Charging station site selection method and device considering traffic and reversible energy storage characteristics of electric vehicles

Abstract

The invention discloses a charging station site selection method and device considering traffic and electric vehicle reversible energy storage characteristics, and belongs to the technical field of charging station planning. The method comprises the following steps: obtaining traffic topology data and historical electric vehicle travel data of a target area; determining a driving path, departure time, an initial charge state and parking duration of each path point of each preset electric vehicle; respectively calculating the actual chargeable and dischargeable time length of each preset electric vehicle at each approach point in each preset analysis time period; calculating the charging and discharging energy storage capacity of each parking place in each preset analysis time period based on the actual charging and discharging time length of each preset electric vehicle in each path point, and determining a candidate charging station site selection point of each preset analysis time period; and analyzing the candidate charging station site selection points in each preset analysis time period, and determining a plurality of candidate charging station site selection points with the highest occurrence frequency as final charging station site selection points. By implementing the charging station, the problem of low energy regulation capability of the charging station in the prior art can be solved.

Description

Technical Field

[0001] This invention relates to the field of charging station planning technology, and in particular to a method and apparatus for selecting charging station sites that takes into account the reversible energy storage characteristics of traffic and electric vehicles. Background Technology

[0002] With the widespread adoption of electric vehicles, the construction of charging infrastructure has become one of the key factors restricting their promotion and improving user experience. Currently, the development of vehicle-to-grid (V2G) technology has enabled electric vehicles to no longer be just load terminals, but to have the ability to interact with the grid bidirectionally, allowing them to feed energy back to the grid while parked, thereby improving grid flexibility and load regulation capabilities.

[0003] Current research and planning methods often rely on static population density or vehicle ownership to plan the layout of public charging stations in cities. This lacks in-depth analysis of actual traffic flow characteristics and vehicle dynamic behavior. The site selection of charging stations often fails to fully consider the electrical value of electric vehicles as mobile energy storage units, resulting in low utilization rates and weak energy regulation capabilities of some charging stations. Summary of the Invention

[0004] This invention provides a charging station site selection method and apparatus that takes into account the reversible energy storage characteristics of traffic and electric vehicles, which can solve the problem of low energy regulation capability of charging stations in the prior art.

[0005] To address the aforementioned technical problems, this invention provides a charging station site selection method that considers the reversible energy storage characteristics of traffic and electric vehicles, comprising: Acquire traffic topology data and historical electric vehicle travel data for the target area; wherein, the traffic topology data includes several parking locations; and the historical electric vehicle travel data includes flow data for each parking location. Based on the traffic topology data and the historical electric vehicle travel data, several preset electric vehicle travel routes are determined; wherein, the travel route includes a starting point, a destination point, and several waypoints; Based on the historical electric vehicle travel data, random sampling is performed to determine the departure time, initial state of charge, and parking duration at each route point for each preset electric vehicle. For each preset electric vehicle, based on the departure time, the initial state of charge, the preset charging and discharging power, the preset charging and discharging efficiency, the parking time at each way point, and the flow data, the actual chargeable and dischargeable time of the preset electric vehicle at each way point in each preset analysis period is calculated. For each preset analysis period, the charging and discharging energy storage capacity of each parking location is calculated based on the actual charging and discharging time of each preset electric vehicle at each route point. Candidate charging station locations for the preset analysis period are determined based on the charging and discharging energy storage capacity of each of the aforementioned parking locations. Analyze the candidate charging station locations during each preset analysis period, and determine the most frequently occurring candidate charging station locations as the final charging station locations.

[0006] As a preferred embodiment, the step of determining several preset electric vehicle travel routes based on the traffic topology data and the historical electric vehicle travel data includes: A travel probability matrix is ​​constructed based on the traffic topology data and the historical electric vehicle travel data; The origin and destination data of each preset electric vehicle are determined based on the travel probability matrix; Based on the traffic topology data and the origin and destination data of each preset electric vehicle, the driving path of each preset electric vehicle is determined using the shortest path method.

[0007] As a preferred embodiment, the calculation of the actual chargeable / dischargeable time of the preset electric vehicle at each route point within each preset analysis period, based on the departure time, the initial state of charge, the preset charging / discharging power, the preset charging / discharging efficiency, the parking time at each route point, and the flow data, includes: Based on the departure time, parking time at each waypoint, and traffic flow data, determine the available parking time for each preset electric vehicle at each waypoint during each preset analysis period. Based on the preset charging and discharging power, preset charging and discharging efficiency, and the initial state of charge, the maximum charging and discharging time of the preset electric vehicle at each path point is calculated; Based on the available parking time of the preset electric vehicle at each waypoint during each preset analysis period and the maximum charging and discharging time of the preset electric vehicle at each waypoint, the actual available charging and discharging time of the preset electric vehicle at each waypoint during each preset analysis period is determined.

[0008] As a preferred embodiment, determining the available parking time for each preset electric vehicle at each waypoint within each preset analysis period, based on the departure time, parking duration at each waypoint, and traffic flow data, includes: Based on the departure time and the flow data at each waypoint, the arrival time of the preset electric vehicle at each waypoint is calculated; Based on the parking time and arrival time at each waypoint, the available parking time of the preset electric vehicle at each waypoint is calculated during each preset analysis period.

[0009] As a preferred embodiment, the step of calculating the arrival time of the preset electric vehicle at each waypoint based on the departure time and traffic flow data at each waypoint includes: The travel time for each waypoint is determined based on the departure time. Based on the flow data and travel time at each waypoint, the road capacity, free-flow travel time and traffic volume of each segment in the travel path are determined. Based on the road capacity, free-flow travel time and traffic volume of each segment in the travel route, calculate the congestion-corrected travel time of each segment in the travel route; Based on the congestion correction time of each road segment in the driving route and the departure time, the arrival time of the preset electric vehicle at each waypoint is calculated respectively.

[0010] As a preferred embodiment, the step of calculating the maximum charging and discharging time of the preset electric vehicle at each path point based on the preset charging and discharging power, preset charging and discharging efficiency, and the initial state of charge includes: Based on the initial state of charge and the distance between the starting point of the preset electric vehicle and each way point, calculate the arrival state of charge of the preset electric vehicle at each way point; Based on the state of charge reached, the maximum energy range of charging and discharging of the preset electric vehicle at each path point is calculated; Based on the preset charging and discharging power, preset charging and discharging efficiency, and the preset maximum charging and discharging energy range of the electric vehicle at each path point, the maximum charging and discharging time of the electric vehicle at each path point is calculated.

[0011] As a preferred embodiment, determining the actual charge / discharge duration of the preset electric vehicle at each route point within each preset analysis period, based on the available parking time of the preset electric vehicle at each route point and the maximum charge / discharge duration of the preset electric vehicle at each route point, includes: The maximum charge / discharge duration includes the maximum charging duration and the maximum discharging duration; The minimum of the maximum charging time and the available parking time is determined as the actual available charging time; The minimum of the maximum discharge duration and the available parking duration is determined as the actual discharge duration; The actual chargeable and dischargeable duration is determined based on the actual chargeable duration and the actual dischargeable duration.

[0012] As a preferred embodiment, the calculation of the charging and discharging energy storage capacity at each parking location based on the actual charging and discharging time of each preset electric vehicle at each route point includes: For each parking location, the charging and discharging energy storage capacity is calculated based on the actual charging and discharging time, preset charging and discharging efficiency, and preset charging and discharging efficiency of each preset electric vehicle at each route point: In the formula, The charging energy storage capacity of parking location i during the preset analysis period t; The discharge energy storage capacity of parking location i during the preset analysis period t; The preset charging efficiency for the electric vehicle k; The preset discharge efficiency of electric vehicle k is given. The preset charging time for electric vehicle k at parking location i is the actual charging time. This is the preset actual discharge time of electric vehicle k at parking location i; Preset charge / discharge efficiency; This is the set of vehicles at parking location i during the preset analysis time period t.

[0013] As a preferred embodiment, determining the candidate charging station locations for the preset analysis period based on the charging and discharging energy storage capacity of each of the parking locations includes: For each preset analysis period, an optimization model is constructed based on the charging and discharging energy storage capacity of each parking location: In the formula, Aggregated charging energy storage capacity for charging station site selection; Aggregated discharge energy storage capacity for charging station site selection; Variance of vehicle distribution at charging station site selection points; , , These are the weighting factors.

[0014] Accordingly, the present invention provides a charging station site selection device that considers the reversible energy storage characteristics of traffic and electric vehicles, including: a data acquisition module, a route generation module, a travel characteristic sampling module, a duration calculation module, an energy storage capacity calculation module, a time-segmented site selection analysis module, and a site selection point determination module; The data acquisition module is used to acquire traffic topology data and historical electric vehicle travel data for the target area; wherein, the traffic topology data includes several parking locations; and the historical electric vehicle travel data includes flow data for each parking location. The route generation module is used to determine several preset electric vehicle driving routes based on the traffic topology data and the historical electric vehicle travel data; wherein, the driving route includes a starting point, a destination point and several waypoints; The travel feature sampling module is used to perform random sampling based on the historical electric vehicle travel data to determine the departure time, initial state of charge, and parking duration at each waypoint for each preset electric vehicle. The duration calculation module is used to calculate the actual chargeable and dischargeable duration of each preset electric vehicle at each preset analysis period based on the departure time, the initial state of charge, the preset charging and discharging power, the preset charging and discharging efficiency, the parking time at each way point, and the flow data. The energy storage capacity calculation module is used to calculate the charging and discharging energy storage capacity of each parking location based on the actual charging and discharging time of each preset electric vehicle at each route point for each preset analysis period. The time-segmented site selection analysis module is used to determine the candidate charging station site selection points for the preset analysis period based on the charging and discharging energy storage capacity of each parking location; The site selection module is used to analyze the candidate charging station site selection points in each preset analysis period, and determine the most frequent candidate charging station site selection points as the final charging station site selection points.

[0015] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: This invention provides a charging station site selection method that considers traffic and the reversible energy storage characteristics of electric vehicles. It acquires traffic topology data and historical electric vehicle travel data for a target area to determine the travel paths of each preset electric vehicle. Through random sampling, it determines the departure time, initial state of charge, and parking duration at each waypoint for each preset electric vehicle. For each preset electric vehicle, based on departure time, initial state of charge, preset charging / discharging power, preset charging / discharging efficiency, parking duration at each waypoint, and current flow data, it calculates the actual chargeable / discharging time at each waypoint within each preset analysis period. For each preset analysis period, it calculates the charging / discharging energy storage capacity at each parking location based on the actual chargeable / discharging time of each preset electric vehicle at each waypoint. Based on the charging / discharging energy storage capacity at each parking location, it determines candidate charging station sites for the preset analysis period. Finally, it analyzes the candidate charging station sites for each preset analysis period and determines the most frequently occurring candidate charging station sites as the final charging station sites. This invention analyzes the energy storage capacity of electric vehicles based on traffic data of the target area, thereby taking into account the reversible energy storage characteristics of electric vehicles when selecting charging station sites, and effectively improving the energy regulation capability of charging stations. Attached Figure Description

[0016] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1This is a flowchart illustrating an embodiment of the charging station site selection method that considers the reversible energy storage characteristics of traffic and electric vehicles provided by the present invention. Figure 2 This is a schematic diagram of one embodiment of the charging station site selection device that takes into account the reversible energy storage characteristics of traffic and electric vehicles provided by the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0020] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0021] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0022] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0023] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0024] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0025] See Figure 1 To address the problem of low energy regulation capability in existing charging stations, an embodiment of the present invention provides a charging station site selection method considering the reversible energy storage characteristics of traffic and electric vehicles. This method includes steps 101 to 107, each step being as follows: Step 101: Obtain traffic topology data and historical electric vehicle travel data for the target area; wherein, the traffic topology data includes several parking locations; and the historical electric vehicle travel data includes traffic flow data for each parking location.

[0026] In this embodiment of the invention, to consider actual traffic flow characteristics and vehicle dynamic behavior, traffic topology data and historical electric vehicle travel data of the target area are acquired when selecting charging station sites. The traffic topology data includes multiple parking locations within the target area, the road segments formed between these parking locations, and the corresponding distance data, road capacity, and free-flow travel time for each road segment. The historical electric vehicle travel data includes traffic flow data for each parking location, specifically the traffic volume of the road segments formed between these parking locations over multiple historical time periods, as well as the departure time, initial state of charge, and parking duration of each electric vehicle at each parking location.

[0027] Step 102: Based on the traffic topology data and the historical electric vehicle travel data, determine several preset electric vehicle travel routes; wherein the travel route includes a starting point, a destination point and several waypoints.

[0028] As a preferred embodiment, based on the traffic topology data and the historical electric vehicle travel data, several preset electric vehicle travel routes are determined, including: A travel probability matrix is ​​constructed based on the traffic topology data and the historical electric vehicle travel data; The origin and destination data of each preset electric vehicle are determined based on the travel probability matrix; Based on the traffic topology data and the origin and destination data of each preset electric vehicle, the driving path of each preset electric vehicle is determined using the shortest path method.

[0029] In this embodiment of the invention, after acquiring traffic topology data and historical electric vehicle travel data for the target area, a number of electric vehicles are pre-selected for charging station site selection analysis. First, a travel probability matrix is ​​constructed, which is an OD (Original Distance Occupation) travel probability matrix, based on the traffic flow between each pair of available parking locations. In the formula, For time period The probability matrix of travel within the area; For time period The probability of a trip from parking location i to parking location j; For time period Traffic flow from parking location i to parking location j.

[0030] Based on the constructed travel probability matrix, in each time period Within the system, random sampling is performed on the start and end points of each preset electric vehicle, i.e., the starting point and the destination point.

[0031] Based on the starting point and destination of each preset electric vehicle, multiple roads can be selected. Therefore, the path length of each road can be calculated according to the distance data between each available parking location in the traffic topology data, and the shortest path can be determined as the driving path of the preset electric vehicle. This driving path includes the starting point, destination, and multiple waypoints.

[0032] Step 103: Based on the historical electric vehicle travel data, random sampling is performed to determine the departure time, initial state of charge, and parking duration at each route point for each preset electric vehicle.

[0033] In this embodiment of the invention, based on historical electric vehicle travel data, the departure time, initial state of charge, and parking duration at each available parking location of each electric vehicle can be obtained. Probabilistic modeling is performed on these data to determine the departure time, initial state of charge, and parking duration at each route point of each preset electric vehicle through random sampling.

[0034] The departure time follows a Gaussian mixture distribution, i.e. : In the formula, Let be the probability density function of departure time; For departure time; This is an identifier for a Gaussian mixture distribution; and These are the means of the two Gaussian sub-distributions, respectively. and These are the standard deviations of the two Gaussian sub-distributions; and These are the weighting coefficients, satisfying... .

[0035] Parking duration follows a normal distribution: In the formula, for; This is an identifier for a normal distribution; This represents the average parking duration. This represents the variance of the parking duration.

[0036] The initial charging state follows a normal distribution: In the formula, These are the initial charged state variables; This is an identifier for a normal distribution; The mean of the initial state of charge; The variance of the initial charged state.

[0037] Step 104: For each preset electric vehicle, based on the departure time, the initial state of charge, the preset charging and discharging power, the preset charging and discharging efficiency, the parking time at each waypoint, and the flow data, calculate the actual chargeable and dischargeable time of the preset electric vehicle at each waypoint during each preset analysis period.

[0038] As a preferred embodiment, based on the departure time, the initial state of charge, the preset charging / discharging power, the preset charging / discharging efficiency, the parking time at each waypoint, and the flow data, the actual chargeable / discharging time of the preset electric vehicle at each waypoint within each preset analysis period is calculated, including: Based on the departure time, parking time at each waypoint, and traffic flow data, determine the available parking time for each preset electric vehicle at each waypoint during each preset analysis period. Based on the preset charging and discharging power, preset charging and discharging efficiency, and the initial state of charge, the maximum charging and discharging time of the preset electric vehicle at each path point is calculated; Based on the available parking time of the preset electric vehicle at each waypoint during each preset analysis period and the maximum charging and discharging time of the preset electric vehicle at each waypoint, the actual available charging and discharging time of the preset electric vehicle at each waypoint during each preset analysis period is determined.

[0039] As a preferred embodiment, based on the departure time, parking duration at each waypoint, and traffic flow data, the available parking duration of each preset electric vehicle at each waypoint during each preset analysis period is determined, including: Based on the departure time and the flow data at each waypoint, the arrival time of the preset electric vehicle at each waypoint is calculated; Based on the parking time and arrival time at each waypoint, the available parking time of the preset electric vehicle at each waypoint is calculated during each preset analysis period.

[0040] In this embodiment of the invention, after obtaining the departure time, initial state of charge, and parking duration at each waypoint of each preset electric vehicle through random sampling, in order to fully consider the electrical value of electric vehicles as mobile energy storage units, it is necessary to calculate the available parking duration of each preset electric vehicle at each waypoint within each preset analysis period. Specifically, firstly, based on the sampled departure time and flow data at each waypoint, the arrival time of the preset electric vehicle at each waypoint is calculated, and then the available parking duration at each waypoint is calculated in combination with the sampled parking duration.

[0041] As a preferred embodiment, the arrival time of the preset electric vehicle at each waypoint is calculated based on the departure time and the traffic flow data at each waypoint, including: The travel time for each waypoint is determined based on the departure time. Based on the flow data and travel time at each waypoint, the road capacity, free-flow travel time and traffic volume of each segment in the travel path are determined. Based on the road capacity, free-flow travel time and traffic volume of each segment in the travel route, calculate the congestion-corrected travel time of each segment in the travel route; Based on the congestion correction time of each road segment in the driving route and the departure time, the arrival time of the preset electric vehicle at each waypoint is calculated respectively.

[0042] In this embodiment of the invention, the arrival time of a preset electric vehicle at each waypoint is calculated. Specifically, the travel time t at each waypoint is first determined based on the departure time. Then, the corresponding road capacity, free-flow travel time, and traffic volume are obtained from the traffic flow data at each waypoint based on the travel time t. The congestion-corrected travel time for each road segment is then calculated. The departure time and the congestion-corrected travel time are added together to calculate the arrival time at each waypoint.

[0043] The formula for calculating congestion-corrected travel time is: In the formula, For road section Congestion-adjusted travel time during time period t; For road section The free-flow travel time is calculated from the road length and speed limit conditions; For road section Traffic flow during time period t; For road section Road capacity; and This is an empirical coefficient, and its value can be... ; From the waypoint to the waypoint The section of road.

[0044] The formula for calculating the arrival time of each waypoint is as follows: In the formula, Let the arrival time of electric vehicle k at the route point i be preset. The preset departure time for electric vehicle k; The preset driving path for electric vehicle k.

[0045] In this embodiment of the invention, after calculating the arrival time of the waypoints, and combining it with the sampled parking duration, the available parking duration of the preset electric vehicle in each preset analysis period can be determined: In the formula, The preset available parking time for electric vehicle k at route point i; Let i be the parking interval of electric vehicle k at the route point i. The preset parking duration for electric vehicle k; This is the preset analysis period.

[0046] This is equivalent to taking the intersection of the parking interval of the preset electric vehicle k at waypoint i and the preset analysis period, and determining the intersection as the available parking time of the preset electric vehicle within the preset analysis period. When the intersection is empty, it means that the preset electric vehicle does not participate in the V2G service at waypoint i during the preset analysis period.

[0047] As a preferred embodiment, the maximum charging and discharging time of the preset electric vehicle at each path point is calculated based on the preset charging and discharging power, preset charging and discharging efficiency, and the initial state of charge, including: Based on the initial state of charge and the distance between the starting point of the preset electric vehicle and each way point, calculate the arrival state of charge of the preset electric vehicle at each way point; Based on the state of charge reached, the maximum energy range of charging and discharging of the preset electric vehicle at each path point is calculated; Based on the preset charging and discharging power, preset charging and discharging efficiency, and the preset maximum charging and discharging energy range of the electric vehicle at each path point, the maximum charging and discharging time of the electric vehicle at each path point is calculated.

[0048] In this embodiment of the invention, based on the sampled initial state of charge and the preset charging / discharging power and preset charging / discharging efficiency, the maximum charging / discharging time of the preset electric vehicle at each path point can be calculated: First, calculate the distance between the starting point and the waypoint of the preset electric vehicle to obtain the cumulative mileage. Multiply the cumulative mileage by the preset energy consumption coefficient per unit mileage to calculate the cumulative energy consumption. Then, based on the cumulative energy consumption, the initial state of charge, and the electric vehicle's battery capacity, calculate the preset state of charge of the electric vehicle upon arrival at the waypoint. In the formula, The preset state of charge of electric vehicle k upon arrival at waypoint i is given. The initial state of charge of the preset electric vehicle k; The cumulative power consumption of electric vehicle k when it reaches route point i is preset; The battery capacity of the preset electric vehicle k is given.

[0049] Based on the calculated preset state of charge at the electric vehicle's arrival point, and the upper and lower limits of the battery's state of charge. and The maximum charge / discharge energy was further calculated: In the formula, The maximum charging energy of electric vehicle k at route point i is preset; Let the maximum discharge energy of electric vehicle k at the path point i be preset. This represents the upper limit of the battery's state of charge. This is the limit of the charged state.

[0050] Based on the preset charging and discharging power and preset charging and discharging efficiency, the maximum charging and discharging time of the electric vehicle at each route point is calculated: In the formula, The maximum discharge time of electric vehicle k at the path point i is preset; The maximum discharge time of electric vehicle k at the path point i is preset; Preset charging power; Preset discharge power; The preset charge / discharge efficiency.

[0051] As a preferred embodiment, the actual charge / discharge time of the preset electric vehicle at each route point within each preset analysis period is determined based on the available parking time of the preset electric vehicle at each route point and the maximum charge / discharge time of the preset electric vehicle at each route point, including: The maximum charge / discharge duration includes the maximum charging duration and the maximum discharging duration; The minimum of the maximum charging time and the available parking time is determined as the actual available charging time; The minimum of the maximum discharge duration and the available parking duration is determined as the actual discharge duration; The actual chargeable and dischargeable duration is determined based on the actual chargeable duration and the actual dischargeable duration.

[0052] In this embodiment of the invention, after calculating the maximum charging time and the maximum discharging time, they are compared with the available parking time to determine the actual chargeable and dischargeable time. In the formula, The preset is the actual charging time of electric vehicle k at route point i; Let k be the preset actual discharge time of electric vehicle k at point i.

[0053] Step 105: For each preset analysis period, calculate the charging and discharging energy storage capacity of each parking location based on the actual charging and discharging time of each preset electric vehicle at each route point.

[0054] As a preferred embodiment, the charging and discharging energy storage capacity of each parking location is calculated based on the actual charging and discharging time of each preset electric vehicle at each route point, including: For each parking location, the charging and discharging energy storage capacity is calculated based on the actual charging and discharging time, preset charging and discharging efficiency, and preset charging and discharging efficiency of each preset electric vehicle at each route point: In the formula, The charging energy storage capacity of parking location i during the preset analysis period t; The discharge energy storage capacity of parking location i during the preset analysis period t; The preset charging efficiency for the electric vehicle k; The preset discharge efficiency of electric vehicle k is given. The preset charging time for electric vehicle k at parking location i is the actual charging time. This is the preset actual discharge time of electric vehicle k at parking location i; Preset charge / discharge efficiency; This is the set of vehicles at parking location i during the preset analysis time period t.

[0055] In this embodiment of the invention, after calculating the relevant data of a preset electric vehicle for each route point, each available parking location is used as the analysis subject. During each preset analysis period, the charging and discharging energy storage capacity of the available parking locations is calculated to reflect the electrical value of the electric vehicle as a mobile energy storage unit. First, the set of vehicles corresponding to each available parking location within the preset analysis period is determined: This formula indicates that when the driving path of the preset electric vehicle k has a parking location i, and the parking interval of the preset electric vehicle k at parking location i has a non-empty intersection with the preset analysis time period t (i.e., If the preset electric vehicle k belongs to the set of vehicles at parking location i during the preset analysis time period t, then it is considered that the preset electric vehicle k belongs to the set of vehicles at parking location i during the preset analysis time period t.

[0056] By multiplying the actual charging time of each preset electric vehicle in the vehicle set by the preset charging efficiency and preset charge-discharge efficiency, the rechargeable energy value of each preset electric vehicle can be obtained. By summing the rechargeable energy values ​​of all preset electric vehicles in the vehicle set, the charging energy storage capacity of the parking location during a specific preset analysis period can be calculated. Similarly, by multiplying the actual discharging time of each preset electric vehicle in the vehicle set by the preset discharging efficiency and preset charge-discharge efficiency, the discharging energy value of each preset electric vehicle can be obtained. By summing the discharging energy values ​​of all preset electric vehicles in the vehicle set, the discharging energy storage capacity of the parking location during a specific preset analysis period can be calculated.

[0057] Step 106: Determine the candidate charging station locations for the preset analysis period based on the charging and discharging energy storage capacity of each parking location.

[0058] As a preferred embodiment, determining the candidate charging station locations for the preset analysis period based on the charging and discharging energy storage capacity of each parking location includes: For each preset analysis period, an optimization model is constructed based on the charging and discharging energy storage capacity of each parking location: In the formula, Aggregated charging energy storage capacity for charging station site selection; Aggregated discharge energy storage capacity for charging station site selection; Variance of vehicle distribution at charging station site selection points; , , These are the weighting factors, satisfying... .

[0059] In this embodiment of the invention, an optimization model is constructed for each preset analysis period, and several optimal parking locations are selected as candidate charging station sites with the objectives of maximizing the energy storage service capacity of candidate charging station sites (reflected by aggregated charging energy storage capacity and aggregated discharging energy storage capacity) and minimizing vehicle distribution variance.

[0060] Step 107: Analyze the candidate charging station locations in each preset analysis period, and determine the most frequent candidate charging station locations as the final charging station locations.

[0061] In this embodiment of the invention, after obtaining one or more candidate charging station locations corresponding to each preset analysis period, the frequency of occurrence of each candidate charging station location is calculated, and the candidate charging station locations with the highest frequency are determined as the final charging station locations. The number of final charging station locations can be considered predetermined.

[0062] Implementing the above embodiments has the following effects: This invention provides a charging station site selection method that considers traffic and the reversible energy storage characteristics of electric vehicles. It acquires traffic topology data and historical electric vehicle travel data for a target area to determine the travel paths of each preset electric vehicle. Through random sampling, it determines the departure time, initial state of charge, and parking duration at each waypoint for each preset electric vehicle. For each preset electric vehicle, based on departure time, initial state of charge, preset charging / discharging power, preset charging / discharging efficiency, parking duration at each waypoint, and current flow data, it calculates the actual chargeable / discharging time at each waypoint within each preset analysis period. For each preset analysis period, it calculates the charging / discharging energy storage capacity at each parking location based on the actual chargeable / discharging time of each preset electric vehicle at each waypoint. Based on the charging / discharging energy storage capacity at each parking location, it determines candidate charging station sites for the preset analysis period. Finally, it analyzes the candidate charging station sites for each preset analysis period and determines the most frequently occurring candidate charging station sites as the final charging station sites. This invention analyzes the energy storage capacity of electric vehicles based on traffic data of the target area, thereby taking into account the reversible energy storage characteristics of electric vehicles when selecting charging station sites, and effectively improving the energy regulation capability of charging stations.

[0063] like Figure 2As shown, based on the above method embodiments, corresponding apparatus embodiments are provided; One embodiment of the present invention provides a charging station site selection device that considers the reversible energy storage characteristics of traffic and electric vehicles, including: a data acquisition module, a route generation module, a travel characteristic sampling module, a duration calculation module, an energy storage capacity calculation module, a time-segmented site selection analysis module, and a site selection point determination module; The data acquisition module is used to acquire traffic topology data and historical electric vehicle travel data for the target area; wherein, the traffic topology data includes several parking locations; and the historical electric vehicle travel data includes flow data for each parking location. The route generation module is used to determine several preset electric vehicle driving routes based on the traffic topology data and the historical electric vehicle travel data; wherein, the driving route includes a starting point, a destination point and several waypoints; The travel feature sampling module is used to perform random sampling based on the historical electric vehicle travel data to determine the departure time, initial state of charge, and parking duration at each waypoint for each preset electric vehicle. The duration calculation module is used to calculate the actual chargeable and dischargeable duration of each preset electric vehicle at each preset analysis period based on the departure time, the initial state of charge, the preset charging and discharging power, the preset charging and discharging efficiency, the parking time at each way point, and the flow data. The energy storage capacity calculation module is used to calculate the charging and discharging energy storage capacity of each parking location based on the actual charging and discharging time of each preset electric vehicle at each route point for each preset analysis period. The time-segmented site selection analysis module is used to determine the candidate charging station site selection points for the preset analysis period based on the charging and discharging energy storage capacity of each parking location; The site selection module is used to analyze the candidate charging station site selection points in each preset analysis period, and determine the most frequent candidate charging station site selection points as the final charging station site selection points.

[0064] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can realize the charging station site selection method that takes into account the reversible energy storage characteristics of traffic and electric vehicles provided by any of the above-described method embodiments of the present invention.

[0065] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0066] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for selecting charging station locations considering the reversible energy storage characteristics of traffic and electric vehicles, characterized in that, include: Acquire traffic topology data and historical electric vehicle travel data for the target area; wherein, the traffic topology data includes several parking locations; and the historical electric vehicle travel data includes flow data for each parking location. Based on the traffic topology data and the historical electric vehicle travel data, several preset electric vehicle travel routes are determined; wherein, the travel route includes a starting point, a destination point, and several waypoints; Based on the historical electric vehicle travel data, random sampling is performed to determine the departure time, initial state of charge, and parking duration at each route point for each preset electric vehicle. For each preset electric vehicle, based on the departure time, the initial state of charge, the preset charging and discharging power, the preset charging and discharging efficiency, the parking time at each way point, and the flow data, the actual chargeable and dischargeable time of the preset electric vehicle at each way point in each preset analysis period is calculated. For each preset analysis period, the charging and discharging energy storage capacity of each parking location is calculated based on the actual charging and discharging time of each preset electric vehicle at each route point. Candidate charging station locations for the preset analysis period are determined based on the charging and discharging energy storage capacity of each of the aforementioned parking locations. Analyze the candidate charging station locations during each preset analysis period, and determine the most frequently occurring candidate charging station locations as the final charging station locations.

2. The charging station site selection method considering the reversible energy storage characteristics of traffic and electric vehicles according to claim 1, characterized in that, Based on the traffic topology data and the historical electric vehicle travel data, several preset electric vehicle travel routes are determined, including: A travel probability matrix is ​​constructed based on the traffic topology data and the historical electric vehicle travel data; The origin and destination data of each preset electric vehicle are determined based on the travel probability matrix; Based on the traffic topology data and the origin and destination data of each preset electric vehicle, the driving path of each preset electric vehicle is determined using the shortest path method.

3. The charging station site selection method considering the reversible energy storage characteristics of traffic and electric vehicles according to claim 1, characterized in that, The calculation of the actual chargeable and dischargeable time of the preset electric vehicle at each waypoint within each preset analysis period, based on the departure time, initial state of charge, preset charging and discharging power, preset charging and discharging efficiency, parking time at each waypoint, and traffic flow data, includes: Based on the departure time, parking time at each waypoint, and traffic flow data, determine the available parking time for each preset electric vehicle at each waypoint during each preset analysis period. Based on the preset charging and discharging power, preset charging and discharging efficiency, and the initial state of charge, the maximum charging and discharging time of the preset electric vehicle at each path point is calculated. Based on the available parking time of the preset electric vehicle at each waypoint during each preset analysis period and the maximum charging and discharging time of the preset electric vehicle at each waypoint, the actual available charging and discharging time of the preset electric vehicle at each waypoint during each preset analysis period is determined.

4. The charging station site selection method considering the reversible energy storage characteristics of traffic and electric vehicles according to claim 3, characterized in that, The determination of the available parking time for each preset electric vehicle at each waypoint within each preset analysis period, based on the departure time, parking duration at each waypoint, and traffic flow data, includes: Based on the departure time and the flow data at each waypoint, the arrival time of the preset electric vehicle at each waypoint is calculated; Based on the parking time and arrival time at each waypoint, the available parking time of the preset electric vehicle at each waypoint is calculated during each preset analysis period.

5. The charging station site selection method considering the reversible energy storage characteristics of traffic and electric vehicles according to claim 4, characterized in that, The calculation of the arrival time of the preset electric vehicle at each waypoint based on the departure time and the flow data at each waypoint includes: The travel time for each waypoint is determined based on the departure time. Based on the flow data and travel time at each waypoint, the road capacity, free-flow travel time and traffic volume of each segment in the travel path are determined. Based on the road capacity, free-flow travel time and traffic volume of each segment in the travel route, calculate the congestion-corrected travel time of each segment in the travel route; Based on the congestion correction time of each road segment in the driving route and the departure time, the arrival time of the preset electric vehicle at each waypoint is calculated respectively.

6. The charging station site selection method considering the reversible energy storage characteristics of traffic and electric vehicles according to claim 3, characterized in that, The step of calculating the maximum charging and discharging time of the preset electric vehicle at each path point based on the preset charging and discharging power, preset charging and discharging efficiency, and the initial state of charge includes: Based on the initial state of charge and the distance between the starting point of the preset electric vehicle and each way point, calculate the arrival state of charge of the preset electric vehicle at each way point; Based on the state of charge reached, the maximum energy range of charging and discharging of the preset electric vehicle at each path point is calculated; Based on the preset charging and discharging power, preset charging and discharging efficiency, and the preset maximum charging and discharging energy range of the electric vehicle at each path point, the maximum charging and discharging time of the electric vehicle at each path point is calculated.

7. The charging station site selection method considering the reversible energy storage characteristics of traffic and electric vehicles according to claim 3, characterized in that, The step of determining the actual charge / discharge duration of the preset electric vehicle at each route point within each preset analysis period, based on the available parking time of the preset electric vehicle at each route point and the maximum charge / discharge duration of the preset electric vehicle at each route point, includes: The maximum charge / discharge duration includes the maximum charging duration and the maximum discharging duration; The minimum of the maximum charging time and the available parking time is determined as the actual available charging time; The minimum of the maximum discharge duration and the available parking duration is determined as the actual discharge duration; The actual chargeable and dischargeable duration is determined based on the actual chargeable duration and the actual dischargeable duration.

8. The charging station site selection method considering the reversible energy storage characteristics of traffic and electric vehicles according to claim 1, characterized in that, The calculation of the charging and discharging energy storage capacity at each parking location based on the actual charging and discharging time of each preset electric vehicle at each route point includes: For each parking location, the charging and discharging energy storage capacity is calculated based on the actual charging and discharging time, preset charging and discharging efficiency, and preset charging and discharging efficiency of each preset electric vehicle at each route point: In the formula, The charging energy storage capacity of parking location i during the preset analysis period t; The discharge energy storage capacity of parking location i during the preset analysis period t; The preset charging efficiency for the electric vehicle k; The preset discharge efficiency of electric vehicle k is given. The preset charging time for electric vehicle k at parking location i is the actual charging time. This is the preset actual discharge time of electric vehicle k at parking location i; Preset charge / discharge efficiency; This is the set of vehicles at parking location i during the preset analysis time period t.

9. The charging station site selection method considering the reversible energy storage characteristics of traffic and electric vehicles according to claim 1, characterized in that, The process of determining candidate charging station locations for the preset analysis period based on the charging and discharging energy storage capacity of each of the parking locations includes: For each preset analysis period, an optimization model is constructed based on the charging and discharging energy storage capacity of each parking location: In the formula, Aggregated charging energy storage capacity for charging station site selection; Aggregated discharge energy storage capacity for charging station site selection; Variance of vehicle distribution at charging station site selection points; , , These are the weighting factors.

10. A charging station site selection device considering the reversible energy storage characteristics of traffic and electric vehicles, characterized in that, include: The system includes a data acquisition module, a route generation module, a travel characteristic sampling module, a duration calculation module, an energy storage capacity calculation module, a time-segmented site selection analysis module, and a site selection point determination module. The data acquisition module is used to acquire traffic topology data and historical electric vehicle travel data for the target area; wherein, the traffic topology data includes several parking locations; and the historical electric vehicle travel data includes flow data for each parking location. The route generation module is used to determine several preset electric vehicle driving routes based on the traffic topology data and the historical electric vehicle travel data; wherein, the driving route includes a starting point, a destination point and several waypoints; The travel feature sampling module is used to perform random sampling based on the historical electric vehicle travel data to determine the departure time, initial state of charge, and parking duration at each waypoint for each preset electric vehicle. The duration calculation module is used to calculate the actual chargeable and dischargeable duration of each preset electric vehicle at each preset analysis period based on the departure time, the initial state of charge, the preset charging and discharging power, the preset charging and discharging efficiency, the parking time at each way point, and the flow data. The energy storage capacity calculation module is used to calculate the charging and discharging energy storage capacity of each parking location based on the actual charging and discharging time of each preset electric vehicle at each route point for each preset analysis period. The time-segmented site selection analysis module is used to determine the candidate charging station site selection points for the preset analysis period based on the charging and discharging energy storage capacity of each parking location; The site selection module is used to analyze the candidate charging station site selection points in each preset analysis period, and determine the most frequent candidate charging station site selection points as the final charging station site selection points.

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