A multi-modal control method, device, equipment and medium of a hydrogen production system

Abstract

The present application belongs to the technical field of thermochemical hydrogen production, and provides a multi-mode control method, device, equipment and medium for a hydrogen production system, which is used to improve control tracking accuracy and the synergy between a mirror field and a reactor. The present application performs fuzzy reasoning through a target temperature deviation and a target temperature change rate to obtain a mirror field power adjustment factor indicating a proportion of a desired mirror field output power to a rated power. According to the mirror field power adjustment factor, a target working mode that needs to be executed by the hydrogen production system is determined. In this way, the present application reduces the temperature overshoot by combining the power adjustment factor and the fuzzy reasoning, and the switching process is free of abrupt changes, thereby reducing thermal shock and improving control tracking accuracy and the synergy between the mirror field and the reactor.

Description

Technical Field

[0001] This invention relates to the field of thermochemical hydrogen production technology, and more specifically, to a multimodal control method, apparatus, equipment, and medium for a hydrogen production system. Background Technology

[0002] Solar thermochemical hydrogen production systems produce hydrogen through a high-temperature-driven redox cycle of metal oxides such as cerium dioxide (CeO2), representing a green and sustainable hydrogen production technology. A typical solar thermochemical hydrogen production system includes a concentrating mirror field (heliostat array), a secondary reflector tower, and a thermochemical reactor.

[0003] However, existing control methods for solar thermochemical hydrogen production systems neglect the thermal inertia of the reactor by directly switching the mirror field operating mode using a fixed temperature threshold. Tests show that temperature overshoot during the transition from reduction to oxidation often reaches ±50°C, which not only reduces hydrogen yield but also easily damages the reactor lining and catalyst materials. Furthermore, the mirror field cannot dynamically adjust the concentrating power according to the real-time reactor temperature, easily leading to energy waste or temperature runaway. Therefore, existing control methods for solar thermochemical hydrogen production systems suffer from low control tracking accuracy and poor coordination between the mirror field and the reactor. Summary of the Invention

[0004] This application aims to provide a multimodal control method, apparatus, equipment, and medium for a hydrogen production system, in order to solve the problems of low control tracking accuracy and poor coordination between the mirror field and the reactor in existing control methods for solar thermochemical hydrogen production systems.

[0005] Firstly, this application provides a multimodal control method for a hydrogen production system, comprising: Obtain the target temperature deviation and the target temperature change rate; whereby the target temperature deviation is the difference between the current measured temperature of the reactor and the preset temperature, and the target temperature change rate is used to indicate the trend of the measured temperature during the sampling period. Based on fuzzy inference using the target temperature deviation and the target temperature change rate, the mirror field power adjustment factor is obtained; whereby the mirror field power adjustment factor is used to indicate the proportion of the expected mirror field output power to the rated power; Based on the mirror field power adjustment factor, the target operating mode that the hydrogen production system needs to execute is determined.

[0006] The technical solution provided in this application offers at least the following beneficial effects: by performing fuzzy inference using the target temperature deviation and the target temperature change rate, a mirror field power adjustment factor is obtained, indicating the proportion of the desired mirror field output power to the rated power. Based on the mirror field power adjustment factor, the target operating mode that the hydrogen production system needs to execute is determined. Thus, by combining the power adjustment factor and fuzzy inference, this application reduces temperature overshoot, eliminates abrupt changes during switching, reduces thermal shock, and thereby improves control tracking accuracy and the synergy between the mirror field and the reactor.

[0007] One possible implementation involves fuzzy reasoning based on the target temperature deviation and the target temperature change rate, including: The membership degree of the target temperature deviation is calculated using a preset first rule table; the first rule table stores the correspondence between different deviation values, preset linguistic value parameters, and linguistic values. The membership degree of the target temperature change rate is calculated using a preset second rule table; the second rule table stores the correspondence between different change rates, preset linguistic value parameters, and linguistic values. Based on the membership degree of the target temperature deviation and the membership degree of the target temperature change rate, Mamdani minimum inference is performed in the preset fuzzy rule table to obtain the activation degree of the corresponding fuzzy rule in the fuzzy rule table and the center value of the fuzzy rule. Based on the activation degree of each fuzzy rule and its corresponding center value, the centroid method is used to defuzzify the image field power adjustment factor.

[0008] One possible implementation is that the fuzzy rule table includes at least a first logical rule, a second logical rule, a third logical rule, and a fourth logical rule; Among them, the first logic rule is used to indicate that when the language values ​​corresponding to the target temperature deviation and the target temperature change rate are both positive, the language value corresponding to the power executed by the hydrogen production system is determined to be zero. The second logic rule is used to indicate that when the linguistic values ​​corresponding to the target temperature deviation and the target temperature change rate are both negative, the linguistic value corresponding to the power executed by the hydrogen production system is also zero. The third logic rule is used to indicate that the language value corresponding to the target temperature deviation is negative and the language value corresponding to the target temperature change rate is positive or positive, and to determine that the language value corresponding to the power executed by the hydrogen production system is positive. The fourth logic rule is used to indicate that when the linguistic value corresponding to the target temperature deviation is zero, the power executed by the hydrogen production system is adjusted according to the target temperature change rate to maintain the stability of the executed power.

[0009] One possible implementation involves determining the target operating mode that the hydrogen production system needs to execute based on the mirror field power adjustment factor, including: When the state of the mirror field power adjustment factor being greater than or equal to the first preset value continues for a preset time, and the measured temperature is greater than or equal to the first preset temperature, the target working mode is determined to be the restored state. When the state of the mirror field power adjustment factor being less than or equal to the second preset value continues for a preset time, and the oxygen concentration at the outlet of the hydrogen production system reaches its peak value within a preset unit time and then tends to stabilize, the target working mode is determined to be the oxidation state. When the hydrogen concentration at the outlet of the hydrogen production system reaches its peak value within a preset unit time and then tends to stabilize, the target operating mode is determined to be standby. Among them, the first preset value is greater than the second preset value, and the stable hydrogen concentration is less than the stable oxygen concentration.

[0010] One possible implementation is that the reduced state is used to indicate that the mirror field in the hydrogen production system is fully powered, so that the reactor is heated to a second preset temperature, which is greater than the first preset temperature. The oxidation state is used to indicate the adjustment of the mirror field power in the hydrogen production system and the introduction of water vapor based on the heliostat control information to achieve stable hydrogen production; where the heliostat control information is the number of heliostats that need to be added or removed.

[0011] In another possible implementation, the power change rate is determined by an incremental proportional-integral controller based on a first-order thermodynamic model equivalent to the reactor. Heliostat control information is calculated based on the power change rate and the average contribution power of a single heliostat.

[0012] One possible implementation involves calculating the heliostat control information using the following formula: ; in, For the number of heliostat stages that need to be increased or decreased, The rate of change of power, The average power contribution of a single heliostat.

[0013] Secondly, this application provides a multi-modal control device for a hydrogen production system, comprising: The acquisition module is used to acquire the target temperature deviation and the target temperature change rate; wherein, the target temperature deviation is the difference between the current measured temperature of the reactor and the preset temperature, and the target temperature change rate is used to indicate the trend of the measured temperature during the sampling period. The processing module is used to perform fuzzy inference based on the target temperature deviation and the target temperature change rate to obtain the mirror field power adjustment factor; wherein, the mirror field power adjustment factor is used to indicate the proportion of the expected mirror field output power to the rated power; The execution module is used to determine the target operating mode that the hydrogen production system needs to execute based on the mirror field power adjustment factor.

[0014] Thirdly, this application provides an electronic device comprising: a processor and a memory; the memory storing processor-executable instructions; when the processor is configured to execute the instructions, causing the electronic device to implement the method of the first aspect described above.

[0015] Fourthly, this application provides a computer-readable storage medium comprising: computer software instructions; which, when executed in an electronic device, cause the electronic device to implement the method described in the first aspect.

[0016] The beneficial effects of the second to fourth aspects mentioned above are described in the corresponding description of the first aspect and will not be repeated here. Attached Figure Description

[0017] Figure 1 A schematic diagram of the system control architecture provided in the embodiments of this application; Figure 2 A multimodal control method for a hydrogen production system is provided in the embodiments of this application; Figure 3 A schematic diagram of a fuzzy logic mode switching algorithm structure provided in an embodiment of this application; Figure 4 A schematic diagram of the composition of a multi-modal control device for a hydrogen production system provided in this application embodiment; Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0018] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone.

[0019] Furthermore, the terms "comprising" and "having," and any variations thereof, used in the description of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include other steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0020] It should be noted that in the embodiments of this application, the words "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0021] In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0022] The solar thermochemical hydrogen production system in this embodiment includes a concentrator field, a thermochemical reactor, and an auxiliary system. The concentrator field comprises multiple heliostats, a secondary reflector tower, and reflectors. The heliostats are centrally scheduled by a host computer within the concentrator field. Each heliostat is equipped with an independent local controller (LOC) and actuator. The secondary reflectors are fixed to the reflector tower.

[0023] The thermochemical reactor has an opening diameter of 20cm, a built-in type B thermocouple, and a pressure sensor and a gas analyzer at the outlet.

[0024] The auxiliary systems include a steam generator, a vacuum pump, an Ar gas circuit, a condenser, a water chiller, and a weather station.

[0025] The embodiments provided in this application will now be described in detail with reference to the accompanying drawings.

[0026] Figure 1 This is a schematic diagram of the system control architecture provided for an embodiment of this application. The multimodal control method for a hydrogen production system provided in this application can be applied to, for example... Figure 1 In the decision-making layer of the control architecture shown. For example... Figure 1 As shown, the system control architecture includes a decision layer, a control layer, and an equipment layer.

[0027] The host computer-borne decision-making layer includes a modal decision-making module, a mirror field scheduling module, a reactor control module, and a corresponding database. The modal decision-making module calculates the mirror field power adjustment factor α based on a fuzzy inference algorithm and automatically determines mode switching based on oxygen and hydrogen concentration thresholds. The mirror field scheduling module generates task instructions and sends them wirelessly to the heliostat's LOC. The reactor control module controls the reactor temperature, steam generator, vacuum pump, valves, etc., via RS485 / Mod-bus protocol. The database stores parameter tables, operation logs, and historical data.

[0028] The control layer includes the heliostat's local controller (LOC) and the reactor control system. The LOC refers to each heliostat being equipped with an independent local controller that receives tasks from the host computer and executes them autonomously (such as sun tracking, preparation, shutdown, and defocusing), and reports its status periodically. The reactor control system collects temperature, pressure, and gas concentration data and feeds them back to the host computer, and regulates flow rates, valves, and vacuum pumps.

[0029] The equipment layer includes the specific execution components such as the heliostat biaxial drive mechanism, reactor body, steam generator, vacuum pump, valves, condenser, and water chiller.

[0030] Figure 2 The multimodal control method for a hydrogen production system provided in this application embodiment can be applied to the above-mentioned system control architecture. Figure 3 This is a schematic diagram of a fuzzy logic mode switching algorithm structure provided in an embodiment of this application. Combined with... Figure 2 and Figure 3 The following describes a multimodal control method for a hydrogen production system provided in an embodiment of this application: S101. Obtain the target temperature deviation and the target temperature change rate.

[0031] The target temperature deviation is the difference between the current measured temperature of the reactor and the preset temperature, and the target temperature change rate is used to indicate the trend of the measured temperature during the sampling period.

[0032] For example, the target temperature deviation is The domain of discourse is When e > 0, the temperature needs to be lowered; when e < 0, the temperature needs to be raised. For example, the target temperature change rate is Sampling period The domain of discourse is .

[0033] in, For actual measured temperature, For preset temperature, Temperature rises, The temperature dropped.

[0034] S102. Based on the target temperature deviation and the target temperature change rate, perform fuzzy inference to obtain the mirror field power adjustment factor.

[0035] In one possible implementation, such as Figure 3 As shown, the membership degree of the target temperature deviation is calculated and obtained through the preset first rule table; wherein, the first rule table stores the correspondence between different deviation values, preset linguistic value parameters and linguistic values.

[0036] For example, a triangular membership function is used, and each variable is defined with 5 language values: NB (negative big), NS (negative small), ZO (zero), PS (positive small), and PB (positive big).

[0037] Specifically, the preset first rule table is shown in Table 1 below: Table 1

[0038] Among them, the target temperature deviation Domain of discourse Five language value parameters (left endpoint, center point, right endpoint).

[0039] In one possible implementation, the membership degree of the target temperature change rate is calculated using a preset second rule table; wherein, the second rule table stores the correspondence between different change rates, preset linguistic value parameters, and linguistic values.

[0040] Specifically, the preset second rule table is shown in Table 2 below: Table 2

[0041] Furthermore, the membership degree of the target temperature deviation and the membership degree of the target temperature change rate are calculated using the triangular membership formula. The triangular membership formula is shown in formula (1) below: (1); Where a, b, and c are the left endpoint, center point, and right endpoint, respectively.

[0042] In one possible implementation, based on the membership degree of the target temperature deviation and the membership degree of the target temperature change rate, Mamdani minimum inference is performed in a preset fuzzy rule table to obtain the activation degree of the corresponding fuzzy rule in the fuzzy rule table and the center value of the fuzzy rule.

[0043] Specifically, the preset fuzzy rule table is shown in Table 3 below: Table 3

[0044] The fuzzy rule table includes at least a first logical rule, a second logical rule, a third logical rule, and a fourth logical rule.

[0045] The first logic rule indicates that when both the target temperature deviation and the target temperature change rate correspond to positive values, the linguistic value corresponding to the power output of the hydrogen production system is determined to be zero. The second logic rule indicates that when both the target temperature deviation and the target temperature change rate correspond to negative values, the linguistic value corresponding to the power output of the hydrogen production system is also determined to be zero. The third logic rule indicates that when the linguistic value corresponding to the target temperature deviation is negative and the linguistic value corresponding to the target temperature change rate is positive or positive, the linguistic value corresponding to the power output of the hydrogen production system is determined to be positive. The fourth logic rule indicates that when the linguistic value corresponding to the target temperature deviation is zero, the power output of the hydrogen production system is adjusted according to the target temperature change rate to maintain stable power output.

[0046] For performing Mamdani minimum inference in the preset fuzzy rule table, the activation degree of the corresponding fuzzy rule in the fuzzy rule table is obtained by the following formula (2): (2); in, It is a membership function , It is the target temperature deviation For the preset first rule table membership degree It is the current target temperature change rate. For the preset second rule table The membership degree is the minimum of the two values, which represents the degree to which the preconditions of the corresponding rule are satisfied.

[0047] In one possible implementation, the mirror field power adjustment factor is obtained by defuzzifying the mirror field based on the activation degree of each fuzzy rule and its corresponding center value using the centroid method.

[0048] Specifically, the fuzziness is resolved using the following formula (3): (3); in, This is the mirror field power adjustment factor. This indicates the ratio of the expected output power of the mirror field to the rated power. The larger the value, the higher the power. The smaller the value, the lower the power. For the first Activation of a fuzzy rule , For the first The center value output by each rule .

[0049] In one possible implementation, the fuzzy rule table provided in this application also exhibits asymmetry for CeO2. This asymmetry means that during the heating phase (preheating → reduction), a mirror field power adjustment factor α ≥ 0.8 for 30 seconds is required to trigger the switching; while during the cooling phase (reduction → oxidation), a mirror field power adjustment factor α ≤ 0.2 for 30 seconds is sufficient for triggering. This design addresses the cycling characteristics of CeO2: reduction requires high energy input, while oxidation requires a rapid response to avoid overheating.

[0050] S103. Determine the target operating mode that the hydrogen production system needs to execute based on the mirror field power adjustment factor.

[0051] In one possible implementation, the state in which the mirror field power adjustment factor α is greater than or equal to a first preset value, such as 0.8, continues for a preset time, such as 30 seconds, and the measured temperature is greater than or equal to the first preset temperature, that is... The target working mode is determined to be the restoration state, that is, the mode is changed from the preheating mode indicated by mode M1 to the restoration state indicated by mode M2.

[0052] The reduced state is used to indicate that the mirror field in the hydrogen production system is fully powered, so that the reactor is heated to a second preset temperature, which is greater than the first preset temperature.

[0053] In one possible implementation, the state in which the mirror field power adjustment factor α is less than or equal to a second preset value, such as 0.2, continues for a preset time, such as 30 seconds, and the oxygen concentration at the outlet of the hydrogen production system reaches its peak value within a preset unit time and then tends to stabilize, i.e., the outlet oxygen concentration... The oxygen concentration rises from a stable m1% to a peak m'1% and then decreases, then decreases again to m1% (m1% is 0.15% to 0.20%, preferably 0.15%). The target working mode is determined to be the oxidation state, that is, the switch from the reduction state indicated by the M2 mode to the oxidation state indicated by the M3 mode.

[0054] The oxidation state is used to indicate the adjustment of the mirror field power in the hydrogen production system and the introduction of water vapor based on the heliostat control information to achieve stable hydrogen production; the heliostat control information is the number of heliostats that need to be added or removed.

[0055] Furthermore, the control information for the heliostat is explained as follows: Based on a first-order thermodynamic model equivalent to the reactor, the power change rate is determined by an incremental proportional-integral controller; the control information for the heliostat is calculated and obtained based on the power change rate and the average contribution power of a single heliostat.

[0056] The power change rate, determined by the incremental proportional-integral controller, can be calculated using the following formula (4): (4); in, For the corresponding temperature deviation, , To set the temperature, such as , The current temperature. For example, a sampling period of 2 seconds. For the first engineering experience value, such as , For the first engineering experience value, such as .

[0057] The control information of the heliostat is calculated based on the power change rate and the average contribution power of a single heliostat, and is obtained by the following formula (5): (5); Where ΔN is the number of heliostats to be added or removed, ΔP is the power change rate, and Psingle is the average contribution power of a single heliostat. If ΔN>0, the first ΔN heliostats are added from the unadded heliostats, sorted by real-time optical efficiency from high to low; if ΔN<0, the first ΔN heliostats are removed from the already added heliostats, sorted by optical efficiency from low to high.

[0058] In one possible implementation, in response to the outlet hydrogen concentration of the hydrogen production system... The peak value m'2 is reached within a preset unit time. Afterwards, the hydrogen concentration m2 tends to stabilize. like At that time, the target working mode is determined to be standby, that is, switching from the oxidation state indicated by the M3 mode to the standby state.

[0059] The first preset value, such as 0.8, is greater than the second preset value, such as 0.2; the stable hydrogen concentration, such as 0.15%, is less than the stable oxygen concentration, such as... .

[0060] In another possible implementation, if a Level 1 alarm is triggered: the current reactor temperature The host computer sends an emergency defocusing broadcast, and all local controllers of heliostats rotate to the protection posture (pitch 0°) within 10 seconds at the highest speed (e.g., 20° / s); the reactor control system immediately shuts off the steam generator, closes the Ar inlet valve, stops the vacuum pump, and opens the safety exhaust valve.

[0061] In another possible implementation, if a level two alarm is triggered: wind speed or the temperature after the condenser At that time, control the partial defocusing of the heliostats, remove 50% of the outer ring heliostats (arranged from farthest to closest to the secondary tower), record the alarm, and do not actively shut down the reactor.

[0062] In summary, the following explanation is provided in conjunction with specific embodiments: 1) After the hydrogen production control system is started, it enters M0 (standby / self-test) to complete the airtightness and communication tests.

[0063] 2) Switch to the preheating state indicated by the M1 mode: At this time, the host computer automatically adjusts the mirror field power adjustment factor α according to the fuzzy inference output, and the reactor temperature rises from room temperature to 800~1000℃.

[0064] 3) After reaching the end of the preheating period, the mirror field power adjustment factor α is ≥0.8 for 30 consecutive seconds, and automatically switches to the reduction state indicated by the M2 mode: at this time, the mirror field is fully powered, the reactor is heated to 1400℃, Ar is introduced and a vacuum is drawn to maintain a low oxygen partial pressure.

[0065] 4) After reduction, the oxygen concentration drops to a stable level, and the mirror field power adjustment factor α ≤ 0.2 for 30 consecutive seconds, then switch to the oxidation state indicated by the M3 mode: introduce water vapor to stabilize hydrogen production, and maintain the outlet hydrogen concentration. When the hydrogen concentration reaches a stable level, the target operating mode is set to standby, and the process ends / purges.

[0066] During the control process, if the current reactor temperature Enter Emergency Mode M4. Under Emergency Mode M4, take corresponding response actions based on the triggered Level 1 or Level 2 alarm.

[0067] The temperature overshoot during the entire process is ≤±15℃, and the hydrogen yield is increased by 18% compared with the traditional method.

[0068] In this embodiment, fuzzy inference is performed using the target temperature deviation and the target temperature change rate to obtain a mirror field power adjustment factor that indicates the proportion of the desired mirror field output power to the rated power. Based on the mirror field power adjustment factor, the target operating mode that the hydrogen production system needs to execute is determined. Thus, by combining the power adjustment factor and fuzzy inference, this application reduces the temperature overshoot from ±50℃ to ±15℃ using the traditional threshold method, with no abrupt changes during the switching process, reducing thermal shock, thereby improving control tracking accuracy and the synergy between the mirror field and the reactor.

[0069] In some embodiments, this application also provides a multimodal control device for a hydrogen production system. This multimodal control device may include one or more functional modules for implementing the multimodal control method for a hydrogen production system provided in the above method embodiments.

[0070] For example, Figure 4 This is a schematic diagram illustrating the composition of a multimodal control device for a hydrogen production system provided in an embodiment of this application. Figure 4As shown, the multi-modal control device of the hydrogen production system includes: an acquisition module 401, a processing module 402, and an execution module 403.

[0071] The acquisition module 401 is used to acquire the target temperature deviation and the target temperature change rate; wherein, the target temperature deviation is the difference between the current measured temperature of the reactor and the preset temperature, and the target temperature change rate is used to indicate the trend of the measured temperature during the sampling period.

[0072] The processing module 402 is used to perform fuzzy inference based on the target temperature deviation and the target temperature change rate to obtain the mirror field power adjustment factor; wherein, the mirror field power adjustment factor is used to indicate the proportion of the expected mirror field output power to the rated power.

[0073] The execution module 403 is used to determine the target operating mode that the hydrogen production system needs to execute based on the mirror field power adjustment factor.

[0074] The processing module 402 is specifically used to calculate and obtain the membership degree of the target temperature deviation through a preset first rule table; wherein, the first rule table stores the correspondence between different deviation values, preset linguistic value parameters and linguistic values; The membership degree of the target temperature change rate is calculated using a preset second rule table; the second rule table stores the correspondence between different change rates, preset linguistic value parameters, and linguistic values. Based on the membership degree of the target temperature deviation and the membership degree of the target temperature change rate, Mamdani minimum inference is performed in the preset fuzzy rule table to obtain the activation degree of the corresponding fuzzy rule in the fuzzy rule table and the center value of the fuzzy rule. Based on the activation degree of each fuzzy rule and its corresponding center value, the centroid method is used to defuzzify the image field power adjustment factor.

[0075] The processing module 402 is specifically used to determine the target working mode as the restoration state when the state of the mirror field power adjustment factor being greater than or equal to the first preset value continues for a preset time and the measured temperature is greater than or equal to the first preset temperature. When the state of the mirror field power adjustment factor being less than or equal to the second preset value continues for a preset time, and the oxygen concentration at the outlet of the hydrogen production system reaches its peak value within a preset unit time and then tends to stabilize, the target working mode is determined to be the oxidation state. When the hydrogen concentration at the outlet of the hydrogen production system reaches its peak value within a preset unit time and then tends to stabilize, the target operating mode is determined to be standby. Among them, the first preset value is greater than the second preset value, and the stable hydrogen concentration is less than the stable oxygen concentration.

[0076] Processing module 402 is specifically used to determine the power change rate based on a first-order thermal dynamic model equivalent to the reactor by using an incremental proportional-integral controller; Heliostat control information is calculated based on the power change rate and the average contribution power of a single heliostat.

[0077] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device includes: a processor 502, a communication interface 503, and a bus 504. Optionally, the electronic device may also include a memory 501.

[0078] Processor 502 may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 502 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 502 may also be a combination of functions implementing computing capabilities, such as a combination including CPU0 and CPU1, a DSP, and a microprocessor.

[0079] The communication interface 503 includes a receiving unit and a transmitting unit, and is used to connect with other devices via a communication network. This communication network can be Ethernet, a wireless access network, a wireless local area network (WLAN), etc.

[0080] The memory 501 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), disk storage medium or other magnetic storage device, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.

[0081] As one possible implementation, the memory 501 can exist independently of the processor 502. The memory 501 can be connected to the processor 502 via a bus 504 and is used to store instructions or program code. When the processor 502 calls the instructions or program code stored in 501, it can implement the multimodal control method of the hydrogen production system provided in this embodiment of the invention.

[0082] In another possible implementation, the memory 501 can also be integrated with the processor 502.

[0083] Bus 504 can be an extended industry standard architecture (EISA) bus, etc. Bus 504 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0084] Through the above description of the implementation methods, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the service calling device can be divided into different functional modules to complete all or part of the functions described above.

[0085] This application also provides a computer-readable storage medium. All or part of the processes in the above method embodiments can be executed by computer instructions instructing related hardware. The program can be stored in the aforementioned computer-readable storage medium, and when executed, it can include the processes of the above method embodiments. The computer-readable storage medium can be any of the foregoing embodiments or memory. The aforementioned computer-readable storage medium can also be an external storage device of the aforementioned service invocation device, such as a plug-in hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the aforementioned service invocation device. Further, the aforementioned computer-readable storage medium can include both internal storage units of the aforementioned service invocation device and external storage devices. The aforementioned computer-readable storage medium is used to store the aforementioned computer program and other programs and data required by the aforementioned service invocation device. The aforementioned computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0086] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A multimodal control method for a hydrogen production system, characterized in that, The method includes: Obtain the target temperature deviation and the target temperature change rate; wherein, the target temperature deviation is the difference between the current measured temperature of the reactor and the preset temperature, and the target temperature change rate is used to indicate the trend of the measured temperature during the sampling period; Based on the target temperature deviation and the target temperature change rate, fuzzy inference is performed to obtain the mirror field power adjustment factor; wherein, the mirror field power adjustment factor is used to indicate the proportion of the desired mirror field output power to the rated power; Based on the mirror field power adjustment factor, the target operating mode that the hydrogen production system needs to execute is determined.

2. The multimodal control method for a hydrogen production system according to claim 1, characterized in that, The fuzzy inference based on the target temperature deviation and the target temperature change rate includes: The membership degree of the target temperature deviation is calculated using a preset first rule table; wherein, the first rule table stores the correspondence between different deviation values, preset language value parameters, and language values. The membership degree of the target temperature change rate is calculated using a preset second rule table; wherein, the second rule table stores the correspondence between different change rates, the preset language value parameter, and the language value. Based on the membership degree of the target temperature deviation and the membership degree of the target temperature change rate, Mamdani minimum inference is performed in the preset fuzzy rule table to obtain the activation degree of the corresponding fuzzy rule in the fuzzy rule table and the center value corresponding to the fuzzy rule. Based on the activation degree and corresponding center value of each fuzzy rule, the centroid method is used to defuzzify and obtain the mirror field power adjustment factor.

3. The multimodal control method for a hydrogen production system according to claim 2, characterized in that, The fuzzy rule table includes at least a first logical rule, a second logical rule, a third logical rule, and a fourth logical rule; Wherein, the first logic rule is used to indicate that when the language values ​​corresponding to the target temperature deviation and the target temperature change rate are both positive, the language value corresponding to the power executed by the hydrogen production system is determined to be zero; The second logic rule is used to determine that when the language values ​​corresponding to the target temperature deviation and the target temperature change rate are both negative, the language value corresponding to the power executed by the hydrogen production system is also zero. The third logic rule is used to indicate that the language value corresponding to the target temperature deviation is negative and the language value corresponding to the target temperature change rate is positive or positive, and to determine that the language value corresponding to the power executed by the hydrogen production system is positive. The fourth logic rule is used to indicate that when the language value corresponding to the target temperature deviation is zero, the power executed by the hydrogen production system is adjusted according to the target temperature change rate to maintain the stability of the execution power.

4. The multimodal control method for a hydrogen production system according to claim 1, characterized in that, The step of determining the target operating mode that the hydrogen production system needs to execute based on the mirror field power adjustment factor includes: When the state of the mirror field power adjustment factor being greater than or equal to the first preset value continues for a preset time, and the measured temperature is greater than or equal to the first preset temperature, the target working mode is determined to be the restoration state. When the state of the mirror field power adjustment factor being less than or equal to the second preset value continues for the preset time, and the oxygen concentration at the outlet of the hydrogen production system reaches a peak value within a preset unit time and then tends to stabilize, the target working mode is determined to be the oxidation state. When the hydrogen concentration at the outlet of the hydrogen production system reaches a peak value within a preset unit time and then tends to stabilize, the target operating mode is determined to be standby. Wherein, the first preset value is greater than the second preset value, and the stable hydrogen concentration is less than the stable oxygen concentration.

5. The multimodal control method for a hydrogen production system according to claim 4, characterized in that, The reduction state is used to indicate that the mirror field in the hydrogen production system is fully powered, so that the reactor is heated to a second preset temperature, which is greater than the first preset temperature. The oxidation state is used to indicate the adjustment of the mirror field power in the hydrogen production system and the introduction of water vapor according to the heliostat control information to achieve stable hydrogen production; wherein, the heliostat control information is the number of heliostats that need to be added or removed.

6. The multimodal control method for a hydrogen production system according to claim 5, characterized in that, The method further includes: Based on a first-order thermodynamic model equivalent to the reactor, the power change rate is determined by an incremental proportional-integral controller. The heliostat control information is calculated based on the power change rate and the average contribution power of a single heliostat.

7. The multimodal control method for a hydrogen production system according to claim 6, characterized in that, The heliostat control information is obtained through calculation using the following formula: ； in, The number of heliostat stages to be added or reduced is... The power change rate, This refers to the average contribution power of the single heliostat.

8. A multi-modal control device for a hydrogen production system, characterized in that, include: The acquisition module is used to acquire the target temperature deviation and the target temperature change rate; wherein, the target temperature deviation is the difference between the current measured temperature of the reactor and the preset temperature, and the target temperature change rate is used to indicate the change trend of the measured temperature during the sampling period; The processing module is used to perform fuzzy inference based on the target temperature deviation and the target temperature change rate to obtain the mirror field power adjustment factor; wherein, the mirror field power adjustment factor is used to indicate the proportion of the desired mirror field output power to the rated power; The execution module is used to determine the target operating mode that the hydrogen production system needs to execute based on the mirror field power adjustment factor.

9. An electronic device, characterized in that, It includes a processor and a memory, the processor being coupled to the memory; the memory is used to store computer instructions, which are loaded and executed by the processor to enable the computer device to perform the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes computer-executable instructions that, when executed on a computer, cause the computer to perform the method according to any one of claims 1 to 7.

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