Multi-cabin cooperative scheduling method, medium and equipment for shared service cabin in electric power operation site

Abstract

The invention provides a multi-cabin collaborative scheduling method, medium and equipment for shared service cabins in an electric power operation site, and relates to the technical field of electric power rush repair, and the method comprises the steps: obtaining the basic information of all electric power operation sites and service cabin dispatch bases in a region, and combining historical operation task information and weather prediction data; the method comprises the following steps: predicting a predicted electric power first-aid repair task possibly occurring in a future set time period in a region, and constructing a prediction task pool by integrating the predicted electric power first-aid repair task and a planned electric power operation task; and performing joint scheduling on the mobile service module according to the position information of the electric power operation site and the service module dispatching base, the prediction task pool and the traffic road condition, and ensuring that the nearest service module dispatching base of the electric power operation site has an enough number of mobile service modules to meet the operation demand when the operation demand is the prediction electric power first-aid repair task. The method can shorten the time required for emergency repair, and power supply can be recovered as timely as possible.

Description

Technical Field

[0001] The present invention relates to the technical field of power emergency repair, and in particular to a method, medium and equipment for collaborative dispatching of multiple shared service cabins at a power operation site. Background Art

[0002] With the progress of urban-rural integration, urban and rural power supply services have gradually integrated and merged. The time limit rate requirements for power supply emergency repair by management departments at all levels have been repeatedly increased. Especially in the face of sudden power failures, how to quickly complete the emergency repair work and restore power supply services has become an important challenge in current power services. After receiving the emergency repair task, the power emergency repair department will use the service cabin equipped with a vehicle-mounted power tool cabinet to carry out power emergency repairs, and transport the commonly used and specific power tools to the site through the service cabin for operation. In the prior art, the dispatch of the service cabin is limited to receiving the planned power operation task. Since the planned power operation task is usually a routine maintenance operation, the operation time limit requirement is not high, so the dispatch of one or more service cabins nearby to dispatch the service cabin of the base can be used for operation. However, due to various weather reasons, sudden power failures often occur, resulting in the problem of power supply service interruption. If a sudden power failure that is not in the planned power operation task occurs, the nearest service cabin dispatches the service cabin of the base when the service cabin is insufficient, dispatching the service cabin from other distant service cabins will increase the emergency repair time, and the emergency repair work cannot be completed quickly, resulting in the failure to restore power supply in time. Summary of the invention

[0003] The purpose of the present invention is to provide a method, medium and device for collaborative dispatching of multiple shared service cabins at a power operation site, aiming to enable collaborative dispatching of service cabins to ensure that when a sudden power failure occurs due to weather reasons, the nearest service cabin dispatching base has a sufficient number of service cabins to complete the emergency repair work, shorten the time required for emergency repair, and restore power supply as promptly as possible. The specific technical solution is as follows: A method for collaboratively dispatching multiple shared service cabins at a power operation site, the method comprising the following steps: S100, obtaining basic information of all power operation sites and service module dispatching bases in the region, including their location information and historical operation task information; S200, combining historical operation task information and weather forecast data, predicting the predicted power emergency repair tasks that may occur in the future set period in the region, and constructing a predicted task pool by comprehensively predicting the power emergency repair tasks and planned power operation tasks; S300. When receiving an operation demand from an electric power operation site in the region, the mobile service cabin is jointly dispatched according to the location information of the electric power operation site and the service cabin dispatching base, the predicted task pool and the traffic conditions, and it is ensured that when the operation demand is a predicted electric power emergency repair task, the service cabin dispatching base closest to the electric power operation site has a sufficient number of mobile service cabins to meet the operation demand.

[0004] Furthermore, step S100 includes the following steps: obtaining location information of all power operation sites in the area; obtaining historical operation task information of all power operation sites in the area in the past preset time period, including time data of each task and service cabin data required for each task; obtaining hardware information of the service cabin dispatching base, including the number of mobile service cabins owned by the service cabin dispatching base and the location information of the service cabin dispatching base; obtaining historical service information of the service cabin dispatching base, including the number and type of power operation tasks undertaken by the service cabin dispatching base in the past preset time period, the number of mobile service cabins dispatched for each task, and mobile service cabin dispatch service time data.

[0005] Furthermore, the step S200 includes the following steps: S210, constructing a power operation historical task pool according to the locations of all power operation sites in the region in the basic information, and the time point and duration of each operation task; S220, according to the nature of the power operation tasks, the power operations in the historical task pool are divided into planned operation tasks and emergency repair tasks, wherein the planned operation tasks are power operation tasks arranged in advance, and the emergency repair tasks are emergency repair tasks performed for sudden power failures; S230, predicting possible power emergency repair tasks based on the emergency repair tasks in the historical task pool and the weather forecast data in the area; S240, in combination with official data, collect and extract planned work tasks for future set periods in the region; S250, comprehensively plan operation tasks and predict power emergency repair tasks to build a prediction task pool within the area in the future set time period.

[0006] Furthermore, the step S230 includes the following steps: S2310, based on the weather forecast data of the area in the future set time period, it is obtained that there is a possibility of extreme weather in the area in the future set time period, and the extreme weather is divided into two categories: extreme weather category 1 refers to strong winds, heavy rains, and heavy snow weather that directly damage power supply facilities; extreme weather category 2 refers to excessively high or low temperatures that indirectly damage power supply facilities due to excessive power load; S2320, obtaining weather information of a preset period in the past in the region, further dividing the power operation historical task pool, and extracting the power operation historical tasks caused by extreme weather type 1 and extreme weather type 2; S2330, the area is divided into grids of a set size, and the historical power operation tasks caused by extreme weather type 1 and extreme weather type 2 that occurred in each grid in the past preset period are counted. If it occurs once, the grid count is accumulated by 1; the Class 1 value and Class 2 value of all grids in the area can be obtained; S2340, according to the number of occurrences of extreme weather category 1 and extreme weather category 2 in the region during the past preset period, as well as the category 1 value and category 2 value of each grid, calculate the category 1 probability and category 2 probability of each grid, wherein the category 1 probability is the ratio of the category 1 value to the number of occurrences of extreme weather category 1, and the category 2 probability is the ratio of the category 2 value to the number of occurrences of extreme weather category 2; S2350. If at least one of extreme weather type 1 and extreme weather type 2 is likely to occur in a set period in the future, then based on the size of the probability of type 1 and type 2 of each grid, predict the probability of power operation tasks caused by extreme weather type 1 and / or extreme weather type 2 in each grid area.

[0007] Furthermore, the step S300 includes the following steps: S310, when receiving an operation demand from a power operation site in the region, dispatching one or more service cabins nearest to the mobile service cabin in the dispatch base to provide service according to the real-time traffic conditions; S320, predicting the time required for the on-site operation task of the power operation; S330, extract the next task to be performed in the predicted task pool, and determine the grid area to which the task belongs; if the task is a planned operation task, then according to the occurrence time of the operation task and the future traffic conditions, select the nearest service cabin dispatching base in the grid area to which the task belongs to provide service; if the task is a predicted power emergency repair task, calculate whether the mobile service cabin in the nearest service cabin dispatching base in the grid where the task is located meets the task requirements. If so, it will not be dispatched and will be processed in real time after the task occurs; if it is not enough to meet the task requirements, judge the size of the Class 1 probability and / or Class 2 probability of the grid and the preset threshold. If it is less than the preset threshold, it will not be dispatched in advance and will be dispatched in real time after the task occurs. If it is greater than or equal to the preset threshold, according to the time period in which the power emergency repair task is predicted to occur and the specific road condition information of the time period, the missing mobile service cabin will be dispatched to the nearest service cabin dispatching base in the grid to stand by.

[0008] Furthermore, the step S300 further includes the following steps: S400: When receiving an emergency task demand from a power operation site in the region that is not in the predicted task pool, a joint dispatch is performed based on the location information of the power operation site and the service cabin dispatching base, the predicted task pool, and traffic conditions to dispatch one or more nearby mobile service cabins from the service cabin dispatching base to meet the operation demand.

[0009] Furthermore, the step S400 includes the following steps: S410, when an emergency task occurs, calculate the grid where the task is located and calculate one or more service module dispatching bases near the grid in real time; S420, assuming that for this emergency task, the service cabin dispatching base dispatches a mobile service cabin to the power operation site, the time required under the real-time road conditions is t0, and the departure time is T0; the next task in the predicted task pool was originally planned to require the service cabin dispatching base to dispatch a mobile service cabin for service, the occurrence time is T1, and the time required for the service cabin dispatching base to the power operation site is t1; if the service cabin dispatching base dispatches a mobile service cabin to serve this emergency task at time T0, it is not enough to meet the next task in the predicted task pool, then the next task in the predicted task pool needs to select its second closest service cabin dispatching base, assuming that the time required for the second closest service cabin dispatching base to the power operation site is t2; calculate the future time as If the future duration is negative, it means that the processing of the emergency task will not affect the next task in the predicted task pool, and no emergency dispatch is required; if the future duration is positive, and the next task in the predicted task pool is a planned operation task, the importance of the task is judged. If the emergency task is more important, the base dispatches the mobile service cabin from the nearest service cabin, and the planned operation task dispatches the mobile service cabin from the second nearest service cabin; if the planned operation task is more important, the emergency task is processed this time to avoid the service cabin dispatch base that needs to serve the planned operation task; if the future duration is positive, and the next task in the predicted task pool is a planned operation task, the importance of the task is judged. If the emergency task is more important, the base dispatches the mobile service cabin from the nearest service cabin, and the planned operation task dispatches the mobile service cabin from the second nearest service cabin; if the planned operation task is more important, the emergency task is processed this time to avoid the service cabin dispatch base that needs to serve the planned operation task; If one task is to predict the power emergency repair task, the size of the Class 1 probability and / or Class 2 probability of the grid and the preset threshold is determined. If it is less than the preset threshold, no special dispatch is made, and the nearest service cabin dispatch base responds to the emergency task; if it is greater than the preset threshold, the importance of the task is determined. If the emergency task is more important, the mobile service cabin is dispatched from the nearest service cabin dispatch base, and the predicted power emergency repair task is dispatched from the second nearest service cabin dispatch base; if the predicted power emergency repair task is more important, the emergency task is handled to avoid the service cabin dispatch base that needs to serve the predicted power emergency repair task.

[0010] Furthermore, the steps S100 and S200 also include a step of visualizing the regional map, which specifically includes the following steps: in ArcGIS software, a base map layer of the regional range is newly created, and the base map can be a high-precision raster image; a new vector layer is newly created, and all power operation sites and service cabin dispatching bases in the region are stored as point elements; the newly created vector layer should be consistent with the coordinate system of the base map layer; in the point element representing the service cabin dispatching base, a new attribute is newly created to store the number of mobile service cabins owned by the service cabin dispatching base; a new service cabin dispatching base visualization label is newly created, and the label content includes: how many mobile service cabins the service cabin dispatching base has, how many mobile service cabins there are currently, and how long the dispatched mobile service cabins have been working; the label is visualized next to the point element of the service cabin dispatching base in the vector layer; a new power operation site visualization label is newly created, and the label content includes: whether there is power operation at the power operation site, if there is power operation, how many mobile service cabins are in operation, and how long the mobile service cabins have been in operation; the label is visualized next to the point element of the power operation site in the vector layer; The step S300 is followed by a step of real-time visualization of a shared mobile service cabin, which specifically includes the following steps: aligning and overlaying the defined base map layer and vector layer in ArcMap for display; acquiring the GPS coordinate information of each mobile service cabin in real time, creating a new service cabin layer in the map, and dynamically displaying it in the form of point features; displaying the service cabin dispatching base in a first color, and visually displaying the number of mobile service cabins currently on-site at the service cabin dispatching base in different shades of the first color values, wherein the darker the first color, the more mobile service cabins on-site; displaying the power operation site in a second color, and visually displaying the operation progress at the power operation site in different shades of the second color values, wherein the darker the second color, the faster the operation progress; and refreshing all visual display data every set time period.

[0011] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for collaborative scheduling of multiple shared service cabins at a power operation site as described above.

[0012] The present invention also provides a computer 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 program, the steps of the method for collaborative scheduling of multiple shared service cabins at a power operation site as described above are implemented.

[0013] The invention provides a method, medium and device for collaborative dispatching of multiple shared service cabins at a power operation site, which has the following beneficial effects: The present invention obtains basic information of all power operation sites and service cabin dispatching bases in a region, combines historical operation task information and weather forecast data, predicts predicted power emergency repair tasks that may occur in a future set time period in the region, and constructs a predicted task pool by comprehensively predicting power emergency repair tasks and planned power operation tasks. When receiving operation requirements from power operation sites in the region, the present invention jointly dispatches mobile service cabins according to the location information of the power operation sites and service cabin dispatching bases, the predicted task pool and traffic conditions, and ensures that when the operation requirement is a predicted power emergency repair task, the service cabin dispatching base closest to the power operation site has a sufficient number of mobile service cabins to meet the operation requirement; it can predict sudden power failures that may occur in the future due to weather reasons based on historical operation task information and weather forecast data, thereby dispatching multiple shared mobile service cabins to ensure that the service cabin dispatching base closest to the power operation site has a sufficient number of mobile service cabins to meet the operation requirement, which can shorten the time required for emergency repairs and realize the timely restoration of power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a flow chart of a method for collaborative dispatching multiple shared service cabins at a power operation site provided by the present invention; Figure 2 It is a structural block diagram of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0015] The following will be combined with the accompanying drawings provided by the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. According to the following description, the advantages and features of the present invention will be more clear. It should be noted that the accompanying drawings are all in a very simplified form and are not in precise proportions, which are only used to conveniently and clearly assist in explaining the purpose of the embodiments of the present invention.

[0016] Embodiment 1: This embodiment provides a method for coordinating multiple shared service cabins at a power operation site. Figure 1 As shown, the method comprises the following steps: S100, obtaining basic information of all power operation sites and service module dispatching bases in the region, including their location information and historical operation task information.

[0017] Specifically, the steps include: obtaining the location information of all power operation sites in the area, preferably recording it in the form of longitude and latitude coordinates; obtaining the historical operation task information of all power operation sites in the area in the past preset time period, including the time data of each task and the service cabin data required for each task; obtaining the hardware information of the service cabin dispatching base, including the number of mobile service cabins owned by the service cabin dispatching base and the location information of the service cabin dispatching base, preferably recording it in the form of longitude and latitude coordinates; obtaining the historical service information of the service cabin dispatching base, including the number and type of power operation tasks undertaken by the service cabin dispatching base in the past preset time period, the number of mobile service cabins dispatched for each task, and the mobile service cabin dispatching service time data.

[0018] In a preferred embodiment, the preset period is 1 year.

[0019] S200. Combine historical operation task information and weather forecast data to predict the predicted power emergency repair tasks that may occur in the future set time period in the region, and build a predicted task pool by comprehensively predicting the power emergency repair tasks and planned power operation tasks.

[0020] The specific steps include: S210, constructing a power operation historical task pool according to the locations of all power operation sites in the region in the basic information, and the time point and duration of each operation task; S220, according to the nature of the power operation tasks, the power operations in the historical task pool are divided into planned operation tasks and emergency repair tasks, wherein the planned operation tasks are power operation tasks arranged in advance, and the emergency repair tasks are emergency repair tasks performed for sudden power failures; S230, predicting possible power emergency repair tasks based on the emergency repair tasks in the historical task pool and the weather forecast data in the area; The specific steps include: S2310, based on the weather forecast data of the area in the future set time period, it is obtained that there is a possibility of extreme weather in the area in the future set time period, and the extreme weather is divided into two categories: extreme weather category 1 refers to strong winds, heavy rains, and heavy snow weather that directly damage power supply facilities; extreme weather category 2 refers to excessively high or low temperatures that indirectly damage power supply facilities due to excessive power load; S2320, obtaining weather information of a preset period in the past in the region, further dividing the power operation historical task pool, and extracting the power operation historical tasks caused by extreme weather type 1 and extreme weather type 2; S2330, the area is divided into grids of a set size, and the historical power operation tasks caused by extreme weather type 1 and extreme weather type 2 that occurred in each grid in the past preset period are counted. If it occurs once, the grid count is accumulated by 1; the Class 1 value and Class 2 value of all grids in the area can be obtained; S2340, according to the number of occurrences of extreme weather category 1 and extreme weather category 2 in the region during the past preset period, as well as the category 1 value and category 2 value of each grid, calculate the category 1 probability and category 2 probability of each grid, wherein the category 1 probability is the ratio of the category 1 value to the number of occurrences of extreme weather category 1, and the category 2 probability is the ratio of the category 2 value to the number of occurrences of extreme weather category 2; S2350. If at least one of extreme weather type 1 and extreme weather type 2 is likely to occur in a set period in the future, then based on the size of the probability of type 1 and type 2 of each grid, predict the probability of power operation tasks caused by extreme weather type 1 and / or extreme weather type 2 in each grid area.

[0021] S240, in combination with official data, collect and extract planned work tasks for future set periods in the region; S250, comprehensively plan operation tasks and predict power emergency repair tasks to build a prediction task pool within the area in the future set time period.

[0022] Among them, the planned operation task is 100% likely to occur, the predicted power emergency repair task is predicted to have a certain probability of occurrence based on historical probability, and the predicted time of occurrence of the predicted power emergency repair task should be accurate to the hour.

[0023] In a preferred embodiment, the set time period is 1 day.

[0024] In a preferred embodiment, in step S2330, the area is divided into grids of 1 km×1 km in size.

[0025] S300. When receiving an operation demand from an electric power operation site in the region, the mobile service cabin is jointly dispatched according to the location information of the electric power operation site and the service cabin dispatching base, the predicted task pool and the traffic conditions, and it is ensured that when the operation demand is a predicted electric power emergency repair task, the service cabin dispatching base closest to the electric power operation site has a sufficient number of mobile service cabins to meet the operation demand.

[0026] The specific steps include: S310, when receiving an operation demand from a power operation site in the region, dispatching one or more service cabins nearest to the mobile service cabin in the dispatch base to provide service according to the real-time traffic conditions; S320, predicting the duration required for the task at the power operation site; preferably, the required duration is obtained by predicting the assigned task through manual experience, or by averaging the duration of historical tasks at the power operation site; S330, extract the next task to be performed in the predicted task pool, and determine the grid area to which the task belongs; if the task is a planned operation task, then according to the occurrence time of the operation task and the future traffic conditions, select the nearest service cabin dispatching base in the grid area to which the task belongs to provide service; if the task is a predicted power emergency repair task, calculate whether the mobile service cabin in the nearest service cabin dispatching base in the grid where the task is located meets the task requirements. If so, it will not be dispatched and will be processed in real time after the task occurs; if it is not enough to meet the task requirements, judge the size of the Class 1 probability and / or Class 2 probability of the grid and the preset threshold. If it is less than the preset threshold, it will not be dispatched in advance and will be dispatched in real time after the task occurs. If it is greater than or equal to the preset threshold, according to the time period in which the power emergency repair task is predicted to occur and the specific road condition information of the time period, the missing mobile service cabin will be dispatched to the nearest service cabin dispatching base in the grid to stand by.

[0027] In a preferred embodiment, a new layer is created in ArcGIS, and the road network information of real-time traffic conditions or the predicted data of future traffic conditions are imported through the Baidu Map API to calculate the time required for each service cabin dispatching base to arrive at the power operation site under the real-time traffic conditions or future traffic conditions, and the distance between the service cabin dispatching base and the power operation site is determined based on the required time; In a preferred embodiment, if the nearest service module dispatching base has a mobile service module for outbound operations, the return time of the mobile service module for outbound operations needs to be predicted. If the mobile service module can return before the next time period in which the mission will occur, the returned mobile service module can be counted as the next mobile service module that can be dispatched for the mission.

[0028] In a preferred embodiment, at the nearest service module dispatching base, if there is a standby mobile service module dispatched from other service module dispatching bases, and the mobile service module for outbound operations that was not planned returns ahead of schedule, the dispatched standby mobile service module will be sent back to the original service module dispatching base.

[0029] The embodiment of the present invention obtains basic information of all power operation sites and service cabin dispatching bases in a region, combines historical operation task information and weather forecast data, predicts predicted power emergency repair tasks that may occur in the future set time period in the region, and constructs a predicted task pool by comprehensively predicting power emergency repair tasks and planned power operation tasks. When receiving operation requirements from power operation sites in the region, the mobile service cabins are jointly dispatched according to the location information of the power operation site and the service cabin dispatching base, the predicted task pool and traffic conditions, and ensure that when the operation requirement is a predicted power emergency repair task, the service cabin dispatching base closest to the power operation site has a sufficient number of mobile service cabins to meet the operation requirement; it can be predicted based on historical operation task information and weather forecast data that sudden power failures may occur in the future due to weather reasons, so as to dispatch multiple shared mobile service cabins to ensure that the service cabin dispatching base closest to the power operation site has a sufficient number of mobile service cabins to meet the operation requirement, which can shorten the time required for emergency repairs and realize the timely restoration of power supply.

[0030] In an optional embodiment, the method for collaboratively dispatching multiple shared service cabins at a power operation site further includes the following steps after step S300: S400: When receiving an emergency task demand from a power operation site in the region that is not in the predicted task pool, a joint dispatch is performed based on the location information of the power operation site and the service cabin dispatching base, the predicted task pool, and traffic conditions to dispatch one or more nearby mobile service cabins from the service cabin dispatching base to meet the operation demand.

[0031] The specific steps include: S410, when an emergency task occurs, calculate the grid where the task is located and calculate one or more service module dispatching bases near the grid in real time; S420, assuming that for this emergency task, the service cabin dispatching base dispatches a mobile service cabin to the power operation site, the time required under the real-time road conditions is t0, and the departure time is T0; the next task in the predicted task pool was originally planned to require the service cabin dispatching base to dispatch a mobile service cabin for service, the occurrence time is T1, and the time required for the service cabin dispatching base to the power operation site is t1; if the service cabin dispatching base dispatches a mobile service cabin to serve this emergency task at time T0, it is not enough to meet the next task in the predicted task pool, then the next task in the predicted task pool needs to select its second closest service cabin dispatching base, assuming that the time required for the second closest service cabin dispatching base to the power operation site is t2; calculate the future time as If the future duration is negative, it means that the processing of the emergency task will not affect the next task in the predicted task pool, and no emergency dispatch is required; if the future duration is positive, and the next task in the predicted task pool is a planned operation task, the importance of the task is judged. If the emergency task is more important, the base dispatches the mobile service cabin from the nearest service cabin, and the planned operation task dispatches the mobile service cabin from the second nearest service cabin; if the planned operation task is more important, the emergency task is processed this time to avoid the service cabin dispatch base that needs to serve the planned operation task; if the future duration is positive, and the next task in the predicted task pool is a planned operation task, the importance of the task is judged. If the emergency task is more important, the base dispatches the mobile service cabin from the nearest service cabin, and the planned operation task dispatches the mobile service cabin from the second nearest service cabin; if the planned operation task is more important, the emergency task is processed this time to avoid the service cabin dispatch base that needs to serve the planned operation task; If one task is to predict the power emergency repair task, the size of the Class 1 probability and / or Class 2 probability of the grid and the preset threshold is determined. If it is less than the preset threshold, no special dispatch is made, and the nearest service cabin dispatch base responds to the emergency task; if it is greater than the preset threshold, the importance of the task is determined. If the emergency task is more important, the mobile service cabin is dispatched from the nearest service cabin dispatch base, and the predicted power emergency repair task is dispatched from the second nearest service cabin dispatch base; if the predicted power emergency repair task is more important, the emergency task is handled to avoid the service cabin dispatch base that needs to serve the predicted power emergency repair task.

[0032] The importance of the task can be determined by submitting it to an administrator for manual determination and receiving the result, or by setting the determination conditions for automatic determination, such as by determining the type of task operation, the location of the power operation site, etc.

[0033] In an optional embodiment, the method for collaboratively dispatching multiple cabins of a shared service cabin at a power operation site further includes a step of visualizing a regional map between steps S100 and S200, and by constructing a map system, map visualization of the power operation site and the service cabin dispatching base based on the latest regional map is realized, specifically including the following steps: In ArcGIS software, create a base map layer of the new area range. The base map can be a high-precision raster image. A new vector layer is created to store all power operation sites and service cabin dispatch bases in the area with point features. The new vector layer should be consistent with the coordinate system of the base map layer. In the point features representing the service cabin dispatch base, a new attribute is created to store the number of mobile service cabins owned by the service cabin dispatch base. A new service cabin dispatch base visualization label is created, and the label content includes: how many mobile service cabins the service cabin dispatch base has, how many mobile service cabins there are currently, and how long the dispatched mobile service cabins have been working. The label is visualized next to the point feature of the service cabin dispatch base in the vector layer. A new power operation site visualization label is created, and the label content includes: whether there is power operation at the power operation site, if there is power operation, how many mobile service cabins are working, and how long the mobile service cabins have been working. The label is visualized next to the point feature of the power operation site in the vector layer.

[0034] In an optional embodiment, the method for collaboratively dispatching multiple shared service cabins at a power operation site further includes a step of real-time visualization of shared mobile service cabins after step S300, which is used to visualize all mobile service cabin information in real time on a map, specifically including the following steps: Align and overlay the defined basemap layer and vector layer in ArcMap; The GPS coordinate information of each mobile service cabin is obtained in real time, and a new service cabin layer is created in the map, which is dynamically displayed in the form of point elements; the service cabin dispatching base is displayed in the first color, and the number of mobile service cabins currently on-site at the service cabin dispatching base is visualized with different shades of the first color values. The darker the first color, the more mobile service cabins are on-site; the power operation site is displayed in the second color, and the operation progress of the power operation site is visualized with different shades of the second color values. The darker the second color, the faster the operation progress; All visual display data is refreshed every set time.

[0035] In a preferred embodiment, the first color is green, the second color is red, and the set duration is 10 seconds.

[0036] Embodiment 2: This embodiment provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the method for collaborative scheduling of multiple shared service cabins at a power operation site described above are implemented.

[0037] The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk (HDD) or a solid-state drive (SSD), etc.; the storage medium may also include a combination of the above-mentioned types of memory.

[0038] Embodiment 3: This embodiment provides a computer device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for collaborative scheduling of multiple cabins in a shared service cabin at a power operation site described above are implemented.

[0039] like Figure 2As shown, the computer device may include: at least one processor 71, such as a CPU (Central Processing Unit), at least one communication interface 73, a memory 74, and at least one communication bus 72. The communication bus 72 is used to realize the connection and communication between these components. The communication interface 73 may include a display screen (Display) and a keyboard (Keyboard), and the optional communication interface 73 may also include a standard wired interface and a wireless interface. The memory 74 may be a high-speed RAM memory (Random Access Memory, volatile random access memory) or a non-volatile memory (non-volatile memory), such as at least one disk storage. The memory 74 may optionally be at least one storage device located away from the aforementioned processor 71. The memory 74 stores an application program, and the processor 71 calls the program code stored in the memory 74 to execute any of the above method steps.

[0040] The communication bus 72 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The communication bus 72 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 2 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0041] Among them, the memory 74 may include a volatile memory (English: volatile memory), such as a random access memory (English: random-access memory, abbreviated: RAM); the memory may also include a non-volatile memory (English: non-volatile memory), such as a flash memory (English: flash memory), a hard disk (English: hard disk drive, abbreviated: HDD) or a solid-state drive (English: solid-state drive, abbreviated: SSD); the memory 74 may also include a combination of the above types of memory.

[0042] The processor 71 may be a central processing unit (CPU), a network processor (NP), or a combination of a CPU and a NP.

[0043] The processor 71 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0044] Optionally, the memory 74 is also used to store program instructions. The processor 71 can call the program instructions to implement the multi-cabin collaborative scheduling method for shared service cabins at a power operation site of the present invention.

[0045] Those skilled in the art should understand that the present invention can be implemented in many other specific forms without departing from the spirit and scope of the present invention. Based on the embodiments of the present invention, any changes and modifications made by ordinary technicians in the field of the present invention according to the above disclosure are within the scope of protection of the claims.

Claims

1. A method for collaborative dispatching of multiple shared service cabins at a power operation site, characterized in that: The method comprises the following steps: S100, obtaining basic information of all power operation sites and service module dispatching bases in the region, including their location information and historical operation task information; S200, combining historical operation task information and weather forecast data, predicting the predicted power emergency repair tasks that may occur in the future set period in the region, and constructing a predicted task pool by comprehensively predicting the power emergency repair tasks and planned power operation tasks; S300. When receiving an operation demand from an electric power operation site in the region, the mobile service cabin is jointly dispatched according to the location information of the electric power operation site and the service cabin dispatching base, the predicted task pool and the traffic conditions, and it is ensured that when the operation demand is a predicted electric power emergency repair task, the service cabin dispatching base closest to the electric power operation site has a sufficient number of mobile service cabins to meet the operation demand.

2. The method for coordinating and dispatching multiple shared service cabins at a power operation site according to claim 1, characterized in that: The step S100 includes the following steps: obtaining the location information of all power operation sites in the area; obtaining the historical operation task information of all power operation sites in the area in the past preset period, including the time data of each task and the service module data required for each task; obtaining the hardware information of the service module dispatching base, including the number of mobile service modules owned by the service module dispatching base and the location information of the service module dispatching base; Obtain historical service information of the service module dispatch base, including the number and type of power operation tasks undertaken by the service module dispatch base in the past preset period, the number of mobile service modules dispatched for each task, and the mobile service module dispatch service time data.

3. The method for coordinating and dispatching multiple shared service cabins at a power operation site according to claim 2, characterized in that: The step S200 includes the following steps: S210, constructing a power operation historical task pool according to the locations of all power operation sites in the region in the basic information, and the time point and duration of each operation task; S220, according to the nature of the power operation tasks, the power operations in the historical task pool are divided into planned operation tasks and emergency repair tasks, wherein the planned operation tasks are power operation tasks arranged in advance, and the emergency repair tasks are emergency repair tasks performed for sudden power failures; S230, predicting possible power emergency repair tasks based on the emergency repair tasks in the historical task pool and the weather forecast data in the area; S240, in combination with official data, collect and extract planned work tasks for future set periods in the region; S250, comprehensively plan operation tasks and predict power emergency repair tasks to build a prediction task pool within the area in the future set time period.

4. The method for coordinating and dispatching multiple shared service cabins at a power operation site according to claim 3 is characterized in that: The step S230 includes the following steps: S2310, based on the weather forecast data of the area in the future set time period, it is obtained that there is a possibility of extreme weather in the area in the future set time period, and the extreme weather is divided into two categories: extreme weather category 1 refers to strong winds, heavy rains, and heavy snow weather that directly damage power supply facilities; extreme weather category 2 refers to excessively high or low temperatures that indirectly damage power supply facilities due to excessive power load; S2320, obtaining weather information of a preset period in the past in the region, further dividing the power operation historical task pool, and extracting the power operation historical tasks caused by extreme weather type 1 and extreme weather type 2; S2330, the area is divided into grids of a set size, and the historical power operation tasks caused by extreme weather type 1 and extreme weather type 2 that occurred in each grid in the past preset period are counted. If it occurs once, the grid count is accumulated by 1; the Class 1 value and Class 2 value of all grids in the area can be obtained; S2340, according to the number of occurrences of extreme weather category 1 and extreme weather category 2 in the region during the past preset period, as well as the category 1 value and category 2 value of each grid, calculate the category 1 probability and category 2 probability of each grid, wherein the category 1 probability is the ratio of the category 1 value to the number of occurrences of extreme weather category 1, and the category 2 probability is the ratio of the category 2 value to the number of occurrences of extreme weather category 2; S2350. If at least one of extreme weather type 1 and extreme weather type 2 is likely to occur in a set period in the future, then based on the size of the probability of type 1 and type 2 of each grid, predict the probability of power operation tasks caused by extreme weather type 1 and / or extreme weather type 2 in each grid area.

5. The method for coordinating and dispatching multiple shared service cabins at a power operation site according to claim 4, characterized in that: The step S300 includes the following steps: S310, when receiving an operation demand from a power operation site in the region, dispatching one or more service cabins nearest to the mobile service cabin in the dispatch base to provide service according to the real-time traffic conditions; S320, predicting the time required for the on-site operation task of the power operation; S330, extracting the next task to be performed in the prediction task pool, and determining the grid area to which the task belongs; If the task is a planned operation task, the service module dispatch base closest to the grid area to which the task belongs will be selected to provide service based on the time when the operation task occurs and the future traffic conditions; If the task is a predicted power emergency repair task, then calculate whether the mobile service cabin in the service cabin dispatching base closest to the grid where the task is located meets the task requirements. If so, it will not be dispatched and will be processed in real time after the task occurs. If it is not enough to meet the task requirements, judge the size of the Class 1 probability and / or Class 2 probability of the grid and the preset threshold. If it is less than the preset threshold, it will not be dispatched in advance and will be dispatched in real time after the task occurs. If it is greater than or equal to the preset threshold, the missing mobile service cabin will be dispatched to the service cabin dispatching base closest to the grid to stand by according to the time period when the power emergency repair task is predicted to occur and the specific road conditions information of the time period.

6. The method for coordinated dispatching of multiple shared service cabins at a power operation site according to claim 5, characterized in that: The step S300 further includes the following steps: S400: When receiving an emergency task demand from a power operation site in the region that is not in the predicted task pool, a joint dispatch is performed based on the location information of the power operation site and the service cabin dispatching base, the predicted task pool, and traffic conditions to dispatch one or more nearby mobile service cabins from the service cabin dispatching base to meet the operation demand.

7. The method for coordinated dispatching of multiple shared service cabins at a power operation site according to claim 6, characterized in that: The step S400 includes the following steps: S410, when an emergency task occurs, calculate the grid where the task is located and calculate one or more service module dispatching bases near the grid in real time; S420, assuming that for this emergency task, the service cabin dispatching base dispatches a mobile service cabin to the power operation site, the time required under the real-time road conditions is t0, and the departure time is T0; the next task in the predicted task pool was originally planned to require the service cabin dispatching base to dispatch a mobile service cabin for service, the occurrence time is T1, and the time required for the service cabin dispatching base to the power operation site is t1; if the service cabin dispatching base dispatches a mobile service cabin to serve this emergency task at time T0, it is not enough to meet the next task in the predicted task pool, then the next task in the predicted task pool needs to select its second closest service cabin dispatching base, assuming that the time required for the second closest service cabin dispatching base to the power operation site is t2; calculate the future time as If the future duration is negative, it means that the processing of the emergency task will not affect the next task in the predicted task pool, and no emergency dispatch is required; if the future duration is positive, and the next task in the predicted task pool is a planned operation task, the importance of the task is judged. If the emergency task is more important, the base dispatches the mobile service cabin from the nearest service cabin, and the planned operation task dispatches the mobile service cabin from the second nearest service cabin; if the planned operation task is more important, the emergency task is processed this time to avoid the service cabin dispatch base that needs to serve the planned operation task; if the future duration is positive, and the next task in the predicted task pool is a planned operation task, the importance of the task is judged. If the emergency task is more important, the base dispatches the mobile service cabin from the nearest service cabin, and the planned operation task dispatches the mobile service cabin from the second nearest service cabin; if the planned operation task is more important, the emergency task is processed this time to avoid the service cabin dispatch base that needs to serve the planned operation task; If one task is to predict the power emergency repair task, the size of the Class 1 probability and / or Class 2 probability of the grid and the preset threshold is determined. If it is less than the preset threshold, no special dispatch is made, and the nearest service cabin dispatch base responds to the emergency task; if it is greater than the preset threshold, the importance of the task is determined. If the emergency task is more important, the mobile service cabin is dispatched from the nearest service cabin dispatch base, and the predicted power emergency repair task is dispatched from the second nearest service cabin dispatch base; if the predicted power emergency repair task is more important, the emergency task is handled to avoid the service cabin dispatch base that needs to serve the predicted power emergency repair task.

8. The method for coordinating and dispatching multiple shared service cabins at a power operation site according to claim 1, characterized in that: The steps between step S100 and step S200 also include a step of visualizing the regional map, which specifically includes the following steps: in ArcGIS software, a base map layer of the regional range is newly created, and the base map can be a high-precision raster image; a new vector layer is newly created, and all the power operation sites and service cabin dispatching bases in the region are stored as point elements; the new vector layer should be consistent with the coordinate system of the base map layer; in the point element representing the service cabin dispatching base, a new attribute is created to store the number of mobile service cabins owned by the service cabin dispatching base; A new visualization label for the service module dispatch base is created. The label content includes: how many mobile service modules there are in the service module dispatch base, how many mobile service modules there are currently, and how long the dispatched mobile service modules have been working; the label is visualized next to the point element of the service module dispatch base in the vector layer; a new visualization label for the power operation site is created. The label content includes: whether there is power operation at the power operation site, if there is power operation, how many mobile service modules are working, and how long the mobile service modules have been working; the label is visualized next to the point element of the power operation site in the vector layer; The step S300 is followed by a step of real-time visualization of a shared mobile service cabin, which specifically includes the following steps: aligning and overlaying the defined base map layer and vector layer in ArcMap for display; acquiring the GPS coordinate information of each mobile service cabin in real time, creating a new service cabin layer in the map, and dynamically displaying it in the form of point features; displaying the service cabin dispatching base in a first color, and visually displaying the number of mobile service cabins currently on-site at the service cabin dispatching base in different shades of the first color values, wherein the darker the first color, the more mobile service cabins on-site; displaying the power operation site in a second color, and visually displaying the operation progress at the power operation site in different shades of the second color values, wherein the darker the second color, the faster the operation progress; and refreshing all visual display data every set time period.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for collaborative scheduling of multiple shared service cabins at an electric power operation site as described in any one of claims 1 to 8 are implemented.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method for collaborative scheduling of multiple shared service cabins at an electric power operation site as described in any one of claims 1-8 are implemented.

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