CN108876000A - A kind of photovoltaic charge station light, storage, transformer capacity coordinate and optimize configuration method - Google Patents
A kind of photovoltaic charge station light, storage, transformer capacity coordinate and optimize configuration method Download PDFInfo
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Abstract
The invention discloses a kind of photovoltaic charge station light, storage, transformer capacities to coordinate and optimize configuration method, it is first determined the objective function of photovoltaic charge station, then the basic data of photovoltaic charge station is obtained, determine photovoltaic electric vehicle charging station constraint condition；Then according to NSGA-II multi-objective genetic algorithm optimization object function is used, optimum results are obtained；Finally according to optimum results, most reasonable construction demand is chosen by investor's construction investment budget, according to construction demand to carrying out corresponding hardware facility configuration in photovoltaic electric vehicle charging station.The present invention is suitable for the city of all kinds of vehicle charging stations containing photovoltaic electric, realizes the photovoltaic charge station Optimal Configuration Method that the light storage based on energy control strategy becomes three's capacity coordination optimization；Theoretical foundation and technical support are provided for the electric automobile charging station Construction and operation containing photovoltaic generating system, guarantees economy, the feature of environmental protection and the reliability of charging station Construction and operation.
Description
Technical field
The present invention relates to substation intelligent monitoring technical field, specifically a kind of photovoltaic charge station light, storage, transformer hold
Amount coordination optimization configuration method.
Background technique
The popularization of electric car is to solve the important means of the gentle solution environmental pressure of energy crisis, electric automobile charging station
Construction is essential condition, has bigger prospect, the technology for needing to solve in conjunction with traditional charging station using photovoltaic power generation
It is exactly the capacity configuration problem of the equipment such as photovoltaic array, energy storage device and transformer.
Research at present is the simple capacity considered between photovoltaic array and energy storage device substantially, passes through the smooth photovoltaic of energy storage
Power output, when photovoltaic power output, which is greater than, stands interior charge requirement, storage is more than electric power；When standing, interior charge requirement is greater than when photovoltaic is contributed just
From power grid power purchase, the effect for reducing maximum peak power and peak load shifting is realized.Do not consider when distributed photovoltaic access tradition
To the influence of traditional power supply unit in station after charging station, the influence of the randomness, fluctuation of photovoltaic power output and workload demand and
The interior dynamic electricity of energy storage device stores constraint.
Summary of the invention
The purpose of the present invention is in view of the deficiency of the prior art, provide a kind of photovoltaic charge station light, storage, transformer
Capacity coordinates and optimizes configuration method.
The purpose of the present invention is what is be achieved through the following technical solutions：
A kind of photovoltaic charge station light, storage, transformer capacity coordinate and optimize configuration method, and specific step is as follows：
Step 1, the objective function for determining photovoltaic charge station, the objective function include：Transformer year comprehensive cost target
Function and light, storage Construction and operation totle drilling cost objective function and photovoltaic resources utilization rate objective function.
Step 2, the basic data for obtaining photovoltaic charge station, determine photovoltaic electric vehicle charging station constraint condition.
Step 3, according to the basic data and basic data in step 2, optimize with NSGA-II multi-objective genetic algorithm and walk
Objective function in rapid 1, obtains optimum results.
Step 4, according to optimum results in step 3, photovoltaic resources are made full use of while construction cost is optimal, by investing
Most reasonable construction demand is chosen in person's construction investment budget, corresponding hard to carrying out in photovoltaic electric vehicle charging station according to construction demand
The configuration of part facility.
In the further design scheme of the present invention, transformer year comprehensive cost function be：C1=Cd+Cs+Ct。
Transformer year, comprehensive cost constraint condition was：
Transformer capacity lower limit meets electric car charging peak load demand S in charging stationb≥SL/n；
The transformer capacity upper limit is when selecting 2 or when 3 transformers, wherein when stoppages in transit, another or 2 transformers appearance
Amount is no more than peak load in planning region：Sb≤SLOr Sb≤SL/2。
In formula：C in formulad、Cs、CtRespectively have a power failure in transformer investment cost, year running wastage expense and photovoltaic charge station
Failure costs, SbFor single transformer capacity, SLFor the maximum apparent energy of photovoltaic charge station operation area charge requirement, n is to become
Depressor number of units.
Light, storage Construction and operation totle drilling cost objective function are minC∑=min (CPV+CB+CC_PV+CC_EV+CC_BA+CG)；
The quantity of photovoltaic cell quantity, energy-storage battery quantity and energy storage unsteady flow module in light, storage Construction and operation totle drilling cost
Constraint condition is：
In formula, CPVFor photovoltaic cell cost, CBFor energy-storage battery cost, CC_PVFor photovoltaic unsteady flow module cost, CC_EVTo fill
Electric module cost, CC_BAFor energy storage unsteady flow module cost, CGFor purchases strategies；NPV.maxFor photovoltaic cell maximum quantity, NB.maxFor
Energy-storage battery maximum quantity, NC_BA.maxFor energy storage unsteady flow module maximum quantity.
Photovoltaic resources utilization rate objective function：
Meet in photovoltaic resources utilization rate function and is constrained to：
1) to guarantee the power supply reliability in charging station, should expire between photovoltaic array capacity and charging demand for electric vehicles
Foot：
∑PPV≤ 45% × ∑ PEV
It 2) is to meet charging station charge requirement, the photovoltaic generation power P that charging station system absorbsPV(t), electric car charges
Power PEV(t), electrical power P is filled and (is put) in energy storageB(t) and from power distribution network power P is absorbedG(t) equilibrium relation should be met：
Energy-storage battery charged state：PPV(t)ηC_PV=PEV(t)/ηC_EV+PB(t)/ηC_BA
When energy-storage battery is in discharge condition：PEV(t)/ηC_EV=PPV(t)ηC_PV+PB(t)ηC_BA+PG(t)
In formula, ηC_PV、ηC_EV、ηC_BAThe respectively working efficiency of photovoltaic unsteady flow module, energy-storage module, energy storage unsteady flow module.
3) constraint condition of the total electricity of energy-storage battery group is in charging station：EB.min≤EB(t)≤EEB·maxIn formula, EB·max
For the maximum allowable capacity of energy-storage battery；EB·minFor energy-storage battery minimum allowable capacity.
Basic data described in step 2 includes：
1) idle running when typical transformer Construction and operation, load running and primary construction parameter；
2) the illumination statistical data of photovoltaic charge station region, for calculating the photovoltaic power generation in photovoltaic charge station region
Amount；
3) daily charge requirement amount of the photovoltaic charge station region at upper 1 year, for predicting that subsequent electric car fills
Power consumption demand；
4) occupied area of photovoltaic charge station；
5) component parameter, including unit price, service life, efficiency and rated capacity are respectively built in photovoltaic charge station.
The present invention has beneficial effect following prominent：
The present invention considers that photovoltaic power output randomness and fluctuation and photovoltaic are incorporated to after traditional electric automobile charging station to confession
The influence of electric reliability, so the present invention considers photovoltaic resources utilization efficiency to meet the feature of environmental protection in the configuration of charging station inner capacities
Requirement, investment cost and operating cost minimum meets economy in photovoltaic charge station, and transformer capacity is based on Optimal load coefficient
Selection meets power supply reliability, realizes the association between photovoltaic array, energy storage and transformer three's capacity based on energy control strategy
Tuning realizes the economic and environment-friendly and reliable fortune of photovoltaic charge station to the equipment of the fair amount, capacity that configure in station the most
Row.
The present invention uses NSGA-II algorithm, which proposes quick non-dominated ranking, introduces elitism strategy, Neng Goubao
The diversity of the last optimization population of card, makes the result solved under the conditions of above-mentioned objective function and constraint have more reasonability, generality.
The NSGA-II algorithm that the present invention uses proposes quick non-dominated ranking algorithm, on the one hand reduces the complexity of calculating, another
It merges parent population with progeny population to aspect, so that follow-on population is chosen from double space, from
And remain all individuals the most outstanding；The NSGA-II algorithm that the present invention uses introduces elitism strategy, guarantees certain excellent
Population at individual will not be dropped during evolution, to improve the precision of optimum results；The NSGA-II that the present invention uses is calculated
Method uses crowding and crowding comparison operator, not only overcomes the defect that artificially specified shared parameter is needed in NSGA, and
As the standard of comparison between individual in population, so that a physical efficiency in the domain Pareto extends equally to entire Pareto
Domain ensure that the diversity of population.
The present invention is run with transformer in Optimal load coefficient, photovoltaic charge station system according to charge requirement in standing
The comprehensive method of investment, operating cost is minimum and distributed photovoltaic power generation utilization rate is up to target, constructs containing photovoltaic generating system
The objective function of electric automobile charging station capacity optimization.According to charge power demand and photovoltaic power output basic data, optimization aim
Power-balance condition and the energy-storage battery energy storage under rated capacity, depth of discharge constraint that the Optimal Configuration Method of setting need to meet
Complete energy exchange strategy is established in the constraint of electricity.
It is excellent that the present invention first determines that light, storage, transformer three's capacity based on energy control strategy coordinate and optimize system progress
Change the objective function used needed for configuration, the performance parameter comprising system cost and power in objective function, then determines preset
The constraint condition of performance parameter, and the basic data for being used to indicate performance parameter value accordingly is obtained, then according to basic number
According to and constraint condition calculating target function, two groups of configuration knots closest to target are arranged from optimum results according to use demand
Fruit, and hardware configuration is carried out to photovoltaic charge station according to target configuration result, it can be obtained by considering construction cost in this way
In the case of, for corresponding optimal hardware configuration scheme under different photovoltaic utilization rates, different transformer load rates.
The present invention is larger suitable for electric car demand, the Urban Areas of illumination resource abundance, for building a kind of base
The electric automobile charging station containing photovoltaic system of light, storage, transformer three's capacity coordination optimization in the EnergyPolicy the considerations of, to build
If capacity configuration provides theoretical foundation when charging station, the economy of charging station Construction and operation is improved, improves the steady of charging station operation
It is qualitative and more effective using the photovoltaic resources guarantee feature of environmental protection according to demand, it is economic and environment-friendly reliably to meet what current social developed
Demand.Theoretical foundation and technical support are provided for the electric automobile charging station Construction and operation containing photovoltaic generating system, guarantees charging
It stands economy, the feature of environmental protection and the reliability of Construction and operation.
Detailed description of the invention
Fig. 1 is that photovoltaic charge station planning construction area light shines intensity data in embodiment；
Fig. 2 is the day charge capacity demand of electric car in photovoltaic charge station institute coverage in embodiment；
Fig. 3 is optimization algorithm operational flow diagram in embodiment.
Fig. 4 is in embodiment by Pareto disaggregation in NSGA-II optimization algorithm optimization such as Fig. 4.
Specific embodiment
Below in conjunction with the accompanying drawings and embodiment the invention will be further described.
Embodiment
With somewhere (32 ° of north latitude, 118 ° of 14' east longitude 48') planning construction 1500m2For photovoltaic charge station：
Step 1, the objective function for determining photovoltaic charge station include：
1) transformer year comprehensive cost function：C1=Cd+Cs+Ct
Transformer year, comprehensive cost constraint condition was：
Transformer capacity lower limit meets electric car charging peak load demand S in charging stationb≥SL/n；
The transformer capacity upper limit is when selecting 2 or when 3 transformers, wherein when stoppages in transit, another or 2 transformers appearance
Amount is no more than peak load in planning region：Sb≤SLOr Sb≤SL/2。
S in formulabFor single transformer capacity, SLFor the maximum apparent energy of photovoltaic charge station operation area charge requirement, n
For transformer number of units.
Wherein transformer investment cost is
I is discount rate in formula, m is service life, n is transformer number of units, SbFor the capacity of single transformer, a and b are normal
Number is fitted by transformer in typical charge station using data.
Transformer year, running wastage expense was
P in formula0For the no-load loss (kW) of transformer, PkIt is run in year for what transformer load loss (kW), t were transformer
Hourage, τmaxHourage, β are lost for transformer peak load1For electric monovalent (member/kWh).And P0=a0+b0Sb、Pk=akSb
+bkSb 2, wherein a0、b0、ak、bkFor constant, it is fitted respectively by transformer typical case's operation data.
Interruption cost refers in charging station that electricity consumption can only be to power grid power purchase, and at this time since failure is unable to satisfy charging
Economic loss caused by charge requirement is in standing
Ct=n [SLf-(n-1)Sb]cosθβ2。
T is that every transformer fault overhauls power off time, f=T in formulamax/ 8760 be rate of load condensate, and cos θ is power factor,
Take 0.9, β2For electricity production ratio.
Corresponding load factor can be obtained according to the objective function of above-mentioned transformer synthesis expense and constraint condition arrangement：
So as to acquire selected transformer capacity Sb=SL/n/γ。
2) light, storage Construction and operation totle drilling cost function：min C∑=min (CPV+CB+CC_PV+CC_EV+CC_BA+CG)。
Wherein each parameter expression is：
In formula, NPV、NB、NC_PV、NC_EV、NC_BARespectively photovoltaic cell, energy-storage battery, photovoltaic unsteady flow module, charging mould
Block, energy storage unsteady flow module；C1、C2、C3、C4、C5It is respectively monovalent；q1、q2、q3、q4、q5For corresponding operation and maintenance cost；u
Indicate that energy-storage battery energy superseded every year accounts for the ratio of energy storage total amount.
Photovoltaic array, energy storage device are mainly photovoltaic cell quantity, energy-storage battery quantity, storage at the decision variable of this part
The quantity of energy unsteady flow module, the constraint condition that they meet are：
Wherein photovoltaic cell maximum quantity NPV.max, energy-storage battery maximum quantity NB.maxWith energy storage unsteady flow module maximum quantity
NC_BA.maxDepending on three is by actual conditions, the maximum quantity of photovoltaic cell is limited by occupied area, energy-storage battery and unsteady flow mould
The quantity of block is configured according to charging demand for electric vehicles, to reduce the search space of algorithm operation.
3) photovoltaic resources utilization rate function：
Meet in photovoltaic resources utilization rate function and is constrained to：
A) to guarantee the power supply reliability in charging station, should expire between photovoltaic array capacity and charging demand for electric vehicles
Foot：
∑PPV≤ 45% × ∑ PEV°
It b) is to meet charging station charge requirement, the photovoltaic generation power P that charging station system absorbsPV(t), electric car charges
Power PEV(t), electrical power P is filled and (is put) in energy storageB(t) and from power distribution network power P is absorbedG(t) equilibrium relation should be met：
Energy-storage battery charged state：PPV(t)ηC_PV=PEV(t)/ηC_EV+PB(t)/ηC_BA；
When energy-storage battery is in discharge condition：PEV(t)/ηC_EV=PPV(t)ηC_PV+PB(t)ηC_BA+PG(t)。
In formula, ηC_PV、ηC_EV、ηC_BAThe respectively working efficiency of photovoltaic unsteady flow module, energy-storage module, energy storage unsteady flow module.
C) energy-storage battery is, in sunshine abundance, to can store the more of extra photovoltaic cell for realizing energy adjustment
Remaining power generation electricity；In sunshine deficiency, then output is charged to electric car.Therefore in charging station energy-storage battery group it is total
Electricity is continually changing, but total electricity is also to be changed in a certain range：EB.min≤EB(t)≤EB.max。
In formula, EB.maxFor the maximum allowable capacity of energy-storage battery；EB.minFor energy-storage battery minimum allowable capacity, EB·minFor storage
Energy battery minimum allowable capacity, is determined by maximum depth of discharge.
Step 2 obtains photovoltaic charge stationBasic data, determine photovoltaic charge station constraint condition.
1) by 1 transformer year of table investment cost and 2 transformer station high-voltage side bus parameter of table, it is fitted transformer year comprehensive cost function
Middle constant amount；
1 transformer year comprehensive method of investment expense of table
A+bS can be obtained using simple regression the Fitting CalculationT=67170+183.8ST。
2 transformer station high-voltage side bus parameter of table
It is obtained using curve matching：No-load loss P0=a0+b0Sb=0.106+0.001747Sb,
Load loss Pk=akSb+bkSb 2=(14.353Sb-0.007666Sb 2)/103。
Obtain a, b, a0、b0、ak、bkEach constant parameter value.
2) it collects statistics photovoltaic charge station planning construction area light and shines intensity data such as Fig. 1, it is photovoltaic charged for calculating
It stands the photovoltaic power generation quantity in region.
3) investigation counts day charge capacity demand such as Fig. 2 of electric car in photovoltaic charge station institute coverage.
4) the standard configuration parameter of each component units such as table 3 in photovoltaic charge station, including unit price, service life, efficiency and rated capacity.
3 photovoltaic charge station of table builds each system parameter
Step 3, according to the basic data and basic data in step 2, optimize with NSGA-II multi-objective genetic algorithm and walk
Objective function in rapid 1, obtains optimum results；Specific algorithm operational process such as Fig. 3.
NSGA-II has the following advantages：
1) quick non-dominated ranking algorithm is proposed, on the one hand reduces the complexity of calculating, on the other hand it is by parent
Population merges with progeny population, so that follow-on population is chosen from double space, to remain the most
Outstanding all individuals.
2) elitism strategy is introduced, guarantees that certain excellent population at individual will not be dropped during evolution, to improve
The precision of optimum results.
3) crowding and crowding comparison operator are used, not only overcomes and needs artificially to specify lacking for shared parameter in NSGA
It falls into, and as the standard of comparison between individual in population, so that a physical efficiency in the domain Pareto extends equally to entirely
The domain Pareto ensure that the diversity of population.
The calculation process of objective function is：
1) initial light of 8760h is inputted according to amount of radiation and one day workload demand data of electric car charging per hour.
2) photovoltaic output power and electric car power demand hourly are calculated.
3) bound of decision variable is determined according to the occupied area of construction area and charge requirement etc..
4) according to the charge-discharge energy exchanging policy model of energy-storage system, calculate the charge-discharge electric power of pure energy storage per hour and
The power absorbed from power grid.
5) electricity of energy-storage system per hour, the electricity that the electricity and power distribution network of electric car charging absorb are calculated.
6) annual maximum load utilization hours number is calculated according to required electric car charge capacity.
7) according to the limitation of different number of units transformers, transformer load rate is calculated separately；The work of analyzing influence transformer exists
Factor under Optimal load coefficient；According to obtained Optimal load coefficient, utilize what is needed to configure in load factor formula calculating charging station
Transformer capacity.
8) constraint that photovoltaic generation power is added between the load power size that charges and energy-storage battery charge capacity it is upper and lower
Limit, advanced optimizes data result.
9) charging station Construction and operation cost and photovoltaic resources utilization rate are calculated.
10) according to construction needs, hardware in corresponding charging station can how much be obtained from cost size or photovoltaic utilization rate
The configuration of equipment.
By being obtained after the optimization of NSGA-II optimization algorithm such as Pareto disaggregation in Fig. 4, the Pareto solution which obtains
Collection is evenly distributed in extensive range, and from the point of view of optimum results, photovoltaic resources utilization rate and charging station construction cost are under constraint condition
A series of good disaggregation can be obtained, if policymaker pays the utmost attention to photovoltaic resources utilization rate, opposite construction cost can be improved,
If only considering Optimum cost, photovoltaic resources cannot be made full use of, so policymaker needs according to different integrated photovoltaics
Under the construction demand of electric automobile charging station, many factors are comprehensively considered, configure the electronic vapour of integrated photovoltaic the most suitable
The requirement of vehicle charging station.
Step 4, according to optimum results in step 3, photovoltaic resources are made full use of while construction cost is optimal, by investing
Most reasonable construction demand is chosen in person's construction investment budget, corresponding hard to carrying out in photovoltaic electric vehicle charging station according to construction demand
The configuration of part facility.
According to optimum results in step 3, consider that configuration data of device is such as under 10%, 30% and 50% photovoltaic resources utilization rate
Table 4.
Arrangements under the different photovoltaic resources utilization rates of table 4
From the data in the table when photovoltaic resources utilization rate lower (10%), at this time without configuring energy-storage system, photovoltaic
Generated energy directly meets charge requirement in station；And under 30% and 50% photovoltaic resources utilization rate, with photovoltaic cell component quantity
Increase, corresponding energy storage and unsteady flow module number will also increase accordingly, and photovoltaic charge station construction cost can also improve.Base area
Section planning construction requirements, by the configuration of Fig. 4 optimum results from considering that economy is optimal or photovoltaic resources maximally utilize angle,
To the photovoltaic charged fried interior corresponding hardware device configuration of progress.
The Optimal load coefficient recommendation for selecting different number of units transformers is calculated according to optimum results in step 3, so as to
Need the transformer capacity value of selection.Optimal load coefficient value when Liang Tai and three transformer of installation is provided in table 4.
Optimal load coefficient recommendation when table 4 installs transformer
Data are that transformer is produced electricity than (member/kWh) in table, install the data of Liang Tai and three transformer by table 4 it is found that becoming
The selection of depressor capacity is with number of working hours based on maximum load and electricity production than related.As electricity production is than increasing, the transformation of option and installment
Device capacity should be gradually increased to reduce interruption cost；When number of working hours based on maximum load increases, distribution should be also increased accordingly
Transformer capacity is to reduce load loss expense.
The present invention considers that photovoltaic power output randomness and fluctuation and photovoltaic are incorporated to after traditional electric automobile charging station to confession
The influence of electric reliability, so the present invention considers photovoltaic resources utilization efficiency to meet the feature of environmental protection in the configuration of charging station inner capacities
Requirement, investment cost and operating cost minimum meets economy in photovoltaic charge station, and transformer capacity is based on Optimal load coefficient
Selection meets power supply reliability, realizes the association between photovoltaic array, energy storage and transformer three's capacity based on energy control strategy
Tuning realizes the economic and environment-friendly and reliable fortune of photovoltaic charge station to the equipment of the fair amount, capacity that configure in station the most
Row.
The present invention is suitable for the city of all kinds of vehicle charging stations containing photovoltaic electric, realizes the light based on energy control strategy
Storage becomes the photovoltaic charge station Optimal Configuration Method of three's capacity coordination optimization；For the electric automobile charging station containing photovoltaic generating system
Construction and operation provides theoretical foundation and technical support, guarantees economy, the feature of environmental protection and the reliability of charging station Construction and operation.
The above are preferred embodiments of the present invention, all any changes made according to the technical solution of the present invention, and generated function is made
When with range without departing from technical solution of the present invention, all belong to the scope of protection of the present invention.
Claims (5)
1. a kind of photovoltaic charge station light, storage, transformer capacity coordinate and optimize configuration method, which is characterized in that specific step is as follows：
Step 1, the objective function for determining photovoltaic charge station, the objective function include：Transformer year comprehensive cost objective function
With light, storage Construction and operation totle drilling cost objective function and photovoltaic resources utilization rate objective function；
Step 2, the basic data for obtaining photovoltaic charge station, determine photovoltaic electric vehicle charging station constraint condition；
Step 3, according to the basic data and basic data in step 2, with NSGA-II multi-objective genetic algorithm Optimization Steps 1
Middle objective function, obtains optimum results；
Step 4, according to optimum results in step 3, photovoltaic resources are made full use of while construction cost is optimal, are built by investor
If investment budgey chooses most reasonable construction demand, set according to construction demand to corresponding hardware is carried out in photovoltaic electric vehicle charging station
Apply configuration.
2. photovoltaic charge station light according to claim 1, storage, transformer capacity coordinate and optimize configuration method, feature exists
In, transformer year comprehensive cost function be：C1=Cd+Cs+Ct；
Transformer year, comprehensive cost constraint condition was：
Transformer capacity lower limit meets electric car charging peak load demand S in charging stationb≥SL/n；
The transformer capacity upper limit is when selecting 2 or when 3 transformers, wherein when a stoppage in transit, another or 2 transformer capacities are not
More than peak load in planning region：Sb≤SLOr Sb≤SL/2；
In formula：C in formulad、Cs、CtRespectively loss of outage in transformer investment cost, year running wastage expense and photovoltaic charge station
Expense, SbFor single transformer capacity, SLFor the maximum apparent energy of photovoltaic charge station operation area charge requirement, n is transformer
Number of units.
3. photovoltaic charge station light according to claim 1, storage, transformer capacity coordinate and optimize configuration method, feature exists
In light, storage Construction and operation totle drilling cost function are minCΣ=min (CPV+CB+CC_PV+CC_EV+CC_BA+CG)；
The constraint of the quantity of photovoltaic cell quantity, energy-storage battery quantity and energy storage unsteady flow module in light, storage Construction and operation totle drilling cost
Condition is：
C in formulaPVFor photovoltaic cell cost, CBFor energy-storage battery cost, CC_PVFor photovoltaic unsteady flow module cost, CC_EVFor the mould that charges
Block cost, CC_BAFor energy storage unsteady flow module cost, CGFor purchases strategies；NPV.maxFor photovoltaic cell maximum quantity, NB.maxFor energy storage
Battery maximum quantity, NC_BA.maxFor energy storage unsteady flow module maximum quantity.
4. photovoltaic charge station light according to claim 1, storage, transformer capacity coordinate and optimize configuration method, feature exists
In photovoltaic resources utilization rate function：
Meet in photovoltaic resources utilization rate function and is constrained to：
1) to guarantee the power supply reliability in charging station, should meet between photovoltaic array capacity and charging demand for electric vehicles：
ΣPPV≤ 45% × Σ PEV；
It 2) is to meet charging station charge requirement, the photovoltaic generation power P that charging station system absorbsPV(t), electric car charge power
PEV(t), electrical power P is filled and (is put) in energy storageB(t) and from power distribution network power P is absorbedG(t) equilibrium relation should be met：
Energy-storage battery charged state：PPV(t)ηC_PV=PEV(t)/ηC_EV+PB(t)/ηC_BA
When energy-storage battery is in discharge condition：PEV(t)/ηC_EV=PPV(t)ηC_PV+PB(t)ηC_BA+PG(t)
In formula, ηC_PV、ηC_EV、ηC_BAThe respectively working efficiency of photovoltaic unsteady flow module, energy-storage module, energy storage unsteady flow module.
3) constraint condition of the total electricity of energy-storage battery group is in charging station：EB·min≤EB(t)≤EB·max；In formula, EB·maxFor storage
It can the maximum allowable capacity of battery；EB·minFor energy-storage battery minimum allowable capacity.
5. photovoltaic charge station light according to claim 1, storage, transformer capacity coordinate and optimize configuration method, feature exists
In basic data described in step 2 includes：
1) idle running when typical transformer Construction and operation, load running and primary construction parameter；
2) the illumination statistical data of photovoltaic charge station region, for calculating the photovoltaic power generation quantity in photovoltaic charge station region；
3) daily charge requirement amount of the photovoltaic charge station region at upper 1 year, for predicting subsequent electric car charging electricity
Amount demand；
4) occupied area of photovoltaic charge station；
5) component parameter, including unit price, service life, efficiency and rated capacity are respectively built in photovoltaic charge station.
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