CN109327031A - Directly driven wind-powered multi-computer system power association control method and system based on battery energy storage - Google Patents
Directly driven wind-powered multi-computer system power association control method and system based on battery energy storage Download PDFInfo
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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
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
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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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
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- H02J3/386—
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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
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
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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
- Y02E40/10—Flexible AC transmission systems [FACTS]
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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
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
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Abstract
The directly driven wind-powered multi-computer system power association control method and system based on battery energy storage that the invention discloses a kind of, the present invention uses inside and outside two power control layers, wherein: external power control layer is made of a dual fuzzy controller and one based on the low-pass first order filter for smoothing out time constant, external power control layer can determine the grid-connected average active power reference value of wind power plant, this reference value output power total with a wind-powered electricity generation group of planes is compared the reference charge/discharge performance number that battery energy storage system can be obtained.Internal power control layer is made of an internal layer fuzzy controller and a power distribution controller, and internal power control layer can determine the charge/discharge value and power reference of each battery energy storage unit respectively.The present invention is embedded in corresponding battery energy storage unit control system, it can be achieved that while smooth wind power power swing, moreover it is possible to avoid the occurrence of each battery energy storage unit and overcharge or the situation of deep discharge, and change towards suitable state-of-charge.
Description
Technical field
The present invention relates to the wind power engineering technologies of electric system, and in particular to a kind of straight wind dispelling based on battery energy storage
Electric multi-computer system power association control method and system.
Background technique
Wind energy resources have fluctuation, and wind power output is caused also to have fluctuation.If by a large amount of wind power integration power grids, it will
The negative effect certain to generations such as the power quality of power grid, voltage stabilization and dispatchings of power netwoks.Therefore, it configures in systems
The energy storage device of certain capacity will play the power swing of smooth wind power, improve the stability and electric energy matter of wind-electricity integration operation
Amount, and the low voltage ride-through capability of wind power system is improved to a certain extent.For the technical performance of energy-storage system, hold
Amount be arranged to it is bigger, will be better to the smooth effect of wind power fluctuation, but this also increase simultaneously the investment of system at
This, cannot meet cost-effectiveness requirement well.Therefore, for the energy-storage system of certain capacity, how by the excellent of its own
Change control, to improve its technical performance in wind power system, it has also become problem in the urgent need to address at present.
The prior art has carried out relevant analysis for the Optimal Control Problem of the energy-storage system of smooth wind power power swing
And research, purpose are all to make energy-storage system while smooth wind power power swing, moreover it is possible to avoid the occurrence of and overcharge or deep
The situation of degree electric discharge occurs.Such as in terms of the Optimal Control Strategy research of wind-powered electricity generation/energy storage one-of-a-kind system, certain prior art root
According to the state-of-charge of super capacitor energy-storage system, certain multiple is zoomed in or out, to grid-connected value and power reference correspondingly with this
To reach the control to super capacitor energy-storage system state-of-charge；Certain prior art proposes a kind of based on fuzzy logic respectively
The control strategy of algorithm come correct energy-storage system refer to charge/discharge power size, thus realize to energy-storage system state-of-charge
Optimal control.Certain prior art installs ungrouped battery energy storage system in wind power plant exit concentratedly, proposes respectively
A kind of charge state feedback control strategy, to realize the optimal control to battery energy storage system entirety state-of-charge.Certain is existing
Technology installs the battery energy storage system of grouping in wind power plant exit concentratedly, and proposes a kind of mixed based on particle swarm algorithm-
The double-deck coordination control strategy of integer Novel Algorithm is closed, to realize the optimization to every group of battery energy storage unit state-of-charge
Control.The super capacitor energy-storage system dispersion of grouping is installed in each wind power generating set by certain prior art, proposes one kind
Multimachine coordination control strategy, while realizing the constant power output at times of wind power plant, moreover it is possible to effectively adjust every group of super electricity
Hold the state-of-charge of energy-storage units.But for directly driven wind-powered/battery energy storage multi-computer system, how to realize in smooth wind power function
Rate fluctuation, moreover it is possible to avoid the occurrence of each battery energy storage unit and overcharge or the situation of deep discharge and towards suitable charged
State transformation, is still a key technical problem urgently to be resolved.
Summary of the invention
The technical problem to be solved in the present invention: it in view of the above problems in the prior art, provides a kind of based on battery energy storage
Method and system are controlled in directly driven wind-powered multi-computer system power association, and the present invention can realize while smooth wind power power swing,
Can also make each battery energy storage unit avoid the occurrence of overcharge or the situation of deep discharge and towards suitable state-of-charge turn
Become, and there is stronger adaptability and robustness for wind-powered electricity generation prediction power and its practical power deviation.
In order to solve the above-mentioned technical problem, the technical solution adopted by the present invention are as follows:
A kind of directly driven wind-powered multi-computer system power association prosecutor method based on battery energy storage, implementation steps include:
1) the total prediction output power P of all wind energy conversion systems is calculatedFIn the deviation power △ P of two period of front and back；According to deviation
What power △ P determined low-pass first order filter smooths out time constant TB；By the total output power P of all wind energy conversion systemsGInput institute
It states low-pass first order filter and obtains the reference value P of wind farm grid-connected average active powerT0 *；
2) by the reference value P of wind farm grid-connected average active powerT0 *The output power P total with all wind energy conversion systemsGCompare,
Obtain the total reference output power P of battery energy storage system* BESS；
3) the reference output power P total according to battery energy storage system* BESSSize determine participate in charge/discharge battery energy storage list
The number N of member, and the reference output power P for combining battery energy storage system total* BESSAnd the reality of all M battery energy storage units
When state-of-charge SOCM×1=[SOCBESS-1,SOCBESS-2,…SOCBESS-M]TAll M battery energy storage units are obtained to join accordingly
Examine output power value PM×1=[PBESS-1,PBESS-2,…PBESS-M]T；As N > 0, then the lesser N number of battery of state-of-charge is selected
Energy-storage units charge, and charge power size is ︱ P* BESS︱/N；As N < 0, then select state-of-charge biggish N number of
Battery energy storage unit discharges, and discharge power size is ︱ P* BESS︱/N.
Preferably, filter time constant T is determined according to deviation power △ P in step 1)BDetailed step include:
1.1) deviation power △ P obtains battery energy storage system in the average charged shape of kth time period through preposition fuzzy controller
State reference value SOC* mean(k)；
1.2) SOC is calculated* mean(k)With its state-of-charge SOC that is averaged in real timemean(k)Deviation △ SOCmean(k)；
1.3) by deviation △ SOCmean(k), the real-time charging and discharging state CS of battery energy storage system it is true through postposition fuzzy controller
Surely time constant T is smoothed outB。
Preferably, the preposition fuzzy controller in step 1.1) is single-input-single-output structure；Input is deviation power △
P, basic domain are [- 1pu, 1pu], and wherein pu indicates per unit value, and obscuring domain is { -3, -2, -1,0 ,+1 ,+2 ,+3 }, right
The fuzzy subset answered is { NB, NM, NS, ZO, PS, PM, PB }, respectively indicates two period consensus forecast function before and after all wind energy conversion systems
The deviation of rate is { negative big, to bear, bear small, zero, just small, center is honest }；Output is battery energy storage system in the flat of kth time period
Equal state-of-charge reference value SOC* mean(k), basic domain is [0,100%], and obscuring domain is { 0,1,2,3,4,5,6 }, right
The fuzzy subset answered is { VS, S, SM, M, BM, B, VB }, respectively indicates the be averaged reference value of state-of-charge of battery energy storage system and is
{ very little, small, smaller, moderate, larger, greatly, very greatly }, control rule for input fuzzy subset NB, NM, NS, ZO, PS, PM,
PB } and output fuzzy subset's sequence be { VB, B, BM, M, SM, S, VS } correspond.
Preferably, the postposition fuzzy controller in step 1.3) is the mono- two-dimensional structure exported of two inputs-；It inputs all the way and is
Deviation △ SOCmean(k), basic domain is [- 100%, 100%], and obscuring domain is { -3, -2, -1,0 ,+1 ,+2 ,+3 }, right
The fuzzy subset answered be { NB, NM, NS, ZO, PS, PM, PB }, respectively indicate present battery energy-storage system be averaged state-of-charge and
The deviation of its reference value is { negative big, to bear, bear small, zero, just small, center is honest }；Another way input is battery energy storage system
Real-time charging and discharging state CS, and indicate that battery energy storage system is in discharge condition with D, the value of CS is+1 under discharge condition；C
Indicate that battery energy storage system is in charged state, the value of CS is -1 under charged state；Output is to smooth out time constant TB,
Basic domain is [0s, 3500s], and obscuring domain is { 0,1,2,3,4,5,6 }, corresponding fuzzy subset be VS, S, SM, M,
BM, B, VB }, respectively indicate output time constant be it is minimum, it is small, it is less than normal, it is moderate, it is bigger than normal, greatly, greatly }；And control rule is
At discharge condition D, deviation △ SOCmean(k)Fuzzy subset be { NB, NM, NS, ZO, PS, PM, PB } and export fuzzy subset
Sequence { VS, S, SM, M, BM, B, VB } corresponds；At charged state C, deviation △ SOCmean(k)Fuzzy subset be NB,
NM, NS, ZO, PS, PM, PB } and output fuzzy subset's sequence { VB, B, BM, M, SM, S, VS } one-to-one correspondence.
Preferably, the transmission function of low-pass first order filter is 1/ (1+sT in step 1)B), wherein s is Laplce's calculation
Sub- volume, TBFor variable time constant.
Preferably, according to the reference output power P that battery energy storage system is total in step 3)* BESSSize determine participate in fill/
The number N of discharge battery energy-storage units specifically refers to the reference output power P that battery energy storage system is total* BESSInput internal layer mould
Fuzzy controllers obtain participating in the number N of charge/discharge battery energy storage unit.
Preferably, the layer fuzzy controller is the structure of single-input-single-output；Input is the total ginseng of battery energy storage system
Examine output power P* BESS, basic domain be [- 1pu, 1pu], wherein pu indicate per unit value, obscure domain be -3, -2, -1,
0 ,+1 ,+2 ,+3 }, corresponding fuzzy subset is { NB, NM, NS, ZO, PS, PM, PB }, and it is total to respectively indicate battery energy storage system
Reference output power is { negative big, to bear, bear small, zero, just small, center is honest }；Output is the battery energy storage for participating in charge/discharge
The number N of unit, basic domain are [- 25,25], and obscuring domain is { -3, -2, -1,0 ,+1 ,+2 ,+3 }, corresponding fuzzy
Subset is { NB, NM, NS, ZO, PS, PM, PB }, and respectively indicating and participating in the numerical value of charge/discharge battery energy storage unit is { to bear greatly, bear
In, bear it is small, zero, it is just small, center, it is honest；Control rule for input fuzzy subset { NB, NM, NS, ZO, PS, PM, PB } and
Fuzzy subset's sequence { PB, PM, PS, ZO, NS, NM, NB } of output.
The present invention also provides a kind of, and the directly driven wind-powered multi-computer system power based on battery energy storage assists control system, including computer
Equipment, computer equipment be programmed to perform the present invention is based on the directly driven wind-powered multi-computer system power of battery energy storage assist prosecutor method
The step of.
The present invention also provides a kind of, and the directly driven wind-powered multi-computer system power based on battery energy storage assists control system, comprising:
Outer layer coordinated control program unit, for calculating the total prediction output power P of all wind energy conversion systemsFIn two period of front and back
Deviation power △ P；Time constant T is smoothed out according to what deviation power △ P determined low-pass first order filterB；By all wind-force
The total output power P of machineGIt inputs the low-pass first order filter and obtains the reference value P of wind farm grid-connected average active powerT0 *；
Outer layer internal layer interactive program unit, for by the reference value P of wind farm grid-connected average active powerT0 *With all wind
The total output power P of power machineGCompare, obtains the total reference output power P of battery energy storage system* BESS；
Internal layer coordinated control program unit, for the reference output power P total according to battery energy storage system* BESSSize it is true
Surely the number N of charge/discharge battery energy storage unit, and the reference output power P for combining battery energy storage system total are participated in* BESSAnd
The real-time state-of-charge SOC of all M battery energy storage unitsM×1=[SOCBESS-1,SOCBESS-2,…SOCBESS-M]TOwned
The corresponding reference output power value P of M battery energy storage unitM×1=[PBESS-1,PBESS-2,…PBESS-M]T；As N > 0, then select
It selects the lesser N number of battery energy storage unit of state-of-charge to charge, charge power size is ︱ P* BESS︱/N；As N < 0,
The biggish N number of battery energy storage unit of state-of-charge is then selected to discharge, discharge power size is ︱ P* BESS︱/N.
Preferably, the outer layer coordinated control program unit includes:
Preposition fuzzy controller subroutine unit, for being obtained according to the deviation power △ P of input through preposition fuzzy control
Average state-of-charge reference value SOC of the battery energy storage system in kth time period* mean(k)；
Average charged drift gage operator program unit in real time, for calculating SOC* mean(k)With its state-of-charge that is averaged in real time
SOC mean(k)Deviation △ SOCmean(k)；
Postposition fuzzy controller subroutine unit is used for deviation △ SOCmean(k), battery energy storage system real-time charge and discharge
Electricity condition CS smooths out time constant T through postposition fuzzy control determinationB。
Compared to the prior art, the present invention has an advantage that the battery energy storage system for smooth wind power power swing
For system, the optimal control of its own state-of-charge is also that improve that its technical performance and economic performance to be considered important is asked
Topic controls the improper battery energy storage device that may result in and is in the presence of overcharging or deep discharge, this will seriously affect
The service life of energy storage device, while also decline its technical performance in wind power system.The present invention is combining wind-powered electricity generation short term power
On the basis of prediction and the monitoring of energy-storage system state-of-charge, a kind of base is proposed for directly driven wind-powered/battery energy storage multi-computer system
Prosecutor method is assisted in the directly driven wind-powered multi-computer system power of battery energy storage, which includes inside and outside two power
Control layer, wherein outer layer is used to control the grid-connected active power of entire wind power plant, and internal layer is then used to control each battery energy storage list
The charge/discharge power of member, makes it while smooth wind power power swing, moreover it is possible to avoid the occurrence of and overcharge or deep discharge
Situation, and change towards suitable state-of-charge, be embedded into corresponding wind-powered electricity generation single machine control system, realizing flat
While sliding wind power fluctuation, additionally it is possible to avoid the occurrence of each battery energy storage unit and overcharge or the situation of deep discharge
And change towards suitable state-of-charge, and there is stronger adaptability for wind-powered electricity generation prediction power and its practical power deviation
And robustness.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of directly driven wind-powered/battery energy storage multi-computer system in the embodiment of the present invention.
Fig. 2 is the basic principle schematic of present invention method.
Fig. 3 is that determination smooths out time constant T in the embodiment of the present inventionBSchematic illustration.
Fig. 4 is the prediction output power segmental averaging value that all wind energy conversion systems are total in the embodiment of the present invention.
Fig. 5 is the subordinating degree function of preposition fuzzy controller input/output variable in the embodiment of the present invention.
Fig. 6 is grid-connected value and power reference P in the embodiment of the present inventionT0 *With smoothing time constant TDVariation characteristic curve.
Fig. 7 is the input/output subordinating degree function of postposition fuzzy controller in the embodiment of the present invention.
Fig. 8 is the control block diagram of internal layer fuzzy controller in the embodiment of the present invention.
Fig. 9 is the input/output subordinating degree function of internal layer fuzzy controller in the embodiment of the present invention.
Figure 10 is the topological structure schematic diagram of each single machine wind power system in the embodiment of the present invention.
Figure 11 is the control block diagram of converter in the embodiment of the present invention.
Figure 12 is the control block diagram of bidirectional DC-DC converter in the embodiment of the present invention.
Figure 13~Figure 27 is the simulation result schematic diagram in the embodiment of the present invention, in which:
Figure 13 is to emulate the total prediction output power of obtained all wind energy conversion systems；
Figure 14 is to emulate the total prediction output power of obtained all wind energy conversion systems average value at times；
Figure 15 is that the obtained battery energy storage system of emulation is averaged state-of-charge reference value；
Figure 16 is to emulate the total real output of obtained all wind energy conversion systems；
Figure 17 be emulation obtain smooth out time constant；
Figure 18 is to emulate the total real output/wind farm grid-connected average active power of obtained all wind energy conversion systems；
Figure 19 is the synthesis output power for the battery energy storage system that emulation obtains；
Figure 20 is the average state-of-charge for the battery energy storage system that emulation obtains；
Figure 21 is the number of the battery energy storage unit for the participation charge and discharge that emulation obtains；
Figure 22 is the state-of-charge of the battery energy storage unit for the initial state-of-charge (85%) of maximum that emulation obtains；
Figure 23 is the output power of the battery energy storage unit for the initial state-of-charge (85%) of maximum that emulation obtains；
Figure 24 is the charging and discharging state of the battery energy storage unit for the initial state-of-charge (85%) of maximum that emulation obtains；
Figure 25 is the state-of-charge of the battery energy storage unit for the initial state-of-charge (65%) of minimum that emulation obtains；
Figure 26 is the output power of the battery energy storage unit for the initial state-of-charge (65%) of minimum that emulation obtains；
Figure 27 is the charging and discharging state of the battery energy storage unit for the initial state-of-charge (65%) of minimum that emulation obtains.
Figure 28~Figure 30 is in the embodiment of the present invention using the simulation result of system when traditional outer layer control strategy, in which:
Figure 28 is the wind farm grid-connected average active power that emulation obtains；
Figure 29 is the synthesis output power for the battery energy storage system that emulation obtains；
Figure 30 is the average state-of-charge for the battery energy storage system that emulation obtains.
Figure 31~Figure 34 is in the embodiment of the present invention using traditional outer layer control strategy, and time constant TDIt is when=200s
The simulation result of system, in which:
Figure 35 is to emulate the total real output/wind farm grid-connected average active power of obtained all wind energy conversion systems；
Figure 36 is the wind farm grid-connected average active power that emulation obtains；
Figure 37 is the synthesis output power for the battery energy storage system that emulation obtains；
Figure 38 is the average state-of-charge for the battery energy storage system that emulation obtains.
Specific embodiment
It hereafter will be by taking directly driven wind-powered/battery energy storage multi-computer system shown in Fig. 1 as an example, to the present invention is based on the straight of battery energy storage
Wind dispelling electricity multi-computer system power association control method and system are described in further detail.As shown in Figure 1, directly driven wind-powered/battery
Energy storage multi-computer system is converged by way of in parallel by each single machine wind power system, presents electric energy using step-up transformer
Enter power grid.Battery energy storage system is broken down into each battery energy storage unit B ESS-1~BESS-M, and dispersion is connected in each single machine wind
In electric system, it on the one hand can assist prosecutor method by the directly driven wind-powered multi-computer system power based on battery energy storage through this embodiment, make it
More smooth grid-connected active power can be exported；On the other hand the low voltage crossing of entire wind power system can also be improved simultaneously
Ability.Wind energy conversion system output voltage P in single machine wind power systemG-i, wind energy conversion system output voltage PG-iSuccessively by motor side converter,
The low-pressure side of the public step-up transformer of 20kV/110kV is converged into after grid side converter, 690V/20kV step-up transformer, it is single
BESS-i in machine wind power system is connected in parallel on the DC side of grid side transformer, wherein [1, M] i ∈, and M is single machine wind power system
Quantity.
Referring to Fig. 1, the grid-connected average active power P of wind power plantT0As shown in formula (1)；
In formula (1), PT0-i (i=1,2 ... M) is the grid-connected average active power of each single machine wind power system, and M is single machine wind
The quantity of electric system.
The total prediction output power P of all wind energy conversion systemsFAnd real output PGRespectively as shown in formula (2) and (3)；
In formula (2) and (3), PF-i, PG-iThe prediction output power and reality of wind energy conversion system in respectively each single machine wind power system
Border output power, M are the quantity of single machine wind power system.
The synthesis output power P of battery energy storage systemBESSAnd average state-of-charge SOCmeanRespectively such as formula (4) and (5) institute
Show；
In formula (4) and (5), PBESS-i, SOCBESS-iThe output work of battery energy storage unit in respectively each single machine wind power system
Rate and state-of-charge, M are the quantity of single machine wind power system.
As shown in Fig. 2, the implementation step of directly driven wind-powered multi-computer system power association prosecutor method of the present embodiment based on battery energy storage
Suddenly include:
1) the total prediction output power P of all wind energy conversion systems is calculatedFIn the deviation power △ P of two period of front and back；According to deviation
What power △ P determined low-pass first order filter smooths out time constant TB；By the total output power P of all wind energy conversion systemsGInput one
Rank low-pass filter obtains the reference value P of wind farm grid-connected average active powerT0 *；
2) by the reference value P of wind farm grid-connected average active powerT0 *The output power P total with all wind energy conversion systemsGCompare,
Obtain the total reference output power P of battery energy storage system* BESS；
3) the reference output power P total according to battery energy storage system* BESSSize determine participate in charge/discharge battery energy storage list
The number N of member, and the reference output power P for combining battery energy storage system total* BESSAnd the reality of all M battery energy storage units
When state-of-charge SOCM×1=[SOCBESS-1,SOCBESS-2,…SOCBESS-M]TAll M battery energy storage units are obtained to join accordingly
Examine output power value PM×1=[PBESS-1,PBESS-2,…PBESS-M]T；As N > 0, then the lesser N number of battery of state-of-charge is selected
Energy-storage units charge, and charge power size is ︱ P* BESS︱/N；As N < 0, then select state-of-charge biggish N number of
Battery energy storage unit discharges, and discharge power size is ︱ P* BESS︱/N.
Referring to fig. 2, in the present embodiment based on battery energy storage directly driven wind-powered multi-computer system power association control strategy mainly by
Outer layer control system and internal layer control system two parts are constituted, and outer layer control system is mainly used for being formed wind farm grid-connected
The reference value P of average active powerT0 *, its output power P total by all wind energy conversion systemsGIt is obtained by a low-pass first order filter
It arrives.Also, filter time constant TBBe it is variable, it will by the relevant featuring parameters of system pass through a dual mould
Fuzzy controllers obtain.Compared with the reference value of the wind farm grid-connected average active power output power total with all wind energy conversion systems
Obtain the total reference output power P of battery energy storage system* BESS.Internal layer control system is mainly used for forming each battery energy storage list
The reference output power P of member* BESS-i, it is by P* BESSIt is obtained through an internal layer fuzzy controller and power distribution controller.This reality
It is flat with wind-powered electricity generation prediction power and battery energy storage system based on directly driven wind-powered multi-computer system power association's prosecutor method of battery energy storage to apply example
Equal state-of-charge smooths out time constant as input, through the output of dual fuzzy controller accordingly, then to own in wind power plant
The gross output of wind energy conversion system is as input, through exporting wind power plant based on the low-pass first order filter for smoothing out time constant
Grid-connected average active power reference value.It is compared with the gross output of all wind energy conversion systems can be obtained battery energy storage system
Reference charge/discharge performance number.In internal power control layer, using the charge/discharge value and power reference of battery energy storage system as
Input accordingly exports the number for participating in the battery energy storage unit of charge/discharge through internal layer fuzzy controller, stores up in conjunction with each battery
The real-time state-of-charge of energy unit, the charge/discharge power reference of each battery energy storage unit is determined through power distribution controller respectively
Value, is embedded into corresponding wind-powered electricity generation single machine control system, it can be achieved that while smooth wind power power swing, moreover it is possible to make each
Battery energy storage unit, which avoids the occurrence of, to overcharge or the situation of deep discharge, and changes towards suitable state-of-charge.Emulation knot
Fruit demonstrates the correctness and validity of proposed control strategy.
As shown in figure 3, determining filter time constant T according to deviation power △ P in step 1)BDetailed step packet
It includes:
1.1) deviation power △ P obtains battery energy storage system in the average charged shape of kth time period through preposition fuzzy controller
State reference value SOC* mean(k)；
1.2) SOC is calculated* mean(k)With its state-of-charge SOC that is averaged in real timemean(k)Deviation △ SOCmean(k)；
1.3) by deviation △ SOCmean(k), the real-time charging and discharging state CS of battery energy storage system it is true through postposition fuzzy controller
Surely time constant T is smoothed outB。
It would be flattened out sliding time constant TBBe embedded in wind power plant control system in, then can real-time control wind power plant it is grid-connected average
Active-power PT0, and then control the synthesis charge/discharge power P of battery energy storage systemBESS, make it in smooth wind power power swing
While, additionally it is possible to it avoids the occurrence of and overcharges or the situation of deep discharge, and towards suitably averagely state-of-charge transformation.
Time series method or the intelligence side such as time series method and artificial neural network can be used in the power prediction of Wind turbines
Method combines to predict mean wind speed, and corresponding Wind turbines then are calculated according to the power characteristic of wind power generating set
Output power predicted value, and then obtain the total prediction output power P of all wind energy conversion systemsF；Fuzzy logic method, artificial can also be used
The intelligent algorithms such as neural network, using meteorological datas such as mean wind speed, wind directions as input quantity, directly prediction wind-force is sent out
Motor group output power.The present embodiment is by the short-term forecast power application of wind-powered electricity generation in the design of above-mentioned preposition fuzzy controller.
According to acquired short-term wind power prediction data, it is divided by equal periods, and find out the consensus forecast of day part
Power and two period of front and back average predicted power (Pmean(k),Pmean(k+1)) deviation △ P, in this, as preposition fuzzy control
The input of device, as shown in Figure 4.
Referring to Fig. 3, the effect of preposition fuzzy controller is according to the total prediction output power of all wind energy conversion systems in front and back two
The mean power (Pmean (k), Pmean (k+1)) of period determines that battery energy storage system is joined in the average state-of-charge of kth time period
Value SOC*mean (k) is examined, (k=1,2,3 ...).When average value of the total prediction output power of wind energy conversion system in+1 period of kth is compared
When kth time period increases, then battery energy storage is accordingly reduced in the average state-of-charge reference value of kth time period, makes it in kth time period
Change towards lower average state-of-charge, this will make battery energy storage system obtain larger charging that may be needed in the k+1 period
Volume space, so as to the power swing of smooth wind power to a greater extent.Conversely, the prediction output power total when wind energy conversion system
When the average value of+1 period of kth is reduced compared to kth time period, then battery energy storage system is increased accordingly in the average lotus of kth time period
Electricity condition reference value changes it towards higher state-of-charge in kth time period, this will make battery energy storage system in the k+1 period
Larger discharge capacity space that may be needed is obtained, to realize the smooth of k+1 period wind farm grid-connected power to a greater extent
Output.
In the present embodiment, the preposition fuzzy controller in step 1.1) is single-input-single-output structure；Input is deviation function
Rate △ P, basic domain be [- 1pu, 1pu], wherein pu indicate per unit value, obscure domain be -3, -2, -1,0 ,+1 ,+2 ,+
3 }, corresponding fuzzy subset is { NB, NM, NS, ZO, PS, PM, PB }, and two periods are average pre- before and after respectively indicating all wind energy conversion systems
The deviation of power scale is { negative big, to bear, bear small, zero, just small, center is honest }；Output is battery energy storage system in kth time period
Average state-of-charge reference value SOC* mean(k), basic domain be [0,100%], obscure domain be 0,1,2,3,4,5,
6 }, corresponding fuzzy subset is { VS, S, SM, M, BM, B, VB }, respectively indicates battery energy storage system and is averaged the ginseng of state-of-charge
Examining value is { very little, small, smaller, moderate, larger, greatly, very greatly }, control rule for input fuzzy subset NB, NM, NS, ZO,
PS, PM, PB } and output fuzzy subset's sequence be { VB, B, BM, M, SM, S, VS } correspond.
In the present embodiment, the input/output subordinating degree function of preposition fuzzy controller is all made of triangular membership functions, such as schemes
Shown in 5, de-fuzzy method is all made of existing gravity model appoach, and it is specific as shown in table 1 to control rule.
Table 1, preposition fuzzy controller rule list.
Under Traditional control strategy, wind farm grid-connected average active power reference value PT0 *It is the output work total by wind energy conversion system
Rate PGThrough low-pass first order filter, (time constant is definite value TD) obtain, shown in transmission function such as formula (6)；
In formula (6), s is Laplace operator, TDFor time constant.
Fig. 6 is the total output power P of all wind energy conversion systemsGWhen=30MW, wind farm grid-connected average active power reference value PT0 *
With low-pass first order filter time constant TDVariation characteristic curve graph.It will be appreciated from fig. 6 that time constant TDValue it is smaller, PT0 *
To Power Output for Wind Power Field PGTracking velocity it is faster, it is on the contrary then slower.
As shown in figure 3, the effect of postposition fuzzy controller is be averaged the in real time state-of-charge, phase according to battery energy storage system
The average state-of-charge reference value and charging and discharging state determination for answering the period smooth out time constant TB.Work as battery energy storage system
When averagely state-of-charge is higher compared to its reference value: if being in charged state (CS=-1), it may be assumed that PG>PT0, then export lesser
Smoothing time constant, this will make wind farm grid-connected average active power PT0The output power P total to wind energy conversion systemGTracking velocity
It becomes faster (assuming that wind farm grid-connected average active power PT0Its reference value P can be preferably fittedT0 *, i.e. PT0≈PT0 *), thus
The opposite size for reducing battery energy storage system charge power slows down the speed that its average state-of-charge rises, prevents battery energy storage
Overcharging occur in system；If being in discharge condition (CS=+1), it may be assumed that PG<PT0, then large time constant is exported, this
It will make wind farm grid-connected average active power PT0The output power P total to wind energy conversion systemGTracking velocity it is slack-off, so that opposite increase
The discharge power of big battery energy-storage system accelerates the reduction of its state-of-charge, is allowed to towards with reference to average state-of-charge SOC* mean
Variation.Vice versa, when battery energy storage system state-of-charge is lower compared to its reference value: if being in charged state, it may be assumed that PG>
PT0, then biggish smoothing time constant is exported；If being in discharge condition, it may be assumed that PG<PT0, then smaller time constant is exported.Work as electricity
When the deviation very little of pond energy-storage system state-of-charge and its reference value, then moderate time constant is exported, it so on the one hand can be with
Guarantee that battery energy storage system generates preferable smooth effect to wind power fluctuation, on the other hand can make battery energy storage system
Average state-of-charge keeps a kind of dynamic equilibrium with respect to its reference value.
In the present embodiment, the postposition fuzzy controller in step 1.3) is the mono- two-dimensional structure exported of two inputs-；It is defeated all the way
Enter for deviation △ SOCmean(k), (that is: it is △ SOCmean=SOCmean-SOC* mean), basic domain is [- 100%, 100%],
Fuzzy domain is { -3, -2, -1,0 ,+1 ,+2 ,+3 }, and corresponding fuzzy subset is { NB, NM, NS, ZO, PS, PM, PB }, respectively
Indicate present battery energy-storage system be averaged state-of-charge and its reference value deviation be negative greatly, in negative, and bear it is small, zero, it is just small, just
In, it is honest }；Another way input is the real-time charging and discharging state CS of battery energy storage system, and is indicated at battery energy storage system with D
The value of CS is+1 under discharge condition, discharge condition；C indicates that battery energy storage system is in charged state, CS under charged state
Value is -1；Output is to smooth out time constant TB, basic domain be [0s, 3500s], obscure domain be 0,1,2,3,4,5,
6 }, corresponding fuzzy subset be { VS, S, SM, M, BM, B, VB }, respectively indicate output time constant be it is minimum, it is small, it is less than normal,
It is moderate, it is bigger than normal, greatly, greatly }；And control rule is the deviation △ SOC at discharge condition Dmean(k)Fuzzy subset be NB,
NM, NS, ZO, PS, PM, PB } and output fuzzy subset's sequence { VS, S, SM, M, BM, B, VB } one-to-one correspondence；In charged state C
Under, deviation △ SOCmean(k)Fuzzy subset be { NB, NM, NS, ZO, PS, PM, PB } and export fuzzy subset's sequence VB, B,
BM, M, SM, S, VS } it corresponds.In the present embodiment, input/output subordinating degree function such as Fig. 7 institute of postposition fuzzy controller
Show, de-fuzzy method is all made of gravity model appoach, controls rule as shown in table 2.
Table 2: postposition fuzzy controller rule list.
In the present embodiment, the transmission function of low-pass first order filter is 1/ (1+sT in step 1)B), wherein s is La Pula
This operator volume, TBFor variable time constant.
In the present embodiment, according to the reference output power P that battery energy storage system is total in step 3)* BESSSize determine participate in
The number N of charge/discharge battery energy storage unit specifically refers to the reference output power P that battery energy storage system is total* BESSInput internal layer
Fuzzy controller obtains participating in the number N of charge/discharge battery energy storage unit.As shown in figure 8, the effect of internal layer fuzzy controller
It is the reference output power P total according to battery energy storage system* BESSSize determine participate in charge/discharge battery energy storage unit
Number N.
As the total reference output power P of battery energy storage system* BESSWhen > 0 (discharge condition): if ︱ P* BESSIt is when ︱ is smaller, then defeated
The lesser negative value of ︱ N ︱ out, it represents system for quantity allotted is lesser and the relatively large battery energy storage unit of state-of-charge
It discharges, other more battery energy storage units are then not involved in charge/discharge, so as to their charge/discharge of opposite reduction
Duration prolongs its service life；If ︱ P* BESSWhen ︱ is larger, then the biggish negative value of ︱ N ︱ is exported, it represents system and will distribute
The relatively large battery energy storage unit of a fairly large number of and state-of-charge discharges, to reduce each battery energy storage unit
Power output, keep it in normal power output range.Vice versa, when the total reference output work of battery energy storage system
Rate P* BESSWhen < 0 (charged state): if ︱ P* BESSWhen ︱ is smaller, then the lesser positive value of ︱ N ︱ is exported；If ︱ P* BESSIt is when ︱ is larger, then defeated
The biggish positive value of ︱ N ︱ out.
In the present embodiment, layer fuzzy controller is the structure of single-input-single-output；Input is the total ginseng of battery energy storage system
Examine output power P* BESS, basic domain be [- 1pu, 1pu], wherein pu indicate per unit value, obscure domain be -3, -2, -1,
0 ,+1 ,+2 ,+3 }, corresponding fuzzy subset is { NB, NM, NS, ZO, PS, PM, PB }, and it is total to respectively indicate battery energy storage system
Reference output power is { negative big, to bear, bear small, zero, just small, center is honest }；Output is the battery energy storage for participating in charge/discharge
The number N of unit, basic domain are [- 25,25], and obscuring domain is { -3, -2, -1,0 ,+1 ,+2 ,+3 }, corresponding fuzzy
Subset is { NB, NM, NS, ZO, PS, PM, PB }, and respectively indicating and participating in the numerical value of charge/discharge battery energy storage unit is { to bear greatly, bear
In, bear it is small, zero, it is just small, center, it is honest；Control rule for input fuzzy subset { NB, NM, NS, ZO, PS, PM, PB } and
Fuzzy subset's sequence { PB, PM, PS, ZO, NS, NM, NB } of output.
In the present embodiment, the input/output subordinating degree function of internal layer fuzzy controller is all made of triangular membership functions, such as schemes
Shown in 9, de-fuzzy method is all made of gravity model appoach, controls rule as shown in table 3.
Table 3, internal layer fuzzy controller rule list.
The topological structure for each single machine wind power system that the present embodiment uses is as shown in Figure 10.Wherein, three-phase bridge is not controlled whole
Current circuit and Boost joint constitute motor side converter；Three-phase voltage source code converter constitutes grid side converter.
By effective control to motor side converter and grid side converter, it can be achieved that the maximal power tracing and system of wind energy
The independent control of active power and reactive power.The DC side of grid side converter is incorporated to battery energy storage unit, it is by battery
Energy storage and bidirectional DC-DC converter etc. are constituted, for keeping the stabilization of DC bus-bar voltage.Motor side Boost is adopted
With power outer ring, the double-loop control strategy of current inner loop, as shown in figure 11, wherein region is the present embodiment in dotted line frame
Based on battery energy storage directly driven wind-powered multi-computer system power association prosecutor method content, power outer ring for realizing wind energy maximum
Power tracking；Current inner loop is used to control the output electric current of Boost.
When unbalanced power supply, the grid-connected power of single machine wind power system can be indicated as shown in formula (7)；
In formula (7), PT0-i、QT0-iIt is expressed as the grid-connected average active power and average idle function of single machine wind power system
Rate, PTs2-i、PTc2-iIt is expressed as 2 frequency multiplication active components, QTs2-i、QTc2-iIt is expressed as 2 frequency multiplication reactive components, ud-i P、uq-i P、ud-i N、
uq-i NIt is expressed as d, q axis component of electric network positive and negative sequence fundamental voltage.id-i P、iq-i P、id-i N、iq-i NIt is expressed as single machine wind
D, q axis component of the grid-connected positive-negative sequence fundamental current of electric system, and all variables are all made of per unit value.
In view of negative-sequence current is to the adverse effect of grid side converter, i is enabled in Control System Designd-i N*=0, iq-i N*
=0.Since grid connected wind power system is normally operated in mean unit power factor state, the grid-connected flat of single machine wind power system can be enabled
Equal reactive power reference qref QT0-i *=0.
As shown in figure 11, the grid-connected average active power reference value P of single machine wind power systemT0-i *As shown in formula (8)；
In formula (8), PG-iFor the output power of separate unit wind energy conversion system；P* BESS-iIt is by wind power plant multimachine coordinated control system
The active power reference offset determined for each single machine wind power system.
If ignoring the internal resistance loss of switching device and capacitor etc., according to conservation of energy principle it is found that single machine wind power system
Grid-connected average active power PT0-iThe output power P of wind energy conversion system should be equal toG-iWith the output power P of battery energy storage systemBESS-i
The sum of.In conjunction with formula (8) it is found that P* BESS-iAt the same time as the output power reference value of battery energy storage unit, and the energy storage
Unit is to track its reference power by the stable mode of control DC bus-bar voltage.
By id-i N=0, iq-i N=0, QT0-i=0 substitutes into formula (7), and only considers grid-connected average active power PT0-iAnd it is grid-connected
Average reactive power QT0-iControl when, then can be obtained shown in the reference value such as formula (9) of system forward-order current；
In formula (9),For the d axis component of system forward-order current reference value,For the q axis point of system forward-order current reference value
Amount, the meaning of remaining parameter are identical with formula (7).
It, can if current inner loop uses feed forward decoupling control strategy after the reference value for obtaining system forward-order current
It obtains shown in the positive sequence modulation voltage reference value such as formula (10) of grid side converter；
In formula (10),WithThe d axis and q axis component of the positive sequence modulation voltage reference value of grid side converter respectively, KP
And KiIt is the parameter of PI controller, 1/s is the transmission function of the integral element of PI controller, and ω is network voltage angular frequency,
L is filter inductance, and the meaning of remaining parameter is identical with formula (7).
Shown in the negative phase-sequence modulation voltage reference value such as formula (11) that grid side converter similarly can be obtained；
In formula (11),WithThe respectively d axis and q axis component of the negative phase-sequence modulation voltage reference value of grid side converter,
KPAnd KiIt is the parameter of PI controller, 1/s is the transmission function of the integral element of PI controller, and ω is network voltage angular frequency,
L is filter inductance,For the d axis component of system negative-sequence current reference value,For the q axis component of system negative-sequence current reference value,
The meaning of remaining parameter is identical with formula (7).Using the unbalance control strategy of above-mentioned inhibition exchange side negative-sequence current, may make
When unbalanced fault occurs for power grid, the three-phase grid electric current of directly driven wind-powered system is still able to maintain almost symmetry, to be conducive to pair
The overcurrent that grid side converter may generate carries out unified Current limited Control.In addition, when the grid collapses, due to
To the Current limited Control of grid side converter, then biggish redundant power may be generated on its DC bus.But, it will
It is absorbed in a manner of controlling DC voltage stability battery energy storage unit, so as to effectively improve wind power system
Low voltage ride-through capability.In the present embodiment, the bidirectional DC-DC converter of connection battery pack to DC bus is using outside voltage
The double-loop control strategy of ring, current inner loop, as shown in figure 12.Referring to Figure 12, the DC voltage of grid side converter is referred to
Value u*And power grid
The DC voltage u of the side DC-i converterDC-iThe difference of the two obtains bidirectional DC-DC converter after passing through PI controller
The current reference value of deviceThe current reference value of bidirectional DC-DC converterWith the electric current i of bidirectional DC-DC converter1-iThe two
Difference pass through PI controller again and obtain bidirectional DC-DC converter duty ratio d1-iFeedback control amountBidirectional DC-DC converter
Device duty ratio d1-iFeedback control amountWith bidirectional DC-DC converter duty ratio d1-iFeedforward control amountIt is obtained after cumulative
Bidirectional DC-DC converter duty ratio d1-i, then by bidirectional DC-DC converter duty ratio d1-iIt carries out PWM modulation and generates PWM letter
Number the working condition of bidirectional DC-DC converter is controlled, for battery pack, output electric current is i1-i, output voltage is
uSB-i, the DC voltage of grid side converter is uDC-i.Outer voltage is for controlling grid side converter DC bus-bar voltage
Stabilization；Current inner loop is used to control the output electric current of battery pack.
In the present embodiment, using Matlab/Simulink to the direct-drive wind power generation field shown in FIG. 1 based on battery energy storage
Carry out simulation analysis.Entire wind power plant is made of 25 directly driven wind-powered/battery energy storage one-of-a-kind systems, i.e. M=25, single machine system
System specific simulation parameter it is as shown in table 1, and assume battery energy storage unit state-of-charge normal range of operation be 10%~
90%.System is imitative when being the multimachine coordination control strategy proposed using the present embodiment below and using Traditional control strategy
True result and its analysis.
The simulation parameter of table 4, one-of-a-kind system.
Figure 13 is all wind energy conversion systems of wind power plant prediction output power value P total in 0min-60minF, output power
The average value of 10min/ period is as shown in figure 14.According to the corresponding battery storage of the available day part of preposition FUZZY ALGORITHMS FOR CONTROL
Can system be averaged state-of-charge reference value SOC* mean, as shown in figure 15.The total prediction output power P of all wind energy conversion systemsF?
The average value of 0min-10min is 9.02MW, and the average value of 10min-20min is 22.04MW, relatively increases 13.02MW.With
This is corresponding to be averaged state-of-charge reference value SOC in 0min-10min period battery energy storage system* meanOutput is 23.14%,
Purpose is that control battery energy storage system changes in 0min-10min towards lower state-of-charge, and providing for 10min-20min can
Larger charging capacity space needed for energy.The total prediction output power P of all wind energy conversion systemsFIt is in the average value of 20min-30min
12.84MW, compared with the average value of 10min-20min, relative reduction 9.2MW.It is corresponding in 10min-20min
Period battery energy storage system is averaged state-of-charge reference value SOC* meanOutput is 73.46%, it is therefore an objective to control battery energy storage system
Change in 10min-20min towards higher state-of-charge, provides larger discharge capacity that may be needed for 20min-30min
Space.When the variation of the mean power of two period of front and back is little, the be averaged output of state-of-charge reference value of battery energy storage system exists
50% or so.By Figure 13~Figure 16 it is found that due to wind power prediction precision influence, the total reality output of all wind energy conversion systems
There are certain deviations between power and its prediction power.
With battery energy storage system be averaged state-of-charge, with reference to the variation of average state-of-charge and charging and discharging state, it is double
Molality fuzzy controllers will export and smooth out time constant T accordinglyB, as shown in figure 17, de-regulation is wind farm grid-connected average active
The size of power.As shown in figure 18, the grid-connected average active power P of wind power plantT0The output power P total compared to all wind energy conversion systemsG
It will smoothly much；The battery energy storage unit determined by internal layer control system is passed through control direct current by the deviation power between them
The stable mode of busbar voltage is compensated, and total output power is as shown in figure 19.In entire simulation process, battery storage
The average state-of-charge SOC of energy systemmeanIt remains in normal range of operation, as shown in figure 20.
At the same time, internal layer fuzzy controller is corresponding defeated also by the reference output power value total according to battery energy storage system
The number N of the battery energy storage unit of charge/discharge, as shown in figure 21, the charge/discharge of each battery energy storage unit of de-regulation are participated in out
Watt level.Figure 22~Figure 27 characterizes the operation characteristic of the battery energy storage unit of minimum and maximum initial state-of-charge respectively.
Their state-of-charge and charge/discharge watt level can be maintained in normal range of operation always, such as Figure 22, figure
23, shown in Figure 25, Figure 26；Their charging and discharging state is 0 within some periods, illustrates energy exchange not to occur with system, from
And their charge and discharge duration opposite can be reduced, it prolongs its service life, as shown in Figure 24, Figure 27.Simulation result also table
It is bright: to coordinate to control there are the multimachine that in the case where certain deviation, the present embodiment is proposed in wind-powered electricity generation prediction power and its actual power
Strategy processed remains to play preferable control action, to embody stronger adaptability and robustness.
The output power P total by all wind energy conversion systems is usually used in traditional outer layer control strategyGThrough first-order low-pass wave
(time constant is definite value T to deviceD) obtain wind farm grid-connected average active power reference value PT0 *, simulation result such as Figure 28~
Shown in 34.If the average state-of-charge SOC of battery energy storage systemmeanBeyond a certain range (10%~90%), then make its stopping
Work.Figure 28~Figure 30 is to determine smoothing time constant TDSystem is imitative when taking 250s, 700s, 1100,1700s, 3000s respectively
True result.By figure Figure 28~Figure 30, it is found that battery energy storage system after running for a period of time, is averaged, state-of-charge will all surpass
Out its limit range and stop working so that influencing the smooth effect to wind-powered electricity generation.As shown in Figure 31~Figure 34, when fixed
Smoothing time constant TDWhen=200s, although can guarantee the average state-of-charge of battery energy storage system not within the emulation period
Beyond the range that it is limited, but to the smooth effect of wind power fluctuation then obviously not as good as using the mentioned control plan of the present embodiment
Smooth effect when slightly is good, as shown in figure 32.Traditional internal layer power distribution control strategy is usually by battery energy storage system
Comprehensive charge/discharge power averaging distributes to each battery energy storage unit.It is the control plan that outer layer uses the present embodiment to be proposed below
Slightly, and internal layer use traditional power distribution control strategy when system simulation result, as shown in Figure 35~Figure 38.Each battery
The output power and charge/discharge state of energy-storage units are as shown in Figure 35, Figure 36, and as seen from the figure, each battery energy storage unit is by one
Under the straight working condition in charge or discharge, this, which is used for the service life, will generate certain negative effect.It is maximum and most
The battery energy storage unit of small initial state-of-charge is in the presence of overcharging or putting deeply within the emulation period, this is used for
Service life can also generate certain negative effect, as shown in Figure 37, Figure 38.
It can be seen that the optimal control of energy-storage system itself is improving it in directly driven wind-powered/battery energy storage multi-computer system
It will play the role of in terms of technical performance and economy vital.The present embodiment is with directly driven wind-powered more based on battery energy storage
Machine system is research object, and combines the short-term forecast of wind power and the real-time detection of energy-storage system state-of-charge, is proposed
A kind of multimachine coordination control strategy based on fuzzy logic algorithm.Simulation result shows: under mentioned control strategy, first
Battery energy storage system can be made to generate relatively good smooth effect to wind power fluctuation with relatively small stored energy capacitance；
Secondly the state-of-charge of each battery energy storage unit can be efficiently controlled, allows to avoid the occurrence of and overcharges or depth is put
The situation of electricity, and change towards suitable state-of-charge；Finally for wind-powered electricity generation prediction power with its actual power in the presence of certain inclined
When poor, remain to play preferable control action, embody stronger adaptability and robustness.The present embodiment is stored up based on battery
The directly driven wind-powered multi-computer system power association prosecutor method of energy is embedded in corresponding wind-powered electricity generation single machine control system, is being realized in smooth wind
Electrical power fluctuate while, additionally it is possible to make each battery energy storage unit avoid the occurrence of overcharge or the situation of deep discharge and to
Suitable state-of-charge transformation, simulation results show the correctness and validity of mentioned control strategy.
In addition, the present embodiment also provides a kind of directly driven wind-powered multi-computer system power association control system based on battery energy storage, packet
Include computer equipment, it is characterised in that: computer equipment is programmed to perform the aforementioned straight drive based on battery energy storage of the present embodiment
Wind-powered electricity generation multi-computer system power assists the step of prosecutor method.
In addition, the present embodiment also provides a kind of directly driven wind-powered multi-computer system power association control system based on battery energy storage, packet
It includes:
Outer layer coordinated control program unit, for calculating the total prediction output power P of all wind energy conversion systemsFIn two period of front and back
Deviation power △ P；Time constant T is smoothed out according to what deviation power △ P determined low-pass first order filterB；By all wind-force
The total output power P of machineGInput low-pass first order filter obtains the reference value P of wind farm grid-connected average active powerT0 *；
Outer layer internal layer interactive program unit, for by the reference value P of wind farm grid-connected average active powerT0 *With all wind
The total output power P of power machineGCompare, obtains the total reference output power P of battery energy storage system* BESS；
Internal layer coordinated control program unit, for the reference output power P total according to battery energy storage system* BESSSize it is true
Surely the number N of charge/discharge battery energy storage unit, and the reference output power P for combining battery energy storage system total are participated in* BESSAnd
The real-time state-of-charge SOC of all M battery energy storage unitsM×1=[SOCBESS-1,SOCBESS-2,…SOCBESS-M]TOwned
The corresponding reference output power value P of M battery energy storage unitM×1=[PBESS-1,PBESS-2,…PBESS-M]T；As N > 0, then select
It selects the lesser N number of battery energy storage unit of state-of-charge to charge, charge power size is ︱ P* BESS︱/N；As N < 0,
The biggish N number of battery energy storage unit of state-of-charge is then selected to discharge, discharge power size is ︱ P* BESS︱/N.
In the present embodiment, outer layer coordinated control program unit includes:
Preposition fuzzy controller subroutine unit, for being obtained according to the deviation power △ P of input through preposition fuzzy control
Average state-of-charge reference value SOC of the battery energy storage system in kth time period* mean(k)；
Average charged drift gage operator program unit in real time, for calculating SOC* mean(k)With its state-of-charge that is averaged in real time
SOC mean(k)Deviation △ SOCmean(k)；
Postposition fuzzy controller subroutine unit is used for deviation △ SOCmean(k), battery energy storage system real-time charge and discharge
Electricity condition CS smooths out time constant T through postposition fuzzy control determinationB。
The above is only a preferred embodiment of the present invention, protection scope of the present invention is not limited merely to above-mentioned implementation
Example, all technical solutions belonged under thinking of the present invention all belong to the scope of protection of the present invention.It should be pointed out that being led for this technology
For the those of ordinary skill in domain, several improvements and modifications without departing from the principles of the present invention, these improvements and modifications
Also it should be regarded as protection scope of the present invention.
Claims (10)
1. a kind of directly driven wind-powered multi-computer system power based on battery energy storage assists prosecutor method, it is characterised in that implementation steps include:
1) the total prediction output power P of all wind energy conversion systems is calculatedFIn the deviation power △ P of two period of front and back；According to deviation power △
What P determined low-pass first order filter smooths out time constant TB；By the total output power P of all wind energy conversion systemsGIt is low to input the single order
Bandpass filter obtains the reference value P of wind farm grid-connected average active powerT0 *；
2) by the reference value P of wind farm grid-connected average active powerT0 *The output power P total with all wind energy conversion systemsGCompare, obtains electricity
The total reference output power P of pond energy-storage system* BESS；
3) the reference output power P total according to battery energy storage system* BESSSize determine and participate in charge/discharge battery energy storage unit
Number N, and the reference output power P for combining battery energy storage system total* BESSAnd all M battery energy storage units is real-time charged
State SOCM×1=[SOCBESS-1,SOCBESS-2,…SOCBESS-M]TAll M battery energy storage units are obtained accordingly with reference to output
Performance number PM×1=[PBESS-1,PBESS-2,…PBESS-M]T；As N > 0, then the lesser N number of battery energy storage unit of state-of-charge is selected
It charges, charge power size is ︱ P* BESS︱/N；As N < 0, then the biggish N number of battery energy storage list of state-of-charge is selected
Member is discharged, and discharge power size is ︱ P* BESS︱/N.
2. the directly driven wind-powered multi-computer system power according to claim 1 based on battery energy storage assists prosecutor method, feature exists
In determining filter time constant T according to deviation power △ P in step 1)BDetailed step include:
1.1) deviation power △ P obtains battery energy storage system in the average state-of-charge ginseng of kth time period through preposition fuzzy controller
Examine value SOC* mean(k)；
1.2) SOC is calculated* mean(k)With its state-of-charge SOC that is averaged in real timemean(k)Deviation △ SOCmean(k)；
1.3) by deviation △ SOCmean(k), battery energy storage system real-time charging and discharging state CS through postposition fuzzy controller determine become
Smoothing time constant TB。
3. the directly driven wind-powered multi-computer system power according to claim 2 based on battery energy storage assists prosecutor method, feature exists
In the preposition fuzzy controller in step 1.1) is single-input-single-output structure；Input is deviation power △ P, basic domain
For [- 1pu, 1pu], wherein pu indicates per unit value, and obscuring domain is { -3, -2, -1,0 ,+1 ,+2 ,+3 }, corresponding fuzzy subset
For { NB, NM, NS, ZO, PS, PM, PB }, it is { negative for respectively indicating the deviation of two period average predicted powers of all wind energy conversion systems front and backs
Greatly, bear in, bear it is small, zero, it is just small, center, it is honest；Output is that battery energy storage system is referred in the average state-of-charge of kth time period
Value SOC* mean(k), basic domain is [0,100%], and obscuring domain is { 0,1,2,3,4,5,6 }, and corresponding fuzzy subset is
{ VS, S, SM, M, BM, B, VB }, respectively indicate battery energy storage system be averaged state-of-charge reference value be very little, it is small, it is smaller,
It is moderate, it is larger, greatly, very greatly }, control rule is the fuzzy subset { NB, NM, NS, ZO, PS, PM, PB } of input and exports fuzzy
Sequence of subsets is { VB, B, BM, M, SM, S, VS } one-to-one correspondence.
4. the directly driven wind-powered multi-computer system power according to claim 2 based on battery energy storage assists prosecutor method, feature exists
In the postposition fuzzy controller in step 1.3) is the mono- two-dimensional structure exported of two inputs-；Input is deviation △ all the way
SOCmean(k), basic domain is [- 100%, 100%], and obscuring domain is { -3, -2, -1,0 ,+1 ,+2 ,+3 }, corresponding mould
Pasting subset is { NB, NM, NS, ZO, PS, PM, PB }, respectively indicates present battery energy-storage system and be averaged state-of-charge and its reference value
Deviation be { negative big, to bear, bear small, zero, just small, center is honest }；Another way input is the real-time charge and discharge of battery energy storage system
Electricity condition CS, and indicate that battery energy storage system is in discharge condition with D, the value of CS is+1 under discharge condition；C indicates battery energy storage
System is in charged state, and the value of CS is -1 under charged state；Output is to smooth out time constant TB, basic domain be [0s,
3500s], obscuring domain is { 0,1,2,3,4,5,6 }, and corresponding fuzzy subset is { VS, S, SM, M, BM, B, VB }, is respectively indicated
Export time constant be it is minimum, it is small, it is less than normal, it is moderate, it is bigger than normal, greatly, greatly }；And control rule is the deviation at discharge condition D
△SOCmean(k)Fuzzy subset be { NB, NM, NS, ZO, PS, PM, PB } and export fuzzy subset's sequence VS, S, SM, M, BM,
B, VB } it corresponds；At charged state C, deviation △ SOCmean(k)Fuzzy subset be { NB, NM, NS, ZO, PS, PM, PB }
It is corresponded with output fuzzy subset's sequence { VB, B, BM, M, SM, S, VS }.
5. the directly driven wind-powered multi-computer system power according to claim 1 based on battery energy storage assists prosecutor method, feature exists
In the transmission function of low-pass first order filter is 1/ (1+sT in step 1)B), wherein s is Laplace operator volume, TBIt is variable
Time constant.
6. the directly driven wind-powered multi-computer system power described according to claim 1~any one of 5 based on battery energy storage assists control
Method, which is characterized in that according to the reference output power P that battery energy storage system is total in step 3)* BESSSize determine participate in fill/
The number N of discharge battery energy-storage units specifically refers to the reference output power P that battery energy storage system is total* BESSIt is fuzzy to input internal layer
Controller obtains participating in the number N of charge/discharge battery energy storage unit.
7. the directly driven wind-powered multi-computer system power according to claim 6 based on battery energy storage assists prosecutor method, feature exists
In the layer fuzzy controller is the structure of single-input-single-output；Input is the total reference output power of battery energy storage system
P* BESS, basic domain is [- 1pu, 1pu], and wherein pu indicates per unit value, and obscuring domain is { -3, -2, -1,0 ,+1 ,+2 ,+3 },
Corresponding fuzzy subset is { NB, NM, NS, ZO, PS, PM, PB }, and respectively indicating the total reference output power of battery energy storage system is
{ negative big, to bear, bear small, zero, just small, center is honest }；Output is the number N for participating in the battery energy storage unit of charge/discharge,
Basic domain is [- 25,25], and obscuring domain is { -3, -2, -1,0 ,+1 ,+2 ,+3 }, corresponding fuzzy subset be NB, NM, NS,
ZO, PS, PM, PB }, respectively indicate participate in charge/discharge battery energy storage unit numerical value be it is negative big, bear, bear it is small, zero, it is just small,
Center, honest；Control rule is the fuzzy subset { NB, NM, NS, ZO, PS, PM, PB } of input and fuzzy subset's sequence of output
{PB,PM,PS,ZO,NS,NM,NB}。
8. a kind of directly driven wind-powered multi-computer system power based on battery energy storage assists control system, including computer equipment, feature to exist
In: the computer equipment is programmed to perform described in any one of claim 1~7 based on the directly driven wind-powered of battery energy storage
Multi-computer system power assists the step of prosecutor method.
9. a kind of directly driven wind-powered multi-computer system power based on battery energy storage assists control system, characterized by comprising:
Outer layer coordinated control program unit, for calculating the total prediction output power P of all wind energy conversion systemsFIt is inclined in two period of front and back
Poor power △ P；Time constant T is smoothed out according to what deviation power △ P determined low-pass first order filterB；All wind energy conversion systems are total
Output power PGIt inputs the low-pass first order filter and obtains the reference value P of wind farm grid-connected average active powerT0 *；
Outer layer internal layer interactive program unit, for by the reference value P of wind farm grid-connected average active powerT0 *With all wind energy conversion systems
Total output power PGCompare, obtains the total reference output power P of battery energy storage system* BESS；
Internal layer coordinated control program unit, for the reference output power P total according to battery energy storage system* BESSSize determine ginseng
With the number N of charge/discharge battery energy storage unit, and the total reference output power P of battery energy storage system is combined* BESSAnd all M
The real-time state-of-charge SOC of a battery energy storage unitM×1=[SOCBESS-1,SOCBESS-2,…SOCBESS-M]TObtain all M electricity
The corresponding reference output power value P of pond energy-storage unitsM×1=[PBESS-1,PBESS-2,…PBESS-M]T；As N > 0, then select charged
The lesser N number of battery energy storage unit of state charges, and charge power size is ︱ P* BESS︱/N；As N < 0, then lotus is selected
The biggish N number of battery energy storage unit of electricity condition discharges, and discharge power size is ︱ P* BESS︱/N.
10. the directly driven wind-powered multi-computer system power based on battery energy storage assists control system according to claim 9, feature exists
In the outer layer coordinated control program unit includes:
Preposition fuzzy controller subroutine unit, for obtaining battery through preposition fuzzy control according to the deviation power △ P of input
Average state-of-charge reference value SOC of the energy-storage system in kth time period* mean(k)；
Average charged drift gage operator program unit in real time, for calculating SOC* mean(k)With its state-of-charge that is averaged in real time
SOCmean(k)Deviation △ SOCmean(k)；
Postposition fuzzy controller subroutine unit is used for deviation △ SOCmean(k), battery energy storage system real-time charging and discharging state
CS smooths out time constant T through postposition fuzzy control determinationB。
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