Off-line hydrogen energy fixed power supply system

Abstract

The invention belongs to the technical field of power supply systems, and particularly relates to an off-line hydrogen energy fixed power supply system which comprises a photovoltaic power generation module, a lithium battery energy storage module, a hydrogen fuel cell power generation module and a normal-temperature and normal-pressure solid hydrogen storage module. The photovoltaic power generation module is used for converting solar energy into direct current by adopting a solar cell panel group and utilizing a photoelectric effect; when illumination is sufficient, direct current generated by the solar cell panel directly supplies power to a load on one hand, and on the other hand, redundant electric energy is transmitted to the lithium battery energy storage module to be stored; meanwhile, when the photovoltaic generating capacity is larger than the load requirement and the lithium battery charging requirement, the residual electric energy can electrolyze water into hydrogen and oxygen based on electrolyzed water, and the hydrogen is stored in the normal-temperature and normal-pressure solid-state hydrogen storage module. According to the system, redundant electric energy is converted into hydrogen energy to be stored, the overall utilization rate of solar energy is increased, excessive dependence on large-area laying of photovoltaic panels is reduced, and the problem of land resource shortage is relieved to a certain extent.

Description

Technical Field

[0001] This invention relates to the field of power system technology, specifically to an offline hydrogen energy stationary power system. Background Technology

[0002] A power supply system is a collection of devices that provide stable and reliable electrical energy to various equipment. It mainly consists of rectifiers, DC power distribution equipment, battery banks, DC converters, etc., and ensures the normal operation of equipment through energy conversion and distribution.

[0003] However, current power systems have the following problems:

[0004] (I) Traditional fossil fuel power generation

[0005] Environmental pollution: Traditional fossil fuel power generation equipment such as diesel generators emit large amounts of pollutants such as carbon dioxide, nitrogen oxides, and particulate matter during operation. Taking a small construction site as an example, if a 50kW diesel generator is used continuously for power supply for a month (based on 8 hours of operation per day), it is estimated that the amount of carbon dioxide emitted can reach tens of tons, while also producing large amounts of nitrogen oxides and other harmful gases. This causes serious damage to the surrounding air quality and ecological environment, exacerbating environmental problems such as global warming.

[0006] Energy resource constraints: Fossil fuels are non-renewable resources, and as extraction continues, reserves are gradually decreasing. Their price fluctuations are also affected by a variety of complex factors, including international politics and economics. For example, during periods of international instability, oil prices may rise sharply, causing a dramatic increase in the cost of relying on diesel power generation, impacting the economic viability and stability of electricity supply.

[0007] Range and storage issues: Fossil fuel power generation relies on a continuous supply of fuel, which requires significant space for storage and poses safety hazards such as flammability and explosiveness. For example, in some remote communication base stations, storing large quantities of diesel fuel not only takes up space but also requires regular replenishment; if transportation is disrupted, there is a risk of power outages.

[0008] (ii) Power generation from a single renewable energy source

[0009] Photovoltaic power generation

[0010] Limited by weather and time: Photovoltaic power generation depends on sunlight conditions. On cloudy days, rainy days, and at night, the power generation efficiency will drop significantly or even stop. For example, during the plum rain season in southern my country, several consecutive weeks of cloudy and rainy weather can reduce the power generation of photovoltaic power plants by 70%-80% compared to normal sunny days, making it difficult to meet stable electricity demand.

[0011] Relatively low energy density: Solar panels require a large footprint, necessitating the installation of large areas of panels to generate significant power. This limitation is particularly pronounced in areas with limited land resources, increasing construction and maintenance costs.

[0012] Wind power generation

[0013] High geographical requirements: Wind power generation requires specific wind resources and is often located in remote grasslands, coastal areas, and other remote regions, making grid connection difficult. For example, in mountainous areas, due to complex terrain and unstable wind speeds, it is difficult to build large-scale wind farms. Even if small wind turbines are built, their power generation efficiency will be greatly reduced due to terrain factors.

[0014] Intermittency and volatility: The size and direction of wind change constantly, resulting in unstable wind power output, which poses a challenge to the stability of power supply and requires large-scale energy storage facilities to balance power fluctuations.

[0015] (III) Existing Energy Storage Systems

[0016] Lead-acid battery energy storage

[0017] Low energy density: Lead-acid batteries have a relatively low energy density, meaning they require a larger volume and weight to store the same amount of energy. In space-constrained applications, such as small emergency power supplies, they are ill-suited to meet the demands of large-capacity energy storage.

[0018] Short cycle life: Generally, lead-acid batteries can only be charged and discharged 300-500 times. After frequent charging and discharging, their performance degrades significantly, requiring frequent battery replacements, which increases usage costs and environmental pollution.

[0019] Lithium-ion battery energy storage

[0020] Safety Hazards: Under abnormal conditions such as high temperature, overcharging, and over-discharging, lithium-ion batteries pose safety risks such as fire and explosion. For example, in recent years, there have been frequent fires in electric vehicles caused by lithium battery malfunctions, posing a serious safety threat to users.

[0021] High cost: The manufacturing cost of lithium-ion batteries is relatively high, especially for high-performance lithium batteries, which limits their large-scale application to some extent, particularly for cost-sensitive markets and application scenarios.

[0022] Recycling challenges: The recycling technology for used lithium-ion batteries is not yet perfect. If not handled properly, the heavy metals and chemicals in them can pollute the soil and water sources.

[0023] Based on the above, an offline hydrogen energy stationary power supply system is invented. Summary of the Invention

[0024] To address the aforementioned technical problems, according to one aspect of the present invention, the present invention provides the following technical solution:

[0025] An offline hydrogen energy stationary power system includes a photovoltaic power generation module, a lithium battery energy storage module, a hydrogen fuel cell power generation module, and a room temperature and pressure solid hydrogen storage module.

[0026] The photovoltaic power generation module is used to convert solar energy into direct current using solar panels through the photoelectric effect. When there is sufficient sunlight, the direct current generated by the solar panels directly powers the load and transmits the excess power to the lithium battery energy storage module for storage. At the same time, when the photovoltaic power generation exceeds the load demand and the lithium battery charging demand, the remaining power can be used to electrolyze water into hydrogen and oxygen, and the hydrogen is stored in a solid hydrogen storage module at room temperature and pressure.

[0027] The lithium battery energy storage module is used to store excess electrical energy generated by photovoltaic power generation using a high-performance lithium-ion battery pack and to provide emergency power support when the system load changes or other modules fail; during periods without sunlight, its lithium battery releases the stored electrical energy to power the load and maintain the normal operation of the system.

[0028] The hydrogen fuel cell power generation module is used to release hydrogen from the solid hydrogen storage module at room temperature and pressure when the lithium battery power is low and the photovoltaic power generation is insufficient to meet the load demand. The hydrogen then reacts with oxygen in the air in the hydrogen fuel cell to convert chemical energy into electrical energy and power the load.

[0029] The ambient temperature and pressure solid-state hydrogen storage module is used to store hydrogen in a solid medium using solid-state hydrogen storage materials. When the system needs hydrogen, it will release hydrogen from the solid-state hydrogen storage material by heating, so that the hydrogen fuel cell can use it.

[0030] As a preferred embodiment of the offline hydrogen energy stationary power supply system described in this invention, it further includes:

[0031] The energy management and monitoring module is used to acquire the operating parameters and status information of each module in real time, and to coordinate and control the operation of each module.

[0032] As a preferred embodiment of the offline hydrogen energy stationary power supply system described in this invention, the energy management and monitoring module includes:

[0033] The data acquisition module is used to collect key operating parameters of each module in real time; at the same time, it also collects real-time load data.

[0034] The data processing and analysis module is used to rapidly process and deeply analyze the massive amounts of collected data. First, the data is screened and verified to remove abnormal data and interference signals, ensuring accuracy and reliability. Then, using preset algorithms and models, it analyzes the power generation trend of the photovoltaic power generation module and, combined with weather forecast data, predicts the photovoltaic power generation capacity for a future period. It assesses the health status and remaining capacity of the lithium battery energy storage module and predicts its available power supply duration. It analyzes the operating efficiency and hydrogen consumption rate of the hydrogen fuel cell and, combined with the hydrogen storage capacity of the ambient temperature and pressure solid-state hydrogen storage module, assesses the sustainability of hydrogen-powered electricity. Simultaneously, it statistically analyzes the load's electricity consumption patterns and fluctuations to determine the load's power demand characteristics.

[0035] As a preferred embodiment of the offline hydrogen energy stationary power supply system described in this invention, the energy management and monitoring module further includes:

[0036] The control strategy formulation and execution module is used to formulate corresponding energy control strategies based on the results of data processing and analysis, and issue control commands to each module. When photovoltaic power generation is high and load demand is low, the module instructs the lithium battery energy storage module to increase charging power and improve the efficiency of water electrolysis to produce hydrogen, converting excess electrical energy into hydrogen energy for storage. When sunlight weakens, photovoltaic power generation decreases, and the lithium battery SOC drops to a set threshold, the module instructs the hydrogen fuel cell power generation module to start, gradually increasing output power to make up for the shortfall in photovoltaic power supply. If load demand suddenly increases, the module prioritizes the use of photovoltaic and lithium battery power while rapidly increasing the output power of the hydrogen fuel cell as needed to ensure stable power supply to the load. In addition, the module dynamically adjusts its operating parameters according to the operating status of each module to ensure that each module is always in the optimal operating state.

[0037] The status monitoring and early warning feedback module is used to monitor the execution and operating status of each module, comparing the actual operating parameters with the preset normal range. If the parameters of a certain module are found to be outside the normal range, an early warning signal will be issued immediately. The early warning signal will be displayed locally through an audible and visual alarm device and simultaneously transmitted to the remote monitoring center. At the same time, the system's operating data, control commands, and fault information will be recorded to form a historical record, providing data support for the system's optimized operation and maintenance.

[0038] As a preferred embodiment of the offline hydrogen energy stationary power supply system described in this invention, it further includes:

[0039] The load demand forecasting and dynamic adjustment module is used to forecast load demand for a period of time in the future by using historical load data, weather forecast information and related algorithms. Based on the forecast results, the energy management and monitoring module can dynamically adjust the operation of each module in advance.

[0040] As a preferred embodiment of the offline hydrogen energy stationary power supply system described in this invention, the load demand prediction and dynamic adjustment module includes:

[0041] The data collection module is used to collect various historical and real-time data related to load requirements;

[0042] The model building and training module is used to first select an appropriate prediction algorithm to build a load demand prediction model based on the collected historical data; then, the model is trained by dividing the historical data into a training set and a validation set according to a certain ratio, using the training set to adjust and optimize the model parameters, and using the validation set to test the model's prediction accuracy.

[0043] As a preferred embodiment of the offline hydrogen energy stationary power supply system described in this invention, the load demand prediction and dynamic adjustment module further includes:

[0044] The prediction execution module is used to input the real-time collected current data into the trained prediction model so that the model can output the load demand prediction results for a period of time in the future. The prediction results are presented in the form of specific power values ​​or power ranges, providing a basis for the energy management and monitoring module to formulate energy control strategies. At the same time, the prediction results are updated regularly. As new real-time data is continuously input, the model will dynamically adjust the prediction results to ensure the timeliness and accuracy of the prediction.

[0045] The dynamic adjustment module enables the energy management and monitoring module to dynamically adjust the operation of each module based on the load demand forecast and the real-time operating status of each energy module. During the adjustment process, the actual load demand is compared with the forecast value in real time. When the difference exceeds the set threshold, the adjustment strategy is corrected in time to ensure accurate matching between energy supply and load demand.

[0046] As a preferred embodiment of the offline hydrogen energy stationary power supply system described in this invention, the load demand prediction and dynamic adjustment module further includes:

[0047] The performance evaluation and optimization module is used to periodically evaluate the accuracy of load demand forecasting and the effectiveness of dynamic adjustments. First, it calculates the deviation rate between the forecast value and the actual load demand and analyzes the causes of the deviation. Then, based on the evaluation results, it optimizes the forecasting model to improve forecast accuracy. At the same time, it improves the dynamic adjustment strategy to make it more adaptable to complex and ever-changing load demands and energy supply conditions, and continuously improves the system's energy utilization efficiency and power supply stability.

[0048] Compared with existing technologies:

[0049] I. Matching Photovoltaic Power Generation Modules with Problems

[0050] Currently, single-phase photovoltaic (PV) power generation is limited by weather and time, with efficiency dropping significantly during cloudy, rainy, and nighttime periods, and energy density remaining low. However, the PV modules in this system not only directly supply power when there is sufficient sunlight, but also store excess energy in lithium batteries and convert it into hydrogen for storage. This working principle effectively addresses its inherent limitations: firstly, by combining with energy storage modules, it compensates for the power supply gap caused by insufficient or no sunlight, eliminating power outages due to weather and time changes; secondly, although the energy density of solar panels is relatively low, the system converts excess energy into hydrogen for storage, improving the overall utilization rate of solar energy, reducing over-reliance on large-scale PV panel deployment, and alleviating land resource constraints to some extent.

[0051] II. Matching Lithium-ion Battery Energy Storage Modules with Problems

[0052] Existing lithium-ion batteries pose safety risks, high costs, and recycling challenges, while lead-acid batteries suffer from low energy density and short cycle life. This system's lithium battery energy storage module utilizes high-performance lithium-ion battery packs, primarily for short-term energy storage and emergency support. Through reasonable charge and discharge management, it reduces overcharging and over-discharging, minimizing safety hazards. Furthermore, it works in conjunction with photovoltaic and hydrogen energy modules, eliminating the need for large-scale lithium battery deployment and reducing reliance on high-performance lithium batteries, thus controlling costs to some extent. In addition, since lithium batteries primarily serve a regulatory and emergency role in the system, the number of charge and discharge cycles is relatively reasonable, extending their lifespan and reducing the amount of waste batteries generated, which also alleviates recycling pressure to some extent. Compared to lead-acid batteries, high-performance lithium batteries have higher energy density, can meet energy storage needs in a smaller space, and have a longer cycle life, reducing replacement frequency and costs.

[0053] III. Matching Hydrogen Fuel Cell Power Generation Modules with Problems

[0054] Traditional fossil fuel power generation is heavily polluting, resource-constrained, and has uncertain lifespans; relying on a single renewable energy source results in poor stability. Hydrogen fuel cell power generation modules use hydrogen as fuel, with water as the only byproduct, completely solving the environmental pollution problems of traditional fossil fuel power generation and eliminating emissions of carbon dioxide, nitrogen oxides, and other pollutants. The hydrogen fuel can be produced from surplus photovoltaic power, eliminating dependence on fossil fuels and protecting against fluctuations in international energy prices, ensuring the economic efficiency and stability of power supply. Regarding lifespan, as long as the solid-state hydrogen storage module at room temperature and pressure has sufficient hydrogen, it can continuously generate electricity. Furthermore, hydrogen production can utilize renewable energy sources, eliminating the need for frequent fuel transportation and solving the lifespan and transportation problems of traditional fossil fuels. Simultaneously, the module activates when photovoltaic and lithium battery power is insufficient, supplementing the power gap. Working in conjunction with other modules, it overcomes the intermittency and volatility of relying on a single renewable energy source, ensuring a stable power supply.

[0055] IV. Matching the Problem with Ambient Temperature and Pressure Solid-State Hydrogen Storage Modules

[0056] Traditional fossil fuel storage poses safety risks and occupies a large space, while high-pressure gaseous hydrogen storage and cryogenic liquid hydrogen storage also present safety and cost issues. Room-temperature and atmospheric-pressure solid-state hydrogen storage modules utilize solid-state hydrogen storage materials to store hydrogen, achieving stable storage at room temperature and pressure. This offers significantly higher safety than traditional fossil fuel storage and other hydrogen storage methods, avoiding the risks of flammability and explosion. Its high storage density and small volume save storage space, solving the problem of large space requirements associated with traditional fuel storage. Furthermore, hydrogen can be produced using photovoltaic power, eliminating the need for external transportation like fossil fuels, ensuring a continuous energy supply and preventing power outages due to fuel transportation disruptions. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the overall framework of the present invention. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0059] This invention provides an offline hydrogen-powered stationary power system. Please refer to [link / reference]. Figure 1 These include photovoltaic power generation modules, lithium battery energy storage modules, hydrogen fuel cell power generation modules, and ambient temperature and pressure solid-state hydrogen storage modules.

[0060] The photovoltaic power generation module is used to convert solar energy into direct current using solar panels through the photoelectric effect. When there is sufficient sunlight, the direct current generated by the solar panels directly powers the load and transmits the excess power to the lithium battery energy storage module for storage. At the same time, when the photovoltaic power generation exceeds the load demand and the lithium battery charging demand, the remaining power can be used to electrolyze water into hydrogen and oxygen, and the hydrogen is stored in a solid hydrogen storage module at room temperature and pressure.

[0061] The lithium battery energy storage module is used to store excess electrical energy generated by photovoltaic power generation using a high-performance lithium-ion battery pack, and to provide emergency power support when the system load changes or other modules fail. During periods of insufficient photovoltaic power generation or no sunlight, such as at night, the lithium battery releases the stored electrical energy to power the load and maintain the normal operation of the system. In addition, the lithium battery can also smoothly regulate the power output of the system, reduce the impact of fluctuations caused by other energy modules, and ensure the stability of the power supply.

[0062] The hydrogen fuel cell power generation module is used to release hydrogen from the solid hydrogen storage module at room temperature and pressure when the lithium battery power is low and the photovoltaic power generation is insufficient to meet the load demand. The hydrogen then reacts with oxygen in the air in the hydrogen fuel cell to convert chemical energy into electrical energy to power the load. The waste heat generated during the hydrogen fuel cell power generation process can be utilized through a heat recovery device, such as for heating water or maintaining a suitable temperature in the system, thereby improving the overall energy utilization efficiency.

[0063] The ambient temperature and pressure solid-state hydrogen storage module utilizes the high hydrogen adsorption capacity of solid-state hydrogen storage materials to store hydrogen in a solid medium. Compared with traditional high-pressure gaseous hydrogen storage and low-temperature liquid hydrogen storage methods, solid-state hydrogen storage has advantages such as high safety, high storage density, and small volume. When the system needs hydrogen, it will release hydrogen from the solid-state hydrogen storage material through heating or other means for use by the hydrogen fuel cell.

[0064] It also includes an energy management and monitoring module, which is used to obtain the operating parameters and status information of each module in real time, and to coordinate and control the operation of each module.

[0065] By setting up the energy management and monitoring module, the following effects can be achieved:

[0066] 1. Optimized Energy Distribution: The energy management and monitoring module can intelligently adjust the flow and distribution of energy among modules based on real-time operating data, such as the output power of photovoltaic power generation, the remaining capacity of lithium batteries, the operating status of hydrogen fuel cells, and the power demand of the load. For example, when there is sufficient sunlight and photovoltaic power generation is high, the module can prioritize supplying electricity to the load, while rationally allocating excess electricity to the lithium battery energy storage module and for hydrogen production, avoiding energy waste; when sunlight is insufficient, it can promptly coordinate the lithium battery and hydrogen fuel cell power generation modules to ensure a stable power supply to the load and improve energy utilization efficiency.

[0067] 2. Fault Diagnosis and Early Warning: By monitoring key parameters such as voltage, current, and temperature of each module in real time, abnormal conditions during module operation can be detected in a timely manner. For example, when the lithium battery shows signs of overcharging or over-discharging, or when the temperature of the hydrogen fuel cell rises abnormally, the module can immediately issue an early warning signal and take corresponding protective measures, such as cutting off the charging circuit and reducing the output power of the fuel cell, to prevent the fault from escalating and improve the reliability and safety of the system.

[0068] 3. Remote Monitoring and Management: Utilizing communication technology, the energy management and monitoring module can transmit system operation data to a remote monitoring center, allowing staff to monitor the system's operational status in real time via remote terminals. For power systems in remote areas, on-site monitoring is unnecessary, reducing maintenance costs and facilitating timely problem detection and resolution, thus improving system maintenance efficiency.

[0069] The energy management and monitoring module includes:

[0070] The data acquisition module is used to collect key operating parameters of each module in real time. For the photovoltaic power generation module, it collects data such as output voltage, current, power, and solar irradiance. For the lithium battery energy storage module, it collects information such as battery SOC (state of charge), voltage, current, temperature, and charge / discharge rate. The hydrogen fuel cell power generation module collects data such as output power, voltage, current, hydrogen inlet flow rate, temperature, pressure, and the state of the reaction product water. The ambient temperature and pressure solid hydrogen storage module mainly collects parameters such as hydrogen storage capacity, internal temperature, and pressure. At the same time, it also collects real-time power demand, voltage, and current data of the load.

[0071] The data processing and analysis module is used to rapidly process and deeply analyze the massive amounts of collected data. First, the data is screened and verified to remove abnormal data and interference signals, ensuring accuracy and reliability. Then, using preset algorithms and models, it analyzes the power generation trend of the photovoltaic power generation module and, combined with weather forecast data, predicts the photovoltaic power generation in the future. It also assesses the health status and remaining capacity of the lithium battery energy storage module, predicting its available power supply duration. Furthermore, it analyzes the operating efficiency and hydrogen consumption rate of the hydrogen fuel cell, and, combined with the hydrogen storage capacity of the ambient temperature and pressure solid-state hydrogen storage module, assesses the sustainability of hydrogen power supply. Simultaneously, it statistically analyzes the load's power consumption patterns and fluctuations to determine the load's power demand characteristics.

[0072] The control strategy formulation and execution module is used to formulate corresponding energy control strategies based on the results of data processing and analysis, and issue control commands to each module. When photovoltaic power generation is high and load demand is low, the module instructs the lithium battery energy storage module to increase charging power and improve the efficiency of water electrolysis to produce hydrogen, converting excess electrical energy into hydrogen energy for storage. When sunlight weakens, photovoltaic power generation decreases, and the lithium battery SOC drops to a set threshold, the module instructs the hydrogen fuel cell power generation module to start, gradually increasing output power to make up for the shortfall in photovoltaic power supply. If load demand suddenly increases, the module prioritizes the use of photovoltaic and lithium battery power while rapidly increasing the output power of the hydrogen fuel cell as needed to ensure stable power supply to the load. In addition, the module dynamically adjusts its operating parameters based on the operating status of each module, such as adjusting the output voltage of the photovoltaic inverter, controlling the charging and discharging current of the lithium battery, and adjusting the hydrogen supply of the hydrogen fuel cell, so that each module is always in the optimal operating state.

[0073] The status monitoring and early warning feedback module monitors the execution and operating status of each module, comparing actual operating parameters with preset normal ranges. If a module's parameters exceed the normal range, such as excessively high lithium battery temperature, abnormal hydrogen fuel cell pressure, or a sudden drop in photovoltaic power generation, an early warning signal will be immediately issued. This signal will be displayed locally via an audible and visual alarm and simultaneously transmitted to the remote monitoring center. For minor anomalies, the module will automatically take protective measures, such as reducing the lithium battery charging current and decreasing the hydrogen fuel cell output power. For serious faults, the module will urgently shut down the operation of the relevant modules to prevent the fault from spreading and will provide detailed fault information to the remote monitoring center for timely maintenance. Simultaneously, the module will record system operating data, control commands, and fault information, creating a historical record to provide data support for system optimization and maintenance.

[0074] It also includes a load demand forecasting and dynamic adjustment module, which uses historical load data, weather forecast information and related algorithms to forecast load demand for a period of time in the future, so that the operation of each module can be dynamically adjusted in advance through the energy management and monitoring module based on the forecast results.

[0075] By setting up a load demand forecasting and dynamic adjustment module, the following effects can be achieved:

[0076] By leveraging historical load data, weather forecasts, and relevant algorithms, the system predicts load demand for a future period. Based on these predictions, the energy management and monitoring module dynamically adjusts the operation of each module in advance. For example, if a high load demand and favorable sunlight conditions are predicted for a future day, the operating status of the photovoltaic power generation module can be adjusted to generate as much power as possible during periods of ample sunlight, and this power can be rationally allocated to the load, energy storage module, and hydrogen production. If a low load demand and subsequent unfavorable weather are predicted, hydrogen production can be reduced, and photovoltaic power can be prioritized for storage in lithium batteries. This step improves the accuracy of energy allocation, avoids energy waste, and ensures efficient and coordinated operation of each module while meeting load demand, thereby enhancing the overall economy and stability of the system.

[0077] The load demand prediction and dynamic adjustment module includes:

[0078] The data collection module is used to collect various historical and real-time data related to load demand. Historical data includes load power consumption values ​​for different time periods in the past (such as hours, days, weeks, and months), corresponding dates (weekdays, weekends, and holidays), weather conditions (temperature, sunshine, rainfall, etc.), and special events (such as equipment maintenance, temporary work, etc.). Real-time data covers the current load operating status, real-time power consumption, and weather change trends. This data is collected through sensors, smart meters, and related data recording devices and stored in the database to provide sufficient samples for subsequent prediction models.

[0079] The model building and training module is used to first construct a load demand prediction model based on collected historical data and a suitable prediction algorithm (such as time series analysis, random forests in machine learning algorithms, neural networks, etc.). Next, the model is trained by dividing the historical data into training and validation sets according to a certain ratio. The training set is used to adjust and optimize the model's parameters, while the validation set is used to verify the model's prediction accuracy. During training, the model's parameters are continuously corrected to accurately capture the patterns of load demand changes with time, weather, special events, and other factors, thereby improving the model's prediction reliability. For example, analysis may reveal that a communication base station experiences a significant increase in load demand during the summer's high-temperature period due to the operation of air conditioning equipment; the model needs to learn this pattern and reflect it in its predictions.

[0080] The prediction execution module is used to input real-time collected current data (such as real-time weather data, current load consumption trends, etc.) into the trained prediction model, so that the model outputs load demand prediction results for a future period of time (such as the next 1 hour, 6 hours, 24 hours). The prediction results are presented in the form of specific power values ​​or power ranges, providing a basis for the energy management and monitoring module to formulate energy control strategies. At the same time, the prediction results are updated regularly. As new real-time data is continuously input, the model will dynamically adjust the prediction results to ensure the timeliness and accuracy of the prediction.

[0081] The dynamic adjustment module enables the energy management and monitoring module to dynamically adjust the operation of each energy module based on load demand forecasts and the real-time operating status of each module (such as photovoltaic power generation, lithium battery energy storage capacity, and solid-state hydrogen storage capacity). If a significant increase in future load demand is predicted, and favorable sunlight conditions are anticipated, the photovoltaic power generation module can be instructed to prepare for full-load power generation in advance, while ensuring that the lithium battery is at a high state of charge, and producing more hydrogen for storage if necessary. If a decrease in load demand is predicted, the power of water electrolysis for hydrogen production can be appropriately reduced to minimize energy waste, and photovoltaic energy can be prioritized for storage in the lithium battery. During the adjustment process, the difference between the actual load demand and the predicted value is compared in real time. When the difference exceeds a set threshold, the adjustment strategy is promptly corrected to ensure a precise match between energy supply and load demand.

[0082] The performance evaluation and optimization module is used to periodically evaluate the accuracy of load demand forecasting and the effectiveness of dynamic adjustments. First, it calculates the deviation rate between the forecast value and the actual load demand and analyzes the causes of the deviation (such as sudden equipment failure, abnormal weather changes, etc.). Then, based on the evaluation results, it optimizes the forecasting model, such as adding new influencing factors and adjusting algorithm parameters, to improve forecast accuracy. At the same time, it improves the dynamic adjustment strategy to better adapt to complex and ever-changing load demands and energy supply conditions, and continuously improves the system's energy utilization efficiency and power supply stability.

[0083] In practical use, the specific steps are as follows:

[0084] S1: The photovoltaic power generation module uses solar panels to convert solar energy into direct current through the photoelectric effect. When there is sufficient sunlight, the direct current generated by the solar panels directly powers the load and transmits the excess power to the lithium battery energy storage module for storage. At the same time, when the photovoltaic power generation exceeds the load demand and the lithium battery charging demand, the remaining power can be used to electrolyze water into hydrogen and oxygen, and the hydrogen is stored in the room temperature and pressure solid hydrogen storage module.

[0085] S2: The lithium battery energy storage module uses a high-performance lithium-ion battery pack to store excess electrical energy generated by photovoltaic power generation and to provide emergency power support when the system load changes or other modules fail. During periods of insufficient photovoltaic power generation or no sunlight, the lithium battery releases the stored electrical energy to power the load and maintain the normal operation of the system. In addition, the lithium battery can also smoothly regulate the power output of the system, reduce the impact of fluctuations in other energy modules, and ensure the stability of the power supply.

[0086] S3: When the lithium battery capacity is low and photovoltaic power generation is insufficient to meet the load demand, the hydrogen in the solid hydrogen storage module at room temperature and pressure can be released through the hydrogen fuel cell power generation module. The hydrogen reacts with oxygen in the air in the hydrogen fuel cell to convert chemical energy into electrical energy to power the load. The waste heat generated during the hydrogen fuel cell power generation process can be utilized through a heat recovery device, such as for heating water or maintaining a suitable temperature in the system, thereby improving the overall energy utilization efficiency.

[0087] S4: The solid-state hydrogen storage module at ambient temperature and pressure utilizes the high hydrogen adsorption capacity of solid-state hydrogen storage materials to store hydrogen in a solid medium. Compared with traditional high-pressure gaseous hydrogen storage and low-temperature liquid hydrogen storage methods, solid-state hydrogen storage has advantages such as high safety, high storage density, and small volume. When the system needs hydrogen, the solid-state hydrogen storage material will release hydrogen through heating or other means to supply hydrogen fuel cells.

[0088] S5: The energy management and monitoring module acquires the operating parameters and status information of each module in real time, and coordinates and controls the operation of each module.

[0089] S6: The load demand forecasting and dynamic adjustment module uses historical load data, weather forecast information, and related algorithms to forecast the load demand for a period of time in the future. Based on the forecast results, the energy management and monitoring module can dynamically adjust the operation of each module in advance.

[0090] Although the present invention has been described above with reference to embodiments, various modifications can be made and components can be replaced with equivalents without departing from the scope of the invention. In particular, as long as there is no structural conflict, the features in the disclosed embodiments can be combined with each other in any manner. The lack of an exhaustive description of these combinations in this specification is merely for the sake of brevity and resource conservation. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. An offline hydrogen-powered stationary power supply system, characterized in that, This includes photovoltaic power generation modules, lithium battery energy storage modules, hydrogen fuel cell power generation modules, and room temperature and pressure solid-state hydrogen storage modules; The photovoltaic power generation module is used to convert solar energy into direct current using solar panels through the photoelectric effect. When there is sufficient sunlight, the direct current generated by the solar panels directly powers the load and transmits the excess power to the lithium battery energy storage module for storage. At the same time, when the photovoltaic power generation exceeds the load demand and the lithium battery charging demand, the remaining power can be used to electrolyze water into hydrogen and oxygen, and the hydrogen is stored in a solid hydrogen storage module at room temperature and pressure. The lithium battery energy storage module is used to store excess electrical energy generated by photovoltaic power generation using a high-performance lithium-ion battery pack and to provide emergency power support when the system load changes or other modules fail. During periods without sunlight, its lithium battery releases the stored electrical energy to power the load and maintain the normal operation of the system; The hydrogen fuel cell power generation module is used to release hydrogen from the solid hydrogen storage module at room temperature and pressure when the lithium battery power is low and the photovoltaic power generation is insufficient to meet the load demand. The hydrogen then reacts with oxygen in the air in the hydrogen fuel cell to convert chemical energy into electrical energy and power the load. The ambient temperature and pressure solid-state hydrogen storage module is used to store hydrogen in a solid medium using ambient temperature and pressure solid-state hydrogen storage materials; when the system needs hydrogen, it will release hydrogen from the solid-state hydrogen storage material by heating, so that the hydrogen fuel cell can use it.

2. The offline hydrogen energy stationary power supply system according to claim 1, characterized in that, Also includes: The energy management and monitoring module is used to acquire the operating parameters and status information of each module in real time, and to coordinate and control the operation of each module.

3. The offline hydrogen energy stationary power supply system according to claim 2, characterized in that, The energy management and monitoring module includes: The data acquisition module is used to collect key operating parameters of each module in real time; at the same time, it also collects real-time load data. The data processing and analysis module is used to rapidly process and deeply analyze the massive amounts of collected data. First, the data is screened and verified to remove abnormal data and interference signals, ensuring accuracy and reliability. Then, using preset algorithms and models, it analyzes the power generation trend of the photovoltaic power generation module and, combined with weather forecast data, predicts the photovoltaic power generation capacity for a future period. It assesses the health status and remaining capacity of the lithium battery energy storage module and predicts its available power supply duration. It analyzes the operating efficiency and hydrogen consumption rate of the hydrogen fuel cell and, combined with the hydrogen storage capacity of the ambient temperature and pressure solid-state hydrogen storage module, assesses the sustainability of hydrogen-powered electricity. Simultaneously, it statistically analyzes the load's electricity consumption patterns and fluctuations to determine the load's power demand characteristics.

4. The offline hydrogen energy stationary power supply system according to claim 3, characterized in that, The energy management and monitoring module also includes: The control strategy formulation and execution module is used to formulate corresponding energy control strategies based on the results of data processing and analysis, and issue control commands to each module. When photovoltaic power generation is high and load demand is low, the module instructs the lithium battery energy storage module to increase charging power and improve the efficiency of water electrolysis to produce hydrogen, converting excess electrical energy into hydrogen energy for storage. When sunlight weakens, photovoltaic power generation decreases, and the lithium battery SOC drops to a set threshold, the module instructs the hydrogen fuel cell power generation module to start, gradually increasing output power to make up for the shortfall in photovoltaic power supply. If load demand suddenly increases, the module prioritizes the use of photovoltaic and lithium battery power while rapidly increasing the output power of the hydrogen fuel cell as needed to ensure stable power supply to the load. In addition, the module dynamically adjusts its operating parameters according to the operating status of each module to ensure that each module is always in the optimal operating state. The status monitoring and early warning feedback module is used to monitor the execution and operating status of each module, comparing the actual operating parameters with the preset normal range. If the parameters of a certain module are found to be outside the normal range, an early warning signal will be issued immediately. The early warning signal will be displayed locally through an audible and visual alarm device and simultaneously transmitted to the remote monitoring center. At the same time, the system's operating data, control commands, and fault information will be recorded to form a historical record, providing data support for the system's optimized operation and maintenance.

5. An offline hydrogen energy stationary power supply system according to claim 1, characterized in that, Also includes: The load demand forecasting and dynamic adjustment module is used to forecast load demand for a period of time in the future by using historical load data, weather forecast information and related algorithms. Based on the forecast results, the energy management and monitoring module can dynamically adjust the operation of each module in advance.

6. An offline hydrogen energy stationary power supply system according to claim 5, characterized in that, The load demand prediction and dynamic adjustment module includes: The data collection module is used to collect various historical and real-time data related to load requirements; The model building and training module is used to first select an appropriate prediction algorithm to build a load demand prediction model based on the collected historical data; then, the model is trained by dividing the historical data into a training set and a validation set according to a certain ratio, using the training set to adjust and optimize the model parameters, and using the validation set to test the model's prediction accuracy.

7. An offline hydrogen energy stationary power supply system according to claim 6, characterized in that, The load demand prediction and dynamic adjustment module also includes: The prediction execution module is used to input the real-time collected current data into the trained prediction model so that the model can output the load demand prediction results for a period of time in the future. The prediction results are presented in the form of specific power values ​​or power ranges, providing a basis for the energy management and monitoring module to formulate energy control strategies. At the same time, the prediction results are updated regularly. As new real-time data is continuously input, the model will dynamically adjust the prediction results to ensure the timeliness and accuracy of the prediction. The dynamic adjustment module enables the energy management and monitoring module to dynamically adjust the operation of each module based on the load demand forecast and the real-time operating status of each energy module. During the adjustment process, the actual load demand is compared with the forecast value in real time. When the difference exceeds the set threshold, the adjustment strategy is corrected in time to ensure accurate matching between energy supply and load demand.

8. An offline hydrogen energy stationary power supply system according to claim 7, characterized in that, The load demand prediction and dynamic adjustment module also includes: The performance evaluation and optimization module is used to periodically evaluate the accuracy of load demand forecasting and the effectiveness of dynamic adjustments. First, it calculates the deviation rate between the forecast value and the actual load demand and analyzes the causes of the deviation. Then, based on the evaluation results, it optimizes the forecasting model to improve forecast accuracy. At the same time, it improves the dynamic adjustment strategy to make it more adaptable to complex and ever-changing load demands and energy supply conditions, and continuously improves the system's energy utilization efficiency and power supply stability.

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