Quantification method of active frequency support capability of wind farm considering wake effect

Abstract

A method for quantifying the active frequency support capability of a wind farm considering the wake effect: 1) A wind turbine consistency factor quantification strategy considering the kinetic energy and electromagnetic power increment of the wind turbine rotor is used to evaluate the operating status of a single wind turbine; 2) A wind farm wind turbine consistency control strategy based on the leader-follower algorithm is proposed to coordinate wind farm wind turbines with differentiated frequency support capabilities caused by different wind speeds due to the wake effect; 3) A wind farm active frequency support capability quantification strategy considering the wake effect is proposed to evaluate the active frequency support capability of the wind farm and maximize the active frequency support capability of the wind farm; the present invention considers the problem of different support capabilities of each wind turbine in the wind farm caused by the wake effect, and constructs a distributed consistency control strategy based on the kinetic energy and electromagnetic power increment of the wind turbine rotor, so that it can more fairly coordinate each wind turbine in the wind farm and maximize the active frequency support capability of the wind farm.

Description

Technical Field

[0001] The present invention belongs to the technical field of new energy power systems, and in particular provides a method for quantifying the active frequency support capability of a wind farm considering wake effects. Background Art

[0002] With the rapid development of large-scale wind farms, multi-terminal high-voltage direct current (HVDC) systems based on voltage source converters (VSCs) have become a flexible solution for large-scale integration and absorption of wind farms (Y. Xiong, W. Yao, J. Wen, et al., "Two-Level Combined Control Scheme of VSC-MTDC Integrated Offshore Wind Farms for Onshore System Frequency Support," IEEE Transactions on Power Systems, vol. 36, no. 1, pp. 781-792, Jan. 2021). As wind farms continue to expand and replace some traditional synchronous generators, the grid's rotational inertia and the corresponding frequency regulation capability are reduced. If the grid does not have sufficient rotational inertia, its frequency deviation and frequency change rate will increase, leading to frequency over-limit problems (Z. Lu, Y. Ye and Y. Qiao, "An Adaptive Frequency Regulation Method With Grid-Friendly Restoration for VSC-HVDC Integrated Offshore Wind Farms," ​​IEEE Transactions on Power Systems, vol. 34, no. 5, pp. 3582-3593, Sept. 2019). However, the traditional centralized control strategy that enables wind farms to participate in active frequency support does not consider the differentiated frequency support capabilities of wind turbines caused by different wind speeds due to the wake effect. The average active frequency support power provided by wind turbines can easily lead to insufficient frequency support capabilities for low-speed wind turbines, while sufficient or even excessive frequency support capabilities for high-speed wind turbines. Centralized control strategies also rely heavily on communication reliability and are susceptible to communication delays and failures (Z. Wang and W. Wu, "Coordinated Control Method for DFIG-Based Wind Farm to Provide Primary Frequency Regulation Service," IEEE Transactions on Power Systems, vol. 33, no. 3, pp. 2644-2659, May 2018). Therefore, a method to quantify the active frequency support capability of wind farms that considers wake effects is urgently needed.However, current wind farm consistency control methods only consider the influence of rotor kinetic energy (Y.Xiong, W Yao, Y.Yao, et al., "Distributed Cooperative Control of Offshore Wind Farms Integrated via MTDC System for Fast Frequency Support," IEEE Transactions on Industrial Electronics, vol. 70, no. 5, pp. 4693-4704, May 2023), ignoring the problem of wind turbine operating point offset caused by the active frequency support process, and are unable to accurately quantify the active frequency support capability of wind turbines. In order to quantify the active frequency support capability of wind farms under the influence of wake effects and maximize the provision of active frequency support services for wind farms;

[0003] Therefore, some people have applied for the following application to solve the above problems;

[0004] Application number: CN113394826B, Patent name: "Frequency support optimization configuration method for doubly-fed induction generator wind farm energy storage system" Technical comparison:

[0005] The technical solution for the "Frequency Support Optimization Configuration Method for Doubly Fed Induction Generator Wind Farm Energy Storage System" adopts a Pf control strategy, coupling the operating status of the wind turbine with the frequency changes of the system to achieve frequency support. However, the frequency support process does not take into account the differences in the support capacity of the wind turbine caused by the wake effect, and cannot fully utilize the frequency support capabilities of the wind turbine / wind farm.

[0006] In this paper, a method for quantifying the active frequency support capacity of wind turbines is proposed to address the situation where the wake effect causes differences in the support capacity of wind turbines. This method analyzes the changes in kinetic energy and electromagnetic power during the dynamic support process of wind turbines. Through a distributed consistency control strategy, wind turbines can achieve "machine-farm" coordination and operate in the same state. Based on this, a method for quantifying the active frequency support capacity of wind farms is constructed to give full play to the active frequency support capacity of wind turbines / wind farms.

[0007] Application number: CN113489073A, Patent name: "A multi-temporal and spatial layered integrated frequency modulation control system based on wind turbine clusters" Technical comparison:

[0008] The technical solution of "a multi-temporal and spatial layered integrated frequency regulation control system based on wind turbine clusters" takes into account the influence of the wake effect and realizes differentiated support of wind turbines by dividing wind turbines into different wind speed ranges. However, this only considers wind turbines in three different wind speed ranges and cannot fully characterize the active frequency support capability of wind turbines, nor can it fully exert the frequency support capability of wind turbines / wind farms.

[0009] In this paper, a method for quantifying the active frequency support capability of wind turbines is proposed to address the situation where the wake effect causes differences in the support capability of wind turbines. This method analyzes the changes in rotor kinetic energy and output electromagnetic power during the dynamic process of transient frequency support of wind turbines. Through a distributed consistency control strategy, wind turbines can achieve "machine-farm" coordination and operate in the same state. Based on this, a method for quantifying the active frequency support capability of wind farms is constructed to give full play to the active frequency support capability of wind turbines / wind farms.

[0010] This paper addresses the problem that large-scale wind farms are affected by the wake effect, resulting in differences in the active frequency support capabilities of wind turbines. A method for quantifying the active frequency support capabilities of wind farms considering the wake effect is proposed. The kinetic energy changes and electromagnetic power changes in the dynamic process of turbine support are considered, and a method for quantifying the active frequency support capabilities of wind turbines is proposed. Through a distributed consistency control strategy, wind turbines are enabled to achieve "machine-farm" coordination and operate in the same state. Based on this, a method for quantifying the active frequency support capabilities of wind farms is constructed to give full play to the active frequency support capabilities of wind turbines / wind farms. Summary of the Invention

[0011] To solve the above technical problems, the present invention proposes a method for quantifying the active frequency support capability of wind farms considering the wake effect. In response to the development trend of new energy power systems, the present invention considers the impact of wake effects and other factors on the active frequency support capability of large-scale wind farms, and realizes the evaluation and maximization of the active frequency support capability of wind farms.

[0012] To achieve the above object, the technical solution adopted by the present invention is:

[0013] A method for quantifying the active frequency support capability of a wind farm considering the wake effect is characterized in that the method comprises the following steps:

[0014] 1) A wind turbine consistency factor quantification strategy considering the wind turbine rotor kinetic energy and electromagnetic power increment is used to evaluate the operating status of a single wind turbine;

[0015] 2) A wind farm wind turbine consistency control strategy based on the leader-follower algorithm is proposed to coordinate wind farm wind turbines with differentiated frequency support capabilities caused by different wind speeds due to the wake effect;

[0016] 3) A quantitative strategy for the active frequency support capability of wind farms considering the wake effect is proposed to evaluate the active frequency support capability of wind farms and maximize the active frequency support capability of wind farms.

[0017] Further, step (1) is specifically as follows;

[0018] Due to the influence of the wake effect, the wind speed received by each wind turbine in an offshore wind farm is different. Each wind turbine is in different operating conditions. The wind speed received by each wind turbine in an offshore wind farm can be solved according to the Jensen wake effect model. It is calculated by the wind speed received by the previous wind turbine and the Jensen wake coefficient. The formula is as follows:

[0019]

[0020] Where v1 and v0 represent the wind speed received by the rear and front fans respectively, D represents the diameter of the fan, k represents the wake influence coefficient, and C T represents the thrust coefficient of the wind, which is mainly affected by the air density ρ, wind speed, and rotor area S. x represents the straight-line distance between the wind turbines;

[0021] The rear-end wind turbines are often affected by the wake effects of multiple front-end wind turbines. The specific calculation is:

[0022]

[0023] where v ω0,ki (t) is the input wind speed of the i-th wind turbine at time t, taking into account the wake effect of the k-th upstream wind turbine, v i0 (t) is the input wind speed of the hypothetical i-th wind turbine without being affected by the wake of any upstream wind turbine, β k =A shad,ik / A ort,i is the ratio of the projected area of ​​the kth wind turbine at the i-th wind turbine to the swept area of ​​the i-th wind turbine, and N is the number of wind turbines in the wind farm;

[0024] Taking into account the dynamic response process of wind turbines providing active frequency support, when the system is in normal operation, wind farm wind turbines all adopt the maximum efficiency tracking strategy and operate at the maximum power point to obtain maximum economic benefits. When a system failure causes the grid frequency to drop, the wind farm needs to increase active power output to provide active frequency support services. During the period when the wind turbine provides active frequency support services, the wind turbine releases the rotor kinetic energy stored in the rotor to increase active power output. However, the release of rotor kinetic energy will cause the wind turbine speed to decrease, causing its operating point to shift, which in turn leads to a reduction in wind energy captured from the environment. Therefore, when the wind turbine releases rotor kinetic energy to provide active frequency support, part of the power converted from the rotor kinetic energy is used to provide active frequency support services, and the other part of the power is used to compensate for the reduction in wind energy capture caused by the shift in the wind turbine operating point due to the reduction in rotor speed. Based on the relationship between electromagnetic power and rotor kinetic energy, the support power ΔP provided by the wind turbine is calculated. e,i :

[0025]

[0026] where ω r,i0 represents the initial rotor speed of the wind turbine, Δω represents the rotor speed adjustment per unit time, Δt represents the unit time, k opt Indicates the slope of the MPPT curve;

[0027] By modifying formula (4), it can be expressed as:

[0028]

[0029] Assuming that all wind turbines in the wind farm are in the position of tracking maximum efficiency, based on the limitation of rotor speed, the maximum and minimum values ​​of formula (5) can be expressed as:

[0030]

[0031] where ω r,n is the rated rotor speed, ω r,min The minimum rotor speed for the fan in the maximum efficiency tracking working area;

[0032] In order to ensure that the wind turbine rotor speed operates within the safe range of 0.7pu~1.2pu, according to the leader-follower consensus algorithm, by considering the support power and rotor speed, the consensus coefficient x of the wind turbine adjacent coordination is obtained. i :

[0033]

[0034] Furthermore, step (2) is as follows:

[0035] Based on the leader-follower consensus algorithm control strategy, the power difference between adjacent wind turbines is expressed as:

[0036]

[0037] where ΔP an,i represents the power difference between the adjacent wind turbines of the i-th wind turbine based on the leader-follower consensus algorithm, K P,i and K I,i represents the proportional coefficient and integral coefficient of the i-th fan; a ij =1 means there is direct communication between the i-th wind turbine and the j-th wind turbine, otherwise, a ij =0; L and K represent the number of leader wind turbines and follower wind turbines in the wind farm;

[0038] According to the leader-follower consensus algorithm, the leader wind turbine acts as a reference to guide the follower wind turbines to jointly provide frequency support services. The follower wind turbines communicate and exchange consensus power differences ΔP with adjacent wind turbines. an To track the status of the leader wind turbine, since the DC voltage can reflect the fluctuation of the onshore power grid frequency, a DC voltage droop controller is added to the maximum efficiency tracking controller of the leader wind turbine to respond to the changes in the onshore power grid frequency. In order to coordinate the various wind turbines in the wind farm and provide active frequency support, a new DCS is proposed based on the consideration of rotor kinetic energy and the capture of wind power changes to fairly control the support power reference values ​​of the leader and follower wind turbines. The details are as follows:

[0039]

[0040] Among them, P leader,ref,l and P follower,ref,k Represent the support rate of the lth leader wind turbine and the kth follower wind turbine, ΔP an,l and ΔP an,k The power difference ΔP of adjacent wind turbines in (6) an,i Rewritten according to the corresponding l-th wind turbine and k-th wind turbine, x l The consensus coefficient x of adjacent wind turbine coordination in (5) is i Rewritten, k dc Indicates the droop control coefficient, U dc Indicates the DC voltage of the offshore converter station.

[0041] Further, step (3) is as follows:

[0042] Assuming that a wind farm contains L leader wind turbines and K follower wind turbines, and considering the difference in the reference power supported by the leader wind turbine and the follower wind turbine, when a frequency disturbance occurs in the power grid, the transient support capacity provided by the wind farm is expressed as:

[0043]

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] The present invention adopts a method for quantifying the active frequency support capability of a wind farm considering the wake effect. It considers the impact of the wake effect of a large-scale wind farm on each wind turbine, and coordinates each wind turbine through a distributed consistency control strategy. Finally, the active frequency support capability of the wind farm is evaluated by the active frequency support power provided by the leader wind turbine and the follower wind turbine in the wind farm. It has high practical value in the active frequency support capability of a new power system containing a large-scale wind farm. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a flow chart of fan control in the present invention;

[0047] Figure 2 This is a working principle diagram of the fan of the present invention providing active frequency support service;

[0048] Figure 3 This is a distributed consistent wind farm communication network diagram adopted by the present invention;

[0049] Figure 4 is the topological structure diagram of the example;

[0050] Figure 5 It is the small signal stability analysis diagram of the example model;

[0051] Figure 6 This is a schematic diagram of the wake effect of a wind turbine;

[0052] Figure 7 It takes into account the speed of each wind turbine in the wind farm under the wake effect;

[0053] Figure 8 This is a comparison chart between the distributed consistency control strategy proposed by the present invention and the traditional solution;

[0054] Figure 9 This is a real-time fan speed simulation diagram under the traditional centralized control strategy;

[0055] Figure 10 This is a real-time simulation diagram of the fan speed using the distributed consistency control strategy proposed by the present invention;

[0056] Figure 11 This is a simulation diagram of real-time formula coefficients under the traditional centralized control strategy;

[0057] Figure 12 This is a simulation diagram of the real-time formula coefficients of the distributed consistency control strategy proposed by the present invention. DETAILED DESCRIPTION

[0058] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be interpreted as limiting the present invention.

[0059] The present invention discloses a method for quantifying the active frequency support capability of a wind farm considering the wake effect, including the evaluation of the operating status of a single wind turbine, the distributed consistency control of wind turbines in a wind farm based on a leader-follower algorithm, and the method for quantifying the active frequency support capability of a wind farm. The wind turbine control flow chart is shown in FIG. Figure 1 As shown, by inputting the rotational inertia and real-time wind speed of each wind turbine, the active support capability of each wind turbine can be evaluated, and frequency support can be coordinated based on the active support capability to maximize the frequency support capability of the wind farm.

[0060] The fan provides active frequency support service working principle as follows Figure 2 As shown in Figure 1, under normal circumstances, wind turbines operate in maximum power point tracking (MPPT) mode to achieve maximum economic benefits. In the event of a frequency fault in the power grid, the wind turbine rotor is triggered to release kinetic energy, increasing the active power of the wind turbine to provide active frequency support services. Figure 2 As shown in (a), during the frequency support service, the electromagnetic power of the wind turbine changes from y1 (MPPT curve) to y2 (frequency support power reference curve). Due to the effect of rotor inertia, the rotor speed of the wind turbine will not change suddenly, so the operating point of the wind turbine will first change from point A to point B, and then gradually change to point C. At the end of active frequency support, since point C in y2 is not a stable operating point, the operating point of the wind turbine will eventually move from point C to point D. In actual applications, the electromagnetic power at point C is usually greater than that at point A. The reduction in wind power capture between points A and D is ΔP ω At the same time, when the wind turbine operating point changes from point A to point B and then to point C, the wind turbine releases rotor kinetic energy ΔE e . With ΔE e The corresponding power generation is ΔPKE. Figure 2 As shown in (b), ΔP KE The incremental support power ΔP e,i and wind power capture to reduce power ΔP ω composition.

[0061] Distributed consistent wind farm communication network such as Figure 3 As shown in Figure 1, a distributed consistency strategy based on the leader-follower consensus algorithm is adopted for wind farms to reduce the communication burden and share the frequency support power more fairly. Assume that there are 25 wind turbines in the wind farm and they are divided into Figure 3(a) shows five wind turbine strings. Each string consists of five wind turbines, representing the leading wind turbine and the following wind turbine. The wind turbine communication network is designed based on the actual geographical location. Figure 3 As shown in (b), each wind turbine communicates with the connected wind turbines in the same string to ensure communication reliability and exchange consensus coefficients to provide active frequency support services based on its own status. Therefore, setting a reasonable consensus coefficient is the key to distributed consistency.

[0062] The topological structure of the example is as follows Figure 4 As shown in the figure, the example system is a 4-machine, 11-node system. In this test system, there are two wind farms, each containing 3, 12, and 15 wind turbines arranged in a matrix. The wind farms are connected to an onshore grid consisting of 4 turbines (G1 to G4) and 11 nodes via a VSC-MTDC system. Three converter stations (Converter Station 1 to Converter Station 3) are connected to nodes 4, 6, and 8 of the onshore grid. The rated frequency and voltage of the grid are 50 Hz and 220 kV, respectively.

[0063] To analyze the impact of the DC voltage droop control parameters of converter station 1 on system stability, the control platform was linearized using the Model Linearization Toolbox in MATLAB / Simulink to analyze the changes in its eigenvalues. Based on small signal analysis, input and output points were selected to construct zero-pole diagrams for different control parameters. The root locus trends of the eigenvalues ​​in the zero-pole diagrams for different control parameters are shown in the figure below. Figure 5 As shown in the figure, as the DC voltage droop control parameter of converter station 1 varies between 5 and 25, the damping ratio (DR) of most critical eigenvalues ​​in its zero-pole diagram remains greater than 0.06. This demonstrates that the system is highly robust when the DC voltage droop control parameter of VSC1 changes.

[0064] The wake effect of wind turbines is as follows Figure 6 As shown in Figure 2, since the upstream wind turbines will block the downstream wind turbines, the wind speed received by the downstream wind turbines will be reduced. Under the influence of the same headwind speed and wake effect, four different wind directions (0°, 30°, 60°, and 90°) are shown. Figure 6 shown.

[0065] The following is a specific example to verify the technical solution of the present invention. Figure 3 is the example structure, and according to Figure 3The constructed wind turbine communication network, when the load on the land AC system suddenly increases within 5s, causing the frequency of the land AC system to drop, at this time, the wind turbines in the wind farm will switch from the maximum power operation state to the frequency support state, and the wind turbines will release their own rotor kinetic energy to increase the active power output to provide frequency support services. In order to compare and verify the effectiveness and superiority of the present invention, a centralized control strategy and the new distributed consistency control strategy proposed by the present invention were used for comparison. The simulation results are as follows Figures 8-12 shown.

[0066] The active frequency support capability of a wind farm is affected by the release of rotor kinetic energy by the rotors of different wind turbines. Different wind directions (0°, 30°, 60°, 90°) and wake effects lead to different speed distributions and active frequency support capabilities of wind turbines within a wind farm. When the onshore AC system is subject to a large disturbance, the wind turbines within the wind farm will release rotor kinetic energy and provide active frequency support services for the onshore power grid. The rotor speed comparison between the distributed consistency strategy proposed in this invention and the traditional centralized control strategy is shown in Figure 2. Figure 8 As shown. As can be seen from the figure, the rotor speed of the wind turbine of the distributed consistency strategy proposed by the present invention corresponds to the overall height of the bar graph, the rotor speed of the wind turbine after providing active frequency support services corresponds to the height of the lower half of the bar graph, and the height of the upper half of the bar graph represents the amount of rotor speed reduction caused by the release of rotor kinetic energy due to the provision of active frequency support services. Under different wind directions, the rotor speed reduction of the traditional centralized control strategy is equal / average, while the rotor speed reduction of the distributed consistency strategy proposed by the present invention varies depending on the speed. Therefore, the traditional centralized control strategy may not be able to provide sufficient support power, thereby reducing the support effect. For example, when the wind direction is 0° or 90°, the rotor speed of the wind turbine under the traditional centralized control strategy may be close to the minimum threshold of 0.7pu. However, in order to fully utilize the active frequency support capability of the wind farm, the distributed consistency strategy proposed by the present invention can enable high-speed wind turbines to provide more support power, while low-speed wind turbines provide less support power.

[0067] Taking the wind direction 0° as an example, the rotor speed and consensus coefficient x of the wind turbine under the distributed consistency strategy proposed in this invention and the traditional centralized control strategy are i like Figure 9-10 and Figure 11-12 As shown. It can be seen that under the condition of releasing the same rotor kinetic energy, the traditional centralized control strategy makes the speed reduction of low-speed wind turbines greater than that of high-speed wind turbines, and x iCompletely inconsistent, with large differences. To maximize the support capabilities of different wind turbines and avoid triggering protection or shutdown of low-speed wind turbines, the distributed consensus strategy proposed in this invention causes high-speed wind turbines to release more rotor kinetic energy and low-speed wind turbines to release less rotor kinetic energy. The consensus coefficient xi is highly consistent with the case with smaller differences.

[0068] The above description is merely a preferred embodiment of the present invention and does not constitute any other form of limitation to the present invention. Any modification or equivalent variation based on the technical essence of the present invention shall still fall within the scope of protection claimed by the present invention.

Claims

1. A quantification method for active frequency support capability of wind farms considering wake effect, characterized in that: The method comprises the following steps: 1) A wind turbine consistency factor quantification strategy considering the wind turbine rotor kinetic energy and electromagnetic power increment is used to evaluate the operating status of a single wind turbine; 2) A wind farm wind turbine consistency control strategy based on the leader-follower algorithm is proposed to coordinate wind farm wind turbines with differentiated frequency support capabilities caused by different wind speeds due to the wake effect; Step 2) is as follows: Based on the leader-follower consensus algorithm control strategy, the power difference between adjacent wind turbines is expressed as: (9) where ΔP an,i represents the power difference between the adjacent wind turbines of the i-th wind turbine based on the leader-follower consensus algorithm, K P,i and K I,i represents the proportional coefficient and integral coefficient of the i-th fan; a ij =1 means there is direct communication between the i-th wind turbine and the j-th wind turbine, otherwise, a ij =0; L and K represent the number of leader wind turbines and follower wind turbines in the wind farm; According to the leader-follower consensus algorithm, the leader wind turbine acts as a reference to guide the follower wind turbines to jointly provide frequency support services. The follower wind turbines communicate and exchange consensus power differences ΔP with adjacent wind turbines. an To track the status of the leader wind turbine, since the DC voltage can reflect the fluctuation of the onshore power grid frequency, a DC voltage droop controller is added to the maximum efficiency tracking controller of the leader wind turbine to respond to the changes in the onshore power grid frequency. In order to coordinate the various wind turbines in the wind farm and provide active frequency support, a new DCS is proposed based on the consideration of rotor kinetic energy and the capture of wind power changes to fairly control the support power reference values ​​of the leader and follower wind turbines. The details are as follows: (10) (11) Among them, P leader,ref,l and P follower,ref,k Represent the support rate of the lth leader wind turbine and the kth follower wind turbine, ΔP an,l and ΔP an,k The power difference ΔP of adjacent wind turbines in (6) an,i Rewritten according to the corresponding l-th wind turbine and k-th wind turbine, x l The consensus coefficient x of adjacent wind turbine coordination in (5) is i Rewritten, k dc Indicates the droop control coefficient, U dc Indicates the DC voltage of the offshore converter station; 3) A quantitative strategy for the active frequency support capability of wind farms considering the wake effect is proposed to evaluate the active frequency support capability of wind farms and maximize their active frequency support capability. Step 3) is as follows: Assuming that a wind farm contains L leader wind turbines and K follower wind turbines, and considering the difference in the reference power supported by the leader wind turbine and the follower wind turbine, when a frequency disturbance occurs in the power grid, the transient support capacity provided by the wind farm is expressed as: (12)。 2. The method for quantifying the active frequency support capability of a wind farm considering the wake effect according to claim 1 is characterized in that: Step 1) is as follows; Due to the influence of the wake effect, the wind speed received by each wind turbine in an offshore wind farm is different. Each wind turbine is in different operating conditions. The wind speed received by each wind turbine in an offshore wind farm can be solved according to the Jensen wake effect model. It is calculated by the wind speed received by the previous wind turbine and the Jensen wake coefficient. The formula is as follows: (1) (2) Where v1 and v0 represent the wind speed received by the rear and front fans respectively, D represents the diameter of the fan, k represents the wake influence coefficient, and C T represents the thrust coefficient of the wind, which is mainly affected by the air density ρ, wind speed, and rotor area S. x represents the straight-line distance between the wind turbines; The rear-end wind turbines are often affected by the wake effects of multiple front-end wind turbines. The specific calculation is: (3) where v ω0,ki (t) is the input wind speed of the i-th wind turbine at time t, taking into account the wake effect of the k-th upstream wind turbine, v i0 (t) is the input wind speed of the hypothetical i-th wind turbine without being affected by the wake of any upstream wind turbine, β k =A shad,ik / A ort,i is the ratio of the projected area of ​​the kth wind turbine at the i-th wind turbine to the swept area of ​​the i-th wind turbine, and N is the number of wind turbines in the wind farm; Taking into account the dynamic response process of wind turbines providing active frequency support, when the system is in normal operation, wind farm wind turbines all adopt the maximum efficiency tracking strategy and operate at the maximum power point to obtain maximum economic benefits. When a system failure causes the grid frequency to drop, the wind farm needs to increase active power output to provide active frequency support services. During the period when the wind turbine provides active frequency support services, the wind turbine releases the rotor kinetic energy stored in the rotor to increase active power output. However, the release of rotor kinetic energy will cause the wind turbine speed to decrease, causing its operating point to shift, which in turn leads to a reduction in wind energy captured from the environment. Therefore, when the wind turbine releases rotor kinetic energy to provide active frequency support, part of the power converted from the rotor kinetic energy is used to provide active frequency support services, and the other part of the power is used to compensate for the reduction in wind energy capture caused by the shift in the wind turbine operating point due to the reduction in rotor speed. Based on the relationship between electromagnetic power and rotor kinetic energy, the support power ΔP provided by the wind turbine is calculated. e,i : (4) where ω r,i0 represents the initial rotor speed of the wind turbine, Δω represents the rotor speed adjustment per unit time, Δt represents the unit time, k opt Indicates the slope of the MPPT curve; By modifying formula (4), it can be expressed as: (5) Assuming that all wind turbines in the wind farm are in the position of tracking maximum efficiency, based on the limitation of rotor speed, the maximum and minimum values ​​of formula (5) can be expressed as: (6) (7) where ω r,n is the rated rotor speed, ω r,min The minimum rotor speed for the fan in the maximum efficiency tracking working area; In order to ensure that the wind turbine rotor speed operates within the safe range of 0.7pu~1.2pu, according to the leader-follower consensus algorithm, by considering the support power and rotor speed, the consensus coefficient x of the wind turbine adjacent coordination is obtained. i : (8)。

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