CN109120007A - A kind of more current transformer control method for coordinating based on particle swarm optimization algorithm - Google Patents
A kind of more current transformer control method for coordinating based on particle swarm optimization algorithm Download PDFInfo
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- CN109120007A CN109120007A CN201810823298.4A CN201810823298A CN109120007A CN 109120007 A CN109120007 A CN 109120007A CN 201810823298 A CN201810823298 A CN 201810823298A CN 109120007 A CN109120007 A CN 109120007A
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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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
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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
- H02J3/01—Arrangements for reducing harmonics or ripples
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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
- 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]
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- 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
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/40—Arrangements for reducing harmonics
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Abstract
The invention discloses a kind of more current transformer control method for coordinating based on particle swarm optimization algorithm, include the following steps: the model for establishing current transformer, analyze and derive the transmission function of output unit；Determine the harmonic frequency approximate range for needing to inhibit, the relevant parameter for setting corresponding PI controller parameter, determining particle swarm optimization algorithm；The virtual resistance value R (i) and renewal speed Vstep (i) of random initializtion particle i；Virtual resistance particle is judged so that the THD [R] of current transformer grid entry point voltage is adaptation value function, initializes individual optimal value and obtains population global optimum；It iterates with speed iterative formula and virtual resistance iterative formula to meeting the condition of convergence or reaching maximum number of iterations, so that it is determined that virtual resistance resistance value；Keep the harmonic wave virtual resistance of each current transformer equal with harmonic impedance, to realize the optimal inhibition effect of multinode harmonic voltage.The method of the present invention can carry out search quickly, accurate, global using swarm of particles optimization algorithm to the size of harmonic wave virtual resistance.
Description
Technical field
The present invention relates to power equipment control research field, in particular to a kind of more changes based on particle swarm optimization algorithm
Device control method for coordinating is flowed, suitable for the distribution network system node voltage harmonic wave accessed containing more distributed power generation current transformers
Coordination optimization is administered.After distributed current transformer accesses distribution network system node, using virtual resistance method control current transformer to spy
Subharmonic is determined in resistive, and then node voltage harmonic wave is inhibited, finally according to particle swarm optimization algorithm to more unsteady flows
The virtual resistance of device, which quickly adjust, obtains global best visual resistance, realizes optimal harmonic suppression effect.
Background technique
The environmental consciousness of people is more and more stronger in recent years, makes to receive extensively using the distributed generation technology of generation of electricity by new energy
General concern, distributed generation resource (DG) are that specific gravity shared in system is higher and higher in electricity.DG equipment based on grid-connected converter,
Power quality controlling equipment is widely applied in power distribution network, these equipment based on grid-connected converter are although technologically advanced, work
It is high-efficient, but there is also problems, for example, equipment and technology content is high, makes its operation, safeguard that there are higher technical thresholds.
But more it is essential that these device fabrication purposes are relatively single, energy conversion or utility power quality control are only considered.In fact, this
Two class equipment (are mostly based on instantaneous power theory and PWM skill in power electronic circuit topology, device hardware structure, control strategy
Art designs) on have many similar features.For this purpose, carrying out technological innovation design in the grid-connected converter of DG, make it in reality
On the basis of existing energy conversion, takes into account and have utility power quality control function, be all feasible from hardware configuration, control strategy.
However due to system, the uncertainty of load, usually line impedance and non-thread can not be accurately obtained by calculating
Property load Equivalent Harmonic current source specific value, but due to the existence of best visual resistance, and harmonic power and empty
There are extreme values for the function of quasi- resistance value, therefore, carry out optimizing to virtual resistance resistance value using certain optimization algorithm.
The control method for using linear search to carry out optimizing to virtual resistance in separate unit current transformer is feasible, but is worked as
Multinode multiple-variable flow device work in the active utility power quality control state based on virtual resistance method, traditional optimization method be by
Multi-objective optimization question is converted into single-object problem, but this is largely dependent upon policymaker to the feature of optimization problem
Information extraction.If problem becomes complicated, scale and dimension become more, and will lead to calculating using traditional optimization method becomes excessively
It is complicated, it is difficult to obtain mathematical model, thereby increases and it is possible to fall into local optimum.In addition, when using linear search, between more current transformers not
Coordinate, more virtual harmonic wave resistance may adjust repeatedly, and when certain current transformer is optimal, remaining current transformer is not up to optimal
State will do it optimizing again, to influence this current transformer in turn, the continuous optimizing of system, search result can not be stablized always,
It is unable to complete solution.
Particle swarm optimization algorithm passes through the foraging behavior of simulation birds, when entire flock of birds goes out to look for food together, in flock of birds
Each bird by adjusting oneself heading with adjacent similar carry out information exchange, as long as a final bird can look for
To food location, all birds in flock of birds can reach food location.Every bird herein can be excellent as population
Change a particle in algorithm, a bird in the particle image flock of birds it is the same with certain speed in designated space (i.e. optimizing
Search space) in movement；Food location is the best solution to be searched for (or most just when), due to every in flock of birds
Bird is likely to find food location, therefore each particle in algorithm is a potential optimal solution of optimization problem；
There are information interchange behavior in flock of birds, the particle in algorithm is then by being added other particles in its speed and location update formula
Coordinate realize communication function.By above-mentioned simulation, each particle of particle swarm optimization algorithm can finally find excellent
The globally optimal solution of change problem.Therefore, particle swarm optimization algorithm is applied to the multiple-variable flow device control algolithm of device for harmonic inhibition
In be a feasible direction.
Summary of the invention
It is an object of the invention to overcome shortcoming and deficiency in the prior art, provide a kind of based on particle swarm optimization algorithm
More current transformer control method for coordinating, this method be based on particle swarm optimization algorithm, by quickly being adjusted in full search space
The size of each equivalent output harmonic wave resistance of current transformer, more current transformers of coordinated control absorb mains by harmonics, realize more piece
Point multiple-variable flow device harmonic voltage inhibits, so that Distributed power net system node harmonic voltage level is effectively reduced.
In order to achieve the above object, the present invention adopts the following technical scheme that:
A kind of more current transformer control method for coordinating based on particle swarm optimization algorithm, by search best visual resistance come
Realize the coordinated control of more electric current devices, which is characterized in that this method includes the following steps:
S1, the model for establishing current transformer, analyze and derive the transmission function of output unit；
S2, the harmonic frequency range for needing to inhibit is determined according to the transmission function, and set PI controller parameter, determine
For searching for the relevant parameter of the particle swarm optimization algorithm of virtual resistance value；
The virtual resistance value R (i) and renewal speed Vstep (i) of S3, random initializtion particle i；
S4, each harmonic voltage magnitude is obtained according to the corresponding virtual resistance value of different particles, and then construct grid-connected change
Device is flowed to the filter effect function of grid entry point voltage harmonic, and the filter effect function is retouched with total harmonic distortion factor THD [R]
It states；It is the filter effect for adapting to value function to judge each particle virtual resistance with the total harmonic distortion factor THD [R]；It will step
The particle virtual resistance initial value of rapid S3 randomization is optimal by the individual of different particles as individual optimum virtual resistance initial value
The filtering adaptive value of virtual resistance initial value is compared, and obtains population global optimum virtual resistance initial value；
S5, particle update is carried out according to individual and global optimum's virtual resistance initial value and iterative formula, then calculated
And haggle over updated each particle i, individual optimum virtual resistance value particle GiWith the filter of global optimum virtual resistance value particle P
Individual and global optimum's virtual resistance value are carried out assignment update, then iterate to satisfaction according to comparison result by wave adaptive value
The condition of convergence reaches maximum number of iterations, most using global optimum's virtual resistance value after iteration as each current transformer
Excellent virtual resistance value；
S6, control current transformer export corresponding harmonic compensation current, so that the optimum virtual resistance value R (i) of each current transformer
With in terms of grid entry point to the harmonic impedance Z of systemhModulus value distinguish equal, subscripthIndicate h subharmonic, by circuit theory it is found that
Extrernal resistance is equal in harmonic source at this time, and current transformer absorbs harmonic power maximum, to realize the control of more converter harmonic voltage.
The step S1 as a preferred technical solution, includes the following steps:
S101, the circuit model for establishing distributed current transformer: LCL filter circuit is used, the first inductance L is specifically included1,
One inductance parasitic resistance R1, the second inductance L2, the second inductance parasitic resistance R2, capacitor C and capacitive parasitic resistance RC；Described first
Inductance L1Connect the first inductance parasitic resistance R1；The second inductance L2Connect the second inductance parasitic resistance R2；The capacitor C connects
Meet capacitive parasitic resistance RC, the first inductance parasitic resistance R1Connect the second inductance parasitic resistance R2With capacitive parasitic resistance RC；
S102, the output-transfer function that current transformer is derived according to the circuit model of distributed current transformer, specifically: according to step
The circuit model of rapid S101 distribution current transformer, when doing Simplified analysis, by the first inductance parasitic resistance R1It is posted with the second inductance
Raw resistance R2Ignore, obtains from inversion bridge voltage UinvElectric current i is exported to grid side2Transmission function, be denoted as GLCL(s), specific public
Formula are as follows:
Wherein, s indicates complex parameter；i2(s) output electric current is indicated；vinv(s) current transformer output voltage is indicated；
The parameter of LCL filter circuit is L1=0.74mH, C=6.6 μ F, L2=55 μ H, therefore the resonance of output-transfer function
FrequencyIt is less than in the frequency of output current of converter humorous
When vibration frequency, gain is higher；When the frequency of output current of converter is greater than resonance frequency, gain reduction is very fast, therefore the filter
Wave circuit can retain the output of low-frequency harmonics compensation and can effectively inhibit high-frequency harmonic, can be used for exporting low-order harmonic simultaneously to height
Subharmonic is inhibited.
Step S2 as a preferred technical solution, specifically include the following steps:
S201, determine the harmonic frequency range for needing to inhibit: the maximum of the current transformer of setting device for harmonic abatement functions is mended
Repay harmonic frequency fmax；The maximum compensation harmonic frequency fmaxLess than the resonance frequency f of transmission functionres, and according to compensation range
Setting；When needing compensation to arrive n times harmonic wave, f is setmax=Nf0, f0It is the multiple of odd number and non-3 for fundamental frequency 50Hz, N, i.e.,
5,7,11,13……；fmax<fres；
S202, current inner loop are controlled using PI, and the PI parameter of respectively specific subharmonic is configured, and are realized and are revolved at each time
Turn the zero steady state error control under coordinate system；The PI parameter includes the proportionality coefficient of ratio control P and the integral coefficient of integration control；
S203, it utilizes particle swarm optimization algorithm: determining the scale and dimension of population according to current transformer quantity, work as separate unit
When current transformer is run, virtual resistance value is an one-dimensional parameter；When more current transformer operations, by the dimension for increasing virtual resistance value
The efficient operation of number more current transformers of tunable, realizes effective inhibition of node harmonic voltage；
S204, the relevant parameter for determining particle swarm optimization algorithm, the relevant parameter include: accelerated factor c1With c2, grain
The initial value w of subgroup inertia weightmaxWith end value wmin, maximum number of iterations tmax, greatest iteration speed vmaxWith minimum iteration
Speed vminAnd the upper limit R in virtual resistance value optimization sectionmaxWith lower limit Rmin。
As a preferred technical solution, in step S204, population inertia weight uses dynamic inertia weight coefficient, with
The increase of the number of iterations and linear decrease, the formula being related to are as follows:
Wherein wmaxFor the initial value of population inertia weight；wminFor the end value of population inertia weight；T is current changes
Generation number.
As a preferred technical solution, in step S204, virtual resistance value section, setting are estimated by one phase equivalent circuit figure
The upper limit R in virtual resistance value optimization sectionmaxWith lower limit Rmin, further according to formula vmax=Rmax-RminDetermine maximum update speed,
By vmin=-vmaxObtain minimum renewal speed.
As a preferred technical scheme, detailed process is as follows by step S3:
Virtual resistance value and the renewal speed initialization of particle i is completed by following two formula respectively:
R (i)=rand × (Rmax-Rmin)+Rmin (3)
Vstep (i)=rand × (vmax-vmin)+vmin (4)
In formula (3) and formula (4), rand is the random number within 0~1；Particle virtual resistance R (i) is generated by random number.
As a preferred technical solution, by search space discretization, two are only retained to the value of particle virtual resistance R (i)
Position decimal.
Step S4 as a preferred technical solution, specifically include the following steps:
S401, grid entry point voltage waveform is obtained under the corresponding virtual resistance value control of different particles, to grid entry point voltage
Fast Fourier Transform (FFT) is done, each harmonic voltage magnitude V is obtainedn, n expression n-th harmonic, n=2,3,4 ... N；
S402, grid-connected converter is described with total harmonic distortion factor THD [R] to the filter effect letter of grid entry point voltage harmonic
Number；
Under the collective effect of nonlinear-load and higher level's background harmonic voltage, the voltage of current transformer grid entry point generates abnormal
Becoming, the filter effect function of separate unit current transformer is denoted as THD [R (i)], specific formula is as follows:
Reach filter effect most preferably, that is, have:
min THD[R(i)]
In formula (5), H=fmax/f0Indicate the corresponding order of maximum compensation harmonic frequency；f0Indicate fundamental frequency；fmaxIt indicates
Maximum compensation harmonic frequency；V1Indicate fundametal compoment virtual value；VnIndicate harmonic component virtual value, i.e. expression each harmonic voltage
Amplitude；
When more current transformers work under active power quality controlling state, the total harmonic distortion factor of each node is added
It is averaged, obtains the filter effect function of more current transformers:
THD [R]={ THD [R1(i)]+THD[R2(i)]+…+THD[Rk(i)]}/k (6)
K indicates the quantity of grid node in formula；Reach filter effect most preferably, then to each node in searching process
THD[Rk(i)] it is added the smallest direction optimizing, keeps the filter function value THD [R] of particle i minimum；
S403, judge so that the filter effect function THD [R] of the step S402 more current transformers obtained is adaptation value function
The filter effect of each particle virtual resistance, the particle virtual resistance initial value that step S3 is randomized is as individual optimum virtual
Resistance initial value, while more each particle, filtering adaptive value THD [R] the smallest particle is virtual as population global optimum
Resistance initial value.
As a preferred technical solution, in step S402, following formula is can be used in the filter effect function of the more current transformers
(7) it is replaced, the proportion of total harmonic distortion factor is rationally arranged in the node importance administered according to current transformer, to coordinate more
The efficient operation of platform current transformer；
THD [R]=α1THD[R1(i)]+α2THD[R2(i)]+…+αkTHD[Rk(i)] (7)
Wherein Rk(i) k-th of node, the corresponding virtual resistance value of particle i are indicated；α1,α2,...,αkRespectively indicate each section
The importance accounting of point, and α1+α2+...+αk=1；Make harmonic wave control effect best, then makes filter effect functional value THD
[R] is minimum.
Step S5 as a preferred technical solution, specifically include the following steps:
S51, the individual and global optimum's virtual resistance initial value obtained according to step S4, and use speed iterative formula
(8) and virtual resistance iterative formula (9) carries out particle update；
VStep (i)=w × VStep (i)+c1×rand×(R(Gi)-R(i))+c2×rand×(R(P)-R(i)) (8)
R (i)=R (i)+VStep (i) (9)
Wherein w is population inertia weight；c1、c2For accelerated factor；R(Gi) indicate that the individual optimum virtual of each particle is electric
Resistance value or its initial value；R (P) indicates global optimum's virtual resistance value or its initial value；
If particle crosses the border, processing of crossing the border is carried out, specifically: as R (i) > RmaxOr VStep (i) > VmaxEven R
(i)=RmaxOr VStep (i)=Vmax；As R (i) <-RmaxOr VStep (i) <-VmaxEven R (i)=- RmaxOr VStep
(i)=- Vmax；
S52, each particle i, global optimum virtual resistance value particle P and individual optimum virtual resistance value particle G are calculatedi's
Adaptive value is filtered, is denoted as respectively: THD [R (i)], THD [R (P)] and THD [R (Gi)]；
S53, by the adaptive value of each particle i with the global optimum virtual resistance value particle P on position adaptive value into
Row compares, if THD [R (i)] < THD [R (P)], is assigned to global optimum's virtual resistance value for the virtual resistance value of particle i
Particle P, R (P)=R (i)；On the contrary, then the virtual resistance value R (P) of particle P is constant；
S54, the adaptive value of each particle is compared with the adaptive value of individual optimal particle, if THD [R (i)] <
THD[R(Gi)], then the virtual resistance value of particle i is assigned to individual optimum virtual resistance value particle Gi, R (Gi)=R (i)；Phase
Instead, then particle GiVirtual resistance value R (Gi) constant；
S55, t=t+1, if reaching maximum number of iterations tmax, then circulation is jumped out, step S51 is otherwise gone back to, is continued excellent
Change.
The present invention has the following advantages compared with the existing technology and effect:
1) more current transformer control method for coordinating of the invention are most preferably empty to grid-connected converter using particle swarm optimization algorithm
Quasi- resistance scans for, and passes through the reasonable setting to accelerated factor, inertia weight, search space and iteration speed, energy
Optimum virtual resistance value is approached with faster speed, higher precision；Simultaneously by particle initial position, iteration speed it is random
Setting, can effectively avoid and fall into local optimum, can be in the case where guaranteeing that current transformer normally issues active power, so that section
Point voltage harmonic level reaches minimum.
2) the method for the present invention is excellent by population when multiple-variable flow device works at the same time under active power quality controlling state
Change algorithm can each current transformer of coordinated control simultaneously, the proportion of adaptive value THD is rationally set according to node importance, coordinates more
The efficient operation of current transformer, it is relatively independent when solving multiple-variable flow device using linear search so that harmonic wave control effect is best,
More virtual harmonic wave resistance may adjust repeatedly, influence each other, the continuous optimizing of system, and search result can not stablize always, can not
Complete the problem of solving.
Detailed description of the invention
Fig. 1 is the more current transformer control method for coordinating flow charts based on particle swarm optimization algorithm of the present embodiment；
Fig. 2 is the circuit topology and working principle diagram of the grid-connected converter in the present embodiment；
Fig. 3 is that the power distribution network containing linear load, nonlinear-load and higher level's background harmonic voltage in the present embodiment is single-phase
Equivalent circuit diagram；
Fig. 4 is the best visual resistance search routine figure based on particle swarm optimization algorithm in the present embodiment；
Fig. 5 is the particle swarm optimization algorithm of the specific embodiment in the present embodiment as a result, including virtual resistance resistance value
Change waveform and the variation waveform of grid entry point voltage THD；
Fig. 6 is the multinode multiple-variable flow device operation schematic diagram in the present embodiment.
Specific embodiment
In order to which the purpose of the present invention, technical solution and advantage is more clearly understood, with reference to the accompanying drawings and embodiments,
The present invention is further described in detail.It should be appreciated that described herein, the specific embodiments are only for explaining the present invention,
It is not limited to the present invention.
Embodiment
As shown in Figure 1, a kind of more current transformer control method for coordinating based on particle swarm optimization algorithm, best by searching for
Virtual resistance realizes the coordinated controls of more electric current devices, specifically include the following steps:
S1, the model for establishing current transformer, analyze and derive the transmission function of output unit；
S2, the harmonic frequency range for needing to inhibit is determined according to the transmission function, and set PI controller parameter, determine
For searching for the relevant parameter of the particle swarm optimization algorithm of virtual resistance value；
The virtual resistance value R (i) and renewal speed Vstep (i) of S3, random initializtion particle i；
S4, each harmonic voltage magnitude is obtained according to the corresponding virtual resistance value of different particles, and then construct grid-connected change
Device is flowed to the filter effect function of grid entry point voltage harmonic, and the filter effect function is retouched with total harmonic distortion factor THD [R]
It states；It is the filter effect for adapting to value function to judge each particle virtual resistance with the total harmonic distortion factor THD [R]；It will step
The particle virtual resistance initial value of rapid S3 randomization is optimal by the individual of different particles as individual optimum virtual resistance initial value
The filtering adaptive value of virtual resistance initial value is compared, and obtains population global optimum virtual resistance initial value；
S5, particle update is carried out according to individual and global optimum's virtual resistance initial value and iterative formula, then calculated
And haggle over updated each particle i, individual optimum virtual resistance value particle GiWith the filter of global optimum virtual resistance value particle P
Individual and global optimum's virtual resistance value are carried out assignment update, then iterate to satisfaction according to comparison result by wave adaptive value
The condition of convergence reaches maximum number of iterations, most using global optimum's virtual resistance value after iteration as each current transformer
Excellent virtual resistance value；
S6, using global optimum's virtual resistance value after step S5 iteration as the optimum virtual resistance of each current transformer
Value, control current transformer export corresponding harmonic compensation current so that the optimum virtual resistance value R (i) of each current transformer with from grid-connected
Point sees the harmonic impedance Z to systemh=Rh+jXhModulus value difference it is equal, wherein RhExpression system Equivalent Harmonic resistance, XhIt indicates
System Equivalent Harmonic reactance, j indicate imaginary unit, and subscript h indicates h subharmonic, by circuit theory it is found that at this time inside and outside harmonic source
Hinder equal, current transformer absorption harmonic power maximum, to realize the control of more converter harmonic voltage.
As shown in Fig. 2, the circuit topology and working principle diagram of the grid-connected converter of the present embodiment, distributed DC power electricity
Pressure exports corresponding watt current reference signal by DC voltage control ring output boost circuit modulated signalTo be
DC side provides DC capacitor voltage that is stable, being available for inversion, and sampling grid entry point voltage in exchange side does fast Fourier
Change (FFT), obtains compensated low-order harmonic voltage value UhabcAnd filtering adaptive value THD, by judging grid entry point voltage
Filtering adaptive value THD with control particle swarm optimization algorithm to virtual resistance value R (i) carry out optimizing, output harmonic wave current reference
SignalSampled output current i2With current reference signalThe sum of obtain current error signal as difference and controlled through PI
The SVPWM of device and three-level current transformer modulates to obtain the control signal S of IGBTa、Sb、Sc, thus output and current reference signal
Corresponding current waveform, output filter use LCL circuit, stablize output in guarantee fundamental wave and the low-order harmonic compensated
Higher hamonic wave caused by cut-offfing because of IGBT high frequency can be effectively filtered out simultaneously.
Carry out the technical solution that the present invention will be described in detail below.
Step S1 establishes the model of current transformer, analyzes and derive the transmission function of output unit, specifically includes following steps
It is rapid:
S101, the circuit model for establishing distributed current transformer: it as shown in Figure 2, using LCL filter circuit, specifically includes
First inductance L1, the first inductance parasitic resistance R1, the second inductance L2, the second inductance parasitic resistance R2, capacitor C and capacitive parasitic electricity
Hinder RC；The first inductance L1Connect the first inductance parasitic resistance R1；The second inductance L2Connect the second inductance parasitic resistance R2；
The capacitor C connection capacitive parasitic resistance RC, the first inductance parasitic resistance R1Connect the second inductance parasitic resistance R2And capacitor
Dead resistance RC；
S102, the output-transfer function that current transformer is derived according to the circuit model of distributed current transformer, specifically: according to step
The circuit model of rapid S101 distribution current transformer, when doing Simplified analysis, by the first inductance parasitic resistance R1It is posted with the second inductance
Raw resistance R2Ignore, obtains from inversion bridge voltage UinvElectric current i is exported to grid side2Transmission function, be denoted as GLCL(s), specific public
Formula are as follows:
Wherein, s indicates complex parameter；i2(s) output electric current is indicated；vinv(s) current transformer output voltage is indicated；
The parameter of LCL filter circuit is L1=0.74mH, C=6.6 μ F, L2=55 μ H, therefore the resonance of output-transfer function
FrequencyWhen frequency is less than resonance frequency, gain is higher,
When frequency is greater than resonance frequency, gain reduction is very fast, therefore the filter circuit can retain the output of low-frequency harmonics compensation and can have
Effect inhibits high-frequency harmonic, can be used for exporting low-order harmonic and inhibits simultaneously to higher hamonic wave.
Step S2 determines the harmonic frequency range for needing to inhibit according to the transmission function, and sets corresponding PI control
Device parameter determines the relevant parameter for searching for the particle swarm optimization algorithm of virtual resistance value；Specifically include the following steps:
S201, determine the harmonic frequency range for needing to inhibit: the maximum of the current transformer of setting device for harmonic abatement functions is mended
Repay harmonic frequency fmax, the maximum compensation harmonic frequency fmaxLess than resonance frequency fres, and set according to compensation range；This reality
It applies example to compensate to 13 subharmonic, then sets fmax=13f0, f0For fundamental frequency (50Hz), N is the multiple of odd number and non-3, i.e., 5,
7,11,13……；fmax<fres；
S202, current inner loop are controlled using PI, and the PI parameter of respectively specific subharmonic is configured, specifically, this reality
Apply a Proportional coefficient K of Set scale control PP=4, the integral coefficient K of integration control II=20, it is rotated to realize at each time
Zero steady state error control under coordinate system；
S203, it utilizes particle swarm optimization algorithm: determining the scale and dimension of population according to current transformer quantity, work as separate unit
When current transformer is run, virtual resistance value is an one-dimensional parameter；When more current transformer operations, by the dimension for increasing virtual resistance value
The efficient operation of number more current transformers of tunable, realizes effective inhibition of node harmonic voltage；
S204, the relevant parameter for determining particle swarm optimization algorithm, the relevant parameter include: accelerated factor c1With c2, grain
The initial value w of subgroup inertia weightmaxWith end value wmin, maximum number of iterations tmax, greatest iteration speed vmaxWith minimum iteration
Speed vminAnd the upper limit R in virtual resistance value optimization sectionmaxWith lower limit Rmin；
In the present embodiment, the accelerated factor c1And c21.85 and 2.0 are set to, particle swarm optimization algorithm has at this time
Faster speed of searching optimization and higher stability；
The population inertia weight uses dynamic inertia weight coefficient, linearly passs with the increase of the number of iterations
Subtract, the formula being related to is as follows:
Wherein wmaxFor the initial value of population inertia weight；wminFor the end value of population inertia weight；T is current changes
Generation number；In the present embodiment, wmaxWith wmin0.9 and 0.4 are taken respectively, it is ensured that algorithm can rapidly search out the overall situation most when originating
Excellent region, algorithm later period fast convergence near minimum value；
In the present embodiment, the maximum number of iterations tmaxIt can be set according to required adjustment time, by t in the present embodimentmax
It is set as 16 times；
To accelerate algorithm the convergence speed, the region of search can not be excessive or too small, by one phase equivalent circuit figure (such as Fig. 3 institute
Show) it can estimate virtual resistance value substantially section, the upper limit (R in setting virtual resistance value optimization sectionmax=5) with lower limit (Rmin=
0.01), further according to vmax=Rmax-RminDetermine maximum update speed (Vstepmax=5), by vmin=-vmaxObtain minimum update speed
Spend (Vstepmin=-5).
Step S3, the virtual resistance value R (i) and renewal speed Vstep (i) of random initializtion particle i, especially by as follows
Two formula are completed:
R (i)=rand × (Rmax-Rmin)+Rmin (3)
Vstep (i)=rand × (vmax-vmin)+vmin (4)
In formula (3) and formula (4), rand is the random number within 0~1；Virtual resistance R (i) is generated by random number.Work as grain
When cuckoo mould is enough, particle is dispersed throughout full search control, it is ensured that optimum results are global optimum's virtual resistance value.In addition, empty
When the value difference of quasi- resistance R (i) is less than 0.01, the difference of total harmonic distortion factor is minimum negligible, therefore can will search
Rope spatial discretization only retains two-decimal to the value of R (i), algorithm is avoided to search for repeatedly near some value, humorous in guarantee
While wave inhibitory effect, search process is further simplified, improves the renewal speed of virtual resistance.
Step S4, each harmonic voltage magnitude is obtained according to the corresponding virtual resistance value of different particles, and then is constructed simultaneously
Net current transformer to the filter effect function of grid entry point voltage harmonic, the filter effect function with total harmonic distortion factor THD [R] come
Description；It is the filter effect for adapting to value function to judge each particle virtual resistance with the total harmonic distortion factor THD [R]；It will
The particle virtual resistance initial value of step S3 randomization is as individual optimum virtual resistance initial value, most by the individual of different particles
The filtering adaptive value of excellent virtual resistance initial value is compared, and obtains population global optimum virtual resistance initial value；
S401, grid entry point voltage waveform is obtained under the corresponding virtual resistance value control of different particles, to grid entry point voltage
Fast Fourier Transform (FFT) is done, each harmonic voltage magnitude V is obtainedn, n expression n-th harmonic, n=2,3,4 ...；
S402, grid-connected converter is described with total harmonic distortion factor THD [R] to the filter effect letter of grid entry point voltage harmonic
Number；
Under the collective effect of nonlinear-load and higher level's background harmonic voltage, the voltage of current transformer grid entry point generates abnormal
Becoming, the filter effect function of separate unit current transformer is denoted as THD [R (i)], specific formula is as follows:
Reach filter effect most preferably, that is, have:
min THD[R(i)]
In formula (5), H=fmax/f0Indicate the corresponding order of maximum compensation harmonic frequency；f0Indicate fundamental frequency；fmaxIt indicates
Maximum compensation harmonic frequency；V1Indicate fundametal compoment virtual value；VnIndicate harmonic component virtual value, i.e. expression each harmonic voltage
Amplitude；
When more current transformers work under active power quality controlling state, the total harmonic distortion factor of each node is added
It is averaged, obtains the filter effect function of more current transformers:
THD (R)={ THD [R1(i)]+THD[R2(i)]+…+THD[Rk(i)]}/k (6)
K indicates interstitial content in formula；The quantity of current transformer is by population virtual resistance Rk(i) dimension embodies；Make to filter
Wave effect reaches most preferably, then to the THD [R of each node in searching processk(i)] it is added the smallest direction optimizing, makes particle i's
Filter function value THD [R] is minimum；
In the present embodiment, the filter effect function of the more current transformers can also be used following formula (7) and be replaced, according to
The proportion of total harmonic distortion factor is rationally arranged in the node importance that current transformer is administered, to coordinate the efficient fortune of more current transformers
Row；
THD [R]=α1THD[R1(i)]+α2THD[R2(i)]+…+αkTHD[Rk(i)] (7)
Wherein Rk(i) k-th of node, the corresponding virtual resistance value of particle i are indicated；α1,α2,...,αkRespectively indicate each section
The importance accounting of point, and α1+α2+...+αk=1；Make harmonic wave control effect best, then makes filter effect functional value THD
[R] is minimum.
S403, judge so that the filter effect function THD [R] of the step S402 more current transformers obtained is adaptation value function
The filter effect of each particle virtual resistance, the particle virtual resistance initial value that step S3 is randomized is as individual optimum virtual
Resistance initial value, while more each particle, filtering adaptive value THD [R] the smallest particle is virtual as population global optimum
Resistance initial value.
Step S5, particle update is carried out according to renewal speed iterative formula and virtual resistance iterative formula, while calculated simultaneously
The adaptive value for haggling over each particle i, global optimum virtual resistance value particle P and individual optimum virtual resistance value particle G, according to
Global and individual optimum virtual resistance value is carried out assignment update by comparison result, then is iterated to meeting the condition of convergence or reach
To maximum number of iterations, so that it is determined that the optimum virtual resistance value of each current transformer, to realize the coordinated control of each current transformer；
As shown in figure 4, specifically include the following steps:
S51, the individual and global optimum's virtual resistance initial value obtained according to step S4, and use speed iterative formula
(8) and virtual resistance iterative formula (9) carries out particle update；
VStep (i)=w × VStep (i)+c1×rand×(R(Gi)-R(i))+c2×rand×(R(P)-R(i)) (8)
R (i)=R (i)+VStep (i) (9)
Wherein w is population inertia weight；c1、c2For accelerated factor；R(Gi) indicate that the individual optimum virtual of each particle is electric
Resistance value or its initial value；R (P) indicates global optimum's virtual resistance value or its initial value；
If particle crosses the border, processing of crossing the border is carried out, specifically: as R (i) > RmaxOr VStep (i) > VmaxEven R
(i)=RmaxOr VStep (i)=Vmax；As R (i) <-RmaxOr VStep (i) <-VmaxEven R (i)=- RmaxOr VStep
(i)=- Vmax；
S52, each particle i, global optimum virtual resistance value particle P and individual optimum virtual resistance value particle G are calculatedi's
Adaptive value is filtered, is denoted as respectively: THD [R (i)], THD [R (P)] and THD [R (Gi)]；
S53, by the adaptive value of each particle i with the global optimum virtual resistance value particle P on position adaptive value into
Row compares, if THD [R (i)] < THD [R (P)], is assigned to global optimum's virtual resistance value for the virtual resistance value of particle i
Particle P, R (P)=R (i)；On the contrary, then the virtual resistance value R (P) of particle P is constant；
S54, the adaptive value of each particle is compared with the adaptive value of individual optimal particle, if THD [R (i)] <
THD[R(Gi)], then the virtual resistance value of particle i is assigned to individual optimum virtual resistance value particle Gi, R (Gi)=R (i)；Phase
Instead, then particle GiVirtual resistance value R (Gi) constant；
S55, t=t+1, if reaching maximum number of iterations tmax, then circulation is jumped out, step S51 is otherwise gone back to, is continued excellent
Change.
The case where the present embodiment works to separate unit current transformer has carried out simulation analysis, and result is as shown in figure 5, virtual resistance
R is finally stable -0.6 by particle swarm optimization algorithm, and grid entry point voltage THD is reduced and stablized 0.8%, therefore base of the invention
Grid entry point harmonic voltage can be effectively suppressed in more current transformer control method for coordinating of swarm of particles optimization algorithm, reduce grid entry point
Voltage THD.When multinode multiple-variable flow device works in the mode as shown in Fig. 6, then filter effect function THD (R) is according to reality
Demand utilization formula (6) or formula (7) are iterated, other steps are constant.
Method of the invention inhibits node voltage harmonic wave using virtual resistance method, can using particle swarm optimization algorithm
More current transformers of coordinated control carry out search quickly, accurate, global, control current transformer output to the size of virtual harmonic wave resistance
Corresponding harmonic compensation current, so that each current transformer each harmonic virtual resistance value and the modulus value of system each harmonic impedance are distinguished
It is equal, to realize the optimal inhibition effect of multinode harmonic voltage.The control algolithm is by particle swarm optimization algorithm to more
The virtual harmonic wave resistance of current transformer carries out optimizing, solves traditional virtual harmonic wave resistance automatic adjustment method based on linear search and exists
Under more current transformer operating conditions, each current transformer independence optimizing influences each other, existing search speed is slow, fall into local optimum,
It is difficult to the problem of coordinating to make more current transformers to work in best visual resistance.
The embodiments described above only express several embodiments of the present invention, and the description thereof is more specific and detailed, but simultaneously
Limitations on the scope of the patent of the present invention therefore cannot be interpreted as.It should be pointed out that for those of ordinary skill in the art
For, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to guarantor of the invention
Protect range.Therefore, the scope of protection of the patent of the present invention should subject to the claims.
Claims (10)
1. a kind of more current transformer control method for coordinating based on particle swarm optimization algorithm, by search best visual resistance come real
The coordinated control of now more electric current devices, which is characterized in that this method includes the following steps:
S1, the model for establishing current transformer, analyze and derive the transmission function of output unit；
S2, the harmonic frequency range for needing to inhibit being determined according to the transmission function, and setting PI controller parameter, determination is used for
Search for the relevant parameter of the particle swarm optimization algorithm of virtual resistance value；
The virtual resistance value R (i) and renewal speed Vstep (i) of S3, random initializtion particle i；
S4, each harmonic voltage magnitude is obtained according to the corresponding virtual resistance value of different particles, and then construct grid-connected converter
To the filter effect function of grid entry point voltage harmonic, the filter effect function is described with total harmonic distortion factor THD [R]；With
The total harmonic distortion factor THD [R] is the filter effect for adapting to value function to judge each particle virtual resistance；By step S3 with
The particle virtual resistance initial value of machine is as individual optimum virtual resistance initial value, by the individual optimum virtual electricity of different particles
The filtering adaptive value of resistance initial value is compared, and obtains population global optimum virtual resistance initial value；
S5, particle update is carried out according to individual and global optimum's virtual resistance initial value and iterative formula, then calculates and counts
More updated each particle i, individual optimum virtual resistance value particle GiFiltering with global optimum virtual resistance value particle P is suitable
It should be worth, according to comparison result, individual and global optimum's virtual resistance value are subjected to assignment update, then iterate to satisfaction and restrain
Condition reaches maximum number of iterations, using global optimum's virtual resistance value after iteration as the optimal void of each current transformer
Quasi- resistance value；
S6, control current transformer export corresponding harmonic compensation current so that the optimum virtual resistance value R (i) of each current transformer with from
Grid entry point sees the harmonic impedance Z to systemhModulus value difference it is equal, subscript h indicate h subharmonic, by circuit theory it is found that at this time
Extrernal resistance is equal in harmonic source, and current transformer absorbs harmonic power maximum, to realize the control of more converter harmonic voltage.
2. the more current transformer control method for coordinating according to claim 1 based on particle swarm optimization algorithm, feature exist
In the step S1 includes the following steps:
S101, the circuit model for establishing distributed current transformer: LCL filter circuit is used, the first inductance (L is specifically included1), first
Inductance parasitic resistance (R1), the second inductance (L2), the second inductance parasitic resistance (R2), capacitor (C) and capacitive parasitic resistance (RC)；
First inductance (the L1) the first inductance parasitic resistance (R of connection1)；Second inductance (the L2) the second inductance parasitic resistance of connection
(R2)；The capacitor (C) connects capacitive parasitic resistance (RC), the first inductance parasitic resistance (R1) the second inductance parasitic of connection
Resistance (R2) and capacitive parasitic resistance (RC)；
S102, the output-transfer function that current transformer is derived according to the circuit model of distributed current transformer, specifically: according to step
The circuit model of S101 distribution current transformer, when doing Simplified analysis, by the first inductance parasitic resistance (R1) and the second inductance post
Raw resistance (R2) ignore, it obtains from inversion bridge voltage UinvElectric current i is exported to grid side2Transmission function, be denoted as GLCL(s), specifically
Formula are as follows:
Wherein, s indicates complex parameter；i2(s) output electric current is indicated；vinv(s) current transformer output voltage is indicated；
The parameter of LCL filter circuit is L1=0.74mH, C=6.6 μ F, L2=55 μ H, therefore the resonance frequency of output-transfer functionIt is less than resonance frequency in the frequency of output current of converter
When rate, gain is higher；When the frequency of output current of converter is greater than resonance frequency, gain reduction is very fast, therefore the filtered electrical
Road can retain the output of low-frequency harmonics compensation and can effectively inhibit high-frequency harmonic, and it is humorous to high order simultaneously to can be used for exporting low-order harmonic
Wave is inhibited.
3. the more current transformer control method for coordinating according to claim 1 based on particle swarm optimization algorithm, feature exist
In, step S2, specifically include the following steps:
S201, determine the harmonic frequency range for needing to inhibit: the maximum compensation of the current transformer of setting device for harmonic abatement functions is humorous
Wave frequency rate fmax；The maximum compensation harmonic frequency fmaxLess than the resonance frequency f of transmission functionres, and set according to compensation range
It is fixed；When needing compensation to arrive n times harmonic wave, f is setmax=Nf0, f0For fundamental frequency 50Hz, N is the multiple of odd number and non-3, i.e., 5,
7,11,13……；fmax<fres；
S202, current inner loop are controlled using PI, and the PI parameter of respectively specific subharmonic is configured, and are realized and are sat in each rotation
Zero steady state error control under mark system；The PI parameter includes the proportionality coefficient of ratio control P and the integral coefficient of integration control；
S203, it utilizes particle swarm optimization algorithm: the scale and dimension of population is determined according to current transformer quantity, when separate unit unsteady flow
When device is run, virtual resistance value is an one-dimensional parameter；When more current transformer operations, the dimension by increasing virtual resistance value can
Coordinate the efficient operation of more current transformers, realizes effective inhibition of node harmonic voltage；
S204, the relevant parameter for determining particle swarm optimization algorithm, the relevant parameter include: accelerated factor c1With c2, population it is used
The initial value w of property weightmaxWith end value wmin, maximum number of iterations tmax, greatest iteration speed vmaxWith minimum iteration speed
vminAnd the upper limit R in virtual resistance value optimization sectionmaxWith lower limit Rmin。
4. the more current transformer control method for coordinating according to claim 3 based on particle swarm optimization algorithm, feature exist
In in step S204, population inertia weight uses dynamic inertia weight coefficient, linearly passs with the increase of the number of iterations
Subtract, the formula being related to is as follows:
Wherein wmaxFor the initial value of population inertia weight；wminFor the end value of population inertia weight；T is current iteration time
Number.
5. the more current transformer control method for coordinating according to claim 3 based on particle swarm optimization algorithm, feature exist
In in step S204, by one phase equivalent circuit figure estimation virtual resistance value section, the upper limit in setting virtual resistance value optimization section
RmaxWith lower limit Rmin, further according to formula vmax=Rmax-RminMaximum update speed is determined, by vmin=-vmaxObtain minimum update speed
Degree.
6. the more current transformer control method for coordinating according to claim 1 based on particle swarm optimization algorithm, feature exist
In detailed process is as follows by step S3:
Virtual resistance value and the renewal speed initialization of particle i is completed by following two formula respectively:
R (i)=rand × (Rmax-Rmin)+Rmin (3)
Vstep (i)=rand × (vmax-vmin)+vmin (4)
In formula (3) and formula (4), rand is the random number within 0~1；Particle virtual resistance R (i) is generated by random number.
7. the more current transformer control method for coordinating according to claim 6 based on particle swarm optimization algorithm, feature exist
In only retaining two-decimal to the value of particle virtual resistance R (i) for search space discretization.
8. the more current transformer control method for coordinating according to claim 1 based on particle swarm optimization algorithm, feature exist
In, step S4, specifically include the following steps:
S401, grid entry point voltage waveform is obtained under the corresponding virtual resistance value control of different particles, grid entry point voltage is done fastly
Fast Fourier transformation obtains each harmonic voltage magnitude Vn, n expression n-th harmonic, n=2,3,4 ... N；
S402, grid-connected converter is described with total harmonic distortion factor THD [R] to the filter effect function of grid entry point voltage harmonic；
Under the collective effect of nonlinear-load and higher level's background harmonic voltage, the voltage of current transformer grid entry point generates distortion, single
The filter effect function of platform current transformer is denoted as THD [R (i)], specific formula is as follows:
Reach filter effect most preferably, that is, have:
minTHD[R(i)]
In formula (5), H=fmax/f0Indicate the corresponding order of maximum compensation harmonic frequency；f0Indicate fundamental frequency；fmaxIndicate maximum
Compensation harmonic frequency；V1Indicate fundametal compoment virtual value；VnIndicate harmonic component virtual value, i.e. expression each harmonic voltage magnitude；
When more current transformers work under active power quality controlling state, the total harmonic distortion factor addition of each node is made even
, the filter effect function of more current transformers is obtained:
THD [R]={ THD [R1(i)]+THD[R2(i)]+…+THD[Rk(i)]}/k (6)
K indicates the quantity of grid node in formula；Reach filter effect most preferably, then to the THD of each node in searching process
[Rk(i)] it is added the smallest direction optimizing, keeps the filter function value THD [R] of particle i minimum；
S403, with step S402 obtain more current transformers filter effect function THD [R] be adapt to value function it is each to judge
The filter effect of particle virtual resistance, the particle virtual resistance initial value that step S3 is randomized is as individual optimum virtual resistance
Initial value, while more each particle, using filtering adaptive value THD [R] the smallest particle as population global optimum virtual resistance
Initial value.
9. the more current transformer control method for coordinating according to claim 8 based on particle swarm optimization algorithm, feature exist
In in step S402, the filter effect function of the more current transformers can be used following formula (7) and be replaced, according to current transformer institute
The proportion of total harmonic distortion factor is rationally arranged in the node importance of improvement, to coordinate the efficient operation of more current transformers；
THD [R]=α1THD[R1(i)]+α2THD[R2(i)]+…+αkTHD[Rk(i)] (7)
Wherein Rk(i) k-th of node, the corresponding virtual resistance value of particle i are indicated；α1,α2,...,αkRespectively indicate the weight of each node
The property wanted accounting, and α1+α2+...+αk=1；Make harmonic wave control effect best, then makes filter effect functional value THD [R] most
It is small.
10. the more current transformer control method for coordinating according to claim 1 based on particle swarm optimization algorithm, feature exist
In, step S5, specifically include the following steps:
S51, the individual and global optimum's virtual resistance initial value obtained according to step S4, and using speed iterative formula (8) and
Virtual resistance iterative formula (9) carries out particle update；
VStep (i)=w × VStep (i)+c1×rand×(R(Gi)-R(i))+c2×rand×(R(P)-R(i)) (8)
R (i)=R (i)+VStep (i) (9)
Wherein w is population inertia weight；c1、c2For accelerated factor；R(Gi) indicate the individual optimum virtual resistance value of each particle
Or its initial value；R (P) indicates global optimum's virtual resistance value or its initial value；
If particle crosses the border, processing of crossing the border is carried out, specifically: as R (i) > RmaxOr VStep (i) > VmaxEven R (i)
=RmaxOr VStep (i)=Vmax；As R (i) <-RmaxOr VStep (i) <-VmaxEven R (i)=- RmaxOr VStep (i)
=-Vmax；
S52, each particle i, global optimum virtual resistance value particle P and individual optimum virtual resistance value particle G are calculatediFiltering
Adaptive value is denoted as respectively: THD [R (i)], THD [R (P)] and THD [R (Gi)]；
S53, the adaptive value of each particle i and the adaptive value of the global optimum virtual resistance value particle P on same position are compared
Compared with if THD [R (i)] < THD [R (P)], the virtual resistance value of particle i is assigned to global optimum's virtual resistance value particle
P, R (P)=R (i)；On the contrary, then the virtual resistance value R (P) of particle P is constant；
S54, the adaptive value of each particle is compared with the adaptive value of individual optimal particle, if THD [R (i)] < THD [R
(Gi)], then the virtual resistance value of particle i is assigned to individual optimum virtual resistance value particle Gi, R (Gi)=R (i)；On the contrary, then
Particle GiVirtual resistance value R (Gi) constant；
S55, t=t+1, if reaching maximum number of iterations tmax, then circulation is jumped out, step S51 is otherwise gone back to, continues to optimize.
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