Green hydrogen production intelligent control system based on multi-source signal fusion

Abstract

The invention belongs to the field of multi-source signal fusion and green hydrogen production, and particularly discloses a green hydrogen production intelligent control system based on multi-source signal fusion, which comprises a multi-source signal acquisition platform, a data fusion platform and an intelligent control platform, the multi-source signal acquisition platform is used for acquiring multi-source signals of the signal acquisition devices in the target area; the data fusion platform is used for fusing the multi-source signals to obtain fusion signals, intelligently analyzing the fusion signals, taking green hydrogen production economic maximization as an analysis target and intelligently controlling the multi-source signal acquisition equipment based on the analysis target; and the intelligent control platform is used for receiving the fusion signal and the control instruction of the data fusion platform, and performing intelligent control on the power generation side, the energy storage side and the power utilization side based on the fusion signal and the control instruction. According to the invention, the stability and efficiency of intelligent control of the hydrogen production system can be improved.

Description

Technical Field

[0001] The present application belongs to the field of multi-source signal fusion and green hydrogen production, and more specifically, to a green hydrogen production intelligent control system based on multi-source signal fusion. Background Art

[0002] Hydrogen energy and its downstream comprehensive utilization (such as ammonia production) have gradually attracted the attention of the industry in recent years. Based on the description of relevant foreign institutions, this field is usually abbreviated as PHX (Power + Hydrogen to X). As we all know, if you want to have green and low-carbon attributes, you must use renewable energy electricity. In order to make full use of abundant renewable energy and achieve zero carbon emissions in the PHX field, the corresponding energy storage is allocated according to the on-site demand. 80% of the power generated by wind power is consumed by hydrogen electrolysis.

[0003] The hydrogen production system accounts for more than 90% of energy consumption and is the main energy consumer. Green hydrogen production cannot rely solely on stable grid electricity like traditional chemical industry. It must adopt renewable energy coupling power supply, which requires the hardware technology level of the equipment and the energy management platform to have the ability to follow the source. However, the power output of wind power generation is unstable, which leads to the overall efficiency of the hydrogen production system being insufficient.

[0004] Therefore, how to improve the stability and efficiency of intelligent control of hydrogen production systems is a technical problem that needs to be solved urgently. Summary of the invention

[0005] In view of the defects of the prior art, the purpose of this application is to provide a green hydrogen production intelligent control system based on multi-source signal fusion, aiming to solve the problems of insufficient stability and efficiency of the current hydrogen production system.

[0006] The present application provides a green hydrogen production intelligent control system based on multi-source signal fusion, including: a multi-source signal acquisition platform, a data fusion platform and an intelligent control platform;

[0007] The multi-source signal acquisition platform is used to collect multi-source signals from various signal acquisition devices in the target area, wherein the multi-source signals include wind energy data signals, illuminance data signals, wind power data signals, photovoltaic data signals, energy storage data signals, hydrogen production data signals, and hydrogen storage data signals;

[0008] The data fusion platform is used to fuse multi-source signals to obtain fused signals, perform intelligent analysis on the fused signals, take maximizing the green hydrogen production economy as the analysis target, and perform intelligent control on the multi-source signal acquisition equipment based on the analysis target;

[0009] The intelligent control platform is used to receive the fusion signal and control instructions of the data fusion platform, and perform intelligent control on the power generation side, energy storage side and power consumption side based on the fusion signal and control instructions.

[0010] Optionally, the multi-source signal acquisition platform includes a wind power prediction subsystem, a light intensity prediction subsystem, a wind turbine subsystem, a photovoltaic collection subsystem, an energy storage subsystem, a hydrogen production subsystem, and a hydrogen storage subsystem;

[0011] The wind power prediction subsystem is used to predict the wind speed in the target area and collect wind energy data signals. The wind power prediction subsystem update time is within a preset time;

[0012] The illumination prediction subsystem is used to predict the illumination in the target area and collect illumination data signals. The illumination prediction subsystem is updated within a preset time.

[0013] The wind turbine subsystem is used to collect the working status, wind speed, active power, reactive power and power generation of the wind turbine, and obtain the wind power data signal based on the various signals collected;

[0014] The photovoltaic data collection subsystem is used to collect the working status, illuminance, active power, reactive power and power generation of the photovoltaic data collection subsystem, and obtain the photovoltaic data signal based on the various signals collected;

[0015] The energy storage subsystem is used to collect the working status of the energy storage subsystem, the available power of the battery and the health status of the battery, and obtain the energy storage data signal based on the various signals collected;

[0016] The hydrogen production subsystem is used to collect the working status, hydrogen production, active power, reactive power and power consumption of the energy storage subsystem, and obtain a hydrogen production data signal based on the various signals collected;

[0017] The hydrogen storage subsystem is used to collect the working status and available hydrogen storage capacity of the hydrogen storage subsystem, and obtain a hydrogen storage data signal based on the working status and available hydrogen storage capacity.

[0018] Optionally, the data fusion platform is specifically used for:

[0019] The multi-source signals are subjected to data preprocessing, data storage, data fusion, data calculation and data output to obtain the fused signal.

[0020] Optionally, the data fusion platform is further used for:

[0021] The data of the multi-source signal that does not use the data source is cleaned and converted according to the data fusion standard to obtain a preprocessed signal;

[0022] Storing valid data in the preprocessed signal in a database;

[0023] The preprocessed signals from different data sources are input into the mathematical model, and the neural network algorithm is used to perform data operations to obtain the operation results, which are then output to the corresponding equipment as fusion signals.

[0024] Optionally, the intelligent control platform is further used for:

[0025] receiving a first input from a user, and selecting a mode in response to the first input;

[0026] receiving a second input from a user, and selecting an operation scenario in response to the second input;

[0027] A third input from the user is received, and a human-machine interface selection is performed in response to the third input.

[0028] The modes include a novice mode and a professional mode, the operating scenarios include sea, desert, Gobi and hills, and the human-computer interface includes voice recognition, keyboard input and touch screen handwriting.

[0029] Optionally, the multi-source signal acquisition platform communicates with each subsystem via a smart Ethernet switch using the ModbusTCP protocol;

[0030] The data fusion platform communicates with the multi-source signal acquisition platform via the core switch using the Modbus TCP protocol;

[0031] The intelligent control platform includes a host computer, which communicates with the data fusion platform via a core switch using the ModbusTCP protocol.

[0032] Optionally, the operation modes of the system include a normal operation mode, a manual operation mode, a fault operation mode, a maintenance operation mode and a fault operation mode, and the switching of the operation modes of the system is achieved through mode switching.

[0033] Optionally, the operation scenarios of the manual operation mode include: system failure and shutdown of the wind farm, failure of the hydrogen production automatic system, and triggering of the safety circuit;

[0034] The intelligent control platform is also used for:

[0035] When a systemic fault occurs and the system shuts down, the hydrogen production automatic system fails, or the safety loop is triggered, the fault and scheduling-related data will be fed back to the upper-level dispatcher based on the internal fault situation. The related data include safety lockout information, fault content, shutdown decision, dispatchable gas volume, and operation and maintenance decision.

[0036] Optionally, the hydrogen production subsystem is further used for:

[0037] In the event of a network outage, the system enters an isolated grid mode and determines a safety control strategy based on internal status, load conditions, hydrogen storage conditions, and a locking signal to maintain system safety based on the safety control strategy.

[0038] Optionally, the working process of the hydrogen production subsystem includes:

[0039] Receive wind power prediction data, optical power prediction data and laser wind measurement data through feedforward control to achieve power prediction;

[0040] The amount of hydrogen is controlled by double-loop PI closed-loop regulation to achieve safe and stable operation of the hydrogen production subsystem;

[0041] The disturbances of photovoltaic power generation, wind speed and power grid are adjusted through disturbance regulation to maintain the stable operation of the hydrogen production subsystem.

[0042] In general, the above technical solutions conceived by this application have the following beneficial effects compared with the prior art:

[0043] (1) This application collects multi-dimensional signals such as wind energy, light intensity, wind power, photovoltaics, energy storage, hydrogen production and storage through the platform. By integrating signals of renewable energy such as wind power and photovoltaics, the system can better cope with the instability of wind and photovoltaic power generation, thereby ensuring the stable operation of the hydrogen production process. The intelligent control platform can respond to changes in multi-source signals in real time, ensure the balance between the power generation side, energy storage side and power consumption side, ensure the stability of the system under different operating conditions, and thus improve the efficiency of hydrogen production in the system.

[0044] (2) Through real-time acquisition and analysis of multi-source signals, the system can flexibly adjust energy production and consumption to maximize energy efficiency in the green hydrogen production process. Fusion of signals from different sources can select the best energy utilization plan based on real-time data, thereby reducing resource waste.

[0045] (3) The intelligent analysis of this application, which aims to maximize the economic benefits of green hydrogen production, can help identify the most cost-effective operating strategy, thereby reducing operating and maintenance costs. Through intelligent control and real-time optimization, the system can improve the efficiency of hydrogen production.

[0046] (4) The system of the present application can monitor the operating status of each signal source in real time, provide timely feedback and adjust the control strategy, and improve response speed and management efficiency. Intelligent analysis based on fusion signals can provide data support for decision-making and ensure the scientificity and effectiveness of all control instructions. Through mode selection, operation scenarios and human-machine interface, it can not only facilitate the operation of on-duty personnel, but also improve the efficiency of green hydrogen production. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a system structure diagram of a green hydrogen production intelligent control system based on multi-source signal fusion proposed in an embodiment of the present application;

[0048] Figure 2 A network topology diagram for multi-source signal fusion proposed in an embodiment of the present application;

[0049] Figure 3 A schematic diagram of the intelligent control process of green hydrogen production based on multi-source signal fusion proposed in an embodiment of the present application;

[0050] Figure 4 A schematic diagram of hierarchical scheduling of green hydrogen production based on multi-source signal fusion proposed in an embodiment of the present application;

[0051] Figure 5 A schematic diagram of intelligent control of green hydrogen production based on multi-source signal fusion proposed in an embodiment of the present application;

[0052] Figure 6 This is a schematic diagram of the green hydrogen production intelligent control software interface proposed in the embodiment of the present application. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0054] The term "and / or" in this article is a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The symbol " / " in this article indicates that the associated objects are in an or relationship, for example, A / B means A or B.

[0055] The terms "first" and "second" in the specification and claims herein are used to distinguish different objects rather than to describe a specific order of the objects. For example, a first response message and a second response message are used to distinguish different response messages rather than to describe a specific order of the response messages.

[0056] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0057] In the description of the embodiments of the present application, unless otherwise specified, "multiple" means two or more than two. For example, multiple processing units refer to two or more processing units, etc.; multiple elements refer to two or more elements, etc.

[0058] Next, the technical solutions provided in the embodiments of the present application are introduced.

[0059] Reference Figure 1 , the present application provides a green hydrogen production intelligent control system based on multi-source signal fusion, including: a multi-source signal acquisition platform, a data fusion platform and an intelligent control platform;

[0060] The multi-source signal acquisition platform is used to collect multi-source signals from various signal acquisition devices in the target area, wherein the multi-source signals include wind energy data signals, illuminance data signals, wind power data signals, photovoltaic data signals, energy storage data signals, hydrogen production data signals, and hydrogen storage data signals;

[0061] The data fusion platform is used to fuse multi-source signals to obtain fused signals, perform intelligent analysis on the fused signals, take maximizing the green hydrogen production economy as the analysis target, and perform intelligent control on the multi-source signal acquisition equipment based on the analysis target;

[0062] The intelligent control platform is used to receive the fusion signal and control instructions of the data fusion platform, and perform intelligent control on the power generation side, energy storage side and power consumption side based on the fusion signal and control instructions.

[0063] Furthermore, the multi-source signal acquisition platform includes a wind power prediction subsystem, a light intensity prediction subsystem, a wind turbine subsystem, a photovoltaic collection subsystem, an energy storage subsystem, a hydrogen production subsystem, and a hydrogen storage subsystem;

[0064] The wind power prediction subsystem is used to predict the wind speed in the target area and collect wind energy data signals. The wind power prediction subsystem update time is within a preset time;

[0065] The illumination prediction subsystem is used to predict the illumination in the target area and collect illumination data signals. The illumination prediction subsystem is updated within a preset time.

[0066] The wind turbine subsystem is used to collect the working status, wind speed, active power, reactive power and power generation of the wind turbine, and obtain the wind power data signal based on the various signals collected;

[0067] The photovoltaic data collection subsystem is used to collect the working status, illuminance, active power, reactive power and power generation of the photovoltaic data collection subsystem, and obtain the photovoltaic data signal based on the various signals collected;

[0068] The energy storage subsystem is used to collect the working status of the energy storage subsystem, the available power of the battery and the health status of the battery, and obtain the energy storage data signal based on the various signals collected;

[0069] The hydrogen production subsystem is used to collect the working status, hydrogen production, active power, reactive power and power consumption of the energy storage subsystem, and obtain a hydrogen production data signal based on the various signals collected;

[0070] The hydrogen storage subsystem is used to collect the working status and available hydrogen storage capacity of the hydrogen storage subsystem, and obtain a hydrogen storage data signal based on the working status and available hydrogen storage capacity.

[0071] It also includes an intelligent gateway subsystem, a data processing subsystem and a storage subsystem.

[0072] Specifically, the target area in this embodiment refers to the industrial park, that is, the site for green hydrogen production. The wind power prediction subsystem is used to collect wind speed and direction signals centered on the industrial park and extending outward 80 kilometers to 120 kilometers. The system update time is no more than five minutes;

[0073] The illumination prediction subsystem is used to collect the illumination at a distance of 6,000 to 8,000 meters vertically upward from the industrial park as the horizontal plane, and the system update time is no more than five minutes;

[0074] The wind turbine subsystem is used to collect wind speed, wind direction, active power, reactive power and maximum active power of the wind farm in the industrial park, and synthesize the above data to obtain wind power data signals;

[0075] The photovoltaic data collection subsystem is used to collect the illuminance, illumination angle, active power, reactive power and maximum active power of the photovoltaic station in the industrial park, and synthesize the above data to obtain a photovoltaic data signal;

[0076] The energy storage subsystem is used to collect the available power of the energy storage station in the industrial park;

[0077] The hydrogen production subsystem is used to collect the total active power and hydrogen production of the hydrogen production equipment in the industrial park;

[0078] The intelligent gateway subsystem is used to connect the wind power prediction subsystem, the optical power prediction subsystem, the wind turbine subsystem, the photovoltaic collection subsystem, the energy storage subsystem, the hydrogen production subsystem, the data processing subsystem and the storage subsystem; the data processing and storage subsystem is used to filter the different source signals of the wind power prediction subsystem, the photovoltaic collection subsystem, the energy storage subsystem and the hydrogen production subsystem collected by the intelligent gateway, output valid signals, and store the output valid signals.

[0079] The multi-source signal acquisition platform is connected to the data fusion platform. The data fusion platform analyzes the multi-source data and real-time operation data of the industrial park collected by the multi-source signal acquisition platform, and controls wind power, photovoltaics, energy storage and hydrogen production equipment based on hydrogen production and carbon emissions, while displaying alarms for abnormal units.

[0080] The data fusion platform fuses multiple data from multi-source signal acquisition platforms to form a comprehensive signal, helping to eliminate noise and redundant data and enhance signal reliability. Based on the operating data of the entire system, real-time analysis and prediction are carried out, focusing on but not limited to the following aspects:

[0081] Supply and demand matching: Analyze real-time wind, solar and hydrogen demand to ensure efficient use of renewable energy.

[0082] Economic maximization: By comprehensively considering factors such as production costs, energy conversion efficiency, and market prices, the green hydrogen production economy can be maximized.

[0083] Intelligent control command generation: Based on the analysis results of the fused signals, control commands are generated for the signal acquisition equipment to optimize the power generation, energy storage and hydrogen production processes.

[0084] The intelligent control platform receives fusion signals and control instructions from the data fusion platform, makes decisions and executes them, including the control of the power generation side, energy storage side and power consumption side. Specifically, it is manifested as:

[0085] Power generation side control: Intelligently adjust the output of wind power and photovoltaic power generation equipment, adjust the power generation strategy according to demand and supply conditions, and ensure maximum utilization of renewable energy.

[0086] Energy storage side control: Based on the fluctuations of grid load and renewable energy, the charging and discharging of the energy storage system is intelligently regulated to balance supply and demand.

[0087] Electricity consumption control: Optimize electricity consumption on the user side, combine real-time price information and demand data, conduct demand-side management, and improve overall economic benefits.

[0088] Specifically manifested as Figure 1Intelligent control of wind turbines, photovoltaic units, energy storage equipment, hydrogen production equipment and hydrogen storage equipment.

[0089] The overall workflow of the green hydrogen production intelligent control system of this application is as follows:

[0090] Data acquisition: Various signal acquisition devices collect relevant data such as wind energy, photovoltaics, energy storage and hydrogen production in real time, and transmit them to the multi-source signal acquisition platform.

[0091] Signal fusion: The multi-source signal acquisition platform transmits the data to the data fusion platform for processing and analysis to obtain a fused signal.

[0092] Intelligent analysis: The data fusion platform performs intelligent analysis on the fused signals and generates control instructions with the goal of maximizing the green hydrogen production economy.

[0093] Intelligent control: The intelligent control platform coordinates and controls power generation, energy storage and electricity consumption based on fusion signals and control instructions to ensure efficient operation of the system.

[0094] This application collects multi-dimensional signals such as wind energy, light intensity, wind power, photovoltaics, energy storage, hydrogen production and storage through the platform. By integrating renewable energy signals such as wind power and photovoltaics, the system can better cope with the instability of wind and photovoltaic power generation, thereby ensuring the stable operation of the hydrogen production process. The intelligent control platform can respond to changes in multi-source signals in real time, ensure the balance between the power generation side, energy storage side and power consumption side, ensure the stability of the system under different operating conditions, and thus improve the efficiency of the system's hydrogen production. .

[0095] Optionally, the data fusion platform is specifically used for:

[0096] The multi-source signals are subjected to data preprocessing, data storage, data fusion, data calculation and data output to obtain the fused signal.

[0097] Specifically, the steps of data fusion include:

[0098] The data of the multi-source signal that does not use the data source is cleaned and converted according to the data fusion standard to obtain a preprocessed signal;

[0099] Storing valid data in the preprocessed signal in a database;

[0100] The preprocessed signals from different data sources are input into the mathematical model, and the neural network algorithm is used to perform data operations to obtain the operation results, which are then output to the corresponding equipment as fusion signals.

[0101] Specifically, data cleaning in this embodiment refers to screening, correcting and supplementing data according to predetermined standards and rules to remove erroneous, incomplete or irrelevant data.

[0102] For example, common data cleaning processes include: missing value processing, which uses interpolation, mean filling or deletion to process missing data in preprocessed signals; outlier detection, which uses statistical methods (such as Z-score) or machine learning methods to detect and eliminate outliers to ensure data accuracy; data format normalization, which ensures that the formats of various signal data are consistent, such as unified timestamp format, data units, etc.

[0103] Secondly, data conversion is to transform the cleaned data to facilitate subsequent analysis and calculation. The process includes but is not limited to adjusting the data to the same scale through de-meaning and normalization to eliminate the impact of dimensional differences. Extract effective features from the preprocessed signal, which may include time series features, statistical features, etc., to provide support for subsequent analysis.

[0104] Furthermore, select a suitable database (such as a relational database or a NoSQL database) and design a database schema to store the cleaned and converted valid data. Store the cleaned and converted valid data in the database to ensure the integrity and traceability of the data. Establish a data management mechanism, regularly back up and maintain the database to ensure the security and availability of the data.

[0105] Extract the preprocessed signals (valid data stored in the database) from different sources and prepare them for input into the mathematical model. The mathematical module builds a neural network model, selects a suitable network structure (such as a fully connected network, a convolutional neural network, or a recursive neural network, etc.) and a loss function, and sets an optimization algorithm (such as Adam or SGD) for training. Based on historical data and target results (such as indicators of the green hydrogen economy), the neural network is trained and tuned to ensure that the model can effectively learn the relationship between data.

[0106] Finally, the input preprocessed signal is forward propagated through the trained neural network to calculate the operation result. The results obtained by the neural network operation are summarized to generate a fusion signal. The fusion signal is output to the corresponding device through the control system or communication interface to guide the execution of the corresponding control instructions. The actual effect of the output result is monitored, and the feedback information is input into the system again for continuous optimization and adjustment of the model.

[0107] Through the above steps, the embodiment of the present application can effectively process multi-source signals and provide strong support for the economic maximization of green hydrogen production. Data cleaning and conversion ensure the data quality of the input model, and the application of neural networks enables the system to intelligently process and predict various complex situations, thereby improving the efficiency and stability of the overall system.

[0108] Optionally, the intelligent control platform is further used for:

[0109] receiving a first input from a user, and selecting a mode in response to the first input;

[0110] receiving a second input from a user, and selecting an operation scenario in response to the second input;

[0111] A third input from the user is received, and a human-machine interface selection is performed in response to the third input.

[0112] The modes include a novice mode and a professional mode, the operating scenarios include sea, desert, Gobi and hills, and the human-computer interface includes voice recognition, keyboard input and touch screen handwriting.

[0113] Optionally, the multi-source signal acquisition platform communicates with each subsystem via a smart Ethernet switch using the ModbusTCP protocol;

[0114] The data fusion platform communicates with the multi-source signal acquisition platform via the core switch using the Modbus TCP protocol;

[0115] The intelligent control platform includes a host computer, which communicates with the data fusion platform via a core switch using the ModbusTCP protocol.

[0116] Specifically, in the embodiment of the present application, the network communication topology between the data fusion platform and the host computer, the wind power prediction system, the optical power prediction system, the wind farm, the photovoltaic farm, the energy storage farm and the hydrogen production farm is as follows: Figure 2 shown.

[0117] Furthermore, the network communication topology is composed of the data acquisition platform PLC as the central node, and the network can be divided into three layers. The first layer is the equipment layer. It includes 7 slave stations, including wind power prediction subsystem, optical power prediction subsystem, wind farm station energy management subsystem, photovoltaic station energy management subsystem, energy storage energy management subsystem, hydrogen production subsystem and hydrogen storage subsystem. The data acquisition platform PLC communicates with each slave station device through the intelligent Ethernet switch using the Modbus TCP protocol.

[0118] Furthermore, the second layer is the data fusion layer. This layer includes wind power prediction data and optical power prediction data, and communicates with the data acquisition layer through the core switch. The communication protocol is Modbus TCP.

[0119] Furthermore, the third layer is the intelligent control layer, which includes the host computer and communicates with the data fusion layer through the core switch, and the communication protocol is Modbus TCP.

[0120] Optionally, the operation modes of the system include a normal operation mode, a manual operation mode, a fault operation mode, a maintenance operation mode and a fault operation mode, and the switching of the operation modes of the system is achieved through mode switching.

[0121] Optionally, the operation scenarios of the manual operation mode include: system failure and shutdown of the wind farm, failure of the hydrogen production automatic system, and triggering of the safety circuit;

[0122] The intelligent control platform is also used for:

[0123] When a systemic fault occurs and the system shuts down, the hydrogen production automatic system fails, or the safety loop is triggered, the fault and scheduling-related data will be fed back to the upper-level dispatcher based on the internal fault situation. The related data include safety lockout information, fault content, shutdown decision, dispatchable gas volume, and operation and maintenance decision.

[0124] Optionally, the hydrogen production subsystem is further used for:

[0125] In the event of a network outage, the system enters an isolated grid mode and determines a safety control strategy based on internal status, load conditions, hydrogen storage conditions, and a locking signal to maintain system safety based on the safety control strategy.

[0126] Reference Figure 3 In the embodiment of the present application, the green hydrogen production intelligent control system realizes the switching of normal operation mode, manual operation mode, fault operation mode, maintenance operation mode and fault operation mode through operation mode switching.

[0127] Specifically, the normal operation mode and the manual operation mode are switched by a button on the control console or a button on the local control cabinet panel.

[0128] Furthermore, under normal working mode, the system network is normal, and the wind farm, photovoltaic, energy storage, hydrogen production, hydrogen storage and other subsystems are normal. The hydrogen production centralized control will complete the system monitoring and scheduling work according to the upper-level scheduling and lower-level status.

[0129] Furthermore, the manual mode is divided into centralized manual mode and local manual mode. When the automatic mode fails or human intervention is required, the system enters the manual mode. This is generally to meet the overall special control needs of the system, such as systemic failure and shutdown of the wind farm, failure of the hydrogen production automatic system, triggering of the safety loop, etc. In order to meet the hydrogen production needs, the system needs to enter a short state of human intervention, and the manual mode can be used.

[0130] Furthermore, when a fault occurs inside the hydrogen production system, the intelligent control system of the hydrogen production equipment of the intelligent control platform will feedback the fault and scheduling related data to the upper-level dispatcher based on the internal fault situation, mainly including safety lockout information, fault content, shutdown decision, dispatchable gas volume, operation and maintenance decision and other information.

[0131] Furthermore, faults are handled in a hierarchical manner, including warnings (continuous operation, planned maintenance), general faults (normal shutdown process of some equipment or the whole), rapid shutdown faults (rapid shutdown under system safety), and emergency shutdown faults (faults that trigger lockout or may cause equipment damage). If a general equipment fault occurs in the global system (such as a fan or electrolysis power supply failure), scheduling or switching can be completed dynamically according to the equipment status.

[0132] Furthermore, the maintenance mode is mainly used for system inspection, maintenance, and upkeep. In the maintenance mode, necessary locking conditions are set so that when the equipment is in operation, the operator, system, and equipment remain in a safe state.

[0133] Furthermore, when a network interruption occurs between the hydrogen production system and the intelligent control platform, the hydrogen production system enters an isolated network mode. At this time, the hydrogen production system may be in various possible states, such as operation, standby, cold, etc. The hydrogen production system should adopt the most favorable safety control strategy for the system according to the internal state, load conditions, hydrogen storage conditions, locking signals, etc.

[0134] In the embodiments of the present application, Figure 4 As shown, a hierarchical energy management scheduling scheme is adopted, which is divided into two levels of scheduling + one level of execution.

[0135] Furthermore, the global energy management system dispatches the hydrogen production system, communicates with the hydrogen production centralized control system through the network, and only makes requirements on the hydrogen production volume and export pressure. The power dispatch of each hydrogen production equipment is completed by the hydrogen production energy management system.

[0136] Furthermore, the hydrogen production energy management system feeds back hydrogen production constraints to the global EMS system based on the status of each device, and executes power control of hydrogen production equipment in the industrial park.

[0137] Specifically, Figure 4 The dispatch architecture of an energy management system (EMS) and supervisory control and data acquisition system (SCADA) is demonstrated, involving four different system levels: hydrogen production, hydrogen storage, wind power, and energy storage.

[0138] Hydrogen production EMS system (hydrogen production centralized control layer):

[0139] Responsible for the scheduling of hydrogen volume, the scheduling of outlet pressure, and the control of the start and stop of hydrogen production equipment at the workshop level, as well as power control.

[0140] Hydrogen storage EMS system (hydrogen storage centralized control layer):

[0141] Responsible for scheduling hydrogen storage, controlling the start and stop of hydrogen storage equipment at the workshop level, and power control.

[0142] Wind power SCADA (wind farm centralized control layer):

[0143] Responsible for monitoring and controlling the power of each wind turbine and controlling the start and stop of each wind turbine.

[0144] Energy storage EMS system (energy storage EMS layer):

[0145] Responsible for the scheduling of charging and discharging power.

[0146] Controls the start and stop of the PCS (Power Conversion System) and BMS (Battery Management System), as well as power control.

[0147] The architecture in this embodiment shows the division of responsibilities between different system levels, each of which is responsible for specific scheduling parameters and equipment control. Through this hierarchical management, efficient and stable operation of the entire energy system can be achieved, which helps to ensure the balance of energy supply and demand, optimize energy utilization efficiency, and improve system reliability and flexibility.

[0148] Optionally, the working process of the hydrogen production subsystem includes:

[0149] Receive wind power prediction data, optical power prediction data and laser wind measurement data through feedforward control to achieve power prediction;

[0150] The amount of hydrogen is controlled by double-loop PI closed-loop regulation to achieve safe and stable operation of the hydrogen production subsystem;

[0151] The disturbances of photovoltaic power generation, wind speed and power grid are adjusted through disturbance regulation to maintain the stable operation of the hydrogen production subsystem.

[0152] Specifically, refer to Figure 5 , Figure 5 This is a real-time intelligent control block diagram that works continuously under normal working conditions. The intelligent control core adopts feedforward control + dual-loop PI regulation + disturbance regulation.

[0153] In the figure, the weather forecast (W w2 ) represents data from weather forecasts. Laser wind measurement (W wT ) represents the wind speed data obtained by the laser wind measuring instrument. VW2 (s) and G WT (s) represent the transfer functions of meteorological forecast and laser wind measurement data, respectively, and are used to describe the dynamic characteristics of the system. HP (s) and G HF(s) represent the power control transfer function and the flow transfer function respectively. G1(s), G2(s) and G2(s) represent the separation, electrolysis and purification transfer functions in the system respectively, which are used to describe the dynamic characteristics of the hydrogen production process. G4(s) represents the buffer tank transfer function in the hydrogen production process. WT1 : Represents the power output of the wind turbine. Ew24: Represents the predicted power output of the wind turbine. The global hydrogen power PI controller is used to adjust the proportional-integral controller of the hydrogen power, and the input is QH / PH. PH represents the feedback power of the system, and QH represents the feedback hydrogen production of the system. The global hydrogen production PI controller is used to adjust the proportional-integral controller of the hydrogen production, and the input is PH. PH represents the feedback power of the system. Electrolysis, separation, purification, and buffer tanks represent different control strategies and processing processes in the system respectively. Energy storage and power grid represent the energy exchange between the hydrogen production system and the energy storage and power grid.

[0154] Furthermore, the decoupling of source, grid, load and storage adopts feedforward control, and the feedforward signal comes from wind power prediction data, optical power prediction data and laser wind measurement data to realize power prediction.

[0155] Furthermore, the dual loop adopts an outer loop of hydrogen volume and an inner loop of power, and realizes safe and stable operation of hydrogen production equipment through closed-loop control of hydrogen volume. In the intelligent control block diagram, the amount of hydrogen produced by electrolysis is determined by the current, and the current regulation is achieved through voltage regulation. Therefore, the power supply control adopts closed-loop control of current feedback, and the response time can reach ms level. In addition, since all pipelines of a single hydrogen production line are interconnected during operation, there are slight pressure and temperature differences between the equipment before connection. A small amount of hydrogen reflux may occur at the moment of connection. The system will control the pressure difference range from the control process, thereby controlling the amount of hydrogen reflux. After connection, the pressure and temperature will be in a self-balanced flow state, and after the system time constant, it will enter a new pressure and temperature balance.

[0156] Furthermore, it involves disturbance issues related to photovoltaics, wind speed and power grid, and the safe and stable operation of hydrogen production equipment can be achieved through the regulation of energy storage.

[0157] Reference Figure 6 The green hydrogen production intelligent control system in the embodiment of the present application can interact with the intelligent monitoring software, wherein the intelligent monitoring software is designed in three layers, the first layer is the main interface, the second layer is the subsystem layer, and the third layer is the secondary interface of the subsystem.

[0158] It should be noted that the intelligent monitoring software adopts B / S architecture. Enter the IP address in the browser, jump out of the login interface, select the role in the login interface, the roles mainly include administrator, operator and duty officer. Then enter the main interface.

[0159] Furthermore, the subsystem interface includes a wind power prediction system, a light power prediction system, a wind farm system, a photovoltaic field system, an energy storage system, a hydrogen production system, a hydrogen storage system, an intelligent control system, an intelligent interactive system and a reporting system.

[0160] Furthermore, the wind power prediction system displays the average wind speed and direction for the next 1 hour, 30 minutes, 10 minutes, and 5 minutes.

[0161] Furthermore, the light power prediction system displays the average illuminance in the next 1 hour, 30 minutes, 10 minutes, and 5 minutes.

[0162] Furthermore, the wind farm system displays wind turbine status (generator, converter, pitch system and yaw system, etc.), wind turbine monitoring (generator, converter, pitch system and yaw system, etc.), wind turbine control (start, reset and stop, etc.) and wind turbine management (user, fault, alarm and report management, etc.).

[0163] Furthermore, the PV field system displays PV status (PV panels, inverters, solar tracking systems, etc.), PV monitoring (PV panels, inverters, solar tracking systems, etc.), PV control (start, reset and stop, etc.) and PV management (user, fault, alarm and report management, etc.).

[0164] Furthermore, the energy storage system displays energy storage status (battery system, inverter, air conditioning and EMS system, etc.), energy storage monitoring (battery system, inverter, air conditioning and EMS system, etc.), energy storage control (start, reset and stop, etc.) and energy storage management (user, fault, alarm and report management, etc.).

[0165] Furthermore, the hydrogen production system displays hydrogen production status (inverter, electrolyzer, separation system, purification system and EMS system, etc.), hydrogen production monitoring (inverter, electrolyzer, separation system, purification system and EMS system, etc.), hydrogen production control (start, reset and stop, etc.) and hydrogen production management (user, fault, alarm and report management, etc.).

[0166] Furthermore, the hydrogen storage system displays hydrogen storage status (hydrogen storage tank and meter, etc.), hydrogen storage monitoring (hydrogen storage tank and meter, etc.), hydrogen storage control (start, reset and stop, etc.) and hydrogen storage management (user, fault, alarm and report management, etc.).

[0167] Furthermore, the intelligent control system displays voice interaction status, voice interaction management, voice interaction monitoring and voice interaction control; stylus status, stylus management, stylus monitoring and stylus control.

[0168] Furthermore, the reporting system mainly provides daily reports (availability, hydrogen production, carbon emissions, power consumption, water consumption, etc.), monthly reports (availability, hydrogen production, carbon emissions, power consumption, water consumption, etc.), and annual reports (availability, hydrogen production, carbon emissions, power consumption, water consumption, etc.).

[0169] Furthermore, the green hydrogen production intelligent control system based on multi-source signal fusion proposed in the embodiment of the present application not only realizes the safe and stable operation of the hydrogen production equipment, but also realizes the economical and efficient operation of the hydrogen production by adopting the above method steps.

[0170] It should be understood that the various numerical numbers involved in the embodiments of the present application are only used for the convenience of description and are not used to limit the scope of the embodiments of the present application.

[0171] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A green hydrogen production intelligent control system based on multi-source signal fusion, characterized in that: include: Multi-source signal acquisition platform, data fusion platform and intelligent control platform; The multi-source signal acquisition platform is used to collect multi-source signals from various signal acquisition devices in the target area, wherein the multi-source signals include wind energy data signals, illuminance data signals, wind power data signals, photovoltaic data signals, energy storage data signals, hydrogen production data signals, and hydrogen storage data signals; The data fusion platform is used to fuse multi-source signals to obtain fused signals, perform intelligent analysis on the fused signals, take maximizing the green hydrogen production economy as the analysis target, and perform intelligent control on the multi-source signal acquisition equipment based on the analysis target; The intelligent control platform is used to receive the fusion signal and control instructions of the data fusion platform, and perform intelligent control on the power generation side, energy storage side and power consumption side based on the fusion signal and control instructions.

2. The green hydrogen production intelligent control system based on multi-source signal fusion according to claim 1 is characterized in that: The multi-source signal acquisition platform includes a wind power prediction subsystem, a light intensity prediction subsystem, a wind turbine subsystem, a photovoltaic collection subsystem, an energy storage subsystem, a hydrogen production subsystem and a hydrogen storage subsystem; The wind power prediction subsystem is used to predict the wind speed in the target area and collect wind energy data signals. The wind power prediction subsystem update time is within a preset time; The illumination prediction subsystem is used to predict the illumination in the target area and collect illumination data signals. The illumination prediction subsystem is updated within a preset time. The wind turbine subsystem is used to collect the working status, wind speed, active power, reactive power and power generation of the wind turbine, and obtain the wind power data signal based on the various signals collected; The photovoltaic data collection subsystem is used to collect the working status, illuminance, active power, reactive power and power generation of the photovoltaic data collection subsystem, and obtain the photovoltaic data signal based on the various signals collected; The energy storage subsystem is used to collect the working status of the energy storage subsystem, the available power of the battery and the health status of the battery, and obtain the energy storage data signal based on the various signals collected; The hydrogen production subsystem is used to collect the working status, hydrogen production, active power, reactive power and power consumption of the energy storage subsystem, and obtain a hydrogen production data signal based on the various signals collected; The hydrogen storage subsystem is used to collect the working status and available hydrogen storage capacity of the hydrogen storage subsystem, and obtain a hydrogen storage data signal based on the working status and available hydrogen storage capacity.

3. The green hydrogen production intelligent control system based on multi-source signal fusion according to claim 1 is characterized in that: The data fusion platform is specifically used for: The multi-source signals are subjected to data preprocessing, data storage, data fusion, data calculation and data output to obtain the fused signal.

4. The green hydrogen production intelligent control system based on multi-source signal fusion according to claim 3 is characterized in that: The data fusion platform is further used for: The data of the multi-source signal that does not use the data source is cleaned and converted according to the data fusion standard to obtain a preprocessed signal; Storing valid data in the preprocessed signal in a database; The preprocessed signals from different data sources are input into the mathematical model, and the neural network algorithm is used to perform data operations to obtain the operation results, which are then output to the corresponding equipment as fusion signals.

5. The green hydrogen production intelligent control system based on multi-source signal fusion according to claim 1 is characterized in that: The intelligent control platform is also used for: receiving a first input from a user, and selecting a mode in response to the first input; receiving a second input from a user, and selecting an operation scenario in response to the second input; A third input from the user is received, and a human-machine interface selection is performed in response to the third input. The modes include a novice mode and a professional mode, the operating scenarios include sea, desert, Gobi and hills, and the human-computer interface includes voice recognition, keyboard input and touch screen handwriting.

6. The green hydrogen production intelligent control system based on multi-source signal fusion according to claim 1 is characterized in that: The multi-source signal acquisition platform communicates with each subsystem via the Modbus TCP protocol through an intelligent Ethernet switch; The data fusion platform communicates with the multi-source signal acquisition platform via a core switch using the Modbus TCP protocol; The intelligent control platform includes a host computer, which communicates with the data fusion platform via a core switch using the Modbus TCP protocol.

7. The green hydrogen production intelligent control system based on multi-source signal fusion according to claim 1 is characterized in that: The operation modes of the system include normal operation mode, manual operation mode, fault operation mode, maintenance operation mode and fault operation mode, and the switching of the system operation modes is achieved through mode switching.

8. The green hydrogen production intelligent control system based on multi-source signal fusion according to claim 7 is characterized in that: The operation scenarios of the manual operation mode include: system failure and shutdown of the wind farm, failure of the hydrogen production automatic system, and triggering of the safety circuit; The intelligent control platform is also used for: When a systemic fault occurs and the system shuts down, the hydrogen production automatic system fails, or the safety loop is triggered, the fault and scheduling-related data will be fed back to the upper-level dispatcher based on the internal fault situation. The related data include safety lockout information, fault content, shutdown decision, dispatchable gas volume, and operation and maintenance decision.

9. The green hydrogen production intelligent control system based on multi-source signal fusion according to claim 2 is characterized in that: The hydrogen production subsystem is also used for: In the event of a network outage, the system enters an isolated grid mode and determines a safety control strategy based on internal status, load conditions, hydrogen storage conditions, and a locking signal to maintain system safety based on the safety control strategy.

10. The green hydrogen production intelligent control system based on multi-source signal fusion according to claim 9 is characterized in that: The working process of the hydrogen production subsystem includes: Receive wind power prediction data, optical power prediction data and laser wind measurement data through feedforward control to achieve power prediction; The amount of hydrogen is controlled by double-loop PI closed-loop regulation to achieve safe and stable operation of the hydrogen production subsystem; The disturbances of photovoltaic power generation, wind speed and power grid are adjusted through disturbance regulation to maintain the stable operation of the hydrogen production subsystem.

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