137results about How to "Flexible scheduling" patented technology

The invention relates to the technical field of power dispatching, and provides a multi-electricity energy storage participation power dispatching system based on an optimal charging demand, which comprises a dynamic price adjustment module, a multivariate data fusion module, a collaborative optimization intelligent dispatching module, an energy storage resource management optimization configuration module and a safety and reliability prompt module, a dynamic price adjustment module, a data fusion module, a collaborative optimization scheduling module, an energy storage resource optimization configuration module and a safety and reliability prompt module are integrated, global optimization of electric power resources is achieved through the intelligent and automatic technology, an intelligent bidding strategy is provided for dynamic price adjustment, a comprehensive information platform is constructed through data fusion, flexible scheduling is achieved through collaborative optimization, and safety and reliability are improved. The energy storage resource management platform monitors and optimizes configuration in real time, safety and reliability are prompted to ensure stable operation of the system, the system is intelligent, the automation integration degree is high, the power dispatching precision, the response speed and the economic benefits are remarkably improved, and the problem of insufficient economic benefits in the prior art is solved through the technical scheme.

The invention discloses a network management computing power session method and system based on 6G communication, sensing and computing integration, belongs to the technical field of mobile communication, and aims to solve the technical problem of how to realize flexible scheduling and on-demand distribution of computing power and network convergence resources in a 6G communication, sensing and computing integration network environment under the condition of not changing network equipment. A mobile network environment supporting a computing power-as-a-service mode is constructed for a user, and the adopted technical scheme is as follows: the method comprises the following steps of: deploying a computing network integration sensing network element, a computing network integration control scheduling network element and a computing network integration service arrangement network element on a core network side, so that the improved core network has a communication, sensing and computing power integration function; and through analysis and identification of computing power application request indexes, computing power business arrangement, computing power and network Qos configuration mapping, decision making and scheduling of computing network fusion resources, distributed cooperative computing tasks are issued, so that computing power session creation is completed, and different computing power requirements of the mobile terminal are met.

The invention discloses a reservoir group scheduling interval multi-target optimization method under an uncertain condition, and belongs to the technical field of reservoir optimization scheduling. The method comprises the following steps: firstly, establishing an innovative cascade reservoir group interval multi-target scheduling model; secondly, providing a double-population dynamic coordination interval optimization method for solving the interval multi-target scheduling model, and further obtaining an optimal scheduling scheme of the reservoir group; and finally, outputting an optimal scheduling scheme set of the reservoir group. According to the optimization method, through organic combination of a chaos-order mapping initialization strategy, a dynamic adaptive mutual promotion updating strategy and an elite guidance optimization strategy, optimization is rapidly and efficiently carried out to obtain a group of reliable and accurate scheduling scheme sets considering runoff uncertainty; an effective decision-making technical means for solving the cascade reservoir group optimization multi-target complex engineering problem is provided for a scheduling decision maker, the intelligent level and comprehensive benefits of water resource management are improved, and the capacity of a water resource system for coping with complex environments and uncertain factors is further enhanced.

The invention relates to the technical field of performance simulation analysis, in particular to a performance simulation method of a power module. The method comprises the following steps: acquiring initial physical characteristic data and initial electrical characteristic data of a power module; the initial physical characteristic data and the initial electrical characteristic data are preprocessed and simulated, and physical field distribution characteristics in the power module are obtained; performing multi-physical field simulation analysis on the power module based on physical field distribution characteristics in the power module by using an adaptive grid generation algorithm and sparse matrix solution to obtain simulation result data; performing parameter adjustment and optimization on a simulation model of the power module according to the simulation result data to generate optimized simulation model parameter data; and according to the optimization simulation model parameter data, performing simplification processing on the design of the power module to establish a simplified model. Through multi-stage simulation and optimization, the performance and the control precision of the power module can be remarkably improved, and the stability and the efficiency of the system are improved.

The invention belongs to the technical field of comprehensive energy system optimization, and discloses a comprehensive energy system optimization method and system based on power-to-gas and carbon capture equipment. The comprehensive energy system comprising two-stage power-to-gas equipment, the carbon capture equipment, electric energy storage equipment and the like is constructed, and the coupling relation and adjusting characteristics between load energy conversion are combined; a low-carbon economic dispatching model is constructed, objective functions are established by considering power purchase cost, gas purchase cost and the like, a constraint set is established by considering thermoelectric power balance, system capacity, carbon capture and the like in a comprehensive energy system, and a multi-objective evolutionary algorithm is adopted to carry out optimization solution on a plurality of objective functions. According to the technical scheme, the total operation cost and the carbon emission of the system are comprehensively considered, the low-carbon and environment-friendly characteristics of hydrogen energy are fully played, the renewable energy consumption of the system is improved, the multi-target intelligent algorithm is adopted for solving, economic benefits are considered, the method is environmentally friendly, and the total operation cost and the CO2 emission of the system are reduced.

The invention discloses a carbon metering system based on cloud pipe edge end cooperation. The carbon metering system comprises a carbon metering terminal, a carbon metering safety pipeline, a carbon metering edge cloud and a carbon metering center cloud. The carbon metering edge cloud comprises an enterprise end edge cloud, a government supervision mechanism end edge cloud, a third-party certification mechanism end edge cloud and a financial mechanism edge cloud which are nodes in a block chain distributed account book; the carbon metering edge cloud stores real-time carbon emission source original data in a distributed account book and upwards migrates the real-time carbon emission source original data to the carbon metering center cloud, the carbon metering center cloud takes the original data as a sample to regularly train a carbon metering algorithm model, if the difference of trained model parameters exceeds a preset threshold value, training parameters are updated, and if the difference of the trained model parameters exceeds a preset threshold value, the carbon metering algorithm is updated; and the model and the new parameters are issued to the carbon metering edge cloud, the carbon metering edge cloud timely updates the calculation parameters for accounting, and the calculation result is issued to complete real-time display. According to the scheme, the balance between resource allocation and calculation is optimized, the scheduling is flexible, and the response is fast.

The invention provides a dynamic scheduling method for new energy station loads, which relates to the technical field of new energy power generation, and comprises the steps of collecting power generation data and equipment operation state data, calling power grid load demand data and power grid operation parameters, building a comprehensive prediction model according to station historical data in combination with a neural network algorithm, and carrying out dynamic scheduling on the new energy station loads. The comprehensive prediction model comprises a power generation power prediction model and a load demand prediction model, inputting the power generation data, the equipment operation state data, the power grid load demand data and the power grid operation parameters into the comprehensive prediction model, performing power generation capacity prediction and load demand prediction, and performing dynamic scheduling based on a power generation capacity prediction result and a load demand prediction result. The technical problems of power grid power imbalance and resource waste caused by the fact that load scheduling is difficult to adapt to the power generation characteristics of the new energy station in the prior art are solved. The technical effects of realizing flexible scheduling of the load of the new energy station and effectively balancing the generated power of the new energy station and the load demand of the power grid are achieved.

The invention belongs to the technical field of satellites, and discloses a centralized photovoltaic power station capacity prediction method and system based on a satellite image and topographic data, and the method comprises the steps: carrying out the recognition of a Sentinel remote sensing image, obtaining a photovoltaic distribution position after photovoltaic automatic recognition according to the spectral characteristics, including the mean value of each spectral band, NDVI, NDWI and other indexes, and carrying out the prediction of the capacity of a photovoltaic power station. Meanwhile, elevation data provided by DEM images are integrated to calculate a topographic slope value, then influence factors such as photovoltaic image area, inclination angle, direction angle and installation spacing are calculated by using parameters such as image resolution and geographic latitude, and finally, parameters such as known photovoltaic scale and photovoltaic materials are combined to obtain a photovoltaic power generation system. And a prediction model of the capacity of the centralized photovoltaic power station is constructed with the installation capacity of a small number of known photovoltaic power stations, so that accurate prediction from the image area of the photovoltaic power station identified by the satellite image to the actual installation capacity is realized. The method comprehensively considers the influence of the direction angle, the inclination angle, the installation spacing and the like of the photovoltaic power station on the actual installation capacity, is suitable for mountainous and hilly areas with complex terrains, improves the problem of inaccuracy of a method for estimating the capacity based on the projection area, and provides a scientific basis for the capacity evaluation of the photovoltaic power station.

The invention provides a computing resource scheduling method, device and system based on bare metal or containers, and the method comprises the steps: predicting first computing power resource data through a pre-trained safety water level prediction model, and obtaining an inventory safety water level corresponding to a current time period; performing system initialization deployment, monitoring use data of target computing power resources and system resources in real time, and converting the use data into inventory information; when a newly added user resource creation request is monitored, analyzing to obtain a target priority label; if the target priority label is a high-priority label and the ratio of the number of idle groups to the number of total groups is judged to be not greater than a preset threshold value corresponding to a safe water level based on inventory information, identifying a target computing power resource group corresponding to a low-priority label and performing instance release operation; and responding to a user resource creation request based on the resource after the instance release operation. According to the invention, reasonable resource scheduling can be carried out, the stability of the key task is ensured, and the service quality and the user experience are improved.

The invention discloses a fused salt multistage energy storage management method and system, and the method comprises the steps: obtaining the historical load data of a power grid, carrying out the modeling prediction based on the historical load data of the power grid, and obtaining the load prediction data of the power grid; performing clustering analysis on the load prediction data of the power grid, and determining a power grid load stage in the load prediction data; setting a multi-stage energy storage management strategy based on a power grid load stage, and performing simulation operation according to the multi-stage energy storage management strategy; and evaluating the simulation operation result to obtain a multi-stage energy storage management evaluation value, and adjusting a multi-stage energy storage management strategy based on the multi-stage energy storage management evaluation value. By means of the technical means of modeling prediction, clustering analysis, simulation operation and the like, intelligent scheduling and management of the multi-stage energy storage system are achieved, the multi-stage energy storage management strategy is adjusted by evaluating the simulation operation result, the multi-stage energy storage management strategy is optimized, the energy utilization efficiency of the system is improved, and the energy utilization efficiency of the system is improved. And the flexibility and the response capability of the system are improved.

The invention provides a parallel computing control optimization method for multiple HASH algorithms in an ASIC chip, and relates to the technical field of data processing, and the method comprises the steps: selecting a matrix according to a mode, and scheduling different SHA-256 processing units and assembly line stages, so as to obtain the adjusted SHA-256 processing units; a control signal is added to each adjusted SHA-256 processing unit, and the control signals are used for controlling starting and stopping of operation of the SHA-256 processing units; optimizing a task allocation scheme between the adjusted SHA-256 processing units, and representing a specific task allocation scheme by using each particle; defining a fitness function for evaluating the performance of each task allocation scheme; and according to the fitness function, calculating the fitness of each particle, updating the speed and position of the particle, and carrying out iterative operation until a preset number of iterations is reached so as to obtain a final task allocation scheme. According to the invention, the data processing efficiency and performance can be improved.

The embodiment of the invention discloses an image data acquisition method, a storage medium and an image acquisition device, and belongs to the field of image processing. Through a double-lens orthogonal synchronization mode, that is, when the first image sensor (sensor0) outputs half-frame data, the synchronization pulse signal is triggered to control the second image sensor (sensor1) to start to output frame data of the second image sensor (sensor1), so that accurate and synchronous acquisition of image data of the two sensors is realized. According to the synchronization mode, the problem of data coverage possibly occurring under the condition that each sensor only has a single buffer area is avoided, and data output of the two sensors is carried out alternately, so that the integrity and accuracy of data are ensured.

The invention provides a distributed photovoltaic and energy storage area autonomous capability optimization method based on a robust chance constraint model, and the method comprises the steps: considering the power fluctuation caused by distributed photovoltaic and load in a distributed photovoltaic and energy storage area autonomous scheduling plan, and defining the condition for achieving the autonomous capability based on the power fluctuation quantity in the area: in any time period, the power fluctuation quantity of the distributed photovoltaic and energy storage area is smaller than the power fluctuation quantity of the distributed photovoltaic and energy storage area; the regional maximum adjustable output is greater than or equal to the regional power total fluctuation quantity; opportunity constraint and a distributed robust optimization method based on Kullback-Leibler divergence are introduced into autonomous capability optimization, and a robust opportunity constraint model is obtained; the distributed robust opportunity constraint is converted into a traditional opportunity constraint through a fuzzy set equivalent conversion formula, and the traditional opportunity constraint is solved by adopting a risk value method; on the premise of considering the regional autonomous capability, the regional scheduling operation is optimized by taking the operation cost minimization as the target.

The invention provides a hotel guest room management method and system based on cloud computing, and is applied to the field of cloud data processing. By monitoring the access resources cached by the hotel terminal in real time, the current access situation can be rapidly obtained, the load state of the system can be reflected in time, whether the current access resources reach the preset load upper limit or not can be judged in real time, it is ensured that corresponding measures are taken in time under the high-load situation, system overload is avoided, and the service life of the system is prolonged. Meanwhile, access resources are predicted through a pre-trained machine learning model, possible peak periods and load conditions can be identified in advance, scheduling can be performed in advance, resource contents of hotel terminals are dynamically scheduled according to prediction results, reasonable allocation and use of resources in peak periods are ensured, and resource waste or shortage is avoided.

The invention relates to the technical field of power plant inspection, and discloses a comprehensive safety inspection method for a smart power plant, which comprises the following steps: S1, arranging various sensors and pulse signal devices on each power device in the power plant, regularly collecting operation data and pulse reflection signal frequency spectrum of each power device, and establishing a normal operation state set of the devices; and S2, generating a visual three-dimensional map of the power plant according to the data of the sensor and the pulse reflection signal spectrum, marking an image model and a number of each device in the map, and mapping the accurate position of the device model in an actual scene to the map in an equal-proportion splicing mode. By introducing the equipment health index and residual life prediction model, the running state of the equipment is evaluated in real time, potential faults are predicted in combination with historical data, the service life of the equipment is prolonged, fault prediction is more accurate, predictive maintenance tasks are generated in advance, and serious faults are avoided.

The embodiment of the invention relates to the technical field of robots, and discloses a robot control method, electronic equipment and a storage medium. The method comprises the steps that a query request sent by a target robot is acquired, the query request is generated when the target robot is forced to be in butt joint with a charging pile, the query request is responded, a target electric quantity range is determined according to a forced pile loading identifier, different electric quantity ranges correspond to different scheduling types, and the scheduling type corresponding to the target electric quantity range is determined as a target scheduling type; and controlling the target robot according to the target scheduling type. According to the embodiment, the situation that the target robot is forced to be in butt joint with the charging pile is marked through the forced pile-on identifier, and the target scheduling type is automatically determined according to the target electric quantity in response to triggering of the forced pile-on identifier, so that the target robot is controlled; in this way, the target robot can be flexibly dispatched by adapting to the electric quantity of the target robot under the condition that the target robot is forced to be in butt joint with the charging pile, and the task execution efficiency is improved.

The embodiment of the invention provides a message transmission method, communication equipment, a storage medium and a program product, and the method comprises the steps: receiving a computing network drainage strategy and a first service message from physical client terminal equipment, and enabling the computing network drainage strategy to be generated according to computing power state information and network state information related to a service, the first service message carries a first service identifier for representing the service type of the first service message; and when virtual client terminal equipment corresponding to the physical client terminal equipment is determined to be in a multi-cloud resource pool deployment mode according to the first service identifier, determining a first target cloud resource pool according to the first service identifier and a computing network drainage strategy, and forwarding the first service message to the first target cloud resource pool. For a multi-cloud resource pool deployment mode, according to the embodiment of the invention, the target cloud resource pool can be selected according to the service type, the computing power state and the network state of the service message to drain the service message, so that flexible scheduling of the service message among the multi-cloud resource pools can be realized.

The invention discloses a short multimedia message sending method, a short multimedia message sending system, a medium and a product, and relates to the field of information transmission. Selecting short and multimedia message sending channels of which the real-time load rates are lower than a preset load rate threshold value from the plurality of short and multimedia message sending channels as candidate channels; determining a short multimedia message feature data set according to the short multimedia message sending request; determining channel feature data according to the candidate channels; inputting the short multimedia message feature data set and the channel feature data into a preset sending failure probability prediction model to obtain a sending failure probability; when the sending failure probability exceeds a preset probability threshold value, sending the short multimedia message to the receiver through the standby channel; and when the sending failure probability is lower than a preset probability threshold, sending the short multimedia message to the receiver through the candidate channel. By implementing the method, the success rate of sending the short multimedia message can be improved.

The invention provides a continuous and stable power generation circulating device for gravity energy storage, which comprises a weight block body, a bearing mechanism, a weight circulating module and a bearing circulating module, and is characterized in that the bearing mechanism can load the weight block body, the weight circulating module comprises a rotating wheel and a chain condition arranged along the conveying direction, and the chain condition rotates around the rotating wheel; the bearing mechanism is slidably arranged on the weight circulation module in the conveying direction, the end of the bearing mechanism is meshed with the chain condition, and the chain condition can keep moving. According to the circulation device, the chain condition can be always in a rotating operation state in the power generation process, then power generation is stable and continuous, power generation circulation of single-channel gravity energy storage can be achieved due to the fact that the chain condition in the weight circulation module can be matched with the bearing mechanism in an accumulation and free mode, extra auxiliary equipment is not needed, and the power generation efficiency is improved. The mechanical loss is reduced, the bearing circulation module can also realize flexible scheduling, the no-load rate is reduced, and the equipment utilization rate and the circulation efficiency are improved.

The invention relates to the technical field of data processing, in particular to an order data processing method and system based on a block chain. The method comprises the following steps: acquiring a multi-source order data set; performing transaction address analysis on the multi-source order data set to generate order transaction address data; order processing server construction is carried out on the multi-source order data through the order transaction address data, and order processing distribution server data is generated; order processing access frequency analysis is carried out on the multi-source order data set through order processing distribution server data, and order processing access frequency data is generated; and performing order screening on the multi-source order data set based on the order processing access frequency data to generate high-frequency order access data and low-frequency order access data. According to the invention, through optimization of multi-source data integration, order access frequency analysis, transaction synchronization and channel optimization, the reliability and efficiency of order transaction are improved.

The invention provides a regional power grid optimal scheduling method and device, electronic equipment and a medium, and the method comprises an obtaining module which is used for obtaining a single operation model of each flexible resource; the first establishing module is used for establishing single power regulation feasible regions of the plurality of flexible resources according to the plurality of single operation models; the clustering module is used for summing the plurality of monomer power regulation feasible regions and determining a power aggregation feasible region of each flexible resource; and the second establishment module is used for establishing a regional power grid optimization scheduling model containing aggregation distributed flexible resources according to the plurality of power aggregation feasible regions. According to the method, the technical problem that the adjustable power is relatively small due to participation of flexible resources of single equipment in regional power grid optimization scheduling in the prior art is solved.

The invention discloses a construction method of a power grid carbon emission distribution network model. The construction method comprises the steps of obtaining node load data, generating capacity data and branch data of a power grid; forming an original data set and a load flow calculation result according to the data, and establishing a network topology model according to the original data set and the load flow calculation result; equivalently transplanting the loss power of each branch in the network topology model to a corresponding upstream node, keeping the size and direction of the power flow of each branch unchanged, and updating the network topology model; and based on the updated network topology model, constructing a carbon emission distribution network model in combination with a proportion sharing principle. According to the method, through real-time data acquisition, network topology modeling, carbon emission flow calculation and optimization solution, the carbon emission in the power system can be accurately quantified, and a scientific basis is provided for low-carbon scheduling and policy making of the power industry.

The utility model relates to a kind of connecting mechanism and equipment pedestal, belong to laser direct imaging equipment technical field.Connecting mechanism includes positioning and guiding component, is set in the splicing of two adjacent pedestals, for the directional splicing of two adjacent pedestals together;Positioning and guiding component includes the first guide plate and second guide plate respectively set in two adjacent pedestals;First guide plate and second guide plate can be slid along splicing direction relative to the pedestal where it is;One of first guide plate and second guide plate is provided with convex part, and the other is provided with recess part;Convex part and recess part are used to guide and position two pedestals in splicing process;Locking assembly is used to fix two adjacent pedestals.By the guiding and positioning effect of first guide plate and second guide plate and the fixing effect of locking assembly, the accuracy and stability of splicing can be ensured while ensuring the rapid splicing of pedestal.

This invention discloses a liquefied petroleum gas (LPG) frying boiler with easy temperature control and its operating method, specifically relating to the field of frying boiler technology. It includes a mounting frame and multiple LPG stoves, all of which are fixedly installed at the bottom of the mounting frame. Each LPG stove has a boiler assembly on its top, and each boiler assembly includes a boiler body, two sliding sleeves, two second sliding groove plates, and two second sliding plates. The opposing sides of the two sliding sleeves are fixedly connected to the boiler body. This invention uses a stepper motor output shaft to drive a lead screw, thereby moving the support frame and boiler body backward. When the first light is energized, it indicates that the current boiler body has moved to a non-heating position away from the LPG stove. Subsequently, another boiler body can be horizontally moved along the length of the mounting frame to a heating position directly above the current LPG stove. Overall, temperature control is convenient and the movement is flexible, effectively improving frying processing efficiency and the stability of finished product quality.

The invention relates to the technical field of communication, and particularly provides an uplink and downlink resource joint scheduling method, a terminal, network equipment, a storage medium and a product. The uplink and downlink resource joint scheduling method can be applied to a terminal, and comprises the following steps: sending first indication information to network equipment, the first indication information being used for indicating a service type of the terminal; receiving second indication information sent by the network equipment, wherein the second indication information is used for indicating the network equipment to configure a periodic first uplink resource and association information of uplink and downlink resources for the terminal according to the service type of the terminal; and determining a first downlink resource according to the association information of the first uplink resource and the uplink and downlink resources. The uplink resource is periodically configured, and under the condition that the uplink resource is determined, the downlink resource can be flexibly configured through the associated information, so that authorization-free scheduling of the uplink resource and the downlink resource is realized, unnecessary signaling overhead and time delay are reduced, and the low-delay transmission requirement of a related network is effectively met.

The invention discloses an intelligent automatic welding system for a beam-column structure and a welding method thereof, and relates to the technical field of welding. The invention aims to solve the problems that the adjustment range of the existing welding equipment is limited, so that a workpiece is easy to deviate in the clamping and assembling processes, the controllability of manual operation on the welding process is low, and the dual requirements of large-scale production on speed and precision cannot be met. The automatic welding device comprises a welding robot, a robot controller, a master control system, a positioner and a welding tool, a welding workpiece is clamped on the positioner through the welding tool, the positioner is used for achieving rotation of the welding workpiece, and the welding robot is arranged on one side of the positioner through a linear moving mechanism. The main control system controls the welding poses and welding parameters of the welding robot through the robot controller, and the main control system controls the displacement and moving parameters of the positioner, the welding tool and the linear moving mechanism. The method is used for intelligent automatic welding.

The present invention provides a microgrid energy storage optimization scheduling method taking into account renewable energy prediction errors, comprising the following steps: S1, constructing a mathematical model of a microgrid and each unit of the microgrid; S2, establishing an energy storage charging and discharging strategy taking into account renewable energy prediction errors; S3, constructing a microgrid energy storage flexible optimization scheduling model, and based on the energy storage charging and discharging strategy taking into account renewable energy prediction errors, determining the optimization target and constraint conditions of the microgrid energy storage flexible optimization scheduling model; S4, solving the microgrid energy storage flexible optimization scheduling model using an optimization algorithm to obtain a microgrid energy storage scheduling plan.

The present invention belongs to the technical field of communication data processing, and more specifically, relates to a system and method for USB device multi-tasking support based on Linux operating system. The system proposes a complete USB multi-process management mechanism, the core of which is to build a dedicated USB device scheduling system. The system first identifies and monitors all processes of the Linux system that request USB devices, then dynamically allocates a unique access identifier to each process that requests USB devices, and when receiving USB device messages, performs process configuration according to the allocated identifier to complete the multi-tasking function. The present invention solves the conflict and inefficiency problems caused when multiple processes simultaneously access the same USB slave device in a multi-user, multi-tasking environment in a USB host device.

The invention provides an access method of an AMP multi-core heterogeneous system and the AMP multi-core heterogeneous system, the AMP multi-core heterogeneous system comprises a first core, a second core, a shared memory and a mailbox, the first core is internally provided with a physical serial port and a first virtual serial port which are communicated with each other, the second core is internally provided with a second virtual serial port, and based on the virtual serial ports, efficient and real-time tty data exchange is realized. A basic serial communication function is realized between the master core and the slave core, and the slave core can access the physical serial port of the master core through the virtual serial port equipment, so that the peripheral serial port equipment can be accessed through the physical serial port of the master core, and the configuration and data communication of the slave core to the serial port equipment are realized; therefore, not only is the resource competition of the hardware interface between the master core and the plurality of slave cores reduced, but also the flexible distribution and scheduling of the UART serial data flow are achieved, so that the requirements of various communication modes of the master core, the slave cores and the UART physical serial port are met.

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.