Low-voltage distribution network operation and maintenance personnel scheduling method based on positioning system and electronic equipment

Abstract

The invention relates to the technical field of electric power, and provides a low-voltage distribution network operation and maintenance personnel scheduling method based on a positioning system and electronic equipment, and the method comprises the steps: obtaining the real-time position data of operation and maintenance personnel terminal equipment, and generating a personnel distribution dynamic view; the method comprises the steps of marking operation areas with personnel density exceeding or lower than a preset threshold value, analyzing distribution network line crossing and equipment sharing conditions of adjacent operation areas, evaluating a resource bearing state for the operation areas with the overlapping degree exceeding a preset overlapping degree threshold value, generating a personnel dispersion or support instruction, and sending the personnel dispersion or support instruction to a server. Matching a to-be-executed distribution network equipment maintenance task list with the real-time position data, generating a distribution network task distribution scheme, pushing the distribution network task distribution scheme to operation and maintenance personnel terminal equipment, receiving execution state feedback, and judging a new aggregation or vacancy phenomenon; and if a new gathering or vacancy phenomenon exists, adjusting personnel distribution and task allocation, updating a terminal equipment instruction, and recording scheduling data.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a low-voltage distribution network operation and maintenance personnel scheduling method and electronic equipment based on a positioning system. Background Art

[0002] In the operation and maintenance of modern power systems, the operation and maintenance management of low-voltage distribution networks is a crucial area, directly impacting the stability of power supply and the reliability of user experience. With the acceleration of urbanization and the growth of electricity demand, how to dispatch operation and maintenance personnel to meet complex network maintenance needs has become a key issue for the industry. These complex demands are primarily manifested in the diversity of equipment types, the highly random distribution of fault points, the varying maintenance skill requirements, and the coexistence of emergency repairs and routine inspections. The effective deployment of operation and maintenance personnel not only affects fault response speed but also resource efficiency and overall service quality. However, many current operation and maintenance scheduling methods still have significant limitations. Traditional scheduling methods often rely on static plans or manual coordination, lacking dynamic awareness of personnel's real-time location and the ability to flexibly adjust. When faced with unexpected tasks or complex environments, this approach often leads to uneven personnel allocation, with personnel concentrated in some areas and resources scarce in others, making efficient team collaboration difficult. Focusing on specific challenges, the sharing and coordination of real-time location information becomes a primary concern. Most existing operation and maintenance management systems use fixed reporting nodes or scheduled reporting methods to monitor personnel dynamics. This method has problems such as information lag and insufficient accuracy. It is impossible to accurately determine whether the distance distribution between personnel is reasonable, and it is difficult to perceive whether there are overlaps or vacancies in the work area. This lack of information further leads to the inability to adjust the scheduling strategy in a timely manner according to actual conditions, such as optimizing task allocation when personnel gather, or quickly organizing support when personnel are dispersed. The deeper problem is that the lack of this dynamic adjustment capability directly affects the flexibility of team collaboration, which limits the efficiency of task execution and the ability to provide mutual assistance in emergency situations, and increases the complexity of operation and maintenance management. Therefore, how to build a coordination mechanism based on real-time location sharing to dynamically adjust the distance distribution and the degree of overlap between work areas between team members, and improve the efficiency of team collaboration through intelligent scheduling strategies, has become a key issue that needs to be solved urgently. Summary of the Invention

[0003] The present invention provides a low-voltage distribution network operation and maintenance personnel scheduling method based on a positioning system, which mainly includes: Acquire real-time location data of the terminal devices of the operation and maintenance personnel, classify and organize the real-time location data according to the operation area of the low-voltage distribution network, display the current location of the operation and maintenance personnel on an electronic map, and generate a dynamic view of the personnel distribution; Count the number of personnel in each work area in the dynamic personnel distribution view, compare it with the preset standard configuration number, mark the work areas where the personnel density exceeds or falls below the threshold, analyze the distribution network line intersection and equipment sharing in adjacent work areas, and determine the degree of overlap of work areas, personnel concentration or vacancies; For operating areas where the degree of overlap exceeds the threshold, the system verifies the configuration of distribution network-specific tools and spare parts, assesses resource carrying capacity, and generates personnel dispersal or support instructions based on the skill level of the operation and maintenance personnel and the time cost of cross-regional movement. According to the personnel dispersion or support instructions, a list of distribution network equipment maintenance tasks to be executed is matched with the real-time location data, and a preliminary distribution network maintenance task allocation plan is generated in combination with the maintenance task priority and the power outage impact; generating an optimized distribution network maintenance task allocation plan based on the preliminary distribution network maintenance task allocation plan; Push the optimized network distribution task allocation plan to the terminal device of the operation and maintenance personnel, receive execution status feedback, and determine new aggregation or vacancy phenomena; If there are new gatherings or vacancies, adjust personnel distribution and task assignments, update terminal device instructions, and record scheduling data.

[0004] An electronic device comprises a communication interface, a processor, a memory and a bus, wherein the communication interface, the processor and the memory are interconnected via the bus; The memory stores machine-readable instructions, and the processor executes the above method by calling the machine-readable instructions.

[0005] The technical solution provided by the embodiment of the present invention may have the following beneficial effects: The present invention discloses a method for dispatching operation and maintenance personnel for a low-voltage distribution network based on a positioning system. The location information of the operation and maintenance personnel is obtained through a real-time positioning and tracking system, the distribution of personnel is dynamically displayed on an electronic map, and a comparative analysis is performed with the standard configuration to identify areas with abnormal personnel density. In response to the phenomenon of personnel gathering or vacancies, the present invention combines the maintenance requirements of distribution network equipment, the skill level of personnel and the cost of mobility to generate optimized personnel dispatch instructions. At the same time, the present invention associates and matches the maintenance tasks to be performed with the positions of personnel, considers the equipment priority and the impact of power outages, dynamically generates and optimizes the distribution network task allocation plan, and avoids maintenance conflicts through staggered operations. The present invention also monitors the task execution status in real time. When a new abnormality in personnel distribution occurs, a dynamic adjustment mechanism is triggered to reallocate tasks and update dispatch instructions. This method can effectively improve the operation and maintenance efficiency of low-voltage distribution networks, optimize human resource allocation, reduce equipment maintenance conflicts, and ensure the reliable operation of distribution networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Figure 1This is a flow chart of the low-voltage distribution network operation and maintenance personnel scheduling method based on the positioning system of the present invention. DETAILED DESCRIPTION

[0007] In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0008] like Figure 1 The low-voltage distribution network operation and maintenance personnel scheduling method based on the positioning system in this embodiment may specifically include: S101. Acquire real-time location data of terminal devices of operation and maintenance personnel, classify and organize the real-time location data according to the operation area of the low-voltage distribution network, display the current location of the operation and maintenance personnel on an electronic map, and generate a dynamic view of personnel distribution.

[0009] The system obtains longitude and latitude coordinate data from the positioning terminals worn by maintenance personnel. The GPS signal receiving module collects location information at preset time intervals. The received raw coordinate data is filtered for noise, eliminating coordinate points with signal strength below a threshold. Valid coordinate data is retained to form a personnel location data sequence. Based on a pre-established distribution network equipment ledger database, the geographic boundary coordinates of the transformer substation, the coordinate sequence of the start and end points of the distribution line segments, and the center coordinates of the switch station are extracted. For each coordinate point in the personnel location data sequence, it is determined whether it falls within the substation boundary polygon. If the coordinate point is within a substation boundary, the corresponding substation affiliation identifier is assigned to the coordinate point. Coordinate points with the same substation affiliation identifier are grouped, and the arithmetic mean of all coordinate points in each group is calculated to obtain the coordinates of the personnel distribution center for that substation. The relative position vector is calculated based on the difference between each personnel coordinate and the distribution center coordinate. Personnel icons for each substation are marked with different colors on the electronic map. The icon positions are refreshed based on real-time coordinate data updates to create a dynamic view of personnel distribution.

[0010] Specifically, data collection in positioning terminals involves the collaborative work of multiple sensors.

[0011] In one possible implementation, the positioning terminal not only includes a GPS receiver module but also integrates a Beidou positioning chip and base station positioning capabilities. When maintenance personnel enter an underground power distribution room or a densely populated area, the GPS signal attenuates. At this point, the positioning terminal automatically switches to base station positioning mode, performing triangulation by detecting the signal strength of surrounding base stations. The noise filtering process primarily assesses signal quality. When the horizontal dilution of precision (HDOP) returned by the GPS module exceeds 2.5, indicating poor satellite geometry, the coordinate data is marked as low-quality. Furthermore, if the distance between two consecutively collected coordinate points exceeds the distance threshold corresponding to a normal walking speed, the system identifies this as an abnormal jump and rejects it.

[0012] It should be noted that the establishment of a distribution network equipment inventory database requires precise mapping of various types of equipment. The geographical boundaries of the transformer substation are obtained through on-site surveys. Surveyors collect the coordinates of key inflection points along the boundaries of the substation's power supply range to form a closed polygonal area. The distribution line section records the coordinates of each pole or cable well, and arranges them in the order of the line direction to form a coordinate sequence. The ray method is used to determine whether the coordinate point is inside the polygon. Rays are emitted from the point to be judged in any direction, and the number of intersections between the rays and the polygon boundary is counted. An odd number of intersections indicates that the point is inside, and an even number indicates that it is outside. This judgment method can accurately handle complex boundary conditions such as concave polygons.

[0013] Specifically, the coordinates of the personnel distribution center are calculated using the arithmetic mean method, that is, the longitude values of all personnel in the same area are added and divided by the number of personnel to obtain the central longitude. The latitude values are calculated similarly. The relative position vector is calculated by subtracting the center coordinates from the coordinates of each person. The resulting difference vector contains both the distance information of the person relative to the center and the direction information. When displayed on the electronic map, different areas are distinguished by eye-catching colors such as red, yellow, and blue. The size of the personnel icon can be adjusted according to the length of their stay. The longer the stay, the larger the icon, making it easier for dispatchers to quickly identify which areas have longer operating times. The refresh frequency of the dynamic view is consistent with the data collection frequency, ensuring the real-time display of the map, allowing dispatchers to promptly grasp the distribution of on-site workers and rationally allocate human resources.

[0014] S102. Count the number of personnel in each work area in the dynamic view of personnel distribution, compare it with the preset standard configuration number, mark the work areas where the personnel density exceeds or falls below the preset threshold, analyze the distribution network line intersection and equipment sharing in adjacent work areas, and determine the degree of overlap of work areas, personnel gathering or vacancy.

[0015] The real-time personnel count for each work area is extracted from the dynamic view of personnel distribution. The pre-set standard personnel count for each area is read and the ratio of the actual personnel count to the standard personnel count is calculated. If the ratio exceeds the preset upper threshold, the area is marked as an area with excessively high personnel density. If the ratio is below the preset lower threshold, the area is marked as an area with insufficient personnel density. The personnel density status mark and corresponding density ratio are obtained for each area. Based on the personnel density status mark and density ratio, adjacent work area pairs with different personnel densities are identified. The equipment lists for these adjacent areas are extracted from the pre-stored distribution equipment location data. The number of distribution lines crossing the area boundary and the number of switchgear under the jurisdiction of the two areas are counted. The ratio of the number of shared equipment to the total number of equipment in the two areas is calculated as the equipment sharing degree value, and the equipment sharing degree value for each adjacent area pair is obtained. For pairs of adjacent areas whose equipment sharing degree values exceed the threshold, combined with the difference in their personnel density ratios, if the personnel density in one area is too high and the personnel density in the adjacent area is too low, it is determined that there is a phenomenon of personnel gathering; if the equipment sharing degree value of adjacent area pairs exceeds the threshold and there are personnel working in both areas, it is determined that there is an overlapping of operating areas; if the personnel density in a certain area is too low and the personnel density of all its adjacent areas does not exceed the standard configuration, it is determined that there is a vacancy in that area.

[0016] Specifically, the calculation process of the personnel density ratio needs to take into account the actual characteristics of the work area.

[0017] In one possible implementation, the standard number of personnel is determined based on the number of devices in the area, historical failure rates, and complexity of the operation.

[0018] For example, a transformer substation has 10 distribution transformers and 50 branch boxes, with a historical average of three failures per month. The standard staffing requirement is four operators. If real-time monitoring shows eight operators in the area, the density ratio is 2.0, exceeding the preset upper threshold of 1.5. The system automatically marks the area as overly dense. This marking mechanism enables rapid identification of abnormalities in human resource allocation.

[0019] It should be noted that the identification of adjacent operating areas depends on the physical connection relationship of the distribution network. The distribution equipment location data contains the latitude and longitude coordinates of each device, the line number to which it belongs, and the jurisdiction information. When there is a direct distribution line connection between two areas, or they share the same upper-level switch station, the two areas are defined as adjacent areas. The calculation of the equipment sharing degree value takes into account the collaborative operation needs in actual operation and maintenance. Shared equipment includes interconnecting switches on regional boundaries, distribution lines for cross-regional power supply, and ring network cabinets serving multiple areas.

[0020] Specifically, the logic for judging the phenomenon of personnel gathering is based on the principle of supply and demand balance. When the personnel density ratio in area A reaches 2.5 and that in the adjacent area B is only 0.3, it indicates that an emergency failure may have occurred in area A or a large-scale maintenance operation is underway, which has attracted personnel support from surrounding areas. The judgment of overlapping operating areas focuses on the intersection of the actual operating range. When the equipment sharing degree value of two adjacent areas exceeds 0.3, it means that more than 30% of the equipment requires joint maintenance by personnel from both areas. At this time, if there are personnel on duty in both areas, it is very likely that unclear responsibilities and repeated operations will occur. The identification of vacancy phenomena is more complicated. It not only depends on the personnel configuration of the current area, but also on the analysis of the support capabilities of the surrounding areas.

[0021] For example, the staff density ratio in Area C is only 0.2, while the density ratios in its three adjacent areas are 0.8, 0.6, and 0.7, respectively—all below standard. This indicates a staff shortage across the entire area, and that Area C's vacancies cannot be addressed by redeploying personnel from adjacent areas. This multi-dimensional assessment method accurately reflects the true state of distribution network O&M personnel, providing a reliable basis for subsequent personnel scheduling decisions.

[0022] S103. For the operation areas where the degree of overlap exceeds the preset overlap threshold, check the configuration of distribution network special tools and spare parts, evaluate the resource carrying status, and generate personnel dispersion or support instructions based on the skill level of the operation and maintenance personnel and the time cost of cross-regional movement.

[0023] When it is detected that the overlap of the operating areas exceeds the preset overlap threshold, the inventory data of the distribution network special tools and spare parts in each overlapping area is obtained, the existing quantity of each type of tools and accessories is counted, and the total number of existing tools is divided by the actual number of workers to obtain the resource allocation value. If the resource allocation value is lower than the preset standard value, it is determined that the area does not have the resource conditions to undertake additional personnel, and the resource carrying status identification of each area is obtained. Based on the resource carrying status identification, the skill level values of the operation and maintenance personnel in the area with concentrated personnel and sufficient resources are read, the current location coordinates of these personnel and the coordinates of the center point of the surrounding resource-deficient area are obtained, the straight-line distance between the two points is calculated and divided by the average moving speed to obtain the estimated moving time, and the moving time is multiplied by the time cost coefficient plus the inverse of the skill level to obtain the personnel deployment cost value. The personnel with the smallest deployment cost value are selected to generate a dispersion instruction containing the target area number. For the vacant areas identified after the personnel deployment cost value calculation is completed, the type and difficulty level of the maintenance tasks to be performed in the area are extracted, and operation and maintenance personnel with skill levels not lower than the task difficulty level are screened from adjacent areas. The personnel skill level value is divided by the task difficulty level to obtain the matching degree. If the matching degree exceeds the preset threshold, a personnel support instruction is generated containing the support personnel number, departure area and target vacant area.

[0024] Specifically, the calculation of resource allocation value needs to comprehensively consider the importance of different types of tools.

[0025] In one embodiment, distribution network-specific tools include three categories: safety protection, measurement and testing, and operation tools, as well as spare parts such as switches, fuses, and other replaceable components. Safety protection tools, such as insulating gloves and hard hats, must be provided to each person. Measurement and testing tools, such as multimeters and clamp-on ammeters, can be shared by multiple people. Operation tools, such as insulating operating rods, are configured based on the specific task. Assume that an area has 20 sets of safety protection tools, 8 measuring instruments, and 12 operating levers. The spare parts category includes 6 sets of key spare parts (2 sets of transformer spare parts and 4 sets of switch spare parts), 25 common spare parts (15 fuses and 10 contactors), 50 general spare parts (various basic materials), and 15 actual operators. The resource allocation value needs to be categorized when calculating the resource allocation value: the safety protection resource allocation value is 1.33, the measurement and testing resource allocation value is 0.53, the operation resource allocation value is 0.8, and the spare parts resource allocation value is (6 + 25 + 50) pieces ÷ 15 people = 81 ÷ 15 = 5.4. The minimum value of 0.53 is taken as the comprehensive resource allocation value for the area.

[0026] It's important to note that the resource load status indicator directly impacts subsequent personnel deployment decisions. When an area is identified as under-resourced, additional personnel should not be transferred in, even if there are vacancies. This prevents tool shortages from reducing operational efficiency or increasing safety risks. Conversely, areas with sufficient resources can be prioritized for personnel deployment. This resource-based deployment mechanism ensures the coordination of personnel distribution and resource allocation.

[0027] Specifically, the calculation of personnel deployment costs integrates time cost and skill matching. The time cost coefficient is typically set based on the urgency of the task, with a higher coefficient for emergency repairs and a lower coefficient for routine inspections. Skill level values are calculated using a five-level system, with level one representing entry-level workers and level five representing senior technicians.

[0028] For example, if a Level 3 technician is deployed from Area A to Area B, 5 kilometers away, at an average speed of 30 kilometers per hour, the estimated travel time is 0.17 hours. With a time cost coefficient of 10, the time cost is 1.7. The inverse of the skill level is 0.33, and the two combined yield a deployment cost of 2.03. This calculation method considers both the timeliness of deployment and the rational utilization of personnel skills. The matching degree calculation emphasizes the correspondence between task requirements and personnel capabilities. Maintenance tasks are divided into five difficulty levels based on equipment type and fault complexity, corresponding to personnel skill levels. When a Level 4 technician handles a Level 3 task, the matching degree is 1.33, indicating sufficient skill. When a Level 2 technician handles a Level 3 task, the matching degree is 0.67, below the threshold of 1.0, making it inappropriate for deployment. This quantitative matching mechanism ensures that each maintenance task is assigned to a person with the appropriate skill level, avoiding overqualification and preventing operational risks caused by insufficient skills, thereby optimizing human resource allocation.

[0029] S104: Based on the personnel dispersion or support instructions, a list of distribution network equipment maintenance tasks to be executed is matched with the real-time location data, and a preliminary distribution network maintenance task allocation plan is generated in combination with maintenance task priorities and power outage impacts.

[0030] Obtain the target area number and personnel number from the personnel dispersal or support instructions. Determine the personnel's post-deployment location based on the target area center coordinates in the instructions. Extract the equipment location coordinates and task type for each task from the distribution network equipment maintenance task list. Calculate the straight-line distance from each personnel location to each device to be maintained to form a personnel-task distance matrix. Based on the distance values in the personnel-task distance matrix, read the distribution network equipment load level corresponding to each maintenance task. Multiply the load level value by the inverse of the distance value to obtain the distance-weighted load importance. Query the number of users downstream of each device from the power supply topology data. Add the number of users to the distance-weighted load importance to obtain a comprehensive priority score for each task. Use the comprehensive priority score to construct a task assignment matrix, where rows represent personnel and columns represent tasks. The matrix elements represent the corresponding comprehensive priority scores. Apply the Hungarian algorithm to find the optimal match for the matrix. Output the maintenance task number and corresponding equipment location assigned to each personnel, generating a preliminary distribution network maintenance task assignment plan.

[0031] Specifically, the construction of the personnel-task distance matrix fully considers the impact of actual geographical conditions on work efficiency.

[0032] In one possible implementation, when a personnel dispersal order specifies that a technician be transferred from Area A to Area B, the coordinates of the target area's center are determined by taking the arithmetic mean of the coordinates of all equipment in Area B. For example, suppose there's a distribution transformer in Area B awaiting repair, located at 121.5 degrees east longitude and 31.2 degrees north latitude. The technician's estimated location is at the center of Area B, at 121.48 degrees east longitude and 31.18 degrees north latitude. By converting longitude and latitude, the straight-line distance is calculated to be approximately 2.8 kilometers. This distance calculation based on actual geographic location provides an objective basis for subsequent task assignments.

[0033] It's important to note that distance-weighted load importance calculation reflects the principles of proximity and prioritizing critical loads. Load levels are typically categorized from one to three. Level one loads, such as hospitals and key government departments, are assigned a value of 3, where power outages could have a significant impact. Level two loads, such as commercial centers, are assigned a value of 2. Level three loads, such as general residential electricity consumption, are assigned a value of 1. If a level one load is 2 kilometers from a technician, the reciprocal of the distance is 0.5, which, multiplied by the load level of 3, yields a distance-weighted load importance of 1.5. This calculation method prioritizes closer, more critical equipment.

[0034] Specifically, querying power supply topology data involves analyzing the tree structure of the distribution network. Each distribution device has a clear upstream and downstream relationship in the topology. By tracing the downstream branches of a device, the number of affected users can be counted. For example, if a 10kV switch is connected to three branch lines downstream, supplying 500, 300, and 200 households, respectively, a switch failure will affect 1,000 households. Adding these 1,000 households to the distance-weighted load importance of 1.5 calculated above yields a comprehensive priority score of 1001.5. This score reflects both the power supply importance of the device and the ease of maintenance response. The application of the Hungarian algorithm to task allocation ensures a globally optimal solution. When constructing the task allocation matrix, if there are three technicians and five maintenance tasks, a 3×5 matrix is formed, with each element representing the comprehensive priority score for a specific technician completing a specific task. The Hungarian algorithm uses row-column transformations to find a matching solution that maximizes the total score, ensuring that each technician is assigned only one task and that each task is handled by only one technician. The algorithm output may show that technician A is responsible for repairing the hospital's distribution room, technician B is responsible for replacing switches in the commercial area, and technician C is responsible for handling line failures in the residential area. This allocation plan maximizes the overall maintenance benefits while satisfying the one-person-one-task constraint.

[0035] S105: Generate an optimized distribution network maintenance task allocation plan based on the preliminary distribution network maintenance task allocation plan.

[0036] The initial distribution network maintenance task allocation plan extracts each person's assigned task location and required tool list. The inventory data for distribution network-specific tools and spare parts at each workstation is compared, and the difference between the required tool quantity and the inventory quantity is calculated. If the difference is negative, the workstation is marked as a resource-deficient point. The ratio of shared equipment between adjacent workstations to the total equipment quantity is calculated. If the ratio exceeds a preset threshold, it is determined that there is overlap in the work area. Based on the marking results of the resource-deficient point and the determination of the overlap in the work area, the skill level values of the relevant personnel and the complexity values of the corresponding maintenance tasks are read. The inventory quantity at the workstation is divided by the required quantity to obtain the resource satisfaction rate. The ratio of the personnel skill level to the task complexity is multiplied by the resource satisfaction rate to obtain the adjusted matching score. The task allocation operation is re-executed based on the adjusted matching score, and the revised task allocation plan is output. For the revised task allocation plan, adjacent operation points that still have shared equipment are identified, and the power outage window period data of these operation points are extracted from the distribution network operation plan. They are sorted according to the number of power users involved in each operation, and the operations with a large number of users are assigned to the earlier time periods, and the operations with a small number of users are assigned to the later time periods. A preset interval time is set between each time period to generate an optimized distribution network task allocation plan that includes time period arrangements.

[0037] Specifically, the inventory comparison of distribution network-specific tools and spare parts involves a multi-level resource management system.

[0038] In one possible implementation, each work site maintains a tool and spare parts log, recording the model and quantity of specialized tools such as insulated operating rods, grounding wire sets, and electroscopes. If a maintenance task requires two grounding wire sets and the work site only has one in stock, the difference is -1, and the system automatically flags the resource as insufficient. This negative value flagging mechanism quickly identifies resource bottlenecks, preventing maintenance personnel from discovering tool shortages only upon arrival.

[0039] It's important to note that the calculation of the shared equipment ratio reflects the degree of physical overlap between work areas. Adjacent work sites often have commonly maintained equipment, such as interconnecting switches and T-connectors. Assuming work site A has 20 devices and work site B has 15 devices, 5 of which are interface devices shared by both sites. The shared equipment ratio then accounts for 5 / 35 of the total equipment, or approximately 14.3%. When this ratio exceeds the preset 10% threshold, it indicates significant overlap between the two work areas, potentially leading to unclear maintenance responsibilities or duplicated work.

[0040] Specifically, the introduction of the resource fulfillment ratio allows for a comprehensive consideration of resource constraints and personnel skills. A certain work site requires three insulated operating rods, but only two are in stock, resulting in a resource fulfillment ratio of 0.67. When a technician with a skill level of 4 is assigned to a task with a complexity of 3, the original matching score is 4 / 3 = 1.33. After accounting for resource constraints, the adjusted matching score becomes 1.33 × 0.67 = 0.89. This adjustment mechanism ensures that even if the skill match is high, the priority of the task will be reduced if resources are insufficient, prompting the system to seek alternative solutions with more sufficient resources. The scheduling of power outage windows reflects the continuity requirements of power grid operations. Distribution network operation plans typically divide the day into multiple time periods, each with corresponding load forecasts and power supply reliability requirements.

[0041] For example, during peak hours for industrial and commercial electricity consumption, 8-10 a.m., power outages affecting more than 1,000 households are scheduled. During the relatively low load hours of 2-4 p.m., maintenance tasks affecting fewer than 500 households are scheduled. A one-hour interval between these time periods ensures the completion of the previous batch of tasks while allowing time for subsequent tasks to be prepared. This user-influence-based time allocation minimizes the impact of power outages on social production and life, while also preventing multiple work groups from competing for shared resources during the same time period.

[0042] S106: Push the optimized distribution network task allocation plan to the operation and maintenance personnel's terminal device, receive execution status feedback, and determine new aggregation or vacancy phenomena.

[0043] From the optimized distribution network task allocation plan, each operator's task number, target device coordinates, and task content are extracted. This data is packaged into task instructions and pushed to the operator's terminal device. A weighted path map is constructed based on the road network in the distribution network area. The Dijkstra algorithm is used to calculate the shortest path from the operator's current location to the target device location. Path guidance data is then output, containing a sequence of nodes passed through and an estimated total distance. The terminal device periodically receives the operator's real-time location coordinates. The Euclidean distance between the real-time location and the expected location at the corresponding moment in the path guidance data is calculated as the position deviation. If the deviation exceeds a preset threshold, the operator's actual work location is updated. The time each operator arrives at the target device location is also recorded, generating dynamic personnel data containing the actual work location and arrival time. Based on the actual work location of each operator in the dynamic personnel data, personnel are assigned to the boundaries of the work area. The real-time density value is calculated as the ratio of the actual number of personnel in each area to the preset standard number of personnel in that area. If the real-time density value in a certain area exceeds an upper threshold, it is considered a new clustering phenomenon; if it falls below a lower threshold, it is considered a new vacancy phenomenon.

[0044] Specifically, building a weighted path map for the road network is the basis for achieving accurate navigation.

[0045] In one embodiment, the roads within the distribution network area are abstracted as edges of a graph, and the road intersections and equipment locations are nodes of the graph. The weight of each edge not only considers the physical distance, but also the road grade factor. The weight of the main road section is set to be the distance multiplied by 0.8 because the vehicle speed is relatively fast; the weight of the roads within the cell is set to be the distance multiplied by 1.5, reflecting the characteristics of slow driving speed and many turns. The Dijkstra algorithm starts from the starting point and gradually expands to the adjacent nodes, each time selecting the path with the smallest current cumulative weight to continue expanding until the target device location is reached. The final output path is the optimal path with the smallest total weight.

[0046] It should be noted that Euclidean distance calculation plays a key role in position deviation monitoring. When the operation and maintenance personnel follow the planned route, the system obtains their real-time coordinates at regular intervals. Assuming that the expected position at a certain moment is 121.48 degrees east longitude and 31.18 degrees north latitude, and the actual position is 121.485 degrees east longitude and 31.175 degrees north latitude, through longitude and latitude conversion and plane distance calculation, the deviation is approximately 707 meters. This deviation value reflects whether the personnel are traveling according to the established route. Excessive deviation may mean that they have encountered road construction, traffic congestion, or that the personnel have gone to other emergency task points.

[0047] Specifically, the calculation of real-time density values requires dynamic updating of the distribution of personnel within the work area. Each work area has a preset standard number of personnel, determined by the number of equipment within the area, historical fault frequency, and daily inspection workload. For example, if a transformer substation has a standard staffing of four personnel, and the system detects seven O&M personnel within the area, the real-time density value is 1.75. This excess may be due to a sudden fault, prompting support from personnel from surrounding areas. Conversely, if only one person is detected, the density value is only 0.25, far below the normal level. The density thresholds reflect the need for flexible O&M management. The upper threshold is typically set at 1.5 to allow for temporary gatherings of personnel to respond to emergencies; the lower threshold is set at 0.5 to ensure basic O&M resources. When the density value in a particular area reaches 1.8, the system identifies a new gathering. If this gathering persists for an extended period, it can create an O&M vacuum in other areas. By continuously monitoring changes in the real-time density values across each area, the system can promptly identify abnormal patterns in personnel distribution, providing real-time basis for scheduling decisions and ensuring optimal allocation of O&M resources across the distribution network.

[0048] S107. If there are new gatherings or vacancies, adjust personnel distribution and task assignments, update terminal device instructions, and record scheduling data.

[0049] If a new cluster or vacancy is detected, the network area number and type of phenomenon that triggered the adjustment are obtained. The current location and skill level values of all operation and maintenance personnel in these areas are re-read. The equipment number and estimated work hours of uncompleted maintenance tasks in each area are counted. The remaining workload is calculated by subtracting the actual work hours from the estimated work hours. The personnel skill levels are arranged into a personnel capability vector, and the remaining workload of the tasks is arranged into a task demand vector. An allocation matrix is constructed based on the personnel capability vector and the task demand vector. The matrix elements represent the personnel's fitness for completing the task. The Hungarian algorithm is used to find the optimal matching solution, and an adjustment instruction set containing the personnel number, new task number, and target location is generated. The adjustment instruction set is sent to the terminal devices of the relevant personnel via a push service, and the push time and receipt confirmation status are recorded. The personnel-task correspondence in the adjustment instruction set is combined with the push time and receipt confirmation status to extract the original task number before the adjustment and the new task number after the adjustment. The adjustment timestamp, the personnel number involved, the task change details, and the network area number are written to the database, generating a distribution network operation and maintenance scheduling log containing complete information about the scheduling process.

[0050] Specifically, the calculation of the remaining workload needs to be accurately evaluated in combination with the actual characteristics of the distribution network maintenance task.

[0051] In one embodiment, each maintenance task is created with an estimated duration, which is determined based on the equipment type, fault level, and historical maintenance data.

[0052] For example, if the standard labor time for replacing a 10kV switch is 4 hours, after 1.5 hours of execution, the remaining workload is 2.5 hours. For inspection tasks, the estimated labor time is calculated based on the number of devices inspected and the average inspection time per device. This quantitative workload assessment provides a clear benchmark for subsequent personnel reallocation.

[0053] It's important to note that the construction of the personnel capability vector and the task requirement vector embodies the principle of matching supply and demand. The personnel capability vector arranges the skill level of each operator in order of their personnel number, forming a one-dimensional array. For example, if a region has five operators with skill levels of 3, 4, 2, 5, and 3, the capability vector would be [3, 4, 2, 5, 3]. The task requirement vector arranges the remaining workload of each uncompleted task by task number, such as [2.5, 1.0, 3.5, 0.5] to represent the remaining hours for four tasks. This vectorized representation facilitates subsequent matrix operations.

[0054] Specifically, the construction of an allocation matrix and the application of the Hungarian algorithm achieve a globally optimal task allocation. Each element of the allocation matrix represents the suitability of a specific person to complete a specific task. This value takes into account the degree to which the person's skills match the complexity of the task, as well as the distance between the person and the task location.

[0055] For example, if a person with skill level 4 is handling a task requiring skill level 3, their basic fitness is 4 / 3 = 1.33. If the person is 2 kilometers from the task location, with a distance factor of 0.8, the final fitness value is 1.06. The Hungarian algorithm uses row-column transformations to find the allocation plan that maximizes the overall fitness, ensuring that each person is assigned the most appropriate task. The generation of a scheduling log not only records the results of adjustments but, more importantly, preserves the complete decision-making process. The timestamps in the log are accurate to the second, recording the entire process from detection of an anomaly to completion of the adjustment. Task change details include information such as the execution progress of the original task, the reason for the interruption, and the urgency of the new task.

[0056] For example, a log entry shows that technician Zhang was transferred from routine inspection duties in Substation A to emergency troubleshooting in Substation B at 2:32:15 PM. The original task completion rate was 60%. The reason for the transfer was a staff vacancy and a level 1 load outage in Substation B. This detailed log provides data support for subsequent O&M efficiency analysis and personnel performance evaluation, and also accumulates empirical data for optimizing scheduling strategies.

[0057] An embodiment of the present application also provides an electronic device, including a communication interface, a processor, a memory and a bus, wherein the communication interface, the processor and the memory are interconnected via a bus; the memory stores machine-readable instructions, and the processor executes the above method by calling the machine-readable instructions.

[0058] With the above embodiments of the present invention as inspiration, and through the above description, relevant personnel can make various changes and modifications without departing from the technical scope of this invention. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A low-voltage distribution network operation and maintenance personnel scheduling method based on a positioning system is characterized by: The method comprises: Acquire real-time location data of the terminal devices of the operation and maintenance personnel, classify and organize the real-time location data according to the operation area of the low-voltage distribution network, display the current location of the operation and maintenance personnel on an electronic map, and generate a dynamic view of the personnel distribution; Counting the number of personnel in each work area in the dynamic personnel distribution view, comparing it with the preset standard configuration number, marking the work areas where the personnel density exceeds or falls below the preset threshold, analyzing the intersection of distribution network lines and equipment sharing in adjacent work areas, and determining the degree of overlap of work areas, personnel concentration, or vacancies; For operating areas where the degree of overlap exceeds the preset overlap threshold, the system verifies the configuration of distribution network-specific tools and spare parts, assesses resource carrying capacity, and generates personnel dispersal or support instructions based on the skill level of the operation and maintenance personnel and the time cost of cross-regional movement. According to the personnel dispersion or support instructions, a list of distribution network equipment maintenance tasks to be executed is matched with the real-time location data, and a preliminary distribution network maintenance task allocation plan is generated in combination with the maintenance task priority and the power outage impact; generating an optimized distribution network maintenance task allocation plan based on the preliminary distribution network maintenance task allocation plan; Push the optimized network distribution task allocation plan to the terminal device of the operation and maintenance personnel, receive execution status feedback, and determine new aggregation or vacancy phenomena; If there are new gatherings or vacancies, adjust personnel distribution and task assignments, update terminal device instructions, and record scheduling data.

2. The low-voltage distribution network operation and maintenance personnel scheduling method based on the positioning system according to claim 1 is characterized in that: The method includes obtaining real-time location data of the terminal device of the operation and maintenance personnel, classifying and arranging the real-time location data according to the operation area of the low-voltage distribution network, displaying the current location of the operation and maintenance personnel on an electronic map, and generating a dynamic view of personnel distribution, including: Obtain longitude and latitude coordinate data from the terminal device of the operation and maintenance personnel, filter out coordinate points with signal strength lower than the preset strength threshold, and retain valid coordinate data to form a personnel location data sequence; According to the distribution network equipment ledger database, determine whether the coordinate point in the personnel location data sequence is located within the boundary of the transformer area, and mark the corresponding area ownership identifier; Group the coordinate points with the same area affiliation identification, calculate the arithmetic mean of the coordinate points in the group, determine the coordinates of the center of personnel distribution, generate relative position vectors, mark personnel icons on the electronic map, refresh the personnel location data sequence, and update the dynamic view of personnel distribution.

3. The low-voltage distribution network operation and maintenance personnel scheduling method based on the positioning system according to claim 1 is characterized in that: The counting of the number of personnel in each work area in the dynamic view of personnel distribution, comparing it with the preset standard configuration number of personnel, and marking the work areas where the personnel density exceeds or falls below the preset threshold value include: The real-time number of personnel in each work area in the dynamic view of personnel distribution is extracted, the ratio to the preset standard configuration number of personnel is calculated, and the areas where the ratio exceeds the upper preset threshold and the areas where the ratio is lower than the lower preset threshold are marked.

4. The method for dispatching low-voltage distribution network operation and maintenance personnel based on a positioning system according to claim 1, characterized in that: For the operation area where the overlap exceeds the preset overlap threshold, the configuration of distribution network-specific tools and spare parts is checked, and the resource carrying status is evaluated, including: Obtain inventory data on distribution network-specific tools and spare parts for operating areas where the degree of overlap exceeds a preset overlap threshold, calculate the resource allocation ratio of the total number of tools and spare parts to the number of operators, and mark areas where the resource allocation ratio is below the standard as resource-scarce areas.

5. The low-voltage distribution network operation and maintenance personnel scheduling method based on the positioning system according to claim 1 is characterized in that: The above-mentioned personnel dispersal or support instructions are generated by combining the skill level of the operation and maintenance personnel and the time cost of cross-region movement, including: Extract the skill level and current location coordinates of the operation and maintenance personnel from the resource-sufficient cluster area, calculate the distance to the center point of the resource-deficient area, combine the travel time cost and skill level to determine the deployment cost value, and generate a dispersion instruction containing the target area number; or For vacant areas, the maintenance task type and difficulty level are extracted, operation and maintenance personnel with matching skill levels are screened from adjacent areas, the matching degree between skill level and task difficulty is calculated, and support instructions containing personnel number and target area are generated.

6. The method for dispatching low-voltage distribution network operation and maintenance personnel based on a positioning system according to claim 1, characterized in that: According to the personnel dispersion or support instructions, matching the list of distribution network equipment maintenance tasks to be executed with the real-time location data, combining the maintenance task priorities and the power outage impact, and generating a preliminary distribution network maintenance task allocation plan, including: Extracting the personnel number and target area in the personnel dispersion or support instructions, calculating the distance between the location of the operation and maintenance personnel and the location of the equipment to be maintained, and forming a distance matrix; According to the distance values of the distance matrix, combined with the load level of the distribution network equipment and the number of downstream users, the comprehensive priority score of the task is calculated, the task allocation matrix is constructed, and a preliminary distribution network maintenance task allocation plan is generated.

7. The method for dispatching low-voltage distribution network operation and maintenance personnel based on a positioning system according to claim 1, characterized in that: Generating an optimized distribution network maintenance task allocation plan based on the preliminary distribution network maintenance task allocation plan includes: Extracting the task locations and required tool lists in the preliminary distribution network maintenance task allocation plan, calculating the difference between tool demand and inventory, and marking resource shortage points; The overlap of the operating areas is determined based on the ratio of the number of shared equipment between adjacent operating points to the total number of equipment; Adjust the matching weights between personnel skills and task difficulty based on resource shortages and overlapping work areas, and regenerate task allocation plans; For overlapping areas, staggered operation times are allocated to generate an optimized distribution network task allocation plan.

8. The method for dispatching low-voltage distribution network operation and maintenance personnel based on a positioning system according to claim 1, characterized in that: The optimized distribution network task allocation plan is pushed to the terminal device of the operation and maintenance personnel to guide the optimal path, receive execution status feedback, and determine new aggregation or vacancy phenomena, including: Encapsulate the task number and target coordinates in the optimized distribution network task allocation plan, push them to the terminal device of the operation and maintenance personnel, and calculate the shortest path from the current location to the target location; Receive real-time location coordinates, calculate deviations from expected locations, count the density of people in the area, and identify new gatherings or vacancies.

9. The method for dispatching low-voltage distribution network operation and maintenance personnel based on a positioning system according to claim 1, characterized in that: If there are new gatherings or vacancies, adjust personnel distribution and task assignments, update terminal device instructions, and record scheduling data, including: Obtain the area number that triggers the adjustment, count the real-time location data and unfinished task requirements, build an allocation matrix of personnel capabilities and task requirements, generate an adjustment instruction set, push it to the terminal device, record the adjustment time, personnel changes and task changes, and generate a scheduling log.

10. An electronic device, characterized in that: It includes a communication interface, a processor, a memory and a bus, wherein the communication interface, the processor and the memory are interconnected via the bus; The memory stores machine-readable instructions, and the processor executes the method according to any one of claims 1 to 9 by calling the machine-readable instructions.

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