Hydrogen fuel cell power generation grid-connected steady-state control method and control system

Abstract

The invention relates to the technical field of grid-connected power generation, in particular to a hydrogen fuel cell power generation grid-connected steady-state control method and system. The method comprises a data acquisition step, a power grid state prediction step, an expectation judgment step, an adjustment amplitude acquisition step, a reliability calculation step, a screening step, a sorting step, a grid connection step and a time period alternative step. The system comprises a data acquisition module, a power grid state prediction module, an expectation judgment module, an adjustment amplitude acquisition module, a reliability calculation module, a screening module, a sorting module, a grid connection module and a time period alternative module. The method has the effect of reducing the influence on the stable operation of the power grid.

Description

Technical Field

[0001] The present application relates to the technical field of grid-connected power generation, and in particular to a hydrogen fuel cell power generation grid-connected steady-state control method and control system. Background Art

[0002] With the transformation of the global energy structure, hydrogen fuel cells, as an important component of clean energy, are increasingly used in power generation and grid connection. However, how to minimize the power output of hydrogen fuel cells and minimize the impact on grid power supply equipment during grid connection is a complex and critical issue.

[0003] Traditional fuel cell grid-connected control methods often lack a comprehensive perception of the working status of the power grid, resulting in improper selection of the timing of grid connection, which in turn causes impacts on the power supply equipment of the power grid and affects the stable operation of the power grid. Summary of the invention

[0004] In order to reduce the impact on the stable operation of the power grid, the present application provides a hydrogen fuel cell power generation grid-connected steady-state control method and control system.

[0005] In the first aspect, the present application provides a hydrogen fuel cell power generation grid-connected steady-state control method, which adopts the following technical solution: A hydrogen fuel cell power generation grid-connected steady-state control method comprises the following steps: Data collection: obtain the real-time working status of the power grid, obtain the working status of hydrogen fuel cell power generation, obtain the grid connection instruction to determine the grid connection time period; Grid status prediction: Using historical data and a data-driven approach, a grid status prediction model is established to predict changes in the grid's working status during the grid-connected period; Expected judgment: Estimate the changes in the power grid that may be caused by the grid-connected operation at any time during the grid-connected period, and judge whether these changes meet the predicted change expectations or will not cause significant impacts. If so, obtain a grid-connected time point set that meets the requirements and execute the adjustment range acquisition step. Otherwise, execute the time period selection step; Adjustment range acquisition: obtain the predicted grid working state corresponding to the grid-connected time point set, compare it with the actual working state of the hydrogen fuel cell, obtain the adjustment range, and store it in association with the grid-connected time point set; Reliability calculation: Calculate the grid connection reliability based on the distance between the grid connection time point set and the grid connection instruction, the adjustment range, and the contribution to grid stability; Screening: judging whether the grid connection reliability corresponding to different grid connection time point sets is greater than a preset reliability threshold, if so, executing the sorting step, otherwise, executing the time period selection step; Sorting: Sorting is done in descending order according to the grid connection reliability, and forming a selection of grid connection opportunities; Grid connection: Select the grid connection time point with the highest grid connection reliability from the grid connection time selection set, and execute the hydrogen fuel cell grid connection; Select another time period: Send a reminder that the time period has a great impact on the power grid and is not suitable for grid connection, and pass it to the sender of the grid connection instruction.

[0006] By adopting the above technical solution, real-time information on the power grid, hydrogen fuel cells and grid-connected instructions is obtained, providing data support for subsequent analysis and decision-making. The comprehensiveness and accuracy of the data are crucial to the effectiveness of subsequent steps.

[0007] The prediction model is established using historical data to predict the changes in the working status of the power grid during the grid-connected period. This helps to understand the load conditions and stability of the power grid in advance and provide a decision-making basis for grid-connected operations.

[0008] By estimating the changes in the power grid that may be caused by the grid-connected operation and comparing them with the predicted changes, it is determined whether they meet the requirements. This step helps to avoid the adverse effects of the grid-connected operation on the power grid and ensure the safe and stable operation of the power grid.

[0009] By comparing the predicted grid operating state with the actual operating state of the hydrogen fuel cell, the adjustment range is obtained and stored in association, which helps to adjust the output of the hydrogen fuel cell before grid connection to better match the grid demand.

[0010] The grid connection reliability is calculated by comprehensively considering factors such as the grid connection time point, adjustment range, and contribution to grid stability. This step helps to quantitatively evaluate the feasibility and safety of grid connection operations. Screening and sorting are carried out according to the grid connection reliability to form a grid connection opportunity selection, which helps to select the optimal grid connection opportunity from multiple possible grid connection time points.

[0011] Selecting the grid-connected time point with the highest grid-connected reliability to execute the grid-connected operation is the final implementation link, which ensures the safety and effectiveness of the grid-connected operation.

[0012] If the current period is not suitable for grid connection, a prompt is sent and passed to the sender of the grid connection instruction. This step helps to avoid grid connection operations at inappropriate periods and protect the safety of the power grid and hydrogen fuel cells.

[0013] In general, compared with traditional grid-connected control methods, this technical solution has a higher level of intelligence and automation, can better adapt to the actual conditions of the power grid and hydrogen fuel cells, improve the safety and effectiveness of grid-connected operations, reduce the impact on power grid power supply equipment caused by incorrect selection of hydrogen fuel cell grid-connected timing, and thus reduce the impact on the stable operation of the power grid.

[0014] Optionally, after the sorting step, a damage possibility acquisition step is also provided; Damage potential acquisition: including fluctuation demand acquisition step and sequencing intervention step; Fluctuating demand acquisition: Obtain the power supply group of the current period through historical data to determine whether there is precision component power supply or high-demand power supply. If so, the intervention steps are sequenced; otherwise, the grid connection steps are executed; Sorting intervention: Optimize the set of grid-connected timings in the sorting step, eliminate grid-connected time points where precision components or high-demand power supply exist, and then execute the grid-connected step.

[0015] By adopting the above technical solution, through the "fluctuation demand acquisition" step, the system can identify whether there are loads in the power grid in the current period that have extremely high requirements for power supply stability, such as precision components or high-demand power supply equipment. These loads are extremely sensitive to voltage fluctuations, frequency changes, etc., and any slight grid disturbance may cause damage to them; the existing technology often ignores this point, and the present application actively identifies and avoids grid connection during these critical periods, thereby effectively reducing the potential threat to such loads and improving the power supply stability of the entire power grid.

[0016] The “sequencing intervention” step further ensures the safe operation of the power grid by optimizing the grid connection timing selection set and eliminating the time points with high-risk grid connection. This optimization not only considers the impact of grid connection operation on the overall stability of the power grid, but also pays special attention to the protection of critical loads. In contrast, existing technologies may pay more attention to the convenience and economy of grid connection operation, while ignoring the deep-level considerations of grid security. Through this step, the new technology solution achieves a better balance between grid connection operation and grid security.

[0017] After the introduction of the "damage potential acquisition step", the entire grid-connected control process has become more intelligent and adaptive. The system can dynamically adjust the grid-connected strategy according to the actual grid status and demand to adapt to the ever-changing grid environment. This improvement in the level of intelligence not only improves the efficiency and accuracy of grid-connected operations, but also enables the grid to better respond to emergencies and abnormal situations, enhancing the resilience and reliability of the grid.

[0018] For new energy sources such as hydrogen fuel cells, friendly and safe grid connection is the key to their widespread application. New technical solutions reduce the potential impact of new energy grid connection on the power grid by finely controlling the timing of grid connection, which helps promote the larger-scale application of new energy.

[0019] Optionally, between the fluctuating demand acquisition step and the grid connection step, a proportion determination step, a proportion intervention step and an optimization sorting step are further provided; Proportion determination: Count the power supply proportion of precision components or high-demand power supply in the power grid, and determine whether the power supply proportion is less than the set proportion threshold. If so, perform the proportion intervention step, otherwise, optimize the sorting step; Proportion intervention: According to the power supply proportion and the fluctuation range of grid connection, the reliability of the grid connection time point in the grid connection opportunity selection set in the sorting step is adjusted and re-sorted, and then the grid connection step is executed; Optimize sorting: Eliminate the grid-connected time points corresponding to the power supply proportion greater than the set proportion threshold, and then execute the grid-connected steps.

[0020] By adopting the above technical solution, the "proportion judgment step" can accurately evaluate the current power grid's demand for power supply stability by counting the proportion of precision component power supply or high-requirement power supply in the power grid. The introduction of this step enables grid-connected control to more accurately identify key loads and potential risk points in the power grid. In contrast, existing technologies often lack such refined analysis of the power supply demand of the power grid, resulting in the grid-connected control strategy being too extensive and unable to effectively cope with complex situations in the power grid.

[0021] The "proportion intervention step" adjusts the reliability of the grid connection time points in the grid connection opportunity set according to the power supply proportion and the grid connection fluctuation range, and re-orders them. The introduction of this step enables the grid connection control to flexibly adjust the grid connection strategy according to different grid conditions and needs to adapt to real-time changes in the grid; this flexibility not only helps to reduce the potential impact of grid connection operations on the grid, but also improves the grid's ability to respond to emergencies and enhances the grid's robustness and resilience.

[0022] The "optimization sorting step" further optimizes the selection of grid connection timing by eliminating the grid connection time points corresponding to the power supply ratio greater than the set ratio threshold. The introduction of this step enables the grid connection control to more strictly screen the grid connection timing to ensure that the grid connection operation will not have an adverse impact on the key loads in the power grid. In contrast, the existing technology may rely too much on fixed grid connection strategies or schedules, and lacks consideration of the real-time status of the power grid. The new technology solution realizes the intelligent and adaptive selection of grid connection timing by optimizing the sorting steps.

[0023] Overall, the newly added steps make the grid-connected control process more refined, intelligent and adaptive. These improvements not only help reduce the potential impact of grid-connected operations on the power grid, but also improve the overall performance and stability of the power grid.

[0024] Optionally, a harmonic intervention step is further provided after the optimization sorting step and the proportion intervention step; Harmonic intervention: obtain the harmonic data of hydrogen fuel cell power generation, recorded as the first harmonic, obtain the real-time harmonic data of the power grid, recorded as the second harmonic, and determine whether the first harmonic and the second harmonic match. If so, execute the harmonic determination step, otherwise, execute the time period selection step; Harmonic judgment: judge whether the first harmonic and the second harmonic are opposite, if so, execute the harmonic adjustment step, otherwise, execute the time period selection step; Harmonic adjustment: Adjust the grid connection timing selection according to the proximity between the first harmonic and the second harmonic.

[0025] By adopting the above technical solution, by obtaining the harmonic data (first harmonic) of hydrogen fuel cell power generation and the real-time harmonic data of the power grid (second harmonic), and making matching judgments, it is possible to ensure that there is a full understanding of the harmonic situation before grid connection. This preprocessing step helps to avoid grid fluctuations or instability caused by harmonic mismatch and improves the compatibility of grid connection.

[0026] In the harmonic judgment stage, if the harmonics match, but the first harmonic is opposite to the second harmonic, it means that there may be a conflict and cancellation between the two. Grid-connected operation may eliminate the harmonics of the grid itself. On the contrary, if the harmonics match or do not match and are opposite, it may be necessary to further optimize the grid-connected timing based on other factors (such as time period selection) and perform harmonic adjustment steps to avoid excessive harmonic interference when connected to the grid.

[0027] The introduction of the time period selection step means that when the harmonic conditions are not ideal, the system can intelligently select other more suitable time periods for grid connection, thereby ensuring a smooth grid connection process.

[0028] The harmonic adjustment step adjusts the grid connection timing selection according to the proximity between the first harmonic and the second harmonic. This dynamic adjustment mechanism makes the grid connection process more flexible and can be adaptively optimized according to different grid conditions.

[0029] By precisely controlling the timing of grid connection and harmonic conditions, the solution helps reduce the negative impact of grid connection on the power grid and improve the overall stability and security of the power grid.

[0030] By optimizing the grid connection process, energy waste caused by harmonic mismatch or inappropriate grid connection timing can be reduced, and the energy utilization efficiency of hydrogen fuel cell power generation can be improved; through precise grid connection control, the equipment failure rate caused by grid connection problems can also be reduced, the equipment service life can be extended, and the economic efficiency of energy utilization can be further improved.

[0031] Optionally, after the time period selection step, there are also provided a time opportunity acquisition step, a ranking recommendation step and a push step; Timing acquisition: Based on historical data, the working status of the power grid in multiple time periods is predicted, matched with the working status of the hydrogen fuel cell, and reliability calculation is performed. The total reliability value of each time period is obtained, and then the sorting recommendation step is performed; Sorting recommendation: Sort by total reliability value from large to small, and execute the push step; Push: Recommend the recommended grid-connected time period to the person who issued the grid-connected instruction according to the sorting.

[0032] By adopting the above technical solution, by predicting the working state of the power grid in multiple time periods and matching it with the working state of the hydrogen fuel cell, the solution can provide a more scientific basis for grid connection decisions based on a data-driven approach. This prediction method based on historical data helps to identify time periods that are more suitable for grid connection and improve the accuracy of grid connection decisions; the reliability calculation sub-step provides more specific indicators for the selection of grid connection timing by quantitatively evaluating the grid connection reliability of each time period, which helps to select the time period with the highest reliability and the lowest risk for grid connection among multiple feasible grid connection time periods.

[0033] The sorting recommendation sub-step sorts the total reliability value in descending order, and pushes the recommended grid-connected time periods to the grid-connection instruction issuer in the form of a clear list. This intuitive and concise presentation method helps users quickly understand and make decisions, improving user experience and satisfaction.

[0034] The push sub-step can push the recommended grid-connected time period to the user in a timely manner based on the sorting results, ensuring that the user can flexibly adjust the grid-connected plan according to the actual situation. This dynamic adjustment mechanism enhances the flexibility and adaptability of the system, enabling it to better adapt to the grid-connected needs in different scenarios.

[0035] By optimizing the timing of grid connection, the solution helps reduce energy waste and environmental pollution caused by improper grid connection. At the same time, by improving grid connection efficiency and reliability, it helps promote the widespread application of clean energy such as hydrogen energy, and promotes efficient energy utilization and sustainable development.

[0036] By accurately predicting the working status of the power grid and recommending appropriate grid-connected time periods, the solution helps reduce the negative impact of grid connection on the power grid and improve the stability and safety of grid operation; this is of great significance for ensuring the safe and stable operation of the power grid and safeguarding the public interest.

[0037] Optionally, after the ranking recommendation step, a healthy grid connection index evaluation step is also provided; Health Grid Index Assessment: including health index calculation steps and recommended intervention steps; Health index calculation: Count the number of time points that exceed the reliability threshold in each period, record it as the first number, and calculate the health grid connection index based on the first number, the sum of each reliability and the mean; Recommended intervention: According to the descending order of the healthy grid connection index, the recommended order obtained in the sorting recommendation step is adjusted, and the push step is executed.

[0038] By adopting the above technical solution, the health index calculation step calculates the healthy grid index by counting the number of time points exceeding the reliability threshold in each time period, and combining the sum and mean of the reliability; this step not only takes into account the level of reliability, but also takes into account the distribution of reliability over time, thereby more comprehensively reflecting the grid health status of each time period.

[0039] The recommended intervention step intervenes and adjusts the recommended order obtained in the sorting recommendation step according to the size of the healthy grid index; the introduction of this step makes the selection of grid connection timing more refined and accurate, and helps to select the time period with the best health and the lowest risk for grid connection among multiple feasible grid connection time periods.

[0040] The introduction of the healthy grid connection index evaluation step enables the grid connection control system to dynamically adjust the grid connection strategy according to the actual operating status of the power grid and hydrogen fuel cells; through the healthy grid connection index evaluation, the system can provide more comprehensive and accurate grid connection recommendations to the issuer of the grid connection instruction.

[0041] By optimizing the timing of grid connection and reducing energy waste and environmental pollution caused by improper grid connection, it will help promote the widespread use of clean energy such as hydrogen.

[0042] Optionally, between the health index calculation step and the intervention recommendation step, there are also provided a power demand acquisition step and a health adjustment step; Power demand acquisition: Based on historical data, obtain the peak power consumption period of the power grid, establish time intervals, delete the time periods after the time intervals, and obtain power consumption trends; Health Adjustment: Based on the electricity consumption trend and the adjustment range of the hydrogen fuel cell, the health index is intervened, and then the recommended intervention steps are executed.

[0043] By adopting the above technical solution, by obtaining the peak period of power consumption of the power grid and establishing a time interval, the time period after the peak period is deleted, thereby effectively avoiding grid connection during the high-load period of the power grid and reducing the impact on the power grid.

[0044] According to the electricity consumption trend and the adjustment range of hydrogen fuel cells, the health index is intervened to make the health index more in line with the actual grid-connected needs. The introduction of this step makes the grid-connected decision not only consider the load situation of the power grid, but also the power generation capacity and adjustment space of hydrogen fuel cells, thereby improving the practicality of the grid-connected decision.

[0045] The health adjustment step intervenes in the health index according to the electricity consumption trend and the adjustment range of the hydrogen fuel cell, and then recommends the intervention step to sort the grid connection opportunities according to the size of the health grid connection index; this combination allows the grid connection decision to take into account not only the load of the power grid and the power generation capacity of the hydrogen fuel cell, but also the health status of the grid connection opportunity, thereby enhancing the accuracy of the grid connection decision.

[0046] By avoiding grid connection during high-load periods, the problems of grid overload and energy waste caused by improper grid connection are reduced. This technical solution avoids grid connection during high-load periods or periods of poor health by comprehensively considering the health of the grid load, hydrogen fuel cell power generation capacity and grid connection timing, thereby reducing the impact and negative impact on the grid and promoting the stable operation of the grid.

[0047] Optionally, a fluctuation adjustment step is provided between the health adjustment step and the recommended intervention step; Fluctuation adjustment: including stable acquisition steps and stable intervention steps; Stable acquisition: Count the number of peaks of power consumption trends between each time point and time interval in each period, and determine whether it is greater than the set number limit. If so, perform the stable intervention step. Otherwise, delete the recommendation for the period and perform the push step. Stabilization intervention: As the number of peaks in electricity consumption trends increases, the healthy grid connection index is adjusted downward, and then the recommended intervention steps are implemented.

[0048] By adopting the above technical solution and introducing the fluctuation adjustment step, the system can respond more flexibly to changes in the power consumption trend in the power grid; whether it is a sudden increase in the number of power consumption trend peaks or other forms of fluctuations, the system can respond promptly through the two sub-steps of stable acquisition and stable intervention, thereby improving the flexibility and adaptability of the entire system; in the stable acquisition step, the system can count and analyze the number of power consumption trend peaks in each time period, each time point and time interval; this detailed data analysis helps the system to grasp the operating status of the power grid more accurately, and promptly discover and deal with potential stability problems; once the number of power consumption trend peaks exceeds the set limit, the system will execute the stable intervention step to reduce the load pressure of the power grid by lowering the healthy grid connection index, thereby further improving the stability of the power grid.

[0049] The introduction of fluctuation adjustment steps also enables the system to allocate power resources more reasonably. During peak power consumption periods, the system can lower the healthy grid connection index through stable intervention steps to reduce unnecessary power consumption, thereby ensuring power supply to key equipment and areas. During low power consumption periods, the system can adjust power output more flexibly and improve resource utilization efficiency.

[0050] Optionally, after the health adjustment step or the fluctuation adjustment step, a load forecasting step is further provided; Load forecasting: Using load forecasting algorithms, combined with historical power consumption data and current power consumption trends, forecasts the load changes of the power grid in the future; Matching optimization: Match the predicted load changes with the power generation capacity of hydrogen fuel cells, and analyze the supplementary effect of hydrogen fuel cell power generation on grid load at different grid connection time points; Adjust again: According to the matching results, adjust the grid connection timing selection set, give priority to those grid connection time points that can smooth the grid load fluctuations and improve the grid stability to the greatest extent, and then execute the recommended intervention steps.

[0051] By adopting the above technical solution, through the load forecasting algorithm, combined with historical electricity consumption data and current electricity consumption trends, the load changes of the power grid in the future period can be accurately predicted; the predicted load changes are matched with the power generation capacity of hydrogen fuel cells, and the supplementary effect of hydrogen fuel cell power generation on the power grid load at different grid-connected time points is analyzed. The introduction of this step makes the grid-connected decision not only consider the load demand of the power grid, but also the power generation capacity and supplementary effect of hydrogen fuel cells, thereby enhancing the refinement of the grid-connected decision.

[0052] According to the matching results, the grid connection timing selection set is adjusted, and priority is given to those grid connection time points that can smooth the grid load fluctuations and improve the grid stability to the greatest extent. The intelligent adjustment of this step makes the grid connection decision more in line with the actual operation needs of the grid, which helps to improve the stability and reliability of the grid.

[0053] Through load forecasting and matching optimization, the timing of grid connection and power generation of hydrogen fuel cells can be determined more accurately, thereby avoiding energy waste caused by grid connection during the low load period of the power grid; at the same time, priority is given to the grid connection time point that can smooth the grid load fluctuations to the greatest extent, which helps to achieve efficient use of hydrogen fuel cell power generation and improve energy utilization efficiency.

[0054] The introduction of load intervention steps makes the grid connection decision more in line with the actual operation needs of the power grid, which helps to reduce grid load fluctuations and improve grid stability; especially during peak grid load periods or periods of large load fluctuations, by reasonably selecting the grid connection time point, effective supplementation and smoothing of the grid load can be achieved, which helps to improve the overall operation efficiency and stability of the power grid.

[0055] In the second aspect, the present application provides a hydrogen fuel cell power generation grid-connected steady-state control system, which adopts the following technical solution: A hydrogen fuel cell power generation grid-connected steady-state control system, comprising the following modules: Data acquisition module: used to obtain the real-time working status of the power grid, the working status of hydrogen fuel cell power generation, and the grid connection instruction to determine the grid connection period; Grid state prediction module: The input end is connected to the output end of the data acquisition module and is used to predict the working state changes of the grid during the grid connection period; Expected judgment module: the input end is connected to the output end of the grid state prediction module to judge whether the grid changes that may be caused by the grid connection operation at any time during the grid connection period meet the predicted change expectations or will not cause significant impact; Adjustment range acquisition module: the input end is connected to the output end of the expected judgment module, and is used to obtain the grid-connected adjustment range of the hydrogen fuel cell at any time during the grid-connected period, and store it in association with the corresponding grid-connected time point set; Reliability calculation module: the input end is connected to the output end of the adjustment amplitude acquisition module, and is used to calculate the grid connection reliability; Screening module: the input end is connected to the output end of the reliability calculation module, and is used to determine whether the grid connection reliability corresponding to different grid connection time point sets is greater than a preset reliability threshold; Sorting module: The input end is connected to the output end of the screening module, and is used to sort the grid-connected reliability corresponding to different grid-connected time points from large to small when the grid-connected reliability is greater than a preset reliability threshold, and form a grid-connected opportunity selection set; Grid connection module: the input end is connected to the output end of the sorting module, and is used to select the grid connection time point with the first priority grid connection reliability from the grid connection opportunity selection set, and execute the hydrogen fuel cell grid connection; Time period selection module: connected to the output end of the input filtering module, used to send a prompt that the time period has a great impact on the power grid and is not suitable for grid connection when the grid connection reliability corresponding to different grid connection time point sets is less than or equal to the preset reliability threshold, and pass it to the sender of the grid connection instruction.

[0056] By adopting the above technical solution, the data acquisition module starts working to collect the real-time working status of the power grid (such as voltage, current, frequency, etc.), the power generation working status of the hydrogen fuel cell (such as output power, temperature, humidity, etc.), and receive the grid-connected instruction to determine the expected grid-connected time period; the grid state prediction module receives the output of the data acquisition module, and uses advanced prediction algorithms (such as time series analysis, machine learning, etc.) to predict the changes in the working status of the power grid during the grid-connected period, including load demand, voltage fluctuations, etc.; the expectation judgment module judges whether the grid changes that may be caused by the grid-connected operation at any time during the grid-connected period are in line with the predicted change expectations or will not cause significant impact based on the results of the grid state prediction.

[0057] The adjustment range acquisition module obtains the adjustment range of the hydrogen fuel cell grid connection during the grid connection period (such as the output power variation range, response time, etc.) based on the expected judgment, and associates this information with the corresponding grid connection time point set for storage; the reliability calculation module uses the adjustment range and other relevant parameters (such as power grid stability indicators, hydrogen fuel cell performance parameters, etc.) to calculate the reliability of the grid connection at different time points during the grid connection period; the screening module determines whether the grid connection reliability corresponding to different grid connection time point sets meets the requirements based on the preset reliability threshold; if the grid connection reliability is greater than the preset threshold, proceed to the next step; otherwise, another module is selected during the trigger period.

[0058] The sorting module sorts the grid-connected time point sets that meet the reliability requirements, and forms a grid-connected opportunity selection set according to the grid-connected reliability from large to small; the grid-connected module selects the first-ranked (i.e., the highest grid-connected reliability) grid-connected time point from the grid-connected opportunity selection set, and executes the hydrogen fuel cell grid-connected operation; if the screening module finds that the grid-connected reliability of all grid-connected time point sets is less than or equal to the preset threshold, the time period selection module sends a prompt message to the sender of the grid-connected instruction, informing that the time period has a great impact on the power grid and is not suitable for grid connection.

[0059] Through grid status prediction and expected judgment, the system can evaluate the impact of grid-connected operations on the grid in advance, avoid grid-connected operations during grid instability or load peak periods, and thus improve the safety of grid connection; the system can sort the grid-connected time points according to grid-connected reliability and select the best time for grid connection, which helps to reduce the impact of grid connection on the grid and improve the stability of the grid; by precisely controlling the timing of grid connection and the adjustment range, the system can ensure that hydrogen fuel cells are connected to the grid for power generation in the optimal state, thereby improving energy utilization efficiency.

[0060] The system integrates multiple modules such as data collection, prediction, judgment, calculation, screening, sorting and grid connection, realizing the intelligent and automated grid connection decision-making and reducing the complexity and uncertainty of manual intervention; each module of the system can be flexibly configured and expanded according to actual needs to adapt to power grids of different sizes and types and hydrogen fuel cells with different performances.

[0061] In summary, the present application includes the following beneficial technical effects: by acquiring information on the power grid, hydrogen fuel cells and grid-connected instructions in real time, data support is provided for subsequent analysis and decision-making, and the comprehensiveness and accuracy of the data are crucial to the effectiveness of subsequent steps; by using historical data to establish a prediction model to predict changes in the working state of the power grid during the grid-connected period, which helps to understand the load conditions and stability of the power grid in advance and provide a decision-making basis for grid-connected operations; by estimating the changes in the power grid that may be caused by the grid-connected operation and comparing them with the predicted expected changes to determine whether they meet the requirements, this step helps to avoid the adverse effects of the grid-connected operation on the power grid and ensure the safe and stable operation of the power grid; by comparing the predicted working state of the power grid with the actual working state of the hydrogen fuel cell, the adjustment range is obtained and stored in association, which helps to adjust the output of the hydrogen fuel cell before the grid is connected to better match the grid demand; by comprehensively considering factors such as the grid-connected time point, adjustment range, and contribution to grid stability, the grid-connected reliability is calculated. This step helps to quantitatively evaluate the feasibility and safety of the grid-connected operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 is a flow chart of the control method in Example 1 of the present application; Figure 2 is a flowchart of possible damage acquisition steps in Example 2 of the present application; Figure 3 It is a detailed flow chart of the possible damage acquisition steps in Example 2 of the present application; Figure 4 is a flow chart from the harmonic intervention step to the harmonic adjustment step in Example 2 of the present application; Figure 5 is a detailed flow chart of the healthy grid connection index evaluation step in Example 2 of the present application; Figure 6 It is a detailed flow chart of the fluctuation adjustment step in Example 2 of the present application. DETAILED DESCRIPTION

[0063] The following combination Figures 1 to 6 This application is described in further detail.

[0064] This embodiment discloses a hydrogen fuel cell power generation grid-connected steady-state control method.

[0065] Example 1: Reference Figure 1, a hydrogen fuel cell power generation grid-connected steady-state control method comprises the following steps: Data collection: obtain the real-time working status of the power grid, obtain the working status of hydrogen fuel cell power generation, obtain the grid connection instruction to determine the grid connection time period; Specifically, the real-time working status of the power grid: obtain real-time data such as voltage, current, and frequency through the power grid monitoring system; the working status of the hydrogen fuel cell: obtain output power, temperature, humidity and other parameters through the fuel cell management system (FCMS); grid connection instructions: receive grid connection requests from the dispatching center and determine the expected grid connection period.

[0066] Grid status prediction: Using historical data and a data-driven approach, a grid status prediction model is established to predict changes in the grid's working status during the grid-connected period; Specifically, the operating status data of the power grid over a period of time is collected and sorted, and a power grid status prediction model is established using machine learning algorithms (such as LSTM, GRU, etc.); current and historical data are input to predict changes in the working status of the power grid during the grid-connected period.

[0067] Expected judgment: Estimate the changes in the power grid that may be caused by the grid-connected operation at any time during the grid-connected period, and judge whether these changes meet the predicted change expectations or will not cause significant impacts. If so, obtain a grid-connected time point set that meets the requirements and execute the adjustment range acquisition step. Otherwise, execute the time period selection step; Specifically, a simulation model (PSASP, ETAP or DIgSILENT / PowerFactory) is used to simulate the impact of grid-connected operations on the power grid; the simulation steps of the simulation model are as follows: Establish a model: First, it is necessary to establish a corresponding mathematical model in the simulation software based on the actual power system structure and parameters; this includes the topological structure of the power grid, the parameters of the transmission lines, the characteristics of the generator, the distribution of the load, etc.

[0068] Input data: After the model is built, relevant operating data needs to be input, such as generator output power, load demand, line flow, etc. These data can be set based on historical data, forecast data or real-time data.

[0069] Set simulation conditions: Set the corresponding simulation conditions according to the analysis requirements. For example, you can simulate different fault conditions (such as line short circuit, generator tripping, etc.), or simulate different operation strategies (such as load transfer, generator output adjustment, etc.).

[0070] Run simulation: After setting the model and simulation conditions, start the simulation program to run. The simulation program will calculate based on the input model and data to simulate the operating status of the power system.

[0071] Analyze results: After the simulation is completed, the simulation results can be analyzed using the analysis tools provided by the simulation software; this includes looking at key indicators such as the power flow distribution, voltage levels, frequency changes, and evaluating the impact of different operating strategies on the stability of the power grid.

[0072] By comparing the simulation results with the prediction results, it was found that the difference was within an acceptable range, and a set of grid-connected time points that met the requirements was obtained.

[0073] Adjustment range acquisition: obtain the predicted grid working state corresponding to the grid-connected time point set, compare it with the actual working state of the hydrogen fuel cell, obtain the adjustment range, and store it in association with the grid-connected time point set; Specifically, the predicted working state of the power grid is compared with the actual working state of the hydrogen fuel cell; the parameters such as the output power of the hydrogen fuel cell that need to be adjusted when connected to the grid are calculated and stored in association with the grid-connected time point set.

[0074] Reliability calculation: Calculate the grid connection reliability based on the distance between the grid connection time point set and the grid connection instruction, the adjustment range, and the contribution to grid stability; Specifically, the time difference between each grid-connected time point and the time when the grid-connected instruction is issued is recorded; based on the predicted grid working status and the actual working status of the hydrogen fuel cell, the amplitude of parameters such as output power, voltage or current that need to be adjusted when connected to the grid is calculated; the degree to which the grid-connected operation improves the stability of the grid is evaluated, which may require calculations based on a simulation model of the power system.

[0075] Based on experience or expert opinion, a weight is assigned to each influencing factor, which reflects the importance of each factor to the grid reliability; the sum of the weights should be 1 to ensure the accuracy of the calculation results; the original data of each influencing factor is converted into a standardized value to eliminate the influence of different dimensions and data ranges on the calculation results. Standardization processing usually includes data normalization or standardization processing, and the specific method depends on the distribution characteristics of the data.

[0076] The grid reliability is calculated using the weighted average method. The standardized value of each influencing factor is multiplied by its corresponding weight, and then the results are added together to obtain the total grid reliability. The calculation formula is: grid reliability = Σ(standardized value of influencing factor i * weight of influencing factor i). Based on the calculation results, the grid reliability at different grid-connected time points is evaluated.

[0077] Screening: judging whether the grid connection reliability corresponding to different grid connection time point sets is greater than a preset reliability threshold, if so, executing the sorting step, otherwise, executing the time period selection step; Sorting: Sorting is done in descending order according to the grid connection reliability, and forming a selection of grid connection opportunities; Grid connection: Select the grid connection time point with the highest grid connection reliability from the grid connection time selection set, and execute the hydrogen fuel cell grid connection; Select another time period: Send a reminder that the time period has a great impact on the power grid and is not suitable for grid connection, and pass it to the sender of the grid connection instruction.

[0078] Specifically, the grid connection reliability threshold is set according to the grid operation requirements and experience, and the reliability and threshold of different grid connection time point sets are compared.

[0079] The grid connection time point set is sorted using algorithms such as quick sort and merge sort, and a grid connection opportunity selection set is formed based on the sorting results; the grid connection time point with the highest reliability is selected from the grid connection opportunity selection set; and the hydrogen fuel cell grid connection operation is performed through a dispatching center or an automatic control system.

[0080] If the reliability of all grid-connected time point sets does not meet the requirements, a prompt message is sent to suggest that the sender of the grid-connected instruction reselect the grid-connected time period or adjust the grid-connected conditions.

[0081] Example 1 of the present application calculates the grid connection reliability at each time point by predicting the working status of the grid, estimating the impact of the grid connection timing on the grid, the contribution of the grid stability and the adjustment range of the hydrogen fuel cell, and then determines the best grid connection timing based on the reliability, thereby reducing the impact on the grid and improving the stability of the grid.

[0082] Example 2: Reference Figure 2 and Figure 3 ,This embodiment is different from Embodiment 1 in that, after the sorting step, a damage possibility acquisition step is also provided; Damage potential acquisition: including fluctuation demand acquisition step and sequencing intervention step; Fluctuating demand acquisition: Obtain the power supply group of the current period through historical data to determine whether there is precision component power supply or high-demand power supply. If so, the intervention steps are sequenced; otherwise, the grid connection steps are executed; Sorting intervention: Optimize the set of grid-connected timings in the sorting step, eliminate grid-connected time points where precision components or high-demand power supply exist, and then execute the grid-connected step.

[0083] Specifically, in this sub-step, the system will use historical data to analyze the power supply groups of the power grid in the current period, especially paying attention to whether there are precision components or high-demand power supply areas with high requirements for power supply quality; if the system detects that there are such power supply needs in the current period, then it will trigger the sorting intervention step; if there is no such demand in the current period, then the system will directly execute the grid connection step.

[0084] In the sorting intervention step, the system will optimize the grid-connected time points obtained previously according to the results obtained from the fluctuating demand; specifically, the system will eliminate those grid-connected time points that conflict with the power supply of precision components or high-demand power supply periods to ensure that the grid-connected operation will not have an adverse effect on such important loads; the optimized set of grid-connected time points will be used as a reference for the final grid-connected operation, and the system will select the most appropriate grid-connected time point for grid-connected operation based on the optimized set of grid-connected time points.

[0085] Reference Figure 3 In other implementations, between the fluctuating demand acquisition step and the grid connection step, there are also provided a proportion determination step, a proportion intervention step and an optimization sorting step; Proportion determination: Count the power supply proportion of precision components or high-demand power supply in the power grid, and determine whether the power supply proportion is less than the set proportion threshold. If so, perform the proportion intervention step, otherwise, optimize the sorting step; Proportion intervention: According to the power supply proportion and the fluctuation range of grid connection, the reliability of the grid connection time point in the grid connection opportunity selection set in the sorting step is adjusted and re-sorted, and then the grid connection step is executed; Optimize sorting: Eliminate the grid-connected time points corresponding to the power supply proportion greater than the set proportion threshold, and then execute the grid-connected steps.

[0086] Specifically, the proportion of power supply to precision components or high-demand power supply in the current power grid is counted, that is, the proportion of such power supply demand in the total power supply demand, and then it is determined whether this proportion is less than the preset proportion threshold; the proportion threshold is a parameter set according to the actual situation of the power grid and the grid connection strategy, and is used to determine whether special measures are needed to deal with such power supply demand; if the result of the proportion judgment step shows that the power supply proportion is less than the set proportion threshold, but there is still a certain impact, the system will enter the proportion intervention step.

[0087] In this step, the system will comprehensively consider the power supply proportion and the grid-connected fluctuation amplitude (i.e., the degree of influence of the grid-connected operation on the grid voltage, frequency and other parameters), and adjust the reliability of the grid-connected time points obtained in the sorting step; the reliability adjustment may include increasing or decreasing the weight of the grid-connected time points, or re-sorting the priority of the grid-connected time points; the adjusted grid-connected time point set will be used as a reference for subsequent grid-connected operations; if the result of the proportion judgment step shows that the power supply proportion is greater than or equal to the set proportion threshold, it means that the current power grid has a large demand for precision component power supply or high-requirement power supply, and directly eliminate those grid-connected time points that conflict with high-precision or high-requirement power supply periods, that is, those grid-connected time points whose power supply proportion is greater than the set proportion threshold; the eliminated grid-connected time point set will be used as a reference for subsequent grid-connected operations to ensure that the grid-connected operation will not have an adverse effect on such important loads.

[0088] Reference Figure 4 In other embodiments, a harmonic intervention step is further provided after the optimization sorting step and the proportion intervention step; Harmonic intervention: obtain the harmonic data of hydrogen fuel cell power generation, recorded as the first harmonic, obtain the real-time harmonic data of the power grid, recorded as the second harmonic, and determine whether the first harmonic and the second harmonic match. If so, execute the harmonic determination step, otherwise, execute the time period selection step; Harmonic judgment: judge whether the first harmonic and the second harmonic are opposite, if so, execute the harmonic adjustment step, otherwise, execute the time period selection step; Harmonic adjustment: Adjust the grid connection timing selection according to the proximity between the first harmonic and the second harmonic.

[0089] Specifically, the harmonic data (first harmonic) of hydrogen fuel cells during power generation is collected, and the real-time harmonic data (second harmonic) of the power grid is collected; the first harmonic and the second harmonic are compared to see if they match, and the matching criteria may be based on the similarity of their parameters such as frequency and amplitude.

[0090] If the harmonics match, further determine whether the first harmonic and the second harmonic are in opposite phase. If so, perform the harmonic adjustment step to adjust the order of the grid-connected time points in the hydrogen fuel cell grid-connected timing selection set corresponding to the second harmonic. The grid-connected time points without harmonics are ranked first, and the closer the opposite second harmonic is to the first harmonic, the higher the order. If the phases are not opposite, consider selecting another time period to avoid the peak period of grid harmonics.

[0091] According to the proximity between the first harmonic and the second harmonic, the grid connection timing selection is adjusted, that is, the appropriate grid connection time or conditions are selected to reduce harmonic conflicts and improve grid connection efficiency.

[0092] For example, a hydrogen fuel cell system: a hydrogen fuel cell power generation system with a capacity of 100kW.

[0093] Power grid: A medium and low voltage distribution network with real-time harmonic monitoring capabilities.

[0094] Monitoring equipment: High-precision harmonic monitor, used to collect and record harmonic data.

[0095] Control System: Microprocessor based intelligent control system to perform the harmonic intervention process.

[0096] Harmonic data collection: A high-precision harmonic monitor is used to collect harmonic data (first harmonic) during hydrogen fuel cell power generation. The recording frequency is 50 Hz, and the main harmonic components are the 3rd, 5th, and 7th harmonics.

[0097] At the same time, real-time grid harmonic data (second harmonic) is obtained from the grid monitoring system. The recording frequency is 50 Hz, and the main harmonic components are also the 3rd, 5th, and 7th harmonics.

[0098] Harmonic matching judgment: Compare the data of the first harmonic and the second harmonic, and calculate the frequency deviation and amplitude deviation of the two; if the frequency deviation is less than 0.1Hz and the amplitude deviation of each harmonic is less than 10%, the harmonics are considered to be matched.

[0099] Harmonic judgment and execution: If the harmonics match, further compare the phases of the first harmonic and the second harmonic; if the phases differ by 180 degrees (i.e., the phases are opposite), execute the harmonic adjustment steps; if the phases are not opposite, consider selecting another time period, such as postponing the grid connection time to a period with lower grid harmonic levels.

[0100] Harmonic adjustment: According to the proximity between the first harmonic and the second harmonic, adjust the grid connection timing selection; for example, if the amplitude deviation of the third harmonic is large, you can consider adjusting the fuel cell load, or use a filter to reduce the output of this harmonic.

[0101] If the adjusted harmonic data still does not meet the grid connection requirements, continue to adjust or consider other technical means, such as using dynamic reactive power compensation devices.

[0102] Reference Figure 5 In other implementations, after the time period selection step, there are also provided an opportunity acquisition step, a ranking recommendation step and a push step; Timing acquisition: Based on historical data, the working status of the power grid in multiple time periods is predicted, matched with the working status of the hydrogen fuel cell, and reliability calculation is performed. The total reliability value of each time period is obtained, and then the sorting recommendation step is performed; Sorting recommendation: Sort by total reliability value from large to small, and execute the push step; Push: Recommend the recommended grid-connected time period to the person who issued the grid-connected instruction according to the sorting.

[0103] Specifically, the data analysis system is used to predict the grid load level, voltage stability and frequency fluctuation in each time period in the next week based on the historical grid data of the past year; the operating characteristics of the hydrogen fuel cell system, such as the power generation efficiency curve and harmonic output characteristics, are matched with the predicted grid working state to determine the output capacity of the fuel cell in each time period; the total reliability value is calculated for each matched time period, which comprehensively considers the grid load level (avoiding grid connection during peak hours), voltage stability (ensuring that voltage fluctuations are within the allowable range after grid connection), frequency fluctuations (avoiding grid connection failure caused by frequency anomalies) and the output capacity of the fuel cell (ensuring stable operation after grid connection); the matched time periods are sorted according to the size of the total reliability value to determine the optimal grid connection time period, for example, if the grid load is low, the voltage is stable, the frequency fluctuation is small, and the fuel cell output capacity is sufficient in a certain time period, then the total reliability value of the time period is high and should be recommended first; the sorted recommended grid connection time period is pushed to the grid connection instruction issuer, such as the grid dispatcher or the operation and maintenance personnel of the hydrogen fuel cell system, through the user interface of the data analysis system, and the pushed information includes the recommended time period, the total reliability value and the grid connection recommendation.

[0104] Reference Figure 5 In other embodiments, after the ranking recommendation step, a healthy grid connection index evaluation step is also provided; Health Grid Index Assessment: including health index calculation steps and recommended intervention steps; Health index calculation: Count the number of time points that exceed the reliability threshold in each period, record it as the first number, and calculate the health grid connection index based on the first number, the sum of each reliability and the mean; Recommended intervention: According to the descending order of the healthy grid connection index, the recommended order obtained in the sorting recommendation step is adjusted, and the push step is executed.

[0105] Specifically, first, the reliability data of the power grid in each time period are collected. These data may include key indicators such as voltage stability, current fluctuation, frequency deviation, etc., and a reliability threshold is set. The threshold represents the safety boundary of the power grid operation. The time point exceeding this threshold indicates that the power grid is in an unstable or potentially dangerous state; the number of time points exceeding the reliability threshold in each time period is counted, recorded as the first number; based on the first number, the sum of the reliability of all time points in each time period and the mean of the reliability, the healthy grid connection index is calculated; the calculation method may involve complex mathematical models, such as weighted average, standard deviation analysis, etc., depending on the complexity and accuracy requirements of the system design.

[0106] According to the size of the healthy grid connection index, the recommended order obtained from the sorting recommendation steps is adjusted, and time periods or areas with higher healthy grid connection indexes should be given priority attention because these time periods or areas may have greater safety hazards.

[0107] According to the adjusted recommended sequence, corresponding intervention strategies are formulated, such as adjusting grid parameters, increasing maintenance frequency, implementing preventive maintenance, etc.; the adjusted recommended sequence and intervention strategies are pushed to the grid operation and maintenance personnel or automatic control system so that timely measures can be taken to ensure the safe and stable operation of the grid.

[0108] For example, suppose a power grid system needs to evaluate its health index and formulate intervention strategies accordingly. The specific implementation steps are as follows: Data collection: Collect 24-hour grid reliability data every day in the past week, including indicators such as voltage stability, current fluctuation and frequency deviation.

[0109] Threshold setting: Set the voltage stability threshold to ±5%, the current fluctuation threshold to ±10%, and the frequency deviation threshold to ±0.2Hz.

[0110] Quantity statistics: Count the number of time points that exceed the above threshold each day to obtain the "first quantity" for each day of the week.

[0111] Calculation of healthy grid connection index: Calculate the total and mean reliability at all time points every day; Use weighted average method to combine the first quantity, the total reliability and the mean to calculate the healthy grid connection index for each day; For example, a weight coefficient can be set to weight the first quantity, the total reliability and the mean in a certain proportion to obtain the final healthy grid connection index.

[0112] Recommended intervention: Sort the healthy grid connection index from large to small to determine the time periods or areas that need priority attention; formulate targeted intervention strategies, such as adding reactive power compensation devices during periods of poor voltage stability, and strengthening line inspections in areas with large current fluctuations; push the adjusted recommended order and intervention strategies to power grid operation and maintenance personnel, requiring them to implement them as soon as possible.

[0113] Reference Figure 5 In other implementations, between the health index calculation step and the recommended intervention step, there are also provided a power demand acquisition step and a health adjustment step; Power demand acquisition: Based on historical data, obtain the peak power consumption period of the power grid, establish time intervals, delete the time periods after the time intervals, and obtain power consumption trends; Health Adjustment: Based on the electricity consumption trend and the adjustment range of the hydrogen fuel cell, the health index is intervened, and then the recommended intervention steps are executed.

[0114] Specifically, first, based on historical electricity consumption data, identify the peak period of electricity consumption in the power grid. This can usually be done through data analysis tools (such as time series analysis, machine learning models, etc.); then, establish time intervals to divide different electricity consumption periods. This time interval can be adjusted according to actual conditions to ensure the accuracy of the analysis; next, delete the time periods after the time interval. The "deletion" here actually means that the data of these time periods are not considered in subsequent analysis, because they may not belong to the peak period of electricity consumption or the period when the electricity consumption trend changes significantly; finally, based on the data of the remaining time periods, obtain the electricity consumption trend, which can be done by calculating indicators such as electricity consumption and electricity consumption growth rate.

[0115] Obtain electricity consumption trend data, which may include changes in electricity consumption, duration of peak electricity consumption, etc. Then, based on the current state and adjustment capacity of the hydrogen fuel cell, determine the power support or adjustment range that it can provide; then, combine the electricity consumption trend and the adjustment range of the hydrogen fuel cell, and use mathematical methods such as weighted average and linear regression to dynamically adjust the health index. If the electricity consumption trend shows that the grid load is high and the hydrogen fuel cell has sufficient adjustment capacity, then the health index can be appropriately lowered to reduce the load pressure on the grid. On the contrary, if the electricity consumption trend is relatively stable and the adjustment capacity of the hydrogen fuel cell is limited, then the health index can be maintained or appropriately increased; finally, use the adjusted health index as input to execute subsequent recommended intervention steps.

[0116] Reference Figure 6 , in other embodiments, a fluctuation adjustment step is further provided between the health adjustment step and the recommended intervention step; Fluctuation adjustment: including stable acquisition steps and stable intervention steps; Stable acquisition: Count the number of peaks of power consumption trends between each time point and time interval in each period, and determine whether it is greater than the set number limit. If so, perform the stable intervention step. Otherwise, delete the recommendation for the period and perform the push step. Stabilization intervention: As the number of peaks in electricity consumption trends increases, the healthy grid connection index is adjusted downward, and then the recommended intervention steps are implemented.

[0117] Specifically, first, collect electricity consumption trend data for each time period (such as every hour, every day, etc.), which includes key indicators such as electricity consumption and electricity load at each time point. For each time period, count the number of peaks in the electricity consumption trend. Peaks usually represent the high points of electricity load. A larger number may mean a greater fluctuation in the grid load and worse stability. Set a limit on the number of peaks to judge the severity of the grid load fluctuation. If the number of peaks counted is greater than the limit, it indicates that the grid load fluctuates greatly and a stabilization intervention step needs to be performed. Otherwise, the grid load is relatively stable and the recommended intervention steps can be directly performed.

[0118] The healthy grid connection index is dynamically adjusted according to the increase in the number of peaks in the electricity consumption trend, usually downward. This is because the greater the load fluctuation, the worse the stability and security of the power grid may be, and intervention strategies need to be considered more carefully.

[0119] Based on the adjusted healthy grid connection index, the recommended intervention strategy is re-evaluated and optimized, which requires increasing the monitoring frequency of the power grid, adjusting the power grid parameters, increasing the backup power supply and other measures to improve the stability and security of the power grid.

[0120] For example, taking a city power grid as an example, the specific implementation process of the fluctuation adjustment steps is explained: Data collection: Collect electricity consumption trend data for 24 hours a day over the past week, including electricity consumption and power load at each time point.

[0121] Peak count: For daily data, count the number of peaks in the power consumption trend. For example, if the power load reaches its peak at 10 a.m. and 3 p.m. on a certain day, the number of peaks is 2; Threshold judgment: Set the limit of the number of peaks to 4. If the number of peaks on a certain day is greater than 4, it is judged that the power grid load fluctuates greatly and needs to perform stabilization intervention steps; otherwise, directly perform the recommended intervention steps.

[0122] Stabilization intervention (assuming that the number of peaks on a certain day is 6): Adjustment of the healthy grid index: Since the number of peaks exceeds the limit, the healthy grid index is lowered. The extent of the reduction can be determined according to the extent to which the number of peaks exceeds the limit. For example, for every peak exceeded, the healthy grid index is lowered by a certain percentage.

[0123] Recommended intervention strategy optimization: Based on the adjusted healthy grid connection index, re-evaluate and optimize the intervention strategy. For example, increase the frequency of real-time monitoring of the power grid to ensure that potential problems can be discovered and handled in time during peak load periods; at the same time, consider adjusting power grid parameters, such as improving voltage stability and optimizing current distribution, to improve the overall stability and safety of the power grid.

[0124] Execute recommended intervention steps: According to the optimized intervention strategy, execute corresponding recommended intervention measures, such as increasing reactive power compensation, adjusting line load distribution, etc., to ensure the safe and stable operation of the power grid.

[0125] Reference Figure 6 In other embodiments, after the health adjustment step or the fluctuation adjustment step, a load forecasting step is further provided; Load forecasting: Using load forecasting algorithms, combined with historical power consumption data and current power consumption trends, forecasts the load changes of the power grid in the future; Matching optimization: Match the predicted load changes with the power generation capacity of hydrogen fuel cells, and analyze the supplementary effect of hydrogen fuel cell power generation on grid load at different grid connection time points; Adjust again: According to the matching results, adjust the grid connection timing selection set, give priority to those grid connection time points that can smooth the grid load fluctuations and improve the grid stability to the greatest extent, and then execute the recommended intervention steps.

[0126] Specifically, historical electricity consumption data is collected, including daily, weekly, monthly or annual electricity consumption, electricity load, etc. over a period of time in the past. At the same time, current electricity consumption trend data is obtained, such as real-time electricity consumption, load change rate, etc.

[0127] Use load forecasting algorithms (such as time series analysis, machine learning models, etc.) to conduct a comprehensive analysis of historical data and current trends to predict the load changes of the power grid in the future (such as the next day, week or month). The forecast results should include information such as load peaks, valleys and change trends.

[0128] Based on the technical parameters and operating status of hydrogen fuel cells, their power generation capacity at different grid-connected time points is evaluated, including the maximum, minimum, average power generation and power generation efficiency.

[0129] The predicted grid load changes are matched with the power generation capacity of hydrogen fuel cells, and the complementary effect of hydrogen fuel cell power generation on grid load at different grid-connected time points is analyzed. The goal is to find those grid-connected time points that can smooth grid load fluctuations to the greatest extent and improve grid stability.

[0130] According to the results of matching optimization, the grid connection timing selection set is adjusted, that is, the grid connection time points that can optimally smooth the grid load fluctuations and improve the grid stability are screened out; based on the adjusted grid connection timing selection set, the recommended intervention strategy is optimized.

[0131] The embodiment of the present application also discloses a hydrogen fuel cell power generation grid-connected steady-state control system.

[0132] The hydrogen fuel cell power generation grid-connected steady-state control system includes the following modules: Data acquisition module: used to obtain the real-time working status of the power grid, the working status of hydrogen fuel cell power generation, and the grid connection instruction to determine the grid connection period; Grid state prediction module: The input end is connected to the output end of the data acquisition module and is used to predict the working state changes of the grid during the grid connection period; Expected judgment module: the input end is connected to the output end of the grid state prediction module to judge whether the grid changes that may be caused by the grid connection operation at any time during the grid connection period meet the predicted change expectations or will not cause significant impact; Adjustment range acquisition module: the input end is connected to the output end of the expected judgment module, and is used to obtain the grid-connected adjustment range of the hydrogen fuel cell at any time during the grid-connected period, and store it in association with the corresponding grid-connected time point set; Reliability calculation module: the input end is connected to the output end of the adjustment amplitude acquisition module, and is used to calculate the grid connection reliability; Screening module: the input end is connected to the output end of the reliability calculation module, and is used to determine whether the grid connection reliability corresponding to different grid connection time point sets is greater than a preset reliability threshold; Sorting module: The input end is connected to the output end of the screening module, and is used to sort the grid-connected reliability corresponding to different grid-connected time points from large to small when the grid-connected reliability is greater than a preset reliability threshold, and form a grid-connected opportunity selection set; Damage potential acquisition module: the input end is connected to the output end of the sorting module, and is used to optimize and adjust the grid connection opportunity selection set according to the power supply group and power supply harmonic stability in the power supply demand; Grid connection module: the input end is connected to the output end of the damage possibility acquisition module, and is used to select the grid connection time point with the first priority grid connection reliability from the grid connection opportunity selection set, and execute the hydrogen fuel cell grid connection; Time period selection module: The input end is connected to the output end of the screening module, and is used to send a prompt that the time period has a great impact on the power grid and is not suitable for grid connection when the grid connection reliability corresponding to different grid connection time point sets is less than or equal to the preset reliability threshold, and pass it to the sender of the grid connection instruction.

[0133] Timing recommendation module: The input end is connected to the output end of the time period selection module. It is used to infer the working status of the power grid through historical data when it is not suitable for grid connection, and then match it with the working status of the hydrogen fuel cell, calculate the reliability and health index, and provide grid connection time recommendations to the issuer of the grid connection instruction based on the reliability.

[0134] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A hydrogen fuel cell power generation grid-connected steady-state control method, characterized in that: The following steps are involved: Data collection: obtain the real-time working status of the power grid, obtain the working status of hydrogen fuel cell power generation, obtain the grid connection instruction to determine the grid connection time period; Grid status prediction: Using historical data and a data-driven approach, a grid status prediction model is established to predict changes in the grid's working status during the grid-connected period; Expected judgment: Estimate the changes in the power grid that may be caused by the grid-connected operation at any time during the grid-connected period, and judge whether these changes meet the predicted change expectations or will not cause significant impacts. If so, obtain a grid-connected time point set that meets the requirements and execute the adjustment range acquisition step. Otherwise, execute the time period selection step; Adjustment range acquisition: obtain the predicted grid working state corresponding to the grid-connected time point set, compare it with the actual working state of the hydrogen fuel cell, obtain the adjustment range, and store it in association with the grid-connected time point set; Reliability calculation: Calculate the grid connection reliability based on the distance between the grid connection time point set and the grid connection instruction, the adjustment range, and the contribution to grid stability; Screening: judging whether the grid connection reliability corresponding to different grid connection time point sets is greater than a preset reliability threshold, if so, executing the sorting step, otherwise, executing the time period selection step; Sorting: Sorting is done in descending order according to the grid connection reliability, and forming a selection of grid connection opportunities; Grid connection: Select the grid connection time point with the highest grid connection reliability from the grid connection time selection set, and connect the hydrogen fuel cell to the grid; Select another time period: Send a reminder that the time period has a great impact on the power grid and is not suitable for grid connection, and pass it to the sender of the grid connection instruction.

2. The method for controlling the hydrogen fuel cell power generation grid connection according to claim 1, characterized in that: After the sorting step, a damage possible acquisition step is also provided; Damage potential acquisition: including fluctuation demand acquisition step and sequencing intervention step; Fluctuating demand acquisition: Obtain the power supply group of the current period through historical data to determine whether there is precision component power supply or high-demand power supply. If so, the intervention steps are sequenced; otherwise, the grid connection steps are executed; Sorting intervention: Optimize the set of grid-connected timings in the sorting step, eliminate grid-connected time points where precision components or high-demand power supply exist, and then execute the grid-connected step.

3. The method for controlling the hydrogen fuel cell power generation grid connection according to claim 2, characterized in that: Between the fluctuating demand acquisition step and the grid connection step, there are also a proportion judgment step, a proportion intervention step and an optimization sorting step; Proportion determination: Count the power supply proportion of precision components or high-demand power supply in the power grid, and determine whether the power supply proportion is less than the set proportion threshold. If so, perform the proportion intervention step, otherwise, optimize the sorting step; Proportion intervention: According to the power supply proportion and the fluctuation range of grid connection, the reliability of the grid connection time point in the grid connection opportunity selection set in the sorting step is adjusted and re-sorted, and then the grid connection step is executed; Optimize sorting: Eliminate the grid-connected time points corresponding to the power supply proportion greater than the set proportion threshold, and then execute the grid-connected steps.

4. The method for controlling the hydrogen fuel cell power generation grid connection according to claim 3, characterized in that: A harmonic intervention step is also provided after the optimization sorting step and the proportion intervention step; Harmonic intervention: obtain the harmonic data of hydrogen fuel cell power generation, recorded as the first harmonic, obtain the real-time harmonic data of the power grid, recorded as the second harmonic, and determine whether the first harmonic and the second harmonic match. If so, execute the harmonic determination step, otherwise, execute the time period selection step; Harmonic judgment: judge whether the first harmonic and the second harmonic are opposite, if so, execute the harmonic adjustment step, otherwise, execute the time period selection step; Harmonic adjustment: Adjust the grid connection timing selection according to the proximity between the first harmonic and the second harmonic.

5. The method for controlling the grid-connected hydrogen fuel cell power generation according to any one of claims 1 to 4, characterized in that: After the time period selection step, there are also opportunity acquisition steps, ranking recommendation steps and push steps; Timing acquisition: Based on historical data, the working status of the power grid in multiple time periods is predicted, matched with the working status of the hydrogen fuel cell, and reliability calculation is performed. The total reliability value of each time period is obtained, and then the sorting recommendation step is performed; Sorting recommendation: Sort by total reliability value from large to small, and execute the push step; Push: Recommend the recommended grid-connected time period to the person who issued the grid-connected instruction according to the sorting.

6. The method for controlling the hydrogen fuel cell power generation grid connection according to claim 5, characterized in that: After the ranking recommendation step, a healthy grid connection index evaluation step is also provided; Health Grid Index Assessment: including health index calculation steps and recommended intervention steps; Health index calculation: Count the number of time points that exceed the reliability threshold in each period, record it as the first number, and calculate the health grid connection index based on the first number, the sum of each reliability and the mean; Recommended intervention: According to the descending order of the healthy grid connection index, the recommended order obtained in the sorting recommendation step is adjusted, and the push step is executed.

7. The method for controlling the hydrogen fuel cell power generation grid connection according to claim 6, characterized in that: Between the health index calculation step and the recommended intervention step, there are also an electricity demand acquisition step and a health adjustment step; Power demand acquisition: Based on historical data, obtain the peak power consumption period of the power grid, establish time intervals, delete the time periods after the time intervals, and obtain power consumption trends; Health Adjustment: Based on the electricity consumption trend and the adjustment range of the hydrogen fuel cell, the health index is intervened, and then the recommended intervention steps are executed.

8. The method for controlling the hydrogen fuel cell power generation grid connection according to claim 7, characterized in that: Between the health adjustment step and the recommended intervention step, there is also a fluctuation adjustment step; Fluctuation adjustment: including stable acquisition steps and stable intervention steps; Stable acquisition: Count the number of peaks of power consumption trends between each time point and time interval in each period, and determine whether it is greater than the set number limit. If so, perform the stable intervention step. Otherwise, delete the recommendation for the period and perform the push step. Stabilization intervention: As the number of peaks in electricity consumption trends increases, the healthy grid connection index is adjusted downward, and then the recommended intervention steps are implemented.

9. The method for controlling the hydrogen fuel cell power generation grid connection according to claim 8, characterized in that: After the health adjustment step or the fluctuation adjustment step, a load forecasting step is also provided; Load forecasting: Using load forecasting algorithms, combined with historical power consumption data and current power consumption trends, forecasts the load changes of the power grid in the future; Matching optimization: Match the predicted load changes with the power generation capacity of hydrogen fuel cells, and analyze the supplementary effect of hydrogen fuel cell power generation on grid load at different grid connection time points; Adjust again: According to the matching results, adjust the grid connection timing selection set, give priority to those grid connection time points that can smooth the grid load fluctuations and improve the grid stability to the greatest extent, and then execute the recommended intervention steps.

10. A control system using the hydrogen fuel cell power generation grid-connected steady-state control method according to any one of claims 1 to 9, characterized in that: Includes the following modules: Data acquisition module: used to obtain the real-time working status of the power grid, the working status of hydrogen fuel cell power generation, and the grid connection instruction to determine the grid connection period; Grid state prediction module: The input end is connected to the output end of the data acquisition module and is used to predict the working state changes of the grid during the grid connection period; Expected judgment module: the input end is connected to the output end of the grid state prediction module to judge whether the grid changes that may be caused by the grid connection operation at any time during the grid connection period meet the predicted change expectations or will not cause significant impact; Adjustment range acquisition module: the input end is connected to the output end of the expected judgment module, and is used to obtain the grid-connected adjustment range of the hydrogen fuel cell at any time during the grid-connected period, and store it in association with the corresponding grid-connected time point set; Reliability calculation module: the input end is connected to the output end of the adjustment amplitude acquisition module, and is used to calculate the grid connection reliability; Screening module: the input end is connected to the output end of the reliability calculation module, and is used to determine whether the grid connection reliability corresponding to different grid connection time point sets is greater than a preset reliability threshold; Sorting module: the input end is connected to the output end of the screening module, and is used to sort the grid-connected reliability corresponding to different grid-connected time points from large to small when the grid-connected reliability is greater than a preset reliability threshold, and form a grid-connected opportunity selection set; Grid connection module: the input end is connected to the output end of the sorting module, and is used to select the grid connection time point with the first priority grid connection reliability from the grid connection opportunity selection set, and execute the hydrogen fuel cell grid connection; Time period selection module: connected to the output end of the input filtering module, used to send a prompt that the time period has a great impact on the power grid and is not suitable for grid connection when the grid connection reliability corresponding to different grid connection time point sets is less than or equal to the preset reliability threshold, and pass it to the sender of the grid connection instruction.

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