Fire fighting method and system for energy storage power station

Abstract

The embodiment of the invention relates to the technical field of fire control management, and particularly discloses a fire control method and system for an energy storage power station. According to the embodiment of the invention, whether the operation is abnormal or not is judged, and if yes, whether the fire risk exists or not is judged; acquiring fire-fighting monitoring data when the fire-fighting risk exists; when the fire-fighting danger exists, determining a fire-fighting direct danger sub-area and a plurality of fire-fighting indirect danger sub-areas; fire-fighting danger alarms of different grades are carried out; and direct and synergistic fire extinguishing treatment is carried out. According to the invention, operation monitoring can be carried out, whether a fire-fighting risk exists or not is judged when operation abnormity exists, fire-fighting monitoring response is carried out when the fire-fighting risk exists, fire-fighting danger alarms of different grades are carried out when fire-fighting danger exists, and direct fire extinguishing treatment and collaborative fire extinguishing treatment are carried out on a target danger range. The intelligent degree of fire-fighting management of the energy storage power station is effectively improved, and rapid fire early warning, monitoring and emergency disposal are realized.

Description

Technical Field

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

[0002] Energy storage power stations usually contain a large number of battery packs or other forms of energy storage devices, which may cause fires or other safety accidents under certain conditions, so fire management is particularly important.

[0003] Fire management of energy storage power stations refers to a complete set of management and operation processes implemented to ensure the safe operation of energy storage power stations. It aims to reduce fire risks and protect the safety of personnel and property through effective prevention, monitoring and response measures.

[0004] In the prior art, the fire management of energy storage power stations is not highly intelligent and usually needs to be combined with manual fire management to achieve fire protection needs, resulting in a certain delay in the emergency response time of fire management and the inability to achieve rapid fire warning, monitoring and emergency response. Summary of the invention

[0005] The purpose of the embodiments of the present invention is to provide a fire protection method and system for an energy storage power station, aiming to solve the problems raised in the background technology.

[0006] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions: A fire fighting method for an energy storage power station, the method specifically comprising the following steps: Determine a target power station area of ​​a target energy storage power station, perform operation monitoring on the target power station area, determine whether there is an operation abnormality, and if there is an operation abnormality, determine whether there is a fire risk; When there is a fire risk, determining a fire risk sub-area, performing fire monitoring response on the fire risk sub-area, and acquiring fire monitoring data; Analyzing the fire monitoring data to determine whether there is a fire hazard, and if there is a fire hazard, determining a direct fire hazard sub-area and a plurality of indirect fire hazard sub-areas; Providing fire hazard alarms of different levels to the direct fire hazard sub-area and the plurality of indirect fire hazard sub-areas; A target danger range in the direct fire danger sub-area is determined, and direct fire extinguishing treatment and coordinated fire extinguishing treatment are performed on the target danger range.

[0007] As a further limitation of the technical solution of the embodiment of the present invention, the step of determining the target power station area of ​​the target energy storage power station, performing operation monitoring on the target power station area, judging whether there is an operation abnormality, and judging whether there is a fire risk when there is an operation abnormality specifically includes the following steps: Determine the target power station area of ​​the target energy storage power station; Generate operation monitoring instructions; According to the operation monitoring instruction, real-time operation monitoring is performed on the target power station area to obtain operation monitoring data; Analyze the operation monitoring data to determine whether there is any operation abnormality; When there is an operation abnormality, identify the abnormal operation type and determine whether there is a fire risk.

[0008] The fire protection system of the energy storage power station includes an operation monitoring and analysis unit, a fire monitoring and response unit, a fire hazard judgment unit, a fire hazard alarm unit and a target fire extinguishing processing unit, wherein: An operation monitoring and analysis unit, used to determine a target power station area of ​​a target energy storage power station, perform operation monitoring on the target power station area, determine whether there is an operation abnormality, and if there is an operation abnormality, determine whether there is a fire risk; A fire monitoring and response unit, used to determine a fire risk sub-area when there is a fire risk, perform fire monitoring and response on the fire risk sub-area, and obtain fire monitoring data; a fire risk judgment unit, configured to analyze the fire monitoring data, judge whether there is a fire risk, and determine a direct fire risk sub-area and a plurality of indirect fire risk sub-areas when there is a fire risk; A fire hazard alarm unit, used for performing fire hazard alarms of different levels for the direct fire hazard sub-area and a plurality of the indirect fire hazard sub-areas; The target fire extinguishing processing unit is used to determine the target danger range in the fire direct danger sub-area, and perform direct fire extinguishing processing and coordinated fire extinguishing processing on the target danger range.

[0009] Compared with the prior art, the present invention has the following beneficial effects: The embodiment of the present invention determines whether there is an operation abnormality, and when there is an operation abnormality, determines whether there is a fire risk; when there is a fire risk, obtains fire monitoring data; when there is a fire hazard, determines a direct fire hazard sub-area and multiple indirect fire hazard sub-areas; performs different levels of fire hazard alarms; and performs direct and coordinated fire extinguishing. It is capable of performing operation monitoring, determining whether there is a fire risk when there is an operation abnormality, and performing fire monitoring response when there is a fire risk, performing different levels of fire hazard alarms when there is a fire hazard, and performing direct fire extinguishing and coordinated fire extinguishing on the target hazard range, effectively improving the intelligent level of fire management of energy storage power stations, and realizing rapid fire early warning, monitoring and emergency disposal. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention.

[0011] Figure 1 A flow chart of a method provided by an embodiment of the present invention is shown.

[0012] Figure 2 A flow chart of running monitoring fire risk judgment in the method provided by an embodiment of the present invention is shown.

[0013] Figure 3 A flow chart of fire monitoring response in the method provided by an embodiment of the present invention is shown.

[0014] Figure 4 A flow chart of positioning a fire risk sub-area in the method provided by an embodiment of the present invention is shown.

[0015] Figure 5 A flow chart of different levels of fire hazard alarms in the method provided by an embodiment of the present invention is shown.

[0016] Figure 6 The flowchart of direct fire extinguishing processing and coordinated fire extinguishing processing in the method provided by the embodiment of the present invention is shown.

[0017] Figure 7 The application architecture diagram of the system provided by the embodiment of the present invention is shown.

[0018] Figure 8 A structural block diagram of an operation monitoring and analysis unit in a system provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] It is understandable that in the prior art, the fire management of energy storage power stations is not highly intelligent and usually needs to be combined with manual fire management to achieve fire protection needs, resulting in a certain delay in the emergency response time of fire management and the inability to achieve rapid fire warning, monitoring and emergency response.

[0021] To solve the above problems, the embodiment of the present invention determines the target power station area of ​​the target energy storage power station, performs operation monitoring on the target power station area, determines whether there is an operation abnormality, and determines whether there is a fire risk when there is an operation abnormality; determines a fire risk sub-area when there is a fire risk, performs fire monitoring response on the fire risk sub-area, and obtains fire monitoring data; analyzes the fire monitoring data to determine whether there is a fire hazard, and determines a direct fire hazard sub-area and multiple indirect fire hazard sub-areas when there is a fire hazard; performs different levels of fire hazard alarms on the direct fire hazard sub-area and multiple indirect fire hazard sub-areas; determines the target hazard range in the direct fire hazard sub-area, and performs direct fire extinguishing and coordinated fire extinguishing on the target hazard range. It is possible to perform operation monitoring, determine whether there is a fire risk when there is an operation abnormality, and perform fire monitoring response when there is a fire risk, perform different levels of fire hazard alarms when there is a fire hazard, and perform direct fire extinguishing and coordinated fire extinguishing on the target hazard range, effectively improving the intelligent level of fire management of the energy storage power station, and realizing rapid fire early warning, monitoring and emergency disposal.

[0022] Figure 1 A flow chart of a method provided by an embodiment of the present invention is shown.

[0023] Specifically, in a preferred embodiment of the present invention, a fire fighting method for an energy storage power station comprises the following steps: Step S101, determining a target power station area of ​​a target energy storage power station, performing operation monitoring on the target power station area, determining whether there is an operation abnormality, and if there is an operation abnormality, determining whether there is a fire risk.

[0024] In an embodiment of the present invention, a target power station area of ​​a target energy storage power station is determined, an operation monitoring instruction is generated, and then real-time operation monitoring is performed on the target power station area according to the operation monitoring instruction to obtain operation monitoring data including voltage, current, temperature, power, internal resistance, humidity, etc., wherein voltage, current, power and internal resistance are internal impact data, and temperature and humidity are internal impact data. The operation monitoring data is then analyzed to determine whether there is an operation abnormality, and when there is an operation abnormality, the abnormal operation type is identified, and according to the abnormal operation type, whether there is a fire risk is determined. Specifically, when the abnormal operation type is related to the fire risk, it is determined that there is a fire risk, for example: abnormal temperature increase; when the abnormal operation type is not related to the fire risk, it is determined that there is no fire risk, for example: abnormal humidity increase.

[0025] Specifically, Figure 2 A flow chart of running monitoring fire risk judgment in the method provided by an embodiment of the present invention is shown.

[0026] Among them, in the preferred embodiment provided by the present invention, the determination of the target power station area of ​​the target energy storage power station, the operation monitoring of the target power station area, the determination of whether there is an operation abnormality, and when there is an operation abnormality, the determination of whether there is a fire risk specifically includes the following steps: Step S1011, determining a target power station area of ​​a target energy storage power station; Step S1012, generating an operation monitoring instruction; Step S1013, performing real-time operation monitoring on the target power station area according to the operation monitoring instruction, and acquiring operation monitoring data; Step S1014, analyzing the operation monitoring data to determine whether there is an operation abnormality; Step S1015, when there is an operation abnormality, identifying the abnormal operation type and determining whether there is a fire risk.

[0027] Among them, in the preferred embodiment provided by the present invention, analyzing the operation monitoring data to determine whether there is an operation abnormality specifically includes the following steps: The principal component analysis operation is used on the operation monitoring data to obtain the key features. The corresponding process has the following relationship: ; in, Represents operation monitoring data, with dimensions of , represents the number of samples, represents the number of features, Represents the weight matrix of PCA, with dimension , the dimension is , represents the number of principal components, Represents the key features, and the dimension is ; The key features are nonlinearly mapped using radial basis functions to obtain nonlinear mapping features. The nonlinear mapping features include internal influence features and external influence features. The corresponding process has the following relationship: ; ; in, represents the nonlinear mapping feature, Represent the internal influence characteristics and external influence characteristics respectively, represents the number of centers of RBF, Indicates i The weights of the radial basis functions, Indicates i The center of the radial basis function, represents radial basis function.

[0028] The state transfer matrix is ​​multiplied by the internal influence feature as the linear transfer part, the neural network is used to process the internal influence feature as the nonlinear disturbance part, and then the control matrix is ​​introduced, and the external influence feature is multiplied by the control matrix as the external influence part. The state transfer model is constructed based on the linear transfer part, the nonlinear disturbance part and the external influence part. The corresponding process has the following relationship: ; in, Indicates time t status, represents the state transfer matrix, Indicates time t -1 internal impact characteristics, Indicates time t -1 external influence characteristics, represents the control matrix, represents a pre-trained neural network; The operation monitoring data at each time point is taken as a state, and different states are input into the state transition model to obtain the probability distribution of different states. The corresponding process has the following relationship: ; in, represents the probability distribution of the state at time t, represents the state transition model, represents a probability mapping operation; The weighted sum of the probability distributions of different states is used as the anomaly scoring result; ; in, Indicates time t The abnormal scoring results of Indicates n The weight of the state probability; The scoring threshold is dynamically calculated based on the mean and standard deviation of historical data. The abnormal scoring result is compared with the scoring threshold. The comparison result is used to determine whether there is an operational abnormality. The corresponding process has the following relationship: ; ; in, represents the scoring threshold, represents the historical mean, represents the historical standard deviation, represents the adjustment factor, Represents a Boolean value.

[0029] In an embodiment of the present invention, in the process of constructing a state transition model, the present invention introduces a neural network for nonlinear modeling, which can identify complex disturbances that may be ignored by traditional linear models. The state transition model is able to track and predict the time series evolution of data and identify abnormal behaviors that change over time. This is particularly useful for detecting progressive or periodic anomalies. In addition, a dynamic scoring threshold is set, which can be automatically adjusted according to the statistical characteristics of historical data, adapt to different operating conditions and environmental changes, and can maintain a low misjudgment rate under different loads and operating conditions, thereby improving the accuracy of anomaly detection.

[0030] Among them, in the preferred embodiment provided by the present invention, when there is an operation abnormality, identifying the abnormal operation type and judging whether there is a fire risk specifically includes the following steps: Get the abnormal feature vector when the operation is abnormal; The abnormal feature vector is divided into multiple perspective features, each perspective feature corresponds to a different type of operation monitoring data, and the corresponding process has the following relationship: ; in, represents the eigenvector in sequence, represents the j-th viewing angle feature; The K-means clustering method is used to cluster each view feature, and the clustering result of each view is obtained. The corresponding process has the following relationship: ; in, Indicates j The first v The clustering results are Represents K-means clustering operation; Assign weights to the clustering results from different perspectives, and then use the consensus clustering method to aggregate and obtain the overall clustering results. The corresponding process has the following relationship: ; in, represents the overall clustering result, represents the consensus clustering operation, Indicates j The weight of the clustering results of each perspective; According to the domain knowledge, fuzzy rules are formulated, and the specific values ​​in the overall clustering results are converted into fuzzy sets using membership functions. The corresponding process of converting the specific values ​​in the overall clustering results into fuzzy sets using membership functions has the following relationship: ; in, represents the membership function, represents the cluster center value, represents the spread parameter of the cluster; Match fuzzy sets with fuzzy rules to obtain fuzzy outputs; The centroid method is used to calculate the centroid of the fuzzy output to obtain the abnormal mode. The corresponding process has the following relationship: ; in, represents the centroid of the fuzzy output, Indicates fuzzy output; The probability of fire incidents in the statistical abnormal mode in history is used to determine the fire risk of the current abnormal mode. The corresponding process has the following relationship: ; in, Represents the centroid of a given fuzzy output The probability of fire risk under

[0031] In the embodiment of the present invention, the present invention adopts a multi-perspective clustering method to capture the diversity of data, avoid the limitations of a single perspective, affect the accuracy of subsequent fire risk judgments, and integrate information from each perspective through weighted and consensus methods to improve the stability and accuracy of clustering results. In addition, the present invention designs a fuzzy logic system that can simultaneously process information from multiple feature dimensions, and comprehensively consider the influence of multiple factors through rule reasoning, so as to more accurately identify abnormal patterns, and then effectively convert complex clustering results into specific abnormal patterns. The computational complexity of the fuzzy logic system is relatively low, and it is suitable for real-time anomaly detection and response, and is more applicable to fields such as fire safety that require timely response.

[0032] Furthermore, the fire fighting method of the energy storage power station further comprises the following steps: Step S102, when there is a fire risk, determining a fire risk sub-area, performing fire monitoring response on the fire risk sub-area, and acquiring fire monitoring data.

[0033] In an embodiment of the present invention, in the event of a fire risk, a fire risk sub-area is located from the target power station area, and then a targeted fire monitoring instruction is generated based on the fire risk sub-area. Then, according to the fire monitoring instruction, a fire monitoring response is performed on the fire risk sub-area to obtain fire monitoring data including temperature, smoke, flame, etc.

[0034] Specifically, Figure 3 A flow chart of fire monitoring response in the method provided by an embodiment of the present invention is shown.

[0035] Among them, in the preferred implementation manner provided by the present invention, when there is a fire risk, determining a fire risk sub-area, performing fire monitoring response on the fire risk sub-area, and obtaining fire monitoring data specifically include the following steps: Step S1021, when there is a fire risk, determining a fire risk sub-area; Step S1022, generating a fire monitoring instruction according to the fire risk sub-area; Step S1023: According to the fire monitoring instruction, a fire monitoring response is performed on the fire risk sub-area to obtain fire monitoring data.

[0036] Furthermore, the fire fighting method of the energy storage power station further comprises the following steps: Step S103, analyzing the fire monitoring data to determine whether there is a fire hazard, and if there is a fire hazard, determining a direct fire hazard sub-area and a plurality of indirect fire hazard sub-areas.

[0037] In an embodiment of the present invention, feature recognition is performed on fire monitoring data according to preset hazard feature data to determine whether there is a fire hazard. If it is determined that there is a fire hazard, direct positioning instructions and indirect positioning instructions are generated, and then according to the direct positioning instructions, the direct fire hazard sub-area is determined. According to the indirect positioning instructions, the spread impact of the fire hazard in the direct fire hazard sub-area is analyzed to determine multiple indirect fire hazard sub-areas.

[0038] Specifically, Figure 4 A flow chart of positioning a fire risk sub-area in the method provided by an embodiment of the present invention is shown.

[0039] Among them, in the preferred embodiment provided by the present invention, the analyzing of the fire monitoring data to determine whether there is a fire hazard, and when there is a fire hazard, determining a direct fire hazard sub-area and a plurality of indirect fire hazard sub-areas specifically comprises the following steps: Step S1031, performing feature recognition on the fire monitoring data according to preset danger feature data to determine whether there is fire danger; Step S1032, when there is a fire risk, generating a direct positioning instruction and an indirect positioning instruction; Step S1033, determining the fire direct danger sub-area according to the direct positioning instruction; Step S1034: perform a fire risk spreading impact analysis according to the indirect positioning instruction, and determine a plurality of fire risk indirect sub-areas.

[0040] Among them, in the preferred implementation mode provided by the present invention, according to the indirect positioning instruction, the spread impact analysis of the fire risk is performed, and the determination of multiple fire indirect risk sub-areas specifically includes the following steps: Divide the energy storage power station area into grids to obtain multiple grid units; Mark the grid cells where fire risk has been detected as direct danger areas, and initialize the risk value of the direct danger area to the highest risk value, and set the initial risk values ​​of other grid cells to zero; Assign a corresponding weight to each grid cell according to the distance from the direct danger area; Obtain the environmental parameters in each grid cell. The environmental parameters include multiple environmental factors. Based on the guidance of experienced experts, obtain the fire protection impact values ​​of different environmental factors. Calculate the fuzzy membership of each environmental factor in each grid cell, and multiply the fuzzy membership of each environmental factor by the corresponding fire protection impact value to obtain the environmental impact value of each environmental factor; The environmental impact values ​​of different environmental factors in each grid are summed up to obtain the comprehensive environmental impact value of the grid; The initial risk of the current cell is updated by taking the weighted sum of the risk values ​​of the adjacent grid cells of the current grid cell and the weight of the corresponding grid cell; Traverse all grid cells according to the time step, update the initial risk values ​​of all grid cells to simulate the spread of risk from the direct danger area to the nearby area, and obtain the cumulative risk value of each grid cell; The comprehensive environmental impact value of each grid unit is multiplied by the cumulative risk value as the comprehensive risk value of the corresponding grid unit; Based on the comprehensive risk value of each grid unit, multiple fire indirect hazard sub-areas are determined.

[0041] In the embodiment of the present invention, the present invention can simulate the trend of fire danger spreading in space in detail through grid processing. This refined processing can better identify potential danger areas, even if they are far away from the direct danger area. In addition, the present invention uses fuzzy logic methods to comprehensively consider various environmental factors, such as temperature, humidity and wind speed. This enables the present invention to dynamically adjust risk assessments to reflect the impact of real-time environmental changes, thereby improving the accuracy and flexibility of assessments.

[0042] Furthermore, the fire fighting method of the energy storage power station further comprises the following steps: Step S104, issuing fire hazard alarms of different levels to the direct fire hazard sub-area and the plurality of indirect fire hazard sub-areas.

[0043] In an embodiment of the present invention, by generating a fire emergency alarm instruction and a fire impact alarm instruction, the fire emergency alarm instruction is sent to a direct fire hazard sub-area, and the fire impact alarm instruction is sent to multiple indirect fire hazard sub-areas, so that a first-level fire hazard alarm is performed in the direct fire hazard sub-area through the fire emergency alarm instruction, and a second-level fire hazard alarm is performed in multiple indirect fire hazard sub-areas through the fire impact alarm instruction, so as to realize different levels of fire hazard alarms in sub-areas with different dangerous situations in the target energy storage power station.

[0044] Specifically, Figure 5 A flow chart of different levels of fire hazard alarms in the method provided by an embodiment of the present invention is shown.

[0045] Among them, in the preferred embodiment provided by the present invention, the fire hazard alarming of different levels for the direct fire hazard sub-area and the plurality of indirect fire hazard sub-areas specifically comprises the following steps: Step S1041, generating a fire emergency alarm instruction and a fire impact alarm instruction; Step S1042, sending the fire emergency alarm instruction to the fire direct danger sub-area, and sending the fire impact alarm instruction to a plurality of the fire indirect danger sub-areas; Step S1043, through the fire emergency alarm instruction, a first-level fire danger alarm is issued in the fire direct danger sub-area; Step S1044: A second-level fire hazard alarm is issued in a plurality of the fire indirect hazard sub-areas through the fire impact alarm instruction.

[0046] Furthermore, the fire fighting method of the energy storage power station further comprises the following steps: Step S105, determining a target danger range in the direct fire danger sub-area, and performing direct fire extinguishing processing and coordinated fire extinguishing processing on the target danger range.

[0047] In an embodiment of the present invention, a target dangerous range that is in fire danger in a direct fire danger sub-area is determined, a direct fire extinguishing instruction and a coordinated fire extinguishing instruction are generated, and multiple coordinated fire extinguishing sub-areas are determined. The direct fire extinguishing instruction is then sent to the direct fire danger sub-area, and direct fire extinguishing treatment (perfluorohexanone fire extinguishing, fine water mist fire extinguishing, etc.) is performed on the target dangerous range, and the coordinated fire extinguishing instruction is sent to multiple coordinated fire extinguishing sub-areas, and coordinated fire extinguishing treatment is performed on the target dangerous range (coordinated transportation of fire extinguishing equipment through drones, mobile vehicles, etc.).

[0048] It can be understood that the multiple coordinated fire-fighting sub-areas are other sub-areas in the target power plant area that do not belong to the multiple fire-fighting indirect hazard sub-areas.

[0049] Specifically, Figure 6 The flowchart of direct fire extinguishing processing and coordinated fire extinguishing processing in the method provided by the embodiment of the present invention is shown.

[0050] Among them, in the preferred embodiment provided by the present invention, the determining of the target danger range in the direct fire danger sub-area and performing direct fire extinguishing and coordinated fire extinguishing on the target danger range specifically include the following steps: Step S1051, determining the target danger range in the fire direct danger sub-area; Step S1052, generating a direct fire extinguishing instruction and a coordinated fire extinguishing instruction; Step S1053, determining a plurality of coordinated fire extinguishing sub-areas; Step S1054, sending the direct fire extinguishing instruction to the fire direct danger sub-area, and performing direct fire extinguishing processing on the target danger range; Step S1055: Send the coordinated fire extinguishing instruction to the multiple coordinated fire extinguishing sub-areas to perform coordinated fire extinguishing on the target danger range.

[0051] Furthermore, Figure 7 The application architecture diagram of the system provided by the embodiment of the present invention is shown.

[0052] Among them, in another preferred embodiment provided by the present invention, the fire protection system of the energy storage power station includes: The operation monitoring and analysis unit 101 is used to determine a target power station area of ​​a target energy storage power station, perform operation monitoring on the target power station area, determine whether there is an operation abnormality, and if there is an operation abnormality, determine whether there is a fire risk.

[0053] In the embodiment of the present invention, the operation monitoring and analysis unit 101 generates an operation monitoring instruction by determining the target power station area of ​​the target energy storage power station, and then performs real-time operation monitoring on the target power station area according to the operation monitoring instruction, obtains operation monitoring data including voltage, current, temperature, power, internal resistance, humidity, etc., and then analyzes the operation monitoring data to determine whether there is an operation abnormality, and when there is an operation abnormality, identifies the abnormal operation type, and determines whether there is a fire risk according to the abnormal operation type. Specifically, when the abnormal operation type is related to the fire risk, it is determined that there is a fire risk, for example: abnormal temperature increase; when the abnormal operation type is not related to the fire risk, it is determined that there is no fire risk, for example: abnormal humidity increase.

[0054] Specifically, Figure 8 It shows a structural block diagram of the operation monitoring and analysis unit 101 in the system provided by an embodiment of the present invention.

[0055] Among them, in the preferred embodiment provided by the present invention, the operation monitoring and analysis unit 101 specifically includes: The area determination module 1011 is used to determine the target power station area of ​​the target energy storage power station; The instruction generation module 1012 is used to generate operation monitoring instructions; An operation monitoring module 1013 is used to perform real-time operation monitoring of the target power station area according to the operation monitoring instruction and obtain operation monitoring data; The abnormality determination module 1014 is used to analyze the operation monitoring data to determine whether there is an operation abnormality; The risk judgment module 1015 is used to identify the abnormal operation type and judge whether there is a fire risk when there is an operation abnormality.

[0056] Furthermore, the fire protection system of the energy storage power station also includes: The fire monitoring and response unit 102 is used to determine a fire risk sub-area when there is a fire risk, perform fire monitoring and response on the fire risk sub-area, and obtain fire monitoring data.

[0057] In an embodiment of the present invention, in the event of a fire risk, the fire monitoring and response unit 102 locates a fire risk sub-area from the target power station area, and then generates targeted fire monitoring instructions based on the fire risk sub-area, and then performs fire monitoring response on the fire risk sub-area according to the fire monitoring instructions to obtain fire monitoring data including temperature, smoke, flame, etc.

[0058] The fire risk judgment unit 103 is used to analyze the fire monitoring data to judge whether there is a fire risk, and if there is a fire risk, determine a direct fire risk sub-area and multiple indirect fire risk sub-areas.

[0059] In an embodiment of the present invention, the fire hazard judgment unit 103 performs feature recognition on the fire monitoring data according to preset hazard feature data to determine whether there is a fire hazard. When it is determined that there is a fire hazard, a direct positioning instruction and an indirect positioning instruction are generated, and then the direct fire hazard sub-area is determined according to the direct positioning instruction. According to the indirect positioning instruction, the spread impact of the fire hazard in the direct fire hazard sub-area is analyzed to determine multiple indirect fire hazard sub-areas.

[0060] The fire hazard alarm unit 104 is used to issue fire hazard alarms of different levels to the direct fire hazard sub-area and the plurality of indirect fire hazard sub-areas.

[0061] In the embodiment of the present invention, the fire hazard alarm unit 104 generates a fire emergency alarm instruction and a fire impact alarm instruction, sends the fire emergency alarm instruction to the direct fire hazard sub-area, and sends the fire impact alarm instruction to multiple indirect fire hazard sub-areas, so that a first-level fire hazard alarm is performed in the direct fire hazard sub-area through the fire emergency alarm instruction, and a second-level fire hazard alarm is performed in multiple indirect fire hazard sub-areas through the fire impact alarm instruction, so as to realize different levels of fire hazard alarms in sub-areas with different dangerous situations in the target energy storage power station.

[0062] The target fire extinguishing processing unit 105 is used to determine the target danger range in the fire direct danger sub-area, and perform direct fire extinguishing processing and coordinated fire extinguishing processing on the target danger range.

[0063] In an embodiment of the present invention, the target fire extinguishing processing unit 105 generates a direct fire extinguishing instruction and a coordinated fire extinguishing instruction by determining the target dangerous range that is in fire danger in the direct fire danger sub-area, and determines multiple coordinated fire extinguishing sub-areas, and then sends the direct fire extinguishing instruction to the direct fire danger sub-area, and performs direct fire extinguishing processing (perfluorohexanone fire extinguishing, fine water mist fire extinguishing, etc.) on the target dangerous range, and sends the coordinated fire extinguishing instruction to multiple coordinated fire extinguishing sub-areas, and performs coordinated fire extinguishing processing on the target dangerous range (coordinated transportation of fire extinguishing equipment through drones, mobile vehicles, etc.).

[0064] In yet another embodiment, a computer device is provided, the computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program: Determine a target power station area of ​​a target energy storage power station, perform operation monitoring on the target power station area, determine whether there is an operation abnormality, and if there is an operation abnormality, determine whether there is a fire risk; When there is a fire risk, determining a fire risk sub-area, performing fire monitoring response on the fire risk sub-area, and acquiring fire monitoring data; Analyzing the fire monitoring data to determine whether there is a fire hazard, and if there is a fire hazard, determining a direct fire hazard sub-area and a plurality of indirect fire hazard sub-areas; Providing fire hazard alarms of different levels to the direct fire hazard sub-area and the plurality of indirect fire hazard sub-areas; A target danger range in the direct fire danger sub-area is determined, and direct fire extinguishing treatment and coordinated fire extinguishing treatment are performed on the target danger range.

[0065] In yet another embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the processor is enabled to perform the following steps: Determine a target power station area of ​​a target energy storage power station, perform operation monitoring on the target power station area, determine whether there is an operation abnormality, and if there is an operation abnormality, determine whether there is a fire risk; When there is a fire risk, determining a fire risk sub-area, performing fire monitoring response on the fire risk sub-area, and acquiring fire monitoring data; Analyzing the fire monitoring data to determine whether there is a fire hazard, and if there is a fire hazard, determining a direct fire hazard sub-area and a plurality of indirect fire hazard sub-areas; Providing fire hazard alarms of different levels to the direct fire hazard sub-area and the plurality of indirect fire hazard sub-areas; A target danger range in the direct fire danger sub-area is determined, and direct fire extinguishing treatment and coordinated fire extinguishing treatment are performed on the target danger range.

[0066] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0067] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0068] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A fire-fighting method for an energy storage power station, characterized in that: The method specifically comprises the following steps: Determine a target power station area of ​​a target energy storage power station, perform operation monitoring on the target power station area, determine whether there is an operation abnormality, and if there is an operation abnormality, determine whether there is a fire risk; When there is a fire risk, determining a fire risk sub-area, performing fire monitoring response on the fire risk sub-area, and acquiring fire monitoring data; Analyzing the fire monitoring data to determine whether there is a fire hazard, and if there is a fire hazard, determining a direct fire hazard sub-area and a plurality of indirect fire hazard sub-areas; Providing fire hazard alarms of different levels to the direct fire hazard sub-area and the plurality of indirect fire hazard sub-areas; A target danger range in the direct fire danger sub-area is determined, and direct fire extinguishing treatment and coordinated fire extinguishing treatment are performed on the target danger range.

2. The fire fighting method of the energy storage power station according to claim 1, characterized in that: The step of determining a target power station area of ​​a target energy storage power station, performing operation monitoring on the target power station area, determining whether there is an operation abnormality, and determining whether there is a fire risk when there is an operation abnormality specifically includes the following steps: Determine the target power station area of ​​the target energy storage power station; Generate operation monitoring instructions; According to the operation monitoring instruction, real-time operation monitoring is performed on the target power station area to obtain operation monitoring data; Analyze the operation monitoring data to determine whether there is any operation abnormality; When there is an operation abnormality, identify the abnormal operation type and determine whether there is a fire risk.

3. The fire fighting method of the energy storage power station according to claim 2, characterized in that: Analyzing the operation monitoring data to determine whether there is an operation abnormality specifically includes the following steps: The principal component analysis operation is used on the operation monitoring data to obtain the key features. The corresponding process has the following relationship: ； in, Represents operation monitoring data, with dimensions of , represents the number of samples, Indicates the number of features; Represents the weight matrix of PCA, with dimension ; represents the number of principal components, Represents the key features, and the dimension is ; The key features are nonlinearly mapped using radial basis functions to obtain nonlinear mapping features. The nonlinear mapping features include internal influence features and external influence features. The corresponding process has the following relationship: ； ； in, represents the nonlinear mapping feature, Represent the internal influence characteristics and external influence characteristics respectively, represents the number of centers of RBF, Indicates i The weights of the radial basis functions, Indicates i The center of the radial basis function, represents radial basis function; The state transfer matrix is ​​multiplied by the internal influence feature as the linear transfer part, the neural network is used to process the internal influence feature as the nonlinear disturbance part, and then the control matrix is ​​introduced, and the external influence feature is multiplied by the control matrix as the external influence part. The state transfer model is constructed based on the linear transfer part, the nonlinear disturbance part and the external influence part. The corresponding process has the following relationship: ； in, represents the state at time t, represents the state transfer matrix, represents the internal impact characteristics at time t-1, represents the external influence characteristics at time t-1, represents the control matrix, represents a pre-trained neural network; The operation monitoring data at each time point is taken as a state, and different states are input into the state transition model to obtain the probability distribution of different states. The corresponding process has the following relationship: ； in, Indicates time t The probability distribution of the state, represents the state transition model, represents a probability mapping operation; The weighted sum of the probability distributions of different states is used as the anomaly scoring result; ； in, Indicates time t The abnormal scoring results of Indicates n The weight of the state probability; The scoring threshold is dynamically calculated based on the mean and standard deviation of historical data. The abnormal scoring result is compared with the scoring threshold. The comparison result is used to determine whether there is an operational abnormality. The corresponding process has the following relationship: ； ； in, represents the scoring threshold, represents the historical mean, represents the historical standard deviation, represents the adjustment factor, Represents a Boolean value.

4. The fire fighting method of the energy storage power station according to claim 3, characterized in that: When there is an operation abnormality, identifying the abnormal operation type and determining whether there is a fire risk specifically includes the following steps: Get the abnormal feature vector when the operation is abnormal; The abnormal feature vector is divided into multiple perspective features, each perspective feature corresponds to a different type of operation monitoring data, and the corresponding process has the following relationship: ； in, represents the eigenvector in sequence, Indicates j Perspective features; The K-means clustering method is used to cluster each view feature, and the clustering result of each view is obtained. The corresponding process has the following relationship: ； in, represents the jth view feature v The clustering results are Represents K-means clustering operation; Assign weights to the clustering results from different perspectives, and then use the consensus clustering method to aggregate and obtain the overall clustering results. The corresponding process has the following relationship: ； in, represents the overall clustering result, represents the consensus clustering operation, Indicates j The weight of the clustering results of each perspective; According to the domain knowledge, fuzzy rules are formulated, and the specific values ​​in the overall clustering results are converted into fuzzy sets using membership functions. The corresponding process of converting the specific values ​​in the overall clustering results into fuzzy sets using membership functions has the following relationship: ； in, represents the membership function, represents the cluster center value, represents the spread parameter of the cluster; Match fuzzy sets with fuzzy rules to obtain fuzzy outputs; The centroid method is used to calculate the centroid of the fuzzy output to obtain the abnormal mode. The corresponding process has the following relationship: ； in, represents the centroid of the fuzzy output, Indicates fuzzy output; The probability of fire incidents in the statistical abnormal mode in history is used to determine the fire risk of the current abnormal mode. The corresponding process has the following relationship: ； in, Represents the centroid of a given fuzzy output The probability of fire risk under 5. The fire fighting method of the energy storage power station according to claim 4, characterized in that: When there is a fire risk, determining a fire risk sub-area, performing fire monitoring response on the fire risk sub-area, and obtaining fire monitoring data specifically include the following steps: When there is a fire risk, determine the fire risk sub-area; Generate targeted fire monitoring instructions according to the fire risk sub-area; According to the fire monitoring instruction, a fire monitoring response is performed on the fire risk sub-area to obtain fire monitoring data.

6. The fire fighting method of the energy storage power station according to claim 5, characterized in that: The analyzing of the fire monitoring data to determine whether there is a fire hazard and, if there is a fire hazard, determining a direct fire hazard sub-area and a plurality of indirect fire hazard sub-areas specifically comprises the following steps: According to the preset dangerous characteristic data, the fire monitoring data is subjected to characteristic recognition to determine whether there is a fire hazard; When there is a fire hazard, direct positioning instructions and indirect positioning instructions are generated; Determine the fire-fighting direct hazard sub-areas in accordance with the direct positioning instructions; According to the indirect positioning instruction, a fire risk spreading impact analysis is performed to determine a plurality of fire indirect risk sub-areas.

7. The fire fighting method of the energy storage power station according to claim 6, characterized in that: According to the indirect location instruction, the spread impact analysis of fire danger is carried out to determine multiple fire indirect danger sub-areas, which specifically includes the following steps: Divide the energy storage power station area into grids to obtain multiple grid units; Mark the grid cells where fire risk has been detected as direct danger areas, initialize the risk value of the direct danger area to the highest risk value, and set the initial risk values ​​of other grid cells to zero; Assign a corresponding weight to each grid cell according to the distance from the direct danger area; Obtain the environmental parameters in each grid cell. The environmental parameters include multiple environmental factors. Based on the guidance of experienced experts, obtain the fire protection impact values ​​of different environmental factors. Calculate the fuzzy membership of each environmental factor in each grid cell, and multiply the fuzzy membership of each environmental factor by the corresponding fire protection impact value to obtain the environmental impact value of each environmental factor; The environmental impact values ​​of different environmental factors in each grid are summed up to obtain the comprehensive environmental impact value of the grid; The initial risk of the current cell is updated by taking the weighted sum of the risk values ​​of the adjacent grid cells of the current grid cell and the weight of the corresponding grid cell; Traverse all grid cells according to the time step, update the initial risk values ​​of all grid cells to simulate the spread of risk from the direct danger area to the nearby area, and obtain the cumulative risk value of each grid cell; The comprehensive environmental impact value of each grid unit is multiplied by the cumulative risk value as the comprehensive risk value of the corresponding grid unit; Based on the comprehensive risk value of each grid unit, multiple fire indirect hazard sub-areas are determined.

8. The fire fighting method of the energy storage power station according to claim 7, characterized in that: The fire hazard alarming of different levels for the direct fire hazard sub-area and the multiple indirect fire hazard sub-areas specifically comprises the following steps: Generate fire emergency alarm instructions and fire impact alarm instructions; Sending the fire emergency alarm instruction to the fire direct danger sub-area, and sending the fire impact alarm instruction to a plurality of the fire indirect danger sub-areas; Through the fire emergency alarm instruction, a first-level fire danger alarm is issued in the fire direct danger sub-area; Through the fire impact alarm instruction, a secondary fire hazard alarm is performed in multiple fire indirect hazard sub-areas.

9. The fire fighting method of the energy storage power station according to claim 8, characterized in that: Determining the target danger range in the direct fire danger sub-area and performing direct fire extinguishing and coordinated fire extinguishing on the target danger range specifically includes the following steps: Determine the target danger range in the direct fire danger sub-area; Generate direct fire-fighting instructions and coordinated fire-fighting instructions; Identify multiple coordinated firefighting sub-areas; Sending the direct fire extinguishing instruction to the fire direct danger sub-area to directly extinguish the fire in the target danger range; The coordinated fire extinguishing instruction is sent to the plurality of coordinated fire extinguishing sub-areas to perform coordinated fire extinguishing processing on the target danger range.

10. A fire fighting system for an energy storage power station, the system being applied to the fire fighting method for an energy storage power station according to any one of claims 1 to 9, characterized in that: The system includes an operation monitoring and analysis unit, a fire monitoring and response unit, a fire hazard judgment unit, a fire hazard alarm unit and a target fire extinguishing processing unit, wherein: An operation monitoring and analysis unit, used to determine a target power station area of ​​a target energy storage power station, perform operation monitoring on the target power station area, determine whether there is an operation abnormality, and if there is an operation abnormality, determine whether there is a fire risk; A fire monitoring and response unit, used to determine a fire risk sub-area when there is a fire risk, perform fire monitoring and response on the fire risk sub-area, and obtain fire monitoring data; a fire risk judgment unit, configured to analyze the fire monitoring data, judge whether there is a fire risk, and determine a direct fire risk sub-area and a plurality of indirect fire risk sub-areas when there is a fire risk; A fire hazard alarm unit, used for performing fire hazard alarms of different levels for the direct fire hazard sub-area and a plurality of the indirect fire hazard sub-areas; The target fire extinguishing processing unit is used to determine the target danger range in the fire direct danger sub-area, and perform direct fire extinguishing processing and coordinated fire extinguishing processing on the target danger range.

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