CN108182483A - Extensive electric vehicle charging schedule system and its optimization method based on secondary cluster - Google Patents
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Abstract
The invention discloses extensive electric vehicle charging schedule systems and its optimization method based on secondary cluster, include charging station, background management system, Map Services, wechat public platform, the background management system includes data reception module, scheduling model establishes module, distribute computing module and generalized information system, it is mostly at present from single motor automobile angle to the research of electric vehicle charging strategy, and with raising of the whole world to the concern temperature of electric vehicle, the quantity of following electric vehicle will be great, if using single motor automobile as research object, its calculation amount can be very big, therefore, considered herein from entire electric vehicle group, research one kind can meet automobile user charge requirement, the method and the corresponding charging schedule system of research and development that corresponding calculation amount can be reduced again are very necessary.
Description
Technical field
The invention belongs to electric vehicle charge control field more particularly to the extensive electric vehicle based on secondary cluster fills
Electric scheduling system and its optimization method.
Background technology
At present, Global Auto industry is fast-developing, and car ownership rapidly increases, but thus caused environment is dirty
The problems such as dye, energy shortage, resource exhaustion, is by global very big concern.Electric vehicle because its energy-saving and environmental protection characteristic into
For the new selection of Global Auto industry future, countries in the world are all added to one after another in electric vehicle engineering research and development and market competition.
It is contemplated that future will have a large amount of moveable electric vehicles charging loads access power grids, however, extensive electric vehicle when
Between and unordered charging behavior spatially may not only cause the resource utilization of charging station unbalanced, the overload of power grid part,
The problems such as line congestion, affects to the stable operation of power grid.And there is a possibility that the charging time of user is long, electricity is influenced
The convenience of electrical automobile user trip, directly affects buying behavior of the consumer to electric vehicle.Therefore, it is necessary in the time and
Electric vehicle charging burden apportionment bootstrap technique is realized to this moving load of electric vehicle in research in the dimension of two, space
Optimized Operation.
In order to solve the problems, such as electric vehicle charging Optimization of Load Dispatching, (electric vehicle charges patent 201210471981.9
Load space dispatches system and method) a kind of electric vehicle charging load space scheduling system and dispatching method are proposed, this is
System includes electric automobile and is loaded with sequence charge controller, dispatching of power netwoks unit and electric vehicle control centre, according to electric vehicle
Charge request, vehicle position information, Vehicular battery remaining capacity and rated capacity that vehicle-mounted orderly charge controller provides and
Whether each charging station charging load that dispatching of power netwoks department provides evenly distributes instruction, realizes the load space that charges to electric vehicle
Scheduling, reaches the problems such as preventing the overload of power grid part, line congestion.But this method is for single motor automobile, meter
Calculation amount is bigger.
Invention content
The technical problems to be solved by the invention be for background technology deficiency provide it is a kind of based on the big of secondary cluster
Scale electric vehicle charging schedule system and its optimization method, realize the Optimized Operation to this moving load of electric vehicle.
The present invention uses following technical scheme to solve above-mentioned technical problem
Extensive electric vehicle charging schedule system based on secondary cluster, includes charging station, background management system, map
Service, wechat public platform, the background management system includes data reception module, scheduling model establishes module, distribution calculates
Module and generalized information system；
Wherein：Charging station, for providing electric energy needed for electric vehicle charging；
Generalized information system, for obtaining each electric vehicle to the optimal path distance of each charging station；
Data reception module, for receiving the real time information of the charge request of user and charging station；
Scheduling model establishes module, and whether the electric vehicle number for calculating in each charging station evenly distributes, according to next
Charge request, electric vehicle position coordinates, batteries of electric automobile remaining mileage and generalized information system from wechat public platform obtain
Each electric vehicle taken establishes electric vehicle charging schedule model to the optimal path distance of each charging station；
Allocation result computing module, for solving i-th electric vehicle distribution using space allocation algorithm and genetic algorithm
To which charging station, and be sent to wechat public platform, at the same send also from Map Services about the charging station
Position navigation Service；
Map Services, for providing real-time road condition information inquiry and navigation Service.
As the present invention is based on the further preferred scheme of the extensive electric vehicle charging schedule system of secondary cluster, institutes
The charge request for stating user includes wechat account, current location, the vehicle of user；The charging station real time information includes charging station
Title, the address of charging station, the electric vehicle number in charging station.
As the present invention is based on the further preferred scheme of the extensive electric vehicle charging schedule system of secondary cluster, institutes
Charging station is stated with background management system by way of optical fiber wire communication to carry out data transmission.
As the present invention is based on the further preferred scheme of the extensive electric vehicle charging schedule system of secondary cluster, electricity
Electrical automobile scheduling model is as follows：
The difference of electric vehicle number and charging pile number ratio distributed in each charging stationWhereinWherein, SjRepresent charging station CSjInterior electric vehicle number；Or 1,1 represents electric vehicle EViSelection charging
Stand CSjCharging, 0 represents no；All electric vehicles are with going to the sum of running time of charging station of charging
Wherein, lijRepresent electric vehicle EViTo charging station CSjOptimal path distance,For electric vehicle EViAverage traveling speed
Degree；Min can be modeled as according to the utilization rate of charging pile and the average running time that charging station is gone to charge in charging station is minimized
F=α1F1+α2F2, wherein α1,α2(α >=0) is balance factor.
As the present invention is based on the further preferred scheme of the extensive electric vehicle charging schedule system of secondary cluster, skies
Between allocation algorithm include hierarchical clustering algorithm and K-means clustering algorithms.
It is micro- as the present invention is based on the further preferred scheme of the extensive electric vehicle charging schedule system of secondary cluster
The mode of data transmission is fiber optic communication mode between letter public platform and Map Services, background management system and Map Services it
Between the mode of data transmission be fiber optic communication mode.
A kind of extensive electric vehicle charging schedule optimization method based on secondary cluster, specifically comprises the following steps：
Step 1, user sends charge request by wechat public platform to wechat public platform；
Step 2, the data reception module of background management system is responsible for receiving the charge request of user, and from each charging station
It collects when the electric vehicle number to be charged in next stop；
Step 3, data reception module obtains electric vehicle EV by calling generalized information systemiTo charging station CSjOptimal path
Range information lij, and the information and charge station information are sent to scheduling model and establish module；
Step 4, scheduling model establishes whether the electric vehicle number that module is calculated in each charging station evenly distributes, according to each
Electric vehicle is to difference
The optimal path distance l of charging stationij, establish electric vehicle charging schedule model；
Step 5 allocation result computing module calculates electric vehicle EViIt distributes to charging station charging CSjDecision variable
Step 6, allocation result is sent to the wechat public of user by allocation result computing module by wechat public platform
Number, at the same send also from the position navigation Service about the charging station in Map Services.
As a kind of the further excellent of extensive electric vehicle charging schedule optimization method based on secondary cluster of the present invention
Scheme is selected, step 5 specific method is as follows：
1) electric vehicle that there is charge request in the same time is clustered by coagulation type hierarchical clustering algorithm, if level
The class number obtained after cluster is K, some electric vehicle group quantity is Qi, minimum charging pile number is q, then electric vehicle group
Clustering target isFrom electric vehicle group QiIn optional kiA sample is as initial cluster center
2) to electric vehicle group QiIn each sample xiFind the cluster centre z nearest from itq, and assign it to zqInstitute
The class u shownq；
3) average method is taken to calculate all kinds of hearts after reclassifying；
4) it calculates
Wherein, D refer to electric vehicle and cluster centre coordinate points distance inside each cluster and；
If 5) D values restrain,And the electric vehicle set in each class, and carry out electric vehicle
Group Qi+1Cluster, otherwise go to 2)；
6) obtaining electric vehicle class number isAnd the cluster centre of each class and electric vehicle set；
7) it is solved using genetic algorithm, establishes initial population, wherein, the gene representation electric vehicle class choosing on chromosome
The charging station type selected；
8) fitness of each individual is calculated；
9) according to genetic probability, by selecting, intersecting, mutation operation, constantly cycle performs, and gradually approaches global optimum
Solution, and then acquire
The present invention compared with prior art, has following technique effect using above technical scheme：
1st, at present to the research of electric vehicle charging strategy mostly be from single motor automobile angle, and with the whole world it is right
The raising of the concern temperature of electric vehicle, the quantity of following electric vehicle will be great, if using single motor automobile to grind
Study carefully object, calculation amount can be very big, therefore, considers that, from entire electric vehicle group, research one kind can meet electronic herein
User vehicle charge requirement, but it is very necessary that can reduce the method for corresponding calculation amount and the corresponding charging schedule system of research and development
's；
2nd, traditional electric vehicle charging selection strategy is from the angle of single motor automobile, but with big mostly
Scale electric vehicle is commonly used, may increase the calculating cost of system, it is also possible to automobile user be caused to obtain most
The time of good charging station increases, and so as to influence the trip of user experience, therefore, this patent consideration goes out from entire electric vehicle group
Hair, research one kind can meet automobile user charge requirement and the method for reducing corresponding calculation amount and research and development are corresponding
Charging schedule system is very necessary；
3rd, it is compared to and each electric vehicle is solved using genetic algorithm, the electric vehicle cluster side that this patent is proposed
Method can quickly provide a user best charging station, improve the trip convenience of user, be conducive to the scale of electric vehicle
Change application, while also have very big benefit to the sustainable development of environment, in addition, the load space tune that charges to electric vehicle
Degree, can make full use of each charging station resource, reach the problems such as preventing the overload of power grid part, line congestion.
4th, by the way of wechat public platform, automobile user can send charging reserve requests by wechat public platform,
It is distinctive in wechat that the geographical location information of cellphone GPS service acquisition user, Yong Hu are passed through based on the geo-location service of LBS
Geographical location can be chosen when sending charging reserve requests, background management system is suitable for its recommendation with regard to that can see its location
Charging station.And map can be showed on wechat browser, and Voice Navigation service can be carried out, for APP, due to
It does not need to download installation, it is more convenient with this mode.And the development cost of APP is high, and continuous iteration is needed to update, and wechat is public
Crowd number is lighter and handier, development cost is low, popularization is easy, and mobile site's entrance is embedded by wechat, can be preferably HTML5+
CSS3+JS technologies incorporate.
Description of the drawings
Fig. 1 is charging schedule policy optimization system structure schematic diagram of the present invention.
Specific embodiment
Technical scheme of the present invention is described in further detail below in conjunction with the accompanying drawings：
As shown in Figure 1, wherein, charging station：When charging pile is charged, generated charge information passes through electric vehicle
Charging pile is uploaded to background management system.Data transmission between charging pile and background management system can pass through optical fiber wire communication
Mode or GPRS, WIFI communication.
Background management system includes data reception module, scheduling model establishes module, distributes computing module and generalized information system,
Wherein：
Data reception module, charge request, the charging station real time information of primary recipient user etc., wherein：
The charge request of user includes：The wechat account of user, current location, vehicle etc.；
Charging station real time information includes：The title of charging station, the address of charging station, vehicle number in charging station etc..
Scheduling model establishes module, calculates whether the vehicle number in each charging station evenly distributes, according to from wechat public affairs
Each vehicle that charge request, vehicle location coordinate, Vehicular battery remaining mileage and the generalized information system of many platforms provide is to difference
The optimal path distance of charging station, establishes electric vehicle charging schedule model, and wherein electric vehicle scheduling model is as follows：
The difference of electric vehicle number and charging pile number ratio distributed in each charging stationWhereinWherein, SjRepresent charging station CSjInterior electric vehicle number；Or 1,1 represents electric vehicle EViSelection charging
Stand CSjCharging, 0 represents no；All electric vehicles are with going to the sum of running time of charging station of charging
Wherein, lijRepresent electric vehicle EViTo charging station CSjOptimal path distance,For electric vehicle EViAverage traveling speed
Degree.Min can be modeled as according to the utilization rate of charging pile and the average running time that charging station is gone to charge in charging station is minimized
F=α1F1+α2F2, wherein α1,α2(α >=0) is balance factor.
Allocation result computing module solves i-th electric vehicle using space allocation algorithm and genetic algorithm and distributes to which
A charging station simultaneously sends wechat public platform, while what is sent navigates also from Map Services about the position of the charging station
Service, which is optional.Wherein, space allocation algorithm includes hierarchical clustering algorithm and K-means clustering algorithms.
Map Services provide real-time road condition information inquiry and navigation Service, and wechat public platform is distinguished with background management system
Related service is called by the open interface (API) of Map Services, which is optional.Wechat public platform and Map Services
Between the mode of data transmission be fiber optic communication mode；The mode of data transmission is light between background management system and Map Services
Fiber communication mode.
User sends charge request by wechat public platform to wechat public platform, and wechat public platform receives filling for user
Electricity request, and background management system is sent to after being arranged to the information of user, background management system is receiving asking for user
After asking, analyze the information of user, and according to generalized information system and Map Services provide a user charging station in the range of wheeled and
Its real time information.Data transmission between wechat public platform and wechat public platform can pass through the side wireless communications such as GPRS, WIFI
Formula, the data transmission between wechat public platform and background management system is by way of fiber optic communication.
By wechat public platform, the electricity price that charging station can be directly pushed to user is believed for electric vehicle charging service operator
Breath, advertising campaign information etc., guiding user charge during network load low ebb, to improve power quality, ensure regional power grid
Stable operation.
Electric vehicle charging schedule system, which is characterized in that the system includes：
User sends charge request by wechat public platform to wechat public platform, and wechat public platform receives filling for user
Electricity request, and background management system is sent to after being arranged to the information of user, background management system is receiving asking for user
After asking, analyze the information of user, and according to generalized information system and Map Services provide a user charging station in the range of wheeled and
Its real time information.
Charging station：Electric vehicle is when charging pile is charged, after generated charge information is uploaded to by charging pile
Platform manages system.Data transmission between charging pile and background management system can be by way of optical fiber wire communication, can also
It is the communication of GPRS, WIFI.
Background management system is responsible for receiving the charge request of user, while current electric vehicle to be charged is uniformly divided
Each charging station is fitted on, and information is sent to by wechat public platform in the wechat public platform of user by treated.
1. electric vehicle charging schedule method, which is characterized in that this method comprises the following steps：
1) user sends charge request by wechat public platform to wechat public platform；
2) data reception module of background management system is responsible for receiving the charge request of user, and is collected from each charging station
When the vehicle number to be charged in next stop；
3) data reception module obtains electric vehicle EV by calling generalized information systemiTo charging station CSjOptimal path distance
Information lij, and the information and charge station information are sent to scheduling model and establish module；
4) scheduling model establishes whether the vehicle number that module is calculated in each charging station evenly distributes, according to each vehicle to not
With the optimal path distance l of charging stationij, establish electric vehicle charging schedule model；
5) allocation result computing module calculates electric vehicle EViIt distributes to charging station charging CSjDecision variable
6) allocation result is sent to the wechat public platform of user by allocation result computing module by wechat public platform, together
When send also from the position navigation Service about the charging station in Map Services, which is optional.
2. electric vehicle EV is calculated in the step 5 in electric vehicle dispatching method described iniIt distributes to charging station charging CSj
Decision variableSpecific method is as follows：
1) vehicle that there is charge request in the same time is clustered by coagulation type hierarchical clustering algorithm, it is assumed that level gathers
The class number obtained after class is K, some electric vehicle group quantity is Qi, minimum charging pile number is q, then electric vehicle group's is poly-
Class index isFrom electric vehicle group QiIn optional kiA sample is as initial cluster center
2) to electric vehicle group QiIn each sample xiFind the cluster centre z nearest from itq, and assign it to zqInstitute
The class u shownq；
3) average method is taken to calculate all kinds of hearts after reclassifying；
4) it calculates
If 5) D values restrain,And the electric vehicle set in each class, and carry out electric vehicle
Group Qi+1Cluster, otherwise go to 2)；
6) finally obtaining electric vehicle class number isAnd the cluster centre of each class and electric vehicle set.
7) electric vehicle class is similar to single motor automobile, and electric vehicle class can be solved.It is true in object function
After fixed, the problem of being how to solve preferred plan.It is solved herein using genetic algorithm, establishes initial population, wherein
The charging station type of gene representation electric vehicle class selection on chromosome, for example, have 8 electric vehicle groups, 4 charging stations,
Then chromosome can be expressed as 12341234 or 43214321；
8) fitness of each individual is calculated, the index for weighing character string (chromosome) quality is fitness, that is, heredity
The object function of algorithm；
9) according to genetic probability, by selecting, intersecting, operations, the constantly cycle such as being mutated and perform, global optimum is gradually approached
Solution, is acquired
Claims (8)
1. the extensive electric vehicle charging schedule system based on secondary cluster, it is characterised in that：Include charging station, back-stage management
System, Map Services, wechat public platform, the background management system includes data reception module, scheduling model establishes module,
Distribute computing module and generalized information system；
Wherein：Charging station, for providing electric energy needed for electric vehicle charging；
Generalized information system, for obtaining each electric vehicle to the optimal path distance of each charging station；
Data reception module, for receiving the real time information of the charge request of user and charging station；
Scheduling model establishes module, and whether the electric vehicle number for calculating in each charging station evenly distributes, according to from micro-
What charge request, electric vehicle position coordinates, batteries of electric automobile remaining mileage and the generalized information system of letter public platform obtained
Each electric vehicle establishes electric vehicle charging schedule model to the optimal path distance of each charging station；
Allocation result computing module is distributed for solving i-th electric vehicle using space allocation algorithm and genetic algorithm to which
A charging station, and be sent to wechat public platform, at the same send also from the position about the charging station in Map Services
Navigation Service；
Map Services, for providing real-time road condition information inquiry and navigation Service.
2. the extensive electric vehicle charging schedule system according to claim 1 based on secondary cluster, it is characterised in that：
The charge request of the user includes wechat account, current location, the vehicle of user；The charging station real time information includes charging
The title stood, the address of charging station, the electric vehicle number in charging station.
3. the extensive electric vehicle charging schedule system according to claim 1 based on secondary cluster, it is characterised in that：
The charging station is carried out data transmission with background management system by way of optical fiber wire communication.
4. the extensive electric vehicle charging schedule system according to claim 1 based on secondary cluster, it is characterised in that：
Wherein, electric vehicle scheduling model is as follows：
The difference of electric vehicle number and charging pile number ratio distributed in each charging stationWhereinWherein, SjRepresent charging station CSjInterior electric vehicle number；Or 1,1 represents electric vehicle EViSelection charging
Stand CSjCharging, 0 represents no；All electric vehicles are with going to the sum of running time of charging station of charging
Wherein, lijRepresent electric vehicle EViTo charging station CSjOptimal path distance,For electric vehicle EViAverage traveling speed
Degree；Min can be modeled as according to the utilization rate of charging pile and the average running time that charging station is gone to charge in charging station is minimized
F=α1F1+α2F2, wherein α1,α2(α >=0) is balance factor.
5. the extensive electric vehicle charging schedule system according to claim 1 based on secondary cluster, it is characterised in that：
Space allocation algorithm includes hierarchical clustering algorithm and K-means clustering algorithms.
6. the extensive electric vehicle charging schedule system according to claim 1 based on secondary cluster, it is characterised in that：
The mode of data transmission is fiber optic communication mode, background management system and Map Services between wechat public platform and Map Services
Between the mode of data transmission be fiber optic communication mode.
7. a kind of extensive electric vehicle charging schedule optimization method based on secondary cluster, feature exist：Specifically comprising as follows
Step：
Step 1, user sends charge request by wechat public platform to wechat public platform；
Step 2, the data reception module of background management system is responsible for receiving the charge request of user, and is collected from each charging station
When the electric vehicle number to be charged in next stop；
Step 3, data reception module obtains electric vehicle EV by calling generalized information systemiTo charging station CSjOptimal path distance
Information lij, and the information and charge station information are sent to scheduling model and establish module；
Step 4, scheduling model establishes whether the electric vehicle number that module is calculated in each charging station evenly distributes, according to each electronic
Automobile to different charging stations optimal path distance lij, establish electric vehicle charging schedule model；
Step 5 allocation result computing module calculates electric vehicle EViIt distributes to charging station charging CSjDecision variable
Step 6, allocation result is sent to the wechat public platform of user by allocation result computing module by wechat public platform, together
When send also from the position navigation Service about the charging station in Map Services.
8. a kind of extensive electric vehicle charging schedule optimization method based on secondary cluster according to claim 7,
It is characterized in that：Step 5 specific method is as follows：
1) electric vehicle that there is charge request in the same time is clustered by coagulation type hierarchical clustering algorithm, if hierarchical clustering
The class number obtained afterwards is K, some electric vehicle group quantity is Qi, minimum charging pile number is the cluster of q, then electric vehicle group
Index isFrom electric vehicle group QiIn optional kiA sample is as initial cluster center
2) to electric vehicle group QiIn each sample xiFind the cluster centre z nearest from itq, and assign it to zqIndicated
Class uq；
3) average method is taken to calculate all kinds of hearts after reclassifying；
4) it calculates
Wherein, D refer to electric vehicle and cluster centre coordinate points distance inside each cluster and；
If 5) D values restrain,And the electric vehicle set in each class, and carry out electric vehicle group Qi+1
Cluster, otherwise go to 2)；
6) obtaining electric vehicle class number isAnd the cluster centre of each class and electric vehicle set；
7) it is solved using genetic algorithm, establishes initial population, wherein, what the gene representation electric vehicle class on chromosome selected
Charging station type；
8) fitness of each individual is calculated；
9) according to genetic probability, by selecting, intersecting, mutation operation, constantly cycle performs, and gradually approaches globally optimal solution, into
And it acquires
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN112818602A (en) * | 2021-02-05 | 2021-05-18 | 清华大学 | Battery digital twin control method and device based on big data analysis |
| CN112818602B (en) * | 2021-02-05 | 2021-09-28 | 清华大学 | Battery digital twin control method and device based on big data analysis |
| CN113932824A (en) * | 2021-09-27 | 2022-01-14 | 西安理工大学 | Electric vehicle charging navigation system and method based on edge calculation |
| CN117273181A (en) * | 2023-11-17 | 2023-12-22 | 天津平高易电科技有限公司 | Electric automobile charging scheduling method and system |
| CN117273181B (en) * | 2023-11-17 | 2024-04-26 | 天津平高易电科技有限公司 | Electric automobile charging scheduling method and system |
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