Charging price updating method and device, equipment and storage medium

Abstract

The invention belongs to the technical field of charging stations, and discloses a charging price updating method and device, equipment and a storage medium. According to the method, the comparison table between the charging pile vacancy rate and the optimal service charge discount rate in each time period in the future is predicted according to the operation condition of the target charging station, the optimal service charge discount rate corresponding to different charging pile vacancy rates can be obtained, and then the current service charge discount rate is searched from the comparison table in real time according to the preset price updating moment. And the charging price of the target charging station is dynamically updated according to the current service charge discount rate.

Description

Technical Field

[0001] This application relates to the field of charging station technology, and in particular to a method, apparatus, device and storage medium for updating charging prices. Background Technology

[0002] With the widespread adoption of electric vehicles, the number of charging stations is rapidly increasing, and their operational efficiency and profitability are becoming core concerns for operators. Pricing strategies, as a key means of influencing charging demand and balancing supply and demand, are typically static pricing strategies. These strategies usually set fixed or time-of-use charging prices in the early stages of charging station planning or construction, based on macro-level grid time-of-use (TOU) pricing, regional average service fees, and estimated operating costs. The drawbacks are that once prices are set, they remain unchanged for a long period, failing to respond to real-time, micro-level supply and demand fluctuations at charging stations, and lacking the ability to perceive and respond to the actual operating status of individual stations. Summary of the Invention

[0003] The main objective of this application is to provide a method, apparatus, device, and storage medium for updating charging prices, aiming to solve the technical problem of how to dynamically adjust the charging prices of charging stations in real time and effectively.

[0004] To achieve the above objectives, this application provides a method for updating charging prices, the method comprising the following steps:

[0005] The optimal charging electricity cost change rate for each charging pile idle rate in future time periods is predicted based on the charging station quantity-price correlation model. The charging station quantity-price correlation model includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity cost change rate corresponding to the target charging station. The charging pile idle rate is correlated with the optimal charging pile utilization rate change rate. Calculate the optimal service fee discount rate for each charging pile at its idle rate based on the optimal charging electricity cost change rate, and construct a comparison table between the charging pile idle rate and the optimal service fee discount rate; The current service fee discount rate is retrieved from the lookup table based on the current charging pile availability rate at the preset price update time. The charging price of the target charging station is updated based on the current service fee discount rate.

[0006] Optionally, before predicting the optimal rate of change in charging electricity costs for each charging pile's idle rate in future time periods based on the charging station volume-price correlation model, the method further includes: Obtain the historical charging pile utilization rate and historical charging electricity cost of the target charging station for different historical time periods; Construct a historical quantity and price data set based on the historical charging utilization rate and the historical charging electricity cost; A charging station volume-price correlation model is constructed based on the aforementioned historical volume and price data set.

[0007] Optionally, constructing a historical quantity and price data set based on the historical charging utilization rate and the historical charging electricity cost includes: The historical utilization rate change rate for each historical period is calculated based on the historical charging pile utilization rate and the historical utilization average rate. Calculate the historical charging electricity cost change rate for each historical period based on the historical charging electricity cost and the historical average charging electricity cost; A historical quantity and price data set is constructed based on the historical utilization rate change rate and the historical charging electricity cost change rate.

[0008] Optionally, constructing a charging station volume-price correlation model based on the historical volume-price data set includes: Determine the one-hot encoding corresponding to the time-division type of each historical time period; The historical price and volume data set is updated based on the unique hot encoding to obtain the updated data set; The updated dataset is fitted using the least squares method, and the model parameters are obtained based on the fitting results. Based on the model parameters, a charging station quantity-price correlation model is obtained, which includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity cost change rate of the target charging station.

[0009] Optionally, the step of predicting the optimal charging electricity cost change rate under the idle rate of each charging pile in future time periods based on the charging station volume-price correlation model includes: The change rate function between the change rate of the utilization rate of the charging piles and the change rate of the charging electricity cost is predicted based on the charging pile quantity-price correlation model for future time periods. Determine the optimal rate of change in the utilization rate of each charging pile based on the expected utilization rate of the charging piles. The optimal charging cost change rate under the idle rate of each charging pile is determined based on the change rate function and the optimal charging pile utilization rate change rate.

[0010] Optionally, the step of predicting the rate of change between the utilization rate of operating charging piles and the rate of change of operating charging electricity costs for future time periods based on the charging pile quantity-price correlation model includes: Obtain the operating service cost price, basic operating service price, and unit electricity cost of the target charging station for each future time period; The service fee adjustment limit for each future time period is calculated based on the operating service fee cost price, the operating service fee base price, and the operating unit electricity cost. Based on the service fee adjustment limit and the charging pile quantity-price correlation model, a rate of change function is generated between the change rate of operating charging pile utilization rate and the change rate of operating charging electricity cost.

[0011] Optionally, obtaining the basic price of the operating service fee for the target charging station in future time periods includes: Identify the surrounding charging stations of the target charging station, and determine the basic price of the surrounding historical service fees for each historical time period. Determine the percentage of the target historical service fee base price of the target charging station in each historical time period relative to the surrounding charging price of the surrounding charging stations; The historical service fee base price of the target charging station for each historical period is determined based on the surrounding historical service fee base price and the percentage. The base price for the operation service fee of the target charging station in each future period is determined based on the historical base price for service fees.

[0012] Optionally, the step of calculating the optimal service fee discount rate for each charging pile's idle rate based on the optimal charging electricity cost change rate, and constructing a lookup table between the charging pile idle rate and the optimal service fee discount rate, includes: The optimal service fee discount rate for each charging pile under the idle rate is calculated based on the base price of the operation service fee, the electricity cost per unit of operation, and the optimal charging electricity cost change rate. Construct a comparison table between the charging pile vacancy rate and the optimal service fee discount rate.

[0013] Optionally, updating the charging price of the target charging station based on the current service fee discount rate includes: The current service fee is determined based on the current service fee discount rate and the base price of the operating service fee. The current charging price is determined based on the electricity cost of the operating unit and the current service fee, so as to update the charging price of the target charging station.

[0014] Furthermore, to achieve the above objectives, this application also provides a charging price updating device, the charging price updating device comprising: The rate of change prediction module is used to predict the optimal rate of change of charging electricity cost under the idle rate of each charging pile in the future time period based on the charging station quantity-price correlation model. The charging station quantity-price correlation model includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity cost change rate corresponding to the target charging station. The charging pile idle rate is correlated with the optimal charging pile utilization rate change rate. The lookup table construction module is used to calculate the optimal service fee discount rate under each charging pile idle rate based on the optimal charging electricity cost change rate, and to construct a lookup table between the charging pile idle rate and the optimal service fee discount rate; The discount rate calculation module is used to look up the current service fee discount rate from the lookup table based on the current charging pile idle rate corresponding to the preset price update time. The price update module is used to update the charging price of the target charging station based on the current service fee discount rate.

[0015] In addition, to achieve the above objectives, this application also proposes a charging price updating device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the charging price updating method as described above.

[0016] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the charging price update method described above.

[0017] This application uses a charging station volume-price correlation model to predict the optimal charging electricity rate change rate for each charging pile idle rate in future time periods. The model includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity rate change rate for the target charging station. The charging pile idle rate is correlated with the optimal charging pile utilization rate change rate. Then, based on the optimal charging electricity rate change rate, the optimal service fee discount rate for each charging pile idle rate is calculated, and a lookup table between the charging pile idle rate and the optimal service fee discount rate is constructed. Then, based on the current charging pile idle rate at the preset price update time, the current service fee discount rate is retrieved from the lookup table, and the charging price for the target charging station is updated accordingly. This application predicts the optimal service fee discount rate for different charging pile idle rates by using the lookup table for future time periods based on the target charging station's operational status. It then retrieves the current service fee discount rate from the lookup table in real time based on the preset price update time, and dynamically updates the charging price for the target charging station based on the current service fee discount rate. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart illustrating the first embodiment of the method for updating the charging price in this application; Figure 2 A flowchart illustrating the second embodiment of the method for updating the charging price in this application; Figure 3 A flowchart illustrating the third embodiment of the method for updating the charging price in this application; Figure 4 A structural block diagram of the first embodiment of the charging price updating device of this application; Figure 5 This is a schematic diagram of the structure of the device for updating the charging price of the hardware operating environment involved in the embodiments of this application.

[0021] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0022] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0023] It should be noted that the executing entity of this application can be a computing service device with data processing, network communication and program execution functions, such as a computer.

[0024] Based on this, embodiments of this application provide a method for updating charging prices, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the method for updating the charging price in this application.

[0025] In this embodiment, the method for updating the charging price includes the following steps: Step S10: Predict the optimal charging electricity cost change rate for each charging pile idle rate in future time periods based on the charging station quantity-price correlation model. The charging station quantity-price correlation model includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity cost change rate corresponding to the target charging station. The charging pile idle rate is correlated with the optimal charging pile utilization rate change rate.

[0026] Understandably, the target charging station refers to a charging station that requires a charging price update and can charge several electric vehicles. The charging station scale correlation model can be pre-established based on historical data related to the target charging station. It reflects the correlation between the rate of change in charging pile utilization and the rate of change in charging electricity costs over a historical period. The rate of change in charging pile utilization represents the increase in charging pile utilization compared to the average, while the rate of change in charging electricity costs represents the increase in charging electricity costs compared to the average. The charging station scale model is a mathematical model used to describe the dynamic relationship between charging service demand and charging electricity costs. This model aims to reveal how price changes affect user demand, thereby optimizing overall revenue.

[0027] It should be understood that the future time periods can be the next week or the next month. In this embodiment, the optimal charging electricity cost change rate under the idle rate of each charging pile can be predicted based on the charging station quantity and price correlation model of historical time periods. The idle rate of the charging pile can be the proportion of the number of unused charging piles in the target charging station to the total number of charging piles. It is a key indicator for measuring the idle status of the station's real-time service capacity. The calculation formula can be: (1 - charging pile utilization rate) × 100%. In this embodiment, the optimal charging pile utilization rate change rate is related to the charging pile idle rate. The optimal charging pile utilization rate change rate can be the ratio of the charging pile idle rate to the charging pile utilization rate.

[0028] In practice, the optimal charging capacity utilization rate for each time period in the future can be predicted based on the charging pile vacancy rate. Then, based on the optimal charging pile utilization rate change rate and the charging station quantity-price correlation model, the optimal charging electricity cost change rate under each charging pile vacancy rate in each time period in the future can be obtained.

[0029] Step S20: Calculate the optimal service fee discount rate for each charging pile under the optimal charging electricity cost change rate, and construct a comparison table between the charging pile vacancy rate and the optimal service fee discount rate.

[0030] Understandably, the optimal service fee discount rate for each charging pile's idle rate can be calculated based on the optimal charging electricity cost change rate. In one feasible embodiment, the optimal service fee discount rate can be calculated by combining the unit electricity cost and the service fee base price of the target charging station. The unit electricity cost can be the electricity cost required to consume one unit of electricity, which usually fluctuates with peak and off-peak periods. It can be divided into two types depending on whether the target charging station has signed a retail contract with an electricity sales company: 1) For charging stations without a retail contract, the unit electricity cost is settled according to the industrial and commercial agency electricity purchase and sale price; 2) For charging stations with a retail contract, the unit electricity cost is settled according to the price agreed in the signed retail contract. The service fee base price refers to the standardized charge amount set by the operator of the target charging station before dynamic adjustments are made and before charging services are provided, for one unit of electricity (usually per kilowatt-hour). It is the benchmark and starting point for all subsequent dynamic price calculations and adjustments. Usually, the electricity cost for one unit of electricity can include the above-mentioned unit electricity cost plus the service fee base price.

[0031] In practical implementation, the lookup table can be a correspondence between charging pile idle rate and optimal service fee discount rate. The generation and update cycle of this lookup table can be configured to different time scales according to business needs: When configured in weekly mode, the system aggregates daily historical operational data into weekly data (the data dimension becomes the future z-week t-period), then constructs a volume-price correlation model based on the historical operational data, and generates a lookup table for each time period within the next week at 23:45 every Sunday evening. This lookup table remains stable within the next week. When configured in monthly mode, the system aggregates daily historical operational data into monthly data (the data dimension becomes z-month t-period), then constructs a volume-price correlation model, and generates a lookup table for each time period within the next month at 23:45 on the last day of each month. This lookup table remains stable within the next month.

[0032] Step S30: Find the current service fee discount rate from the lookup table based on the current charging pile vacancy rate corresponding to the preset price update time.

[0033] It should be understood that the preset price update time refers to the time at which the target charging station will update its price. This time can be determined by both the discount period and the strategy update frequency. The discount period is the time range within which the dynamic pricing strategy is enabled, preset before the target charging station's operation date. The price update frequency defines the cycle in which the service fee is updated within this time range, such as 15 minutes / time, 30 minutes / time, or 1 hour / time. From the start time of the discount period to the end time, all time points that meet the update frequency requirement constitute the set of price update times. For example, if the price update frequency is 15 minutes / time, the preset price update time could be 00:15, 00:30, 00:45, 1:00, etc.

[0034] In the specific implementation, the current charging pile vacancy rate corresponding to the preset price update time can be determined first. The current charging pile vacancy rate can be the ratio between the number of vacant charging piles and the total number of charging piles at the preset price update time. Then, the current service fee discount rate corresponding to the current charging pile vacancy rate can be found from the reference table. The service fee discount rate refers to the discount ratio adjusted based on the base service fee price.

[0035] Step S40: Update the charging price of the target charging station according to the current service fee discount rate.

[0036] Understandably, the base service fee price of the target charging station can be adjusted based on the current service fee discount rate. For example, if the base service fee price is 0.8 yuan / kWh, and the current service fee discount rate is 80%, then the actual service fee charged will be 0.8 × 0.8 = 0.64 yuan / kWh. The final charging price can be the updated service fee plus the unit electricity cost, and will be used as the charging price of the target charging station at the time of the preset price update.

[0037] This embodiment predicts the optimal charging electricity rate change rate for each charging pile idle rate in future time periods based on a charging station volume-price correlation model. The model includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity rate change rate for the target charging station. The charging pile idle rate is correlated with the optimal charging pile utilization rate change rate. Then, the optimal service fee discount rate is calculated for each charging pile idle rate based on the optimal charging electricity rate change rate, and a lookup table between the charging pile idle rate and the optimal service fee discount rate is constructed. Next, the current service fee discount rate is retrieved from the lookup table based on the current charging pile idle rate at the preset price update time, and then the charging price for the target charging station is updated based on the current service fee discount rate. This embodiment predicts the lookup table between the charging pile idle rate and the optimal service fee discount rate for each future time period based on the target charging station's operating status, obtaining the optimal service fee discount rate corresponding to different charging pile idle rates. Then, the current service fee discount rate is retrieved from the lookup table in real time according to the preset price update time, and the charging price for the target charging station is dynamically updated based on the current service fee discount rate.

[0038] refer to Figure 2 , Figure 2 This is a flowchart illustrating the second embodiment of the method for updating the charging price in this application.

[0039] Based on the first embodiment described above, in this embodiment, before step S10, the method further includes: Step S01: Obtain the historical charging utilization rate and historical charging electricity cost of the target charging station for each historical time period.

[0040] Understandably, historical time periods could be within a week prior to the target charging station's operation date, or within a month prior, or other time periods.

[0041] It should be understood that the historical charging utilization rate of the target charging station at various historical time periods can be obtained. and historical charging electricity costs The historical charging utilization rate of charging piles during the historical period d days t is recorded as follows: It can be based on the historical busy / idle status of the charging piles at the target charging station. It can be calculated that, where i is the charging gun serial number, G is the total number of guns in the target charging station, and d,t are historical time series identifiers. The calculation formula is:

[0042] In the formula, the historical busy / idle status of the charging piles at the target charging station is used. One-hot encoding, ∈0,1, A value of 0 indicates that the charging gun i was in an idle state during the historical period d days t. A value of 1 indicates that the charging gun i was in working condition during the historical period d days t. This indicates that there are 96 time slots per day, each of which can be fifteen minutes long, such as 00:15, 00:30, 00:45, 1:00, etc.

[0043] In the specific implementation, the historical charging electricity cost of the target charging station during the historical period t on day d is recorded as follows: The calculation formula is:

[0044] In the formula, The unit electricity cost for the target charging station during the historical d-day t-period. This represents the unit service fee for the target charging station during the historical period t on day d.

[0045] Step S02: Construct a historical quantity and price data set based on the historical charging utilization rate and the historical charging electricity cost.

[0046] Understandably, a historical charging volume and price data set can be constructed based on historical charging utilization rates and historical charging electricity costs. This historical charging volume and price data set can be used to train a charging station volume and price correlation model.

[0047] Furthermore, in order to effectively construct a historical quantity and price data set, in this embodiment, step S202 includes: calculating the historical utilization rate change rate for each historical period based on the historical charging pile utilization rate and the historical average utilization rate; calculating the historical charging cost change rate for each historical period based on the historical charging cost and the historical average charging cost; and constructing a historical quantity and price data set based on the historical utilization rate change rate and the historical charging cost change rate.

[0048] It should be understood that the historical utilization rate change rate can be calculated using the following formula. :

[0049] In the formula, This represents the increase in the charging utilization rate of charging piles during the historical period t on day d compared to the historical average. The charging utilization rate of charging piles during the historical period d days t. This represents the average charging utilization rate of charging piles over all historical periods.

[0050] Understandably, the historical rate of change in charging electricity costs can be calculated using the following formula. :

[0051] In the formula, This represents the increase in charging electricity costs for the historical period t over a given day (d) compared to the historical average. The charging electricity cost for the historical d-day t-period. This represents the average charging cost over all historical periods.

[0052] In the specific implementation, , It is a collection of historical volume and price data.

[0053] Step S03: Construct a charging station quantity-price correlation model based on the historical quantity-price data set.

[0054] It is understood that in this embodiment, historical charging volume and price data sets can be used as training sets. These sets may include historical charging pile utilization rate change rate and historical charging electricity price change rate. The linear model is trained using these sets to obtain a charging station volume and price correlation model.

[0055] Furthermore, in order to effectively construct a charging station quantity-price correlation model, in this embodiment, step S03 includes: determining the one-hot code corresponding to the time-sharing type of each historical time period; updating the historical quantity-price data set based on the one-hot code to obtain an updated data set; fitting the updated data set using the least squares method and obtaining model parameters based on the fitting result; obtaining a charging station quantity-price correlation model based on the model parameters, wherein the charging station quantity-price correlation model includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity cost change rate corresponding to the target charging station.

[0056] Understandably, the time-sharing types for different historical time periods can be valley periods, normal periods, and peak periods, and each time-sharing type can correspond to a one-hot code, which can be used... This refers to the unique hot code corresponding to the time-sharing type of historical day d and time period t. Based on the unique hot code, the historical volume and price data set is updated to obtain an updated data set, which may include the historical utilization rate change rate. Historical charging electricity price change rate One-hot encoding .

[0057] It should be understood that the updated dataset can be fitted using the least squares method, and the model parameters can be obtained based on the fitting results. The updated dataset can be used as a training set to train a pre-defined linear model. After training, a charging station price-volume correlation model can be obtained, along with its corresponding model parameters. The charging station price-volume correlation model can be represented as: , The historical utilization rate change rate for the historical period t (day d). The historical rate of change in charging electricity costs over a historical period d days t. and For model parameters, For each time period of historical day d, there is a corresponding time-sharing type. Components, that is, different time-sharing types have different price elasticity parameters.

[0058] This embodiment obtains the historical charging pile utilization rate and historical charging electricity cost of the target charging station for various historical time periods. Then, it constructs a historical volume-price data set based on the historical charging utilization rate and historical charging electricity cost, and further constructs a charging station volume-price correlation model based on this data set. This embodiment constructs a historical volume-price data set based on the historical charging utilization rate and historical charging electricity cost, and trains a preset linear model based on this data set, thereby effectively constructing a charging station volume-price correlation model. The charging station volume-price correlation model includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity cost change rate corresponding to the target charging station.

[0059] refer to Figure 3 , Figure 3 This is a flowchart illustrating the third embodiment of the method for updating the charging price in this application.

[0060] Based on the above embodiments, in this embodiment, step S10 includes: Step S101: Based on the charging pile quantity-price correlation model, predict the rate of change function between the utilization rate of operating charging piles and the rate of change of operating charging electricity costs for each future time period.

[0061] Understandably, since the charging pile quantity-price correlation model is the relationship between the historical charging pile utilization rate change rate and the historical charging electricity cost change rate, in order to predict the optimal charging electricity cost change rate for each future time period, we can first predict the rate of change function between the operating charging pile utilization rate change rate and the operating charging electricity cost change rate for each future time period based on the above charging pile quantity-price correlation model.

[0062] Furthermore, in order to generate a rate-of-change function between the utilization rate of the operating charging pile and the rate of change of the operating charging electricity cost, in this embodiment, step S101 includes: obtaining the operating service fee cost price, the operating service fee base price, and the operating unit electricity cost of the target charging station for each future time period; calculating the service fee adjustment limit value for each future time period based on the operating service fee cost price, the operating service fee base price, and the operating unit electricity cost; and generating a rate-of-change function between the utilization rate of the operating charging pile and the rate of change of the operating charging electricity cost based on the service fee adjustment limit value and the charging pile quantity-price correlation model.

[0063] It should be understood that when the lookup table is updated weekly, the operating service cost price, operating service base price, and unit electricity cost for each time period within each day of the coming week can be considered the same value; when the lookup table is updated monthly, the operating service cost price, operating service base price, and unit electricity cost for each time period within each day of the coming month can be considered the same value. Therefore, only the time period t needs to be restricted, not the date d.

[0064] Understandably, the limit values ​​for service fee adjustments in future time periods can be calculated using the following formula. :

[0065] In the formula, This represents the service fee adjustment limit for time period t on the operating day. It is the theoretical minimum value of the service fee. The operating day can be a future date on which the charging price of the target charging station needs to be updated. This represents the operating service cost price for the t-hour period of the operating day. This represents the base price of the operating service fee for the t-hour period on the operating day. This represents the unit electricity cost for the operating day during time period t.

[0066] In practical implementation, the rate of change function can be expressed as:

[0067] In the formula, This represents the rate of change in charging electricity costs during the t-hour period of the operating day. This represents the rate of change in the utilization rate of charging piles during the t-hour period of the operating day. This indicates the service fee adjustment limit for the t-hour period on the operating day.

[0068] In addition, after obtaining the model parameters through least squares fitting, the price elasticity coefficient is also included. The steps for verification and correction are as follows: The reasonable threshold range for the price elasticity coefficient is... If the fitted price elasticity coefficients for different time-sharing types are obtained If the price elasticity coefficient exceeds the aforementioned reasonable threshold range, then... Corrected to the nearest threshold boundary value, i.e.: The revised price elasticity coefficient can be used to generate a comparison table between charging pile vacancy rates and optimal service fee discount rates.

[0069] Furthermore, in order to calculate the base price of the operating service fee for the target charging station in future time periods, in this embodiment, obtaining the base price of the operating service fee for the target charging station in future time periods includes: determining the surrounding charging stations of the target charging station, and determining the historical base price of the surrounding charging stations in historical time periods; determining the ratio of the target historical base price of the target charging station in historical time periods to the surrounding charging prices of the surrounding charging stations; determining the historical base price of the target charging station in historical time periods based on the historical base price of the surrounding charging stations and the ratio; and determining the base price of the operating service fee for the target charging station in future time periods based on the historical base price of the operating service fee.

[0070] It should be understood that the base price of the service fee for the target charging station is determined based on the charging pricing level of the surrounding charging stations. The surrounding charging stations can be competing charging stations within a 5km radius of the target charging station, and competing charging stations can be charging stations of the same type as the target charging station.

[0071] Understandably, by obtaining the historical base prices of surrounding charging stations for various historical periods, the base prices of future operating service fees for the target charging station can be calculated using the following formula. :

[0072] In the formula, This represents the base price for operating services during time period t on the operating day. CP is the set of surrounding charging stations. Indicates surrounding charging stations Based on historical service fees for the surrounding historical d-day t-period. The quantile of the target charging station's target historical service fee base price relative to the charging prices of surrounding charging stations is used to measure the target charging station's operational preferences. When the percentage is 25%, it means that the base service fee of the target charging station for the current period exceeds 25% of the historical pricing level of surrounding charging stations for the same period over multiple days. When =0%, The minimum value among the historical base prices of service fees for surrounding charging stations over D days, when When = 100%, This is the maximum value among the historical base prices of service fees for surrounding charging stations over multiple days.

[0073] Step S102: Determine the optimal charging pile utilization rate change rate corresponding to the idle rate of each charging pile based on the expected charging pile utilization rate.

[0074] It should be understood that the combination of charging pile idle rates can be expressed as: G represents the total number of charging guns at the target charging station. This represents the vacancy rate from 1 vacant stake to G vacant stakes.

[0075] Understandably, the rate of change in the optimal charging station utilization rate is... , The idle rate of charging piles, , The expected utilization rate of charging piles, of which In ideal circumstances, It is 100%.

[0076] Step S103: Determine the optimal charging electricity cost change rate under the idle rate of each charging pile based on the change rate function and the optimal charging pile utilization rate change rate.

[0077] It should be understood that by replacing the rate of change of the utilization rate of the operating charging piles in the rate of change function with the rate of change of the optimal charging pile utilization rate, the optimal rate of change of charging electricity cost under the idle rate of each charging pile can be obtained, expressed as:

[0078] In the formula, Indicates the different time periods of the operating day Idle rate of each charging station The optimal rate of change in charging electricity costs is as follows. This is the corrected price elasticity coefficient.

[0079] Further, in this embodiment, step S20 includes: calculating the optimal service fee discount rate under each charging pile idle rate based on the basic price of the operation service fee, the electricity cost per unit of operation, and the optimal charging electricity cost change rate; and constructing a comparison table between the charging pile idle rate and the optimal service fee discount rate.

[0080] Understandably, the optimal service fee discount rate for each charging station's vacancy rate can be calculated using the following formula:

[0081] In the formula, Indicates the different time periods of the operating day Idle rate of each charging station The best service fee discount rate, Indicates the different time periods of the operating day Idle rate of each charging station The optimal rate of change in charging electricity costs is as follows. Indicates the different time periods of the operating day Electricity cost per unit of operation Indicates the different time periods of the operating day The base price for operating service fees.

[0082] In practical implementation, the above-mentioned charging pile idle rate can be constructed. and the above-mentioned best service fee discount rate A lookup table between them, which can be updated weekly or monthly.

[0083] Furthermore, in this embodiment, step S40 includes: determining the current service fee based on the current service fee discount rate and the operating service fee base price; and determining the current charging price based on the operating unit electricity cost and the current service fee, so as to update the charging price of the target charging station.

[0084] It should be understood that future time periods can be discounted time periods. These discounted time periods are pre-defined time ranges within which a dynamic pricing strategy is enabled, set before the launch date. The preset update times are determined by both the discounted time periods and the strategy update frequency. The strategy update frequency defines the cycle in which service fees are updated within the aforementioned time range, such as every 15 minutes, 30 minutes, or 1 hour. From the start time of a discounted time period until its end time, all time points that meet the update frequency requirements constitute the set of preset price update times.

[0085] Understandably, on a future operating day, if the current time reaches the preset price update time, the current charging pile vacancy rate of the target charging station at that time can be obtained. Based on the current charging pile vacancy rate, the current service fee discount rate can be obtained by looking up the reference table. The current service fee = operating service fee base price × current service fee discount rate. The current charging price = operating unit electricity cost + current service fee. Thus, the charging price of the charging station for each time period on the operating day can be obtained.

[0086] This embodiment predicts the rate of change function between the utilization rate and the charging cost of operating charging piles in future time periods based on a charging pile quantity-price correlation model. Then, it determines the optimal charging pile utilization rate corresponding to the idle rate of each charging pile based on the expected charging pile utilization rate. Finally, it determines the optimal charging cost change rate under each charging pile idle rate based on the rate of change function and the optimal charging pile utilization rate. This embodiment, by incorporating the charging pile idle rate, accurately obtains the optimal charging cost change rate under each charging pile idle rate.

[0087] Reference Figure 4 , Figure 4 This is a structural block diagram of the first embodiment of the charging price update device of this application.

[0088] like Figure 4 As shown, the charging price updating device proposed in this application includes: The rate of change prediction module 10 is used to predict the optimal rate of change of charging electricity cost under the idle rate of each charging pile in the future time period according to the charging station quantity-price correlation model. The charging station quantity-price correlation model includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity cost change rate corresponding to the target charging station. The charging pile idle rate is associated with the optimal charging pile utilization rate change rate. The lookup table construction module 20 is used to calculate the optimal service fee discount rate under the idle rate of each charging pile based on the optimal charging electricity cost change rate, and to construct a lookup table between the idle rate of the charging pile and the optimal service fee discount rate. The discount rate calculation module 30 is used to look up the current service fee discount rate from the lookup table based on the current charging pile idle rate corresponding to the preset price update time. The price update module 40 is used to update the charging price of the target charging station according to the current service fee discount rate.

[0089] This embodiment predicts the optimal charging electricity rate change rate for each charging pile idle rate in future time periods based on a charging station volume-price correlation model. The model includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity rate change rate for the target charging station. The charging pile idle rate is correlated with the optimal charging pile utilization rate change rate. Then, the optimal service fee discount rate is calculated for each charging pile idle rate based on the optimal charging electricity rate change rate, and a lookup table between the charging pile idle rate and the optimal service fee discount rate is constructed. Next, the current service fee discount rate is retrieved from the lookup table based on the current charging pile idle rate at the preset price update time, and then the charging price for the target charging station is updated based on the current service fee discount rate. This embodiment predicts the lookup table between the charging pile idle rate and the optimal service fee discount rate for each future time period based on the target charging station's operating status, obtaining the optimal service fee discount rate corresponding to different charging pile idle rates. Then, the current service fee discount rate is retrieved from the lookup table in real time according to the preset price update time, and the charging price for the target charging station is dynamically updated based on the current service fee discount rate.

[0090] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this application. In practical applications, those skilled in the art can select some or all of it to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.

[0091] In addition, for technical details not described in detail in this embodiment, please refer to the charging price update method provided in any embodiment of this application, which will not be repeated here.

[0092] Based on the first embodiment of the charging price updating device described in this application, a second embodiment of the charging price updating device of this application is proposed.

[0093] In this embodiment, the charging price update device further includes a model building module, used to obtain the historical charging pile utilization rate and historical charging electricity cost of the target charging station in different historical time periods; to build a historical quantity-price data set based on the historical charging utilization rate and the historical charging electricity cost; and to build a charging station quantity-price correlation model based on the historical quantity-price data set.

[0094] Furthermore, the model building module is also used to calculate the historical utilization rate change rate for each historical period based on the historical charging pile utilization rate and the historical average utilization rate; calculate the historical charging electricity cost change rate for each historical period based on the historical charging electricity cost and the historical average charging electricity cost; and construct a historical quantity and price data set based on the historical utilization rate change rate and the historical charging electricity cost change rate.

[0095] Furthermore, the model building module is also used to determine the one-hot encoding corresponding to the time-sharing type of each historical time period; update the historical quantity-price data set based on the one-hot encoding to obtain the updated data set; fit the updated data set using the least squares method, and obtain model parameters based on the fitting result; obtain a charging station quantity-price correlation model based on the model parameters, wherein the charging station quantity-price correlation model includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity cost change rate corresponding to the target charging station.

[0096] Furthermore, the rate of change prediction module 10 is also used to predict the rate of change function between the utilization rate of the operating charging pile and the rate of change of the operating charging electricity cost for each future time period based on the charging pile quantity-price correlation model; determine the optimal rate of change of the charging pile utilization rate corresponding to the idle rate of each charging pile based on the expected charging pile utilization rate; and determine the optimal rate of change of the charging electricity cost under the idle rate of each charging pile based on the rate of change function and the optimal rate of change of the charging pile utilization rate.

[0097] Furthermore, the rate of change prediction module 10 is also used to obtain the operating service fee cost price, the basic operating service fee price, and the unit electricity cost of the target charging station in future time periods; calculate the service fee adjustment limit value for each future time period based on the operating service fee cost price, the basic operating service fee price, and the unit electricity cost; and generate a rate of change function between the rate of change of the operating charging pile utilization rate and the rate of change of the operating charging electricity cost based on the service fee adjustment limit value and the charging pile quantity-price correlation model.

[0098] Furthermore, the rate of change prediction module 10 is also used to determine the surrounding charging stations of the target charging station, and to determine the historical service fee base price of the surrounding charging stations in each historical time period; to determine the ratio of the target historical service fee base price of the target charging station in each historical time period to the surrounding charging price of the surrounding charging stations; to determine the historical service fee base price of the target charging station in each historical time period based on the surrounding historical service fee base price and the ratio; and to determine the operating service fee base price of the target charging station in each future time period based on the historical service fee base price.

[0099] Furthermore, the lookup table construction module 20 is also used to calculate the optimal service fee discount rate under each charging pile idle rate based on the basic price of the operation service fee, the electricity cost of the operation unit, and the optimal charging electricity cost change rate; and to construct a lookup table between the charging pile idle rate and the optimal service fee discount rate.

[0100] Furthermore, the price update module 40 is also used to determine the current service fee based on the current service fee discount rate and the operating service fee base price; and to determine the current charging price based on the operating unit electricity cost and the current service fee, so as to update the charging price of the target charging station.

[0101] Other embodiments or specific implementations of the charging price update device of this application can be found in the above-described method embodiments, and will not be repeated here.

[0102] This application provides a charging price updating device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the charging price updating method in the first embodiment described above.

[0103] The following is for reference. Figure 5 The diagram illustrates a structural schematic of a charging price update device suitable for implementing embodiments of this application. The charging price update device in embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 5 The updated charging price device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0104] like Figure 5As shown, the charging price update device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the charging price update device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the charging price update device to communicate wirelessly or wiredly with other devices to exchange data. Although charging price update devices with various systems are shown in the figures, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0105] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0106] The charging price updating device provided in this application, employing the charging price updating method in the above embodiments, can solve the technical problem of how to dynamically adjust the charging price of charging stations in real time and effectively. Compared with the prior art, the beneficial effects of the charging price updating device provided in this application are the same as those of the charging price updating method provided in the above embodiments, and other technical features in the charging price updating device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0107] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0108] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0109] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the charging price update method in the above embodiments.

[0110] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0111] The aforementioned computer-readable storage medium may be included in the charging price update device; or it may exist independently and not be assembled into the charging price update device.

[0112] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by a charging price updating device, the charging price updating device: predicts the optimal charging electricity rate change rate for each charging pile idle rate in future time periods based on a charging station quantity-price correlation model, wherein the charging station quantity-price correlation model includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity rate change rate corresponding to the target charging station, and the charging pile idle rate is correlated with the optimal charging pile utilization rate change rate; calculates the optimal service fee discount rate for each charging pile idle rate based on the optimal charging electricity rate change rate, and constructs a lookup table between the charging pile idle rate and the optimal service fee discount rate; searches for the current service fee discount rate in the lookup table based on the current charging pile idle rate corresponding to the preset price update time; and updates the charging price of the target charging station based on the current service fee discount rate.

[0113] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages—such as Python, Java, Smalltalk, and C++—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0114] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0115] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0116] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described method for updating charging prices, thereby solving the technical problem of how to dynamically adjust the charging prices of charging stations in real time and effectively. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the charging price updating method provided in the above embodiments, and will not be repeated here.

[0117] The above description is only a part of the embodiments of this application and does not limit the scope of protection of this application. All equivalent structural transformations made under the technical concept of this application and using the content of this application specification and drawings, or direct / indirect applications in other related technical fields, are included in the scope of protection of this application.

Claims

1. A method of updating a charging price, characterized by, The method for updating the charging price includes the following steps: The optimal charging electricity cost change rate for each charging pile idle rate in future time periods is predicted based on the charging station quantity-price correlation model. The charging station quantity-price correlation model includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity cost change rate corresponding to the target charging station. The charging pile idle rate is correlated with the optimal charging pile utilization rate change rate. Calculate the optimal service fee discount rate for each charging pile at its idle rate based on the optimal charging electricity cost change rate, and construct a comparison table between the charging pile idle rate and the optimal service fee discount rate; The current service fee discount rate is retrieved from the lookup table based on the current charging pile availability rate at the preset price update time. The charging price of the target charging station is updated based on the current service fee discount rate.

2. The method for updating charging prices as described in claim 1, characterized in that, Before predicting the optimal rate of change in charging electricity costs for each charging pile's idle rate in future time periods based on the charging station volume-price correlation model, the following is also included: Obtain the historical charging pile utilization rate and historical charging electricity cost of the target charging station for different historical time periods; Construct a historical quantity and price data set based on the historical charging utilization rate and the historical charging electricity cost; A charging station volume-price correlation model is constructed based on the aforementioned historical volume and price data set.

3. The method for updating charging prices as described in claim 2, characterized in that, The step of constructing a historical volume and price data set based on the historical charging utilization rate and the historical charging electricity cost includes: The historical utilization rate change rate for each historical period is calculated based on the historical charging pile utilization rate and the historical utilization average rate. Calculate the historical charging electricity cost change rate for each historical period based on the historical charging electricity cost and the historical average charging electricity cost; A historical quantity and price data set is constructed based on the historical utilization rate change rate and the historical charging electricity cost change rate.

4. The method for updating charging prices as described in claim 2, characterized in that, The step of constructing a charging station volume-price correlation model based on the historical volume-price data set includes: Determine the one-hot encoding corresponding to the time-division type of each historical time period; The historical price and volume data set is updated based on the unique hot encoding to obtain the updated data set; The updated dataset is fitted using the least squares method, and the model parameters are obtained based on the fitting results. Based on the model parameters, a charging station quantity-price correlation model is obtained, which includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity cost change rate of the target charging station.

5. The method for updating charging prices as described in any one of claims 1-4, characterized in that, The method of predicting the optimal charging electricity cost change rate for each charging pile idle rate in future time periods based on the charging station volume-price correlation model includes: The change rate function between the change rate of the utilization rate of the charging piles and the change rate of the charging electricity cost is predicted based on the charging pile quantity-price correlation model for future time periods. Determine the optimal rate of change in the utilization rate of each charging pile based on the expected utilization rate of the charging piles. The optimal charging cost change rate under the idle rate of each charging pile is determined based on the change rate function and the optimal charging pile utilization rate change rate.

6. The method for updating charging prices as described in claim 5, characterized in that, The rate of change function for predicting the rate of change of utilization rate of operating charging piles and the rate of change of electricity cost for operating charging piles in future time periods based on the charging pile quantity-price correlation model includes: Obtain the operating service cost price, basic operating service price, and unit electricity cost of the target charging station for each future time period; The service fee adjustment limit for each future time period is calculated based on the operating service fee cost price, the operating service fee base price, and the operating unit electricity cost. Based on the service fee adjustment limit and the charging pile quantity-price correlation model, a rate of change function is generated between the change rate of operating charging pile utilization rate and the change rate of operating charging electricity cost.

7. The method for updating charging prices as described in claim 6, characterized in that, The acquisition of the base price for the operating service fee of the target charging station in future time periods includes: Identify the surrounding charging stations of the target charging station, and determine the basic price of the surrounding historical service fees for each historical time period. Determine the percentage of the target historical service fee base price of the target charging station in each historical time period relative to the surrounding charging price of the surrounding charging stations; The historical service fee base price of the target charging station for each historical period is determined based on the surrounding historical service fee base price and the percentage. The base price for the operation service fee of the target charging station in each future period is determined based on the historical base price for service fees.

8. The method for updating charging prices as described in claim 6, characterized in that, The step of calculating the optimal service fee discount rate for each charging pile's idle rate based on the optimal charging electricity cost change rate, and constructing a comparison table between the charging pile idle rate and the optimal service fee discount rate, includes: The optimal service fee discount rate for each charging pile under the idle rate is calculated based on the base price of the operation service fee, the electricity cost per unit of operation, and the optimal charging electricity cost change rate. Construct a comparison table between the charging pile vacancy rate and the optimal service fee discount rate.

9. The method for updating charging prices as described in claim 6, characterized in that, The step of updating the charging price of the target charging station based on the current service fee discount rate includes: The current service fee is determined based on the current service fee discount rate and the base price of the operating service fee. The current charging price is determined based on the electricity cost of the operating unit and the current service fee, so as to update the charging price of the target charging station.

10. A charging price update device, characterized in that, The charging price updating device includes: The rate of change prediction module is used to predict the optimal rate of change of charging electricity cost under the idle rate of each charging pile in the future time period based on the charging station quantity-price correlation model. The charging station quantity-price correlation model includes the correspondence between the historical charging pile utilization rate change rate and the historical charging electricity cost change rate corresponding to the target charging station. The charging pile idle rate is correlated with the optimal charging pile utilization rate change rate. The lookup table construction module is used to calculate the optimal service fee discount rate under each charging pile idle rate based on the optimal charging electricity cost change rate, and to construct a lookup table between the charging pile idle rate and the optimal service fee discount rate; The discount rate calculation module is used to look up the current service fee discount rate from the lookup table based on the current charging pile idle rate corresponding to the preset price update time. The price update module is used to update the charging price of the target charging station based on the current service fee discount rate.

11. A device for updating charging prices, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the method for updating the charging price as claimed in any one of claims 1 to 9.

12. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the method for updating the charging price as described in any one of claims 1 to 9.

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