turbine generator set; a fourth calculation module, configured to calculate the active power of the wind turbine according to the feedforward pitch angle, the feedback pitch angle and the pitch angle deviation; A control module is used to control the active power of the wind turbine generator set according to the active power.

7. The device according to claim 6, characterized in that The first computing module includes: A prediction submodule, configured to use the wind speed estimator to predict the incoming wind speed of the wind turbine according to the current wind speed, and obtain the predicted incoming wind speed of the wind turbine; The matching submodule is used to calculate the feedforward pitch angle of the wind turbine set by using the feedforward controller to match the blade pitch angle of the incoming flow predicted wind speed.

8. The device according to claim 6, characterized in that The second computing module includes: an estimation submodule, configured to estimate the rotation speed of the wind turbine generator set according to the current rotation speed of the wind turbine generator set and the current wind speed, and output the estimated rotation speed of the wind turbine generator set; The first calculation submodule is used to calculate the feedback pitch angle according to the estimated rotation speed by using a feedback controller.

9. The device according to claim 8, characterized in that Estimation submodule, including: A first output unit, used to input the current rotation speed into a feedforward controller, and output an initial estimated rotation speed of the wind turbine generator set; A second output unit, configured to input the current wind speed into the wind speed estimator and output an initial estimated wind speed of the wind turbine generator; A determination unit is used to determine a pitch command of the wind turbine generator system according to the initial estimated rotational speed and the initial estimated wind speed, and iteratively determine an estimated rotational speed that meets the pitch command.

10. The device according to claim 6, characterized in that The third computing module includes: A comparison submodule is used to compare the frequency monitoring value with the power grid set frequency of 50 Hz to obtain a frequency deviation; A second calculation submodule, configured to calculate a power difference of the wind turbine generator set according to the frequency deviation; The third calculation submodule is used to calculate the pitch angle deviation of the wind turbine generator set according to the power difference.

11. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program is used to execute the method according to any one of claims 1 to 5.

12. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing instructions executable by the processor; The processor is used to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1 to 5.

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