New energy hydrogen production integrated control method and device

Abstract

The invention provides a new energy hydrogen production integrated control method and device, and the method comprises the steps: combining a wind power prediction value and a methanol demand prediction value of a future prediction interval based on rolling updating operation data, and through a multi-target optimization model with the maximum hydrogen production amount, the minimum operation cost and the minimum wind curtailment amount as optimization targets, carrying out the optimization of the wind power prediction value and the methanol demand prediction value of the future prediction interval; determining and updating a scheduling instruction of a future prediction interval; the scheduling instruction comprises an electrolysis power instruction value; determining a first deviation value between the actual wind power and the electrolytic power instruction value, dynamically compensating the first deviation value in combination with a preset rule, and dynamically correcting the electrolytic power instruction value; when a second deviation value between the actual total electrolysis power and the corrected electrolysis power instruction value exceeds a preset fluctuation interval, target total electrolysis power is determined, and the target total electrolysis power is distributed to each electrolytic cell group of the electrolysis array by adopting an equal-hydrogen-yield micro-increasing rate distribution method; and each electrolytic cell group is controlled to operate at the distributed power. And real-time power rebalance and stable control of the hydrogen production process are realized.

Description

Technical Field

[0001] This disclosure relates to the field of new energy hydrogen production technology, specifically to an integrated control method and device for new energy hydrogen production. Background Technology

[0002] Extensive research has been conducted in the industry on control technologies for integrated hydrogen production systems, resulting in various technical solutions. The mainstream approach combines model prediction and digital twin technology to construct a multi-physics domain coupled model encompassing the electrolyzer, hydrogen storage tank, and fuel cell. This model is then combined with fuzzy PID (Proportional-Integral-Derivative Control) algorithms to optimize the electrolyzer current regulation accuracy. Some studies have incorporated reinforcement learning algorithms to optimize control parameters.

[0003] However, existing technical solutions have some problems: First, they are not adaptable enough to complex operating conditions, which leads to a decrease in system stability when the load fluctuates; second, they do not accurately characterize the key processes of electric-hydrogen scheduling, which leads to inaccurate electric-hydrogen scheduling; third, when faced with changes in grid load demand, there are delays in information transmission or conflicts in control commands between the control levels of various electric-hydrogen equipment, resulting in low equipment response efficiency. Summary of the Invention

[0004] This disclosure addresses the problems existing in the prior art by providing an integrated control method and device for new energy hydrogen production, which can partially or completely solve the problems existing in the above-mentioned prior art solutions, realize real-time power rebalancing and stable control of the hydrogen production process, and improve system stability, accuracy of electric hydrogen scheduling and equipment response efficiency.

[0005] To achieve the above objectives, the technical solution adopted in this disclosure is as follows: The first aspect of this disclosure provides an integrated control method for hydrogen production from new energy sources, comprising: based on rolling updated operating data from wind power, electric energy storage, hydrogen energy storage, hydrogen production, and methanol production, and combined with pre-determined wind power and methanol demand forecasts for a future forecast period, determining and updating dispatch instructions for the future forecast period through a multi-objective optimization model with the optimization objectives of maximizing hydrogen production, minimizing operating costs, and minimizing wind curtailment; wherein the dispatch instructions include an electrolysis power instruction value; and determining the actual wind power on the wind power side and the electrolysis power instruction value. A first deviation is dynamically compensated based on a preset calling sequence, and the electrolysis power command value is dynamically corrected. The preset calling sequence includes, in order: energy storage side, hydrogen production side, and alcohol production side. When the second deviation between the actual total electrolysis power of the hydrogen production side and the corrected electrolysis power command value exceeds a preset fluctuation range, the target total electrolysis power of the hydrogen production side is determined, and the target total electrolysis power is allocated to each electrolyzer group of the electrolysis array on the hydrogen production side using an equal hydrogen production incremental rate allocation method. Each electrolyzer group of the electrolysis array is then controlled to operate at the allocated power.

[0006] In one possible implementation, when the first deviation is positive, dynamic compensation is performed on the first deviation in conjunction with a preset calling sequence, including: if the energy storage side has not reached its upper limit, the energy storage side is prioritized to compensate for the first deviation; if the energy storage side has reached its upper limit, or if the first deviation is still remaining after the energy storage side has compensated for the first deviation by charging at rated power, and if the hydrogen energy storage side has not reached its upper limit, the hydrogen production side is called to compensate for the remaining first deviation; if the energy storage side has reached its upper limit, or if the first deviation is still remaining after the energy storage side has compensated for the first deviation by charging at rated power, and if the hydrogen energy storage side has reached its upper limit, or if the hydrogen production side has still remaining remaining after operating at rated power to compensate for the remaining first deviation: if the alcohol production side purchases electricity from the grid, the alcohol production side is called to use surplus wind power instead of grid power to compensate for the remaining first deviation; if the alcohol production side does not purchase electricity from the grid, or if the first deviation is still remaining after the alcohol production side uses surplus wind power instead of grid power, wind power is forced to be curtailed.

[0007] In one possible implementation, when the first deviation is negative, dynamic compensation is performed on the first deviation in conjunction with a preset calling sequence, including: if the energy storage side has not reached its lower limit, the energy storage side is prioritized to compensate for the first deviation; if the energy storage side has reached its lower limit, or if the first deviation is still remaining after the energy storage side has compensated for the first deviation by discharging at its rated power, the hydrogen production side is called to perform residual compensation for the first deviation; if a hydrogen shortage occurs when the hydrogen production side is called to perform residual compensation for the first deviation, and the hydrogen storage side has reached its lower limit, or if the hydrogen storage side cannot replenish the hydrogen shortage even when releasing hydrogen at its rated rate, then the alcohol production side is called to perform residual compensation for the first deviation after compensation by the hydrogen production side.

[0008] In one possible implementation, dynamically correcting the electrolysis power command value includes: when the hydrogen production side participates in compensating for the first deviation, correcting the electrolysis power command value based on the amount of compensation for the first deviation by the hydrogen production side.

[0009] In one possible implementation, an equal hydrogen production incremental rate allocation method is used to allocate the target total electrolysis power to each electrolyzer group of the electrolysis array on the hydrogen production side. This includes: determining the total power constraint of the electrolysis array based on the target total electrolysis power; under the constraint including the total power constraint, determining the optimal hydrogen production incremental rate for each electrolyzer group of the electrolysis array using an electrolyzer hydrogen production model with the optimization objective of maximizing the total hydrogen production of the array, and determining the optimal allocated power for each electrolyzer group of the electrolysis array based on the optimal hydrogen production incremental rate for each electrolyzer group of the electrolysis array; wherein the sum of the optimal allocated power of all electrolyzer groups is equal to the target total electrolysis power.

[0010] In one possible implementation, the formula for calculating the optimal incremental rate of hydrogen content includes: In the formula, To achieve the optimal rate of slight increase in hydrogen content, The coefficient for the first-order term of hydrogen production from the electrolyzer is... The coefficient of the quadratic term for hydrogen production from the electrolyzer is... The coefficient of the cubic term for hydrogen production from the electrolyzer is... Let n be the target total electrolysis power, and n be the number of electrolytic cell groups.

[0011] In one possible implementation, the formula for calculating the optimal power allocation includes: In the formula, The optimal power allocation for the i-th electrolytic cell group is... The coefficient for the first-order term of hydrogen production from the electrolyzer is... The coefficient of the quadratic term for hydrogen production from the electrolyzer is... The coefficient of the cubic term for hydrogen production from the electrolyzer is... Let n be the target total electrolysis power, and n be the number of electrolytic cell groups.

[0012] In one possible implementation, when the actual total electrolysis power of the electrolysis array reaches the target total electrolysis power, the hydrogen increment rate of each electrolysis cell group in the electrolysis array is equal.

[0013] In one possible implementation, the constraints of the multi-objective optimization model include equipment operation constraints, catalyst activity constraints for methanol synthesis, and carbon dioxide supply stability constraints; equipment operation constraints include electrical energy storage constraints, electrolyzer constraints, methanol synthesis unit constraints, and energy balance constraints; wherein, electrical energy storage constraints include upper and lower limits of energy storage state constraints and upper and lower limits of charge and discharge power constraints; electrolyzer constraints include hydrogen production power constraints of the electrolyzer group, hydrogen production power constraints of the electrolyzer workshop, upper and lower limits of hydrogen production power constraints of alkaline electrolyzers, upper and lower limits of hydrogen production power constraints of proton exchange membrane electrolyzers, and constraints on the number of electrolyzer start-ups and shutdowns; methanol synthesis unit constraints include upper and lower limits of methanol production and hydrogen-to-carbon ratio constraints; energy balance constraints include electrical balance constraints, hydrogen balance constraints, and methanol synthesis balance constraints.

[0014] A second aspect of this disclosure provides an integrated control device for new energy hydrogen production, comprising: an optimization scheduling layer, including a centralized monitoring module, a power prediction module, and a rolling optimization module, used to determine and update scheduling instructions for the future prediction period based on rolling updated operating data from the wind power side, the electric energy storage side, the hydrogen energy storage side, the hydrogen production side, and the methanol production side, combined with pre-determined wind power prediction values ​​and methanol demand prediction values ​​for the future prediction period, through a multi-objective optimization model with the optimization objectives of maximizing hydrogen production, minimizing operating costs, and minimizing wind curtailment; wherein the scheduling instructions include electrolysis power instruction values; and a coordination control layer, including a wind power deviation power allocation module and an electrolysis array. The internal allocation module is used to determine the first deviation between the actual wind power on the wind power side and the electrolysis power command value, dynamically compensate for the first deviation in combination with a preset calling sequence, and dynamically correct the electrolysis power command value. The preset calling sequence includes, in order: energy storage side, hydrogen production side, and alcohol production side. When the second deviation between the actual total electrolysis power on the hydrogen production side and the corrected electrolysis power command value exceeds a preset fluctuation range, the target total electrolysis power on the hydrogen production side is determined, and the target total electrolysis power is allocated to each electrolyzer group of the electrolysis array on the hydrogen production side using an equal hydrogen production rate increment allocation method. The module also controls each electrolyzer group of the electrolysis array to operate at the allocated power. This disclosure also provides an electronic device, comprising: a memory for storing at least one instruction; and a processor for calling the instruction stored in the memory to execute the integrated control method for new energy hydrogen production in the first aspect and any possible implementation thereof.

[0015] This disclosure also provides a computer-readable storage medium storing at least one executable instruction, which is loaded and executed by a processor to implement the integrated control method for new energy hydrogen production in the first aspect and any possible implementation thereof.

[0016] This disclosure also provides a computer program product, which includes computer program code. When the computer program code is run by a computer, it causes the computer to execute the integrated control method for new energy hydrogen production in the first aspect and any possible implementation thereof.

[0017] Compared with the prior art, this disclosure has the following beneficial effects: This disclosure dynamically generates scheduling instructions using rolling updates of real-time data and predicted values, ensuring that the instructions align with real-time operating conditions and future demand trends. Furthermore, using the electrolysis power meter instruction value in the scheduling instructions as a benchmark reference, it dynamically compensates for deviations between actual wind power and the benchmark reference value according to a preset call sequence, mitigating the impact of wind power fluctuations. When the deviation between the actual total electrolysis power and the benchmark reference value exceeds the limit, an equal hydrogen production rate-based allocation method is adopted to achieve precise allocation of the target total electrolysis power, ensuring that each electrolyzer group operates under optimal conditions. This maximizes the total hydrogen production of the array while maintaining stability on the hydrogen production side, avoiding system stability degradation caused by local load imbalances. Through closed-loop control of rolling optimization, dynamic compensation, precise allocation, and controlled operation, coordinated scheduling on all sides is achieved, improving the system's real-time response capability and operational stability under changes in source load demand. Attached Figure Description

[0018] Figure 1 This is a control architecture diagram of an integrated new energy hydrogen production system provided in an embodiment of this disclosure; Figure 2 This is a schematic flowchart of an integrated control method for hydrogen production from new energy sources provided in an embodiment of this disclosure; Figure 3 This is a flowchart illustrating a dynamic compensation and coordinated control strategy for wind turbine output deviation provided in an embodiment of this disclosure; Figure 4 This is a structural block diagram of an integrated control device for hydrogen production from new energy sources, provided in an embodiment of this disclosure. Detailed Implementation

[0019] The present disclosure will now be further described with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present disclosure and should not be construed as limiting the scope of protection of the present disclosure. It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application.

[0020] The acquisition, transmission, storage, use, and processing of data in this disclosed technical solution comply with relevant national laws and regulations. In the embodiments of this disclosure, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this disclosure, and do not imply that the applicant has already used or necessarily used such solutions.

[0021] All terms used in this disclosure have the same meaning as understood by one of ordinary skill in the art to which this disclosure pertains, unless otherwise specifically defined. It should also be understood that terms defined in general dictionaries should be interpreted as having meanings consistent with their meanings in the context of the relevant art, and not as idealized or highly formalized, unless expressly defined herein.

[0022] The integrated new energy hydrogen production system includes a wind power side, an electrical energy storage side, a hydrogen energy storage side, a hydrogen production side, and a methanol production side. To facilitate understanding of the improved integrated new energy hydrogen production control method in the embodiments of this disclosure, the following is combined with... Figure 1 First, the integrated control architecture for new energy hydrogen production in this disclosure will be described in general.

[0023] Figure 1 This is a control architecture diagram of an integrated new energy hydrogen production system provided in this embodiment. Figure 1As shown, the system is divided into an energy management layer, a coordination and control layer, and an equipment layer from top to bottom. The energy management layer includes an energy management system responsible for global energy scheduling and monitoring. The coordination and control layer includes a coordination controller and switches. The coordination controller communicates with lower-level subsystems through the switches to achieve centralized control. Fiber optic GOOSE communication is used to transmit control signals with high real-time requirements, while Ethernet 103, 104, and Modbus communication are used to transmit status monitoring and non-real-time commands. The equipment layer contains various functional units. The wind power side includes a wind turbine system with a rated power of up to 450MW, providing wind power input to the system. The energy storage side includes a BMS (Battery Management System), a PCS (Power Conversion System), and electrochemical energy storage with a capacity of up to 90MW / 90MWh, enabling the storage and release of electrical energy. The hydrogen production side is divided into two hydrogen production branches: an ALK (Alkaline) array and a PEM (Proton Exchange Membrane) array. The ALK array includes an ALK array controller, a hydrogen production power supply, and a DCS (Distributed Control System). The system comprises a distributed control system (DCS) and an alkaline electrolyzer, with a capacity of 52 x 1000 N / m³, producing hydrogen through alkaline electrolysis. The PEM array includes a PEM array controller, a hydrogen production power supply, a DCS, and a PEM electrolyzer, with capacities of 13 x 250 N / m³ and 1 x 500 N / m³, producing hydrogen through proton exchange membrane electrolysis. The hydrogen storage side includes a compressor, a hydrogen storage tank, and hydrogen purification equipment to compress, store, and purify hydrogen, and receives hydrogen produced from the hydrogen production side via a hydrogen connection. The alcohol production side includes an alcohol production controller, an alcohol production power supply, and alcohol production equipment, using hydrogen to produce alcohol products. Power transmission is achieved through electrical connections between the various equipment units, and hydrogen delivery is achieved through hydrogen connections. Information exchange with the coordinating controller and energy management system is completed through fiber optic GOOSE communication, Ethernet 103, 104, and Modbus communication, forming a complete integrated control architecture for new energy hydrogen production.

[0024] Figure 2 This is a schematic flowchart of an integrated control method for hydrogen production from new energy sources provided in an embodiment of this disclosure. Figure 2 As shown, the integrated control method for hydrogen production from new energy sources includes the following steps S11 to S14.

[0025] Step S11: Based on the rolling updated operating data of the wind power side, electric energy storage side, hydrogen energy storage side, hydrogen production side and methanol production side, combined with the wind power forecast value and methanol demand forecast value of the predetermined future forecast interval, the scheduling instructions for the future forecast interval are determined and updated through a multi-objective optimization model with the optimization objectives of maximizing hydrogen production, minimizing operating costs and minimizing wind curtailment.

[0026] It should be noted that, in this embodiment, the wind power side refers to the power generation unit including a wind turbine system and a supporting monitoring unit, and its operating data may include actual output power, wind turbine operating status, adjustable capacity, etc.; the electrical energy storage side refers to the electrical energy storage and release unit including a battery management system, a power conversion system, and an electrochemical energy storage device, and its operating data may include state of charge, charge and discharge power, charge and discharge efficiency, remaining capacity, etc.; the hydrogen energy storage side refers to the hydrogen storage and processing unit including a compressor, a hydrogen storage tank, and a hydrogen purification equipment, and its operating data may include hydrogen storage pressure, hydrogen storage temperature, hydrogen purity, hydrogen storage quantity, leakage rate, etc.; the hydrogen production side refers to the hydrogen production unit including an alkaline electrolyzer array, a proton exchange membrane electrolyzer array, and supporting power supply and controller, and its operating data may include real-time electrolysis current, cell voltage, electrolysis efficiency, cooling water temperature, etc. of the alkaline electrolyzer and the proton exchange membrane electrolyzer; the methanol production side refers to the methanol preparation unit including a methanol production controller, a methanol production power supply, and methanol production equipment, and its operating data may include the inlet hydrogen-to-carbon ratio, reaction temperature, reaction pressure, methanol production, etc. of the methanol synthesis reactor.

[0027] Rolling update operational data refers to the real-time operational parameters of each unit that are continuously collected and refreshed at preset time intervals, such as 5 minutes or 15 minutes. During the rolling optimization process, the data is updated once in real time and a safety threshold check is triggered.

[0028] The future forecast range refers to a pre-set time range used for scheduling optimization, such as 1 hour or 4 hours; the wind power forecast value refers to the expected output power of the wind power side within this range, obtained by combining meteorological data with historical operating data and a forecast model; the methanol demand forecast value refers to the expected methanol demand on the methanol production side within this range, obtained based on market demand, production plans, etc.

[0029] In some embodiments, for wind power forecasting: a combined "short-term + ultra-short-term" mode can be adopted. Short-term forecasts, such as for the next 4-6 hours, are based on numerical weather predictions and historical power output data, outputting power output forecasts at 15-minute intervals, with an error rate set to ≤12%. Ultra-short-term forecasts, such as for the next 1 hour, are combined with real-time wind speed feedback and updated every 15 minutes, with an error rate controlled within 8%. For methanol demand forecasting: based on historical order data and real-time order change information from downstream users, such as those in the chemical and transportation sectors, a fusion model can be used to output demand forecasts at 15-minute intervals for the next 4-6 hours. A demand fluctuation threshold can be set, such as ±10%, triggering an emergency dispatch response when the threshold is exceeded.

[0030] A multi-objective optimization model refers to a mathematical model that simultaneously aims to maximize hydrogen production, minimize operating costs, and minimize wind curtailment. It can balance the conflicts between multiple objectives through weight allocation and output scheduling instructions for each unit. The scheduling instructions include electrolysis power instruction values, which refer to the target electrolysis power set for the hydrogen production side and are used to guide the power allocation of the hydrogen production units.

[0031] In one possible implementation, the constraints of the multi-objective optimization model include equipment operation constraints, catalyst activity constraints for methanol synthesis, and carbon dioxide supply stability constraints. Equipment operation constraints include electrical energy storage constraints, electrolyzer constraints, methanol synthesis unit constraints, and energy balance constraints. Specifically, electrical energy storage constraints include upper and lower limits for energy storage state and upper and lower limits for charge / discharge power; electrolyzer constraints include hydrogen production power constraints for the electrolyzer group, the electrolyzer workshop, the upper and lower limits for hydrogen production power of alkaline electrolyzers, the upper and lower limits for hydrogen production power of proton exchange membrane electrolyzers, and constraints on the number of electrolyzer start-ups and shutdowns; methanol synthesis unit constraints include upper and lower limits for methanol production and hydrogen-to-carbon ratio constraints; and energy balance constraints include electrical balance constraints, hydrogen balance constraints, and methanol synthesis balance constraints.

[0032] For example, in one specific embodiment, the upper and lower limits of the energy storage state constraints include: The upper and lower limits of charge and discharge power constraints include In the formula, Let t be the energy storage state of electrical energy storage at time t. Let be the charging and discharging power of the electrical energy storage at time t. These are the upper and lower limits for electrical energy storage. These are the upper and lower limits of the charging and discharging power of the electric energy storage.

[0033] In one specific embodiment, the hydrogen production power constraint of the electrolyzer group includes: The hydrogen production capacity constraints of the electrolyzer workshop include: The upper and lower limits of hydrogen production power in alkaline electrolyzers include: The upper and lower limits of hydrogen production power in proton exchange membrane electrolyzers include: The number of start-ups and shutdowns of the electrolytic cell is constrained to ≤a times / hour to avoid losses from frequent start-ups and shutdowns. In the formula, This represents the hydrogen production capacity of a single cell in the electrolyzer. Hydrogen production capacity of the electrolyzer group, Let t be the hydrogen production power of the alkaline electrolyzer and the PEM electrolyzer at time t. These are the upper and lower limits of hydrogen production capacity for the electrolyzer group. These are the upper and lower limits of hydrogen production capacity in the electrolyzer workshop. and These represent the upper and lower limits of hydrogen production power for alkaline electrolyzers and PEM electrolyzers, respectively.

[0034] In one specific embodiment, the upper and lower limits of alcohol production constraints include: Hydrogen-to-carbon ratio constraints include: In the formula, Let t be the amount of alcohol produced. These represent the upper and lower limits of alcohol production.

[0035] In one specific embodiment, the electrical balance constraint includes: Hydrogen balance constraints include: ; ; The equilibrium constraints for methanol synthesis include: In the formula, Let t be the wind power output. Let t be the power output of the power grid. Let t be the charge / discharge power of the electrochemical energy storage. Let be the total hydrogen production mass at time t. Let be the mass of hydrogen entering the hydrogen purification equipment at time t. Let be the mass of hydrogen gas added to the hydrogen storage tank at time t. Let be the mass of hydrogen gas released from the hydrogen storage tank at time t. This refers to the electrolysis efficiency of an alkaline electrolytic cell. The electrolysis efficiency of the PEM electrolyzer. This refers to the lower heating value of hydrogen, which is the amount of heat released when one kilogram of hydrogen is completely burned. Let be the mass of hydrogen gas consumed in the synthesis of methanol at time t. This represents the methanol synthesis efficiency.

[0036] Furthermore, in one specific embodiment, the inlet temperature of the methanol synthesis tower is required to be ≤280℃ to avoid catalyst overheating and sintering, and the activity coefficient is required to be ≥0.85. It should be noted that the activity coefficient decreases with increasing temperature, and when it falls below 0.8, the unit must be shut down for regeneration.

[0037] In this embodiment, the rolling optimization scheduling is based on real-time data feedback and adopts a "dynamic rolling cycle" update optimization strategy to achieve dynamic and stable operation throughout the entire process. The dynamic rolling cycle can be adjustable to 15 minutes, 30 minutes, or 60 minutes, updating the scheduling plan for the next 4-6 hours in each cycle, while only executing the plan for the current time period.

[0038] For example, in one specific embodiment, the system updates the operating data of each side every 15 minutes, and the future prediction interval is set to 4 hours. Combining the wind power prediction value obtained from numerical weather forecast and the methanol demand prediction value provided by downstream chemical enterprises, the system calculates the electrolysis power command value every 15 minutes in the next 4 hours through a constructed multi-objective optimization model.

[0039] Step S12: Determine the first deviation between the actual wind power on the wind power side and the electrolysis power command value in the dispatch instruction, dynamically compensate the first deviation in combination with the preset dispatch sequence, and dynamically correct the electrolysis power command value.

[0040] It should be noted that in this embodiment, the first deviation refers to the difference between the actual wind power output and the electrolysis power command value. When the first deviation is positive, it indicates that the wind power is surplus; when the first deviation is negative, it indicates that the wind power is insufficient. Dynamic compensation refers to calling preset compensation resources to balance the power gap or absorb surplus power based on the sign and magnitude of the deviation. The preset calling order refers to the pre-set priority of compensation resources. In this embodiment, the priority is as follows: electric energy storage side, hydrogen production side, and alcohol production side. The priority is set based on response speed, adjustment cost, and system impact. The electric energy storage side has the fastest response speed and is prioritized for smoothing short-term fluctuations; the hydrogen production side is flexible in adjustment and is the second priority compensation unit; the alcohol production side affects production stability and is the last compensation unit. Dynamically correcting the electrolysis power command value refers to adjusting the initial electrolysis power command value based on the actual power balance result after compensation to ensure that the power demand of the hydrogen production side matches the actual available power. The purpose of this step is to maintain system power balance when wind power fluctuates, avoid wind curtailment or power shortage affecting hydrogen production stability, improve system anti-disturbance capability, and ensure continuous and stable operation of the hydrogen production side.

[0041] In one possible implementation, when the first deviation is positive, dynamic compensation is performed on the first deviation in conjunction with a preset calling sequence. Specifically, this may include: if the energy storage side has not reached its upper limit, prioritizing the use of the energy storage side to compensate for the first deviation; if the energy storage side has reached its upper limit, or if the first deviation remains after the energy storage side has compensated for the first deviation by charging at rated power, and if the hydrogen energy storage side has not reached its upper limit, then the hydrogen production side is called to compensate for the remaining first deviation; if the energy storage side has reached its upper limit, or if the first deviation remains after the energy storage side has compensated for the first deviation by charging at rated power, and if the hydrogen energy storage side has reached its upper limit, or if the hydrogen production side has compensated for the first deviation by operating at rated power, then if the methanol production side purchases electricity from the grid, then the methanol production side is called to use surplus wind power instead of grid power to compensate for the remaining first deviation; if the methanol production side does not purchase electricity from the grid, or if the first deviation remains after the methanol production side uses surplus wind power instead of grid power, then wind power is forced to be curtailed.

[0042] In another possible implementation, when the first deviation is negative, dynamic compensation is performed on the first deviation in combination with a preset calling sequence. Specifically, this may include: if the energy storage side has not reached its lower limit, prioritizing the energy storage side to compensate for the first deviation; if the energy storage side has reached its lower limit, or if the first deviation is still remaining after the energy storage side has compensated for the first deviation by discharging at its rated power, then calling the hydrogen production side to compensate for the remaining first deviation; if a hydrogen shortage occurs when the hydrogen production side is called for remaining compensation for the first deviation, and the hydrogen storage side has reached its lower limit, or if the hydrogen storage side cannot replenish the hydrogen shortage even when releasing hydrogen at its rated rate, then calling the alcohol production side to compensate for the remaining first deviation after compensation by the hydrogen production side.

[0043] In another possible implementation, dynamically correcting the electrolysis power command value may specifically include: when the hydrogen production side participates in compensating for the first deviation, correcting the electrolysis power command value based on the amount of compensation for the first deviation by the hydrogen production side.

[0044] For example, in a specific embodiment, when the actual wind power on the wind power side is 400MW and the electrolysis power command value is 350MW, the first deviation is +50MW, which is a positive deviation. The system first controls the energy storage side to charge at 20MW power according to the preset calling sequence. The remaining 30MW deviation is absorbed by increasing the electrolysis power by 25MW on the hydrogen production side and increasing the power consumption by 5MW on the alcohol production side, and the electrolysis power command value is dynamically corrected to 375MW.

[0045] The coordination control strategy of the embodiments of this disclosure will be described in general below.

[0046] When the system is operating in a normal state, the coordination controller follows the following... Figure 3The coordinated control strategy shown can quickly determine the operating status of the equipment and correct the electrolysis power command issued by the energy management system in order to dynamically compensate for the deviation of the fan output.

[0047] Specifically, such as Figure 3 As shown, when the wind power output exceeds the reference value (i.e., the wind turbine output error > 0), if the energy storage system has not reached its maximum capacity, the battery power is adjusted first to absorb the excess power. If the energy storage capacity has reached its maximum and cannot continue charging, or if the energy storage is charged at its rated power but still cannot fully absorb the excess power, and the hydrogen storage tank has not reached its maximum capacity, the electrolyzer power can be increased to convert the excess electrical energy into hydrogen and store it in the hydrogen storage tank. Since the PEM electrolyzer responds faster than the alkaline electrolyzer, the PEM electrolyzer power is increased first. If all PEM electrolyzers have reached their maximum power but still cannot fully consume the excess power, the alkaline electrolyzer power is then increased. If there is still residual power after adjusting the battery and electrolyzer power, and the alcohol production system obtains power from the main grid, the residual power is used to replace the main grid power supply. If there is still residual power after the main grid power supply is completely replaced by the residual power, wind power is forced to be curtailed, limiting the wind turbine output.

[0048] When wind power output is less than the reference value (i.e., wind turbine output error < 0), if the energy storage has not reached its lower limit, the battery power will be adjusted first to compensate for the wind power shortfall. If the battery power has reached its lower limit and cannot continue to discharge, or if the battery discharges at its rated power but still cannot compensate for the wind power shortfall, the electrolyzer power will be reduced. To ensure a stable hydrogen supply, while reducing the electrolyzer power, the hydrogen storage tank will release hydrogen to compensate for the hydrogen shortfall, ensuring sufficient raw materials for alcohol production. If the hydrogen storage tank has reached its lower limit and cannot continue to release hydrogen, or if the hydrogen storage tank releases hydrogen at its maximum rate but still cannot compensate for the hydrogen shortfall, the alcohol production will be forced to be reduced.

[0049] In addition, for abnormal operating conditions that may occur during system operation, such as electrolyzer failure or drastic fluctuations in carbon dioxide supply, an event-triggered emergency control strategy can be set up to ensure the stable operation of the system and a sufficient supply of raw materials for alcohol production under abnormal conditions.

[0050] For example, when an electrolyzer malfunctions and shuts down, the sudden reduction in electrolysis power can cause a power imbalance in the system, threatening its safe and stable operation. If the hydrogen storage system's capacity and hydrogen flow rate allow, the hydrogen flow rate can be adjusted to compensate for the hydrogen supply shortfall caused by the electrolyzer shutdown, ensuring the supply of raw materials for the methanol production system. At the same time, the power of the electric energy storage system can be quickly adjusted to mitigate the power imbalance. If the electric energy storage system reaches its limit and cannot continue charging due to capacity and power limitations, the power imbalance still cannot be mitigated. In this case, the remaining electrolyzers will share the power imbalance. If the power imbalance cannot be mitigated using either of these methods, wind power will be forced to be curtailed, reducing wind power output. If the remaining electrolyzers cannot fully meet the hydrogen production demand, methanol production will be forced to be reduced.

[0051] For example, when there are drastic fluctuations in carbon dioxide supply, hydrogen production is adjusted according to the priority order of hydrogen storage system, PEM electrolyzer, and alkaline electrolyzer to adapt to changes in carbon dioxide supply.

[0052] This step uses the electrolysis power command value generated by rolling optimization as a benchmark reference value, and integrates real-time information such as actual wind power output, electrolyzer operating status, carbon dioxide supply, and hydrogen storage level to dynamically compensate for power or energy deviations caused by wind and solar power fluctuations, equipment operation delays, and material supply fluctuations. Through a coordinated allocation strategy among multiple devices, the deviation is distributed to adjustable units, such as electrical energy storage, PEM or alkaline electrolyzer load, and hydrogen energy storage, according to preset rules, thereby achieving real-time power rebalancing and stable control of the hydrogen production process.

[0053] Step S13: When the second deviation between the actual total electrolysis power on the hydrogen production side and the corrected electrolysis power command value exceeds the preset fluctuation range, determine the target total electrolysis power on the hydrogen production side, and use the equal hydrogen production rate increment allocation method to allocate the target total electrolysis power to each electrolysis cell group of the electrolysis array on the hydrogen production side.

[0054] It should be noted that, in this embodiment, the second deviation refers to the difference between the actual total electrolysis power of all electrolyzer groups on the hydrogen production side and the corrected electrolysis power command value; the preset fluctuation range refers to a pre-set allowable power fluctuation range, such as ±2% or ±5%, used to determine whether the power on the hydrogen production side is in a stable operating state. The target total electrolysis power refers to the total electrolysis power that the hydrogen production side needs to achieve, determined according to the second deviation and system operating constraints; the equal hydrogen production incremental rate allocation method refers to a power allocation algorithm whose core idea is to make the hydrogen production incremental rate of each electrolyzer group equal, thereby maximizing hydrogen production or minimizing operating costs when the total electrolysis power is fixed. The electrolysis array refers to the collection of all electrolyzer groups included on the hydrogen production side, including alkaline electrolyzer arrays and proton exchange membrane electrolyzer arrays; each electrolyzer group refers to an independent operating unit composed of several electrolyzers connected in parallel. The purpose of this step is to achieve optimal power allocation when the power on the hydrogen production side deviates from the command, which can improve hydrogen production efficiency, reduce inter-unit operating losses, and ensure the coordinated and stable operation of each electrolyzer group.

[0055] For example, in one specific implementation, the corrected electrolysis power command value is 375MW, and the preset fluctuation range is ±3%, i.e., 363.75MW~386.25MW. When the actual total electrolysis power on the hydrogen production side is 350MW, the second deviation is -25MW, which exceeds the lower limit of the fluctuation range. The target total electrolysis power is determined to be 375MW. Then, the 375MW is allocated to the 52 electrolyzer groups of the alkaline electrolyzer array and the 1 electrolyzer group of the proton exchange membrane electrolyzer array through the equal hydrogen production increment rate allocation method. This ensures that the hydrogen production increment rate of each electrolyzer group is equal when the total electrolysis power reaches the target total electrolysis power, thereby achieving the optimal hydrogen production efficiency.

[0056] In one possible implementation, an equal hydrogen production incremental rate allocation method is used to allocate the target total electrolysis power to each electrolyzer group of the electrolysis array on the hydrogen production side. Specifically, this may include: determining the total power constraint of the electrolysis array based on the target total electrolysis power; under the constraint including the total power constraint, determining the optimal hydrogen production incremental rate for each electrolyzer group of the electrolysis array using an electrolyzer hydrogen production model with the optimization objective of maximizing the total hydrogen production of the array, and determining the optimal allocated power for each electrolyzer group of the electrolysis array based on the optimal hydrogen production incremental rate for each electrolyzer group of the electrolysis array; wherein the sum of the optimal allocated power of all electrolyzer groups is equal to the target total electrolysis power.

[0057] In one specific embodiment, the formula for calculating the optimal incremental rate of hydrogen content includes: In the formula, To achieve the optimal rate of slight increase in hydrogen content, The coefficient for the first-order term of hydrogen production from the electrolyzer is... The coefficient of the quadratic term for hydrogen production from the electrolyzer is... The coefficient of the cubic term for hydrogen production from the electrolyzer is... Let n be the target total electrolysis power, and n be the number of electrolytic cell groups.

[0058] In one specific embodiment, the formula for calculating the optimal power allocation includes: In the formula, The optimal power allocation for the i-th electrolytic cell group is... The coefficient for the first-order term of hydrogen production from the electrolyzer is... The coefficient of the quadratic term for hydrogen production from the electrolyzer is... The coefficient of the cubic term for hydrogen production from the electrolyzer is... Let n be the target total electrolysis power, and n be the number of electrolytic cell groups.

[0059] It should be noted that the criterion for equal hydrogen production increment rate includes: the core principle of optimal power allocation is that when the total array power is adjusted to the target value, the hydrogen production increment rate of all operating electrolyzer groups is equal, that is... , where n is the number of electrolyzer groups in the array. At this point, the overall hydrogen production of the array is at its maximum, or the energy consumption per unit of hydrogen production is at its minimum.

[0060] The following section details the derivation of the power allocation formula based on the equal hydrogen production incremental rate criterion. The specific steps are as follows: The first step is to construct a characteristic model of the electrolytic cell.

[0061] Ignoring individual equipment differences, the hydrogen production of a single electrolyzer group follows a non-linear relationship with input power, as electrolysis efficiency fluctuates with power. In actual operation, due to electrolyzer polarization effects, such as activation polarization, ohmic polarization, and concentration polarization, these effects increase non-linearly with power, causing the actual hydrogen production-power relationship to deviate from linearity. Specifically, the polarization effect is weak in the low-power range, and the curve is close to linear; in the medium-to-high power range, the polarization effect strengthens, and the curve's growth rate slows down, corresponding to the model's... The inhibitory effect, based on a general model fitted from experimental data, is as follows: ,in, The coefficient for the first-order term of hydrogen production from the electrolyzer is... The coefficient of the quadratic term for hydrogen production from the electrolyzer is... The coefficient of the cubic term for hydrogen production from the electrolyzer is... , The hydrogen production of the i-th electrolyzer group is... Let be the input power of the i-th electrolytic cell group.

[0062] The second step is to determine the optimization objective.

[0063] Under the total power constraint, maximize the total hydrogen production of the array, i.e.: In the formula, This represents the total hydrogen production.

[0064] The third step is to determine the constraints.

[0065] Total power constraint: , ,in, The adjusted total target power of the array. This represents the actual total electrolysis power. This is the electrolysis power adjustment value.

[0066] Single device capacity constraints: ,in, This is the minimum operating power for the electrolytic cell group, typically 20%-30% of the rated power. This is the rated power.

[0067] Step 4: Derive the optimal allocation using the Lagrange multiplier method.

[0068] To solve the "maximization under constraints" problem, the Lagrange multiplier is introduced. Construct the Lagrange function: .

[0069] 1) Find the partial derivative and set it to 0 (extremum condition); right Find the partial derivative, i.e., the condition that the optimal power of each electrolytic cell group must satisfy: Combined with the definition of the incremental rate of hydrogen content We can obtain: (for all) (Established).

[0070] This proves that a necessary condition for optimal power allocation is that the incremental rate of hydrogen production in all electrolyzers is equal and equal to the Lagrange multiplier. ,in The physical meaning is the marginal increment of the total hydrogen quantity of the array, that is, the increment of the total hydrogen production when the total power increases by 1kW.

[0071] 2) Derive the expression for the incremental rate of hydrogen production; Differentiating the hydrogen production model for a single electrolyzer group yields the specific form of the incremental rate of hydrogen production: ; Due to optimal allocation The optimal power for each electrolytic cell group can be determined: ; This is about Solving the quadratic equation in one variable, we get: ; Combining the physical meaning of electrolytic cell power, that is And in Within the range, find solutions that have positive roots and satisfy the capacity constraints: The negative root leads to Too small, does not meet actual operating requirements, so discard.

[0072] 3) Determine the optimal incremental rate of hydrogen content ; Will Substituting the expression into the total power constraint We can obtain: ; The above formula can be simplified to: .

[0073] 4) Final power allocation formula; Will Substitution The expression yields the optimal power allocation for each electrolytic cell group: .

[0074] In another possible implementation, a load balancing allocation method is used to distribute the target total electrolysis power to each electrolyzer group in the hydrogen production side of the electrolysis array. The core principle of load balancing allocation is a three-tiered dynamic allocation logic involving the electrolysis workshop, electrolyzer groups, and individual electrolyzers, with each level requiring load balancing. The overall electrolysis power adjustment command that needs to be adjusted is then sent. The specific steps for allocating the cells to the electrolytic cell group are as follows: Let the load rate of the k-th workshop and the j-th group be... ,but: ,in, Let J be the rated electrolytic power of the j-th group of electrolytic cells in the k-th workshop. This is the reference value for the electrolysis power of the j-th group of electrolytic cells in the k-th workshop.

[0075] The adjustment power to be allocated to the j-th group of electrolytic cells in the k-th workshop for: ;when When, prioritize increasing the electrolysis power of electrolytic cell groups with low load rates; when When necessary, the electrolysis power of electrolytic cell groups with high load rates should be reduced first.

[0076] It should be noted that an electrolytic cell group typically consists of N individual electrolytic cells connected in parallel. The electrolysis power is distributed evenly from the group to the individual cells, but must meet the upper and lower limits of the operating power: ,in, This refers to the electrolysis power of a single electrolytic cell. , These are the upper and lower limits of the electrolysis power of the electrolytic cell group.

[0077] The load balancing method ensures that the total load of all individual electrolytic cells meets the workshop-level total power and capacity requirements. By balancing the load, it reduces the power difference between different cells and avoids some equipment from aging faster due to long-term high load.

[0078] Step S14: Control each electrolytic cell group of the electrolytic array to operate at the allocated power.

[0079] It should be noted that, in this embodiment of the disclosure, the allocated power refers to the target operating power of each electrolyzer group obtained by the equal hydrogen production incremental rate allocation method. The purpose of this step is to implement the optimized power allocation command, ensure that the hydrogen production side operates stably according to the target total electrolysis power, and guarantee the power tracking accuracy of each electrolyzer group, thereby improving the controllability and stability of the hydrogen production process.

[0080] In one possible implementation, the system sends power commands to the controller of each electrolyzer group through a distributed control system (DCS), and the controller adjusts the output power of the hydrogen production power source in real time to track the commands; in another possible implementation, the system transmits real-time power commands through fiber optic GOOSE communication to ensure low latency and high reliability of command transmission.

[0081] Additionally, it should be noted that when the actual total electrolysis power of the electrolysis array reaches the target total electrolysis power, the hydrogen increment rate of each electrolysis cell group in the electrolysis array is equal.

[0082] The integrated control method for new energy hydrogen production provided in this embodiment generates electrolysis power command values ​​through rolling updates of operating data, ensuring the real-time nature of the electrolysis power command values. When there is a deviation between the actual wind power and the electrolysis power command values, i.e., when the wind turbine output deviation is caused by wind and solar power fluctuations, equipment operation delays, material supply fluctuations, etc., the deviation is dynamically compensated according to the priority order of calling the energy storage side, hydrogen production side, and alcohol production side, and the electrolysis power command values ​​are dynamically corrected at the same time. Among them, the energy storage side is given priority to dynamically compensate for the deviation, which can reduce the number of electrolysis power adjustments on the hydrogen production side and improve the stability of the hydrogen production side. Adjustment upper and lower limits are set. When the deviation between the actual total electrolysis power on the hydrogen production side and the last issued electrolysis power command value exceeds the limit, it indicates that the electrolysis power on the hydrogen production side needs to be allocated and adjusted. At this time, the power allocation method of equal hydrogen production rate increment is used to ensure that the allocation maximizes the total hydrogen production of the electrolysis array.

[0083] Figure 4 This is a structural block diagram of an integrated control device for hydrogen production from new energy sources, provided in an embodiment of this disclosure. Figure 4 As shown, the integrated control device for hydrogen production from new energy sources includes an optimization scheduling layer 110 and a coordination control layer 120. The optimization scheduling layer 110 includes a centralized monitoring module 111, a power prediction module 112, and a rolling optimization module 113. The coordination control layer 120 includes a wind power deviation power allocation module 121 and an internal allocation module 122 for the electrolysis array.

[0084] In some embodiments, the centralized monitoring module 111 is used to collect operating data from the wind power side, the electric energy storage side, the hydrogen energy storage side, the hydrogen production side, and the methanol production side; the power prediction module 112 is used to determine the predicted wind power and methanol demand values ​​for the future prediction period; the rolling optimization module 113 is used to determine and update the scheduling instructions for the future prediction period based on the rolling updated operating data from the wind power side, the electric energy storage side, the hydrogen energy storage side, the hydrogen production side, and the methanol production side, combined with the pre-determined predicted wind power and methanol demand values ​​for the future prediction period, through a multi-objective optimization model with the optimization objectives of maximizing hydrogen production, minimizing operating costs, and minimizing wind curtailment; wherein, the scheduling instructions include electrolysis power instruction values.

[0085] In some embodiments, the wind power deviation allocation module 121 is used to determine the first deviation between the actual wind power on the wind power side and the electrolysis power command value, dynamically compensate the first deviation in combination with a preset calling sequence, and dynamically correct the electrolysis power command value; wherein, the preset calling sequence includes, in sequence: energy storage side, hydrogen production side, and alcohol production side; the electrolysis array internal allocation module 122 is used to determine the target total electrolysis power on the hydrogen production side when the second deviation between the actual total electrolysis power on the hydrogen production side and the corrected electrolysis power command value exceeds a preset fluctuation range, and allocate the target total electrolysis power to each electrolysis cell group of the electrolysis array on the hydrogen production side using an equal hydrogen production rate incremental allocation method; and control each electrolysis cell group of the electrolysis array to operate at the allocated power.

[0086] It should be noted that the optimized scheduling layer mainly includes an energy management platform, i.e., an energy management system, which has application functions such as data acquisition and monitoring, wind power forecasting, methanol demand forecasting, hydrogen production, and methanol production scheduling plans, realizing comprehensive analysis of system operation status, energy allocation, and economic scheduling. The optimized scheduling layer of this embodiment mainly focuses on maximizing methanol production, maximizing wind energy utilization efficiency, minimizing operating costs, and optimizing the matching of hydrogen and methanol production capacity as its core objectives. It dynamically adjusts the load allocation of electrolytic hydrogen production, electric energy storage, and methanol synthesis units through optimization algorithms to ensure that the overall system operates in an economically optimal state.

[0087] Additionally, it should be noted that the coordination control layer mainly includes a coordination control device, namely a coordination controller. This controller collects real-time information from wind power units, hydrogen production loads, methanol synthesis units, energy storage systems, and grid-connected lines via a high-speed communication network. It uses the electrolysis power command value generated by the optimization dispatch layer as a reference value for deviation power control. When significant disturbances occur in the system, such as a sudden drop in wind power output, grid failures, or abnormal disconnection of hydrogen production or methanol synthesis equipment, the system coordinates and controls the power of wind turbines, energy storage converters, electrolyzers, hydrogen storage capacity, the operating status of methanol synthesis equipment, and protection devices based on the GOOSE fast communication mechanism. By rapidly adjusting power allocation or shedding loads, it achieves a balance between hydrogen and methanol production capacity.

[0088] The integrated hydrogen production control device provided in this disclosure includes an optimization scheduling layer and a coordination control layer. It can perform layered regulation of the hydrogen production equipment in the face of complex operating conditions, improving system stability. For the optimization scheduling layer, an energy optimization management method is proposed, comprising three levels: centralized monitoring, power prediction, and rolling optimization. The optimization objectives are to maximize hydrogen production, minimize operating costs such as electrolyzer start-up and shutdown, and minimize wind curtailment, guiding efficient coordination between heterogeneous energy flows in the hydrogen production process. For the coordination control layer, a wind power deviation power allocation strategy is proposed. When faced with wind and solar power output deviations, it allocates power to adjustable equipment such as electric energy storage, PEM or alkaline electrolyzers, and hydrogen energy storage in real time based on the system's normal operating response characteristics and abnormal operating event triggering rules, achieving real-time power rebalancing and stable control of the hydrogen production process. Furthermore, an equal hydrogen production incremental rate allocation strategy is proposed, which can allocate power to ensure that the total hydrogen production of the array reaches the theoretical maximum value under the same total electrolysis power.

[0089] For specific details and benefits of the integrated control device for new energy hydrogen production provided in the embodiments of this disclosure, please refer to the above description of the integrated control method for new energy hydrogen production, which will not be repeated here.

[0090] This disclosure also provides an electronic device, comprising: a memory for storing at least one instruction; and a processor for calling the instruction stored in the memory to execute the integrated control method for new energy hydrogen production in any of the above embodiments.

[0091] This disclosure also provides a computer-readable storage medium storing at least one executable instruction, which is loaded and executed by a processor to implement the integrated control method for new energy hydrogen production in any of the above embodiments.

[0092] This disclosure also provides a computer program product, which includes computer program code. When the computer program code is run by a computer, it causes the computer to execute the integrated control method for new energy hydrogen production in any of the above embodiments.

[0093] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure 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.

[0094] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. 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 machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0095] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0096] 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.

[0097] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0098] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0099] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0100] It should be noted that the terms "first," "second," and similar terms used in this disclosure do not indicate any order, quantity, or importance, but are merely used to distinguish different parts. Terms such as "including" or "contains" mean that the element preceding the word covers the element listed after the word, and do not exclude the possibility of covering other elements as well.

[0101] Although operations are described in a specific order in the accompanying drawings in this disclosure, it should not be construed as requiring these operations to be performed in the specific order or serial order shown, or requiring all of the shown operations to obtain the desired result. In certain environments, multitasking and parallel processing may be advantageous.

[0102] Finally, it should be noted that the above content is only used to illustrate the technical solution of this disclosure, and is not intended to limit the scope of protection of this disclosure. Simple modifications or equivalent substitutions made by those skilled in the art to the technical solution of this disclosure do not depart from the substance and scope of the technical solution of this disclosure.

Claims

1. An integrated control method for hydrogen production from new energy sources, characterized in that, include: Based on the rolling updated operational data from the wind power side, electric energy storage side, hydrogen energy storage side, hydrogen production side, and methanol production side, combined with the wind power power forecast and methanol demand forecast for the predetermined future forecast period, a multi-objective optimization model with the optimization objectives of maximizing hydrogen production, minimizing operating costs, and minimizing wind curtailment is used to determine and update the scheduling instructions for the future forecast period; wherein, the scheduling instructions include electrolysis power instruction values; The first deviation between the actual wind power on the wind power side and the electrolysis power command value is determined, and the first deviation is dynamically compensated in combination with a preset calling sequence, and the electrolysis power command value is dynamically corrected; wherein, the preset calling sequence includes the following in sequence: the energy storage side, the hydrogen production side, and the alcohol production side; When the second deviation between the actual total electrolysis power on the hydrogen production side and the corrected electrolysis power command value exceeds a preset fluctuation range, the target total electrolysis power on the hydrogen production side is determined, and the target total electrolysis power is allocated to each electrolyzer group of the electrolysis array on the hydrogen production side using an equal hydrogen production incremental rate allocation method; and Each group of electrolytic cells in the electrolytic array is controlled to operate at the allocated power.

2. The integrated control method for new energy hydrogen production according to claim 1, characterized in that, When the first deviation is positive, the step of dynamically compensating for the first deviation in conjunction with a preset calling order includes: If the energy storage side does not reach its upper limit, the energy storage side will be used first to compensate for the first deviation. If the first deviation remains after the energy storage side has reached its limit or after the energy storage side has compensated for the first deviation by charging at rated power, and if the hydrogen energy storage side has not reached its limit, then the hydrogen production side is invoked to compensate for the remaining first deviation. If the first deviation remains after the energy storage side has reached its limit or after the energy storage side has compensated for the first deviation by charging at rated power, and if the hydrogen energy storage side has reached its limit or after the hydrogen production side has compensated for the first deviation by operating at rated power, then if the alcohol production side purchases electricity from the grid, then the alcohol production side uses surplus wind power instead of grid power to compensate for the remaining first deviation; if the alcohol production side does not purchase electricity from the grid, or if the first deviation remains after the alcohol production side uses surplus wind power instead of grid power, then wind power is forced to be curtailed.

3. The integrated control method for new energy hydrogen production according to claim 1, characterized in that, When the first deviation is negative, the step of dynamically compensating for the first deviation in conjunction with a preset calling order includes: If the energy storage side does not reach the lower limit, the energy storage side will be used first to compensate for the first deviation. If the first deviation amount is still remaining after the energy storage side has reached its lower limit or after the energy storage side has compensated for the first deviation amount by discharging at rated power, the hydrogen production side is invoked to compensate for the remaining first deviation amount. If a hydrogen shortage occurs and the hydrogen storage side has reached its lower limit, or the hydrogen storage side is unable to replenish the hydrogen shortage even when releasing hydrogen at the rated rate, then the alcohol production side is invoked to perform residual compensation on the first deviation amount after compensation by the hydrogen production side.

4. The integrated control method for new energy hydrogen production according to claim 2 or 3, characterized in that, The dynamic correction of the electrolysis power command value includes: When the hydrogen production side participates in compensating for the first deviation, the electrolysis power command value is corrected based on the compensation amount of the hydrogen production side for the first deviation.

5. The integrated control method for new energy hydrogen production according to any one of claims 1-3, characterized in that, The method of allocating the target total electrolysis power to each electrolyzer group of the electrolysis array on the hydrogen production side using the equal hydrogen production rate incremental allocation method includes: Based on the target total electrolysis power, the total power constraint of the electrolysis array is determined; Under the constraints including the total power constraint, the optimal hydrogen increment rate of each electrolyzer group in the electrolysis array is determined by an electrolyzer hydrogen production model with the optimization objective of maximizing the total hydrogen production of the array. Based on the optimal hydrogen increment rate of each electrolyzer group in the electrolysis array, the optimal power allocation of each electrolyzer group in the electrolysis array is determined; wherein, the sum of the optimal power allocation of all electrolyzer groups is equal to the target total electrolysis power.

6. The integrated control method for new energy hydrogen production according to claim 5, characterized in that, The formula for calculating the optimal incremental rate of hydrogen content includes: ， In the formula, To achieve the optimal rate of slight increase in hydrogen content, The coefficient for the first-order term of hydrogen production from the electrolyzer is... The coefficient of the quadratic term for hydrogen production in the electrolyzer is... The coefficient of the cubic term for hydrogen production from the electrolyzer is... Let n be the target total electrolysis power, and n be the number of electrolytic cell groups.

7. The integrated control method for new energy hydrogen production according to claim 5, characterized in that, The formula for calculating the optimal power allocation includes: In the formula, The optimal power allocation for the i-th electrolytic cell group is... The coefficient for the first-order term of hydrogen production from the electrolyzer is... The coefficient of the quadratic term for hydrogen production in the electrolyzer is... The coefficient of the cubic term for hydrogen production from the electrolyzer is... Let n be the target total electrolysis power, and n be the number of electrolytic cell groups.

8. The integrated control method for new energy hydrogen production according to claim 1, characterized in that, When the actual total electrolysis power of the electrolysis array reaches the target total electrolysis power, the hydrogen increment rate of each electrolysis cell group in the electrolysis array is equal.

9. The integrated control method for new energy hydrogen production according to claim 1, characterized in that, The constraints of the multi-objective optimization model include equipment operation constraints, catalyst activity constraints for methanol synthesis, and carbon dioxide supply stability constraints. The equipment operation constraints include electrical energy storage constraints, electrolyzer constraints, methanol synthesis unit constraints, and energy balance constraints. Specifically, the electrical energy storage constraints include upper and lower limits for energy storage state and upper and lower limits for charge / discharge power. The electrolyzer constraints include hydrogen production power constraints for the electrolyzer group, hydrogen production power constraints for the electrolyzer workshop, upper and lower limits for hydrogen production power in alkaline electrolyzers, upper and lower limits for hydrogen production power in proton exchange membrane electrolyzers, and constraints on the number of electrolyzer start-ups and shutdowns. The methanol synthesis unit constraints include upper and lower limits for methanol production and hydrogen-to-carbon ratio constraints. The energy balance constraints include electrical balance constraints, hydrogen balance constraints, and methanol synthesis balance constraints.

10. An integrated control device for hydrogen production from new energy sources, characterized in that, include: The optimized scheduling layer includes a centralized monitoring module, a power prediction module, and a rolling optimization module. Based on rolling updates of operational data from the wind power side, electric energy storage side, hydrogen energy storage side, hydrogen production side, and methanol production side, and combined with pre-determined wind power and methanol demand forecasts for the future forecast period, a multi-objective optimization model is used to determine and update scheduling instructions for the future forecast period, with the optimization objectives of maximizing hydrogen production, minimizing operating costs, and minimizing wind curtailment. The scheduling instructions include electrolysis power command values. The coordination and control layer includes a wind power deviation allocation module and an internal allocation module for the electrolysis array. It is used to determine the first deviation between the actual wind power on the wind power side and the electrolysis power command value, dynamically compensate for the first deviation in conjunction with a preset calling sequence, and dynamically correct the electrolysis power command value. The preset calling sequence sequentially includes: the energy storage side, the hydrogen production side, and the alcohol production side. When the second deviation between the actual total electrolysis power on the hydrogen production side and the corrected electrolysis power command value exceeds a preset fluctuation range, the target total electrolysis power on the hydrogen production side is determined, and an equal hydrogen production rate incremental allocation method is used to allocate the target total electrolysis power to each electrolysis cell group of the electrolysis array on the hydrogen production side. It also controls each electrolysis cell group of the electrolysis array to operate at the allocated power.

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