New energy equipment control parameter optimization method and system

Abstract

The invention belongs to the technical field of power systems, and discloses a new energy equipment control parameter optimization method and system. The new energy equipment control parameter optimization method comprises the following steps: establishing a full-system quasi-steady-state model based on time scale separation; based on the whole system quasi-steady-state model and the power flow information, performing preset fault quasi-steady-state calculation to obtain a new energy unit state and a direct current system state; and based on the whole-system quasi-steady-state model, the state of the new energy unit and the state of the direct-current system, carrying out gradient calculation on a transient overvoltage value at a preset fault clearing moment relative to a new energy control parameter, and obtaining a new energy equipment control parameter which is most beneficial to voltage stability by utilizing a gradient descent method. According to the method, the new energy equipment control parameters in the power system are optimized based on the gradient of the transient overvoltage value at the preset fault removal moment relative to the new energy control parameters, and the purpose of improving the voltage stability of the power system can be achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power systems, and in particular relates to a method and system for optimizing control parameters of new energy equipment. Background Art

[0002] New energy systems have become the core component of new power systems. Building new energy cluster bases and making full use of the northwest wind resources, northeast wind resources and offshore wind resources around the eastern coastline are important strategies for achieving the "dual carbon" strategic goals.

[0003] In terms of geographical space, large-scale centralized wind power stations and photovoltaic power stations on land are distributed inversely to the load center; therefore, it is necessary to use ultra-high voltage direct current or alternating current transmission technology to achieve large-scale, long-distance and efficient transmission of new energy. In addition, with the rapid development of offshore wind power in coastal areas, especially the rapid development of deep-sea wind power, flexible direct current transmission has become the preferred technical route for large-capacity deep-sea wind power to access the power grid.

[0004] At present, large-scale centralized renewable energy power stations are connected to the power system through power electronic devices such as inverters and converters, which has greatly changed the grid structure and dynamic characteristics of the power grid and increased the risk of transient overvoltage in the renewable energy access system. To give a specific example, when renewable energy is connected to the system through a DC converter station, system failures such as DC commutation failure and DC interlocking may occur, and the renewable energy access to the large power grid system will lose reactive balance. Large-scale oscillations in reactive power and systemic failures will directly lead to severe voltage fluctuations on the DC converter side and the nearby large power grid side, causing transient overvoltage in the system. A large number of power electronic devices in the DC system are vulnerable to transient overvoltage attacks, resulting in breakdown, which in turn leads to system paralysis. When the system transient overvoltage exceeds the fault voltage crossing range of the new energy system, a chain of grid disconnection failures will occur directly on the new energy cluster side.

[0005] In summary, new energy parameters, especially fault ride-through control parameters, often play a decisive role in the fault ride-through characteristics of new energy. The fault ride-through characteristics of new energy have an important impact on the voltage stability of the system during transient processes. Therefore, it is urgent to carry out research on control parameter optimization design oriented towards improving voltage stability. Summary of the invention

[0006] The purpose of the present invention is to provide a method and system for optimizing the control parameters of new energy equipment to solve one or more of the above-mentioned technical problems. The technical solution disclosed in the present invention is specifically a new energy equipment control parameter optimization solution for improving the voltage stability of the power system, which optimizes the control parameters of the new energy equipment in the power system based on the gradient of the transient overvoltage value at the preset fault removal time with respect to the new energy control parameter, and ultimately can achieve the purpose of improving the voltage stability of the power system.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a method for optimizing control parameters of new energy equipment, comprising the following steps:

[0009] Based on the new energy power system with the control parameters of the new energy equipment to be optimized, a quasi-steady-state model of the whole system based on time scale separation is established for the fault ride-through characteristics of new energy and the transient overvoltage problem caused by DC commutation failure.

[0010] Based on the quasi-steady-state model of the whole system, the power flow information of the new energy power system is calculated; based on the quasi-steady-state model of the whole system and the power flow information, a quasi-steady-state calculation of a preset fault is performed to obtain the state of the new energy unit and the state of the DC system;

[0011] Based on the quasi-steady-state model of the whole system, the state of the new energy unit and the state of the DC system, the gradient calculation of the transient overvoltage value at the preset fault removal moment with respect to the new energy control parameter is performed, and the gradient descent method is used to obtain the new energy equipment control parameter that is most conducive to voltage stability.

[0012] A further improvement of the present invention is that

[0013] The expression of the quasi-steady-state model of the whole system based on time scale separation is:

[0014] Y[V]e jθ =[e jθ ](I d (V,p)-jI q (V,p))+I g (δ,x);

[0015] In the formula, j is an imaginary unit, Y represents the power system node admittance matrix; [V], e jθ Respectively represent the voltage amplitude and phase angle of all nodes in the power system; I d (V,p)-jI q (V,p) represents the current injected into the grid by the new energy unit and the DC system, V represents the grid connection point voltage, and p represents the current control state; I g (δ,x) represents the current injected into the grid by the synchronous generator, δ represents the synchronous generator power angle, and x represents the state variable transient electromotive force; [e jθ The i-th element in ] is expressed by Euler's formula expansion as θ i represents the phase angle of the voltage at the i-th node.

[0016] A further improvement of the present invention is that

[0017] The quasi-steady-state model of the whole system includes the quasi-steady-state models of synchronous generators, loads, new energy units and DC systems; wherein,

[0018] The quasi-steady-state model of the synchronous generator is expressed as:

[0019] In the formula, I d ,I q They represent the direct-axis and quadrature-axis components of the current injected into the node by the synchronous generator in the rotating coordinate system; E q ′、E d ′ represents the transient electromotive force of the quadrature axis and direct axis of the synchronous generator respectively; V x 、V y They represent the nodes where the synchronous generator is located at rest.

[0020] ''

[0021] Real and imaginary parts of node voltage in the coordinate system; x d 、x q They represent the quadrature-axis and direct-axis transient reactances of synchronous generators respectively;

[0022] The quasi-steady-state model of the load is expressed as:

[0023] In the formula, I d,load represents the d-axis current injected by the load into the power system; d1, d2, and d3 represent the coefficients of the constant impedance, constant current, and constant power terms corresponding to the active power in the ZIP model, respectively. Z represents the constant impedance model, I represents the constant current model, and P represents the constant power model; V load represents the voltage amplitude of the node where the load is located; q1, q2, and q3 represent the coefficients of the constant impedance, constant current, and constant power terms corresponding to reactive power in the ZIP model, respectively; I q,load To represent the q-axis current injected into the power system by the load;

[0024] Under normal conditions, the quasi-steady-state model of the new energy unit is expressed as:

[0025]

[0026] In the formula, I d1 +jI q1 The current injected into the grid by the new energy unit under normal conditions; P ref , Q ref Respectively represent the active and reactive control command values ​​output by the control strategy; V PCC Indicates the grid connection point voltage;

[0027] When a fault occurs, the quasi-steady-state model of the new energy unit is expressed as:

[0028]

[0029] In the formula, I d2 +jI q2 Indicates the current injected into the grid by the new energy unit in the low-voltage state; K 1_Ip_LV Indicates active current calculation coefficient 1; K 2_Ip_LV Indicates active current calculation coefficient 2; I pset_LV Indicates the active current setting value; I p0 Represents the initial active current; V t Indicates the terminal voltage amplitude; K 1_Iq_LV Indicates reactive current calculation coefficient 1; K 2_Iq_LV Indicates reactive current calculation coefficient 2; I qset_LV Indicates the reactive current setting value; I q0 Represents the initial reactive current; V Lin Indicates entering the low voltage ride-through threshold;

[0030] After adopting the low voltage fault ride-through strategy, the quasi-steady-state model of the new energy unit is expressed as:

[0031]

[0032] In the formula, I d3 +jI q3 It indicates the current injected into the grid by new energy after the low voltage fault ride-through strategy is adopted; K Ip_LVREC0 Indicates active current calculation coefficient 1; I pset_LVREC0 It shows the active current setting value; I p0 Indicates the initial active current;

[0033] During a fault, the quasi-steady-state model of the DC system is expressed as:

[0034]

[0035] In the formula,

[0036] After the fault, the quasi-steady-state model of the DC system is expressed as:

[0037]

[0038] In the formula,

[0039] in, and Combine them to find the analytical solution for the current;

[0040] Where U cr , U ci is the AC bus voltage on both sides of the DC system, I dThe DC system injects current into the grid, X cr , X ci is the leakage reactance of the converter transformer converted to the valve side, R d is the DC line resistance, T r 、T i is the transformer ratio on both sides, α is the trigger lag angle on the rectifier side, α min is the minimum critical trigger angle on the rectifier side, β is the trigger advance angle on the inverter side, γ is the arc extinction angle on the inverter side, P drref , P diref are the active power reference values ​​of the rectifier side and the inverter side respectively, γ iref is the reference value of the arc extinction angle on the inverter side, I δ is the DC current control margin on the inverter side, U dh , U dl are the thresholds for entering and exiting the low-voltage current limiting link, I vdmin It is the minimum current value of the low voltage current limiting link.

[0041] A further improvement of the present invention is that

[0042] In the step of calculating the gradient of the transient overvoltage value at the preset fault removal time with respect to the new energy control parameter,

[0043] The gradient calculation expression is:

[0044]

[0045] In the formula, V(τ c ) represents the preset fault removal τ c Transient overvoltage value at every moment; All are characteristics of components in the power system;

[0046] In the step of using the gradient descent method to obtain the control parameters of the new energy equipment that are most conducive to voltage stability, the update expression is:

[0047] Where η represents the selected step size; Indicates the updated value of the new energy control parameter during iteration;

[0048] Among them, the maximum number of iterations is reached or When , the optimization ends and the control parameters of the new energy equipment that are most conducive to voltage stability are obtained.

[0049] A further improvement of the present invention is that

[0050] The preset fault is an AC fault or a DC fault;

[0051] The AC fault is a three-phase permanent grounding fault or a generator and load shedding fault; and the DC fault is a DC commutation failure fault.

[0052] A second aspect of the present invention provides a new energy equipment control parameter optimization system, comprising:

[0053] The model building module is used to establish a quasi-steady-state model of the whole system based on time scale separation for the fault ride-through characteristics of new energy equipment and transient overvoltage problems caused by DC commutation failure.

[0054] A quasi-steady-state calculation module is used to calculate and obtain the power flow information of the new energy power system based on the quasi-steady-state model of the whole system; based on the quasi-steady-state model of the whole system and the power flow information, a quasi-steady-state calculation of a preset fault is performed to obtain the state of the new energy unit and the state of the DC system;

[0055] The parameter updating and optimization module is used to calculate the gradient of the transient overvoltage value with respect to the new energy control parameter at the preset fault removal moment based on the quasi-steady-state model of the whole system, the state of the new energy unit and the state of the DC system, and to obtain the new energy equipment control parameter that is most conducive to voltage stability by using the gradient descent method.

[0056] A further improvement of the present invention is that

[0057] The expression of the quasi-steady-state model of the whole system based on time scale separation is:

[0058] Y[V]e jθ =[e jθ ](I d (V,p)-jI q (V,p))+I g (δ,x);

[0059] In the formula, j is an imaginary unit, Y represents the power system node admittance matrix; [V], e jθ Respectively represent the voltage amplitude and phase angle of all nodes in the power system; I d (V,p)-jI q (V,p) represents the current injected into the grid by the new energy unit and the DC system, V represents the grid connection point voltage, and p represents the current control state; I g (δ,x) represents the current injected into the grid by the synchronous generator, δ represents the synchronous generator power angle, and x represents the state variable transient electromotive force; [e jθ The i-th element in ] is expressed by Euler's formula expansion as θ i represents the phase angle of the voltage at the i-th node.

[0060] A further improvement of the present invention is that

[0061] The quasi-steady-state model of the whole system includes the quasi-steady-state models of synchronous generators, loads, new energy units and DC systems; wherein,

[0062] The quasi-steady-state model of the synchronous generator is expressed as:

[0063] In the formula, I d ,I q They represent the direct-axis and quadrature-axis components of the current injected into the node by the synchronous generator in the rotating coordinate system; E q ′、E d ′ represents the transient electromotive force of the quadrature axis and direct axis of the synchronous generator respectively; V x 、V y They represent the nodes where the synchronous generator is located at rest.

[0064] ''

[0065] Real and imaginary parts of node voltage in the coordinate system; x d 、x q They represent the quadrature-axis and direct-axis transient reactances of synchronous generators respectively;

[0066] The quasi-steady-state model of the load is expressed as:

[0067] In the formula, I d,load represents the d-axis current injected by the load into the power system; d1, d2, and d3 represent the coefficients of the constant impedance, constant current, and constant power terms corresponding to the active power in the ZIP model, respectively. Z represents the constant impedance model, I represents the constant current model, and P represents the constant power model; V load represents the voltage amplitude of the node where the load is located; q1, q2, and q3 represent the coefficients of the constant impedance, constant current, and constant power terms corresponding to reactive power in the ZIP model, respectively; I q,load To represent the q-axis current injected into the power system by the load;

[0068] Under normal conditions, the quasi-steady-state model of the new energy unit is expressed as:

[0069]

[0070] In the formula, I d1 +jI q1 The current injected into the grid by the new energy unit under normal conditions; P ref , Q ref Respectively represent the active and reactive control command values ​​output by the control strategy; V PCC Indicates the grid connection point voltage;

[0071] When a fault occurs, the quasi-steady-state model of the new energy unit is expressed as:

[0072]

[0073] In the formula, I d2 +jI q2 Indicates the current injected into the grid by the new energy unit in the low-voltage state; K 1_Ip_LV Indicates active current calculation coefficient 1; K 2_Ip_LV Indicates active current calculation coefficient 2; I pset_LV Indicates the active current setting value; I p0 Represents the initial active current; V t Indicates the terminal voltage amplitude; K 1_Iq_LV Indicates reactive current calculation coefficient 1; K 2_Iq_LV Indicates reactive current calculation coefficient 2; I qset_LV Indicates the reactive current setting value; I q0 Represents the initial reactive current; V Lin Indicates entering the low voltage ride-through threshold;

[0074] After adopting the low voltage fault ride-through strategy, the quasi-steady-state model of the new energy unit is expressed as:

[0075]

[0076] In the formula, I d3 +jI q3 It indicates the current injected into the grid by new energy after the low voltage fault ride-through strategy is adopted; K Ip_LVREC0 Indicates active current calculation coefficient 1; I pset_LVREC0 It shows the active current setting value; I p0 Indicates the initial active current;

[0077] During a fault, the quasi-steady-state model of the DC system is expressed as:

[0078]

[0079] In the formula,

[0080] After the fault, the quasi-steady-state model of the DC system is expressed as:

[0081]

[0082] In the formula,

[0083] in, and Combine them to find the analytical solution for the current;

[0084] Where U cr , U ciis the AC bus voltage on both sides of the DC system, I d The DC system injects current into the grid, X cr , X ci is the leakage reactance of the converter transformer converted to the valve side, R d is the DC line resistance, T r 、T i is the transformer ratio on both sides, α is the trigger lag angle on the rectifier side, α min is the minimum critical trigger angle on the rectifier side, β is the trigger advance angle on the inverter side, γ is the arc extinction angle on the inverter side, P drref , P diref are the active power reference values ​​of the rectifier side and the inverter side respectively, γ iref is the reference value of the arc extinction angle on the inverter side, I δ is the DC current control margin on the inverter side, U dh , U dl are the thresholds for entering and exiting the low-voltage current limiting link, I vdmin It is the minimum current value of the low voltage current limiting link.

[0085] A further improvement of the present invention is that

[0086] In the step of calculating the gradient of the transient overvoltage value at the preset fault removal time with respect to the new energy control parameter,

[0087] The gradient calculation expression is:

[0088]

[0089] In the formula, V(τ c ) represents the preset fault removal τ c Transient overvoltage value at every moment; All are characteristics of components in the power system;

[0090] In the step of using the gradient descent method to obtain the control parameters of the new energy equipment that are most conducive to voltage stability, the update expression is:

[0091] Where η represents the selected step size; Indicates the updated value of the new energy control parameter during iteration;

[0092] Among them, the maximum number of iterations is reached or When , the optimization ends and the control parameters of the new energy equipment that are most conducive to voltage stability are obtained.

[0093] A further improvement of the present invention is that

[0094] The preset fault is an AC fault or a DC fault;

[0095] The AC fault is a three-phase permanent grounding fault or a generator and load shedding fault; and the DC fault is a DC commutation failure fault.

[0096] Compared with the prior art, the present invention has the following beneficial effects:

[0097] In the new energy equipment control parameter optimization method disclosed in the present invention, the gradient of the transient overvoltage value with respect to the new energy control parameter at the preset fault removal moment is calculated, and this is used as the direction for suppressing transient overvoltage, and then the optimal parameters for improving voltage stability are determined, which can ultimately achieve the purpose of improving the voltage stability of the power system.

[0098] Furthermore, in order to improve the parameter optimization problem of voltage stability, the present invention strictly derives the sensitivity expression of the voltage amplitude at the moment of fault removal with respect to the new energy control parameter from a theoretical level, and uses this as the direction of suppressing transient overvoltage to further determine the optimal parameters for improving voltage stability. Since the technical solution of the present invention is a strict mathematical derivation and is aimed at all new energy units in the power system, when solving the above problems, the control parameters of new energy equipment can be adjusted in a macroscopic manner so that the control department can control it conveniently, and the control parameters of each new energy unit can be accurately adjusted at a microscopic level so that the system voltage stability can achieve the best effect. In summary, the technical solution of the present invention establishes a quasi-steady-state model based on time scale separation for the transient overvoltage problem, obtains the state of the new energy unit and the DC system through quasi-steady-state calculation, and further determines the direction of suppressing transient overvoltage, that is, the negative gradient direction, through the gradient descent algorithm, and finally determines a set of new energy control parameters that optimize the system voltage stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0099] In order to more clearly illustrate the technical solutions in the present invention or 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 some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0100] Figure 1 It is a flow chart of a method for optimizing control parameters of new energy equipment in an embodiment of the present invention.

[0101] Figure 2 It is a schematic diagram of a new energy structure under quasi-steady state in a specific embodiment of the present invention.

[0102] Figure 3It is a schematic diagram of a CSEE-FS (Chinese Society for Electrical Engineering-Frequency Stability) standard calculation example in a specific embodiment of the present invention.

[0103] Figure 4 It is a specific flow chart of a method for optimizing control parameters of new energy equipment based on a gradient descent method in an embodiment of the present invention.

[0104] Figure 5 1 is a schematic diagram of a time domain simulation of the voltage amplitude of the node B10 before and after the new energy optimization parameters in an embodiment of the present invention.

[0105] Figure 6 : is a schematic diagram of time domain simulation of active power of new energy units before and after new energy optimization parameters in an embodiment of the present invention; wherein, Figure 6 (a) is a schematic diagram of the wind turbine WT01-1. Figure 6 (b) is a schematic diagram of the photovoltaic unit PV01-1.

[0106] Figure 7 It is a schematic diagram of a new energy equipment control parameter optimization system in an embodiment of the present invention. DETAILED DESCRIPTION

[0107] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention; it is obvious that the described embodiments and technical solutions are only part of the embodiments of the present invention, not all of the embodiments.

[0108] All other embodiments obtained by those of ordinary skill in the art without creative work based on the technical solutions disclosed in the embodiments of the present invention belong to the scope of protection of the present invention. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device including a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0109] See also Figure 1 The embodiment of the present invention discloses a method for optimizing control parameters of a new energy device, specifically a method for optimizing control parameters of a new energy device capable of improving voltage stability of a power system, comprising the following steps:

[0110] Step S1, based on the new energy power system whose control parameters of the new energy equipment are to be optimized, a quasi-steady-state model of the whole system based on time scale separation is established for the fault ride-through characteristics of the new energy and the transient overvoltage problem caused by the DC commutation failure; wherein the quasi-steady-state model of the whole system includes the quasi-steady-state models of the synchronous generator, the load, the new energy unit and the DC system;

[0111] Step S2, based on the full-system quasi-steady-state model established in step 1, the power flow information of the new energy power system is obtained; based on the full-system quasi-steady-state model and the power flow information, a preset fault quasi-steady-state calculation is performed to obtain the state of the new energy unit and the state of the DC system; in a specific exemplary technical solution, when obtaining the power flow information of the new energy power system, an alternating iterative method can be used for calculation; the power flow information includes line current information and node voltage information of the new energy power system;

[0112] Step S3, based on the quasi-steady-state model of the whole system, the state of the new energy unit and the state of the DC system, calculate the gradient of the transient overvoltage value with respect to the new energy control parameter at the preset fault removal moment, and use the gradient descent method to obtain the new energy equipment control parameter that is most conducive to voltage stability.

[0113] In the technical solution disclosed in the embodiment of the present invention, it is elaborated in detail that the optimization direction of suppressing transient overvoltage is clarified by calculating the gradient of the transient overvoltage value at the preset fault removal moment relative to the new energy control parameter. This gradient information is used as a guide to accurately determine the optimal parameter set that can improve voltage stability. Therefore, the technical solution of the embodiment of the present invention can enhance the voltage stability of the power system and ensure the robustness of the system when facing fault conditions.

[0114] In a specific embodiment of the present invention, in step S1, the quasi-steady-state model of the synchronous generator is expressed as:

[0115]

[0116] In the formula, I d ,I q are the direct-axis and quadrature-axis components of the current injected into the node by the synchronous generator in the rotating coordinate system; E q ′、E d ′ are the transient electromotive force of the quadrature axis and direct axis of the synchronous generator respectively; V x 、V y They are the nodes where the synchronous generator is located in the stationary coordinates

[0117] ''

[0118] The real and imaginary parts of the node voltage under the system; δ is the synchronous generator power angle; x d 、x qThey are the quadrature-axis and direct-axis transient reactances of synchronous generators respectively;

[0119] The quasi-steady-state model of the load is expressed as:

[0120]

[0121] In the formula, I d,load is the d-axis current injected into the power system by the load; d1, d2, and d3 are the coefficients of the constant impedance, constant current, and constant power terms corresponding to the active power in the ZIP model (for explanation, Z represents the constant impedance model, I represents the constant current model, and P represents the constant power model); V load is the voltage amplitude of the node where the load is located; q1, q2, q3 are the coefficients of the constant impedance, constant current, and constant power terms corresponding to reactive power in the ZIP model; I q,load Injects q-axis current into the power system for the load.

[0122] See also Figure 2 ,Example Explanatory, renewable power system is a very complex dynamic system ,with multi-timescale characteristics, which needs to be analyzed and studied at ,different levels, and according to the application requirements, the analysis model that ,can reflect the corresponding time scale is selected. The exemplary structure ,is shown in the figure. Figure 2 shown.

[0123] Under normal conditions, the grid voltage is greater than the fault ride-through threshold, i.e. V PCC >V LV_set At this time, the converter is in constant power control mode, and its control strategy will output active and reactive control command values ​​P ref and Q ref At this time, the current injected by the new energy unit to the grid is: I d1 +jI q1 , its quasi-steady-state model is:

[0124]

[0125] When a fault occurs, the voltage V PCC The disturbance is lower than the set threshold V LV_set When V PCC <V LV_set When the new energy unit enters the low voltage ride-through state, its active power will be rapidly reduced due to the reduction of the terminal voltage and the low-voltage ride-through control strategy. After the low-voltage ride-through state ends, it will gradually recover to the level before the fault. Its reactive power will be increased during the low-voltage ride-through process to raise the terminal voltage. After the low-voltage ride-through process ends, it will immediately stop increasing reactive power and restore the steady-state reactive power control strategy. At this time, the current injected into the grid by the new energy unit in the low-voltage ride-through state is: I d2 +jI q2 , its quasi-steady-state model is:

[0126]

[0127] In the formula, K 1_Ip_LV is the active current calculation coefficient 1; K 2_Ip_LV is the active current calculation coefficient 2; I pset_LV is the active current setting value; I p0 is the initial active current; V t is the terminal voltage amplitude; K 1_Iq_LV is the reactive current calculation coefficient 1; K 2_Iq_LV is the reactive current calculation coefficient2; I qset_LV is the reactive current setting value; I q0 is the initial reactive current; V Lin It is the low voltage ride-through threshold;

[0128] After adopting the low voltage fault ride-through strategy, the voltage V PCC It will recover to the normal state when the voltage is higher than the low voltage crossing recovery threshold V LV_set_re When V PCC >V LV_set_re , the new energy unit enters the low voltage fault ride-through recovery state. At this time, the current injected by the new energy to the grid is: I d3 +jI q3 , its quasi-steady-state model is:

[0129]

[0130] In the formula, K Ip_LVREC0 is the active current calculation coefficient 1; I pset_LVREC0 is the active current setting value; I p0 is the initial active current.

[0131] In addition, the DC system also needs to consider two quasi-steady-state models during and after a fault. The quasi-steady-state model during a fault adopts a fixed minimum trigger angle on the rectifier side and a fixed current control on the inverter side, which can be expressed as:

[0132]

[0133] In the formula,

[0134] After a fault, the rectifier side uses a constant current and the inverter side uses a constant arc extinction angle control, which can be expressed as:

[0135]

[0136] Again with and By combining these two, we can get the analytical solution for the current.

[0137] The dynamic response speed of power electronic equipment is significantly faster than the electromechanical transient of synchronous units. When studying the transient overvoltage problem of AC system, the quasi-steady-state model of power electronic control system can be used, that is, in the electromechanical transient time scale, it is considered that the switching control process of power electronics instantaneously reaches its quasi-steady-state equilibrium point, so that the impact of power electronic equipment on AC system can be described by a set of switching nonlinear algebraic equations. In short, the quasi-steady-state electromechanical transient model of power electronic equipment such as DC transmission and new energy generation can be expressed as:

[0138]

[0139] Among them, the algebraic variable y represents the internal operating state of the device, V is the voltage phasor of the device grid connection point, and I is the current phasor injected by the device into the system; R(·) is a non-smooth and possibly non-continuous function, and the dimension of its range space is equal to the dimension of the algebraic variable y; and It is generally a continuous smooth function, and the quasi-steady-state model of the equipment can be concisely expressed as:

[0140]

[0141] Here H(·) becomes a non-smooth, non-continuous function that may not have an explicit analytical expression, which describes the highly sensitive characteristics of the switching control of the equipment during the system transient process and its injected current to the grid-connected bus voltage.

[0142] In one embodiment of the present invention, step S2 is based on the quasi-steady-state model of all power system equipment. Each device in the power system depends on the voltage of its node grid connection point to determine its quasi-steady-state control strategy, and the power system voltage is affected by the current injected by each device. Therefore, the quasi-steady-state algebraic equations of all devices are combined to form the following power system network equations, and the equations are solved iteratively. When the equations converge, it is considered that the voltage at which the equations are iterated to converge is the node voltage required by the quasi-steady-state model. Based on the quasi-steady-state modeling of power electronic equipment, the quasi-steady-state model of the entire system can be written in the following compact form, and the equation expression is:

[0143] Y[V]e jθ =[e jθ ](I d (V,p)-jI q (V,p))+I g (δ,x);

[0144] Where Y is the power system node admittance matrix; [V], e jθ are the voltage amplitude and phase angle of all nodes in the power system respectively; I d (V,p)-jI q(V,p) is the current injected into the grid by the new energy unit and the DC system, indicating that it is affected by the grid connection point voltage V and the current control state p; I g (δ,x) is the current injected by the synchronous generator into the grid, indicating that it is affected by the current power angle δ and the transient electromotive force of the state variable; [e jθ ]The i-th element is expressed by Euler's formula expansion as follows: In the formula, θ i is the phase angle of the voltage at the i-th node.

[0145] Specifically and illustratively, a test is conducted on the CSEE-FS frequency stability standard example, as shown in the schematic diagram. Figure 3 As shown, node B10 is selected to set a three-phase grounding fault, the line where the fault is located is "B10-B05", and the fault duration is 0.1s. According to the fault information, the power system node admittance matrix is ​​modified to the node admittance matrix Y' when the fault occurs, and the quasi-steady-state model of each element is combined to estimate whether the DC phase change failure occurs, and the DC information of the phase change failure during the fault period is obtained; after the fault is over, the line is not cut off to restore the fault, and the power system node admittance matrix is ​​modified to the node admittance matrix Y" after the fault is restored. Combined with the quasi-steady-state model of each element and the DC information of the phase change failure during the fault, based on the quasi-steady-state calculation of the system during the fault, it is considered that the initial value of the current in the recovery stage is equal to the current during the fault, and the voltage level of each node after the fault recovery is calculated to obtain the transient overvoltage assessment result of each node.

[0146] In one embodiment of the present invention, step S3 performs disturbance analysis on the voltage amplitude immediately after the fault is removed, and the negative gradient direction is the direction of suppressing transient overvoltage; wherein,

[0147]

[0148] In the formula, V(τ c ) is the preset fault removal τ c The transient overvoltage value at the moment, Characteristics of the components in the system.

[0149] In the specific exemplary technical solution, the optimization method of the new energy control parameters is to take When the maximum number of iterations is reached or The optimization ends when .

[0150] Faced with the challenge of complex parameter optimization to improve voltage stability, the present invention, starting from basic theory, rigorously derives the sensitivity relationship expression between the voltage amplitude at the moment of fault removal and the control parameters of new energy sources. This expression not only provides clear directional guidance for suppressing transient overvoltages, but also is the key basis for determining the optimal control parameters. It is worth noting that the uniqueness of the present invention lies in the rigor and comprehensiveness of its mathematical derivation, which covers the conditions of all new energy units in the power system. At the application level, the significant advantages of the technical solution of the embodiment of the present invention are: from a macro perspective, it supports the overall adjustment of the control parameters of new energy equipment in different zones, which greatly facilitates the operation and management of the control department; from a micro level, it can realize fine adjustment of the control parameters of each new energy unit to ensure that the system voltage stability reaches the optimal state. This macro-micro combination of control strategy reflects the high flexibility and practicality of the present invention. In summary, the technical solution of the embodiment of the present invention aims at the problem of transient overvoltage, and establishes a quasi-steady-state model based on time scale separation. The model accurately captures the real-time status of the new energy unit and the DC system through quasi-steady-state calculation, and then uses the gradient descent algorithm to iteratively search and finally determine the set of new energy control parameters that can achieve the optimal system voltage stability along the negative gradient direction (i.e., the most effective path to suppress transient overvoltage). This series of innovative measures not only improves the power system's ability to respond to faults, but also provides strong technical support for the stable operation of smart grids.

[0151] In a specific embodiment of the present invention, the preset fault may be an AC fault or a DC fault. The AC fault includes a three-phase permanent grounding fault, a generator shedding fault, and the like. The DC fault may be set to a DC commutation failure fault.

[0152] In the embodiment of the present invention, it is assumed that the power network includes n nodes, wherein the grid-connected power electronic device establishes an analytical expression h of the injected current with respect to the grid-connected point voltage in the dq coordinate system: d (V)-jh q (V), the network uses xy synchronous coordinates, and the state quantity of the power electronic equipment is transformed into the node admittance equation, and the following is obtained:

[0153] Y[e jθ ]V=[e jθ ](h d (V)-jh q (V));

[0154] in, is the admittance matrix, is the angular difference between the local dq coordinate of the device and the global xy coordinate, [e j θ ] is e jθis a diagonal matrix of elements. To simplify writing, h d (V), h q (V) are denoted as h d 、h q In order to study the change of grid voltage with current after the system is stabilized by small disturbance, the above equation is linearized at the equilibrium point.

[0155]

[0156] Let Y = G + jB, expand the above formula by real and imaginary parts to get:

[0157]

[0158] in,

[0159] M 11 =-G[V][sinθ]-B[V][cosθ]+[h d (V)][sinθ]-[h q (V)][cosθ];

[0160] M 21 =G[V][cosθ]-B[V][sinθ]-[h d )V)][cosθ]-[h q (V)][sinθ];

[0161]

[0162] In this way, the above process solves and 's problem of solution, and It is necessary to consider the characteristics of the components in the system; for example, for the low voltage ride-through control strategy of new energy units, when applying the specified current control, the following can be obtained:

[0163]

[0164]

[0165] In the formula, K 1_IP_LV is the active current calculation coefficient 1; V PCC is the voltage amplitude at the grid connection point; is the power factor angle of the new energy unit; S m_base is the capacity of the new energy station; S base is the system baseline capacity; K 2_IP_LV is the active current calculation coefficient 2; I Pset_LV is the active current setting value; N is the number of units in the new energy plant; K 1_IQ_LV is the reactive current calculation coefficient 1; VLin To enter the low voltage crossing threshold; K 2_IQ_LV is the reactive current calculation coefficient 2; I Q0 is the initial reactive current; I Qset_LV is the reactive current setting value, so the above process solves of solving problems;

[0166] Next, the gradient descent method is used to find the optimal control parameters: select an appropriate step size η, and calculate the voltage amplitude V(τ c ), and then update it:

[0167]

[0168] Where p is the initial value of the new energy control parameter at the kth iteration, is the updated value of the new energy control parameter at the kth iteration.

[0169] In the embodiment of the present invention, when the iteration satisfies Or when the maximum number of iterations is reached, it is considered that the most effective suppression of transient overvoltage is achieved through the optimization of parameters, thereby improving the system voltage stability; finally, the flowchart of the voltage stability algorithm based on the gradient descent method is as follows Figure 4 The parameters of the system before and after the optimization of new energy are shown in Table 1. The time domain simulation diagram of the node B10 voltage and the active output of the new energy unit before and after the optimization of new energy parameters is shown in Figure 5 and Figure 6 As shown in the result diagram, it can be seen that t = 1.6s corresponds to the transient overvoltage moment before parameter optimization. The strategy after parameter optimization makes the active output of the new energy unit begin to decline at t = 1.5 to 1.6s, the transient overvoltage moment is advanced to t = 1.5s, and the transient overvoltage value is reduced from 1.0763pu to 1.02pu. Therefore, after parameter optimization, the voltage stability is improved.

[0170] Table 1 Parameters before and after system new energy optimization (unit: %)

[0171]

[0172]

[0173] The following are device embodiments of the present invention, which can be used to implement the method embodiments of the present invention. For details not disclosed in the device embodiments, please refer to the method embodiments of the present invention.

[0174] See also Figure 7 In an embodiment of the present invention, a new energy equipment control parameter optimization system is provided, comprising:

[0175] The model building module is used to establish a quasi-steady-state model of the whole system based on time scale separation for the fault ride-through characteristics of new energy equipment and transient overvoltage problems caused by DC commutation failure.

[0176] A quasi-steady-state calculation module is used to calculate and obtain the power flow information of the new energy power system based on the quasi-steady-state model of the whole system; based on the quasi-steady-state model of the whole system and the power flow information, a quasi-steady-state calculation of a preset fault is performed to obtain the state of the new energy unit and the state of the DC system;

[0177] The parameter updating and optimization module is used to calculate the gradient of the transient overvoltage value with respect to the new energy control parameter at the preset fault removal moment based on the quasi-steady-state model of the whole system, the state of the new energy unit and the state of the DC system, and to obtain the new energy equipment control parameter that is most conducive to voltage stability by using the gradient descent method.

[0178] In one embodiment of the present invention, a computer device is provided, the computer device including a processor and a memory, the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc., which are the computing core and control core of the terminal, which are suitable for implementing one or more instructions, and are specifically suitable for loading and executing one or more instructions in a computer storage medium to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used to perform the operation of the new energy device control parameter optimization method.

[0179] In one embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It is understandable that the computer-readable storage medium here may include a built-in storage medium in a computer device, and of course may also include an extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions may be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here may be a high-speed RAM (Random Access Memory) memory, or a non-volatile memory (non-volatile memory), such as at least one disk memory. The processor may load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the control parameter optimization method for new energy equipment in the above-mentioned embodiment.

[0180] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, optical storage, etc.) that contain computer-usable program code.

[0181] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0182] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0183] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0184] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for optimizing control parameters of new energy equipment, characterized in that: The following steps are involved: Based on the new energy power system with the control parameters of the new energy equipment to be optimized, a quasi-steady-state model of the whole system based on time scale separation is established for the fault ride-through characteristics of new energy and the transient overvoltage problem caused by DC commutation failure. Based on the quasi-steady-state model of the whole system, the power flow information of the new energy power system is calculated; based on the quasi-steady-state model of the whole system and the power flow information, a quasi-steady-state calculation of a preset fault is performed to obtain the state of the new energy unit and the state of the DC system; Based on the quasi-steady-state model of the whole system, the state of the new energy unit and the state of the DC system, the gradient calculation of the transient overvoltage value at the preset fault removal moment with respect to the new energy control parameter is performed, and the gradient descent method is used to obtain the new energy equipment control parameter that is most conducive to voltage stability.

2. A method for optimizing control parameters of new energy equipment according to claim 1, characterized in that: The expression of the quasi-steady-state model of the whole system based on time scale separation is: Y[V]e jθ =[e jθ ](I d (V,p)-jI q (V,p))+I g (δ,x); In the formula, j is an imaginary unit, Y represents the power system node admittance matrix; [V], e jθ Respectively represent the voltage amplitude and phase angle of all nodes in the power system; I d (V,p)-jI q (V,p) represents the current injected into the grid by the new energy unit and the DC system, V represents the grid connection point voltage, and p represents the current control state; I g (δ,x) represents the current injected into the grid by the synchronous generator, δ represents the synchronous generator power angle, and x represents the state variable transient electromotive force; [e jθ The i-th element in ] is expressed by Euler's formula expansion as θ i represents the phase angle of the voltage at the i-th node.

3. A method for optimizing control parameters of new energy equipment according to claim 2, characterized in that: The quasi-steady-state model of the whole system includes the quasi-steady-state models of synchronous generators, loads, new energy units and DC systems; wherein, The quasi-steady-state model of the synchronous generator is expressed as: In the formula, I d ,I q They represent the direct-axis and quadrature-axis components of the current injected into the node by the synchronous generator in the rotating coordinate system; E q ′、E d ′ represents the transient electromotive force of the quadrature axis and direct axis of the synchronous generator respectively; V x 、V y They represent the node where the synchronous generator is located at rest' Real and imaginary parts of node voltage in the coordinate system; x d 、x q They represent the quadrature-axis and direct-axis transient reactances of synchronous generators respectively; The quasi-steady-state model of the load is expressed as: In the formula, I d,load represents the d-axis current injected by the load into the power system; d1, d2, and d3 represent the coefficients of the constant impedance, constant current, and constant power terms corresponding to the active power in the ZIP model, respectively. Z represents the constant impedance model, I represents the constant current model, and P represents the constant power model; V load represents the voltage amplitude of the node where the load is located; q1, q2, and q3 represent the coefficients of the constant impedance, constant current, and constant power terms corresponding to reactive power in the ZIP model, respectively; I q,load To represent the q-axis current injected into the power system by the load; Under normal conditions, the quasi-steady-state model of the new energy unit is expressed as: In the formula, I d1 +jI q1 The current injected into the grid by the new energy unit under normal conditions; P ref , Q ref Respectively represent the active and reactive control command values ​​output by the control strategy; V PCC Indicates the grid connection point voltage; When a fault occurs, the quasi-steady-state model of the new energy unit is expressed as: In the formula, I d2 +jI q2 Indicates the current injected into the grid by the new energy unit in the low-voltage state; K 1_Ip_LV Indicates active current calculation coefficient 1; K 2_Ip_LV Indicates active current calculation coefficient 2; I pset_LV Indicates the active current setting value; I p0 Represents the initial active current; V t Indicates the terminal voltage amplitude; K 1_Iq_LV Indicates reactive current calculation coefficient 1; K 2_Iq_LV Indicates reactive current calculation coefficient 2; I qset_LV Indicates the reactive current setting value; I q0 Represents the initial reactive current; V Lin Indicates entering the low voltage ride-through threshold; After adopting the low voltage fault ride-through strategy, the quasi-steady-state model of the new energy unit is expressed as: In the formula, I d3 +jI q3 It indicates the current injected into the grid by new energy after the low voltage fault ride-through strategy is adopted; K Ip_LVREC0 Indicates active current calculation coefficient 1; I pset_LVREC0 It shows the active current setting value; I p0 Indicates the initial active current; During a fault, the quasi-steady-state model of the DC system is expressed as: In the formula, After the fault, the quasi-steady-state model of the DC system is expressed as: In the formula, in, and Combine them to find the analytical solution of the current; Where U cr , U ci is the AC bus voltage on both sides of the DC system, I d The DC system injects current into the grid, X cr , X ci is the leakage reactance of the converter transformer converted to the valve side, R d is the DC line resistance, T r 、T i is the transformer ratio on both sides, α is the trigger lag angle on the rectifier side, α min is the minimum critical trigger angle on the rectifier side, β is the trigger advance angle on the inverter side, γ is the arc extinction angle on the inverter side, P drref , P diref are the active power reference values ​​of the rectifier side and the inverter side respectively, γ iref is the reference value of the arc extinction angle on the inverter side, I δ is the DC current control margin on the inverter side, U dh , U dl are the thresholds for entering and exiting the low-voltage current limiting link, I vdmin It is the minimum current value of the low voltage current limiting link.

4. A method for optimizing control parameters of new energy equipment according to claim 3, characterized in that: In the step of calculating the gradient of the transient overvoltage value at the preset fault removal time with respect to the new energy control parameter, The gradient calculation expression is: In the formula, V(τ c ) represents the preset fault removal τ c Transient overvoltage value at each moment; All are characteristics of components in the power system; In the step of using the gradient descent method to obtain the control parameters of the new energy equipment that are most conducive to voltage stability, the update expression is: Where η represents the selected step size; Indicates the updated value of the new energy control parameter during iteration; Among them, the maximum number of iterations is reached or When , the optimization ends and the control parameters of the new energy equipment that are most conducive to voltage stability are obtained.

5. A method for optimizing control parameters of new energy equipment according to claim 1, characterized in that: The preset fault is an AC fault or a DC fault; The AC fault is a three-phase permanent grounding fault or a generator and load shedding fault; and the DC fault is a DC commutation failure fault.

6. A new energy equipment control parameter optimization system, characterized in that: include: The model building module is used to establish a quasi-steady-state model of the whole system based on time scale separation for the fault ride-through characteristics of new energy equipment and transient overvoltage problems caused by DC commutation failure. A quasi-steady-state calculation module is used to calculate and obtain the power flow information of the new energy power system based on the quasi-steady-state model of the whole system; based on the quasi-steady-state model of the whole system and the power flow information, a quasi-steady-state calculation of a preset fault is performed to obtain the state of the new energy unit and the state of the DC system; The parameter updating and optimization module is used to calculate the gradient of the transient overvoltage value with respect to the new energy control parameter at the preset fault removal moment based on the quasi-steady-state model of the whole system, the state of the new energy unit and the state of the DC system, and to obtain the new energy equipment control parameter that is most conducive to voltage stability by using the gradient descent method.

7. A new energy equipment control parameter optimization system according to claim 6, characterized in that: The expression of the quasi-steady-state model of the whole system based on time scale separation is: Y[V]e jθ =[e jθ ](I d (V,p)-jI q (V,p))+I g (δ,x); In the formula, j is an imaginary unit, Y represents the power system node admittance matrix; [V], e jθ Respectively represent the voltage amplitude and phase angle of all nodes in the power system; I d (V,p)-jI q (V,p) represents the current injected into the grid by the new energy unit and the DC system, V represents the grid connection point voltage, and p represents the current control state; I g (δ,x) represents the current injected into the grid by the synchronous generator, δ represents the synchronous generator power angle, and x represents the state variable transient electromotive force; [e jθ The i-th element in ] is expressed by Euler's formula expansion as θ i represents the phase angle of the voltage at the i-th node.

8. A new energy equipment control parameter optimization system according to claim 7, characterized in that: The quasi-steady-state model of the whole system includes the quasi-steady-state models of synchronous generators, loads, new energy units and DC systems; wherein, The quasi-steady-state model of the synchronous generator is expressed as: In the formula, I d ,I q They represent the direct-axis and quadrature-axis components of the current injected into the node by the synchronous generator in the rotating coordinate system; E q ′、E d ′ represents the transient electromotive force of the quadrature axis and direct axis of the synchronous generator respectively; V x 、V y They represent the node where the synchronous generator is located at rest' Real and imaginary parts of node voltage in the coordinate system; x d 、x q They represent the quadrature-axis and direct-axis transient reactances of synchronous generators respectively; The quasi-steady-state model of the load is expressed as: In the formula, I d,load represents the d-axis current injected by the load into the power system; d1, d2, and d3 represent the coefficients of the constant impedance, constant current, and constant power terms corresponding to the active power in the ZIP model, respectively. Z represents the constant impedance model, I represents the constant current model, and P represents the constant power model; V load represents the voltage amplitude of the node where the load is located; q1, q2, and q3 represent the coefficients of the constant impedance, constant current, and constant power terms corresponding to reactive power in the ZIP model, respectively; I q,load To represent the q-axis current injected into the power system by the load; Under normal conditions, the quasi-steady-state model of the new energy unit is expressed as: In the formula, I d1 +jI q1 The current injected into the grid by the new energy unit under normal conditions; P ref , Q ref Respectively represent the active and reactive control command values ​​output by the control strategy; V PCC Indicates the grid connection point voltage; When a fault occurs, the quasi-steady-state model of the new energy unit is expressed as: In the formula, I d2 +jI q2 Indicates the current injected into the grid by the new energy unit in the low-voltage state; K 1_Ip_LV Indicates active current calculation coefficient 1; K 2_Ip_LV Indicates active current calculation coefficient 2; I pset_LV Indicates the active current setting value; I p0 Represents the initial active current; V t Indicates the terminal voltage amplitude; K 1_Iq_LV Indicates reactive current calculation coefficient 1; K 2_Iq_LV Indicates reactive current calculation coefficient 2; I qset_LV Indicates the reactive current setting value; I q0 Represents the initial reactive current; V Lin Indicates entering the low voltage ride-through threshold; After adopting the low voltage fault ride-through strategy, the quasi-steady-state model of the new energy unit is expressed as: In the formula, I d3 +jI q3 It indicates the current injected into the grid by new energy after the low voltage fault ride-through strategy is adopted; K Ip_LVREC0 Indicates active current calculation coefficient 1; I pset_LVREC0 It shows the active current setting value; I p0 Indicates the initial active current; During a fault, the quasi-steady-state model of the DC system is expressed as: In the formula, After the fault, the quasi-steady-state model of the DC system is expressed as: In the formula, in, and Combine them to find the analytical solution for the current; Where U cr , U ci is the AC bus voltage on both sides of the DC system, I d The DC system injects current into the grid, X cr , X ci is the leakage reactance of the converter transformer converted to the valve side, R d is the DC line resistance, T r , T i is the transformer ratio on both sides, α is the trigger lag angle on the rectifier side, α min is the minimum critical trigger angle on the rectifier side, β is the trigger advance angle on the inverter side, γ is the arc extinction angle on the inverter side, P drref , P diref are the active power reference values ​​of the rectifier side and the inverter side respectively, γ iref is the reference value of the arc extinction angle on the inverter side, I δ is the DC current control margin on the inverter side, U dh , U dl are the thresholds for entering and exiting the low-voltage current limiting link, I vdmin It is the minimum current value of the low voltage current limiting link.

9. A new energy equipment control parameter optimization system according to claim 8, characterized in that: In the step of calculating the gradient of the transient overvoltage value at the preset fault removal time with respect to the new energy control parameter, The gradient calculation expression is: In the formula, V(τ c ) represents the preset fault removal τ c Transient overvoltage value at each moment; All are characteristics of components in the power system; In the step of using the gradient descent method to obtain the control parameters of the new energy equipment that are most conducive to voltage stability, the update expression is: Where η represents the selected step size; Indicates the updated value of the new energy control parameter during iteration; Among them, the maximum number of iterations is reached or When , the optimization ends and the control parameters of the new energy equipment that are most conducive to voltage stability are obtained.

10. A new energy equipment control parameter optimization system according to claim 6, characterized in that: The preset fault is an AC fault or a DC fault; The AC fault is a three-phase permanent grounding fault or a generator and load shedding fault; and the DC fault is a DC commutation failure fault.

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