2492 results about "Multiple device" patented technology

The invention relates to the technical field of smart power grids and artificial intelligence, in particular to a substation autonomous intelligent inspection method and system based on multi-modal data, and the method comprises the steps: obtaining inspection data of multiple modals, and generating fusion features; identifying system alarm information; performing intention recognition and task classification to generate an executable task sequence; generating a multi-device cooperative scheduling scheme; executing the multi-device cooperative scheduling scheme; iterative optimization is carried out; according to the intelligent inspection method provided by the invention, more accurate and more robust multi-mode perception and diagnosis are realized, and deep understanding of complex instructions and safe and efficient cooperation of multiple devices are also realized; and meanwhile, through dynamic re-planning and a verification type feedback learning mechanism, high real-time performance and robustness are ensured, and meanwhile, the system is endowed with the capability of iterative optimization.

The invention discloses a water-cooling energy consumption adaptive regulation and control method suitable for a data center, and the method comprises the following steps: obtaining a multi-dimensional operation parameter set of the data center in real time, and generating a real-time thermal load density distribution diagram reflecting the heat distribution condition in a machine room; calculating the overall thermal deviation degree and the local hot spot intensity, and solving through a dynamic energy efficiency optimization function to obtain a target system supply and return water temperature difference and a target cooling liquid flow; inputting into a hydraulic and thermodynamic simulation model, and generating an optimal multi-device coordinated regulation instruction set; and executing the multi-device coordinated regulation instruction set, and then performing parameter calibration on the hydraulic and thermodynamic simulation model. The method has the following advantages and effects that the thermal environment of the machine room can be sensed in real time, the energy consumption and heat dissipation requirements can be intelligently balanced, and multiple devices in the cooling system can be cooperatively regulated and controlled, so that the overall energy consumption of the cooling system is optimized while the local overheating risk of the machine room is thoroughly eliminated.

The invention relates to the technical field of data compression, in particular to an intelligent data compression method and system based on multi-protocol heterogeneous equipment interconnection. The method comprises the following steps: when it is detected that a new heterogeneous device applies to join a network, carrying out communication protocol real-time analysis and protocol conversion adaptation to obtain a heterogeneous device adaptation protocol; carrying out multi-device data stream receiving according to a heterogeneous device adaptation protocol, and generating data streams of a plurality of time windows; adaptive coding and multi-level compression are carried out on the data streams of the multiple time windows, and a multi-device adaptive compression mechanism is constructed; identifying compression load characteristics of each heterogeneous device, and performing dynamic task allocation to obtain an intelligent task allocation strategy; and driving real-time data intelligent compression operation based on an intelligent task allocation strategy and a multi-device adaptive compression mechanism. According to the invention, efficient and adaptive data compression of different devices is realized, and the data transmission efficiency and quality are improved.

The invention relates to the technical field of state monitoring, in particular to an SMT production line analysis method and system based on real-time data acquisition, and the method comprises the following steps: calling a multi-device operation log to judge a device connection relation, analyzing a track gauge and pressure change to mark a structure turning point, recognizing a path code of rate offset temperature control, and generating a direction sequence; the method comprises the following steps: establishing a device connection relation based on a time sequence and intervals of a running log, dynamically determining a process link, analyzing an abnormal signal sequence to generate a path identifier, matching a migration direction according to a state score change to predict a fault trend, and generating a fault trend prediction result. Marking a structure turning point based on direction combination of track gauge and pressure and packaging a structure section, judging a dominant path behavior based on direction combination of rate offset temperature control and a repetition condition, positioning a main attribution chain starting point based on abnormal signal starting and a coverage section, and outputting fault evolution prediction based on scoring sequence and migration direction matching.

The invention relates to the technical field of intelligent inspection control, and discloses a multi-dimensional intelligent inspection multi-device cooperative control method. The method comprises the following steps: synchronously acquiring a real-time operation parameter set of a plurality of monitored devices, wherein the real-time operation parameter set comprises a vibration spectrum, a temperature distribution map and a current waveform; performing multi-source heterogeneous data fusion processing on the real-time operation parameter set to generate a multi-dimensional feature vector; based on a preset collaborative optimization target, performing dynamic association analysis on the multi-dimensional feature vector to generate an equipment operation feature vector; and performing a matching decision according to the equipment operation feature vector and a preset cooperative constraint condition, and outputting a cooperative control instruction set. According to the method, through multi-dimensional data acquisition, fusion processing and dynamic association analysis, comprehensive perception and cooperative control of the multi-device operation state are realized, the coordination and reliability of device group operation are improved, and the method is suitable for multi-device cooperative operation and maintenance in a complex scene.

The invention belongs to the technical field of charging pile thermoelectric control, and particularly relates to a high-power liquid cooling charging pile charging power optimization scheduling method and system. The method comprises the following steps: collecting operation state parameters of a plurality of liquid cooling charging piles; identifying a target pile body in a charging state or a standby state; calculating a theoretical energy supply upper limit based on an electrothermal model; combining the vehicle charging demand, the priority, the battery state and the power grid load to construct a power scheduling model and execute distribution; power adjustment and redistribution are carried out when cooling abnormity or connection faults are detected; and finally, a scheduling control instruction is generated and executed in real time. The system comprises an information acquisition module, a state identification module, a model calculation module, a power distribution module, a dynamic adjustment module and an instruction issuing module. According to the invention, efficient, safe and dynamic power scheduling control of the high-power liquid cooling charging pile in a multi-device parallel connection scene is realized.

The invention discloses a multi-device cooperative online control system and method, belongs to the technical field of multi-device cooperative control, and aims to solve the problems of low synchronization precision and response lag during multi-device cooperative action. Triggering and responding execution equipment is accessed and identified, time reference deviation is calibrated, triggering state and auxiliary state data are received to construct a multi-dimensional state data set, triggering conditions are analyzed and judged, and a click-through triggering initial signal is generated and then compared with a sequence tail end signal timestamp so as to update a sequence and transmit the sequence to a central control platform in an incremental mode; measuring communication delay through a test signal, generating and iterating an online control instruction in real time to drive equipment to cooperatively act, identifying an optimization instruction according to the type, and dynamically updating through an updating interface; and constructing a correction data set based on the returned execution state feedback, and calculating an execution deviation to correct the online control instruction. Finally, high-precision synchronization and efficient response of cooperative actions of multiple devices are realized, and the stability and adaptability of an online control system are improved.

The invention discloses an access method, device and equipment and a computer readable storage medium, which are applied to the technical field of computers, and comprise the following steps: loading a consistency label list corresponding to an authorized access consistency domain; when an access request is initiated to a target consistency domain in the shared memory, performing permission verification on the access request through the consistency label list and the target consistency domain; when the permission verification is passed, determining whether an access conflict exists or not through a local access state cache and the type of the access request; if the access conflict exists, a controller arbitration engine is triggered, and the access request is executed according to an arbitration result; and if the access conflict does not exist, executing the access request. According to the method, the consistency label list and the access state cache are formulated for each device, the consistency problem existing when multiple devices access the shared memory in an existing system is solved, and efficient, low-conflict and flexible consistency guarantee can be achieved under the scene that multiple devices concurrently access the shared memory.

The invention discloses a smart home equipment state monitoring and abnormity early warning method and system, and relates to the technical field of smart home equipment state monitoring and abnormity early warning, and the method comprises the steps: constructing a dynamic space-time topological graph between home equipment; monitoring state data of each node device in the topological graph in real time; identifying a source abnormal node in the topological graph based on the state data and a preset abnormal rule; by taking the source abnormal node as input, executing fault propagation simulation deduction in combination with the direction and the weight of the edge to obtain a risk equipment node set and a fault propagation path; and based on the set and the propagation path, generating diagnosis early warning information used for positioning a fault root cause and representing a propagation link. According to the invention, through dynamic topology modeling, equipment physical connection and a logic dependency relationship are uniformly represented, root causes can be quickly locked and potential affected equipment can be predicted when multiple equipment are abnormal at the same time, prospective early warning of hidden cascading failures is realized, and operation and maintenance efficiency and system reliability are improved through a visual report.

The invention discloses an intelligent charging priority distribution system and method based on multi-device identification, and particularly relates to the technical field of charging priority distribution. Equipment identity and charging demand information are obtained through an intelligent identification technology, a priority score is calculated in combination with a preset weight parameter, the real-time performance of priority distribution is ensured by adopting a dynamic threshold adjustment strategy, power demand fluctuation in a short time in the future is predicted based on a load prediction algorithm of machine learning, power distribution is optimized in advance, and the power distribution efficiency is improved. The method comprises the steps of reducing instantaneous load impact, monitoring equipment power in real time in the charging process, comparing the equipment power with the maximum distributable power, and dynamically adjusting the charging power or switching the charging sequence through a self-adaptive power adjustment mechanism if abnormality is detected, so as to guarantee the stability of a power grid and the safety of the equipment, and the method can effectively improve the utilization efficiency of charging resources and reduce the energy consumption. Overload of a power grid is prevented, multi-device charging scheduling is optimized, and safety, reliability and intelligence of the charging process are ensured.

The invention discloses a method for increasing and suppressing the number of alarms through an alarm source, and relates to the technical field of communication network operation and maintenance, and the method specifically comprises the steps: constructing a network real-time topology, building a set membership graph between a router and a downlink device, and when the heartbeat overtime alarm of the downlink device occurs in the network, starting the router according to the set membership graph. And counting the proportion of the lost equipment in a sliding time window taking the parent router as the dimension, when the proportion of the lost equipment exceeds a threshold value, judging that the router is a root cause, sending out an early warning of the router meeting the condition of a root cause determiner, and shielding the overtime alarm of the router. According to the method, the root cause event of'all the downlink devices of the same route are disconnected 'is dynamically identified in the real-time alarm flow, and a high-severity router fault alarm is used for replacing a plurality of device heartbeat overtime alarms, so that the alarm noise is remarkably reduced, and the operation and maintenance efficiency is improved.

The invention discloses a multi-device cooperative control system and method for a construction site intelligent capsule bin, and relates to the technical field of industrial control, and the system comprises a data interface layer, a model construction module, a situation prediction module, a cooperative control unit, a self-adaptive cooperative optimization module, and a safety helmet positioning module. The method comprises a model construction step, a data acquisition step, a simulation prediction step, a situation judgment step, a cooperative control step and a self-adaptive cooperative optimization step. According to the method, unified data fusion and cooperative control are carried out on various devices, dynamic adjustment and strategy optimization of the devices can be carried out in time according to the actual situation of the site, the resource scheduling efficiency is improved, and the utilization efficiency of data is improved.

The invention relates to the technical field of industrial automation and machine vision, in particular to a peripheral signal control method for a visual detection system, and the method comprises the steps: creating a virtual signal node for each peripheral in an upper computer, and configuring a time sequence parameter for a device function node; dragging the link nodes through a graphical interface to form an executable signal sequence triggered by a product in-place signal; in response to an initial event, the signal control unit records the position P0 of the reference encoder, and plans and generates an absolute execution position point of a complete sequence control instruction at one time so as to trigger a peripheral action; and the upper computer graphically monitors the node state and records a sequence log, and supports triggering of a standby sequence and pose offset self-adaptive compensation based on image feedback in case of abnormality. The system is suitable for quality detection of industrial products such as glass bottle mouths, solves the high-precision synchronization problem of multi-equipment cooperative control, and improves the reliability, detection precision and deployment flexibility of a visual detection system.

The invention relates to the technical field of laser displacement meters, discloses a calibration method of a laser displacement meter for a Beidou device based on multi-data coupling, and effectively solves the problems of time delay compensation and data synchronization of cooperative work of multiple devices in a dynamic environment. According to the invention, when a carrier moves at a high speed or environmental parameters suddenly change, submillimeter-level positioning precision can still be maintained, meanwhile, data processing delay is controlled within a millisecond-level range, the reliability of a measurement system under a complex working condition is remarkably improved, and through double marking of a GNSS timestamp and a local clock, the measurement precision is greatly improved. And an accurate time deviation observation value is provided for a subsequent time delay compensation algorithm, so that a time-space unified data basis is established in a data preprocessing stage, and the feasibility of multi-source heterogeneous data fusion is remarkably improved.

The invention discloses a building pipeline node auxiliary positioning method applying three-dimensional digital management, and relates to the technical field of building construction, and the method comprises the steps: 1, collecting multi-source data of a multi-device terminal, fusing the multi-source data through adaptive federated filtering, and outputting the three-dimensional coordinates and component parameters of a node; 2, a BIM attribute graph of a building pipeline is obtained in advance, an actual measurement attribute graph is constructed based on the three-dimensional coordinates and component parameters of the nodes, deviation nodes are screened out by matching spatial positions and semantic attributes of the BIM attribute graph and the actual measurement attribute graph through a graph convolutional network, the deviation nodes are corrected through reinforcement learning, and a corrected calibration model is output; 3, automatically highlighting corresponding pipeline components in the BIM based on the three-dimensional coordinates of the nodes and the calibration model, and displaying design parameters and historical maintenance records in an overlapping manner; a correction strategy is automatically decided by using the deep Q network according to the deviation type and grade, intelligent and iterative correction of deviation nodes is realized, and manual intervention is greatly reduced.

The invention relates to the technical field of intelligent ports, in particular to an inland port unmanned shore tackle automatic scheduling method and system based on artificial intelligence, and the method comprises the steps: S1, collecting multi-source data in real time through a sensor network deployed in a port environment, and generating structured scheduling information after processing; s2, based on the structured scheduling information, generating an initial scheduling scheme by using an improved Q-Learning reinforcement learning model; s3, when a plan deviation event is detected, triggering a correction mechanism based on an improved particle swarm algorithm, and dynamically optimizing the initial scheduling scheme to generate a corrected scheduling scheme; s4, the scheduling scheme is issued to corresponding equipment to be executed, and the instruction execution state is monitored in real time; and S5, calculating an efficiency comprehensive score based on the port operation efficiency evaluation model. According to the method, a sensing-decision-correction-execution-evaluation full-process closed-loop intelligent scheduling system is constructed, so that multi-equipment collaborative automatic scheduling is realized, and the port operation efficiency, safety and resource utilization rate are remarkably improved.

The invention provides a parallel orientation control method and system for multiple welding devices, and the method comprises the steps: S1, collecting real-time three-dimensional space coordinate data and device attitude angle information from multiple operation devices through a multi-source sensor, and obtaining an initial positioning information set; s2, performing multi-source data fusion processing on the initial positioning information set by adopting a state estimation filtering algorithm to obtain a fused operation equipment position and attitude estimation result; s5, acquiring the corrected accurate equipment positioning information and the three-dimensional geometric model data of the target workpiece, and generating a task allocation scheme of multi-equipment collaborative operation; and S7, simulating a potential motion interference scene among multiple devices according to the preliminary movement path sequence and the device attitude adjustment specification, and judging whether a path conflict condition exists or not. According to the method, the positioning precision and the operation efficiency of multi-device collaborative operation are remarkably improved, path conflicts are effectively avoided, and the stability and the safety of coordinated control in a complex scene are ensured.

In an infusion pump system that includes a pump that may have a user interface for pump programming, one or more smartphones or other remote control devices that interface with the infusion pump, and / or an automated insulin delivery algorithm, there is a potential conflict between commands such as boluses being programmed on multiple devices and / or calculated by the AID algorithm at the same time. In order to avoid low glucose levels that could result from delivering multiple boluses from these various sources when only one bolus is needed, systems and methods disclosed herein provide a bolus permissions and prioritization scheme that prioritizes boluses programmed with the infusion pump and one or more remote control devices and calculated by a closed loop delivery algorithm.

The invention discloses a hardware equipment anomaly detection and fault prediction method and system, and relates to the technical field of server room operation and maintenance, and the system comprises a data collection module which is used for collecting CPU utilization rate, memory utilization rate, fan rotation speed and mainboard temperature indexes in real time from baseboard management controller (BMC) equipment; the graph causal modeling module is used for modeling the correlation and causal relationship among multiple equipment indexes to form a causal graph structure; the time sequence prediction module is used for predicting the equipment operation state in a period of time in the future through graph convolution and a causal attention mechanism; the anomaly detection module is used for generating an anomaly score and identifying a potential fault based on the deviation between a predicted value and a real value; and the alarm module is used for feeding an abnormal detection result back to the operation and maintenance system to realize early warning and decision support. The abnormal detection accuracy is remarkably improved, faults are predicted in advance, the interpretability of the causal relationship between equipment is provided, and the operation and maintenance risk of a machine room is reduced.

The invention relates to the technical field of energy equipment asset management, in particular to an energy equipment digital intelligent management method and system based on multi-protocol compatibility. The method comprises the following steps: constructing a protocol feature library, carrying out iterative updating, identifying a communication protocol of newly accessed energy equipment, generating a temporary analysis rule, converting analyzed equipment operation data, and uploading the converted equipment operation data; cross-device and cross-period collaborative analysis is carried out on the operation data of different energy devices, device fault precursor characteristics are identified, and fault early warning and root cause positioning are carried out; based on a digital ledger and a staged management and control strategy, carrying out standardized management on the whole life cycle link of the energy equipment; the system comprises an equipment multi-protocol dynamic adaptation module, a collaborative data analysis early warning module and an equipment full-life-cycle management module. Through the above mode, the protocol is dynamically adapted, the multi-device data is associated cooperatively, and the coupling fault identification precision between the devices is improved.

The invention discloses an automatic driving carrying equipment scheduling system and method for an industrial robot. The system comprises a plurality of automatic driving carrying devices, a central dispatching device and corresponding communication modules. The system adopts a multi-agent reinforcement learning framework and combines a graph neural network processing environment topological structure to realize dynamic path planning and multi-device collaborative scheduling; integrating an energy consumption prediction mechanism based on a Kalman filter, and bringing energy consumption factors into a task allocation decision; meanwhile, a fault-tolerant management mechanism based on a distributed account book and federated learning is established, and fault detection and rapid recovery are achieved. The technical modules are deeply coupled, and a unified collaborative optimization framework is formed through reward function design, utility function optimization and fault probability calculation of multi-agent reinforcement learning. According to the method, the problems of poor dynamic environment adaptability, isolated decision making of each module, extensive energy consumption management and the like in the prior art are effectively solved, and the overall efficiency, energy efficiency and reliability of a scheduling system are remarkably improved.

The invention relates to an intelligent home equipment intelligent control method based on deep learning, and the method comprises the following steps: S1, collecting environment data and the operation state information of each piece of home equipment in real time through various sensors disposed in an intelligent home environment, the environment data including temperature, humidity, illumination intensity and personnel activity conditions; the operation state information of the home equipment comprises an on-off state, a working mode and an energy consumption parameter of the equipment; all the collected data are transmitted to the central control system; s2, according to the environment data and the home equipment operation state information obtained in the step S1, the current operation mode of the smart home equipment is analyzed, and the operation mode of the smart home equipment at least comprises a basic function mode, an energy efficiency management mode and a multi-equipment interaction linkage mode; and S3, based on the current operation mode analyzed and determined in the step S2, generating an optimization control instruction for one or more smart home devices, and selecting different energy consumption driving modes.

The invention discloses a multi-device collaborative passenger flow statistical method and system, and the method comprises the following steps: presetting a unique identity label and a physical position index for devices, reading the unique identity label and the physical position index, and initializing the attribute information of the devices; a user datagram protocol broadcasting mechanism is started, and heartbeat information including the unique identity label, the physical position index and the online state is sent according to a preset period; monitoring the user datagram protocol broadcast message in the local area network, constructing and maintaining an online equipment list, and updating the online state of the equipment according to the heartbeat information receiving analysis condition; judging adjacent equipment based on a physical location index, and deciding whether to start a first boundary or a second boundary according to the online state of the adjacent equipment; and the decision result is transmitted to a passenger flow statistical algorithm to generate a shop-crossing detection line. According to the invention, multi-device collaborative passenger flow statistics dynamic boundary configuration is realized, the shop-crossing detection line is accurately generated, and the passenger flow statistics problems of fixed boundary configuration, easy missed counting and poor multi-device collaboration are solved.

The invention provides a task priority and equipment state linkage path adjustment method and related equipment, and relates to the technical field of intelligent distribution center systems. Task queue information, production system feedback information and equipment state information are obtained in real time, the dynamic priority score of each task is calculated based on the information, the urgency of a production critical path and the equipment suitability are integrated in the scores, and therefore it is ensured that priority calculation focuses on the core target of avoiding production interruption. Then, the system ranks the tasks according to the dynamic priority scores, and adopts a strategy of'high priority priority planning + path reservation '; the path of the high-priority task is preferentially planned and reserved on the space-time map, and path conflicts among multiple devices are avoided from the source. The low priority tasks are then directed to avoid these reserved areas. Finally, the planned conflict-free path is issued to the robot equipment for execution, and the overall operation efficiency and stability of the intelligent distribution center system are comprehensively improved.

The invention relates to the technical field of production state management, in particular to an LCD display screen production state collaborative management method based on the industrial internet, which comprises the following steps of: acquiring execution cycles and response delays of multiple devices, performing aggregation analysis, generating a rhythm synchronization parameter table, performing time sequence alignment to calculate time sequence offset and generating a time sequence calibration instruction; the method comprises the following steps of: analyzing current power and cycle deviation to form an equipment coupling trend, monitoring a scheduling rhythm correction execution sequence, dynamically estimating delay and optimizing a production state management cooperative control result, realizing cooperative measurement and difference identification through multi-equipment rhythm normalization aggregation, and improving state response precision and synchronization consistency through time sequence alignment; load coupling analysis balances energy consumption distribution and rhythm, whole-line scheduling correction realizes production rhythm balance and continuous operation, the resource utilization rate and the production efficiency are improved, process waiting and energy consumption fluctuation are reduced, and the system cooperation and self-adaptive regulation and control capability is enhanced.

The invention relates to the technical field of key generation and distribution, in particular to a multi-device automatic configuration encryption method and system based on Bluetooth. The method comprises the following steps: firstly, acquiring instruction information and attributes, RSSI values and historical pairing information of to-be-distributed network equipment, and providing a data basis for configuration; core equipment is screened through instruction and attribute matching and attribute similarity analysis, and equipment strongly related to user requirements is accurately positioned; historical pairing and RSSI value quantization equipment distance weights are fused, association conditions are analyzed, and a network structure is visually presented; analyzing the path length of the core equipment based on a graph structure, dividing closely associated target equipment groups, and determining the influence range of the core equipment; finally, the differentiated dynamic key is dynamically generated in combination with the equipment attribute, the distance weight and the instruction information in the group, the scheme effectively adapts to the dynamic change scene of the equipment through association analysis and dynamic adaptation, and the communication security and specificity are improved.

The invention discloses an industrial PLC control system, and belongs to the technical field of PLC control systems, and the system comprises a function distribution module which divides the production process of each type of circuit board into a plurality of logic steps, the logic steps are packaged and converted into independent function module modules, and a multi-device cooperation module carries out the scheduling data interaction with each processing device in real time. The edge calculation module is used for acquiring operation parameters, performing multi-device cooperative adaptive control on each processing device in the circuit board production workshop, predicting a fault risk, judging a risk level and performing fault positioning when a fault occurs according to the operation parameters of the processing devices, and generating a fault self-healing strategy to perform fault repair. Meanwhile, personnel and equipment interaction logs are recorded, fault event reasons are traced, the control logic reconstruction time can be shortened, the production change adaptability and the production reliability are improved, the equipment cooperation precision and the stability of the circuit board production process are improved, the fault processing time is shortened, and the production shutdown loss is reduced.

The application discloses an automatic assembling machine for piston rod assembly, comprising a rack and a connecting seat locking device, a piston rod clamping device, a sealing assembly detection device, a limiting gasket locking device, a nut locking detection device, a lifting device, a translation device and a central control unit arranged on the rack; the central control unit can control all actions of the connecting seat locking device, the piston rod clamping device, the sealing assembly detection device, the limiting gasket locking device, the nut locking detection device, the lifting device and the translation device. The application has the beneficial effects that: through the automatic design of the cooperation of multiple devices, the high precision, high efficiency and high reliability of the piston rod assembly are realized, and the problems of low efficiency, poor precision and easy damage in traditional manual assembly are effectively solved.

The invention provides an off-grid synthetic ammonia park electrolytic bath column level-energy storage-hydrogen storage collaborative optimization method based on rolling optimization, and relates to the technical field of energy storage and hydrogen storage collaboration. The method comprises the following steps: constructing an off-grid system architecture comprising wind-solar power generation, a plurality of rows of electrolytic cells, energy and hydrogen storage equipment and a synthesis ammonia device; a multi-device collaborative optimization strategy based on an eight-hour rolling time domain is designed, the system operation state is divided into high, medium and low working conditions through a working condition recognition mechanism, a current device operation scheme is actively adjusted according to wind and light power information of a next scheduling period, and collaborative regulation and control of energy storage and hydrogen storage are achieved. Compared with a traditional scheduling strategy, the collaborative optimization strategy provided by the invention improves the consumption rate of renewable energy sources of the system, reduces abandoned wind and light, improves the yield of synthetic ammonia, and verifies the effectiveness of the strategy.

An electronic device including a receiver configured to receive a first Subscriber Identity Module (SIM); a receiver configured to receive a second SIM; and circuitry configured to receive data from the first SIM; and send a request, to a first public land mobile network (PLMN), to register the electronic device to the first PLMN, wherein the request indicates that the electronic device is a multi-SIM device and the request includes multi-SIM assistance information, and wherein the multi-SIM assistance information informs the first PLMN of the electronic device's preference for multi-SIM operations.