Wind power plant active frequency supporting capability quantification method considering wake effect

Abstract

The invention discloses a wind power plant active frequency supporting capacity quantification method considering a wake effect. The method comprises the following steps: 1) a fan consistency factor quantification strategy considering fan rotor kinetic energy and electromagnetic power increment is used for evaluating the running state of a single fan; 2) putting forward a wind power plant fan consistency control strategy based on a leader-follower algorithm for cooperating with wind power plant fans with differentiated frequency supporting capabilities caused by different wind speeds due to a wake flow effect; 3) proposing a wind power plant active frequency support capability quantification strategy considering the wake effect for evaluating the active frequency support capability of the wind power plant so as to maximize the active frequency support capability of the wind power plant; according to the method, the problem of supporting capacity difference of each fan of the wind power plant caused by the wake effect is considered, and a distributed consistency control strategy is constructed according to the kinetic energy of the fan rotor and the electromagnetic power increment, so that each fan in the wind power plant is more fairly coordinated, and the active frequency supporting capacity of the wind power plant is maximized.

Description

Technical Field

[0001] The present invention belongs to the technical field of new energy power systems, and specifically is a method for quantifying active frequency support capability of a wind farm taking into account wake effects. Background Art

[0002] With the rapid development of large-scale wind farms, multi-terminal high-voltage direct current systems based on voltage source converters 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 the scale of wind farms continues to expand and replace some traditional synchronous generators, the grid's rotational inertia and corresponding frequency regulation capabilities are reduced. If the grid does not have enough 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 enables wind farms to participate in active frequency support methods without considering the differentiated frequency support capacity of wind turbines caused by different wind speeds due to the wake effect. The average active frequency support power provided by wind turbines is likely to lead to insufficient frequency support capacity of low-speed wind turbines, while the frequency support capacity of high-speed wind turbines is sufficient or even excessive. At the same time, the centralized control strategy needs to be highly dependent on communication reliability and is easily affected by communication delays and communication 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, there is an urgent need for a method to quantify the active frequency support capability of a wind farm that takes into account the wake effect.However, the current wind farm consistency control method only considers 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 active frequency support, and cannot 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 effect, and at the same time maximize the provision of active frequency support services for wind farms;.

[0003] Therefore, some people are currently applying for the following application to solve the above problems;

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

[0005] The technical solution of “Frequency Support Optimization Configuration Method for Doubly-Fed Induction Generator Wind Farm Energy Storage System” adopts the Pf control strategy to couple the operating status of the wind turbine with the frequency change of the system to achieve frequency support. However, in the frequency support process, the difference in the support capacity of the wind turbine caused by the wake effect is not taken into account, and the frequency support capacity of the wind turbine / wind farm cannot be fully utilized.

[0006] Aiming at the situation where the support capacity of wind turbines varies due to wake effect, this paper proposes a quantification method for the active frequency support capacity of wind turbines by analyzing the changes in kinetic energy and electromagnetic power during the dynamic process of wind turbine support. Through the distributed consistency control strategy, the wind turbines can achieve "machine-farm" coordination and the wind turbines can operate in the same state. Based on this, a quantification method for 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 control system based on wind turbine clusters" takes into account the influence of the wake effect, and realizes differentiated support for wind turbines by dividing wind turbines into different wind speed ranges. However, this only considers wind turbines in three different wind speed ranges, which cannot fully characterize the active frequency support capability of wind turbines, and cannot fully exert the frequency support capability of wind turbines / wind farms.

[0009] Aiming at the situation where the support capacity of wind turbines varies due to wake effect, this paper proposes a quantification method for the active frequency support capacity of wind turbines by analyzing the changes in rotor kinetic energy and output electromagnetic power during the dynamic process of transient frequency support of wind turbines. Through the distributed consistency control strategy, the wind turbines can achieve "machine-farm" coordination and the wind turbines can operate in the same state. Based on this, a quantification method for 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.

[0010] In this paper, a method for quantifying the active frequency support capacity of wind turbines is proposed to address the problem that large-scale wind farms are affected by the wake effect, resulting in differences in the active frequency support capacity of wind turbines. The method takes into account the kinetic energy changes and electromagnetic power changes in the dynamic process of turbine support, and through a distributed consistency control strategy, the 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 capacity of wind farms is constructed to give full play to the active frequency support capacity of wind turbines / wind farms. Summary of the invention

[0011] In order to solve the above technical problems, the present invention proposes a method for quantifying the active frequency support capability of a wind farm taking into account the wake effect. Aiming at the development trend of new energy power systems, the present invention considers the impact of wake effects and the like 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 active frequency support capability of a wind farm considering wake effect, 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 the offshore wind farm is different. Each wind turbine is in different operating conditions. The wind speed received by each wind turbine in the offshore wind farm can be solved according to the Jensen wake effect model, and 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 wind, which is mainly affected by air density ρ, wind speed, and rotor area S. x represents the straight-line distance between wind turbines;

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

[0022]

[0023] where v ω0,ki (t) is the input wind speed of the i-th wind turbine considering the wake effect of the k-th upstream wind turbine at time t, v i0 (t) is the input wind speed of the hypothetical i-th wind turbine that is not 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 wheel 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 the maximum economic benefit. When a system failure causes the grid frequency to drop, the wind farm needs to increase the 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 the 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, a 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. According to 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 adjacent coordination of the wind turbine is obtained: i :

[0033]

[0034] Further, 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 indicates that there is a direct communication link 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 neighboring 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 change of 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, as follows:

[0039]

[0040] Among them, P leader,ref,l and P follower,ref,k Represent the support rate of the lth leader fan and the kth follower fan, ΔP an,l and ΔP an,k The power difference ΔP of adjacent wind turbines in (6) an,i Rewritten according to the corresponding lth and kth fans, x l The consensus coefficient x of adjacent wind turbine coordination in (5) is i Rewritten, k dc represents 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 the wind farm contains L leader wind turbines and K follower wind turbines, considering the difference in the reference value of the support power between the leader wind turbine and the follower wind turbine, when the grid frequency disturbance occurs, 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, which takes into account the impact of the wake effect of a large-scale wind farm on each wind turbine set, and coordinates each wind turbine set 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 of the wind farm. The active frequency support capability of a new power system containing a large-scale wind farm has high practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a flow chart of fan control of 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 It 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] Fig. 9 It is a real-time fan speed simulation diagram under the traditional centralized control strategy;

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

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

[0057] Fig.12 It 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 cannot 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 single wind turbine operation status evaluation, wind farm wind turbine distributed consistency control based on a leader-follower algorithm, and a method for quantifying the active frequency support capability of a wind farm, wherein the wind turbine control flow chart is as follows: 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 according to the active support capability to maximize the frequency support capability of the wind farm.

[0060] The fan provides active frequency support service. 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 reduces 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, which 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 of which contains 3, 12, and 15 wind turbines arranged in a matrix. The wind farm is connected to the 4-machine (G1~G4) 11-node onshore power grid through the VSC-MTDC system. Three converter stations (converter station 1~converter station 3) are connected to the onshore grid nodes 4, 6, and 8. The rated frequency and voltage of the grid are 50Hz and 220kV, respectively.

[0063] In order to analyze the influence of the DC voltage droop control parameters of the converter station 1 on the system stability, the control platform is linearized using the model linearization toolbox in MATLAB / Simulink to analyze the changes in its eigenvalues. According to the small signal analysis, the input and output points are selected to construct the zero-pole diagram with different control parameters. The root locus trend of the eigenvalues ​​in the zero-pole diagram under different control parameters is shown in the figure. Figure 5 As shown. It can be seen that as the DC voltage droop control parameter of converter station 1 changes between 5 and 25, the damping ratio (DR) of most critical eigenvalues ​​in its zero-pole diagram is still greater than 0.06. This proves that when the DC voltage droop control parameter of VSC1 changes, the system has strong robustness.

[0064] The wake effect of wind turbines is as follows Figure 6 As shown in Figure 1, the upstream wind turbine will block the downstream wind turbine, thereby reducing the wind speed received by the downstream wind turbine. Under the same headwind speed and wake effect, four different wind directions (0°, 30°, 60°, 90°) are shown in Figure 1. Figure 6 shown.

[0065] The technical solution of the present invention is verified by a specific example below. Figure 3 is the example structure, and according to Figure 3The constructed wind turbine communication network, when the load in the land AC system suddenly increases within 5s, causing the frequency of the land AC system to drop, at this time, the wind farm wind turbine will switch from the maximum power operation state to the frequency support state, and the wind turbine will release its 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 are used for comparison. The simulation results are shown in the figure. Figure 8-Figure 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 in a wind farm. When the onshore AC system is subject to a large disturbance, the wind turbines in the wind farm will release rotor kinetic energy to 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. It can be seen from the figure that the rotor speed of the wind turbine set of the distributed consistency strategy proposed in the present invention corresponds to the overall height of the bar graph, the rotor speed of the wind turbine set 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 reduction in rotor speed 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 in 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 set under the traditional centralized control strategy may be close to the minimum threshold of 0.7pu. However, in order to make full use of the active frequency support capability of the wind farm, the distributed consistency strategy proposed in the present invention enables high-speed wind turbines to provide more support power, while low-speed wind turbines provide less support power.

[0067] Taking the wind direction of 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 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 iIn order to maximize the support capabilities of different wind turbines and avoid triggering the protection or shutdown of low-speed wind turbines, the distributed consistency strategy proposed in the present invention will make high-speed wind turbines release more rotor kinetic energy and low-speed wind turbines release less rotor kinetic energy, and the consensus coefficient xi is highly consistent with the case with small differences.

[0068] The above description is only a preferred embodiment of the present invention and does not constitute any other form of limitation to the present invention. Any modification or equivalent change made based on the technical essence of the present invention still falls within the scope of protection required by the present invention.

Claims

1. A method for quantifying active frequency support capability of a wind farm 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; 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.

2. The method for quantifying active frequency support capability of a wind farm considering 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 the offshore wind farm is different. Each wind turbine is in different operating conditions. The wind speed received by each wind turbine in the offshore wind farm can be solved according to the Jensen wake effect model, and calculated by the wind speed received by the previous wind turbine and the Jensen wake coefficient. The formula is as follows: 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 wind, which is mainly affected by air density ρ, wind speed, and rotor area S. x represents the straight-line distance between wind turbines; The rear wind turbines are often affected by the wake effect of multiple front wind turbines. The specific calculation is: where v ω0,ki (t) is the input wind speed of the i-th wind turbine considering the wake effect of the k-th upstream wind turbine at time t, v i0 (t) is the input wind speed of the hypothetical i-th wind turbine that is not 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 wheel 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 the maximum economic benefit. When a system failure causes the grid frequency to drop, the wind farm needs to increase the 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 the 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, a 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. According to the relationship between electromagnetic power and rotor kinetic energy, the support power ΔP provided by the wind turbine is calculated. e,i : 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: 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: 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 adjacent coordination of the wind turbine is obtained: i :

3. The method for quantifying active frequency support capability of a wind farm considering wake effect according to claim 1 is characterized in that: Step 2) is as follows: Based on the leader-follower consensus algorithm control strategy, the power difference between adjacent wind turbines is expressed as: 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 indicates that there is a direct communication link 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 neighboring 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 change of 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, as follows: Among them, P leader,ref,l and P follower,ref,k Represent the support rate of the lth leader fan and the kth follower fan, ΔP an,l and ΔP an,k The power difference ΔP of adjacent wind turbines in (6) an,i Rewritten according to the corresponding lth and kth fans, x l The consensus coefficient x of adjacent wind turbine coordination in (5) is i Rewritten, k dc represents the droop control coefficient, U dc Indicates the DC voltage of the offshore converter station.

4. The method for quantifying active frequency support capability of a wind farm considering wake effect according to claim 1 is characterized in that: Step 3) is as follows: Assuming that the wind farm contains L leader wind turbines and K follower wind turbines, considering the difference in the reference value of the support power between the leader wind turbine and the follower wind turbine, when the grid frequency disturbance occurs, the transient support capacity provided by the wind farm is expressed as:

Images