CN107886186A - A kind of charging pile method to set up based on travelling data and Wei Nuotu zonings - Google Patents
A kind of charging pile method to set up based on travelling data and Wei Nuotu zonings Download PDFInfo
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Abstract
The present invention proposes a kind of charging pile method to set up based on travelling data and Wei Nuotu zonings, belongs to electric automobile field.This method first with dimension promise drawing method to need set charging pile region division subregion；Using travelling data, calculate the maximum charge per sub-regions and load, select maximum therein and its corresponding subregion；Value models are established to the subregion, using particle cluster algorithm to model solution, obtain the optimum results of charging station location that the subregion newly increases and charging pile quantity；Then the charging station newly increased is added in the map in the region, the optimization that all charging stations are re-started with sub-zone dividing and charging station calculates, until constraints exceeds the default upper limit, setting completed for charging pile in the region.The present invention is carried out the reasonable plant-site selection and constant volume of charging pile setting using vehicle operation data, has very strong of overall importance and accuracy to obtain charging electric vehicle efficiently and reduce electrically-charging equipment construction cost as target.
Description
Technical field
The invention belongs to electric automobile field, more particularly to a kind of charging based on travelling data and Wei Nuotu zonings
Stake method to set up.
Background technology
Electric automobile has the advantages that pollution-free, energy utilization rate is high, simple in construction, noise is small compared with conventional truck.From
Reply Energy restructuring, environmental protection, cultivation future technology competitive advantage are set out, and the development trend of electric automobile has been must
So.With the steady-state growth of electric automobile recoverable amount, there is the problem of some suppress electric car development, wherein charging pile is distributed
Unreasonable, utilization rate is lowly stood in the breach, and seriously constrains the popularization and popularization of electric automobile.
To solve this problem, optimization layout of the domestic and foreign scholars to charging station conducts a preliminary study.It is existing
Electric automobile charging pile set and be broadly divided into that city highway charging pile is set and intercity highway charging pile sets 2 sides
Face；The charging pile of highway sets main consideration running distance of eletric vehicles to limit, and the setting of city highway charging pile, removes
Outside driving course, it is also necessary to consider electric car user's request (suitable charging interval, suitable charge position etc.).Both fill
The setting of electric stake is had in common that all using (such as the charging based on user's trip requirements of certain method prediction charge requirement
Load prediction, the charge requirement prediction based on spatial and temporal distributions), so as to be planned charging pile and constant volume.
A kind of existing charging pile method to set up is as follows：A certain region (city or cities and towns) is selected, the region is obtained and goes through
Year GDP growth rate, electric automobile recoverable amount over the years, function building plans (residential estate, public facilities, industry in region
Land used etc.), traffic zone is divided according to difference in functionality, electric automobile recoverable amount and charging pile are then predicted by elastic coefficient method
Demand, the trip for quantifying and demarcating different traffic zones by gravity model method produce intensity, trip attraction intensity, traffic resistance
It is anti-, trip abundance of the prediction electric automobile between each cell, according to peak hour flow ratio and different charging tendency crowds
Accounting, predict the charge requirement of a traffic zone.Consideration electric automobile course continuation mileage is short, the inherent characteristic of charging interval length, right
Charging electric vehicle behavior makes it is assumed that simultaneously combined charge facility development scale restrictive condition, is established and always consumed with all users
When minimum object function charging station site selection model.The demand that traffic zone is thought of as collection meter by the model produces point, utilizes
Genetic algorithm judges whether each point sets charging station.
But these existing methods problems are that its data (for example region GDP growth rate over the years in above method, is gone through
Year electric automobile recoverable amount, function building plans etc. in region) carry out survey, belong to statistics, come in advance by statistics
Surveying charge requirement has the drawbacks of obvious, and data volume is small；And be affected by human factors, partial data subjectivity is too strong, such as traffic
The trip of cell produces intensity, trip attraction intensity, traffic impedance, can not be accurately worth by demarcation, also cannot
Obtain accurate result.
Wei Nuotu (Voronoi), it is called Thiessen polygon or Dirichlet figures：N number of dispersion number distinguishing in the plane
Strong point, plane is divided into N number of region, the corresponding region of each discrete data point, each point in N number of region to the region
The distance of corresponding discrete data point is nearest.This method has critical role in computational geometry subject, due to its basis
Point set division region to put it is closest the characteristics of, it is in geography, meteorology, crystallography, space flight, nuclear physics, machine
The fields such as device people have a wide range of applications.Such as concentrated in barrier point, optimal path is found using this method obstacle avoidance.Mesh
Before, Wei Nuotu is not yet applied to electric automobile charging pile and sets field.
The content of the invention
It is contemplated that overcome the deficiencies in the prior art, a kind of filling based on travelling data and Wei Nuotu zonings is proposed
Electric stake method to set up.This method utilizes Wei Nuotu zonings, and vehicle operation data is analyzed, it is contemplated that electrically-charging equipment has
There is the double attribute of urban transportation public service facility and common electricity consumption facility, meeting the charge requirement of electric car in region
On the basis of, to obtain charging electric vehicle efficiently and reduce electrically-charging equipment construction cost as target, it is reasonable that charging pile is carried out
Addressing and constant volume, lay the foundation for electric automobile scale application.
The present invention proposes a kind of charging pile method to set up based on travelling data and Wei Nuotu zonings, and its feature exists
In comprising the following steps：
1) to need set charging pile region division subregion；
Obtain the map that needing, charging pile region is set；On the map in the region, mark the region is all existing to fill
Power station simultaneously calculates the distance of all charging stations between any two；If the distance between all charging stations are all higher than the distance threshold of setting
L, then each charging station in the region is arranged to a discrete data point on map；If in the presence of between two charging stations away from
From the distance threshold L less than or equal to setting, then two charging stations are merged into a new charging station on map, this newly fills
The position in power station take two charging station location central point, and on map by each charging station in the region be arranged to one from
Dissipate data point；It is different subregions by tieing up promise drawing method by the region division using discrete data point, the number of subregion
Equal to the number of discrete data point；
2) travelling data is utilized, the maximum charge per sub-regions is calculated and loads, maximum therein is selected and records and be somebody's turn to do
Subregion is designated as A corresponding to maximum；Comprise the following steps that：
Whole day 2-1) is divided into 24 periods by 1 hour, make i represent period sequence number, i=1,2,3 ... 24；
Any one subregion 2-2) is chosen, calculates the effective charge requirement vehicle number of subregion；
Effective charge requirement vehicle refers to the electric automobile for having actual charge requirement in random time section in subregion, bag
Include following two parts：
Effective parking vehicle：Disposably stopped duration more than 30 minutes and dump energy hundred in the subregion any time period
Divide than electric automobiles of the SOC less than the residual power percentage threshold value E of setting；
By way of vehicle：The subregion any time period electric automobile vehicle flowrate and the effectively difference of parking quantity；
Anyon zone time section i effective charge requirement vehicle number calculation expression is as follows：
N0i=α Nei+βNpi
In formula, N0iFor effective charge requirement vehicle number of period i in subregion；NeiHave for period i in subregion
Imitate parking vehicle number；NpiFor in subregion period i by way of vehicle number；α is effectively parking weight coefficient；β is by way of vehicle
Weight coefficient；
2-3) calculate subregion vehicle average charge demand；
Vehicle average charge demand refers to any time period effective charge requirement vehicle unit time in the subregion
Average charge demand；According to step 2-1) the obtained effective parking vehicle of division and by way of vehicle, any time period is chosen, point
Do not count each the effective parking vehicle period Nei SOC and each by way of vehicle minimum SOC, and carry out accumulative summation, point
∑ SOC is not designated aseiWith ∑ SOCpi, it is A to make vehicle average power battery capacity, then subregion period i vehicles average charge needs
The amount of asking QiCalculation expression be：
Qi=[α (Nei* 100%- ∑s SOCei)+β·(Npi* 100%- ∑s SOCpi)]·A/N0i
The charging load of subregion all periods interior for a period of time 2-4) is calculated, the maximum charge for obtaining the subregion is born
Carry；
Obtain the charging pile quantity of charging station in per sub-regions, the calculation expression of subregion any time period charging load
Formula is：
Ci=Qi·N0i/(Nc·q)
In formula, CiFor subregion charging load in period i；NcFor charging pile quantity in subregion；Q is to be filled in subregion
Electric stake average charge ability；
Interception a period of time, the charging load of all periods in the subregion in the time of interception is calculated,
Choose the period wherein corresponding to maximum and record the subregion charging load of the period as the subregion
Maximum charge load Cmax；
2-5) traversal step 1) the obtained all subregions of division, repeat step 2-2) to 2-4), every height is calculated
C corresponding to regionmax, choose wherein CmaxThe maximum subregion of value is designated as subregion A；
3) subregion maximum charge load corresponding to A compared with charging load threshold value [C] and is judged：If subregion
A maximum charge load increases charging station higher than the charging load threshold value set, then subregion A, into step 4)；Conversely, then
Setting completed for charging pile in the region；
4) value models are established to subregion A, using particle cluster algorithm to model solution, filled to what the subregion newly increased
Plant location and charging pile quantity optimize；Comprise the following steps that：
4-1) determine the object function of model；Expression formula is as follows
G=aDj+b·M
In formula, DjBy all vehicles in subregion drive to minimum range that subregion A current charging station j travels it
With objective cost of the M representatives in subregion A one new charging station of setting；A is distance optimization weight, and b weighs for cost optimization
Weight；
DjCalculation expression it is as follows：
In formula, DjiThe distance of i-th vehicle and charging station j points is represented, k is vehicle fleet；
Objective cost M includes：Charging station cost of investment Ms, charging pile cost of investment M altogetherq, charging station O＆M cost Mom
And charging income Mp；Expression formula is as follows：
M=Min (Ms+Mq+Mom-Mp)
4-2) to model solution；
Using particle cluster algorithm, with the charging pile quantity accumulated in whole region, the charging station quantity accumulated,
Objective cost M and charging load threshold value [C] are constraints, are object function to the charging station that is newly increased in subregion A using G
The quantity of position and charging pile optimizes；Order only increases a charging station in the subregion A for needing to increase charging station every time, then
Particle cluster algorithm output result be：Increase a charging station in the subregion, the position coordinates of the newly-increased charging station and this is new
Increase charging pile quantity in charging station；
5) the newly-increased charging station of the acquisition of step 4) is added in the map of step 1), returns to step 1), to all
The optimization that charging station re-starts sub-zone dividing and charging station calculates, until the charging station quantity accumulated in region, tired
Count increased charging pile quantity or objective cost and exceed constraints, setting completed for charging pile in the region.
The features of the present invention and beneficial effect are：
A kind of charging pile method to set up based on travelling data and Wei Nuotu zonings proposed by the present invention, can basis
The demand of user, preset charged station sum, charging pile sum, charging load threshold value, unit charging pile are taken in per hour, charging pile
With the cost and cost of charging station and the weight of distance.This method utilizes cartographic information and charging pile the charging station location obtained
Information, region is divided with Wei Nuotu method, from vehicle driving extracting data vehicle latitude and longitude information, Parking
Information, charge event information, calculate the charge requirement in each region, the parameter and positional information set according to user, utilize certain
The comprehensive value function of the one charging pile plan of establishment, by particle cluster algorithm, choose optimal solution therein.The present invention utilizes vehicle
Running data carries out the reasonable plant-site selection and constant volume of charging pile setting, has very strong of overall importance and accuracy.The present invention is meeting
In region on the basis of the charge requirement of electric car, using obtain charging electric vehicle efficiently and reduce electrically-charging equipment construction cost as
Target, rational addressing and constant volume are carried out to charging pile, laid the foundation for electric automobile scale application.
Relative to conventional method, present invention uses more accurate data source, uses more reasonably region division side
Method, the quantized value reliability in pilot process is high, and can rationally be advised to increasing charging station location capacity in region newly immediately
Draw (charge requirement obtained by different time phase data, sign is reasonably charged at that time station location and capacity), have
Real-time, the degree of accuracy and validity are high.
Brief description of the drawings
Fig. 1 is the overall flow block diagram of the inventive method.
Fig. 2 is the charging pile optimum results schematic diagram of the embodiment of the present invention.
Embodiment
A kind of charging pile method to set up based on travelling data and Wei Nuotu zonings proposed by the present invention, with reference to
The drawings and specific embodiments are further described as follows.
A kind of charging pile method to set up based on travelling data and Wei Nuotu zonings proposed by the present invention, overall flow
As shown in figure 1, comprise the following steps：
1) to need set charging pile region division subregion；
Obtaining the map that needs to set charging pile region, (region can be a city, or a small towns, according to planning
Person's needs voluntarily to select；The present embodiment map uses high moral map)；On the map in the region, mark the region all
Some charging stations simultaneously calculate the distance of all charging stations between any two；If the distance between all charging stations be all higher than setting away from
From threshold value L, then each charging station in the region is arranged to a discrete data point on map；If in the presence of two charging stations it
Between distance be less than or equal to setting distance threshold L, then two charging stations are merged into a new charging station on map,
The position of the new charging station takes the central point of two charging station locations, and is arranged to each charging station in the region on map
One discrete data point (distance threshold can voluntarily be set as needed by user, and the present embodiment is preset as 200m)；Utilize
Discrete data point, by the region division it is different subregions by Wei Nuotu (Voronoi) methods, the number of subregion is equal to
The number of discrete data point；
The key for establishing Wei Nuotu is reasonably to be linked to be the triangulation network to discrete data point, that is, builds delaunay (Delaunay)
The triangulation network.Structure Delaunay triangulation network need to use Delaunay Triangulation algorithm, and the algorithm is primarily referred to as generating Wei Nuotu
When first generate its antithesis member Delaunay triangulation network, then find out the circumscribed circle center of circle of each triangle of the triangulation network, finally connect phase
The circumscribed circle center of circle of adjacent triangle, form the polygon latticed using each triangular apex as generation member.Establish the specific of Wei Nuotu
Step is as follows：
1-1) set discrete data point (present invention in by each it is existing charging station location be a discrete data point,
It should be strongly noted that when two charging station positional distances are less than the distance threshold of setting, two charging stations are considered as one
Charging station, the position of the charging station take the central point of two charging station locations, and the distance threshold can be as needed certainly by user
Row is set, and the present embodiment is preset as 200m), build Delaunay triangulation network.To discrete data point and each triangle formed
Numbering, triangle chained list is formed, it is three discrete data points that triangle chained list, which is used to record each triangle of composition,.
1-2) calculate the circumscribed circle center of circle of each triangle and record；
1-3) arbitrarily one triangle of selection is designated as current triangle pTri, traversing triangle chained list, finds and works as first three
Adjacent triangles of the angular pTri tri- while altogether is designated as TriA, TriB and TriC respectively；And judge：
If there is the adjacent triangle on common side, then the outer of the unfaithful intention of the adjacent triangle on the common side searched out and pTri
The heart connects, in the line segment deposit dimension promise side chain table of formation；If certain of the current triangle adjacent triangle when being not present altogether
Shape, then obtain the perpendicular bisector ray on the side and be stored in dimension promise side chain table.
Each triangle 1-4) is traveled through, all Wei Nuobian is found and is stored in dimension promise side chain table；Using tieing up promise side chain table
In all Wei Nuobian draw Wei Nuotu (i.e. needs that the present embodiment obtains set the Wei Nuotu in the region of charging pile).
2) travelling data is utilized, the maximum charge per sub-regions is calculated and loads, maximum therein is selected and records and be somebody's turn to do
Subregion is designated as A corresponding to maximum；
Charge requirement is the basis of charging electric vehicle facilities planning.Charge requirement is based primarily upon effective charge requirement vehicle
Number, vehicle average charge demand, subregion charging load are calculated.
Gps sensing equipments and travelling data collecting device need to be installed in the present invention on vehicle, are employed herein
In the market T-box equipment gathers travelling data, including：Vehicle parking position (latitude and longitude coordinates), data (time down time
Scope), charge position (latitude and longitude coordinates), charging interval data (time range) data, vehicle SOC (dump energy percentages
Than), calculate the charge requirement of the vehicle and charging load by these data.Comprise the following steps that：
Whole day 2-1) is divided into 24 periods by 1 hour, make i represent period sequence number, i=1,2,3 ... 24；When then
Between Duan Kewei 00：00-01：00,01：00-02：00 ... by that analogy, i=1, then it represents that period be 00：00-01：00；
Any one subregion 2-2) is chosen, calculates the effective charge requirement vehicle number of subregion；
Effective charge requirement vehicle refers to the electric automobile for having actual charge requirement in any time period in subregion, bag
Include following two parts：
Effective parking vehicle：Disposably stopped duration more than 30 minutes and SOC (remaining electricity in the subregion any time period
Amount percentage) less than residual power percentage threshold value E (the present embodiment 80%) electric automobile set it is designated as the period
Effective parking vehicle.Wherein, SOC electricity percentage threshold E can start to charge up the progress of SOC statistical results according to existing vehicle
Adjustment.
By way of vehicle：The subregion any time period electric automobile vehicle flowrate and the effectively difference of parking quantity.
Effective parking vehicle and the charging possibility by way of vehicle in the subregion have marked difference, effective parking vehicle
Charging possibility be much larger than by way of vehicle, therefore assign higher weight to effective parking vehicle.Subregion period i's
Effective charge requirement vehicle number calculation expression is as follows：
N0i=α Nei+βNpi
In formula, N0iFor effective charge requirement vehicle number of period i in subregion；NeiHave for period i in subregion
Imitate parking vehicle number；NpiFor in subregion period i by way of vehicle number；(NeiAnd NpiValue obtained by travelling data)
α is effectively parking weight coefficient (span：0-1, take 0.5) in the present embodiment；β is by way of vehicle weight coefficient
(span 0-0.5, take 0.15) in the present embodiment；
2-3) calculate subregion vehicle average charge demand；
Vehicle average charge demand refers to any time period effective charge requirement vehicle unit time in the subregion
Average charge demand.According to step 2-1) the obtained effective parking vehicle of division and by way of vehicle, any time period is chosen, point
SOCs of the SOC of each the effective parking vehicle period Nei with each by way of vehicle is not counted, and carries out accumulative summation, respectively
It is designated as ∑ SOCeiWith ∑ SOCpi, it is A to make vehicle average power battery capacity, then period i vehicle average charge needs in subregion
The amount of asking QiCalculation expression be：
Qi=[α (Nei* 100%- ∑s SOCei)+β·(Npi* 100%- ∑s SOCpi)]·A/N0i
The charging load of subregion all periods interior for a period of time 2-4) is calculated, the maximum charge for obtaining the subregion is born
Carry；
Subregion charging load is defined as in the subregion in any time period vehicle average charge demand and subregion
The ratio of charging pile charging ability.
Obtain the charging pile quantity of charging station in per sub-regions, the calculation expression of subregion any time period charging load
Formula is：
Ci=Qi·N0i/(Nc·q)
In formula, CiFor subregion charging load in period i, NcFor charging pile quantity in subregion；Q is to be filled in subregion
Electric stake average charge ability (being averaged to all charging pile charging abilities in subregion charging station, unit kw)；
Interception a period of time (such as one month), the charging for calculating all periods in the subregion in the time of interception are born
Carry, choose wherein corresponding to maximum the period and record the subregion charging load of the period and filled for the maximum of the subregion
Electric loading Cmax。
2-5) traversal step 1) the obtained all subregions of division, repeat step 2-2) to 2-4), every height is calculated
C corresponding to regionmax, choose wherein CmaxThe maximum subregion of value is designated as subregion A；
3) by subregion maximum charge load corresponding to A, (span is generally 0- with default charging load threshold value [C]
2, it is set to 1.2) be compared and judge in of the invention：If subregion A maximum charge load is higher than the charging load threshold of setting
It is worth, then subregion A is needed to increase charging station, and into step 4), the position of charging station may be set by calculating the subregion, to the son
The charging station location and charging pile quantity that region newly increases optimize；It is on the contrary, then it is assumed that whole region need not add charging station,
Setting completed for charging pile in the region.
4) value models are established to subregion A, using particle cluster algorithm to model solution, filled to what the subregion newly increased
Plant location and charging pile quantity optimize；Comprise the following steps that：
4-1) determine the object function of model；Expression formula is as follows
G=aDj+b·M
The object function is a cost function, including two parts of distance and cost；In formula, DjTo own in subregion
Vehicle drives to the minimum range sum that subregion A current charging station j is travelled, M represent subregion A set one it is new
The objective cost of charging station；A is 0.7) distance optimization weight (span 0-1, is taken in the present embodiment, b is cost optimization power
0.3) weight (span 0-1, is taken in the present embodiment；
DjCalculation expression it is as follows：
In formula, DjiThe distance of i-th vehicle and charging station j points is represented, k is vehicle fleet；
The planning of electrically-charging equipment needs to consider the cost of engineering, and needs consider target while user's convenient use is met
Cost.Objective cost M mainly considers charging station cost of investment Ms(including land used cost and construction cost), altogether charging pile are invested
Cost Mq, charging station O＆M cost MomAnd charging income Mp(deduction purchases strategies).Expression formula is as follows：
M=Min (Ms+Mq+Mom-Mp)
Wherein,
Ms=charging station quantity * charging stations construction unit cost
Mq=charging pile quantity * charging piles construction unit cost
Mom=charging pile quantity * operation maintenance cost * times unit charging pile unit interval
Mp=charging pile quantity * profit * times unit charging pile unit interval
4-2) to model solution；
Using particle cluster algorithm with the charging pile quantity accumulated in whole region, the charging station quantity accumulated,
Objective cost M and charging load threshold value [C] are that (constraints above condition can voluntarily be set constraints by designer according to self-condition
Put), the position (latitude and longitude coordinates) of charging station newly increased in subregion A and the quantity of charging pile are entered using G as object function
Row optimization, obtains the increased optimal charging station location in subregion A.Current invention assumes that needing the son of increase charging station every time
Region A only increases a charging station, then the result of particle cluster algorithm output is：Increase a charging station in the subregion, this is new
Increase charging pile quantity in the position coordinates and the newly-increased charging station of charging station.
5) the newly-increased charging station of the acquisition of step 4) is added in the map of step 1), returns to step 1), to all
The optimization that charging station re-starts sub-zone dividing and charging station calculates, until the charging station quantity accumulated in region, tired
Count increased charging pile quantity or objective cost and exceed constraints, setting completed for charging pile in the region.
Fig. 2 is charging pile optimum results schematic diagram in one embodiment of the present of invention, and area is Shanghai City as shown in Figure 2
Area, the present embodiment utilize the vehicle operation data of a period of time, and according to certain user's request, (i.e. parameter setting includes：Charging
Stake sum, the charging of charging station sum, charging load threshold value, charging station construction unit cost, charging pile construction unit cost, unit
Stake unit interval operation maintenance cost, unit charging pile unit interval profit, distance and cost weight), the charging pile rule of acquisition
The scheme of drawing.Figure orbicular spot represents Parking, and color, which is more deeply felt, shows that Parking is more, and thick straight line utilizes Wei Nuotu in figure
The zoning plan that method is drawn, two plus siges represent to be calculated using the inventive method in way adds charging station at two at this
It can be the optimal plan of establishment.
Claims (1)
1. a kind of charging pile method to set up based on travelling data and Wei Nuotu zonings, it is characterised in that including following step
Suddenly：
1) to need set charging pile region division subregion；
Obtain the map that needing, charging pile region is set；On the map in the region, all existing charging stations in the region are marked
And calculate the distance of all charging stations between any two；If the distance between all charging stations are all higher than the distance threshold L of setting,
Each charging station in the region is arranged to a discrete data point on map；It is if small in the presence of the distance between two charging stations
In the distance threshold L equal to setting, then two charging stations are merged into a new charging station on map, the new charging station
Position take the central points of two charging station locations, and each charging station in the region is arranged to a dispersion number on map
Strong point；It is different subregions by tieing up promise drawing method by the region division, the number of subregion is equal to using discrete data point
The number of discrete data point；
2) travelling data is utilized, the maximum charge per sub-regions is calculated and loads, select maximum therein and record the maximum
Subregion is designated as A corresponding to value；Comprise the following steps that：
Whole day 2-1) is divided into 24 periods by 1 hour, make i represent period sequence number, i=1,2,3 ... 24；
Any one subregion 2-2) is chosen, calculates the effective charge requirement vehicle number of subregion；
Effective charge requirement vehicle refers to the electric automobile for having actual charge requirement in random time section in subregion, including with
Lower two parts：
Effective parking vehicle：Disposably stopped duration more than 30 minutes and residual power percentage in the subregion any time period
Electric automobiles of the SOC less than the residual power percentage threshold value E of setting；
By way of vehicle：The subregion any time period electric automobile vehicle flowrate and the effectively difference of parking quantity；
Anyon zone time section i effective charge requirement vehicle number calculation expression is as follows：
N0i=α Nei+βNpi
In formula, N0iFor effective charge requirement vehicle number of period i in subregion；NeiStop for the effective of period i in subregion
Car vehicle number；NpiFor in subregion period i by way of vehicle number；α is effectively parking weight coefficient；β is by way of vehicle weight
Coefficient；
2-3) calculate subregion vehicle average charge demand；
Vehicle average charge demand refers to that any time period effective charge requirement vehicle unit time is averaged in the subregion
Charge requirement amount；According to step 2-1) the obtained effective parking vehicle of division and by way of vehicle, any time period is chosen, is united respectively
Count each the effective parking vehicle period Nei SOC and each by way of vehicle minimum SOC, and carry out accumulative summation, remember respectively
For ∑ SOCeiWith ∑ SOCpi, it is A to make vehicle average power battery capacity, then subregion period i vehicles average charge demand
QiCalculation expression be：
Qi=[α (Nei* 100%- ∑s SOCei)+β·(Npi* 100%- ∑s SOCpi)]·A/N0i
The charging load of subregion all periods interior for a period of time 2-4) is calculated, obtains the maximum charge load of the subregion；
The charging pile quantity of charging station in per sub-regions is obtained, the calculation expression of subregion any time period charging load is：
Ci=Qi·N0i/(Nc·q)
In formula, CiFor subregion charging load in period i；NcFor charging pile quantity in subregion；Q is charging pile in subregion
Average charge ability；
Interception a period of time, the charging load of all periods in the subregion in the time of interception is calculated,
Choose wherein corresponding to maximum the period and record the period subregion charging load be the subregion maximum
Charging load Cmax；
2-5) traversal step 1) the obtained all subregions of division, repeat step 2-2) to 2-4), every sub-regions are calculated
Corresponding Cmax, choose wherein CmaxThe maximum subregion of value is designated as subregion A；
3) subregion maximum charge load corresponding to A compared with charging load threshold value [C] and is judged：If subregion A's
Maximum charge load increases charging station higher than the charging load threshold value set, then subregion A, into step 4)；Conversely, Ze Gai areas
Setting completed for charging pile in domain；
4) value models are established to subregion A, using particle cluster algorithm to model solution, the charging station newly increased to the subregion
Position and charging pile quantity optimize；Comprise the following steps that：
4-1) determine the object function of model；Expression formula is as follows
G=aDj+b·M
In formula, DjThe minimum range sum that subregion A current charging station j travels, M are driven to by all vehicles in subregion
Represent the objective cost that a new charging station is set in subregion A；A is distance optimization weight, and b is cost optimization weight；
DjCalculation expression it is as follows：
In formula, DjiThe distance of i-th vehicle and charging station j points is represented, k is vehicle fleet；
Objective cost M includes：Charging station cost of investment Ms, charging pile cost of investment M altogetherq, charging station O＆M cost MomAnd fill
Electric income Mp；Expression formula is as follows：
M=Min (Ms+Mq+Mom-Mp)
4-2) to model solution；
Using particle cluster algorithm, with the charging pile quantity accumulated in whole region, the charging station quantity, the target that accumulate
Cost M and charging load threshold value [C] are constraints, are object function to the position of the charging station newly increased in subregion A using G
Optimized with the quantity of charging pile；Order only increases a charging station in the subregion A for needing to increase charging station every time, then particle
Group algorithm output result be：Increase a charging station in the subregion, the position coordinates of the newly-increased charging station and this newly-increased fill
Charging pile quantity in power station；
5) the newly-increased charging station of the acquisition of step 4) is added in the map of step 1), step 1) is returned to, to all chargings
Station re-starts sub-zone dividing and the optimization of charging station calculates, until the charging station quantity accumulated in region, accumulative increasing
The charging pile quantity or objective cost added exceeds constraints, and setting completed for charging pile in the region.
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