System and method for enhancing wind farm support capability to the grid during critical events

Abstract

The present application relates to a system and method for enhancing the support capability of a wind farm to a power grid during a critical event, which considers the wake effect of wind turbines, so that part of the wind farm operates in a maximum power mode or in an unloading mode according to load demand, optimizes the active power output of the wind farm while leaving a certain active power reserve margin. In the unloading mode, the wind farm is maximized in terms of reactive power capability, and the voltage support capability of the wind farm to the power grid is improved. The controller is assigned a reference value, which, while meeting the maximum reactive power capability of the wind farm, reduces the wear and tear of the mechanical device of the wind turbine during the pitch adjustment of the mode switching process. A controller parameter lookup table based on the maximum active power support of the grid guide and system constraints is generated, and the support capability of the wind farm to the grid frequency during voltage ride-through is improved. The present method is realized based on the controller parameter lookup table, so that for a specific wind farm, only one calculation is required to generate the controller parameter lookup table.

Description

Technical Field

[0001] This invention belongs to the field of active power output control technology for wind power generation, and relates to a method for wind farms to actively support grid voltage and frequency during faults, specifically a system and method to enhance the ability of wind farms to support the grid during critical events. Background Technology

[0002] As wind power penetration in the power grid continues to increase, improving the grid's capacity to accept wind power requires enhancing both the grid's regulation capabilities and the wind power's own regulation capabilities. The inherent frequency and voltage support capabilities of wind farms are a key characteristic of "grid-friendly" wind farms.

[0003] To improve the power output efficiency of wind farms, the maximum wind energy capture (MAV) scheme for individual turbines is commonly adopted. This involves adjusting the pitch angle and rotational speed of the wind turbines to achieve the optimal wind energy utilization coefficient, maximizing the wind energy captured by a single turbine. However, due to the wake effect, after the upwind turbines capture wind energy, the input wind speed of the downwind turbines decreases. If all wind turbines in a wind farm operate at maximum MAV, the upwind turbines will capture too much wind energy, resulting in a decrease in wind speed along the wake propagation direction, while the downwind turbines will suffer significant wind speed losses, making it difficult to maximize the power output efficiency of the wind farm. Therefore, it is necessary to coordinate the wind energy captured by each turbine to regulate the wake distribution within the wind farm, improve aerodynamic coupling between turbines, and ultimately improve wind energy utilization at the wind farm level.

[0004] Variable-speed wind turbines, the mainstream type in grid-connected wind farms, can adjust the active and reactive power output of the wind farm through converters, track the maximum power point trajectory, and improve wind energy utilization. However, to achieve maximum wind energy capture, the coupling relationship between the wind turbine speed and the grid frequency is no longer present, making the wind turbines unable to respond to grid frequency changes. To address wind farm participation in system frequency regulation, many countries are researching allowing some wind turbines to operate under reduced load. For example, Spain explicitly stipulates in its grid guidelines that wind turbines must have a 1.5% frequency reserve margin. The advantages of reduced load are: providing some reserve for the system without shutting down the turbines, saving investment costs for conventional equipment; and enabling real-time frequency response to the system, ensuring grid frequency stability.

[0005] In high-proportion renewable energy power systems, the ability of wind turbines to maintain operation and provide support to the system during grid faults is increasingly valued. Current research methods mainly focus on how wind turbines can provide reactive power output to support grid voltage during low-voltage ride-through (LVRT). However, since wind turbines typically employ reactive power priority control during LVRT, active power output is limited. Furthermore, after fault clearance, active power recovers at a relatively slow rate to avoid a sudden and significant increase in turbine load. Therefore, the system will be affected by a continuous and non-step active power deficit during this process, and the higher the penetration rate of wind turbines not participating in system frequency regulation, the more severe the frequency stability problem during LVRT becomes.

[0006] In summary, there is an urgent need for a new coordinated control method that optimizes wind energy utilization at the wind farm level and enhances the frequency support capability of wind turbines for the power grid during voltage ride-through. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the prior art and provide a system and method to enhance the grid support capability of wind farms during critical events.

[0008] The technical problem solved by this invention is achieved through the following technical solution:

[0009] A system for enhancing the grid support capability of wind farms during critical events, characterized by comprising a wind farm-level optimization module and a grid support module.

[0010] The wind farm-level optimization module determines whether the wind farm operates in maximum power mode or load reduction mode based on the wind farm's steady-state active power demand, and assigns the optimal controller reference value to the wind turbine controller.

[0011] In maximum power mode, the wind farm-level optimization module considers the wake effect between wind turbines and generates controller parameters for each wind turbine, so that the overall active power output of the wind farm reaches its peak value.

[0012] In the unloaded mode, the wind farm-level optimization module also considers the wake effect between wind turbines, so that the power output of the wind farm meets the load demand while maximizing the non-functional capacity of the wind farm, maximizing the kinetic energy stored in the rotor and minimizing the pitch angle change during mode switching.

[0013] This wind farm-level optimization module is mainly used to optimize the operation of wind farms during non-fault periods, so that wind farms have active and reactive power reserves. Whether wind farms can provide safe and compliant voltage and frequency support during grid faults depends on the grid support module's constraint on the wind turbine power reference value during faults.

[0014] The grid support module generates a set of grid support constraints based on the reactive power capacity curve of the wind farm. These constraints provide the active power support limit for the wind farm during high / low voltage ride-through. During fault periods, the frequency of the grid is supported by droop control, and the power reference value of the droop control must be within this limit value to ensure that the voltage support capability of the wind farm and the operation limitations of the grid are not affected. The energy source for frequency support in the grid support module is the kinetic energy stored in the rotor in the optimization module.

[0015] A method for enhancing the grid support capability of wind farms during critical events, characterized by comprising the following steps:

[0016] Step 1: Based on the Jensen model, obtain the wind turbine output power P that takes into account the wind turbine wake effect. i ;

[0017] Step 2: Based on the wind turbine output power considering the wake effect obtained in Step 1, solve for the optimization objective function of the wind farm in the maximum power operation mode. Optimize for different wind speeds to obtain the wind energy utilization coefficient of each wind turbine in the maximum power mode.

[0018] Step 3: Based on the wind turbine output power considering the wake effect obtained in Step 1, solve for the optimization objective function of the wind farm in unloading mode. Perform repeated optimization for different wind speeds and electric field load rates to obtain the wind energy utilization coefficient of each wind turbine in unloading mode.

[0019] Step 4: Convert the wind energy utilization coefficient in the maximum power mode of Step 2 and the wind energy utilization coefficient in the unloading mode of Step 3 into optimal controller reference values, thereby generating the pitch angle reference value. and rotor speed Controller parameter lookup table for reference values;

[0020] Step 5: Generate a set of maximum active power support limits for the power grid based on the reactive power capacity curve of the wind farm;

[0021] Step 6: Within the active power support limit of Step 5, the wind turbine provides primary frequency regulation to the grid during voltage ride-through through droop control without affecting the non-functional capacity of the wind farm.

[0022] Furthermore, according to the Jensen model, when considering the wake effect of the wind turbines, the cut-in velocity of each wind turbine can be expressed as:

[0023]

[0024] Among them, v wind,i The wind speed received by fan i, vj The unobstructed wind speed is given by α, which is the axial disturbance coefficient, and D is the wind speed. j Let A be the rotor diameter of fan j. ji Let x be the ratio of the area of ​​fan i blocking fan j to the swept area of ​​fan j. ji Let be the diameter distance between wind turbines j and i, k be the attenuation constant, and n be the number of wind turbines;

[0025] Then, in step 1, the output power of each wind turbine considering the wake effect can be expressed as:

[0026]

[0027] λ=K b ω / v wind

[0028] Where, ρ ar C is the power constant of the wind turbine. p β is the wind energy utilization coefficient, λ is the blade pitch angle, and v is the tip speed ratio. wind To cut into the wind speed, K b ω is a constant, and ω is the rotor speed.

[0029] Furthermore, the objective function for optimizing the wind farm under maximum power operation mode, taking into account the wake effect, in step 2 is:

[0030]

[0031] Among them, P i The output power of each fan at different wind speeds,

[0032] The wind turbine output power in maximum power mode is converted into the wind energy utilization coefficient of the wind turbine according to the following formula:

[0033]

[0034] Where, ρ ar Wind turbine power constant, v wind To cut into wind speed, This is the wind energy utilization coefficient of the wind turbine in the maximum power mode.

[0035] Furthermore, the optimization objective function for the wind farm in unloading mode, taking into account the wake effect in step 3, is:

[0036] 1)

[0037] 2)min||[L ΔC pi L]||

[0038]

[0039] in, V is the maximum non-functional force of fan i. pcc ΔC is the voltage at the grid connection point of the wind farm. pi Let be the change in the wind energy utilization coefficient of the i-th wind turbine.

[0040] The wind turbine output power in unloading mode is converted into the wind energy utilization coefficient of the wind turbine according to the following formula.

[0041]

[0042] Where, ρ ar Wind turbine power constant, v wind To cut into wind speed, This is the wind energy utilization coefficient of the wind turbine in unloading mode.

[0043] Furthermore, in both the maximum power mode and the offloading mode in steps 2 and 3, the operating point of the wind farm satisfies the following constraints:

[0044] v wind,i ≥v min

[0045] λ min,i ≤λ i ≤λ max,i

[0046] 0≤C pi ≤C p,i,max

[0047] P i,min ≤P i ≤P i,max

[0048]

[0049] Among them, v min For the minimum cut-in wind speed, λ min,i and λ max,i These are the minimum and maximum values ​​of the tip speed ratio, C. pi Let C be the wind energy utilization coefficient of the i-th wind turbine in both modes. p,i,max Let P be the maximum wind energy utilization coefficient of the i-th wind turbine. i,min and P i,max Q represents the minimum and maximum output power of the wind turbine. i This is the reactive power output of the wind turbine. and These represent the minimum and maximum values ​​of the fan's non-functional capacity.

[0050] Furthermore, step 4 transforms the wind energy utilization coefficient in the maximum power mode of step 2 and the wind energy utilization coefficient in the unloading mode of step 3 into the optimal controller reference value. This requires establishing a quadratic optimization objective function between the wind energy utilization coefficient and the pitch angle reference value and angular velocity reference value, so that the kinetic energy stored in the wind turbine rotor is maximized, while the change in wind turbine pitch angle when the wind field switches from the maximum power mode to the unloading mode is minimized.

[0051] Furthermore, the quadratic optimization objective function for establishing the relationship between the wind energy utilization coefficient and the reference values ​​of pitch angle and angular velocity is:

[0052]

[0053]

[0054]

[0055] λ min,i ≤λ i ≤λ max,i

[0056] 0≤C pi ≤C p,max,i

[0057] β min ≤β i ≤β max

[0058] Where, λ i This refers to the tip speed ratio of the fan blades. K is the reference value for rotor speed. b v is a constant wind To cut off the wind speed, C pi The wind energy utilization coefficients are for the two modes. For the pitch angle reference value, load cmd This refers to the load factor of the wind farm.

[0059] Furthermore, in step 5, a set of maximum active power support limits for the power grid is generated based on the reactive power capacity curve of the wind farm, which is expressed as follows during the low voltage ride-through period of the power grid:

[0060]

[0061] Where P i This refers to the active power output of the wind turbine. V represents the maximum value of the fan's no-efficiency capacity. pcc This refers to the voltage at the wind farm's grid connection point.

[0062] During high-voltage ride-through in the power grid, it is represented as:

[0063]

[0064] Among them, P i This refers to the active power output of the wind turbine. V is the minimum value of the no-function capacity of the fan. pcc This is the voltage at the grid connection point of the wind farm.

[0065] The advantages and beneficial effects of this invention are as follows:

[0066] This invention considers the wake effect of wind turbines and optimizes wind energy utilization efficiency at the wind farm level, enabling the wind farm to operate in maximum power mode or, depending on system load demand, in unloaded mode. It also provides the wind farm with voltage support capability and primary frequency regulation capability. This invention maximizes the wind farm's non-functional capacity and the kinetic energy stored in the rotor while minimizing the pitch angle change during mode switching, thereby reducing the wear and tear on mechanical devices during wind farm operation mode switching. This invention is based on a controller parameter lookup table; for a specific wind farm, only one calculation is needed to generate the controller reference value lookup table. Attached Figure Description

[0067] Figure 1 It involves the pitch angle control of the wind turbine and the converter control.

[0068] Figure 2 This is a flowchart illustrating the overall implementation of the power grid support scheme based on the controller parameter lookup table of the present invention.

[0069] Figure 1 Chinese: v w ω represents the real-time wind speed of the wind farm, load represents the wind farm load factor, and ω represents the wind speed. ref and β ref Reference values ​​for the wind turbine angular frequency and pitch angle, β, are generated for the controller parameter lookup table. ω It is the pitch angle correction value generated based on rotor frequency fluctuations, P ref f is the active power reference value. means and ω means These are the measured values ​​of system frequency and angular frequency, respectively, K. f Let ΔP be the droop coefficient of the first frequency response. PFR P represents the power increment during the frequency response process. ord For the final active power control signal input to the machine-side converter, v rot,dq This refers to the port voltage output by the machine-side converter.

[0070] Figure 2 In: β ref,min,max (v wind ,load) is a controller parameter lookup table for the reference value, maximum value, and minimum value of the pitch angle, ω ref,min,max (v wind,load) is a controller parameter lookup table for angular frequency reference, maximum, and minimum values. cap,max (P,V pcc ,) and Q cap,min (P,V pcc ,) are controller parameter lookup tables for reactive power reference values ​​of wind farms during low voltage ride-through and high voltage ride-through, respectively. Detailed Implementation

[0071] The present invention will be further described in detail below through specific embodiments. The following embodiments are merely descriptive and not limiting, and should not be used to limit the scope of protection of the present invention.

[0072] The control loop of this scheme is as follows: Figure 1 As shown, a controller parameter lookup table for the power grid under steady-state and transient conditions is generated by optimizing the objective function. During steady-state or transient periods, the wind turbine controller updates the pitch angle reference value and the turbine angular frequency reference value according to different wind speeds and load rates based on the controller parameter lookup table. The control loop consists of two parts: pitch angle control and turbine-side converter control. Pitch angle control adjusts the angle of the turbine blades to control the amount of electricity extracted from the incident wind. Simultaneously, the PI controller uses a rate sensor to sense rotor speed deviations to balance load fluctuations, thereby correcting the pitch angle reference value. The corrected value is... Figure 1 β in ω The servo circuit simulates the dynamic response of the pitch system and limits the rate and range of pitch angle change. The turbine-side converter employs active power droop control, using a PI controller to sense rotor speed deviations and control the active power P output by the turbine. ref P ref Adding the power increment ΔP during the frequency response process PFR The final control signal P of the input-side converter is obtained through the rate limiter. ord After undergoing dual-loop control within the converter, the port voltage output by the machine-side converter in the rotating coordinate system is v. rot,dq .

[0073] The specific implementation process of this solution is as follows: Figure 2As shown. First, the wind farm data is read to determine if the wind farm topology has changed. If it has changed, the controller parameter lookup table needs to be regenerated according to the optimization algorithm. When the wind farm topology has not changed, the operating point of the wind farm can be set directly according to the controller parameter lookup table. When setting the wind farm operating point, it is first determined whether the wind farm is in a steady state. If it is in a steady state, the wind farm is operated in either maximum power mode or load shedding mode according to the load demand in the system. When the grid only experiences load disturbances, the wind farm provides a primary frequency response to the grid through droop control. When the grid experiences voltage ride-through events, the wind farm provides the grid with corresponding voltage support and a primary frequency response simultaneously, depending on the type of voltage ride-through.

[0074] The system for enhancing the grid support capability of wind farms during critical events consists of two modules: the Farm-Level Optimization (FLO) module determines whether the wind farm operates in maximum power mode or reduced load mode based on the wind farm's steady-state active power demand, and assigns the optimal controller reference value to the wind turbine controller to maximize the wind farm's reactive power and the kinetic energy stored in the rotor, and reduce the mechanical losses generated during mode switching.

[0075] In maximum power mode, the wind farm-level optimization module considers the wake effect between wind turbines and generates controller parameters for each wind turbine, so that the overall active power output of the wind farm reaches its peak value.

[0076] In the unloaded mode, the wind farm-level optimization module also considers the wake effect between wind turbines, so that the power output of the wind farm meets the load demand while maximizing the non-functional capacity of the wind farm, maximizing the kinetic energy stored in the rotor and minimizing the pitch angle change during mode switching.

[0077] This wind farm-level optimization module is mainly used to optimize the operation of wind farms during non-fault periods, so that wind farms have active and reactive power reserves. However, whether wind farms can provide safe and compliant voltage and frequency support during grid faults depends on the grid support module's constraint on the wind turbine power reference value during fault periods.

[0078] The grid support module generates a set of grid support constraints (GS-L) based on the wind farm's reactive power capacity curve. These constraints provide the active power support limit for the wind farm during high / low voltage ride-throughs, ensuring a consistent frequency response. During fault periods, droop control supports the grid frequency, and the power reference value for droop control must be within these limits to prevent the wind farm's voltage support capability and grid operation limitations from being affected. The energy source for frequency support in the grid support module is ultimately the kinetic energy stored in the rotor within the optimization module.

[0079] The innovation of this invention lies in considering the wake effect of wind turbines, allowing some wind farms to operate entirely in maximum power mode or in off-load mode according to load demand, thus optimizing the active power output of wind farms while maintaining a certain active power reserve margin. In off-load mode, the reactive power capacity of wind farms is maximized, improving their voltage support capability to the grid. Reference values ​​are assigned to the controller to reduce wear on wind turbine mechanical devices during pitch regulation while meeting the maximum reactive power capacity of the wind farm. A controller parameter lookup table based on grid guidelines and system constraints is generated to support the maximum active power, improving the wind farm's ability to support grid frequency during voltage ride-through. This method is based on the controller parameter lookup table; therefore, for a specific wind farm, only one calculation is needed to generate the controller parameter lookup table.

[0080] A method for enhancing the grid support capability of wind farms during critical events includes the following steps:

[0081] Step 1: Based on the Jensen model, obtain the wind turbine output power P that takes into account the wind turbine wake effect. i ;

[0082] Step 2: Based on the wind turbine output power considering the wake effect obtained in Step 1, solve for the optimization objective function of the wind farm in the maximum power operation mode. Optimize for different wind speeds to obtain the wind energy utilization coefficient of each wind turbine in the maximum power mode.

[0083] Step 3: Based on the wind turbine output power considering the wake effect obtained in Step 1, solve for the optimization objective function of the wind farm in unloading mode. Perform repeated optimization for different wind speeds and electric field load rates to obtain the wind energy utilization coefficient of each wind turbine in unloading mode.

[0084] Step 4: Convert the wind energy utilization coefficient in the maximum power mode of Step 2 and the wind energy utilization coefficient in the unloading mode of Step 3 into optimal controller reference values, thereby generating the pitch angle reference value. and rotor speed Controller parameter lookup table for reference values;

[0085] Step 5: Generate a set of maximum active power support limits for the power grid based on the reactive power capacity curve of the wind farm;

[0086] Step 6: Within the active power support limit of Step 5, the wind turbine provides primary frequency regulation to the grid during voltage ride-through through droop control without affecting the non-functional capacity of the wind farm.

[0087] According to the Jensen model, when considering the wake effect of the wind turbine, the cut-in velocity of each wind turbine can be expressed as:

[0088]

[0089] Among them, v wind,i The wind speed received by fan i, v j The unobstructed wind speed is given by α, which is the axial disturbance coefficient, and D is the wind speed. j Let A be the rotor diameter of fan j. ji Let x be the ratio of the area of ​​fan i blocking fan j to the swept area of ​​fan j. ji Let be the diameter distance between wind turbines j and i, k be the attenuation constant, and n be the number of wind turbines.

[0090] Then, in step 1, the output power of each wind turbine considering the wake effect can be expressed as:

[0091]

[0092] λ=K b ω / v wind

[0093] Where, ρ ar C is the power constant of the wind turbine. p β is the wind energy utilization coefficient, λ is the blade pitch angle, and v is the tip speed ratio. wind To cut into the wind speed, K b ω is a constant, and ω is the rotor speed.

[0094] The objective function for optimizing the wind farm under maximum power operation mode, taking into account the wake effect, in step 2 is:

[0095]

[0096] Among them, P i Output power of each wind turbine at different wind speeds

[0097] The wind turbine output power in maximum power mode is converted into the wind energy utilization coefficient of the wind turbine according to the following formula:

[0098]

[0099] Where, ρ ar Wind turbine power constant, v wind To cut into wind speed, This is the wind energy utilization coefficient of the wind turbine in the maximum power mode.

[0100] The optimization objective function for the wind farm in unloading mode, taking into account the wake effect in step 3, is:

[0101] 1)

[0102] 2)min||[L ΔC pi L]||

[0103]

[0104] in, V is the maximum non-functional force of fan i. pcc ΔC is the voltage at the grid connection point of the wind farm. pi Let be the change in the wind energy utilization coefficient of the i-th wind turbine.

[0105] The wind turbine output power in unloading mode is converted into the wind energy utilization coefficient of the wind turbine according to the following formula.

[0106]

[0107] Where, ρ ar Wind turbine power constant, v wind To cut into wind speed, This is the wind energy utilization coefficient of the wind turbine in unloading mode.

[0108] In both the maximum power mode and the offloading mode in steps 2 and 3, the operating point of the wind farm satisfies the following constraints:

[0109] v wind,i ≥v min

[0110] λ min,i ≤λ i ≤λ max,i

[0111] 0≤C pi ≤C p,i,max

[0112] P i,min ≤P i ≤P i,max

[0113]

[0114] Among them, v min For the minimum cut-in wind speed, λ min,i and λ max,i These are the minimum and maximum values ​​of the tip speed ratio, C. pi Let C be the wind energy utilization coefficient of the i-th wind turbine in both modes. p,i,max Let P be the maximum wind energy utilization coefficient of the i-th wind turbine. i,min and P i,max Q represents the minimum and maximum output power of the wind turbine. i This is the reactive power output of the wind turbine. and These represent the minimum and maximum values ​​of the fan's non-functional capacity.

[0115] Step 4 converts the wind energy utilization coefficient in the maximum power mode in Step 2 and the wind energy utilization coefficient in the unloading mode in Step 3 into the optimal controller reference value. It is necessary to establish a quadratic optimization objective function between the wind energy utilization coefficient and the pitch angle reference value and the angular velocity reference value, so as to maximize the kinetic energy stored in the wind turbine rotor and minimize the change in wind turbine pitch angle when the wind field switches from the maximum power mode to the unloading mode.

[0116] The objective function for establishing the relationship between the wind energy utilization coefficient and the reference values ​​for pitch angle and angular velocity is as follows:

[0117]

[0118]

[0119]

[0120] λ min,i ≤λ i ≤λ max,i

[0121] 0≤C pi ≤C p,max,i

[0122] β min ≤β i ≤β max

[0123] Where, λ i This refers to the tip speed ratio of the fan blades. K is the reference value for rotor speed. b v is a constant wind To cut off the wind speed, C pi The wind energy utilization coefficients are for the two modes. For the pitch angle reference value, load cmd This refers to the load factor of the wind farm.

[0124] In step 5, a set of maximum active power support limits for the power grid is generated based on the reactive power capacity curve of the wind farm. These limits are expressed as follows during the low-voltage ride-through period of the power grid:

[0125]

[0126] Where P i This refers to the active power output of the wind turbine. V represents the maximum value of the fan's no-efficiency capacity. pcc This is the voltage at the grid connection point of the wind farm.

[0127] During high-voltage ride-through in the power grid, it is represented as:

[0128]

[0129] Where P i This refers to the active power output of the wind turbine. V is the minimum value of the no-function capacity of the fan. pcc This is the voltage at the grid connection point of the wind farm.

[0130] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0131] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0132] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0133] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do 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 of enhancing the grid support capability of a wind farm during a critical event, characterized in that: This method is based on the system implementation of enhancing the grid support capability of wind farms during critical events, and the method includes the following steps: Step 1, the output power of the wind turbine considering the wake effect of the wind turbine is obtained according to the Jensen model P i ; Step 2: Based on the wind turbine output power considering the wake effect obtained in Step 1, solve for the optimization objective function of the wind farm in the maximum power operation mode. Optimize for different wind speeds to obtain the wind energy utilization coefficient of each wind turbine in the maximum power mode. ; Step 3, according to the wind turbine output power considering the wake effect in step 1, the optimization objective function of the wind farm in the unloading mode is solved, and the combination of different wind speeds and farm load rates is repeated to obtain the wind energy utilization coefficient of each wind turbine in the unloading mode ; Step 4, converting the wind energy utilization coefficients in the maximum power mode in step 2 and the wind energy utilization coefficients in the unloading mode in step 3 into optimal controller reference values, thereby generating the pitch angle reference value and the rotor rotational speed a controller parameter lookup table for the reference value; Step 5: Generate a set of maximum active power support limits for the power grid based on the reactive power capacity curve of the wind farm; Step 6: Within the active power support limit of Step 5, the wind turbine provides primary frequency regulation to the grid during voltage ride-through through droop control without affecting the non-functional capacity of the wind farm. The system for enhancing the grid support capability of wind farms during critical events includes a wind farm-level optimization module and a grid support module. The wind farm-level optimization module is used to optimize the operation of the wind farm during non-fault periods, so that the wind farm has active and reactive power reserves. Whether the wind farm can provide safe and compliant voltage and frequency support during grid faults depends on the grid support module's constraint on the wind turbine power reference value during faults. The grid support module generates a set of grid support constraints based on the reactive power capacity curve of the wind farm. These constraints provide the active power support limit for the wind farm during high / low voltage ride-through. During fault periods, the frequency of the grid is supported by droop control, and the power reference value of the droop control must be within this limit value to ensure that the voltage support capability of the wind farm and the operation limitations of the grid are not affected. The energy source for frequency support in the grid support module is the kinetic energy stored in the rotor in the optimization module.

2. The method of claim 1, wherein: According to the Jensen model, when considering the wake effect of the wind turbine, the cut-in velocity of each wind turbine can be expressed as: in, v wind,i For wind turbine i Acceptable wind speed, v j For unobstructed wind speed, The axial disturbance coefficient is... D j For wind turbine j rotor diameter, A ji For wind turbine i In the fan j The area of ​​the shielding on the wind turbine j The ratio of the swept area, x ji For wind turbine j and i The diameter distance between them k The attenuation constant is n Number of wind turbines; Then, in step 1, the output power of each wind turbine considering the wake effect can be expressed as: wherein, ρ ar is the fan power constant, C p is the wind energy utilization coefficient, β is the pitch angle, λ is the tip speed ratio, v wind is the cut-in wind speed, K b is a constant, ω is the rotor rotational speed.

3. The method of claim 2, wherein: The objective function for optimizing the wind farm under maximum power operation mode, taking into account the wake effect, in step 2 is: wherein, P i P is the output power of the wind turbine at the respective wind speed, The wind turbine output power in maximum power mode is converted into the wind energy utilization coefficient of the wind turbine according to the following formula: in, ρ ar Fan power constant, v wind To cut into wind speed, This is the wind energy utilization coefficient of the wind turbine in the maximum power mode.

4. The method of claim 3, wherein: The optimization objective function for the wind farm in unloading mode, taking into account the wake effect in step 3, is: wherein is the maximum power of the wind turbine i , V pcc is the grid point voltage of the wind farm, Δ C pi is the wind energy utilization coefficient variation of the first i wind turbine The wind turbine output power in unloading mode is converted into the wind energy utilization coefficient of the wind turbine according to the following formula. wherein, ρ ar fan power constant, v wind is the cut-in wind speed, is the wind energy utilization coefficient of the fan in the unloaded mode.

5. The method of claim 4, wherein: In both the maximum power mode and the offloading mode in steps 2 and 3, the operating point of the wind farm satisfies the following constraints: in, v min To minimize the cut-in wind speed, λ min , i and λ max , i These are the minimum and maximum values ​​of the tip speed ratio, respectively. For the first i Wind energy utilization coefficient of typhoon turbines in two modes For the first i The maximum wind energy utilization coefficient of a typhoon turbine. P i,min and P i,max These represent the minimum and maximum output power of the fan. Q i This is the reactive power output of the wind turbine. and These are the minimum and maximum values ​​of the fan's no-function capacity. λ i This refers to the tip speed ratio of the fan blades.

6. The method of claim 5, wherein: Step 4 converts the wind energy utilization coefficient in the maximum power mode in Step 2 and the wind energy utilization coefficient in the unloading mode in Step 3 into the optimal controller reference value. It is necessary to establish a quadratic optimization objective function between the wind energy utilization coefficient and the pitch angle reference value and the angular velocity reference value, so as to maximize the kinetic energy stored in the wind turbine rotor and minimize the change in wind turbine pitch angle when the wind field switches from the maximum power mode to the unloading mode.

7. The method of claim 6, wherein: The objective function for establishing the relationship between the wind energy utilization coefficient and the reference values ​​for pitch angle and angular velocity is as follows: in, λ i This refers to the tip speed ratio of the fan blades. This is a reference value for rotor speed. K b It is a constant. v wind To cut into wind speed, C pi The wind energy utilization coefficients are for the two modes. βref i This is a reference value for the pitch angle. load cmd This refers to the load factor of the wind farm.

8. The method for enhancing the grid support capability of wind farms during critical events according to claim 7, characterized in that: In step 5, a set of maximum active power support limits for the power grid is generated based on the reactive power capacity curve of the wind farm. These limits are expressed as follows during the low-voltage ride-through period of the power grid: wherein P i P is the active power output by the wind turbine, Qmax cap,i Pmax is the maximum value of the wind turbine's reactive power capability, V pcc V is the grid point voltage of the wind farm. During high-voltage ride-through in the power grid, it is represented as: wherein, P i P is the active power output by the wind turbine, Qmin cap,i Pmin is the minimum value of the wind turbine's reactive power capability, V pcc V is the grid point voltage of the wind farm.

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