CN113610276A - Urban electric vehicle charging infrastructure planning method and system - Google Patents
Urban electric vehicle charging infrastructure planning method and system Download PDFInfo
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Abstract
The invention relates to a method and a system for planning urban electric automobile charging infrastructure, which comprises the following steps: calculating the number of electric vehicle public charging stations; constructing electric vehicle public charging station distribution points based on the number of the electric vehicle public charging stations, wherein the electric vehicle public charging station distribution points enable the service range of the electric vehicle public charging stations to cover the city construction area; measuring and calculating the quantity of electric vehicles in the service range of the electric vehicle charging station; and calculating the arrangement quantity of the charging piles of each electric vehicle charging station based on the quantity of the electric vehicles in the service range of the electric vehicle charging stations. The method can provide important basis for scientific and reasonable city-level electric vehicle charging infrastructure planning, and makes up for the lack of consideration on feasibility of service range and construction land in city-level charging station site selection planning.
Description
Technical Field
The invention relates to the technical field of electric automobile charging, in particular to a method and a system for planning urban electric automobile charging infrastructure.
Background
The electric vehicle charging station is an important basic support system for energy supply of the electric vehicle, and is also an important link in the commercialization and industrialization processes of the electric vehicle, and along with the large-scale construction of charging facilities, the scientific and reasonable configuration of the charging facilities of the electric vehicle obviously becomes one of the problems which are urgently needed to be solved at present.
At present, a great deal of research is done on the planning of electric vehicle charging facilities at home and abroad. For example, according to the dynamic distribution rule of the charging demand of the user, relevant index factors of the power distribution network influencing the charging load of the electric automobile are determined, and an addressing model maximizing benefits of investors and the user is built. And simulating the charging load curves of the electric vehicles under different types of charging modes by using a Monte Carlo method, wherein the number of the charging stations is calculated according to the demand of the user on the electric vehicles every day. Or setting the minimum torsion loss as the filling age as a target function through electric vehicle operation data acquired by the vehicle-pile integrated platform, and establishing a charging station location and volume model. Or analyzing the influence of the electric energy quality of the power distribution network accessed by the charging station, the load balance of the power grid and the economical efficiency of the operation indexes, and summarizing the requirements and the targets for carrying out site selection on the charging station under the urban traffic network and the highway traffic network. Or, based on the existing road information of the city, determining the service range of the charging station through the cruising ability and the charging convenience coefficient of the charging vehicle, and finally solving the optimal distribution and capacity of each station by adopting a two-step search algorithm in combination with the predicted number of the vehicles in the planning year. Or, mainly considering several factors influencing the site selection, providing site selection conditions and constant volume conditions of the charging station, performing site selection through an entropy weight fuzzy method, and then accurately calculating the position of the charging station through a genetic algorithm. Or analyzing two different scenes, namely a holiday scene and a working day scene, to obtain the driving characteristics of the user, and providing a traffic satisfaction model to plan the charging station according to the queuing tolerance of the user, the power grid flow and other factors.
In view of the above analysis, it can be seen that for regional charging station planning, research is currently conducted on the consideration that the site selection of the charging stations lacks the rationality of construction land, and the checking of the service range of the electric vehicle charging stations is omitted for the determination of the number of electric vehicle charging stations based on the demand of the charging amount of the electric vehicle.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the technical defects that the site selection of the charging stations lacks the consideration of the rationality of construction land, the quantity of the electric vehicle charging stations is determined based on the requirement of the charging quantity of the electric vehicle, and the checking of the service range of the electric vehicle charging stations is omitted in the prior art.
In order to solve the technical problem, the invention provides a method for planning urban electric vehicle charging infrastructure, which comprises the following steps:
calculating the number of electric vehicle public charging stations;
constructing electric vehicle public charging station distribution points based on the number of the electric vehicle public charging stations, wherein the electric vehicle public charging station distribution points enable the service range of the electric vehicle public charging stations to cover the city construction area;
measuring and calculating the quantity of electric vehicles in the service range of the electric vehicle charging station;
and calculating the arrangement quantity of the charging piles of each electric vehicle charging station based on the quantity of the electric vehicles in the service range of the electric vehicle charging stations.
Preferably, the calculating the number of electric vehicle public charging stations comprises:
and comparing and analyzing the number M of the electric automobile public charging stations according to a charging service radius method, a charging station pile ratio method and a charging demand method.
Preferably, the comparing and analyzing of the number M of the electric vehicle public charging stations according to a charging service radius method, a charging station pile ratio method and a charging demand method specifically includes:
calculating the number M of public charging stations according to a charging service radius methodr，
Wherein S is the public charging station serving the urban area, S0Serving a range for a single charging station;
calculating the number M of public charging stations according to a charging station vehicle-to-pile ratio methodc，
Wherein Q is the number of urban electric vehicles;
calculating the number M of public charging stations according to a charging demand methodd，
Wherein W isDaily charging capacity of urban electric vehicles; w0The daily average charging capacity of a single charging station is charged;
the number M of the public charging stations is obtained through calculation,
preferably, the service range of the single charging station is 2.54km2-7.06km2.。
Preferably, the constructing of the electric vehicle public charging station distribution points based on the number of the electric vehicle public charging stations enables the service range of the electric vehicle public charging station to cover the city construction area, and specifically includes:
the number M of public charging stations satisfies:
wherein r isiIs the service radius of the ith charging station, and S is the urban area served by the public charging station.
Preferably, riThe value range of (A) is 0.9km-1.5 km.
Preferably, the measuring and calculating the number of electric vehicles in the service range of the electric vehicle charging station specifically includes:
measuring and calculating the quantity of the electric vehicles in the service range of the electric vehicle charging station according to the permeability level of the electric vehicles and the quantity of the vehicles in the service range,
Ni,c＝εNi，
wherein N isi,cThe number of electric vehicles served for the ith charging station; epsilon is the electric vehicle permeability; n is a radical ofiThe number of cars in the area.
Preferably, the calculating the arrangement number of the charging piles of each electric vehicle charging station based on the number of the electric vehicles in the service range of the electric vehicle charging stations comprises:
based on the number of the electric automobiles served by the charging station, considering that the shortest charging queuing time of electric automobile users and the smallest investment cost of the charging station are taken as optimization targets, and establishing an electric automobile charging station charging pile number optimization model by taking power grid capacity constraint and user queuing time tolerance as constraint conditions;
wherein, the optimization target of the electric automobile charging station charging pile quantity optimization model is as follows:
constraint conditions of the electric vehicle charging station charging pile quantity optimization model are as follows: n is a radical ofi,zPz≤Pi,g；
Ti,w≤tmax；
Wherein N isi,zThe number of charging piles in the ith charging station; cZThe comprehensive cost of a single charging pile includes the cost of electromechanics, civil engineering and the like; t isi,wAverage queuing time for users in the ith charging station; pzCharging capacity for a charging pile; pi,gMaximum limit capacity for the power grid at the ith charging station; t is tmaxThe maximum queuing time tolerance time of the user is obtained; a and b are the minimum pile ratio and the maximum pile ratio, respectively.
Preferably, the average queuing time T of users in the ith charging stationi,wRelated to the number of the charging piles in the charging station, the calculation formula is as follows:
wherein li,qThe average queuing time of the users of the electric vehicle in the ith charging process; lambda [ alpha ]iThe number of electric vehicles arriving in the ith charging station in unit time is; rhoiThe charging pile utilization rate of the electric automobile for the ith charging station is obtained; p0,iProbability that 0 th electric vehicle can receive charging service for the ith charging station; mu.siAnd (4) the average charging time of the electric vehicle in the ith charging station.
The invention discloses a city-level electric automobile charging infrastructure planning system, which comprises:
the public charging station number calculating module is used for calculating the number of the electric automobile public charging stations;
the public charging station distribution point module is used for constructing electric vehicle public charging station distribution points based on the number of electric vehicle public charging stations, and the electric vehicle public charging station distribution points enable the service range of the electric vehicle public charging stations to cover an urban construction area;
the electric vehicle quantity calculating module is used for measuring and calculating the quantity of electric vehicles in the service range of the electric vehicle charging station;
the charging pile arrangement module calculates the charging pile arrangement quantity of each electric vehicle charging station based on the quantity of electric vehicles in the service range of the electric vehicle charging stations.
Compared with the prior art, the technical scheme of the invention has the following advantages:
the method can provide important basis for the planning of the urban electric vehicle charging infrastructure scientifically and reasonably, makes up for the lack of consideration of feasibility of the urban charging station site selection planning on the service range and the construction land, and plans the electric vehicle charging infrastructure scientifically and reasonably.
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FIG. 1 is a flow chart of a method for planning a municipal electric vehicle charging infrastructure in accordance with the present invention;
fig. 2 is a logic diagram of city electric vehicle charging infrastructure planning.
Detailed Description
The present invention is further described below in conjunction with the following figures and specific examples so that those skilled in the art may better understand the present invention and practice it, but the examples are not intended to limit the present invention.
Referring to fig. 1-2, the invention discloses a method for planning an urban electric vehicle charging infrastructure, comprising the following steps:
step one, calculating the number of electric vehicle public charging stations: comparing and analyzing the number M of the electric automobile public charging stations according to a charging service radius method, a charging station pile ratio method and a charging demand method, and specifically comprising the following steps:
the method comprises the following steps of comparing and analyzing the number M of the electric automobile public charging stations according to a charging service radius method, a charging station pile ratio method and a charging demand method, and specifically comprises the following steps:
charging service radius method: referring to the design specification requirement of the refueling and gas filling station and the service radius requirement of each province and city electric vehicle charging station, the primarily adopted charging service radius is 0.9km-1.5km, and the service range of the charging station is 2.54km2-7.06km2. The areas of water areas, mountain forests and basic farmlands are deducted, and areas such as development boundaries and ecological protection lines are superposed to obtain the service area of the charging station. Thus, the number of charging stations is calculated as:
here, MrNumber of public charging stations; s is the public charging station serving the urban area, S0Serving a range for a single charging station.
A charging station pile comparison method: at least 1 charging station is configured for every 2000 electric vehicles to calculate the number of public charging stations according to implementation comments (survey comments) about further improving the service guarantee capability of the charging and conversion infrastructure by the State transformation agency, and the minimum number of the charging stations of the calculation result is checked.
Here, McNumber of public charging stations; q is the number of urban electric vehicles.
The method of the charging demand: the urban public charging station is mainly a small-sized charging station and is assisted by a large-sized and medium-sized charging station. And counting the daily average charging electric quantity of each station of the urban public charging station, and analyzing the daily average charging quantity of the urban electric vehicles by combining the daily average driving mileage and the power consumption to further obtain the number of the charging stations.
Here, MdNumber of public charging stations; w is daily average charging capacity of the urban electric automobiles; w0The daily average charging capacity of a single charging station is charged.
The number M of public charging stations is calculated. The number of urban public charging stations can be MrAnd MdAnd ensuring that M is greater than Mc。
Step two, establish electric automobile public charging station distribution point based on electric automobile public charging station quantity, electric automobile public charging station distribution point makes electric automobile public charging station service range cover city construction district, specifically includes:
the number M of public charging stations satisfies:
wherein r isiIs the service radius of the ith charging station, and S is the urban area served by the public charging station. r isiThe value range of (A) is 0.9km-1.5 km.
Step three, measuring and calculating the quantity of the electric automobiles in the service range of the electric automobile charging station, and specifically comprising the following steps:
measuring and calculating the quantity of the electric vehicles in the service range of the electric vehicle charging station according to the permeability level of the electric vehicles and the quantity of the vehicles in the service range,
Ni,c＝εNi，
wherein N isi,cThe number of electric vehicles served for the ith charging station; epsilon is the electric vehicle permeability; n is a radical ofiThe number of cars in the area.
Step four, based on electric automobile quantity in the electric automobile charging station service range, calculate every electric automobile charging station and fill electric pile and arrange quantity, include:
based on the number of the electric automobiles served by the charging stations, considering that the shortest charging queuing time of electric automobile users and the smallest investment cost of the charging stations are taken as optimization targets, and taking power grid capacity constraint and user queuing time tolerance as constraint conditions, establishing an electric automobile charging station charging pile number optimization model to calculate the arrangement number of each charging station charging pile;
wherein, the optimization target of the electric automobile charging station charging pile quantity optimization model is as follows:
Constraint conditions of the electric vehicle charging station charging pile quantity optimization model are as follows: n is a radical ofi,zPz≤Pi,g；
Ti,w≤tmax；
Wherein N isi,zThe number of charging piles in the ith charging station; cZThe comprehensive cost of a single charging pile includes the cost of electromechanics, civil engineering and the like; t isi,wAverage queuing time for users in the ith charging station; pzCharging capacity for a charging pile; pi,gFor the power grid in the ith charging stationA large limiting capacity; t is tmaxThe maximum queuing time tolerance time of the user is obtained; a and b are the minimum pile ratio and the maximum pile ratio, respectively.
Average queuing time T of users in ith charging stationi,wRelated to the number of the charging piles in the charging station, the calculation formula is as follows:
wherein li,qThe average queuing time of the users of the electric vehicle in the ith charging process; lambda [ alpha ]iThe number of electric vehicles arriving in the ith charging station in unit time is; rhoiThe charging pile utilization rate of the electric automobile for the ith charging station is obtained; p0,iProbability that 0 th electric vehicle can receive charging service for the ith charging station; mu.siAnd (4) the average charging time of the electric vehicle in the ith charging station.
The invention discloses a city-level electric vehicle charging infrastructure planning system which comprises a public charging station quantity calculation module, a public charging station distribution point module, an electric vehicle quantity calculation module and a charging pile arrangement module.
The public charging station number calculating module is used for calculating the number of the electric automobile public charging stations.
The public charging station distribution point module is used for constructing electric automobile public charging station distribution points based on the number of electric automobile public charging stations, and the electric automobile public charging station distribution points enable the service range of the electric automobile public charging stations to cover the city construction area.
The electric vehicle quantity calculation module is used for measuring and calculating the quantity of electric vehicles in the service range of the electric vehicle charging station.
The charging pile arrangement module calculates the arrangement quantity of the charging piles of each electric vehicle charging station based on the quantity of electric vehicles in the service range of the electric vehicle charging stations.
For public charging stations, the public charging station planning scheme is formed mainly by a two-step method of determining the number and distribution of the charging stations and determining the configuration capacity of the charging stations. In the aspect of analyzing the number and the distribution of the charging stations, the number of the electric vehicle public charging stations is compared and analyzed through a service radius method, a vehicle pile ratio method and a charging demand method, and the space distribution of the charging station sites is planned and analyzed according to the charging service radius, the charging hot spot analysis and the land space. In the aspect of the configuration capacity of the charging station, based on the spatial distribution of the charging station sites, the service range of the electric vehicle charging station is analyzed according to the urban space plan, the number of the electric vehicle charging services is calculated, and then a charging station capacity optimal configuration model is established by considering the power grid capacity, the charging station income and the user queuing time, so that the optimal configuration capacity of the charging station is obtained. And finally, adding the number of the charging piles of each charging station and comparing the added number with the existing typical charging pile ratio method to obtain the actual configuration capacity of the charging station.
The method can provide important basis for scientific and reasonable urban electric vehicle charging infrastructure planning, and makes up for the lack of consideration on feasibility of service range and construction land in urban charging station site selection planning.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (10)
1. A city-level electric automobile charging infrastructure planning method is characterized by comprising the following steps:
calculating the number of electric vehicle public charging stations;
constructing electric vehicle public charging station distribution points based on the number of the electric vehicle public charging stations, wherein the electric vehicle public charging station distribution points enable the service range of the electric vehicle public charging stations to cover the city construction area;
measuring and calculating the quantity of electric vehicles in the service range of the electric vehicle charging station;
and calculating the arrangement quantity of the charging piles of each electric vehicle charging station based on the quantity of the electric vehicles in the service range of the electric vehicle charging stations.
2. The city-level electric vehicle charging infrastructure planning method of claim 1, wherein the calculating the number of electric vehicle public charging stations comprises:
and comparing and analyzing the number M of the electric automobile public charging stations according to a charging service radius method, a charging station pile ratio method and a charging demand method.
3. The city-level electric vehicle charging infrastructure planning method according to claim 2, wherein comparing and analyzing the number M of electric vehicle public charging stations according to a charging service radius method, a charging station pile ratio method and a charging demand method specifically comprises:
calculating the number M of public charging stations according to a charging service radius methodr，
Wherein S is the public charging station serving the urban area, S0Serving a range for a single charging station;
calculating the number M of public charging stations according to a charging station vehicle-to-pile ratio methodc，
Wherein Q is the number of urban electric vehicles;
calculating the number M of public charging stations according to a charging demand methodd，
Wherein W is daily average charging capacity of the urban electric automobile; w0The daily average charging capacity of a single charging station is charged;
the number M of the public charging stations is obtained through calculation,
4. the city-level electric vehicle charging infrastructure planning method of claim 3, wherein the single charging station service range is 2.54km2-7.06km2.。
5. The city-level electric vehicle charging infrastructure planning method according to claim 1, wherein the electric vehicle public charging station distribution points are constructed based on the number of electric vehicle public charging stations, and the electric vehicle public charging station distribution points enable an electric vehicle public charging station service range to cover a city construction area, and specifically comprise:
the number M of public charging stations satisfies:
wherein r isiIs the service radius of the ith charging station, and S is the urban area served by the public charging station.
6. The city-level electric vehicle charging infrastructure planning method of claim 5, wherein r isiThe value range of (A) is 0.9km-1.5 km.
7. The city-level electric vehicle charging infrastructure planning method according to claim 1, wherein the measuring and calculating the number of electric vehicles within the service range of the electric vehicle charging station specifically comprises:
measuring and calculating the quantity of the electric vehicles in the service range of the electric vehicle charging station according to the permeability level of the electric vehicles and the quantity of the vehicles in the service range,
Ni,c＝εNi，
wherein N isi,cThe number of electric vehicles served for the ith charging station; epsilon is the electric vehicle permeability; n is a radical ofiThe number of cars in the area.
8. The city-level electric vehicle charging infrastructure planning method of claim 1, wherein calculating the number of arranged charging piles for each electric vehicle charging station based on the number of electric vehicles within the service range of the electric vehicle charging station comprises:
based on the number of the electric automobiles served by the charging station, considering that the shortest charging queuing time of electric automobile users and the smallest investment cost of the charging station are taken as optimization targets, and establishing an electric automobile charging station charging pile number optimization model by taking power grid capacity constraint and user queuing time tolerance as constraint conditions;
wherein, the optimization target of the electric automobile charging station charging pile quantity optimization model is as follows:
constraint conditions of the electric vehicle charging station charging pile quantity optimization model are as follows: n is a radical ofi,zPz≤Pi,g；
Ti,w≤tmax；
Wherein N isi,zThe number of charging piles in the ith charging station; cZThe comprehensive cost of a single charging pile includes the cost of electromechanics, civil engineering and the like; t isi,wAverage queuing time for users in the ith charging station; pzCharging capacity for a charging pile; pi,gMaximum limit capacity for the power grid at the ith charging station; t is tmaxThe maximum queuing time tolerance time of the user is obtained; a and b are each the mostA stub ratio of small and a stub ratio of maximum.
9. The city-level electric vehicle charging infrastructure planning method of claim 8, wherein the average queuing time T of users in the ith charging stationi,wRelated to the number of the charging piles in the charging station, the calculation formula is as follows:
wherein li,qThe average queuing time of the users of the electric vehicle in the ith charging process; lambda [ alpha ]iThe number of electric vehicles arriving in the ith charging station in unit time is; rhoiThe charging pile utilization rate of the electric automobile for the ith charging station is obtained; p0,iProbability that 0 th electric vehicle can receive charging service for the ith charging station; mu.siAnd (4) the average charging time of the electric vehicle in the ith charging station.
10. An urban electric vehicle charging infrastructure planning system, comprising:
the public charging station number calculating module is used for calculating the number of the electric automobile public charging stations;
the public charging station distribution point module is used for constructing electric vehicle public charging station distribution points based on the number of electric vehicle public charging stations, and the electric vehicle public charging station distribution points enable the service range of the electric vehicle public charging stations to cover an urban construction area;
the electric vehicle quantity calculating module is used for measuring and calculating the quantity of electric vehicles in the service range of the electric vehicle charging station;
the charging pile arrangement module calculates the charging pile arrangement quantity of each electric vehicle charging station based on the quantity of electric vehicles in the service range of the electric vehicle charging stations.
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