533 results about "Hydrogen consumption" patented technology

The invention discloses a power distribution method and system based on fuel cell multi-stack health state difference, and belongs to the technical field of fuel cell application. The specific method comprises the following steps: monitoring operation parameters of a plurality of fuel cell stacks through a sensor; obtaining the health state of each fuel cell stack and the health state of the lithium battery; establishing a hydrogen consumption model, a fuel cell SOH loss model, a multi-stack SOH difference equivalent loss model, a lithium battery SOH loss model and a lithium battery start and end SOC loss model; the calculation loss is converted into equivalent hydrogen loss, and a target function model is constructed; and optimizing the target function by using a reinforcement learning algorithm, distributing power output of the fuel cell and the lithium battery according to the current required power and the health state through an energy management system, and regularly updating parameters of a parameter identification module and a model to realize dynamic optimization. The method can identify the life difference between multiple piles, balance the life difference to realize multi-pile performance balance and improve the overall life of a multi-pile system.

The invention provides a safety check and real-time prediction linkage system and method for a hydrogen-doped natural gas pipeline network. The system comprises a digital twin module, a detection module, a hydrogen-doped pry module and a consumption prediction module, the detection module comprises a terminal user, a thermometer and a flow meter, the thermometer is used for collecting temperature data of the terminal user, the temperature data is transmitted to the digital twin module, the flow meter is used for collecting load data of the terminal user, and the load data is transmitted to the consumption prediction module; the use amount prediction module predicts the hydrogen-doped natural gas use amount of the user per hour in real time according to the data collected by the detection module; the hydrogen doping pry module controls the mixing ratio of hydrogen to natural gas according to the output result of the dosage prediction module; and the digital twin module checks the safety operation feasibility and the hydrogen doping ratio by calculating the physical property parameters of the hydrogen-doped natural gas. Accurate prediction, dynamic scheduling and safety checking of the natural gas and hydrogen consumption are achieved, and it is ensured that the energy use efficiency is improved.

The invention discloses a fuel cell hybrid electric heavy truck power source optimization design method and system, and the method comprises the steps: building a target function of the total cost per unit travelled distance in a life cycle based on the basic parameters of a fuel cell, a power cell and a super capacitor, and the degradation parameters and hydrogen consumption of the fuel cell and the power cell; an energy management strategy of the fuel cell hybrid electric heavy truck is established based on the average required power of the truck and the SOC of the power cell and the super capacitor; and a cancer cell competition and transfer algorithm is adopted, under an energy management strategy, a minimum objective function meeting the driving working condition is searched, and energy size optimization is completed. According to the method, the power source of the fuel cell hybrid electric heavy truck is subjected to global optimization design by adopting the cancer cell competition and transfer algorithm, the service life of the power source is prolonged while the power performance of the truck is guaranteed, the manufacturing cost, degradation cost and hydrogen consumption of a hybrid power system are remarkably reduced, and the energy efficiency of the system is improved.

The invention discloses a hydrogen fuel cell hybrid electric vehicle energy management method based on robust optimization, and the method comprises the following steps: building a vehicle model: building a longitudinal dynamic model of a hydrogen fuel cell hybrid electric vehicle, determining a vehicle demand power model, and building an evaluation function of instantaneous hydrogen consumption, constructing an output power model of the hydrogen fuel cell and the capacitor; performing uncertainty analysis on the hydrogen fuel cell hybrid electric vehicle, determining uncertain parameters in the vehicle model, and constructing an uncertainty set of the uncertain parameters; the method comprises the following steps: constructing an sLSTM vehicle speed prediction model through vehicle historical speed data, predicting a future driving speed, analyzing the uncertainty of the prediction model, and outputting a prediction speed error in a current prediction time domain; and according to the optimization target, constructing a target function for minimizing the hydrogen consumption, solving the target function by applying a robust optimization algorithm, and outputting a first control result of the optimal control sequence.

The invention provides a wind power hydrogen production energy scheduling method and a wind power hydrogen production energy scheduling system. The wind power hydrogen production energy scheduling method comprises the following steps: predicting the wind power, the hydrogen load and the electricity price of a wind power plant in a wind power hydrogen production system in a future time period; and based on the predicted wind power, the predicted hydrogen consumption load and the predicted electricity price, determining energy scheduling among a plurality of components in the wind power hydrogen production system, so that at least one of the net income and the renewable energy consumption rate of the wind power hydrogen production system within the predetermined time period is maximum.

The invention discloses a hydrogen fuel cell unmanned aerial vehicle energy management and trajectory tracking cooperative control method, and belongs to the field of hydrogen fuel cell long-endurance unmanned aerial vehicle energy management and trajectory tracking control. According to the method, the influence of external disturbance and model uncertainty is studied, fixed time control and active disturbance rejection control principles are introduced, a double-closed-loop unmanned aerial vehicle trajectory tracking method based on fixed time active disturbance rejection control is designed, and effective unmanned aerial vehicle working condition demand information and power control output in a time domain are obtained; based on demand information generated by trajectory tracking control, factors such as hydrogen fuel cell temperature difference, lithium battery SoC maintenance, hydrogen fuel consumption and energy source service life are comprehensively considered, a life attenuation cost function and an energy consumption cost function based on minimum equivalent fuel consumption are established, and an intelligent energy management cooperative control method fusing trajectory tracking control is designed. Hydrogen consumption is reduced, and the cruising ability of the whole machine is improved.

The invention discloses an OPSA-ECMS hydrogen fuel hybrid power unmanned aerial vehicle energy management method, and the method comprises the steps: building an unmanned aerial vehicle hybrid power system model employing a hydrogen fuel cell as a main power supply and a lithium ion battery as an auxiliary power supply, and building an energy management system model. According to the method, the OPSA and the ECMS are combined, the minimum hydrogen consumption and the highest efficiency are taken as optimization objectives, the OPSA is adopted to calculate an optimal reference energy distribution scheme in an off-line manner under a known preset route, and the ECMS is adopted to optimize the reference energy distribution scheme in an on-line manner in the task execution process of the unmanned aerial vehicle, so that the optimal energy distribution of the system is realized. According to the method, OPSA off-line calculation and ECMS on-line optimization are combined, the high energy density of hydrogen fuel and the quick response characteristic of the battery are exerted to the maximum extent, and the overall energy utilization efficiency is improved.

The invention discloses a fuel cell hybrid train energy dispatching method and system. The method comprises the steps that S1, a hydrogen fuel hybrid train power system model is constructed; s2, acquiring required power in a train running process, and decomposing the required power into a low-frequency component and a high-frequency component by using a low-pass filter with adjustable cut-off frequency; constructing a double-layer reinforcement learning agent, and performing real-time dynamic optimization adjustment by taking the cut-off frequency of the low-pass filter as an action variable of the reinforcement learning agent; s3, designing a multi-objective reward function and a system total cost function, and synchronously optimizing fuel cell efficiency, fuel cell power fluctuation, hydrogen consumption and lithium battery SOC to approach initial values; and updating double-layer reinforcement learning agent network parameters through a depth deterministic strategy gradient algorithm, and finally outputting a real-time power distribution instruction of the fuel cell and the lithium battery. The method has the advantages of reducing the fluctuation of the output power of the hydrogen fuel cell, reducing the hydrogen consumption and the like.

The invention discloses a fuel cell hybrid electric vehicle power distribution method based on heuristic action planning deep reinforcement learning. The method comprises the following steps: establishing a power distribution system model of a fuel cell hybrid electric vehicle equipped with a lithium battery and a super capacitor; a power layered structure is provided, a deep reinforcement learning model of the fuel cell hybrid electric vehicle is designed, a probability transfer matrix of required power is constructed, and model training is performed in a data driving mode; designing a reward function by adopting an equivalent consumption minimum strategy, and guiding optimization of an energy management strategy by fuel economy; the motion space of deep reinforcement learning is improved by adopting heuristic planning, and smooth output of the fuel cell is kept on the premise of reducing equivalent hydrogen consumption. According to the method, power distribution of the three-energy-source fuel cell hybrid electric vehicle can be achieved in a complex and random driving environment, hydrogen consumption is reduced, dynamic adaptability to different driving conditions is improved, and meanwhile the method has the potential of real-time application.

The present disclosure provides an apparatus and a method for controlling an ammonia fuel cell vehicle, which are capable of storing ammonia in an ammonia tank; decomposing the ammonia stored in the ammonia tank into hydrogen; controlling at least one of an ammonia supply amount to be supplied to the cracker and conditions of a cracker; calculating a predicted hydrogen consumption amount based on at least one of driving information and battery information; and controlling at least one of the ammonia supply amount and the conditions of the cracker based on the calculated predicted hydrogen consumption amount.

The invention discloses a method for calculating the real-time hydrogen storage amount and the remaining endurance mileage of a fuel cell vehicle, and belongs to the solid hydrogen storage amount measurement technology of a fuel cell. The method comprises the following steps: firstly, carrying out calibration and cycle test analysis on a hydrogen storage material, including establishing relationships between hydrogen storage capacity, temperature and pressure in a full life cycle of a fuel cell stack; the initial hydrogen storage amount is obtained when the vehicle is started, and the obtaining mode comprises the steps that the temperature of the hydrogen storage device and pressure sensor data are read based on the FCU to convert and calculate the initial hydrogen storage amount; when the vehicle runs, the hydrogen consumption amount of the fuel cell stack and the remaining hydrogen storage amount in the hydrogen storage device are calculated in real time, the remaining endurance mileage is calculated in real time on the basis of the remaining hydrogen storage amount, and calculation includes calculation based on the driving mileage within the time t1 to t2 and the hydrogen consumption amount. The method can overcome the defect that in the prior art, the error of estimating the hydrogen storage amount based on thermodynamics in the vehicle running process is too large, the estimation precision of the real-time hydrogen storage amount in the hydrogen storage device is improved, application of hydrogen energy to new energy vehicles, ships and aircrafts can be promoted, and precise prediction of endurance is improved.

The invention provides a fuel cell vehicle energy-heat cooperative control method considering thermal characteristics of a power system, and solves the problem that energy and heat management at low temperature is difficult to collaboratively optimize. According to the method, an energy-heat collaborative global dynamic planning model is established through a long-time-domain average vehicle speed, and the optimal reference trajectory of the SOC and the fuel cell temperature is solved off line by integrating the preheating energy consumption of a power cell and the temperature coupling effect of the fuel cell. And in a short time domain, an LSSVM and BPNN fusion algorithm is adopted to predict the vehicle speed, real-time rolling optimization is performed on the SOC and the fuel cell temperature in combination with a nonlinear MPC strategy, and a global optimal track is tracked. According to the method, on the premise of meeting the temperature requirements of the cabin and the battery, the lowest hydrogen consumption of the whole vehicle and the optimal power system efficiency are achieved, and the energy utilization rate and the cruising ability under the severe cold working condition are improved.

The invention discloses a hydrogen fuel cell hybrid power system grid-connected control method, which comprises the following steps of: analyzing and establishing a plurality of models of a system, comprehensively considering a plurality of cost weights on the basis of a hydrogen consumption model of the system, and constructing a comprehensive cost function; establishing a system operation state model; the speed, the acceleration and the system operation state serve as input of a self-adaptive Elman neural network together, a state transition matrix real-time correction factor of the system in the state is obtained, and a basic state transition matrix is adjusted through the real-time correction factor to obtain a real-time state transition matrix after the influence of the current driving condition on system state transition is considered; and according to the real-time state transition matrix, predicting the system demand power within a period of time, solving the comprehensive cost to enable the cost to be minimum, and completing the power distribution between the multiple stacks of fuel cells and storage batteries. According to the method, the fuel economy of the system is ensured, the internal balance of the multi-stack fuel cell system is improved, the service life of the system is prolonged, and the real-time prediction capability of the system is improved.

The invention provides an energy management method and device of an unmanned aerial vehicle, which can be used for the unmanned aerial vehicle capable of autonomous flight and can significantly improve the energy utilization efficiency of the unmanned aerial vehicle capable of autonomous flight, and the unmanned aerial vehicle can perform autonomous flight. The unmanned aerial vehicle flight power demand table comprises load powers required by the unmanned aerial vehicle for executing different flight actions at various speeds of the unmanned aerial vehicle; according to the flight task, performing flight path planning; according to the optimal flight path obtained by planning, querying an unmanned aerial vehicle flight power demand table, obtaining load power required by different flight stages in the flight path, and further obtaining global load power change of the unmanned aerial vehicle completing a flight task; a global load power change is derived based on the path planning, and the fuel cells and the power output of the cells are optimized to meet load power consumption and minimize hydrogen consumption of the fuel cells.

The invention discloses a real-time SLMP fuel cell hybrid electric vehicle energy management method. The method comprises the following steps: firstly, collecting vehicle operation data in real time, constructing an operation state vector containing kinetic parameters, and initializing a state transition matrix as agent action input; on the basis, the speed and the acceleration are predicted through a self-learning Markov predictor, and dynamic self-adaptive power distribution of the fuel cell and the power cell is achieved in combination with a multi-objective optimization function and power distribution constraints. The method passes hardware-in-the-loop (HIL) verification, aims at reducing hydrogen consumption and improving efficiency, and exits if two times of circulation are not passed. Compared with a traditional method based on rules or static optimization, the method innovatively embeds a self-learning mechanism, has the advantages of being high in adaptability, high in prediction precision and good in generalization performance, and is suitable for energy management optimization under complex working conditions.

According to the hydrogen fuel heavy truck energy management method provided by the invention, according to the current electric quantity of a power battery, the optimization objectives of reducing or maintaining the temperature of a battery cell group of the power battery and reducing the hydrogen consumption of a fuel battery system are taken; according to the minimum value of the power system boundary power, the power battery boundary power, the fuel cell system boundary power and the management strategy boundary power as the fuel cell system target power in the current state, the output power of the fuel cell system is adjusted within the minimum variable power time allowed by the fuel cell system; and the endurance of the whole vehicle is prolonged while the dynamic property is considered.

According to the preparation method and the preparation system of the efficient circulating hydrogen-donating solvent for direct coal liquefaction, the circulating solvent prepared by the method has relatively high hydrogen-donating performance, the coal conversion rate and the oil yield in the direct coal liquefaction process can be remarkably improved, and the hydrogen consumption and the gas yield are reduced. The preparation method comprises the following steps: (1) fractionating the direct coal liquefaction oil in a first fractionating tower; (2) carrying out a first hydrogenation reaction on a mixed material obtained by mixing the heavy distillate oil and an initial solvent in a first hydrogenation reactor, and feeding the obtained product into a first separation unit for separation to obtain first-stage light distillate oil, first-stage medium distillate oil and first-stage heavy distillate oil; (3) performing a second hydrogenation reaction on a mixed material obtained by mixing the first-stage heavy distillate oil and the medium distillate oil in a second hydrogenation reactor, and feeding an obtained product into a second separation unit for separation to obtain second-stage heavy oil; and (4) mixing the second-stage heavy oil with the first-stage medium distillate oil to obtain the circulating hydrogen-donating solvent.

The embodiment of the invention provides a hierarchical control method, system and device for battery energy management, and belongs to the technical field of discharge control of batteries. The control method comprises the following steps: acquiring total required power; separating high-frequency power from the total demand power by adopting a second-order high-pass filter; subtracting the total required power from the high-frequency power to obtain low-frequency power; inputting the high-frequency power into a super capacitor to obtain super capacitor power; subtracting the high-frequency power from the power of the super capacitor; adding the difference value of the high-frequency power and the power of the super capacitor and the low-frequency power to obtain the total power required by the battery and the lithium battery; and determining optimal battery power and lithium battery power by adopting a preset optimization algorithm according to the total required power of the battery and the lithium battery by taking the minimum equivalent hydrogen consumption as an optimization target and taking the start-stop times, the power change rate and the maximum power which influence the performance degradation of the battery as constraint conditions.

The invention provides a vehicle transportation route hydrogen consumption simulation system and method based on multiple models. The method belongs to the technical field of new energy and simulation, and comprises the steps of based on a basic power demand model and a hydrogen consumption calculation model, collecting multi-source data in real time through a multi-source data collection network, combining the multi-source data with historical data, optimizing an existing model through a machine learning algorithm, and updating the hydrogen consumption calculation model. By collecting multi-source data in real time and optimizing an existing model in combination with historical data and a machine learning algorithm, the hydrogen consumption condition can be predicted more accurately. Meanwhile, by collecting new data of external environmental factors in real time, the environmental influence model is optimized, the hydrogen consumption calculation result is further corrected, and the simulation precision is improved.

The invention provides a rapid activation method of a proton exchange membrane fuel cell, and belongs to the technical field of fuel cells. The rapid activation method comprises a hydrogen pump activation stage and a variable load activation stage. In the hydrogen pump activation process, a current with the current density of 50-200mA / cm < 2 > is applied to the fuel cell in a constant current mode for 5-30 minutes, so that the utilization rate of an electrode catalyst is improved, and the generation of surface oxides of a cathode catalyst can be removed or avoided; in the variable load activation process, low current density and high current density are alternately changed, the ratio of the high current density to the rated current density of the battery is 0.8-1.2, and the ratio of the low current density to the high current density is less than or equal to 0.2, so that establishment of water, gas, electron and proton channels in the membrane electrode is facilitated. By adopting the activation method provided by the invention, the activation time of the proton exchange membrane fuel cell is effectively shortened, the hydrogen consumption is reduced, and the manufacturing cost of the fuel cell is reduced.

The invention relates to the technical field of renewable energy consumption, in particular to a vehicle-hydrogen-steel collaborative green hydrogen fluctuation stabilizing method and system, a physical layer is provided with a wind-solar power generation device, an electrolytic hydrogen production device, a hydrogen storage buffer tank, a steel heat supply device, an electric vehicle and a V2G charging pile which are connected with one another through a hydrogen conveying pipeline and a power cable; the information layer takes the central regulation and control platform as a core, collects wind-solar power, hydrogen yield, steel hydrogen consumption and electric vehicle SOC by using sensors, and transmits the collected power, hydrogen yield, steel hydrogen consumption and electric vehicle SOC to the central regulation and control platform; the central regulation and control platform executes a hierarchical dynamic fluctuation regulation and control mechanism; when the fluctuation range of the hydrogen yield does not exceed a set value, the hydrogen is stabilized by controlling the hydrogen storage buffer tank to charge and discharge hydrogen; and when the fluctuation amplitude exceeds a set value, a V2G system is started, and stabilizing is carried out by controlling charging and discharging of the electric vehicle. On the premise that the special energy storage cost is not greatly increased, stable and low-cost supply of green hydrogen is achieved, and energy conservation and emission reduction of steel and other high-energy-consumption industries are achieved.

The invention provides a bacteriostatic proppant technology based on a palladium oxide-reduced graphene oxide composite material, aiming at the problem of hydrogen loss caused by microbial activity in a hydrogen storage bank of an exhausted gas reservoir. A PdO (at) rGO composite material functionally modified by lead ions (Pb < 2 + >) is loaded on the surface of a porous ceramsite carrier to form an adsorption-inactivation-blocking synergistic antibacterial network; precise laying of the proppant in a crack network is achieved through the end sand removal technology, hydrogen consumption is reduced, and an efficient, economical and environment-compatible innovative solution is provided for biological pollution control of the underground hydrogen storage library.

The invention discloses a fuzzy control-based multi-stack fuel cell energy management method and a fuzzy control-based multi-stack fuel cell energy management system. The method comprises the following steps of constructing an energy system comprising a multi-stack fuel cell and a lithium battery; constructing a fuzzy logic controller by taking the required power of the energy system and the charge state of the lithium battery as input variables and taking the output power of the multi-stack fuel battery as an output variable; establishing a hydrogen consumption function of the energy system according to the relationship between the output power of the multi-stack fuel cells and the lithium batteries and the hydrogen consumption, and establishing an optimization function by taking the value of the minimum hydrogen consumption function as a target; and solving the optimization function to obtain an optimal parameter of the fuzzy logic controller, and controlling the output power of the multi-stack fuel cell according to the optimal parameter. According to the method, the energy consumption of the fuel cell is optimized, the use of hydrogen fuel is reduced, and the energy utilization efficiency of the system is improved.

The invention discloses a power control method of a hybrid power system, the hybrid power system comprises a hydrogen fuel cell and a power cell, and the method comprises the following steps: establishing a hydrogen fuel cell model, a power cell model and a load model; monitoring the SOC of a power battery, the opening degree of an accelerator pedal and the real-time rotating speed of a motor in real time; based on an intelligent control algorithm, with the hydrogen consumption, the hydrogen fuel cell output power variation and the power cell SOC as optimization targets, designing a target function and formulating constraint conditions; performing smooth filtering processing on the optimal control sequence solved based on the intelligent control algorithm; if the current working mode is in a hybrid mode, real-time acquisition and optimization are repeated in each control period, and otherwise, power control is performed according to a pure electric mode; and applying the solved control sequence to the hybrid power system. While power dynamic response is guaranteed, the hydrogen consumption is effectively reduced, and the problem of frequent load changing of a hydrogen fuel system is solved.

The invention discloses a reverse shift catalyst capable of inhibiting methanation side reaction under the process condition of higher pressure and a preparation method of the reverse shift catalyst, the catalyst comprises the following effective component: iron accounting for 40-80% (weight percentage) of the total amount of the catalyst in terms of Fe2O3, an auxiliary agent for inhibiting methanation side reaction is added, and the preparation method of the catalyst is a mixing and kneading method. According to the present invention, the auxiliary agent for inhibiting the methanation side reaction is added under the reverse transformation process condition, such that the methane generation amount of the catalyst under the reverse transformation high pressure process condition is significantly reduced, the selectivity of the CO2 reverse transformation reaction is improved, the hydrogen consumption is reduced, and the new requirement of the national green dual-carbon development is met.

The invention provides a fuel cell vehicle hydrogen consumption life optimization management method and system, relates to the technical field of vehicle control and energy management of fuel cell vehicles, and aims to solve the problem that in the prior art, a fuel cell vehicle is difficult to balance hydrogen consumption economy and life durability at the same time. According to the method, a hydrogen consumption-service life dual-objective optimization model containing a dynamic efficiency coefficient and a catalyst attenuation item is constructed by collecting the whole vehicle working condition, environment and fuel cell stack core state data in real time, an improved NSGA-II algorithm introducing a self-adaptive crossover operator and an elitist retention strategy is adopted for solving, optimization parameters are selected in combination with scene priorities, and the optimal performance of the fuel cell stack is improved. Working condition pre-judgment response is realized through a pre-adjustment unit; the system is composed of a data acquisition module, a model construction module, an algorithm solution module, an optimization decision module and a control execution module, supports model online updating and fault degradation, can consider hydrogen consumption economy, service life durability and dynamic responsiveness, and is suitable for various fuel cell commercial vehicles and passenger vehicles.

The invention discloses a hierarchical energy management method for a multi-stack fuel cell hybrid power system. The method comprises the following steps: acquiring the recession state and real-time maximum efficiency of each fuel cell, each lithium battery and each super capacitor of the system; dividing a fuel cell, a lithium battery and a super capacitor with similar decline degrees and maximum efficiency into a region by using a decoupling feature clustering neural network, so as to divide the whole system into a plurality of regions; a nested deep reinforcement learning controller is constructed according to the instantaneous efficiency of the fuel cell, the equivalent hydrogen consumption of the system, the instantaneous decline rate of each power unit, the SOC of the lithium battery and the super capacitor and the operating temperature of the fuel cell, and optimal energy management of each region is realized; and performing system-level coordination scheduling on energy management results of all regions, and realizing cross-region power balance and boundary condition constraint through a central power coordination module. According to the invention, efficient operation and service life protection of a multi-pile hybrid power system in high-power and high-reliability application scenes such as rail transit vehicles are realized.

The invention discloses a method and a device for adjusting the output power of a fuel cell in a vehicle and the vehicle. The method comprises the following steps: acquiring operation data of a vehicle in an operation process; a self-adaptive parameter set corresponding to the operation condition is determined, and the self-adaptive parameter set comprises a plurality of self-adaptive parameters; based on the self-adaptive parameter set, an objective function is constructed and obtained, the objective function is used for representing the mapping relation between the equivalent hydrogen consumption of the fuel cell and the distribution power, and the distribution power is used for guiding power distribution between the fuel cell and the power cell; according to a target function, mapping the plurality of distribution powers into a plurality of equivalent hydrogen consumptions, and screening out a target distribution power corresponding to the fuel cell from the plurality of distribution powers based on the plurality of equivalent hydrogen consumptions; and determining the output power of the fuel cell according to the target distribution power. The technical problem that the working condition adaptability of the energy management strategy of the battery in the vehicle is poor is solved.

The invention relates to the technical field of catalysts, in particular to a desulfurization catalyst and application thereof in hydrodesulfurization. The desulfurization catalyst adopts a hollow core shell, a weak acid site is constructed on a shell surface, and a boron-containing polymerization network is formed through surface-initiated polymerization; and linear / branched polyethyleneimine complexation is used for synergistically introducing Ni and Mo, in-situ vulcanization is performed after inert atmosphere pretreatment, and a dispersed nickel molybdenum sulfide active phase and shallow and deep double-peak metal distribution are obtained. The structure inhibits excessive hydrogenation while ensuring diffusion and structural stability, promotes a direct desulfurization path, and shows high conversion and high selectivity to 4, 6-dimethyl dibenzothiophene. The catalyst has low hydrogen consumption, high aromatic hydrocarbon retention and cycling stability, and is suitable for deep desulfurization of diesel oil and preparation of ultralow-sulfur fuel.

The invention discloses a scheduling method adaptive to multi-time-scale rolling between wind-light fluctuation and maximum hydrogen yield. The scheduling method specifically comprises a wind-light power generation prediction model, an electrolytic tank group, a power model of a storage battery pack, a price type demand response model and the like. In the working process, electric energy input caused by wind and light is included, wind and light fluctuation is responded through the hydrogen load demand, it is ensured that the hydrogen consumption is increased when there is more wind and more light, the hydrogen consumption is reduced when there is less wind and less light while electricity is converted into hydrogen, and the effect of flexibly adapting to volatility is achieved. Electricity-hydrogen conversion is achieved through a storage battery-electrolytic cell system, the wind and light abandoning rate and the electricity abandoning rate of new energy are reduced, the consumption level of renewable energy is improved, economic and stable operation of the system is guaranteed, and meanwhile the maximum hydrogen production amount is obtained. According to the method, the adaptability and the flexibility of the renewable energy hydrogen production system are enhanced, the economical efficiency and the prediction accuracy are improved, efficient consumption of renewable energy is promoted, and carbon peak reaching and carbon neutralization targets are supported to be achieved.