Method for suppressing subsynchronous resonance of doubly-fed wind turbine based on additional electromagnetic torque

Abstract

The application discloses a method for suppressing subsynchronous resonance of a doubly-fed wind turbine based on additional electromagnetic torque, and the method comprises the following steps: constructing a transfer function between a rotor-side electromagnetic torque variation and a rotor speed disturbance by a flux linkage equation of a three-phase asynchronous motor and a rotor-side electromagnetic torque expression of the three-phase asynchronous motor; deriving a generation mechanism of the subsynchronous resonance from a physical layer according to the transfer function; and adding a subsynchronous resonance damping control strategy for additional electromagnetic torque of a target doubly-fed wind turbine in a d-axis controller of a rotor-side converter according to the generation mechanism of the subsynchronous resonance, so that the target doubly-fed wind turbine generates an electromagnetic torque which is opposite in phase to the rotor speed disturbance, thereby effectively suppressing the subsynchronous resonance of a power transmission system for transmitting wind power from the doubly-fed wind turbine to outside through a series compensation transmission line.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of wind power generation, in particular to a doubly-fed wind turbine subsynchronous resonance suppression method based on additional electromagnetic torque, which can be applied to the subsynchronous resonance suppression of a doubly-fed wind turbine. BACKGROUND

[0002] At present, under the increasingly severe form of global problems such as energy shortage, environmental pollution and climate warming, large-scale development and utilization of wind, light and other renewable energy has become an important choice of energy strategy for countries around the world. With the transformation of China's energy structure, the large-scale grid connection of wind power, photovoltaic and other new energy units, the early sending end power source with the main body of synchronous generator thermal power / water power is gradually replaced by wind power with the main body of power electronic devices. High proportion of new energy leads to further weakness of the sending end grid, causing subsynchronous oscillation problem of new energy units connected to weak grid, threatening the safe and stable operation of the system, seriously restricting the large-scale development and efficient utilization of new energy, and being not conducive to the construction of new energy-based new power system.

[0003] Doubly-fed wind generator (DFIG, Doubly fed Induction Generator) is the most widely used wind generator at present, which is composed of a stator winding directly connected to a fixed-frequency three-phase power grid winding type asynchronous generator and a bidirectional back-to-back IGBT voltage source converter installed on the rotor winding. Among them, the converter connected to the rotor of the doubly-fed wind turbine is called rotor side converter (RSC, Rotor Side Convertor), and the control of the RSC converter can realize the control of the stator output active and reactive power of the doubly-fed wind turbine.

[0004] Studies have shown that when the doubly-fed wind turbine transmits wind power to the outside through the series compensation transmission line, the transmission system may cause serious subsynchronous resonance (SSR, Subsynchronous Resonance). The subsynchronous resonance of the doubly-fed wind farm is mainly caused by the interaction between the doubly-fed wind power generator control system and the fixed series compensation. However, there is no good solution to how to design a subsynchronous resonance damping control strategy that can effectively suppress the subsynchronous resonance of the doubly-fed wind turbine. SUMMARY

[0005] In order to solve the technical problems existing in the prior art, the present application particularly innovatively proposes a doubly-fed wind turbine subsynchronous resonance suppression method based on additional electromagnetic torque, which can effectively suppress the subsynchronous resonance of the transmission system of the doubly-fed wind turbine transmitting wind power to the outside through the series compensation transmission line.

[0006] In order to achieve the above-mentioned object of the present application, the present application provides a method for suppressing subsynchronous resonance of a doubly-fed wind turbine based on additional electromagnetic torque, which comprises the following steps:

[0007] constructing a transfer function between the rotor-side electromagnetic torque variation and the rotor speed disturbance based on the flux linkage equation of the three-phase asynchronous motor and the rotor-side electromagnetic torque expression of the three-phase asynchronous motor;

[0008] determining a subsynchronous resonance damping control strategy for adding electromagnetic torque to the target doubly-fed wind turbine based on the transfer function between the rotor-side electromagnetic torque variation and the rotor speed disturbance;

[0009] adding the subsynchronous resonance damping control strategy to the d-axis controller of the rotor-side converter of the target doubly-fed wind turbine;

[0010] controlling the target doubly-fed wind turbine based on the d-axis controller of the rotor-side converter of the target doubly-fed wind turbine to which the subsynchronous resonance damping control strategy is added, taking the rotor speed disturbance as a feedback quantity, so that the target doubly-fed wind turbine generates an electromagnetic torque opposite in phase to the rotor speed disturbance to suppress subsynchronous resonance of the target doubly-fed wind turbine.

[0011] Preferably, the method further comprises:

[0012] constructing a mathematical model of the d-axis controller of the rotor-side converter of the target doubly-fed wind turbine to which the subsynchronous resonance damping control strategy is added;

[0013] obtaining a relationship between the rotor-side electromagnetic torque variation and the rotor speed disturbance after adding the subsynchronous resonance damping control strategy based on the transfer function and the mathematical model, wherein the relationship is as follows:

[0014] ΔT ersedc* =G SEDC (s)Δω r* (1)

[0015] wherein ΔT ersedc is the rotor-side electromagnetic torque variation after adding the subsynchronous resonance damping control strategy, Δω r is the rotor speed disturbance, and G SEDC (s) is the transfer function between the rotor speed disturbance and the rotor-side electromagnetic torque variation after adding the subsynchronous resonance damping control strategy.

[0016] Preferably, the subsynchronous resonance damping control strategy comprises a filtering link, a subsynchronous frequency detection link and a phase compensation link, wherein:

[0017] the filtering link is used to select out the subsynchronous resonance component in the rotor speed;

[0018] The subsynchronous frequency detection link is used for detecting a subsynchronous frequency value of the subsynchronous resonance existing in the power transmission system in which the doubly-fed wind generator set transmits wind power to the outside through the series compensation transmission line, wherein the subsynchronous frequency value is used for adaptive control of filter parameters of the filter link;

[0019] The phase compensation link is used for adjusting a phase angle between a transfer function of the speed disturbance quantity and the rotor-side electromagnetic torque variation quantity after the speed disturbance quantity and the rotor-side electromagnetic torque variation quantity are subjected to the subsynchronous resonance damping control strategy to 180°, so as to realize maximum positive damping effect on the subsynchronous resonance.

[0020] Preferably,

[0021] The filter used by the filter link comprises a second-order high-pass filter and a second-order band-pass filter, the cutoff frequency of the second-order high-pass filter and the cutoff frequency of the second-order band-pass filter are both determined by the subsynchronous frequency value, wherein,

[0022] The second-order high-pass filter is used for filtering out a direct current component and a low-frequency component existing in the rotor speed signal, and a transfer function of the second-order high-pass filter is as follows:

[0023]

[0024] Wherein, G HPF (s) is a transfer function of the second-order high-pass filter, Q hpass is a quality factor of the second-order high-pass filter, and ω hpass is a cutoff angular velocity of the second-order high-pass filter.

[0025] The second-order band-pass filter is used for selecting a subsynchronous resonance component from the rotor speed signal processed by the second-order high-pass filter, and a transfer function of the second-order band-pass filter is as follows:

[0026]

[0027] Wherein, G BPF (s) is a transfer function of the second-order band-pass filter, Q pass is a quality factor of the second-order band-pass filter, and ω pass is a cutoff angular velocity of the second-order band-pass filter.

[0028] Preferably, phase adjustment of the phase compensation link adopts a high-order lead / lag phase compensator to realize 360° range of lead / lag phase compensation, and a transfer function of the lead / lag phase compensator is as follows:

[0029]

[0030] Wherein, K shiftFor the gain of the phase compensator, T s1 and T s2 is the time parameter of the phase compensator, and n is the number of compensation cycles of the phase compensator.

[0031] Preferably, the method further includes:

[0032] An improved particle swarm optimization algorithm is used to perform parameter optimization calculations for the control parameters of the subsynchronous resonant damping control strategy in the phase compensation stage under all operating conditions. These control parameters include the time parameter T of the phase compensator. s1 and T s2 And the number of compensation cycles n of the phase compensator.

[0033] Preferably,

[0034] The formula for calculating the inertia weight ω in the improved particle swarm optimization algorithm is as follows:

[0035]

[0036] Where, ω min The minimum value of the inertial weight ω, ω max Let ω be the maximum value of the inertia weight, and t be the current iteration number. max The maximum number of iterations is set.

[0037] The asynchronous learning factor update calculation formula of the improved particle swarm optimization algorithm is as follows:

[0038]

[0039] Where c1 is the individual learning factor, c2 is the group learning factor, and c... 1intial Let c1 be the initial value, and c 1end The final value of c1, c 2intial Let c1 be the initial value, and c 2end c2 represents the final value, and t represents the current iteration number. max The maximum number of iterations is set.

[0040] The velocity update formula for the improved particle swarm optimization algorithm is as follows:

[0041]

[0042] Where t is the current iteration number, i is the number of different particles in the swarm, ω is the inertia weight, and v i Let x be the current velocity of the i-th particle. i Let c1 be the current position of the i-th particle, c2 be the individual learning factor, c2 be the group learning factor, and rand1 and rand2 be random numbers between [0,1]. pbesti gbest is the individual best value i gbest is the global best value, is a shrinkage factor, wherein the shrinkage factor The expression of is as follows:

[0043]

[0044] Preferably, the constructing the transfer function between the rotor-side electromagnetic torque variation and the rotor speed disturbance based on the flux equation of the three-phase asynchronous motor and the rotor-side electromagnetic torque expression of the three-phase asynchronous motor comprises:

[0045] Based on the flux equation of the three-phase asynchronous motor and the Lenz law, and performing the abc-dq coordinate system transformation to obtain an expression of the rotor-side induced electromotive force variation;

[0046] Performing the normalization and the Laplace transformation on the expression of the rotor-side induced electromotive force variation to obtain a relationship between the normalized value of the rotor-side induced electromotive force variation and the normalized value of the rotor speed disturbance in the dq coordinate system;

[0047] Performing the small-range linearization calculation and the Laplace transformation on the rotor-side electromagnetic torque expression of the three-phase asynchronous motor to obtain an expression of the rotor-side electromagnetic torque variation;

[0048] Based on the Laplace transformation to obtain the expression of the rotor-side electromagnetic torque variation and the relationship between the normalized value of the rotor-side induced electromotive force variation and the normalized value of the rotor speed disturbance in the dq coordinate system, a transfer function between the rotor-side electromagnetic torque variation and the rotor speed disturbance is obtained.

[0049] The application constructs a transfer function between a rotor-side electromagnetic torque change and a rotor speed disturbance based on a flux linkage equation of a three-phase asynchronous motor and a rotor-side electromagnetic torque expression of the three-phase asynchronous motor; determines a subsynchronous resonance damping control strategy for adding an electromagnetic torque to a target double-fed wind turbine based on the transfer function between the rotor-side electromagnetic torque change and the rotor speed disturbance; adds the subsynchronous resonance damping control strategy to a d-axis controller of a rotor-side converter of the target double-fed wind turbine; controls the target double-fed wind turbine based on the d-axis controller of the rotor-side converter of the target double-fed wind turbine to which the subsynchronous resonance damping control strategy is added, takes the rotor speed disturbance as a feedback, and makes the target double-fed wind turbine generate an electromagnetic torque opposite in phase to the rotor speed disturbance to suppress subsynchronous resonance of the target double-fed wind turbine. The application adds the subsynchronous resonance damping control strategy for adding an electromagnetic torque to a target double-fed wind turbine to a d-axis controller of a rotor-side converter, makes the target double-fed wind turbine generate an electromagnetic torque opposite in phase to the rotor speed disturbance, and thus can effectively suppress subsynchronous resonance of a power transmission system in which the double-fed wind turbine transmits wind power to the outside through a series compensation transmission line.

[0050] Additional aspects and advantages of the application will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following and / or can be learned by practice of the application. BRIEF DESCRIPTION OF DRAWINGS

[0051] The above and / or additional aspects and advantages of the application will become apparent and be readily appreciated from the description of the embodiments, taken in conjunction with the following drawings in which:

[0052] Figure 1 is a flow chart of a double-fed wind turbine subsynchronous resonance suppression method based on an additional electromagnetic torque in a preferred embodiment of the application;

[0053] Figure 2 is a principle diagram of the additional subsynchronous resonance damping control strategy of the application;

[0054] Figure 3 is a control block diagram of the d-axis controller of the rotor-side converter to which the subsynchronous resonance damping control strategy is added in a specific example of the application;

[0055] Figure 4 is a flow chart of the additional subsynchronous resonance damping control strategy in a specific example of the application;

[0056] Figure 5 is a function image of a linear differential decreasing strategy under a given value in a specific example of the application;

[0057] Figure 6is a flow chart of a particle swarm optimization algorithm improved in a preferred embodiment of the present application;

[0058] Figures 7(a)-7(d) is a simulation waveform diagram obtained by model simulation of the additional subsynchronous resonance damping control strategy in the rotor-side converter of the simulation model of the present application;

[0059] Figures 8(a)-8(e) is an active power simulation waveform diagram of a doubly-fed wind turbine with the additional subsynchronous resonance damping control strategy under different operating conditions and different phase compensator control parameters. DETAILED DESCRIPTION

[0060] Exemplary embodiments of the present disclosure will be described in greater detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be embodied in various forms without being limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure can be more thoroughly understood, and so that the scope of the present disclosure can be completely conveyed to those skilled in the art.

[0061] Those skilled in the art can understand that, unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art to which the present application belongs. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with those in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined.

[0062] As shown in Figure 1 The embodiment of the present application provides a doubly-fed wind turbine subsynchronous resonance suppression method based on additional electromagnetic torque, which can include the following steps:

[0063] S101, a transfer function between a rotor speed disturbance and a rotor-side electromagnetic torque change is constructed based on a flux equation of a three-phase asynchronous motor and a rotor-side electromagnetic torque expression of a three-phase asynchronous motor;

[0064] At present, for the subsynchronous oscillation problem of the power transmission system of the doubly-fed wind turbine transmitting wind power to the outside through the series compensation transmission line, there is a lack of physical level mechanism derivation of the generation mechanism of the subsynchronous resonance, and it is impossible to effectively develop subsynchronous oscillation suppression measures. The embodiment lacks physical level mechanism derivation for the generation mechanism of the subsynchronous resonance, and therefore the transfer function between the rotor speed disturbance and the rotor-side electromagnetic torque change is derived.

[0065] In the embodiment, the above step S101 specifically includes:

[0066] Based on the flux linkage equation and the law of Lenz of three-phase asynchronous motor, the expression of the rotor side induction electromotive force variation is obtained by abc-dq coordinate transformation.

[0067] The rotor side induction electromotive force variation expression is normalized and Laplace transformed to obtain the relationship between the rotor side induction electromotive force variation normalized value and the rotor speed disturbance normalized value in dq coordinate system.

[0068] The rotor side electromagnetic torque expression of three-phase asynchronous motor is linearized in a small range and Laplace transformed to obtain the rotor side electromagnetic torque variation expression.

[0069] Based on the rotor side electromagnetic torque variation expression and the relationship between the rotor side induction electromotive force variation normalized value and the rotor speed disturbance normalized value in dq coordinate system, the transfer function between the rotor side electromagnetic torque variation and the rotor speed disturbance is obtained.

[0070] The construction process of the transfer function between the rotor side electromagnetic torque variation and the rotor speed disturbance is described in detail as follows:

[0071] Let the leakage inductance of the stator winding and the rotor winding in abc coordinate system be L lsabc and L lrabc , and the mutual inductance between the stator winding and the rotor winding be L mabc , then the self-inductance and mutual inductance matrix L 11 between the stator windings and the self-inductance and mutual inductance matrix L 12 between the rotor windings can be respectively expressed as:

[0072]

[0073] wherein, L AA , L BB , L CC represent the self-inductance of the stator winding, L AB , L AC , L BA , L BC , L CA , L CB represent the mutual inductance of the stator winding.

[0074]

[0075] wherein, L aa , L bb , L cc represent the self-inductance of the rotor winding, L ab , L ac , L ba , L bc , L ca , L cbrepresents the rotor winding mutual inductance.

[0076] Mutual inductance matrix L between stator winding and rotor winding 12 , L 21 may be expressed as:

[0077]

[0078] wherein L Aa , L Ab , L Ac , L Ba , L Bb , L Bc , L Ca , L Cb , L Cc , L aA , L aB , L aC , L bA , L bB , L bC , L cA , L cB , L cC represents mutual inductance between stator winding and rotor winding; ω r0 represents steady state rotating speed of rotor side, Δω r represents rotor rotating speed disturbance of double-fed wind turbine.

[0079] Assuming that positive current generates negative magnetic linkage, the magnetic linkage equation of three-phase asynchronous motor can be expressed as:

[0080]

[0081] wherein ψ sabc represents stator three-phase magnetic linkage, ψ rabc represents rotor three-phase magnetic linkage, i sabc represents stator three-phase current, i rabc represents rotor three-phase current.

[0082] Substitute (9), (10), (11) into (12), and multiply both sides by Perform dq transformation, ignore zero-axis component, and record L ss = L lsabc + 3L mabc / 2, L rr = L lrabc + 3L mabc / 2, L m = 3L mabc / 2, and simplify and arrange to obtain:

[0083]

[0084] wherein Lss L represents the self-inductance of the stator equivalent winding in the dq0 coordinate system. rr L represents the self-inductance of the rotor equivalent winding in the dq coordinate system. m ψ represents the mutual inductance between the stator and rotor windings. sd ψ represents the stator flux linkage along the d-axis. sq ψ represents the q-axis stator flux linkage. rd ψ represents the rotor flux linkage on the d-axis. rq This represents the q-axis rotor flux linkage, t represents time, and i sd0 and i sq0 i represents the steady-state current on the stator side in the dq coordinate system. rd0 and i rq0 ψ represents the steady-state current on the rotor side in the dq coordinate system. sd0 ψ sq0 ψ represents the steady-state value of the stator-side flux linkage in the dq coordinate system. rd0 ψ rq0 Δψ represents the steady-state value of the rotor-side flux linkage in the dq coordinate system. sd0 , Δψ sq0 Δψ represents the change in stator flux linkage in the dq coordinate system. rd0 , Δψ rq0 This represents the change in rotor-side flux linkage in the dq coordinate system.

[0085] Assuming that the stator and rotor windings of the three-phase asynchronous motor in the doubly fed wind turbine generator set both adopt the conventional method for electric motors, e sa e sb e sc e represents the three-phase induced electromotive force of the stator of a three-phase asynchronous motor. ra e rb e rc To represent the three-phase induced electromotive force of the rotor of a three-phase asynchronous motor, we can obtain the following from Lenz's law:

[0086]

[0087] Among them, e sabc e represents the three-phase induced electromotive force of the stator. rabc This represents the induced electromotive force of the three phases of the rotor.

[0088] Multiply both sides of the above equation by the orthogonal dq transformation matrix. And ignoring the zero-axis component, we get:

[0089]

[0090] Where, ω s ω represents the stator angular frequency. r This represents the rotor angular frequency.

[0091] Substitute (13) into (15), the rotor side induction electromotive force variation expression is obtained:

[0092]

[0093] wherein, e rd , e rq represents the stator induction electromotive force in dq coordinate system, Δψ rd , Δψ rq represents the rotor side flux linkage variation in dq coordinate system, e rd0 , e rq0 represents the stator induction electromotive force steady state value in dq coordinate system, Δe rd , Δe rq represents the stator induction electromotive force variation in dq coordinate system.

[0094]

[0095] wherein, Δδ represents the rotor angle variation.

[0096] The above formula is normalized and Laplace transformed, and the following is obtained:

[0097]

[0098] wherein, ΔE rd and ΔE rq represents the rotor side induction electromotive force variation in dq coordinate system.

[0099] Since

[0100]

[0101] Laplace transform is performed on both sides, and the following is obtained:

[0102]

[0103] Substitute (18) into (18), and the relationship between the rotor side induction electromotive force variation in dq coordinate system and the rotor speed disturbance in normalized value is obtained:

[0104]

[0105] wherein, ΔE rd and ΔE rq are the rotor side induction electromotive force variation in dq coordinate system, L m is the mutual inductance between stator and rotor windings, i sd0 and i sq0 are the steady state currents in dq coordinate system, ω s0 and ω r0 are the steady state speeds of stator and rotor respectively, ω​Base is the complex frequency, and * denotes the conjugate.

[0106] The electromagnetic torque expression of three-phase asynchronous motor is as follows:

[0107] T e = L m (i sq i rd -i sd i rq )(22)

[0108] wherein T e denotes the electromagnetic torque, i sq and i sd denote the stator currents in the dq coordinate system, and i rq and i rd denote the rotor currents in the dq coordinate system.

[0109] Dividing both sides of the above formula by and performing small-range linearization can obtain:

[0110]

[0111] wherein ΔT e denotes the electromagnetic torque change, Δi rd and Δi rq denote the rotor current change in the dq coordinate system, Δi sd and Δi sq denote the stator current change in the dq coordinate system, ΔT er denotes the electromagnetic torque rotor change, and ΔT es denotes the electromagnetic torque stator change.

[0112] Taking Laplace transform on the above formula, the following formula is obtained:

[0113]

[0114] wherein ΔI rd is the d-axis rotor current change, and ΔI rq is the q-axis rotor current change.

[0115] By combining formula (21) and formula (24), the transfer function between the rotor-side electromagnetic torque change ΔT er and the rotor speed disturbance Δω r can be obtained as follows:

[0116]

[0117] wherein A1, B1, C1, D1, E1 and F1 are respectively:

[0118]

[0119] Among them, L rsc and R R K represents the impedance parameters of the rotor and its side converter. rscip K represents the proportional coefficient of the inner ring on the RSC rotor side. rscir This represents the proportional coefficient of the outer ring on the RSC rotor side.

[0120] S102, Based on the transfer function between the change in electromagnetic torque on the rotor side and the disturbance of rotor speed, determine the subsynchronous resonant damping control strategy for adding electromagnetic torque to the target doubly fed wind turbine.

[0121] like Figure 2 The diagram shown is a schematic of the additional subsynchronous resonance damping control strategy, where G... Tω G′ represents electromagnetic torque. Tω G represents the change in total electromagnetic torque. SSDC G′ represents the additional electromagnetic torque. Tω-x The x-axis component of the total electromagnetic torque change, Δω r This represents the rotor speed disturbance. Based on this diagram, the mechanism of subsynchronous resonance can be deduced from a physical perspective, allowing for the design of corresponding subsynchronous resonance damping control strategies. The rotor-side electromagnetic torque change ΔT er and rotor speed disturbance Δω r The transfer function coefficients between them are at the subsynchronous frequency, assuming the rotor speed disturbance Δω r And the change in electromagnetic torque on the rotor side ΔT er In the complex plane coordinate system formed by the transfer functions between them, the rotor speed disturbance Δω r The change in electromagnetic torque ΔT on the rotor side coincides with the positive x-axis direction. er When the phase angle is in the range of [-90°, 90°], the change in electromagnetic torque ΔT on the rotor side er The projection onto the x-axis lies in the positive direction of the x-axis, and is related to the rotor speed disturbance Δω. r In the same direction, this generates negative damping for the subsynchronous resonance, causing the subsynchronous resonance phenomenon to occur; conversely, when the change in electromagnetic torque ΔT on the rotor side is opposite, er When the phase angle is in the range of [90°, 270°], the change in electromagnetic torque ΔT on the rotor side er The projection on the x-axis is located in the opposite direction of the x-axis, and is related to the rotor speed disturbance Δω. r The opposite direction can achieve a positive damping effect on subsynchronous resonance, reduce the risk of subsynchronous resonance, and reduce the change in electromagnetic torque ΔT on the rotor side. er The closer the phase angle is to 180°, the greater the change in rotor-side electromagnetic torque ΔTer The larger the component on the x-axis, the greater the damping effect on the subsynchronous resonance.

[0122] S103, The subsynchronous resonant damping control strategy is added to the d-axis controller of the rotor-side converter of the target doubly fed wind turbine;

[0123] After determining the subsynchronous resonance damping control strategy based on the mechanism of subsynchronous resonance, it is necessary to attach the subsynchronous resonance damping control strategy to the d-axis controller of the rotor-side converter of the target doubly-fed wind turbine. This allows the d-axis excitation voltage to be controlled by the d-axis controller attached to the rotor-side converter of the target doubly-fed wind turbine. By controlling the d-axis excitation voltage, the change in rotor-side electromagnetic torque is adjusted. That is, an electromagnetic torque is superimposed on the original electromagnetic torque, so that the projection of the change in rotor-side electromagnetic torque on the x-axis is in the opposite direction of the x-axis, opposite to the direction of the rotor speed disturbance. This achieves a positive damping effect on subsynchronous resonance and reduces the risk of subsynchronous resonance.

[0124] In this embodiment, the method further includes:

[0125] A mathematical model of the d-axis controller of the rotor-side converter of the target doubly-fed wind turbine unit with the addition of a subsynchronous resonant damping control strategy is constructed.

[0126] Based on the transfer function and mathematical model, the relationship between the change in rotor-side electromagnetic torque and the rotor speed disturbance after adding the subsynchronous resonance damping control strategy is obtained, where the relationship is as follows:

[0127] ΔT ersedc* =G SEDC (s)Δω r* (1)

[0128] Where, ΔT ersedc Δω represents the change in rotor-side electromagnetic torque after the addition of a subsynchronous resonance damping control strategy. r G is the rotor speed disturbance. SEDC (s) is the transfer function between the rotor speed disturbance and the rotor-side electromagnetic torque change after the addition of the subsynchronous resonant damping control strategy.

[0129] like Figure 3 The diagram shown is a control block diagram of the d-axis controller of the rotor-side converter after adding a subsynchronous resonant damping control strategy in a specific example. G... Terw (s) represents the additional subsynchronous resonance damping control strategy, U Rdref* ΔU is the output reference voltage of the rotor-side converter without the addition of a subsynchronous resonant damping control strategy. sedc*is the output voltage generated after the torque control with the subsynchronous resonance damping control strategy added.

[0130] According to Figure 3 the control block diagram corresponding to the d-axis control strategy, the expression of the d-axis output voltage U' of the rotor-side converter with the subsynchronous resonance damping control strategy added can be derived as follows: Rdref*

[0131] U' Rdref* = U Rdref* + ΔU sedc* (27)

[0132]

[0133] ΔU sedc* = G Terω (s)Δω r* (29)

[0134] wherein K rscip represents the RSC rotor-side inner loop proportional coefficient, K iir represents the RSC rotor-side inner loop integral coefficient, K rscii represents the RSC rotor-side outer loop proportional coefficient, K iω represents the RSC rotor-side outer loop integral coefficient, and ω rref represents the rotor speed given value.

[0135] Assuming that the output voltage of the rotor-side converter is the reference voltage, i.e., the voltage control outer loop is ignored, and the equations (27)-(29) are combined, the mathematical model of the d-axis controller of the rotor-side converter with the subsynchronous resonance damping control strategy added can be obtained as follows:

[0136]

[0137] Without any transformation, i.e., G Terω (s) = 1, the equations (25), (26) and (30) are combined, and the relationship between the rotor-side electromagnetic torque variation ΔT ersedc and the rotor speed disturbance Δω r after the subsynchronous resonance damping control strategy is added can be obtained as follows:

[0138]

[0139] wherein G SEDC (s) is the transfer function between the rotor speed disturbance Δω r and the rotor-side electromagnetic torque variation ΔT ersedc after the subsynchronous resonance damping control strategy is added. According to the step S102, the relationship between the rotor speed disturbance Δω Figure 2 ​The phase angle of the transfer function G SEDC (s) between the rotor speed disturbance Δω r and the rotor-side electromagnetic torque variation ΔT ersedc is closer to 180°, the phase of the new torque generated by the superposition of the additional electromagnetic torque and the original electromagnetic torque is closer to 180°, and the system has a greater damping effect on the subsynchronous resonance at the frequency, thereby reducing the risk of subsynchronous resonance of the doubly-fed wind power generator at the frequency. According to the above inference, the phase of G SEDC (s) can be adjusted by an additional subsynchronous resonance damping control strategy, so that the phase angle of the adjusted overall transfer function can reach 180°, thereby achieving the maximum positive damping effect on the subsynchronous resonance.

[0140] Therefore, in this example, a subsynchronous resonance damping control strategy with phase compensation as the core is added to the d-axis controller of the rotor-side converter, and the rotor speed disturbance is used as the feedback quantity. After the addition of the subsynchronous resonance damping control strategy, the d-axis controller of the rotor-side converter generates an electromagnetic torque component that is in the opposite phase of the rotor speed disturbance, so as to achieve the suppression of the subsynchronous resonance.

[0141] Since G SEDC (s) is the transfer function between the rotor speed disturbance Δω r and the rotor-side electromagnetic torque variation ΔT ersedc , the rotor speed signal needs to be appropriately filtered, and the cutoff frequency parameter of the filter needs to be adjusted according to different subsynchronous resonance frequencies.

[0142] Specifically, in this embodiment, as shown in Figure 4 , a flowchart of the subsynchronous resonance damping control strategy, the subsynchronous resonance damping control strategy mainly includes a filtering link, a subsynchronous frequency detection link, and a phase compensation link, wherein,

[0143] The filtering link is used to gate out the subsynchronous resonance component in the rotor speed;

[0144] The subsynchronous frequency detection link is used to detect the subsynchronous frequency value of the subsynchronous resonance existing in the power transmission system in which the doubly-fed wind power generator transmits wind power to the outside through the series compensation transmission line, wherein the subsynchronous frequency value is used for adaptive control of the filtering parameter of the filtering link;

[0145] The phase compensation link is used to adjust the phase angle of the transfer function between the rotor speed disturbance and the rotor-side electromagnetic torque variation after the addition of the subsynchronous resonance damping control strategy to 180°, so as to comply with step S102 of adjusting the phase angle of the overall transfer function to 180° according to Figure 2The maximum positive damping mechanism of the derived subsynchronous resonance is achieved to realize the maximum positive damping effect on the subsynchronous resonance.

[0146] Since the control target of the subsynchronous resonance damping control strategy is the disturbance amount Δω r in the rotor speed signal, a corresponding filter link needs to be designed for the rotor speed signal to select out the subsynchronous resonance component in the rotor speed signal. In this embodiment, the filter used by the filter link includes a second-order high-pass filter and a second-order band-pass filter, and the cutoff frequency of the second-order high-pass filter and the cutoff frequency of the second-order band-pass filter are both determined by the subsynchronous frequency value, wherein,

[0147] For the direct current component and the low frequency component existing in the rotor speed signal, a second-order high-pass filter can be introduced to filter out, and the transfer function of the second-order high-pass filter is as follows:

[0148]

[0149] Wherein, G HPF (s) is the transfer function of the second-order high-pass filter, Q hpass is the quality factor of the second-order high-pass filter, and ω hpass is the cutoff angular velocity of the second-order high-pass filter.

[0150] For the subsynchronous frequency component in the rotor speed, in order to reduce the influence of the subsequent phase compensation link on the non-subsynchronous frequency signal, a second-order band-pass filter can be used to select out the subsynchronous resonance component to improve the amplitude-frequency characteristic of the subsynchronous resonance damping controller as a whole, and the transfer function of the second-order band-pass filter is as follows:

[0151]

[0152] Wherein, G BPF (s) is the transfer function of the second-order band-pass filter, Q pass is the quality factor of the second-order band-pass filter, and ω pass is the cutoff angular velocity of the second-order band-pass filter.

[0153] Specifically, in this embodiment, the cutoff frequency of the second-order band-pass filter can be set to the subsynchronous resonance frequency, and the cutoff frequency of the second-order high-pass filter can be set to 50% of the subsynchronous resonance frequency.

[0154] The phase compensation link is the core link of the whole subsynchronous resonance damping control strategy. In order to realize the maximum positive damping effect on the subsynchronous resonance, the rotor speed disturbance amount Δω r and the rotor-side electromagnetic torque change amount ΔT ersedcThe phase angle of the total transfer function obtained by multiplying the transfer function between the two and the transfer function of the additional filter link is adjusted to 180°, while ensuring that the adjustment phase does not affect the gain size of the transfer function. Therefore, the phase adjustment requirement can be realized by a phase compensator. In order to make the phase adjustment more flexible and variable, and improve the damping control effect on subsynchronous resonance, the embodiment adopts a high-order lead / lag phase compensator, which can realize 360° range of lead / lag phase compensation. Specifically, the transfer function of the lead / lag phase compensator in the embodiment is as follows:

[0155]

[0156] wherein K shift is the gain of the phase compensator, T s1 and T s2 are the time parameters of the phase compensator, and n is the compensation number of the phase compensator.

[0157] In this example, a subsynchronous resonance damping control strategy with phase compensation as the core is added to the d-axis controller of the rotor-side converter. The rotor speed disturbance is used as the feedback quantity, and the d-axis controller of the rotor-side converter generates an electromagnetic torque component opposite in phase to the rotor speed disturbance after the addition of the subsynchronous resonance damping control strategy, so as to realize the suppression of subsynchronous resonance.

[0158] S104, based on the d-axis controller of the rotor-side converter of the target double-fed wind turbine after the addition of the subsynchronous resonance damping control strategy, the target double-fed wind turbine is controlled to generate an electromagnetic torque opposite in phase to the rotor speed disturbance to suppress the subsynchronous resonance of the target double-fed wind turbine.

[0159] The online calculation of the optimal parameters of the phase compensator cannot meet the real-time requirements of subsynchronous resonance suppression, therefore, in this embodiment, an intelligent optimization algorithm is used to calculate the optimal parameters of the control parameters of the phase compensation link under all operating conditions, and the best parameters under different speeds and different subsynchronous oscillation frequencies are selected to realize effective suppression of subsynchronous oscillation. Specifically, the control parameters of the phase compensation link include the time parameters T s1 and T s2 of the phase compensator, and the compensation number n of the phase compensator.

[0160] The traditional particle swarm optimization algorithm simulates a bird swarm by establishing a group of particles. These particles have no mass, only two attributes of speed and position, and each particle moves independently within a given range. The position and speed formula in formula (32) is used to update and iterate each particle, and finally the optimal parameter value is obtained.

[0161]

[0162] where t is the current iteration number, i is the number of different particles in the group, ω is the inertia weight, v i is the current speed of the i-th particle, x i is the current position of the i-th particle, c1 is the individual learning factor, c2 is the group learning factor, rand1 and rand2 are random numbers between 0 and 1, pbest i is the individual optimal value, gbest i is the global optimal value.

[0163] The particle swarm optimization algorithm is an optimization algorithm relying on swarm intelligence search. When all particles of the entire particle swarm are gathered in one or several specific positions and no longer move, it indicates that the particle swarm has matured in the current state, that is, the algorithm has completed convergence. However, the traditional particle swarm optimization algorithm has the problem of too fast convergence speed, and it is easy to occur that the position gathered by the particle is not the real global optimal position when the particle swarm matures. In this case, it can be considered that the algorithm falls into a local optimal problem, resulting in errors in the output result.

[0164] Therefore, the traditional particle swarm optimization algorithm is improved in the embodiment, further improving the fast convergence ability and reducing the risk of falling into a local optimal problem due to premature convergence of the algorithm.

[0165] The value of the inertia weight ω determines the strength of the global and local optimization abilities of the algorithm. When the value of the inertia weight ω is large, the proportion of the historical speed in the speed update formula is high, causing the search range of the algorithm to be wider, thereby improving the global search ability of the algorithm and accelerating the convergence speed of the algorithm, but there is also the shortcoming of weakening the local search performance of the algorithm; on the contrary, when the value of ω is small, the influence of the historical speed will be small, thereby strengthening the local optimization ability of the algorithm, but also reducing the convergence speed of the algorithm. According to the above-described characteristics, the value of the inertia weight ω needs to be optimized and designed. The optimization goal of the inertia weight ω is to enable the algorithm to improve the convergence speed in the early stage of running, thereby rapidly reducing the search range of the algorithm; in the later stage of running of the algorithm, since the search range is greatly reduced, the convergence speed of the algorithm needs to be appropriately reduced, so that more computing power is concentrated on searching for the optimal value in the existing range rather than further shrinking the search range, thereby improving the local search ability of the algorithm and avoiding the problem of falling into a local optimal problem due to too fast convergence. In order to solve this problem, the linear differential decreasing strategy is used to optimize the inertia weight ω in the particle swarm optimization algorithm.

[0166] Specifically, the calculation formula of the inertia weight ω of the improved particle swarm optimization algorithm is as follows:

[0167]

[0168] where ω min is the minimum value of the inertia weight ω, ω max is the maximum value of the inertia weight ω, t is the current iteration number, t max is the maximum iteration number set.

[0169] Take ω min = 0.4, ω max = 1.0, t max = 1000, the function image of ω(t) is drawn with ω(t) as the x-axis and t as the y-axis, as shown in Figure 5 .

[0170] As can be seen from Figure 5 , the inertia weight ω(t) and the current iteration number t of the algorithm present a negative correlation. And in the initial stage of iteration, ω(t) slowly decreases, so that the algorithm can meet the fast convergence mentioned in the foregoing in the initial stage of algorithm operation; as the iteration number increases, ω(t) starts to decrease, and the decreasing trend also starts to gradually accelerate, so that the algorithm reduces the convergence speed after determining the range of each local optimum, and more finely searches for the optimal value in the existing range, thereby avoiding falling into the local optimum problem. Compared with the commonly used linear decreasing optimization strategy of inertia weight, the linear differential decreasing strategy has a smaller reduction rate of inertia weight in the early stage of algorithm operation, and the inertia weight is rapidly reduced in the later stage of operation, so that the strategy can more effectively reduce the most significant premature convergence and local optimum problem in the traditional particle swarm optimization algorithm.

[0171] The learning factors c1 and c2 also have a crucial influence on the search ability and convergence speed of the particle swarm optimization algorithm, and therefore appropriate optimization measures can also be adopted. The learning factors affect the weight size of the individual extreme value and the population extreme value in the speed update formula, wherein the value of c1 affects the local search ability of the algorithm, and the value of c2 affects the global search ability of the algorithm. In order to achieve the optimization goal of ensuring the fast convergence of the traditional particle swarm optimization algorithm while reducing the risk of falling into the local optimum, the method of introducing an asynchronous learning factor is introduced to improve the traditional particle swarm optimization algorithm: in the initial stage of algorithm operation, a larger value is assigned to c1, and a smaller value is taken for c2, so as to improve the weight proportion of the optimal value pbest i of each particle in the speed update formula, thereby improving the global search ability of the algorithm; in the later stage of algorithm operation, a smaller value is taken for c1, and a larger value is taken for c2, so as to improve the overall optimal value gbest ithe weight proportion in the velocity update formula, so as to strengthen the local search ability of the algorithm; during the running of the algorithm, the values of c1 and c2 are changed through a linear strategy, c1 linearly decreases to affect the weight of individual extreme value, and c2 linearly increases to affect the weight of group extreme value. After the introduction of the linear change of the asynchronous learning factor improvement measure, the asynchronous learning factor update calculation formula of the improved particle swarm optimization algorithm is as follows:

[0172]

[0173] wherein, c1 is an individual learning factor, c2 is a group learning factor, c 1intial is an initial value of c1, c 1end is a final value of c1, c 2intial is an initial value of c1, c 2end is a final value of c2, t is a current iteration number, t max is a set maximum iteration number;

[0174] For the velocity update calculation formula, the present embodiment proposes a contraction factor particle swarm optimization algorithm (CFPSO) to optimize it. Compared with the traditional particle swarm optimization algorithm, the improvement measure introduces a new parameter, called contraction factor parameter The velocity update formula of the improved particle swarm optimization algorithm is as follows:

[0175]

[0176] wherein, t is a current iteration number, i is the number of different particles in the group, ω is an inertia weight, v i is a current speed of the i-th particle, x i is a current position of the i-th particle, c1 is an individual learning factor, c2 is a group learning factor, rand1 and rand2 are random numbers between 0 and 1, pbest i is an individual optimal value, gbest i is a global optimal value, is a contraction factor, wherein, the expression of the contraction factor is as follows:

[0177]

[0178] After the introduction of the contraction factor parameter , the individual search ability and convergence speed of the algorithm are improved.

[0179] In this embodiment, the shrinkage factor is introduced to improve and optimize the inertia weight coefficient, learning factor and velocity update formula of the traditional particle swarm optimization algorithm. The optimization goal of the algorithm is to improve the convergence speed of the algorithm while reducing the risk of falling into local optimum. The flow chart of the optimized algorithm is shown in Figure 6 .

[0180] In order to more intuitively show the beneficial effects of the additional electromagnetic torque based DFIG wind turbine subsynchronous resonance suppression method of the present embodiment, the subsynchronous resonance damping control strategy is added to the rotor side converter control of the DFIG wind turbine in the Simulink simulation model, and the operating condition setting and the optimal control parameter values calculated under the subsynchronous resonance condition are substituted. The series compensation device is set to be put into operation at 3s; the subsynchronous resonance damping control strategy is put into operation at 4s. The simulation waveforms obtained are shown in Figures 7(a)-7(d) , wherein Fig. 7(a) is an active power simulation waveform diagram, Fig. 7(b) is a rotor speed simulation waveform diagram, Fig. 7(c) is a rotor side current a-phase simulation waveform diagram, and Fig. 7(d) is a stator side current a-phase simulation waveform diagram.

[0181] As can be seen from Figures 7(a)-7(d) , the simulation model occurs subsynchronous resonance phenomenon due to the input of series compensation device at 3s; after the simulation model runs to 4s, i.e. the subsynchronous resonance damping control strategy is put into operation, the active power, rotor speed, rotor side current and stator side current waveforms are rapidly changed from the original divergent trend to the convergent trend, which shows that the additional damping control strategy improved based on high-order lead / lag phase compensator can well suppress the subsynchronous resonance caused by the DFIG wind turbine through the series compensation device.

[0182] According to Figures 8(a)-8(e) (wherein, Figures 8(a)-8(e)It can be seen from the simulation waveform graphs of the active power of the doubly-fed wind turbine in the working conditions 1-5 that the convergence speed of the Best1 waveform (simulation result after the additional subsynchronous resonance damping control strategy) in Fig. 8 (b) and the Best2 waveform (simulation result of the particle swarm optimization algorithm) in Fig. 8 (d) is slightly higher than that of the PSO waveform (simulation result of the particle swarm optimization algorithm improved for the subsynchronous resonance damping control strategy) in the respective simulation graphs, so it can be concluded that the optimal control parameters obtained through calculation in a single working condition have slightly better suppression ability on subsynchronous resonance in the respective specific working condition than the optimal parameters obtained through the improved particle swarm optimization algorithm in all working conditions, further verifying the correctness of the additional electromagnetic torque subsynchronous resonance mechanism analysis. However, due to the difficulty in predicting the subsynchronous resonance phenomenon in actual engineering, it is difficult to predict the working condition of the doubly-fed wind turbine and the subsynchronous resonance frequency when the subsynchronous resonance occurs in advance, and the optimal control parameters of the damping control strategy require a large amount of calculation, which makes it difficult to realize rapid and accurate control parameter calculation in actual engineering in case of an emergency.

[0183] In addition to the above, Figures 8(a)-8(e) The PSO waveform in other simulation waveform graphs will be better than the Best1 and Best2 waveforms in convergence speed, so as to reflect that the parameters obtained through the improved particle swarm optimization algorithm have excellent convergence speed while improving the global optimization ability in a wide range of working conditions, and reflect that the subsynchronous damping control strategy under the parameters has excellent adaptability, and achieves the expected design goal of the particle swarm optimization algorithm improved for the damping control strategy.

[0184] It can be seen from the above that the embodiment of the application is directed to the subsynchronous resonance damping control strategy of the doubly-fed wind turbine through the series compensation transmission line external sending system, and the physical mechanism derivation is lacking in the aspect of the subsynchronous resonance generation mechanism, so the transfer function between the rotor speed disturbance and the rotor-side electromagnetic torque is derived, and the damping control strategy is optimized and designed, mainly including: improving the filter combination mode of the filter link, proposing a fast subsynchronous frequency detection strategy to realize adaptive control of the filter cutoff frequency, and using a high-order lead / lag phase compensator to improve the phase compensation link, so that the link can realize 360° lead / lag phase compensation capability. Then, aiming at the problems that the subsynchronous resonance of the doubly-fed wind turbine cannot be predicted and the wind turbine working conditions are numerous, the traditional particle swarm optimization algorithm is improved, the rapid convergence ability is further improved, and the risk of falling into local optimum due to premature convergence of the algorithm is also reduced. And the improved particle swarm optimization algorithm is used to select the optimal parameters of the phase compensation link of the subsynchronous resonance damping control strategy in all working conditions.

[0185] The present application realizes all or part of the processes in the above-mentioned embodiment methods, which can be completed by a computer program instructing relevant hardware. The computer program can be stored in a computer readable storage medium, and when executed by a processor, the computer program can realize the steps of the above-mentioned various method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content included in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

[0186] Those skilled in the art will appreciate that a combination of features of different embodiments means within the scope of the present application and forms different embodiments, although some embodiments herein include certain features rather than other features included in other embodiments. For example, in the following claims, any one of the claimed embodiments can be used in any combination.

[0187] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for suppressing subsynchronous resonance in a doubly-fed wind turbine based on additional electromagnetic torque, characterized in that, The method includes the following steps: Based on the flux linkage equation and the rotor-side electromagnetic torque expression of a three-phase asynchronous motor, a transfer function is constructed between the change in rotor-side electromagnetic torque and the rotor speed disturbance. Based on the transfer function between the rotor-side electromagnetic torque change and the rotor speed disturbance, a subsynchronous resonant damping control strategy for applying additional electromagnetic torque to the target doubly-fed wind turbine is determined. This subsynchronous resonant damping control strategy includes a filtering stage, a subsynchronous frequency detection stage, and a phase compensation stage. The filtering stage is used to select the subsynchronous resonance component in the rotor speed. The subsynchronous frequency detection stage is used to detect the subsynchronous frequency value of the subsynchronous resonance in the power transmission system that transmits wind power from the doubly fed wind turbine to the outside through the series compensation transmission line. The subsynchronous frequency value is used for the adaptive control of the filtering parameters of the filtering stage. The phase compensation stage is used to adjust the phase angle of the transfer function between the speed disturbance and the change in electromagnetic torque on the rotor side after the addition of the subsynchronous resonance damping control strategy to 180°, so as to achieve the maximum positive damping effect of the subsynchronous resonance. The subsynchronous resonance damping control strategy is applied to the d-axis controller of the rotor-side converter of the target doubly-fed wind turbine, specifically including: A mathematical model of the d-axis controller of the rotor-side converter of the target doubly-fed wind turbine unit with the addition of a subsynchronous resonant damping control strategy is constructed. Based on the transfer function and the mathematical model, the relationship between the change in rotor-side electromagnetic torque and the rotor speed disturbance after adding the subsynchronous resonance damping control strategy is obtained, wherein the relationship is as follows: Where * denotes conjugate, ΔT ersedc Δω represents the change in rotor-side electromagnetic torque after the addition of a subsynchronous resonance damping control strategy. r G is the rotor speed disturbance. SEDC (s) is the transfer function between the rotor speed disturbance and the rotor-side electromagnetic torque change after the addition of the subsynchronous resonant damping control strategy, where i sd0 and i sq0 L represents the steady-state current on the stator side in the dq coordinate system. rsc and R R ω represents the impedance parameters of the rotor and its side converter. Base ω represents the reference value of angular velocity, s = 2πjω represents the complex frequency, and ω represents the angular velocity reference value. s0 ω represents the steady-state rotational speed on the stator side. r0 Indicates the steady-state speed on the rotor side; The d-axis controller of the rotor-side converter of the target doubly-fed wind turbine is based on the subsynchronous resonance damping control strategy. The rotor speed disturbance is used as feedback to generate an electromagnetic torque that is opposite in phase to the rotor speed disturbance in order to suppress the subsynchronous resonance of the target doubly-fed wind turbine.

2. The method for suppressing subsynchronous resonance of a doubly-fed wind turbine based on additional electromagnetic torque according to claim 1, characterized in that, The filtering stage employs a second-order high-pass filter and a second-order band-pass filter. The cutoff frequencies of both the second-order high-pass and band-pass filters are determined by the subsynchronous frequency value. The second-order high-pass filter is used to filter out the DC component and low-frequency component in the rotor speed signal. The transfer function of the second-order high-pass filter is as follows: Among them, G HPF (s) is the transfer function of a second-order high-pass filter, Q hpass ω is the quality factor of the second-order high-pass filter. hpass This represents the cutoff angular velocity of the second-order high-pass filter. The second-order bandpass filter is used to select the subsynchronous resonance component from the rotor speed signal processed by the second-order highpass filter. The transfer function of the second-order bandpass filter is as follows: Among them, G BPF (s) is the transfer function of a second-order bandpass filter, Q pass ω is the quality factor of a second-order bandpass filter. pass This represents the cutoff angular velocity of the second-order bandpass filter.

3. The method for suppressing subsynchronous resonance of a doubly-fed wind turbine based on additional electromagnetic torque according to claim 2, characterized in that, The phase adjustment in the phase compensation stage employs a high-order lead / lag phase compensator to achieve 360° lead / lag phase compensation. The transfer function of the lead / lag phase compensator is as follows: Among them, K shift For the gain of the phase compensator, T s1 and T s2 is the time parameter of the phase compensator, and n is the number of compensation cycles of the phase compensator.

4. The method for suppressing subsynchronous resonance of a doubly-fed wind turbine based on additional electromagnetic torque according to claim 3, characterized in that, The method further includes: An improved particle swarm optimization algorithm is used to perform parameter optimization calculations for the control parameters of the subsynchronous resonant damping control strategy in the phase compensation stage under all operating conditions. These control parameters include the time parameter T of the phase compensator. s1 and T s2 And the number of compensation cycles n of the phase compensator.

5. The method for suppressing subsynchronous resonance of a doubly-fed wind turbine based on additional electromagnetic torque according to claim 4, characterized in that, The formula for calculating the inertia weight ω in the improved particle swarm optimization algorithm is as follows: Where, ω min The minimum value of the inertial weight ω, ω max Let ω be the maximum value of the inertia weight, and t be the current iteration number. max The maximum number of iterations is set. The asynchronous learning factor update calculation formula of the improved particle swarm optimization algorithm is as follows: Where c1 is the individual learning factor, c2 is the group learning factor, and c... 1intial Let c1 be the initial value, and c 1end The final value of c1, c 2intial Let c1 be the initial value, and c 2end c2 represents the final value, and t represents the current iteration number. max The maximum number of iterations is set. The velocity update formula for the improved particle swarm optimization algorithm is as follows: Where t is the current iteration number, i is the number of different particles in the swarm, ω is the inertia weight, and v i Let x be the current velocity of the i-th particle. i Let c1 be the current position of the i-th particle, c2 be the individual learning factor, c2 be the group learning factor, and rand1 and rand2 be random numbers between [0,1]. pbest i For the individual optimal value, gbest i The global optimal value. Let be the contractility factor, where is the contractility factor. The expression is as follows:

6. The method for suppressing subsynchronous resonance of a doubly-fed wind turbine based on additional electromagnetic torque according to any one of claims 1-5, characterized in that, The transfer function constructed based on the flux linkage equation and the rotor-side electromagnetic torque expression of a three-phase asynchronous motor includes: Based on the flux linkage equation and Lenz's law of a three-phase asynchronous motor, and by performing an abc-dq coordinate system transformation, the expression for the change in rotor-side induced electromotive force is obtained. By standardizing and Laplace transforming the expression for the change in rotor-side induced electromotive force, the relationship between the per-unit value of the change in rotor-side induced electromotive force and the per-unit value of rotor speed disturbance in the dq coordinate system is obtained. The expression for the rotor-side electromagnetic torque of a three-phase asynchronous motor is linearized within a small range and then transformed using Laplace transform to obtain the expression for the change in rotor-side electromagnetic torque. Based on the Laplace transform, the expression for the change in rotor-side electromagnetic torque and the relationship between the per-unit value of the change in rotor-side induced electromotive force and the per-unit value of rotor speed disturbance in the dq coordinate system are obtained, thus yielding the transfer function between the change in rotor-side electromagnetic torque and the rotor speed disturbance.

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