CN109583136A - Electric car based on schedulable potentiality, which fills, changes storage one station method for establishing model - Google Patents
Electric car based on schedulable potentiality, which fills, changes storage one station method for establishing model Download PDFInfo
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Abstract
It is filled the present invention relates to a kind of electric car based on schedulable potentiality and changes storage one station method for establishing model, the fast charge station user and electrical changing station user to differ greatly for behavioral trait is respectively adopted two kinds of different approaches and models, sampled analog random distribution in Monte Carlo is carried out to the initiation of charge moment of fast charge user, daily travel number and fast charge number of users, the rapid modeling ability to extensive automobile user charging load is improved, Practical Project situation is as a result able to reflect；It is analyzed in conjunction with travel situations of the road traffic model to electric bus, engineering reality can really be reflected by analyzing vehicle average overall travel speed, the remaining capacity etc. that acquire, provide true and reliable data and new thinking for filling to change storage one station and optimize to dispatch；Be BSS and the charge and discharge behavior of ESS with schedulable potentiality, when accessing operation of power networks, have the characteristics that heterogeneity and subsystem between power flow, energy stream and information flow joint optimal operation.
Description
Technical field
The present invention relates to a kind of electric cars to fill storage technology of changing, in particular to a kind of electric car based on schedulable potentiality
It fills and changes storage one station method for establishing model.
Background technique
In recent years, electric car charging load is modeled there are mainly two types of approach, one is filled based on electric car
Power station longtime running data propose a kind of queue theory model, i.e. the arrival of hypothesis EV is Poisson process；Another kind is based on practical
Road traffic condition comprehensively considers influencing each other between EV user and highway communication, models to EV load.The first way
As long as diameter determines that relevant parameter can be completed modeling, but EV user's accuracy for being affected by traffic accidentalia compared with
It is weak；Second of approach model is more accurate, but quickly weaker to the ability of extensive EV cluster charging load prediction.
In recent years, as electric car (Electric Vehicle, EV) owning amount increases sharply, charging infrastructure
The development of construction relatively lags behind.Different from the exchanging trickle charge mode of common EV in terms of charge mode, there are three types of new services moulds
Formula has the potentiality that grow a lot.The first is direct current charge mode, and user is generally electric taxi, has the charging time short,
The characteristics of charge power is big and extends daily travel, but it is affected to battery life, needs to comprehensively consider evaluation
Its influence to battery life and power grid.Second is to change power mode, as a kind of good controllable energy source form, changes power mode
It is more suitable public transport.The third is to improve comprehensive utilization benefit, by charging station (battery charging
Station, BCS), electrical changing station (battery swapping station, BSS) and step energy-accumulating power station (energy
Storage station, ESS) integrated station mode (the Charging-Swapping-Storage Integrated that is integrated into
Station,CSSIS).CSSIS has had both the advantages of first two service mode, can optimize with power grid joint and run, where meeting
Region EV charge requirement, response load fluctuation, subtracts consumption distributed generation resource (Distributed generation, DG) power output
Few power grid operation management expense, has good development prospect.But it is less for its research at present, and focus primarily upon
The building of its moving model, it is less for the research of its Optimized Operation strategy.The structure chart of CSSIS is shown in Figure 1.
Therefore, further research is also needed to CSSIS building model.
Summary of the invention
The present invention be directed to electric cars to fill the problem of changing storage one station model construction, propose a kind of based on schedulable latent
The electric car of power, which fills, changes storage one station method for establishing model, and it is biggish for electric vehicle can to comprehensively consider a variety of behavioral differences
The accuracy of electric automobile load rapid modeling ability and modeling is taken into account at family.
The technical solution of the present invention is as follows: a kind of electric car based on schedulable potentiality, which fills, changes storage one station model foundation side
Method specifically comprises the following steps:
1) electric car is filled to change to store up and integrally be stood including electric car fast charge station, electrical changing station and step energy-accumulating power station, right respectively
It is modeled:
1.1) electric taxi traffic-operating period and other fast charge user behavior characteristics are combined, the electricity based on queuing theory is established
Electrical automobile fast charge station BCS model:
BCS power demand is as follows:
In formula, Pi,BCSIt (t) is charge power of i-th of fast charge user in the t period, KW；PBCSIt (t) is BCS in t
Total charge power of section, KW；ηBCSFor BCS fast charge machine charge efficiency, it is taken as 95% herein；Nt,BCSFor BCS the t period
The fast charge number of users of charging；
Since other fast charges user differs greatly in the operating range of different periods, only consider that the electricity of electric taxi closes
System, BCS energy relationship are as follows:
In formula, EBCSIt (t) is t-th of period BCS total electricity, EBCSIt (t-1) is the t-1 period BCS total electricity, KWh；WithCharge capacity and kwh loss of the respectively BCS within the t-1 period, KWh；
1.2) by GIS-Geographic Information System foundation based on and network topology structure, Speed-flow Relationship magnitude of traffic flow model,
Using electric bus departure time-table and line arrangements, the traveling of electric bus is determined in conjunction with speed-flow utility model
Speed, determination change power consumption and establish electrical changing station BSS model:
BSS charge power is as follows:
In formula, PBSSIt (t) is BSS in t period total charge power, KW；For PB group number in BSS；Pi,swapIt (t) is sequence
Number for i charge power of the PB t-th of period, KW；For the specified charge power of separate-box type DC charging motor, KW；For 0-1 state variable, indicate the PB of serial number i in t period charged state, be 1 if charging, otherwise for
0；NBSSFor BSS separate-box type DC charging motor number；ηBSSFor BSS separate-box type DC charging motor charge efficiency, it is taken as 95%；
BSS energy state is as follows:
In formula, EBSS(t) total electricity of the BSS t-th of period, E are indicatedBSS(t-1) indicate BSS in the t-1 period
Total electricity, KWh；PBSSIt (t-1) is BSS in t-1 period total charge power, KW；Number of segment when T is total；It is Eb
T-1 period total travel energy consumption, KWh；
1.3) assume that each group battery status is all the same in ESS, establishes step energy-accumulating power station ESS model:
In formula, PESSIt (t) is total charge-discharge electric power in t-th of the period station ESS, PESS,cIt (t) is total in t-th of the period station ESS
Charge power, PESS,dIt (t) is total discharge power in t-th of the period station ESS, KW；ηESS,c、ηESS,dRespectively energy-storage battery SB fills,
Discharging efficiency is taken as 90% here；ωc(t)、ωD(t) it is 0-1 state variable, ESS charging and discharging state is indicated, if when t
Section ESS charging then ωc(t)=1, otherwise ωD(t)=1.
ESS derivation of energy formula are as follows:
In formula, EESS(t) total electricity of the ESS t-th of period, KWh are indicated；
2) electric car fill change storage one station the total charge-discharge electric power of CSSIS it is as follows:
PCSSIS(t)=PBCS(t)+PBSS(t)+PESS(t)
In formula, PCSSISIt (t) is CSSIS in t period total charge-discharge electric power, KW；
CSSIS total energy state is as follows:
ECSSIS(t)=EBCS(t)+EBSS(t)+EESS(t)
In formula, ECSSIS(t) total electricity of the CSSIS t-th of period, KWh are indicated.It is needed completely in addition, CSSIS is operated normally
Foot periodicity constraint condition, periodical constraint condition refer to that it is periodical to be respectively necessary for the electricity met by CSS, BSS and ESS in CSSIS
Constraint, i.e., total electricity when one typical case starts day are equal to total electricity when a typical end of day；
3) it using the charge and discharge behavior of BSS and ESS as control variable, is put into Practical Project to fill and changes storage one station access electricity
Net operation, have the characteristics that heterogeneity and subsystem between power flow, energy stream and information flow combined optimization tune
Degree can obtain filling the overall power demand curve and electric quantity curve for changing that storage is integrally stood.
Step 1.1) the electric taxi traffic-operating period characteristic are as follows: obey negative in electric taxi user arrival time interval
Exponential distribution, reaching is Poisson process；
Other described fast charge user behavior characteristics: assuming that other fast charges user, which reaches behavior, obeys Poisson distribution, other are fast
It fills the daily driving range number approximation of user and obeys logarithm normal distribution, the charging process of fast charge user can use the M/ in queuing theory
G/k model modeling；Input process obeys the Poisson distribution that parameter is λ in M/G/k model, and the charging service time obeys normal state point
Cloth is desired for ET, variance DT；If assuming, the fast charge user charging time is t, DTAnd ETIt is respectively fast charge user charging
The standard deviation and expectation of time；Charging duration t, ETAnd DTIt can be acquired respectively by following formula:
In formula,For fast charge user's battery rated capacity, KWh；E(Bi,BCS) when being that i-th fast charge user reaches CSSIS
The expectation of remaining capacity；For the specified charge power of fast charge machine, KW；DTFor the variance of t；Bi,BCSIt is arrived for i-th of fast charge user
Remaining capacity when up to CSSIS, distribution function can be obtained by fast charge user's daily travel statistical data；D(Bi,BCS) it is i-th
The variance of remaining capacity when fast charge user reaches CSSIS.
The beneficial effects of the present invention are: the present invention is based on the electric car of schedulable potentiality fill change storage one station model build
Cube method, the fast charge station user and electrical changing station user to differ greatly for behavioral trait are respectively adopted two kinds of different approaches and build
Mould, while considering the accuracy of electric automobile load rapid modeling ability and modeling.Model construction process is clear, design step
It is rapid clear, there is reference value in actual engineering application, solution electric car is filled after changing storage one station access power grid and produced
The problems such as raw economy operation of power grid, is with important application value；Initiation of charge moment of the present invention to fast charge user, day row
It sails mileage number and fast charge number of users carries out Monte Carlo sampled analog random distribution, improve to extensive for electric vehicle
The rapid modeling ability of family charging load, is as a result able to reflect Practical Project situation；Present invention combination road traffic model is to electricity
The travel situations of electric bus are analyzed, and the accuracy of model is improved, and analyze the vehicle average overall travel speed acquired, residue
Electricity etc. can really reflect engineering reality, for fill change storage one station optimize dispatch provide true and reliable data
With new thinking；The present invention establishes the concept of schedulable potentiality, and electric car is filled and changes storage one station, has schedulable latent
Power is BSS and the charge and discharge behavior of ESS, and control variable is the 0-1 state variable in BSS and ESS.For in Practical Project
Fill change storage one station access operation of power networks when, schedulable potentiality be suitable for power grid carry out the subsystem with heterogeneity sum
Between power flow, energy stream and information flow joint optimal operation.
Detailed description of the invention
Fig. 1 is the structure chart of CSSIS；
Fig. 2 fills for electric car of the present invention changes storage one station model construction frame diagram；
Fig. 3 is BCS power demand product process figure of the present invention；
Fig. 4 is the schedulable Potentials flow chart of BSS of the present invention；
The city Tu5Wei Mou public bus network network schematic diagram；
Fig. 6 is Optimal Operation Model solution procedure figure of the present invention；
Fig. 7 is CSSIS power demand curves figure of the present invention；
Fig. 8 is CSSIS electric quantity curve figure of the present invention；
Fig. 9 is that BSS of the present invention orderly charges and unordered charging comparison diagram.
Specific embodiment
To be more clear the objectives, technical solutions, and advantages of the present invention, define, it is right as follows in conjunction with drawings and embodiments
The present invention is further described.
One, CSSIS is mainly by parts groups such as the control centre Zhan Nei, charge-discharge machine, electric charging system and step energy-storage systems
At composed structure is as shown in Figure 1.The control centre Zhan Nei is the control centre in the station CSSIS, can grasp station self-energy stream in real time
The quantity of states such as power flow, will stand in state feed back to the control centre Zhan Wai, can also according to the outer scheduling central dispatching plan in station or
Person's MG (micro-capacitance sensor Micro-grid) operating condition works out interior operational plan of standing.Charge-discharge machine is that energy is multidirectional inside and outside CSSIS stands
The channel of flowing is made of multipurpose converter plant.Power battery in charging station BCS and electrical changing station BSS (power battery,
It PB) is lithium battery.After PB reaches the life-cycle, energy-storage battery (storage can be converted by the PB of capacity attenuation
Battery, SB), and it is configured at step energy-accumulating power station ESS cascade utilization.Electric charging system, step energy-storage system are counted according to scheduling
It draws, electric charging arrangement and charge and discharge scheduling can be carried out respectively to power battery PB and energy-storage battery SB.
Two, as shown in Fig. 2, building electric car, which fills, changes the model that storage is integrally stood, model construction process is as follows:
(1) electric taxi traffic-operating period and other fast charge user behavior characteristics are combined, filling based on queuing theory is established
Power station BCS model.
The electric taxi traffic-operating period is analyzed as follows:
The electric taxi daily travel of large- and-medium size cities is generally 350~500km, usually divides day shift by two drivers
It is driven in turn with night shift.Under normal circumstances, electric taxi can charge when relieving, it is assumed that two changeover times point
It Wei not morning 02:00-06:00 and 14:00-18:00 in afternoon.It is analyzed according to data, electric taxi user arrival time interval
Quantum condition entropy is obeyed, therefore it is Poisson process that it, which is reached,.If electric taxi user some changeover time segment length is Tc, then
Its Parameter for Poisson Distribution λ can be acquired by following formula:
In formula, AtaxiThe electric taxi quantity in charging service region is provided for CSSIS.
Other described fast charge user behavior specificity analysis are as follows:
It is usually chosen in that charging when relieving is different from electric taxi user, the charging time selection of other fast charges user
There is no apparent feature.Pass through the analysis to survey data, it is assumed that other fast charges user reaches behavior and obeys Poisson distribution, general
Rate density function is as follows:
In formula, XtFor other fast charges user's arriving amt within t-th of period；λtFor other fast charges user in t-th of period
Arrival rate, k！It is the formula of Poisson distribution probability density function, Xt=k indicates that other fast charges user reaches number in t-th of period
Amount is k, can refer to vehicle arriving rate in certain gas station one day and is shown in Table 1.
Table 1
| Period | λ t/% | Period | λ t//% | Period | λ t//% |
| 0:00-01:00 | 1.5 | 08:00-09:00 | 31.8 | 16:00-17:00 | 37.2 |
| 01:00-02:00 | 0.9 | 09:00-10:00 | 15 | 17:00-18:00 | 21 |
| 02:00-03:00 | 0.9 | 10:00-11:00 | 15 | 18:00-19:00 | 9.6 |
| 03:00-04:00 | 0.9 | 11:00-12:00 | 15 | 19:00-20:00 | 8.4 |
| 04:00-05:00 | 0.9 | 12:00-13:00 | 15 | 20:00-21:00 | 8.4 |
| 05:00-06:00 | 3 | 13:00-14:00 | 15 | 21:00-22:00 | 6 |
| 06:00-07:00 | 21.3 | 14:00-15:00 | 9.6 | 22:00-23:00 | 3 |
| 07:00-08:00 | 21.6 | 15:00-16:00 | 36 | 23:00-0:00 | 1.8 |
Studies have shown that the daily driving range number approximation of other fast charges user obeys logarithm normal distribution, probability density letter
Number are as follows:
In formula, x is the daily driving range number of other fast charges user, μD、σDThe respectively expectation of x and variance, μD=3.2；σD
=0.88.
To sum up, the charging process of fast charge user can use the M/G/k model modeling in queuing theory.It is inputted in M/G/k model
Process obeys the Poisson distribution that parameter is λ, and charging service time Normal Distribution is desired for ET, variance DT.If assuming
Fast charge user's charging time is t, then DTAnd ETIt is respectively the standard deviation and expectation in fast charge user charging time.Charging duration t,
ETAnd DTIt can be acquired respectively by following formula:
In formula,For fast charge user's battery rated capacity, KWh；E(Bi,BCS) when being that i-th fast charge user reaches CSSIS
The expectation of remaining capacity；For the specified charge power of fast charge machine, KW；DTFor the variance of t；Bi,BCSIt is arrived for i-th of fast charge user
Remaining capacity when up to CSSIS, distribution function can be obtained by fast charge user's daily travel statistical data；D(Bi,BCS) it is i-th
The variance of remaining capacity when fast charge user reaches CSSIS.
Assuming that fast charge is invariable power charging process, while power, electricity remain unchanged in the identical period.Performance number is positive
Indicate charging, be negative expression electric discharge.BCS charge power is as follows:
In formula, Pi,BCSIt (t) is charge power of i-th of fast charge user in the t period, KW；PBCSIt (t) is BCS in t
Total charge power of section, KW；ηBCSFor BCS fast charge machine charge efficiency, it is taken as 95% herein；Nt,BCSFor BCS the t period
The fast charge number of users of charging.
Since other fast charges user differs greatly in the operating range of different periods, the electricity of electric taxi is only considered
Magnitude relation.BCS energy relationship is as follows:
In formula, EBCSIt (t) is t-th of period BCS total electricity, EBCSIt (t-1) is the t-1 period BCS total electricity, KWh；WithCharge capacity and kwh loss of the respectively BCS within the t-1 period, KWh.
Since the behavioural characteristics such as two kinds of fast charge user's daily travel mean values differ greatly, classification is carried out to it and is begged for
By.Assuming that BCS only provides fast charge service to taxi within the taxi interval of service.In order to improve model accuracy, according to queuing
M/G/k model carries out Monte Carlo sampling, obtains the power demand of two kinds of fast charge users respectively.Specific steps are as shown in Figure 3.
(2) the magnitude of traffic flow model of meter and network topology structure, Speed-flow Relationship is established by GIS-Geographic Information System, it is sharp
With electric bus departure time-table and line arrangements, the traveling speed of electric bus is determined in conjunction with speed-flow utility model
Degree, determination change power consumption and establish electrical changing station BSS model.
The magnitude of traffic flow model analysis is as follows:
As urban road traffic flow typical characteristics, speed flow models are to predict that average link speed, road-section average go out
The basic model of row time.Model expression is as follows:
In formula, m, n are respectively the beginning and end in certain section；VmnIt (t) is the electric bus t period in direct-connected section
Travel speed on (m, n), KM/h；Vmn 0For zero flow velocity degree of direct-connected section (m, n), KM/h；β is to seek Vmn(t) ginseng to be used when
Numerical value；CmnFor direct-connected section (m, the n) traffic capacity, determined by road type；qmn(t)/CmnIndicate t period direct-connected section (m,
N) saturation degree；R, a, b are parameter value under different road types；Q is the actual traffic amount in section, pcu/h (pcu=
Passenger Car Unit standard vehicle equivalents；Pcu/h is vehicle flowrate unit)；It, will not according to zero different flow velocity degree mean values
It is divided into Ι type and Ι Ι type with road type, Ι type road r, a, b distinguish value 3,1.726 and 3.150, Ι Ι type road r, a, b difference
Value 3,2.153 and 3.984.
By separate-box type DC charging motor, to the PB charging that Eb is changed, (Eb is electric bus Electric bus's to BSS
Referred to as).It may assume that simplify the analysis
I. the multiple groups PB configured on single Eb is thought of as a monolith PB.
Ii. Eb is numbered by public bus network serial number and its first round sequencing of dispatching a car.
Eb number, separate-box type DC charging motor number and spare PB number are equal in iii.BSS.
Iv. separate-box type DC charging motor is charged as invariable power charging process.
BSS charge power is as follows:
In formula, PBSSIt (t) is BSS in t period total charge power, KW；For PB group number in BSS；Pi,swapIt (t) is sequence
Number for i charge power of the PB t-th of period, KW；For the specified charge power of separate-box type DC charging motor, KW；For 0-1 state variable, indicate the PB of serial number i in t period charged state, be 1 if charging, otherwise for
0；NBSSFor BSS separate-box type DC charging motor number；ηBSSFor BSS separate-box type DC charging motor charge efficiency, it is taken as 95%.
BSS energy state is as follows:
In formula, EBSS(t) total electricity of the BSS t-th of period, E are indicatedBSS(t-1) indicate BSS in the t-1 period
Total electricity, KWh；PBSSIt (t-1) is BSS in t-1 period total charge power, KW；Number of segment when T is total；It is Eb
T-1 period total travel energy consumption, KWh.
It is analyzed in conjunction with the real road situation of certain city's public bus network, the electricity demanding of changing of BSS day part can be obtained, further
Analysis can calculate the schedulable potentiality of BSS, and specific steps are as shown in Figure 4.
(3) assume that each group battery status is all the same in ESS, establishes step energy-accumulating power station ESS model.
In formula, PESSIt (t) is total charge-discharge electric power in t-th of the period station ESS, PESS,cIt (t) is total in t-th of the period station ESS
Charge power, PESS,dIt (t) is total discharge power in t-th of the period station ESS, KW；ηESS,c、ηESS,dRespectively energy-storage battery is filled, is put
Electrical efficiency is taken as 90% here；ωc(t)、ωD(t) it is 0-1 state variable, ESS charging and discharging state is indicated, if the t period
ESS charging then ωc(t)=1, otherwise ωD(t)=1.
ESS derivation of energy formula are as follows:
In formula, EESS(t) total electricity of the ESS t-th of period, KWh are indicated.
ESS needs the constraint condition met are as follows:
I. electricity bound constrains:
In formula,For ESS stored energy capacitance limit value, KWh.
Ii. charge-discharge electric power constrains:
In formula,For the rated power of ESS, KW.
(4) the total charge-discharge electric power of CSSIS is as follows:
PCSSIS(t)=PBCS(t)+PBSS(t)+PESS(t)
In formula, PCSSISIt (t) is CSSIS in t period total charge-discharge electric power, KW.
CSSIS total energy state is as follows:
ECSSIS(t)=EBCS(t)+EBSS(t)+EESS(t)
In formula, ECSSIS(t) total electricity of the CSSIS t-th of period, KWh are indicated.It is needed completely in addition, CSSIS is operated normally
(periodical constraint condition refers to that it is periodical to be respectively necessary for the electricity met by CSS, BSS and ESS in CSSIS to foot periodicity constraint condition
Constraint, i.e., total electricity when one typical case starts day are equal to total electricity when a typical end of day).
Three, in conjunction with the concept of schedulable potentiality, become in practice using the charge and discharge behavior of BSS and ESS as control in engineering
Amount.Filled when changing the access operation of power networks of storage one station in practical projects, have the characteristics that heterogeneity and subsystem between
Power flow, energy stream and information flow joint optimal operation, and obtain filling change overall power demand curve that storage is integrally stood and
Electric quantity curve.
The present invention, which fills the electric car based on schedulable potentiality of proposition, changes the model building method application that storage is integrally stood
In actual engineering application.The present invention is based on Matlab emulation platform, changes the model that storage is integrally stood simulation results show filling
Construction method and its schedulable potentiality participate in the feasibility and validity of optimal dispatch.
Simulation Example parameter is configured first, with the real road situation of certain city's public bus network and specific power grid system
Sample calculation analysis is carried out for system.The public bus network network is made of three public bus networks, contains 19 road circuit nodes and 18 roads altogether
Road, average lane length are 3.5KM, as shown in Figure 5.For three public bus networks, totally 62 Eb provide electric charging service to BSS, stand in
Share 62 groups of spare PB, 3 change motor and 62 sets of separate-box type chargers.BCS configures 10 direct current charge machines, is charged using 3C.
Taxis quantity is 160 in the region MG.ESS capacity is 3MWh, and initial SOC is 0.6.Miniature gas turbine rated power is
2MW, blower installed capacity are 2MW, and photovoltaic installed capacity is 1MW.Fig. 6 is to change the optimal dispatch mould integrally stood of storage based on filling
Type solution procedure.
By simulation calculation, electric car can be obtained fills and change power demand curves that storage is integrally stood and electric quantity curve respectively such as
Shown in Fig. 7, Fig. 8.As seen from Figure 7, BCS reaches power requirement peaks twice, can improve load in load curve paddy
Demand reduces load curve peak-valley difference.Similar with BCS, BSS power demand curves reach peak value in the 3rd and the 86th period twice,
Play the role of for reduction load curve peak-valley difference positive.
It can be obtained by Fig. 8, the total electricity curve of electric taxi is presented apparent periodical in BCS, and the period is about total period
Several half.The minimum point of electric quantity curve just corresponds to electric taxi in BCS and hands over to the next shift time initial time, and electric quantity curve is most
High point corresponds to electric taxi in BCS and hands over to the next shift finish time time.ESS can regard load charging as in load valley,
Corona discharge can be regarded as in load curve peak period, and there is good effect to load curve is adjusted.
Electric bus is orderly in BSS, unordered influence of the charging to optimum results is as shown in Figure 9.As can be seen that BSS without
Sequence charge power demand reaches maximum value 3400kW in the load curve peak period, if will cause to power grid without Optimized Operation
The consequence on peak plus peak, the peak-valley difference of further expansion power grid.In contrast, the peak value of the orderly charge power demand of BSS is smaller,
About 2000kW.BSS, which orderly charges, simultaneously can be transferred to the charge power demand part of load curve peak period load song
The line paddy period extends the total charging duration of BSS, plays the effect of peak load shifting, and the peak-valley difference for alleviating power grid has more careless
Justice.
Electric car proposed by the present invention, which fills, changes storage one station model building method clear thinking, has good regulation effect
Fruit, it is applied widely.For filled in Practical Project change storage one station access operation of power networks when, schedulable potentiality be suitable for power grid into
Row have the characteristics that heterogeneity and subsystem between power flow, energy stream and information flow joint optimal operation.Emulation knot
Fruit shows that filling for proposition is changed after operation of power networks is accessed at storage one station and can be run with power grid joint optimization, and it is electronic to meet region
Automobile charge requirement, response load fluctuation, reduces power grid operation management expense at consumption distributed generation resource power output, for reducing electricity
Net load curve peak-valley difference is of great practical significance.
Electric car proposed by the present invention based on schedulable potentiality, which fills, changes storage one station model building method mentality of designing
Clearly, there is for complex in Practical Project in the case of good regulating effect, it is applied widely.It should be understood that
The application of the present invention is not limited to the above can more appeal explanation and be changed for those of ordinary skills
Into or transformation, all these modifications and variations should all belong to the protection domain of appended claims of the present invention.
Claims (2)
1. a kind of electric car based on schedulable potentiality, which fills, changes storage one station method for establishing model, which is characterized in that specific packet
Include following steps:
1) electric car fill change storage one station include electric car fast charge station, electrical changing station and step energy-accumulating power station, respectively to its into
Row modeling:
1.1) electric taxi traffic-operating period and other fast charge user behavior characteristics are combined, the electronic vapour based on queuing theory is established
Vehicle fast charge station BCS model:
BCS power demand is as follows:
In formula, Pi,BCSIt (t) is charge power of i-th of fast charge user in the t period, KW；PBCSIt (t) is BCS in the t period
Total charge power, KW；ηBCSFor BCS fast charge machine charge efficiency, it is taken as 95% herein；Nt,BCSIt is charging for BCS in the t period
Fast charge number of users；
Since other fast charges user differs greatly in the operating range of different periods, the electricity relationship of electric taxi is only considered,
BCS energy relationship is as follows:
In formula, EBCSIt (t) is t-th of period BCS total electricity, EBCSIt (t-1) is the t-1 period BCS total electricity, KWh；WithCharge capacity and kwh loss of the respectively BCS within the t-1 period, KWh；
1.2) by GIS-Geographic Information System establish meter and network topology structure, Speed-flow Relationship magnitude of traffic flow model, utilization
Electric bus departure time-table and line arrangements determine the travel speed of electric bus in conjunction with speed-flow utility model,
Determination changes power consumption and establishes electrical changing station BSS model:
BSS charge power is as follows:
In formula, PBSSIt (t) is BSS in t period total charge power, KW；For PB group number in BSS；Pi,swapIt (t) is serial number
Charge power of the PB of i t-th of period, KW；For the specified charge power of separate-box type DC charging motor, KW；
For 0-1 state variable, the PB of serial number i is indicated in t period charged state, is 1 if charging, is otherwise 0；NBSSFor
BSS separate-box type DC charging motor number；ηBSSFor BSS separate-box type DC charging motor charge efficiency, it is taken as 95%；
BSS energy state is as follows:
In formula, EBSS(t) total electricity of the BSS t-th of period, E are indicatedBSS(t-1) indicate BSS in total electricity of the t-1 period
Amount, KWh；PBSSIt (t-1) is BSS in t-1 period total charge power, KW；Number of segment when T is total；It is Eb in t-1
Period total travel energy consumption, KWh；
1.3) assume that each group battery status is all the same in ESS, establishes step energy-accumulating power station ESS model:
In formula, PESSIt (t) is total charge-discharge electric power in t-th of the period station ESS, PESS,cIt (t) is total charging in t-th of the period station ESS
Power, PESS,dIt (t) is total discharge power in t-th of the period station ESS, KW；ηESS,c、ηESS,dRespectively energy-storage battery SB charge and discharge
Efficiency is taken as 90% here；ωc(t)、ωD(t) it is 0-1 state variable, ESS charging and discharging state is indicated, if the t period
ESS charging then ωc(t)=1, otherwise ωD(t)=1.
ESS derivation of energy formula are as follows:
In formula, EESS(t) total electricity of the ESS t-th of period, KWh are indicated；
2) electric car fill change storage one station the total charge-discharge electric power of CSSIS it is as follows:
PCSSIS(t)=PBCS(t)+PBSS(t)+PESS(t)
In formula, PCSSISIt (t) is CSSIS in t period total charge-discharge electric power, KW；
CSSIS total energy state is as follows:
ECSSIS(t)=EBCS(t)+EBSS(t)+EESS(t)
In formula, ECSSIS(t) total electricity of the CSSIS t-th of period, KWh are indicated.It needs to meet week in addition, CSSIS is operated normally
Phase property constraint condition, periodical constraint condition refer to that CSS, BSS and ESS are respectively necessary for the electricity met periodically constraint in CSSIS,
Total electricity when i.e. one typical case starts day is equal to total electricity when a typical end of day；
3) it using the charge and discharge behavior of BSS and ESS as control variable, is put into Practical Project to fill and changes storage one station access power grid fortune
Row, have the characteristics that heterogeneity and subsystem between power flow, energy stream and information flow joint optimal operation, can
It obtains filling the overall power demand curve and electric quantity curve for changing that storage is integrally stood.
2. the electric car according to claim 1 based on schedulable potentiality, which fills, changes storage one station method for establishing model, special
Sign is, step 1.1) the electric taxi traffic-operating period characteristic are as follows: obeys negative in electric taxi user arrival time interval
Exponential distribution, reaching is Poisson process；
Other described fast charge user behavior characteristics: assuming that other fast charges user, which reaches behavior, obeys Poisson distribution, other fast charges are used
The daily driving range number approximation in family obeys logarithm normal distribution, and the charging process of fast charge user can use the M/G/k in queuing theory
Model modeling；The Poisson distribution that input process obedience parameter is λ in M/G/k model, charging service time Normal Distribution,
It is desired for ET, variance DT；If assuming, the fast charge user charging time is t, DTAnd ETIt is respectively the fast charge user charging time
Standard deviation and expectation；Charging duration t, ETAnd DTIt can be acquired respectively by following formula:
In formula,For fast charge user's battery rated capacity, KWh；E(Bi,BCS) it is residue when i-th of fast charge user reaches CSSIS
The expectation of electricity；For the specified charge power of fast charge machine, KW；DTFor the variance of t；Bi,BCSIt is reached for i-th of fast charge user
Remaining capacity when CSSIS, distribution function can be obtained by fast charge user's daily travel statistical data；D(Bi,BCS) it is fast i-th
Fill the variance of remaining capacity when user reaches CSSIS.
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