1039 results about "Mobile charge" patented technology

The invention relates to a path planning method for a mobile charging robot in an unstructured environment, which combines global path planning and local dynamic obstacle avoidance, performs global path planning through an improved A * algorithm, and performs real-time local obstacle avoidance by using a dynamic window method. The global path and the local path are fused through dynamic weight adjustment, and it is ensured that the robot keeps the continuity of the global path while avoiding obstacles. In the path planning process, factors such as terrain complexity and robot advancing speed are considered, and the energy consumption of the path is minimized by adopting an energy consumption optimization algorithm, so that the working time of the robot is prolonged, and the execution efficiency is improved. The path planning method is suitable for storage, industry, field inspection and other complex dynamic environments, has high adaptability, real-time performance and robustness, and provides an effective solution for efficient application of the mobile charging robot in an unstructured environment.

The invention discloses an unmanned aerial vehicle autonomous homeward voyage charging system based on wireless charging, and relates to the field of flight control and energy management, and the system comprises the steps: monitoring the flight path, remaining power and environmental parameters of an unmanned aerial vehicle, predicting the remaining power required for completing a task, and triggering a homeward voyage condition signal and the current position information of the unmanned aerial vehicle; generating an optimal homeward flight path of the nearest wireless charging platform based on the homeward flight triggering condition signal and the current position information of the unmanned aerial vehicle; obtaining an optimal charging point based on the generated return path, and sending a deployment instruction to the mobile charging platform; the mobile charging platform advances according to the deployment instruction path, the unmanned aerial vehicle returns according to the optimal return path, the course is corrected through inertial navigation and a visual algorithm, and the landing point of the unmanned aerial vehicle is obtained. Fine adjustment and positioning of the flight attitude are formed by using the visual identification and attitude control module, and a closed-loop flight control mechanism based on image processing and attitude adjustment amount calculation is realized.

The invention relates to the technical field of topographic survey, in particular to an overwater and underwater topographic survey method based on cooperation of an unmanned ship and an unmanned aerial vehicle. The method comprises the following steps: acquiring platform parameter data of an unmanned ship and an unmanned aerial vehicle; according to the platform parameter data, isomerization grouping based on the residual electric quantity, the communication signal strength, the cruising ability and the measurement precision is carried out, a collaborative formation scheme is determined according to a preset water area measurement task sequence, and collaborative parameter data is obtained; acquiring environment data of a measurement area; and performing regional division modeling based on water area topographic features and environmental complexity according to the environmental data of the measurement region, and applying the collaborative parameter data to a regional model to obtain a topological model of the measurement region. The unmanned ship is used as a mobile charging platform, real-time electric quantity monitoring and docking charging mechanisms are combined, the endurance guarantee of the unmanned aerial vehicle is realized through energy supply strategy optimization, and the continuity and stability of tasks are ensured.

The invention discloses a mobile charging pile path planning method and system for an electric vehicle, and relates to the technical field of charging piles, and the method comprises the steps: obtaining a travel plan and a real-time state of a target vehicle, and recognizing a weak energy compensation section; real-time states (including tasks, electric quantity and positions) of all the mobile charging piles in the section are collected; the schedulable electric piles are screened in combination with the vehicle and electric pile states, an alternative set is formed, and schedulability evaluation is carried out; and according to the evaluation result, an optimal service path is planned and issued for the optimal scheduling electric pile according to a preset path strategy, and the optimal service path is guided to execute an energy complementing task. Therefore, the technical effects of improving the scheduling level, improving the energy complementing efficiency and optimizing the energy complementing feeling are achieved.

A multifunctional and rotatable charging dock is provided, which includes a mobile phone charging dock, a watch charging dock, an earphone charging dock, and a common component. The mobile phone charging dock is provided on a top of the common component and can be rotated to achieve wireless charging a mobile phone; the watch charging dock and the earphone charging dock are placed on two sides of the common component for charging the watch and earphones. The common component includes a middle shell, a decoration piece, a main PCB, a counterweight block, a light guide piece, and a bottom cover. The mobile phone charging dock has components such as a lens, a magnet, a coil, etc., and a motor controls its rotation. The watch charging dock can be opened and closed by rotating a shaft, and the earphone charging dock can be turned outward by 90 degrees.

The invention relates to the technical field of mobile charging piles, in particular to a mobile charging pile control method and system, and the method comprises the following steps: S1, charging pile positioning and user demand receiving: obtaining the real-time position information of a mobile charging pile through a GPS; s2, path planning and charging pile movement: controlling a mobile device to drive the charging pile to move to a position designated by a user; s3, charging preparation: performing charging preparation work; s4, electromagnetic interference suppression: suppressing electromagnetic interference; s5, charging and completion: after the charging is completed, disconnecting the power supply, and notifying the user that the charging is completed through the user terminal; s6, dynamic load balancing: monitoring and adjusting the output power of the charging pile in real time; and S7, charging pile returning and data recording: the mobile charging pile returns to an initial position or moves to a standby position according to an instruction of the charging pile control center. According to the invention, efficient scheduling and management of the mobile charging pile are realized.

The invention relates to the technical field of vehicle scheduling, provides a mobile charging vehicle scheduling method and device, electronic equipment and a storage medium, and aims at a plurality of candidate vehicles which send charging requests or are in a low-electric-quantity emergency state to obtain real-time vehicle state data and real-time road network data of each candidate vehicle in real time; according to the method, real-time vehicle state data and real-time road network data are acquired, a corresponding spatial feature risk threshold is acquired from a spatial feature risk database, meanwhile, a time path threshold is determined according to the real-time vehicle state data and the real-time road network data, and then the spatial feature risk threshold and the time path threshold are fused to generate a comprehensive scheduling weight; and finally, according to the comprehensive scheduling weight and the service attribute of the mobile charging vehicle, determining a target vehicle needing to be served and a target parking lot for parking and charging, and scheduling the corresponding mobile charging vehicle to go to the target parking lot to complete the charging service of the target vehicle, so that the user does not need to wait for a long time or empty driving to find a fixed charging pile in the whole process. And the intelligent level and the user experience of the emergency charging service are improved.

The invention discloses a mobile charging robot intelligent navigation method and system based on a distillation strategy, and relates to the technical field of robot navigation. The method comprises the steps that the use state of a charging pile and the use state of a mobile charging robot in a target area are monitored in real time, and nonlinear road network information data in the target area are acquired; processing the non-linear road network information data, and performing environment feature extraction on the processed linear structured data by using a convolutional neural network to construct a dynamic node road network; the dynamic node road network serves as input, a DQN algorithm is used for training a teacher model for path planning, and an optimal path strategy in the dynamic environment is generated; and judging whether a knowledge distillation process needs to be carried out or not, if so, training a student model based on a distillation strategy, and visualizing a navigation path. According to the method and the system, intelligent navigation of the mobile charging robot in a weak network signal nonlinear dynamic scene can be realized.

The invention discloses a method and system for detecting abnormal conditions of multiple mobile phone charging power supplies, and relates to the field of mobile power supplies, and the system comprises a sensing module which is used for monitoring the operation state of power supply equipment, and sensing the operation state information of the power supply equipment in real time when the power supply equipment operates; the judging module is used for traversing the running state information of the power equipment sensed by the sensing module and judging whether the power equipment runs abnormally or not based on the running state information of the power equipment; the interaction module is used for interacting with charging equipment on the power supply equipment in real time to feed back a judgment result about whether the power supply equipment operates abnormally; according to the invention, comprehensive and real-time monitoring is carried out on the operation state of the power supply equipment, key information such as input and output voltage and current, charging power and the like is covered, subtle changes during operation of the power supply can be timely perceived, whether the power supply has abnormal operation or not can be accurately judged by comparing the subtle changes with a safety judgment threshold value, the abnormal condition can be found at the first time, and the safety of the power supply is ensured. And the safety of the charging process is effectively ensured.

The invention relates to the technical field of charging piles, in particular to a mobile charging system based on a charging order-placing intelligent terminal, which comprises a charging order-placing intelligent terminal. An operation platform; a mobile charging terminal; and a user terminal. According to the mobile charging system provided by the embodiment of the invention, the to-be-charged state of the charging port of the to-be-charged vehicle is simulated by using the charging order-placing intelligent terminal, so that the to-be-charged vehicle is locked, and the charging order-placing intelligent terminal sends related information in combination with the user terminal, the operation platform and the mobile charging terminal; the operation platform generates a charging order according to the related information and issues the charging order to the mobile charging terminal, and the mobile charging terminal responds to the charging order and moves to the position of the vehicle to be charged to realize a non-contact and flexible charging process, thereby improving the convenience of the charging process, reducing the limitation of a parking lot through a non-fixed charging providing mode, and improving the charging efficiency. And the use efficiency of the mobile charging terminal can be improved, and resource waste is avoided.

The utility model discloses a multifunctional mobile power pack with a tracking function, including a mobile power pack body and a card holder assembly. A wireless charging module and a position tracking module are disposed in the mobile power pack body, and the card holder assembly is rotatably connected to the mobile power pack body. In the utility model, as the card holder assembly for placing important cards such as bank cards is disposed on the mobile power pack body, the mobile power pack body and the cards are placed together and convenient for the user to carry. The wireless charging module of the mobile power pack body supplies power to a phone and includes a built-in position tracking module that can quickly locate the mobile power pack in case of loss.

The invention provides a mobile charging service method and system based on laser navigation, and relates to the technical field of electric vehicle charging. After a charging demand of a user is obtained through a mobile terminal, an optimal scheduling instruction is generated by integrating the electric quantity of an energy storage pile, a vehicle position and a battery inventory state, and a mobile charging vehicle is controlled to complete automatic battery replacement; and the laser radar SLAM technology and real-time path planning are utilized to realize accurate navigation to the user position for charging, and finally, the old battery pack is automatically recycled and returned to the energy storage pile for energy complementation, so that efficient and intelligent mobile charging service is realized.

The invention discloses a photovoltaic-based mobile charging pile auxiliary energy supplement method and system, and particularly relates to the technical field of energy supply. The method comprises the following steps: acquiring real-time illumination intensity data in a photovoltaic mobile charging pile deployment area and real-time charging demand data of an electric vehicle, and performing data preprocessing to form regional photovoltaic power generation capacity data and regional user charging demand data; analyzing the photovoltaic power generation potential of each grid position, and generating spatial distribution data of the regional illumination power generation potential; identifying space aggregation features of the user charging demand, and generating space aggregation position data of the user charging demand; according to the spatial matching degree between the illumination power generation potential and the charging demand position, determining spatial matching priority data of the optimal deployment position; path planning is carried out based on the space matching priority data, real-time optimal energy complementation scheduling path data is generated, and the scheduling efficiency of the mobile charging pile and the photovoltaic energy utilization rate are improved.

The invention discloses a mobile charging robot return charging scheduling method, and particularly relates to the technical field of mobile robot scheduling management, and the method comprises the steps: collecting state information including the current position, residual electric quantity, task residual path length, battery performance and other contents; when the state meets a scheduling evaluation triggering condition, calculating a behavior urgency index and an energy competition index; inputting the two indexes into a trained learning model, and outputting a decision parameter group containing a scheduling trigger mark, a path sorting factor and a path tradeoff factor; weighing the candidate charging paths according to the decision parameter group, and selecting a comprehensive optimization result as a target path; according to the method, the scheduling quantitative judgment is realized by collecting the multi-dimensional state information and constructing the behavior urgency and energy competition index, the decision parameter group is generated based on the index result, target path screening is guided, a closed-loop mechanism from state perception and intelligent evaluation to path selection is formed, and the scheduling accuracy and the response efficiency are improved.

The invention discloses a mobile charging pile charging demand prediction method and system based on big data analysis, and relates to the related technical field of charging piles, and the method comprises the steps: obtaining the position distribution and remaining power distribution of all mobile charging piles in a preset region in real time; performing prediction of a first type of charging demands from a peak to a trough, and performing charging task distribution density partition identification; second type charging demand prediction of the mobile charging piles is executed based on the charging pile distribution map; executing a second type of charging scheme decision to generate a second charging decision; and controlling the charging of the mobile charging pile according to the second charging decision. The technical problems that in the prior art, dynamic tracks of users cannot be matched, dynamically-changing charging requirements are difficult to adapt, charging resource distribution is unreasonable, charging requirement prediction is not accurate, and the charging service efficiency and the user experience are poor are solved. The technical effects of optimizing the charging resource configuration, improving the charging demand prediction accuracy, and improving the charging service efficiency and the user experience are achieved.

The invention relates to the technical field of vehicles, in particular to a vehicle frame multi-objective optimization method based on rollover collision battery pack safety, which comprises the following steps of: constructing a battery homogenization mechanical model to obtain the distance between current collectors of a positive electrode and a negative electrode of a battery under stress; establishing a battery electrical model through the equivalent circuit, and judging whether the battery is short-circuited in the battery electrical model according to the distance between the current collectors of the positive electrode and the negative electrode; establishing a mobile charging vehicle frame three-dimensional model to obtain an instant angular velocity, and analyzing the damage degree of the battery through the coupling model; and converting each unit of the finite element analysis model into independent cells, adjusting cell attributes according to a preset rule, and performing multi-round iteration by adjusting the cell attributes so as to complete optimization of the frame model. According to the method, aiming at the defect of safety optimization of the battery pack during rollover collision, the lightweight of the frame and the improvement of the safety of the battery pack can be realized at the same time, and the optimization efficiency of a complex model is effectively improved.

The invention relates to an electric vehicle mobile charging station intelligent scheduling method based on a conditional diffusion model, and the method comprises the steps: training an idle charging station state at a current moment and a charging demand information graph in a future time period, and carrying out the model learning of how to generate an optimal target position; specifically, the model firstly collects information generated by each component in the Internet of Things of the electric vehicle in a previous time interval, then draws a two-dimensional information graph by using the information generated by a charging station and the electric vehicle in each time interval, and then uses a conditional diffusion model to train the ability of the model to generate a future time period information graph through time features. And finally, on the basis of a reasoning result, a reasonable target scheduling position is generated for each idle electric vehicle mobile charging station in the current state.

The invention discloses an intelligent charging management method based on a mobile charging device and heat supply network inspection robot dogs. The intelligent charging management method comprises the following steps: setting a plurality of inspection robot dogs to execute different types of heat supply network inspection tasks; the back-end service platform analyzes the real-time inspection power consumption of the inspection robot dogs according to the heat supply network inspection paths, the inspection tasks and the electric quantity attenuation mechanism of the inspection robot dogs, calculates the real-time residual electric quantity of each inspection robot dog, compares the real-time residual electric quantity with the inspection power consumption at the next moment, and sets the charging plan of each inspection robot dog; a plurality of new energy mobile charging devices are arranged to charge each inspection robot dog, and the back-end service platform predicts the power supply value of each new energy mobile charging device; the back-end service platform performs charging optimization distribution of the mobile charging device, and sets an optimal charging path of the mobile charging device and the inspection robot dog; and each mobile charging device and the inspection robot dog autonomously drive to a charging meeting point according to the optimal charging path, and charging is completed in a wireless charging mode.

The mobile charging equipment comprises a semi-trailer type vehicle body, an energy storage compartment, a photovoltaic power generation and heat collection device, a solar photovoltaic panel, a storage battery pack, a heat collection device, a water electrolysis hydrogen production pool, a hydrogen storage tank, a boiler device, a steam turbine generator unit and a fuel cell power generation system. By integrating the technologies of solar power generation and heat collection, solid oxide water electrolysis hydrogen production, steam turbine unit power generation, fuel cell power generation and the like, convenient energy supplementation of the electric agricultural machine is achieved. The equipment is an efficient and environment-friendly energy supply platform, automatic control and remote management can be achieved, and operation convenience and efficiency are improved. Meanwhile, the steam turbine power generation and fuel cell technology is adopted to replace a traditional diesel generator, pollutant emission is reduced, and the requirements of green energy and sustainable development are met. In addition, the equipment can serve as energy storage equipment when being idle, peak load shifting of energy is achieved, and agricultural modernization and sustainable development are promoted.

The invention relates to an electric vehicle mobile charging station scheduling method for realizing charge and discharge collaborative scheduling, which comprises the following steps of: 1, constructing a mobile charging station charging scheduling model based on a multi-agent reinforcement learning algorithm idea; 2, designing a negotiation mechanism between the power grid and the mobile charging station according to reasonable constraint conditions, and constructing a discharging scheduling model of the mobile charging station; 3, integrating the charging and discharging scheduling model, considering the conflict problem of the mobile charging station in response to the charging and discharging request, constructing a charging and discharging collaborative optimization scheduling framework, and scheduling the mobile charging station of the electric vehicle; 4, scheduling the mobile charging station according to the constructed charging and discharging collaborative optimization scheduling framework; according to the scheme, power grid load data is introduced as a constraint condition to promote the mobile charging station to respond to a discharging request, and charging and discharging cooperative scheduling of the mobile charging station is achieved.

The invention discloses a mobile charging pile double-layer dynamic scheduling method and system considering multiple target constraints. The method comprises the following steps: initializing a distribution network topology parameter and a load demand to obtain first data; constructing an upper layer model and a lower layer model; the upper layer model takes distribution network electric vehicle bearing capacity maximization and power purchase cost minimization as double targets; the lower-layer model aims at maximizing the operation income; the upper-layer model takes a preset time length as a calculation period, performs solution according to the first data and positive semidefinite programming, obtains a dispatching guide electricity price of the mobile charging pile, and sends the dispatching guide electricity price to a lower-layer model; the lower-layer model carries out solving according to the dispatching guide electricity price in combination with a multi-cycle rolling optimization mechanism and an improved particle swarm optimization algorithm, and spatial and temporal distribution information of the mobile charging load within preset time is obtained and sent to the upper-layer model; and the upper-layer model calculates a scheduling guide electricity price according to the space-time distribution information, performs cooperative iteration solution with the lower-layer model, and outputs a mobile charging pile scheduling scheme.

The utility model discloses a mobile charging device suitable for an electric agricultural machine, which comprises a semi-trailer body, an energy storage carriage, a photovoltaic power generation and heat collection device, a solar photovoltaic panel, a storage battery pack, a heat collection device, a water electrolysis hydrogen production pool, a hydrogen storage tank, a boiler device, a steam turbine generator unit and a fuel cell power generation system, by integrating the technologies of solar power generation and heat collection, solid oxide water electrolysis hydrogen production, steam turbine unit power generation, fuel cell power generation and the like, convenient energy supplementation of the electric agricultural machine is achieved. The equipment is an efficient and environment-friendly energy supply platform, meanwhile, a turbine power generation and fuel cell technology is adopted to replace a traditional diesel generator, pollutant emission is reduced, and the requirements of green energy and sustainable development are met.

The utility model provides a mobile energy complementing flat car device for a battery pack of a heavy truck. The mobile energy complementing flat car device comprises a mobile flat car, a concentrated direct current charging seat, a battery pack assembly, a charging and discharging connector and a vehicle-mounted charging pile, the movable flat car is mounted on one side of the driving car; the centralized direct-current charging seats are respectively arranged at the front end and the tail end of the upper surface of the mobile flat car, and are independently and electrically connected with the charging and discharging connector; a plurality of groups of charging and discharging connectors are arranged, are electrically connected with the battery pack assembly and are used for being connected with a charging port of a battery pack; the vehicle-mounted charging pile is fixedly installed on the movable flat car, one end of the vehicle-mounted charging pile is electrically connected with the battery pack assembly, and the other end of the vehicle-mounted charging pile is connected with an external charging device. The mobile flat car has the advantages of being reasonable in design, complete in function, easy to produce, convenient and fast to operate, capable of achieving mobile nearby battery replacement, convenient in battery energy supplement circulation and high in efficiency, and therefore a lot of convenience is provided for users.

The invention discloses an electric vehicle charging scheduling method based on mean field multi-agent reinforcement learning. Charging scheduling is carried out on a mobile charging station and an electric vehicle in a large-scale mobile charging scene at the same time. A charging scheduling problem is modeled as a partially observable Markov decision process, a mobile charging station and an electric vehicle serve as two different intelligent agents, a reinforcement learning scheduling network is trained respectively to recommend a scheduling position, and meanwhile, the average field theory is utilized to simplify the mutual influence between the intelligent agents; the trained scheduling network is distributed to the mobile charging station and the electric vehicle, so that the mobile charging station and the electric vehicle can quickly make a scheduling decision only by obtaining local observation, and complete distributed charging scheduling is realized. According to the scheduling method, the dynamically changing charging demand is met, the charging income of the mobile charging station is obviously increased, and the successful charging proportion of the electric vehicle is effectively improved.

An air mobile charging robot system of a full-automatic plugging gun comprises a charging robot, an air track, a power supply circuit, a robot fixing module and a control unit, and the charging robot comprises a charging robot body, a charging module, a mechanical arm, a charging gun cable, a charging gun, a walking module, a power taking module and a positioning guide module. The utility model relates to the field of new energy vehicle charging, a charging robot can move along a track path of an aerial track and provide a mobile charging service of charging while parking for an electric vehicle on any parking space below the track, and the whole charging process including gun insertion and gun pulling is full-automatic, so that the charging efficiency is greatly improved. After the charging robot is in place, the charging robot can automatically insert the gun to start charging, and after charging is completed or a user finishes charging, the charging gun can be automatically pulled out and automatically withdrawn to the initial state, so that the charging robot can continue to move to other parking spaces to provide charging service for other vehicles, and the charging resource utilization rate and the charging operation efficiency are greatly improved; and the user charging experience is improved.

1. The name of the design product: rotating wireless charger (R10). 2. The use of the design product: for charging mobile phones. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The invention discloses a mobile energy storage charging system and a control method thereof, and relates to the technical field of automobile charging, and the method comprises the steps: collecting a pull-in time period corresponding to a historical charging record, and determining a peak time period according to the historical charging record condition of the pull-in time period; calculating the waiting duration ratio of the historical charging record, determining the waiting level of the historical charging record, calculating the waiting score of the peak period, and determining the feature level corresponding to the peak period; screening a characteristic time period, calculating an average operation score of the characteristic time period, and drawing an operation curve graph of the mobile charging system; and drawing a real-time operation curve graph of the mobile charging system, calculating a real-time optimization period of the mobile charging system by combining the real-time operation curve graph with the operation curve graph, and judging an optimization state of the mobile charging system according to the real-time optimization period, so that the overall operation efficiency of the system is improved.

The invention relates to the related technical field of charging equipment control, in particular to a mobile charging equipment path navigation method and system based on an intelligent sensor, and the method comprises the steps: synchronous sensor electric quantity information alignment, to-be-charged sensor screening, initial path setting of a navigation map, priority score setting, navigation instruction obtaining through multi-target optimization, and charging after equipment arrives. The technical problems that an effective mechanism for dynamically adjusting path planning is lacked, so that mobile charging equipment is difficult to flexibly cope with environment changes and the charging efficiency of the sensor is limited are solved, the multi-dimensional electric quantity information of the sensor is synchronously processed, alignment and screening are carried out, the data set of the sensor to be charged can be quickly and accurately determined, and the charging efficiency of the sensor is improved. The navigation map is constructed by combining the road network and the obstacle information, and the charging priority is determined by taking the residual electric quantity percentage and the predicted power-off time as evaluation indexes, so that the technical effects of optimizing the charging resource distribution, carrying out path planning multi-objective optimization balance and improving the charging task execution efficiency are achieved.

The invention relates to a charging temperature control method and system for a mobile phone charger. The charging temperature control method comprises the following steps: periodically outputting a test signal to a connected charging data line at each charging output port of a mobile phone charger, and collecting voltage response data and current response data of the ports in real time; calculating an impedance spectrum of the port according to the collected voltage response data and current response data; the impedance spectrum is analyzed, abnormal deviation in the impedance spectrum is recognized, the abnormal deviation is quantized into a connection quality deviation value, and the connection quality deviation value is related to the charging temperature; and when the connection quality deviation value exceeds a preset threshold value, starting an adaptive compensation mechanism to adjust the electric energy output of the port. Therefore, the problems of local overheating and element performance degradation caused by connection quality problems in the prior art can be effectively solved, and the safety and stability of the charger are improved.

The invention discloses a mobile charging pile control system based on artificial intelligence, and relates to the technical field of intelligent charging, and the system constructs a real-time power grid load state diagram, combines the operation state data of a fast charging station and power grid sensing information, dynamically models the power grid load distribution and transmission capability, and improves the power grid load distribution and transmission capability. A Gaussian function is introduced into the state diagram to quantify the influence of the fast charging station on the node load, and a traditional power transmission capability model is improved, so that the power grid state expression is more intuitive; a load state diagram is processed through a graph neural network GNN, spatio-temporal evolution characteristics of a load are captured, a load change trend and a regulation level of each node in a future short time period are predicted, a multi-target optimization algorithm is adopted to formulate a preliminary regulation strategy based on a load prediction diagram, and the purposes of relieving a peak-valley difference, reducing energy loss and improving the service capability of a fast charging station are achieved. And an optimization problem is solved through a genetic algorithm, so that the globality and effectiveness of a regulation and control strategy are guaranteed.