A wind farm collaborative control method and system based on active pitch control strategy

Abstract

The present invention discloses a wind farm collaborative control method and system based on an active pitch control strategy. The method includes: obtaining the wind turbine model, its wind turbine rotor diameter, and wind turbine arrangement information within the wind farm; constructing a wind farm output power simulation system under pitch angle conditions based on an established wind turbine pitch characteristic database, rotor diameter, and unit arrangement information, and combining it with a wind turbine analytical wake model; obtaining the operating data of each unit in the wind farm in real time and inputting it into the power simulation system to establish an optimization function with the pitch angle of each unit as the independent variable and the total power of the wind farm as the dependent variable; optimizing the optimization function to obtain the pitch angle combination of each unit with the maximum output power, and using the pitch angle optimization result as the control instruction for its active pitch control, thereby implementing collaborative pitch control for each unit in the wind farm. The present invention realizes more efficient and reliable online optimization control, and can achieve an increase in the total power of the wind farm without sacrificing the service life of the blades.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and in particular to a wind farm collaborative control method and system based on an active pitch control strategy. Background Art

[0002] Wind energy is one of the most mature and competitive renewable energy sources. To maximize wind energy utilization and ensure economic viability, large wind farms typically deploy a large number of wind turbines. Large-scale wind farm development can reduce initial land use, infrastructure, and subsequent operations and maintenance costs. However, once a certain number of wind turbines is reached, further expansion can lead to a decrease in wind farm power generation. This is because the wake effect of upstream turbines reduces the incoming wind speed of downstream turbines, further reducing their output power. Therefore, it is crucial to minimize power generation losses caused by the wake effect during wind farm design and operation.

[0003] During the operational phase of a wind farm, wind turbine collaborative control technology is generally used to reduce the impact of wake turbulence. By optimizing the operating status of the front-row turbines, the wake impact on the rear-row turbines is reduced, thereby achieving the goal of maximizing overall farm power. Existing wind farm collaborative control technologies mainly fall into two categories. One is an open-loop, offline optimization technology. This technology pre-optimizes and simulates the possible incoming flow conditions of the wind farm, generating control instructions corresponding to different conditions to adjust the operating status of each turbine. The other is a closed-loop, online optimization technology. This technology simulates the wind farm status in real time using a wind farm surrogate model, performing optimization calculations simultaneously, and providing collaborative control instructions for each turbine in real time after receiving real-time data from the wind farm. However, whether based on an open-loop or closed-loop approach, existing wind farm collaborative control mostly regulates the turbine's yaw angle or thrust coefficient.

[0004] Open-loop control technology cannot flexibly adapt to the changing inflow conditions and complex turbine status of wind farms. While closed-loop control technology can address the problems of open-loop technology, the method of using thrust coefficient as the control object is theoretical research and difficult to directly apply to actual wind farm coordinated control projects. The method of using the turbine yaw angle as the control object is likely to cause large unbalanced loads on the controlled turbine rotor, increasing the burden on the blades and shortening the turbine lifespan. It does not have an economic advantage over the entire life cycle scale. Summary of the Invention

[0005] Therefore, an embodiment of the present invention provides a wind farm collaborative control method and system based on an active pitch control strategy. The pitch angle of the wind turbine is used as the controlled object, and a wind farm real-time simulation system is constructed, which includes the pitch characteristics of the turbine, the wake development law and the output power of the entire field. The pitch angle of each wind turbine is optimized online with the aid of an intelligent optimization algorithm, thereby realizing an efficient, reliable and practical application potential wind farm collaborative control method, which can solve the problems existing in the existing technology.

[0006] In order to achieve the above object, the present invention provides the following technical solutions:

[0007] In a first aspect, an embodiment of the present invention provides a wind farm coordinated control method based on an active pitch control strategy, comprising:

[0008] Obtain the wind turbine model and rotor diameter of the wind turbine in the wind farm, as well as the wind turbine layout information in the wind farm;

[0009] Establish a database of wind turbine pitch characteristics;

[0010] Based on the wind turbine pitch characteristic database, wind turbine rotor diameter and turbine arrangement information, and combined with the wind turbine analytical wake model, a wind farm output power simulation system under variable pitch angle conditions is constructed;

[0011] The operating data of each unit in the wind farm is obtained in real time and input into the wind farm output power simulation system under the variable pitch angle condition to establish an optimization function with the pitch angle of each unit as the independent variable and the total power of the wind farm as the dependent variable;

[0012] The optimization function is optimized using a preset intelligent optimization algorithm to obtain the pitch angle combination of each unit with the maximum output power in the entire field under the current inflow conditions. The pitch angle optimization result is output to the main control system of each unit as its active pitch control instruction, and coordinated pitch control is implemented for each unit in the wind farm.

[0013] Furthermore, the wind farm coordinated control method based on the active pitch control strategy further includes: acquiring power data fed back by the wind turbines to online correct the adjustable parameters in the simulation system.

[0014] Furthermore, the process of establishing a wind turbine pitch characteristic database includes:

[0015] Wind turbine simulation software is used to obtain the turbine power curve and thrust coefficient curve at pitch angles of 0 to 10 degrees, and the wind turbine variable pitch characteristic database is obtained.

[0016] Furthermore, the process of constructing a wind farm output power simulation system under variable pitch angle conditions includes:

[0017] The Jensen wake model is used to describe the wake effect in the field to calculate the incoming wind speed of each unit. The formula is:

[0018]

[0019] Among them, U W is the velocity in the wake zone; U0 is the incoming flow velocity; C T is the thrust coefficient; k w is the Jensen wake diffusion coefficient; x is the wake diffusion distance, which is determined according to the wind turbine layout information in the wind farm; d is the wind turbine rotor diameter.

[0020] Furthermore, the process of establishing the optimization function with the pitch angle of each unit as the independent variable and the full-field power as the dependent variable includes:

[0021] The incoming wind speed of each unit in the wind farm is calculated by the wake model. Combined with the operating characteristics of each unit, the overall power output of the wind farm under a certain wind direction is expressed as:

[0022]

[0023] Among them, U W,i represents the incoming wind speed of the i-th unit, and β i represents the pitch angle of the unit, and N represents the total number of units;

[0024] The full-field power is the optimization function of the dependent variable:

[0025]

[0026] Among them, β lb and β ub Represent the minimum and maximum limits of the unit pitch angle, β lb =0°, β ub =10°.

[0027] Furthermore, the optimization function of the differential evolution algorithm is used for online optimization to obtain the pitch angle combination of each unit that can maximize the overall output power under the current incoming flow conditions.

[0028] In a second aspect, an embodiment of the present invention provides a wind farm coordinated control system based on an active pitch control strategy, comprising:

[0029] The wind farm data acquisition module is used to obtain the wind turbine model and its wind turbine rotor diameter in the wind farm, as well as the wind turbine arrangement information in the wind farm;

[0030] A variable pitch characteristic database establishment module is used to establish a variable pitch characteristic database for wind turbines;

[0031] An output power simulation system establishment module is used to construct a wind farm output power simulation system under variable pitch angle conditions based on a wind turbine pitch characteristic database, wind turbine rotor diameter, and turbine arrangement information, combined with a wind turbine analytical wake model;

[0032] An optimization function establishment module is used to obtain the operating data of each unit in the wind farm in real time and input it into the wind farm output power simulation system under the variable pitch angle condition to establish an optimization function with the pitch angle of each unit as the independent variable and the total power of the wind farm as the dependent variable;

[0033] The collaborative pitch control module is used to optimize the optimization function using a preset intelligent optimization algorithm to obtain the pitch angle combination of each unit with the maximum output power in the entire field under the current inflow conditions, and output the pitch angle optimization result to the main control system of each unit as its active pitch control instruction, so as to implement collaborative pitch control of each unit in the wind farm.

[0034] Furthermore, the wind farm coordinated control system based on the active pitch control strategy is characterized by further comprising:

[0035] The parameter correction module is used to obtain the power data fed back by the wind turbine generator set to correct the adjustable parameters in the simulation system online.

[0036] In a third aspect, an embodiment of the present invention provides a computer device comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the wind farm collaborative control method based on the active pitch strategy as described in any embodiment of the first aspect of the present invention.

[0037] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the wind farm collaborative control method based on the active pitch strategy described in any embodiment of the first aspect of the present invention.

[0038] The technical solution of the present invention has the following advantages:

[0039] The present invention provides a wind farm collaborative control method and system based on an active pitch-changing strategy. The method and system perform collaborative control of the wind farm based on the active change of the pitch angle of the wind turbine, and achieve more efficient and reliable online optimization control by constructing a real-time simulation system for the wind farm output power. Compared with the existing wind farm collaborative control based on offline optimization technology, it can more flexibly adapt to the real-time changing incoming flow environment of the wind farm and the original state of the unit; compared with the collaborative control method based on the yaw of the unit, the method provided by the embodiment of the present invention has a faster response speed and can more efficiently reduce the influence of the wake in the field. More importantly, the collaborative control based on pitch change will not increase the unbalanced load on the controlled unit, and can achieve an increase in the power of the entire field without sacrificing the service life of the blades. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0041] Figure 1 This is a flowchart of a specific example of a wind farm coordinated control method based on an active pitch control strategy provided in an embodiment of the present invention;

[0042] Figure 2 A control principle block diagram of a wind farm coordinated control method based on an active pitch control strategy according to an embodiment of the present invention;

[0043] Figure 3 : is the thrust coefficient curve of the unit under the variable pitch condition in the embodiment of the present invention;

[0044] Figure 4 is the power curve of the unit under the variable pitch condition in the embodiment of the present invention;

[0045] Figure 5 This is a comparison diagram of the output power of the wind farm before and after adopting the wind farm coordinated control method provided by an embodiment of the present invention;

[0046] Figure 6 Comparison chart of unit loads before and after the wind farm coordinated control method provided by an embodiment of the present invention;

[0047] Figure 7 FIG. 1 is a module composition diagram of an example of a wind farm coordinated control system based on an active pitch control strategy provided in an embodiment of the present invention;

[0048] Figure 8 A diagram showing the composition of a specific example of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0050] In addition, the technical features involved in different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0051] Example 1

[0052] The embodiment of the present invention provides a wind farm coordinated control method based on active pitch control strategy, such as Figure 1 As shown, the method comprises the following steps:

[0053] Step S1: Obtain the wind turbine model and its rotor diameter in the wind farm, as well as the wind turbine layout information in the wind farm.

[0054] In the embodiment of the present invention, a standard NERL-5MW turbine model is used, the obtained wind turbine rotor diameter is 130m, and three turbines are arranged in sequence in the wind farm with an interval of 500m.

[0055] Step S2: Establish a wind turbine pitch characteristic database.

[0056] In an embodiment of the present invention, wind turbine simulation software is used to simulate the characteristics of the unit at different pitch angles. Considering that an excessively large pitch angle will greatly reduce the output power of the unit in the low wind speed area, in order to prevent the unit in the cooperative control from frequently performing start-up and shutdown operations, the angle of active pitch cannot be too large. In addition, the main working range of cooperative control is within the range of 5m / s to rated wind speed. From the simulation results, the unit can still operate at a wind speed of 5m / s with a pitch of 10°. If the pitch is increased further, the unit will shut down. Therefore, active pitch of 10° is the maximum pitch angle acceptable to cooperative control, and the maximum simulated pitch angle is set to 10 degrees. Finally, the unit power curve and thrust coefficient curve at pitch angles of 0 to 10 degrees are obtained, and a wind turbine pitch characteristic database is established. Specifically, Bladed simulation software is used to simulate the unit characteristics at different pitch angles, and the unit pitch characteristics are obtained as follows: Figure 2 and Figure 3 shown.

[0057] Step S3: Based on the wind turbine pitch characteristic database, the impeller diameter and the turbine arrangement information, and in combination with the wind turbine analytical wake model, a wind farm output power simulation system under variable pitch angle conditions is constructed.

[0058] The embodiment of the present invention uses the Jensen wake model to describe the wake effect in the field to calculate the incoming wind speed of each unit. The formula is:

[0059]

[0060] Among them, U W is the velocity in the wake zone; U0 is the incoming flow velocity; C T is the thrust coefficient; k w is the Jensen wake diffusion coefficient, which is taken as 0.05; x is the wake diffusion distance (equal to the spacing between wind turbines); and d is the diameter of the wind turbine rotor.

[0061] The above model can calculate the incoming wind speed of each unit in the wind farm. Combined with the operating characteristics of each unit, the overall power output of the wind farm under a certain wind direction can be expressed as:

[0062]

[0063] Among them, U W,i represents the incoming wind speed of the i-th unit, and β i represents the pitch angle of the unit, and N represents the total number of units.

[0064] Step S4: Acquire the operating data of each unit in the wind farm in real time and input it into the wind farm output power simulation system under the variable pitch angle condition to establish an optimization function with the pitch angle of each unit as the independent variable and the total power as the dependent variable.

[0065] In practical applications, real-time operating data of each wind farm unit is obtained, including wind speed, wind direction, and power data. In this embodiment, the real-time wind farm operating data is obtained through the output of the Fast.Farm simulation software. An optimization function is established with the pitch angle of each unit as the independent variable and the total farm power as the dependent variable:

[0066]

[0067] Among them, β lb and β ub Represent the minimum and maximum limits of the unit pitch angle respectively, so β lb =0°, β ub =10°.

[0068] Step S5: Optimize the optimization function using a preset intelligent optimization algorithm to obtain the pitch angle combination of each unit with the maximum output power in the entire field under the current inflow conditions, and output the pitch angle optimization result to the main control system of each unit as its active pitch control instruction, so as to implement coordinated pitch control for each unit in the wind farm.

[0069] In this embodiment, a differential evolution algorithm is used to perform online optimization on the established optimization function, obtaining the pitch angle combination for each turbine that maximizes the overall power output under the current inflow conditions. In one specific embodiment, the key parameters of differential evolution include: a population size of 10, a maximum number of iterations of 100, a crossover probability of 0.8, and a mutation probability of 0.5. Differential evolution is a relatively mature and efficient global optimization algorithm, and the process of optimizing the optimization function using it will not be detailed here.

[0070] Furthermore, the pitch angle optimization result is output to the main control system of each unit as the control instruction for its active pitch change, and the coordinated pitch control is implemented for each unit in the wind farm. Figure 4 As shown, the adjustable parameters in the simulation system in step S3 are corrected online based on the power data fed back by the turbines to ensure simulation accuracy. Then, steps S4 and S5 are repeated based on the incoming wind conditions to achieve coordinated pitch control of the wind farm, aiming to reduce the impact of wake turbulence and thereby increase overall power generation.

[0071] The embodiment of the present invention implements coordinated pitch control on the wind farm through Fast.Farm simulation software. Figure 5 The output power comparison of the wind farm before and after the adoption of this method is shown, and it can be seen that the coordinated control method significantly improves the power generation of the entire farm. Figure 6 The comparison of the unit load before and after the adoption of this method is shown. It can be seen that the collaborative control based on active variable pitch can not only improve the overall power but also effectively reduce the load borne by the unit.

[0072] Example 2

[0073] The embodiment of the present invention provides a wind farm coordinated control system based on active pitch control strategy, such as Figure 7 Shown, including:

[0074] The wind farm data acquisition module 1 is used to obtain the wind turbine model and its wind turbine rotor diameter, as well as the wind turbine arrangement information in the wind farm; this module executes the method described in step S1 of embodiment 1, which will not be repeated here.

[0075] The variable pitch characteristic database establishing module 2 is used to establish a variable pitch characteristic database of the wind turbine generator set; this module executes the method described in step S2 of embodiment 1, which will not be described in detail here.

[0076] The output power simulation system establishes a module 3, which is used to construct a wind farm output power simulation system under variable pitch angle conditions based on the wind turbine pitch characteristic database, the wind turbine rotor diameter and the unit arrangement information, and in combination with the wind turbine analytical wake model; this module executes the method described in step S3 in Example 1 and will not be repeated here.

[0077] The optimization function establishment module 4 is used to obtain the operating data of each unit in the wind farm in real time and input it into the wind farm output power simulation system under the variable pitch angle condition to establish an optimization function with the pitch angle of each unit as the independent variable and the total power of the wind farm as the dependent variable; this module executes the method described in step S4 of Example 1 and will not be repeated here.

[0078] Coordinated pitch control module 5 is configured to optimize the optimization function using a preset intelligent optimization algorithm to determine the pitch angle combination for each turbine that maximizes the overall field output power under the current inflow conditions. This module then outputs the optimized pitch angle results to the main control system of each turbine as control instructions for its active pitch control, thereby implementing coordinated pitch control for each turbine in the wind farm. This module executes the method described in step S5 of Example 1 and is not further described here.

[0079] The system provided by an embodiment of the present invention also includes a parameter correction module for obtaining power data fed back by wind turbines and online correcting adjustable parameters in the simulation system. The adjustable parameters in the wind farm output power simulation system under variable pitch angle conditions are corrected online based on the power data fed back by the turbines to ensure simulation accuracy.

[0080] The wind farm collaborative control system based on the active pitch control strategy provided by the embodiment of the present invention takes the pitch angle of the wind turbine as the controlled object, constructs a wind farm real-time simulation system that includes the pitch characteristics of the unit, the wake development law and the output power of the entire field, and uses the differential evolution algorithm to optimize the pitch angle of each unit online, thereby realizing efficient, reliable and practical application potential wind farm collaborative control.

[0081] Example 3

[0082] An embodiment of the present invention provides a computer device, such as Figure 8As shown, it includes: at least one processor 501, such as a CPU (Central Processing Unit), at least one communication interface 503, a memory 504, and at least one communication bus 502. Among them, the communication bus 502 is used to realize the connection and communication between these components. Among them, the communication interface 503 may include a display screen (Display), a keyboard (Keyboard), and the optional communication interface 503 may also include a standard wired interface and a wireless interface. The memory 504 may be a high-speed RAM memory (Ramdom Access Memory, volatile random access memory) or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 504 may optionally be at least one storage device located away from the aforementioned processor 501. Among them, the processor 501 can execute the wind farm collaborative control method based on the active pitch strategy of Example 1. A set of program codes are stored in the memory 504, and the processor 501 calls the program code stored in the memory 504 to execute the wind farm collaborative control method based on the active pitch strategy of Example 1.

[0083] The communication bus 502 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The communication bus 502 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Although only one line is used, it does not mean that there is only one bus or one type of bus.

[0084] Among them, the memory 504 may include volatile memory (English: volatile memory), such as random-access memory (English: random-access memory, abbreviated: RAM); the memory may also include non-volatile memory (English: non-volatile memory), such as flash memory (English: flash memory), hard disk drive (English: hard disk drive, abbreviated: HDD) or solid-state drive (English: solid-state drive, abbreviated: SSD); the memory 504 may also include a combination of the above types of memory.

[0085] The processor 501 may be a central processing unit (CPU), a network processor (NP), or a combination of a CPU and a NP.

[0086] The processor 501 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0087] Optionally, the memory 504 is further configured to store program instructions. The processor 501 may call the program instructions to implement the wind farm coordinated control method based on the active pitch control strategy in Example 1 of the present application.

[0088] An embodiment of the present invention further provides a computer-readable storage medium having computer-executable instructions stored thereon, which can execute the wind farm coordinated control method based on the active pitch control strategy of Example 1. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD), or a solid-state drive (SSD); the storage medium can also include a combination of the aforementioned types of memory.

[0089] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will appreciate that other variations or modifications can be made based on the above description. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. A wind farm coordinated control method based on active pitch control strategy, characterized in that: include: Obtain the wind turbine model and rotor diameter of the wind turbine in the wind farm, as well as the wind turbine layout information in the wind farm; Establish a database of wind turbine pitch characteristics; Based on the wind turbine pitch characteristic database, wind turbine rotor diameter and turbine arrangement information, and combined with the wind turbine analytical wake model, a wind farm output power simulation system under variable pitch angle conditions is constructed; The operating data of each unit in the wind farm is obtained in real time and input into the wind farm output power simulation system under the variable pitch angle condition to establish an optimization function with the pitch angle of each unit as the independent variable and the total power of the wind farm as the dependent variable; The optimization function is optimized using a preset intelligent optimization algorithm to obtain the pitch angle combination of each unit with the maximum output power in the entire field under the current inflow conditions. The pitch angle optimization result is output to the main control system of each unit as its active pitch control instruction, and coordinated pitch control is implemented for each unit in the wind farm.

2. The wind farm coordinated control method based on active pitch control strategy according to claim 1 is characterized in that: Also includes: The power data fed back by the wind turbine generator set is obtained to correct the adjustable parameters in the simulation system online.

3. The wind farm coordinated control method based on active pitch control strategy according to claim 2 is characterized in that: The process of establishing a wind turbine pitch characteristic database includes: Wind turbine simulation software is used to obtain the turbine power curve and thrust coefficient curve at pitch angles of 0 to 10 degrees, and the wind turbine variable pitch characteristic database is obtained.

4. The wind farm coordinated control method based on active pitch control strategy according to claim 3 is characterized in that: The process of constructing a wind farm output power simulation system under variable pitch angle conditions includes: The Jensen wake model is used to describe the wake effect in the field to calculate the incoming wind speed of each unit. The formula is: Among them, U W is the velocity in the wake zone; U0 is the incoming flow velocity; C T is the thrust coefficient; k w is the Jensen wake diffusion coefficient; x is the wake diffusion distance, which is determined according to the wind turbine layout information in the wind farm; d is the wind turbine rotor diameter.

5. The wind farm coordinated control method based on active pitch control strategy according to claim 4 is characterized in that: The process of establishing the optimization function with the pitch angle of each unit as the independent variable and the full-field power as the dependent variable includes: The incoming wind speed of each unit in the wind farm is calculated by the wake model. Combined with the operating characteristics of each unit, the overall power output of the wind farm under a certain wind direction is expressed as: Among them, U W,i represents the incoming wind speed of the i-th unit, and β i represents the pitch angle of the unit, and N represents the total number of units; The full-field power is the optimization function of the dependent variable: Among them, β lb and β ub Represent the minimum and maximum limits of the unit pitch angle, β lb =0°, β ub =10°.

6. The wind farm coordinated control method based on active pitch control strategy according to claim 5 is characterized in that: The optimization function is optimized online using a differential evolution algorithm to obtain the pitch angle combination of each unit that can maximize the overall output power under the current inflow conditions.

7. A wind farm collaborative control system based on active pitch control strategy, characterized in that: include: The wind farm data acquisition module is used to obtain the wind turbine model and its wind turbine rotor diameter in the wind farm, as well as the wind turbine arrangement information in the wind farm; A variable pitch characteristic database establishment module is used to establish a variable pitch characteristic database for wind turbines; An output power simulation system establishment module is used to construct a wind farm output power simulation system under variable pitch angle conditions based on a wind turbine pitch characteristic database, wind turbine rotor diameter, and turbine arrangement information, combined with a wind turbine analytical wake model; An optimization function establishment module is used to obtain the operating data of each unit in the wind farm in real time and input it into the wind farm output power simulation system under the variable pitch angle condition to establish an optimization function with the pitch angle of each unit as the independent variable and the total power of the wind farm as the dependent variable; The collaborative pitch control module is used to optimize the optimization function using a preset intelligent optimization algorithm to obtain the pitch angle combination of each unit with the maximum output power in the entire field under the current inflow conditions, and output the pitch angle optimization result to the main control system of each unit as its active pitch control instruction, so as to implement collaborative pitch control of each unit in the wind farm.

8. The wind farm coordinated control system based on active pitch control strategy according to claim 7, characterized in that: Also includes: The parameter correction module is used to obtain the power data fed back by the wind turbine generator set to correct the adjustable parameters in the simulation system online.

9. A computer device, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the wind farm collaborative control method based on the active pitch strategy as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the wind farm coordinated control method based on the active pitch strategy according to any one of claims 1 to 6.

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