119 results about "Charge model" patented technology

The invention discloses a modelling method for a surface potential basis intensive model of an III-V group HEMT (High Electron Mobility Transistor). The method comprises the following steps of firstly, establishing an intrinsic structure model and an extrinsic structure model of the III-V group HEMT, combining a physical structure and a behavior mechanism of a device to construct a topological structure, and then embedding the established models into a commercial EDA (Electronic Design Automation) tool; secondly, carrying out on-wafer testing on an actual depletion device to obtain various performance test data of the device; and lastly, verifying the intensive model. The model solves the problems that the existing current and charge equations of the device cannot integrate, the segment points are discontinuous and the equations cannot be used for nonlinear circuit simulation; through a method for solving a surface potential source equation to deduce model current and charge/capacitance equations, a physical problem for quantum effect processing and a numerical algorithm problem caused by simultaneous self-consistent solution of a classic carrier transport equation and a new effect in the existing physical model are solved; and furthermore, a computational formula for volume charge density is deducted again, so that a problem of difficulty in gluing in a charge model is solved.

The invention discloses a workflow application flexible resource supplying method in a cloud environment. A demand-based charging model based on a time interval, data transmission time, virtual machine starting time and software mounting (downloading) time are considered. The multi-rules based heuristic (MRH) method mainly includes the steps that A, deadlines of sub-tasks are divided, and the step A is mainly characterized in that through removing the constraint from the original problem that charging is performed according to the time interval, the original problem is simplified, then the integer planning model of the problem is solved, and therefore the deadlines of all the sub-tasks are obtained; B, according to a multi-rules based sub-task and virtual machine time slot matching method, the step B is mainly characterized in that three priority rules considering multiple factors are provided, and the tasks are matched with suitable virtual machine available time slots. Through the appropriate sub-task deadline division and the multi-rules based time slot matching method, the resource rent cost for a whole workflow application is greatly lowered.

The invention discloses a photovoltaic intelligent community electric automobile and controllable load two-stage optimization scheduling method. A controllable load output model is established based on residential area, controllable load use characteristics and laws of thermodynamics, an electric automobile charging model is established based on electric automobile user driving characteristics, and a photovoltaic probability model is established based on the condition that photovoltaic output forecast deviations meet normal distribution; in day-ahead scheduling, time-of-use electricity price is set with profit maximization of an operator obtained after orderly charging of electric automobiles being as a target, and the electric automobiles are guided to be charged orderly through the time-of-use electricity price to reduce system valley-peak difference; taking consideration of influence of photovoltaic prediction and temperature prediction deviation on intelligent community electric automobile and controllable load co-scheduling, supply and demand unbalance due to day-ahead predication is corrected by introducing real-time scheduling; and in real-time scheduling, with the time-of-use electricity price set in day-ahead scheduling being as a basis, a day-ahead charging scheme of the electric automobiles is optimized to reduce real-time scheduling cost and stabilize load fluctuation. The method comprises day-ahead scheduling and real-time scheduling two-stage optimization.

The invention discloses a directional charging base station deployment method of a wireless rechargeable sensor network. According to the wireless rechargeable sensor network adopted by the invention, N rechargeable sensors are randomly deployed in a two-dimensional plane; according to the adopted wireless charging model, a directional base station only can charge one sensor at a moment, through rotating the direction of a charging antenna, different sensors can be charged at different moments in a time period, and moreover, one sensor only can be charged by one directional base station. The specific steps are as follows: 1, solving a sensor set with feasible base stations; 2, solving a candidate base station set corresponding to the result set RFS of the sensor set; 3, calculating appearing frequencies of the sensors; and 4, selecting the base stations from the candidate base stations as few as possible. According to the method, through combination of the time divided charging models of the rotary directional charging base stations, the method conforms to the practical application scene well; and through adoption of two heuristic algorithms based on cupidity, the operation speeds of the algorithms are improved.

The invention relates to an electric vehicle battery swap station orderly charging control method. The electric vehicle battery swap station orderly charging control method comprises steps that a battery charged state level is discretized; an electric vehicle battery swap requirement is acquired; the orderly charging model of the battery swap station taking valley filling as a target is built, and the fitness function of the orderly charging control is determined by taking a deviation square sum of a load as an index; the optimal solution of the orderly charging control of the battery swap station is solved by adopting an improved cuckoo search algorithm according to the determined fitness function, and a battery charging schedule is determine for the battery swap station according to the solved optimal solution. By adopting the orderly charging and battery swap control method capable of facilitating operation of a power swap station manager, the number of the electric vehicles participating in battery swap service in each time period and the number of the swapped batteries participating in charging behaviors in each time period are acquired, and the orderly charging and battery swap scheduling of the battery swap station are realized, and therefore the daily operation of the power swap station is satisfied, and a function of filling a valley of a regional power grid is realized.

A method of online charging in a communication network. The method includes receiving a service request from a user, determining whether the service request is an access network session, a media network session or a service network session, determining if a type of charging model the user wants to use to provide the service request is an event based model, a volume based model, a time based model, an event based model or a combination of the models, determining which network element corresponding to the access network session, the media network session and the service network session in the communication network is responsible for providing the service request from the user, and provisioning identification rules for providing the service request to the network element that is determined to be responsible for providing the service request from the user. Further, the step of provisioning the identification rules comprises updating the rules when the access network session, the media network session and the service network session interact with each other in a charging transaction requested in the service request from the user.

The invention provides an entering and exiting exception handling method and an entering and exiting exception handling system based on a cloud parking platform, and a medium. The method comprises thefollowing steps: monitoring whether an entrance and an exit of an offline parking lot have exceptions in real time; if the entrance and the exit of the offline parking lot have exceptions, recordingvideo for the entrance and the exit of the offline parking lot, uploading the video for the entrance and the exit of the offline parking lot to a cloud monitoring end of the cloud parking platform inreal time, and thereby pushing the video to a central on-duty idle cloud agent; receiving operation instructions of the idle cloud agent through an entrance and exit operation screen of the cloud parking platform, and handling the entrance and exit exceptions of the offline parking lot according to the operation instructions, wherein the operation instructions are generated according to types of the exceptions of the offline parking lot. The method can perform real-time monitoring on the exceptions of the offline parking lot and handle the exceptions timely, avoid charging vulnerabilities which may be generated in the conventional charging mode, effectively reduce hardware and labor cost of the parking lot and realize optimized allocation of resources.

The invention discloses a method for forecasting and producing narrow hardenability strip steel by hardenability, mainly aiming at steel grade which has a hardenability requirement and evaluates tail-end quenching hardness by a Jominy value. The strip steel comprises pinion steel, hardened and tempered steel, spring steel and bearing steel. The invention combines a BP (back propagation) manual neural network model with an incremental algorithm, takes the component increment of chemical components to a reference furnace as input, takes end quenching value increment of Jominy tail-end quenching hardness to the reference furnace as output, and builds a hardenability forecast model based on an incremental neural network; according to the difference of the end quenching precast value and the end quenching target value of the neural network model, a component rule base gives the adjustment quantity of each element component, and the process of charging is carried out according to the alloy addition calculated by an alloy charging model so as to realize on-line fine tuning and narrow hardenability strip steel control of the chemical components in the molten steel refining process. The method in the invention can be used to produce the end quenching steel of which the hardenability bandwidth is 4HRC.

The invention relates to a soft floating body unit, a pipeline pole based on the floating body unit, a generating station and an air charging model. The floating body unit comprises a floating body and a supporting body, wherein the floating body is manufactured from soft airtight material; the floating body floats in water after being inflated; when the floating body is covered with water and suspended below water surface, at least part of the supporting body exposes and is kept above the water surface; the supporting body of the floating body unit pipeline pole is arranged to be a rigid supporting rod; a connector for mounting and connecting a pipeline is arranged at the upper end of the supporting rod; the floating body is fixed to the water bottom through an anchor chain or a cable; the floating generating station, the supporting column of the floating body unit or a floating body platform are provided with generating devices; the floating body unit air charging model and the supporting body are manufactured into air tightness structures through soft materials; after air charging, the air charging model with special shape can be formed. The floating body unit is high in strength, light in weight, small in cost, convenient for mass manufacturing and implementation, and provides a feasible solution for commercial development and utilization of ocean energy resources and resources.

The invention discloses a hybrid cloud charging method and system. The method comprises the following steps: acquiring bill data from hybrid cloud, wherein the hybrid cloud comprises public cloud and/or private cloud, and different clouds comprise the bill data in different forms; processing fields in the bill data as a way of cost model in a unified way, and storing in a database; wherein the cost model comprises an unique identifier, a manufacturer identifier, a region identifier, a resource type, a charge mode, a resource identifier, the cost, a charging timestamp, a resource usage department and the resource subordinated application identifier. The query efficiency is improved by unifying the bill data of different cloud manufacturers, the bill data of different cloud manufacturers areassociated with an internal system, so that the different query demands of different users are satisfied, the queried data is displayed in a pattern manner, a user interaction interface is friendlier, and the user experience is better.

The present invention discloses a system and method for counting Web-Services by means of a Resource-Counter Service offered as an own, independent Web-Service based on a SOAP communication protocol as well as a system and method for billing Web-Services using the result of the Resource-Counter Service for calculation of a charge. The Resource-Counter Service may be accessed by all Service-Provider having service description of the Resource-Counter Service. The service description for the Resource-Counter Service may be preferably created and published by the Service-Provider, categorized by the Service-Broker, and can be found and used to invoke the Resource-Counter Service by all Service-Provider using a charging model for their Web-Services. The Resource-Counter Service mainly provides the functionality to create all necessary data allowing calculation of the charge for the use of a Web-Service. The final calculation of the charge itself may be done by a separate specific accounting and bill presentment component.

The invention discloses an intelligent charging method for a centralized charging station in the technical field of power system. A technical scheme is as below: firstly, conducting classification treatment on a battery on the basis of state of charge of the battery at alternating current moment; secondly, based on a closed-loop supply chain theory, constructing a coordination model of a charging station and an alternating current point based on a forward supply chain; and constructing a coordination model of the alternating current point and a user, based on a reverse supply chain; and finally optimizing battery access charging in the station by using a constrained multi-objective integer differential evolution algorithm. The constrained multi-objective integer differential evolution algorithm takes full consideration of limit for battery charging at different access time, and introduces an initial optimizing upper bound method with variable weight; and because of the many constraints within a charging model, a dynamic constraint implementation method based on population information is introduced in. The method is suitable for various multi-objective integer optimization problems, and has good robustness, fast convergence speed and good global search ability.

The invention provides a general charge method with realization method for charge model, which comprises: the charge module reads the charge information for user business request from net element, and compares the service type number and the number on service-price matching table to find opposite price type number; the server loads the charge rule opposite to price type number and calculates business cost. When the charge rule changes, it just needs to modify, add or reduce charge rule, and said relation. This invention is fast and flexible.

The invention relates to an electric automobile public charging facility planning method, more specifically, relates to an electric automobile public charging facility planning method. According to the construction type difference and the characteristics of the electric automobile, the charging piles are divided into two types of high-power quick-charging piles and small-power slow-charging piles;the charging behavior characteristics of all types of electric automobiles are analyzed, an electric automobile charging model is adopted, the proportion of the charging time occupied by the public charging requirement and the self-charging requirement is distinguished, the total demand of all types of electric automobiles on the public charging amount is calculated, and through the combination of the charging capabilities of the quick/slow charging piles, the number of charging piles contained in an integrated charging station and the number of scattered charging piles, the total demand of an integrated city charging station and scattered public charging piles are calculated, and furthermore, the setting sites and quick/slow charging pile number of electric automobile public charging facilities are planned according to the actual construction conditions of the local public charging facilities and the principle of demand priority.

The invention provides a charging pile intelligent scheduling management method. The method comprises the following steps: S1, setting geographic position partitions; s2, establishing a charging pilemodel and an electric vehicle charging model; s3, acquiring charging request information of a user; s4, determining a geographic position subarea of the user and inquiring charging pile position information of all charging piles in the subarea; s5, calculating the consumed time and distance on the road; s6, adding a plurality of charging piles with the least time consumption on a fixed path into apriority queue; s7, calculating queuing waiting time; s8, calculating electric energy supplementing time; s9, calculating the total charging time consumption to form a first priority sequence; s10, calculating the charging cost of each charging pile to form a second priority sequence; and S11, pushing the position information of the charging pile and the total charging time consumption to the user. According to the intelligent scheduling management method for the charging pile, the charging pile model and the electric vehicle charging model are established, and the charging requirement of a user is met through an intelligent scheduling management strategy.

A system and method is provided to implement charging models for subscriber driven media agnostic content delivery across same or different networks. The method includes receiving content of a first media type over a network from a sending client. The method further includes sending the content or a reference to the content to a receiving client in a preferred media type and to a preferred device in accordance with at least one preference of the receiving client. The method also includes generating a billing record based on the content and user preferences of a sending client and/or a receiving client.

The invention discloses a charging load model establishment and node voltage calculation method of an electric vehicle. The method comprises: S1, establishing a load charging model of an electric vehicle; S2, establishing a dynamic load model of a power distribution system; S3, giving access points of all load charging models in the power distribution system; and S4, analyzing the impact of electric vehicle charging on the power distribution system. According to the invention, three kinds of charging load models are established, so that the result is suitable for the actual circumstance and become reliable. And on the basis of calculation of the distribution probability characteristics of node voltages of the three models, the following conclusions are made: firstly, conventional chargingmode has the greatest influence on the operational stability of the distribution network; secondly, with the quick charging mode, the peak-to-valley difference of the load is increased substantially,so that economical operation of the grid is affected greatly; and thirdly, with increasing of the proportion of replacing the battery charging mode, the peak-to-valley difference of the load is reduced and the economical efficiency of the grid operation is increased, and the stability of distribution network operation of the power system is enhanced. Therefore, the charging load model establishment and node voltage calculation method has the great significance in research and development of charging vehicles in the field.

The invention is suitable for the technical field of data processing, and provides a calculation model generation method and device, and the method comprises the steps: receiving a charging model generation request; obtaining product information of the target product based on the product identifier, and extracting at least one charging project associated with the product information from a charging project library; generating a charging template about the target product according to the charging algorithm of each charging project; and adjusting the bit value of the configurable parameter in the charging template through the user information, and generating a charging model about the requesting user. The matched charging model can be automatically generated according to the user informationand the product information, the generation efficiency of the charging model is improved, and the configuration difficulty is reduced.

The invention provides a facsimile apparatus and a method for transmitting fax. When a fax service is indicated for executing charge process, a requirement for transmitting process under charge mode is received, on the other hand, when a charge process is not indicated for executing, a requirement for transmitting process under non-charge mode is received. In transmitting process under non-charge mode, when a requirement is inserted for transmitting process, the executing transmitting process is interrupted and the required insert transmitting process is executed. In transmitting process under charge mode, even a requirement for transmitting process is inserted, the executing transmitting process is executed continuously.

The invention discloses a charging system and method for calculating different fees of property business, belongs to the technical field of property management informationization and provides an engine design method of a whole set of charging model. The charging system comprises a charge item module, charge item unit price module, a calculation rule module, an allocation rule module, a utilities expense house-household-meter relation module, a client charging rule module, a meter item module, a general rule module and a charging engine calculating module. Data prepared to be input, including households (owners), charge cycles, meter items, rule numbers, unit prices, meter example information and the like, are determined through early-stage preparation according to bookkeeping intervals determined residential areas, property types, houses and households, selected area charge items, charge cycle types, charge intervals and metering intervals, and runtime parameters are invoked to calculate the receivables corresponding to different charge items through checkout at all levels, house-household-meter relation design and client charging rule design according to variable cost rules and fixed cost rules.

The invention relates to a multi-benefit subject coordination game scheduling method considering EV vehicle owner willingness. The method comprises the steps that S1,establishing an EV load polymer charging scheduling model wherein the EV load polymer charging scheduling model comprises an EV access moment and driving probability model, an EV cluster charging model and an EV vehicle owner willingness probability function model; S2, according to the established EV load aggregate charging scheduling model and the distributed power supply model, establishing a master-slave non-cooperative game model of a power distribution network, a lower-level EV load aggregate and a distributed power supply benefit subject to carry out day-ahead optimal scheduling; and S3, performing intra-day real-time optimization scheduling based on peer-to-peer cooperative games of the lower-level DGs and the load aggregate main bodies under the time-of-use electricity price determined by day-ahead optimization andthe basic strategy of each main body. Through two-stage game scheduling, the reactive power regulation capability of the distributed power supply can be fully stimulated, so that the safe and stableoperation of the power distribution network can be consciously maintained when multiple benefit subjects chase own benefits to be maximized.

The invention discloses an orderly charging control method for electric vehicles in a charging station. The method comprises the steps of: building a vehicle charging model through employing the charging energy and charging price of each vehicle in each time period as the input and the charging income of each vehicle as the output; constructing a charging station model by taking the charging electricity price of each vehicle, the electricity purchasing price of the charging station and the charging energy of each vehicle in each time period as input and taking the charging income of the charging station as output; optimizing the charging station model according to a charging electricity price constraint and the balance constraint of the vehicle charging energy, and determining the optimalcharging electricity price; determining an aggregated game model of vehicle charging according to the vehicle charging model and the optimal charging electricity price; and solving the aggregation game model by using a distributed solving algorithm to determine the charging plan of each vehicle. According to the method of the invention, the aggregation game model of vehicle charging is established, the coupling relationship between the charging vehicles is processed, the optimal charging plan is made for the vehicles in the charging station, and the charging operation efficiency of the vehicles in the charging station is improved.

A charge control method of a photovoltaic charge controller is characterized in that charging models needed by a storage battery energy storage system are obtained through judgment, corresponding control algorithms are adopted according to the different charging models to obtain input voltage instructs, and the purpose of accurately and fast controlling the charging models is achieved through a double closed loop of input voltage and an output current and feedforward control. The charging models are all used for controlling the input voltage so as to enable the control algorithms to be simple, convenient and practical, and smooth switchover among the charging models can be achieved. The photovoltaic charge controller is enabled to have the advantages of being high in dynamic response speed and control precision, and simple in control procedures through a control method of combining of the closed loop and the feedforward control. The purposes of carrying out high-efficient, fast and accurate maximum power tracing, equalized charging and floating charging continuation multi-model charge control on the storage battery energy storage system through the photovoltaic charge controller are well achieved. According to the charge control method of the photovoltaic charge controller, photovoltaic charging speed can be improved, voltage control precision of a storage battery group can be improved, and service life of a storage battery is prolonged.

The invention discloses an electric vehicle ordered charging strategy and a simulation method thereof. The method comprises the following steps: establishing a user side objective function; establishing a power grid side objective function; integrating the user side objective function and the power grid side objective function, and establishing an electric vehicle ordered charging model in the district; introducing constraint conditions to perfect an electric vehicle ordered charging model in the district; and realizing specific calculation and regulation according to the orderly charging model of the electric vehicle in the district. According to the technical scheme, the electric vehicle charging load in the regional power distribution network is used as a research object, the influence on the power grid node voltage and the system network loss when the electric vehicle is accessed disorderly is analyzed, then the minimum user side charging cost and the minimum power grid side load peak-valley difference are used as objective functions, the orderly charging optimization model of the electric vehicles in the districts is established, the objective function is solved by using the adaptive particle swarm optimization, an optimal electric vehicle charging mode is obtained, and the peak-valley difference of the system load can be effectively reduced.

The invention discloses a crowded road charging determination method and system for heterogeneous users. Different time values w (x) are set for different users, heterogeneity of the users is fully considered when the charging model for the crowded road is constructed, and the model better meets actual requirements. According to the designed crowded road use charging model oriented to the heterogeneous users, the driving time of the path r between the OD pair w contains the flow of the corresponding road section and is determined by f *. Therefore, any target flow distribution can be realized,and the calculation process is simple and practical.

A distributed energy control method comprises: when a power grid is powered off, a distributed charging station in a pre-constructed optical storage charging model supplying power in a station; when the in-station power supply of the optical storage and charging model is insufficient, the operation monitoring system regulating and controling the optical storage and charging model to carry out inter-station power supply; wherein the optical storage and charging model comprises a plurality of distributed charging stations in an area, and each distributed charging station is connected with a physical layer circuit of a power grid through a power transmission wire. According to the scheme, an efficient energy management strategy is formulated for the photovoltaic storage and charging integrated system and used for managing energy flow of a plurality of photovoltaic charging levels, the phenomenon that a family cannot meet basic electricity consumption due to power failure of a power grid is avoided, and maximum utilization of photovoltaic power generation is achieved.