CN114629133A - Wind turbine generator frequency modulation parameter optimization method considering frequency twice dropping - Google Patents

Wind turbine generator frequency modulation parameter optimization method considering frequency twice dropping Download PDF

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CN114629133A
CN114629133A CN202111676288.0A CN202111676288A CN114629133A CN 114629133 A CN114629133 A CN 114629133A CN 202111676288 A CN202111676288 A CN 202111676288A CN 114629133 A CN114629133 A CN 114629133A
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吴琛
辛焕海
张雯欣
黄伟
高晖胜
程旻
谢一工
张丹
曾丕江
黄润
刘旭斐
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Yunnan Power Grid Co Ltd
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Abstract

The invention relates to a wind turbine generator frequency modulation parameter optimization method considering frequency twice dropping, and belongs to the technical field of power system frequency modulation. The method is used for establishing a simplified frequency response model to analyze power disturbance delta P in a multi-machine power system comprising power generation equipmentLSystem overall frequency response characteristics under(s); the overall frequency response characteristic of the system is expressed by frequency common-mode component delta omega(s); combining the participation of the wind turbine generator in frequency modulation and the quitting of the frequency modulation action to obtain a system frequency track analytical formula considering the frequency secondary falling, and obtaining a primary and secondary falling lowest point analytical expression of the frequency based on the derivation of the analytical formula; analytic expression based on frequency primary and secondary falling lowest pointAnd optimizing the wind turbine generator frequency modulation parameters meeting the system frequency modulation requirements by using an over-optimization algorithm. The method can comprehensively consider the lowest frequency point of the system frequency in the primary falling and secondary falling processes to optimize the wind power frequency modulation parameters, and is favorable for better supporting the system frequency.

Description

Wind turbine generator frequency modulation parameter optimization method considering frequency twice dropping
Technical Field
The invention belongs to the technical field of power system frequency modulation, relates to a wind turbine generator frequency modulation parameter optimization method, and particularly relates to a wind turbine generator frequency modulation parameter optimization method considering frequency twice falling.
Background
In recent years, the permeability of new energy such as wind and light in a power system is continuously improved, and the new energy generally runs in a maximum power tracking mode and does not participate in frequency modulation, so that the inertia of the system is reduced, the frequency modulation capability of the system is reduced, and the adverse effect is brought to the frequency stability of the system. Therefore, scholars at home and abroad propose a control strategy for actively participating in frequency modulation in new energy grid connection.
The wind turbine is generally connected to the grid through a converter, and the rotor speed is decoupled from the frequency of the power system. In order to support the frequency by utilizing the kinetic energy in the fan rotor, additional frequency modulation control is required. The fan based on the control can release the kinetic energy of the rotor in the process of supporting the frequency, and the rotating speed is reduced. When the rotor reaches the minimum rotational speed limit, it cannot continue to release kinetic energy to support the system frequency, but instead needs to absorb power from the grid to increase the rotational speed, which may result in a secondary drop in frequency. At present, the research of setting the wind power frequency modulation parameters by comprehensively considering the frequency characteristics of the system in the process of primary falling and secondary falling is less. If the frequency modulation parameter setting is carried out only by taking the lifting of the primary falling lowest point as a target, the wind turbine generator provides a large amount of active support for the system in the primary falling process of the frequency, and correspondingly, more energy needs to be absorbed when the rotating speed is recovered, so that the secondary falling lowest point is further reduced. If the frequency modulation parameters are set only by taking the avoidance of the frequency secondary falling as a target, the wind turbine generator is limited to be actively supported in the process of the frequency primary falling, the frequency secondary falling is avoided, and the lowest point of the frequency primary falling is not well improved.
Therefore, in order to provide effective frequency support for the system and meet the actual frequency modulation requirement of the system, the whole frequency dynamic process including primary falling and secondary falling needs to be comprehensively considered, the lowest point of the primary falling is lifted as much as possible, and the lowest point of the secondary falling frequency is ensured not to be lower.
Disclosure of Invention
The invention aims to solve the defects of the prior art, optimize the frequency modulation parameters of a wind turbine generator to provide effective frequency support for a system, and provide a wind turbine generator frequency modulation parameter optimization method considering frequency twice falling.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a wind turbine generator frequency modulation parameter optimization method considering frequency twice dropping comprises the following steps:
step (1), establishing a simplified frequency response model to analyze power disturbance delta P in a multi-machine power system containing power generation equipmentLSystem overall frequency response characteristics under(s); the overall frequency response characteristic of the system is adoptedExpressed in terms of frequency common mode component Δ ω(s);
step (2), combining the wind turbine generator to participate in frequency modulation and quit the frequency modulation action, obtaining a system frequency track analytic expression considering frequency secondary falling;
step (3), obtaining a frequency primary and secondary falling lowest point analytic expression based on the analytic derivation of the system frequency track analytic expression;
and (4) optimizing wind turbine generator frequency modulation parameters meeting system frequency modulation requirements through an optimization algorithm based on the frequency primary and secondary falling lowest point analytical expression.
Further, preferably, the power generation equipment comprises a synchronous machine and a wind turbine.
Further, it is preferable that the specific method of step (1) is:
the multi-machine power system has n devices which can participate in frequency modulation power generation; power disturbance of Δ PL(s)，ΔPL(s)＝-ΔPLS, s denotes the Laplace operator, Δ PLRepresenting the magnitude of the disturbance; analyzing system frequency common mode component delta omega(s) and power disturbance delta PLThe simplified frequency response model of the(s) relationship is as follows:
Figure BDA0003451419770000021
in the formula, Jus，DusAnd KusRespectively expressed as the effective inertia, effective damping coefficient and effective static deviation coefficient of the system, JusBy effective inertia J of each frequency-modulated power generation equipmentuiAre superimposed (i.e. summed) to form DusEffective damping coefficient D of each frequency modulation power generation deviceuiAre superposed to formusThe effective static difference-adjusting coefficient K of each frequency-modulation power generation deviceuiAre superposed to form T0Adjusting a time constant for the system;
power response delta P of each frequency modulation power generation deviceei(s) satisfies with the frequency common mode component Δ ω(s):
Figure BDA0003451419770000022
in the formula, Jui，DuiAnd KuiRespectively representing the effective inertia, the effective damping coefficient and the effective static difference-adjusting coefficient of each frequency modulation power generation device; the effective coefficient is based on the actual model G of each devicei(s) derived power response Δ PeiAnd(s) is an optimization target and is obtained by least square algorithm fitting.
Further, preferably, in the step (2), the wind turbine generator is combined to participate in frequency modulation and quit the frequency modulation action, and the analytic expression of the system frequency trajectory considering the frequency secondary falling is obtained as follows:
Figure BDA0003451419770000031
in the formula (I), the compound is shown in the specification,
Figure BDA0003451419770000032
wherein, Jus1、Dus1、1/Kus1Expressed as the effective inertia, effective damping coefficient and effective static difference coefficient of the system, J, when the wind turbine generator participates in frequency modulationus2、Dus2、1/Kus2The coefficient is expressed after the wind turbine generator exits frequency modulation; omegad、ωd1Respectively representing the damping oscillation frequency in the process of primary falling and secondary falling of the system frequency; sigma, sigma1Respectively representing the attenuation coefficients of the system frequency in the processes of primary falling and secondary falling; t is t1Indicating the time for the wind turbine generator to exit from frequency modulation; p is1Represents t1The system input power disturbance magnitude at the moment; p is0Denotes t0And (5) the input power disturbance of the system at the moment.
Further, it is preferable that the specific method of step (3) is:
(3.1) one-time frequency dip lowest point Δ fnadir1
Figure BDA0003451419770000033
In the formula, tnadir1The moment of maximum frequency deviation occurs once;
(3.2) lowest point of secondary frequency dip Δ fnadir2
Figure BDA0003451419770000034
In the formula, tnadir2The moment of occurrence of the quadratic maximum frequency deviation.
Further, it is preferable that the specific method of the step (4) is:
the optimization problem derived from the system frequency modulation requirements is specifically described as
Figure BDA0003451419770000041
In the formula, Jul、Dul、1/KulThe parameter is expressed as a parameter equivalent to the simplified frequency response model by the wind turbine generator frequency-power response transfer function; p isw(t)、Pm(t) respectively representing the output electromagnetic power and the input mechanical power of the wind turbine; hWExpressed as the equivalent time constant of the wind turbine; omegarExpressed as wind turbine rotor speed;
and constructing the inequality constraint and the target function into a Lagrange function meeting the KKT condition, and nesting the Lagrange multiplier method and the global search algorithm to obtain a parameter setting result under optimal control in the active frequency modulation process of the wind turbine generator.
Compared with the prior art, the invention has the beneficial effects that:
the method can analyze the overall frequency characteristic of the system by utilizing the simplified frequency response model, obtain the first-time and second-time minimum point analytical expressions, establish an optimization problem by taking the minimum point as a target to optimize the wind power frequency modulation parameter under the condition of comprehensively considering two-time frequency drop, and is favorable for better supporting the system frequency.
After the frequency modulation parameter obtained by the method is subjected to frequency modulation, the secondary falling lowest point and the primary falling lowest point of the system frequency can be simultaneously improved compared with the frequency modulation parameter obtained by the conventional method.
Drawings
FIG. 1 is a schematic flow diagram of the process of the present invention.
Fig. 2 is a schematic diagram of a three-machine system in simulation verification according to an embodiment of the present invention.
FIG. 3 is a diagram of a steam turbine governor system model in simulation verification according to an embodiment of the present invention.
Fig. 4 is a control diagram of the wind turbine generator power in simulation verification according to the embodiment of the present invention.
FIG. 5 is a comparison graph of a simulation trajectory of a wind turbine generator set participating in frequency modulation and an approximate trajectory of a simplified frequency response model in simulation verification according to an embodiment of the invention.
FIG. 6 is a comparison diagram of the frequency and the rotor speed of the wind turbine generator under different parameter setting modes.
Detailed Description
The present invention will be described in further detail with reference to examples.
It will be appreciated by those skilled in the art that the following examples are illustrative of the invention only and should not be taken as limiting the scope of the invention. The examples do not specify particular techniques or conditions, and are performed according to the techniques or conditions described in the literature in the art or according to the product specifications. The materials or equipment used are not indicated by manufacturers, and all are conventional products available by purchase.
1) In a multi-machine power system comprising (synchronous machines, wind turbines, etc.) power generation equipment, a simplified frequency response model is proposed to analyze power disturbance delta PLThe overall frequency response characteristic (frequency common mode component) Δ ω(s) of the system under(s);
2) combining the participation of the wind turbine generator in frequency modulation and the quitting of the frequency modulation action to obtain a system frequency track considering the frequency secondary falling;
3) obtaining a frequency primary and secondary falling lowest point analytic expression based on the analytic derivation of the system frequency track;
4) optimizing wind turbine generator frequency modulation parameters meeting system frequency modulation requirements through an optimization algorithm based on the primary and secondary falling minimum point analytical expressions of frequency;
in the step 1), the multi-machine power system has n pieces of frequency modulation power generation equipment (if the dynamic response of equipment such as loads is considered, the equipment is regarded as special power generation equipment); the power disturbance (such as sudden load increase) is delta PL(s)，ΔPL(s)＝-ΔPLS, s denotes the Laplace operator, Δ PLRepresenting the size of the disturbance; analyzing system frequency common mode component delta omega(s) and power disturbance delta PLThe simplified frequency response model of the(s) relationship is as follows:
Figure BDA0003451419770000051
in the formula, Jus，DusAnd KusRespectively expressed as effective inertia, effective damping coefficient and effective static difference-adjusting coefficient of the system, and formed by superposing the effective coefficients of all frequency-modulation power generation equipment, T0The system settling time constant is obtained.
Respective device power response Δ Pei(s) satisfies with the system frequency common mode component Δ ω(s):
Figure BDA0003451419770000052
in the formula, Jui，DuiAnd KuiRespectively expressed as effective inertia, effective damping coefficient and effective static difference-adjusting coefficient of each frequency-modulation power generation device. The effective coefficients are based on actual models G of all devicesi(s) derived power response Δ PeiAnd(s) is an optimization target and is obtained by least square algorithm fitting.
In the step 2), the approximate frequency trajectory under the step disturbance can be obtained by using the simplified frequency response model as follows:
Figure BDA0003451419770000053
if the system frequency is modulatedAfter a period of time, the wind turbine generator quits frequency modulation, so that the unified structure parameters of the system and the input power disturbance of the system are changed. Definition Jus1、Dus1、1/Kus1The effective coefficient of the system is unified when the wind turbine generator participates in frequency modulation, Jus2、Dus2、1/Kus2Is t1Coefficient of the wind turbine generator after exiting frequency modulation at the moment; delta PL1Is t1Time of system input power disturbance, and t0Time of day power disturbance Δ PLThe rotating speed recovery strategy adopted when the wind turbine generator quits frequency modulation is related; if the wind turbine generator adopts a constant output electromagnetic power recovery rotation speed strategy, the wind turbine generator is at t1Variation Δ P of electromagnetic power output at a timew(t1)＝ΔPm(t1)-ΔPd，ΔPm(t1) For wind turbine at t1Change in mechanical power, Δ P, input at a timedTo define the power difference, satisfy Δ PL1＝ΔPL+ΔPd+ΔPm(t1)。
An approximate frequency time domain analytic expression considering the frequency primary fall and the secondary fall can be obtained through a state space solution:
Figure BDA0003451419770000061
in the formula (I), the compound is shown in the specification,
Figure BDA0003451419770000062
wherein, ω isd、ωd1、σ、σ1Respectively representing the damping oscillation frequency and the damping coefficient in the primary falling and secondary falling processes of the system frequency; t is t1Indicating the time for the wind turbine generator to exit from frequency modulation; p1Represents t1The system input power disturbance magnitude at the moment; p0Represents t0And (5) the input power disturbance of the system at the moment.
The mechanical power input by the wind turbine meets the following requirements:
Figure BDA0003451419770000063
in the formula, rho and R, v are respectively air density, wind wheel radius and undisturbed wind speed; cp(λ, β) is a wind energy utilization coefficient, and includes:
Figure BDA0003451419770000071
wherein, lambda and beta are respectively the tip speed ratio and the pitch angle, omegarExpressed as wind turbine rotor speed; coefficient c1～c8Satisfies the following conditions: c. C1＝0.5176、c2＝116、c3＝0.4、c4＝5、c5＝21、c6＝0.0068、c7＝0.08、c8＝0.035。
In the step 3), the analytic expressions of the primary and secondary frequency drop lowest points are obtained by derivation of a frequency trajectory analytic expression considering the primary and secondary frequency drops:
Figure BDA0003451419770000072
in the formula, tnadir1For a time of maximum frequency deviation, tnadir2The moment of occurrence of the quadratic maximum frequency deviation.
In the step 4), the set system frequency modulation requirement is to raise the lowest point of the primary drop of the system frequency as much as possible, ensure that the lowest point of the secondary drop of the frequency is not more than the lowest point of the primary drop of the frequency, and ensure that the rotating speed of the wind turbine generator does not reach the lowest rotating speed limit during the period that the wind turbine generator does not quit the frequency modulation, so that the wind turbine generator stalls and the frequency drops more seriously.
The optimization problem derived from the system frequency modulation requirements is described in detail as follows:
Figure BDA0003451419770000073
in the formula, Jul、Dul、1/KulExpressed as a parameter equivalent to a unified structure by a wind turbine generator frequency-power response transfer function; pw(t)、Pm(t) respectively representing the output electromagnetic power and the input mechanical power of the wind turbine; hWExpressed as the equivalent time constant of the wind turbine; omegarExpressed as the wind turbine rotor speed.
And constructing the inequality constraint and the target function into a Lagrangian function meeting a KKT (Karush-Kuhn-Tucker) condition, and nesting the Lagrangian multiplier method and a global search algorithm to obtain a parameter setting result under optimal control in the active frequency modulation process of the wind turbine generator.
Examples of applications
As shown in FIG. 1, the method of the invention is adopted to process, and the power generation equipment in a multi-machine power system comprises a synchronous machine, a wind turbine generator and the like.
Combining a simplified frequency response model to obtain power disturbance delta PL(s) is related to the overall frequency response of the system Δ ω(s). Then adopting least square algorithm and combining transfer functions G of all devicesiAnd(s) obtaining four parameters of effective inertia, effective damping, effective static difference adjustment and system difference adjustment time constants of each power generation device. And finally, solving the lowest point of the frequency drop twice by using the parameters and optimizing the frequency modulation parameters of the wind turbine generator.
The specific embodiment of the invention is as follows:
a three-machine power system is built in Matlab/Simulink software, as shown in FIG. 2. In the figure, the capacity of the synchronizers G1 and G2 at the nodes 1 and 2 are respectively 200MVA and 100MVA, and the prime movers adopt steam turbines. The capacity of the double-fed wind turbine WTG3 at the node 3 is 30 MVA. The nodes 4-6 are network nodes. The nodes 7-9 are load nodes, and the load is a constant power load. The network nodes and the load nodes are collectively referred to as constant power nodes. The line purity is expressed in table 1 when the capacity of G2 is used as a capacity reference value. In a steady state, the voltage of each node is converted into 1, and the phase angle difference of each line is converted into 0.
Table 1 example line reactance values in simulation verification
X14 0.05 X25 0.15 X36 0.05
X47 0.1 X48 0.1 X57 0.2
X59 0.2 X68 0.1 X69 0.1
Using the capacity of G2 as a capacity reference value, F is ═ F1,F2,F3]T＝[2,1,1]T。FiIs the capacity ratio of each power generation device.
G1 and G2 are steam turbine units,frequency-active transfer function Gi(s) is
Gi(s)＝Figi(s)
gi(s)＝Jis+Di+GTSi(s)
Figure BDA0003451419770000081
Wherein GTSi(s) is GiThe transfer function of a governor-turbine system (simply referred to as a governor system) is modeled in fig. 3. The parameters per unit of the rated power per unit are as follows: moment of inertia J1＝J28 s; damping coefficient D1＝D 22; rate of decrease R1＝R20.05; time constant T of speed regulatorG1＝TG20.2 s; time constant T of steam inlet chamberCH1＝TCH20.3 s; time constant T of reheaterRH1＝10s， TRH25 s; high pressure cylinder power ratio FHP1＝FHP2＝0.3。
The wind turbine generator adopts a DFIG model as shown in FIG. 4, wherein V issqThe component of the q axis of the voltage at the stator side of the wind turbine generator is obtained; the PLL is a phase-locked loop; omegarefIs the rated value of the angular frequency of the power grid; omegagIs the grid angular frequency; omegarThe rotating speed of the rotor of the wind turbine generator set; kJAs a virtual coefficient of inertia, KDIs the sag factor; t is1Is a filtering link time constant; pMPPTThe active power reference value obtained by the MPPT curve; pinAnd PdpAdditional active reference value components generated for virtual inertia and droop control respectively; prefThe reference value of the active power of the wind turbine generator is Pm wind power mechanical power; p isWThe wind power generates electromagnetic power; delta PdAnd the difference value between the mechanical power and the electromagnetic power at the moment of exiting the frequency modulation.
Difference value delta P of rotating speed recovery powerd0.03p.u, frequency-active transfer function G on the electromechanical scale3(s) is
G3(s)＝F3g3(s)
Figure BDA0003451419770000091
The values of the parameters are shown in table 2.
Table 2 parameter values of part of inverter variables in simulation verification of embodiment
Figure BDA0003451419770000092
Figure BDA0003451419770000101
By adopting the method of the invention, a relational expression of disturbance and frequency response is obtained:
Figure BDA0003451419770000102
when a 50MW power disturbance occurs at node 8. Combining the transfer functions G of the devices in a time range within 8s for the frequency common mode component by a least square algorithmiAnd(s) obtaining four parameters of effective inertia, effective damping, effective static difference adjustment and system difference adjustment time constants of each power generation device. The calculation results are shown in table 3.
TABLE 3 Effect coefficients of the respective Power plants
Reduced frequency response model effective coefficients G1 G2 WTG3
T
0 5 5 5
Jui 13.94 6.79 4.50
Dui 11.46 5.73 6.64
1/Kui 23.58 16.73 -1.06
According to the method of the present invention, a frequency trace and system common mode trace pair is obtained by using a simplified frequency response model, as shown in fig. 5. As can be seen from FIG. 5, at different FM exit times t1And then, the frequency track obtained based on the simplified frequency response model is basically consistent with the system common mode track. The established simplified frequency response model can analyze the common-mode frequency characteristic of the system in a long period of time, and the wind power frequency modulation parameter optimization is carried out by using the analytic expression of the system frequency twice falling to the lowest point calculated under the model.
When the wind turbine generator frequency modulation parameter setting simulation is carried out, the influence of the wind turbine generator frequency modulation control parameter on the lowest point of the first and second dropping of the frequency is mainly researched, and the exiting frequency modulation time t is given in the optimization14 s. The initial rotating speed of the wind turbine generator is 1.1/p.u., and the lowest rotating speed is taken to limit omegarminIs 0.7/p.u. The setting result of the wind turbine generator set parameters under different capacity ratios of the WTG3 obtained through the optimization algorithm is shown in Table 4.
TABLE 4 optimal control parameter setting result of wind turbine generator
Figure BDA0003451419770000103
Figure BDA0003451419770000111
In order to verify the effectiveness of the provided frequency modulation parameter setting method, the wind power capacity is 5% as an example, and system frequency responses obtained by the following frequency modulation parameter setting methods are compared: (1) the methods as set forth herein; (2) the kinetic energy of the rotor is fully utilized, and virtual inertia control is taken as a main control; (3) the kinetic energy of the rotor is fully utilized, and the downward hanging control is mainly performed; (4) the method consumes the same kinetic energy of the rotor as the method provided by the text, and takes virtual inertia control as the main control; (5) the wind turbine generator does not participate in frequency modulation.
Under the system and disturbance, the kinetic energy constraint of the rotor is considered, and when the following droop control is taken as the main control, the parameter D of the wind turbine generatoru3A maximum value of about 230; wind turbine generator parameter J mainly controlled by virtual inertiau3The maximum value is about 400; and controlling the virtual inertia as a main parameter Ju3 value 22.9 under the condition of consuming the same rotor kinetic energy as the optimized result.
The frequency change of the system and the rotating speed change of the rotor of the wind turbine generator set obtained by comparing the setting parameters and carrying out simulation are shown in FIG. 6. According to the figure, in the 5 wind turbine generator frequency modulation control parameter setting methods, the method can optimally improve the first and second dropping lowest points of the system frequency. Therefore, the setting of the control parameters of the wind turbine generator under different capacity ratios is completed by utilizing the optimization problem, and the effective frequency support including the secondary falling process can be realized.
According to the result, the frequency modulation parameters of the wind turbine generator can be reasonably set by utilizing the analyzed minimum frequency point and an optimization algorithm so as to meet the frequency modulation requirements that the minimum frequency secondary falling point is greater than the minimum frequency primary falling point and the minimum deviation of the minimum frequency primary falling point is ensured to be as small as possible.
The example of the invention proves the approximation method of the overall frequency track of the multi-machine power system comprising the wind turbine generator and the like and the effectiveness of the frequency modulation parameter setting algorithm of the wind turbine generator.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (6)

1. A wind turbine generator frequency modulation parameter optimization method considering frequency twice dropping is characterized by comprising the following steps:
step (1), establishing a simplified frequency response model to analyze power disturbance delta P in a multi-machine power system containing power generation equipmentLSystem overall frequency response characteristics under(s); the overall frequency response characteristic of the system is expressed by frequency common-mode component delta omega(s);
step (2), combining the wind turbine generator to participate in frequency modulation and quit the frequency modulation action, obtaining a system frequency track analytic expression considering frequency secondary falling;
step (3), obtaining a frequency primary and secondary falling lowest point analytic expression based on the analytic derivation of the system frequency track analytic expression;
and (4) optimizing wind turbine generator frequency modulation parameters meeting system frequency modulation requirements through an optimization algorithm based on the frequency primary and secondary falling lowest point analytical expression.
2. The method for optimizing the frequency modulation parameters of the wind turbine generator considering the frequency double dropping as claimed in claim 1, wherein the power generation equipment comprises a synchronous machine and a wind turbine generator.
3. The wind turbine generator frequency modulation parameter optimization method considering frequency double dropping according to claim 1, wherein the specific method in the step (1) is as follows:
the multi-machine power system has n devices which can participate in frequency modulation power generation; power disturbance of Δ PL(s)，ΔPL(s)＝-ΔPLS, s denotes the Laplace operator, Δ PLRepresenting the size of the disturbance; analyzing system frequency common mode component delta omega(s) and power disturbance delta PLThe simplified frequency response model of the(s) relationship is as follows:
Figure FDA0003451419760000011
in the formula, Jus，DusAnd KusRespectively expressed as the effective inertia, effective damping coefficient and effective static deviation coefficient of the system, JusBy effective inertia J of each frequency-modulated power generation equipmentuiAre superposed to formusEffective damping coefficient D of each frequency modulation power generation deviceuiAre superposed to formusThe effective static difference-adjusting coefficient K of each frequency-modulation power generation deviceuiAre superimposed to form T0Adjusting a time constant for the system;
power response delta P of each frequency modulation power generation deviceei(s) satisfies with the frequency common mode component Δ ω(s):
Figure FDA0003451419760000012
in the formula, Jui，DuiAnd KuiRespectively expressed as effective inertia, effective damping coefficient and effective static difference-adjusting coefficient of each frequency-modulation power generation device.
4. The wind turbine generator frequency modulation parameter optimization method considering frequency twice dropping according to claim 3, wherein in the step (2), by combining participation of the wind turbine generator in frequency modulation and exiting of the frequency modulation, an analytic expression of a system frequency trajectory considering the frequency twice dropping is obtained as follows:
Figure FDA0003451419760000021
in the formula (I), the compound is shown in the specification,
Figure FDA0003451419760000022
wherein, Jus1、Dus1、1/Kus1Expressed as the effective inertia, effective damping coefficient and effective static difference-adjusting coefficient of the system when the wind turbine generator participates in frequency modulation, Jus2、Dus2、1/Kus2The coefficient is expressed after the wind turbine generator quits frequency modulation; omegad、ωd1Respectively representing the damping oscillation frequency of the system frequency in the process of primary falling and secondary falling; sigma, sigma1Respectively representing the attenuation coefficients of the system frequency in the processes of primary falling and secondary falling; t is t1Indicating the time for the wind turbine generator to exit from frequency modulation; p1Represents t1The system input power disturbance magnitude at the moment; p0Represents t0And (5) the input power disturbance of the system at the moment.
5. The wind turbine generator frequency modulation parameter optimization method considering the frequency double dropping is characterized in that the specific method in the step (3) is as follows:
(3.1) one-time frequency dip lowest point Δ fnadir1
Figure FDA0003451419760000023
In the formula, tnadir1The moment of maximum frequency deviation occurs once;
(3.2) lowest point of secondary frequency dip Δ fnadir2
Figure FDA0003451419760000031
In the formula, tnadir2The moment of occurrence of the quadratic maximum frequency deviation.
6. The wind turbine generator frequency modulation parameter optimization method considering frequency double dropping according to claim 5, wherein the specific method of the step (4) is as follows:
the optimization problem derived from the system frequency modulation requirements is specifically described as
Figure FDA0003451419760000032
In the formula, Jul、Dul、1/KulThe parameter is expressed as a parameter equivalent to the simplified frequency response model by the wind turbine generator frequency-power response transfer function; pw(t)、Pm(t) respectively representing the output electromagnetic power and the input mechanical power of the wind turbine; hWExpressed as the equivalent time constant of the wind turbine; omegarExpressed as wind turbine rotor speed;
and constructing the inequality constraint and the target function into a Lagrange function meeting the KKT condition, and nesting the Lagrange multiplier method and the global search algorithm to obtain a parameter setting result under optimal control in the active frequency modulation process of the wind turbine generator.
CN202111676288.0A 2021-12-31 2021-12-31 Wind turbine generator frequency modulation parameter optimization method considering frequency twice dropping Pending CN114629133A (en)

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Publication number Priority date Publication date Assignee Title
CN117477605A (en) * 2023-12-27 2024-01-30 山东大学 New energy hysteresis inertia control method cooperated with primary frequency modulation response of synchronous machine

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117477605A (en) * 2023-12-27 2024-01-30 山东大学 New energy hysteresis inertia control method cooperated with primary frequency modulation response of synchronous machine
CN117477605B (en) * 2023-12-27 2024-04-02 山东大学 New energy hysteresis inertia control method cooperated with primary frequency modulation response of synchronous machine

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