CN107565867A - A kind of Parameter Identification Method of Synchronous Generator based on trace sensitivity - Google Patents
A kind of Parameter Identification Method of Synchronous Generator based on trace sensitivity Download PDFInfo
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Abstract
The present invention relates to a kind of Parameter Identification Method of Synchronous Generator based on trace sensitivity.The parameter identification problem of synchronous generator, by trajectory sensitivity analysis, the data interval for being advantageous to improve identification precision is chosen, on the basis of solving Identification Data section On The Choice, it is also proposed that complete identification model.The present invention has good robustness, advances the practicalization of generator parameter identification.
Description
Technical field
The present invention relates to a kind of Parameter Identification Method of Synchronous Generator based on trace sensitivity.
Background technology
Synchronous generator is as one of equipment most crucial in power system, and the accuracy of its mathematical modeling is to power system
Dynamic Simulation Results influence huge.Due to lacking actual parameter, current Electrical power system analysis and computing emulation synchronous hair used
The data or representative value that the parameter of electric machine is provided using producer more, or have no alternative but use simplified model, and synchronous generator dynamic is joined
Number is much equivalent model parameter, is changed such as system conditions difference.Simultaneously because data it is incomplete and do not count and
The influence of the actual operating modes such as vortex, magnetic hysteresis, saturation, the parameter provided using producer carries out emulating acquired results and reality is dynamic
State process has greater difference, and has had a strong impact on the degree of accuracy and the confidence level of Electrical Power System Dynamic calculating.Therefore synchronous generator
Parameter identification is always the important content studied in power system.
Parameter Identification Method of Synchronous Generator is broadly divided into two classes at present：Off-line identification and on-line identification.Off-line identification is led to
Cross and short-circuit test is carried out in generator outage period, throws the upset tests such as load experiment, parameter identification is carried out according to test data.But
Because field test is relatively complicated and is possible to bring potential safety hazard to generator, off-line identification work is implemented more difficult.And
On-line identification avoids the cumbersome of experiment, and the result based on actual operating data identification is more close to operating condition, therefore more suitable
Together in generator parameter identification.
When Generator Stable is run, its steady state data only reflects Steady-state Parameters Xd,XqSize and it is unrelated with transient state parameter, only
Have when generator is disturbed, the change of its generator terminal electrical quantity could reflect the size of generator transient state parameter, therefore generator
On-line parameter identification must combine generator noisy data and carry out.But during practical application, how by effective generator disturb number
According to separating, i.e., how Identification Data section is chosen from longer metric data, there is no document to propose related solve so far
Scheme.The difficult point of Identification Data section On The Choice is, excessive steady state data is contained in long data segment, is reduced
The proportion of transient state, secondary transient information in data, the reduction of transient state, secondary transient state parameter identification precision can be caused；And too short number
It is likely to lack required secondary transient state, secondary transient information according to section, is less useful for parameter identification.Therefore how Identification Data is chosen
Section be one with parameter identification precision be closely related the problem of.
The content of the invention
It is an object of the invention to provide a kind of Parameter Identification Method of Synchronous Generator based on trace sensitivity, this method
With good robustness, the practicalization of generator parameter identification is advanced.
To achieve the above object, the technical scheme is that：A kind of Generator Parameters based on trace sensitivity
Discrimination method, it is characterised in that：Comprise the following steps,
Step S1, the selection in Identification Data section is carried out based on trace sensitivity：
Trace sensitivity absolute value in S11, solution complete period | Sd(t)|,|Sq(t)|；
S12, using the stable state sampled point before disturbance as Identification Data section starting point, i.e., from t0=0 starts, every Δ t=
4T”d0Data segment calculate once from starting point to the trace sensitivity average value of the point
SΔt,avg,S2Δt,avg,S3Δt,avg…：
Wherein, NnΔtFor t0Sampling number in the n Δ t periods, SnΔt,avgThe trace sensitivity calculated for n-th is put down
Average；
S13, decay to S when trace sensitivity average valuenΔt,avg≤SnΔt/10,avg/ 4 or n Δs t >=30s, you can stop meter
Calculate, with t0The n Δ t periods are as d axle parameter identification data intervals；Q axle parameter identification data intervals can similarly be solved；
Step S2, using robust Optimized model as identification model identified parameters：
By the rank utility model of synchronous generator six：
Wherein, TJFor the inertia time constant of generating set, D is the Damping Power coefficient of generator；
Understand,
D axles parameter to be identified has Xd,X'd,X'd',Td'0,Td”0, q axles parameter to be identified has Xq,Xq',Xq”,Tq'0,Tq”0；
By taking the identification of q axle parameters as an example, it is assumed that measured value x, according to estimates of parametersAnd solve obtained q axles ginseng
Number Identification Data section, x=ud、iq, ω,Pass through following robust Optimized models：
It is that the identification of q axle parameters can be achieved to solve above formula optimization problem using interior point method；Wherein, tiFor i-th in section
Time step moment, tiSection be q axle parameter identification data intervals required in step S1.Similarly, distinguishing for d axle parameters can be achieved
Know.
Further, the calculation formula of trace sensitivity absolute value is as follows in the step S11：
Compared to prior art, the invention has the advantages that：
The present invention proposes parameter identification data interval choosing method, and solve that parameter identification data are difficult to choose asks
Topic.The present invention is based on trajectory sensitivity analysis, chooses the data interval for being advantageous to improve identification precision, and to solve, engineering is actual to ask
Topic provides theoretical foundation.On the basis of solving Identification Data section On The Choice, the invention also provides complete parameter
Identification model, there is good robustness, advance the practicalization of generator parameter identification.
Brief description of the drawings
Fig. 1 is that MATLAB of the present invention throws load experiment simulation system figure.
Fig. 2 is trace sensitivity curve map of the present invention.
Fig. 3 is trace sensitivity curve map of the present invention.
Fig. 4 is the Identification Errors figure in different Identification Data sections.
Fig. 5 is the Identification Errors figure in different Identification Data sections.
Embodiment
Below in conjunction with the accompanying drawings, technical scheme is specifically described.
A kind of Parameter Identification Method of Synchronous Generator based on trace sensitivity, it is characterised in that：Comprise the following steps,
Step S1, the selection in Identification Data section is carried out based on trace sensitivity：
Trace sensitivity absolute value in S11, solution complete period | Sd(t)|,|Sq(t)|；
S12, using the stable state sampled point before disturbance as Identification Data section starting point, i.e., from t0=0 starts, every Δ t=
4T”d0Data segment calculate once from starting point to the trace sensitivity average value of the point
SΔt,avg,S2Δt,avg,S3Δt,avg…：
Wherein, NnΔtFor t0Sampling number in the n Δ t periods；
S13, decay to S when trace sensitivity average valuenΔt,avg≤SnΔt/10,avg/ 4 or n Δs t >=30s, you can stop meter
Calculate, with t0The n Δ t periods are as d axle parameter identification data intervals；Q axle parameter identification data intervals can similarly be solved；
Step S2, using robust Optimized model as identification model identified parameters：
By the rank utility model of synchronous generator six：
Understand,
D axles parameter to be identified has Xd,X'd,X'd',Td'0,Td”0, q axles parameter to be identified has Xq,Xq'q,Xq”,Tq'0,Tq”0；
By taking the identification of q axle parameters as an example, it is assumed that measured value x, according to estimates of parametersAnd solve obtained q axles ginseng
Number Identification Data section, x=ud、iq, ω,Pass through following robust Optimized models：
The identification of q axle parameters can be achieved；Similarly, the identification of d axle parameters can be achieved；Wherein, tiSection be required
Q axle parameter identification data intervals.
Further, the calculation formula of trace sensitivity absolute value is as follows in the step S11：
It is below the specific implementation process of the present invention.
The invention mainly comprises the data interval choosing method of Parameter Estimation of Synchronous Machines；Based on robust Optimized model
This both sides of parameter identification method works.
Choose in Identification Data section
Steady-state operating condition is normality in generator actual moving process, and state of disturbance only accounts for small part, because
This can be used in the metric data of parameter identification generally comprising the steady state data of long period, and include transient state, secondary transient information
Noisy data it is then shorter.When Identification Data is selected from metric data, should as far as possible using noisy data as Identification Data,
Because steady state data can only reflect Steady-state Parameters Xd,XqSize and it is unrelated with transient state parameter, only when generator is disturbed, its
The change of generator terminal electrical quantity could reflect the size of generator transient state parameter.During noisy data being chosen from metric data,
The starting point of noisy data, that is, the initial time of generation is disturbed, be relatively easy to recognize, but the terminal of noisy data is difficult then definition.
Excessive steady state data is contained in long data segment, the proportion of transient state, secondary transient information in data is reduced, can cause
The reduction of transient state, secondary transient state parameter identification precision；And too short data segment is likely to lack required secondary transient state, secondary transient state letter
Breath, is less useful for parameter identification.Therefore Identification Data section On The Choice is most important for Identification of parameter.
The present invention chooses Identification Data section based on trace sensitivity, it is necessary first to analyzes trace sensitivity and its calculating side
Method.The dynamic characteristic of generator can use following subordination principle to describe：
In formula：X is state vector, and Y is algebraically vector, and θ is parameter vector.Trace sensitivity is that state variable or output become
The track knots modification of amount is defined as to the ratio of parameter change amount：
In formula：yiFor the track of i-th of variable in system；θjFor j-th of parameter in system；M is parameter sum；K is the time
Sampled point.To improve trace sensitivity computational accuracy, it is necessary to first calculate track at twice： yi(θ1,θ2,…θj+Δθj,…θm,
K), yi(θ1,θ2,…θj-Δθj,…θm, k), then calculating trace sensitivity is：
Trace sensitivity reflects the intensity of variation that model output dynamic trajectory during minor variations occurs for parameter, wide at present
It is general to be applied in parameters of electric power system discrimination method.If Generator Status amount is in specific section to the trace sensitivity of certain parameter
Larger, then explanation can cause fitting and measured data to produce very big deviation in the less Identification Errors of section intrinsic parameter,
Because parameter identification is the minimum target of error to be fitted and survey, therefore the higher identification for meaning parameter of trace sensitivity
Precision is high or identifiability is higher.Implication based on trace sensitivity, the present invention propose to be selected according to trace sensitivity size
Identification Data section, and because parameter identification method is d, q decoupler shaft, therefore can be respectively that the selection of d, q axle parameter is rationally distinguished
Know data interval.
After generator outer net breaks down or operated, generator terminal electric current often fluctuates the most violent in each electrical quantity, therefore
The trace sensitivity of selection should be with d, q shaft current id,iqFor state variable, and it is the dynamic fluctuation time of generator and transient state, secondary
Time constant is directly related, therefore chooses trace sensitivity：
Because the size of trace sensitivity is that relative two measuring points are relative, therefore should declining with trace sensitivity
It is foundation to subtract degree, carries out the selection in Identification Data section, and specific algorithm step is as follows：
1) the trace sensitivity absolute value in complete period is solved | Sd(t)|,|Sq(t)|。
2) using the stable state sampled point before disturbance as Identification Data section starting point (t0=0), every Δ t=4T "d0Data segment
Calculate the once trace sensitivity average value S from starting point to the pointΔt,avg,S2Δt,avg,S3Δt,avg…：
Wherein NnΔtFor t0Sampling number in the n Δ t periods.
3) when trace sensitivity average value decays to SnΔt,avg≤SnΔt/10,avg/ 4 or n Δs t >=30s, you can stop calculating,
With t0The n Δ t periods are as d axle parameter identification data intervals.Q axle parameter identification data intervals can similarly be solved.
Parameter identification method based on robust Optimized model
Synchronous generator utility model is most widely used generator model, therefore chooses the rank of synchronous generator six herein
Practical mould carries out parameter identification, and the rank utility model of synchronous generator six is as shown in formula:
Wherein d axles parameter to be identified has Xd,X'd,X'd',Td'0,T”d0, q axles parameter to be identified has Xq,X'q,X”q,Tq
'0,”q0(ignore armature resistance Ra).In addition to special mark, all parameters herein and variable are perunit value.
The essence of parameter identification problem is an optimization problem, and (parameter identification of d, q axle is decoupling by taking q axle parameters as an example
Separately carry out), it is assumed that measuring value is x (including ud,iq, ω), known i.e. to the searching process of following formula according to estimates of parameters：
Solving can cause fitting electric current to reach one group of estimates of parameters of highest with measured current degree of fittingIt is but actual
Measurement error in measurement unavoidably be present, in some instances it may even be possible to several sample point data substantial deviation actual values of minority be present, be called
Bad data.The presence of bad data can cause bad data item in optimization object function to occupy leading position, thus optimum results are more
Tend to be fitted bad data.For such case, present invention employs robust Optimized model as identification model：
In the object function of the model, if bad data i be presentq(ti), its shared ratio in whole object function isBecause the difference of bad data item and fitting current value is larger, therefore its institute in object function
Accounting example will be narrowed in admissible error, so that identification model is provided with robustness.
It is below the specific embodiment of the present invention
A kind of Identification Data section choosing method based on trace sensitivity of the present invention, carried out using MATLAB emulation data
Parameter identification, it compared for choosing the parameter identification result and the parameter of other data intervals in Identification Data section based on context of methods
Identification result.Using MATLAB emulation data carry out parameter identification benefit be generator parameter true value be it is known, therefore
The quality of identification result can be judged.
Synchronous generator is built using MATLAB and throws load experiment simulation system, as shown in Figure 1.Wherein synchronous generator uses
Non-salient pole alternator model in MATLAB-SIMULINK, capacity 555MVA, specified set end voltage are 24kV.The system
There is provided two loads, respectively 150MW+15MVar (Initial Load) and 100MW (Load Step off), emulating
Disconnected to 6s moment Load Step off loads with synchronous generator.
The trace sensitivity in complete period is calculated firstAs shown in Figure 2.
From Fig. 2,3, trace sensitivity Sd(t),Sq(t) numerical value is all very small under initial steady state, is thrown in 6s
Trace sensitivity starts to fluctuate after carrying disturbance, as generator is transitioned into new stable state, trace sensitivity Sd(t),Sq(t) and decline
Reduce to compared with fractional value.Using moment 5.96s before disturbance as Identification Data section starting point, chosen and distinguished according to institute's extracting method step of the present invention
Know data interval, Sd(t),Sq(t) meet damp condition in 15.2s and 15.5s respectively, therefore choose d axle parameter identification data
Section is [5.96s, 15.2s], and q axle parameter identifications data interval is [5.96s, 15.5s].
Fig. 4,5 compare the parameter identification error obtained according to different Identification Data sections, and wherein data interval starting point is equal
Moment (5.96s) is fixed as before disturbance occurs, and the transverse axis coordinate each put is the end point values of its data interval, chooses different areas
Between terminal correspond to different Identification Data sections, wherein parameter identification error refers to the relative error of d axles or all parameters of q axles
Absolute value and.
From Fig. 4,5, excessive or too small Identification Data section can all cause parameter identification error larger, and by this hair
The parameter identification error that the Identification Data section that bright proposition method is chosen obtains is smaller, is in close proximity to accessible minimum identification
Error, it was demonstrated that the validity proposed by the present invention based on trace sensitivity selection Identification Data interval method.
Above is presently preferred embodiments of the present invention, all changes made according to technical solution of the present invention, caused function are made
During with scope without departing from technical solution of the present invention, protection scope of the present invention is belonged to.
Claims (2)
- A kind of 1. Parameter Identification Method of Synchronous Generator based on trace sensitivity, it is characterised in that：Comprise the following steps,Step S1, the selection in Identification Data section is carried out based on trace sensitivity：Trace sensitivity absolute value in S11, solution complete period | Sd(t)|,|Sq(t)|；S12, using the stable state sampled point before disturbance as Identification Data section starting point, i.e., from t0=0 starts, every Δ t=4T "d0's Data segment calculates the once trace sensitivity average value S from starting point to the pointΔt,avg,S2Δt,avg,S3Δt,avg…：Wherein, SnΔt,avgThe trace sensitivity average value calculated for n-th, NnΔtFor t0Sampling number in the n Δ t periods；S13, decay to S when trace sensitivity average valuenΔt,avg≤SnΔt/10,avg/ 4 or n Δs t >=30s, you can stop calculating, with t0The n Δ t periods are as d axle parameter identification data intervals；Q axle parameter identification data intervals can similarly be solved；Step S2, using robust Optimized model as identification model identified parameters：By the rank utility model of synchronous generator six：Wherein, TJFor the inertia time constant of generating set, D is the Damping Power coefficient of generator；Understand,D axles parameter to be identified has Xd,X'd,X'd,T'd0,T”d0, q axles parameter to be identified has Xq,X'q,X”q,T'q0,T”q0；By taking the identification of q axle parameters as an example, it is assumed that measured value x, according to estimates of parametersAnd solve obtained q axle parameters and distinguish Know data interval, x=ud、iq, ω,Xq'、X”q、T'q0、T”q0, pass through following robust Optimized models：It is that the identification of q axle parameters can be achieved to solve above formula optimization problem using interior point method；Wherein, tiFor in section during i-th of time step Carve, tiSection be q axle parameter identification data intervals required in step S1.Similarly, the identification of d axle parameters can be achieved.
- 2. according to the method for claim 1, it is characterised in that：The calculating of trace sensitivity absolute value in the step S11 Formula is as follows：
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| CN110943485B (en) * | 2019-12-22 | 2022-03-22 | 东北电力大学 | Index evaluation method for simulation reliability of equivalent model of doubly-fed wind power plant |
| CN114094900A (en) * | 2021-11-19 | 2022-02-25 | 合肥工业大学 | Permanent magnet synchronous motor parameter online identification method |
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