Chemical energy storage container temperature control system, temperature control method and device

Abstract

The invention relates to the technical field of electrochemical energy storage temperature control, and discloses a chemical energy storage container temperature control system, temperature control method and device, and the system comprises a distributed optical fiber temperature measurement host which is used for collecting the temperature data of optical fiber measurement points in a chemical energy storage container, the temperature data of the optical fiber measuring points in the chemical energy storage container are sent to the upper controller; wherein the optical fiber measuring point is arranged at a key position in the chemical energy storage container; the upper controller is used for carrying out abnormal heat source identification analysis on the temperature data of the optical fiber measuring points in the chemical energy storage container to obtain an abnormal heat source identification analysis result; and the upper controller is also used for generating a cooling optimization strategy based on the abnormal heat source identification analysis result, and regulating and controlling the internal temperature of the chemical energy storage container by using the cooling optimization strategy. The level of heat management of the energy storage container is comprehensively improved, and the requirements of a large-scale and high-power energy storage system are met.

Description

Technical Field

[0001] The present invention relates to the technical field of electrochemical energy storage temperature control, and in particular to a chemical energy storage container temperature control system, a temperature control method and a device. Background Art

[0002] A chemical energy storage container is an energy storage equipment system that combines chemical energy storage technology with container-type modular design. It mainly stores and releases electrical energy through chemical energy storage media such as batteries. It has the characteristics of integration, strong mobility, and flexible deployment.

[0003] Chemical energy storage containers typically use air cooling for thermal management, supplemented by point-based temperature monitoring to achieve temperature control. However, these temperature control solutions cannot meet the needs of large-scale, high-power energy storage systems, leading to incorrect temperature control decisions. Summary of the Invention

[0004] In view of this, the present invention provides a chemical energy storage container temperature control system, temperature control method and device to solve the problem that related energy storage temperature control solutions cannot meet the needs of large-scale, high-power energy storage systems.

[0005] In a first aspect, the present invention provides a temperature control system for a chemical energy storage container, comprising a temperature-sensing optical fiber, a distributed optical fiber temperature measurement host, and a host controller; the temperature-sensing optical fiber is arranged at a key position inside the chemical energy storage container, the temperature-sensing optical fiber is connected to the distributed optical fiber temperature measurement host, and the distributed optical fiber temperature measurement host is connected to the host controller;

[0006] A distributed optical fiber temperature measurement host is used to collect temperature data from optical fiber measurement points inside the chemical energy storage container and send the temperature data from the optical fiber measurement points inside the chemical energy storage container to a host controller; wherein the optical fiber measurement points are set at key locations inside the chemical energy storage container;

[0007] The upper controller is used to perform abnormal heat source identification and analysis on the temperature data of the optical fiber measuring points inside the chemical energy storage container to obtain abnormal heat source identification and analysis results;

[0008] The upper controller is also used to generate a cooling optimization strategy based on the abnormal heat source identification and analysis results, and use the cooling optimization strategy to regulate the internal temperature of the chemical energy storage container.

[0009] This embodiment provides a temperature control system for a chemical energy storage container. By deploying temperature-sensing optical fibers at key locations within the container, this system achieves global temperature sensing and monitoring within the container. Temperature data from optical fiber measurement points within the container is collected via a distributed optical fiber temperature measurement host. This system has the advantages of high temperature measurement accuracy and wide spatial coverage. Furthermore, a host computer controller identifies and analyzes abnormal heat sources from the temperature data at these points. Based on these results, a cooling optimization strategy is generated, improving airflow uniformity, enhancing cooling in targeted heat source areas, significantly reducing cooling dead zones, and increasing heat exchange efficiency. Global temperature sensing and intelligent optimization control eliminate blind spots, balance cooling, achieve coordinated responses, and improve efficiency, comprehensively enhancing the thermal management of energy storage containers and meeting the requirements of large-scale, high-power energy storage systems.

[0010] In an optional embodiment, the temperature-sensing optical fiber is arranged in the gap channels between the battery packs inside the chemical energy storage container, the top space and the bottom space of the battery rack, and the cooling dead corner area.

[0011] In an optional embodiment, the distributed optical fiber temperature measurement host is specifically used to transmit laser pulses to the temperature-sensing optical fiber at the optical fiber measuring point inside the chemical energy storage container, receive backscattered signals, and calculate the temperature data of the optical fiber measuring point inside the chemical energy storage container based on the backscattered signals.

[0012] In an optional embodiment, the system further comprises: a linkage control device connected to the upper controller; the linkage control device comprises a fire protection platform and a remote monitoring alarm platform;

[0013] Firefighting platform, used to obtain abnormal heat source identification and analysis results, and to extinguish fires based on these results;

[0014] The remote monitoring and alarm platform is used to obtain abnormal heat source identification and analysis results and send early warning notifications based on the abnormal heat source identification and analysis results.

[0015] In a second aspect, the present invention provides a temperature control method for a chemical energy storage container temperature control system, which is applied to a host controller in a chemical energy storage container temperature control system according to the second aspect or any corresponding embodiment thereof; the method comprises:

[0016] Obtain temperature data of optical fiber measurement points inside the chemical energy storage container sent by the distributed optical fiber temperature measurement host;

[0017] Abnormal heat source identification and analysis is performed on the temperature data of the optical fiber measurement points inside the chemical energy storage container to obtain abnormal heat source identification and analysis results;

[0018] Based on the abnormal heat source identification and analysis results, a cooling optimization strategy is generated, and the internal temperature of the chemical energy storage container is regulated using the cooling optimization strategy.

[0019] This embodiment provides a temperature control method for a chemical energy storage container temperature control system. This method generates a cooling optimization strategy based on the results of abnormal heat source identification and analysis. This improves airflow uniformity, strengthens cooling in targeted heat source areas, significantly reduces cooling dead spots, and improves heat exchange efficiency. It can promptly detect local hotspots and adjust the cooling strategy, reducing the risk of thermal runaway and ensuring the safe operation of the chemical energy storage container temperature control system.

[0020] In an optional embodiment, abnormal heat source identification analysis is performed on the temperature data of the optical fiber measurement points inside the chemical energy storage container to obtain abnormal heat source identification analysis results, including:

[0021] Obtaining a three-dimensional model of the chemical energy storage container and the locations of the temperature-sensing optical fibers, and constructing a three-dimensional thermal distribution model based on the three-dimensional model of the chemical energy storage container and the locations of the temperature-sensing optical fibers;

[0022] Interpolate the temperature data of the optical fiber measurement point and map it to the three-dimensional thermal distribution model to obtain the temperature distribution field;

[0023] Identify abnormal heat sources in the temperature distribution field and obtain abnormal temperature measurement points;

[0024] A CFD simulation model was established, and the abnormal temperature measurement points were simulated and verified using the CFD simulation model to obtain the abnormal heat source identification and analysis results.

[0025] This embodiment provides a temperature control method for a chemical energy storage container temperature control system. This method constructs a high-precision temperature distribution field, accurately locates the heat source location and heat conduction path, and optimizes the air duct structure of the air conditioning cooling system based on the results of abnormal heat source identification and analysis. This improves airflow uniformity and strengthens cooling in the heat source area in a targeted manner. By dynamically adjusting fan power and wind direction based on real-time data, this method achieves on-demand cooling and reduces energy consumption.

[0026] In a third aspect, the present invention provides a temperature control device for a chemical energy storage container temperature control system, the device comprising:

[0027] An acquisition module is used to obtain temperature data of optical fiber measurement points inside the chemical energy storage container sent by the distributed optical fiber temperature measurement host;

[0028] An identification and analysis module is used to identify and analyze abnormal heat sources based on the temperature data of optical fiber measurement points inside the chemical energy storage container to obtain abnormal heat source identification and analysis results;

[0029] The control module is used to generate a cooling optimization strategy based on the abnormal heat source identification and analysis results, and use the cooling optimization strategy to control the internal temperature of the chemical energy storage container.

[0030] In a fourth aspect, the present invention provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to thereby execute the temperature control method for the chemical energy storage container temperature control system of the second aspect or any corresponding embodiment thereof.

[0031] In a fifth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the temperature control method for a chemical energy storage container temperature control system according to the second aspect or any corresponding embodiment thereof.

[0032] In a sixth aspect, the present invention provides a computer program product comprising computer instructions, which are used to enable a computer to execute the temperature control method for a chemical energy storage container temperature control system according to the second aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0034] Figure 1 This is a schematic structural diagram of a temperature control system for a chemical energy storage container according to an embodiment of the present invention;

[0035] Figure 2 is a front view of a chemical energy storage container according to an embodiment of the present invention;

[0036] Figure 3 is a right side view of a chemical energy storage container according to an embodiment of the present invention;

[0037] Figure 4 is a rear view of a chemical energy storage container according to an embodiment of the present invention;

[0038] Figure 5 is a left side view of a chemical energy storage container according to an embodiment of the present invention;

[0039] Figure 6 This is a structural block diagram of a temperature control system for a chemical energy storage container according to an embodiment of the present invention;

[0040] Figure 7 This is a schematic diagram of the working process of a temperature control system for a chemical energy storage container according to an embodiment of the present invention;

[0041] Figure 8 1 is a flow chart of a temperature control method for a chemical energy storage container temperature control system according to an embodiment of the present invention;

[0042] Figure 9 is a flow chart of another temperature control method for a chemical energy storage container temperature control system according to an embodiment of the present invention;

[0043] Figure 10 is a schematic diagram of temperature distribution according to an embodiment of the present invention;

[0044] Figure 11 is a schematic diagram of wind speed in a characteristic cross section according to an embodiment of the present invention;

[0045] Figure 12 This is a structural block diagram of a temperature control device of a chemical energy storage container temperature control system according to an embodiment of the present invention;

[0046] Figure 13 Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0047] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0048] In practical applications, chemical energy storage containers typically employ air cooling for thermal management, supplemented by simple point-based temperature monitoring. Specifically, each battery pack incorporates several thermistors or thermocouples as temperature sensors, with the Battery Management System (BMS) monitoring the temperature of the battery cells / modules. A small number of ambient temperature sensors are installed within the container compartment (e.g., on the roof or in the equipment compartment) to control the air conditioning start / stop. For cooling, most energy storage containers are equipped with integrated air conditioners or fans, which deliver cold air into the battery compartment through pre-set air ducts for forced air cooling. For example, a standard 20-foot energy storage container typically has one or two industrial air conditioners (with a total cooling capacity of tens of kilowatts) installed at one end, with fans directing the cool air along the aisle to the other end. For battery placement, a common layout involves creating double-layer or multi-row battery racks within the container, with air circulating from the air conditioners to remove heat from the battery surfaces.

[0049] The above energy storage temperature control solution has the advantages of simple implementation and low cost. It can basically meet the needs in situations where the ambient temperature is moderate and the power of a single box is not too high. However, as energy storage systems develop towards larger scales and higher powers, the shortcomings of the above energy storage temperature control solution are becoming increasingly prominent:

[0050] 1) Limited temperature measurement range and sparse distribution: Point temperature sensors are few in number and fixed in position, making them unable to cover the entire battery compartment. For example, a battery rack may have only one or two temperature sensors on the top and bottom floors. The temperature of the large area between these detection points is actually unknown, making it difficult to provide a comprehensive picture of the temperature distribution inside the battery compartment. This means that if a battery module overheats between two sensors, the monitoring system may not be able to detect it in time, thus posing a hidden danger. Even if the BMS monitors the temperature of each battery cell, it is limited to the battery cell itself. Localized abnormalities in the ambient temperature in the compartment (such as hot air accumulation in a corner) are still difficult to detect in a timely manner.

[0051] 2) Cooling blind spots and imbalances: The design of fixed air ducts + air conditioning is often based on experience and cannot take into account the cooling needs of every corner. In practice, cooling blind spots often occur. Heat accumulates in certain areas far from the air supply or where airflow is not available. The temperature measurement points cannot sense the temperature in these blind spots, causing these areas to remain high for a long time without anyone knowing. When extreme conditions occur (such as thermal runaway of a battery), these blind spots become high-incidence points for accidents. At the same time, air supply from air conditioning is generally controlled as a whole, lacking differentiated adjustment for different areas, resulting in uneven cooling: batteries close to the air conditioner may be overcooled, while batteries far away may be overheated. The temperature difference is large, and excessive temperature differences can accelerate the aging of some batteries and shorten their overall lifespan.

[0052] 3) Lack of thermal field feedback optimization: Once the design inside the energy storage box is established, the air duct layout and cooling scheme are rarely improved based on operational data. The air conditioner installation position, air outlet angle, and circulating air path are usually determined in the early stages of the design. Subsequently, no matter which areas are found to have high temperatures during operation, there is no means to adjust the air path (unless the system is shut down for major renovations). In other words, the temperature field and cooling structure are disconnected: the temperature control system cannot "sense" the quality of its own cooling effect, and therefore cannot achieve closed-loop optimization. The above situation is similar to "blindly adjusting the air conditioner", where the fan speed and air outlet are set based on experience, and the cooling area is cooled according to pre-set assumptions, without using actual temperature distribution data for iterative optimization.

[0053] 4) Insufficient early warning and linkage: Currently, temperature monitoring and control in many energy storage systems still operate independently. Many containers rely solely on the BMS's own alarms or simple thermostats, only initiating an alarm shutdown when the battery temperature is too high. These systems lack real-time linkage with more advanced energy management systems (EMS) or fire protection systems. For example, in some systems, the air conditioning system only starts and stops according to the average cabin temperature. Abnormally high temperature signals are not shared with the EMS for power adjustment, nor is fire suppression triggered. This results in delayed early warning responses and a single approach. Once battery thermal runaway occurs, the system often can only passively wait for the temperature to reach the smoke / gas alarm threshold before initiating fire protection, lacking an earlier proactive intervention mechanism. Overall, energy storage temperature control systems lack a closed loop between monitoring, control, and safety.

[0054] 5) Energy efficiency and cost issues: Due to inaccurate detection and control, air conditioning systems typically adopt more conservative strategies (such as continuous low-temperature operation) to ensure cooling, resulting in low energy efficiency and increased operating costs. For example, for safety reasons, some energy storage stations set the air conditioning to operate at temperatures far below the required level year-round to compensate for the uncertainty of monitoring blind spots, resulting in high energy consumption. In addition, many systems are largely manually adjusted and lack intelligent optimization, which also increases manual operation and maintenance costs.

[0055] To address these shortcomings, technicians in this field are exploring solutions. For example, they are introducing distributed fiber-optic temperature measurement technology for energy storage systems to obtain comprehensive temperature field information; they are also trying to add regional dampers or independent fans to air conditioning controls to achieve a certain degree of zoned cooling. However, most commercial energy storage products have not yet truly achieved the integrated optimization of temperature monitoring and temperature control design.

[0056] Based on the above technical analysis, the key issues and bottlenecks that need to be urgently addressed in the engineering application of temperature control and temperature measurement methods for energy storage containers are as follows:

[0057] (1) It is difficult to measure the temperature in full space in real time: Point-based temperature measurement cannot achieve real-time temperature perception of all locations inside the energy storage compartment. Specifically, the number of temperature sensors is limited, and it is difficult to cover every battery module, aisle, and top / bottom space in terms of layout. The temperature data collection of some hidden corners or battery gaps is blank, forming a monitoring blind spot. This means that the system lacks the ability to fully perceive the three-dimensional temperature field and cannot achieve "what you see is what you get". For large-capacity battery compartments, even an inconspicuous corner temperature abnormality may trigger a safety accident. The lack of comprehensive monitoring is a major hidden danger.

[0058] (2) The cooling design lacks a temperature feedback closed loop: The current air duct and air conditioning configuration of the energy storage cabin is mainly based on experience and limited simulation, and lacks actual temperature data guidance, so it is impossible to optimize the problems found during operation. In other words, the design and operation of the cooling system are rarely adjusted based on real-time temperature feedback; for example, when a certain area is continuously hot, the air volume should be increased or the air path should be modified, but the relevant system cannot obtain this information in time, let alone make optimization decisions. This lack of a closed loop results in poor adaptability of the cooling system, and it is difficult to adjust in time when facing environmental changes or load changes, resulting in inefficiencies that do not match the design with reality.

[0059] (3) Separation of monitoring and control, insufficient linkage: Most energy storage thermal management systems have not been linked with EMS, fire protection and other systems, and therefore lack the ability to proactively warn and accurately locate faults. For example, when a part of the battery overheats, the BMS may sound an alarm, but the air conditioner will not automatically increase the cooling of that part, and the fire department will not intervene until the temperature rises to trigger a smoke / heat alarm. In addition, the alarm information of many systems is only a simple prompt, and cannot indicate which specific battery or location has a problem. Operation and maintenance personnel often need to spend time to investigate and locate the problem. This model of each system operating independently cannot provide layered security protection and is prone to missing the best time for intervention.

[0060] (4) Unbalanced air-conditioning operation and low energy efficiency: The air-conditioning system does not differentiate between the cooling needs of different areas, and the phenomenon of "the strong ones are not strong, and the weak ones are not weak" often occurs; for example, when the load is partially loaded or the ambient temperature is low, the air-conditioning may still operate at full load, resulting in unnecessary energy consumption; on the contrary, there is insufficient cooling in the high heat load area; this non-optimized operation leads to low energy efficiency of the entire system and high long-term operating costs; especially in the scenario of multiple air-conditioning units working in parallel, the lack of overall coordination will result in some air-conditioning units frequently starting and stopping, and some units being idle for a long time, which not only wastes electricity but also increases equipment wear.

[0061] In summary, the pain points in current engineering applications are: incomplete visibility, poor adjustment, inability to connect, and high energy consumption; that is, the temperature cannot be fully "seen", cooling measures cannot accurately "take care of" every corner, and the subsystems cannot work together. As a result, efficiency is often sacrificed for safety.

[0062] To solve the above-mentioned technical problems, an embodiment of the present invention provides a temperature control system for a chemical energy storage container, which is developed around the principles of "complete measurement, clear visualization, accurate analysis, effective modification, and controllable": first, high-density optical fiber sensing is used to cover the entire cabin to obtain detailed temperature data; then, simulation is used to diagnose problems; then, the cooling design is optimized; and finally, a fusion control system is used to achieve active adjustment and multi-system linkage. The entire solution can be integrated into the entire life cycle of the design, construction, and operation and maintenance of the energy storage container. On the one hand, applying this method in the design phase of a new energy storage system can pre-optimize the air conditioning and air duct solutions, improving the reliability of the first round of design; on the other hand, for existing energy storage projects that are already in operation, optical fiber temperature measurement can also be deployed for physical examination, evaluation, and modification to promptly discover and resolve potential risks, thereby improving the safety margin and operating efficiency of the existing system.

[0063] It should be noted that the embodiments of the present invention belong to the technical direction of electrochemical energy storage safety monitoring and thermal management in the field of new energy power systems. Specifically, its technology covers the following sub-fields and related interdisciplinary disciplines:

[0064] Energy storage system engineering: For chemical energy storage container systems represented by lithium-ion batteries, energy storage projects involve the design and integration of battery modules, energy storage cabins, air conditioning, ventilation and other temperature control devices. Therefore, the technical field involved is first and foremost the design and operation of electrochemical energy storage systems, with a core focus on battery thermal management and safety protection.

[0065] Fiber-optic sensing and measurement and control technology: This technology utilizes distributed fiber-optic temperature sensing, a key branch of the fiber-optic sensor field. DTS uses optical fiber as the sensing medium and belongs to the fields of optoelectronics and sensing technology. It utilizes optical principles such as Raman scattering and Brillouin scattering to measure temperature along the entire length of the fiber. Therefore, the embodiments of the present invention also fall within the application scope of optical sensors and measuring instruments. Unlike traditional electrical measurement, fiber-optic sensing technology offers advantages such as resistance to electromagnetic interference, long-distance deployment, and the ability to achieve continuous spatially distributed measurements. These advantages are highly consistent with the high-voltage, strong magnetic environment and large spatial scale characteristics of energy storage systems.

[0066] Thermal Energy and HVAC Engineering: This involves analyzing and regulating the thermal flow and temperature fields within the energy storage cabin, and is therefore closely related to thermal energy engineering and HVAC technology. The temperature control system of the energy storage container is essentially similar to a small, special air-conditioned room, including refrigeration, air supply, circulation, and other links. Through thermal field simulation and air duct optimization, it falls into the airflow organization optimization design problem in the HVAC field. At the same time, it involves using temperature measurement feedback to dynamically adjust cooling power and airflow distribution, which is the content of thermal automatic control. Therefore, the embodiments of the present invention also intersect with knowledge of disciplines such as thermodynamics, heat transfer, and fluid mechanics to understand and improve the heat dissipation performance within the cabin.

[0067] Battery Management and Safety Engineering: Temperature control of energy storage systems is directly related to battery safety and performance, and is an extension of battery management systems and fire safety. It is also related to areas such as battery thermal runaway protection and energy storage fire protection. For example, distributed fiber optic temperature measurement can be considered a high-level battery thermal safety monitoring method, which can assist the BMS in determining battery status and can also be regarded as an early warning detector for fire protection systems. The embodiment of the present invention and the fire protection linkage design mean that it partially belongs to the field of fire detection and linkage control technology (combining temperature sensing, alarm and fire extinguishing control).

[0068] IoT and Intelligent Operations: Because the system architecture involves remote collection and real-time transmission of sensor data, as well as integration with cloud-based monitoring platforms, embodiments of this invention can also be categorized within the energy IoT and intelligent operations. Data acquired by the fiber-optic temperature measurement host needs to be connected to energy management systems such as EMS / SCADA via a communication interface for monitoring and closed-loop control. This involves industrial communication protocols and IoT architecture design. Therefore, within a broader technological ecosystem, this connects technical fields such as the Industrial IoT, real-time monitoring, and big data analytics, enabling intelligent management of energy storage infrastructure.

[0069] This embodiment provides a chemical energy storage container temperature control system, such as Figure 1 As shown, it includes: a temperature-sensing optical fiber 101, a distributed optical fiber temperature measurement host 102 and an upper controller 103; the temperature-sensing optical fiber 101 is arranged at a key position inside the chemical energy storage container, the temperature-sensing optical fiber 101 is connected to the distributed optical fiber temperature measurement host 102, and the distributed optical fiber temperature measurement host 102 is connected to the upper controller 103;

[0070] The distributed optical fiber temperature measurement host 102 is used to collect temperature data of optical fiber measurement points inside the chemical energy storage container and send the temperature data of the optical fiber measurement points inside the chemical energy storage container to the upper controller 103; wherein the optical fiber measurement points are set at key positions inside the chemical energy storage container.

[0071] Specifically, the laid temperature-sensing optical fiber 101 is connected to a distributed optical fiber temperature measurement host 102 (ie, a DTS host). The distributed optical fiber temperature measurement host 102 uses a high spatial resolution DTS device, such as a system with a temperature resolution of 0.1°C and a positioning accuracy of ±1m.

[0072] Furthermore, the distributed optical fiber temperature measurement host 102 can scan tens of thousands of measurement points per second, and the temperature distribution of the entire cabin can be obtained within a typical scanning cycle of less than 10 seconds. The collected temperature data is sent to the upper controller 103 (or industrial computer) in real time through the communication interface; wherein, the communication interface can adopt MODBUS / TCP (an Ethernet communication protocol based on the Modbus protocol) or IEC 61850 (a general standard in the field of power system automation) protocol.

[0073] The upper controller 103 is used to perform abnormal heat source identification and analysis on the temperature data of the optical fiber measuring points inside the chemical energy storage container to obtain abnormal heat source identification and analysis results.

[0074] Specifically, the real-time collected temperature field data is used in combination with historical data patterns to identify abnormal heat sources and analyze cooling performance.

[0075] Furthermore, in the upper controller 103, a three-dimensional thermal distribution model is constructed by combining the CAD model of the energy storage compartment of the chemical energy storage container and the optical fiber layout position. The three-dimensional thermal distribution model interpolates and maps the temperature data of discrete optical fiber measurement points into the temperature field of the entire space, which is visualized as a "thermal map" for analysis.

[0076] Furthermore, the upper controller 103 can record historical temperature data for subsequent big data analysis and model correction. For example, after a period of operation, a cloud map of the temperature distribution in the cabin under different charging and discharging states can be obtained to provide a basis for optimization.

[0077] The upper controller 103 is further configured to generate a cooling optimization strategy based on the abnormal heat source identification and analysis results, and to use the cooling optimization strategy to regulate the internal temperature of the chemical energy storage container.

[0078] Specifically, for cooling control, the upper controller 103 adopts an automatic control unit (PLC or industrial computer) to adjust the air-conditioning operation in a closed loop: it receives optical fiber temperature measurement data and automatically adjusts the start and stop of the air-conditioning compressor, air supply mode and air valve opening according to a pre-set strategy (which can be based on PID or fuzzy control); for example, when the local temperature rises, the air volume of the corresponding air outlet in the area is automatically increased and the air volume in other areas is reduced to achieve optimized cold and heat distribution.

[0079] This embodiment provides a temperature control system for a chemical energy storage container. By deploying temperature-sensing optical fibers at key locations within the container, this system achieves global temperature sensing and monitoring within the container. Temperature data from optical fiber measurement points within the container is collected via a distributed optical fiber temperature measurement host. This system has the advantages of high temperature measurement accuracy and wide spatial coverage. Furthermore, a host computer controller identifies and analyzes abnormal heat sources from the temperature data at these points. Based on these results, a cooling optimization strategy is generated, improving airflow uniformity, enhancing cooling in targeted heat source areas, significantly reducing cooling dead zones, and increasing heat exchange efficiency. Global temperature sensing and intelligent optimization control eliminate blind spots, balance cooling, achieve coordinated responses, and improve efficiency, comprehensively enhancing the thermal management of energy storage containers and meeting the requirements of large-scale, high-power energy storage systems.

[0080] In some optional embodiments, the temperature-sensing optical fiber 101 is arranged in the gap channels between the battery packs inside the chemical energy storage container, the top space and the bottom space of the battery rack, and the cooling dead corner area.

[0081] Specifically, if Figure 2-5 As shown, temperature-sensing optical fibers 101 are laid out at key locations inside the chemical energy storage container to form a dense temperature sensing network. The layout strategy includes: laying optical fibers along the gaps between each row of battery packs, keeping them close to the surface of the battery modules; laying optical fibers in the top and bottom spaces of the battery racks to monitor the rising hot air gathering areas and the cold air distribution at the bottom; and arranging additional optical fiber loops in potential cooling dead spots such as aisles and corners. Through reasonable routing, the entire cabin is ensured to be covered by optical fibers in the longitudinal, transverse, and vertical directions, thereby forming a perception of the three-dimensional temperature field of the energy storage cabin. Through the above-mentioned optical fiber sensing layout, blind-spot monitoring of the energy storage cabin temperature is achieved.

[0082] For example, a 6-meter-long 20-foot battery box can be laid with a total length of about 100 meters of temperature-sensitive optical cable, which is divided into several routes to cover all battery racks and channels, and a temperature measurement point is obtained every 0.5 to 1 meter.

[0083] Furthermore, the temperature-sensitive optical fiber 101 is preferably a multimode temperature-sensitive optical fiber (62.5 / 125 μm) to increase the Raman scattering signal intensity. The temperature-sensitive optical fiber 101 is covered with a high-temperature resistant insulation layer and fixed on the battery rack or the cabin wall to withstand the harsh environment in the cabin.

[0084] In some optional embodiments, the distributed optical fiber temperature measurement host 102 is specifically used to transmit laser pulses to the temperature-sensitive optical fiber 101 at the optical fiber measuring point inside the chemical energy storage container, receive backscattered signals, and calculate the temperature data of the optical fiber measuring point inside the chemical energy storage container based on the backscattered signals.

[0085] Specifically, based on the principle of optical time domain reflectometry, the DTS host injects laser pulses into the temperature-sensing optical fiber 101 and receives backscattered signals. The temperature of each point along the line is calculated using the Raman frequency shift signal intensity ratio. The relationship between the Raman frequency shift signal intensity ratio and temperature can be obtained through experiments. The calculation formula for the temperature data of the optical fiber measurement point inside the chemical energy storage container is as follows:

[0086] I S / I A =f(T)

[0087] Among them, I S is the Stokes signal intensity, I A is the anti-Stokes signal intensity, T is the temperature, and f(T) is the function of temperature T.

[0088] In some optional embodiments, such as Figure 6As shown, it also includes: a linkage control device 104, which is connected to the upper controller 103; the linkage control device 104 includes a fire protection platform 1041 and a remote monitoring alarm platform 1042;

[0089] The fire protection platform 1041 is used to obtain abnormal heat source identification and analysis results and perform firefighting based on the abnormal heat source identification and analysis results.

[0090] The remote monitoring alarm platform 1042 is used to obtain abnormal heat source identification and analysis results and send early warning notifications based on the abnormal heat source identification and analysis results.

[0091] Specifically, based on the cooling optimization strategy, the distributed fiber optic temperature measurement host 102 is integrated with the fire protection platform 1041, energy management system and remote monitoring alarm platform 1042 of the energy storage station to form an intelligent linkage control system. Through the intelligent linkage control system, a closed loop from "perception → decision-making → execution" is formed to realize the integrated intelligent thermal management of temperature measurement - control - early warning - cooling.

[0092] Furthermore, the temperature data and warning signals detected by the distributed optical fiber temperature measurement host 102 are connected to the EMS, so that the EMS can dynamically adjust the operation of the energy storage system according to the temperature field, such as reducing the charge and discharge power of overheated battery packs, starting the backup cooling device, etc.; at the same time, the temperature abnormality signal is synchronously transmitted to the fire protection platform 1041: when the temperature at a certain location exceeds the dangerous threshold and continues to rise, the fire protection platform 1041 enters the alert state in advance (such as starting the fan smoke exhaust mode, pressurizing the fire extinguishing agent pipeline, etc.), and does not need to wait for the smoke sensor to operate before responding.

[0093] Furthermore, the distributed fiber optic temperature measurement host 102 is linked to the remote monitoring alarm platform 1042 (SMS, APP, email, etc.) to send early warning notifications to operation and maintenance personnel, and highlight abnormal areas on the three-dimensional model of the monitoring center to achieve precise positioning and multi-level alarms.

[0094] Furthermore, if the distributed optical fiber temperature measurement host 102 finds that the temperature continues to exceed the limit and cannot be controlled, the PLC (Programmable Logic Controller) will actively trigger the emergency shutdown of the energy storage system and link the fire fighting platform 1041 to extinguish the fire to prevent the accident from escalating.

[0095] like Figure 7 As shown, the working process of a chemical energy storage container temperature control system is described below through a specific embodiment.

[0096] Example 1:

[0097] The working process of a chemical energy storage container temperature control system includes:

[0098] 1) Six optical fibers are laid inside the energy storage container, covering the top, middle, and bottom layers;

[0099] 2) Use the DTS host to demodulate the optical signal and collect temperature data;

[0100] 3) Use thermodynamic simulation software to establish a two-dimensional heat distribution field;

[0101] 4) Optimize the position of the air-conditioning outlet, changing from the original one-way air supply to double-layer distributed air supply.

[0102] Example 2:

[0103] The working process of a chemical energy storage container temperature control system includes:

[0104] 1) Deploy 12 optical fibers at a 100MW / 200MWh project site, integrating temperature and humidity sensors;

[0105] 2) Establish a data interface with the EMS system to trigger fan acceleration and fire protection system linkage when the local temperature rises to a set threshold;

[0106] 3) Operation and maintenance personnel receive real-time alarms and location information through the APP.

[0107] The above embodiment has the following advantages:

[0108] Distributed fiber optic "thermal imaging" perception: For the first time, a distributed fiber optic temperature sensing system was introduced into the large space environment of the energy storage cabin, replacing the thermal resistor / thermistor point temperature measurement mode. Distributed fiber optic continuous temperature measurement is adopted, which has high temperature measurement accuracy, wide spatial coverage and fast response speed, realizing comprehensive temperature monitoring and high-precision early warning.

[0109] Thermal field model-assisted optimization mechanism: A method system combining thermal field numerical model and cooling design optimization was constructed. The cooling scheme was optimized through thermal field feedback, which significantly reduced cooling dead spots and improved heat exchange efficiency, resulting in a significant increase in cooling efficiency and good temperature balance.

[0110] Closed-loop thermal management with integrated measurement and control: This system achieves closed-loop integration of multiple links, including temperature measurement, control, early warning, and cooling. Through early warning and proactive intervention, it significantly reduces the risk of widespread thermal runaway, significantly improving safety and reliability. Furthermore, through linkage with EMS, firefighting platforms, and other systems, it essentially achieves intelligent O&M of energy storage temperature control, resulting in enhanced intelligence and high O&M efficiency.

[0111] High-precision positioning and intelligent diagnosis: With the spatial continuity of distributed optical fibers, hotspot positioning with an accuracy of 1 meter or even higher can be achieved.

[0112] Redundancy and reliability design: Considering the harsh conditions of industrial sites, redundant backup and fault-tolerant design are adopted in the system architecture. Although the introduction of the fiber optic temperature measurement system will increase the initial investment, it achieves cost-effectiveness advantages in many aspects.

[0113] According to an embodiment of the present invention, an embodiment of a temperature control method for a temperature control system of a chemical energy storage container is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0114] In this embodiment, a temperature control method for a chemical energy storage container temperature control system is provided, which can be used in the above-mentioned upper controller 103. Figure 8 FIG. 1 is a flow chart of a temperature control method for a chemical energy storage container temperature control system according to an embodiment of the present invention. Figure 8 As shown, the process includes the following steps:

[0115] Step S801: Acquire temperature data of optical fiber measurement points inside a chemical energy storage container sent by a distributed optical fiber temperature measurement host.

[0116] Step S802 , performing abnormal heat source identification analysis on the temperature data of the optical fiber measuring points inside the chemical energy storage container to obtain abnormal heat source identification analysis results.

[0117] Step S803: Generate a cooling optimization strategy based on the abnormal heat source identification and analysis results, and use the cooling optimization strategy to regulate the internal temperature of the chemical energy storage container.

[0118] Specifically, based on the heat distribution analysis and simulation results (i.e., the abnormal heat source identification and analysis results), targeted air conditioning air supply and duct structure optimization plans are generated. The optimization methods include: adjusting the position and orientation of the air conditioning cold air outlet, such as adding new air outlets near hot spots or changing the angle of the louvers to direct the airflow to blind spots; adding guide plates or fans where needed to guide the airflow circulation to each battery unit; optimizing the cabinet / battery layout, such as increasing ventilation gaps in overheated areas; if one air conditioner cannot cover the entire range, consider using multiple air conditioners for zoned air supply to take care of the temperature requirements of different areas; in addition, control parameters can also be adjusted, such as increasing the fan speed near the hot spot area and reducing the air volume in other areas to achieve on-demand distribution of cooling capacity.

[0119] Furthermore, cooling optimization strategies will be implemented as far as is feasible and cost-effective in engineering. For example, simply adding a few guide plates and optimizing the fan control curve can significantly improve temperature uniformity. The optimized cooling solution needs to be verified again through simulation to confirm that the cooling blind spots have been eliminated and the temperatures at all locations are within a safe range. The final cooling optimization solution will then be used to modify the energy storage cabin to improve cooling efficiency.

[0120] This embodiment provides a temperature control method for a chemical energy storage container temperature control system. This method generates a cooling optimization strategy based on the results of abnormal heat source identification and analysis. This method improves airflow uniformity, strengthens cooling in targeted heat source areas, significantly reduces cooling dead zones, and improves heat exchange efficiency. It can promptly detect local hot spots and adjust the cooling strategy, reducing the risk of thermal runaway and ensuring the safe operation of the chemical energy storage container temperature control system.

[0121] In this embodiment, a temperature control method for a chemical energy storage container temperature control system is provided, which can be used in the above-mentioned upper controller 103. Figure 9 FIG. 1 is a flow chart of a temperature control method for a chemical energy storage container temperature control system according to an embodiment of the present invention. Figure 9 As shown, the process includes the following steps:

[0122] Step S901: Obtain the temperature data of the optical fiber measuring point inside the chemical energy storage container sent by the distributed optical fiber temperature measurement host. Figure 8 Step S801 of the illustrated embodiment will not be described in detail here.

[0123] Step S902 : performing abnormal heat source identification analysis on the temperature data of the optical fiber measuring points inside the chemical energy storage container to obtain abnormal heat source identification analysis results.

[0124] Specifically, the above step S902 includes:

[0125] Step S9021: Acquire the three-dimensional model of the chemical energy storage container and the temperature sensing optical fiber layout positions, and construct a three-dimensional thermal distribution model based on the three-dimensional model of the chemical energy storage container and the temperature sensing optical fiber layout positions.

[0126] Step S9022: Interpolate and map the temperature data of the optical fiber measurement points to the three-dimensional thermal distribution model to obtain a temperature distribution field.

[0127] Specifically, in the upper controller 103, a three-dimensional thermal distribution model is constructed by combining the CAD model of the energy storage cabin and the optical fiber layout position. The model interpolates the temperature data of discrete optical fiber measurement points and maps them into the temperature field of the entire space, which is visualized as a "thermal map" for analysis.

[0128] Step S9023: Identify abnormal heat sources in the temperature distribution field to obtain abnormal temperature measurement points.

[0129] Specifically, the upper controller 103 continuously compares the temperature distribution field with the normal benchmark, automatically identifies areas with significantly higher temperatures (hot spots) and areas with large temperature gradients (possible cooling weak areas), and once a cooling dead corner or potential high-temperature hot spot is found, its specific position is first located (corresponding to a certain module or shelf in the box).

[0130] Step S9024: Establish a CFD simulation model, use the CFD simulation model to simulate and verify the abnormal temperature measurement points, and obtain abnormal heat source identification and analysis results.

[0131] Specifically, if Figure 10-11 As shown, based on the detected temperature boundary conditions, a CFD (Computational Fluid Dynamics) model of the energy storage cabin is established to simulate the air flow and temperature distribution under the current air duct design.

[0132] Furthermore, simulating the air flow and temperature distribution under the current air duct design is equivalent to a "physical examination" of the current cooling solution, verifying which areas have low wind speeds and vortex retention. Simulation analysis combined with actual temperature measurement makes the results closer to the actual working conditions, different from the idealized simulation in the initial design stage.

[0133] Furthermore, simulation analysis determined that the airflow velocity in a certain corner of the temperature distribution field was close to zero, which was consistent with the high-temperature area detected by fiber optic detection, confirming that this was a cooling blind spot. The simulation analysis also included evaluating whether the air conditioning cooling capacity was sufficient and whether the air path was unobstructed. Through a two-pronged approach of data and models, a comprehensive diagnosis of current thermal management problems was achieved.

[0134] Step S903: Generate a cooling optimization strategy based on the abnormal heat source identification and analysis results, and use the cooling optimization strategy to control the internal temperature of the chemical energy storage container. Figure 8 Step S803 of the illustrated embodiment will not be described in detail here.

[0135] This embodiment provides a temperature control method for a chemical energy storage container temperature control system. This method constructs a high-precision temperature distribution field, accurately locates the heat source location and heat conduction path, and optimizes the air duct structure of the air conditioning cooling system based on the results of abnormal heat source identification and analysis. This improves airflow uniformity and strengthens cooling in the heat source area in a targeted manner. By dynamically adjusting fan power and wind direction based on real-time data, this method achieves on-demand cooling and reduces energy consumption.

[0136] This embodiment also provides a temperature control device for a chemical energy storage container temperature control system. This device is used to implement the above-mentioned embodiments and preferred embodiments. Details already described will not be repeated here. As used below, the term "module" may refer to a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0137] This embodiment provides a temperature control device for a chemical energy storage container temperature control system, such as Figure 12 Shown, including:

[0138] An acquisition module 1201 is configured to acquire temperature data of an optical fiber measurement point inside a chemical energy storage container sent by a distributed optical fiber temperature measurement host;

[0139] Identification and analysis module 1202, used to perform abnormal heat source identification and analysis on the temperature data of the optical fiber measurement points inside the chemical energy storage container to obtain abnormal heat source identification and analysis results;

[0140] The control module 1203 is used to generate a cooling optimization strategy based on the abnormal heat source identification and analysis results, and use the cooling optimization strategy to control the internal temperature of the chemical energy storage container.

[0141] In some optional implementations, the identification and analysis module 1202 includes:

[0142] A construction unit is used to obtain a three-dimensional model of the chemical energy storage container and the layout position of the temperature-sensing optical fiber, and to construct a three-dimensional thermal distribution model based on the three-dimensional model of the chemical energy storage container and the layout position of the temperature-sensing optical fiber;

[0143] A mapping unit, used for interpolating and mapping the temperature data of the optical fiber measuring point to the three-dimensional thermal distribution model to obtain a temperature distribution field;

[0144] Identification unit, used to identify abnormal heat sources in the temperature distribution field and obtain abnormal temperature measurement points;

[0145] The simulation verification unit is used to establish a CFD simulation model, use the CFD simulation model to simulate and verify the abnormal temperature measurement points, and obtain abnormal heat source identification and analysis results.

[0146] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0147] In this embodiment, a temperature control device of a chemical energy storage container temperature control system is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0148] The embodiment of the present invention also provides a computer device having the above Figure 12 A temperature control device of a chemical energy storage container temperature control system is shown.

[0149] See also Figure 13 , Figure 13 is a structural diagram of a computer device provided by an optional embodiment of the present invention, such as Figure 13 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of a GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 13 A processor 10 is taken as an example.

[0150] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0151] The memory 20 stores instructions that can be executed by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0152] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0153] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0154] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0155] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0156] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0157] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A chemical energy storage container temperature control system, characterized in that: include: Temperature sensing optical fiber, distributed optical fiber temperature measurement host and upper controller; The temperature-sensing optical fiber is arranged at a key position inside the chemical energy storage container, the temperature-sensing optical fiber is connected to the distributed optical fiber temperature measurement host, and the distributed optical fiber temperature measurement host is connected to the upper controller; The distributed optical fiber temperature measurement host is used to collect temperature data of optical fiber measurement points inside the chemical energy storage container and send the temperature data of the optical fiber measurement points inside the chemical energy storage container to the host controller; wherein the optical fiber measurement points are set at key positions inside the chemical energy storage container; The upper controller is used to perform abnormal heat source identification and analysis on the temperature data of the optical fiber measuring points inside the chemical energy storage container to obtain abnormal heat source identification and analysis results; The upper controller is further configured to generate a cooling optimization strategy based on the abnormal heat source identification and analysis results, and to use the cooling optimization strategy to regulate the internal temperature of the chemical energy storage container.

2. The system according to claim 1, wherein: The temperature-sensing optical fiber is arranged in the gap channels between the battery packs inside the chemical energy storage container, the top space and the bottom space of the battery rack, and the cooling dead corner area.

3. The system according to claim 1, wherein: The distributed optical fiber temperature measurement host is specifically used to transmit laser pulses to the temperature-sensitive optical fiber at the optical fiber measuring point inside the chemical energy storage container, receive backscattered signals, and calculate the temperature data of the optical fiber measuring point inside the chemical energy storage container based on the backscattered signals.

4. The system according to claim 1, wherein: It also includes: a linkage control device, the linkage control device is connected to the upper controller; the linkage control device includes a fire protection platform and a remote monitoring alarm platform; The fire fighting platform is used to obtain the abnormal heat source identification and analysis results and perform fire fighting based on the abnormal heat source identification and analysis results; The remote monitoring alarm platform is used to obtain the abnormal heat source identification and analysis results, and send an early warning notification based on the abnormal heat source identification and analysis results.

5. A temperature control method for a chemical energy storage container temperature control system, characterized in that: A host controller used in a temperature control system for a chemical energy storage container according to any one of claims 1 to 4; the method comprising: Obtain temperature data of optical fiber measurement points inside the chemical energy storage container sent by the distributed optical fiber temperature measurement host; performing abnormal heat source identification analysis on temperature data of optical fiber measuring points inside the chemical energy storage container to obtain abnormal heat source identification analysis results; A cooling optimization strategy is generated based on the abnormal heat source identification and analysis results, and the internal temperature of the chemical energy storage container is regulated using the cooling optimization strategy.

6. The method according to claim 5, characterized in that The abnormal heat source identification and analysis is performed on the temperature data of the optical fiber measuring points inside the chemical energy storage container to obtain abnormal heat source identification and analysis results, including: Obtaining a three-dimensional model of the chemical energy storage container and the temperature-sensing optical fiber layout positions, and constructing a three-dimensional thermal distribution model based on the three-dimensional model of the chemical energy storage container and the temperature-sensing optical fiber layout positions; Interpolating and mapping the temperature data of the optical fiber measuring points to the three-dimensional thermal distribution model to obtain a temperature distribution field; Identifying abnormal heat sources on the temperature distribution field to obtain abnormal temperature measurement points; A CFD simulation model is established, and the abnormal temperature measurement point is simulated and verified using the CFD simulation model to obtain the abnormal heat source identification and analysis results.

7. A temperature control device for a chemical energy storage container temperature control system, characterized in that: The device comprises: An acquisition module is used to obtain temperature data of optical fiber measurement points inside the chemical energy storage container sent by the distributed optical fiber temperature measurement host; an identification and analysis module for performing abnormal heat source identification and analysis on the temperature data of the optical fiber measuring points inside the chemical energy storage container to obtain abnormal heat source identification and analysis results; The control module is used to generate a cooling optimization strategy based on the abnormal heat source identification and analysis results, and use the cooling optimization strategy to control the internal temperature of the chemical energy storage container.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the temperature control method of the chemical energy storage container temperature control system according to claim 5 or 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, which are used to enable a computer to execute the temperature control method of the chemical energy storage container temperature control system according to claim 5 or 6.

10. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the temperature control method of the chemical energy storage container temperature control system according to claim 5 or 6.

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