A fire alarm control system and method for energy storage power station

Abstract

This invention discloses a fire alarm control system and method for energy storage power stations, belonging to the field of energy storage power station operation. The fire alarm control system includes a fire monitoring system, a fire information processing system, and a fire alarm system. The control method includes: constructing a three-dimensional fire monitoring model using the battery compartment as the fire monitoring unit, and acquiring infrared thermal imaging data; calculating the fire risk coefficient of sub-battery modules and screening sub-battery modules with and without fire risk; calculating the open flame risk coefficient of sub-battery modules with fire risk based on video data acquired by the video acquisition module, and marking them; calculating the predicted combustion coefficient of sub-battery modules without flame; assessing the risk level of the fire based on the calculated risk level coefficient, and generating a fire alarm signal. This greatly improves the reliability of fire alarms in energy storage power stations, realizing early monitoring, timely warning, and rapid response to fire risks in energy storage power stations.

Description

Technical Field

[0001] The present invention relates to the field of energy storage power station operation, and in particular to a fire alarm control system and method for an energy storage power station. Background Art

[0002] As global energy issues become increasingly severe, energy storage technology has developed rapidly as an important means to solve the problems of renewable energy consumption and grid peak and frequency regulation. However, energy storage power stations, especially electrochemical energy storage power stations, have a high risk of fire due to the use of flammable materials such as lithium batteries. In the prior art, a corresponding fire detection or monitoring system is installed in the energy storage power station to monitor the fire in the energy storage power station in real time, but the existing fire alarm system mostly relies on data collected by a single smoke, temperature or gas detector, and has problems such as false alarms, missed alarms and delayed response, and cannot achieve unified and coordinated alarms for multiple data. Therefore, it is urgent to develop a new fire alarm control system and method for energy storage power stations. Summary of the invention

[0003] In view of the above-mentioned deficiencies in the prior art, the present invention provides a fire alarm control system and method for an energy storage power station, which realizes the fire risk warning and fire level alarm functions of the energy storage power station by integrating multiple data monitoring functions.

[0004] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0005] Provided is a fire alarm control system for an energy storage power station, comprising: a fire monitoring system, a fire information processing system and a fire alarm system installed in a battery compartment of the energy storage power station;

[0006] The fire monitoring system includes a smoke sensor, a fire gas sensor, an infrared thermal imager, a video acquisition module, a data processing module, a power supply module and a data transmission module installed on the heat dissipation window of the battery compartment;

[0007] The infrared thermal imager is installed around the battery compartment to monitor the temperature of the sub-battery modules around the battery compartment to form infrared thermal imaging data. The video acquisition module is used to collect video data in the battery compartment with the same viewing angle as the infrared thermal imaging data.

[0008] The smoke sensor is used to detect the smoke concentration in the battery compartment, and the fire gas sensor is used to detect the concentration of fire gas markers in the battery compartment;

[0009] The data processing module is used to process and summarize the collected smoke density, fire gas marker concentration, infrared thermal imaging data and video data, and transmit them to the fire information processing system through the data transmission module; the power module is connected to the power supply outside the battery compartment, and is connected in parallel with the sub-battery module in the battery compartment, and the power module provides power for the fire monitoring system;

[0010] The fire information processing system includes a data analysis module and a monitoring terminal. By analyzing the smoke concentration, fire gas marker concentration, infrared thermal imaging data and video data, a fire alarm signal is generated and sent to the fire alarm system; the monitoring terminal is used to display the fire alarm signal analyzed by the data analysis module;

[0011] The fire alarm system generates alarm information based on the fire alarm signal and sends it to the alarm module in the energy storage power station to execute the alarm action.

[0012] A fire alarm control method for an energy storage power station is provided, which is applied to the above-mentioned fire alarm control system for an energy storage power station, and comprises:

[0013] Step S1: Taking the battery compartment as a fire monitoring unit, a fire monitoring three-dimensional model is constructed according to the size parameters of the battery compartment, and displayed on the monitoring terminal of the fire information processing system; the infrared thermal imager obtains infrared thermal imaging data of the four surfaces of the sub-battery module in the battery compartment;

[0014] Step S2: analyzing the infrared thermal imaging image according to the infrared thermal imaging image data, calculating the fire risk coefficient of the sub-battery module, and screening the sub-battery modules with fire risk and without fire risk;

[0015] Step S3: extracting the frame image of the same viewing angle as the infrared thermal imaging image based on the video data collected by the video acquisition module, analyzing and calculating the open flame risk coefficient of the sub-battery module with fire risk based on the frame image, and marking whether the sub-battery module with fire risk has generated combustion on the monitoring three-dimensional model;

[0016] Step S4: Calculate the predicted combustion coefficient of the sub-battery module without flame;

[0017] Step S5: Calculate the risk level coefficient of this fire according to the calculated fire risk coefficient, open flame risk coefficient and predicted combustion coefficient, evaluate the risk level of this fire, and generate a fire alarm signal.

[0018] Further, step S2 includes:

[0019] Step S21: splitting the infrared thermal imaging image into several temperature evaluation areas according to the size of the sub-battery module, each temperature evaluation area corresponds to a sub-battery module, and graying the infrared thermal imaging image to obtain a thermal imaging grayscale image;

[0020] Step S22: Setting a threshold for the grayscale value of pixels in the thermal imaging grayscale image that represents the fire risk , obtain the grayscale value of each pixel in the temperature assessment area of ​​the thermal imaging grayscale image, and calculate the fire risk coefficient of the sub-battery module ;

[0021] ;

[0022] in, n is the number of pixels in the temperature evaluation area, h i For each temperature assessment area i The gray value of a pixel, m Gray value exceeds the threshold for temperature evaluation area The number of pixels, are the corresponding weight coefficients, and ;

[0023] Step S23: Setting the fire alarm coefficient ;like , it is determined that the sub-battery module corresponding to the temperature evaluation area has a fire risk, and step S24 is executed; otherwise, it is determined that the sub-battery module corresponding to the temperature evaluation area has no fire risk;

[0024] Step S24: repeating steps S22-S23, taking the temperature assessment area where the sub-battery module determined to have a fire risk is located as the center, calculating the fire risk coefficients corresponding to the adjacent temperature assessment areas, and screening out the adjacent sub-battery modules with a fire risk;

[0025] Step S25: After all sub-battery modules with fire risk are screened out, the area of ​​the temperature assessment area is evaluated. s Calculate the area at risk of fire S : ;in, M The number of temperature assessment areas corresponding to the sub-battery modules with fire risks included in the infrared thermal imaging image.

[0026] Further, step S3 includes:

[0027] Step S31: Based on the video data collected by the video acquisition module, extract the frame image with the same viewing angle as the infrared thermal imaging image, grayscale the frame image, and set the grayscale value range of the flame color generated when the sub-battery module burns. ;

[0028] Step S32: extract the image area corresponding to all sub-battery modules with fire risk in the grayscale processed frame image as the flame assessment area, and calculate the open fire risk coefficient according to the grayscale value of the pixels in the flame assessment area f 2;

[0029] ;

[0030] in, For the flame assessment area i The gray value of a pixel, u The number of flame pixels in the flame evaluation area;

[0031] Step S33: Setting the threshold of the open fire risk factor f 阈值 ;

[0032] like , there is a flame in the flame assessment area; the corresponding sub-battery module area is marked in red on the fire monitoring three-dimensional model to indicate the location of the sub-battery module where the combustion occurs;

[0033] like , there is no flame in the flame assessment area, and the corresponding sub-battery module area on the fire monitoring three-dimensional model is marked in yellow, indicating the location of the sub-battery module with fire risk, and executing step S4.

[0034] Furthermore, step S4 is specifically as follows:

[0035] Obtain the flame assessment area where there is no flame, and calculate the predicted combustion coefficient of the sub-battery module corresponding to the flame assessment area where there is no flame according to the temperature value of the flame assessment area where there is no flame on the corresponding infrared thermal imaging image y ;

[0036] ;

[0037] in, Q is the heat generation efficiency of the sub-battery module when it is working normally. is the mass of the sub-battery module, is the reaction heat of the sub-battery module, E is the activation energy of the sub-battery module reaction, R is the temperature fluctuation coefficient of the sub-battery module, It is the maximum temperature value in the flame evaluation area where no flame exists.

[0038] Further, step S5 includes:

[0039] Step S51: Calculate the risk level coefficient of the fire according to the calculated fire risk coefficients, open flame risk coefficients and predicted combustion coefficients of all sub-battery modules with fire risks. D ;

[0040] ;

[0041] in, e Number the sub-battery modules that pose a fire risk. E is the number of sub-battery modules with fire risk, For the e The fire risk factor of each sub-battery module with fire risk, w is the number of the sub-battery module where the fire occurs, For the w The open flame risk factor of a sub-battery module with flames, W is the number of sub-battery modules with flames, x is the number of the sub-battery module corresponding to the flame assessment area where there is no flame, For the x The predicted combustion coefficient of the sub-cell module corresponding to the flame assessment area where there is no flame, are the corresponding weight coefficients, and ;

[0042] Step S52: Setting the coefficient threshold for evaluating the fire level D 阈值 ;like , then generate a high-level fire alarm signal and send it to the fire alarm system. , then a medium-level fire alarm signal is generated and sent to the fire alarm system.

[0043] The beneficial effects of the present invention are as follows: the present invention comprehensively monitors fires in energy storage power stations by integrating infrared temperature monitoring, gas monitoring, smoke monitoring and video monitoring, and can comprehensively analyze the various data collected, realize the classification of fire information / fire alarms, and realize the location of the fire inside the battery compartment, so as to facilitate the staff to respond in time. Fire monitoring uses each battery compartment in the energy storage power station as a monitoring unit and each sub-battery module in the battery compartment as a monitoring object, which can achieve high-precision and sensitive fire alarm response, greatly improving the reliability of fire alarm alarms in energy storage power stations, and realizing early monitoring, timely warning and rapid response to fire risks in energy storage power stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a functional block diagram of a fire alarm control system for an energy storage power station.

[0045] Figure 2Schematic diagram of the area division within the infrared thermal imaging image and the frame image. DETAILED DESCRIPTION

[0046] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0047] like Figure 1 As shown, a fire alarm control system for an energy storage power station includes a fire monitoring system, a fire information processing system and a fire alarm system installed in a battery compartment of the energy storage power station.

[0048] The fire monitoring system includes smoke sensors, fire gas sensors, infrared thermal imagers, video acquisition modules, data processing modules, power modules and data transmission modules installed on the heat dissipation windows of the battery compartment. Internal heat dissipation will be carried out on the heat dissipation windows of the battery compartment, and the flow of air will drive smoke and gas through the heat dissipation windows, so the detection of smoke and gas is more accurate and there will be no blind spots in detection.

[0049] Infrared thermal imagers are installed around the battery compartment to monitor the temperature of the sub-battery modules around the battery compartment to form infrared thermal imaging data. The video acquisition module is used to collect video data in the battery compartment with the same viewing angle as the infrared thermal imaging data.

[0050] The smoke sensor is used to detect the smoke concentration in the battery compartment, and the fire gas sensor is used to detect the concentration of fire gas markers in the battery compartment. Energy storage batteries are generally electrochemical batteries, which produce special gases during the combustion process. For example, the combustion of lithium batteries will produce carbon monoxide, carbon dioxide, methane, and carbon fluoride. The monitoring of smoke concentration or fire gas marker concentration can be used to assess whether a fire has occurred.

[0051] The data processing module is used to process and summarize the collected smoke concentration, fire gas marker concentration, infrared thermal imaging data and video data, and transmit them to the fire information processing system through the data transmission module; the power module is connected to the power supply outside the battery compartment and is connected in parallel with the sub-battery module in the battery compartment. The power module provides power for the fire monitoring system to avoid failure of the entire system when a fire occurs in the battery compartment and the power is cut off.

[0052] The fire information processing system includes a data analysis module and a monitoring terminal. By analyzing the smoke density, fire gas marker concentration, infrared thermal imaging data and video data, a fire alarm signal is generated and sent to the fire alarm system; the monitoring terminal is used to display the fire alarm signal analyzed by the data analysis module, as well as various types of monitoring data;

[0053] The fire alarm system generates alarm information based on the fire alarm signal and sends it to the alarm module in the energy storage power station to execute alarm actions, such as executing emergency fire alarm based on high-level fire alarm signals and executing general fire alarm based on intermediate fire alarm signals.

[0054] A fire alarm control method for an energy storage power station, applied to the above-mentioned fire alarm control system for an energy storage power station, comprises:

[0055] Step S1: Taking the battery compartment as the fire monitoring unit, a three-dimensional fire monitoring model is constructed according to the size parameters of the battery compartment, and displayed on the monitoring terminal of the fire information processing system. Through the subsequent fire risk marking of the sub-battery module, it is convenient for the staff to intuitively obtain the risk location and handle or investigate it in time; the infrared thermal imager obtains the infrared thermal imaging data of the four sides of the sub-battery module in the battery compartment, and fire monitoring can be achieved from all four sides without blind spots in monitoring.

[0056] The battery compartment is made up of a number of stacked sub-battery modules, which are connected in series or in parallel. Fire monitoring is achieved by performing temperature and video data analysis on the stacking surface formed by the sub-battery modules. The fire risk location and the fire occurrence location can also be located accurately to a single sub-battery module.

[0057] Step S2: Analyze the infrared thermal imaging image according to the infrared thermal imaging image data, calculate the fire risk coefficient of the sub-battery module, and screen the sub-battery modules with fire risk and without fire risk. Step S2 specifically includes:

[0058] Step S21: splitting the infrared thermal imaging image into several temperature evaluation areas according to the size of the sub-battery module, each temperature evaluation area corresponds to a sub-battery module, and graying the infrared thermal imaging image to obtain a thermal imaging grayscale image;

[0059] Step S22: Setting a threshold for the grayscale value of pixels in the thermal imaging grayscale image that represents the fire risk , obtain the grayscale value of each pixel in the temperature assessment area of ​​the thermal imaging grayscale image, and calculate the fire risk coefficient of the sub-battery module ;

[0060] ;

[0061] in,n is the number of pixels in the temperature evaluation area, h i For each temperature assessment area i The gray value of a pixel, m Gray value exceeds the threshold for temperature evaluation area H 阈值 The number of pixels, m The initial value of is 0. are the corresponding weight coefficients, and ; Fire risk factor f 1 indicates that the sub-battery module is hot, and the fire risk factor is f 1. The larger the sub-battery module, the more heat it generates.

[0062] Step S23: Setting the fire alarm coefficient ;like , it is determined that the sub-battery module corresponding to the temperature evaluation area has a fire risk, and step S24 is executed; otherwise, it is determined that the sub-battery module corresponding to the temperature evaluation area has no fire risk;

[0063] Step S24: repeating steps S22-S23, taking the temperature assessment area where the sub-battery module determined to have a fire risk is located as the center, calculating the fire risk coefficients corresponding to the adjacent temperature assessment areas, and screening out the adjacent sub-battery modules with a fire risk;

[0064] Step S25: After all sub-battery modules with fire risk are screened out, the area of ​​the temperature assessment area is evaluated. s Calculate the area at risk of fire S : ;in, M The number of temperature assessment areas corresponding to the sub-battery modules with fire risks included in the infrared thermal imaging image. Area of ​​fire risk S It indicates the area of ​​the sub-battery module where there is a risk of fire. The larger the area, the higher the fire risk level.

[0065] Step S3: according to the video data collected by the video acquisition module, a frame image with the same viewing angle as the infrared thermal imaging image is extracted, and the region division of the frame image and the infrared thermal imaging image is the same, such as Figure 2 As shown, the open flame risk coefficient of the sub-battery module with fire risk is calculated based on the frame image analysis, and whether the sub-battery module with fire risk has generated combustion is marked on the monitoring three-dimensional model;

[0066] Step S3 specifically includes:

[0067] Step S31: Based on the video data collected by the video acquisition module, extract the frame image with the same viewing angle as the infrared thermal imaging image, grayscale the frame image, and set the grayscale value range of the flame color generated when the sub-battery module burns. ;

[0068] Step S32: extract the image area corresponding to all sub-battery modules with fire risk in the grayscale processed frame image as the flame assessment area, and calculate the open fire risk coefficient according to the grayscale value of the pixels in the flame assessment area f 2;

[0069] ;

[0070] in, For the flame assessment area i The gray value of a pixel, u is the number of flame pixels in the flame evaluation area, u The initial value of is 0;

[0071] Step S33: Setting the threshold of the open fire risk factor f 阈值 ;

[0072] like , there is a flame in the flame assessment area; the corresponding sub-battery module area is marked in red on the fire monitoring three-dimensional model, indicating the location of the sub-battery module generating the combustion in the battery compartment;

[0073] like , there is no flame in the flame assessment area, and the corresponding sub-battery module area on the fire monitoring three-dimensional model is marked in yellow, indicating the location of the sub-battery module with fire risk in the battery compartment, and executing step S4.

[0074] Step S4: Calculate the predicted combustion coefficient of the sub-battery module without flame. Step S4 is specifically as follows:

[0075] Obtain the flame assessment area where there is no flame, and calculate the predicted combustion coefficient of the sub-battery module corresponding to the flame assessment area where there is no flame according to the temperature value of the flame assessment area where there is no flame on the corresponding infrared thermal imaging image y ;

[0076] ;

[0077] in, Q is the heat generation efficiency of the sub-battery module when it is working normally. is the mass of the sub-battery module, is the reaction heat of the sub-battery module, E is the activation energy of the sub-battery module reaction,R is the temperature fluctuation coefficient of the sub-battery module, The maximum temperature value in the flame evaluation area without flame is used to predict the combustion coefficient y Indicates the ability of the sub-battery module to burn during the heating process. The larger the value, the easier it is to burn.

[0078] Step S5: Calculate the risk level coefficient of this fire according to the calculated fire risk coefficient, open flame risk coefficient and predicted combustion coefficient, evaluate the risk level of this fire, and generate a fire alarm signal.

[0079] Step S5 specifically includes:

[0080] Step S51: Calculate the risk level coefficient of the fire according to the calculated fire risk coefficient, open flame risk coefficient and predicted combustion coefficient of all sub-battery modules with fire risk D ;

[0081] ;

[0082] in, e Number the sub-battery modules that pose a fire risk. E is the number of sub-battery modules with fire risk, For the e The fire risk factor of each sub-battery module with fire risk, w is the number of the sub-battery module where the fire occurs, For the w The open flame risk factor of a sub-battery module with flames, W is the number of sub-battery modules with flames, x is the number of the sub-battery module corresponding to the flame assessment area where there is no flame, For the x The predicted combustion coefficient of the sub-cell module corresponding to the flame assessment area where there is no flame, are the corresponding weight coefficients, and ;

[0083] Step S52: Setting the coefficient threshold for evaluating the fire level D 阈值 ;like , then generate a high-level fire alarm signal and send it to the fire alarm system. , then a medium-level fire alarm signal is generated and sent to the fire alarm system.

[0084] The present invention comprehensively monitors fires in energy storage power stations by integrating infrared temperature monitoring, gas monitoring, smoke monitoring and video monitoring, and can comprehensively analyze the various data collected to achieve classification of fire information / fire alarms, as well as positioning of the location of fires inside the battery compartment, so that staff can respond in a timely manner. Fire monitoring uses each battery compartment in the energy storage power station as a monitoring unit and each sub-battery module in the battery compartment as a monitoring object, which can achieve high-precision and sensitive fire alarm response, greatly improving the reliability of fire alarm alarms in energy storage power stations, and achieving early monitoring, timely warning and rapid response to fire risks in energy storage power stations.

Claims

1. A fire alarm control method for an energy storage power station, applied to a fire alarm control system for an energy storage power station, the fire alarm control system for an energy storage power station comprising: Fire monitoring systems, fire information processing systems and fire alarm systems installed in the battery compartments of energy storage power stations; The fire monitoring system includes a smoke sensor, a fire gas sensor, an infrared thermal imager, a video acquisition module, a data processing module, a power module and a data transmission module; the smoke sensor and the fire gas sensor are installed on the heat dissipation window of the battery compartment; The infrared thermal imager is installed around the battery compartment to monitor the temperature of the sub-battery modules around the battery compartment to form infrared thermal imaging data, and the video acquisition module is used to acquire video data in the battery compartment with the same viewing angle as the infrared thermal imaging data; The smoke sensor is used to detect the smoke concentration in the battery compartment, and the fire gas sensor is used to detect the concentration of fire gas markers in the battery compartment; The data processing module is used to process and summarize the collected smoke density, fire gas marker concentration, infrared thermal imaging data and video data, and transmit them to the fire information processing system through the data transmission module; the power module is connected to the power supply outside the battery compartment, and is connected in parallel with the sub-battery module in the battery compartment, and the power module provides power for the fire monitoring system; The fire information processing system includes a data analysis module and a monitoring terminal, which generates a fire alarm signal and sends it to the fire alarm system by analyzing the smoke concentration, fire gas marker concentration, infrared thermal imaging data and video data; the monitoring terminal is used to display the fire alarm signal analyzed by the data analysis module; The fire alarm system generates alarm information according to the fire alarm signal and sends it to the alarm module in the energy storage power station to execute the alarm action; The invention is characterized by comprising: Step S1: Taking the battery compartment as a fire monitoring unit, a fire monitoring three-dimensional model is constructed according to the size parameters of the battery compartment, and displayed on the monitoring terminal of the fire information processing system; the infrared thermal imager obtains infrared thermal imaging data of the four surfaces of the sub-battery module in the battery compartment; Step S2: analyzing the infrared thermal imaging image according to the infrared thermal imaging image data, calculating the fire risk coefficient of the sub-battery module, and screening the sub-battery modules with fire risk and without fire risk; Step S3: extracting the frame image of the same viewing angle as the infrared thermal imaging image based on the video data collected by the video acquisition module, analyzing and calculating the open flame risk coefficient of the sub-battery module with fire risk based on the frame image, and marking whether the sub-battery module with fire risk has generated combustion on the monitoring three-dimensional model; Step S4: Calculate the predicted combustion coefficient of the sub-battery module without flame; Step S5: Calculate the risk level coefficient of the fire according to the calculated fire risk coefficient, open flame risk coefficient and predicted combustion coefficient, evaluate the risk level of the fire, and generate a fire alarm signal; The step S2 comprises: Step S21: splitting the infrared thermal imaging image into several temperature evaluation areas according to the size of the sub-battery module, each temperature evaluation area corresponds to a sub-battery module, and graying the infrared thermal imaging image to obtain a thermal imaging grayscale image; Step S22: Setting a threshold for the grayscale value of pixels in the thermal imaging grayscale image that represents the fire risk , obtain the grayscale value of each pixel in the temperature assessment area of ​​the thermal imaging grayscale image, and calculate the fire risk coefficient of the sub-battery module ; ； in, n is the number of pixels in the temperature evaluation area, h i For each temperature assessment area i The gray value of a pixel, m Gray values ​​in the temperature evaluation area exceed the threshold The number of pixels, are the corresponding weight coefficients, and ; Step S23: Setting the fire alarm coefficient ;like , it is determined that the sub-battery module corresponding to the temperature evaluation area has a fire risk, and step S24 is executed; otherwise, it is determined that the sub-battery module corresponding to the temperature evaluation area has no fire risk; Step S24: repeating steps S22-S23, taking the temperature assessment area where the sub-battery module determined to have a fire risk is located as the center, calculating the fire risk coefficients corresponding to the adjacent temperature assessment areas, and screening out the adjacent sub-battery modules with a fire risk; Step S25: After all sub-battery modules with fire risk are screened out, the area of ​​the temperature assessment area is evaluated. s Calculate the area at risk of fire S : ;in, M The number of temperature assessment areas corresponding to the sub-battery modules with fire risks included in the infrared thermal imaging image; The step S3 comprises: Step S31: Based on the video data collected by the video acquisition module, extract the frame image with the same viewing angle as the infrared thermal imaging image, grayscale the frame image, and set the grayscale value range of the flame color generated when the sub-battery module burns. ; Step S32: extract the image area corresponding to all sub-battery modules with fire risk in the grayscale processed frame image as the flame assessment area, and calculate the open fire risk coefficient according to the grayscale value of the pixels in the flame assessment area f 2; ； in, For the flame assessment area i The gray value of a pixel, u is the number of flame pixels in the flame assessment area; Step S33: Setting the threshold of the open fire risk factor f 阈值 ; like , there is a flame in the flame assessment area; the corresponding sub-battery module area is marked in red on the fire monitoring three-dimensional model to indicate the location of the sub-battery module where the combustion occurs; like , then there is no flame in the flame assessment area, and the corresponding sub-battery module area on the fire monitoring three-dimensional model is marked in yellow, indicating the location of the sub-battery module with fire risk, and executing step S4; The step S4 is specifically as follows: Obtain the flame assessment area where there is no flame, and calculate the predicted combustion coefficient of the sub-battery module corresponding to the flame assessment area where there is no flame according to the temperature value of the flame assessment area where there is no flame on the corresponding infrared thermal imaging image y ; ； in, Q is the heat generation efficiency of the sub-battery module when it is working normally. is the mass of the sub-battery module, is the reaction heat of the sub-battery module, E is the activation energy of the sub-battery module reaction, R is the temperature fluctuation coefficient of the sub-battery module, It is the maximum temperature value in the flame evaluation area where no flame exists.

2. The fire alarm control method for energy storage power station according to claim 1, characterized in that: The step S5 comprises: Step S51: Calculate the risk level coefficient of the fire according to the calculated fire risk coefficient, open flame risk coefficient and predicted combustion coefficient of all sub-battery modules with fire risk D ; ； in, e Number the sub-battery modules that pose a fire risk, E is the number of sub-battery modules with fire risk, For the e The fire risk factor of each sub-battery module with fire risk, w is the number of the sub-battery module where the fire occurs, For the w The open flame risk factor of a sub-battery module with flames, W is the number of sub-battery modules with flames, x is the number of the sub-battery module corresponding to the flame assessment area where there is no flame, For the x The predicted combustion coefficient of the sub-cell module corresponding to the flame assessment area where there is no flame, are the corresponding weight coefficients, and ; Step S52: Setting the coefficient threshold for evaluating the fire level D 阈值 ;like , then generate a high-level fire alarm signal and send it to the fire alarm system. , then a medium-level fire alarm signal is generated and sent to the fire alarm system.

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