Vehicle network interaction regulation and control method based on power grid multi-agent cooperation and related equipment

Abstract

The invention provides a vehicle network interaction regulation and control method based on power grid multi-agent cooperation and related equipment. The method comprises the steps of determining weather information, vehicle information, vehicle owner information, a prediction agent, a regulation and control agent and a pricing agent; according to the weather information, the vehicle information, the vehicle owner information and the prediction agent, determining a regional power utilization load, a regional power generation load and a vehicle charging request; and according to the regional electricity consumption predicted quantity, the regional electricity generation predicted quantity, the vehicle charging request, the regulation and control agent and the pricing agent, regulating and controlling the charging and discharging state of the vehicle accessed to the power grid, calculating the income of the vehicle owner according to the pricing agent, and sending the income to the vehicle owner. Through organic cooperation of the multiple power grid intelligent agents, on the premise that the travel requirements of users are met, temporary power supply provided by non-renewable energy generator sets is reduced in the climbing process of the power grid, the peak regulation capacity of the power grid is improved, and the income of the users is increased.

Description

Technical Field

[0001] The present application relates to the field of vehicle-grid interaction technology, and in particular to a vehicle-grid interaction control method based on power grid multi-agent collaboration and related equipment. Background Art

[0002] Vehicle-grid interaction, namely the two-way charging technology of electric vehicles (Vehicle to Grid, referred to as V2G), refers to the connection of new energy vehicles to the power grid through charging and discharging devices to build a two-way interactive system of information flow and energy flow. By using the batteries of new energy vehicles as movable energy storage batteries, new energy vehicles can be charged when the power load of the power grid is low, and discharge to the power grid when the load is peak, thereby enhancing the peak-shaving capacity of the power grid.

[0003] The profit model of vehicle-grid interaction is mostly based on the difference between peak and valley electricity prices. However, the limited difference between peak and valley electricity prices in existing technologies reduces the enthusiasm of car owners to off-peak charging and discharging. The fixed peak and valley electricity prices also limit the ability of the power grid to use price means to regulate peak loads. Therefore, it is necessary to propose a more reasonable and flexible pricing mechanism and an accurate load forecasting model for charging and discharging regulation. Summary of the invention

[0004] In view of this, the purpose of this application is to propose a vehicle-grid interactive control method and related equipment based on multi-agent collaboration in the power grid.

[0005] Based on the above purpose, the present application provides a vehicle-grid interactive control method based on the collaboration of multiple intelligent agents in the power grid, which performs data processing, data storage and data transmission through a cloud-edge-end architecture, including:

[0006] Determine weather information, vehicle information, owner information, prediction agent, control agent and pricing agent;

[0007] Determine regional power load, regional power generation load and vehicle charging request based on the weather information, the vehicle information, the vehicle owner information and the prediction agent;

[0008] According to the regional electricity consumption forecast, the regional power generation forecast, the vehicle charging request, the control intelligent agent and the pricing intelligent agent, the charging and discharging status of the vehicle connected to the power grid is regulated, and the owner's profit is calculated according to the pricing intelligent agent and sent to the owner.

[0009] Optionally, the meteorological information includes: cloud cover information, precipitation information, temperature information, humidity information and air pressure information;

[0010] The vehicle information includes: vehicle battery status and vehicle battery energy consumption rate;

[0011] The vehicle owner information includes: the vehicle owner's future travel plans and the vehicle owner's historical travel plans.

[0012] Optionally, the prediction agent includes: a vehicle status prediction agent, a power consumption prediction agent, and a renewable energy generation prediction agent;

[0013] The determining of the regional power load, the regional power generation load and the vehicle charging request according to the meteorological information, the vehicle information, the vehicle owner information and the prediction agent comprises:

[0014] Inputting the meteorological information into the power consumption forecasting agent and the renewable energy generation forecasting agent to determine the regional power consumption forecast and regional power generation forecast;

[0015] Inputting the vehicle information and the vehicle owner information into the vehicle state prediction agent to determine the vehicle battery capacity and the vehicle charging request;

[0016] The regional electricity load and the regional power generation load are determined according to the regional power consumption forecast, the regional power generation forecast and the vehicle battery capacity.

[0017] Optionally, the prediction agent further includes: a power grid load prediction agent;

[0018] The determining the regional power load and the regional power generation load according to the regional power consumption forecast, the regional power generation forecast and the vehicle battery capacity includes:

[0019] The predicted regional electricity consumption, predicted regional power generation and the vehicle battery capacity are input into the power grid load prediction intelligent body to determine the regional electricity load and the regional power generation load.

[0020] Optionally, the regulating agent includes: a price regulating agent;

[0021] The step of regulating the charging and discharging state of the vehicle connected to the power grid according to the regional power consumption forecast, the regional power generation forecast, the vehicle charging request, the regulation intelligent agent and the pricing intelligent agent includes:

[0022] Inputting the regional electricity consumption forecast, the regional power generation forecast and the vehicle charging request into the control intelligent body to determine the charging electricity price and the discharging electricity price;

[0023] The charging and discharging status of the vehicle connected to the power grid is regulated according to the vehicle charging request, the charging electricity price, the discharging electricity price and the pricing intelligent entity.

[0024] Optionally, the control agent further includes: a charging strategy agent and a discharging strategy agent;

[0025] The regulating the charging and discharging state of the vehicle connected to the power grid according to the vehicle charging request, the charging electricity price, the discharging electricity price and the pricing intelligent agent includes:

[0026] Inputting the vehicle charging request and the charging electricity price into the charging strategy agent to determine the charging strategy;

[0027] Inputting the discharge electricity price into the discharge strategy agent to determine the discharge strategy;

[0028] According to the charging strategy, the discharging strategy and the pricing intelligent body, the charging and discharging status of the vehicles connected to the power grid is regulated.

[0029] Optionally, the calculating the vehicle owner's profit according to the pricing agent and sending it to the vehicle owner includes:

[0030] The charging strategy and the discharging strategy are input into the pricing intelligent agent to determine the car owner's profit, and the car owner's profit is sent to the car owner.

[0031] Based on the same inventive concept, the embodiment of the present application also provides a vehicle-grid interactive control device based on power grid multi-agent collaboration, including:

[0032] an information determination module configured to determine weather information, vehicle information, and vehicle owner information;

[0033] A prediction module is configured to determine a regional power load, a regional power generation load, and a vehicle charging request based on the weather information, the vehicle information, and the vehicle owner information; wherein the regional power load, the regional power generation load, and the vehicle charging request are determined by a prediction agent;

[0034] The control module is configured to control the charging and discharging strategy of the intelligent vehicle in the area according to the predicted power consumption in the area, the predicted power generation in the area, and the vehicle charging request, and calculate the owner's profit.

[0035] Based on the same inventive concept, an embodiment of the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements a vehicle-grid interactive control method based on multi-agent collaboration of a power grid as described in any one of the above.

[0036] Based on the same inventive concept, an embodiment of the present application also provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to execute any of the above-mentioned vehicle-grid interactive control methods based on multi-agent collaboration of the power grid.

[0037] From the above, it can be seen that the vehicle-grid interactive control method and related equipment based on the cooperation of multiple intelligent agents in the power grid provided by this application include: determining meteorological information, vehicle information, owner information, prediction intelligent agent, control intelligent agent and pricing intelligent agent; according to the meteorological information, the vehicle information, the owner information and the prediction intelligent agent, determining the regional power load, regional power generation load and vehicle charging request; according to the regional power consumption forecast, the regional power generation forecast, the vehicle charging request, the control intelligent agent and the pricing intelligent agent, the charging and discharging state of the vehicle connected to the power grid is regulated, and the owner's income is calculated according to the pricing intelligent agent and sent to the owner. This application improves the peak load regulation capacity of the power grid and increases user benefits on the premise of meeting the travel needs of users through multiple intelligent agents. Thereby improving the reliable power supply obtained during the climbing process of the power grid, reducing the activation of non-renewable energy generators to provide temporary power supply; increasing the benefits obtained by car owners from the interaction of the vehicle grid, thereby increasing participation enthusiasm, making full use of idle electric vehicle batteries, reducing the pressure on the power grid during high load, and making full use of renewable energy generation peaks to charge batteries. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the present application or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0039] Figure 1 A schematic diagram of the flow of a vehicle-grid interactive control method based on multi-agent collaboration in a power grid according to an embodiment of the present application;

[0040] Figure 2 A schematic diagram of multi-agent collaboration according to an embodiment of the present application;

[0041] Figure 3 This is a schematic diagram of the agent data processing flow in an embodiment of the present application;

[0042] Figure 4 A schematic diagram of a cloud-edge-end structure for running a vehicle-grid interactive control method based on power grid multi-agent collaboration according to an embodiment of the present application;

[0043] Figure 5 This is a schematic diagram of the structure of a vehicle-grid interactive control device based on power grid multi-agent collaboration according to an embodiment of the present application;

[0044] Figure 6 A schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0046] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should be the usual meanings understood by people with ordinary skills in the field to which the present application belongs. The "first", "second" and similar words used in the embodiments of the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0047] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0048] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0049] As an optional but non-limiting implementation, in response to receiving an active request from the user, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0050] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet the relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0051] In order to facilitate understanding of the technical solutions of the present disclosure, some technical terms involved in the present disclosure are introduced below.

[0052] Vehicle to Grid (V2G), or bidirectional charging technology for electric vehicles, refers to the connection of new energy vehicles to the power grid through charging and discharging devices, allowing the charging equipment of electric vehicles to switch between charging and discharging modes. When the load on the power grid is low and the electricity price is cheap, electric vehicles can charge from the power grid; when the load on the power grid is peak, the electricity price is high, or the power grid needs additional power support (such as insufficient renewable energy generation), electric vehicles can discharge to the power grid to enhance the peak load regulation capacity of the power grid.

[0053] In order to make the technical solution of the present disclosure clearer and easier to understand, the vehicle-grid interactive control method based on power grid multi-agent collaboration provided by the embodiment of the present disclosure is described in detail below with reference to the accompanying drawings.

[0054] As mentioned in the background technology section, vehicle-grid interaction, that is, the two-way charging technology of electric vehicles (Vehicle to Grid, abbreviated as V2G), refers to the connection of new energy vehicles to the power grid through charging and discharging devices to build a two-way interactive system of information flow and energy flow. By using the batteries of new energy vehicles as movable energy storage batteries, new energy vehicles can be charged when the power load of the power grid is low, and discharge to the power grid when the load is peak, thereby enhancing the peak-shaving capacity of the power grid.

[0055] The profit model of vehicle-grid interaction is mostly based on the difference between peak and valley electricity prices. However, the limited difference between peak and valley electricity prices in existing technologies reduces the enthusiasm of car owners to off-peak charging and discharging. The fixed peak and valley electricity prices also limit the ability of the power grid to use price means to regulate peak loads. Therefore, it is necessary to propose a more reasonable and flexible pricing mechanism and an accurate load forecasting model for charging and discharging regulation.

[0056] In view of this, the embodiments of the present application provide a vehicle-grid interactive control method, device, electronic device and storage medium based on the collaboration of multiple intelligent agents in the power grid. It includes: determining meteorological information, power grid information, vehicle information, owner information, prediction intelligent agent, control intelligent agent and pricing intelligent agent; determining regional power load, regional power generation load and vehicle charging request according to the meteorological information, the power grid information, the vehicle information, the owner information and the prediction intelligent agent; regulating the charging and discharging state of the vehicle connected to the power grid according to the regional power consumption forecast, the regional power generation forecast, the vehicle charging request, the control intelligent agent and the pricing intelligent agent, and calculating the owner's income according to the pricing intelligent agent and sending it to the owner. This application improves the peak-shaving capacity of the power grid and increases user income on the premise of meeting the travel needs of users through multiple power intelligent agents, thereby improving the reliable power supply obtained during the climbing process of the power grid and reducing the activation of non-renewable energy generators to provide temporary power supply.

[0057] like Figure 1As shown, the vehicle-grid interactive control method based on power grid multi-agent collaboration performs data processing, data storage and data transmission through a cloud-edge-end architecture, including:

[0058] Step S102, determining weather information, vehicle information, vehicle owner information, prediction agent, control agent and pricing agent;

[0059] Step S104, determining a regional power load, a regional power generation load and a vehicle charging request according to the meteorological information, the vehicle information, the vehicle owner information and the prediction agent;

[0060] Step S106: According to the regional electricity consumption forecast, the regional power generation forecast, the vehicle charging request, the control intelligent agent and the pricing intelligent agent, the charging and discharging status of the vehicle connected to the power grid is regulated, and the owner's profit is calculated according to the pricing intelligent agent and sent to the owner.

[0061] In some embodiments, meteorological information includes cloud cover, precipitation information, temperature information, humidity information, and air pressure information, etc.; vehicle information includes: vehicle battery status, vehicle battery energy consumption rate, etc.; owner information includes: owner's future travel plan, owner's historical travel plan, etc. Among them, the owner's travel plan can be obtained by accessing calendar, hotel, ticket purchase and other applications, or through a user-specific owner travel plan application.

[0062] In some embodiments, meteorological information can be used to predict residential electricity consumption and upstream renewable energy generation. For example, when the summer weather is hot, residents' demand for cooling will continue to increase, which will also bring certain challenges to the power supply. For another example, when there is a lot of precipitation in the target area, it will cause the flow of water in the river to increase, thereby affecting the power generation of electricity using water flow.

[0063] Specifically, renewable energy includes but is not limited to solar energy, wind energy, hydropower, geothermal energy, biomass energy, geomagnetic energy and ocean energy, and the increase or decrease of the above-mentioned renewable energy sources is affected by the weather.

[0064] In some embodiments, the temperature will have a certain impact on the charging speed, whether the temperature is too high or too low. In a high temperature environment, the chemical reaction of the power battery will be accelerated, which may cause the battery temperature to rise and the internal pressure to increase, thereby affecting the performance of the battery. This will cause the battery's charging and discharging efficiency to decrease and the charging speed to slow down. High temperature will also cause the conductivity of the electrolyte to decrease, reducing the output current of the battery, further affecting the charging speed and causing the charging efficiency to decrease. In a low temperature environment, the battery will go through the process of "charging → low temperature v low charging power → slow speed". This is because the internal resistance of the battery increases, the chemical activity decreases, and the capacity decreases at low temperatures, resulting in a significant slowdown in the charging speed. In addition, environmental factors such as air pressure and humidity will also affect the charging speed.

[0065] In some embodiments, Figure 2 As shown, the prediction agent includes: a vehicle status prediction agent, a power consumption prediction agent and a renewable energy generation prediction agent;

[0066] The determining of the regional power load, the regional power generation load and the vehicle charging request according to the meteorological information, the vehicle information, the vehicle owner information and the prediction agent comprises:

[0067] Inputting the meteorological information into the power consumption forecasting agent and the renewable energy generation forecasting agent to determine the regional power consumption forecast and regional power generation forecast;

[0068] Inputting the vehicle information and the vehicle owner information into the vehicle state prediction agent to determine the vehicle battery capacity and the vehicle charging request;

[0069] The regional electricity load and the regional power generation load are determined according to the regional power consumption forecast, the regional power generation forecast and the vehicle battery capacity.

[0070] In some embodiments, the forecasting agent further comprises: a power grid load forecasting agent;

[0071] The determining the regional power load and the regional power generation load according to the regional power consumption forecast, the regional power generation forecast and the vehicle battery capacity includes:

[0072] The predicted regional electricity consumption, predicted regional power generation and the vehicle battery capacity are input into the power grid load prediction intelligent body to determine the regional electricity load and the regional power generation load.

[0073] In some embodiments, an agent is generally defined as an entity with characteristics of autonomy, responsiveness, initiative, and sociability, which can perceive the environment, make decisions, and perform actions. In a multi-agent collaborative system, each agent is independent and has specific roles or responsibilities. Agents collaborate through communication or information sharing to jointly solve complex problems. With the rapid development of large language models (LLM), LLM-based multi-agent collaboration in power grids has shown great potential in power system-related tasks such as power grid fault diagnosis, power system dispatching and operation, load forecasting, and intelligent inspection.

[0074] In some embodiments, the regulating agent includes: a price regulating agent;

[0075] Therefore, the method of regulating the charging and discharging state of the vehicle connected to the power grid according to the regional power consumption forecast, the regional power generation forecast, the vehicle charging request, the regulation agent and the pricing agent includes:

[0076] Inputting the regional electricity consumption forecast, the regional power generation forecast and the vehicle charging request into the control intelligent body to determine the charging electricity price and the discharging electricity price;

[0077] The charging and discharging status of the vehicle connected to the power grid is regulated according to the vehicle charging request, the charging electricity price, the discharging electricity price and the pricing intelligent entity.

[0078] In some embodiments, the control agent further includes: a charging strategy agent and a discharging strategy agent;

[0079] Therefore, the method of regulating the charging and discharging state of the vehicle connected to the power grid according to the vehicle charging request, the charging electricity price, the discharging electricity price and the pricing intelligent agent includes:

[0080] Inputting the vehicle charging request and the charging electricity price into the charging strategy agent to determine the charging strategy;

[0081] Inputting the discharge electricity price into the discharge strategy agent to determine the discharge strategy;

[0082] According to the charging strategy, the discharging strategy and the pricing intelligent body, the charging and discharging status of the vehicles connected to the power grid is regulated.

[0083] In some embodiments, during the construction of the intelligent agent, different training data sets are constructed for different intelligent agent roles, and the Supervised Fine-tuning (SFT) technology and the reinforcement learning alignment method based on human feedback (Reinforcement Learning from Human Feedback) are used to enable the pre-trained large model to be competent for specific roles, and the model training cost is reduced through low-rank adaptation (LoRA).

[0084] In some embodiments, Figure 2 As shown, the electricity consumption prediction agent is trained and determined based on meteorological information to predict residents' electricity consumption; the renewable energy generation prediction agent predicts the upstream renewable energy generation based on meteorological information; the vehicle status prediction agent designs vehicle charging requests and can provide peak-shaving battery capacity according to the owner's travel plan and vehicle battery status, thereby determining the status of all vehicles connected to the power grid; the grid load prediction agent is determined based on regional electricity consumption forecasts, renewable energy supply forecasts, and vehicle battery capacity forecasts; the price control agent performs price control based on the predicted load; and the charging strategy agent is designed and trained based on vehicle charging requests and the formulated peak and valley electricity prices.

[0085] In some embodiments, Figure 3 As shown, any intelligent agent consists of two parts: tools and power knowledge base. After receiving external input (or not), the power intelligent agent generates the final result by calling appropriate tools and querying related data. Specifically:

[0086] For the vehicle status prediction agent, the input is the travel plan and battery status. After querying the driving habits of the owner, the energy consumption rate of the battery of this model and other data, the output is the battery capacity of the vehicle that can be used for peak load shifting, as well as the charging request;

[0087] For the electricity consumption prediction agent, the tool collects the weather information of the current city, analyzes the population flow and electricity consumption of the current city on weekdays or holidays under the weather conditions, and predicts the city's electricity consumption;

[0088] For the renewable energy power generation prediction agent, the tool collects weather information at the location of the power generation facility, queries the power generation of the relevant power generation facilities, and predicts the power generation of the power generation facilities in each period;

[0089] The inputs to the power grid load forecasting intelligent body are vehicle battery capacity, regional power consumption forecast, and renewable energy supply forecast. After querying the power generation of stable power supply facilities such as thermal power and nuclear power, the power load and power generation load are predicted. Among them, power load: the power consumed by the power equipment connected to the power system, that is, the work done by the current and voltage in a certain time interval. It reflects the load demand of the power grid; power generation load: the sum of the power output of each power plant in the power grid at a certain moment. It represents the actual power generation output of the power grid, excluding the power transmitted on the interconnected lines;

[0090] For the price control agent, the input is the electricity consumption and power generation load forecast. Based on the difference between the two, by predicting the owner's willingness to charge and discharge under different electricity prices, a reasonable peak and valley electricity price is formulated on the premise of meeting the user's electricity demand and ensuring the stable operation of the power grid;

[0091] For the charging strategy agent, according to the peak and valley electricity prices (time-of-use peak and valley electricity prices) and the vehicle's charging request, the most economical charging strategy is formulated based on the battery charging curve and the peak and valley electricity prices while meeting the user's travel needs;

[0092] For the discharge strategy agent, the input is the peak and valley electricity price and battery status, and the highest-profit discharge strategy is formulated based on battery loss and user travel plans;

[0093] For the pricing agent, according to the charging strategy and discharging strategy, according to the charging and discharging curves of the battery, the charging cost and discharging strategy (calculation of discharge benefits) are calculated to obtain the user's final benefit.

[0094] In some embodiments, in order to reduce latency and increase response speed, improve system reliability and fault tolerance, and support distributed intelligence and real-time analysis, the following methods are adopted in the deployment of intelligent agents: Figure 4 The cloud-edge-end collaborative integrated architecture shown runs the vehicle-grid interactive control method based on the collaboration of multiple intelligent agents in the power grid in this application. New energy vehicles, various types of power-consuming equipment, and meteorological-related sensors belong to the end, which processes basic data such as battery capacity, power demand, and weather conditions and transmits them to the power intelligent agent at the edge. After processing, the edge intelligent agent sends the processing results to the cloud intelligent agent. After summarizing, the cloud intelligent agent transmits today's peak and valley electricity prices to the charging strategy intelligent agent and the discharging strategy intelligent agent at the edge. The edge intelligent agent determines the charging and discharging strategy of each vehicle based on the cloud results and the needs of the end equipment, and performs the final pricing.

[0095] As can be seen from the above, the vehicle-grid interaction control method based on the cooperation of multiple intelligent agents in the power grid provided by the present application includes: determining meteorological information, vehicle information, owner information, prediction intelligent agent, control intelligent agent and pricing intelligent agent; according to the meteorological information, the vehicle information, the owner information and the prediction intelligent agent, determining the regional power load, regional power generation load and vehicle charging request; according to the regional power consumption forecast, the regional power generation forecast, the vehicle charging request, the control intelligent agent and the pricing intelligent agent, the charging and discharging state of the vehicle connected to the power grid is regulated, and the owner's income is calculated according to the pricing intelligent agent and sent to the owner. This application improves the peak load regulation capacity of the power grid and increases user income on the premise of meeting the travel needs of users through multiple intelligent agents, and then regulates the charging and discharging state of the vehicle connected to the power grid according to the income. Thereby improving the reliable power supply obtained during the climbing process of the power grid, reducing the use of non-renewable energy generators to provide temporary power supply; increasing the benefits obtained by car owners from the vehicle-grid interaction, thereby increasing participation enthusiasm, making full use of idle electric vehicle batteries, reducing the pressure on the power grid during high load, and making full use of renewable energy generation peaks to charge batteries.

[0096] It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0097] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a vehicle-grid interactive control device based on an intelligent body.

[0098] refer to Figure 5 The vehicle-grid interactive control device based on power grid multi-agent collaboration includes:

[0099] An information determination module 502 is configured to determine weather information, vehicle information, and vehicle owner information;

[0100] A prediction module 504 is configured to predict a regional power load, a regional power generation load, and a vehicle charging request based on the weather information, the vehicle information, and the vehicle owner information; wherein the regional power load, the regional power generation load, and the vehicle charging request are determined by a prediction agent;

[0101] The control module 506 is configured to control the vehicle charging and discharging strategy and calculate the vehicle owner's profit according to the regional power consumption forecast, the regional power generation forecast, and the vehicle charging request.

[0102] For the convenience of description, the above device is described in terms of functions divided into various modules. Of course, when implementing the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0103] The device of the above embodiment is used to implement the corresponding vehicle-grid interactive control method based on power grid multi-agent collaboration in any of the aforementioned embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0104] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the vehicle-grid interactive control method based on multi-agent collaboration of a power grid as described in any of the above embodiments is implemented.

[0105] Figure 6 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 in the device.

[0106] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0107] The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0108] The input / output interface 1030 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0109] The communication interface 1040 is used to connect a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0110] The bus 1050 includes a path that transmits information between the various components of the device (eg, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).

[0111] It should be noted that, although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040 and the bus 1050, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

[0112] The electronic device of the above-mentioned embodiment is used to implement the corresponding vehicle-grid interactive control method based on multi-agent collaboration of the power grid in any of the aforementioned embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0113] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the vehicle-grid interactive control method based on power grid multi-agent collaboration as described in any of the above embodiments.

[0114] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0115] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the vehicle-grid interactive control method based on power grid multi-agent collaboration as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0116] Based on the same inventive concept, corresponding to the vehicle-grid interactive control method based on multi-agent collaboration of the power grid described in any of the above embodiments, the present disclosure also provides a computer program product, which includes computer program instructions. In some embodiments, the computer program instructions can be executed by one or more processors of a computer so that the computer and / or the processor executes the vehicle-grid interactive control method based on multi-agent collaboration of the power grid. Corresponding to the execution subject corresponding to each step in each embodiment of the vehicle-grid interactive control method based on multi-agent collaboration of the power grid, the processor that executes the corresponding step may belong to the corresponding execution subject.

[0117] The computer program product of the above embodiment is used to enable the computer and / or the processor to execute the vehicle-grid interactive control method based on power grid multi-agent collaboration as described in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0118] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0119] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuits) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0120] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0121] The embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of the present application.

Claims

1. A vehicle-grid interactive control method based on multi-agent collaboration of power grid, characterized in that: Data processing, data storage, and data transmission are performed through the cloud-edge-device architecture, including: Determine weather information, vehicle information, owner information, prediction agent, control agent and pricing agent; Determine regional power load, regional power generation load and vehicle charging request based on the weather information, the vehicle information, the vehicle owner information and the prediction agent; According to the regional electricity consumption forecast, the regional power generation forecast, the vehicle charging request, the control intelligent agent and the pricing intelligent agent, the charging and discharging status of the vehicle connected to the power grid is regulated, and the owner's profit is calculated according to the pricing intelligent agent and sent to the owner.

2. The method according to claim 1, characterized in that The meteorological information includes: cloud cover information, precipitation information, temperature information, humidity information and air pressure information; The vehicle information includes: vehicle battery status and vehicle battery energy consumption rate; The vehicle owner information includes: the vehicle owner's future travel plans and the vehicle owner's historical travel plans.

3. The method according to claim 1, characterized in that The prediction agents include: vehicle status prediction agent, power consumption prediction agent and renewable energy generation prediction agent; The determining of the regional power load, the regional power generation load and the vehicle charging request according to the meteorological information, the vehicle information, the vehicle owner information and the prediction agent comprises: Inputting the meteorological information into the power consumption forecasting agent and the renewable energy generation forecasting agent to determine the regional power consumption forecast and regional power generation forecast; Inputting the vehicle information and the vehicle owner information into the vehicle state prediction agent to determine the vehicle battery capacity and the vehicle charging request; The regional electricity load and the regional power generation load are determined according to the regional power consumption forecast, the regional power generation forecast and the vehicle battery capacity.

4. The method according to claim 3, characterized in that The prediction agent also includes: a power grid load prediction agent; The determining the regional power load and the regional power generation load according to the regional power consumption forecast, the regional power generation forecast and the vehicle battery capacity includes: The predicted regional electricity consumption, predicted regional power generation and the vehicle battery capacity are input into the power grid load prediction intelligent body to determine the regional electricity load and the regional power generation load.

5. The method according to claim 4, characterized in that The regulation agent includes: a price regulation agent; The step of regulating the charging and discharging state of the vehicle connected to the power grid according to the regional power consumption forecast, the regional power generation forecast, the vehicle charging request, the regulation intelligent agent and the pricing intelligent agent includes: Inputting the regional electricity consumption forecast, the regional power generation forecast and the vehicle charging request into the control intelligent body to determine the charging electricity price and the discharging electricity price; The charging and discharging status of the vehicle connected to the power grid is regulated according to the vehicle charging request, the charging electricity price, the discharging electricity price and the pricing intelligent entity.

6. The method according to claim 5, characterized in that The control agent also includes: a charging strategy agent and a discharging strategy agent; The regulating the charging and discharging state of the vehicle connected to the power grid according to the vehicle charging request, the charging electricity price, the discharging electricity price and the pricing intelligent agent includes: Inputting the vehicle charging request and the charging electricity price into the charging strategy agent to determine the charging strategy; Inputting the discharge electricity price into the discharge strategy agent to determine the discharge strategy; According to the charging strategy, the discharging strategy and the pricing intelligent body, the charging and discharging status of the vehicles connected to the power grid is regulated.

7. The method according to claim 1, characterized in that The calculating the car owner's profit according to the pricing intelligent agent and sending it to the car owner includes: The charging strategy and the discharging strategy are input into the pricing intelligent agent to determine the car owner's profit, and the car owner's profit is sent to the car owner.

8. A vehicle-grid interactive control device based on multi-agent collaboration of power grid, characterized in that: include: an information determination module configured to determine weather information, vehicle information, and vehicle owner information; A prediction module is configured to determine a regional power load, a regional power generation load, and a vehicle charging request based on the weather information, the vehicle information, and the vehicle owner information; wherein the regional power load, the regional power generation load, and the vehicle charging request are determined by a prediction agent; The control module is configured to control the vehicle charging and discharging strategy and calculate the vehicle owner's profit based on the regional electricity consumption forecast, the regional power generation forecast, and the vehicle charging request.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the computer program. 10 . A non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method according to claim 1 .

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