Safety guarantee system of centralized large-scale power grid energy storage power station

Abstract

The invention belongs to the technical field of power grid energy storage systems, and discloses a safety guarantee system of a centralized large-scale power grid energy storage power station. Comprising an equipment data acquisition module, an equipment state calculation module, a path planning module, a personnel data scoring module and a path generation module, and an equipment state report, user information data and personnel positioning data are analyzed through the path planning module, so that a worker can carry out detection and maintenance on a plurality of battery packs needing to be detected and maintained; according to the method, high-efficiency inspection is realized, the safety guarantee efficiency of the energy storage power station is greatly improved, the safety guarantee of workers in the face of relatively large danger can be greatly improved through the emergency path planning data obtained through analysis according to an equipment state report, and generally, the safety of the workers is greatly improved. The method has the remarkable advantages of being high in routing inspection aiming capability, high in routing inspection efficiency improving effect and high in safety guarantee in case of danger.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid energy storage systems, and more specifically, to a safety guarantee system for a centralized large-scale power grid energy storage power station. Background Art

[0002] An energy storage power station refers to a device system that stores, converts, and releases recyclable electric energy through electrochemical batteries or electromagnetic energy storage media. Thanks to the rapid development of China's economy, power supply has been fully popularized in China. However, along with it are the time differences, regional differences, and power generation and consumption differences in electricity demand. Therefore, energy storage power stations have emerged. Since electric power is easily affected by various factors during the storage process, the safety of energy storage power stations is threatened. The traditional response method is to detect and investigate potential safety hazards through manual inspections. However, this response method not only increases the operating cost of the energy storage power station, but also easily increases the labor cost and time cost during the inspection process due to repeated inspections of safety battery packs, resulting in a low safety guarantee efficiency.

[0003] The patent with the application publication number CN114123270A discloses a control method and system for a centralized large-scale battery energy storage power station. Through the energy storage management and control system EMS, it is connected to the corresponding battery management system BMS in each energy storage unit, and the battery power of each battery cluster in each energy storage unit is monitored in real time through the battery management system BMS. According to the high-efficiency operating power range of the PCS device and the real-time monitored power status of the energy storage unit system, scientific and reasonable power distribution is carried out to achieve safe, efficient, rapid response, and execution of charge and discharge plans as well as power grid power dispatching instructions, enabling the energy storage power station to achieve the target effects of suppressing power grid power fluctuations, adjusting power surpluses and shortages, and ensuring the safe operation of the power grid.

[0004] However, for the above-mentioned control method and system for a centralized large-scale battery energy storage power station, although the monitoring and distribution of the corresponding battery clusters are realized to a certain extent through the energy storage management and control system EMS and the battery management system BMS, in the use of energy storage power stations, safety guarantee is of utmost importance. Since the energy storage power station stores electric power in battery packs in the form of chemical energy or electromagnetic energy, etc., this makes the energy storage power station vulnerable to various factors, resulting in dangerous situations such as the shutdown, fire, or even explosion of the energy storage power station. Moreover, since the traditional safety guarantee measures are realized based on manual inspections, this not only increases the operating cost of the energy storage power station, but also easily exposes the staff directly to danger during the maintenance and inspection of the battery packs in the energy storage power station.

[0005] In view of this, the present invention proposes a safety guarantee system for a centralized large-scale power grid energy storage power station to solve the above problems. Summary of the Invention

[0006] To overcome the above-mentioned defects of the prior art and to achieve the above object, the present invention provides the following technical solutions: including:

[0007] The device data acquisition module is used to collect device data information and environmental data information through a collection device;

[0008] The device status calculation module is used to calculate the device data information and environmental data information to obtain a device status report, and the device status report includes a device good report and a device repair report;

[0009] The path planning module is used to receive the device status report, and judge the device status report through a data recognition model to judge whether to generate path planning data, and generate path planning data for the judgment result that path planning is required. The judgment criterion of the data recognition model is that if the device status report is a device repair report, path planning data needs to be generated, and if the device status report is a device good report, path planning data does not need to be generated;

[0010] The path planning module is also used to receive the user information data and personnel positioning data generated by the personnel information login module and the personnel positioning module, and calculate the path planning data through the personnel ability evaluation model, task priority model and dynamic path adjustment model;

[0011] Further, the path planning module includes:

[0012] The data recognition module is used to judge the device good report and device repair report in the device status report based on the data recognition model. If the device status report recognized is a device good report, path planning data does not need to be generated. If the device status report recognized is a device repair report, path planning data needs to be generated;

[0013] The data recognition module is also used to obtain the device repair report in the total device status report, perform deviation sorting according to the value of the comprehensive reference value, and transmit it to the task assignment module;

[0014] The data retrieval module is used to retrieve the device status report, user information data and personnel positioning data in the device status calculation module, personnel information login module and personnel positioning module based on the data retrieval model;

[0015] The personnel evaluation module is used to calculate the user information data based on the personnel ability evaluation model, output the comprehensive ability score data, and transmit it to the task assignment module;

[0016] The task evaluation module is used to process the deviation sorting of the device repair report based on the task priority model to obtain task priority data, and transmit it to the task assignment module;

[0017] A task allocation module, which is used to process comprehensive ability scoring data, task priority data, and personnel positioning data based on a dynamic path adjustment model, and output path planning data;

[0018] Further, the path planning module receives a device status report, and uses a data recognition model to identify whether path planning is required. The specific working steps are as follows:

[0019] A1. Obtain the device status report generated by the device status calculation module;

[0020] A2. Based on the data recognition model, identify the content in the device status report. If the recognized content is a device good report, it means that no path planning data needs to be generated. If the recognized content is a device repair report, it means that path planning data needs to be generated, and step B1 is executed;

[0021] The path planning module receives user information data and personnel positioning data generated by the personnel information login module and the personnel positioning module, and calculates path planning data through a personnel ability evaluation model, a task priority model, and a dynamic path adjustment model. The specific working steps are as follows:

[0022] B1. Obtain user information data, a device repair report, and personnel positioning data;

[0023] B2. Based on the user information data obtained in step B1, calculate comprehensive ability scoring data through a personnel ability evaluation model;

[0024] B3. Based on the device repair report obtained in step B1, sort to obtain task priority data through a task priority model;

[0025] B4. Based on the comprehensive ability scoring data and task priority data obtained in steps B2 and B3, calculate the original path planning data through a dynamic path adjustment model;

[0026] B5. Based on the personnel positioning data and path planning data obtained in steps B1 and B4, perform real-time calculation through a dynamic path adjustment model to obtain path planning data;

[0027] The personnel data scoring module is used to calculate comprehensive data information, and based on a preset working time unit, obtain personnel comprehensive data and transmit it to the personnel information login module to be merged into the user information data. The comprehensive data information includes arrival speed data, task difficulty data, and repair time data;

[0028] Further, the steps for calculating the comprehensive data information include:

[0029] C1. Obtain the comprehensive data information;

[0030] C2. Based on the comprehensive data information obtained in step C1, using a data calculation model, perform a weighted sum on the arrival speed data, task difficulty data, and maintenance time data to obtain the comprehensive personnel data;

[0031] C3. Based on the comprehensive data information and the comprehensive personnel data in steps C1 and C2, take the comprehensive personnel data in step 2 as the historical comprehensive personnel data, input it into the data calculation model in the form of a compensation function, and recalculate to obtain the comprehensive personnel data;

[0032] The path generation module is used to generate a path planning route;

[0033] The path generation module further includes an emergency evacuation module, which is used to analyze based on the equipment status report to obtain emergency path planning data

[0034] Furthermore, the emergency evacuation module includes:

[0035] The data calling module is used to retrieve the equipment status report, personnel positioning data, equipment positioning data, and safety distance data based on the equipment calculation module, personnel positioning module, and database;

[0036] The risk judgment module is used to judge whether the equipment maintenance data reaches the danger standard based on a risk judgment model, where the risk judgment model judges the danger standard as the equipment maintenance data danger threshold stored in the database. If the equipment maintenance data is greater than or equal to the danger standard, it means that an escape route needs to be planned and transmitted to the escape planning module;

[0037] The escape planning module is used to calculate the personnel positioning data, equipment positioning data, and safety distance data based on a route planning model, output the escape path planning data, and transmit it to the real-time navigation module;

[0038] The real-time navigation module is used to calculate the escape path planning data and the personnel positioning data based on a real-time navigation model, output the user movement data, and transmit it to the voice broadcast module;

[0039] The voice broadcast module is used to convert in real time based on the user movement data through a voice navigation model and broadcast the required forward direction of the user in real time;

[0040] Furthermore, the emergency evacuation module analyzes based on the equipment status report, specifically including the following working steps:

[0041] D1, obtain the device status report, personnel location data, device location data, and safety distance data. Use the risk judgment model to determine whether the device maintenance report in the device status report reaches the danger standard. If the device maintenance report does not reach the danger standard, there is no need to plan an escape route. If the device maintenance report reaches the danger standard, an escape route needs to be planned and D2 is executed;

[0042] D2, based on the personnel location data, device location data, and safety distance data obtained in step D1, calculate the difference between the personnel location data and the device location data through the route planning model, and subtract the safety distance data to output the escape path planning data;

[0043] D3, based on the escape path planning data output in step D2, calculate the distance and relative direction between the personnel location data and the escape path planning data through the real-time navigation model. If the personnel location data is on the planned route of the escape path planning data, the user movement data needs to be output according to the escape path planning data. If the personnel location data is outside the planned route of the escape path planning data, the user needs to be guided to the planned route and the escape path planning data is integrated to output the user movement data;

[0044] D4, based on the user movement data output in step D3, perform real-time conversion through the voice navigation model and conduct real-time voice external playback;

[0045] Furthermore, it also includes:

[0046] The personnel information login module is used for the user to log in to the security guarantee system and read the corresponding user information data according to the user login information through the database;

[0047] The personnel location module is used to locate the current location of the user to obtain the personnel location data;

[0048] Furthermore, it includes the following steps:

[0049] S1, the user logs in to the security guarantee system through the personnel information login module and reads the user information data;

[0050] S2, the device data acquisition module acquires the device data information and the environmental data information;

[0051] S3, based on the device data information and the environmental data information acquired in step S2, calculate the comprehensive reference value through the device status calculation module and output the device status report;

[0052] S4. Based on the device status report output in step S3, identify the device status report using the data recognition model. If the recognition result is a device good report, it means that path planning is not required. If the recognition result is a device maintenance report, it means that path planning is required, and step S5 is executed;

[0053] S5. Obtain the device status report, user information data, and personnel location data;

[0054] S6. Based on the device status report, user information data, and personnel location data obtained in step S5, calculate the user information data using the personnel ability assessment model, and output the comprehensive ability score data. Sort the device maintenance reports in the device status report through the task priority model, and output the task priority data;

[0055] S7. Based on the comprehensive ability score data and task priority data output in step S6, and import the personnel location data obtained in step S5, and obtain the original path planning data through real-time calculation using the dynamic path adjustment model;

[0056] S8. Based on the comprehensive data information, calculate the comprehensive data information using the data calculation model to obtain the personnel comprehensive data;

[0057] S9. Use the personnel comprehensive data in step S8 as the historical personnel comprehensive data, input it into the calculation model for recalculation, and output the personnel comprehensive data;

[0058] S10. Transmit the personnel comprehensive data output in step S9 to the personnel information login module and integrate it into the user information data;

[0059] S11. Generate a path planning route based on the path planning data output in step S7;

[0060] S12. Based on the device status report output in step S3, use the risk judgment model to determine whether the device maintenance report in the device status report reaches the danger standard. If the device maintenance report does not reach the danger standard, there is no need to plan an escape route. If the device maintenance report reaches the danger standard, an escape route needs to be planned, and S13 is executed;

[0061] S13. Obtain the personnel location data, device location data, and safety distance data;

[0062] S14. Calculate the difference between the personnel location data and the device location data through the route planning model, and subtract the safety distance data to output the escape path planning data;

[0063] S15. Based on the escape path planning data output in step S14, calculate the distance and relative direction between the personnel location data and the escape path planning data through the real-time navigation model, and output the user movement data;

[0064] S16, based on the user movement data outputted in step S15, the user movement data is converted in real time through the voice navigation model and a real-time voice broadcast is performed.

[0065] The technical effects and advantages of the safety assurance system of a centralized large-scale power grid energy storage power station of the present invention are as follows:

[0066] The present invention calculates the equipment data information and environmental data information to obtain an equipment status report, which can intuitively show the operating status of the equipment, greatly reducing the huge labor cost and time cost brought by the traditional flood-type inspection method. The analysis of the equipment status report, user information data and personnel positioning data by the path planning module can enable the staff to achieve high-efficiency inspection when facing multiple battery packs that need to be inspected and repaired, greatly improving the safety efficiency of the energy storage power station. The comprehensive personnel data obtained by calculating the comprehensive data information can effectively improve the staff's work efficiency based on the staff's work performance. The emergency path planning data obtained by analyzing the equipment status report can greatly improve the safety of the staff when facing greater dangers. Generally speaking, the present invention has the significant advantages of strong inspection targeting ability, high effect of improving inspection efficiency and strong safety assurance when facing danger. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 It is a schematic diagram of a safety assurance system of a centralized large-scale power grid energy storage power station of the present invention. DETAILED DESCRIPTION

[0068] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0069] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two.

[0070] Depending on the context, as used herein, the words "if" and "when" may be interpreted as "when" or "while" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detecting (stated condition or event)" may be interpreted as "when determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)".

[0071] In addition, the step timings in the following method embodiments are only examples and not strictly limited.

[0072] In fact, the server devices deployed in the security guarantee system of the centralized large-scale grid energy storage power station may be composed of one or more devices. The above-mentioned security guarantee system of the centralized large-scale grid energy storage power station can be implemented as: a service instance, a virtual machine, or a hardware device. For example, the security guarantee system of the centralized large-scale grid energy storage power station can be implemented as a service instance deployed on one or more devices in a cloud node. Simply put, the security guarantee system of the centralized large-scale grid energy storage power station can be understood as a software deployed on a cloud node for providing the security guarantee system of the centralized large-scale grid energy storage power station for each client. Alternatively, the security guarantee system of the centralized large-scale grid energy storage power station can also be implemented as a virtual machine deployed on one or more devices in a cloud node. An application software for managing each client is installed in the virtual machine. Or, the security guarantee system of the centralized large-scale grid energy storage power station can also be implemented as a server composed of many identical or different types of hardware devices, and one or more hardware devices are set to provide the security guarantee system of the centralized large-scale grid energy storage power station for each client.

[0073] In terms of implementation form, the security guarantee system of the centralized large-scale grid energy storage power station and the client adapt to each other. That is, if the security guarantee system of the centralized large-scale grid energy storage power station is an application installed on a cloud service platform, then the client is a client that establishes a communication connection with the application; or if the security guarantee system of the centralized large-scale grid energy storage power station is implemented as a website, then the client is implemented as a web page; or if the security guarantee system of the centralized large-scale grid energy storage power station is implemented as a cloud service platform, then the client is implemented as a small program in an instant messaging application.

[0074] As Figure 1 shown, it is the system architecture diagram of the security guarantee system of the centralized large-scale grid energy storage power station provided by an embodiment of the present invention.

[0075] The security guarantee system of the centralized large-scale power grid energy storage power station described in the present invention can be set in a cloud server. In terms of implementation form, it can be used as one or more service devices, or can be installed as an application on the cloud (such as the server of a mobile service operator, a server cluster, etc.), or can also be developed into a website. According to the functions achieved, the security guarantee system of the centralized large-scale power grid energy storage power station can include a device data acquisition module, a device status calculation module, a personnel information login module, a personnel positioning module, a path planning module, a personnel data scoring module, and a path generation module. The modules described in the present invention can also be referred to as units, which refer to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, and are stored in the memory of the electronic device.

[0076] In the embodiment of the present invention, in the security guarantee system of the centralized large-scale power grid energy storage power station, each of the above modules can be independently implemented and called by other modules. Here, the call can be understood as that a certain module can be connected to multiple modules of another type and provide corresponding services for the multiple modules it is connected to. For example, the sharing and evaluation module can call the same information acquisition module to obtain the information collected by the information acquisition module. Based on the above characteristics, in the security guarantee system of the centralized large-scale power grid energy storage power station provided by the embodiment of the present invention, without modifying the program code, the applicable range of the security guarantee system architecture of the centralized large-scale power grid energy storage power station can be adjusted by adding modules and directly calling them, realizing cluster-level horizontal expansion, so as to achieve the purpose of quickly and flexibly expanding the security guarantee system of the centralized large-scale power grid energy storage power station. In practical applications, the above modules can be set in the same device or different devices, or can also be set in virtual devices, such as service instances in a cloud server.

[0077] Embodiment 1

[0078] Please refer to Figure 1 As shown, the security guarantee system of a centralized large-scale power grid energy storage power station described in this embodiment includes:

[0079] The device data acquisition module is used to acquire device data information and environmental data information through an acquisition device;

[0080] It should be explained that the device data information includes voltage data, current data, and device temperature data, and the environmental data information includes temperature data, humidity data, and gas concentration data;

[0081] The device status calculation module is used to calculate the device data information and environmental data information to obtain a device status report, and the device status report includes a device good report and a device repair report;

[0082] Further, the methods for calculating the device data information and the environmental data information include:

[0083] Obtain a set of device data information and environmental data information;

[0084] By substituting into the calculation formula:

[0085] Obtain a comprehensive reference value, where Ab is voltage data, Ac is current data, Ad is device temperature data, Ae is temperature data, Af is humidity data, Ag is gas concentration data, An is standard device data, Ad is standard environmental data, and As1, As2, As3, As4, As5, and As6 are corresponding weighting factors respectively;

[0086] When the comprehensive reference value Aa is less than the warning threshold AL1 or greater than the warning threshold AL2, output a device maintenance report. When the comprehensive reference value Aa is greater than or equal to the warning threshold AL1 and less than or equal to the warning threshold AL2, output a device good report;

[0087] It should be noted that the warning threshold AL1 and the warning threshold AL2 are obtained through experiments and input manually;

[0088] Package the device good report and the device maintenance report to obtain a device status report;

[0089] The path planning module is used to receive the device status report, and judge whether to generate path planning data through a data recognition model. For the judgment result that path planning is required, generate path planning data. The judgment criterion of the data recognition model is that if the device status report is a device maintenance report, path planning data needs to be generated. If the device status report is a device good report, path planning data does not need to be generated;

[0090] The path planning module is also used to receive the user information data and the personnel location data generated by the personnel information login module and the personnel location module, and calculate the path planning data through the personnel ability evaluation model, the task priority model, and the dynamic path adjustment model;

[0091] Further, the path planning module includes:

[0092] The data recognition module is used to judge the device good report and the device maintenance report in the device status report based on the data recognition model. If the device status report identified is a device good report, path planning data does not need to be generated. If the device status report identified is a device maintenance report, path planning data needs to be generated;

[0093] The data recognition module is also used to obtain the equipment maintenance report in the total equipment status report, perform deviation ranking based on the value of the comprehensive reference value, and transmit it to the task assignment module;

[0094] It should be noted that the total equipment status report refers to the equipment status reports of all energy storage groups in the energy storage power station; deviation ranking refers to the two-way corresponding ranking of the comprehensive reference values less than the warning threshold AL1 and greater than the warning threshold AL2. For example, the warning threshold AL1 is 1 and the warning threshold AL2 is 2. When there is a set of data -1, 0, 3, and 4, the deviation ranking is 0, 3, -1, and 4;

[0095] The data retrieval module is used to retrieve the equipment status report, user information data, and personnel location data in the equipment status calculation module, personnel information login module, and personnel location module based on the data retrieval model;

[0096] The personnel evaluation module is used to calculate the user information data based on the personnel ability evaluation model, output the comprehensive ability score data, and transmit it to the task assignment module;

[0097] The task evaluation module is used to process the deviation ranking of the equipment maintenance report based on the task priority model, obtain the task priority data, and transmit it to the task assignment module;

[0098] The task assignment module is used to process the comprehensive ability score data, task priority data, and personnel location data based on the dynamic path adjustment model, and output the path planning data;

[0099] Furthermore, the path planning module receives the equipment status report and identifies whether path planning is required through the data recognition model, specifically including the following working steps:

[0100] A1. Obtain the equipment status report generated by the equipment status calculation module;

[0101] A2. Based on the data recognition model, identify the content in the equipment status report. If the identified content is an equipment good report, it means that no path planning data needs to be generated. If the identified content is an equipment maintenance report, it means that path planning data needs to be generated, and step B1 is executed;

[0102] Furthermore, the path planning module receives the user information data and personnel location data generated by the personnel information login module and personnel location module, and calculates the path planning data through the personnel ability evaluation model, task priority model, and dynamic path adjustment model, specifically including the following working steps:

[0103] B1. Obtain the user information data, equipment maintenance report, and personnel location data;

[0104] B2. Based on the user information data obtained in step B1, calculate the comprehensive ability score data through the personnel ability evaluation model;

[0105] B3. Based on the equipment maintenance report obtained in step B1, sort through the task priority model to obtain the task priority data;

[0106] B4. Based on the comprehensive ability score data and task priority data obtained in steps B2 and B3, calculate the original path planning data through the dynamic path adjustment model;

[0107] B5. Based on the personnel positioning data and path planning data obtained in steps B1 and B4, perform real-time calculation through the dynamic path adjustment model to obtain the path planning data;

[0108] The personnel data scoring module is used to calculate the comprehensive data information, obtain the personnel comprehensive data based on the preset working time unit, and transmit it to the personnel information login module to be merged into the user information data. The comprehensive data information includes arrival speed data, task difficulty data, and repair time data;

[0109] It should be noted that the working time unit refers to the time from the user's login time to the user's logout time; the arrival speed data is the average speed of the user from receiving the equipment maintenance report to arriving at the maintenance location divided by the required distance; the task difficulty data is to assign values to the task priority data. The larger and smaller the task priority data, the higher the value of the task difficulty data; the repair time data is the difference between the time when the user arrives at the required maintenance location and the time when the repair is completed, and the unit is seconds;

[0110] Further, the steps for calculating the comprehensive data information include:

[0111] C1. Obtain the comprehensive data information;

[0112] C2. Based on the comprehensive data information obtained in step C1, through the data calculation model, perform weighted summation on the arrival speed data, task difficulty data, and repair time data to obtain the personnel comprehensive data;

[0113] C3. Based on the comprehensive data information and personnel comprehensive data in steps C1 and C2, take the personnel comprehensive data in step 2 as the historical personnel comprehensive data, input it into the data calculation model in the form of a compensation function, and recalculate to obtain the personnel comprehensive data;

[0114] The path generation module is used to generate a path planning route;

[0115] The path generation module further includes an emergency evacuation module, which is used to analyze based on the equipment status report to obtain the emergency path planning data;

[0116] Further, the emergency evacuation module includes:

[0117] A data call module, configured to retrieve device status reports, personnel location data, device location data, and safety distance data based on the device calculation module, personnel location module, and database;

[0118] It should be noted that the device location data is the location data information of all devices used in the energy storage power station;

[0119] A risk judgment module, configured to judge whether the device maintenance data reaches the danger standard based on a risk judgment model, where the risk judgment model judges the danger standard as the device maintenance data danger threshold stored in the database. If the device maintenance data is greater than or equal to the danger standard, it indicates that an escape route needs to be planned and transmitted to the escape planning module;

[0120] An escape planning module, configured to calculate the personnel location data, device location data, and safety distance data based on a route planning model, output escape path planning data, and transmit it to the real-time navigation module;

[0121] A real-time navigation module, configured to calculate the escape path planning data and personnel location data based on a real-time navigation model, output user movement data, and transmit it to the voice broadcast module;

[0122] A voice broadcast module, configured to be converted in real time through a voice navigation model based on the user movement data and broadcast the required forward direction of the user in real time by voice;

[0123] Further, the emergency evacuation module analyzes according to the device status report, specifically including the following working steps:

[0124] D1. Obtain the device status report, personnel location data, device location data, and safety distance data, and judge whether the device maintenance report in the device status report reaches the danger standard through the risk judgment model. If the device maintenance report does not reach the danger standard, there is no need to plan an escape route. If the device maintenance report reaches the danger standard, an escape route needs to be planned and D2 is executed;

[0125] D2. Based on the personnel location data, device location data, and safety distance data obtained in step D1, calculate the difference between the personnel location data and the device location data through the route planning model, and subtract the safety distance data to output the escape path planning data;

[0126] D3. Based on the escape route planning data output in step D2, calculate the distance and relative direction between the personnel positioning data and the escape route planning data through the real-time navigation model. If the personnel positioning data is located on the planned route of the escape route planning data, the user movement data needs to be output according to the escape route planning data. If the personnel positioning data is located outside the planned route of the escape route planning data, the user needs to be guided to the planned route and the escape route planning data needs to be integrated to output the user movement data;

[0127] D4. Based on the user movement data output in step D3, perform real-time conversion through the voice navigation model and conduct real-time voice external playback;

[0128] It also includes:

[0129] The personnel information login module is used for the user to log in to the security protection system and read the corresponding user information data according to the user login information through the database;

[0130] It should be noted that the user information data includes skill data, physical fitness data, and personnel comprehensive data;

[0131] The personnel positioning module is used to locate the current position of the user and obtain the personnel positioning data;

[0132] Furthermore, it includes the following steps:

[0133] S1. The user logs in to the security protection system through the personnel information login module and reads the user information data;

[0134] S2. The device data acquisition module acquires device data information and environmental data information;

[0135] S3. Based on the device data information and environmental data information acquired in step S2, calculate the comprehensive reference value through the device status calculation module and output the device status report;

[0136] S4. Based on the device status report output in step S3, identify the device status report through the data recognition model. If the recognition result is a device good report, it means that no path planning is required. If the recognition result is a device repair report, it means that path planning is required and step S5 is executed;

[0137] S5. Obtain the device status report, user information data, and personnel positioning data;

[0138] S6. Based on the device status report, user information data, and personnel positioning data obtained in step S5, calculate the user information data through the personnel ability evaluation model and output the comprehensive ability score data. Sort the device repair reports in the device status report through the task priority model and output the task priority data;

[0139] S7, based on the comprehensive ability score data and task priority data output in step S6, and importing the personnel location data obtained in step S5, the original path planning data is calculated in real time by the dynamic path adjustment model;

[0140] S8, based on the comprehensive data information, calculating the comprehensive data information through a data calculation model to obtain comprehensive personnel data;

[0141] S9, inputting the personnel comprehensive data in step S8 as historical personnel comprehensive data into the calculation model for recalculation, and outputting the personnel comprehensive data;

[0142] S10, transmitting the comprehensive personnel data outputted in step S9 to the personnel information login module and integrating it into the user information data;

[0143] S11, generating a path planning route based on the path planning data output in step S7;

[0144] S12, based on the equipment status report output in step S3, determine whether the equipment maintenance report in the equipment status report reaches the danger standard through the risk judgment model. If the equipment maintenance report does not reach the danger standard, there is no need to plan an escape route. If the equipment maintenance report reaches the danger standard, it is necessary to plan an escape route and execute S13;

[0145] S13, obtaining personnel positioning data, equipment positioning data and safety distance data;

[0146] S14, calculating the difference between the personnel positioning data and the device positioning data through the route planning model, subtracting the safety distance data, and outputting the escape path planning data;

[0147] S15, based on the escape path planning data outputted in step S14, the distance and relative direction between the personnel positioning data and the escape path planning data are calculated by a real-time navigation model, and the user movement data is outputted;

[0148] S16, based on the user movement data output in step S15, the user movement data is converted in real time through the voice navigation model and a real-time voice broadcast is performed;

[0149] In this embodiment, the beneficial effects are as follows. By calculating the device data information and environmental data information, the obtained device status report can intuitively display the operating status of the device, greatly reducing the huge labor cost and time cost brought by the traditional flood irrigation inspection method. Through the analysis of the device status report, user information data, and personnel positioning data by the path planning module, when the staff faces multiple battery packs that need to be detected and repaired, high-efficiency inspection can be achieved, greatly improving the safety guarantee efficiency of the energy storage power station. By calculating the comprehensive data information, the obtained comprehensive personnel data can effectively improve the operation efficiency of the staff according to their operation performance. By analyzing based on the device status report, the obtained emergency path planning data can greatly improve the safety guarantee of the staff when facing greater risks. Generally speaking, the present invention has the remarkable advantages of strong inspection targeting ability, high improvement in inspection efficiency, and strong safety guarantee when facing risks.

[0150] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms.

[0151] Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present invention. Any reference signs in the claims should not be regarded as limiting the claimed claim.

[0152] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is a theory, method, technology, and application system that uses a digital computer or a machine controlled by a digital computer to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to obtain the best results.

[0153] In addition, obviously, the term "including" does not exclude other units or steps, and the singular does not exclude the plural. The multiple units or devices stated in the system claims can also be implemented by one unit or device through software or hardware. Words such as first, second, etc. are used to represent names and do not represent any specific order.

[0154] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A safety guarantee system for a centralized large-scale power grid energy storage power station, characterized in that It includes a device data acquisition module, a device status calculation module, a path planning module, a personnel data scoring module, and a path generation module, where: The device data acquisition module is used to collect device data information and environmental data information through a collection device; The device status calculation module is used to calculate the device data information and environmental data information to obtain a device status report, and the device status report includes a device good report and a device repair report; The path planning module is used to receive the device status report, and judge whether to generate path planning data through a data recognition model, and generate path planning data for the judgment result that path planning is required. The judgment criterion of the data recognition model is that if the device status report is a device repair report, path planning data needs to be generated, and if the device status report is a device good report, path planning data does not need to be generated; The path planning module is also used to receive the user information data and personnel location data generated by the personnel information login module and the personnel location module, and calculate the path planning data through a personnel ability evaluation model, a task priority model, and a dynamic path adjustment model; The personnel data scoring module is used to calculate the comprehensive data information, and obtain the personnel comprehensive data based on the preset working time unit, and transmit it to the personnel information login module to be merged into the user information data. The comprehensive data information includes arrival speed data, task difficulty data, and repair time data; The path generation module is used to generate a path planning route; The path generation module also includes an emergency evacuation module, which is used to analyze based on the device status report to obtain emergency path planning data.

2. The safety guarantee system of a centralized large-scale power grid energy storage power station according to claim 1, characterized in that, It also includes: The personnel information login module is used for users to log in to the security protection system, and read the corresponding user information data through the database according to the user login information; The personnel location module is used to locate the current location of the user to obtain personnel location data.

3. The safety guarantee system of a centralized large-scale power grid energy storage power station according to claim 1, characterized in that, The path planning module includes: The data recognition module is used to judge the device good report and the device repair report in the device status report based on the data recognition model. If the device status report is recognized as a device good report, path planning data does not need to be generated. If the device status report is recognized as a device repair report, path planning data needs to be generated; The data recognition module is also used to obtain the device repair report in the total device status report, perform deviation sorting according to the value of the comprehensive reference value, and transmit it to the task assignment module; The data retrieval module is used to retrieve the device status report, user information data, and personnel location data in the device status calculation module, personnel information login module, and personnel location module based on the data retrieval model; The personnel evaluation module is used to calculate the user information data based on the personnel ability evaluation model, output the comprehensive ability score data, and transmit it to the task assignment module; The task evaluation module is used to process the deviation sorting of the device repair report based on the task priority model to obtain task priority data, and transmit it to the task assignment module; The task allocation module is used to process the comprehensive ability scoring data, task priority data, and personnel positioning data based on the dynamic path adjustment model, and output the path planning data.

4. The safety guarantee system of a centralized large-scale power grid energy storage power station according to claim 3, characterized in that, The path planning module receives the device status report and uses the data recognition model to identify whether path planning is required. The specific working steps are as follows: A1. Obtain the device status report generated by the device status calculation module; A2. Based on the data recognition model, identify the content in the device status report. If the recognized content is a device good report, it means that no path planning data needs to be generated. If the recognized content is a device repair report, it means that path planning data needs to be generated, and step B1 is executed; The path planning module receives the user information data and personnel positioning data generated by the personnel information login module and the personnel positioning module, and calculates the path planning data through the personnel ability evaluation model, task priority model, and dynamic path adjustment model. The specific working steps are as follows: B1. Obtain the user information data, device repair report, and personnel positioning data; B2. Based on the user information data obtained in step B1, calculate the comprehensive ability scoring data through the personnel ability evaluation model; B3. Based on the device repair report obtained in step B1, sort to obtain the task priority data through the task priority model; B4. Based on the comprehensive ability scoring data and task priority data obtained in steps B2 and B3, calculate the original path planning data through the dynamic path adjustment model; B5. Based on the personnel positioning data and path planning data obtained in steps B1 and B4, perform real-time calculation through the dynamic path adjustment model to obtain the path planning data.

5. The safety guarantee system of a centralized large-scale power grid energy storage power station according to claim 1, characterized in that, The steps for calculating the comprehensive data information include: C1. Obtain the comprehensive data information; C2. Based on the comprehensive data information obtained in step C1, use the data calculation model to perform weighted summation on the arrival speed data, task difficulty data, and repair time data to obtain the personnel comprehensive data; C3. Based on the comprehensive data information and personnel comprehensive data in steps C1 and C2, use the personnel comprehensive data in step 2 as the historical personnel comprehensive data and input it into the data calculation model in the form of a compensation function for recalculation to obtain the personnel comprehensive data.

6. The safety guarantee system for a centralized large-scale power grid energy storage power station according to claim 1, characterized in that The emergency evacuation module includes: The data calling module is used to retrieve the device status report, personnel positioning data, device positioning data, and safety distance data based on the device calculation module, personnel positioning module, and database; The risk judgment module is used to judge whether the device repair data reaches the danger standard based on the risk judgment model. The risk judgment model judges the danger standard as the device repair data danger threshold stored in the database. If the device repair data is greater than or equal to the danger standard, it means that an escape route needs to be planned and transmitted to the escape planning module; The escape planning module is used to calculate the personnel positioning data, device positioning data, and safety distance data based on the route planning model, output the escape path planning data, and transmit it to the real-time navigation module; The real-time navigation module is used to calculate the escape path planning data and personnel positioning data based on the real-time navigation model, output the user movement data, and transmit it to the voice broadcast module; The voice broadcast module is used to convert in real time based on the user's mobile data through a voice navigation model and broadcast the required forward direction of the user in real time by voice.

7. The safety guarantee system of a centralized large-scale power grid energy storage power station according to claim 6, characterized in that, The emergency evacuation module analyzes based on the device status report, and specifically includes the following working steps: D1. Obtain the device status report, personnel positioning data, device positioning data, and safety distance data. Use the risk judgment model to judge whether the device maintenance report in the device status report reaches the dangerous standard. If the device maintenance report does not reach the dangerous standard, there is no need to plan an escape route. If the device maintenance report reaches the dangerous standard, an escape route needs to be planned, and D2 is executed; D2. Based on the personnel positioning data, device positioning data, and safety distance data obtained in step D1, calculate the difference between the personnel positioning data and the device positioning data through the route planning model, and subtract the safety distance data to output the escape path planning data; D3. Based on the escape path planning data output in step D2, calculate the distance and relative direction between the personnel positioning data and the escape path planning data through the real-time navigation model. If the personnel positioning data is located in the planned route of the escape path planning data, the user's mobile data needs to be output according to the escape path planning data. If the personnel positioning data is located outside the planned route of the escape path planning data, the user needs to be guided to the planned route and the escape path planning data is integrated to output the user's mobile data; D4. Based on the user's mobile data output in step D3, convert it in real time through the voice navigation model and perform real-time voice external broadcast.

8. The safety guarantee system of a centralized large-scale power grid energy storage power station according to claim 7, characterized in that, It includes the following steps: S1. The user logs in to the security protection system through the personnel information login module and reads the user information data; S2. The device data acquisition module acquires device data information and environmental data information; S3. Based on the device data information and environmental data information acquired in step S2, calculate the comprehensive reference value based on the device status calculation module and output the device status report; S4. Based on the device status report output in step S3, identify the device status report based on the data identification model. If the identification result is a device good report, it means that no path planning is required. If the identification result is a device maintenance report, it means that path planning is required, and step S5 is executed; S5. Obtain the device status report, user information data, and personnel positioning data; S6. Based on the device status report, user information data, and personnel positioning data obtained in step S5, calculate the user information data through the personnel ability evaluation model and output the comprehensive ability score data. Sort the device maintenance reports in the device status report through the task priority model and output the task priority data; S7. Based on the comprehensive ability score data and task priority data output in step S6, and import the personnel positioning data obtained in step S5, calculate the original path planning data in real time through the dynamic path adjustment model; S8. Based on the comprehensive data information, calculate the comprehensive data information through the data calculation model to obtain the personnel comprehensive data; S9. Use the personnel comprehensive data in step S8 as the historical personnel comprehensive data, input it into the calculation model for recalculation, and output the personnel comprehensive data; S10, transmitting the comprehensive personnel data outputted in step S9 to the personnel information login module and integrating it into the user information data; S11, generating a path planning route based on the path planning data output in step S7; S12, based on the equipment status report output in step S3, determine whether the equipment maintenance report in the equipment status report reaches the danger standard through the risk judgment model. If the equipment maintenance report does not reach the danger standard, there is no need to plan an escape route. If the equipment maintenance report reaches the danger standard, it is necessary to plan an escape route and execute S13; S13, obtaining personnel positioning data, equipment positioning data and safety distance data; S14, calculating the difference between the personnel positioning data and the device positioning data through the route planning model, subtracting the safety distance data, and outputting the escape path planning data; S15, based on the escape path planning data outputted in step S14, the distance and relative direction between the personnel positioning data and the escape path planning data are calculated by a real-time navigation model, and the user movement data is outputted; S16, based on the user movement data outputted in step S15, the user movement data is converted in real time through the voice navigation model and a real-time voice broadcast is performed.

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