CN106447129B - A kind of efficient charging station recommended method based on quick charge stake - Google Patents
A kind of efficient charging station recommended method based on quick charge stake Download PDFInfo
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- CN106447129B CN106447129B CN201610928953.3A CN201610928953A CN106447129B CN 106447129 B CN106447129 B CN 106447129B CN 201610928953 A CN201610928953 A CN 201610928953A CN 106447129 B CN106447129 B CN 106447129B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C11/00—Arrangements, systems or apparatus for checking, e.g. the occurrence of a condition, not provided for elsewhere
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C11/00—Arrangements, systems or apparatus for checking, e.g. the occurrence of a condition, not provided for elsewhere
- G07C2011/04—Arrangements, systems or apparatus for checking, e.g. the occurrence of a condition, not provided for elsewhere related to queuing systems
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/10—Technologies relating to charging of electric vehicles
- Y02T90/16—Information or communication technologies improving the operation of electric vehicles
- Y02T90/167—Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S30/00—Systems supporting specific end-user applications in the sector of transportation
- Y04S30/10—Systems supporting the interoperability of electric or hybrid vehicles
- Y04S30/12—Remote or cooperative charging
Abstract
The efficient charging station recommended method based on quick charge stake that the present invention provides a kind of, characterized by comprising the following steps: step 1: the charge information including electric car VIN code of the electric car to charge is uploaded to charging pile network server by the charging pile of each charging station；……；Step 5: the prediction that real-time predictive server calculates each charging station in real time is lined up duration；Step 6: the scheduled time T that the electric car reaches each charging station is calculated in the Rechargeable vehicle for initiating charging station predictions request by user's intelligent terminal, real-time predictive server firstj(t)；Step 7: real-time predictive server by each charging station predict at the time of starting to charge and the waiting time of prediction returns to user's intelligent terminal of request prediction.Efficient charging station recommended method of the invention can effectively reduce queuing time, save the time of driver and improve the service efficiency of charging pile.Queue length is reduced, the utilization rate of charging pile is improved.
Description
Technical field
The invention belongs to electric vehicles and charging station to control management domain, in particular to a kind of based on the efficient of quick charge stake
The charging station recommended method of rate.
Background technique
The recommendation of existing charging pile is all based on reservation and the state of existing charging pile is judged, and mentions to user
For the inquiry and reservation of charging pile.Substantially reserve the reservation for being all based on time slice.
The charging pile of exchanging trickle charge is usually all at 6 more than hour, and the charging pile of direct current charge is at least also required to half
More than a hour, existing charging pile recommends and reservation technology, can effectively improve the service efficiency of these charging piles.But it is right
In newest high power direct current charge charging pile and the electric car that can be full of at 10 minutes or so of quick charge is supported
It says, with charging just facilitates present oiling as, and most probable usage scenario is, queuing is charged at the scene, with to filling,
It does not need to reserve.
Summary of the invention
Goal of the invention of the invention is to provide a kind of efficient charging pile recommended method based on quick charge stake, can
It is effective to reduce queuing time, it saves the time of driver and improves the service efficiency of charging pile.It can also can be provided for user
More autonomous selections, reduce queue length, improve the utilization rate of charging pile.
The specific technical solution of the present invention is a kind of efficient charging station recommended method based on quick charge stake, is used
The recommender system of composition including electric car car running computer, user's intelligent terminal, real-time predictive server and charging station, it is described
Charging station include charging pile and charging pile network server, which comprises the following steps:
Step 1: the charging pile of each charging station is by the charging including electric car VIN code of the electric car to charge
Information is uploaded to charging pile network server, and is transferred by charging pile network server to real-time predictive server；
Step 2: module is connected user's intelligent terminal by wireless communication with electric car car running computer, passes through movement
Communication network or WiFi access recommender system, electric car VIN code are transferred to real-time predictive server, and be uploaded in real time
The GPS position information of this electric vehicle of real-time predictive server；
Step 3: the GPS position information that real-time predictive server is uploaded according to user's intelligent terminal, temporally node statistics
J-th of charging station different distance and different timing nodes electric car charge conversion ratio,
Since 0 point of one day, counted for the period away from electric car number uncharged within charging station 50m with 10 minutes
AmountWherein t1Current time when to count, in statistics moment t1In 30 minutes afterwards, acquisition existsThe quantity of the Rechargeable vehicle to charge is actually transferred in quantityWhen obtaining statistics
Carve t1Electric car charge conversion ratio It is calculatedFor
Within away from charging station 50m, including statistics moment t1The statistics moment t of first 30 days of the same day1Average electric car charging turns
Rate,
Since 0 point of one day, counted for the period away from except charging station 50m and not filling within 1km with 15 minutes
The electric car quantity of electricityIn statistics moment t2In 30 minutes afterwards, acquisition existsIt is practical in quantity
It is converted into the quantity of the Rechargeable vehicle to chargeObtain statistics moment t2Electric car charging turn
RateIt is calculatedFor except away from charging station 50m
And within 1km, including statistics moment t2The statistics moment t of first 30 days of the same day2Average electric car charging conversion ratio,
Since 0 point of one day, counted for the period away from except charging station 1km and not filling within 10km with 30 minutes
The electric car quantity of electricityIn statistics moment t3In 60 minutes afterwards, acquisition existsIt is practical in quantity
It is converted into the quantity of the Rechargeable vehicle to chargeObtain statistics moment t3Electric car charge conversion
RateIt is calculatedFor except away from charging station 1km simultaneously
Within 10km, including statistics moment t3The statistics moment t of first 30 days of the same day3Average electric car charging conversion ratio,
Since 0 point of one day, with 60 minutes for the period count away from except charging station 10km and within 50km not
The electric car quantity of chargingIn statistics moment t4In 90 minutes afterwards, acquisition existsIt is real in quantity
Border is converted into the quantity of the Rechargeable vehicle to chargeObtain statistics moment t4Electric car charging
Conversion ratio It is calculatedFor away from charging station 10km it
It is outer and within 50km, including statistics moment t4The statistics moment t of first 30 days of the same day4Average electric car charging conversion ratio；
Step 4: the GPS position information that real-time predictive server is uploaded according to user's intelligent terminal is calculated uncharged
I-th electric car speed per hour ViIf DijFor i-th distance of the electric car away from j-th of charging station, if t is current time,
D is calculatedij≤ 50m and ViThe quantity of the uncharged electric car of≤5km/h, is denoted as j-th of charging station
It is lined up radix Q1 in real timej(t),
50m < D is calculatedijThe quantity of≤1km and the uncharged electric car of unlimited electric car speed per hour, are denoted as
J-th of charging station is lined up radix Q2 in real timej(t),
1km < D is calculatedijThe quantity of≤10km and the uncharged electric car of unlimited electric car speed per hour, are denoted as
J-th of charging station is lined up radix Q3 in real timej(t),
10km < D is calculatedijThe quantity of≤50km and the uncharged electric car of unlimited electric car speed per hour, note
It is lined up radix Q4 in real time for j-th of charging stationj(t)；
Step 5: the prediction that real-time predictive server calculates each charging station in real time is lined up duration,
If T1j(t)It is lined up duration for the prediction away from the uncharged automobile within charging station 50m, if T2j(t)For away from the charging
The prediction for the uncharged automobile stood except 50m and within 1km is lined up duration, if T3j(t)For away from except charging station 1km and
The prediction of uncharged automobile within 10km is lined up duration, if T4j(t)For away from except charging station 10km and within 50km
The prediction of uncharged automobile is lined up duration,
T1j(t)、T2j(t)、T3j(t)And T4j(t)Formula (I), (II), (III) and (IV) is pressed respectively to calculate,
Upper formula (I), (II), in (III) and (IV), t1、t2、t3And t4Obtaining value method be, with nearest away from current time
Count moment selection t1、t2、t3And t4Value, a be constant indicate charging station average charge duration, by nearest the one of the charging station
After a month charging total duration is divided by Rechargeable vehicle quantity, then obtain divided by the quantity of the charging station charging pile；
Step 6: the Rechargeable vehicle for initiating charging station predictions request by user's intelligent terminal, in real time prediction service
The scheduled time T that the electric car reaches each charging station is calculated in device firstj(t),
If Tj(t)≤t+T1j(t), then that electric car prediction is t+T1 at the time of starting to chargej(t), when needing to wait
Between be predicted as t+T1j(t)-Tj(t),
If t+T1j(t)<Tj(t)≤t+T2j(t), then that electric car prediction is t+T2 at the time of starting to chargej(t), need
The waiting time is wanted to be predicted as t+T2j(t)-Tj(t),
If t+T2j(t)<Tj(t)≤t+T3j(t), then that electric car prediction is t+T3 at the time of starting to chargej(t), need
The waiting time is wanted to be predicted as t+T3j(t)-Tj(t),
If t+T3j(t)<Tj(t)≤t+T4j(t), then that electric car prediction is t+T4 at the time of starting to chargej(t), need
The waiting time is wanted to be predicted as t+T4j(t)-Tj(t),
If t+T4j(t)<Tj(t), then that electric car prediction is t+T at the time of starting to chargej(t), need the waiting time
It is predicted as 0；
Step 7: real-time predictive server by each charging station predict at the time of starting to charge and the waiting time of prediction
Return to user's intelligent terminal of request prediction, user's intelligent terminal is according to the prediction latency time received from being short to long carry out pair
Charging station is ranked up.
The efficient charging pile recommended method based on quick charge stake that the beneficial effects of the invention are as follows of the invention, in electricity
Electrical automobile when needing to charge, can recommend to driver out under current electric quantity when can reach in course continuation mileage with regard to chargeable
The probability distribution of charging pile list can effectively reduce queuing time, save the time of driver and improve the use of charging pile
Efficiency.More autonomous selections can be provided for user, user can be according to oneself time, in conjunction with the direction of traveling, independently
Decision charge in that charging station, while the queuing efficiency of charging pile can also be improved, reduce queue length, raising is filled
The utilization rate of electric stake can be effectively saved the time of user and reduce charging station congestion.
Detailed description of the invention
Fig. 1 is the flow chart using the efficient charging station recommended method of the invention based on quick charge stake；
Fig. 2 is the group using the recommender system of the efficient charging station recommended method of the invention based on quick charge stake
At schematic diagram.
Specific embodiment
Technical solution of the present invention is further described with reference to the accompanying drawings of the specification.
Intelligent charging spot 3 is connected with charging pile server 2 by WLAN, and intelligent charging spot 3 passes through charge port and filling
The electric car 6 of electricity is connected, and obtains charge information of electric car, including VIN code etc..Charging pile server 2 by WLAN with
Real-time predictive server is connected.
Module is connected user's intelligent terminal 5 by wireless communication with electric car car running computer 4, and obtains electric car
VIN code simultaneously passes through acquisition GPS information, by mobile communications network or the real-time predictive server 1 of WiFi connection, by electric car
VIN code and GPS information are transferred to real-time predictive server 1.
The current course continuation mileage of the electric car 6 of one traveling on the way is 100 kilometers, and current time t is 8:42, user
Charging station predictions request is initiated by intelligent terminal 5, and real-time predictive server 1 inquires charging station within the scope of course continuation mileage and pre-
It counts arrival time available charging station list and corresponding E.T.A is as follows:
| Charging station | E.T.A |
| Station1 | 8:50 |
| Station2 | 9:15 |
| Station3 | 10:36 |
E.T.A can be by implementation predictive server according to the position of electric car, using some of the prior art
Commerce services can obtain, such as just built-in such service in some navigation softwares.
Real-time predictive server 1 obtains the row of above-mentioned 3 charging stations according to the GPS data that current all electric cars report
Team radix Q1, Q2, Q3, Q4 is as follows:
| Charging station | Q1 | Q2 | Q3 | Q4 |
| Station1 | 5 | 10 | 5 | 20 |
| Station2 | 4 | 8 | 5 | 10 |
| Station3 | 3 | 2 | 5 | 12 |
30 days electric car GPS datas and the charge data with above-mentioned 3 charging stations are obtained, can be calculated by formula
It obtains 3 charging stations and corresponds to the charging of average electric car conversion ratio P1, P2, P3, the P4 at moment such as in above-mentioned E.T.A
Under:
| Charging station | Moment | P1 | P2 | P3 | P4 |
| Station1 | 8:50 | 50% | 80% | 80% | 70% |
| Station2 | 9:15 | 70% | 70% | 90% | 70% |
| Station3 | 10:36 | 80% | 70% | 60% | 50% |
By available above-mentioned 3 charging stations of the charge data of the last 30 days average charge when long constant a it is as follows:
Estimated queuing duration T1, T2, T3, T4 data that 3 charging stations are calculated according to formula are as follows:
| Charging station | T1 (minute) | T2 (minute) | T3 (minute) | T4 (minute) |
| Station1 | 12.5 | 52.5 | 72.5 | 142.5 |
| Station2 | 4.2 | 15.4 | 24.4 | 38.4 |
| Station3 | 24 | 38 | 68 | 128 |
It is lined up duration according to the prediction in the electric car estimated charging time for reaching 3 charging stations and 3 charging stations, it can be with
Judge that electric car meets the following condition of 3 charging stations, and can be started to charge according to the calculation formula of respective conditions
Moment and need the waiting time:
| Charging station | Meet condition | Start to charge the moment | It needs waiting time (minute) |
| Station1 | Tj(t)≤t+T1j(t) | 9:02 | 12 |
| Station2 | t+T3j(t)<Tj(t)≤t+T4j(t) | 9:20 | 5 |
| Station3 | t+T3j(t)<Tj(t)≤t+T4j(t) | 10:50 | 14 |
The queuing result for the charging station that intelligent terminal 5 obtains are as follows:
[{ " StationName ": " Station1 ", " Waiting ": 5, " PossibleChargingTime ": " 9:
20 " },
{ " StationName ": " Station2 ", " Waiting ": 12, " PossibleChargingTime ": " 9:
02 " },
{ " StationName ": " Station3 ", " Waiting ": 14, " PossibleChargingTime ": " 10:
50”}]
User returns the result (the possible waiting time may start to charge the time) according to what intelligent terminal 5 was shown, in conjunction with certainly
Oneself traffic route independently determines the charging station to be gone.
Claims (1)
1. a kind of efficient charging station recommended method based on quick charge stake, using including electric car car running computer, use
The recommender system of the composition of family intelligent terminal, real-time predictive server and charging station, the charging station include charging pile and fill
Electric stake network server, which comprises the following steps:
Step 1: the charging pile of each charging station is by the charge information including electric car VIN code of the electric car to charge
It is uploaded to charging pile network server, and is transferred by charging pile network server to real-time predictive server；
Step 2: module is connected user's intelligent terminal by wireless communication with electric car car running computer, passes through mobile communication
Network or WiFi access recommender system, and electric car VIN code is transferred to real-time predictive server, and are uploaded in real time in real time
The GPS position information of electric car described in predictive server；
Step 3: the GPS position information that real-time predictive server is uploaded according to user's intelligent terminal, temporally node statistics jth
For a charging station in the electric car charging conversion ratio of different distance and different timing nodes, j is the positive integer greater than 0,
Since 0 point of one day, counted for the period away from electric car quantity uncharged within charging station 50m with 10 minutesWherein t1Current time when to count, in statistics moment t1In 30 minutes afterwards, acquisition exists
The quantity of the Rechargeable vehicle to charge is actually transferred in quantityObtain statistics moment t1It is electronic
Automobile charging conversion ratio It is calculatedFor away from the charging
It stands within 50m, including statistics moment t1The statistics moment t of first 30 days of the same day1Average electric car charging conversion ratio,
Since 0 point of one day, counted for the period away from except charging station 50m and uncharged within 1km with 15 minutes
Electric car quantityIn statistics moment t2In 30 minutes afterwards, acquisition existsIt is actually converted in quantity
Quantity for the Rechargeable vehicle to chargeObtain statistics moment t2Electric car charge conversion ratioIt is calculatedFor except away from charging station 50m and
Within 1km, including statistics moment t2The statistics moment t of first 30 days of the same day2Average electric car charging conversion ratio,
Since 0 point of one day, counted for the period away from except charging station 1km and uncharged within 10km with 30 minutes
Electric car quantityIn statistics moment t3In 60 minutes afterwards, acquisition existsIt is actually converted in quantity
Quantity for the Rechargeable vehicle to chargeObtain statistics moment t3Electric car charge conversion ratioIt is calculatedFor except away from charging station 1km and
Within 10km, including statistics moment t3The statistics moment t of first 30 days of the same day3Average electric car charging conversion ratio,
Since 0 point of one day, counted for the period away from except charging station 10km and uncharged within 50km with 60 minutes
Electric car quantityIn statistics moment t4In 90 minutes afterwards, acquisition existsActually turn in quantity
Turn to the quantity of the Rechargeable vehicle to chargeObtain statistics moment t4Electric car charge conversion
Rate It is calculatedFor except away from charging station 10km simultaneously
Within 50km, including statistics moment t4The statistics moment t of first 30 days of the same day4Average electric car charging conversion ratio；
Step 4: the GPS position information that real-time predictive server is uploaded according to user's intelligent terminal is calculated uncharged the
The speed per hour V of i electric cari, i is the positive integer greater than 0, if DijFor i-th distance of the electric car away from j-th of charging station,
If t is current time,
D is calculatedij≤ 50m and ViThe quantity of the uncharged electric car of≤5km/h, it is real-time to be denoted as j-th of charging station
It is lined up radix Q1j(t),
50m < D is calculatedijThe quantity of≤1km and the uncharged electric car of unlimited electric car speed per hour, are denoted as j-th
Charging station is lined up radix Q2 in real timej(t),
1km < D is calculatedijThe quantity of≤10km and the uncharged electric car of unlimited electric car speed per hour, are denoted as jth
A charging station is lined up radix Q3 in real timej(t),
10km < D is calculatedijThe quantity of≤50km and the uncharged electric car of unlimited electric car speed per hour, are denoted as jth
A charging station is lined up radix Q4 in real timej(t)；
Step 5: the prediction that real-time predictive server calculates each charging station in real time is lined up duration,
If T1j(t)It is lined up duration for the prediction away from the uncharged automobile within charging station 50m, if T2j(t)For away from the charging station
The prediction of uncharged automobile except 50m and within 1km is lined up duration, if T3j(t)For away from except charging station 1km and
The prediction of uncharged automobile within 10km is lined up duration, if T4j(t)For away from except charging station 10km and within 50km
The prediction of uncharged automobile is lined up duration,
T1j(t)、T2j(t)、T3j(t)And T4j(t)Formula (I), (II), (III) and (IV) is pressed respectively to calculate,
Upper formula (I), (II), in (III) and (IV), t1、t2、t3And t4Obtaining value method be, with the statistics nearest away from current time
Moment chooses t1、t2、t3And t4Value, a be constant indicate charging station average charge duration, by nearest one month of the charging station
After the total duration that charges is divided by Rechargeable vehicle quantity, then obtain divided by the quantity of the charging station charging pile；
Step 6: the Rechargeable vehicle for initiating charging station predictions request by user's intelligent terminal, real-time predictive server are first
The scheduled time T that the electric car reaches each charging station is first calculatedj(t),
If Tj(t)≤t+T1j(t), then that electric car prediction is t+T1 at the time of starting to chargej(t), need the waiting time pre-
Surveying is t+T1j(t)-Tj(t),
If t+T1j(t)<Tj(t)≤t+T2j(t), then that electric car prediction is t+T2 at the time of starting to chargej(t), need
It is t+T2 to time predictionj(t)-Tj(t),
If t+T2j(t)<Tj(t)≤t+T3j(t), then that electric car prediction is t+T3 at the time of starting to chargej(t), need
It is t+T3 to time predictionj(t)-Tj(t),
If t+T3j(t)<Tj(t)≤t+T4j(t), then that electric car prediction is t+T4 at the time of starting to chargej(t), need
It is t+T4 to time predictionj(t)-Tj(t),
If t+T4j(t)<Tj(t), then that electric car prediction is t+T at the time of starting to chargej(t), the waiting time is needed to predict
It is 0；
Step 7: real-time predictive server returns what each charging station was predicted at the time of starting to charge with the waiting time of prediction
To user's intelligent terminal of request prediction, user's intelligent terminal is carried out from length is short to charging according to the prediction latency time received
Station is ranked up.
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| CN112115350A (en) * | 2020-08-27 | 2020-12-22 | 上海电享信息科技有限公司 | Smart city charging intelligent recommendation method and system |
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| CN105095611A (en) * | 2015-09-25 | 2015-11-25 | 东南大学 | Highway electric vehicle quick charging station queuing algorithm |
| CN105398347A (en) * | 2015-10-21 | 2016-03-16 | 北京小飞快充网络科技有限公司 | Electric vehicle intelligent queuing method capable of improving charging efficiency |
| CN105760949A (en) * | 2016-02-04 | 2016-07-13 | 国网山东省电力公司经济技术研究院 | Optimizing configuration method for amount of chargers of electromobile charging station |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN105046442A (en) * | 2015-08-10 | 2015-11-11 | 安徽普为智能科技有限责任公司 | Electric vehicle charging station charging management method |
| CN105095611A (en) * | 2015-09-25 | 2015-11-25 | 东南大学 | Highway electric vehicle quick charging station queuing algorithm |
| CN105398347A (en) * | 2015-10-21 | 2016-03-16 | 北京小飞快充网络科技有限公司 | Electric vehicle intelligent queuing method capable of improving charging efficiency |
| CN105760949A (en) * | 2016-02-04 | 2016-07-13 | 国网山东省电力公司经济技术研究院 | Optimizing configuration method for amount of chargers of electromobile charging station |
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