Method and device for predicting energy storage configuration of charging station, electronic equipment and medium

Abstract

The application discloses a kind of prediction method, device, electronic equipment and medium of charging station energy storage configuration, its method includes: obtaining the energy storage prediction data in the preset historical duration of charging station, the energy storage prediction data includes: historical power consumption data and historical price data;According to the energy storage prediction data, respectively based on the first energy storage strategy Determine the first historical income of the charging station, and determine the second historical income of the charging station based on the second energy storage strategy;According to the first historical income and the second historical income, determine the preferred energy storage strategy of the charging station and whether the charging station is suitable for increasing energy storage equipment.The prediction result of the present application is accurate, adjusts power consumption in the energy peak period, reduces the pressure of power grid;And whether the charging station increases energy storage equipment provides reliable reference information, can make the charging station obtain greater benefit, avoid investment risk.

Description

Technical Field

[0001] This application relates to the field of power data processing technology, specifically to a prediction method, device, electronic equipment, and medium for energy storage configuration in charging stations. Background Technology

[0002] In the electricity market, charging stations often add energy storage equipment in pursuit of higher profits. However, the cost of building energy storage equipment is very high, and if not handled carefully, it can lead to huge investment failures.

[0003] Therefore, before building energy storage equipment, it is usually necessary to predict whether a charging station is suitable for adding energy storage equipment. However, in the existing technology, simulation systems are usually used for prediction, which is not very accurate and has little reference value. Summary of the Invention

[0004] In view of the above situation, this application proposes a method, device, electronic device and medium for predicting the energy storage configuration of charging stations, so as to overcome or at least partially overcome the shortcomings of the prior art.

[0005] In a first aspect, embodiments of this application provide a method for predicting the energy storage configuration of charging stations, including:

[0006] Obtain energy storage prediction data for the charging station within a preset historical time period. The energy storage prediction data includes: historical electricity consumption data and historical price data.

[0007] Based on the energy storage forecast data, the first historical revenue of the charging station is determined based on the first energy storage strategy, and the second historical revenue of the charging station is determined based on the second energy storage strategy, wherein the first energy storage strategy and the second energy storage strategy are established using a peak shaving and valley filling mechanism.

[0008] Based on the first historical revenue and the second historical revenue, determine the preferred energy storage strategy for the charging station and whether the charging station is suitable for adding energy storage equipment.

[0009] Optionally, in the above method, the first energy storage strategy is to use the off-peak price period as the charging time and the par price, peak price and peak price periods as the discharging time.

[0010] The determination of the first historical revenue of the charging station based on the first energy storage strategy includes:

[0011] Each natural day is divided into at least one charge-discharge cycle according to the time sequence, and the first total charge and the first total power consumption of each charge-discharge cycle are determined.

[0012] Determine whether the first total charging amount is greater than the first total electricity consumption. If so, determine the total energy storage discharge amount of the charge-discharge cycle as the first total electricity consumption, and determine the first cycle revenue of the charge-discharge cycle based on the first total consumption amount and the historical price data.

[0013] If not, the total energy storage discharge of the charge-discharge cycle is determined to be the first total charge, and the first cycle revenue of the charge-discharge cycle is determined based on the first total charge and the historical price data.

[0014] The first daily revenue of the charging station is obtained by summing the revenue of the first cycle of at least one charge-discharge cycle for each natural day.

[0015] The first-stage revenue of the charging station is obtained by summing up the multiple first daily revenues within the preset historical time period.

[0016] Optionally, in the above method, determining the first cycle revenue of the charge-discharge cycle based on the first total usage and the historical price data includes:

[0017] Based on the electricity consumption during the flat, peak, and peak price periods in the charging and discharging cycle, the first total electricity consumption is divided into the first flat electricity consumption, the first peak electricity consumption, and the first peak electricity consumption.

[0018] The difference between the parity price and the valley price during the charging and discharging cycle is multiplied by the first average electricity consumption to obtain the first parity revenue; the difference between the peak price and the valley price during the charging and discharging cycle is multiplied by the second average electricity consumption to obtain the first peak revenue; the difference between the peak price and the valley price during the charging and discharging cycle is multiplied by the first peak electricity consumption to obtain the first peak revenue.

[0019] The first parity return, the first peak return, and the first sharpest return are summed to obtain the first cycle return of the charge-discharge cycle.

[0020] Optionally, in the above method, determining the first cycle revenue of the charge-discharge cycle based on the first total charge amount and the historical price data includes:

[0021] Determine whether the remaining energy storage capacity per unit time of the charge / discharge cycle is greater than the energy consumption per unit time;

[0022] If yes, then the product of the electricity consumption per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time; if no, then the product of the remaining energy storage capacity per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time.

[0023] The gross revenue per unit time of the charge-discharge cycle is summed to obtain the gross revenue of the charge-discharge cycle.

[0024] The first cycle revenue of the charge / discharge cycle is obtained by subtracting the energy storage charging cost of the charge / discharge cycle from the gross revenue of the cycle. The energy storage charging cost is the product of the off-peak price period of the charge cycle and the off-peak price of the charge / discharge cycle.

[0025] Optionally, in the above method, the second energy storage strategy is to use the period between off-peak and flat prices as the charging time, and the period between peak and slack prices as the discharging time.

[0026] The determination of the second historical revenue of the charging station based on the second energy storage strategy includes:

[0027] Each natural day is divided into at least one charge-discharge cycle according to the time sequence, and the second total charge and the second total power consumption of each charge-discharge cycle are determined.

[0028] Determine whether the second total charging amount is greater than the second total electricity consumption. If so, determine the total energy storage discharge amount of the charge-discharge cycle as the second total electricity consumption, and determine the second cycle revenue of the charge-discharge cycle based on the second total consumption amount and the historical price data.

[0029] If not, the total energy storage discharge of the charge-discharge cycle is determined to be the second total charge, and the second cycle revenue of the charge-discharge cycle is determined based on the second total charge and the historical price data.

[0030] The second daily revenue of the charging station is obtained by summing the second-cycle revenue of at least one charge-discharge cycle for each natural day.

[0031] The second-stage revenue of the charging station is obtained by summing up the multiple second daily revenues within the preset historical time period.

[0032] Optionally, in the above method, determining the second cycle revenue of the charge-discharge cycle based on the second total usage and the historical price data includes:

[0033] Based on the electricity consumption during the off-peak, peak, and slack periods in the charging and discharging cycle, the second total electricity consumption is divided into the second peak electricity consumption and the second slack electricity consumption.

[0034] The second peak price revenue is obtained by multiplying the difference between the peak price and the valley price during the charging and discharging cycle by the second average electricity consumption; the second peak price revenue is obtained by multiplying the difference between the high price and the valley price during the charging and discharging cycle by the second high electricity consumption.

[0035] The second peak price gain and the second sharp price gain are summed to obtain the second cycle gain of the charge-discharge cycle.

[0036] Optionally, in the above method, determining the second cycle revenue of the charge-discharge cycle based on the second total charge amount and the historical price data includes:

[0037] Determine whether the remaining energy storage capacity per unit time of the charge / discharge cycle is greater than the energy consumption per unit time;

[0038] If yes, then the product of the electricity consumption per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time; if no, then the product of the remaining energy storage capacity per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time.

[0039] The gross revenue per unit time of the charge-discharge cycle is summed to obtain the gross revenue of the charge-discharge cycle.

[0040] The second cycle revenue of the charge-discharge cycle is obtained by subtracting the energy storage charging cost of the charge-discharge cycle from the gross revenue of the cycle. The energy storage charging cost is the product of the off-peak price period of the charging cycle and the off-peak price of the charge-discharge cycle.

[0041] Optionally, in the above method, the first historical return includes: a first daily return and a first phase return, wherein the first phase return is the first year's return; the second historical return includes: a second daily return and a second phase return, wherein the second phase return is the second year's return.

[0042] The step of determining the preferred energy storage strategy for the charging station and whether it is suitable to add energy storage equipment based on the first historical revenue and the second historical revenue includes:

[0043] The maximum value of the first year's revenue and the second year's revenue is determined, and the energy storage strategy corresponding to the maximum value is taken as the preferred energy storage strategy.

[0044] Optionally, in the above method, determining the preferred energy storage strategy of the charging station based on the first historical revenue and the second historical revenue, and whether to add energy storage equipment, further includes: reading the maximum daily charging amount of the determined preferred energy storage strategy from the historical electricity consumption data.

[0045] The maximum daily charging volume is used as the required energy storage capacity of the charging station to determine the cost of building the energy storage equipment.

[0046] The payback period for the equipment is determined based on the annual revenue of the preferred energy storage strategy and the cost of building the energy storage equipment.

[0047] Based on multiple preset thresholds, the daily revenue of the preferred energy storage strategy, and the payback period of the equipment, it is determined whether the charging station is suitable for adding energy storage equipment.

[0048] Optionally, in the above method, determining the cost of building the energy storage device by using the maximum daily charging capacity as the required energy storage capacity of the charging station includes:

[0049] The maximum daily charging volume is taken as the required energy storage capacity of the charging station. The average cost per kilowatt-hour of energy storage equipment is determined by multiplying the average cost per kilowatt-hour of energy storage equipment by the required energy storage capacity to obtain the cost of building the energy storage equipment.

[0050] The process of determining the payback period for the equipment based on the annual revenue of the preferred energy storage strategy and the cost of constructing the energy storage equipment includes:

[0051] The first quotient of the cost of building the energy storage equipment and the annual return of the preferred energy storage strategy is used to obtain the payback period for the equipment.

[0052] Optionally, in the above method, the plurality of thresholds includes: a daily revenue threshold, a number of days threshold, and a payback period threshold;

[0053] The determination of whether a charging station is suitable for adding energy storage equipment, based on multiple preset thresholds, the daily revenue of the preferred energy storage strategy, and the payback period of the equipment, includes:

[0054] Within a preset historical period, determine the number of days in which the daily revenue of the preferred energy storage strategy is greater than the daily revenue threshold;

[0055] Determine whether the number of days is greater than the number of days threshold; if not, determine that the charging station is not suitable for adding energy storage equipment.

[0056] If so, determine whether the payback period for the equipment is less than the payback period threshold. If not, determine that the charging station is not suitable for adding energy storage equipment; if so, determine that the charging station is suitable for adding energy storage equipment.

[0057] Secondly, embodiments of this application also provide a predictive device for the energy storage configuration of a charging station, the device comprising:

[0058] The acquisition unit is used to acquire energy storage prediction data of the charging station within a preset historical time period. The energy storage prediction data includes: historical electricity consumption data and historical price data.

[0059] The revenue retrospective unit is used to determine the first historical revenue of the charging station based on the energy storage forecast data, and to determine the second historical revenue of the charging station based on the first energy storage strategy and the second energy storage strategy, wherein the first energy storage strategy and the second energy storage strategy are established using a peak shaving and valley filling mechanism.

[0060] The prediction unit is used to determine the preferred energy storage strategy for the charging station and whether the charging station is suitable for adding energy storage equipment based on the first historical revenue and the second historical revenue.

[0061] Optionally, in the above-mentioned device, the first energy storage strategy is to use the off-peak price period as the charging time and the par price, peak price and peak price periods as the discharging time.

[0062] The revenue tracking unit is used to divide each natural day into at least one charge-discharge cycle according to the time sequence, and to determine the first total charge and the first total electricity consumption for each charge-discharge cycle.

[0063] Determine whether the first total charging amount is greater than the first total electricity consumption. If so, determine the total energy storage discharge amount of the charge-discharge cycle as the first total electricity consumption, and determine the first cycle revenue of the charge-discharge cycle based on the first total consumption amount and the historical price data.

[0064] If not, the total energy storage discharge of the charge-discharge cycle is determined to be the first total charge, and the first cycle revenue of the charge-discharge cycle is determined based on the first total charge and the historical price data.

[0065] The first daily revenue of the charging station is obtained by summing the revenue of the first cycle of at least one charge-discharge cycle for each natural day.

[0066] The first-stage revenue of the charging station is obtained by summing up the multiple first daily revenues within the preset historical time period.

[0067] Optionally, in the above device, the revenue tracking unit is used to divide the first total electricity consumption into a first flat electricity consumption, a first peak electricity consumption, and a first peak electricity consumption based on the electricity consumption during the flat price, peak price, and peak price periods in the charging and discharging cycle.

[0068] The difference between the parity price and the valley price during the charging and discharging cycle is multiplied by the first average electricity consumption to obtain the first parity revenue; the difference between the peak price and the valley price during the charging and discharging cycle is multiplied by the second average electricity consumption to obtain the first peak revenue; the difference between the peak price and the valley price during the charging and discharging cycle is multiplied by the first peak electricity consumption to obtain the first peak revenue.

[0069] The first parity return, the first peak return, and the first sharpest return are summed to obtain the first cycle return of the charge-discharge cycle.

[0070] Optionally, in the above device, the revenue tracking unit is used to determine whether the remaining energy storage capacity per unit time of the charge-discharge cycle is greater than the energy consumption per unit time.

[0071] If yes, then the product of the electricity consumption per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time; if no, then the product of the remaining energy storage capacity per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time.

[0072] The gross revenue per unit time of the charge-discharge cycle is summed to obtain the gross revenue of the charge-discharge cycle.

[0073] The first cycle revenue of the charge / discharge cycle is obtained by subtracting the energy storage charging cost of the charge / discharge cycle from the gross revenue of the cycle. The energy storage charging cost is the product of the off-peak price period of the charge cycle and the off-peak price of the charge / discharge cycle.

[0074] Optionally, in the above-mentioned device, the second energy storage strategy is to use the time between valley price and flat price as the charging time, and the time between peak price and peak price as the discharging time.

[0075] The revenue backtracking unit is used to divide each natural day into at least one charge-discharge cycle according to the time sequence, and to determine the second total charge and the second total power consumption for each charge-discharge cycle.

[0076] Determine whether the second total charging amount is greater than the second total electricity consumption. If so, determine the total energy storage discharge amount of the charge-discharge cycle as the second total electricity consumption, and determine the second cycle revenue of the charge-discharge cycle based on the second total consumption amount and the historical price data.

[0077] If not, the total energy storage discharge of the charge-discharge cycle is determined to be the second total charge, and the second cycle revenue of the charge-discharge cycle is determined based on the second total charge and the historical price data.

[0078] The second daily revenue of the charging station is obtained by summing the second-cycle revenue of at least one charge-discharge cycle for each natural day.

[0079] The second-stage revenue of the charging station is obtained by summing up the multiple second daily revenues within the preset historical time period.

[0080] Optionally, in the above device, the revenue tracking unit is used to divide the second total electricity consumption into a second peak electricity consumption and a second peak electricity consumption based on the electricity consumption during the parity, peak and climax periods in the charging and discharging cycle.

[0081] The second peak price revenue is obtained by multiplying the difference between the peak price and the valley price during the charging and discharging cycle by the second average electricity consumption; the second peak price revenue is obtained by multiplying the difference between the high price and the valley price during the charging and discharging cycle by the second high electricity consumption.

[0082] The second peak price gain and the second sharp price gain are summed to obtain the second cycle gain of the charge-discharge cycle.

[0083] Optionally, in the above device, the revenue tracking unit is used to determine whether the remaining energy storage capacity per unit time of the charge-discharge cycle is greater than the energy consumption per unit time.

[0084] If yes, then the product of the electricity consumption per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time; if no, then the product of the remaining energy storage capacity per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time.

[0085] The gross revenue per unit time of the charge-discharge cycle is summed to obtain the gross revenue of the charge-discharge cycle.

[0086] The second cycle revenue of the charge-discharge cycle is obtained by subtracting the energy storage charging cost of the charge-discharge cycle from the gross revenue of the cycle. The energy storage charging cost is the product of the off-peak price period of the charging cycle and the off-peak price of the charge-discharge cycle.

[0087] Optionally, in the above-described apparatus, the first historical revenue includes: a first daily revenue and a first phase revenue, and the second historical revenue includes: a second daily revenue and a second phase revenue.

[0088] The prediction unit is used to determine the maximum value of the first stage revenue and the second stage revenue, and to use the energy storage strategy corresponding to the maximum value as the preferred energy storage strategy.

[0089] Optionally, in the above-mentioned device, the prediction unit is further configured to read the maximum daily charging amount of the determined preferred energy storage strategy from the historical electricity consumption data.

[0090] The maximum daily charging volume is used as the required energy storage capacity of the charging station to determine the cost of building the energy storage equipment.

[0091] The payback period for the equipment is determined based on the phased benefits of the preferred energy storage strategy and the cost of constructing the energy storage equipment.

[0092] Based on multiple preset thresholds, the daily revenue of the preferred energy storage strategy, and the payback period of the equipment, it is determined whether the charging station is suitable for adding energy storage equipment.

[0093] Optionally, in the above-mentioned device, the prediction unit is used to take the maximum daily charging volume as the required energy storage capacity of the charging station, determine the first product of the average cost per kilowatt-hour of energy storage equipment and the required energy storage capacity, and obtain the cost of building the energy storage equipment.

[0094] The step of determining the payback period for the equipment based on the phased benefits of the preferred energy storage strategy and the cost of constructing the energy storage equipment includes:

[0095] The first quotient of the cost of building the energy storage equipment and the phased benefits of the preferred energy storage strategy is used to obtain the payback period for the equipment.

[0096] Optionally, in the above-described device, the plurality of thresholds includes: a daily revenue threshold, a number of days threshold, and a payback period threshold;

[0097] The prediction unit is used to determine the number of days within a preset historical period where the daily revenue of the preferred energy storage strategy is greater than the daily revenue threshold.

[0098] Determine whether the number of days is greater than the number of days threshold; if not, determine that the charging station is not suitable for adding energy storage equipment.

[0099] If so, determine whether the payback period for the equipment is less than the payback period threshold. If not, determine that the charging station is not suitable for adding energy storage equipment; if so, determine that the charging station is suitable for adding energy storage equipment.

[0100] Thirdly, embodiments of this application also provide an electronic device, including: a processor; and a memory arranged to store computer-executable instructions, which, when executed, cause the processor to perform any of the methods described above.

[0101] Fourthly, embodiments of this application also provide a computer-readable storage medium that stores one or more programs, which, when executed by an electronic device including multiple applications, cause the electronic device to perform any of the methods described above.

[0102] The above-described technical solutions adopted in the embodiments of this application can achieve the following beneficial effects:

[0103] This application provides a predictive method for configuring energy storage in charging stations. It obtains real historical data of a charging station over a certain period as its predicted energy storage data. This predicted data may include, but is not limited to, historical electricity consumption data and historical price data. Based on a peak-shaving and valley-filling strategy, two different energy storage methods are designed, one designated as the first energy storage strategy and the other as the second. Then, according to the first energy storage strategy and the predicted energy storage data, the first historical revenue of the charging station over the historical period is calculated. Simultaneously, according to the second energy storage strategy and the predicted energy storage data, the second historical revenue of the charging station over the historical period is calculated. The first and second historical revenues are compared to determine which of the two energy storage strategies is more suitable for the charging station. Furthermore, based on the selected energy storage strategy, it can be determined whether the charging station is suitable for adding energy storage equipment. This application designs two energy storage strategies based on the principle of peak shaving and valley filling. The returns of the two strategies are calculated using real historical data from charging stations. Based on the returns, a preferred energy storage strategy is predicted for the charging station. Furthermore, the suitability of adding energy storage equipment to the charging station is determined based on the preferred strategy. The prediction results are accurate, allowing for power regulation during peak hours to reduce grid pressure. It also provides reliable reference information for deciding whether to add energy storage equipment to the charging station, enabling it to obtain greater returns and avoid investment risks. Attached Figure Description

[0104] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0105] Figure 1 A flowchart illustrating a method for predicting the energy storage configuration of a charging station according to an embodiment of this application is shown.

[0106] Figure 2 A schematic diagram illustrating changes in electricity prices based on actual electricity consumption scenarios is shown.

[0107] Figure 3 A flowchart illustrating a method for predicting the energy storage configuration of a charging station according to another embodiment of this application is shown.

[0108] Figure 4 A schematic diagram of the structure of a predictive device for a charging station energy storage configuration according to an embodiment of this application is shown;

[0109] Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0110] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0111] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0112] The concept of this application is to design two energy storage strategies based on the principle of peak shifting and valley filling of electricity. The benefits of the two energy storage strategies are calculated based on real data of the charging station over a historical period. Based on the obtained benefits, a preferred energy storage strategy is predicted for the charging station. Furthermore, the suitability of the charging station for adding energy storage equipment is determined based on the preferred energy storage strategy. The prediction results are accurate.

[0113] Figure 1 A flowchart illustrating a method for predicting the energy storage configuration of a charging station according to an embodiment of this application is shown. Figure 1 It can be seen that this application includes at least steps S110 to S130:

[0114] Step S110: Obtain energy storage prediction data for the charging station within a preset historical time period. The energy storage prediction data includes historical electricity consumption data and historical price data.

[0115] In the actual electricity market, various regions typically adopt time-of-use pricing, with prices generally fluctuating from low to high and then back to low from 0:00 to 24:00. There are one or two peak-valley pricing cycles per day. For example, ... Figure 2 As shown, Figure 2 This diagram illustrates changes in electricity prices based on actual electricity consumption scenarios. Figure 2 As can be seen, over time, electricity prices typically fluctuate through a low-price phase, a flat-price phase, a peak-price phase, and a peak-price phase (usually occurring in June, July, and August each year). After entering the next cycle, prices then re-enter the low-price phase, with prices typically fluctuating by one to two times a day. Figure 2 The electricity price changes are shown below. For ease of explanation, the daily electricity price is assumed to have at least one cycle from a low-price phase to a flat-price phase to a peak-price phase to a very high-price phase. However, this does not constitute any limitation on this application; in the actual scenario being predicted, calculations can be performed based on the actual situation.

[0116] For a charging station to be predicted, its power data within a preset historical period, such as the past quarter (e.g., 90 days) or the past year (e.g., 365 days) from the current time, is read as energy storage prediction data. Usually, one year's data is more representative.

[0117] In some embodiments of this application, energy storage forecast data includes, but is not limited to, historical electricity consumption data and historical price data. Since the price and billing of electricity are usually based on a certain time unit, such as hours, when obtaining energy storage forecast data, this time unit can be used as the unit of measurement. For example, historical electricity consumption data represents the daily 24-hour electricity consumption data in hours over the past year; historical price data represents the daily 24-hour electricity purchase price data in hours over the past year.

[0118] For ease of explanation, the following example uses a preset historical duration of one year and a time unit of days.

[0119] In addition, some necessary parameters for the charging station are required, such as the rated power of the charging station transformer and the average cost per kilowatt-hour of energy storage equipment. These data can be accessed as needed, and this application does not impose any restrictions.

[0120] Step S120: Based on the energy storage prediction data, determine the first historical revenue of the charging station based on the first energy storage strategy and the second historical revenue of the charging station based on the second energy storage strategy, wherein the first energy storage strategy and the second energy storage strategy are established using a peak shaving and valley filling mechanism.

[0121] This application employs an electric peak-shifting and valley-filling mechanism to design two energy storage strategies, referred to as the first energy storage strategy and the second energy storage strategy. The first energy storage strategy uses the valley price period as the charging time and the par price, peak price, and peak price periods as the discharging time. The second energy storage strategy uses the valley price and par price periods as the charging time and the peak price and peak price periods as the discharging time.

[0122] It should be noted that an energy storage device cannot be charged and discharged simultaneously. In other words, if one energy storage device is charging, it cannot discharge, and vice versa. The difference between the first and second energy storage strategies lies in how they classify the grid parity period. In the first strategy, the grid parity period is classified as discharge time; in the second strategy, it is classified as charging time.

[0123] Then, based on the first and second energy storage strategies, the revenue of the charging station is calculated separately according to the energy storage forecast data. It should be noted that the first and second energy storage strategies are hypothetical behaviors. The charging and discharging behavior and data generated by the charging station in the past year are actual occurrences and were not executed according to either the first or second energy storage strategy.

[0124] The revenue of the charging station under the first energy storage strategy over the past year can be obtained through calculation, and is recorded as the first historical revenue. At the same time, the revenue of the charging station under the second energy storage strategy over the past year can also be obtained through calculation, and is recorded as the second historical revenue.

[0125] The first historical revenue includes, but is not limited to, the first daily revenue and the first phase revenue; the second historical revenue includes, but is not limited to, the second daily revenue and the second phase revenue. The first daily revenue can be defined as the revenue of the charging station for each natural day in the past year under the first energy storage strategy; the first phase revenue can be defined as the annual revenue of the charging station for the past year under the first energy storage strategy; the second daily revenue can be defined as the revenue of the charging station for each natural day in the past year under the second energy storage strategy; and the second phase revenue can be defined as the annual revenue of the charging station for the past year under the second energy storage strategy.

[0126] Specifically, in some embodiments of this application, in the above method, determining the first historical revenue of the charging station based on the first energy storage strategy includes: dividing each natural day into at least one charging and discharging cycle according to time sequence, and determining the first total charging amount and the first total electricity consumption for each charging and discharging cycle; determining whether the first total charging amount is greater than the first total electricity consumption; if so, determining the total energy storage discharge amount of the charging and discharging cycle as the first total electricity consumption, and determining the first cycle revenue of the charging and discharging cycle based on the first total consumption and the historical price data; if not, determining the total energy storage discharge amount of the charging and discharging cycle as the first total charging amount, and determining the first cycle revenue of the charging and discharging cycle based on the first total charging amount and the historical price data; accumulating the first cycle revenue of at least one charging and discharging cycle for each natural day to obtain the first daily revenue of the charging station; accumulating multiple first daily revenues within the preset historical time period to obtain the first stage revenue of the charging station.

[0127] Please refer to Figure 2 According to Figure 2 The illustrated pattern of electricity price changes divides a calendar day into at least one charge-discharge cycle; that is, one charge-discharge cycle includes one... Figure 2 The diagram illustrates the cycle from the trough price stage to the parity price stage, the peak price stage, and the sharp price stage.

[0128] Then, a charge-discharge cycle is divided into charging time and discharging time. In the first energy storage strategy, the valley price period is the charging time, and the parity price period, peak price period and peak price period are the discharging time.

[0129] Then, the relevant data is retrieved from the energy storage forecast data. This data includes the electricity consumption and purchase price for each hour (time unit) within this charge-discharge cycle. By summarizing this data, the first total charge and the first total electricity consumption for this charge-discharge cycle can be obtained. The first total charge is the cumulative value of the hourly charge during the charging period. The hourly charge is calculated as: Charging station transformer rated power - Electricity consumed by the charging station for vehicle charging in that hour (referred to as low-level electricity consumption). This is because during low-level (charging time), the vehicle is charged using mains power, which consumes a certain amount of transformer capacity. Therefore, the amount charged per hour to the energy storage equipment (battery) at the charging station is the rated power of the charging station transformer minus the low-level electricity consumption. The first total electricity consumption is obtained by summing the hourly electricity consumption during the grid price, peak price, and peak price periods.

[0130] The charging station's revenue is generated by profiting from the peak-valley electricity price difference. By comparing the relative size of the first total charging volume and the first total electricity consumption, the actual discharge volume of the charging station can be determined. Specifically, it is determined whether the first total charging volume is greater than the first total electricity consumption. If so, it means that the total energy storage discharge volume (actual discharge volume) of the charging station in this charging and discharging cycle is equal to the first total electricity consumption. Further, based on the first total consumption volume and historical price data, the revenue of the charging station in this charging and discharging cycle is determined, and this revenue is recorded as the revenue of the first cycle.

[0131] For the first daily earnings of each natural day, if a natural day contains only one charge-discharge cycle, then the earnings of the first cycle of that charge-discharge cycle are taken as the first daily earnings of that natural day; if a natural day contains multiple charge-discharge cycles, then the earnings of the first cycle of each charge-discharge cycle in a natural day are summed up to obtain the first daily earnings of that natural day.

[0132] For the stage revenue (annual revenue) within the preset historical period, the first stage revenue of the charging station can be obtained by summing the first daily revenue of each natural day within the preset historical period.

[0133] In some embodiments of this application, in the above method, determining the first cycle revenue of the charge-discharge cycle based on the first total usage and the historical price data includes: dividing the first total usage into a first average usage, a first peak usage, and a first peak usage based on the electricity consumption during the average, peak, and climax periods of the charge-discharge cycle; multiplying the difference between the average price and the valley price of the charge-discharge cycle by the first average usage to obtain the first average revenue; multiplying the difference between the peak price and the valley price of the charge-discharge cycle by the second average usage to obtain the first peak revenue; multiplying the difference between the climax price and the valley price of the charge-discharge cycle by the first climax usage to obtain the first climax revenue; and summing the first average revenue, the first peak revenue, and the first climax revenue to obtain the first cycle revenue of the charge-discharge cycle.

[0134] Within a single charge-discharge cycle, electricity consumption is statistically analyzed for the periods of flat price, peak price, and trough price. The electricity consumption during the flat price period, peak price period, and trough price period within that charge-discharge cycle are respectively denoted as the first flat price consumption, the first peak price consumption, and the first trough price consumption. Then, the difference between the flat price, peak price, trough price, and valley price is calculated, and multiplied by the electricity consumption for the corresponding period to obtain the first cycle revenue for that charge-discharge cycle. More clearly, the first cycle revenue can be calculated using the following formula:

[0135] First cycle revenue = (flat price - valley price) * first flat electricity consumption + (peak price - valley price) * first peak electricity consumption + (peak price - valley price) * first peak electricity consumption (1).

[0136] As mentioned above, by comparing the relative sizes of the first total charging amount and the first total electricity consumption, the actual discharge amount of the charging station can be determined. If the first total charging amount is less than the first total electricity consumption, then the total energy storage discharge amount (actual discharge amount) of the charging station is the first total charging amount. Furthermore, based on the first total charging amount and historical price data, the first cycle revenue of this charging and discharging cycle can be determined.

[0137] Specifically, in some embodiments of this application, the step of determining the first cycle revenue of the charge-discharge cycle based on the first total charging amount and the historical price data includes: determining whether the remaining energy storage capacity in one unit time of the charge-discharge cycle is greater than the electricity consumption in one unit time; if so, determining the product of the electricity consumption in one unit time and the electricity purchase price in one unit time as the unit gross revenue in one unit time; if not, determining the product of the remaining energy storage capacity in one unit time and the electricity purchase price in one unit time as the unit gross revenue in one unit time; summing the unit gross revenue of multiple units time of the charge-discharge cycle to obtain the cycle gross revenue of the charge-discharge cycle; subtracting the energy storage charging cost of the charge-discharge cycle from the cycle gross revenue to obtain the first cycle revenue of the charge-discharge cycle, wherein the energy storage charging cost is the product of the off-peak price period of the charge-discharge cycle and the off-peak price of the charge-discharge cycle.

[0138] Still using hours as the unit of time, for one hour within a charge-discharge cycle, the relative magnitude of the remaining energy storage capacity of the charging station and the electricity consumption during that hour is compared. If the remaining energy storage capacity of the charging station is greater than the electricity consumption during that hour, the electricity purchase price for that hour (the purchase price can be the off-peak price, parity price, peak price, or slack price) is multiplied by the electricity consumption during that hour, and the product is taken as the gross revenue (revenue before deducting costs) for that hour, recorded as the unit gross revenue. If the remaining energy storage capacity of the charging station is less than the electricity consumption during that hour, the electricity purchase price for that hour is multiplied by the remaining energy storage capacity for that hour, and the product is taken as the unit gross revenue for that hour. The gross revenue for each hour within the charge / discharge cycle is accumulated to obtain the cycle gross revenue for that charge / discharge cycle. Finally, the energy storage charging cost for that charge / discharge cycle is subtracted from the cycle gross revenue to obtain the first cycle revenue for that charge / discharge cycle. The energy storage charging cost is the product of the off-peak price period and the off-peak price for that charge / discharge cycle. The off-peak price period is the charging time at the charging station, and the off-peak price is the charging unit price per hour. Simply put, the energy storage charging cost is: off-peak price * number of charging hours. In some embodiments of this application, in the above method, the second energy storage strategy uses the off-peak and flat price periods as charging times and the peak and slack price periods as discharging times. The calculation method for the second historical revenue of the second energy storage strategy is consistent with that of the first historical revenue of the first energy storage strategy, the only difference being that the flat price period is assigned as the charging time. Based on this, in some embodiments of this application, determining the second historical revenue of the charging station based on the second energy storage strategy includes: dividing each natural day into at least one charging / discharging cycle according to time sequence, and determining the second total charging amount and the second total electricity consumption for each charging / discharging cycle; determining whether the second total charging amount is greater than... If the second total electricity consumption is true, then the total energy storage discharge of the charging and discharging cycle is determined as the second total electricity consumption, and the second cycle revenue of the charging and discharging cycle is determined based on the second total consumption and the historical price data; if not, then the total energy storage discharge of the charging and discharging cycle is determined as the second total charging, and the second cycle revenue of the charging and discharging cycle is determined based on the second total charging and the historical price data; the second cycle revenue of at least one charging and discharging cycle for each natural day is accumulated to obtain the second daily revenue of the charging station; multiple second daily revenues within the preset historical time period are accumulated to obtain the second stage revenue of the charging station.

[0139] In some embodiments of this application, in the above method, determining the second cycle revenue of the charge-discharge cycle based on the second total consumption and the historical price data includes: dividing the second total electricity consumption into a second peak consumption and a second peak consumption based on the electricity consumption during the flat, peak, and slack price periods in the charge-discharge cycle; multiplying the difference between the peak price and the valley price of the charge-discharge cycle by the second flat consumption to obtain the second peak price revenue; multiplying the difference between the slack price and the valley price of the charge-discharge cycle by the second slack consumption to obtain the second slack price revenue; and summing the second peak price revenue and the second slack price revenue to obtain the second cycle revenue of the charge-discharge cycle.

[0140] In some embodiments of this application, determining the second cycle revenue of the charge-discharge cycle based on the second total charging amount and the historical price data includes: determining whether the remaining energy storage capacity in one unit time of the charge-discharge cycle is greater than the electricity consumption in one unit time; if so, determining the product of the electricity consumption in one unit time and the electricity purchase price in one unit time as the unit gross revenue in one unit time; if not, determining the product of the remaining energy storage capacity in one unit time and the electricity purchase price in one unit time as the unit gross revenue in one unit time; summing the unit gross revenue of multiple units time of the charge-discharge cycle to obtain the cycle gross revenue of the charge-discharge cycle; subtracting the energy storage charging cost of the charge-discharge cycle from the cycle gross revenue to obtain the second cycle revenue of the charge-discharge cycle, wherein the energy storage charging cost is the product of the off-peak price period of the charge-discharge cycle and the off-peak price of the charge-discharge cycle.

[0141] The calculation method for the second historical return will not be elaborated here; please refer to the calculation method for the first historical return mentioned above.

[0142] Step S130: Based on the first historical revenue and the second historical revenue, determine the preferred energy storage strategy for the charging station and whether the charging station is suitable for adding energy storage equipment.

[0143] Finally, based on the first and second historical returns, the optimal energy storage strategy for the charging station and whether the charging station is suitable for adding energy storage equipment are determined.

[0144] Specifically, the first historical returns of the first energy storage strategy include: the first daily returns and the first phase returns, and the second historical returns of the second energy storage strategy include: the second daily returns and the second phase returns.

[0145] In some embodiments of this application, in the above method, determining the preferred energy storage strategy of the charging station and whether it is suitable to add energy storage equipment based on the first historical revenue and the second historical revenue includes: determining the maximum value of the first stage revenue and the second stage revenue, and taking the energy storage strategy corresponding to the maximum value as the preferred energy storage strategy.

[0146] Taking the example that both the first-stage and second-stage revenues are annual revenues, the relative sizes of the first-stage and second-stage revenues are compared. The one with the larger revenue is selected as the preferred energy storage strategy.

[0147] The first historical returns include: first daily returns and first phase returns, the first phase returns being the first year's returns; the second historical returns include: second daily returns and second phase returns, the second phase returns being the second year's returns.

[0148] In some embodiments of this application, the first-stage revenue is the revenue of the first year, and the second-stage revenue is the revenue of the second year; the step of determining the preferred energy storage strategy for the charging station and whether to add energy storage equipment based on the first historical revenue and the second historical revenue further includes: reading the maximum daily charging volume of the determined preferred energy storage strategy from the historical electricity consumption data; using the maximum daily charging volume as the required energy storage equipment capacity of the charging station to determine the cost of building the energy storage equipment; determining the payback period for the equipment based on the annual revenue of the preferred energy storage strategy and the cost of building the energy storage equipment; and determining whether the charging station is suitable for adding energy storage equipment based on multiple preset thresholds, the daily revenue of the preferred energy storage strategy, and the payback period for the equipment.

[0149] After determining the optimal energy storage strategy, the daily charging volume of the charging station under this strategy is read from historical electricity consumption data. The maximum value is determined and recorded as the daily maximum charging volume. This daily maximum charging volume is used as the capacity of the energy storage equipment to be added to the charging station, recorded as the required energy storage capacity. The cost of building the added energy storage equipment is calculated based on this required capacity. Specifically, the average cost per kilowatt-hour of energy storage equipment at the charging station is multiplied by the determined required energy storage capacity, and the product of the two is recorded as the first product, which is the cost of building the energy storage equipment to be added to the charging station.

[0150] After obtaining the predicted cost of building the energy storage equipment, the payback period can be determined based on the annual revenue of the preferred energy storage strategy and the cost of building the energy storage equipment. Specifically, the determined cost of building the energy storage equipment is divided by the annual revenue of the preferred energy storage strategy (which can be the revenue of the first year or the revenue of the second year), and the quotient is recorded as the first quotient. This gives the payback period of the energy storage equipment to be added to the charging station, such as 5 years.

[0151] Finally, based on multiple preset thresholds, the daily revenue of the preferred energy storage strategy, and the payback period of the equipment, it is determined whether the charging station is suitable for adding energy storage equipment.

[0152] A pre-set rule is established to determine whether a charging station is suitable for adding energy storage equipment. If the daily revenue and payback period of the preferred energy storage strategy meet the rule, the charging station is deemed suitable for adding energy storage equipment; otherwise, the charging station is deemed unsuitable for adding energy storage equipment.

[0153] In some embodiments of this application, the above method includes, but is not limited to, a daily revenue threshold, a number of days threshold, and a payback period threshold. Determining whether a charging station is suitable for adding energy storage equipment based on the preset multiple thresholds, the daily revenue of the preferred energy storage strategy, and the payback period includes: determining the number of days within a preset historical period where the daily revenue of the preferred energy storage strategy is greater than the daily revenue threshold; determining whether the number of days is greater than the number of days threshold; if not, determining that the charging station is not suitable for adding energy storage equipment; if so, determining whether the payback period is less than the payback period threshold; if not, determining that the charging station is not suitable for adding energy storage equipment; if so, determining that the charging station is suitable for adding energy storage equipment.

[0154] For example, over the past year, the daily revenue under the preferred energy storage strategy is read to determine if the daily revenue exceeds a daily revenue threshold. If it does, the number of days with revenue exceeding the threshold is incremented by one. This operation is performed for each daily revenue, resulting in a cumulative value of the number of days with revenue exceeding the threshold. This cumulative value is then compared with a preset number of days threshold. If the cumulative value is less than the threshold, it indicates that the charging station's profitability is poor and it is not suitable to add energy storage equipment. If the cumulative value is greater than the threshold, it is further determined whether the payback period for the equipment is less than a preset payback period threshold. If it is, the charging station is suitable for adding energy storage equipment; otherwise, it is not suitable.

[0155] Depend on Figure 1As shown in the method, this application provides a prediction method for configuring energy storage in charging stations. It obtains real historical data of a charging station over a certain period as the predicted energy storage data for that charging station. The predicted energy storage data may include, but is not limited to, historical electricity consumption data and historical price data. Based on a peak-shaving and valley-filling strategy, two different energy storage methods are designed, one designated as the first energy storage strategy and the other as the second energy storage strategy. Then, according to the first energy storage strategy, the first historical revenue of the charging station over the historical period is calculated based on the predicted energy storage data. Simultaneously, according to the second energy storage strategy, the second historical revenue of the charging station over the historical period is calculated based on the predicted energy storage data. The first and second historical revenues are compared to determine which of the two energy storage strategies is more suitable for the charging station. Furthermore, based on the selected energy storage strategy, it can be determined whether the charging station is suitable for adding energy storage equipment. This application designs two energy storage strategies based on the principle of peak shaving and valley filling. The returns of the two strategies are calculated using real historical data from charging stations. Based on the returns, a preferred energy storage strategy is predicted for the charging station. Furthermore, the suitability of adding energy storage equipment to the charging station is determined based on the preferred strategy. The prediction results are accurate, allowing for power regulation during peak hours to reduce grid pressure. It also provides reliable reference information for deciding whether to add energy storage equipment to the charging station, enabling it to obtain greater returns and avoid investment risks.

[0156] Figure 3 A flowchart illustrating a testing method for a charging station energy storage configuration according to another embodiment of this application is shown. Figure 3 As can be seen, this embodiment includes:

[0157] Read the rated power of the transformer at the charging station, historical electricity consumption data for the past year in hourly terms, and historical electricity purchase price data.

[0158] Then, the revenue calculations for the first and second energy storage strategies are performed separately. Taking the second energy storage strategy as an example, a natural day is divided into at least one charging and discharging cycle, with the valley and parity price phases being the charging time and the peak and slack price phases being the discharging time.

[0159] Calculate the second total charge and the second total electricity consumption during the charge and discharge cycle. The second total charge = (transformer rated power - mains electricity consumption) * (valley + flat) price duration; the second total electricity consumption = the sum of electricity consumption during peak and off-peak price periods.

[0160] Determine whether the second total charging amount is greater than the second total electricity consumption. If so, determine that the total energy storage discharge amount is the second total electricity consumption, and the second cycle revenue of the charging and discharging cycle = (peak price - valley price) * first peak electricity consumption + (peak price - valley price) * first peak electricity consumption.

[0161] If not, determine whether the remaining energy storage capacity per hour is greater than the total electricity consumption per hour. If yes, the hourly revenue = hourly electricity consumption * hourly electricity price; if not, the hourly revenue = remaining energy storage capacity per hour * hourly electricity price. The revenue for the second cycle of the charge / discharge cycle = the sum of the hourly revenues for each hour of that charge / discharge cycle.

[0162] Determine if there are still charge / discharge cycles in the current day. If so, repeat the above steps until the second cycle revenue of the charge / discharge cycles in the current day has been calculated.

[0163] The second daily revenue is obtained by summing up the revenue from multiple second-cycle charging and discharging cycles over a natural day under the second energy storage strategy. Furthermore, the second daily revenue is obtained by summing up all the second daily revenues over the past year.

[0164] The calculation for the first energy storage strategy is the same as for the second energy storage strategy; please refer to the aforementioned content and... Figure 3 This will not be elaborated upon here.

[0165] Based on the relative magnitude of the returns in the first and second years, the energy storage strategy corresponding to the larger return is selected as the preferred energy storage strategy.

[0166] Read the maximum daily charging capacity of the preferred energy storage strategy and calculate the cost of building the energy storage equipment.

[0167] Determine the number of days under the preferred energy storage strategy where the daily revenue exceeds the daily revenue threshold, and determine if this number of days exceeds a preset threshold. If not, directly determine that the charging station is not suitable for adding energy storage equipment. If so, determine if the payback period for the equipment is less than a preset threshold. If not, directly determine that the charging station is not suitable for adding energy storage equipment; if so, determine that the charging station is suitable for adding energy storage equipment. The process ends.

[0168] Figure 4 A schematic diagram of a predictive device for a charging station energy storage configuration according to an embodiment of this application is shown. Figure 4 It can be seen that the predictive device 400 for the energy storage configuration of the charging station includes:

[0169] The acquisition unit 410 is used to acquire energy storage prediction data of the charging station within a preset historical time period. The energy storage prediction data includes: historical electricity consumption data and historical price data.

[0170] The revenue retrospective unit 420 is used to determine the first historical revenue of the charging station based on the energy storage prediction data, and to determine the second historical revenue of the charging station based on the first energy storage strategy, wherein the first energy storage strategy and the second energy storage strategy are established using a peak shaving and valley filling mechanism.

[0171] The prediction unit 430 is used to determine the preferred energy storage strategy of the charging station and whether the charging station is suitable for adding energy storage equipment based on the first historical revenue and the second historical revenue.

[0172] In some embodiments of this application, in the above-described device, the first energy storage strategy is to use off-peak price periods as charging times and flat, peak, and high-price periods as discharging times; the revenue retrospective unit 420 is used to divide each natural day into at least one charging and discharging cycle according to time sequence, and determine the first total charging amount and the first total electricity consumption for each charging and discharging cycle; determine whether the first total charging amount is greater than the first total electricity consumption, and if so, determine the total energy storage discharge amount of the charging and discharging cycle as the first total electricity consumption, and determine the first cycle revenue of the charging and discharging cycle based on the first total consumption amount and the historical price data; if not, determine the total energy storage discharge amount of the charging and discharging cycle as the first total charging amount, and determine the first cycle revenue of the charging and discharging cycle based on the first total charging amount and the historical price data; accumulate the first cycle revenue of at least one charging and discharging cycle for each natural day to obtain the first daily revenue of the charging station; accumulate multiple first daily revenues within the preset historical time period to obtain the first stage revenue of the charging station.

[0173] In some embodiments of this application, in the above-described apparatus, the revenue retrospective unit 420 is configured to divide the first total electricity consumption into a first flat electricity consumption, a first peak electricity consumption, and a first peak electricity consumption based on the electricity consumption during the flat, peak, and apex price periods in the charge-discharge cycle; multiply the difference between the flat price and the valley price of the charge-discharge cycle by the first flat electricity consumption to obtain the first flat price revenue; multiply the difference between the peak price and the valley price of the charge-discharge cycle by the second flat electricity consumption to obtain the first peak price revenue; multiply the difference between the apex price and the valley price of the charge-discharge cycle by the first apex electricity consumption to obtain the first apex price revenue; and sum the first flat price revenue, the first peak price revenue, and the first apex price revenue to obtain the first cycle revenue of the charge-discharge cycle.

[0174] In some embodiments of this application, in the above-described apparatus, the revenue tracking unit 420 is used to determine whether the remaining energy storage capacity per unit time of the charge-discharge cycle is greater than the electricity consumption per unit time; if yes, the product of the electricity consumption per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time; if no, the product of the remaining energy storage capacity per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time; the unit gross revenues of multiple units time of the charge-discharge cycle are accumulated to obtain the cycle gross revenue of the charge-discharge cycle; the energy storage charging cost of the charge-discharge cycle is subtracted from the cycle gross revenue to obtain the first cycle revenue of the charge-discharge cycle, wherein the energy storage charging cost is the product of the off-peak price period of the charge-discharge cycle and the off-peak price of the charge-discharge cycle.

[0175] In some embodiments of this application, in the above-described device, the second energy storage strategy is to use the off-peak and flat price periods as charging times and the peak and slack price periods as discharging times; the revenue retrospective unit 420 is used to divide each natural day into at least one charging and discharging cycle according to the time sequence, and determine the second total charging amount and the second total electricity consumption for each charging and discharging cycle; determine whether the second total charging amount is greater than the second total electricity consumption, and if so, determine the total energy storage discharge amount of the charging and discharging cycle as the second total electricity consumption, and determine the second cycle revenue of the charging and discharging cycle according to the second total consumption amount and the historical price data; if not, determine the total energy storage discharge amount of the charging and discharging cycle as the second total charging amount, and determine the second cycle revenue of the charging and discharging cycle according to the second total charging amount and the historical price data; accumulate the second cycle revenue of at least one charging and discharging cycle for each natural day to obtain the second daily revenue of the charging station; accumulate multiple second daily revenues within the preset historical time period to obtain the second stage revenue of the charging station.

[0176] In some embodiments of this application, in the above-described apparatus, the revenue retrospective unit 420 is used to divide the second total electricity consumption into a second peak electricity consumption and a second peak electricity consumption based on the electricity consumption during the flat, peak, and apex price periods in the charge-discharge cycle; multiply the difference between the peak price and valley price of the charge-discharge cycle by the second flat electricity consumption to obtain the second peak price revenue; multiply the difference between the apex price and valley price of the charge-discharge cycle by the second apex electricity consumption to obtain the second apex price revenue; and sum the second peak price revenue and the second apex price revenue to obtain the second cycle revenue of the charge-discharge cycle.

[0177] In some embodiments of this application, in the above-described apparatus, the revenue tracking unit 420 is used to determine whether the remaining energy storage capacity per unit time of the charge-discharge cycle is greater than the electricity consumption per unit time; if yes, the product of the electricity consumption per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time; if no, the product of the remaining energy storage capacity per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time; the unit gross revenues of multiple units time of the charge-discharge cycle are accumulated to obtain the cycle gross revenue of the charge-discharge cycle; the energy storage charging cost of the charge-discharge cycle is subtracted from the cycle gross revenue to obtain the second cycle revenue of the charge-discharge cycle, wherein the energy storage charging cost is the product of the off-peak price period of the charging cycle and the off-peak price of the charge-discharge cycle.

[0178] In some embodiments of this application, in the above-described apparatus, the first historical revenue includes: a first daily revenue and a first phase revenue, and the second historical revenue includes: a second daily revenue and a second phase revenue; the prediction unit 430 is used to determine the maximum value of the first phase revenue and the second phase revenue, and to use the energy storage strategy corresponding to the maximum value as the preferred energy storage strategy.

[0179] In some embodiments of this application, in the above-described apparatus, the prediction unit 430 is further configured to: read the maximum daily charging amount of the determined preferred energy storage strategy from the historical electricity consumption data; use the maximum daily charging amount as the required energy storage equipment capacity of the charging station to determine the cost of building the energy storage equipment; determine the payback period for the equipment based on the phased benefits of the preferred energy storage strategy and the cost of building the energy storage equipment; and determine whether the charging station is suitable for adding energy storage equipment based on multiple preset thresholds, the daily benefits of the preferred energy storage strategy, and the payback period for the equipment.

[0180] In some embodiments of this application, in the above-described apparatus, the prediction unit 430 is used to take the maximum daily charging amount as the required energy storage capacity of the charging station, determine the first product of the average cost per kilowatt-hour of energy storage equipment and the required energy storage capacity to obtain the cost of building the energy storage equipment; and to determine the first quotient of the cost of building the energy storage equipment and the stage benefit of the preferred energy storage strategy to obtain the payback period of the equipment.

[0181] In some embodiments of this application, in the above-described apparatus, the plurality of thresholds includes: a daily revenue threshold, a number of days threshold, and a payback period threshold; the prediction unit 430 is used to determine the number of days within a preset historical period where the daily revenue of the preferred energy storage strategy is greater than the daily revenue threshold; determine whether the number of days is greater than the number of days threshold, and if not, determine that the charging station is not suitable for adding energy storage equipment; if so, determine whether the payback period of the equipment is less than the payback period threshold, and if not, determine that the charging station is not suitable for adding energy storage equipment; if so, determine that the charging station is suitable for adding energy storage equipment.

[0182] It should be noted that the aforementioned predictive device for charging station energy storage configuration can implement the aforementioned predictive method for charging station energy storage configuration, and will not be elaborated further.

[0183] Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Please refer to it. Figure 5 At the hardware level, the electronic device includes a processor, and optionally also includes an internal bus, a network interface, and memory. The memory may include main memory, such as high-speed random-access memory (RAM), or non-volatile memory, such as at least one disk drive. Of course, the electronic device may also include other hardware required for other business operations.

[0184] The processor, network interface, and memory can be interconnected via an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0185] Memory is used to store programs. Specifically, programs may include program code, which includes computer operation instructions. Memory may include main memory and non-volatile memory, and provides instructions and data to the processor.

[0186] The processor reads the corresponding computer program from non-volatile memory into main memory and then runs it, forming a predictive device for the energy storage configuration of the charging station at the logical level. The processor executes the program stored in memory and specifically performs the aforementioned method.

[0187] The above is as stated in this application. Figure 4 The method executed by the predictive device for charging station energy storage configuration disclosed in the illustrated embodiment can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the field, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory, and the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method.

[0188] The electronic device can also perform Figure 4 A method for executing a predictive device for the energy storage configuration of a charging station, and the implementation of the predictive device for the energy storage configuration of a charging station in... Figure 4 The functions of the embodiments shown are not described in detail here.

[0189] This application also proposes a computer-readable storage medium that stores one or more programs, the programs including instructions that, when executed by an electronic device including multiple applications, enable the electronic device to perform... Figure 4 The method executed by the prediction device of the charging station energy storage configuration in the illustrated embodiment is specifically used to execute the aforementioned method.

[0190] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0191] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0192] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0193] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0194] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0195] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0196] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0197] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0198] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0199] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for predicting the energy storage configuration of a charging station, characterized in that, include: Obtain energy storage prediction data for the charging station within a preset historical time period. The energy storage prediction data includes: historical electricity consumption data and historical price data. Based on the energy storage forecast data, a first historical revenue of the charging station is determined based on a first energy storage strategy, and a second historical revenue of the charging station is determined based on a second energy storage strategy. The first and second energy storage strategies are established using a peak-shaving and valley-filling mechanism. The first energy storage strategy uses off-peak price periods as charging times and periods of parity, peak, and high-price prices as discharging times. The second energy storage strategy uses off-peak and parity price periods as charging times and periods of peak and high-price prices as discharging times. The first historical revenue includes a first daily revenue and a first-stage revenue, with the first-stage revenue being the first-year revenue. The second historical revenue includes a second daily revenue and a second-stage revenue, with the second-stage revenue being the second-year revenue. Based on the first historical revenue and the second historical revenue, determine the preferred energy storage strategy for the charging station and whether the charging station is suitable for adding energy storage equipment; The step of determining the preferred energy storage strategy for the charging station and whether it is suitable to add energy storage equipment based on the first historical revenue and the second historical revenue includes: Determine the maximum value of the first year's revenue and the second year's revenue, and use the energy storage strategy corresponding to the maximum value as the preferred energy storage strategy; The maximum daily charging capacity of the preferred energy storage strategy is determined from the historical electricity consumption data. The maximum daily charging volume is used as the required energy storage capacity of the charging station to determine the cost of building the energy storage equipment. The payback period for the equipment is determined based on the annual revenue of the preferred energy storage strategy and the cost of building the energy storage equipment. Based on multiple preset thresholds, the daily revenue of the preferred energy storage strategy, and the payback period of the equipment, it is determined whether the charging station is suitable for adding energy storage equipment.

2. The method according to claim 1, characterized in that, The determination of the first historical revenue of the charging station based on the first energy storage strategy includes: Each natural day is divided into at least one charge-discharge cycle according to the time sequence, and the first total charge and the first total power consumption of each charge-discharge cycle are determined. Determine whether the first total charging amount is greater than the first total electricity consumption. If so, determine the total energy storage discharge amount of the charge-discharge cycle as the first total electricity consumption, and determine the first cycle revenue of the charge-discharge cycle based on the first total electricity consumption and the historical price data. If not, then the total energy storage discharge of the charge-discharge cycle is determined to be the first total charge, and the first cycle revenue of the charge-discharge cycle is determined based on the first total charge and the historical price data. The first daily revenue of the charging station is obtained by summing the revenue of the first cycle of at least one charge-discharge cycle for each natural day. The first-stage revenue of the charging station is obtained by summing up the multiple first daily revenues within the preset historical time period.

3. The method according to claim 2, characterized in that, The step of determining the first cycle revenue of the charging and discharging cycle based on the first total electricity consumption and the historical price data includes: Based on the electricity consumption during the flat, peak, and peak price periods in the charging and discharging cycle, the first total electricity consumption is divided into the first flat electricity consumption, the first peak electricity consumption, and the first peak electricity consumption. The difference between the parity price and the valley price during the charging and discharging cycle is multiplied by the first average electricity consumption to obtain the first parity revenue; the difference between the peak price and the valley price during the charging and discharging cycle is multiplied by the first peak electricity consumption to obtain the first peak revenue; the difference between the peak price and the valley price during the charging and discharging cycle is multiplied by the first peak electricity consumption to obtain the first peak revenue. The first parity return, the first peak return, and the first sharpest return are summed to obtain the first cycle return of the charge-discharge cycle.

4. The method according to claim 2, characterized in that, The step of determining the first cycle revenue of the charge-discharge cycle based on the first total charging amount and the historical price data includes: Determine whether the remaining energy storage capacity per unit time of the charge / discharge cycle is greater than the energy consumption per unit time; If yes, then the product of the electricity consumption per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time; if no, then the product of the remaining energy storage capacity per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time. The gross revenue per unit time of the charge-discharge cycle is summed to obtain the gross revenue of the charge-discharge cycle. The first cycle revenue of the charge-discharge cycle is obtained by subtracting the energy storage charging cost of the charge-discharge cycle from the gross revenue of the cycle. The energy storage charging cost is the product of the off-peak price period of the charge-discharge cycle and the off-peak price of the charge-discharge cycle.

5. The method according to claim 1, characterized in that, The determination of the second historical revenue of the charging station based on the second energy storage strategy includes: Each natural day is divided into at least one charge-discharge cycle according to the time sequence, and the second total charge and the second total power consumption of each charge-discharge cycle are determined. Determine whether the second total charging amount is greater than the second total electricity consumption. If so, determine the total energy storage discharge amount of the charge-discharge cycle as the second total electricity consumption, and determine the second cycle revenue of the charge-discharge cycle based on the second total electricity consumption and the historical price data. If not, then the total energy storage discharge of the charge-discharge cycle is determined to be the second total charge, and the second cycle revenue of the charge-discharge cycle is determined based on the second total charge and the historical price data. The second daily revenue of the charging station is obtained by summing the second-cycle revenue of at least one charge-discharge cycle for each natural day. The second-stage revenue of the charging station is obtained by summing up the multiple second daily revenues within the preset historical time period.

6. The method according to claim 5, characterized in that, The step of determining the second-cycle revenue of the charging and discharging cycle based on the second total electricity consumption and the historical price data includes: Based on the electricity consumption during the off-peak, peak, and slack periods in the charging and discharging cycle, the second total electricity consumption is divided into the second peak electricity consumption and the second slack electricity consumption. The second peak price revenue is obtained by multiplying the difference between the peak price and the valley price during the charge-discharge cycle by the second peak electricity consumption; the second peak price revenue is obtained by multiplying the difference between the high price and the low price during the charge-discharge cycle by the second high electricity consumption. The second peak price gain and the second sharp price gain are summed to obtain the second cycle gain of the charge-discharge cycle.

7. The method according to claim 5, characterized in that, The step of determining the second-cycle revenue of the charge-discharge cycle based on the second total charging amount and the historical price data includes: Determine whether the remaining energy storage capacity per unit time of the charge / discharge cycle is greater than the energy consumption per unit time; If yes, then the product of the electricity consumption per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time; if no, then the product of the remaining energy storage capacity per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time. The gross revenue per unit time of the charge-discharge cycle is summed to obtain the gross revenue of the charge-discharge cycle. The second cycle revenue of the charge-discharge cycle is obtained by subtracting the energy storage charging cost of the charge-discharge cycle from the gross revenue of the cycle. The energy storage charging cost is the product of the off-peak price period of the charge-discharge cycle and the off-peak price of the charge-discharge cycle.

8. The method according to claim 1, characterized in that, The step of using the maximum daily charging volume as the required energy storage capacity for the charging station and determining the cost of building the energy storage equipment includes: The maximum daily charging volume is taken as the required energy storage capacity of the charging station. The average cost per kilowatt-hour of energy storage equipment is determined by multiplying the average cost per kilowatt-hour of energy storage equipment by the required energy storage capacity to obtain the cost of building the energy storage equipment. The process of determining the payback period for the equipment based on the annual revenue of the preferred energy storage strategy and the cost of constructing the energy storage equipment includes: The first quotient of the cost of building the energy storage equipment and the annual return of the preferred energy storage strategy is used to obtain the payback period for the equipment.

9. The method according to claim 1, characterized in that, The multiple thresholds include: daily revenue threshold, number of days threshold, and payback period threshold; The determination of whether a charging station is suitable for adding energy storage equipment, based on multiple preset thresholds, the daily revenue of the preferred energy storage strategy, and the payback period of the equipment, includes: Within a preset historical period, determine the number of days in which the daily revenue of the preferred energy storage strategy is greater than the daily revenue threshold; Determine whether the number of days is greater than the number of days threshold; if not, determine that the charging station is not suitable for adding energy storage equipment. If so, determine whether the payback period for the equipment is less than the payback period threshold. If not, determine that the charging station is not suitable for adding energy storage equipment; if so, determine that the charging station is suitable for adding energy storage equipment.

10. A predictive device for energy storage configuration in a charging station, characterized in that, The device includes: The acquisition unit is used to acquire energy storage prediction data of the charging station within a preset historical time period. The energy storage prediction data includes: historical electricity consumption data and historical price data. The revenue retrospective unit is used to determine the first historical revenue of the charging station based on the energy storage forecast data, and to determine the second historical revenue of the charging station based on the first energy storage strategy and the second energy storage strategy. The first and second energy storage strategies are established using a peak-shaving and valley-filling mechanism. The first energy storage strategy uses valley price periods as charging times and flat price, peak price, and peak price periods as discharging times. The second energy storage strategy uses valley price and flat price periods as charging times and peak price and peak price periods as discharging times. The first historical revenue includes a first daily revenue and a first phase revenue, where the first phase revenue is the first year's revenue. The second historical revenue includes a second daily revenue and a second phase revenue, where the second phase revenue is the second year's revenue. The prediction unit is used to determine the preferred energy storage strategy of the charging station and whether the charging station is suitable for adding energy storage equipment based on the first historical revenue and the second historical revenue. The prediction unit is used to determine the maximum value of the first-year revenue and the second-year revenue, and to select the energy storage strategy corresponding to the maximum value as the preferred energy storage strategy; to read the maximum daily charging volume of the preferred energy storage strategy from the historical electricity consumption data; to use the maximum daily charging volume as the required energy storage equipment capacity of the charging station, and to determine the cost of building the energy storage equipment; to determine the payback period for the equipment based on the annual revenue of the preferred energy storage strategy and the cost of building the energy storage equipment; and to determine whether the charging station is suitable for adding energy storage equipment based on multiple preset thresholds, the daily revenue of the preferred energy storage strategy, and the payback period for the equipment.

11. The apparatus according to claim 10, characterized in that, The revenue tracking unit is used to divide each natural day into at least one charge-discharge cycle according to the time sequence, and to determine the first total charge and the first total electricity consumption for each charge-discharge cycle. Determine whether the first total charging amount is greater than the first total electricity consumption. If so, determine the total energy storage discharge amount of the charge-discharge cycle as the first total electricity consumption, and determine the first cycle revenue of the charge-discharge cycle based on the first total electricity consumption and the historical price data. If not, then the total energy storage discharge of the charge-discharge cycle is determined to be the first total charge, and the first cycle revenue of the charge-discharge cycle is determined based on the first total charge and the historical price data. The first daily revenue of the charging station is obtained by summing the revenue of the first cycle of at least one charge-discharge cycle for each natural day. The first-stage revenue of the charging station is obtained by summing up the multiple first daily revenues within the preset historical time period.

12. The apparatus according to claim 11, characterized in that, The revenue tracking unit is used to divide the first total electricity consumption into a first flat electricity consumption, a first peak electricity consumption, and a first peak electricity consumption based on the electricity consumption during the flat price, peak price, and peak price periods in the charging and discharging cycle. The difference between the parity price and the valley price during the charging and discharging cycle is multiplied by the first average electricity consumption to obtain the first parity revenue; the difference between the peak price and the valley price during the charging and discharging cycle is multiplied by the first peak electricity consumption to obtain the first peak revenue; the difference between the peak price and the valley price during the charging and discharging cycle is multiplied by the first peak electricity consumption to obtain the first peak revenue. The first parity return, the first peak return, and the first sharpest return are summed to obtain the first cycle return of the charge-discharge cycle.

13. The apparatus according to claim 11, characterized in that, The revenue tracking unit is used to determine whether the remaining energy storage capacity per unit time of the charge-discharge cycle is greater than the energy consumption per unit time. If so, the product of the electricity consumption per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time. If not, then the product of the remaining energy storage capacity per unit time and the purchase price of electricity per unit time is determined as the unit gross revenue per unit time. The gross revenue per unit time of the charge-discharge cycle is summed to obtain the gross revenue of the charge-discharge cycle. The first cycle revenue of the charge-discharge cycle is obtained by subtracting the energy storage charging cost of the charge-discharge cycle from the gross revenue of the cycle. The energy storage charging cost is the product of the off-peak price period of the charge-discharge cycle and the off-peak price of the charge-discharge cycle.

14. The apparatus according to claim 10, characterized in that, The revenue backtracking unit is used to divide each natural day into at least one charge-discharge cycle according to the time sequence, and to determine the second total charge and the second total power consumption for each charge-discharge cycle. Determine whether the second total charging amount is greater than the second total electricity consumption. If so, determine the total energy storage discharge amount of the charge-discharge cycle as the second total electricity consumption, and determine the second cycle revenue of the charge-discharge cycle based on the second total electricity consumption and the historical price data. If not, then the total energy storage discharge of the charge-discharge cycle is determined to be the second total charge, and the second cycle revenue of the charge-discharge cycle is determined based on the second total charge and the historical price data. The second daily revenue of the charging station is obtained by summing the second-cycle revenue of at least one charge-discharge cycle for each natural day. The second-stage revenue of the charging station is obtained by summing up the multiple second daily revenues within the preset historical time period.

15. The apparatus according to claim 14, characterized in that, The revenue tracking unit is used to divide the second total electricity consumption into the second peak electricity consumption and the second peak electricity consumption based on the electricity consumption during the parity, peak and slack price periods in the charging and discharging cycle. The second peak price revenue is obtained by multiplying the difference between the peak price and the valley price during the charge-discharge cycle by the second peak electricity consumption; the second peak price revenue is obtained by multiplying the difference between the high price and the low price during the charge-discharge cycle by the second high electricity consumption. The second peak price gain and the second sharp price gain are summed to obtain the second cycle gain of the charge-discharge cycle.

16. The apparatus according to claim 14, characterized in that, The revenue tracking unit is used to determine whether the remaining energy storage capacity per unit time of the charge-discharge cycle is greater than the energy consumption per unit time. If so, the product of the electricity consumption per unit time and the electricity purchase price per unit time is determined as the unit gross revenue per unit time. If not, then the product of the remaining energy storage capacity per unit time and the purchase price of electricity per unit time is determined as the unit gross revenue per unit time. The gross revenue per unit time of the charge-discharge cycle is summed to obtain the gross revenue of the charge-discharge cycle. The second cycle revenue of the charge-discharge cycle is obtained by subtracting the energy storage charging cost of the charge-discharge cycle from the gross revenue of the cycle. The energy storage charging cost is the product of the off-peak price period of the charge-discharge cycle and the off-peak price of the charge-discharge cycle.

17. The apparatus according to claim 10, characterized in that, The prediction unit is used to take the maximum daily charging volume as the required energy storage capacity of the charging station, determine the first product of the average cost per kilowatt-hour of energy storage equipment and the required energy storage capacity, and obtain the cost of building the energy storage equipment. as well as, A first quotient is used to determine the cost of building the energy storage equipment and the phased benefits of the preferred energy storage strategy, thereby obtaining the payback period for the equipment.

18. The apparatus according to claim 10, characterized in that, The multiple thresholds include: daily revenue threshold, number of days threshold, and payback period threshold; The prediction unit is used to determine the number of days within a preset historical period where the daily revenue of the preferred energy storage strategy is greater than the daily revenue threshold. Determine whether the number of days is greater than the number of days threshold; if not, determine that the charging station is not suitable for adding energy storage equipment. If so, determine whether the payback period for the equipment is less than the payback period threshold. If not, determine that the charging station is not suitable for adding energy storage equipment; if so, determine that the charging station is suitable for adding energy storage equipment.

19. An electronic device comprising: processor; as well as A memory configured to store computer-executable instructions, characterized in that, when executed, the executable instructions cause the processor to perform the prediction method for the energy storage configuration of a charging station as described in any one of claims 1 to 9.

20. A computer-readable storage medium storing one or more programs, characterized in that, When the one or more programs are executed by an electronic device including multiple applications, the electronic device performs the prediction method for the energy storage configuration of the charging station according to any one of claims 1 to 9.

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