Path planning method, device and equipment for new energy station based on digital twinning

Abstract

The invention provides a path planning method, device and equipment for a new energy station based on digital twinning, and relates to an information processing technology in the field of new energy. In the application, a digital twinning intelligent operation and maintenance platform obtains information of each device, weather information and an accident position in a fire accident area in a digital twinning three-dimensional scene corresponding to a new energy station; determining a target parking position of the fire-fighting vehicle in the fire accident area according to the information of each device, the weather information and the accident position; and according to the predicted driving duration of the fire-fighting vehicle from the entrance position of the fire accident area to the target parking position, and the predicted number of the devices passing by by the fire-fighting vehicle, the probability of causing damage to the fire-fighting vehicle being greater than the first probability value, determining the optimal path of the fire-fighting vehicle driving from the entrance position to the target parking position. The method comprehensively considers various information in the fire accident area, can accurately plan the path which is more suitable for the fire-fighting vehicle to run, and improves the fire accident processing efficiency.

Description

Technical Field

[0001] The present application relates to information processing technology in the field of new energy, and in particular to a path planning method, device and equipment for new energy stations based on digital twins. Background Art

[0002] In the field of fire accident emergency response, especially when dealing with fire accidents in new energy sites (such as wind power stations, solar power stations and energy storage facilities), the rapid and accurate arrival of fire trucks is crucial to controlling the fire and reducing losses.

[0003] Traditionally, the route planning of fire trucks mainly relies on pre-set plans (planned before the fire accident according to the site layout, road network and expected risk points). However, relying solely on the plan planned before the fire, it is difficult for fire trucks to quickly adapt to the actual situation on the scene, resulting in the inability to reach the accident location (fire point) in the fire accident area in time. In addition, the occurrence of actual fire accidents is often accompanied by unforeseen complexity and dynamic changes. After arriving at the fire accident area, fire trucks need to temporarily adjust the dispatch strategy according to the on-site situation, but this impromptu decision often relies on personal experience and intuition, and still cannot guarantee that the fire trucks can quickly reach the fire point.

[0004] In summary, whether a pre-set plan or an impromptu decision is adopted, the existing fire accident handling plans have limitations, and it is difficult to ensure that the fire trucks can quickly reach the fire point in the fire accident area, which greatly affects the overall handling efficiency of the fire accident. Summary of the invention

[0005] The present application provides a path planning method, device and equipment for a new energy station based on digital twins, which can accurately plan a path that is more suitable for fire trucks in simulated drills of fire accidents, help fire trucks to quickly reach the accident location and deal with the fire accident, and can significantly improve the efficiency of handling fire accidents.

[0006] The present application provides a path planning method for a new energy station based on digital twins, which is applied to a digital twin intelligent operation and maintenance platform. The digital twin intelligent operation and maintenance platform displays a digital twin three-dimensional scene of the new energy station. The digital twin three-dimensional scene is a virtual three-dimensional scene built for the new energy station based on digital twin technology. The path planning method includes: Acquire information of each device in a fire accident area, weather information, and an accident location, wherein the fire accident area is an area within the digital twin three-dimensional scene of the new energy station; Determine a target parking position for a fire truck among a plurality of parking positions within the fire accident area according to the information of each device, the weather information and the accident position; Based on the predicted driving time of the fire truck from the entrance position of the fire accident area to the target parking position and the predicted number of first-category equipment among the various equipment passed by the fire truck, a first path for the fire truck to travel is determined among multiple paths from the entrance position to the target parking position, wherein the first-category equipment is equipment whose probability of causing damage to the fire truck is greater than a first probability value.

[0007] According to a path planning method provided by the present application, before determining the first path for the fire truck to travel, the method further includes: Determining a parking strategy of the fire truck at the target parking position, the parking strategy comprising a target parking direction, under which a water spraying position on a body of the fire truck is on a side close to the accident position; The step of determining a first path for the fire truck to travel among a plurality of paths from the entrance position to the target parking position comprises: When the fire truck stops at the target parking position according to the parking strategy, a first path for the fire truck to travel is determined among multiple paths from the entrance position to the target parking position.

[0008] According to a path planning method provided by the present application, the method determines a first path for the fire truck to travel from a plurality of paths from the entrance position to the target parking position according to the predicted driving time of the fire truck from the entrance position to the target parking position and the predicted number of first-category equipment among the equipment passed by the fire truck, including: Taking the shortest predicted driving time of the fire truck from the entrance position to the target parking position and the smallest predicted number of the first type of equipment passed by the fire truck as the optimization goal, a first path for the fire truck to travel is determined from multiple paths from the entrance position to the target parking position through a multi-factor non-dominated sorting genetic algorithm.

[0009] According to a path planning method provided by the present application, after determining the first path for the fire truck to travel, the method further includes: Acquire the locations of each exit in the fire accident area and the current locations of each target object to be evacuated; According to the exit position and the current position of the target object, a second path for each target object to travel from the current position to the corresponding exit position is determined by a preset path search algorithm.

[0010] According to a path planning method provided by the present application, determining a second path for each target object to travel from the current position to the corresponding exit position includes: Under the condition that each of the target objects does not pass through the second type of equipment among the devices, a second path for each of the target objects to travel from the current position to the corresponding exit position is determined, wherein the second type of equipment is equipment whose probability value of causing damage to the target object is greater than a second probability value.

[0011] According to a path planning method provided by the present application, determining a second path for each target object to travel from the current position to the corresponding exit position includes: When all paths from the current position of each target object to the corresponding exit position pass through the second type of equipment, the shortest path among all the paths in which the second type of equipment is located in the upwind direction when passing through the second type of equipment is determined as the second path from the current position of each target object to the corresponding exit position.

[0012] According to a path planning method provided by the present application, the method is applied to a virtual simulation environment, and the acquisition of information of each device in the fire accident area, weather information and the accident location includes: According to the preset simulation data for simulating the fire accident, the information of each device in the fire accident area, weather information and the accident location are obtained. According to a path planning method provided by the present application, the weather information at least includes wind direction information.

[0013] According to a path planning method provided by the present application, after determining the first path for the fire truck to travel, the method further includes: The first path is displayed in the digital twin three-dimensional scene by using image output.

[0014] The present application also provides a path planning device, which is applied to a digital twin intelligent operation and maintenance platform. The digital twin intelligent operation and maintenance platform displays a digital twin three-dimensional scene of a new energy station. The digital twin three-dimensional scene is a virtual three-dimensional scene built for the new energy station based on digital twin technology. The path planning device includes the following modules: A first acquisition module is used to obtain information of each device in a fire accident area, weather information, and an accident location, wherein the fire accident area is an area within the digital twin three-dimensional scene of the new energy station; A first determination module is used to determine a target parking position of a fire truck among a plurality of parking positions within the fire accident area according to the information of each device, the weather information and the accident position; The second determination module is used to determine a first path for the fire truck to travel among multiple paths from the entrance position to the target parking position based on the predicted driving time of the fire truck from the entrance position of the fire accident area to the target parking position and the predicted number of first-category equipment among the various equipment passed by the fire truck, wherein the first-category equipment is equipment whose probability of causing damage to the fire truck is greater than a first probability value.

[0015] The present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, a path planning method for a new energy station based on digital twins as described in any one of the above is implemented.

[0016] The present application also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it implements the path planning method for a new energy station based on digital twins as described in any of the above.

[0017] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements a path planning method for a new energy station based on digital twins as described in any one of the above.

[0018] The present application provides a path planning method, device and equipment for a new energy station based on digital twin. To implement the method of the present application, first obtain the information of each device in the fire accident area, weather information and accident location, the fire accident area is the area within the digital twin three-dimensional scene of the new energy station; then, according to the information of each device, the weather information and the accident location, determine the target parking location of the fire truck among multiple parking locations in the fire accident area; then, according to the predicted driving time of the fire truck from the entrance location of the fire accident area to the target parking location, and the predicted number of first-class equipment among the various equipment passed by the fire truck, determine the first path for the fire truck to travel among the multiple paths from the entrance location to the target parking location, the first-class equipment is the equipment whose probability of causing damage to the fire truck is greater than the first probability value. This application can implement fire drills for fire accidents based on the digital twin three-dimensional scene of the new energy station. After a fire accident occurs, this application comprehensively considers the information of various equipment in the fire accident area, weather information, accident location and other information, and can accurately plan the best path (i.e., the first path) that is more suitable for fire trucks to travel, which helps fire trucks to quickly reach the accident location in the fire accident area and deal with the fire accident, and can significantly improve the efficiency of handling fire accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present application or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 It is a flow chart of a path planning method for a new energy station based on digital twins shown in an embodiment of the present application; Figure 2 This is a schematic diagram of a simulated fire accident handling process shown in an embodiment of the present application; Figure 3 It is a structural schematic diagram of a path planning device for a new energy station based on digital twins shown in an embodiment of the present application; Figure 4 It is a schematic diagram of the physical structure of an electronic device shown in an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0022] The method of the present application can be applied to the handling of fire accidents in actual scenarios, and can also be applied to the handling of simulated fire accidents in virtual simulation environments. The principles of handling fire accidents in both are the same, and only the data sources used are different.

[0023] The execution subject of the method of the present application may be a path planning device, or any type of electronic device. The path planning method of the present application will be described below by taking the execution subject as an electronic device as an example.

[0024] To facilitate the description of the method of this application, the subsequent embodiments are described by taking the fire accident area as a new energy station as an example. When the fire accident area is other types of areas, the implementation principle of the method is the same as the implementation principle when the fire accident area is a new energy station.

[0025] In this application, a digital twin intelligent operation and maintenance platform needs to be built on the electronic device, and path planning is realized through the digital twin intelligent operation and maintenance platform. The following first introduces the construction process of the digital twin intelligent operation and maintenance platform in detail, which mainly includes the following two steps.

[0026] Step 1: Build a three-dimensional static model for new energy stations.

[0027] New energy stations can be, for example, wind power stations, photovoltaic power stations, energy storage power stations, etc.

[0028] When constructing a three-dimensional static model, the three-dimensional static model can be constructed based on the building information model (Building Information Modeling, BIM) corresponding to the new energy site and multi-source collected materials.

[0029] The building information model is a three-dimensional model produced during the design phase of a new energy station. The model contains the framework model, physical location information, and attribute information of each physical entity in the new energy station. The framework model refers to the basic geometric shape and structure of the buildings and equipment in the new energy station, the physical location information refers to the specific coordinates of these elements in the new energy station, and the attribute information includes the model, manufacturer, and operating status of the equipment.

[0030] Multi-source collection materials are various data and information sources required to build a three-dimensional static model of a new energy station. Multi-source collection materials may include laser point cloud, oblique photography, construction drawings, equipment structure drawings, equipment images and other data. Laser point cloud refers to the three-dimensional point cloud data of a new energy station obtained by laser scanning equipment, which is used to accurately restore the physical form of the new energy station. Oblique photography refers to photos of new energy stations taken from different angles using drones or ground photography equipment, which are formed into a three-dimensional model or texture map through splicing and processing. Construction drawings include architectural design drawings, equipment installation drawings, etc., which are used to provide detailed building and equipment information. Equipment structure drawings are used to describe the internal structure and working principle of the equipment. Equipment images refer to physical photos or videos of the equipment, which are used to assist in model construction and texture mapping. Multi-source collection materials can be set according to actual needs, and this embodiment does not impose specific restrictions on this.

[0031] According to the above-mentioned building information model and multi-source collection materials, a three-dimensional static model of the new energy station can be constructed. The three-dimensional static model can specifically include a three-dimensional static model of a building, a three-dimensional static model of key equipment, a three-dimensional static model of fire-fighting facilities, a three-dimensional static model of a panel cabinet, etc. Among them, the three-dimensional static model of a building refers to a three-dimensional model of a building in a new energy station constructed based on construction drawings and data such as laser point clouds. The three-dimensional static model of key equipment refers to a three-dimensional model of key equipment in a new energy station constructed based on data such as equipment structure drawings and equipment images. The three-dimensional static model of fire-fighting facilities refers to a three-dimensional model of fire-fighting facilities including fire-fighting systems and fire-fighting vehicles, which is used to simulate and evaluate fire emergency responses. The three-dimensional static model of a panel cabinet is a three-dimensional model constructed based on panel cabinet equipment such as control panels and distribution cabinets in a new energy station to display its layout and internal structure.

[0032] Secondly, when constructing a three-dimensional static model, it is necessary to follow the principle of 1:1 restoration of the new energy station in the physical world, so that each element in the three-dimensional static model is constructed according to its actual size in the real new energy station to ensure the accuracy of the model.

[0033] Step 2: Build a digital twin intelligent operation and maintenance platform.

[0034] Among them, digital twin is a technology that closely connects physical entities (such as new energy stations) with their virtual representations in the digital world (i.e. digital models). Through digital twin technology, the operation of physical entities can be simulated, monitored and optimized in real time.

[0035] In this application, the digital twin intelligent operation and maintenance platform can realize data mapping between three-dimensional static models and real-time data and panoramic visualization of the fire protection system.

[0036] Data mapping between three-dimensional static models and real-time data refers to associating the real-time operating data of new energy stations (such as equipment status, environmental monitoring data, etc.) with three-dimensional static models, so that the operating status of the equipment can be seen in real time on the digital twin intelligent operation and maintenance platform.

[0037] Panoramic visualization of the fire protection system refers to the use of a digital twin intelligent operation and maintenance platform to panoramically display the operating status of the fire protection system in the new energy station, including the real-time status of various equipment in the pump room (such as pressure gauges, water level gauges, valves, etc.), as well as the start and stop status of the fire pump.

[0038] The digital twin intelligent operation and maintenance platform in this embodiment adopts the BS (Browser Server) architecture, and users can access the various functions provided by the platform through a browser. The front end uses multiple graphics rendering engines such as UE (Unreal Engine, a real-time 3D rendering engine) and webGL (a JavaScript API running in a browser for rendering high-performance 2D and 3D graphics. Through WebGL, the platform can display complex three-dimensional models and animation effects in the browser, while realizing interactive operations with users). The back end is developed based on the industrial Internet platform, following the microservice development model (splitting the platform into multiple independent service modules, each module is responsible for different functions), and supports cloud containerized deployment (using the elasticity and scalability of cloud resources to reduce operation and maintenance costs) and local server deployment (ensuring data security and privacy).

[0039] In this application, the digital twin smart operation and maintenance platform can be deployed in the centralized control station corresponding to the new energy station to centrally manage and monitor the operation of the new energy station and improve the operation and maintenance efficiency. The centralized control station is responsible for managing and monitoring the operation of multiple new energy stations.

[0040] When realizing the data mapping between the three-dimensional static model and the real-time data, the three-dimensional static model of the new energy station is first divided into a plurality of different types of sub-models and named, for example, it can be classified according to the types of main equipment, auxiliary equipment, safety exits, roads, etc. Then, multiple digital twin model objects are established on the digital twin intelligent operation and maintenance platform, and then each sub-model is mapped with the corresponding digital twin model object, so as to realize the data mapping between the three-dimensional static model and the real-time data. After the mapping is completed, the real-time operation status of the new energy station can be viewed through the digital twin model corresponding to the three-dimensional static model on the digital twin intelligent operation and maintenance platform (including the above-mentioned multiple digital twin model objects with established mapping relationships). After obtaining the digital twin intelligent operation and maintenance platform through the above steps, the digital twin intelligent operation and maintenance platform can show the user a digital twin three-dimensional scene based on the new energy station based on the digital twin model, and the digital twin three-dimensional scene is a virtual three-dimensional scene that completely restores the new energy station in the real world. The present application can quickly handle fire accidents based on the virtual three-dimensional scene.

[0041] Below, taking the implementation of the method of this application in the virtual simulation environment provided by the digital twin intelligent operation and maintenance platform (i.e., the digital twin three-dimensional scene of the new energy station is displayed on the digital twin intelligent operation and maintenance platform, and the digital twin three-dimensional scene is a virtual three-dimensional scene built for the new energy station based on digital twin technology) as an example, the simulation processing process of a virtual fire accident is explained, including the following steps.

[0042] Step 1: Set up fire accident simulation conditions in the digital twin intelligent operation and maintenance platform.

[0043] The digital twin smart operation and maintenance platform is equipped with a fire accident simulation configuration module to simulate fire accidents. Through the fire accident simulation configuration module, users can set different fire scenarios, including the location of the fire (accident location), the type of equipment involved, weather information (wind direction, wind speed, etc.), fire spread speed and other parameters.

[0044] After successfully setting up the fire accident simulation conditions, the digital twin intelligent operation and maintenance platform will automatically generate the corresponding accident alarm. The accident alarm includes information such as the location of the fire, the size of the fire, the spread trend, and the equipment and personnel that may be involved. The accident alarm can be presented in multiple forms such as graphics, text or sound, so that relevant personnel can respond quickly.

[0045] After the fire accident simulation conditions are successfully set up, the corresponding fire accident phenomena can be presented in real time in the digital twin three-dimensional scene.

[0046] Step 2: Start the fire emergency plan drill mode.

[0047] In this mode, the data source of the digital twin 3D scene is switched to the data corresponding to the pre-configured fire accident simulation conditions. According to the fire accident simulation conditions, the corresponding equipment of the fire accident is confirmed, and the corresponding real-time video stream address is found according to the mapping relationship between the 3D static model and the real-time data, and the digital twin intelligent operation and maintenance platform is retrieved and displayed, and the accident status is confirmed according to the actual phenomenon in the video.

[0048] In the fire emergency plan drill mode, the presentation status of each device in the digital twin three-dimensional scene is supported and calculated by the mechanism model of each device in the new energy station.

[0049] Step 3: In the fire emergency plan drill mode, realize the preliminary simulation of the fire accident scene, including the activation of the fire system, confirmation of the distribution of fire hydrants, confirmation of real-time parameters of the fire system, and emergency power outage, etc. The specific settings can be made according to actual needs.

[0050] In the digital twin intelligent operation and maintenance platform, the digital twin 3D scene can intuitively display the static distribution of fire-fighting facilities such as fire-fighting equipment, fire hydrants, and water reservoirs, and support overview viewing and single-click detailed viewing. At the same time, the digital twin intelligent operation and maintenance platform can display the emergency power outage processing process and the status of the fire-fighting system (such as automatic sprinkler devices, water pressure, water level, etc.), and quickly locate and highlight the nearest fire hydrant according to the fire location, thereby improving emergency response efficiency.

[0051] Step 4: Plan the best path for fire trucks to enter the fire accident area to facilitate fire trucks to deal with fire accidents in a timely manner, and plan the best escape path for people to be evacuated in the fire accident area to prevent harm to people to be evacuated in the fire accident area.

[0052] Step 5: Evaluate the fire incident handling process.

[0053] Based on the simulation results of the fire accident, including the vehicle entry path, the personnel evacuation path, the fire extinguishing process and the safe distance of the operating arm (during the fire extinguishing process, if the operating arm of the fire truck is required to perform operations, the digital twin intelligent operation and maintenance platform will simulate the extension and retraction animation of the operating arm in the digital twin three-dimensional scene, and calculate in real time the safe distance between the operating arm and the station connection line and equipment during the action. If the distance does not meet the standard requirements, an alarm will be issued), etc., the rationality of the fire fighting plan is analyzed to provide a basis for further optimization of the fire fighting plan.

[0054] This application mainly improves the above step 4 to ensure that the fire truck can quickly reach the accident location (fire location) in the fire accident area, thereby improving the efficiency of handling fire accidents. The improved solution will be described in detail below.

[0055] Figure 1 1 is a flow chart of a path planning method for a new energy station based on digital twins, shown in an embodiment of the present application. Figure 1 , the path planning method of the present application specifically includes the following steps: Step 101: Obtain information of each device in the fire accident area, weather information, and accident location. The fire accident area is an area within the digital twin three-dimensional scene of the new energy station.

[0056] The accident location refers to the location of the fire, or the source of the fire. The accident location is located in the fire accident area, which is a large area with risks. The scope of the fire accident area can be determined according to actual needs. For example, when a fire occurs in a wind power station, the area where the entire wind power station is located can be used as the fire accident area. The information of each device includes at least the distribution information of fire-fighting equipment, the distribution information of live equipment, and the location information of the fire hydrant closest to the accident location. The information of each device can be set according to actual needs.

[0057] Weather information includes wind direction information, wind speed information, etc.

[0058] Step 102: Determine a target parking location for the fire truck from among multiple parking locations within the fire accident area based on information from each device, weather information, and the accident location.

[0059] In this embodiment, the best parking position search strategy is pre-set, that is, multiple key points are pre-set in the fire accident area, and for each key point, a corresponding best parking position is set according to weather information and information of each device. For example, if key points 1 to 10 are pre-marked, for key point 1, if the corresponding wind direction information is south wind level 3, and the nearest fire hydrant is available, then parking position X is determined to be the best parking position, if the corresponding wind direction information is east wind level 3, and the nearest fire hydrant is available, then parking position Y is determined to be the best parking position, and so on.

[0060] When using the optimal parking position search strategy, the key point closest to the accident location is first determined, and then the target parking position is determined based on the key point.

[0061] Therefore, by executing step 102, the best parking position for the fire truck can be quickly determined among multiple parking positions in the fire accident area directly according to the preset best parking position search strategy. The best parking position is the target parking position.

[0062] Step 103: Based on the predicted driving time of the fire truck from the entrance position to the target parking position of the fire accident area and the predicted number of first-category equipment among the equipment passed by the fire truck, a first path for the fire truck to travel is determined from multiple paths from the entrance position to the target parking position. The first-category equipment is equipment whose probability of causing damage to the fire truck is greater than a first probability value.

[0063] In one implementation, the entrance location of the fire truck into the fire accident area can be determined based on information input by relevant personnel, where the relevant personnel refer to personnel who handle fire accidents in the new energy station.

[0064] In another embodiment, the correspondence between the entrance position and each key point in the fire accident area can be preset. When determining the entrance position of the fire truck entering the fire accident area, first determine the key point closest to the accident position, and then, based on the correspondence between the entrance position and the key point, determine the entrance position corresponding to the closest key point as the final entrance position of the fire truck entering the fire accident area.

[0065] Among all the paths available for the fire truck to travel from the entrance location to the target parking location, a first path available for the fire truck to travel can be determined based on the predicted travel time of the fire truck from the entrance location to the target parking location and the predicted number of first-category equipment that the fire truck passes by. The first path is the best path for the fire truck to quickly reach the accident location.

[0066] In this embodiment, if there are multiple fire trucks, a first path needs to be planned for each fire truck, that is, each fire truck corresponds to a first path. The first paths of different fire trucks may be different.

[0067] When determining the first type of equipment, equipment with a probability of causing damage to fire trucks greater than a first probability value can be selected from the live equipment in the fire accident area and used as the first type of equipment. The first probability value can be set according to actual needs.

[0068] After the first path is obtained, information of the first path may be output to prompt the fire truck to enter the fire accident area according to the first path and handle the fire accident.

[0069] Among them, the output of the first path information can be output in the form of images, in the form of sounds, or in a combination of the two. When outputting in the form of images, each first path can be displayed in different styles (such as animation) in the digital twin three-dimensional scene (virtual simulation environment) of the digital twin intelligent operation and maintenance platform, so that relevant personnel can make decisions in a timely manner. When outputting in the form of sounds, the information of the first path can be sent to the equipment used by each fire truck, and the equipment used by each fire truck outputs the information of the first path by sound broadcasting. To implement the method of the present application, first obtain the information of each device in the fire accident area, weather information and accident location; then, according to the information of each device, weather information and accident location, determine the target parking location of the fire truck in multiple parking locations in the fire accident area; then, according to the predicted driving time of the fire truck from the entrance location of the fire accident area to the target parking location and the predicted number of the first type of equipment passed by the fire truck, determine the first path for the fire truck to travel in multiple paths from the entrance location to the target parking location. This application can implement fire drills for fire accidents based on the digital twin three-dimensional scene of the new energy station. After a fire accident occurs, this application comprehensively considers the information of various equipment in the fire accident area, weather information, accident location and other information, and can accurately plan the best path (i.e., the first path) that is more suitable for fire trucks to travel, which helps fire trucks to quickly reach the accident location in the fire accident area and deal with the fire accident, and can significantly improve the efficiency of handling fire accidents.

[0070] In combination with the above embodiments, in one implementation, before determining the first path for the fire truck to travel, the method of the present application may further include: Determine a parking strategy of the fire truck at the target parking position, the parking strategy including a target parking direction, in which a water spraying position on a body of the fire truck is on a side close to the accident position; On this basis, a first path for the fire truck to travel is determined among multiple paths from the entrance position to the target parking position of the fire accident area, including: When the fire truck stops at the target parking position according to the parking strategy, a first path for the fire truck to travel is determined among multiple paths from the entrance position of the fire accident area to the target parking position.

[0071] In this embodiment, the parking strategy includes a parking direction. When the fire truck is parked at the target parking position, it is necessary to ensure that the water spraying position on the vehicle body is on the side close to the accident position, so as to achieve smooth water spraying.

[0072] Therefore, in this embodiment, the influence of the parking direction of the fire truck at the target parking position can be considered. When the fire truck parks at the target parking position according to the parking strategy, the first path is determined from multiple paths from the entrance position of the fire accident area to the target parking position.

[0073] The docking strategy may include not only the docking direction but also other factors, which can be set according to actual needs.

[0074] Through this embodiment, the accuracy of the planning results of the optimal path for the fire truck can be improved, so that the fire truck can quickly reach the accident location and handle the fire accident, further improving the efficiency of handling the fire accident.

[0075] In combination with the above embodiments, in one implementation, according to the predicted driving time of the fire truck from the entrance position to the target parking position of the fire accident area and the predicted number of first-type equipment among various equipments passed by the fire truck, determining a first path for the fire truck to travel from multiple paths from the entrance position to the target parking position may include: Taking the shortest predicted driving time of the fire truck from the entrance position to the target parking position and the smallest predicted number of the first type of equipment passed by the fire truck as the optimization goal, a first path for the fire truck to travel is determined among multiple paths from the entrance position to the target parking position through a multi-factor non-dominated sorting genetic algorithm.

[0076] The multi-factor non-dominated sorting genetic algorithm is a non-dominated sorting genetic algorithm (such as NSGA-II) applied in multi-objective optimization problems. The algorithm is based on the Pareto optimal concept and can find a set of solutions that are as optimal as possible on multiple objectives through continuous iteration and selection operations (that is, these solutions are as optimal as possible on multiple objective functions).

[0077] In the present application, when implementing the multi-factor non-dominated sorting genetic algorithm, a first objective function can be set for the predicted driving time of the fire truck from the entrance position to the target parking position, and a second objective function can be set for the predicted number of first-class equipment among the various equipment passed by the fire truck. When solving with the shortest predicted driving time (the minimum value of the first objective function) and the minimum predicted number of second-class equipment (the minimum value of the second objective function) as the optimization goal, a set of solutions can be obtained, which can achieve the best results on the first objective function and the second objective function as much as possible (that is, it is not guaranteed that the first objective function and the second objective function simultaneously obtain the minimum value). The specific solution process can refer to the existing technology, and this embodiment will not be described in detail here.

[0078] After obtaining a set of solutions through the multi-factor non-dominated sorting genetic algorithm, each solution in this set of solutions represents a path. When determining the first path, the solution ranked first in this set of solutions can be used as the first path, or the final first path can be determined in this set of solutions according to other strategies. Other strategies can be set according to actual needs.

[0079] In this embodiment, the multi-factor non-dominated sorting genetic algorithm can quickly and accurately determine the optimal driving path (first path) for each fire truck to reach the corresponding target parking position from the entrance position, ensuring that the fire accident is quickly handled.

[0080] In combination with the above embodiments, in one implementation, after determining the first path for the fire truck to travel, the method of the present application may further include: Obtain the locations of each exit in the fire accident area and the current locations of each target object to be evacuated; According to the exit position and the current position of the target object, a second path for each target object to travel from the current position to the corresponding exit position is determined through a preset path search algorithm.

[0081] After the second path is obtained, information of the second path may be output to prompt each target object to leave the fire accident area according to the second path.

[0082] The target object mainly refers to a person object, but may also be other types of objects, which can be set according to actual needs.

[0083] In this embodiment, in addition to planning the optimal driving path for the fire truck, it is also necessary to plan the optimal escape path for the target objects to be evacuated in the fire accident area.

[0084] In this embodiment, since the digital twin model in the digital twin intelligent operation and maintenance platform has established a mapping relationship with the real-time data in the fire accident area in advance, the digital twin intelligent operation and maintenance platform can directly obtain the current position of each exit location and each target object to be evacuated.

[0085] In this embodiment, a preset path search algorithm may be used to search for an optimal path, i.e., a second path, in a three-dimensional road model. Each target object corresponds to a second path, and the second paths of different target objects may be different. The three-dimensional road model may be obtained from a three-dimensional static model pre-constructed for the fire accident area.

[0086] When determining the second path of each target object, first determine the exit position of the target object, which can be the nearest exit position or an exit position determined according to other strategies. Then, determine the second path corresponding to the target object through a preset path search algorithm.

[0087] The preset path search algorithm may include an A* algorithm, a Dijkstra algorithm, an ant colony algorithm, etc., which may be selected according to actual needs, and this embodiment does not impose any specific restrictions on this.

[0088] When outputting the second path information, it can be outputted in the form of images, sounds, or a combination of the two. When outputting in the form of images, each second path can be displayed in different styles in the digital twin three-dimensional scene (virtual simulation environment) of the digital twin intelligent operation and maintenance platform, so that the staff handling the fire accident can promptly understand the evacuation situation on the scene. When outputting in the form of sounds, the information of the second path can be sent to the sound output device in the fire accident area, and each sound output device outputs the information of the second path by sound broadcasting.

[0089] Through this embodiment, the best escape route can be quickly planned for the target objects to be evacuated in the fire accident area, which helps to quickly evacuate the on-site personnel and avoid casualties.

[0090] In combination with the above embodiments, in one implementation, determining the second path of each target object from the current position to the corresponding exit position may include: Under the condition that each target object does not pass through the second type of equipment in each device, a second path for each target object to travel from the current position to the corresponding exit position is determined, wherein the second type of equipment is equipment with a probability value of causing damage to the target object greater than the second probability value.

[0091] When determining the second type of equipment, the equipment with a probability of causing damage to the target object greater than the second probability value can be screened out from the live equipment in the fire accident area and used as the second type of equipment. The second probability value can be set according to actual needs. When determining the second path of each target object through the preset path search algorithm, if a second path currently determined needs to pass through the second type of equipment, then the second path is abandoned and a new second path is searched again according to the preset path search algorithm until a second path that does not pass through the second type of equipment is found.

[0092] Through this embodiment, the best escape path (second path) can be quickly planned for each target object to be evacuated in the fire accident area, so as to prevent the target object from being harmed during the escape process.

[0093] In combination with the above embodiments, in one implementation, determining a second path for each target object from a current position to a corresponding exit position includes: When all paths from the current position of each target object to the corresponding exit position pass through the second type of equipment, among all the paths, the shortest path in which the second type of equipment is located in the upwind direction when passing through the second type of equipment will be determined as the second path from the current position of each target object to the corresponding exit position.

[0094] In this embodiment, when determining the second path of each target object through a preset path search algorithm, if all the determined second paths need to pass through the second type of equipment, then among all the paths, the shortest path in which the second type of equipment is located in the upwind direction when passing through the second type of equipment will be determined as the second path.

[0095] Through this embodiment, the most suitable escape path can be found for all target objects to be evacuated in the fire accident area, ensuring that all target objects can leave the fire accident area in time.

[0096] Since the above embodiments are described by taking the method of the present application applied to a virtual simulation environment as an example, obtaining information of each device in the fire accident area, weather information, and the accident location may include: According to the pre-set simulation data for simulating fire accidents, the information of each device in the fire accident area, weather information and the accident location are obtained.

[0097] Among them, the simulation data used to simulate fire accidents is the data pre-configured in the fire accident simulation configuration module of the digital twin intelligent operation and maintenance platform.

[0098] The following is a complete description of the method of handling fire accidents in a virtual simulation environment. The entire process is as follows Figure 2 shown. Figure 2 This is a schematic diagram of a simulated fire accident processing process shown in an embodiment of the present application. Taking the fire of transformer M in new energy station Y as an example, the entire processing process includes: Import the three-dimensional static model of the new energy station Y into the digital twin intelligent operation and maintenance platform, and realize the association between the three-dimensional static model and various real-time data in the new energy station Y, so as to display the digital twin three-dimensional scene corresponding to the new energy station Y in the digital twin intelligent operation and maintenance platform. Next, set up the fire accident simulation working condition for the transformer M of the new energy station Y. After the setting is successful, the fire accident alarm pops up in the digital twin intelligent operation and maintenance platform. The alarm content is that the transformer M of the new energy station Y caught fire at XX o'clock on XX day of XX month. The weather is clear and the wind direction is south wind level 3. Then, start the fire drill of the simulated working condition. The process includes: Step 1: Check the video data of the camera corresponding to transformer M of new energy station Y, confirm the fire, call 119 fire alarm and report to the control center. At the same time, confirm the equipment related to the fire at the scene, identify the equipment that needs to be disconnected and disconnect and isolate it.

[0099] Step 2: Select an emergency plan (pre-set fire protection plan) and determine the location of the fire hydrant closest to transformer M.

[0100] Step 3: Combine the digital twin 3D scene status and on-site video to confirm whether the sprinkler device corresponding to transformer M is working, and check the parameters of the fire protection system in the new energy station Y, including various pressure values ​​in the pump room, the status of parameters such as water level gauges, and the distribution of fire protection facilities in the station. According to the panoramic monitoring of the fire protection system, the emergency plan is revised to obtain the rehearsal plan.

[0101] Step 4: Confirm the safe exit location of the new energy station Y and the optimal escape route for the people to be evacuated, and visualize them in a three-dimensional scene to guide the evacuation of people in the event of a fire.

[0102] Step 5: Comprehensively consider the information of each device in the new energy station Y (distribution information of fire-fighting equipment, distribution information of live equipment, location information of the fire hydrant closest to the accident location), weather information (including wind direction information) and the location of transformer M, and determine the optimal path for the fire truck to enter the new energy station Y.

[0103] Step 6: Based on the calculation results of the optimal path for the fire truck, the fire truck will enter the station and extinguish the fire according to the optimal path in an animated way, which is convenient for querying the simulation process. The simulation process can be paused at any time and can also be replayed.

[0104] Step 7: Analyze the rationality of the fire plan based on the drill results, form a drill report, and improve the quality of the fire plan.

[0105] In summary, the technical solution of this application has at least the following technical effects: First, after a fire accident occurs, comprehensive consideration of information such as the information of various equipment in the fire accident area, weather information, and the accident location can accurately plan a route that is more suitable for fire trucks, which will help fire trucks quickly reach the accident location and deal with the fire accident, and can significantly improve the efficiency of handling fire accidents.

[0106] Second, in addition to planning the driving path for fire trucks, the best escape path can also be planned for the target objects (such as people) to be evacuated in the fire accident area, which helps to quickly evacuate on-site personnel and avoid casualties.

[0107] Third, the digital twin intelligent operation and maintenance platform can simulate the handling process of various fire accidents, test the rationality of various fire-fighting plans, and effectively improve the quality of fire-fighting plans.

[0108] The path planning device provided in the present application is described below. The path planning device described below and the path planning method described above can be referenced to each other.

[0109] The path planning device for the new energy station based on digital twin of the present application is applied to the digital twin intelligent operation and maintenance platform, on which a digital twin three-dimensional scene of the new energy station is displayed. The digital twin three-dimensional scene is a virtual three-dimensional scene built for the new energy station based on the digital twin technology.

[0110] Figure 3 1 is a schematic diagram of a path planning device for a new energy station based on digital twins, shown in an embodiment of the present application. Figure 3 , the path planning device 300 of the present application includes: The first acquisition module 301 is used to obtain information of each device in the fire accident area, weather information and accident location, and the fire accident area is an area within the digital twin three-dimensional scene of the new energy station; A first determination module 302 is used to determine a target parking position of a fire truck among a plurality of parking positions within the fire accident area according to the information of each device, the weather information and the accident position; The second determination module 303 is used to determine a first path for the fire truck to travel among multiple paths from the entrance position to the target parking position based on the predicted driving time of the fire truck from the entrance position of the fire accident area to the target parking position and the predicted number of first-category equipment among the various equipment passed by the fire truck, wherein the first-category equipment is equipment with a probability of causing damage to the fire truck greater than a first probability value.

[0111] According to the path planning device 300 provided in the present application, the device 300 further includes: A third determination module is used to determine a parking strategy of the fire truck at the target parking position before determining the first path for the fire truck to travel, wherein the parking strategy includes a target parking direction, and under the target parking direction, a water spraying position on the body of the fire truck is on a side close to the accident position; The second determining module 303 includes: The first determination submodule is used to determine a first path for the fire truck to travel among multiple paths from the entrance position to the target parking position when the fire truck stops at the target parking position according to the parking strategy.

[0112] According to the path planning device 300 provided in the present application, the second determination module 303 includes: The second determination submodule is used to determine a first path for the fire truck to travel from the entrance position to the target parking position by using a multi-factor non-dominated sorting genetic algorithm, with the shortest predicted driving time of the fire truck from the entrance position to the target parking position and the smallest predicted number of the first type of equipment passed by the fire truck as the optimization goal.

[0113] According to the path planning device 300 provided in the present application, the device 300 further includes: A second acquisition module is used to acquire the positions of each exit in the fire accident area and the current positions of each target object to be evacuated; The fourth determination module is used to determine, according to the exit position and the current position of the target object, a second path for each target object to travel from the current position to the corresponding exit position through a preset path search algorithm.

[0114] According to the path planning device 300 provided in the present application, the fourth determination module includes: The third determination submodule is used to determine a second path for each of the target objects to travel from the current position to the corresponding exit position without passing through a second type of device among the devices, wherein the second type of device is a device whose probability value of causing damage to the target object is greater than a second probability value.

[0115] According to the path planning device 300 provided in the present application, the fourth determination module includes: The fourth determination submodule is used to, when all paths for each of the target objects to travel from the current position to the corresponding exit position pass through the second type of equipment, determine, among all the paths, the shortest path in which the second type of equipment is located in the upwind direction when passing through the second type of equipment as the second path for each of the target objects to travel from the current position to the corresponding exit position.

[0116] According to the path planning device 300 provided in the present application, the method is applied to a virtual simulation environment, and the first acquisition module 301 includes: The acquisition submodule is used to acquire information of each device in the fire accident area, weather information and the accident location according to pre-set simulation data for simulating the fire accident.

[0117] The path planning device 300 provided in the present application further includes: A display module is used to display the first path in the digital twin three-dimensional scene by using image output after the first path for the fire truck to travel is determined.

[0118] According to the path planning device 300 provided in the present application, the weather information at least includes wind direction information.

[0119] Figure 4 FIG. 1 is a schematic diagram of the physical structure of an electronic device shown in an embodiment of the present application. Figure 4 As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communications interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute a path planning method for a new energy station based on digital twins, the method comprising: Acquire information of each device in a fire accident area, weather information, and an accident location, wherein the fire accident area is an area within the digital twin three-dimensional scene of the new energy station; Determine a target parking position for a fire truck among a plurality of parking positions within the fire accident area according to the information of each device, the weather information and the accident position; Based on the predicted driving time of the fire truck from the entrance position of the fire accident area to the target parking position and the predicted number of first-category equipment among the various equipment passed by the fire truck, a first path for the fire truck to travel is determined among multiple paths from the entrance position to the target parking position, wherein the first-category equipment is equipment whose probability of causing damage to the fire truck is greater than a first probability value.

[0120] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0121] On the other hand, the present application also provides a computer program product, the computer program product includes a computer program, the computer program can be stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer can execute a path planning method for a new energy station based on a digital twin provided by the above methods, the method comprising: Acquire information of each device in a fire accident area, weather information, and an accident location, wherein the fire accident area is an area within the digital twin three-dimensional scene of the new energy station; Determine a target parking position for a fire truck among a plurality of parking positions within the fire accident area according to the information of each device, the weather information and the accident position; Based on the predicted driving time of the fire truck from the entrance position of the fire accident area to the target parking position and the predicted number of first-category equipment among the various equipment passed by the fire truck, a first path for the fire truck to travel is determined among multiple paths from the entrance position to the target parking position, wherein the first-category equipment is equipment whose probability of causing damage to the fire truck is greater than a first probability value.

[0122] On the other hand, the present application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to execute a path planning method for a new energy station based on a digital twin provided by the above methods, the method comprising: Acquire information of each device in a fire accident area, weather information, and an accident location, wherein the fire accident area is an area within the digital twin three-dimensional scene of the new energy station; Determine a target parking position for a fire truck among a plurality of parking positions within the fire accident area according to the information of each device, the weather information and the accident position; Based on the predicted driving time of the fire truck from the entrance position of the fire accident area to the target parking position and the predicted number of first-category equipment among the various equipment passed by the fire truck, a first path for the fire truck to travel is determined among multiple paths from the entrance position to the target parking position, wherein the first-category equipment is equipment whose probability of causing damage to the fire truck is greater than a first probability value.

[0123] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0124] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A path planning method for a new energy station based on digital twins, characterized in that: Applied to a digital twin intelligent operation and maintenance platform, the digital twin intelligent operation and maintenance platform displays a digital twin three-dimensional scene of a new energy station, the digital twin three-dimensional scene is a virtual three-dimensional scene built for the new energy station based on digital twin technology, and the path planning method includes: Acquire information of each device in a fire accident area, weather information, and an accident location, wherein the fire accident area is an area within the digital twin three-dimensional scene of the new energy station; Determine a target parking position for a fire truck among a plurality of parking positions within the fire accident area according to the information of each device, the weather information and the accident position; Based on the predicted driving time of the fire truck from the entrance position of the fire accident area to the target parking position and the predicted number of first-category equipment among the various equipment passed by the fire truck, a first path for the fire truck to travel is determined among multiple paths from the entrance position to the target parking position, wherein the first-category equipment is equipment whose probability of causing damage to the fire truck is greater than a first probability value.

2. The path planning method according to claim 1, characterized in that: Before determining the first path for the fire truck to travel, the method further includes: Determining a parking strategy of the fire truck at the target parking position, the parking strategy comprising a target parking direction, under which a water spraying position on a body of the fire truck is on a side close to the accident position; The step of determining a first path for the fire truck to travel among a plurality of paths from the entrance position to the target parking position comprises: When the fire truck stops at the target parking position according to the parking strategy, a first path for the fire truck to travel is determined among multiple paths from the entrance position to the target parking position.

3. The path planning method according to claim 1, characterized in that: The method of determining a first path for the fire truck to travel from the entrance position to the target parking position according to the predicted travel time of the fire truck from the entrance position to the target parking position and the predicted number of first-type equipment among the equipment passed by the fire truck comprises: Taking the shortest predicted driving time of the fire truck from the entrance position to the target parking position and the smallest predicted number of the first type of equipment passed by the fire truck as the optimization goal, a first path for the fire truck to travel is determined from multiple paths from the entrance position to the target parking position through a multi-factor non-dominated sorting genetic algorithm.

4. The path planning method according to claim 1, characterized in that: After determining the first path for the fire truck to travel, the method further includes: Acquire the locations of each exit in the fire accident area and the current locations of each target object to be evacuated; According to the exit position and the current position of the target object, a second path for each target object to travel from the current position to the corresponding exit position is determined by a preset path search algorithm.

5. The path planning method according to claim 4, characterized in that: The determining of a second path for each target object to travel from the current position to the corresponding exit position includes: Under the condition that each of the target objects does not pass through the second type of equipment among the devices, a second path for each of the target objects to travel from the current position to the corresponding exit position is determined, wherein the second type of equipment is equipment whose probability value of causing damage to the target object is greater than a second probability value.

6. The path planning method according to claim 5, characterized in that: The determining of a second path for each target object to travel from the current position to the corresponding exit position includes: When all paths from the current position of each target object to the corresponding exit position pass through the second type of equipment, the shortest path among all the paths in which the second type of equipment is located in the upwind direction when passing through the second type of equipment is determined as the second path from the current position of each target object to the corresponding exit position.

7. The path planning method according to any one of claims 1 to 6, characterized in that: The obtaining of information of each device in the fire accident area, weather information and accident location includes: According to the preset simulation data for simulating the fire accident, the information of each device in the fire accident area, weather information and the accident location are obtained.

8. The path planning method according to claim 7, characterized in that: After determining the first path for the fire truck to travel, the method further includes: The first path is displayed in the digital twin three-dimensional scene by using image output.

9. A path planning device for a new energy station based on digital twin, characterized in that: Applied to a digital twin intelligent operation and maintenance platform, the digital twin intelligent operation and maintenance platform displays a digital twin three-dimensional scene of a new energy station, the digital twin three-dimensional scene is a virtual three-dimensional scene built for the new energy station based on digital twin technology, and the path planning device includes: A first acquisition module is used to obtain information of each device in a fire accident area, weather information, and an accident location, wherein the fire accident area is an area within the digital twin three-dimensional scene of the new energy station; A first determination module is used to determine a target parking position of a fire truck among a plurality of parking positions within the fire accident area according to the information of each device, the weather information and the accident position; The second determination module is used to determine a first path for the fire truck to travel among multiple paths from the entrance position to the target parking position based on the predicted driving time of the fire truck from the entrance position of the fire accident area to the target parking position and the predicted number of first-category equipment among the various equipment passed by the fire truck, wherein the first-category equipment is equipment with a probability of causing damage to the fire truck greater than a first probability value.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, it implements the path planning method for a new energy station based on digital twins as described in any one of claims 1 to 8.

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