Charging pile node location determination method, device, equipment and storage medium

Abstract

The present invention relates to the field of charging pile planning, and discloses a method, device, equipment and storage medium for determining the location of a charging pile node. The method obtains road information of a road; determines preset charging pile node distribution information based on the road information; obtains real-time state change information of a power grid and charging pile information, evaluates the preset charging pile node distribution information through the real-time state change information of the power grid and the charging pile information, obtains a charging pile visualization distribution model based on the evaluation result; and determines the charging pile node location based on the charging pile visualization distribution model. Since the preset charging pile node distribution information is determined through road information, and the preset charging pile node distribution information is evaluated based on the real-time state information of the power grid and the charging pile information, the load distribution of the power grid can be better utilized, and the site selection optimization of the charging pile node can be realized, which helps to improve the utilization rate and service quality of the charging piles, and improves the sustainable development capacity of clean energy transportation.

Description

Technical Field

[0001] The present invention relates to the technical field of charging pile planning, and in particular to a method, device, equipment and storage medium for determining a charging pile node position. Background Art

[0002] As climate change, energy shortages and environmental pollution become increasingly serious, especially air pollution caused by automobile emissions, it is a major problem in the environmental governance of large cities. As a result, new energy products such as electric vehicles have an increasing market share, and more and more research and investment in electric vehicles are being made around the world.

[0003] As more and more users choose to use electric vehicles as a means of transportation, the limitations of electric vehicle range and charging time mean that electric vehicles can only reach destinations with a fixed or shorter distance. Therefore, in order for electric vehicles to travel without being troubled by power and charging problems, it is necessary to reasonably determine the location of charging piles.

[0004] The existing distribution of charging pile nodes is mainly set according to the mileage of the car, and the setting of charging pile nodes on highways is not scientific.

[0005] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0006] The main purpose of the present invention is to provide a method, device, equipment and storage medium for determining the location of a charging pile node, aiming to solve the technical problem of the poor scientificity of the charging pile node setting in the prior art.

[0007] To achieve the above object, the present invention provides a method for determining the location of a charging pile node, the method comprising the following steps:

[0008] Get road information of the road;

[0009] Determine preset charging pile node distribution information based on the road information;

[0010] Acquire real-time state change information of the power grid and charging pile information, evaluate the preset charging pile node distribution information based on the real-time state change information of the power grid and the charging pile information, and obtain a charging pile visualization distribution model based on the evaluation result;

[0011] The charging pile node locations are determined based on the charging pile visualization distribution model.

[0012] Optionally, the step of acquiring road information of the road includes:

[0013] Acquire geographic information raster data and vector data, and establish a road model of the road according to the geographic information raster data and vector data;

[0014] Dividing the road model into regions to obtain monitoring sub-regions and regional information of each monitoring sub-region;

[0015] The traffic flow data of each monitoring sub-area is obtained, and each monitoring sub-area is scored according to the traffic flow data to obtain a traffic score; the road information includes the area information and traffic score of each monitoring sub-area.

[0016] Optionally, the step of determining preset charging pile node distribution information based on the road information includes:

[0017] Based on the traffic score, a monitoring sub-area with a preset number of charging piles is selected from each of the monitoring sub-areas as a first priority sub-area, and other monitoring sub-areas are selected as second priority sub-areas;

[0018] Determine a first priority charging pile node position in each first priority sub-area based on the area information of each first priority sub-area;

[0019] and, determining a second priority charging pile node position in each of the second priority sub-areas based on the area information of each of the second priority sub-areas;

[0020] The preset charging pile node distribution information includes a first priority charging pile node position and a second priority charging pile node position.

[0021] Optionally, the step of acquiring real-time grid state change information and charging pile information, evaluating the preset charging pile node distribution information through the real-time grid state change information and the charging pile information, and obtaining a charging pile visualization distribution model includes:

[0022] Obtain real-time status change information of the power grid and charging pile information;

[0023] Based on the real-time state change information of the power grid and the charging pile information, each monitoring sub-area is simulated and deduced to determine the power grid load priority of each monitoring sub-area;

[0024] The charging pile visualization distribution model is determined by the power grid load priority and the preset charging pile node distribution information.

[0025] Optionally, the step of determining a charging pile visualization distribution model according to the grid load priority and the preset charging pile node distribution information includes:

[0026] Based on the grid load priority, a monitoring sub-area with a preset number of charging piles is selected from each monitoring sub-area as a load priority sub-area;

[0027] The monitoring sub-area which is both the load priority sub-area and the first priority sub-area is used as the benchmark monitoring sub-area of ​​the charging pile visualization distribution model;

[0028] Determine the location of the benchmark charging pile node and the location of the additional charging pile node based on the benchmark monitoring sub-area;

[0029] A charging pile visualization distribution model is determined according to the reference charging pile node position and the position of the additional charging pile node.

[0030] Optionally, the step of determining the position of the benchmark charging pile node and the position of the additional charging pile node based on the benchmark monitoring sub-area includes:

[0031] Determine the reference charging pile node position corresponding to the reference monitoring sub-area;

[0032] Obtain the charging pile node density constraint function of the charging pile visualization distribution model;

[0033] The monitoring sub-area where the additional charging pile node is located is determined based on the reference charging pile node position and the charging pile node density constraint function.

[0034] Optionally, when determining the monitoring sub-area where the additional charging pile node is located, the first priority sub-area is preferentially selected as the monitoring sub-area where the additional charging pile node is located.

[0035] In addition, to achieve the above-mentioned purpose, the present invention also proposes a charging pile node position determination device, the charging pile node position determination device comprising:

[0036] A data acquisition module, used to acquire road information of a road;

[0037] A node preset module, used to determine preset charging pile node distribution information based on the road information;

[0038] A node verification module is used to obtain real-time state change information of the power grid and charging pile information, evaluate the preset charging pile node distribution information through the real-time state change information of the power grid and the charging pile information, and obtain a visual distribution model of the charging piles;

[0039] The location determination module is used to determine the location of the charging pile node based on the charging pile visualization distribution model.

[0040] In addition, to achieve the above-mentioned purpose, the present invention also proposes a charging pile node location determination device, which includes: a memory, a processor, and a charging pile node location determination program stored in the memory and executable on the processor, and the charging pile node location determination program is configured to implement the steps of the charging pile node location determination method as described above.

[0041] In addition, to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a charging pile node location determination program is stored. When the charging pile node location determination program is executed by a processor, the steps of the charging pile node location determination method described above are implemented.

[0042] The embodiment of the present invention obtains the road information of the road; determines the preset charging pile node distribution information based on the road information; obtains the real-time state change information of the power grid and the charging pile information, evaluates the preset charging pile node distribution information through the real-time state change information of the power grid and the charging pile information, obtains the charging pile visualization distribution model based on the evaluation result; and determines the charging pile node location based on the charging pile visualization distribution model. Since the charging pile nodes are preset through the road information, the preset charging pile node distribution information is determined, and the preset charging pile node distribution information is evaluated based on the real-time state information of the power grid and the charging pile information, the load distribution of the power grid can be better utilized, and the site selection optimization of the charging pile nodes can be realized, which helps to improve the utilization rate and service quality of the charging piles and improve the sustainable development capacity of clean energy transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a structural diagram of a charging pile node position determination device in a hardware operating environment involved in an embodiment of the present invention;

[0044] Figure 2 This is a flow chart of a first embodiment of a method for determining a charging pile node position according to the present invention;

[0045] Figure 3 This is a flow chart of a second embodiment of a method for determining a charging pile node position according to the present invention;

[0046] Figure 4 This is a structural block diagram of the first embodiment of the charging pile node location determination device of the present invention.

[0047] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0048] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0049] Reference Figure 1 , Figure 1 A schematic diagram of the structure of a charging pile node location determination device in a hardware operating environment involved in an embodiment of the present invention.

[0050] like Figure 1 As shown, the charging pile node location determination device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM), or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0051] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the charging pile node location determination device, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0052] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a charging pile node location determination program.

[0053] exist Figure 1 In the charging pile node location determination device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the charging pile node location determination device of the present invention can be set in the charging pile node location determination device, and the charging pile node location determination device calls the charging pile node location determination program stored in the memory 1005 through the processor 1001, and executes the charging pile node location determination method provided by the embodiment of the present invention.

[0054] The embodiment of the present invention provides a method for determining the location of a charging pile node, referring to Figure 2 , Figure 2It is a flow chart of the first embodiment of the method for determining the location of a charging pile node of the present invention.

[0055] In this embodiment, the charging pile node location determination method includes the following steps:

[0056] Step S10: Acquire road information of the road.

[0057] It should be noted that the execution subject of the method of this embodiment can be a terminal device with data acquisition, map recognition, data processing and program running functions, such as a computer, server, etc., or an electronic device with the same or similar functions, such as the above-mentioned charging pile node location determination device. The following takes the charging pile node location determination device (hereinafter referred to as the location device) as an example to illustrate this embodiment and the following embodiments.

[0058] It is understandable that the above-mentioned road can be a highway or an ordinary urban road. When car owners are driving on highways, there are difficult to deal with problems such as long-distance mileage anxiety and tidal phenomena. The present invention obtains road information of highways and establishes a visual distribution model of charging piles to determine the location distribution of charging piles, thereby supporting a variety of charging scenarios including highway service areas, highway entrances and exits, and large parking lots, providing car owners with more comprehensive charging resources, and transforming scenes such as highway service areas from oil vehicle services to energy services for all models.

[0059] It should be noted that the above-mentioned road information may include the specific route and connection conditions of the expressway, such as the starting and ending points of the expressway, the length of the expressway, the expressway service areas along the way, traffic conditions, surrounding environment, vehicle types, power supply conditions, etc.

[0060] In an implementation of the embodiment of the present invention, the step of acquiring the road information of the road includes:

[0061] Obtain geographic information raster data and vector data, and establish a road model of the road according to the geographic information raster data and vector data.

[0062] It should be noted that geographic information raster data is a type of data organized by regular rectangular grids or pixels, where each rectangular grid or pixel can represent an area in geographic space and contain attribute information of the area.

[0063] It can be understood that geographic information vector data is data that describes geographic information through a collection of objects such as points, lines, and surfaces. For each object in the geographic space, it has a specific spatial position and geometric shape. Through geographic information vector data, geographic objects, geometric shapes, and attribute information can be accurately represented to facilitate spatial analysis and modeling.

[0064] It should be understood that by extracting data features of raster data and quantity data and fusing the extracted features, modeling can be performed based on the fused features to obtain a road model. The embodiment of the present invention does not limit the specific modeling method, and different modeling methods can be selected according to the application in actual situations.

[0065] The road model is divided into regions to obtain monitoring sub-regions and regional information of each monitoring sub-region.

[0066] It should be noted that, when the road model is built, the road model can be divided into regions to obtain different monitoring sub-regions and regional information corresponding to each monitoring sub-region.

[0067] It is understandable that by dividing the road model into multiple monitoring sub-areas, the site selection of charging piles can be evaluated more precisely. At the same time, a more scientific and reasonable charging pile distribution strategy can be formulated based on factors such as traffic flow, road grade, and surrounding facilities in different areas to avoid centralized deployment.

[0068] Specifically, the method of dividing the region may be based on the area of ​​the region, or may be based on other methods, such as surrounding facilities, road grade, etc., which is not limited in the embodiment of the present invention.

[0069] The traffic flow data of each monitoring sub-area is obtained, and each monitoring sub-area is scored according to the traffic flow data to obtain a traffic score; the road information includes the area information and traffic score of each monitoring sub-area.

[0070] It should be noted that when the road model is divided into multiple monitoring sub-areas, the traffic flow data of each monitoring sub-area can be obtained, and the level scoring of each monitoring sub-area can be achieved through the traffic flow data to obtain the traffic score of each monitoring sub-area.

[0071] It is understandable that by analyzing the collected traffic flow data, the traffic score of each monitoring sub-area can be determined by using a corresponding algorithm, such as a rule-based scoring method, a machine learning model, etc., and the embodiment of the present invention is not limited to this.

[0072] It should be understood that the greater the traffic volume in a monitoring sub-area, the higher the demand for the corresponding charging pile deployment. Therefore, the priority of the monitoring sub-area needs to be increased. That is, the greater the traffic volume in a monitoring sub-area, the higher the traffic score, and vice versa.

[0073] In a specific implementation, the location device can obtain road information of the road. Since the location of the charging pile node is determined based on the road information, it helps to improve the utilization rate and service quality of the charging piles and enhance the sustainable development capacity of clean energy transportation.

[0074] Step S20: Determine preset charging pile node distribution information based on the road information.

[0075] It should be understood that the location of charging pile nodes can be selected based on road information, thereby determining the distribution information of preset charging pile nodes.

[0076] It should be noted that the above-mentioned site selection method can be based on distance, can be based on traffic volume, or can be based on other methods, and the embodiment of the present invention is not limited to this.

[0077] It should be understood that the charging pile node described in the embodiment of the present invention is an area where charging piles are set. In each charging pile node, at least one charging pile can be set, so that electric vehicles passing through the charging pile node can be charged based on the charging pile.

[0078] In one implementation of an embodiment of the present invention, the number and distance intervals of charging pile nodes to be set on the highway can be determined based on the driving distance of the car owner on the highway and the endurance of the electric vehicle to ensure that the driver can reach the next charging pile in time during driving.

[0079] It should be noted that, in order to ensure that the charging pile nodes can be screened and optimized, when determining the distribution information of the preset charging pile nodes based on the distance, the embodiment of the present invention may not use the optimal distance as the distance between two preset charging pile nodes, thereby increasing the number of preset charging pile nodes. For example, if the optimal charging pile node distance is 100 kilometers, the distance between the two preset charging pile nodes can be set to 50 kilometers or 30 kilometers in the embodiment of the present invention.

[0080] In one implementation of an embodiment of the present invention, preset charging pile nodes may be set at intersections and road connections or forks on a highway. By acquiring distribution information of the preset charging pile nodes and screening the preset charging pile nodes, the charging pile nodes with settings may be determined.

[0081] In one implementation of the embodiment of the present invention, the road information may include the regional information and traffic information of the monitoring sub-area. The preset charging pile node distribution information may be determined based on the regional information and traffic information of each monitoring sub-area. Specifically, the step of determining the preset charging pile node distribution information based on the road information includes:

[0082] Based on the traffic score, a monitoring sub-area with a preset number of charging piles is selected from each of the monitoring sub-areas as a first priority sub-area, and other monitoring sub-areas are selected as second priority sub-areas.

[0083] Determine a first priority charging pile node position in each first priority sub-area based on the area information of each first priority sub-area;

[0084] and, determining a second priority charging pile node position in each of the second priority sub-areas based on the area information of each of the second priority sub-areas;

[0085] The preset charging pile node distribution information includes a first priority charging pile node position and a second priority charging pile node position.

[0086] It should be noted that when determining the preset charging pile node distribution information, the preset number of charging piles can be determined first, for example, the preset number of charging piles is x. The x monitoring sub-areas with the highest traffic scores can be selected as the first priority sub-areas in each monitoring sub-area, and the other monitoring sub-areas can be selected as the second priority sub-areas. When determining the first priority sub-area and the second priority sub-area, the location of the charging pile node in the area can be determined based on the area information of each area, that is, the location of the first priority charging pile node and the second priority charging pile node can be determined.

[0087] It should be understood that the above-mentioned preset number of charging piles can be determined according to the size of the deployment area, and the embodiment of the present invention is not limited to this.

[0088] In the specific implementation, the location device can determine the preset charging pile node distribution information based on the road information, and can better understand the areas with high traffic demand and good traffic conditions, so as to determine the layout of the charging piles in a targeted manner. Setting up charging pile nodes in areas with heavy traffic or severe traffic congestion can provide electric car owners with more convenient and efficient charging services, improve user experience and improve the utilization rate of charging facilities, avoid waste of resources and idle charging piles, and improve the efficiency of the overall charging network.

[0089] Step S30: acquiring real-time state change information of the power grid and charging pile information, evaluating the preset charging pile node distribution information through the real-time state change information of the power grid and the charging pile information, and obtaining a charging pile visualization distribution model based on the evaluation result;

[0090] Step S40: Determine the charging pile node location based on the charging pile visualization distribution model.

[0091] It is understandable that the real-time state change information of the power grid is also the information on the changes of various parameters and indicators in the power system during real-time operation. The real-time state change information of the power grid may include real-time change information of load data, real-time change information of voltage data, etc., which is not limited in the embodiments of the present invention.

[0092] It should be understood that the above-mentioned charging pile information may include power information, charging interface information, charging pile type, charging pile rate and other information of the charging pile, and the embodiment of the present invention is not limited to this.

[0093] It should be noted that when the real-time state change information of the power grid and the charging pile information are obtained, the visual distribution model of the charging piles can be determined according to the real-time state change information of the power grid and the charging pile information. Specifically, the preset charging pile nodes in each monitoring sub-area can be evaluated in combination with the load information and the voltage information, and screened according to the evaluation results to obtain the final charging pile node position, and modeling is performed based on the final charging pile node position to obtain the visual distribution model of the charging piles.

[0094] It can be understood that the location of each charging pile node can be determined based on the charging pile visualization distribution model.

[0095] In the specific implementation, the real-time state change information of the power grid and the charging pile information can be obtained, and the charging pile node distribution information can be evaluated through the real-time state change information of the power grid and the charging pile information, and the charging pile visualization distribution model can be obtained based on the evaluation results. The location of the charging pile node can be determined based on the charging pile visualization distribution model. Since the charging pile node distribution information is evaluated based on the real-time state change information of the power grid and the charging pile information, the load distribution of the power grid can be better utilized, the site selection of the charging pile node can be optimized, the utilization rate and convenience of the charging facilities are improved, and the charging efficiency of the charging network is improved, the charging cost is optimized, and it is conducive to the popularization of electric vehicles.

[0096] The embodiment of the present invention obtains the road information of the road; determines the preset charging pile node distribution information based on the road information; obtains the real-time state change information of the power grid and the charging pile information, evaluates the preset charging pile node distribution information through the real-time state change information of the power grid and the charging pile information, obtains the charging pile visualization distribution model based on the evaluation result; and determines the charging pile node location based on the charging pile visualization distribution model. Since the charging pile nodes are preset through the road information, the preset charging pile node distribution information is determined, and the preset charging pile node distribution information is evaluated based on the real-time state information of the power grid and the charging pile information, the load distribution of the power grid can be better utilized, and the site selection optimization of the charging pile nodes can be realized, which helps to improve the utilization rate and service quality of the charging piles and improve the sustainable development capacity of clean energy transportation.

[0097] Based on the first embodiment of the method for determining the location of a charging pile node of the present invention as described above, a second embodiment of the method for determining the location of a charging pile node of the present invention is proposed.

[0098] refer to Figure 3 , Figure 3 This is a flow chart of a second embodiment of a method for determining a charging pile node location according to the present invention.

[0099] like Figure 3 As shown, in this embodiment, the step of obtaining the real-time state change information of the power grid and the charging pile information, evaluating the preset charging pile node distribution information through the real-time state change information of the power grid and the charging pile information, and obtaining the charging pile visualization distribution model includes:

[0100] Step S31: Obtaining real-time grid status change information and charging pile information;

[0101] Step S32: simulating and deducing each monitoring sub-area based on the real-time state change information of the power grid and the charging pile information to determine the power grid load priority of each monitoring sub-area;

[0102] Step S33: Determine a charging pile visualization distribution model according to the grid load priority and the preset charging pile node distribution information.

[0103] It should be noted that when the real-time state change information of the power grid and the charging pile information are obtained, the charging pile can be simulated based on the charging pile information, and the simulated charging pile can be added to the road model. Then, the real-time state change information of the power grid is combined with the road model to realize the joint simulation of the road network and the power grid, and optimize the layout of the charging pile.

[0104] In one implementation of the embodiment of the present invention, when the charging piles are deployed, the greater the grid load in the monitoring sub-area, the lower the relative charge priority, and vice versa. Traffic bottlenecks, peak hours, and congested areas can be analyzed based on traffic information, and vehicle location information can be analyzed to determine vehicle distribution, running trajectory, and speed, thereby forming a vehicle trajectory map. In combination with the vehicle trajectory map and the grid charge distribution, the distribution information of the preset charging pile nodes can be screened, thereby optimizing the location of the charging pile nodes.

[0105] Specifically, the step of determining the charging pile visualization distribution model according to the power grid load priority and the preset charging pile node distribution information includes:

[0106] Based on the grid load priority, a monitoring sub-area with a preset number of charging piles is selected from each monitoring sub-area as a load priority sub-area;

[0107] The monitoring sub-area which is both the load priority sub-area and the first priority sub-area is used as the benchmark monitoring sub-area of ​​the charging pile visualization distribution model;

[0108] Determine the location of the benchmark charging pile node and the location of the additional charging pile node based on the benchmark monitoring sub-area;

[0109] A charging pile visualization distribution model is determined according to the reference charging pile node position and the position of the additional charging pile node.

[0110] It should be noted that a preset number of monitoring sub-areas for charging piles can be selected in each monitoring sub-area as a load priority sub-area. If a monitoring sub-area is both a first priority sub-area and a load priority sub-area, it can be explained that the monitoring sub-area can be directly used as an area for charging piles to be arranged, that is, a benchmark monitoring sub-area. Correspondingly, the charging pile node position set in the benchmark monitoring sub-area is also the benchmark charging pile node position.

[0111] In a specific implementation, the embodiment of the present invention simulates and deduces each detection sub-area through real-time grid status change information and charging pile information, thereby realizing the combination of road parameters and grid parameters and improving the rationality of the layout of charging pile locations.

[0112] Furthermore, in order to prevent the waste of resources caused by the over-dense charging pile nodes, the charging pile node density constraint function of the charging pile visualization distribution model can be obtained, and modeling can be performed based on the charging pile node density constraint function, so as to determine the monitoring sub-area where the additional charging pile nodes are located in the charging pile visualization distribution model, and then establish the charging pile visualization distribution model modeling. Specifically, the step of determining the location of the reference charging pile node and the location of the additional charging pile node based on the reference monitoring sub-area includes:

[0113] Determine the reference charging pile node position corresponding to the reference monitoring sub-area;

[0114] Obtain the charging pile node density constraint function of the charging pile visualization distribution model;

[0115] The monitoring sub-area where the additional charging pile node is located is determined based on the reference charging pile node position and the charging pile node density constraint function.

[0116] It should be noted that, when determining the monitoring sub-area where the additional charging pile node is located, if the density indexes are close, the first priority sub-area is preferentially selected as the monitoring sub-area where the additional charging pile node is located.

[0117] It can be understood that the embodiment of the present invention constrains the density of charging pile nodes through the charging pile node density constraint function, so that the charging pile nodes are not too dense when deployed, reducing the waste of resources caused by the charging pile nodes being deployed too close.

[0118] The embodiment of the present invention obtains real-time state change information of the power grid and charging pile information; simulates and deduces each monitoring sub-area based on the real-time state change information of the power grid and the charging pile information to determine the power grid load priority of each monitoring sub-area; and determines the charging pile visualization distribution model through the power grid load priority and the preset charging pile node distribution information. Since the monitoring sub-area is simulated and deduced based on the real-time state change information of the power grid and the charging pile information, the rationality of the charging pile node location layout is improved by combining the power grid charge and road information.

[0119] In addition, an embodiment of the present invention further proposes a storage medium, on which a charging pile node location determination program is stored. When the charging pile node location determination program is executed by a processor, the steps of the charging pile node location determination method described above are implemented.

[0120] Based on the first embodiment of the charging pile node position determination method of the present invention, the first embodiment of the charging pile node position determination device of the present invention is proposed, referring to Figure 4 , Figure 4 This is a structural block diagram of the first embodiment of the charging pile node location determination device of the present invention.

[0121] like Figure 4 As shown, the charging pile node location determination device proposed in the embodiment of the present invention includes:

[0122] A data acquisition module 401 is used to acquire road information of a road;

[0123] A node preset module 402, configured to determine preset charging pile node distribution information based on the road information;

[0124] The node verification module 403 is used to obtain the real-time state change information of the power grid and the charging pile information, and evaluate the preset charging pile node distribution information through the real-time state change information of the power grid and the charging pile information to obtain a visual distribution model of the charging piles;

[0125] The location determination module 404 is used to determine the location of the charging pile node based on the charging pile visualization distribution model.

[0126] The embodiment of the present invention obtains the road information of the road; determines the preset charging pile node distribution information based on the road information; obtains the real-time state change information of the power grid and the charging pile information, evaluates the preset charging pile node distribution information through the real-time state change information of the power grid and the charging pile information, obtains the charging pile visualization distribution model based on the evaluation result; and determines the charging pile node location based on the charging pile visualization distribution model. Since the charging pile nodes are preset through the road information, the preset charging pile node distribution information is determined, and the preset charging pile node distribution information is evaluated based on the real-time state information of the power grid and the charging pile information, the load distribution of the power grid can be better utilized, and the site selection optimization of the charging pile nodes can be realized, which helps to improve the utilization rate and service quality of the charging piles and improve the sustainable development capacity of clean energy transportation.

[0127] In one implementation of an embodiment of the present invention, the data acquisition module 401 is also used to acquire geographic information raster data and vector data, and establish a road model of the road based on the geographic information raster data and vector data; divide the road model into regions to obtain monitoring sub-regions and regional information of each monitoring sub-region; obtain traffic flow data of each monitoring sub-region, score each monitoring sub-region based on the traffic flow data, and obtain a traffic score; the road information includes the regional information and traffic score of each monitoring sub-region.

[0128] In one implementation of an embodiment of the present invention, the node preset module 402 is also used to select a monitoring sub-area with a preset number of charging piles in each of the monitoring sub-areas as a first priority sub-area based on the traffic score, and other monitoring sub-areas as second priority sub-areas; determine the first priority charging pile node position in each of the first priority sub-areas based on the area information of each of the first priority sub-areas; and determine the second priority charging pile node position in each of the second priority sub-areas based on the area information of each of the second priority sub-areas; the preset charging pile node distribution information includes the first priority charging pile node position and the second priority charging pile node position.

[0129] In one implementation of an embodiment of the present invention, the node verification module 403 is also used to obtain real-time power grid state change information and charging pile information; based on the real-time power grid state change information and the charging pile information, each monitoring sub-area is simulated and deduced to determine the power grid load priority of each monitoring sub-area; and the charging pile visualization distribution model is determined through the power grid load priority and the preset charging pile node distribution information.

[0130] In one implementation of the embodiment of the present invention, the node verification module 403 is also used to select a monitoring sub-area with a preset number of charging piles in each of the monitoring sub-areas as a load priority sub-area based on the power grid load priority; use a monitoring sub-area that is both a load priority sub-area and a first priority sub-area as a benchmark monitoring sub-area for a charging pile visualization distribution model; determine a benchmark charging pile node position and an additional charging pile node position based on the benchmark monitoring sub-area; and determine a charging pile visualization distribution model according to the benchmark charging pile node position and the additional charging pile node position.

[0131] In one implementation of an embodiment of the present invention, the node verification module 403 is also used to determine the benchmark charging pile node position corresponding to the benchmark monitoring sub-area; obtain the charging pile node density constraint function of the charging pile visualization distribution model; and determine the monitoring sub-area where the additional charging pile node is located based on the benchmark charging pile node position and the charging pile node density constraint function.

[0132] In an implementation of the embodiment of the present invention, when determining the monitoring sub-area where the additional charging pile node is located, the first priority sub-area is preferentially selected as the monitoring sub-area where the additional charging pile node is located.

[0133] Other embodiments or specific implementations of the device for determining the location of a charging pile node of the present invention may refer to the above-mentioned method embodiments and will not be described in detail here.

[0134] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0135] 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.

[0136] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory / random access memory, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0137] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for determining the location of a charging pile node, characterized in that: The method comprises: Acquire geographic information raster data and vector data, and establish a road model of the road according to the geographic information raster data and vector data; Dividing the road model into regions to obtain monitoring sub-regions and regional information of each monitoring sub-region; Obtaining traffic flow data of each monitoring sub-area, scoring each monitoring sub-area according to the traffic flow data, and obtaining a traffic score; the road information includes the area information and traffic score of each monitoring sub-area; Based on the traffic score, a monitoring sub-area with a preset number of charging piles is selected from each of the monitoring sub-areas as a first priority sub-area, and other monitoring sub-areas are selected as second priority sub-areas; Determine a first priority charging pile node position in each first priority sub-area based on the area information of each first priority sub-area; and, determining the second priority charging pile node position in each second priority sub-region based on the region information of each second priority sub-region; the preset charging pile node distribution information includes the first priority charging pile node position and the second priority charging pile node position; Obtain real-time status change information of the power grid and charging pile information; Based on the real-time state change information of the power grid and the charging pile information, each monitoring sub-area is simulated and deduced to determine the power grid load priority of each monitoring sub-area; Based on the grid load priority, a monitoring sub-area with a preset number of charging piles is selected from each monitoring sub-area as a load priority sub-area; The monitoring sub-area that is both a load priority sub-area and a first priority sub-area is used as a benchmark monitoring sub-area of ​​the charging pile visualization distribution model; the benchmark monitoring sub-area is a monitoring sub-area where charging piles can be directly deployed; Determine the position of the reference charging pile node corresponding to the reference monitoring sub-area; the reference charging pile node is the charging pile node in the reference monitoring sub-area; Obtain the charging pile node density constraint function of the charging pile visualization distribution model; Determine the monitoring sub-area where the additional charging pile node is located based on the reference charging pile node position and the charging pile node density constraint function; When determining the monitoring sub-area where the additional charging pile node is located, the first priority sub-area is preferentially selected as the monitoring sub-area where the additional charging pile node is located; Determine a charging pile visualization distribution model according to the reference charging pile node position and the additional charging pile node position; The charging pile node locations are determined based on the charging pile visualization distribution model.

2. A charging pile node location determination device, characterized in that: The charging pile node position determination device comprises: A data acquisition module is used to acquire geographic information raster data and vector data, and establish a road model of the road according to the geographic information raster data and vector data; divide the road model into regions, and obtain monitoring sub-regions and regional information of each monitoring sub-region; acquire traffic flow data of each monitoring sub-region, and score each monitoring sub-region according to the traffic flow data to obtain a traffic score; the road information includes the regional information and traffic score of each monitoring sub-region; A node preset module, used for selecting a monitoring sub-area with a preset number of charging piles in each of the monitoring sub-areas as a first priority sub-area based on the traffic score, and other monitoring sub-areas as second priority sub-areas; determining a first priority charging pile node position in each of the first priority sub-areas based on the area information of each of the first priority sub-areas; and determining a second priority charging pile node position in each of the second priority sub-areas based on the area information of each of the second priority sub-areas; the preset charging pile node distribution information includes the first priority charging pile node position and the second priority charging pile node position; A node verification module is used to obtain real-time state change information of the power grid and charging pile information; simulate and deduce each monitoring sub-area based on the real-time state change information of the power grid and the charging pile information to determine the power grid load priority of each monitoring sub-area; select a monitoring sub-area with a preset number of charging piles in each monitoring sub-area as a load priority sub-area based on the power grid load priority; use a monitoring sub-area that is both a load priority sub-area and a first priority sub-area as a benchmark monitoring sub-area of ​​a charging pile visualization distribution model; determine the benchmark charging pile node position corresponding to the benchmark monitoring sub-area; obtain a charging pile node density constraint function of a charging pile visualization distribution model; determine the monitoring sub-area where the additional charging pile node is located based on the benchmark charging pile node position and the charging pile node density constraint function; when determining the monitoring sub-area where the additional charging pile node is located, the first priority sub-area is preferentially selected as the monitoring sub-area where the additional charging pile node is located; determine the charging pile visualization distribution model according to the benchmark charging pile node position and the position of the additional charging pile node; the benchmark monitoring sub-area is a monitoring sub-area where charging piles can be directly deployed; the benchmark charging pile node is a charging pile node in the benchmark monitoring sub-area; The location determination module is used to determine the location of the charging pile node based on the charging pile visualization distribution model.

3. A charging pile node location determination device, characterized in that: The device comprises: A memory, a processor, and a charging pile node location determination program stored in the memory and executable on the processor, wherein the charging pile node location determination program is configured to implement the steps of the charging pile node location determination method as claimed in claim 1.

4. A storage medium, characterized in that: The storage medium stores a charging pile node location determination program, and when the charging pile node location determination program is executed by the processor, the steps of the charging pile node location determination method according to claim 1 are implemented.

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