Wind power plant dynamic reactive capacity demand calculation method and system for maintaining voltage stability

Abstract

The invention discloses a wind power plant dynamic reactive capacity demand calculation method and system for maintaining voltage stability, and belongs to the technical field of new energy grid connection. The method comprises the following steps: establishing a steady-state and transient-state model for a wind power plant group to access a main network, performing time-domain simulation of a power grid fault based on the steady-state and transient-state model, and obtaining a time-domain simulation result; for each iteration, based on the time domain simulation result corresponding to the initial control quantity and the state quantity, a perturbation method is adopted to calculate a plurality of target physical quantities such as sensitivity of node voltage to dynamic reactive power output of the wind power plant, and a linear optimization model of the dynamic reactive power demand of the wind power plant is established; and performing loop iteration solution on the sequence linear optimization model, and determining the dynamic reactive capacity demand of the wind power plant group based on a solution result. According to the method, the aims of improving the voltage stability of wind power integration under fault disturbance, preventing and controlling the continuous fault ride-through risk of wind power and the like can be achieved, and new energy acceptance is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy grid connection, and more specifically, to a method and system for calculating the dynamic reactive capacity demand of a wind farm group for maintaining voltage stability. Background Art

[0002] After the wind farm group is connected to the grid, a reasonable reactive voltage balance point should be established under fault disturbance, so as to maintain the voltage stability after the wind power is connected to the grid, prevent the wind turbines from continuously entering and exiting the fault ride-through, and further impact the safety and stability of the grid. In particular, with the gradual increase in wind power access capacity and the continuous reduction in short-circuit ratio, the problem of wind power grid-connected voltage stability and unit fault ride-through has become more prominent. In order to improve the voltage stability after the wind farm group is connected and prevent the problem of wind power continuously entering and exiting the fault ride-through, the wind farm must have the ability to provide dynamic reactive support for the grid under fault disturbance. According to the "Technical Regulations on Wind Farm Access to the Power System", wind farm access needs to be equipped with sufficient and multi-type reactive sources. Generally speaking, in addition to the wind turbines themselves being able to output dynamic reactive power, dynamic reactive compensation devices such as SVG can also be installed.

[0003] Wind turbines, SVG dynamic compensation and other types of reactive sources in wind farms provide dynamic reactive support in coordination. Among them, wind turbines provide dynamic reactive support in two situations: one is the reactive voltage response control during fault ride-through; the other is the normal PID (proportional (P), integral (I), differential (D)) reactive voltage response control after the fault ride-through exits. After the fault disturbance, the wind power voltage decreases. When the low voltage fault ride-through (low ride-through) action threshold is reached (generally set to 0.9pu), the wind turbine fault ride-through control function is activated, generally adopting control strategies such as reducing active power and issuing capacitive reactive power to provide more dynamic support for voltage recovery and assist the wind turbine to complete fault ride-through; when the wind power voltage recovers and reaches the threshold for exiting low ride-through (generally set to greater than 0.9pu), the wind turbine switches the fault ride-through reactive voltage control to the normal PID reactive voltage control. After the switch, in order to maintain the economic efficiency of the unit operation, the wind turbine PID reactive voltage control mode is generally set to operate at a constant power factor of 1, that is, only active power is output, and the reactive power output is 0. In this way, when the fault disturbance is more serious or the connected grid is weak, the ability of wind power to provide dynamic reactive support is limited.

[0004] Due to various factors in actual operation, the dynamic reactive power support capacity of wind turbines is limited, so the dynamic reactive power sources such as SVG configured in the wind farm will play a major role. However, SVG also participates in the steady-state reactive power voltage control to deal with the daily fluctuation of wind power output. If the reactive power resources are exhausted or insufficient, the dynamic support effect provided under fault disturbance will be greatly reduced. In the case of low new energy short-circuit ratio and serious faults, the risk of safe and stable operation of wind power grid connection without dynamic reactive power support will increase. Summary of the invention

[0005] In view of the above problems, the present invention proposes a method for calculating the dynamic reactive capacity demand of a wind farm for maintaining voltage stability, comprising:

[0006] For the wind farm group, a steady-state and transient model of the wind farm group connected to the main grid is established. Based on the steady-state and transient models, a time-domain simulation of the power grid fault is performed, and the time-domain simulation results are obtained. If the wind power grid-connected voltage is stable and there is no continuous fault crossing in the time-domain simulation results, the time-domain simulation is terminated to obtain the final wind farm dynamic reactive demand optimization solution. Otherwise, the current wind farm SVG reactive capacity and the node voltage state quantity under the corresponding fault disturbance are used as the initial value of a new cycle iteration;

[0007] For one cycle iteration, a plurality of target physical quantities are calculated based on the time domain simulation results, and a linear optimization model of dynamic reactive power demand of the wind farm for maintaining voltage stability is established based on the plurality of target physical quantities;

[0008] Solving the linear optimization model, and determining an optimal solution for the dynamic reactive capacity demand of the wind farm group in this iteration based on the solution result;

[0009] Based on the optimized solution of the dynamic reactive capacity demand of the wind farm group under this iteration, the time domain simulation is performed to judge the voltage stability and fault ride-through problems under the new SVG dynamic reactive capacity demand. If the voltage is unstable and continuous fault ride-through problems occur, the linear optimization model is established and solved in a cyclic iteration until the voltage is stable and there is no continuous fault ride-through, and the final optimized solution for the dynamic reactive capacity demand of the wind farm is obtained.

[0010] Optionally, establish a steady-state and transient model of the wind farm group connected to the main grid, including:

[0011] Equivalent aggregation model of each wind farm in the wind farm group, low-voltage fault ride-through control / protection model of wind turbines, and SVG constant voltage response control strategy model of each wind farm in the wind farm group.

[0012] Optionally, a steady-state and transient model of a wind farm group connected to a main grid is established based on PSD simulation software, and based on the PSD simulation software, a time domain simulation of a grid fault is performed according to the steady-state and transient models.

[0013] Optionally, time domain simulation results include: wind turbine terminal voltage simulation curve, wind turbine active power / reactive power simulation curve, grid-connected point bus voltage simulation curve, grid-connected line active power / reactive power simulation curve, wind farm group access area hub bus voltage simulation curve and wind turbine low-voltage fault ride-through control / protection action event information.

[0014] Optionally, multiple target physical quantities include: a sensitivity matrix of grid node voltage to the dynamic reactive output size of wind farm SVG, a positive / negative adjustment amount of reactive adjustment ΔQj of control variable SVG, node voltage after reactive adjustment ΔQ of SVG, and restrictions on the ΔQ control range of control variable SVG.

[0015] Optionally, based on the time domain simulation results, multiple target physical quantities are calculated, including:

[0016] For the basic operating conditions under voltage instability / continuous fault ride-through problems, the sensitivity matrix S of the grid node voltage to the dynamic reactive power output of the wind farm SVG is calculated. vq ;

[0017] Under the basic operating conditions, the reactive adjustment amount of the j-th wind farm SVG in the wind farm group is defined as follows:

[0018]

[0019] in:

[0020]

[0021] in, They are the reactive adjustment value ΔQ of the control variable SVG j The positive and negative adjustment amount,

[0022] Among them, Q j,0 is the current reactive power of the j-th wind farm SVG, is the upper limit of the reactive capacity of the SVG of the jth wind farm, is the lower limit of SVG reactive capacity of the jth wind farm;

[0023] The node basic operating voltage V under fault 0 Under this condition, the node voltage after SVG reactive power adjustment ΔQ is calculated, and the calculation formula is as follows:

[0024] V=V 0 +S vq ·(ΔQ + -ΔQ - );

[0025] Based on the effective interval of the linear sensitivity of the basic operating condition, a control range limitation is imposed on ΔQ of the control variable SVG.

[0026] Optionally, the perturbation method is used to calculate the sensitivity of the voltage of the main grid node and the wind power node to the reactive power output of the wind farm SVG. Based on the initial reactive power value Q of the wind farm SVG 0 , the initial voltage value of the main grid node and wind power node V 0 , the wind farm SVG reactive power is adjusted with a small step size ΔQ, and the transient time domain simulation is performed using PSD software. The simulation outputs the voltage curves of the main grid and wind turbine nodes under fault disturbance after the SVG reactive power is adjusted ΔQ. The change in voltage of each node ΔV is calculated from the simulation curve. Therefore, S vq The calculation formula is as follows:

[0027] S vq =ΔV·(ΔQ) -1

[0028] Wherein, ΔV is the voltage change.

[0029] Optionally, the objective function and constraints of the linear optimization model are as follows:

[0030] Objective function:

[0031]

[0032] Constraints:

[0033] S vq ·(ΔQ + -ΔQ - )≤V max -V 0

[0034] S vq ·(ΔQ + -ΔQ - )≥V min -V 0

[0035]

[0036] in, They are the reactive adjustment value ΔQ of the control variable SVG j The positive and negative adjustment amount, S vq is the sensitivity matrix of the grid node voltage to the dynamic reactive power output of the wind farm SVG, and the change in the dynamic reactive power of each wind farm SVG is ΔQ = ΔQ + -ΔQ - , V max 、V minare the upper and lower limit vectors of the node voltage threshold for maintaining voltage stability / preventing wind power from continuous crossing, V 0 is the initial node voltage of this iteration, Q j,0 is the current reactive power of the j-th wind farm SVG, is the upper limit of the reactive capacity of the SVG of the jth wind farm, is the lower limit of the reactive capacity of the SVG of the jth wind farm, ΔQ ad Maximum adjustment amount for the SVG reactive power for this iteration.

[0037] On the other hand, the present invention also proposes a wind farm group dynamic reactive capacity demand calculation system for maintaining voltage stability, comprising:

[0038] The time domain simulation unit is used to establish a steady-state and transient model of the wind farm group connected to the main grid for the wind farm group, perform a time domain simulation of the power grid fault based on the steady-state and transient models, and obtain the time domain simulation results. If the wind power grid-connected voltage is stable and there is no continuous fault crossing in the time domain simulation results, the time domain simulation is terminated to obtain the final wind farm dynamic reactive demand optimization solution. Otherwise, the current wind farm SVG reactive capacity and the node voltage state quantity under the corresponding fault disturbance are used as the initial value of a new cycle iteration;

[0039] A calculation unit, configured to calculate a plurality of target physical quantities based on the time domain simulation result for one cycle iteration, and to establish a linear optimization model of a dynamic reactive power demand of a wind farm for maintaining voltage stability based on the plurality of target physical quantities;

[0040] A solving unit, used for solving the linear optimization model, and determining an optimized solution for the dynamic reactive capacity demand of the wind farm group in this iteration based on the solving result;

[0041] Based on the optimized solution of the dynamic reactive capacity demand of the wind farm group under this iteration, the time domain simulation is performed to judge the voltage stability and fault ride-through problems under the new SVG dynamic reactive capacity demand. If the voltage is unstable and continuous fault ride-through problems occur, the linear optimization model is established and solved in a cyclic iteration until the voltage is stable and there is no continuous fault ride-through, and the final optimized solution for the dynamic reactive capacity demand of the wind farm is obtained.

[0042] Optionally, establish a steady-state and transient model of the wind farm group connected to the main grid, including:

[0043] Equivalent aggregation model of each wind farm in the wind farm group, low-voltage fault ride-through control / protection model of wind turbines, and SVG constant voltage response control strategy model of each wind farm in the wind farm group.

[0044] Optionally, a steady-state and transient model of a wind farm group connected to a main grid is established based on PSD simulation software, and based on the PSD simulation software, a time domain simulation of a grid fault is performed according to the steady-state and transient models.

[0045] Optionally, time domain simulation results include: wind turbine terminal voltage simulation curve, wind turbine active power / reactive power simulation curve, grid-connected point bus voltage simulation curve, grid-connected line active power / reactive power simulation curve, wind farm group access area hub bus voltage simulation curve and wind turbine low-voltage fault ride-through control / protection action event information.

[0046] Optionally, multiple target physical quantities, including: the sensitivity matrix of the grid node voltage to the dynamic reactive output of the wind farm SVG, the reactive adjustment of the control variable SVG ΔQ j The positive / negative adjustment amount of SVG, the node voltage after the reactive power adjustment ΔQ of SVG and the limitation of the ΔQ control range of the control variable SVG are imposed.

[0047] Optionally, based on the time domain simulation results, multiple target physical quantities are calculated, including:

[0048] For the basic operating conditions under voltage instability / continuous fault ride-through problems, the sensitivity matrix S of the grid node voltage to the dynamic reactive power output of the wind farm SVG is calculated. vq ;

[0049] Under the basic operating conditions, the reactive adjustment amount of the j-th wind farm SVG in the wind farm group is defined as follows:

[0050]

[0051] in:

[0052]

[0053] in, They are the reactive adjustment value ΔQ of the control variable SVG j The positive and negative adjustment amount,

[0054] Among them, Q j,0 is the current reactive power of the j-th wind farm SVG, is the upper limit of the reactive capacity of the SVG of the jth wind farm, is the lower limit of SVG reactive capacity of the jth wind farm;

[0055] The node basic operating voltage V under fault 0 Under this condition, the node voltage after SVG reactive power adjustment ΔQ is calculated, and the calculation formula is as follows:

[0056] V=V0 +S vq ·(ΔQ + -ΔQ - );

[0057] Based on the effective interval of the linear sensitivity of the basic operating condition, a control range limitation is imposed on ΔQ of the control variable SVG.

[0058] Optionally, the perturbation method is used to calculate the sensitivity of the voltage of the main grid node and the wind power node to the reactive power output of the wind farm SVG. Based on the initial reactive power value Q of the wind farm SVG 0 , the initial voltage value of the main grid node and wind power node V 0 , the wind farm SVG reactive power is adjusted with a small step size ΔQ, and the transient time domain simulation is performed using PSD software. The simulation outputs the voltage curves of the main grid and wind turbine nodes under fault disturbance after the SVG reactive power is adjusted ΔQ. The change in voltage of each node ΔV is calculated from the simulation curve. Therefore, S vq The calculation formula is as follows:

[0059] S vq =ΔV·(ΔQ) -1

[0060] Wherein, ΔV is the voltage change.

[0061] Optionally, the objective function and constraints of the linear optimization model are as follows:

[0062] Objective function:

[0063]

[0064] Constraints:

[0065] S vq ·(ΔQ + -ΔQ - )≤V max -V 0

[0066] S vq ·(ΔQ + -ΔQ - )≥V min -V 0

[0067]

[0068] in, They are the reactive adjustment value ΔQ of the control variable SVG j The positive and negative adjustment amount, S vqis the sensitivity matrix of the grid node voltage to the dynamic reactive power output of the wind farm SVG, and the change in the dynamic reactive power of each wind farm SVG is ΔQ = ΔQ + -ΔQ - , V max 、V min are the node voltage threshold upper and lower limit vectors for maintaining voltage stability / preventing wind power from continuous crossing, V 0 is the initial node voltage of this iteration, Q j,0 is the current reactive power of the j-th wind farm SVG, is the upper limit of the reactive capacity of the SVG of the jth wind farm, is the lower limit of the reactive capacity of the SVG of the jth wind farm, ΔQ ad Maximum adjustment amount for the SVG reactive power for this iteration.

[0069] In yet another aspect, the present invention further provides a computing device, comprising: one or more processors;

[0070] a processor for executing one or more programs;

[0071] When the one or more programs are executed by the one or more processors, the above-described method is implemented.

[0072] In yet another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, the method described above is implemented.

[0073] Compared with the prior art, the present invention has the following beneficial effects:

[0074] The present invention provides a method for calculating the dynamic reactive capacity demand of a wind farm to maintain voltage stability, comprising: for a wind farm group, establishing a steady-state and transient model of the wind farm group connected to the main grid, performing a time-domain simulation of a grid fault based on the steady-state and transient models, and obtaining a time-domain simulation result; if the wind power grid-connected voltage is stable and there is no continuous fault crossing in the time-domain simulation result, then the time-domain simulation is terminated to obtain a final wind farm dynamic reactive demand optimization solution; otherwise, the current wind farm SVG reactive capacity and the node voltage state quantity under the corresponding fault disturbance are used as the initial values ​​of a new cycle iteration; for one cycle iteration, multiple target physical quantities are calculated based on the time-domain simulation result, and the optimal solution is obtained based on the time-domain simulation result. Based on the multiple target physical quantities, a linear optimization model of the dynamic reactive power demand of the wind farm for maintaining voltage stability is established; the linear optimization model is solved, and based on the solution results, the optimized solution of the dynamic reactive power capacity demand of the wind farm group under this iteration is determined; based on the optimized solution of the dynamic reactive power capacity demand of the wind farm group under this iteration, the time domain simulation is performed to judge the voltage stability and fault ride-through problems under the new SVG dynamic reactive power demand. If the voltage is unstable and continuous fault ride-through problems occur, the linear optimization model is established and solved in a cyclic iteration until the voltage is stable and there is no continuous fault ride-through, and the final optimized solution of the dynamic reactive power capacity demand of the wind farm is obtained. The present invention can achieve the goals of improving the voltage stability of wind power grid-connected under fault disturbances, preventing and controlling the risk of continuous fault ride-through of wind power, and promoting the acceptance of new energy and improving the safety of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 is a flow chart of the method of the present invention;

[0076] Figure 2 A flowchart of an embodiment of the method of the present invention;

[0077] Figure 3 A structural diagram of a wind turbine model according to an embodiment of the method of the present invention;

[0078] FIG. 4( a ) and FIG. 4( b ) are active power control diagrams and reactive power control diagrams of low voltage ride-through of a wind turbine generator set according to an embodiment of the method of the present invention;

[0079] Figure 5 It is a low voltage ride through protection action envelope diagram of a wind turbine generator set in an embodiment of the method of the present invention;

[0080] Figure 6 It is a structure and parameter diagram of the SVG constant voltage response control model of the method embodiment of the present invention;

[0081] Figure 7 A schematic diagram of power flow distribution of a wind farm group connected to a power grid and a wind farm at full output according to an embodiment of the method of the present invention;

[0082] Figure 8 This is a diagram of wind turbine terminal voltage simulation results according to an embodiment of the method of the present invention;

[0083] Fig. 9 It is a diagram showing simulation results of wind farm grid-connected bus voltage and main grid bus voltage according to an embodiment of the method of the present invention;

[0084] Fig.10 This is a wind farm active power simulation result diagram taking DLF as an example according to an embodiment of the method of the present invention;

[0085] Fig.11 This is a simulation result diagram of active power transmitted through an mld500kV transformer according to an embodiment of the method of the present invention;

[0086] Fig.12 After dynamic reactive power is reserved for each wind farm SVG in the embodiment of the method of the present invention, the reactive power output simulation result diagram of SVG under 500kV double-circuit line mld-hft three-way N-2;

[0087] Fig.13 This is a diagram showing the simulation results of the bus voltage at the wind turbine end of mld-hft Sanyong N-2 under the condition of reserved reactive dynamic support of each wind farm SVG in the embodiment of the method of the present invention;

[0088] Fig.14 This is a simulation result diagram of the voltage of the wind farm grid-connected bus and the main grid bus of mld-hft Sanyong N-2 under the reserved reactive dynamic support of each wind farm SVG in the method embodiment of the present invention;

[0089] Fig.15 This is a simulation result diagram of active power transmission of 500kV mld transformer of mld-hft Sanyong N-2 under the condition of reserved reactive power dynamic support of each wind farm SVG in the embodiment of the method of the present invention;

[0090] Fig.16 It is a structural diagram of the system of the present invention. DETAILED DESCRIPTION

[0091] Now, exemplary embodiments of the present invention are described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0092] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0093] Embodiment 1:

[0094] The present invention proposes a method for calculating the dynamic reactive capacity demand of a wind farm to maintain voltage stability. Figure 1 As shown, including:

[0095] Step 1: For the wind farm group, a steady-state and transient model of the wind farm group connected to the main grid is established, and a time-domain simulation of the power grid fault is performed based on the steady-state and transient models, and the time-domain simulation results are obtained. If the wind power grid-connected voltage is stable and there is no continuous fault crossing in the time-domain simulation results, the time-domain simulation is terminated to obtain the final wind farm dynamic reactive demand optimization solution. Otherwise, the current wind farm SVG reactive capacity and the node voltage state quantity under the corresponding fault disturbance are used as the initial value of a new cycle iteration;

[0096] Step 2: for one cycle iteration, based on the time domain simulation results, multiple target physical quantities are calculated, and based on the multiple target physical quantities, a linear optimization model of the dynamic reactive power demand of the wind farm for maintaining voltage stability is established;

[0097] Step 3: Solve the linear optimization model, and determine the optimal solution of the dynamic reactive capacity demand of the wind farm group in this iteration based on the solution result;

[0098] Step 4: Based on the optimized solution of the dynamic reactive capacity demand of the wind farm group in this iteration, the time domain simulation is performed to judge the voltage stability and fault ride-through problems under the new SVG dynamic reactive capacity demand. If the voltage is unstable and continuous fault ride-through problems occur, the linear optimization model is established and solved in a cyclic iteration until the voltage is stable and there is no continuous fault ride-through, and the final optimized solution for the dynamic reactive capacity demand of the wind farm is obtained.

[0099] Among them, the steady-state and transient models of wind farm groups connected to the main grid are established, including:

[0100] Equivalent aggregation model of each wind farm in the wind farm group, low-voltage fault ride-through control / protection model of wind turbines, and SVG constant voltage response control strategy model of each wind farm in the wind farm group.

[0101] Among them, based on the PSD simulation software, a steady-state and transient model of the wind farm group connected to the main grid is established, and based on the PSD simulation software, a time domain simulation of the power grid fault is performed according to the steady-state and transient models.

[0102] Among them, the time domain simulation results include: wind turbine terminal voltage simulation curve, wind turbine active power / reactive power simulation curve, grid-connected point bus voltage simulation curve, grid-connected line active power / reactive power simulation curve, wind farm group access area hub bus voltage simulation curve and wind turbine low-voltage fault ride-through control / protection action event information.

[0103] Among them, multiple target physical quantities include: the sensitivity matrix of the grid node voltage to the dynamic reactive output of the wind farm SVG, the reactive adjustment amount ΔQ of the control variable SVG j The positive / negative adjustment amount of SVG, the node voltage after the reactive power adjustment ΔQ of SVG and the limitation of the ΔQ control range of the control variable SVG are imposed.

[0104] Wherein, based on the time domain simulation results, multiple target physical quantities are calculated, including:

[0105] For the basic operating conditions under voltage instability / continuous fault ride-through problems, the sensitivity matrix S of the grid node voltage to the dynamic reactive power output of the wind farm SVG is calculated. vq ;

[0106] Under the basic operating conditions, the reactive adjustment amount of the j-th wind farm SVG in the wind farm group is defined as follows:

[0107]

[0108] in:

[0109]

[0110] in, They are the reactive adjustment value ΔQ of the control variable SVG j The positive and negative adjustment amount,

[0111] Among them, Q j,0 is the current reactive power of the j-th wind farm SVG, is the upper limit of the reactive capacity of the SVG of the jth wind farm, is the lower limit of SVG reactive capacity of the jth wind farm;

[0112] The node basic operating voltage V under fault 0 Under this condition, the node voltage after SVG reactive power adjustment ΔQ is calculated, and the calculation formula is as follows:

[0113] V=V 0 +S vq ·(ΔQ + -ΔQ - );

[0114] Based on the effective interval of the linear sensitivity of the basic operating condition, a control range limitation is imposed on ΔQ of the control variable SVG.

[0115] The perturbation method is used to calculate the sensitivity of the voltage of the main grid node and wind power node to the reactive power output of the wind farm SVG. Based on the initial reactive power value Q 0 , the initial voltage value of the main grid node and wind power node V 0 , the wind farm SVG reactive power is adjusted with a small step size ΔQ, and the transient time domain simulation is performed using PSD software. The simulation outputs the voltage curves of the main grid and wind turbine nodes under fault disturbance after the SVG reactive power is adjusted ΔQ. The change in voltage of each node ΔV is calculated from the simulation curve. Therefore, S vq The calculation formula is as follows:

[0116] S vq =ΔV·(ΔQ) -1

[0117] Wherein, ΔV is the voltage change.

[0118] Among them, the objective function and constraints of the linear optimization model are as follows:

[0119] Objective function:

[0120]

[0121] Constraints:

[0122] S vq ·(ΔQ + -ΔQ - )≤V max -V 0

[0123] S vq ·(ΔQ + -ΔQ - )≥V min -V 0

[0124]

[0125] in, They are the reactive adjustment value ΔQ of the control variable SVG j The positive and negative adjustment amount, S vq is the sensitivity matrix of the grid node voltage to the dynamic reactive power output of the wind farm SVG, and the change in the dynamic reactive power of each wind farm SVG is ΔQ = ΔQ + -ΔQ - , V max 、V minare the node voltage threshold upper and lower limit vectors for maintaining voltage stability / preventing wind power from continuous crossing, V 0 is the initial node voltage of this iteration, Q j,0 is the current reactive power of the j-th wind farm SVG, is the upper limit of the reactive capacity of the SVG of the jth wind farm, is the lower limit of the reactive capacity of the SVG of the jth wind farm, ΔQ ad Maximum adjustment amount for the SVG reactive power for this iteration.

[0126] The present invention is further described below with reference to specific cases:

[0127] Specific steps, such as Figure 2 As shown, including the following:

[0128] (1) Based on the PSD power system simulation analysis software, the steady-state and transient models of wind farm groups connected to the main grid are established to perform simulation calculations and prepare data for optimization modeling.

[0129] (2) PSD software is used to perform time domain simulation of power grid faults. The grid nodes with voltage instability are located through the time domain simulation output curves of physical quantities such as node voltage (the present invention considers that the node voltage is long-term lower than 0.9pu is a voltage instability node); the information of wind farms with voltage instability and possible continuous fault ride-through is given through the time domain simulation output curves of physical quantities such as bus voltage and event information such as fault ride-through action output by the wind farm. If there are main grid nodes with voltage instability and wind farms with continuous fault ride-through, the current SVG reactive capacity and the node voltage under the corresponding fault disturbance are used as the initial values ​​of a new iteration, and the process goes to step (3). Otherwise, the process ends.

[0130] (3) For faults with voltage instability, continuous fault ride-through, and operating voltage V under fault 0 Under the same basic working conditions, the sensitivity matrix S of the grid node voltage to the dynamic reactive power output of the wind farm SVG is calculated. vq .

[0131] (4) Based on the basic operating conditions under fault conditions, define the reactive power adjustment of the j-th wind farm SVG They are the reactive adjustment value ΔQ of the control variable SVG j The positive and negative adjustment amount.

[0132] (5) Based on the current reactive power Q of the j-th wind farm SVG j,0 , after positive and negative adjustments, the upper and lower limits of SVG reactive power should not be exceeded, that is, the inequality constraint is satisfied:

[0133] (6) Under fault conditions, the node basic operating voltage V0 Under this condition, calculate the node voltage V=V after SVG reactive power adjustment ΔQ 0 +S vq ·(ΔQ + -ΔQ - ), the goal is to control the node voltage within the voltage upper and lower threshold ranges to maintain voltage stability and prevent continuous wind power fault crossing;

[0134] (7) Based on the effective interval of linear sensitivity of the current initial operating condition, during the iteration process, the control range of the control variable SVG is limited by the maximum adjustment amount ΔQ per iteration. ad The limitation of can ensure that the solution remains within the valid domain of the linearized model.

[0135] (8) Based on the calculation of the physical quantities in steps (3) to (7), a linear optimization model of the dynamic reactive power demand of the wind farm to maintain voltage stability is established.

[0136] (9) A linear programming method is used to solve the linear optimization model of step (8), and a set of wind farm SVG optimization solutions ΔQ are obtained, and the SVG reactive power adjustment amount Q=Q based on the current initial operating conditions is obtained. 0 +ΔQ is the dynamic reactive energy that SVG should reserve.

[0137] (10) Jump to step (2) and use PSD software to perform time domain simulation to verify the voltage instability after the wind farm SVG dynamic reactive reserve adjustment and the continuous fault ride-through of the wind farm.

[0138] The step (1):

[0139] Modeling highlights include:

[0140] 1. Establish an equivalent aggregation model for each wind farm, including wind turbines, on-site cables, step-up transformers, and supporting SVGs.

[0141] According to the wind conditions, internal wiring, unit type, converter control and other conditions of the wind farm, multiple wind turbines in the field are aggregated. For a typical 300MW wind farm with a total of 48 wind turbines with a single unit capacity of 6.25MW, they are generally aggregated into 2-4 equivalent wind turbines, and the equivalent wind turbine capacity is a multiple of a single wind turbine. The transient model of the aggregated wind turbine uses typical types of wind turbines, typical converter control models, structures and parameters; in addition to wind turbines, wind farm access modeling also includes modeling of wind power unit transformers, internal cables, grid-connected step-up transformers, supporting SVGs and grid-connected lines; according to the impact of wind farm group aggregation, access and transmission, the main grid is modeled in detail or simplified. Generally, the regional power grid to which the wind farm group is connected needs detailed modeling, and other main grids outside the regional power grid can be modeled equivalently and simplified according to the situation.

[0142] 2. Carry out modeling of low-voltage fault ride-through control / protection for wind turbines.

[0143] PSD software is used to establish a wind turbine transient model containing multiple control function modules. The structure of the wind turbine transient model is as follows: Figure 3 As shown, the details are as follows, where the wind turbine fault ride-through control related models are: WEV, WLP, and WLQ.

[0144] WDF, WFC models——doubly fed, direct drive generator models;

[0145] WES model - converter current control and limiting model;

[0146] WEV model——fault-through state judgment model;

[0147] WLP model——active power control model under fault ride-through state;

[0148] WLQ model - reactive power control model under fault ride-through state;

[0149] WME model – axis system model;

[0150] WTG model – wind power model;

[0151] WGF model——pitch angle control model;

[0152] WEP model - active power control model under normal operating conditions, such as Figure 4a As shown;

[0153] WEQ model - reactive power control model under normal operating conditions, such as Figure 4b shown.

[0154] The RE model of PSD simulation software is used to simulate the low-voltage fault ride-through protection of wind turbines. The main parameters of the RE model are filled in according to the envelope formed by the action voltage threshold of the low-voltage protection and the inverse time delay of the action. The typical envelope is as follows: Figure 5 As shown.

[0155] The envelope is discretized, and the two parameters of the action voltage threshold and the action delay time corresponding to each discrete point are filled into the RE model.

[0156] 3. Establish the SVG constant voltage response control strategy model for each wind farm in the wind farm group.

[0157] The constant voltage response control model of wind farm SVG is simulated based on the VG and VG+ models of PSD simulation software.

[0158] SVG model structure, such as Figure 6As shown, the specific parameters are as follows:

[0159] BNAME, the name of the node connected to the system;

[0160] BASE, the reference voltage of the node connected to the system (kV);

[0161] MVABASE, rated capacity (MVA);

[0162] T 1V , time constant of constant voltage control filter and measurement circuit (seconds);

[0163] T 2V , constant voltage control first stage leading time constant (seconds);

[0164] T 3V , constant voltage control first stage hysteresis time constant (seconds);

[0165] T 4V , constant voltage control second stage leading time constant (seconds);

[0166] T 5V , constant voltage control second stage hysteresis time constant (seconds);

[0167] T PV , constant voltage control proportional link time constant (seconds);

[0168] T SV , constant voltage control STATCOM response delay (seconds);

[0169] K PV , constant voltage control proportional link magnification;

[0170] K IV , the magnification of the constant voltage control integral link;

[0171] K D , the slope of the VI characteristic curve of SVG must be greater than or equal to 0;

[0172] REF_BNAME, control node name;

[0173] BASE, control node reference voltage;

[0174] V MAX , the upper limit of the voltage limiting link (pu);

[0175] V MIN , the lower limit of the voltage limiting link (pu);

[0176] I CMAX , maximum capacitive current (pu, based on SVG rated capacity);

[0177] I LMAX , maximum inductive current (pu, based on SVG rated capacity);

[0178] The step (2):

[0179] Run the PSD simulation software to perform transient simulation of the fault and output the simulation curves of the following key physical quantities and key event information:

[0180] Wind turbine terminal voltage simulation curve;

[0181] Wind turbine active power and reactive power simulation curves;

[0182] Grid connection point bus voltage simulation curve;

[0183] Active power and reactive power simulation curves of grid-connected lines;

[0184] The simulation curve of the hub bus voltage in the area where the wind farm group is connected;

[0185] Event information of low-voltage fault ride-through control and protection action of wind turbines.

[0186] According to the simulation curve and event information, the establishment characteristics of the reactive voltage operating balance point and voltage stability characteristics of the wind turbine are analyzed, and it is evaluated whether voltage instability and continuous fault ride-through of the wind farm occur.

[0187] The step (3):

[0188] Based on the initial reactive value Q of wind farm SVG 0 , the initial voltage value of the main grid node and wind power node V 0 , the sensitivity of the voltage of the main grid node and wind power node to the reactive power output of the wind farm SVG is calculated by the perturbation method. The reactive power of the wind farm SVG is adjusted with a smaller step size ΔQ, which is tentatively set to 5Mvar in the present invention. The transient simulation is carried out using PSD software, and the voltage curve of the main grid and wind turbine node under the fault disturbance after the SVG reactive power is adjusted ΔQ is simulated and output. The change ΔV of each node voltage is calculated from the simulation curve, and the sensitivity of each node voltage to the reactive power output of the wind farm SVG is:

[0189] S vq =ΔV·(ΔQ) -1

[0190] The step (8):

[0191] In each iteration, the following linear optimization model of wind farm dynamic reactive capacity demand is established:

[0192] Objective function:

[0193]

[0194] The following constraints are met:

[0195] S vq ·(ΔQ + -ΔQ - )≤V max -V 0 (2)

[0196] S vq ·(ΔQ + -ΔQ - )≥V min -V 0 (3)

[0197]

[0198] Where, the reactive adjustment of the j-th wind farm SVG in this iteration is They are the reactive adjustment value ΔQ of the control variable SVG j Positive and negative adjustment of the objective function In order to maintain voltage stability after a fault and minimize the dynamic reactive power demand of SVG for preventing and controlling continuous fault ride-through of wind farms; in the constraint, S vq is the sensitivity matrix of the grid node voltage to the dynamic reactive power output of the wind farm SVG; the change in the dynamic reactive power of each wind farm SVG ΔQ=ΔQ + -ΔQ - , V max 、V min They are the upper and lower limit vectors of the node voltage threshold (upper limit is 1.1pu and lower limit is 0.9pu) to maintain voltage stability and prevent wind power from continuously crossing. 0 is the initial node voltage of this iteration, S vq ΔQ is the voltage change ΔV after SVG reactive power regulation at the current operating point. Constraints (2) and (3) indicate that controlling the voltage after the fault within the upper and lower limits can avoid voltage instability and continuous wind power fault ride-through problems. Constraints (4) and (5) indicate the initial reactive power Q of the SVG at the jth wind farm in this iteration. j，0 The capacity can be adjusted based on the SVG capacity. The adjustment amount cannot exceed the upper and lower limits of the SVG capacity. The present invention adopts the method of equivalently treating the nonlinear optimization model as a sequential linear programming model. Since a linear sensitivity model is established in each iteration, the effective interval of the linear sensitivity should be considered. In each iteration, the control range is limited to the control variable to ensure that the solution is maintained within the effective domain of the linearized model. For the adjustment of the reactive power of the wind farm SVG, constraints (6) and (7) must be satisfied. In the formula, ΔQ adIt is the set maximum adjustment amount of SVG. The present invention takes 5Mvar. After adopting this strategy, the adjustment amount of each iteration can be made not too large and far exceeds its linear effective range.

[0199] The main effects of the present invention are as follows: 1) A dynamic reactive capacity demand optimization model of SVG in wind farms for establishing reactive voltage balance points under fault disturbances, maintaining voltage stability, and preventing and controlling continuous fault crossing is proposed, and a model solution method is given: Based on the sensitivity method, the nonlinear optimization model of SVG dynamic reactive capacity is equivalently processed as a sequential linear optimization model, and the equivalent linear optimization model is modeled, and the linear programming method is used for solution to obtain the minimum dynamic reactive capacity demand of SVG. 2) Optimize the SVG capacity for maintaining voltage stability and preventing and controlling continuous fault crossing of wind power, and optimize its allocation in each wind farm SVG: The optimal capacity of SVG dynamic reactive demand for maintaining voltage stability and preventing and controlling continuous fault crossing of wind power can be given, and the total dynamic demand capacity of SVG can be optimized in each wind farm according to multi-dimensional factors such as the current initial operating state of SVG, the upper and lower limits of SVG reactive power, and the contribution of SVG to maintaining voltage stability.

[0200] The following takes the access of a certain wind farm group to the power grid as an example to further describe the specific implementation mode of the present invention in detail.

[0201] The schematic diagram of the grid structure of wind farm groups connected to the power grid is as follows Figure 7As shown, the installed capacity of mqf and hnf wind farms are 200MW respectively, and the installed capacity of hlf and dlf wind farms are 300MW respectively. The total installed capacity of this wind farm group is 1000MW; the capacity of a single wind turbine is 6.25MW, so there are 32 wind turbines in the 200MW wind farm and 48 wind turbines in the 300MW wind farm. The wind turbines in each wind farm are boosted to 35kV through unit transformers. The 35kV medium-voltage cables are collected and connected to the 35 / 220kV booster stations mq, hn, hl, and dl in each wind farm, boosted to 220kV and connected to the power grid. The mqf and hnf wind farms are each equipped with two SVGs with a single capacity of 18Mvar on the 35kV side of their respective booster transformers mq and hn. The total amount of SVG in each farm is 36Mvar, and the upper and lower limits of SVG reactive capacity are 36Mvar and -36Mvar respectively; the hlf and dlf wind farms are each equipped with two SVGs with a single capacity of 23Mvar on the 35kV side of their respective booster transformers hl and dl. The total amount of SVG in each farm is 46Mvar, and the upper and lower limits of SVG reactive capacity are 46Mvar and -46Mvar respectively. The upper and lower limits of the reactive power output of the wind farm can be set according to the power factor of the wind farm rated active power, which is 0.95 leading to 0.95 lagging. The upper and lower limits of the reactive power of the mqf and hnf wind farms are 66Mvar and -66Mvar respectively; the upper and lower limits of the reactive power of the hlf and dlf wind farms are 99Mvar and -99Mvar respectively. After part of the wind power is consumed by the local load, the remaining power is sent through the 500kV substation mld. The power source connected to the mld substation does not have a thermal power plant, but only 1000MW wind power.

[0202] Based on the typical access mode of wind farm group, the research is carried out. The grid-related active power, reactive power flow and bus voltage are shown in the figure: (1) The active power flow is as follows. Each wind farm in the wind farm group operates at full capacity according to the installed capacity. The mqf wind farm is 200MW, the hlf wind farm is 300MW, the dlf wind farm is 300MW, and the hnf wind farm is 200MW. The total wind power output of the wind farm group is 1000MW. After a part of the local 220kV load is consumed, the remaining wind power of about 594MW is sent through the 500kV substation mld. The 220kV power stations with larger load power are: arq station is 99.8MW, ay station is 37.8MW, tjb station is 15MW, hzx station is 89.3MW, and mgq station is 31.5MW. (2) The reactive voltage situation is as follows: The bus voltage in the wind power grid-connected area is controlled by adjusting the reactive output of the wind turbines in the four wind farms mqf, hlf, dlf, and hnf. The reactive output of the SVG configured in the 220kV booster stations mq, hl, dl, and hn is 0 Mvar respectively. The main grid bus voltage is controlled within the range of 97% to 107% of the nominal voltage of 220kV, that is, 213.4 to 235.4kV, of which mq is 216.8kV, hl is 217.6kV, and dl is 217.6kV. kV and hn are 218.7kV; the terminal voltage of each wind farm is expressed in per-unit value, and generally the terminal voltage is controlled in the range of 0.9-1.1, among which mqf is 0.941pu, hlf is 0.937pu, dlf is 0.937pu, and hnf is 0.947pu. After regulation, the initial value of the terminal voltage amplitude is set lower. Under this condition, the optimized dynamic reactive power demand of SVG may be larger, which can adapt to fault disturbances under conditions with higher initial voltage amplitude and has better adaptability.

[0203] The specific implementation includes the following steps:

[0204] Based on the grid structure and arrangement of the above-mentioned wind farm group access to the power grid, steady-state and transient modeling of the wind farm group access is carried out to form the data files required for calculation and analysis.

[0205] A typical fault set of the near-area power grid after wind power access is established for the establishment of reactive voltage balance points and the risk assessment of voltage stability and continuous fault ride-through. Combined with this specific example, the fault set mainly includes the three-way N-1 and N-2 typical faults of the wind farm group near the grid, such as the three-way N-1 of the 220kV line arq-ml, arq-tjb, arq-ay, ay-mld, mld-tjb, mld-mgq, and the three-way N-1 of the 500kV line mld-mxl and mld-hft; such as the three-way N-2 of the 220kV double-circuit line arq-ml, mld-tjb, and the three-way N-2 of the 500kV double-circuit line mld-hft and mld-mxl. Among them, the fault breaking time of the 220kV line is 6 cycles; the fault breaking time of the 500kV line is 5 cycles.

[0206] Based on PSD simulation software, the RE model is used to simulate the low-voltage fault ride-through protection function of wind turbines, taking the mqf wind farm as an example:

[0207] REmqf .8 0.9 100.0.7 80.0.5 61.0.35 46.0.2 31.

[0208] RE+mqf .8 0.1990.

[0209] The inverse time envelope of the low voltage ride through protection is discretized and simulated with voltage thresholds of 0.9pu, 0.7pu, 0.5pu, 0.35pu, 0.2pu and 0.199pu and corresponding durations of 100 cycles, 80 cycles, 61 cycles, 46 cycles, 31 cycles and 0 cycle respectively, to realize the following low voltage ride through protection functions: 1) When the wind power voltage drops to 0.2pu, the wind turbine generator set shall ensure continuous operation for 625ms (31 cycles) without disconnection from the grid; 2) When the wind power voltage is lower than 0.2pu, the wind turbine generator set can be disconnected from the grid without delay; 3) When the wind power voltage can recover to 0.9pu within 2s after the voltage drops, the wind turbine generator set shall ensure continuous operation without disconnection from the grid.

[0210] Based on PSD simulation software, WEV, WLP and WLQ models are used to simulate the judgment of low-voltage penetration state, active power control under low-voltage penetration state and reactive power control under low-voltage penetration state. The mqf wind farm is still taken as an example:

[0211] WEV mq.800 000.9 0.91 0.01

[0212] WLP mq.800 L 12.94150.29 0.359310.17

[0213] WLQ mq.800L 21.9761 0.2 0.9 0 0

[0214] WEV judges that the voltage type of low-breakthrough is positive sequence voltage; the voltage value for entering the low-breakthrough state is 0.9pu, the voltage value for exiting the low-breakthrough state is 0.91pu, and the low-breakthrough judgment time is 0.01 cycle.

[0215] The "L" mark in WLP represents the active power control strategy during the low-voltage ride-through period. The active power ride-through control adopts a three-stage simulation method: ① Stage, the control method during the ride-through period, select the control method of the specified active current, and the active current formula is: IP ref =K v ×V t +K I ×IP 0 +IP set , where IP 0 is the initial active current, V t is the voltage amplitude at the machine end, and the coefficient K v is 0.9415, K I 0.29, IP set The set active current constant coefficient is 0.359; Section ②, the recovery starting point uses the active power during the fault period; Section ③, the recovery process control mode selects the specified slope recovery, and the slope is 0.17pu / s.

[0216] The "L" in WLQ represents the reactive power control strategy during low-voltage ride-through. Reactive power ride-through control adopts a three-stage simulation method: ① Stage, the control method during ride-through, select the specified reactive current control method, the reactive current formula is: IQ ref =K v ×(V set -V t )+K I ×IQ 0 +IQ set , where IQ 0 is the initial reactive current, V t is the voltage amplitude at the machine end, and the coefficient K v is 1.976, K I =1, IQ set The reactive current constant coefficient is set to 0.2, V set is 0.9pu; the recovery starting point control mode and recovery process control mode of sections ② and ③ are both selected as no control, that is: recovery to the initial reactive current without delay.

[0217] Based on PSD simulation software, VG and VG+ models are used to simulate the SVG constant voltage control strategy model of the wind farm, still taking the mqf wind farm as an example:

[0218] VGQmqf_s1 35..0080 0 0 0.01.01 0.20.1.2-1.2

[0219] The mqf wind farm is equipped with two 18Mvar SVGs, each of which is connected to the 35kV bus mqf_s1 of the wind farm booster station. The time constant of the filter and measurement circuit is 0.008 seconds, the time constant of the control proportional link is 0.01s, the STATCOM response delay is 0.01s, the amplification factor of the integral link is 20, the upper and lower limits of the reactive power limiting link are 1.2 and -1.2 respectively, and other parameters are set to 0.

[0220] Based on the PSD simulation software, an assessment is conducted on the risk of voltage instability and continuous fault ride-through when a wind farm group cannot establish a dynamic reactive voltage balance point under typical fault conditions.

[0221] The 500kV double-circuit line mld-hft Sanyong N-2 is used as an example for risk assessment. Since the initial reactive power of SVG is 0Mvar, the dynamic reactive power support during the fault disturbance is 0Mvar. If the dynamic reactive power support is insufficient, the reactive voltage balance point cannot be established, and the wind power continues to have low voltage and cannot be restored. The medium- and long-term voltage stability problem further triggers the low-voltage action of the wind turbine. The wind turbine frequently enters and exits the low-voltage action, causing the active power and reactive power of the wind power to oscillate, affecting the safe and stable operation of the main grid. The simulation results are as follows: Figure 8-11 As shown;

[0222] A dynamic reactive capacity demand optimization model of wind farm SVG is established and solved to maintain the reactive voltage balance point and prevent and control voltage instability and continuous fault ride-through problems.

[0223] The parameters in the optimization models (1) to (7) are as follows:

[0224] The initial reactive power of wind turbines in mqf, hlf, dlf and hnf wind farms is 34Mvar, 34Mvar, 34Mvar and 28Mvar respectively. The initial reactive power of SVG in each wind farm is 0Mvar. The initial value of bus voltage is shown in " Figure 7 Schematic diagram of power flow distribution of wind farm groups connected to the power grid and wind farms at full output.

[0225] At the initial operating point, based on the simulation output of the PSD software, the perturbation method is used to obtain the reactive adjustment sensitivity S of the SVG vq Based on the sensitivity of wind turbine terminal voltage to SVG reactive power, the reactive power of SVG is adjusted according to the step size ΔQ of 5Mvar. Based on the simulation output of PSD software, the wind turbine terminal voltage simulation curve after the reactive power of SVG is changed ΔQ under fault disturbance is obtained, and the change of terminal voltage ΔV is calculated. The reactive voltage sensitivity S of SVG is calculated by perturbation method. vq, as shown in the following table:

[0226] Table 1

[0227] <![CDATA[Sensitivity S w vq > <![CDATA[△Q mqf ]]> <![CDATA[△Q hlf > <![CDATA[△Q dlf > <![CDATA[△Q hnf ]]> <![CDATA[△V w,mqf ]]> 0.88 0.71 0.72 0.65 <![CDATA[△V w,hlf ]]> 0.71 0.81 0.71 0.64 <![CDATA[△V w,dlf ]]> 0.72 0.71 0.82 0.65 <![CDATA[△V w,hnf ]]> 0.62 0.61 0.61 0.67

[0228] V max 、V min They are the upper and lower limit vectors of the node voltage threshold (upper limit is 1.1pu and lower limit is 0.9pu) to maintain voltage stability and prevent wind power from continuously crossing. min and Q max They are the reactive lower and upper limit vectors of the wind farm SVG. The upper and lower limits of the reactive capacity of the SVG for mqf and hnf wind farms are 36Mvar and -36Mvar respectively; the upper and lower limits of the reactive capacity of the SVG for hlf and dlf wind farms are 46Mvar and -46Mvar respectively.

[0229] Substitute the above parameters into the optimization model (1) to (7), and use the linear programming method to solve the sequential linear optimization model to obtain the SVG dynamic reactive adjustment optimization solution ΔQ. Let Q+ΔQ update the SVG reactive power, and perform fault disturbance simulation under the support of this SVG dynamic reactive power. According to the voltage curve, wind power low-through control and protection action and other information, the establishment of the wind farm reactive power voltage balance point and the evaluation of voltage stability and continuous fault ride-through problems are carried out. If the wind power reactive power voltage balance point cannot be established and voltage instability and continuous fault ride-through still occur, the latest SVG dynamic reactive power and the latest wind turbine terminal voltage in the iteration are used as the initial values ​​to further calculate the sensitivity S vq , the sensitivity is brought into and the optimization model (1)~(7) is established, and then ΔQ is further solved, and the cycle is iterated until the optimal adjustment amount ΔQ of SVG and the dynamic reactive amount Q+ΔQ that SVG should reserve are obtained, so as to achieve the optimization goals of establishing reactive voltage balance point, maintaining voltage stability, preventing and controlling continuous fault ride-through, etc.

[0230] Table 2

[0231]

[0232] Under the optimal dynamic reactive capacity reserved by SVG of each wind farm, the same 500kV double-circuit line mld-hft Sanyong N-2 fault simulation analysis is carried out. Figure 12-15 The simulation results shown show that:

[0233] After the fault, SVG used almost all of its reserved dynamic reactive power, providing sufficient dynamic reactive power support in a timely manner.

[0234] With the support of SVG dynamic reactive power, the reactive voltage balance point of the wind farm after the fault disturbance was established, and the unit voltage could be maintained in the range of 0.92 to 0.94 pu, ensuring the voltage stability of wind power grid-connected, and the wind turbines did not have the problem of continuous fault ride-through.

[0235] Embodiment 2:

[0236] The present invention also proposes a wind farm group dynamic reactive capacity demand calculation system 200 for maintaining voltage stability, such as Fig.16 As shown, including:

[0237] The time domain simulation unit 201 is used to establish a steady-state and transient model of the wind farm group connected to the main grid for the wind farm group, perform a time domain simulation of the grid fault based on the steady-state and transient models, and obtain the time domain simulation result. If the wind power grid-connected voltage is stable and there is no continuous fault crossing in the time domain simulation result, the time domain simulation is terminated to obtain the final wind farm dynamic reactive demand optimization solution. Otherwise, the current wind farm SVG reactive capacity and the node voltage state quantity under the corresponding fault disturbance are used as the initial value of a new cycle iteration;

[0238] The calculation unit 202 is used to calculate a plurality of target physical quantities based on the time domain simulation result for one cycle iteration, and to establish a linear optimization model of the dynamic reactive power demand of the wind farm for maintaining voltage stability based on the plurality of target physical quantities;

[0239] A solving unit 203 is used to solve the linear optimization model and determine an optimized solution for the dynamic reactive capacity demand of the wind farm group in this iteration based on the solving result;

[0240] Based on the optimized solution of the dynamic reactive capacity demand of the wind farm group under this iteration, the time domain simulation is performed to judge the voltage stability and fault ride-through problems under the new SVG dynamic reactive capacity demand. If the voltage is unstable and continuous fault ride-through problems occur, the linear optimization model is established and solved in a cyclic iteration until the voltage is stable and there is no continuous fault ride-through, and the final optimized solution for the dynamic reactive capacity demand of the wind farm is obtained.

[0241] Among them, the steady-state and transient models of wind farm groups connected to the main grid are established, including:

[0242] Equivalent aggregation model of each wind farm in the wind farm group, low-voltage fault ride-through control / protection model of wind turbines, and SVG constant voltage response control strategy model of each wind farm in the wind farm group.

[0243] Among them, based on the PSD simulation software, a steady-state and transient model of the wind farm group connected to the main grid is established, and based on the PSD simulation software, a time domain simulation of the power grid fault is performed according to the steady-state and transient models.

[0244] Among them, the time domain simulation results include: wind turbine terminal voltage simulation curve, wind turbine active power / reactive power simulation curve, grid-connected point bus voltage simulation curve, grid-connected line active power / reactive power simulation curve, wind farm group access area hub bus voltage simulation curve and wind turbine low-voltage fault ride-through control / protection action event information.

[0245] Among them, multiple target physical quantities include: the sensitivity matrix of the grid node voltage to the dynamic reactive output of the wind farm SVG, the reactive adjustment amount ΔQ of the control variable SVG j The positive / negative adjustment amount of SVG, the node voltage after the reactive power adjustment ΔQ of SVG and the limitation of the ΔQ control range of the control variable SVG are imposed.

[0246] Wherein, based on the time domain simulation results, multiple target physical quantities are calculated, including:

[0247] For the basic operating conditions under voltage instability / continuous fault ride-through problems, the sensitivity matrix S of the grid node voltage to the dynamic reactive power output of the wind farm SVG is calculated. vq ;

[0248] Under the basic operating conditions, the reactive adjustment amount of the j-th wind farm SVG in the wind farm group is defined as follows:

[0249]

[0250] in:

[0251]

[0252] in, They are the reactive adjustment value ΔQ of the control variable SVG j The positive and negative adjustment amount,

[0253] Among them, Q j,0 is the current reactive power of the j-th wind farm SVG, is the upper limit of the reactive capacity of the SVG of the jth wind farm, is the lower limit of SVG reactive capacity of the jth wind farm;

[0254] The node basic operating voltage V under fault 0 Under this condition, the node voltage after SVG reactive power adjustment ΔQ is calculated, and the calculation formula is as follows:

[0255] V=V 0 +S vq ·(ΔQ + -ΔQ - );

[0256] Based on the effective interval of the linear sensitivity of the basic operating condition, a control range limitation is imposed on ΔQ of the control variable SVG.

[0257] The perturbation method is used to calculate the sensitivity of the voltage of the main grid node and wind power node to the reactive power output of the wind farm SVG. Based on the initial reactive power value Q 0 , the initial voltage value of the main grid node and wind power node V 0 , the wind farm SVG reactive power is adjusted with a small step size ΔQ, and the transient time domain simulation is performed using PSD software. The simulation outputs the voltage curves of the main grid and wind turbine nodes under fault disturbance after the SVG reactive power is adjusted ΔQ. The change in voltage of each node ΔV is calculated from the simulation curve. Therefore, S vq The calculation formula is as follows:

[0258] S vq =ΔV·(ΔQ) -1

[0259] Wherein, ΔV is the voltage change.

[0260] Optionally, the objective function and constraints of the linear optimization model are as follows:

[0261] Objective function:

[0262]

[0263] Constraints:

[0264] S vq ·(ΔQ + -ΔQ - )≤V max -V 0

[0265] S vq ·(ΔQ + -Δq - )≥V min -V 0

[0266]

[0267] in, They are the reactive adjustment value ΔQ of the control variable SVG j The positive and negative adjustment amount, S vq is the sensitivity matrix of the grid node voltage to the dynamic reactive power output of the wind farm SVG, and the change in the dynamic reactive power of each wind farm SVG is ΔQ = ΔQ + -ΔQ - , V max 、V minare the node voltage threshold upper and lower limit vectors for maintaining voltage stability / preventing wind power from continuous crossing, V 0 is the initial node voltage of this iteration, Q j,0 is the current reactive power of the j-th wind farm SVG, is the upper limit of the reactive capacity of the SVG of the jth wind farm, is the lower limit of the reactive capacity of the SVG of the jth wind farm, ΔQ ad Maximum adjustment amount for the SVG reactive power for this iteration.

[0268] The present invention can achieve the goals of improving the voltage stability of wind power grid-connected under fault disturbances, preventing and controlling the risk of continuous fault crossing in wind power, etc., thereby promoting the acceptance of new energy and improving the safety of the power grid.

[0269] Embodiment 3:

[0270] Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, wherein 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. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding functions, so as to implement the steps of the method in the above embodiment.

[0271] Embodiment 4:

[0272] Based on the same inventive concept, the present invention also provides a storage medium, 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 can include both a built-in storage medium in a computer device and 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 can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiment.

[0273] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0274] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks 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 produce 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.

[0275] 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 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0276] 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 The steps for the functions specified in one or more boxes.

[0277] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0278] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for calculating the dynamic reactive capacity demand of a wind farm to maintain voltage stability, characterized in that: include: For the wind farm group, a steady-state and transient model of the wind farm group connected to the main grid is established. Based on the steady-state and transient models, a time-domain simulation of the power grid fault is performed, and the time-domain simulation results are obtained. If the wind power grid-connected voltage is stable and there is no continuous fault crossing in the time-domain simulation results, the time-domain simulation is terminated to obtain the final wind farm dynamic reactive demand optimization solution. Otherwise, the current wind farm SVG reactive capacity and the node voltage state quantity under the corresponding fault disturbance are used as the initial value of a new cycle iteration; For one cycle iteration, a plurality of target physical quantities are calculated based on the time domain simulation results, and a linear optimization model of dynamic reactive power demand of the wind farm for maintaining voltage stability is established based on the plurality of target physical quantities; Solving the linear optimization model, and determining an optimal solution for the dynamic reactive capacity demand of the wind farm group in this iteration based on the solution result; Based on the optimized solution of the dynamic reactive capacity demand of the wind farm group under this iteration, the time domain simulation is performed to judge the voltage stability and fault ride-through problems under the new SVG dynamic reactive capacity demand. If the voltage is unstable and continuous fault ride-through problems occur, the linear optimization model is established and solved in a cyclic iteration until the voltage is stable and there is no continuous fault ride-through, and the final optimized solution for the dynamic reactive capacity demand of the wind farm is obtained.

2. The method according to claim 1, characterized in that The establishment of a steady-state and transient model of a wind farm group connected to a main grid includes: Equivalent aggregation model of each wind farm in the wind farm group, low-voltage fault ride-through control / protection model of wind turbines, and SVG constant voltage response control strategy model of each wind farm in the wind farm group.

3. The method according to claim 1, characterized in that Based on the PSD simulation software, a steady-state and transient model of the wind farm group connected to the main grid is established, and based on the PSD simulation software, a time domain simulation of the power grid fault is performed according to the steady-state and transient models.

4. The method according to claim 1, characterized in that The time domain simulation results include: wind turbine terminal voltage simulation curve, wind turbine active power / reactive power simulation curve, grid-connected point bus voltage simulation curve, grid-connected line active power / reactive power simulation curve, wind farm group access area hub bus voltage simulation curve and wind turbine low-voltage fault ride-through control / protection action event information.

5. The method according to claim 1, characterized in that The multiple target physical quantities include: the sensitivity matrix of the grid node voltage to the dynamic reactive output of the wind farm SVG, the reactive adjustment value ΔQ of the control variable SVG j The positive / negative adjustment amount of SVG, the node voltage after the reactive power adjustment ΔQ of SVG and the limitation of the ΔQ control range of the control variable SVG are imposed.

6. The method according to claim 1, characterized in that The method further comprises calculating a plurality of target physical quantities based on the time domain simulation results, including: For the basic operating conditions under voltage instability / continuous fault ride-through problems, the sensitivity matrix S of the grid node voltage to the dynamic reactive power output of the wind farm SVG is calculated. vq ; Under the basic operating conditions, the reactive adjustment amount of the j-th wind farm SVG in the wind farm group is defined as follows: in: in, They are the reactive adjustment value ΔQ of the control variable SVG j The positive and negative adjustment amount, Among them, Q j,0 is the current reactive power of the j-th wind farm SVG, is the upper limit of the reactive capacity of the SVG of the jth wind farm, is the lower limit of SVG reactive capacity of the jth wind farm; Under the basic operating voltage V0 of the node under fault conditions, the node voltage after SVG reactive power adjustment ΔQ is calculated. The calculation formula is as follows: V=V0+S vq ·(ΔQ + -ΔQ - ); Based on the effective interval of the linear sensitivity of the basic operating condition, a control range limitation is imposed on ΔQ of the control variable SVG.

7. The method according to claim 6, characterized in that: The perturbation method is used to calculate the sensitivity of the voltage of the main grid node and wind power node to the reactive power output of the wind farm SVG. Based on the initial reactive value Q0 of the wind farm SVG and the initial voltage value V0 of the main grid node and wind power node, the reactive power of the wind farm SVG is adjusted with a small step size ΔQ. The transient time domain simulation is performed using PSD software. The simulation outputs the voltage curve of the main grid and wind turbine node under the fault disturbance after the SVG reactive amount is adjusted ΔQ. The change ΔV of the voltage of each node is calculated from the simulation curve. Therefore, S vq The calculation formula is as follows: S vq =ΔV·(ΔQ) -1 Wherein, ΔV is the voltage change.

8. The method according to claim 1, characterized in that The objective function and constraints of the linear optimization model are as follows: Objective function: Constraints: S vq ·(ΔQ + -ΔQ - )≤V max -V0 S vq ·(ΔQ + -ΔQ - )≥V min -V0 in, They are the reactive adjustment value ΔQ of the control variable SVG j The positive and negative adjustment amount, S vq is the sensitivity matrix of the grid node voltage to the dynamic reactive power output of the wind farm SVG, and the change in the dynamic reactive power of each wind farm SVG is ΔQ = ΔQ + -ΔQ - , V max 、V min are the upper and lower limit vectors of the node voltage threshold for maintaining voltage stability / preventing continuous wind power crossing, V0 is the initial node voltage of this iteration, Q j,0 is the current reactive power of the j-th wind farm SVG, is the upper limit of the reactive capacity of the SVG of the jth wind farm, is the lower limit of the reactive capacity of the SVG of the jth wind farm, ΔQ ad Maximum adjustment amount for the SVG reactive power for this iteration.

9. A wind farm group dynamic reactive capacity demand calculation system for maintaining voltage stability, characterized in that: include: The time domain simulation unit is used to establish a steady-state and transient model of the wind farm group connected to the main grid for the wind farm group, perform a time domain simulation of the power grid fault based on the steady-state and transient models, and obtain the time domain simulation results. If the wind power grid-connected voltage is stable and there is no continuous fault crossing in the time domain simulation results, the time domain simulation is terminated to obtain the final wind farm dynamic reactive demand optimization solution. Otherwise, the current wind farm SVG reactive capacity and the node voltage state quantity under the corresponding fault disturbance are used as the initial value of a new cycle iteration; A calculation unit, configured to calculate a plurality of target physical quantities based on the time domain simulation result for one cycle iteration, and to establish a linear optimization model of a dynamic reactive power demand of a wind farm for maintaining voltage stability based on the plurality of target physical quantities; A solving unit, used for solving the linear optimization model, and determining an optimized solution for the dynamic reactive capacity demand of the wind farm group in this iteration based on the solving result; Based on the optimized solution of the dynamic reactive capacity demand of the wind farm group under this iteration, the time domain simulation is performed to judge the voltage stability and fault ride-through problems under the new SVG dynamic reactive capacity demand. If the voltage is unstable and continuous fault ride-through problems occur, the linear optimization model is established and solved in a cyclic iteration until the voltage is stable and there is no continuous fault ride-through, and the final optimized solution for the dynamic reactive capacity demand of the wind farm is obtained.

10. The system according to claim 9, characterized in that The establishment of a steady-state and transient model of a wind farm group connected to a main grid includes: Equivalent aggregation model of each wind farm in the wind farm group, low-voltage fault ride-through control / protection model of wind turbines, and SVG constant voltage response control strategy model of each wind farm in the wind farm group.

11. The system according to claim 9, characterized in that Based on the PSD simulation software, a steady-state and transient model of the wind farm group connected to the main grid is established, and based on the PSD simulation software, a time domain simulation of the power grid fault is performed according to the steady-state and transient models.

12. The system according to claim 9, characterized in that The time domain simulation results include: wind turbine terminal voltage simulation curve, wind turbine active power / reactive power simulation curve, grid-connected point bus voltage simulation curve, grid-connected line active power / reactive power simulation curve, wind farm group access area hub bus voltage simulation curve and wind turbine low-voltage fault ride-through control / protection action event information.

13. The system according to claim 9, characterized in that The multiple target physical quantities include: the sensitivity matrix of the grid node voltage to the dynamic reactive output of the wind farm SVG, the reactive adjustment value ΔQ of the control variable SVG j The positive / negative adjustment amount of SVG, the node voltage after the reactive power adjustment ΔQ of SVG and the limitation of the ΔQ control range of the control variable SVG are imposed.

14. The system according to claim 9, characterized in that The method further comprises calculating a plurality of target physical quantities based on the time domain simulation results, including: For the basic operating conditions under voltage instability / continuous fault ride-through problems, the sensitivity matrix S of the grid node voltage to the dynamic reactive power output of the wind farm SVG is calculated. vq ; Under the basic operating conditions, the reactive adjustment amount of the j-th wind farm SVG in the wind farm group is defined as follows: in: in, They are the reactive adjustment value ΔQ of the control variable SVG j The positive and negative adjustment amount, Among them, Q j,0 is the current reactive power of the j-th wind farm SVG, is the upper limit of the reactive capacity of the SVG of the jth wind farm, is the lower limit of SVG reactive capacity of the jth wind farm; Under the basic operating voltage V0 of the node under fault conditions, the node voltage after SVG reactive power adjustment ΔQ is calculated. The calculation formula is as follows: V=V0+S vq ·(ΔQ + -ΔQ - ); Based on the effective interval of the linear sensitivity of the basic operating condition, a control range limitation is imposed on ΔQ of the control variable SVG.

15. The system according to claim 9, characterized in that The perturbation method is used to calculate the sensitivity of the voltage of the main grid node and wind power node to the reactive power output of the wind farm SVG. Based on the initial reactive value Q0 of the wind farm SVG and the initial voltage value V0 of the main grid node and wind power node, the reactive power of the wind farm SVG is adjusted with a small step size ΔQ. The transient time domain simulation is performed using PSD software. The simulation outputs the voltage curve of the main grid and wind turbine node under the fault disturbance after the SVG reactive amount is adjusted ΔQ. The change ΔV of the voltage of each node is calculated from the simulation curve. Therefore, S vq The calculation formula is as follows: S vq =ΔV·(ΔQ) -1 Wherein, ΔV is the voltage change.

16. The system according to claim 9, characterized in that The objective function and constraints of the linear optimization model are as follows: Objective function: Constraints: S vq ·(ΔQ + -ΔQ - )≤V max -V0 S vq ·(ΔQ + -ΔQ - )≥V min -V0 in, They are the reactive adjustment value ΔQ of the control variable SVG j The positive and negative adjustment amount, S vq is the sensitivity matrix of the grid node voltage to the dynamic reactive power output of the wind farm SVG, and the change in the dynamic reactive power of each wind farm SVG is ΔQ = ΔQ + -ΔQ - , V max 、V min are the upper and lower limit vectors of the node voltage threshold for maintaining voltage stability / preventing continuous wind power crossing, V0 is the initial node voltage of this iteration, Q j,0 is the current reactive power of the j-th wind farm SVG, is the upper limit of the reactive capacity of the SVG of the jth wind farm, is the lower limit of the reactive capacity of the SVG of the jth wind farm, ΔQ ad Maximum adjustment amount for the SVG reactive power for this iteration.

17. A computer device, characterized in that: include: one or more processors; a processor for executing one or more programs; When the one or more programs are executed by the one or more processors, the method according to any one of claims 1 to 8 is implemented.

18. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed, the method according to any one of claims 1 to 8 is implemented.

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