Park comprehensive energy capacity optimization system based on hydrogen energy coupling

Abstract

The invention provides a park comprehensive energy capacity optimization system based on hydrogen energy coupling, and relates to the technical field of power grid systems, and the system comprises a water electrolysis device, a self-adaptive control algorithm based on a deep neural network, and a predictive maintenance system based on the Internet of Things technology and big data analysis. The core innovation of the technology in the aspect of energy conversion is an efficient water electrolysis device. According to the device, the specially-made nano electrode and the high-performance ion exchange membrane are utilized, so that the output efficiency and the purity of hydrogen are remarkably improved. The innovation not only improves the production efficiency of the hydrogen energy, but also contributes to reducing the dependence on fossil fuel due to the wide application of the hydrogen energy as a clean energy, thereby reducing the environmental pollution. The high-efficiency energy conversion technology has great significance in promoting the development of a sustainable energy system.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid systems, and in particular to a park comprehensive energy capacity optimization system based on hydrogen energy coupling. Background Art

[0002] Based on the concept of energy hub, the energy proportion distribution modeling and analysis is carried out for the multi-energy coupling link with regional integrated energy station as the core. Considering the goals of maximizing efficiency, minimizing costs, and minimizing carbon emission indicators, a low-carbon economic operation and dispatching strategy for the regional integrated energy system is proposed, the composition of the park's integrated energy architecture with hydrogen energy coupling is studied, and a comprehensive energy system model considering the multi-mode utilization of electric hydrogen production is established; the influencing factors and changing characteristics of hydrogen production efficiency are studied, and a hydrogen energy storage optimization configuration method is proposed; the operation mechanism of the integrated energy system of the park's electricity-hydrogen-gas energy coupling is studied, and the dispatching plan of the park's integrated energy system is optimized. Summary of the invention

[0003] In view of the deficiencies of the prior art, the present invention provides a park comprehensive energy capacity optimization system based on hydrogen energy coupling, which solves the deficiencies of the prior art.

[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: a park comprehensive energy capacity optimization system based on hydrogen energy coupling,

[0005] It includes a water electrolysis device, including the following parts:

[0006] A nanoelectrode having a high specific surface area and high electrochemical activity, and used to improve the efficiency of hydrogen production;

[0007] Ion exchange membrane, which is a low resistivity and high ion selectivity membrane used to reduce energy loss and improve electrolysis efficiency;

[0008] An adaptive control algorithm based on a deep neural network, the adaptive control algorithm includes the following parts:

[0009] Real-time module: used to analyze and respond to climate change, energy demand fluctuations, equipment performance and market dynamics in real time to adjust energy production, distribution and storage strategies;

[0010] Learning module: built-in data processing and model training algorithms to continuously optimize the overall performance and efficiency of the system;

[0011] The predictive maintenance system based on IoT technology and big data analysis includes the following parts:

[0012] Sensors deployed on the equipment, which collect equipment operation data in real time, including temperature, pressure, flow rate and electrochemical parameters;

[0013] The predictive maintenance system based on Internet of Things technology and big data analysis is electrically connected to a cloud computing platform for storing, processing and analyzing collected data, and using machine learning algorithms for fault prediction and maintenance plan optimization.

[0014] Preferably, the water electrolysis device further comprises:

[0015] The catalyst is a metal oxide and is used to accelerate the water decomposition reaction and reduce the required electrical energy input; the catalyst is prepared by a nano powder processing process.

[0016] Preferably, the adaptive control algorithm based on deep neural network further includes:

[0017] a composite forecasting model that combines time series analysis, climate patterns, and market dynamics analysis to accurately forecast short-term and long-term energy demand changes;

[0018] Machine learning algorithms are used to automatically adjust energy allocation strategies to optimize cost-effectiveness and energy efficiency, continuously improving forecast accuracy and decision-making efficiency based on historical data and real-time feedback.

[0019] Preferably, the park comprehensive energy capacity optimization system based on hydrogen energy coupling further includes a system virtual copy module, and the system virtual copy module has the following parts:

[0020] 3D modeling and simulation modules to accurately reproduce the physical properties, operating parameters and behavioral characteristics of actual energy systems;

[0021] The suggestion module is used to integrate real-time operation data and historical performance data to simulate system performance, including energy efficiency analysis, fault prediction and optimization suggestions;

[0022] An interactive user interface for operators to simulate operations and maintenance in a virtual environment to improve the safety and efficiency of actual operations.

[0023] Preferably, the system virtual copy module is created using a digital twin, and the digital twin further includes:

[0024] VR interfaces to provide intuitive 3D visual representations and interactive experiences, allowing users to explore and manage energy systems in an immersive way;

[0025] The VR interface includes a sensory feedback mechanism for enhancing the realism and intuitiveness of the user's interaction with the system;

[0026] The VR interface is integrated with an analysis tool that includes sensors and an interactive user interface.

[0027] Preferably, the park comprehensive energy capacity optimization system based on hydrogen energy coupling further includes:

[0028] A blockchain-based energy management platform, which uses blockchain protocols for energy transactions and data security, and provides an unalterable and transparent recording mechanism;

[0029] The blockchain energy management platform includes a distributed ledger that records all energy production, consumption and transaction data, as well as related financial transactions, ensuring data integrity and traceability;

[0030] The blockchain's energy management platform has built-in smart contracts for automatically executing energy transactions, including automatic calculation of energy costs, transaction execution, automatic settlement and compliance verification.

[0031] Preferably, the energy management platform of the blockchain includes the following parts:

[0032] Consensus mechanism module, including proof of stake, delegated proof of stake, or a combination of the two, to increase transaction processing speed and reduce energy consumption;

[0033] The blockchain energy management platform includes a smart contract verification and execution framework, which is used to adapt to different types of energy transactions and contract requirements while ensuring the security and compliance of transactions;

[0034] The blockchain energy management platform also includes a user interface and API for allowing users to access and manage their energy transactions and contracts.

[0035] Preferably, the energy management platform of the blockchain further includes:

[0036] An advanced smart contract framework to support multiple transaction types and conditions, including real-time pricing, demand response, and renewable energy certificate trading;

[0037] The advanced smart contract framework includes contract lifecycle management, automatically starting, executing, monitoring and ending contracts, while ensuring transparency and traceability of contract execution.

[0038] Preferably, the park comprehensive energy capacity optimization system based on hydrogen energy coupling also includes an energy storage unit:

[0039] The energy storage unit uses high-density lithium-ion batteries and solid-state hydrogen storage batteries to achieve efficient and stable energy storage and rapid response capabilities;

[0040] The energy storage unit also includes a thermal management system for optimizing the operating temperature of the battery and hydrogen storage unit to improve their performance and life;

[0041] The energy storage unit also includes a battery management system (BMS) for real-time monitoring of battery status, including charge and discharge status, health status and temperature to ensure safety and efficiency.

[0042] Preferably, the energy storage unit further comprises the following parts:

[0043] A multi-mode temperature control system for automatically adjusting the temperature according to environmental conditions and storage requirements, optimizing storage efficiency and extending the life of the storage medium;

[0044] The multi-mode temperature control system uses intelligent algorithms to predict and respond to temperature changes, while combining passive and active cooling technologies to ensure optimal operating conditions for batteries and hydrogen storage units;

[0045] The multi-mode temperature control system also includes a remote monitoring and diagnostic module for tracking the performance and safety status of the storage unit in real time, supporting remote troubleshooting and maintenance planning.

[0046] The present invention provides a park comprehensive energy capacity optimization system based on hydrogen energy coupling. It has the following beneficial effects:

[0047] 1. The innovation of efficient energy conversion of the present invention. The core innovation of this technology in energy conversion lies in the efficient water electrolysis device. The device uses specially made nano-electrodes and high-efficiency ion exchange membranes to significantly improve the efficiency and purity of hydrogen output. This innovation not only improves the production efficiency of hydrogen energy, but also, as hydrogen energy is a clean energy, its widespread application helps reduce dependence on fossil fuels, thereby reducing environmental pollution. This efficient energy conversion technology is of great significance to promoting the development of sustainable energy systems.

[0048] 2. The breakthrough of intelligent energy management in the present invention. Another innovation in the system is the adaptive control algorithm based on deep neural network. This algorithm can respond to environmental changes and energy demand in real time and automatically optimize energy production and distribution strategies. This intelligent energy management method not only improves the efficiency of energy utilization, but also can flexibly respond to changes in energy demand and market conditions, thereby providing more economical and efficient energy solutions. This is crucial to ensure the economy and sustainability of the energy system.

[0049] 3. Importance of the predictive maintenance system of the present invention. The system-integrated predictive maintenance system is the third innovation. The system uses Internet of Things technology and big data analysis to monitor and predict maintenance of key equipment in real time. This method can effectively prevent equipment failures, reduce system downtime, and improve the reliability of overall operation. In the long run, this predictive maintenance can significantly reduce maintenance costs and improve system efficiency.

[0050] 4. Application of digital twin and virtual reality technology in the present invention. The fourth innovation of the system is the application of digital twin technology and virtual reality. By creating a virtual copy of the system, operators can perform simulated operation and maintenance training in a risk-free environment, greatly improving the safety and efficiency of operations. At the same time, the application of this technology makes maintenance and management decisions more accurate and intuitive, effectively reducing errors and improving the overall performance of the system.

[0051] 5. Innovative application of blockchain technology in energy management. The last important innovation is the application of blockchain technology to the energy management platform. The application of this technology provides a secure, transparent and tamper-proof energy data and transaction record platform. The use of the blockchain platform improves the efficiency and trust of energy transactions and helps promote the modernization of the energy market. This innovation has important practical significance in ensuring the security of energy transactions and improving management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is the overall system diagram of the present invention. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Specific embodiment one:

[0055] The park comprehensive energy capacity optimization system based on hydrogen energy coupling includes a water electrolysis device, including the following parts: nanoelectrodes, which have high specific surface area and high electrochemical activity, and are used to improve the production efficiency of hydrogen; ion exchange membranes, which are low resistivity and high ion selectivity membranes, are used to reduce energy loss and improve electrolysis efficiency; adaptive control algorithms based on deep neural networks, and the adaptive control algorithms include the following parts: real-time module: used to analyze and respond to climate change, energy demand fluctuations, equipment performance and market dynamics in real time, and to adjust energy production, distribution and storage strategies; learning module: built-in data processing and model training algorithms, used to continuously optimize the overall performance and efficiency of the system; based on Internet of Things technology and The predictive maintenance system based on big data analysis includes the following parts: sensors deployed on the equipment, which collect equipment operation data in real time, including temperature, pressure, flow and electrochemical parameters; the predictive maintenance system based on Internet of Things technology and big data analysis is electrically connected to the cloud computing platform for storing, processing and analyzing the collected data, and using machine learning algorithms to predict faults and optimize maintenance plans. The water electrolysis device further includes: a catalyst, which is a metal oxide, used to accelerate the water decomposition reaction and reduce the required electrical energy input; the catalyst is prepared by a nanopowder processing process, and the adaptive control algorithm based on a deep neural network further includes: a composite prediction model, which combines time series analysis, Climate pattern and market dynamics analysis for accurate prediction of short-term and long-term energy demand changes; machine learning algorithms for automatically adjusting energy allocation strategies, optimizing cost-effectiveness and energy efficiency, and continuously improving prediction accuracy and decision-making efficiency based on historical data and real-time feedback. The park comprehensive energy capacity optimization system based on hydrogen energy coupling further includes a system virtual copy module, which has the following parts: a three-dimensional modeling and simulation module for accurately reproducing the physical properties, operating parameters and behavioral characteristics of the actual energy system; a recommendation module for integrating real-time operation data and historical performance data to simulate the performance of the system, including energy efficiency analysis, fault prediction and optimization suggestions; an interactive user interface for operators to use in a virtual environment Simulate operation and maintenance to improve the safety and efficiency of actual operations. The system virtual copy module is created using digital twins. The digital twins further include: a VR interface for providing intuitive three-dimensional visual representations and interactive experiences, allowing users to explore and manage energy systems in an immersive way; the VR interface includes a sensory feedback mechanism to enhance the realism and intuitiveness of user interaction with the system; the VR interface is integrated with an analysis tool, which includes sensors and an interactive user interface. The park comprehensive energy capacity optimization system based on hydrogen energy coupling further includes: a blockchain-based energy management platform, which uses blockchain protocols for energy transactions and data security, and provides an unalterable and transparent recording mechanism;The energy management platform of blockchain includes a distributed ledger for recording all energy production, consumption and transaction data, as well as related financial transactions, to ensure the integrity and traceability of data; the energy management platform of blockchain has built-in smart contracts for automatically executing energy transactions, including automatic calculation of energy costs, execution of transactions, automatic settlement and compliance verification. The energy management platform of blockchain includes the following parts: a consensus mechanism module, including proof of stake, delegated proof of stake, or any one of the two, or a combination of the two, to increase transaction processing speed and reduce energy consumption; the energy management platform of blockchain includes a verification and execution framework for smart contracts, which is used to adapt to different types of energy transactions and contract requirements while ensuring the security and compliance of transactions; the energy management platform of blockchain also includes a user interface and API to allow users to access and manage their energy transactions and contracts. The energy management platform of blockchain further includes: an advanced smart contract framework to support multiple transaction types and conditions, including real-time pricing, demand response and renewable energy certificate transactions; the advanced smart contract framework includes contract lifecycle management, automatic start, execution, monitoring and termination The energy storage unit also includes a thermal management system for optimizing the operating temperature of the battery and hydrogen storage unit and improving its performance and life. The energy storage unit also includes a battery management system (BMS) for real-time monitoring of the battery status, including charging and discharging status, health status and temperature, to ensure safety and efficiency. The energy storage unit also includes the following parts: a multi-mode temperature control system, which is used to automatically adjust the temperature according to environmental conditions and storage requirements, optimize storage efficiency and extend the life of the storage medium. The multi-mode temperature control system uses intelligent algorithms to predict and respond to temperature changes, and combines passive and active cooling technologies to ensure the optimal working state of the battery and hydrogen storage unit. The multi-mode temperature control system also includes a remote monitoring and diagnosis module for real-time tracking of the performance and safety status of the storage unit, supporting remote troubleshooting and maintenance planning. Specific embodiment 2:

[0057] Composition and working principle of water electrolysis device Nanoelectrodes: These electrodes use high specific surface area and optimized electrochemical activity to improve hydrogen production efficiency. Materials that may be used include metal nanoparticles (such as platinum or palladium) to provide efficient electrocatalytic performance. These electrodes are designed to maximize the surface contact of water electrolysis, thereby increasing the yield of hydrogen. Ion exchange membrane: This membrane has low resistivity and high ion selectivity, which is used to reduce energy loss during the electrolysis process while improving the purity of hydrogen and oxygen. Materials may include perfluorosulfonate membranes (such as Nafion) or other advanced synthetic polymer materials. Catalyst: Metal oxides such as iron oxide or nickel oxide are used to accelerate the water splitting reaction and reduce the required electrical energy input. Catalysts are prepared through a nanopowder processing process to ensure uniform particle size and high surface activity. Adaptive control algorithm Real-time module: Use deep neural networks to analyze and respond to climate change, energy demand fluctuations, equipment performance and market dynamics in real time. This module is capable of processing large amounts of data to achieve real-time decision support. Learning module: Integrated self-learning function to optimize system performance and efficiency by continuously analyzing historical data and real-time feedback. The algorithms used may include feedback loops and adaptive control strategies. Composite prediction model: Combines time series analysis, climate patterns, and market dynamics analysis to accurately predict short-term and long-term changes in energy demand. Predictive maintenance system sensor network: Deployed on key equipment to collect operating data such as temperature, pressure, flow, and electrochemical parameters in real time. Cloud computing platform connection: The collected data is sent to the cloud computing platform for storage, processing, and analysis. Use machine learning algorithms for fault prediction and maintenance plan optimization. System virtual replica module (digital twin technology) 3D modeling and simulation module: Used to accurately reproduce the physical properties, operating parameters, and behavioral characteristics of the actual energy system. Recommendation module: Provides energy efficiency analysis, fault prediction, and optimization recommendations based on simulation data. Interactive user interface: Allows operators to perform operation and maintenance simulations in a virtual environment. VR interface and sensory feedback mechanism VR interface: Provides intuitive 3D visual representation and interactive experience, allowing users to explore and manage energy systems in an immersive way. Sensory feedback mechanism: Enhances the realism and intuitiveness of user interaction with the system, which may include tactile, visual, and auditory feedback. Energy management platform based on blockchainBlockchain protocol: used for energy trading and data security, providing an immutable and transparent recording mechanism. Distributed ledger: records all energy production, consumption and transaction data to ensure data integrity and traceability. Smart contracts: automatically execute energy transactions, including automatic calculation of energy costs, execution of transactions and automatic settlement. Advanced smart contract frameworkContract lifecycle management: automatically start, execute, monitor and end contracts to ensure transparency and traceability. Consensus mechanism: such as proof of stake or delegated proof of stake, used to increase transaction processing speed and reduce energy consumption. Energy storage unitLithium-ion battery and solid-state hydrogen storage battery: used for efficient and stable energy storage.Thermal management system: optimizes the operating temperature of the battery and hydrogen storage unit. Battery management system (BMS): monitors the battery status, including charge and discharge status, health status and temperature. Multi-mode temperature control system intelligent algorithm: used to predict and respond to temperature changes, combining passive and active cooling technologies. Remote monitoring and diagnostic module: used to track the performance and safety status of the storage unit in real time. Specific embodiment three:

[0059] Further disclosed technical content:

[0060] The hardware of the water electrolysis device includes nanoelectrodes, ion exchange membranes, and catalysts:

[0061]

[0062]

[0063] The adaptive control algorithm includes computing units: high-performance servers or cloud computing platforms, sensor networks: temperature, pressure, flow sensors, etc.

[0064] Deep learning optimization: using loss functions (such as mean squared error MSE)

[0065]

[0066] Time series forecasting (such as using ARIMA models):

[0067] y t =c+∈ t +∑φ i y t-i +∑θ i ∈ t-i .

[0068] Predictive maintenance systems include sensors: vibration, temperature, sound sensors, etc.

[0069] Data processing unit: server or dedicated computer.

[0070] Predictive Model: Uses machine learning algorithms (Random Forest) to predict failures.

[0071] The system virtual copy module includes a graphics processing unit (GPU), a central processing unit (CPU), and data storage: a high-capacity storage system.

[0072] Simulation accuracy: Usually determined using error analysis, root mean square error (RMSE).

[0073] VR interfaces and sensory feedback mechanisms include VR helmets: including displays and sensors, and interactive controllers: for user interaction.

[0074] The blockchain-based energy management platform includes servers: used to maintain the blockchain network. Network equipment: to ensure high-speed and secure data transmission.

[0075] Blockchain consensus algorithm efficiency: usually evaluated based on block confirmation time and transaction throughput.

[0076] Energy storage units include battery cells: lithium-ion batteries or other types of high energy density batteries. Hydrogen storage systems: high pressure storage tanks or solid hydrogen storage materials.

[0077] Multi-mode temperature control system includes temperature sensor: monitors ambient and equipment temperature. Cooling system: passive or active cooling system. Temperature regulation efficiency:

[0078]

[0079] Efficient energy conversion uses nano-electrodes and special ion exchange membranes in water electrolysis devices, combined with high-efficiency catalysts, to greatly improve the efficiency and purity of hydrogen production. This technology can significantly improve the production efficiency of hydrogen energy, pave the way for large-scale application of clean energy, help reduce dependence on fossil fuels, and reduce environmental pollution.

[0080] Intelligent energy management introduces adaptive control algorithms based on deep neural networks, which can respond to environmental changes and energy demand in real time and optimize energy production and distribution strategies. Intelligent energy management not only improves energy utilization efficiency, but also responds to changing energy demand and market conditions, providing more flexible and cost-effective energy solutions.

[0081] Predictive Maintenance The integrated predictive maintenance system uses IoT technology and big data analysis to monitor key equipment in real time and prevent failures. It reduces system failures and downtime, improves the reliability and continuous operation of the overall system, and reduces maintenance costs.

[0082] Digital twin and virtual reality create a virtual copy of the system through digital twin technology, and combine with VR technology to provide an immersive interactive experience. It enables operators to conduct risk assessment and operation training in a virtual environment, improve operational safety and efficiency, and make maintenance and management decisions more accurate and intuitive.

[0083] Blockchain integration uses blockchain technology to manage energy transactions, ensuring data security, transparency and immutability. It provides a safe and reliable platform for energy transactions, improves transaction efficiency and trust, and promotes the modernization and digital transformation of the energy market.

[0084] Efficient energy storage combines high-density lithium-ion batteries and solid-state hydrogen storage technology to provide efficient and stable energy storage solutions. It provides greater flexibility and responsiveness for the system, especially during demand fluctuations and peak load periods, ensuring the stability and reliability of energy supply.

[0085] Overall, this technology creates an efficient, intelligent, reliable and environmentally friendly integrated energy system by integrating innovative materials science, advanced control algorithms, Internet of Things technology, virtual reality and blockchain and other modern technologies. This not only represents the cutting-edge development of energy technology, but also has important practical application value, including promoting the popularization of clean energy, improving the economy and sustainability of energy systems, enhancing energy security and reducing environmental pollution. This technology is of great significance in supporting the large-scale application of renewable energy, promoting the transformation and upgrading of the energy industry, and responding to the global energy crisis and climate change.

[0086] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprising a reference structure" do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0087] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The park comprehensive energy capacity optimization system based on hydrogen energy coupling is characterized by: It includes a water electrolysis device, including the following parts: A nanoelectrode having a high specific surface area and high electrochemical activity, and used to improve the efficiency of hydrogen production; Ion exchange membrane, which is a low resistivity and high ion selectivity membrane used to reduce energy loss and improve electrolysis efficiency; An adaptive control algorithm based on a deep neural network, the adaptive control algorithm includes the following parts: Real-time module: used to analyze and respond to climate change, energy demand fluctuations, equipment performance and market dynamics in real time to adjust energy production, distribution and storage strategies; Learning module: built-in data processing and model training algorithms to continuously optimize the overall performance and efficiency of the system; The predictive maintenance system based on IoT technology and big data analysis includes the following parts: Sensors deployed on the equipment, which collect equipment operation data in real time, including temperature, pressure, flow rate and electrochemical parameters; The predictive maintenance system based on Internet of Things technology and big data analysis is electrically connected to a cloud computing platform for storing, processing and analyzing collected data, and using machine learning algorithms for fault prediction and maintenance plan optimization.

2. The park comprehensive energy capacity optimization system based on hydrogen energy coupling according to claim 1 is characterized by: The water electrolysis device further comprises: The catalyst is a metal oxide and is used to accelerate the water decomposition reaction and reduce the required electrical energy input; the catalyst is prepared by a nano powder processing process.

3. The park comprehensive energy capacity optimization system based on hydrogen energy coupling according to claim 1 is characterized in that: The adaptive control algorithm based on deep neural network further includes: a composite forecasting model that combines time series analysis, climate patterns, and market dynamics analysis to accurately forecast short-term and long-term energy demand changes; Machine learning algorithms are used to automatically adjust energy allocation strategies to optimize cost-effectiveness and energy efficiency, continuously improving forecast accuracy and decision-making efficiency based on historical data and real-time feedback.

4. The park comprehensive energy capacity optimization system based on hydrogen energy coupling according to claim 1 is characterized by: The park comprehensive energy capacity optimization system based on hydrogen energy coupling further includes a system virtual copy module, and the system virtual copy module has the following parts: 3D modeling and simulation modules to accurately reproduce the physical properties, operating parameters and behavioral characteristics of actual energy systems; The suggestion module is used to integrate real-time operation data and historical performance data to simulate system performance, including energy efficiency analysis, fault prediction and optimization suggestions; An interactive user interface for operators to simulate operations and maintenance in a virtual environment to improve the safety and efficiency of actual operations.

5. The park comprehensive energy capacity optimization system based on hydrogen energy coupling according to claim 4 is characterized in that: The system virtual replica module is created using a digital twin, which further includes: VR interface for providing intuitive three-dimensional visual representation and interactive experience; The VR interface includes a sensory feedback mechanism for enhancing the realism and intuitiveness of the user's interaction with the system; The VR interface is integrated with an analysis tool that includes sensors and an interactive user interface.

6. The park comprehensive energy capacity optimization system based on hydrogen energy coupling according to claim 1 is characterized by: The park comprehensive energy capacity optimization system based on hydrogen energy coupling further includes: A blockchain-based energy management platform, wherein the blockchain-based energy management platform uses blockchain protocols for energy transactions and data security, and provides an unalterable and transparent recording mechanism; The blockchain-based energy management platform includes a distributed ledger for recording all energy production, consumption and transaction data, as well as related financial transactions, to achieve data integrity and traceability; The blockchain-based energy management platform has built-in smart contracts for automatically executing energy transactions, including automatic calculation of energy costs, transaction execution, automatic settlement and compliance verification.

7. The park comprehensive energy capacity optimization system based on hydrogen energy coupling according to claim 6 is characterized in that: The blockchain-based energy management platform includes the following parts: Consensus mechanism module, including proof of stake, delegated proof of stake, or a combination of the two, to increase transaction processing speed and reduce energy consumption; The blockchain-based energy management platform includes a smart contract verification and execution framework, which is used to adapt to different types of energy transactions and contract requirements while ensuring the security and compliance of transactions; The blockchain-based energy management platform also includes a user interface and API for allowing users to access and manage their energy transactions and contracts.

8. The park comprehensive energy capacity optimization system based on hydrogen energy coupling according to claim 7 is characterized by: The blockchain-based energy management platform further includes: An advanced smart contract framework to support multiple transaction types and conditions, including real-time pricing, demand response, and renewable energy certificate trading; The advanced smart contract framework includes contract lifecycle management, automatically starting, executing, monitoring and ending contracts, while ensuring transparency and traceability of contract execution.

9. The park comprehensive energy capacity optimization system based on hydrogen energy coupling according to any one of claims 1 to 8, characterized in that: The park comprehensive energy capacity optimization system based on hydrogen energy coupling also includes an energy storage unit: The energy storage unit uses high-density lithium-ion batteries and solid-state hydrogen storage batteries to achieve efficient and stable energy storage and rapid response capabilities; The energy storage unit also includes a thermal management system for optimizing the operating temperature of the battery and the hydrogen storage unit; The energy storage unit also includes a battery management system (BMS) for real-time monitoring of battery status, including charge and discharge status, health status and temperature.

10. The park comprehensive energy capacity optimization system based on hydrogen energy coupling according to claim 9 is characterized in that: The energy storage unit also includes the following parts: A multi-mode temperature control system for automatically adjusting the temperature according to environmental conditions and storage requirements, optimizing storage efficiency and extending the life of the storage medium; The multi-mode temperature control system uses intelligent algorithms to predict and respond to temperature changes, while combining passive and active cooling technologies to ensure optimal operating conditions for batteries and hydrogen storage units; The multi-mode temperature control system also includes a remote monitoring and diagnostic module for tracking the performance and safety status of the storage unit in real time, supporting remote troubleshooting and maintenance planning.

Images