CN110571794B - Transient model equivalent calculation method suitable for doubly-fed wind power plant - Google Patents
Transient model equivalent calculation method suitable for doubly-fed wind power plant Download PDFInfo
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Abstract
The invention discloses a transient model equivalent calculation method suitable for a doubly-fed wind power plant, and belongs to the field of fault modeling calculation of power systems. According to the invention, sampling is carried out according to the rotating speed change condition of each doubly-fed wind turbine generator in the wind power plant in the external voltage drop fault process of the wind power plant, the weighted dynamic time bending distance calculation among all the wind power plants is carried out based on the sampled time sequence data of the rotating speed of the wind power plant, the grouping of the wind power plants in the wind power plant is realized according to the distance, the grouping of the wind power plants is carried out, the grouping parameters of the grouped wind power plants are polymerized, the equivalent transformation of the current collecting lines is carried out on the line impedance based on the principle that the power consumption of the current collecting lines is equal before and after the equivalent, and finally, the grouping transient equivalent model suitable for fault analysis of the doubly-fed wind power plant is obtained, and on the premise of ensuring the equivalent precision of the wind power plant, the fault simulation time of a power system containing a large-scale wind power plant can be shortened, and the engineering practicability is good.
Description
Technical Field
The invention belongs to the field of fault modeling calculation of power systems, and particularly relates to a transient model equivalent calculation method suitable for a doubly-fed wind power plant.
Background
With the deep research and technological progress of wind power, the wind power generation in China is gradually scaled and industrialized, so that the wind power permeability in local areas is continuously increased, and the capacity of wind power plants is continuously increased. The grid connection point of the wind turbine generator is upgraded from an initial low-voltage distribution network to a high-voltage alternating current/direct current power transmission network, and the interaction influence between a wind power plant and a power system is more worth focusing due to the improvement of voltage level. The influence of the wind power plant on the power grid has been from local voltage deviation and harmonic pollution caused by wind power intermittence and randomness when the capacity is small, and the method is upgraded to challenges brought to the aspects of peak regulation strategy, reserve capacity determination, economic operation, relay protection, safety and stability and the like of a power system when large-scale wind power is accessed.
The variable-speed constant-frequency double-fed asynchronous wind power generator (double-fed Induction Generator, DFIG) has excellent control characteristics and high-efficiency energy conversion capability, and has become a mainstream model of a wind power plant. Doubly-fed wind generators comprise a large number of power electronic devices and control systems, and under the influence of wind randomness and fluctuation, transient characteristics of a wind farm during faults are obviously different from those of synchronous generators. In order to study the external characteristics of a wind power plant with power system faults, the wind power plant needs to be integrally modeled, but the operation working conditions of each DFIG are obviously different, the fault performances are different, the DFIG single-machine model is quite complex, modeling the wind power plant by using a detailed model of each DFIG can cause overlong simulation time, and the efficiency of data processing and analysis is reduced. In order to obtain the overall dynamic characteristics of a large-scale wind farm during a fault transient process, a suitable transient equivalence method is required to dynamically equivalent the wind farm.
In the prior art, the wind power plant equivalent model based on steady state data clustering can better fit the influence of the wind power plant on the power grid under the normal working condition, and mainly performs clustering equivalence according to steady state operation data (including wind speed conditions, steady state operation power and the like) of the unit. However, the method is related to the time length and the representativeness of the time period of the selected operation data samples, and the dispersion of the sample groups can lead to a large number of groups, so that the simulation efficiency is low. In addition, the doubly-fed wind turbine generator is very sensitive to voltage drop, and the deeper the port voltage drop degree is, the stronger the transient variation is, and the more complicated the coherent characteristics are. The equivalence method based on the wind speed-power relation lacks the wind power plant equivalence under the voltage drop fault, steady-state operation data is insufficient, and fitting accuracy of the model on wind power plant fault current contribution and voltage interaction influence under the transient process is not high enough. The existing current collecting line equivalent method neglects aggregation of any unit, and the obtained impedance model is low in accuracy.
Disclosure of Invention
Aiming at the defects and improvement demands of the prior art, the invention provides a transient model equivalent calculation method suitable for a doubly-fed wind power plant, and aims to obtain a wind power plant equivalent model which more accurately simulates the dynamic characteristics of the wind power plant in the power grid fault process.
To achieve the above object, according to one aspect of the present invention, there is provided a transient model equivalence calculation method suitable for a doubly-fed wind power plant, the method comprising the steps of:
s1, acquiring distribution parameters and unit parameters of a doubly-fed wind power plant;
s2, sampling parameters of the doubly-fed wind turbine generator set, and constructing a generator set rotor speed time sequence vector according to rotor speeds of the doubly-fed wind turbine generator sets in the sampled wind power plant during faults;
s3, calculating weighted dynamic time bending distances among all units based on the time sequence vectors of the rotating speeds of the units;
s4, aggregating the wind turbine generator sets according to the size of the weighted dynamic time bending distance, so that grouping of the wind turbine generator sets in the wind power plant is realized;
s5, performing equivalent aggregation on the unit parameters in the wind power plant according to the unit parameters and the grouping result; and carrying out equivalent aggregation on the current collection network according to the distribution parameters of the wind power plant and the grouping result.
Specifically, step S2 includes the following sub-steps:
s21, sampling the rotor rotation speed of the doubly-fed wind turbine from the moment that the wind power plant suffers from an external voltage drop fault to the moment of fault clearing, and constructing a data pair from the sampling time and the sampled set rotor rotation speed;
s22, all data pairs obtained by sampling of each unit form a rotor speed time sequence of the unit, and rotor speed time sequences of a plurality of fans form a rotor speed time sequence vector of the unit.
Specifically, in step S3, the weighted dynamic time warping distance PWDTW between the two time series a and B is calculated as follows:
wherein L is w (i, j) represents the ith sampling point A of the time series A i And the jth sampling point B of the time sequence B j Weighted dynamic time warping distance between d ij For the ith sampling point A of the time sequence A i And the jth sampling point B of the time sequence B j The base distance between the two is m is the number of sampling points of the time sequence A, and n is the number of sampling points of the time sequence B.
Specifically, the ith sampling point a of the time series a i And the jth sampling point B of the time sequence B j Distance d between ij The calculation formula of (2) is as follows:
d ij ＝d(A i ，B j )＝w i-j (A i -B j ) 2
wherein w is i-j The weight values corresponding to the position points of the two rotating speed time series are w max As the upper limit of the weight, g is the curvature constant used to control the weight function w, c= |i-j| is a i And B j E is a profile factor for detecting the change trend of two time tracks, wherein i is 1 < min (m, n), j is 1 < min (m, n).
Specifically, in step S5, in the equivalent cluster of p clusters aggregated in the same cluster, the calculation method of each parameter is as follows:
wherein R is si 、X si 、R ri 、X ri 、X mi 、R ci 、s i Respectively representing the per unit value and slip of the stator resistance, the stator reactance, the rotor resistance, the rotor reactance, the exciting reactance and the Crowbar resistance of the ith unit in the equivalent machine group, and taking the rated capacity of each unit as a reference; r is R s-eq 、X s-eq 、R r-eq 、X r-eq 、X m-e 、R c-eq 、s eq Respectively the stator impedance, the rotor impedance, the exciting reactance, the per unit value of the Crowbar resistance and the slip ratio of the equivalent doubly-fed fan, and the equivalent rated capacity s eq Based on, w i The weight of each generator is represented.
Specifically, in step S5, the equivalent parameters of the shafting transmission model parameters are calculated as follows:
wherein H is i 、D i 、K s-i Is the inertia time constant, the generator damping coefficient and the rigidity coefficient of the ith unit in the cluster, H eq 、D eq 、K s-eq And p represents the number of fans aggregated into a group, wherein the inertia time constant, the generator damping coefficient and the rigidity coefficient of the equivalent unit shafting model are obtained.
Specifically, in step S5, the equivalent parameters of the equivalent post-machine-end box-type transformer are calculated as follows:
S T-eq ＝pS T
wherein C is i Is a machine end capacitor S T Z is the capacity of the machine-side transformer T For the machine side transformer impedance, p represents the number of fans aggregated into a cluster.
Specifically, according to the distribution parameters of the wind power plant and the grouping result, performing equivalent aggregation on the current collection network, wherein the method comprises the following steps of:
(1) Carrying out topology transformation on units on each trunk line in the wind power plant, so that the connection form of the units is changed from trunk line access point to parallel access point;
(2) Calculating equivalent impedance of the unit access point after each transformation;
(3) And calculating the equivalent impedance of the current collecting circuit of the fans in the same group based on the grouping result, the equivalent impedance of the unit connected with the grid-connected point after each transformation and the wind farm parallel connection topological structure.
Specifically, the equivalent impedance calculation formula of the transformed i-th unit connected to the public bus is as follows:
wherein Z is 1 Representing the impedance between the first fan and the grid-connected point, Z 2 Representing the impedance between the second blower and the first blower access point, and so on; p (P) i Representing the output power of the ith fan; l denotes the number of all fans of the mains connection.
Specifically, the calculation formula of the equivalent impedance of the current collecting line of the ith unit and the PCC bus after the equivalent is as follows:
wherein Z is i-eq And the equivalent impedance of the ith unit accessed to the public bus after transformation is represented.
In general, through the technical scheme of the invention, the following beneficial effects can be obtained:
(1) Aiming at the defect that the existing grouping equivalence is mainly based on steady-state operation data, the invention samples according to the rotating speed change condition of each doubly-fed wind turbine in the wind power plant in the process of external voltage drop fault of the wind power plant, carries out weighted dynamic time bending distance calculation among the wind power plants based on the rotating speed time series data of the wind power plants obtained by sampling, and carries out grouping of the wind power plants according to the distance, thereby realizing grouping of the wind power plants and finally obtaining a grouping transient equivalence model of the wind power plant which is suitable for fault analysis.
(2) Aiming at the problem that the precision of the obtained impedance model is not high due to neglecting the aggregation of any position units in the existing current collecting line equivalent method, the method carries out unit parameter aggregation on the clustered wind turbines, carries out current collecting line equivalent transformation on the line impedance based on the principle that the power consumption of the current collecting lines is equal before and after the equivalent, finally obtains the clustered transient equivalent model suitable for fault analysis of the doubly-fed wind turbine farm, and can shorten the fault simulation time of the power system of the large-scale wind turbine farm on the premise of ensuring the equivalent precision of the wind turbine farm, thereby having better engineering practicability.
Drawings
FIG. 1 is a flow chart of a transient model equivalence calculation method suitable for a doubly-fed wind power plant, which is provided by the embodiment of the invention;
fig. 2 is an alignment matching schematic diagram of the same group of time sequences provided by the embodiment of the invention under the PWDTW algorithm;
FIG. 3 is a topology diagram of a wind farm trunk connection provided by an embodiment of the present invention;
fig. 4 is a topological structure diagram of a parallel connection of a wind farm according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. In addition, the technical features of the embodiments of the invention described below can be combined with one another as long as they do not conflict with one another.
As shown in fig. 1, a transient model equivalence calculation method suitable for a doubly-fed wind power plant includes the following steps:
s1, obtaining distribution parameters and unit parameters of a doubly-fed wind power plant.
Wind farm distribution parameters include: positional relationship among fans in a wind power plant, resistance reactance parameters of a connecting line (a collecting line) and a connecting topological relationship.
The unit parameters include: rated capacity, stator resistance, stator reactance, rotor speed, rotor resistance, rotor reactance, excitation reactance, crowbar resistance and slip of the machine set.
S2, sampling parameters of the doubly-fed wind turbine generator set, and constructing a generator set rotor speed time sequence vector according to rotor speeds during faults of all doubly-fed wind turbine generator sets in the sampled wind turbine generator set.
The purpose of the transient state equivalent model is to simulate the characteristics of the wind power plant in the fault process, the effect of the unit in the fault process can be reflected more accurately by adopting the data in the fault period, and the data can be more accurate compared with the data in the normal working condition. The doubly-fed wind turbine generator is very sensitive to voltage drop faults, transient output voltage and current of the doubly-fed wind turbine generator can contain various attenuation components, and the method for acquiring the grouping index from transient electric quantity of the doubly-fed wind turbine generator has very important significance.
When the grid voltage deep drop fault occurs, the Crowbar protection circuit of the doubly-fed wind turbine generator is put into operation, and when the Crowbar resistance value is not large, the fault current component output by the stator is very complex, and comprises a direct current attenuation component, a rotor frequency attenuation component, a positive sequence component and a negative sequence component. The doubly-fed wind turbine generator does not contain an external excitation power supply, and rotor excitation is generated through machine end voltage coupling, so that the change of the machine end voltage triggers all excitation responses, armature responses and rotor responses of the doubly-fed wind turbine generator. Considering that the transient state time of fault ride-through of the doubly-fed wind turbine is short, the power tracking control and the pitch control hardly act, and the mechanical movement of the turbine can be omitted in the electromagnetic transient process. For the doubly-fed wind turbine group in the same area, when the mechanical parameters and the control system are consistent, under the condition of the same voltage drop fault, the short-circuit current is only related to the drop of the machine end voltage and the rotating speed of the rotor, and is irrelevant to other operation parameters.
In summary, in the electromagnetic transient process of the doubly-fed wind turbine, the rotor rotation speed change of the doubly-fed wind turbine represents the transient change process of the doubly-fed wind turbine, and the same rotor rotation speed change process represents that the doubly-fed wind turbine has fault consistency, and reflects the change characteristics of the running state of the doubly-fed wind turbine. Therefore, the rotor rotating speeds of the doubly-fed wind turbine generator are used as grouping data, the rotor rotating speeds of all the wind turbine generator after the fault moment are collected and sampled, and a unitary time sequence of the rotating speeds is formed to serve as a wind turbine group index.
And sampling the rotor rotating speed of the doubly-fed wind turbine from the moment that the wind power plant suffers from an external voltage drop fault to the moment of fault clearing. And forming a one-dimensional time sequence from the sampled unit rotating speed data, thereby obtaining a rotating speed time sequence group of the unit. The rotor speed is sampled every 0.05s in this embodiment.
Specifically, a time and rotation speed data pair (a fan has a corresponding rotation speed at a moment) is constructed, and the time sequence becomes a rotation speed time sequence of sampling time length along with the time. Each unit corresponds to a unit rotating speed time sequence, namely a sample of the unit, and the rotating speed time sequences of the plurality of fans form a unit rotor rotating speed time sequence vector.
And S3, calculating the weighted dynamic time bending distance among all the units based on the time sequence vector of the rotating speed of the unit rotor.
The invention provides a weighted dynamic time warping (PWDTWW) algorithm based on Profile features, which is used for carrying out PWDTWW distance calculation on a set rotating speed time sequence. As with the weighted based dynamic time warping method (WDTW), the present invention is based on the dynamic programming concept, allowing the time series to be shifted in the coordinate axes to find the shortest aligned matching path, but weighting the computation of the base distance by introducing factors describing the change in the profile of the sequence. When the difference of the local contour features between the sequences is larger, the distance weight between the corresponding points is higher, and the similarity is lower. The distance algorithm considers local contour feature matching when the similarity measurement is carried out on the sequence, so that more accurate feature matching can be realized.
As shown in fig. 2, the time sequence a= [ a ] 1 ，A 2 ，...，A m ] T And B= [ B ] 1 ，B 2 ，...，B n ] T Alignment matching is performed under the PWDTW algorithm. Distance matrix D of time series A and B m*n Element d of (3) ij ＝d(A i ，B j )＝w i-j (A i -B j ) 2 Taking the distance as a base distance, wherein m is the number of sampling points of a sequence A, n is the number of sampling points of a sequence B, and the weight values w corresponding to two rotating speed time sequence position points i-j The calculation formula is as follows:
wherein w is max As the upper limit of the weight, the value 1 is generally taken, g is a curvature constant for controlling the weight function w, when g=0, the weight values of all points are the same, and as g increases, the penalty value for mismatch between the time interval of 2 points and the morphology of the points increases. Better effect can be obtained when g is between 0.1 and 0.6, and g is 0.5 in the embodiment. c= |i-j| is the sampling point a i And B j Distance factor between location points of (a), m c As the middle point of the sequence a/B,e is a profile factor for detecting the change trend of the two time tracks.
The profile factor E is defined as follows:
wherein i is more than 1 and less than min (m, n), j is more than 1 and less than min (m, n).
As can be seen from the definition of E, the value of E ranges from {0,1,2}, i.e., when A i And B is connected with j When the slope signs of the two points are the same, the change trend of the two points is ascending or descending, E obtains the minimum value 0, at the moment, the weight coefficient is not influenced by the distance factor, and the weight value takes the minimum value. When the slope of at least one of the two points is 0, e=1, and only the distance factor affects the weight coefficient; when A is i And B is connected with j When the slope signs of (a) are opposite, E takes a maximum value of 2, namely, the matching is performed by increasing the influence of the profile factor to avoid the points with opposite change trends. E is used for controlling the positive and negative of the slope of the two pointsIs a function of (a) and (b).
After the calculation of the base distance between each group of corresponding points in the sequence is completed, the PWDTWW distances of the two time sequences are calculated, and the calculation formula is as follows:
wherein L is w (i, j) represents the weighted dynamic time warping distance of sequences A and B at i, j.
And S4, aggregating the wind turbine generator sets according to the size of the weighted dynamic time bending distance, so that grouping of the wind turbine generator sets in the wind power plant is realized.
The clustering purpose of wind power plant clustering is to equate fan clustering with the same electromagnetic transient variation, simplify wind power plant model and ensure maximum simulation precision. The generators divided into the same group have similar change processes in the fault transient process, which indicates that the generators have similar characteristics and can be equivalent to an equivalent fan. The units in the same group after grouping have similar fault characteristics, and the change characteristics of the units among different groups are different.
And after the PWDTW distance of the rotor rotating speed time sequence between every two units is calculated, each unit sample is regarded as an independent sample, a grouping distance threshold value is set, and clustering and grouping are carried out on the unit samples according to grouping precision requirements by adopting a hierarchical aggregation clustering algorithm.
For the grouping of doubly fed machine sets under the fault of voltage deep drop, the basic idea is as follows:
1) Calculating PWDTWW distance between rotor transient curves of every two units, and regarding each unit sample as an independent sample;
2) Given a threshold epsilon of merging distance between clusters, regarding two samples farthest from each other as two new clusters;
3) Calculating the distance between the nearest sample to the cluster and the cluster, and adding the sample into the cluster if the distance is smaller than a threshold value;
4) Taking the average value of the samples in the combined clusters, and calculating PWDTWDTW distances between the average value and other samples;
5) Merging samples with the inter-cluster distance smaller than the merging threshold again;
6) Repeating steps 3) to 5) until all samples are assigned to a cluster, or a desired number of clustered clusters are obtained.
S5, performing equivalent aggregation on the unit parameters in the wind power plant according to the unit parameters and the grouping result; and carrying out equivalent aggregation on the current collection network according to the distribution parameters of the wind power plant and the grouping result.
In the prior art, wind power plants are equivalent to one set, or wind power sets in the same row and column or in the same region are equivalent to one set. However, for a large wind farm, because of different terrains and influence of wake effects, maximum wind speeds of units flowing through the same area are different, and wind speed differences among the units can cause a control system to work in different states, so that the equivalent precision of the wind farm units is lower after the wind farm units are equivalent to a single unit or divided according to the areas.
S51, performing parameter equivalence on the unit according to the unit parameters and the grouping result.
And carrying out parameter weighted aggregation on the clustered same group units to obtain equivalent unit parameters. And aiming at the wind turbine generators in different wind speed intervals, carrying out parameter weighted aggregation by adopting different parameter equivalent methods.
Model parameter equivalence of wind driven generator
The calculation method of each parameter in the equivalent cluster after the aggregation of the p units in the same cluster is as follows:
wherein R is si 、X si 、R ri 、X ri 、X mi 、R ci 、s i Respectively representing the per unit value and slip of the stator resistance, the stator reactance, the rotor resistance, the rotor reactance, the exciting reactance and the Crowbar resistance of the ith unit in the equivalent machine group, and taking the rated capacity of each unit as a reference; r is R s-eq 、X s-eq 、R r-eq 、X r-eq 、X m-eq 、R c-eq 、s eq Respectively the stator impedance, the rotor impedance, the exciting reactance, the per unit value of the Crowbar resistance and the slip ratio of the equivalent doubly-fed fan, and the equivalent rated capacity s eq Based on, w i Representing the weight of each generator, and p represents the number of fans clustered into a cluster.
Shafting transmission model parameter equivalence
Wherein H is i 、D i 、K s-i Is the inertia time constant, the generator damping coefficient and the rigidity coefficient of the ith unit in the cluster, H eq 、D eq 、K s-eq The model is the inertia time constant, the generator damping coefficient and the rigidity coefficient of the equivalent post-unit shafting model.
Box transformer parameter equivalence
The equivalent parameters of the equivalent post-machine end box-type transformer are calculated as follows:
S T-eq ＝pS T
wherein C is i Is a machine end capacitor S T Z is the capacity of the machine-side transformer T Is the impedance of the machine-side transformer.
Controller operating parameter equivalence
When the input wind speeds of all the units in the cluster are between the cut-in wind speed and the rated wind speed, the unit determines the maximum active output according to MPT (Maximum Power Tracking ) tracking curves, the active control strategies are the same, the equivalent wind speeds of the aggregated units are also in the wind speed interval, and the parameters of PI controllers in the rotor-side converter and the grid-side converter of the equivalent unit are as follows:
wherein k is pi 、k ii Is the proportional parameter and integral parameter, k of the i-th doubly-fed fan converter control p-eq 、k i-eq The proportional and integral parameters of the equivalent unit control machine are obtained.
S52, performing equivalent aggregation on the current collection network according to the distribution parameters of the wind power plant and the grouping result.
The collector network of the wind power plant refers to all circuits of the high-voltage side of the booster at the machine end, which are connected with the public bus PCC (point common coupling) of the wind power plant, and the collector network is generally composed of cables and is an important component in the wind power plant. Because fans at any position of the wind power plant are required to be aggregated, a cable impedance equivalence method based on network resistance equivalent transformation is adopted.
S521, performing topology transformation on the units on each trunk line in the wind power plant, so that the connection form of the units is changed from trunk line type access point to parallel type access point.
S522, calculating the equivalent impedance of the unit access point after each transformation.
The fan arrangement inside the wind farm is typically connected in a trunk line, as shown in fig. 3. The topology transformation is carried out on the unit, so that the connection form of the unit is changed from the trunk access to the parallel access, and the equivalent impedance of the unit connected to the public bus after transformation is calculated as follows:
wherein Z is 1 Representing the impedance between the first fan and the grid-connected point, Z 2 Representing the impedance between the second blower and the first blower access point, and so on; p (P) 1 Representing the output power of the first fan, and so on; l denotes the number of all fans of the mains connection.
S523, calculating the equivalent impedance of the current collecting line of the fans in the same group based on the grouping result, the equivalent impedance of the unit connected with the grid-connected point after each transformation and the wind farm parallel connection topological structure.
The obtained wind farm parallel connection topology is shown in fig. 4. If a certain machine group after division is composed of l machine groups with the numbers of 1-l, according to the principle that the power consumption of the current collecting lines before and after the equivalence is equal, the equivalent impedance of the current collecting lines of the machine group after the equivalence and the PCC bus is as follows:
wherein Z is i-eq The equivalent impedance of the set-up access common bus calculated in step S522 is represented, and l represents the number of all fans connected to the trunk.
For the cable capacitance before and after the equivalent, the difference between the secondary side voltage of the machine-side step-up transformer and the PCC bus voltage can be ignored, and the cable charging capacitance after the equivalent can be regarded as the sum of the charging capacitance before the equivalent. And carrying out equivalent transformation on cable parameters of the wind power plant based on the principle that the power consumption of the current collecting lines is equal before and after the equivalent, so as to realize aggregation of fans at any position in the wind power plant.
The characteristic-approximate fans are aggregated into equivalent fans through the collection, calculation and analysis of the parameters of the doubly-fed fans wind power plant and the data during the fault period, and the purpose of the equivalent is to reflect the characteristics of the wind power plant as accurately as possible and reduce the simulation scale when the fault simulation analysis is carried out on the power system connected with the wind power plant.
It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the invention and is not intended to limit the invention, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. The transient model equivalent calculation method suitable for the doubly-fed wind power plant is characterized by comprising the following steps of:
s1, acquiring distribution parameters and unit parameters of a doubly-fed wind power plant;
s2, sampling parameters of the doubly-fed wind turbine generator set, and constructing a generator set rotor speed time sequence vector according to rotor speeds of the doubly-fed wind turbine generator sets in the sampled wind power plant during faults;
s3, calculating weighted dynamic time bending distances among all units based on the time sequence vectors of the rotating speeds of the units;
s4, aggregating the wind turbine generator sets according to the size of the weighted dynamic time bending distance, so that grouping of the wind turbine generator sets in the wind power plant is realized;
s5, performing equivalent aggregation on the unit parameters in the wind power plant according to the unit parameters and the grouping result; and carrying out equivalent aggregation on the current collection network according to the distribution parameters of the wind power plant and the grouping result.
2. The transient model equivalent calculation method of claim 1, wherein step S2 comprises the sub-steps of:
s21, sampling the rotor rotation speed of the doubly-fed wind turbine from the moment that the wind power plant suffers from an external voltage drop fault to the moment of fault clearing, and constructing a data pair from the sampling time and the sampled set rotor rotation speed;
s22, all data pairs obtained by sampling of each unit form a rotor speed time sequence of the unit, and rotor speed time sequences of a plurality of fans form a rotor speed time sequence vector of the unit.
3. The transient model equivalent calculation method according to claim 1, characterized in that in step S3, the weighted dynamic time warping distance PWDTW between the two time series a and B is calculated as follows:
wherein L is w (i, j) represents the ith sampling point A of the time series A i And the jth sampling point B of the time sequence B j Weighted dynamic time warping distance between d ij For the ith sampling point A of the time sequence A i And the jth sampling point B of the time sequence B j The base distance between the two is m is the number of sampling points of the time sequence A, and n is the number of sampling points of the time sequence B.
4. The transient model equivalent calculation method of claim 3, wherein the ith sampling point a of the time series a i And the jth sampling point B of the time sequence B j Distance d between ij The calculation formula of (2) is as follows:
d ij ＝d(A i ,B j )＝w i-j (A i -B j ) 2
wherein w is i-j The weight values corresponding to the position points of the two rotating speed time series are w max As the upper limit of the weight, g is the curvature constant used to control the weight function w, c= |i-j| is a i And B j E is a profile factor for detecting the change trend of two time tracks, 1<i<min(m,n)，1<j<min(m,n)。
5. The method for calculating the equivalence of the transient model according to claim 1, wherein in the step S5, the calculation method for each parameter in the equivalence cluster after the aggregation of p units in the same cluster is as follows:
wherein R is si 、X si 、R ri 、X ri 、X mi 、R ci 、s i Respectively representing the per unit value and slip of the stator resistance, the stator reactance, the rotor resistance, the rotor reactance, the exciting reactance and the Crowbar resistance of the ith unit in the equivalent machine group, and taking the rated capacity of each unit as a reference; r is R s-eq 、X s-eq 、R r-eq 、X r-eq 、X m-eq 、R c-eq 、s eq Respectively the stator impedance, the rotor impedance, the exciting reactance, the per unit value of the Crowbar resistance and the slip ratio of the equivalent doubly-fed fan, and the equivalent rated capacity s eq Based on, w i The weight of each generator is represented.
6. The transient model equivalent calculation method of claim 1, wherein in step S5, shafting transmission model parameter equivalent parameters are calculated as follows:
wherein H is i 、D i 、K s-i Is the inertia time constant, the generator damping coefficient and the rigidity coefficient of the ith unit in the cluster, H eq 、D eq 、K s-eq And p represents the number of fans aggregated into a group, wherein the inertia time constant, the generator damping coefficient and the rigidity coefficient of the equivalent unit shafting model are obtained.
7. The method for calculating the equivalence of the transient model according to claim 1, wherein in the step S5, the equivalence parameters of the post-equivalence box-type transformer are calculated as follows:
S T-eq ＝pS T
wherein C is i Is a machine end capacitor S T Z is the capacity of the machine-side transformer T For the machine side transformer impedance, p represents the number of fans aggregated into a cluster.
8. The transient model equivalence calculation method according to claim 1, wherein the performing equivalence aggregation on the collector network according to the distribution parameters and the grouping result of the wind power plant comprises the following steps:
(1) Carrying out topology transformation on units on each trunk line in the wind power plant, so that the connection form of the units is changed from trunk line access point to parallel access point;
(2) Calculating equivalent impedance of the unit access point after each transformation;
(3) And calculating the equivalent impedance of the current collecting circuit of the fans in the same group based on the grouping result, the equivalent impedance of the unit connected with the grid-connected point after each transformation and the wind farm parallel connection topological structure.
9. The method for calculating the equivalent impedance of the transient model according to claim 8, wherein the equivalent impedance of the transformed ith unit connected to the common bus is calculated as follows:
wherein Z is 1 Representing the impedance between the first fan and the grid-connected point, Z 2 Representing the impedance between the second blower and the first blower access point, and so on; p (P) i Representing the output power of the ith fan; l denotes the number of all fans of the mains connection.
10. The transient model equivalent calculation method of claim 8, wherein the calculation formula of the equivalent impedance of the current collecting line of the ith unit and the PCC bus after the equivalent is as follows:
wherein Z is i-eq And the equivalent impedance of the ith unit accessed to the public bus after transformation is represented.
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