A hydrogen production device and method using low-energy consumption alkaline electrolysis of water

Abstract

The application discloses a low-energy-consumption hydrogen production device and method by alkaline electrolysis of water, the device comprises a hydrogen collection system, an oxygen collection system, an intelligent control system and the like; the hydrogen collection system is provided with a catalytic combustion sensor to realize multidimensional detection and graded early warning; the intelligent control system integrates various sensors, a catalyst activity dynamic monitoring module, a central processing unit, an actuator and the like, can monitor and control the operating parameters of the electrolytic cell assembly in real time, automatically adjusts the current density to prolong the service life of the catalyst, can also predict the performance change trend and adjust the operating parameters in advance to prolong the service life of the electrolytic cell assembly; the method utilizes the intelligent control system to realize fine management of the electrolytic cell assembly, automatically adjusts the operation mode through real-time monitoring data and a prediction model, fully utilizes renewable energy, and reduces energy consumption and cost. The application realizes the intelligentization, automation and high efficiency of the hydrogen production process by alkaline electrolysis of water through the intelligent control technology.

Description

Technical Field

[0001] This invention belongs to the technical field of alkaline water electrolysis for hydrogen production, specifically relating to a low-energy-consumption alkaline water electrolysis hydrogen production device and method. Background Technology

[0002] Existing hydrogen production facilities generally employ static operation control strategies, lacking real-time sensing capabilities for the internal state of the electrolyzer. They can only monitor threshold values ​​for basic parameters such as temperature and pressure, failing to provide in-situ diagnosis of core performance indicators such as catalyst activity decay and membrane ion conductivity degradation. This leads to a continuous increase in energy consumption and a significant decrease in electrolysis efficiency during long-term operation. At the materials level, reliance on precious metal catalysts results in high costs, and the membrane is susceptible to electrolyte contamination, causing voltage increases. Furthermore, traditional technologies lack effective catalyst performance monitoring and regeneration mechanisms, and insufficient material lifespan further increases the overall cost of hydrogen production.

[0003] In terms of system integration, existing devices are limited by their narrow power operating range, making it difficult to adapt to the wide fluctuations in power from renewable energy sources such as wind and solar power. Sudden power changes can easily trigger overheating of the electrolyzer and gas cross-contamination risks, resulting in low utilization rates of renewable energy. Data management also suffers from serious deficiencies; locally stored operational data lacks tamper-proof mechanisms and cannot meet the stringent requirements for data authenticity in green hydrogen carbon footprint tracking and carbon credit trading. Furthermore, conventional equipment exhibits technical defects such as electrolyte solidification and sealing failure in low-temperature, high-humidity, or high-dust environments, severely limiting its application potential in distributed hydrogen production scenarios. These interconnected technical shortcomings have become key obstacles to the commercialization of alkaline water electrolysis for hydrogen production. Summary of the Invention

[0004] The purpose of this invention is to provide a low-energy alkaline water electrolysis hydrogen production device and method. Through an intelligent control system, it achieves refined management and adaptive optimization of the electrolyzer components. By combining high-efficiency materials and advanced control strategies, it significantly reduces hydrogen production energy consumption, improves electrolysis efficiency and safety, and supports renewable energy coupling and reliable data management. This solves the problems of high energy consumption, poor stability and high operation and maintenance costs of traditional water electrolysis hydrogen production devices.

[0005] To achieve the above objectives, the present invention provides the following solution: A low-energy alkaline water electrolysis hydrogen production device includes: a hydrogen collection system, an oxygen collection system, an electrolyzer assembly, and an intelligent control system.

[0006] The hydrogen collection system is connected to the cathode chamber and equipped with a catalytic combustion sensor to achieve multi-dimensional detection and graded early warning of hydrogen leakage. When the hydrogen concentration exceeds the set threshold, the intelligent control system automatically shuts off the inlet valve and power supply of the corresponding electrolyzer and starts inert gas purging.

[0007] The oxygen collection system is connected to the anode chamber and is equipped with a catalytic combustion sensor to collect the generated oxygen.

[0008] The intelligent control system is connected to the electrolytic cell assembly and is used for real-time monitoring and control of operating parameters. This intelligent control system includes: Multiple sensors are installed at different locations on the electrolytic cell assembly to monitor parameters such as temperature, pressure, current, voltage, electrolyte concentration, and liquid level in real time. The catalyst activity dynamic monitoring module evaluates catalyst performance in real time through in-situ Raman spectroscopy or electrochemical impedance spectroscopy. The central processing unit is connected to various sensors, receives parameter data and analyzes the operating status according to a preset control algorithm; the central processing unit can automatically adjust the current density to extend the catalyst life based on catalyst activity data, and start pulse electrolysis or chemical cleaning program when a decrease in activity is detected. The actuator adjusts operating parameters according to instructions from the central processing unit, including valves that regulate electrolyte flow, power regulators that regulate current, and heaters or coolers that control the temperature of the electrolytic cell. This actuator can improve ion conduction efficiency by adjusting the electrolyte flow or temperature to change the hydrophilicity of the membrane surface. The data storage module uses a blockchain distributed ledger to store historical sensor data and central processor calculation results, ensuring that the data is tamper-proof, and is connected to the power grid blockchain platform to realize automated settlement of green hydrogen production data and carbon credit trading. The remote monitoring module transmits operational data to the remote monitoring center via the network, enabling remote monitoring and management. The alarm module issues an alarm signal when the operating parameters exceed the safe range.

[0009] The electrolytic cell assembly adopts a multi-electrode structure with multiple electrolysis chambers connected in series. It uses non-precious metal catalysts and embedded iridium oxide catalysts, with titanium alloy electrodes and carbon fiber reinforced plastic injection molding for the flow field plate. It is equipped with a thin composite diaphragm with a nano-zirconia coating on its surface. The assembly uses an IP68-rated protective shell and double O-rings, and adds 20% ethylene glycol to the electrolyte, enabling it to operate under extreme conditions of high humidity, high dust, and low temperature.

[0010] Optionally, the electrolytic cell assembly has a multi-pole structure with multiple electrolysis chambers connected in series; the intelligent control system can independently monitor and control the operating parameters of each electrolysis chamber, thereby achieving refined management of the electrolytic cell assembly, improving electrolysis efficiency and reducing energy consumption.

[0011] Optionally, the intelligent control system is connected to a data storage module to store historical data collected by sensors and calculation results of the central processing unit, so as to monitor and analyze the operating status over a long period of time and provide data support for optimizing the operating parameters and control strategies of the electrolytic cell.

[0012] Optionally, the intelligent control system is also connected to a remote monitoring module, which can transmit the operating data of the electrolyzer components to the remote monitoring center in real time via the network, realize remote monitoring and management of the hydrogen production unit, facilitate timely detection and handling of equipment failures, and improve the reliability and operational stability of the equipment.

[0013] Optionally, the intelligent control system is also connected to an alarm module. When the monitored operating parameters exceed the preset safety range, the alarm module can promptly issue an alarm signal to remind the operator to take appropriate measures to ensure the safe operation of the hydrogen production unit.

[0014] A control method for a low-energy alkaline water electrolysis hydrogen production device, employing the aforementioned low-energy alkaline water electrolysis hydrogen production device, includes the following steps: Add electrolyte to the electrolytic cell assembly and turn on the power to start the water electrolysis reaction in the electrolytic cell assembly; The intelligent control system uses sensors to monitor parameters such as temperature, pressure, current, voltage, electrolyte concentration, and liquid level in the electrolyzer in real time. The catalyst activity dynamic monitoring module evaluates the catalyst performance in real time and transmits the data to the central processing unit. The central processing unit analyzes whether the operating status is optimal according to the received parameter data and preset control algorithm. At the same time, it automatically adjusts the current density according to the catalyst performance data and starts the regeneration program when the catalyst activity decreases. If the operating state deviates from the optimal state, the central processing unit sends instructions to the actuator to adjust parameters such as electrolyte flow rate, current magnitude, and electrolytic cell temperature in real time to restore the electrolytic cell to the optimal operating state; at the same time, the hydrophilicity of the diaphragm is changed by adjusting the electrolyte flow rate or temperature. The generated hydrogen and oxygen are collected through hydrogen collection systems and oxygen collection systems, respectively; the hydrogen collection system monitors for leaks in real time, and handles any abnormalities according to preset procedures. During the electrolysis process, the intelligent control system uses LSTM neural network based on real-time parameter data to predict the performance change trend of the electrolyzer and adjust the operating parameters in advance to extend its service life. The intelligent control system automatically adjusts its operating mode based on the renewable energy generation and grid load conditions in different regions, using a power fluctuation smoothing algorithm and a wide power range operation strategy to achieve effective coupling with renewable energy. The intelligent control system uses the blockchain distributed ledger of the data storage module to store data, so as to realize the immutability of data and the automated settlement of carbon credit transactions with the power grid blockchain platform; The intelligent control system maps the physical equipment status in real time through a digital twin platform, predicts potential faults and generates maintenance suggestions, and at the same time uses reinforcement learning strategies to automatically optimize operating parameters to improve overall energy efficiency.

[0015] Optionally, during the electrolysis process, the intelligent control system can also predict the performance change trend of the electrolyzer components based on the real-time monitored parameter data, and adjust the operating parameters in advance to extend the service life of the electrolyzer components and further reduce the cost of hydrogen production.

[0016] Optionally, the intelligent control system can automatically adjust the operating mode of the electrolyzer components according to the renewable energy power generation and grid load conditions in different regions, so as to achieve effective coupling with renewable energy, make full use of renewable energy for hydrogen production, reduce dependence on traditional energy, and improve the economic efficiency and environmental friendliness of hydrogen production.

[0017] The beneficial effects of this invention are as follows: This invention significantly reduces hydrogen production energy consumption and improves energy conversion efficiency through multi-dimensional collaborative optimization of the electrolysis process via an intelligent control system; the dynamic monitoring and regeneration mechanism of catalytic activity effectively extends the lifespan of core materials; multi-level safety protection and extreme condition adaptability design greatly improve system reliability; renewable energy coupling capability and blockchain data storage technology enhance the environmental friendliness and credibility of the hydrogen production process; the application of digital twins and artificial intelligence algorithms enables predictive maintenance and global energy efficiency self-optimization, providing efficient, stable, and intelligent technical support for large-scale green hydrogen production. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the hydrogen production apparatus of the present invention; Among them, 1-hydrogen collection system, 2-transport pipeline, 3-intelligent control system, 4-actuator (electrolyte flow rate, power regulator, heating / cooling plate), 5-oxygen collection system, 6-controller, 7-sensor (temperature sensor, pressure sensor, electrolyte concentration sensor), 8-catalytic combustion sensor.

[0019] Figure 2 This is a diagram of the intelligent control system architecture. Figure 3 This is a flowchart of a hydrogen production process. Detailed Implementation

[0020] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0021] According to one embodiment of the present invention, the overall structure of the device is shown in Figure 1. The core consists of a hydrogen collection system 1, an oxygen collection system 5, an electrolyzer assembly, and an intelligent control system. The hydrogen collection system 1 is connected to the cathode chamber and is equipped with a catalytic combustion sensor 8, which can perform multi-dimensional detection and graded early warning of hydrogen leakage. When the hydrogen concentration exceeds a threshold, the intelligent control system 3 automatically shuts off the inlet valve and power supply of the corresponding electrolyzer and initiates inert gas purging. The oxygen collection system 5 is connected to the anode chamber and is used to collect the oxygen produced by electrolysis.

[0022] The electrolyzer assembly adopts a multi-electrode structure, with multiple electrolysis chambers connected in series. The electrodes are made of titanium alloy, and the flow field plate is injection molded from carbon fiber reinforced plastic. It is equipped with a thin composite diaphragm with a nano-zirconia coating to improve ion conduction efficiency. The assembly features an IP68-rated protective shell and double O-rings. The electrolyte contains 20% ethylene glycol, enabling stable operation under extreme conditions such as high humidity, high dust, and low temperature. The combination of a non-precious metal catalyst and an embedded iridium oxide catalyst within the electrolyzer assembly reduces costs while maintaining catalytic activity.

[0023] The intelligent control system 3 is the core of the device of this invention, and its architecture is shown in Figure 2. As shown, the system includes multiple functional modules. Multiple sensors 7 are installed at different locations in the electrolyzer assembly to monitor parameters such as temperature, pressure, current, voltage, electrolyte concentration, and liquid level in real time. The catalyst activity dynamic monitoring module evaluates catalyst performance changes in real time through in-situ Raman spectroscopy or electrochemical impedance spectroscopy. The central processing unit is connected to each sensor, receives parameter data, and analyzes the operating status according to a preset control algorithm. It can automatically adjust the current density based on catalyst activity data to extend catalyst life and initiate pulse electrolysis or chemical cleaning programs when a decrease in activity is detected. The actuator 4 includes valves for adjusting electrolyte flow, a power regulator for adjusting current, and a heater or cooler for controlling electrolyzer temperature. It can change the hydrophilicity of the diaphragm surface by adjusting the electrolyte flow or temperature, thereby improving ion conduction efficiency. The data storage module uses a blockchain distributed ledger to store historical sensor data and central processing unit calculation results to ensure data immutability. It is also connected to the power grid blockchain platform to achieve automated settlement of green hydrogen production data and carbon credit trading. The remote monitoring module transmits operating data to a remote monitoring center via the network for remote management. The alarm module issues an alarm signal when operating parameters exceed safe ranges.

[0024] The hydrogen production method of this invention, as shown in Figure 3, first involves adding an electrolyte (a mixture of alkali and antifreeze) to the electrolyzer assembly, and then starting the power supply to initiate the water electrolysis reaction. Sensors 7 in the intelligent control system 3 monitor parameters such as temperature, pressure, current, voltage, electrolyte concentration, and level within the electrolyzer in real time. The catalyst activity dynamic monitoring module evaluates catalyst performance in real time and transmits the data to the central processing unit. The central processing unit analyzes the operating status according to the parameter data and a preset control algorithm, automatically adjusts the current density based on the catalyst performance data, and initiates a regeneration program when activity decreases.

[0025] If the operating state deviates from the optimal state, the central processing unit sends instructions to the actuator to adjust parameters such as electrolyte flow rate, current magnitude, and electrolytic cell temperature in real time to restore the electrolytic cell to its optimal state. Simultaneously, the hydrophilicity of the diaphragm is altered by adjusting the electrolyte flow rate or temperature. The generated hydrogen and oxygen are collected through separate hydrogen and oxygen collection systems. The hydrogen collection system monitors for leaks in real time and handles any abnormalities according to a preset procedure.

[0026] During electrolysis, the intelligent control system 3 uses LSTM neural networks to predict the performance trends of the electrolyzer based on real-time parameter data, adjusting operating parameters in advance to extend its service life. Simultaneously, based on the renewable energy generation situation and grid load conditions in different regions, it employs power fluctuation smoothing algorithms and a wide power range operation strategy to automatically adjust the operating mode, achieving effective coupling with renewable energy. The data storage module utilizes a blockchain distributed ledger to store data, ensuring data immutability and automated settlement of carbon credit transactions with the grid blockchain platform. The intelligent control system maps the physical equipment status in real time through a digital twin platform, predicts potential faults and generates maintenance suggestions, and automatically optimizes operating parameters using reinforcement learning strategies to improve overall energy efficiency.

[0027] Taking a sudden drop in wind power as an example, the current sensor reports fluctuations in the electrolysis current. The central processing unit (CPU) predicts the trend of catalyst activity changes using an LSTM neural network, automatically instructs the power regulator to reduce the current density, and adjusts the electrolyte flow rate to improve ion conduction efficiency. Simultaneously, the heating / cooling plates maintain a stable tank temperature, ensuring the electrolysis voltage remains within the optimized range. In low-temperature environments, if the temperature sensor 7 detects a deviation from the target temperature, the CPU activates a redundant heating mode, adjusts the electrolyte flow rate to reduce heat dissipation, ensures the hydrophilicity of the diaphragm and ion conduction efficiency, and prevents electrolyte solidification.

[0028] Taking the operation of the device in a low-temperature environment as an example, when the device is in a low-temperature environment, the temperature sensor detects that the tank temperature deviates from the target value. The central processing unit immediately activates the redundant heating mode and adjusts the electrolyte flow rate to reduce heat dissipation. At this time, the 20% concentration of ethylene glycol added to the electrolyte plays an antifreeze role, preventing the electrolyte from solidifying. Simultaneously, the actuator adjusts the electrolyte temperature to change the hydrophilicity of the diaphragm surface, ensuring that the ion conduction efficiency is not affected by the low temperature. Throughout the process, the intelligent control system monitors various parameters in real time and maintains the electrolyzer in optimal operation through dynamic adjustments, ensuring that the device can still stably produce hydrogen under extreme low-temperature conditions without the risk of electrolyte solidification.

[0029] This device significantly reduces hydrogen production energy consumption, improves electrolysis efficiency and safety, and supports renewable energy coupling and reliable data management through multi-dimensional collaborative optimization of the electrolysis process via an intelligent control system. It combines high-efficiency materials and advanced control strategies, providing technical support for large-scale green hydrogen production.

Claims

1. A low-energy alkaline water electrolysis hydrogen production device, comprising: Hydrogen collection system, oxygen collection system, electrolyzer components and intelligent control system; The hydrogen collection system is connected to the cathode chamber and is equipped with a catalytic combustion sensor to achieve multi-dimensional detection and graded early warning of hydrogen leakage. When the hydrogen concentration exceeds the set threshold, the intelligent control system automatically shuts off the inlet valve and power supply of the corresponding electrolyzer and starts inert gas purging. The oxygen collection system is connected to the anode chamber and is equipped with a catalytic combustion sensor to collect the generated oxygen; The intelligent control system is connected to the electrolytic cell assembly and is used to monitor and control the operating parameters in real time.

2. The hydrogen production apparatus according to claim 1, characterized in that, The intelligent control system includes: Multiple sensors are installed at different locations on the electrolyzer assembly to monitor temperature, pressure, current, voltage, electrolyte concentration, and liquid level parameters in real time. The catalyst activity dynamic monitoring module evaluates catalyst performance in real time through in-situ Raman spectroscopy or electrochemical impedance spectroscopy. The central processing unit is connected to various sensors, receives parameter data and analyzes the operating status according to a preset control algorithm; the central processing unit automatically adjusts the current density to extend the catalyst life based on catalyst activity data, and starts a pulse electrolysis or chemical cleaning program when a decrease in activity is detected. The actuator adjusts operating parameters according to instructions from the central processing unit, including valves that regulate electrolyte flow, power regulators that regulate current, and heaters or coolers that control the temperature of the electrolytic cell. The actuator improves ion conduction efficiency by adjusting the electrolyte flow or temperature to change the hydrophilicity of the membrane surface. The data storage module uses a blockchain distributed ledger to store historical sensor data and central processor calculation results, ensuring that the data is tamper-proof, and is connected to the power grid blockchain platform to realize automated settlement of green hydrogen production data and carbon credit trading. The remote monitoring module transmits operational data to the remote monitoring center via the network, enabling remote monitoring and management. The alarm module issues an alarm signal when the operating parameters exceed the safe range.

3. The hydrogen production apparatus according to claim 1, characterized in that, The electrolytic cell assembly adopts a multi-pole structure with multiple electrolytic cells connected in series. The intelligent control system can independently monitor and control the operating parameters of each electrolytic cell.

4. The hydrogen production apparatus according to claim 2, characterized in that, The electrolytic cell assembly uses non-precious metal catalysts and embedded iridium oxide catalysts, the electrode material is titanium alloy, and the flow field plate is made of carbon fiber reinforced plastic injection molding; it is equipped with a thin composite diaphragm with a nano-zirconia coating on the surface; it adopts an IP68-level protective shell and double O-rings, and 20% ethylene glycol is added to the electrolyte.

5. The hydrogen production apparatus according to claim 1, characterized in that, The intelligent control system is connected to a data storage module, which stores historical data collected by sensors and calculation results of the central processing unit, monitors and analyzes the operating status, and provides data support for optimizing the operating parameters and control strategies of the electrolytic cell.

6. The hydrogen production apparatus according to claim 1, characterized in that, The intelligent control system is also connected to a remote monitoring module, which transmits the operating data of the electrolyzer components to the remote monitoring center in real time via the network, enabling remote monitoring and management of the hydrogen production unit, facilitating timely detection and handling of equipment failures, and improving the reliability and operational stability of the equipment.

7. The hydrogen production apparatus according to claim 1, characterized in that, The intelligent control system is also connected to an alarm module. When the monitored operating parameters exceed the preset safety range, the alarm module can promptly issue an alarm signal to remind the operator to take appropriate measures to ensure the safe operation of the hydrogen production unit.

8. The control method for the hydrogen production apparatus according to claim 1, characterized in that, The low-energy alkaline water electrolysis hydrogen production device described above includes the following steps: (1) Add electrolyte to the electrolytic cell assembly and start the power supply to start the electrolysis of water reaction in the electrolytic cell assembly; (2) The temperature, pressure, current, voltage, electrolyte concentration and liquid level parameters in the electrolytic cell are monitored in real time by the sensors in the intelligent control system, the catalyst performance is evaluated in real time by the catalyst activity dynamic monitoring module, and the data is transmitted to the central processing unit. (3) The central processing unit analyzes whether the operating state is optimal according to the received parameter data and the preset control algorithm. At the same time, it automatically adjusts the current density according to the catalyst performance data and starts the regeneration program when the catalyst activity decreases. (4) If the operating state deviates from the optimal state, the central processing unit sends instructions to the actuator to adjust the electrolyte flow rate, current magnitude and electrolytic cell temperature parameters in real time to restore the electrolytic cell to the optimal operating state; at the same time, the hydrophilicity of the diaphragm is changed by adjusting the electrolyte flow rate or temperature. (5) The generated hydrogen and oxygen are collected through a hydrogen collection system and an oxygen collection system, respectively; the hydrogen collection system monitors for leaks in real time, and if any abnormality is found, it is handled according to the preset procedure. (6) During the electrolysis process, the intelligent control system uses LSTM neural network based on real-time parameter data to predict the performance change trend of the electrolyzer and adjusts the operating parameters in advance to extend the service life. (7) The intelligent control system adopts a power fluctuation smoothing algorithm and a wide power range operation strategy to automatically adjust the operation mode according to the renewable energy power generation and grid load conditions in different regions, so as to achieve effective coupling with renewable energy. (8) The intelligent control system uses the blockchain distributed ledger of the data storage module to store data, so as to realize the immutability of data and the automated settlement of carbon credit transactions with the power grid blockchain platform; (9) The intelligent control system maps the physical equipment status in real time through the digital twin platform, predicts potential faults and generates maintenance suggestions, and at the same time uses reinforcement learning strategy to automatically optimize operating parameters to improve overall energy efficiency.

9. The control method according to claim 7, characterized in that, During the electrolysis process, the intelligent control system predicts the performance change trend of the electrolytic cell components based on the real-time monitored parameter data and adjusts the operating parameters in advance.

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