Control method and device of hydrogen production system, hydrogen production system and computer storage medium

Abstract

The invention provides a control method and device of a hydrogen production system, the hydrogen production system and a computer storage medium, and the control method of the hydrogen production system comprises the steps: determining a to-be-optimized control parameter set based on current dynamic response characteristic data of an electrolytic bath, and then optimizing parameters of all control parameter types in the to-be-optimized control parameter set, finally, the control parameters of the electrolytic cell and the heating power of the integrated heater are adjusted at the same time based on the optimal control parameter combination, accurate control over the temperature of the electrolytic cell is achieved, the electrolytic cell can be kept at the optimal operation temperature, and then the hydrogen production efficiency is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of hydrogen production technology, and in particular to a control method, apparatus, hydrogen production system, and computer storage medium for a hydrogen production system. Background Technology

[0002] Currently, alkaline water electrolysis (AWE) is considered the optimal solution for large-scale hydrogen production due to its mature technology and low cost.

[0003] However, under fluctuating operating conditions, the electrolyzer struggles to maintain its optimal operating temperature, leading to reduced hydrogen production efficiency.

[0004] Therefore, there is an urgent need for a method to precisely control the temperature of the electrolyzer so that it can be maintained at the optimal operating temperature, thereby effectively improving hydrogen production efficiency. Summary of the Invention

[0005] In view of this, the present invention provides a control method, apparatus, hydrogen production system, and computer storage medium for a hydrogen production system, so as to effectively improve hydrogen production efficiency.

[0006] The first aspect of this invention provides a control method for a hydrogen production system, comprising:

[0007] Real-time acquisition of the current dynamic response characteristics data of the electrolyzer;

[0008] Based on the current dynamic response characteristic data of the electrolyzer, determine the set of control parameters to be optimized;

[0009] Optimize all parameters of all control parameter types in the set of control parameters to be optimized to obtain the optimal combination of control parameters;

[0010] The control parameters of the electrolytic cell and the heating power of the integrated heater are adjusted based on the optimal combination of control parameters.

[0011] Optionally, real-time acquisition of the current dynamic response characteristic data of the electrolyzer, including:

[0012] Real-time acquisition of voltage and current data from the electrolytic cell;

[0013] The current density is determined based on the current data and the total area of ​​all electrodes in the electrolytic cell.

[0014] Based on the voltage and current density of the electrolyzer, the current dynamic response characteristics data of the electrolyzer are generated.

[0015] Optionally, parameters of all control parameter types in the set of control parameters to be optimized are optimized to obtain the optimal combination of control parameters, including:

[0016] An initial population is generated based on the parameter range of all control parameter types in the set of control parameters to be optimized; the initial population consists of multiple individuals; each individual includes parameters of all control parameter types.

[0017] The fitness value of each individual is determined based on the fitness function;

[0018] Genetic iteration is performed based on the fitness values ​​of all individuals to determine the optimal individual, and the parameters of all control parameter types included in the optimal individual are taken as the optimal combination of control parameters.

[0019] Optionally, the control method for the above-mentioned hydrogen production system further includes:

[0020] Real-time monitoring of the temperature of each fuel cell stack in the electrolytic cell;

[0021] When the temperature difference between any fuel cell stack and the average temperature of the fuel cell stack is greater than the temperature difference threshold, the power regulation amount of the fuel cell stack is determined based on the proportional coefficient, integral coefficient, the temperature of the fuel cell stack, and the average temperature of the fuel cell stack.

[0022] The alkaline solution flow rate and current density in the branch where the fuel cell stack is located are adjusted based on the power regulation of the fuel cell stack.

[0023] Optionally, the control method for the above-mentioned hydrogen production system further includes:

[0024] Real-time monitoring of voltage and current data of the photovoltaic array;

[0025] Based on the voltage and current data of the monitored photovoltaic array, the real-time equivalent impedance is determined;

[0026] The self-impedance of the electrolytic cell is adjusted to the real-time equivalent impedance.

[0027] Optionally, the control method for the above-mentioned hydrogen production system further includes:

[0028] Real-time monitoring of the photovoltaic array's output power;

[0029] The target step size is determined based on the rate of change of the output power of the photovoltaic array.

[0030] The power of the electrolytic cell is adjusted in real time based on the target step size and the rated power of the electrolytic cell.

[0031] Optionally, the target step size is determined based on the rate of change of the photovoltaic array's output power, including:

[0032] The first step length is determined based on the rate of change of the output power of the photovoltaic array;

[0033] Determine whether the difference between the first step length and the previous step length is less than the step length difference threshold;

[0034] If it is determined that the difference between the first step length and the previous step length is less than the step length difference threshold, then the first step length is taken as the target step length.

[0035] If it is determined that the difference between the first step length and the previous step length is not less than the step length difference threshold, then the sum of the previous step length and the step length difference is taken as the target step length.

[0036] A second aspect of the present invention provides a control device for a hydrogen production system, comprising:

[0037] The acquisition unit is used to acquire the current dynamic response characteristic data of the electrolyzer in real time;

[0038] The determination unit is used to determine the set of control parameters to be optimized based on the current dynamic response characteristic data of the electrolyzer;

[0039] The optimization unit is used to optimize parameters of all control parameter types in the set of control parameters to be optimized, so as to obtain the optimal combination of control parameters.

[0040] The adjustment unit is used to adjust the control parameters of the electrolytic cell and the heating power of the integrated heater based on the optimal combination of control parameters.

[0041] Optionally, the above-mentioned acquisition unit includes:

[0042] The acquisition unit is used to acquire voltage and current data of the electrolytic cell in real time.

[0043] The current density determination unit is used to determine the current density based on current data and the total area of ​​all electrodes in the electrolytic cell;

[0044] The voltage change data generation unit is used to generate current dynamic response characteristic data of the electrolyzer based on the voltage data and current density of the electrolyzer.

[0045] Optionally, the above-mentioned optimization unit includes:

[0046] The initial population generation unit is used to generate an initial population based on the parameter range of all control parameter types in the set of control parameters to be optimized; wherein, the initial population includes multiple individuals; each individual includes parameters of all control parameter types;

[0047] The fitness value determination unit is used to determine the fitness value of each individual based on the fitness function.

[0048] The iterative unit is used to perform genetic iteration based on the fitness values ​​of all individuals to determine the optimal individual, and to take all the parameters of the control parameter types included in the optimal individual as the optimal combination of control parameters.

[0049] Optionally, the control device for the aforementioned hydrogen production system further includes:

[0050] The fuel cell stack temperature monitoring unit is used to monitor the temperature of each fuel cell stack in the electrolytic cell in real time.

[0051] The adjustment amount determination unit is used to determine the power adjustment amount of the electric stack based on the proportional coefficient, integral coefficient, temperature of the electric stack, and average temperature of the electric stack when the difference between the temperature of any electric stack and the average temperature of the electric stack is greater than the temperature difference threshold.

[0052] The regulating unit is used to regulate the alkaline flow rate and current density of the branch where the fuel cell stack is located based on the power regulation amount of the fuel cell stack.

[0053] Optionally, the control device for the aforementioned hydrogen production system further includes:

[0054] A photovoltaic array detection unit is used to monitor the voltage and current data of the photovoltaic array in real time.

[0055] The real-time equivalent impedance determination unit is used to determine the real-time equivalent impedance based on the voltage and current data of the monitored photovoltaic array.

[0056] The impedance adjustment unit is used to adjust the self-impedance of the electrolytic cell to the real-time equivalent impedance.

[0057] Optionally, the control device for the aforementioned hydrogen production system further includes:

[0058] Output power monitoring unit, used to monitor the output power of photovoltaic array in real time;

[0059] The target step size determination unit is used to determine the target step size based on the rate of change of the output power of the photovoltaic array.

[0060] The power adjustment unit is used to adjust the power of the electrolyzer in real time based on the target step size and the rated power of the electrolyzer.

[0061] Optionally, the target step size determination unit mentioned above includes:

[0062] The first step length determination unit is used to determine the first step length based on the rate of change of the output power of the photovoltaic array.

[0063] The judgment unit is used to determine whether the difference between the first step length and the previous step length is less than the step length difference threshold.

[0064] The first target step size determination subunit is used to determine the first step size as the target step size if the judgment unit determines that the difference between the first step size and the previous step size is less than the step size difference threshold.

[0065] The second target step size determination subunit is used to determine the target step size if the judgment unit determines that the difference between the first step size and the previous step size is not less than the step size difference threshold.

[0066] A third aspect of the present invention provides a hydrogen production system, comprising:

[0067] Electrolyzer module, thermal management module, and control device for the hydrogen production system as described in the second aspect;

[0068] The electrolyzer module is connected to the thermal management module; the control device of the hydrogen production system is connected to both the electrolyzer module and the thermal management module.

[0069] A fourth aspect of the present invention provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements a control method for a hydrogen production system as described in any of the first aspects.

[0070] As can be seen from the above scheme, the present invention provides a control method, device, system, and computer storage medium for a hydrogen production system. The control method determines the set of control parameters to be optimized based on the current dynamic response characteristic data of the electrolyzer. Then, it optimizes the parameters of all control parameter types in the set to be optimized to obtain the optimal combination of control parameters. Finally, based on the optimal combination of control parameters, it simultaneously adjusts the control parameters of the electrolyzer and the heating power of the integrated heater to achieve precise control of the electrolyzer temperature, so that the electrolyzer can be maintained at the optimal operating temperature, thereby effectively improving the hydrogen production efficiency. Attached Figure Description

[0071] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0072] Figure 1 A flowchart of a control method for a hydrogen production system provided in an embodiment of the present invention;

[0073] Figures 2 to 6 A flowchart of a control method for a hydrogen production system provided in another embodiment of the present invention;

[0074] Figure 7 A schematic diagram of a control device for a hydrogen production system provided in another embodiment of the present invention;

[0075] Figure 8 This is a schematic diagram of a hydrogen production system provided for another embodiment of the present invention. Detailed Implementation

[0076] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0077] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0078] It should be noted that the information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this invention are all information and data authorized by the user or fully authorized by all parties.

[0079] It should be noted that the concepts of "first" and "second" mentioned in this invention are only used to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0080] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0081] This invention provides a control method for a hydrogen production system, such as... Figure 1 As shown, the specific steps include:

[0082] S101. Real-time acquisition of the current dynamic response characteristic data of the electrolytic cell.

[0083] It should be noted that the voltage change data corresponding to the change in current density of the electrolytic cell is the dynamic response characteristic data of the electrolytic cell.

[0084] Optionally, in another embodiment of the present invention, one implementation of step S101 is as follows: Figure 2 As shown, it includes:

[0085] S201. Real-time acquisition of voltage and current data from the electrolytic cell.

[0086] In the practical application of this invention, the voltage and current data of the electrolytic cell can be fed back in real time through efficient and secure transmission of industrial Ethernet via a rectifier cabinet, but this is not limited to that.

[0087] Specifically, a current-voltage feedback control system can be set up to acquire voltage and current data from the electrolyzer. This system must include at least: a current source, a voltage sensor, and a data acquisition module.

[0088] The current source is used to stably output the set current value and quickly respond to changes in the current command during dynamic processes; the voltage sensor is used to monitor the voltage changes at both ends of the electrolytic cell in real time, and transmits the collected voltage signal to the data acquisition module, which then transmits the data to the rectifier cabinet.

[0089] S202. Determine the current density based on the current data and the total area of ​​all electrodes in the electrolytic cell.

[0090] Specifically, the current density J can be calculated using the following formula:

[0091] J = I / A; where I is the current data (total current of the electrolytic cell), and A is the total area of ​​all electrodes in the electrolytic cell.

[0092] S203. Based on the voltage data and current density of the electrolyzer, generate the current dynamic response characteristic data of the electrolyzer.

[0093] Specifically, after aligning the current density and voltage data over time, the current dynamic response characteristics data of the electrolyzer are generated based on the voltage and current density data of the electrolyzer.

[0094] For example, a line graph can be drawn with current density on the horizontal axis and voltage on the vertical axis to represent the current dynamic response characteristics of the electrolytic cell.

[0095] In the practical application of this invention, the dynamic response characteristics of the electrolytic cell under different current density changes can be quickly obtained by applying a step current signal, that is, quickly switching from the current value to the target current value, while recording the voltage change data of the electrolytic cell over time.

[0096] The current dynamic performance of an electrolyzer can be evaluated by using parameters such as rise time, overshoot, settling time, and steady-state error from its current dynamic response characteristic data.

[0097] For example, rise time reflects the electrolyzer's ability to respond quickly to current changes, while overshoot reflects the system's stability during dynamic processes. A shorter settling time indicates a faster recovery to steady state, and a smaller steady-state error indicates higher system control precision. In the current-voltage feedback process, the electrochemical reaction kinetics within the electrolyzer must be considered. At low current densities (e.g., 0.1 A / cm²), the polarization of the electrolyzer is relatively weak, and the voltage response may be relatively smooth. As the current density increases to 0.4 A / cm², the electrochemical reaction rate accelerates, and concentration polarization and activation polarization effects become more significant. The current dynamic response characteristics of the electrolyzer (e.g., voltage response curve) may exhibit more pronounced nonlinear features.

[0098] S102. Based on the current dynamic response characteristic data of the electrolyzer, determine the set of control parameters to be optimized.

[0099] Continuing with the above examples, the present invention can analyze the differences in dynamic behavior of the electrolyzer under different current density changes by comparing the dynamic response characteristic data of the electrolyzer under different current density changes in advance, and set the corresponding set of control parameters that need to be optimized for different dynamic behavior differences.

[0100] In the practical application of this invention, after obtaining the current dynamic response characteristic data of the electrolytic cell, the set of control parameters to be optimized can be quickly determined by searching and matching.

[0101] The set of control parameters to be optimized includes the proportional and integral coefficients of the electrolytic cell's equalization controller, the weighting of the power distribution between the electrolytic cell and the integrated heater, etc., which are not limited here.

[0102] S103. Optimize the parameters of all control parameter types in the set of control parameters to be optimized to obtain the optimal combination of control parameters.

[0103] It should be noted that the optimization method can be, but is not limited to, using the Model Predictive Control (MPC) algorithm to adjust the parameter set in real time through rolling optimization to achieve optimal control; no limitation is made here.

[0104] Specifically, a dynamic model of the electrolyzer (such as an impulse response model or a state-space model) is established using experimental data. The MPC algorithm is then used to adjust the parameter set in real time through rolling optimization to achieve optimal control. Finally, through experimental verification and simulation optimization, the parameters are adjusted until optimal performance is achieved (such as minimizing energy consumption and maximizing gas production efficiency).

[0105] Optionally, in another embodiment of the present invention, one implementation of step S103 is as follows: Figure 3 As shown, it includes:

[0106] S301. Generate an initial population based on the parameter range of all control parameter types in the set of control parameters to be optimized.

[0107] The initial population consists of multiple individuals; each individual includes parameters of all control parameter types.

[0108] Taking the set of control parameters to be optimized, which includes proportional coefficient, integral coefficient, power allocation weight of electrolytic cell, and power allocation weight of integrated heater, as an example, assuming that the parameter range of proportional coefficient is 0 to 10, the parameter range of integral coefficient is 0 to 5, the power allocation weight of electrolytic cell is 0 to 40%, and the power allocation weight of integrated heater is 0 to 30%.

[0109] First, the parameters of each type mentioned above need to be encoded, including but not limited to converting the parameters into binary or real number encoding. For example, binary encoding requires determining the number of bits, while real number encoding directly uses floating-point numbers, which is not limited here.

[0110] Then, within the parameter range of the above parameters, an initial population is randomly generated. It is assumed that the initial population includes 10 individuals, and each individual includes a proportional coefficient, an integral coefficient, a power allocation weight for the electrolytic cell, and a power allocation weight for the integrated heater, corresponding to the encoding.

[0111] S302. Determine the fitness value of each individual based on the fitness function.

[0112] The fitness function can be pre-designed based on indicators such as overshoot, rise time, settling time, and steady-state error, but this is not limited here.

[0113] Specifically, the individual's parameters are passed as input to the fitness function. By evaluating the impact of the individual's parameters on the fitness function, the fitness value is output (the better the value, the higher the fitness, and the more suitable it is as a candidate for the next generation of optimization).

[0114] In the practical application of this invention, the fitness value of each individual can also be associated with parameters to form a fitness table, and individuals can be sorted according to their fitness values, with priority given to individuals with high fitness for the next generation of optimization. This is not limited here.

[0115] S303. Perform genetic iteration based on the fitness values ​​of all individuals to determine the optimal individual, and use the parameters of all control parameter types included in the optimal individual as the optimal control parameter combination.

[0116] The methods of genetic iteration include, but are not limited to, roulette wheel selection, tournament selection, simulated binary crossover, Gaussian mutation, and race update, etc., which are not limited here.

[0117] In the practical application of this invention, multi-objective optimization can also be transformed into single-objective optimization by weighted summation, which is not limited here.

[0118] S104. Adjust the control parameters of the electrolytic cell and the heating power of the integrated heater based on the optimal combination of control parameters.

[0119] The control parameters of the electrolyzer include at least the power distribution of each stack in the electrolyzer, the alkali flow rate, and the power of the electrolyzer, etc., which are not limited here.

[0120] Continuing with the above example, the power distribution and alkali flow rate of each stack in the electrolytic cell are adjusted by the proportional coefficient and integral coefficient in the optimal control parameter combination, and the power is distributed to the electrolytic cell and the integrated heater according to the power distribution weight of the electrolytic cell and the power distribution weight of the integrated heater in the optimal control parameter combination.

[0121] Specifically, power distribution is achieved by adjusting the voltage output of each stack in the electrolytic cell through a proportional coefficient; and the dynamic adjustment of the alkali flow rate is indirectly affected by eliminating steady-state errors through an integral coefficient.

[0122] Optionally, in another embodiment of the present invention, one implementation of the control method for the hydrogen production system is as follows: Figure 4 As shown, it also includes:

[0123] S401. Real-time monitoring of the temperature of each stack in the electrolytic cell.

[0124] In the practical application of this invention, temperature sensors can be installed on each stack to monitor the temperature of each stack in the electrolytic cell in real time, but this is not limited to that.

[0125] Of course, in the actual application of this invention, a dual-channel redundancy design can also be used to ensure the reliability of the temperature signal, but this is not limited to that.

[0126] S402. When the temperature difference between any fuel cell stack and the average temperature of the fuel cell stack is greater than the temperature difference threshold, the power regulation amount of the fuel cell stack is determined based on the proportional coefficient, integral coefficient, the temperature of the fuel cell stack, and the average temperature of the fuel cell stack.

[0127] Specifically, the adjustment amount of the fuel cell stack can be calculated using the following formula:

[0128] ΔP_i=K_p×(T_avg-T_i)+K_i×∫(T_avg-T_i)dt;

[0129] Where ΔP_i is the power regulation of the i-th stack, T_avg is the average module temperature, T_i is the temperature of the i-th stack, and K_p and K_i are the proportional and integral coefficients.

[0130] S403. Adjust the alkaline solution flow rate and current density of the branch where the fuel cell stack is located based on the power regulation of the fuel cell stack.

[0131] Specifically, the alkaline solution flow rate is increased in the branch containing the low-temperature fuel cell stack to improve ion transport efficiency and increase current density, thereby increasing power output; while the alkaline solution flow rate is reduced in the branch containing the high-temperature fuel cell stack to improve ion transport efficiency and reduce current density, thereby reducing power output.

[0132] Optionally, in another embodiment of the present invention, one implementation of the control method for the hydrogen production system is as follows: Figure 5 As shown, it also includes:

[0133] S501: Real-time monitoring of voltage and current data of the photovoltaic array.

[0134] In the practical application of this invention, the voltage and current data of the photovoltaic array can be monitored in real time through the voltage and current sampling module of the photovoltaic array, but this is not limited to that.

[0135] S502. Based on the voltage and current data of the monitored photovoltaic array, determine the real-time equivalent impedance.

[0136] Understandably, as the output power of a photovoltaic system changes with illumination, its equivalent internal resistance (Req) also changes dynamically. When the photovoltaic power (calculated based on voltage and current data at the same moment) decreases, Req increases; when the power increases, Req decreases. By adjusting its own impedance (Rl) in real time to always equal Req, the electrolyzer can maximize power transmission.

[0137] S503. Adjust the self-impedance of the electrolytic cell to the real-time equivalent impedance.

[0138] In the practical application of this invention, the input impedance of the electrolytic cell can be adjusted by a DC-DC converter to keep Rl=Req, but this is not limited to that.

[0139] Optionally, in another embodiment of the present invention, one implementation of the control method for the hydrogen production system is as follows: Figure 6 As shown, it also includes:

[0140] S601, Real-time monitoring of the output power of the photovoltaic array.

[0141] In the practical application of this invention, the voltage and current data of the photovoltaic array can be monitored in real time through the voltage and current sampling module of the photovoltaic array, and the output power of the photovoltaic array can be determined based on the voltage and current data. No limitation is made here.

[0142] S602. Determine the target step size based on the rate of change of the output power of the photovoltaic array.

[0143] It should be noted that in the prior art, the maximum power point (MPP) of a photovoltaic array is usually searched by a fixed step size, while the target step size in this invention is a dynamic step size, which is determined according to the rate of change of the output power of the photovoltaic array.

[0144] The rate of change of the output power of the photovoltaic array is the difference between the output power at the current moment and the output power at the previous moment.

[0145] If the rate of change is positive and large, it indicates that the system is currently in the power increase phase. In this case, the step size should be appropriately increased to accelerate the search speed towards the maximum power point (MPP) and avoid slow convergence due to an excessively small step size. Conversely, if the rate of change is negative and large in absolute value, it indicates that the system is currently in the power decrease phase. Similarly, the step size needs to be increased to quickly cross any potential local extrema and enter the power increase region as soon as possible. When the rate of change is close to zero or small, it indicates that the system may be approaching or near the MPP. In this case, the tracking step size should be reduced to improve tracking accuracy, reduce oscillations near the MPP, and ensure that the system operates stably at the maximum power point.

[0146] In addition, to prevent excessive fluctuations during step size adjustment, in another embodiment of the present invention, upper and lower limit thresholds for the step size are set to ensure that the step size varies within a reasonable range.

[0147] Specifically, the first step length is determined based on the rate of change of the output power of the photovoltaic array; then, it is determined whether the difference between the first step length and the previous step length is less than the step length difference threshold.

[0148] Specifically, if the difference between the first step length and the previous step length is less than the step length difference threshold, then the first step length is taken as the target step length; if the difference between the first step length and the previous step length is not less than the step length difference threshold, then the sum of the previous step length and the step length difference is taken as the target step length.

[0149] This invention utilizes a mechanism that dynamically adjusts the step size based on the rate of change of the photovoltaic array's output power. This allows for a balance between tracking speed and accuracy under varying illumination conditions and load changes, effectively improving the energy conversion efficiency of the photovoltaic system. It achieves a balance between rapid response and stability.

[0150] S603. Adjust the power of the electrolyzer in real time based on the target step size and the rated power of the electrolyzer.

[0151] Assuming the target step size is 0.1, the rated power of the electrolytic cell is 1200W, at time T1 the electrolytic cell power is 800W, and the output power of the photovoltaic array is 1400W. Then at time T2, the electrolytic cell power needs to be adjusted to 920W = 800W + 1200W * 0.1. At time T2, the output power of the photovoltaic array needs to be measured again, assuming it is still 1200W. Then at time T3, the electrolytic cell power needs to be adjusted to 1040W = 920W + 1200W * 0.1, and the output power of the photovoltaic array needs to be measured again. This process continues until the electrolytic cell power is adjusted to 1200W (reaching the rated power of the electrolytic cell), or if the output power of the photovoltaic array changes at any time, then after adjusting the target step size, the electrolytic cell power is adjusted in real time based on the target step size and the rated power of the electrolytic cell.

[0152] It should be noted that the closer the electrolyzer's own impedance is to the photovoltaic array's real-time equivalent impedance, the easier it is to find the photovoltaic array's maximum power point (MPP). This is because impedance matching reduces energy reflection, accelerates power transmission, and allows the system to reach the MPP more quickly. Therefore, in another embodiment of the present invention, after real-time monitoring of the photovoltaic array's voltage and current data, the electrolyzer's own impedance is first adjusted to the real-time equivalent impedance. Then, the target step size is determined based on the rate of change of the photovoltaic array's output power. Finally, based on the target step size and the electrolyzer's rated power, the electrolyzer's power is adjusted in real-time to further accelerate the search speed towards the maximum power point (MPP).

[0153] As can be seen from the above scheme, the present invention provides a control method for a hydrogen production system. By determining the set of control parameters to be optimized based on the current dynamic response characteristic data of the electrolyzer, the parameters of all control parameter types in the set of control parameters to be optimized are then optimized to obtain the optimal combination of control parameters. Finally, based on the optimal combination of control parameters, the control parameters of the electrolyzer and the heating power of the integrated heater are simultaneously adjusted to achieve precise control of the electrolyzer temperature, so that the electrolyzer can be maintained at the optimal operating temperature, thereby effectively improving the hydrogen production efficiency.

[0154] Another embodiment of the present invention provides a control device for a hydrogen production system, such as... Figure 7 As shown, it specifically includes:

[0155] The acquisition unit 710 is used to acquire the current dynamic response characteristic data of the electrolytic cell in real time.

[0156] Optionally, in another embodiment of the present invention, one implementation of the acquisition unit 710 includes:

[0157] The acquisition unit is used to acquire voltage and current data of the electrolytic cell in real time.

[0158] The current density determination unit is used to determine the current density based on current data and the total area of ​​all electrodes in the electrolytic cell.

[0159] The voltage change data generation unit is used to generate voltage change data of the electrolytic cell based on the voltage data and current density of the electrolytic cell.

[0160] The specific working process of the units disclosed in the above embodiments of the present invention can be found in the corresponding method embodiments, and will not be repeated here.

[0161] The determination unit 720 is used to determine the set of control parameters to be optimized based on the current dynamic response characteristic data of the electrolyzer.

[0162] The optimization unit 730 is used to optimize the parameters of all control parameter types in the set of control parameters to be optimized, so as to obtain the optimal combination of control parameters.

[0163] Optionally, in another embodiment of the present invention, one implementation of the optimization unit 730 includes:

[0164] The initial population generation unit is used to generate an initial population based on the parameter range of all control parameter types in the set of control parameters to be optimized.

[0165] The initial population consists of multiple individuals; each individual includes parameters of all control parameter types.

[0166] The fitness value determination unit is used to determine the fitness value of each individual based on the fitness function.

[0167] The iterative unit is used to perform genetic iteration based on the fitness values ​​of all individuals to determine the optimal individual, and to take all the parameters of the control parameter types included in the optimal individual as the optimal combination of control parameters.

[0168] The specific working process of the units disclosed in the above embodiments of the present invention can be found in the corresponding method embodiments, and will not be repeated here.

[0169] The adjustment unit 740 is used to adjust the control parameters of the electrolytic cell and the heating power of the integrated heater based on the optimal combination of control parameters.

[0170] For details on the specific operation of the units disclosed in the above embodiments of the present invention, please refer to the corresponding method embodiments, such as... Figure 1 As shown, it will not be elaborated further here.

[0171] Optionally, in another embodiment of the present invention, one implementation of the control device for the hydrogen production system further includes:

[0172] The fuel cell stack temperature monitoring unit is used to monitor the temperature of each fuel cell stack in the electrolytic cell in real time.

[0173] The adjustment amount determination unit is used to determine the power adjustment amount of the electric stack based on the proportional coefficient, integral coefficient, temperature of the electric stack, and average temperature of the electric stack when the difference between the temperature of any electric stack and the average temperature of the electric stack is greater than the temperature difference threshold.

[0174] The regulating unit is used to regulate the alkaline flow rate and current density of the branch where the fuel cell stack is located based on the power regulation amount of the fuel cell stack.

[0175] The specific working process of the units disclosed in the above embodiments of the present invention can be found in the corresponding method embodiments, and will not be repeated here.

[0176] Optionally, in another embodiment of the present invention, one implementation of the control device for the hydrogen production system further includes:

[0177] The photovoltaic array detection unit is used to monitor the voltage and current data of the photovoltaic array in real time.

[0178] The real-time equivalent impedance determination unit is used to determine the real-time equivalent impedance based on the voltage and current data of the monitored photovoltaic array.

[0179] The impedance adjustment unit is used to adjust the self-impedance of the electrolytic cell to the real-time equivalent impedance.

[0180] The specific working process of the units disclosed in the above embodiments of the present invention can be found in the corresponding method embodiments, and will not be repeated here.

[0181] Optionally, in another embodiment of the present invention, one implementation of the control device for the hydrogen production system further includes:

[0182] Output power monitoring unit, used to monitor the output power of photovoltaic array in real time.

[0183] The target step size determination unit is used to determine the target step size based on the rate of change of the output power of the photovoltaic array.

[0184] The power adjustment unit is used to adjust the power of the electrolyzer in real time based on the target step size and the rated power of the electrolyzer.

[0185] The specific working process of the units disclosed in the above embodiments of the present invention can be found in the corresponding method embodiments, and will not be repeated here.

[0186] Optionally, in another embodiment of the present invention, one implementation of the target step size determination unit further includes:

[0187] The first step length determination unit is used to determine the first step length based on the rate of change of the output power of the photovoltaic array.

[0188] The judgment unit is used to determine whether the difference between the first step length and the previous step length is less than the step length difference threshold.

[0189] The first target step size determination sub-unit is used to determine the first step size as the target step size if the judgment unit determines that the difference between the first step size and the previous step size is less than the step size difference threshold.

[0190] The second target step size determination subunit is used to determine the target step size if the judgment unit determines that the difference between the first step size and the previous step size is not less than the step size difference threshold.

[0191] The specific working process of the units disclosed in the above embodiments of the present invention can be found in the corresponding method embodiments, and will not be repeated here.

[0192] As can be seen from the above scheme, the present invention provides a control device for a hydrogen production system. After the acquisition unit 710 acquires the current dynamic response characteristic data of the electrolyzer in real time, the determination unit 720 determines the set of control parameters to be optimized based on the current dynamic response characteristic data of the electrolyzer. Then, the optimization unit 730 optimizes the parameters of all control parameter types in the set of control parameters to be optimized to obtain the optimal combination of control parameters. Finally, the adjustment unit 740 simultaneously adjusts the control parameters of the electrolyzer and the heating power of the integrated heater based on the optimal combination of control parameters, so as to achieve precise control of the temperature of the electrolyzer, so that the electrolyzer can be maintained at the optimal operating temperature, thereby effectively improving the hydrogen production efficiency.

[0193] Another embodiment of the present invention provides a hydrogen production system, such as Figure 8 As shown, it specifically includes:

[0194] Electrolyzer module 810, thermal management module 820, and control device for hydrogen production system.

[0195] The electrolyzer module 810 is connected to the thermal management module 820; the control device of the hydrogen production system is connected to the electrolyzer module 810 and the thermal management module 820 respectively.

[0196] The electrolytic cell module 810 may, but is not limited to, adopt a parallel configuration of multiple alkaline electrolytic cell stacks. Each stack consists of multiple bipolar electrode pressure filters. Sealing material is used between the electrode plates, and the stacks are connected by parallel pipelines to ensure uniform distribution of alkali solution. No limitation is made here.

[0197] Specifically, the electrolytic cell can be designed to operate at a temperature of 60-90℃ and a pressure of 1.0-1.6MPa, without any specific limit.

[0198] The thermal management module 820 includes an integrated heater, a temperature sensor, an alkali circulation system, etc., which are not limited here.

[0199] It should be noted that the integrated heater can employ, but is not limited to, electromagnetic induction heating technology, steam heating technology, etc., and can be directly embedded inside the electrolytic cell; no limitation is made here. Temperature sensors can be placed at the inlet and outlet of each fuel cell stack, as well as at the overall inlet and outlet of the module, to monitor the temperature distribution in real time; no limitation is made here. The alkali circulation system can employ, but is not limited to, a variable frequency circulation pump, using real-time data from the temperature probe to perform PID calculations and output a variable frequency signal to adjust the alkali flow rate and achieve temperature control; no limitation is made here.

[0200] In the practical application of this invention, the initial system startup temperature is low, requiring a large startup effort and a relatively slow rate of increase and decrease. Introducing an integrated heater allows for stable load control within a controllable temperature range, shortening the cold start time. Once the operating temperature is reached, the power load can be adjusted over a wide range. This reduces the system's cold start time from over 30 minutes to less than 10 minutes, and the hot start time to less than 1 minute.

[0201] The control device of the hydrogen production system can consist of two parts: a power distribution module and a control module. The power distribution module is connected to the control module, the electrolyzer module 810, and the thermal management module 820, respectively.

[0202] The power distribution module includes a high-efficiency DC / DC converter and a power distribution controller, with a conversion efficiency greater than 98%. The power distribution controller can dynamically distribute the input power between the electrolyzer and the integrated heater, prioritizing heating power during startup and optimizing electrolysis power during steady-state operation.

[0203] In the practical application of this invention, during the initial system startup, 20%-40% of the input power is allocated to the integrated heating device via the power distribution unit, causing the electrolyzer to rise from room temperature to above 60°C within 3-5 minutes. Simultaneously, a "dual-temperature zone dynamic response" strategy is employed to implement graded temperature control at the inlet and outlet of the electrolyzer. When the system detects that the temperature difference between the various electrolyzer stacks within the module exceeds a preset threshold (e.g., 5°C), the control module performs temperature equalization control. Power distribution and temperature equalization between the various electrolyzer stacks within the module are achieved through the internal control of each individual alkaline electrolyzer module.

[0204] The control module can adopt a hierarchical architecture, including a bottom-level single-module temperature equalization controller and an upper-level central coordination controller. The bottom-level single-module temperature equalization controller, based on real-time temperature feedback from each fuel cell stack, adjusts power distribution and alkali flow rate to keep the temperature difference between stacks within a minimal range. The upper-level central coordination controller comprehensively considers system load demand, renewable energy fluctuations, and the operating status of each module, dynamically adjusting the operating parameters of each module to ensure efficient and stable system operation under various conditions.

[0205] The hierarchical control module in this invention not only achieves precise temperature control but also rapidly adjusts the system's operating strategy based on real-time changes in renewable energy. For example, when renewable energy power suddenly increases, the upper-level controller quickly assesses the system's load capacity and rationally allocates power to the electrolyzer and heating device, preventing system damage due to excessive power while maximizing the utilization of renewable energy for hydrogen production. When power decreases, the controller also adjusts promptly to reduce unnecessary energy consumption and ensure system energy efficiency.

[0206] In the practical application of this invention, after the system is powered on, the control module first detects the readings of each temperature sensor to determine the initial temperature state of the system. If the system temperature is below 40°C, it is determined to be a cold start; if the temperature is between 40-60°C, it is determined to be a warm start; if the temperature is above 60°C, it is determined to be a hot start.

[0207] Subsequently, depending on the startup type, the power allocation unit implements different power allocation strategies:

[0208] Cold start: Allocate 30%-40% of the input power to the integrated heater to rapidly increase the temperature of the electrolytic cell;

[0209] Warm start: Allocate 20%-30% of the input power to the integrated heater;

[0210] Hot start: Allocate 5%-10% of the input power to the integrated heater.

[0211] Once the system temperature reaches the set operating temperature (e.g., 80°C), the system switches to a high-efficiency operating mode. A multi-parameter coordinated control strategy based on feasible region analysis dynamically optimizes control parameters by establishing a safety boundary mapping in a four-dimensional parameter space encompassing temperature, current density, pressure, and electrolyte flow rate. Model predictive control (MPC) and genetic iteration methods are employed to determine the fitness function that maximizes hydrogen production efficiency, thereby determining the optimal combination of control parameters in real time.

[0212] To adapt to the fluctuating characteristics of renewable energy, this system adopts an equivalent dynamic impedance model combined with a dynamic step size, which makes the response time less than 10ms, enabling it to quickly track changes in photovoltaic power and reduce the energy efficiency fluctuation error to 1.1%.

[0213] In this invention, the various modules of the system cooperate and coordinate with each other. The thermal management module 820 provides a suitable temperature environment for the electrolyzer unit, ensuring the efficient conduct of the electrolysis reaction; the power distribution module accurately allocates power according to the real-time needs of the system, improving energy utilization efficiency; and the control module acts as the brain of the system, coordinating the work of each unit to make the entire system an organic whole. Through this collaborative working mode, the hydrogen production system of this invention exhibits significant advantages in terms of start-up speed, temperature control, system efficiency, safety and reliability, and adaptability to renewable energy, providing a practical solution for efficient and stable hydrogen production under renewable energy fluctuation scenarios.

[0214] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0215] Another embodiment of the present invention provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the control method of the hydrogen production system as described in the above embodiments.

[0216] 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 include, but are 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.

[0217] It should be noted that the computer-readable medium described above in this invention can be a computer-readable signal medium, a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0218] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0219] Another embodiment of the present invention provides a computer program product, which, when executed, is used to perform the control method of the hydrogen production system described above.

[0220] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device, or installed from a ROM. When the computer program is executed by a processing device, it performs the functions defined in the methods of the embodiments of the present invention.

[0221] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in this invention is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely exemplary forms for implementing the invention.

[0222] While several specific implementation details are included in the foregoing discussion, these should not be construed as limiting the scope of the invention. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0223] The above description is merely a preferred embodiment of the present invention and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention is not limited to the specific combination of the above-described technical features, but also includes other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above-described features with technical features of the present invention (but not limited to) that have similar functions.

Claims

1. A control method for a hydrogen production system, characterized in that, include: Real-time acquisition of the current dynamic response characteristics data of the electrolyzer; Based on the current dynamic response characteristic data of the electrolyzer, determine the set of control parameters to be optimized; Optimize the parameters of all control parameter types in the set of control parameters to be optimized to obtain the optimal combination of control parameters; The control parameters of the electrolytic cell and the heating power of the integrated heater are adjusted based on the optimal combination of control parameters.

2. The control method for the hydrogen production system according to claim 1, characterized in that, The real-time acquisition of the current dynamic response characteristic data of the electrolyzer includes: Real-time acquisition of voltage and current data from the electrolytic cell; The current density is determined based on the current data and the total area of ​​all electrodes in the electrolytic cell. Based on the voltage data and current density of the electrolytic cell, the current dynamic response characteristic data of the electrolytic cell is generated.

3. The control method for the hydrogen production system according to claim 1, characterized in that, The optimization of parameters of all control parameter types in the set of control parameters to be optimized to obtain the optimal combination of control parameters includes: An initial population is generated based on the parameter range of all control parameter types in the set of control parameters to be optimized; wherein, the initial population includes multiple individuals; each individual includes parameters of all control parameter types; The fitness value of each individual is determined based on the fitness function; Genetic iteration is performed based on the fitness values ​​of all individuals to determine the optimal individual, and the parameters of all control parameter types included in the optimal individual are taken as the optimal control parameter combination.

4. The control method for the hydrogen production system according to claim 1, characterized in that, Also includes: Real-time monitoring of the temperature of each fuel cell stack in the electrolytic cell; When the temperature difference between any fuel cell stack and the average temperature of the fuel cell stack is greater than the temperature difference threshold, the power regulation amount of the fuel cell stack is determined based on the proportional coefficient, the integral coefficient, the temperature of the fuel cell stack, and the average temperature of the fuel cell stack. The alkaline solution flow rate and current density of the branch where the fuel cell stack is located are adjusted based on the power regulation amount of the fuel cell stack.

5. The control method for the hydrogen production system according to claim 1, characterized in that, Also includes: Real-time monitoring of voltage and current data of the photovoltaic array; Based on the voltage and current data of the monitored photovoltaic array, the real-time equivalent impedance is determined; The self-impedance of the electrolytic cell is adjusted to the real-time equivalent impedance.

6. The control method for the hydrogen production system according to claim 1, characterized in that, Also includes: Real-time monitoring of the photovoltaic array's output power; The target step size is determined based on the rate of change of the output power of the photovoltaic array. The power of the electrolytic cell is adjusted in real time based on the target step size and the rated power of the electrolytic cell.

7. The control method for the hydrogen production system according to claim 6, characterized in that, The determination of the target step size based on the rate of change of the output power of the photovoltaic array includes: The first step length is determined based on the rate of change of the output power of the photovoltaic array; Determine whether the difference between the first step length and the previous step length is less than the step length difference threshold; If it is determined that the difference between the first step length and the previous step length is less than the step length difference threshold, then the first step length is taken as the target step length. If it is determined that the difference between the first step length and the previous step length is not less than the step length difference threshold, then the sum of the previous step length and the step length difference is taken as the target step length.

8. A control device for a hydrogen production system, characterized in that, include: The acquisition unit is used to acquire the current dynamic response characteristic data of the electrolyzer in real time; The determining unit is used to determine the set of control parameters to be optimized based on the current dynamic response characteristic data of the electrolyzer; The optimization unit is used to optimize the parameters of all control parameter types in the set of control parameters to be optimized, so as to obtain the optimal combination of control parameters; The adjustment unit is used to adjust the control parameters of the electrolytic cell and the heating power of the integrated heater based on the optimal combination of control parameters.

9. A hydrogen production system, characterized in that, include: Electrolyzer module, thermal management module, and control device for the hydrogen production system as described in claim 8; The electrolyzer module is connected to the thermal management module; the control device of the hydrogen production system is connected to both the electrolyzer module and the thermal management module.

10. A computer storage medium, characterized in that, It stores a computer program, wherein the computer program, when executed by a processor, implements the control method of the hydrogen production system as described in any one of claims 1 to 7.

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