1052 results about "Distribution control" patented technology

The invention discloses an intelligent household electrical appliance interaction control method and system, and the method comprises the following steps: collecting the operation state parameters, environment perception data and user behavior characteristics of each household electrical appliance in a living space in real time, and generating an environment perception data packet through a multi-modal data fusion model; constructing a user habit preference model library, generating a household appliance control strategy decision tree in combination with historical interaction records, and matching an optimal control strategy set according to a real-time scene type; and when a user active intervention signal or an environment sudden change event is detected, a dynamic strategy reconstruction mechanism is triggered, an instruction updating request carrying a priority identifier is broadcasted to the associated household appliance group, and a redistribution control instruction set is generated. The method has the following advantages and effects: multi-source environment data can be deeply fused, the user habit model is constructed in real time, and the method has a dynamic strategy reconstruction capability so as to solve the problems of response lag, strategy stiffness and energy efficiency imbalance in a complex home environment in the prior art.

The invention discloses a multi-parameter MPC two-phase liquid cooling energy efficiency optimization distribution control system and method, and relates to the technical field of liquid cooling energy efficiency optimization. The multi-parameter MPC two-phase liquid cooling energy efficiency optimization distribution control system and method comprises the following steps: S1, collecting and preprocessing two-phase liquid cooling control data; s2, the thermal load level of each area is evaluated periodically, a discrete time linear state space model is constructed, and the thermal load change rate is extracted; s3, the cold distribution amount of each area is quantified periodically, the pump speed and the valve opening target value are calculated, and an adjustment control instruction is generated; and S4, high heat risk and low heat stability areas are recognized, the cooling capacity compensation requirement is evaluated, a cooling capacity enhancement and recovery distribution value is output, and a corresponding control instruction is generated. The problems that an existing two-phase liquid cooling system generally only depends on temperature feedback for adjustment, so that cooling capacity distribution response lags behind, a short-time overheating phenomenon is prone to occurring in a high-heat area, and cooling capacity waste exists in a low-heat area at the same time are solved.

The invention relates to the technical field of storage batteries, in particular to a storage battery monitoring, detection, treatment and evaluation integrated system and a storage battery management method, and the system comprises a plurality of accompanying modules, a collection power distribution control module, a storage battery management capacity checking host and a remote platform; the internal resistance analysis test of the system is based on multi-frequency-point alternating current excitation (0.5 Hz-7. 5kHz), a complex impedance spectrum of not less than 20 frequency points can be constructed, and the internal polarization characteristics of the battery are analyzed; the system adopts a feed network type discharge capacity checking, so that discharge electric energy is fed back to a power grid, and the capacity detection precision is improved to 98%; according to the system, EIS data and an LSTM neural network are fused, and a battery state of health (SOH) prediction model is established; the system is based on a DSP digital power supply technology, and can realize 50A active equalization topology.

The invention provides a water flow dynamic distribution control method driven by air conditioner terminal load prediction, and relates to the technical field of air conditioner engineering.The method comprises the steps that 1, the people flow density, the environment temperature and humidity and the equipment running state of each air conditioner terminal service area are collected in real time, and a load prediction mechanism is constructed based on a spatial-temporal feature fusion algorithm; the minimum cooling capacity demand of each tail end in the future time period is predicted; 2, based on the minimum cooling capacity requirement, areas with similar load characteristics are classified into the same cluster through hot area clustering, and building scale dynamic cooling load distribution is generated with cluster mass center data as the benchmark; and step 3, calculating an energy flexibility penalty coefficient based on the dynamic cooling load distribution in combination with the real-time deviation between the indoor temperature and the comfortable temperature difference, and generating a regional water flow regulation weight. According to the method, dynamic distribution of the water flow is driven through load prediction, the water pump frequency and the refrigerating unit strategy are dynamically adjusted in combination with real-time energy consumption feedback, and self-adaptive adjustment of the branch water flow is achieved.

The invention discloses a parallel processor dynamic resource allocation system and method based on reconfigurable hardware, and relates to the technical field of computer chips, and the system comprises a workload monitoring module which is responsible for monitoring the workload type and the resource demand of a task processed by a parallel processor in real time, and determining the task type and the resource demand by identifying the task type and the resource demand; a monitoring result is fed back to the resource allocation control module; the resource allocation control module is responsible for generating a corresponding resource allocation control signal based on feedback information of the workload monitoring module and dynamically configuring the reconfigurable hardware module; the reconfigurable hardware module is responsible for realizing efficient adaptation to diversified tasks through a plurality of reconfigurable units formed by programmable logic devices according to different working load dynamic reconfiguration functions and connection modes; and the data caching and transmission module is responsible for cross-module data circulation and global data storage. Different task requirements can be accurately adapted, and the resource utilization rate is improved.

The invention relates to the field of power distribution control, and particularly discloses a self-healing control system and method based on multi-agent collaboration, and the system comprises a regional agent and a local agent which are disposed in a power distribution network. Wherein the local intelligent agent is configured to obtain real-time operation data of a monitoring point in the power distribution network, and perform rapid fault detection on the real-time operation data; the regional intelligent agent is configured to fuse the fault analysis information of the plurality of local intelligent agents to determine fault position information when the power distribution network has a fault, generate a self-healing control strategy according to the fault position information, and send the self-healing control strategy to the local intelligent agents for execution; through cooperative work of the distributed intelligent agents, the problems of low response speed, low positioning precision, weak autonomous capability and the like in traditional power distribution network fault management are solved. In addition, the system does not need to depend on centralized control of a master station, can still operate autonomously when communication is interrupted, and improves the efficiency and reliability of fault processing through cooperation of multiple agents.

The invention discloses a micro-grid load distribution control method, device and equipment based on entropy increase disturbance, and the method comprises the steps: analyzing the operation state of a micro-grid through chaos measurement, and constructing an entropy increase disturbance excitation mechanism to actively excite the vitality of a system; after random disturbance is applied, inherent frequency characteristics of each power supply are extracted, and a frequency synchronization coordination mechanism is established to realize multi-source coordination; adopting counter-example search to actively identify distribution scheme vulnerabilities, and generating an enhanced distribution strategy to improve robustness; evaluating the load bearing capacity of each power supply, constructing a load conduction topology and analyzing pressure distribution; each power supply bearing limit parameter is obtained through boundary active detection, and the equipment potential is fully excavated; and a final control instruction is generated based on a multi-layer time sequence synchronization mechanism, and multi-power-supply coordinated output is realized. A chaos theory is introduced into micro-grid control, local optimum is avoided through active disturbance, a multi-layer coordination mechanism is adopted to adapt to new energy volatility, and a self-adaptive load distribution control scheme is provided for a micro-grid with high-proportion renewable energy access.

The invention relates to the field of locomotive power battery electric quantity control, and particularly discloses a locomotive power battery electric quantity hysteresis equalization control method, which comprises the following steps that: a traction force exerting mode is reset into an axle load transfer mode, and the initial value of an electric quantity equalization compensation coefficient K is a rack axle load transfer coefficient corresponding to zero speed; judging whether the current mode is a power battery power supply mode; if yes, the TCU receives the electric quantity of a front power battery and the electric quantity of a rear power battery in real time according to the current locomotive working mode, calculates the electric quantity average value difference value, monitors the auxiliary load power and the traction motor power and calculates the power difference value; entering a hysteresis control logic process; calculating a dynamic traction force compensation coefficient, ensuring that the traction force compensation amount is matched with the actual load characteristic of the system, correcting the traction characteristic curve in real time, and dynamically compensating the electric quantity difference of the battery; and performing traction distribution control according to the locomotive speed and outputting corresponding traction.

The invention discloses a face recognition and encryption verification multi-grid article distribution control method and a distribution vehicle, and relates to the technical field of recognition and verification safety, and the method comprises the steps: fusing three-dimensional environment information through employing a vehicle-mounted edge calculation terminal and a navigation positioning terminal, and constructing a dynamic safety response strategy; the warehouse is analyzed through the vehicle-mounted warehouse control unified management terminal and the dynamic safety response strategy, and an edge intelligent control mechanism is obtained; processing based on a vehicle control and monitoring terminal and an edge intelligent control mechanism to obtain a real-time state; a vehicle interaction terminal and an intelligent operation terminal are utilized to obtain a face image and a visual dynamic feature, and a multi-modal detection strategy is utilized to analyze the face image and the visual dynamic feature to obtain a final authorized face image and a final authorized visual dynamic feature; and a dual-mode intelligent redundant unlocking technology is constructed, and face recognition and encryption verification are performed on the distribution vehicle based on the dual-mode intelligent redundant unlocking technology. According to the invention, compliance, high-efficiency and safe distribution of high-value materials is realized in an unmanned environment.

Systems, methods, and computer-readable storage media to protect tokens using a protection architecture. One method includes identifying asset tokens including links to a plurality of asset metadata objects. Further, the method includes generating a container metadata object including metadata of the asset tokens. Further, the method includes generating a container token including a link with the container metadata object. Further, the method includes encapsulating the container token and the asset tokens within a container including a container control structure restricting outputs of the container metadata object and the plurality of asset metadata objects. Further, the method includes generating an allocation token compatible with a segmented allocation control structure restricting outputs by the container of a first segmented allocation of the asset tokens based on metadata of a subset of the plurality of asset metadata objects. Further, the method includes providing, using the segmented allocation control structure, the allocation token.

The invention relates to the technical field of parking lot digital management, and discloses a digital twin enabling parking lot digital global management system. According to the system, a global digital twin model of a parking lot is generated, and multi-source sensing data such as parking space states, vehicle identities and environmental parameters are fused; generating a parking space distribution matrix with priorities and time windows in combination with the parking request of the user and the real-time parking space state; according to the parking space two-dimensional code hardware parameters, the digital twin model and the parking space distribution matrix, outputting a vehicle guiding path set with a timestamp; a real-time obstacle avoidance and dynamic adjustment system is constructed to generate a safe driving path set so as to dispatch vehicles; outputting a power distribution control instruction set and updating the digital twinborn model by combining the electric quantity of the energy storage unit, the power distribution network data and the safe driving path set; and finally, system knowledge evolution and end-to-end closed-loop optimization are realized through scheduling execution logs. According to the system, global efficient management of the parking lot is realized, and the parking space utilization, vehicle scheduling and energy utilization levels are improved.

The invention discloses a power distribution control method and device for an optical storage DC flexible power distribution system, and relates to the technical field of power distribution control methods, and the method comprises the steps: determining a power consumption path of each power distribution region based on a power load and a photovoltaic power generation path of each power distribution region, and an energy storage path corresponding to the optical storage DC flexible power distribution system; and the power distribution balance event of each power distribution area is determined according to each power consumption path, the power distribution level of each power distribution area and the power distribution control relationship among the power distribution areas, so that the accuracy of the power distribution balance event of each power distribution area is improved. Therefore, the dynamic restoration event of the power distribution area is determined based on the autonomous management and control system and the abnormal power distribution position of the power distribution area, and the flexible regulation and control event of the optical storage direct-current flexible power distribution system is determined based on each dynamic restoration event, the working process of the optical storage direct-current flexible power distribution system and the flexible management and control path. And the autonomous flexible regulation and control effect of the optical storage direct-current flexible power distribution system is ensured.

The invention belongs to the technical field of aviation hybrid power, and discloses a self-adaptive intelligent power distribution control method for an aviation hybrid power system, which comprises the following steps: constructing a full-dimensional state model through multi-dimensional perception fusion, predicting working condition transition in combination with deep reinforcement learning, and dynamically adjusting a power distribution strategy; the response speed is guaranteed preferentially during emergency takeoff, energy recovery is emphasized during conventional landing, the problem that a traditional distribution mode is disjointed with actual requirements is solved, power output of an engine and a battery better fits the flight working condition, and stable operation can still be achieved in complex environments such as sudden airflow; by introducing digital twinborn rehearsal verification and adaptive robust control, risks of engine overtemperature, battery overcharge and the like are exposed and corrected in advance through virtual simulation, disturbance is dealt with in combination with a'basic + compensation 'power structure, part faults caused by unreasonable power distribution in traditional control are avoided, and the reliability of the system is improved. And the reliability of the hybrid power system in key stages of takeoff and landing is improved.

The invention discloses a fork type mobile robot power distribution unit dynamic distribution control method and system, and relates to the technical field of intelligent robots, and the method comprises the steps: arranging sensors at a robot PDU input end and each output channel, collecting an operation data set in real time, and carrying out the preprocessing to form a dynamic feature data set; the main control microcontroller carries out power response analysis and evaluates a channel response state based on the dynamic characteristic data set, generates a preliminary power distribution instruction, calculates a target current MI during preliminary power distribution, carries out thermal stress analysis, and constructs a thermal stress identification index Htt to carry out thermal accumulation risk evaluation; when a heat accumulation risk exists, calculating a channel target current MII when the secondary power supply is distributed, and adjusting the duty ratio of an MOSFET (Metal-Oxide-Semiconductor Field Effect Transistor) switch to carry out heat suppression regulation and control; and after the distribution is completed, calculating an energy utilization rate Nsys and executing energy efficiency state evaluation. According to the method, adaptive distribution and safe operation management of the multi-channel power supply of the robot are realized.

The invention discloses a distributed intelligent power distribution method and system for a power network, and belongs to the technical field of power distribution control, and the method comprises the steps: collecting multi-dimensional electrical parameters of a power generation node in real time, and carrying out the dynamic power monitoring at a feeder terminal of a transformer substation through an edge calculation node; executing line loss calculation and load prediction in the power distribution unit, generating a demand feedback instruction to a feeder terminal node, and triggering an adaptive power distribution strategy; and on the basis of a digital twin system of a regional dispatching center, credibility verification is carried out on operation decisions of all edge nodes, and global optimization compensation control is executed. The method has the remarkable advantages in the aspects of optimizing power distribution, reducing line loss, improving system stability and safety and achieving efficient energy utilization, and intelligent management of a power network becomes possible.

The invention relates to the technical field of intelligent power distribution control, and discloses an intelligent power distribution box control system based on the Internet of Things. The system comprises a power distribution parameter acquisition unit, a multi-dimensional electrical characteristic space construction unit, an overload risk simulation unit, a parameter dynamic optimization unit and a control instruction generation unit. The power distribution parameter acquisition unit acquires voltage waveform, current harmonic distribution, temperature distribution and the like in real time; the multi-dimensional electrical feature space construction unit classifies the parameters after preprocessing the parameters, extracts time-frequency domain features and fuses the time-frequency domain features into a multi-dimensional electrical feature space; the overload risk simulation unit marks an abnormal load interval, and matches historical and current features to generate a device degradation feature subset; the parameter dynamic optimization unit corrects the subset, simulates an overload risk diffusion path and outputs a feedback instruction; the control instruction generation unit generates an adjustment strategy and sends the adjustment strategy to the execution mechanism. According to the system, comprehensive perception and intelligent regulation and control of the power distribution operation state are realized, and the operation stability and adaptability of the power distribution box are improved.

The invention provides a real-time stability test platform and method for data acquisition of a power distribution control chip. The real-time stability test platform comprises a test power grid, an acquisition system, a to-be-tested control chip, a high-low temperature alternating box, an upper computer and a clock module, the upper computer is used for storing a plurality of test programs, controlling the high and low temperature alternating box and the test power grid to obtain different working conditions, calling the corresponding test programs according to the different working conditions, sending out corresponding control instructions, and performing stability analysis on the control chip to be tested according to the first test data and the second test data; and obtaining a stability test result. The problem that in the prior art, a single parameter testing method is difficult to comprehensively evaluate the stability of a control chip in an actual complex environment in real time is solved; according to the invention, the stability of the control chip is efficiently tested in real time, and the problems of difficult simulation of complex working conditions and multi-parameter coupling influence can be solved.

The invention belongs to the technical field of man-machine interaction and robot control, and particularly relates to a man-machine physical twin system based on multi-modal video analysis and adaptive mapping and a control method, and the system comprises a multi-modal collection unit which is used for collecting original video streams of human body actions, expressions and voices, and compensating and repairing dynamic shielding; the semantic analysis unit comprises an action analysis module used for extracting a human skeleton key point set object interaction track from the original video stream, and an expression / voice analysis module used for outputting a facial action unit coefficient and a voice text with an emotion label; the self-adaptive mapping unit is used for establishing human body-robot joint kinematics mapping, distributing control bandwidth in real time according to task types and degrading non-key modes based on network states to guarantee action continuity, and non-contact action capture is achieved through a pure vision scheme by eliminating dependence on a wearable sensor; and the problems of failure and the like of a traditional visual scheme under shielding and illumination variation are solved.

The invention relates to the technical field of fluid mechanics experiments and wind environment simulation, in particular to an integrated turbulent flow guiding wind speed distribution control wind wall and a control method.The wind wall comprises a mounting frame and a two-dimensional cross turbulent flow module, the mounting frame is of a rectangular frame structure, and the two-dimensional cross turbulent flow module is arranged on the mounting frame; the two-dimensional cross turbulent flow module comprises a plurality of turbulent flow shafts which are arranged vertically and horizontally, a plurality of turbulent flow blades are arranged on the turbulent flow shafts which are arranged vertically and horizontally, and air gaps used for air outlet are formed between the vertically-arranged turbulent flow blades and the horizontally-arranged turbulent flow blades. A fan is arranged right behind the position where each longitudinally-arranged turbulent flow shaft intersects with each transversely-arranged turbulent flow shaft. The control method is applied to the wind wall, and a wind speed gradient and turbulence gradient superposed complex wind field model is constructed by regulating and controlling the rotating speed of the fan and the rotating speed of the turbulence shaft and regulating the wind speed and turbulence in a partitioned and differentiated manner.

The invention relates to the technical field of control systems, in particular to a plate production control system with a heating function, which comprises a cross-domain data fusion module for acquiring deformation data, energy transfer data, electrical signal data, acoustic emission signals and stress distribution images through a distributed sensor network; generating a characteristic matrix containing a mapping relation of thermal resistance distribution, stress gradient and current density based on a physical field coupling model; the multi-parameter coupling control module synchronously outputs a temperature gradient adjustment signal, a pressure distribution control signal and a current density modulation signal according to the characteristic matrix; the heat flow coordinated regulation and control module combines conductive layer power data and temperature field characteristics; the digital twinning optimization module constructs a thermodynamic electric coupling virtual model, optimizes a weight coefficient through a genetic algorithm and returns the weight coefficient to the control module. Through cross-domain data association and multi-target cooperative control, heat conduction path stability and interface stress dynamic digestion are realized.

The invention provides a laser cutting production line task automatic allocation control method based on multi-device state coupling analysis, and belongs to the technical field of intelligent manufacturing and industrial automation. The method comprises the following steps: constructing a dynamic closed-loop control process through a central control scheduling system: receiving a task information packet of an MES; constructing an equipment state vector based on a real-time station state, and introducing a dynamic weight factor set to generate a weighted state vector; performing task triggering judgment through a coupling triggering judgment function in combination with the task dependency graph and historical task records; when the conditions are met, a task instruction is issued to the target station; and feeding back the state and updating the historical record after the task is completed. The invention further relates to AGV intelligent scheduling, visual positioning compensation, process parameter dynamic adjustment, predictive conflict detection, weight self-optimization and the like. According to the method, the production line cooperation efficiency is remarkably improved, manual intervention and system delay are reduced, and the method is suitable for an intelligent laser processing scene in which multiple devices run in parallel.

The invention provides a heavy duty gas turbine control system which comprises a signal conditioning module and a plurality of parameter control modules, and a rotating speed control module, a load control module, a temperature limit control module and an acceleration control module in the parameter control modules are all used for achieving closed-loop control according to the deviation between a set value and a corresponding observation value; the starting control module is used for acquiring a starting fuel quantity instruction through a designed control strategy; the IGV and VGVs control module obtains an IGV and VGVs angle instruction according to the turbine inlet temperature set value, the turbine outlet temperature set value and the deviation maximum value of the corresponding observation value; the fuel quantity control module obtains a total fuel quantity instruction based on a full working condition range fuel quantity control strategy; the fuel gas distribution control module is used for obtaining an opening degree instruction of each fuel valve according to the total fuel quantity instruction; the adaptability, the reliability and the usability of the control system in application scenes such as autonomous design and technical improvement are improved.

The invention discloses a wind and light energy storage power generation distribution control method and system. The method comprises the following steps: acquiring related parameters of a wind and light energy storage system; a multi-target control function is constructed based on a multi-target Harris eagle optimization algorithm, and system constraint conditions are combined in the directions of wind and light output fluctuation suppression, energy storage charge and discharge loss reduction and power grid supply and demand matching degree improvement; monitoring and adjusting the state of charge of the multi-mode hybrid energy storage unit through a wind storage combined wide-area SOC virtual synchronous control strategy, establishing association mapping and determining an initial threshold value; preliminarily distributing a power difference value between wind and light output and a power grid load by using the platform; iteratively optimizing the preliminary distribution power and then outputting target power; and sending a control instruction to realize real-time distribution. The number of the system is six, and all the units work cooperatively. According to the invention, the energy storage resource utilization efficiency and the system operation stability are improved, and the dynamic adaptation capability of the wind-solar energy storage system to the power grid load is enhanced.

The invention discloses a full-working-condition driving force optimal distribution control method based on an HCU, and relates to the technical field of new energy automobile control, and the method comprises the following steps: building a long slope energy flux analysis model, generating a time sequence envelope curve of recovery power based on a slope, an automobile speed and a wheel end inertia, and extracting a local peak value interval in the time sequence envelope curve; and in the peak value interval, based on the open-circuit voltage, pulse current and impedance spectrum information of the power battery, online identifying the absorption capacity of the power battery, correcting the upper limit of the state of charge of the power battery, determining a rechargeable current threshold value, carrying out coupling analysis on the threshold value and the recovery power envelope curve, and identifying the reverse current risk time period of the inverter. According to the method, real-time constraint on the absorption capacity of the power battery under the long-slope deceleration working condition is achieved, the inverter reverse irrigation risk is recognized, a peak clipping track and a transient discharge channel are constructed, micro-pulse, accessory absorption and super-capacitor shunting are fused, energy closed-loop control is formed, and the safety of the whole vehicle and the energy utilization efficiency are improved.

The invention discloses an ejector pin anti-fatigue strengthening method based on multi-section variable-temperature treatment, and relates to the technical field of ejector pin anti-fatigue strengthening, and the ejector pin anti-fatigue strengthening method comprises the following steps: austenitizing high-temperature quenching: heating an ejector pin to an austenitizing temperature, and then carrying out zoned cooling on the ejector pin; medium-temperature tempering and thermal-state mechanical strengthening are conducted, specifically, the ejector pin is tempered at the medium-temperature tempering temperature, and thermal-state shot blasting or laser shock is conducted on the ejector pin in the heat preservation period or after heat preservation is completed; intermediate low-temperature plasma nitriding: carrying out plasma nitriding in a nitrogen-hydrogen gas environment; subzero treatment: placing the ejector pin in liquid nitrogen; and finally, low-temperature tempering and cold-state mechanical strengthening are conducted. Through multi-section temperature gradient treatment, phase change distribution control over different temperature sections is achieved, too high internal stress and brittleness generated by one-time quenching are avoided, sudden size change and hot cracks induced by phase change are prevented, a controllable surface-core hardness and toughness gradient is formed, the surface crack initiation tendency is reduced, and the surface quality is improved. And the consistency and controllability of anti-fatigue basic conditions are improved.

The invention relates to the technical field of power distribution control, in particular to an intelligent power distribution cabinet control method and a power distribution cabinet, and the method comprises the steps: collecting operation parameters in real time, carrying out the hierarchical anomaly detection of each branch in the power distribution cabinet according to the obtained operation parameters, and setting the corresponding anomaly characteristics of each branch; identifying the composition of the abnormal feature corresponding to each branch, judging each composition of the abnormal feature, and setting an early warning parameter under the current abnormal power distribution; trend analysis is carried out according to the early warning parameters, the relative variation of the early warning parameters under the variation trend is identified, state deduction is carried out according to the relative variation, and a strategy control target under the variation trend is identified; the occurrence frequency of a target is controlled by using a strategy, the trigger condition of each branch is quantified, and a hierarchical control strategy is set based on the logic connection relationship of each branch under the trigger condition. The response speed and the control efficiency of power distribution cabinet control are realized.

The invention relates to the technical field of power distribution network dispatching, in particular to a power distribution network dispatching optimization method and device. Constructing a dynamic digital twin of the power distribution network to be dispatched, and reversely correcting a line impedance parameter and an equipment efficiency coefficient in combination with a twin simulation result; multiple scheduling strategies are rehearsed in parallel, and the optimal scheduling strategy is selected through weighted scoring; generating a multi-energy flow collaborative scheduling instruction set according to the optimal scheduling strategy; dynamically distributing a control task by utilizing an edge node; and performing differentiated load response in combination with the power consumption behavior classification of the user. Space-time synchronous acquisition of electricity-heat-gas data is realized by deploying a multi-energy-flow sensor group, a multi-energy-flow collaborative scheduling instruction is generated by combining reverse parameter correction and scene rehearsal optimization of a dynamic digital twin, and dynamic resource allocation is realized based on an edge node dynamic allocation control task and load classification response. The new energy consumption rate capability is obviously improved, and the carbon emission intensity is reduced.

The invention discloses an optical storage and charging dynamic power distribution control method and system based on AI prediction, and the method comprises the steps: collecting photovoltaic, energy storage, charging, power grid and environment multi-dimensional operation data through a sensor network, and obtaining a historical and real-time data set through preprocessing; training an AI joint prediction model by using the historical data set, and outputting a photovoltaic output and charging load demand prediction result; inputting system operation constraint condition parameters to delimit an optimization boundary; solving a power instruction reference value of each power module through a multi-objective optimization algorithm in combination with a prediction result and a constraint condition to realize global optimal distribution; and correcting the reference value based on the hardware operation parameters and the deviation between the predicted value and the real-time value, issuing an instruction, monitoring operation, and triggering fault protection. The method effectively solves the problems that a traditional system is rigid in power dispatching, low in photovoltaic consumption rate, large in energy storage life loss, remarkable in power grid impact, insufficient in prediction precision, high in energy transmission loss and weak in multi-target coordination.

The invention discloses a charging pile module dynamic power distribution control method and a related device, which are used for improving the stability and prolonging the service life of a charging pile during use. The method comprises the following steps: collecting real-time operation data of all charging pile modules in use in a charging pile layout matrix; performing power demand prediction on the real-time operation data according to historical operation records through a prediction model to obtain a prediction result; generating a virtual load mapping space according to the prediction result and an energy coupling relationship, wherein the virtual load mapping space is a mapping model of a charging pile node and an energy flow, wherein the charging pile node takes a charging pile module in use as a node; inputting the virtual load mapping space into a multi-agent collaborative optimization algorithm to obtain a target power value of a charging pile node so as to control a corresponding charging pile module according to the target power value; and recording the control feedback of the target power value as the historical operation record.

The invention discloses an energy-saving power distribution control system and method for a multi-load power distribution cabinet, and relates to the technical field of power system automation control, and the system comprises a main control module, a multi-path power distribution execution module, a load feature extraction module, a priority control module, and a strategy judgment and control execution module. The main control module, the multi-path power distribution execution module, the load feature extraction module, the priority control module and the strategy judgment and control execution module are electrically connected with one another; wherein the main control module is used for centrally managing operation data from a plurality of load branches, executing load state identification, controlling strategy calculation and issuing a power-off decision; the multi-path power distribution execution module comprises a plurality of intelligent circuit break control units corresponding to different load branches; according to the invention, the problems of extensive load perception, single energy-saving strategy, high control error rate and weak linkage protection capability in the prior art are solved.