A method for quantifying virtual inertia support capacity and allocating load shedding power in wind farms

Abstract

The invention discloses a method for quantifying virtual inertia support capacity and allocating load shedding power in a wind farm, comprising calculating the inertial response capacity H of the wind turbine set under MPPT, overspeed load shedding and underspeed load shedding modes based on the parameters of the wind turbine set. w1 , H w2 and H w3 , and obtain the operating inertia constant range of each wind turbine; calculate the wind turbine wake speed affected by the Jensen wake effect, and correct the wake wind speed to obtain the corrected wake wind speed; calculate the wind power P captured by the wind turbine based on the corrected wake wind speed w (t); Based on P w (t) Update H w2 and H w3 , thereby updating the inertia constant range; calculating the wake influence factor B of the wind turbines in the wind farm on the kth wind turbine k , based on B k Update the corrected wake wind speed to obtain the corrected wind speed of the wind turbine; based on H w1 、After update H w2 and the wind turbine corrected wind speed, and calculate the weight coefficient γ of each wind turbine i , based on γ i Allocate the overall inertia response capability and load shedding power demand of the wind farm obtained in real time. Flexibly adjust the wind power virtual inertia and load shedding power.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy power systems, and in particular to a method for quantifying virtual inertia support capacity of a wind farm and allocating load shedding power. Background Art

[0002] In the power system, synchronous generators, which occupy a large scale in the power system, have long been actively providing the inertia and damping requirements required by the power system. When the power is unbalanced, they can respond immediately and keep it within the acceptable range of the system. Their inertia response capability and effect have been well mastered. In order to further control carbon emissions, the green and low-carbon transformation of the power system has become a basic orientation. Renewable energy generation connected to the grid using inverters has developed rapidly and has occupied an increasing share in the power generation structure. Compared with synchronous generators, renewable energy connected to the grid using inverters cannot provide or can only provide very little inertia response support. At the same time, with the increase in the commissioning of high-voltage direct current transmission projects and the replacement of direct-coupled motor loads by power electronic loads, the system inertia level will further deteriorate.

[0003] With the increasing maturity of control technology, the configuration of inverters based on virtual inertia enables renewable energy to contribute to frequency regulation and inertia support, and has been applied in many scenarios, such as wind and photovoltaic power stations, high-voltage direct current transmission, energy storage systems (ESS), microgrids, static synchronous compensators (STATCOM), etc. The configuration of virtual inertia makes the system frequency minimum point and RoCoF (Rate of Change of Frequency) and other frequency stability indicators perform better, and also has a positive effect on response time and frequency recovery time.

[0004] Virtual inertia technology is a technology that enables renewable energy to provide frequency support services through control means. It is used to replace the inertia support of synchronous generators and achieve the specified performance level. The means that can be used to cope with frequency changes in wind power generation are mainly divided into two categories: the first category is inertia simulation, rapid power reserve and droop technology, etc., which release the reserve power of renewable energy in low-frequency disturbance events through flexible settings of the controller; the second category is load reduction technology, which allows renewable energy to retain a certain amount of reserve power, but it will cause energy loss, so a balance must be made between system stability requirements and costs.

[0005] Since most renewable energy sources are dependent on weather conditions and have significant intermittent characteristics, fluctuations in weather conditions will directly affect the output and inertia response capabilities of renewable energy sources, which in turn will lead to changes in the number of synchronous generators connected to the grid in the system, making the inertia level assessment of the power system more complicated. Therefore, when assessing the inertia level of the system, the support capacity assessment of wind power virtual inertia becomes a key link.

[0006] Existing technologies have failed to adequately address the intermittent and instability issues of wind farms when providing inertia response due to meteorological conditions. Wind farms are generally considered to be like synchronous generators with fixed constants or no inertia response capabilities, and there is a lack of methods for refined quantitative evaluation of the virtual inertia support capabilities of wind farms and effective load shedding power allocation. Summary of the invention

[0007] In view of the above analysis, an embodiment of the present invention aims to provide a method for quantifying the virtual inertia support capacity of a wind farm and allocating load shedding power, so as to solve the technical problem that the existing methods lack a method for fine-grained quantitative evaluation of the virtual inertia support capacity of a wind farm and effective load shedding power allocation.

[0008] The present invention provides a method for quantifying virtual inertia support capacity of a wind farm and allocating load shedding power, comprising the following steps:

[0009] Based on the parameters of each wind turbine, the inertial response capability H of the wind turbine under three inertial control modes of wind turbine: MPPT, overspeed load reduction and underspeed load reduction is calculated. w1 , H w2 and H w3 , and then obtain the operating inertia constant range of each wind turbine;

[0010] Calculate the wind speed of the wind turbine affected by the Jensen wake effect, and correct the wake speed to obtain a corrected wake speed; based on the corrected wake speed, calculate the wind power P captured by the wind turbine w (t); Based on P w (t) Further update H w2 and H w3 , thereby updating the inertia constant range;

[0011] Calculate the wake influence factor B of the wind turbines in the wind farm on the kth wind turbine k , the corrected wake wind speed is updated based on the wake influence factor, and the updated wake wind speed is obtained as the corrected wind speed of the wind turbine;

[0012] Based on the H w1 , updated H w2 and the corrected wind speed of the wind turbine generator set, and the weight coefficient γ of each wind turbine generator set is calculatedi , based on γ i The overall inertia response capability and load reduction power demand of the wind farm obtained in real time are allocated.

[0013] Furthermore, the inertia response capacity H of the wind turbine under MPPT mode is calculated. w1 ,as follows:

[0014]

[0015] Among them, J D , S W are the moment of inertia and rated capacity of the wind turbine respectively; ω MPPT is the speed corresponding to the maximum power operation point of the wind turbine; ω' is the rotor speed of the wind turbine corresponding to the end of the inertia response;

[0016] The load shedding reserve power P that the wind turbine can respond to under load shedding mode ref (t), as follows:

[0017] P ref (t) = P MPPT (t)-P de Formula (2)

[0018] Among them, P MPPT (t) is the power of the wind turbine at different times under the MPPT operation mode, P de It is the minimum load-reduced operating power value within the safe operating range of the wind turbine;

[0019] Calculate the inertia response capacity H of wind turbines under overspeed load reduction control mode w2 ,as follows:

[0020]

[0021] Among them, t start ,t end are the start time and end time of inertia response respectively; ω tstart ,ω tend They are the starting speed and ending speed of inertia response respectively;

[0022] Calculate the inertia response capacity H of wind turbines under low-speed load reduction control mode w3 ,as follows:

[0023]

[0024] Furthermore, the inertia constant range of each wind turbine is [0, max(H w1 +H w2 ,H w1 +H w3 )]].

[0025] Furthermore, the wind turbine wake speed affected by the Jensen wake effect is calculated as follows:

[0026]

[0027] Among them, v * (t) is the wake wind speed at a distance x meters downwind after being affected by the wake; v0(t) is the wind speed not affected by the wake; a is the axial induction coefficient; R r is the blade radius of the wind turbine; ε is the wake expansion rate under different terrains, as follows:

[0028]

[0029] Wherein, z′ is the height of the wind turbine after considering the influence of terrain roughness, z′=z / z0, z is the height of the wind turbine hub, and z0 is the terrain roughness value.

[0030] Furthermore, the Jensen wake model based on Gaussian function is used to calculate the wind speed v * (t) is corrected to obtain the corrected wake wind speed v GJ (r,t);

[0031]

[0032] in, represents the reduction in wind speed at the centerline of the wake; r is the distance between the wind turbine and the centerline of the wake; r w is the wake radius, r w =R r +k w x; k w is the wake attenuation coefficient, and x is the downwind distance.

[0033] Furthermore, the wind power P captured by the wind turbine is calculated w (t), as follows:

[0034]

[0035] Where ρ is the atmospheric density; S r is the circular area swept by the wind turbine blades, and ω is the wind turbine rotation speed.

[0036] Furthermore, based on P w (t) Further update H w2 and H w3 , thereby updating the inertia constant range, including:

[0037] Different corrected wind speeds, wind power P captured by wind turbines w(t) is different, for each P w (t), generate a wind power curve, the power at the highest point of the wind power curve is P MPPT (t);

[0038] Based on different P MPPT (t), and use formula (2) to obtain the load reduction reserve power P that the wind turbine can respond to under different load reduction modes: ref (t); then the load reduction reserved power P ref (t) Substitute into formula (3) and (4) to recalculate H w2 and H w3 , and then obtain the range of inertia constants of each wind turbine at different wind speeds.

[0039] Furthermore, the wake influence factor B of the wind turbines in the wind farm on the kth wind turbine is calculated. k , as shown below:

[0040]

[0041] Among them, S m is the wake influence area of ​​the kth wind turbine from other wind turbines in the wind farm;

[0042] Corrected wind speed v of wind turbine at time t GJB (t), as follows:

[0043] v GJB (t) = B k v GJ (dR r ,t)

[0044] Formula (10)

[0045] Where d is the distance between the center of the kth wind turbine and the center of the wake impact area, R r is the radius of the wind turbine blade.

[0046] Furthermore, based on t start ~t end All corrected wind speeds v for the time period GJB (t), and then substitute into formula (8) to obtain each v GJB (t) Corresponding wind power P w (t), based on each wind power P obtained w (t) and P w (t) The wind power curve is obtained by the wind turbine speed ω corresponding to the wind turbine speed ω. The power at the highest point of the wind power curve is P MPPT (t); Based on the H w1 and H w2 The sum of P MPPT(t), the unit power inertia constant J(t) is calculated as follows:

[0047]

[0048] Among them, P ws To safely limit the power of wind turbine speed;

[0049] The unit power inertia constant at each moment is connected to obtain a broken line, and the extreme points A, B, C, and D of the inertia response characteristics of the wind turbine are obtained, and the slope constant ω1 and intercept constant δ1 of DA are obtained; the slope constant ω2 and intercept constant δ2 of AB; the slope constant ω3 and intercept constant δ3 of BC are obtained, and ω1, ω2, ω3, δ1, δ2, and δ3 are constants greater than zero;

[0050] Determine the wind speed range corresponding to the extreme point of the wind turbine’s corrected wind speed, and calculate the wind turbine’s weight coefficient γ i ,as follows:

[0051]

[0052] Among them, v D is the minimum corrected wind speed of the wind turbines in the wind farm, v A 、v B 、v C is the wind speed at the location of the wind turbine at the extreme point.

[0053] Furthermore, the wind turbine parameters include the moment of inertia J D , Rated capacity S W , the speed corresponding to the maximum power operating point ω MPPT , the corresponding wind turbine rotor speed ω' after the inertia response ends, and the minimum load reduction operating power value P within the safe operating range of the wind turbine de , for wind power P w (t) corresponds to the power P at the highest point of the wind power curve MPPT (t).

[0054] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0055] 1. This application comprehensively considers the three operating modes and wake effect of wind turbines. The method can optimize the power output and frequency regulation capability of wind farms, and conduct refined quantitative evaluation of the virtual inertia support capability of wind farms and effective load shedding power allocation, thereby improving the stability and reliability of the entire power system and improving the overall performance of the power system;

[0056] 2. The wind farm of the present application dynamically adjusts the inertia response and load shedding power distribution according to the real-time wind speed and wind power data, thereby improving the response speed and accuracy of the power system to frequency changes; solving the intermittent and instability problems of the wind farm when providing inertia response affected by meteorological conditions; more precisely describing the inertia response support capacity of the wind farm under different wind speeds, so that the short-term virtual inertia level estimation of the wind farm can be realized by relying on the wind speed estimation method;

[0057] 3. This application provides a quantitative assessment of the specific inertial response capability and load shedding reserve power for each wind turbine through refined calculations, which helps to more accurately assess the virtual inertial support capability of the wind farm;

[0058] 4. By considering the Jensen wake effect and correcting it, the present application can more accurately calculate the wind speed and wind power of the wind turbine in actual operation, thereby more reasonably allocating power and evaluating inertia response;

[0059] 5. The method in this application can embed the dynamic inertia support affected by meteorology into the advance dispatch plan of the power system, and be applied in the new power system dispatch decision method with coordinated support of multiple inertia resources. The smooth supplement of virtual inertia support is smoother than the stepped inertia supplement of conventional units, and can better absorb new energy in the power system with new energy penetration.

[0060] In the present invention, the above-mentioned technical solutions can also be combined with each other to achieve more preferred combination solutions. Other features and advantages of the present invention will be described in the subsequent description, and some advantages can become obvious from the description, or can be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained through the contents particularly pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The drawings are only for the purpose of illustrating particular embodiments and are not to be considered limiting of the present invention. Like reference symbols denote like components throughout the drawings.

[0062] Figure 1 A flow chart of a method for quantifying virtual inertia support capacity and allocating load shedding power in a wind farm;

[0063] Figure 2 Schematic diagram of inertia constant of wind turbine under three wind turbine inertia control modes;

[0064] Figure 3 is the Jensen wake model based on Gaussian function;

[0065] Figure 4 It is a schematic diagram of the wake effect area;

[0066] Figure 5 Schematic diagram of the inertia response characteristics of wind turbine overspeed and load reduction. DETAILED DESCRIPTION

[0067] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0068] In order to solve the above problems, the present invention proposes a method for quantifying the virtual inertia response capacity of wind farms and allocating load-reducing power for wind turbines. Starting from the inertia response energy source of wind turbines, the inertia response capacity of wind turbines in wind farms under three different wind turbine inertia control operation modes is calculated, and the inertia support effects under the three operation modes are analyzed and compared to form an inertia response operation strategy; then, the wind speed of each wind turbine in the wind farm is refined and corrected based on the Jensen wake model of the Gaussian function, so that the wind speed estimation method can realize the quantitative level estimation of the short-term virtual inertia support capacity of the wind farm; finally, the wind speed-weighted wind turbine inertia response power allocation method is adopted according to the system inertia demand, so that the dynamic virtual inertia of wind turbines affected by the weather is embedded in the ex ante scheduling plan, which is suitable for the inertia demand of new power systems with increasing penetration of new energy.

[0069] The present invention is used to provide a more energy-saving inertia supplement method in a new power system with an increasing penetration rate of new energy. At the same time, through refined evaluation, the dynamic inertia of wind power affected by meteorology can be embedded into the advance scheduling plan of the power system. By flexibly adjusting the virtual inertia of wind power, the new power system can reduce the scheduling of conventional units and the amount of wind power abandoned by new energy.

[0070] Wind turbines are equipped with reserved load shedding power to reduce the wind and power abandonment rate of new energy wind turbines, and the reserved load shedding power provides inertia support.

[0071] There is an upper limit to the release of rotor kinetic energy. When all the rotor kinetic energy is released, it still cannot meet the goal of providing inertia requirements, and then inertia support is provided by reserving load reduction power.

[0072] A wind farm includes multiple wind turbines. The inertia required in a wind farm is allocated to each corresponding wind turbine. All the following steps are calculated for each wind turbine in the wind farm.

[0073] A specific embodiment of the present invention discloses a method for quantifying virtual inertia support capacity of a wind farm and allocating load shedding power, such as Figure 1 As shown, the following steps are included:

[0074] Step S1: Calculate the inertial response capability H of the wind turbine under three inertial control modes: MPPT (Maximum Power Point Tracking), overspeed load reduction, and underspeed load reduction based on the parameters of each wind turbine. w1 , H w2 and H w3 , and then obtain the operating inertia constant range of each wind turbine;

[0075] Step S2: Calculate the wind speed of the wind turbine affected by the Jensen wake effect, and correct the wake speed to obtain a corrected wake speed; Based on the corrected wake speed, calculate the wind power P captured by the wind turbine. w (t); Based on P w (t) Further update H w2 and H w3 , thereby updating the inertia constant range;

[0076] Step S3: Calculate the wake influence factor B of the wind turbines in the wind farm on the kth wind turbine k , the corrected wake wind speed is updated based on the wake influence factor, and the updated wake wind speed is obtained as the corrected wind speed of the wind turbine;

[0077] Step S4: Based on the H w1 , updated H w2 and the corrected wind speed of the wind turbine generator set, and the weight coefficient γ of each wind turbine generator set is calculated i , based on γ i The overall inertia response capability and load reduction power demand of the wind farm obtained in real time are allocated.

[0078] Step S1 includes steps S11-S12.

[0079] Step S11: Calculate the inertial response capability H of the wind turbine under three inertial control modes of the wind turbine: MPPT, overspeed load reduction and underspeed load reduction, based on the parameters of each wind turbine. w1 , H w2 and H w3 .

[0080] Calculate the inertia response capacity H of wind turbines under MPPT mode w1 , as shown in formula (1):

[0081]

[0082] Among them, J D , S W are the moment of inertia and rated capacity of the wind turbine respectively; ω MPPTis the speed corresponding to the maximum power operation point of the wind turbine; ω' is the rotor speed of the wind turbine corresponding to the end of the inertia response;

[0083] The load shedding reserve power P that the wind turbine can respond to under load shedding mode ref (t), as shown in formula (2):

[0084] P ref (t) = P MPPT (t)-P de Formula (2)

[0085] Among them, P MPPT (t) is the power of the wind turbine at different times under the MPPT operation mode, P de It is the minimum load-reduced operating power value within the safe operating range of the wind turbine;

[0086] Calculate the inertia response capacity H of wind turbines under overspeed load reduction control mode w2 , as shown in formula (3):

[0087]

[0088] Among them, t start ,t end are the start time and end time of inertia response respectively; ω tstart ,ω tend They are the starting speed and ending speed of inertia response respectively;

[0089] Calculate the inertia response capacity H of wind turbines under low-speed load reduction control mode w3 , as shown in formula (4):

[0090]

[0091] (1) Calculate the inertial response capability H of the wind turbine under MPPT operation mode w1 .

[0092] The wind turbines are operated in MPPT mode and can use their own rotor energy for virtual inertia response. w1 ; Wind turbines generate maximum power when operating in MPPT mode.

[0093] J D : is the physical property of the wind turbine rotor, which represents the product of the wind turbine rotor mass and the blade rotation radius. It is a fixed value and a constant, which can be obtained from the technical specifications in the wind turbine technical manual;

[0094] S W ,ω MPPT : Obtained from the technical specifications of the wind turbine technical manual;

[0095] ω': refers to the new steady-state speed reached by the rotor of a wind turbine after a disturbance. This value is obtained from the speed sensor of the wind turbine. Different disturbances will result in different ω' values.

[0096] In wind power generation systems, MPPT adjusts the pitch angle or speed of wind turbine blades to adapt to wind speed changes, tracks the maximum power point, and ensures maximum energy capture at different wind speeds. Wind speed is variable, and MPPT ensures maximum power output at different wind speed conditions.

[0097] (2) Calculate the inertia response capacity H of the wind turbine under overspeed load reduction control mode w2 .

[0098] When the wind turbine is running in overspeed load reduction control mode, the inertia response capacity of the wind turbine is w2 It comes from the sum of the load reduction reserved energy and the rotor kinetic energy. Inertia response starting speed and ending speed ω tstart ,ω tend Obtain the speed value from a speed sensor of the wind turbine generator set;

[0099] P ref (t) is the load-shedding power at time t, The energy reserved for wind turbines to reduce load. The time integral of power is energy.

[0100] For example, t end -t start The general value is 10s.

[0101] In the overspeed load reduction operation mode, the inertia response capacity H of the wind turbine is obtained by adding the reserved energy and the rotor kinetic energy release. w2 .

[0102] Overspeed load shedding means that when the wind speed exceeds a certain preset threshold, the wind turbine reduces the speed by reducing the windward area of ​​the blades to prevent mechanical overload or damage, thereby protecting the wind turbine.

[0103] (3) Calculate the inertia response capacity H of the wind turbine under low-speed load reduction control mode w3 .

[0104] When a wind turbine is operating in a low-speed load reduction control mode, the energy source of the wind turbine is the difference between the load reduction reserved energy and the rotor kinetic energy.

[0105] Low-speed load shedding: When the wind speed is lower than a certain preset threshold, the wind turbine reduces the output power by adjusting the control strategy to improve efficiency or prevent mechanical damage.

[0106] Inertia response capability H w1 , H w2 and H w3 The unit is seconds. Figure 2 As shown in the figure, the inertial response capacity H of three wind turbine inertial control modes is calculated based on the wind turbine parameters. w1 , H w2 and H w3 .

[0107] The wind turbine parameters include the moment of inertia J D , Rated capacity S W , the speed corresponding to the maximum power operating point ω MPPT , the corresponding wind turbine rotor speed ω' after the inertia response ends, and the minimum load reduction operating power value P within the safe operating range of the wind turbine de , for wind power P w (t) corresponds to the power P at the highest point of the wind power curve MPPT (t).

[0108] Step S12: Based on H w1 , H w2 and H w3 The calculation results give the inertia constant range of each wind turbine.

[0109] The inertia constant range of each wind turbine is [0, max(H w1 +H w2 ,H w1 +H w3 )]].

[0110] After determining the unit operation mode, select the larger value of two combinations of the three as the upper limit of the range.

[0111] max(H w1 +H w2 ,H w1 +H w3 ), obtain the upper limit, and obtain the upper and lower limit range of the inertia constant of each wind turbine unit [0, max (H w1 +H w2 ,H w1 +H w3 )], where 0 means no inertial support. The minimum value is 0 and the maximum value is two combinations of H w1 +H w2 and H w1 +H w3 Take the larger value to obtain the range of inertia constants for each wind turbine operation.

[0112] Reserved load reduction power. This reserved load reduction power cannot be sold. This part includes overspeed load reduction and low speed load reduction. The reserved load reduction power provided by overspeed load reduction and low speed load reduction at different wind speeds is different. For example, at a wind speed of 8m / s, low speed load reduction will reserve more load reduction power than overspeed load reduction, and more power can be reserved at overspeed load reduction of 12m / s.

[0113] The inertia constant range of the inertia support capacity changes at any time, and is combined through the three wind turbine inertia control modes of step S1, either rotor kinetic energy release plus overspeed load reduction; or rotor kinetic energy release plus low speed load reduction.

[0114] Step S2 includes steps S21-S23.

[0115] Large wind farms usually have hundreds of wind turbines and cover an area of ​​tens or hundreds of square kilometers. In such a large area, due to its spatial scale and the dynamic characteristics of wind, it is almost impossible to provide the same wind speed to each turbine at every moment, which is called the spatial discreteness of wind speed. For large wind farms, due to its spatial scale and the dynamic changes of wind, there are obvious differences in wind speed at different wind turbines. This difference is mainly caused by the wake effect, which is specifically manifested as the total energy obtained by the downwind wind turbine will be less than the upwind wind turbine in front.

[0116] The logarithmic law is a basic method for simulating incoming wind and is often used to describe wind speed distribution. In order to more accurately calculate the wind speed at the height of the wind turbine hub, the wind speed is processed according to the logarithmic law after being obtained through wind speed prediction, and the influence of the terrain where the wind turbine is located is taken into account.

[0117] Step S21, calculating the wind speed of the wind turbine affected by the Jensen wake effect, as shown in formula (5):

[0118]

[0119] Among them, v * (t) is the wake wind speed at a distance x meters downwind after being affected by the wake; v0(t) is the wind speed not affected by the wake; a is the axial induction coefficient; R r is the blade radius of the wind turbine; ε is the wake expansion rate under different terrains, as shown in formula (6):

[0120]

[0121] Wherein, z′ is the height of the wind turbine after considering the influence of terrain roughness, z′=z / z0, z is the height of the wind turbine hub, and z0 is the terrain roughness value.

[0122] The axial induction coefficient a is determined by the thrust coefficient CT It is calculated that C T =4a(1-a), C T is a known quantity, obtained from the technical specifications of the wind turbine technical manual; the radius R of the wind turbine blade r , obtained from the technical specifications in the wind turbine technical manual.

[0123] Formulas (5)-(6) take into account the influence of terrain roughness and wake effect on wind speed, thereby estimating the wake wind speed at a specific downwind distance x.

[0124] Taking into account the influence of the terrain where the wind turbine is located, the terrain roughness value z0 is shown in Table 1.

[0125] Table 1: Roughness values ​​z0 corresponding to different terrains

[0126]

[0127] Step S22: Jensen wake model based on Gaussian function for wind speed v * (t) is corrected to obtain the corrected wake wind speed v GJ (r, t), as shown in formula (7);

[0128]

[0129] in, represents the reduction in wind speed at the centerline of the wake; r is the distance between the wind turbine and the centerline of the wake; r w is the wake radius, r w =R r +k w x; k w is the wake attenuation coefficient, and x is the downwind distance.

[0130] Downwind distance x, in meters; v GJ (r, t) is the wind speed corrected by the Jensen wake model based on the Gaussian function at time t.

[0131] Step S22 uses a Gaussian function to simulate the distribution of the wake effect on the wind speed, and uses the Gaussian distribution to correct the wind speed according to the position of the wind turbine relative to the center line of the wake. If no correction is made, deviation will occur, and the inertia constant range calculated in step 1 will have an error.

[0132] Step S23: Calculate the wind power P captured by the wind turbine w (t), as shown in formula (8):

[0133]

[0134] Where ρ is the atmospheric density; S r is the circular area swept by the wind turbine blades, and ω is the wind turbine rotation speed.

[0135] Wind power captured by wind turbine P w The calculation process of formula (8) of (t) is as follows:

[0136] The wind power captured by the wind turbine is shown in (9).

[0137]

[0138] Where v(t) is the corrected wake wind speed; wind energy utilization coefficient C p (λ,β) is as shown in formulas (10)-(12):

[0139]

[0140]

[0141] Among them, λ i is the intermediate variable; R r is the blade radius of the wind turbine; C p (λ, β) is a high-order nonlinear function of the tip speed ratio λ and the wind turbine pitch angle β; Substituting formula (10)(11)(12) into formula (9), we get formula (8).

[0142] It can be seen from formula (8) that the maximum power point of the wind turbine is at different wind turbine speeds ω at different wind speeds. Considering the speed safety limit, the maximum speed difference before and after the inertia response will change with the wind speed of the wind farm. At the same time, the energy that can be provided by the load reduction operation at different wind speeds will also change, which means that the inertia constant of the wind turbine is not a fixed value.

[0143] Based on P w (t) Further update H w2 and H w3 , thereby updating the inertia constant range, including:

[0144] Different corrected wind speeds, wind power P captured by wind turbines w (t) is different, for each P w (t), generate a wind power curve, the power at the highest point of the wind power curve is P MPPT (t);

[0145] Based on different P MPPT (t), and use formula (2) to obtain the load reduction reserve power P that the wind turbine can respond to under different load reduction modes: ref (t); then the load reduction reserved power P ref(t) Substitute into formula (3) and (4) to recalculate H w2 and H w3 , and then obtain the range of inertia constants of each wind turbine at different wind speeds.

[0146] Update the inertia constant range to obtain different inertia constant range interval values.

[0147] The purpose of step S2 is to consider the wind speed in the actual wind farm to avoid using the average wind speed to evaluate the inertia response capability of the wind turbine set too high or too low. Wind speed data is crucial for evaluating the power output and inertia response capability of the wind turbine set. This step can better evaluate and predict the dynamic characteristics of the wind farm, thereby optimizing the inertia constant range of the wind farm.

[0148] Step S3, specifically.

[0149] like Figure 3 As shown in the figure, the wind is affected by the wind turbines, which will produce an impact range, thus affecting the wind speed at the location of the wind turbines in the downwind direction.

[0150] To estimate wind power loss more accurately, the area S swept by the wind turbine blades is r The overlap with the wake influence area is taken into account, e.g. Figure 4 As shown, the shaded area is the wake impact area S mi , the area of ​​a wind turbine in a wind farm affected by the wake of another wind turbine is S mi , the wake impact area affected by other wind turbines in the wind farm, the cumulative shadow area S mi For S m , d is the distance between the center of the downwind wind turbine and the center of the wake impact area (the distance between the two centers of the circle), Figure 4 Medium S mi It is the area of ​​the wake influence of one of the upstream wind turbines on this wind turbine.

[0151] A wind farm has many wind turbines, and each wind turbine will have an impact on the downwind wind turbines.

[0152] Calculate the wake influence factor B of the wind turbines in the wind farm on the kth wind turbine k , as shown in formula (13):

[0153]

[0154] Among them, S m is the wake influence area of ​​the kth wind turbine from other wind turbines in the wind farm;

[0155] Corrected wind speed v of wind turbine at time t GJB(t), as shown in formula (14):

[0156] v GJB (t) = B k v GJ (dR r ,t)

[0157] Formula (14)

[0158] Where d is the distance between the center of the kth wind turbine and the center of the wake impact area, R r is the blade radius of the wind turbine.

[0159] v GJB (t) is the wake influence factor B of the wind turbine at time t k Corrected wind speed after

[0160] v GJ (dR r ,t) means (dR r ,t) into the wind speed correction formula (7), multiplied by the wake influence factor B k Get the corrected wind speed v of the wind turbine at time t GJB (t).

[0161] The purpose of step S3 is to calculate the wind speed at each wind turbine in the wind farm more precisely, because the inertia response capability of the wind turbine is affected by the wind speed, so as to avoid over- or under-evaluation of the inertia response capability of the wind turbine.

[0162] Step 4: Specifically.

[0163] Based on t start ~t end All corrected wind speeds v for the time period GJB (t), and then substitute into formula (8) to obtain each v GJB (t) Corresponding wind power P w (t), based on each wind power P obtained w (t) and P w (t) The wind power curve is obtained by the wind turbine speed ω corresponding to the wind power curve. The power at the highest point of the wind power curve is P MPPT (t); Based on the H w1 and H w2 The sum of P MPPT (t), the unit power inertia constant J(t) is calculated as shown in formula (15):

[0164]

[0165] Among them, P ws To safely limit the power of wind turbine speed;

[0166] The unit power inertia constant at each moment is connected to obtain a broken line, and the extreme points A, B, C, and D of the inertia response characteristics of the wind turbine are obtained, and the slope constant ω1 and intercept constant δ1 of DA are obtained; the slope constant ω2 and intercept constant δ2 of AB; the slope constant ω3 and intercept constant δ3 of BC are obtained, and ω1, ω2, ω3, δ1, δ2, and δ3 are constants greater than zero;

[0167] Determine the wind speed range corresponding to the extreme point of the wind turbine’s corrected wind speed, and calculate the wind turbine’s weight coefficient γ i , as shown in formula (16):

[0168]

[0169] Among them, ω1, ω2, ω3, δ1, δ2 and δ3 are constants greater than zero

[0170] , v D is the minimum corrected wind speed of the wind turbines in the wind farm, v A 、v B 、v C is the wind speed at the location of the wind turbine at the extreme point.

[0171] Depend on Figure 5 As shown, the wind speed on the horizontal axis is the corrected wind speed v GJB (t), the column is the wind power P corresponding to the corrected wind speed w (t), in the wind speed range of 5-12m / s, ignoring the minimum wind speed (5-7m / s, which is almost non-existent in reality) where the load reduction is too small, there are three extreme points when the wind speed is 8m / s, 10m / s and 12m / s, which are set as point A, point B and point C respectively. Figure 5 It can be seen that at wind speeds A and C, the same amount of power reduction can respond to a greater inertia response support capacity than at other wind speeds.

[0172] For each wind turbine, the corrected wind speed is determined to determine the range in which it is located, and then the weight coefficient γ of the wind turbine is obtained. i .

[0173] Based on the acquired real-time wind speed, the weight coefficient of the wind turbine is calculated, and the overall inertia response capability and load shedding power demand of the wind farm are allocated based on the weight coefficient to achieve optimal inertia response allocation and load shedding power allocation.

[0174] For example, at different times, the inertia response capability and load shedding power demand of the wind farm are obtained from the power grid energy management system, or are set by power operation and maintenance personnel.

[0175] The role of step S4 is to obtain the inertia support demand and load reduction power demand target of the wind farm, and the inertia response capability and load reduction power of each unit are based on the weight coefficient γ i Carry out weighted distribution to avoid the average distribution method which would result in a high total load reduction of wind turbines.

[0176] In summary, a method for quantifying virtual inertia support capacity of a wind farm and allocating load shedding power according to an embodiment of the present invention has the following beneficial effects:

[0177] 1. This application comprehensively considers the three operating modes and wake effect of wind turbines. The method can optimize the power output and frequency regulation capability of wind farms, and conduct refined quantitative evaluation of the virtual inertia support capability of wind farms and effective load shedding power allocation, thereby improving the stability and reliability of the entire power system and improving the overall performance of the power system;

[0178] 2. The wind farm of the present application dynamically adjusts the inertia response and load shedding power distribution according to the real-time wind speed and wind power data, thereby improving the response speed and accuracy of the power system to frequency changes; solving the intermittent and instability problems of the wind farm when providing inertia response affected by meteorological conditions; more precisely describing the inertia response support capacity of the wind farm under different wind speeds, so that the short-term virtual inertia level estimation of the wind farm can be realized by relying on the wind speed estimation method;

[0179] 3. This application provides a quantitative assessment of the specific inertial response capability and load shedding reserve power for each wind turbine through refined calculations, which helps to more accurately assess the virtual inertial support capability of the wind farm;

[0180] 4. By considering the Jensen wake effect and correcting it, the present application can more accurately calculate the wind speed and wind power of the wind turbine in actual operation, thereby more reasonably allocating power and evaluating inertia response;

[0181] 5. The method in this application can embed the dynamic inertia support affected by meteorology into the advance dispatch plan of the power system, and be applied in the new power system dispatch decision method with coordinated support of multiple inertia resources. The smooth supplement of virtual inertia support is smoother than the stepped inertia supplement of conventional units, and can better absorb new energy in the power system with new energy penetration.

[0182] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for quantifying virtual inertia support capacity of a wind farm and allocating load shedding power, characterized in that: The steps include: Based on the parameters of each wind turbine, the inertial response capability H of the wind turbine under three inertial control modes of wind turbine: MPPT, overspeed load reduction and underspeed load reduction is calculated. w1 , H w2 and H w3 , and then obtain the operating inertia constant range of each wind turbine; Calculating the wake wind speed of the wind turbine affected by the Jensen wake effect, and correcting the wake wind speed to obtain a corrected wake wind speed; Based on the corrected wake wind speed, the wind power P captured by the wind turbine is calculated. w (t); Based on P w (t) Further update H w2 and H w3 , thereby updating the inertia constant range; Calculate the wake influence factor B of the wind turbines in the wind farm on the kth wind turbine k , the corrected wake wind speed is updated based on the wake influence factor, and the updated wake wind speed is obtained as the corrected wind speed of the wind turbine; Based on the H w1 , updated H w2 and the corrected wind speed of the wind turbine generator set, and the weight coefficient γ of each wind turbine generator set is calculated i , based on γ i Allocate the overall inertia response capability and load shedding power demand of the wind farm obtained in real time; Calculate the inertia response capacity H of wind turbines under MPPT mode w1 ,as follows: Among them, J D , S W are the moment of inertia and rated capacity of the wind turbine respectively; ω MPPT is the speed corresponding to the maximum power operation point of the wind turbine; ω' is the rotor speed of the wind turbine corresponding to the end of the inertia response; The load shedding reserve power P that the wind turbine can respond to under load shedding mode ref (t), as follows: P ref (t) = P MPPT (t)-P de Formula (2) Among them, P MPPT (t) is the power of the wind turbine at different times under the MPPT operation mode, P de It is the minimum load-reduced operating power value within the safe operating range of the wind turbine; Calculate the inertia response capacity H of wind turbines under overspeed load reduction control mode w2 ,as follows: Among them, t start ,t end They are the start time and end time of inertia response respectively; They are the starting speed and ending speed of inertia response respectively; Calculate the inertia response capacity H of wind turbines under low-speed load reduction control mode w3 ,as follows: The inertia constant range of each wind turbine is [0, max(H w1 +H w2 ,H w1 +H w3 )]; Calculate the wind speed of the wind turbine affected by the Jensen wake effect as follows: Among them, v * (t) is the wake wind speed at a distance x meters downwind after being affected by the wake; v0(t) is the wind speed not affected by the wake; a is the axial induction coefficient; R r is the blade radius of the wind turbine; ε is the wake expansion rate under different terrains, as follows: Wherein, z′ is the height of the wind turbine after considering the influence of terrain roughness, z'=z / z0, z is the height of the wind turbine hub, and z0 is the terrain roughness value; Jensen wake model based on Gaussian function for wind speed v * (t) is corrected to obtain the corrected wake wind speed v GJ (r,t); in, represents the reduction in wind speed at the centerline of the wake; r is the distance between the wind turbine and the centerline of the wake; r w is the wake radius, r w =R r +k w x; k w is the wake attenuation coefficient, and x is the downwind distance.

2. The method according to claim 1, characterized in that: Calculate the wind power P captured by the wind turbine w (t), as follows: Where ρ is the atmospheric density; S r is the circular area swept by the wind turbine blades, and ω is the wind turbine rotation speed.

3. The method according to claim 2, characterized in that: Based on P w (t) Further update H w2 and H w3 , thereby updating the inertia constant range, including: Different corrected wind speeds, wind power P captured by wind turbines w (t) is different, for each P w (t), generate a wind power curve, the power at the highest point of the wind power curve is P MPPT (t); Based on different P MPPT (t), and use formula (2) to obtain the load shedding reserve power P that the wind turbine can respond to under different load shedding modes: ref (t); then the load reduction reserved power P ref (t) Substitute into formula (3) and (4) to recalculate H w2 and H w3 , and then obtain the range of inertia constants of each wind turbine at different wind speeds.

4. The method according to claim 3, characterized in that: Calculate the wake influence factor B of the wind turbines in the wind farm on the kth wind turbine k , as shown below: Among them, S m is the wake influence area of ​​the kth wind turbine from other wind turbines in the wind farm; Corrected wind speed v of wind turbine at time t GJB (t), as follows: v GJB (t)=B k v GJ (d-R r ,t) Formula (10) Where d is the distance between the center of the kth wind turbine and the center of the wake impact area, R r is the blade radius of the wind turbine.

5. The method according to claim 4, characterized in that: Based on t start ~t end All corrected wind speeds v for the time period GJB (t), and then substitute into formula (8) to obtain each v GJB (t) Corresponding wind power P w (t), based on each wind power P obtained w (t) and P w (t) The wind power curve is obtained by the wind turbine speed ω corresponding to the wind power curve. The power at the highest point of the wind power curve is P MPPT (t); Based on the H w1 and H w2 The sum of P MPPT (t), the unit power inertia constant J(t) is calculated as follows: Among them, P ws To safely limit the power of wind turbine speed; The unit power inertia constant at each moment is connected to obtain a broken line, and the extreme points A, B, C, and D of the inertia response characteristics of the wind turbine are obtained, and the slope constant ω1 and intercept constant δ1 of DA are obtained; the slope constant ω2 and intercept constant δ2 of AB; the slope constant ω3 and intercept constant δ3 of BC are obtained, and ω1, ω2, ω3, δ1, δ2, and δ3 are constants greater than zero; Determine the wind speed range corresponding to the extreme point of the wind turbine’s corrected wind speed, and calculate the wind turbine’s weight coefficient γ i ,as follows: Among them, v D is the minimum corrected wind speed of the wind turbines in the wind farm, v A 、v B 、v C is the wind speed at the location of the wind turbine at the extreme point.

6. The method according to any one of claims 1 to 5, characterized in that: The wind turbine parameters include the moment of inertia J D , Rated capacity S W , the speed corresponding to the maximum power operating point ω MPPT , the corresponding wind turbine rotor speed ω' after the inertia response ends, and the minimum load reduction operating power value P within the safe operating range of the wind turbine de , for wind power P w (t) corresponds to the power P at the highest point of the wind power curve MPPT (t).

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