Method for on-off grid switching of hydrogen fuel cell grid tied controller

Abstract

This invention discloses a method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller, relating to the field of intelligent control technology. The method includes: acquiring the hydrogen fuel cell grid-connected controller; monitoring and acquiring multi-dimensional operational sensing data streams through a data sensing module; constructing a power integrated operation evaluation network based on an analytical evaluation module; performing analytical evaluation on the multi-dimensional operational sensing data streams based on the power integrated operation evaluation network to obtain power operation stability parameters; invoking a grid connection / off-grid switching strategy according to an intelligent switching module, and triggering a grid connection / off-grid control activation strategy based on the matching of power operation stability parameters and the grid connection / off-grid switching strategy; and performing grid connection / off-grid switching and power supply coordination control on the hydrogen fuel cell grid-connected controller based on the grid connection / off-grid control activation strategy. This solves the technical problem in the prior art where hydrogen fuel cell grid-connected controllers are unable to intelligently switch between grid connection and off-grid modes according to power operation status, achieving the technical effect of intelligent grid connection / off-grid mode switching.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology, and more specifically to a method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller. Background Technology

[0002] With the rapid development of hydrogen fuel cell technology, its application in distributed energy systems is gradually expanding. Hydrogen fuel cells are clean and efficient, capable of working collaboratively with energy storage devices, the power grid, and loads to provide stable power for various application scenarios. In actual operation, the hydrogen fuel cell grid-connected controller needs to switch between grid-connected and off-grid modes to cope with complex operating conditions such as grid fluctuations, load changes, or sudden failures. However, in existing technologies, the controller struggles to intelligently assess and accurately switch based on real-time power operating status, leading to response delays, instability during switching, and insufficient power supply coordination management. These problems severely impact system reliability and the continuity of power supply to the load. Summary of the Invention

[0003] This application provides a method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller, which solves the technical problem in the prior art that the hydrogen fuel cell grid-connected controller is difficult to intelligently switch between grid connection and off-grid operation modes according to the power operating status.

[0004] In view of the above problems, this application provides a method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller.

[0005] A first aspect of this application provides a method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller, the method comprising:

[0006] A hydrogen fuel cell grid-connected controller is acquired, which integrates a data sensing module, an analysis and evaluation module, and an intelligent switching module. The data sensing module monitors and acquires multi-dimensional operational sensing data streams, the sources of which include the hydrogen fuel cell system, energy storage device, power grid, and load. A power integrated operation evaluation network is constructed based on the analysis and evaluation module, including a power grid operation status evaluation network and a hydrogen fuel cell status evaluation network. The multi-dimensional operational sensing data streams are analyzed and evaluated based on the power integrated operation evaluation network to obtain power operation stability parameters. The intelligent switching module invokes a grid-connected / off-grid switching strategy, and based on the matching of the power operation stability parameters with the grid-connected / off-grid switching strategy, a grid-connected / off-grid control activation strategy is triggered. Based on the grid-connected / off-grid control activation strategy, the hydrogen fuel cell grid-connected controller performs grid-connected / off-grid switching and power supply coordination control.

[0007] A second aspect of this application provides a grid-connected / off-grid switching system for a hydrogen fuel cell grid-connected controller, the system comprising:

[0008] Interactive Components: Acquires data from the hydrogen fuel cell grid-connected controller, which includes a data sensing module, an analysis and evaluation module, and an intelligent switching module. Data Acquisition Components: Monitors and acquires multi-dimensional operational sensing data streams through the data sensing module. These data streams originate from the hydrogen fuel cell system, energy storage devices, the power grid, and loads. Evaluation Network Construction Components: Constructs an integrated power operation evaluation network based on the analysis and evaluation module. This network includes a power grid operation status evaluation network and a hydrogen fuel cell status evaluation network. Analysis and Evaluation Components: Analyze and evaluate the multi-dimensional operational sensing data streams based on the integrated power operation evaluation network to obtain power operation stability parameters. Strategy Matching Components: Invokes grid-connected / off-grid switching strategies based on the intelligent switching module. Matches the power operation stability parameters with the grid-connected / off-grid switching strategies to trigger a grid-connected / off-grid control activation strategy. Control Components: Performs grid-connected / off-grid switching and power supply coordination control on the hydrogen fuel cell grid-connected controller based on the grid-connected / off-grid control activation strategy.

[0009] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0010] First, a hydrogen fuel cell grid-connected controller is acquired, which integrates a data sensing module, an analysis and evaluation module, and an intelligent switching module. Next, the data sensing module monitors and acquires multi-dimensional operational sensing data streams, originating from the hydrogen fuel cell system, energy storage devices, the power grid, and loads. Simultaneously, a power integrated operation evaluation network is constructed based on the analysis and evaluation module, comprising a power grid operation status evaluation network and a hydrogen fuel cell status evaluation network. Then, the multi-dimensional operational sensing data streams are analyzed and evaluated based on the power integrated operation evaluation network to obtain power operation stability parameters. Further, the intelligent switching module invokes a grid-connected / off-grid switching strategy, matching the power operation stability parameters with the strategy to trigger a grid-connected / off-grid control activation strategy. Finally, based on the grid-connected / off-grid control activation strategy, the hydrogen fuel cell grid-connected controller performs grid-connected / off-grid switching and power supply coordination control. This solves the technical problem in existing technologies where hydrogen fuel cell grid-connected controllers struggle to intelligently switch between grid-connected and off-grid modes based on power operation status, achieving intelligent grid-connected / off-grid mode switching. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 A schematic flowchart of a grid-connected / off-grid switching method for a hydrogen fuel cell grid-connected controller provided in an embodiment of this application;

[0013] Figure 2 This is a schematic diagram of the grid-connected / off-grid switching system for a hydrogen fuel cell grid-connected controller provided in an embodiment of this application.

[0014] Figure labeling: Interactive component 11, Data acquisition component 12, Evaluation network construction component 13, Parsing and evaluation component 14, Policy matching component 15, Control component 16. Detailed Implementation

[0015] This application solves the technical problem in the prior art that it is difficult for the grid-connected controller of hydrogen fuel cells to intelligently switch between grid-connected and off-grid modes according to the power operation status by providing a method for switching between grid-connected and off-grid modes for a grid-connected controller of hydrogen fuel cells.

[0016] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0017] It should be noted that the terms "comprising" and "having" are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to these processes, methods, products, or devices.

[0018] Example 1, as Figure 1 As shown in the embodiment of this application, a method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller is provided, wherein the method includes:

[0019] Obtain a hydrogen fuel cell grid-connected controller, which has a built-in data sensing module, analysis and evaluation module, and intelligent switching module.

[0020] The hydrogen fuel cell grid-connected controller integrates a data sensing module, an analysis and evaluation module, and an intelligent switching module. The data sensing module monitors and acquires multi-dimensional operational sensing data streams in real time, covering relevant operational information of the hydrogen fuel cell system, energy storage device, power grid, and load, providing fundamental data support for subsequent analysis and control. The analysis and evaluation module analyzes and evaluates the multi-dimensional data streams collected by the data sensing module, constructing a power integrated operation evaluation network. By evaluating the power grid status and the hydrogen fuel cell operating status, it generates power operation stability parameters, providing a basis for grid-connected / off-grid switching decisions. The intelligent switching module enables intelligent switching between grid-connected and off-grid modes for the hydrogen fuel cell. By acquiring data from the hydrogen fuel cell grid-connected controller, real-time sensing, intelligent evaluation, and decision-making switching of multi-source data can be achieved, meeting the efficient control requirements of complex application scenarios for the grid-connected operation of hydrogen fuel cells.

[0021] The data sensing module monitors and acquires multi-dimensional operational sensing data streams, the sources of which include hydrogen fuel cell systems, energy storage devices, power grids, and loads.

[0022] The data sensing module monitors and collects multi-dimensional operational sensing data streams in real time. These data streams originate from the hydrogen fuel cell system, energy storage devices, the power grid, and loads. From the hydrogen fuel cell system, key operating parameters such as voltage, current, temperature, and output power are acquired to monitor the fuel cell's health status and performance indicators, ensuring operational stability. From the energy storage device, the module collects the energy storage device's state of charge (e.g., SOC, DOD), obtaining charging and discharging current, voltage, and temperature data. The module monitors the real-time operating status of the power grid, including voltage fluctuations, frequency changes, and power supply and demand, acquiring load change information at grid connection points and analyzing the grid's demand on the hydrogen fuel cell's output. It also collects the real-time power demand of the connected loads, monitoring load change trends and their impact on power supply stability. Through the comprehensive sensing of multi-source data, the data sensing module forms a multi-dimensional operational sensing data stream covering the entire system, providing comprehensive and accurate data support for subsequent status assessments and grid-connected / off-grid switching strategies.

[0023] A power integrated operation assessment network is built based on the analytical assessment module. The power integrated operation assessment network includes a power grid operation status assessment network and a hydrogen fuel cell status assessment network.

[0024] The analysis and evaluation module constructs an integrated power operation evaluation network based on the acquired multi-dimensional operational sensing data to comprehensively assess the system's operational status. This network consists of a power grid operation status evaluation network and a hydrogen fuel cell status evaluation network. The power grid operation status evaluation network assesses the power grid's operational status in real time, ensuring that grid stability parameters meet grid-connected operation requirements. The hydrogen fuel cell status evaluation network assesses the health status and operational capabilities of the hydrogen fuel cells, determining their adaptability in grid-connected or off-grid modes.

[0025] Furthermore, the establishment of the power integrated operation evaluation network includes:

[0026] A power operation database is constructed, comprising historical power grid operation status datasets and historical hydrogen fuel cell operation status datasets. Correlation features are extracted from both datasets to obtain initial power grid operation correlation feature sets and initial hydrogen fuel cell correlation feature sets. Dimensionality reduction and labeling training are performed on these sets to obtain a power grid operation status assessment network and a hydrogen fuel cell status assessment network. The power grid operation status assessment network and the hydrogen fuel cell status assessment network are then concatenated with equally weighted parameters to construct an integrated power operation assessment network, which is then stored in the parsing and assessment module.

[0027] Specifically, historical power grid operation status data and hydrogen fuel cell operation status data are collected and stored to form a power operation database. The historical power grid operation status dataset includes information such as grid voltage fluctuations, frequency deviations, load demand changes, and grid fault recovery times. The historical hydrogen fuel cell operation status dataset includes information such as battery output power, temperature changes, fuel consumption rate, aging status, and fault records. Key features related to power grid operation stability are extracted from the historical power grid operation status dataset to form an initial power grid operation correlation feature set, such as voltage stability indicators, frequency change rate, and load adaptability. Key features related to fuel cell health status and operating performance are extracted from the historical hydrogen fuel cell operation status dataset to form an initial hydrogen fuel cell correlation feature set, such as power output characteristics, operating temperature range, and fuel utilization rate. The initial power grid operation correlation feature set and the initial hydrogen fuel cell correlation feature set are then processed separately. Dimensionality reduction is performed to decrease data redundancy while retaining core features. Label training algorithms (such as neural networks and autoencoders) are used to optimize feature representation, resulting in a power grid operation status assessment network and a hydrogen fuel cell status assessment network. The power grid operation status assessment network is used to calculate power grid stability parameters in real time, while the hydrogen fuel cell status assessment network is used to dynamically assess fuel cell health and performance parameters. The power grid operation status assessment network and the hydrogen fuel cell status assessment network are concatenated with equal weights to ensure that both contribute equally to the integrated power operation assessment. A fusion algorithm (such as a weighted graph network) is used to achieve dynamic collaborative analysis of the two assessment networks, building a complete integrated power operation assessment network. The completed integrated power operation assessment network is stored in the parsing assessment module, which can call this assessment network to parse the real-time multidimensional sensing data stream and output power operation stability parameters, providing a decision-making basis for the subsequent intelligent switching module.

[0028] Furthermore, the aforementioned network for assessing the power grid operating status and the hydrogen fuel cell operating status includes:

[0029] The initial power grid operation associated feature set and the initial hydrogen fuel cell associated feature set are subjected to dimensionality reduction processing to obtain a power grid operation feature sample set and a hydrogen fuel cell feature sample set. Characteristic analysis is then performed on the power grid operation feature sample set and the hydrogen fuel cell feature sample set to obtain power grid data characteristic information and hydrogen fuel cell data characteristic information, respectively. Based on the power grid data characteristic information and the hydrogen fuel cell data characteristic information, a power grid data evaluation model set and a hydrogen fuel cell evaluation model set are selected. Based on the power grid data evaluation model set and the hydrogen fuel cell evaluation model set, the power grid operation feature sample set and the hydrogen fuel cell feature sample set are integrated, trained, and optimized to obtain the power grid operation status evaluation network and the hydrogen fuel cell status evaluation network.

[0030] Specifically, principal component analysis (PCA), linear discriminant analysis (LDA), or autoencoder techniques are used to perform dimensionality reduction on the initial power grid operation-related feature sets and the initial hydrogen fuel cell-related feature sets, respectively. Redundant information is removed and feature representations are optimized, resulting in efficiently expressed power grid operation feature sample sets and hydrogen fuel cell feature sample sets, while retaining key influencing factors such as grid voltage fluctuation rate, frequency deviation rate, and fuel cell output power efficiency. Characteristic analysis is then performed on both the power grid operation feature sample sets and the hydrogen fuel cell feature sample sets to extract core data characteristic information. Power grid data characteristic information includes time-series fluctuation characteristics, load response characteristics, and frequency regulation capability; hydrogen fuel cell data characteristic information includes performance change trends, aging characteristics, and stability characteristics. Based on the power grid data characteristic information and the hydrogen fuel cell data characteristic information, an appropriate evaluation model set is selected. The power grid data evaluation model set can... The hydrogen fuel cell evaluation model set includes models such as Support Vector Machine (SVM), Random Forest (RF), and Long Short-Term Memory Network (LSTM). It can also include Decision Tree (DT), Gradient Boosting Tree (GBDT), and Deep Neural Network (DNN). Based on the selected model set, the power grid operation feature sample set and the hydrogen fuel cell feature sample set are integrated and trained for optimization. By integrating and training the power grid data evaluation model set (using model fusion, such as weighted averaging), the prediction results of multiple models are fused to obtain the power grid operation status evaluation network. Similarly, by integrating and training the hydrogen fuel cell evaluation model set (using model fusion, such as weighted averaging), the fuel cell state prediction capability is optimized to obtain the hydrogen fuel cell state evaluation network. The optimized and trained power grid operation status evaluation network and hydrogen fuel cell state evaluation network are output, used for real-time evaluation of power grid stability and fuel cell operating health status, respectively.

[0031] Furthermore, obtaining the power grid operation characteristic sample set and the hydrogen fuel cell characteristic sample set includes:

[0032] Information on factors influencing power grid operation and hydrogen fuel cell operation is obtained. Based on this information, correlation analysis is performed on the initial power grid operation correlation feature set and the initial hydrogen fuel cell correlation feature set to determine the power grid operation feature correlation set and the hydrogen fuel cell operation feature correlation set. Based on these two sets, a power grid operation feature cluster and a hydrogen fuel cell operation feature cluster are constructed. The power grid operation feature cluster and the hydrogen fuel cell operation feature cluster are then subjected to feature dimensionality reduction and filtering at a preset distance to obtain the power grid operation feature sample set and the hydrogen fuel cell feature sample set.

[0033] Specifically, information on factors influencing power grid operation is acquired, covering key parameters affecting grid stability, such as voltage fluctuation rate, frequency deviation, load change rate, and power supply reliability indicators. Information on factors influencing hydrogen fuel cell operation is also acquired, covering major parameters affecting battery performance, such as output power, operating temperature, fuel utilization efficiency, and aging characteristics. Based on the information on factors influencing power grid operation and hydrogen fuel cell operation, correlation analysis is performed on the initial power grid operation correlation feature set and the initial hydrogen fuel cell correlation feature set, respectively. Statistical correlation analysis (such as Pearson correlation coefficient) can be used to quantify the degree of correlation between features and influencing factors, thereby obtaining the power grid operation feature correlation set and the hydrogen fuel cell operation feature correlation set. Based on the power grid operation feature correlation set and the hydrogen fuel cell operation feature correlation set, clustering algorithms (such as K-means, DBSCAN, or hierarchical clustering) are used to group highly correlated features. Clustering is performed on the degree features to construct power grid operation feature clusters, including feature groups with similar correlation properties, such as voltage stability feature clusters and load fluctuation feature clusters. Hydrogen fuel cell operation feature clusters include performance parameter-related feature groups, such as power output feature clusters and fuel efficiency feature clusters. According to a preset distance criterion (such as Euclidean distance or cosine similarity), dimensionality reduction is performed on the power grid operation feature clusters and hydrogen fuel cell operation feature clusters to remove redundant features. For the power grid operation feature clusters, the core features with the greatest impact on the operating state are retained, such as the power grid frequency deviation rate and load response time. For the hydrogen fuel cell operation feature clusters, the most representative features are retained, such as fuel utilization efficiency and output power stability index. The filtered power grid operation feature sample set and hydrogen fuel cell feature sample set are output as input datasets for subsequent training of the power grid operation state assessment network and the hydrogen fuel cell state assessment network, respectively.

[0034] The multi-dimensional operation perception data stream is analyzed and evaluated based on the power integrated operation evaluation network to obtain power operation stability parameters.

[0035] The multi-dimensional operational sensing data stream acquired through the data sensing module is input into the power integrated operation assessment network. Based on the power integrated operation assessment network, the power grid operation status assessment network and the hydrogen fuel cell status assessment network are analyzed separately to extract power grid characteristics (power grid voltage fluctuations, frequency change rate, load change trends, etc.) and fuel cell characteristics (output power stability, fuel consumption efficiency, operating temperature, etc.). Using the power grid operation status assessment network, the multi-dimensional characteristics of the power grid operation status are comprehensively evaluated to generate power grid stability assessment parameters. Using the hydrogen fuel cell status assessment network, the fuel cell operation characteristics are dynamically analyzed to generate fuel cell health status assessment parameters. Combining the power grid stability assessment parameters and the fuel cell health status assessment parameters, the overall power operation stability parameters are calculated using a weighted fusion algorithm (such as hierarchical weighted fusion, Bayesian inference). The operation stability parameters are used to quantify the current stability level of the power grid.

[0036] The grid connection and off-grid switching strategy is invoked by the intelligent switching module. Based on the matching of the power operation stability parameters with the grid connection and off-grid switching strategy, the grid connection and off-grid control activation strategy is triggered.

[0037] The intelligent switching module stores and incorporates a database of off-grid switching strategies, including switching rules and parameter thresholds applicable to different operating conditions. Examples include off-grid switching strategies for grid anomalies, rapid adjustment strategies for sudden load increases or decreases, and power supply switching strategies for fuel cell anomalies. The module analyzes power operation stability parameters, including the current grid stability index, fuel cell health status assessment values, and load power demand trends. Based on matching rules for these stability parameters, judgments are made. For instance, when grid frequency fluctuations exceed a preset threshold, an off-grid strategy is triggered; when fuel cell output power is insufficient, grid connection is prioritized to supplement power supply. Based on the matching results, switching control decisions are generated, such as grid connection initiation, off-grid withdrawal, or power supply mode adjustment.

[0038] Based on the aforementioned grid-connected / off-grid control activation strategy, the hydrogen fuel cell grid-connected controller is used for grid-connected / off-grid switching and power supply coordination control.

[0039] Based on the grid-connected and off-grid control activation strategy, the grid-connected controller of the hydrogen fuel cell is controlled to realize intelligent switching between grid-connected and off-grid modes.

[0040] Furthermore, the step of performing grid-connection / off-grid switching and power supply coordination control on the hydrogen fuel cell grid-connected controller based on the grid-connection / off-grid control activation strategy includes:

[0041] Based on the grid connection / off-grid control activation strategy, a target grid connection / off-grid mode is determined; the hydrogen fuel cell grid connection controller is switched between grid connection and off-grid mode according to the target grid connection / off-grid mode to obtain a grid connection / off-grid control strategy; based on the grid connection / off-grid control strategy, a grid connection / off-grid control strategy space is constructed; based on the power operation stability parameters, the grid connection / off-grid control strategy space is analyzed and optimized to determine the target grid connection / off-grid control strategy parameters, and power supply coordination control is performed through the target grid connection / off-grid control strategy parameters.

[0042] Specifically, based on the analysis of power operation stability parameters and the activation strategy for off-grid control, a target grid connection / off-grid mode is determined. When the grid is operating normally and the fuel cell cannot meet the load demand independently, the grid connection mode is selected; conversely, when the grid is abnormal or requires independent power supply, the off-grid mode is selected. The hydrogen fuel cell grid connection controller is switched according to the target grid connection / off-grid mode. Grid connection is achieved by gradually synchronizing the power of the fuel cell and the grid, or by increasing the power supply ratio between the fuel cell and the energy storage device to achieve off-grid switching. Corresponding grid connection / off-grid control strategies are generated, including power allocation, load priority management, and energy balance measures. These strategies are further refined by analyzing historical operating data and real-time sensing data. Based on the known data, a grid-connected / off-grid control strategy space is constructed, which includes multiple power supply modes, dynamic power allocation parameters, and load priorities. This space contains strategy combinations under different grid-connected / off-grid modes. Optimization algorithms (such as particle swarm optimization, genetic algorithms, or dynamic programming) are used to calculate and evaluate the adaptability of different strategies. With power supply stability, switching response time, and system efficiency as optimization objectives, the optimal strategy is selected from the strategy space to determine the target grid-connected / off-grid control strategy parameters. Based on the determined target grid-connected / off-grid control strategy parameters, power supply coordination control is adjusted in real time, including dynamic power regulation (adjusting the output power ratio of fuel cells, energy storage devices, and the grid) and load management.

[0043] Furthermore, the grid connection and off-grid control strategies specifically include: grid connection control strategies in grid connection mode and islanding control strategies in off-grid mode.

[0044] In grid-connected mode, a grid-connected control strategy is adopted to ensure the synchronous operation of the hydrogen fuel cell system with the power grid; in off-grid mode, an islanding control strategy is adopted to ensure that the hydrogen fuel cell system can stably supply power to the load.

[0045] Furthermore, the parameters for determining the target and disconnecting from the network control strategy include:

[0046] Using the power operation stability parameters as constraint parameters, the grid connection and disconnection control strategy space is analyzed to obtain control strategy parameter thresholds; based on the grid connection and disconnection control objectives, a control strategy fitness function is constructed; multiple control strategy parameters are randomly selected within the control strategy parameter thresholds, and the control strategy fitness function is used to perform global optimization on the multiple control strategy parameters to obtain the target grid connection and disconnection control strategy parameters.

[0047] Furthermore, obtaining the target and disconnection control strategy parameters includes:

[0048] The fitness of the multiple control strategy parameters is evaluated using the control strategy fitness function to obtain the fitness of multiple strategy parameters; gradient ascent is calculated on the fitness of the multiple strategy parameters to determine the optimization direction of the strategy parameters; the threshold of the control strategy parameters is iteratively optimized according to the optimization direction of the strategy parameters to determine the target and off-grid control strategy parameters.

[0049] Preferably, power operation stability parameters are input as constraints into the grid connection / disconnection control strategy space. An initial threshold range for the strategy parameters is obtained through analytical analysis. These thresholds reflect the fundamental limitations on system operation safety and stability. Subsequently, based on the grid connection / disconnection control objectives (such as minimum switching response time or maximum power supply stability), a control strategy fitness function is constructed. This function optimizes power supply efficiency, switching stability, and load fulfillment rate. Multiple control strategy parameters are randomly selected within the threshold range for preliminary optimization evaluation. Next, the fitness function is used to calculate the fitness of the selected control strategy parameters, evaluating the effectiveness of each parameter combination under the current operating conditions. Based on the evaluation results, the fitness gradient direction is calculated, and the direction of the parameter with the largest gradient increase is used as the optimization direction. Finally, the control strategy parameter thresholds are iteratively optimized multiple times according to the optimization direction, gradually adjusting the parameter range and specific values ​​until the optimal parameter combination for the fitness function is found, thus determining the final target grid connection / disconnection control strategy parameters.

[0050] Furthermore, the methods include:

[0051] The grid-connected controller of the hydrogen fuel cell is monitored for grid-connection / off-grid switching to obtain the switching response rate of the grid-connected controller; the switching delay coefficient of the controller is determined based on the switching response rate of the grid-connected controller; power supply loss analysis is performed on the switching delay coefficient of the controller to obtain the power supply loss factor of the controller, and the power supply compensation factor is determined based on the power supply loss factor of the controller; the target grid-connected / off-grid control strategy parameters are further optimized and corrected based on the power supply compensation factor.

[0052] First, the grid-connected controller of the hydrogen fuel cell is monitored for grid-connected / off-grid switching, and the response rate between the grid and the fuel cell during the switching process is recorded to obtain key indicators of the switching response rate. Then, based on the switching response rate, the delay of the controller during grid-connected / off-grid switching is calculated, generating a switching delay coefficient. This coefficient reflects the controller's dynamic response capability during the switching process. Next, the switching delay coefficient is used to analyze power supply loss, assessing the insufficient or excessive power supply to the load caused by the delay, and calculating the controller's power supply loss factor. The power supply impact factor = load interruption power × interruption time + excess power supply × excess time. This factor quantifies the potential impact of power supply fluctuations during the switching process. Further, based on the power supply loss factor, combined with load demand and system energy balance, a corresponding power supply compensation factor (power supply compensation factor = power supply loss factor / switching time) is determined to offset the impact of insufficient or overloaded power supply caused by the switching delay. Finally, the power supply compensation factor is used to further optimize and correct the target grid-connected / off-grid control strategy parameters, ensuring that the strategy parameters can dynamically adapt to actual power supply demands during the switching process, improving switching stability and power supply continuity, thereby further optimizing controller performance.

[0053] In summary, the embodiments of this application have at least the following technical effects:

[0054] First, a hydrogen fuel cell grid-connected controller is acquired, which integrates a data sensing module, an analysis and evaluation module, and an intelligent switching module. Next, the data sensing module monitors and acquires multi-dimensional operational sensing data streams, originating from the hydrogen fuel cell system, energy storage devices, the power grid, and loads. Simultaneously, a power integrated operation evaluation network is constructed based on the analysis and evaluation module, comprising a power grid operation status evaluation network and a hydrogen fuel cell status evaluation network. Then, the multi-dimensional operational sensing data streams are analyzed and evaluated based on the power integrated operation evaluation network to obtain power operation stability parameters. Further, the intelligent switching module invokes a grid-connected / off-grid switching strategy, matching the power operation stability parameters with the strategy to trigger a grid-connected / off-grid control activation strategy. Finally, based on the grid-connected / off-grid control activation strategy, the hydrogen fuel cell grid-connected controller performs grid-connected / off-grid switching and power supply coordination control. This solves the technical problem in existing technologies where hydrogen fuel cell grid-connected controllers struggle to intelligently switch between grid-connected and off-grid modes based on power operation status, achieving intelligent grid-connected / off-grid mode switching.

[0055] Example 2, based on the same inventive concept as the grid-connected / off-grid switching method for the hydrogen fuel cell grid-connected controller in the foregoing examples, such as... Figure 2 As shown, this application provides a grid-connected / off-grid switching system for a hydrogen fuel cell grid-connected controller, wherein the system includes:

[0056] Interactive Component 11: Acquires the hydrogen fuel cell grid-connected controller, which has a built-in data sensing module, analysis and evaluation module, and intelligent switching module; Data Acquisition Component 12: Monitors and acquires multi-dimensional operation sensing data streams through the data sensing module, the sources of which include the hydrogen fuel cell system, energy storage device, power grid, and load; Evaluation Network Construction Component 13: Constructs a power integrated operation evaluation network based on the analysis and evaluation module, which includes a power grid operation status evaluation network and a hydrogen fuel cell status evaluation network; Analysis and Evaluation Component 14: Analyzes and evaluates the multi-dimensional operation sensing data streams based on the power integrated operation evaluation network to obtain power operation stability parameters; Strategy Matching Component 15: Calls the grid-connected / off-grid switching strategy according to the intelligent switching module, and triggers the grid-connected / off-grid control activation strategy based on the power operation stability parameters and the grid-connected / off-grid switching strategy; Control Component 16: Performs grid-connected / off-grid switching and power supply coordination control on the hydrogen fuel cell grid-connected controller based on the grid-connected / off-grid control activation strategy.

[0057] Furthermore, the evaluation network building component 13 is used to perform the following methods:

[0058] A power operation database is constructed, comprising historical power grid operation status datasets and historical hydrogen fuel cell operation status datasets. Correlation features are extracted from both datasets to obtain initial power grid operation correlation feature sets and initial hydrogen fuel cell correlation feature sets. Dimensionality reduction and labeling training are performed on these sets to obtain a power grid operation status assessment network and a hydrogen fuel cell status assessment network. The power grid operation status assessment network and the hydrogen fuel cell status assessment network are then concatenated with equally weighted parameters to construct an integrated power operation assessment network, which is then stored in the parsing and assessment module.

[0059] Furthermore, the evaluation network building component 13 is used to perform the following methods:

[0060] The initial power grid operation associated feature set and the initial hydrogen fuel cell associated feature set are subjected to dimensionality reduction processing to obtain a power grid operation feature sample set and a hydrogen fuel cell feature sample set. Characteristic analysis is then performed on the power grid operation feature sample set and the hydrogen fuel cell feature sample set to obtain power grid data characteristic information and hydrogen fuel cell data characteristic information, respectively. Based on the power grid data characteristic information and the hydrogen fuel cell data characteristic information, a power grid data evaluation model set and a hydrogen fuel cell evaluation model set are selected. Based on the power grid data evaluation model set and the hydrogen fuel cell evaluation model set, the power grid operation feature sample set and the hydrogen fuel cell feature sample set are integrated, trained, and optimized to obtain the power grid operation status evaluation network and the hydrogen fuel cell status evaluation network.

[0061] Furthermore, the evaluation network building component 13 is used to perform the following methods:

[0062] Information on factors influencing power grid operation and hydrogen fuel cell operation is obtained. Based on this information, correlation analysis is performed on the initial power grid operation correlation feature set and the initial hydrogen fuel cell correlation feature set to determine the power grid operation feature correlation set and the hydrogen fuel cell operation feature correlation set. Based on these two sets, a power grid operation feature cluster and a hydrogen fuel cell operation feature cluster are constructed. The power grid operation feature cluster and the hydrogen fuel cell operation feature cluster are then subjected to feature dimensionality reduction and filtering at a preset distance to obtain the power grid operation feature sample set and the hydrogen fuel cell feature sample set.

[0063] Furthermore, the control component 16 is used to perform the following methods:

[0064] Based on the grid connection / off-grid control activation strategy, a target grid connection / off-grid mode is determined; the hydrogen fuel cell grid connection controller is switched between grid connection and off-grid mode according to the target grid connection / off-grid mode to obtain a grid connection / off-grid control strategy; based on the grid connection / off-grid control strategy, a grid connection / off-grid control strategy space is constructed; based on the power operation stability parameters, the grid connection / off-grid control strategy space is analyzed and optimized to determine the target grid connection / off-grid control strategy parameters, and power supply coordination control is performed through the target grid connection / off-grid control strategy parameters.

[0065] Furthermore, the control component 16 is used to perform the following methods:

[0066] Using the power operation stability parameters as constraint parameters, the grid connection and disconnection control strategy space is analyzed to obtain control strategy parameter thresholds; based on the grid connection and disconnection control objectives, a control strategy fitness function is constructed; multiple control strategy parameters are randomly selected within the control strategy parameter thresholds, and the control strategy fitness function is used to perform global optimization on the multiple control strategy parameters to obtain the target grid connection and disconnection control strategy parameters.

[0067] Furthermore, the control component 16 is used to perform the following methods:

[0068] The fitness of the multiple control strategy parameters is evaluated using the control strategy fitness function to obtain the fitness of multiple strategy parameters; gradient ascent is calculated on the fitness of the multiple strategy parameters to determine the optimization direction of the strategy parameters; the threshold of the control strategy parameters is iteratively optimized according to the optimization direction of the strategy parameters to determine the target and off-grid control strategy parameters.

[0069] Furthermore, the control component 16 is used to perform the following methods:

[0070] The grid-connected controller of the hydrogen fuel cell is monitored for grid-connection / off-grid switching to obtain the switching response rate of the grid-connected controller; the switching delay coefficient of the controller is determined based on the switching response rate of the grid-connected controller; power supply loss analysis is performed on the switching delay coefficient of the controller to obtain the power supply loss factor of the controller, and the power supply compensation factor is determined based on the power supply loss factor of the controller; the target grid-connected / off-grid control strategy parameters are further optimized and corrected based on the power supply compensation factor.

[0071] Furthermore, the control component 16 is used to perform the following methods:

[0072] The grid connection and off-grid control strategies specifically include: grid connection control strategy in grid connection mode and islanding control strategy in off-grid mode.

[0073] It should be noted that the order of the embodiments described above is for descriptive purposes only and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0074] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0075] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and modifications fall within the scope of this application and its equivalents, this application intends to include such modifications and modifications.

Claims

1. A method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller, characterized in that, The method includes: Obtain a hydrogen fuel cell grid-connected controller, which has a built-in data sensing module, analysis and evaluation module and intelligent switching module; The data sensing module monitors and acquires multi-dimensional operational sensing data streams, the sources of which include hydrogen fuel cell systems, energy storage devices, power grids, and loads. A power integrated operation assessment network is constructed based on the analytical assessment module. The power integrated operation assessment network includes a power grid operation status assessment network and a hydrogen fuel cell status assessment network. Based on the power integrated operation evaluation network, the multi-dimensional operation perception data stream is analyzed and evaluated to obtain power operation stability parameters; According to the intelligent switching module, the grid connection and off-grid switching strategy is invoked, and the grid connection and off-grid switching strategy is matched with the power operation stability parameters to trigger the grid connection and off-grid control activation strategy. Based on the aforementioned grid-connected / off-grid control activation strategy, the hydrogen fuel cell grid-connected controller is used for grid-connected / off-grid switching and power supply coordination control.

2. The method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller as described in claim 1, characterized in that, The establishment of the integrated power operation assessment network includes: Construct a power operation database, which includes a historical power grid operation status dataset and a historical hydrogen fuel cell operation status dataset; Correlation features were extracted from the historical power grid operation status dataset and the historical hydrogen fuel cell operation status dataset to obtain the initial power grid operation correlation feature set and the initial hydrogen fuel cell correlation feature set. The initial power grid operation associated feature set and the initial hydrogen fuel cell associated feature set are subjected to dimensionality reduction and labeling training to obtain the power grid operation status assessment network and the hydrogen fuel cell status assessment network. The power grid operation status assessment network and the hydrogen fuel cell status assessment network are connected in series with equal weights to build an integrated power operation assessment network, and the integrated power operation assessment network is stored in the parsing assessment module.

3. The method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller as described in claim 2, characterized in that, The obtained power grid operation status assessment network and hydrogen fuel cell status assessment network include: The initial power grid operation associated feature set and the initial hydrogen fuel cell associated feature set are subjected to dimensionality reduction processing to obtain the power grid operation feature sample set and the hydrogen fuel cell feature sample set. Characteristic analysis was performed on the power grid operation characteristic sample set and the hydrogen fuel cell characteristic sample set respectively to obtain power grid data characteristic information and hydrogen fuel cell data characteristic information. Based on the power grid data characteristic information and the hydrogen fuel cell data characteristic information, select the power grid data evaluation model set and the hydrogen fuel cell evaluation model set; Based on the power grid data evaluation model set and the hydrogen fuel cell evaluation model set, the power grid operation feature sample set and the hydrogen fuel cell feature sample set are integrated, trained and optimized respectively to obtain the power grid operation status evaluation network and the hydrogen fuel cell status evaluation network.

4. The method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller as described in claim 3, characterized in that, The acquisition of the power grid operation characteristic sample set and the hydrogen fuel cell characteristic sample set includes: Obtain information on factors affecting power grid operation and hydrogen fuel cell operation; Based on the information on factors affecting power grid operation and hydrogen fuel cell operation, correlation analysis is performed on the initial power grid operation correlation feature set and the initial hydrogen fuel cell correlation feature set to determine the power grid operation feature correlation set and the hydrogen fuel cell operation feature correlation set. Based on the aforementioned power grid operation characteristic correlation set and hydrogen fuel cell operation characteristic correlation set, construct power grid operation characteristic clusters and hydrogen fuel cell operation characteristic clusters; The power grid operation feature cluster and the hydrogen fuel cell operation feature cluster are subjected to feature dimensionality reduction screening according to a preset distance to obtain the power grid operation feature sample set and the hydrogen fuel cell feature sample set.

5. The method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller as described in claim 1, characterized in that, The method of performing grid-connection / off-grid switching and power supply coordination control on the hydrogen fuel cell grid-connected controller based on the grid-connection / off-grid control activation strategy includes: Based on the aforementioned grid connection / disconnection control activation strategy, determine the target grid connection / disconnection mode; According to the target grid-connected / off-grid mode, the hydrogen fuel cell grid-connected controller is switched between grid-connected and off-grid modes to obtain the grid-connected / off-grid control strategy; Based on the aforementioned grid connection and disconnection control strategies, the grid connection and disconnection control strategy space is explored and constructed. Based on the power operation stability parameters, the control analysis and optimization of the grid connection and disconnection control strategy space are performed to determine the target grid connection and disconnection control strategy parameters, and power supply coordination control is performed through the target grid connection and disconnection control strategy parameters.

6. The method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller as described in claim 5, characterized in that, The parameters for the target determination and off-grid control strategy include: Using the power operation stability parameters as constraint parameters, the grid connection and disconnection control strategy space is analyzed to obtain the control strategy parameter thresholds. Based on the control objectives of grid connection and disconnection, construct the fitness function of the control strategy; Multiple control strategy parameters are randomly selected within the threshold range of the control strategy parameters. The control strategy fitness function is used to perform global optimization on the multiple control strategy parameters to obtain the target and off-grid control strategy parameters.

7. The method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller as described in claim 6, characterized in that, The process of obtaining the target and disconnecting the network control strategy parameters includes: The fitness of the multiple control strategy parameters is evaluated using the control strategy fitness function to obtain the fitness of the multiple strategy parameters; Gradient ascent calculation is performed on the fitness of the multiple strategy parameters to determine the optimization direction of the strategy parameters. The threshold of the control strategy parameters is iteratively optimized according to the optimization direction of the strategy parameters to determine the target and off-grid control strategy parameters.

8. The method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller as described in claim 7, characterized in that, The method includes: The grid-connected controller of the hydrogen fuel cell is monitored for grid-connected / off-grid switching to obtain the switching response rate of the grid-connected controller; The controller switching delay coefficient is determined based on the grid-connected controller switching response rate; A power supply loss analysis is performed on the switching delay coefficient of the controller to obtain the controller power supply loss factor, and a power supply compensation factor is determined based on the controller power supply loss factor. The target on-grid and off-grid control strategy parameters are further optimized and corrected based on the power supply compensation factor.

9. The method for switching between grid connection and off-grid operation for a hydrogen fuel cell grid-connected controller as described in claim 5, characterized in that, The grid connection and off-grid control strategies specifically include: grid connection control strategy in grid connection mode and islanding control strategy in off-grid mode.

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