Hydrogen energy conversion efficiency optimization system and method based on historical data

Abstract

The invention discloses a hydrogen energy conversion efficiency optimization system and method based on historical data, and relates to the technical field of hydrogen energy conversion, the efficiency optimization system comprises a hydrogen energy data acquisition and processing module, a hardware architecture management module, a hydrogen energy conversion efficiency optimization module and a historical data management and control module, according to the invention, by arranging the hydrogen energy data acquisition and processing module, the hardware architecture management module, the hydrogen energy conversion efficiency optimization module and the historical data management and control module, a perfect efficiency optimization system is constructed, remote and on-site early warning processing is carried out on abnormal data in environmental data monitoring, the environmental data monitoring condition is imaged in real time, and the monitoring efficiency is improved. Through intelligent data analysis and access cooperation of various algorithms, hydrogen energy conversion efficiency optimization data and corresponding analysis results are managed, visualized and stored, hydrogen energy conversion efficiency optimization management can be achieved through cloud management and control of the Internet of Things, and the intelligent level of hydrogen energy conversion efficiency optimization management is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrogen energy conversion, and particularly to a hydrogen energy conversion efficiency optimization system and method based on historical data. Background Art

[0002] As a clean energy source, hydrogen energy is widely used in fields such as fuel cells, power systems, and transportation. However, during the conversion process of hydrogen energy, affected by various factors such as equipment performance, environmental conditions, and operating parameters, the conversion efficiency often fluctuates.

[0003] Chinese Patent Publication No. CN 119209650 B discloses an intelligent optimization method and system for the photovoltaic conversion efficiency of a water-light-storage energy source, which relates to the technical field of electrical energy storage. By obtaining the hydraulic power generation parameter space and the photovoltaic power generation environmental parameters, constructing a hydraulic power generation optimization function, optimizing the hydraulic power generation parameters, obtaining the optimal hydraulic power generation parameters, the optimal hydraulic power generation power, the optimal photovoltaic power generation power, and the optimal basic conversion efficiency of photovoltaic power generation, calculating the optimal total power generation according to the optimal hydraulic power generation power and the optimal photovoltaic power generation power for energy storage scheduling optimization, calculating the optimal scheduling conversion efficiency, and correcting and calculating the optimal basic conversion efficiency to obtain the optimization result of the photovoltaic conversion efficiency. It solves the technical problems in the prior art that the energy storage and photovoltaic conversion efficiency in water-light-storage are low, affecting the reasonable distribution and efficient utilization of electrical energy. It achieves the technical effect of improving the energy storage and photovoltaic conversion efficiency in water-light-storage and improving the overall performance of the water-light-storage energy platform.

[0004] However, the following problems still exist in the above solution: In the process of hydrogen energy conversion based on long-term historical data, there are multiple influencing factors, and at the same time, the hardware equipment runs for a long time, making it difficult to accurately predict the impact of equipment decline on efficiency in the long term. As the equipment ages, it will also affect the optimization of hydrogen energy conversion efficiency, making it inconvenient for staff to supervise the overall process, and the overall intelligent management level is relatively low. Therefore, the present invention needs to design a hydrogen energy conversion efficiency optimization system and method based on historical data to solve the above problems. Summary of the Invention

[0005] The purpose of the present invention is to provide a hydrogen energy conversion efficiency optimization system and method based on historical data to solve the problems mentioned in the background art.

[0006] To solve the above problems, the present invention provides a technical solution:

[0007] A hydrogen energy conversion efficiency optimization system based on historical data. The efficiency optimization system includes a hydrogen energy data acquisition and processing module, a hardware architecture management module, a hydrogen energy conversion efficiency optimization module, and a historical data control module. The hardware architecture management module maintains data interconnection and sharing with the hydrogen energy data acquisition and processing module, the hydrogen energy conversion efficiency optimization module, and the historical data control module respectively through the Internet of Things. Staff can access the hydrogen energy conversion efficiency optimization module to view the real-time operation data of the hydrogen energy data acquisition and processing module, the hardware architecture management module, and the historical data control module one by one inside the efficiency optimization system.

[0008] As a preferred embodiment of the present invention, the output end of the hydrogen energy data acquisition and processing module is communicatively connected to the input end of the hydrogen energy conversion efficiency optimization module. The output end of the historical data control module is communicatively connected to the input end of the hydrogen energy conversion efficiency optimization module. The hardware architecture management module is in bidirectional communication connection with the hydrogen energy conversion efficiency optimization module. The efficiency optimization system further includes an environmental data supervision module, and the output end of the environmental data supervision module is communicatively connected to the input end of the hydrogen energy conversion efficiency optimization module.

[0009] As a preferred embodiment of the present invention, the hydrogen energy data acquisition and processing module is used to collect historical data related to hydrogen energy conversion, clean and standardize the historical data, and locate the collected historical data sources at the same time.

[0010] The hardware architecture management module is used to construct a hardware management center and a software management center, continuously update the hardware and software information inside the management center, provide the permission for users to edit independently, and customize a personalized user operation interface.

[0011] The hydrogen energy conversion efficiency optimization module is used to construct an efficiency optimization model, train the model using historical data, evaluate the accuracy and generalization ability of the model, and connect algorithms related to hydrogen energy conversion efficiency optimization at the same time, and continuously update the connected algorithms.

[0012] The historical data control module is used to store the historical data generated during the hydrogen energy conversion process, analyze the performance of the hydrogen energy conversion equipment through historical data, evaluate the energy efficiency performance under different operating conditions, obtain the equipment of different manufacturers and the sensor data of different standards, and adopt a unified communication protocol to promote the standardization of data in the hydrogen energy field.

[0013] The environmental data supervision module is used to obtain the specific data of the hydrogen energy conversion equipment as time goes by and the surrounding environmental conditions change through sensing and acquisition equipment, remotely and on-site give early warnings for abnormal data in environmental data monitoring, and image the environmental data monitoring situation in real time.

[0014] As a preferred embodiment of the present invention, the hydrogen energy data acquisition and processing module includes a hydrogen energy data acquisition unit, a hydrogen energy data preprocessing unit, a synchronous monitoring unit, and a hydrogen energy data source positioning unit. The output end of the hydrogen energy data acquisition unit is communicatively connected to the input end of the hydrogen energy data preprocessing unit. The hydrogen energy data source positioning unit is integrated inside the hydrogen energy data acquisition unit, and the hydrogen energy data preprocessing unit and the synchronous monitoring unit are communicatively connected bidirectionally;

[0015] The hydrogen energy data acquisition unit is used to collect historical data related to hydrogen energy conversion, including hydrogen production data, storage and transportation data, and air pressure and temperature data;

[0016] The hydrogen energy data preprocessing unit is used to clean and standardize the historical data, including filling missing values, processing outliers, and feature scaling;

[0017] The synchronous monitoring unit is used to perform real-time monitoring and processing on the data of each module and unit during the operation of the efficiency optimization system. Sensitive words, risk factors, and other data are preset, and autonomous interception processing is performed during monitoring, and necessary manual intervention is carried out;

[0018] The hydrogen energy data source positioning unit is used to locate the collected historical data sources, and when data anomalies occur, the real location can be located for query and corresponding processing.

[0019] As a preferred embodiment of the present invention, the hardware architecture management module includes a hardware architecture construction unit, a hardware architecture management unit, a hardware architecture software access unit, and a user interface interaction unit. The output end of the hardware architecture construction unit is communicatively connected to the input end of the hardware architecture management unit. The hardware architecture management unit and the hardware architecture software access unit are communicatively connected bidirectionally;

[0020] The hardware architecture construction unit is used to construct a hardware management center and continuously update the hardware information inside the management center;

[0021] The hardware architecture management unit is used to record the hardware device information at different locations and keep subsequent data updated, including hardware device installation data information, hardware device maintenance data information, and hardware device operation data information;

[0022] The hardware architecture software access unit is used to construct a software management center and continuously update the hardware information inside the management center, and continuously access different software according to the requirements of each energy conversion and efficiency optimization;

[0023] The user interface interaction unit is used to provide the permission for users to edit independently, customize a personalized user operation interface, facilitate the operation of staff with different requirements, and perform identity information verification operations when users edit independently.

[0024] As a preferred embodiment of the present invention, the hydrogen energy conversion efficiency optimization module includes a hydrogen energy conversion efficiency optimization unit, an algorithm access database, an algorithm optimization unit, and an evaluation and feedback unit. The algorithm optimization unit is integrated inside the algorithm access database. The output end of the algorithm access database is communicatively connected to the input end of the hydrogen energy conversion efficiency optimization unit, and the output end of the hydrogen energy conversion efficiency optimization unit is communicatively connected to the input end of the evaluation and feedback unit;

[0025] The hydrogen energy conversion efficiency optimization unit is used to construct an efficiency optimization model, train the model using historical data, and evaluate the accuracy and generalization ability of the model;

[0026] The algorithm access database is used to access algorithms related to the optimization of hydrogen energy conversion and continuously update the accessed algorithms;

[0027] The algorithms include but are not limited to:

[0028] The time series analysis algorithm. When analyzing the production and conversion efficiency of hydrogen energy, historical data is often time series data. The time series analysis is used to extract patterns such as seasonality, trend, and periodicity from historical data through the algorithm for prediction and optimization;

[0029] The linear regression algorithm. The linear regression algorithm is used to predict the efficiency in the hydrogen energy conversion process through regression analysis;

[0030] The decision tree and random forest algorithms. The decision tree and random forest algorithms are used to construct a decision model by training historical data and evaluate the influence of different operating conditions on the conversion efficiency;

[0031] The particle swarm optimization algorithm. The particle swarm optimization algorithm is used to find the optimal hydrogen energy conversion parameters in a multi-dimensional space;

[0032] The long short-term memory network algorithm. The long short-term memory network algorithm is used to process and predict time series data and is used for long-term prediction of the long-term efficiency of the hydrogen energy system;

[0033] The algorithm optimization unit is used to optimize various key parameters in the hydrogen production and storage processes according to different environments and operating conditions. By optimizing these parameters, the production efficiency of hydrogen energy can be maximized. The parameters include temperature, pressure, flow rate, and current density;

[0034] It is also used to utilize distributed computing and cloud computing platforms to allocate data storage and computing tasks to multiple nodes, improve computing efficiency, and thus balance multiple targets. The distributed computing framework includes, but is not limited to, large-scale data sets of Apache Spark and Hadoop;

[0035] The evaluation and feedback unit is used to evaluate the optimized hydrogen energy conversion efficiency, conduct comparative experiments by analyzing the effects of different models, and feedback the evaluation results to the efficiency optimization system according to the evaluation results. The optimization algorithm then iteratively adjusts based on new data, realizing intelligent control and automated adjustment operations, comparing real-time data with historical data, and automatically adjusting model parameters and operating conditions.

[0036] As a preferred embodiment of the present invention, the historical data management module includes a historical data storage center, a data security and backup unit, and a historical data integration unit. The data security and backup unit is integrated inside the historical data storage center, and the output end of the historical data integration unit is communicatively connected to the input end of the historical data storage center;

[0037] The historical data storage center is used to store historical data generated during the hydrogen energy conversion process. The historical data includes the production volume of hydrogen, conversion efficiency, equipment status, key parameters of energy input and output, data mining, and trend analysis;

[0038] It is also used to analyze the performance of hydrogen energy conversion equipment through historical data, evaluate the energy efficiency performance under different operating conditions, help identify the bottlenecks and inefficient links of the efficiency optimization system, and provide data support for optimization measures;

[0039] The data security and backup unit is used to protect important data in the efficiency optimization system, ensure the integrity, availability, and security of the data, and perform encryption processing during data storage and transmission;

[0040] It is also used to regularly back up key data in the efficiency optimization system, including historical data, equipment operation data, and optimization algorithm models. The backups are stored in different locations, including local storage, cloud storage, and off-site storage;

[0041] The historical data integration unit is used to obtain data from equipment of different manufacturers and sensors of different standards, adopt a unified communication protocol to promote the standardization of data in the hydrogen energy field. The communication protocol includes, but is not limited to, MQTT and OPC UA, to facilitate data sharing and integration between different devices.

[0042] As a preferred embodiment of the present invention, the environmental data supervision module includes an environmental data supervision unit, a field data warning unit, and a visualization imaging unit. The output ends of the environmental data supervision unit and the field data warning unit are both communicatively connected to the input end of the visualization imaging unit;

[0043] The environmental data supervision unit is used to obtain the specific data of the hydrogen energy conversion device as the usage time progresses and the surrounding environmental conditions change through sensing and acquisition devices. The environmental conditions include temperature, humidity, and air pressure. The sensing and acquisition devices include temperature and humidity sensors;

[0044] The field data warning unit is used to perform remote and on-site warning processing on abnormal data detected in environmental data monitoring. Abnormal data thresholds can be preset manually, and the responses when the thresholds are exceeded can be set for different levels;

[0045] Primary warning: It can be processed by the efficiency optimization system itself;

[0046] Intermediate warning: Conduct dual on-site and remote warnings through warning devices;

[0047] Ultimate warning: Back up the data of the real-time operation of the efficiency optimization system. After the backup is completed, interrupt the operation status of the efficiency optimization system;

[0048] The visualization imaging unit is used to manually set warning thresholds and indicators, and is used to image the environmental data monitoring situation in real time, conduct comprehensive comparison in tabular form, and adopt a reinforcement learning algorithm to enable the efficiency optimization system to continuously learn and optimize based on historical data and real-time feedback to cope with equipment degradation and environmental changes.

[0049] A method for optimizing hydrogen energy conversion efficiency based on historical data includes the following specific steps:

[0050] S1. The efficiency optimization system collects historical data related to hydrogen energy conversion, cleans and standardizes the historical data, presets data such as sensitive words and risk factors, and conducts real-time monitoring and processing on the data of each module and unit during operation. The efficiency optimization system constructs a hardware and software management center, continuously updates the hardware and software information inside the management center, provides the right for users to edit independently, and conducts identity information verification operations when users edit independently;

[0051] S2. The efficiency optimization system constructs an efficiency optimization model, uses historical data for model training, and evaluates the accuracy and generalization ability of the model. It accesses algorithms related to the optimization of hydrogen energy conversion efficiency, optimizes various key parameters in the hydrogen production and storage processes according to different environmental and operating conditions. By optimizing these parameters, the accessed algorithms are continuously updated, and the optimized hydrogen energy conversion efficiency is evaluated. Comparative experiments are conducted by analyzing the effects of different models.

[0052] S3. The efficiency optimization system stores the historical data generated during the hydrogen energy conversion process, analyzes the performance of hydrogen energy conversion equipment through historical data, and evaluates the energy efficiency performance under different operating conditions. It obtains data from equipment of different manufacturers and sensor data of different standards, adopts a unified communication protocol to promote the standardization of data in the hydrogen energy field. Specific data on hydrogen energy conversion equipment over time and changes in the surrounding environmental conditions are obtained through sensing and acquisition devices. Remote and on-site warning processing is carried out for abnormal data in environmental data monitoring. Warning thresholds and indicators are set manually, and the environmental data monitoring situation is imaged in real time and comprehensively compared in tabular form to complete a hydrogen energy conversion efficiency optimization process.

[0053] As a preferred embodiment of the present invention, the thresholds in step S3 include the following levels:

[0054] Primary warning: It can be processed by the efficiency optimization system itself.

[0055] Intermediate warning: Dual on-site and remote warnings are carried out through warning devices.

[0056] Ultimate warning: Back up the data of the real-time operation of the efficiency optimization system, and interrupt the operation status of the efficiency optimization system after the backup is completed.

[0057] The beneficial effects of the present invention are as follows: By setting up a hydrogen energy data acquisition and processing module, a hardware architecture management module, a hydrogen energy conversion efficiency optimization module, and a historical data control module, a perfect efficiency optimization system is constructed. In actual use, the historical data related to hydrogen energy conversion is collected by the hydrogen energy data acquisition and processing module, and the historical data is cleaned and standardized. At the same time, the location of the collected historical data sources is determined. The hardware architecture management module constructs a hardware management center and a software management center, and continuously updates the hardware and software information inside the management center, providing users with the permission to edit independently and customizing a personalized user operation interface. The hydrogen energy conversion efficiency optimization module constructs an efficiency optimization model, uses historical data for model training, and evaluates the accuracy and generalization ability of the model. At the same time, algorithms related to hydrogen energy conversion efficiency optimization are connected, and the connected algorithms are continuously updated. The historical data control module stores the historical data generated during the hydrogen energy conversion process, analyzes the performance of the hydrogen energy conversion equipment through historical data, evaluates the energy efficiency performance under different operating conditions, obtains the data of equipment from different manufacturers and sensors with different standards, and adopts a unified communication protocol to promote the standardization of data in the hydrogen energy field. The environmental data supervision module is used to obtain the specific data of the hydrogen energy conversion equipment as time goes by and the surrounding environmental conditions change through sensing and acquisition devices, and remotely and on-site warn and process abnormal data in environmental data monitoring, and real-time image the environmental data monitoring situation. It can cooperate with intelligent data analysis and various connected algorithms to optimize various parameters in the hydrogen energy conversion process in real time, significantly improve the energy conversion efficiency, reduce energy consumption, avoid the equipment from operating under inappropriate working conditions through historical data analysis and optimization, thereby reducing the equipment failure rate, reducing the maintenance cost, and extending the service life of the equipment. Managing, visualizing, and storing the hydrogen energy conversion efficiency optimization data and the corresponding analysis results helps to realize the optimization management of hydrogen energy conversion efficiency through Internet of Things cloud control and improve the intelligent level of hydrogen energy conversion efficiency optimization management. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] For ease of explanation, the present invention is described in detail by the following specific embodiments and the accompanying drawings.

[0059] Figure 1 FIG. is the overall system structure topology diagram of a hydrogen energy conversion efficiency optimization system and method based on historical data according to the present invention;

[0060] Figure 2 FIG. is the overall method flow chart of a hydrogen energy conversion efficiency optimization system and method based on historical data according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0061] As Figure 1 - Figure 2 shown, the following technical solutions are adopted in this specific embodiment:

[0062] A hydrogen energy conversion efficiency optimization system based on historical data. The efficiency optimization system includes a hydrogen energy data acquisition and processing module, a hardware architecture management module, a hydrogen energy conversion efficiency optimization module, and a historical data control module. The hardware architecture management module maintains data intercommunication and sharing with the hydrogen energy data acquisition and processing module, the hydrogen energy conversion efficiency optimization module, and the historical data control module respectively through the Internet of Things. Staff can access the hydrogen energy conversion efficiency optimization module to view the real-time operation data of the hydrogen energy data acquisition and processing module, the hardware architecture management module, and the historical data control module one by one inside the efficiency optimization system.

[0063] The output end of the hydrogen energy data acquisition and processing module is communicatively connected to the input end of the hydrogen energy conversion efficiency optimization module. The output end of the historical data control module is communicatively connected to the input end of the hydrogen energy conversion efficiency optimization module. The hardware architecture management module is in two-way communication connection with the hydrogen energy conversion efficiency optimization module. The efficiency optimization system further includes an environmental data supervision module, and the output end of the environmental data supervision module is communicatively connected to the input end of the hydrogen energy conversion efficiency optimization module.

[0064] Hydrogen energy data acquisition:

[0065] S100. The hydrogen energy data acquisition and processing module is used to collect historical data related to hydrogen energy conversion, clean and standardize the historical data, and locate the collected historical data sources at the same time.

[0066] S101. The hydrogen energy data acquisition and processing module includes a hydrogen energy data acquisition unit, a hydrogen energy data preprocessing unit, a synchronous monitoring unit, and a hydrogen energy data source location unit. Keep the output end of the hydrogen energy data acquisition unit communicatively connected to the input end of the hydrogen energy data preprocessing unit. Keep the hydrogen energy data source location unit integrated inside the hydrogen energy data acquisition unit. Keep the hydrogen energy data preprocessing unit and the synchronous monitoring unit in two-way communication connection.

[0067] S102. The hydrogen energy data acquisition unit collects historical data related to hydrogen energy conversion, including hydrogen production data, storage and transportation data, and air pressure and temperature data.

[0068] S103. The hydrogen energy data preprocessing unit cleans and standardizes the historical data, including filling in missing values, dealing with outliers, and feature scaling.

[0069] S104. The hydrogen energy data source location unit locates the collected historical data sources, and when the data is abnormal, it can locate the real location for query and corresponding processing.

[0070] S105. The synchronization monitoring unit performs real-time monitoring and processing on the data of each module and unit during the operation of the efficiency optimization system, pre-sets data such as sensitive words and risk factors, performs autonomous interception processing during monitoring, and conducts necessary manual intervention.

[0071] Environmental data supervision:

[0072] S200. The environmental data supervision module acquires the specific data of the hydrogen energy conversion device over time and changes in surrounding environmental conditions through sensing and acquisition devices, conducts remote and on-site early warning processing for abnormal data in environmental data monitoring, and provides real-time imaging of the environmental data monitoring situation;

[0073] S201. The environmental data supervision module includes an environmental data supervision unit, an on-site data early warning unit, and a visualization imaging unit, and keeps the output ends of the environmental data supervision unit and the on-site data early warning unit in communication connection with the input end of the visualization imaging unit;

[0074] S202. The environmental data supervision unit acquires the specific data of the hydrogen energy conversion device over time and changes in surrounding environmental conditions through sensing and acquisition devices. The environmental conditions include temperature, humidity, and air pressure. The sensing and acquisition devices include temperature and humidity sensors;

[0075] S203. The on-site data early warning unit conducts remote and on-site early warning processing for abnormal data in environmental data monitoring, and the abnormal data threshold can be pre-set manually;

[0076] S204. Set the level of response when exceeding the threshold;

[0077] Primary early warning: It can be processed by the efficiency optimization system itself;

[0078] Intermediate early warning: Conduct dual on-site and remote early warnings through warning devices;

[0079] Ultimate early warning: Back up the data of the real-time operation of the efficiency optimization system, and interrupt the operation status of the efficiency optimization system after the backup is completed;

[0080] S205. The visualization imaging unit is used to manually set early warning thresholds and indicators, for real-time imaging of the environmental data monitoring situation, conduct comprehensive comparison in tabular form, and adopt a reinforcement learning algorithm to enable the efficiency optimization system to continuously learn and optimize based on historical data and real-time feedback to cope with equipment decline and environmental changes.

[0081] Hydrogen energy conversion efficiency optimization:

[0082] S300. The hydrogen energy conversion efficiency optimization module constructs an efficiency optimization model, uses historical data for model training, evaluates the accuracy and generalization ability of the model, and at the same time accesses algorithms related to hydrogen energy conversion efficiency optimization and continuously updates the accessed algorithms;

[0083] S301. The hydrogen energy conversion efficiency optimization module includes a hydrogen energy conversion efficiency optimization unit, an algorithm access database, an algorithm optimization unit, and an evaluation and feedback unit. The algorithm optimization unit is integrated inside the algorithm access database, maintaining a communication connection between the output end of the algorithm access database and the input end of the hydrogen energy conversion efficiency optimization unit, and maintaining a communication connection between the output end of the hydrogen energy conversion efficiency optimization unit and the input end of the evaluation and feedback unit;

[0084] S302. The hydrogen energy conversion efficiency optimization unit constructs an efficiency optimization model, uses historical data for model training, and evaluates the accuracy and generalization ability of the model;

[0085] S303. The algorithm access database accesses algorithms related to hydrogen energy conversion efficiency optimization and continuously updates the accessed algorithms;

[0086] S304. The algorithms include but are not limited to:

[0087] The time series analysis algorithm. When analyzing hydrogen energy production and conversion efficiency, historical data is often time series data. The algorithm extracts patterns such as seasonality, trend, and periodicity from historical data for prediction and optimization;

[0088] The linear regression algorithm. The linear regression algorithm is used to predict the efficiency in the hydrogen energy conversion process through regression analysis;

[0089] The decision tree and random forest algorithms. The decision tree and random forest algorithms are used to construct a decision model by training historical data to evaluate the impact of different operating conditions on the conversion efficiency;

[0090] The particle swarm optimization algorithm. The particle swarm optimization algorithm is used to find the optimal hydrogen energy conversion parameters in a multi-dimensional space;

[0091] The long short-term memory network algorithm. The long short-term memory network algorithm is used to process and predict time series data for long-term prediction of the long-term efficiency of the hydrogen energy system;

[0092] S305. The algorithm optimization unit optimizes various key parameters in the hydrogen production and storage processes according to different environments and operating conditions. By optimizing these parameters, the production efficiency of hydrogen energy can be maximized. The parameters include temperature, pressure, flow rate, and current density;

[0093] S306. The algorithm optimization unit also utilizes distributed computing and cloud computing platforms to distribute data storage and computing tasks to multiple nodes, improving computing efficiency, thereby balancing among multiple targets. The distributed computing framework includes, but is not limited to, large-scale data sets of Apache Spark and Hadoop;

[0094] S307. The evaluation and feedback unit evaluates the optimized hydrogen energy conversion efficiency, conducts comparative experiments by analyzing the effects of different models, and feeds back the evaluation results to the efficiency optimization system. The optimization algorithm then iteratively adjusts according to new data, realizing intelligent control and automated adjustment operations, comparing real-time data with historical data, and automatically adjusting model parameters and operating conditions.

[0095] Hardware architecture management:

[0096] S400. The hardware architecture management module is used to construct a hardware management center and a software management center, continuously update the hardware and software information inside the management center, provide the right for users to edit independently, and customize a personalized user operation interface;

[0097] S401. The hardware architecture management module includes a hardware architecture construction unit, a hardware architecture management unit, a hardware architecture software access unit, and a user interface interaction unit. Keep the output end of the hardware architecture construction unit in communication connection with the input end of the hardware architecture management unit, and keep the hardware architecture management unit and the hardware architecture software access unit in two-way communication connection;

[0098] S402. The hardware architecture construction unit constructs a hardware management center and continuously updates the hardware information inside the management center;

[0099] S403. The hardware architecture management unit records the hardware device information at different locations and keeps subsequent data updated, including hardware device installation data information, hardware device maintenance data information, and hardware device operation data information;

[0100] S404. The hardware architecture software access unit constructs a software management center, continuously updates the hardware information inside the management center, and continuously accesses different software according to each energy conversion and efficiency optimization requirement;

[0101] S405. The user interface interaction unit provides the right for users to edit independently, customizes a personalized user operation interface, facilitates the operation of staff with different requirements, and conducts identity information verification operations when users edit independently.

[0102] Historical data control:

[0103] S500. The historical data control module is used to store the historical data generated during the hydrogen energy conversion process, analyze the performance of hydrogen energy conversion equipment through historical data, evaluate the energy efficiency performance under different operating conditions, obtain the equipment of different manufacturers and sensor data of different standards, and adopt a unified communication protocol to promote the standardization of data in the hydrogen energy field;

[0104] S501. The historical data control module includes a historical data storage center, a data security and backup unit, and a historical data integration unit. The data security and backup unit is integrated inside the historical data storage center, and the output end of the historical data integration unit is communicatively connected to the input end of the historical data storage center;

[0105] S502. The historical data storage center stores the historical data generated during the hydrogen energy conversion process. The historical data includes the production volume of hydrogen, conversion efficiency, equipment status, key parameters of energy input and output, data mining, and trend analysis;

[0106] S503. The historical data storage center also analyzes the performance of hydrogen energy conversion equipment through historical data, evaluates the energy efficiency performance under different operating conditions, helps identify the bottlenecks and inefficient links of the efficiency optimization system, and provides data support for optimization measures;

[0107] S504. The data security and backup unit protects the important data in the efficiency optimization system, ensures the integrity, availability, and security of the data, and performs encryption processing during data storage and transmission;

[0108] S505. The data security and backup unit also regularly backs up the key data in the efficiency optimization system, including historical data, equipment operation data, and optimization algorithm models. The backups are stored in different locations, including local storage, cloud storage, and off-site storage;

[0109] S506. The historical data integration unit is used to obtain the equipment of different manufacturers and sensor data of different standards, and adopt a unified communication protocol to promote the standardization of data in the hydrogen energy field. The communication protocol includes but is not limited to MQTT and OPC UA to facilitate data sharing and integration between different devices.

[0110] Embodiment

[0111] When the efficiency optimization system is connected to the hydrogen energy conversion management:

[0112] S1. The staff conducts a one-by-one inspection of the on-site and remote power equipment. After ensuring that they can all operate normally, the efficiency optimization system is started, and the corresponding algorithms are accessed according to the historical data and hydrogen energy data to be queried this time;

[0113] The linear regression algorithm, which is used to predict the efficiency in the hydrogen energy conversion process through regression analysis;

[0114] The decision tree and random forest algorithms, which are used to construct a decision model by training historical data and evaluate the impact of different operating conditions on the conversion efficiency;

[0115] The particle swarm optimization algorithm, which is used to find the optimal hydrogen energy conversion parameters in a multi-dimensional space;

[0116] S2. The efficiency optimization system collects historical data related to hydrogen energy conversion, cleans and standardizes the historical data, pre-sets data such as sensitive words and risk factors, performs real-time monitoring on the data of each module and unit during operation, constructs a hardware and software management center, continuously updates the hardware and software information inside the management center, provides the permission for users to edit independently, and conducts identity information verification operations when users edit independently;

[0117] S3. The efficiency optimization system constructs an efficiency optimization model, uses historical data for model training, evaluates the accuracy and generalization ability of the model, accesses algorithms related to the optimization of hydrogen energy conversion efficiency, optimizes various key parameters in the hydrogen production and storage processes according to different environments and operating conditions, continuously updates the accessed algorithms by optimizing these parameters, evaluates the optimized hydrogen energy conversion efficiency, and conducts comparative experiments by analyzing the effects of different models;

[0118] S4. The efficiency optimization system stores the historical data generated during the hydrogen energy conversion process, analyzes the performance of hydrogen energy conversion equipment through historical data, evaluates the energy efficiency performance under different operating conditions, obtains the data of equipment from different manufacturers and sensors with different standards, adopts a unified communication protocol to promote the standardization of data in the hydrogen energy field, obtains the specific data of hydrogen energy conversion equipment as time goes by and the surrounding environmental conditions change through sensing and acquisition devices, conducts remote and on-site early warning processing for abnormal data in environmental data monitoring, manually sets early warning thresholds and indicators, and conducts real-time imaging of the environmental data monitoring situation and comprehensive comparison in tabular form to complete a hydrogen energy conversion efficiency optimization process.

[0119] Specifically: In practical applications, there are multiple hydrogen energy data acquisition and processing modules, which are respectively used in cooperation with the hardware architecture management module, the hydrogen energy conversion efficiency optimization module, and the historical data control module. The multiple hydrogen energy data acquisition and processing modules are located in different geographical locations. By setting up the hydrogen energy data acquisition and processing module, the hardware architecture management module, the hydrogen energy conversion efficiency optimization module, and the historical data control module, a complete efficiency optimization system is constructed. During actual use, the hydrogen energy data acquisition and processing module collects historical data related to hydrogen energy conversion, cleans and standardizes the historical data, and at the same time locates the collected historical data sources. The hardware architecture management module constructs a hardware management center and a software management center, and continuously updates the hardware and software information inside the management center, provides the user with the right to edit independently, and customizes a personalized user operation interface. The hydrogen energy conversion efficiency optimization module constructs an efficiency optimization model, uses historical data for model training, and evaluates the accuracy and generalization ability of the model. At the same time, algorithms related to hydrogen energy conversion efficiency optimization are accessed, and the accessed algorithms are continuously updated. The historical data control module stores the historical data generated during the hydrogen energy conversion process, analyzes the performance of the hydrogen energy conversion equipment through the historical data, evaluates the energy efficiency performance under different operating conditions, obtains the data of equipment from different manufacturers and sensors with different standards, and adopts a unified communication protocol to promote the standardization of data in the hydrogen energy field. The environmental data supervision module is used to obtain the specific data of the hydrogen energy conversion equipment as the usage time progresses and the surrounding environmental conditions change through sensing and acquisition devices, and conducts remote and on-site early warning processing for abnormal data in environmental data monitoring, and real-time imaging of the environmental data monitoring situation. It can cooperate with intelligent data analysis and various algorithms to access and optimize various parameters in the hydrogen energy conversion process in real time, significantly improve the energy conversion efficiency, reduce energy consumption, avoid the equipment from operating under inappropriate working conditions through historical data analysis and optimization, thereby reducing the equipment failure rate, reducing the maintenance cost, and extending the service life of the equipment. Managing, visualizing, and storing the hydrogen energy conversion efficiency optimization data and the corresponding analysis results helps to achieve the optimization management of hydrogen energy conversion efficiency through Internet of Things cloud control and improve the intelligent level of hydrogen energy conversion efficiency optimization management.

[0120] Those of ordinary skill in the art can realize that the modules and method steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraint conditions of the technical solution. Professional technicians can use different methods for each specific application to implement the described functions, but this implementation should not be considered to exceed the scope of the present invention.

[0121] The modules for hydrogen energy data acquisition and processing, hardware architecture management, hydrogen energy conversion efficiency optimization, and historical data management and control may or may not be physically separate, and the components displayed as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of this embodiment.

[0122] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0123] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program instructions, such as a USB flash drive, a mobile hard disk, a read-only storage server, a random access storage server, a magnetic disk, or an optical disk.

[0124] In addition, it should be noted that the combination of the various technical features in this case is not limited to the combination described in the claims of this case or the combination described in the specific embodiments. All technical features recorded in this case can be freely combined or combined in any way unless there is a contradiction between them.

[0125] It should be noted that the above examples are merely specific embodiments of the present invention. Obviously, the present invention is not limited to the above examples, and many similar variations are possible. All variations directly derived from or associating with the present invention by those skilled in the art are intended to fall within the scope of protection of the present invention.

[0126] The above are only preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A hydrogen energy conversion efficiency optimization system based on historical data, characterized in that, The efficiency optimization system includes a hydrogen energy data acquisition and processing module, a hardware architecture management module, a hydrogen energy conversion efficiency optimization module, and a historical data control module. The hardware architecture management module maintains data interconnection and sharing with the hydrogen energy data acquisition and processing module, the hydrogen energy conversion efficiency optimization module, and the historical data control module respectively through the Internet of Things. Staff can access the hydrogen energy conversion efficiency optimization module to view the real-time operation data of the hydrogen energy data acquisition and processing module, the hardware architecture management module, and the historical data control module one by one inside the efficiency optimization system.

2. The hydrogen energy conversion efficiency optimization system based on historical data according to claim 1, characterized in that: The output end of the hydrogen energy data acquisition and processing module is communicatively connected to the input end of the hydrogen energy conversion efficiency optimization module. The output end of the historical data control module is communicatively connected to the input end of the hydrogen energy conversion efficiency optimization module. The hardware architecture management module is in bidirectional communication connection with the hydrogen energy conversion efficiency optimization module. The efficiency optimization system further includes an environmental data supervision module, and the output end of the environmental data supervision module is communicatively connected to the input end of the hydrogen energy conversion efficiency optimization module.

3. The hydrogen energy conversion efficiency optimization system based on historical data according to claim 2, wherein: The hydrogen energy data acquisition and processing module is used to collect historical data related to hydrogen energy conversion, clean and standardize the historical data, and locate the collected historical data sources at the same time; The hardware architecture management module is used to construct a hardware management center and a software management center, continuously update the hardware and software information inside the management center, provide the permission for users to edit independently, and customize a personalized user operation interface; The hydrogen energy conversion efficiency optimization module is used to construct an efficiency optimization model, use historical data for model training, evaluate the accuracy and generalization ability of the model, and at the same time access algorithms related to hydrogen energy conversion efficiency optimization and continuously update the accessed algorithms; The historical data control module is used to store the historical data generated during the hydrogen energy conversion process, analyze the performance of hydrogen energy conversion equipment through historical data, evaluate the energy efficiency performance under different operating conditions, obtain the data of equipment from different manufacturers and sensors with different standards, and adopt a unified communication protocol to promote the standardization of data in the hydrogen energy field; The environmental data supervision module is used to obtain the specific data of hydrogen energy conversion equipment as the usage time goes by and the surrounding environmental conditions change through sensing and acquisition equipment, give remote and on-site early warning for abnormal data in environmental data monitoring, and image the environmental data monitoring situation in real time.

4. The hydrogen energy conversion efficiency optimization system based on historical data according to claim 3, wherein: The hydrogen energy data acquisition and processing module includes a hydrogen energy data acquisition unit, a hydrogen energy data preprocessing unit, a synchronous monitoring unit, and a hydrogen energy data source location unit. The output end of the hydrogen energy data acquisition unit is communicatively connected to the input end of the hydrogen energy data preprocessing unit. The hydrogen energy data source location unit is integrated inside the hydrogen energy data acquisition unit. The hydrogen energy data preprocessing unit and the synchronous monitoring unit are in bidirectional communication connection; The hydrogen energy data acquisition unit is used to collect historical data related to hydrogen energy conversion; The hydrogen energy data preprocessing unit is used to clean and standardize historical data; The synchronous monitoring unit is used to perform real-time monitoring and processing on the data of each module and unit during the operation of the efficiency optimization system, and preset data such as sensitive words and risk factors; The hydrogen energy data source positioning unit is used to locate the collected historical data sources.

5. The hydrogen energy conversion efficiency optimization system based on historical data according to claim 1, characterized in that: The hardware architecture management module includes a hardware architecture construction unit, a hardware architecture management unit, a hardware architecture software access unit, and a user interface interaction unit. The output end of the hardware architecture construction unit is communicatively connected to the input end of the hardware architecture management unit, and the hardware architecture management unit and the hardware architecture software access unit are communicatively connected bidirectionally; The hardware architecture construction unit is used to construct a hardware management center; The hardware architecture management unit is used to record the information of hardware devices in different locations and keep subsequent data updated; The hardware architecture software access unit is used to construct a software management center; The user interface interaction unit is used to provide the user with the right to edit independently and customize a personalized user operation interface.

6. The hydrogen energy conversion efficiency optimization system based on historical data according to claim 5, characterized in that: The hydrogen energy conversion efficiency optimization module includes a hydrogen energy conversion efficiency optimization unit, an algorithm access database, an algorithm optimization unit, and an evaluation and feedback unit. The algorithm optimization unit is integrated inside the algorithm access database. The output end of the algorithm access database is communicatively connected to the input end of the hydrogen energy conversion efficiency optimization unit, and the output end of the hydrogen energy conversion efficiency optimization unit is communicatively connected to the input end of the evaluation and feedback unit; The hydrogen energy conversion efficiency optimization unit is used to construct an efficiency optimization model and use historical data for model training; The algorithm access database is used to access algorithms related to hydrogen energy conversion efficiency optimization; The algorithm optimization unit is used to optimize various key parameters in the hydrogen production and storage processes according to different environments and operating conditions; The evaluation and feedback unit is used to evaluate the optimized hydrogen energy conversion efficiency and conduct comparative experiments by analyzing the effects of different models.

7. The hydrogen energy conversion efficiency optimization system based on historical data according to claim 1, characterized in that: The historical data management and control module includes a historical data storage center, a data security and backup unit, and a historical data integration unit. The data security and backup unit is integrated inside the historical data storage center. The output end of the historical data integration unit is communicatively connected to the input end of the historical data storage center; The historical data storage center is used to store the historical data generated during the hydrogen energy conversion process; The data security and backup unit is used to protect the important data in the efficiency optimization system; The historical data integration unit is used to obtain the data of devices from different manufacturers and sensors with different standards, and adopt a unified communication protocol.

8. The hydrogen energy conversion efficiency optimization system based on historical data according to claim 2, characterized in that: The environmental data supervision module includes an environmental data supervision unit, a field data warning unit, and a visualization imaging unit. The output ends of the environmental data supervision unit and the field data warning unit are both communicatively connected to the input end of the visualization imaging unit; The environmental data supervision unit is used to obtain the specific data of the hydrogen energy conversion device as the usage time progresses and the surrounding environmental conditions change through sensing and acquisition devices; The on-site data warning unit is used to remotely and on-site warn and process abnormal data in environmental data monitoring; The visualization imaging unit is used to manually set warning thresholds and indicators for real-time imaging of environmental data monitoring.

9. A method for optimizing the hydrogen energy conversion efficiency based on historical data, which is used to implement a system for optimizing the hydrogen energy conversion efficiency based on historical data according to any one of claims 1-8, characterized in that: It includes the following specific steps: S1. The efficiency optimization system collects historical data related to hydrogen energy conversion, cleans and standardizes the historical data, and performs real-time monitoring on the data of each module and unit during operation. By constructing a hardware and software management center, the hardware and software information inside the management center is continuously updated, and at the same time, the permission for users to edit independently is provided; S2. The efficiency optimization system constructs an efficiency optimization model, uses historical data for model training, evaluates the accuracy and generalization ability of the model, accesses algorithms related to hydrogen energy conversion efficiency optimization, and optimizes various key parameters in the hydrogen production and storage processes according to different environmental and operating conditions. By optimizing these parameters, the accessed algorithms are continuously updated, the optimized hydrogen energy conversion efficiency is evaluated, and comparative experiments are carried out by analyzing the effects of different models; S3. The efficiency optimization system stores the historical data generated during the hydrogen energy conversion process, analyzes the performance of the hydrogen energy conversion equipment through historical data, evaluates the energy efficiency performance under different operating conditions, obtains the data of equipment from different manufacturers and sensors with different standards, and obtains the specific data of the hydrogen energy conversion equipment as time goes by and the surrounding environmental conditions change through the sensing and acquisition equipment. For abnormal data in environmental data monitoring, remote and on-site warning and processing are carried out, warning thresholds and indicators are manually set, and the environmental data monitoring situation is imaged in real time. Comprehensive comparison is carried out in tabular form to complete a hydrogen energy conversion efficiency optimization process.

10. The method for optimizing the hydrogen energy conversion efficiency based on historical data according to claim 9, wherein: The thresholds in step S3 include the following levels: Primary warning: It can be processed by the efficiency optimization system itself; Intermediate warning: Dual on-site and remote warnings are carried out through warning devices; Ultimate warning: Back up the data running in real time by the efficiency optimization system, and interrupt the operation status of the efficiency optimization system after the backup is completed.

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