Damping control method of wind power integration system and related equipment

Abstract

The embodiment of the invention discloses a damping control method for a wind power grid-connected system and related equipment, and the method can achieve the quantitative characterization of the contribution degree of the interaction between control links to the stability of the system through obtaining the interaction energy of a direct-driven wind power grid-connected system. Meanwhile, according to the fault ride-through period optimization control scheme constructed based on the first aperiodic component change rate and the second aperiodic component change rate, system oscillation suppression considering the voltage support requirement is realized from the angle of interaction energy dissipation rate optimization; the oscillation stability of the direct-driven wind turbine generator in the fault ride-through process can be effectively improved.

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 the stable operation of wind turbines during faults and provide certain reactive power support for the power grid. However, after the low voltage ride-through control is put into operation, it may be coupled with the wind turbine control link, changing its damping characteristics during faults and causing oscillation stability problems. For the oscillation suppression problem in direct-drive wind power grid-connected systems, there are now three types of solution strategies based on the suppression principle, namely optimizing controller parameters, changing the control link topology, and adding damping. However, the above strategies all ignore the impact of the low voltage ride-through control process on system stability, and use damping as the single control target, making it difficult to achieve system 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: by analyzing the control strategy of the direct-drive wind power grid-connected system in the transient stage of the fault, constructing a state space model of multiple subsystems of the direct-drive wind power grid-connected system; 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; based on the state space model of each subsystem and the energy function construction method, the dynamic energy of each state space model is obtained; the dynamic energy includes the stored energy and the interaction energy expression between the subsystems; based on the stored energy and the interaction energy expression, the interaction energy of each subsystem is obtained 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 the target.

[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 according to the direct-drive wind turbine control structure and the interactive energy term includes: 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 crossing d-axis subsystem, and the interactive energy term in the low voltage crossing 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 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 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 It is the oscillation phase angle of the change of 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 refis 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 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 It is the oscillation phase angle of the change of 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 the subsystems; 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] Implementing the embodiments 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 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. 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 fault ride-through 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 drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying 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 state 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 It is the change of the total energy of the system along the oscillation divergence trajectory after the fault occurs in the simulation;

[0026] Figure 5b It is 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 7aIt is the change of total energy of the system along the oscillation convergence trajectory after the fault occurs in the simulation;

[0029] Figure 7b It is 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 in the oscillation divergence scenario in the simulation;

[0031] Fig. 9 Dynamic energy changes of the system during low voltage ride-through before and after parameter adjustment in simulation

[0032] Fig.10 It is a structural schematic 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 the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0035] The terms "first", "second", etc. in the specification, claims and drawings of this application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or modules is not limited to the listed steps or modules, but optionally includes steps or modules that are not listed, or optionally includes other steps or modules that are inherent to these processes, methods, products or devices.

[0036] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood 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 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: Obtaining the interaction energy term of each subsystem based on the stored energy and the interaction energy expression;

[0041] Step 104, obtaining 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 constraint conditions.

[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] In the formula, 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 They 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 、u sq are the voltages of the inverter ports d and q, respectively. pccd 、u pccq are the d-axis and q-axis voltages at the wind turbine grid connection point, respectively. ω0 is the synchronous angular frequency, ω0=100π.

[0047] When the voltage drops at the grid connection point of the direct-drive wind power grid-connected system, the voltage outer loop is generally disconnected and the low voltage ride-through control strategy is adopted to obtain the current control command i according to the voltage drop degree. dref 、i qref The grid-connected point voltage drops deeply, so the reference value of the low voltage ride-through control current is:

[0048]

[0049] Wherein, K represents the reactive current compensation coefficient, which is 1.5 in this embodiment; U pcc Indicates the grid voltage per unit value; I N Indicates rated current; I max Indicates the maximum allowable current value of the grid-side converter during the fault phase. Figure 3 In the reference direction, i qref is a negative value, and reactive current flows into the fan.

[0050] The direct-drive wind power grid-connected system uses a PLL phase-locked loop controller to track the voltage phase at 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 wind turbine grid-connected point in the infinite grid voltage directional vector dq coordinate system, K pp and K ip They are the proportional and integral parameters of the phase-locked loop PI controller respectively. pll is the phase-locked loop output voltage phase.

[0053] According to the dq-axis 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 q-axis subsystem, and there are mutually coupled state quantities between each subsystem.

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

[0055] (1) State space model of 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, 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 in the disturbance process. Subscript 0 represents the steady-state component, is the q-axis voltage reference value.

[0058] (2) State space model of low voltage ride-through q-axis subsystem

[0059]

[0060] Among them, K iq , K pq is the integral and proportional gain coefficient of the inner loop of the q-axis current, 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 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 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 side of formula (4) to formula (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 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 for stored energy, dissipated energy and interaction energy between subsystems; 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 The 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 crossing d-axis subsystem, and the interactive energy term in the low voltage crossing 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 energy stored in each subsystem and the energy expression of its interaction with other subsystems are used to obtain the interaction energy terms in each subsystem, and the voltage support and damping stability coupling effect is analyzed. Specifically, by substituting equations (4)-(8) into equation (9), the energy stored in each subsystem and the energy expression of its interaction with other subsystems can be obtained analytically, and the interaction energy terms in each subsystem are as follows.

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

[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 system. V 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 generated by 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 It is the interaction energy between the grid-side q-axis subsystem and the q-axis current inner loop subsystem.

[0089] By comparing equation (14) and equation (15), it can be seen that after the introduction of low voltage ride-through control, the dq axis interaction energy term presents an asymmetric characteristic.

[0090] (3) Phase-locked loop subsystem interaction energy term

[0091]

[0092] Where V t34 is the interaction energy between the d-axis grid-side subsystem and the phase-locked loop. t35 is the interaction energy between the q-axis grid-side subsystem and the phase-locked loop. t345 It is the interactive energy generated by the coupling between the d-axis grid-side subsystem, the q-axis grid-side subsystem and the phase-locked loop.

[0093] (4) Equivalent grid d-axis subsystem interaction energy term

[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 It is the interaction energy between the d-axis grid-side subsystem and the q-axis grid-side subsystem.

[0096] (5) Equivalent grid q-axis subsystem interaction energy term

[0097]

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

[0099] According to the interactive energy terms contained in each subsystem in equations (14) and (18), the energy transfer path between the control links of the direct-drive wind power grid-connected system during the fault transient period can be described, as follows: Figure 3 shown.

[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 the direct-drive wind turbine, equation (1) is substituted into equations (14) and (15), and the derivatives of the two interactive energy terms are analyzed to obtain:

[0101]

[0102] When the system is disturbed, the induced mode is α+jω c When the sub- / supersynchronous oscillation occurs, the non-periodic component in equation (19) can be extracted to obtain:

[0103]

[0104] In a specific embodiment, the first non-periodic component change rate is obtained using the following formula:

[0105]

[0106] 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 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 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 It is the oscillation phase angle of the change of the d-axis component of the wind turbine terminal current.

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

[0108]

[0109] 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 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 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 It is the oscillation phase angle of the change of the q-axis component of the wind turbine terminal current.

[0110] Specifically, They are respectively 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 know 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 power 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 The dissipation speed improves the system stability

[0112] However, the interaction energy between the low voltage ride-through control and the q-axis current inner loop subsystem V t2_LVRT The rate of change is always negative, that is, the interaction energy will help increase the dynamic energy accumulation of the system, 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 power 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 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. At this time, if the voltage support optimization is the only goal and the control parameters such as reactive power compensation coefficient are set with the maximum boundary, it may induce system oscillation and instability.

[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 parameters are set unreasonably, it may induce system oscillation and 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 parameter 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 the fault transient process, reactive voltage support and effective low voltage ride-through capability are still the main control targets of direct-drive wind turbines. Therefore, the 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 grid voltage per unit value, 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 of the 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] , usually 1.2 to 1.5. That is, the constraint condition of K is:

[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 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.

[0129] Specifically, the first step is to measure the voltage at the direct-drive wind power port online. When a voltage drop occurs, measure the voltage drop value and collect the current inner loop proportional control coefficient K of the wind power grid-connected system 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: In 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, terminate the search, and 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 in Figure 1, the rated capacity of the wind turbine is 1MW, which is connected to the PCC point through a 0.69 / 20kV on-site transformer and then a 20 / 230kV transformer. The parameters of the grid-side converter of 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 using interaction energy to judge system stability in this simulation.

[0137] Assume that a three-phase short circuit 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 The oscillation component information of the machine end after the fault occurs is collected, and the change trend of the total interaction energy of the system along the oscillation operation trajectory is calculated according to equations (14)-(18), as shown in Figure 5a and Figure 5b shown.

[0138] Figure 5(a) depicts the change of the total interaction energy of the system along the oscillation trajectory. As can be seen from the figure, during the oscillation divergence process, the total interaction energy of the system gradually increases with the oscillation component, showing an outward divergence and spiral growth trend, indicating that the total accumulated energy of the system continues to grow after the disturbance, and the system gradually becomes unstable, which is consistent with the time domain simulation.

[0139] Figure 5(b) reflects the change of the total interaction energy between the low voltage ride-through control and the dq axis subsystem. As can be seen from the figure, the interaction energy between the low voltage ride-through control and the subsystem is positive, which helps to increase the energy accumulation of the system and is not conducive to the rapid convergence of the oscillation.

[0140] Assume that a three-phase short circuit 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 The oscillation component information of the machine end after the fault occurs is collected, and the change trend of the total interaction energy of the system along the oscillation operation trajectory is calculated according to equations (14)-(18), as shown in 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 low voltage ride-through control and other subsystems is calculated as shown in Figure 7(b). At this time, the interaction energy generated by the low voltage ride-through is still positive and spirally rises, showing a negative dissipation effect on the system. However, since the dissipation effect generated by the interaction of other subsystems in the system is greater than the interaction energy generated by the low voltage ride-through control link, the system presents an oscillating convergence trajectory. Therefore, the interaction energy generally presents a spiral contraction feature.

[0143] Then, 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 the PCC points d and q of the wind power grid-connected system before and after the control parameter optimization are as follows Figure 8 shown.

[0144] The curve before adjusting the parameters is as follows Figure 8 As shown by the broken line in . 2.5s after the fault occurred, the voltage at the PCC point of the system dropped sharply, and triggered a 63Hz broadband oscillation on the d-axis of the system. If reasonable parameter adjustment is not performed, the system will show a divergent oscillation trend and gradually become unstable. After parameter optimization, the oscillation curve is shown as the red line. The system oscillation converges quickly and gradually stabilizes. Although the voltage recovery degree at the initial stage of oscillation is less than that of the original parameter scheme, it still meets the system voltage support requirements and achieves oscillation suppression on the basis of ensuring voltage stability.

[0145] The dynamic energy changes of the system during low voltage ride-through were further compared before and after parameter adjustment. Fig. 9 As shown in the figure. Calculated from the moment of fault occurrence, it can be seen from the figure 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 downward trend, which was conducive to the rapid dissipation of the accumulated energy of the fault and enabled the system to quickly reach a stable 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 embodiments, see Fig.10, is a structural schematic diagram of a damping control system of a wind power grid-connected system in the second example of the present application, the system comprising: 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 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 202 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 the subsystems; the interactive energy The acquisition module 203 is used to obtain the interactive energy terms of each subsystem based on the stored energy and the interactive energy expression; the non-periodic component change rate acquisition module 204 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 205 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 206 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.

[0150] In a specific embodiment, the third embodiment of the present application provides a damping control device for 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 as described in any one of the first embodiments of the present application.

[0151] In a specific embodiment, 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 as described in any one of the first embodiments of the present application.

[0152] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

[0153] The above description is only a preferred embodiment of the present invention and does not limit the present invention in other forms. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the protection scope 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 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; Based on the state space model of each subsystem and the energy function construction method, the dynamic energy of each state space model is obtained; 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 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; Constructing an objective function of the direct-drive wind power grid-connected system during fault ride-through 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 direct-drive wind power grid-connected system is damped controlled with the objective function and the parameter constraint conditions as targets.

2. The damping control method of the wind power grid-connected system according to claim 1, characterized in that: The state space model and energy function construction method based on each subsystem obtains the dynamic energy of each state space model, including: The state space model is cross-multiplied by two equations and time is integrated to obtain a dynamic energy model of each state space model; the dynamic energy model includes expressions of stored energy, dissipated energy and interaction energy between subsystems; The dynamic energy is obtained in the dynamic energy model.

3. The damping control method of the wind power grid-connected system according to claim 1, characterized in that: 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 comprises: 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 of the wind power grid-connected system according to claim 3, characterized in that: The first non-periodic component change rate is obtained by 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 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 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 It is the oscillation phase angle of the change of the d-axis component of the wind turbine terminal current.

5. The damping control method of the wind power grid-connected system according to claim 3, characterized in that: The change rate of the second non-periodic component is obtained by the following formula: 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 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 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 It is the oscillation phase angle of the change of the q-axis component of the wind turbine terminal current.

6. The damping control method of the wind power grid-connected system according to claim 1, characterized in that: The parameter constraints include transient voltage support constraints, converter capacity constraints and reactive current compensation coefficient constraints.

7. The damping control method of the wind power grid-connected system according to claim 1, characterized in that: The damping control of the direct-drive wind power grid-connected system based on the objective function and the parameter constraint condition comprises: Constructing a parameter optimization model of a direct-drive wind power grid-connected system in a fault transient phase according to the objective function and the parameter constraint conditions; Determine 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; The control parameters are used to perform damping control on the direct-drive wind power grid-connected system.

8. A damping control system for a wind power grid-connected system, characterized in that: The system comprises: a state space model building 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 fault phase; 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 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 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 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 with the objective function and the parameter constraint conditions as targets.

9. 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 7.

10. 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 7.

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