A damping control method of a wind power grid-connected system and related equipment

Abstract

The embodiment of the application discloses a damping control method of a wind power grid-connected system and related equipment, through obtaining the interactive energy of the direct-drive wind power grid-connected system, the contribution degree of the interaction between control links to the system stability can be quantitatively characterized, and meanwhile, the application realizes the system oscillation suppression considering the voltage support demand from the perspective of the interactive energy dissipation rate optimization, and can effectively improve the oscillation stability of the direct-drive wind turbine during the fault ride-through process based on the optimization control scheme constructed based on the first non-periodic component change rate and the second non-periodic component change rate during the fault ride-through.

Description

Technical field

[0001] The present invention relates to the technical field of direct-drive wind power grid-connected system control, and in particular to a damping control method and related equipment for a wind power grid-connected system. [Background Technology]

[0002] In recent years, low voltage ride-through control has been incorporated into the basic functions of wind turbines to ensure stable operation during faults and provide a certain degree of reactive power support for the power grid. However, after low voltage ride-through control is put into operation, it may couple with the wind turbine control link, changing its damping characteristics during faults and causing oscillation stability problems. To address the oscillation suppression problem that occurs in direct-drive wind power grid-connected systems, solutions can be roughly divided into three categories based on the suppression principle: optimizing controller parameters, changing the control link topology, and adding damping. However, these strategies all ignore the impact of the low voltage ride-through control process on system stability, and with damping as the sole control objective, it is difficult to achieve systematic optimization of voltage support and system oscillation stability. [Summary of the invention]

[0003] In view of this, the present invention provides a damping control method and related equipment for a wind power grid-connected system.

[0004] The specific technical solution of the first embodiment of the present invention is: a damping control method for a wind power grid-connected system, the method comprising: constructing a state space model of multiple subsystems of the direct-drive wind power grid-connected system by analyzing the control strategy of the direct-drive wind power grid-connected system in the transient stage of the fault; the subsystems include a low voltage ride-through d-axis subsystem, a low voltage ride-through q-axis subsystem, a phase-locked loop subsystem, a power grid d-axis subsystem and a power grid q-axis subsystem; obtaining the dynamic energy of each state space model based on the state space model and energy function construction method of each subsystem; the dynamic energy includes the stored energy and the interaction energy expression between each subsystem; obtaining the interaction energy of each subsystem based on the stored energy and the interaction energy expression Item; obtain the first non-periodic component change rate and the second non-periodic component change rate according to the direct-drive wind turbine control structure and the interactive energy item; the first non-periodic component change rate is the non-periodic component change rate in the interactive energy between the low voltage ride-through control and the d-axis current inner-loop sub-control system, and the second non-periodic component change rate is the non-periodic component change rate in the interactive energy between the low voltage ride-through control and the q-axis current inner-loop sub-control system; construct the objective function of the direct-drive wind power grid-connected system during fault ride-through and the parameter constraints of the objective function based on the first non-periodic component change rate and the second non-periodic component change rate; perform damping control on the direct-drive wind power grid-connected system with the objective function and the parameter constraints as targets.

[0005] Preferably, the state space model and energy function construction method based on each subsystem obtains the dynamic energy of each state space model, including: cross-multiplying the state space model by two equations and integrating the time to obtain the dynamic energy model of each state space model; the dynamic energy model includes expressions for stored energy, dissipated energy and interaction energy between subsystems; and obtaining the dynamic energy in the dynamic energy model.

[0006] Preferably, the method of obtaining the first non-periodic component change rate and the second non-periodic component change rate based on the direct-drive wind turbine control structure and the interactive energy term includes: obtaining the non-periodic component based on the current inner loop control response equation of the direct-drive wind turbine control structure, the interactive energy term in the low voltage ride-through d-axis subsystem, and the interactive energy term in the low voltage ride-through q-axis subsystem; and extracting the non-periodic component to obtain the first non-periodic component change rate and the second non-periodic component change rate when the induced mode after the direct-drive wind power grid-connected system is disturbed is synchronous oscillation.

[0007] Preferably, the first non-periodic component change rate is obtained using the following formula:

[0008]

[0009] in, is the derivative of the rate of change of the first non-periodic component, θ0 is the steady-state value of the phase difference between the PCC point voltage and the fault point voltage, K pd is the proportional gain coefficient, ω c is the synchronous angular frequency, e is a constant, α is the real part of the synchronous oscillation, t is the time, I max is the maximum allowable current value of the grid-side converter during the fault phase, A ref A is the oscillation amplitude of the current reference value change of the current inner loop, Id1 is the oscillation amplitude of the d-axis component of the wind turbine terminal current, θ ref is the oscillation phase angle of the current reference value change of the current inner loop, θ d is the oscillation phase angle of the change in the d-axis component of the wind turbine terminal current.

[0010] Preferably, the second non-periodic component change rate is obtained using the following formula:

[0011]

[0012] in, is the derivative of the rate of change of the second non-periodic component, K pd is the proportional gain coefficient, θ0 is the steady-state value of the phase difference between the PCC point voltage and the fault point voltage, e is a constant, α is the real part of the synchronous oscillation, t is the time, A refA is the oscillation amplitude of the current reference value change of the current inner loop, Iq1 is the oscillation amplitude of the q-axis component of the wind turbine terminal current, θ ref is the oscillation phase angle of the current reference value change of the current inner loop, θ q is the oscillation phase angle of the change in the q-axis component of the wind turbine terminal current.

[0013] Preferably, the parameter constraints include transient voltage support constraints, converter capacity constraints and reactive current compensation coefficient constraints.

[0014] Preferably, the damping control of the direct-drive wind power grid-connected system with the objective function and the parameter constraints as the target includes: constructing a parameter optimization model of the direct-drive wind power grid-connected system in the transient stage of the fault according to the objective function and the parameter constraints; determining the control parameters of the direct-drive wind power grid-connected system parameter optimization model by using a pattern search method and the direct-drive wind power grid-connected system parameter optimization model; and performing damping control on the direct-drive wind power grid-connected system by using the control parameters.

[0015] The specific technical solution of the second embodiment of the present invention is: a damping control system of a wind power grid-connected system, the system comprising: a state space model construction module, a dynamic energy acquisition module, an interactive energy acquisition module, a non-periodic component change rate acquisition module, an optimization module and a control module; the state space model construction module is used to construct a state space model of multiple subsystems of the direct-drive wind power grid-connected system by analyzing the control strategy of the direct-drive wind power grid-connected system in the transient stage of the fault; the subsystems include a low voltage ride-through d-axis subsystem, a low voltage ride-through q-axis subsystem, a phase-locked loop subsystem, a power grid d-axis subsystem and a power grid q-axis subsystem; the dynamic energy acquisition module is used to obtain the dynamic energy of each state space model based on the state space model of each subsystem and the energy function construction method; the dynamic energy includes the stored energy and the interactive energy expression between each subsystem; the interactive energy acquisition module is used to The interactive energy terms of each subsystem are obtained based on the stored energy and the interactive energy expression; the non-periodic component change rate acquisition module is used to obtain the first non-periodic component change rate and the second non-periodic component change rate according to the direct-drive wind turbine control structure and the interactive energy term; the first non-periodic component change rate is the non-periodic component change rate in the interactive energy between the low voltage ride-through control and the d-axis current inner-loop sub-control system, and the second non-periodic component change rate is the non-periodic component change rate in the interactive energy between the low voltage ride-through control and the q-axis current inner-loop sub-control system; the optimization module is used to construct the objective function of the direct-drive wind power grid-connected system during fault ride-through and the parameter constraints of the objective function based on the first non-periodic component change rate and the second non-periodic component change rate; the control module is used to perform damping control on the direct-drive wind power grid-connected system with the objective function and the parameter constraints as the target.

[0016] The specific technical solution of the third embodiment of the present invention is: a damping control device of a wind power grid-connected system, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the method described in any one of the first embodiments of the present application.

[0017] The specific technical solution of the fourth embodiment of the present invention is: a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to perform the steps of the method described in any one of the first embodiments of the present application.

[0018] The implementation of the present invention will have the following beneficial effects:

[0019] The present invention obtains the dynamic energy of each state space model and the interactive energy term based on the state space model and energy function construction method of each subsystem; obtains the first non-periodic component change rate and the second non-periodic component change rate according to the direct-drive wind turbine control structure and the interactive energy term; constructs the objective function of the direct-drive wind power grid-connected system during the fault ride-through period and the parameter constraints of the objective function based on the first non-periodic component change rate and the second non-periodic component change rate. By obtaining the interactive energy of the direct-drive wind power grid-connected system, it is possible to quantitatively characterize the contribution of the interaction between each control link to the stability of the system. At the same time, the application constructs an optimized control scheme during the fault ride-through period based on the first non-periodic component change rate and the second non-periodic component change rate. From the perspective of optimizing the interactive energy dissipation rate, it achieves system oscillation suppression that takes into account the voltage support requirements, and can effectively improve the oscillation stability of the direct-drive wind turbine during the fault ride-through process.

Brief Description of the Drawings

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0021] Figure 1 A flow chart of the steps of a damping control method for a wind power grid-connected system;

[0022] Figure 2 The structure diagram of the direct-drive wind turbine grid-connected system used in the simulation of this application;

[0023] Figure 3 The energy transfer path between the control links of the direct-drive wind power grid-connected system during the fault transient period analyzed in this application;

[0024] Figure 4 To simulate the oscillation divergence condition when the three-phase short circuit voltage drops to 0.8pu at the wind turbine end;

[0025] Figure 5a The change of the total energy of the system along the oscillation divergence trajectory after the fault occurs in the simulation;

[0026] Figure 5b The change of the system interaction energy along the oscillation divergence trajectory after the fault occurs in the simulation;

[0027] Figure 6 To simulate the oscillation convergence condition when the three-phase short circuit voltage drops to 0.85pu at the wind turbine end;

[0028] Figure 7aThe change of the total energy of the system along the oscillation convergence trajectory after the fault occurs in the simulation;

[0029] Figure 7b The change of the system interaction energy along the oscillation convergence trajectory after the fault occurs in the simulation;

[0030] Figure 8 The oscillation curves before and after optimization control for the oscillation divergence scenario in the simulation;

[0031] Figure 9 The dynamic energy changes of the system during the low voltage ride-through process before and after parameter adjustment in the simulation

[0032] Figure 10 This is a structural diagram of the damping control system of the wind power grid-connected system;

[0033] Among them, 201 is a state space model construction module; 202 is a dynamic energy acquisition module; 203 is an interactive energy acquisition module; 204 is a non-periodic component change rate acquisition module; 205 is an optimization module; and 206 is a control module. [Specific implementation method]

[0034] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0035] The terms "first," "second," and the like in the specification, claims, and drawings of this application are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or modules is not limited to the listed steps or modules but may optionally include steps or modules not listed, or may optionally include other steps or modules inherent to the process, method, product, or apparatus.

[0036] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0037] See also Figure 1, is a flowchart of the steps of a damping control method for a wind power grid-connected system in the first embodiment of the present application, the method comprising:

[0038] Step 101: By analyzing the control strategy of the direct-drive wind power grid-connected system in the transient fault phase, a state space model of multiple subsystems of the direct-drive wind power grid-connected system is constructed; the subsystems include a low voltage ride-through d-axis subsystem, a low voltage ride-through q-axis subsystem, a phase-locked loop subsystem, a power grid d-axis subsystem, and a power grid q-axis subsystem;

[0039] Step 102: obtaining the dynamic energy of each state-space model based on the state-space model of each subsystem and the energy function construction method; the dynamic energy includes the stored energy and the interaction energy expression between each subsystem;

[0040] Step 103: Obtain interaction energy terms of each subsystem based on the stored energy and the interaction energy expression;

[0041] Step 104: Obtain a first non-periodic component change rate and a second non-periodic component change rate according to the direct-drive wind turbine control structure and the interactive energy term; the first non-periodic component change rate is the non-periodic component change rate in the interactive energy between the low voltage ride-through control and the d-axis current inner-loop sub-control system, and the second non-periodic component change rate is the non-periodic component change rate in the interactive energy between the low voltage ride-through control and the q-axis current inner-loop sub-control system;

[0042] Step 105: constructing an objective function of the direct-drive wind power grid-connected system during the fault ride-through period and parameter constraints of the objective function based on the first non-periodic component change rate and the second non-periodic component change rate;

[0043] Step 106: Perform damping control on the direct-drive wind power grid-connected system based on the objective function and the parameter constraints.

[0044] Specifically, the control mode of the direct-drive wind power grid-connected system is grid voltage oriented vector control. In the infinite grid voltage oriented vector dq coordinate system, the current inner loop control response equation is:

[0045]

[0046] Where K i , K p are the integral coefficient and proportional coefficient of the current loop control respectively. R and L are the filter resistance and filter inductance of the grid-side converter respectively. d 、i q are the d-axis and q-axis currents output by the grid-side converter respectively. dref 、i qref are the d-axis and q-axis current reference values ​​respectively, and the output is controlled by low voltage ride-through during the fault phase.sd sq are the inverter port d, q-axis voltages, respectively. pccd pccq are the grid-connection point d, q-axis voltages of the wind turbine, respectively. ω0is the synchronous angular frequency, ω0= 100π.

[0047] After the grid-connection point voltage dip occurs in the direct-drive wind power grid-connected system, the voltage outer loop is generally disconnected, and a low voltage ride through control strategy is adopted. The current control instruction i dref qref is obtained according to the voltage dip degree.

[0048]

[0049] In the formula, K represents a reactive current compensation coefficient, which is taken as 1.5 in the embodiment; U pcc represents a grid-connection point voltage standard value; I N represents a rated current; and I max represents a maximum allowable current value of the grid-side converter in the fault stage. Figure 3 In the reference direction, i qref is negative, and the reactive current flows into the wind turbine.

[0050] The direct-drive wind power grid-connected system adopts a PLL phase-locked loop controller to track the voltage phase of the PCC point. The transfer function of the phase-locked loop can be expressed as:

[0051]

[0052] In the formula, u pccq is the q-axis voltage of the grid-connection point of the wind turbine in the dq coordinate system of the voltage directional vector of the infinite grid, K pp and K ip are the proportional and integral parameters of the phase-locked loop PI controller, respectively; and θ pll is the output voltage phase of the phase-locked loop.

[0053] According to the dq coordinate system, the direct-drive wind turbine control system can be divided into five subsystems, namely, the low voltage ride through d-axis subsystem and q-axis subsystem, the phase-locked loop subsystem, the grid d-axis subsystem and the grid q-axis subsystem, and there is a mutual coupling state quantity between each subsystem.

[0054] According to the module decomposition method (CCM) method, combined with the control structure of each subsystem, the modular state space model of the direct-drive wind power grid-connected system can be obtained as follows.

[0055] (1) State space model of the low voltage ride through d-axis subsystem

[0056] ​​​

[0057] Among them, K id , K pd is the d-axis current inner loop integral and proportional gain coefficient, L1 and R1 are the equivalent reactance and resistance from the wind turbine generator set to the PCC point, and θ0 is the PCC point voltage U pcc,dq And the fault point voltage U m,dq The steady-state value of the phase difference between q10 、U q0 and I q1_c0 I dq,1 、U dq and I dq,1c The steady-state value of the q-axis component. cd and U cq are the intermediate state variables of the inner loop control of the dq axis current, I d1 and I q1 are the d-axis and q-axis components of the wind turbine terminal current respectively; I dref and I qref are the reference values ​​of the d-axis and q-axis of the inner current loop respectively; U pccd and U pccq are the d-axis and q-axis components of the grid-connected point voltage respectively; Δ represents the change during the disturbance process. Subscript 0 represents the steady-state component. is the q-axis voltage reference value.

[0058] (2) State space model of the LVRT q-axis subsystem

[0059]

[0060] Among them, K iq , K pq is the q-axis current inner loop integral and proportional gain coefficient, I d10 、U d0 and I d1_c0 I dq,1 、U dq and I dq,1c The steady-state value of the d-axis component.

[0061] (3) State space model of the phase-locked loop subsystem

[0062]

[0063] Where K i_pll and K p_pll are the integral and proportional gain coefficients of the phase-locked loop PI control link respectively; x p_pll is the intermediate state variable of the phase-locked loop; U pccd0 and U pccq0 For U pcc,dq The steady-state values ​​of the d-axis and q-axis components.

[0064] (4) State space model of the equivalent grid d-axis subsystem

[0065]

[0066] Where C t is the grounding capacitance of the PCC point, L2 is the equivalent reactance of the distance between the PCC point and the fault point, I d2 , I q2 is the dq axis current component on the line from PCC point to fault point, ΔI d2 For I dq,2 The perturbation of the d-axis component.

[0067] (5) State space model of the equivalent grid q-axis subsystem

[0068]

[0069] In summary, the above five subsystem expressions can be expressed as:

[0070]

[0071] The differential coefficients on the left in formulas (4) to (8) are uniformly expressed as C, L, and K respectively. R ;K C and K L is a constant term; the state variables are uniformly expressed as ΔU and ΔI respectively; the interaction links that affect the voltage ΔU are uniformly expressed as F C ; The interaction links that affect the current ΔI are all uniformly expressed as F L .

[0072] In a specific embodiment, the state space model and energy function construction method based on each subsystem obtains the dynamic energy of each state space model, including: cross-multiplying the state space model by two equations and integrating the time to obtain the dynamic energy model of each state space model; the dynamic energy model includes expressions of stored energy, dissipated energy and interaction energy between each subsystem; and obtaining the dynamic energy in the dynamic energy model.

[0073] Specifically, based on the energy function construction method, the two equations in equation (9) are cross-multiplied and integrated over time t to obtain the corresponding dynamic energy model. The formula of the dynamic energy model is:

[0074]

[0075] Based on formula (10), the energy function V is defined as:

[0076] V=V s -V d -V t (11)

[0077] In the formula

[0078]

[0079] Among them, V s To store energy; V d Represents resistance K R Dissipated energy on V t Represents the interaction energy between subsystems.

[0080] In a specific embodiment, the first non-periodic component change rate and the second non-periodic component change rate are obtained according to the direct-drive wind turbine control structure and the interactive energy term, including: obtaining the non-periodic component according to the current inner loop control response equation of the direct-drive wind turbine control structure, the interactive energy term in the low voltage ride-through d-axis subsystem, and the interactive energy term in the low voltage ride-through q-axis subsystem; when the induced mode after the direct-drive wind power grid-connected system is disturbed is synchronous oscillation, extracting the non-periodic component to obtain the first non-periodic component change rate and the second non-periodic component change rate.

[0081] In a specific embodiment, the stored energy of each subsystem and its interaction energy with other subsystems are expressed to obtain the interaction energy terms in each subsystem, and the coupling effect of voltage support and damping stability is analyzed. Specifically, by substituting equations (4)-(8) into equation (9), the stored energy of each subsystem and its interaction energy with other subsystems can be analytically obtained. The interaction energy terms in each subsystem are shown below.

[0082] (1) Interaction energy term in the d-axis subsystem of low voltage crossing

[0083]

[0084] Where V t1_LVRT is the interaction energy between the low voltage ride-through control and the d-axis current inner loop subsystem, V t12 is the interaction energy between the q-axis current inner loop subsystem and the d-axis current inner loop subsystem network. t13 is the interaction energy between the phase-locked loop and the d-axis current inner loop subsystem, V t14 is the interaction energy between the grid-side d-axis subsystem and the d-axis current inner loop subsystem, where R k =K pd =K pq .

[0085] It can be seen from formula (14) that after the low voltage ride-through control is put into use, a new dq coupling energy channel is introduced. The interaction energy mainly depends on the low voltage ride-through control parameters.

[0086] (2) Interaction energy term in the q-axis subsystem of low voltage ride-through

[0087]

[0088] where V t2_LVRT is the self-interaction energy between the low voltage ride through control and the q-axis current inner loop subsystem, V t21 is the interaction energy between the d-axis current inner loop subsystem and the q-axis current inner loop subsystem, V t23 is the interaction energy between the phase locked loop and the q-axis current inner loop subsystem, V t25 is the interaction energy between the grid-side q-axis subsystem and the q-axis current inner loop subsystem.

[0089] Comparing equation (14) and equation (15), it can be seen that the dq-axis interaction energy terms are asymmetric after the introduction of the low voltage ride through control.

[0090] (3) Interaction energy term of the phase locked loop subsystem

[0091]

[0092] where V t34 is the interaction energy between the d-axis grid-side subsystem and the phase locked loop, V t35 is the interaction energy between the q-axis grid-side subsystem and the phase locked loop, V t345 is the interaction energy between the d-axis grid-side subsystem and the q-axis grid-side subsystem coupling together and the phase locked loop.

[0093] (4) Interaction energy term of the equivalent grid d-axis subsystem

[0094]

[0095] where V t41 is the interaction energy between the d-axis current inner loop subsystem and the grid-side d-axis subsystem, V t45 is the interaction energy between the d-axis grid-side subsystem and the q-axis grid-side subsystem.

[0096] (5) Interaction energy term of the equivalent grid q-axis subsystem

[0097]

[0098] where V t52 is the interaction energy between the q-axis current inner loop subsystem and the grid-side d-axis subsystem, V t54 is the interaction energy between the q-axis grid-side subsystem and the d-axis grid-side subsystem.

[0099] According to the interaction energy terms contained in each subsystem in equation (14) and equation (18), the energy transmission paths between each control loop of the direct-driven wind power system during the fault transient state can be depicted, as shown in FIG. 2. Figure 3 ​

[0100] From the above derivation, it can be seen that the energy term changed by low voltage ride through control is mainly V t1_LVRT and V t2_LVRT According to the control structure of direct-drive wind turbine, formula (1) is brought into formula (14) and formula (15), and the derivatives of the two interactive energy terms are analyzed respectively to obtain:

[0101]

[0102] When the system is disturbed to induce sub / super synchronous oscillation with a+jω c , the non-periodic component in formula (19) is extracted to obtain:

[0103]

[0104] In specific embodiments, the first non-periodic component change rate is obtained by the following formula:

[0105]

[0106] wherein, is the derivative of the first non-periodic component change rate, θ0 is the steady-state value of the phase difference between the PCC point voltage and the fault point voltage, K pd is a proportional gain coefficient, ω c is a synchronous angular frequency, e is a constant, α is the real part of the synchronous oscillation, t is time, I max is the maximum allowable current value of the grid-side converter in the fault stage, A ref is the oscillation amplitude of the current reference value change of the current inner loop, A Id1 is the oscillation amplitude of the d-axis component change of the wind turbine terminal current, θ ref is the oscillation phase angle of the current reference value change of the current inner loop, θ d is the oscillation phase angle of the d-axis component change of the wind turbine terminal current.

[0107] In specific embodiments, the second non-periodic component change rate is obtained by the following formula:

[0108]

[0109] wherein, is the derivative of the second non-periodic component change rate, K pd is a proportional gain coefficient, θ0 is the steady-state value of the phase difference between the PCC point voltage and the fault point voltage, e is a constant, α is the real part of the synchronous oscillation, t is time, A ref is the oscillation amplitude of the current reference value change of the current inner loop, A Iq1 is the oscillation amplitude of the q-axis component change of the wind turbine terminal current, θ refis the oscillation phase angle of the current reference value change of the current inner loop, θ q is the oscillation phase angle of the change in the q-axis component of the wind turbine terminal current.

[0110] Specifically, They are the change rates of the non-periodic components in the interaction energy between the low voltage ride-through control and the dq axis current inner loop sub-control system.

[0111] From formula (20), we can see that the interaction energy V between the low voltage ride-through control and the d-axis current inner loop subsystem is t1_LVRT The rate of change is always negative, that is, the interaction process has a positive dissipation effect on the system oscillation, which is conducive to the reduction of the accumulated energy of the fault disturbance. In addition, V t1_LVRT The rate of change is mainly affected by the d-axis current inner loop parameter K pd And the reactive compensation coefficient K in low voltage ride through control. Increase the current inner loop parameter K pd Or increasing the reactive power compensation coefficient K will help speed up V t1_LVRT dissipation speed, improving system stability

[0112] However, the interaction energy V between the low voltage ride-through control and the q-axis current inner loop subsystem t2_LVRT The rate of change is always negative, that is, the interaction energy will help increase the system dynamic energy accumulation, aggravate the system oscillation divergence, and is also the key link to cause the system oscillation divergence. According to formula (20), increasing the q-axis current inner loop parameter K pq and the reactive compensation coefficient K in low voltage ride-through control, which will aggravate V t2_LVRT The growth of is not conducive to the stability of system oscillation. t1_LVRT and V t2_LVRT The rate of change is known to be affected by The effect of smaller values, V t2_LVRT The rate of change plays a dominant role in the interaction between low-voltage ride-through control and other subsystems. In this case, if the sole objective is to optimize voltage support and control parameters such as the reactive power compensation coefficient are set within their maximum limits, system oscillation and instability may result.

[0113] In a specific embodiment, the parameter constraints include transient voltage support constraints, converter capacity constraints, and reactive current compensation coefficient constraints.

[0114] Specifically, during the fault ride-through process, the increase in the current inner loop control parameters and the reactive power compensation coefficient will intensify the interaction between the low voltage ride-through control and the q-axis current inner loop subsystem, and accelerate the accumulation of fault energy. If the parameter settings are unreasonable, it may induce system oscillation instability. Therefore, this application starts from the perspective of interactive energy path optimization, with the goal of reducing the negative dissipated energy generated by the interaction between the low voltage ride-through control and the q-axis current inner loop subsystem, and improving the overall interactive energy dissipation rate of the system, to construct an optimization adjustment strategy for the control parameters of wind turbines during fault ride-through. The objective function of the optimization control strategy is:

[0115]

[0116] in, f() is the expression for associating the control parameters with the interaction energy change rate obtained according to equations (14)-(18).

[0117] The parameter constraints contained in the objective function are as follows;

[0118] (1) Transient voltage support constraints

[0119] During a fault transient, reactive voltage support and effective low voltage ride-through capability remain the primary control objectives for direct-drive wind turbines. Therefore, transient voltage support requirements must be met first during parameter optimization:

[0120] I qref ≥1.5(0.9-u g )I N (twenty two)

[0121] Among them, u g is the per-unit value of the grid-connected point voltage, I N is the rated current.

[0122] (2) Converter capacity constraints

[0123] Considering the capacity constraint of the converter, the sum of the d-axis current reference value and the q-axis voltage reference value for low voltage ride-through control must meet the converter maximum current limit, that is:

[0124]

[0125] (3) Reactive current compensation coefficient constraints

[0126] The value of the reactive current compensation coefficient K in low voltage ride-through control is related to the limiting link of the inverter.

[58] , generally taken as 1.2 to 1.5. That is, the constraints of K are:

[0127] 1.2<K<1.5 (24)

[0128] In a specific embodiment, the damping control of the direct-drive wind power grid-connected system with the objective function and the parameter constraints as the target includes: constructing a parameter optimization model of the direct-drive wind power grid-connected system in the fault transient stage according to the objective function and the parameter constraints; determining the control parameters of the direct-drive wind power grid-connected system parameter optimization model by using a pattern search method and the direct-drive wind power grid-connected system parameter optimization model; and performing damping control on the direct-drive wind power grid-connected system by using the control parameters.

[0129] Specifically, the first step is to measure the voltage of the direct-drive wind power port online. When a voltage drop occurs, measure the voltage drop value and collect the inner loop proportional control coefficient K of the wind power grid-connected system current at the initial moment of the fault. p , current outer loop integral control coefficient K i , Phase-locked loop proportional control coefficient K pp , low voltage ride through control reactive current compensation coefficient K, determine the initial value of the optimization coefficient And record it as the initial solution k1.

[0130] Step 2: Determine whether the initial value meets the constraints. If so, k1 is the current optimal solution. If not, redetermine k1 until a feasible solution is found.

[0131] Step 3: At the current optimal solution k i =(i=1,2,3,···), the control parameters are updated by applying pattern search, and a new feasible solution k is obtained by satisfying the constraints. i+1 . Calculate the objective function, if V i >V i+1 , then k i+1 is the current feasible solution, otherwise repeat step 3.

[0132] Step 4: Repeat the search process until the number of iterations is met, then terminate the search. The current optimal solution is the optimal low voltage ride-through control parameter.

[0133] In order to verify the correctness of the active damping control method and system of the direct-drive wind power grid-connected system that takes into account the low-voltage stability requirements provided by the above analysis of this application, this application provides a specific simulation. The structure diagram of the direct-drive wind turbine grid-connected system used in the simulation is as follows: Figure 2 As shown, the wind turbine has a rated capacity of 1 MW and is connected to the PCC point via a 0.69 / 20 kV on-site transformer and then a 20 / 230 kV transformer. The grid-side converter parameters for the direct-drive wind turbine are shown in Table 1.

[0134]

[0135] Table 1 Grid-side converter parameters

[0136] In order to verify the impact of interaction energy on system stability, two simulation scenarios of oscillation divergence and convergence during fault ride-through were set up, and the changes in the total interaction energy of the system were calculated respectively to verify the accuracy of the proposed method of using interaction energy to judge system stability.

[0137] Assume that a three-phase short circuit fault occurs at the wind turbine end at 2.5s, the voltage drops to 0.8pu, and the low voltage ride-through control is activated, causing the system to oscillate and diverge. At this time, the oscillation divergence curve is as follows: Figure 4 As shown. After the fault occurs, the oscillation component information of the machine end is collected, and the trend of the total interaction energy of the system along the oscillation trajectory is calculated according to formulas (14)-(18), as shown in the following figure: Figure 5a and Figure 5b shown.

[0138] Figure 5(a) depicts the evolution of the system's total interaction energy along the oscillation trajectory. As can be seen, during the oscillation divergence process, the system's total interaction energy gradually increases with the oscillating component, exhibiting an outward divergent and spiraling growth trend. This indicates that after the disturbance, the accumulated total energy of the system continues to grow, and the system gradually becomes unstable, consistent with the time-domain simulation.

[0139] Figure 5(b) shows the changes in the total interaction energy between the LVRT control and the dq-axis subsystem. As can be seen, the interaction energy between the LVRT control and the subsystem is positive, which increases system energy accumulation and hinders rapid oscillation convergence.

[0140] Assume that a three-phase short circuit fault occurs at the wind turbine end at 2.5s, the voltage drops to 0.85pu, and the low voltage ride-through control is activated, causing the system oscillation to converge. At this time, the oscillation convergence condition is as follows: Figure 6 As shown. After the fault occurs, the oscillation component information of the machine end is collected, and the trend of the total interaction energy of the system along the oscillation trajectory is calculated according to formulas (14)-(18), as shown in the following figure: Figure 7a and Figure 7b shown.

[0141] The variation of the total interaction energy of the system along the oscillation trajectory is shown in Figure 7(a). As the oscillation converges, the total interaction energy of the system shows a spiral downward trend. The dynamic energy generated by the disturbance is gradually dissipated, and the system tends to be stable.

[0142] Furthermore, the interaction energy between the LVRT control and other subsystems is calculated, as shown in Figure 7(b). At this point, the interaction energy generated by the LVRT remains positive and spirals upward, exhibiting a negative dissipative effect on the system. However, because the dissipative effect of the interaction with other subsystems in the system is greater than the interaction energy generated by the LVRT control link, the system exhibits an oscillatory convergence trajectory. Consequently, the overall interaction energy exhibits a spiral contraction characteristic.

[0143] Taking the oscillation divergence scenario as an example, a voltage drop disturbance at the grid connection point occurs at t = 2.5s, and the grid connection point voltage drops to 80% of the normal voltage value. The low voltage ride-through control parameters before optimization are: K pd =1.05, K=1.5. After calculation, the optimized parameters are: K pd =2.11, K = 1.2. The voltage waveforms of PCC points d and q of the wind power grid-connected system before and after control parameter optimization are as follows: Figure 8 shown.

[0144] The curve before adjusting the parameters is as follows Figure 8 The broken line in the figure shows the voltage drop. 2.5 seconds after the fault occurred, the system PCC voltage dropped significantly, triggering a 63Hz broadband oscillation on the system's d-axis. Without proper parameter adjustment, the system would exhibit a divergent oscillation trend and gradually become unstable. After parameter optimization, the oscillation curve, shown in red, rapidly converges and gradually stabilizes. Although the voltage recovery in the initial oscillation phase is less than that of the original parameter solution, it still meets the system voltage support requirements, achieving oscillation suppression while ensuring voltage stability.

[0145] The dynamic energy changes of the system during low voltage ride-through were further compared before and after parameter adjustment. Figure 9 Calculated from the moment the fault occurred, the figure shows that before parameter adjustment, the total dynamic energy generated by the interaction between the submodules of the direct-drive wind power grid-connected system showed an increasing trend and gradually diverged. After parameter optimization, the interaction between the submodules showed a decreasing trend, which helped to quickly dissipate the accumulated energy of the fault and quickly achieve a stable system state.

[0146] Low voltage ride-through control has been incorporated into the basic functions of wind turbines to ensure stable operation of wind turbines during faults and provide certain reactive power support for the power grid. This application has the following features:

[0147] 1) The interactive energy model of the direct-drive wind power grid-connected system constructed in this application can quantitatively characterize the contribution of the interaction between various control links to the system stability.

[0148] 2) The optimized control scheme during fault ride-through constructed in this application achieves system oscillation suppression while taking into account voltage support requirements from the perspective of optimizing the interactive energy dissipation rate, and can effectively improve the oscillation stability of direct-drive wind turbines during fault ride-through.

[0149] In the specific embodiment, see Figure 10Fig. 2 is a structural schematic diagram of a damping control system of a wind power grid-connected system according to a second embodiment of the present application. The system comprises a state space model construction module 201, a dynamic energy acquisition module 202, an interactive energy acquisition module 203, a non-periodic component change rate acquisition module 204, an optimization module 205, and a control module 206. The state space model construction module 201 is configured to construct state space models of multiple subsystems of a direct-drive wind power grid-connected system by analyzing a control strategy of the direct-drive wind power grid-connected system in a fault transient stage. The subsystems include a low-voltage ride-through d-axis subsystem, a low-voltage ride-through q-axis subsystem, a phase-locked loop subsystem, a grid d-axis subsystem, and a grid q-axis subsystem. The dynamic energy acquisition module 202 is configured to obtain dynamic energy of each state space model based on the state space model of each subsystem and an energy function construction method. The dynamic energy includes storage energy and an interactive energy expression between the subsystems. The interactive energy acquisition module 203 is configured to obtain an interactive energy item of each subsystem based on the storage energy and the interactive energy expression. The non-periodic component change rate acquisition module 204 is configured to obtain a first non-periodic component change rate and a second non-periodic component change rate according to a direct-drive wind turbine control structure and the interactive energy item. The first non-periodic component change rate is a non-periodic component change rate in interactive energy between low-voltage ride-through control and a d-axis current inner loop sub-control system, and the second non-periodic component change rate is a non-periodic component change rate in interactive energy between low-voltage ride-through control and a q-axis current inner loop sub-control system. The optimization module 205 is configured to construct a target function of the direct-drive wind power grid-connected system during fault ride-through and a parameter constraint condition of the target function based on the first non-periodic component change rate and the second non-periodic component change rate. The control module 206 is configured to perform damping control on the direct-drive wind power grid-connected system with the target function and the parameter constraint condition as targets.

[0150] In specific embodiments, the third embodiment of the present application provides a damping control device of a wind power grid-connected system, comprising a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor executes the steps of the method according to any one of the first embodiment of the present application.

[0151] In specific embodiments, the fourth embodiment of the present application provides a computer readable storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the method according to any one of the first embodiment of the present application.

[0152] The above embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

[0153] The above description is merely a preferred embodiment of the present invention and does not constitute any other form of limitation to the present invention. Any person skilled in the art may utilize the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes for application in other fields. However, any simple modification, equivalent change, and modification of the above embodiments made in accordance with the technical essence of the present invention without departing from the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A damping control method for a wind power grid-connected system, characterized in that: The method comprises: By analyzing the control strategy of the direct-drive wind power grid-connected system in the transient phase of the fault, a state space model of multiple subsystems of the direct-drive wind power grid-connected system is constructed; the subsystems include the low voltage ride-through d-axis subsystem, the low voltage ride-through q-axis subsystem, the phase-locked loop subsystem, the grid d-axis subsystem, and the grid q-axis subsystem; The dynamic energy of each state space model is obtained based on the state space model of each subsystem and the energy function construction method; the dynamic energy includes the stored energy and the interaction energy expression between each subsystem; Obtaining interaction energy terms of each subsystem based on the stored energy and the interaction energy expression; According to the direct-drive wind turbine control structure and the interactive energy term, a first non-periodic component change rate and a second non-periodic component change rate are obtained; the first non-periodic component change rate is the non-periodic component change rate in the interactive energy between the low voltage ride-through control and the d-axis current inner-loop control system, and the second non-periodic component change rate is the non-periodic component change rate in the interactive energy between the low voltage ride-through control and the q-axis current inner-loop control system; Establishing an objective function of the direct-drive wind power grid-connected system during the fault ride-through period and parameter constraints of the objective function based on the first non-periodic component change rate and the second non-periodic component change rate; Performing damping control on the direct-drive wind power grid-connected system based on the objective function and the parameter constraint conditions; The first non-periodic component change rate and the second non-periodic component change rate are obtained using the following formula: in, is the derivative of the rate of change of the first non-periodic component, θ0 is the steady-state value of the phase difference between the PCC point voltage and the fault point voltage, K pd is the proportional gain coefficient, ω c is the synchronous angular frequency, e is a constant, α is the real part of the synchronous oscillation, t is the time, I max is the maximum allowable current value of the grid-side converter during the fault phase, A ref A is the oscillation amplitude of the current reference value change of the current inner loop, Id1 is the oscillation amplitude of the d-axis component of the wind turbine terminal current, θ ref is the oscillation phase angle of the current reference value change of the current inner loop, θ d is the oscillation phase angle of the d-axis component of the wind turbine terminal current, is the derivative of the rate of change of the second non-periodic component, K pq is the proportional gain coefficient, is the oscillation amplitude of the q-axis component of the wind turbine terminal current, θ q is the oscillation phase angle of the change in the q-axis component of the wind turbine terminal current; The objective function aims to reduce the negative dissipated energy generated by the interaction between the low voltage ride-through control and the q-axis current inner loop subsystem and improve the overall interactive energy dissipation rate of the system. The wind turbine control parameter optimization adjustment strategy during the fault ride-through period is constructed. The objective function is obtained using the following formula: in, f() is the expression for the correlation between the control parameters and the interaction energy change rate obtained based on the interaction energy terms in the LVRT d-axis subsystem, the LVRT q-axis subsystem, the PLL subsystem, the equivalent grid d-axis subsystem, and the equivalent grid q-axis subsystem. is the interaction energy term of each subsystem, K pd and K pq is the proportional gain coefficient, and K is the reactive current compensation coefficient of low voltage ride through control.

2. The damping control method for a wind power grid-connected system according to claim 1, wherein: The method for constructing a state space model and an energy function based on each subsystem obtains the dynamic energy of each state space model, including: Cross-multiplying the state-space model by two equations and integrating the time to obtain a dynamic energy model of each state-space model; the dynamic energy model includes expressions for stored energy, dissipated energy, and interaction energy between subsystems; The dynamic energy is obtained in the dynamic energy model.

3. The damping control method for a wind power grid-connected system according to claim 1, wherein: The obtaining of the first non-periodic component change rate and the second non-periodic component change rate according to the direct-drive wind turbine control structure and the interactive energy term includes: Obtaining a non-periodic component according to the current inner loop control response equation of the direct-drive wind turbine control structure, the interactive energy term in the low voltage ride-through d-axis subsystem, and the interactive energy term in the low voltage ride-through q-axis subsystem; When the induced mode of the direct-drive wind power grid-connected system after being disturbed is synchronous oscillation, the non-periodic component is extracted to obtain the first non-periodic component change rate and the second non-periodic component change rate.

4. The damping control method for a wind power grid-connected system according to claim 1, wherein: The parameter constraints include transient voltage support constraints, converter capacity constraints and reactive current compensation coefficient constraints.

5. The damping control method for a wind power grid-connected system according to claim 1, wherein: The performing damping control on the direct-drive wind power grid-connected system based on the objective function and the parameter constraint condition includes: Constructing a parameter optimization model for a direct-drive wind power grid-connected system in a fault transient phase according to the objective function and the parameter constraints; Determining control parameters of the direct-drive wind power grid-connected system parameter optimization model using a pattern search method and the direct-drive wind power grid-connected system parameter optimization model; The control parameters are used to perform damping control on the direct-drive wind power grid-connected system.

6. A damping control system for a wind power grid-connected system, applied to the damping control method for a wind power grid-connected system according to claim 1, characterized in that: The system includes: a state space model construction module, a dynamic energy acquisition module, an interactive energy acquisition module, a non-periodic component change rate acquisition module, an optimization module and a control module; The state-space model building module is used to build a state-space model of multiple subsystems of the direct-drive wind power grid-connected system by analyzing the control strategy of the direct-drive wind power grid-connected system in the transient phase of the fault; the subsystems include the low voltage ride-through d-axis subsystem, the low voltage ride-through q-axis subsystem, the phase-locked loop subsystem, the grid d-axis subsystem and the grid q-axis subsystem; The dynamic energy acquisition module is used to obtain the dynamic energy of each state space model based on the state space model of each subsystem and the energy function construction method; the dynamic energy includes the stored energy and the interaction energy expression between each subsystem; The interaction energy acquisition module is used to obtain the interaction energy items of each subsystem based on the stored energy and the interaction energy expression; The non-periodic component change rate acquisition module is used to obtain a first non-periodic component change rate and a second non-periodic component change rate according to the direct-drive wind turbine control structure and the interactive energy term; the first non-periodic component change rate is the non-periodic component change rate in the interactive energy between the low voltage ride-through control and the d-axis current inner-loop control system, and the second non-periodic component change rate is the non-periodic component change rate in the interactive energy between the low voltage ride-through control and the q-axis current inner-loop control system; The optimization module is used to construct an objective function of the direct-drive wind power grid-connected system during the fault ride-through period and parameter constraints of the objective function based on the first non-periodic component change rate and the second non-periodic component change rate; The control module is used to perform damping control on the direct-drive wind power grid-connected system based on the objective function and the parameter constraint conditions.

7. A damping control device for a wind power grid-connected system, comprising a memory and a processor, characterized in that: The memory stores a computer program, and when the computer program is executed by the processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the processor is caused to perform the steps of the method according to any one of claims 1 to 5.

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