Off-grid new energy hydrogen production starting control method, system, equipment and medium

Abstract

The invention discloses an off-grid new energy hydrogen production start control method, system, device and medium, and relates to the technical field of new energy hydrogen production control and micro-grid operation management, and the method comprises the steps: employing energy storage zero-to-boost control and anti-interference communication to establish a bus voltage based on an off-grid system architecture; the output power of the wind turbine generator is adjusted through a variable pitch power following strategy based on short-term wind speed prediction, the power distribution proportion of the wind turbine generator and the energy storage device is dynamically adjusted by adopting an improved NSGA-II multi-target optimization algorithm in combination with the equipment health state factor, and the power output path and the response rate of the equipment are optimized; electrolytic hydrogen production is carried out by adopting electrolytic tank pre-starting condition inspection, stepped power rising and stepped starting of grid-connected transition in cooperation with closed-loop temperature flow regulation and a PID pressure management strategy, and black-start rollback and self-healing control are executed. According to the method, the stable construction of the bus voltage is realized through the boost control from zero energy storage, and the current impact in the starting process is effectively inhibited.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy hydrogen production control and microgrid operation management, and specifically to an off-grid new energy hydrogen production startup control method, system, equipment and medium. Background Art

[0002] The operating characteristics and regulatory capabilities of traditional power grids are no longer sufficient to meet the system stability and security requirements of a high proportion of renewable energy integration. To enhance renewable energy absorption capacity and enable energy transfer across time and space, water electrolysis hydrogen production technology, with its excellent energy storage and energy conversion properties, is becoming an important technical path for building a new energy system. In particular, in off-grid, independent microgrid scenarios, the coordinated operation of wind power, energy storage, and hydrogen electrolysis not only improves renewable energy utilization but also effectively supports energy supply and system black start capabilities in isolated island mode.

[0003] However, current off-grid renewable energy hydrogen production systems still face numerous technical challenges during black start. First, the lack of external grid support during the initial black start phase makes it difficult to ensure system voltage and frequency stability. Second, the coordinated startup of wind turbines and energy storage devices presents significant current surges and frequent bus voltage fluctuations, which can lead to increased equipment losses and even failure. Furthermore, the direct operation of electrolytic hydrogen production equipment during a black start presents challenges such as excessive starting current and unstable temperature and pressure control, impacting the system's overall startup efficiency and equipment safety.

[0004] Existing technologies often utilize single energy storage or wind power equipment for black starts, lacking a coordinated optimization control strategy for wind, storage, and hydrogen. Energy storage systems typically don't dynamically adjust power based on the state of charge and equipment health, resulting in low energy storage utilization. Wind turbines lack a variable pitch control strategy based on short-term wind speed forecasts, making it difficult to promptly adapt to the impact of wind speed fluctuations on system power demand. Furthermore, most existing hydrogen production systems fail to utilize phased startup and dynamic adjustment strategies, resulting in high energy consumption, severe equipment wear, and difficulty ensuring hydrogen purity during electrolysis.

[0005] In summary, there is an urgent need for an off-grid new energy hydrogen production startup control method that can achieve coordinated optimization of wind-hydrogen storage systems, and has perfect black start capability, dynamic power adjustment capability, and stable control capability of electrolysis hydrogen production process, so as to improve the utilization rate of new energy and system operation stability, and realize a safe, economical and efficient off-grid hydrogen production startup process. Summary of the Invention

[0006] In view of the above-mentioned problems, the present invention is proposed.

[0007] Therefore, the technical problem solved by the present invention is: the existing off-grid new energy hydrogen production control method has insufficient black start capability, low system power regulation flexibility, and unstable electrolysis hydrogen production startup process, as well as how to achieve bus voltage stability, power balance and safe and efficient startup of the electrolysis hydrogen production process during the black start process through wind hydrogen storage multi-energy coordinated optimization without external power grid support.

[0008] In order to solve the above technical problems, the present invention provides the following technical solutions: an off-grid new energy hydrogen production startup control method, comprising establishing bus voltage based on an off-grid system architecture using energy storage zero-start boost control and anti-interference communication.

[0009] The output power of the wind turbine is regulated by a variable pitch power following strategy based on short-term wind speed forecast. Combined with the equipment health status factor, an improved NSGA-II multi-objective optimization algorithm is used to dynamically adjust the power distribution ratio of the wind turbine and the energy storage device, and optimize the equipment power output path and response rate.

[0010] A stepped start-up with electrolyzer pre-start condition check, step-by-step power ramp-up, and grid-connected transition is adopted, along with closed-loop temperature and flow regulation and PID pressure management strategies for electrolytic hydrogen production, and black start fallback and self-healing control are implemented.

[0011] Adjusting the power allocation ratio of wind turbines and energy storage devices includes constructing a variable pitch power following strategy based on short-term wind speed forecasts, combining the improved NSGA-II multi-objective optimization algorithm and equipment health status factors, using energy storage power change rate calculation and stage-by-stage setting of slope thresholds to control the power adjustment rate of the energy storage system's charging and discharging process, and dynamically adjusting the wind turbine variable pitch rate according to wind speed forecasts.

[0012] Adjusting the power distribution ratio of wind turbines and energy storage devices also includes optimizing the slope threshold of each device in real time through the main control unit combined with bus voltage fluctuations and digital twin simulation results.

[0013] As a preferred solution of the off-grid new energy hydrogen production startup control method described in the present invention, the energy storage zero-start boost control and anti-interference communication include deploying a time-sensitive network protocol in an independent microgrid architecture and realizing redundant link switching of key control instructions through the Rapid Spanning Tree Protocol.

[0014] The AES-256 advanced encryption algorithm and CRC cyclic redundancy check mechanism are introduced for key control data, and the electrical physical model is established and dynamically controlled through the digital twin method. Virtual simulation calculations are performed using real-time collected wind speed, bus voltage, energy storage charge state and electrolyzer operating parameters. The control strategy of the microgrid bus voltage construction process is dynamically optimized based on the simulation results.

[0015] As a preferred solution of the off-grid new energy hydrogen production startup control method described in the present invention, the establishment of the bus voltage includes establishing the bus voltage through the energy storage device in three stages: pre-charging, impedance matching and closed-loop voltage stabilization, adopting a constant current and voltage limiting mode in the pre-charging stage, and limiting the initial charging current through the pre-charging resistor network.

[0016] In the impedance matching stage, based on the real-time identification technology of line parameters, the TOPSIS algorithm generalized by the non-inferior ideal point is introduced. The relative proximity calculation formula of the ideal point based on TOPSIS is used to dynamically calculate the matching degree between the energy storage output impedance and the equivalent impedance of the transmission line. By screening the optimal impedance matching scheme, the energy storage output impedance is adjusted to dynamically adapt to the transmission line impedance.

[0017] In the closed-loop voltage stabilization stage, when the bus voltage reaches the preset value, the energy storage controller switches to the voltage-reactive dual-loop closed-loop control mode, and steadily increases the bus voltage to the rated voltage value through a controllable slope.

[0018] As a preferred solution of the off-grid new energy hydrogen production startup control method described in the present invention, the adjustment of the output power of the wind turbine includes establishing a wind speed prediction model based on an improved long short-term memory network, inputting historical wind speed change data and real-time wind speed, air pressure, and temperature meteorological data collected by the weather station, combining the real-time operation data for model training, and dynamically updating the model parameters using a sliding window mechanism.

[0019] Based on the prediction results output by the wind speed prediction model and the current power demand, a pre-adjustment instruction for the pitch angle is generated. The optimal pitch angle setting value is determined by searching the wind speed-power mapping database. Based on the deviation between the real-time power output of the wind turbine and the predicted demand, the pitch angle adjustment amount is dynamically corrected using a feedback compensation algorithm.

[0020] During the pitch angle adjustment process, the main control unit sets the pitch angle rate limit value based on the response characteristics of the wind turbine in different wind speed ranges, so that the pitch angle adjustment rate is within the safety threshold. When the main control unit determines that the wind turbine has completed startup and is in a stable operating state, and its output power reaches 20% of the total system demand and remains stable for 60 seconds, the main control unit sends a pre-start instruction to the electrolysis hydrogen production system.

[0021] During the power regulation process of wind turbines, the health status of each unit is dynamically calculated by real-time monitoring of the temperature, vibration and current fluctuation state parameters of the wind turbines in combination with the equipment health status evaluation factor, and wind turbines with good health status are preferentially dispatched to participate in power output.

[0022] As a preferred solution of the off-grid new energy hydrogen production startup control method described in the present invention, the adjustment of the power distribution ratio of the wind turbine group and the energy storage device includes calculating the optimal power distribution ratio of the wind turbine group and the energy storage device through a multi-objective optimization algorithm, constructing a multi-objective optimization function to minimize the wind power output deviation, energy storage output deviation, voltage fluctuation index and black start time cost, and optimizing the power distribution in combination with the equipment health status factor.

[0023] An improved NSGA-II multi-objective genetic algorithm is used. By introducing a congestion comparison operator and a non-inferior solution elite retention strategy, a Pareto optimal frontier solution set is generated during the optimization process. The optimal power allocation solution is determined by calculating the Euclidean distance calculation formula using the ideal point method.

[0024] During the power distribution process, the output power of the wind turbine and energy storage device is dynamically adjusted according to the optimization calculation results, combined with the load changes, bus voltage status and wind speed prediction results collected in real time by the main control unit. The wind turbine takes priority in the benchmark power output task in the optimization algorithm results, and the energy storage adjusts the load response according to the prediction deviation and health status to jointly meet the power demand.

[0025] As a preferred solution of the off-grid new energy hydrogen production startup control method described in the present invention, the optimization of the equipment power output path and response rate includes dynamically adjusting the power output path of the wind turbine and the energy storage device based on the optimization algorithm through the main control unit, and controlling the response rate of each device to adapt to changes in the hydrogen production load.

[0026] In order to optimize the energy storage output path, combined with the energy storage charge state and predicted load change trend, the output power change slope of the energy storage device is dynamically adjusted to control the power change rate during the charge and discharge conversion process not to exceed the set slope threshold. The charge and discharge change rate of the energy storage is calculated using the energy storage power change rate calculation formula.

[0027] As a preferred embodiment of the off-grid new energy hydrogen production startup control method described in the present invention, the optimization of the equipment power output path and response rate also includes limiting the charge and discharge change rate of the energy storage to within the maximum slope threshold calculated by the main control unit. When the energy storage charge state is greater than 80% and the health status factor is greater than 0.9, the maximum allowable slope threshold does not exceed 0.5kW / s.

[0028] When the energy storage state of charge is greater than 50% and less than 80% and the health status factor is greater than or equal to 0.8, the maximum slope threshold does not exceed 0.3kW / s.

[0029] When the energy storage state of charge is less than 50%, the health factor is less than 0.8, and the maximum slope threshold is limited to 0.1kW / s.

[0030] As a preferred solution of the off-grid new energy hydrogen production startup control method described in the present invention, the maximum slope threshold includes setting a slope threshold for the wind turbine generator set, analyzing the current wind speed change trend through a wind speed prediction model and historical operation data, and dynamically setting the maximum slope threshold of the pitch angle change rate based on the predicted wind speed change rate and system load adjustment requirements. In the stable stage of wind speed change, the pitch angle adjustment slope is set to no more than 1.5° / s.

[0031] When the wind speed changes dramatically, the pitch angle adjustment rate is dynamically adjusted according to the load demand, not exceeding 3° / s, and feedback compensation is used to avoid instability caused by excessive changes in the pitch rate.

[0032] The main control unit corrects the above slope threshold in real time according to the bus voltage fluctuation. When the bus voltage fluctuation exceeds ±2.5%, it automatically lowers the power adjustment slope threshold of the energy storage and wind turbine units to prioritize stability. It simulates the response effect under each slope threshold through digital twin simulation, and dynamically optimizes the threshold setting based on the simulation results and current operating data.

[0033] As a preferred embodiment of the off-grid new energy hydrogen production startup control method described in the present invention, the electrolytic hydrogen production includes, in the pre-start condition check stage, when the microgrid bus voltage and frequency are stable within a preset range, the main control unit controls the electrolytic cell to not exceed 10% of the rated current for initial power-on, and at the same time maintains the temperature rise rate at no more than 2°C / min through the temperature sensor and flow controller, so that the structural material of the electrolytic cell is in a safe stress state.

[0034] During stepped power loading, the electrolyzer is powered by a combination of wind power and energy storage. The current allocable power is calculated based on the remaining power after the wind-storage system is dispatched, and the electrolyzer power is gradually increased to between 15% and 100% of the rated power. The pressure valve is adjusted by a PID controller to maintain the internal pressure fluctuation at ±0.05 MPa.

[0035] During the grid-connected transition phase, the DC side voltage and electrolysis current change rate are adjusted to control the electrolytic cell to smoothly access the load, the feedback signals of each sensor are monitored in real time, and the operating status of the electrolytic cell is dynamically adjusted.

[0036] Executing black start fallback and self-healing control includes: the main control unit setting black start key monitoring indicators. When the indicators exceed the set thresholds, the main control unit triggers the fallback mechanism based on the state machine logic.

[0037] Key monitoring indicators include bus voltage fluctuation, energy storage SOC, electrolyzer temperature, and frequency fluctuation.

[0038] During the fallback process, the electrolyzer power output is reduced to 50% of the current value, and the cooling forced cooling is triggered at the same time, the electrolyte flow is adjusted to the maximum set value, and the internal temperature and pressure are reduced.

[0039] During the black start period, key operating indicators such as voltage, current, and temperature are detected in real time.

[0040] If any indicator is detected to have exceeded a safety threshold, a fallback mechanism is immediately implemented. During the fallback process, the electrolysis power is reduced to 50%, and the electrolyte flow rate is forcibly increased to accelerate cooling, while also improving the energy storage and wind power output stability bus. The main control uses fuzzy logic to determine the fault level and, after recovery, gradually restores electrolyzer operation using a step-by-step strategy.

[0041] During the self-healing control process, the main control unit uses a fuzzy logic algorithm to judge the fault level. When the status is restored to the point where each monitoring indicator is lower than the set safety threshold, the power output of the electrolyzer is gradually restored and the load is readjusted according to the step-by-step startup process.

[0042] Fault records and response data at each stage are stored reliably through blockchain.

[0043] Another object of the present invention is to provide an off-grid new energy hydrogen production startup control system, which can dynamically distribute power through a variable pitch power following strategy based on short-term wind speed prediction and an improved NSGA-II multi-objective optimization algorithm, thereby solving the problems of unreasonable power distribution, slow response rate and uncoordinated equipment adjustment in the current off-grid microgrid black start technology.

[0044] As a preferred solution of the off-grid new energy hydrogen production startup control system described in the present invention, it includes: a bus voltage construction module, a wind storage power optimization distribution and dynamic adjustment module, and an electrolytic hydrogen production startup and fallback self-healing module.

[0045] The bus voltage building module is used to establish the bus voltage based on the off-grid system architecture by adopting energy storage zero-start boost control and anti-interference communication.

[0046] The wind-storage power optimization allocation and dynamic adjustment module is used to regulate the output power of wind turbines through a variable pitch power following strategy based on short-term wind speed forecasts. In combination with the equipment health status factor, an improved NSGA-II multi-objective optimization algorithm is used to dynamically adjust the power allocation ratio of wind turbines and energy storage devices, and optimize the equipment power output path and response rate.

[0047] The electrolytic hydrogen production startup and fallback self-healing module is used to adopt a step-by-step start-up of electrolyzer pre-start condition check, power step increase and grid-connected transition, cooperate with closed-loop temperature flow regulation and PID pressure management strategy to perform electrolytic hydrogen production, and execute black start fallback and self-healing control.

[0048] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a step of an off-grid new energy hydrogen production startup control method.

[0049] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of an off-grid new energy hydrogen production startup control method.

[0050] Beneficial effects of the present invention: The off-grid new energy hydrogen production startup control method provided by the present invention realizes the stable construction of bus voltage through energy storage zero-start boost control, effectively suppresses the current shock during the startup process, improves the wind energy utilization rate and optimizes the power output path through the variable pitch power following strategy based on short-term wind speed prediction, and reduces the thermal stress and pressure fluctuations during the electrolysis startup process through the electrolytic cell step-by-step startup combined with the PID pressure management strategy. The present invention achieves better results in black start success rate, system stability and equipment service life. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 1 This is an overall flow chart of an off-grid new energy hydrogen production startup control method provided by the first embodiment of the present invention.

[0053] Figure 2 This is a system structure diagram of an off-grid new energy hydrogen production startup control method provided by the second embodiment of the present invention. DETAILED DESCRIPTION

[0054] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0055] Example 1, reference Figure 1 , which is an embodiment of the present invention, provides an off-grid new energy hydrogen production startup control method, comprising: S1: Based on the off-grid system architecture, energy storage zero-start boost control and anti-interference communication are used to establish the bus voltage.

[0056] Deploy the time-sensitive network protocol in the off-grid system architecture, and implement redundant link switching of key control instructions through the Rapid Spanning Tree Protocol, with the link switching time not exceeding 50ms.

[0057] The AES-256 advanced encryption algorithm and CRC cyclic redundancy check mechanism are introduced for key control data, and the electrical physical model is established and dynamically controlled through the digital twin method. The real-time collected wind speed, bus voltage, energy storage charge state and electrolyzer operating parameters are used for virtual simulation calculations. The control strategy of the microgrid bus voltage construction process is dynamically optimized based on the simulation results, and the transmission delay of key control instructions is kept within 5ms.

[0058] Furthermore, the bus voltage is established through the energy storage device in three stages: pre-charging, impedance matching and closed-loop voltage stabilization. In the pre-charging stage, a constant current and voltage limiting mode is adopted, and the initial charging current is limited by the pre-charging resistor network, so that the initial charging current is controlled within 5% of the rated current of the energy storage device.

[0059] A preferred solution for limiting the initial charging current through a pre-charge resistor network is: , in, represents the initial charging current, Indicates the rated current of the energy storage device.

[0060] In the impedance matching stage, based on the real-time identification technology of line parameters, the TOPSIS algorithm generalized by the non-inferior ideal point is introduced to dynamically calculate the matching degree between the energy storage output impedance and the equivalent impedance of the transmission line using the TOPSIS-based ideal point relative proximity calculation formula.

[0061] A preferred solution for dynamically calculating the matching degree between the energy storage output impedance and the equivalent impedance of the transmission line is: , in, Representation scheme The relative proximity of Representation scheme The distance to the positive ideal solution, Representation scheme The distance to the negative ideal solution.

[0062] By screening the optimal impedance matching scheme, the energy storage output impedance is adjusted to dynamically adapt to the transmission line impedance.

[0063] In the closed-loop voltage stabilization stage, when the bus voltage reaches 0.95pu and remains stable for 10 seconds, the energy storage controller switches to the voltage-reactive dual-loop closed-loop control mode.

[0064] The voltage-reactive dual-loop closed-loop control model includes an outer loop that controls voltage stability and an inner loop that controls reactive power distribution, achieving joint regulation of voltage amplitude and phase angle to steadily increase the bus voltage to the rated voltage value through a controllable slope.

[0065] An optimal solution to stably increase the bus voltage to the rated voltage is: , in, Indicates time Bus voltage, represents the initial bus voltage, Indicates the bus voltage boost slope, Indicates time.

[0066] S2: The output power of the wind turbine is regulated through a variable pitch power following strategy based on short-term wind speed forecasts. The improved NSGA-II multi-objective optimization algorithm is used in combination with the equipment health status factor to dynamically adjust the power distribution ratio of the wind turbine and energy storage device, and optimize the equipment power output path and response rate.

[0067] A wind speed prediction model is established based on an improved long short-term memory network. The model is trained by inputting historical wind speed change data and real-time wind speed, air pressure, and temperature meteorological data collected by weather stations, combined with real-time operation data, and the model parameters are dynamically updated using a sliding window mechanism.

[0068] An optimal solution for establishing a wind speed prediction model is: , in, represents the predicted wind speed, represents the LSTM neural network prediction function, Indicates time wind speed, Indicates the number of historical wind speed samples used for prediction.

[0069] According to the prediction results output by the wind speed prediction model and the current power demand, a pre-adjustment instruction for the pitch angle is generated.

[0070] A preferred solution for generating a preset instruction for the pitch angle is: , in, represents the wind turbine power coefficient, represents the air density, represents the swept area of ​​the wind wheel, represents the predicted wind power, represents the cube of the predicted wind speed, Indicates the predicted wind power value corresponding to the time.

[0071] The optimal pitch angle setting value is determined by searching the wind speed-power mapping database, and the pitch angle adjustment value is dynamically corrected using a feedback compensation algorithm based on the deviation between the real-time power output of the wind turbine and the predicted demand.

[0072] The deviation between the real-time power output of the wind turbine and the predicted demand includes the deviation between the real-time power output of the wind turbine and the target power obtained by the wind speed prediction model and the load calculation result.

[0073] A preferred solution for correcting the pitch angle adjustment amount is: , in, Indicates the change in pitch angle adjustment, represents the proportional adjustment coefficient, represents the target power, Indicates actual power output.

[0074] During the pitch angle adjustment process, the main control unit sets the pitch angle rate limit value based on the response characteristics of the wind turbine in different wind speed ranges, so that the pitch angle adjustment rate is within the safety threshold. When the main control unit determines that the wind turbine has completed startup and is in a stable operating state, and its output power reaches 20% of the total system demand and remains stable for 60 seconds, the main control unit sends a pre-start instruction to the electrolysis hydrogen production system.

[0075] During the power regulation process of wind turbines, the health status of each unit is dynamically calculated by real-time monitoring of the temperature, vibration and current fluctuation state parameters of the wind turbines in combination with the equipment health status evaluation factor, and wind turbines with good health status are preferentially dispatched to participate in power output.

[0076] The optimal power distribution ratio of wind turbines and energy storage devices is calculated through a multi-objective optimization algorithm, and a multi-objective optimization function is constructed.

[0077] Calculation of the optimal power distribution ratio of wind turbines and energy storage devices includes priority supply of wind power, dynamic adjustment of energy storage, and absorption of auxiliary wind power redundant power.

[0078] An optimal solution for constructing a multi-objective function is: , in, Indicates the wind power output deviation, Indicates the energy storage output deviation, Indicates voltage fluctuation index, represents the black start time cost, Indicates the equipment health status factor, represents the wind power forecast deviation objective function, represents the energy storage scheduling deviation objective function, represents the voltage fluctuation evaluation function, represents the startup time cost function, Represents the equipment health status evaluation function.

[0079] The calculation of the black start time cost includes the total time required to recover from the power outage state to the stable operation of the electrolysis hydrogen production system, which includes three stages: energy storage pressure building, wind power output stabilization, and electrolyzer stable loading.

[0080] The goal of minimizing wind power output deviation is to control the actual power output close to the theoretical prediction target by adjusting the pitch angle and other means, thereby reducing the control error caused by wind speed fluctuations and equipment response lag.

[0081] The power distribution is optimized by minimizing the wind power output deviation, energy storage output deviation, voltage fluctuation index and black start time cost, and combining the equipment health status factor.

[0082] An improved NSGA-II multi-objective genetic algorithm was adopted. By introducing the crowding comparison operator and the non-inferior solution elite retention strategy, the multi-objective function was input into the improved NSGA-II multi-objective genetic algorithm. The Pareto frontier solution set was generated through the non-dominated sorting and crowding comparison mechanism, and the final optimal solution was calculated by the ideal point method Euclidean distance.

[0083] A preferred solution for calculating and determining the optimal power allocation solution is: , in, Representation scheme The Euclidean distance of Representation scheme In the The actual value under the target, Indicates the The ideal value of a target, Represents the number of objective functions.

[0084] During the power distribution process, the output power of the wind turbine and energy storage device is dynamically adjusted according to the optimization calculation results, combined with the load changes, bus voltage status and wind speed prediction results collected in real time by the main control unit. The wind turbine takes priority in the benchmark power output task in the optimization algorithm results, and the energy storage adjusts the load response according to the prediction deviation and health status to jointly meet the power demand.

[0085] The wind turbine is started after the energy storage is pressurized, and assumes the minimum power baseline. The power is the judgment condition for the start-up of the electrolyzer.

[0086] The main control unit dynamically adjusts the power output paths of wind turbines and energy storage devices based on the optimization algorithm, and controls the response rate of each device to adapt to changes in hydrogen production load.

[0087] In order to optimize the energy storage output path, combined with the energy storage charge state and predicted load change trend, the output power change slope of the energy storage device is dynamically adjusted to control the power change rate during the charge and discharge conversion process not to exceed the set slope threshold. The charge and discharge change rate of the energy storage is calculated using the energy storage power change rate calculation formula.

[0088] The output path includes the equipment power supply sequence and the load-side energy supply structure.

[0089] A preferred method for calculating the rate of change of energy storage charge and discharge is: , in, Indicates the rate of change of energy storage power, Indicates the target output power of energy storage, Indicates the current output power of the energy storage. Indicates the adjustment time interval.

[0090] The charge and discharge change rate of the energy storage is limited to the maximum slope threshold calculated by the main control unit. When the energy storage charge state is greater than 80% and the health factor is greater than 0.9, the maximum slope threshold allowed does not exceed 0.5kW / s.

[0091] When the energy storage state of charge is greater than 50% and less than 80% and the health status factor is greater than or equal to 0.8, the maximum slope threshold does not exceed 0.3kW / s.

[0092] When the energy storage state of charge is less than 50%, the health factor is less than 0.8, and the maximum slope threshold is limited to 0.1kW / s.

[0093] For the slope threshold setting of wind turbines, the current wind speed change trend is analyzed through the wind speed prediction model and historical operation data. According to the predicted wind speed change rate and system load adjustment requirements, the maximum slope threshold of the pitch angle change rate is dynamically set. In the stable wind speed change stage, the pitch angle adjustment slope is set to no more than 1.5° / s.

[0094] When the wind speed changes dramatically, the pitch angle adjustment rate is dynamically adjusted according to the load demand, not exceeding 3° / s, and feedback compensation is used to avoid instability caused by excessive changes in the pitch rate.

[0095] The main control unit corrects the above slope threshold in real time according to the bus voltage fluctuation. When the bus voltage fluctuation exceeds ±2.5%, it automatically lowers the power adjustment slope threshold of the energy storage and wind turbine units to prioritize stability. It simulates the response effect under each slope threshold through digital twin simulation, and dynamically optimizes the threshold setting based on the simulation results and current operating data.

[0096] S3: Adopt the step start of electrolyzer pre-start condition check, power step increase and grid transition, cooperate with closed-loop temperature flow regulation and PID pressure management strategy to produce hydrogen by electrolysis, and implement black start fallback and self-healing control.

[0097] During the pre-start condition check phase, when the system bus voltage and frequency are stable within the preset range, the main control unit controls the electrolytic cell to not exceed 10% of the rated current for initial power-on. At the same time, the temperature sensor and flow controller are used to maintain the temperature rise rate at no more than 2°C / min, so that the electrolytic cell structural materials are in a safe stress state.

[0098] A preferred solution for maintaining the temperature rise rate through temperature sensors and flow controllers is: , in, represents the temperature change, Indicates a time interval.

[0099] During the power coupling stage, the electrolyzer is jointly powered by wind power and energy storage. The current allocable power is calculated based on the remaining power after the wind-storage system is dispatched, and the electrolyzer power is gradually increased to between 15% and 100% of the rated power.

[0100] The cell current includes the cell current measured by the sensor.

[0101] The pressure valve is adjusted by the PID controller to maintain the internal pressure fluctuation within ±0.05MPa.

[0102] A preferred solution for regulating the pressure valve using a PID controller is: , in, Indicates time The pressure adjustment value, Indicates the current pressure deviation, Indicates the PID ratio, represents the integral, represents the differential coefficient.

[0103] During the grid-connected transition phase, the electrolytic cell is controlled to smoothly access the load by adjusting the DC side voltage and the electrolysis current change rate.

[0104] A preferred solution for adjusting the DC side voltage and the electrolysis current rate of change is: , in, Indicates the change in electrolytic cell power, Indicates the time interval, Indicates the maximum allowable power change rate of the electrolytic cell.

[0105] Monitor the feedback signals of each sensor in real time and dynamically adjust the operating status of the electrolyzer.

[0106] A preferred solution for dynamically adjusting the operating state of the electrolyzer is: , in, Indicates the total amount of electricity consumed by the electrolytic cell during the entire operating cycle. Indicates that the electrolytic cell is at time Power, Indicates the calculation cycle.

[0107] Through blockchain technology, data from key operating stages can be tamper-proofed and distributed, enabling post-audit, exception playback, and control logic tracking functions, enhancing operational transparency and security. The data can be used as a basis for optimizing subsequent scheduling strategies and tracing faults for wind-storage electrolysis.

[0108] Executing black start fallback and self-healing control includes: the main control unit setting black start key monitoring indicators. When the indicators exceed the set thresholds, the main control unit triggers the fallback mechanism based on the state machine logic.

[0109] Key monitoring indicators include bus voltage fluctuation, energy storage SOC, electrolyzer temperature, and frequency fluctuation.

[0110] During the fallback process, the electrolyzer power output is reduced to 50% of the current value, and the cooling forced cooling is triggered at the same time, the electrolyte flow is adjusted to the maximum set value, and the internal temperature and pressure are reduced.

[0111] During the black start period, key operating indicators such as voltage, current, and temperature are detected in real time.

[0112] If any indicator is detected to have exceeded a safety threshold, a fallback mechanism is immediately implemented. During the fallback process, the electrolysis power is reduced to 50%, and the electrolyte flow rate is forcibly increased to accelerate cooling, while also improving the energy storage and wind power output stability bus. The main control uses fuzzy logic to determine the fault level and, after recovery, gradually restores electrolyzer operation using a step-by-step strategy.

[0113] During the self-healing control process, the main control unit uses a fuzzy logic algorithm to judge the fault level. When the status is restored to the point where each monitoring indicator is lower than the set safety threshold, the power output of the electrolyzer is gradually restored and the load is readjusted according to the step-by-step startup process.

[0114] Fault records and response data at each stage are stored reliably through blockchain.

[0115] Example 2, reference Figure 2 , which is an embodiment of the present invention, provides an off-grid new energy hydrogen production startup control system, including a bus voltage construction module 100, a wind storage power optimization allocation and dynamic adjustment module 200, and an electrolysis hydrogen production startup and fallback self-healing module 300.

[0116] Among them, S4: bus voltage construction module 100 is used to establish bus voltage based on the off-grid system architecture by adopting energy storage zero-start boost control and anti-interference communication.

[0117] It should also be noted that the bus voltage construction module 100 first establishes a stable bus voltage to provide starting conditions for the wind power storage power optimization allocation and dynamic adjustment module 200.

[0118] S5: The wind-storage power optimization allocation and dynamic adjustment module 200 is used to adjust the output power of the wind turbine through a variable pitch power following strategy based on short-term wind speed forecasts, and adopt an improved NSGA-II multi-objective optimization algorithm in combination with the equipment health status factor to dynamically adjust the power allocation ratio of the wind turbine and the energy storage device, and optimize the equipment power output path and response rate.

[0119] It should also be noted that the wind storage power optimization distribution and dynamic adjustment module 200 performs power distribution and dynamic adjustment after the bus voltage stabilizes, and sends a startup instruction to the electrolysis hydrogen production startup and fallback self-healing module 300 after meeting the startup requirements.

[0120] S6: The electrolysis hydrogen production startup and fallback self-healing module 300 is used to adopt the electrolyzer pre-start condition check, power step increase and grid-connected transition step start, cooperate with the closed-loop temperature flow regulation and PID pressure management strategy to perform electrolysis hydrogen production, and execute black start fallback and self-healing control.

[0121] It should also be noted that the electrolysis hydrogen production startup and fallback self-healing module 300 performs a step-by-step startup according to the status, and in abnormal circumstances, feedback adjustment signals to the bus voltage construction module 100 and the wind storage power optimization allocation and dynamic adjustment module 200 through fallback and self-healing control.

[0122] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0123] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0124] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting, or processing it in another suitable manner as necessary, and then storing it in a computer memory.

[0125] It should be understood that various aspects of the present invention may be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods may be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one or a combination of the following technologies known in the art may be used: a discrete logic circuit having logic gates for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gates, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc. It should be noted that the above embodiments are intended only to illustrate the technical solutions of the present invention and are not intended to be limiting. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art will understand that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and such modifications are intended to be encompassed by the claims of the present invention.

Claims

1. A startup control method for off-grid new energy hydrogen production, characterized in that: include: Based on the off-grid system architecture, energy storage zero-start boost control and anti-interference communication are used to establish bus voltage; The output power of wind turbines is regulated through a variable pitch power following strategy based on short-term wind speed forecasts. The improved NSGA-II multi-objective optimization algorithm, combined with equipment health factors, dynamically adjusts the power allocation ratio between wind turbines and energy storage devices, and optimizes the equipment power output path and response rate. The system uses a stepped start-up process that includes electrolyzer pre-start condition checks, step-by-step power ramp-up, and grid-connected transition. It also utilizes closed-loop temperature and flow regulation and PID pressure management strategies for electrolytic hydrogen production, along with black start fallback and self-healing control. Adjusting the power allocation ratio between wind turbines and energy storage devices involves constructing a variable pitch power following strategy based on short-term wind speed forecasts. This strategy, combined with an improved NSGA-II multi-objective optimization algorithm and equipment health status factors, uses energy storage power change rate calculation and phased slope threshold setting to control the power adjustment rate during the energy storage system's charging and discharging process. Furthermore, the pitch rate of the wind turbines is dynamically adjusted based on the wind speed forecast. Adjusting the power distribution ratio of wind turbines and energy storage devices also includes optimizing the slope threshold of each device in real time through the main control unit combined with bus voltage fluctuations and digital twin simulation results.

2. The off-grid new energy hydrogen production startup control method according to claim 1, characterized in that: The energy storage zero-start boost control and anti-interference communication include: Deploy time-sensitive networking protocols in independent microgrid architectures and implement redundant link switching for key control instructions through the Rapid Spanning Tree Protocol; The AES-256 advanced encryption algorithm and CRC cyclic redundancy check mechanism are introduced for key control data, and the electrical physical model is established and dynamically controlled through the digital twin method. Virtual simulation calculations are performed using real-time collected wind speed, bus voltage, energy storage charge state and electrolyzer operating parameters. The control strategy of the microgrid bus voltage construction process is dynamically optimized based on the simulation results.

3. The off-grid new energy hydrogen production startup control method according to claim 1 or 2, characterized in that: The establishing of the bus voltage comprises, The bus voltage is established through the energy storage device in three stages: pre-charging, impedance matching, and closed-loop voltage regulation. In the pre-charging stage, a constant current and voltage limiting mode is adopted, and the initial charging current is limited by the pre-charging resistor network. During the impedance matching phase, based on real-time line parameter identification technology, the TOPSIS algorithm, which is generalized from non-inferior ideal points, is introduced to dynamically calculate the matching degree between the energy storage output impedance and the equivalent impedance of the transmission line using the TOPSIS-based ideal point relative proximity calculation formula. The optimal impedance matching solution is then selected to adjust the energy storage output impedance to dynamically adapt to the transmission line impedance. In the closed-loop voltage stabilization stage, when the bus voltage reaches the preset value, the energy storage controller switches to the voltage-reactive dual-loop closed-loop control mode, and steadily increases the bus voltage to the rated voltage value through a controllable slope.

4. The off-grid new energy hydrogen production startup control method according to claim 3, characterized in that: The adjusting of the wind turbine output power comprises: A wind speed prediction model is established based on an improved long-short-term memory network. The model is trained by inputting historical wind speed change data and real-time wind speed, air pressure, and temperature meteorological data collected by weather stations, combined with real-time operating data. The model parameters are dynamically updated using a sliding window mechanism. Based on the prediction results output by the wind speed prediction model and the current power demand, a pre-adjustment instruction for the pitch angle is generated. The optimal pitch angle setting value is determined by searching the wind speed-power mapping database. Based on the deviation between the real-time power output of the wind turbine and the predicted demand, the pitch angle adjustment amount is dynamically corrected using a feedback compensation algorithm. During the pitch angle adjustment process, the main control unit sets the pitch angle rate limit value based on the response characteristics of the wind turbine in different wind speed ranges, so that the pitch angle adjustment rate is within the safety threshold. When the main control unit determines that the wind turbine has completed startup and is in a stable operating state, and its output power reaches 20% of the total system demand and remains stable for 60 seconds, the main control unit sends a pre-start instruction to the electrolysis hydrogen production system; During the power regulation process of wind turbines, the health status of each unit is dynamically calculated by real-time monitoring of the temperature, vibration and current fluctuation state parameters of the wind turbines in combination with the equipment health status evaluation factor, and wind turbines with good health status are preferentially dispatched to participate in power output.

5. The off-grid new energy hydrogen production startup control method according to claim 1, 2 or 4, characterized in that: The adjusting of the power distribution ratio between the wind turbine generator set and the energy storage device includes: The optimal power allocation ratio between wind turbines and energy storage devices is calculated using a multi-objective optimization algorithm. A multi-objective optimization function is constructed to minimize wind power output deviation, energy storage output deviation, voltage fluctuation index, and black start time cost. Power allocation is optimized by combining equipment health status factors. An improved NSGA-II multi-objective genetic algorithm is used. By introducing a congestion comparison operator and a non-inferior solution elite retention strategy, a Pareto optimal frontier solution set is generated during the optimization process. The optimal power allocation solution is determined by calculating the Euclidean distance formula using the ideal point method. During the power distribution process, the output power of the wind turbine and energy storage device is dynamically adjusted according to the optimization calculation results, combined with the load changes, bus voltage status and wind speed prediction results collected in real time by the main control unit. The wind turbine takes priority in the benchmark power output task in the optimization algorithm results, and the energy storage adjusts the load response according to the prediction deviation and health status to jointly meet the power demand.

6. The off-grid new energy hydrogen production startup control method according to claim 5, characterized in that: The optimization device power output path and response rate includes: The main control unit dynamically adjusts the power output paths of wind turbines and energy storage devices based on an optimization algorithm, and controls the response rate of each device to adapt to changes in hydrogen production load. In order to optimize the energy storage output path, combined with the energy storage charge state and predicted load change trend, the output power change slope of the energy storage device is dynamically adjusted to control the power change rate during the charge and discharge conversion process not to exceed the set slope threshold. The charge and discharge change rate of the energy storage is calculated using the energy storage power change rate calculation formula.

7. The off-grid new energy hydrogen production startup control method according to claim 1, 2, 4 or 6, characterized in that: The optimizing device power output path and response rate also includes: Limit the charge and discharge rate of the energy storage to the maximum slope threshold calculated by the main control unit. When the state of charge of the energy storage is greater than 80% and the health factor is greater than 0.9, the maximum slope threshold allowed does not exceed 0.5kW / s. When the energy storage state of charge is greater than 50% and less than 80% and the health factor is greater than or equal to 0.8, the maximum slope threshold does not exceed 0.3kW / s; When the energy storage state of charge is less than 50%, the health factor is less than 0.8, and the maximum slope threshold is limited to 0.1kW / s.

8. The off-grid new energy hydrogen production startup control method according to claim 7, characterized in that: The maximum slope threshold includes: For the slope threshold setting of wind turbines, the current wind speed change trend is analyzed through the wind speed prediction model and historical operation data. Based on the predicted wind speed change rate and system load adjustment requirements, the maximum slope threshold of the pitch angle change rate is dynamically set. When the wind speed changes steadily, the pitch angle adjustment slope is set to no more than 1.5° / s. When the wind speed changes dramatically, the pitch angle adjustment rate is dynamically adjusted according to the load demand, not exceeding 3° / s, and feedback compensation is used to avoid instability caused by excessive changes in the pitch rate. The main control unit corrects the above slope threshold in real time according to the bus voltage fluctuation. When the bus voltage fluctuation exceeds ±2.5%, it automatically lowers the power adjustment slope threshold of the energy storage and wind turbine units to prioritize stability. It simulates the response effect under each slope threshold through digital twin simulation, and dynamically optimizes the threshold setting based on the simulation results and current operating data.

9. The off-grid new energy hydrogen production startup control method according to claim 8, characterized in that: The electrolysis hydrogen production comprises: During the pre-startup check phase, when the system bus voltage and frequency are stable within the preset range, the main control unit controls the electrolytic cell to not exceed 10% of the rated current for initial power-on. At the same time, the temperature sensor and flow controller are used to maintain the temperature rise rate at no more than 2°C / min, so that the electrolytic cell structural materials are in a safe stress state. During the step-by-step power ramp-up phase, the electrolyzer is powered by a combination of wind power and energy storage. The currently distributable power is calculated based on the remaining power after dispatching the wind and energy storage system, and the electrolyzer power is gradually increased to between 15% and 100% of the rated power. The pressure valve is adjusted using a PID controller to maintain internal pressure fluctuations within ±0.05 MPa. During the grid-connected transition phase, the DC side voltage and electrolysis current change rate are adjusted to control the electrolyzer to smoothly access the load, and the feedback signals from each sensor are monitored in real time to dynamically adjust the electrolyzer operating status. Executing black start fallback and self-healing control involves the master control unit setting key black start monitoring indicators. When the indicators exceed the set thresholds, the master control unit triggers the fallback mechanism based on state machine logic. Key monitoring indicators include bus voltage fluctuation, energy storage SOC, electrolyzer temperature, and frequency fluctuation; During the fallback process, the electrolyzer power output is reduced to 50% of the current value, and forced cooling is triggered at the same time, and the electrolyte flow rate is adjusted to the maximum set value to reduce the internal temperature and pressure; During black start, key operating indicators such as voltage, current, and temperature are detected in real time; When any indicator is detected to exceed the safety threshold, the fallback mechanism is immediately implemented. During the fallback process, the electrolysis power is reduced to 50%, and the electrolyte flow rate is forcibly increased to accelerate cooling, while also improving the energy storage and wind power output stability busbar; The main control uses fuzzy logic to determine the fault level and gradually restores the electrolyzer operation according to a step-by-step strategy after recovery; During the self-healing control process, the main control unit uses a fuzzy logic algorithm to determine the fault level. When the status is restored to the point where each monitoring indicator is below the set safety threshold, the electrolyzer power output is gradually restored and the load is readjusted according to the step-by-step startup process. Fault records and response data at each stage are stored reliably through blockchain.

10. An off-grid new energy hydrogen production startup control system, characterized by: It includes a bus voltage construction module (100), a wind power storage power optimization allocation and dynamic adjustment module (200), and an electrolysis hydrogen production startup and fallback self-healing module (300); The bus voltage building module (100) is used to establish the bus voltage based on an independent microgrid architecture by adopting energy storage zero-start boost control and anti-interference communication; The wind-storage power optimization allocation and dynamic adjustment module (200) is used to adjust the output power of the wind turbine generator set through a variable pitch power following strategy based on short-term wind speed prediction, dynamically adjust the power allocation ratio of the wind turbine generator set and the energy storage device by using an improved NSGA-II multi-objective optimization algorithm in combination with the equipment health status factor, and optimize the equipment power output path and response rate; The electrolytic hydrogen production start-up and fallback self-healing module (300) is used to adopt a step start of electrolytic cell and start-up condition inspection, power step increase and grid-connected transition, cooperate with closed-loop temperature flow regulation and PID pressure management strategy to perform electrolytic hydrogen production, and execute black start fallback and self-healing control.

11. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the off-grid new energy hydrogen production startup control method according to any one of claims 1 to 9 are implemented.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the off-grid new energy hydrogen production startup control method according to any one of claims 1 to 9 are implemented.

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