3777 results about "Energy supply" patented technology

The invention relates to the technical field of energy scheduling, in particular to a multi-modal data fusion method and system based on energy scheduling and a storage medium. The method comprises the following steps: obtaining multi-modal data, and carrying out abnormal fluctuation feature extraction to obtain a space-time fusion abnormal feature labeling set; deducing a multi-objective optimization path according to the space-time fusion abnormal feature labeling set to obtain a dynamic scheduling decision map; performing edge node game equilibrium calculation according to the dynamic scheduling decision map to obtain a trusted scheduling verification chain; performing digital twinborn constraint optimization on the trusted scheduling verification chain to obtain a closed-loop scheduling digital twinborn body; compiling a dynamic scheduling instruction set based on the closed-loop scheduling digital twin to obtain an anti-disturbance energy scheduling strategy library; and obtaining real-time energy supply and demand data, and performing scheduling deviation tracing on the real-time energy supply and demand data according to the anti-disturbance energy scheduling strategy library to obtain an energy distribution decision. According to the invention, the efficiency and reliability of energy scheduling can be improved.

The present disclosure relates to the technical field of intelligent monitoring and management of power systems, and specifically relates to an intelligent collaborative power consumption regulation and control method, apparatus and system for source-grid-load-storage, an electronic device and a storage medium. Said system comprises an energy regulation and control center and energy regulation and control units provided in microgrids; the energy regulation and control units use a temporal attention mechanism-based LRCN dual-layer network combined model to predict power consumption amounts, so as to generate power consumption surpluses and shortages within a future preset time; and on the basis of the power consumption surpluses and shortages and latest current electricity prices of the microgrids, the energy regulation and control center uses a fusion multi-objective algorithm based on a Pareto front curve and a fuzzy algorithm to generate a microgrid collaborative power consumption regulation and control solution, and sends the regulation and control solution to the energy regulation and control units for execution, so as to ensure the balance of energy supply and demand of the microgrids. Therefore, the present disclosure achieves efficient, intelligent and refined energy management for microgrid clusters, reducing energy consumption and costs, and providing solid support for sustainable development of microgrids.

The invention relates to an electric energy comprehensive management control method for high and low load working conditions, and belongs to the field of energy supply system control. The method comprises the following steps: acquiring current operation information of an energy supply system, including a working condition mode, a target power demand and a battery state of charge (SOC) value, and further judging a working condition type and calculating a total power demand value of the system; on the basis, a power distribution scheme of a power generation unit and a battery is judged according to an SOC value and a power demand: under a normal working condition, the balance of power generation and battery charging and discharging is realized by setting an SOC threshold interval, and under an emergency working condition, the maximum rate discharging of the battery is dynamically controlled or the charging current is limited to cope with load fluctuation. According to the system, the bus voltage and the SOC are maintained in a safe range through a closed-loop regulation mode, so that the stability and the response capability of the energy supply system are improved.

Various electric energy supply vehicles and electric energy supply vehicle control system; a to-be-replaced electric vehicle and an electric vehicle battery replacement control system; a robot, a robot driving system, a carrying robot and a carrying robot control system; a plurality of programmable controllers, a plurality of wireless programmable controllers, a plurality of charging and replacing cabinets, a charging and replacing cabinet control system, a plurality of programmable controllers, a plurality of wireless programmable controllers, a plurality of to-be-replaced electric vehicles with different structures, a constructed electric vehicle finding mode, a plurality of electric vehicles to be subjected to battery replacement, a construction battery swapping station link is omitted, one electric energy supply vehicle can provide replenishment for a plurality of electric vehicles, an electric energy supply vehicle is put according to the amount of electric vehicles, invalid investment is avoided, and a vehicle owner does not need to center the battery again.

The invention provides a flexible preparation system and method for sustainable aviation fuel, and the system comprises a green power supply module which is used for outputting fluctuating green electric energy; the process execution device is connected with the green power supply module and comprises five process modules, namely an air carbon capture module, a co-electrolysis module, a Fischer-Tropsch synthesis module, a hydrogen production module and a hydrogenation refining module; the data acquisition module is used for acquiring the temperature, the pressure, the liquid level, the raw material input flow and / or the product output flow of each process module in the process execution device; and the decision control module is used for predicting the future power supply condition of the green electricity based on the historical weather data of the green electricity location, adjusting the distribution of the power in each process module according to the future power supply condition, and adjusting the temperature, pressure and / or raw material input flow in each process module. According to the invention, the cost, the reliability, the operation and maintenance performance, the product quality and the green power utilization rate can be substantially improved at the same time, and the flexible and stable operation of the system under the green power condition is realized.

The invention discloses a power supply method and a power supply system for on-line monitoring equipment of a lightning arrester, and the method specifically comprises the steps: activating a multi-source energy module according to a preset priority order based on the operation state and environment parameters of the lightning arrester, and supplying power to the on-line monitoring equipment; based on the output characteristics of the multi-source energy module and the residual electric quantity of the on-line monitoring equipment, a constant voltage-constant current hybrid power supply strategy in a conventional mode or an anti-interference power supply strategy in an abnormal mode is executed on the on-line monitoring equipment; and processing the historical leakage current, environmental temperature and humidity and vibration spectrum characteristics of the lightning arrester acquired by the online monitoring equipment through the LSTM prediction model, predicting the energy supply trend of the online monitoring equipment in the preset future time, and dynamically adjusting the working parameters of the online monitoring equipment according to the energy supply trend. According to the invention, stable power supply of the lightning arrester on-line monitoring equipment in a complex environment is realized, and the power supply reliability and the equipment availability are improved.

The invention discloses a distributed energy system source load coordinated optimization method based on a quasi-potential game method, and the method comprises the steps: constructing a distributed energy system model, inputting system parameters, and predicting renewable energy power generation and initial load demands. In a source side optimization stage, a leader layer potential function of a quasi-potential game is established by taking minimization of source side cost # imgabs0 # as a target, and an initial power generation plan is generated by comprehensively considering economical efficiency and carbon emission constraints; and then, based on a scheduling result, calculating a carbon potential epsilon t of each node and a dynamic carbon emission factor # imgabs1 # of each stage, optimizing a load side response based on an LCDR scheme, constructing a local potential function of a follower layer, reflecting a relationship between a user profit maximization target and carbon emission, and adjusting user behaviors through a distributed decision. And the updated load demand is fed back to the source side, and the source side optimizes the output plan of each unit based on the updated load, so that an iterative process of source side potential function optimization-load side equilibrium response is formed, and an optimal scheduling strategy and scheduling result of the energy supply side are obtained. According to the framework, the global consistency requirement of a traditional potential game is relaxed, independent optimization of source-load two sides under the guidance of respective potential functions is allowed, and a Nash equilibrium state is finally achieved only by ensuring monotonous convergence of total potential energy of a system in an iteration process. According to the method, the convergence advantage of the potential game is reserved, the method is also adapted to the characteristics of a source-load heterogeneous decision subject, efficient consumption of renewable energy and collaborative optimization of carbon emission are realized through bidirectional transmission of the carbon potential signal, and the overall efficiency of the system is remarkably improved.

The invention relates to a virtual power plant scheduling method considering source-load coupling and multi-agent game. The method comprises the following steps: establishing a multi-temporal-spatial-scale model of a multi-energy system in a virtual power plant; the uncertainty of the source load is quantified; on the basis of quantification of source load uncertainty and a multi-temporal-spatial-scale model, a multi-subject scheduling model under a master-slave game framework is constructed, and in the multi-subject scheduling model, a VPP operator serves as a leader, and the market is regulated and controlled through dynamic electricity price and heat price; an energy supply aggregator, a user side aggregator and a carbon processing aggregator are used as followers, unit output, load adjustment and carbon processing strategies are optimized respectively, the two parties perform multi-stage dynamic gaming to form balance, and the user side aggregator comprises CSRLA and EVA; and solving the multi-subject scheduling model to obtain a virtual power plant scheduling optimization strategy. Compared with the prior art, the method has the advantages of realizing dynamic balance of interests of multiple parties, privacy protection and the like.

The invention discloses a self-sensing monitoring method, system and equipment based on a lightning arrester, and relates to the technical field of power equipment monitoring. The self-sensing monitoring method, system and equipment based on the lightning arrester comprises the following steps: S1, collecting lightning stroke data in real time through multi-sensing fusion, and performing data cleaning and standardization processing on the lightning stroke data; s2, adopting a three-mode sensing and three-source power supply cooperation mechanism to realize state-driven adaptive sensing and energy path switching; s3, automatically scheduling a communication path according to a communication type and link quality, dynamically analyzing and compensating transmitting power, and completing authentication encryption and multi-hop secure transmission; s4, lightning stroke characteristics are extracted, an equipment life prediction model is constructed, residual life prediction is realized, and equipment health grade division and operation strategy adjustment are carried out according to the residual life prediction model; and S5, calculating an electric leakage deviation value by reconstructing a current waveform, triggering graded early warning and linking a communication power and energy supply strategy. The problem that the operation of a power system is affected due to large leakage current monitoring errors is solved.

The invention discloses a fuel cell coupled flow battery energy supply system and an operation control method thereof. The energy supply system comprises a basic energy supply unit, an energy storage peak regulation unit, a renewable energy power generation unit, an electrolytic hydrogen production unit, a hydrogen storage unit, a first-stage waste heat recycling unit, a second-stage waste heat recycling unit and a heat storage unit. The basic energy supply unit is used for providing a basic power load of the target building group; the energy storage peak regulation unit is used for providing fluctuation power load of the target building group; the first-stage waste heat recycling unit receives first-stage waste heat generated by power generation of the fuel cell and is used for indoor heating or indoor refrigeration. And the second-stage waste heat recycling unit directly receives the first-stage waste heat or second-stage waste heat from the first-stage waste heat recycling unit and is used for preheating the electrolyzed water and / or the hydrogen storage unit. By arranging the first-stage waste heat recycling unit and the second-stage waste heat recycling unit, waste heat is utilized in a multi-stage mode according to requirements, and the waste heat utilization rate is high.

The invention discloses a morning orbit computing power satellite, and belongs to the field of aerospace technology and space infrastructure. The satellite comprises a satellite platform and a computing force load arranged on the satellite platform. The satellite platform is provided with a condensation type energy system and a space pump drive fluid loop system. The condensation type energy system adopts an expandable condensation type solar cell array to generate power, switches a power supply mode according to an illumination period and an earth shadow period of a morning and night orbit, and supplies power to computing force loads and platform equipment. The space pump drive fluid loop system adopts an expandable flexible radiation cooling plate for heat dissipation, heat dissipation is conducted on computing force loads through a fluid loop, and a heating assembly is arranged to prevent a working medium from being frozen under the low-temperature working condition. Through the expandable structure and the orbit environment adaptability design, continuous energy supply and effective heat management are provided for the computing power load in the morning and night orbit environment, and high-power-consumption computing power load in-orbit stable operation is supported.

The invention discloses an intelligent energy consumption distribution method for a multi-source energy system. The method comprises the steps of energy supply data fusion, dual-channel joint prediction, energy response lag correction, multi-objective optimization and intelligent energy consumption distribution. The invention relates to the technical field of data processing of power management and resource scheduling, and the method comprises the steps: carrying out the unified collection and archiving of operation control data and environment information of power grid energy, distributed photovoltaic energy and an energy storage system, and constructing an energy supply fusion data set; respectively extracting energy availability and user load characteristics by adopting a double-domain attention decoupling fusion joint supply and demand prediction method, and realizing double-channel joint modeling; modeling, estimating and correcting response lags of different energy sources in combination with a dynamic response curve reconstruction method; and further constructing a layered target penalty function containing real-time response error, economic cost, carbon emission and response penalty terms, and embedding the layered target penalty function into a particle swarm optimization algorithm to obtain an energy distribution strategy under multi-target optimization.

The invention relates to the technical field of electric power energy monitoring, and discloses a remote monitoring analysis method and system based on electric power equipment operation data, and the method comprises the steps: collecting the multi-element energy operation parameters of a multi-source energy system and the multi-element energy use parameters of a user side in real time; after the collected data are preprocessed, the preprocessed equipment operation state data are evaluated, and an electric power equipment operation state index is obtained; whether equipment faults exist or not is judged according to power equipment operation state indexes, virtual mapping of a multi-source energy system is constructed, and system operation conditions under different energy scheduling strategies are simulated in real time by combining user energy demand prediction and external environment changes; when potential energy supply abnormity or equipment failure is detected, a multi-stage early warning mechanism is triggered, and a decision report including abnormity positioning, reason analysis, energy scheduling optimization and equipment maintenance disposal suggestions is generated, so that potential problems can be found in time, and the stability and reliability of energy system operation are improved.

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 belongs to the technical field of energy management optimization, and discloses a micro-grid system energy management optimization method and system based on big data analysis. The method comprises the following steps: constructing a multi-source time sequence data processing model, an energy supply and demand prediction model and an energy management optimization model of a micro-grid system; updating the model according to an alliance learning mechanism; performing data processing on the real-time multi-source time sequence data; acquiring a real-time topology network and a dynamic data model; energy supply and demand prediction is carried out, and an energy management optimization scheme is generated; and visualizing the real-time energy supply and demand prediction result and the real-time energy management optimization scheme. The problems that in the prior art, the data processing capacity is limited, model updating is not timely, real-time performance is lacked, prediction precision is insufficient, and an optimization scheme is not flexible enough are solved.

The invention relates to the technical field of downhole operation control, in particular to a downhole operation platform control system and a crane, and the system comprises a task identification module, a demand index module, a power sequencing module, a rhythm switching module and a command reconstruction module. According to the method, through accurate recognition of the structure state and parameter linkage, accurate judgment of the initial operation stage is achieved, false starting and false action of the platform are avoided, coupling analysis between operation data can dynamically set the scheduling priority, it is guaranteed that key tasks are executed in advance, coordination is improved, energy supply conditions are judged through power parameter fusion, and paths are distributed according to needs; the energy utilization efficiency is enhanced, stage rhythm conversion achieves stable switching based on action states and logic mapping, action disjunction is prevented, finally, control instructions are rearranged through feedback time delay and an execution sequence, an efficient and ordered response mechanism is formed, the overall operation efficiency, stability and the intelligent level are improved, and the risk of manual intervention and operation imbalance is reduced.

The invention discloses an urban energy network intelligent allocation method and system, and the method comprises the steps: obtaining building energy consumption data and energy supply network topology information, building a supply and demand matching reference, recognizing a load peak value dense time period and a peak clipping and valley filling potential region, and exporting transferable load data to form a regional supply and demand distribution diagram; generating a peak shifting adjustment space in combination with the user response delay duration and the equipment start-stop period; performing gap matching analysis on the regional supply and demand distribution map and the peak shifting adjustment space, creating a hierarchical regulation instruction set, and differentially generating an instant response instruction and a delay response instruction; a regulation and control coordination parameter is formed through coordination configuration of the peak shifting revenue coefficient and the instant response instruction; finally, a regulation and control execution range is determined, cost benefit evaluation is implemented, an urban-level energy scheduling execution scheme is formed, accurate matching and efficient scheduling of urban energy supply and demand are achieved, and comprehensive and efficient scheduling decision support can be provided for application scenes such as an intelligent power grid, regional heat supply and comprehensive energy service.

The invention relates to the technical field of smart home, and discloses a smart home real-time energy consumption monitoring and dynamic distribution system, which comprises a data acquisition module, a spatial-temporal feature fusion module, an energy distribution module and a dynamic control module. The data acquisition module acquires household energy supply and demand real-time data, the spatial-temporal feature fusion module processes the data to generate an energy state feature matrix, the energy distribution module constructs a model to optimize an energy distribution sequence according to the matrix, and the dynamic control module constructs a hierarchical control framework to complete energy dynamic distribution. According to the system, energy can be accurately and efficiently distributed, and the power utilization cost is reduced according to a real-time electricity price and equipment energy consumption optimization strategy. The service life of the energy storage battery is effectively prolonged by considering the charge-discharge cycle times of the energy storage battery. Meanwhile, the decision-making layer, the scheduling layer and the execution layer cooperate to improve the intelligent level of equipment management. The execution layer introduces a fault-tolerant mechanism to enhance the reliability and stability of the system, ensure stable supply of household energy and improve the user experience.

The invention discloses a two-phase cold plate liquid cooling ORC waste heat recovery and photovoltaic cooperative energy supply system and method, and relates to the technical field of energy management and waste heat utilization. The two-phase cold plate liquid cooling ORC waste heat recovery and photovoltaic cooperative energy supply system and method comprises the following steps that S1, thermal parameters and electric power states related to cooperative energy supply are collected, and a thermoelectric cooperative input data set is constructed and preprocessed; s2, the supply and demand difference of the high-temperature steam in the main condensation branch and the ORC branch is recognized; s3, coordinating a photovoltaic power supply structure and a cooperative energy supply sequence, and judging the matching degree of cooperative energy supply to a load; and S4, evaluating a cooling, heating and power cooperation and double-source coupling state in combination with a load matching condition and an output behavior. The problems that in an existing two-phase cold plate liquid cooling structure, high-temperature steam is not recycled, photovoltaic power generation does not participate in linkage energy supply, the power source is single, waste heat waste is serious, and energy collaboration is insufficient are solved.

The invention, which relates to the technical field of energy system regulation and control, provides a seasonal multi-scene-driven adaptive regulation and control system for a park integrated energy system, comprising a seasonal feature intelligent extraction module, a multi-scene plan library construction module, a three-party non-cooperative game model module and an adaptive execution module. The seasonal feature intelligent extraction module is used for decomposing historical load data, extracting seasonal feature parameters and generating an energy supply priority sequence; the multi-scene pre-arranged plan library construction module is used for constructing a regulation and control pre-arranged plan for coping with electricity price fluctuation, equipment faults, extreme weather and production scheduling, and realizing multi-target dynamic balance; the three-party non-cooperative game model module is used for defining strategy spaces and revenue functions of an energy supply side, an energy consumption side and an energy storage side; according to the method, through dynamic operation of the seasonal feature vector and the load incidence matrix, accurate adjustment of the energy supply priority is achieved, the refrigeration power supply response time in summer is shortened, and the waste heat recovery efficiency in winter is improved.

The invention provides a building energy consumption real-time monitoring and carbon emission evaluation method based on digital twinning, and the method comprises the steps: obtaining regional energy supply real-time data and building group load demand data, predicting an energy supply fluctuation trend and a load change trend, and obtaining a short-term supply and demand dynamic prediction result; adjusting the operation mode of the building group combined cooling heating and power system in real time according to the mode switching optimization scheme, dynamically matching the output change of the distributed energy, and feeding back the output change to the digital twinborn model; carbon emission data is extracted from the optimized load distribution scheme, a digital twinborn model is used for predicting the total carbon emission amount and peak value change trend, the threshold value and constraint of carbon emission control are adjusted, and a final energy scheduling scheme is generated; and obtaining operation data according to the final energy scheduling scheme, calculating the energy utilization efficiency and the carbon emission reduction amount of the building group through an energy efficiency evaluation method preset in the digital twin model, and obtaining an execution effect evaluation result of the scheduling scheme.

The invention relates to the technical field of intelligent power grids, in particular to a micro-grid energy storage optimization method and system based on big data analysis, and the method comprises the steps: obtaining the comprehensive prediction power generation through the prediction segmentation time, a wind power generator set and a solar power generator set, and obtaining the analysis power based on the prediction segmentation time and the comprehensive prediction power generation, an energy storage battery parameter set is obtained, if the analysis electric quantity is larger than or equal to a storage electric quantity threshold value, a target storage battery pack is retrieved from the energy storage battery packs through the energy storage battery parameter set, active equalizing charging is conducted on the target storage battery pack, and an updated storage battery pack is obtained; and after it is confirmed that a preset target energy supply battery pack is retrieved in the energy storage battery packs by using the analysis electric quantity and the energy storage battery parameter set, power is supplied by using the target energy supply battery pack, and an updated power supply battery pack is obtained. According to the method, the energy storage of the micro-grid can be accurately and intelligently optimized.

The invention discloses a waste heat-demand two-stage optimization design method for a multi-energy combined supply Carnot battery system, and belongs to the field of energy storage and comprehensive energy utilization, and the method comprises the steps: determining the energy demand and waste heat source condition of a target energy supply object; constructing a multi-energy combined supply Carnot battery energy storage system model composed of a multi-energy conversion subsystem and a Carnot battery subsystem; the method comprises the following steps: performing parameter optimization on performance expressions of an energy storage loop and an energy release loop of a Carnot battery subsystem through first-layer optimization, and determining Carnot battery system performance and state parameters of each point under unit cold and heat source flow; and through second-layer optimization, multi-objective optimization is carried out on the efficiency of the first law of thermodynamics, the efficiency of the second law of thermodynamics and the economical efficiency of the system, and the optimal heat source flow input into the energy storage loop, the optimal heat storage water flow input into the multi-energy conversion subsystem, the optimal heat storage water flow input into the energy release loop and the corresponding overall performance of the Carnot battery system are determined.

The invention relates to the technical field of energy system control, and discloses a distributed cooperative fault-tolerant control method for a multi-energy-station cooling and heating system, and the method comprises the steps: enabling each energy station to measure and calculate a residual error based on a physical model and a sensor, forming a normalized health index, and carrying out the neighborhood broadcasting; carrying out robust anomaly judgment by utilizing a neighborhood median and a median absolute deviation, and isolating an abnormal site; cost coefficients are automatically generated for available sites according to equipment maneuverability, and control redistribution of minimum disturbance is solved and implemented through distributed consistency optimization; an exponential weighting updating mechanism of a residual error sequence is adopted to carry out online self-adaption on a noise baseline and a judgment threshold value so as to realize closed-loop self-calibration; when sensor abnormity, equipment errors or individual station faults occur in the multiple energy stations which work cooperatively, distributed rapid identification is achieved, faults are isolated, energy supply is redistributed with minimum disturbance, system control requirements are met, and equipment safety constraints are kept.

The invention relates to the technical field of computer systems based on specific calculation models, and discloses a control method and system for an intelligent calculation center comprehensive energy supply device, and the method comprises the steps: collecting the operation data of energy supply equipment and an environment sensor in real time through an SCADA system, and carrying out the preprocessing; based on the collected data and simulation data generated by a simulation environment, performing offline mixed training on the reinforcement learning model to generate an energy scheduling strategy; inputting a real-time state into the trained reinforcement learning model to generate a preliminary scheduling instruction, performing security verification and interpretability analysis by using a large language model, and optimizing a strategy; and fusing the preliminary scheduling instruction with the suggestion of the large language model, generating a final scheduling command through the energy router control unit, and issuing the final scheduling command to the energy supply equipment for execution. The problems that in the prior art, black box decision making and simulation are not accurate, and experience is difficult to solidify are solved, and the purposes of decision making transparency, simulation high fidelity and experience structuring are achieved.

An electromechanical brake system (10) includes a first energy supply apparatus (20) and a second energy supply apparatus (21), a first system control device (30) and a second system control device (31), a plurality of electromechanical brake actuator devices (41), and a first plurality and a second plurality of electronic brake control systems (40a, 40b). Each of the electronic brake control systems is set up to control one of the electromechanical brake actuator devices. The first energy supply apparatus is connected to the first system control device and to each of the first electronic brake control systems, and the second energy supply apparatus is connected to the second system control device and to each of the second electronic brake control systems. A further control device (32, 47) may be connected to at least one of the first electronic brake control systems or one of the second electronic brake control systems.

The invention relates to the technical field of automobile energy supply, in particular to a solid hydrogen storage-fuel cell integrated power assembly system based on dual-mode hydrogen supply, which comprises a hydrogen supply path identification module, a hydrogen storage unit state monitoring module, a linkage path switching module, a fuel cell load matching module and a safe hydrogen discharge regulation and control module. According to the method, the hydrogen supply pressure difference value is obtained by dynamically comparing the pressure of the cavity of the hydrogen storage tank with the pressure of the hydrogen inlet of the fuel cell, the current hydrogen supply path state can be accurately recognized in the early stage, rapid judgment of the hydrogen supply mode and accurate control of path switching are achieved, whether the risk of hydrogen supply interruption exists or not can be effectively screened, and the reliability of hydrogen supply is improved. The switching reliability of a hydrogen supply channel is improved through cross comparison of key state signals of a main channel and a standby channel, and instant response and energy consumption optimization of hydrogen discharge safety regulation and control are guaranteed through a linkage feedback mechanism between the hydrogen concentration change rate in unit time and catalytic converter control power.

The invention discloses an automatic control system for a railway bridge static load bending test, which relates to the technical field of bridge engineering detection and comprises an intelligent sensing layer, a digital twin engine, an intelligent control layer, a trusted data management layer, a green energy supply layer and a man-machine interaction layer. The equipment health prediction model integrates oil temperature, vibration and current data to predict mechanical faults, performs early warning 30 minutes in advance, automatically switches to a slow loading mode when the crack propagation rate exceeds the limit, breaks through a passive protection mode of single threshold alarm, realizes multi-dimensional active protection from structural damage to equipment degradation, and drives finite element model updating through sensor data. The simulation prediction reverse correction loading strategy and the RBF neural network online correction material parameters are simulated and predicted, parameter iteration is triggered when the deviation is larger than a set value, the island problem that a traditional BIM only uploads data in a one-way mode is solved, closed-loop verification of test data and design parameters is achieved, and simulation precision is improved.

The invention discloses a photovoltaic photo-thermal coupling hydrogen production system control method for a hydrogen-burning heavy truck traffic network. The method comprises the following steps: S01, collecting operation data of a photovoltaic array, an electrolytic cell and a hydrogen storage tank; s02, based on a model prediction control algorithm, establishing a multi-objective optimization model containing an objective function and constraint conditions; s03, merging the sub-objective functions into a comprehensive objective function through a linear weighting method; s04, applying constraint conditions; S05, performing rolling optimization calculation by adopting a model prediction control algorithm; s06, outputting an optimal control variable; s07, adjusting corresponding parameters in the system; s08, monitoring the running state of the system; s09, whether the system meets constraint conditions is judged, according to the control method, through multi-target collaborative optimization and precise constraint control, the performance, efficiency, economical efficiency and safety of the photovoltaic photo-thermal coupling hydrogen production system can be remarkably improved, and clean, efficient and stable hydrogen energy supply is provided for a hydrogen combustion heavy truck traffic network.

The invention relates to the technical field of power management, in particular to a multi-source data fusion photovoltaic power scheduling control system, which comprises a sensing extraction module, a disturbance identification module, an offset trend analysis module, a path switching module and a frequency band suppression module. According to the method, a disturbance pre-judgment interval is identified by constructing a time derivative sequence and combining illumination and wind speed trend change in a continuous period, a disturbance time period is accurately discriminated, the disturbance interval is confirmed and disturbance characteristics are extracted through conjoint analysis of photovoltaic and energy storage current change trend and grid-connected point fluctuation amplitude, and the disturbance accuracy is improved. An offset trend curve is formed by calculating photovoltaic and energy storage current change differences, the energy supply offset degree is judged in real time to trigger scheduling conditions, dynamic suppression adjustment is performed on regulation and control signal parameters according to spectrum energy distribution, the accuracy and timeliness of disturbance recognition, energy supply offset judgment and frequency band regulation and control are improved from multiple levels, and the energy storage and energy supply efficiency is improved. And more stable and efficient optical storage combined scheduling control is realized.