Regulation and control method and device for hydrogen production and methanol production and electronic equipment

Abstract

The invention discloses a regulation and control method and device for hydrogen production and methanol production and electronic equipment, and relates to the technical field of energy system regulation and control, and the method comprises the steps: firstly, obtaining weather forecast data in a preset time period, carrying out wind power generation prediction according to the weather forecast data, and obtaining a wind power prediction result; then, a reward function and a penalty function corresponding to each production link are constructed, and a comprehensive score corresponding to each production link is obtained based on the reward function and the penalty function; and finally, based on the wind power prediction result and the comprehensive score corresponding to each production link, performing wind power distribution and production scheduling for each production link. By means of the method, the reward function and the penalty function are designed, the fluctuation situation occurring in the production process can be effectively dealt with, the production process is adjusted in advance, high risks possibly existing in a short time when the demand list is currently met are actively avoided, the production smoothness is optimized, and the production stability and continuity are improved.

Description

Technical Field

[0001] This application relates to the field of energy system regulation technology, and in particular to a regulation method, apparatus and electronic equipment for hydrogen production and methanol production. Background Technology

[0002] Green electricity-to-hydrogen-to-methanol technology has become an important development direction in the fields of new energy and chemical engineering in recent years. Utilizing renewable energy sources (such as wind and solar power) to produce hydrogen through water electrolysis, and then combining the hydrogen with feedstocks such as carbon monoxide or carbon dioxide to produce green methanol, has become one of the important pathways to achieve zero carbon emissions. This process not only helps reduce the use of fossil fuels but also improves energy efficiency and promotes the green transformation of the energy structure.

[0003] However, in practical applications, the volatility and intermittency of renewable energy make it difficult for the water electrolysis hydrogen production process to operate stably, easily leading to decreased equipment efficiency and energy waste. Secondly, traditional hydrogen-to-methanol production processes typically employ a relatively simple control strategy, focusing only on the hydrogen or methanol production process without considering the management or output of raw materials. While this production process is simple and easy to implement, it proves inadequate in the face of complex and ever-changing production environments, failing to controllably adjust the production schedule of various materials, thus hindering high-efficiency production and making it impossible to cope with fluctuations in the production process.

[0004] Therefore, how to improve the efficiency of hydrogen and methanol production and effectively cope with fluctuations in various stages of the production process to improve production stability and continuity is a technical problem that urgently needs to be solved. Summary of the Invention

[0005] This application provides a method, apparatus, and electronic device for regulating hydrogen production to methanol production, which solves the problem of low production efficiency caused by the inability to cope with various fluctuations in the production process when producing hydrogen to methanol in related technologies, and can significantly improve production stability and continuity.

[0006] In a first aspect, this application provides a method for regulating hydrogen production to methanol production, the method comprising: Obtain weather forecast data for a preset time period, and predict wind power generation based on the weather forecast data to obtain wind power prediction results; Construct reward functions and penalty coefficients for each production stage, and obtain a comprehensive score for each production stage based on the reward functions and penalty functions; wherein, the reward function is used to instruct each production stage to increase production output, the penalty function is used to instruct each production stage to reduce production output or suspend production, and the comprehensive score is used to instruct the wind power allocation ratio for each production stage. Based on the wind power forecast results and the comprehensive scores corresponding to each production stage, wind power is allocated and production is scheduled for each production stage.

[0007] By using the above methods to design reward and penalty functions, we can effectively cope with fluctuations in the production process, adjust the production process in advance, proactively avoid high risks that may exist in the short term to meet current demand, optimize production smoothness, and improve production stability and continuity.

[0008] In one optional implementation, the reward function consists of a material sufficiency reward function, an excess reward function, and a production continuity reward function, while the penalty function consists of a material shortage penalty function, a start-stop penalty function, and a power fluctuation penalty function; wherein, The material sufficiency reward function is used to indicate the sufficiency of materials required at each production stage; The excess reward function is used to instruct each production stage to increase production output when logistics are sufficient. The production continuity reward function is used to indicate that if each production stage was producing at the previous moment, continuing production at the current moment will result in a reward; The material shortage penalty function is used to instruct each production stage to prohibit the allocation of wind power when there is a shortage of materials; The start / stop penalty function is used to indicate whether each production stage should start the equipment to produce; The power fluctuation penalty function is used to smooth the production load of each production stage.

[0009] In one alternative implementation, the expression for the material sufficiency reward function is: ,in, Indicates the rated power of the methanol production unit. Indicates the inventory of solid raw materials. This indicates the amount of solid raw materials consumed per unit of power. The expression for the excess reward function is: Where represents the material inventory capacity at time t. Indicates the upper limit of material inventory capacity. This represents the inventory of solid raw materials at time t. Indicates the upper limit of the capacity of solid raw materials. , These represent weighting coefficients, used to adjust the relative importance of the adequacy of hydrogen and solid feedstock inventories; The expression for the production continuity reward function is: ,in, Indicates a constant reward value; The expression for the material shortage penalty function is: Where M is a preset positive number, This represents the material inventory capacity at time t. This represents the inventory of solid raw materials at time t. The power of the methanol production unit at time t is represented. The expression for the start / stop penalty function is: ,in, This represents the preset penalty constant. This represents the power of the methanol manufacturing unit at time t. This represents the power of the methanol manufacturing unit at time t-1.

[0010] The expression for the power fluctuation penalty function is: ,in, This indicates the preset penalty coefficient. This represents the power of the methanol manufacturing unit at time t. This represents the power of the methanol manufacturing unit at time t-1.

[0011] In an optional implementation, the method further includes constructing a material production reward and penalty function, which is used to maintain the material inventory capacity at each production stage at the target capacity. The expression of the material production reward and penalty function is as follows: ,in, Indicates the ideal material inventory capacity. This represents the high inventory penalty coefficient set when the material inventory capacity is higher than the ideal material inventory capacity. This represents the low inventory penalty coefficient set when the material inventory capacity is lower than the ideal material inventory capacity. This represents the material inventory capacity at time t. This indicates the upper limit of material inventory capacity.

[0012] In one optional implementation, during the hydrogen production process, the electrolyzer is divided into a dynamic cell and a static cell. When the wind power fluctuation exceeds a preset threshold, the dynamic cell is used to regulate the wind power. When the dynamic cell is used to regulate the wind power, the health status parameters of the dynamic cell are obtained, and the dynamic cell that can be used to regulate the wind power is determined based on the health status parameters. The expression for the health status parameters is: ,in, This represents the cumulative fatigue coefficient. The preset fatigue coefficient is indicated. The cumulative fatigue coefficient is calculated based on the damage degree of a single power change. The damage degree of a single power change characterizes the degree of damage to the electrolytic cell each time the power is adjusted.

[0013] The above method enables rapid adjustment of wind power. Using dynamic troughs for wind power adjustment balances stability and responsiveness, prioritizing the use of dynamic troughs in good health to avoid more severe damage to those in poor health, ensuring uniform wear of each dynamic trough and extending its service life.

[0014] In one optional implementation, when allocating wind power, the methanol production efficiency per unit time and per unit power consumption is calculated. If the methanol production efficiency is greater than the target production efficiency, the wind power allocation is reduced; if the methanol production efficiency is less than the target production efficiency, the wind power allocation is increased. The expression for calculating the methanol production efficiency is as follows: ,in, Indicates the time interval The quality of methanol produced domestically. In time interval The total electrical power consumed by the internal methanol production unit Indicates a time interval.

[0015] Secondly, this application provides a control device for hydrogen production and methanol production, the device comprising: The forecasting module is used to acquire weather forecast data within a preset time period and to perform wind power generation forecasting based on the weather forecast data, thereby obtaining wind power prediction results. The processing module is used to construct the reward function and penalty function corresponding to each production stage, and obtain the comprehensive score corresponding to each production stage based on the reward function and penalty function; wherein, the reward function is used to instruct each production stage to increase production output, the penalty function is used to instruct each production stage to reduce production output or suspend production, and the comprehensive score is used to instruct the wind power allocation ratio of each production stage. The control module is used to allocate wind power and schedule production for each production stage based on wind power forecast results and comprehensive scores corresponding to each production stage.

[0016] In one optional implementation, the reward function consists of a material sufficiency reward function, an excess reward function, and a production continuity reward function, while the penalty function consists of a material shortage penalty function, a start-stop penalty function, and a power fluctuation penalty function; wherein, The material sufficiency reward function is used to indicate the sufficiency of materials required at each production stage; The excess reward function is used to instruct each production stage to increase production output when materials are sufficient. The production continuity reward function is used to indicate that if each production stage was producing at the previous moment, continuing production at the current moment will result in a reward; The material shortage penalty function is used to instruct each production stage to prohibit the allocation of wind power when there is a shortage of materials; The start / stop penalty function is used to indicate whether each production stage should start the equipment to produce; The power fluctuation penalty function is used to smooth the production load of each production stage.

[0017] In one alternative implementation, the expression for the material sufficiency reward function is: ,in, Indicates the rated power of the methanol production unit. Indicates the inventory of solid raw materials. This indicates the amount of solid raw materials consumed per unit of power. The expression for the excess reward function is: Where represents the material inventory capacity at time t. Indicates the upper limit of material inventory capacity. This represents the inventory of solid raw materials at time t. Indicates the upper limit of the capacity of solid raw materials. , These represent weighting coefficients, used to adjust the relative importance of the adequacy of hydrogen and solid feedstock inventories; The expression for the production continuity reward function is: ,in, Indicates a constant reward value; The expression for the material shortage penalty function is: Where M is a preset positive number, This represents the material inventory capacity at time t. This represents the inventory of solid raw materials at time t. The power of the methanol production unit at time t is represented. The expression for the start / stop penalty function is: ,in, This represents the preset penalty constant. This represents the power of the methanol manufacturing unit at time t. This represents the power of the methanol manufacturing unit at time t-1.

[0018] The expression for the power fluctuation penalty function is: ,in, This indicates the preset penalty coefficient. This represents the power of the methanol manufacturing unit at time t. This represents the power of the methanol manufacturing unit at time t-1.

[0019] In an optional implementation, the processing module is further configured to construct a material production reward and penalty function, which is used to maintain the material inventory capacity at each production stage at the target capacity. The expression of the material production reward and penalty function is as follows: ,in, Indicates the ideal material inventory capacity. This represents the high inventory penalty coefficient set when the material inventory capacity is higher than the ideal material inventory capacity. This represents the low inventory penalty coefficient set when the material inventory capacity is lower than the ideal material inventory capacity. This represents the material inventory capacity at time t. This indicates the upper limit of material inventory capacity.

[0020] In one optional implementation, the control module is further configured to divide the electrolyzer into a dynamic cell and a static cell during the hydrogen production process. When the wind power fluctuation exceeds a preset threshold, the dynamic cell is used to regulate the wind power. When the dynamic cell is used to regulate the wind power, the health status parameters of the dynamic cell are obtained, and the dynamic cell that can be used to regulate the wind power is determined based on the health status parameters. The expression for the health status parameters is: ,in, This represents the cumulative fatigue coefficient. The preset fatigue coefficient is indicated. The cumulative fatigue coefficient is calculated based on the damage degree of a single power change. The damage degree of a single power change characterizes the degree of damage to the electrolytic cell each time the power is adjusted.

[0021] In one optional implementation, the control module is further configured to calculate the methanol production efficiency per unit time and per unit power consumption when allocating wind power. If the methanol production efficiency is greater than the target production efficiency, the wind power allocation is reduced; if the methanol production efficiency is less than the target production efficiency, the wind power allocation is increased. The expression for calculating the methanol production efficiency is as follows: ,in, Indicates the time interval The quality of methanol produced domestically. In time interval The total electrical power consumed by the internal methanol production unit Indicates a time interval.

[0022] Thirdly, this application provides an electronic device including a processor and a memory, wherein the memory stores program code that, when executed by the processor, causes the processor to perform the steps of the hydrogen-to-methanol control method described in the first aspect.

[0023] Fourthly, this application provides a computer-readable storage medium including program code that, when run on an electronic device, causes the electronic device to perform the steps of the hydrogen-to-methanol control method described in the first aspect.

[0024] Fifthly, this application provides a computer program product that, when invoked by a computer, causes the computer to execute the control method steps for hydrogen production and methanol production as described in the first aspect.

[0025] Furthermore, other features and advantages of this application will be set forth in the following description and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 A schematic diagram of a suitable system architecture is provided for an embodiment of this application; Figure 2 A schematic diagram illustrating the implementation process of a method for regulating hydrogen production to methanol provided in this application embodiment; Figure 3 A schematic diagram of a control device for hydrogen production and methanol production provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this application. Obviously, the described embodiments are only some embodiments of the technical solutions of this application, and not all embodiments. Based on the embodiments recorded in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the technical solutions of this application.

[0028] It should be noted that in the description of this application, "multiple" is understood as "at least two". "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. A connected to B can represent: A and B directly connected, or A and B connected through C. Furthermore, in the description of this application, terms such as "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance or order.

[0029] Furthermore, the data collection, dissemination, and use in the technical solution of this application all comply with the requirements of relevant national laws and regulations.

[0030] The design concept of the embodiments of this application is briefly introduced below: Green electricity-to-hydrogen-to-methanol technology has become an important development direction in the fields of new energy and chemical engineering in recent years. Utilizing renewable energy sources (such as wind and solar power) to produce hydrogen through water electrolysis, and then combining the hydrogen with feedstocks such as carbon monoxide or carbon dioxide to produce green methanol, has become one of the important pathways to achieve zero carbon emissions. This process not only helps reduce the use of fossil fuels but also improves energy efficiency and promotes the green transformation of the energy structure.

[0031] However, in practical applications, the volatility and intermittency of renewable energy make it difficult for water electrolysis to operate stably, easily leading to decreased equipment efficiency and energy waste. Secondly, traditional hydrogen-to-methanol production processes typically employ a simplistic control strategy, focusing only on the hydrogen or methanol production process without considering raw material management or output. While this process is simple and easy to implement, it falls short in handling complex and ever-changing production environments, failing to controllably adjust the production schedule of various materials, thus hindering high-efficiency production and making it unable to cope with fluctuations during the production process.

[0032] In view of this, this application provides a method for regulating hydrogen production and methanol production. The method includes: first, acquiring weather forecast data for a preset time period and predicting wind power generation based on the weather forecast data to obtain wind power prediction results; then, constructing reward and penalty functions for each production stage, and obtaining a comprehensive score for each production stage based on the reward and penalty functions; wherein the reward function instructs each production stage to increase production output, the penalty function instructs each production stage to reduce production output or suspend production, and the comprehensive score instructs the wind power allocation ratio for each production stage; next, based on the wind power prediction results and the comprehensive scores for each production stage, wind power allocation and production scheduling are performed for each production stage. Through this method, wind power allocation and production scheduling are transformed from static rule-based allocation to real-time dynamic allocation of wind power and production scheduling. This allows for advance monitoring of material inventory and wind power status, optimizing production smoothness, reducing equipment wear, and proactively avoiding situations such as material inventory shortages and insufficient wind power, thereby improving long-term production stability.

[0033] See Figure 1 The diagram shown illustrates a system architecture according to an embodiment of this application. This system architecture includes a target terminal 101 and a server 102. The target terminal 101 and the server 102 can interact via a communication network. The communication network can employ wireless communication or wired communication methods.

[0034] For example, the target terminal 101 can access the network and communicate with the server 102 through cellular mobile communication technology, wherein the cellular mobile communication technology includes, for example, 5th generation mobile networks (5G) technology.

[0035] Optionally, the target terminal 101 can access the network and communicate with the server 102 via short-range wireless communication, wherein the short-range wireless communication method includes, for example, Wireless Fidelity (Wi-Fi) technology.

[0036] This application embodiment does not impose any limitation on the number of communication devices involved in the above system architecture. For example, there may be more target terminals, or no target terminals, or other network devices may be included, such as... Figure 1 As shown, only the target terminal 101 and server 102 are described as examples. The following is a brief introduction to each of the above devices and their respective functions.

[0037] The target terminal 101 is a device that can provide voice and / or data connectivity to a user, and may be a device that supports limited and / or wireless connectivity.

[0038] For example, the target terminal 101 includes, but is not limited to: mobile phones, tablets, laptops, handheld computers, mobile internet devices (MID), wearable devices, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminal devices in industrial control, wireless terminal devices in autonomous driving, wireless terminal devices in smart grids, wireless terminal devices in transportation safety, wireless terminal devices in smart cities, or wireless terminal devices in smart homes, etc.

[0039] Furthermore, the target terminal 101 may have a related client installed, and this client may be software, such as an application (APP), browser, short video software, or a network element, mini-program, etc. In this embodiment, the target terminal 101 may use the aforementioned client related to the regulation of hydrogen and methanol production to send the obtained wind power prediction results to the server 102 for subsequent wind power allocation and production scheduling.

[0040] Server 102 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0041] It is worth noting that, in the embodiments of this application, the methods in these embodiments can be executed by an electronic device, which can be the target terminal 101 or the server 102. That is, the method can be executed by the terminal device 101 or the server 102 alone, or by the target terminal device 101 and the server 102 together. Furthermore, the executing entities for each method can be the same or different, and this embodiment of the application does not impose any restrictions on this.

[0042] For example, when the target terminal 101 executes the hydrogen production and methanol production control method provided in this application alone, the target terminal 101 can first obtain weather forecast data within a preset time period, and make wind power generation prediction based on the weather forecast data to obtain wind power prediction results; then, construct reward functions and penalty functions corresponding to each production link, and obtain comprehensive scores corresponding to each production link based on the reward functions and penalty functions; finally, based on the wind power prediction results and the comprehensive scores corresponding to each production link, allocate wind power and schedule production for each production link.

[0043] For example, when the target terminal 101 and the server 102 jointly execute the hydrogen production and methanol production control method of this application, the target terminal 101 can obtain weather forecast data within a preset time period, and make wind power generation prediction based on the weather forecast data to obtain wind power prediction results, as well as construct reward functions and penalty functions corresponding to each production link, and obtain comprehensive scores corresponding to each production link based on the reward functions and penalty functions. Then, the wind power prediction results and the comprehensive scores corresponding to each production link are sent to the server 102 which is communicatively connected to the target terminal 101. The server 102 allocates wind power and schedules production for each production link based on the wind power prediction results and the comprehensive scores corresponding to each production link.

[0044] The following describes the control method for hydrogen production and methanol production provided by the exemplary embodiments of this application in conjunction with the above system architecture and with reference to the accompanying drawings. It should be noted that the above system architecture is only shown to facilitate understanding of the spirit and principles of this application, and the embodiments of this application are not limited in any way in this respect.

[0045] See Figure 2 The diagram shown is a schematic representation of the implementation flow of a method for controlling hydrogen production to methanol production according to an embodiment of this application. The specific implementation flow of this method is as follows: S1: Obtain weather forecast data for a preset time period, and predict wind power generation based on the weather forecast data to obtain wind power prediction results.

[0046] S2: Construct reward and penalty functions for each production stage, and obtain the comprehensive score for each production stage based on the reward and penalty functions.

[0047] S3: Based on the wind power prediction results and the comprehensive scores of each production stage, wind power is allocated and production is scheduled for each production stage.

[0048] In the embodiments of this application, wind power generation can be predicted for a specific time period to obtain wind power prediction results. For example, by predicting wind power generation in 24-hour or 48-hour units, wind power prediction results can be obtained for a specific time period such as 23:00 on October 28 to 23:00 on October 29 or 23:00 on October 28 to 23:00 on October 30.

[0049] When forecasting wind power generation, the first step is to obtain weather forecast data for the time period to be predicted (i.e., the preset time period). For example, this weather forecast data may include wind speed, wind direction, temperature, air pressure, humidity, and other data. Weather data can significantly affect wind energy resources and wind turbine power; therefore, accurate weather forecast data is a key factor in accurately predicting wind turbine efficiency and output power.

[0050] In the embodiments of this application, when predicting wind power generation based on the obtained weather forecast data, a Long Short-Term Memory Network (LSTM) can be used. LSTM can solve the gradient vanishing or gradient explosion problem when processing long sequences by introducing memory units and gating mechanisms. It can learn long-term dependencies in sequence data, so it can have a good prediction effect on time series data. Alternatively, an extreme gradient boosting model (XGBoost) can also be used. XGBoost also has good performance in tasks such as classification, regression, and prediction.

[0051] The model is trained and validated using historical weather and wind power data, enabling it to learn the mapping relationship between weather forecast data and wind power. This allows for real-time wind power generation prediction based on weather forecast data, providing a wind power forecast of the wind turbines' output within a preset time period. Furthermore, the model can be updated in real-time during wind power generation prediction. For example, if the current forecast is for wind power from 12:00 to 20:00, the forecast for 14:00 to 22:00 can be updated after the current forecast is obtained. Real-time prediction of wind power within a preset time period provides data support for subsequent production processes such as hydrogen and methanol production. This allows for wind power allocation and production scheduling for each production stage based on the predicted wind power, improving wind power utilization efficiency, avoiding power shortages or waste, enhancing production continuity, and preventing instability in production processes due to power issues.

[0052] In this embodiment, to consider the balance of wind power and materials in each production stage, a closed-loop production scheduling strategy prioritizing wind power, methanol production, and dynamic replenishment is implemented to achieve the optimal wind power allocation scheme and production scheduling scheme for each production stage, thereby enhancing the stability and continuity of each production process. This embodiment uses reward and penalty functions to achieve dynamic control of wind power allocation and production scheduling in each production stage.

[0053] Specifically, in this embodiment of the application, a reward function is constructed to encourage production and increase the output of each production stage. A penalty function is constructed to avoid material usage exceeding the inventory limit, frequent equipment start-ups and shutdowns, and large fluctuations in wind power. In these situations, each production stage should be instructed to reduce its output or suspend production.

[0054] In this embodiment, the reward function includes a material sufficiency reward function, an excess reward function, and a production continuity reward function. The material sufficiency reward function indicates the sufficiency of materials required at each production stage. For example, during methanol production, a fixed base reward is given if and only if the current hydrogen inventory and solid feedstock inventory simultaneously meet the current methanol production requirements. This serves as a "production permit" signal, indicating that the materials for current methanol production are sufficient to meet production needs and can adapt to current production, preventing material shortages that could lead to a halt in methanol production.

[0055] For example, in this embodiment of the application, the expression of the material sufficiency reward function is: ,in, Indicates the rated power of the methanol production unit. Indicates the inventory of solid raw materials. This represents the amount of solid raw materials consumed per unit of power. The material sufficiency reward function can be used to determine whether the current material inventory is sufficient to meet methanol production needs.

[0056] The excess reward function is used to instruct each production stage to increase production output when materials are plentiful. That is, the material inventory not only meets current production needs, but the more abundant the inventory, the higher the reward. This encourages increased production output when material inventory is sufficient, thereby improving the "robustness" of production and preventing low-volume production due to ample material inventory, which leads to low production efficiency and wasted resources.

[0057] For example, the expression for the excess reward function during methanol production is as follows: Where represents the material inventory capacity at time t. Indicates the upper limit of material inventory capacity. This represents the inventory of solid raw materials at time t. Indicates the upper limit of the capacity of solid raw materials. , These represent weighting coefficients used to adjust the relative importance of hydrogen and solid feedstock adequacy. Increasing the excess reward function allows for increased production when material inventories are sufficient, thereby improving methanol production efficiency.

[0058] Furthermore, in order to maintain continuous methanol production and prevent production from stopping due to slight fluctuations in wind power, a production continuity reward function is set up. This function indicates that methanol production was in progress at the previous moment, and continuing production will earn a reward, thereby extending the production status and improving the continuity and stability of production. This makes the production process more continuous and less susceptible to interruptions from minor external influences.

[0059] For example, the expression for the production continuity reward function during methanol production is as follows: ,in, Indicates the rated power of the methanol production unit. Indicates the inventory of solid raw materials. This indicates the amount of solid raw materials consumed per unit of power.

[0060] The reward function in the cost application embodiment, which consists of a material sufficiency reward function, an excess reward function, and a production continuity reward function, can regulate the methanol production process from aspects such as material inventory sufficiency and production continuity. This allows the methanol production process to maintain a good production status when materials are sufficient, increase production output, and reduce the impact of external factors on the production process.

[0061] Furthermore, in the embodiments of this application, the penalty function includes a material shortage penalty function, a start-stop penalty function, and a power fluctuation penalty function.

[0062] By setting a material shortage penalty function, methanol production can be prevented from starting or maintaining when material inventory is insufficient, thus avoiding problems in the production process due to insufficient material inventory.

[0063] Specifically, the expression for the material shortage penalty function used in methanol production is as follows: Where M is a preset positive number, This represents the material inventory capacity at time t. This represents the inventory of solid raw materials at time t. This represents the power of the methanol production unit at time t. It should be noted that in this embodiment, the value of M is set to a large positive number, for example, M is set to 105. Setting the value of M large enough can offset any positive rewards during the production process, ensuring that when methanol production is started or continued due to insufficient material inventory, the subsequent calculated comprehensive score for methanol production becomes extremely low, thus failing in the wind power allocation competition and avoiding the need to start or continue methanol production when material inventory is insufficient.

[0064] Next, a start-stop penalty function was set for methanol production. This function indicates whether the methanol production equipment can be started for production. When material inventory is insufficient or wind power fluctuates, methanol production equipment may frequently start and stop. Frequent start-stops lead to greater equipment wear, energy consumption, and material loss during production, thus reducing overall production efficiency. By setting a start-stop penalty function, the number of start-stop operations of methanol production equipment can be reduced. The equipment will only be started or stopped when absolutely necessary, keeping the number of start-stop operations within a reasonable range.

[0065] Specifically, in the embodiments of this application, the expression for the start-stop penalty function used in methanol production is as follows: ,in, This represents the preset penalty constant. This represents the power of the methanol manufacturing unit at time t. This represents the power of the methanol production unit at time t-1. It should be noted that the preset penalty constant in the start-stop penalty function is a fixed value used to set the switching action from shutdown to operation of the equipment. Depending on the actual application scenario, this value can be set to a medium size so that the preset penalty function is not so large as to completely prevent startup, but must be able to offset some minor rewards, and be able to determine whether the equipment startup is truly necessary when required, avoiding various losses caused by frequent startups.

[0066] In addition, a power fluctuation penalty function is set in this embodiment. By setting the power fluctuation penalty function, the production load in the production process can be smoothed, and drastic changes in wind power can be avoided. This helps the equipment avoid the impact of large production loads, thereby extending the service life of the equipment under stable production loads and maintaining stable wind power.

[0067] Specifically, in the embodiments of this application, the expression for the power fluctuation penalty function is as follows: ,in, This indicates the preset penalty coefficient. This represents the power of the methanol manufacturing unit at time t. This represents the power of the methanol production unit at time t-1. It is worth noting that in this embodiment, the power fluctuation penalty function can penalize the change in wind power between two time points. The greater the change in wind power, the greater the penalty. The preset penalty coefficient can be set to a relatively small value (e.g., -0.1). By using the preset penalty coefficient, the change in wind power can be linearly penalized, thus preventing drastic fluctuations in production load.

[0068] By designing material sufficiency reward functions, excess reward functions, production continuity reward functions, material shortage penalty functions, start-up and shutdown penalty functions, and power fluctuation penalty functions, we can ensure that the production process is optimized, that material inventory meets production needs, that the production process is continuous and stable without significant fluctuations, that the impact of wind power fluctuations on the production process is avoided, that equipment start-up and shutdown timing is optimized, and that profits are maximized when scheduling production.

[0069] Then, through the reward and penalty functions, a comprehensive score corresponding to the production process can be obtained. This comprehensive score is used to regulate the wind power allocation ratio in the production process and to control production scheduling. The comprehensive score at each time point can be expressed as:

[0070] The comprehensive score is obtained by adding the reward functions and penalty functions. Since the comprehensive score integrates reward and penalty factors, dynamic competition can be achieved in each production stage, eliminating the use of static priorities. This allows for a deeper understanding of the status of each production stage during power allocation and production scheduling, including real-time material inventory, wind power inventory, and equipment operating status. This enables optimal decision-making based on real-time application scenarios, improving the flexibility of power allocation and production scheduling.

[0071] When scheduling production, the status of material inventory is usually considered. Therefore, in this embodiment, a material production reward and penalty function is constructed. By constructing this function, the material capacity in each production stage is maintained at the target capacity, effectively avoiding material shortages or waste due to excess inventory. The reward and penalty function increases production efficiency when inventory is low and decreases efficiency when inventory is high, thereby achieving inventory balance. Specifically, the expression for the material production reward and penalty function is: ,in, Indicates the ideal material inventory capacity. This represents the high inventory penalty coefficient set when the material inventory capacity is higher than the ideal material inventory capacity. This represents the low inventory penalty coefficient set when the material inventory capacity is lower than the ideal material inventory capacity. This represents the material inventory capacity at time t. This indicates the upper limit of material inventory capacity.

[0072] for When the material inventory level exceeds the target inventory level, this setting can typically be set to a negative value (e.g., -0.2). This effectively reduces the efficiency and output of material production. The setting can usually be set to a positive value (e.g., 3), which can improve the efficiency and output of material production, and the lower the material inventory, the higher the reward value.

[0073] Taking into account the comprehensive score of the production process and the material reward and penalty function, wind power allocation and production scheduling are dynamically carried out. The higher the comprehensive score, the higher the priority. Therefore, wind power is allocated first to ensure that the wind power required for production is sufficient. In addition, production processes with high comprehensive scores are scheduled first to ensure that the production process can be carried out stably and continuously and will not be easily affected by external fluctuations.

[0074] In one alternative implementation, methanol production relies on hydrogen production, which is typically accomplished using an electrolyzer. The electrolyzer converts electrical energy into chemical energy through electrolysis, which is used to decompose water or other compounds to produce hydrogen. Dividing the electrolyzer into a dynamic cell and a static cell allows for a balance between wind power consumption and hydrogen production demand. The dynamic cell acts as a storage device to regulate wind power fluctuations, participating in wind power regulation, while the static cell operates at a constant power and does not participate in wind power regulation. This ensures that the static cell is not damaged by frequent power conversions.

[0075] When regulating the wind power of a dynamic trough, the health status parameters of the dynamic troughs participating in the wind power regulation can be obtained first. Then, the dynamic troughs are sorted according to their health status parameters, and the dynamic troughs with better health status are selected to participate in the wind power regulation. Furthermore, when the health status of a dynamic trough exceeds the maintenance threshold, the dynamic trough can be converted into a static trough so that it no longer participates in the wind power regulation, and a new spare trough can be added to participate in the wind power regulation.

[0076] Specifically, in this embodiment, the expression for the health status parameter is: ,in, This parameter represents the health status of the moving groove, expressed as a percentage. A higher value indicates a higher level of health for the moving groove. This represents the cumulative fatigue coefficient. This indicates the preset fatigue coefficient (e.g., set to 0.8). When the cumulative fatigue coefficient exceeds the preset fatigue coefficient, it indicates that the health condition of the dynamic trough is poor, and it can be excluded from wind power regulation and maintenance should be performed.

[0077] It should also be noted that the cumulative fatigue coefficient mentioned above is calculated based on the damage degree of a single power change, and the specific calculation expression for the damage degree of a single power change is as follows: ; in, This represents the loss degree of the moving trough i in the k-th wind power conversion, i.e., the damage degree of a single power conversion; This represents the change in wind power during the kth iteration (unit: kW). Indicates the rated power of the moving slot; This indicates the rated life cycle count, which is the typical number of cycles the moving tank can withstand within the rated power variation range. For example, This indicates that the moving slot can theoretically perform 10,000 start-stop cycles within the rated power variation range.

[0078] Furthermore, after calculating the damage degree of a single power conversion in the moving groove, the cumulative fatigue coefficient of the moving groove can be calculated. Specifically, the expression for calculating the cumulative fatigue coefficient of the moving groove is as follows: ; in, This represents the change in wind power output during the k-th iteration; Indicates the rated power of the moving slot; Indicates the number of rated life cycles.

[0079] Using the above calculation formula, the damage degree of a single power change in the dynamic trough is first calculated. Then, the cumulative fatigue coefficient of the dynamic trough is calculated based on the damage degree of the single power change. Finally, the health status parameters can be calculated based on the cumulative fatigue coefficient of the dynamic trough. Subsequently, dynamic troughs participating in wind power regulation can be selected based on the health status parameters. Simultaneously, hysteresis control is introduced during wind power regulation of the dynamic troughs to prevent frequent start-stop operations (for example, when the wind power command change is <5%, the dynamic trough remains in its original state and does not participate in wind power regulation). This allows for advance regulation of wind power changes while ensuring the health status of the dynamic troughs.

[0080] In one alternative implementation, since wind power is used in the methanol production process, it is also necessary to monitor whether the wind power output exceeds the upper limit. Specifically, when the methanol production efficiency is greater than the target production efficiency, the wind power allocation needs to be reduced; when the methanol production efficiency is less than the target production efficiency, the wind power allocation can be increased.

[0081] In this embodiment of the application, the formula for calculating methanol production efficiency is as follows: ,in, Indicates the time interval The quality of methanol produced domestically. In time interval The total electrical power consumed by the internal methanol production unit Indicates a time interval.

[0082] The above methods can maintain good production efficiency in methanol production and improve the utilization efficiency of green wind power.

[0083] When allocating wind power, due to fluctuations in wind power generation, appropriate limiting measures must be implemented based on the wind power output and actual production conditions. When wind power exceeds production load demand, excess wind power is prioritized for charging energy storage devices, with the charging power controlled to not exceed the maximum capacity of the energy storage devices. When wind power is insufficient, the gap is supplemented from the energy storage devices according to demand. When releasing power from the energy storage devices, replenishment is based on the importance of each production stage, thereby ensuring stable production and achieving optimal energy utilization efficiency.

[0084] Furthermore, during the production process, a human-machine interface (HMI) can be set up to display the predicted and actual wind power curves, the dynamic liquid levels of each material storage tank, and parameters such as the operating status and compliance rate of the methanol production unit. The HMI can also be set to display abnormal events such as exceeding limits, equipment failures, and communication interruptions, and supports audible and visual alarm linkage, enabling relevant personnel to monitor the entire production process in real time.

[0085] Furthermore, based on the same technical concept, embodiments of this application provide a control device for hydrogen production to methanol production, which is used to implement the above-described method flow of embodiments of this application. See also... Figure 3 As shown, the device includes: a prediction module 301, a processing module 302, and a control module 303, wherein, The prediction module 301 is used to acquire weather forecast data within a preset time period, and to perform wind power generation prediction based on the weather forecast data to obtain wind power prediction results. The processing module 302 is used to construct the reward function and penalty function corresponding to each production stage, and obtain the comprehensive score corresponding to each production stage based on the reward function and penalty function; wherein, the reward function is used to instruct each production stage to increase production output, the penalty function is used to instruct each production stage to reduce production output or suspend production, and the comprehensive score is used to instruct the wind power allocation ratio of each production stage. The control module 303 is used to allocate wind power and schedule production for each production stage based on wind power forecast results and comprehensive scores corresponding to each production stage.

[0086] In one optional implementation, the reward function consists of a material sufficiency reward function, an excess reward function, and a production continuity reward function, while the penalty function consists of a material shortage penalty function, a start-stop penalty function, and a power fluctuation penalty function; wherein, The material sufficiency reward function is used to indicate the sufficiency of materials required at each production stage; The excess reward function is used to instruct each production stage to increase production output when materials are sufficient. The production continuity reward function is used to indicate that if each production stage was producing at the previous moment, continuing production at the current moment will result in a reward; The material shortage penalty function is used to instruct each production stage to prohibit the allocation of wind power when there is a shortage of materials; The start / stop penalty function is used to indicate whether each production stage should start the equipment to produce; The power fluctuation penalty function is used to smooth the production load of each production stage.

[0087] In one alternative implementation, the expression for the material sufficiency reward function is: ,in, Indicates the rated power of the methanol production unit. Indicates the inventory of solid raw materials. This indicates the amount of solid raw materials consumed per unit of power. The expression for the excess reward function is: Where represents the material inventory capacity at time t. Indicates the upper limit of material inventory capacity. This represents the inventory of solid raw materials at time t. Indicates the upper limit of the capacity of solid raw materials. , These represent weighting coefficients, used to adjust the relative importance of the adequacy of hydrogen and solid feedstock inventories; The expression for the production continuity reward function is: ,in, Indicates a constant reward value; The expression for the material shortage penalty function is: Where M is a preset positive number, This represents the material inventory capacity at time t. This represents the inventory of solid raw materials at time t. The power of the methanol production unit at time t is represented. The expression for the start / stop penalty function is: ,in, This represents the preset penalty constant. This represents the power of the methanol manufacturing unit at time t. This represents the power of the methanol manufacturing unit at time t-1.

[0088] The expression for the power fluctuation penalty function is: ,in, This indicates the preset penalty coefficient. This represents the power of the methanol manufacturing unit at time t. This represents the power of the methanol manufacturing unit at time t-1.

[0089] In an optional implementation, the processing module 302 is further configured to construct a material production reward and penalty function, which is used to maintain the material inventory capacity in each production stage at the target capacity. The expression of the material production reward and penalty function is as follows: ,in, Indicates the ideal material inventory capacity. This represents the high inventory penalty coefficient set when the material inventory capacity is higher than the ideal material inventory capacity. This represents the low inventory penalty coefficient set when the material inventory capacity is lower than the ideal material inventory capacity. This represents the material inventory capacity at time t. This indicates the upper limit of material inventory capacity.

[0090] In an optional implementation, the control module 303 is further configured to divide the electrolyzer into a dynamic cell and a static cell during the hydrogen production process. When the wind power fluctuation exceeds a preset threshold, the dynamic cell is used to regulate the wind power. When the dynamic cell is used to regulate the wind power, the health status parameters of the dynamic cell are obtained, and the dynamic cell that can be used to regulate the wind power is determined based on the health status parameters. The expression for the health status parameters is: ,in, This represents the cumulative fatigue coefficient. The preset fatigue coefficient is indicated. The cumulative fatigue coefficient is calculated based on the damage degree of a single power change. The damage degree of a single power change characterizes the degree of damage to the electrolytic cell each time the power is adjusted.

[0091] In an optional implementation, the control module 303 is further configured to calculate the methanol production efficiency per unit time and per unit power consumption when allocating wind power. If the methanol production efficiency is greater than the target production efficiency, the wind power allocation is reduced; if the methanol production efficiency is less than the target production efficiency, the wind power allocation is increased. The expression for calculating the methanol production efficiency is as follows: ,in, Indicates the time interval The quality of methanol produced domestically. In time interval The total electrical power consumed by the internal methanol production unit Indicates a time interval.

[0092] Based on the same technical concept, embodiments of this application also provide an electronic device that can implement the controlled process flow for hydrogen production and methanol production provided in the above embodiments of this application. In one embodiment, the electronic device can be a server, a terminal device, or other electronic equipment. See also... Figure 4 As shown, the electronic device may include: At least one processor 401 and a memory 402 connected to at least one processor 401. In this embodiment, the specific connection medium between the processor 401 and the memory 402 is not limited. Figure 4 The example shown is the connection between processor 401 and memory 402 via bus 400. Bus 400 is... Figure 4 The connections between other components are indicated by thick lines and are for illustrative purposes only, not as limiting information. The 400 bus can be divided into address bus, data bus, control bus, etc., for ease of representation. Figure 4 The term is represented by a single thick line, but this does not imply that there is only one bus or one type of bus. Alternatively, processor 401 can also be called a controller; there is no restriction on the name.

[0093] In this embodiment, memory 402 stores instructions executable by at least one processor 501. By executing the instructions stored in memory 402, at least one processor 401 can perform the aforementioned method for controlling the production of hydrogen and methanol. Processor 401 can implement... Figure 3 The functions of each module in the device shown.

[0094] The processor 401 is the control center of the device. It can connect to various parts of the control device through various interfaces and lines. By running or executing instructions stored in memory 402 and calling data stored in memory 402, the processor can perform various functions and process data, thereby monitoring the device as a whole.

[0095] In one possible design, processor 401 may include one or more processing units. Processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into processor 401. In some embodiments, processor 401 and memory 402 may be implemented on the same chip; in some embodiments, they may also be implemented separately on separate chips.

[0096] Processor 401 can be a general-purpose processor, such as a CPU, digital signal processor, application-specific integrated circuit, field-programmable gate array or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the hydrogen-to-methanol control method disclosed in the embodiments of this application can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0097] Memory 402, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory 402 may include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic memory, magnetic disk, optical disk, etc. Memory 402 can be any other medium capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer, but is not limited thereto. In the embodiments of this application, memory 402 can also be a circuit or any other device capable of implementing storage functions for storing program instructions and / or data.

[0098] By designing and programming the processor 401, the code corresponding to the hydrogen-to-methanol production control method described in the foregoing embodiments can be embedded into the chip, enabling the chip to execute the code during operation. Figure 2The illustrated embodiment describes the steps of a method for controlling hydrogen production and methanol production. How to design and program the processor 401 is a technique well-known to those skilled in the art and will not be described further here.

[0099] Based on the same inventive concept, embodiments of this application also provide a storage medium storing computer instructions that, when executed on a computer, cause the computer to perform a controlled method for producing hydrogen and methanol as described above.

[0100] In some possible implementations, this application also provides a method for regulating hydrogen production to methanol production, which can also be implemented as a program product including program code. When the program product is run on an apparatus, the program code is used to cause the control device to perform the steps in a method for regulating hydrogen production to methanol production according to various exemplary embodiments of this application as described above.

[0101] It should be noted that although several units or sub-units of the device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units.

[0102] Furthermore, although the operations of the method of this application are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0103] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0104] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a server, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0105] Program code for performing the operations of this application can be written using any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0106] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0107] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for regulating hydrogen production to methanol production, characterized in that, The method comprises: acquiring weather forecast data in a preset time period, and performing wind power generation prediction according to the weather forecast data to obtain a wind power prediction result; constructing a reward function and a penalty function corresponding to each production link, and obtaining a comprehensive score corresponding to each production link based on the reward function and the penalty function; wherein the reward function is used to indicate that each production link increases production output, the penalty function is used to indicate that each production link reduces production output or suspends production, and the comprehensive score is used to indicate the wind power distribution ratio of each production link; based on the wind power prediction result and the comprehensive score corresponding to each production link, performing wind power distribution and production scheduling for each production link.

2. The method of claim 1, wherein, The reward function is composed of a material sufficiency reward function, an excess reward function and a production continuity reward function, and the penalty function is composed of a material shortage penalty function, a start-stop penalty function and a power fluctuation penalty function; wherein The material sufficiency reward function is used to indicate the sufficiency of the materials required by each production link; The excess reward function is used to indicate that each production link increases production output when the material is sufficient; The production continuity reward function is used to indicate that if the last time of each production link is producing, the current time will obtain a reward for continuing production; The material shortage penalty function is used to indicate that each production link is prohibited from obtaining wind power distribution when the material is insufficient; The start-stop penalty function is used to indicate whether the equipment of each production link is started for production; The power fluctuation penalty function is used to smooth the production load of each production link.

3. The method of claim 2, wherein, The expression of the material sufficiency reward function is: wherein, represents the rated power of the methanol manufacturing device, represents the solid raw material inventory, represents the solid raw material per unit power consumption; The expression of the excess reward function is: wherein, S(t) denotes the inventory capacity of the material at time t, denotes the upper limit of the inventory capacity of the material, denotes the inventory amount of the solid raw material at time t, denotes the upper limit of the inventory capacity of the solid raw material, , denote the weight coefficients, respectively, for adjusting the relative importance of the hydrogen and the solid raw material inventory adequacy; The expression of the production continuity reward function is: wherein, represents a constant reward value; The expression of the material shortage penalty function is: wherein M is a preset positive number, represents the inventory capacity of the material at time t, represents the inventory amount of the solid raw material at time t, represents the power of the methanol manufacturing device at time t; The expression of the start-stop penalty function is: wherein, represents a preset penalty constant, represents the power of the methanol manufacturing device at time t, represents the power of the methanol manufacturing device at time t-1; The expression of the power fluctuation penalty function is: wherein, represents a preset penalty coefficient, represents the power of the methanol manufacturing device at time t, represents the power of the methanol manufacturing device at time t-1.

4. The method of claim 1, wherein, The method further comprises constructing a material production reward-penalty function, which is used to maintain the material inventory capacity of each production link at a target capacity, and the expression of the material production reward-penalty function is: wherein, represents an ideal material inventory capacity, represents a high inventory penalty coefficient set when the material inventory capacity is higher than the ideal material inventory capacity, represents a low inventory penalty coefficient set when the material inventory capacity is lower than the ideal material inventory capacity, represents a material inventory capacity at time t, represents an upper limit of the material inventory capacity.

5. The method of claim 1, wherein, In the hydrogen production process, the electrolytic cell is divided into a dynamic cell and a static cell, and the dynamic cell is used to adjust the wind power when the wind power fluctuation exceeds a preset threshold. When the dynamic cell is used to adjust the wind power, the health state parameters of the dynamic cell are obtained, and the dynamic cell available for adjusting the wind power is determined according to the health state parameters. The expression of the health state parameters is: wherein, represents a cumulative fatigue coefficient, represents a preset fatigue coefficient, the cumulative fatigue coefficient is calculated according to a single power change damage degree, and the single power change damage degree represents the damage degree to the electrolytic cell each time the power adjustment is performed.

6. The method of claim 1, wherein, When performing wind power distribution, the methanol production efficiency under unit time and unit power consumption is calculated, if the methanol production efficiency is greater than the target production efficiency, the wind power distribution is reduced, if the methanol production efficiency is less than the target production efficiency, the wind power distribution is increased, and the calculation expression of the methanol production efficiency is: wherein, represents the mass of methanol produced during the time interval , represents the total electric power consumed by the methanol production plant during the time interval , represents the time interval.

7. A control device for hydrogen production and methanol production, characterized by, The device comprises: a prediction module, configured to acquire weather forecast data in a preset time period, and perform wind power generation prediction according to the weather forecast data to obtain a wind power prediction result; The processing module is configured to construct a reward function and a penalty function corresponding to each production link, and obtain a comprehensive score corresponding to each production link based on the reward function and the penalty function; the reward function is used to indicate that each production link increases production output, the penalty function is used to indicate that each production link reduces production output or suspends production, and the comprehensive score is used to indicate a wind power distribution ratio of each production link; The regulation and control module is configured to perform wind power distribution and production scheduling for each production link based on the wind power prediction result and the comprehensive score corresponding to each production link.

8. The apparatus of claim 7, wherein, The reward function is composed of a material sufficiency reward function, an excess reward function, and a production continuity reward function, and the penalty function is composed of a material shortage penalty function, a start-stop penalty function, and a power fluctuation penalty function; wherein The material sufficiency reward function is used to indicate the sufficiency of materials required by each production link; The excess reward function is used to indicate that each production link increases production output when materials are sufficient; The production continuity reward function is used to indicate that if each production link is producing at the previous time, continuing production at the current time will obtain a reward; The material shortage penalty function is used to indicate that each production link is prohibited from obtaining wind power distribution when materials are insufficient; The start-stop penalty function is used to indicate whether each production link starts a device to produce; The power fluctuation penalty function is used to smooth the production load of each production link.

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the method of any one of claims 1-6.

10. A computer-readable storage medium having stored thereon computer program instructions, wherein, The computer program instructions are executed by the processor to implement the method of any one of claims 1-6.

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