Energy self-adaptive regulation and control method of hydrogen fuel power generation flywheel UPS (Uninterrupted Power Supply) system

Abstract

The invention discloses an energy self-adaptive regulation and control 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 steps of predicting system load requirements and dynamically generating layered power supply instructions; starting, stopping and output of the hydrogen fuel generator set and the flywheel energy storage device are cooperatively regulated and controlled, and closed-loop correction is carried out on power supply parameters; and in combination with life equilibrium state evaluation of key components, electrolytic hydrogen production and storage are completed as required by using redundant electric energy. According to the invention, a dynamic scheduling decision based on load prediction, hydrogen-flywheel hybrid energy storage collaborative optimization and an energy and state closed-loop feedback control technology are adopted, so that self-adaption and efficient management of UPS system energy and optimal configuration of multi-stage energy storage resources can be realized; and the dynamic response performance, the energy utilization efficiency and the overall power supply reliability of the uninterruptible power supply system are remarkably improved.

Description

Technical Field

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

[0002] An uninterruptible power supply system (UPS) is a core device to ensure continuous power supply for 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 day by day. When facing complex and changing load demands and longer emergency power supply times, the traditional UPS faces new challenges in its energy configuration and management strategies.

[0003] Existing uninterruptible power supply solutions often struggle to balance rapid response to sudden loads and long-term power supply. UPSs with a single energy storage medium often have limitations in terms of energy density, cycle life, or maintenance cost. In addition, under dynamic load conditions, how to achieve efficient collaborative operation of multiple power supply units and improve the overall energy utilization efficiency is also an urgent area for improvement in the current technological development. Summary of the Invention

[0004] To solve the above problems, the present invention provides an energy adaptive regulation method for a hydrogen fuel power generation flywheel UPS system. By adopting dynamic scheduling decision based on load prediction, collaborative optimization of hydrogen-flywheel hybrid energy storage, and closed-loop feedback control technology for energy and state, it can achieve adaptive and efficient management of the energy of the UPS system and optimal allocation 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: An energy adaptive regulation method for a hydrogen fuel power generation flywheel UPS system, comprising obtaining the current load data of the UPS system and the load data in a preset historical database to generate a load demand prediction curve; performing dynamic hierarchical prioritization 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; triggering the start of a hydrogen fuel power generation set by using the transition layer power supply instruction and synchronously invoking a preset inertial compensation control signal of a flywheel energy storage device; collecting the current output curve of the hydrogen fuel power generation set and the inertial discharge curve of the flywheel energy storage device to generate a cooperative power supply correction parameter; correcting the transition layer power supply instruction according to the cooperative power supply correction parameter to form a closed-loop adjusted power supply instruction set; obtaining the hydrogen fuel cell stack temperature data of the hydrogen fuel power generation set and the flywheel speed monitoring data of the flywheel energy storage device to generate a life loss balance parameter; generating an electrolyzed water hydrogen production trigger signal based on the closed-loop adjusted power supply instruction set and the life loss balance parameter; executing the electrolyzed water hydrogen production trigger signal and inputting the redundant electric energy in the closed-loop adjusted power supply instruction set into a preset bypass electrolyzer for hydrogen energy storage operation.

[0006] Optionally, the generating of the load demand prediction curve includes: real-time monitoring of the AC bus voltage and current to generate a current instantaneous load power value; extracting the load data in a preset historical database to generate a load fluctuation frequency statistic; inputting the current instantaneous load power value and the load fluctuation frequency statistic into a pre-trained exponential load prediction model and outputting a load demand prediction curve.

[0007] Optionally, the performing of the dynamic hierarchical prioritization includes: obtaining a gradient change value of the load demand prediction 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, delaying the switch to the steady state layer power supply instruction.

[0008] Optionally, the generating of the cooperative power supply correction parameter includes: extracting a power rise delay time based on the current output curve of the hydrogen fuel power generation set; extracting a 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 timings of the hydrogen fuel power generation set and the flywheel energy storage device according to the phase compensation parameter to generate a cooperative power supply correction parameter.

[0009] Optionally, the generation of the phase compensation parameter includes: simulating the inertial output characteristics of the hydrogen fuel power generation set through a preset flywheel power attenuation model; using the difference between the inertial output characteristics of the hydrogen fuel power generation set and the current output curve of the hydrogen fuel power generation set as an input to be provided to the proportional-integral control module of the PID regulator; and obtaining the phase compensation parameter through the processing and output of the proportional-integral control module based on the input.

[0010] Optionally, the method further includes: adjusting the starting current slope of the hydrogen fuel power generation set according to the phase compensation parameter; synchronously reducing the starting current slope when it is detected that the electrolytic water hydrogen production trigger signal is activated; and updating the closed-loop adjusted power supply instruction set according to the starting current slope.

[0011] Optionally, the formation of the closed-loop adjusted power supply instruction set includes: analyzing the collaborative power supply correction parameter to determine the required power adjustment amount for the power supply instruction of the transition layer; adjusting the amplitude and duration of the power supply instruction of the transition layer according to the required power adjustment amount to generate a corrected power supply instruction of the transition layer; and integrating the corrected power supply instruction of the transition layer, the emergency layer power supply instruction, and the steady-state layer power supply instruction to form a closed-loop adjusted power supply instruction set.

[0012] Optionally, the generation of the life loss balance parameter includes: obtaining the temperature-rotation speed correlation characteristics of the flywheel bearing of the flywheel energy storage device and generating a first limit threshold according to a preset mechanical wear model; obtaining the temperature-current correlation characteristics of the hydrogen fuel cell stack of the hydrogen fuel power generation set and generating a second limit threshold according to a preset chemical decay model; and inputting the first limit threshold and the second limit 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 jointly constitute the life loss balance parameter.

[0013] Optionally, the generation of the electrolytic water hydrogen production trigger signal includes: determining whether the redundant electric energy exceeds the upper limit value of the flywheel charge and discharge depth constraint parameter; and generating an electrolytic water hydrogen production trigger signal if the redundant electric energy exceeds the upper limit value and the output power of the current hydrogen fuel power generation set is higher than the second limit threshold.

[0014] Optionally, the execution of the electrolytic water hydrogen production trigger signal includes: switching a preset DC / AC inverter to a bypass mode, rectifying the redundant electric energy, and inputting it in a DC form into a preset bypass electrolytic cell; detecting the hydrogen output pressure of the preset bypass electrolytic cell to generate an electrolysis efficiency feedback parameter; and jointly correcting the electrolysis efficiency feedback parameter and the closed-loop adjusted power supply instruction set to form a two-way closed-loop regulation mechanism for electric energy and hydrogen energy.

[0015] Compared with the prior art, the present invention has the following advantages: 1. By integrating flywheel energy storage with fast response and hydrogen fuel power generation with long-duration power supply, and combining precise prediction of load demand for dynamic priority scheduling and instruction generation, precise and efficient response to various power disturbances and power outage events of different durations is achieved. This method can instantaneously compensate for power gaps and suppress load fluctuations using flywheel energy storage, and ensure persistent and stable power supply for critical loads by hydrogen fuel generator sets. Compared with the traditional UPS system with a single energy storage medium, it significantly enhances the fast response ability and uninterruptible power supply reliability under complex operating conditions with a wide dynamic range; 2. A closed-loop collaborative control mechanism based on the actual operating states of hydrogen fuel generator sets and flywheel energy storage devices is constructed. By real-time collecting key operating parameters and generating collaborative power supply correction parameters, dynamic optimization and closed-loop adjustment of multi-level power supply instructions are carried out. This method can instantaneously feedback and adaptively adjust the output strategies and cooperation time sequences of each energy unit. Compared with traditional schemes that rely on fixed control logic or open-loop control, it significantly improves the energy conversion and utilization efficiency, and enhances the adaptability and robustness of the entire power supply system to changes in operating conditions; 3. A life loss equalization management strategy for key components is introduced, and the in-situ hydrogen production and storage functions of redundant electric energy are combined. By monitoring equipment operating condition data and generating life loss balance parameters to guide energy scheduling and the electrolysis water hydrogen production process, it can not only actively balance the operating loads of core energy storage and power generation units and effectively extend their service lives, but also efficiently convert surplus electric energy into hydrogen fuel for storage under specific operating conditions, thereby improving the energy self-sustaining ability, operating economy and reducing the dependence on externally purchased hydrogen.

[0016] Other features and advantages of the present invention will be described in the following specification, and, in part, will become apparent from the specification or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be realized and obtained by the structures pointed out in the specification, claims and drawings. Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 It is a schematic flowchart of an energy adaptive control method for a hydrogen fuel power generation flywheel UPS system according to an embodiment of the present invention.

[0019] Figure 2It is the load demand prediction curve graph of the embodiment of the present invention.

[0020] Figure 3 It is the collaborative response curve graph of the hydrogen fuel power generation unit and the flywheel energy storage device of the embodiment of the present invention.

[0021] Figure 4 It is the 2D constraint region graph for generating the life loss balance parameter of the embodiment of the present invention. Detailed implementation manners

[0022] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0023] Refer to Figure 1 , an embodiment of the present invention proposes an energy adaptive regulation method for a hydrogen fuel power generation flywheel UPS system. By adopting dynamic scheduling decision-making based on load prediction, collaborative optimization of hydrogen-flywheel hybrid energy storage, and closed-loop feedback control technology for energy and state, it can achieve the adaptive and efficient management of the energy of the UPS system and the optimal allocation of multi-level energy storage resources, and significantly improve the dynamic response performance, energy utilization efficiency and overall power supply reliability of the uninterruptible power supply system.

[0024] The method of this embodiment specifically includes: Obtain the current load data of the UPS system and the load data in the preset historical database, and generate a load demand prediction curve; Specifically, this step aims to master the current state and historical change law of the load of the UPS system. By monitoring real-time load information and combining historical data records, prediction technology is used to generate a demand prediction curve that can reflect future load trends, providing a forward-looking basis for subsequent energy scheduling.

[0025] Based on the load demand prediction curve and the preset flywheel response time parameter, perform dynamic hierarchical prioritization to generate an emergency layer power supply instruction, a transition layer power supply instruction, and a steady state layer power supply instruction; Specifically, according to the generated load demand prediction curve and the characteristic parameters of the fast-response energy storage unit such as the flywheel, this step performs dynamic priority evaluation. According to the evaluation results, different power supply scenarios are divided into different priority levels, and corresponding emergency layer, transition layer, and steady state layer power supply instructions are generated to form a preliminary and differentiated power supply strategy.

[0026] Trigger the start of the hydrogen fuel power generation unit using the power supply instruction of the transition layer, and simultaneously call the preset inertial compensation control signal of the flywheel energy storage device; Specifically, when long-term power supply or power support is required, start the hydrogen fuel power generation unit according to the power supply instruction of the transition layer to enter the power generation preparation state. At the same time, to ensure a smooth power transition, this instruction will simultaneously call the inertial compensation power issued by the flywheel energy storage device to achieve the coordinated cooperation of the two.

[0027] Collect the current output curve of the hydrogen fuel power generation unit and the inertial discharge curve of the flywheel energy storage device to generate a coordinated power supply correction parameter; Specifically, during the coordinated operation of the hydrogen fuel power generation unit and the flywheel energy storage device, the actual power output or relevant operation data of the two are collected in real time to form their respective output characteristic curves. By analyzing these actual operation data, the coordinated power supply correction parameters for closed-loop control are calculated and generated.

[0028] Correct the power supply instruction of the transition layer according to the coordinated power supply correction parameter to form a closed-loop adjusted power supply instruction set; Specifically, apply the generated coordinated power supply correction parameter to the power supply control logic to dynamically adjust the currently executed power supply instruction of the transition layer. The corrected instruction and other hierarchical instructions together form a real-time updated closed-loop adjusted power supply instruction set to adapt to changing working conditions.

[0029] Obtain the hydrogen fuel cell stack temperature data of the hydrogen fuel power generation unit and the flywheel speed monitoring data of the flywheel energy storage device to generate a life loss balance parameter; Specifically, to achieve equipment health management, this step obtains in real time the key state monitoring data of the core components of the hydrogen fuel power generation unit, such as the hydrogen fuel cell stack and the flywheel energy storage device, such as temperature and speed. Based on these data, the life loss balance parameter reflecting the current relative loss or health status of each component is calculated and generated through a life assessment model.

[0030] Generate an electrolytic water hydrogen production trigger signal based on the closed-loop adjusted power supply instruction set and the life loss balance parameter; Specifically, comprehensively consider the current energy balance state, that is, judge whether there is redundant electric energy through the closed-loop adjusted power supply instruction set, and the life loss balance status of key components, that is, evaluate according to the life loss balance parameter, and make a decision judgment. When the preset conditions are met, a trigger signal for starting the electrolytic water hydrogen production process is generated.

[0031] Execute the electrolytic water hydrogen production trigger signal, and input the redundant electric energy in the closed-loop adjusted power supply instruction set into a preset bypass electrolytic cell for hydrogen energy storage operation.

[0032] Specifically, in response to the generated electrolytic water hydrogen production trigger signal, the power conversion unit is controlled to deliver the determined redundant electric energy to a preset bypass electrolyzer device. The electrolyzer uses the input electric energy to electrolyze water to produce hydrogen, and stores the hydrogen, realizing the on-site conversion and recycling of energy.

[0033] By obtaining load information for prediction and generating hierarchical instructions, starting and coordinately controlling the hydrogen fuel generator set and the flywheel energy storage device to supply power, using real-time feedback parameters for closed-loop correction, and simultaneously monitoring the device status to generate life parameters to guide the hydrogen production decision-making and execution of redundant electric energy, a complete set of energy adaptive regulation processes is formed. This method can give full play to the complementary advantages of long-term power supply of hydrogen fuel and fast response of the flywheel, and achieve intelligent, efficient, and reliable response to complex working conditions.

[0034] Optionally, the generation of the load demand prediction curve includes: Real-time monitoring of the AC bus voltage and current to generate the current instantaneous load power value; Specifically, in order to achieve accurate prediction of the load demand, this embodiment first needs to obtain real-time and historical load basic data. Through voltage and current sensing devices deployed on the output AC bus of the uninterruptible power supply, such as a potential transformer PT and a current transformer CT, the real-time AC voltage effective value and current effective value are continuously or frequently collected. Based on these measured values and relevant power factor information, the current instantaneous load power value is calculated in real time. For example, for a three-phase balanced system, the calculation of this instantaneous active power value can be expressed as: ; In the formula, represents the current instantaneous load power value, represents the AC voltage effective value, represents the AC current effective value, represents the power factor. The calculated current instantaneous load power value accurately reflects the current actual power consumption of the load.

[0035] Extracting the load data from the preset historical database to generate a load fluctuation frequency statistic; Specifically, the control system extracts the load power time series data within a preset time window in the past from the internal storage unit or the historical database. By performing statistical analysis on this historical data sequence, such as calculating the number of times the power fluctuation exceeds a specific threshold or analyzing its periodic characteristics, a load fluctuation frequency statistic that can characterize the regularity of historical load fluctuations is generated. This statistic helps the subsequent prediction model to grasp the dynamic characteristics of the load.

[0036] Inputting the current instantaneous load power value and the load fluctuation frequency statistic into a pre-trained exponential load prediction model, and outputting a load demand prediction curve.

[0037] Specifically, the obtained current instantaneous load power value and the load fluctuation frequency statistic are used as key input features and fed into a pre-trained exponential load prediction model. This model uses the idea of exponential weighting, combines the current load state, historical information, and fluctuation characteristics to predict the load power in the future for a period of time. An exemplary quadratic exponential smoothing model combined with trend adjustment can be used for this purpose, and its prediction logic involves updating the load level estimate and the smoothed trend estimate, and combining the fluctuation adjustment term to calculate the future prediction value. Its core calculation relationships can include the following steps: Update the smoothed load level estimate: ; Update the load trend estimate: ; Calculate the predicted load power at the k-th future time step: ; In the above formulas, the symbol definitions are as follows: and are the smoothed load level estimates at the current and previous moments respectively, and are the load trend estimates at the current and previous moments respectively, is the actual measured value of the current instantaneous load power, and are the smoothing coefficients, is the predicted load power at the k-th future step, is the adjustment function based on the prediction step k and the load fluctuation frequency statistic obtained from the above calculations. This model iteratively calculates the predicted power values at a series of future time points and finally outputs a time series curve, that is, the load demand prediction curve, as Figure 2 shown.

[0038] Exemplarily, assume that the obtained current instantaneous load power value is 210 kW, and based on historical data and the model state, the smoothed level at the previous moment is 200 kW, and the trend at the previous moment is 2 kW / 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, the smoothed level at the current moment can be obtained to be approximately 206.8 kW, and the trend at the current moment is approximately 3.44 kW / step. If the adjustment term obtained based on the calculated load fluctuation frequency statistic is +5 kW at the 5th future step, the load power predicted by the model at the 5th future step is approximately 229 kW. By performing similar calculations for different future steps, a complete load demand prediction curve can be generated.

[0039] Optionally, the dynamic hierarchical prioritization includes: Obtaining the gradient change value of the load demand prediction curve and determining the dynamic priority parameter based on the gradient change value; Specifically, this step aims to dynamically evaluate the current or upcoming power supply priority according to the change trend of the load prediction curve, and accordingly adjust the status of the key power supply instructions, providing a decision-making basis for realizing the adaptive regulation of energy. The control system first analyzes the generated load demand prediction curve and calculates its gradient change value at the current time point of concern or a certain key time period in the future. This gradient change value intuitively reflects the change rate of the predicted load power over time. A commonly used and effective method for calculating the gradient is the numerical difference method. For example, calculate the ratio of the power difference between two points on the prediction curve separated by a preset small time interval to this time interval. The calculation of this gradient change value can be expressed by the following formula: ; In the formula, represents the gradient change value evaluated at time point t, and are the predicted load power values corresponding to the future time and the current t time on the prediction curve respectively, is a preset and relatively small time interval for calculating the gradient. Based on the calculated gradient change value, the control system can determine one or a set of dynamic priority parameters. The dynamic priority parameter can be a quantified numerical value, such as directly using the calculated gradient change value itself or the value after normalization, to accurately represent the severity of the load change; it can also be a discrete status level. For example, determine the priority category according to the gradient change value falling into different preset intervals. This dynamic priority parameter will be used as a subsequent judgment condition to guide the activation or switching logic of specific power supply instructions.

[0040] When the gradient change value exceeds the preset sudden increase threshold, activate the transition layer power supply instruction in advance; Specifically, to ensure that the system can respond calmly to a rapid increase in load, the control system will compare the calculated gradient change value with a preset sudden increase threshold that represents a sharp increase in load in real time. This sudden increase threshold is a positive value, and its magnitude is set according to the specific application scenario and capabilities. If the currently calculated gradient change value is greater than the preset sudden increase threshold, it indicates that it is predicted that the load is about to or is currently experiencing a rapid and significant upward process. In this case, relying solely on the flywheel energy storage may not be sufficient to fully handle it, and a long-duration and large-capacity power source such as a hydrogen fuel generator set needs to be prepared or intervened in advance. Therefore, the control system will take an early activation operation, which means that instead of waiting for the load to actually reach the power threshold that triggers the start of the hydrogen fuel generator set, based on the predicted rapid upward trend, the previously generated transition layer power supply command for coordinating the start of the hydrogen fuel generator set and its cooperation with the flywheel is set to the active state, or the original execution time point of this command is significantly advanced. This predictive early action reserves valuable time for the preheating, start-up, and power ramping of the hydrogen fuel generator set, which helps to ensure the power supply stability and voltage quality during the load increase process.

[0041] When the gradient change value is lower than the preset steady-state threshold, the switch to the steady-state layer power supply command is delayed.

[0042] Specifically, identify the state where the load tends to be stable or decreasing in order to switch to a potentially more economical and conventional steady-state operation mode. The control system will compare the calculated gradient change value with a preset steady-state threshold that represents the load change tending to be gentle or decreasing. This steady-state threshold is usually a small positive value, zero, or a small negative value, which is used to define the steady interval of the load change. If the currently calculated gradient change value is less than the preset steady-state threshold, it indicates that the predicted load growth has slowed down significantly, tended to be stable, or even started to decline. In this case, the higher power reserve or the special hydrogen-flywheel cooperation mode maintained by the transition layer power supply command may no longer be needed. To avoid frequent switching of the control mode due to short-term load fluctuations affecting stability, 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, the switch to the steady-state layer power supply command will not be made immediately, but the state will be observed to see if it can last for a period of time. Only after confirming that the load has indeed entered a relatively stable low change rate state will the control system officially switch the dominant power supply strategy to the steady-state layer power supply command with lower priority, which usually focuses more on efficiency and economy.

[0043] Optionally, the generation of the cooperative power supply correction parameter includes: Based on the current output curve of the hydrogen fuel generator set, extract its power rise delay time; Specifically, this step aims to calculate and generate correction parameters for optimizing the collaborative power supply effect of the hydrogen fuel generator set and the flywheel energy storage device based on their respective different dynamic response characteristics, ensuring the smooth and efficient power switching and superposition processes. It is necessary to analyze and process the actual current output curve of the hydrogen fuel generator set obtained by acquisition or the power output curve converted from voltage. By identifying the time point on this curve from when the generator set receives a start or power increase command to the time point when its actual output power reaches a certain predetermined ratio, calculate the time difference between the two. Alternatively, the rising section of this curve can be fitted with a standard first-order or second-order response model to extract the time parameter representing the response speed. Through one of the above methods, the power rise delay time characterizing the inherent response lag characteristic of the hydrogen fuel generator set is finally obtained.

[0044] Based on the inertial discharge curve of the flywheel energy storage device, extract its power decay time constant; Specifically, analyze the actual output characteristic curve of the flywheel energy storage device obtained by acquisition during the inertial discharge operation. This curve can be the curve of the flywheel output power changing with time, or the curve of its rotational speed decreasing with time. The rotational speed is directly related to the 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 actually measured discharge curve data with a standard exponential decay function model or other applicable dynamic models, 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 decreases naturally with time when providing short-term power support.

[0045] Input the power rise delay time and the power decay time constant into a PID regulator to generate a phase compensation parameter; Specifically, take the two key time characteristic parameters, namely the power rise delay time of the hydrogen fuel generator set and the power decay time constant of the flywheel energy storage device, as input signals and send them into a specially configured proportional-integral-derivative regulator or a control algorithm module with similar functions. Based on the values of these two time parameters, such as their difference, ratio, or other combined relationships, this PID regulator calculates and outputs a phase compensation parameter through its internal PID operation logic, including the processing of the input signal by the proportional, integral, and derivative links. The core purpose of this phase compensation parameter is to quantify the amount of advance or lag adjustment required in the control timing to achieve the best coordination between hydrogen fuel power generation and flywheel energy storage in the time dimension. For example, to make the flywheel output peak exactly cover the low valley period of the hydrogen fuel power climb, or to make the total output after the two powers are superimposed the smoothest. This phase compensation parameter can be a specific time value, a phase angle value, or a dimensionless adjustment factor.

[0046] Perform a reverse superposition operation on the output timings of the hydrogen fuel power generation set and the flywheel energy storage device according to the phase compensation parameter to generate a coordinated power supply correction parameter.

[0047] Specifically, use the generated phase compensation parameter to guide how to adjust the expected output power curves or the timing arrangements of the control instructions of the hydrogen fuel power generation set and the flywheel energy storage device to achieve the optimal coordination effect. The reverse superposition operation here is a functional description referring to an optimization process: according to the adjustment direction and magnitude indicated by the phase compensation parameter, for example, how much earlier the flywheel needs to start or increase the initial output, perform relative translation, scaling, or deformation on the ideal output power curves of the two in the original plan on the time axis, and then superimpose the adjusted two curves to evaluate whether the total output power curve after superposition is closest to the target load demand curve and has the smallest fluctuation. The final output of this optimization operation process is the coordinated power supply correction parameter. The coordinated power supply correction parameter can be a set of specific, corrected control parameters, for example, the updated power distribution ratio, the exact time points for starting and stopping respectively, or a comprehensive correction signal or correction function that can be directly applied to the existing control instructions. This parameter will be used for actual closed-loop correction of the power supply instructions for the transition layer, as Figure 3 shown.

[0048] Optionally, the generating of the phase compensation parameter includes: Simulate the inertial output characteristics of the hydrogen fuel power generation set through a preset flywheel power decay model; Specifically, this step aims to accurately calculate the phase compensation parameter for coordinating the dynamic responses of the hydrogen fuel power generation set and the flywheel energy storage device by comparing the ideal response with the actual operation data and using the proportional-integral control strategy. To generate a benchmark for comparison, a preset flywheel power decay model is adopted. Mathematically, this model describes the characteristics of the power output over time of an ideal power source with fast response ability like the flywheel energy storage device when responding to instructions. Using this model and according to the current power instruction or expected working state of the hydrogen fuel power generation set, simulate and calculate the theoretical power output time series if the hydrogen fuel power generation set can reach this ideal fast response level. This simulation result is the inertial output characteristic of the hydrogen fuel power generation set. It constructs an idealized reference output curve without obvious delay.

[0049] Use the difference between the inertial output characteristic of the hydrogen fuel power generation set and the current output curve of the hydrogen fuel power generation set as the input and provide it to the proportional-integral control module of the PID regulator; Specifically, the inertial output characteristics of the hydrogen fuel generator set obtained through simulation are compared point by point or period by period with the actual current output curve of the hydrogen fuel generator set obtained through real-time acquisition, and the real-time difference or error signal between the two is calculated. This error signal quantifies the lag or deviation of the actual response of the hydrogen fuel generator set relative to the ideal fast response. The calculated error signal is then used as the main feedback input and provided to a specific functional unit inside the mentioned PID regulator, namely the proportional-integral control module. This module is specifically responsible for processing this error signal to generate phase compensation information.

[0050] The proportional-integral control module obtains phase compensation parameters based on the input processing output.

[0051] Specifically, the proportional-integral control module receives the input error signal and processes it using the proportional-integral control algorithm. The core of this algorithm is to consider both the magnitude of the current error and the cumulative effect of historical errors. The proportional term provides an immediate response, and the integral term helps to eliminate possible steady-state errors. This module operates on the error signal according to the set proportional gain and integral gain, and its output is the phase compensation parameter to be finally generated in this step. The calculation process of this phase compensation parameter can be represented by the standard PI control law: ; In the formula, 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 moment to the current moment t of the time integral. The proportional-integral control module continuously updates and outputs this phase compensation parameter based on the error calculated in real time, providing a key adjustment basis for achieving precise timing coordination between the hydrogen fuel generator set and the flywheel energy storage device.

[0052] Exemplarily, assume that at moment, the inertial output characteristic of the hydrogen fuel generator set obtained through simulation is 190 kW, while the actual power output measured in real time is 170 kW, then the error . Assume that the proportional gain configured by the proportional-integral control module is 0.06 and the integral gain is 0.02. If the value of the error integral term at this time is 40 kWs. Then the phase compensation parameter output by the proportional-integral control module at this moment is calculated as: seconds. This 2.0-second compensation parameter will be used in the subsequent steps to adjust the control timing of related equipment.

[0053] Optionally, the method further includes: Adjusting the starting current slope of the hydrogen fuel power generation set according to the phase compensation parameter; Specifically, refined control of the start-up process of the hydrogen fuel power generation set is introduced, as well as the linkage coordination between this control and the state of electrolytic water hydrogen production, aiming to further optimize the dynamic response characteristics and ensure the quality of the output electric energy. When the hydrogen fuel power generation set needs to start according to the power supply instruction, this method does not adopt a fixed start-up program, but uses the phase compensation parameter generated by real-time calculation to dynamically adjust the rate of increase of the output current of the hydrogen fuel power generation set during this start-up process, that is, the starting current slope. This phase compensation parameter itself reflects the timing or phase adjustment amount required for the hydrogen fuel power generation set and the flywheel energy storage device to achieve the best dynamic coordination. Based on the value of this phase compensation parameter, the control system calculates and sets a suitable starting current slope through a preset functional relationship, look-up table or control logic. For example, if the phase compensation parameter indicates that the hydrogen fuel power generation set needs to bear the load faster to relieve the flywheel pressure, the starting current slope can be appropriately increased; conversely, if a smoother cooperation between the two is desired, the slope can be decreased. This adjustment relationship can be conceptually expressed as: ; In the formula, represents the starting current slope of the hydrogen fuel power generation set actually adopted after dynamic adjustment for this start-up, represents a function or algorithm logic for calculating the adjusted slope according to the input phase compensation parameter, the calculated phase compensation parameter, represents a preset reference or default starting current slope value. Through this step, the starting acceleration of the hydrogen fuel power generation set can be personalized according to the real-time cooperation requirements.

[0054] When it is detected that the electrolytic water hydrogen production trigger signal is activated, the starting current slope is synchronously reduced; Specifically, the impact on the startup process during the electrolytic water hydrogen production operation is considered. The control system continuously monitors the status of the electrolytic water hydrogen production trigger signal generated. When this signal is detected to be in an active state, it indicates that electrolytic water hydrogen production is currently in progress or about to start. This process consumes a certain amount of power and may introduce additional electrical disturbances to the power grid. To avoid the adverse impact on stability caused by the superposition of the relatively fast startup process of the hydrogen fuel generator set and the electrolyzer load, this method adopts a coordinated avoidance strategy. Once the hydrogen production trigger signal is detected to be in an active state, the currently set startup current slope is reduced. The reduction amplitude 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.

[0055] Update the closed-loop adjusted power supply instruction set according to the startup current slope.

[0056] Specifically, the determined startup current slope that comprehensively considers the phase compensation requirements and the impact of the hydrogen production state is used as a key execution parameter to update the closed-loop adjusted power supply instruction set maintained in real time. The specific update operation is to modify the part of the instruction set related to the startup control of the hydrogen fuel generator set. For example, set the target slope parameter of the startup controller, or adjust the power instruction sequence sent to the underlying drive unit to make it strictly follow the newly adjusted startup current slope to perform power ramping. By using the finally adjusted slope to update and execute the instructions, it can effectively ensure that the startup process of the hydrogen fuel generator set is more stable and controllable. Especially when concurrent with the electrolytic water hydrogen production operation, it can significantly avoid or mitigate the harmonic interference to the UPS output voltage or other power quality problems caused thereby, and guarantee the high-quality requirements for power supply to critical loads.

[0057] Exemplarily, assume that according to the phase compensation parameter, the startup current slope of the hydrogen fuel generator set is initially set to 150 A / s. At this time, it is simultaneously detected that the electrolytic water hydrogen production trigger signal has been activated. According to the preset linkage strategy, when hydrogen production is activated, the startup current slope needs to be reduced by 20%. Therefore, the control system corrects the startup current slope finally applied to . Subsequently, update the closed-loop adjusted power supply instruction set to ensure that the control instruction sent to the hydrogen fuel generator set will make its output current ramp smoothly at a rate of 120 A / s.

[0058] Optionally, the forming of the closed-loop adjusted power supply instruction set includes: Analyze the collaborative power supply correction parameter to determine the required power adjustment amount for the power supply instruction of the transition layer; Specifically, this step details how to use the co - power supply correction parameters generated in real - time to complete the closed - loop adjustment of the power supply instruction, and finally form a complete set of power supply instructions that reflect the current optimal control strategy. It is necessary to analyze and interpret the co - power supply correction parameters to be generated. These co - power supply correction parameters contain information about the deviation between the current collaborative working state of the hydrogen fuel generator set and the flywheel energy storage device and the ideal state. The control system processes this parameter through built - in parsing logic or a look - up table method, and extracts the key quantitative indicators that are most directly used to guide the adjustment of the current main execution instruction, that is, the required power adjustment amount. This required power adjustment amount clarifies the specific value by which the total power contribution represented by the transition - layer instruction needs to be increased or decreased currently in order to achieve a better collaborative effect or more precisely meet the load demand.

[0059] Adjust the amplitude and duration of the transition - layer power supply instruction according to the required power adjustment amount to generate a corrected transition - layer power supply instruction; 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 that is currently being executed or about to be issued according to this adjustment amount. The objects of adjustment usually include the target power amplitude set by this instruction or the effective action duration that this instruction needs to maintain. The adjustment logic can be determined according to the preset control strategy. For example, the power amplitude is adjusted preferentially, or the duration is adjusted when the amplitude reaches the limit. An exemplary adjustment relationship can be conceptually expressed as: ; In the formula, represents the corrected transition - layer power supply instruction generated after adjustment, represents the function or control logic for performing the adjustment operation, represents the original transition - layer power supply instruction to be corrected, represents the required power adjustment amount obtained by parsing.

[0060] 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 adjusted power supply instruction set.

[0061] Specifically, the corrected transition layer power supply instruction is integrated with other potentially co - existing power supply instructions at the current time, namely the currently valid emergency layer power supply instruction and the steady - state layer power supply instruction. The purpose of the integration is to form a complete, consistent, and clearly prioritized instruction set at the current moment. The integration process may involve determining which layer's instruction is the currently dominant one to be executed based on the current overall operating mode, while instructions from other layers may be in a standby, inhibited, or background execution state. Through this integration and possible arbitration logic, a closed - loop adjusted power supply instruction set containing all necessary layer instructions is finally formed and output. This instruction set is a specific manifestation of the optimal control strategy at the current moment and will be sent to each relevant power supply unit and possibly the power distribution unit for precise execution, thereby achieving closed - loop adaptive energy regulation based on real - time operation feedback.

[0062] Optionally, the generation of the life loss balance parameter includes: Obtain the temperature - rotation speed correlation characteristics of the flywheel bearing of the flywheel energy storage device, and generate a first limit threshold according to a preset mechanical wear model; Specifically, by evaluating the health status of key components, a life loss balance parameter for guiding energy scheduling is generated, 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 the flywheel bearing temperature and operating speed, to obtain its temperature - rotation speed correlation characteristics. Based on this characteristic, a preset mechanical wear model is used to evaluate the current loss risk and generate a first limit threshold for restricting the over - use of the flywheel, which may be related to the charge - discharge depth or the rotation speed upper limit.

[0063] Obtain the temperature - current correlation characteristics of the hydrogen fuel cell stack of the hydrogen fuel generator set, and generate a second limit threshold according to a preset chemical decay model; Specifically, collect real - time data reflecting the chemical state of the hydrogen fuel cell stack, the core component of the hydrogen fuel generator set, such as the stack temperature and output current, to obtain its temperature - current correlation characteristics. Based on this characteristic, a preset chemical decay model is used to evaluate the current performance decay risk and generate a second limit threshold for restricting the over - operation of the hydrogen fuel cell stack, which may be related to the output power or the current upper limit.

[0064] Input the first limit threshold and the second limit threshold into a preset multi - objective optimization model to generate a flywheel charge - discharge depth constraint parameter and a hydrogen fuel output power constraint parameter that jointly constitute the life loss balance parameter.

[0065] 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 under the current state, are provided as inputs to a preset multi-objective optimization model. This model comprehensively considers these life-related limits and other possible operating objectives, 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 parameter finally output in this step, which is used for subsequent energy management decisions, especially affecting whether to perform electrolytic water hydrogen production, such as Figure 4 shown.

[0066] Optionally, the generation of the electrolytic water hydrogen production trigger signal includes: Determining whether the redundant electric energy exceeds the upper limit value of the flywheel charge and discharge depth constraint parameter; Specifically, this step is a decision-making link for determining whether to activate the electrolytic water hydrogen production function. It comprehensively considers the current energy surplus situation and the health state constraints of key components, reflecting the combination of energy scheduling and life management. The control system first evaluates the real-time energy balance based on the currently effective closed-loop adjusted power supply instruction set to determine whether there is redundant electric energy available for other purposes and its quantity. At the same time, it obtains the flywheel charge and discharge depth constraint parameter generated and used as part of the life loss balance parameter, and pays attention to its set upper limit value. For example, the maximum charge amount currently allowed for the flywheel to receive or the charge state limit value already reached. Then, a judgment is made to compare whether the determined quantity of the redundant electric energy exceeds the further energy storage space or limit allowed by the flywheel charge and discharge depth constraint parameter. This judgment gives priority to satisfying the life or state constraints of the flywheel component.

[0067] 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, an electrolytic water hydrogen production trigger signal is generated.

[0068] Specifically, only when the first judgment condition is met, that is, there is indeed redundant electric energy and it exceeds the current constraint or storage capacity of the flywheel, the control system will then check the second condition. Obtain the real-time output power of the current hydrogen fuel generator set and compare it with the second limit threshold generated and also used as part of the life loss balance parameter. Only when the first condition is met, the redundant electric energy exceeds the limit, and the second condition is also met, that is, the output power of the current hydrogen fuel generator set is higher than the second limit threshold designed to protect it, which means it is not appropriate to let it increase power generation to consume the redundant, or the current power generation load is already relatively high, will the control system finally decide to activate the electrolytic water hydrogen production trigger signal. If either condition is not met, for example, the redundant electric energy does not exceed the flywheel constraint, or the power of the hydrogen fuel generator is lower than its limit threshold, the hydrogen production trigger signal will not be activated.

[0069] Exemplarily, it is assumed that the evaluation yields that there is currently 6 kWh of redundant electric energy available for scheduling. At the same time, as indicated by the generated life loss balance parameter, the upper limit of the flywheel charge-discharge depth constraint parameter is that 3 kWh of electric energy is allowed to be recharged, and the second limit threshold corresponding to the hydrogen fuel output power constraint parameter is 75 kW. First, it is judged that the redundant electric energy of 6 kWh exceeds the upper limit of 3 kWh that the flywheel can still accept, and the first condition is satisfied. Then, it is monitored that the output power of the current hydrogen fuel generator set is 80 kW, which is higher than the second limit threshold of 75 kW, and the second condition is also satisfied. Therefore, the control system activates the electrolytic water hydrogen production trigger signal and instructs the redundant electric energy to be used for hydrogen production.

[0070] Optionally, the execution of the electrolytic water hydrogen production trigger signal includes: Switching a preset DC / AC inverter to the bypass mode, and rectifying the redundant electric energy and then inputting it into a preset bypass electrolyzer in a direct current form; Specifically, the specific process of performing electrolytic hydrogen production and related closed-loop regulation after receiving the electrolytic water hydrogen production trigger signal is described, realizing the in-situ 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 allocate the redundant electric energy. This may involve controlling a preset DC / AC inverter to switch to a specific working state, such as the bypass mode, so as to determine that the available redundant electric energy is safely directed to the hydrogen production unit. Before the redundant electric energy is input into the electrolyzer, it will undergo necessary rectification processing 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 direct current form.

[0071] Detecting the hydrogen output pressure of a preset bypass electrolyzer to generate an electrolysis efficiency feedback parameter; Specifically, during the electrolytic water hydrogen production operation, in order to monitor its operation efficiency, it is necessary to monitor the key operation parameters of a preset bypass electrolyzer in real time. An important monitoring index is the hydrogen output pressure, which can be obtained by a pressure sensor installed at the hydrogen outlet of the electrolyzer. The magnitude of the hydrogen output pressure is related to factors such as the hydrogen production rate and storage state. The control system evaluates the current electrolysis efficiency based on the real-time detected hydrogen output pressure data and may combine information such as the input electric power, and generates a quantified electrolysis efficiency feedback parameter through an internal algorithm or model. This parameter reflects the actual efficiency level of converting electric energy into hydrogen energy in the current hydrogen production process.

[0072] Linking and correcting the electrolysis efficiency feedback parameter with the closed-loop adjustment power supply instruction set to form an electric energy-hydrogen energy two-way closed-loop regulation mechanism.

[0073] 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 operation 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 operating efficiency.

[0074] For example, assume that the electrolysis of water to produce hydrogen is started according to the instruction. After running for a period of time, it is detected that the hydrogen output pressure is low, and the electrolysis efficiency feedback parameter is calculated based on this, indicating that the current efficiency is only 70%, which is lower than the set target efficiency of 80%. After receiving this feedback, the control system executes the linkage correction logic and adjusts the closed-loop adjustment power supply instruction set for the next period, reducing the redundant power share planned to be allocated to the bypass electrolyzer, and re-planning this part of energy for a short-term supplementary charging of the flywheel, in order to obtain better support in subsequent load fluctuations, while avoiding excessive consumption of electricity for hydrogen production in an inefficient state.

[0075] It should be noted that the formulas appearing above can translate physical quantities of different attributes into unitless standard values ​​or superimposable parameters of the same dimension through the principle of dimensional consistency and mathematical standardization means (such as normalization, dimensionless parameter conversion or unit system unification), so as to eliminate the interference of different dimensions on the operation logic, so that the formulas have mathematical operation rationality and objective law adaptability while retaining the distribution characteristics of the original data. It is a conventional technical means and will not be elaborated here. The electrical connection between the above-mentioned units does not necessarily mean a direct connection of the circuit. The indirect connection method can be applied to the embodiments of the present invention as long as the purpose of the present invention is achieved. The above is only an exemplary embodiment of the present invention and cannot be used to limit the scope of the present invention.

[0076] That is, any equivalent changes and modifications made according to the teachings of the present invention are still within the scope of the present invention. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present invention. This application is intended to cover any variation, use or adaptive change of the present invention, which follows the general principles of the present invention and includes common knowledge or customary technical means in the art that are not described in the present invention.

Claims

1. An energy adaptive regulation method for a hydrogen fuel power generation flywheel UPS system, characterized in that, The method includes: Obtaining the current load data of the UPS system and the load data in the preset historical database to generate a load demand prediction curve; Based on the load demand prediction curve and the preset flywheel response time parameter, performing dynamic hierarchical prioritization to generate an emergency layer power supply instruction, a transition layer power supply instruction, and a steady state layer power supply instruction; Using the transition layer power supply instruction to trigger the start of the hydrogen fuel generator set and synchronously invoking the preset inertial compensation control signal of the flywheel energy storage device; Collecting the current output curve of the hydrogen fuel generator set and the inertial discharge curve of the flywheel energy storage device to generate a collaborative power supply correction parameter; Correcting the transition layer power supply instruction according to the collaborative power supply correction parameter to form a closed-loop adjusted power supply instruction set; Obtaining the hydrogen fuel cell stack temperature data of the hydrogen fuel generator set and the flywheel speed monitoring data of the flywheel energy storage device to generate a life loss balance parameter; Based on the closed-loop adjusted power supply instruction set and the life loss balance parameter, generating an electrolytic water hydrogen production trigger signal; Executing the electrolytic water hydrogen production trigger signal and inputting the redundant electric energy in the closed-loop adjusted power supply instruction set into a preset bypass electrolytic cell for hydrogen energy storage operation.

2. The energy adaptive regulation method of a hydrogen fuel power generation flywheel UPS system according to claim 1, characterized in that The generating of the load demand prediction curve includes: Real-time monitoring of the AC bus voltage and current to generate the current instantaneous load power value; Extracting the load data in the preset historical database to generate a load fluctuation frequency statistic; Inputting the current instantaneous load power value and the load fluctuation frequency statistic into a pre-trained exponential load prediction model to output a load demand prediction curve.

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

4. The energy adaptive regulation method of a hydrogen fuel power generation flywheel UPS system according to claim 1, characterized in that The generating of the collaborative power supply correction parameter includes: Based on the current output curve of the hydrogen fuel generator set, extracting its power rise delay time; Based on the inertial discharge curve of the flywheel energy storage device, extracting its power decay time constant; Inputting the power rise delay time and the power decay time constant into a PID regulator to generate a phase compensation parameter; According to the phase compensation parameter, performing a reverse superposition operation on the output timings of the hydrogen fuel generator set and the flywheel energy storage device to generate a collaborative power supply correction parameter.

5. The energy adaptive regulation method of a hydrogen fuel power generation flywheel UPS system according to claim 4, characterized in that The generating of the phase compensation parameter includes: Simulating the inertial output characteristics of the hydrogen fuel generator set through a preset flywheel power decay model; Taking the difference between the inertial output characteristics of the hydrogen fuel generator set and the current output curve of the hydrogen fuel generator set as an input and providing it to the proportional-integral control module of the PID regulator; The proportional-integral control module outputs the phase compensation parameter based on the input processing.

6. The energy self - adaptive regulation method of a hydrogen - fuel - powered flywheel UPS system according to claim 4, characterized in that, The method further includes: Adjusting the starting current slope of the hydrogen fuel generator set according to the phase compensation parameter; When it is detected that the electrolytic water hydrogen production trigger signal is activated, synchronously reducing the starting current slope; Update the closed-loop adjusted power supply instruction set according to the startup current slope.

7. The energy self-adaptive regulation method of a hydrogen fuel power generation flywheel UPS system according to claim 1, characterized in that The formation of the closed-loop adjusted power supply instruction set includes: Analyze the collaborative power supply correction parameter to determine the required power adjustment amount for the power supply instruction of the transition layer; Adjust the amplitude and duration of the power supply instruction of the transition layer according to the required power adjustment amount to generate a corrected power supply instruction for the transition layer; Integrate the corrected power supply instruction for the transition layer, the emergency layer power supply instruction, and the steady-state layer power supply instruction to form a closed-loop adjusted power supply instruction set.

8. The energy adaptive regulation method of a hydrogen fuel power generation flywheel UPS system according to claim 1, characterized in that, The generation of the life loss balance parameter includes: Obtain the temperature-rotation speed correlation characteristics of the flywheel bearing of the flywheel energy storage device, and generate a first limit threshold according to a preset mechanical wear model; Obtain the temperature-current correlation characteristics of the hydrogen fuel cell stack of the hydrogen fuel generator set, and generate a second limit threshold according to a preset chemical decay model; Input the first limit threshold and the second limit 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 jointly constitute the life loss balance parameter.

9. The energy adaptive regulation method of a hydrogen fuel power generation flywheel UPS system according to claim 8, characterized in that The generation of the electrolytic water hydrogen production trigger signal includes: Judge whether the redundant electric energy exceeds the 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, generate an electrolytic water hydrogen production trigger signal.

10. The energy adaptive regulation method of a hydrogen fuel power generation flywheel UPS system according to claim 9, characterized in that, The execution of the electrolytic water hydrogen production trigger signal includes: Switch the preset DC / AC inverter to the bypass mode, rectify the redundant electric energy, and input it into the preset bypass electrolyzer in the form of direct current; Detect the hydrogen output pressure of the preset bypass electrolyzer to generate an electrolysis efficiency feedback parameter; Perform linkage correction on the electrolysis efficiency feedback parameter and the closed-loop adjusted power supply instruction set to form an electric energy-hydrogen energy bidirectional closed-loop regulation mechanism.

Images