Dynamic virtual inertia control strategy and system of wind turbine based on tracking differentiator

Abstract

The invention discloses a wind turbine dynamic virtual inertia control strategy and system based on a tracking differentiator, comprising the steps of acquiring a frequency deviation signal of a power system; performing tracking filtering through a preset tracking differentiator according to the frequency deviation signal to obtain a first state signal and a second state signal, and using the first state signal and the second state signal as feedback input signals of the tracking differentiator, wherein the first state signal is a tracking state frequency deviation, and the second state signal is a frequency change rate; determining a control reference power signal through a preset virtual inertia controller according to the first state signal and the second state signal; and performing output power compensation on a wind farm where the wind turbine is located according to the control reference power signal, avoiding the amplification effect of a conventional differentiator on a high-frequency signal, effectively suppressing measurement noise and high-frequency interference, and then realizing wind power participation in frequency modulation in combination with a dynamic virtual inertia control method, making fuller use of the releasable kinetic energy of the wind turbine, and improving the ability of wind power participation in frequency modulation.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power systems, and in particular to a dynamic virtual inertia control strategy and system for a wind turbine based on a tracking differentiator. Background Art

[0002] Wind power is part of the power system. The methods of wind power participating in system frequency regulation can be mainly divided into two categories: virtual inertia control and load shedding control. Virtual inertia control is to temporarily release the kinetic energy stored in the rotor by adding an auxiliary control loop to the maximum power tracking controller to compensate for the reduction of system inertia, thereby increasing the system virtual inertia and suppressing system frequency fluctuations. Load shedding control is to operate the wind turbine in load shedding mode, reserving some power to support the frequency. Compared with the two, load shedding control has a wider adjustment range and better adjustment ability, but load shedding control relies heavily on mechanical adjustment, which will greatly increase the mechanical damage rate and maintenance costs.

[0003] Traditional proportional differential (PD) virtual inertia control can release the kinetic energy of the wind turbine rotor to support system frequency regulation, but on the one hand, the fixed control parameters make it difficult to fully utilize the available kinetic energy of the wind turbine under different operating conditions; on the other hand, virtual inertia control requires a frequency change rate signal during implementation, and the differentiator will amplify high-frequency noise, such as measurement noise and other system interference. To solve the above problems, existing studies have introduced low-pass filters and inertia control based on extended state observers, but this will affect the control effect. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention proposes a wind turbine dynamic virtual inertia control strategy and system based on a tracking differentiator, which can suppress the influence of measurement noise and high-frequency disturbance on control performance.

[0005] In a first aspect, a wind turbine dynamic virtual inertia control strategy based on a tracking differentiator according to an embodiment of the present invention includes:

[0006] Obtain frequency deviation signal of power system;

[0007] According to the frequency deviation signal, tracking filtering is performed through a preset tracking differentiator to obtain a first state signal and a second state signal, and the first state signal and the second state signal are used as feedback input signals of the tracking differentiator, wherein the first state signal is a tracking state frequency deviation, and the second state signal is a frequency change rate;

[0008] Determining a control reference power signal through a preset virtual inertia controller according to the first state signal and the second state signal;

[0009] Output power compensation is performed on the wind farm where the wind turbine is located according to the control reference power signal.

[0010] The wind turbine dynamic virtual inertia control strategy based on the tracking differentiator according to the embodiment of the present invention has at least the following beneficial effects:

[0011] The embodiment of the present invention obtains the frequency change rate of the power system by tracking the differentiator, avoids the amplification effect of the conventional differentiator on the high-frequency signal, thereby effectively suppressing the measurement noise and high-frequency interference, and then combines the dynamic virtual inertia control method to realize the participation of wind power in frequency regulation, more fully utilize the releasable kinetic energy of the wind turbine, and enhance the ability of wind power to participate in frequency regulation.

[0012] According to some embodiments of the present invention, the state space equation of the tracking differentiator is:

[0013]

[0014] In the formula, , x 1 is the first state signal, x 2 is the second state signal, ,in, fhan is the fastest control synthesis function, the reference signal v =-Δ f , Δ f is the frequency deviation signal, r is the speed factor, h is the filtering factor, k 0 h To track step length; , , , is the output state quantity.

[0015] According to some embodiments of the present invention, the mathematical model of the virtual inertia controller is:

[0016]

[0017] where Δ P ref is the control reference power signal, K ωp0 is the first gain coefficient, K ωd0 is the second gain coefficient, x 1 is the first state signal, x 2 is the second state signal, ω g is the rotor speed of the fan, ω max is the upper limit speed of the rotor of the fan, ω min is the lower limit speed of the rotor of the fan.

[0018] According to some embodiments of the present invention, the second gain coefficient .

[0019] According to some embodiments of the present invention, the wind turbine dynamic virtual inertia control strategy based on tracking differentiator further includes:

[0020] According to the frequency deviation signal, the power system is subjected to secondary frequency modulation by a preset load frequency controller, wherein the state space equation of the system to be observed of the load frequency controller is:

[0021]

[0022] In the formula, represents the system state vector, represents the input of the system to be observed, represents the differential of the total disturbance of the system to be observed, represents the output of the system to be observed, and the coefficient matrix in the state space equation of the system to be observed is:

[0023] , , , ,in b is a preset constant;

[0024] The equation of the extended state observer of the load frequency controller is:

[0025]

[0026] In the formula, is the state vector of the extended state observer, and the coefficient matrix of the extended state observer is

[0027] , , ;

[0028] The state feedback control law of the observed system is:

[0029] in, , , and are the bandwidth of the load frequency controller and the bandwidth of the extended state observer respectively.

[0030] In a second aspect, a wind turbine dynamic virtual inertia control system based on a tracking differentiator according to an embodiment of the present invention includes:

[0031] A tracking differentiator, used for acquiring a frequency deviation signal of the power system, and performing tracking filtering according to the frequency deviation signal to obtain a first state signal and a second state signal, and using the first state signal and the second state signal as its own feedback input signal, wherein the first state signal is a tracking state frequency deviation, and the second state signal is a frequency change rate;

[0032] The virtual inertia controller is used to determine a control reference power signal according to the first state signal and the second state signal, wherein the control reference power signal is used to perform output power compensation on a wind farm where the wind turbine is located.

[0033] The wind turbine dynamic virtual inertia control system based on the tracking differentiator according to the embodiment of the present invention has at least the following beneficial effects:

[0034] The embodiment of the present invention obtains the frequency change rate of the power system by tracking the differentiator, avoids the amplification effect of the conventional differentiator on the high-frequency signal, thereby effectively suppressing the measurement noise and high-frequency interference, and then combines the dynamic virtual inertia control method to realize the participation of wind power in frequency regulation, more fully utilize the releasable kinetic energy of the wind turbine, and enhance the ability of wind power to participate in frequency regulation.

[0035] According to some embodiments of the present invention, the state space equation of the tracking differentiator is:

[0036]

[0037] In the formula, , x 1 is the first state signal, x 2 is the second state signal, ,in, fhan is the fastest control synthesis function, the reference signal v =-Δ f , Δ f is the frequency deviation signal, r is the speed factor, h is the filtering factor, k 0 h To track step length; , , , is the output state quantity.

[0038] According to some embodiments of the present invention, the mathematical model of the virtual inertia controller is:

[0039]

[0040] where Δ Pref is the control reference power signal, K ωp0 is the first gain coefficient, K ωd0 is the second gain coefficient, x 1 is the first state signal, x 2 is the second state signal, ω g is the rotor speed of the fan, ω max is the upper limit speed of the rotor of the fan, ω min is the lower limit speed of the rotor of the fan.

[0041] According to some embodiments of the present invention, the second gain coefficient .

[0042] According to some embodiments of the present invention, the wind turbine dynamic virtual inertia control system based on the tracking differentiator also includes a load frequency controller, which is used to perform secondary frequency modulation on the power system according to the frequency deviation signal, wherein the state space equation of the system to be observed of the load frequency controller is:

[0043]

[0044] In the formula, represents the system state vector, represents the input of the system to be observed, represents the differential of the total disturbance of the system to be observed, represents the output of the system to be observed, and the coefficient matrix in the state space equation of the system to be observed is:

[0045] , , , ,in b is a preset constant;

[0046] The equation of the extended state observer of the load frequency controller is:

[0047]

[0048] In the formula, is the state vector of the extended state observer, and the coefficient matrix of the extended state observer is

[0049] , , ;

[0050] The state feedback control law of the observed system is:

[0051] in, , , and are the bandwidth of the load frequency controller and the bandwidth of the extended state observer respectively.

[0052] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0054] Figure 1 A single-region control block diagram of a wind turbine dynamic virtual inertia control strategy based on a tracking differentiator according to an embodiment of the present invention;

[0055] Figure 2 A system block diagram of a wind turbine dynamic virtual inertia control strategy based on a tracking differentiator according to an embodiment of the present invention;

[0056] Figure 3 It is a system dynamic response curve diagram of the fan dynamic virtual inertia control strategy based on tracking differentiator in the embodiment of the present invention when the frequency is modulated once under the frequency measurement disturbance;

[0057] Figure 4 It is a dynamic response curve diagram of the frequency change rate of the wind turbine dynamic virtual inertia control strategy based on the tracking differentiator under the frequency measurement disturbance according to an embodiment of the present invention;

[0058] Figure 5 A system dynamic response curve diagram of a primary frequency modulation under random load disturbance using a dynamic virtual inertia control strategy for a fan based on a tracking differentiator according to an embodiment of the present invention;

[0059] Figure 6 It is a system frequency deviation curve diagram of primary and secondary frequency modulation under load step change of the dynamic virtual inertia control strategy of the fan based on the tracking differentiator according to an embodiment of the present invention;

[0060] Figure 7 It is a system dynamic response curve diagram of primary and secondary frequency modulation under load step change of the dynamic virtual inertia control strategy of the fan based on the tracking differentiator according to an embodiment of the present invention;

[0061] Figure 8It is a system frequency deviation curve diagram of primary and secondary frequency modulation under random load disturbance of the dynamic virtual inertia control strategy of the fan based on the tracking differentiator according to an embodiment of the present invention;

[0062] Fig. 9 It is a system dynamic response curve diagram of primary and secondary frequency modulation under random load disturbance of the dynamic virtual inertia control strategy of the fan based on the tracking differentiator according to an embodiment of the present invention;

[0063] Fig.10 It is a frequency change rate dynamic response curve diagram of the primary and secondary frequency modulation under random load disturbance of the dynamic virtual inertia control strategy of the fan based on the tracking differentiator according to the embodiment of the present invention;

[0064] Fig.11 It is a system frequency deviation response curve diagram of the wind turbine dynamic virtual inertia control strategy based on tracking differentiator under different wind power penetration rates according to an embodiment of the present invention;

[0065] In the figure, Without VIC / noVIC: No virtual inertia control

[0066] DVIC / VIC: Virtual Inertia Control;

[0067] Traditional VIC: Traditional virtual inertia control;

[0068] Filter-based VIC: Filter-based virtual inertia control;

[0069] TD-VIC / TD-based VIC: Virtual inertia control based on tracking differentiator;

[0070] LADRC: Linear Active Disturbance Rejection Control. DETAILED DESCRIPTION

[0071] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0072] In the description of the present invention, "several" means one or more, "multiple" means more than two, greater than, less than, and exceeding are understood as not including the number itself, and "above", "below", and "within" are understood as including the number itself. If there is a description of "first", "second", etc., it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0073] In the description of the present invention, unless otherwise clearly defined, words such as “setting”, “installation” and “connection” should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above words in the present invention in combination with the specific content of the technical solution.

[0074] In the description of the present invention, the consecutive numbering of the method steps is for the convenience of review and understanding. Combined with the overall technical scheme of the present invention and the logical relationship between the various steps, adjusting the implementation order between the steps will not affect the technical effect achieved by the technical scheme of the present invention.

[0075] Please refer to Figure 1 and Figure 2 This embodiment discloses a wind turbine dynamic virtual inertia control strategy based on a tracking differentiator, the strategy includes steps S100 to S400, and the details of each step are as follows:

[0076] S100, obtaining a frequency deviation signal of the power system;

[0077] S200, performing tracking filtering through a preset tracking differentiator according to the frequency deviation signal to obtain a first state signal and a second state signal, and using the first state signal and the second state signal as feedback input signals of the tracking differentiator, wherein the first state signal is a tracking state frequency deviation, and the second state signal is a frequency change rate;

[0078] S300, determining a control reference power signal through a preset virtual inertia controller according to the first state signal and the second state signal;

[0079] S400: Compensate the output power of the wind farm where the wind turbine is located according to the control reference power signal.

[0080] In order to facilitate understanding of the fan dynamic virtual inertia control strategy based on the tracking differentiator of the present embodiment, the fan dynamic virtual inertia control strategy based on the tracking differentiator of the present embodiment is discussed in detail below in combination with the design method of the fan dynamic virtual inertia control system based on the tracking differentiator. The design method of the fan dynamic virtual inertia control system based on the tracking differentiator includes:

[0081] 1) Establish a single-region load frequency control model including wind power

[0082] Please refer to Figure 1 , Figure 1 In the single-area load frequency control model shown in , the wind farm adopts a single-machine equivalent model, and the thermal power unit is used as a secondary frequency regulation unit. Among them, the mechanical power captured by the wind turbine for:

[0083] (1)

[0084] In the formula, ρ is the air density, A is the area covered by the wind turbine blades, C p is the wind energy utilization coefficient, is the wind speed, among which, the wind energy utilization coefficient The calculation method is as follows:

[0085] (2)

[0086] In the formula, λ is the tip speed ratio of the wind turbine, β is the propeller distance angle of the wind turbine, is the rotor speed of the wind turbine unit, K is the blade radius of the wind turbine unit, a 1~ a 6. b 1~ b 2 are adjustable coefficients.

[0087] The mechanical power captured by the wind turbine is transmitted to the generator via the transmission system, where the transmission system adopts a concentrated mass transmission system. The model of the concentrated mass transmission system is:

[0088] (3)

[0089] In the formula, is the rotor speed of the wind turbine, is the derivative of the rotor speed of the wind turbine, is the rotor inertia coefficient of the wind turbine, is the electromagnetic power of the wind turbine.

[0090] When the wind turbine operates in the maximum power tracking mode, the relationship between the rotor speed and power of the wind turbine is:

[0091] (4)

[0092] In the formula, is the power of the wind turbine operating in the maximum power tracking mode, is the optimal tracking coefficient of the maximum power tracking mode.

[0093] Of course, during the actual operation, the wind turbine also receives adjustment instructions from the auxiliary control module (such as the virtual inertia controller described below). Therefore, after being controlled by the inverter, the output power of the wind farm where the wind turbine is located is for:

[0094] (5)

[0095] In the formula, is the response time coefficient of the inverter,s is the differential operator, It is the control reference power signal of the auxiliary control module.

[0096] The frequency regulation model of the thermal power unit in this embodiment is:

[0097] (6)

[0098] (7)

[0099] (8)

[0100] In the formula, Δ f is the frequency deviation signal of the power system, R is the adjustment coefficient, P c , X g and T g are the input power, boiler output and boiler dynamic response time coefficient of the thermal power plant boiler, is the derivative of boiler output, P r , F and T r They are the output power of the steam turbine of the thermal power plant, the gain coefficient of the steam turbine of the thermal power plant and the response time coefficient of the steam turbine of the thermal power plant. is the derivative of the output power of the steam turbine in a thermal power plant, P g and T t They are respectively the output power of the thermal power plant speed regulator and the response time coefficient of the thermal power plant speed regulator.

[0101] In the power system, the imbalance of active power will cause frequency fluctuations. The power-frequency response process of the power system can be expressed as:

[0102] (9)

[0103] In the formula, H and D are the inertia constant and damping coefficient of the power system, is the wind farm power change value, is the load change value, It is the output power change value of the thermal power unit.

[0104] 2) Design tracking differentiator

[0105] Please refer to Figure 2 , the tracking differentiator of this embodiment is a nonlinear tracking differentiator, and the state space equation of the nonlinear tracking differentiator is:

[0106] (10)

[0107] In the formula, , x 1 is the first state signal, x 2 is the second state signal, ,in, fhan is the fastest control comprehensive function, Δ f is the frequency deviation signal of the power system, r is the speed factor, h is the filtering factor, k 0 h To track step length; , , , is the output state quantity. fhan The expression is:

[0108] (11)

[0109] In the formula, sign is the symbolic function, d is the linear interval of the function, a , a 0. a 1. a 2 are intermediate variables, and y is the output value.

[0110] In this embodiment, the reference signal of the tracking differentiator v =-Δ f， First status signal x 1 and second status signals x 2 are tracking state frequency deviations and frequency change rate .

[0111] 3) Design virtual inertia control link

[0112] Please continue to refer to Figure 2 , when the above tracking differentiator is used for tracking, the model of the virtual inertia controller is designed as follows:

[0113] (12)

[0114] In the formula, Δ P ref To control the reference power signal, K ωp and K ωp These are the controller coefficients of the virtual inertia controller, which change with the fan speed and are calculated as follows:

[0115] (13)

[0116] In the formula, K ωp0 is the first gain coefficient, K ωd0 is the second gain coefficient, x 1 is the first state signal, x 2 is the second state signal, ω g is the rotor speed of the fan, ω max is the upper limit speed of the fan rotor, ω min is the lower limit speed of the fan rotor. In this embodiment, K ωp0 Set to 2%, .

[0117] 4) Design load frequency controller

[0118] Please refer to Figure 1 In order to further improve the anti-disturbance capability of the system, a second-order linear anti-disturbance load frequency controller is designed for secondary frequency modulation. Assume that the state space equation of the observed system of the load frequency controller is:

[0119] (14)

[0120] In the formula, represents the system state vector, represents the input of the system to be observed, represents the differential of the total disturbance of the system to be observed, represents the output of the system to be observed, and the coefficient matrix in the state space equation of the system to be observed is:

[0121] , , , ,in b is a preset constant;

[0122] The equation of the extended state observer of the load frequency controller is:

[0123] (15)

[0124] In the formula, is the state vector of the extended state observer, and the coefficient matrix of the extended state observer is

[0125] , , ;

[0126] The state feedback control law of the observed system is:

[0127] (16)

[0128] in, , , and are the bandwidth of the load frequency controller and the bandwidth of the extended state observer respectively.

[0129] This embodiment obtains the frequency change rate of the power system by tracking the differentiator, avoiding the amplification effect of the conventional differentiator on the high-frequency signal, thereby effectively suppressing the measurement noise and high-frequency interference, and then combines the dynamic virtual inertia control method to realize the participation of wind power in frequency regulation, making fuller use of the releasable kinetic energy of the wind turbine, and improving the ability of wind power to participate in frequency regulation. This embodiment also observes the system disturbance through the extended state observer of the linear self-disturbance rejection load frequency controller, and compensates the control signal, which can further improve the system's anti-disturbance capability.

[0130] Based on the above discussion, it can be seen that the present embodiment further provides a wind turbine dynamic virtual inertia control system based on a tracking differentiator, comprising a tracking differentiator and a virtual inertia controller;

[0131] The tracking differentiator is used to obtain the frequency deviation signal of the power system, and to perform tracking filtering according to the frequency deviation signal to obtain a first state signal and a second state signal, and use the first state signal and the second state signal as its own feedback input signal, wherein the first state signal is the tracking state frequency deviation, and the second state signal is the frequency change rate;

[0132] The virtual inertia controller is used to determine a control reference power signal according to the first state signal and the second state signal, and the control reference power signal is used to perform output power compensation on the wind farm where the wind turbine is located.

[0133] This embodiment obtains the frequency change rate of the power system by tracking the differentiator, avoids the amplification effect of the conventional differentiator on the high-frequency signal, thereby effectively suppressing the measurement noise and high-frequency interference, and then combines the dynamic virtual inertia control method to realize the participation of wind power in frequency regulation, more fully utilize the releasable kinetic energy of the wind turbine, and enhance the ability of wind power to participate in frequency regulation.

[0134] The wind turbine dynamic virtual inertia control system based on tracking differentiator in this embodiment also includes a load frequency controller, which is used to perform secondary frequency modulation on the power system according to the frequency deviation signal. In this embodiment, the extended state observer of the linear anti-disturbance load frequency controller is used to observe the system disturbance and compensate the control signal, which can further improve the system anti-disturbance capability.

[0135] In order to have a more intuitive understanding of the technical effect of this embodiment, this embodiment builds a system model in MATLAB / Simulink for simulation, wherein the parameters of the system model and related controllers are shown in Table 1:

[0136]

[0137] Table 1

[0138] In order to test the anti-disturbance capability of the virtual inertia control strategy based on tracking differentiator proposed in this embodiment, interferences such as measurement noise, step load and random load are introduced respectively, and the results are compared with those of control methods such as no virtual inertia control, traditional virtual inertia control and filter-based virtual inertia control.

[0139] Please refer to Figure 3 , Figure 3 The simulation results of frequency response and dynamic response of wind power under measurement noise disturbance using control strategies such as Without VIC, Traditional VIC, Filter-based VIC, and TD-based VIC are described. Figure 3 (a) shows the frequency deviation dynamic response curves of each method, Figure 3 (b) shows the wind power dynamic response curves without virtual inertia control and traditional virtual inertia control. Figure 3 (c) shows the wind power dynamic response curves of the filter-based virtual inertia control and the tracking differentiator-based virtual inertia control. It can be clearly seen from the figure that the wind turbine dynamic virtual inertia control strategy based on the tracking differentiator in this embodiment has smaller frequency and wind power fluctuations than other control strategies, indicating that the wind turbine dynamic virtual inertia control strategy based on the tracking differentiator in this embodiment has better control performance, and the smaller wind power fluctuation means that the frequent adjustment of the power generation unit is reduced, which is beneficial to extending the life cycle of the power generation equipment.

[0140] In addition, the system frequency change rate fluctuation of the fan dynamic virtual inertia control strategy based on the tracking differentiator of this embodiment is also smaller. Figure 4 As shown, Figure 4 (a) shows the dynamic response curves of the frequency change rate of control strategies such as traditional virtual inertia control (Traditional VIC), filter-based virtual inertia control (Filter-based VIC) and tracking differentiator-based virtual inertia control (TD-based VIC) under frequency measurement disturbance, where Figure 4 (b) is Figure 4The enlarged view of the part of position A circled in (a) of FIG. From the comparison in the figure, it can be seen that, compared with the other two dynamic response curves, the dynamic response curve of the frequency change rate of the fan dynamic virtual inertia control strategy based on the tracking differentiator in this embodiment is a straight line with a value close to 0, which indicates that the fan dynamic virtual inertia control strategy based on the tracking differentiator in this embodiment can well suppress the amplification of noise.

[0141] In order to further verify the effectiveness of the wind turbine dynamic virtual inertia control strategy based on tracking differentiator in this embodiment, random load disturbance and step load disturbance are introduced. Figure 5 As shown in (a), the step load disturbance occurs at 10s, which reduces the load demand by 0.1pu. Figure 5 The simulation results of the system dynamic response of the primary frequency modulation under random load disturbance using different control methods are described. It can be clearly found that the system frequency fluctuation of the fan dynamic virtual inertia control strategy based on the tracking differentiator of this embodiment is small (such as Figure 5 (b)), wind power fluctuations are smaller (such as Figure 5 (c)), the generator power curve is smoother (as shown in Figure 5 (d)), the system frequency change rate is significantly reduced (as shown in Figure 5 (as shown in (e)).

[0142] Figure 6 (a) describes the system frequency deviation of primary and secondary frequency regulation under load step change. Figure 6 (b) is Figure 6 The enlarged view of the part of position B circled in (a) is shown in FIG. Figure 7 (a) describes the simulation results of the wind power response of the primary and secondary frequency regulation under load step changes. Figure 7 (b) describes the simulation results of the response of the generator power of the primary and secondary frequency modulation under the load step change. It can be clearly seen that the dynamic virtual inertia control strategy of the fan based on the tracking differentiator in this embodiment has smaller overshoot, faster adjustment speed and better control performance.

[0143] Figure 8 (a) describes the simulation results of the system frequency deviation response under random loads with primary and secondary frequency modulation. Figure 8 (b) is Figure 8 The enlarged view of the part of the circled position C in (a) is shown. Fig. 9 (a) describes the simulation results of wind power response under random loads with primary and secondary frequency regulation. Fig. 9 (b) describes the simulation results of the generator power response of the primary and secondary frequency regulation under random loads. Fig.10(a) describes the response simulation results of the frequency change rate of primary and secondary frequency modulation under random loads for four control strategies: no virtual inertia control (noVIC), no virtual inertia and nonlinear active disturbance rejection control (noVIC+LADRC), virtual inertia control (VIC), and virtual inertia and linear active disturbance rejection control (VIC+LADRC). Fig.10 (b) describes the response simulation results of the frequency change rate of the primary and secondary frequency modulation of the three control strategies, namely, filter-based virtual inertia control (Filter-VIC), filter-based virtual inertia control and linear anti-disturbance control (Filter-VIC+LADRC), and tracking differentiator-based virtual inertia control and linear anti-disturbance control (TD-VIC+LADRC) under random load. As can be seen from the figure, the frequency and frequency change rate fluctuations of the wind turbine dynamic virtual inertia control strategy based on the tracking differentiator of this embodiment are smaller, and the wind power change curve is smoother. The above results can further show that the wind turbine dynamic virtual inertia control strategy based on the tracking differentiator of this embodiment can effectively avoid the impact of high-frequency interference signal amplification on the system, and at the same time can reduce the regulation frequency of the wind turbine and reduce the operation and maintenance costs.

[0144] Since the wind speed in the actual system is in a time-varying state, it may cause the start and stop state of the fan, thereby changing the system inertia and frequency support capacity. In view of the above problems, simulation tests are carried out on systems with different permeabilities while keeping the controller parameters unchanged. Fig.11 (a) describes the simulation results of system frequency response under different wind power penetration rates without virtual inertia control strategy. Fig.11 (b) describes the simulation results of system frequency response under different wind power penetration rates without virtual inertia and nonlinear active disturbance rejection control strategy. Fig.11 (c) describes the simulation results of system frequency response under different wind power penetration rates under the virtual inertia control strategy. Fig.11 (d) describes the simulation results of system frequency response under different wind power penetration rates under virtual inertia and linear active disturbance rejection control strategies. Fig.11 (e) describes the simulation results of system frequency response under different wind power penetration rates under the filter-based virtual inertia control strategy. Fig.11 (f) describes the simulation results of system frequency response under different wind power penetration rates under filter-based virtual inertia control and linear active disturbance rejection control strategies. Fig.11(g) describes the simulation results of system frequency response under different wind power penetration rates under virtual inertia control based on tracking differentiator and linear anti-disturbance control strategy. It can be seen that the higher the penetration rate, the greater the overshoot. However, compared with other control strategies, the wind turbine dynamic virtual inertia control strategy based on tracking differentiator in this embodiment can still avoid large frequency fluctuations. The results show that the wind turbine dynamic virtual inertia control strategy based on tracking differentiator in this embodiment improves the robustness of the grid frequency and can adapt to high wind power penetration systems.

[0145] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge scope of ordinary technicians in the relevant technical field without departing from the purpose of the present invention.

Claims

1. A wind turbine dynamic virtual inertia control strategy based on tracking differentiator, characterized in that: include: Obtain frequency deviation signal of power system; According to the frequency deviation signal, tracking filtering is performed through a preset tracking differentiator to obtain a first state signal and a second state signal, and the first state signal and the second state signal are used as feedback input signals of the tracking differentiator, wherein the first state signal is a tracking state frequency deviation, and the second state signal is a frequency change rate; Determining a control reference power signal through a preset virtual inertia controller according to the first state signal and the second state signal; According to the control reference power signal, output power compensation is performed on the wind farm where the wind turbine is located; The state space equation of the tracking differentiator is: In the formula, , x 1 is the first state signal, x 2 is the second state signal, ,in, fhan is the fastest control synthesis function, the reference signal v =-Δ f , Δ f is the frequency deviation signal, r is the speed factor, h is the filtering factor, k 0 h To track step length; , , , is the output state quantity; The mathematical model of the virtual inertia controller is: Where Δ P ref is the control reference power signal, K ωp0 is the first gain coefficient, K ωd0 is the second gain coefficient, x 1 is the first state signal, x 2 is the second state signal, ω g is the rotor speed of the fan, ω max is the upper limit speed of the rotor of the fan, ω min is the lower limit speed of the rotor of the fan.

2. The wind turbine dynamic virtual inertia control strategy based on tracking differentiator according to claim 1 is characterized in that: The second gain coefficient .

3. The wind turbine dynamic virtual inertia control strategy based on tracking differentiator according to claim 1 is characterized in that: Also includes: According to the frequency deviation signal, the power system is subjected to secondary frequency modulation by a preset load frequency controller, wherein the state space equation of the system to be observed of the load frequency controller is: In the formula, represents the system state vector, represents the input of the system to be observed, represents the differential of the total disturbance of the system to be observed, represents the output of the system to be observed, and the coefficient matrix in the state space equation of the system to be observed is: , , , ,in b is a preset constant; The equation of the extended state observer of the load frequency controller is: In the formula, is the state vector of the extended state observer, and the coefficient matrix of the extended state observer is ， ， ； The state feedback control law of the observed system is: in, , , and are the bandwidth of the load frequency controller and the bandwidth of the extended state observer respectively.

4. A wind turbine dynamic virtual inertia control system based on a tracking differentiator, used to implement the wind turbine dynamic virtual inertia control strategy based on a tracking differentiator according to any one of claims 1 to 3, characterized in that: include: A tracking differentiator, used for acquiring a frequency deviation signal of the power system, and performing tracking filtering according to the frequency deviation signal to obtain a first state signal and a second state signal, and using the first state signal and the second state signal as its own feedback input signal, wherein the first state signal is a tracking state frequency deviation, and the second state signal is a frequency change rate; The virtual inertia controller is used to determine a control reference power signal according to the first state signal and the second state signal, wherein the control reference power signal is used to perform output power compensation on a wind farm where the wind turbine is located.

5. The wind turbine dynamic virtual inertia control system based on tracking differentiator according to claim 4 is characterized in that: The state space equation of the tracking differentiator is: In the formula, , x 1 is the first state signal, x 2 is the second state signal, ,in, fhan is the fastest control synthesis function, the reference signal v =-Δ f , Δ f is the frequency deviation signal, r is the speed factor, h is the filtering factor, k 0 h To track step length; , , , is the output state quantity.

6. The wind turbine dynamic virtual inertia control system based on tracking differentiator according to claim 4, characterized in that: The mathematical model of the virtual inertia controller is: Where Δ P ref is the control reference power signal, K ωp0 is the first gain coefficient, K ωd0 is the second gain coefficient, x 1 is the first state signal, x 2 is the second state signal, ω g is the rotor speed of the fan, ω max is the upper limit speed of the rotor of the fan, ω min is the lower limit speed of the rotor of the fan.

7. The wind turbine dynamic virtual inertia control system based on tracking differentiator according to claim 6, characterized in that: The second gain coefficient .

8. The wind turbine dynamic virtual inertia control system based on tracking differentiator according to claim 4, characterized in that: The system further includes a load frequency controller, which is used to perform secondary frequency modulation on the power system according to the frequency deviation signal, wherein the state space equation of the system to be observed of the load frequency controller is: In the formula, represents the system state vector, represents the input of the system to be observed, represents the differential of the total disturbance of the system to be observed, represents the output of the system to be observed, and the coefficient matrix in the state space equation of the system to be observed is: , , , ,in b is a preset constant; The equation of the extended state observer of the load frequency controller is: In the formula, is the state vector of the extended state observer, and the coefficient matrix of the extended state observer is ， ， ； The state feedback control law of the observed system is: in, , , and are the bandwidth of the load frequency controller and the bandwidth of the extended state observer respectively.

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