User portrait generation method and device of energy storage aggregator, equipment and storage medium

Abstract

The embodiment of the invention provides a user portrait generation method and device of an energy storage aggregator, equipment and a storage medium. Acquiring incentive price data of each distributed user participating in aggregation regulation under a target energy storage aggregator within a preset time period, determining a target incentive price value corresponding to the target energy storage aggregator according to the incentive price data, and constructing a price incentive function of each distributed user based on the target incentive price value, according to the price incentive function and the number of all distributed users under the target energy storage aggregator, determining a user participation degree-incentive price response model corresponding to each distributed user number, and aiming at each distributed user, according to the user participation degree-incentive price response model corresponding to the user and the actual incentive price, determining a user participation degree-incentive price response model corresponding to the user; and constructing user portraits of the distributed users. Through the method, the response characteristics of the user are more accurately captured, the efficiency of the evaluation process is remarkably improved, and the technical problems of complex calculation, low efficiency and insufficient practicability in the prior art are solved.

Description

Technical Field

[0001] The present application relates to the field of power supply technology, and in particular to a method, device, equipment and storage medium for generating a user profile of an energy storage aggregator. Background Art

[0002] With the promotion of renewable energy, energy transformation has become a major task for global development. The application of energy storage technology can improve the utilization rate of renewable energy, stabilize the power grid, and promote energy transformation and the development of a low-carbon economy. Among them, the emergence of energy storage aggregators can aggregate scattered energy storage resources, realize participation in the power market and provide services, thereby better meeting the needs of energy consumers.

[0003] At present, the evaluation method for user portraits in energy storage aggregators usually relies only on historical data for static analysis, which is difficult to accurately reflect the dynamic response of users when faced with different incentive prices. It also fails to fully consider the complexity and diversity of user behavior, resulting in insufficient accuracy and practicality of the evaluation results.

[0004] In summary, how to flexibly, accurately and efficiently build user portraits in energy storage aggregators is a technical problem that needs to be solved urgently in this field. Summary of the invention

[0005] The embodiments of the present application provide a method, apparatus, device and storage medium for generating a user portrait of an energy storage aggregator, so as to solve the problem of how to flexibly, accurately and efficiently realize the construction of user portraits in an energy storage aggregator.

[0006] In a first aspect, an embodiment of the present application provides a method for generating a user portrait of an energy storage aggregator, comprising:

[0007] Obtain the incentive price data for each distributed user participating in the aggregation control under the target energy storage aggregator within the preset time period;

[0008] Determining a target incentive price value corresponding to the target energy storage aggregator according to the incentive price data;

[0009] Based on the target incentive price value, construct a price incentive function for each distributed user;

[0010] Determine a user participation-incentive price response model corresponding to each number of distributed users according to the price incentive function and the number of all distributed users under the target energy storage aggregator, wherein the user participation-incentive price response model represents a functional relationship between user participation and incentive price;

[0011] For each distributed user, a user profile of the distributed user is constructed according to the user participation-incentive price response model and the actual incentive price corresponding to the user.

[0012] In a possible implementation manner, obtaining the incentive price data for each distributed user participating in the aggregated regulation under the target energy storage aggregator within a preset time period includes:

[0013] Divide the preset time period according to a preset division rule to obtain multiple sub-time periods;

[0014] For each sub-period, obtaining the incentive price sub-data of each distributed user participating in the aggregated regulation under the target energy storage aggregator in the sub-period;

[0015] The incentive price sub-data of each distributed user participating in the aggregated regulation in all sub-periods are aggregated to obtain the incentive price data of each distributed user participating in the aggregated regulation.

[0016] In a possible implementation manner, obtaining the incentive price sub-data for each distributed user participating in the aggregated regulation under the target energy storage aggregator in the sub-period includes:

[0017] For each sub-period, obtaining control information of each distributed user in the sub-period;

[0018] For each distributed user, determining whether the distributed user participates in aggregated regulation based on the type data of the control information of the distributed user;

[0019] If the distributed user participates in aggregated regulation, the incentive price data when the distributed user participates in aggregated regulation is determined as the incentive price sub-data for the distributed user to participate in aggregated regulation in the sub-period.

[0020] In a possible implementation manner, obtaining the incentive price sub-data for each distributed user participating in the aggregated regulation under the target energy storage aggregator in the sub-period includes:

[0021] For each sub-period, obtaining the operation data of each distributed user in the sub-period;

[0022] For each distributed user, determining the operating state of the distributed user according to the operating data of the distributed user;

[0023] Determining whether the distributed user participates in aggregated regulation according to the operating status;

[0024] If the distributed user participates in aggregated regulation, the incentive price data when the distributed user participates in aggregated regulation is determined as the incentive price sub-data for the distributed user to participate in aggregated regulation in the sub-period.

[0025] In a possible implementation, determining a user participation-incentive price response model corresponding to each number of distributed users according to the price incentive function and the number of all distributed users under the target energy storage aggregator includes:

[0026] Determining participation data of each distributed user according to the price incentive function and the number of distributed users under the target energy storage aggregator;

[0027] For each distributed user, based on the participation data of the distributed user, a user participation-incentive price response model corresponding to the distributed user is determined.

[0028] In a possible implementation, constructing the user profile of the distributed user according to the user participation-incentive price response model and the actual incentive price corresponding to the user includes:

[0029] Based on the pre-obtained portrait request information, determine whether the user can access the user portrait;

[0030] If it is true that the requesting user can access the user portrait, for each distributed user, the user participation information of the distributed user is determined based on the actual incentive price in the portrait request information;

[0031] A user profile of the distributed user is constructed according to the user participation information.

[0032] In a possible implementation manner, determining the target incentive price value corresponding to the target energy storage aggregator according to the incentive price data includes:

[0033] Calculating an average value of the incentive price data, and determining the average value as the target incentive price value;

[0034] or,

[0035] The data with the highest frequency of occurrence in the incentive price data is determined as the target incentive price value.

[0036] In a second aspect, an embodiment of the present application provides a user portrait generation device for an energy storage aggregator, comprising:

[0037] An acquisition module is used to obtain the incentive price data of each distributed user participating in the aggregation regulation under the target energy storage aggregator within a preset time period;

[0038] A first determination module, configured to determine a target incentive price value corresponding to the target energy storage aggregator according to the incentive price data;

[0039] A first building module, configured to build a price incentive function for each distributed user based on the target incentive price value;

[0040] A second determination module is used to determine a user participation-incentive price response model corresponding to each number of distributed users according to the price incentive function and the number of all distributed users under the target energy storage aggregator, wherein the user participation-incentive price response model represents a functional relationship between user participation and incentive price;

[0041] The second construction module is used to construct a user profile of each distributed user according to the user participation-incentive price response model and the actual incentive price corresponding to the user.

[0042] In a possible implementation manner, the acquisition module is used to:

[0043] Divide the preset time period according to a preset division rule to obtain multiple sub-time periods;

[0044] For each sub-period, obtaining the incentive price sub-data of each distributed user participating in the aggregated regulation under the target energy storage aggregator in the sub-period;

[0045] The incentive price sub-data of each distributed user participating in the aggregated regulation in all sub-periods are aggregated to obtain the incentive price data of each distributed user participating in the aggregated regulation.

[0046] In a possible implementation manner, the acquisition module acquires the incentive price sub-data of each distributed user participating in the aggregated regulation under the target energy storage aggregator in the sub-period, specifically including:

[0047] For each sub-period, obtaining control information of each distributed user in the sub-period;

[0048] For each distributed user, determining whether the distributed user participates in aggregated regulation based on the type data of the control information of the distributed user;

[0049] If the distributed user participates in aggregated regulation, the incentive price data when the distributed user participates in aggregated regulation is determined as the incentive price sub-data for the distributed user to participate in aggregated regulation in the sub-period.

[0050] In a possible implementation manner, the acquisition module acquires the incentive price sub-data of each distributed user participating in the aggregated regulation under the target energy storage aggregator in the sub-period, specifically including:

[0051] For each sub-period, obtaining the operation data of each distributed user in the sub-period;

[0052] For each distributed user, determining the operating state of the distributed user according to the operating data of the distributed user;

[0053] Determining whether the distributed user participates in aggregated regulation according to the operating status;

[0054] If the distributed user participates in aggregated regulation, the incentive price data when the distributed user participates in aggregated regulation is determined as the incentive price sub-data for the distributed user to participate in aggregated regulation in the sub-period.

[0055] In a possible implementation manner, the second determining module is used to:

[0056] Determining participation data of each distributed user according to the price incentive function and the number of distributed users under the target energy storage aggregator;

[0057] For each distributed user, based on the participation data of the distributed user, a user participation-incentive price response model corresponding to the distributed user is determined.

[0058] In a possible implementation manner, the second building module is used to:

[0059] Based on the pre-obtained portrait request information, determine whether the user can access the user portrait;

[0060] If it is true that the requesting user can access the user portrait, for each distributed user, the user participation information of the distributed user is determined based on the actual incentive price in the portrait request information;

[0061] A user profile of the distributed user is constructed according to the user participation information.

[0062] In a possible implementation manner, the first determining module is used to:

[0063] Calculating an average value of the incentive price data, and determining the average value as the target incentive price value;

[0064] or,

[0065] The data with the highest frequency of occurrence in the incentive price data is determined as the target incentive price value.

[0066] In a third aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor;

[0067] The memory stores computer-executable instructions;

[0068] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0069] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementations of the first aspect.

[0070] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0071] The user portrait generation method, device, equipment and storage medium of the energy storage aggregator provided in the embodiments of the present application. The incentive price data of each distributed user participating in the aggregation regulation under the target energy storage aggregator within a preset time period is obtained, and the target incentive price value corresponding to the target energy storage aggregator is determined based on the incentive price data. Based on the target incentive price value, a price incentive function for each distributed user is constructed, and the user participation-incentive price response model corresponding to each number of distributed users is determined according to the price incentive function and the number of all distributed users under the target energy storage aggregator. For each distributed user, a user portrait of the distributed user is constructed according to the user participation-incentive price response model and the actual incentive price corresponding to the user. The price incentive function of each distributed user is constructed by using the incentive price data of each distributed user under the target energy storage aggregator when performing aggregation regulation within a preset time period, so as to more accurately capture the response characteristics of the user. The generated price incentive function is simpler than the linear model calculation process, thereby significantly improving the efficiency of the evaluation process, and overcoming the technical problems of complex calculation, low efficiency and insufficient practicality in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0073] Figure 1 Schematic diagram of the process of generating a user portrait of an energy storage aggregator provided in this application Figure 1 ;

[0074] Figure 2 is an example diagram of the price incentive function;

[0075] Figure 3 Schematic diagram of the process of generating a user portrait of an energy storage aggregator provided in this application Figure 2 ;

[0076] Figure 4 Schematic diagram of the process of generating a user portrait of an energy storage aggregator provided in this application Figure 3 ;

[0077] Figure 5 Schematic diagram of the process of generating a user portrait of an energy storage aggregator provided in this application Figure 4 ;

[0078] Figure 6 Schematic diagram of the process of generating a user portrait of an energy storage aggregator provided in this application Figure 5 ;

[0079] Figure 7 Schematic diagram of the process of generating a user portrait of an energy storage aggregator provided in this application Figure 6 ;

[0080] Figure 8 A schematic diagram of the structure of a user portrait generation device for an energy storage aggregator provided in this application;

[0081] Fig. 9 A schematic diagram of the structure of the electronic device provided in this application.

[0082] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0083] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0084] With the promotion of renewable energy, energy transformation has become one of the main tasks of global development. The application of energy storage technology can improve the utilization rate of renewable energy, stabilize the power grid, and promote energy transformation and the development of a low-carbon economy. Among them, the emergence of energy storage aggregators can aggregate decentralized energy storage resources, realize participation in the electricity market and provide services, so as to better meet the needs of energy consumers. In the prior art, the generation of user portraits in the energy storage aggregator model has the following problems: First, the current evaluation method usually only relies on historical data for static analysis, which is difficult to accurately reflect the dynamic response of users when facing different incentive prices. Secondly, when calculating the relationship between user participation and incentive prices, the existing method uses a linear model, which fails to fully consider the complexity and diversity of user behavior, resulting in insufficient accuracy and practicality of the evaluation results. In addition, when dealing with multi-distributed user energy storage systems, the linear model has a high computational complexity and is difficult to effectively deal with scenarios with large-scale user participation. In summary, how to flexibly, accurately and efficiently realize the construction of user portraits in energy storage aggregators is a technical problem that needs to be solved in this field.

[0085] In response to the above problems, the present application provides a method, device, equipment and storage medium for generating user portraits of energy storage aggregators, which realizes the problem of how to flexibly, accurately and efficiently realize the construction of user portraits in energy storage aggregators. Specifically, in the prior art, the generation of user portraits in the energy storage aggregator mode has the following problems: First, the current evaluation method usually only relies on historical data for static analysis, which is difficult to accurately reflect the dynamic response of users when facing different incentive prices. Secondly, when calculating the relationship between user participation and incentive prices, the existing method uses a linear model, which fails to fully consider the complexity and diversity of user behavior, resulting in insufficient accuracy and practicality of the evaluation results. In addition, when dealing with multi-distributed user energy storage systems, the linear model has a high computational complexity and is difficult to effectively cope with scenarios involving large-scale user participation. In view of these problems, the inventor studied whether it is possible to consider the dynamic response of users under different incentive conditions and construct it based on their individual behavioral characteristics, so that the user portrait is closer to the actual situation and more personalized. By constructing a nonlinear price incentive function, the complexity and diversity of user behavior can be more accurately captured. Based on this, the solution of the present application is proposed.

[0086] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0087] Figure 1 Schematic diagram of the process of generating a user portrait of an energy storage aggregator provided in this application Figure 1,like Figure 1 As shown, the method includes:

[0088] S101: Obtain incentive price data for each distributed user participating in aggregation control under a target energy storage aggregator within a preset time period.

[0089] In this step, in order to accurately construct a user profile for each distributed user under the target energy storage aggregator and make it closer to reality and more flexible, the time period can be pre-set to obtain the incentive price data for each distributed user participating in the aggregation regulation in the preset time period.

[0090] Specifically, the preset time period is divided according to a pre-set division rule to obtain multiple sub-periods, and for each sub-period, the incentive price sub-data of each distributed user participating in the aggregation regulation under the target energy storage aggregator in the sub-period is obtained, and the incentive price sub-data of each distributed user participating in the aggregation regulation in all sub-periods are summarized to obtain the incentive price data of each distributed user participating in the aggregation regulation.

[0091] For example, since electricity consumption data has obvious regional and seasonal characteristics, for example, in a certain area, the climate is hot in summer, and the use of refrigeration appliances such as air conditioners and refrigerators is large, resulting in a certain area of ​​electricity consumption in summer is much greater than a certain area of ​​electricity consumption in winter. Therefore, the incentive prices in summer and winter in a certain area may be different. Therefore, the preset time period can be selected according to the season as a cycle.

[0092] Optionally, since selecting the preset time period according to season as a cycle will result in a large selected time span and a large amount of calculation, it is also possible to select the preset time period according to "week" as a cycle. The embodiment of the present application does not specifically limit the method for selecting the preset time period, and it can be determined according to the actual scenario.

[0093] Exemplarily, the incentive price is the price for recycling the electric energy stored by the distributed users, and the incentive price data may correspond to the price for the distributed users to participate in the aggregated regulation and the price for the distributed users to refuse to participate in the aggregated regulation.

[0094] S102: Determine the target incentive price value corresponding to the target energy storage aggregator based on the incentive price data.

[0095] In this step, since the incentive price data is floating, the incentive prices of distributed users participating in aggregated regulation are also different. Therefore, selecting a single data cannot represent the characteristics of distributed users participating in aggregated regulation. Then, based on the incentive price data, the target incentive price value for aggregated regulation is calculated, that is, the target incentive price value corresponding to the target energy storage aggregator is determined. This can obtain a more accurate and representative target incentive price value to construct a price incentive function for each distributed user and ensure the accuracy of the price incentive function.

[0096] Specifically, the average value of the incentive price data is calculated, and the average value is determined as the target incentive price value.

[0097] Optionally, the data with the highest frequency in the incentive price data may be determined as the target incentive price value. The embodiment of the present application does not specifically limit the specific method for determining the target incentive price value.

[0098] S103: Construct a price incentive function for each distributed user based on the target incentive price value.

[0099] In this step, after the target incentive price value is determined, the price incentive function for each distributed user can be constructed according to the target incentive price value.

[0100] Specifically, the target incentive price value is used as a function condition, and a price incentive function for each distributed user is constructed according to the function condition. In this function, two preset values ​​are set: a first preset value (for example, 1 or 100%, indicating a full response) and a second preset value (for example, 0 or 0%, indicating no response). When the actual incentive price is greater than or equal to the target incentive price value, the price incentive function outputs the first preset value, indicating that the user tends to actively respond to aggregate regulation in this case. When the actual incentive price is less than the target incentive price value, the price incentive function outputs the second preset value, indicating that the user may be less willing to participate in aggregate regulation in this case.

[0101] For example, Figure 2 is an example diagram of the price incentive function, such as Figure 2 As shown, the mathematical expression of the price incentive function is:

[0102]

[0103] Among them, P represents the incentive price, the vertical axis r represents the user participation, and the target incentive price value As a function condition, when When , it means that the user is willing to participate in energy concentration regulation. , it means that the user refuses to participate in energy concentration regulation.

[0104] Optionally, in order to more accurately reflect the complex relationship between the actual incentive price and user responsiveness, and taking into account user heterogeneity, the user's response behavior may be affected by time factors, as well as the dynamic changes in the market environment and user needs, the price incentive function can be constructed in the following way:

[0105]

[0106] Among them, P represents the actual incentive price, t represents the time variable, which can be different time periods in a day, different days in a week, or a division of a longer time scale, and U represents the user characteristic variable, which is used to reflect user heterogeneity and may include user type (such as residential, commercial), energy storage device capacity, historical response behavior, etc. It represents the real-time user responsiveness indicator, reflecting the average or expected response level of users at the current time and incentive price. It represents the market supply and demand status indicator, which is used to reflect the current balance of electricity supply and demand in the market.

[0107] function is a basic price incentive function that can calculate a basic responsiveness based on the incentive price, time, and user characteristics. This function can be nonlinear to capture the complex relationship between price, time, and user characteristics. For example, it can be based on the logistic function or other S-curve variants, which include parameters adjusted according to user type.

[0108] For example, a time coefficient can be introduced to adjust the responsiveness of different time periods. The formula is:

[0109]

[0110] in, and is the adjustment parameter for residential and commercial users, used to control the steepness of the curve. and It is a target incentive price value that changes over time and can be set based on historical data and real-time market conditions.

[0111] Optionally, the time factor can be a simple piecewise function to reflect the difference in responsiveness at different time periods:

[0112]

[0113] in, and It is the adjustment factor for peak and off-peak hours.

[0114] Optionally, in practical applications, the time coefficient may be multiplied by the logistic function to obtain a basic responsiveness that takes the time factor into account.

[0115] function is a dynamic adjustment function that adjusts the basic responsiveness based on the real-time user responsiveness index and the market supply and demand status index. This function can be linear or nonlinear to reflect the dynamic impact of these factors on the price incentive effect. For example, when the market supply and demand are tight ( higher), the function can increase the incentive effect (i.e., improve responsiveness) to attract more users to participate in aggregate regulation; and when the user responsiveness is already high ( approaching the upper limit), the function may reduce the incentive to avoid increased costs caused by over-incentives.

[0116] For example, the dynamic adjustment function is a linear function:

[0117]

[0118] in, and is the adjustment coefficient, which is used to control the influence of real-time user responsiveness index and market supply and demand status index on basic responsiveness. and They are the maximum possible values ​​of the real-time user responsiveness indicator and the market supply and demand status indicator respectively.

[0119] S104: Determine a user participation-incentive price response model corresponding to each number of distributed users based on the price incentive function and the number of all distributed users under the target energy storage aggregator.

[0120] In this step, the comprehensive behavior of all users and how they respond to different incentive prices are taken into account. Based on the constructed price incentive function and the number of distributed users under the target energy storage aggregator, the user participation-incentive price response model corresponding to each distributed user can be determined, where the user participation-incentive price response model represents the functional relationship between user participation and incentive price.

[0121] Specifically, according to the number of distributed users under the target energy storage aggregator of the price incentive function, the participation data of each distributed user is determined, and for each distributed user, based on the participation data of the distributed user, a user participation-incentive price response model corresponding to the distributed user is determined.

[0122] S105: For each distributed user, a user profile of the distributed user is constructed according to the user participation-incentive price response model and the actual incentive price corresponding to the user.

[0123] In this step, after obtaining the user participation-incentive price response model corresponding to each distributed user, the participation data of the distributed users in the target energy storage aggregator with the actual incentive price can be calculated based on the functional relationship and the actual incentive price. Based on the participation data of the distributed users in the target energy storage aggregator, the user profile of the distributed users in the target energy storage aggregator is constructed.

[0124] Specifically, based on the portrait request information obtained in advance, it is determined whether the requesting user can access the user portrait. If the requesting user can access the user portrait, for each distributed user, the user participation information of the distributed user is determined based on the actual incentive price in the portrait request information, and the user portrait of the distributed user is constructed based on the user participation information.

[0125] The method for generating a user portrait of an energy storage aggregator provided in the embodiment of the present application obtains the incentive price data of each distributed user participating in the aggregation regulation under the target energy storage aggregator within a preset time period, determines the target incentive price value corresponding to the target energy storage aggregator based on the incentive price data, constructs a price incentive function for each distributed user based on the target incentive price value, determines the user participation-incentive price response model corresponding to each number of distributed users based on the price incentive function and the number of all distributed users under the target energy storage aggregator, and constructs a user portrait of the distributed user for each distributed user based on the user participation-incentive price response model and the actual incentive price corresponding to the user. The price incentive function of each distributed user is constructed using the incentive price data of each distributed user under the target energy storage aggregator when performing aggregation regulation within a preset time period, so as to more accurately capture the response characteristics of the user. The generated price incentive function is simpler than the linear model calculation process, thereby significantly improving the efficiency of the evaluation process, and overcoming the technical problems of complex calculation, low efficiency, and insufficient practicality in the prior art.

[0126] Figure 3 Schematic diagram of the process of generating a user portrait of an energy storage aggregator provided in this application Figure 2 ,like Figure 3 As shown, based on the above embodiment, step S101 specifically includes:

[0127] S301: Divide a preset time period according to a preset division rule to obtain a plurality of sub-time periods.

[0128] S302: For each sub-period, obtain the incentive price sub-data of each distributed user participating in the aggregation control under the target energy storage aggregator in the sub-period.

[0129] S303: Summarize the incentive price sub-data of each distributed user participating in the aggregated regulation in all sub-periods to obtain the incentive price data of each distributed user participating in the aggregated regulation.

[0130] Optionally, the preset time period can be divided into "days" to obtain at least two sub-periods, and the incentive price sub-data when each distributed user under the target energy storage aggregator performs aggregation control within the sub-period is obtained.

[0131] Exemplarily, when the preset time period is a week (7 days), the preset time period is divided into 7 sub-periods by "day", and the incentive price sub-data of distributed users participating in aggregation regulation in the past 7 days are read, and then the average of these 7 prices is calculated, where i is used to represent the i-th distributed user under the target energy storage aggregator, and t is used to represent the t-th sub-period of the preset time period.

[0132] Exemplarily, when the preset time period is a quarter, the preset time period is divided into "months" to obtain three sub-periods, the average incentive price sub-data of distributed users each month are read, and then the average of the three incentive price sub-data is calculated.

[0133] The user portrait generation method of the energy storage aggregator provided in the embodiment of the present application divides the preset time period according to the pre-set division rules to obtain multiple sub-periods, and for each sub-period, obtains the incentive price sub-data of each distributed user participating in the aggregation regulation under the target energy storage aggregator in the sub-period, and summarizes the incentive price sub-data of each distributed user participating in the aggregation regulation in all sub-periods to obtain the incentive price data of each distributed user participating in the aggregation regulation. Through the above method, the incentive price data of each distributed user under the target energy storage aggregator when performing aggregation regulation in the preset time period can be obtained more accurately, providing strong support for subsequent user portrait generation and strategy formulation.

[0134] Figure 4 Schematic diagram of the process of generating a user portrait of an energy storage aggregator provided in this application Figure 3 ,like Figure 4 As shown, based on the above embodiment, step S302 specifically includes:

[0135] S401: For each sub-period, obtain control information of each distributed user in the sub-period.

[0136] S402: For each distributed user, based on the type data of the control information of the distributed user, determine whether the distributed user participates in the aggregation control.

[0137] S403: If the distributed user participates in the aggregated regulation, the incentive price data when the distributed user participates in the aggregated regulation is determined as the incentive price sub-data when the distributed user participates in the aggregated regulation in the sub-period.

[0138] Exemplarily, since distributed users inevitably need to control energy storage devices when participating in aggregated regulation, control information for distributed users in a sub-period is obtained, and type data of the control information is obtained. When the type data of the control information indicates that it is used to control the energy storage device to release energy to the external power grid, it is considered that the distributed user performs aggregated regulation, and the incentive price when the distributed user performs aggregated regulation is recorded. By identifying whether a distributed user performs aggregated regulation through the type data of the control information, it is possible to determine whether the distributed user performs aggregated regulation when the distributed user is ready to participate in aggregated regulation. The judgment process is faster, avoiding the situation where the distributed user is identified to perform aggregated regulation only after participating in aggregated regulation.

[0139] Specifically, in each sub-period, control information for distributed users is first obtained. These control information may come from the system of the energy storage aggregator, including dispatch instructions, aggregation requests, price signals, etc. The type of the acquired control information is identified. For example, the format and content of the control information are parsed to determine its type, such as the dispatch instruction type, price signal type, etc. Based on the type data of the control information, it is determined whether the distributed user has performed aggregation regulation. For example, if the control information is a dispatch instruction, and the instruction requires the user to adjust the charge and discharge status of its energy storage device to respond to grid demand, it can be considered that the user has performed aggregation regulation.

[0140] The user portrait generation method of the energy storage aggregator provided in the embodiment of the present application obtains the control information of each distributed user in each sub-period for each distributed user, and determines whether the distributed user participates in the aggregation regulation based on the type data of the control information of the distributed user for each distributed user. If the distributed user participates in the aggregation regulation, the incentive price data when the distributed user participates in the aggregation regulation is determined as the incentive price sub-data of the distributed user participating in the aggregation regulation in the sub-period. Through the above method, the incentive price data when each distributed user under the target energy storage aggregator performs aggregation regulation in the sub-period can be obtained more effectively, providing strong support for subsequent user portrait generation and strategy formulation.

[0141] Figure 5 Schematic diagram of the process of generating a user portrait of an energy storage aggregator provided in this application Figure 4 ,like Figure 5 As shown, based on the above embodiment, step S302 specifically includes:

[0142] S501: For each sub-period, obtain the operation data of each distributed user in the sub-period.

[0143] S502: For each distributed user, determine the running status of the distributed user according to the running data of the distributed user.

[0144] S503: Determine whether the distributed user participates in the aggregation control according to the operation status.

[0145] S504: If the distributed user participates in the aggregated regulation, the incentive price data when the distributed user participates in the aggregated regulation is determined as the incentive price sub-data when the distributed user participates in the aggregated regulation in the sub-period.

[0146] Exemplarily, the operating status of the distributed user is judged according to the operating data of the distributed user, and whether the distributed user executes aggregate regulation is determined according to the operating status, that is, whether the distributed user executes aggregate regulation is determined based on the actual situation, so as to avoid the user stopping participating in aggregate regulation after controlling the energy storage device to release energy to the external power grid, thereby making the judgment result more reliable.

[0147] Specifically, in each sub-period, in addition to obtaining control information, the operating data of each distributed user under the target energy storage aggregator can also be obtained. The operating data may include key indicators such as the charging and discharging status, power level, and power output of the energy storage device. Based on the acquired operating data, the operating status of the distributed user is judged. To determine whether the user is in a normal operating state, whether it has responded to the aggregated control instructions, etc. Based on the operating status judgment result, it is further determined whether the distributed user has executed aggregated control. For example, if the user's energy storage device performs charge and discharge adjustments in accordance with the aggregated control instructions within a specific time period, it can be considered that the user has executed aggregated control.

[0148] The user portrait generation method of the energy storage aggregator provided in the embodiment of the present application obtains the operating data of each distributed user in each sub-period for each distributed user, determines the operating status of the distributed user based on the operating data of the distributed user, and determines whether the distributed user participates in aggregated regulation based on the operating status. If the distributed user participates in aggregated regulation, the incentive price data when the distributed user participates in aggregated regulation is determined as the incentive price sub-data of the distributed user participating in aggregated regulation in the sub-period. By combining the operating data of the distributed user to determine whether it performs aggregated regulation and recording the corresponding incentive price data, the user's behavioral characteristics and market response in different time periods can be more effectively obtained. This provides more comprehensive and accurate data support for subsequent user portrait generation and strategy formulation.

[0149] Figure 6 Schematic diagram of the process of generating a user portrait of an energy storage aggregator provided in this application Figure 5 ,like Figure 6 As shown, based on the above embodiment, step S104 specifically includes:

[0150] S601: Determine participation data of each distributed user according to the number of distributed users under the target energy storage aggregator of the price incentive function.

[0151] S602: For each distributed user, based on the distributed user's participation data, determine a user participation-incentive price response model corresponding to the distributed user.

[0152] Exemplarily, the price incentive function can be used as the dividend, the number of distributed users under the target energy storage aggregator can be used as the divisor, the participation data of each distributed user can be calculated, and then the participation data can be accumulated to obtain the functional relationship between user participation and incentive price under the target energy storage aggregator.

[0153] The user participation-incentive price response model can also be expressed as:

[0154]

[0155] Where r is the user participation rate under the target energy storage aggregator, N is the number of distributed users under the target energy storage aggregator, Represents the participation data of the i-th distributed user, and ∑ represents cumulative calculation.

[0156] Optionally, according to the price incentive function and the needs of the target energy storage aggregator, the total number of known distributed users is N. The participation data can be expressed as the degree or proportion of users willing to participate in energy storage aggregation. This can be determined based on factors such as the user's historical data, needs, preferences, etc.

[0157] Suppose there is an engagement dataset in, represents the participation of the i-th distributed user ( ).

[0158] The user engagement-incentive price response model describes the relationship between user engagement and incentive price. It shows how user engagement changes under different incentive prices. It can be expressed by the following formula:

[0159]

[0160] in, is the weight of the ith user, reflecting the relative importance of the user in the total participation, It is the sum of all users’ price incentive functions and is used for normalization.

[0161] The method for generating a user portrait of an energy storage aggregator provided in the embodiment of the present application determines the participation data of each distributed user according to the number of distributed users under the target energy storage aggregator of the price incentive function, and determines the user participation-incentive price response model corresponding to each distributed user based on the participation data of the distributed user.

[0162] Figure 7 Schematic diagram of the process of generating a user portrait of an energy storage aggregator provided in this application Figure 6 ,like Figure 7 As shown, based on the above embodiment, step S105 specifically includes:

[0163] S701: Based on the pre-acquired portrait request information, it is determined whether the user can access the user portrait.

[0164] S702: If the requesting user can indeed access the user portrait, for each distributed user, the user participation information of the distributed user is determined based on the actual incentive price in the portrait request information.

[0165] S703: Build a user profile of the distributed user based on the user participation information.

[0166] Obtain user portrait request information, and determine whether the portrait request information meets the permission conditions based on the identity information and preset permission data in the portrait request information. If the portrait request information meets the permission conditions, calculate the user participation information of the distributed users in the target energy storage aggregator at the actual incentive price based on the actual incentive price in the portrait request information, and build a user portrait of the distributed users in the target energy storage aggregator based on the user participation information.

[0167] Exemplarily, identity information and preset permission data are used to determine whether the portrait request information meets the permission conditions, thereby ensuring data security and preventing unauthorized personnel from obtaining user portraits of distributed users in the target energy storage aggregator.

[0168] Exemplarily, when displaying the user portrait, it also includes obtaining identity recognition information of a display device used to display the user portrait, determining whether the display device meets the permission conditions based on the identity recognition information and preset permission data, and if the display device meets the permission conditions, displaying the user portrait.

[0169] Specifically, the system needs to receive user portrait request information from the requester. This information usually includes the identity information of the requester (such as user ID, account name, etc.), actual incentive price data, and other relevant parameters that may be required. Optionally, the received request information can also be initially verified to ensure its integrity and correct format.

[0170] According to the identity information in the request information, it is matched with the preset permission database. The permission database should contain a list of requesters that are allowed to access the user portrait and their corresponding permission levels. According to the matching results, it is determined whether the requester meets the permission conditions for accessing the user portrait. If the requester is not in the permission list, or its permission level is not sufficient to access the requested user portrait, the request is rejected and a corresponding error prompt is returned.

[0171] Extract the actual incentive price data from the request information, parse and verify it to ensure that it meets the data format and range required by the system. Using the previously established functional relationship (i.e., the functional relationship between user participation and incentive price), take the actual incentive price as input to calculate the participation information of distributed users in the target energy storage aggregator at a given incentive price. This may include each user's participation score, participation ranking, participation change trend, etc. Integrate the calculated user participation information to form a complete user participation information data set.

[0172] Extract key features from the user participation information dataset. These features should be able to reflect the user's behavior patterns, preferences, response speed, etc. in the energy storage aggregator. Based on the extracted features, use appropriate algorithms and techniques (such as cluster analysis, association rule mining, etc.) to build user portraits. User portraits should include user types (such as high-engagement users, low-engagement users, etc.), behavioral characteristics (such as active response, conservative wait-and-see, etc.), and possible future behavior predictions (such as participation trends under different incentive prices). After construction, verify the user portrait to ensure its accuracy and practicality. If it is found that the portrait deviates significantly from the actual situation, optimization and adjustment are required.

[0173] The user portrait generation method for energy storage aggregators provided in the embodiment of the present application determines whether the requesting user can access the user portrait based on the pre-acquired portrait request information. If the requesting user can access the user portrait, for each distributed user, the user participation information of the distributed user is determined based on the actual incentive price in the portrait request information, and the user portrait of the distributed user is constructed based on the user participation information. The above method constructs the user portrait of the distributed users in the target energy storage aggregator based on the functional relationship and the actual incentive price, providing the energy storage aggregator with valuable user behavior analysis and prediction results.

[0174] Figure 8 A schematic diagram of the structure of a user portrait generation device for an energy storage aggregator provided in this application, such as Figure 8 As shown, the user portrait generation device 800 of the energy storage aggregator provided in this embodiment includes:

[0175] An acquisition module 801 is used to obtain incentive price data for each distributed user participating in aggregated regulation under a target energy storage aggregator within a preset time period;

[0176] A first determination module 802 is used to determine a target incentive price value corresponding to a target energy storage aggregator according to the incentive price data;

[0177] The first construction module 803 is used to construct a price incentive function for each distributed user based on the target incentive price value;

[0178] A second determination module 804 is used to determine a user participation-incentive price response model corresponding to each number of distributed users according to the price incentive function and the number of all distributed users under the target energy storage aggregator, wherein the user participation-incentive price response model represents a functional relationship between user participation and incentive price;

[0179] The second construction module 805 is used to construct a user profile of each distributed user according to the user participation-incentive price response model and the actual incentive price corresponding to the distributed user.

[0180] In a possible implementation, the acquisition module 801 is specifically used for:

[0181] According to the preset division rules, the preset time period is divided into multiple sub-time periods;

[0182] For each sub-period, obtain the incentive price sub-data of each distributed user participating in the aggregation regulation under the target energy storage aggregator in the sub-period;

[0183] The incentive price sub-data of each distributed user participating in the aggregated regulation in all sub-periods are aggregated to obtain the incentive price data of each distributed user participating in the aggregated regulation.

[0184] In a possible implementation, the acquisition module 801 acquires the incentive price sub-data of each distributed user participating in the aggregated regulation under the target energy storage aggregator in the sub-period, specifically including:

[0185] For each sub-period, obtain control information of each distributed user in the sub-period;

[0186] For each distributed user, based on the type data of the control information of the distributed user, determine whether the distributed user participates in the aggregated control;

[0187] If the distributed users participate in the aggregated regulation, the incentive price data when the distributed users participate in the aggregated regulation is determined as the incentive price sub-data when the distributed users participate in the aggregated regulation in the sub-period.

[0188] In a possible implementation, the acquisition module 801 acquires the incentive price sub-data of each distributed user participating in the aggregated regulation under the target energy storage aggregator in the sub-period, specifically including:

[0189] For each sub-period, obtain the operation data of each distributed user in the sub-period;

[0190] For each distributed user, determine the running status of the distributed user according to the running data of the distributed user;

[0191] Determine whether distributed users participate in aggregate control based on the running status;

[0192] If the distributed users participate in the aggregated regulation, the incentive price data when the distributed users participate in the aggregated regulation is determined as the incentive price sub-data when the distributed users participate in the aggregated regulation in the sub-period.

[0193] In a possible implementation, the second determining module 804 is configured to:

[0194] Determine the participation data of each distributed user based on the price incentive function and the number of distributed users under the target energy storage aggregator;

[0195] For each distributed user, based on the distributed user's participation data, a user participation-incentive price response model corresponding to the distributed user is determined.

[0196] In a possible implementation, the second building module 805 is configured to:

[0197] Based on the pre-obtained portrait request information, determine whether the user can access the user portrait;

[0198] If the requesting user can access the user portrait, for each distributed user, the user participation information of the distributed user is determined based on the actual incentive price in the portrait request information;

[0199] Build user profiles of distributed users based on user participation information.

[0200] In a possible implementation, the first determining module 802 is configured to:

[0201] Calculate the average of the incentive price data and determine the average as the target incentive price value;

[0202] or,

[0203] The data that appears most frequently in the incentive price data is determined as the target incentive price value.

[0204] The user portrait generation device for energy storage aggregators provided in this embodiment can execute the user portrait generation method for energy storage aggregators provided in the above method embodiment. Its implementation principle and technical effects are similar and will not be described in detail in this embodiment.

[0205] Fig. 9 This is a schematic diagram of the structure of the electronic device provided in this application. Fig. 9As shown, the electronic device 900 provided in this embodiment includes: at least one processor 901 and a memory 902. Optionally, the electronic device 900 further includes a communication component 903. The processor 901, the memory 902 and the communication component 903 are connected via a bus 904.

[0206] In a specific implementation process, at least one processor 901 executes the computer execution instructions stored in the memory 902, so that at least one processor 901 executes the above method.

[0207] The specific implementation process of the processor 901 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0208] In the above embodiments, it should be understood that the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly implemented as a hardware processor, or can be implemented by a combination of hardware and software modules in the processor.

[0209] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk storage.

[0210] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0211] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0212] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0213] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0214] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0215] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0216] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0217] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0218] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0219] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0220] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for generating a user profile of an energy storage aggregator, characterized in that: include: Obtain the incentive price data for each distributed user participating in the aggregation control under the target energy storage aggregator within the preset time period; Determining a target incentive price value corresponding to the target energy storage aggregator according to the incentive price data; Based on the target incentive price value, construct a price incentive function for each distributed user; Determine a user participation-incentive price response model corresponding to each number of distributed users according to the price incentive function and the number of all distributed users under the target energy storage aggregator, wherein the user participation-incentive price response model represents a functional relationship between user participation and incentive price; For each distributed user, a user profile of the distributed user is constructed according to the user participation-incentive price response model and the actual incentive price corresponding to the user.

2. The method according to claim 1, characterized in that The step of obtaining the incentive price data for each distributed user participating in the aggregated regulation under the target energy storage aggregator within the preset time period includes: Divide the preset time period according to a preset division rule to obtain multiple sub-time periods; For each sub-period, obtaining the incentive price sub-data of each distributed user participating in the aggregated regulation under the target energy storage aggregator in the sub-period; The incentive price sub-data of each distributed user participating in the aggregated regulation in all sub-periods are aggregated to obtain the incentive price data of each distributed user participating in the aggregated regulation.

3. The method according to claim 2, characterized in that The obtaining of incentive price sub-data for each distributed user participating in aggregated regulation under the target energy storage aggregator in the sub-period includes: For each sub-period, obtaining control information of each distributed user in the sub-period; For each distributed user, determining whether the distributed user participates in aggregated regulation based on the type data of the control information of the distributed user; If the distributed user participates in aggregated regulation, the incentive price data when the distributed user participates in aggregated regulation is determined as the incentive price sub-data for the distributed user to participate in aggregated regulation in the sub-period.

4. The method according to claim 2, characterized in that: The obtaining of incentive price sub-data for each distributed user participating in aggregated regulation under the target energy storage aggregator in the sub-period includes: For each sub-period, obtaining the operation data of each distributed user in the sub-period; For each distributed user, determining the operating state of the distributed user according to the operating data of the distributed user; Determining whether the distributed user participates in aggregated regulation according to the operating status; If the distributed user participates in aggregated regulation, the incentive price data when the distributed user participates in aggregated regulation is determined as the incentive price sub-data for the distributed user to participate in aggregated regulation in the sub-period.

5. The method according to claim 1, characterized in that The determining of a user participation-incentive price response model corresponding to each number of distributed users according to the price incentive function and the number of all distributed users under the target energy storage aggregator includes: Determining participation data of each distributed user according to the price incentive function and the number of distributed users under the target energy storage aggregator; For each distributed user, based on the participation data of the distributed user, a user participation-incentive price response model corresponding to the distributed user is determined.

6. The method according to claim 1, characterized in that The step of constructing a user profile of the distributed user according to the user participation-incentive price response model and the actual incentive price corresponding to the user includes: Based on the pre-obtained portrait request information, determine whether the user can access the user portrait; If it is true that the requesting user can access the user portrait, for each distributed user, the user participation information of the distributed user is determined based on the actual incentive price in the portrait request information; A user profile of the distributed user is constructed according to the user participation information.

7. The method according to claim 1, characterized in that Determining the target incentive price value corresponding to the target energy storage aggregator according to the incentive price data includes: Calculating an average value of the incentive price data, and determining the average value as the target incentive price value; or, The data with the highest frequency of occurrence in the incentive price data is determined as the target incentive price value.

8. A user portrait generation device for an energy storage aggregator, characterized in that: include: An acquisition module is used to obtain the incentive price data of each distributed user participating in the aggregation regulation under the target energy storage aggregator within a preset time period; A first determination module, configured to determine a target incentive price value corresponding to the target energy storage aggregator according to the incentive price data; A first building module, configured to build a price incentive function for each distributed user based on the target incentive price value; A second determination module is used to determine a user participation-incentive price response model corresponding to each number of distributed users according to the price incentive function and the number of all distributed users under the target energy storage aggregator, wherein the user participation-incentive price response model represents a functional relationship between user participation and incentive price; The second construction module is used to construct a user profile of each distributed user according to the user participation-incentive price response model and the actual incentive price corresponding to the user.

9. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes the method for generating a user portrait of an energy storage aggregator as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method for generating a user portrait of an energy storage aggregator as described in any one of claims 1 to 7.

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