Safety detection method and device for user-side energy storage scene, computer equipment, storage medium and program product

Abstract

The invention relates to a security detection method and device for a user-side energy storage scene, computer equipment, a storage medium and a program product. The method comprises the following steps: acquiring target scene elements of a to-be-tested energy storage scene; determining each potential dangerous scene existing in the to-be-tested energy storage scene according to the target scene element, and determining a risk level corresponding to each potential dangerous scene; according to the risk level corresponding to each potential dangerous scene, identifying each key potential dangerous scene from each potential dangerous scene; obtaining residual risks and tolerable occurrence frequencies corresponding to the key potential dangerous scenes; and determining whether the safety of the to-be-tested energy storage scene meets a preset safety requirement or not according to the residual risk and the tolerable occurrence frequency corresponding to each key potential dangerous scene. According to the embodiment of the invention, more accurate security detection of the to-be-detected energy storage scene can be realized, and security detection requirements in different to-be-detected energy storage scenes can be met.

Description

Technical Field

[0001] This application relates to the field of energy storage technology, and in particular to a safety detection method, device, computer equipment, storage medium and program product for user-side energy storage scenarios. Background Technology

[0002] User-side energy storage refers to the installation of energy storage systems at the electricity user's end to store electrical energy and release it when needed to meet the user's electricity demand. As an important component of distributed energy systems, it plays a vital role in optimizing energy utilization, improving power supply reliability, and reducing electricity costs.

[0003] Typically, user-side energy storage is the application node of new energy storage closest to the user. It is directly deployed in areas with high density of people and equipment, such as production units and public places. Once a safety accident occurs, it will pose a serious threat to people and property.

[0004] Therefore, in order to ensure the safe operation of user-side energy storage, how to accurately detect the safety of user-side energy storage is an urgent problem to be solved. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, device, computer equipment, storage medium, and program product that can accurately detect the safety of user-side energy storage scenarios, addressing the aforementioned technical problems.

[0006] Firstly, this application provides a safety testing method for user-side energy storage scenarios. The method includes: acquiring target scenario elements of the energy storage scenario to be tested; determining each potential hazardous scenario existing in the energy storage scenario to be tested based on the target scenario elements, and determining the risk level corresponding to each potential hazardous scenario; identifying each key potential hazardous scenario from each potential hazardous scenario based on the risk level corresponding to each potential hazardous scenario; acquiring the residual risk and tolerable occurrence frequency corresponding to each key potential hazardous scenario; and determining whether the safety of the energy storage scenario to be tested meets preset safety requirements based on the residual risk and tolerable occurrence frequency corresponding to each key potential hazardous scenario.

[0007] In one embodiment, determining the potential hazardous scenarios of the energy storage scenario under test based on the target scenario elements includes: determining the potential hazard sources of the energy storage scenario under test based on the target scenario elements; and determining the corresponding potential hazardous scenarios based on each potential hazard source.

[0008] In one embodiment, determining the risk level corresponding to each potential hazardous scenario includes: obtaining the severity level and probability level of the consequences corresponding to each potential hazardous scenario; and for each potential hazardous scenario, determining the risk level corresponding to the potential hazardous scenario based on the severity level and probability level of the consequences corresponding to the potential hazardous scenario.

[0009] In one embodiment, obtaining the residual risk and tolerable occurrence frequency corresponding to each key potential hazard scenario includes: for each key potential hazard scenario, obtaining the occurrence probability of the triggering event corresponding to the key potential hazard scenario, the failure probability of each preset safety measure, and the severity level of the consequences; determining the residual risk corresponding to the key potential hazard scenario based on the occurrence probability of the triggering event and the failure probability of each preset safety measure; and determining the tolerable occurrence frequency corresponding to the key potential hazard scenario based on the severity level of the consequences corresponding to the key potential hazard scenario.

[0010] In one embodiment, determining whether the safety of the energy storage scenario under test meets the preset safety requirements based on the residual risk and tolerable occurrence frequency corresponding to each key potential hazard scenario includes: determining the risk reduction factor corresponding to each key potential hazard scenario based on the residual risk and tolerable occurrence frequency corresponding to each key potential hazard scenario; if the risk reduction factor corresponding to each key potential hazard scenario is less than or equal to 1, then the safety of the energy storage scenario under test is determined to meet the preset safety requirements; if the risk reduction factor corresponding to any key potential hazard scenario is greater than 1, then the safety of the energy storage scenario under test is determined to not meet the preset safety requirements.

[0011] In one embodiment, the method further includes: if it is determined that the safety of the energy storage scenario under test does not meet the preset safety requirements, then determining the target safety improvement measures corresponding to each key potential hazard scenario with a risk reduction factor greater than 1; for each key potential hazard scenario, updating the preset safety measures corresponding to the key potential hazard scenario according to the target safety improvement measures corresponding to the key potential hazard scenario.

[0012] Secondly, this application also provides a safety testing device for user-side energy storage scenarios. The device includes: a first acquisition module for acquiring target scenario elements of the energy storage scenario under test; a first determination module for determining each potential hazardous scenario existing in the energy storage scenario under test based on the target scenario elements, and determining the risk level corresponding to each potential hazardous scenario; an identification module for identifying each key potential hazardous scenario from the potential hazardous scenarios based on the risk level corresponding to each potential hazardous scenario; a second acquisition module for acquiring the residual risk and tolerable occurrence frequency corresponding to each key potential hazardous scenario; and a second determination module for determining whether the safety of the energy storage scenario under test meets preset safety requirements based on the residual risk and tolerable occurrence frequency corresponding to each key potential hazardous scenario.

[0013] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method steps of any of the embodiments in the first aspect described above.

[0014] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method steps of any of the embodiments in the first aspect described above.

[0015] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the method steps of any of the embodiments in the first aspect described above.

[0016] The aforementioned safety detection method, apparatus, computer equipment, storage medium, and program product for user-side energy storage scenarios, by determining various potential hazardous scenarios existing in the energy storage scenario under test based on the acquired target scenario elements of the energy storage scenario under test, and determining the risk level corresponding to each potential hazardous scenario, can cover all scenario elements of the energy storage scenario under test, so as to more comprehensively determine each potential hazardous scenario and its corresponding risk level. Furthermore, the method of identifying key potential hazardous scenarios from among the potential hazardous scenarios based on their corresponding risk levels can help improve the efficiency of safety detection for user-side energy storage scenarios. Furthermore, the method of obtaining the residual risk and tolerable occurrence frequency corresponding to each key potential hazardous scenario, and determining whether the safety of the energy storage scenario under test meets the preset safety requirements based on the residual risk and tolerable occurrence frequency corresponding to each key potential hazardous scenario, comprehensively considers residual risk and tolerable occurrence frequency in the safety detection of the energy storage scenario under test; therefore, the embodiments of this application can achieve more accurate safety detection of the energy storage scenario under test. Furthermore, the safety detection method for user-side energy storage scenarios in this application embodiment can be applied to safety detection in different energy storage scenarios under test, and its scenario adaptability is strong, so as to meet the safety detection requirements of different energy storage scenarios under test, thereby helping to further improve the accuracy of safety detection in different energy storage scenarios under test. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating a safety detection method for a user-side energy storage scenario in one embodiment.

[0019] Figure 2 This is a flowchart illustrating a method for determining potential hazardous scenarios in one embodiment;

[0020] Figure 3This is a flowchart illustrating a method for determining the risk level corresponding to a potential hazardous scenario in one embodiment.

[0021] Figure 4 This is a flowchart illustrating a method for obtaining residual risk and tolerable frequency of occurrence in one embodiment;

[0022] Figure 5 This is a flowchart illustrating a method for determining whether the safety of an energy storage scenario under test meets preset safety requirements in one embodiment.

[0023] Figure 6 This is a flowchart illustrating a safety detection method for a user-side energy storage scenario in another embodiment;

[0024] Figure 7 This is a schematic diagram of the structure of a safety detection device for a user-side energy storage scenario in one embodiment;

[0025] Figure 8 This is a schematic diagram of the structure of a computer device in one embodiment. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0027] The safety detection method, device, computer equipment, storage medium, and program product for user-side energy storage scenarios provided in this application embodiment can be applied to energy storage charging station application scenarios; of course, they can also be applied to other energy storage application scenarios.

[0028] The computer devices involved in the embodiments of this application may include, but are not limited to, any of the following: personal computer, laptop computer, tablet computer, supercomputer, mainframe computer, embedded computer, network computer, and cluster computer.

[0029] With the rapid development of user-side energy storage (such as industrial and commercial energy storage, charging station energy storage, etc.), its safety issues are becoming increasingly prominent. If not given sufficient attention, these issues will seriously hinder the promotion and application of energy storage systems in user-side scenarios, thereby affecting the healthy development of the new energy storage industry. Therefore, establishing a safety testing (or evaluation) method for user-side energy storage is of great significance for identifying weaknesses in user-side energy storage safety and ensuring its safe operation.

[0030] In one exemplary embodiment, Figure 1 This is a flowchart illustrating a safety detection method for a user-side energy storage scenario in one embodiment. This application uses the application of this method to a computer device as an example for explanation. Figure 1As shown, the safety detection method for user-side energy storage scenarios in this application embodiment may include the following steps:

[0031] Step S101: Obtain the target scene elements of the energy storage scenario to be tested.

[0032] For example, the energy storage scenarios to be tested involved in the embodiments of this application may include, but are not limited to, user-side energy storage scenarios.

[0033] The target scenario elements in this application embodiment can be used to indicate key factors of the energy storage scenario under test. For example, the target scenario elements may include, but are not limited to, at least one of the following: scenario category, scenario equipment composition, and limiting conditions. The scenario category may include, but is not limited to, (photovoltaic) energy storage charging stations, industrial and commercial park energy storage, and residential energy storage. The scenario equipment composition may include, but is not limited to, the energy storage system itself, other equipment and facilities in the energy storage scenario under test besides the energy storage system itself (such as electrical equipment, power distribution systems, safety systems, auxiliary facilities, etc.), and / or, external equipment. The limiting conditions may include, but are not limited to, the environmental conditions of the energy storage scenario under test, spatial layout limitations, and equipment usage specification limitations.

[0034] In this step, the computer device can receive the target scene elements of the energy storage scenario under test input by the user, or it can obtain the target scene elements of the energy storage scenario under test from other devices (such as the equipment of the energy storage scenario construction party, or cloud devices, etc.).

[0035] Of course, computer equipment can also acquire target scene elements of the energy storage scenario under test through other means.

[0036] Step S102: Determine the potential hazardous scenarios existing in the energy storage scenario to be tested based on the target scenario elements, and determine the risk level corresponding to each potential hazardous scenario.

[0037] Any potential hazard scenario involved in the embodiments of this application can be used to indicate the accident chain information corresponding to the possible consequences of a potential hazard source.

[0038] In this step, the computer equipment can determine the potential hazardous scenarios existing in the energy storage scenario under test based on the target scenario elements, and determine the risk level corresponding to each potential hazardous scenario, so as to facilitate the subsequent identification of each key potential hazardous scenario. It should be understood that the higher the risk level corresponding to any potential hazardous scenario, the greater the risk it poses.

[0039] For ease of understanding, the following embodiments of this application provide an exemplary description of how to implement the above-mentioned "determine the potential hazardous scenarios existing in the energy storage scenario under test based on the target scenario elements".

[0040] In one possible implementation, the computer device can determine the potential hazards in the energy storage scenario under test based on the target scenario elements, and determine the corresponding potential hazard scenarios based on each potential hazard.

[0041] The potential hazards mentioned in this application embodiment can refer to hazardous factors existing in the energy storage scenario under test that may affect the safe operation of the energy storage scenario. For example, potential hazards may include, but are not limited to, any of the following: unsafe conditions of equipment, unsafe acts of personnel, and hazardous factors in the environment.

[0042] The potential hazard scenarios corresponding to any potential hazard source involved in the embodiments of this application can be used to indicate the accident chain information corresponding to the possible consequences of the potential hazard source.

[0043] In another possible implementation, the computer device can determine each potential hazard scenario by inputting the target scene elements into a preset potential hazard scenario prediction model and then determining the potential hazard scenario based on the output of the preset potential hazard scenario prediction model. The preset potential hazard scenario prediction model may include, but is not limited to, artificial intelligence (AI) models such as machine learning models.

[0044] Of course, computer equipment can also determine the potential hazardous scenarios in the energy storage scenario under test through other means, based on the target scenario elements.

[0045] For ease of understanding, the following embodiments of this application provide an exemplary description of how to implement the above-mentioned "determining the risk level corresponding to each potential hazardous scenario".

[0046] In one possible implementation, the computer device can obtain the severity level and probability level of the consequences corresponding to each potential hazardous scenario, and determine the risk level corresponding to each potential hazardous scenario based on the severity level and probability level of the consequences corresponding to each potential hazardous scenario.

[0047] The severity level of consequences corresponding to any potential hazardous scenario involved in the embodiments of this application can be used to measure the severity of the consequences that the potential hazardous scenario may bring.

[0048] The consequence probability level corresponding to any potential hazardous scenario involved in the embodiments of this application can be used to measure the degree of probability of the consequences that the potential hazardous scenario may bring.

[0049] In another possible implementation, for each potential hazardous scenario, the computer device can input the potential hazardous scenario into a preset risk level prediction model, and then determine the risk level corresponding to the potential hazardous scenario based on the output of the preset risk level prediction model. The preset risk level prediction model may include, but is not limited to, AI models such as machine learning models.

[0050] Of course, computer equipment can also determine the risk level corresponding to each potential hazardous scenario in other ways.

[0051] Step S103: Identify key potential hazards from each potential hazard scenario based on the risk level corresponding to each potential hazard scenario.

[0052] In this step, the computer equipment can identify potential hazardous scenarios with a risk level greater than or equal to a preset risk level threshold as critical potential hazardous scenarios based on the risk level corresponding to each potential hazardous scenario. For example, the preset risk level threshold can be risk level 5 or risk level 6.

[0053] Step S104: Obtain the residual risk and tolerable frequency of occurrence for each key potential hazard scenario.

[0054] In this step, the computer equipment can acquire the residual risk and tolerable frequency of occurrence for each critical potential hazard scenario. The residual risk for any critical potential hazard scenario can be used to indicate the risk that still exists after safety measures have been taken for that critical potential hazard scenario. The tolerable frequency of occurrence for any critical potential hazard scenario can be used to indicate the highest acceptable frequency of occurrence for that critical potential hazard scenario.

[0055] In one possible implementation, the computer device can determine the residual risk and tolerable frequency of occurrence for each key potential hazard scenario based on the acquired safety-related information. The safety-related information for any key potential hazard scenario may include, but is not limited to, at least one of the following: the probability of occurrence of the triggering event corresponding to the key potential hazard scenario, the failure probability of each preset safety measure, and the severity level of the consequences.

[0056] In another possible implementation, the computer device can receive user input of the residual risk and tolerable frequency of occurrence for each key potential hazard scenario.

[0057] In another possible implementation, the computer device can obtain the residual risks and tolerable frequency of occurrence of each key potential hazard scenario from other devices (such as the equipment of the energy storage construction party, or cloud devices).

[0058] Of course, computer equipment can also obtain the residual risks and tolerable frequency of occurrence corresponding to each key potential hazard scenario through other means.

[0059] Step S105: Based on the residual risks and tolerable occurrence frequencies corresponding to each key potential hazard scenario, determine whether the safety of the energy storage scenario under test meets the preset safety requirements.

[0060] In this step, the computer equipment can determine whether the safety of the energy storage scenario under test meets the preset safety requirements based on the residual risks and tolerable occurrence frequencies corresponding to each key potential hazard scenario.

[0061] In one possible implementation, for each key potential hazard scenario, the computer device can determine the risk reduction factor corresponding to the key potential hazard scenario based on the residual risk and tolerable occurrence frequency of the key potential hazard scenario, so as to determine whether the safety of the energy storage scenario under test meets the preset safety requirements based on the magnitude of the risk reduction factor corresponding to the key potential hazard scenario.

[0062] In another possible implementation, for each key potential hazard scenario, the computer equipment can input the residual risk and tolerable occurrence frequency corresponding to that key potential hazard scenario into a preset safety requirement detection model. The output of the preset safety requirement detection model can then determine whether the safety of the energy storage scenario under test meets the preset safety requirements. The preset safety requirement detection model can include, but is not limited to, AI models such as machine learning models.

[0063] Of course, based on the residual risks and tolerable frequency of occurrence corresponding to each key potential hazard scenario, computer equipment can also determine whether the safety of the energy storage scenario under test meets the preset safety requirements through other means.

[0064] The aforementioned safety detection method for user-side energy storage scenarios, by determining the potential hazardous scenarios present in the energy storage scenario under test based on the acquired target scenario elements, and determining the risk level corresponding to each potential hazardous scenario, can cover all scenario elements of the energy storage scenario under test, thus enabling a more comprehensive determination of each potential hazardous scenario and its corresponding risk level. Furthermore, identifying key potential hazardous scenarios from among the potential hazardous scenarios based on their corresponding risk levels can improve the efficiency of safety detection for user-side energy storage scenarios. Furthermore, obtaining the residual risk and tolerable occurrence frequency corresponding to each key potential hazardous scenario, and determining whether the safety of the energy storage scenario under test meets preset safety requirements based on these residual risks and tolerable occurrence frequencies, allows for more accurate safety detection of the energy storage scenario under test by comprehensively considering residual risk and tolerable occurrence frequency. Furthermore, the safety detection method for user-side energy storage scenarios in this application embodiment can be applied to safety detection in different energy storage scenarios under test, and its scenario adaptability is strong, so as to meet the safety detection requirements of different energy storage scenarios under test, thereby helping to further improve the accuracy of safety detection in different energy storage scenarios under test.

[0065] In one exemplary embodiment, Figure 2 This is a flowchart illustrating a method for determining potential hazardous scenarios in one embodiment. This application embodiment provides an exemplary description of the relevant content in step S102 above, "determining the potential hazardous scenarios existing in the energy storage scenario under test based on the target scenario elements." For example... Figure 2 As shown, the method in this application embodiment may include the following steps:

[0066] Step S1021: Determine the potential hazards in the energy storage scenario to be tested based on the target scenario elements.

[0067] For example, computer equipment can use a preset hazard identification method based on the target scenario elements to determine the potential hazards present in the energy storage scenario under test. The preset hazard identification method may include, but is not limited to, any of the following: safety checklist method, Failure Modes and Effects Analysis (FMEA), Fault Tree Analysis (FTA), and Hazard and Operability Analysis (HAZOP).

[0068] As another example, a computer device can input target scene elements into a preset hazard identification model, and then determine the potential hazards present in the energy storage scene under test based on the output of the preset hazard identification model. The preset hazard identification model may include, but is not limited to, AI models such as machine learning models.

[0069] Step S1022: Determine the corresponding potential hazard scenarios based on each potential hazard source.

[0070] In this step, for any potential hazard source, the computer equipment can determine the corresponding potential hazard scenario based on that potential hazard source.

[0071] In one possible implementation, a computer device can determine the potential hazard scenario corresponding to the potential hazard by querying the correspondence between preset reference hazard sources and their corresponding reference hazard scenarios. The correspondence between preset reference hazard sources and their corresponding reference hazard scenarios can be used to indicate the correspondence between different reference hazard sources and their corresponding reference hazard scenarios.

[0072] In another possible implementation, a computer device can input the potential hazard source into a preset hazard scenario construction model, and then determine the potential hazard scenario corresponding to the potential hazard source based on the output of the preset hazard scenario construction model. The preset hazard scenario construction model can include, but is not limited to, AI models such as machine learning models.

[0073] In another possible implementation, the computer device can output the potential hazard source in order to receive the potential hazard scenario corresponding to the potential hazard source input by the user.

[0074] In another possible implementation, the computer device can send a hazard scenario query message containing the potential hazard source to other devices, so that the other devices can respond to the hazard scenario query message and return the potential hazard scenario corresponding to the potential hazard source to the computer device.

[0075] Of course, computer equipment can also determine the corresponding potential hazard scenarios through other means based on the potential hazard source.

[0076] In summary, in this embodiment of the application, by determining the potential hazards in the energy storage scenario under test based on the target scenario elements, and by determining the corresponding potential hazard scenarios based on each potential hazard, the various scenario elements of the energy storage scenario under test can be covered. This allows for a more comprehensive determination of different potential hazards, which in turn facilitates a more comprehensive determination of different potential hazard scenarios, thereby further improving the accuracy of safety testing in the energy storage scenario under test.

[0077] In one exemplary embodiment, Figure 3This is a flowchart illustrating a method for determining the risk level corresponding to a potential hazardous scenario in one embodiment. This application embodiment provides an exemplary description of the relevant content of "determining the risk level corresponding to each potential hazardous scenario" in step S102 above. For example... Figure 3 As shown, the method in this application embodiment may include the following steps:

[0078] Step S1023: Obtain the severity level and probability level of consequences corresponding to each potential hazardous scenario.

[0079] In this step, for each potential hazardous scenario, the computer device can obtain the severity level and probability level of the consequences corresponding to that potential hazardous scenario.

[0080] In one possible implementation, a computer device can determine the severity level of a potential hazard by querying the correspondence between preset reference hazard scenarios and their corresponding reference consequence severity levels, and also determine the likelihood level of a potential hazard by querying the correspondence between preset reference hazard scenarios and their corresponding reference consequence probability levels. The correspondence between preset reference hazard scenarios and their corresponding reference consequence severity levels can be used to indicate the correspondence between different reference hazard scenarios and their corresponding reference consequence severity levels; similarly, the correspondence between preset reference hazard scenarios and their corresponding reference consequence probability levels can be used to indicate the correspondence between different reference hazard scenarios and their corresponding reference consequence probability levels.

[0081] It should be noted that, for different energy storage scenarios under test, the correspondence between the preset reference hazardous scenarios and the corresponding reference consequence severity levels, as well as the correspondence between the preset reference hazardous scenarios and the corresponding reference consequence probability levels, involved in the embodiments of this application may be different.

[0082] For ease of understanding, the different severity levels of the reference consequences described above are illustrated in the embodiments of this application.

[0083] Table 1 is a schematic diagram of different reference consequence severity levels. As shown in Table 1, different reference consequence severity levels may include, but are not limited to, reference consequence severity level A, reference consequence severity level B, reference consequence severity level C, reference consequence severity level D, reference consequence severity level E, and reference consequence severity level F. Each reference consequence severity level may have corresponding level requirements for both personnel and property.

[0084] Table 1 is a schematic diagram of different reference consequence severity levels.

[0085]

[0086] It should be noted that the number of reference consequence severity levels in Table 1 and the corresponding level requirement standards for each reference consequence severity level can be flexibly adjusted according to actual needs.

[0087] For ease of understanding, the different levels of probability of the reference consequences described above are illustrated in the embodiments of this application.

[0088] Table 2 is a schematic diagram of different reference consequence probability levels. As shown in Table 2, different reference consequence probability levels may include, but are not limited to, reference consequence probability level A', reference consequence probability level B', reference consequence probability level C', reference consequence probability level D', reference consequence probability level E', and reference consequence probability level F'. Each reference consequence probability level may have corresponding level requirement standards.

[0089] Table 2 is a schematic diagram of different levels of the likelihood of reference consequences.

[0090] Reference Consequence Probability Level Grade requirement standards A’ A similar incident has never happened in the industry before. B’ Similar incidents have occurred in the industry. C’ Similar incidents have occurred multiple times within the industry. D’ Similar incidents have occurred in our unit. E’ Similar incidents have occurred multiple times in our unit. F’ Similar incidents occur every year in our unit.

[0091] It should be noted that the number of reference consequence probability levels and the corresponding level requirement standards in Table 2 can be flexibly adjusted according to actual needs.

[0092] In another possible implementation, the computer device can query the correspondence between preset reference hazard scenarios and their corresponding reference consequence levels based on the potential hazard scenario, and determine the severity level and probability level of the consequence corresponding to the potential hazard scenario. The correspondence between preset reference hazard scenarios and their corresponding reference consequence levels can be used to indicate the correspondence between different reference hazard scenarios and their corresponding reference consequence severity and probability levels.

[0093] It should be noted that the correspondence between the preset reference hazard scenarios and the corresponding reference consequence levels involved in the embodiments of this application may be different for different energy storage scenarios under test.

[0094] In another possible implementation, the computer device can output the potential hazard scenario in order to receive user input of the severity level and probability level of the consequences corresponding to the potential hazard scenario.

[0095] In another possible implementation, the computer device can send a consequence level query message containing the potential hazardous scenario to other devices, so that the other devices can respond to the consequence level query message and return to the computer device the severity level and probability level of the consequences corresponding to the potential hazardous scenario.

[0096] Of course, computer devices can also obtain the severity level and probability level of the consequences corresponding to the potential dangerous scenario through other means.

[0097] Step S1024: For each potential hazardous scenario, determine the risk level corresponding to the potential hazardous scenario based on the severity level and probability level of the consequences.

[0098] In this step, for each potential hazardous scenario, the computer equipment can determine the risk level corresponding to the potential hazardous scenario based on the severity level and probability level of the consequences.

[0099] In one possible implementation, a computer device can determine the risk level corresponding to the potential hazard scenario by querying the correspondence between a preset reference consequence level and its corresponding reference risk level based on the severity level and probability level of the consequence. The correspondence between the preset reference consequence level and its corresponding reference risk level can be used to indicate the correspondence between different reference consequence severity levels and different reference consequence probability levels and their corresponding reference risk levels.

[0100] It should be noted that the correspondence between the preset reference consequence level and the corresponding reference risk level involved in the embodiments of this application may be different for different energy storage scenarios under test.

[0101] For ease of understanding, this application embodiment uses a table to illustrate the correspondence between the preset reference consequence level and the corresponding reference risk level.

[0102] Table 3 illustrates the correspondence between preset reference consequence levels and corresponding reference risk levels.

[0103]

[0104] It should be noted that the number of reference consequence severity levels and reference consequence probability levels in Table 3 can be flexibly adjusted according to actual needs.

[0105] In another possible implementation, the computer device can receive the risk level corresponding to the potential dangerous situation from the user by outputting the severity level and probability level of the consequences corresponding to the potential dangerous situation.

[0106] In another possible implementation, the computer device can send a risk level query message to other devices, which contains the severity level and probability level of the consequences corresponding to the potential hazardous scenario, so that the other devices can respond to the risk level query message and return the risk level corresponding to the potential hazardous scenario to the computer device.

[0107] Of course, computer equipment can also determine the risk level of a potential hazardous scenario through other means, based on the severity and likelihood of the consequences.

[0108] In summary, in this embodiment of the application, by obtaining the severity level and probability level of the consequences corresponding to each potential hazardous scenario, and determining the risk level corresponding to each potential hazardous scenario based on the severity level and probability level of the consequences, this embodiment of the application can more accurately determine the risk level corresponding to different potential hazardous scenarios because it comprehensively considers the severity level and probability level of the consequences.

[0109] In one exemplary embodiment, Figure 4 This is a flowchart illustrating a method for obtaining residual risk and tolerable frequency of occurrence in one embodiment. This application embodiment provides an exemplary description of the relevant content in step S104 above, "obtaining the residual risk and tolerable frequency of occurrence corresponding to each key potential hazard scenario." For example... Figure 4 As shown, the method in this application embodiment may include the following steps:

[0110] Step S1041: For each key potential hazard scenario, obtain the probability of occurrence of the triggering event corresponding to the key potential hazard scenario, the failure probability of each preset safety measure, and the severity level of the consequences.

[0111] In this step, for each critical potential hazard scenario, the computer device can obtain the probability of occurrence of the triggering event corresponding to the critical potential hazard scenario, the probability of failure of each preset safety measure, and the severity level of the consequences.

[0112] In the embodiments of this application, the triggering event corresponding to any critical potential hazard scenario can refer to the initial event that causes the critical potential hazard scenario to occur.

[0113] The pre-set safety measures corresponding to any key potential hazard scenario involved in the embodiments of this application can refer to the prevention and response measures formulated in advance for the possible occurrence of the key potential hazard scenario, which aim to reduce the possibility of the hazard occurring and mitigate the loss and impact caused when the hazard occurs (or be called risk reduction measures).

[0114] For example, pre-set safety measures may include, but are not limited to, safety measures that can intercept initial events, or / or safety measures that can eliminate dangerous consequences. For instance, pre-set safety measures may include, but are not limited to, at least one of the following: safety design measures for energy storage scenarios (such as physical barriers, high-safety materials, etc.), safety function measures (such as early warning, interlocking, etc.), and safety configuration measures (such as fire extinguishing systems, ventilation systems, etc.).

[0115] In one possible implementation, the computer device can receive the probability of occurrence of the triggering event corresponding to the critical potential hazard scenario and the failure probability of each preset safety measure (the probability that the preset safety measure cannot function properly to reduce the risk when the initial event occurs) input by the user. For example, the computer device can output the critical potential hazard scenario to facilitate receiving the probability of occurrence of the triggering event corresponding to the critical potential hazard scenario and the failure probability of each preset safety measure input by the user.

[0116] In another possible implementation, the computer device can obtain the probability of occurrence of the triggering event corresponding to the critical potential hazard scenario and the failure probability of each preset safety measure from other devices. For example, the computer device can send a probability query message containing the critical potential hazard scenario to other devices, so that the other devices can respond to the probability query message and return to the computer device the probability of occurrence of the triggering event corresponding to the critical potential hazard scenario and the failure probability of each preset safety measure.

[0117] For example, the failure probability of any preset safety measure can be a probability calculated based on historical data from the energy storage industry, and / or a probability assessed based on professional equipment; of course, the failure probability of a preset safety measure can also be a probability obtained through other means.

[0118] It should be noted that the method by which the computer device obtains the severity level of the consequences corresponding to the key potential hazard scenario can refer to the relevant content on "obtaining the severity level of the consequences corresponding to each potential hazard scenario" in the above embodiments, and will not be repeated here.

[0119] Step S1042: Determine the residual risk corresponding to the key potential hazard scenario based on the probability of the triggering event and the failure probability of each preset safety measure.

[0120] In this step, for each critical potential hazard scenario, the computer equipment can determine the residual risk corresponding to the critical potential hazard scenario based on the probability of occurrence of the triggering event corresponding to the critical potential hazard scenario and the failure probability of each preset safety measure.

[0121] For example, the computer device can determine the residual risk corresponding to the critical potential hazard scenario based on the probability of occurrence of the triggering event corresponding to the critical potential hazard scenario and the failure probability of each preset safety measure using the following formula (1).

[0122] Residual risk = Probability of triggering event * Probability of failure of all preset safety measures (Formula 1)

[0123] Of course, based on the probability of the triggering event corresponding to the critical potential hazard scenario and the failure probability of each preset safety measure, the computer equipment can also determine the residual risk corresponding to the critical potential hazard scenario through other variations or equivalent formulas of the above formula (1).

[0124] Step S1043: Determine the tolerable frequency of occurrence of the key potential hazard scenarios based on the severity level of the consequences corresponding to the key potential hazard scenarios.

[0125] In this step, for each critical potential hazard scenario, the computer equipment can determine the tolerable frequency of occurrence of that critical potential hazard scenario based on the severity level of the consequences it corresponds to.

[0126] In one possible implementation, the computer device can query the correspondence between a preset reference consequence severity level and the corresponding reference tolerable occurrence frequency based on the consequence severity level corresponding to the critical potential hazard scenario, and determine the tolerable occurrence frequency corresponding to the critical potential hazard scenario.

[0127] It should be noted that the correspondence between the preset reference consequence severity level and the corresponding reference tolerable occurrence frequency involved in the embodiments of this application may differ for different energy storage scenarios under test. That is, the tolerance for different reference consequence severity levels varies in different energy storage scenarios under test. For example, energy storage systems deployed in data centers are more concerned with property damage caused by accidents, while energy storage systems deployed in densely populated areas require that the probability of personal injury or death be as low as possible. The reference tolerable occurrence frequency corresponding to different reference consequence severity levels can be flexibly adjusted according to actual needs.

[0128] It should be understood that the reference tolerable frequency of occurrence corresponding to different reference consequence severity levels needs to meet the pre-set regulatory agency guidelines, energy storage industry standards and / or expert recommendations, etc.

[0129] For ease of understanding, this application embodiment uses a table to illustrate the correspondence between the preset reference consequence severity level and the corresponding reference tolerable occurrence frequency.

[0130] Table 4 illustrates the correspondence between preset reference consequence severity levels and corresponding reference tolerable occurrence frequencies.

[0131]

[0132] It should be noted that the number of reference consequence severity levels, the level description corresponding to each reference consequence severity level, and the corresponding reference tolerable occurrence frequency in Table 4 can be flexibly adjusted according to actual needs, thereby demonstrating stronger applicability to different scenarios.

[0133] In another possible implementation, the computer device can output the severity level of the consequences corresponding to the critical potential hazard scenario in order to receive the tolerable frequency of occurrence of the critical potential hazard scenario input by the user.

[0134] In another possible implementation, the computer device can send a tolerability query message to other devices containing the severity level of the consequences corresponding to the critical potential hazard scenario, so that the other devices can respond to the tolerability query message and return to the computer device the tolerable frequency of occurrence corresponding to the critical potential hazard scenario.

[0135] Of course, computer equipment can also determine the tolerable frequency of occurrence of a critical potential hazard scenario through other means, based on the severity level of the consequences of that critical potential hazard scenario.

[0136] In summary, in this embodiment of the application, for each key potential hazard scenario, the residual risk corresponding to the key potential hazard scenario is determined by the probability of occurrence of the triggering event corresponding to the key potential hazard scenario and the failure probability of each preset safety measure. Furthermore, the tolerable occurrence frequency corresponding to the key potential hazard scenario is determined by the severity level of the consequences corresponding to the key potential hazard scenario. This method can accurately determine the residual risk and tolerable occurrence frequency corresponding to different key potential hazard scenarios, so that the safety test of the energy storage scenario under test can be carried out by comprehensively considering the residual risk and the tolerable occurrence frequency.

[0137] In one exemplary embodiment, Figure 5 This is a flowchart illustrating a method for determining whether the safety of an energy storage scenario under test meets preset safety requirements in one embodiment. This application embodiment provides an exemplary description of the relevant content in step S105 above, "determining whether the safety of the energy storage scenario under test meets preset safety requirements based on the residual risk and tolerable frequency of occurrence corresponding to each key potential hazard scenario." For example... Figure 5 As shown, the method in this application embodiment may include the following steps:

[0138] Step S1051: Based on the residual risk and tolerable occurrence frequency corresponding to each key potential hazard scenario, determine the risk reduction factor corresponding to each key potential hazard scenario.

[0139] In this step, for each critical potential hazard scenario, the computer equipment can determine the risk reduction factor corresponding to that critical potential hazard scenario based on the residual risk and tolerable frequency of occurrence.

[0140] For example, the computer device can determine the risk reduction factor corresponding to the critical potential hazard scenario based on the residual risk and tolerable frequency of occurrence of the critical potential hazard scenario using the following formula (2).

[0141] Risk Reduction Factor (RPF) = Residual Risk / Tolerable Occurrence Frequency (Formula 2)

[0142] Of course, based on the residual risk and tolerable frequency of occurrence corresponding to the key potential hazard scenario, the computer equipment can also determine the risk reduction factor corresponding to the key potential hazard scenario through other variations or equivalent formulas of the above formula (2).

[0143] Furthermore, if the risk reduction factor corresponding to each key potential hazard scenario is less than or equal to 1, the computer equipment can determine that the failure efficiency of the energy storage scenario under the current preset safety measures can meet the risk reduction factor requirements, and execute step S1052; if the risk reduction factor corresponding to any key potential hazard scenario is greater than 1, the computer equipment can determine that the failure efficiency of the energy storage scenario under the current preset safety measures does not meet the risk reduction factor requirements, and execute step S1053.

[0144] Step S1052: Determine that the safety of the energy storage scenario under test meets the preset safety requirements.

[0145] In this step, the computer equipment can determine that the safety of the energy storage scenario under test can meet the preset safety requirements under the current preset safety measures, that is, determine that the safety of the energy storage scenario under test meets the preset safety requirements.

[0146] Step S1053: Determine that the safety of the energy storage scenario under test does not meet the preset safety requirements.

[0147] In this step, the computer equipment can determine that the safety of the energy storage scenario under test does not meet the preset safety requirements under the current preset safety measures, that is, determine that the safety of the energy storage scenario under test does not meet the preset safety requirements, so that the preset safety measures corresponding to the energy storage scenario under test can be adjusted in a timely manner.

[0148] In summary, in this embodiment of the application, by determining the risk reduction factor corresponding to each key potential hazard scenario based on the residual risk and tolerable occurrence frequency of each key potential hazard scenario, and by determining whether the safety of the energy storage scenario under test meets the preset safety requirements based on the risk reduction factor corresponding to each key potential hazard scenario, the safety detection of the energy storage scenario under test is improved by using the risk reduction factor determined based on the residual risk and tolerable occurrence frequency.

[0149] In some embodiments, if it is determined that the safety of the energy storage scenario under test does not meet the preset safety requirements, the computer device can also determine the target safety improvement measures corresponding to each key potential hazard scenario with a risk reduction factor greater than 1.

[0150] For example, the target safety improvement measures corresponding to any key potential hazard scenario may include, but are not limited to: new safety measures (whose failure probability needs to be less than or equal to 1 / RRF), or safety measures obtained by adjusting the current preset safety measures (whose failure probability is lower than the failure probability of the current preset safety measures, so that the risk reduction factor RRF corresponding to each key potential hazard scenario is less than or equal to 1).

[0151] In one possible implementation, for each critical potential hazard scenario with a risk reduction factor greater than 1, the computer device can output the critical potential hazard scenario with a risk reduction factor greater than 1 to facilitate receiving the target safety improvement measures corresponding to the critical potential hazard scenario input by the user.

[0152] In another possible implementation, for each critical potential hazard scenario with a risk reduction factor greater than 1, the computer device can send an improvement measure query message containing the improvement measure query message for that critical potential hazard scenario to other devices, so that the other devices can respond to the improvement measure query message and return the target safety improvement measure corresponding to that critical potential hazard scenario to the computer device.

[0153] Of course, computer equipment can also identify target security improvement measures in other ways.

[0154] Furthermore, for each critical potential hazard scenario, the computer equipment can update the preset safety measures corresponding to the critical potential hazard scenario based on the target safety improvement measures corresponding to the critical potential hazard scenario, so that the updated preset safety measures can be used for safety assurance in the future, thereby helping to further improve the safety operation level of the energy storage system in the energy storage scenario under test.

[0155] In one exemplary embodiment, Figure 6This is a flowchart illustrating a safety detection method for a user-side energy storage scenario in another embodiment. For ease of understanding, this embodiment uses an energy storage charging station as an example to exemplify the overall process of the safety detection method for a user-side energy storage scenario. Figure 6 As shown, the method in this application embodiment may include the following steps:

[0156] Step S601: The computer equipment can acquire the target scene elements of the energy storage scenario to be tested.

[0157] Step S602: The computer equipment can determine the potential hazards in the energy storage scenario under test based on the target scenario elements.

[0158] Step S603: The computer equipment can determine the corresponding potential hazard scenarios based on each potential hazard source.

[0159] Table 5 is a schematic table of hazard identification results corresponding to the energy storage charging station scenario. As shown in Table 5, the computer equipment can identify 18 potential hazard sources in 6 categories, as well as the corresponding potential hazard scenarios.

[0160] Table 5 shows the hazard identification results for energy storage charging station scenarios.

[0161]

[0162] Step S604: The computer equipment can obtain the severity level and probability level of the consequences corresponding to each potential hazardous scenario.

[0163] Step S605: For each potential hazardous scenario, the computer equipment can determine the risk level corresponding to the potential hazardous scenario based on the severity level and probability level of the consequences.

[0164] Table 6 is a schematic diagram of the assessment results for the severity level, likelihood level, and risk level of consequences corresponding to different potential hazardous scenarios.

[0165] Potential hazardous scenarios Consequence Probability Level Severity level of consequences Risk level 1 C’ E 6 2 B’ D 4 3 B’ E 5 4 B’ D 4 5 B’ D 4 6 B’ C 3 7 B’ D 5 8 B’ D 5 9 B’ D 4 10 B’ E 5 11 B’ E 5 12 C’ E 6 13 B’ D 4 14 A’ D 3 15 B’ E 5 16 A’ C 2 17 B’ D 4 18 C’ D 5

[0166] Step S606: The computer equipment can identify key potential hazards from each potential hazard scenario based on the risk level corresponding to each potential hazard scenario.

[0167] For example, computer equipment can designate potential hazardous scenarios 1 and 12, which have a risk level greater than or equal to a preset risk level threshold (such as risk level 6), as key potential hazardous scenarios.

[0168] Step S607: For each critical potential hazard scenario, the computer device can obtain the probability of occurrence of the triggering event corresponding to the critical potential hazard scenario, the failure probability of each preset safety measure, and the severity level of the consequences.

[0169] Step S608: For each critical potential hazard scenario, the computer equipment can determine the residual risk corresponding to the critical potential hazard scenario based on the probability of occurrence of the triggering event corresponding to the critical potential hazard scenario and the failure probability of each preset safety measure.

[0170] Step S609: For each critical potential hazard scenario, the computer equipment can determine the tolerable frequency of occurrence of the critical potential hazard scenario based on the severity level of the consequences corresponding to the critical potential hazard scenario.

[0171] Step S610: The computer equipment can determine the risk reduction factor corresponding to each key potential hazard scenario based on the residual risk and tolerable occurrence frequency corresponding to each key potential hazard scenario.

[0172] If the risk reduction factor corresponding to each key potential hazard scenario is less than or equal to 1, then proceed to step S611; if the risk reduction factor corresponding to any key potential hazard scenario is greater than 1, then proceed to step S612.

[0173] Step S611: The computer equipment can determine that the safety of the energy storage scenario under test meets the preset safety requirements.

[0174] Step S612: The computer equipment can determine that the safety of the energy storage scenario under test does not meet the preset safety requirements.

[0175] Step S613: The computer equipment can determine the target safety improvement measures corresponding to each key potential hazard scenario with a risk reduction factor greater than 1.

[0176] Step S614: For each critical potential hazard scenario, the computer equipment can update the preset safety measures corresponding to the critical potential hazard scenario based on the target safety improvement measures corresponding to the critical potential hazard scenario.

[0177] Table 7 is a schematic diagram of the safety test results for energy storage charging station scenarios.

[0178]

[0179] In summary, the safety testing method for user-side energy storage scenarios provided in this application includes a systematic safety evaluation process, covering all scenario elements of the energy storage scenario under test. This enables a more comprehensive identification of potential hazards and risk assessment, thereby improving the comprehensiveness, accuracy, and guidance of the safety testing results for user-side energy storage scenarios. Furthermore, the safety testing method for user-side energy storage scenarios in this application can be adaptively adjusted according to the safety needs of different energy storage scenarios under test, exhibiting strong scenario adaptability and meeting the safety testing requirements of various energy storage scenarios.

[0180] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0181] Based on the same inventive concept, this application also provides a security detection device for implementing the security detection method for the user-side energy storage scenario described above. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the security detection device for the user-side energy storage scenario provided below can be found in the limitations of the security detection method for the user-side energy storage scenario described above, and will not be repeated here.

[0182] In one exemplary embodiment, Figure 7 This is a schematic diagram of the structure of a safety detection device in a user-side energy storage scenario in one embodiment, such as... Figure 7 As shown, the safety detection device for user-side energy storage scenarios in this application embodiment may include: a first acquisition module 701, a first determination module 702, an identification module 703, a second acquisition module 704, and a second determination module 705.

[0183] The system comprises: a first acquisition module 701 for acquiring target scenario elements of the energy storage scenario under test; a first determination module 702 for determining each potential hazardous scenario existing in the energy storage scenario under test based on the target scenario elements, and determining the risk level corresponding to each potential hazardous scenario; an identification module 703 for identifying each key potential hazardous scenario from among the potential hazardous scenarios based on the risk level corresponding to each potential hazardous scenario; a second acquisition module 704 for acquiring the residual risk and tolerable occurrence frequency corresponding to each key potential hazardous scenario; and a second determination module 705 for determining whether the safety of the energy storage scenario under test meets the preset safety requirements based on the residual risk and tolerable occurrence frequency corresponding to each key potential hazardous scenario.

[0184] In an exemplary embodiment, the first determining module 702 may include: a first determining unit, configured to determine each potential hazard source existing in the energy storage scenario to be tested based on the target scenario elements; and a second determining unit, configured to determine the corresponding potential hazard scenario based on each potential hazard source.

[0185] In an exemplary embodiment, the first determining module 702 may include: a first acquiring unit, configured to acquire the severity level and probability level of consequences corresponding to each potential hazardous scenario; and a third determining unit, configured to determine the risk level corresponding to each potential hazardous scenario based on the severity level and probability level of consequences corresponding to the potential hazardous scenario.

[0186] In an exemplary embodiment, the second acquisition module 704 may include: a second acquisition unit, configured to acquire, for each key potential hazard scenario, the probability of occurrence of a triggering event, the probability of failure of each preset safety measure, and the severity level of the consequences; a fourth determination unit, configured to determine the residual risk corresponding to the key potential hazard scenario based on the probability of occurrence of the triggering event and the probability of failure of each preset safety measure; and a fifth determination unit, configured to determine the tolerable frequency of occurrence corresponding to the key potential hazard scenario based on the severity level of the consequences corresponding to the key potential hazard scenario.

[0187] In an exemplary embodiment, the second determining module 705 may include: a sixth determining unit, configured to determine the risk reduction factor corresponding to each key potential hazard scenario based on the residual risk and tolerable occurrence frequency corresponding to each key potential hazard scenario; a seventh determining unit, configured to determine that the safety of the energy storage scenario under test meets the preset safety requirements if the risk reduction factor corresponding to each key potential hazard scenario is less than or equal to 1; and an eighth determining unit, configured to determine that the safety of the energy storage scenario under test does not meet the preset safety requirements if the risk reduction factor corresponding to any key potential hazard scenario is greater than 1.

[0188] In an exemplary embodiment, the user-side energy storage scenario safety detection device of this application embodiment may further include: a third determining module, configured to determine target safety improvement measures corresponding to each key potential hazard scenario with a risk reduction factor greater than 1 if the eighth determining unit determines that the safety of the energy storage scenario under test does not meet the preset safety requirements; and an updating module, configured to update the preset safety measures corresponding to each key potential hazard scenario according to the target safety improvement measures corresponding to the key potential hazard scenario.

[0189] The safety detection device for user-side energy storage scenarios provided in this application can be used to execute the technical solutions in the above-described safety detection method embodiments for user-side energy storage scenarios. Its implementation principle and technical effects are similar, and will not be repeated here.

[0190] The modules in the safety detection device for the aforementioned user-side energy storage scenario can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0191] In one exemplary embodiment, Figure 8 This is a schematic diagram of the structure of a computer device in one embodiment, such as... Figure 8 As shown, the computer device in this application embodiment may include a processor, memory, input / output interface (I / O), and communication interface. The processor, memory, and I / O interface are connected via a system bus, and the communication interface is connected to the system bus via the I / O interface. The processor of this computer device provides computing and control capabilities. The memory of this computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of this computer device stores data information involved in the safety detection process of user-side energy storage scenarios. The I / O interface of this computer device is used for exchanging information between the processor and external devices. The communication interface of this computer device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the technical solutions in any of the user-side energy storage scenario safety detection method embodiments of this application.

[0192] Those skilled in the art will understand that Figure 8The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0193] In one exemplary embodiment, a computer device is also provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps in the above embodiments of the security detection method for any user-side energy storage scenario.

[0194] In one exemplary embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above embodiments of the security detection method for any user-side energy storage scenario.

[0195] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above embodiments of the security detection method for any user-side energy storage scenario.

[0196] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0197] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above 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 application.

[0198] The above embodiments merely illustrate several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of this application's patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for security detection of a user-side energy storage scenario, characterized in that, The method comprises: acquiring a target scene element of a to-be-tested energy storage scene; determining each potential dangerous scenario existing in the to-be-tested energy storage scene according to the target scene element, and determining a risk level corresponding to each potential dangerous scenario; identifying each key potential dangerous scenario from each potential dangerous scenario according to the risk level corresponding to each potential dangerous scenario; acquiring a residual risk and a tolerable occurrence frequency corresponding to each key potential dangerous scenario; determining whether the safety of the to-be-tested energy storage scene meets a preset safety requirement according to the residual risk and the tolerable occurrence frequency corresponding to each key potential dangerous scenario.

2. The method of claim 1, wherein, The determination of each potential dangerous scenario according to the target scene element comprises: determining each potential dangerous source existing in the to-be-tested energy storage scene according to the target scene element; determining the corresponding potential dangerous scenario according to each potential dangerous source.

3. The method of claim 1, wherein, The determination of the risk level corresponding to each potential dangerous scenario comprises: acquiring a consequence severity level and a consequence possibility level corresponding to each potential dangerous scenario; for each potential dangerous scenario, determining the risk level corresponding to the potential dangerous scenario according to the consequence severity level and the consequence possibility level corresponding to the potential dangerous scenario.

4. The method according to any one of claims 1 to 3, characterized in that, The acquisition of the residual risk and the tolerable occurrence frequency corresponding to each key potential dangerous scenario comprises: for each key potential dangerous scenario, acquiring a trigger event occurrence probability, a failure probability of each preset safety measure, and a consequence severity level corresponding to the key potential dangerous scenario; determining the residual risk corresponding to the key potential dangerous scenario according to the trigger event occurrence probability and the failure probability of each preset safety measure; determining the tolerable occurrence frequency corresponding to the key potential dangerous scenario according to the consequence severity level corresponding to the key potential dangerous scenario.

5. The method according to any one of claims 1-3, characterized in that, The determination of whether the safety of the to-be-tested energy storage scene meets the preset safety requirement according to the residual risk and the tolerable occurrence frequency corresponding to each key potential dangerous scenario comprises: determining a risk reduction factor corresponding to each key potential dangerous scenario according to the residual risk and the tolerable occurrence frequency corresponding to each key potential dangerous scenario; if the risk reduction factor corresponding to each key potential dangerous scenario is less than or equal to 1, it is determined that the safety of the to-be-tested energy storage scene meets the preset safety requirement; if the risk reduction factor corresponding to any key potential dangerous scenario is greater than 1, it is determined that the safety of the to-be-tested energy storage scene does not meet the preset safety requirement.

6. The method of claim 5, wherein, The method further comprises: if it is determined that the safety of the to-be-tested energy storage scene does not meet the preset safety requirement, determining a target safety improvement measure corresponding to each key potential dangerous scenario with the risk reduction factor greater than 1; for each key potential dangerous scenario, updating the preset safety measure corresponding to the key potential dangerous scenario according to the target safety improvement measure corresponding to the key potential dangerous scenario. 7.A security detection apparatus for a user-side energy storage scenario, characterized in that, The device comprises: a first acquisition module configured to acquire a target scene element of a to-be-tested energy storage scene; A first determining module is configured to determine each potential dangerous scenario existing in the to-be-tested energy storage scene according to the target scene element, and determine a risk level corresponding to each potential dangerous scenario; An identifying module is configured to identify each key potential dangerous scenario from each potential dangerous scenario according to the risk level corresponding to each potential dangerous scenario; A second acquiring module is configured to acquire a residual risk and a tolerable occurrence frequency corresponding to each key potential dangerous scenario; A second determining module is configured to determine whether the safety of the to-be-tested energy storage scene meets a preset safety requirement according to the residual risk and the tolerable occurrence frequency corresponding to each key potential dangerous scenario.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method in any one of claims 1 to 6.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method in any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method in any one of claims 1 to 6.

Images