Electricity-hydrogen-ammonia bidirectional conversion system of offshore energy island and debugging method

Abstract

The invention relates to the technical field of offshore energy conversion, in particular to an electricity-hydrogen-ammonia bidirectional conversion system of an offshore energy island and a debugging method. The electric hydrogen ammonia bidirectional conversion system comprises a volatility renewable energy source module, an energy medium bidirectional conversion module, a medium supply module, a power generation and energy routing module, an auxiliary module and an intelligent control module. The energy medium bidirectional conversion module is provided with a hydrogen production function unit, a synthesis function unit and a cracking function unit; the medium supply module is provided with a water production unit and a nitrogen production unit; and a hydrogen output end of a cracking function unit configured by the power generation and energy routing module is connected with a fuel input end of the power generation unit. Through the mode, the technical problem that in an offshore energy island scene in the prior art, renewable energy consumption and stable cooperative operation of system energy supply are difficult to consider at the same time is solved, and a key hardware system support is provided for subsequent efficient, stable and autonomous offshore energy supply.

Description

Technical Field

[0001] This invention relates to the field of marine energy conversion technology, and in particular to a bidirectional electro-hydrogen-ammonia conversion system and commissioning method for a marine energy island. Background Technology

[0002] Offshore energy islands, as crucial energy security carriers for marine resource development and deep-sea operations, heavily rely on renewable energy sources such as wind and solar power. However, due to the complex and variable marine environment, renewable energy exhibits significant intermittent and fluctuating output characteristics, posing a severe challenge to the stability and sustainability of energy supply. Furthermore, offshore energy islands are far from the mainland power grid, making external energy replenishment difficult and costly, thus placing extremely high demands on the autonomy and comprehensive utilization efficiency of their energy systems. Against this backdrop, converting surplus renewable energy electricity into easily stored and transportable chemical energy carriers has become a key path to achieving intertemporal energy scheduling and ensuring stable energy supply. Currently, green hydrogen, as a clean and efficient secondary energy carrier, shows great application potential in offshore energy systems, but its storage and long-distance transportation still face bottlenecks in terms of technology and safety, restricting its large-scale application. Liquid ammonia, with its high energy density, mature liquefaction process, and relatively safe and convenient storage and transportation characteristics, is considered an ideal storage and transportation carrier for green hydrogen, thus giving rise to the technological demand for the mutual conversion and synergistic interaction of the three energy media: electricity, hydrogen, and ammonia.

[0003] In the field of offshore energy supply and storage technology, existing technologies have explored the use of ammonia as an energy carrier. For example, existing technology (application publication number CN120824816A) discloses an off-grid integrated energy supply system using ammonia as an energy carrier. This system integrates multiple power generation methods, including wind, photovoltaic, nuclear, and biomass energy, to power the ammonia synthesis system. It utilizes hydrogen produced by water electrolysis and nitrogen obtained by separating it from air to synthesize ammonia through electrochemical synthesis or the Haber process, and then uses the resulting ammonia for storage, transportation, or downstream applications. This technical solution attempts to use ammonia to solve the problems of energy storage and transportation. However, existing technologies, represented by this one, still have significant limitations when adapted to the specific scenario of offshore energy islands. Firstly, the system design focuses on unidirectional energy conversion from electricity to ammonia and a fixed-path ammonia synthesis, lacking a flexible and efficient bidirectional synergistic conversion mechanism between the three energy media: electricity, hydrogen, and ammonia. Each energy conversion module (such as hydrogen production and ammonia synthesis) operates relatively independently, making it impossible to dynamically adjust energy flow paths based on real-time fluctuations in offshore renewable energy. This results in rigid energy storage and dispatch strategies, hindering flexible responses to dynamic changes in island load and intermittent renewable energy output. Secondly, the system control methods fail to form a closed-loop optimization covering the entire chain of "power fluctuation prediction - real-time control of medium conversion processes - multi-medium coordinated dispatch." Existing methods lack precise linkage control and scientific quantitative assessment of operating parameters for key reaction processes such as hydrogen production and ammonia synthesis, failing to effectively mitigate the impact of renewable energy fluctuations on subsequent conversion stages. This makes it difficult to further improve the overall system operational stability and comprehensive energy utilization efficiency, failing to meet the urgent needs of offshore energy islands for highly autonomous and reliable energy supply. Therefore, existing technologies in the offshore energy island scenario face the technical challenge of simultaneously addressing renewable energy consumption and stable coordinated operation of the system's energy supply. Summary of the Invention

[0004] To address the aforementioned shortcomings or deficiencies, this invention provides a bidirectional electro-hydrogen-ammonia conversion system and commissioning method for offshore energy islands, which can solve the technical problem that existing technologies in offshore energy island scenarios struggle to simultaneously ensure the consumption of renewable energy and the stable and coordinated operation of the system's power supply.

[0005] This invention provides a bidirectional electro-hydrogen-ammonia conversion system for an offshore energy island, comprising a fluctuating renewable energy module, an energy medium bidirectional conversion module, a medium supply module, a power generation and energy routing module, an auxiliary module, and an intelligent control module.

[0006] The power output terminal of the fluctuating renewable energy module is connected to the power input terminal of the bidirectional energy medium conversion module.

[0007] The bidirectional energy medium conversion module is equipped with a hydrogen production unit, a synthesis unit, and a cracking unit.

[0008] The media supply module is equipped with a water production unit and a nitrogen production unit. The pure water output terminal of the water production unit is connected to the raw material input terminal of the hydrogen production unit, and the nitrogen output terminal of the nitrogen production unit is connected to the raw material input terminal of the synthesis unit.

[0009] The power generation and energy routing module is equipped with a power generation unit and a routing unit. The hydrogen output terminal of the cracking function unit is connected to the fuel input terminal of the power generation unit.

[0010] The auxiliary module is connected to the bidirectional energy medium conversion module, the medium supply module, and the power generation and energy routing module.

[0011] The intelligent control module is connected to the fluctuating renewable energy module, the bidirectional energy medium conversion module, the medium supply module, the power generation and energy routing module, and the auxiliary module.

[0012] According to a second aspect, this invention provides a commissioning method for a bidirectional electro-hydrogen-ammonia conversion system on a marine energy island. This method, based on the bidirectional electro-hydrogen-ammonia conversion system described in the above embodiment, is applied to an intelligent control module and includes: Based on the pre-set phased commissioning principle, the core individual equipment in the fluctuating renewable energy module, the bidirectional energy medium conversion module, the medium supply module, the power generation and energy routing module, and the auxiliary module were sequentially subjected to medium-free and load-free operation verification, and system-level functional verification was performed on each module.

[0013] In response to the completion of system-level functional verification of each module, the equipment in each module is started in the preset order: water production unit in the fluctuating renewable energy module, hydrogen production unit in the energy medium bidirectional conversion module, nitrogen production unit in the energy medium bidirectional conversion module, synthesis and cracking units in the energy medium bidirectional conversion module, power generation unit in the power generation and energy routing module, and routing unit in the power generation and energy routing module.

[0014] In the system's no-load operation state after each unit is started, the media transmission pipelines and circuits connecting each module are purged and tested for sealing.

[0015] In response to the qualified testing of the medium transmission pipeline and circuit, the actual energy medium is introduced, the fluctuating renewable energy module is started, and the bidirectional energy medium conversion module, medium supply module, power generation and energy routing module and auxiliary module are put into load operation state to perform the full-process load commissioning of the electric hydrogen ammonia bidirectional conversion system.

[0016] According to a third aspect, the present invention provides a computer device comprising: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the control method of the bidirectional electro-hydrogen-ammonia conversion system of any marine energy island in the embodiments of the present invention.

[0017] According to another aspect of the present invention, a non-transient computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause a computer to execute the control method of the bidirectional electro-hydrogen-ammonia conversion system of any of the marine energy islands in the embodiments of the present invention.

[0018] The present invention provides a bidirectional electro-hydrogen-ammonia conversion system for offshore energy islands. This system constructs an integrated energy conversion architecture adapted to the offshore energy island scenario through the physical connection and logical coordination of six core components: a fluctuating renewable energy module, an energy medium bidirectional conversion module, a medium supply module, a power generation and energy routing module, an auxiliary module, and an intelligent control module. Specifically, the fluctuating renewable energy module, as a green electricity source, provides the initial energy input to the system; the energy medium bidirectional conversion module, configured with hydrogen production, synthesis, and cracking functional units, forms a hardware link for the mutual conversion between the three core energy media: electricity, hydrogen, and ammonia; the medium supply module, configured with water production and nitrogen production units, provides the necessary raw material guarantee for the hydrogen production and ammonia synthesis processes; the power generation and energy routing module, configured with power generation and routing units, realizes the reverse conversion of ammonia for power generation and establishes a flexible transmission and distribution channel for energy and media within the system; the auxiliary module provides support functions for medium storage and waste heat utilization for each module; and the intelligent control module, connected to all the above modules, provides a control center for the coordinated operation of the entire system.

[0019] In the overall technical solution, this invention addresses the core problems of fixed energy medium conversion paths and insufficient scheduling flexibility mentioned in the background technology. By constructing a bidirectional energy medium conversion module that includes hydrogen production, synthesis, and cracking functional units, and cooperating with the routing unit in the power generation and energy routing module, this invention breaks the unidirectional fixed conversion mode of "electricity → hydrogen → ammonia" at the hardware level. It establishes multiple reversible and selectable energy flow paths between the three media: electricity, hydrogen, and ammonia. This allows for dynamic adjustment of the energy conversion direction and storage form based on the real-time output fluctuations of offshore renewable energy, solving the deficiency of existing technologies that cannot flexibly adapt to fluctuating energy supply demands due to the single conversion path. Addressing another core issue mentioned in the background technology—the lack of global collaborative optimization control covering the entire chain of power generation, conversion, and scheduling—this invention constructs a centralized and unified control architecture by setting up an intelligent control module connected to all functional modules. This enables collaborative monitoring and coordinated regulation of the entire process, including fluctuating renewable energy power generation, medium conversion, product storage, energy routing, and waste heat recovery. This lays the physical foundation for implementing closed-loop optimization control from power fluctuation prediction to multi-medium collaborative scheduling, thus solving the shortcomings of existing technologies where each subsystem is controlled independently, failing to achieve optimal global energy efficiency and improved operational stability. Therefore, the technical solution of this invention, from a system architecture perspective, solves the technical problem of existing technologies in offshore energy island scenarios, which struggle to simultaneously consider renewable energy consumption and stable system power supply, providing crucial hardware system support for achieving efficient, stable, and autonomous offshore energy supply. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the bidirectional electro-hydrogen-ammonia conversion system architecture of a marine energy island according to an embodiment of the present invention; Figure 2 This is a flowchart of the control method of an electro-hydrogen-ammonia bidirectional conversion system according to an embodiment of the present invention; Figure 3 This is a schematic diagram of a visual centralized debugging interface for an energy management system based on deep learning, according to an embodiment of the present invention. Figure 4 This is a block diagram of a computer device for implementing embodiments of the present invention. Detailed Implementation

[0021] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0022] During the development of this invention, researchers conducted extensive experiments and data analysis, revealing the inherent relationship between the output characteristics of fluctuating renewable energy sources at sea (such as wind and solar power), the reaction kinetics of chemical energy storage media such as hydrogen / ammonia, and the dynamic changes in load demand on offshore energy islands. The intermittent fluctuations of renewable energy cannot be effectively mitigated by a single energy storage or conversion path. Furthermore, hydrogen and ammonia, as energy carriers, involve complex trade-offs between reaction rate, energy density, safety, and economy in their preparation, storage, and re-conversion cycles, and these relationships dynamically change with the fluctuation patterns of the input energy. Based on this discovery, this invention innovatively proposes this technical solution, the core of which lies in constructing a physical system architecture that integrates a bidirectional conversion link and unified intelligent routing for three energy media: electricity, hydrogen, and ammonia. This architecture enables flexible conversion and intertemporal scheduling of energy forms based on source and load status. By introducing a centralized intelligent control module covering the entire system, combined with real-time acquisition of operating parameters from each module and collaborative optimization algorithms, it achieves adaptive regulation of the entire chain from fluctuating power sources to stable energy supply. This solution embodies the core inventive concept of "using multi-media bidirectional reversible conversion to cope with input fluctuations and using global collaborative intelligent control to enhance the system's autonomy."

[0023] Specifically, through systematic testing and verification, the invention team discovered that traditional solutions suffer from technical defects such as a single, fixed energy conversion path and a lack of coordination among the independent operation of each energy conversion unit (e.g., hydrogen production, ammonia synthesis, and power generation). This invention, however, integrates hydrogen production, ammonia synthesis, ammonia cracking for hydrogen production, and fuel cell power generation into a unified bidirectional energy medium conversion module and power generation routing module. Utilizing standardized interfaces and routing units between modules, it constructs a bidirectional flow network of electricity, hydrogen, and ammonia, breaking the traditional linear, unidirectional energy conversion chain. Furthermore, by introducing an intelligent control module deeply connected to all physical modules, it dynamically allocates fluctuating renewable energy power to hydrogen production or energy storage, converts surplus hydrogen into more easily stored and transportable liquid ammonia, and cracks stored liquid ammonia for power generation on demand. By combining real-time operational data to optimize the multi-path selection and flow, it improves overall energy utilization efficiency and the ability to absorb renewable energy fluctuations, achieving a highly reliable and autonomous clean energy supply for offshore energy islands far from the mainland power grid.

[0024] Therefore, according to the first aspect, the present invention provides a bidirectional electro-hydrogen-ammonia conversion system for an offshore energy island, comprising a fluctuating renewable energy module, an energy medium bidirectional conversion module, a medium supply module, a power generation and energy routing module, an auxiliary module, and an intelligent control module.

[0025] The power output terminal of the fluctuating renewable energy module is connected to the power input terminal of the bidirectional energy medium conversion module.

[0026] Among them, the fluctuating renewable energy module refers to a collection of power generation units deployed on offshore energy islands, utilizing natural resources such as wind and solar energy to generate electricity, and whose output power varies significantly with time and climate conditions. This module is the initial energy supply end of the system.

[0027] Specifically, the fluctuating renewable energy module adopts a wind and solar complementary power supply architecture, comprising multiple offshore wind turbines, a photovoltaic array composed of monocrystalline silicon solar panels, and an electrochemical energy storage buffer unit to smooth out short-term power fluctuations. The module captures maximum output power through maximum power point tracking technology, with an output voltage range of 380 volts to 10 kV and frequency fluctuations controlled within ±0.5 Hz. For example, the fluctuating renewable energy module can be configured with 10 offshore wind turbines (3 MW each, 30 MW installed capacity), paired with a 10 MW photovoltaic array with a conversion efficiency of 22%, for a total installed capacity of 40 MW, and equipped with an 8 MWh energy storage unit, capable of adapting to typical offshore environments with wind speeds of 3 to 25 m / s and solar irradiance of 200 to 1000 W / m².

[0028] The bidirectional energy medium conversion module is equipped with a hydrogen production unit, a synthesis unit, and a cracking unit.

[0029] The energy medium bidirectional conversion module refers to a collection of physical and chemical reaction devices that enable the interconversion of three energy media: electricity, hydrogen, and liquid ammonia. The hydrogen production unit refers to a device that uses electricity to decompose water into hydrogen and oxygen. The synthesis unit refers to a device that synthesizes ammonia from hydrogen and nitrogen under the action of a catalyst. The cracking unit refers to a device that catalytically decomposes liquid ammonia into a mixture of hydrogen and nitrogen.

[0030] Specifically, the hydrogen production unit employs a parallel alkaline electrolyzer and a proton exchange membrane electrolyzer, operating at a temperature of 60 to 80 degrees Celsius. The working pressure is 1 to 3 MPa. The synthesis functional unit adopts a low-pressure synthesis process, with a reactor working pressure of 10 to 15 MPa and a temperature of 400 to 500 degrees Celsius. Iron-based or ruthenium-based catalysts are used. The cracking unit employs a catalytic cracking process, with the cracking furnace operating at a pressure of 0.5~1MPa and a temperature of 800~900℃. Nickel-based catalysts are used. For example, the hydrogen production unit is designed to produce hydrogen at a capacity of 300 standard cubic meters per hour (Nm³ / h) with an electrolysis efficiency of no less than 75%; the synthesis unit receives a mixture of hydrogen and nitrogen at a volume ratio of 3:1, and the single-pass conversion rate of ammonia synthesis can reach 18%; the cracking unit processes liquid ammonia at a flow rate of 50 Nm³ / h, and the ammonia cracking conversion rate is no less than 99%.

[0031] The media supply module is equipped with a water production unit and a nitrogen production unit. The pure water output terminal of the water production unit is connected to the raw material input terminal of the hydrogen production unit, and the nitrogen output terminal of the nitrogen production unit is connected to the raw material input terminal of the synthesis unit.

[0032] The media supply module refers to the pretreatment unit that provides the necessary raw materials for the core reaction process of the system. The water production unit refers to the device that desalinates and purifies seawater to produce deionized water. The nitrogen production unit refers to the device that separates and purifies high-purity nitrogen from the air.

[0033] Specifically, the water production unit includes seawater desalination and deep purification processes via reverse osmosis or electrodialysis. The nitrogen production unit includes air compression, pretreatment, cryogenic distillation separation, and pressure swing adsorption (PSA) deep purification processes, operating at a pressure of 5-8 MPa and a cooling temperature as low as -196°C. For example, the water treatment unit can process seawater at a flow rate of 15 cubic meters per hour (m³ / h), producing an electrical conductivity of less than 1 microsiemens per centimeter (µSiemens per centimeter). The nitrogen generator produces deionized water. The nitrogen generation unit processes air at a flow rate of 150 Nm³ / h, producing nitrogen gas with a purity of not less than 99.5%, with an output rate of 60 Nm³ / h.

[0034] The power generation and energy routing module is equipped with a power generation unit and a routing unit. The hydrogen output terminal of the cracking function unit is connected to the fuel input terminal of the power generation unit.

[0035] The power generation and energy routing module refers to the unit that converts chemical energy into electrical energy and distributes and transmits various energy media within the system. The power generation unit refers to the device that consumes hydrogen gas to generate electricity through an electrochemical reaction. The routing unit refers to the hub device that possesses functions for power conversion and control of the transmission of various fluid media, enabling flexible scheduling of energy media across modules.

[0036] Specifically, the power generation unit employs a proton exchange membrane fuel cell or a solid oxide fuel cell stack. The routing unit includes a power electronic converter, an AC / DC converter, and valve assemblies and transfer pumps / compressors connecting hydrogen, nitrogen, and liquid ammonia pipelines, enabling bidirectional transmission and distribution of electrical, hydrogen, and ammonia energy. For example, the power generation unit has a rated power of 3 megawatts (MW) and a power generation efficiency of no less than 50%. The routing unit has a rated voltage of 10kV, a hydrogen transmission pressure of 1~3MPa, a liquid ammonia transmission flow rate of 30m³ / h, and an overall energy medium conversion efficiency of no less than 90%.

[0037] The auxiliary module is connected to the bidirectional energy medium conversion module, the medium supply module, and the power generation and energy routing module.

[0038] Among them, the auxiliary module refers to the set of units that provide supporting functions such as media buffer storage and waste heat recovery and utilization for the system.

[0039] Specifically, the auxiliary module includes pressure storage tanks for storing hydrogen, liquid ammonia, and nitrogen, as well as a heat exchange system for recovering waste heat from synthesis, cracking, and other reaction processes to preheat feedstocks or drive seawater desalination. The liquid ammonia storage tank employs a double-insulated design to maintain cryogenic storage. For example, the auxiliary module may include an 80 cubic meter (m³) liquid ammonia storage tank with an operating pressure of 0.1~0.5 MPa and a temperature maintained at -30°C. Approximately; and includes a waste heat recovery device with a heat exchange area of ​​100 square meters (m²), capable of recovering reaction waste heat to preheat the raw material gas to 300°C. .

[0040] The intelligent control module is connected to the fluctuating renewable energy module, the bidirectional energy medium conversion module, the medium supply module, the power generation and energy routing module, and the auxiliary module.

[0041] The intelligent control module refers to the computing and instruction distribution center that centrally monitors, coordinates, controls, and optimizes the scheduling of all other modules in the system.

[0042] Specifically, the intelligent control module collects real-time operating parameters of each module, including power, temperature, pressure, flow rate, liquid level, and medium concentration, through an industrial bus network and sensor network. Based on a built-in optimization algorithm model, it generates control commands to dynamically adjust the operating status of equipment within each module, achieving global coordination of energy medium production, storage, conversion, and consumption. For example, the intelligent control module can collect key system parameters 10 times per second, dynamically adjust the load of electrolytic hydrogen production based on output predictions of fluctuating renewable energy sources, and control liquid ammonia cracking for hydrogen power generation when load demand increases. The delay between command issuance and actuator transmission is no more than 10 milliseconds (ms), forming a closed-loop optimized control.

[0043] Therefore, by utilizing the aforementioned bidirectional conversion system of electricity, hydrogen, and ammonia, users can achieve efficient absorption and cross-temporal storage of fluctuating renewable energy sources (wind and solar power) at sea. Through flexible bidirectional conversion and intelligent scheduling of the three energy media of electricity, hydrogen, and ammonia, the power output fluctuations of renewable energy can be dynamically mitigated, ensuring a continuous, stable, and clean energy supply for the offshore energy island under various operating conditions, and significantly improving the autonomy and comprehensive utilization efficiency of the energy system.

[0044] In other embodiments, such as Figure 1 This diagram illustrates a bidirectional electro-hydrogen-ammonia conversion system architecture for a marine energy island, designed for general-purpose applications and utilizing ammonia as the energy carrier for hydrogen production, storage, and efficient utilization. While this system architecture is also based on the core concept of multi-energy medium conversion and coordinated scheduling, it differs from the aforementioned specific embodiments of marine energy islands in terms of module composition and topological connections.

[0045] Specifically, the system comprises a fluctuating power supply module, a multi-port energy routing module, an electrolytic hydrogen production reaction module, an air separation and purification module, an ammonia synthesis reaction module, a liquid nitrogen storage stage, an ammonia cracking and decomposition reaction module, and a fuel cell power generation module. The output of the fluctuating power supply module is connected to the input of the multi-port energy routing module. The multi-port energy routing module has multiple energy and material output ports, connected to the electrolytic hydrogen production reaction module and the air separation and purification module, respectively. The electrolytic hydrogen production reaction module produces hydrogen, and the air separation and purification module produces nitrogen; both are jointly transported to the ammonia synthesis reaction module to react and generate ammonia. The liquid ammonia produced by the ammonia synthesis reaction module can be buffered and stored in the liquid nitrogen storage stage, or transported to the ammonia cracking and decomposition reaction module for decomposition. The high-purity hydrogen produced by the ammonia cracking and decomposition reaction module is ultimately supplied to the fuel cell power generation module for power generation. Notably, the ammonia synthesis reaction module also uses a "circulation and feedback" path to return the unreacted hydrogen and nitrogen mixture to the multi-port energy routing module, forming a material circulation loop, thereby significantly improving raw material utilization and reducing operating energy consumption.

[0046] This embodiment demonstrates another implementation of the core concept of the present invention: flexible allocation and path selection of electrical energy, hydrogen energy, and ammonia energy are achieved through a multi-port energy routing module. Furthermore, by coordinating ammonia synthesis and ammonia cracking reaction modules, and combining this with the recycling of unreacted gases, an efficient and sustainable "electricity-hydrogen-ammonia-electricity" energy conversion and storage cycle is constructed. This verifies the adaptability and effectiveness of the bidirectional energy medium conversion and intelligent routing concept described in this invention across different application scenarios.

[0047] Next, according to the first aspect, the present invention provides a debugging method for a bidirectional electro-hydrogen-ammonia conversion system for an offshore energy island. This method, based on the bidirectional electro-hydrogen-ammonia conversion system described in the above embodiment, is applied to an intelligent control module. This intelligent control module can integrate an industrial computer, a programmable logic controller (PLC), a distributed control system, a data acquisition and monitoring control system, an edge computing server, and a safety instrumented system. Specifically, this intelligent control module can collect and process real-time operating parameters from fluctuating renewable energy modules, energy medium bidirectional conversion modules, medium supply modules, power generation and energy routing modules, and auxiliary modules under all operating conditions. It completes the screening, integration, and feature extraction of multi-source heterogeneous data, and executes power output prediction based on deep learning networks, operating parameter optimization using nonlinear programming algorithms, and closed-loop feedback control logic to generate dynamic scheduling and control command sequences for adjusting the start-up, shutdown, load, and operating conditions of equipment within each module. Specifically, the hardware devices of this intelligent control module include, but are not limited to: an industrial control computer, a PLC, a distributed control system controller, a remote terminal unit, a data acquisition card, an industrial Ethernet switch, a fiber optic transceiver, a serial server, various sensor transmitters, safety barriers, relay modules, and an uninterruptible power supply.

[0048] like Figure 2 As shown, the method may include: Step S110: Based on the preset phased commissioning principle, perform medium-free and load-free operation verification on the core individual equipment in the fluctuating renewable energy module, energy medium bidirectional conversion module, medium supply module, power generation and energy routing module and auxiliary module in sequence, and perform system-level functional verification on each module.

[0049] The pre-defined phased commissioning principle refers to a commissioning procedure that strictly follows the sequence of "individual device commissioning, system module commissioning, and complete system commissioning." Core individual devices refer to the independent, operable basic physical devices that constitute each system module. Medium-free and load-free operation verification refers to the process of testing and verifying the mechanical, electrical, and control functions of the equipment itself without introducing actual working media (such as seawater, hydrogen, or liquid ammonia) and without any actual workload. System-level functional verification refers to the process of testing the overall functionality, including control logic, parameter linkage, and fault response, when multiple related devices within the same module operate collaboratively, after the individual device verification has passed.

[0050] Specifically, the system can issue control commands through the intelligent control module to sequentially start equipment such as wind turbine generators, photovoltaic power generation arrays, electrochemical energy storage devices, electrolyzers, synthesis reactors, pyrolysis reactors, seawater desalination devices, air compressors, fuel cell stacks, inverters, power electronic converters, and storage tanks. Under no-load conditions, its start-up, shutdown, regulation, protection, and monitoring functions are tested, and the command linkage and fault conditions between devices within the module are simulated to verify the correctness of the module-level control logic.

[0051] For example, the system can control the wind turbine generator to operate under no-load conditions, and the test pitch system command response time is no more than 2 seconds (s), and the yaw system positioning deviation is no more than ±1 degree (). The overspeed protection function was verified; the no-load operation of the electrolysis hydrogen production module was controlled, and the electrolysis current was tested to be adjustable in the range of 0 to 3000 amperes per square meter (A / m²), and the adjustment function of the temperature and pressure control loop was verified.

[0052] Step S120: In response to the completion of system-level functional verification of each module, control the devices in each module to start up in the preset order of the fluctuating renewable energy module, the water production unit in the medium supply module, the hydrogen production unit in the energy medium bidirectional conversion module, the nitrogen production unit in the medium supply module, the synthesis and cracking units in the energy medium bidirectional conversion module, the power generation unit in the power generation and energy routing module, and the routing unit in the power generation and energy routing module.

[0053] The preset sequence refers to the equipment startup order set to ensure the system's safe and smooth entry into the no-load linkage operation state. This sequence is determined based on the dependency relationship between energy flow and material flow, that is, first start the energy supply end, then start the raw material preparation end, then start the core conversion and power generation end, and finally start the system scheduling hub.

[0054] Specifically, the system can automatically send start commands to each target device in sequence at certain intervals after receiving the signal that the system-level function verification of each module has passed through the program logic of the intelligent control module, and confirm the operating status signal fed back by the device.

[0055] For example, after completing all verifications, the system first starts the fluctuating renewable energy module to generate electricity under no-load conditions; after waiting for 5 minutes, it starts the electrolyzer system in the hydrogen production unit; after waiting for another 3 minutes, it starts the air separation system in the nitrogen production unit; after the nitrogen production stabilizes, it starts the synthesis unit, the cracking unit, and the power generation unit in sequence, and finally starts the routing unit, so that the entire system enters a linkage no-load operation state without media circulation.

[0056] Step S130: Under the no-load operation state of the system linkage after each unit is started, perform purging treatment and sealing test on the medium transmission pipelines and circuits connecting each module.

[0057] The system's no-load operation refers to a condition where all major equipment in the system is started and in a low-power standby or circulation state, but no actual chemical reaction medium is introduced or an actual load is applied. Purging refers to the process of introducing dry, clean inert gas (such as nitrogen) into the pipeline to remove residual moisture, grease, or other impurities. Leakage testing refers to the test of whether there are leaks at pipeline, valve, flange, and other connections by pressurizing and holding the pressure for a period of time and monitoring the pressure drop.

[0058] Specifically, the system can control the corresponding valves via an intelligent control module to purge the hydrogen, nitrogen, and liquid ammonia delivery pipelines, as well as the cooling medium circuit, with nitrogen as the purging medium for a certain period. Subsequently, the relevant valves are closed, and the pipeline system is pressurized (e.g., to 1.5 times the design pressure) and maintained at that pressure for a period. Pressure changes are monitored using a high-precision pressure sensor to verify the sealing performance of the pipeline system. The power supply and control circuits are tested using an insulation resistance tester and a loop resistance tester.

[0059] For example, if the system pressurizes the hydrogen delivery pipeline to 3 MPa and maintains that pressure for 30 minutes (min), and the pressure drop during this period does not exceed 0.01 MPa, then the pipeline is considered to be airtight. An insulation test is performed on the power supply circuit, requiring an insulation resistance of not less than 10 megohms. ).

[0060] Step S140: In response to the qualified detection of the medium transmission pipeline and circuit, the actual energy medium is introduced, the fluctuating renewable energy module is started, and the energy medium bidirectional conversion module, medium supply module, power generation and energy routing module and auxiliary module are put into the load operation state to perform the full-process load commissioning of the electric hydrogen ammonia bidirectional conversion system.

[0061] The actual energy medium refers to the actual working materials processed by the system, including seawater, air, deionized water, hydrogen, nitrogen, liquid ammonia, and corresponding catalysts (such as electrolytes, synthesis catalysts, and cracking catalysts). Load-bearing operation refers to the operating conditions of the equipment when processing the actual working medium and bearing the actual workload. Full-process load-bearing commissioning refers to the testing process that allows the system to completely undergo the entire energy conversion and utilization process, from renewable energy power generation to hydrogen production, ammonia synthesis, ammonia storage / cracking, and power generation, to verify its design functions and performance.

[0062] Specifically, the system can automatically perform a series of operations through the intelligent control module: first, open the seawater and air intake valves to introduce raw materials into the medium supply module; confirm that the catalyst has been loaded; then increase the output of the fluctuating renewable energy module to the predetermined value; then sequentially start the relevant production programs of the medium supply module, the energy medium bidirectional conversion module, and the power generation and energy routing module, gradually establish and adjust the material balance and energy balance, so that the system transitions to steady-state load operation.

[0063] For example, after the system passes the sealing test, the intelligent control module automatically starts the seawater pump and air compressor to supply materials to the water production and nitrogen production units; then, wind and photovoltaic power generation are activated to transmit electrical energy to the electrolyzer; the water production unit produces pure water to supply the electrolyzer to produce hydrogen, and the nitrogen production unit produces nitrogen, which is mixed with hydrogen and sent to the synthesis tower to generate liquid ammonia; part of the generated liquid ammonia is stored in a storage tank, and part is sent to a cracking furnace to decompose into hydrogen; the hydrogen is used to power the fuel cell, and the generated electricity is distributed through the routing unit. During this process, the intelligent control module continuously monitors and records hundreds of operating parameters throughout the entire process, verifying the system's operational stability and energy conversion efficiency under simulated real marine environmental fluctuations.

[0064] In another embodiment, such as Figure 3This showcases a centralized, visualized debugging interface for an energy management system based on deep learning. This interface is the core of the human-machine interface (HMI) for the intelligent control module, providing debugging engineers with an integrated digital operating platform for monitoring, analysis, and decision-making. The interface background features a light blue, technological design, and the main body consists of multiple rectangular data panels, clearly separated by dark gray lines, reflecting the structured and logical organization of the data. Specifically, the structure and functions of this debugging interface are as follows: Real-time parameter monitoring area (top left): This area dynamically displays the real-time operating parameters of the fluctuating renewable energy module, energy medium bidirectional conversion module, medium supply module, power generation and energy routing module, and auxiliary modules under all operating conditions. Specific parameters include wind / photovoltaic power generation, electrolyzer current and temperature, synthesis reactor pressure and temperature, instantaneous flow rates of hydrogen / liquid ammonia / nitrogen, pressure and level of each storage tank, and fuel cell stack voltage. All data is refreshed in both digital and analog instrument formats, with a refresh cycle set to 500ms.

[0065] Trend and Forecast Analysis Area (Main Area on the Right): The core of this area is to present the predicted trend of fluctuating power output power and compare it with historical curves using multi-color line charts. For example, the blue line represents the power prediction value for the next 60 minutes based on a deep learning model, while the gray line represents the actual power over the past 2 hours. Below the chart, the confidence interval of the prediction model, key inflection point data, and synchronous change curves of environmental parameters (wind speed, sunlight) can be displayed in conjunction with the chart.

[0066] Command Issuance and Interaction Area (Bottom Area): This area provides a series of operation buttons and parameter input boxes, allowing commissioning engineers to directly issue commissioning commands to various modules on the interface. For example, the target current value of the electrolysis hydrogen production unit (such as 3000 amperes (A)) can be manually entered. After clicking the "Issue" button, the command is sent to the corresponding programmable logic controller for execution via the industrial Ethernet bus. This area also provides a one-click start / stop function for preset commissioning plans.

[0067] The complete debugging process integrated on the interface is intuitively presented to engineers through clearly labeled steps S1 to S6: Step S1: Emphasize the use of a deployed sensor network to synchronously collect multi-dimensional data such as power, flow rate, temperature, pressure, and concentration, and construct a multi-dimensional data acquisition matrix for debugging. Steps S2 and S3: Demonstrate how the backend uses a distributed computing architecture and deep learning networks to process and predict the collected data, providing a data foundation and forward-looking decision-making basis for optimization and debugging; Steps S4 and S5: The system automatically generates a debugging scheme based on the optimization objective using a nonlinear programming algorithm, and decomposes the scheme into specific control commands, which are then sent to the actuators (such as frequency converters and regulating valves) via the industrial bus. Step S6: Reveals the real-time feedback control mechanism established by the system. By monitoring the deviation between the execution result and the target, the instructions are dynamically corrected, thus forming a closed-loop debugging process from perception, decision-making, execution to correction.

[0068] Therefore, the visual commissioning interface in this embodiment not only makes the complex algorithms and decision-making processes of the intelligent control module transparent and intuitive, but also serves as an important bridge connecting commissioning personnel and the physical system. It enables engineers to dynamically set or adjust optimization targets (such as maximum hydrogen production efficiency and minimum island load power failure probability) based on real-time data and predicted trends presented on the interface, and to instantly translate decisions into control commands. This greatly improves the controllability, accuracy, and interaction efficiency of the commissioning process, making it a key operational terminal for achieving efficient energy conversion and intelligent scheduling.

[0069] In summary, based on the above implementation method, the system first constructs an integrated energy conversion architecture adapted to the offshore energy island scenario through the physical connection and logical coordination of six core components: a fluctuating renewable energy module, an energy medium bidirectional conversion module, a medium supply module, a power generation and energy routing module, an auxiliary module, and an intelligent control module. Specifically, the fluctuating renewable energy module, as a green electricity source, provides the initial energy input to the system; the hydrogen production, synthesis, and cracking functional units configured in the energy medium bidirectional conversion module form a hardware link for the mutual conversion between the three core energy media: electricity, hydrogen, and ammonia; the water production and nitrogen production units configured in the medium supply module provide the necessary raw material guarantee for the hydrogen production and ammonia synthesis processes; the power generation and routing units configured in the power generation and energy routing module, on the one hand, realize the reverse conversion of ammonia to generate electricity, and on the other hand, establish a flexible transmission and distribution channel for energy and media within the system; the auxiliary module provides support functions for medium storage and waste heat utilization for each module; and the connection between the intelligent control module and all the above modules provides a control center for the coordinated operation of the entire system.

[0070] Throughout the process, this embodiment addresses the core issues of fixed energy medium conversion paths and insufficient scheduling flexibility mentioned in the background technology. By constructing a bidirectional energy medium conversion module that includes hydrogen production, synthesis, and cracking functional units, and cooperating with the routing unit in the power generation and energy routing module, it breaks the unidirectional fixed conversion mode of "electricity → hydrogen → ammonia" at the hardware level. It establishes multiple reversible and selectable energy flow paths between the three media: electricity, hydrogen, and ammonia. This allows for dynamic adjustment of the energy conversion direction and storage form based on the real-time output fluctuations of offshore renewable energy, solving the deficiency of existing technologies that cannot flexibly adapt to fluctuating energy supply demands due to the single conversion path. Addressing another core issue mentioned in the background technology—the lack of global collaborative optimization control covering the entire chain of power generation, conversion, and scheduling—this invention constructs a centralized and unified control architecture by setting up an intelligent control module connected to all functional modules. This enables collaborative monitoring and coordinated regulation of the entire process, including fluctuating renewable energy power generation, medium conversion, product storage, energy routing, and waste heat recovery. This lays the physical foundation for implementing closed-loop optimization control from power fluctuation prediction to multi-medium collaborative scheduling, thus solving the shortcomings of existing technologies where each subsystem is controlled independently, failing to achieve optimal global energy efficiency and improved operational stability. Therefore, the technical solution of this invention, from a system architecture perspective, solves the technical problem of existing technologies in offshore energy island scenarios, which struggle to simultaneously consider renewable energy consumption and stable system power supply, providing crucial hardware system support for achieving efficient, stable, and autonomous offshore energy supply.

[0071] In some embodiments, based on a preset phased commissioning principle, the core individual devices within the fluctuating renewable energy module, the bidirectional energy medium conversion module, the medium supply module, the power generation and energy routing module, and the auxiliary module undergo a process of performing on-site operation verification without medium or load, including: No-load start-up was performed on the wind turbine generator, photovoltaic array and electrochemical energy storage device in the fluctuating renewable energy module, and the response and execution status of the pitch system, yaw system and charge and discharge system to control commands, as well as the triggering of overvoltage and overcurrent protection logic, were verified.

[0072] The pitch system refers to the electromechanical system that adjusts the wind turbine blades' angle of attack to control output power and speed. The yaw system refers to the control system that drives the wind turbine nacelle to rotate, aligning the rotor with the wind direction. The charge / discharge system refers to the power electronic conversion and management system that controls the storage and release of electrical energy by electrochemical energy storage devices (such as batteries). Overvoltage and overcurrent protection logic refers to the control program that automatically triggers equipment shutdown or circuit breaking when voltage or current exceeds a set safety threshold.

[0073] Specifically, the system can issue simulated start, stop, power setting, and protection trigger commands through the intelligent control module. It monitors the pitch angle change rate, yaw positioning accuracy, generator no-load voltage and frequency, photovoltaic inverter no-load loss and voltage / frequency stability, and energy storage converter charging / discharging switching speed of the wind turbine generator. It also simulates overspeed, overvoltage, and overcurrent fault conditions to verify the accurate operation of protection functions. For example, the system controls the wind turbine generator to run under no-load conditions, testing that the pitch system's response time to angle adjustment commands does not exceed 2 seconds, and the yaw system's positioning deviation does not exceed ±0.5%. The generator no-load voltage is 10kV, with a deviation of no more than ±2%; under simulated overvoltage conditions, the overvoltage protection is verified to be reliably triggered within 100ms when the voltage reaches 10.5kV.

[0074] Inert gas purging and no-load start-up were performed on the electrolyzer in the hydrogen production unit, the synthesis reactor in the synthesis unit, and the pyrolysis reactor in the pyrolysis unit of the energy medium bidirectional conversion module, respectively. The regulation functions of the temperature control loop and the pressure control loop, as well as the interlocking action of the safety valve group, were verified.

[0075] Inert gas purging refers to the process of introducing a chemically inert gas (such as nitrogen) into the reaction vessel and related pipelines to displace impurities such as air and moisture, ensuring the safety of subsequent reactions. Temperature and pressure control loops are closed-loop control systems composed of sensors, controllers, and actuators (such as heaters, cooling valves, and pressure reducing valves) used to automatically maintain the temperature and pressure within the reactor within a set range. Safety valve assemblies are mechanical or electromechanical safety devices that automatically open to relieve pressure when the system is overpressured. Interlocking refers to a protection mechanism where, when a certain safety condition (such as overpressure) is triggered, related equipment (such as feed valves and heaters) automatically executes specific actions (such as closing or stopping) according to preset logic.

[0076] Specifically, the system can use an intelligent control module to purge the electrolytic cell, synthesis reactor, and pyrolysis reactor with nitrogen gas. Subsequently, it activates the auxiliary systems for heating, cooling, and pressure regulation in each reactor. Without an actual reaction medium, it tests whether the internal temperature and pressure can be regulated and stabilized within preset ranges. It also simulates overpressure conditions to test the safety valve's tripping pressure and interlock shutdown function. For example, the system performs no-load commissioning on the synthesis reactor, controlling its electric heating system to raise the internal temperature from room temperature to 450°C. Temperature regulation accuracy deviation does not exceed The pressure was increased to 12MPa through the pressure regulation system, and the pressure control accuracy deviation did not exceed ±0.05MPa. The overpressure was simulated to 16MPa to verify that the safety valve accurately started to release pressure at 15MPa and simultaneously interlocked to shut off the raw material inlet valve.

[0077] The seawater desalination unit, reverse osmosis or electrodialysis unit in the water production unit of the media supply module, and the air compressor, distillation column and pressure swing adsorption unit in the nitrogen production unit were started under no-load conditions to verify the start-stop control and parameter adjustment functions of the pump body, valves and refrigeration system, and to test the sealing of the related pipelines.

[0078] Among these, pumps, valves, and refrigeration systems are key actuators for fluid transport and temperature control. Start-stop control and parameter adjustment functions refer to the ability to remotely or automatically control the start and stop of these devices, as well as adjust their operating parameters (such as pump speed, valve opening, and chiller power) via control commands. Associated pipelines refer to the piping system that connects the above-mentioned equipment to form a complete process flow.

[0079] Specifically, the system can remotely start power equipment such as seawater pumps, high-pressure pumps, air compressors, and refrigeration units sequentially through an intelligent control module to test their stable operation and absence of abnormal noises; remotely adjust valve openings and pump frequencies to observe whether changes in flow rate and pressure match the commands; and pressurize and maintain the pressure of the installed pipeline system, judging its sealing performance through pressure changes. For example, the system starts the air compressor of the nitrogen generation unit and tests whether its exhaust pressure can be stably adjusted within the range of 0~8MPa; it performs a sealing test on the reverse osmosis membrane pipeline of the water production unit, pressurizing it to 1MPa and maintaining the pressure for 30 minutes, during which the pressure drop does not exceed 0.01MPa.

[0080] The fuel cell stack and inverter in the power generation unit of the power generation and energy routing module, as well as the power electronic converter, medium delivery valve and pump body in the routing unit, were started under no-load conditions. The voltage conversion control, power distribution strategy execution, medium flow regulation control and electrical protection logic were verified.

[0081] Among these, voltage conversion control refers to the function of power electronic converters in converting AC to DC and changing voltage levels. Power distribution strategy execution refers to the ability of the routing unit to distribute input electrical energy to different output ports according to a set ratio based on scheduling instructions. Medium flow regulation control refers to the function of precisely controlling the flow rate of media such as hydrogen, nitrogen, and liquid ammonia by adjusting valve openings or pump speeds. Electrical protection logic refers to the program that detects abnormal electrical conditions such as overload, short circuit, and reverse power and triggers protective actions.

[0082] Specifically, the system can start the auxiliary systems of the fuel cell stack (such as air supply and thermal management) through the intelligent control module, start the inverter and power electronic converter without load, and test the stability of their no-load output voltage and frequency; issue simulated power distribution and medium flow regulation commands to verify whether the power changes and medium valve opening changes at each output port meet expectations; simulate electrical faults to verify whether the corresponding protection circuits or programs can operate correctly. For example, the system starts the inverter for no-load operation, tests its output AC voltage at 380V and frequency at 50Hz, with deviations not exceeding ±0.5%; controls a medium delivery valve in the routing unit from fully closed to fully open, verifying that its action time does not exceed 5 seconds; simulates a circuit short circuit to verify that the short-circuit protection triggers within 10ms.

[0083] The hydrogen storage tank, liquid ammonia storage tank, and nitrogen storage tank in the auxiliary module were subjected to airtightness testing. The accuracy of the acquisition and processing of tank pressure and liquid level monitoring data, the execution of control commands by the regulating valve, and the safety interlock triggering conditions of the emergency shut-off valve were verified.

[0084] Among them, airtightness testing refers to a test that checks whether there is a leak in the tank and its connections by filling the tank with a gas (such as nitrogen) at a certain pressure and maintaining the pressure, and then checking whether the pressure drops. Pressure and level monitoring data refers to process parameters that are collected in real time by pressure transmitters and level gauges installed on the tank and converted into electrical signals. Regulating valves are valves used to automatically regulate the inflow and outflow of materials into the tank according to control commands to maintain stable pressure or level. Emergency shut-off valves are safety valves that can quickly and automatically close to isolate the tank in emergency situations such as leakage or overpressure. Safety interlock trigger conditions refer to preset logic conditions (such as excessively high pressure, excessively low level, or remote emergency stop signals) that cause the emergency shut-off valve to operate.

[0085] Specifically, the system can use an intelligent control module to control each storage tank to perform nitrogen filling and pressurization tests, and record pressure decay data. Simultaneously, under different pressure or liquid level conditions in the storage tank, it compares the readings of the field instruments with those displayed by the control system to see if they are consistent; it issues pressure or liquid level setpoints and observes whether the regulating valve's action can stabilize the parameters at the set point; it simulates interlocking conditions such as overpressure and leakage alarms to verify whether the emergency shut-off valve can close quickly. For example, the system conducts an airtightness test on a liquid ammonia storage tank, filling it with nitrogen and pressurizing it to 0.6 MPa (1.2 times the design pressure of 0.5 MPa) and holding it for 30 minutes, with the pressure drop not exceeding 0.02 MPa; when the tank level reaches 50%, the deviation between the liquid level value displayed by the control system and the field liquid level gauge reading does not exceed ±1%; it simulates receiving a fire alarm signal to verify that the emergency shut-off valve completely closes within 1 second.

[0086] Therefore, according to the above implementation method, the system can comprehensively and systematically verify the performance, control functions, safety protection and monitoring accuracy of all core individual devices before introducing actual energy medium and load, laying a solid foundation for subsequent system-level linkage debugging and safe and stable load operation, and avoiding the risk of system debugging failure or operation due to individual device failure or substandard performance.

[0087] In some embodiments, the step of performing system-level functional verification on each module includes: The system controls the coordinated startup of wind turbine generators, photovoltaic arrays, and electrochemical energy storage devices in the fluctuating renewable energy module, issues simulated power fluctuation commands, verifies the response logic of each subsystem to the simulated commands, and collects coordinated operation data under simulated fluctuating conditions.

[0088] The simulated power fluctuation command refers to the control signal generated by the intelligent control module to simulate the fluctuations in renewable energy output caused by drastic changes in wind speed and light intensity in a real marine environment. This command aims to test the dynamic response capability and coordinated adjustment performance of each generator system. Response logic refers to the internal program logic of each subsystem (such as the pitch system, maximum power point tracker, and energy storage converter) adjusting its own operating state according to a preset control algorithm after receiving the fluctuation command to track the target power or achieve stable output. Simulated fluctuation conditions refer to artificially set, near-realistic but controllable input condition change scenarios. Coordinated operation data refers to the set of parameters reflecting the overall operating status of the entire module, such as wind speed, rotational speed, power, voltage, current, and energy storage charging and discharging status, synchronously collected during the simulated fluctuation period.

[0089] Specifically, the system can generate a simulated power curve lasting several minutes, including step, ramp, and random disturbance components, through the simulation unit of the intelligent control module, and send it to the wind turbine controller, photovoltaic inverter, and energy storage management system. Simultaneously, the system monitors and records data such as the pitch system's operating rate and angle, the photovoltaic array's operating point voltage and current, and the energy storage unit's charging / discharging power and switching time. It analyzes whether these components can coordinate effectively to quickly and smoothly track changes in target power and maintain the bus voltage within permissible limits. For example, simulating offshore gusts, the system generates commands to increase the target power from 5MW to 8MW within 30 seconds, and then ramp it down to 4MW within 60 seconds. The system verifies whether the wind turbine's pitch system can increase the power to the target within 10 seconds, whether the photovoltaic inverter can quickly adjust its maximum power point, and whether the electrochemical energy storage device can switch from charging to discharging within 5ms to fill the power gap. Throughout the process, the system records whether the bus voltage fluctuation exceeds ±0.5%.

[0090] The hydrogen production unit, synthesis unit, and cracking unit in the bidirectional energy medium conversion module are started respectively. Inert gas is introduced into the electrolyzer in the hydrogen production unit and the synthesis reactor in the synthesis unit. Simulated electrolysis current adjustment commands or reactor temperature and pressure adjustment commands are issued to verify the parameter coupling relationship between the relevant control loops in the hydrogen production unit, synthesis unit, and cracking unit, and to monitor the linkage control response of each unit.

[0091] Parameter coupling refers to the physical or control correlation within a functional unit or among multiple related units, where a change in one operating parameter (such as current, temperature, pressure, or flow rate) causes a chain reaction of changes in one or more other parameters. Linkage control response refers to the compensatory or following adjustment actions automatically performed by a control system on other related parameters when adjusting one parameter to maintain process stability or follow instructions.

[0092] Specifically, the system, through an intelligent control module, activates the auxiliary systems of each reactor (such as circulating pumps, heaters, and coolers) after establishing a safe environment by introducing nitrogen. Subsequently, it sends a simulated command to the electrolysis hydrogen production unit, increasing the electrolysis current by a step, and monitors the response of its DC power supply, changes in the electrolyzer temperature, and whether the cooling water system flow rate automatically increases to maintain temperature stability. Simultaneously, it can simulate changing the pressure setpoint of the synthesis reactor, observing whether the heating power, circulating compressor speed, and cooling water valves adjust in tandem to quickly reach and stabilize the new pressure setpoint. For example, the system controls the hydrogen production unit to increase the electrolysis current command from 2000A to 2500A. The system verifies that the DC power supply output current reaches the new setpoint within 2 seconds, while the temperature control loop automatically increases the cooling water flow rate from 5 m³ / h to 6.5 m³ / h, stabilizing the electrolyzer temperature at [the setpoint value]. (Settings) ,deviation (within), which reflects the coupling relationship between current and temperature, flow rate and the effective linkage of the control system.

[0093] The water production unit and nitrogen production unit in the control medium supply module are started respectively, and simulated inlet water flow rate adjustment command or inlet air pressure adjustment command is issued to verify the control timing connection and equipment coordinated scheduling between the various processing units inside the water production unit and nitrogen production unit.

[0094] Control timing coordination refers to the requirement that the start-up, shutdown, and parameter adjustment of control actions between series-connected or parallel equipment in a process flow must follow a specific time sequence logic to ensure the safe and stable operation of the process. Equipment collaborative scheduling refers to the unified load distribution and coordinated control of multiple parallel or serially operating equipment to achieve a common production goal (such as producing nitrogen of a specified flow rate and purity).

[0095] Specifically, the system can use an intelligent control module to simulate changes in the seawater inlet flow rate setpoint of the water production unit, verifying whether the start-up, shutdown, or speed adjustment of equipment such as the seawater booster pump, pretreatment filter, high-pressure pump, and reverse osmosis membrane module operates correctly according to the safe sequence of "start first, then stop, flow rate matching." For the nitrogen production unit, the system simulates changes in air inlet pressure to verify whether equipment such as the air compressor, precooler, molecular sieve adsorption tower, and distillation tower feed valve can coordinate and adjust to maintain stable nitrogen production and purity after pressure changes. For example, the system sends a command to the nitrogen production unit to reduce the air inlet pressure from 0.7 MPa to 0.6 MPa. The system verifies that the air compressor exhaust pressure regulation system can stabilize the pressure to the new setpoint within 30 seconds; simultaneously, the subsequent precooler power and molecular sieve adsorption tower switching time can be automatically fine-tuned and compensated; ultimately, the nitrogen product flow rate is maintained at 60 Nm³ / h, and the purity remains above 99.5%, achieving coordinated scheduling between equipment.

[0096] The system controls the startup of the power generation and routing units in the power generation and energy routing module, and issues simulated power distribution strategies or media transmission scheduling instructions to verify the execution of the grid connection control logic of the power generation unit and the scheduling and distribution control of electrical energy and media flow by the routing unit.

[0097] Among them, grid connection control logic refers to a series of control rules that a power generation unit (such as a fuel cell power generation system) must follow during startup, shutdown, and power regulation to achieve a safe connection and power exchange with the internal (or external) power grid, including synchronization, power control, frequency / voltage regulation, and protection. Dispatch and allocation control refers to the control function of the routing unit, based on instructions from the upper-level energy management system, to select paths and allocate flow of energy media such as electricity, hydrogen, and liquid ammonia flowing into its ports according to preset strategies.

[0098] Specifically, the system can simulate the voltage and frequency conditions of the internal power grid through an intelligent control module, start the fuel cell power generation unit, and verify whether its inverter can achieve synchronous grid connection and whether it can smoothly adjust the output according to the simulated power command (such as increasing from 1MW to 2MW) after grid connection. Simultaneously, it sends simulated commands to the routing unit, requesting that 3MW of the 5MW of electrical energy from the fluctuating power source be allocated to the hydrogen production unit and 2MW to the electrochemical energy storage unit; or that liquid ammonia from the storage tank be allocated to the cracking unit at a flow rate of 20m³ / h, verifying whether the corresponding power electronic switches and media valves can operate accurately to achieve the allocation target. For example, the system simulates an increase in internal power grid load and sends a command to the power generation unit to increase the output power from 2MW to 3MW. The system verifies that the fuel cell stack current, air supply, and thermal management system can respond in unison, allowing the output power to smoothly rise to the new set point within 60 seconds, with stable output voltage and frequency. At the same time, an instruction is sent to the routing unit to switch the hydrogen from storage tank A to power generation unit B. The system verifies that the corresponding hydrogen delivery pipeline valve group can complete the switching within 10 seconds, and the flow fluctuation is less than ±5%.

[0099] The pressure regulation system and safety monitoring system of the hydrogen storage tank, liquid ammonia storage tank and nitrogen storage tank in the control auxiliary module are started, and the threshold change event of the storage tank pressure or liquid level is simulated to verify the state synchronization and action triggering relationship between the pressure control loop, liquid level monitoring logic and safety interlock system.

[0100] Among them, state synchronization refers to the consistency between the monitoring data (pressure, level display values) of the control system and the actual values ​​of the field instruments, as well as the consistency of the perception of the same dangerous state among different safety systems. Action triggering relationship refers to the reliable triggering of corresponding adjustment actions (such as opening the discharge valve) or safety actions (such as starting emergency shut-off or triggering audible and visual alarms) according to a predetermined logical sequence when the monitored parameters reach the preset alarm value or interlock value.

[0101] Specifically, the system can use an intelligent control module to simulate the process of a storage tank pressure slowly rising to a high alarm value, verifying whether the pressure value displayed in the control room is synchronized with the reading of the field pressure transmitter in real time. When the pressure reaches the alarm value, it verifies whether the audible and visual alarms are accurately triggered. The system continues to simulate the pressure rising to the high-high interlock value, verifying whether the pressure regulation circuit can act first (e.g., open the pressure relief valve). If ineffective, it verifies whether the emergency shut-off valve automatically and quickly closes according to the design logic after the overpressure interlock signal is triggered, while simultaneously uploading the alarm signal to the central control system. For example, the system tests a liquid ammonia storage tank, simulating a pressure rise from 0.3 MPa by injecting a signal through software. When the simulated pressure reaches 0.45 MPa (high alarm value), the human-machine interface (HMI) in the central control room accurately issues an audible and visual alarm, and the displayed value is consistent with the injected value. The simulated pressure continued to rise to 0.48 MPa (high-high interlock value), and the system verified that the pressure regulating valve automatically opened to release pressure. If the simulated pressure release was ineffective, the pressure rose to 0.5 MPa (emergency shut-off value), and the emergency shut-off valve reliably closed within 1 second, triggering the highest level alarm. This fully verified the state synchronization and action triggering relationship between the monitoring, regulation, and protection systems.

[0102] After completing the independent system-level functional verification of each module, maintain each module in the linkage no-load operation state for a preset time, and continuously collect and record the operating status parameters of each individual device and the system coordination data between each module.

[0103] The preset duration refers to the continuous operating time set to fully observe the stability and reliability of the system under no-load linkage conditions and to collect sufficient analytical data. Operating status parameters refer to indicators reflecting the health and performance of individual devices, such as vibration, temperature, current, voltage, and speed. System coordination data refers to parameters reflecting the interaction and performance of different modules under linkage conditions, such as power interaction between modules, media flow matching degree, and control command response time difference.

[0104] Specifically, the system can initiate a timed task lasting several hours after ensuring that all modules have completed the aforementioned independent verification and entered a linked no-load state, through the intelligent control module's program. During this period, the intelligent control module's data acquisition system continuously reads data from all sensors and control units throughout the system at a fixed frequency (e.g., once per second) and stores it in a historical database. This data is used to analyze the long-term stability of the system under no-medium load conditions and to preliminarily assess the compatibility of the interfaces of each module and the real-time performance of communication. For example, the system is set to a preset duration of 2 hours. During this period, the wind turbine generator is kept idle, the photovoltaic inverter is in standby mode, the electrolyzer and reactor temperature and pressure are cyclical, the pumps and compressors are running under no-load conditions, and the routing unit ports are energized. The system continuously collects and records simulated wind speed values, generator bearing temperatures, inverter standby losses, temperature fluctuations in the jackets of each reactor, pump vibration data, voltages at each port of the routing unit, and collaborative data such as the time delay between issuing a simulated wind power fluctuation command and the start of the electrolysis current response in the hydrogen production unit, recording more than 10,000 sets of valid data points for subsequent commissioning report analysis and system optimization.

[0105] Therefore, based on the above implementation method, the system can further verify the internal collaborative working capability, control logic correctness, and preliminary cross-module linkage compatibility of a complete functional module composed of multiple devices, based on the full functionality of each individual device. This removes the obstacles at the control logic and system integration levels for subsequent introduction of actual media and full-system load testing, ensuring that the entire complex system can be put into operation safely, orderly, and efficiently.

[0106] In some embodiments, the media transmission pipeline includes a hydrogen transmission pipeline, a nitrogen transmission pipeline, and a liquid ammonia transmission pipeline; the steps of performing purging treatment and sealing tests on the media transmission pipelines and circuits connecting each module include: The system controls the flow of purging medium into the hydrogen delivery pipeline and maintains pressure, monitors pipeline pressure data, and verifies the sealing status of the hydrogen delivery pipeline based on the pressure data. The hydrogen delivery pipeline connects to the hydrogen production unit, synthesis unit, cracking unit, power generation unit, and storage tanks in the auxiliary modules.

[0107] The purging medium refers to an inert, dry, and clean gas, typically nitrogen, used to remove impurities, moisture, or air from the pipeline before a pipeline sealing test. Pressure holding refers to the process of filling the pipeline with gas at a certain pressure, closing the inlet and outlet valves, and maintaining that pressure for a specified period. Sealing verification involves comparing the pressure values ​​at the beginning and end of the pressure holding test to determine if the pressure drop is within acceptable limits, thereby assessing whether a leak exists in the pipeline system.

[0108] Specifically, the system can automatically control the relevant valves through the intelligent control module. First, isolate the hydrogen delivery pipeline from the reaction module and the storage tank, and then introduce dry nitrogen from one end of the pipeline for purging. After purging, close all valves, and use a pressurization device to raise the pressure in the pipeline to the preset test pressure value. After reaching the pressure, stop pressurization and start timing for pressure holding. During the pressure holding period, a high-precision pressure sensor continuously monitors the pipeline pressure, and the intelligent control module records the pressure data and calculates the pressure drop value. For example, the system tests the hydrogen delivery pipeline from the hydrogen production functional unit to the synthesis functional unit. First, introduce nitrogen for purging for 5 minutes, then pressurize to 3 MPa (1.5 times the design pressure of 2 MPa) and hold the pressure for 30 minutes. The intelligent control module records the initial pressure MPa, and the pressure after 30 minutes MPa, and the pressure drop value MPa. If it is lower than the allowable 0.01 MPa, it is determined that the sealing state of this section of the hydrogen delivery pipeline is qualified.

[0109] Control the introduction of the purging medium into the nitrogen delivery pipeline and conduct pressure holding, monitor the pipeline pressure data, and verify the sealing state of the nitrogen delivery pipeline based on the pressure data. The nitrogen delivery pipeline connects the nitrogen generation unit, the synthesis functional unit, the cracking functional unit, and the storage tank in the auxiliary module.

[0110] Among them, the nitrogen delivery pipeline refers to a pipeline system specifically used for transporting high-purity nitrogen, which connects the air separation nitrogen generation device, the ammonia synthesis reactor, the ammonia cracking reactor, and the nitrogen buffer storage tank.

[0111] Specifically, the system can adopt an automated test process similar to that of the hydrogen delivery pipeline through the intelligent control module, but set different test pressures according to the actual working pressure range of the nitrogen pipeline. During testing, it is necessary to ensure that the corresponding valves of the reactors and storage tanks connected to the nitrogen delivery pipeline are in the correct isolation state. For example, the system tests the nitrogen delivery pipeline from the nitrogen generation unit to the synthesis functional unit. After introducing nitrogen for purging for 3 minutes, pressurize to 2.5 MPa and hold the pressure for 30 minutes. The monitored pressure drop value is 0.006 MPa, which is lower than the allowable 0.008 MPa, and it is determined that the sealing state of this section of the nitrogen delivery pipeline is qualified.

[0112] Control the introduction of the purging medium into the liquid ammonia delivery pipeline and conduct pressure holding, monitor the pipeline pressure data, and verify the sealing state of the liquid ammonia delivery pipeline based on the pressure data. The liquid ammonia delivery pipeline connects the synthesis functional unit, the cracking functional unit, and the storage tank in the auxiliary module.

[0113] Among them, the liquid ammonia delivery pipeline refers to a cold-insulated pipeline system used for transporting low-temperature liquid ammonia, which needs to withstand the low temperature and corrosion of liquid ammonia.

[0114] Specifically, the system can control the nitrogen purging of the liquid ammonia delivery pipeline through the intelligent control module. Since liquid ammonia is easy to vaporize at room temperature and has a relatively low working pressure, the pressure setting for the pressure holding test needs to consider the design pressure of the pipeline and the saturated vapor pressure of liquid ammonia. The test should be carried out after the pipeline is dried to avoid the reaction between moisture and liquid ammonia. For example, the system tests the delivery pipeline from the liquid ammonia storage tank to the cracking functional unit. After purging and drying, the pipeline is pressurized to 1 MPa and the pressure is held for 30 minutes. The pressure drop during the pressure holding period is 0.004 MPa, which is lower than the allowed 0.005 MPa, and it is determined that the sealing state of this section of the liquid ammonia delivery pipeline is qualified.

[0115] Control the medium circulation and pressure holding test of the cooling medium circuit and the heat exchange medium circuit in the medium supply module, the energy medium bidirectional conversion module, and the power generation and energy routing module, and verify the sealing performance of each circuit based on the test data.

[0116] Among them, the cooling medium circuit refers to a closed-loop liquid (such as water, ethylene glycol solution) pipeline system used to remove the reaction heat of equipment (such as electrolytic cells, synthesis towers, fuel cells). The heat exchange medium circuit refers to a closed-loop fluid (such as heat-conducting oil, steam) pipeline system that transfers heat between different equipment. The medium circulation and pressure holding test means first starting the circulation pump to make the medium flow in the circuit to remove gas and test the functions of the pump and valves, and then stopping the circulation and pressurizing and holding the pressure of the static circuit to test the sealing performance.

[0117] Specifically, the system can start the circulation pumps of each circuit in sequence through the intelligent control module, make the medium (usually water) circulate in the circuit for a period of time, and check whether the pump body operation, pressure establishment, and flow rate are normal. Subsequently, stop the circulation pump, close the inlet and outlet valves of the circuit, pressurize (usually through a pressure test pump) and hold the pressure of the static circuit filled with the medium, and monitor the pressure change. For example, the system tests the reactor jacket cooling water circuit of the synthesis functional unit. First, start the circulation pump and run for 10 minutes, and the system pressure stabilizes at 0.8 MPa. Then stop the pump and close the valves, and raise the circuit pressure to 1.2 MPa (1.5 times the working pressure of 0.8 MPa) through the pressure test pump and hold the pressure for 60 minutes. After the pressure holding ends, the pressure drops by 0.007 MPa, which is lower than the allowed 0.01 MPa, and it is determined that the sealing performance of this cooling medium circuit is qualified.

[0118] Send electrical test signals to the power supply and control circuits connecting the fluctuating renewable energy module, the energy medium bidirectional conversion module, the power generation and energy routing module, and the intelligent control module, collect the response data, and verify the insulation resistance and loop connectivity of the circuits based on the response data.

[0119] Among them, the power supply and control circuit refers to the cable and wiring system that provides power supply (such as 380V alternating current) for each module device and transmits control signals (such as 4-20mA current signal, Ethernet signal). Insulation resistance refers to the resistance between two conductors separated by electrical insulating materials under specified conditions, and is used to measure the insulation performance. Loop connectivity refers to the characteristic that current can flow from the power supply end through the load and back to the other end of the power supply, forming a complete path. Electrical test signal refers to a standardized electrical signal used to detect the performance of a circuit, such as a high-voltage DC signal for insulation test and a low-voltage signal for connectivity test.

[0120] Specifically, the system can coordinate dedicated electrical test equipment (such as insulation resistance tester, loop resistance tester) through the intelligent control module or use the system's own power supply and measurement module to perform tests on different circuits. For the power supply cable, mainly test the insulation resistance between its phase lines and between the phase line and the ground wire. For the control signal cable, mainly test its continuity, insulation between lines and insulation to the ground. For example, the system tests the 380V AC power cable connecting the fuel cell power generation unit and the routing unit. After the line is powered off and grounded for discharge, apply a 500V DC test voltage for 60s, measure and record the insulation resistance values of the A, B, and C phase conductors to the ground wire, all of which are not less than If so, it is determined that the insulation is qualified. For a 4~20mA control signal loop from the intelligent control module to the electrolyzer current regulator, inject a low-level test current, measure the return signal at the far end, and calculate the loop resistance as If it is within the standard range (such as less than ), it is determined that the connectivity of the control loop is good.

[0121] Therefore, according to the above embodiments, before introducing actual energy media (such as hydrogen, liquid ammonia) with corrosiveness, flammability, explosiveness or low temperature into the whole set of equipment, the system can comprehensively and reliably verify the safety and integrity of all key medium conveying pipelines and electrical connections through a systematic and automated purging and sealing detection procedure, fundamentally preventing medium leakage, equipment damage and even safety accidents caused by pipeline leakage or poor circuit insulation, and providing crucial basic guarantee for subsequent safe and stable full-process load commissioning and long-term operation.

[0122] In some embodiments, the steps of introducing actual energy media, starting the fluctuating renewable energy module, and putting the energy media bi-directional conversion module, the medium supply module, the power generation and energy routing module, and the auxiliary module into the load operation state include: Control to open the seawater supply valve and the air intake valve, introduce raw materials into the water production unit and the nitrogen production unit in the medium supply module respectively, and confirm the catalyst loading status of the synthesis function unit and the cracking function unit in the energy media bi-directional conversion module.

[0123] Among them, seawater supply valves and air intake valves refer to the actuators installed on the raw material (seawater, air) conveying pipelines to control the on / off state and flow rate of the raw materials, usually electric or pneumatic regulating valves. Confirming the catalyst loading status refers to verifying, before operation under load, that the catalyst in the synthesis reactor and cracking reactor has been correctly loaded according to design requirements, and that the bed is uniform and free of short circuits. This is usually done by checking loading records, measuring bed pressure differential, or using an endoscope.

[0124] Specifically, the system can automatically or remotely and manually open the electric valves before the seawater intake pump and the electric dampers before the air compressor inlet via the intelligent control module. Simultaneously, the intelligent control module can retrieve the catalyst loading acceptance report or receive signals from the differential pressure transmitter installed on the reactor. By comparing the current bed pressure differential with the reference pressure differential at the time of loading completion, it indirectly confirms that there has been no significant loosening or settling of the catalyst bed. For example, the system controls the opening of a DN200 (nominal diameter 200 mm) electric seawater regulating valve to 30% and opens the air intake electric damper. The intelligent control module reads the differential pressure transmitter value of the catalyst bed in the synthesis reactor as 0.15 MPa, which is basically consistent with the 0.148 MPa in the loading acceptance record, with a deviation within ±5%, thus confirming that the catalyst loading status of the synthesis functional unit is normal.

[0125] The system controls the operation of the fluctuating renewable energy module for power generation and distributes the electrical energy output from the fluctuating renewable energy module to the power input terminal of the energy medium bidirectional conversion module.

[0126] "Commissioning to power generation" refers to the process of putting equipment such as wind turbine generators and photovoltaic power generation arrays from standby or idling states into actual power generation states and outputting electrical energy to the power grid. "Distribution" refers to guiding the generated electrical energy to different electrical loads according to predetermined paths and proportions through power electronic conversion equipment and switching equipment.

[0127] Specifically, the system can sequentially issue commands through the intelligent control module to release the braking of the wind turbine generators, start the photovoltaic inverters, and connect the generated electricity to the system's internal AC bus via circuit breakers and transformers. Subsequently, the intelligent control module controls the grid-connected converter or solid-state switch connected between the bus and the bidirectional energy medium conversion module to close, transmitting the bus power to the DC or AC distribution cabinets of units such as the hydrogen electrolysis unit. For example, based on current wind speed and sunlight conditions, the system controls five wind turbine generators to connect to the grid, controls all photovoltaic arrays to operate, and stabilizes the internal bus voltage at 10kV. The intelligent control module then closes the circuit breaker connected to the 10kV / 0.4kV transformer of the hydrogen electrolysis unit, distributing approximately 2MW of power to the unit's power input.

[0128] The control medium supply module operates, starts the water production process of the water production unit and supplies pure water to the hydrogen production unit, and simultaneously starts the nitrogen production process of the nitrogen production unit and supplies nitrogen to the synthesis unit.

[0129] Among them, the water production process and nitrogen production process refer to the complete and continuous production process of seawater desalination to produce pure water and air separation to produce nitrogen, including pretreatment, core separation, post-treatment and other processes.

[0130] Specifically, the system can sequentially start the seawater booster pump, pretreatment unit, high-pressure pump, reverse osmosis membrane module, and product water transfer pump in the water production unit through an intelligent control module, establishing a continuous production process from seawater to pure water. The pure water is then delivered to the pure water buffer tank in the hydrogen production unit at a set flow rate via flow meters and regulating valves. Simultaneously, the air compressor, air precooler, molecular sieve adsorption tower, expander, and distillation tower in the nitrogen production unit are started sequentially to produce high-purity nitrogen gas, which is then pressure-regulated and delivered to the feed gas buffer tank in the synthesis unit. For example, when the system starts the water production unit, the operating pressure of the reverse osmosis unit gradually increases to 6 MPa, the water production rate stabilizes at 8 m³ / h, and the conductivity of the pure water is lower than... The pure water is continuously transported to the hydrogen production unit. Simultaneously, the nitrogen production unit starts up, producing nitrogen gas with a purity of 99.6%, a flow rate of 50 Nm³ / h, and a pressure of 2.5 MPa, which is then transported to the synthesis unit.

[0131] The system controls the operation of the bidirectional energy medium conversion module, initiates the electrolysis hydrogen production process of the hydrogen production unit, and delivers the generated hydrogen to the synthesis unit; initiates the catalytic synthesis process of the synthesis unit to produce liquid ammonia, and controls the output flow of the liquid ammonia to the storage tank or cracking unit in the auxiliary module; initiates the catalytic cracking process of the cracking unit to decompose the input liquid ammonia into hydrogen and deliver it to the power generation unit.

[0132] Among them, the electrolytic hydrogen production program, catalytic synthesis program, and catalytic cracking program refer to the series of automated control sequences for the corresponding functional units, from the initial state through heating, pressurization, feeding, and reaction start-up, ultimately reaching a stable production state. Output flow control refers to the logic of guiding the produced liquid ammonia to different destinations by controlling valve switching according to the current scheduling needs of the system (storage or immediate use).

[0133] Specifically, the system can execute a preset startup script through an intelligent control module. First, power is supplied to the electrolyzer, gradually increasing the current density to activate the hydrogen purification and drying system. Qualified hydrogen is pressurized and sent to the raw material gas pipeline of the synthesis unit. Then, the heating and circulation system of the synthesis reactor is activated, raising the temperature and pressure to the reaction conditions. A hydrogen-nitrogen mixture is introduced to begin the reaction. Liquid ammonia is obtained through a controlled cooling and separation system, and the liquid ammonia discharge valve is automatically switched according to the liquid ammonia storage tank level and the needs of the cracking unit. Finally, the heating system of the cracking furnace is activated, raising the temperature to the reaction temperature. Ammonia vaporized from liquid ammonia is then introduced for cracking, and the product is purified to obtain hydrogen. For example, when the system starts the electrolysis hydrogen production program, the electrolysis current linearly climbs from 0A to 5000A within 30 minutes, achieving a hydrogen production rate of 200 Nm³ / h. The purified hydrogen has a purity greater than 99.9% and is then transported to the synthesis unit. The synthesis unit starts up, and the reaction temperature rises to [a certain value] within 2 hours (h). The pressure rises to 12 MPa, and liquid ammonia production begins. Initially, the liquid ammonia production is small, and the intelligent control module ensures that all of it is stored in the liquid ammonia storage tank. When the tank level reaches 30%, the system begins to switch a portion of the liquid ammonia (e.g., 10 Nm³ / h) to the cracking unit. The cracking unit starts up, and the cracking furnace heats up to [temperature missing] within 1.5 hours. After ammonia gas is introduced, hydrogen gas with a purity of 99.5% is produced and transported to the power generation unit.

[0134] The system controls the operation of the power generation and energy routing module, initiates the fuel cell power generation program of the power generation unit, and controls the routing unit to perform real-time allocation and dynamic scheduling of the transmission paths and flows of electrical energy, hydrogen, nitrogen, and liquid ammonia between the fluctuating renewable energy module, the bidirectional energy medium conversion module, the auxiliary module, and the power generation unit based on a preset scheduling strategy.

[0135] The fuel cell power generation process refers to the startup process of a fuel cell stack, which gradually builds up voltage and outputs power to the grid from a standby state through steps such as gas supply, humidification, heating, and soft start. The preset scheduling strategy refers to an optimized plan for energy medium conversion paths, flow allocation, and power flow, pre-formulated or calculated in real time based on boundary conditions such as renewable energy forecast power, storage tank inventory, and system load demand.

[0136] Specifically, the system can first activate the air supply system, hydrogen circulation system, and thermal management system of the fuel cell power generation unit through the intelligent control module. Once the conditions are met, the grid-connected circuit breaker is closed, and the load current is gradually increased until the output power reaches the set value. Simultaneously, the intelligent control module runs the energy management system's optimization algorithm to generate real-time scheduling commands, which are then sent to the routing unit. For example, commands might include "allocate 80% of the wind power to the electrolysis hydrogen production," "direct all the output flow from liquid ammonia storage tank A to the cracking unit B," and "set the fuel cell power generation to 1.5MW." Upon receiving the commands, the routing unit controls the corresponding power electronic switches and medium valves to achieve the required allocation and scheduling. For instance, when the system starts the fuel cell power generation program, the output power steadily increases from 0kW to 1MW within 20 minutes. Meanwhile, the intelligent control module makes decisions based on algorithms and executes scheduling through the routing unit: allocating 2.5MW of the current 3MW photovoltaic power generation to hydrogen electrolysis and 0.5MW to power the system plant; controlling the valves on the liquid ammonia delivery pipeline to distribute liquid ammonia from the storage tank to the cracking unit at a flow rate of 15m³ / h; and instructing the fuel cell to maintain its output power at 1MW.

[0137] The system synchronously collects and stores the full-process operating parameter data of the fluctuating renewable energy module, the bidirectional energy medium conversion module, the medium supply module, the power generation and energy routing module, and the auxiliary modules under load operation.

[0138] Synchronous acquisition refers to the simultaneous or near-simultaneous reading of measured values ​​from various sensors and data acquisition units distributed throughout the system during load operation, using the same time reference. Full-process operating parameter data refers to the operating status, process parameters, product quality, and energy flow data of all key equipment throughout the entire chain, from renewable energy input to medium conversion, storage, power generation, and finally, power output.

[0139] Specifically, the system can use the data acquisition and monitoring control system of the intelligent control module to poll data from hundreds or thousands of input / output channels at a fixed scanning cycle (e.g., 500ms) or through event triggering. This data includes wind speed, sunlight, power generation, electrolysis current, reaction temperature and pressure, medium flow rate and purity, tank level and pressure, fuel cell voltage and current, and routing unit port status. The acquired data is timestamped and stored in a predefined structured format in a real-time or historical database. For example, during an 8-hour load-bearing commissioning operation, the intelligent control module synchronously acquired and recorded over 200 key parameters at a frequency of twice per second, including the real-time power of the wind turbine generator, the DC voltage of the photovoltaic array, the DC current and temperature of the electrolyzer, the inlet hydrogen-to-nitrogen ratio and outlet ammonia concentration of the synthesis reactor, the liquid ammonia storage tank level, the single voltage of the fuel cell stack, and the power values ​​of each power port of the routing unit. This generated approximately 11.5 million timestamped data records, which were stored in a database file for subsequent performance analysis and report generation.

[0140] Therefore, according to the above implementation method, the system can safely, smoothly, and orderly guide the entire electro-hydrogen-ammonia bidirectional conversion system from the commissioning and preparation state to the full-process load-bearing operation state through a highly automated, programmed, and logically rigorous control sequence. This process not only verifies the ability of each module to operate independently under load, but more importantly, it verifies the collaborative working ability between modules under real material and energy interaction, the linkage logic of the control system, and the effectiveness of the preset scheduling strategy. This provides the final and most important empirical evidence for the system to be put into commercial operation and achieve stable and efficient energy autonomy.

[0141] In some embodiments, the fluctuating renewable energy module is configured with an output power prediction model, and the above method further includes: Configure the model to calculate multiple feature parameters, including the total number of prediction periods, real-time power output of the power supply, power correction coefficient, power fluctuation angular frequency, time variable, phase offset, fluctuation amplitude adjustment coefficient, maximum power output of the power supply in each historical period, minimum power output of the power supply in each historical period, attenuation coefficient, and basic power offset.

[0142] Here, the total number of prediction periods, n, refers to the number of equal parts into which the future time interval covered by the model is divided in a single prediction, used to define the scope of historical fluctuation statistics. Real-time power output. This refers to the instantaneous power generation value actually measured and fed back by the wind turbine or photovoltaic array at the moment the model starts prediction. Power correction factor. It is a dimensionless adjustment factor used to calibrate real-time power measurements or model reference values. Power fluctuation angular frequency. The angular velocity describes the periodic fluctuations of offshore wind and solar resources, measured in radians per second (rad / s). The time variable t represents the elapsed time calculated from the prediction start time, measured in seconds (s). The phase offset Y is used to adjust the initial phase angle of the periodic fluctuation curve, measured in radians (rad). The fluctuation amplitude adjustment coefficient δ is a weighting factor used to scale the impact of historical fluctuations. The maximum output power of the power source in the i-th time period is also described. With minimum output power These represent the maximum and minimum values ​​of the power supply output power actually monitored during the i-th historical statistical period, respectively. Attenuation coefficient. This determines how quickly the impact of historical fluctuations decays over time. Base power offset. This represents the base output power of the power supply under fluctuating conditions, or the base value calculated by the model. Specifically, the system can obtain the real-time output power of the power supply through the data acquisition unit of the intelligent control module. The parameters, including the total number of forecast periods n, power fluctuation angular frequency β, phase offset Y, fluctuation amplitude adjustment coefficient δ, attenuation coefficient ε, and basic power offset ζ, can be pre-set and stored in the model parameter database through spectral analysis and regression fitting of long-term historical operating data, or by system engineers based on the statistical characteristics of marine climate. The maximum output power of the power source during each historical period is also specified. With minimum output power This is provided by the historical database. For example, the system sets the total number of prediction periods n=5, meaning it considers data from the past 5 statistical periods (each period being 10 minutes). At the current moment, the real-time output power of the wind turbine generator is measured. The power is 2.5MW. The model parameters retrieved from the parameter library are: power correction coefficient. Based on the local daily wind speed cycle characteristics, the power fluctuation angular frequency β = 0.05 radians per second (rad / s), the phase offset Y = 0.3 rad, and the fluctuation amplitude adjustment coefficient are determined. attenuation coefficient Basic power offset The historical database provides the maximum and minimum power for the past five time periods as follows: .

[0143] The output power prediction model performs fusion calculations, which include: determining the periodic fluctuation power component based on the power correction coefficient, real-time power output, power fluctuation angular frequency, time variable, and phase offset; determining the historical fluctuation attenuation weight component based on the fluctuation amplitude adjustment coefficient, the difference between the maximum and minimum power output of the power supply in each historical period, the attenuation coefficient, and the time variable; and synthesizing the periodic fluctuation power component, the historical fluctuation attenuation weight component, and the basic power offset to output the predicted power output value of the power supply.

[0144] The periodic fluctuation power component refers to the part used to predict power changes caused by regular climate factors such as diurnal and semi-diurnal cycles (e.g., sea and land breezes, sunshine variations). The historical fluctuation attenuation weight component refers to the part used to predict the impact of recent historical fluctuation trends (e.g., gusts, cloud drift), but whose impact gradually diminishes over time. Fusion calculation refers to the mathematical process of combining the above two components with a base value through linear addition to obtain the final predicted value.

[0145] Specifically, the system can use the model calculation unit in the intelligent control module, according to the formula: The calculations are performed. First, the periodic fluctuation power components are calculated: Secondly, calculate the historical volatility decay weight components: This involves summing the maximum and minimum power differences for each of the past n time periods, then multiplying by a fluctuation amplitude adjustment coefficient δ and a weighting term that decays Gaussian over time. Finally, the two components mentioned above are compared with the base power offset. Add them together to obtain the predicted power output at time t. For example, to predict the power in the next 120 seconds (t=120 seconds), first calculate the periodic fluctuation component: Next, calculate the historical fluctuation attenuation component: first calculate the power difference for each time period: The summation yields 8.3MW. Then, the attenuation weight is calculated: (This is a very small number). The component is then: (Nearly 0). Final synthesized predicted value: This result indicates that, based on the current model parameters and historical data, the power is predicted to drop to approximately 0.278 MW after 120 seconds. The periodic fluctuation component has a negative impact, while the influence of historical fluctuations has been reduced to negligible levels, with the main component being the base offset.

[0146] Therefore, according to the above implementation method, the system can achieve quantitative and forward-looking prediction of power output in the short term (e.g., within minutes to hours) by mathematically modeling the output characteristics of offshore fluctuating renewable energy sources and integrating real-time power, periodic patterns, and historical fluctuation trends. This provides crucial input data for subsequent energy dispatch and conversion plans, enabling the intelligent control module to adjust the load of units such as hydrogen production and ammonia synthesis in advance based on the prediction results, or to activate backup schemes such as energy storage and cracking power generation. This effectively mitigates the impact of renewable energy fluctuations on the stable operation of the system and enhances the adaptability and operational economy of the entire energy system.

[0147] In some embodiments, the hydrogen production functional unit is configured with a hydrogen production rate calculation model, and the above method further includes: The configuration of the hydrogen production rate calculation model requires multiple characteristic parameters, including reaction rate constant, input current variable, current influence index, electrolysis reaction temperature, temperature influence index, electrolysis reaction pressure, pressure influence index, electrolysis efficiency coefficient, reactant concentration parameter, concentration threshold parameter, temperature compensation coefficient, and temperature difference variable.

[0148] Wherein, the reaction rate constant k is a coefficient characterizing the intrinsic kinetic properties of a water electrolysis reaction in a specific electrolyzer under standard conditions, and its unit is moles per ampere-second (mol / s). The input current variable I refers to the actual DC current value input to the electrolyzer, measured in amperes (A). The current influence index m is a dimensionless power exponent used to describe the nonlinear relationship between the hydrogen production rate and the current. The electrolysis reaction temperature T refers to the average operating temperature of the electrolyte inside the electrolyzer, measured in Kelvin (K) or degrees Celsius (°C). The temperature effect index *p* is a dimensionless power exponent used to describe the enhancing effect of temperature on the reaction rate. The electrolytic reaction pressure *p* refers to the operating pressure of the electrolytic cell, measured in MPa. The pressure effect index *q* is a dimensionless power exponent used to describe the inhibiting effect of pressure on the reaction rate. Electrolysis efficiency coefficient. This is the overall efficiency of the electrolysis process in converting electrical energy into the chemical energy of hydrogen; it is a dimensionless number between 0 and 1. Reactant concentration parameter. This refers to the actual concentration of water in the electrolyte, expressed in moles per liter (mol / L). Concentration threshold parameter. This is a critical water concentration value, expressed in mol / L. When the water concentration is below this value, the reaction rate will decrease significantly. The temperature compensation coefficient λ is a coefficient used to linearly correct the effect of temperature difference, expressed in cubic meters per hour per degree Celsius. Temperature difference variable The electrolysis reaction temperature T is compared with a pre-set standard reference temperature. The difference between them, i.e. The unit is .

[0149] Specifically, the system can obtain the reaction rate constant k, current influence index m, temperature influence index p, pressure influence index q, and electrolysis efficiency coefficient from the model parameter database of the intelligent control module. Concentration threshold parameters And the temperature compensation coefficient λ, these parameters are usually provided by the equipment manufacturer or calibrated through prior experiments. Input current variable I, electrolysis reaction temperature T, electrolysis reaction pressure p, reactant concentration parameters The concentration is obtained in real time by current sensors, temperature sensors, pressure sensors, and an online concentration analyzer installed on the electrolysis hydrogen production unit. Standard reference temperature. For example, 25. Or the optimal operating temperature of the electrolyzer. For example, for a hydrogen production unit using an alkaline electrolyzer, the model parameters loaded from the parameter library are: reaction rate constant. The influence factors of current (m) are 0.65, temperature (p) are 0.8, pressure (q) are 0.1, and the electrolysis efficiency coefficient is... Concentration threshold parameter mol / L, temperature compensation coefficient λ = 0.05 cubic meters per hour per degree Celsius ( ), standard reference temperature Real-time sensor measurements: input current variable I = 5000A, electrolysis reaction temperature T = 75°C, electrolysis reaction pressure p = 2MPa, reactant concentration parameters. Therefore, the temperature difference variable can be calculated. .

[0150] A comprehensive calculation is performed using a hydrogen production rate calculation model. This comprehensive calculation includes: determining the basic hydrogen production rate component based on the reaction rate constant, input current variable, current influence index, electrolysis efficiency coefficient, reactant concentration parameters, and concentration threshold parameters; determining the temperature correction component based on the electrolysis reaction temperature, temperature influence index, temperature compensation coefficient, and temperature difference variable; determining the pressure correction component based on the electrolysis reaction pressure and pressure influence index; and then performing correlation calculations on the basic hydrogen production rate component, temperature correction component, and pressure correction component to output a predicted hydrogen production rate value.

[0151] The basic hydrogen production rate component characterizes the fundamental calculation of the hydrogen production rate under specific current, efficiency, and concentration conditions. The temperature correction component characterizes the additional linear effect of the actual operating temperature relative to the standard reference temperature on the hydrogen production rate. The pressure correction component characterizes the inhibitory effect of operating pressure on the hydrogen production rate. Correlation calculations refer to calculations performed according to the formula... The above components are combined using multiplication, division, logarithmic and addition operations.

[0152] Specifically, the system can use the model calculation unit in the intelligent control module to calculate according to this formula. First, calculate the basic hydrogen production rate component: This formula calculates the basic hydrogen production rate considering the effects of current, temperature, pressure, efficiency, and concentration on several factors. Next, the temperature correction component is calculated: This formula contains a linear correction term. The pressure correction effect is already reflected in the denominator of the basic components. In the end, the predicted hydrogen production rate was... It is obtained by adding the base component and the temperature correction component: .

[0153] For example, calculations can be performed based on the aforementioned parameter example. First, the fundamental components are calculated. : (dimensions are) ); (dimensions are) ); (dimensions are) ); ; Substitute into the formula: ; Calculate the numerator: ; Calculate the denominator: ; Moles per second (mol / s); Convert the units to the more commonly used standard cubic meters per hour (Nm³ / h): ; Secondly, calculate the temperature correction component. : ; Ultimately, the predicted hydrogen production rate... .

[0154] Therefore, according to the above implementation method, the system can quickly and accurately predict the instantaneous hydrogen production capacity of the hydrogen production unit under the current operating conditions based on the real-time operating parameters (current, temperature, pressure, concentration) of the electrolyzer and preset physical properties and efficiency parameters through an integrated hydrogen production rate calculation model. This predictive capability provides a key basis for the intelligent control module to perform dynamic energy scheduling of the entire system. For example, based on the predicted hydrogen production rate and the demand of the downstream ammonia synthesis unit, the input current or the number of electrolyzers can be optimized and adjusted in real time, thereby achieving precise control of the hydrogen production load and dynamic balance of the energy flow (electricity-hydrogen-ammonia) of the entire system, improving overall operating efficiency and economy.

[0155] In some embodiments, the synthesis functional unit is configured with an ammonia yield prediction model, and the above method further includes: The configuration of the ammonia yield prediction model requires several characteristic parameters, including the reaction proportion coefficient, total pressure of the reaction system, total pressure influence index, hydrogen mole fraction, hydrogen proportion influence index, nitrogen mole fraction, nitrogen proportion influence index, pressure inhibition coefficient, pressure inhibition index, temperature influence coefficient, reaction temperature, catalyst activity coefficient, reaction residence time, and residence time influence index.

[0156] Here, the reaction proportion coefficient 'a' is a comprehensive proportionality constant related to catalyst characteristics, reactor structure, and process conditions. It is used to correlate the reaction rate with various driving factors, and its unit depends on the overall structure of the model, for example, it is moles per second per megapascal per liter (b). Total pressure of the reaction system The absolute pressure of the hydrogen-nitrogen mixture within the synthesis reactor, measured in MPa. The total pressure influence index b is a dimensionless power exponent used to describe the degree of influence of total pressure on the forward driving force of the reaction. Hydrogen mole fraction. With nitrogen mole fraction These refer to the mole fractions of hydrogen and nitrogen in the reactant gases, respectively, and are dimensionless values ​​that satisfy the following conditions: The hydrogen ratio influence index *c* and the nitrogen ratio influence index *d* are both dimensionless power exponents, used to describe the effects of the mole fractions of hydrogen and nitrogen on the reaction rate, respectively. The pressure inhibition coefficient *e* and the pressure inhibition index *f* are used to characterize the inhibitory effects on the reaction caused by factors such as over-occupancy of catalyst active sites or diffusion restriction that may occur at higher pressures. The temperature influence coefficient *g* is a coefficient related to the reaction activation energy, measured in Kelvin. This is used to characterize the Arrhenius-type effect of temperature on the reaction rate constant. The reaction temperature T refers to the average temperature of the catalyst bed within the synthesis reactor, expressed in Kelvin (K). Catalyst activity coefficient. The intrinsic reactivity coefficient refers to the catalytic production of ammonia per unit volume of catalyst per unit time, and its unit may be moles per second per cubic meter of catalyst. The residence time τ refers to the average residence time of the reactants in the catalyst bed, measured in seconds. The residence time effect index h is a dimensionless power exponent used to describe the nonlinear effect of residence time on cumulative yield.

[0157] Specifically, the system can obtain preset model constant parameters from the process database through the intelligent control module, including the reaction proportion coefficient a, total pressure influence index b, hydrogen proportion influence index c, nitrogen proportion influence index d, pressure suppression coefficient e, pressure suppression index f, temperature influence coefficient g, and residence time influence index h. Simultaneously, the total pressure of the reaction system is collected in real time by pressure sensors, temperature sensors, and an online gas analyzer installed on the synthesis reactor. Reaction temperature T and Catalyst activity coefficient The reaction residence time τ can be obtained from empirical curves based on the catalyst type and service life, while the reaction residence time τ is calculated based on the total feed gas flow rate and catalyst bed volume. For example, for a medium-pressure ammonia synthesis reactor using an iron-based catalyst, the model parameters loaded from the process database are: reaction proportion coefficient. The total pressure influence index b = 0.8, the hydrogen ratio influence index c = 1.5, the nitrogen ratio influence index d = 0.5, the pressure suppression coefficient e = 0.02, the pressure suppression index f = 1.2, and the temperature influence coefficient... The residence time influence index h=0.7. The real-time collected process parameters are: total pressure of the reaction system. The reaction temperature is T = 700 K (approximately 427°C), and the hydrogen mole fraction is... Nitrogen mole fraction The activity coefficient of the currently used catalyst The residence time τ, calculated based on the feed flow rate, is 5s.

[0158] A comprehensive calculation is performed using an ammonia yield prediction model. This calculation includes: determining the reaction driving force component based on the reaction proportion coefficient, total pressure of the reaction system, total pressure influence index, hydrogen mole fraction, hydrogen proportion influence index, nitrogen mole fraction, and nitrogen proportion influence index; determining the pressure suppression correction component based on the pressure suppression coefficient, pressure suppression index, and total pressure of the reaction system; determining the temperature influence correction component based on the temperature influence coefficient and reaction temperature; determining the space-time yield integral component based on the catalyst activity coefficient, reaction residence time, and residence time influence index; and then performing correlation calculations on the reaction driving force component, pressure suppression correction component, temperature influence correction component, and space-time yield integral component to output the predicted ammonia yield value.

[0159] Among them, the driving force component of the reaction Corresponding to the formula It combines the positive driving effects of pressure and reactant concentration on the reaction rate. Pressure suppression correction component. Corresponding to the formula It describes the reaction inhibition effect that may occur under high pressure. Temperature affects the correction component. Corresponding to the formula It characterizes the exponential effect of temperature on the reaction rate constant. Space-time yield integral component. Corresponding to the formula This reflects the ammonia yield resulting from the cumulative effect of catalyst activity over reaction residence time. Correlation calculation refers to the calculation according to the formula... The calculation involves dividing the reaction driving force component by the product of the pressure suppression correction component and the temperature effect correction component, and then multiplying by the space-time yield integral component to obtain the predicted ammonia yield. .

[0160] Specifically, the ammonia yield model for the ammonia synthesis reaction module can satisfy the following conditions: .

[0161] Therefore, according to the above implementation method, the system can utilize this ammonia yield prediction model to quickly and quantitatively predict the instantaneous ammonia yield of the synthesis functional unit under specific operating conditions based on key process parameters such as real-time reaction pressure, temperature, feed gas composition, catalyst activity, and residence time. This provides a core decision-making basis for the intelligent control module to achieve precise control and optimization of the ammonia synthesis process. For example, the prediction results can be used to dynamically adjust the reactor's feed flow rate, pressure, or temperature setpoints to ensure stable operation under the goal of optimal energy efficiency or maximum output, thereby effectively improving the operational economy and product output controllability of the entire electro-hydrogen-ammonia bidirectional conversion system.

[0162] In some embodiments, the pyrolysis functional unit is configured with a hydrogen purity model, and the above method further includes: The configuration of the hydrogen purity prediction model requires several characteristic parameters, including the cracking efficiency coefficient, cracking reaction rate, cracking rate influence index, membrane separation area, membrane area influence index, ammonia concentration influence coefficient, uncracked ammonia concentration, ammonia concentration influence index, pressure difference influence coefficient, pressure difference across the membrane, multiple impurity influence coefficients, separation time, and number of impurity types.

[0163] The cracking efficiency coefficient μ is a dimensionless efficiency factor related to catalyst activity, reactor design, and operating conditions. It typically ranges from 0 to 1 and characterizes the approximation of the theoretical maximum efficiency in converting ammonia to hydrogen. The cracking reaction rate... This refers to the progress of ammonia cracking reaction per unit volume or mass of catalyst per unit time, expressed in units of... Or similar. The cracking rate effect index v is a dimensionless power exponent used to describe the nonlinear effect of the cracking reaction rate on the final hydrogen purity. Membrane separation area. The total effective area of ​​the selective permeation membrane used to separate and purify hydrogen from cracked gas is measured in square meters (m²). The membrane area effect index *w* is a dimensionless power exponent used to describe the scale effect of membrane area on hydrogen separation and purification capabilities. The ammonia concentration effect coefficient *σ* is a coefficient related to the selective permeation characteristics of the membrane material for ammonia, measured in moles per liter (m²). Uncracked ammonia concentration The concentration of residual, unreacted ammonia gas in the pyrolysis gas entering the membrane separation module is expressed in mol / L. The ammonia concentration influence index z is a dimensionless power exponent used to describe the degree to which ammonia concentration inhibits membrane separation performance. The pressure difference influence coefficient ρ is a coefficient related to the membrane material permeability coefficient and module structure, expressed in megapascals (MPa). The pressure difference Δp across the membrane refers to the transmembrane pressure difference that drives hydrogen gas to permeate the membrane, i.e., the absolute pressure difference between the feed side and the permeate side, expressed in MPa. Multiple impurity influence coefficients. These are a set of dimensionless coefficients, each characterizing the adsorption or permeation-impeding effect of the j-th impurity gas (such as nitrogen, residual ammonia, trace hydrocarbons, etc.) on the membrane surface. Separation time t refers to the average residence time of the cracked gas within the membrane separation module or the continuous operating time of the membrane, measured in seconds. The number of impurity types m refers to the total number of impurity gas types considered in the model that significantly affect hydrogen purity.

[0164] Specifically, the system can obtain preset model constant parameters from the process database through the intelligent control module, including the pyrolysis efficiency coefficient μ, the pyrolysis rate influence index v, the membrane area influence index w, the ammonia concentration influence coefficient σ, the ammonia concentration influence index z, the pressure difference influence coefficient ρ, and the influence coefficients of various impurities. Meanwhile, the pyrolysis reaction rate is collected in real time or periodically by sensors installed in the pyrolysis and membrane separation units. Membrane separation area (Typically a fixed design value), uncracked ammonia concentration The pressure difference Δp across the membrane and the separation time t are considered. The number of impurity types m is determined based on the types of impurities that may exist in the process flow. For example, for a pyrolysis unit using a palladium composite membrane for hydrogen purification, the model parameters loaded from the process database are: pyrolysis efficiency coefficient μ=0.88, pyrolysis rate influence index v=0.7, membrane area influence index w=0.9, ammonia concentration influence coefficient σ=0.05, ammonia concentration influence index z=1.2, and pressure difference influence coefficient ρ=0.1. Two main impurities are considered: nitrogen ( =0.02) and residual methane ( =0.005), meaning the number of impurity types m=2. The real-time collected process parameters are: pyrolysis reaction rate. Membrane separation area =200m², concentration of uncracked ammonia =0.01mol / L, pressure difference across the membrane Δp=0.5MPa, separation time t=10s.

[0165] A comprehensive calculation is performed using a hydrogen purity prediction model. This calculation includes: determining the pyrolysis efficiency component based on the pyrolysis efficiency coefficient, pyrolysis reaction rate, and pyrolysis rate influence index; determining the separation efficiency component based on the membrane separation area and membrane area influence index; determining the ammonia concentration suppression component based on the ammonia concentration influence coefficient, unpyrolyzed ammonia concentration, and ammonia concentration influence index; determining the pressure difference influence component based on the pressure difference influence coefficient and the pressure difference across the membrane; determining the impurity cumulative influence component based on the impurity influence coefficients, separation time, and number of impurity types; and then performing correlation calculations on the pyrolysis efficiency component, separation efficiency component, ammonia concentration suppression component, pressure difference influence component, and impurity cumulative influence component to output the predicted hydrogen purity value.

[0166] Wherein, the pyrolysis efficiency component corresponds to the formula in It characterizes the fundamental contribution of the pyrolysis reaction itself to the purity of the generated hydrogen. The separation efficiency component corresponds to the formula in... This characterizes the positive effect of membrane separation area on hydrogen purification capacity. The ammonia concentration suppression component corresponds to the formula in... This characterizes the fouling or competitive inhibition effect of uncracked ammonia on the membrane separation process. The pressure difference component corresponds to the component in the formula. It characterizes the effect of the driving force. The component of accumulated impurities corresponds to the one in the formula. It describes the productive decay effect of various impurities on purity accumulated over separation time. Correlation operation refers to the operation according to the formula... The calculation involves multiplying the cracking efficiency component of the aforementioned molecular fraction by the separation efficiency component, dividing by the sum of the ammonia concentration suppression component and the pressure difference influence component, and then multiplying by the impurity accumulation influence component to finally obtain the predicted hydrogen purity value. .

[0167] Therefore, according to the above implementation method, the system can utilize this hydrogen purity prediction model to dynamically predict the purity of hydrogen produced by the pyrolysis unit based on real-time pyrolysis reaction conditions, membrane separation conditions, and operating time. This provides a key basis for the intelligent control module to optimize the pyrolysis and separation process, for example, by adjusting the pyrolysis temperature (which affects...). ), membrane module pressure difference Or switch membrane modules (affecting) This is to maintain or improve the purity of hydrogen, ensure the quality of fuel supplied to the power generation unit, thereby ensuring the stability and efficiency of the entire power generation process, and effectively assess the performance degradation of the membrane separation component over time.

[0168] In some embodiments, the characteristic parameters include electrical energy weighting coefficient, input electrical energy, electrical energy influence index, hydrogen energy weighting coefficient, input hydrogen energy, hydrogen energy influence index, ammonia energy weighting coefficient, input ammonia energy, ammonia energy influence index, electrical energy loss coefficient, electrical energy loss amount, hydrogen energy loss coefficient, hydrogen energy loss amount, ammonia energy loss coefficient, ammonia energy loss amount, phase influence coefficient, energy conversion phase difference, and basic efficiency offset.

[0169] Among them, the electrical energy weighting coefficient ω, the hydrogen energy weighting coefficient φ, and the ammonia energy weighting coefficient ψ are dimensionless coefficients used to measure the importance or contribution weight of electrical energy, hydrogen energy, and ammonia energy in the comprehensive evaluation system. Their values ​​typically range from 0 to 1, and the sum of the three can equal 1, representing the differentiated consideration of the value of different forms of energy. Input electrical energy Input hydrogen energy Input ammonia energy These represent the numerical values ​​of electrical energy, hydrogen energy, and ammonia energy entering the system or participating in the evaluation within a specific statistical period, expressed in joules (J) or kilowatt-hours (kWh). The electrical energy impact index s, hydrogen energy impact index t, and ammonia energy impact index u are all dimensionless power exponents used to describe the nonlinear impact of different forms of energy input on the overall efficiency index, typically calibrated based on the energy conversion characteristics of the actual system. The electrical energy loss coefficient ξ, hydrogen energy loss coefficient χ, and ammonia energy loss coefficient ω are the proportions or conversion coefficients related to calculating electrical energy loss, hydrogen energy loss, and ammonia energy loss, respectively; their specific physical meanings depend on the loss model. Electrical energy loss amount. Hydrogen energy loss Ammonia energy loss These represent the energy losses during the conversion, storage, or transmission of the corresponding energy form, with units identical to the input energy. The phase influence coefficient κ is a dimensionless coefficient used to adjust the degree of influence of the energy conversion phase difference on the efficiency assessment value. The energy conversion phase difference Δθ refers to the measure of the synchronicity of different energy flows in time or phase during multi-energy coupling conversion, with units of rad. The baseline efficiency offset τ is a constant term representing the inherent baseline conversion efficiency level of the system or the model calibration benchmark, and is a dimensionless value.

[0170] Specifically, the system can use the energy management unit of the intelligent control module to obtain the cumulative values ​​of electrical energy, hydrogen energy, and ammonia energy input into the system within a specified time period (e.g., the past hour) from a real-time database as... , , Simultaneously, based on the measurement and loss models of each stage, the corresponding... , , Weighting coefficients Impact Index Loss coefficient The phase influence coefficient κ and the basic offset τ are used as model parameters, which are usually preset by the system designer based on energy policy, economic cost, or technical characteristics, or calibrated by regression analysis of historical operating data and then stored in the model parameter database. The energy conversion phase difference Δθ can be obtained by analyzing the correlation or phase difference of time series data of different energy flows (such as the power generation curve and the hydrogen production load curve). For example, within an evaluation period, the system measures the input electrical energy... kWh, input hydrogen energy kWh (calculated based on calorific value), input ammonia energy kWh. Preset weighting coefficients. The impact index is calibrated as follows: The calculated power loss kWh, hydrogen energy loss kWh, ammonia energy loss kWh. Preset loss factor. The calculated energy conversion phase difference Δθ = 0.2 rad under the current operating conditions is as follows: Preset phase influence coefficient κ = 0.5, and basic efficiency offset τ = 0.05.

[0171] A comprehensive evaluation calculation is performed using an energy conversion efficiency model. This calculation includes: determining the effective component of electrical energy based on the electrical energy weighting coefficient, input electrical energy, and electrical energy influence index; determining the effective component of hydrogen energy based on the hydrogen energy weighting coefficient, input hydrogen energy, and hydrogen energy influence index; determining the effective component of ammonia energy based on the ammonia energy weighting coefficient, input ammonia energy, and ammonia energy influence index; determining the total system loss component based on the electrical energy loss coefficient and electrical energy loss, hydrogen energy loss coefficient and hydrogen energy loss, and ammonia energy loss coefficient and ammonia energy loss; and correlating the combined results of the effective components of electrical energy, hydrogen energy, and ammonia energy with the total system loss component. The calculation results are then corrected based on the phase influence coefficient, energy conversion phase difference, and basic efficiency offset to output an energy conversion efficiency evaluation value.

[0172] Wherein, the effective components of electrical energy, hydrogen energy, and ammonia energy correspond to the following in the formula: These represent the "effective contribution value" of each input energy source after weighting and exponential adjustment. The total system loss component corresponds to the value in the formula. It represents the total energy loss of the system after being weighted by the corresponding loss coefficient. Correlation calculation refers to the calculation according to the formula: The calculation involves dividing the sum of all effective components by the total loss components, and then multiplying by a correction factor determined by the phase difference. Finally, the baseline efficiency offset τ is added to obtain the energy conversion efficiency assessment value. .

[0173] Therefore, according to the above implementation method, the system can use this energy conversion efficiency model to comprehensively consider the input, loss, and spatiotemporal coupling characteristics (reflected by phase difference) of three heterogeneous energy sources: electricity, hydrogen, and ammonia, and calculate a unified and quantitative comprehensive efficiency evaluation index. This allows the intelligent control module to objectively evaluate the energy efficiency level of the current system operation mode based on this index, and seek higher efficiency by adjusting energy routing strategies and optimizing the load allocation of each conversion unit. This value enables continuous optimization and improvement of the overall energy conversion efficiency of the system.

[0174] The specific functions and examples of each module and submodule of the device in this embodiment can be found in the relevant descriptions of the corresponding steps in the above method embodiments, and will not be repeated here.

[0175] According to a fourth aspect, the present invention provides a computer device comprising: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the control method of the bidirectional electro-hydrogen-ammonia conversion system of any marine energy island in the embodiments of the present invention.

[0176] According to another aspect of the present invention, a non-transient computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause a computer to execute the control method of the bidirectional electro-hydrogen-ammonia conversion system of any of the marine energy islands in the embodiments of the present invention.

[0177] Figure 4 A schematic block diagram of an example computer device 600 that can be used to implement embodiments of the present invention is shown. The computer device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The computer device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0178] like Figure 4As shown, the computer device 600 includes a computing unit 601, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. The RAM 603 may also store various programs and data required for the operation of the computer device 600. The computing unit 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0179] Multiple components in computer device 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of monitors, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows computer device 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0180] The computing unit 601 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as a method for regulating a bidirectional electro-hydrogen-ammonia conversion system for an offshore energy island. For example, in some embodiments, a method for regulating a bidirectional electro-hydrogen-ammonia conversion system for an offshore energy island can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed on the computer device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the method for regulating a bidirectional electro-hydrogen-ammonia conversion system for an offshore energy island described above can be performed. Alternatively, in other embodiments, the computing unit 601 may be configured by any other suitable means (e.g., by means of firmware) to perform a method for regulating a bidirectional electro-hydrogen-ammonia conversion system for a marine energy island.

[0181] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0182] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0183] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0184] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT or LCD monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual, auditory, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0185] The systems and technologies described herein can be implemented in computing systems that include back-end components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0186] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0187] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this is not limited herein.

[0188] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of this invention should be included within the scope of protection of this invention.

Claims

1. A bidirectional electro-hydrogen-ammonia conversion system for a marine energy island, characterized in that, It includes a fluctuating renewable energy module, an energy medium bidirectional conversion module, a medium supply module, a power generation and energy routing module, an auxiliary module, and an intelligent control module; The power output terminal of the fluctuating renewable energy module is connected to the power input terminal of the bidirectional energy medium conversion module; The energy medium bidirectional conversion module is equipped with a hydrogen production unit, a synthesis unit, and a cracking unit. The medium supply module is equipped with a water production unit and a nitrogen production unit. The pure water output terminal of the water production unit is connected to the raw material input terminal of the hydrogen production unit, and the nitrogen output terminal of the nitrogen production unit is connected to the raw material input terminal of the synthesis unit. The power generation and energy routing module is equipped with a power generation unit and a routing unit, and the hydrogen output terminal of the cracking functional unit is connected to the fuel input terminal of the power generation unit. The auxiliary module is connected to the bidirectional energy medium conversion module, the medium supply module, and the power generation and energy routing module. The intelligent control module is connected to the fluctuating renewable energy module, the bidirectional energy medium conversion module, the medium supply module, the power generation and energy routing module, and the auxiliary module.

2. A commissioning method for an electro-hydrogen-ammonia bidirectional conversion system, characterized in that, The method, based on the bidirectional electro-hydrogen-ammonia conversion system as described in claim 1, is applied to the intelligent control module and includes: Based on the preset phased debugging principle, the core individual equipment in the fluctuating renewable energy module, the bidirectional energy medium conversion module, the medium supply module, the power generation and energy routing module, and the auxiliary module are sequentially subjected to medium-free and load-free operation verification, and system-level functional verification is performed on each module. In response to the completion of system-level functional verification of each module, the devices in each module are controlled to start up in the preset order of the fluctuating renewable energy module, the water production unit in the medium supply module, the hydrogen production unit in the energy medium bidirectional conversion module, the nitrogen production unit in the medium supply module, the synthesis and cracking units in the energy medium bidirectional conversion module, the power generation unit in the power generation and energy routing module, and the routing unit in the power generation and energy routing module. In the system linkage no-load operation state after each unit is started, the medium transmission pipelines and circuits connecting each module are purged and tested for sealing. In response to the qualified testing of the medium transmission pipeline and circuit, the actual energy medium is introduced, the fluctuating renewable energy module is started, and the energy medium bidirectional conversion module, the medium supply module, the power generation and energy routing module and the auxiliary module are put into load operation state to perform the full-process load commissioning of the electric-hydrogen-ammonia bidirectional conversion system.

3. The method according to claim 2, characterized in that, The steps of performing no-medium, no-load operation verification on the core individual devices within the fluctuating renewable energy module, the bidirectional energy medium conversion module, the medium supply module, the power generation and energy routing module, and the auxiliary module in accordance with the preset phased debugging principle include: The wind turbine generator, photovoltaic array and electrochemical energy storage device in the fluctuating renewable energy module were started under no-load conditions, and the response and execution status of the pitch system, yaw system and charge / discharge system to control commands, as well as the triggering of overvoltage and overcurrent protection logic, were verified. Inert gas purging and no-load start-up were performed on the electrolyzer included in the hydrogen production functional unit, the synthesis reactor included in the synthesis functional unit, and the cracking reactor included in the cracking functional unit in the energy medium bidirectional conversion module, respectively, and the adjustment functions of the temperature control loop and the pressure control loop, as well as the interlocking action of the safety valve group, were verified. The seawater desalination device, reverse osmosis or electrodialysis device included in the water production unit of the media supply module, and the air compressor, distillation column and pressure swing adsorption device included in the nitrogen production unit are started under no-load conditions to verify the start-stop control and parameter adjustment functions of the pump body, valves and refrigeration system, and to test the sealing of the associated pipelines. The fuel cell stack and inverter included in the power generation unit of the power generation and energy routing module, as well as the power electronic converter, medium delivery valve and pump body included in the routing unit, are started under no-load conditions, and the voltage conversion control, power distribution strategy execution, medium flow regulation control and electrical protection logic are verified. The hydrogen storage tank, liquid ammonia storage tank, and nitrogen storage tank in the auxiliary module are subjected to airtightness testing, and the accuracy of the acquisition and processing of tank pressure and liquid level monitoring data, the execution of control commands by the regulating valve, and the safety interlock triggering conditions of the emergency shut-off valve are verified.

4. The method according to claim 2, characterized in that, The steps for performing system-level functional verification on each module include: The system controls the coordinated startup of wind turbine generators, photovoltaic power generation arrays, and electrochemical energy storage devices in the fluctuating renewable energy module, issues simulated power fluctuation commands, verifies the response logic of each subsystem to the simulated command, and collects coordinated operation data under simulated fluctuating conditions. The hydrogen production unit, synthesis unit, and cracking unit in the bidirectional energy medium conversion module are started respectively. Inert gas is introduced into the electrolyzer in the hydrogen production unit and the synthesis reactor in the synthesis unit. Simulated electrolysis current adjustment commands or reactor temperature and pressure adjustment commands are issued to verify the parameter coupling relationship between the relevant control loops inside the hydrogen production unit, synthesis unit, and cracking unit, and to monitor the linkage control response of each unit. The water production unit and the nitrogen production unit in the medium supply module are started respectively, and simulated water flow rate adjustment command or air pressure adjustment command is issued to verify the control timing connection and equipment coordinated scheduling between the processing units inside the water production unit and the nitrogen production unit. The system controls the startup of the power generation unit and the routing unit in the power generation and energy routing module, and issues simulated power distribution strategies or media transmission scheduling instructions to verify the execution of the grid connection control logic of the power generation unit and the scheduling and distribution control of the routing unit for electrical energy and media flow. The pressure regulation system and safety monitoring system of the hydrogen storage tank, liquid ammonia storage tank and nitrogen storage tank in the auxiliary module are started, and the threshold change event of the storage tank pressure or liquid level is simulated to verify the state synchronization and action triggering relationship between the pressure control loop, liquid level monitoring logic and safety interlock system. After completing the independent system-level functional verification of each module, maintain each module in the linked no-load operation state for a preset time, and continuously collect and record the operating status parameters of each individual device and the system coordination data between each module.

5. The method according to claim 2, characterized in that, The media transmission pipeline includes a hydrogen transmission pipeline, a nitrogen transmission pipeline, and a liquid ammonia transmission pipeline; the steps of performing purging treatment and sealing test on the media transmission pipelines and circuits connecting each module include: The system controls the flow of purging medium into the hydrogen delivery pipeline and maintains pressure, monitors the pipeline pressure data, and verifies the sealing status of the hydrogen delivery pipeline based on the pressure data. The hydrogen delivery pipeline is connected to the hydrogen production unit, the synthesis unit, the cracking unit, the power generation unit, and the storage tank in the auxiliary module. The nitrogen delivery pipeline is controlled to be purged with a purging medium and pressure maintained. The pipeline pressure data is monitored, and the sealing status of the nitrogen delivery pipeline is verified based on the pressure data. The nitrogen delivery pipeline is connected to the nitrogen generation unit, the synthesis functional unit, the pyrolysis functional unit, and the storage tank in the auxiliary module. The system controls the flow of purging medium into the liquid ammonia delivery pipeline and maintains pressure, monitors the pipeline pressure data, and verifies the sealing status of the liquid ammonia delivery pipeline based on the pressure data. The liquid ammonia delivery pipeline is connected to the synthesis functional unit, the pyrolysis functional unit, and the storage tank in the auxiliary module. The control system performs medium circulation and pressure holding tests on the cooling medium circuit and heat exchange medium circuit in the medium supply module, the energy medium bidirectional conversion module, and the power generation and energy routing module, and verifies the sealing performance of each circuit based on the test data. Electrical test signals are sent to the power supply and control circuits connecting the fluctuating renewable energy module, the bidirectional energy medium conversion module, the power generation and energy routing module, and the intelligent control module. Response data is collected, and the insulation resistance and loop connectivity of the circuit are verified based on the response data.

6. The method according to claim 2, characterized in that, The steps of introducing an actual energy medium, activating the fluctuating renewable energy module, and putting the energy medium bidirectional conversion module, the medium supply module, the power generation and energy routing module, and the auxiliary module into a load-bearing operation state include: Control the opening of the seawater supply valve and the air intake valve to introduce raw materials into the water production unit and the nitrogen production unit in the medium supply module, respectively, and confirm the catalyst loading status of the synthesis functional unit and the cracking functional unit in the energy medium bidirectional conversion module; The system controls the fluctuating renewable energy module to start generating electricity and distributes the electrical energy output by the fluctuating renewable energy module to the power input terminal of the energy medium bidirectional conversion module. The operation of the medium supply module is controlled, the water production process of the water production unit is started and pure water is supplied to the hydrogen production unit, and the nitrogen production process of the nitrogen production unit is started and nitrogen is supplied to the synthesis unit. The system controls the operation of the bidirectional energy medium conversion module, initiates the electrolytic hydrogen production process of the hydrogen production unit, and delivers the generated hydrogen to the synthesis unit; initiates the catalytic synthesis process of the synthesis unit to produce liquid ammonia, and controls the output flow of the liquid ammonia to either the storage tank in the auxiliary module or the cracking unit; initiates the catalytic cracking process of the cracking unit to decompose the input liquid ammonia into hydrogen and deliver it to the power generation unit. The system controls the operation of the power generation and energy routing module, starts the fuel cell power generation program of the power generation unit, and controls the routing unit to perform real-time allocation and dynamic scheduling of the transmission paths and flows of electrical energy, hydrogen, nitrogen and liquid ammonia between the fluctuating renewable energy module, the energy medium bidirectional conversion module, the auxiliary module and the power generation unit based on a preset scheduling strategy. The system synchronously collects and stores the full-process operating parameter data of the fluctuating renewable energy module, the bidirectional energy medium conversion module, the medium supply module, the power generation and energy routing module, and the auxiliary module under load operation.

7. The method according to claim 2, characterized in that, The fluctuating renewable energy module is equipped with an output power prediction model, and the method further includes: Configure multiple feature parameters required for model calculation, including the total number of prediction periods, real-time power output of the power supply, power correction coefficient, power fluctuation angular frequency, time variable, phase offset, fluctuation amplitude adjustment coefficient, maximum power output of the power supply in each historical period, minimum power output of the power supply in each historical period, attenuation coefficient, and basic power offset. The output power prediction model is used to perform a fusion calculation, which includes: determining a periodic fluctuation power component based on the power correction coefficient, the real-time output power of the power supply, the power fluctuation angular frequency, the time variable, and the phase offset; determining a historical fluctuation attenuation weight component based on the fluctuation amplitude adjustment coefficient, the difference between the maximum and minimum output power of the power supply in each historical period, the attenuation coefficient, and the time variable; and synthesizing the periodic fluctuation power component, the historical fluctuation attenuation weight component, and the basic power offset to output the predicted value of the power supply output power.

8. The method according to claim 2, characterized in that, The hydrogen production functional unit is equipped with a hydrogen production rate calculation model, and the method further includes: The hydrogen production rate calculation model is configured with multiple characteristic parameters, including reaction rate constant, input current variable, current influence index, electrolysis reaction temperature, temperature influence index, electrolysis reaction pressure, pressure influence index, electrolysis efficiency coefficient, reactant concentration parameter, concentration threshold parameter, temperature compensation coefficient, and temperature difference variable. A comprehensive calculation is performed using the hydrogen production rate calculation model. This comprehensive calculation includes: determining a basic hydrogen production rate component based on the reaction rate constant, the input current variable, the current influence index, the electrolysis efficiency coefficient, the reactant concentration parameter, and the concentration threshold parameter; determining a temperature correction component based on the electrolysis reaction temperature, the temperature influence index, the temperature compensation coefficient, and the temperature difference variable; determining a pressure correction component based on the electrolysis reaction pressure and the pressure influence index; and performing a correlation operation on the basic hydrogen production rate component, the temperature correction component, and the pressure correction component to output a predicted hydrogen production rate value.

9. The method according to claim 2, characterized in that, The synthetic functional unit is equipped with an ammonia yield prediction model, and the method further includes: The ammonia yield prediction model is configured with multiple characteristic parameters, including reaction ratio coefficient, total pressure of the reaction system, total pressure influence index, hydrogen mole fraction, hydrogen ratio influence index, nitrogen mole fraction, nitrogen ratio influence index, pressure inhibition coefficient, pressure inhibition index, temperature influence coefficient, reaction temperature, catalyst activity coefficient, reaction residence time and residence time influence index. The ammonia yield prediction model is used to perform a comprehensive calculation, which includes: determining the reaction driving force component based on the reaction proportion coefficient, the total pressure of the reaction system, the total pressure influence index, the hydrogen mole fraction, the hydrogen proportion influence index, the nitrogen mole fraction, and the nitrogen proportion influence index; determining the pressure suppression correction component based on the pressure suppression coefficient, the pressure suppression index, and the total pressure of the reaction system; determining the temperature influence correction component based on the temperature influence coefficient and the reaction temperature; determining the space-time yield integral component based on the catalyst activity coefficient, the reaction residence time, and the residence time influence index; and performing correlation calculations on the reaction driving force component, the pressure suppression correction component, the temperature influence correction component, and the space-time yield integral component to output the predicted ammonia yield value.

10. The method according to claim 2, characterized in that, The pyrolysis functional unit is equipped with a hydrogen purity model, and the method further includes: The hydrogen purity prediction model is configured with multiple characteristic parameters, including the cracking efficiency coefficient, cracking reaction rate, cracking rate influence index, membrane separation area, membrane area influence index, ammonia concentration influence coefficient, uncracked ammonia concentration, ammonia concentration influence index, pressure difference influence coefficient, pressure difference across the membrane, multiple impurity influence coefficients, separation time, and number of impurity types. The hydrogen purity prediction model performs a comprehensive calculation, which includes: determining the pyrolysis efficiency component based on the pyrolysis efficiency coefficient, the pyrolysis reaction rate, and the pyrolysis rate influence index; determining the separation efficiency component based on the membrane separation area and the membrane area influence index; determining the ammonia concentration suppression component based on the ammonia concentration influence coefficient, the unpyrolyzed ammonia concentration, and the ammonia concentration influence index; determining the pressure difference influence component based on the pressure difference influence coefficient and the pressure difference across the membrane; determining the impurity cumulative influence component based on each impurity influence coefficient, the separation time, and the number of impurity types; and performing correlation calculations on the pyrolysis efficiency component, the separation efficiency component, the ammonia concentration suppression component, the pressure difference influence component, and the impurity cumulative influence component to output a predicted hydrogen purity value.

11. The method according to claim 2, characterized in that, The power generation and energy routing module is configured with an energy conversion efficiency model, and the method further includes: The energy conversion efficiency model is configured with multiple characteristic parameters, including electrical energy weighting coefficient, input electrical energy, electrical energy influence index, hydrogen energy weighting coefficient, input hydrogen energy, hydrogen energy influence index, ammonia energy weighting coefficient, input ammonia energy, ammonia energy influence index, electrical energy loss coefficient, electrical energy loss amount, hydrogen energy loss coefficient, hydrogen energy loss amount, ammonia energy loss coefficient, ammonia energy loss amount, phase influence coefficient, energy conversion phase difference, and basic efficiency offset. A comprehensive evaluation calculation is performed using the energy conversion efficiency model. This calculation includes: determining the effective component of electrical energy based on the electrical energy weighting coefficient, the input electrical energy, and the electrical energy influence index; determining the effective component of hydrogen energy based on the hydrogen energy weighting coefficient, the input hydrogen energy, and the hydrogen energy influence index; determining the effective component of ammonia energy based on the ammonia energy weighting coefficient, the input ammonia energy, and the ammonia energy influence index; determining the total system loss component based on the electrical energy loss coefficient and the electrical energy loss, the hydrogen energy loss coefficient and the hydrogen energy loss, and the ammonia energy loss coefficient and the ammonia energy loss; and correlating the combined result of the effective components of electrical energy, hydrogen energy, and ammonia energy with the total system loss component, and correcting the calculation result based on the phase influence coefficient, the energy conversion phase difference, and the basic efficiency offset to output an energy conversion efficiency evaluation value.

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