CN106965688A - A kind of charging electric vehicle method under power network and the network of communication lines cooperative surroundings - Google Patents

A kind of charging electric vehicle method under power network and the network of communication lines cooperative surroundings Download PDF

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Publication number
CN106965688A
CN106965688A CN201710159464.0A CN201710159464A CN106965688A CN 106965688 A CN106965688 A CN 106965688A CN 201710159464 A CN201710159464 A CN 201710159464A CN 106965688 A CN106965688 A CN 106965688A
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network
charging
electric automobile
communication lines
driving path
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吴英俊
江星洵
梁欣怡
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Nanjing Post and Telecommunication University
Nanjing University of Posts and Telecommunications
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Nanjing Post and Telecommunication University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/64—Optimising energy costs, e.g. responding to electricity rates
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/70—Interactions with external data bases, e.g. traffic centres
    • B60L2240/72—Charging station selection relying on external data
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/12—Electric charging stations

Abstract

The invention discloses a kind of charging electric vehicle method under power network and network of communication lines cooperative surroundings, including：Input electric automobile data, network of communication lines vehicle flowrate data, distribution network data, electricity price information；Set up the mileage model of electric automobile；Combining geographic information calculates electric automobile current location to destination and destination and the shortest route of its nearest charging station, and judges whether electric automobile needs charging；It is time-consuming according to the financial cost or charging that calculate each driving path, or according to the optimal solution that object function is tried to achieve is set up, select charging electric vehicle driving path；Network of communication lines vehicle flowrate Optimized model is set up, and sets up power distribution network optimal operation model, row constraint is entered to selected charging electric vehicle driving path；The processing of three target optimizations is carried out to the charging driving path of electric automobile, final charging driving path is obtained.The present invention can take into full account Operation of Electric Systems requirement and network of communication lines traffic requirement, ensure power system and the normal operation of traffic system.

Description

A kind of charging electric vehicle method under power network and the network of communication lines cooperative surroundings
Technical field
The present invention relates to a kind of charging electric vehicle method under power network and network of communication lines cooperative surroundings, belong to power system fortune Row and the technical field of control.
Background technology
It is expected that after 2015, China's electric automobile recoverable amount is up to 2,660,000, even more many.If each electronic vapour The power of car is calculated according to 20, then, total capacity will at least reach 6.32x107kW, moreover, its predicted value can have rising to become Gesture.It will thus be seen that electric automobile is after following extensive access power distribution network, its total capacity requirement to power network will be very huge Greatly, there may be enormous impact to existing operation of power networks.In addition its discharge and recharge power load distributing over time and space random Property, the interest with V2G technologies, it will cause the network load of certain time period to sharply increase, installed capacity increased dramatically, some Original transmission and distribution networkses must increase-volume increment could meet the demand of newly-increased energy.Therefore, the electricity of labor electric automobile Can demand and its load distribution character, to the load prediction in future city, power Transmission, infrastructure construction planning etc. each Aspect all has great importance.
It is general using centralized prioritization scheme to the research approach of electric car electric energy, i.e., by electric automobile group, power network, friendship Logical net can be rated as the entirety of a unified operation, be carried out by same control centre.But, this hypothesis obviously with traffic system, The operation of electric power networks is actually inconsistent.In fact, electric automobile, traffic system, electric power networks, are three different portions Point, its method of operation is acted on by three different control centres, and electric automobile is by people, and transportation network is by traffic department, electricity Power network is by power department control.
And after electric automobile turns into main means of transport, power system of advocating peace to electric automobile and the network of communication lines are generated New the problem of.On the one hand, each electric automobile car owner can consider in a distributed manner, how to select an optimal charge path, make trip Spend money or the charging interval is most short；On the other hand, power system and the network of communication lines need to avoid electric automobile from largely concentrating on some On charging station and a certain section of road, to avoid a series of electrical problems and network of communication lines congestion problems.
In order to solve problem above, it is necessary to when designing charging electric vehicle path, be made separate decisions by each electric automobile, The method cooperateed with using distributed coordination, sets up " power distribution network-electric automobile-network of communication lines " emerging system optimized mathematical model.
The content of the invention
The technical problems to be solved by the invention are to overcome the deficiencies in the prior art to assist there is provided a kind of power network and the network of communication lines With the charging electric vehicle method under environment, existing charging electric vehicle method is solved typically using centralized prioritization scheme, Distributed AC servo system can not be realized, it is impossible to select while an optimal charge path so that power system and the network of communication lines avoid one be Row electrical problems and network of communication lines congestion, accomplish the problem of accurate control and decision-making.
It is of the invention specific using following technical scheme solution above-mentioned technical problem：
A kind of charging electric vehicle method under power network and the network of communication lines cooperative surroundings, comprises the following steps：
Step 1, input electric automobile data, network of communication lines vehicle flowrate data, distribution network data, electricity price information；
Step 2, every kilometer of average energy consumption according to electric automobile in the electric automobile data of input and initial energy storage, set up The mileage model of electric automobile；
Step 3, according to mileage model is set up in step 2, combining geographic information calculates electric automobile present bit Put to the shortest route of destination and destination and the shortest route of its closest charging station, and judge whether electric automobile needs Charge；
Step 4, traversal electric automobile go to whole driving paths of any charging station again to destination, according to each row of calculating Financial cost or the charging for sailing path are time-consuming, or set up object function according to average financial cost and average charge are time-consuming and tried to achieve Optimal solution, select charging electric vehicle driving path；
Step 5, using the macroscopical stationary stream amount critical vehicle number in each section of the network of communication lines as constraints, set up network of communication lines vehicle flowrate excellent Change model, and according to the network of communication lines vehicle flowrate Optimized model set up to the selected charging electric vehicle driving path of step 4 Enter row constraint；
Step 6, according to the constraint of each node capacity of power distribution network and operation loss of power grids, set up power distribution network optimal operation model, And according to the power distribution network optimal operation model set up with the minimum target of operation loss of power grids electronic vapour selected to step 4 Car charging driving path enters row constraint；
To electric automobile in step 7, charging electric vehicle driving path and step 5, step 6 according to selected by step 4 The constraint of charging driving path, the processing of three target optimizations is carried out to the charging driving path of electric automobile, obtains final electronic Automobile charging driving path.
Further, as a preferred technical solution of the present invention, the step 2 is set up in the wheeled of electric automobile Journey model is specially：
Wherein,For the mileage of electric automobile；For the initial energy storage of electric automobile；For electric automobile Every kilometer of average energy consumption.
Further, as a preferred technical solution of the present invention, the step 4 calculate each driving path it is economical into This uses formula：
Wherein,WithElectric automobile i capacity, initial energy storage and every kilometer of average energy consumption is represented,For Electric automobile i to charging station j traveling distance,For charging station j to destination traveling distance, CaveFor standard electricity price, CjtFor Spot Prices of the charging station j in moment t.
Further, as a preferred technical solution of the present invention, constraints is in the step 5：The network of communication lines is each The hourly traffic volume sum in section is less than the macroscopical net flow of network when the net truck kilometer number STD in key area reaches maximum.
Further, as a preferred technical solution of the present invention, the step 5 sets up network of communication lines vehicle flowrate optimization mould Type is specially：
Wherein, STD is the net truck kilometer number in emphasis region；ApqFor PathpqThe hourly traffic volume in section, and ApqLess than section PathpqThe maximum traffic capacityLpqFor section PathpqLength.
Further, as a preferred technical solution of the present invention, the step 6 sets up power distribution network optimal operation model Specially：
Wherein, Δ t is time in counting period, PLOSSIt is the active loss of power distribution network, RlIt is the resistance of each power network line, It is the longitudinal component and cross stream component of each branch current, t respectivelymaxMost end time point is represented, l is branch road number, and B is represented Circuitry number.
The present invention uses above-mentioned technical proposal, can produce following technique effect：
Charging electric vehicle method under power network and network of communication lines cooperative surroundings that the present invention is provided, is that electric automobile car owner carries For an optimal charge path, be conducive to the trip requirements of car owner, and take into full account Operation of Electric Systems requirement and the network of communication lines Traffic requirement, has ensured power system and the normal operation of traffic system.Further, since in reality, electric automobile, traffic system System, electric power networks, are three different parts, and its method of operation is acted on by three different control centres, electric automobile By people, transportation network is by traffic department, the characteristics of electric power networks are controlled by power department, and the present invention is than centralized optimization side Case, i.e., can be rated as electric automobile group, power network, the network of communication lines entirety of one unified operation, the side carried out by same control centre It is more practical for method.The present invention combines traffic conditions and power distribution network situation and carries out charge path to extensive electric automobile Planning, and the method made separate decisions using each electric automobile, are provided charging electric vehicle strategy, can quickly and efficiently realized Charging electric vehicle policy control.
Brief description of the drawings
Fig. 1 is the schematic flow sheet of the charging electric vehicle method under power network of the present invention and network of communication lines cooperative surroundings.
Fig. 2 is network of communication lines configuration schematic diagram of the present invention by taking Nanjing as an example.
Fig. 3 is the electric network composition schematic diagram of power distribution network in the present invention.
Embodiment
Embodiments of the present invention are described with reference to Figure of description.
As shown in figure 1, the present invention proposes a kind of charging electric vehicle method under power network and network of communication lines cooperative surroundings, the party Method specifically includes following steps：
Step 1, input electric automobile data, network of communication lines vehicle flowrate data, distribution network data, electricity price information.
First, electric automobile data are inputted：Electric automobile i=1 capacityInitial energy storageEvery kilometer of average energy ConsumptionSecondly, network of communication lines vehicle flowrate data are inputted：Road network topology figure, link length, each road traffic；And input is matched somebody with somebody Electric network data：Each node injection is active, each node injects idle, voltage magnitude, specific voltage phase angle；And electricity price information：Peak Paddy electricity is taken and average electricity price.
Wherein, electric automobile data are specifically as shown in table 1；Traffic network data is specific such as table 2,3,4, wherein the Zhong Jiang roads of table 2 Waypoint is divided into the 1st class, and charge point is used as the 2nd class；And table 3 provide charge point specifically have A14, A20, A27, A28, C10, C13, C16, C19, C23, E2, E5, E8, E13, E16, G2 etc.；And table 4 is provided under different branch, first point of road topology side and second Point, and road are long, and the specific arrangement of the traffic network data is by taking the map of Nanjing as an example, and it is specifically distributed as shown in Fig. 2 shown in Fig. 2 A.C.E.G is that big region is divided into behind four zonules in map, and the label of each zonule, i.e. A.C.E.G are charge points With the set of road waypoint, A has at 31 points in the present embodiment, and C has at 24 points, and E has at 16 points, and G has at 3 points；Distribution network data is specific such as table 5,6 It is shown；Electricity price information is specifically as shown in table 7.
Table 1：
Table 2：
Table 3：
Table 4：
Branch road number First point of road topology side Road topology side second point Road length (unit：Km)
1 A1 A2 1.3
2 A2 A3 1.3
3 A3 A4 1
4 A4 A27 0.2
5 A27 A5 0.4
6 A5 A6 1.1
7 A6 A7 0.5
8 A7 A8 0.5
9 A8 A31 0.5
10 A9 A29 0.6
11 A29 A10 1.5
12 A10 A11 1.8
13 A11 A1 0.8
14 A11 A28 0.9
15 A28 A25 0.6
16 A25 A9 0.6
17 A25 A23 1.9
18 A23 A9 0.8
19 A23 A20 0.4
20 A20 A19 0.2
21 A19 A8 0.7
22 A19 A21 0.4
23 A19 A18 0.3
24 A18 A7 0.6
25 A18 A17 0.4
26 A17 A5 0.4
27 A17 A16 0.4
28 A16 A21 0.4
29 A16 A15 0.7
30 A15 A13 0.7
Table 5：
Table 6：
Branch road number Generate electricity Sink Resistance Reactance Susceptance No-load voltage ratio
1 1 2 0.01938 0.05917 0.0264 0
2 1 2 0.05403 0.22304 0.0246 0
3 2 3 0.04699 0.19797 0.0219 0
4 2 4 0.05811 0.17632 0.0187 0
5 2 5 0.05695 0.17388 0.0170 0
6 3 4 0.06701 0.17103 0.0173 0
7 4 5 0.01335 0.04211 0.0064 0
8 4 7 0 0.20912 0 0.9789
9 4 9 0 0.55618 0 0.9690
10 5 6 0 0.25022 0 0.9320
11 6 11 0.09498 0.19890 0 0
12 6 12 0.12291 0.25581 0 0
13 6 13 0.06615 0.13027 0 0
14 7 8 0 0.17615 0 0
15 7 9 0 0.11001 0 0
16 9 10 0.03181 0.08450 0 0
17 9 14 0.12711 0.27038 0 0
18 10 11 0.08205 0.19207 0 0
19 12 13 0.22092 0.19988 0 0
20 13 14 0.17002 0.34802 0 0
Table 7：
Step 2, every kilometer of average energy consumption according to electric automobile and initial energy storage, set up the mileage of electric automobile Model；In the present embodiment, the mileage of foundationModel is：
Wherein, as i=1,For every kilometer of average energy consumption of electric automobile, value is 0.1617；For electronic vapour The initial energy storage of car, value is 0.5.
Step 3, according to mileage model is set up in step 2, combining geographic information calculates electric automobile present bit Put to the shortest route of destination and destination and the shortest route of its closest charging station, and judge whether electric automobile needs Charge.In the present embodiment, electric automobile current location exemplified by destination is point C4, is judged in minimal path with point A12 Footpath, it is specific as follows：
Plan electric automobile need to go to the point C4 of destination from current location point A12, judge under minimal path, if energy Enough arrive at specific.Specific path profile is as shown in Fig. 2 shown in a length of table 4 in each section.
Known by existing minimal path algorithm：
That is 5.2+0.4 ＞ 3.092
Wherein, sA12- ＞ C4It is distances of the point A12 to point C4.sC4- ＞ chargePoint C4 to away from the nearest charge points of point C4 away from From.
So, by the electric automobile current location point A12 that calculates to destination point C4 shortest routes, and destination C4 It is more than mileage with the shortest route of its closest charging stationJudgement show that electric automobile needs first to fill in point A12 Electricity, then goes to the point C4 of destination.If calculate electric automobile current location point A12 to destination the most short rows of point C4 Journey, and destination C4 and its closest charging station shortest route are less than mileageThen electric automobile allows straight Connect and go to destination.
Step 4, traversal electric automobile first charge to any charging station, then go to whole driving paths of destination, according to Financial cost or the charging for calculating each driving path are time-consuming, or set up target letter according to average financial cost and average charge are time-consuming Several tried to achieve optimal solutions, select charging electric vehicle driving path.It is specific as follows：
Different needs during charging station, selection charging driving path are gone to according to electric automobile.Herein, and spend money and charge Time-consuming weight ratio coefficient is all 0.5.
The first numerical procedure provided is that traversal electric automobile first charges, thereafter point of arrival C4 charging driving path, Calculate each charging driving path financial cost.This goes to point A14 to press shortest path, after be by minimal path point of arrival C4 Example.
Calculated for financial cost：
In formula,WithElectric automobile i=1 capacity, initial energy storage and every kilometer of average energy consumption is represented,For electric automobile i=1 to charging station j=A14 distance,Destination is arrived for charging station j=A14 Distance, CaveFor standard electricity price, CJ=A14, tFor Spot Prices of the charging station j=A14 in moment t.
Therefore, YI=1, j=A14=[85%*48.5- (0.5-0.1617*1.6)] * 0.55+0.1617* (1.6+2.9) * 0.52=22.9, that is, spend money as 22.9 yuan.
All charging driving paths are traveled through, the corresponding charging of scheme for recording each charging driving path is time-consuming as shown in table 8, And obtain highest and spend money Ymax=the 39.1 and minimum Y that spends moneymin=22.9.
Table 8：
Scheme Spend money (unit：Member)
1 22.9
2 28.5
3 39.0
4 60.2
5 53.6
Thus, then can be according to minimum scheme of being spent money in table 8, it is determined that and 1 pair of the program of selection if it is desired to spend money minimum The charging electric vehicle driving path answered.
The numerical procedure of second of offer is, time-consuming to charging to calculate：
First, the path model of foundation, charging takes the distance for electric automobile i=1 to charging station j=A14Time, electric automobile i=1 filling in charging station j=A14 wait in line charging interval, electric automobile i=1 In power station j=A14 charging interval, electric automobile i=1 is from charging station j=A14 to destination distanceTime sum.
Wherein, electric automobile i=1 is in charging station j=A14 charging interval
I.e. charging was taken as 1.0121 hours.
Electric automobile i=1 is in charging station j=A14 queuing time
Charge and take 1.141 hours.
Distances of the electric automobile i=1 to charging station j=A14TimeFor electric automobile i=1 To charging station j=A14 Ge Duan roads sum.Electric automobile i=1 is from charging station j=A14 to destination distance's TimeFor electric automobile i=1 to charging station j=A14 Ge Duan roads sum.
Herein,
So, total charging is taken as TI=1, j=A14=1.141+1.0121+0.09+0.3=2.5431.
All charging driving paths are so traveled through, each scheme charging is recorded and takes as shown in table 9, and obtain highest charging consumption When Tmax=the 3.2 and time-consuming T of minimum chargingmin=2.1.
Table 9：
Scheme Charging is time-consuming (hour)
1 2.10
2 2.23
3 2.15
4 2.89
5 3.01
Thus, if it is desired to charge it is time-consuming minimum, can be according to the time-consuming scheme of minimum charging in table 9, it is determined that should with selection The corresponding charging electric vehicle driving path of scheme 1.
The third numerical procedure provided is, time-consuming according to the average financial cost and average charge of calculating, sets up target Function and the optimal solution tried to achieve, select charging electric vehicle driving path.The scheme of all charging driving paths of the procedure ergodic, And obtain the Y that averagely spends moneyaveT is taken with average chargeave, and to it is all charging driving paths scheme to financial cost and charging It is time-consuming to be weighted processing, shown in tables of data 10.
Herein, α=0.5, β=0.5.
Weight expression formula：
Thus
Table 10：
Scheme Weighted value
1 0.192
2 0.201
3 0.222
4 0.267
5 0.361
Finally, the available optimal objective required according to passenger is：
Therefore, to solve the optimization objective function, the corresponding charge path of minimum scheme is selected.
Step 5, using the macroscopical stationary stream amount critical vehicle number in each section of the network of communication lines as constraints, set up network of communication lines vehicle flowrate excellent Change model, and according to the network of communication lines vehicle flowrate Optimized model set up to the selected charging electric vehicle driving path of step 4 Enter row constraint；The network of communication lines vehicle flowrate Optimized model of foundation, aiming at makes key area (referred to the primary city zone of Nanjing city) net car Milimeter number STD reaches maximum, and constraints should be not more than the net truck kilometer number in key area for the hourly traffic volume sum in each section STD reaches maximum STDmaxWhen the macroscopical net flow of network, and the hourly traffic volume in each section should be not more than each car section Hourly traffic volume maximum.
ConstraintsThe maximum hourly traffic volume in each section is limited, electric automobile i=1 is in optimization charging circuit During footpath, it is both needed to meet the constraint to the m section that charging station j=A14 distance is included, i.e.,：
Therefore, if having the section not satisfied the constraint in the power path of electric automobile i=1 selections, the path can not OK.
Object function：
Constraints is：
Wherein, ApqFor section PathpqHourly traffic volume unit be veh/h；LpqFor section PathpqLength, unit is km；For section PathpqThe maximum traffic capacity, unit is veh/h；NV is the macroscopical net flow of network, and unit is veh, NVm To reach maximum STD corresponding to the net truck kilometer number STD in key areamaxWhen the macroscopical net flow of network, STD unit is (vehkm)/h, STDmaxMacroscopical parent map emulation can be carried out according to regional traffic detector data to obtain.P and q represent UNICOM 2 points of road, practical operation such as table 11 can be replaced with branch road number.The data of network of communication lines vehicle flowrate are as shown in table 11.
Table 11：
Road number (branch road number) Vehicle number (vehkm)/h
1 12
2 23
3 24
4 9
5 10
6 30
7 17
Make hereinBranch road 6 is then excluded, the charging of optimization is travelled route scheme and does not include by branch road 6.
Make NVm=1000, then the macroscopical net flow of the network of key area, which is met, requires.
Traversal vehicle goes to the caused road Traffic Volume change of each place charging, obtains the scheme of each charging driving path Total wheel traffic is as shown in table 12.
Table 12：
Step 6, according to the constraint of each node capacity of power distribution network and operation loss of power grids, set up power distribution network optimal operation model, And according to the power distribution network optimal operation model set up with the minimum target of operation loss of power grids electronic vapour selected to step 4 Car charging driving path enters row constraint.
Set up power distribution network optimal operation model.By IEEE14 node samples, it is considered to power network containing 14 nodes and 20 it is defeated Contain 15 charging stations and 50 electric automobiles in the range of electric line, and the power network, 50 electric automobiles are all in power distribution network section Point 2 is charged.Scheme needs electric automobile to arrange that, toward different power distribution network nodes, the distribution obtained under variant scheme need to be traveled through Network loss consumes, in case three objective optimizations are solved.
Electric network composition as shown in figure 3, electrical network parameter as shown in Table 5,6.
Distributor point capacity-constrained：
ConstraintsLimit the electric automobile number that each charging station allows.Electric automobile i=1 existsModel Enclose interior NiWhen individual charging station selects optimal charging station, selected charging station should meet the constraint.Therefore, if electric automobile I=1, the charging station of selection are not satisfied the constraint, then the selection is infeasible.
Take hereinThe scheme that the charge point that then exclusion electric automobile goes to power distribution network node 2 to be powered charges.
Operation loss of power grids is：
Wherein, Δ t is the time in counting period.
The trend constraint of circuit and the voltage magnitude bound constraint of node：
Wherein, circuitThe strength of current allowed for circuit l；U sWithFor node s voltage upper lower limit value.
Take hereinU s=1.0,Then exclude the charge point charging that electric automobile goes to power distribution network node 8 to be powered Scheme, RlIt is the resistance of each power network line,It is the longitudinal component and cross stream component of each branch current respectively, l is branch Lu Hao, B represent circuitry number.
Thus, electric automobile can only go to the non-power distribution network node 2 of the supply terminals of charge node and where power distribution network node 8 Charge point is charged.Table 13 is geographical map charge point numbering and the corresponding relation of power distribution network node.
Table 13：
Power distribution network node serial number The corresponding charge point numbering of power distribution network node
1 1、2
2 3
3 13
4 4、5
5 Nothing
6 Nothing
7 7
8 Nothing
9 Nothing
10 10、11
11 8、9
12 6
13 Nothing
14 12、14、15
Table 14 and table 15 are that IEEE14 node power distributions net goes to charge point 3 to be charged under (scheme 1) in electric automobile Node and branch data.
Table 14：
Table 15：
Now, total losses are active loss 13.393MW, reactive loss 54.54MW, and tangible loss is 56.16MVA each side Under case, loss is as shown in table 16 respectively.
Table 16：
Scheme It is lost (MVA)
1 56.16
2 58.89
3 47.89
4 60.45
5 57.65
One object function of three objective optimizations：Operation of power networks is using loss minimization as target：
Wherein, Δ t is the time in counting period.In the present embodiment, according to table 16 operation of power networks can be determined with loss minimization During for target, scheme 3 is most rational charging electric vehicle driving path.
To electric automobile in step 7, charging electric vehicle driving path and step 5, step 6 according to selected by step 4 The constraint of charging driving path, the processing of three target optimizations is carried out to the charging driving path of electric automobile, obtains final electronic Automobile charging driving path.Handled, three object function weightings handled using existing method using three target optimizations such as, Optimization processing is carried out again, and obtained charging driving path is closed the most in integrated condition in time, power consumption and distribution network data Final scheme under reason, to determine the charging driving path for obtaining final electric automobile.
To sum up, the charging electric vehicle method under the present invention is provided power network and network of communication lines cooperative surroundings, is electric automobile Car owner provide an optimal charge path, be conducive to the trip requirements of car owner, and taken into full account Operation of Electric Systems requirement and Network of communication lines traffic requirement, has ensured power system and the normal operation of traffic system.
Embodiments of the present invention are explained in detail above in conjunction with accompanying drawing, but the present invention is not limited to above-mentioned implementation Mode, can also be on the premise of present inventive concept not be departed from the knowledge that those of ordinary skill in the art possess Make a variety of changes.

Claims (6)

1. a kind of charging electric vehicle method under power network and network of communication lines cooperative surroundings, it is characterised in that comprise the following steps：
Step 1, input electric automobile data, network of communication lines vehicle flowrate data, distribution network data, electricity price information；
Step 2, according to every kilometer of average energy consumption of electric automobile and initial energy storage in the electric automobile data of input, set up electronic vapour The mileage model of car；
Step 3, according to mileage model is set up in step 2, combining geographic information calculates electric automobile current location and arrived The shortest route of destination and destination and the shortest route of its closest charging station, and judge whether electric automobile needs to fill Electricity；
Step 4, traversal electric automobile go to whole driving paths of any charging station again to destination, according to each traveling road of calculating The financial cost in footpath or charging are time-consuming, or set up object function according to average financial cost and average charge are time-consuming and tried to achieve most Excellent solution, selects charging electric vehicle driving path；
Step 5, using the macroscopical stationary stream amount critical vehicle number in each section of the network of communication lines as constraints, set up network of communication lines vehicle flowrate optimization mould Type, and the selected charging electric vehicle driving path of step 4 is carried out according to the network of communication lines vehicle flowrate Optimized model set up Constraint；
Step 6, according to the constraint of each node capacity of power distribution network and operation loss of power grids, set up power distribution network optimal operation model, and root The selected electric automobile of step 4 is filled with operation loss of power grids minimum target according to the power distribution network optimal operation model set up Electric driving path enters row constraint；
Charging in step 7, charging electric vehicle driving path and step 5, step 6 according to selected by step 4 to electric automobile The constraint of driving path, carries out three target optimizations processing to the charging driving path of electric automobile, obtains final electronic vapour Car charging driving path.
2. the charging electric vehicle method under power network and network of communication lines cooperative surroundings according to claim 1, it is characterised in that institute State step 2 and set up the mileage model of electric automobile and be specially：
D r u n i = E S O C i E a v e i
Wherein,For the mileage of electric automobile；For the initial energy storage of electric automobile；For the every of electric automobile Kilometer average energy consumption.
3. the charging electric vehicle method under power network and network of communication lines cooperative surroundings according to claim 1, it is characterised in that institute State step 4 and calculate the financial cost of each driving path and use formula：
Y i j = [ 85 %E B i - ( E S O C i - E a v e i D 0 i j ( 1 ) ) ] C j t + E a v e i ( D 0 i j ( 1 ) + D 0 i j ( 2 ) ) C a v e
Wherein,WithElectric automobile i capacity, initial energy storage and every kilometer of average energy consumption is represented,To be electronic Automobile i to charging station j traveling distance,For charging station j to destination traveling distance, CaveFor standard electricity price, CjtFor Spot Prices of the charging station j in moment t.
4. the charging electric vehicle method under power network and network of communication lines cooperative surroundings according to claim 1, it is characterised in that institute Stating constraints in step 5 is：The hourly traffic volume sum in each section of the network of communication lines is less than the net truck kilometer number STD in key area and reached The macroscopical net flow of network during maximum.
5. the charging electric vehicle method under power network and network of communication lines cooperative surroundings according to claim 1, it is characterised in that institute State step 5 and set up network of communication lines vehicle flowrate Optimized model and be specially：
max S T D = Σ p q ( A p q L p q )
Wherein, STD is the net truck kilometer number in emphasis region；ApqFor PathpqThe hourly traffic volume in section, and ApqLess than section Pathpq The maximum traffic capacityLpqFor section PathpqLength.
6. the charging electric vehicle method under power network and network of communication lines cooperative surroundings according to claim 1, it is characterised in that institute State step 6 and set up power distribution network optimal operation model and be specially：
min P L O S S = ∫ t = 0 t = t m a x Σ l = 0 B R l ( ( I a l , t ) 2 + ( I b l , t ) 2 ) Δ t
Wherein, Δ t is time in counting period, PLOSSIt is the active loss of power distribution network, RlIt is the resistance of each power network line, Point It is not the longitudinal component and cross stream component of each branch current, tmaxMost end time point is represented, l is branch road number, and B represents circuitry number.
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Application publication date: 20170721