CN115455687A - Wind power plant dynamic aggregation modeling method based on virtual synchronous wind generating set - Google Patents
Wind power plant dynamic aggregation modeling method based on virtual synchronous wind generating set Download PDFInfo
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Abstract
The invention discloses a dynamic aggregation modeling method for a wind power plant based on a virtual synchronous wind generating set, which comprises the following steps: simulating the external characteristics of the traditional synchronous generator by using a virtual synchronous fan model; respectively representing an electromechanical dynamic equation and a machine end voltage steady-state equation in each synchronous fan model after parallel connection and confluence by using a uniform aggregation equation set; providing a solving method of virtual inertia, a damping coefficient and virtual synchronous impedance which are required to be set by the synchronous fan model; the obtained dynamic response characteristics of the grid-connected frequency and the voltage of the fan model have consistency under the constraints of virtual inertia and damping coefficients. The invention provides a polymerization method of a virtual synchronous fan in an electromechanical time constant through small signal modeling of the fan set, deduces a generator end voltage equation, a virtual synchronous shaft equation and a polymerization formula thereof after parallel connection and convergence of the wind turbine generator, and represents an electromechanical dynamic equation and a generator end voltage steady-state equation in a synchronous fan model by using a uniform polymerization equation set.
Description
Technical Field
The invention belongs to the technical field of wind power plant control and modeling, and particularly relates to a dynamic aggregation modeling method for a wind power plant based on a virtual synchronous wind generating set.
Background
In order to practically and effectively deal with increasingly serious energy and environmental problems, wind power generation is rapidly developed in various countries in the world, and as the influence of a large number of grid-connected wind fields on the stability of a power system is gradually increased, a dynamic aggregation model of the wind fields is more and more concerned by experts and scholars. Because the wind field is generally formed by connecting a large number of fans in parallel and converging, the space distribution and control difference among all the units are obvious, and equivalent modeling needs to be carried out on the parallel units when the influence of the grid-connected wind field on the power system is researched in order to avoid overhigh order and nonlinearity of the system.
The currently common aggregation equivalence methods are mainly classified into a capacity weighting method, an interface fitting method, a coherence equivalence method and the like. The capacity weighting method is based on a parameter consistency principle, takes the capacity of each unit as weight, directly equates units of the same model and control mode to be a wind turbine unit, and the method cannot effectively reduce the system order in wind fields with uneven wind speed, wide geographical distribution and more fan models. In order to reduce the order to the maximum extent, the interface fitting method equates the characteristics of a wind field grid-connected access Point (PCC) to a generator set, and converts the aggregation problem into the parameter calculation and optimization problem of the motor, but one set of optimization parameters usually cannot meet the requirement of the complex working condition of the wind field. The homodyne equivalence method clusters the units with similar terminal voltage and stator frequency change modes according to the aggregation principle of the synchronous generator, but the types of the wind turbine units are different, the actual frequency and voltage dynamic characteristics are determined by respective converter control parameters, and the current Maximum Power Point Tracking (MPPT) control based on grid voltage vector orientation causes that uniform dynamic response rules are lacked among the units. The dynamic difference of each unit is obvious under the traditional vector control, the wind speed and the wind direction change in the wind field are various, the wind field is difficult to be aggregated into one unit by a clustering method, the grid-connected characteristics under different working conditions are represented, and an effective model is difficult to be provided for the stability analysis of the power grid under high wind energy permeability.
In recent years, the idea of Virtual Synchronous Generator (VSG) has been gradually emphasized, wherein the VSG type wind turbine has the capability of simulating the external characteristics of the synchronous generator, so as to provide a control basis for dynamic aggregation of a wind field according to a conventional power system, and the order and physical characteristics of the aggregated wind field model are close to those of the conventional synchronous generator, so that the integration of a power electronic type power supply and the power system which is dominated by the synchronous generator is enhanced.
In consideration of the fact that power information of each wind turbine in an actual system can be measured locally in real time, and steady-state power of each wind turbine can be obtained through SCADA low-speed communication, dynamic aggregation can be performed on the wind turbines on the basis, grid-connected frequency and voltage dynamic response characteristics of each fan are enabled to be consistent under the constraint of virtual inertia and damping coefficients, electromechanical dynamic processes of the wind turbines can be constrained through a control model and meet aggregation conditions, and therefore a feasible scheme is provided for solving the dynamic aggregation problem of a wind field in the power grid disturbance process.
Disclosure of Invention
The invention is provided for solving the problems in the prior art, and aims to provide a dynamic aggregation modeling method for a wind power plant based on a virtual synchronous wind generating set.
The technical scheme of the invention is as follows: a dynamic aggregation modeling method for a wind power plant based on a virtual synchronous wind generating set comprises the following steps:
A. simulating the external characteristics of the traditional synchronous generator by using a virtual synchronous fan model;
B. representing electromechanical dynamic equations in each synchronous fan model after parallel connection and confluence by using a uniform aggregation equation set;
C. representing the steady-state equation of the terminal voltage in each synchronous fan model after parallel connection and confluence by using a uniform aggregation equation set;
D. providing a solving method of virtual inertia, damping coefficient and virtual synchronous impedance which are required to be set by each synchronous fan model;
E. the obtained synchronization frequency and voltage dynamic response characteristics of each synchronous fan model have consistency under the constraints of virtual inertia and damping coefficients.
Furthermore, in the step A, the virtual synchronous fan models are used for simulating the external characteristics of the traditional synchronous generator, each synchronous fan model in the wind field operates in a unit power factor output mode, and each synchronous fan model is connected in a parallel connection converging mode.
Furthermore, in the step C, the steady-state equations of the terminal voltage in each synchronous fan model after parallel connection and confluence are represented by a uniform aggregation equation set, and the specific process is as follows:
firstly, the unit 1 and the unit 2 are two units positioned at the tail end of a bus;
then, MPPT power value P under current wind speed of the unit 1 and the unit 2 is utilized 1 、P 2 As the weight of the equation, obtaining the terminal voltage expression of the power junction of the two units,
then, the terminal voltage expression u 1 The method comprises the following specific steps:
P 1 ·u 1 ＝-P 1 ·j(X s1 +X l1 )i 1 +P 1 ·e o1
P 2 ·u 1 ＝-P 2 ·jX s2 i 2 +P 2 ·e o2
in the formula, X s Is the terminal equivalent impedance;
X lk bus line impedance corresponding to the kth unit;
e ok the terminal internal potential of the kth fan;
i k the output current of the kth unit;
and finally, obtaining an aggregation voltage equation according to the terminal voltage expression.
Furthermore, the power junction of the unit 1 and the unit 2 is the 1 st confluence point in the bus line.
Further, an aggregate voltage equation is obtained according to the terminal voltage expression, and the specific process is as follows:
firstly, the impedance matching degree of the parallel unit determines the dynamic polymerization of the terminal voltage, and then, P is enabled 1 (X s1 +X l1 )＝P 2 X s2 And obtaining a polymerization voltage equation:
furthermore, step C represents the steady-state equations of the terminal voltages in the synchronous fan models after parallel connection and confluence by using a uniform aggregation equation set, and further comprises the step of obtaining any confluence point voltage equation based on the aggregation voltage equation.
Furthermore, the specific process of obtaining any one of the confluence point voltage equations is as follows:
firstly, if n sets exist in each bus line, the voltage aggregation condition of the h-1 st bus point is as follows:
in the formula, h is more than or equal to 2 and less than or equal to n;
then, because the system only has n units, any confluence point voltage equation can be obtained:
furthermore, step C represents the steady-state equation of the terminal voltage in each synchronous fan model after parallel connection and confluence by using a uniform aggregation equation set, and further comprises the following contents,
first, the equivalent synchronous reactance at the grid tie point needs to be
When the current is over;
then, according to the reverse recursion calculation of polymerization condition, the terminal equivalent reactance X of every machine set s An iteration rule formula is required to be satisfied, so that the total voltage drop generated by the output power of each unit on equivalent output impedance and a bus line can reflect the grid-connected power of a wind field
The voltage drop over.
Furthermore, the formula of the iteration rule is as follows:
the invention has the following beneficial effects:
the method is provided aiming at the problems that the dynamic processes of the frequency and the voltage of each unit in the existing wind farm are different, the wind farm aggregation model can only be equivalent based on the steady-state output power, and an effective dynamic process aggregation mechanism is lacked. The virtual synchronous type fan has the capability of simulating the external characteristics of the traditional synchronous generator, the frequency dynamic response of the virtual synchronous type fan is mainly influenced by virtual inertia and a damping coefficient, and the voltage dynamic response is determined by parameters of an excitation regulator, so that the dynamic aggregation method of the traditional synchronous generator has certain referential property for the fan.
The invention takes a self-synchronization mechanism of a unit under a complex network of a Kuramoto model as a mathematical basis, and provides a polymerization method of a virtual synchronous fan in an electromechanical time constant through unit small signal modeling, namely a dynamic polymerization method of a wind power plant based on the virtual synchronous fan, deduces a terminal voltage equation, a virtual synchronous shaft equation and a mathematical polymerization formula of the terminal voltage equation after a plurality of wind power units are connected in parallel and converged, represents an electromechanical dynamic equation and a terminal voltage steady-state equation in each synchronous fan model after the parallel and the convergence by a uniform polymerization equation set, and provides a solution method of virtual inertia, a damping coefficient and virtual synchronous impedance which are set by each fan.
Because the order and the physical characteristics of the aggregated wind field model are close to those of the traditional synchronous motor, the method also enhances the integration of the power electronic power supply and the traditional power system taking the synchronous motor as the main factor, and is favorable for the power system to better analyze the dynamic stability problem of the power grid containing a large-scale wind field.
Drawings
FIG. 1 is a schematic diagram of the wind farm architecture and its aggregate model in the present invention;
FIG. 2 is a schematic diagram of a small signal model of a virtual synchronous wind turbine according to the present invention;
FIG. 3 is a comparison between the actual wind field model and the dynamic aggregation model of the present invention;
FIG. 4 is a short term wind speed curve corresponding to a bus bar according to the present invention;
FIG. 5 is a comparison between the actual wind field model and the dynamic aggregation model of the present invention.
Detailed Description
The present invention is described in detail below with reference to the accompanying drawings and examples:
as shown in fig. 1 to 5, a wind farm dynamic aggregation modeling method based on a virtual synchronous wind generating set includes the following steps:
A. simulating the external characteristics of the traditional synchronous generator by using a virtual synchronous fan model;
B. representing electromechanical dynamic equations in each synchronous fan model after parallel connection and confluence by using a uniform aggregation equation set;
C. representing the steady-state equation of the terminal voltage in each synchronous fan model after parallel connection and confluence by using a uniform aggregation equation set;
D. providing a solving method of virtual inertia, damping coefficient and virtual synchronous impedance which are required to be set by each synchronous fan model;
E. the grid-connected frequency and voltage dynamic response characteristics of each obtained synchronous fan model have consistency under the constraints of virtual inertia and damping coefficients.
And step A, in the process of simulating the external characteristics of the traditional synchronous generator by utilizing the virtual synchronous fan models, each synchronous fan model in the wind field operates in a unit power factor output mode, and each synchronous fan model is connected in a parallel connection converging mode.
Step C, representing the steady-state equation of the generator-end voltage in each synchronous fan model after parallel connection and convergence by using a uniform polymerization equation set, wherein the specific process is as follows:
firstly, the unit 1 and the unit 2 are two units positioned at the tail end of a bus;
then, MPPT power value P of the unit 1 and the unit 2 under the current wind speed is utilized 1 、P 2 As the weight of the equation, obtaining the terminal voltage expression of the power junction of the two units,
then, the terminal voltage expression u 1 The method comprises the following specific steps:
P 1 ·u 1 ＝-P 1 ·j(X s1 +X l1 )i 1 +P 1 ·e o1
P 2 ·u 1 ＝-P 2 ·jX s2 i 2 +P 2 ·e o2
in the formula, X s Is the terminal equivalent impedance;
X lk bus line impedance corresponding to the kth unit;
e ok the terminal internal potential of the kth fan;
i k the output current of the kth unit;
and finally, obtaining an aggregation voltage equation according to the terminal voltage expression.
And the power junction of the unit 1 and the unit 2 is the 1 st confluence point in the bus.
Obtaining a polymerization voltage equation according to the terminal voltage expression, wherein the specific process is as follows:
firstly, the impedance matching degree of the parallel unit determines the dynamic polymerization of the terminal voltage,
then let P 1 (X s1 +X l1 )＝P 2 X s2 Obtaining a polymerization voltage equation:
and step C, representing the steady-state equations of the terminal voltage in each synchronous fan model after parallel connection and confluence by using a uniform polymerization equation set, and obtaining any confluence point voltage equation based on the polymerization voltage equations.
The voltage equation of any one confluence point is obtained by the following specific process:
firstly, if n sets exist in each bus line, the voltage aggregation condition of the h-1 st bus point is as follows:
in the formula, h is more than or equal to 2 and less than or equal to n;
then, because the system only has n units, any confluence point voltage equation can be obtained:
step C, representing the steady-state equation of the terminal voltage in each synchronous fan model after parallel connection and confluence by using a uniform aggregation equation set, and further comprising the following contents,
first, the equivalent synchronous reactance at the grid-tie point needs to be
When the current is in the normal state;
then, according to the reverse recursion calculation of polymerization condition, the terminal equivalent reactance X of every machine set s Is required to be full ofThe formula of the iteration rule is sufficient, so that the total voltage drop generated by the output power of each unit on the equivalent output impedance and the bus line can reflect the grid-connected power of the wind field
The voltage drop over.
The iteration rule formula is as follows:
specifically, in the step B, the electromechanical dynamic equations in the synchronous fan models after parallel connection and confluence are represented by a uniform aggregation equation set, and the specific process is as follows:
firstly, under a dynamic power per unit system, the frequency characteristics of each virtual synchronous type controlled unit can be represented by electromechanical equations in a virtual synchronous machine control model:
then, the control system of each unit under the dynamic power per unit system sets the same virtual inertia under the MPPT power value per unit
And damping coefficient
At the output of mechanical torque
And electromagnetic torque
Under the action of (3), the angular acceleration of each set is equal to the frequency change rate in the same time.
Finally, let the acceleration and frequency change rate of the polymerization back angle be alpha a And Δ ω a Because the angular velocity and the change rate thereof meet the following conditions of the formula in the dynamic process within the same time, the electromechanical equations can be polymerized as follows:
specifically, the electromechanical dynamic equation and the terminal voltage equation of each fan which are controlled virtually and synchronously in combination with the step B and the step C can be represented by a set of complete electromechanical equations and terminal voltage equations, wherein the electromechanical equations reflect the frequency characteristics of the fans, the terminal voltage equations reflect the voltage characteristics of the fans, the equivalent impedance at the machine end represents synchronous reactance in a virtual synchronous machine model, and the dynamic current distribution condition in the system disturbance process and the armature reaction of the virtual synchronous machine in a steady state are reflected, and the specific expression is as follows:
in the formula u apcc Representing the voltage at the common connection point.
Specifically, the relationship between the electromechanical dynamic equation and the steady-state electromagnetic equation is related through the torque expressions of the units, specifically:
wherein theta is o And theta h-1 The phase angle of the counter electromotive force of the unit and the voltage phase angle of the confluence point corresponding to the unit are respectively.
In particularIn the dynamic process, the frequency change rate of each unit is close to the normalized virtual inertia
And damping coefficient
The terminal voltage characteristic is determined by a normalized excitation regulation parameter, and a weighting coefficient P h And the current MPPT power of each h unit is expressed.
In particular, on the basis of the aggregation model, the equivalent value of the distributed wind turbines needs to be made, and the distributed wind turbines are used as prime movers of the synchronous generator set.
Specifically, because the inertia time constants of the wind turbine rotor with the same power level are relatively close and far greater than the active-frequency closed-loop time constant controlled by the virtual synchronous motor, a group of equivalent inertia time constants H can be used w Characterizing a wind wheel rotor as follows:
according to system capacity S n Rated frequency f n And the number p of the pole pairs of the rotor can determine the equivalent inertia J w . The wind turbine mainly determines the closed-loop time of the MPPT in the system, and the closed-loop time comprises power following in the wind speed disturbance process and the MPPT recovery process after net side disturbance.
And characterizing the wind energy which can be absorbed by the wind field at present by using the equivalent wind speed as an input variable of the equivalent wind turbine.
Example one
And under the same working condition, representing the 2 virtual synchronous wind generation sets adopting the PWM average model by using an actual synchronous generator with the rated power of 3MW, wherein the parameters of the synchronous generator set in the aggregation model are shown in Table 1.
TABLE 1 dynamic aggregation synchronous generator System parameters
Considering that a large power grid is formed by connecting large synchronous machines in parallel, a 30MW synchronous generator set is used for replacing an infinite power grid model, and 30MW is initially loaded.
And when the wind speed is 2s in simulation, the corresponding wind speeds of the No. 1 unit and the No. 2 unit are respectively increased from 9m/s and 8.8m/s to 9.5m/s and 9.2m/s, and because the change rule of the wind speed in the calculation example is simpler, the corresponding equivalent wind speed of a prime mover in a wind field aggregation model with the rated power of 3MW and the equivalent inertia time constant of a wind wheel of 5s can be calculated and increased from 8.93m/s to 9.38m/s. And through the dynamic response of the aggregation model when the load is suddenly increased by 5% in 12s and the power grid is disturbed, the grid-connected power of each unit and the wind field and the system frequency are respectively observed as shown in figure 2. With the increase of the wind speed, the system frequency of the actual model slightly increases after 2s, and the change rate of the system frequency is smaller because the rotation speed of the wind turbine rotor slowly increases in the process; the electromagnetic power of the 30MW synchronous generator representing the power grid is suddenly increased by 5% load sudden increase at 12s, the system frequency greatly falls under the constraint of the rotor inertia of the synchronous machine and the virtual inertia of the virtual synchronous machine, the MPPT is recovered along with the fan to enter a new stable working point, and the frequency supporting effect of the aggregation model on the system is consistent with that of an actual model.
PI in FIG. 2 stands for proportional-integral controller, ω n Representing the nominal angular frequency of the AC system, E s And theta s Representing the amplitude and phase angle, P, of the modulation voltage ref And P g Representing active command and actual active power, Q ref And Q g Representing reactive command versus actual reactive power, and Δ represents small signal increments.
However, the wind speed fluctuation in an actual wind field is random, the accurate wind field equivalent wind speed cannot be calculated generally, and if all the fans adopt a fine model, the system order is too high, and the effectiveness of the aggregation model in a large wind field cannot be verified.
In the case, MPPT (maximum power point tracking) instruction values of all units transmitted by the SCADA (supervisory control and data acquisition) system replace output mechanical power of an engine in a polymerization model, output internal potential of a virtual synchronous machine model is used as a controlled voltage source to replace a PWM (pulse-width modulation) model of a fan, and the feasibility of the application of the polymerization method provided by the embodiment in a large wind farm is verified by taking an actual wind farm of complete 33 fans as an example. The parameters of the wind field bus are shown in the appendix, the per unit values of the parameters of the synchronous generators in the aggregation model are consistent with those in table 1, only the rated power is increased to 49.5MW, the large power grid is represented by a traditional synchronous generator with the rated capacity of 200MW, and the initial load is 200MW.
The wind speed profile used in the simulation contains a step component of the second order variation and a random component of the Hz order variation. In the simulation, wind speed curves corresponding to the three bus lines A, B and C are shown in FIG. 4. MPPT data of the three bus lines uploaded by the SCADA system are further overlapped to serve as mechanical driving power of a synchronous generator in a wind field dynamic aggregation model, and 300ms communication time required by uploading data in the SCADA system is simulated by the aid of the zero-order retainer and the delay module. In the simulation of the aggregation model, the grid-connected dynamic characteristics of the aggregation model are verified through a 5% load sudden increase at 2s and a load recovery process at 12 s. Comparing the grid-connected power waveform of the aggregation model under the working condition with the grid-connected total power of the three bus lines at the PCC point in the actual wind field model, the result is shown in fig. 5 (a), and the system frequency is shown in fig. 5 (b).
When 2s is simulated, the load on the network side is suddenly increased by 5%, the three bus bars all show a frequency supporting function, because the total power of the steady-state output of the bus bars A and B before disturbance is close, the dynamic supporting power born by the two bus bars is similar, and because the steady-state power of the bus bar C before disturbance is smaller, the dynamic supporting power equally divided according to the steady-state power is also smaller, but the dynamic power adjusting time of the three bus bars is basically consistent; when the rated load of the 12s system is recovered, the power dynamic characteristics of the three bus bars still keep high consistency. Meanwhile, as can be seen from the grid-connected total power comparison curve in fig. 5 (a), because of communication delay caused by the SCADA system and without consideration of factors such as line loss in the process of converging the power of each unit, the output power of the aggregation model and the output power of the actual model have a deviation of less than 10%, but the maximum power tracking in the whole simulation process tends to be consistent. Meanwhile, load disturbance occurs at the same moment in two times of simulation, the dynamic response process of the output power of each model completely depends on the constraint of the electromechanical dynamic model, so that the steady-state power error of the two models at the same moment is small, and the dynamic consistency of the output power of the dynamic aggregation model and the output power of the actual wind field model is high when the dynamic aggregation model and the actual wind field model participate in frequency support. The system frequency change process in fig. 5 (b) may reflect the contribution of the wind field to the large power grid inertia, the lowest point of the system frequency of the actual model and the aggregation model is 49.98Hz in the sudden load increase process, the highest point of the system frequency of the actual model and the highest point of the aggregation model reach 50.07Hz in the load recovery process, the frequency adjustment time is consistent, the occurrence time of the lowest point of the aggregation model is slightly delayed by the influence of the communication period, and the above simulation result may also indicate that the dynamic aggregation model better reflects the contribution of the virtual inertia of the wind turbine in the actual model to the power grid.
In case two, although the input mechanical power of the aggregation model needs to be uploaded by the SCADA system to obtain the MPPT data, the MPPT data can be used as the driving power of the synchronous generator in the aggregation model by simply accumulating the MPPT data, and the electromechanical dynamic consistency of each unit is ensured by the control of the respective virtual synchronizer. Meanwhile, even if a certain communication delay is taken into consideration in the second calculation example, the MPPT command is filtered by the inertia of the rotor, and the change rate of the MPPT command is smaller than the fluctuation frequency of the wind speed, so that the influence of the communication delay on the accuracy of the output power of the aggregation model is further reduced, and the dynamic frequency response mechanisms of the two models in the power grid disturbance process are similar because the electromechanical dynamic equation of the aggregation model is the same as the virtual synchronous axis equation, so that the aggregation method is suitable for the aggregation modeling of a large-scale wind power plant.
The method is provided aiming at the problems that the dynamic processes of the frequency and the voltage of each unit in the existing wind farm are different, the wind farm aggregation model can only be equivalent based on the steady-state output power, and an effective dynamic process aggregation mechanism is lacked. The virtual synchronous type fan has the capability of simulating the external characteristics of the traditional synchronous generator, the frequency dynamic response of the virtual synchronous type fan is mainly influenced by virtual inertia and a damping coefficient, and the voltage dynamic response is determined by parameters of an excitation regulator, so that the dynamic aggregation method of the traditional synchronous generator has certain referential property for the fan.
The invention takes a unit self-synchronization mechanism under a complex network of a Kuramoto model as a mathematical basis, and provides a polymerization method of a virtual synchronous fan in an electromechanical time constant through unit small signal modeling, namely a dynamic polymerization method of a wind power plant based on the virtual synchronous fan, deduces a machine end voltage equation, a virtual synchronous shaft equation and a mathematical polymerization formula thereof after a plurality of wind power units are connected in parallel and converged, represents electromechanical dynamic equations and machine end voltage steady-state equations in each synchronous fan model after parallel and convergent by a uniform polymerization equation set, and provides a solution method of virtual inertia, damping coefficient and virtual synchronous impedance which are required to be set by each fan.
Because the order and the physical characteristics of the aggregated wind field model are close to those of the traditional synchronous motor, the method also enhances the integration of the power electronic power supply and the traditional power system taking the synchronous motor as the main factor, and is favorable for the power system to better analyze the dynamic stability problem of the power grid containing a large-scale wind field.
Claims (9)
1. A wind power plant dynamic aggregation modeling method based on a virtual synchronous wind generating set is characterized in that: the method comprises the following steps:
(A) Simulating the external characteristics of the traditional synchronous generator by using a virtual synchronous fan model;
(B) Representing electromechanical dynamic equations in each synchronous fan model after parallel connection and confluence by using a uniform aggregation equation set;
(C) The steady state equation of the generator end voltage in each synchronous fan model after parallel connection and confluence is represented by a uniform aggregation equation set;
(D) Providing a solving method of virtual inertia, damping coefficient and virtual synchronous impedance which are required to be set by each synchronous fan model;
(E) The obtained synchronization frequency and voltage dynamic response characteristics of each synchronous fan model have consistency under the constraints of virtual inertia and damping coefficients.
2. The dynamic aggregation modeling method for the wind power plant based on the virtual synchronous wind generating set according to claim 1, characterized in that: in the step (A), a virtual synchronous fan model is used for simulating the external characteristics of the traditional synchronous generator, each synchronous fan model in a wind field operates in a unit power factor output mode, and each synchronous fan model is connected in a parallel connection converging mode.
3. The dynamic aggregation modeling method for the wind power plant based on the virtual synchronous wind generating set according to claim 1, is characterized in that: and (C) representing the steady-state equation of the terminal voltage in each synchronous fan model after parallel connection and confluence by using a uniform aggregation equation set, wherein the specific process is as follows:
firstly, the unit 1 and the unit 2 are two units positioned at the end of a bus;
then, MPPT power value P under current wind speed of the unit 1 and the unit 2 is utilized 1 、P 2 As the weight of the equation, obtaining the terminal voltage expression of the power junction of the two units,
then, the terminal voltage expression u 1 The method comprises the following specific steps:
P 1 ·u 1 ＝-P 1 ·j(X s1 +X l1 )i 1 +P 1 ·e o1
P 2 ·u 1 ＝-P 2 ·jX s2 i 2 +P 2 ·e o2
in the formula, X s Is terminal equivalent impedance;
X lk bus line impedance corresponding to the kth unit;
e ok the terminal internal potential of the kth fan;
i k the output current of the kth unit;
and finally, obtaining an aggregation voltage equation according to the terminal voltage expression.
4. The dynamic aggregation modeling method for the wind power plant based on the virtual synchronous wind generating set according to claim 3, characterized in that: and the power junction of the unit 1 and the unit 2 is the 1 st confluence point in the bus line.
5. The dynamic aggregation modeling method for the wind power plant based on the virtual synchronous wind generating set according to claim 3, characterized in that: obtaining a polymerization voltage equation according to the terminal voltage expression, wherein the specific process is as follows:
firstly, the impedance matching degree of the parallel unit determines the dynamic polymerization of the terminal voltage,
then let P 1 (X s1+ X l1 )＝P 2 X s2 And obtaining a polymerization voltage equation:
6. the dynamic aggregation modeling method for the wind power plant based on the virtual synchronous wind generating set according to claim 5, is characterized in that: and (C) representing the steady-state equations of the terminal voltage in each synchronous fan model after parallel connection and confluence by using a uniform aggregation equation set, and obtaining any confluence point voltage equation based on the aggregation voltage equations.
7. The dynamic aggregation modeling method for the wind power plant based on the virtual synchronous wind generating set according to claim 6, characterized in that: the voltage equation of any one confluence point is obtained by the following specific process:
firstly, if n sets exist in each bus line, the voltage aggregation condition of the h-1 st bus point is as follows:
in the formula, h is more than or equal to 2 and less than or equal to n;
then, since the system has only n units, any junction point voltage equation can be obtained:
8. the dynamic aggregation modeling method for the wind power plant based on the virtual synchronous wind generating set according to claim 1, characterized in that: step (C) the steady state equation of the terminal voltage in each synchronous fan model after parallel connection and confluence is represented by a uniform aggregation equation set, and the method also comprises the following contents,
firstly, when the equivalent synchronous reactance at a grid-connected point is Xa s;
then, according to the reverse recursion calculation of polymerization condition, the terminal equivalent reactance X of every machine set s An iteration rule formula is required to be satisfied, so that the total voltage drop generated by the output power of each unit on equivalent output impedance and a bus line can reflect the grid-connected power of a wind field
The voltage drop over.
9. The dynamic aggregation modeling method for the wind power plant based on the virtual synchronous wind generating set according to claim 8, characterized in that: the iteration rule formula is as follows:
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116025515A (en) * | 2023-01-10 | 2023-04-28 | 广东工业大学 | Full converter type fan parameter debugging method based on analytical inertia model |
| CN116025515B (en) * | 2023-01-10 | 2024-01-12 | 广东工业大学 | Full converter type fan parameter debugging method based on analytical inertia model |
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