Electric vehicle charging station economic benefit evaluation model and method fused with time sequence analysis

Abstract

The invention relates to the technical field of data processing, in particular to an electric vehicle charging station economic benefit evaluation model and method fused with time sequence analysis, and the method comprises the steps: dividing all users in a charging station into resident users and mobile users based on the possibility of resident users; obtaining an electricity price ratio correction factor of the charging station according to the difference between the charging amount and the charging cost between the mobile users and the resident users in the charging station and the regional competitiveness of the charging station; the change trend of the mobile users is corrected through the electricity price ratio correction factor, and the corrected change trend of the mobile users in the charging station is obtained; a user overall change trend of the charging station is obtained by combining a corrected mobile user change trend and a resident user change trend in the charging station; and performing economic benefit evaluation on the charging station based on the user overall change trend of the charging station. The accuracy of the economic benefit evaluation model of the charging station is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an economic benefit evaluation model and method for an electric vehicle charging station integrating time series analysis. Background Art

[0002] With the large-scale use of electric vehicles, charging stations have begun to be laid out in large numbers across the country. However, as the number of charging stations increases, market competition becomes more intense. Factors such as price, service and location of different charging stations directly affect their economic benefits. Time series analysis is an important way to evaluate the economic benefits of electric vehicle charging stations. By summarizing the collected charging data according to a certain time period, characteristic variables such as charging amount, charging time, charging frequency, etc. are extracted, and then combined with the construction cost, investment benefit, charging standard and other aspects of the charging station, an economic benefit evaluation model is constructed. However, when analyzing time series data, this method will consider the time series characteristics of the charging station itself more, but does not combine the time series characteristics of the users, that is, it does not distinguish between mobile users and resident users, and the charging habits of resident users are not considered. As a result, due to the high instability of mobile users, the economic benefit evaluation model obtained is prone to fluctuations, and the economic benefit evaluation model of the charging station is inaccurate. Summary of the invention

[0003] In order to solve the above problems, the present invention provides an economic benefit evaluation model and method for electric vehicle charging stations integrating time series analysis.

[0004] An embodiment of the present invention provides an economic benefit evaluation method for electric vehicle charging stations integrating time series analysis, the method comprising the following steps: Obtain the charging time, charging duration, charging amount and charging cost of each user at each charging station in each quarter of the urban area in the past year, as well as the distance between all charging stations in the urban area; By analyzing the periodic distribution of the user's charging time, charging duration and charging amount in the charging station, the possibility of the user being a resident user in each charging station is obtained; based on the possibility of being a resident user, all users in the charging station are divided into resident users and mobile users; Obtain all reference charging stations of the charging station; obtain the charging frequency of resident users of the reference charging station of the charging station according to the number of charging frequencies of resident users in the charging station at its reference charging station; screen all reference charging stations of the charging station based on the charging frequency of resident users to obtain the influencing charging station of the charging station; obtain the degree of influence between the charging station and the charging station it influences according to the difference in the possibility of being resident users between the charging station and the charging station it influences; obtain the regional competitiveness of the charging station according to the distance and degree of influence between the charging station and the charging station it influences; obtain the electricity price ratio correction factor of the charging station according to the difference in charging volume and charging cost between mobile users and resident users in the charging station and the regional competitiveness of the charging station; obtain the mobile user change trend and the resident user change trend in the charging station according to the change in charging volume and charging cost of mobile users and resident users in the charging station; correct the mobile user change trend by the electricity price ratio correction factor to obtain the corrected mobile user change trend in the charging station; combine the corrected mobile user change trend and the resident user change trend in the charging station to obtain the overall user change trend of the charging station; The economic benefits of charging stations are evaluated based on the overall changing trend of charging station users.

[0005] Preferably, the possibility of a user being a resident user in each charging station is obtained by analyzing the periodic distribution of the user's charging time, charging duration, and charging amount in the charging station, including the specific method of: For urban areas User in In each charging station, a three-dimensional coordinate system is constructed with the charging time as the X-axis, the charging time as the Y-axis and the charging amount as the Z-axis. Next quarter User in All charging times, charging durations and charging amounts in the charging station are input into the three-dimensional coordinate system to obtain the Next quarter User in Several charging data points in a charging station; No. In the next quarter, for User in Charging station charging data point, The charging data point and The absolute value of the difference in charging time between the charging data points is recorded as The charging time interval of each charging data point; The charging data point and The absolute value of the difference in charging time between the charging data points is recorded as The charging time difference value of the charging data point; The charging data point and The absolute value of the difference in charge capacity between the charging data points is recorded as The difference in charge capacity of each charging data point; The first Next quarter User in The reciprocal of the mean of the charging time intervals of all charging data points in the charging station is taken as Next quarter User in The frequency of charging cycles in each charging station; No. Next quarter, the User in The variance of the charging time difference values ​​of all charging data points in the charging station is User in The sum of the variances of the charging amount difference values ​​of all charging data points in the charging station is recorded as the first sum value; User in The product of the variance of the charging time intervals of all charging data points in the charging station and the first sum is recorded as the first product; User in The normalized value of the ratio between the charging cycle frequency in the first charging station and the first product is used as the Next quarter User in The possibility of permanent users in a charging station.

[0006] Preferably, the method of obtaining the charging frequency of the resident users of the reference charging station of the charging station according to the number of charging frequencies of the resident users of the charging station at the reference charging station includes the following specific methods: For Any reference charging station of charging stations, in the Next quarter, the The number of all charging times of all resident users in the reference charging station is recorded as a first number; the first number is added to the The ratio of the total number of charging times of all resident users in the charging station in all reference charging stations is used as the Next quarter The charging frequency of the resident users of the reference charging station is determined based on the charging frequency of the resident users of the reference charging station.

[0007] Preferably, the method of obtaining the influence degree between the charging station and the charging stations it affects based on the difference in the possibility that the charging station and the charging stations it affects are permanent users includes the following specific methods: Preset a possible parameter , for the Any resident user at a charging station In the next quarter, if the resident user Charging station The possibility of permanent users in the charging station is not , record the resident user as the target resident user; record all the target resident users in the first The average probability of the charging station belonging to the resident user is the same as the average probability of all the target resident users in the Charging station The inverse of the absolute value of the difference between the means of the factors that affect the probability of being a resident user in the charging station is taken as the Next quarter A charging station and its The degree of influence between charging stations.

[0008] Preferably, the method of obtaining the regional competitiveness of a charging station according to the distance between the charging station and the degree of influence of the charging station and its affected charging stations includes the following specific methods: The first The charging station and Charging station The distance between the charging stations is recorded as the first distance; Next quarter A charging station and its The ratio of the impact degree between the first charging stations to the first distance is recorded as factors that affect the competition of charging stations; The normalized value of the mean of all competitive factors affecting the charging station is taken as the Next quarter Regional competitiveness of charging stations.

[0009] Preferably, the method of obtaining the electricity price ratio correction factor of the charging station according to the difference in charging amount and charging cost between mobile users and resident users in the charging station and the regional competitiveness of the charging station includes the following specific methods: No. Next quarter, the The average of all charging times of all permanent users in the charging station is The average of all charging costs of all permanent users in the charging station is recorded as Next quarter The electricity price ratio of the permanent users in the charging station; The average of all charging times of all mobile users in the charging station is The average of all charging costs of all mobile users in the charging station is recorded as Next quarter The electricity price ratio of mobile users in the charging station; Next quarter The price ratio of mobile users in the charging station is Charging station No. The product of the regional competitiveness in the first quarter is recorded as the mobile attraction electricity price ratio; Next quarter The absolute value of the difference between the electricity price ratio of resident users and the mobile attraction electricity price ratio in the charging station is taken as the Next quarter The electricity price ratio correction factor for each charging station.

[0010] Preferably, the method of obtaining the changing trend of mobile users and resident users in the charging station according to the changing situation of the charging amount and charging cost of mobile users and resident users in the charging station includes the following specific methods: A three-dimensional coordinate system is constructed with the charging time as the X-axis, the charging amount as the Y-axis and the charging cost as the Z-axis. Next quarter The charging time series data sequence of all permanent users in the charging station is input into the three-dimensional coordinate system to obtain the Next quarter Several resident user charging data points of a charging station; Next quarter The charging time series data of all mobile users in the charging station are input into the three-dimensional coordinate system to obtain the Next quarter Several charging data points of mobile users at a charging station; use the least squares method to Next quarter The curve fitting is performed on all the charging data points of the permanent users and all the charging data points of the mobile users of the charging station to obtain the Next quarter The charging curve of the resident users of the charging station and the Next quarter The charging curve of mobile users at the charging station; Next quarter The average slope of all resident user charging data points in the resident user charging curve of the charging station is taken as the Next quarter The trend of permanent users of charging stations; Next quarter The average slope of all mobile user charging data points in the mobile user charging curve of the charging station is taken as Next quarter The changing trend of mobile users of charging stations.

[0011] Preferably, the method of correcting the mobile user change trend by the electricity price ratio correction factor to obtain the corrected mobile user change trend in the charging station includes the following specific methods: The first Next quarter The number of all mobile users in the charging station is Next quarter The ratio of the total number of users in the charging station is recorded as the proportion of mobile users; Next quarter The number of all mobile users in the charging station is Next quarter The product of the price ratio correction factors of the charging stations is recorded as the correction confidence factor; the normalized value of the product of the proportion of mobile users and the correction confidence factor is recorded as the confidence level of the trend correction; Next quarter The product of the mobile user change trend of the charging station and the confidence of the change trend correction is taken as the Next quarter Modified mobile user trends of charging stations.

[0012] Preferably, the method of combining the modified mobile user change trend and the resident user change trend in the charging station to obtain the overall user change trend of the charging station includes the following specific methods: The first Next quarter The number of all permanent users in the charging station is Next quarter The ratio of the total number of all users in the charging station is recorded as the resident user ratio; the resident user ratio is divided by the Next quarter The product of the change trend of permanent users of each charging station is recorded as the permanent change product; the proportion of mobile users is Next quarter The product of the modified mobile user change trend of the charging station is recorded as the mobile change product; the normalized value of the sum of the permanent change product and the mobile change product is taken as the Next quarter The overall trend of users of charging stations.

[0013] The present invention also proposes an economic benefit evaluation model for electric vehicle charging stations that integrates timing analysis, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any step of the economic benefit evaluation method for electric vehicle charging stations that integrates timing analysis.

[0014] The beneficial effects of the technical solution of the present invention are as follows: the present invention obtains the possibility that a user is a resident user in each charging station by analyzing the periodic distribution of the user's charging time, charging duration and charging amount in the charging station; divides all users in the charging station into resident users and mobile users based on the possibility of being resident users; thereby distinguishing mobile users from resident users in the charging station, which facilitates feature extraction of the user's charging data; obtains the electricity price ratio correction factor of the charging station according to the differences in charging amount and charging costs between mobile users and resident users in the charging station, as well as the regional competitiveness of the charging station; corrects the changing trend of mobile users by the electricity price ratio correction factor to obtain a corrected changing trend of mobile users in the charging station; combines the corrected changing trend of mobile users and the changing trend of resident users in the charging station to obtain the overall changing trend of users in the charging station; evaluates the economic benefits of the charging station based on the overall changing trend of users in the charging station; thereby, quantifying the instability of mobile users in the time series data analysis process, and improving the accuracy of the economic benefit evaluation model of the charging station. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 A flowchart of the steps of the economic benefit evaluation method of an electric vehicle charging station integrating timing analysis according to the present invention; Figure 2 The present invention is a characteristic relationship flow chart of the economic benefit evaluation method of electric vehicle charging stations integrated with time series analysis. DETAILED DESCRIPTION

[0017] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the economic benefit evaluation model and method of electric vehicle charging stations integrated with timing analysis proposed by the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments, as well as its specific implementation, structure, features and effects. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0018] Unless defined otherwise, 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 invention belongs.

[0019] The specific scheme of the economic benefit evaluation model and method of electric vehicle charging station integrating timing analysis provided by the present invention is described in detail below with reference to the accompanying drawings.

[0020] See also Figure 1 , which shows a flowchart of a method for evaluating the economic benefits of an electric vehicle charging station by integrating timing analysis according to an embodiment of the present invention, the method comprising the following steps: Step S001: Obtain the charging time, charging duration, charging amount and charging fee of each user at each charging station in each quarter in the urban area in the past year, as well as the distances between all charging stations in the urban area.

[0021] It should be noted that due to the popularity of electric vehicles in the current market, electric vehicle charging stations are also popular in major shopping malls, parking lots, and industrial parks in cities, so electric vehicle owners have a lot of choices when choosing charging stations; at the same time, due to the different energy consumption of electric vehicles in different seasons, most users have extremely high mobility when choosing charging stations; Therefore, when evaluating the economic benefits of a charging station, if we only focus on the operating data of the charging station itself, we can only obtain a relatively vague analysis result, and the analysis result is greatly affected by the data quality. The users of a charging station can be roughly divided into two types, namely resident users and mobile users. Resident users have higher loyalty, and by analyzing their charging data, we can obtain relatively stable long-term profit data, while mobile users can obtain more short-term profit data, reflecting the market situation of charging stations in the area. By combining the charging data characteristics of different types of users, we can obtain the upper and lower limits of the economic benefits of the charging station, which can help managers better formulate pricing strategies and improve the economic benefits of charging stations.

[0022] Specifically, it is necessary to first collect the charging time, charging duration, charging amount and charging cost of each user at each charging station in each quarter of the urban area in the past year, as well as the distance between all charging stations in the urban area. The specific process is as follows: For any charging station in the urban area, the corresponding application of the charging station and the built-in data of all charging piles in the charging station are used to collect the charging time, charging duration, charging amount and charging fee of each user at each charging station in each quarter in the past year; and the distance between all charging stations in the urban area is collected.

[0023] So far, the above method is used to obtain the charging time, charging duration, charging amount and charging fee of each user at each charging station in each quarter in the urban area in the latest year, as well as the distances between all charging stations in the urban area.

[0024] Step S002: By analyzing the periodic distribution of the user's charging time, charging duration and charging amount in the charging station, the possibility of the user being a resident user in each charging station is obtained; based on the possibility of being a resident user, all users in the charging station are divided into resident users and mobile users.

[0025] It should be noted that when electric car owners choose a charging station, they usually take the location and price of the charging station into comprehensive consideration. Therefore, the users of the charging station can be roughly divided into two types, namely resident users and mobile users. Resident users are usually local residents or electric car users who work in the area for a long time, and usually have a high frequency of use in the charging station, while mobile users may be electric car owners passing by or staying in the area for a short period of time, and have a low frequency of use in the charging station.

[0026] Preferably, in some implementations of the embodiments of the present invention, by analyzing the periodic distribution of charging time, charging duration and charging amount of each user in the charging station in each quarter, a specific method for obtaining the possibility that each user is a resident user in each charging station in each quarter is: For urban areas User in In each charging station, a three-dimensional coordinate system is constructed with the charging time as the X-axis, the charging time as the Y-axis and the charging amount as the Z-axis. Next quarter User in All charging times, charging durations and charging amounts in the charging station are input into the three-dimensional coordinate system to obtain the Next quarter User in Several charging data points in a charging station; No. In the next quarter, for User in Charging station charging data point, The charging data point and The absolute value of the difference in charging time between the charging data points is recorded as The charging time interval of each charging data point; The charging data point and The absolute value of the difference in charging time between the charging data points is recorded as The charging time difference value of the charging data point; The charging data point and The absolute value of the difference in charge capacity between the charging data points is recorded as The difference in charge capacity of each charging data point; The first Next quarter User in The reciprocal of the mean of the charging time intervals of all charging data points in the charging station is taken as Next quarter User in The frequency of charging cycles in each charging station; No. Next quarter, the User in The variance of the charging time difference values ​​of all charging data points in the charging station is User in The sum of the variances of the charging amount difference values ​​of all charging data points in the charging station is recorded as the first sum value; User in The product of the variance of the charging time intervals of all charging data points in the charging station and the first sum is recorded as the first product; User in The normalized value of the ratio between the charging cycle frequency in the first charging station and the first product is used as the Next quarter User in The possibility of resident users in the charging stations; The specific formula is: In the formula, Indicates Next quarter User in The possibility of resident users in the charging stations; Indicates Next quarter User in The frequency of charging cycles in each charging station; Indicates Next quarter User in The variance of the charging time intervals of all charging data points in a charging station; Indicates Next quarter User in The variance of the charging capacity difference values ​​of all charging data points in a charging station; Indicates Next quarter User in The variance of the charging time difference values ​​of all charging data points in a charging station; Represents the preset hyperparameters. This implementation presets , used to prevent the denominator from being 0; represents the linear normalization function.

[0027] It should be noted that the smaller the variance of the time interval, charging time difference and charging amount difference between all adjacent charging data points, the smaller the variance of the charging time difference and charging amount difference between all adjacent charging data points. The stronger the periodicity of the data in the charging time series data of a user in all quarters, the The more similar the charging time and the charging amount, the greater the possibility that the user is a resident user; for resident users, their charging cycles are usually relatively fixed, and the power consumption and charging time of each charging are relatively fixed. Therefore, when the user has a certain charging cycle and the charging amount and charging time of each charging are more similar, the possibility that the user is a resident user is greater.

[0028] Preferably, in some implementations of the embodiments of the present invention, the specific method for dividing all users in each charging station in each quarter into resident users and mobile users based on the possibility of being resident users is: Preset a partition parameter , wherein this embodiment is based on This example is described as an example, and this embodiment is not specifically limited. Depends on the specific implementation situation; For urban areas User, if Next quarter User in The probability that the charging stations belong to permanent users is greater than the partition parameter , will The user is recorded as Next quarter If the resident user is in a charging station Next quarter User in The probability that the charging stations belong to permanent users is less than or equal to the partition parameter , will The user is recorded as Next quarter Mobile users at a charging station.

[0029] So far, the resident users and floating users in each power station in each quarter are obtained through the above method.

[0030] Step S003: Obtain all reference charging stations of the charging station; obtain the charging frequency of resident users of the reference charging station of the charging station according to the number of charging frequencies of resident users in the charging station at its reference charging station; screen all reference charging stations of the charging station based on the charging frequency of resident users to obtain the influencing charging station of the charging station; obtain the degree of influence between the charging station and the charging station it influences according to the difference in the possibility of being resident users between the charging station and the charging station it influences; obtain the regional competitiveness of the charging station according to the distance and degree of influence between the charging station and the charging station it influences; obtain the electricity price ratio correction factor of the charging station according to the difference in charging amount and charging cost between mobile users and resident users in the charging station and the regional competitiveness of the charging station; obtain the mobile user change trend and the resident user change trend in the charging station according to the change in charging amount and charging cost of mobile users and resident users in the charging station; correct the mobile user change trend by the electricity price ratio correction factor to obtain the corrected mobile user change trend in the charging station; combine the corrected mobile user change trend and the resident user change trend in the charging station to obtain the overall user change trend of the charging station.

[0031] It should be noted that by analyzing the charging timing data series of the resident users of the charging station in each quarter, the influencing factors of the charging station on user loyalty, namely competitiveness, can be effectively identified. The level of competitiveness will directly affect mobile users. Higher competitiveness will make the data analysis results of mobile users more reliable and improve the accuracy of subsequent economic benefit evaluation.

[0032] Preferably, in some implementations of the embodiments of the present invention, all reference charging stations of each charging station are obtained in each quarter; according to the number of charging frequencies of the resident users in each charging station at its reference charging station, the specific method for obtaining the charging frequency of the resident users of each reference charging station of each charging station in each quarter is: For charging stations in urban areas. All the charging stations used by permanent users except the All charging stations except the first charging station are recorded as the A reference charging station for charging stations; For Any reference charging station of charging stations, in the Next quarter, the The number of all charging times of all resident users in the reference charging station is recorded as a first number; the first number is added to the The ratio of the total number of charging times of all resident users in the charging station in all reference charging stations is used as the Next quarter a charging frequency of resident users of the reference charging station of the charging station; Preferably, in some implementations of the embodiments of the present invention, all reference charging stations of each charging station are screened based on the charging frequency of resident users, and a specific method for obtaining the influencing charging station of each charging station in each quarter is: Preset a frequency parameter , wherein this embodiment is based on This example is described as an example, and this embodiment is not specifically limited. Depends on the specific implementation situation; For Next quarter If the charging frequency of the resident users of the reference charging station is greater than or equal to the frequency parameter , taking the reference charging station as the first Next quarter The impact of charging stations on charging stations.

[0033] Preferably, in some implementations of the embodiments of the present invention, according to the difference in the possibility that each charging station and its influenced charging stations are resident users, a specific method for obtaining the degree of influence between each charging station and each of its influenced charging stations in each quarter is: Preset a possible parameter , wherein this embodiment is based on This example is described as an example, and this embodiment is not specifically limited. Depends on the specific implementation situation; For Any resident user at a charging station In the next quarter, if the resident user Charging station The possibility of permanent users in the charging station is not , record the resident user as the target resident user; record all the target resident users in the first The average probability of the charging station belonging to the resident user is the same as the average probability of all the target resident users in the Charging station The inverse of the absolute value of the difference between the means of the factors that affect the probability of being a resident user in the charging station is taken as the Next quarter A charging station and its The degree of influence between charging stations; The specific formula is: In the formula, Indicates Next quarter A charging station and its The degree of influence between charging stations; Indicates All target resident users in the next quarter The mean probability of being a resident user in the charging stations; Indicates All target resident users in the next quarter Charging station The average value of the probability of being a resident user in the charging station; Indicates taking the absolute value.

[0034] Preferably, in some implementations of the embodiments of the present invention, the specific method for obtaining the regional competitiveness of each charging station in each quarter according to the distance between each charging station and its affected charging station and the degree of influence is: The first The charging station and Charging station The distance between the charging stations is recorded as the first distance; Next quarter A charging station and its The ratio of the impact degree between the first charging stations to the first distance is recorded as factors that affect the competition of charging stations; The normalized value of the mean of all competitive factors affecting the charging station is taken as the Next quarter Regional competitiveness of charging stations; The specific formula is: In the formula, Indicates Next quarter Regional competitiveness of charging stations; Indicates All impacts of charging stations The number of charging stations; Indicates Next quarter A charging station and its The degree of influence between charging stations; Indicates A charging station and its The distance between charging stations is affected by: represents the linear normalization function.

[0035] Preferably, in some implementations of the embodiments of the present invention, since the lower the ratio of the charging amount to the charging cost, the lower the cost performance of the charging station, according to the difference in charging amount and charging cost between mobile users and resident users in each charging station, and the regional competitiveness of the charging station in each quarter, the specific method for obtaining the electricity price ratio correction factor of each charging station in each quarter is: No. Next quarter, the The average of all charging times of all permanent users in the charging station is The average of all charging costs of all permanent users in the charging station is recorded as Next quarter The electricity price ratio of the permanent users in the charging station; The average of all charging times of all mobile users in the charging station is The average of all charging costs of all mobile users in the charging station is recorded as Next quarter The electricity price ratio of mobile users in the charging station; Next quarter The price ratio of mobile users in the charging station is Charging station No. The product of the regional competitiveness in the first quarter is recorded as the mobile attraction electricity price ratio; Next quarter The absolute value of the difference between the electricity price ratio of resident users and the mobile attraction electricity price ratio in the charging station is taken as the Next quarter The electricity price ratio correction factor of each charging station; The specific formula is: In the formula, Indicates Next quarter The electricity price ratio correction factor of each charging station; Indicates Next quarter The electricity price ratio of permanent users in each charging station; Indicates Next quarter Regional competitiveness of charging stations; Indicates Next quarter The electricity price ratio of mobile users in each charging station; Indicates taking the absolute value.

[0036] It should be noted that the regional competitiveness of a charging station is a manifestation of its attractiveness to mobile users. The higher the attraction intensity, the more referenceable the charging data of mobile users. Since resident users usually cover all operating hours of a charging station, their electricity price ratio can represent the average electricity price ratio of the charging station. When the electricity price ratio of mobile users is similar to that of resident users, it means that there are mobile users charging during most hours of the day.

[0037] Preferably, in some implementations of the embodiments of the present invention, according to the changes in the charging amount and charging costs of mobile users and resident users in each charging station in each quarter, the specific method for obtaining the change trend of mobile users and resident users in each charging station in each quarter is: A three-dimensional coordinate system is constructed with the charging time as the X-axis, the charging amount as the Y-axis and the charging cost as the Z-axis. Next quarter The charging time series data sequence of all permanent users in the charging station is input into the three-dimensional coordinate system to obtain the Next quarter Several resident user charging data points of a charging station; Next quarter The charging time series data of all mobile users in the charging station are input into the three-dimensional coordinate system to obtain the Next quarter Several charging data points of mobile users at a charging station; use the least squares method to Next quarter The curve fitting is performed on all the charging data points of the permanent users and all the charging data points of the mobile users of the charging station to obtain the Next quarter The charging curve of the resident users of the charging station and the Next quarter The charging curve of mobile users at the charging station; Next quarter The average slope of all resident user charging data points in the resident user charging curve of the charging station is taken as the Next quarter The trend of permanent users of charging stations; Next quarter The average slope of all mobile user charging data points in the mobile user charging curve of the charging station is taken as Next quarter The changing trend of mobile users of charging stations.

[0038] Preferably, in some implementations of the embodiments of the present invention, the change trend of mobile users is corrected by the electricity price ratio correction factor, and the specific method for obtaining the corrected change trend of mobile users in each charging station in each quarter is: The first Next quarter The number of all mobile users in the charging station is Next quarter The ratio of the total number of users in the charging station is recorded as the proportion of mobile users; Next quarter The number of all mobile users in the charging station is Next quarter The product of the price ratio correction factors of the charging stations is recorded as the correction confidence factor; the normalized value of the product of the proportion of mobile users and the correction confidence factor is recorded as the confidence level of the trend correction; Next quarter The product of the mobile user change trend of the charging station and the confidence of the change trend correction is taken as the Next quarter The revised mobile user trends of charging stations; The specific formula is: In the formula, Indicates Next quarter The revised mobile user trends of charging stations; Indicates Next quarter The number of all mobile users in the charging station; Indicates Next quarter The total number of users in the charging station; Indicates Next quarter The electricity price ratio correction factor of each charging station; Indicates Next quarter Trends in mobile users of charging stations; represents the linear normalization function.

[0039] Preferably, in some implementations of the embodiments of the present invention, the specific method of obtaining the overall change trend of users at each charging station in each quarter by combining the modified mobile user change trend and the resident user change trend at each charging station in each quarter is: The first Next quarter The number of all permanent users in the charging station is Next quarter The ratio of the total number of all users in the charging station is recorded as the resident user ratio; the resident user ratio is divided by the Next quarter The product of the change trend of permanent users of each charging station is recorded as the permanent change product; the proportion of mobile users is Next quarter The product of the modified mobile user change trend of the charging station is recorded as the mobile change product; the normalized value of the sum of the permanent change product and the mobile change product is taken as the Next quarter The overall trend of users of charging stations.

[0040] So far, the overall change trend of users of each charging station in each quarter is obtained through the above method.

[0041] Step S004: Evaluate the economic benefits of the charging station based on the overall change trend of the users of the charging station.

[0042] Preferably, in some implementations of the embodiments of the present invention, the specific method for evaluating the economic benefits of a charging station based on the overall change trend of users of the charging station is: Preset an economic benefit parameter , wherein this embodiment is based on This example is described as an example, and this embodiment is not specifically limited. Depends on the specific implementation situation; All quarterly The average of the overall change trend of users at the charging stations is taken as the Economic benefit evaluation factors of each charging station; Jordi The economic benefit evaluation factor of the charging station is greater than or equal to the economic benefit parameter , will The economic benefit of the charging station is evaluated as good; The economic benefit evaluation factor of the charging station is less than the economic benefit parameter , will The economic benefit evaluation of each charging station is average and needs to be improved and strengthened.

[0043] See also Figure 2 , which shows a characteristic relationship flow chart of an economic benefit evaluation method for electric vehicle charging stations integrating time series analysis; Through the above steps, the economic benefit evaluation method of electric vehicle charging stations integrating timing analysis is completed.

[0044] The present invention also proposes an economic benefit evaluation model for electric vehicle charging stations that integrates timing analysis, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the economic benefit evaluation method for electric vehicle charging stations that integrates timing analysis in steps S001 to S004 are implemented.

[0045] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An economic benefit evaluation method for electric vehicle charging stations integrating time series analysis is characterized in that: The method comprises the following steps: Obtain the charging time, charging duration, charging amount and charging cost of each user at each charging station in each quarter of the urban area in the past year, as well as the distance between all charging stations in the urban area; By analyzing the periodic distribution of the user's charging time, charging duration and charging amount in the charging station, the possibility of the user being a resident user in each charging station is obtained; based on the possibility of being a resident user, all users in the charging station are divided into resident users and mobile users; Obtain all reference charging stations of the charging station; obtain the charging frequency of resident users of the reference charging station of the charging station according to the number of charging frequencies of resident users in the charging station at its reference charging station; screen all reference charging stations of the charging station based on the charging frequency of resident users to obtain the influencing charging station of the charging station; obtain the degree of influence between the charging station and the charging station it influences according to the difference in the possibility of being resident users between the charging station and the charging station it influences; obtain the regional competitiveness of the charging station according to the distance and degree of influence between the charging station and the charging station it influences; obtain the electricity price ratio correction factor of the charging station according to the difference in charging volume and charging cost between mobile users and resident users in the charging station and the regional competitiveness of the charging station; obtain the mobile user change trend and the resident user change trend in the charging station according to the change in charging volume and charging cost of mobile users and resident users in the charging station; correct the mobile user change trend by the electricity price ratio correction factor to obtain the corrected mobile user change trend in the charging station; combine the corrected mobile user change trend and the resident user change trend in the charging station to obtain the overall user change trend of the charging station; The economic benefits of charging stations are evaluated based on the overall changing trend of charging station users.

2. The economic benefit evaluation method of electric vehicle charging station integrating time series analysis according to claim 1 is characterized in that: The method of analyzing the periodic distribution of the user's charging time, charging duration, and charging amount in the charging station to obtain the possibility that the user is a resident user in each charging station includes the following specific methods: For urban areas User in In each charging station, a three-dimensional coordinate system is constructed with the charging time as the X-axis, the charging time as the Y-axis and the charging amount as the Z-axis. Next quarter User in All charging times, charging durations and charging amounts in the charging station are input into the three-dimensional coordinate system to obtain the Next quarter User in Several charging data points in a charging station; No. In the next quarter, for User in Charging station charging data point, The charging data point and The absolute value of the difference in charging time between the charging data points is recorded as The charging time interval of each charging data point; The charging data point and The absolute value of the difference in charging time between the charging data points is recorded as The charging time difference of the charging data points; The charging data point and The absolute value of the difference in charge capacity between the charging data points is recorded as The difference in charge capacity of each charging data point; The first Next quarter User in The reciprocal of the mean of the charging time intervals of all charging data points in the charging station is taken as Next quarter User in The frequency of charging cycles in each charging station; No. Next quarter, the User in The variance of the charging time difference values ​​of all charging data points in the charging station is User in The sum of the variances of the charging amount difference values ​​of all charging data points in the charging station is recorded as the first sum value; User in The product of the variance of the charging time intervals of all charging data points in the charging station and the first sum is recorded as the first product; User in The normalized value of the ratio between the charging cycle frequency in the first charging station and the first product is used as the Next quarter User in The possibility of permanent users in a charging station.

3. The economic benefit evaluation method of electric vehicle charging station integrating time series analysis according to claim 1 is characterized in that: The specific method of obtaining the charging frequency of the resident users of the reference charging station of the charging station according to the number of charging frequencies of the resident users of the charging station at the reference charging station includes: For Any reference charging station of charging stations, in the Next quarter, the The number of all charging times of all resident users in the reference charging station is recorded as a first number; the first number is added to the The ratio of the total number of charging times of all resident users in the charging station in all reference charging stations is used as the Next quarter The charging frequency of the resident users of the reference charging station is determined based on the charging frequency of the resident users of the reference charging station.

4. The economic benefit evaluation method of electric vehicle charging station integrating time series analysis according to claim 1 is characterized in that: The method of obtaining the influence degree between the charging station and the charging station it affects based on the difference in the possibility that the charging station and the charging station it affects are permanent users includes: Preset a possible parameter , for the Any resident user at a charging station In the next quarter, if the resident user Charging station The possibility of permanent users in the charging station is not , record the resident user as the target resident user; record all the target resident users in the first The average probability of the charging station belonging to the resident user is the same as the average probability of all the target resident users in the Charging station The inverse of the absolute value of the difference between the means of the factors that affect the probability of being a resident user in the charging station is taken as the Next quarter A charging station and its The degree of influence between charging stations.

5. The economic benefit evaluation method of electric vehicle charging station integrating timing analysis according to claim 1 is characterized in that: The specific method for obtaining the regional competitiveness of a charging station based on the distance and influence degree between the charging station and the charging stations it affects is as follows: The first Charging station and Charging station The distance between the charging stations is recorded as the first distance; Next quarter A charging station and its The ratio of the impact degree between the first charging stations to the first distance is recorded as factors that affect the competition of charging stations; The normalized value of the mean of all competitive factors affecting the charging station is taken as the Next quarter Regional competitiveness of charging stations.

6. The economic benefit evaluation method of electric vehicle charging station integrating time series analysis according to claim 1 is characterized in that: The specific method for obtaining the electricity price ratio correction factor of the charging station according to the difference in charging amount and charging cost between mobile users and resident users in the charging station and the regional competitiveness of the charging station is as follows: No. Next quarter, the The average of all charging times of all permanent users in the charging station is The average of all charging costs of all permanent users in the charging station is recorded as Next quarter The electricity price ratio of the permanent users in the charging station; The average of all charging times of all mobile users in the charging station is The average of all charging costs of all mobile users in the charging station is recorded as Next quarter The electricity price ratio of mobile users in the charging station; Next quarter The price ratio of mobile users in the charging station is Charging station No. The product of the regional competitiveness in the first quarter is recorded as the mobile attraction electricity price ratio; Next quarter The absolute value of the difference between the electricity price ratio of resident users and the mobile attraction electricity price ratio in the charging station is taken as the Next quarter The electricity price ratio correction factor for each charging station.

7. The economic benefit evaluation method of electric vehicle charging station integrating time series analysis according to claim 1 is characterized in that: The method of obtaining the changing trend of mobile users and resident users in the charging station according to the changing situation of the charging amount and charging fee of mobile users and resident users in the charging station includes the following specific methods: A three-dimensional coordinate system is constructed with the charging time as the X-axis, the charging amount as the Y-axis and the charging cost as the Z-axis. Next quarter The charging time series data sequence of all permanent users in the charging station is input into the three-dimensional coordinate system to obtain the Next quarter Several resident user charging data points of a charging station; Next quarter The charging time series data of all mobile users in the charging station are input into the three-dimensional coordinate system to obtain the Next quarter Several charging data points of mobile users at a charging station; use the least squares method to Next quarter The curve fitting is performed on all the charging data points of the permanent users and all the charging data points of the mobile users of the charging station to obtain the Next quarter The charging curve of the resident users of the charging station and the Next quarter The charging curve of mobile users at the charging station; Next quarter The average slope of all resident user charging data points in the resident user charging curve of the charging station is taken as the Next quarter The trend of permanent users of charging stations; Next quarter The average slope of all mobile user charging data points in the mobile user charging curve of the charging station is taken as Next quarter The changing trend of mobile users of charging stations.

8. The economic benefit evaluation method of electric vehicle charging station integrating time series analysis according to claim 1 is characterized in that: The method of correcting the mobile user change trend by the electricity price ratio correction factor to obtain the corrected mobile user change trend in the charging station includes: The first Next quarter The number of all mobile users in the charging station is Next quarter The ratio of the total number of users in the charging station is recorded as the proportion of mobile users; Next quarter The number of all mobile users in the charging station is Next quarter The product of the electricity price ratio correction factors of the charging stations is recorded as the correction confidence factor; the normalized value of the product of the proportion of mobile users and the correction confidence factor is recorded as the confidence level of the change trend correction; The first Next quarter The product of the mobile user change trend of the charging station and the confidence of the change trend correction is taken as the Next quarter Modified mobile user trends of charging stations.

9. The economic benefit evaluation method of electric vehicle charging station integrating timing analysis according to claim 8 is characterized in that: The method of combining the modified mobile user change trend and the resident user change trend in the charging station to obtain the overall user change trend of the charging station includes the following specific methods: The first Next quarter The number of all permanent users in the charging station is Next quarter The ratio of the total number of all users in the charging station is recorded as the resident user ratio; the resident user ratio is divided by the Next quarter The product of the change trend of permanent users of each charging station is recorded as the permanent change product; the proportion of mobile users is Next quarter The product of the modified mobile user change trend of the charging station is recorded as the mobile change product; the normalized value of the sum of the permanent change product and the mobile change product is taken as the Next quarter The overall trend of users of charging stations.

10. An economic benefit evaluation model for electric vehicle charging stations integrating timing analysis, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the method for evaluating the economic benefits of an electric vehicle charging station integrating timing analysis as described in any one of claims 1 to 9 are implemented.

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