12results about How to "Reduce charging costs" patented technology

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 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.

This invention belongs to the field of power technology, specifically disclosing a method, device, equipment, and medium for autonomous charging and navigation of unmanned aerial vehicles (UAVs). It includes the following steps: scanning environmental information to obtain LiDAR data; identifying charging station landmarks from the LiDAR data and establishing a coordinate system; processing the coordinate system using the ICP method to obtain pose gain; acquiring the odometer information corresponding to the pose gain; fusing the odometer information and pose gain using the extended Kalman filter method to obtain an estimated pose; and using the estimated pose as input for a PID control method to complete navigation. This invention, by applying landmark recognition and positioning navigation technology, replaces the traditional manual charging method, greatly reducing the need for human resources, lowering UAV charging costs, and improving charging efficiency.

This application relates to the field of battery thermal management technology, and particularly to a method, device, vehicle, storage medium, and product for heating control of a power battery. The method includes: acquiring the current temperature, target state of charge (SOC), and initial SOC of the power battery during charging; determining the target temperature of the power battery based on the initial SOC and target SOC; calculating the temperature difference between the current temperature and the target temperature; and controlling the heating action of the power battery based on the temperature difference. This solves the problems of excessive energy consumption and increased costs in thermal management due to super-fast charging in new energy vehicle charging technology.

The invention provides a charging control method and charging equipment. The charging control method provided by the invention comprises the following steps: when request charging information is received, sending a charging strategy request to cloud equipment according to the request charging information; determining reference charging power of the charging equipment based on a charging strategy fed back by the cloud equipment; acquiring actual grid-connected power between the alternating-current bus and the power grid and actual charging power of the charging equipment through the intelligent electric meter; determining redundant power according to the actual grid-connected power and the actual charging power; determining target charging power of the charging equipment according to the reference charging power and the redundant power; and generating a control signal according to the target charging power and sending the control signal to the charging equipment, wherein the control signal is used for adjusting the actual charging power of the charging equipment. According to the charging control method provided by the invention, the charging cost can be better reduced while the charging requirement of a user is met.

The utility model discloses a kind of multifunctional wireless charging equipment, comprising: top seat, with first charging contact surface;Base, inside is equipped with cavity, second charging contact surface is equipped in cavity, and cavity has opening on base, opening is equipped with the cavity door of movable connection, third charging contact surface is equipped on cavity door;The present application can realize three electronic devices charging simultaneously on the same equipment, for example, place mobile phone on top seat, receive wireless earphone in cavity, and unfold cavity door to support smart watch.Three charging areas do not interfere with each other and have high space utilization, effectively solve the defect that traditional equipment charging surface is single, significantly improve use efficiency and reduce the charging cost of multiple equipment users.

This invention proposes a two-stage optimization method for distribution networks integrating electric vehicles (EVs) and distributed generation. In the first stage, an orderly scheduling of EVs is achieved by establishing a user participation dispatch probability model and a dynamic electricity price model considering load. The optimized EV load is then superimposed onto the distribution network reconfiguration optimization model in the second stage. Finally, network reconfiguration and distributed generation output are used to reduce network losses and node voltage deviations across the entire distribution network. The proposed method reduces peak-to-valley load differences. Considering user participation rates, it not only reduces user charging costs but also improves node voltage levels and reduces network losses.

The application discloses an inland port electric transfer vehicle charging scheduling method, comprising the following steps: constructing a transfer vehicle task matching model with the purpose of maximizing the utilization rate of the transfer vehicle and completing all transfer tasks; constructing a transfer vehicle charging scheduling model with the purpose of minimizing the delay, maximizing the transfer vehicle efficiency and minimizing the charging cost; constructing an energy-traffic collaborative scheduling model through the transfer vehicle task matching model and the transfer vehicle charging scheduling model; taking the transfer task and the initial state of all transfer vehicles as the input of the energy-traffic collaborative scheduling model, solving the energy-traffic collaborative scheduling model with the input of the transfer task and the initial state of all transfer vehicles through a deep Q network algorithm, and generating an optimal energy-traffic collaborative scheduling scheme; and scheduling the transfer vehicle through the optimal energy-traffic collaborative scheduling scheme to complete the transfer task of the port. The application can improve the overall transportation efficiency of the port and reduce the transportation cost.

This application relates to the field of automatic control technology, and provides a charging method, system, device, and storage medium based on self-propelled charging devices. The method includes: a server responding to a user order sent by a user; determining the target service area where the vehicle to be charged is located based on the charging location information in the user order; determining whether there is an idle self-propelled charging device within the target service area; and, if an idle self-propelled charging device exists within the target service area, generating a movement command based on the charging location information and sending the movement command to the target idle self-propelled charging device. Because a movement command can be generated based on the charging location information and sent to an idle self-propelled charging device within the target service area upon receiving a user order, and the self-propelled charging device can move autonomously within the target service area, the power delivery process can be automated, thereby saving on the costs of delivery personnel and distribution vehicles, and ultimately reducing charging costs.