A method and control system for steady-state control of hydrogen fuel cell power generation connected to the grid

Abstract

This application relates to the technical field of grid-connected power generation, and in particular to a method and control system for steady-state control of grid-connected hydrogen fuel cell power generation. The method includes a data acquisition step, a grid state prediction step, a prediction judgment step, an adjustment range acquisition step, a reliability calculation step, a screening step, a sorting step, a grid connection step, and a time period selection step. The system includes a data acquisition module, a grid state prediction module, a prediction judgment module, an adjustment range acquisition module, a reliability calculation module, a screening module, a sorting module, a grid connection module, and a time period selection module. This application has the effect of reducing the impact on the stable operation of the power grid.

Description

Technical Field

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

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

[0003] Traditional fuel cell grid connection control methods often lack a comprehensive understanding of the grid's operating status, leading to inappropriate grid connection timing, which in turn impacts grid power supply equipment and affects the stable operation of the grid. Summary of the Invention

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

[0005] Firstly, this application provides a steady-state control method for grid-connected hydrogen fuel cell power generation, which adopts the following technical solution:

[0006] A steady-state control method for grid-connected hydrogen fuel cell power generation includes the following steps:

[0007] Data acquisition: Obtain the real-time operating status of the power grid, obtain the operating status of hydrogen fuel cell power generation, and obtain grid connection instructions to determine the grid connection period;

[0008] Power grid status prediction: Using historical data and a data-driven approach, a power grid status prediction model is established to predict changes in the operating status of the power grid during the grid connection period;

[0009] Expected judgment: Estimate the grid changes that grid connection operation at any time during the grid connection period may cause, and determine whether these changes are in line with the predicted changes or will not have a significant impact. If so, obtain the set of grid connection time points that meet the requirements and execute the adjustment range acquisition step; otherwise, execute the time period selection step.

[0010] Adjustment range acquisition: Obtain the predicted grid operating status corresponding to the grid connection time point set, compare it with the actual operating status of the hydrogen fuel cell, obtain the adjustment range, and store it in association with the corresponding grid connection time point set;

[0011] Reliability calculation: The grid connection reliability is calculated based on the distance and duration from the grid connection command issuance, the adjustment range, and the contribution to grid stability.

[0012] Filtering: Determine whether the grid connection reliability corresponding to different grid connection time point sets is greater than the preset reliability threshold. If so, execute the sorting step; otherwise, execute the time period selection step.

[0013] Sorting: Sort the grid connection reliability from highest to lowest to form a grid connection timing selection set;

[0014] Grid connection: Select the grid connection time point with the highest grid connection reliability from the grid connection time selection set, and execute the grid connection of the hydrogen fuel cell;

[0015] Select a different time period: Send a notification that the current time period has a significant impact on the power grid and is not suitable for grid connection, and pass it on to the grid connection command sender.

[0016] By adopting the above technical solution, information on the power grid, hydrogen fuel cells, and grid connection commands can be obtained in real time, providing data support for subsequent analysis and decision-making. The comprehensiveness and accuracy of the data are crucial to the effectiveness of subsequent steps.

[0017] By using historical data to build predictive models, we can predict changes in the operating status of the power grid during the grid connection period. This helps us to understand the load conditions and stability of the power grid in advance, and provides a basis for decision-making in grid connection operations.

[0018] By estimating the potential changes to the power grid caused by grid connection operations and comparing them with the predicted changes, it is determined whether the requirements are met. This step helps to avoid adverse effects on the power grid caused by grid connection operations and ensures the safe and stable operation of the power grid.

[0019] By comparing the predicted grid operating conditions with the actual operating conditions of the hydrogen fuel cell, the adjustment range can be obtained and stored in a correlated manner. This helps to adjust the output of the hydrogen fuel cell before grid connection to better match grid demand.

[0020] Taking into account factors such as grid connection time, adjustment range, and contribution to grid stability, the grid connection reliability is calculated. This step helps to quantitatively assess the feasibility and safety of grid connection operations. Based on the grid connection reliability, a selection set of grid connection opportunities is formed, which helps to select the optimal grid connection time from multiple possible grid connection time points.

[0021] Selecting the grid connection time point with the highest priority in grid connection reliability to perform the grid connection operation is the final implementation step, ensuring the safety and effectiveness of the grid connection operation.

[0022] If the current time period is not suitable for grid connection, a notification is sent and relayed to the grid connection instruction sender. This step helps avoid grid connection operations during inappropriate times, protecting the safety of the power grid and hydrogen fuel cells.

[0023] Overall, compared with traditional grid-connected control methods, this technical solution has a higher level of intelligence and automation, can better adapt to the actual situation of the power grid and hydrogen fuel cells, improve the safety and effectiveness of grid-connected operation, reduce the impact on power grid equipment caused by incorrect timing of hydrogen fuel cell grid connection, and thus reduce the impact on the stable operation of the power grid.

[0024] Optionally, a step for obtaining potentially damaged data is also provided after the sorting step;

[0025] Damage may be acquired: including the steps for acquiring fluctuating demand and the steps for sorting intervention;

[0026] Fluctuation demand acquisition: By using historical data to obtain the current grid power supply group, determine whether there is power supply for precision components or high-demand power supply. If so, sort out the intervention steps; otherwise, execute the grid connection steps.

[0027] Sequencing intervention: Optimize the grid connection timing selection set in the sequencing step, eliminate grid connection time points with precision component power supply or high demand power supply, and then execute the grid connection step.

[0028] By adopting the above technical solution and through the "fluctuation demand acquisition" step, the system can identify whether there are loads with extremely high requirements for power supply stability in the power grid during the current period, such as precision components or high-requirement power supply equipment. These loads are extremely sensitive to voltage fluctuations and frequency changes, and any slight power grid disturbance may cause damage to them. Existing technologies often overlook this point, while this application effectively reduces the potential threat to such loads and improves the power supply stability of the entire power grid by actively identifying and avoiding grid connection during these critical periods.

[0029] The "sequencing intervention" step optimizes the grid connection timing selection set, eliminating high-risk grid connection times and further ensuring the safe operation of the power grid. This optimization not only considers the impact of grid connection operations on the overall stability of the power grid, but also pays special attention to the protection of critical loads. In contrast, existing technologies may focus more on the convenience and economy of grid connection operations, while neglecting the deeper considerations of power grid security. The new technology solution achieves a better balance between grid connection operations and power grid security through this step.

[0030] With the introduction of the "damage probabilities acquisition step," the entire grid connection control process becomes more intelligent and adaptive. The system can dynamically adjust the grid connection strategy according to the actual grid status and demand to adapt to the ever-changing grid environment. This improvement in intelligence not only enhances the efficiency and accuracy of grid connection operations but also enables the grid to better cope with emergencies and abnormal situations, thereby strengthening the grid's resilience and reliability.

[0031] For new energy sources such as hydrogen fuel cells, friendly and safe grid connection is key to their widespread application. New technology solutions reduce the potential impact of new energy grid connection on the power grid by finely controlling the timing of grid connection, which helps to promote the larger-scale application of new energy sources.

[0032] Optionally, between the fluctuation demand acquisition step and the grid connection step, there are also a proportion judgment step, a proportion intervention step, and an optimization sorting step.

[0033] Proportion judgment: Statistically determine the proportion of power supply to the power grid for precision components or high-requirement components, and determine whether the power supply proportion is less than the set proportion threshold. If so, execute the proportion intervention step; otherwise, optimize the sorting step.

[0034] Proportional Intervention: Based on the power supply proportion and grid connection fluctuation range, the reliability of the grid connection timing in the sorting steps is adjusted and the grid connection time points are reordered before the grid connection steps are executed.

[0035] Optimize the sorting: Remove grid connection time points where the power supply ratio is greater than the set ratio threshold, and then execute the grid connection steps.

[0036] By adopting the above technical solution, the "proportion judgment step" can accurately assess the current power grid's demand for power supply stability by statistically analyzing the proportion of power supplied by precision components or high-requirement power supplies 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 this refined analysis of power grid demand, which may lead to grid-connected control strategies that are too coarse and unable to effectively cope with complex situations in the power grid.

[0037] The "proportion intervention step" adjusts the reliability of grid connection time points selected in the grid connection timing pool based on the power supply proportion and grid connection fluctuation amplitude, and reorders them. The introduction of this step enables grid connection control to flexibly adjust grid connection strategies according to different grid conditions and demands 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.

[0038] The "optimized sequencing step" further optimizes the selection of grid connection timing by eliminating grid connection time points where the power supply ratio exceeds a set threshold. This step allows grid connection control to more rigorously screen connection times, ensuring that grid connection operations do not adversely affect critical loads in the grid. In contrast, existing technologies may rely too heavily on fixed grid connection strategies or schedules, lacking consideration for the real-time state of the grid. The new technology solution achieves intelligent and adaptive grid connection timing selection through optimized sequencing steps.

[0039] Overall, the new steps make the grid connection control process more refined, intelligent, and adaptive. These improvements not only help reduce the potential impact of grid connection operations on the power grid, but also improve the overall performance and stability of the power grid.

[0040] Optionally, a harmonic intervention step is set after the optimization sorting step and the proportion intervention step;

[0041] Harmonic intervention: Obtain harmonic data during hydrogen fuel cell power generation, denoted as the first harmonic; obtain real-time harmonic data from the power grid, denoted as the second harmonic; determine whether the first and second harmonics match; if they match, execute the harmonic judgment step; otherwise, execute the step of selecting another time period.

[0042] Harmonic detection: Determine whether the first harmonic and the second harmonic are opposite. If they are, execute the harmonic adjustment steps; otherwise, execute the time period selection steps.

[0043] Harmonic adjustment: The grid connection timing selection set is adjusted according to the proximity of the first harmonic to the second harmonic.

[0044] By adopting the above technical solution, by acquiring the harmonic data (first harmonic) during hydrogen fuel cell power generation and the real-time harmonic data (second harmonic) of the power grid, and performing matching judgment, 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 grid connection compatibility.

[0045] During the harmonic judgment stage, if the harmonics match, but the first harmonic is opposite to the second harmonic, it indicates that there is a possibility of conflict cancellation between the two. Performing grid connection operation may eliminate the harmonics of the power grid itself. Conversely, if the harmonics match or do not match and are opposite, it may be necessary to further optimize the grid connection timing based on other factors (such as time period selection) and perform harmonic adjustment steps to avoid generating excessive harmonic interference during grid connection.

[0046] The introduction of the alternative time period selection step means that when harmonic conditions are not ideal, the system can intelligently select other more suitable time periods for grid connection, thereby ensuring the smooth progress of the grid connection process.

[0047] The harmonic adjustment steps adjust the grid connection timing selection set according to the proximity of 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.

[0048] By precisely controlling the timing of grid connection and harmonic conditions, this scheme helps reduce the negative impact of grid connection on the power grid and improves the overall stability and security of the power grid.

[0049] By optimizing the grid connection process, energy waste caused by harmonic mismatch or improper grid connection timing is reduced, thus improving the energy utilization efficiency of hydrogen fuel cell power generation. 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.

[0050] Optionally, after the time period selection step, there are also time acquisition step, sorting recommendation step and push step;

[0051] Timing acquisition: Based on historical data, predict the grid operating status for multiple time periods, match it with the operating status of the hydrogen fuel cell, perform reliability calculations, obtain the total reliability value for each time period, and then execute the sorting recommendation steps;

[0052] Sorting Recommendation: Sort the data according to the total reliability score from largest to smallest, and then execute the push notification step;

[0053] Push notification: Recommended grid connection time slots to the grid connection command issuer according to the sorting.

[0054] By adopting the above technical solution, and by predicting the grid operating status over multiple time periods and matching it with the operating status of hydrogen fuel cells, this 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 identify more suitable grid connection periods, improving the accuracy of grid connection decisions. The reliability calculation sub-step provides more specific indicators for selecting the grid connection timing by quantitatively evaluating the grid connection reliability of each time period. This helps to select the time period with the highest reliability and lowest risk among multiple feasible grid connection time periods.

[0055] The sorting recommendation sub-step sorts the grid connection time periods from highest to lowest based on the total reliability value and pushes the recommended grid connection time periods to the grid connection instruction issuer in a clear list format. This intuitive and concise presentation helps users quickly understand and make decisions, improving user experience and satisfaction.

[0056] The push sub-step can promptly deliver recommended grid connection time slots to users based on the sorting results, ensuring that users can flexibly adjust their grid connection plans according to actual conditions. This dynamic adjustment mechanism enhances the system's flexibility and adaptability, enabling it to better meet grid connection needs in different scenarios.

[0057] By optimizing the timing of grid connection, this approach 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 sources such as hydrogen energy, and promotes energy efficiency and sustainable development.

[0058] By accurately predicting the power grid's operating status and recommending suitable grid connection times, this scheme helps reduce the negative impact of grid connection on the power grid and improves the stability and security of power grid operation; this is of great significance for ensuring the safe and stable operation of the power grid and safeguarding the public interest.

[0059] Optionally, a healthy grid connection index assessment step is also set after the sorting and recommendation step;

[0060] Health Grid Connection Index Assessment: Includes health index calculation steps and recommended intervention steps;

[0061] Health Index Calculation: Count the number of time points that exceed the reliability threshold in each time period, and record it as the first number. Calculate the health grid connection index based on the first number, the sum of each reliability level, and the mean.

[0062] Recommended intervention: Based on the healthy grid connection index from largest to smallest, the recommendation order obtained in the sorting recommendation step is adjusted through intervention, and the push step is executed.

[0063] By adopting the above technical solution, the health index calculation step calculates the healthy grid connection index by counting the number of time points that exceed the reliability threshold in each time period and combining the sum and mean of the reliability. This step not only considers the level of reliability, but also the distribution of reliability over time, thus reflecting the grid connection health status of each time period more comprehensively.

[0064] The recommended intervention steps adjust the order of recommendations obtained from the ranking recommendation steps based on the size of the health grid connection index. The introduction of this step makes the selection of grid connection timing more refined and accurate, and helps to select the time with the best health and the least risk among multiple feasible grid connection time periods.

[0065] The introduction of the healthy grid connection index assessment step enables the grid connection control system to dynamically adjust the grid connection strategy based on the actual operating status of the power grid and hydrogen fuel cells. Through the healthy grid connection index assessment, the system can provide more comprehensive and accurate grid connection suggestions to the grid connection command issuer.

[0066] Optimizing grid connection timing can reduce energy waste and environmental pollution caused by improper grid connection, which will help promote the widespread application of clean energy sources such as hydrogen.

[0067] Optionally, between the health index calculation step and the recommended intervention step, an electricity demand acquisition step and a health adjustment step are also set;

[0068] Electricity demand acquisition: Based on historical data, identify peak electricity consumption periods in the power grid, establish time intervals, delete time periods after the time intervals, and obtain electricity consumption trends;

[0069] Health Adjustment: Based on electricity consumption trends and the adjustment range of hydrogen fuel cells, intervene in the health index and then implement the recommended intervention steps.

[0070] By adopting the above technical solution, the peak electricity consumption period of the power grid is obtained and a time interval is established. The 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.

[0071] Based on electricity consumption trends and the adjustment range of hydrogen fuel cells, the health index is intervened to make it more in line with actual grid connection needs. The introduction of this step means that grid connection decisions not only consider the grid load, but also the power generation capacity and adjustment space of hydrogen fuel cells, thereby improving the practicality of grid connection decisions.

[0072] The health adjustment steps intervene in the health index based on electricity consumption trends and the adjustment range of hydrogen fuel cells. Then, the recommended intervention steps are used to rank the grid connection timing based on the size of the health grid connection index. This combination ensures that grid connection decisions not only consider the grid load and the power generation capacity of hydrogen fuel cells, but also the health status of the grid connection timing, thereby enhancing the accuracy of grid connection decisions.

[0073] By avoiding grid connection during periods of high grid load, the problem of excessive grid load and energy waste caused by improper grid connection is reduced. This technical solution avoids grid connection during periods of high grid load or poor grid health by comprehensively considering grid load, hydrogen fuel cell power generation capacity, and the health status of grid connection timing, thereby reducing the impact and negative effects on the grid and promoting the stable operation of the grid.

[0074] Optionally, a fluctuation adjustment step is also provided between the health adjustment step and the recommended intervention step;

[0075] Volatility adjustment includes stabilization acquisition steps and stabilization intervention steps;

[0076] Stable acquisition: Count the number of peak electricity consumption trends between each time point and time interval in each period, and determine whether it exceeds the set limit. If it does, execute the stabilization intervention step; otherwise, delete the recommendation for that period and execute the push step.

[0077] Stable intervention: As the number of peak electricity consumption trends increases, the healthy grid connection index is lowered, and then the recommended intervention steps are implemented.

[0078] By adopting the above technical solution and introducing a fluctuation adjustment step, the system can respond more flexibly to changes in electricity consumption trends in the power grid. Whether it is a sudden increase in the number of electricity consumption trend peaks or other forms of fluctuations, the system can respond in a timely manner through two sub-steps: stability acquisition and stability intervention, thereby improving the flexibility and adaptability of the entire system. In the stability acquisition step, the system can statistically analyze the number of electricity consumption trend peaks for each time period, each time point, and each time interval. This detailed data analysis helps the system to more accurately grasp the operating status of the power grid and promptly identify and address potential stability issues. Once the number of electricity consumption trend peaks exceeds the set limit, the system will execute a stability intervention step, reducing the load pressure on the power grid by lowering the healthy grid connection index, thereby further improving the stability of the power grid.

[0079] The introduction of fluctuation adjustment steps also enables the system to allocate power resources more rationally. During peak electricity consumption periods, the system can lower the healthy grid connection index through stabilization intervention steps to reduce unnecessary power consumption, thereby ensuring power supply for critical equipment and areas. During off-peak electricity consumption periods, the system can adjust power output more flexibly to improve resource utilization efficiency.

[0080] Optionally, a load forecasting step is also provided after the health adjustment step or the fluctuation adjustment step;

[0081] Load forecasting: Using load forecasting algorithms, combined with historical electricity consumption data and current electricity consumption trends, to predict the load changes of the power grid over a future period of time;

[0082] 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;

[0083] Further adjustments: Based on the matching results, adjust the grid connection timing selection set, prioritizing those grid connection times that can smooth grid load fluctuations to the greatest extent and improve grid stability, and then execute the recommended intervention steps.

[0084] By adopting the above technical solution, and using a load forecasting algorithm that combines historical electricity consumption data and current electricity consumption trends, the load changes of the power grid in the future can be accurately predicted. The predicted load changes are then matched with the power generation capacity of hydrogen fuel cells to analyze the supplementary effect of hydrogen fuel cell power generation on the power grid load at different grid connection times. The introduction of this step ensures that grid connection decisions 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 grid connection decisions.

[0085] Based on the matching results, the grid connection timing selection set is adjusted, prioritizing those grid connection times that can smooth grid load fluctuations to the greatest extent and improve grid stability. This intelligent adjustment makes grid connection decisions more in line with the actual operating needs of the grid, which helps to improve the stability and reliability of the grid.

[0086] By using 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 periods of low grid load. At the same time, prioritizing grid connection times that can smooth grid load fluctuations to the greatest extent helps to achieve efficient utilization of hydrogen fuel cell power generation and improve energy efficiency.

[0087] The introduction of load intervention steps makes grid connection decisions more in line with the actual operating 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 rationally selecting the grid connection time, it is possible to effectively supplement and smooth the grid load, which helps to improve the overall operating efficiency and stability of the power grid.

[0088] Secondly, the steady-state control system for grid-connected hydrogen fuel cell power generation provided in this application adopts the following technical solution:

[0089] A steady-state control system for grid-connected hydrogen fuel cell power generation includes the following modules:

[0090] Data acquisition module: used to acquire the real-time operating status of the power grid, the operating status of hydrogen fuel cell power generation, and to acquire grid connection instructions to determine the grid connection period;

[0091] Power grid status prediction module: The input end is connected to the output end of the data acquisition module, and it is used to predict the changes in the working status of the power grid during the grid connection period;

[0092] Expected Judgment Module: The input end is connected to the output end of the power grid state prediction module to determine whether the power grid changes that may be caused by the grid connection operation at any time during the grid connection period are in line with the predicted changes or will not have a significant impact.

[0093] Adjustment range acquisition module: The input end is connected to the output end of the expected judgment module. It is used to acquire the adjustment range of hydrogen fuel cells for grid connection at any time during the grid connection period, and store the corresponding set of grid connection time points.

[0094] Reliability calculation module: The input end is connected to the output end of the adjustment range acquisition module, and it is used to calculate the grid connection reliability;

[0095] Filtering module: The input end is connected to the output end of the reliability calculation module, and it is used to determine whether the grid connection reliability corresponding to different grid connection time point sets is greater than the preset reliability threshold.

[0096] Sorting module: The input end is connected to the output end of the filtering module. It is used to sort the grid connection reliability corresponding to different grid connection time points that are greater than the preset reliability threshold, and form a grid connection timing selection set according to the order of grid connection reliability from large to small.

[0097] 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 time selection set to execute the grid connection of the hydrogen fuel cell;

[0098] Time Period Selection Module: Connected to the output of the input filtering module, this module sends a message indicating that the time period has a significant 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 a preset reliability threshold. This message is then transmitted to the grid connection command sender.

[0099] By adopting the above technical solution, the data acquisition module starts working, collecting the real-time operating status of the power grid (such as voltage, current, frequency, etc.), the power generation operating status of the hydrogen fuel cell (such as output power, temperature, humidity, etc.), and receiving grid connection instructions to determine the expected grid connection period; the power grid status 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 operating status of the power grid during the grid connection period, including load demand, voltage fluctuations, etc.; the expectation judgment module, based on the results of the power grid status prediction, determines whether the changes in the power grid that may be caused by the grid connection operation at any time during the grid connection period are in line with the predicted changes or will not have a significant impact.

[0100] Based on the expected judgment, the adjustment range acquisition module acquires the adjustment range (such as the range of output power change, response time, etc.) for the hydrogen fuel cell to connect to the grid during the grid connection period, and stores this information in association with the corresponding set of grid connection time points; the reliability calculation module uses the adjustment range and other relevant parameters (such as grid stability indicators, hydrogen fuel cell performance parameters, etc.) to calculate the reliability of grid connection at different time points during the grid connection period; the screening module judges whether the grid connection reliability corresponding to different sets of grid connection time points meets the requirements according to the preset reliability threshold; if the grid connection reliability is greater than the preset threshold, the next step is continued; otherwise, the time period selection module is triggered.

[0101] The sorting module sorts the set of grid connection time points that meet the reliability requirements, forming a grid connection timing selection set according to the grid connection reliability from largest to smallest. The grid connection module selects the first priority (i.e., the grid connection reliability is the highest) grid connection time point from the grid connection timing selection set and performs the hydrogen fuel cell grid connection operation. If the screening module finds that the grid connection reliability of all grid connection time point sets is less than or equal to the preset threshold, the time period alternative selection module sends a prompt message to the grid connection command sender, informing them that the time period has a significant impact on the power grid and is not suitable for grid connection.

[0102] By predicting and assessing grid conditions, the system can evaluate the impact of grid connection operations on the grid in advance, avoiding grid connection during periods of grid instability or peak load, thereby improving grid connection safety. The system can prioritize grid connection times based on grid connection reliability, selecting the optimal time for grid connection, which helps reduce the impact of grid connection on the grid and improve grid stability. By precisely controlling the timing and adjustment range of grid connection, the system can ensure that hydrogen fuel cells are connected to the grid for power generation under optimal conditions, thereby improving energy utilization efficiency.

[0103] The system integrates multiple modules such as data acquisition, prediction, judgment, calculation, screening, sorting, and grid connection, realizing 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 different scales and types of power grids and hydrogen fuel cells with different performance.

[0104] In summary, this application offers the following beneficial technical effects: By acquiring real-time information on the power grid, hydrogen fuel cells, and grid connection commands, it provides data support for subsequent analysis and decision-making. The comprehensiveness and accuracy of the data are crucial to the effectiveness of subsequent steps. Utilizing historical data to establish a predictive model forecasts changes in the power grid's operating state during the grid connection period helps to understand the grid's load and stability in advance, providing a basis for grid connection operations. By estimating the potential changes to the power grid caused by grid connection operations and comparing them with the predicted changes, it determines whether the requirements are met. This step helps to avoid adverse effects on the power grid caused by grid connection operations, ensuring the safe and stable operation of the power grid. By comparing the predicted power grid operating state with the actual operating state of the hydrogen fuel cell, the adjustment range is obtained and stored in association. This helps to adjust the output of the hydrogen fuel cell before grid connection to better match the power grid's needs. Considering factors such as the grid connection time, adjustment range, and contribution to grid stability, the grid connection reliability is calculated. This step helps to quantitatively assess the feasibility and safety of grid connection operations. Attached Figure Description

[0105] Figure 1 This is a flowchart of the control method in Embodiment 1 of this application;

[0106] Figure 2 This is a flowchart of the steps for obtaining possible damage in Embodiment 2 of this application;

[0107] Figure 3 This is a detailed flowchart of the steps for obtaining the possible damage in Embodiment 2 of this application;

[0108] Figure 4 This is a flowchart of the harmonic intervention step to the harmonic adjustment step in Embodiment 2 of this application;

[0109] Figure 5This is a detailed flowchart of the health grid connection index assessment steps in Embodiment 2 of this application;

[0110] Figure 6 This is a detailed flowchart of the fluctuation adjustment steps in Embodiment 2 of this application. Detailed Implementation

[0111] The following combination Figures 1 to 6 This application will be described in further detail.

[0112] This embodiment discloses a steady-state control method for grid-connected hydrogen fuel cell power generation.

[0113] Example 1: Refer to Figure 1 A steady-state control method for grid-connected hydrogen fuel cell power generation includes the following steps:

[0114] Data acquisition: Obtain the real-time operating status of the power grid, obtain the operating status of hydrogen fuel cell power generation, and obtain grid connection instructions to determine the grid connection period;

[0115] Specifically, the real-time operating status of the power grid is obtained through the power grid monitoring system, including real-time data such as voltage, current, and frequency; the operating status of the hydrogen fuel cell is obtained through the fuel cell management system (FCMS), including parameters such as output power, temperature, and humidity; and the grid connection command is received from the dispatch center to determine the expected grid connection time period.

[0116] Power grid status prediction: Using historical data and a data-driven approach, a power grid status prediction model is established to predict changes in the operating status of the power grid during the grid connection period;

[0117] Specifically, the system collects and organizes power grid operation status data over a period of time, and uses machine learning algorithms (such as LSTM, GRU, etc.) to establish a power grid status prediction model; it inputs current and historical data to predict changes in the power grid's operating status during the grid connection period.

[0118] Expected judgment: Estimate the grid changes that grid connection operation at any time during the grid connection period may cause, and determine whether these changes are in line with the predicted changes or will not have a significant impact. If so, obtain the set of grid connection time points that meet the requirements and execute the adjustment range acquisition step; otherwise, execute the time period selection step.

[0119] Specifically, simulation models (PSASP, ETAP, or DIgSILENT / PowerFactory) are used to simulate the impact of grid connection operations on the power grid. The simulation steps of the simulation model are as follows: Model establishment: First, it is necessary to establish the corresponding mathematical model in the simulation software based on the actual power system structure and parameters. This includes the topology of the power grid, the parameters of transmission lines, the characteristics of generators, the distribution of loads, etc.

[0120] Input Data: After the model is built, relevant operational data needs to be input, such as generator output power, load demand, and power flow of the lines. This data can be set based on historical data, forecast data, or real-time data.

[0121] 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 different operating strategies (such as load transfer, generator output adjustment, etc.).

[0122] Running the simulation: After setting up the model and simulation conditions, start the simulation program. The simulation program will perform calculations based on the input model and data to simulate the operating state of the power system.

[0123] Analysis Results: After the simulation is completed, the simulation results can be analyzed using the analysis tools provided by the simulation software. This includes viewing key indicators such as power flow distribution, voltage level, and frequency changes in the power grid, as well as evaluating the impact of different operating strategies on power grid stability.

[0124] By comparing the simulation results with the prediction results, the differences were found to be within an acceptable range, and a set of grid connection time points that met the requirements was obtained.

[0125] Adjustment range acquisition: Obtain the predicted grid operating status corresponding to the grid connection time point set, compare it with the actual operating status of the hydrogen fuel cell, obtain the adjustment range, and store it in association with the corresponding grid connection time point set;

[0126] Specifically, the predicted grid operating state is compared with the actual operating state of the hydrogen fuel cell; the output power and other parameters that the hydrogen fuel cell needs to adjust when connected to the grid are calculated and stored in the grid connection time point set.

[0127] Reliability calculation: The grid connection reliability is calculated based on the distance and duration from the grid connection command issuance, the adjustment range, and the contribution to grid stability.

[0128] Specifically, the time difference between each grid connection time point and the time when the grid connection command is issued is recorded. Based on the predicted grid operating state and the actual operating state of the hydrogen fuel cell, the magnitude of the output power, voltage, or current parameters that need to be adjusted during grid connection is calculated. The degree to which the grid connection operation improves grid stability is evaluated, which may require calculation based on a power system simulation model.

[0129] Based on experience or expert opinion, assign a weight to each influencing factor. These weights reflect the importance of each factor to grid connection reliability. The sum of the weights should be 1 to ensure the accuracy of the calculation results. Convert the raw data of each influencing factor into standardized values ​​to eliminate the influence of different units and data ranges on the calculation results. Standardization usually includes data normalization or standardization, and the specific method depends on the distribution characteristics of the data.

[0130] The grid connection reliability is calculated using the weighted average method. The standardized value of each influencing factor is multiplied by its corresponding weight, and the results are summed to obtain the total grid connection reliability. The calculation formula is: Grid connection reliability = Σ(Standardized value of influencing factor i * Weight of influencing factor i). Based on the calculation results, the grid connection reliability at different grid connection time points is evaluated.

[0131] Filtering: Determine whether the grid connection reliability corresponding to different grid connection time point sets is greater than the preset reliability threshold. If so, execute the sorting step; otherwise, execute the time period selection step.

[0132] Sorting: Sort the grid connection reliability from highest to lowest to form a grid connection timing selection set;

[0133] Grid connection: Select the grid connection time point with the highest grid connection reliability from the grid connection time selection set, and execute the grid connection of the hydrogen fuel cell;

[0134] Select a different time period: Send a notification that the current time period has a significant impact on the power grid and is not suitable for grid connection, and pass it on to the grid connection command sender.

[0135] Specifically, based on grid operation requirements and experience, a grid connection reliability threshold is set, and the reliability of different grid connection time point sets is compared with the threshold.

[0136] Algorithms such as quicksort and mergesort are used to sort the set of grid connection time points, and a grid connection time selection set is formed based on the sorting results. The grid connection time point with the highest reliability is selected from the grid connection time selection set, and the hydrogen fuel cell grid connection operation is executed through the dispatch center or automatic control system.

[0137] If the reliability of all grid connection time points does not meet the requirements, a prompt message will be sent, suggesting that the grid connection instruction sender reselect the grid connection time period or adjust the grid connection conditions.

[0138] In Embodiment 1 of this application, the grid connection reliability at each time point is calculated by predicting the grid operating status, estimating the impact of grid connection timing on the grid, the contribution to grid stability, and the adjustment range of hydrogen fuel cells. Then, based on the reliability, the best grid connection timing is determined to reduce the impact on the grid and improve grid stability.

[0139] Example 2: Refer to Figure 2 and Figure 3The difference between this embodiment and embodiment 1 is that, after the sorting step, a step for obtaining possible damage is also provided;

[0140] Damage may be acquired: including the steps for acquiring fluctuating demand and the steps for sorting intervention;

[0141] Fluctuation demand acquisition: By using historical data to obtain the current grid power supply group, determine whether there is power supply for precision components or high-demand power supply. If so, sort out the intervention steps; otherwise, execute the grid connection steps.

[0142] Sequencing intervention: Optimize the grid connection timing selection set in the sequencing step, eliminate grid connection time points with precision component power supply or high demand power supply, and then execute the grid connection step.

[0143] Specifically, in this sub-step, the system uses historical data to analyze the power supply groups of the power grid in the current period, paying particular attention to whether there are precision components or high-demand power supply areas with high requirements for power quality. If the system detects that there is such power demand in the current period, it will trigger the sorting intervention step; if there is no such demand in the current period, the system will directly execute the grid connection step.

[0144] During the sorting intervention step, the system optimizes the previously sorted grid connection time points based on the results obtained from fluctuating demand. Specifically, the system eliminates grid connection time points that conflict with power supply periods for precision components or high-demand power supply periods to ensure that grid connection operations will not adversely affect such important loads. The optimized set of grid connection time points will serve as a reference for the final grid connection operation. The system will select the most suitable grid connection time point for grid connection operation based on the optimized set of grid connection time points.

[0145] Reference Figure 3 In other implementations, between the fluctuation demand acquisition step and the grid connection step, there are also a proportion judgment step, a proportion intervention step and an optimization sorting step.

[0146] Proportion judgment: Statistically determine the proportion of power supply to the power grid for precision components or high-requirement components, and determine whether the power supply proportion is less than the set proportion threshold. If so, execute the proportion intervention step; otherwise, optimize the sorting step.

[0147] Proportional Intervention: Based on the power supply proportion and grid connection fluctuation range, the reliability of the grid connection timing in the sorting steps is adjusted and the grid connection time points are reordered before the grid connection steps are executed.

[0148] Optimize the sorting: Remove grid connection time points where the power supply ratio is greater than the set ratio threshold, and then execute the grid connection steps.

[0149] Specifically, the system calculates the proportion of power supply to precision components or high-requirement power in the current power grid, i.e., the proportion of this type of power supply demand to the total power supply demand. Then, it determines whether this proportion is less than a preset proportion threshold. The proportion threshold is a parameter set according to the actual situation of the power grid and the grid connection strategy, used to determine whether special measures need to be taken to deal with this type of 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.

[0150] In this step, the system comprehensively considers the power supply ratio and grid connection fluctuation amplitude (i.e., the degree of impact of grid connection operation on grid voltage, frequency, and other parameters), and adjusts the reliability of the grid connection time points obtained in the sorting step. The reliability adjustment may include increasing or decreasing the weight of the grid connection time points, or reordering the priority of the grid connection time points. The adjusted set of grid connection time points will serve as a reference for subsequent grid connection operations. If the result of the ratio judgment step shows that the power supply ratio is greater than or equal to the set ratio threshold, it indicates that the current power supply demand for precision components or high-requirement power supply in the grid is large. Grid connection time points that conflict with the high-precision or high-requirement power supply periods are directly eliminated, i.e., those grid connection time points whose power supply ratio is greater than the set ratio threshold. The set of grid connection time points after elimination will serve as a reference for subsequent grid connection operations to ensure that grid connection operations will not adversely affect such important loads.

[0151] Reference Figure 4 In other embodiments, a harmonic intervention step is provided after the optimization sorting step and the proportion intervention step.

[0152] Harmonic intervention: Obtain harmonic data during hydrogen fuel cell power generation, denoted as the first harmonic; obtain real-time harmonic data from the power grid, denoted as the second harmonic; determine whether the first and second harmonics match; if they match, execute the harmonic judgment step; otherwise, execute the step of selecting another time period.

[0153] Harmonic detection: Determine whether the first harmonic and the second harmonic are opposite. If they are, execute the harmonic adjustment steps; otherwise, execute the time period selection steps.

[0154] Harmonic adjustment: The grid connection timing selection set is adjusted according to the proximity of the first harmonic to the second harmonic.

[0155] Specifically, harmonic data (first harmonic) is collected during hydrogen fuel cell power generation, and real-time harmonic data (second harmonic) is collected from the power grid. The first and second harmonics are compared to see if they match. The matching criteria may be based on the similarity of parameters such as frequency and amplitude between the two.

[0156] If the harmonics match, further determine whether the first harmonic and the second harmonic are out of phase. If they are out of phase, execute the harmonic adjustment step to adjust the order of the grid connection time points for the hydrogen fuel cell corresponding to the second harmonic. The grid connection time points without harmonics are ranked earlier, and the second harmonic is ranked earlier the closer it is to the first harmonic. If the phases are not out of phase, consider selecting another time period to avoid the peak period of grid harmonics.

[0157] Based on the proximity of the first harmonic to the second harmonic, the grid connection timing selection set is adjusted, that is, a suitable grid connection time or condition is selected to reduce harmonic conflicts and improve grid connection efficiency.

[0158] For example, a hydrogen fuel cell system: a hydrogen fuel cell power generation system with a capacity of 100kW.

[0159] Power Grid: A medium- and low-voltage distribution network with real-time harmonic monitoring capabilities.

[0160] Monitoring equipment: High-precision harmonic monitoring instrument, used to collect and record harmonic data.

[0161] Control system: A microprocessor-based intelligent control system used to execute harmonic intervention procedures.

[0162] Harmonic data acquisition: A high-precision harmonic monitor is used to collect harmonic data (first harmonic) during hydrogen fuel cell power generation. The recording frequency is 50Hz, and the main harmonic components are the 3rd, 5th, and 7th harmonics.

[0163] At the same time, real-time power grid harmonic data (second harmonic) is obtained from the power grid monitoring system, with a recording frequency of 50Hz. The main harmonic components are also the 3rd, 5th, and 7th harmonics.

[0164] Harmonic matching judgment: Compare the data of the first harmonic and the second harmonic, and calculate the frequency deviation and amplitude deviation between the two; if the frequency deviation is less than 0.1Hz and the amplitude deviation of each harmonic is less than 10%, then the harmonics are considered to be matched.

[0165] Harmonic detection and execution: If the harmonics match, further compare the phases of the first and second harmonics; if the phases differ by 180 degrees (i.e., the phases are opposite), then 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 when the grid harmonic level is lower.

[0166] Harmonic adjustment: Adjust the grid connection timing selection based on the proximity of the first and second harmonics; for example, if the amplitude deviation of the third harmonic is large, consider adjusting the load on the fuel cell or using a filter to reduce the output of that harmonic.

[0167] 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.

[0168] Reference Figure 5 In other implementations, after the time period selection step, a timing acquisition step, a sorting and recommendation step, and a push step are also provided.

[0169] Timing acquisition: Based on historical data, predict the grid operating status for multiple time periods, match it with the operating status of the hydrogen fuel cell, perform reliability calculations, obtain the total reliability value for each time period, and then execute the sorting recommendation steps;

[0170] Sorting Recommendation: Sort the data according to the total reliability score from largest to smallest, and then execute the push notification step;

[0171] Push notification: Recommended grid connection time slots to the grid connection command issuer according to the sorting.

[0172] Specifically, using a data analysis system, based on historical grid data from the past year, the system predicts the grid load level, voltage stability, and frequency fluctuations for each time period within the next week. Based on the operating characteristics of the hydrogen fuel cell system, such as its power generation efficiency curve and harmonic output characteristics, the system matches these characteristics with the predicted grid operating conditions to determine the fuel cell output capacity for each time period. A total reliability value is calculated for each matched time period, taking into account grid load levels (avoiding grid connection during peak hours), voltage stability (ensuring voltage fluctuations remain within acceptable limits after grid connection), frequency fluctuations (avoiding grid connection failures due to frequency anomalies), and fuel cell output capacity (ensuring stable operation after grid connection). The matched time periods are ranked according to their total reliability values ​​to determine the optimal grid connection time. For example, a time period with low grid load, stable voltage, small frequency fluctuations, and sufficient fuel cell output capacity has a higher total reliability value and should be prioritized. The ranked recommended grid connection time periods are then pushed to the grid connection command issuer, such as a grid dispatcher or hydrogen fuel cell system maintenance personnel, through the data analysis system's user interface. The pushed information includes the recommended time period, the total reliability value, and grid connection suggestions.

[0173] Reference Figure 5 In other implementations, a healthy grid connection index assessment step is provided after the sorting and recommendation step.

[0174] Health Grid Connection Index Assessment: Includes health index calculation steps and recommended intervention steps;

[0175] Health Index Calculation: Count the number of time points that exceed the reliability threshold in each time period, and record it as the first number. Calculate the health grid connection index based on the first number, the sum of each reliability level, and the mean.

[0176] Recommended intervention: Based on the healthy grid connection index from largest to smallest, the recommendation order obtained in the sorting recommendation step is adjusted through intervention, and the push step is executed.

[0177] Specifically, firstly, reliability data of the power grid is collected for each time period. This data may include key indicators such as voltage stability, current fluctuation, and frequency deviation. A reliability threshold is set, which represents the safety boundary of the power grid operation. Time points exceeding this threshold indicate 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 and recorded as the first number. Based on the first number, the sum of reliability at all time points in each time period, and the mean of reliability, a healthy grid connection index is calculated. The calculation method may involve complex mathematical models, such as weighted average and standard deviation analysis, depending on the complexity and accuracy requirements of the system design.

[0178] Based on the size of the health grid connection index, the recommendation order obtained from the sorting recommendation step is adjusted. Time periods or areas with higher health grid connection indices should be given priority attention, as these time periods or areas may have greater safety risks.

[0179] For the adjusted recommended order, corresponding intervention strategies should be developed, such as adjusting grid parameters, increasing maintenance frequency, and implementing preventive maintenance. The adjusted recommended order and intervention strategies should be pushed to grid operation and maintenance personnel or automatic control systems so that timely measures can be taken to ensure the safe and stable operation of the grid.

[0180] For example, suppose a power grid system needs to assess its grid health index and formulate intervention strategies accordingly. The specific implementation steps are as follows: Data collection: Collect grid reliability data for 24 hours a day over the past week, including indicators such as voltage stability, current fluctuation, and frequency deviation.

[0181] Threshold settings: Set the voltage stability threshold to ±5%, the current fluctuation threshold to ±10%, and the frequency deviation threshold to ±0.2Hz.

[0182] Quantitative statistics: Count the number of times each day that exceed the above threshold to obtain the "first number" for each day within a week.

[0183] Health grid connection index calculation: Calculate the sum and mean of reliability at all time points each day; use the weighted average method, combining the first quantity, the sum and mean of reliability, to calculate the health grid connection index for each day; for example, a weighting coefficient can be set to sum the first quantity, the sum and mean of reliability according to a certain proportion to obtain the final health grid connection index.

[0184] Recommended interventions: Based on the healthy grid connection index, prioritize the time periods or areas that require attention; develop 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; and push the adjusted recommended order and intervention strategies to grid operation and maintenance personnel, requiring them to implement them as soon as possible.

[0185] Reference Figure 5 In other embodiments, an electricity demand acquisition step and a health adjustment step are also provided between the health index calculation step and the recommended intervention step.

[0186] Electricity demand acquisition: Based on historical data, identify peak electricity consumption periods in the power grid, establish time intervals, delete time periods after the time intervals, and obtain electricity consumption trends;

[0187] Health Adjustment: Based on electricity consumption trends and the adjustment range of hydrogen fuel cells, intervene in the health index and then implement the recommended intervention steps.

[0188] Specifically, first, peak electricity consumption periods are identified based on historical electricity data. This is typically accomplished using data analysis tools such as time series analysis and machine learning models. Next, time intervals are established to divide different electricity consumption periods. These intervals can be adjusted based on actual conditions to ensure the accuracy of the analysis. Then, periods after the time intervals are deleted. "Deletion" here means excluding these periods from subsequent analysis, as they may not belong to peak consumption periods or periods with significant changes in electricity consumption trends. Finally, based on the data from the remaining periods, electricity consumption trends are obtained, which can be achieved by calculating indicators such as electricity consumption and electricity consumption growth rate.

[0189] Acquire electricity consumption trend data, which may include changes in electricity consumption and the duration of peak consumption periods. Then, based on the current status and adjustment capabilities of the hydrogen fuel cell, determine the power support it can provide or the adjustment range it can adjust. Next, combining the electricity consumption trend and the adjustment range of the hydrogen fuel cell, use mathematical methods such as weighted averaging and linear regression to dynamically adjust the health index. If the electricity consumption trend indicates a high grid load and the hydrogen fuel cell has sufficient adjustment capabilities, the health index can be appropriately lowered to reduce the load pressure on the grid. Conversely, if the electricity consumption trend is relatively stable and the hydrogen fuel cell's adjustment capabilities are limited, the health index can be maintained or appropriately increased. Finally, use the adjusted health index as input to execute subsequent recommended intervention steps.

[0190] Reference Figure 6 In other embodiments, a fluctuation adjustment step is also provided between the health adjustment step and the recommended intervention step;

[0191] Volatility adjustment includes stabilization acquisition steps and stabilization intervention steps;

[0192] Stable acquisition: Count the number of peak electricity consumption trends between each time point and time interval in each period, and determine whether it exceeds the set limit. If it does, execute the stabilization intervention step; otherwise, delete the recommendation for that period and execute the push step.

[0193] Stable intervention: As the number of peak electricity consumption trends increases, the healthy grid connection index is lowered, and then the recommended intervention steps are implemented.

[0194] Specifically, firstly, electricity consumption trend data for each time period (such as hourly, daily, etc.) is collected. This includes key indicators such as electricity consumption and load at each time point. For each time period, the number of peaks in the electricity consumption trend is counted. Peaks usually represent the high points of the load. The more peaks there are, the greater the fluctuation of the grid load and the worse the stability. A limit is set for 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 fluctuation is large and stabilization intervention steps need to be taken. Conversely, the grid load is relatively stable and the recommended intervention steps can be taken directly.

[0195] The healthy grid connection index is dynamically adjusted based on the increase in the number of peak electricity consumption trends, usually by lowering it. This is because the greater the load fluctuation, the worse the stability and security of the power grid may be, requiring more careful consideration of intervention strategies.

[0196] Based on the adjusted grid health index, the recommended intervention strategy needs to be reassessed and optimized. This requires measures such as increasing the frequency of grid monitoring, adjusting grid parameters, and adding backup power sources to improve the stability and security of the grid.

[0197] For example, taking a city's power grid as an example, the specific implementation process of the fluctuation adjustment steps is explained:

[0198] Data collection: Collect electricity consumption trend data for 24 hours a day over the past week, including electricity consumption and load at each time point.

[0199] Peak Count Statistics: For daily data, count the number of peaks in the electricity consumption trend. For example, if the electricity load reaches its peak at 10:00 AM and 3:00 PM on a certain day, the peak count is 2. Threshold Judgment: Set a limit of 4 for the number of peaks. If the number of peaks on a certain day is greater than 4, it is judged that the grid load fluctuates greatly and stabilization intervention steps need to be performed; otherwise, the recommended intervention steps are directly performed.

[0200] Stable intervention (assuming the number of peaks on a certain day is 6): Health grid connection index adjustment: Since the number of peaks exceeds the limit, the health grid connection index is lowered. The reduction range can be determined according to the degree to which the number of peaks exceeds the limit. For example, for each peak exceeding the limit, the health grid connection index is reduced by a certain percentage.

[0201] Recommended intervention strategy optimization: Based on the adjusted grid health index, reassess 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 detected and addressed in a timely manner during peak load periods; at the same time, consider adjusting grid parameters, such as improving voltage stability and optimizing current distribution, to improve the overall stability and security of the power grid.

[0202] Implement recommended intervention steps: Based on the optimized intervention strategy, implement corresponding recommended intervention measures, such as increasing reactive power compensation and adjusting line load distribution, to ensure the safe and stable operation of the power grid.

[0203] Reference Figure 6 In other embodiments, a load forecasting step is provided after the health adjustment step or the fluctuation adjustment step.

[0204] Load forecasting: Using load forecasting algorithms, combined with historical electricity consumption data and current electricity consumption trends, to predict the load changes of the power grid over a future period of time;

[0205] 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;

[0206] Further adjustments: Based on the matching results, adjust the grid connection timing selection set, prioritizing those grid connection times that can smooth grid load fluctuations to the greatest extent and improve grid stability, and then execute the recommended intervention steps.

[0207] Specifically, historical electricity consumption data is collected, including daily, weekly, monthly, or yearly electricity consumption and load over a period of time. At the same time, current electricity consumption trend data is obtained, such as real-time electricity consumption and load change rate.

[0208] By using load forecasting algorithms (such as time series analysis, machine learning models, etc.) to comprehensively analyze historical data and current trends, the load changes of the power grid in the future (such as the next day, week or month) can be predicted. The prediction results should include information such as the peak load, valley load and the trend of change.

[0209] Based on the technical parameters and operating status of hydrogen fuel cells, their power generation capacity at different grid connection points is evaluated, including the maximum, minimum, and average power generation, as well as power generation efficiency.

[0210] By matching predicted grid load changes with the power generation capacity of hydrogen fuel cells, the supplementary effect of hydrogen fuel cell power generation on grid load under different grid connection time points is analyzed. The goal is to identify the grid connection time points that can smooth grid load fluctuations to the greatest extent and improve grid stability.

[0211] Based on the results of matching optimization, the grid connection timing selection set is adjusted, that is, those grid connection time points that can optimally smooth grid load fluctuations and improve grid stability are selected; based on the adjusted grid connection timing selection set, the recommended intervention strategy is optimized.

[0212] This application also discloses a steady-state control system for grid-connected hydrogen fuel cell power generation.

[0213] The steady-state control system for grid-connected hydrogen fuel cell power generation includes the following modules:

[0214] Data acquisition module: used to acquire the real-time operating status of the power grid, the operating status of hydrogen fuel cell power generation, and to acquire grid connection instructions to determine the grid connection period;

[0215] Power grid status prediction module: The input end is connected to the output end of the data acquisition module, and it is used to predict the changes in the working status of the power grid during the grid connection period;

[0216] Expected Judgment Module: The input end is connected to the output end of the power grid state prediction module to determine whether the power grid changes that may be caused by the grid connection operation at any time during the grid connection period are in line with the predicted changes or will not have a significant impact.

[0217] Adjustment range acquisition module: The input end is connected to the output end of the expected judgment module. It is used to acquire the adjustment range of hydrogen fuel cells for grid connection at any time during the grid connection period, and store the corresponding set of grid connection time points.

[0218] Reliability calculation module: The input end is connected to the output end of the adjustment range acquisition module, and it is used to calculate the grid connection reliability;

[0219] Filtering module: The input end is connected to the output end of the reliability calculation module, and it is used to determine whether the grid connection reliability corresponding to different grid connection time point sets is greater than the preset reliability threshold.

[0220] Sorting module: The input end is connected to the output end of the filtering module. It is used to sort the grid connection reliability corresponding to different grid connection time points that are greater than the preset reliability threshold, and form a grid connection timing selection set according to the order of grid connection reliability from large to small.

[0221] Damage acquisition module: The input end is connected to the output end of the sorting module, and it is used to optimize and adjust the grid connection timing selection set according to the power supply group and power supply harmonic stability in the power supply demand;

[0222] Grid connection module: The input terminal is connected to the output terminal of the module that may detect damage, and is used to select the grid connection time point with the first priority grid connection reliability from the grid connection time selection set to execute the grid connection of the hydrogen fuel cell;

[0223] The time period selection module is connected to the output of the filtering module. It 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 then transmits it to the grid connection command sender.

[0224] Timing Recommendation Module: The input end is connected to the output end of the Time Period Selection Module. It is used to infer the grid operating status through historical data when it is not suitable for grid connection, and then match it with the operating status of the hydrogen fuel cell to calculate the reliability and health index. Based on the reliability, it provides a grid connection time recommendation to the grid connection command issuer.

[0225] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for steady state control of hydrogen fuel cell power generation grid connected, characterized by: The method comprises the following steps: Data collection: obtaining the real-time working state of the power grid, obtaining the working state of the hydrogen fuel cell power generation, and obtaining the grid-connected instruction to determine the grid-connected period; Power grid state prediction: using historical data, a data-driven method is used to establish a power grid state prediction model to predict the change of the working state of the power grid in the grid-connected period; Expected judgment: estimating the possible changes in the power grid caused by grid connection operation at any time in the grid-connected period, and judging whether these changes meet the expected changes or will not cause significant impact, if so, obtaining a set of grid-connected time points meeting the requirements, and performing the adjustment amplitude acquisition step, otherwise, performing the period alternative step; Adjustment amplitude acquisition: comparing the predicted power grid working state corresponding to the set of grid-connected time points with the actual working state of the hydrogen fuel cell to obtain the adjustment amplitude, and storing the corresponding set of grid-connected time points; Reliability calculation: calculating the grid connection reliability according to the distance time length from the grid connection instruction, the adjustment amplitude, and the power grid stability contribution degree of the set of grid-connected time points; Screening: judging whether the grid connection reliability corresponding to different sets of grid-connected time points is greater than a preset reliability threshold, if so, performing the sorting step, otherwise, performing the period alternative step; Sorting: sorting according to the order of the grid connection reliability from large to small, and forming a set of grid connection opportunities; Grid connection: selecting the grid-connected time point with the first order grid connection reliability from the set of grid connection opportunities, and performing the hydrogen fuel cell grid connection; Period alternative: sending a prompt that the period has a large impact on the power grid and is not suitable for grid connection, and delivering it to the grid connection instruction sender.

2. The hydrogen fuel cell power plant grid tied steady state control method of claim 1 wherein: After the sorting step, a damage possibility acquisition step is further provided; Damage possibility acquisition: including fluctuation demand acquisition step and sorting intervention step; Fluctuation demand acquisition: obtaining the power supply group of the current period of the power grid through historical data, and judging whether there is precision component power supply or high demand power supply, if so, performing the sorting intervention step, otherwise, performing the grid connection step; Sorting intervention: optimizing the set of grid connection opportunities in the sorting step, and eliminating the grid connection time points with precision component power supply or high demand power supply, and then performing the grid connection step.

3. The hydrogen fuel cell power plant grid tied steady state control method of claim 2 wherein: Between the fluctuation demand acquisition step and the grid connection step, there are also proportion judgment step, proportion intervention step and optimization sorting step; Proportion judgment: judging whether the power supply proportion of the precision component power supply or the high demand power supply in the power grid is less than the set proportion threshold, if so, performing the proportion intervention step, otherwise, performing the optimization sorting step; Proportion intervention: adjusting the reliability of the grid connection time points in the set of grid connection opportunities in the sorting step according to the power supply proportion and the grid connection fluctuation amplitude, and re-sorting, and then performing the grid connection step; Optimization sorting: eliminating the grid connection time points corresponding to the power supply proportion greater than the set proportion threshold, and then performing the grid connection step.

4. The hydrogen fuel cell power plant grid tied steady state control method of claim 3 wherein: After the optimization sorting step and the proportion intervention step, a harmonic intervention step is further provided; Harmonic intervention: obtaining the harmonic data of the hydrogen fuel cell power generation, denoted as the first harmonic, obtaining the real-time harmonic data of the power grid, denoted as the second harmonic, and judging whether the first harmonic and the second harmonic match, if so, performing the harmonic judgment step, otherwise, performing the period alternative 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 alternative step; Harmonic adjustment: according to the closeness of the first harmonic and the second harmonic, adjust the grid connection time selection.

5. The method of claim 1-4, wherein: After the time period alternative step, there is also a time acquisition step, a sorting recommendation step and a push step; Time acquisition: according to historical data, predict the grid working state of multiple time periods, match with the working state of hydrogen fuel cell, and calculate the reliability, and obtain the total value of reliability of each time period, and then execute the sorting recommendation step; Sorting recommendation: according to the order of reliability total value from large to small, sorting is carried out, and the push step is executed; Push: according to the order, recommend the grid connection time period to the grid connection instruction issuer.

6. The hydrogen fuel cell power plant grid tied steady state control method of claim 5 wherein: After the sorting recommendation step, there is also a healthy grid connection index evaluation step; Healthy grid connection index evaluation: including health index calculation step and recommended intervention step; Health index calculation: the number of time points exceeding the reliability threshold in each time period is counted as the first number, and the health grid connection index is calculated according to the first number, the sum and the average of each reliability; Recommended intervention: according to the order of health grid connection index from large to small, the recommended order obtained by the sorting recommendation step is intervened and adjusted, and the push step is executed.

7. The hydrogen fuel cell power plant grid tied steady state control method of claim 6 wherein: Between the health index calculation step and the recommended intervention step, there is also a power demand acquisition step and a health adjustment step; Power demand acquisition: according to historical data, obtain the power grid power consumption peak period, establish time interval, delete the time period after the time interval, and obtain the power consumption trend; Health adjustment: according to the power consumption trend and the adjustment range of hydrogen fuel cell, the health index is intervened, and then the recommended intervention step is executed.

8. The hydrogen fuel cell power plant grid tied steady state control method of claim 7, wherein: Between the health adjustment step and the recommended intervention step, there is also a fluctuation adjustment step; Fluctuation adjustment: including stability acquisition step and stability intervention step; Stability acquisition: the number of power consumption trend peaks between each time point and time interval in each time period is counted, and it is judged whether it is greater than the set number limit value, if so, the stability intervention step is executed, otherwise, the recommendation of this time period is deleted, and the push step is executed; Stability intervention: with the increase of the number of power consumption trend peaks, the health grid connection index is adjusted downward, and then the recommended intervention step is executed.

9. The hydrogen fuel cell power plant grid tied steady state control method of claim 8, wherein: After the health adjustment step or the fluctuation adjustment step, there is also a load prediction step; Load prediction: using load prediction algorithm, combining historical power consumption data and current power consumption trend, predicting the load change of power grid in a period of time in the future; Matching optimization: match the predicted load change with the power generation capacity of hydrogen fuel cell, analyze the supplement effect of hydrogen fuel cell power generation on power grid load at different grid connection time points; Adjustment again: according to the matching result, adjust the grid connection time selection, preferentially select those grid connection time points which can smooth the load fluctuation of power grid to the greatest extent and improve the stability of power grid, and then execute the recommended intervention step.

10. A control system for grid-connected steady state control of a hydrogen fuel cell power plant using the method of any of claims 1-9. Including the following modules: Data acquisition module: used for acquiring the real-time working state of power grid, acquiring the working state of hydrogen fuel cell power generation, and acquiring the grid connection instruction to determine the grid connection time period; The grid state prediction module is connected with the output end of the data acquisition module, and is configured to predict the working state change of the grid in the grid connection period; The expectation judgment module is connected with the output end of the grid state prediction module, and is configured to judge whether the grid change caused by the grid connection operation at any time in the grid connection period conforms to the predicted change expectation or does not cause significant influence; The adjustment range acquisition module is connected with the output end of the expectation judgment module, and is configured to acquire the adjustment range of the hydrogen fuel cell for grid connection at any time in the grid connection period, and to store the corresponding grid connection time point set; The reliability calculation module is connected with the output end of the adjustment range acquisition module, and is configured to calculate the grid connection reliability; The screening module is connected with the output end of the reliability calculation module, and is configured to judge whether the grid connection reliability corresponding to different grid connection time point sets is greater than a preset reliability threshold value; The sorting module is connected with the output end of the screening module, and is configured to sort the grid connection reliability corresponding to different grid connection time point sets in descending order when the grid connection reliability is greater than the preset reliability threshold value, and to form a selected grid connection time set; The grid connection module is connected with the output end of the sorting module, and is configured to select the grid connection time point with the first order grid connection reliability from the selected grid connection time set, and to execute the grid connection of the hydrogen fuel cell; The period alternative module is connected with the output end of the screening module, and is configured to send a prompt that the period has a great influence on the 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 value, and to deliver the prompt to a grid connection instruction sender.

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