A planning method and device for an electric vehicle charging station

Abstract

The application discloses a planning method and device for electric vehicle charging stations, comprising the following steps: obtaining the grid structure, line parameters and historical load of a regional distribution network, and calculating initial candidate nodes of the charging stations; correcting the initial candidate nodes of the charging stations according to the road network structure to obtain corrected candidate nodes; optimizing the corrected candidate nodes, and taking the node with the maximum value of the comprehensive evaluation index as the optimal arrangement node of the charging station. The application obtains the load limit value of each candidate node in the distribution network through power flow calculation, sorts the initial candidate nodes according to the load limit value to obtain the initial candidate node sequence, corrects the initial candidate nodes through the road network structure and the comprehensive evaluation index considering safety and economy, and obtains the most ideal layout position of the charging station. The method takes into account the safety and economic operation of the distribution network, the road network constraint and the like, and can fully consider the rationality of the charging station position.

Description

Technical Field

[0001] This invention belongs to the field of electric vehicle charging technology, specifically relating to a planning method and apparatus for electric vehicle charging stations. Background Technology

[0002] Electric vehicles have become an important means for countries to enhance their automotive industry competitiveness and develop a low-carbon economy, and related technologies have attracted high attention from countries around the world. Against this backdrop, the electric vehicle industry has developed rapidly in recent years, and the construction of electric vehicle charging infrastructure has also been in full swing. my country's electric vehicle and corresponding charging infrastructure will experience rapid growth in the next few years, and it is estimated that by 2030, the number of electric vehicles in China will exceed 100 million. The construction and operation management of integrated charging stations that combine electric vehicles, charging infrastructure, and new energy sources ("source-storage-charging") are an important means and an inevitable choice for the future development of "zero-carbon" transportation.

[0003] Charging station planning involves multi-dimensional spatiotemporal coupling of the source and load sides within the planning period. It needs to take into account source-load matching scenarios and network constraints in different areas of the distribution network, while also considering economic efficiency and reliability. Constructing a joint planning model for charging stations to maximize the distribution network's capacity to accommodate large-scale electric vehicles is an important aspect related to the future integrated development of the new energy and electric vehicle industries and the promotion of green and low-carbon transportation development.

[0004] Research on electric vehicle charging station planning technology is still in its early stages. Further in-depth research is needed on planning methods for charging stations that take into account the safe and economical operation of the power distribution network and meet the increased charging demand caused by the growth in the number of electric vehicles. Summary of the Invention

[0005] The purpose of this invention is to propose a planning method and apparatus for electric vehicle charging stations. This method can simultaneously ensure the safety and economy of power distribution network operation, while also meeting the constraints of road network conditions.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A method for planning electric vehicle charging stations includes the following steps:

[0008] Obtain the regional power distribution network structure, line parameters, and historical loads, and calculate the initial candidate nodes for charging stations;

[0009] Obtain the road network structure, and correct the initial candidate nodes of the charging station based on the road network structure to obtain the corrected candidate nodes;

[0010] The candidate nodes are optimized after correction, and a comprehensive evaluation index is calculated. The node with the maximum value of the comprehensive evaluation index is the optimal node for the charging station layout.

[0011] Furthermore, the initial candidate nodes for the charging station are calculated through the following process:

[0012] 1) Obtain the regional power distribution network structure, line parameters, and historical loads;

[0013] 2) Based on the number and location of existing charging stations in the area, traffic flow, and current road network conditions, select a node as the initial node for the initial layout of the charging station;

[0014] 3) If the n neighboring nodes of the initial node are set as candidate nodes, then all nodes that are less than or equal to n from the initial node are candidate nodes.

[0015] 4) Calculate the weighted average of the historical loads of all candidate nodes to obtain a typical daily load curve;

[0016] 5) For each candidate node, the typical daily load curve is calculated sequentially at set time intervals to obtain the maximum load value sequence at each time point under the conditions of line non-overload and voltage over-limit.

[0017] 6) Take the minimum value of the sequence of maximum load values ​​of the line under the conditions of no overload and voltage over-limit at each time point as the node load limit;

[0018] 7) Repeat steps 5)-6) for all candidate nodes to obtain the load limit of each node; and sort all the load limits of all nodes in descending order, and use all the sorted nodes as the initial candidate nodes of the charging station.

[0019] Furthermore, the step of performing power flow calculations on the typical daily load curve at set time intervals for each candidate node to obtain the maximum load value sequence at each time point under the conditions of line overload and voltage over-limit includes the following process: For each candidate node, performing power flow calculations on the typical daily load curve at set time intervals to determine whether there is line overload or voltage over-limit; if there is no line overload or voltage over-limit, incrementing the load value and repeating the power flow calculation; if there is line overload or voltage over-limit, reducing the increment to 1 / 2 of the original and repeating the power flow calculation.

[0020] Furthermore, the initial candidate nodes for charging stations are modified according to the road network structure to obtain modified candidate nodes. The process includes the following steps: scoring the candidate nodes based on their distance from existing charging stations in the road network, whether they are located at intersections of main urban roads, and their safe distance from densely populated areas. Based on the scores, the modified candidate nodes are obtained.

[0021] Furthermore, the specific process for scoring the initial layout nodes of the charging station is as follows:

[0022] If the distance between the candidate node and the existing charging station is less than the set distance, this indicator will score 0 points; otherwise, it will score 1 point.

[0023] If the distance between the candidate node and the intersection of the main urban road is less than the set distance, this indicator will score 0 points; otherwise, it will score 1 point.

[0024] If the candidate node is less than the safe distance from a densely populated area, this indicator scores 0 points; otherwise, it scores 1 point.

[0025] Furthermore, the scoring process is as follows: if a candidate node scores 0 points in any item, the total score of the candidate node is 0; if all scores are 1, the candidate node scores 1; charging stations with a score of 0 are removed to obtain the corrected candidate nodes.

[0026] Furthermore, the initial layout nodes of the charging stations are modified according to the road network structure to obtain modified candidate nodes. This also includes: calculating the geographical space where the candidate nodes are located and eliminating nodes whose space cannot meet the minimum construction requirements of the charging stations.

[0027] Furthermore, the comprehensive evaluation indicators are calculated using the following formula:

[0028] a i =ζ1s i +ζ2w i

[0029] Among them, a i Let s be the comprehensive evaluation index for the i-th candidate node. i w is a capacity metric representing the security of the i-th candidate node. i Let ζ1 be the line loss index representing the economic efficiency of the i-th candidate node, and let ζ2 be the weight of the safety index.

[0030] Furthermore, the capacity metric representing the security of the i-th candidate node is calculated using the following formula:

[0031]

[0032] Among them, s′ i Let s be the load limit of the i-th candidate node calculated in the above steps. min s is the minimum of the load limits for all candidate nodes. max This is the maximum value of the load limit for all candidate nodes.

[0033] Furthermore, the line loss index representing the economic efficiency of the i-th candidate node is calculated using the following formula:

[0034]

[0035] Among them, parameters w″ i Let w be the distribution network line loss at the maximum load of the i-th candidate node. min For all parameters w′ i The minimum value, w max For all w′ i The maximum value.

[0036] A planning device for an electric vehicle charging station, comprising:

[0037] The initial candidate node calculation unit for charging stations is used to obtain the regional power distribution network structure, line parameters and historical load, and to calculate the initial candidate nodes for charging stations.

[0038] The candidate node correction unit is used to obtain the road network structure and correct the initial candidate nodes of the charging station according to the road network structure to obtain the corrected candidate nodes.

[0039] The candidate node optimization unit is used to optimize the corrected candidate nodes and calculate the comprehensive evaluation index. The node with the maximum value of the comprehensive evaluation index is the optimal node for the charging station layout.

[0040] Furthermore, the initial candidate nodes for the charging station are calculated through the following process:

[0041] 1) Obtain the regional power distribution network structure, line parameters, and historical loads;

[0042] 2) Based on the number and location of existing charging stations in the area, traffic flow, and current road network conditions, select a node as the initial node for the initial layout of the charging station;

[0043] 3) If the n neighboring nodes of the initial node are set as candidate nodes, then all nodes that are less than or equal to n from the initial node are candidate nodes.

[0044] 4) Calculate the weighted average of the historical loads of all candidate nodes to obtain a typical daily load curve;

[0045] 5) For each candidate node, the typical daily load curve is calculated sequentially at set time intervals to obtain the maximum load value sequence at each time point under the conditions of line non-overload and voltage over-limit.

[0046] 6) Take the minimum value of the sequence of maximum load values ​​of the line under the conditions of no overload and voltage over-limit at each time point as the node load limit;

[0047] 7) Repeat steps 5)-6) for all candidate nodes to obtain the load limit of each node; and sort all the load limits of all nodes in descending order, and use all the sorted nodes as the initial candidate nodes of the charging station.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] This invention obtains initial candidate nodes for charging stations based on the regional power distribution network structure, line parameters, and historical loads. After correction and optimization, the node with the highest comprehensive evaluation index is designated as the optimal node for charging station placement, thus realizing the planning of electric vehicle charging stations. This method takes into account power distribution network safety and economic operation, road network constraints, and fully considers the rationality of charging station locations.

[0050] Furthermore, this invention calculates the load limit of each candidate node in the distribution network through power flow calculation, sorts them according to their size to obtain an initial candidate node sequence, and corrects the initial candidate node sequence through a comprehensive evaluation index that takes into account the road network structure, safety and economy, to obtain the most ideal charging station layout location.

[0051] Furthermore, this method sets a variable n, the size of which reflects the charging station investor's acceptance of the charging station location. The value of n can be set according to the charging station investor's wishes, which also improves the applicability of this method to some extent. Attached Figure Description

[0052] Figure 1 This is a schematic diagram of the IEEE 33-node distribution network architecture. Detailed Implementation

[0053] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Preferred embodiments of the invention are shown in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a thorough and complete understanding of the disclosure of the invention.

[0054] The present invention provides a method for planning electric vehicle charging stations, comprising the following steps:

[0055] (1) Calculate the initial candidate nodes for charging stations based on the regional distribution network structure, line parameters, and historical loads. The specific steps are as follows:

[0056] 1) Obtain information such as the regional power distribution network structure, line parameters, and historical loads;

[0057] 2) Assuming that the number and location of existing charging stations in the area, traffic flow and the current road network are taken into account, a suitable node is selected as the initial location for the charging station;

[0058] 3) If we assume that all n neighboring nodes of the initial node can be candidate nodes, then all nodes that are less than or equal to n from the initial node are candidate nodes.

[0059] 4) The historical load of all candidate nodes is weighted and averaged to obtain a typical daily load curve.

[0060] 5) For each candidate node, power flow calculations are performed on the typical daily load curves at certain time intervals to obtain the maximum load value sequence at each time point under the conditions of line not being overloaded and voltage exceeding limits.

[0061] 6) Use the minimum value of the sequence as the load limit for that node.

[0062] 7) Repeat steps 5)-6) for all candidate nodes in sequence to obtain the load limit of each node. Sort all nodes in descending order of load limit and use them as the initial candidate nodes for the charging station.

[0063] (2) Obtain the road network structure and correct the initial candidate nodes of the charging station according to the road network structure to obtain the corrected candidate nodes.

[0064] Candidate nodes are scored based on their distance from existing charging stations in the road network, whether they are located at intersections of main urban roads, and their safe distance from densely populated areas, as detailed below:

[0065] 1) If the distance between the candidate node and the existing charging station is less than the set distance (determined according to the actual situation), this indicator will score 0 points; otherwise, it will score 1 point.

[0066] 2) If the intersection of the candidate node and the main urban road is less than the set distance (determined according to the actual situation), this indicator will score 0 points; otherwise, it will score 1 point.

[0067] 3) If the candidate node is less than the safe distance (determined according to the actual situation) from densely populated places such as hospitals, schools, bus stops, and subway entrances, this indicator will score 0 points; otherwise, it will score 1 point.

[0068] 4) Calculate the geographic space of the candidate nodes and eliminate nodes whose space does not meet the minimum construction requirements of the charging station.

[0069] 5) Calculate the scores. If a candidate node scores 0 points in any category, its total score is 0; if all four categories score 1, the candidate node scores 1. Remove the charging stations with scores of 0 to obtain the corrected candidate nodes.

[0070] (3) Optimize the corrected candidate nodes and calculate the comprehensive evaluation index. The node with the maximum value of the comprehensive evaluation index is the optimal node for the charging station layout.

[0071] 1) For candidate node i, calculate its distribution network line loss w″ at maximum load. i .

[0072] 2) Establish a charging station site selection model based on power grid security and economic operation of the distribution network, as detailed below:

[0073] a i =ζ1s i +ζ2w i

[0074] Among them, a i Let s be the comprehensive evaluation index for the i-th candidate node. i w is a capacity metric representing the security of the i-th candidate node. i Let ζ1 be the line loss index representing the economic efficiency of the i-th candidate node, and ζ2 be the weight of the safety index. To unify the dimensions of the two indices, they are normalized here.

[0075] The capacity metric representing the security of the i-th candidate node is calculated using the following formula:

[0076]

[0077] Among them, s′ i Let s be the load limit of the i-th candidate node calculated in the above steps. min s is the minimum of the load limits for all candidate nodes. max This is the maximum value of the load limit for all candidate nodes.

[0078] The line loss metric representing the economic viability of the i-th candidate node is calculated using the following formula:

[0079]

[0080] in, w min For all w′ i The minimum value, w max For all w′ i The maximum value.

[0081] The node with the maximum value of the comprehensive evaluation index 'a' is the optimal node for charging station placement, and the maximum capacity of the charging station at this node is s′. i .

[0082] Example 1

[0083] See Figure 1 Taking the IEEE 33-node distribution network architecture as an example, and referring to Table 1 for branch parameters, the present invention provides a planning method for electric vehicle charging stations, which includes the following steps:

[0084] (1) Calculate the initial candidate nodes for charging stations based on the regional distribution network structure, line parameters, and historical load.

[0085] 1) Collect information on the regional power distribution network structure, line parameters, historical loads, etc.;

[0086] 2) Assuming that the location and number of existing charging stations in the area, traffic flow and the current road network are taken into account, a suitable node is randomly selected as the initial location for the charging station;

[0087] 3) If the layout position can be selected from the n adjacent nodes of the initial node, then all nodes that are less than or equal to n from the initial node will be selected as candidate nodes.

[0088] The value of n represents the flexibility in selecting the location of the charging station, which can be changed according to actual needs.

[0089] If n = 3, then all nodes that are less than or equal to 3 from the initial node are selected as candidate nodes.

[0090] Assuming the initial node is 10, the candidate nodes are 7, 8, 9, 10, 11, 12 and 13.

[0091] 4) The historical load of all candidate nodes is weighted and averaged to obtain a typical daily load curve.

[0092] 5) For each candidate node, power flow calculations are performed on the load curves at various times on a typical day at certain time intervals to obtain the maximum load value that the node can withstand to ensure the safe operation of the distribution network at each time. Details are as follows:

[0093] Assuming there are 96 points throughout the day, select the load value of the first time step for a candidate node and perform the following steps:

[0094] a) Increase the load value by a certain increment Δp, where the initial Δp can be set to p. 峰 -p 谷 / 8, where p 峰 p represents the maximum value of the daily load curve. 谷 This represents the minimum value of the daily load curve.

[0095] b) Perform power flow calculations to determine if there are any line overloads or voltage overruns: if there are no line overloads or voltage overruns, proceed to step c); if there are line overloads or voltage overruns, proceed to step d).

[0096] c) Keep the increment constant, continue to increase the load value, and repeat step b);

[0097] d) Reduce the increment to half of the original value, i.e., Δp': if Δp' < 1 / 8 Δp, proceed to step e); if Δp' ≥ 1 / 8 Δp, increment the load value by the increment Δp', and repeat step b).

[0098] e) Record the maximum load value.

[0099] 6) Repeat steps a)-e) to perform power flow calculations for the other 95 time points, resulting in a total of 96 maximum load value sequences.

[0100] 7) The minimum value of the 96 maximum load value sequences is used as the load limit of the candidate node.

[0101] 8) Repeat steps 5)-7) for all candidate nodes in sequence to obtain the load limit of each candidate node. Sort all nodes in descending order of load limit and use them as the initial candidate nodes for the charging station.

[0102] Table 1 Branch parameters of IEEE 33-node distribution network architecture

[0103]

[0104] (2) The initial candidate nodes of the charging station are corrected according to the road network structure to obtain the corrected candidate nodes.

[0105] Candidate nodes are scored based on their distance from existing charging stations in the road network, whether they are located at intersections of main urban roads, and their safe distance from densely populated areas, as detailed below:

[0106] 1) If the distance between the candidate node and the existing charging station is less than the set distance, this indicator will score 0 points; otherwise, it will score 1 point.

[0107] 2) If the distance between the candidate node and the intersection of the main urban road is less than the set distance, this indicator will score 0 points; otherwise, it will score 1 point.

[0108] 3) If the candidate node is less than the safe distance from densely populated places such as hospitals, schools, bus stops, and subway entrances, this indicator will score 0 points; otherwise, it will score 1 point.

[0109] 4) Calculate the geographic space of the candidate nodes and eliminate nodes whose space does not meet the minimum construction requirements of the charging station.

[0110] 5) Calculate the scores. If a candidate node scores 0 points in any category, its total score is 0; if all four categories score 1, the candidate node scores 1. Remove the charging stations with scores of 0 to obtain the corrected candidate nodes.

[0111] (3) Optimize the candidate nodes after correction. The node with the maximum value of the comprehensive evaluation index is the optimal node for the charging station layout.

[0112] 1) For candidate node i, calculate its distribution network line loss w″ at maximum load. i .

[0113] 2) Establish a charging station site selection model based on power grid security and economic operation of the distribution network, as detailed below:

[0114] a i =ζ1s i +ζ2w i

[0115] Among them, a i Let s be the comprehensive evaluation index for the i-th candidate node. i w is a capacity metric representing the security of the i-th candidate node. i Let ζ1 be the line loss index representing the economic efficiency of the i-th candidate node, and ζ2 be the weight of the safety index. To unify the dimensions of the two indices, they are normalized here.

[0116] The capacity metric representing the security of the i-th candidate node is calculated using the following formula:

[0117]

[0118] Where s′ i Let s be the load limit of the i-th node calculated in the above steps. min s is the minimum of the load limits for all candidate nodes. max This is the maximum value of the load limit for all candidate nodes.

[0119] The line loss metric representing the economic viability of the i-th candidate node is calculated using the following formula:

[0120]

[0121] Among them, parameters w min For all w′ i Minimum value, w max For all w′ i The maximum value.

[0122] The node containing the maximum value of the comprehensive evaluation index 'a' is the optimal node for charging station placement, where the maximum power of the charging station at that node is s′. i .

[0123] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0124] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0125] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0126] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0127] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0128] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A planning method for electric vehicle charging stations, characterized in that, Includes the following steps: Obtain the regional power distribution network structure, line parameters, and historical loads, and calculate the initial candidate nodes for charging stations; Obtain the road network structure, and correct the initial candidate nodes of the charging station based on the road network structure to obtain the corrected candidate nodes; The candidate nodes are optimized after correction, and a comprehensive evaluation index is calculated. The node with the maximum value of the comprehensive evaluation index is the optimal node for the charging station layout. The initial candidate nodes for charging stations are modified based on the road network structure to obtain the modified candidate nodes. This also includes: calculating the geographical space where the candidate nodes are located and eliminating nodes whose space does not meet the minimum construction requirements for charging stations. The comprehensive evaluation index is calculated using the following formula: in, Let be the comprehensive evaluation index for the i-th candidate node. The capacity metric representing the security of the i-th candidate node. The line loss indicator represents the economic performance of the i-th candidate node. As the weight of security indicators, The weighting of economic indicators; The capacity metric representing the security of the i-th candidate node is calculated using the following formula: in, Let be the load limit for the i-th candidate node. The minimum value of the load limit for all candidate nodes. The maximum value of the load limit for all candidate nodes; The line loss metric representing the economic viability of the i-th candidate node is calculated using the following formula: Among them, parameters , The distribution network line loss is the maximum load of the i-th candidate node. For all parameters The minimum value, For all parameters The maximum value.

2. The planning method for electric vehicle charging stations according to claim 1, characterized in that, The initial candidate nodes for the charging station are calculated through the following process: 1) Obtain the regional distribution network structure, line parameters, and historical load; 2) Based on the number and location of existing charging stations in the area, traffic flow, and current road network conditions, select a node as the initial node for the initial layout of the charging station; 3) If the n neighboring nodes of the initial node are set as candidate nodes, then all nodes that are less than or equal to n from the initial node are candidate nodes. 4) Calculate the weighted average of the historical loads of all candidate nodes to obtain a typical daily load curve; 5) For each candidate node, power flow calculations are performed on the typical daily load curves at set time intervals to obtain the maximum load value sequence at each time point under the conditions of line non-overload and voltage over-limit. 6) Take the minimum value of the sequence of maximum load values ​​of the line under the conditions of no overload and voltage over-limit at each time point as the node load limit; 7) Repeat steps 5)-6) for all candidate nodes to obtain the load limit of each node; and sort all the load limits of all nodes in descending order, and use all the sorted nodes as the initial candidate nodes of the charging station.

3. The planning method for electric vehicle charging stations according to claim 2, characterized in that, The step of performing power flow calculations on typical daily load curves at set time intervals for each candidate node to obtain the maximum load value sequence for each time point under both unloaded and voltage over-limit conditions is as follows: The process includes the following steps: For each candidate node, power flow calculations are performed on the typical daily load curves at set time intervals to determine whether there are line overloads or voltage overruns; if there are no line overloads or voltage overruns, the load value is incremented and the power flow calculation is repeated; if there are line overloads or voltage overruns, the increment is reduced to half of the original value and the power flow calculation is repeated.

4. The planning method for electric vehicle charging stations according to claim 1, characterized in that, The initial candidate nodes for charging stations are revised based on the road network structure to obtain the revised candidate nodes. The process includes the following steps: scoring candidate nodes based on their distance from existing charging stations in the road network, whether they are located at intersections of main urban roads, and their safe distance from densely populated areas; and obtaining revised candidate nodes based on the scores.

5. The planning method for electric vehicle charging stations according to claim 4, characterized in that, The specific process for scoring the initial candidate nodes of the charging station is as follows: If the distance between the candidate node and the existing charging station is less than the set distance, this indicator will score 0 points; otherwise, it will score 1 point. If the distance between the candidate node and the intersection of the main urban road is less than the set distance, this indicator will score 0 points; otherwise, it will score 1 point. If the candidate node is less than the safe distance from a densely populated area, this indicator scores 0 points; otherwise, it scores 1 point.

6. The planning method for electric vehicle charging stations according to claim 5, characterized in that, The scoring process is as follows: if a candidate node scores 0 points in any item, the total score of the candidate node is 0; if all scores are 1, the candidate node scores 1; nodes with scores of 0 are removed to obtain the corrected candidate nodes.

7. A planning device for an electric vehicle charging station, characterized in that, include: The initial candidate node calculation unit for charging stations is used to obtain the regional power distribution network structure, line parameters and historical load, and to calculate the initial candidate nodes for charging stations. The candidate node correction unit is used to obtain the road network structure and correct the initial candidate nodes of the charging station according to the road network structure to obtain the corrected candidate nodes. The candidate node optimization unit is used to optimize the corrected candidate nodes and calculate the comprehensive evaluation index. The node with the maximum value of the comprehensive evaluation index is the optimal layout node of the charging station. The initial candidate nodes for charging stations are modified based on the road network structure to obtain the modified candidate nodes. This also includes: calculating the geographical space where the candidate nodes are located and eliminating nodes whose space does not meet the minimum construction requirements for charging stations. The comprehensive evaluation index is calculated using the following formula: in, Let be the comprehensive evaluation index for the i-th candidate node. The capacity metric representing the security of the i-th candidate node. The line loss indicator represents the economic performance of the i-th candidate node. As the weight of security indicators, The weighting of economic indicators; The capacity metric representing the security of the i-th candidate node is calculated using the following formula: in, Let be the load limit for the i-th candidate node. The minimum value of the load limit for all candidate nodes. The maximum value of the load limit for all candidate nodes; The line loss metric representing the economic viability of the i-th candidate node is calculated using the following formula: Among them, parameters , The distribution network line loss is the maximum load of the i-th candidate node. For all parameters The minimum value, For all parameters The maximum value.

8. The planning device for electric vehicle charging stations according to claim 7, characterized in that, The initial candidate nodes for the charging station are calculated through the following process: 1) Obtain the regional distribution network structure, line parameters, and historical load; 2) Based on the number and location of existing charging stations in the area, traffic flow, and current road network conditions, select a node as the initial node for the initial layout of the charging station; 3) If the n neighboring nodes of the initial node are set as candidate nodes, then all nodes that are less than or equal to n from the initial node are candidate nodes. 4) Calculate the weighted average of the historical loads of all candidate nodes to obtain a typical daily load curve; 5) For each candidate node, power flow calculations are performed on the typical daily load curves at set time intervals to obtain the maximum load value sequence at each time point under the conditions of line non-overload and voltage over-limit. 6) Take the minimum value of the sequence of maximum load values ​​of the line under the conditions of no overload and voltage over-limit at each time point as the node load limit; 7) Repeat steps 5)-6) for all candidate nodes to obtain the load limit of each node; and sort all the load limits of all nodes in descending order, and use all the sorted nodes as the initial candidate nodes of the charging station.

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