Energy adaptive regulation method for hydrogen fuel power flywheel UPS system

Abstract

The application discloses an energy adaptive regulation method of a hydrogen fuel power generation flywheel UPS system, and belongs to the field of uninterruptible power supply and energy storage system control. The method comprises the following steps: predicting system load demand and dynamically generating hierarchical power supply instructions; cooperatively regulating start-stop and output of a hydrogen fuel generator set and a flywheel energy storage device, and performing closed-loop correction on power supply parameters; in combination with life balance state evaluation of key components, electrolytic hydrogen production and storage are completed according to needs by using redundant electric energy. The application adopts dynamic scheduling decision based on load prediction, hydrogen-flywheel hybrid energy storage cooperative optimization and closed-loop feedback control technology of energy and state, can realize adaptive, efficient management of energy of the UPS system and optimal allocation of multi-level energy storage resources, and significantly improves dynamic response performance, energy utilization efficiency and overall power supply reliability of the uninterruptible power supply system.

Description

Technical Field

[0001] The present invention relates to the field of uninterruptible power supply and energy storage system control, and in particular to an energy adaptive control method for a hydrogen fuel power generation flywheel UPS system. Background Art

[0002] Uninterruptible power systems (UPS) are core equipment that ensures continuous power supply to critical loads such as data centers, communication hubs, medical institutions, and precision manufacturing. With the rapid development of informatization and intelligentization, the requirements for power supply quality and reliability are increasing. Traditional UPSs face new challenges in energy configuration and management strategies when faced with complex and changing load demands and longer emergency power supply periods.

[0003] Existing uninterruptible power supply solutions often struggle to balance rapid response to sudden loads with guaranteed long-term power supply. UPSs using a single energy storage medium often face limitations in energy density, cycle life, or maintenance costs. Furthermore, achieving efficient coordination of multiple power supply units and improving overall energy efficiency under dynamic load conditions are areas of urgent technological development. Summary of the Invention

[0004] To solve the above problems, the present invention provides an energy adaptive control method for a hydrogen fuel power generation flywheel UPS system. It adopts dynamic scheduling decisions based on load forecasting, hydrogen-flywheel hybrid energy storage collaborative optimization, and closed-loop feedback control technology of energy and state. It can realize the adaptive and efficient management of UPS system energy and the optimal configuration of multi-level energy storage resources, significantly improving the dynamic response performance, energy utilization efficiency and overall power supply reliability of the uninterruptible power supply system.

[0005] The above objectives can be achieved through the following solutions:

[0006] A method for adaptive energy control of a hydrogen fuel cell flywheel UPS system comprises obtaining current load data of the UPS system and load data in a preset historical database to generate a load demand prediction curve; performing dynamic tiered priority based on the load demand prediction curve and a preset flywheel response time parameter to generate an emergency layer power supply instruction, a transition layer power supply instruction, and a steady-state layer power supply instruction; utilizing the transition layer power supply instruction to trigger the start-up of a hydrogen fuel cell generator set and synchronously calling a preset inertia compensation control signal of a flywheel energy storage device; acquiring a current output curve of the hydrogen fuel cell generator set and an inertia discharge curve of the flywheel energy storage device to generate a coordinated power supply correction parameter; correcting the transition layer power supply instruction according to the coordinated power supply correction parameter to form a closed-loop adjustment power supply instruction set; obtaining hydrogen fuel cell stack temperature data of the hydrogen fuel cell generator set and flywheel speed monitoring data of the flywheel energy storage device to generate a life loss balance parameter; generating a water electrolysis hydrogen production trigger signal based on the closed-loop adjustment power supply instruction set and the life loss balance parameter; executing the water electrolysis hydrogen production trigger signal to input redundant electric energy in the closed-loop adjustment power supply instruction set into a preset bypass electrolyzer for hydrogen energy storage operation.

[0007] Optionally, generating a load demand prediction curve includes: real-time monitoring of the AC bus voltage and current to generate a current instantaneous load power value; extracting load data from a preset historical database to generate load fluctuation frequency statistics; inputting the current instantaneous load power value and the load fluctuation frequency statistics into a pre-trained exponential load prediction model to output a load demand prediction curve.

[0008] Optionally, the dynamic stratified priority includes: obtaining the gradient change value of the load demand forecast curve, and determining the dynamic priority parameter based on the gradient change value; when the gradient change value exceeds a preset surge threshold, activating the transition layer power supply instruction in advance; when the gradient change value is lower than a preset steady-state threshold, delaying switching to the steady-state layer power supply instruction.

[0009] Optionally, generating the collaborative power supply correction parameter includes: extracting the power rise delay time based on the current output curve of the hydrogen fuel generator set; extracting the power decay time constant based on the inertia discharge curve of the flywheel energy storage device; inputting the power rise delay time and the power decay time constant into a PID regulator to generate a phase compensation parameter; performing a reverse superposition operation on the output timing of the hydrogen fuel generator set and the flywheel energy storage device according to the phase compensation parameter to generate the collaborative power supply correction parameter.

[0010] Optionally, the generating the phase compensation parameter comprises: simulating the inertia output characteristic of the hydrogen fuel generator set by a preset flywheel power attenuation model; providing a difference between the inertia output characteristic of the hydrogen fuel generator set and a current output curve of the hydrogen fuel generator set as an input to a proportional integral control module of the PID regulator; and obtaining the phase compensation parameter by the proportional integral control module based on the input processing output.

[0011] Optionally, the method further comprises: adjusting a starting current slope of the hydrogen fuel generator set according to the phase compensation parameter; synchronously reducing the starting current slope when detecting that the water electrolysis hydrogen production trigger signal is activated; and updating the closed-loop adjustment power supply instruction set according to the starting current slope.

[0012] Optionally, the forming the closed-loop adjustment power supply instruction set comprises: determining a required power adjustment amount of the transition layer power supply instruction based on the cooperative power supply correction parameter; adjusting an amplitude and a duration of the transition layer power supply instruction according to the required power adjustment amount to generate a corrected transition layer power supply instruction; and integrating the corrected transition layer power supply instruction, the emergency layer power supply instruction and the steady-state layer power supply instruction to form the closed-loop adjustment power supply instruction set.

[0013] Optionally, the generating the life loss balancing parameter comprises: obtaining a temperature-rotation speed correlation characteristic of a flywheel bearing of the flywheel energy storage device and generating a first limit threshold according to a preset mechanical wear model; obtaining a temperature-current correlation characteristic of a hydrogen fuel stack of the hydrogen fuel generator set and generating a second limit threshold according to a preset chemical attenuation model; and inputting the first limit threshold and the second limit threshold into a preset multi-objective optimization model to generate a flywheel charging and discharging depth constraint parameter and a hydrogen fuel output power constraint parameter which jointly constitute the life loss balancing parameter.

[0014] Optionally, the generating the water electrolysis hydrogen production trigger signal comprises: judging whether the redundant electric energy exceeds an upper limit value of the flywheel charging and discharging depth constraint parameter; and generating the water electrolysis hydrogen production trigger signal if the redundant electric energy exceeds the upper limit value and the output power of the hydrogen fuel generator set is higher than the second limit threshold.

[0015] Optionally, the executing the water electrolysis hydrogen production trigger signal comprises: switching a preset DC / AC inverter to a bypass mode and inputting the redundant electric energy in a direct current form to a preset bypass electrolyzer after rectification processing; detecting a hydrogen output pressure of the preset bypass electrolyzer to generate an electrolysis efficiency feedback parameter; and linking and correcting the electrolysis efficiency feedback parameter and the closed-loop adjustment power supply instruction set to form an electric energy-hydrogen energy bidirectional closed-loop regulation mechanism.

[0016] Compared with the prior art, the present application has the following advantages:

[0017] 1. By fusing the fast response flywheel energy storage and the long time power supply of hydrogen fuel power generation, and combining the accurate prediction of load demand to generate dynamic priority scheduling and instructions, the accurate and efficient response to various power disturbances and different duration power failure events is realized. Compared with the traditional single energy storage medium UPS system, this method can use flywheel energy storage to compensate for instantaneous power gaps and smooth load fluctuations, and hydrogen fuel generators to ensure the persistent and stable power supply of critical loads, significantly enhancing the rapid response capability and uninterrupted power supply reliability in a wide dynamic range of complex working conditions.

[0018] 2. A closed-loop cooperative control mechanism based on the actual operating state of the hydrogen fuel generator set and the flywheel energy storage device is constructed, and by real-time acquisition of key operating parameters and generation of cooperative power supply correction parameters, multi-level power supply instructions are dynamically optimized and closed-loop adjusted. This method can instantly feedback and adaptively adjust the output strategy and coordination timing of each energy unit, significantly improving the energy conversion and utilization efficiency compared with traditional schemes that rely on fixed control logic or open-loop control, and enhancing the self-adaptive ability and robustness of the entire power supply system to changes in working conditions.

[0019] 3. A life loss balancing management strategy for key components is introduced, and combined with the in-situ hydrogen production and storage function of redundant electrical energy. By monitoring equipment operating data and generating life loss balancing parameters to guide energy scheduling and water electrolysis hydrogen production, not only can the operating load of the core energy storage and power generation units be actively balanced, effectively extending their service life, but also the excess electrical energy under certain working conditions can be efficiently converted into hydrogen fuel for storage, thereby improving energy self-sufficiency, operational economy and reducing dependence on purchased hydrogen.

[0020] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the present application. The objects and other advantages of the present application can be realized and achieved by the structures indicated in the specification, claims and drawings. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0022] Figure 1 is a flowchart of an energy adaptive control method of a hydrogen fuel power generation flywheel UPS system according to an embodiment of the present application.

[0023] Figure 2 4 is a load demand prediction curve diagram of an embodiment of the present invention.

[0024] Figure 3 This is a synergistic response curve diagram of a hydrogen fuel generator set and a flywheel energy storage device according to an embodiment of the present invention.

[0025] Figure 4 This is a 2D constraint region diagram generated by lifetime loss balance parameters according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0027] Reference Figure 1 One embodiment of the present invention proposes an energy adaptive control method for a hydrogen fuel power generation flywheel UPS system. It adopts dynamic scheduling decisions based on load forecasting, hydrogen-flywheel hybrid energy storage collaborative optimization, and closed-loop feedback control technology of energy and state. It can achieve adaptive and efficient management of UPS system energy and optimal configuration of multi-level energy storage resources, significantly improving the dynamic response performance, energy utilization efficiency and overall power supply reliability of the uninterruptible power supply system.

[0028] The method of this embodiment specifically includes:

[0029] Obtain the current load data of the UPS system and the load data in the preset historical database to generate a load demand forecast curve;

[0030] Specifically, this step aims to understand the current state and historical trends of the UPS system load. By monitoring real-time load information and combining it with historical data records, forecasting technology is used to generate a demand forecast curve that reflects future load trends, providing a forward-looking basis for subsequent energy scheduling.

[0031] Based on the load demand forecast curve and the preset flywheel response time parameters, dynamic stratification priority is performed to generate emergency layer power supply instructions, transition layer power supply instructions, and steady-state layer power supply instructions;

[0032] Specifically, this step performs a dynamic priority assessment based on the generated load demand forecast curve and the characteristic parameters of fast-response energy storage units, such as flywheels. Based on the assessment results, different power supply scenarios are classified into different priority levels, and corresponding emergency, transition, and steady-state power supply instructions are generated, forming a preliminary, differentiated power supply strategy.

[0033] The transition layer power supply instruction is used to trigger the start-up of the hydrogen fuel generator set, and the preset inertia compensation control signal of the flywheel energy storage device is synchronously called;

[0034] Specifically, when long-term power supply or power support is needed, the hydrogen fuel cell generator set is activated and put into power generation preparation according to the transition layer power supply instruction. At the same time, to ensure a smooth power transition, this instruction will also synchronously call on the flywheel energy storage device to generate inertia compensation power, achieving synergistic cooperation between the two.

[0035] collecting a current output curve of the hydrogen fuel generator set and an inertial discharge curve of the flywheel energy storage device to generate a coordinated power supply correction parameter;

[0036] Specifically, during the coordinated operation of the hydrogen fuel cell generator set and the flywheel energy storage device, the actual power output or related operating data of both is collected in real time to form their respective output characteristic curves. By analyzing this actual operating data, the coordinated power supply correction parameters used for closed-loop control are calculated.

[0037] Modifying the transition layer power supply instruction according to the coordinated power supply correction parameter to form a closed-loop adjustment power supply instruction set;

[0038] Specifically, the generated coordinated power supply correction parameters are applied to the power supply control logic to dynamically adjust the currently executed transition-layer power supply instructions. These corrected instructions, combined with instructions from other layers, form a real-time, closed-loop power supply adjustment instruction set to adapt to changing operating conditions.

[0039] Acquiring hydrogen fuel cell stack temperature data of the hydrogen fuel generator set and flywheel speed monitoring data of the flywheel energy storage device to generate life loss balance parameters;

[0040] Specifically, to achieve equipment health management, this step acquires real-time key status monitoring data, such as temperature and rotational speed, for the hydrogen fuel cell generator's core components, such as the hydrogen fuel cell stack and flywheel energy storage device. Based on this data, a lifespan assessment model calculates and generates lifespan loss balance parameters that reflect the current relative wear and tear or health status of each component.

[0041] generating a water electrolysis hydrogen production trigger signal based on the closed-loop adjustment power supply instruction set and the life loss balance parameter;

[0042] Specifically, the system comprehensively considers the current energy balance state—determining whether there is redundant power through closed-loop adjustment of the power supply instruction set—and the lifespan loss balance of key components, evaluating them based on lifespan loss balance parameters. When preset conditions are met, a trigger signal is generated to initiate the hydrogen production process by water electrolysis.

[0043] The water electrolysis hydrogen production trigger signal is executed, and the redundant electric energy in the closed-loop adjustment power supply instruction set is input into a preset bypass electrolyzer to perform a hydrogen energy storage operation.

[0044] Specifically, in response to the generated water electrolysis hydrogen production trigger signal, the power conversion unit is controlled to transmit the determined redundant power to a preset bypass electrolyzer device. The electrolyzer uses the input power to electrolyze water to produce hydrogen, which is then stored, achieving on-site energy conversion and recycling.

[0045] By acquiring load information for prediction and generating hierarchical instructions, the system activates and coordinates the power supply of the hydrogen fuel cell generator set and the flywheel energy storage device. Real-time feedback parameters are used for closed-loop corrections. Simultaneously, equipment status is monitored to generate life parameters to guide the decision-making and execution of hydrogen production using redundant power. This constitutes a complete adaptive energy control process. This approach fully leverages the complementary advantages of hydrogen fuel's long-term power supply and the flywheel's rapid response, enabling intelligent, efficient, and reliable response to complex operating conditions.

[0046] Optionally, generating a load demand forecast curve includes:

[0047] Monitor AC bus voltage and current in real time to generate the current instantaneous load power value;

[0048] Specifically, to accurately predict load demand, this embodiment first requires acquiring real-time and historical basic load data. Voltage and current sensors, such as voltage transformers (PTs) and current transformers (CTs), deployed on the uninterruptible power supply's AC output busbars continuously or at high frequency collect real-time AC voltage and current RMS values. Based on these measurements and associated power factor information, the current instantaneous load power value is calculated in real time. For example, for a three-phase balanced system, the instantaneous active power value can be calculated as:

[0049] ;

[0050] Where, Represents the current instantaneous load power value, Represents the effective value of AC voltage, represents the effective value of AC current, Represents power factor. The calculated instantaneous load power value accurately reflects the actual power consumption of the load.

[0051] Extract load data from the preset historical database and generate load fluctuation frequency statistics;

[0052] Specifically, the control system extracts load power time series data from an internal storage unit or historical database within a preset time window. By performing statistical analysis on this historical data series, such as counting the number of times power fluctuations exceed a specific threshold or analyzing their periodic characteristics, it generates load fluctuation frequency statistics that characterize the regularity of historical load fluctuations. This statistic helps subsequent prediction models understand the dynamic characteristics of the load.

[0053] The current instantaneous load power value and the load fluctuation frequency statistic are input into a pre-trained exponential load prediction model to output a load demand prediction curve.

[0054] Specifically, the current instantaneous load power value and load fluctuation frequency statistics are used as key input features and fed into a pre-trained exponential load forecasting model. This model uses the idea of ​​exponential weighting, combined with the current load status, historical information and fluctuation characteristics, to predict the load power within a period of time in the future. An exemplary quadratic exponential smoothing model with trend adjustment can be used for this purpose. Its prediction logic involves updating the load level estimate and smoothing trend estimate, and combining the fluctuation adjustment term to calculate the future prediction value. Its core calculation relationship may include the following steps:

[0055] Update the smoothed load level estimate:

[0056] ;

[0057] Update the load trend estimate:

[0058] ;

[0059] Calculate the predicted load power for the kth time step in the future:

[0060] ;

[0061] In the above formulas, the symbols are defined as follows: and are the smoothed load level estimates at the current and previous moments, and are the load trend estimates at the current and previous moments, is the actual measured value of the current instantaneous load power, and is the smoothing coefficient, is the predicted load power for the kth step in the future, is the load fluctuation frequency statistic based on the prediction step k and the above calculation The model iteratively calculates the predicted power values ​​at a series of future time points and finally outputs a time series curve, namely the load demand prediction curve, such as Figure 2 shown.

[0062] For example, it is assumed that the current instantaneous load power value obtained is 210kW, and based on historical data and model status, the smoothing level at the previous moment is 200kW, and the trend at the previous moment is 2kW / step. The smoothing coefficient adopted by the model is 0.6, and the trend smoothing coefficient is 0.3. According to the above exponential smoothing formula, it can be obtained that the smoothing level at the current moment is approximately 206.8kW, and the trend at the current moment is approximately 3.44kW / step. If the adjustment item obtained based on the calculated load fluctuation frequency statistics is +5kW at the fifth step in the future, the load power predicted by the model for the fifth step in the future is approximately 229kW. By performing similar calculations for different future steps, a complete load demand forecast curve can be generated.

[0063] Optionally, the performing dynamic hierarchical priority includes:

[0064] Obtaining a gradient change value of the load demand forecast curve, and determining a dynamic priority parameter based on the gradient change value;

[0065] Specifically, this step aims to dynamically evaluate the current or upcoming power supply priority based on the changing trend of the load forecast curve, and adjust the status of key power supply instructions accordingly, providing a decision-making basis for achieving adaptive energy regulation. The control system first analyzes the generated load demand forecast curve and calculates its gradient change value at the current focus time point or a certain key time period in the future. The gradient change value intuitively reflects the rate of change of the predicted load power over time. A common and effective method for calculating the gradient is to use a numerical difference method, for example, calculating the ratio of the power difference between two points on the forecast curve separated by a preset small time interval to the time interval. The calculation of the gradient change value can be expressed by the following formula:

[0066] ;

[0067] Where, represents the gradient change value evaluated at time point t, and They are the predicted curves corresponding to the future The predicted load power value at time t and the current time t, A preset, relatively short time interval used to calculate the gradient. Based on the calculated gradient change value, the control system can determine one or a set of dynamic priority parameters. This dynamic priority parameter can be a quantized value, such as the calculated gradient change value itself or a normalized value to accurately represent the severity of the load change. It can also be a discrete state level, such as determining the priority category based on whether the gradient change value falls within a pre-defined interval. This dynamic priority parameter will serve as a subsequent judgment condition to guide the activation or switching logic of specific power supply instructions.

[0068] When the gradient change value exceeds a preset sudden increase threshold, activating the transition layer power supply instruction in advance;

[0069] Specifically, to ensure it can handle rapid load increases, the control system compares the calculated gradient change value with a pre-set surge threshold in real time, indicating a sharp increase in load. This surge threshold is a positive value, set based on the specific application scenario and capabilities. If the calculated gradient change value exceeds the pre-set surge threshold, this indicates that a rapid and significant load increase is predicted to occur or is currently occurring. In this situation, relying solely on flywheel energy storage may not be sufficient to fully cope with the situation, requiring the early preparation or intervention of long-duration, high-capacity power sources such as hydrogen fuel cell generators. Therefore, the control system implements preemptive activation. This means that the previously generated transitional power supply command for coordinating hydrogen fuel cell generator startup and operation with the flywheel is activated or significantly advanced based on the predicted rapid load increase, rather than waiting for the load to actually reach the power threshold required to trigger the hydrogen fuel cell generator startup. This preemptive action reserves valuable time for the hydrogen fuel cell generator to warm up, start, and power ramp, helping to ensure power supply stability and voltage quality during the load increase.

[0070] When the gradient change value is lower than a preset steady-state threshold, switching to the steady-state layer power supply instruction is delayed.

[0071] Specifically, the control system identifies a state where the load tends to be stable or decreasing, so as to switch to a steady-state operation mode which can be more economical and regular. The control system compares the calculated gradient change value with a pre-set steady-state threshold value representing a state where the load change tends to be stable or decreasing. The steady-state threshold value is usually a small positive value, zero or a small negative value, defining a stable interval of load change. If the current calculated gradient change value is smaller than the pre-set steady-state threshold value, it indicates that the predicted load growth has slowed down significantly, tends to be stable, or even starts to decrease. In this case, the higher power reserve maintained by the transition layer power supply instruction or the special hydrogen-flywheel cooperative mode can no longer be needed. In order to avoid the impact on stability caused by frequent switching of control modes due to short-term load fluctuations, the control system can adopt a delayed switching strategy. This means that even if the gradient change value is temporarily lower than the steady-state threshold value, the steady-state layer power supply instruction will not be switched immediately, but the state will be observed for a period of time. Only when it is confirmed that the load has indeed entered a relatively stable low change rate state, will the control system formally switch the dominant power supply strategy to the steady-state layer power supply instruction which has lower priority and is usually more focused on efficiency and economy.

[0072] Optionally, the generating the cooperative power supply correction parameter comprises:

[0073] extracting a power rise delay time of the hydrogen fuel generator set based on a current output curve of the hydrogen fuel generator set;

[0074] Specifically, this step aims to calculate and generate correction parameters for optimizing the cooperative power supply effect of the hydrogen fuel generator set and the flywheel energy storage device based on their respective different dynamic response characteristics, ensuring smooth and efficient power switching and superposition process. The actual current output curve or the power output curve converted from the voltage of the hydrogen fuel generator set collected needs to be analyzed and processed. By identifying the time difference between the time point when the generator set receives a start or power boost instruction and the time point when its actual output power reaches a certain predetermined proportion on the curve, or by fitting the rising segment of the curve with a standard first-order or second-order response model to extract a time parameter representing the response speed, the power rise delay time characteristic of the hydrogen fuel generator set is finally obtained.

[0075] extracting a power decay time constant of the flywheel energy storage device based on an inertia discharge curve of the flywheel energy storage device;

[0076] Specifically, the actual output characteristic curve of the flywheel energy storage device collected when performing the inertial discharge operation is analyzed. The curve can be a curve showing the change of the flywheel output power over time, or a curve showing the decrease of its speed over time, and the speed is directly related to the amount of stored energy. When the flywheel is in pure inertial discharge, its energy release or power output can usually be approximated as an exponential decay process. By fitting the actual measured discharge curve data with a standard exponential decay function model or other applicable dynamic model, the key characteristic parameter, namely the power decay time constant, can be extracted. This time constant reflects the rate at which the flywheel's output naturally decays over time when providing short-term power support.

[0077] Inputting the power rise delay time and the power decay time constant into a PID regulator to generate a phase compensation parameter;

[0078] Specifically, the two key time characteristic parameters of the extracted hydrogen fuel power generation unit power rise delay time and the power decay time constant of the flywheel energy storage device are sent as input signals to a specially configured proportional-integral-differential regulator or a control algorithm module with similar functions. The PID regulator calculates and outputs a phase compensation parameter based on the values ​​of the two time parameters, such as their difference, ratio or other combination relationship, through its internal PID operation logic, including the processing of the input signal by the proportional, integral and differential links. The core purpose of the phase compensation parameter is to quantify the advance or lag adjustment required to achieve the best coordination between hydrogen fuel power generation and flywheel energy storage in the time dimension, for example, so that the flywheel output peak just covers the trough period of the hydrogen fuel power rise, or so that the total output is the most stable after the power of the two is superimposed. The phase compensation parameter can be a specific time value, a phase angle value, or a dimensionless adjustment factor.

[0079] The output timings of the hydrogen fuel generator set and the flywheel energy storage device are reversely superimposed according to the phase compensation parameters to generate collaborative power supply correction parameters.

[0080] Specifically, the generated phase compensation parameter is used to guide how to adjust the expected output power curve of the hydrogen fuel generator set and the flywheel energy storage device or the timing arrangement of the control instructions to achieve the best synergistic effect. The reverse superposition operation here is a functional description, referring to an optimization process: according to the adjustment direction and value indicated by the phase compensation parameter, for example, how much time in advance the flywheel needs to start or increase the initial output, the ideal output power curves of the two in the original plan are relatively translated, scaled or deformed on the time axis, and then the two adjusted curves are superimposed to evaluate whether the superimposed total output power curve is closest to the target load demand curve and has the smallest fluctuation. The final output of this optimization operation process is the collaborative power supply correction parameter. The collaborative power supply correction parameter can be a set of specific, corrected control parameters, such as the updated power distribution ratio, the precise time points of each start and stop, or a comprehensive correction signal or correction function that can be directly applied to existing control instructions. This parameter will be used to perform actual closed-loop corrections to the transition layer power supply instructions, such as Figure 3 shown.

[0081] Optionally, generating the phase compensation parameter includes:

[0082] Simulating the inertial output characteristics of the hydrogen fuel generator set through a preset flywheel power attenuation model;

[0083] Specifically, this step aims to accurately calculate the phase compensation parameters used to coordinate the dynamic response of the hydrogen fuel cell generator set and the flywheel energy storage device by simulating the comparison of the ideal response and the actual operating data, and using the proportional-integral control strategy. In order to generate a benchmark for comparison, a pre-set flywheel power attenuation model is used. This model mathematically describes the time-varying characteristics of the power output of an ideal power source with fast response capability, such as a flywheel energy storage device, when responding to instructions. Using this model and based on the current power instruction or expected working state of the hydrogen fuel cell generator set, the theoretical power output time series of the hydrogen fuel cell generator set is simulated and calculated if it can achieve this ideal fast response level. This simulation result is the inertial output characteristic of the hydrogen fuel cell generator set. It constructs an idealized reference output curve without obvious delay.

[0084] providing the difference between the inertial output characteristic of the hydrogen fuel generator set and the current output curve of the hydrogen fuel generator set as input to the proportional-integral control module of the PID regulator;

[0085] Specifically, the simulated inertial output characteristics of the hydrogen fuel cell generator set are compared point by point or time period by time period with the actual current output curve of the hydrogen fuel cell generator set, obtained through real-time data collection. The real-time difference, or error signal, between the two is calculated. This error signal quantifies the degree of lag or deviation of the hydrogen fuel cell generator set's actual response from the ideal fast response. This calculated error signal is then provided as the primary feedback input to a specific functional unit within the PID controller, namely the proportional-integral control module. This module is specifically responsible for processing this error signal to generate phase compensation information.

[0086] The proportional-integral control module processes the output based on the input to obtain a phase compensation parameter.

[0087] Specifically, the proportional-integral control module receives the input error signal and applies the proportional-integral control algorithm. The core of this algorithm is to consider both the current error magnitude and the cumulative effect of historical errors. The proportional term provides immediate response, while the integral term helps eliminate any potential steady-state errors. This module operates on the error signal based on the set proportional and integral gains. The output is the phase compensation parameter ultimately generated in this step. The calculation process for this phase compensation parameter can be expressed using the standard PI control law:

[0088] ;

[0089] Where, represents the phase compensation parameter output at time point t, represents the error signal input to the proportional-integral control module at time point t, Represents the proportional gain coefficient set by the proportional-integral control module, Represents the integral gain coefficient set by the proportional integral control module, Represents the error signal from the initial time to the current time t The proportional-integral control module continuously updates and outputs the phase compensation parameter based on the real-time calculated error, providing a key adjustment basis for achieving precise timing coordination between the hydrogen fuel generator set and the flywheel energy storage device.

[0090] For example, assuming that At this moment, the simulated inertial output characteristic of the hydrogen fuel generator set is 190kW, while the actual power output measured in real time is 170kW, so the error Assume that the proportional gain of the proportional-integral control module is 0.06 and the integral gain is 0.02. If the value of the error integral term is 40kWs at this time, the phase compensation parameter output by the proportional-integral control module at this moment is calculated as: This 2.0 second compensation parameter will be used in subsequent steps to adjust the control timing of related devices.

[0091] Optionally, the method further includes:

[0092] Adjusting the starting current slope of the hydrogen fuel generator set according to the phase compensation parameter;

[0093] Specifically, refined control of the starting process of the hydrogen fuel generator set and the linkage and coordination of this control with the state of hydrogen production by electrolysis of water are introduced, aiming to further optimize the dynamic response characteristics and ensure the quality of the output power. When the hydrogen fuel generator set needs to be started according to the power supply instruction, this method does not adopt a fixed starting program, but uses the phase compensation parameters generated by real-time calculation to dynamically adjust the rate of increase of the output current of the hydrogen fuel generator set during this startup process, that is, the starting current slope. The phase compensation parameter itself reflects the timing or phase adjustment required to achieve optimal dynamic coordination between the hydrogen fuel generator set and the flywheel energy storage device. The control system calculates and sets a suitable starting current slope based on the value of the phase compensation parameter through a preset functional relationship, lookup table or control logic. For example, if the phase compensation parameter indicates that the hydrogen fuel generator set needs to bear the load faster to reduce the flywheel pressure, the starting current slope can be appropriately increased; conversely, if the two are expected to cooperate more smoothly, the slope can be reduced. The adjustment relationship can be conceptually expressed as:

[0094] ;

[0095] Where, Represents the starting current slope of the hydrogen fuel generator set actually used in this startup after dynamic adjustment. Represents a function or algorithm logic that calculates the adjusted slope based on the input phase compensation parameters. The calculated phase compensation parameters, Represents a preset baseline or default starting current slope value. Through this step, the starting acceleration of the hydrogen fuel generator set can be personalized according to the real-time coordination needs.

[0096] When it is detected that the water electrolysis hydrogen production trigger signal is activated, the starting current slope is synchronously reduced;

[0097] Specifically, the impact of water electrolysis on the startup process is taken into account. The control system continuously monitors the status of the generated water electrolysis hydrogen production trigger signal. When the signal is detected to be in an activated state, it indicates that water electrolysis hydrogen production is currently in progress or is about to be carried out. This process consumes a certain amount of power and may introduce additional electrical disturbances on the power grid. In order to avoid the possible adverse effects of the superposition of the faster startup process of the hydrogen fuel generator set and the electrolyzer load on the stability, this method adopts a coordinated avoidance strategy. Once the hydrogen production trigger signal is detected to be in an activated state, the currently set startup current slope is reduced. The reduction range can be a fixed percentage or value, or it can be dynamically calculated based on factors such as the current electrolysis power. This ensures that during hydrogen production, the hydrogen fuel generator set starts in a smoother and more conservative manner.

[0098] The closed-loop adjustment power supply instruction set is updated according to the startup current slope.

[0099] Specifically, the starting current slope that is determined and takes into account the phase compensation requirements and the influence of the hydrogen production status is used as a key execution parameter to update the closed-loop adjustment power supply instruction set for real-time maintenance. The specific update operation is to modify the part of the instruction set related to the start-up control of the hydrogen fuel generator set, such as setting the target slope parameter of the start-up controller, or adjusting the power instruction sequence sent to the underlying drive unit so that it strictly follows the starting current slope obtained by the latest adjustment to perform power ramping. By using the final adjusted slope to update and execute instructions, it can effectively ensure that the startup process of the hydrogen fuel generator set is smoother and more controllable, especially when it is concurrent with the water electrolysis hydrogen production operation, it can significantly avoid or reduce the harmonic interference or other power quality problems that may be caused by this, and ensure high quality requirements for power supply to critical loads.

[0100] For example, assume that the starting current slope of the hydrogen fuel generator set is initially set to 150A / s based on the phase compensation parameters. At this time, it is detected that the trigger signal for hydrogen production by water electrolysis has been activated. According to the preset linkage strategy, the starting current slope needs to be reduced by 20% when hydrogen production is activated. Therefore, the control system corrects the starting current slope of the final application to Subsequently, the closed-loop adjustment power supply instruction set is updated to ensure that the control instructions sent to the hydrogen fuel cell generator set will cause its output current to climb steadily at a rate of 120A / s.

[0101] Optionally, forming a closed-loop power supply adjustment instruction set includes:

[0102] parsing the coordinated power supply correction parameter to determine a required power adjustment amount for the transition layer power supply instruction;

[0103] Specifically, this step describes in detail how to use the real-time generated collaborative power supply correction parameters to complete the closed-loop adjustment of the power supply instructions, and finally form a complete power supply instruction set reflecting the current optimal control strategy. The collaborative power supply correction parameters generated need to be analyzed and interpreted. The collaborative power supply correction parameters contain information about the deviation between the current hydrogen fuel generator set and flywheel energy storage device collaborative working state and ideal state. The control system processes the parameter through built-in analysis logic or lookup table method to extract the key quantitative index that is most directly used to guide the adjustment of the current main execution instruction, i.e. the required power adjustment amount. The required power adjustment amount clearly indicates the specific value of the total power contribution represented by the transition layer instruction that needs to be increased or decreased in order to achieve better collaboration or more accurately meet the load demand.

[0104] According to the required power adjustment amount, adjust the amplitude and duration of the transition layer power supply instruction to generate a corrected transition layer power supply instruction;

[0105] Specifically, after determining the required power adjustment amount, the control system will modify one or more key control parameters in the transition layer power supply instruction currently being executed or about to be issued according to the adjustment amount. The objects of adjustment usually include the target power amplitude set by the instruction or the effective action duration that the instruction needs to maintain. The adjustment logic can be determined according to the pre-set control strategy, for example, preferentially adjusting the power amplitude, or adjusting the duration when the amplitude reaches the limit. An exemplary adjustment relationship can be conceptually represented as:

[0106] ;

[0107] In the formula, represents the corrected transition layer power supply instruction generated after adjustment, represents the function or control logic that performs the adjustment operation, represents the original, uncorrected transition layer power supply instruction, represents the required power adjustment amount obtained by analysis.

[0108] Integrate the corrected transition layer power supply instruction, the emergency layer power supply instruction and the steady state layer power supply instruction to form a closed-loop adjustment power supply instruction set.

[0109] Specifically, the revised transition layer power supply instruction is integrated with other layers of power supply instructions that may exist at the same time, namely the currently valid emergency layer power supply instruction and steady-state layer power supply instruction. The purpose of the integration is to form a complete, consistent and prioritized instruction set at the current moment. The integration process may involve determining which layer of instructions is the currently dominant instruction based on the current overall operating mode, while instructions at other layers may be in standby, suppressed or background execution states. Through this integration and possible arbitration logic, a closed-loop adjustment power supply instruction set containing all necessary layer instructions is finally formed and output. This instruction set is the concrete embodiment of the optimal control strategy at the current moment. It will be issued to each relevant power supply unit and possible power distribution unit for precise execution, thereby realizing closed-loop adaptive energy regulation based on real-time operation feedback.

[0110] Optionally, generating the lifespan loss balance parameter includes:

[0111] Acquiring a temperature-speed correlation characteristic of a flywheel bearing of the flywheel energy storage device, and generating a first limiting threshold value according to a preset mechanical wear model;

[0112] Specifically, by assessing the health status of key components, life-loss balance parameters are generated to guide energy scheduling, aiming to balance performance and equipment life. The control system collects real-time data reflecting the mechanical state of the flywheel energy storage device, such as flywheel bearing temperature and operating speed, to obtain its temperature-speed correlation characteristic. Based on this characteristic, a preset mechanical wear model is used to assess the current wear risk and generate a first limit threshold to limit excessive flywheel use. This threshold may be related to the charge / discharge depth or the upper speed limit.

[0113] Acquiring a temperature-current correlation characteristic of a hydrogen fuel cell stack of the hydrogen fuel cell generator set, and generating a second limiting threshold value according to a preset chemical decay model;

[0114] Specifically, real-time data reflecting the chemical state of the hydrogen fuel cell stack, a core component of the hydrogen fuel cell generator set, such as stack temperature and output current, is collected to obtain its temperature-current correlation characteristic. Based on this characteristic, a preset chemical decay model is used to assess the current performance degradation risk and generate a second limit threshold for limiting excessive operation of the hydrogen fuel cell stack. This threshold may be associated with the output power or current upper limit.

[0115] The first limiting threshold and the second limiting threshold are input into a preset multi-objective optimization model to generate a flywheel charge and discharge depth constraint parameter and a hydrogen fuel output power constraint parameter that together constitute a life loss balance parameter.

[0116] Specifically, the first limit threshold and the second limit threshold, which respectively represent the operating limits of the flywheel and the hydrogen fuel cell stack in the current state, are provided as input to a preset multi-objective optimization model. The model comprehensively considers these life-related limits and other possible operating goals, and calculates a set of optimal operating constraint parameters for actual regulation, namely the flywheel charge and discharge depth constraint parameters and the hydrogen fuel output power constraint parameters. These two parameters together constitute the life loss balance parameters finally output in this step, which are used for subsequent energy management decisions, especially those affecting whether to electrolyze water to produce hydrogen, such as Figure 4 shown.

[0117] Optionally, generating a trigger signal for producing hydrogen by electrolyzing water includes:

[0118] Determining whether the redundant electric energy exceeds an upper limit value of the flywheel charge and discharge depth constraint parameter;

[0119] Specifically, this step is the decision-making process for activating the water electrolysis hydrogen production function. It integrates the current energy surplus and the health constraints of key components, embodying the integration of energy scheduling and lifespan management. The control system first evaluates the real-time energy balance based on the currently effective closed-loop power adjustment instruction set to determine whether there is redundant power available for other purposes and its amount. Simultaneously, it obtains the flywheel charge-discharge depth constraint parameter generated as part of the lifespan loss balance parameter and focuses on its upper limit, such as the maximum charge the flywheel is currently allowed to receive or the state of charge limit reached. A determination is then made to compare and determine whether the amount of redundant power exceeds the further energy storage capacity or limit allowed by the flywheel charge-discharge depth constraint parameter. This determination prioritizes satisfying the lifespan or state constraints of the flywheel component.

[0120] If the redundant electric energy exceeds the upper limit value and the output power of the current hydrogen fuel generator set is higher than the second limit threshold, a water electrolysis hydrogen production trigger signal is generated.

[0121] Specifically, only when the first judgment condition is met, that is, there is indeed redundant power and it exceeds the current constraints or storage capacity of the flywheel, the control system will then check the second condition. The real-time output power of the current hydrogen fuel generator set is obtained and compared with the second limit threshold generated by it, which is also part of the life loss balance parameter. Only when the first condition is met, the redundant power exceeds the limit, and the second condition is also met, the output power of the current hydrogen fuel generator set is higher than the second limit threshold designed to protect it, which means that it is not appropriate to increase power generation to consume the redundancy, or the current power generation load is already high, the control system will finally decide to activate the water electrolysis hydrogen production trigger signal. If any condition is not met, for example, the redundant power does not exceed the flywheel constraint, or the hydrogen fuel generator power is lower than its limit threshold, the hydrogen production trigger signal will not be activated.

[0122] For example, it is assumed that the assessment concludes that there is currently 6kWh of redundant electricity available for dispatch. At the same time, as indicated by the generated life loss balance parameter, the upper limit of the flywheel charge and discharge depth constraint parameter is to allow another 3kWh of electricity to be charged, and the second limit threshold corresponding to the hydrogen fuel output power constraint parameter is 75kW. First, it is judged that the redundant electricity of 6kWh exceeds the 3kWh upper limit that the flywheel can still accept, and the first condition is met. Then, it is monitored that the output power of the current hydrogen fuel generator set is 80kW, which is higher than the second limit threshold of 75kW, and the second condition is also met. Therefore, the control system activates the water electrolysis hydrogen production trigger signal, instructing the use of redundant electricity for hydrogen production.

[0123] Optionally, executing the water electrolysis hydrogen production trigger signal includes:

[0124] Switching the preset DC / AC inverter to the bypass mode, and rectifying the redundant electric energy and inputting it into the preset bypass electrolyzer in the form of DC;

[0125] Specifically, the specific process of executing electrolysis hydrogen production and related closed-loop regulation after receiving the trigger signal for hydrogen production by water electrolysis is described, realizing on-site conversion, storage and intelligent feedback regulation of energy. In response to the activation state of the trigger signal, the control system first adjusts the internal power flow path to distribute redundant power. This may involve controlling a preset DC / AC inverter to switch to a specific working state, such as bypass mode, in order to determine whether the available redundant power is safely directed to the hydrogen production unit. Before being input into the electrolyzer, the redundant power will undergo necessary rectification or DC / DC conversion to ensure that its voltage and current characteristics meet the input requirements of the preset bypass electrolyzer and are supplied in a stable DC form.

[0126] Detecting the hydrogen output pressure of the preset bypass electrolyzer and generating electrolysis efficiency feedback parameters;

[0127] Specifically, during the operation of hydrogen production by electrolysis of water, in order to monitor its operating efficiency, it is necessary to monitor the key operating parameters of the preset bypass electrolyzer in real time. An important monitoring indicator is the hydrogen output pressure, which can be obtained by a pressure sensor installed at the hydrogen outlet of the electrolyzer. The size of the hydrogen output pressure is related to factors such as the hydrogen production rate and storage status. Based on the real-time detected hydrogen output pressure data, and possibly combined with information such as the input electric power, the control system evaluates the current electrolysis efficiency through an internal algorithm or model, and thereby generates a quantitative electrolysis efficiency feedback parameter. This parameter reflects the actual efficiency level of the current hydrogen production process in converting electrical energy into hydrogen energy.

[0128] The electrolysis efficiency feedback parameter is linked to the closed-loop adjustment power supply instruction set to form an electric energy-hydrogen energy bidirectional closed-loop regulation mechanism.

[0129] Specifically, in order to achieve optimal management of overall energy, the electrolysis efficiency feedback parameter in this step is introduced into the main energy management control loop as an important feedback signal. The feedback parameter is used to make linkage corrections to the closed-loop adjustment power supply instruction set maintained in real time. This linkage means that the actual efficiency performance of the electrolysis hydrogen production process will react on the operating strategy of the main power supply or the allocation strategy of redundant power. For example, if the feedback parameter shows that the electrolysis efficiency is low, the control system may reduce the power allocated to the electrolyzer in the next scheduling cycle and use more energy for load or flywheel charging. On the contrary, if the efficiency is high, the hydrogen production power may be increased when conditions permit. Through this process of feeding back the electrolysis efficiency to the main control instruction and making corresponding adjustments, a dynamic electricity-hydrogen energy two-way closed-loop regulation mechanism is established, which improves the precision of energy management and the overall operational efficiency.

[0130] For example, suppose water electrolysis is initiated according to instructions for hydrogen production. After a period of operation, the hydrogen output pressure is detected to be low. Based on this, the calculated electrolysis efficiency feedback parameter indicates that the current efficiency is only 70%, below the set target efficiency of 80%. After receiving this feedback, the control system executes linkage correction logic to adjust the closed-loop power supply instruction set for the next period. This reduces the redundant power allocated to the bypass electrolyzer and redirects this energy to a short-term supplemental charge of the flywheel, thereby providing better support for subsequent load fluctuations and avoiding excessive power consumption for hydrogen production under inefficient conditions.

[0131] It should be noted that the above formulae can be converted into unitless standard values or parameters of the same dimension that can be superimposed by using the dimensional consistency principle and mathematical standardization methods (for example, normalization processing, dimensionless parameter conversion, or unit system unification), so as to eliminate the interference of different dimensions on the operation logic, make the formula have mathematical operation rationality and objective law adaptability while preserving the original data distribution characteristics. It is a conventional technical means, and will not be described here. The electrical connection between the above-mentioned units does not necessarily mean direct connection, and indirect connection can also be used as long as the purpose of the application is achieved. The above-mentioned is only an exemplary embodiment of the application, and cannot limit the scope of the application.

[0132] That is, any equivalent changes and modifications made according to the teachings of the present application are still within the scope of the present application. Other embodiments of the present application will be readily apparent to those skilled in the art upon considering the description and practice of the principles disclosed herein. The present application is intended to cover any variations, uses, or adaptive changes of the present application that follow the general principles of the present application and include common knowledge or conventional technical means in the art that are not described in the present application.

Claims

1. An energy adaptive control method for a hydrogen fuel power generation flywheel UPS system, characterized in that: The method comprises: Obtain the current load data of the UPS system and the load data in the preset historical database to generate a load demand forecast curve; Based on the load demand forecast curve and the preset flywheel response time parameters, dynamic stratification priority is performed to generate emergency layer power supply instructions, transition layer power supply instructions, and steady-state layer power supply instructions; The transition layer power supply instruction is used to trigger the start-up of the hydrogen fuel generator set, and the preset inertia compensation control signal of the flywheel energy storage device is synchronously called; The current output curve of the hydrogen fuel generator set and the inertial discharge curve of the flywheel energy storage device are collected to generate a coordinated power supply correction parameter; wherein, the generating of the coordinated power supply correction parameter comprises: extracting the power rise delay time based on the current output curve of the hydrogen fuel generator set; extracting the power decay time constant based on the inertial discharge curve of the flywheel energy storage device; inputting the power rise delay time and the power decay time constant into a PID regulator to generate a phase compensation parameter; performing a reverse superposition operation on the output timing of the hydrogen fuel generator set and the flywheel energy storage device according to the phase compensation parameter to generate the coordinated power supply correction parameter; Modifying the transition layer power supply instruction according to the coordinated power supply correction parameter to form a closed-loop adjustment power supply instruction set; Obtaining the temperature data of the hydrogen fuel cell stack of the hydrogen fuel cell generator set and the flywheel speed monitoring data of the flywheel energy storage device to generate a life loss balance parameter; wherein, generating the life loss balance parameter includes: obtaining the temperature-speed correlation characteristics of the flywheel bearing of the flywheel energy storage device, and generating a first limiting threshold according to a preset mechanical wear model; obtaining the temperature-current correlation characteristics of the hydrogen fuel cell stack of the hydrogen fuel cell generator set, and generating a second limiting threshold according to a preset chemical decay model; inputting the first limiting threshold and the second limiting threshold into a preset multi-objective optimization model to generate a flywheel charge and discharge depth constraint parameter and a hydrogen fuel output power constraint parameter that together constitute the life loss balance parameter; generating a water electrolysis hydrogen production trigger signal based on the closed-loop adjustment power supply instruction set and the life loss balance parameter; The water electrolysis hydrogen production trigger signal is executed, and the redundant electric energy in the closed-loop adjustment power supply instruction set is input into a preset bypass electrolyzer to perform a hydrogen energy storage operation.

2. The energy adaptive control method of a hydrogen fuel power generation flywheel UPS system according to claim 1 is characterized in that: Generating a load demand forecast curve includes: Monitor AC bus voltage and current in real time to generate the current instantaneous load power value; Extract load data from the preset historical database and generate load fluctuation frequency statistics; The current instantaneous load power value and the load fluctuation frequency statistic are input into a pre-trained exponential load prediction model to output a load demand prediction curve.

3. The energy adaptive control method of a hydrogen fuel power generation flywheel UPS system according to claim 1, characterized in that: The dynamic hierarchical priority includes: Obtaining a gradient change value of the load demand forecast curve, and determining a dynamic priority parameter based on the gradient change value; When the gradient change value exceeds a preset sudden increase threshold, activating the transition layer power supply instruction in advance; When the gradient change value is lower than a preset steady-state threshold, switching to the steady-state layer power supply instruction is delayed.

4. The energy adaptive control method of a hydrogen fuel power generation flywheel UPS system according to claim 1, characterized in that: Generating the phase compensation parameter comprises: Simulating the inertial output characteristics of the hydrogen fuel generator set through a preset flywheel power attenuation model; providing the difference between the inertial output characteristic of the hydrogen fuel generator set and the current output curve of the hydrogen fuel generator set as input to the proportional-integral control module of the PID regulator; The proportional-integral control module processes the output based on the input to obtain a phase compensation parameter.

5. The energy adaptive control method of a hydrogen fuel power generation flywheel UPS system according to claim 1, characterized in that: The method further comprises: Adjusting the starting current slope of the hydrogen fuel generator set according to the phase compensation parameter; When it is detected that the water electrolysis hydrogen production trigger signal is activated, the starting current slope is synchronously reduced; The closed-loop adjustment power supply instruction set is updated according to the startup current slope.

6. The energy adaptive control method of a hydrogen fuel power generation flywheel UPS system according to claim 1, characterized in that: The closed-loop power supply adjustment instruction set includes: parsing the coordinated power supply correction parameter to determine a required power adjustment amount for the transition layer power supply instruction; Adjusting the amplitude and duration of the transition layer power supply instruction according to the required power adjustment amount to generate a revised transition layer power supply instruction; The modified transition layer power supply instruction, the emergency layer power supply instruction and the steady-state layer power supply instruction are integrated to form a closed-loop adjustment power supply instruction set.

7. The energy adaptive control method of a hydrogen fuel power generation flywheel UPS system according to claim 1, characterized in that: The generating of the trigger signal for producing hydrogen by electrolysis of water comprises: Determining whether the redundant electric energy exceeds an upper limit value of the flywheel charge and discharge depth constraint parameter; If the redundant electric energy exceeds the upper limit value and the output power of the current hydrogen fuel generator set is higher than the second limit threshold, a water electrolysis hydrogen production trigger signal is generated.

8. The energy adaptive control method of a hydrogen fuel power generation flywheel UPS system according to claim 7, characterized in that: The trigger signal for executing the water electrolysis hydrogen production comprises: Switching the preset DC / AC inverter to the bypass mode, and rectifying the redundant electric energy and inputting it into the preset bypass electrolyzer in the form of DC; Detecting the hydrogen output pressure of the preset bypass electrolyzer and generating electrolysis efficiency feedback parameters; The electrolysis efficiency feedback parameter is linked to the closed-loop adjustment power supply instruction set to form an electric energy-hydrogen energy bidirectional closed-loop regulation mechanism.

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