Wind-solar-hydrogen storage integrated safety assessment and risk control system, device and method

Abstract

The invention discloses a wind, light and hydrogen storage integrated safety assessment and risk control system, device and method. The system comprises a risk perception layer, a dynamic assessment layer, an intelligent decision-making layer, a linkage control layer and a data interaction layer. The device comprises a data acquisition layer, a method scheduling layer, a weight fusion layer and a result output layer. The method comprises the steps of matching a rule engine based on input parameters, judging, screening and calling evaluation method combinations in a method library based on a threshold value, carrying out research, judgment and analysis to generate risk levels and management and control suggestions, and outputting an evaluation result. The fault and risk evolution trend can be accurately identified in an early stage, the risk identification is comprehensive, and the coverage is obviously enhanced; the evaluation cost in a low-risk scene is greatly reduced while the high evaluation precision is ensured; the scientificity and reliability of risk analysis are remarkably improved, and the balance between precision and economical efficiency is realized; a special prevention and control device and interlocking logic are configured for the core risk, single-point protection failure is avoided through cross-subsystem cooperative linkage, and the reliability of the overall safety barrier is remarkably enhanced.

Description

Technical Field

[0001] This invention relates to the field of energy storage system technology, and in particular to a wind-solar-hydrogen-storage integrated safety assessment and risk control system, device and method. Background Technology

[0002] Hydrogen energy, as a highly promising clean energy carrier, has been successfully applied on a large scale in integrated wind, solar, and hydrogen storage projects. Through mature alkaline water electrolysis technology, the unstable electrical energy generated during wind and solar power generation is efficiently converted into hydrogen energy in the form of chemical energy. Subsequently, relying on high-pressure hydrogen storage, while ensuring storage safety and density, long-term static storage of hydrogen energy is achieved, providing an important solution for improving the renewable energy consumption rate and building a stable and reliable new power system.

[0003] In the field of safety assessment for integrated wind, solar, hydrogen, and storage projects, existing technologies still have limitations in multiple dimensions. The core problem is that the technical solutions mostly rely on single or simple combinations of assessment methods for independent implementation, and each method has a clear boundary of application. They are often only used for phased and local assessments of power generation, hydrogen production, or hydrogen storage units, making it difficult to form a systematic control. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing an integrated wind, solar, hydrogen, and storage safety assessment and risk control system, device, and method.

[0005] To achieve the above objectives, in a first aspect, the present invention provides an integrated wind-solar-hydrogen-storage safety assessment and risk control system, comprising: The risk perception layer includes a multi-dimensional sensor module, a process parameter acquisition module, a material property database, a historical accident analysis module, and a three-dimensional hazard source model. It is used to collect multi-dimensional data of the energy storage system and construct a three-dimensional hazard source model, identify typical hazardous scenarios, and transmit raw data and perception data in real time. The dynamic evaluation layer includes a multi-dimensional safety evaluation module, a threshold judgment module, and a result output module. It is used to obtain input parameters and real-time data matching rules engine, intelligently filter and call evaluation method combinations in the method library, and analyze and generate risk levels and control suggestions. The intelligent decision-making layer includes a risk classification module, a data processing module, and a decision analysis module. It is used to establish risk level classification standards, combine dynamic assessment results with full life cycle management requirements to calculate and map corresponding control strategies and processing results, and issue control instructions and early warning information. The linkage control layer includes a precision prevention and control module, an execution control module, and an early warning release module. It is used to monitor the status of the energy storage system, generate control strategies, issue execution control linkage operations, monitor execution feedback signals, and simultaneously release graded early warnings. The data interaction layer includes a data storage module, a remote communication module, and a system integration output module. It is used to build real-time and historical databases, synchronize data with the project monitoring center and emergency management platform, and store system operation data, evaluation results, control records, and safety evaluation reports.

[0006] In some embodiments, the multi-dimensional sensor module is connected to the process parameter acquisition module via a data interface, the process parameter acquisition module, the material property database and the historical accident analysis module are connected to the three-dimensional hazard source model via a data interface, and the three-dimensional hazard source model is connected to the dynamic evaluation layer and the data interaction layer via a data interface.

[0007] In some embodiments, the multidimensional security evaluation module is connected to the threshold judgment module through a data interface, the threshold judgment module is connected to the result output module through a data interface, and the result output module is connected to the intelligent decision-making layer through a data interface.

[0008] In some embodiments, the risk classification module and the data processing module are connected to the decision analysis module through a data interface, and the decision analysis module is connected to the linkage control layer and the data interaction layer through a data interface.

[0009] In some embodiments, the precision prevention and control module is connected to the execution control module through a data interface, the execution control module is connected to the early warning release module through a data interface, and the early warning release module is connected to the data interaction layer through a data interface.

[0010] In some embodiments, the data storage module is connected to the remote communication module and the system integration output module through a data interface, and the data storage module is connected to the risk perception layer, the intelligent decision-making layer and the linkage control layer through the data interface.

[0011] Secondly, the present invention also provides a wind-solar-hydrogen storage integrated safety assessment and risk control device, comprising: The data acquisition layer is used to collect multi-dimensional data from the energy storage system and build a three-dimensional hazard source model, identify typical hazardous scenarios, and transmit raw data and sensing data in real time. The method scheduling layer is used to obtain input parameters and real-time data matching rules engine, intelligently filter and call the evaluation method combination in the method library, and analyze and generate risk level and control suggestions; The weighted fusion layer is used to establish risk level classification standards, combine dynamic assessment results with full life cycle management requirements to calculate and map corresponding control strategies and processing results, and issue control instructions and early warning information. The output layer is used to monitor the energy storage system status, generate control strategies, issue control linkage operations and monitor execution feedback signals, and simultaneously issue hierarchical early warnings.

[0012] Thirdly, the present invention also provides a method for safety assessment and risk control of integrated wind-solar-hydrogen storage, comprising: Get the input parameters; Based on the input parameter matching rule engine, the evaluation method combination in the method library is selected and called based on the threshold judgment. The analysis and assessment generate risk levels and control recommendations, and output evaluation results.

[0013] In some embodiments, the input parameters include hydrogen storage capacity and risk level, and the evaluation method combination includes a combination of qualitative evaluation methods, a combination of semi-quantitative evaluation methods, and a combination of quantitative evaluation methods.

[0014] In some embodiments, the combination of evaluation methods in the threshold-based filtering method library includes: If the risk level is determined to be ≤ Level 2 based on the threshold, a combination of qualitative evaluation methods should be used; If the risk level is determined to be between Level 2 and Level 3 based on a threshold, a combination of semi-quantitative evaluation methods should be used. If the risk level is determined to be ≥ Level 4 based on a threshold, a combination of quantitative evaluation methods should be used.

[0015] The present invention has the following beneficial effects: 1. This invention enables real-time continuous monitoring and comprehensive analysis of the entire process and risks of wind-solar coupled power generation, hydrogen production, and hydrogen storage through dynamic quantitative risk models and real-time data processing. It can accurately identify faults and risk evolution trends in the early stages and accurately capture typical dangerous scenarios such as hydrogen-oxygen mixing, hydrogen embrittlement cracks, and electrolyte leakage. The risk identification is comprehensive and the coverage is significantly enhanced. 2. This invention establishes a dynamic switching mechanism for evaluation methods. Based on parameters such as hydrogen storage capacity and risk level, and threshold judgments, it selects and calls combinations of evaluation methods from the method library. While ensuring high evaluation accuracy, it significantly reduces the evaluation cost in low-risk scenarios. Compared with existing single evaluation methods, the overall evaluation cost is reduced, and through a dynamically updated quantitative risk model, the scientificity and reliability of risk analysis are significantly improved, achieving a balance between accuracy and economy. 3. This invention utilizes a multi-dimensional sensor array and edge computing technology, resulting in a short hydrogen concentration detection response time and a high accuracy rate in predicting hydrogen embrittlement evolution trends. The specialized prevention and control devices and interlocking logic configured for core risks shorten the hydrogen leak response time, reduce the probability of hydrogen embrittlement failure of hydrogen storage tanks, and the cross-subsystem collaborative linkage further avoids single-point protection failures, significantly enhancing the overall reliability of the safety barrier. 4. This invention achieves full-chain linkage of risk assessment, monitoring, and response through a data interaction module, improving the efficiency of emergency drill response. It can automatically generate a safety assessment report containing a risk matrix and exposure area map, providing comprehensive situational awareness and decision-making basis for operation and management, and helping to optimize operation mode and emergency plan. At the same time, the system fully meets the regulatory requirements of "two key points and one major point", providing technical support for projects to obtain special equipment use licenses, reducing reliance on personnel experience, and improving the consistency and timeliness of safety response. 5. This invention adopts a modular design and standard interface. The algorithm model can be customized and extended according to the project scale and equipment type, adapting to wind and solar hydrogen storage projects with different technical routes, and has strong scalability. In terms of environmental and social benefits, it effectively reduces environmental risks such as hydrogen leakage and alkaline corrosion, reduces casualties and property losses caused by accidents, and lays a safe foundation for the large-scale application of hydrogen energy. Attached Figure Description

[0016] Figure 1 This is a schematic diagram illustrating the principle of the safety assessment and risk control system proposed in this invention; Figure 2 This is a schematic diagram illustrating the principle of the safety assessment and risk control device proposed in this invention; Figure 3 This is a flowchart illustrating the safety assessment and risk control method proposed in this invention. Figure 1 ; Figure 4 This is a flowchart illustrating the safety assessment and risk control method proposed in this invention. Figure 2 ; Figure 5 This is a flowchart illustrating the safety assessment and risk control method proposed in this invention. Figure 3 . Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] This application provides an integrated wind-solar-hydrogen-storage safety assessment and risk control system, device, and method, which solves the problem that existing technologies often rely on single or simple combinations of evaluation methods for independent implementation. Furthermore, these methods have clearly defined applicability boundaries and often only conduct phased or partial assessments of power generation, hydrogen production, or hydrogen storage units, making it difficult to form a systematic control capability. Specifically, firstly, there is insufficient systematic and full-process risk identification capability. Existing assessments mostly use qualitative methods such as safety checklists and HAZOP, which cannot quantify risks and often focus on single links, failing to cover the differentiated risk characteristics of the entire chain of wind and solar power generation fluctuations, electrolytic hydrogen production, and high-pressure hydrogen storage. For example, the electrical fire risk of photovoltaic power generation systems and the hydrogen embrittlement risk of high-pressure hydrogen storage systems require different evaluation logics; independent assessments directly lead to fragmented risk perception. Secondly, real-time and dynamic early warning capabilities are weak. Traditional offline or periodic assessment modes cannot effectively cope with dynamic operating conditions such as power fluctuations and equipment status changes. Key safety parameters such as hydrogen embrittlement and hydrogen leakage also lack online monitoring and rapid response mechanisms. Thirdly, quantitative analysis and precise prevention and control methods are lacking. For high-risk scenarios such as fire, explosion, and hydrogen embrittlement, there is a lack of integrated quantitative assessment models and data-driven predictive capabilities. Existing safety measures are mostly general-purpose designs, and there is a serious lack of specific prevention and control solutions for core risks such as hydrogen-oxygen mixing and seal failure. Fourth, there is a lack of linkage control. The data of safety devices in each subsystem are independent of each other, and there is a lack of a collaborative linkage mechanism based on system-level risks, which greatly reduces the timeliness, accuracy and effectiveness of overall safety management. Fifth, the construction of the safety standard system lags behind the development of technology. At present, there are no special evaluation tools and integrated management and control platforms adapted to the complex wind, solar and hydrogen storage systems, and no unified evaluation standards have been established for system coupling risks, making it difficult to support the safety assurance needs of the entire life cycle of the project.

[0019] Reference Figure 1 The present invention provides an embodiment of a wind-solar-hydrogen-storage integrated safety assessment and risk control system, comprising: a risk perception layer, a dynamic assessment layer, an intelligent decision-making layer, a linkage control layer, and a data interaction layer; It should be explained in detail that this application operates based on an integrated closed-loop logic of data perception, method matching, fusion evaluation, and linkage control: Multi-dimensional sensor arrays are deployed at key points in subsystems such as wind and solar inverters, electrolyzer inlets and outlets, hydrogen storage tank outer walls, and pipe joints. This allows for real-time acquisition of multi-source heterogeneous data such as pressure, temperature, hydrogen concentration, and acoustic emission signals. The sampling frequency is dynamically adjusted according to operating conditions. Data is transmitted to the backend via industrial Ethernet and simultaneously stored in a real-time database. The built-in intelligent matching engine presets multiple rules, combines current hydrogen storage capacity and wind and solar power fluctuations, and automatically and intelligently selects and calls the most suitable combination of one or more safety evaluation methods from the method library, analyzes and judges them to generate risk levels and management... The system provides control recommendations; subsequently, it establishes risk level grading standards, calculates and maps corresponding control strategies and processing results based on dynamic assessment results and full lifecycle management requirements, and issues control instructions and early warning information. This is achieved by driving the underlying execution mechanisms through protocols. Furthermore, the various methods invoked are executed in parallel or sequentially, and their analysis results are not output in isolation but are weighted, coupled, or logically synthesized to ultimately generate a unified, high-confidence system risk profile and quantitative level. Based on the risk conclusions output by the fusion assessment, the system automatically generates precise, tiered control instructions and directly drives the underlying SIS, DCS, power regulation systems, and other execution mechanisms through standard interfaces, achieving an automatic closed loop from risk assessment to risk control.

[0020] For example, the risk perception layer includes a multi-dimensional sensor module, a process parameter acquisition module, a material property database, a historical accident analysis module, and a three-dimensional hazard source model. It can acquire data such as electrolyzer temperature / pressure and hydrogen storage tank pressure / level in real time. By storing the physicochemical parameters and hazard levels of hazardous chemicals such as hydrogen and potassium hydroxide, as well as accident cases of similar projects, and collecting multi-dimensional data of the energy storage system and constructing a three-dimensional hazard source model, it can identify typical hazardous scenarios and transmit raw data and perception data in real time. Specifically, the multi-dimensional sensor module is connected to the process parameter acquisition module through a data interface. The process parameter acquisition module, the material property database, and the historical accident analysis module are connected to the three-dimensional hazard source model through a data interface. The three-dimensional hazard source model is connected to the dynamic assessment layer and the data interaction layer through a data interface.

[0021] Understandably, the multi-dimensional sensor module includes temperature sensors (TT), pressure sensors (PT), liquid level sensors (LT), hydrogen concentration sensors (AT), vibration sensors (VT), acoustic emission sensors (AE), hydrogen embrittlement monitoring sensors, online hydrogen and oxygen concentration analyzers, temperature / pressure transmitters, etc.: temperature sensors are used to monitor the electrolyzer and hydrogen storage tank (-20-60℃), and pressure sensors are used to monitor the electrolyzer and hydrogen storage tank; hydrogen concentration sensors are deployed in the hydrogen storage room and around the electrolyzer, acoustic emission sensors are attached to the weld seams of the hydrogen storage tank to monitor crack initiation signals, hydrogen embrittlement monitoring sensors are embedded in the metal wall of the hydrogen storage tank to collect hydrogen diffusion rates in real time, and online hydrogen and oxygen concentration analyzers are installed at the hydrogen and oxygen separation end of the electrolyzer to monitor hydrogen purity and oxygen content; the process parameter acquisition module connects to sensors, wind and solar inverters, and electrolyzer controllers through data interfaces such as RS485 to acquire multiple process parameter data such as wind and solar power generation, electrolyzer current, voltage, and hydrogen storage tank liquid level in real time and synchronize them to subsequent modules; the material property database stores basic data of various hazardous chemicals involved in the project and supports real-time retrieval and calculation of risk parameters. The historical accident analysis module integrates accident cases of similar wind, solar, hydrogen, and storage projects. It is classified according to risk type, records the causes, consequences, and handling measures of accidents, and provides case support for the three-dimensional hazard source model to avoid the recurrence of similar risks. Furthermore, the three-dimensional hazard source model is constructed based on a three-dimensional framework of energy carrier, release path, and affected object. It can effectively identify different types of typical hazardous scenarios, such as the scenario where hydrogen and oxygen mixture reaches the explosion limit after the hydrogen-oxygen separation membrane of the electrolyzer is damaged, or the scenario where hydrogen leakage from the hydrogen storage tank spreads to the distribution cabinet after hydrogen embrittlement cracks expand, causing electrical sparks to ignite, and the scenario where the electrolyte of the electrolyzer leaks due to a sudden drop in wind and solar power. The probability of occurrence of the risk scenarios is dynamically updated.

[0022] For example, the dynamic assessment layer includes a multi-dimensional safety assessment module, a threshold judgment module, and a result output module, which are used to acquire input parameters and real-time data, match the rule engine, intelligently select and call the combination of assessment methods in the method library based on input parameters such as real-time hydrogen storage capacity and risk level, comprehensively judge and couple the output results of multiple methods, and finally generate a unified and accurate risk level and control recommendations. Specifically, the multi-dimensional security evaluation module is connected to the threshold judgment module through a data interface, the threshold judgment module is connected to the result output module through a data interface, and the result output module is connected to the intelligent decision-making layer through a data interface.

[0023] Understandably, the multi-dimensional safety evaluation module integrates an evaluation method library and a matching rule engine. The evaluation method library stores various safety evaluation methods and parameters, covering different risk scenarios: the risk architecture pre-analysis method is suitable for preliminary risk screening during the project design phase; the process deviation refinement analysis targets dynamic operating conditions such as electrolyzer temperature / pressure deviations and wind and solar power fluctuations; the fire and explosion risk assessment, based on the F&EI index, calculates the fire and explosion risk of the hydrogen storage system; the multi-level barrier failure analysis analyzes the failure paths of the barrier chains of hydrogen storage tanks, valves, and pipelines through fault tree (FTA) / event tree (ETA); the analytic hierarchy process (AHP) and fuzzy mathematics method, combined with subjective weights (expert scoring) and objective weights (entropy weight method), evaluate the overall safety of the system; and the matching rule engine pre-stores multiple logical rules, filtering and matching them based on real-time parameters and risk level input parameters. Furthermore, the fusion analysis module employs a dual mechanism of weight allocation and logical verification to process results from multiple methods: the weight of each method is determined through the analytic hierarchy process (AHP), and if the deviation of a single method's result from other methods exceeds a preset value, the data source is automatically traced to exclude outliers, and a multi-dimensional assessment result of risk source, probability, and impact range is generated; the threshold judgment module sets a preset warning threshold, compares the data from the process parameter acquisition module in real time, and if the warning threshold is triggered, sends an enhanced assessment signal and an emergency preprocessing instruction to the multi-dimensional safety evaluation module to avoid assessment delays that could lead to increased risk; the result output module transforms the fusion analysis results into standardized output, including multi-level risk levels and control recommendations.

[0024] For example, the intelligent decision-making layer includes a risk classification module, a data processing module, and a decision analysis module, which are used to establish risk level classification standards, combine dynamic assessment results with full life cycle management requirements to form full-process control measures from design to maintenance, and for the first-level major hazard source of hydrogen storage system, clarify the multi-barrier protection scheme including 24-hour online monitoring, SIS interlock, explosion-proof wall and nitrogen inerting, and use edge computing to map the corresponding control strategies and processing results and issue control instructions and early warning information. Specifically, the risk classification module and the data processing module are connected to the decision analysis module through a data interface, and the decision analysis module is connected to the linkage control layer and the data interaction layer through a data interface.

[0025] Understandably, the risk grading module establishes multi-level risk grading standards, clearly defining the risk level, its scope of impact, and control priority. The data processing module uses edge computing technology to achieve real-time parameter analysis and strategy optimization, performing secondary processing on the risk data output from the dynamic assessment layer to ensure accurate decision-making. Based on historical data, it adjusts control parameters and reduces storage pressure on the data interaction layer. The decision analysis module combines dynamic assessment results with full lifecycle management requirements to generate customized control strategies and formulate multi-barrier protection schemes. Through 24-hour online monitoring of parameters such as hydrogen concentration, hydrogen embrittlement, and pressure, SIS interlocks enable automatic pressure relief and automatic leak cutoff.

[0026] For example, the linkage control layer includes a precision prevention and control module, an execution control module, and an early warning release module. It is used to monitor the status of the energy storage system to generate control strategies, drive equipment such as the electrolyzer power supply and the emergency shut-off valve of the hydrogen storage tank through the interlocking control unit, monitor the status with special protection devices such as hydrogen embrittlement monitoring sensors, and implement rapid intervention using an emergency response submodule that integrates a nitrogen inerting system and a high-pressure water mist fire extinguishing device. It issues execution control linkage operations and monitors execution feedback signals and simultaneously releases graded early warnings. Relying on DCS, SIS and other systems and their connected valves, circuit breakers and other actuators, it translates control strategies into specific operations and releases graded early warnings through audible and visual alarms, SMS notifications and other means. Specifically, the precision prevention and control module is connected to the execution control module through a data interface, the execution control module is connected to the early warning release module through a data interface, and the early warning release module is connected to the data interaction layer through a data interface.

[0027] Understandably, the precision prevention and control module generates tiered prevention and control logic based on the intelligent decision-making layer's control strategy. It drives key equipment such as the electrolyzer power supply, hydrogen storage tank emergency shut-off valve, nitrogen inerting system, and high-pressure water mist fire extinguishing device through interlocking units. It monitors the effectiveness of prevention and control measures in real time using hydrogen embrittlement monitoring sensors and hydrogen concentration sensors. It integrates emergency logic for leak sealing, fire fighting, and personnel evacuation, supporting manual / automatic switching. The execution control module translates control strategies into specific equipment operations based on the distributed control system (DCS) and safety instrumented system (SIS). The actuators include multiple sets of emergency shut-off valves, pressure relief valves, and high-pressure water mist nozzles, all with self-diagnostic fault functions. The early warning release module issues tiered early warnings according to risk levels, ensuring timely response from relevant personnel. Warning levels correspond to risk levels, and release methods include audible and visual alarms, information notifications, and system pop-ups, supporting the setting of early warning cancellation conditions.

[0028] For example, the data interaction layer includes a data storage module, a remote communication module, and a system integration output module, which are used to build real-time and historical databases, synchronize data with the project monitoring center and emergency management platform, and store system operation data, assessment results and control records, as well as a safety evaluation report containing a risk matrix, exposure area map, and rectification suggestions. It supports the docking of digital twin systems and provides standard interfaces to adapt to projects of different sizes. Specifically, the data storage module is connected to the remote communication module and the system integration output module through a data interface, and the data storage module is also connected to the risk perception layer, the intelligent decision-making layer, and the linkage control layer through a data interface.

[0029] Understandably, the data storage module constructs a real-time database and a historical database architecture to meet different data needs. The real-time database stores high-frequency data from the most recent usage period for real-time monitoring and dynamic assessment, while the historical database stores historical data, including operational data, assessment results, and management records. A backup function is also included, with backup data stored on a remote server to prevent data loss. The remote communication module achieves multi-platform data synchronization through a communication network. The project monitoring center can transmit risk assessment results and equipment status data in real time and supports remote viewing of risk heatmaps and the status of implementing agencies. The emergency management platform uploads data on major hazard sources according to regulatory requirements and supports remote access to the historical database to query equipment operating trends and assist in developing maintenance plans. Furthermore, the system integration output module automatically generates standardized reports and interfaces, supporting multi-scenario applications. Safety evaluation reports are automatically generated quarterly, including risk matrices, exposure area maps, and rectification suggestions. It can provide standard interfaces to support integration with the project's digital twin system, synchronizing risk scenarios and equipment status in real time to achieve linkage between virtual simulation and real-world management. It can also provide API interfaces for third-party systems, outputting data such as equipment maintenance records and risk handling costs to support integrated enterprise management. The module supports online preview and download of reports and automatically pushes them to relevant personnel.

[0030] It is understood that in this application: (1) Comprehensive risk identification with significantly enhanced coverage: Real-time continuous monitoring and comprehensive analysis of the entire process and risks of wind-solar coupled power generation, hydrogen production, and hydrogen storage are achieved through dynamic quantitative risk models and real-time data processing. Faults and risk evolution trends can be accurately identified in the early stage, and typical dangerous scenarios such as hydrogen-oxygen mixing, hydrogen embrittlement cracks, and electrolyte leakage can be accurately captured. (2) The evaluation system is accurate and achieves a balance between accuracy and economy: a dynamic switching mechanism for evaluation methods is established. Based on parameters such as hydrogen storage capacity and risk level, and threshold judgment, the combination of evaluation methods in the method library is selected and called. While ensuring high evaluation accuracy, the evaluation cost in low-risk scenarios is greatly reduced. Compared with the existing single evaluation method, the comprehensive evaluation cost is reduced, and the scientificity and reliability of risk analysis are significantly improved through the dynamically updated quantitative risk model. (3) High efficiency in prevention and control response and significant improvement in intrinsic safety level: With the help of multi-dimensional sensor array and edge computing technology, the hydrogen concentration detection response time is short and the prediction accuracy of hydrogen embrittlement evolution trend is high. The special prevention and control devices and interlocking logic configured for core risks shorten the hydrogen leakage response time, reduce the probability of hydrogen embrittlement failure of hydrogen storage tank, and cross-subsystem collaborative linkage further avoids single-point protection failure, and the overall safety barrier reliability is significantly enhanced. (4) Strong management collaboration, meeting regulatory and practical needs: Through the data interaction module, the entire chain of risk assessment, monitoring and disposal is linked, the emergency response efficiency is improved, and a safety evaluation report containing risk matrix and exposure area map can be automatically generated, providing comprehensive situational awareness and decision-making basis for operation and management, and helping to optimize operation mode and emergency plan; at the same time, the system fully meets the regulatory requirements of "two key points and one major point", providing technical support for projects to obtain special equipment use licenses, reducing the dependence on personnel experience, and improving the consistency and timeliness of safety response; (5) Outstanding adaptability and social benefits: The modular design and standard interface allow the algorithm model to be customized and extended according to the project scale and equipment type, adapting to wind and solar hydrogen storage projects with different technical routes, and has strong scalability; in terms of environmental and social benefits, it effectively reduces environmental risks such as hydrogen leakage and alkaline corrosion, reduces casualties and property losses caused by accidents, and lays a safe foundation for the large-scale application of hydrogen energy.

[0031] Reference Figure 2 The present invention also provides an embodiment of a wind-solar-hydrogen storage integrated safety assessment and risk control device, comprising: The data acquisition layer is used to collect multi-dimensional data from the energy storage system and build a three-dimensional hazard source model, identify typical hazardous scenarios, and transmit raw data and sensing data in real time. The method scheduling layer is used to obtain input parameters and real-time data matching rules engine, intelligently filter and call the evaluation method combination in the method library, and analyze and generate risk level and control suggestions; The weighted fusion layer is used to establish risk level classification standards, combine dynamic assessment results with full life cycle management requirements to calculate and map corresponding control strategies and processing results, and issue control instructions and early warning information. The output layer is used to monitor the energy storage system status, generate control strategies, issue control linkage operations and monitor execution feedback signals, and simultaneously issue hierarchical early warnings.

[0032] Understandably, a four-layer architecture—data acquisition, method scheduling, weight fusion, and result output—is adopted to achieve a closed-loop process from multi-source data perception to intelligent risk management. The data acquisition layer utilizes multi-dimensional sensor arrays deployed in subsystems such as wind and solar power generation, electrolytic hydrogen production, and high-pressure hydrogen storage to collect heterogeneous data in real time, including power fluctuations, electrolyte parameters, and hydrogen storage tank structural stress. Furthermore, relying on 3D modeling technology for energy carriers, release paths, and affected objects, a three-dimensional model is constructed to include typical hazardous scenarios such as hydrogen-oxygen mixing, hydrogen embrittlement cracking, and electrical short circuits. The hazard source model transmits raw data and scenario-based perception data to the next level in real time. The method scheduling layer is equipped with an intelligent rule engine and a multi-method evaluation library, which includes various methods such as risk architecture pre-analysis, process deviation fine analysis, safety checklist, analytic hierarchy process, fuzzy mathematics, fire and explosion risk assessment, multi-level barrier failure analysis, operating condition risk assessment, and process unit risk index classification. Based on input parameters such as hydrogen storage capacity and risk prediction, it dynamically matches appropriate evaluation method combinations, and generates quantitative risk levels and preliminary control suggestions through parallel or serial computation and analysis. Furthermore, the weight fusion layer establishes a multi-level risk classification standard. Combining dynamic assessment results with the requirements of project lifecycle management, it calculates the weight of each risk factor through AHP weight calculation, entropy weight correction, fuzzy comprehensive evaluation, and risk level determination, mapping precise control strategies and issuing control instructions and early warning information to the execution end. The result output layer monitors the operating status of the energy storage system in real time, transforms the control strategies into specific control logic, and drives the DCS, SIS, and other systems to perform linked operations such as emergency shutdown of the electrolyzer and closure of the hydrogen storage tank shut-off valve. At the same time, it collects execution feedback signals and releases graded early warnings through various means such as audible and visual alarms, information push, and platform alarms, ultimately forming a complete closed loop of data collection, method adaptation, strategy generation, and execution feedback.

[0033] Reference Figures 3-5 The present invention also provides an embodiment of a method for safety assessment and risk control of integrated wind-solar-hydrogen storage, comprising: S100, Obtain input parameters; S200 is an input parameter matching rule engine that uses threshold judgment to filter and call the evaluation method combination in the method library. S300 analyzes and assesses risks to generate risk levels and control recommendations, and outputs evaluation results.

[0034] Input parameters include hydrogen storage capacity and risk level, and the evaluation method combination includes a combination of qualitative evaluation methods, a combination of semi-quantitative evaluation methods, and a combination of quantitative evaluation methods.

[0035] Please continue reading. Figure 4In this implementation, the combination of evaluation methods in the method library for threshold-based selection in S200 includes: S210A: If the risk level is determined to be ≤ Level 2 based on the threshold, a combination of qualitative evaluation methods shall be used. S210B, if the risk level is determined to be between level 2 and level 3 based on a threshold, a combination of semi-quantitative evaluation methods shall be used. S210C, if the risk level is determined to be ≥ Level 4 based on the threshold, a combination of quantitative evaluation methods shall be adopted.

[0036] Example 1: This embodiment is based on a 30MW wind-solar-hydrogen storage integrated demonstration project, configured with a 150kg high-pressure hydrogen storage system and 12 alkaline electrolyzers. The installed wind and solar power includes 20MW of wind power and 10MW of photovoltaic power. The hydrogen storage pressure is 30-45MPa, and the wind and solar power generation power fluctuates dynamically by ±6MW, which can easily lead to a chain of risks such as electrolyzer load imbalance and hydrogen storage system pressure fluctuation. The system execution process includes: (1) Data perception and method matching: The system captures the amount of hydrogen stored and the power of wind and solar power generation in real time through a multi-dimensional sensor array deployed on the top of the hydrogen storage tank and at the inlet and outlet of the electrolyzer. When the amount of hydrogen stored reaches 150kg, exceeding the threshold of 100kg, the built-in intelligent rule engine triggers the preset logic: IF hydrogen storage > 100kg THEN call the quantitative method, automatically generate method combination instructions and then conduct a special assessment of fire and explosion risk and multi-level barrier failure analysis. At the same time, due to the monitoring data of wind and solar power fluctuation exceeding ±5MW, the system triggers the additional rule to automatically generate method combination instructions and then comprehensively evaluates and analyzes the system stability through the hierarchical analysis method and fuzzy mathematics method. Thus, the system automatically configures a fusion analysis task of multiple methods for the current scenario. (2) Evaluation method integration analysis: The fire and explosion risk assessment calculation receives real-time pressure data of 32MPa and ambient temperature of 25℃ from the hydrogen storage tank. Based on the electrochemical fire and explosion index (F&EI) model, the initial F&EI is 73.92, corresponding to a significant hazard level. After the system automatically calls the compensation measures parameters and recalculates, the F&EI drops to 34.74, corresponding to a comparative hazard level. It is preliminarily determined that the overall risk of the hydrogen storage system is controllable. Multi-level barrier failure analysis is initiated in parallel with fault tree analysis (FTA). Taking the hydrogen storage tank leakage as the top event, the analysis is conducted on the hydrogen storage tank body, high-pressure hose and valve. Combined with the hose vibration data collected by the acoustic emission sensor and historical operation and maintenance records, the high pressure is quantitatively analyzed to obtain the results. Hose aging is a critical weak point, with a failure probability exceeding the preset value. A multi-level evaluation index system was constructed, including wind and solar power fluctuations, hydrogen storage pressure stability, and equipment health status. The weights were determined by combining expert scoring with the entropy weight method. The final comprehensive safety score of the system was calculated to be 82.4, corresponding to a level II controllable risk. The above results were coupled and analyzed. Although the fire and explosion risk assessment showed that the overall risk was controllable, the multi-level barrier failure analysis identified high-pressure hose aging as a high-probability failure path and did not fully consider the interlocking effect of component-level risks. Through weight correction and logical verification mechanisms, the optimistic conclusion of a single method was rejected. Finally, it was determined that the system is currently in a high-risk state, and the core risk source is the high-pressure hose assembly. (3) Risk decision-making and joint prevention and control: The system immediately triggers an orange warning, which is displayed in a bright red pop-up window on the large screen of the project monitoring center, and sends an information warning containing risk source location and disposal suggestions to the operation and maintenance manager and safety officer; and automatically executes the preset multi-level prevention and control logic: the first-level linkage is to automatically increase the sampling frequency of the hydrogen concentration sensor in the hydrogen storage room and simultaneously pre-start the nitrogen purging system to control the risk of leakage and diffusion at the initial stage; the second-level linkage is a condition trigger. If the hydrogen concentration is detected to be >0.8%LEL or the hose crack propagation is accelerated, the system will perform an emergency shutdown operation, cut off the pneumatic valves at the inlet and outlet of the hydrogen storage tank, and start full-flow nitrogen purging; the system automatically generates an emergency maintenance work order, which clearly requires the immediate maintenance of the high-pressure hose with a specific number.

[0037] This embodiment overcomes the limitations of single evaluation methods by intelligently combining fire and explosion risk assessment, multi-level barrier failure analysis, and hierarchical-fuzzy mathematics comprehensive assessment. It accurately identifies the hidden danger of high-pressure hose aging, which cannot be identified by isolated analysis, thus achieving comprehensive risk identification. The fusion analysis, through the coupling of quantitative data and qualitative logic, corrects the bias of single methods and effectively improves the assessment accuracy. Based on the hierarchical prevention and control logic of multi-method fusion, it realizes an automated closed loop of early warning, linkage, and maintenance.

[0038] Example 2: This embodiment is based on the safety management scenario of the electrolyzer in a 10MW distributed photovoltaic hydrogen production project. It configures six 500Nm³ / h alkaline electrolyzers, each equipped with a 3m³ low-pressure hydrogen buffer tank. The design pressure is 1.6MPa, and the hydrogen buffer capacity is ≤5m³. This is a small-scale hydrogen production system. The system execution process includes: (1) Deviation identification and method matching: Temperature data is collected in real time by temperature sensors deployed in the electrolytic cell. When the temperature of an electrolytic cell exceeds the 90℃ safety threshold, the MORE temperature process deviation warning is triggered. The built-in intelligent rule engine triggers the preset logic IF hydrogen buffer ≤ 5m³ THEN to call the qualitative method. After automatically generating the method combination instruction, it is controlled by the process deviation refinement analysis and safety checklist. (2) Analysis and decision-making: The process deviation fine analysis receives real-time data such as electrolytic cell temperature, cooling water inlet flow rate, and rectifier cabinet output current to analyze the cause of deviation. For example, insufficient cooling water flow leads to a decrease in heat dissipation efficiency and an increase in electrolytic cell temperature, which in turn increases electrode overpotential and further aggravates heat generation. At the same time, historical operating data is called to verify the pattern; the safety checklist automatically triggers relevant inspection items and marks relevant inspection abnormalities. (3) Multi-level linkage control: Automatically executes preset multi-level prevention and control logic. The first level of control is rapid adjustment. The system sends a coordinated command to the photovoltaic inverter or rectifier cabinet through the linkage interface, so that the photovoltaic inverter reduces the output power and the rectifier cabinet reduces the current of the electrolyzer and reduces the heat generated by the electrolysis reaction. The second level of interlock is emergency handling. If the temperature still does not drop below the preset value, the system automatically triggers the SIS system emergency shutdown, closes the hydrogen outlet valve and the electrolyte circulation valve, opens the tank vent valve, and triggers the sound and light alarm.

[0039] This embodiment adaptively selects a more economical and efficient combination of qualitative methods based on the project size (buffer capacity), which not only meets the needs of risk analysis but also reduces the calculation cost of a single assessment, adapts to the cost control requirements of small-scale projects, and realizes an automated closed loop from analysis to control.

[0040] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A wind-solar-hydrogen storage integrated safety assessment and risk control system, characterized in that, Comprise: The risk perception layer includes a multi-dimensional sensor module, a process parameter acquisition module, a material property database, a historical accident analysis module and a three-dimensional hazard source model, which is used to collect multi-dimensional data of energy storage system and construct three-dimensional hazard source model, identify typical dangerous scene and real-time transmission of original data and perception data; The dynamic evaluation layer includes a multi-dimensional safety evaluation module, a threshold judgment module and a result output module, which is used to obtain input parameters and real-time data matching rule engine, intelligently screen and call evaluation method combination in method library and generate risk level and control suggestion through research and analysis; The intelligent decision-making layer includes a risk grading module, a data processing module and a decision analysis module, which is used to establish risk level grading standard, calculate corresponding control strategy and processing result combined with dynamic evaluation result and whole life cycle management requirement and issue control instruction and early warning information; The linkage control layer includes a precise prevention and control module, an execution control module and an early warning release module, which is used to monitor energy storage system state to generate control strategy, issue execution control linkage operation and monitor execution feedback signal and synchronously release hierarchical early warning; The data interaction layer includes a data storage module, a remote communication module and a system integration output module, which is used to construct real-time and historical database, synchronize data with project monitoring center and emergency management platform and store system running data, evaluation result and control record and safety evaluation report.

2. The wind-solar-hydrogen storage integrated safety assessment and risk control system according to claim 1, characterized in that, The multi-dimensional sensor module is connected with the process parameter acquisition module through a data interface, the process parameter acquisition module, the material property database and the historical accident analysis module are connected with the three-dimensional hazard source model through a data interface, and the three-dimensional hazard source model is connected with the dynamic evaluation layer and the data interaction layer through a data interface.

3. The wind-solar-hydrogen storage integrated safety assessment and risk control system according to claim 1, characterized in that, The multi-dimensional safety evaluation module is connected with the threshold judgment module through a data interface, the threshold judgment module is connected with the result output module through a data interface, and the result output module is connected with the intelligent decision-making layer through a data interface.

4. The wind-solar-hydrogen storage integrated safety assessment and risk control system according to claim 1, characterized in that, The risk grading module and the data processing module are connected with the decision analysis module through a data interface, and the decision analysis module is connected with the linkage control layer and the data interaction layer through a data interface.

5. The wind-solar-hydrogen storage integrated safety assessment and risk control system according to claim 1, characterized in that, The precise prevention and control module is connected with the execution control module through a data interface, the execution control module is connected with the early warning release module through a data interface, and the early warning release module is connected with the data interaction layer through a data interface.

6. The wind-solar-hydrogen storage integrated safety assessment and risk control system according to claim 1, characterized in that, The data storage module is connected with the remote communication module and the system integration output module through a data interface, and the data storage module is connected with the risk perception layer, the intelligent decision-making layer and the linkage control layer through a data interface.

7. A wind-solar-hydrogen storage integrated safety assessment and risk control device, characterized in that, Comprise: The data acquisition layer is used to collect multi-dimensional data of energy storage system and construct three-dimensional hazard source model, identify typical dangerous scene and real-time transmission of original data and perception data; The method scheduling layer is used to obtain input parameters and real-time data matching rule engine, intelligently screen and call evaluation method combination in method library and generate risk level and control suggestion through research and analysis; The weight fusion layer is used to establish risk level grading standard, calculate corresponding control strategy and processing result combined with dynamic evaluation result and whole life cycle management requirement and issue control instruction and early warning information; The weight fusion layer is used to establish risk level grading standard, calculate corresponding control strategy and processing result combined with dynamic evaluation result and whole life cycle management requirement and issue control instruction and early warning information; An output layer for monitoring the state of the energy storage system to generate a control strategy, issue an execution control linkage operation, monitor an execution feedback signal, and synchronously issue a hierarchical early warning.

8. A wind-solar-hydrogen storage integrated safety assessment and risk control method, characterized in that, The method comprises the following steps: acquiring input parameters; matching a rule engine based on the input parameters, judging and screening an evaluation method combination in a method library based on a threshold value; analyzing and judging a risk level and a control suggestion to generate an evaluation result.

9. The wind-solar-hydrogen storage integrated safety assessment and risk control method according to claim 8, characterized in that, The input parameters include hydrogen storage capacity and risk level, and the evaluation method combination includes a qualitative evaluation method combination, a semi-quantitative evaluation method combination, and a quantitative evaluation method combination.

10. The wind-solar-hydrogen storage integrated safety assessment and risk control method according to claim 8, characterized in that, The step of judging and screening the evaluation method combination in the method library based on the threshold value comprises the following steps: if the risk level is determined to be less than or equal to secondary risk based on the threshold value, the qualitative evaluation method combination is adopted; if secondary risk is determined to be less than the risk level and the risk level is determined to be less than or equal to tertiary risk based on the threshold value, the semi-quantitative evaluation method combination is adopted; if the risk level is determined to be greater than or equal to quaternary risk based on the threshold value, the quantitative evaluation method combination is adopted.

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