Planning method and device of electric vehicle charging facility, medium and electronic equipment

Abstract

The invention discloses an electric vehicle charging facility planning method and device, a medium and electronic equipment. Relates to the power technology field. The method comprises the steps that the number of charging facilities of each service area in a to-be-planned area is initialized, initial charging facility data are obtained, and the types of the charging facilities comprise fixed charging facilities and mobile charging facilities; based on the historical traffic flow data, determining a charging prediction value of each electric vehicle in the to-be-planned area; and determining a target planning result based on the charging predicted value of each electric vehicle and the initial charging facility data. According to the invention, the technical problem of poor deployment effect of the charging facility of the electric vehicle deployed in the highway network in the related technology is solved.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a planning method, device, medium and electronic equipment for electric vehicle charging facilities. Background Art

[0002] With the rapid development of the electric vehicle industry and the supporting energy replenishment facilities industry, the charging demand in the highway network has increased sharply. In the related technology, fixed charging piles are deployed in each service area of ​​the highway network to charge electric vehicles. However, the fixed charging piles are difficult to move after deployment, and the charging demand of different service areas is constantly changing, resulting in the deployment of charging facilities in the service areas being difficult to meet the charging needs of electric vehicles, and the cost of deploying fixed charging piles is high. Therefore, the charging facilities for electric vehicles deployed in the highway network in the related technology have poor deployment effects.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present invention provide a method, device, medium and electronic device for planning electric vehicle charging facilities, so as to at least solve the technical problem of poor deployment effect of electric vehicle charging facilities deployed in highway networks in related technologies.

[0005] According to one aspect of an embodiment of the present invention, a planning method for electric vehicle charging facilities is provided, comprising: initializing the number of charging facilities in each service area in a planned area to obtain initial charging facility data, wherein the types of charging facilities include: fixed charging facilities and mobile charging facilities; determining a charging prediction value for each electric vehicle in the planned area based on historical traffic flow data, wherein the historical traffic flow data at least includes: the battery capacity, remaining range and unit power consumption of each electric vehicle in the planned area within a historical time period, and the charging prediction value of each electric vehicle is used to represent the probability of charging the electric vehicle; determining a target planning result based on the charging prediction value of each electric vehicle and the initial charging facility data, wherein the target planning result includes: the planning result of the mobile charging facilities in the planned area.

[0006] Furthermore, based on the charging prediction value of each electric vehicle and the initial charging facility data, a target planning result is determined, including: based on the charging prediction value of each electric vehicle, an average queuing time of electric vehicles in each service area is determined; based on the average queuing time of electric vehicles in each service area and the initial charging facility data, the target planning result is determined.

[0007] Furthermore, the area to be planned includes: an area in the expressway network where mobile charging facilities are to be planned, the area to be planned includes: M service areas, the service areas are used to provide charging services for electric vehicles, M is a positive integer, and the target planning result is determined based on the average queuing time of electric vehicles in each of the service areas and the initial charging facility data, including: when there is a target service area among the M service areas, based on the remaining power supply capacity of the target service area, updating the initial charging facility data to obtain the target planning result, wherein the target service area includes: a service area where the average queuing time of the electric vehicle does not meet a preset condition, the preset condition includes: the average queuing time of the electric vehicle is less than a preset time, and the remaining power supply capacity is used to indicate the number of charging facilities that can be added to the service area; when there is no target service area among the M service areas, the target planning result is determined based on the initial charging facility data.

[0008] Furthermore, in the case where there is a target service area among the M service areas, the initial charging facility data is updated based on the remaining power supply capacity of the target service area to obtain the target planning result, including: in the case where there is the remaining power supply capacity in the target service area, based on the target service area with the remaining power supply capacity, the initial charging facility data is updated to obtain first charging facility data, and the target planning result is determined based on the first charging facility data, wherein the number of mobile charging facilities in the first charging facility data is greater than the number of mobile charging facilities in the initial charging facility data; in the case where there is no remaining power supply capacity in the target service area, the target planning result is determined based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in N designated service areas, wherein the N designated service areas include: the service areas in the area to be planned except the target service area, and N is a positive integer less than M.

[0009] Furthermore, in the case that the remaining power supply capacity does not exist in the target service area, the target planning result is determined based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in N designated service areas, including: judging whether the mobile charging facilities can be added to each of the designated service areas based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in the N designated service areas, and obtaining a judgment result; and in the case that the judgment result indicates that the mobile charging facilities can be added to any of the designated service areas, updating the number of the mobile charging facilities in the designated service area in the initial charging facility data, and obtaining the target planning result.

[0010] Furthermore, the mobile charging facility comprises: a socket assembly of a component-type mobile charging facility, wherein the component-type mobile charging facility is used to charge the electric vehicle, and the component-type mobile charging facility comprises: a socket assembly and a charger assembly, the socket assembly is fixed in the service area, and the charger assembly is movable.

[0011] Furthermore, in the case where the remaining power supply capacity exists in the target service area, based on the target service area with the remaining power supply capacity, the initial charging facility data is updated to obtain first charging facility data, and based on the first charging facility data, the target planning result is determined, including: in the case where the remaining power supply capacity exists in the target service area, based on the average queuing time of the electric vehicles, the target service areas with the remaining power supply capacity are sorted to obtain a sorting result; based on the sorting result, the number of mobile charging facilities in the target service area with the remaining power supply capacity in the initial charging facility data is updated to obtain the target planning result.

[0012] According to another aspect of an embodiment of the present invention, a planning device for charging facilities is also provided, comprising: an initialization unit, used to initialize the number of charging facilities in each service area in the planning area to obtain initial charging facility data, wherein the types of charging facilities include: fixed charging facilities and mobile charging facilities; a first determination unit, used to determine the charging prediction value of each electric vehicle in the planning area based on historical traffic flow data, wherein the historical traffic flow data at least includes: the battery capacity, remaining cruising range and unit power consumption of each electric vehicle in the planning area within a historical time period, and the charging prediction value of each electric vehicle is used to represent the probability of charging the electric vehicle; a second determination unit, used to determine the target planning result based on the charging prediction value of each electric vehicle and the initial charging facility data, wherein the target planning result includes: the planning result of the mobile charging facilities in the planning area.

[0013] Furthermore, the second determination unit includes: a first determination subunit, used to determine the average queuing time of electric vehicles in each of the service areas based on the charging prediction value of each of the electric vehicles; and a second determination subunit, used to determine the target planning result based on the average queuing time of electric vehicles in each of the service areas and the initial charging facility data.

[0014] Furthermore, the area to be planned includes: an area in the expressway network where mobile charging facilities are to be planned, the area to be planned includes: M service areas, the service areas are used to provide charging services for electric vehicles, M is a positive integer, and the second determination subunit includes: an update module, which is used to update the initial charging facility data based on the remaining power supply capacity of the target service area when there is a target service area among the M service areas, so as to obtain the target planning result, wherein the target service area includes: a service area where the average queuing time of the electric vehicle does not meet the preset conditions, and the preset conditions include: the average queuing time of the electric vehicle is less than the preset time, and the remaining power supply capacity is used to indicate the number of charging facilities that can be added to the service area; a determination module, which is used to determine the target planning result based on the initial charging facility data when there is no target service area among the M service areas.

[0015] Furthermore, the update module includes: a processing submodule, which is used to update the initial charging facility data based on the target service area where the remaining power supply capacity exists, obtain first charging facility data, and determine the target planning result based on the first charging facility data, wherein the number of mobile charging facilities in the first charging facility data is greater than the number of mobile charging facilities in the initial charging facility data; a determination submodule, which is used to determine the target planning result based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in N designated service areas, when the remaining power supply capacity does not exist in the target service area, wherein the N designated service areas include: service areas in the area to be planned except the target service area, and N is a positive integer less than M.

[0016] Furthermore, the determination submodule includes: a judgment submodule one, which is used to judge whether the mobile charging facilities can be added to each of the designated service areas based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in the N designated service areas, and obtain a judgment result; a determination submodule one, which is used to update the number of the mobile charging facilities in the designated service area in the initial charging facility data when the judgment result indicates that the mobile charging facilities can be added to any of the designated service areas, and obtain the target planning result.

[0017] Furthermore, the mobile charging facility comprises: a socket assembly of a component-type mobile charging facility, wherein the component-type mobile charging facility is used to charge the electric vehicle, and the component-type mobile charging facility comprises: a socket assembly and a charger assembly, the socket assembly is fixed in the service area, and the charger assembly is movable.

[0018] Furthermore, the processing submodule includes: a sorting submodule one, which is used to sort the target service areas with the remaining power supply capacity based on the average queuing time of the electric vehicles when the remaining power supply capacity exists in the target service area, and obtain a sorting result; a determination submodule two, which is used to update the number of mobile charging facilities in the target service area with the remaining power supply capacity in the initial charging facility data based on the sorting result, and obtain the target planning result.

[0019] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute any one of the above-mentioned methods for planning electric vehicle charging facilities by executing the executable instructions.

[0020] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, which stores a computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned methods for planning electric vehicle charging facilities.

[0021] In the present invention, the number of charging facilities in each service area in the planning area is initialized to obtain initial charging facility data, wherein the types of charging facilities include: fixed charging facilities and mobile charging facilities; based on historical traffic flow data, the charging prediction value of each electric vehicle in the planning area is determined, wherein the historical traffic flow data at least includes: the battery capacity, remaining cruising range and unit power consumption of each electric vehicle in the planning area during the historical time period, and the charging prediction value of each electric vehicle is used to indicate the probability of charging of the electric vehicle; based on the charging prediction value of each electric vehicle and the initial charging facility data, the target planning result is determined, wherein the target planning result includes: the planning result of the mobile charging facility in the planning area. Thus, the technical problem of poor deployment effect of charging facilities for electric vehicles deployed in the highway network in the related technology is solved. In the present invention, based on the historical traffic flow characteristics, the mobile charging facilities in each service area in the planning area are planned, which avoids the situation in the related technology that only fixed charging facilities are deployed in the service area and mobile charging facilities cannot be planned, so as to achieve the purpose of making the planning results of the charging facilities of electric vehicles meet the charging needs of electric vehicles, and achieve the technical effect of improving the accuracy of the deployment of charging facilities for electric vehicles in the highway network. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0023] Figure 1 is a flow chart of an optional method for planning electric vehicle charging facilities according to an embodiment of the present invention;

[0024] Figure 2 is a flowchart of another optional method for planning electric vehicle charging facilities according to an embodiment of the present invention;

[0025] Figure 3 is a flowchart of solving a socket layout planning for an optional scenario of increased charging demand on a high-speed road network according to an embodiment of the present invention;

[0026] Figure 4 is a schematic diagram of an optional planning device for electric vehicle charging facilities according to an embodiment of the present invention;

[0027] Figure 5 is a schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] It should be noted that the user information (including but not limited to user device information, user personal information, etc.), collected information and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with the relevant laws, regulations and standards of the relevant regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0031] Embodiment 1

[0032] According to an embodiment of the present invention, a method embodiment of an optional method for planning electric vehicle charging facilities is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0033] Figure 1 is a flow chart of an optional method for planning electric vehicle charging facilities according to an embodiment of the present invention, such as Figure 1 As shown, the method comprises the following steps:

[0034] Step S101, initializing the number of charging facilities in each service area in the planned area to obtain initial charging facility data, wherein the types of charging facilities include: fixed charging facilities and mobile charging facilities.

[0035] The above-mentioned area to be planned may include: an area in the expressway network where mobile charging facilities are to be planned, the area to be planned includes: M service areas, the service areas are used to provide charging services for electric vehicles, the types of charging facilities include: fixed charging facilities, mobile charging facilities, wherein, in the process of initializing the number of charging facilities in each service area, the number of fixed charging facilities in each service area can be initialized to the number of fixed charging facilities that already exist in the service area at the current moment, and the number of mobile charging facilities in each service area can be initialized to 0 to obtain initial charging facility data.

[0036] Step S102, based on the historical traffic flow data, determine the charging prediction value of each electric vehicle in the area to be planned, wherein the historical traffic flow data at least includes: the battery capacity, remaining range and unit power consumption of each electric vehicle in the area to be planned during the historical time period, and the charging prediction value of each electric vehicle is used to represent the probability of charging the electric vehicle.

[0037] The above-mentioned traffic flow data may include the battery capacity of electric vehicles, remaining cruising range, unit power consumption, departure rate distribution and origin and destination cities, etc.

[0038] In an optional example, it can be determined that there are a certain number of fixed charging piles (corresponding to fixed charging facilities) in each service area in the highway network. A pair of service area charging stations on both sides of the road can share the capacity of the distribution transformer, but vehicles can only choose to charge in the service area on the same side. It can be determined that in the highway network, there are a certain number of city nodes and service area nodes. At the city nodes, electric vehicles can choose to charge at the charging station at the exit of the highway section, which serves vehicles coming in both directions.

[0039] Based on the historical statistical data of electric vehicles in the area to be planned, the traffic flow characteristics between cities in the area to be planned are obtained, including the battery capacity of electric vehicles, unit power consumption, departure rate distribution and starting and ending cities, and the above-mentioned historical traffic flow data are obtained.

[0040] In this embodiment, a first indicator (or mileage anxiety indicator) can be calculated based on the charge state of each electric vehicle, the power consumption per unit mileage, the distance to the next service area, and the preset charge state of the electric vehicle. Then, the queuing time of each electric vehicle can be calculated by estimating the queuing rounds. For example, the second indicator (or queuing time indicator) can be calculated based on the current number of electric vehicles in the service area, the current number of mobile charging facilities, the original number of fixed charging facilities, the upper limit threshold of the charge state of electric vehicles in the highway network, etc. Then, the first indicator and the second indicator of each electric vehicle can be weighted and summed according to the preset weights to obtain the charging prediction value of the electric vehicle.

[0041] In an optional example, it is possible to determine whether charging should be performed based on the remaining range, the usage of charging facilities in the current service area, and the distance to the next service area, that is, to determine the charging prediction value of the electric vehicles in the planned area, and quantify the judgment basis into a user charging tendency index, including a user mileage anxiety index and a queue time index. The relevant indicators are calculated according to formulas (1) to (4) to obtain the charging prediction value of each electric vehicle.

[0042]

[0043] In formula (1), represents the range anxiety value of user i (or the i-th electric car), is the current state of charge of the i-th electric vehicle, λ is the power consumption per unit mileage of the electric vehicle, E represents the battery capacity of the electric vehicle, is the distance from the i-th electric vehicle to the next service area, The lower limit of the state of charge of electric vehicles in the highway network, To avoid An illegal situation occurred where the denominator was 0.

[0044]

[0045] In formula (2), is the queuing time of the i-th electric vehicle. The queuing time can be calculated by estimating the queuing rounds. is the floor function, is the current number of electric vehicles in the charging station, The number of additional component mobile charging facilities (i.e. the number of mobile charging facilities) is is the number of existing fixed charging facilities, is the average battery capacity, is the upper limit of the state of charge of electric vehicles in the highway network, η is the charger efficiency in the service area, and p HW Charging power for chargers in service areas.

[0046]

[0047] In formula (3), It represents the queue time index, expressed in the form of negative exponential of queue time.

[0048]

[0049] In formula (4), represents the charging tendency index of user i (or the i-th electric vehicle) (corresponding to the charging prediction value of the electric vehicle), which is the weighted sum of the range anxiety index and the queue time index, where α HW and β HW are the preset parameters.

[0050] For an electric car, its departure time is known Departure City HW , Destination city HW , and then the mileage of the electric car can be obtained It is also known that the starting state of charge The power consumption per kilometer is λ, the battery capacity is E, and considering the user's anxiety about the remaining power and the power demand when arriving at the destination, the mid-distance charge state threshold needs to be given and destination state of charge threshold The mid-trip state of charge of electric vehicles should not be less than There are n service areas between the departure city and the destination city, namely SE 1 , S.E.2 ,......,SE n , service area i has Charging piles. The distance between service areas i and j is When the departure time is reached, the electric vehicle enters the running state. Each time it enters the service area, it can settle the charging tendency index once. According to the calculation result, it is determined whether to enter the charging / queuing state. For example, if the user's charging tendency index is greater than the preset threshold, it can be determined that the electric vehicle enters the charging / queuing state, marked as 1. If the user's charging tendency index is less than or equal to the preset threshold, the electric vehicle does not need to enter the charging / queuing state, marked as 0. After charging is completed, The vehicle leaves the service area and re-enters the running state until it reaches the destination and resumes the parking state. It should be noted that considering the travel needs of users, a destination charge state threshold is set. To ensure that users still have enough power to support their next activities in the destination city after arriving at the destination, according to general logic, such as formula (5):

[0051]

[0052] On the way from the departure city to the destination city, the electric vehicle can only be recharged in the service area. If the electric vehicle leaves the highway network before reaching the destination city d and enters the intermediate city c, the operation process of the electric vehicle can be set as two independent parts, (departure place, destination) are (o, c) and (c, d) respectively, and have corresponding other parameters. These two parts are regarded as independent trips when solving.

[0053] The prediction of charging demand for expressway networks also requires the collection of information on electric vehicle models, quantities, expressway network structure, user travel starting and ending points, departure time, and charging facilities in service areas. If there is no condition to obtain detailed data, refer to existing statistical data. Then generate a certain number of electric vehicles, set their relevant attributes according to the current data, and simulate the operating status of electric vehicles to obtain the queuing situation and charging demand distribution in each service area.

[0054] Step S103, determining a target planning result based on the charging prediction value of each electric vehicle and the initial charging facility data, wherein the target planning result includes: a planning result of mobile charging facilities in the area to be planned.

[0055] The target planning results include: the planning results of mobile charging facilities in the area to be planned, for example, the number of mobile charging facilities expected to be added in each service area in the area to be planned, and the average queuing time of electric vehicles in each service area based on the charging prediction value of each electric vehicle. The initial charging facility data can then be adjusted according to the average queuing time, for example, the number of mobile charging facilities can be increased to obtain the target planning results. After obtaining the target planning results, mobile charging facilities can also be added to the service areas in the area to be planned according to the target planning results.

[0056] In this embodiment, through the above steps, based on the historical traffic flow characteristics, the mobile charging facilities of each service area in the planning area are planned, avoiding the situation in the related art that only fixed charging facilities are deployed in the service area and the mobile charging facilities cannot be planned, achieving the purpose of making the planning results of the charging facilities for electric vehicles meet the charging needs of electric vehicles, and achieving the technical effect of improving the accuracy of the deployment of charging facilities for electric vehicles in the highway network. In addition, the technical problem of poor deployment effect of charging facilities for electric vehicles deployed in the highway network in the related art is solved.

[0057] Optionally, based on the charging prediction value of each electric vehicle and the initial charging facility data, the target planning result is determined, including: based on the charging prediction value of each electric vehicle, determining the average waiting time of electric vehicles in each service area; based on the average waiting time of electric vehicles in each service area and the initial charging facility data, determining the target planning result.

[0058] For example, the number of electric vehicles in the queue in each period of the historical time period can be determined, and then the average queue time can be calculated as shown in formula (6):

[0059]

[0060] In formula (6), is the average queuing time of electric vehicles in charging station j (or electric vehicles in the service area where charging station j is located) in each time period, Δt is the length of each time period, A binary variable representing the state of an electric vehicle. If electric vehicle m is charging or queuing at charging station i at time i, then is 1, otherwise it is 0. It can be determined by the user's charging tendency index (corresponding to the charging prediction value), that is, if the user's charging tendency index is greater than the preset threshold, it can be determined that the electric vehicle is in the charging queue is 1, otherwise, is 0. T is the total number of time periods, is the number of existing charging facilities (i.e. the number of fixed charging facilities). is the average battery capacity, η is the charger efficiency, P HW Charging power for the charger.

[0061] Optionally, the area to be planned includes: an area in the expressway network where mobile charging facilities are to be planned, the area to be planned includes: M service areas, the service areas are used to provide charging services for electric vehicles, M is a positive integer, and based on the average queuing time of electric vehicles in each service area and the initial charging facility data, the target planning result is determined, including: when there is a target service area among the M service areas, based on the remaining power supply capacity of the target service area, the initial charging facility data is updated to obtain the target planning result, wherein the target service area includes: a service area where the average queuing time of electric vehicles does not meet preset conditions, the preset conditions include: the average queuing time of electric vehicles is less than the preset time, and the remaining power supply capacity is used to indicate the number of charging facilities that can be added to the service area; when there is no target service area among the M service areas, the target planning result is determined based on the initial charging facility data.

[0062] In this embodiment, after obtaining the average charging queue time (corresponding to the average queue time) of each high-speed service area, it can be determined whether to increase charging facilities based on the average charging queue time.

[0063] For example, if the average charging queue time of electric vehicles in a highway service area does not meet the queue time constraint (corresponding to the target condition) and the service area has surplus power supply capacity (i.e., charging facilities can be added), the service area with the longest queue time can be selected to add a preset number (e.g., 1) of mobile charging facilities (e.g., component charging and discharging facility sockets).

[0064] If there is a situation where the average charging queue time of electric vehicles in a highway service area does not meet the queue time constraint and the service area has no remaining power supply capacity, then each service area can be traversed in descending order according to the queue time of each charging service area to determine whether component-type charging and discharging facility sockets can be added to its adjacent nodes until a service area where certain charging facilities can be added is found, wherein the adjacent nodes of each service area can be pre-set service areas, that is, the adjacent nodes of each service area can be pre-set.

[0065] After adding mobile charging facilities, the average charging queue time for electric vehicles in each service area can be recalculated, and then the decision on whether to add charging facilities can be made based on the average charging queue time until the average charging queue time for electric vehicles in the highway service areas meets the queue time constraints, or there is no service area where charging facilities can be added. The final charging facility data is used as the target planning result.

[0066] When there is no target service area among the M service areas, that is, the average queuing time of all electric vehicles in the M service areas meets the preset conditions, it can be said that the current initial charging facilities can meet the charging needs of electric vehicles, and the initial charging facility data can be directly used as the target planning result.

[0067] Based on the historical traffic flow characteristics, the average waiting time for electric vehicles in each service area is calculated. According to the average waiting time and the remaining power supply capacity, the initial charging facility data is adjusted to obtain the target planning results, achieving the technical effect of accurately deploying charging facilities in the service area.

[0068] Optionally, when there is a target service area among the M service areas, the initial charging facility data is updated based on the remaining power supply capacity of the target service area to obtain a target planning result, including: when there is remaining power supply capacity in the target service area, based on the target service area with remaining power supply capacity, the initial charging facility data is updated to obtain first charging facility data, and the target planning result is determined based on the first charging facility data, wherein the number of mobile charging facilities in the first charging facility data is greater than the number of mobile charging facilities in the initial charging facility data; when there is no remaining power supply capacity in the target service area, the target planning result is determined based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in N designated service areas, wherein the N designated service areas include: service areas in the area to be planned except the target service area, and N is a positive integer less than M.

[0069] If there are charging station nodes in the service area that do not meet the queuing time constraint (corresponding to the preset conditions), then the node with the longest average queuing time among the nodes (i.e., service areas) that still have charging facility construction capacity (corresponding to the remaining power supply capacity) can be selected from the service areas (target service areas) that do not meet the charging time constraint, and a preset number (e.g., 1) of mobile charging facilities (e.g., component-type mobile charging facility socket components) can be added. If all service areas that do not meet the queuing time constraint have no remaining capacity, then each node can be traversed in descending order according to the queuing time (i.e., the target service area) to determine whether charging facilities can be added to its adjacent nodes (corresponding to the designated service area) until a service area node where charging facilities can be added is found in the area to be planned.

[0070] For each pair of service areas, the capacity constraint must be satisfied. The capacity constraint is shown in formula (7):

[0071]

[0072] In formula (7), and Respectively represents the number of component mobile charging facilities deployed in a pair of shared capacity service areas on both sides of the road (corresponding to mobile charging facilities), The maximum number of charging piles that can be accommodated in the pair of service areas.

[0073] Optionally, when there is no remaining power supply capacity in the target service area, the target planning result is determined based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in N designated service areas, including: judging whether mobile charging facilities can be added to each designated service area based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in the N designated service areas, and obtaining a judgment result; when the judgment result indicates that mobile charging facilities can be added to any designated service area, updating the number of mobile charging facilities in the designated service area in the initial charging facility data to obtain the target planning result.

[0074] In this embodiment, each node (i.e., each target service area among the M service areas) can be traversed in descending order according to the queuing time (corresponding to the average queuing time) to determine whether the adjacent node (corresponding to the designated service area) can be equipped with additional charging facilities (e.g., mobile charging facilities). If it can be equipped, a preset number (e.g., 1) of mobile charging facilities are added to the adjacent node, i.e., the number of mobile charging facilities in the designated service area in the initial charging facility data is updated. If it cannot be equipped, the adjacent node of the next node (target service area) can be queried in descending order according to the queuing time, until the designated service area in the area to be planned where mobile charging facilities can be installed is found, and the service area node with the largest reduction in the queuing time of its corresponding node is found, and the target planning result is obtained to achieve accurate planning of mobile charging facilities for electric vehicles according to traffic flow characteristics.

[0075] Optionally, the mobile charging facility includes: a socket assembly of a component-type mobile charging facility, wherein the component-type mobile charging facility is used to charge electric vehicles, and the component-type mobile charging facility includes: a socket assembly and a charger assembly, the socket assembly is fixed in the service area, and the charger assembly is movable.

[0076] In this embodiment, the mobile charging facility can be a component-type mobile charging facility, which can be composed of two main parts: a socket component and a charger component. In the planning stage of the mobile charging facility, the socket components can be built in the expressway network service area and the urban area charging station according to the predicted charging demand distribution and the actual construction conditions, and connected to the distribution network. After the construction, the socket components will not be moved. During holidays, due to the substantial increase in user travel, the charging demand in the expressway network has increased sharply. The operator can call the charger components from the surrounding urban areas, put them in the expressway network service area, connect them with the socket components, and form a complete charging facility to provide charging services for electric vehicles, meet the charging needs of electric vehicles, reduce queuing time, and provide travel convenience.

[0077] It should be noted that the component-type mobile charging facility provided in this embodiment has the advantages of low investment cost and flexible deployment. It can be used as a supplement to fixed charging facilities to meet the surging charging demand in the highway network during holidays with a lower investment.

[0078] Optionally, when there is surplus power supply capacity in the target service area, the initial charging facility data is updated based on the target service area with surplus power supply capacity to obtain first charging facility data, and based on the first charging facility data, the target planning result is determined, including: when there is surplus power supply capacity in the target service area, based on the average queuing time of electric vehicles, the target service areas with surplus power supply capacity are sorted to obtain a sorting result; based on the sorting result, the number of mobile charging facilities in the target service area with surplus power supply capacity in the initial charging facility data is updated to obtain a target planning result.

[0079] In the case where there is surplus power supply capacity in the target service area, the target service areas with surplus power supply capacity are sorted in order of the average queuing time of electric vehicles in ascending order or in order of the average queuing time to obtain a sorting result, and then the service area with the longest average queuing time can be selected according to the sorting result, and a preset number of mobile charging facilities (for example, component charging and discharging facility sockets) can be added to update the number of mobile charging facilities in the target service area with surplus power supply capacity in the initial charging facility data to obtain a target planning result.

[0080] In this embodiment, based on the historical traffic flow characteristics, mobile charging facilities are planned for each service area in the planning area, avoiding the situation in the related art that only fixed charging facilities are deployed in the service area and mobile charging facilities cannot be planned, so as to achieve the purpose of making the planning results of the charging facilities for electric vehicles meet the charging needs of electric vehicles. The mobile charging facilities in this embodiment can be socket components in component-type mobile charging facilities, which have the characteristics of low deployment cost, and the charger components in the component-type mobile charging facilities can be moved at any time, which can ensure that the charging facilities in the highway network can be flexibly scheduled according to the charging needs of electric vehicles.

[0081] Embodiment 2

[0082] Embodiment 2 of the present invention provides another optional planning method for electric vehicle charging facilities, which solves the problem that in the related art, only fixed charging facilities are deployed in the service area in the highway network scenario, mobile charging facilities are lacking, and there are no component-type mobile charging and discharging facility sockets (corresponding to the mobile charging facilities in Embodiment 1), resulting in unreasonable location layout and capacity selection of component-type mobile charging and discharging facility sockets during the deployment of mobile charging facilities.

[0083] The electric vehicle charging facility planning method provided in this embodiment is implemented by the following steps:

[0084] Figure 2 is a flow chart of an alternative method for planning electric vehicle charging facilities according to an embodiment of the present invention, such as Figure 2 As shown, including:

[0085] Step A, charging facility distribution initialization, data initialization. In the initial stage of algorithm modeling, the planning object is the highway network service area. It is assumed that the number of component mobile charging facilities in each service area in the planned area is 0 and there is a certain number of fixed charging facilities (corresponding to fixed charging facilities). That is, the number of charging facilities in each service area in the planned area is initialized to obtain the initial charging facility data.

[0086] Step B: Calculate the predicted value of the charging demand of electric vehicles in the area to be planned (including multiple high-speed service areas) during holidays, that is, determine the charging prediction value of each electric vehicle in the area to be planned based on historical traffic flow data.

[0087] Step C: Calculate the average queuing time in the service area, and calculate the average charging queuing time in the high-speed service area (corresponding to the average queuing time in Example 1).

[0088] Step D: Plan the site selection and layout plan for the sockets of the component-type charging and discharging facilities in the area to be planned.

[0089] Step E: determine whether the stop condition is met, repeat steps B to D until the end condition (i.e., the stop condition) is met, obtain the socket component planning results of the high-speed road network component mobile charging facility (corresponding to the target planning results), and output the socket component planning information.

[0090] Step B specifically includes the following steps:

[0091] Step B1: Input and store the data required for calculation (i.e., historical traffic flow data). The required data items include: obtaining traffic flow characteristics between cities in the area to be planned (including multiple highway service areas), including electric vehicle battery capacity, remaining range, unit power consumption, departure rate distribution and starting and ending cities.

[0092] Step B2: Calculate the charging tendency index (corresponding to the charging prediction value in the first embodiment) of the electric vehicle user based on the data item to predict the charging demand.

[0093] Step D specifically includes the following steps:

[0094] Step D1, judging the average charging queue time of each high-speed service area obtained in step C, if there is a high-speed service area where the average charging queue time does not meet the queue time constraint (corresponding to the preset condition in embodiment one), and the service area has surplus power supply capacity (corresponding to the surplus power supply capacity in embodiment one), the service area with the longest queue time is selected to add one component charging and discharging facility socket.

[0095] Step D2: If the average charging queue time of a high-speed service area does not meet the queue time constraint and the service area has no remaining power supply capacity, then traverse each service area in descending order according to the queue time of each charging service area, and determine whether its adjacent nodes (corresponding to the designated service area in Example 1) can be equipped with additional component-type charging and discharging facility sockets until a service area where additional sockets can be installed is found.

[0096] Specifically, step 1: initialization of charging facility distribution: in the initialization stage, it is assumed that each service area has a certain number of fixed charging facilities and the number of component mobile charging facilities is 0.

[0097] Step 2: Forecasting charging demand for highway networks during holidays: In an optional example, it can be confirmed that there are a certain number of fixed charging piles (corresponding to the fixed charging facilities in Example 1) in each service area in the highway network. A pair of service area charging stations on both sides of the road share the capacity of the distribution transformer, but vehicles can only choose to charge in the service area on the same side. In the highway network, a certain number of city nodes and service area nodes can be included. At the city node, electric vehicles can choose to charge at the charging station at the exit of the highway section, which serves vehicles coming in both directions.

[0098] Based on historical statistical data, the traffic flow characteristics between cities in the region are obtained (corresponding to historical traffic flow data), including electric vehicle battery capacity, unit power consumption, departure rate distribution and origin and destination cities.

[0099] In an optional example, whether charging should be performed can be determined based on the remaining range, the usage of charging facilities in the current service area, and the distance to the next service area. In this embodiment, the judgment basis is quantified as a user charging tendency index, including a user mileage anxiety index and a queue time index. The calculation process of the user charging tendency index, the user mileage anxiety index, and the queue time index is explained below.

[0100]

[0101] in, represents the mileage anxiety value of user i, is the current state of charge, λ is the power consumption per unit mileage, is the distance to the next service area, The lower limit of the state of charge on the highway, E represents the battery capacity, is a small real number, avoiding An illegal situation occurred where the denominator was 0.

[0102]

[0103] in, For the queuing time, the queuing time can be calculated by estimating the queuing rounds. is the floor function, is the current number of electric vehicles in the charging station, To add the number of component mobile charging facilities, is the number of existing fixed charging facilities, is the average battery capacity, is the upper limit of the state of charge on the highway, η is the charger efficiency in the service area, P HW Charging power for chargers in service areas.

[0104]

[0105] in, It represents the queue time index, expressed in the form of negative exponential of queue time.

[0106]

[0107] in, represents the user charging tendency index, which is the weighted sum of the mileage anxiety index and the queue time index, where α HW and β HW are the preset parameters.

[0108] In an optional example, a simulation method may be used to predict the distribution of charging demand in each service area within a highway network.

[0109] For an electric car, its departure time is known Departure City HW , Destination city HW , and then get the mileage It is also known that the starting state of charge The power consumption per kilometer is λ, the battery capacity is E, and considering the user's anxiety about the remaining power and the power demand when arriving at the destination, the mid-distance charge state threshold needs to be given and destination state of charge threshold There are n service areas between the departure city and the destination city, namely SE 1 , SE 2 ,......,SE n , service area i has Charging piles. The distance between service areas i and j is When the departure time is reached, the electric vehicle enters the running state. Each time it enters the service area, a charging tendency index is calculated. The calculation result determines whether to enter the charging / queuing state. For example, if the user's charging tendency index is greater than the preset threshold, it can be determined that the electric vehicle enters the charging / queuing state, marked as 1. If the user's charging tendency index is less than or equal to the preset threshold, the electric vehicle does not need to enter the charging / queuing state, marked as 0. After charging is completed, The vehicle leaves the service area and re-enters the running state until it reaches the destination and resumes the parking state. Special note: considering the travel needs of users, a destination charge state threshold is set. To ensure that users have enough power to support their next activities in the destination city after arriving at the destination, according to general logic, there are:

[0110]

[0111] On the way from the departure city to the destination city, the electric vehicle can only be recharged in the service area. If the electric vehicle leaves the highway network before reaching the destination city d and enters the intermediate city c, the operation process of the electric vehicle can be regarded as two independent parts, (departure place, destination) are (o, c) and (c, d) respectively, and have corresponding other parameters. These two parts are regarded as independent trips when solving.

[0112] The prediction of charging demand for expressway networks also requires the collection of information on electric vehicle models, quantities, expressway network structure, user travel starting and ending points, departure time, and charging facilities in service areas. If there is no condition to obtain detailed data, refer to existing statistical data. Then generate a certain number of electric vehicles, set their relevant attributes according to the current data, and simulate the operating status of electric vehicles to obtain the queuing situation and charging demand distribution in each service area.

[0113] Step 3: Calculation of average charging queue time at high-speed service areas:

[0114] In an optional example, the number of electric vehicles in the queue in each time period is calculated by the simulation results in step 2, and then the average queue time is calculated. The calculation formula is:

[0115]

[0116] in, is the average queuing time at charging station j, Δt is the length of each time period, is a binary variable representing the state of an electric vehicle. If electric vehicle m is charging or queuing at charging station j at time t, then is 1, otherwise it is 0. By simulation method, N T is the total number of time periods, The number of existing charging facilities. is the average battery capacity, η is the charger efficiency in the service area, P HW Charging power for chargers in service areas.

[0117] Step 4: Planning of socket components for component-based mobile charging and discharging facilities in highway network service areas.

[0118] In an optional example, if there are service area charging station nodes that do not meet the queuing time constraint, the node with the longest queuing time among such nodes that still have the capacity to build charging facilities is selected, and a component-type mobile charging facility socket component is added; if all charging facilities that do not meet the queuing time constraint have no remaining capacity, each node is traversed in descending order according to the queuing time to determine whether charging facilities can be added to the adjacent nodes, until a service area node where charging facilities can be added is found in the planning area.

[0119] For each pair of service areas, the capacity constraints must be met:

[0120]

[0121] in, and Represents the number of component mobile charging facilities deployed in a pair of service areas with shared capacity on both sides of the road. The maximum number of charging piles that can be accommodated in the pair of service areas.

[0122] Step 5: Iterate between step 2 and step 4 until the end condition is met to obtain the planning results of the socket components of the component-type mobile charging facilities of the highway network.

[0123] In each iteration, first, the charging demand distribution in the highway network is calculated according to step 2, and then the average waiting time of each service area is calculated through step 2.

[0124] In each iteration, if all charging stations in the service area meet the queuing time requirements, that is: Then the iteration is terminated and the planning result is output, where is the maximum average queuing time.

[0125] Figure 3 is a flowchart of solving the socket layout planning for an optional scenario of increased charging demand on a high-speed road network according to an embodiment of the present invention, such as Figure 3 As shown, including:

[0126] S1. Initialize the highway network structure and the distribution of fixed charging facilities, simulate electric vehicle information, and set the number of mobile charging facilities in each service area to 0;

[0127] S2, calculate the charging demand distribution using the highway network electric vehicle travel simulation model;

[0128] S3. Calculate the queuing time in each service area charging station, and select the service area charging stations with a maximum queuing time. The serial numbers of the service area charging stations constitute a set SER = {ser k};

[0129] S4, determine whether SER is an empty set, and if SER is an empty set, output the final socket component planning result; otherwise, execute S5;

[0130] S5. Calculate the set SER = {ser k}Communication SER with service area charging station assembly with spare capacity to build component mobile charging facility socket assembly P ;

[0131] S6. Determine SERP Is it an empty set? In SER P If it is not an empty set, select SER P For the node with the longest queue time, add a component mobile charging facility to the node, and then execute S2. If the SERP is an empty set, execute S7.

[0132] S7, select the service area with the longest queuing time in SER, and select its adjacent node;

[0133] S8. Determine whether the adjacent node has surplus capacity. If there is surplus capacity, obtain the optimal construction location according to the preset simulation method and add a component mobile charging facility to the node. If there is no surplus capacity, P Remove the service area and then execute S7.

[0134] In this embodiment, based on the historical traffic flow characteristics, mobile charging facilities are planned for each service area in the planning area, avoiding the situation in the related art that only fixed charging facilities are deployed in the service area and mobile charging facilities cannot be planned, so that the planning results of the charging facilities for electric vehicles meet the charging needs of electric vehicles. In addition, the mobile charging facilities in this embodiment can be socket components in component-type mobile charging facilities, which have the characteristics of low deployment cost, and achieve the technical effect of improving the accuracy of deployment of charging facilities for electric vehicles in the highway network and the deployment cost of charging facilities.

[0135] Embodiment 3

[0136] An optional charging facility planning device according to an embodiment of the present invention, wherein each implementation unit in the planning device corresponds to each implementation step in the first embodiment.

[0137] Figure 4 is a schematic diagram of an optional charging facility planning device according to an embodiment of the present invention, such as Figure 4 As shown, it includes: an initialization unit 41, a first determination unit 42 and a second determination unit 43.

[0138] The initialization unit 41 is used to initialize the number of charging facilities in each service area in the planned area to obtain initial charging facility data, wherein the service area is used to provide charging services for electric vehicles, and the types of charging facilities include: fixed charging facilities and mobile charging facilities;

[0139] A first determination unit 42 is used to determine a charging prediction value of each electric vehicle in the area to be planned based on historical traffic flow data, wherein the historical traffic flow data at least includes: a battery capacity, a remaining cruising range, and a unit power consumption of each electric vehicle in the area to be planned within a historical time period, and the charging prediction value of each electric vehicle is used to indicate a probability of charging of the electric vehicle;

[0140] The second determining unit 43 is used to determine the target planning result based on the charging prediction value of each electric vehicle and the initial charging facility data, wherein the target planning result includes: the planning result of the mobile charging facilities in the area to be planned.

[0141] In the charging facility planning device provided in the third embodiment of the present invention, the number of charging facilities in each service area in the planned area can be initialized by the initialization unit 41 to obtain the initial charging facility data, wherein the types of charging facilities include: fixed charging facilities and mobile charging facilities, and the charging prediction value of each electric vehicle in the planned area is determined by the first determination unit 42 based on the historical traffic flow data, wherein the historical traffic flow data at least includes: the battery capacity, remaining cruising range and unit power consumption of each electric vehicle in the planned area during the historical time period, and the charging prediction value of each electric vehicle is used to indicate the probability of the electric vehicle being charged, and the target planning result is determined by the second determination unit 43 based on the charging prediction value of each electric vehicle and the initial charging facility data, wherein the target planning result includes: the planning result of the mobile charging facilities in the planned area. This solves the technical problem of poor deployment effect of charging facilities for electric vehicles deployed in the highway network in the related technology.

[0142] In this embodiment, based on the historical traffic flow characteristics, mobile charging facilities are planned for each service area in the planning area, avoiding the situation in the related technology that only fixed charging facilities are deployed in the service area and mobile charging facilities cannot be planned. The purpose of making the planning results of the charging facilities for electric vehicles meet the charging needs of electric vehicles is achieved, and the technical effect of improving the accuracy of the deployment of charging facilities for electric vehicles in the highway network is achieved.

[0143] Optionally, in the charging facility planning device provided in Example 3 of the present invention, the second determination unit includes: a first determination subunit, used to determine the average queuing time of electric vehicles in each service area based on the charging prediction value of each electric vehicle; and a second determination subunit, used to determine the target planning result based on the average queuing time of electric vehicles in each service area and the initial charging facility data.

[0144] Optionally, in the charging facility planning device provided in Example 3 of the present invention, the area to be planned includes: the area of ​​mobile charging facilities to be planned in the expressway network, the area to be planned includes: M service areas, the service areas are used to provide charging services for electric vehicles, M is a positive integer, and the second determination subunit includes: an update module, which is used to update the initial charging facility data based on the remaining power supply capacity of the target service area when there is a target service area among the M service areas, so as to obtain a target planning result, wherein the target service area includes: a service area where the average queuing time of electric vehicles does not meet preset conditions, and the preset conditions include: the average queuing time of electric vehicles is less than the preset time, and the remaining power supply capacity is used to indicate the number of charging facilities that can be added to the service area; a determination module, which is used to determine the target planning result based on the initial charging facility data when there is no target service area among the M service areas.

[0145] Optionally, in the charging facility planning device provided in Example 3 of the present invention, the updating module includes: a processing submodule, which is used to update the initial charging facility data based on the target service area with remaining power supply capacity to obtain first charging facility data, and determine the target planning result based on the first charging facility data, wherein the number of mobile charging facilities in the first charging facility data is greater than the number of mobile charging facilities in the initial charging facility data; a determining submodule, which is used to determine the target planning result based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in N designated service areas when there is no remaining power supply capacity in the target service area, wherein the N designated service areas include: service areas other than the target service area in the area to be planned, and N is a positive integer less than M.

[0146] Optionally, in the charging facility planning device provided in Example 3 of the present invention, the determination submodule includes: a judgment submodule one, used to judge whether each designated service area can add mobile charging facilities based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in the N designated service areas, and obtain a judgment result; a determination submodule one, used to update the number of mobile charging facilities in the designated service area in the initial charging facility data when the judgment result indicates that mobile charging facilities can be added in any designated service area, and obtain a target planning result.

[0147] Optionally, in the planning device for charging facilities provided in Example 3 of the present invention, the mobile charging facilities include: a socket assembly of a component-type mobile charging facility, wherein the component-type mobile charging facility is used to charge electric vehicles, and the component-type mobile charging facility includes: a socket assembly and a charger assembly, the socket assembly is fixed in the service area, and the charger assembly is movable.

[0148] Optionally, in the charging facility planning device provided in Example 3 of the present invention, the processing submodule includes: a sorting submodule one, which is used to sort the target service areas with remaining power supply capacity based on the average queuing time of electric vehicles when there is remaining power supply capacity in the target service area, and obtain a sorting result; a determination submodule two, which is used to update the number of mobile charging facilities in the target service area with remaining power supply capacity in the initial charging facility data based on the sorting result, and obtain a target planning result.

[0149] The above-mentioned charging facility planning device may also include a processor and a memory. The above-mentioned initialization unit 41, the first determination unit 42 and the second determination unit 43, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize corresponding functions.

[0150] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the kernel parameters can be adjusted to plan the mobile charging facilities in each service area in the planning area based on the historical traffic flow characteristics, thereby avoiding the situation in the related technology that only fixed charging facilities are deployed in the service area and the mobile charging facilities cannot be planned, so as to achieve the purpose of making the planning results of the charging facilities for electric vehicles meet the charging needs of electric vehicles, and realize the technical effect of improving the accuracy of the deployment of charging facilities for electric vehicles in the highway network.

[0151] The above-mentioned memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one storage chip.

[0152] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute any one of the above-mentioned methods for planning electric vehicle charging facilities by executing the executable instructions.

[0153] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, which stores a computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned methods for planning electric vehicle charging facilities.

[0154] Figure 5 is a schematic diagram of an electronic device according to an embodiment of the present invention, such as Figure 5As shown, an embodiment of the present invention provides an electronic device 50, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, any one of the above-mentioned methods for planning electric vehicle charging facilities is implemented.

[0155] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0156] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0157] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0158] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0159] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0160] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0161] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for planning electric vehicle charging facilities, characterized in that: include: Initializing the number of charging facilities in each service area in the planned area to obtain initial charging facility data, wherein the types of the charging facilities include: fixed charging facilities and mobile charging facilities; Based on the historical traffic flow data, determining the charging prediction value of each electric vehicle in the area to be planned, wherein the historical traffic flow data at least includes: the battery capacity, remaining cruising range and unit power consumption of each electric vehicle in the area to be planned during the historical time period, and the charging prediction value of each electric vehicle is used to indicate the probability of charging of the electric vehicle; Based on the charging prediction value of each electric vehicle and the initial charging facility data, a target planning result is determined, wherein the target planning result includes: a planning result of the mobile charging facilities in the area to be planned.

2. The planning method according to claim 1, characterized in that: Based on the charging prediction value of each electric vehicle and the initial charging facility data, a target planning result is determined, including: Determine the average queuing time of electric vehicles in each of the service areas based on the charging prediction value of each of the electric vehicles; The target planning result is determined based on the average queuing time of electric vehicles in each of the service areas and the initial charging facility data.

3. The planning method according to claim 2, characterized in that: The area to be planned includes: an area of ​​mobile charging facilities to be planned in the expressway network, the area to be planned includes: M service areas, the service areas are used to provide charging services for electric vehicles, M is a positive integer, based on the average queuing time of electric vehicles in each of the service areas and the initial charging facility data, the target planning result is determined, including: In the case where there is a target service area among the M service areas, based on the remaining power supply capacity of the target service area, the initial charging facility data is updated to obtain the target planning result, wherein the target service area includes: a service area where the average queuing time of the electric vehicle does not meet a preset condition, and the preset condition includes: the average queuing time of the electric vehicle is less than a preset time, and the remaining power supply capacity is used to indicate the number of charging facilities that can be added to the service area; When the target service area does not exist in the M service areas, the target planning result is determined based on the initial charging facility data.

4. The planning method according to claim 3, characterized in that: In the case where there is a target service area among the M service areas, updating the initial charging facility data based on the remaining power supply capacity of the target service area to obtain the target planning result includes: In the case where the remaining power supply capacity exists in the target service area, based on the target service area where the remaining power supply capacity exists, the initial charging facility data is updated to obtain first charging facility data, and the target planning result is determined based on the first charging facility data, wherein the number of mobile charging facilities in the first charging facility data is greater than the number of mobile charging facilities in the initial charging facility data; In the case that the target service area does not have the remaining power supply capacity, the target planning result is determined based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in N designated service areas, wherein the N designated service areas include: the service areas in the area to be planned except the target service area, and N is a positive integer less than M.

5. The planning method according to claim 4, characterized in that: In the case that the target service area does not have the remaining power supply capacity, the target planning result is determined based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in N designated service areas, including: Based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in the N designated service areas, determining whether each of the designated service areas can add the mobile charging facility to obtain a determination result; When the judgment result indicates that the mobile charging facility can be added in any of the designated service areas, the number of the mobile charging facilities in the designated service area is updated in the initial charging facility data to obtain the target planning result.

6. The planning method according to claim 1, characterized in that: The mobile charging facility comprises: a socket component of a component-type mobile charging facility, wherein the component-type mobile charging facility is used to charge the electric vehicle, and the component-type mobile charging facility comprises: a socket component and a charger component, the socket component is fixed in the service area, and the charger component is movable.

7. The planning method according to claim 4, characterized in that: In the case where the remaining power supply capacity exists in the target service area, based on the target service area where the remaining power supply capacity exists, updating the initial charging facility data to obtain first charging facility data, and determining the target planning result based on the first charging facility data, including: In the case where the target service area has the remaining power supply capacity, the target service area having the remaining power supply capacity is sorted based on the average queuing time of the electric vehicles to obtain a sorting result; Based on the sorting result, the number of mobile charging facilities in the target service area with the remaining power supply capacity in the initial charging facility data is updated to obtain the target planning result.

8. A planning device for electric vehicle charging facilities, characterized in that: include: An initialization unit, used to initialize the number of charging facilities in each service area in the planned area to obtain initial charging facility data, wherein the types of the charging facilities include: fixed charging facilities and mobile charging facilities; A first determination unit is used to determine a charging prediction value of each electric vehicle in the area to be planned based on historical traffic flow data, wherein the historical traffic flow data at least includes: a battery capacity, a remaining cruising range, and a unit power consumption of each electric vehicle in the area to be planned within a historical time period, and the charging prediction value of each electric vehicle is used to indicate a probability of charging of the electric vehicle; The second determination unit is used to determine the target planning result based on the charging prediction value of each electric vehicle and the initial charging facility data, wherein the target planning result includes: the planning result of the mobile charging facility in the area to be planned.

9. The planning device according to claim 8, characterized in that The second determining unit includes: A first determining subunit, configured to determine an average queuing time of electric vehicles in each of the service areas based on a charging prediction value of each of the electric vehicles; The second determination subunit is used to determine the target planning result based on the average queuing time of electric vehicles in each of the service areas and the initial charging facility data.

10. The planning device according to claim 9, characterized in that The area to be planned includes: an area in the expressway network where mobile charging facilities are to be planned, the area to be planned includes: M service areas, the service areas are used to provide charging services for electric vehicles, M is a positive integer, and the second determination subunit includes: An updating module, configured to update the initial charging facility data based on the remaining power supply capacity of the target service area to obtain the target planning result when there is a target service area among the M service areas, wherein the target service area includes: a service area where the average queuing time of the electric vehicle does not meet a preset condition, and the preset condition includes: the average queuing time of the electric vehicle is less than a preset time, and the remaining power supply capacity is used to indicate the number of charging facilities that can be added to the service area; A determination module is used to determine the target planning result based on the initial charging facility data when the target service area does not exist in the M service areas.

11. The planning device according to claim 10, characterized in that Update modules include: a processing submodule, configured to update the initial charging facility data based on the target service area where the remaining power supply capacity exists, obtain first charging facility data, and determine the target planning result based on the first charging facility data, if the remaining power supply capacity exists in the target service area, wherein the number of mobile charging facilities in the first charging facility data is greater than the number of mobile charging facilities in the initial charging facility data; A determination submodule is used to determine the target planning result based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in N designated service areas when the remaining power supply capacity does not exist in the target service area, wherein the N designated service areas include: the service areas in the area to be planned except the target service area, and N is a positive integer less than M.

12. The planning device according to claim 11, characterized in that The submodules include: A judgment submodule 1 is used to judge whether each designated service area can add the mobile charging facility based on the average queuing time of electric vehicles in the target service area and the remaining power supply capacity in the N designated service areas, and obtain a judgment result; Determine submodule one, for updating the number of mobile charging facilities in any designated service area in the initial charging facility data to obtain the target planning result when the judgment result indicates that the mobile charging facility can be added in any designated service area.

13. The planning device according to claim 8, characterized in that The mobile charging facility comprises: a socket component of a component-type mobile charging facility, wherein the component-type mobile charging facility is used to charge the electric vehicle, and the component-type mobile charging facility comprises: a socket component and a charger component, the socket component is fixed in the service area, and the charger component is movable.

14. The planning device according to claim 11, characterized in that The processing submodules include: A sorting submodule 1 is used for sorting the target service areas with the remaining power supply capacity based on the average queuing time of the electric vehicles to obtain a sorting result when the remaining power supply capacity exists in the target service area; Determine submodule two, for updating the number of mobile charging facilities in the target service area with the remaining power supply capacity in the initial charging facility data based on the sorting result, and obtain the target planning result.

15. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the electric vehicle charging facility planning method according to any one of claims 1 to 7.

16. An electronic device, characterized in that: It includes one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the electric vehicle charging facility planning method described in any one of claims 1 to 7.

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