Charging pile charging strategy determination method and device, equipment and medium

Abstract

The invention relates to the technical field of charging piles, in particular to a charging pile charging strategy determination method and device, equipment and a medium. The method comprises the steps that the area scale (including the number of charging piles and construction cost) and the area position of a charging area are acquired, the user quantity, namely the number of charging vehicles, of each sub-period in a future period is predicted based on the number of the charging piles and the area position, the electricity purchasing degree is further predicted, and when the charging standard is set, the charging time is shortened. And the busy degree of the sub-cycles is considered, so that the charging is more reasonable. The sub-period with high busy degree corresponds to a higher charging standard, which is helpful for motivating users to charge in off-peak periods, the busy degree of each sub-period is calculated, a charging sub-strategy is formulated according to the busy degree, and a part of users sensitive to price are guided through a price lever to change charging habits and charge in low-price off-peak periods, so that the charging efficiency is improved. The charging queuing phenomenon in the peak period is avoided to a certain extent, and the credibility and the satisfaction degree of the user are enhanced.

Description

Technical Field

[0001] The present application relates to the technical field of charging piles, and in particular to a method, device, equipment and medium for determining a charging strategy for a charging pile. Background Art

[0002] With the booming development of my country's electric vehicle industry, the market share of electric vehicles continues to rise. This trend has directly led to the rapid development of various charging stations as key infrastructure. Charging piles, as an important carrier for electric vehicle energy replenishment, have immeasurable value in promoting the widespread popularization and in-depth application of electric vehicles through their extensive layout and efficient operation.

[0003] These charging piles are often clustered to build convenient and efficient charging areas. Most of the charging areas are located in residential areas, parking lots of shopping malls and office buildings, and highway service areas with high traffic flow, accurately matching users' daily travel and long-distance travel needs. However, in these popular areas, the fluctuation of charging demand is particularly significant: during a specific period of time, electric vehicles flock to compete for charging, resulting in resource shortages and frequent queues. Some users even miss the opportunity to charge, which to some extent weakens the charging experience of electric vehicle users in the charging area. Summary of the invention

[0004] In order to improve the charging experience of electric vehicle users in a charging area, the present application provides a method, device, equipment and medium for determining a charging strategy for a charging pile.

[0005] In a first aspect, the present application provides a method for determining a charging strategy for a charging pile, which adopts the following technical solution: A method for determining a charging strategy for a charging pile, comprising: Obtaining the regional scale and regional location of the charging area, wherein the regional scale includes the number of charging piles and construction costs; Based on the number of charging piles and the location of the area, determining the number of users corresponding to each sub-period of the charging area in the future cycle, the number of users being the number of charging vehicles charged using the charging piles in a sub-period of the future cycle; Based on the number of users, predict the amount of electricity purchased by the charging area in each sub-period in the future period; Predicting the maintenance cost of the charging area in a future period and the grid load distribution corresponding to the future period, and determining the basic cost corresponding to the charging area based on the grid load distribution, the purchased electricity corresponding to each sub-period and the maintenance cost; Determining the weights of the power grid load distribution and the user quantity; Based on the load distribution of the power grid and the weights of the user quantities, the busyness corresponding to each sub-period is calculated; Based on the busyness corresponding to each sub-cycle, the construction cost and the basic cost, the billing standard corresponding to each sub-cycle is determined, and the charging sub-strategy corresponding to each sub-cycle in the future cycle is determined, and the corresponding charging operation is performed based on the billing standard and the charging sub-strategy corresponding to each sub-cycle.

[0006] By adopting the above technical solution, by obtaining the regional scale of the charging area (including the number of charging piles and construction costs) and the regional location, the basic information of the charging area can be accurately grasped, which is helpful for the subsequent formulation of more refined management and operation strategies. Predicting the number of users in each sub-cycle in the future cycle based on the number of charging piles and regional location, that is, the number of charging vehicles, helps to prepare resources in advance, avoid imbalance between supply and demand, and improve user satisfaction. Further predicting the number of purchased electricity will help to reasonably arrange electricity procurement, reduce costs, and ensure the stability of electricity supply. When setting the billing standard, the busyness of the sub-cycle is taken into account to make the billing more reasonable. Sub-cycles with high busyness correspond to higher billing standards, which helps to motivate users to charge during non-peak hours. By calculating the busyness of each sub-cycle and formulating charging sub-strategies accordingly, dynamic monitoring and adjustment of the operating status of the charging area is achieved. Through price leverage, some price-sensitive users are guided to change their charging habits and charge during low-price periods. To a certain extent, charging queues during peak hours are avoided, the charging demand churn rate is reduced and user satisfaction is improved. The charging operation is closely related to the billing standards and charging sub-strategies, which ensures the fairness and transparency of charging and enhances user trust and satisfaction.

[0007] In a possible implementation, determining the number of users corresponding to each sub-period in the charging area in a future period based on the number of charging piles and the area location includes: Obtaining a charging demand source corresponding to the regional location, where the charging demand source is used to characterize vehicles passing through the regional location and having charging demand; Determine whether the type corresponding to the charging demand source is a stable type, so as to determine whether there are primary users and secondary users in the regional location; If there are primary users and secondary users in the area, then historical charging data corresponding to the charging area is obtained, wherein the historical charging data includes the number of historical charging users corresponding to each historical period and the historical charging times and historical charging times corresponding to each historical charging user; Based on the historical charging data, dividing the historical period into a plurality of historical sub-periods; The future cycle is divided into multiple sub-cycles based on the start and end times corresponding to each historical sub-cycle, and the number of users corresponding to each sub-cycle in the charging area in the future cycle is determined based on the historical number of charging users corresponding to each historical sub-cycle.

[0008] By adopting the above technical solution, by obtaining the source of charging demand corresponding to the regional location, determining whether the type of charging demand source is a stable type, it is helpful to distinguish between primary users and secondary users. Primary users may be a fixed user group that frequently charges in the area, while secondary users may be temporary users who occasionally pass by, which helps to analyze user behavior more finely and formulate more targeted operation strategies. Obtaining historical charging data corresponding to the charging area, including the historical number of charging users, historical charging times, and historical charging times, provides a reliable data basis for predicting future user volume. Dividing both historical cycles and future cycles into multiple sub-cycles helps to more finely analyze the charging needs of users in different time periods, and can also provide important references for resource allocation, power procurement, and charging strategies in charging areas.

[0009] In a possible implementation, based on the historical charging data, the historical period is divided into a plurality of historical sub-periods, including: From the historical charging users, historical charging users whose historical charging times are greater than a charging times threshold are selected as first historical charging users, and historical charging users whose historical charging times have a regularity greater than a regularity threshold are selected from the historical charging users as second historical charging users; Determine the first historical charging user and the second historical charging user as primary users, and determine the historical charging users other than the primary user as secondary users; The historical period is divided into a plurality of historical sub-periods based on the historical charging times corresponding to the primary user and the historical charging times corresponding to the secondary user.

[0010] By adopting the above technical solution, users with a large number of historical charging times and regular charging times are screened out as main users. The behavior patterns of these users are more stable and representative. Dividing historical sub-periods based on the data of these users can more accurately reflect the cyclical changes in electric vehicle charging behavior, providing a more reliable basis for subsequent analysis and prediction. At the same time, understanding the distribution of charging demand in different historical sub-periods will help charging station operators to better plan the layout and capacity of charging facilities to meet the charging needs in different time periods. They can also adjust the charging price strategy or optimize the charging service process according to the charging behavior characteristics in the historical sub-periods, thereby improving user experience and operational efficiency.

[0011] In a possible implementation, determining the basic fee corresponding to the charging area based on the grid load distribution, the purchased electricity kilowatt-hours corresponding to each sub-period, and the maintenance fee includes: Based on the load distribution of the power grid, the future time period is divided into peak period, normal period and valley period; Based on the purchased electricity kilowatt-hours corresponding to each sub-period, a first purchased electricity kilowatt-hour corresponding to the peak period, a second purchased electricity kilowatt-hour corresponding to the normal period, and a third purchased electricity kilowatt-hour corresponding to the valley period are calculated; Predict the unit electricity prices corresponding to the peak period, normal period and valley period in the future cycle; Based on Formula 1: M = M1 + C, the basic fee corresponding to the charging area is calculated; Wherein, M is the basic cost of the charging area in the future cycle, M1 is the electricity purchase cost of the charging area in the future cycle, and C is the maintenance cost; Among them, based on formula 2: M1=∑ t∈所有时段 ((E t,p *P p +E t,N *P N +E t,L *P L )*F(U t )) to predict the electricity purchase cost of the charging area in the future period; Among them, M1 is the electricity purchase cost of the charging area in the future cycle, E t,p is the first purchased electricity quantity, E t,N is the second purchased electricity quantity, E t,L is the third purchased electricity quantity, P p is the unit electricity price during peak hours, P N is the unit electricity price during normal periods, P L is the unit electricity price during the off-peak period, F(U t ) is a discount or markup factor related to the number of users; Based on formula 3: Calculate discount or markup factors related to user volume; Among them, F(U t ) is the discount or markup factor related to the number of users, U threshold is the first threshold corresponding to the number of users, U max is the second threshold corresponding to the number of users.

[0012] By adopting the above technical solution, by dividing the future time period into peak period, normal period and valley period, and calculating the purchased electricity in each period respectively, the electricity purchase cost of the charging area can be estimated more accurately, and by introducing discounts or price increase factors related to the number of users, the solution can encourage users to charge at different times, thereby balancing the load of the power grid. When the number of users in the charging area is small, discounts are given to attract users; when the number of users is too large, the charging demand is limited by price increases to avoid excessive pressure on the power grid, which helps to achieve a reasonable distribution of charging demand and a smooth operation of the power grid load.

[0013] In a possible implementation, when there are no primary users and secondary users in the regional location, determining the number of users corresponding to each sub-period in the charging area in the future period based on the number of charging piles and the regional location includes: Based on the number of charging piles, at least one target charging area is selected from the remaining charging areas, the number of charging piles in the target charging area is the same as the number of charging piles corresponding to the charging area, and there are no primary users and secondary users in the target charging area; Acquire first historical data corresponding to the target charging area and second historical data corresponding to the charging area, wherein the first historical data includes historical usage time of each charging pile in the target charging area, and the second historical data includes historical usage time of each charging pile in the charging area; Dividing the future period into at least two sub-periods based on each historical usage moment included in the first historical data and each historical usage moment included in the second historical data; Determine the date label corresponding to each sub-period; Based on the date tag corresponding to each sub-period and the historical usage time of each charging pile, the number of users corresponding to each sub-period in the charging area in the future period is determined.

[0014] By adopting the above technical solution, by screening out target charging areas with the same number of charging piles and no primary and secondary users from the remaining charging areas, a cross-regional data ratio is achieved, which helps to discover charging behavior patterns under similar conditions and provides a valuable reference for predicting the number of users in the current charging area. Based on the historical usage moments, the future cycle is divided into at least two sub-cycles, and the date label of each sub-cycle is determined, which helps to more accurately capture the periodic changes in charging behavior and thus more accurately predict the number of users. And by combining the date label of each sub-cycle with the historical usage moments of the charging piles, the scheme can more comprehensively consider various factors that affect the number of users, such as the difference between weekdays and weekends, the impact of holidays, etc. This comprehensive consideration helps to improve the accuracy of user volume prediction.

[0015] In a possible implementation, determining the weights of the power grid load distribution and the user quantity includes: Based on the grid load sub-distribution corresponding to each sub-period in the future period, a first judgment matrix is ​​established; Based on the amount of users corresponding to each sub-period, establishing a second judgment matrix; The maximum eigenvalue and eigenvector corresponding to the first judgment matrix and the second judgment matrix are calculated to obtain the weights of the power grid load distribution and the user quantity.

[0016] By adopting the above technical solution, the weights are determined by establishing a first judgment matrix (based on the sub-distribution of grid load) and a second judgment matrix (based on the number of users), and calculating the eigenvectors corresponding to the respective maximum eigenvalues. This is scientific and objective, avoids the deviation caused by subjective judgment, and makes the determination of weights more accurate and reliable, which helps to more comprehensively evaluate their impact on the operation of the charging area and provide more comprehensive information support for subsequent decision-making.

[0017] In a possible implementation, based on the busyness corresponding to each sub-period, the completion fee, and the basic fee, determining the charging standard corresponding to each sub-period includes: Determine the estimated usage time corresponding to the charging area; Determine the construction sub-cost corresponding to each sub-period in the future period based on the estimated usage time and the construction cost; Determine the proportion of the construction cost and basic cost allocated to each sub-period to obtain the cost allocation factor corresponding to each sub-period; Based on formula 4: Get the billing standard corresponding to each sub-period; Among them, S i is the cost per kWh of electricity corresponding to the sub-period, E i The amount of electricity purchased corresponding to the sub-period, S base is the sum of the basic cost corresponding to the sub-period and the sub-cost of completion, F a F is the busyness level. b is the cost allocation factor, α and β are both constants.

[0018] By adopting the above technical solution, by considering the busyness, construction cost and basic cost of each sub-cycle, it can more accurately reflect the cost changes of charging services in different time periods, thereby providing users with more fair and reasonable charging costs. As an important factor in the billing standard, busyness can encourage users to charge during non-peak hours, thereby balancing the load of the power grid and reducing the pressure during peak hours.

[0019] In a second aspect, the present application provides a device for determining a charging strategy for a charging pile, which adopts the following technical solution: A device for determining a charging strategy for a charging pile, comprising: An acquisition module, used to acquire the regional scale and regional location of the charging area, wherein the regional scale includes the number of charging piles and the construction cost; A user quantity determination module, configured to determine the user quantity corresponding to each sub-period of the charging area in a future cycle based on the number of charging piles and the area location, wherein the user quantity is the number of charging vehicles charged using the charging piles in a sub-period of the future cycle; A prediction module, configured to predict the amount of electricity purchased in each sub-period of the charging area in a future period based on the amount of users; A cost determination module, used to predict the maintenance cost of the charging area in the future period and the grid load distribution corresponding to the future period, and determine the basic cost corresponding to the charging area based on the grid load distribution, the purchased electricity corresponding to each sub-period and the maintenance cost; A weight determination module, used to determine the weights of the power grid load distribution and the user quantity; A calculation module, configured to calculate the busyness corresponding to each sub-period based on a first weight corresponding to the power grid load distribution and a second weight corresponding to the user quantity; The strategy determination module is used to determine the billing standard corresponding to each sub-cycle based on the busyness corresponding to each sub-cycle, the construction cost and the basic cost, so as to obtain the charging sub-strategy corresponding to each sub-cycle in the future cycle, and perform corresponding charging operations based on the billing standard and the charging sub-strategy corresponding to each sub-cycle, wherein the greater the busyness of the sub-cycle, the higher the corresponding billing standard.

[0020] In a third aspect, the present application provides an electronic device, which adopts the following technical solution: An electronic device, comprising: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the charging pile charging strategy determination method described in the first aspect above.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium includes: a computer program that can be loaded by a processor and execute the method for determining a charging strategy for a charging pile described in the first aspect above.

[0022] In summary, the present application includes the following beneficial technical effects: By obtaining the regional scale (including the number of charging piles and construction costs) and regional location of the charging area, the basic information of the charging area can be accurately grasped, which is helpful for the subsequent formulation of more refined management and operation strategies. Predicting the number of users in each sub-cycle in the future cycle based on the number of charging piles and regional location, that is, the number of charging vehicles, helps to prepare resources in advance, avoid imbalances between supply and demand, and improve user satisfaction. Further predicting the number of purchased electricity will help to reasonably arrange electricity procurement, reduce costs, and ensure the stability of electricity supply. When setting the billing standard, the busyness of the sub-cycle is taken into account to make the billing more reasonable. Sub-cycles with high busyness correspond to higher billing standards, which helps to motivate users to charge during non-peak hours. By calculating the busyness of each sub-cycle and formulating charging sub-strategies accordingly, dynamic monitoring and adjustment of the operating status of the charging area is achieved. Through price leverage, some price-sensitive users are guided to change their charging habits and charge during low-price periods. To a certain extent, charging queues during peak hours are avoided, the charging demand churn rate is reduced and user satisfaction is improved. The charging operation is closely related to the billing standards and charging sub-strategies, which ensures the fairness and transparency of charging and enhances user trust and satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 This is a schematic diagram of the connection and interaction between an electronic device and a charging pile in a charging area provided by an embodiment of the present application; Figure 2 It is a flow chart of a method for determining a charging strategy for a charging pile provided in an embodiment of the present application; Figure 3 It is a block diagram of a device for determining a charging strategy for a charging pile provided in an embodiment of the present application; Figure 4 It is a schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The following is combined with Figure 1 -Attached Figure 4 This application is described in further detail.

[0025] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0026] In order to facilitate understanding of the technical solution proposed in this application, several elements introduced in the description of this application are first introduced here. It should be understood that the following introduction is only for the convenience of understanding these elements, so as to understand the content of the embodiments of this application, and does not necessarily cover all possible situations.

[0027] The charging area is an area containing multiple charging piles, which is generally located in residential areas, shopping malls, office buildings or highway service areas, so as to provide power for new energy vehicles (hereinafter referred to as charging vehicles).

[0028] Charging piles are devices that provide DC or AC power to charging vehicles. They can be fixed on the ground. The input end of the charging pile is connected to the AC power grid, and the output end is connected to the electric vehicle through a charging plug to achieve the transmission of electrical energy. Most charging piles have multiple functions such as display, card swiping, billing and charging information printing. The owner of the charging vehicle can select the charging time by scanning the code or swiping the card.

[0029] Charging areas are often precisely matched to users' daily travel and long-distance travel needs. However, in these popular areas, the fluctuation of charging demand is particularly significant: during a specific period of time, charging vehicles flock to compete for charging, causing resource shortages and frequent queues. Some users even miss the opportunity to charge, which to some extent weakens the charging experience of charging vehicle users in the charging area.

[0030] In view of this, an embodiment of the present application provides a method for determining a charging strategy for a charging pile, such as Figure 1 As shown, the electronic device establishes connections with each charging pile in the charging area respectively, and the electronic device can obtain the charging information of each charging pile. The electronic device can also control the charging billing information corresponding to each charging pile.

[0031] The present application embodiment provides a method for determining a charging strategy for a charging pile, such as Figure 2 As shown, the method provided in the embodiment of the present application is performed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application. The method includes steps S201-S207, wherein: Step S201, obtaining the regional scale and regional location of the charging area.

[0032] Among them, the regional scale includes the number of charging piles and the construction costs.

[0033] For any charging area, the charging location, construction cost and number of charging piles corresponding to the charging area are all stored in the charging database, and the charging scale and regional location of the charging area to be queried can be obtained from the charging database.

[0034] Step S202: Based on the number of charging piles and the regional location, determine the number of users corresponding to each sub-period in the charging area in the future period.

[0035] Among them, the user volume is the number of charging vehicles charged by charging piles in a sub-period of the future cycle. The future cycle can be one day or the next twelve hours, which is not limited in the embodiment of the present application. Specifically, the future cycle can be evenly divided into multiple sub-periods, or based on the number of charging piles and the regional location, a curve of the user volume corresponding to each charging area in each historical cycle over time can be obtained, and according to each curve, the cycle is divided into a time range where users appear in a concentrated manner and a time range where users do not appear in a concentrated manner, so as to divide the future cycle into multiple sub-periods. More specifically, based on the curve of the user volume corresponding to each sub-period over time, the time range where most of the user volume is located is identified, and the future cycle is divided into multiple sub-periods according to the time range. Exemplarily, the future period is 6:00:00-18:00:00, and most of the users are in the time range of 8:00:00-9:00:00 and 14:00:00-16:00:00. Then the future period is divided into five sub-periods, namely 6:00:00-8:00:00, 8:00:00-9:00:00, 9:00:00-14:00:00, 14:00:00-16:00:00 and 16:00:00-18:00:00.

[0036] After obtaining the curve of the user volume corresponding to each charging area in each historical period over time, each historical period is divided into multiple historical sub-periods in the form of dividing the future period into multiple sub-periods, and the historical user volume corresponding to each historical sub-period is obtained. The average value of the historical user volume corresponding to the same sub-period is calculated as the user volume corresponding to each sub-period in the future period.

[0037] Step S203: Based on the number of users, predict the purchased electricity quantity corresponding to each sub-period in the charging area in the future period.

[0038] Each charging vehicle corresponds to a battery capacity, which is the amount of electricity required to fully charge the charging vehicle. The average battery capacity of the charging vehicles is obtained as the battery capacity of each charging vehicle.

[0039] Specifically, based on the battery capacity of each charging vehicle and the number of users corresponding to each sub-cycle in the future cycle, the amount of electricity provided to the charging vehicle corresponding to each sub-cycle is calculated, thereby obtaining the amount of electricity purchased corresponding to each sub-cycle in the charging area in the future cycle.

[0040] Step S204: predict the maintenance cost of the charging area in the future period and the grid load distribution corresponding to the future period, and determine the basic cost corresponding to the charging area based on the grid load distribution, the purchased electricity corresponding to each sub-period and the maintenance cost.

[0041] Among them, the grid load distribution can be expressed in the form of a grid load distribution curve, which is a graphical representation of the changes of various types of power loads in the power system over time. Among them, the horizontal axis of the grid load distribution curve usually represents time. In the load curve, time can be divided into hours, half hours or shorter time intervals to show the changes of power load over time. The vertical axis of the grid load distribution curve represents the load value, which usually refers to active power or reactive power. Active power is the power actually consumed by the grid, which is used to do work, such as driving motors, heaters and other equipment; reactive power is the power used to establish and maintain electromagnetic fields in the grid. It does not directly consume energy, but it is crucial to the stable operation of the grid. The load value of the vertical axis shows the load situation of the grid at a specific point in time, which is an important basis for the dispatching and planning of the power system.

[0042] Specifically, multiple historical load distribution curves corresponding to regional locations in the future period are obtained, and the ARIMA model is used to find the rules in the time series using multiple historical load distribution curves, and the power grid load distribution curve in the future period is predicted to obtain the power grid load distribution corresponding to the future period. Among them, the time interval between the historical period and the future period corresponding to each historical load distribution curve is not greater than the time interval threshold.

[0043] The process of predicting the maintenance costs of the charging area in the future cycle can be: obtain the damage records of the charging piles and the maintenance costs corresponding to each damage, calculate the damage frequency of each charging pile (number of damages / total number of days), and based on the average damage frequency = Σ(charge pile damage frequency) / number of charging piles, calculate the average damage frequency of all charging piles to obtain the average damage frequency of the charging piles. Based on the average maintenance cost = Σ(maintenance cost) / number of maintenance times, average all maintenance costs to obtain the average maintenance cost. Based on the number of charging piles in the charging area, the predicted number of damages in the future cycle is calculated, and based on the predicted number of damages = average damage frequency * number of charging piles * number of days in the future cycle and maintenance cost = predicted number of damages * average maintenance cost, the maintenance cost of the charging area in the future cycle is calculated.

[0044] Furthermore, the electricity price table corresponding to the grid load distribution is obtained, and the electricity purchase fee corresponding to each sub-period is calculated based on the purchased electricity kilowatt-hours corresponding to each sub-period and the grid load distribution corresponding to each sub-period, and the electricity purchase fee corresponding to each sub-period is summed to obtain the electricity purchase fee of the charging area in the future period. Furthermore, based on the electricity purchase fee and maintenance fee of the charging area in the future period, the basic fee corresponding to the charging area is obtained.

[0045] Step S205: Determine the weights of the grid load distribution and the number of users.

[0046] The analytic hierarchy process (AHP) can be used to determine the weights of the grid load distribution and the number of users. Specifically, a hierarchical model is constructed, the target layer is to determine the target as "assessing the busyness of the grid sub-cycle", the criterion layer is to set two main criteria, where criterion A is the grid load distribution and criterion B is the number of users, and different sub-cycles are used as scheme layer elements.

[0047] For each criterion (A and B) and the elements between the scheme layer, a judgment matrix is ​​constructed. Constructing the judgment matrix of criterion A (grid load distribution): Compare the load fluctuations corresponding to different sub-periods, and use the 1-9 scaling method to construct the judgment matrix.

[0048] Construct the judgment matrix of criterion B (user volume): compare the relative importance of different sub-periods in terms of user volume, also using the 1-9 scale method. The relative importance is based on the historical user volume in different sub-periods. The more historical user volume, the greater the importance of the sub-period.

[0049] For each judgment matrix, the eigenvalue method is used to calculate the maximum eigenvalue and eigenvector corresponding to each judgment matrix. The elements of the eigenvector are the weights of the corresponding sub-periods. The weights are normalized so that the sum of the weights of all sub-periods under each criterion is 1. According to the relative importance of the criterion layer (A and B), the total weights (for example, A: 0.6, B: 0.4) are assigned to criteria A and B to obtain the weights of the grid load distribution and the number of users.

[0050] Step S206: The power grid load distribution and the weights of the user quantities are used to calculate the busyness corresponding to each sub-period.

[0051] The busyness is used to characterize the energy supply tension in the charging area. The tighter the energy supply, the busier the corresponding busyness.

[0052] Specifically, the collected grid load data and user volume data of each sub-cycle are standardized to eliminate dimensional differences. Then, the weight of each sub-cycle is multiplied by the standardized grid load and user volume data, and the grid load weighted value and user volume weighted value of each sub-cycle are added to obtain the busyness value of the sub-cycle.

[0053] Step S207: Based on the busyness, construction cost and basic cost corresponding to each sub-cycle, determine the billing standard corresponding to each sub-cycle, determine the charging sub-strategy corresponding to each sub-cycle in the future cycle, and perform corresponding charging operations based on the billing standard and charging sub-strategy corresponding to each sub-cycle.

[0054] The busier the sub-cycle is, the higher the corresponding charging standard is, and the charging standard is the fee charged after providing unit electricity.

[0055] Specifically, the average usage time of each charging area is obtained to obtain the estimated usage time corresponding to the charging area, and the construction sub-cost corresponding to the future period is calculated based on the estimated usage time and the construction cost.

[0056] Further, based on the construction sub-cost and basic cost corresponding to the future cycle, the cost of the charging area in the future cycle is obtained, and the profit rate corresponding to the charging area is obtained. Based on the cost and profit rate in the future cycle, and based on income = profit rate * purchased electricity + cost, the income in the future cycle is obtained. Among them, the profit rate is the ratio of the difference between the cost and the cost collected after providing a unit amount of electric energy to the cost. Specifically, based on the busyness corresponding to each sub-cycle, the profit rate corresponding to each sub-cycle is determined, and based on the profit rate corresponding to each sub-cycle and the purchased electricity corresponding to each sub-cycle, the income in the future cycle is obtained. More specifically, based on the profit rate corresponding to each sub-cycle = the busyness corresponding to the sub-cycle / Σ(the busyness corresponding to each sub-cycle)*, the profit rate corresponding to each sub-cycle is calculated, and then based on the sub-income corresponding to each sub-cycle = the profit rate corresponding to the sub-cycle * the purchased electricity corresponding to the sub-cycle, the sub-income corresponding to each sub-cycle is obtained; based on the sub-cost corresponding to each sub-cycle = sub-cycle / future cycle * the cost of the charging area in the future cycle, the sub-cost corresponding to each sub-cycle is obtained. Furthermore, for each sub-period, the billing standard corresponding to the sub-period = (sub-expenditure + sub-income) / the number of kilowatt-hours of electricity purchased corresponding to the sub-period.

[0057] After obtaining the billing standard corresponding to each sub-cycle, the electronic device generates a charging sub-strategy including the start and end time of each sub-cycle and the billing standard corresponding to each cycle, and sends instructions to each charging pile in the charging area to control the charging pile to charge according to the corresponding charging sub-strategy.

[0058] The embodiment of the present application provides a method for determining a charging strategy for a charging pile. By obtaining the regional scale (including the number of charging piles and construction costs) and regional location of the charging area, it is possible to accurately grasp the basic information of the charging area, which is helpful for the subsequent formulation of more refined management and operation strategies. Predicting the number of users in each sub-cycle in the future cycle based on the number of charging piles and regional location, that is, the number of charging vehicles, helps to prepare resources in advance, avoid imbalances between supply and demand, and improve user satisfaction. Further predicting the number of purchased electricity will help to reasonably arrange electricity procurement, reduce costs, and ensure the stability of electricity supply. When setting the billing standard, the busyness of the sub-cycle is taken into account to make the billing more reasonable. Sub-cycles with high busyness correspond to higher billing standards, which helps to motivate users to charge during non-peak hours. By calculating the busyness of each sub-cycle and formulating charging sub-strategies accordingly, dynamic monitoring and adjustment of the operating status of the charging area is achieved. Through price leverage, some price-sensitive users are guided to change their charging habits and charge during low-price periods. To a certain extent, charging queues during peak hours are avoided, the charging demand churn rate is reduced and user satisfaction is improved. The charging operation is closely related to the billing standards and charging sub-strategies, which ensures the fairness and transparency of charging and enhances user trust and satisfaction.

[0059] A possible implementation of the embodiment of the present application is that in the above step S102, based on the number of charging piles and the regional location, determining the number of users corresponding to each sub-period in the charging area in the future period includes: Obtaining a charging demand source corresponding to a regional location, where the charging demand source is used to characterize vehicles passing through the regional location and having charging demand; Determine whether the type corresponding to the charging demand source is a stable type to determine whether there are primary users and secondary users in the regional location; If there are primary users and secondary users in the area, the historical charging data corresponding to the charging area is obtained, and the historical charging data includes the number of historical charging users corresponding to each historical period and the historical charging times and historical charging times corresponding to each historical charging user; Based on the historical charging data, the historical cycle is divided into multiple historical sub-cycles; Based on the start and end times corresponding to each historical sub-cycle, the future cycle is divided into multiple sub-cycles, and based on the historical number of charging users corresponding to each historical sub-cycle, the number of users corresponding to each sub-cycle in the charging area in the future cycle is determined.

[0060] When the charging area is located near places such as residential areas, shopping malls or office buildings, since there is a fixed flow of people in these places, the vehicles charging in the charging area are also relatively fixed. Therefore, the charging demand source corresponding to the charging area can be determined based on the regional location of the charging area to predict the number of users corresponding to each sub-period of the charging area in the future cycle. Specifically, based on the regional location corresponding to the charging area, the charging demand source corresponding to the regional location is obtained, and it is determined whether the type corresponding to the charging demand source is a stable type to determine whether there are primary users and secondary users in the regional location, that is, when the type corresponding to the charging demand source is a stable type, there are primary users and secondary users in the regional location; when the type corresponding to the charging demand source is an unstable type, there are no primary users or secondary users in the regional location. More specifically, it is obtained whether there is a place with a fixed flow of people within a certain range from the regional location. If so, it is determined that the type of the charging demand source corresponding to the regional location is a stable type; if not, it is determined that the type of the charging demand source corresponding to the regional location is an unstable type.

[0061] Furthermore, if there are primary users and secondary users in the regional location, the historical charging data of the charging area is obtained, including the number of charging users in each historical period, the number of charging times of each user, and the charging time. The historical data is then divided into multiple historical sub-periods according to time (such as days and hours) to analyze the charging behavior patterns in different time periods, and the future period is also divided into corresponding sub-periods according to the start and end times of the historical sub-periods.

[0062] Furthermore, the number of users in each historical sub-period is statistically analyzed to identify the changing trend of the number of users. Based on the historical data, a prediction model is constructed and trained to obtain a trained prediction model. The time parameters of the future period are input into the trained prediction model to obtain the predicted number of users corresponding to each sub-period output by the prediction model. For example, the ARIMA model, LSTM neural network, etc. can be used to predict the number of users in each future sub-period.

[0063] A possible implementation of the embodiment of the present application, in the above embodiment, based on the historical charging data, the historical cycle is divided into multiple historical sub-cycles, including: From the historical charging users, historical charging users whose historical charging times are greater than a charging times threshold are selected as first historical charging users, and historical charging users whose historical charging times have a regularity greater than a regularity threshold are selected from the historical charging users as second historical charging users; Determine the first historical charging user and the second historical charging user as primary users, and determine the historical charging users other than the primary user as secondary users; The historical period is divided into a plurality of historical sub-periods based on the historical charging times corresponding to the primary user and the historical charging times corresponding to the secondary user.

[0064] Specifically, the historical charging data is traversed to obtain the number of charging times of each historical charging user, and users whose charging times are greater than the charging times threshold (e.g., charging times greater than 5 times per month) are selected as the first historical charging users. For each historical charging user, its historical charging time is analyzed, and the standard deviation of the charging time is calculated to obtain the regularity of the historical charging user. Furthermore, after obtaining the regularity of each historical charging user, users whose regularity is greater than the regularity threshold (e.g., the standard deviation is less than the corresponding threshold) are selected as the second historical charging users.

[0065] The first historical charging user and the second historical charging user are combined to obtain the main user set, and the remaining historical charging users are determined as secondary users. The historical charging time of the main users is statistically analyzed to identify the main charging time periods (such as 7 pm to 10 pm, 8 am to 10 am, etc.), and the historical period is divided into multiple historical sub-periods based on the distribution of the main users' charging time periods.

[0066] A possible implementation of the embodiment of the present application, in the above embodiment, based on the load distribution of the power grid, the purchased electricity corresponding to each sub-period and the maintenance cost, the basic cost corresponding to the charging area is determined, including: Based on the load distribution of the power grid, the future time period is divided into peak period, normal period and valley period; Based on the purchased electricity kilowatt-hours corresponding to each sub-period, a first purchased electricity kilowatt-hour corresponding to the peak period, a second purchased electricity kilowatt-hour corresponding to the normal period, and a third purchased electricity kilowatt-hour corresponding to the valley period are calculated; Predict the unit electricity prices corresponding to the peak period, normal period and valley period in the future cycle; Based on Formula 1: M = M1 + C, the basic fee corresponding to the charging area is calculated; Among them, M is the basic cost of the charging area in the future cycle, M1 is the electricity purchase cost of the charging area in the future cycle, and C is the maintenance cost; Among them, based on formula 2: M1=∑ t∈所有时段 ((E t,p *P p +E t,N *P N +E t,L *P L )*F(U t )) to predict the electricity purchase cost of the charging area in the future cycle; Among them, M1 is the electricity purchase cost of the charging area in the future cycle, E t,pis the first purchased electricity quantity, E t,N is the second purchased electricity quantity, E t,L is the third purchased electricity quantity, P p is the unit electricity price during peak hours, P N is the unit electricity price during normal periods, P L is the unit electricity price during the off-peak period, F(U t ) is a discount or markup factor related to the number of users; Based on formula 3: Calculate discount or markup factors related to user volume; Among them, F(U t ) is the discount or markup factor related to the number of users, U threshold is the first threshold corresponding to the number of users, U max is the second threshold corresponding to the number of users.

[0067] Among them, peak time period: the time period when the load is higher than the average load by a certain percentage (such as more than 120% of the average load). Normal time period: the time period when the load is between the peak time period and the valley time period. Valley time period: the time period when the load is lower than the average load by a certain percentage (such as lower than 80% of the average load). Specifically, after obtaining the load distribution of the power grid in the future cycle, the future time period is divided into peak time period, normal time period and valley time period, and based on the overlapping time period of the sub-cycle with the peak time period, normal time period and valley time period and the purchased electricity kilowatt-hour corresponding to each sub-cycle, the first purchased electricity kilowatt-hour corresponding to the peak time period, the second purchased electricity kilowatt-hour corresponding to the normal time period and the third purchased electricity kilowatt-hour corresponding to the valley time period are obtained. More specifically, the first purchased electricity number = the duration corresponding to the overlapping time period of the sub-cycle and the peak time period / the duration corresponding to the sub-cycle * the purchased electricity number corresponding to the sub-cycle. Similarly, the second purchased electricity number = the duration corresponding to the overlapping time period of the sub-cycle and the normal time period / the duration corresponding to the sub-cycle * the purchased electricity number corresponding to the sub-cycle. The third purchased electricity number = the duration corresponding to the overlapping time period of the sub-cycle and the valley time period / the duration corresponding to the sub-cycle * the purchased electricity number corresponding to the sub-cycle.

[0068] The unit electricity prices corresponding to the peak period, normal period and valley period in the current cycle are obtained, and used as the unit electricity prices corresponding to the peak period, normal period and valley period in the future cycle respectively, so as to obtain the predicted unit electricity prices corresponding to the peak period, normal period and valley period in the future cycle.

[0069] Furthermore, based on Formula 1: M=M1+C, the basic cost corresponding to the charging area is calculated, where M is the basic cost of the charging area in the future cycle, M1 is the electricity purchase cost of the charging area in the future cycle, and C is the maintenance cost.

[0070] Among them, the electricity purchase cost of the charging area in the future cycle can be based on Formula 2: M1 = ∑ t∈所有时段((E t,p *P p +E t,N *P N +E t,L *P L )*F(U t )) is predicted. Among them, M1 is the electricity purchase cost of the charging area in the future cycle, E t,p is the amount of electricity purchased during peak hours, E t,N E is the amount of electricity purchased during normal periods, t,L P is the amount of electricity purchased during off-peak hours. p is the unit electricity price during peak hours, P N is the unit electricity price during normal periods, P L is the unit electricity price during the off-peak period, F(U t ) is a discount or markup factor related to the number of users.

[0071] The discount or price increase factor related to the user volume in Formula 2 can be based on Formula 3: Calculated. Among them, F(U t ) is the discount or markup factor related to the number of users, U threshold is the first threshold corresponding to the number of users, U max The first threshold is the lower limit of the number of users, and the second threshold is the upper limit of the number of users. It can be a value input by the receiving manager or can be set according to actual conditions, which is not limited in the present embodiment of the application.

[0072] A possible implementation of the embodiment of the present application is to determine the number of users corresponding to each sub-period in the charging area in the future period based on the number of charging piles and the regional location when there are no primary users and secondary users in the regional location, including: based on the number of charging piles, screening out at least one target charging area from the remaining charging areas, the number of charging piles in the target charging area is the same as the number of charging piles corresponding to the charging area, and there are no primary users and secondary users in the target charging area; obtaining first historical data corresponding to the target charging area and second historical data corresponding to the charging area, the first historical data including the historical usage time of each charging pile in the target charging area, and the second historical data including the historical usage time of each charging pile in the charging area; Dividing the future period into at least two sub-periods based on each historical usage moment included in the first historical data and each historical usage moment included in the second historical data; Determine the date label corresponding to each sub-period; Based on the date label corresponding to each sub-period and the historical usage time of each charging pile, the number of users corresponding to each sub-period in the charging area in the future period is determined.

[0073] When there is no place with a fixed flow of people within a certain range from the location of the area, that is, when the type of charging demand source corresponding to the location of the area is a non-stable type, the historical data of the charging area can be obtained, and the number of users corresponding to the charging area can be predicted based on the historical data. Specifically, according to the number of charging piles in the charging area, an area with the same number of charging piles is searched from other charging areas in the charging database as the target charging area. For each selected target charging area and current charging area, the first historical data corresponding to each target charging area containing the historical usage time of each charging pile is obtained, and the second historical data corresponding to the charging area containing the historical usage time of each charging pile is obtained.

[0074] Furthermore, based on the usage moments in the historical data, cluster analysis is used to analyze the periodic patterns of charging pile usage (such as differences between weekdays and weekends, seasonal changes, etc.), divide the future cycle into several sub-cycles, and assign one or more date labels to each sub-cycle. These labels are used to identify the date range or characteristics corresponding to the sub-cycle (such as "weekdays", "weekends", "holidays", etc.).

[0075] Furthermore, based on the date tag of each sub-period and the historical usage time of the charging pile, the number of users in the current charging area in future sub-periods is predicted.

[0076] For each sub-cycle, the average number of times the charging piles are used under the same date label in the target charging area is counted as the number of times the charging piles are used corresponding to each sub-cycle, and the sum of the number of times each charging pile is used is calculated to obtain the number of users corresponding to the charging area in the future cycle.

[0077] In a possible implementation of the embodiment of the present application, in the above step S205, determining the weights of the grid load distribution and the user quantity respectively includes: Based on the grid load sub-distribution corresponding to each sub-period in the future period, a first judgment matrix is ​​established; Based on the number of users corresponding to each sub-period, a second judgment matrix is ​​established; The maximum eigenvalue and eigenvector corresponding to the first judgment matrix and the second judgment matrix are calculated to obtain the weights of the power grid load distribution and the user quantity.

[0078] Specifically, the process of constructing the first judgment matrix is ​​as follows: Assuming that the future period is divided into n sub-periods, an n*n matrix is ​​created, in which both rows and columns represent different sub-periods, and the element aij in the matrix represents the importance of the grid load distribution of sub-period i relative to sub-period j. For example, if the grid load distribution of sub-period 1 is slightly more important than that of sub-period 2, a12 may be 3; if the two are equally important, a12=a21=1.

[0079] The process of constructing the second judgment matrix is ​​as follows: Create an n*n matrix, the elements of which represent the relative importance of the number of users in different sub-periods. Use the same scaling method as the first judgment matrix to determine the element values.

[0080] Furthermore, mathematical methods (such as the power method, Jacobi method, etc.) are used to calculate all eigenvalues ​​of the matrix, and the largest eigenvalue is found among all eigenvalues, denoted as λmax, and the eigenvector corresponding to λmax is found, and each element in the eigenvector represents the weight of the corresponding sub-period.

[0081] Furthermore, in order to ensure the rationality of the judgment matrix, a consistency check is usually required. Specifically, the consistency index (CI) is calculated, the random consistency ratio (RI) is found, and the consistency ratio (CR = CI / RI) is calculated. If CR is less than 0.1, the consistency of the judgment matrix is ​​considered acceptable.

[0082] If the consistency of the first judgment matrix and the second judgment matrix is ​​acceptable, each element in the eigenvector is normalized so that the sum of all elements is equal to 1. The vector obtained after normalization is the weight of the grid load distribution and the user quantity.

[0083] A possible implementation of the embodiment of the present application, in the above embodiment, based on the busyness, construction cost and basic cost corresponding to each sub-period, the billing standard corresponding to each sub-period is determined, including: Determine the estimated usage time corresponding to the charging area; Based on the expected duration of use and construction costs, determine the construction sub-costs corresponding to each sub-period in the future period; Determine the proportion of the construction cost and basic cost allocated to each sub-period to obtain the cost allocation factor corresponding to each sub-period; Based on formula 4: Get the billing standard corresponding to each sub-period; Among them, S i is the cost per kWh of electricity corresponding to the sub-period, E i The amount of electricity purchased corresponding to the sub-period, S baseis the sum of the basic cost corresponding to the sub-period and the sub-cost of completion, F a F is the busyness level. b is the cost allocation factor, α and β are both constants.

[0084] The cost allocation factor is the coefficient for allocating the total cost to each sub-period.

[0085] Specifically, the average usage time of each charging area is obtained to obtain the estimated usage time corresponding to the charging area, and the construction sub-cost corresponding to the future period is calculated based on the estimated usage time and the construction cost.

[0086] For the grid load, the load factor of each sub-cycle can be calculated based on the ratio of the average load of the sub-cycle to the average load of the entire cycle, that is, based on the load factor of the sub-cycle = the average load of the sub-cycle / the average load of the future cycle, to obtain the load factor of each sub-cycle. And based on the usage frequency of the sub-cycle = the number of times the sub-cycle is used / the number of times the future cycle is used, the usage frequency of each sub-cycle is obtained, where the number of times the sub-cycle is used is the sum of the number of times each charging pile is used in the charging area within the sub-cycle, and the number of times the future cycle is used is the sum of the number of times each charging pile is used in the charging area within the future cycle.

[0087] Furthermore, the usage frequency of the sub-period and the average of the load factor are used as the allocation ratio, and based on the cost allocation factor of the sub-period = the allocation ratio of the sub-period / the sum of the allocation ratios of each sub-period, the cost allocation factor of each sub-period is obtained.

[0088] After obtaining the cost allocation factor corresponding to each sub-period, we can use Formula 4 as follows: Calculate the billing standard corresponding to each sub-period, where S i is the cost per kWh of electricity corresponding to the sub-period, E i The amount of electricity purchased corresponding to the sub-period, S base is the sum of the basic cost corresponding to the sub-period and the sub-cost of completion, F a F is the busyness level. b is the cost allocation factor, α and β are both constants. For example, assuming Sbase = 100 (yuan / sub-period), α = 0.5, β = 0.3, the busyness factor of a sub-period Fbi = 0.8, and the cost allocation factor Fci = 0.2. Then: Si = 100 × (1 + 0.5 × 0.8 + 0.3 × 0.2) = 100 × (1 + 0.4 + 0.06) = 100 × 1.46 = 146 (yuan / sub-period).

[0089] The above embodiment introduces a method for determining a charging pile charging strategy from the perspective of a method flow, and the following embodiment introduces a device for determining a charging pile charging strategy from the perspective of a virtual module or a virtual unit. For details, please refer to the following embodiment.

[0090] See also Figure 3 The charging pile charging strategy determination device 30 may specifically include: an acquisition module 301, a user quantity determination module 302, a prediction module 303, a cost determination module 304, a weight determination module 305, a calculation module 306 and a strategy determination module 307. Specifically: A charging pile charging strategy determination device 30, comprising: An acquisition module 301 is used to acquire the regional scale and regional location of the charging area, where the regional scale includes the number of charging piles and construction costs; The user quantity determination module 302 is used to determine the user quantity corresponding to each sub-period in the charging area in the future cycle based on the number of charging piles and the regional location. The user quantity is the number of charging vehicles charged by the charging piles in a sub-period in the future cycle; The prediction module 303 is used to predict the number of purchased electricity corresponding to each sub-period in the future cycle of the charging area based on the number of users; the fee determination module 304 is used to predict the maintenance cost of the charging area in the future cycle and the grid load distribution corresponding to the future cycle, and determine the basic fee corresponding to the charging area based on the grid load distribution, the number of purchased electricity corresponding to each sub-period and the maintenance cost; The weight determination module 305 is used to determine the weights of the grid load distribution and the user quantity; A calculation module 306 is used to calculate the busyness corresponding to each sub-period based on the power grid load distribution and the weights of the user quantities; The strategy determination module 307 is used to determine the billing standard corresponding to each sub-cycle based on the busyness, construction cost and basic cost corresponding to each sub-cycle, and determine the charging sub-strategy corresponding to each sub-cycle in the future cycle, and perform corresponding charging operations based on the billing standard and charging sub-strategy corresponding to each sub-cycle.

[0091] In a possible implementation of the embodiment of the present application, the user quantity determination module 302 is specifically used to determine the user quantity corresponding to each sub-period in the charging area in the future period based on the number of charging piles and the regional location: Obtaining a charging demand source corresponding to a regional location, where the charging demand source is used to characterize vehicles passing through the regional location and having charging demand; Determine whether the type corresponding to the charging demand source is a stable type to determine whether there are primary users and secondary users in the regional location; If there are primary users and secondary users in the area, the historical charging data corresponding to the charging area is obtained, and the historical charging data includes the number of historical charging users corresponding to each historical period and the historical charging times and historical charging times corresponding to each historical charging user; Based on the historical charging data, the historical cycle is divided into multiple historical sub-cycles; Based on the start and end times corresponding to each historical sub-cycle, the future cycle is divided into multiple sub-cycles, and based on the historical number of charging users corresponding to each historical sub-cycle, the number of users corresponding to each sub-cycle in the charging area in the future cycle is determined.

[0092] In a possible implementation of the embodiment of the present application, when the user quantity determination module 302 divides the historical period into multiple historical sub-periods based on the historical charging data, it is specifically used to: From the historical charging users, historical charging users whose historical charging times are greater than a charging times threshold are selected as first historical charging users, and historical charging users whose historical charging times have a regularity greater than a regularity threshold are selected from the historical charging users as second historical charging users; Determine the first historical charging user and the second historical charging user as primary users, and determine the historical charging users other than the primary user as secondary users; The historical period is divided into a plurality of historical sub-periods based on the historical charging times corresponding to the primary user and the historical charging times corresponding to the secondary user.

[0093] In a possible implementation of the embodiment of the present application, the fee determination module 304 is specifically used to: divide the future time period into a peak period, a normal period, and a valley period based on the load distribution of the power grid, when determining the basic fee corresponding to the charging area based on the load distribution of the power grid, the purchased electricity corresponding to each sub-period, and the maintenance fee; Based on the purchased electricity kilowatt-hours corresponding to each sub-period, a first purchased electricity kilowatt-hour corresponding to the peak period, a second purchased electricity kilowatt-hour corresponding to the normal period, and a third purchased electricity kilowatt-hour corresponding to the valley period are calculated; Predict the unit electricity prices corresponding to the peak period, normal period and valley period in the future cycle; Based on Formula 1: M = M1 + C, the basic fee corresponding to the charging area is calculated; Among them, M is the basic cost of the charging area in the future cycle, M1 is the electricity purchase cost of the charging area in the future cycle, and C is the maintenance cost; Among them, based on formula 2: M1=∑ t∈所有时段 ((E t,p *P p +E t,N *P N +E t,L *PL )*F(U t )) to predict the electricity purchase cost of the charging area in the future cycle; Among them, M1 is the electricity purchase cost of the charging area in the future cycle, E t,p is the first purchased electricity quantity, E t,N is the second purchased electricity quantity, E t,L is the third purchased electricity quantity, P p is the unit electricity price during peak hours, P N is the unit electricity price during normal periods, P L is the unit electricity price during the off-peak period, F(U t ) is a discount or markup factor related to the number of users; Based on formula 3: Calculate discount or markup factors related to user volume; Among them, F(U t ) is the discount or markup factor related to the number of users, U threshold is the first threshold corresponding to the number of users, U max is the second threshold corresponding to the number of users.

[0094] In a possible implementation of the embodiment of the present application, when there are no primary users and secondary users in the regional location, the user quantity determination module 302 determines the user quantity corresponding to each sub-period in the charging area in the future period based on the number of charging piles and the regional location, specifically for: Based on the number of charging piles, at least one target charging area is screened out from the remaining charging areas, the number of charging piles in the target charging area is the same as the number of charging piles corresponding to the charging area, and there are no primary users and secondary users in the target charging area; first historical data corresponding to the target charging area and second historical data corresponding to the charging area are obtained, the first historical data including the historical usage time of each charging pile in the target charging area, and the second historical data including the historical usage time of each charging pile in the charging area; Dividing the future period into at least two sub-periods based on each historical usage moment included in the first historical data and each historical usage moment included in the second historical data; Determine the date label corresponding to each sub-period; Based on the date label corresponding to each sub-period and the historical usage time of each charging pile, the number of users corresponding to each sub-period in the charging area in the future period is determined.

[0095] In a possible implementation of the embodiment of the present application, the weight determination module 305 is specifically used to determine the weights of the power grid load distribution and the user quantity: Based on the grid load sub-distribution corresponding to each sub-period in the future period, a first judgment matrix is ​​established; Based on the number of users corresponding to each sub-period, a second judgment matrix is ​​established; The maximum eigenvalue and eigenvector corresponding to the first judgment matrix and the second judgment matrix are calculated to obtain the weights of the power grid load distribution and the user quantity.

[0096] In a possible implementation of the embodiment of the present application, the policy determination module 307 is specifically used to determine the charging standard corresponding to each sub-period based on the busyness, construction cost and basic cost corresponding to each sub-period: Determine the estimated usage time corresponding to the charging area; Based on the expected duration of use and construction costs, determine the construction sub-costs corresponding to each sub-period in the future period; Determine the proportion of the allocated construction costs and basic costs corresponding to each sub-period to obtain the cost allocation factor corresponding to each sub-period; Based on formula 4: Get the billing standard corresponding to each sub-period; Among them, S i is the cost per kWh of electricity corresponding to the sub-period, E i The amount of electricity purchased corresponding to the sub-period, S base is the sum of the basic cost corresponding to the sub-period and the sub-cost of completion, F a F is the busyness level. b is the cost allocation factor, α and β are both constants.

[0097] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0098] See also Figure 4 , the embodiment of the present application also introduces an electronic device from the perspective of a physical device, such as Figure 4 As shown, Figure 4 The electronic device 40 shown includes: a processor 401 and a memory 403. The processor 401 and the memory 403 are connected, such as through a bus 402. Optionally, the electronic device 40 may also include a transceiver 404. It should be noted that in actual applications, the transceiver 404 is not limited to one, and the structure of the electronic device 40 does not constitute a limitation on the embodiments of the present application.

[0099] Processor 401 may be a CPU (Central Processing Unit), a general purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. Processor 401 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0100] The bus 402 may include a path to transmit information between the above components. The bus 402 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 402 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0101] The memory 403 can be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0102] The memory 403 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 401. The processor 401 is used to execute the application code stored in the memory 403 to implement the contents shown in the above method embodiment.

[0103] Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc., and can also be servers, etc. Figure 4 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0104] An embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment.

[0105] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0106] The above are only some implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for determining a charging strategy for a charging pile, characterized in that: The method comprises: Obtaining the regional scale and regional location of the charging area, wherein the regional scale includes the number of charging piles and the construction cost; based on the number of charging piles and the regional location, determining the number of users corresponding to each sub-period of the charging area in a future period, wherein the number of users is the number of charging vehicles that use the charging piles to charge in a sub-period of the future period; Based on the number of users, predict the amount of electricity purchased by the charging area in each sub-period in the future period; Predicting the maintenance cost of the charging area in a future period and the grid load distribution corresponding to the future period, and determining the basic cost corresponding to the charging area based on the grid load distribution, the purchased electricity corresponding to each sub-period and the maintenance cost; Determining the weights of the power grid load distribution and the user quantity; Based on the load distribution of the power grid and the weights of the respective user quantities, the busyness corresponding to each sub-cycle is calculated; based on the busyness corresponding to each sub-cycle, the construction cost and the basic cost, the billing standard corresponding to each sub-cycle is determined, and the charging sub-strategy corresponding to each sub-cycle in the future cycle is determined, and the corresponding charging operation is performed based on the billing standard and the charging sub-strategy corresponding to each sub-cycle.

2. The method for determining a charging pile charging strategy according to claim 1, characterized in that: The determining, based on the number of charging piles and the regional location, the number of users corresponding to each sub-period of the charging area in the future period includes: obtaining a charging demand source corresponding to the regional location, the charging demand source being used to characterize vehicles passing through the regional location and having charging demand; Determine whether the type corresponding to the charging demand source is a stable type, so as to determine whether there are primary users and secondary users in the regional location; If there are primary users and secondary users in the area, then historical charging data corresponding to the charging area is obtained, wherein the historical charging data includes the number of historical charging users corresponding to each historical period and the historical charging times and historical charging times corresponding to each historical charging user; Based on the historical charging data, dividing the historical period into a plurality of historical sub-periods; The future cycle is divided into multiple sub-cycles based on the start and end times corresponding to each historical sub-cycle, and the number of users corresponding to each sub-cycle in the charging area in the future cycle is determined based on the historical number of charging users corresponding to each historical sub-cycle.

3. The method for determining a charging strategy for a charging pile according to claim 2, characterized in that: The dividing the historical cycle into a plurality of historical sub-cycles based on the historical charging data includes: From the historical charging users, historical charging users whose historical charging times are greater than a charging times threshold are selected as first historical charging users, and historical charging users whose historical charging times have a regularity greater than a regularity threshold are selected from the historical charging users as second historical charging users; Determine the first historical charging user and the second historical charging user as primary users, and determine the historical charging users other than the primary user as secondary users; The historical period is divided into a plurality of historical sub-periods based on the historical charging times corresponding to the primary user and the historical charging times corresponding to the secondary user.

4. The method for determining a charging strategy for a charging pile according to claim 2 or 3, characterized in that: The determining of the basic fee corresponding to the charging area based on the load distribution of the power grid, the purchased electricity kilowatt-hours corresponding to each sub-period, and the maintenance fee includes: Based on the load distribution of the power grid, the future time period is divided into peak period, normal period and valley period; Based on the purchased electricity kilowatt-hours corresponding to each sub-period, a first purchased electricity kilowatt-hour corresponding to the peak period, a second purchased electricity kilowatt-hour corresponding to the normal period, and a third purchased electricity kilowatt-hour corresponding to the valley period are calculated; Predict the unit electricity prices corresponding to the peak period, normal period and valley period in the future cycle; Based on Formula 1: M = M1 + C, the basic fee corresponding to the charging area is calculated; Wherein, M is the basic cost of the charging area in the future cycle, M1 is the electricity purchase cost of the charging area in the future cycle, and C is the maintenance cost; Among them, based on formula 2: M1=∑ t∈所有时段 ((E t,p *P p +E t,N *P N +E t,L *P L )*F(U t )) to predict the electricity purchase cost of the charging area in the future period; Among them, M1 is the electricity purchase cost of the charging area in the future cycle, E t,p is the first purchased electricity quantity, E t,N is the second purchased electricity quantity, E t,L is the third purchased electricity quantity, P p is the unit electricity price during peak hours, P N is the unit electricity price during normal periods, P L is the unit electricity price during the off-peak period, F(U t ) is a discount or markup factor related to the number of users; Based on formula 3: Calculate discount or markup factors related to user volume; Among them, F(U t ) is the discount or markup factor related to the number of users, U threshold is the first threshold corresponding to the number of users, U max is the second threshold corresponding to the number of users.

5. The method for determining a charging pile charging strategy according to claim 2, characterized in that: When there are no primary users and secondary users in the regional location, determining the number of users corresponding to each sub-period in the charging area in the future period based on the number of charging piles and the regional location includes: Based on the number of charging piles, at least one target charging area is selected from the remaining charging areas, the number of charging piles in the target charging area is the same as the number of charging piles corresponding to the charging area, and there are no primary users and secondary users in the target charging area; Acquire first historical data corresponding to the target charging area and second historical data corresponding to the charging area, wherein the first historical data includes historical usage time of each charging pile in the target charging area, and the second historical data includes historical usage time of each charging pile in the charging area; Dividing the future period into at least two sub-periods based on each historical usage moment included in the first historical data and each historical usage moment included in the second historical data; Determine the date label corresponding to each sub-period; Based on the date tag corresponding to each sub-period and the historical usage time of each charging pile, the number of users corresponding to each sub-period in the charging area in the future period is determined.

6. The method for determining a charging strategy for a charging pile according to claim 1, characterized in that: The determining of the weights of the power grid load distribution and the user quantity respectively includes: Based on the grid load sub-distribution corresponding to each sub-period in the future period, a first judgment matrix is ​​established; Based on the amount of users corresponding to each sub-period, establishing a second judgment matrix; The maximum eigenvalue and eigenvector corresponding to the first judgment matrix and the second judgment matrix are calculated to obtain the weights of the power grid load distribution and the user quantity.

7. The method for determining a charging pile charging strategy according to claim 6, characterized in that: The determining of the charging standard corresponding to each sub-cycle based on the busyness corresponding to each sub-cycle, the construction fee and the basic fee includes: determining the estimated usage time corresponding to the charging area; Determine the construction sub-cost corresponding to each sub-period in the future period based on the estimated usage time and the construction cost; Determine the proportion of the construction cost and basic cost allocated to each sub-period to obtain the cost allocation factor corresponding to each sub-period; Based on formula 4: Get the billing standard corresponding to each sub-period; Among them, S i is the cost per kWh of electricity corresponding to the sub-period, E i The amount of electricity purchased corresponding to the sub-period, S base is the sum of the basic cost corresponding to the sub-period and the sub-cost of completion, F a F is the busyness level. b is the cost allocation factor, α and β are both constants.

8. A device for determining a charging strategy for a charging pile, characterized in that: include: An acquisition module, used to acquire the regional scale and regional location of the charging area, wherein the regional scale includes the number of charging piles and the construction cost; A user quantity determination module, configured to determine the user quantity corresponding to each sub-period of the charging area in a future cycle based on the number of charging piles and the area location, wherein the user quantity is the number of charging vehicles charged using the charging piles in a sub-period of the future cycle; A prediction module, configured to predict the amount of electricity purchased in each sub-period of the charging area in a future period based on the amount of users; A cost determination module, used to predict the maintenance cost of the charging area in the future period and the grid load distribution corresponding to the future period, and determine the basic cost corresponding to the charging area based on the grid load distribution, the purchased electricity corresponding to each sub-period and the maintenance cost; A weight determination module, used to determine the weights of the power grid load distribution and the user quantity; A calculation module, used to calculate the busyness corresponding to each sub-period based on the power grid load distribution and the weights of the user quantities; The strategy determination module is used to determine the billing standard corresponding to each sub-cycle based on the busyness corresponding to each sub-cycle, the construction cost and the basic cost, and determine the charging sub-strategy corresponding to each sub-cycle in the future cycle, and perform corresponding charging operations based on the billing standard and the charging sub-strategy corresponding to each sub-cycle.

9. An electronic device, characterized in that: The electronic device includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the charging pile charging strategy determination method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed in a computer, the computer is caused to execute the method for determining a charging strategy for a charging pile according to any one of claims 1 to 7.

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