Intelligent planning method and device for super charging station, computer device and storage medium

Abstract

This application discloses an intelligent planning method, apparatus, computer equipment, and storage medium for supercharging stations. The method includes: acquiring a target site model, project requirement data, and project constraint data; obtaining a conventional parking space layout scheme by calling a conventional parking space layout algorithm within an algorithmic intelligent agent; obtaining a complete parking space layout scheme by calling a supercharging parking space layout algorithm within the algorithmic intelligent agent; obtaining an overall layout scheme by calling a modular equipment layout algorithm within the algorithmic intelligent agent; determining a target layout scheme by calling a power verification algorithm within the algorithmic intelligent agent; obtaining an evaluated cost by calling a cost estimation algorithm within the algorithmic intelligent agent; and if the evaluated cost is less than or equal to the cost constraint data in the project constraint data, then the planning result corresponding to the target layout scheme is output by summarizing the data from the intelligent agent. Implementing the method of this application can improve the planning efficiency of supercharging stations.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence technology, and in particular to intelligent planning methods, devices, computer equipment and storage media for supercharging stations. Background Technology

[0002] With the rapid development of the electric vehicle industry, the demand for high-power DC charging stations (hereinafter referred to as "supercharging stations"), as a key infrastructure, is becoming increasingly urgent. The planning and design of supercharging stations is a typical complex systems engineering project, involving deep coupling of multiple professional fields such as civil engineering, electrical engineering, fire protection, and economics. Its technical complexity and design difficulty are far higher than those of traditional charging stations.

[0003] Currently, the planning of supercharging stations mainly relies on the human experience of designers, supplemented by computer-aided design (CAD) tools and some relatively independent professional algorithms. However, supercharging station planning needs to meet multiple specifications simultaneously, which leads to high manual iteration costs, complex processes, and a high risk of omissions or repeated rework, resulting in low efficiency in supercharging station planning. Summary of the Invention

[0004] This application provides a method, apparatus, computer equipment, and storage medium for intelligent planning of supercharging stations, which can improve the planning efficiency of supercharging stations.

[0005] In a first aspect, embodiments of this application provide a supercharging station intelligent planning method. The method is applied to a supercharging station intelligent planning system, which includes a planning agent, an algorithm agent, and a summarizing agent. The algorithm agent includes multiple algorithms. The method includes:

[0006] Based on user input, obtain the target site model, project requirement data, and project constraint data;

[0007] The planning agent calls the conventional parking space layout algorithm in the algorithm agent, and plans multiple conventional parking spaces in the target site model based on the total number of parking spaces in the project demand data and the parking lot constraint data in the project constraint data, to obtain a conventional parking space layout scheme.

[0008] The planning agent calls the supercharging parking space layout algorithm in the algorithm agent. Based on the number of supercharging parking spaces in the project demand data and the conventional parking space layout scheme, some of the conventional parking spaces are converted into supercharging parking spaces to obtain a complete parking space layout scheme.

[0009] The planning agent calls the module equipment layout algorithm in the algorithm agent. Based on the complete parking space layout plan, the preset power supply equipment module library, and the power supply equipment requirement data in the project requirement data, a power supply equipment module is added to the complete parking space layout plan to obtain the overall layout plan.

[0010] The planning agent calls the power verification algorithm in the algorithm agent to perform electrical connection and matching verification on the overall layout scheme, obtain the verification result, and determine the target layout scheme based on the verification result;

[0011] The planning agent calls the cost estimation algorithm in the algorithm agent to evaluate the cost of the target layout scheme based on the preset equipment cost parameter table, and obtains the evaluated cost.

[0012] If the assessed cost is less than or equal to the cost constraint data in the project constraint data, the summarizing agent outputs the planning result corresponding to the target layout scheme; otherwise, the process returns to calling the module equipment layout algorithm or the power verification algorithm until the assessed cost meets the cost constraint data or the preset iteration stop condition.

[0013] In some embodiments, the step of converting a portion of the multiple conventional parking spaces into supercharging parking spaces based on the number of supercharging parking spaces in the project demand data and the conventional parking space layout scheme to obtain a complete parking space layout scheme includes:

[0014] Based on the preset combination of the number of supercharging parking spaces and regular parking spaces in each group of parking spaces, and the number of supercharging parking spaces, the multiple regular parking spaces in the regular parking space layout scheme are grouped to obtain multiple parking space groups.

[0015] For parking space groups that require supercharging parking spaces, the regular parking spaces within the group that are closest to the power supply and have a specified number of supercharging parking spaces are converted into supercharging parking spaces to obtain the complete parking space layout scheme.

[0016] In some embodiments, the power supply equipment module in the overall layout scheme includes multiple transformers, each transformer being connected to multiple main units via cables, and each main unit being connected to multiple load terminals via cables; the step of performing electrical connection and matching verification on the overall layout scheme, obtaining verification results, and determining the target layout scheme based on the verification results includes:

[0017] For each of the aforementioned transformers:

[0018] The first verification result is obtained by verifying whether the number of load-bearing terminal connections of the transformer is less than a preset connection number threshold.

[0019] The second verification result is obtained by verifying whether the cable length between the transformer and each of the load terminals is less than a preset cable length threshold.

[0020] The third verification result is obtained by verifying whether the power supply radius between the transformer and each of the load-bearing terminal devices is less than the preset power supply radius threshold.

[0021] Verify whether the distance between the transformer and the designated equipment is greater than the preset safety distance to obtain the fourth verification result. The designated equipment includes other transformers, the host, and the load terminal.

[0022] If the first verification result, the second verification result, the third verification result, and the fourth verification result are all verified successfully, then the verified successful result is taken as the verification result; otherwise, the verified unsuccessful result is taken as the verification result.

[0023] When the verification result is a pass result, the overall layout scheme is determined as the target layout scheme;

[0024] When the verification result is a failure result, an adjustment plan corresponding to the failure result is generated, and the overall layout plan is adjusted according to the adjustment plan to obtain the target layout plan.

[0025] In some embodiments, the step of outputting the planning result corresponding to the target layout scheme through the summarizing agent includes:

[0026] The aggregation agent generates a layout planning diagram corresponding to the planning results, an equipment list corresponding to the layout planning diagram, a cost summary table, a design description, and a verification report.

[0027] Generate download links for the layout plan, the equipment list, the cost summary table, the design specifications, and the verification report.

[0028] In some embodiments, before obtaining the assessed cost by evaluating the target layout scheme based on a preset equipment cost parameter table, the method further includes:

[0029] The planning agent calls the auxiliary facility layout algorithm in the algorithm agent to add monitoring equipment to the target layout scheme based on preset monitoring requirements, and adds fire-fighting equipment to the target layout scheme based on preset fire-fighting requirements.

[0030] In some embodiments, the step of obtaining the target site model, project requirement data, and project constraint data based on user input includes:

[0031] The candidate site model is obtained by parsing the user-input CAD drawings using a preset CAD preprocessing algorithm.

[0032] Candidate demand data and candidate constraint data are determined by the user's corresponding historical dialogues, personalized demand data and personalized constraint data input by the user.

[0033] A completeness analysis is performed on the candidate site model, the candidate demand data, and the candidate constraint data.

[0034] If the integrity analysis passes, the candidate site model, the candidate requirement data, and the candidate constraint data are respectively determined as the target site model, the project requirement data, and the project constraint data;

[0035] If the integrity analysis fails, supplementary information is generated so that the user can input the corresponding supplementary information based on the supplementary information.

[0036] The candidate site model, candidate requirement data, and / or candidate constraint data are improved based on the supplementary information to obtain the target site model, project requirement data, and project constraint data.

[0037] In some embodiments, the supercharging station intelligent planning system further includes a networked intelligent agent, and the method further includes:

[0038] The target question is to receive user input.

[0039] The networked intelligent agent queries the network for the answer to the target question.

[0040] Secondly, embodiments of this application also provide an intelligent planning system for supercharging stations. The intelligent planning system includes an input unit, a planning agent, an algorithm agent, and a summarizing agent. The algorithm agent includes multiple algorithms, wherein:

[0041] The input unit is used to obtain the target site model, project requirement data, and project constraint data based on the user's input;

[0042] The planning agent is used to invoke the conventional parking space layout algorithm in the algorithmic agent to plan multiple conventional parking spaces in the target site model based on the total number of parking spaces in the project requirement data and the parking lot constraint data in the project constraint data, thereby obtaining a conventional parking space layout scheme; invoke the supercharging parking space layout algorithm in the algorithmic agent to convert some of the multiple conventional parking spaces into supercharging parking spaces based on the number of supercharging parking spaces in the project requirement data and the conventional parking space layout scheme, thereby obtaining a complete parking space layout scheme; invoke the module equipment layout algorithm in the algorithmic agent to add power supply equipment modules to the complete parking space layout scheme based on the complete parking space layout scheme, a preset power supply equipment module library, and power supply equipment requirement data in the project requirement data, thereby obtaining an overall layout scheme; invoke the power verification algorithm in the algorithmic agent to perform electrical connection and matching verification on the overall layout scheme, obtain verification results, and determine the target layout scheme based on the verification results; invoke the cost estimation algorithm in the algorithmic agent to evaluate the cost of the target layout scheme based on a preset equipment cost parameter table, thereby obtaining the evaluated cost;

[0043] The aggregation agent is used to output the planning result corresponding to the target layout scheme when the evaluated cost is less than or equal to the cost constraint data in the project constraint data; otherwise, it returns to the step of calling the module equipment layout algorithm or the power verification algorithm until the evaluated cost meets the cost constraint data or the preset iteration stop condition.

[0044] Thirdly, embodiments of this application also provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0045] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, the computer program including program instructions that, when executed by a processor, can implement the above-described method.

[0046] This application provides a method, apparatus, computer equipment, and storage medium for intelligent planning of supercharging stations. The intelligent planning agent in the supercharging station planning system provided in this application can automatically invoke corresponding algorithms at different design stages based on user-input data to plan supercharging stations. This includes intelligent layout, intelligent power verification, and automatic cost estimation. The planning results are automatically output by summarizing the data, requiring minimal human intervention and improving the efficiency of supercharging station planning. Attached Figure Description

[0047] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 A flowchart illustrating the intelligent planning method for supercharging stations provided in this application embodiment;

[0049] Figure 2 This is a schematic diagram of a sub-process of the intelligent planning method for supercharging stations provided in an embodiment of this application;

[0050] Figure 3 This is another sub-process diagram of the intelligent planning method for supercharging stations provided in the embodiments of this application;

[0051] Figure 4 A schematic block diagram of the intelligent planning system for supercharging stations provided in the embodiments of this application;

[0052] Figure 5 A schematic block diagram of a computer device provided in an embodiment of this application. Detailed Implementation

[0053] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0054] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0055] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0056] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0057] This application provides a method, apparatus, computer equipment, and storage medium for intelligent planning of supercharging stations.

[0058] The supercharging station intelligent planning method can be implemented by the supercharging station intelligent planning system provided in the embodiments of this application, or by a computer device that integrates the supercharging station intelligent planning system. The supercharging station intelligent planning system can be implemented in hardware or software. The computer device can be a terminal or a server. The terminal can be a smartphone, tablet computer, handheld computer, or laptop computer, etc.

[0059] The intelligent supercharging station planning method provided in this embodiment can be applied to supercharging retrofits of urban ground / multi-level parking lots, parking lots of shopping malls / industrial parks / convention centers, logistics and ride-hailing capacity stations, new energy replenishment hubs in suburban / highway service areas, and BIPV (photovoltaic carport) integrated stations, among other supercharging station planning scenarios.

[0060] The intelligent planning system for supercharging stations provided in this application includes at least a planning agent, an algorithm agent, and a summarizing agent. The algorithm agent includes multiple algorithms, including at least a conventional parking space layout algorithm, a supercharging parking space layout algorithm, a modular equipment layout algorithm, a power verification algorithm, and a cost estimation algorithm. Other types of agents and / or algorithms may be added as needed.

[0061] Figure 1 This is a flowchart illustrating the intelligent planning method for supercharging stations provided in an embodiment of this application. Figure 1 As shown, the method includes the following steps S110-S170.

[0062] S110. Obtain the target site model, project requirement data, and project constraint data based on user input.

[0063] In some embodiments, step S110 includes: parsing the CAD drawings input by the user using a preset CAD preprocessing algorithm to obtain candidate site models; determining candidate demand data and candidate constraint data through the user's corresponding historical dialogue, personalized demand data input by the user, and personalized constraint data; performing a completeness analysis on the candidate site models, the candidate demand data, and the candidate constraint data; if the completeness analysis passes, determining the candidate site models, the candidate demand data, and the candidate constraint data as the target site model, the project demand data, and the project constraint data, respectively; if the completeness analysis fails, generating supplementary information to allow the user to input corresponding supplementary information based on the supplementary information; and improving the candidate site models, the candidate demand data, and / or the candidate constraint data based on the supplementary information to obtain the target site model, the project demand data, and the project constraint data.

[0064] Specifically, the personalized requirement data in this application includes the total number of parking spaces (which can be a range, such as 100-120) and the number of supercharging parking spaces (which can be a range, such as 10-15), photovoltaic carports, and battery swapping stations. If any item in the personalized requirement data is empty, the corresponding regular requirement data is determined as the corresponding project requirement data. For example, if the total number of parking spaces is empty, the total number of parking spaces is determined based on the site area in the target site model. If the photovoltaic carports and battery swapping stations are empty, then there is no need to set up photovoltaic carports and battery swapping stations to generate complete project requirement data. The personalized constraint data includes cost constraint data (i.e., maximum cost limit), parking lot constraint data (one or more of parking space size, aisle width, and turning radius), transformer capacity, safety distance, and transformer capacity, etc. Among them, cost constraint data is a required field, while the personalization of other data is optional. If the personalized data corresponding to other data is empty, regular data is pulled as the corresponding project constraint data. For example, if the parking space size is empty, regular charging parking space size is pulled from the local database or external database as the corresponding project requirement data to generate complete project constraint data.

[0065] Personalized demand data and personalized constraint data can be extracted from the user's corresponding historical dialogues and / or input separately. By analyzing the user's historical dialogues, the user's goals and preferences can be obtained, and the candidate demand data and candidate constraint data can be improved without the user needing to understand the specific algorithms or parameters.

[0066] If the integrity analysis fails, for example, if the analysis reveals that the supercharging station site does not have marked entrances and exits, the system will ask follow-up questions to prompt the user to mark the entrance and exit locations (supplementary information). It can be seen that when there are information gaps or high uncertainty, the system will proactively ask follow-up questions instead of blindly seeking solutions, thereby improving the accuracy of supercharging station planning. In addition, this application maintains a traceable chain of dialogue decision results.

[0067] This embodiment involves input data reading and preprocessing: parsing the site CAD (boundaries, entrances / exits, obstacles, existing facilities, etc.) and converting it into a geometric structure usable by the algorithm; and loading project indicators, cost parameters, equipment libraries, and specification texts. Rule and constraint initialization: structuring national / industry / enterprise standards and empirical rules; including thresholds for parking space dimensions, aisle width, turning radius, fire / safety distance, transformer capacity, and voltage drop.

[0068] This application involves a two-stage site layout plan through steps S120 and S130.

[0069] S120. The planning agent calls the conventional parking space layout algorithm in the algorithm agent to plan multiple conventional parking spaces in the target site model based on the total number of parking spaces in the project demand data and the parking lot constraint data in the project constraint data, thereby obtaining a conventional parking space layout scheme.

[0070] In this embodiment, when planning the site layout, the conventional parking space arrangement algorithm is first called to prioritize the arrangement of conventional parking spaces. If no total number of parking spaces is specified, the number of compliant parking spaces can be maximized within the available area. If a total number of parking spaces is specified, the maximum number of parking spaces within the range of the total number of parking spaces will be arranged first.

[0071] In some embodiments, after a standard parking space layout plan is generated, it is displayed in real time. At this time, the user can confirm or adjust the standard parking space layout plan. If the standard parking space layout plan is adjusted (for example, the positions of some parking spaces are changed), the subsequent steps will be executed based on the adjusted standard parking space layout plan. If the user adjusts the standard parking space layout plan while the system is executing subsequent steps, or if the system has completed the planning, the system will recalculate the subsequent plans based on the adjusted standard parking space layout plan.

[0072] S130. The supercharging parking space layout algorithm in the algorithmic agent is called through the planning agent. Based on the number of supercharging parking spaces in the project demand data and the conventional parking space layout scheme, some of the conventional parking spaces are converted into supercharging parking spaces to obtain a complete parking space layout scheme.

[0073] In this embodiment, supercharging parking spaces are allocated after the regular parking spaces are arranged.

[0074] Specifically, in some embodiments, please refer to Figure 2 Step S130 includes:

[0075] S1301. Based on the preset combination of the number of supercharging parking spaces and regular parking spaces in each group of parking spaces and the number of supercharging parking spaces, the multiple regular parking spaces in the regular parking space layout scheme are grouped to obtain multiple parking space groups.

[0076] S1302. For parking space groups that need to be equipped with supercharging parking spaces, convert the regular parking spaces in the group that are closest to the power supply and have a specified number of supercharging parking spaces into supercharging parking spaces to obtain the complete parking space layout scheme.

[0077] For example, each group of parking spaces consists of 12 fast-charging spaces, or 10 fast-charging spaces and 1 supercharging space, or 8 fast-charging spaces and 2 supercharging spaces. The combination of 10 fast-charging spaces and 1 supercharging space is preferred. If the supercharging spaces cannot be fully utilized, the ratio of all or part of the fast-charging and supercharging spaces is adjusted to 8 fast-charging spaces and 2 supercharging spaces. To save on supercharging cable costs, this embodiment places the supercharging spaces in each group at the location closest to the power supply, which is a transformer or distribution cabinet.

[0078] In some embodiments, after a complete parking space layout plan is generated, it is displayed in real time. At this time, the user can confirm or adjust the complete parking space layout plan. If the complete parking space layout plan is adjusted (for example, the positions of some parking spaces are changed), the subsequent steps will be executed based on the adjusted complete parking space layout plan. If the user adjusts the complete parking space layout plan while the system is executing subsequent steps, or if the system has completed the planning, the system will recalculate the subsequent plans based on the adjusted complete parking space layout plan.

[0079] S140. The planning agent calls the module equipment layout algorithm in the algorithm agent. Based on the complete parking space layout plan, the preset power supply equipment module library and the power supply equipment requirement data in the project requirement data, the power supply equipment module is added to the complete parking space layout plan to obtain the overall layout plan.

[0080] This embodiment employs modular equipment layout. For example, it calls a modular equipment layout algorithm to arrange transformers / distribution cabinets, main control rooms, photovoltaic vehicle sheds (optional), battery swapping stations, and station buildings according to standard dimensions and margin parameters.

[0081] In addition, the planning agent calls the auxiliary facility layout algorithm in the algorithm agent to add monitoring equipment to the target layout scheme based on preset monitoring requirements, and adds fire-fighting equipment to the target layout scheme based on preset fire-fighting requirements.

[0082] In some embodiments, after the overall layout scheme is generated, it is displayed in real time. At this time, the user can confirm or adjust the overall layout scheme. If the overall layout scheme is adjusted (for example, the position of some power supply equipment is changed), the subsequent steps will be performed based on the adjusted overall layout scheme. If the user adjusts the overall layout scheme when the system performs subsequent steps, or after the system planning is completed, the system will recalculate the subsequent scheme based on the adjusted overall layout scheme.

[0083] S150. The planning agent calls the power verification algorithm in the algorithm agent to perform electrical connection and matching verification on the overall layout scheme, obtain the verification result, and determine the target layout scheme based on the verification result.

[0084] This embodiment performs electrical connection and matching verification, such as verifying the number of load terminals, line length / voltage drop, power supply radius and safety distance of each transformer; and proposes supplementary or redistribution suggestions.

[0085] Specifically, in some embodiments, the power supply equipment module in the overall layout scheme includes multiple transformers, each transformer being connected to multiple main units via cables, and each main unit being connected to multiple load terminals via cables. Please refer to [link to relevant documentation]. Figure 3 For each of the aforementioned transformers, step S150 includes:

[0086] S1501. Verify whether the number of load-bearing terminal connections of the transformer is less than the first preset connection number threshold, and verify whether the number of load-bearing terminal connections of each host is less than the second preset connection number threshold, and obtain the first verification result.

[0087] Specifically, if the number of load-bearing terminal connections of the transformer is not less than the first preset connection number threshold and the number of load-bearing terminal connections of the host is not less than the second preset connection number threshold, then the verification is passed and determined as the first verification result; otherwise, the verification fails and is determined as the first verification result.

[0088] S1502. Verify whether the cable length between the transformer and each of the load terminals is less than a preset cable length threshold, and obtain a second verification result.

[0089] Specifically, in this embodiment, different preset cable length thresholds are set for different cable types. For each cable, the corresponding cable type is first determined, and then the corresponding preset cable length threshold is found based on the cable type. Then, it is checked whether the cable length of each cable is less than the corresponding preset cable length threshold. If they are all less than the threshold, the verification is passed and determined as the second verification result; otherwise, the verification fails and is determined as the second verification result.

[0090] S1503. Verify whether the power supply radius between the transformer and each of the load-bearing terminal devices is less than the preset power supply radius threshold, and obtain the third verification result;

[0091] Specifically, in this embodiment, the load terminal is limited to not exceeding the power supply radius of the transformer. If it does not exceed the radius, the verification is passed and determined as the third verification result; otherwise, the verification fails and is determined as the third verification result.

[0092] S1504. Verify whether the distance between the transformer and the designated equipment is greater than the preset safety distance to obtain the fourth verification result. The designated equipment includes other transformers, the host and the load terminal.

[0093] Specifically, different preset safety distances can be set for different devices. If the distance between the transformer and the specified device is greater than the preset safety distance, the verification will be passed and determined as the fourth verification result; otherwise, the verification will fail and be determined as the fourth verification result.

[0094] S1505. If the first verification result, the second verification result, the third verification result, and the fourth verification result are all verified successfully, then the verified successful result shall be used as the verification result; otherwise, the verified unsuccessful result shall be used as the verification result.

[0095] S1506. When the verification result is a pass result, the overall layout scheme is determined as the target layout scheme;

[0096] S1507. When the verification result is a verification failure result, an adjustment scheme corresponding to the verification failure result is generated, and the overall layout scheme is adjusted through the adjustment scheme to obtain the target layout scheme.

[0097] Specifically, the adjustment plan corresponding to the failed verification result is related to the specific failed item (whether it is the first verification result, the second verification result, the third verification result, or the fourth verification result that failed). For example, when the first verification result fails, the transformer can be added or removed, or parking spaces can be redistributed. For instance, if a main unit under a transformer only connects to 2 charging terminals (while the second preset connection threshold is 5), more supercharging parking spaces can be added under that transformer to make full use of the main unit. Or, for example, if a transformer only has 3 charging terminals (while the first preset connection threshold is 10), it is not cost-effective to build an additional transformer for a small number of charging terminals, so these parking spaces can be deleted. By reducing the number of "cross-critical" terminals and other strategies, a cost-capacity balance can be achieved.

[0098] In this embodiment, one parking space corresponds to one terminal.

[0099] S160. The planning agent calls the cost estimation algorithm in the algorithm agent to evaluate the cost of the target layout scheme based on the preset equipment cost parameter table, and obtain the evaluated cost.

[0100] Specifically, this embodiment summarizes the costs of civil engineering, equipment, cables, carport / battery swapping modules, monitoring, and other sub-items to obtain the assessed cost.

[0101] If a user modifies the cost of a device, step S160 will be automatically triggered and re-executed to re-evaluate the cost.

[0102] S170. If the assessed cost is less than or equal to the cost constraint data in the project constraint data, the planning result corresponding to the target layout scheme is output through the summarizing agent. Otherwise, the process returns to the step of calling the module equipment layout algorithm or the power verification algorithm until the assessed cost meets the cost constraint data or the preset iteration stop condition.

[0103] Specifically, if the assessed cost is less than or equal to the cost constraint data, the aggregation agent outputs the planning result corresponding to the target layout scheme; otherwise, a backtracking mechanism is triggered, returning to step S120 for re-layout, or returning to step S150 to adjust the equipment model to reduce costs. Whether to return to step S120 or step S150 depends on the settings. It can be based on the user-specified steps or on the specific cost parameters in the assessed cost. For example, if the cost parameters show that the parking space cost is high (the number of parking spaces (total number of parking spaces or number of supercharging parking spaces), the ratio of supercharging to fast charging, and the parking space layout (e.g., whether some parking spaces are arranged in a row horizontally or in two rows vertically) can be updated during iteration), then step S120 can be returned. If the cost of equipment and cables is high, step S150 can be returned (the equipment model can be updated during iteration).

[0104] The preset iteration stop condition can be reaching the maximum number of iterations. If a suitable solution is not found after reaching the maximum number of iterations, the user will be prompted to modify the solution.

[0105] In some embodiments, the step of outputting the planning results corresponding to the target layout scheme through the summarizing agent includes: generating a layout planning diagram corresponding to the planning results, an equipment list, a cost summary table, a design specification, and a verification report corresponding to the layout planning diagram through the summarizing agent; and generating download links for the layout planning diagram, the equipment list, the cost summary table, the design specification, and the verification report.

[0106] In some embodiments, the supercharging station intelligent planning system further includes a networked intelligent agent, and the method further includes:

[0107] Receive the target question input by the user; query the answer corresponding to the target question through the networked intelligent agent.

[0108] For example, if a user needs to check the safety regulations for supercharging stations in region A, the networked intelligent agent can help the user with the search.

[0109] In this embodiment, the summarizing agent can also explain the results and system execution steps to the user in plain language.

[0110] In some embodiments, the algorithmic agent may include various algorithms, such as: CAD processing tools, reinforcement learning-based layout algorithms, greedy algorithms, genetic (annealing) algorithms, decision tree algorithms, grid fitting algorithms, linear programming layout algorithms, clustering algorithms, and tile callers.

[0111] In summary, the planning agent in the supercharging station intelligent planning system provided in this application can automatically call the corresponding algorithm to plan supercharging stations at different design stages based on user-input data, perform intelligent layout, intelligent power verification, and automatic cost estimation for supercharging stations, and automatically output the planning results of supercharging stations by summarizing the intelligent agent, without requiring much human intervention, thus improving the planning efficiency of supercharging stations.

[0112] In addition, this application has the following advantages:

[0113] Text Specifications → Executable Constraints: LLM parsing specifications / empirical texts, "extracting hard constraints / soft constraints / strategy switches," and providing heuristic decisions in multi-solution scenarios (corresponding to the steps of obtaining target site models, project requirement data, and project constraint data);

[0114] Multi-module orchestration: Select and call up links such as regular parking space → supercharging space → electrical verification → cost optimization → backtracking and relocation according to real-time status;

[0115] Decoupling / pluggable: 1. Standards, knowledge bases such as graphs can be added, deleted, or modified at any time, and can be used directly after AI analysis. 2. Agent (intelligent agent) functional modules can also be added or removed according to business needs, which facilitates reuse and upgrades.

[0116] Auditable and traceable: The use of cot (mind chain) can show the complete thought process and solution flow, and key decisions, parameters and results are traced, which is convenient for review and reproduction.

[0117] Furthermore, the aggregated intelligent agent of this application can interact and provide feedback to users using natural language. The entire process only requires natural language chat, and all output processes will be displayed and explained in real time. Users can watch the entire process and intervene to modify it at any step without having to start from scratch.

[0118] Figure 4 This is a schematic block diagram of an intelligent planning system for supercharging stations provided in an embodiment of this application. Figure 4 As shown, corresponding to the above-described intelligent supercharging station planning method, this application also provides an intelligent supercharging station planning system. This intelligent supercharging station planning system includes a unit for executing the above-described intelligent supercharging station planning method, and the intelligent supercharging station planning system 400 can be configured in a desktop computer, tablet computer, laptop computer, or other terminal. For details, please refer to... Figure 4 The intelligent planning system 400 for supercharging stations includes an input unit 401, a planning agent 402, an algorithm agent 403, and a summarizing agent 404. The algorithm agent 403 includes multiple algorithms, among which:

[0119] The input unit 401 is used to obtain the target site model, project requirement data and project constraint data based on the user's input.

[0120] The planning agent 402 is used to call the conventional parking space layout algorithm in the algorithm agent 403 to plan multiple conventional parking spaces in the target site model based on the total number of parking spaces in the project demand data and the parking lot constraint data in the project constraint data, thereby obtaining a conventional parking space layout scheme; it calls the supercharging parking space layout algorithm in the algorithm agent 403 to convert some of the multiple conventional parking spaces into supercharging parking spaces based on the number of supercharging parking spaces in the project demand data and the conventional parking space layout scheme, thereby obtaining a complete parking space layout scheme; it calls the model in the algorithm agent 403... The block equipment layout algorithm, based on the complete parking space layout scheme, a preset power supply equipment module library, and power supply equipment requirement data in the project requirement data, adds power supply equipment modules to the complete parking space layout scheme to obtain an overall layout scheme; it calls the power verification algorithm in the algorithm agent 403 to perform electrical connection and matching verification on the overall layout scheme, obtains the verification result, and determines the target layout scheme based on the verification result; it calls the cost estimation algorithm in the algorithm agent 403 to perform cost evaluation on the target layout scheme based on a preset equipment cost parameter table to obtain the evaluated cost;

[0121] The aggregation agent 404 is used to output the planning result corresponding to the target layout scheme when the evaluated cost is less than or equal to the cost constraint data in the project constraint data; otherwise, it returns to the step of calling the module equipment layout algorithm or calling the power verification algorithm until the evaluated cost meets the cost constraint data or the preset iteration stop condition.

[0122] In some embodiments, when the planning agent 402 executes the step of converting a portion of the multiple conventional parking spaces into supercharging parking spaces based on the number of supercharging parking spaces in the project demand data and the conventional parking space layout scheme, to obtain a complete parking space layout scheme, it is specifically used for:

[0123] Based on the preset combination of the number of supercharging parking spaces and regular parking spaces in each group of parking spaces, and the number of supercharging parking spaces, the multiple regular parking spaces in the regular parking space layout scheme are grouped to obtain multiple parking space groups.

[0124] For parking space groups that require supercharging parking spaces, the regular parking spaces within the group that are closest to the power supply and have a specified number of supercharging parking spaces are converted into supercharging parking spaces to obtain the complete parking space layout scheme.

[0125] In some embodiments, the power supply equipment module in the overall layout scheme includes multiple transformers, each transformer being connected to multiple main units via cables, and each main unit being connected to multiple load terminals via cables; when the planning intelligent agent 402 performs the steps of electrical connection and matching verification of the overall layout scheme, obtaining verification results, and determining the target layout scheme based on the verification results, it is specifically used for:

[0126] For each of the aforementioned transformers:

[0127] The first verification result is obtained by verifying whether the number of load-bearing terminal connections of the transformer is less than a preset connection number threshold.

[0128] The second verification result is obtained by verifying whether the cable length between the transformer and each of the load terminals is less than a preset cable length threshold.

[0129] The third verification result is obtained by verifying whether the power supply radius between the transformer and each of the load-bearing terminal devices is less than the preset power supply radius threshold.

[0130] Verify whether the distance between the transformer and the designated equipment is greater than the preset safety distance to obtain the fourth verification result. The designated equipment includes other transformers, the host, and the load terminal.

[0131] If the first verification result, the second verification result, the third verification result, and the fourth verification result are all verified successfully, then the verified successful result is taken as the verification result; otherwise, the verified unsuccessful result is taken as the verification result.

[0132] When the verification result is a pass result, the overall layout scheme is determined as the target layout scheme;

[0133] When the verification result is a failure result, an adjustment plan corresponding to the failure result is generated, and the overall layout plan is adjusted according to the adjustment plan to obtain the target layout plan.

[0134] In some embodiments, when the aggregating agent 404 executes the step of outputting the planning result corresponding to the target layout scheme, it is specifically used for:

[0135] Generate a layout plan diagram corresponding to the planning results, an equipment list corresponding to the layout plan diagram, a cost summary table, a design description, and a verification report;

[0136] Generate download links for the layout plan, the equipment list, the cost summary table, the design specifications, and the verification report.

[0137] In some embodiments, before executing the step of evaluating the cost of the target layout scheme based on a preset equipment cost parameter table and obtaining the evaluated cost, the planning agent 402 is further configured to:

[0138] The auxiliary facility layout algorithm in the algorithmic agent 403 is invoked to add monitoring equipment to the target layout scheme based on preset monitoring requirements, and to add fire-fighting equipment to the target layout scheme based on preset fire-fighting requirements.

[0139] In some embodiments, when performing the step of acquiring the target site model, project requirement data, and project constraint data based on user input, the input unit 401 is specifically used for:

[0140] Acquire CAD drawings used for input, historical dialogues, personalized requirement data and personalized constraint data input by the user;

[0141] The candidate site model is obtained by parsing the user-input CAD drawings using a preset CAD preprocessing algorithm.

[0142] Candidate demand data and candidate constraint data are determined by the user's corresponding historical dialogues, personalized demand data and personalized constraint data input by the user.

[0143] A completeness analysis is performed on the candidate site model, the candidate demand data, and the candidate constraint data.

[0144] If the integrity analysis passes, the candidate site model, the candidate requirement data, and the candidate constraint data are respectively determined as the target site model, the project requirement data, and the project constraint data;

[0145] If the integrity analysis fails, supplementary information is generated so that the user can input the corresponding supplementary information based on the supplementary information.

[0146] The candidate site model, candidate requirement data, and / or candidate constraint data are improved based on the supplementary information to obtain the target site model, project requirement data, and project constraint data.

[0147] In some embodiments, the supercharging station intelligent planning system 400 further includes a networked intelligent agent:

[0148] The input unit 401 is also used to receive the target question input by the user;

[0149] The networked intelligent agent is used to query the answer to the target question via the network.

[0150] In summary, the planning agent 402 in the supercharging station intelligent planning system 400 provided in this application can automatically call the corresponding algorithm to plan supercharging stations at different design stages based on user-input data, perform intelligent layout, intelligent power verification, and automatic cost estimation for supercharging stations, and automatically output the planning results of supercharging stations by summarizing the data through agent 404, without requiring excessive human intervention, thus improving the planning efficiency of supercharging stations.

[0151] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the above-mentioned supercharging station intelligent planning system 400 and its various units can be referred to the corresponding descriptions in the aforementioned method embodiments. For the sake of convenience and brevity, these details will not be repeated here.

[0152] The aforementioned intelligent planning system for supercharging stations can be implemented as a computer program, which can, for example, Figure 5 It runs on the computer device shown.

[0153] Please see Figure 5 , Figure 5 This is a schematic block diagram of a computer device provided in an embodiment of this application. The computer device 500 can be a terminal or a server. The terminal can be an electronic device with communication functions, such as a smartphone, tablet, laptop, desktop computer, personal digital assistant, or wearable device. The server can be a standalone server or a server cluster composed of multiple servers.

[0154] The computer device 500 is equipped with a supercharging station intelligent planning system, which includes a planning agent, an algorithm agent, and a summarizing agent. The algorithm agent includes a variety of algorithms.

[0155] See Figure 5 The computer device 500 includes a processor 502, a memory, and a network interface 505 connected via a system bus 501. The memory may include a non-volatile storage medium 503 and internal memory 504.

[0156] The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions that, when executed, cause the processor 502 to perform a supercharging station intelligent planning method.

[0157] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0158] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a supercharging station intelligent planning method.

[0159] This network interface 505 is used for network communication with other devices. Those skilled in the art will understand that... Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 500 to which the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0160] The processor 502 is used to run a computer program 5032 stored in the memory to perform the following steps:

[0161] Based on user input, obtain the target site model, project requirement data, and project constraint data;

[0162] The planning agent calls the conventional parking space layout algorithm in the algorithm agent, and plans multiple conventional parking spaces in the target site model based on the total number of parking spaces in the project demand data and the parking lot constraint data in the project constraint data, to obtain a conventional parking space layout scheme.

[0163] The planning agent calls the supercharging parking space layout algorithm in the algorithm agent. Based on the number of supercharging parking spaces in the project demand data and the conventional parking space layout scheme, some of the conventional parking spaces are converted into supercharging parking spaces to obtain a complete parking space layout scheme.

[0164] The planning agent calls the module equipment layout algorithm in the algorithm agent. Based on the complete parking space layout plan, the preset power supply equipment module library, and the power supply equipment requirement data in the project requirement data, a power supply equipment module is added to the complete parking space layout plan to obtain the overall layout plan.

[0165] The planning agent calls the power verification algorithm in the algorithm agent to perform electrical connection and matching verification on the overall layout scheme, obtain the verification result, and determine the target layout scheme based on the verification result;

[0166] The planning agent calls the cost estimation algorithm in the algorithm agent to evaluate the cost of the target layout scheme based on the preset equipment cost parameter table, and obtains the evaluated cost.

[0167] If the assessed cost is less than or equal to the cost constraint data in the project constraint data, the summarizing agent outputs the planning result corresponding to the target layout scheme; otherwise, the process returns to calling the module equipment layout algorithm or the power verification algorithm until the assessed cost meets the cost constraint data or the preset iteration stop condition.

[0168] It should be understood that in the embodiments of this application, the processor 502 may be a central processing unit (CPU), or it may be 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. The general-purpose processor may be a microprocessor or any conventional processor.

[0169] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0170] Therefore, this application also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When executed by a processor, the program instructions cause the processor to perform the following steps:

[0171] Based on user input, obtain the target site model, project requirement data, and project constraint data;

[0172] The planning agent calls the conventional parking space layout algorithm in the algorithm agent, and plans multiple conventional parking spaces in the target site model based on the total number of parking spaces in the project demand data and the parking lot constraint data in the project constraint data, to obtain a conventional parking space layout scheme.

[0173] The planning agent calls the supercharging parking space layout algorithm in the algorithm agent. Based on the number of supercharging parking spaces in the project demand data and the conventional parking space layout scheme, some of the conventional parking spaces are converted into supercharging parking spaces to obtain a complete parking space layout scheme.

[0174] The planning agent calls the module equipment layout algorithm in the algorithm agent. Based on the complete parking space layout plan, the preset power supply equipment module library, and the power supply equipment requirement data in the project requirement data, a power supply equipment module is added to the complete parking space layout plan to obtain the overall layout plan.

[0175] The planning agent calls the power verification algorithm in the algorithm agent to perform electrical connection and matching verification on the overall layout scheme, obtain the verification result, and determine the target layout scheme based on the verification result;

[0176] The planning agent calls the cost estimation algorithm in the algorithm agent to evaluate the cost of the target layout scheme based on the preset equipment cost parameter table, and obtains the evaluated cost.

[0177] If the assessed cost is less than or equal to the cost constraint data in the project constraint data, the summarizing agent outputs the planning result corresponding to the target layout scheme; otherwise, the process returns to calling the module equipment layout algorithm or the power verification algorithm until the assessed cost meets the cost constraint data or the preset iteration stop condition.

[0178] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0179] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0180] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0181] The steps in the methods of this application embodiment can be adjusted, merged, or deleted according to actual needs. The units in the apparatus of this application embodiment can be merged, divided, or deleted according to actual needs. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0182] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0183] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A super-charging station intelligent planning method, characterized in that, The method is applied to an intelligent planning system of a super charging station, the intelligent planning system of the super charging station comprises a planning agent, an algorithm agent and a summary agent, the algorithm agent comprises multiple algorithms, and the method comprises the following steps: Obtain a target site model, project requirement data and project constraint data based on user input; Call a regular parking space arrangement algorithm in the algorithm agent by the planning agent, plan multiple regular parking spaces in the target site model based on a total number of parking spaces in the project requirement data and parking lot constraint data in the project constraint data, and obtain a regular parking space layout scheme; Call a super charging parking space arrangement algorithm in the algorithm agent by the planning agent, convert part of the regular parking spaces into super charging parking spaces based on the number of super charging parking spaces in the project requirement data and the regular parking space layout scheme, and obtain a complete parking space layout scheme; Call a module device arrangement algorithm in the algorithm agent by the planning agent, add power supply device modules in the complete parking space layout scheme based on a preset power supply device module library and power supply device requirement data in the project requirement data, and obtain an overall layout scheme; The power supply device modules in the overall layout scheme comprise multiple transformers, each transformer is connected to multiple hosts through a cable, and each host is connected to multiple load terminals through a cable, call a power checking algorithm in the algorithm agent by the planning agent, perform electrical connection and matching checking on the overall layout scheme, and obtain a checking result, comprising: for each transformer, check whether the number of load terminals connected to the transformer is less than a preset connection number threshold to obtain a first checking result; check whether the length of the cable between the transformer and each load terminal is less than a preset cable length threshold to obtain a second checking result; check whether the power supply radius between the transformer and each load terminal is less than a preset power supply radius threshold to obtain a third checking result; check whether the distance between the transformer and a specified device is greater than a preset safety distance to obtain a fourth checking result, the specified device comprising other transformers, hosts and load terminals; if the first checking result, the second checking result, the third checking result and the fourth checking result are all checked, the checking pass result is taken as the checking result, otherwise, the checking fail is taken as the checking result, and a target layout scheme is determined based on the checking result; Call a cost estimation algorithm in the algorithm agent by the planning agent, perform cost evaluation on the target layout scheme based on a preset device cost parameter table, and obtain an evaluation cost; If the evaluation cost is less than or equal to cost constraint data in the project constraint data, output a planning result corresponding to the target layout scheme by the summary agent, otherwise, return to execute the steps of calling the module device arrangement algorithm or calling the power checking algorithm until the evaluation cost meets the cost constraint data or a preset iteration stop condition.

2. The method of claim 1, wherein, The method further comprises: According to the preset combination of super-charging stations and regular parking spaces in each group of parking spaces and the number of super-charging stations, the regular parking spaces in the regular parking space layout scheme are grouped to obtain a plurality of groups of parking spaces. For the group of parking spaces that need to be provided with super-charging stations, the regular parking spaces closest to the power supply in the group of parking spaces are converted into super-charging stations, and the number of super-charging stations in the group is specified to obtain the complete parking space layout scheme.

3. The method of claim 1, wherein, The method further comprises: When the checking result is a verification pass result, the overall layout scheme is determined as the target layout scheme; When the checking result is a verification fail result, an adjustment scheme corresponding to the verification fail result is generated, and the overall layout scheme is adjusted by the adjustment scheme to obtain the target layout scheme.

4. The method of claim 1, wherein, The method further comprises: The planning result corresponding to the target layout scheme is output by the summary agent. A layout planning diagram corresponding to the planning result, an equipment list corresponding to the layout planning diagram, a cost summary table, a design specification, and a verification report are generated by the summary agent.

5. The method of claim 1, wherein, A download link of the layout planning diagram, the equipment list, the cost summary table, the design specification, and the verification report is generated. Before the cost of the target layout scheme is evaluated based on the preset equipment cost parameter table, the method further comprises:

6. The method of claim 1, wherein, The planning agent calls the ancillary facility arrangement algorithm in the algorithm agent, adds monitoring equipment in the target layout scheme based on preset monitoring requirements, and adds fire-fighting equipment in the target layout scheme based on preset fire-fighting requirements. The method further comprises: A candidate site model is obtained by analyzing the CAD drawing input by the user through a preset CAD preprocessing algorithm; Candidate demand data and candidate constraint data are determined based on the historical dialogue corresponding to the user, the personalized demand data input by the user, and the personalized constraint data input by the user; The candidate site model, the candidate demand data, and the candidate constraint data are subjected to integrity analysis; If the integrity analysis passes, the candidate site model, the candidate demand data, and the candidate constraint data are determined as the target site model, the project demand data, and the project constraint data, respectively; If the integrity analysis fails, supplementary information is generated to enable the user to input corresponding supplementary information based on the supplementary information; 7. The method of claim 1, wherein, The target site model, the project demand data, and the project constraint data are obtained by perfecting the candidate site model, the candidate demand data, and / or the candidate constraint data based on the supplementary information. The super-charging station intelligent planning system further comprises a networked agent, and the method further comprises: Receiving a target problem input by a user; The networking intelligent agent is connected to query the answer corresponding to the target problem.

8. An intelligent planning system for super-charging stations, characterized in that, The super-charging station intelligent planning system comprises an input unit, a planning agent, an algorithm agent and a summary agent, the algorithm agent comprises multiple algorithms, wherein: The input unit is configured to obtain a target site model, project requirement data and project constraint data based on user input; The planning agent is configured to call a regular parking space arrangement algorithm in the algorithm agent, plan multiple regular parking spaces in the target site model based on a total number of parking spaces in the project requirement data and parking field constraint data in the project constraint data, and obtain a regular parking space layout scheme; call a super-charging parking space arrangement algorithm in the algorithm agent, convert part of the multiple regular parking spaces into super-charging parking spaces based on the number of super-charging parking spaces in the project requirement data and the regular parking space layout scheme, and obtain a complete parking space layout scheme; call a module device arrangement algorithm in the algorithm agent, add power supply device modules in the complete parking space layout scheme based on the complete parking space layout scheme, a preset power supply device module library and power supply device requirement data in the project requirement data, and obtain an overall layout scheme; the power supply device modules in the overall layout scheme comprise multiple transformers, each transformer is connected to multiple hosts via a cable, and each host is connected to multiple load terminals via a cable; call a power checking algorithm in the algorithm agent to check electrical connection and matching of the overall layout scheme, and obtain a checking result, comprising: for each transformer, check whether the number of load terminals connected to the transformer is less than a preset connection number threshold to obtain a first checking result; check whether the length of the cable between the transformer and each load terminal is less than a preset cable length threshold to obtain a second checking result; check whether the power supply radius between the transformer and each load terminal is less than a preset power supply radius threshold to obtain a third checking result; check whether the distance between the transformer and a specified device is greater than a preset safety distance to obtain a fourth checking result, the specified device comprising other transformers, hosts and load terminals; if the first checking result, the second checking result, the third checking result and the fourth checking result are all checked, the checking pass result is taken as the checking result, otherwise, the checking fail is taken as the checking result, and a target layout scheme is determined based on the checking result; call a cost estimation algorithm in the algorithm agent to evaluate the cost of the target layout scheme based on a preset device cost parameter table, and obtain an evaluation cost; The summary agent is configured to output a planning result corresponding to the target layout scheme through the summary agent when the evaluation cost is less than or equal to cost constraint data in the project constraint data, otherwise, return to execute the steps of calling the module device arrangement algorithm or calling the power checking algorithm until the evaluation cost meets the cost constraint data or a preset iteration stopping condition.

9. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the super-charging station intelligent planning method in any one of claims 1-7 when executing the computer program.

10. A storage medium, characterized by The storage medium stores a computer program, and the computer program includes program instructions, which, when executed by a processor, cause the processor to execute the super-charging station intelligent planning method in any one of claims 1-7.

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