49 results about "Energy hub" patented technology

The invention discloses a megawatt electric hydrogen energy hub peak regulation capability evaluation method and system, and the method comprises the steps: constructing an electric-hydrogen-heat multi-physics field coupling model, outputting a megawatt electric hydrogen energy hub dynamic digital twin body, carrying out the peak regulation demand feature extraction, outputting a peak regulation demand matrix with a timestamp, and carrying out the hydrogen energy storage dynamic feature analysis. And outputting a hydrogen energy storage peak regulation capability map, carrying out multi-objective optimization decision-making to obtain a peak regulation optimization scheduling scheme, implementing Monte Carlo reliability simulation, outputting a risk-efficiency balance scheme, and determining a megawatt electric hydrogen energy hub peak regulation capability evaluation result based on a toughness index. According to the method, the electric-hydrogen-thermal multi-physics field coupling model and the dynamic digital twins are constructed, and Monte Carlo reliability simulation and toughness index evaluation are combined, so that the peak regulation capability can be comprehensively and accurately evaluated, complex working conditions and extreme scenes are effectively considered, and the evaluation reliability and accuracy are improved.

The invention relates to the technical field of property intelligent management, and provides a collaborative optimization intelligent lighting system dynamic energy scheduling method, which comprises the following steps: constructing an energy concentrator network of an intelligent lighting system, abstracting lighting equipment of a plurality of projects into an energy concentrator model, wherein each energy concentrator describes a conversion relation between electric energy and luminous flux through a coupling matrix; a multi-objective optimization function with maximization of the electric energy utilization rate as the core is established, the multi-objective optimization function integrates comfort, equipment and power grid constraints, and dynamic configuration is carried out based on operation parameters of the energy hub network; solving the multi-objective optimization function by adopting a two-stage optimization process, generating a reference operation plan and performing rolling correction; and issuing a dynamic dimming control signal to each lighting terminal through an energy concentrator network based on the optimized scheduling instruction obtained by solving so as to cooperatively schedule the electric energy of the intelligent lighting system. Therefore, the cross-region and multi-project intelligent lighting system is optimized in a collaborative manner, and the energy utilization rate is improved.

The present discourse provides a system and method for simultaneous energy scheduling and trading portfolio optimization for an energy hub (EH). In the present disclosure, an optimal strategy is generated for (i) energy scheduling and (ii) portfolio based trading in a simultaneous manner using a dynamic optimization model for the EH with multiple energy types, taking into account an uncertainty factor on each of a supply side and a demand side. The dynamic optimization model provides the EH with an optimal schedule for a plurality of energy assets, and provides an EH operator with an optimal trading portfolio for the multiple energy types in the EH. The optimal schedule for the plurality of energy assets and trading portfolio of the EH operator are calculated while maximizing the realized profit. Furthermore, the dynamic optimization model ensures the sustainability while minimizing the CO2 emissions and increased overall efficiency of the EH.

The invention discloses a comprehensive energy system source-load collaborative low-carbon economic dispatching method based on extended carbon emission flow. The method comprises the following steps: constructing a comprehensive energy system extended carbon emission flow model based on an energy hub; constructing a combined operation model of a wind turbine generator, a carbon capture unit and power-to-gas based on carbon flow; a low-carbon demand response mechanism based on carbon potential is designed, and the carbon reduction potential of the load side is released; a carbon flow-based master-slave game framework is constructed, and the high-carbon attribute of the system is improved; and designing a source-load cooperative operation method under a carbon flow view angle to realize low-carbon economic operation of the system. According to the method, an extended carbon emission flow model of the comprehensive energy system is constructed, a combined operation model of a wind turbine generator, a carbon capture unit and power-to-gas is constructed based on the extended carbon emission flow model, and the coupling characteristic of the source side of the system is improved; a low-carbon demand response mechanism based on carbon potential is designed, and the perceptibility of a user to carbon difference is improved; source-load cooperative operation is realized based on the master-slave game, and the low-carbon economic level of the system is improved.

The invention discloses a communication tower and social tower dual-rotation extension holding pole, comprising: a communication module comprising a signal center and an energy center, the signal center being used for guaranteeing 5G / 6G communication and emergency communication coverage, the energy center being used for integrating green energy supply and energy storage to realize self-sufficiency and peripheral feedback functions; the social module comprises a sensing center and a service center, the sensing center is used for collecting environment, traffic and safety data, and the service center is used for facilitating interaction, emergency response and community service functions; according to the invention, the structure is simple, each conversion tower becomes a'small and complete 'urban intelligent micro hub, the existing infrastructure resources are activated, a brand new solution is provided for urban governance, public service and resident life, and'multiple purposes, multiple functions and multiple win-win purposes' of one tower are really realized.

The invention discloses a power distribution network and optical storage and charging system collaborative planning method considering an N-1 safety criterion, and belongs to the field of novel power systems. The method comprises the following steps: constructing a power distribution network computable power flow model based on second-order cone relaxation and linearization, and constructing a light storage and charging energy hub model based on EH multi-energy flow coupling; constructing a two-stage stochastic programming framework, performing joint optimization on investment and operation, and performing N-1 fault recovery simulation; maximizing an uncertainty interval of photovoltaic output and charging load fluctuation at a fault moment by adopting an information gap decision theory; and based on the double-stage stochastic programming framework, a fault problem is decomposed into a main problem and a corresponding sub-problem, key element identification is carried out, and fault verification is completed. According to the method, the total cost of the whole life cycle of the system is minimized on the premise that the N-1 safety criterion is met, the power supply safety in an extreme scene is ensured, and the calculation efficiency of actual engineering application is ensured.

This invention relates to a low-carbon economic dispatch method for integrated energy systems that considers the variable operating conditions of energy conversion equipment, belonging to the field of power systems. The method includes the following steps: S1: Combining the variable operating conditions of energy conversion equipment in the integrated energy system with static energy hubs to construct a dynamic energy hub state transition model for the integrated energy system; S2: Combining a full life-cycle analysis method with a carbon quota trading mechanism to construct a carbon trading model for the integrated energy system; S3: Based on the dynamic energy hub state transition model and the carbon trading model, constructing a low-carbon economic dispatch model for the integrated energy system that considers the variable operating conditions of energy conversion equipment, and solving for the low-carbon economic dispatch strategy that considers the variable operating conditions of energy conversion equipment. This method can provide technical support for the operation and dispatch of integrated energy systems, and has advantages such as low system operating costs, low carbon emissions, and flexible and reliable operation.

The application discloses a regional building carbon emission optimization system and method, aiming at solving the problem of multiple optimization targets of regional building balanced carbon emission, economic cost and user comfort. The system includes a perception layer, a transmission layer, a platform layer and an application layer. The perception layer collects multi-source data such as building energy consumption, environmental state and regional energy. The energy load prediction module of the platform layer predicts future load based on historical data. The multi-objective collaborative optimization module constructs a target function with the minimum regional total carbon emission, the lowest total energy cost and the highest average user comfort as the target. The non-dominated sorting genetic algorithm is used to solve the optimal regional energy scheduling strategy. Finally, the strategy is executed through the regional energy hub module. Through data-driven collaborative scheduling, the application scientifically balances the contradiction between emission reduction, economy and comfort, and significantly improves the comprehensive energy efficiency and low-carbon operation level of the regional building group.

The application discloses a mine truck cableway energy circulation system and a collaborative control method. The circulation system comprises a mine truck, an energy hub vehicle, a mine area power grid and a control center. The mine truck is connectable with another mine truck. The energy hub vehicle is connectable with the mine truck. The mine area power grid is connectable with the mine truck and the energy hub vehicle. The control center is signal-connected with each mine truck and the energy hub vehicle. The collaborative control method comprises an uphill scheduling method and a downhill scheduling method. The uphill scheduling method is that when the residual power of an uphill mine truck is lower than a minimum threshold, another mine truck or the energy hub vehicle on the downhill is used to charge the uphill mine truck. The downhill scheduling method is that when the residual power of a downhill mine truck is higher than a maximum threshold, the downhill mine truck is used to charge another mine truck or the energy hub vehicle on the uphill. Compared with the prior art, the circulation system and the collaborative control method fully recover the downhill energy of the mine truck through the direct connection of the uphill and downhill mine trucks or the energy storage and transfer of the energy hub vehicle, and thus the waste of energy is avoided.

The invention belongs to the technical field of nuclear power production risk identification, and particularly relates to a nuclear power production work risk identification method based on safety improvement. The method comprises the following steps: 1, single system fault modeling: performing task decomposition on a nuclear power production process, performing FMEA analysis on each subtask, listing a single system fault mode, and evaluating an influence level; carrying out HAZOP analysis: identifying a process deviation through a guide word, and quantifying the influence of a single fault on the system; 2, identifying a multi-system coupling path: constructing an inter-system coupling matrix, namely an energy hub available energy coupling matrix M and an energy storage coupling matrix K; 3, dynamic risk visualization is carried out, and a coupling path is converted into a graph structure. The method is suitable for fusing FMEA, HAZOP and multi-system coupling analysis, establishing a risk identification system covering the whole process of equipment maintenance, fuel operation and radiation monitoring, and quantifying a risk propagation path and an influence level.

The invention relates to the field of ocean engineering structures, and provides a floating foundation for an offshore facility and a construction method of the floating foundation. The floating foundation for the offshore facility comprises at least one composite component, the composite component comprises an internal load-bearing framework, and the internal load-bearing framework comprises a steel framework composed of a plurality of limbs; and the outer coating layer comprises a concrete layer wrapping the inner load-bearing framework, and the outer coating layer and the inner load-bearing framework are cooperatively stressed. According to the floating foundation for the offshore facilities, the composite advantages of steel and concrete are exerted, the economical efficiency, durability, structural efficiency and construction convenience of the floating foundation in the whole life cycle are remarkably improved, and the floating foundation is suitable for various offshore facilities such as floating wind power, deep sea oil and gas platforms, offshore energy hubs and future floating cities.

The invention belongs to the technical field of power distribution network bearing capacity evaluation, and relates to a power distribution network hydrogen energy comprehensive bearing capacity evaluation method, which comprises the following steps: 1, enabling a hydrogen energy system to be equivalent to an internal source-containing energy hub, and constructing a green electricity-hydrogen energy power distribution system connected with a plurality of hydrogen production energy hubs; 2, establishing a power distribution network hydrogen energy comprehensive bearing capacity evaluation model; 3, aiming at a green electricity hydrogen energy system accessed in the power distribution network, taking the maximum hydrogen load access capacity of the power distribution network as a hydrogen energy comprehensive bearing capacity index, and analyzing the influence of the maximum hydrogen load bearing capacity of the power distribution network, the access capacity of an electrolytic bath, new energy development and the line capacity of the power distribution network on the comprehensive hydrogen load bearing capacity of the power distribution network; external characteristic modeling is carried out on the green electricity hydrogen energy system based on the energy hub, the green electricity hydrogen energy system can serve as a generalized node to be connected to the power distribution network, and the problem that multi-energy system coordinated dispatching is difficult is solved.

Systems, apparatuses, and methods are described for a smart energy home. The smart energy home may promote optimization of consumption of electricity by appliances and other consumer devices. Prioritization of where and when electricity may be provided to various appliances, chargers, or other devices which draw electrical power may be managed by the smart energy home. Information concerning prevailing weather conditions and contemporaneous electrical tariffs may be utilized in processes executed by the smart energy home. Related systems, apparatuses, and methods are also described.

The application discloses a green hydrogen preparation storage and lithium battery cooling system and method using a cascade heat pump, and belongs to the technical field of comprehensive energy systems. The lithium battery cabin in the system suppresses the power fluctuation of fluctuating power sources, outputs stable power, and simultaneously drives the cascade heat pump and the electrolytic cell. The cascade heat pump is configured to: absorb lithium battery cabin heat through its low-temperature stage circuit evaporator to cool the battery cabin; release heat to the electrolytic cell through its condensing evaporator to heat and maintain temperature; and release heat to the organic liquid hydrogen storage system through its high-temperature stage circuit condenser to provide a reaction heat source. The electrolytic cell produces hydrogen under stable power and suitable temperature, and the hydrogen is transported to the organic liquid hydrogen storage system for storage or release. The application uses the cascade heat pump as an energy hub, and utilizes the lithium battery waste heat in stages for electrolysis and hydrogen storage processes, realizes efficient collaboration of electricity-heat-hydrogen and energy self-consistency, and improves the energy efficiency, economy and accommodation capacity for fluctuating renewable energy of the system.

The invention discloses a comprehensive energy random optimization scheduling method for a multi-energy scene generation park. The method comprises the following steps: constructing a multi-energy coupling condition feature database based on historical source load multi-energy prediction data; inputting day-ahead prediction information in the multi-energy coupling condition feature database, and constructing an improved condition generative adversarial network model; generating a day-ahead random scene set with a multi-energy coupling characteristic based on the adversarial network model; clustering processing is carried out on the day-ahead random scene set to obtain a typical scene set representing multi-energy uncertainty characteristics and probability distribution of the typical scene set; building a park comprehensive energy system structure based on the energy hub model, and building a day-ahead multi-energy scene random optimization scheduling model in combination with the typical scene set and the probability distribution thereof; and solving the stochastic optimization scheduling model by adopting an optimization algorithm to obtain a robust optimization scheduling scheme of the system equipment. Through the method, a multi-energy coupling scene is generated, scheduling resource waste caused by prediction uncertainty is reduced, and robustness of system optimization scheduling is improved.

This invention relates to the field of overhead contact line electrified highway heavy trucks, and discloses an energy hub system including a pre-charging module, a first input regulator, a first bidirectional DC transformer, a second input regulator, and a second bidirectional DC transformer. A first end of the input side of the first input regulator is connected to a first output end of the overhead contact line, and the output side of the first input regulator is connected to the input side of the first bidirectional DC transformer. The output side of the first bidirectional DC transformer is connected to the pre-charging module. A first end of the input side of the second input regulator is connected to a second end of the input side of the first input regulator, and the second end of the input side of the second input regulator is connected to a second output end of the overhead contact line. The output side of the second input regulator is connected to the input side of the second bidirectional DC transformer, and the output side of the second bidirectional DC transformer is connected to the pre-charging module.

The invention discloses a regional building carbon emission optimization system and method, and aims to solve the problem of multiple optimization objectives of balancing carbon emission, economic cost and user comfort of a regional building. The system comprises a sensing layer, a transmission layer, a platform layer and an application layer, the sensing layer collects multi-source data such as building energy consumption, environment states and regional energy, and an energy consumption load prediction module of the platform layer predicts future load based on historical data; the multi-target collaborative optimization module constructs a target function with the minimum regional total carbon emission, the lowest total energy cost and the highest user average comfort as targets, a non-dominated sorting genetic algorithm is adopted for solving to obtain an optimal regional energy scheduling strategy, and finally the strategy is executed through the regional energy hub module. Through data-driven collaborative scheduling, the contradiction among emission reduction, economy and comfort is scientifically balanced, and the comprehensive energy efficiency and the low-carbon operation level of regional building groups are remarkably improved.

The application discloses a kind of uncertain energy hub participation energy and standby market's bidding optimization method, it is related to electric power market technical field, including input market basic information and energy hub's basic information and new energy parameter information, establish the uncertainty model of new energy output outside energy hub;Based on comprehensive energy information, the energy relationship inside comprehensive energy and the safe operation condition, establish the self-scheduling model of comprehensive energy;According to market information, new energy information and network information, establish the comprehensive clearing model of day-ahead energy market and standby market;Using Matlab describes double-layer optimization problem, and using gurobi commercial solver solves, obtains the optimization bidding method of energy hub in considering uncertainty.The application considers the influence of the uncertainty factor of new energy unit in market on energy hub bidding, fully considers market factor outside energy hub, and the bidding method after optimization has significant accuracy improvement.

The application discloses a kind of variable working condition under the scheduling method and system of comprehensive energy system carbon emission, method includes: obtaining the multi-energy coupling relationship of comprehensive energy system and the variable working condition characteristics of energy conversion equipment;According to the multi-energy coupling relationship of comprehensive energy system, establish energy hub model;Based on the variable working condition characteristics of energy conversion equipment, the efficiency parameter in the energy hub model is corrected using the efficiency correction model based on deep neural network constructed in advance, to obtain dynamic energy hub model;Based on dynamic energy hub model, construct the scheduling model of comprehensive energy system carbon emission under variable working condition, and the scheduling scheme of comprehensive energy system under variable working condition is obtained by solving.This application pays attention to the influence of equipment variable working condition characteristics on system carbon emission, can realize the low-carbon operation of comprehensive energy system, improve the solving speed and accuracy of scheduling model.

This invention discloses a method for energy community electricity-carbon differential matching based on an improved slime mold algorithm, belonging to the field of smart grids. First, considering the coupling characteristics of energy hubs at the distribution network level, a data-driven method is used to quantitatively analyze the peak-valley coupling potential between different types of energy hubs. Initial differential matching is then performed on energy hubs with different external characteristics. Combining the load characteristics and carbon quota balance of energy hubs, a comprehensive index system that considers both regional structural and functional needs is constructed. Finally, aiming for optimal overall energy community characteristics, a matching strategy based on an improved slime mold optimization algorithm is proposed, introducing an adaptive search mechanism and information sharing strategy to optimize the structure and boundaries of the energy community. This invention simulates the dynamic matching process of energy communities, achieving differential matching that considers both electricity and carbon quotas, efficiently and accurately determining the boundaries and optimal matching schemes of energy communities, providing a new approach to improving the comprehensive benefits of electricity and carbon emission management.

The application discloses a kind of comprehensive energy system multi-time scale optimization scheduling method considering equipment variable working condition, it is related to energy optimization scheduling technical field, the method includes considering the energy input link in regional comprehensive energy system, production link, conversion link, storage link and consumption link, and considering equipment variable working condition characteristics, constructs dynamic energy hub model containing electric gas conversion equipment;According to dynamic energy hub model and different load prediction scales, a comprehensive energy system multi-time scale rolling optimization scheduling model is established;According to the comprehensive demand response of day-ahead scheduling stage and intraday rolling scheduling stage, a double demand response model is established, and a mixed integer nonlinear programming model is constructed according to the comprehensive energy system multi-time scale rolling optimization scheduling model and double demand response model and is solved.The application can exert the advantage in different time dimensions, while making the system operation scheduling more accurate.

This invention belongs to the field of multi-energy system collaborative optimization scheduling, specifically, it relates to an energy network security management optimization method based on large-scale renewable energy grid connection, including the following steps: establishing an EH model and a P2G unit model for the multi-energy system; constructing a collaborative optimization scheduling model among multi-energy hub units containing large-scale renewable energy grid connection before and after a sudden event occurs in the system's power grid or natural gas network; solving the constructed model to obtain the optimal collaborative optimization scheduling scheme among multi-energy hub units containing large-scale renewable energy grid connection. The energy network security management optimization method based on large-scale renewable energy grid connection proposed in this invention can not only significantly improve the system's energy supply security, but also effectively solve the problem of renewable energy power generation absorption.

The invention discloses a distributed power supply acceptance capability improving method based on a PC-SOP interconnected energy hub, a storage medium and equipment, and relates to the technical field of a novel power system.The method comprises the steps that a PC-SOP optimization model is established, SOP is transferred to form the PC-SOP in a phase power transfer or phase change SOP mode, the advantages of the PC-SOP in an unbalanced three-phase four-wire system are analyzed, and the optimal model is established; power loss of a neutral line is considered, and an optimization model of PC-SOP is established; the optimal operation strategy of the unbalanced active power distribution network based on PC-SOP comprises the following steps: modeling a three-phase four-wire active power distribution network by using photovoltaic, SOP and energy storage; and converting the obtained model into a second-order cone programming model for solving so as to achieve the goals of reducing power loss, reducing voltage deviation and improving a voltage unbalance state. According to the method, unnecessary economic loss caused by the fact that an unbalanced power distribution network optimization operation strategy in the prior art cannot fully consider SOP network reconstruction, energy storage scheduling and three-phase four-wire imbalance conditions is solved, the comprehensive operation cost is reduced, and the operation efficiency is higher and more stable.

The invention provides an adsorption type ammonia energy hub system and an ammonia supply and storage combined cycle operation method, the adsorption type ammonia energy hub system comprises a plurality of adsorption beds, a condenser, an evaporator and an application unit, and the adsorption beds respectively utilize high-temperature, medium-temperature and low-temperature waste heat through design of different temperature intervals to realize multifunctional conversion of ammonia. In the adsorption bed, the ammonia gas is stored through an adsorption process; in the aspect of heat supply, the system utilizes a condenser to condense ammonia gas into liquid ammonia, and heat released in the process can be used for heat supply; cold supply is achieved through the evaporator, liquid ammonia is evaporated into ammonia gas in the evaporator, and meanwhile heat is absorbed and used for refrigeration application. In addition, the desorption process of ammonia in the adsorption bed provides high-quality ammonia gas supply for subsequent application. According to the circulating working mode of adsorption-desorption and condensation-evaporation, ammonia energy can efficiently operate in the storage and energy supply process, meanwhile, efficient conversion among different energy forms is achieved, and the overall energy utilization efficiency of the system is greatly improved.

The invention belongs to the technical field of power grid peak regulation control, and particularly relates to a grid-connected peak regulation control method and system for a high-power electric hydrogen energy hub, and the method comprises the steps: carrying out the heterogeneous data fusion of an electric hydrogen energy hub multi-source market and compliance data, and deconstructing a fusion result interaction relation, and obtaining a flexible connection interconnection variable; carrying out heterogeneous coupling on the flexible connection interconnection variable and the internal operation constraint of the electro-hydrogen energy hub to obtain a decision architecture; based on the real-time operation situation of the electro-hydrogen energy hub, performing toughness enhancement reconstruction on the decision-making architecture to obtain a toughness operation framework; based on the instant market state of the electric hydrogen energy hub, self-adaptive strategy evolution is carried out in a tough operation framework, and a robust strategy is obtained; performing strategy space mapping on the robust strategy to obtain a strategy map; and based on the real-time power grid state of the electric hydrogen energy hub, parameterization adaptation is carried out in the strategy map, and an adaptation result is coded into a real-time optimization control instruction. According to the invention, the regulation and control efficiency of grid-connected peak regulation of the electric hydrogen energy hub can be improved.

This invention belongs to the field of power grid peak-shaving control technology, and particularly relates to a method and system for grid-connected peak-shaving control of high-power electric hydrogen energy hubs. The method includes: fusing heterogeneous data from multi-source market and compliant data of the electric hydrogen energy hub, deconstructing the interaction relationships of the fusion results to obtain soft-connection interconnection variables; heterogeneously coupling the soft-connection interconnection variables with the internal operating constraints of the electric hydrogen energy hub to obtain a decision architecture; enhancing and reconstructing the resilience of the decision architecture based on the real-time operating status of the electric hydrogen energy hub to obtain a resilient operating framework; adaptively evolving strategies within the resilient operating framework based on the real-time market state of the electric hydrogen energy hub to obtain robust strategies; mapping the robust strategies to a strategy space to obtain a strategy graph; and parameterizing and adapting the strategies within the strategy graph based on the real-time grid state of the electric hydrogen energy hub, encoding the adaptation results into real-time optimized control commands. This invention can improve the regulation efficiency of grid-connected peak-shaving for electric hydrogen energy hubs.

The invention discloses an energy hub energy sharing method and device, terminal equipment and a storage medium, and belongs to the field of power grid energy management, and the method comprises the steps: constructing a constraint condition of each energy hub, and constructing a virtual queue of the corresponding energy hub according to the constraint condition; defining a Lyapunov function according to all the virtual queues, and obtaining energy supply and demand data of each energy hub by optimizing the sum of the drift distance of the Lyapunov function and a preset penalty term; taking each energy hub as a game participant, and constructing a corresponding non-cooperative game model by minimizing the energy sharing cost among the energy hubs; and initializing the energy supply and demand data and iteratively solving the non-cooperative game model to obtain an optimal energy sharing strategy of each energy hub, and controlling each energy hub to share energy according to the optimal energy sharing strategy. The energy utilization rate can be improved under the condition that the operation cost of the comprehensive energy system is guaranteed.

The application discloses an energy system configuration method and device considering carbon transaction price uncertainty, and the method comprises the following steps: establishing a carbon-energy coupling model based on the multi-energy flow of an energy hub and the carbon transaction volume; performing uncertainty modeling based on a normal distribution with zero mean, and generating a scenario set according to the modeling result; establishing a system planning total cost model according to the carbon-energy coupling model and the scenario set; establishing a risk value model under each confidence level based on the system planning total cost model; and solving to obtain a configuration scheme with the minimum risk value model as the target, so that the technical problem of planning total cost fluctuation risk can be solved.

The present application belongs to the technical field of power grid control, and particularly relates to a dynamic balance control method for a power grid-friendly electric-hydrogen integrated energy hub, which comprises the following steps: collecting multi-source data in real time, including power grid frequency deviation value, wind and light power generation, energy storage device state of charge, hydrogen storage tank pressure, electrolytic hydrogen production device input power and fuel cell output power, to form a multi-dimensional operating parameter set; according to the amplitude and duration of the power grid frequency deviation, hierarchically calling the energy storage device, electrolytic hydrogen production device and fuel cell device for collaborative regulation; controlling the wind turbine generator to release rotor kinetic energy, while adjusting the electrolytic hydrogen production device as an interruptible load to provide virtual inertia support; calling the energy storage device, electrolytic hydrogen production device and fuel cell device according to priority for power compensation, to realize dynamic balance of the electric-hydrogen integrated energy system. The present application significantly improves the power grid frequency stability, reduces the energy storage configuration demand, and improves the hydrogen energy utilization efficiency and new energy consumption capacity.