Energy storage system safety monitoring and control system for comprehensive energy station

Abstract

The invention discloses an energy storage system safety monitoring and control system for a comprehensive energy station, and relates to the technical field of system safety monitoring. In order to solve the technical problems of battery thermal runaway, low intelligent degree and insufficient integrated management of the application of the existing energy storage system in a micro-grid in the prior art, the invention provides the technical scheme that the energy storage system safety monitoring and control system for the comprehensive energy station. The system comprises an operation monitoring and integrated management module which is used for monitoring power input and output of an energy storage system, power grid interaction parameters, capacity and energy utilization rate; the safety monitoring and early warning module is used for monitoring preset parameters in the energy storage equipment and in the operation environment; and the data analysis and optimization control module is used for acquiring data of operation parameters of the load system and carrying out scheduling and optimization control on load behaviors of the load system according to real-time data. The method is suitable for safety monitoring and control of an energy storage system of a comprehensive energy station.

Description

Technical Field

[0001] The present invention relates to the technical field of system safety monitoring, and specifically to the safety monitoring and control of energy storage systems in integrated energy stations. Background Art

[0002] In integrated energy stations, energy storage systems are an important component to ensure a stable supply of electricity. With the rapid development of renewable energy, the role of energy storage systems in power systems is becoming increasingly important, especially in balancing supply and demand, stabilizing the power grid, and improving energy utilization. However, existing energy storage systems still face many technical bottlenecks and challenges.

[0003] At present, the research on energy storage systems is mainly focused on improving battery energy density, extending battery life, and improving system safety and reliability. Common energy storage technologies include lithium-ion batteries, sodium-sulfur batteries, all-vanadium flow batteries, superconducting energy storage, flywheel energy storage, etc. Among them, lithium-ion batteries have become the mainstream choice due to their high energy density and efficiency. However, lithium-ion batteries also have the risk of thermal runaway, especially under high-rate charging and discharging and extreme environmental conditions, which may cause the internal temperature of the battery to rise sharply, causing thermal runaway and fire accidents.

[0004] For example, in actual applications, some large energy storage power stations have experienced major fire accidents caused by battery thermal runaway, which not only caused equipment damage and economic losses, but also posed a threat to the surrounding environment and personnel safety. To solve this problem, researchers have tried to reduce the risk of thermal runaway by improving battery materials, adding cooling systems, and optimizing battery management systems (BMS), but these methods still face technical complexity and high costs in practical applications.

[0005] In addition, with the popularization of microgrids and distributed energy, energy storage systems are gradually integrated into distributed energy networks and participate in the regulation of power supply and demand. However, the application of existing energy storage systems in microgrids faces the problem of insufficient intelligent scheduling and is difficult to adapt to complex and changing load demands. For example, traditional scheduling methods rely on fixed rules or experience and lack the ability to dynamically analyze real-time data and make intelligent decisions, which limits the economy and reliability of energy storage systems.

[0006] The technical problems existing in the prior art are:

[0007] 1. Battery thermal runaway: The battery of the energy storage system may experience thermal runaway during the charging and discharging process, leading to fire accidents. The causes of thermal runaway include internal equipment failures, changes in external environmental conditions, and improper operation. Existing improvement measures, such as adding a cooling system or optimizing the BMS, have some effects, but they are insufficient in terms of high cost and complexity.

[0008] 2. Low intelligence: The existing energy storage system lacks intelligence in dispatching and operating control in microgrids, various operating data are not integrated and managed, fault warnings are not timely, and potential risks are difficult to detect in time. Traditional dispatching methods cannot effectively adapt to complex load changes, which affects the system's responsiveness and economy.

[0009] 3. Insufficient integrated management: The monitoring data of the energy storage system is scattered and difficult to manage and analyze in a unified manner, which makes it difficult to effectively ensure the efficiency and safety of the system. Due to the lack of a unified monitoring and management platform, the operating status of the equipment cannot be fully monitored, which increases the difficulty of system maintenance. Summary of the invention

[0010] In order to solve the technical problems existing in the prior art, the application of the existing energy storage system in the microgrid faces battery thermal runaway, low intelligence and insufficient integrated management, the technical solution provided by the present invention is:

[0011] A safety monitoring and control system for an energy storage system of an integrated energy station, the system comprising:

[0012] Operation monitoring and integrated management module, used to monitor the power input and output of the energy storage system, grid interaction parameters, capacity and energy utilization;

[0013] The safety monitoring and early warning module is used to monitor the preset parameters inside the energy storage device and in the operating environment;

[0014] The data analysis and optimization control module is used for data collection of load system operating parameters, and for scheduling and optimizing the load behavior of the load system based on real-time data.

[0015] Furthermore, a preferred embodiment is provided, in which the operation monitoring and integrated management module includes a monitoring device for the power input and output of the energy storage system, grid interaction parameters, capacity and energy utilization, and a display device for summarizing and displaying the data model of the energy storage system.

[0016] Further, a preferred embodiment is provided, the safety monitoring and early warning module includes temperature, pressure and electrical safety monitoring devices, monitoring preset parameters inside the energy storage device and in the operating environment;

[0017] Furthermore, a preferred implementation is provided, wherein the safety monitoring and early warning module is also used to set a multi-level early warning strategy, and to provide emergency prompts or treatment measures for abnormal situations according to different preset risk levels.

[0018] Furthermore, a preferred embodiment is provided, in which the data analysis and optimization control module includes a data acquisition device for load system operating parameters, and a prediction device for predicting future load demand in combination with historical load data.

[0019] Furthermore, a preferred embodiment is provided, which also includes a fault detection and emergency response module, including a fault detection device for analyzing the operating failure mode of the load system, identifying potential faults by comparing with a failure mode library, and initiating emergency treatment measures and remotely controlled emergency response devices.

[0020] Based on the same inventive concept, the present invention also provides a method for safety detection and control of an energy storage system for an integrated energy station. The method is implemented based on the system, and includes:

[0021] Steps for monitoring energy storage system power input and output, grid interaction parameters, capacity and energy utilization;

[0022] Steps for monitoring preset parameters within the energy storage device and in the operating environment;

[0023] The steps of collecting data on the operating parameters of the load system and scheduling and optimizing the load behavior of the load system based on real-time data.

[0024] Based on the same inventive concept, the present invention also provides a computer storage medium for storing a computer program, and when the computer reads the computer program, the computer executes the described method.

[0025] Based on the same inventive concept, the present invention also provides a computer, including a processor and a storage medium. When the processor reads a computer program stored in the storage medium, the computer executes the method described.

[0026] Based on the same inventive concept, the present invention also provides a computer program product, which is a computer program. When the computer program is executed, the method described above is implemented.

[0027] Compared with the prior art, the technical solution provided by the present invention is beneficial in that:

[0028] The present invention manages the energy storage system in a unified manner through a highly integrated platform, integrating operation data, fault information, safety monitoring, etc. into the same platform, improving management efficiency and reducing management complexity. Compared with the existing decentralized management method, this integrated management method significantly reduces the management difficulty and improves the stability of system operation.

[0029] The use of high-precision 3D data models to dynamically display the operation status allows managers to intuitively understand the health status and operation of the energy storage system. This method significantly improves the efficiency of operation management and safety maintenance, especially in the management of complex systems. 3D visualization provides great convenience for equipment operation and reduces the possibility of human misjudgment.

[0030] Through the mining and analysis of historical data, the system can formulate reasonable load forecasting and energy storage scheduling strategies. This intelligent forecasting and optimized scheduling significantly improves the economic efficiency of the system, especially in the peak and valley regulation of electricity. Through intelligent scheduling, the energy storage utilization is maximized, the electricity cost is reduced, and the return on investment of the energy storage system is improved.

[0031] Combining the multi-level safety monitoring of equipment internal safety parameters, electrical safety and environmental parameters, a comprehensive safety protection system has been built. This multi-level safety protection can effectively avoid accidents caused by equipment failure or external environmental factors. Compared with a single monitoring method, the safety is significantly improved, making the system more reliable during operation.

[0032] The intelligent emergency response mechanism can quickly initiate emergency measures when abnormal conditions are detected to ensure the stable operation of the system. Compared with traditional manual processing methods, the intelligent emergency response mechanism not only shortens the response time, but also greatly reduces the impact of system failures on the power grid and equipment, ensuring the safety of the system in various extreme situations.

[0033] The present invention uses automated fault repair and remote control technology to reduce the need for manual intervention and support unattended operation. Compared with the existing operation and maintenance methods that require a large amount of manual participation, this automation and remote maintenance significantly reduces the operation and maintenance costs and has important application value in remote or dangerous environments.

[0034] The system can be flexibly adjusted according to the needs of the power grid, and the economic benefits of the system can be improved by the peak-shaving and valley-filling function, while enhancing the stability of the power grid. Compared with the traditional fixed adjustment method, this demand response and intelligent adjustment can better adapt to the changes in power grid load, and enhance the importance and flexibility of energy storage systems in power dispatching.

[0035] It is suitable for use in the safety monitoring and control of energy storage systems in integrated energy stations. DETAILED DESCRIPTION

[0036] In order to make the benefits of the technical solution provided by the present invention more clearly reflected, the technical solution provided by the present invention is further described in detail below through specific implementation methods, specifically:

[0037] Embodiment 1: This embodiment provides a safety monitoring and control system for an energy storage system of a comprehensive energy station, the system comprising:

[0038] Operation monitoring and integrated management module, used to monitor the power input and output of the energy storage system, grid interaction parameters, capacity and energy utilization;

[0039] The safety monitoring and early warning module is used to monitor the preset parameters inside the energy storage device and in the operating environment;

[0040] The data analysis and optimization control module is used for data collection of load system operating parameters, and for scheduling and optimizing the load behavior of the load system based on real-time data.

[0041] Specifically, this embodiment aims to solve the following problems in the prior art through an integrated comprehensive energy station energy storage system safety detection method and early warning system:

[0042] Improve the safety of energy storage systems and reduce the risk of battery thermal runaway.

[0043] Improve the intelligence level of scheduling, use real-time data for dynamic analysis and optimized control, and meet complex and changing load demands.

[0044] Realize integrated management of energy storage systems, improve data visualization and management efficiency, and reduce the complexity of system maintenance.

[0045] This embodiment involves a safety detection method and early warning system for an integrated energy station energy storage system, which aims to solve problems such as battery thermal runaway and low intelligent dispatching in existing energy storage systems. Through integrated safety monitoring and intelligent control systems, the safety and economy of energy storage system operation are improved.

[0046] include:

[0047] Integrated comprehensive energy station backup system:

[0048] It includes operation monitoring and integrated management systems to ensure real-time monitoring of the energy storage system's power input and output, grid interaction, capacity utilization, etc.

[0049] The three-dimensional data model is used to display the system operation status and provide visual information support for managers.

[0050] Multi-level safety monitoring and early warning system:

[0051] Includes temperature and pressure monitoring systems to ensure the equipment is operating within safe parameters.

[0052] Electrical safety monitoring systems, such as grounding and insulation status monitoring points, to ensure electrical safety.

[0053] Environmental parameter monitoring: monitor the temperature and humidity in the system operating environment to avoid the impact of the external environment on the energy storage system.

[0054] Scheduling standardization and optimization control:

[0055] Collect operating parameters through the data acquisition and analysis system and formulate reasonable backup scheduling strategies.

[0056] Use historical load data to predict future load demand and adjust load strategies accordingly.

[0057] The application of intelligent optimization algorithms uses machine learning and optimization algorithms to intelligently analyze and optimize the operating mode of the storage system.

[0058] Fault detection and emergency response mechanism:

[0059] Establish a failure mode library through failure analysis modes to identify potential risks.

[0060] The intelligent emergency handling mechanism automatically initiates emergency measures, such as reducing power or switching to backup power, when an abnormal situation is detected, to ensure stable operation of the system.

[0061] Remote control and automated maintenance support remote monitoring and fault repair, reduce manual support, and ensure continuous system operation.

[0062] Implementation method 2. This implementation method is a further limitation of the energy storage system safety detection and control system for an integrated energy station provided in implementation method 1. The operation monitoring and integrated management module includes a monitoring device for the power input and output, grid interaction parameters, capacity and energy utilization of the energy storage system, and a display device for summarizing and displaying the data model of the energy storage system.

[0063] Embodiment 3: This embodiment further limits the energy storage system safety detection and control system for a comprehensive energy station provided in Embodiment 1. The safety detection and early warning module includes temperature, pressure and electrical safety monitoring devices, and monitors preset parameters inside the energy storage device and in the operating environment;

[0064] Implementation method 4. This implementation method is a further limitation of the energy storage system safety detection and control system for a comprehensive energy station provided in implementation method 1. The safety detection and early warning module is also used to set a multi-level early warning strategy to provide emergency prompts or treatment measures for abnormal situations according to different preset risk levels.

[0065] Implementation method five: This implementation method further limits the energy storage system safety detection and control system for a comprehensive energy station provided in implementation method one. The data analysis and optimization control module includes a data acquisition device for load system operating parameters and a prediction device for predicting future load demand based on historical load data.

[0066] Implementation method six. This implementation method is a further limitation of the energy storage system safety detection and control system for an integrated energy station provided in implementation method one, and also includes a fault detection and emergency response module, including a fault detection device that analyzes the operating failure mode of the load system, identifies potential faults by comparing with a failure mode library, and initiates emergency treatment measures and remotely controlled emergency response devices.

[0067] Embodiment 7: This embodiment provides a method for safety detection and control of an energy storage system for an integrated energy station. The method is implemented based on the system provided in embodiment 1, and includes:

[0068] Steps for monitoring energy storage system power input and output, grid interaction parameters, capacity and energy utilization;

[0069] Steps for monitoring preset parameters within the energy storage device and in the operating environment;

[0070] The steps of collecting data on the operating parameters of the load system and scheduling and optimizing the load behavior of the load system based on real-time data.

[0071] The steps to implement the program are:

[0072] 1. System installation and hardware configuration: Install high-precision sensors to collect key parameters such as temperature, pressure, and current, and connect the sensors to the data acquisition system to ensure accurate collection of various monitoring data.

[0073] 2. Data integration and modeling: Build an integrated data management platform and use three-dimensional data modeling tools to visualize, integrate and model various types of data of the energy storage system to form a digital twin of the system.

[0074] 3. Algorithm development and system debugging: Based on load data and equipment operating parameters, develop prediction algorithms and optimization scheduling algorithms, and debug the energy storage system multiple times to ensure the stability and accuracy of the system.

[0075] 4. Operation monitoring and data analysis: After the system is put into operation, the platform will monitor various types of data in real time, analyze equipment status, identify potential risks in a timely manner, and make corresponding scheduling adjustments and optimizations.

[0076] 5. Emergency response and system maintenance: When the system detects an abnormality, it automatically executes emergency response measures and maintains the equipment through remote control functions to ensure the safe and reliable operation of the system.

[0077] 6. Automated optimization and continuous improvement: During operation, the system continuously collects data and optimizes analysis, and improves the overall operating efficiency and reliability of the energy storage system by continuously improving the control strategy.

[0078] Through this implementation, the integrated energy station energy storage system achieves all-round management from operation monitoring, data analysis to safety warning and intelligent scheduling. The integrated management platform and intelligent control system make the energy storage system operation safer and more efficient, reduce the risk of equipment failure, and improve the economy of the system by optimizing the scheduling strategy and extend the service life of the battery. At the same time, the intelligent emergency handling and remote control functions also lay the foundation for the unattended operation mode in the future, providing strong support for the sustainable development of the integrated energy station.

[0079] Embodiment 8: This embodiment provides a computer storage medium for storing a computer program. When the computer reads the computer program, the computer executes the method provided in embodiment 7.

[0080] Embodiment 9: This embodiment provides a computer, including a processor and a storage medium. When the processor reads a computer program stored in the storage medium, the computer executes the method provided in embodiment 7.

[0081] Embodiment 10: This embodiment provides a computer program product, which is a computer program. When the computer program is executed, the method provided in embodiment 7 is implemented.

[0082] Implementation eleven: This implementation further describes the above technical solution in detail through specific examples, specifically:

[0083] This embodiment proposes an integrated comprehensive energy station energy storage system safety detection method and early warning system, which mainly includes the following aspects:

[0084] Operation monitoring and integrated management of energy storage systems

[0085] 1. Power input and output monitoring: Real-time monitoring of the power flow of the energy storage system, including power input and output during charging and discharging, to ensure that the energy storage system maintains efficient operation between load demand and power balance.

[0086] 2. Grid interaction monitoring: Monitor the interaction between the energy storage system and the grid, including grid frequency, voltage and other parameters, to ensure the system’s responsiveness and stability to the grid.

[0087] 3. Capacity and energy utilization monitoring: Monitor and analyze the capacity and energy utilization of the energy storage system to provide an overall assessment of the system's operating status, thereby optimizing energy distribution.

[0088] 4. Three-dimensional data model display: By summarizing and displaying various types of energy storage system data through high-precision three-dimensional models, managers can understand the health status and operation of the system in real time to make quick decisions.

[0089] 5. Energy type and consumption data monitoring: Monitor the energy type and source consumed by the energy storage system to ensure the rational use and distribution of energy, so as to achieve the optimal configuration of the energy system and the efficient use of green energy.

[0090] Energy storage system safety monitoring and early warning system

[0091] 1. Temperature and pressure monitoring: Real-time monitoring of key safety parameters such as temperature and pressure of energy storage equipment, detection of abnormal conditions inside the equipment, and timely measures to avoid equipment failure.

[0092] 2. Electrical safety monitoring: Monitor the electrical safety of the energy storage system, including key indicators such as grounding and insulation, to ensure that the equipment is in a safe operating state.

[0093] 3. Environmental parameter monitoring: Monitor the temperature, humidity, etc. in the system operating environment to ensure that the energy storage equipment operates under suitable environmental conditions and avoid adverse effects of adverse environmental factors on the system.

[0094] 4. Early warning display and management: The early warning system can visualize abnormal situations to help managers take timely measures, and realize the tracking and historical record management of alarm information through an integrated platform.

[0095] 5. Multi-level early warning strategy: According to different risk levels, the system will adopt different early warning strategies, such as sending prompt information when the risk is low, and automatically launching emergency response measures when the risk is high, to ensure the safe operation of the system under various circumstances.

[0096] Data analysis and optimization control

[0097] 1. Data collection and analysis: Use high-precision and high-efficiency intelligent control systems to collect and analyze the operating data of energy storage equipment, including voltage, current, power, state of charge and discharge (SOC), etc. Through in-depth analysis of these data, a reasonable energy storage scheduling strategy can be formulated.

[0098] 2. Load forecasting and energy storage scheduling: Based on historical load data, a forecasting model is established to predict the load demand in the future and help the system formulate a charging and discharging strategy. The scheduling strategy includes determining the time, power, and priority of energy storage equipment for charging and discharging, ensuring that the economic benefits and safety of the system are maximized while meeting the load demand.

[0099] 3. Dynamic optimization and scheduling adjustment: The system dynamically adjusts the scheduling strategy according to the operating status and real-time data of the equipment to avoid the impact on battery health caused by overcharging or over-discharging, extend battery life, and improve the overall stability of the system.

[0100] 4. Load response and demand-side management: Through real-time monitoring and load forecasting, the system can respond to the demand-side management strategy of the power grid, adjust the charging and discharging behavior of the energy storage system, achieve peak load shaving and valley filling, and maintain stable operation of the power grid.

[0101] 5. Application of intelligent optimization algorithms: Use advanced machine learning and optimization algorithms to intelligently analyze and optimize the operating mode of the energy storage system, and continuously adjust the control strategy to improve the operating efficiency and economy of the system.

[0102] Fault detection and emergency response

[0103] 1. Failure mode analysis: By analyzing historical failure data, a failure mode library for the energy storage system is established. The library is used to compare real-time monitoring data, identify potential failure risks, and prevent accidents in advance.

[0104] 2. Intelligent emergency response mechanism: When an abnormal situation is detected in the energy storage equipment, the system automatically activates the emergency response mechanism, such as reducing the charging and discharging power, switching to the backup power supply, etc., to ensure the continuity and safety of the system operation.

[0105] 3. Remote control and maintenance: Remote monitoring and maintenance of the energy storage system can be achieved through the platform, which improves the response speed of the equipment, supports unattended operation mode, and reduces the cost of manual intervention.

[0106] 4. Automated fault repair: Using self-diagnosis and self-repair technology, the system can automatically repair faults in certain situations, such as restoring the normal operation of the equipment by adjusting the charging and discharging parameters, thereby reducing manual intervention and maintenance costs.

[0107] 5. Backup and redundancy design: Introduce backup and redundancy mechanisms in system design to ensure that the system can still operate normally when some equipment fails. For example, design multiple parallel circuits to ensure that when one circuit fails, other circuits can take over its work to ensure the stability and reliability of the system.

[0108] The technical solution provided by the present invention is further described in detail above through several specific implementation modes in order to highlight the advantages and benefits of the technical solution provided by the present invention. However, the several specific implementation modes described above are not intended to be used as limitations on the present invention. Any reasonable modification and improvement of the present invention, combination of implementation modes and equivalent substitution within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A safety monitoring and control system for an energy storage system in an integrated energy station, characterized in that: The system comprises: Operation monitoring and integrated management module, used to monitor the power input and output of the energy storage system, grid interaction parameters, capacity and energy utilization; The safety monitoring and early warning module is used to monitor the preset parameters inside the energy storage device and in the operating environment; The data analysis and optimization control module is used for data collection of load system operating parameters, and to schedule and optimize the load behavior of the load system based on real-time data.

2. The energy storage system safety detection and control system for a comprehensive energy station according to claim 1, characterized in that: The operation monitoring and integrated management module includes monitoring devices for energy storage system power input and output, grid interaction parameters, capacity and energy utilization, as well as display devices for summarizing and displaying energy storage system data models.

3. The energy storage system safety detection and control system for a comprehensive energy station according to claim 1, characterized in that: The safety detection and early warning module includes temperature, pressure and electrical safety monitoring devices, and monitors preset parameters inside the energy storage device and in the operating environment.

4. The energy storage system safety detection and control system for a comprehensive energy station according to claim 1, characterized in that: The safety detection and early warning module is also used to set a multi-level early warning strategy to provide emergency prompts or handling measures for abnormal situations according to different preset risk levels.

5. The energy storage system safety detection and control system for a comprehensive energy station according to claim 1, characterized in that: The data analysis and optimization control module includes a data acquisition device for load system operating parameters and a prediction device for predicting future load demand in combination with historical load data.

6. The energy storage system safety detection and control system for a comprehensive energy station according to claim 1, characterized in that: It also includes a fault detection and emergency response module, including a fault detection device that analyzes the operating failure mode of the load system, identifies potential faults by comparing with a failure mode library, and initiates emergency treatment measures and remote control emergency response devices.

7. A method for safety detection and control of energy storage system for integrated energy station, characterized in that: The method is implemented based on the system according to claim 1, and includes: Steps for monitoring energy storage system power input and output, grid interaction parameters, capacity and energy utilization; Steps for monitoring preset parameters within the energy storage device and in the operating environment; The steps of collecting data on the operating parameters of the load system and scheduling and optimizing the load behavior of the load system based on real-time data.

8. A computer storage medium for storing a computing program, characterized in that: When the computer reads the computer program, the computer executes the method of claim 7.

9. A computer, comprising a processor and a storage medium, characterized in that: When the processor reads the computer program stored in the storage medium, the computer executes the method of claim 7 .

10. A computer program product, being a computer program, characterized in that When the computer program is executed, the method of claim 7 is implemented.