CN113077113A

CN113077113A - Intelligent planning and design method for charging infrastructure

Info

Publication number: CN113077113A
Application number: CN202110505504.9A
Authority: CN
Inventors: 胡海锋; 胡英健; 刘峻峰; 童君
Original assignee: Chengdu Tgood New Energy Co Ltd
Current assignee: Deri Energy Research Institute; Chengdu Tgood New Energy Co Ltd; Qingdao Teld New Energy Technology Co Ltd
Priority date: 2021-05-10
Filing date: 2021-05-10
Publication date: 2021-07-06
Anticipated expiration: 2041-05-10
Also published as: CN113077113B

Abstract

The invention provides an intelligent planning and designing method of charging infrastructure, which comprises the following steps: s1, collecting line type information, shift point position information, number information of vehicles equipped on a line, vehicle type energy consumption information and charging station position information; s2, obtaining a line charging station and a charging demand point according to the position information of the departure point and the position information of the charging station; s3, obtaining a planning charging station by using a planning merging model according to the charging demand point; and S4, measuring and calculating the required configuration number of the charging equipment in the planned charging station by using a service capacity measuring and calculating model according to the vehicle number information and the vehicle type energy consumption information allocated to the line. The invention obtains an optimal planning design scheme by continuous dynamic planning and adjustment, thereby realizing the minimization of investment and the maximization of benefit.

Description

Intelligent planning and design method for charging infrastructure

Technical Field

The invention relates to the technical field of charging piles and charging infrastructures, in particular to an intelligent planning and design method for the charging infrastructures.

Background

With the continuous development of new energy electric vehicles, more and more electric vehicle charging infrastructures (networks, stations and points) exist in cities, no design standard exists for planning and site selection and site design scale of the electric vehicle charging infrastructures (networks, stations and points), and particularly for planning and designing the urban charging infrastructures (networks, stations and points), no reasonable design principle exists at present for the building of the charging infrastructures (networks, stations and points) and the large scale of the charging infrastructures. The design of the unguided planning can finally lead to the problems of unbalanced space distribution of the charging station, too high idle rate of equipment, too large investment cost, social resource waste, unavailable investment and poor charging experience of users. Therefore, there is a need to provide a charging infrastructure intelligent planning and designing method to overcome the above problems.

Disclosure of Invention

The invention provides an intelligent planning and designing method for a charging infrastructure, which aims to solve the problems that the existing planning and site selection of the charging infrastructure of an electric vehicle and the site design scale do not have a design standard, so that the space distribution of a charging station is unbalanced, the equipment idle rate is too high, the investment cost is too high, social resources are wasted, the investment cannot be gained, and the charging experience of a user is poor.

In order to solve the technical problems, the technical scheme adopted by the invention is as follows:

an intelligent planning and design method for charging infrastructure comprises the following steps:

s1, collecting line type information, shift point position information, number information of vehicles equipped on a line, vehicle type energy consumption information and charging station position information;

s2, obtaining a line charging station and a charging demand point according to the position information of the departure point and the position information of the charging station;

s3, obtaining a planning charging station by using a planning merging model according to the charging demand point;

and S4, measuring and calculating the required configuration number of the charging equipment in the planned charging station by using a service capacity measuring and calculating model according to the vehicle number information and the vehicle type energy consumption information allocated to the line.

Further, step S2 includes:

and S21, judging whether a charging station exists in a range with the shift point as the circle center and the radius of a kilometer or not according to the shift point position information and the charging station position information.

Further, step S2 further includes:

and S22, if a charging station exists in the kilometer range of the shift point a, whether the charging station has the residual service capacity is measured and calculated according to the service capacity measuring and calculating model.

Further, step S2 further includes:

and S23, if the charging station has the residual service capacity, confirming that the charging station is a line charging station.

Further, step S2 further includes:

and S24, if the charging station has no residual service capacity, confirming that the departure point is a charging demand point.

Further, step S2 further includes:

and S25, if no charging station exists in the range of a kilometer of the departure point, confirming the departure point as a charging demand point.

Further, in step S3, the planning and merging model includes:

if S (m1, m2) > 2aKM, X1 is (m1X, m1y), X2 is (m2X, m2y), where m is the total number of lines, m is (line 1, line 2, line 3 … …, line Z), m1 is the departure point of line 1, m2 is the departure point of line 2, S (m1, m2) is the distance between departure point m1 and departure point m2, (m1X, m1y) is the set of geographic coordinates with departure point m1 as the center and a kilometer as the radius, (m2X, m2y) is the set of geographic coordinates with departure point m2 as the center and a kilometer as the radius, KM is the KM as the total number of charging stations, and X is the total number of charging stations (charging station X1, charging station X2, charging station X3 … …).

Further, in step S3, the planning and merging model further includes:

if S (m1, m2) ≦ 2aKM, X1 ═ m1X, m1y ≦ m2X, m2 y.

Further, in step S3, the planning and merging model further includes:

if S (m1, m2) < 2aKM, S (m1, m3) < 2aKM, and S (m2, m3) < 2aKM, X1 is (m1X, m1y) — (m2X, m2y) — n (m3X, m3y), where m3 is the forward point of the line 3, S (m1, m3) is the distance between the forward point m1 and the forward point m3, S (m2, m3) is the distance between the forward point m2 and the forward point m3, and (m3X, m3y) is a set of geographic coordinates with the forward point m3 as the center and a kilometer as the radius.

Further, in step S3, the planning and merging model further includes:

if S (m1, m2) ═ 2aKM, S (m1, m3) ═ 2aKM, and S (m2, m3) ═ 2aKM, X1 ═ m1X, m1y ═ n (m2X, m2y), X2 ═ m1X, m1y ═ n (m3X, m3y), X3 ═ m2X, m2y ═ n (m3X, m3 y).

Compared with the prior art, the invention has the following beneficial effects: the intelligent planning and design method for the charging infrastructure combines the power stations in the range through the planning and combining model, combines the respective investment construction of the original two or more charging stations into the investment construction of one power station, and greatly saves the total investment cost of the project;

through the service capacity measuring and calculating model, the charging equipment demand carding can be accurately calculated for the charging stations at different positions, and the excessive throwing of the charging equipment is avoided, so that the overall utilization rate of the equipment is influenced;

the dynamic planning and adjusting model keeps the configuration number of the charging equipment within a limit value all the time while meeting the charging requirement, and after the construction condition of a single charging station is changed, all the charging stations are in linkage change, so that the charging requirement can be met while the input quantity of the charging equipment is controllable, and the situation that the charging requirement is excessive and the charging congestion is caused due to too few input equipment of some charging stations is avoided.

And continuously planning and adjusting through a dynamic planning and adjusting model to finally obtain an optimal intelligent planning and designing scheme of the charging infrastructure, so that the investment minimization and the benefit maximization are realized.

Drawings

Fig. 1 is a schematic step diagram of an intelligent planning and designing method for charging infrastructure according to the present invention.

Fig. 2 is a schematic flow chart of the dynamic programming adjustment model logic according to the third embodiment of the present invention.

Fig. 3 is a schematic diagram of initial planning data in a third embodiment of the present invention.

Fig. 4 is a schematic diagram of a dynamic transfer of vehicle demand in the third embodiment of the present invention.

Fig. 5 is a schematic diagram of a multi-group Sxy scheme in the third embodiment of the present invention.

Detailed Description

The technical solutions of the present invention are further described in detail below with reference to the accompanying drawings, but the scope of the present invention is not limited to the following.

In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings of the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.

The present invention will be further described with reference to the following examples, which are intended to illustrate only some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, other embodiments used by those skilled in the art without any creative effort belong to the protection scope of the present invention.

Referring to fig. 1 to 5, an embodiment of the present invention is shown, which is for illustration purposes only and is not limited to this structure.

Example one

As shown in fig. 1, an intelligent planning and designing method for charging infrastructure includes the following steps:

s4, measuring and calculating the required configuration number of charging equipment in the planned charging station by using a service capacity measuring and calculating model according to the number information of vehicles and the energy consumption information of the vehicles, which are allocated on the line;

s5, dynamically adjusting the required configuration number of the charging equipment in the planning charging station by using a dynamic planning adjustment model according to the line type information and the line charging station to obtain the actual configuration number of the charging equipment in the planning charging station;

and S6, the planning charging station and the actual configuration number of the charging equipment in the planning charging station are the intelligent planning design scheme of the charging infrastructure.

Wherein, in the practical application process, a is set to 1 or 2 or 3 or 4 … … ZKM according to the practical situation, such as the line type information, the line charging station, the density of the shift points in a certain area, the average number of vehicles at the shift points, and the like.

Step S2 includes:

and S21, judging whether a charging station exists in a range with the shift point as the circle center and the radius of 2 kilometers or not according to the shift point position information and the charging station position information.

And S22, if a charging station exists within the range of 2 kilometers of the shift point, whether the charging station has the residual service capacity is measured and calculated according to the service capacity measuring and calculating model.

And S25, if no charging station exists within the range of 2 kilometers of the departure point, confirming that the departure point is a charging demand point.

In step S3, the planning and merging model includes:

if S (m1, m2) > 4KM, X1 is (m1X, m1y), X2 is (m2X, m2y), where m is the total number of lines, m is (line 1, line 2, line 3 … …, line Z), m1 is the departure point of line 1, m2 is the departure point of line 2, S (m1, m2) is the distance between departure point m1 and departure point m2, (m1X, m1y) is the set of geographic coordinates with departure point m1 as the center and 2 KM as the radius, (m2X, m2y) is the set of geographic coordinates with departure point m2 as the center and 2 KM as the radius, KM as the total number of charging stations, and X is (charging station X1, charging station X2, charging station X3 … …, and XZ planning).

If S (m1, m2) ≦ 4KM, X1 ═ m1X, m1y ≦ n (m2X, m2 y).

If S (m1, m2) < 4KM, S (m1, m3) < 4KM, and S (m2, m3) < 4KM, X1 is (m1X, m1y) — n (m2X, m2y) — n (m3X, m3y), where m3 is the shift point of the line 3, S (m1, m3) is the distance between the shift point m1 and the shift point m3, S (m2, m3) is the distance between the shift point m2 and the shift point m3, and (m3X, m3y) is a set of geographic coordinates with the shift point m3 as the center and 2 KM as the radius.

If S (m1, m2) ═ 4KM, S (m1, m3) ═ 4KM, and S (m2, m3) ═ 4KM, X1 ═ m1X, m1y) — (m2X, m2y), X2 ═ m1X, m1y ═ m3X, m3y, and X3 ═ m2X, m2y — (m3X, m3 y).

The planning and merging model further needs to consider the existing charging stations, that is, the line charging stations confirmed in step S23, measure and calculate the remaining service capacity of the line charging stations, that is, the actual configuration number is subtracted from the maximum configuration number of the line charging stations, the actual configuration number of the charging devices of the planning and charging stations is measured and calculated, and under the condition that the shift point is within 2 km of the charging stations, the vehicles are preferentially planned to the line charging stations until the line charging stations have no remaining service capacity, so that the number of the charging devices to be finally constructed is the actual configuration number of the charging devices of the planning and charging stations minus the number of the vehicles planned to the line charging stations.

Example two

The second embodiment is a further optimization of the first embodiment.

The present embodiment further describes the technical solution of the present invention by taking an electric bus as an example.

The electric buses may be classified into slow-charging type electric buses and fast-charging type electric buses according to the characteristics of the vehicles.

Electric bus of type that charges slowly and its charging station characteristics:

1. long endurance: the subsequent voyage after one-time full charging can reach 200-;

2. the charging speed is slow: due to the characteristics of the vehicle, the vehicle has small receiving power, small charging power and low charging speed;

3. charging time period: the vehicle charging time is mainly concentrated at night, the single charging time is 4-6 hours, and the requirement of multi-day operation can be met after the vehicle is fully charged at night;

4. planning and designing elements of the charging station: only need select a place that the area is enough big, build a centralized charging station, the bus is gone to at night and is fully charged can to the electricity. The distance between the charging station and the daily bus shift dispatching station does not need to be considered, and factors such as daily operation route mileage, operation shift dispatching time and the like of the bus do not need to be considered.

Quick-charging type electric bus and charging station characteristics thereof:

1. the endurance mileage is short: the subsequent mileage after single full power is 40-60km, multiple times of charging are needed in the daytime, and the space dependence on a charging station is high;

2. the charging power is large: due to the characteristics of the vehicle, the vehicle has large receiving power, large charging power and high charging speed;

3. charging time period: the vehicle charging time is mainly in the daytime operation period, the single charging is carried out for 10-15 minutes, and the charging is carried out for multiple times in the daytime;

4. planning and designing elements of the charging station: because the vehicle is charged during the daytime operation, the charging station needs to be selected near the vehicle departure point, and the planning design of the charging station needs to take the line as the planning core, so that the full coverage of line charging is realized. Meanwhile, factors such as shift frequency, vehicle type, route mileage, operation mode and the like of the vehicle need to be considered in planning and design of the charging station, and a vehicle charging plan needs to be combined with an operation plan.

Aiming at the quick-charging type electric bus, the vehicle needs to adopt high-power charging equipment, because different vehicle types have different energy consumption per kilometer, different receivable charging amounts per minute, different lines have different vehicle operation mileage and different daily charging durations, so that a single set of high-power charging equipment can meet the charging requirements of how many vehicles are charged, and the charging equipment needs to carry out comprehensive calculation according to the daily effective charging amount of vehicle type lines and the daily consumed electric quantity of the vehicle.

The bus route and vehicle initial data of a certain place are as follows:

the service capacity measurement model is as follows:

T＝C/(H*S)；

t: the number of vehicles, units (stations) that a single set of charging equipment can serve;

c: the single set of charging equipment effectively outputs electric quantity in unit (degree) every day;

h: power consumption per kilometer of line vehicle type, unit (degree/kilometer);

s: the daily running mileage of the line vehicle is unit (kilometer);

the quick-charging type electric bus generally has three types: 6 meters, 10 meters and 18 meters, and the power consumption of each vehicle type is respectively as follows:

wherein, the effective output electric quantity C of single equipment day need to combine the daily running style of the charging characteristic of motorcycle type self and circuit to carry out the integrated analysis:

C＝P*K*D/60；

p: the rated output power of a single set of charging equipment is in unit (kilowatt), all vehicle types adopt high-power quick charging equipment, and the rated power of the single set of charging equipment is 360 kW;

k: the receiving coefficient of charging of the vehicle type, the receiving coefficient K of charging per minute of each vehicle type is:

vehicle model	K(6)	K(10)	K(18)
				Charge reception coefficient K	0.6	0.7	0.8

D: the effective charging time length that the motorcycle type circuit corresponds, unit (hour), bus operation charging time quantum 7: 00-22:00, the peak time of the trunk line and the branch line cannot be charged for 4 h; the bus single charging operation is 15 minutes, factors such as parking, gun insertion and connection are considered, the actual effective charging time of the single operation is 10 minutes, and the daily effective time of the bus is 440-600 minutes, namely:

the number of vehicles served by a single set of charging equipment for the type and the type of the line can be obtained when the type of a certain bus line is a trunk line, the type of the bus is 10 meters, and the vehicle runs for 100 kilometers per day.

According to the following steps: c ═ P ═ K ═ D/60;

the effective daily output electric quantity of a single set of equipment is C (360X 0.7X 440/60) (1848 degrees) aiming at the model of the line vehicle;

according to T ═ C/(H × S);

h takes H (10) as 1 degree/kilometer, S as 100 kilometers; the number of vehicles T1848/(1 × 100) that the single charging device can serve the line is 18.48, that is, the single charging device can serve 18 vehicles in the line.

EXAMPLE III

The third embodiment is further optimized by the second embodiment.

The configuration number of the charging equipment of a single planning charging station is calculated comprehensively according to the number of lines, the types of the lines and the number of vehicles contained in the planning charging station.

The dynamic programming adjustment model is as follows:

as is known, the total number of buses is n, and the total number of routes is m, where m is { route m1, route m2, route m3 … }.

Assuming that y is the required configuration number of charging devices of all planned charging stations of the bus, x is the total number of the planned charging stations, the number of lines served by the charging station a is x (m1 and m2 …), the number of buses contained in m1 is represented by m1n, the number of buses contained in m2 is represented by m2n, the required number of the charging devices of the charging station a is represented by Ay (unit: set), and the method can be obtained according to a service capacity calculation model:

Ay＝m1n/Tm1+m2n/Tm2+…；

the service range of a certain charging station A contains 2 bus lines, the number of vehicles on the line 1 is 37, the line type is a trunk line, the vehicle type is 10 meters, and the vehicles run for 100 kilometers per day; the number of vehicles on the route 2 is 45, the route type is a fast route, the vehicle type is 6.8 meters, and the vehicle runs 80 kilometers per day.

According to Ay-m 1n/Tm1+ m2n/Tm2, one can obtain:

tm1 ═ P × K (10) × D (1)/(H (10) × S60 ═ 360 × 0.7 × 440/(1 × 100 × 60) ═ 18.5 stations;

tm12 (P × K (6.8) × D (2)/(H (6.8) × S60) ═ 360 × 0.6 × 600/(0.6 × 80 × 60)45 stations;

therefore, the required configuration number Ay of the charging equipment at the charging station a is 37/18.5+47/45 is 3.

Since the number of charging equipment configurations for the planned charging site is influenced by factors such as a site, a road, city power, city management, and the like, the actual number of charging equipment configurations for charging site a is represented by SAy, and the maximum actual number of charging equipment configurations for charging site a is represented by SAymax.

xy represents the equipment demand number of a certain station, Sxy represents the actual equipment configuration number of the certain station, and x and y realize dynamic matching and control the number of x and y.

Let charging site a service line m be { m1, m3, m100}, charging site B service line m be { m1, m10, m99}, charging site C service line m be { m10, m20}, and charging site D service line m be { m99, m180}, where m1 is chargeable between a and B, which may be referred to as a and B association m1, and similarly B and C associate m10, and B and D associate m 99. Aiming at a line with m2 charging stations, in an initial state, the required equipment number my of the line m needs to be equally divided into 2 charging stations, and Amy represents the required equipment number of the m line of the charging station A.

As shown in fig. 2, the whole dynamic programming adjustment model logic is as follows:

initial n is 0;

if SAymax < Ay, since the m1 vehicle can be charged in both points a and B, to meet the normal charging requirements of m3 and m100, the charging requirement of the m1 vehicle will be gradually and completely adjusted to point B, i.e., point B m1n/2 is gradually increased to point m1n, and By will be dynamically adjusted SBy.

If SBymax > SBy, then a value of SBy was determined.

If SBymax is less than SBy, m1 needs to be transmitted from B to C and D through correlation of m10 or m99, namely, the charging requirement of m10 is completely adjusted to C or the charging requirement of m99 is completely adjusted to C, SCy and SDy change correspondingly, dynamic programming adjustment is carried out according to SCymax and SDymax, and the like, and finally all Symax > Sxy is realized.

The dynamic programming adjustment model is based on the difference between Sxymax and Sxy in the charging station x, adjustment is carried out through the incidence relation between m and the station, the whole network can form various Sxy combinations, and the combination with smaller x is the optimal combination scheme because y is a customization.

An example of a dynamic programming adjustment model is as follows:

according to the existing 7 bus routes, initial planning data can be obtained by combining a planning combination model and a service capacity measuring and calculating model according to information of vehicles, vehicle types, energy consumption and the like of all routes, and the initial planning data is shown in fig. 3.

According to the information, the total demand of the 7 bus routes is 10.85, the vehicle information of any route changes, the corresponding demand number of the bus routes also changes, and the demand of the bus route equipment associated with the bus route also changes.

1021 way distance E district is in 2 kilometers scope, so this line charging demand point merges to E district charging station automatically.

There are 6 planning charging stations in these 7 lines, and there are 2 charging that seek the point in 5 lines, and two charging stations divide the line equipment demand equally.

According to the actual construction conditions of each planned charging station, the maximum equipment configuration number of the charging station can be obtained, and according to the set demand number and the maximum configuration number, the vehicle demand dynamic transfer can be performed on the line which is charged on two sides, and is shown in fig. 4.

According to the result of the dynamic planning adjustment, the actual maximum equipment configuration number in the 6 stations is 16, and the total equipment demand number is 10.85, so that multiple groups of Sxy can be obtained from the 6 stations, and the scheme of the multiple groups of Sxy is shown in fig. 5.

According to the comparison result of multiple groups of Sxy, the smaller the number of x is, the optimal result is, x in the third group is 4, in the actual charging station investment construction, the combination can construct 2 charging stations with less investment, and therefore the result of the dynamic distribution of the Sxy in the third group is the optimal scheme.

Because the bus route has the situations of new line opening, adjustment, change, cancellation and the like, the demand number of the line equipment can be changed continuously, and further the demand change of the charging station is caused, and according to the established equipment number of the charging station, the optimal actual equipment configuration number obtained by combining a dynamic planning model can be obtained to obtain the equipment difference number, which is as follows:

and according to the comparison of the difference number between the optimal actual demand number of the equipment and the constructed reserve number, the next equipment construction demand of each planning charging station can be guided.

The maximum equipment configuration number is equivalent to the construction limit of one charging station, and the actual construction number of the charging equipment does not exceed the limit value. If the required number is found to be smaller than the maximum equipment configuration number and larger than the constructed equipment number after dynamic adjustment, the charging station needs to be expanded and constructed continuously, the space of the existing charging station is preferentially utilized to the maximum extent, and the number of the charging stations is reduced as much as possible, so that the investment cost is reduced, and the utilization rate of the charging stations is improved.

The invention solves the problems of planning and site selection and design scale of the urban electric bus charging station, and establishes a set of planning and design model method for the urban fast-charging bus charging station according to the information of bus route position, number of vehicles, shift-sending running time and the like and by combining the charging characteristics of the buses, so as to guide where the urban fast-charging bus charging station is established and how many large-scale charging stations are established.

The invention can realize full automation of planning, full association of lines and full dynamic of design, automatically match in space and time, and provide feasibility analysis support of maximum service benefit efficiency and minimum investment cost for the charging station in planning, designing, constructing and managing stages.

The invention is also suitable for planning and designing operation vehicle charging stations (networks) such as renting, network reservation, logistics, urban sanitation and the like.

The above-described embodiments are intended to be illustrative, not limiting, of the invention, and therefore, variations of the example values or substitutions of equivalent elements are intended to be within the scope of the invention.

From the above detailed description, it will be apparent to those skilled in the art that the foregoing objects and advantages of the invention are achieved and are in accordance with the provisions of the patent statutes.

While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention. The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, it should be noted that any modifications, equivalents and improvements made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims

1. An intelligent planning and design method for charging infrastructure is characterized by comprising the following steps:

2. The charging infrastructure intelligent planning and design method of claim 1, wherein the step S2 comprises:

3. The charging infrastructure intelligent planning and design method of claim 2, wherein the step S2 further comprises:

4. The charging infrastructure intelligent planning and design method of claim 3, wherein the step S2 further comprises:

5. The charging infrastructure intelligent planning and design method of claim 4, wherein the step S2 further comprises:

6. The charging infrastructure intelligent planning and design method of claim 5, wherein the step S2 further comprises:

7. The intelligent planning and design method for charging infrastructure of claim 1, wherein in step S3, the planning and merging model comprises:

8. The intelligent planning and design method for charging infrastructure of claim 7, wherein in step S3, the planning and merging model further comprises:

if S (m1, m2) ≦ 2aKM, X1 ═ m1X, m1y ≦ m2X, m2 y.

9. The intelligent planning and design method for charging infrastructure of claim 8, wherein in step S3, the planning and merging model further comprises:

10. The intelligent planning and design method for charging infrastructure of claim 9, wherein in step S3, the planning and merging model further comprises: