CN106169747A - A kind of double fed induction generators parameter identification method - Google Patents

A kind of double fed induction generators parameter identification method Download PDF

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CN106169747A
CN106169747A CN201610574727.XA CN201610574727A CN106169747A CN 106169747 A CN106169747 A CN 106169747A CN 201610574727 A CN201610574727 A CN 201610574727A CN 106169747 A CN106169747 A CN 106169747A
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parameter
stator
short circuit
identification
circuit current
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CN106169747B (en
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潘学萍
殷紫吟
鞠平
吴峰
金宇清
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Hohai University HHU
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/30—Circuit design
    • G06F30/36—Circuit design at the analogue level
    • G06F30/367—Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B10/00—Integration of renewable energy sources in buildings
    • Y02B10/30—Wind power

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  • Engineering & Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Power Engineering (AREA)
  • Microelectronics & Electronic Packaging (AREA)
  • Evolutionary Computation (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Control Of Eletrric Generators (AREA)

Abstract

The invention discloses a kind of double fed induction generators (DFIG) parameter identification method, belong to power system modeling field.First, double fed induction generators stator in the case of port three-phase metallic short circuit is determinedThe analytical expression of axle short circuit current, determines parameter to be identified according to this analytical expression；Based on the Matlab/Simulink platform building one machine infinity bus system containing double-fed fan motor unit, arranging three-phase metallic short circuit at double fed induction generators port, emulation obtains statorThe disturbed path of axle short circuit current；Use trace sensitivity method, analyze identifiability and the complexity of parameter identification of each parameter to be identified；Finally use each parameter to be identified of particle swarm optimization algorithm identification, determine parameter identification value based on repeatedly identification result.The present invention is based on statorAxle short circuit current carries out DFIG parameter identification, with compared with active power and reactive power, is affected little by current transformer controlling unit；The repeatedly parameter identification result is used to determine parameter identification value, it is to avoid the problem that error that single identification may cause is big.

Description

A kind of double fed induction generators parameter identification method
Technical field
The invention belongs to power system modeling field, particularly to a kind of double fed induction generators parameter identification method.
Background technology
Modeling is power system computation, analyzes and run the basis of control.Rationally and accurately wind turbine model ginseng Several correctness analyzing electromagnetic transient in power system and electromechanical transient simulation are particularly important, how to obtain closer to actual wind Group of motors model parameter, is the study hotspot of electric power academia and industrial quarters.
When identification double fed induction generators DFIG parameter, being generally basede on Wind turbines at present has under port voltage falls The disturbed path of merit power and reactive power carries out parameter identification.But owing to current transformer controlling unit is dynamic and DFIG Dynamic Coupling Relatively strong, active power, the disturbed path of reactive power that under Voltage Drop, Wind turbines exports are not only the most closely related with DFIG, Affected the biggest by current transformer controlling unit.Therefore time based on active power and reactive power identification DFIG parameter, if control Device parameter set-point processed is inaccurate, will cause the bigger Identification Errors of generator parameter.
Summary of the invention
The technical problem to be solved is: for current DFIG parameter identification precision by current transformer controlling unit shadow The problem rung, propose a kind of based on stator dq axle short circuit current as the parameter identification new method of observed quantity.The present invention proposes Double fed induction generators parameter identification method, carries out parameter identification based on stator dq axle short circuit current；The present invention is additionally based upon repeatedly Identification result obtains parameter identification value, it is to avoid single identification may bring the problem that error is big.
The present invention solves above-mentioned technical problem by the following technical solutions:
The present invention provides a kind of double fed induction generators parameter identification method, including step in detail below:
Step 1, according to double fed induction generators stator dq axle short circuit current in the case of port three-phase metallic short circuit Analytical expression, determine parameter to be identified；
Step 2, based on the Matlab/Simulink platform building one machine infinity bus system containing double-fed fan motor unit, double Feedback influence generator port arranges three-phase metallic short circuit fault, and emulation obtains the disturbed path of stator dq axle short circuit current；
Step 3, uses trace sensitivity method, using stator dq axle short circuit current as observed quantity, calculates parameter to be identified Trace sensitivity；
Step 4, according to trace sensitivity curve calculated in step 3, it is judged that the identifiability of parameter to be identified；
Step 5, the absolute average of the trace sensitivity of each parameter to be identified, choosing in different time window after calculating short circuit The time window selecting trace sensitivity absolute average maximum carries out parameter identification；
Step 6, the time window selected according to step 5, use particle swarm optimization algorithm to carry out parameter identification, the mesh of identification Scalar functions is that error criterion err minimizes, i.e.Its In, K is always counting of identification time window inner stator dq axle short circuit current；isd_estN () is the n-th base in identification time window Stator d axle short circuit current in identifier；isdN () is the n-th stator d axle short circuit current actual value in identification time window； isq_estN () is the n-th stator q axle short circuit current based on identifier in identification time window；isqN () is identification time window Interior n-th stator q axle short circuit current actual value；
Step 7, individually carries out repeatedly parameter identification, calculates repeatedly the average of identification result, rejects and is more than with mean bias The identification result of 100%；Again remaining identification result is asked for average again, as the final identification of each parameter to be identified of DFIG Result.
As the further prioritization scheme of the present invention, in step 1, the analytical expression of stator dq axle short circuit current is:
In formula, isdAnd isqIt is respectively stator d axle short circuit current and q axle short circuit current；is∞And δsuIt is respectively stator side steady The amplitude of state electric current and phase place；M is transient inductance,LsFor stator self inductance, Ls=Lσs+Lm, LσsLeak for stator Sense, LmFor rotor mutual inductance, LrFor rotor self-induction, Lr=Lσr+Lm, LσrFor rotor leakage inductance；WithIt is respectively stator and rotor The initial value of magnetic linkage amplitude；ωsFor synchronous rotational speed；T is the time；δ1And δ2It is respectively stator and the initial value of rotor flux phase place；TSWith TrIt is respectively stator and rotor damping time constant,ω0For specified synchronous rotational speed；RsFor stator resistance,RrFor rotor resistance；S is slippage.
As the further prioritization scheme of the present invention, in step 1, parameter to be identified is Rs、Rr、LsLrAnd Lm。
As the further prioritization scheme of the present invention, in step 2, double-fed fan motor unit uses the measures model phasor model。
As the further prioritization scheme of the present invention, in step 3, the computational methods of trace sensitivity are:
A: the numerical value of a parameter θ to be identified is increased Δ θ, emulation obtains stator dq axle short circuit current disturbed track y, its In, Δ θ is increment, Δ θ=10% θ0, θ0Initial value for parameter θ to be identified；
B: the numerical value of parameter θ to be identified reduces Δ θ, emulation obtains stator dq axle short circuit current disturbed track y '；
C: according to formulaCalculate trace sensitivity S of θj, wherein, K is identification Always counting of time window inner stator dq axle short circuit current；Y (n) and y ' (n) is respectively the n-th stator d axle and q axle short circuit electricity Stream.
As the further prioritization scheme of the present invention, in step 4, the determination methods of parameter differentiability is: be more than if had Or the trace sensitivity curve zero crossing simultaneously equal to 2 parameters to be identified, then judge that these parameters are not uniquely can identification；As The zero passage when sensitivity of the most all parameters is all different, then judge that these parameters uniquely can identification.
As the further prioritization scheme of the present invention, step 3 selects the time after current transformer controlling unit release Window carries out trace sensitivity calculating.
The present invention uses above technical scheme compared with prior art, has following technical effect that the present invention proposes to use Double fed induction generators stator dq axle short circuit current in the case of port three-phase shortcircuit carries out parameter identification, is controlled ring by current transformer The parameter impact of joint is little, and identification precision is high；The repeatedly parameter identification result is used to determine parameter identification value, it is to avoid single identification can The problem that the error that can cause is bigger, improves the identification precision of parameter on the whole.
Accompanying drawing explanation
Fig. 1 is the one machine infinity bus system structure chart containing double-fed fan motor unit.
Fig. 2 is the structure chart of double-fed fan motor unit.
Fig. 3 is the trace sensitivity of each parameter of DFIG, and wherein, (a) is stator resistance RsTrace sensitivity, (b) rotor Resistance RrTrace sensitivity, (c) rotor leakage inductance Lσs、LσrTrace sensitivity, (d) rotor mutual inductance LmTrack sensitive Degree.
Fig. 4 is 50 identification results of each parameter to be identified, and wherein, (a) is stator resistance Rs50 identification results, B () is rotor resistance Rr50 identification results, (c) is the product L of rotor self-inductionsLr50 identification results, (d) is fixed Rotor mutual inductance Lm50 identification results.
Fig. 5 is disturbed path based on parameter identification result Yu actual short electric current, and wherein, (a) is stator d shaft current isd Disturbed path, (b) stator q shaft current isqDisturbed path.
Fig. 6 is the workflow diagram of the present invention.
Detailed description of the invention
Below in conjunction with the accompanying drawings and technical scheme is described in further detail by specific embodiment:
Analogue system is as it is shown in figure 1, be that a stylobate accesses Infinite bus system in the Wind turbines of DFIG, and this analogue system is taken Being built in Matlab 2013b software platform, in system, all elements are taken from the wind energy turbine set example that Matlab carries, double-fed fan motor Unit uses the measures model (phasor model), and the parameter of double fed induction generators is shown in Table 1.
Table 1DFIG simulation parameter
Parameter name Numerical value
Rated power/MW 1.5
Rated voltage/kV 0.575
Initial slip/pu 0.2
Stator resistance/pu 0.00706
Rotor resistance/pu 0.005
Stator leakage inductance/pu 0.171
Rotor leakage inductance/pu 0.156
Mutual inductance/pu 2.9
As in figure 2 it is shown, wherein, β is the propeller pitch angle of pneumatic equipment blades to the structure of double-fed fan motor unit, ωrFor DFIG rotor Rotating speed, irFor the electric current (hereinafter referred to as " rotor current ") in rotor windings, vdrAnd vqrBe respectively rotor excited voltage d axle and Q axle component；vDCRepresent the voltage of DC bus capacitor；vg、igRepresent the output voltage of net side converter, electric current respectively；vdg、vqgPoint Do not represent d, q axle component of net side converter output voltage.
At double fed induction generators port B1 bus as shown in Figure 1, three-phase metallic short circuit fault is set, at time t During=1s, B1 busbar voltage reduces to zero, and fault continues 0.2s, and at time t=1.2s failure vanishes, system recovery is to original state state.
As shown in Figure 6, specifically comprising the following steps that of the DFIG parameter identification that the present invention provides
Step 1: according to the stator dq axle short circuit current analytical expression of double-fed fan motor unit, analytical parameters can identification Property.
Stator dq axle short circuit current expression formula is as follows:
In formula, is∞And δsuIt is respectively amplitude and the phase place of stator side steady-state current；M is transient inductance, LsFor stator self inductance, Ls=Lσs+Lm, LσsFor stator leakage inductance, LmFor rotor mutual inductance, LrFor rotor self-induction, Lr=Lσr+Lm, LσrFor Rotor leakage inductance；WithIt is respectively stator and the initial value of rotor flux amplitude；ωsFor synchronous rotational speed；T is the time；δ1And δ2Point Wei stator and the initial value of rotor flux phase place；TSAnd TrIt is respectively stator and rotor damping time constant,ω0 For specified synchronous rotational speed；RsFor stator resistance,RrFor rotor resistance；S is slippage.
Analytical expression according to said stator dq axle short circuit current: if the resolution table of stator dq axle short circuit current Reach formula it is known that then parameter Lr/M、Lm/M、TsAnd TrUnderstand, and due to ω0Relevant with original state, numerical value is known.Then basis Lr/M、Lm/M、TsAnd TrParameter R can be tried to achievesAnd Rr.According to Lr/ M and Lm/ M can try to achieve LsLrAnd Lm.If therefore stator dq Axle short circuit current is it is known that then parameter Rs、Rr、LsLrAnd LmCan identification, but parameter LsAnd LrCan not individually identification.
Step 2: with stator dq axle short circuit current as observed quantity, calculate the trace sensitivity of each parameter, as shown in Figure 3.From Parameter L in Fig. 3σsAnd LσrTrace sensitivity curve, it can be determined that parameter LσsAnd LσrCannot be distinguished by identification, due to Ls=Lσs+ Lm, Lr=Lσr+Lm, then parameter LsWith LrAlso cannot be distinguished by identification.This conclusion is consistent with the conclusion in step 1.
Step 3: for the size of Quantitative Comparison each parameter trajectory sensitivity, calculate the trace sensitivity of each parameter further Absolute average.Selecting disturbed path time window is the period after current transformer controlling unit release, in order to ignore control The impact on short circuit current of the dynamic characteristic of device.The present invention selects to start the time window before terminating to fault from 1.06s and carries out Calculation of Sensitivity.Different when observing in window each parameter trajectory sensitivity the results are shown in Table 2.
The trace sensitivity of each parameter under window during table 2 different observation
Time window/s Rs/pu Lσs/pu Rr/pu Lσr/pu Lm/pu
1.06-1.10 0.0992 0.2657 0.0462 0.2103 0.0924
1.06-1.12 0.1031 0.2582 0.0340 0.2095 0.1998
1.06-1.14 0.1022 0.2489 0.0272 0.1801 0.2064
1.06-1.16 0.1030 0.2711 0.0230 0.2191 0.2092
1.06-1.18 0.1025 0.2607 0.0210 0.1966 0.2164
1.06-1.20 0.1034 0.2609 0.0200 0.1931 0.2306
Step 4: select the disturbed path of the time window of trace sensitivity absolute average maximum to carry out parameter from table 2 Identification.As selected the stator dq axle short circuit current disturbed path identification stator resistance R in time window [1.06-1.2s]sWith mutually Sense Lm, select time window [1.06-1.1s] inner stator dq axle short circuit current disturbed path identification rotor resistance Rr, select the time The long-pending L of window [1.06-1.16s] inner stator dq axle short circuit current disturbed path identification rotor self-inductionsLr。
Step 5: use each parameter of particle swarm optimization algorithm identification.Individually carry out repeatedly (present invention uses 50 times) parameter to distinguish Knowing, repeatedly identification result is shown in Fig. 4.Repeatedly parameter identification result averagely, the identification knot being more than 100% with mean bias will be rejected Really；Again that remaining parameter is again average, as the final identification result of each parameter of DFIG, it is shown in Table 3.
Table 3DFIG parameter identification result
Parameter True value Average Variance × 10-4 Mean bias/%
Rs/pu 0.00706 0.00745 33.00 5.5241%
Rr/pu 0.005 0.00529 70.00 5.8000%
LsLr/pu 9.385 9.43672 14.43 0.5511%
Lm/pu 2.9 2.90209 1.64 0.0721%
Step 6: compare disturbed path based on parameter identification result Yu actual short electric current, see Fig. 5.
The above, the only detailed description of the invention in the present invention, but protection scope of the present invention is not limited thereto, and appoints What is familiar with the people of this technology in disclosed technical scope, it will be appreciated that the conversion expected or replacement, all should contain Within the scope of the comprising of the present invention, therefore, protection scope of the present invention should be as the criterion with the protection domain of claims.

Claims (7)

1. a double fed induction generators parameter identification method, it is characterised in that include step in detail below:
Step 1, according to double fed induction generators DFIG stator dq axle short circuit current in the case of port three-phase metallic short circuit Analytical expression, determine parameter to be identified；
Step 2, based on the Matlab/Simulink platform building one machine infinity bus system containing double-fed fan motor unit, in double-fed sense Answering electromotor port to arrange three-phase metallic short circuit fault, emulation obtains the disturbed path of stator dq axle short circuit current；
Step 3, uses trace sensitivity method, using stator dq axle short circuit current as observed quantity, calculates the rail of parameter to be identified Mark sensitivity；
Step 4, according to trace sensitivity curve calculated in step 3, it is judged that the identifiability of parameter to be identified；
Step 5, after calculating short circuit, the absolute average of the trace sensitivity of each parameter to be identified in different time window, selects rail The time window of mark sensitivity absolute average maximum carries out parameter identification；
Step 6, the time window selected according to step 5, use particle swarm optimization algorithm to carry out parameter identification, the target letter of identification Number minimizes for error criterion err, i.e.Wherein, K is Always counting of identification time window inner stator dq axle short circuit current；isd_estN () is n-th based on identification in identification time window The stator d axle short circuit current of value；isdN () is the n-th stator d axle short circuit current actual value in identification time window；isq_est(n) For the in identification time window n-th stator q axle short circuit current based on identifier；isqN () is n-th fixed in identification time window Sub-q axle short circuit current actual value；
Step 7, individually carries out repeatedly parameter identification, calculates repeatedly the average of identification result, rejects with mean bias more than 100% Identification result；Again remaining identification result is asked for average again, as the final identification result of each parameter to be identified of DFIG.
A kind of double fed induction generators parameter identification method the most according to claim 1, it is characterised in that fixed in step 1 The analytical expression of sub-dq axle short circuit current is:
In formula, isdAnd isqIt is respectively stator d axle short circuit current and q axle short circuit current；is∞And δsuIt is respectively stator side steady-state current Amplitude and phase place；M is transient inductance,LsFor stator self inductance, Ls=Lσs+Lm, LσsFor stator leakage inductance, LmFor Rotor mutual inductance, LrFor rotor self-induction, Lr=Lσr+Lm, LσrFor rotor leakage inductance；WithIt is respectively stator and rotor flux width The initial value of value；ωsFor synchronous rotational speed；T is the time；δ1And δ2It is respectively stator and the initial value of rotor flux phase place；TSAnd TrRespectively For stator and rotor damping time constant,ω0For specified synchronous rotational speed；RsFor stator resistance, RrFor rotor resistance；S is slippage.
A kind of double fed induction generators parameter identification method the most according to claim 2, it is characterised in that treat in step 1 Identified parameters is Rs、Rr、LsLrAnd Lm。
A kind of double fed induction generators parameter identification method the most according to claim 1, it is characterised in that double in step 2 Feedback Wind turbines uses the measures model phasor model.
A kind of double fed induction generators parameter identification method the most according to claim 1, it is characterised in that rail in step 3 The computational methods of mark sensitivity are:
A: the numerical value of a parameter θ to be identified is increased Δ θ, emulates and obtains stator dq axle short circuit current disturbed track y, wherein, Δ θ is increment, Δ θ=10% θ0, θ0Initial value for parameter θ to be identified；
B: the numerical value of parameter θ to be identified reduces Δ θ, emulation obtains stator dq axle short circuit current disturbed track y '；
C: according to formulaCalculate trace sensitivity S of θj, wherein, K is the identification time Always counting of window inner stator dq axle short circuit current；Y (n) and y ' (n) is respectively the n-th stator d axle and q axle short circuit current.
A kind of double fed induction generators parameter identification method the most according to claim 1, it is characterised in that join in step 4 The determination methods of number identifiability is: if there being the trace sensitivity curve zero passage simultaneously more than or equal to 2 parameters to be identified Point, then judge that these parameters are not uniquely can identification；Zero passage when if the sensitivity of all parameters is all different, then judge that these are joined Number uniquely can identification.
A kind of double fed induction generators parameter identification method the most according to claim 1, it is characterised in that select in step 3 Select the time window after current transformer controlling unit release and carry out trace sensitivity calculating.
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CN107239606A (en) * 2017-05-27 2017-10-10 国网福建省电力有限公司 A kind of Sensitivity Analysis Method for presurized water reactor system dynamic model parameter evaluation
CN107453401A (en) * 2017-09-13 2017-12-08 河海大学 A kind of double-fed wind power generator parameter identification method
CN107798205A (en) * 2017-12-11 2018-03-13 河海大学 The independent discrimination method of double-fed induction wind driven generator group shafting model parameter
CN108197381A (en) * 2017-12-29 2018-06-22 河海大学 Parameter identification method based on optimizing spatial shape analysis
CN109981011A (en) * 2019-04-03 2019-07-05 中国水利水电科学研究院 A kind of generator parameter identification method
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CN107239606A (en) * 2017-05-27 2017-10-10 国网福建省电力有限公司 A kind of Sensitivity Analysis Method for presurized water reactor system dynamic model parameter evaluation
CN107453401A (en) * 2017-09-13 2017-12-08 河海大学 A kind of double-fed wind power generator parameter identification method
CN107798205A (en) * 2017-12-11 2018-03-13 河海大学 The independent discrimination method of double-fed induction wind driven generator group shafting model parameter
CN108197381A (en) * 2017-12-29 2018-06-22 河海大学 Parameter identification method based on optimizing spatial shape analysis
CN108197381B (en) * 2017-12-29 2019-09-27 河海大学 Parameter identification method based on optimizing spatial shape analysis
CN109981011A (en) * 2019-04-03 2019-07-05 中国水利水电科学研究院 A kind of generator parameter identification method
CN111293693A (en) * 2020-03-30 2020-06-16 华北电力大学 Doubly-fed wind turbine converter control parameter identification method based on extended Kalman filtering
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