108results about How to "Reduce charging costs" patented technology

The invention discloses a slow charging and quick discharging method of a storage and charging integrated charging pile. Comprising the following steps: S1, predicting the charging demand of the electric vehicle through obtained power grid load data, energy storage system state information and other external factors; s2, predicting the state of the energy storage system through the acquired information such as the charge state, the temperature condition and the health degree of the battery; s3, constructing a slow-charging and quick-discharging scheduling strategy based on the prediction result of the charging demand of the electric vehicle and the prediction result of the state of the energy storage system in combination with factors such as an electricity price policy and battery life; and S4, monitoring the load condition of the power grid, the use condition of the charging pile and the state information of the energy storage system in real time, and optimizing and adjusting the scheduling strategy of slow charging and quick discharging. By optimizing the charging and discharging processes, efficient utilization of energy, stability of the power grid load and prolonging of the service life of the battery are achieved, and the charging and discharging strategies can be flexibly adjusted according to the power grid load and electricity price changes.

The invention discloses a new energy charging pile charging control method and system, and relates to the technical field of new energy, and the method comprises the steps: collecting user historical charging data, power grid load data, fixed electricity price information and weather forecast data in real time, and recognizing user charging habits and demands; generating a personalized charging scheduling strategy according to the charging habit of the user and the real-time power grid state; the availability of various energy sources is monitored in real time, the generating capacity and the cost of each energy source are evaluated, the priority of energy source selection is adjusted by using a personalized charging scheduling strategy, and an optimal charging mode is automatically selected; executing charging operation based on the charging mode selected by the user, and performing adjustment according to the power grid load and the energy consumption condition; the availability of various energy sources is monitored in real time, the generating capacity and the cost are evaluated, and the priority of the energy sources is dynamically adjusted, so that the response capability of the charging pile to environment change is improved, the charging cost of a user can be reduced, and renewable energy sources are fully utilized.

The invention relates to the technical field of traffic energy management, in particular to a traffic energy intelligent fusion management system and method based on artificial intelligence. According to the calculated coincidence degree and the function value of each charging area, the alternative charging areas selected by recommendation are output, allocation can be carried out according to the mobility of the electric vehicles, and the peak load of the power distribution network is reduced; furthermore, the standby power utilization demand of the target vehicle is analyzed and calculated, the recommended charging duration of the target vehicle is calculated according to the standby power utilization demand and is pushed to the user side, the charging duration of the vehicle can be planned, the coincidence duration between the charging duration of the vehicle and the power utilization peak time period is shortened, and the charging efficiency of the vehicle is improved. Therefore, the load scheduling of the power distribution network can be realized, the charging cost of a user can be reduced, the charging duration can be reduced in a peak period, the charging duration can be increased in a low peak period, and the charging cost is reduced.

The invention relates to the technical field of intelligent scheduling of bus real-time data, in particular to an intelligent scheduling optimization system based on bus real-time data and a control method thereof, comprising a data acquisition module, a regional scheduling module, a charging strategy module, an intelligent optimization module, a communication module and a display and control module; the data acquisition module is used for acquiring operation data of the electric bus in real time, including position, speed, battery remaining capacity, current passenger number and environment information; according to the system, the running route and the charging plan of the buses can be dynamically adjusted, the operation efficiency of the electric bus fleet is improved, the charging strategy module combines the battery electric quantity, the endurance mileage prediction and the charging station load, the charging process is optimized, the charging efficiency is improved, and the charging efficiency of the electric bus fleet is improved. And the intelligent optimization module considers a battery life optimization strategy, and the service life of the battery is prolonged by reasonably scheduling the charging time and power.

The invention discloses an intelligent charging management system and method based on edge computing, and relates to the field of edge computation.The method comprises the steps that 1, an edge computing node module is arranged, the edge computing node module comprises a data acquisition unit and a data processing unit, data of a charging pile is acquired based on the data acquisition unit and the data processing unit, and the data of the charging pile is acquired; by introducing an edge computing node, computing and control part data of the charging pile are moved to the local; step 2, the edge computing node module uploads the collected data to a central control platform; 3, the central control platform receives and processes the data uploaded by the edge computing node, and based on the reservation time of the user, the current power grid load and the real-time electricity price, cyclic charging optimization scheduling is carried out in a cyclic iteration mode; and 4, after the edge computing node detects that charging is completed or the target electric quantity set by the user is reached, charging is automatically cut off, a charging record is uploaded to the central control platform, and long-term data analysis and strategy optimization are carried out.

The invention discloses an optimal scheduling method, system and device for a new energy charging station and a medium, and relates to the technical field of charging pile scheduling optimization, and the method comprises the following steps: setting a vehicle data collection end at an entrance of the charging station, and collecting the real-time data of a vehicle; obtaining the charging power of a vehicle battery based on the vehicle real-time data; the fluctuation index of the idle charging pile is analyzed; based on the fluctuation index of the idle charging pile and the real-time data of the vehicle, the optimal idle charging pile is matched for the vehicle or different charging strategies are adopted; the vehicle is guided to the corresponding charging pile for charging through the guiding indicating lamp; the method is used for solving the problems that the deviation between the charging duration of the vehicle and expectation is large and the service life of a battery pack of the vehicle is shortened due to the fact that the stability of the charging pile is not considered sufficiently in an existing charging pile dispatching optimization technology.

The EV charging and discharging optimization method considering user will and battery loss comprises the steps that a V2G model is constructed according to driving characteristics and user habits of an EV owner, subjective factors and objective factors influencing decision making of an electric vehicle user are analyzed, and modeling is carried out; the method comprises the following steps: adding discharge income and battery loss cost into comprehensive charging cost, and firstly, carrying out modeling quantification on the battery loss cost based on temperature and discharge depth; secondly, analyzing a three-dimensional relationship among the temperature, the discharge depth and the battery life, and finally, considering seasonal characteristics of temperature loss; and adding dynamic adjustment of user willingness and loss seasonal characteristics in an optimization strategy, constructing a typical scene, and optimizing the comprehensive charging cost of the user side and the peak-valley difference of the power grid side by using a dung beetle algorithm. According to the optimization method, charging and discharging behaviors are optimized by introducing user willingness, and the user satisfaction is improved; battery loss is considered, battery life is prolonged, and maintenance cost is reduced; in combination with seasonal characteristics, the overall efficiency of the system is improved, and stable operation is ensured.

The invention relates to the technical field of electric vehicle charging and discharging regulation and control, in particular to a large-scale electric vehicle charging and discharging rate multi-level optimization regulation and control method. Establishing a daily driving mileage prediction model by analyzing historical driving and charging data of the electric vehicle, and calculating a charging demand of the daily driving mileage according to the daily driving mileage prediction model; designing an optimization model based on linear programming based on the determined charging demand, and obtaining reasonable charging power of each electric vehicle in different time periods; on the basis of the determined charging demand, constructing a multi-level optimization model; under the guidance of the constructed multi-objective optimization model, a specific charging and discharging strategy of each electric vehicle is refined by adopting a heuristic algorithm; the charging power is dynamically adjusted by combining real-time data of the electric vehicle and the power grid; and based on the dynamic adjustment result, the charging power of different levels is coordinated, and multi-level cooperative control is realized. According to the large-scale electric vehicle charging and discharging rate multi-level optimization regulation and control method, efficient and stable operation of a charging system is achieved.

The invention discloses a charging control method of a two-wheeled vehicle shared charging pile and a charging pile, and relates to the technical field of shared charging piles, and the method comprises the following steps: obtaining various parameter information generated by the two-wheeled vehicle shared charging pile in the process of charging a two-wheeled vehicle, the parameter information including energy management information and system compatibility information; the charging process of the two-wheeled vehicle shared charging pile is intelligently monitored, the charging hidden danger index is generated in time, the high-risk state is effectively recognized, especially, early warning is rapidly given out under the non-accidental condition, workers are reminded of inspection, battery overheating, expansion or explosion is prevented, and the safety of users and the environment is guaranteed. In addition, by analyzing energy management and system compatibility information, an energy conversion efficiency index and a charging adaptability index are generated, and it is ensured that the charging pile intelligently matches different electric vehicle requirements. Through the optimization, the utilization rate of electric energy is improved, the charging cost is reduced, data support is provided for subsequent maintenance, and the management efficiency and the service reliability are enhanced.

The invention discloses an electric quantity dynamic early warning system and method for a mobile storage and charging robot, and the system comprises an electric quantity prediction module which is used for obtaining the consumed electric quantity of a standby robot through a constructed electric quantity consumption prediction model, and calculating the predicted output electric quantity of the standby robot; the task management module is used for acquiring order information and performing task allocation according to the required electricity consumption of the order information and the predicted output electricity quantity of the standby robot; the dynamic early warning module is used for judging whether charging early warning needs to be started or not according to the constructed order prediction model and the predicted output electric quantity extreme value of the standby robot; if yes, charging early warning is started, and the standby robot is charged according to the charging early warning; and if not, closing the charging early warning, and charging the standby robot in the valley price time period. The invention relates to the technical field of new energy storage and charging, and solves the technical problems that in an electric quantity early warning system of an existing mobile storage and charging robot, an early warning mechanism is not intelligent, and a charging management method is single.

The invention discloses a control method of a photovoltaic energy storage system and the photovoltaic energy storage system. The method comprises the following steps: acquiring the generating capacity and power consumption of the photovoltaic energy storage system; when the generating capacity is greater than or equal to the power consumption, controlling the photovoltaic energy storage system to supply power or charge on the grid according to the relationship between the on-grid electricity price and the trough electricity price; and when the generating capacity is less than the power consumption, controlling the photovoltaic energy storage system to discharge, or controlling the photovoltaic energy storage system to charge according to the SOC value of the energy storage module or the predicted generating capacity of the photovoltaic energy storage system based on the relationship between the grid-connected electricity price and the trough electricity price. According to the technical scheme provided by the embodiment of the invention, on the basis of the generating capacity and the power consumption of the photovoltaic energy storage system, the utilization rate and the flexibility of photovoltaic energy are effectively improved by combining the SOC value and the predicted generating capacity of the energy storage module through the relationship between the on-grid electricity price and the trough electricity price, and the yield of photovoltaic storage and charging is improved.

The invention relates to the technical field of charging piles, and discloses a full-matrix intelligent output integrated charging pile which comprises a cabinet body and a cabinet door on one side of one end of the cabinet body, and further comprises a touch screen arranged on the top of one end of the cabinet door and a first charging gun arranged on one side of the cabinet body. And the second charging gun is arranged on one side, far away from the first charging gun, of the cabinet body. According to the full-matrix intelligent output integrated charging pile, the power distribution unit calls any number of modules according to instructions of the controller and requirements of different vehicle powers, the power output granularity of the first charging gun or the second charging gun can be the power of a single module, and each charging module corresponds to one power distribution plate; each power distribution board can correspond to the first charging gun or the second charging gun, and after the multiple power distribution boards are gathered, the high-power connectors, the power distribution boards and the high-power connectors are directly connected with the diodes, so that the current of a vehicle battery can be prevented from flowing backwards.

The present invention discloses a health status prediction and analysis method and system based on a charging pile, which relates to the technical field of charging pile management, including extracting data from a database system based on a central processing unit to obtain historical operation data of the charging pile; and obtaining complete historical operation data of the charging pile. The present invention determines whether the state of the charging pile is a healthy state by judging the temperature deviation of the charging pile, the charging deviation of the charging pile, and the factory parameter information of the charging pile. In addition, the state of the healthy charging pile is predicted to determine within what time the state of the healthy charging pile will become sub-healthy, and the state of the charging pile is monitored to avoid damage to the internal electronic components of the charging pile due to excessive temperature increase, thereby increasing the service life of the charging pile. Moreover, the charging rate of the charging pile is monitored to avoid the charging time of the charging pile being too long, resulting in abnormal energy loss, and reducing the charging cost.

The invention discloses a day-ahead-day multi-time scale electric vehicle cluster division strategy based on different charging completion times of electric vehicles. According to the method, modeling is carried out through historical travel statistical data, and the moment when the electric vehicles are connected to the network and the moment when the electric vehicles are disconnected from the network are determined; aiming at each scheduling period, considering constraints of a power grid, a vehicle owner, an electric vehicle battery and the like, solving a charging and discharging plan by two layers of strategies, and determining the total charging and discharging power of a cluster in a current time period by taking the minimum load change curve of a power distribution network in a scheduling interval as a target in the upper strategy; the lower-layer strategy takes the lowest cost of an electric vehicle owner as a target, finds a charging and discharging plan of a single electric vehicle, and introduces a scheduling penalty factor to adjust the difference with a cluster charging and discharging plan; according to the method, the load fluctuation can be effectively smoothed, the optimal real-time scheduling difficulty of the large-scale electric vehicle is remarkably reduced, and a better optimization effect and a higher solving speed are achieved for processing the access problem of the large-scale electric vehicle.

The invention relates to the field of electric bicycle charging equipment, and discloses an electric bicycle charging pile, which comprises a charging main body provided with a plurality of independent charging interfaces, and each interface can detect and identify the battery type and the battery state of a connected electric bicycle; the control module is connected with the charging interface and used for automatically adjusting charging voltage and current according to the detected battery type and state, and the control module can be dynamically switched between a constant-current charging mode and a constant-voltage charging mode based on the current electric quantity level and the battery voltage of the battery of the electric bicycle. Through the combination of the communication module and the control module, a user can remotely set the starting time and the ending time of charging, and can flexibly arrange the charging time according to actual demands, particularly, charging is carried out in a time period with a low electricity price, so that the charging cost is effectively reduced, meanwhile, overcharging is avoided through intelligent control, and the user experience is improved. And the service life of the battery is prolonged.

The invention discloses an electricity consumption control method and system based on time-of-use electricity price and peak load shifting, and belongs to the technical field of photovoltaic measurement. The method comprises the following steps: collecting power consumption data and power generation data of a target area within a preset time; constructing a power market influence model based on the power utilization data, the power generation data, the time-of-use electricity price and a peak load shifting strategy; and solving the electricity market influence model to obtain an electricity consumption minimization strategy, and controlling the electricity consumption of the target area based on the electricity consumption minimization strategy. The application of the invention reduces the charging cost of a user, and gives full play to the flexible adjustment and support capability of photovoltaic power generation to a power grid.

The invention provides a mobile and fixed hybrid charging scheduling method and system, and a storage medium. The method comprises the steps of obtaining a charging request of at least one target vehicle; a space-time distribution model of a hybrid charging station is constructed according to the charging request, the hybrid charging station comprises a fixed charging pile FCP and a mobile charging pile MCV, and the total cost of the same target vehicle in the mobile charging mode and the total cost of the same target vehicle in the fixed charging mode are obtained according to the space-time distribution model; generating a target vehicle charging selection scheme based on a principle of lowest target vehicle charging cost; and if the target vehicle charging selection scheme is a mobile charging mode, constructing a target function by taking the minimum total operation cost of the hybrid charging station as an optimization target, and solving the target function to obtain an optimal scheduling scheme for selecting the mobile charging mode in the next day. According to the invention, the most economical charging selection scheme can be pushed to the customer, so that the user cost can be reduced, and the optimal scheduling of the MCV can be completed under the condition of selecting the mobile charging mode.

The invention discloses an electric vehicle ordered charging and discharging control method based on an improved differential evolution algorithm. The method comprises the following steps: constructing a probability model of an electric vehicle charging behavior through a Monte Carlo method; demand analysis and electric vehicle dispatching feasibility judgment are carried out by acquiring power grid information and charging electric vehicle information; considering the power grid operation safety risk and the user credit rating, and formulating a dynamic electricity price; establishing a charging and discharging control model by taking minimization of the comprehensive cost of the user and the construction cost of the power grid as a target; and an improved differential evolution algorithm is adopted to solve the model to obtain the optimal electricity price and the optimal charging and discharging strategy, so that the operation efficiency and the economical efficiency of the power system are improved. The method effectively overcomes the defects of flexibility and cost of an existing electricity price strategy and the defects of dynamic electricity price making in the aspect of user credit, can effectively cope with power grid load fluctuation, and promotes coordinated development of the electric vehicle and the power grid.

The invention provides an alternating current charging and discharging system of a vehicle and an alternating current charging and discharging control method. The system comprises a plurality of first windings of a first motor of an electric drive system, a plurality of first inverters of the electric drive system, a direct current bus, an active front end rectifier and a controller. The first windings are correspondingly connected with the first inverters respectively; the plurality of first inverters are connected in parallel to the direct-current bus, and a first isolating switch is arranged on the direct-current bus between two adjacent first inverters; one end of the direct-current bus is connected to a battery of the vehicle, and the other end of the direct-current bus is connected to the active front-end rectifier; the controller is configured to control opening and closing of the first isolation switch, when the first isolation switch is controlled to be closed, the first motor outputs torque, when the first isolation switch is controlled to be disconnected, the multiple first windings and the multiple first inverters achieve DC / DC energy transmission and electrical insulation isolation of alternating current charging and discharging, and after the first isolation switch is controlled to be disconnected, the multiple second windings and the multiple first inverters achieve DC / DC energy transmission and electrical insulation isolation of alternating current charging and discharging. And controlling the bridge arm end of the first inverter to generate high-frequency pulse voltage.

The invention relates to the technical field of intelligent scheduling, in particular to a new energy charging pile intelligent scheduling system based on big data, and the system comprises an information collection module which is used for obtaining the scheduling period of a charging pile, and collecting the charging amount, power consumption and charging time of the charging pile in each scheduling period; the scheduling identification module is used for identifying a scheduling target and a scheduling price in each scheduling period and checking power consumption distribution in each scheduling period to obtain a consumption evaluation factor; the scheduling adjustment module is used for acquiring a plurality of excitation clusters corresponding to the scheduling targets according to the scheduling targets and the scheduling prices in each scheduling period; each incentive cluster comprises a scheduling target, a scheduling pricing and an incentive effect; clustering the plurality of excitation clusters according to scheduling pricing to obtain excitation factors in each scheduling period, and determining a target set of charging pile scheduling according to the obtained excitation factors; the utilization rate and efficiency of the charging pile are improved, and intelligent scheduling of the charging pile is realized.

The present invention provides an intelligent dispatching method and system for a photovoltaic storage and charging microgrid system, which relates to the technical field of power dispatching, including: obtaining the current photovoltaic installed capacity, the current energy storage installed capacity and the corresponding current collection time, the current weather data and the current electricity price to form a first eigenvector; according to the current photovoltaic power generation power sequence of the park, the current charging power sequence of the charging pile system and the current load power sequence of the remaining loads in the park, respectively predicting the predicted photovoltaic power generation power, the predicted charging power and the predicted load power corresponding to the future time period to form a second eigenvector; inputting the first eigenvector and the second eigenvector into an intelligent dispatching model trained under the goal of maximizing the electricity consumption income of the park and a corresponding constraint condition to predict the predicted energy storage capacity of the energy storage system. Comprehensively considering multiple characteristic indicators, the prediction accuracy is improved, and the stability and economy of the photovoltaic storage and charging microgrid system are effectively improved.

The invention provides a wind turbine generator backup power supply system, which comprises a wind turbine generator main controller and a wind turbine generator cabin system load device, and the wind turbine generator main controller is in communication connection with the wind turbine generator cabin system load device; the back-up power supply module is electrically connected with the wind turbine generator cabin system load equipment, the back-up power supply module comprises a storage battery pack and a back-up power supply controller, and the back-up power supply module is in electric signal connection with the back-up power supply controller; and the miniature wind power generation system is electrically connected with the back-up power supply module, the miniature wind power generation system comprises a miniature fan and a miniature fan controller, and the miniature fan is in electric signal connection with the miniature fan controller. The technical problems that in the prior art, an existing wind power plant back-up power source mostly adopts a diesel generator to supply power, regular maintenance and fuel oil supply are needed, and inconvenience is particularly inconvenient in remote areas or severe weather are solved.

The embodiment of the invention provides a charging control method, device and equipment for an electric forklift. The method comprises the following steps: acquiring historical charging data of the electric forklift in a historical time period; processing the historical charging data and a preset peak-valley electricity price database based on a time sequence prediction model to obtain suggested charging time of a future time period; wherein the time sequence prediction model is obtained by training an initial neural network model through historical charging training data and a preset peak-valley electricity price database; the preset peak-valley electricity price database represents electricity price differences in different time periods; the historical charging data, the suggested charging time and a preset peak and valley electricity price database are processed based on a semantic model, and a charging control mode of the electric forklift is generated; based on the charging control mode, the electric forklift is controlled to be charged; wherein the charging control mode indicates the charging time period of the electric forklift. The method is used for achieving the effect of charging the electric forklift economically and efficiently.

The application discloses a kind of considering user false information's electric vehicle space-time scheduling optimization method and system, belong to electric vehicle optimization scheduling field.Scheduling center needs to minimize overall charging cost under the charging demand constraint of satisfying all electric vehicles, user once lies report demand, possibly will reduce own charging cost, but the charging cost of other electric vehicle users will rise, leading to the rise of total cost, to solve this problem, based on the space-time two-dimensional electric vehicle optimization scheduling framework, a new charging cost billing mechanism is designed, considering the influence of the charging strategy reported by user on optimization scheduling result, so that individual charging cost minimization and overall charging cost minimization tend to consistency.Not only reduce the charging cost of each user after participating in scheduling, but also avoid the phenomenon that user chooses to report false information to gain profit when participating in scheduling, better encourage user to participate in scheduling, improve optimization effect.

The application provides a kind of based on double-layer optimization model electric vehicle participates in power grid frequency modulation determination method and system, it is related to smart grid and electric vehicle technical field.The method comprises: based on the historical charging cost data of electric vehicle and the historical subsidy income data of participating in power grid frequency modulation, establishes first layer optimization model, determines the comprehensive income value of to be evaluated object, based on the time-of-use electricity price introduced random noise, the charging probability of to be evaluated object in different period is calculated, further determines the frequency modulation willingness evaluation value of to be evaluated object;Power distribution network frequency fluctuation model is constructed to be used to establish second layer optimization model, to quantify the evaluation based on the total load of power grid caused by to be evaluated object power grid fluctuation amount;According to optimization strategy, first layer optimization model and second layer optimization model are double-layer iteration optimization, and the frequency modulation participation evaluation value after optimization is obtained, to determine the frequency modulation participation evaluation value of to be evaluated object.The application realizes the charging cost of user side is lower while improving the stability of power grid.

The invention discloses a flexible charging method, platform and system based on a communication base station. The method comprises the following steps: firstly, acquiring flexible surplus energy capacity of a communication base station in a preset range; acquiring a charging demand of the electric vehicle; then flexibly matching the charging demand of the electric vehicle with the surplus energy capacity of the communication base station to obtain a charging strategy; then, when the electric vehicle is connected to the communication base station to be charged, charging control is conducted on the electric vehicle based on the charging strategy; calculating the charging cost; and finally, after charging of the electric vehicle is finished, the charging cost is displayed for payment of a user, and flexible charging based on the communication base station is completed. According to the method, the charging current can be adjusted at any time according to changes of communication services, environment conditions and the like, the power supply safety of main services of the communication base station can be ensured, existing communication infrastructures can be flexibly integrated, comprehensive coverage and marketization selection are achieved, and the overall charging economical efficiency and convenience are improved.

The invention discloses an intelligent power dispatching unit and an intelligent power dispatching system thereof, and belongs to the crossing field of intelligent power grids, new energy storage and traffic infrastructures. The intelligent power dispatching unit comprises m charging piles, an energy storage system and a relay array; the relay array is arranged between the charging pile and the energy storage system and is used for power dispatching and coupling of the charging pile and the energy storage system; the energy storage system comprises n DC / DC chargers; the number of relays in the relay array is m (m + 3) / 2 + n, m is an integer greater than or equal to 2, n is an integer greater than or equal to 2, and m is an integral multiple of n. A plurality of charging piles are combined with an energy storage system and a related detection control system to form an intelligent power dispatching unit, so that the purposes of flexibly dispatching charging power, relieving peak electricity consumption pressure, charging an energy storage battery by utilizing photovoltaic or electricity price valley sections and reducing charging cost are achieved.

The utility model relates to a take-up track transfer type pile line split air mobile charging robot system, which comprises an air track, a walking module, a movable charger, a winding gun line module, a charger side butt joint module, a winding side butt joint module, a power taking module, a charging call response system and a control processing unit, the movable charger can move along the aerial track and change the track and steer under the driving of the walking module, a winding gun line module is arranged beside each parking space, the movable charger can achieve the purpose that any parking space can be in electrical butt joint with the winding gun line module, and therefore the charging service can be provided for an electric automobile below the movable charger. The utility model relates to the field of new energy vehicle charging, eliminates the one-to-one binding relationship between a movable charger and a charging gun line, greatly improves the utilization rate of charging resources, supports reservation charging and queuing charging, can take back the charging gun line after a user pulls out a gun, and is more convenient, more efficient, cleaner and safer.

The utility model belongs to the technical field of charging piles, and particularly relates to a solar charging device which comprises an energy storage box body, a wire inlet is formed in one side of the bottom end of the energy storage box body, a wire outlet is formed in one side of the top end of the energy storage box body corresponding to the wire inlet, and a hollow supporting frame is welded to the position, close to the wire outlet, of the top end of the energy storage box body. A slow charging pile is mounted at the top of one end of the hollow supporting frame, n-shaped supporting plates are symmetrically welded to the top end of the hollow supporting frame, a fixing frame is mounted at the top ends of the two n-shaped supporting plates, and a solar panel is mounted in the fixing frame. Through cooperative use of the charging controller and the lithium battery, electric energy converted by the solar panel can be stored, and through use of the inverter, the stored electric energy can be provided for the slow charging pile to enable the slow charging pile to charge a vehicle, so that the charging cost of the electric vehicle can be reduced, and the slow charging pile is convenient to use.

The utility model relates to the technical field of automobile awning, in particular to an automatic telescopic awning for a parking space, which comprises a bottom rod, a vertical rod on the bottom rod is connected with an arc-shaped top rod, a sliding seat on the top rod is slidably connected with a telescopic awning, the telescopic awning is connected with a linkage rod, and the top rod is rotatably connected with a driven belt matched with the linkage rod. The remote mobile client controls the control box to generate forward rotation or reverse rotation operation instructions to the gear motor, so that the driven belt drives the telescopic awning to slide on the sliding seat of the ejector rod, the telescopic awning extends out or retracts relative to the ceiling, the effect of automatically adjusting the conversion of the telescopic state of the awning is achieved, and convenience is brought to a user; the photovoltaic panel is arranged on the ceiling, the photovoltaic panel is electrically connected with the storage battery, the storage battery can charge the electric automobile after being subjected to voltage transformation through the transformer, solar energy is converted into electric energy to be used by a user, the electricity utilization cost of the user is saved, and the effects of energy conservation and environment protection are achieved.