Wind power virtual inertia control parameter optimization method based on optimal system frequency trajectory

Abstract

The present invention provides a wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory, which belongs to the technical field of wind turbine frequency regulation strategy. In the scenario involving wind power participation in frequency regulation, according to the optimal system frequency trajectory, wind turbine unit output and traditional unit output characteristics, the expected virtual inertia control parameter change trajectory transfer function expression and analytical expression are derived. In addition, the dead zone correction expression is derived considering the dead zone influence, and the wind power virtual inertia control parameter optimization method is improved and expanded to be applicable to different wind speed scenarios. The present invention gives full play to the frequency regulation potential of wind turbine units, effectively improves the system frequency response characteristics under different wind speed and disturbance scenarios, avoids secondary frequency drops, and can correct the influence of dead zones to achieve approximate optimal system frequency trajectory, and has strong practicality.

Description

Technical Field

[0001] The present invention relates to the technical field of wind turbine frequency regulation strategies, and in particular to a method for optimizing wind power virtual inertia control parameters based on optimal system frequency trajectory. Background Art

[0002] As the proportion of new energy represented by wind power increases, the overall inertia of the power system continues to decrease, and the problem of system frequency safety and stability becomes increasingly prominent. Compared with the previous expectation that wind power can output as much as possible to ensure a certain power generation efficiency and economic benefits, today's power grid dispatching hopes that large wind farms can have a certain frequency support capability to alleviate the adverse effects of low inertia characteristics on the power system. However, variable-speed wind turbines have gradually replaced traditional fixed-speed generators to become the mainstream of the wind power market. This type of variable-speed wind turbine belongs to the inverter interface power supply. When the system frequency shifts, the unit cannot actively respond to the system frequency to provide active power support.

[0003] Wind power support capacity has a certain adjustable space and degree of freedom, which brings new opportunities and challenges to the frequency control of high-proportion renewable energy power systems. By transforming the control structure of wind turbines and allowing wind power to actively participate in frequency response, the frequency security guarantee capability of the power system can be effectively improved. However, wind power generally does not have power reserve, and its frequency regulation capability is restricted by the stored rotor kinetic energy. Therefore, it is urgent to fully tap the frequency regulation potential of wind turbines, cooperate with traditional units, and improve the system frequency response characteristics.

[0004] When a load disturbance occurs, the traditional additional fixed parameter integrated inertia control and step inertia control can quickly release the kinetic energy stored in the rotor to provide active support, thereby improving the system frequency response characteristics to a certain extent. However, unreasonable parameter settings may, on the one hand, limit the frequency regulation capability of wind power and fail to maximize the improvement of the system frequency response characteristics. On the other hand, due to unreasonable active power distribution, there may be a large active power difference in the wind turbine during the rotor speed recovery phase, resulting in a serious secondary frequency drop. How to design wind power virtual inertia control parameters based on the optimal system frequency trajectory characteristics to adapt to different load disturbances and wind speed scenarios, give full play to the potential of wind power frequency regulation, improve the system frequency response characteristics and avoid secondary frequency drops is an important research topic.

[0005] The latest guidelines stipulate that the dead zone setting range for wind farms participating in the primary frequency regulation of the power grid is 0.03 to 0.1 Hz. Zhang Feng et al. analyzed the nonlinear impact of the dead zone from the mechanism level in the literature [“Modeling of the dead zone impact mechanism and coefficient correction strategy for new energy primary frequency regulation [J]. Automation of Electric Power Systems, 2023, 47(6): 158-167.”] and proposed a dead zone correction formula to compensate for the adverse impact of the dead zone on the system frequency, but did not take into account the impact of the dead zone and make corrections in the control strategy based on the optimal system frequency trajectory design. Summary of the invention

[0006] The purpose of the present invention is to provide a wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory, which can be applied to different disturbance and wind speed scenarios to improve the system frequency response characteristics, avoid secondary frequency drop, and correct the influence of dead zone, so as to achieve the approximate optimal system frequency trajectory, so as to solve at least one technical problem existing in the above-mentioned background technology.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a method for optimizing wind power virtual inertia control parameters based on optimal system frequency trajectory, comprising:

[0009] According to the optimal system frequency trajectory and the output characteristics of each unit, the transfer function of the expected virtual inertia control parameter change trajectory of the wind turbine is constructed; considering the influence of the dead zone, the wind turbine output active power increment transfer function used to correct the dead zone influence is constructed;

[0010] Considering the scenario below the rated wind speed, based on the principle of wind speed similarity and combining the transfer function of the wind turbine set's expected virtual inertia control parameter change trajectory and the wind turbine set's output active power increment transfer function, it is determined that wind turbine sets in the same wind speed range should adopt consistent wind power virtual inertia control parameter trajectory.

[0011] Furthermore, for different wind speed scenarios, considering the scenarios below the rated wind speed, the wind speeds are classified into: high wind speed segment, medium wind speed segment, medium-low wind speed segment and low wind speed segment. Based on the principle of wind speed similarity, wind turbines in the same wind speed segment adopt a consistent wind power virtual inertia control parameter trajectory, that is, the expected wind power virtual inertia control parameter trajectory under the average wind speed in each wind speed segment is adopted.

[0012] Furthermore, the transfer function expression of the expected virtual inertia control parameter change trajectory of the wind turbine is determined, including: obtaining the moment when the wind turbine participates in frequency regulation through traversal search and simulation calculation; determining the dynamic equation of active power shortage and system frequency response; based on the traditional steam turbine frequency regulation, determining the traditional unit output during the wind turbine frequency regulation period, and determining the wind turbine output; obtaining the transfer function expression of the expected virtual inertia control parameter change trajectory.

[0013] Furthermore, the active power shortage and the lowest frequency point under the corresponding optimal frequency trajectory are approximately equal to a constant, and the time domain analytical expression of the variation trajectory is obtained.

[0014] Furthermore, the wind turbine output active power increment transfer function expression for correcting the dead zone effect is determined, including: the existence of the dead zone will reduce the wind power output, making the actual system frequency minimum point lower than expected; considering the common frequency regulation dead zone, in order to correct the dead zone effect and improve the unit output, the dead zone correction expression is determined based on the wind turbine output active power increment for correcting the dead zone effect and the wind turbine frequency regulation dead zone boundary value.

[0015] Furthermore, when an active power shortage occurs, the output of wind turbines is increased to provide active power support. When the disturbance is large, the dead zone is triggered and the dead zone is corrected. In different wind speed scenarios, the wind speed segment in which the wind speed is located is determined, and the expected virtual inertia control parameter change trajectory at the average wind speed of the wind speed segment is used to participate in frequency regulation.

[0016] In a second aspect, the present invention provides a wind power virtual inertia control parameter optimization system based on optimal system frequency trajectory, comprising:

[0017] A construction module is used to construct a wind turbine unit expected virtual inertia control parameter change trajectory transfer function according to the optimal system frequency trajectory and the output characteristics of each unit; considering the influence of the dead zone, a wind turbine unit output active power increment transfer function for correcting the dead zone influence is constructed;

[0018] The solution module is used to consider the scenario below the rated wind speed. Based on the wind speed similarity principle, combined with the wind turbine expected virtual inertia control parameter change trajectory transfer function and the wind turbine output active power increment transfer function, it determines that the wind turbines in the same wind speed range adopt a consistent wind power virtual inertia control parameter trajectory.

[0019] In a third aspect, the present invention provides a non-transitory computer-readable storage medium, which is used to store computer instructions. When the computer instructions are executed by a processor, the wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory as described in the first aspect is implemented.

[0020] In a fourth aspect, the present invention provides a computer device, comprising a memory and a processor, wherein the processor and the memory communicate with each other, the memory stores program instructions executable by the processor, and the processor calls the program instructions to execute the wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory as described in the first aspect.

[0021] In a fifth aspect, the present invention provides an electronic device, comprising: a processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory so that the electronic device executes instructions for implementing the wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory as described in the first aspect.

[0022] The beneficial effects of the present invention are as follows: it can effectively improve the lowest point of the system frequency, improve the system frequency response characteristics, and make the system frequency trajectory present an approximately optimal form, and can correct the adverse effects of the dead zone on the system frequency, and has a certain adaptability to different wind speeds and disturbance scenarios; the virtual inertia control structure is adopted, and there is no need to significantly modify the structure of the wind turbine power controller, and the practicality is strong.

[0023] Additional advantages of the present invention will be more clearly given in the following description or learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0025] Figure 1 It is the optimal system frequency trajectory and unit output characteristic diagram described in the embodiment of the present invention.

[0026] Figure 2 This is a block diagram of the virtual inertia control including dead zone correction according to an embodiment of the present invention.

[0027] Figure 3 This is a comparison chart of control effects of different methods described in the embodiments of the present invention.

[0028] Figure 4 This is a control effect diagram taking into account dead zone correction according to an embodiment of the present invention.

[0029] Figure 5 This is a control effect diagram of each wind speed section described in an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below by the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be interpreted as limiting the present invention.

[0031] It should be understood by those skilled in the art that unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art to which this invention belongs.

[0032] It should also be understood that terms, such as those defined in commonly used dictionaries, should be understood to have a meaning consistent with that in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless as defined herein.

[0033] Those skilled in the art will appreciate that, unless otherwise stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements and / or groups thereof.

[0034] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. Different embodiments or examples described in this specification and features of different embodiments or examples may be combined and combined by those skilled in the art without contradiction.

[0035] To facilitate understanding of the present invention, the present invention is further explained below with reference to specific embodiments in conjunction with the accompanying drawings, and the specific embodiments do not constitute a limitation on the embodiments of the present invention.

[0036] Those skilled in the art should understand that the drawings are merely schematic diagrams of embodiments, and the components in the drawings are not necessarily necessary for implementing the present invention.

[0037] Example 1

[0038] In this embodiment 1, a wind power virtual inertia control parameter optimization system based on the optimal system frequency trajectory is first provided, including: a construction module, used to construct a wind turbine unit's expected virtual inertia control parameter change trajectory transfer function according to the optimal system frequency trajectory and the output characteristics of each unit; considering the influence of the dead zone, constructing a wind turbine unit output active power increment transfer function for correcting the dead zone influence; a solution module, used to consider the scenario below the rated wind speed, based on the wind speed similarity principle, combined with the wind turbine unit's expected virtual inertia control parameter change trajectory transfer function and the wind turbine unit output active power increment transfer function, to determine that the wind turbine units with wind speeds in the same wind speed range adopt a consistent wind power virtual inertia control parameter trajectory.

[0039] In this embodiment, based on the above-mentioned system, a wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory is implemented, including: constructing a wind turbine expected virtual inertia control parameter change trajectory transfer function according to the optimal system frequency trajectory and the output characteristics of each unit; considering the influence of the dead zone, constructing a wind turbine output active power increment transfer function for correcting the dead zone influence; considering the scenario below the rated wind speed, based on the wind speed similarity principle, combining the wind turbine expected virtual inertia control parameter change trajectory transfer function and the wind turbine output active power increment transfer function, determining that wind turbines in the same wind speed range use a consistent wind power virtual inertia control parameter trajectory.

[0040] The implementation of the wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory may specifically include the following steps:

[0041] Step 1: In the scenario of wind power frequency regulation, analyze the optimal system frequency trajectory and the output characteristics of each unit (including wind turbines and traditional units). From the output characteristics, it can be seen that when the wind turbine participates in frequency regulation, the system frequency change rate is 0, and the optimal system frequency trajectory always remains at the lowest point. When the wind turbine exits frequency regulation, the output of the wind turbine gradually recovers to the initial output value, and the system frequency recovers to the steady-state frequency.

[0042] Step 2: Based on the characteristics of step 1, derive the transfer function expression and analytical expression of the wind turbine set's expected virtual inertia control parameter change trajectory.

[0043] Step 3: Considering the influence of the dead zone, derive the transfer function expression and analytical expression of the wind turbine output active power increment used to correct the influence of the dead zone.

[0044] Step 4: Based on the wind speed similarity principle, the virtual inertia control parameter optimization method is improved and expanded. The core idea is to use consistent virtual inertia control parameter trajectories for wind turbines in the same wind speed range to adapt to different wind speed scenarios.

[0045] The transfer function expression and analytical expression of the wind turbine set expected virtual inertia control parameter change trajectory described in step 2 are derived, including:

[0046] The moment when wind turbines participate in frequency regulation can be obtained through traversal search and simulation calculation.

[0047] Active power shortage ΔP L (s) is expressed as:

[0048]

[0049] Where ΔP L It is the active power shortage amount.

[0050] The system frequency response dynamic equation expression is:

[0051] ΔP SG (s)+ΔP we (s)-ΔP L (s)=2H sys sΔf(s)+D sys Δf(s)(2)

[0052] Where ΔP SG (s) is the output increment of the traditional unit during frequency regulation; ΔP we (s) is the output increment of wind turbine when frequency is adjusted; H sys and D sys are the system inertia time constant and damping coefficient respectively; s is the Laplace operator; Δf(s) is the system frequency change.

[0053] Not considering D sys The sum of the output of traditional units and wind turbines in the AB section is equal to the disturbance. Based on this characteristic, the dynamic equation expression of the system frequency response in the AB section is:

[0054] ΔP SG (s)+ΔP we (s)-ΔP L (s)=0(3)

[0055] The frequency regulation expression of the traditional steam turbine unit is:

[0056]

[0057] In the formula, F h , T R and R are respectively the work proportion of the high pressure cylinder of the traditional unit, the reheater time constant and the adjustment coefficient.

[0058] During the frequency regulation of wind turbines, the output of traditional units expression:

[0059]

[0060] In the formula, ΔP L The lowest frequency point under the optimal frequency trajectory under disturbance.

[0061] Wind turbine output in section AB The expression is:

[0062]

[0063] In the formula, η is the wind power penetration rate, and the benchmark value is the total capacity of traditional units; H w is the wind turbine rotor inertia time constant; ω r0 is the initial value of the wind turbine rotor speed; k m To capture the coefficient of mechanical power variation; k t is the output active power change coefficient under the maximum power point operation mode; the expected virtual inertia control parameter change trajectory transfer function expression is recorded as k p,ex (s).

[0064] Combining equations (3) to (6), we can further obtain the expected virtual inertia control parameter change trajectory transfer function expression k for segment AB: p,ex (s) is:

[0065]

[0066] In formula (7), the expressions of G1(s) and G2(s) are:

[0067]

[0068] Through simulation tests on different active power shortage scenarios, the active power shortage ΔP L The lowest frequency point under the corresponding optimal frequency trajectory It is approximately equal to a constant (denoted as κ). Further deduction of formula (8) yields:

[0069]

[0070] In formula (9), the expressions of G1′(s) and G2′(s) are:

[0071]

[0072] Expanding the partial fraction of equation (10) yields k p,ex (s) Time domain analytical expression of the change trajectory k p,ex (t):

[0073]

[0074] The specific expressions of α, γ1, γ2, μ1 and μ2 in formula (12) are as follows:

[0075]

[0076] γ2 can be derived from α and γ1:

[0077]

[0078] The incremental transfer function expression and analytical expression of the wind turbine output active power used to correct the dead zone effect described in step 3 are derived, including:

[0079] The existence of dead zone will reduce wind power output, making the actual system frequency minimum point lower than the expected Considering the common frequency regulation dead zone, in order to correct the influence of the dead zone and improve the unit output, the dead zone correction expression is:

[0080] ΔP com (s) = dk p,ex (s)(18)

[0081] In the formula, ΔP com (s) is the increase in active power output of the wind turbine used to correct the dead zone impact; d is the boundary value of the wind turbine frequency regulation dead zone.

[0082] Analytical expression of wind turbine output active power increment ΔP for correcting dead zone effect com (t) is:

[0083]

[0084] In this embodiment, step 4 is aimed at different wind speed scenarios. The core idea is to consider the scenario below the rated wind speed and classify the wind speed into: high wind speed segment, medium wind speed segment, medium-low wind speed segment and low wind speed segment. Based on the wind speed similarity principle, wind turbines in the same wind speed segment adopt consistent wind power virtual inertia control parameter trajectory, that is, the expected wind power virtual inertia control parameter trajectory under the average wind speed in each wind speed segment is adopted, and its trajectory analytical expression is determined according to equations (12) to (17). For units in the low wind speed segment, since the rotor kinetic energy that can be released is small and the rotor speed is low, in order to ensure the safe and stable operation of the unit, the low wind speed unit does not participate in frequency modulation.

[0085] When an active power shortage scenario occurs, the virtual inertia control module takes effect and increases the output of the wind turbine generator set based on formula (12) to provide active power support. Formula (12) is basically independent of the size of the active power shortage. Therefore, this embodiment can be applied to different disturbance scenarios. When the disturbance is large and the dead zone is triggered, the dead zone is corrected based on formula (19). In different wind speed scenarios, the wind speed segment in which the wind speed is located is determined, and the expected virtual inertia control parameter change trajectory under the average wind speed of the wind speed segment is used to participate in frequency modulation.

[0086] The method described in this embodiment can effectively increase the lowest point of the system frequency, improve the system frequency response characteristics, avoid secondary frequency drops, correct the adverse effects of the dead zone, make the system frequency trajectory present a near-optimal form, and have a certain degree of robustness to different wind speeds and disturbance scenarios.

[0087] Example 2

[0088] In this embodiment 2, a wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory is provided, which can be applied to different disturbance and wind speed scenarios to improve the system frequency response characteristics, avoid secondary frequency drop, and correct the influence of dead zone, so as to achieve the approximate optimal system frequency trajectory.

[0089] The optimal system frequency trajectory and the general form of each unit output are as follows: Figure 1 As shown. Figure 1 It can be seen that when the system suffers from active power shortage disturbance, the system frequency drops to the lowest point at point A. During the AB period, the wind turbines participate in frequency modulation, and the speed of decrease of wind turbine support power matches the speed of increase of traditional generator frequency modulation power to keep the system frequency change rate at 0. The lowest frequency point under the optimal frequency trajectory remains unchanged, which is recorded as At point B, the wind turbine exits frequency regulation, the wind turbine output gradually recovers to the initial output value before the disturbance, and the system frequency recovers to the steady-state frequency.

[0090] The wind turbine participation time, i.e. point A, can be obtained through traversal search and simulation calculation.

[0091] Active power shortage ΔP L (s) is expressed as:

[0092]

[0093] Where ΔP L It is the active power shortage amount.

[0094] The system frequency response dynamic equation expression is:

[0095] ΔP SG (s)+ΔP we (s)-ΔP L (s)=2H syssΔf(s)+D sys Δf(s)(2)

[0096] In the formula, ΔP SG (s) is the output increment of the traditional unit during frequency regulation; ΔP we (s) is the output increment of wind turbine when frequency is adjusted; H sys and D sys are the system inertia time constant and damping coefficient respectively; s is the Laplace operator; Δf(s) is the system frequency change.

[0097] Not considering D sys The sum of the output of traditional units and wind turbines in the AB section is equal to the disturbance. Based on this characteristic, the dynamic equation expression of the system frequency response in the AB section is:

[0098] ΔP SG (s)+ΔP we (s)-ΔP L (s)=0(3)

[0099] The frequency regulation expression of the traditional steam turbine unit is:

[0100]

[0101] In the formula, F h 、T R and R are respectively the work proportion of the high pressure cylinder of the traditional unit, the reheater time constant and the adjustment coefficient.

[0102] Output of conventional units in AB section expression:

[0103]

[0104] Wind turbine output in section AB The expression is:

[0105]

[0106] In the formula, η is the wind power penetration rate, and the benchmark value is the total capacity of traditional units; H w is the wind turbine rotor inertia time constant; ω r0 is the initial value of the wind turbine rotor speed; k m To capture the coefficient of mechanical power variation; k t is the output active power change coefficient under the maximum power point operation mode; the expected virtual inertia control parameter change trajectory transfer function expression is recorded as k p,ex (s).

[0107] Combining equations (3) to (6), we can further obtain the expected virtual inertia control parameter change trajectory transfer function expression k for segment AB: p,ex (s) is:

[0108]

[0109] In formula (7), the expressions of G1(s) and G2(s) are:

[0110]

[0111] Through simulation tests on different active power shortage scenarios, the active power shortage ΔP L The lowest frequency point under the corresponding optimal frequency trajectory It is approximately equal to a constant (denoted as κ). Further deduction of formula (8) yields:

[0112]

[0113] In formula (9), the expressions of G1′(s) and G2′(s) are:

[0114]

[0115] Expanding the partial fraction of equation (10) yields k p,ex (s) Time domain analytical expression of the change trajectory k p,ex (t) is:

[0116]

[0117] The specific expressions of α, γ1, γ2, μ1 and μ2 in formula (12) are as follows:

[0118]

[0119] γ2 can be derived from α and γ1:

[0120]

[0121] The existence of dead zone will reduce wind power output, making the actual system frequency minimum point lower than the expected Considering the common frequency regulation dead zone, in order to correct the influence of the dead zone and improve the unit output, the dead zone correction expression is:

[0122]

[0123] In the formula, ΔP com (s) is the increase in active power output of the wind turbine used to correct the dead zone impact; d is the boundary value of the wind turbine frequency regulation dead zone.

[0124] Analytical expression of wind turbine output active power increment ΔP for correcting dead zone effect com (t) is:

[0125] ΔP com (t) = dk p,ex (t)(19)

[0126] Taking the doubly-fed wind turbine as an example, the virtual inertia control block diagram including dead zone correction is as follows: Figure 2 shown.

[0127] Figure 2 In, Q e and Q ref are the actual value and reference value of reactive power output by wind turbines respectively; P we_ref It is the reference value of active power output of wind turbine in the maximum power point tracking mode; i dr_ref 、i qr_ref 、i dr 、i qr are the d-axis and q-axis rotor current reference values, and the d-axis and q-axis rotor currents respectively; v dr 、i qr are the d-axis and q-axis rotor voltages respectively; L r , L m and L s They are the rotor reactance, the mutual reactance between the stator and rotor windings, and the stator reactance; PI is the proportional-integral controller. When an active power shortage occurs, the virtual inertia control module takes effect, and the output of the wind turbine is increased based on formula (12) to provide active power support. When the disturbance is large and the dead zone is triggered, the dead zone is corrected based on formula (19).

[0128] When the wind turbine is in different wind speed scenarios, the unit operation state is different. It can be seen from equations (12) to (17) that the expected virtual inertia control parameter change trajectory is actually affected by the wind speed. If the expected optimal system frequency trajectory is to be achieved under different wind speed scenarios, the virtual inertia change trajectory needs to be derived multiple times, which is obviously difficult to achieve in actual control. Therefore, based on the wind speed similarity principle of wind turbines, wind turbines are classified.

[0129] The rated wind speed is recorded as v N The minimum allowable wind speed for the rotor speed lower limit is denoted as v in , considering the scenario below the rated wind speed, the wind speed interval [v in , v N ] is evenly divided into four wind speed segments, see Table 1.

[0130] Table 1 Wind speed segment classification

[0131]

[0132] vh 、v zd 、v d They respectively represent the boundary wind speeds of each adjacent wind speed segment.

[0133] Since wind turbines with adjacent wind speeds have similar operating conditions, the control effects of the same control strategy are not very different. Therefore, the virtual inertia control parameter optimization method can be improved and expanded based on the wind speed similarity principle. That is, wind turbines with wind speeds in the same wind speed range adopt consistent virtual inertia control parameter trajectories to adapt to different wind speed scenarios.

[0134] The virtual inertia control parameter trajectory of different wind speed segments is determined by the average wind speed of each wind speed segment (i.e., the average wind speed value of each wind speed segment). In the low wind speed segment, the wind turbine rotor speed is relatively low, and the kinetic energy that can be released is relatively small. In order to ensure the safe and stable operation of the wind turbine, the low wind speed unit does not participate in the frequency regulation.

[0135] To illustrate the effectiveness of the wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory proposed in this embodiment, a four-machine two-region simulation model is built on the MATLAB / Simulink simulation platform. Based on the standard model, the simulation model replaces one of the traditional units with a wind farm consisting of 450 1.5MW wind turbines. The total installed capacity of the traditional units is 2700MW, and the wind power penetration rate is 20%. The following three tests are performed:

[0136] Test 1: It shows that the proposed optimization method can effectively improve the lowest point of system frequency and achieve the optimal form of system frequency trajectory.

[0137] The frequency regulation effects of wind turbines using additional fixed parameter integrated inertia control, adaptive integrated inertia control, and the proposed optimization method were compared and tested. For the convenience of analysis, the three control methods are represented by C1, C2, and C3 respectively. It should be noted that C1 and C2 use timed frequency reduction, and the frequency regulation time is 20s.

[0138] Figure 3 The control effects of the three methods C1, C2 and C3 are compared. Figure 3 This is a comparison chart of the lowest system frequency points of the three methods under different disturbances, where the disturbance varies from 0.05pu to 0.15pu (interval 0.01pu).

[0139] Depend on Figure 3 It can be seen that the proposed method in different active power shortage scenarios can effectively and adaptively adjust the unit output active power according to the shortage size, and approximately achieve the desired control effect.

[0140] Test 2: Dead zone correction effectiveness.

[0141] Set the dead zone boundary value d to 0.1Hz, assume that the wind speed is the rated wind speed, and a 0.1pu load sudden increase disturbance occurs at 5s. In the two cases of not setting the dead zone and taking the dead zone into account but not correcting, the system frequency response and the wind turbine output power waveform are compared as shown below: Figure 4 (a) Figure 4 (c) The comparison results of the corrected system frequency response and wind power output power with those without setting the dead zone are shown in Figure 2. Figure 4 (b) Figure 4 (d) as shown.

[0142] Depend on Figure 4 (a) and (b) show that the output of wind turbines is reduced due to the existence of the dead zone, and the minimum system frequency is 0.04 Hz lower than the expected value. Figure 4 (c) and (d) show that after the dead zone correction module is introduced, the output of wind turbines in the frequency regulation stage is increased, thereby raising the lowest point of the system frequency, and the frequency trajectory is basically consistent with the expected optimal frequency trajectory. The results prove the effectiveness of the dead zone correction.

[0143] Test 3: Effectiveness of the proposed optimization method under different wind speed scenarios.

[0144] The data of each wind speed section are shown in Table 2.

[0145] Table 2 Data of each wind speed segment

[0146]

[0147] The analytical expression of the expected virtual inertia control parameter trajectory in each wind speed segment is determined by equations (12) to (17).

[0148] The absolute error between the lowest frequency point and the expected value in each wind speed range caused by the active power shortage and wind speed change is r Impact Figure 5 , where the active power shortage disturbance range is 0.05pu~0.15pu, and the wind speed variation range corresponds to each wind speed segment. Within the wind speed segment that allows frequency modulation, the system frequency trajectory can be approximately optimized, and its absolute error e r ≤0.02Hz (within the acceptable error range).

[0149] In summary, the wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory provided in this embodiment 2 can effectively improve the lowest point of the system frequency, improve the system frequency response characteristics, and make the system frequency trajectory present an approximately optimal form, and can correct the adverse effects of the dead zone on the system frequency, and has a certain adaptability to different wind speeds and disturbance scenarios. In addition, this method adopts a virtual inertia control structure, and does not require a substantial modification of the wind turbine power controller structure, and is highly practical.

[0150] Example 3

[0151] This embodiment 3 provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, the wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory as described above is implemented. The method includes:

[0152] According to the optimal system frequency trajectory and the output characteristics of each unit, the transfer function of the expected virtual inertia control parameter change trajectory of the wind turbine is constructed; considering the influence of the dead zone, the wind turbine output active power increment transfer function used to correct the dead zone influence is constructed;

[0153] Considering the scenario below the rated wind speed, based on the principle of wind speed similarity and combining the transfer function of the wind turbine set's expected virtual inertia control parameter change trajectory and the wind turbine set's output active power increment transfer function, it is determined that wind turbine sets in the same wind speed range should adopt consistent wind power virtual inertia control parameter trajectory.

[0154] Example 4

[0155] This embodiment 4 provides a computer device, including a memory and a processor, the processor and the memory communicate with each other, the memory stores program instructions executable by the processor, the processor calls the program instructions to execute the wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory as described above, the method comprising:

[0156] According to the optimal system frequency trajectory and the output characteristics of each unit, the transfer function of the expected virtual inertia control parameter change trajectory of the wind turbine is constructed; considering the influence of the dead zone, the wind turbine output active power increment transfer function used to correct the dead zone influence is constructed;

[0157] Considering the scenario below the rated wind speed, based on the principle of wind speed similarity and combining the transfer function of the wind turbine set's expected virtual inertia control parameter change trajectory and the wind turbine set's output active power increment transfer function, it is determined that wind turbine sets in the same wind speed range should adopt consistent wind power virtual inertia control parameter trajectory.

[0158] Example 5

[0159] This embodiment 5 provides an electronic device, including: a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory, so that the electronic device executes instructions for implementing the wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory as described above, the method comprising:

[0160] According to the optimal system frequency trajectory and the output characteristics of each unit, the transfer function of the expected virtual inertia control parameter change trajectory of the wind turbine is constructed; considering the influence of the dead zone, the wind turbine output active power increment transfer function used to correct the dead zone influence is constructed;

[0161] Considering the scenario below the rated wind speed, based on the principle of wind speed similarity and combining the transfer function of the wind turbine set's expected virtual inertia control parameter change trajectory and the wind turbine set's output active power increment transfer function, it is determined that wind turbine sets in the same wind speed range should adopt consistent wind power virtual inertia control parameter trajectory.

[0162] In summary, the wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory described in the embodiment of the present invention. In the scenario involving wind power participation in frequency regulation, the expected virtual inertia control parameter change trajectory transfer function expression and analytical expression are derived according to the optimal system frequency trajectory, wind turbine output and traditional unit output characteristics. In addition, the dead zone correction expression is derived considering the dead zone influence, and the wind power virtual inertia control parameter optimization method is improved and expanded to be suitable for different wind speed scenarios. The present invention gives full play to the frequency regulation potential of wind turbines, effectively improves the system frequency response characteristics under different wind speed and disturbance scenarios, avoids secondary frequency drops, and can correct the influence of dead zones to achieve approximate optimal system frequency trajectory, and has strong practicality.

[0163] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0164] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0165] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0166] These computer program instructions can also be loaded onto a computer or other programmable data processing device, and a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0167] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative work on the basis of the technical solution disclosed in the present invention should be included in the scope of protection of the present invention.

Claims

1. A wind power virtual inertia control parameter optimization method based on optimal system frequency trajectory, characterized in that: include: According to the optimal system frequency trajectory and the output characteristics of each unit, the wind turbine unit expected virtual inertia control parameter change trajectory transfer function is constructed; considering the influence of the dead zone, the wind turbine unit output active power increment transfer function used to correct the dead zone influence is constructed; among them, The expected virtual inertia control parameter change trajectory transfer function expression k p,ex (s) is: In the formula, the expressions of G1(s) and G2(s) are: Where η is the wind power penetration rate, F h , T R and R are respectively the work ratio of the high pressure cylinder of the conventional unit, the time constant of the reheater and the adjustment coefficient, ΔP L The lowest frequency point under the optimal frequency trajectory under disturbance, ΔP L is the active power shortage, s is the Laplace operator, H w is the wind turbine rotor inertia time constant, ω r0 is the initial value of the wind turbine rotor speed, k m To capture the coefficient of mechanical power variation, k t It is the output active power variation coefficient under the maximum power point operation mode; The existence of dead zone will reduce wind power output, making the actual system frequency minimum point lower than the expected Low, considering the common frequency regulation dead zone, in order to correct the influence of the dead zone and improve the unit output, the dead zone correction expression is: ΔP com (s)=dk p,ex (s); Where ΔP com (s) is the wind turbine output active power increment used to correct the dead zone effect; d is the wind turbine frequency regulation dead zone boundary value; Analytical expression of wind turbine output active power increment ΔP for correcting dead zone effect com (t) is: in, Among them, the active power shortage ΔP L The lowest frequency point under the corresponding optimal frequency trajectory is approximately equal to a constant, denoted as κ; γ2 is derived from α and γ1: Considering the scenario below the rated wind speed, based on the principle of wind speed similarity and combining the transfer function of the wind turbine set's expected virtual inertia control parameter change trajectory and the wind turbine set's output active power increment transfer function, it is determined that wind turbine sets in the same wind speed range should adopt consistent wind power virtual inertia control parameter trajectory.

2. The wind power virtual inertia control parameter optimization method based on optimal system frequency trajectory according to claim 1 is characterized in that: For different wind speed scenarios, considering the rated wind speed scenario, the wind speed is classified into: high wind speed segment, medium wind speed segment, medium-low wind speed segment and low wind speed segment. Based on the principle of wind speed similarity, wind turbines in the same wind speed segment adopt a consistent wind power virtual inertia control parameter trajectory, that is, the expected wind power virtual inertia control parameter trajectory under the average wind speed in each wind speed segment is adopted.

3. The wind power virtual inertia control parameter optimization method based on optimal system frequency trajectory according to claim 1 is characterized in that: Determining the transfer function expression of the expected virtual inertia control parameter change trajectory of the wind turbine group includes: obtaining the time when the wind turbine group participates in frequency regulation through traversal search and simulation calculation; determining the active power shortage and system frequency response dynamic equation; based on the traditional steam turbine unit frequency regulation, determining the traditional unit output during the wind turbine unit frequency regulation, and determining the wind turbine unit output; obtaining the transfer function expression of the expected virtual inertia control parameter change trajectory.

4. The wind power virtual inertia control parameter optimization method based on optimal system frequency trajectory according to claim 3 is characterized in that: The active power shortage and the lowest frequency point under the corresponding optimal frequency trajectory are approximately equal to a constant, and the time domain analytical expression of the changing trajectory is obtained.

5. The wind power virtual inertia control parameter optimization method based on system frequency trajectory optimization according to claim 1 is characterized in that: The wind turbine output active power increment transfer function expression for correcting the dead zone effect is determined, including: the existence of the dead zone will reduce the wind power output, making the actual system frequency minimum point lower than expected; considering the common frequency regulation dead zone, in order to correct the dead zone effect to improve the unit output, based on the wind turbine output active power increment for correcting the dead zone effect and the wind turbine frequency regulation dead zone boundary value, the dead zone correction expression is determined.

6. The wind power virtual inertia control parameter optimization method based on system frequency trajectory optimization according to claim 1 is characterized in that: When an active power shortage occurs, the output of wind turbines is increased to provide active power support. When the disturbance is large, the dead zone is triggered and the dead zone is corrected. In different wind speed scenarios, the wind speed segment is determined, and the expected virtual inertia control parameter change trajectory at the average wind speed of the wind speed segment is used to participate in frequency modulation.

7. A wind power virtual inertia control parameter optimization system based on optimal system frequency trajectory, characterized in that: include: The construction module is used to construct the transfer function of the change trajectory of the expected virtual inertia control parameters of the wind turbine according to the optimal system frequency trajectory and the output characteristics of each unit; considering the influence of the dead zone, the wind turbine output active power increment transfer function for correcting the influence of the dead zone is constructed; wherein, The expected virtual inertia control parameter change trajectory transfer function expression k p,ex (s) is: In the formula, the expressions of G1(s) and G2(s) are: Where η is the wind power penetration rate, F h , T R and R are respectively the work ratio of the high pressure cylinder of the conventional unit, the time constant of the reheater and the adjustment coefficient, ΔP L The lowest frequency point under the optimal frequency trajectory under disturbance, ΔP L is the active power shortage, s is the Laplace operator, H w is the wind turbine rotor inertia time constant, ω r0 is the initial value of the wind turbine rotor speed, k m To capture the coefficient of mechanical power variation, k t It is the output active power variation coefficient under the maximum power point operation mode; The existence of dead zone will reduce wind power output, making the actual system frequency minimum point lower than the expected Low, considering the common frequency regulation dead zone, in order to correct the influence of the dead zone and improve the unit output, the dead zone correction expression is: ΔP com (s)=dk p,ex (s); Where ΔP com (s) is the wind turbine output active power increment used to correct the dead zone effect; d is the wind turbine frequency regulation dead zone boundary value; Analytical expression of wind turbine output active power increment ΔP for correcting dead zone effect com (t) is: in, Among them, the active power shortage ΔP L The lowest frequency point under the corresponding optimal frequency trajectory is approximately equal to a constant, denoted as κ; γ2 is derived from α and γ1: The solution module is used to consider the scenario below the rated wind speed. Based on the wind speed similarity principle, combined with the wind turbine expected virtual inertia control parameter change trajectory transfer function and the wind turbine output active power increment transfer function, it determines that the wind turbines in the same wind speed range adopt a consistent wind power virtual inertia control parameter trajectory.

8. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by the processor, the wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory as described in any one of claims 1 to 6 is implemented.

9. A computer device, characterized in that: It includes a memory and a processor, the processor and the memory communicate with each other, the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory as described in any one of claims 1-6.

10. An electronic device, characterized in that: include: A processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory so that the electronic device executes instructions for implementing the wind power virtual inertia control parameter optimization method based on the optimal system frequency trajectory as described in any one of claims 1 to 6.

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