CN102521488A - Electromobile power exchanging station site selection method - Google Patents

Electromobile power exchanging station site selection method Download PDF

Info

Publication number
CN102521488A
CN102521488A CN2011103859193A CN201110385919A CN102521488A CN 102521488 A CN102521488 A CN 102521488A CN 2011103859193 A CN2011103859193 A CN 2011103859193A CN 201110385919 A CN201110385919 A CN 201110385919A CN 102521488 A CN102521488 A CN 102521488A
Authority
CN
China
Prior art keywords
changing station
electrical changing
cost
electric
station
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN2011103859193A
Other languages
Chinese (zh)
Inventor
张连宏
张勇
胥明凯
高自彬
孙英涛
王宁
丁素英
韩冬泊
高翔
李援非
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
State Grid Corp of China SGCC
Jinan Power Supply Co of State Grid Shandong Electric Power Co Ltd
Original Assignee
Jinan Power Supply Co of State Grid Shandong Electric Power Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Jinan Power Supply Co of State Grid Shandong Electric Power Co Ltd filed Critical Jinan Power Supply Co of State Grid Shandong Electric Power Co Ltd
Priority to CN2011103859193A priority Critical patent/CN102521488A/en
Publication of CN102521488A publication Critical patent/CN102521488A/en
Pending legal-status Critical Current

Links

Images

Landscapes

  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention relates to an electromobile power exchanging station site selection method, which is used for selecting sites for an electromobile power exchanging station and solves the problems of difficulty in site selection and planning of the electromobile power exchanging station. The power exchanging station site selection method gives consideration to both benefit of power station operating companies and power exchangers, leads the minimum total cost of the power station operating companies and the power exchangers to be the target function, considers traffic convenience, timeliness and power exchanging station total capacity constraint, adds constraint of hard time windows on power exchanger travelling and power exchanging total time, and selects sites for the electromobile power exchanging station. The method considers different considerations of benefit of both sides in different planning stages with the minimum total cost of the power station operating companies and the power exchangers as the target function, and selects sites for the electromobile power exchanging station in different planning stages by changing benefit weight of the power station operating companies and the power exchangers. The constraint of the hard time windows includes traveling time of a driver reaching a goal power exchanging station, queuing time and power exchanging time.

Description

A kind of electric automobile electrical changing station site selecting method
Technical field
The present invention relates to a kind of electric automobile electrical changing station site selecting method.
Background technology
Under the background that the low-carbon economy that with low energy consumption, low pollution and low emission is characteristics makes the transition, the electric automobile development receives various countries and payes attention in economic development.Chinese Government is also supporting new-energy automobile and auxiliary facility construction thereof energetically.
The electric automobile energy supplement mode has rechargeable and changes two kinds of electric formulas.Charging modes is major equipment with the charging pile, in family warehouse and charging station, to be used for the master.Yet it also has, and charging rate is slow, the duration of charging concentrated, influences defectives such as electrical network normally moves, fixed investment height.Change electric mode and be meant, with the method for the empty electric weight battery on the Full Charge Capacity battery altering automobile, come to be the electric automobile electric energy supplement through directly.As a kind of comparatively novel electric energy arbitrary way, it has the advantages that construction cost is low, operating rate is fast, battery protection is perfect, is welcoming fast-developing period.China's two big electricity provider national grids and Southern Power Grid Company have shown that all will develop from now on the electrical changing station is that main electric automobile fills the ability mode.Yet still having at home, the location problem of electrical changing station do not specialize in.
The present invention is taking into account electrical changing station operating company and is changing interests aspect two of the electric persons; And according in the division of electrically-charging equipment planning stage it being divided into different the considering of demonstration phase, public good stage and commercial operation stage interests side; Through changing electrical changing station operating company and changing two aspects of electric person interests weight and come different planning stage electric automobile electrical changing stations are carried out addressing, consider traffic convenience property and ageing simultaneously.
Summary of the invention
The object of the invention provides electric automobile electrical changing station site selecting method exactly for addressing the above problem, and is used to solve the difficult problem of addressing of electric automobile electrical changing station and planning.
For realizing above-mentioned purpose, the present invention adopts following scheme:
The present invention considers electrical changing station operating company and changes two aspect interests of electric person, is that target is analyzed with total social cost minimum.Because electric automobile market still is in demonstration phase, the convenience that changes electricity has considerable influence for the buying behavior of potential electric automobile.Therefore when considering the electrical changing station profitability, must consider the requirement when changing power consumption for each electric automobile, in the addressing process, should exchange electric person and go and change the constraint that electricity adds hard time window T.T..
A kind of electric automobile electrical changing station site selecting method, step is:
A) considering electrical changing station operating company and change two aspect interests of electric person, is that target is set up objective function with electric automobile electrical changing station total cost minimum; Total cost mainly comprises fixed cost and variable cost; The electric person of exchange goes and changes the constraint that electricity adds hard time window T.T. in the addressing process simultaneously;
B) be objective function with the total cost minimum, adopt two stage heuritic approaches to find the solution objective function.
Above-mentioned steps is specially:
Suppose that N is the transportation network node set at each candidate's electrical changing station construction point place in the survey region.Each node is also represented an electric automobile aggregation zone.P (p ∈ N) is a certain node in the transportation network.
Figure BDA0000113440600000021
is for containing the transportation network node of electrical changing station.S (s ∈ S) is a certain electrical changing station.
Objective function is suc as formula shown in (1):
min?Z=α.K+ω.C (1)
Wherein: K is the electrical changing station total cost; C is for changing electric person's total cost; α is the weight of electrical changing station cost in total cost, and ω changes the weight of electric person's cost in total cost, α+ω=1; And the value of α, ω is drawn the difference difference because of the electrically-charging equipment planning stage; At the demonstration phase electric automobile is main with the minority vehicle that government helps mainly, and objective function is not considered the electrical changing station total cost basically, only considers to change electric person's total cost minimum; So α ≈ 0, ω ≈ 1; The public good stage still relies on government subsidy, leading propaganda, and the electric automobile that can accept to charge can expand electric bus, large-scale enterprises and institutions utility car, minority public vehicles to, and this moment, α was less, and ω is bigger; The commercial operation stage, electric vehicle engineering was mature on the whole, and total amount reaches certain scale, and the kind rich also comprises a large amount of taxis and private car, had bigger charging demand, got α=ω=0.5 this moment.
The cost of electric automobile electrical changing station mainly comprises fixed cost and variable cost.Wherein fixed cost is construction cost, necessary facility cost etc., with the proportional relation of the electric number of devices of changing of electrical changing station.And variable cost is relevant with electricity sold for along with the different personal expenditures that bring of electrical changing station electricity sold, electricity expense etc.The electrical changing station total cost is each electrical changing station total cost sum, shown in (2).
K = Σ s ∈ S k s - - - ( 2 )
The cost K of electrical changing station s sShown in (3):
K s = K sf + K sv = K sf n g s + k sv ∫ 0 T P s ( t ) dt - - - ( 3 )
Wherein, K SfAnd K SvBe respectively fixed cost and the variable cost of electrical changing station s; N is the design and operation fate of electrical changing station s; Gs is the electric number of devices of changing of electrical changing station s, and on behalf of this electrical changing station, it can change electric operation for several cars simultaneously; k SfBe every fixed cost (comprising construction cost, facility expense etc.) of changing electric equipment; T is the electrical changing station working time of every day; k SvBe the corresponding variable cost (comprise personnel's wage, purchase the electricity charge etc.) of electrical changing station s unit electricity sold; P s(t) be the t electric general power of changing of changing electricity of s electrical changing station constantly.Its value is:
P s ( t ) = x s ( t ) &eta; x s ( t ) < g s g s &eta; x s ( t ) &GreaterEqual; g s - - - ( 4 )
&Integral; 0 T P s ( t ) dt &le; Q s - - - ( 5 )
Formula (4) is for changing the electric general power of electricity.Wherein, x s(t) be the t interior vehicle number of s electrical changing station constantly, comprise and change electric vehicle and queuing vehicle; What η changed electric equipment changes the electric power coefficient because battery is full of in advance, so under the certain situation of skills involved in the labour, η for and change the irrelevant constant of electric power.
Formula (5) is changed electric demand, wherein Q for the electrical changing station capacity can satisfy all vehicles that arrive electrical changing station sBe one day battery capacity of electrical changing station s.
User's total cost is suc as formula shown in (6):
C = &Sigma; p &Element; N &Sigma; s &Element; S &Integral; 0 T f ps ( t ) C ps ( t ) dt - - - ( 6 )
Wherein, C is for changing electric person's total cost; f PsFor t constantly changes the electric automobile sum of electricity by the p s electrical changing station that sets out; C Ps(t) for the user changes the cost that electricity is consumed constantly at t from a p to electrical changing station s, shown in (7):
C ps(t)=α s(t)v+β(τ ps(t)+T s(t+τ ps(t))) (7)
Wherein, τ Ps(t) be to arrive the needed time of s from p constantly at t; α s(t) be the price of electrical changing station s unit quantity of electricity when electric motor car arrives; V changes electric weight for the user; β is the time cost coefficient, comprises running time and changes the electricity time; T s(t+ τ Ps(t)) be that electrical changing station s is the time of its services consume when electric automobile arrives, comprise queuing time and change the electricity time.
Suppose that but electric automobile driver selection schemer is to change electric cost C in the selection schemer PsMiddle minimum route and electrical changing station.Efficient when this has reflected whole electrical changing station system stable operation.
Consider that the electrical changing station service is ageing and satisfy customer requirements that promptly the electric automobile driver satisfies the requirement of hard time window follow to changing electricity total time τ that is no more than consuming time that finishes.Constraint condition is suc as formula shown in (8):
τ ps(t)+T s(t+τ ps(t))≤τ (8)
T is the preliminary research moment, and formula 1-formula 8 is to calculate the model of electrical changing station total cost, is K and the concrete method for solving of C of objective function min Z=α .K+ β .C.Step1-5 is based on the algorithm that the objective function minimum is found the solution optimal location.
The present invention is minimised as addressing layout foundation to electrical changing station with electrical changing station total cost and the objective function that changes the two foundation of electric person's total cost, adopts two stage heuritic approaches to carry out minimum the finding the solution of total cost:
Step1. at first comprise the loading of road network information, electric motor car aggregation node information such as (being the S collection).Carry out the electric demand of changing of each node, impedance factor, the isoparametric initialization of various places construction cost simultaneously;
Step2. the electric automobile of searching on the whole road network is minimum to the average running cost of which node, and { the S that sorts from low to high 1, S 2, S 3..., S n; The minimum average running time of user that refers to of the average running cost here is minimum, supposes that the time cost coefficient is certain.
Step3. whether check that all electric automobile convergence points arrive S in the road network 1Point time spent τ P1(t)+T 1(t+ τ P1(t))<τ.If institute satisfies condition a little, then go to step5, otherwise go to step4;
Step4. with selecting a point to form the electrical changing station set in s1 and the left point, attempt setting up minimum feasible and separate (selecting sequence more in addition be average running cost from low to high).Setting up minimum feasible, to separate conditions for successful be the time τ that a bit arrives arbitrarily nearest electrical changing station in the road network Ps(t)+T s(T+ τ Ps(t))<τ.If unsuccessful, the construction quantity of increase electrical changing station, the quantity of element recomputated the time that a bit arrives nearest electrical changing station in the road network arbitrarily, up to the time window constraint satisfaction during promptly minimum feasible was separated;
Step5. other nodes that are not selected as electrical changing station are added current minimum feasible and concentrate and to calculate, if total cost reduces, then current scheme is set to minimum feasible and separates, and continues search, and cost can't reduce, and exports current minimum feasible and separates and be final plan.
The invention has the beneficial effects as follows: it can be taken into account electrical changing station operating company and change two aspect interests of electric person, and considers traffic convenience property and ageing, and the electric automobile electrical changing station is carried out addressing, and addressing of electric automobile electrical changing station and planning provide foundation.
Description of drawings
Fig. 1 is the electrical changing station network (min of unit) in the home-delivery center Z administrative area.
Embodiment
Below in conjunction with embodiment the present invention is further specified.
If the electrical changing station network in certain home-delivery center Z administrative area is as shown in Figure 1, and suppose that planning has been in the commercial operation stage, gets α=ω=0.5.Wherein A, B, C, D, E are five places with different electric motor-car recoverable amount and different road connection states.Between the different roads place because differences such as load-bearing capacity, traffic state, road section length have different running times.Always when supposing that the driver goes between starting point and destination select shortest path, and each electric motor car to change the electricity time be 5 minutes, it is 20 minutes that the maximum that the driver bears is changed the electricity time spent, promptly time window is [0,20min].The electrical changing station network node data is seen table 1.
Table 1 electrical changing station network node data
Electric automobile is weight factor to the calculating of the average running time of each node to change electric demand on Fig. 1 road network, A, B, C, D, the average running time t of E point A, t B, t C, t D, t ECalculate as follows:
t A=(0*3+4*4+9*2+12*2+20*3)/(3+4+2+2+3)=8.4
t B=(4*3+0*4+5*2+15*2+16*3)/(3+4+2+2+3)=7.1
t C=(9*3+5*4+0*2+20*2+11*3)/(3+4+2+2+3)=11.1
t D=(12*3+15*4+20*2+0*2+14*3)/(3+4+2+2+3)=11.4
t E=(20*3+16*4+11*2+14*2+0*3)/(3+4+2+2+3)=13.7
The average running time of network of the arrival A that draws according to running time data among Fig. 1, B, C, D, five nodes of E for 8.4,7.1,11.1,11.4,13.7}min, ordering is { B, A, C, D, E} from small to large.
1.B be the minimum point of average running time, according to time constraint condition, hard time window is [0,20min], i.e. τ=20.If selecting B is that electrical changing station is built place, τ eP1(t)+T 1(t+ τ P1(t))=and 16+5=21>τ, do not satisfy the time window requirement;
According to B, A, C, D, the order of E} adds electrical changing station with minimum average B configuration running time point A in the left point and builds in the place τ eStill can't meet the demands;
According to B, A, C, D, the order of E} continues B and C are formed electrical changing station selection place, τ e=11+5=16<τ satisfies the requirement of time window constraint.Then { B, C} are that current minimum feasible is separated.This moment, the average running time of road network of whole electrical changing station system was 5.2143min.
4. with D, E forms electrical changing station with B respectively and selects the place, and its time window all meets the demands, and the average running time of road network of whole electrical changing station system is respectively 5.4286min and 4.4286min.
5. calculate the current total cost of respectively organizing feasible solution, the present invention is from electrical changing station and change the consideration of electric person two aspects through the definite originally electrical changing station construction of social assembly place.The total cost Z=α .K+ ω .C=0.5K+0.5C of society; Calculate { B; C}; { B; D}, and B, the social total cost of E} feasible solution draws total cost order { B from low to high according to
Figure BDA0000113440600000061
and
Figure BDA0000113440600000062
and this routine data qualification; E}<{ B; D}<and B, so C} is B and this minimum of E combined assembly;
6. finally select B and E to build the place as electrical changing station.Wherein B design services vehicle number is 90,000, and E design services vehicle number is 50,000.The present invention is constrained to foundation with hard time window, has considered electrical changing station operating company and the minimum cost of changing two aspect interests of electric person, and very big directive function has been played in addressing to electrical changing station.

Claims (5)

1. electric automobile electrical changing station site selecting method is characterized in that:
A) considering electrical changing station operating company and change two aspect interests of electric person, is that target is set up objective function with electric automobile electrical changing station total cost minimum; Total cost mainly comprises fixed cost and variable cost; The electric person of exchange goes and changes the constraint that electricity adds hard time window T.T. in the addressing process simultaneously;
B) adopt two stage heuritic approaches to find the solution to objective function.
2. method according to claim 1 is characterized in that step a) is specially, and the transportation network node set at each candidate's electrical changing station construction point place is N in the survey region; Each node is also represented an electric automobile aggregation zone; P (p ∈ N) is a certain node in the transportation network; is for containing the transportation network node of electrical changing station; S (s ∈ S) is a certain electrical changing station;
Objective function is suc as formula shown in (1):
min?Z=α.K+ω.C (1)
Wherein: K is the electrical changing station total cost; C is for changing electric person's total cost; α is the weight of electrical changing station cost in total cost, and ω changes the weight of electric person's cost in total cost, α+ω=1;
The cost of electric automobile electrical changing station comprises fixed cost and variable cost; The electrical changing station total cost is each electrical changing station total cost sum, shown in (2):
K = &Sigma; s &Element; S k s - - - ( 2 )
The cost K of electrical changing station s sShown in (3):
K s = K sf + K sv = K sf n g s + k sv &Integral; 0 T P s ( t ) dt - - - ( 3 )
Wherein, K SfAnd K SvBe respectively fixed cost and the variable cost of electrical changing station s; N is the design and operation fate of electrical changing station s; g sBe the electric number of devices of changing of electrical changing station s, on behalf of this electrical changing station, it can change electric operation for several cars simultaneously; k SfBe every fixed cost of changing electric equipment; T is the electrical changing station working time of every day; k SvBe the corresponding variable cost of electrical changing station s unit electricity sold; P s(t) be the t electric general power of changing of changing electricity of s electrical changing station constantly; Its value is:
P s ( t ) = x s ( t ) &eta; x s ( t ) < g s g s &eta; x s ( t ) &GreaterEqual; g s - - - ( 4 )
&Integral; 0 T P s ( t ) dt &le; Q s - - - ( 5 )
Formula (4) is for changing the electric general power of electricity; Wherein, x s(t) be the t interior vehicle number of s electrical changing station constantly, comprise and change electric vehicle and queuing vehicle; What η changed electric equipment changes the electric power coefficient, η for and change the irrelevant constant of electric power;
Formula (5) is changed electric demand, wherein Q for the electrical changing station capacity can satisfy all vehicles that arrive electrical changing station sBe one day battery capacity of electrical changing station s;
User's total cost is suc as formula shown in (6):
C = &Sigma; p &Element; N &Sigma; s &Element; S &Integral; 0 T f ps ( t ) C ps ( t ) dt - - - ( 6 )
Wherein, C is for changing electric person's total cost; f PsFor t constantly changes the electric automobile sum of electricity by the p s electrical changing station that sets out; C Ps(t) for the user changes the cost that electricity is consumed constantly at t from a p to electrical changing station s, shown in (7):
C ps(t)=α s(t)v+β(τ ps(t)+T s(t+τ ps(t))) (7)
Wherein, τ Ps(t) be to arrive the needed time of s from p constantly at t; α s(t) be the price of electrical changing station s unit quantity of electricity when electric motor car arrives; V changes electric weight for the user; β is the time cost coefficient, comprises running time and changes the electricity time; T s(t+ τ Ps(t)) be that electrical changing station s is the time of its services consume when electric automobile arrives, comprise queuing time and change the electricity time;
But electric automobile driver selection schemer is to change electric cost C in the selection schemer PsMiddle minimum route and electrical changing station;
Consider that the electrical changing station service is ageing and satisfy customer requirements, promptly the electric automobile driver satisfies the requirement of hard time window follow to changing electricity total time τ that is no more than consuming time that finishes, and constraint condition is suc as formula shown in (8):
Hard time window τ Ps(t)+T s(t+ τ Ps(t))≤τ (8).
3. method according to claim 2 is characterized in that, the value of weight and weights omega is drawn differently because of the electrically-charging equipment planning stage, does not consider the electrical changing station total cost basically at the demonstration phase objective function, and it is minimum only to consider to change electric person's total cost, α ≈ 0; The public good stage, α was still less, and ω is bigger; The equilibrium of commercial operation stage is considered electrical changing station operating company and is changed two aspect interests of electric person, α=ω=0.5.
4. method according to claim 1 is characterized in that, adopts two stage heuritic approaches to the process of electrical changing station addressing optimization to be:
Step1. at first carry out the loading of essential information, carry out the initialization of the parameters of each node simultaneously;
Step2. the electric automobile of searching on the whole road network is minimum to the average running time of which node, and { the S that sorts from low to high 1, S 2, S 3..., S n;
Step3. whether check that all electric automobile convergence points arrive primary election website S1 point time spent τ in the road network P1(t)+T 1(t+ τ P1(t))<τ; If institute satisfies condition a little, then go to step5, otherwise go to step4;
Step4. with selecting a point to form the electrical changing station set in s1 and the left point, attempt setting up minimum feasible and separate, selecting sequence more in addition be average running cost from low to high; Setting up minimum feasible, to separate conditions for successful be the time τ that a bit arrives arbitrarily nearest electrical changing station in the road network Ps(t)+T s(t+ τ Ps(t))<τ; If unsuccessful, the construction quantity of increase electrical changing station, the quantity of element recomputated the time that a bit arrives nearest electrical changing station in the road network arbitrarily, up to the time window constraint satisfaction during promptly minimum feasible was separated;
Step5. other nodes that are not selected as electrical changing station are added current minimum feasible and concentrate and to calculate, if total cost reduces, then current scheme is set to minimum feasible and separates, and continues search, and cost can't reduce, and exports current minimum feasible and separates and be final plan.
5. the method for claim 1 is characterized in that, said fixed cost is construction cost, necessary facility cost, with the proportional relation of the electric number of devices of changing of electrical changing station; Said variable cost is for along with different personal expenditures, the electricity expense usefulness of bringing of electrical changing station electricity sold, and is relevant with electricity sold.
CN2011103859193A 2011-11-28 2011-11-28 Electromobile power exchanging station site selection method Pending CN102521488A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN2011103859193A CN102521488A (en) 2011-11-28 2011-11-28 Electromobile power exchanging station site selection method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN2011103859193A CN102521488A (en) 2011-11-28 2011-11-28 Electromobile power exchanging station site selection method

Publications (1)

Publication Number Publication Date
CN102521488A true CN102521488A (en) 2012-06-27

Family

ID=46292399

Family Applications (1)

Application Number Title Priority Date Filing Date
CN2011103859193A Pending CN102521488A (en) 2011-11-28 2011-11-28 Electromobile power exchanging station site selection method

Country Status (1)

Country Link
CN (1) CN102521488A (en)

Cited By (19)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103699950A (en) * 2013-09-07 2014-04-02 国家电网公司 Electric vehicle charging station planning method considering traffic network flow
CN105139096A (en) * 2015-09-28 2015-12-09 东南大学 Two-stage optimization-based locating and sizing method for electric vehicle charging station
CN105160428A (en) * 2015-08-19 2015-12-16 天津大学 Planning method of electric vehicle fast-charging station on expressway
CN105956743A (en) * 2016-04-20 2016-09-21 国网浙江省电力公司杭州供电公司 Planning system for electric vehicle battery swapping and charging station
CN106447574A (en) * 2016-09-14 2017-02-22 齐鲁工业大学 Smart city building site selection method
CN106682759A (en) * 2016-08-30 2017-05-17 大连理工大学 Battery supply system for electric taxi, and network optimization method
CN107016451A (en) * 2016-10-11 2017-08-04 蔚来汽车有限公司 Electrical changing station site selecting method based on clustering
CN108053058A (en) * 2017-11-29 2018-05-18 东南大学 A kind of electric taxi charging pile site selecting method based on big data
CN108805500A (en) * 2018-06-06 2018-11-13 合肥工业大学 A kind of site selecting method of batteries of electric automobile home-delivery center
CN109754119A (en) * 2018-12-29 2019-05-14 国网天津市电力公司电力科学研究院 Electric car charging and conversion electric service network Method for optimized planning based on Floyd algorithm
CN109920252A (en) * 2019-04-24 2019-06-21 燕山大学 A kind of coordination optimizing method and system of electrical traffic interacted system
CN110119856A (en) * 2019-06-19 2019-08-13 广东工业大学 Charging station site selection system and method based on sensing network
CN110399993A (en) * 2018-04-25 2019-11-01 蔚来汽车有限公司 For distributing the method, apparatus and computer storage medium of Service Source
CN110895638A (en) * 2019-11-22 2020-03-20 国网福建省电力有限公司 Method for establishing active power distribution network planning model considering electric vehicle charging station location and volume
CN111461441A (en) * 2020-04-03 2020-07-28 国网辽宁省电力有限公司 Multi-class charging facility optimal configuration method based on electric vehicle parking situation division
CN111695942A (en) * 2020-06-17 2020-09-22 云南省设计院集团有限公司 Electric vehicle charging station site selection method based on time reliability
CN112381325A (en) * 2020-11-27 2021-02-19 云南电网有限责任公司电力科学研究院 Hydrogenation station planning method
CN112990733A (en) * 2021-03-29 2021-06-18 厦门金龙联合汽车工业有限公司 Battery replacement location site selection method of mobile battery replacement equipment
CN115438840A (en) * 2022-08-15 2022-12-06 北京化工大学 Site selection optimization method for electric vehicle power changing station with controllable average waiting time

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101639503A (en) * 2009-08-25 2010-02-03 青海电力科学试验研究院 Tibet plateau lightning location system site selection method
US20100211643A1 (en) * 2009-02-17 2010-08-19 Richard Lowenthal Transmitting Notification Messages for an Electric Vehicle Charging Network
CN101853332A (en) * 2010-05-12 2010-10-06 中国农业大学 Multi-facility fair site selecting method and system

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100211643A1 (en) * 2009-02-17 2010-08-19 Richard Lowenthal Transmitting Notification Messages for an Electric Vehicle Charging Network
CN101639503A (en) * 2009-08-25 2010-02-03 青海电力科学试验研究院 Tibet plateau lightning location system site selection method
CN101853332A (en) * 2010-05-12 2010-10-06 中国农业大学 Multi-facility fair site selecting method and system

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
任玉珑等: "电动汽车充电站最优分布和规模研究", 《电力系统自动化》 *
寇凌峰等: "区域电动汽车充电站规划的模型与算法", 《现代电力》 *

Cited By (32)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103699950A (en) * 2013-09-07 2014-04-02 国家电网公司 Electric vehicle charging station planning method considering traffic network flow
US10360519B2 (en) 2015-08-19 2019-07-23 Tianjin University Planning method of electric vehicle fast charging stations on the expressway
CN105160428A (en) * 2015-08-19 2015-12-16 天津大学 Planning method of electric vehicle fast-charging station on expressway
CN105160428B (en) * 2015-08-19 2018-04-06 天津大学 The planing method of electric automobile on highway quick charge station
CN105139096A (en) * 2015-09-28 2015-12-09 东南大学 Two-stage optimization-based locating and sizing method for electric vehicle charging station
CN105956743A (en) * 2016-04-20 2016-09-21 国网浙江省电力公司杭州供电公司 Planning system for electric vehicle battery swapping and charging station
CN106682759A (en) * 2016-08-30 2017-05-17 大连理工大学 Battery supply system for electric taxi, and network optimization method
CN106682759B (en) * 2016-08-30 2021-06-11 大连理工大学 Battery supply system for electric taxi and network optimization method
CN106447574A (en) * 2016-09-14 2017-02-22 齐鲁工业大学 Smart city building site selection method
CN107016451A (en) * 2016-10-11 2017-08-04 蔚来汽车有限公司 Electrical changing station site selecting method based on clustering
CN107016451B (en) * 2016-10-11 2020-12-04 蔚来(安徽)控股有限公司 Cluster analysis-based power station site selection method
CN108053058B (en) * 2017-11-29 2021-12-07 东南大学 Electric taxi charging pile site selection method based on big data
CN108053058A (en) * 2017-11-29 2018-05-18 东南大学 A kind of electric taxi charging pile site selecting method based on big data
CN110399993A (en) * 2018-04-25 2019-11-01 蔚来汽车有限公司 For distributing the method, apparatus and computer storage medium of Service Source
CN108805500B (en) * 2018-06-06 2021-04-06 合肥工业大学 Site selection method for battery distribution center of electric vehicle
CN108805500A (en) * 2018-06-06 2018-11-13 合肥工业大学 A kind of site selecting method of batteries of electric automobile home-delivery center
CN109754119B (en) * 2018-12-29 2023-07-04 国网天津市电力公司电力科学研究院 Floyd algorithm-based electric vehicle charging and changing service network optimization planning method
CN109754119A (en) * 2018-12-29 2019-05-14 国网天津市电力公司电力科学研究院 Electric car charging and conversion electric service network Method for optimized planning based on Floyd algorithm
CN109920252B (en) * 2019-04-24 2020-06-19 燕山大学 Coordination optimization method and system for electric traffic interconnection system
CN109920252A (en) * 2019-04-24 2019-06-21 燕山大学 A kind of coordination optimizing method and system of electrical traffic interacted system
CN110119856A (en) * 2019-06-19 2019-08-13 广东工业大学 Charging station site selection system and method based on sensing network
CN110119856B (en) * 2019-06-19 2022-03-25 广东工业大学 Charging station site selection system and method based on sensor network
CN110895638A (en) * 2019-11-22 2020-03-20 国网福建省电力有限公司 Method for establishing active power distribution network planning model considering electric vehicle charging station location and volume
CN110895638B (en) * 2019-11-22 2022-12-06 国网福建省电力有限公司 Active power distribution network model establishment method considering electric vehicle charging station site selection and volume fixing
CN111461441A (en) * 2020-04-03 2020-07-28 国网辽宁省电力有限公司 Multi-class charging facility optimal configuration method based on electric vehicle parking situation division
CN111461441B (en) * 2020-04-03 2023-09-12 国网辽宁省电力有限公司 Multi-class charging facility optimal configuration method based on electric automobile parking situation division
CN111695942A (en) * 2020-06-17 2020-09-22 云南省设计院集团有限公司 Electric vehicle charging station site selection method based on time reliability
CN112381325A (en) * 2020-11-27 2021-02-19 云南电网有限责任公司电力科学研究院 Hydrogenation station planning method
CN112381325B (en) * 2020-11-27 2023-11-21 云南电网有限责任公司电力科学研究院 Hydrogenation station planning method
CN112990733A (en) * 2021-03-29 2021-06-18 厦门金龙联合汽车工业有限公司 Battery replacement location site selection method of mobile battery replacement equipment
CN112990733B (en) * 2021-03-29 2022-05-17 厦门金龙联合汽车工业有限公司 Battery replacement location site selection method of mobile battery replacement equipment
CN115438840A (en) * 2022-08-15 2022-12-06 北京化工大学 Site selection optimization method for electric vehicle power changing station with controllable average waiting time

Similar Documents

Publication Publication Date Title
CN102521488A (en) Electromobile power exchanging station site selection method
Ke et al. Minimizing the costs of constructing an all plug-in electric bus transportation system: A case study in Penghu
Guo et al. Rapid-charging navigation of electric vehicles based on real-time power systems and traffic data
CN102880921B (en) A kind of electric automobile charging station Optimization Method for Location-Selection
CN110880054B (en) Planning method for electric network car-booking charging and battery-swapping path
CN103915869B (en) A kind of Intelligent charging system of electric automobile based on mobile device and method
CN109492791B (en) Inter-city expressway network light storage charging station constant volume planning method based on charging guidance
CN103236179A (en) Method for charging and navigating electric vehicles on basis of traffic information and power grid information
CN112418610B (en) Charging optimization method based on fusion of SOC information and road network power grid information
Jia et al. A novel approach for urban electric vehicle charging facility planning considering combination of slow and fast charging
CN107392336A (en) Distributed electric automobile charging dispatching method based on reservation in intelligent transportation
CN106530180A (en) High-cold region charging service network planning method
CN108062591A (en) Electric vehicle charging load spatial and temporal distributions Forecasting Methodology
CN112183882A (en) Intelligent charging station charging optimization method based on electric vehicle quick charging requirement
CN110254285A (en) It is a kind of to provide the method and system of service to mileage anxiety user based on car networking
CN114611993A (en) Urban and rural electric bus dispatching method based on mobile battery pack
CN115660501A (en) Electric vehicle charging load adjustable margin evaluation method
Feng et al. Review of electric vehicle charging demand forecasting based on multi-source data
Lu et al. En-route electric vehicles charging navigation considering the traffic-flow-dependent energy consumption
CN105160418A (en) Charging distribution predication method based on electric vehicle application features
Guo et al. Optimal path planning method of electric vehicles considering power supply
CN112016745A (en) Planning method for electric vehicle charging station
CN109740974A (en) Electric car fills feed matching process under driving mode
Shu et al. Locational Price Driven Electric Bus Fleet Operation and Charging Demand Management
Crow Multi-objective electric vehicle scheduling considering customer and system objectives

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
ASS Succession or assignment of patent right

Owner name: STATE GRID CORPORATION OF CHINA

Effective date: 20121203

C41 Transfer of patent application or patent right or utility model
TA01 Transfer of patent application right

Effective date of registration: 20121203

Address after: Ji'nan City, Shandong province 250012 Luoyuan Street No. 238

Applicant after: Jinan Power Supply Co., Ltd. of Shandong Electric Power Corporation

Applicant after: State Grid Corporation of China

Address before: Ji'nan City, Shandong province 250012 Luoyuan Street No. 238

Applicant before: Jinan Power Supply Co., Ltd. of Shandong Electric Power Corporation

ASS Succession or assignment of patent right

Owner name: JINAN POWER SUPPLY COMPANY, STATE GRID SHANDONG EL

Free format text: FORMER OWNER: STATE ELECTRIC NET CROP.

Effective date: 20140106

Owner name: STATE ELECTRIC NET CROP.

Free format text: FORMER OWNER: JINAN POWER SUPPLY COMPANY OF SHANDONG ELECTRIC POWER CORPORATION

Effective date: 20140106

C41 Transfer of patent application or patent right or utility model
C53 Correction of patent of invention or patent application
CB03 Change of inventor or designer information

Inventor after: Zhang Lianhong

Inventor after: Gao Xiang

Inventor after: Li Yuanfei

Inventor after: Zhang Yong

Inventor after: Xu Mingkai

Inventor after: Gao Zibin

Inventor after: Sun Yingtao

Inventor after: Wang Ning

Inventor after: Cai Hongjian

Inventor after: Ding Suying

Inventor after: Han Dongbo

Inventor before: Zhang Lianhong

Inventor before: Li Yuanfei

Inventor before: Zhang Yong

Inventor before: Xu Mingkai

Inventor before: Gao Zibin

Inventor before: Sun Yingtao

Inventor before: Wang Ning

Inventor before: Ding Suying

Inventor before: Han Dongbo

Inventor before: Gao Xiang

COR Change of bibliographic data

Free format text: CORRECT: ADDRESS; FROM: 250012 JINAN, SHANDONG PROVINCE TO: 100031 XICHENG, BEIJING

Free format text: CORRECT: INVENTOR; FROM: ZHANG LIANHONG ZHANG YONG XU MINGKAI GAO ZIBIN SUN YINGTAO WANG NING DING SUYING HAN DONGBO GAO XIANG LI YUANFEI TO: ZHANG LIANHONG ZHANG YONG XU MINGKAI GAO ZIBIN SUN YINGTAO WANG NING CAI HONGJIAN DING SUYING HAN DONGBO GAO XIANG LI YUANFEI

TA01 Transfer of patent application right

Effective date of registration: 20140106

Address after: 100031 Xicheng District West Chang'an Avenue, No. 86, Beijing

Applicant after: State Grid Corporation of China

Applicant after: Jinan Power Supply Company, State Grid Shandong Electric Power Company

Address before: Ji'nan City, Shandong province 250012 Luoyuan Street No. 238

Applicant before: Jinan Power Supply Co., Ltd. of Shandong Electric Power Corporation

Applicant before: State Grid Corporation of China

C02 Deemed withdrawal of patent application after publication (patent law 2001)
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20120627