A charging power adjustable range calculation method, system, device and medium

Abstract

The application provides a charging power adjustable range calculation method, system, device and medium, comprising: collecting historical charging orders of a user, calculating the maximum extended charging time of the user in each charging scene on a charging pile in a predicted period before and in the predicted period according to the user type and the historical charging orders through a charging capacity prediction model; calculating the acceptable minimum charging power of the user on the charging pile in the predicted period according to the maximum extended charging time of the user in each charging scene on the charging pile in the predicted period, the minimum charging power of the charging pile and the updated charging capacity of the user; and determining the charging power adjustable space of the user according to the rated charging power of the charging pile and the acceptable minimum charging power of the user on the charging pile in the predicted period. The application accurately calculates the charging power adjustable space of the user, reasonably sets the charging pile, and avoids resource waste caused by excessive setting of the charging pile.

Description

Technical Field

[0001] This invention belongs to the field of charging power calculation technology, specifically relating to a method, system, device, and medium for calculating the adjustable range of charging power. Background Technology

[0002] In analyzing user charging behavior, scholars tend to use conditional probability methods, which use historical data to obtain the probability distribution of user travel time or charging amount, in order to estimate user charging behavior.

[0003] The paper "Text Classification Using KNN Algorithm" constructs an electric vehicle aggregation model based on queue network theory, and analyzes the probability distribution of the number of schedulable electric vehicles and the schedulable potential of electric vehicles. However, the constructed model does not fully consider the uncertain travel needs of users.

[0004] The article "Selection of Electricity Consumption Characteristics and Behavioral Profiling of Electricity Users" points out that by tracking and investigating the driving behavior of multiple electric vehicle users, the possible charging times and locations of electric vehicles can be summarized. The paper "Research on Residential User Profiling Method Based on Multidimensional Fine-Grained Behavioral Data" uses GPS devices installed in users' vehicles to track and record the time and distance traveled by 76 users from leaving and returning home within a day. Based on this, a load forecasting model based on conditional probability is proposed.

[0005] The paper "User-based Hierarchical Clustering and Package Recommendation Method for Electricity Sales-side Reform" proposes a probability distribution method for evaluating the dispatchable capacity of electric vehicles and optimizes the contracted capacity for frequency regulation, but it has some errors compared to the actual situation. The paper "Electricity User Behavior Model: Basic Concepts and Research Framework" simulates the randomness of electric vehicles based on queuing theory, evaluates the dispatchable capacity of parking lots, and points out that it has significant market potential, but it does not consider user demand. The paper "Ordered Charging Optimization and Benefit Analysis of Electric Vehicles Based on Game Theory Algorithm" establishes an electric vehicle dispatch priority evaluation system based on factors such as electric vehicle integrity, dispatchable time periods and capacity, and battery loss. Electric vehicles are divided into three categories according to their dispatchable capacity: priority dispatch, standby dispatch, and no dispatch. Dispatching is performed according to priority during actual electric vehicle charging and discharging. The paper "Electric Vehicle Participation Load Balancing Strategy Based on Improved Particle Swarm Optimization Algorithm" proposes the concept of electric vehicle dispatchable capacity, considering three dimensions: battery loss degree, user credit (i.e., completion status of dispatch participation over a period of time), and electric vehicle battery reverse power supply capability. It constructs an electric vehicle dispatchable capacity evaluation model to quantitatively evaluate the dynamic energy assessment capability of EVs participating in regulation.

[0006] As can be seen from the above description of the existing technical solutions, the results of the adjustable charging power range of the existing technical solutions are not accurate. Summary of the Invention

[0007] To overcome the shortcomings of the prior art, this invention proposes a method for calculating the adjustable range of charging power, comprising:

[0008] Collect users’ historical charging orders, and calculate the maximum extended charging time for users at charging piles in various charging scenarios before and during the predicted period using a charging volume prediction model based on user type and the historical charging orders.

[0009] Based on the maximum extended charging time for users in each charging scenario during the predicted period, the minimum charging power of the charging pile, and the updated charging amount of the user, calculate the minimum acceptable charging power for users at the charging pile during the predicted period.

[0010] The adjustable range of a user's charging power is determined based on the rated charging power of the charging pile and the minimum acceptable charging power of the user at the charging pile during the predicted time period.

[0011] Preferably, the step of collecting users' historical charging orders, based on user type and the historical charging orders, uses a charging volume prediction model to calculate the maximum extended charging time for users at charging stations in various charging scenarios before and during the predicted period, including:

[0012] The system retrieves historical charging orders from users in various charging scenarios within a preset time period. Invalid orders are removed from the historical charging orders through data cleaning and verification to obtain valid historical charging orders.

[0013] The valid historical charging orders are aggregated and categorized according to the charging scenarios under each user type to obtain a set of categorized orders;

[0014] Based on the categorized order set, select the corresponding charging volume prediction model from the pre-built model library;

[0015] Based on the charging volume prediction model, calculate the maximum extended charging time for users at charging piles in each charging scenario before and during the predicted period.

[0016] Preferably, the step of calculating the maximum extended charging time for the user at the charging pile in each charging scenario before and during the predicted period, based on the charging volume prediction model, includes:

[0017] According to the charging volume prediction model, when the business scenario requires the reported response power demand before the predicted time period, the user's charging volume before the predicted time period is obtained.

[0018] Based on the user's parking time and charging duration before the predicted time period, calculate the maximum extended charging time for the user at the corresponding charging pile in each charging scenario before the predicted time period.

[0019] When the business scenario requirement is the electricity trading requirement for the predicted period, the user's charging status during the predicted period is obtained according to the preset operating cycle.

[0020] Based on the charging status, the user's charging power is updated, the updated user's charging power is obtained, and the user's charging duration during the predicted period is calculated based on the updated user's charging power and the charging pile's rated charging power.

[0021] Based on the user's charging time and parking time during the predicted period, calculate the maximum extended charging time for the user at the corresponding charging station in each charging scenario during the predicted period.

[0022] Preferably, the user charging time is calculated using the following formula:

[0023]

[0024] In the formula, T represents the user's charging duration during the predicted period; E1 represents the user's charging capacity after the update; and P represents the rated charging power of the charging pile.

[0025] Preferably, the formula for calculating the maximum extended charging time for users at charging stations in each charging scenario during the predicted time period is as follows:

[0026] T max,t =T park,t -T

[0027] In the formula, T max,t This represents the maximum extended charging time for users at charging stations in various charging scenarios during the predicted time period; T park,t The predicted parking time is represented by ; T represents the predicted charging time for users during the same period.

[0028] Preferably, the process of obtaining the user parking time for the predicted time period includes:

[0029] Based on the user's historical vehicle start-stop information in various charging scenarios, the user's parking time in each charging scenario is predicted, and the user's parking time in the predicted period is obtained.

[0030] Preferably, the formula for calculating the minimum acceptable charging power for the user at the charging station during the predicted time period is as follows:

[0031]

[0032] In the formula, P minThis indicates the minimum acceptable charging power for users at charging stations during the predicted time period; Indicates the minimum charging power of the charging station; T max,t E1 indicates the maximum extended charging time for users at charging stations in various charging scenarios during the predicted period; E1 indicates the user's charging capacity after the update.

[0033] Preferably, the expression for the user's adjustable charging power range is as follows:

[0034] P 可调 ∈[P min [P]

[0035] In the formula, P 可调 Indicates the user's adjustable charging power range; P min This indicates the minimum acceptable charging power for the user at the charging station during the predicted time period; P represents the rated charging power of the charging station.

[0036] Based on the same inventive concept, the present invention also provides a charging power adjustable range calculation system, comprising:

[0037] The time calculation module is used to collect users' historical charging orders and, based on user type and the historical charging orders, calculate the maximum extended charging time for users at charging piles in various charging scenarios before and during the predicted period using a charging volume prediction model.

[0038] The power calculation module is used to calculate the minimum acceptable charging power for users at charging piles in the predicted period based on the maximum extended charging time for users at charging piles in various charging scenarios during the predicted period, the minimum charging power of the charging piles, and the updated charging power of users.

[0039] The adjustable space determination module is used to determine the adjustable space of the user's charging power based on the rated charging power of the charging pile and the minimum acceptable charging power of the user at the charging pile during the predicted time period.

[0040] Preferably, the time calculation module is specifically used for:

[0041] The system retrieves historical charging orders from users in various charging scenarios within a preset time period. Invalid orders are removed from the historical charging orders through data cleaning and verification to obtain valid historical charging orders.

[0042] The valid historical charging orders are aggregated and categorized according to the charging scenarios under each user type to obtain a set of categorized orders;

[0043] Based on the categorized order set, select the corresponding charging volume prediction model from the pre-built model library;

[0044] Based on the charging volume prediction model, calculate the maximum extended charging time for users at charging piles in each charging scenario before and during the predicted period.

[0045] Preferably, the time calculation module calculates, based on the charging volume prediction model, the maximum extended charging time for the user at the charging pile in each charging scenario before and during the predicted period, including:

[0046] According to the charging volume prediction model, when the business scenario requires the reported response power demand before the predicted time period, the user's charging volume before the predicted time period is obtained.

[0047] Based on the user's parking time and charging duration before the predicted time period, calculate the maximum extended charging time for the user at the corresponding charging pile in each charging scenario before the predicted time period.

[0048] When the business scenario requirement is the electricity trading requirement for the predicted period, the user's charging status during the predicted period is obtained according to the preset operating cycle.

[0049] Based on the charging status, the user's charging power is updated, the updated user's charging power is obtained, and the user's charging duration during the predicted period is calculated based on the updated user's charging power and the charging pile's rated charging power.

[0050] Based on the user's charging time and parking time during the predicted period, calculate the maximum extended charging time for the user at the corresponding charging station in each charging scenario during the predicted period.

[0051] Preferably, the user charging time calculation formula in the time calculation module is as follows:

[0052]

[0053] In the formula, T represents the user's charging duration during the predicted period; E1 represents the user's charging capacity after the update; and P represents the rated charging power of the charging pile.

[0054] Preferably, the formula for calculating the maximum extended charging time for a user at a charging station in each charging scenario during the predicted time period in the time calculation module is as follows:

[0055] T max,t =T park,t -T

[0056] In the formula, T max,t This represents the maximum extended charging time for users at charging stations in various charging scenarios during the predicted time period; T park,t The predicted parking time is represented by ; T represents the predicted charging time for users during the same period.

[0057] Preferably, the process of obtaining the user parking time for the predicted time period in the time calculation module includes:

[0058] Based on the user's historical vehicle start-stop information in various charging scenarios, the user's parking time in each charging scenario is predicted, and the user's parking time in the predicted period is obtained.

[0059] Preferably, the formula for calculating the minimum acceptable charging power for a user at a charging station during the predicted time period in the power calculation module is as follows:

[0060]

[0061] In the formula, P min This indicates the minimum acceptable charging power for users at charging stations during the predicted time period; Indicates the minimum charging power of the charging station; T max,t E1 indicates the maximum extended charging time for users at charging stations in various charging scenarios during the predicted period; E1 indicates the user's charging capacity after the update.

[0062] Preferably, the expression for the user's adjustable charging power space in the adjustable space determination module is as follows:

[0063] P 可调 ∈[P min [P]

[0064] In the formula, P 可调 Indicates the user's adjustable charging power range; P min This indicates the minimum acceptable charging power for the user at the charging station during the predicted time period; P represents the rated charging power of the charging station.

[0065] Based on the same inventive concept, the present invention also provides a computer device, comprising: one or more processors;

[0066] Memory, used to store one or more programs;

[0067] When the one or more programs are executed by the one or more processors, the method for calculating the adjustable range of charging power is implemented.

[0068] Based on the same inventive concept, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, it implements the aforementioned method for calculating the adjustable range of charging power.

[0069] Compared with the closest existing technology, the present invention has the following beneficial effects:

[0070] 1. A method, system, device, and medium for calculating the adjustable range of charging power, comprising: collecting historical charging orders of users; calculating, based on user type and the historical charging orders, the maximum extended charging time for users at charging piles in various charging scenarios before and during the predicted period using a charging volume prediction model; calculating the minimum acceptable charging power for users at charging piles during the predicted period based on the maximum extended charging time for users at charging piles in various charging scenarios during the predicted period, the minimum charging power of the charging pile, and the updated charging volume of the user; and determining the adjustable range of the user's charging power based on the rated charging power of the charging pile and the minimum acceptable charging power for users at charging piles during the predicted period. This invention, based on the charging behavior habits of different types of users, can accurately calculate in real time the extended charging time and the adjustable range of charging power for users at charging piles in a certain charging scenario.

[0071] 2. Based on the calculated adjustable range of charging power, the present invention can reasonably set up charging piles, which can both meet the charging needs of users and avoid resource waste caused by setting up too many charging piles. Attached Figure Description

[0072] Figure 1 A schematic flowchart of a method for calculating the adjustable range of charging power provided by the present invention;

[0073] Figure 2 A flowchart for predicting charging capacity and charging time provided by the present invention;

[0074] Figure 3 The overall flowchart for calculating the adjustable range of charging power provided by this invention;

[0075] Figure 4 This is a schematic diagram of a charging power adjustable range calculation system provided by the present invention. Detailed Implementation

[0076] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0077] Example 1:

[0078] A flowchart illustrating the method for calculating the adjustable range of charging power provided by this invention is shown below. Figure 1 As shown, it includes:

[0079] Step 1: Collect users' historical charging orders. Based on user type and the historical charging orders, use the charging volume prediction model to calculate the maximum extended charging time for users at charging piles in various charging scenarios before and during the predicted period.

[0080] Step 2: Calculate the minimum acceptable charging power for users at charging stations during the predicted period based on the maximum extended charging time for users in each charging scenario, the minimum charging power of the charging station, and the updated charging power of the user.

[0081] Step 3: Determine the adjustable range of the user's charging power based on the rated charging power of the charging pile and the minimum acceptable charging power of the user at the charging pile during the predicted time period.

[0082] Specifically, step 1 includes:

[0083] The system retrieves historical charging orders from users in various charging scenarios within a preset time period. Invalid orders are removed from the historical charging orders through data cleaning and verification to obtain valid historical charging orders.

[0084] The valid historical charging orders are aggregated and categorized according to the charging scenarios under each user type to obtain a set of categorized orders;

[0085] Based on the categorized order set, select the corresponding charging volume prediction model from the pre-built model library;

[0086] Based on the charging volume prediction model, calculate the maximum extended charging time for users at charging piles in each charging scenario before and during the predicted period.

[0087] According to the charging volume prediction model, when the business scenario requires the reported response power demand before the predicted time period, the user's charging volume before the predicted time period is obtained.

[0088] Based on the user's parking time and charging duration before the predicted time period, calculate the maximum extended charging time for the user at the corresponding charging pile in each charging scenario before the predicted time period.

[0089] When the business scenario requirement is the electricity trading requirement for the predicted period, the user's charging status during the predicted period is obtained according to the preset operating cycle.

[0090] Based on the charging status, the user's charging power is updated, the updated user's charging power is obtained, and the user's charging duration during the predicted period is calculated based on the updated user's charging power and the charging pile's rated charging power.

[0091] Based on the user's charging time and parking time during the predicted period, calculate the maximum extended charging time for the user at the corresponding charging station in each charging scenario during the predicted period.

[0092] The formula for calculating the user charging time is as follows:

[0093]

[0094] In the formula, T represents the user's charging duration during the predicted period; E1 represents the user's charging capacity after the update; and P represents the rated charging power of the charging pile.

[0095] The formula for calculating the maximum extended charging time for users at charging stations in various charging scenarios during the predicted time period is as follows:

[0096] T max,t =T park,t -T

[0097] In the formula, T max,t This represents the maximum extended charging time for users at charging stations in various charging scenarios during the predicted time period; T park,t The predicted parking time is represented by ; T represents the predicted charging time for users during the same period.

[0098] The process of obtaining the user's parking time for the predicted period includes:

[0099] Based on the user's historical vehicle start-stop information in various charging scenarios, the user's parking time in each charging scenario is predicted, and the user's parking time in the predicted period is obtained.

[0100] Among them, such as Figure 2 and Figure 3 As shown, the charging volume of different user types, such as private cars, ride-hailing vehicles, buses, and taxis, is first predicted in different charging scenarios, including communities, dedicated charging stations, business districts, office buildings, and highways.

[0101] The prediction method is as follows: Select users' historical charging orders from the past 3 months, and remove invalid orders through data cleaning and verification.

[0102] The orders are further aggregated and categorized by user type and charging scenario. The aggregation and categorization principle is: for each user type, the orders in different scenarios are classified separately, such as: private car charging orders in communities, private car charging orders in office buildings, private car charging orders in commercial district charging stations, etc.

[0103] After classifying and aggregating charging orders according to charging scenarios and charging user types, the characteristics of user charging behavior in each set are analyzed. For different order sets after classification, a user charging time and charging amount prediction model is selected based on the order situation. For example, for the order set of private cars charging in the community, this type of aggregate has a large number of orders. First, observe the data characteristics. If obvious regularity is shown, it can be directly predicted by combining historical data.

[0104] For private car order sets in commercial areas or high-speed charging scenarios, the number of such aggregated orders is relatively small. If there is no obvious pattern, the user's charging behavior can be predicted by combining the day type and weather conditions, and using support vector machine (SVM) or artificial neural network (ANN).

[0105] The aforementioned prediction of user charging behavior specifically includes the user's charging time before and during the predicted period, as well as the amount of electricity the user charges.

[0106] Specifically, step 2 includes:

[0107] The formula for calculating the minimum acceptable charging power for users at charging stations during the predicted time period is as follows:

[0108]

[0109] In the formula, P min This indicates the minimum acceptable charging power for users at charging stations during the predicted time period; Indicates the minimum charging power of the charging station; T max,t E1 indicates the maximum extended charging time for users at charging stations in various charging scenarios during the predicted period; E1 indicates the user's charging capacity after the update.

[0110] Specifically, step 3 includes:

[0111] The expression for the user's adjustable charging power range is as follows:

[0112] P 可调 ∈[P min [P]

[0113] In the formula, P 可调 Indicates the user's adjustable charging power range; P min This indicates the minimum acceptable charging power for the user at the charging station during the predicted time period; P represents the rated charging power of the charging station.

[0114] Example 2:

[0115] A schematic diagram of a charging power adjustable range calculation system provided by this invention is shown below. Figure 4 As shown, it includes:

[0116] The time calculation module is used to collect users' historical charging orders and, based on user type and the historical charging orders, calculate the maximum extended charging time for users at charging piles in various charging scenarios before and during the predicted period using a charging volume prediction model.

[0117] The power calculation module is used to calculate the minimum acceptable charging power for users at charging piles in the predicted period based on the maximum extended charging time for users at charging piles in various charging scenarios during the predicted period, the minimum charging power of the charging piles, and the updated charging power of users.

[0118] The adjustable space determination module is used to determine the adjustable space of the user's charging power based on the rated charging power of the charging pile and the minimum acceptable charging power of the user at the charging pile during the predicted time period.

[0119] Specifically, the time calculation module is used for:

[0120] The system retrieves historical charging orders from users in various charging scenarios within a preset time period. Invalid orders are removed from the historical charging orders through data cleaning and verification to obtain valid historical charging orders.

[0121] The valid historical charging orders are aggregated and categorized according to the charging scenarios under each user type to obtain a set of categorized orders;

[0122] Based on the categorized order set, select the corresponding charging volume prediction model from the pre-built model library;

[0123] Based on the charging volume prediction model, calculate the maximum extended charging time for users at charging piles in each charging scenario before and during the predicted period.

[0124] The time calculation module calculates, based on the charging volume prediction model, the maximum extended charging time for the user at the charging pile in each charging scenario before and during the predicted period, including:

[0125] According to the charging volume prediction model, when the business scenario requires the reported response power demand before the predicted time period, the user's charging volume before the predicted time period is obtained.

[0126] Based on the user's parking time and charging duration before the predicted time period, calculate the maximum extended charging time for the user at the corresponding charging pile in each charging scenario before the predicted time period.

[0127] When the business scenario requirement is the electricity trading requirement for the predicted period, the user's charging status during the predicted period is obtained according to the preset operating cycle.

[0128] Based on the charging status, the user's charging power is updated, the updated user's charging power is obtained, and the user's charging duration during the predicted period is calculated based on the updated user's charging power and the charging pile's rated charging power.

[0129] Based on the user's charging time and parking time during the predicted period, calculate the maximum extended charging time for the user at the corresponding charging station in each charging scenario during the predicted period.

[0130] The formula for calculating user charging time in the time calculation module is as follows:

[0131]

[0132] In the formula, T represents the user's charging duration during the predicted period; E1 represents the user's charging capacity after the update; and P represents the rated charging power of the charging pile.

[0133] The formula for calculating the maximum extended charging time for users in various charging scenarios during the predicted time period in the time calculation module is as follows:

[0134] T max,t =T park,t -T

[0135] In the formula, T max,t This represents the maximum extended charging time for users at charging stations in various charging scenarios during the predicted time period; T park,t The predicted parking time is represented by ; T represents the predicted charging time for users during the same period.

[0136] The process of obtaining the user parking time for the predicted time period in the time calculation module includes:

[0137] Based on the user's historical vehicle start-stop information in various charging scenarios, the user's parking time in each charging scenario is predicted, and the user's parking time in the predicted period is obtained.

[0138] Specifically, the formula for calculating the minimum acceptable charging power for a user at a charging station during the predicted time period in the power calculation module is as follows:

[0139]

[0140] In the formula, P min This indicates the minimum acceptable charging power for users at charging stations during the predicted time period; Indicates the minimum charging power of the charging station; T max,t E1 indicates the maximum extended charging time for users at charging stations in various charging scenarios during the predicted period; E1 indicates the user's charging capacity after the update.

[0141] Specifically, the expression for the user's adjustable charging power space in the adjustable space determination module is as follows:

[0142] P 可调 ∈[P min [P]

[0143] In the formula, P 可调 Indicates the user's adjustable charging power range; P min This indicates the minimum acceptable charging power for the user at the charging station during the predicted time period; P represents the rated charging power of the charging station.

[0144] Example 4:

[0145] Based on the same inventive concept, this invention also provides a computer device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement corresponding method flows or corresponding functions, thereby implementing the steps of the adjustable charging power range calculation method in the above embodiments.

[0146] Example 5:

[0147] Based on the same inventive concept, this invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the charging power adjustable range calculation method in the above embodiments.

[0148] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention 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.

[0149] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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 illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0150] 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.

[0151] 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.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit its scope of protection. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that after reading the present invention, they can still make various changes, modifications or equivalent substitutions to the specific implementation of the application. However, all such changes, modifications or equivalent substitutions are within the scope of protection of the claims pending approval.

Claims

1. A method for calculating the adjustable range of charging power, characterized in that, include: Collect users’ historical charging orders, and calculate the maximum extended charging time for users at charging piles in various charging scenarios before and during the predicted period using a charging volume prediction model based on user type and the historical charging orders. Based on the maximum extended charging time for users in each charging scenario during the predicted period, the minimum charging power of the charging pile, and the updated charging amount of the user, calculate the minimum acceptable charging power for users at the charging pile during the predicted period. The adjustable range of the user's charging power is determined based on the rated charging power of the charging pile and the minimum acceptable charging power of the user at the charging pile during the predicted time period. The system collects users' historical charging orders and, based on user type and the historical charging orders, uses a charging volume prediction model to calculate the maximum extended charging time for users at charging stations in various charging scenarios before and during the predicted period, including: The system retrieves historical charging orders from users in various charging scenarios within a preset time period. Invalid orders are removed from the historical charging orders through data cleaning and verification to obtain valid historical charging orders. The valid historical charging orders are aggregated and categorized according to the charging scenarios under each user type to obtain a set of categorized orders; Based on the categorized order set, select the corresponding charging volume prediction model from the pre-built model library; Based on the charging volume prediction model, calculate the maximum extended charging time for users at charging piles in each charging scenario before and during the predicted period. The step of calculating the maximum extended charging time for users at charging stations in various charging scenarios before and during the predicted period, based on the charging volume prediction model, includes: According to the charging volume prediction model, when the business scenario requires the reported response power demand before the predicted time period, the user's charging volume before the predicted time period is obtained. Based on the user's parking time and charging duration before the predicted time period, calculate the maximum extended charging time for the user at the corresponding charging pile in each charging scenario before the predicted time period. When the business scenario requirement is the electricity trading requirement for the predicted period, the user's charging status during the predicted period is obtained according to the preset operating cycle. Based on the charging status, the user's charging power is updated, the updated user's charging power is obtained, and the user's charging duration during the predicted period is calculated based on the updated user's charging power and the charging pile's rated charging power. Based on the user's charging time and parking time during the predicted period, calculate the maximum extended charging time for the user at the corresponding charging station in each charging scenario during the predicted period.

2. The method as described in claim 1, characterized in that, The formula for calculating the user charging time is as follows: In the formula, This indicates the user's charging time during the predicted period; This indicates the user's charging capacity after the update; P indicates the rated charging power of the charging station.

3. The method as described in claim 2, characterized in that, The formula for calculating the maximum extended charging time for users at charging stations in various charging scenarios during the predicted time period is as follows: In the formula, This indicates the maximum extended charging time for users at charging stations in various charging scenarios during the predicted period. This indicates the user's parking time during the predicted period; This indicates the user's charging time during the predicted period.

4. The method as described in claim 1, characterized in that, The process of obtaining user parking time for the predicted time period includes: Based on the user's historical vehicle start-stop information in various charging scenarios, the user's parking time in each charging scenario is predicted, and the user's parking time in the predicted period is obtained.

5. The method as described in claim 3, characterized in that, The formula for calculating the minimum acceptable charging power for users at charging stations during the predicted time period is as follows: In the formula, This indicates the minimum acceptable charging power for users at charging stations during the predicted time period; This indicates the minimum charging power of the charging station; This indicates the maximum extended charging time for users at charging stations in various charging scenarios during the predicted period. This indicates the user's charging level after the update.

6. The method as described in claim 5, characterized in that, The expression for the user's adjustable charging power range is as follows: In the formula, This indicates the user's adjustable charging power range; This indicates the minimum acceptable charging power for users at charging stations during the predicted time period; This indicates the rated charging power of the charging station.

7. A charging power adjustable range calculation system, characterized in that, include: The time calculation module is used to collect users’ historical charging orders and, based on user type and the historical charging orders, calculates the maximum extended charging time for users at charging piles in various charging scenarios before and during the predicted period using a charging volume prediction model. The power calculation module is used to calculate the minimum acceptable charging power for users at charging piles in the predicted period based on the maximum extended charging time for users at charging piles in various charging scenarios during the predicted period, the minimum charging power of the charging piles, and the updated charging amount of users. The adjustable space determination module is used to determine the adjustable space of the user's charging power based on the rated charging power of the charging pile and the minimum acceptable charging power of the user at the charging pile during the predicted time period. The time calculation module is specifically used for: The system retrieves historical charging orders from users in various charging scenarios within a preset time period. Invalid orders are removed from the historical charging orders through data cleaning and verification to obtain valid historical charging orders. The valid historical charging orders are aggregated and categorized according to the charging scenarios under each user type to obtain a set of categorized orders; Based on the categorized order set, select the corresponding charging volume prediction model from the pre-built model library; Based on the charging volume prediction model, calculate the maximum extended charging time for users at charging piles in each charging scenario before and during the predicted period. Therefore, the time calculation module calculates, based on the charging volume prediction model, the maximum extended charging time for the user at the charging pile in each charging scenario before and during the predicted period, including: According to the charging volume prediction model, when the business scenario requires the reported response power demand before the predicted time period, the user's charging volume before the predicted time period is obtained. Based on the user's parking time and charging duration before the predicted time period, calculate the maximum extended charging time for the user at the corresponding charging pile in each charging scenario before the predicted time period. When the business scenario requirement is the electricity trading requirement for the predicted period, the user's charging status during the predicted period is obtained according to the preset operating cycle. Based on the charging status, the user's charging power is updated, the updated user's charging power is obtained, and the user's charging duration during the predicted period is calculated based on the updated user's charging power and the charging pile's rated charging power. Based on the user's charging time and parking time during the predicted period, calculate the maximum extended charging time for the user at the corresponding charging station in each charging scenario during the predicted period.

8. The system as described in claim 7, characterized in that, The formula for calculating user charging time in the time calculation module is as follows: In the formula, This indicates the user's charging time during the predicted period; This indicates the user's charging capacity after the update; P indicates the rated charging power of the charging station.

9. The system as described in claim 8, characterized in that, The formula for calculating the maximum extended charging time for users in various charging scenarios during the predicted time period in the time calculation module is as follows: In the formula, This indicates the maximum extended charging time for users at charging stations in various charging scenarios during the predicted period. This indicates the user's parking time during the predicted period; This indicates the user's charging time during the predicted period.

10. The system as described in claim 7, characterized in that, The process of obtaining the user parking time for the predicted time period in the time calculation module includes: Based on the user's historical vehicle start-stop information in various charging scenarios, the user's parking time in each charging scenario is predicted, and the user's parking time in the predicted period is obtained.

11. The system as described in claim 9, characterized in that, The formula for calculating the minimum acceptable charging power for a user at a charging station during the predicted time period in the power calculation module is as follows: In the formula, This indicates the minimum acceptable charging power for users at charging stations during the predicted time period; This indicates the minimum charging power of the charging station; This indicates the maximum extended charging time for users at charging stations in various charging scenarios during the predicted period. This indicates the user's charging level after the update.

12. The system as described in claim 11, characterized in that, The expression for the user's adjustable charging power space in the adjustable space determination module is as follows: In the formula, This indicates the user's adjustable charging power range; This indicates the minimum acceptable charging power for users at charging stations during the predicted time period; This indicates the rated charging power of the charging station.

13. A computer device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the computation method as described in any one of claims 1-6 is implemented.

14. A computer-readable storage medium, characterized in that, It contains a computer program, which, when executed, implements the calculation method as described in any one of claims 1-6.

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