CN109995076A - A kind of photovoltaic based on energy storage collects system power and stablizes output cooperative control method - Google Patents
A kind of photovoltaic based on energy storage collects system power and stablizes output cooperative control method 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
- H02J3/28—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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- H02J3/383—
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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
- H02J3/46—Controlling of the sharing of output between the 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
- 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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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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- 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
Collect system power this application provides a kind of photovoltaic based on energy storage and stablizes output cooperative control method, method includes: according to photovoltaic power output ultra-short term prediction data identification current control period photovoltaic power changing pattern, it is adaptively adjusted for different mode and optimization object function, optimal filter coefficient is obtained by objective function combination particle swarm algorithm, energy storage power output is controlled according to optimal filter coefficient, the fluctuation of smooth photovoltaic power, reduces the fluctuation of light wave power；On this basis, it is feedback using energy-storage battery state-of-charge, second-order correction is carried out to the charge and discharge of energy-storage battery, so that final light storage joint output can be located in prediction power output section, track photovoltaic prediction power output, the accuracy of photovoltaic predictive ability is improved, the application will stabilize photovoltaic output pulsation and be combined in compensate photovoltaic power generation output forecasting error the problem of, and realize and utilize the above-mentioned double target of small-scale energy-storage battery completion.
Description
Technical field
This application involves photovoltaic system technical field more particularly to a kind of power that the photovoltaic based on energy storage collects system are steady
Surely cooperative control method is exported.
Background technique
In recent years, swift and violent using photovoltaic as the Renewable Energy Development of representative, however China's photovoltaic utilization rate is relatively low,
Main cause have two aspect: first is that photovoltaic system power output fluctuation, photovoltaic go out fluctuation conference cause grid entry point voltage to flash,
The problems such as frequency fluctuation, excessive harmonic wave；Photovoltaic, which goes out fluctuation, can be divided into high-frequency fluctuation and low-frequency fluctuation, wherein for low frequency wave
Dynamic, power grid possesses the enough reaction time and is responded, therefore influence of the low-frequency fluctuation to power grid can be ignored, and reduce light
Lie prostrate out the high-frequency fluctuation that fluctuation generally refers to reduce photovoltaic power output；Second is that the accuracy of photovoltaic power generation output forecasting is low, power grid root
Photovoltaic online space is directly affected according to the plan of photovoltaic power generation output forecasting photovoltaic plant power output and system reserve, prediction accuracy.
Photovoltaic generating system based on energy storage is to increase energy storage device on the basis of photovoltaic generating system, passes through energy storage system
System quick release and the function of absorbing electric energy stabilize the high-frequency fluctuation of photovoltaic generating system power output, can achieve to system output work
The smooth control purpose of rate；However photovoltaic wave is inhibited in smooth photovoltaic power based on the photovoltaic generating system of energy storage in the prior art
While dynamic, though photovoltaic power generation output forecasting preferably can be carried out using the historical data of photovoltaic power output, do not look to the future light
Influence of the volt power output to current time energy storage charge and discharge behavior；Or prediction data is directly replaced into practical power output input emulation mould
Type causes photovoltaic processing prediction accuracy to reduce.
Therefore a kind of contribute with smooth photovoltaic power with tracking photovoltaic prediction is needed to export for the power stability of double goal
System control method.
Summary of the invention
Collect system power this application provides a kind of photovoltaic based on energy storage and stablize output cooperative control method, with smooth
Tracking prediction power output improves the accuracy of photovoltaic prediction power output while photovoltaic power stablizes photovoltaic power output.
In order to solve the above-mentioned technical problem, the embodiment of the present application discloses following technical solution:
This application provides the power stabilities that a kind of photovoltaic based on energy storage collects system to export cooperative control method, described
Method includes:
Ultra-short term is carried out to photovoltaic power output to predict to obtain photovoltaic prediction output power Pf；
Output power P is predicted according to the photovoltaicfDetermine photovoltaic power output Trend Pattern, the photovoltaic power output Trend Pattern packet
Include ascending fashion, drop mode and fluctuation model；
λ is obtained according to photovoltaic power output Trend Pattern, the λ is the weight coefficient for characterizing battery charging and discharging intensity item；
Objective function J is established, the objective function J isWherein POFor light
Store up joint output power, PbFor energy-storage battery output power；
Optimal filter factor alpha is obtained using particle swarm algorithm according to the objective function Jopt；
According to the optimal filter factor alphaoptBased on the smooth photovoltaic output power of low-pass filtering algorithm, while by described in most
Excellent filter coefficient alphaoptIt passes to Collaborative Control module and obtains preliminary light storage joint output power Po,tempAnd battery power generating value Pb,pri；
Joint output power P is stored up to the preliminary light according to energy-storage battery state-of-charge SOCo,tempPrediction is compensated to miss
Difference obtains energy storage corrected output Pb,rec；
According to the battery power generating value Pb,priWith the energy storage corrected output Pb,recCalculate energy-storage battery output power Pb。
Preferably, described that output power P is predicted according to the photovoltaicfDetermine that photovoltaic power output Trend Pattern includes:
Defined function P=[Po(t-1),PPV(t),Pf(t+1),Pf(t+2),PfAnd function Δ P (t+3)]m=Pf(t+3)-
Po(t-1), wherein PPVIt (t) is current time photovoltaic output power, Po(t-1) joint output power, P are stored up for previous moment lightf(t
+1)、Pf(t+2) and Pf(t+3) respectively the photovoltaic at future t+1 moment, t+2 moment and t+3 moment predicts output power；
The monotonicity for determining the function P, when the function P monotonic increase, the photovoltaic power output Trend Pattern is to rise
Mode, when the function P monotone decreasing, the photovoltaic power output Trend Pattern is drop mode；
When the function P there are first order pole and be maximum when, if Δ Pm>=0, then photovoltaic power output Trend Pattern be
Ascending fashion, if Δ Pm<-ε, then the photovoltaic power output Trend Pattern is drop mode, if-ε≤Δ Pm< 0, the then photovoltaic
Power output Trend Pattern is fluctuation model；
When the function P there are first order pole and be minimum when, if Δ Pm>=ε, then photovoltaic power output Trend Pattern be
Ascending fashion, if Δ Pm< 0, then the photovoltaic power output Trend Pattern is drop mode, if 0≤Δ Pm< ε, then the photovoltaic goes out
Power Trend Pattern is fluctuation model；
When the function P is there are when duopole, if Δ Pm> ε, then the photovoltaic power output Trend Pattern is ascending fashion, if
ΔPm<-ε, then the photovoltaic power output Trend Pattern is drop mode, if-ε≤Δ Pm< 0≤Δ of ε Pm< ε, then the photovoltaic goes out
Power Trend Pattern is fluctuation model.
Preferably, described to include: according to photovoltaic power output Trend Pattern acquisition λ
When photovoltaic power output Trend Pattern is ascending fashion, λ=SOC (t)；
When photovoltaic power output Trend Pattern is drop mode, λ=100%-SOC (t)；
When photovoltaic power output Trend Pattern is fluctuation model, λ=2 | 50%-SOC (t) |；
Wherein SOC (t) is current time energy-storage battery state of charge.
Preferably, described by the optimal filter factor alphaoptIt passes to Collaborative Control module and obtains light storage joint output work
Rate Po,tempAnd battery power generating value Pb,priInclude:
According to Po,temp=αopt PPV(t)+(1-αopt) Po (t-1) acquisition Po,temp；
According to Pb,pri=PPV(t)-Po,temp(t) P is obtainedb,pri。
Preferably, described according to the battery power generating value Pb,priWith the energy storage corrected output Pb,recCalculate energy-storage battery
Output power PbInclude:
According to Pb=Pb,pri+Pb,recCalculate the energy-storage battery output power Pb。
Compared with prior art, the application has the beneficial effect that
(1) the application recognizes current control period photovoltaic power changing pattern according to photovoltaic power output ultra-short term prediction data,
It is adaptively adjusted for different mode and optimization object function, passes through objective function combination particle swarm algorithm and obtain optimal filter system
Number controls energy storage power output according to optimal filter coefficient, and the stabilization of light wave output is stablized in the fluctuation of smooth photovoltaic power, improves light
Lie prostrate utilization rate.
(2) the application is by the optimal filter factor alpha optIt passes to Collaborative Control module and obtains preliminary light storage joint output
Power P o,tempAnd battery power generating value Pb,pri；Joint output power is stored up to the preliminary light according to energy-storage battery state-of-charge SOC
Po,tempIt compensates prediction error and obtains energy storage corrected output Pb,rec；According to the battery power generating value Pb,priIt is repaired with the energy storage
Positive Pb,recCalculate energy-storage battery output power Pb, realize Collaborative Control, the charge and discharge progress completed to energy-storage battery is secondary
Amendment, so that final light storage joint output can be located in prediction power output section, tracking photovoltaic prediction power output improves photovoltaic prediction
The accuracy of ability reduces the deviation of photovoltaic power output and scheduling power output, improves the percentage regulation of light-preserved system joint power output
With space.
(3) the application will stabilize photovoltaic output pulsation and be combined in compensate photovoltaic power generation output forecasting error the problem of, and
Second-order correction has been carried out to the charge and discharge of energy-storage system, has realized and completes above-mentioned double target using small-scale energy-storage battery.
Detailed description of the invention
In order to illustrate more clearly of the technical solution of the application, letter will be made to attached drawing needed in the embodiment below
Singly introduce, it should be apparent that, for those of ordinary skills, without creative efforts, also
Other drawings may be obtained according to these drawings without any creative labor.
Fig. 1 collects the structural schematic diagram of system for the photovoltaic based on energy storage in the application；
Fig. 2 is that a kind of photovoltaic based on energy storage provided by the present application collects the stable output cooperative control method of system power
Flow diagram；
Fig. 3 is the flow diagram that the optimal filter coefficient in the application solves；
Fig. 4 is the photovoltaic power output changing pattern schematic diagram in the embodiment of the present invention.
Specific embodiment
In order to make those skilled in the art better understand the technical solutions in the application, below in conjunction with the application reality
The attached drawing in example is applied, the technical scheme in the embodiment of the application is clearly and completely described, it is clear that described implementation
Example is only some embodiments of the present application, rather than whole embodiments.Based on the embodiment in the application, the common skill in this field
The application protection all should belong in art personnel every other embodiment obtained without making creative work
Range.
Collect system power this application provides a kind of photovoltaic based on energy storage and stablize output cooperative control method, with smooth
Tracking prediction power output improves the accuracy of photovoltaic prediction power output while photovoltaic power reduces photovoltaic fluctuation, improves photovoltaic and utilizes
Rate.
As shown in FIG. 1, FIG. 1 is the knots that the photovoltaic based on energy storage in the application collects system for the structure of light storage association system
Structure schematic diagram, from figure 1 it appears that system includes large-sized photovoltaic electric field, energy-storage battery, DC/DC inverter, high no-load voltage ratio DC/
DC inverter, grid-connected DC/AC inverter.Centralized energy-storage battery is installed on photovoltaic exit and coordinates renewable energy output, control
Device processed provides energy-storage battery charge-discharge electric power reference value.Ignore the energy loss in transmission and conversion process, then have:
Po=PPV-Pb
Wherein, POJoint output power, P are stored up for lightPVFor photovoltaic plant raw output power, PbFor energy-storage battery output work
Rate；Pb> 0 indicates battery charging, otherwise discharges.
The application is to realize the double goal for stabilizing optical power fluctuation and compensation prediction error, by using adaptive optimization
Filter factor module optimizes the filter factor for flat volatility, then via Collaborative Control module, it is real further to adjust energy storage
The target for chasing after prediction error is completed in border output.It mainly includes BPNN method light that light-preserved system power stability, which exports coordination control strategy,
The prediction of volt power output ultra-short term, three optimization of adaptive-filtering coefficient, Collaborative Control modules.
Conventional low-pass is filtered photovoltaic field output power sequence PPVInput time constant is the first order inertial loop of T, is obtained
More smooth output Po, transmission function are as follows:
It will be obtained after above formula discretization:
Wherein, Δ t is time interval, defines filter factorα∈[0,1]。
FormulaIt is exported after showing filtering
Power smooth degree is related with filter factor: when α=0, Po(t)=Po(t-1), light stores up association system stable output power, but light
Volt power swing is compensated by energy-storage battery completely, and battery single charge-discharge electric power is larger, easily saturation or emptying rapidly.If it is desired to store up
Energy battery last participates in photovoltaic output and adjusts, then needs to configure biggish battery capacity, and cost of investment is high；P when α=1o(t)=
PPV(t), battery is latched, that is, is not involved in photovoltaic plant fluctuation and is stabilized.
Specifically, the power stability for collecting system this application provides a kind of photovoltaic based on energy storage exports Collaborative Control side
Method, with specific reference to Fig. 2, Fig. 2 is the power stability output collaboration that a kind of photovoltaic based on energy storage provided by the present application collects system
The flow diagram of control method, which comprises
S01: ultra-short term is carried out to photovoltaic power output and predicts to obtain photovoltaic prediction output power Pf。
Ultra-short term is carried out to photovoltaic power output to predict to obtain photovoltaic prediction output power Pf, specifically, photovoltaic plant is original out
Force data sampling time interval Ts, PfOutput power is predicted for photovoltaic DC field, and photovoltaic DC field ultra-short term is gone out using BP neural network
Power predicted, when prediction a length of Tl, prediction data time interval is Tf, and Tf> Ts.It contributes to photovoltaic and carries out ultra-short term prediction
Purpose be in TfIn time scale, filter factor is completed using prediction data and is optimized.Photovoltaic power output ultra-short term is pre- in this patent
It surveys and uses traditional BPNN method.BPNN method is technological means commonly used in the art, therefore details are not described herein.
S02: output power P is predicted according to the photovoltaicfDetermine photovoltaic power output Trend Pattern, the photovoltaic power output trend mould
Formula includes ascending fashion, drop mode and fluctuation model.
The application recognizes current control period photovoltaic power changing pattern according to photovoltaic power output ultra-short term prediction data, therefore
Define three kinds of photovoltaic power output changing patteries: up and down and steady fluctuation model.Power for pattern identification is respectively previous
Moment light stores up joint output power, current time photovoltaic real output and photovoltaic prediction output work in following a period of time
Rate.In view of photovoltaic forecasting accuracy declines with predicted time, determine so selection future 30min interior prediction value participates in mode.
Specifically, output power P is predicted according to the photovoltaicfDetermine that photovoltaic power output Trend Pattern includes:
Defined function P=[Po(t-1),PPV(t),Pf(t+1),Pf(t+2),PfAnd function Δ P (t+3)]m=Pf(t+3)-
Po(t-1), wherein PPVIt (t) is current time photovoltaic output power, Po(t-1) joint output power, P are stored up for previous moment lightf(t
+1)、Pf(t+2) and Pf(t+3) respectively the photovoltaic at future t+1 moment, t+2 moment and t+3 moment predicts output power；
The monotonicity for determining the function P, when the function P monotonic increase, the photovoltaic power output Trend Pattern is to rise
Mode, when the function P monotone decreasing, the photovoltaic power output Trend Pattern is drop mode；
When the function P there are first order pole and be maximum when, if Δ Pm>=0, then photovoltaic power output Trend Pattern be
Ascending fashion, if Δ Pm<-ε, then the photovoltaic power output Trend Pattern is drop mode, if-ε≤Δ Pm< 0, the then photovoltaic
Power output Trend Pattern is fluctuation model；
When the function P there are first order pole and be minimum when, if Δ Pm>=ε, then photovoltaic power output Trend Pattern be
Ascending fashion, if Δ Pm< 0, then the photovoltaic power output Trend Pattern is drop mode, if 0≤Δ Pm< ε, then the photovoltaic goes out
Power Trend Pattern is fluctuation model；
When the function P is there are when duopole, if Δ Pm> ε, then the photovoltaic power output Trend Pattern is ascending fashion, if
ΔPm<-ε, then the photovoltaic power output Trend Pattern is drop mode, if-ε≤Δ Pm< 0≤Δ of ε Pm< ε, then the photovoltaic goes out
Power Trend Pattern is fluctuation model.
Above content table 1 indicates are as follows:
The power output Trend Pattern criterion of 1 photovoltaic of table
S03: λ is obtained according to photovoltaic power output Trend Pattern, the λ is the weight system for characterizing battery charging and discharging intensity item
Number.When photovoltaic power output Trend Pattern is ascending fashion, λ=SOC (t)；
When photovoltaic power output Trend Pattern is drop mode, λ=100%-SOC (t)；
When photovoltaic power output Trend Pattern is fluctuation model, λ=2 | 50%-SOC (t) |；
Wherein SOC (t) is current time energy-storage battery state of charge.
The specific corresponding scene of mode is referring to FIG. 4, Fig. 4 is the photovoltaic power output changing pattern signal in the embodiment of the present invention
Figure.
Under the different mode of photovoltaic power output, to meet the requirement for reducing power swing, battery has different chargings, electric discharge
Mode, the limitation that state-of-charge contributes to battery are also different.In ascending fashion, the original power output of photovoltaic continues to increase, to reduce
Light storage joint output growth rate in the period is controlled, energy-storage battery is needed unidirectionally to charge.The ability to work and SOC of energy-storage battery at this time
Negative correlation, i.e., as SOC increases, energy storage working space reduces.To mitigate battery power output intensity at this time, need suitably to promote energy storage
Cell output item weight, therefore λ is set under the mode as current time energy storage SOC value, i.e. λ=SOC (t)；On the contrary, under
Drop mode, energy-storage battery need to discharge to slow down photovoltaic power decline, and the ability to work of energy-storage battery and SOC are positively correlated at this time,
To reduce working strength of the energy storage when SOC is lower, therefore λ=100%-SOC (t) under the mode is set, so as to when SOC is lower
Promote PbItem weight；Under fluctuation model, energy-storage battery charge and discharge movement within the control period is existed simultaneously, therefore to maintain SOC
50% perfect condition be target, set λ=2 | 50%-SOC (t) |.Coefficient " 2 " is predominantly united with up and down mode
One, guarantee λ range between [0,1].
S04: establishing objective function J, and the objective function J isWherein PO
Joint output power, P are stored up for lightbFor energy-storage battery output power.
Battery charging and discharging intensity is combined to meet photovoltaic output smoothing effect, constructs multi-goal Optimization Model,
Optimal filter coefficient is solved, objective function is as follows:
Two respectively indicate to light storage joint output-power fluctuation constraint and the constraint of energy-storage battery charge-discharge electric power in above formula,
The two is mutual restricting relation, and N is data points, and λ is the weight coefficient for characterizing battery charging and discharging intensity item: λ=0 item optimizes mesh
Mark only considers that smooth effect, λ increase, then PbItem influences to enhance on optimization aim J, stabilizes ripple effect reduction.
Existing method takes the mode directly for weight coefficient assignment more, lacks power when constructing Model for Multi-Objective Optimization
Weight coefficient configuration standard is easy to cause objective function variation to rely primarily on a certain item in some cases, it is excellent not to be able to satisfy multiple target
The target of change.For formulaMulti-objective optimization question situation, set forth herein one kind certainly
The weight coefficient of adaptation determines scheme, weight coefficient by current and future for a period of time in photovoltaic power generation trend and energy-storage battery lotus
Electricity condition SOC is codetermined.
S05: optimal filter factor alpha is obtained using particle swarm algorithm according to the objective function Jopt。
The application controls energy storage power output according to optimal filter coefficient, and light wave output is stablized in the fluctuation of smooth photovoltaic power
Stablize, therefore optimal filter factor alphaoptAcquisition be the key that the application, the application uses particle according to the objective function J
Group's algorithm obtains optimal filter factor alphaopt；Specific method for solving refers to Fig. 3, and Fig. 3 is that the optimal filter coefficient in the application solves
Flow diagram；It is as follows that process is solved as can be seen from Figure 3:
Set the control parameter of particle swarm algorithm: population sum Γ, inertia constant section [Wmin,Wmax], Studying factors
c1,c2, the number of iterations L；
Initialize the position and speed and the number of iterations k=0 of population；
Particle fitness is sought based on objective function, and more new individual is optimal and global optimum；
Update the number of iterations k=k+1, discriminate whether to reach maximum number of iterations: if so, iteration stopping, record is current complete
Office's optimal solution；Otherwise particle position and speed are updated, continues to execute and " particle fitness, more new individual is sought based on objective function
The step for optimal and global optimum ".
S06: according to the optimal filter factor alphaoptBased on the smooth photovoltaic output power of low-pass filtering algorithm, while by institute
State optimal filter factor alphaoptIt passes to Collaborative Control module and obtains preliminary light storage joint output power Po,tempAnd battery power generating value
Pb,pri。
Optimal filter factor alpha in current control period is obtained after the optimization of adaptive-filtering coefficient in the applicationopt, and transmit
Give Collaborative Control module.By by αoptInput carries out pre-smoothed to the original power output of photovoltaic DC field, and the application contributes super according to photovoltaic
Short term predicted data recognizes current control period photovoltaic power changing pattern, adaptively adjusts for different mode and optimization aim
Function obtains optimal filter coefficient by objective function combination particle swarm algorithm, controls energy storage power output according to optimal filter coefficient,
The fluctuation of smooth photovoltaic power, stablizes the stabilization of light wave output, improves photovoltaic utilization rate.
Specifically pre-smoothed method is based on low-pass filtering algorithm, and low pass rate algorithm is technological means commonly used in the art,
Therefore this is repeated no more again；Obtain preliminary light storage joint output power Po,tempAnd battery power generating value Pb,pri, compared to photovoltaic plant original
Begin to export, Po,tempStability bandwidth reduces.Later, in Po,tempOn the basis of further regulating cell charge and discharge movement, compensation prediction
Error, amendment light storage joint output.Energy-storage battery SOC is actively engaged in battery charging and discharging power adjustment as closed loop feedback amount, meter
Calculate energy storage corrected output Pb,rec, the reference output of energy-storage battery is by Pb,priAnd Pb,recIt codetermines, realizes Collaborative Control.
Specifically, described by the optimal filter factor alphaoptIt passes to Collaborative Control module and obtains light storage joint output work
Rate Po,tempAnd battery power generating value Pb,priInclude:
According to Po,temp=αopt PPV(t)+(1-αopt)Po(t-1) P is obtainedo,temp；
According to Pb,pri=PPV(t)-Po,temp(t) P is obtainedb,pri。
S07: joint output power P is stored up to the preliminary light according to energy-storage battery state-of-charge SOCo,tempIt compensates pre-
It surveys error and obtains energy storage corrected output Pb,rec。
Energy-storage battery charge-discharge electric power, which is repaired, is based on different Po,temp, SOC state interval.For this purpose, definition is pre- first
Survey the upper limit and prediction lower limit:
ΔPtolFor margin for error；According to Po,tempIt delimited with forecast interval relationship: lower than prediction lower limit (Po,temp< Pl),
Allow (P in section between predictionl≤Po,temp≤Ph) and higher than the prediction upper limit (Po,temp> Ph).Meanwhile by the charged of battery
State demarcation is three sections: [0, SOClow], [SOClow,SOChigh], [SOChigh, 100%], SOChigh、SOClowRespectively
The upper and lower boundary value in energy-storage battery ideal operation section.Energy-storage battery second-order correction power output is shown in Table under every kind of interval combinations
2。
The corresponding energy storage corrected output P of 2 difference SOC of tableb,recValue
With P in tableo,temp> PhThe analysis of behavior example: it for tracking prediction, needs to charge the battery, if battery SOC < SOClowTable
Bright battery has charging space enough, is to promote battery charge state as early as possible, should make full use of Po,tempWith PlBetween power space
Supplement battery charge state；If opposite battery SOC > SOChigh, remaining battery charging insufficient space, to avoid overcharging and being subsequent
Charge reserved space, then does not act to current time battery and carry out second-order correction；When battery SOC is in ideal operation section,
The second-order correction power of energy-storage battery and current SOC are linearly related, and the lower corrected output of SOC is bigger.For Pl≤Po,temp≤
PhAnd Po,temp< PlThe case where, energy-storage battery second-order correction power is determined using identical thinking.
S08: according to the battery power generating value Pb,priWith the energy storage corrected output Pb,recCalculate energy-storage battery output power
Pb；Specifically according to Pb=Pb,pri+Pb,recCalculate the energy-storage battery output power Pb。
The final real output of energy-storage battery by part and tracking prediction for flat volatility second-order correction part
It codetermines:
Pb=Pb,pri+Pb,rec
Due to having adjusted light storage joint output behind tracking prediction section, a fixing is produced to the smooth effect of joint power output
Ring, do not add it is subsequent stabilize module under the premise of, require photovoltaic prediction to answer relatively accurate, while Δ P hereintolDo not answer it is excessive,
To avoid | Pb,pri| > > | Pb,rec|。
The application realizes Collaborative Control, completes the charge and discharge to energy-storage battery and carries out second-order correction, so that final light storage connection
Closing output can be located in prediction power output section, and tracking photovoltaic prediction power output improves the accuracy of photovoltaic predictive ability, reduces
The deviation of photovoltaic power output and scheduling power output improves percentage regulation and the space of light-preserved system joint power output.
Meanwhile the application can be adjusted in real time energy-storage battery state-of-charge, realize the preliminary filling prevention of battery, effectively
State-of-charge is stablized in reasonable working range, to extend battery.
It is quantitative assessment energy storage in the application in smooth photovoltaic power and the effect of compensation prediction error, herein using following
Four evaluation indexes, M indicates data number in evaluation cycle in each index.
Fluctuate average value:
Fluctuate maximum value:
The out-of-limit average value of predicting tracing:
Perr(t)=max (| Po(t)-Pf(t)|-ΔPtol,0)
The out-of-limit probability of predicting tracing:
Predicting tracing gets over limit value P in formulaerr(t) and neighbouring when indicating t moment output power not in forecast interval
Predict the distance of up/down limit.
Since embodiment of above is that reference combination is illustrated on other modes, have between different embodiments
There is identical part, identical, similar part may refer to each other between each embodiment in this specification.Herein no longer in detail
It illustrates.
Those skilled in the art will readily occur to its of the application after considering specification and practicing the disclosure invented here
His embodiment.This application is intended to cover any variations, uses, or adaptations of the invention, these modifications, purposes or
Person's adaptive change follows the general principle of the application and including the undocumented common knowledge in the art of the application
Or conventional techniques.The description and examples are only to be considered as illustrative, and the true scope and spirit of the application are wanted by right
The content asked is pointed out.
Above-described the application embodiment does not constitute the restriction to the application protection scope.
Claims (5)
1. a kind of photovoltaic based on energy storage, which collects system power, stablizes output cooperative control method, which is characterized in that the method
Include:
Ultra-short term is carried out to photovoltaic power output to predict to obtain photovoltaic prediction output power Pf；
Output power P is predicted according to the photovoltaicfDetermine photovoltaic power output Trend Pattern, the photovoltaic power output Trend Pattern includes upper
Rising mould formula, drop mode and fluctuation model；
λ is obtained according to photovoltaic power output Trend Pattern, the λ is the weight coefficient for characterizing battery charging and discharging intensity item；
Objective function J is established, the objective function J isWherein POFor light Chu Lian
Close output power, PbFor energy-storage battery output power；
Optimal filter factor alpha is obtained using particle swarm algorithm according to the objective function Jopt；
According to the optimal filter factor alphaoptBased on the smooth photovoltaic output power of low-pass filtering algorithm, while by the optimal filter
Wave factor alphaoptIt passes to Collaborative Control module and obtains preliminary light storage joint output power Po,tempAnd battery power generating value Pb,pri；
Joint output power P is stored up to the preliminary light according to energy-storage battery state-of-charge SOCo,tempPrediction error is compensated to obtain
To energy storage corrected output Pb,rec；
According to the battery power generating value Pb,priWith the energy storage corrected output Pb,recCalculate energy-storage battery output power Pb。
2. the method according to claim 1, wherein described predict output power P according to the photovoltaicfDetermine light
Lying prostrate power output Trend Pattern includes:
Defined function P=[Po(t-1),PPV(t),Pf(t+1),Pf(t+2),PfAnd function Δ P (t+3)]m=Pf(t+3)-Po(t-
1), wherein PPVIt (t) is current time photovoltaic output power, Po(t-1) joint output power, P are stored up for previous moment lightf(t+1)、
Pf(t+2) and Pf(t+3) respectively the photovoltaic at future t+1 moment, t+2 moment and t+3 moment predicts output power；
The monotonicity for determining the function P, when the function P monotonic increase, the photovoltaic power output Trend Pattern is upper rising mould
Formula, when the function P monotone decreasing, the photovoltaic power output Trend Pattern is drop mode；
When the function P there are first order pole and be maximum when, if Δ Pm>=0, then the photovoltaic power output Trend Pattern is upper rising mould
Formula, if Δ Pm<-ε, then the photovoltaic power output Trend Pattern is drop mode, if-ε≤Δ Pm< 0, then the photovoltaic power output becomes
Gesture mode is fluctuation model；
When the function P there are first order pole and be minimum when, if Δ Pm>=ε, then the photovoltaic power output Trend Pattern is upper rising mould
Formula, if Δ Pm< 0, then the photovoltaic power output Trend Pattern is drop mode, if 0≤Δ Pm< ε, then the photovoltaic is contributed trend
Mode is fluctuation model；
When the function P is there are when duopole, if Δ Pm> ε, then the photovoltaic power output Trend Pattern is ascending fashion, if Δ Pm
<-ε, then the photovoltaic power output Trend Pattern is drop mode, if-ε≤Δ Pm< 0≤Δ of ε Pm< ε, then the photovoltaic power output becomes
Gesture mode is fluctuation model.
3. the method according to claim 1, wherein described obtain λ packet according to photovoltaic power output Trend Pattern
It includes:
When photovoltaic power output Trend Pattern is ascending fashion, λ=SOC (t)；
When photovoltaic power output Trend Pattern is drop mode, λ=100%-SOC (t)；
When photovoltaic power output Trend Pattern is fluctuation model, λ=2 | 50%-SOC (t) |；
Wherein SOC (t) is current time energy-storage battery state of charge.
4. the method according to claim 1, wherein described by the optimal filter factor alphaoptPass to collaboration
Control module obtains light storage joint output power Po,tempAnd battery power generating value Pb,priInclude:
According to Po,temp=αopt PPV(t)+(1-αopt)Po(t-1) P is obtainedo,temp；
According to Pb,pri=PPV(t)-Po,temp(t) P is obtainedb,pri。
5. the method according to claim 1, wherein described according to the battery power generating value Pb,priWith the energy storage
Corrected output Pb,recCalculate energy-storage battery output power PbInclude:
According to Pb=Pb,pri+Pb,recCalculate the energy-storage battery output power Pb。
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