Intelligent dispatching method, device, equipment and storage medium of smart charging port

Abstract

The present application relates to the field of intelligent scheduling technology, and in particular to a method, device, equipment and storage medium for intelligent scheduling of a smart charging port. The method includes: calculating the energy storage charging and discharging demand information in the target area at the current moment based on the acquired scheduling related information; determining the rechargeable battery module used as the rechargeable battery from the battery modules in the target area based on the energy storage charging and discharging demand information; determining the execution action of each unmanned vehicle chassis based on the working status information of each unmanned vehicle chassis inside and outside the smart charging port in the scheduling related information; generating the scheduling information corresponding to the unmanned vehicle chassis equipped with the corresponding rechargeable battery module at the current moment based on the execution action of each unmanned vehicle chassis and the battery evaluation information corresponding to each rechargeable battery module. The embodiments of the present disclosure realize the reasonable matching between the unmanned vehicle chassis and the battery module in the parking lot scene, thereby reducing the configuration cost of the unmanned vehicle chassis in the parking lot scene.

Description

Technical Field

[0001] The present application relates to the field of intelligent scheduling technology, and in particular to an intelligent scheduling method, device, equipment and storage medium for a smart charging port. Background Art

[0002] Under the pressure of energy and environmental protection, new energy vehicles will undoubtedly become the development direction of future automobiles. Vehicles that use on-board power as power, use motors to drive wheels, and meet the requirements of road traffic and safety regulations; because their impact on the environment is relatively small compared to traditional vehicles, their prospects are widely optimistic; pure electric vehicles (Battery Electric Vehicle, referred to as BEV), which are vehicles that are completely powered by rechargeable batteries (such as lead-acid batteries, nickel-cadmium batteries, nickel-metal hydride batteries or lithium-ion batteries). Although it has a long history of 186 years, it has always been limited to certain specific applications and has a small market. The main reason is that various types of batteries generally have high prices, short lifespans, large dimensions and weights, and long charging times.

[0003] Electric motor-driven vehicles have become popular in recent years because they use clean energy and are energy-saving and environmentally friendly. As the number of electric motor-driven vehicles grows rapidly, so does the problem of range anxiety. Both commercial electric motor-driven vehicles and passenger electric motor-driven vehicles need to be recharged quickly. In order to meet user needs, more and more electric motor-driven vehicles support both charging mode and battery replacement mode, and there are more and more recharging stations that can provide charging and / or battery replacement services.

[0004] There are a total of 24.06 million new energy vehicles in the world facing public charging needs, but there is a contradiction in the allocation of ordinary parking spaces and charging pile parking spaces in parking lots, which makes it impossible to lay fixed charging piles over a large area. Summary of the invention

[0005] The main purpose of the present invention is to provide a smart charging port intelligent scheduling method, device, equipment and storage medium, which can be used to solve the problem of high chassis configuration cost of unmanned vehicles in parking lot scenarios.

[0006] To achieve the above-mentioned object, the present invention provides a smart charging port intelligent scheduling method, comprising: calculating the energy storage charging and discharging demand information in the target area at the current moment based on the acquired scheduling related information;

[0007] Based on the energy storage charging and discharging demand information, determining a rechargeable battery module to be used as a rechargeable battery from the battery modules in the target area;

[0008] Based on the working status information of each unmanned vehicle chassis inside and outside the intelligent charging port in the scheduling related information, determining the execution action of each unmanned vehicle chassis;

[0009] Based on the execution actions of the chassis of each unmanned vehicle and the battery evaluation information corresponding to each rechargeable battery module, the scheduling information corresponding to the unmanned vehicle chassis equipped with the corresponding rechargeable battery module at the current moment is generated.

[0010] Optionally, before calculating the energy storage charging and discharging demand information in the target area at the current moment based on the acquired scheduling related information, the target area includes a target building and a target parking lot, and the method further includes:

[0011] Acquire the local micro-meteorological conditions corresponding to the target parking lot at the current moment, wherein the local micro-meteorological conditions include environmental information in the target parking lot and meteorological parameter information at the current moment; the environmental information includes humidity, air velocity and temperature in the target parking lot;

[0012] The temperature in the target parking lot is regulated by using the acquired historical battery temperature information, the humidity in the target parking lot, the air flow rate and the temperature.

[0013] Optionally, before calculating the energy storage charging and discharging demand information in the target area at the current moment based on the acquired scheduling related information, the scheduling related information includes new energy vehicle charging load information and building load information, and the method further includes:

[0014] Determine the charging load information of the new energy vehicle based on the acquired spatiotemporal distribution information of the parking lot traffic flow and the pre-trained new energy vehicle charging load prediction model;

[0015] The building load information is determined based on the acquired operation information of electrical equipment in the target building in the target area and a pre-trained building load prediction model.

[0016] Optionally, after calculating the energy storage charging and discharging demand information in the target area at the current moment based on the acquired scheduling related information, the method further includes:

[0017] Based on the energy storage charging and discharging demand information, determining an energy storage battery module to be used as an energy storage battery from the battery modules in the target area;

[0018] Based on the energy storage battery modules used as energy storage batteries and the time-of-use electricity price information, a charge and discharge strategy for each energy storage battery at the current moment is generated.

[0019] Optionally, generating scheduling information corresponding to the corresponding rechargeable battery module carried by each unmanned vehicle chassis at the current moment based on the execution actions of each unmanned vehicle chassis and the battery evaluation information corresponding to each rechargeable battery module includes:

[0020] Selecting a target rechargeable battery module from the rechargeable battery modules according to the battery evaluation information corresponding to the rechargeable battery modules at the current moment;

[0021] According to the execution actions of the unmanned vehicle chassis at the current moment, a target unmanned vehicle chassis is selected from the unmanned vehicle chassis inside and outside the smart charging port;

[0022] In response to the acquired power demand information of the new energy vehicle, the corresponding scheduling information is generated based on the selected target unmanned vehicle chassis and the target rechargeable battery module.

[0023] Optionally, based on the charging load information of the new energy vehicle, the rechargeable battery module used as the rechargeable battery is determined from the battery modules in the target area;

[0024] Based on the building load information, an energy storage battery module to be used as an energy storage battery is determined from the battery modules in the target area.

[0025] Optionally, in response to detecting a trigger operation for a new energy vehicle charging demand page, obtaining location information of the new energy vehicle to be charged;

[0026] Based on the position information, control the chassis of the target unmanned vehicle to carry the target rechargeable battery module to the position of the new energy vehicle to be charged;

[0027] Control the chassis of the target unmanned vehicle to remove the target rechargeable battery module, and control the plug of the target rechargeable battery module to start the new energy vehicle charging service;

[0028] In response to acquiring the charging completion information corresponding to the new energy vehicle, based on the execution actions of the unmanned vehicle chassis at the current moment and the position information, selecting a loading unmanned vehicle chassis from the unmanned vehicle chassis inside and outside the smart charging port;

[0029] Control the loading unmanned vehicle chassis to carry the target rechargeable battery module and return to the smart charging port.

[0030] In addition, to achieve the above purpose, the present invention also provides an intelligent dispatching device for a smart charging port, comprising:

[0031] A calculation module, used to calculate the energy storage charging and discharging demand information in the target area at the current moment based on the acquired scheduling related information;

[0032] A rechargeable battery module determination module, used to determine a rechargeable battery module to be used as a rechargeable battery from the battery modules in the target area based on the energy storage charging and discharging demand information;

[0033] An execution action determination module, used to determine the execution action of each unmanned vehicle chassis based on the working status information of each unmanned vehicle chassis inside and outside the smart charging port in the scheduling related information;

[0034] The generation module is used to generate the scheduling information corresponding to the corresponding rechargeable battery module installed on the unmanned vehicle chassis at the current moment based on the execution actions of each unmanned vehicle chassis and the battery evaluation information corresponding to each rechargeable battery module.

[0035] Optionally, before the calculation module, the target area includes a target building and a target parking lot, and the device further includes:

[0036] An acquisition submodule is used to acquire the local micro-meteorological conditions corresponding to the target parking lot at the current moment, wherein the local micro-meteorological conditions include environmental information in the target parking lot and meteorological parameter information at the current moment; the environmental information includes humidity, air flow rate and temperature in the target parking lot;

[0037] The regulating submodule is used to regulate the temperature in the target parking lot according to the acquired historical battery temperature information, the humidity in the target parking lot, the air flow rate and the temperature.

[0038] Optionally, before the calculation module, the scheduling related information includes new energy vehicle charging load information and building load information, and the device further includes:

[0039] A new energy vehicle charging load information determination submodule, used to determine the new energy vehicle charging load information based on the acquired parking lot traffic spatiotemporal distribution information and a pre-trained new energy vehicle charging load prediction model;

[0040] The building load information determination submodule is used to determine the building load information based on the acquired operation information of the electrical equipment in the target building in the target area and the pre-trained building load prediction model.

[0041] Optionally, after the calculation module, the device further includes:

[0042] An energy storage battery module determination submodule, used to determine an energy storage battery module to be used as an energy storage battery from the battery modules in the target area based on the energy storage charging and discharging demand information;

[0043] The charge and discharge strategy generation submodule is used to generate the charge and discharge strategy of each energy storage battery at the current moment based on each energy storage battery module used as the energy storage battery and the time-sharing electricity price information.

[0044] Optionally, the generating module includes:

[0045] A target rechargeable battery module selection submodule, configured to select a target rechargeable battery module from the rechargeable battery modules according to battery evaluation information corresponding to the rechargeable battery modules at a current moment;

[0046] The unmanned vehicle chassis selection submodule is used to select a target unmanned vehicle chassis from the unmanned vehicle chassis inside and outside the smart charging port according to the execution actions of the unmanned vehicle chassis at the current moment;

[0047] The scheduling information generation submodule is used to generate the corresponding scheduling information in response to the acquired power demand information of the new energy vehicle based on the selected target unmanned vehicle chassis and the target rechargeable battery module.

[0048] Optionally, the device further comprises:

[0049] A rechargeable battery module determination submodule, configured to determine the rechargeable battery module used as a rechargeable battery from the battery modules in the target area based on the charging load information of the new energy vehicle;

[0050] The energy storage battery module determination submodule is used to determine the energy storage battery module to be used as the energy storage battery from the battery modules in the target area based on the building load information.

[0051] Optionally, the device further comprises:

[0052] A location information acquisition submodule, for acquiring location information of the new energy vehicle to be charged in response to detecting a trigger operation on the new energy vehicle charging demand page;

[0053] The first control submodule of the target unmanned vehicle chassis is used to control the target unmanned vehicle chassis to carry the target rechargeable battery module to the location of the new energy vehicle to be charged based on the location information;

[0054] The second control submodule of the chassis of the target unmanned vehicle is used to control the chassis of the target unmanned vehicle to remove the target rechargeable battery module, and control the plug of the target rechargeable battery module to start the new energy vehicle charging service;

[0055] The unmanned vehicle chassis loading selection submodule is used to select the unmanned vehicle chassis to be loaded from the unmanned vehicle chassis inside and outside the smart charging port in response to the charging completion information corresponding to the new energy vehicle, based on the execution actions of the unmanned vehicle chassis at the current moment and the position information;

[0056] The unmanned vehicle chassis control submodule is used to control the unmanned vehicle chassis to carry the target rechargeable battery module and return to the smart charging port.

[0057] In addition, to achieve the above-mentioned purpose, the present invention also provides a smart charging port intelligent scheduling device, characterized in that the smart charging port intelligent scheduling device includes: a memory, a processor, and a smart charging port intelligent scheduling program stored in the memory and executable on the processor, and when the smart charging port intelligent scheduling program is executed by the processor, the steps of the smart charging port intelligent scheduling method as described in any one of the above are implemented.

[0058] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, characterized in that a smart charging port intelligent scheduling program is stored on the computer-readable storage medium, and when the smart charging port intelligent scheduling program is executed by the processor, the steps of the smart charging port intelligent scheduling method as described in any one of the above are implemented.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] Based on the acquired scheduling-related information, the energy storage charging and discharging demand information in the target area at the current moment is calculated; based on the energy storage charging and discharging demand information, the rechargeable battery module used as the rechargeable battery is determined from the battery modules in the target area; based on the working status information of each unmanned vehicle chassis inside and outside the smart charging port in the scheduling-related information, the execution action of each unmanned vehicle chassis is determined; based on the execution action of each unmanned vehicle chassis and the battery evaluation information corresponding to each rechargeable battery module, the scheduling information corresponding to the unmanned vehicle chassis equipped with the corresponding rechargeable battery module at the current moment is generated. The embodiments of the present disclosure realize the reasonable matching between the unmanned vehicle chassis and the battery module in the parking lot scene, thereby reducing the configuration cost of the unmanned vehicle chassis in the parking lot scene. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 A schematic diagram of an embodiment of the intelligent dispatching method of the smart charging port in an embodiment of the present invention;

[0062] Figure 2 It is a schematic diagram of an overall embodiment of the intelligent dispatching method of the smart charging port in an embodiment of the present invention;

[0063] Figure 3 It is a schematic diagram of an embodiment of an application scenario of the intelligent scheduling method of the smart charging port in an embodiment of the present invention;

[0064] Figure 4 A schematic diagram of an embodiment of the intelligent dispatching device of the smart charging port in an embodiment of the present invention;

[0065] Figure 5 It is a schematic diagram of an embodiment of the intelligent dispatching equipment of the smart charging port in an embodiment of the present invention. DETAILED DESCRIPTION

[0066] The main purpose of the present invention is to provide a smart charging port intelligent scheduling method, device, equipment and storage medium, which realizes the reasonable matching between the unmanned vehicle chassis and battery module in the parking lot scene, thereby reducing the unmanned vehicle chassis configuration cost in the parking lot scene.

[0067] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0068] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 , is a schematic diagram of an embodiment of the intelligent dispatching method of the smart charging port in an embodiment of the present invention, including:

[0069] Step 101, based on the acquired scheduling related information, calculate the energy storage charging and discharging demand information in the target area at the current moment.

[0070] It is understandable that the execution subject of the present invention may be the intelligent charging port intelligent scheduling method, or may be a terminal or a server, which is not specifically limited here. The embodiment of the present invention is described by taking the server as the execution subject as an example.

[0071] The above-mentioned scheduling-related information may be all information related to the use of battery modules in the smart charging port within the above-mentioned target area; the above-mentioned scheduling-related information may be information that the executing entity can obtain through a wired connection or a wireless connection; the above-mentioned target area may be a pre-selected area, for example, it may be a building, including: a building and a corresponding parking lot; the above-mentioned energy storage charging and discharging demand information includes energy storage charging demand information and energy storage discharging demand information within the above-mentioned target area; the above-mentioned energy storage charging demand information may be the corresponding required charging amount of new energy vehicles that need to be charged in the parking lot; the above-mentioned energy storage discharging demand information may be the amount of electricity required in the building during the peak electricity price period.

[0072] It should be noted that the above-mentioned wireless connection methods may include but are not limited to 3G / 4G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods currently known or to be developed in the future.

[0073] Optionally, before calculating the energy storage charging and discharging demand information in the target area at the current moment based on the acquired scheduling-related information, the target area includes a target building and a target parking lot, and the method further includes: obtaining the local micro-meteorological conditions corresponding to the target parking lot at the current moment, wherein the local micro-meteorological conditions include the environmental information in the target parking lot and the meteorological parameter information at the current moment; the environmental information includes the humidity, air flow rate and temperature in the target parking lot; and regulating the temperature in the target parking lot by using the acquired historical battery temperature information, the humidity in the target parking lot, the air flow rate and the temperature.

[0074] The execution subject can obtain the environmental information in the target parking lot and the meteorological parameter information at the current moment through a wired connection or a wireless connection; the meteorological parameter information at the current moment can be connected to a third-party software through a wired connection or a wireless connection to obtain the weather forecast at the current moment; the historical battery temperature information can be the temperature of the battery in various time periods in history, and the battery temperature information can be obtained in real time by installing a temperature sensor on the battery module and measuring the sensor. Based on the historical battery temperature information obtained, the humidity in the target parking lot, the air flow rate and the temperature, the temperature of the battery in the next time period is predicted. If the temperature of the battery is too high, the temperature in the target parking lot is lowered, thereby reducing the temperature of the battery; the execution subject can adjust the temperature in the target parking lot by controlling cooling equipment such as air conditioners or fans in the target parking lot.

[0075] In order to solve the problem of thermal dissipation or thermal runaway caused by the battery working at too high or too low temperature, the battery temperature can be regulated by adjusting the temperature of a fixed environment through environmental information and historical battery thermal information, thereby increasing the battery life and avoiding danger.

[0076] Optionally, before calculating the energy storage charging and discharging demand information in the target area at the current moment based on the acquired scheduling-related information, the scheduling-related information includes new energy vehicle charging load information and building load information, and the method further includes: determining the new energy vehicle charging load information based on the acquired parking lot traffic spatiotemporal distribution information and a pre-trained new energy vehicle charging load prediction model; determining the building load information based on the acquired target building electrical equipment operation information in the target area and a pre-trained building load prediction model.

[0077] The above-mentioned spatiotemporal distribution information of parking lot traffic flow may be the vehicle information in the target area at the current moment, and the above-mentioned vehicle information includes the number of vehicles, the type of vehicles, and the position of vehicles in the parking lot; the above-mentioned vehicle type may include refueling vehicles and charging new energy vehicles; the above-mentioned new energy vehicle charging load information may be the predicted charging load of new energy vehicles in the target area; the above-mentioned new energy vehicle charging load prediction model may be a model for predicting the charging load information of new energy vehicles based on the above-mentioned spatiotemporal distribution information of parking lot traffic flow; the above-mentioned new energy vehicle charging load prediction model may be obtained by training with a new energy vehicle charging load training sample set; each training sample in the above-mentioned new energy vehicle charging load training sample set includes: sample parking lot traffic spatiotemporal distribution information and corresponding new energy vehicle charging load information; the sample parking lot traffic spatiotemporal distribution information in the training samples in the new energy vehicle charging load training sample set is used as input, and the new energy vehicle charging load information corresponding to the input sample parking lot traffic spatiotemporal distribution information is used as the expected output, and the new energy vehicle charging load prediction model is obtained by training.

[0078] The above-mentioned target building electrical equipment operation information may be the operation information of all electrical equipment in the target area at the current moment except for the electricity domain required by new energy vehicles; for example, it may be the operation information of all lights, air conditioners and other equipment on the building; the above-mentioned building load information may be the predicted electricity load in the building within the target area; the above-mentioned building load prediction model may be a model for predicting the building load information based on the above-mentioned target building electrical equipment operation information; the above-mentioned building load prediction model may be obtained by training with a building load training sample set; each training sample in the above-mentioned building load training sample set includes: sample target building electrical equipment operation information and corresponding building load information; the sample target building electrical equipment operation information in the training samples in the building load training sample set is used as input, and the building load information corresponding to the input sample target building electrical equipment operation information is used as the expected output, and the building load prediction model is obtained by training.

[0079] Optionally, based on the charging load information of the new energy vehicle, the charging battery module used as the charging battery is determined from the battery modules in the target area; based on the building load information, the energy storage battery module used as the energy storage battery is determined from the battery modules in the target area.

[0080] The executing entity can use all other battery modules in the smart charging port as charging batteries when the charging needs of new energy vehicles in the parking lot are met; it can also use all other battery modules in the smart charging port as energy storage batteries when the charging needs of the building are met.

[0081] Optionally, based on the energy storage charging and discharging demand information, an energy storage battery module used as an energy storage battery is determined from the battery modules in the target area; based on the energy storage battery modules used as energy storage batteries and time-of-use electricity price information, a charging and discharging strategy for each energy storage battery at the current moment is generated.

[0082] The executing entity can determine the number and power of battery modules required based on the building load information in the energy storage charging and discharging demand information, and determine the energy storage battery module to be used as the energy storage battery in the smart charging port; the above-mentioned energy storage battery module used as the energy storage battery can be a battery module used to store energy in the smart charging port during the valley period of electricity prices, and supply power to the above-mentioned building during the peak period of electricity prices.

[0083] Step 102: Based on the energy storage charging and discharging demand information, a rechargeable battery module to be used as a rechargeable battery is determined from the battery modules in the target area.

[0084] The execution entity can determine the number and power of the required battery modules based on the new energy vehicle charging load information in the energy storage charging and discharging demand information, and determine the rechargeable battery module used as the rechargeable battery in the smart charging port. The rechargeable battery module used as the rechargeable battery can be a battery module used to charge new energy vehicles in the target area.

[0085] Step 103, based on the working status information of each unmanned vehicle chassis inside and outside the intelligent charging port in the scheduling related information, determine the execution action of each unmanned vehicle chassis.

[0086] The execution subject can determine the execution action of each unmanned vehicle chassis based on the working status information of each unmanned vehicle chassis inside and outside the smart charging port in the scheduling related information; the working status information of the unmanned vehicle chassis can be information used to describe the working status of the unmanned vehicle chassis, and the working status of the unmanned vehicle chassis can be a charging state, an idle state and a working state; the execution action of the unmanned vehicle chassis can correspond to, when the working state is a charging state, the execution action can be stationary; when the working state is an idle state, the execution action can be pending; when the working state is a working state, the execution action can be moving.

[0087] Step 104, based on the execution actions of the chassis of each unmanned vehicle and the battery evaluation information corresponding to each rechargeable battery module, generate the scheduling information corresponding to the corresponding rechargeable battery module installed on the chassis of the unmanned vehicle at the current moment.

[0088] The execution subject may generate the scheduling information corresponding to the corresponding charging battery module carried by the unmanned vehicle chassis at the current moment based on the execution actions of the unmanned vehicle chassis and the battery evaluation information corresponding to the charging battery modules; the above-mentioned battery evaluation information may be the SOC (State of Charge) and SOH (State of Health) of each battery module in the smart charging port; SOC represents the remaining power or charging state of the battery, which is a percentage value used to describe the amount of charge that has been charged to the battery relative to the total capacity of the battery. For example, if the SOC is 50%, it means that the battery has been charged to 50% of the total capacity. In new energy vehicles, SOC is an important indicator for measuring the remaining power of the energy storage system, which can reflect how long the energy storage system can provide power. SOH represents the health status or performance level of the battery. It measures the accumulated loss and aging of the battery during long-term use. SOH is usually represented by a value between 0 and 1, where 0 indicates extremely poor battery performance and 1 indicates good battery performance. As the battery is used and the number of charging cycles increases, the SOH will gradually decrease, resulting in a decrease in battery performance. Therefore, regular monitoring and maintenance of the battery's SOH is essential to ensure the normal operation of electric vehicles and extend battery life. The above dispatch information may be which unmanned vehicle chassis carries which charging battery module and takes which route to reach which parking space to charge the new energy vehicle.

[0089] Optionally, according to the battery evaluation information corresponding to the various rechargeable battery modules at the current moment, a target rechargeable battery module is selected from the various rechargeable battery modules; according to the execution actions of the various unmanned vehicle chassis at the current moment, a target unmanned vehicle chassis is selected from the unmanned vehicle chassis inside and outside the smart charging port; in response to the acquired power demand information of the new energy vehicle, the corresponding scheduling information is generated based on the selected target unmanned vehicle chassis and the target rechargeable battery module.

[0090] The power demand information of the above-mentioned new energy vehicles indicates that the corresponding new energy vehicles have power demand, and an idle unmanned vehicle chassis and a charging battery module with sufficient power are selected; a route is planned for the unmanned vehicle chassis so that the unmanned vehicle chassis is equipped with a corresponding charging battery module to provide charging services for the above-mentioned new energy vehicles according to the planned route.

[0091] In the embodiment of the present invention, the energy storage charging and discharging demand information in the target area at the current moment is calculated based on the obtained scheduling related information; based on the energy storage charging and discharging demand information, the rechargeable battery module used as the rechargeable battery is determined from the battery modules in the target area; based on the working status information of each unmanned vehicle chassis inside and outside the smart charging port in the scheduling related information, the execution action of each unmanned vehicle chassis is determined; based on the execution action of each unmanned vehicle chassis and the battery evaluation information corresponding to each rechargeable battery module, the scheduling information corresponding to the unmanned vehicle chassis equipped with the corresponding rechargeable battery module at the current moment is generated. The embodiment of the present disclosure realizes the reasonable matching between the unmanned vehicle chassis and the battery module in the parking lot scene, thereby reducing the configuration cost of the unmanned vehicle chassis in the parking lot scene.

[0092] The overall process of the embodiment of the present invention is described below. Figure 2 , is a schematic diagram of an overall embodiment of the intelligent scheduling method of the smart charging port in an embodiment of the present invention;

[0093] The scheduling-related information obtained by the executor of the intelligent scheduling method of Zhichonggang (represented as "Intelligent Scheduling Method of Zhichonggang" in the figure) includes the information obtained after passing through the battery thermal management module based on the obtained local micro-meteorological conditions; the information obtained after passing through the new energy vehicle charging load prediction module based on the obtained spatiotemporal distribution of parking lot traffic; the information obtained after passing through the building load prediction module based on the obtained operating status of the energy consumption system (i.e. the operating status of the building's electrical equipment); the time and electricity price information corresponding to the peak, valley and flat periods corresponding to the time-of-use electricity price mechanism; the SOH and SOC of each battery module in the Zhichonggang; and the working status of each unmanned vehicle chassis inside and outside the Zhichonggang.

[0094] The energy storage charging and discharging demand of the current target area (represented as "target park (building)" in the figure") is calculated through the above-mentioned execution entity; based on the energy storage charging and discharging demand, the battery module used as the energy storage battery, the battery module used as the rechargeable battery and the execution action of each unmanned vehicle chassis are determined; based on the battery module used by the energy storage battery, the charging and discharging strategy of each energy storage battery at the current moment is generated; based on the battery module used as the rechargeable battery and the execution action of each unmanned vehicle chassis, it is determined that at the current moment, one (or more) unmanned vehicle chassis is equipped with a corresponding rechargeable battery and goes to the charging demand parking space to provide charging services; and / or at the current moment, one (or more) unmanned vehicle chassis is equipped with a corresponding rechargeable battery and returns to the smart charging port to recharge the unmanned vehicle and the battery module.

[0095] The following is a description of the process of the embodiment of the present invention. Figure 3 , is a schematic diagram of an embodiment of an application scenario of the intelligent scheduling method of the smart charging port in an embodiment of the present invention;

[0096] Step 301, in response to detecting a trigger operation for a new energy vehicle charging demand page, obtaining location information of a new energy vehicle to be charged.

[0097] The above-mentioned new energy vehicle charging demand page can be a page on the mini program where new energy vehicle owners with charging needs enter the parking space number on the mini program, and the above-mentioned trigger operation can be a submission operation for the parking space number on the page; the above-mentioned location information can be the location in the parking lot corresponding to the parking space number.

[0098] Step 302: Based on the position information, control the chassis of the target unmanned vehicle to carry the target rechargeable battery module to the location of the new energy vehicle to be charged.

[0099] The execution entity can control the target unmanned vehicle chassis to carry the target rechargeable battery module to the location of the new energy vehicle to be charged.

[0100] Step 303, control the chassis of the target unmanned vehicle to remove the target rechargeable battery module, and control the plug of the target rechargeable battery module to start the new energy vehicle charging service.

[0101] After arriving at the location of the new energy vehicle to be charged, the execution subject can control the chassis of the target unmanned vehicle to unload the target charging battery module, and control the plug of the target charging battery module to start the new energy vehicle charging service. The effect of vehicle-battery separation has been achieved. After the battery module is delivered, the unmanned vehicle puts the battery module next to the parking space of the new energy vehicle to charge the new energy vehicle; the unmanned vehicle is in an idle state and can arrange other work, thus realizing the reasonable matching between the chassis and battery module of the unmanned vehicle in the parking lot scene, thereby reducing the configuration cost of the chassis of the unmanned vehicle in the parking lot scene.

[0102] Step 304, in response to obtaining the charging completion information corresponding to the new energy vehicle, based on the execution actions of the unmanned vehicle chassis at the current moment and the position information, select the unmanned vehicle chassis to be loaded from the unmanned vehicle chassis inside and outside the smart charging port.

[0103] After obtaining the charging completion information corresponding to the new energy vehicle, the execution subject can select the loading unmanned vehicle chassis from the unmanned vehicle chassis inside and outside the smart charging port based on the execution actions and the position information of the unmanned vehicle chassis at the current moment. When the charging completion information corresponding to the new energy vehicle is obtained, the unmanned vehicle chassis in an idle state nearby is mobilized as the loading unmanned vehicle chassis.

[0104] Step 305, controlling the loading unmanned vehicle chassis to carry the target rechargeable battery module and return to the smart charging port.

[0105] The execution entity can control the unmanned vehicle chassis carrying the target rechargeable battery module to return to the smart charging port for recharging.

[0106] The above describes the intelligent dispatching method of the smart charging port in the embodiment of the present invention. The following describes the intelligent dispatching device 400 of the smart charging port in the embodiment of the present invention. Figure 4 In an embodiment of the present invention, an embodiment of the intelligent dispatching device of the smart charging port includes:

[0107] The calculation module 401 is used to calculate the energy storage charging and discharging demand information in the target area at the current moment based on the acquired scheduling related information;

[0108] A rechargeable battery module determination module 402, configured to determine a rechargeable battery module to be used as a rechargeable battery from the battery modules in the target area based on the energy storage charging and discharging demand information;

[0109] An execution action determination module 403 is used to determine the execution action of each unmanned vehicle chassis based on the working status information of each unmanned vehicle chassis inside and outside the smart charging port in the scheduling related information;

[0110] The generation module 404 is used to generate the scheduling information corresponding to the corresponding rechargeable battery module installed on the unmanned vehicle chassis at the current moment based on the execution actions of the unmanned vehicle chassis and the battery evaluation information corresponding to the each rechargeable battery module.

[0111] The functional implementation of each module in the above-mentioned smart charging port intelligent scheduling device corresponds to the steps in the above-mentioned smart charging port intelligent scheduling method embodiment, and its functions and implementation processes will not be repeated here one by one.

[0112] Optionally, before the calculation module, the target area includes a target building and a target parking lot, and the device further includes:

[0113] An acquisition submodule is used to acquire the local micro-meteorological conditions corresponding to the target parking lot at the current moment, wherein the local micro-meteorological conditions include environmental information in the target parking lot and meteorological parameter information at the current moment; the environmental information includes humidity, air flow rate and temperature in the target parking lot;

[0114] The regulating submodule is used to regulate the temperature in the target parking lot according to the acquired historical battery temperature information, the humidity in the target parking lot, the air flow rate and the temperature.

[0115] Optionally, before the calculation module, the scheduling related information includes new energy vehicle charging load information and building load information, and the device further includes:

[0116] A new energy vehicle charging load information determination submodule, used to determine the new energy vehicle charging load information based on the acquired parking lot traffic spatiotemporal distribution information and a pre-trained new energy vehicle charging load prediction model;

[0117] The building load information determination submodule is used to determine the building load information based on the acquired operation information of the electrical equipment in the target building in the target area and the pre-trained building load prediction model.

[0118] Optionally, after the calculation module, the device further includes:

[0119] An energy storage battery module determination submodule, used to determine an energy storage battery module to be used as an energy storage battery from the battery modules in the target area based on the energy storage charging and discharging demand information;

[0120] The charge and discharge strategy generation submodule is used to generate the charge and discharge strategy of each energy storage battery at the current moment based on each energy storage battery module used as the energy storage battery and the time-sharing electricity price information.

[0121] Optionally, the generating module includes:

[0122] A target rechargeable battery module selection submodule, configured to select a target rechargeable battery module from the rechargeable battery modules according to battery evaluation information corresponding to the rechargeable battery modules at a current moment;

[0123] The unmanned vehicle chassis selection submodule is used to select a target unmanned vehicle chassis from the unmanned vehicle chassis inside and outside the smart charging port according to the execution actions of the unmanned vehicle chassis at the current moment;

[0124] The scheduling information generation submodule is used to generate the corresponding scheduling information in response to the acquired power demand information of the new energy vehicle based on the selected target unmanned vehicle chassis and the target rechargeable battery module.

[0125] Optionally, the device further comprises:

[0126] A rechargeable battery module determination submodule, configured to determine the rechargeable battery module used as a rechargeable battery from the battery modules in the target area based on the charging load information of the new energy vehicle;

[0127] The energy storage battery module determination submodule is used to determine the energy storage battery module to be used as the energy storage battery from the battery modules in the target area based on the building load information.

[0128] Optionally, the device further comprises:

[0129] A location information acquisition submodule, for acquiring location information of the new energy vehicle to be charged in response to detecting a trigger operation on the new energy vehicle charging demand page;

[0130] The first control submodule of the target unmanned vehicle chassis is used to control the target unmanned vehicle chassis to carry the target rechargeable battery module to the location of the new energy vehicle to be charged based on the location information;

[0131] The second control submodule of the chassis of the target unmanned vehicle is used to control the chassis of the target unmanned vehicle to remove the target rechargeable battery module, and control the plug of the target rechargeable battery module to start the new energy vehicle charging service;

[0132] The unmanned vehicle chassis loading selection submodule is used to select the unmanned vehicle chassis to be loaded from the unmanned vehicle chassis inside and outside the smart charging port in response to the charging completion information corresponding to the new energy vehicle, based on the execution actions of the unmanned vehicle chassis at the current moment and the position information;

[0133] The unmanned vehicle chassis control submodule is used to control the unmanned vehicle chassis to carry the target rechargeable battery module and return to the smart charging port.

[0134] In the embodiment of the present invention, the device calculates the energy storage charging and discharging demand information in the target area at the current moment based on the acquired scheduling related information; determines the rechargeable battery module used as the rechargeable battery from the battery modules in the target area based on the energy storage charging and discharging demand information; determines the execution action of each unmanned vehicle chassis based on the working status information of each unmanned vehicle chassis inside and outside the smart charging port in the scheduling related information; generates the scheduling information corresponding to the unmanned vehicle chassis equipped with the corresponding rechargeable battery module at the current moment based on the execution action of each unmanned vehicle chassis and the battery evaluation information corresponding to each rechargeable battery module. The disclosed embodiment realizes the reasonable matching between the unmanned vehicle chassis and the battery module in the parking lot scene, thereby reducing the configuration cost of the unmanned vehicle chassis in the parking lot scene.

[0135] above Figure 4 The smart charging port intelligent dispatching device in the embodiment of the present invention is described in detail from the perspective of modular functional entities. The smart charging port intelligent dispatching device in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0136] Figure 5 It is a structural schematic diagram of a smart dispatching device for a smart charging port provided in an embodiment of the present invention. The smart dispatching device 500 for a smart charging port may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 510 (for example, one or more processors) and a memory 520, and one or more storage media 530 (for example, one or more mass storage devices) storing application programs 533 or data 532. Among them, the memory 520 and the storage medium 530 may be short-term storage or persistent storage. The program stored in the storage medium 530 may include one or more modules (not shown in the figure), and each module may include a series of computer program operations in the smart dispatching device 500 for a smart charging port. Furthermore, the processor 510 may be configured to communicate with the storage medium 530 to execute a series of computer program operations in the storage medium 530 on the smart dispatching device 500 for a smart charging port.

[0137] The intelligent charging port intelligent dispatching device 500 may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input and output interfaces 560, and / or one or more operating systems 531, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. It can be understood by those skilled in the art that Figure 5The structure of the smart dispatching equipment of the Zhichong Port shown does not constitute a limitation on the smart dispatching equipment of the Zhichong Port, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0138] The present invention also provides a smart charging port intelligent scheduling device, comprising: a memory and at least one processor, wherein a computer program is stored in the memory, and the memory and the at least one processor are interconnected through a line; the at least one processor calls the computer program in the memory so that the smart charging port intelligent scheduling device executes the steps in the above-mentioned smart charging port intelligent scheduling method.

[0139] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. A computer program is stored in the computer-readable storage medium. When the computer program runs on a computer, the computer executes the steps of the smart charging port intelligent scheduling method.

[0140] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0141] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, 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. The computer software product is stored in a storage medium, including several computer programs to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0142] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A smart charging port intelligent dispatching method, characterized in that: include: Determine the charging load information of new energy vehicles based on the acquired spatiotemporal distribution information of parking lot traffic and the pre-trained new energy vehicle charging load prediction model; Based on the acquired target building electrical equipment operation information in the target area and the pre-trained building load prediction model, the building load information is determined, and the energy vehicle charging load information and the building load information are used as scheduling related information; Based on the scheduling related information, calculate the energy storage charging and discharging demand information in the target area at the current moment; Based on the energy storage charging and discharging demand information, determining a rechargeable battery module to be used as a rechargeable battery from the battery modules in the target area; Based on the working status information of each unmanned vehicle chassis inside and outside the intelligent charging port in the scheduling related information, determining the execution action of each unmanned vehicle chassis; Based on the execution actions of each unmanned vehicle chassis and the battery evaluation information corresponding to each rechargeable battery module, generating the scheduling information corresponding to the unmanned vehicle chassis equipped with the corresponding rechargeable battery module at the current moment; Based on the charging load information of the new energy vehicle, determining the rechargeable battery module used as the rechargeable battery from the battery modules in the target area; Based on the building load information, an energy storage battery module to be used as an energy storage battery is determined from the battery modules in the target area.

2. According to claim 1, a smart charging port intelligent dispatching method is characterized in that: Before calculating the energy storage charging and discharging demand information in the target area at the current moment based on the acquired scheduling related information, the target area includes a target building and a target parking lot, and the method further includes: Acquire the local micro-meteorological conditions corresponding to the target parking lot at the current moment, wherein the local micro-meteorological conditions include environmental information in the target parking lot and meteorological parameter information at the current moment; the environmental information includes humidity, air velocity and temperature in the target parking lot; The temperature in the target parking lot is regulated by using the acquired historical battery temperature information, the humidity in the target parking lot, the air flow rate and the temperature.

3. According to claim 1, a smart charging port intelligent dispatching method is characterized in that: After calculating the energy storage charging and discharging demand information in the target area at the current moment based on the acquired scheduling related information, the method further includes: Based on the energy storage charging and discharging demand information, determining an energy storage battery module to be used as an energy storage battery from the battery modules in the target area; Based on the energy storage battery modules used as energy storage batteries and the time-of-use electricity price information, a charge and discharge strategy for each energy storage battery at the current moment is generated.

4. According to claim 1, a smart charging port intelligent dispatching method is characterized in that: The generating, based on the execution actions of the chassis of each unmanned vehicle and the battery evaluation information corresponding to each rechargeable battery module, the dispatching information corresponding to the corresponding rechargeable battery module carried by each chassis of the unmanned vehicle at the current moment includes: Selecting a target rechargeable battery module from the rechargeable battery modules according to the battery evaluation information corresponding to the rechargeable battery modules at the current moment; According to the execution actions of the unmanned vehicle chassis at the current moment, a target unmanned vehicle chassis is selected from the unmanned vehicle chassis inside and outside the smart charging port; In response to the acquired power demand information of the new energy vehicle, the corresponding scheduling information is generated based on the selected target unmanned vehicle chassis and the target rechargeable battery module.

5. According to claim 4, a smart charging port intelligent dispatching method is characterized in that: The method further comprises: In response to detecting a trigger operation for a new energy vehicle charging demand page, obtaining location information of the new energy vehicle to be charged; Based on the position information, control the chassis of the target unmanned vehicle to carry the target rechargeable battery module to the position of the new energy vehicle to be charged; Control the chassis of the target unmanned vehicle to remove the target rechargeable battery module, and control the plug of the target rechargeable battery module to start the new energy vehicle charging service; In response to acquiring the charging completion information corresponding to the new energy vehicle, based on the execution actions of the unmanned vehicle chassis at the current moment and the position information, selecting a loading unmanned vehicle chassis from the unmanned vehicle chassis inside and outside the smart charging port; Control the loading unmanned vehicle chassis to carry the target rechargeable battery module and return to the smart charging port.

6. An intelligent dispatching device for a smart charging port, characterized in that: include: A new energy vehicle charging load information determination submodule is used to determine the new energy vehicle charging load information based on the acquired parking lot traffic spatiotemporal distribution information and the pre-trained new energy vehicle charging load prediction model; A building load information determination submodule is used to determine the building load information based on the acquired target building electrical equipment operation information in the target area and the pre-trained building load prediction model, and use the energy vehicle charging load information and the building load information as scheduling related information; A calculation module, used to calculate the energy storage charging and discharging demand information in the target area at the current moment based on the scheduling related information; A rechargeable battery module determination module, used to determine a rechargeable battery module to be used as a rechargeable battery from the battery modules in the target area based on the energy storage charging and discharging demand information; An execution action determination module, used to determine the execution action of each unmanned vehicle chassis based on the working status information of each unmanned vehicle chassis inside and outside the smart charging port in the scheduling related information; A generation module, for generating scheduling information corresponding to the corresponding rechargeable battery module mounted on the chassis of the unmanned vehicle at the current moment based on the execution actions of the chassis of each unmanned vehicle and the battery evaluation information corresponding to each rechargeable battery module; A rechargeable battery module determination submodule, configured to determine the rechargeable battery module used as a rechargeable battery from the battery modules in the target area based on the charging load information of the new energy vehicle; The energy storage battery module determination submodule is used to determine the energy storage battery module to be used as the energy storage battery from the battery modules in the target area based on the building load information.

7. A smart dispatching device for a smart charging port, characterized in that: The smart charging port intelligent scheduling device includes: a memory, a processor, and a smart charging port intelligent scheduling program stored in the memory and executable on the processor. When the smart charging port intelligent scheduling program is executed by the processor, the steps of the smart charging port intelligent scheduling method as described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a smart charging port intelligent scheduling program, and when the smart charging port intelligent scheduling program is executed by the processor, the steps of the smart charging port intelligent scheduling method as described in any one of claims 1 to 5 are implemented.

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