Current collection line path planning method, device, equipment, medium and product

Abstract

The embodiment of the invention belongs to the technical field of electric power engineering, and particularly relates to a current collection line path planning method, device and equipment, a medium and a product. The method comprises the following steps of: identifying a sensitive area crossed by a starting fan and a target fan through a connecting line path of the starting fan and the target fan, determining an obstacle avoidance anchor point capable of bypassing the sensitive area according to a spatial relationship between a vertex of the area and the path, generating a primary obstacle avoidance path based on the obstacle avoidance anchor point, and identifying a sensitive area possibly crossed by the path again; and then, for each newly traversed sensitive area, a local optimization anchor point bypassing the area is determined, an optimized new path section is generated by inserting the local optimization anchor point into the path, and then the process is executed circularly until a global obstacle avoidance path which completely avoids all the sensitive areas and is close to the optimal in total length is formed. According to the method, automatic and accurate planning of the line path under the complex geographical constraint is realized, and the economical efficiency and the engineering implementability of the current collection line planning are remarkably improved.

Description

Technical Field

[0001] This application relates to the field of power engineering technology, and in particular to methods, apparatus, equipment, media and products for planning power line routes. Background Technology

[0002] In the construction of large-scale wind farms or wind power bases, collector line topology planning is a core step in connecting hundreds of wind turbine generators, directly impacting construction costs, operation and maintenance efficiency, and project feasibility. Traditional planning methods rely on manual experience to interconnect the units, resulting in problems such as large workload, low efficiency, high cost, and unsatisfactory planning results. In recent years, with technological advancements, the industry has gradually introduced algorithms such as triangulation, minimum spanning tree algorithm, genetic algorithm, and particle swarm optimization to achieve automated collector line topology planning. These algorithms have solved technical challenges such as parameter selection, topology optimization, and cost analysis, significantly improving planning efficiency and accuracy.

[0003] However, existing methods for calculating power line topology typically employ a simple straight-line connection when linking two wind turbines, failing to adequately consider and effectively avoid restricted spatial areas such as basic farmland, forest farms, mining areas, nature reserves, residential areas, and specific restricted zones. Cost models based on straight-line distance ignore the additional line length required to bypass these restricted areas, causing the life-cycle assessment results to deviate from actual operating conditions and resulting in a final solution that falls short of the true cost-optimal solution.

[0004] Therefore, how to avoid sensitive areas during the planning of power transmission lines has become an urgent problem that needs to be solved by current technology. Summary of the Invention

[0005] The main objective of this application is to provide a method, apparatus, equipment, medium, and product for planning power line routes, aiming to solve the technical problem of how to avoid sensitive areas during the planning of power lines in the prior art.

[0006] To achieve the above objectives, this application provides a method for planning power line routes, the method comprising the following steps: Obtain the connection path between the starting fan and the target fan, and designate the sensitive area traversed by the connection path as the first sensitive area; Based on the regional vertices of the first sensitive area and the connecting path, determine the obstacle avoidance anchor point; Based on the obstacle avoidance anchor points, an obstacle avoidance path is obtained, and the sensitive area traversed by the obstacle avoidance path is designated as the second sensitive area. Based on the region vertices of the second sensitive region and the obstacle avoidance path, an obstacle avoidance optimization anchor point is determined, and the obstacle avoidance optimization anchor point updates the obstacle avoidance path to obtain a global obstacle avoidance path.

[0007] Optionally, determining the obstacle avoidance anchor point based on the region vertices of the first sensitive region and the connecting path includes: The first sensitive region is segmented according to the connection path to obtain multiple sub-regions; Candidate obstacle avoidance anchor points are determined based on the distance between the vertices of each of the divided sub-regions and the connecting path. The starting wind turbine, the candidate obstacle avoidance anchor point, and the target wind turbine are connected in sequence to form multiple candidate paths, and the total length of each candidate path is calculated. The obstacle avoidance anchor point is determined based on the sorting result of the total length of the candidate paths.

[0008] Optionally, the step of segmenting the first sensitive region according to the connection path to obtain multiple sub-regions includes: Based on the straight line of the connecting path, the vertices of the first sensitive region are divided to both sides; Based on the distribution of the vertices of the region on both sides of the connecting path, the vertices of the region located on the same side are grouped into the same set; Based on each vertex set and its connection relationship on the boundary of the sensitive region, the respective closed polygon regions are determined, resulting in the multiple sub-regions.

[0009] Optionally, determining candidate obstacle avoidance anchor points based on the distance between each vertex of the divided sub-region and the connecting path includes: Based on the vertices of the divided sub-regions, calculate the vertical distance from each region vertex to the connecting path; Based on the vertical distance and the vertical intersection relationship between the vertices of each region and the connecting path, the candidate anchor points for dividing the sub-regions are determined; The candidate anchor points of each sub-region are summarized to obtain the candidate obstacle avoidance anchor points.

[0010] Optionally, obtaining the obstacle avoidance path based on the obstacle avoidance anchor point, and designating the sensitive area traversed by the obstacle avoidance path as the second sensitive area, includes: By sequentially connecting the starting fan, obstacle avoidance anchor point and target fan, an obstacle avoidance path composed of several path segments is obtained. Based on the spatial position of each path segment in the obstacle avoidance path and the sensitive area, the path segment that was crossed and the sensitive area corresponding to the path segment are obtained. The sensitive regions are arranged sequentially according to the connection order of the path segments to obtain the second sensitive region.

[0011] Optionally, the step of determining obstacle avoidance optimization anchor points based on the region vertices of the second sensitive region and the obstacle avoidance path, and updating the obstacle avoidance path using the obstacle avoidance optimization anchor points to obtain a global obstacle avoidance path, includes: Traverse the vertices of the second sensitive region and divide the vertices of the region according to the corresponding path segments to obtain the subset of vertices of the region corresponding to each path segment; Based on the spatial relationship between the subset of region vertices and the target path segment, determine the vertical distance from each region vertex to the path segment; Based on the vertical distances corresponding to the vertices of each region, the obstacle avoidance optimization anchor points corresponding to the path segments are determined; Each obstacle avoidance optimization anchor point is inserted sequentially between the two endpoints of the corresponding path segment in the obstacle avoidance path according to the connection order of its corresponding path segment in the obstacle avoidance path, so as to generate a local obstacle avoidance path that bypasses the boundary of the second sensitive area. The local obstacle avoidance path is replaced with the corresponding path segment in the obstacle avoidance path to obtain the global obstacle avoidance path.

[0012] Furthermore, to achieve the above objectives, this application also proposes a collector line path planning device, which includes: The path planning module is used to obtain the connection path between the starting wind turbine and the target wind turbine, and to use the sensitive area traversed by the connection path as the first sensitive area. The path planning module is also used to determine obstacle avoidance anchor points based on the regional vertices of the first sensitive area and the connecting path; The path optimization module is used to obtain an obstacle avoidance path based on the obstacle avoidance anchor points, and to use the sensitive area traversed by the obstacle avoidance path as a second sensitive area. The path optimization module is further configured to determine obstacle avoidance optimization anchor points based on the region vertices of the second sensitive region and the obstacle avoidance path, and update the obstacle avoidance path using the obstacle avoidance optimization anchor points to obtain a global obstacle avoidance path.

[0013] Furthermore, to achieve the above objectives, this application also proposes a power line path planning device, which includes: a memory, a processor, and a power line path planning program stored in the memory and executable on the processor. The power line path planning program is configured to implement the steps of the power line path planning method described above.

[0014] In addition, to achieve the above objectives, this application also proposes a storage medium storing a collector path planning program, which, when executed by a processor, implements the steps of the collector path planning method described above.

[0015] In addition, to achieve the above objectives, this application also proposes a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the collector line path planning method described above.

[0016] The proposed technical solutions (one or more) have at least the following technical effects: This solution generates obstacle avoidance anchor points to guide detours by identifying and anchoring sensitive areas traversed by the initial path, thereby quickly constructing a preliminary obstacle avoidance path. Then, by further performing secondary conflict detection and anchor point optimization on the newly generated obstacle avoidance path, an iterative optimization closed loop is formed, eliminating all path obstacles layer by layer. This method, through a two-level anchor point mechanism and iterative updates, can automatically and reliably ensure that the path completely avoids all sensitive areas. Simultaneously, the selection and optimization process of anchor points is essentially a continuous local adjustment of the path length under geometric constraints, making the final global obstacle avoidance path approach optimal in terms of the total length of the entire line, significantly improving the economy and engineering feasibility of power line planning. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the first embodiment of the power line path planning method according to this application. Figure 2 This is a flowchart illustrating a second embodiment of the power line path planning method provided in this application. Figure 3 A structural block diagram of the first embodiment of the power line path planning device provided in this application; Figure 4 This is a schematic diagram of the structure of the power line path planning device in the hardware operating environment involved in the embodiment of the present application. Detailed Implementation

[0020] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of the embodiments of this application and are not intended to limit the embodiments of this application.

[0021] To better understand the technical solutions of the embodiments of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0022] Currently, existing power transmission line planning typically employs simple straight-line connections, failing to adequately consider and effectively avoid restricted areas such as basic farmland and forest farms. Furthermore, cost models based on straight-line distances neglect the additional line length required to bypass these restricted areas, causing life-cycle assessment results to deviate from actual operating conditions and ultimately leading to a solution that falls short of the true cost-optimal solution. Therefore, how to achieve avoidance of sensitive areas during power transmission line planning is a pressing technical problem that needs to be solved.

[0023] To address the aforementioned issues, this application provides a power collection line path planning method. By identifying the sensitive areas traversed by the connecting path between the starting and target wind turbines, and determining obstacle avoidance anchor points that can bypass the sensitive areas based on the spatial relationship between the region vertices and the path, a preliminary obstacle avoidance path is generated based on these anchor points. The sensitive areas that this path may traverse are then identified again. Subsequently, for each newly traversed sensitive area, a locally optimized anchor point is determined to bypass that area. By inserting this anchor point into the path, an optimized new path segment is generated. This process is repeated until a globally optimized obstacle avoidance path is formed that completely avoids all sensitive areas and is close to the optimal path in terms of total length. This method achieves automatic and accurate planning of power collection line paths under complex geographical constraints, significantly improving the economy and engineering feasibility of power collection line planning.

[0024] The execution subject of this application embodiment can be a power line path planning device, or a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or a thermal management device capable of realizing the above functions of a power line path planning device, etc. This embodiment does not specifically limit it. The following uses a power line path planning device as the execution subject as an example to describe this embodiment and the following embodiments.

[0025] Figure 1 This is a flowchart illustrating the power line path planning method provided in an embodiment of this application.

[0026] Reference Figure 1 In this embodiment, the power line path planning method includes steps S10 to S40: Step S10: Obtain the connection path between the starting fan and the target fan, and designate the sensitive area traversed by the connection path as the first sensitive area.

[0027] In practice, the system first obtains the straight-line connection between the starting wind turbine and the target wind turbine in space, i.e., the theoretical shortest path. Then, the system performs spatial intersection analysis on this straight-line path and the spatial boundary data of all known sensitive areas, either pre-entered or obtained through a geographic information system. If the analysis shows that the straight-line path traverses the interior of one or more sensitive areas, these traversed areas are marked and collectively referred to as the first sensitive area.

[0028] Understandably, this process is entirely automated by the algorithm, requiring no human intervention. The initial path represents the cost-optimal solution without considering any obstacles, but its passage through sensitive areas means that the solution is rejected due to unmet constraints. By first focusing on these directly conflicting areas, the algorithm can identify the core objectives that need to be avoided in the current stage, thus providing a clear and limited set of objects to be processed for subsequent detour strategies, avoiding the computational chaos caused by simultaneously handling all potentially complex terrains and constraints.

[0029] It is important to note that the sensitive areas traversed have a specific order on the connecting line. When identifying the first sensitive area, the algorithm should not simply treat all traversed areas as an unordered set, but must accurately calculate the sequence of areas encountered in the initial connecting path as it travels from the starting wind turbine end to the target wind turbine end, based on their geographical coordinates.

[0030] Step S20: Determine the obstacle avoidance anchor point based on the region vertices and connecting paths of the first sensitive region.

[0031] In this embodiment, the scope of the sensitive area is typically represented digitally as a polygon. This polygon is formed by connecting a series of ordered points with geographic coordinates, creating a closed shape to precisely define the planar geometric boundary of the area. Based on the boundary data of these polygons, the system performs spatial analysis such as "whether a point is inside the polygon" or "whether a line segment intersects the polygon" to determine whether a path constitutes a crossing.

[0032] In practical implementation, for each traversed sensitive area, the system divides the sensitive area into two sub-parts using the initial connecting path. Then, it calculates the perpendicular distance from all boundary vertices of each sub-part to the initial line segment, and selects the vertex with the farthest perpendicular distance from each sub-part. These two vertices are candidate obstacle avoidance anchor points. For example, for a traversed forest area, the algorithm will find the vertex furthest from the line segment in the left part and the vertex furthest from the line segment in the right part. By setting the anchor points outside the boundary of the sensitive area, it ensures that the path does not intrude into the area. Simultaneously, the anchor point selection process involves preliminary optimization of the total path length. Its goal is to make the connection between new path segments (i.e., from one anchor point to the next) as close to a straight line as possible, while satisfying the hard constraint of obstacle avoidance, thereby controlling the additional cost of detours.

[0033] Understandably, the core principle of this approach lies in selecting the vertex furthest from the initial line segment in each segmented part, thereby maximizing the guidance of the path away from the sensitive area and ensuring safe obstacle avoidance. Simultaneously, the algorithm compares the total lengths of the two new paths formed via candidate points on both sides, calculating the distances from the starting point to candidate point one and then to the ending point, and from the starting point to candidate point two and then to the ending point, respectively. The candidate point corresponding to the path with the shorter total length is selected as the final insertion anchor point. This introduces preliminary length optimization based on the triangle inequality, while satisfying obstacle avoidance constraints, laying the foundation for generating shorter detour paths.

[0034] It's important to note that when selecting vertices, only those whose perpendiculars to the initial line segment fall between the two endpoints of the segment should be considered. This is because the core operation of the algorithm is to divide the sensitive area to be traversed into two parts on the left and right sides of the initial line segment. The "farthest vertex" calculated subsequently must belong to these two specific parts generated by the line segment. If the perpendicular from a vertex to the line segment falls on the extension of the line segment, then the geometric projection of this point exceeds the range of the path segment being processed, or it is a vertex in a region with a significant deviation from the direction of the current path segment. Including it in this stage of calculation would lead to the selection of an incorrectly oriented "farthest point," causing the generated detour path to deviate from the optimal direction and failing to converge to a compliant path.

[0035] In one embodiment, step S20 includes steps A10 to A40.

[0036] Step A10: Divide the first sensitive region according to the connection path to obtain multiple sub-regions.

[0037] In practice, the segmentation operation essentially divides the first sensitive region to be traversed into two sides, with the connecting path within it serving as the boundary. Each side contains one or more independent sub-regions. Then, for each sub-region, the vertical distance from all vertices within it to the connecting path is calculated, and the vertex furthest from the line containing the connecting path is selected as the candidate obstacle avoidance anchor point for that region. Next, using the starting wind turbine, each candidate obstacle avoidance anchor point, and the target wind turbine as key points, multiple corresponding candidate paths are sequentially connected, and the total length of each candidate path is calculated. Finally, the total lengths of all candidate paths are compared and sorted, and the candidate obstacle avoidance anchor point corresponding to the candidate path with the shortest total length is selected as the final obstacle avoidance anchor point.

[0038] In one embodiment, the first sensitive region is divided according to the connecting path to obtain multiple sub-regions, including: dividing the region vertices of the first sensitive region to both sides according to the straight line where the connecting path is located; grouping the region vertices located on the same side into the same set according to the distribution of the region vertices on both sides of the connecting path; and determining the closed polygon region of each vertex set and its connection relationship on the boundary of the sensitive region to obtain multiple sub-regions.

[0039] Step A20: Determine candidate obstacle avoidance anchor points based on the distance between the vertices of each region within the divided sub-region and the connecting path.

[0040] In practical implementation, for each sub-region defined in the aforementioned steps, the algorithm needs to traverse all vertices contained on the boundary of that sub-region and calculate the perpendicular distance from each vertex to the straight line containing the initial connecting path. After the calculation is completed, the distance values ​​calculated by all vertices in the region are compared, and the vertex with the largest distance value, i.e., the vertex furthest from the initial path straight line, is selected and marked as the candidate obstacle avoidance anchor point corresponding to that sub-region. If multiple vertices have the same distance and all are the largest, one can be randomly selected or determined according to preset rules (such as selecting the one with better coordinate position).

[0041] In one embodiment, determining candidate obstacle avoidance anchor points based on the distance between each region vertex and the connecting path within a sub-region includes: calculating the vertical distance from each region vertex to the connecting path based on the region vertices in the sub-region; determining candidate anchor points for the sub-region based on the vertical distance and the vertical intersection relationship between each region vertex and the connecting path; and summarizing the candidate anchor points of each sub-region to obtain candidate obstacle avoidance anchor points.

[0042] It should be noted that, under normal circumstances, the aforementioned segmentation method is a basic processing approach for sensitive regions with simple convex polygons or regular shapes. However, for certain sensitive regions with special shapes, such as concave regions or regions containing holes (i.e., not simple polygons), when a connecting path passes through them, the set of vertices on the same side of the path may not form a single connected region. In this case, regardless of whether the segmentation results in one or multiple sub-regions, the core logic remains unchanged. For each defined, connected sub-region, the algorithm independently calculates the perpendicular distance from all its internal vertices to the connecting path and selects the vertex with the farthest distance as the candidate obstacle avoidance anchor point for that region. In this way, even when facing sensitive regions with complex shapes, the algorithm can generate an effective candidate guiding point for each independent obstacle that needs to be bypassed, thus ensuring the universality and logical consistency of the path optimization process.

[0043] Step A30: Connect the starting wind turbine, candidate obstacle avoidance anchor points, and target wind turbine in sequence to form multiple candidate paths, and calculate the total length of each candidate path.

[0044] Understandably, the starting and target wind turbine positions are fixed endpoints, while each candidate obstacle avoidance anchor point represents a turning point that guides the path away from sensitive areas from a specific angle. Connecting these points sequentially constructs a series of polyline paths. Each polyline segment consisting of "starting point - anchor point - target point" is a complete candidate path. The economics of each path can be measured by calculating the total length of each polyline.

[0045] Step A40: Determine the obstacle avoidance anchor point based on the sorting results of the total length of the candidate paths.

[0046] Among all the polyline paths constructed from different candidate obstacle avoidance anchor points, the path with the shortest total length, that is, the path with the least raw material consumption and loss corresponding to the obstacle avoidance anchor point line under the premise of achieving effective obstacle avoidance.

[0047] It's important to note that in real-world planning scenarios, the initial connection path may often traverse multiple primary sensitive areas. Each traversed sensitive area generates a candidate obstacle avoidance anchor point on both sides. Therefore, if three sensitive areas are traversed, theoretically at least six candidate points will be generated. This step evaluates the total length of the multiple candidate paths formed by connecting all these candidate points to the starting and ending points respectively. By comparing the lengths of all these paths composed of anchor points on different sides, we select the anchor point on the side that minimizes the overall path length, taking a global perspective.

[0048] Step S30: Obtain the obstacle avoidance path based on the obstacle avoidance anchor point, and take the sensitive area traversed by the obstacle avoidance path as the second sensitive area.

[0049] By connecting the obstacle avoidance anchors to the wind turbines on both sides in the order of the sensitive areas they pass through, a preliminary obstacle avoidance path can be obtained. At this time, it is necessary to perform a check on the new path to see if it passes through sensitive areas, similar to the previous steps, and define the area passed through by the new path as the second sensitive area.

[0050] In one embodiment, an obstacle avoidance path is obtained based on the obstacle avoidance anchor point, and the sensitive area traversed by the obstacle avoidance path is designated as the second sensitive area. This includes: sequentially connecting the starting wind turbine, the obstacle avoidance anchor point, and the target wind turbine to obtain an obstacle avoidance path composed of several path segments; obtaining the path segments that are traversed and the corresponding sensitive areas based on the spatial positions of each path segment in the obstacle avoidance path and the sensitive areas corresponding to the path segments; and arranging the sensitive areas sequentially according to the connection order of the path segments to obtain the second sensitive area.

[0051] Understandably, the initial obstacle avoidance problem might not be completely solved by inserting anchor points in a single iteration due to the complexity of the obstacle shapes. By independently identifying newly discovered obstacle avoidance regions in each iteration as second sensitive regions, the algorithm decomposes a complex global obstacle avoidance problem into a series of simpler subproblems targeting local obstacles. Each iteration focuses on resolving the conflict between the current line segment and a specific region (the second sensitive region), thus transforming the planning of long detours into connecting multiple local shortest detours. This ensures that the algorithm can progressively and robustly handle irregularly shaped obstacles, ultimately synthesizing a globally feasible optimized path.

[0052] In practice, obtaining the obstacle avoidance path based on obstacle avoidance anchor points is an iterative optimization process. Once an obstacle avoidance anchor point is selected as the insertion point, the starting point, the anchor point, and the ending point are connected to form a new polyline path composed of two line segments. Subsequently, the system checks each sub-segment of this new path segment by segment to see if it still crosses a sensitive area. If a sub-segment, such as the segment from the starting point to the anchor point, is found to still cross a sensitive area, it will be automatically regarded as a new object to be optimized. Its starting and ending points are set as new path endpoints, and the sensitive area it currently crosses becomes the core obstacle to be addressed in the new iteration. This process is repeated, requiring the path to gradually bypass the various convex corners of the obstacle until a complete obstacle avoidance path composed of multiple ordered vertices is generated, and all line segments do not cross any sensitive areas. During this process, the most recently discovered sensitive area that is still crossed by line segments is dynamically marked and recorded as the second sensitive area in this iteration, becoming the target of the next round of optimization.

[0053] In a preferred embodiment, to balance the effectiveness and efficiency of the processing, on the one hand, the algorithm terminates naturally and outputs the final path when all line segments of the iteratively generated path do not cross any sensitive areas. On the other hand, to prevent infinite loops or excessively low efficiency due to extremely complex obstacle shapes, the system presets a maximum iteration limit. When the iteration count reaches this limit, even if the path still does not completely avoid all areas, the algorithm will directly generate a path around the area for each breakpoint based on the currently incompletely optimized path. For example, it can directly use the boundary of the crossed area as the current optimal path. This ensures that a complete solution can be obtained in most normal cases, while avoiding meaningless calculations in the face of special adversarial graphics, significantly improving the robustness and practicality of the algorithm in engineering applications.

[0054] Step S40: Based on the region vertices of the second sensitive region and the obstacle avoidance path, determine the obstacle avoidance optimization anchor point, and update the obstacle avoidance path using the obstacle avoidance optimization anchor point to obtain the global obstacle avoidance path.

[0055] Since the most severe crossing problem has been solved in the preceding steps, the newly generated path may still locally hug or slightly cross the edges of other regions. By marking the region traversed by each new path as the second sensitive region and specifically calculating and optimizing anchor points, the complex multi-obstacle detour problem can be transformed into a series of manageable optimization subproblems targeting individual local conflicts, thereby systematically approximating the overall optimal solution.

[0056] In practice, the logic is similar to that of selecting obstacle avoidance anchor points. This involves analyzing the positional relationship between local line segments and sensitive areas, and selecting the shortest vertex from the boundary of the traversed area that can guide the path around the obstacle. Once this vertex is obtained, it is inserted into the corresponding vertex sequence of the current path, replacing the original path segment that traversed the area. The system continues to perform this update operation until a complete planned path—a global obstacle avoidance path—is finally generated where no line segment from the starting point to the ending point traverses any sensitive area.

[0057] Understandably, after each path update, it is necessary to completely re-examine the intersection relationships of all line segments with all sensitive areas to prevent new detours from introducing additional crossings. At the same time, reasonable termination conditions should be set for the entire optimization loop; for example, the algorithm should automatically stop when several consecutive iterations fail to further shorten the total path length or completely eliminate all crossings.

[0058] In this embodiment, by using the direct connection path between the starting wind turbine and the target wind turbine, the first type of sensitive area directly traversed is first identified. Through geometric segmentation and global distance comparison, a single optimal obstacle avoidance anchor point is selected to construct the initial obstacle avoidance path. Subsequently, the area traversed by the new path is iteratively regarded as the second type of sensitive area. By introducing local optimization anchor points, segmented obstacle avoidance and path fine-tuning are performed for each newly traversed area. Finally, a feasible route is generated that satisfies the obstacle avoidance constraints on a global scale and tries to get as close as possible to the shortest distance.

[0059] In summary, this technical solution, through the aforementioned phased processing method, ensures complete avoidance of sensitive areas, laying the foundation for path safety. The introduction of a global comparison based on the total path length during the selection of obstacle avoidance anchor points naturally guides to a more economical detour direction while meeting hard constraints. The subsequent iterative optimization mechanism decomposes the detour problem of complex nonlinear obstacles into a series of solvable local linear optimizations. This not only ensures the algorithm can effectively handle irregularly shaped obstacle groups but also avoids excessive path redundancy, achieving effective control of the total path length and significantly improving the engineering practicality and economy of the planning results.

[0060] Based on the first embodiment of the present invention, in the second embodiment of the present invention, the content that is the same as or similar to that in the first embodiment can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 In the power line path planning method, step S40 includes steps S401 to S405: Step S401: Traverse the vertices of the second sensitive region and divide the vertices of the region according to the corresponding path segments to obtain the subset of the vertices of the region corresponding to each path segment.

[0061] In practice, when one or more segments of the obstacle avoidance path cross a secondary sensitive area, it means that it is necessary to accurately identify which specific path segment and which areas constitute a spatial crossing relationship. Therefore, the system will check each crossed area and its corresponding polyline segment one by one.

[0062] Step S402: Determine the vertical distance from each region vertex to the path segment based on the spatial relationship between the region vertex subset and the target path segment.

[0063] In each line segment corresponding to the second sensitive region, the perpendicular distance and projected position from each vertex within this sensitive region to the corresponding line segment are calculated. If the foot of the perpendicular from a vertex falls between the two endpoints of a line segment, then that vertex is assigned to the threat set represented by that path segment. In this way, the complex obstacle constraints that originally covered the entire path are transformed into a series of clear and definite local optimization problems, that is, each specific path segment corresponds to a set of specific region vertices that need to be avoided.

[0064] Understandably, the core purpose of this step is to discretize the continuous two-dimensional obstacle region and establish a one-to-one correspondence with discrete path segments. Since the obstacle avoidance path is composed of ordered line segments, and the boundaries of the sensitive area are defined by ordered vertices, the geometric relationship of interference between the two can be accurately projected onto each line segment and its neighboring boundary vertices. The distance-based algorithm can automatically filter out those local obstacle points that truly pose a "close-range challenge" to a certain section of the path, rather than blindly associating all vertices of the entire region with the entire path. This method significantly reduces the complexity of the problem, allowing the algorithm to focus on the most critical conflict points for local correction, thereby maintaining the smoothness of the original path and the global planning intent to the greatest extent while ensuring obstacle avoidance effectiveness.

[0065] Step S403: Determine the obstacle avoidance optimization anchor point corresponding to the path segment based on the vertical distance to the vertices of each region.

[0066] Understandably, for each path segment requiring optimization and its corresponding subset of vertices, the system directly selects the vertex in the subset with the smallest perpendicular distance to the original path segment, as this point represents the most direct intrusion threat. The selected vertex is then designated as the "obstacle avoidance optimization anchor point" for this path segment. Geometrically, this anchor point is the most obstructive convex point on the obstacle boundary, hindering the current path from moving straight; it is a critical turning point that the path must detour around.

[0067] Step S404: Insert each obstacle avoidance optimization anchor point into the two endpoints of the corresponding path segment in the order of their connection in the obstacle avoidance path, so as to generate a local obstacle avoidance path that bypasses the boundary of the second sensitive area.

[0068] In this step, the system performs local path reconstruction. For each original path segment with an obstacle avoidance optimization anchor point, the algorithm calculates the precise positional relationship of that anchor point relative to the segment. The system then inserts the optimization anchor point sequentially between the two endpoints of the segment. As a result, the original local straight line segment is replaced with a two-segment polyline containing the anchor point. This operation ensures that the newly generated local path actively bulges outward, bypassing previously threatening vertices, thus locally eliminating the problem of intersection with the boundary of the second sensitive region. After all segments are processed in this way, a local obstacle avoidance path is generated that smoothly and accurately fits and bypasses the boundary of the second sensitive region.

[0069] Step S405: Replace the local obstacle avoidance path with the corresponding path segments in the obstacle avoidance path to obtain the global obstacle avoidance path.

[0070] After multiple iterations, a complete obstacle avoidance path is obtained when all the original path segments related to the second sensitive area are replaced by the calculated local obstacle avoidance path segments (i.e., the polyline segments after the anchor points are inserted).

[0071] This embodiment calculates and assigns each vertex on the boundary of the sensitive area to its nearest conflict path segment, establishing a precise local correspondence. Then, the most threatening obstacle vertex is selected as a key anchor point for each path segment. Subsequently, these anchor points are sequentially inserted into the corresponding original path segments to construct a local path that smoothly bypasses the obstacle boundary. Finally, the generated local path replaces the original conflict segments, thus forming a global obstacle avoidance path.

[0072] In summary, this embodiment decomposes the conflict between the overall path and complex obstacle areas into discrete local conflicts between line segments and specific vertices through geometric relationships, and achieves local path reshaping by inserting key anchor points. This eliminates the need for significant adjustments to the global path. Therefore, this method achieves accurate obstacle avoidance with minimal changes to the original path, effectively maintaining the initial planning intent and smoothness of the global path, while significantly reducing computational complexity and improving planning efficiency.

[0073] The above examples are only for understanding this application and do not constitute a limitation on the current collector line path planning method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0074] This application also provides a power line path planning device. Please refer to... Figure 3 The power line path planning device includes: The path planning module 10 is used to obtain the connection path between the starting wind turbine and the target wind turbine, and to take the sensitive area traversed by the connection path as the first sensitive area. The path planning module 10 is further configured to determine obstacle avoidance anchor points based on the regional vertices of the first sensitive area and the connecting path. The path optimization module 20 is used to obtain an obstacle avoidance path based on the obstacle avoidance anchor point, and to use the sensitive area traversed by the obstacle avoidance path as a second sensitive area. The path optimization module 20 is further configured to determine an obstacle avoidance optimization anchor point based on the region vertices of the second sensitive region and the obstacle avoidance path, and update the obstacle avoidance path using the obstacle avoidance optimization anchor point to obtain a global obstacle avoidance path.

[0075] In one embodiment, the path planning module 10 is further configured to: segment the first sensitive region according to the connecting path to obtain multiple sub-regions; determine candidate obstacle avoidance anchor points according to the distance between the vertices of each sub-region and the connecting path; connect the starting wind turbine, the candidate obstacle avoidance anchor points, and the target wind turbine in sequence to form multiple candidate paths, and calculate the total length of each candidate path; and determine the obstacle avoidance anchor points according to the sorting result of the total length of the candidate paths.

[0076] In one embodiment, the path planning module 10 is further configured to divide the vertices of the first sensitive region to both sides according to the straight line where the connecting path is located; to group the vertices of the region located on the same side into the same set according to the distribution of the vertices of the region on both sides of the connecting path; and to determine the respective closed polygon regions according to each vertex set and its connection relationship on the boundary of the sensitive region, thereby obtaining the plurality of sub-regions.

[0077] In one embodiment, the path planning module 10 is further configured to calculate the vertical distance from each region vertex to the connecting path based on the region vertices on the divided sub-regions; determine the candidate anchor points of the divided sub-regions based on the vertical distances and the vertical intersection relationship between each region vertex and the connecting path; and summarize the candidate anchor points of each divided sub-region to obtain the candidate obstacle avoidance anchor points.

[0078] In one embodiment, the path planning module 10 is further configured to sequentially connect the starting wind turbine, the obstacle avoidance anchor point, and the target wind turbine to obtain an obstacle avoidance path composed of several path segments; based on the spatial position of each path segment in the obstacle avoidance path and the sensitive area, obtain the path segment that is crossed and the sensitive area corresponding to the path segment; and arrange the sensitive areas sequentially according to the connection order of the path segments to obtain the second sensitive area.

[0079] In one embodiment, the path optimization module 20 is further configured to sequentially connect the starting wind turbine, the obstacle avoidance anchor point, and the target wind turbine to obtain an obstacle avoidance path composed of several path segments; based on the spatial position of each path segment in the obstacle avoidance path and the sensitive area, obtain the path segment that is crossed and the sensitive area corresponding to the path segment; and arrange the sensitive areas sequentially according to the connection order of the path segments to obtain the second sensitive area.

[0080] In one embodiment, the path optimization module 20 is further configured to traverse the vertices of the second sensitive region and divide the vertices into subsets of vertices corresponding to the path segments to obtain subsets of vertices corresponding to each path segment; determine the vertical distance from each vertices to the path segments based on the spatial relationship between the subsets of vertices and the target path segments; determine the obstacle avoidance optimization anchor points corresponding to the path segments based on the vertical distances corresponding to each vertices; insert each obstacle avoidance optimization anchor point sequentially between the two endpoints of the corresponding path segments according to the connection order of their corresponding path segments in the obstacle avoidance path to generate a local obstacle avoidance path that bypasses the boundary of the second sensitive region; and replace the corresponding path segments in the obstacle avoidance path with the local obstacle avoidance path to obtain the global obstacle avoidance path.

[0081] The power line path planning device provided in this application, employing the power line path planning method described in the above embodiments, can solve the technical problem of how to avoid sensitive areas during power line planning. Compared with the prior art, the beneficial effects of the power line path planning device provided in this application are the same as those of the power line path planning method provided in the above embodiments, and other technical features in the power line path planning device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0082] This application provides a power line path planning device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the power line path planning method in the first embodiment described above.

[0083] The following is for reference. Figure 4The diagram illustrates a structural schematic of a collector line path planning device suitable for implementing embodiments of this application. The collector line path planning device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 4 The illustrated collector line path planning device is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0084] like Figure 4 As shown, the collector path planning device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.) that can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the collector path planning device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the collector line path planning device to communicate wirelessly or wiredly with other devices to exchange data. Although the figure shows collector line path planning devices with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0085] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0086] The power line path planning device provided in this application, employing the power line path planning method in the above embodiments, can solve the technical problem of how to avoid sensitive areas during the power line planning process. Compared with the prior art, the beneficial effects of the power line path planning device provided in this application are the same as those of the power line path planning method provided in the above embodiments, and other technical features of this power line path planning device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0087] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0088] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0089] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the collector line path planning method in the above embodiments.

[0090] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0091] The aforementioned computer-readable storage medium may be included in the collector line path planning device; or it may exist independently and not be assembled into the collector line path planning device.

[0092] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the power line path planning device, the power line path planning device: acquires the connection path between the starting wind turbine and the target wind turbine, and designates the sensitive area traversed by the connection path as a first sensitive area; determines obstacle avoidance anchor points based on the region vertices of the first sensitive area and the connection path; obtains an obstacle avoidance path based on the obstacle avoidance anchor points, and designates the sensitive area traversed by the obstacle avoidance path as a second sensitive area; determines an obstacle avoidance optimization anchor point based on the region vertices of the second sensitive area and the obstacle avoidance path, and updates the obstacle avoidance path using the obstacle avoidance optimization anchor point to obtain a global obstacle avoidance path.

[0093] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via an Internet service provider through an Internet connection).

[0094] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0095] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0096] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described power line path planning method, which can solve the technical problem of how to avoid sensitive areas during power line planning. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the power line path planning method provided in the above embodiments, and will not be repeated here.

[0097] The computer program product provided in this application can solve the technical problem of collector line path planning. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the collector line path planning method provided in the above embodiments, and will not be repeated here.

[0098] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application through the content of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for planning the path of a power collection line, characterized in that, The power collection line path planning method includes: Obtain the connection path between the starting fan and the target fan, and designate the sensitive area traversed by the connection path as the first sensitive area; Based on the regional vertices of the first sensitive area and the connecting path, determine the obstacle avoidance anchor point; Based on the obstacle avoidance anchor points, an obstacle avoidance path is obtained, and the sensitive area traversed by the obstacle avoidance path is designated as the second sensitive area. Based on the region vertices of the second sensitive region and the obstacle avoidance path, an obstacle avoidance optimization anchor point is determined, and the obstacle avoidance optimization anchor point updates the obstacle avoidance path to obtain a global obstacle avoidance path.

2. The method for planning the path of a power collection line according to claim 1, characterized in that, The step of determining obstacle avoidance anchor points based on the region vertices of the first sensitive region and the connecting path includes: The first sensitive region is segmented according to the connection path to obtain multiple sub-regions; Candidate obstacle avoidance anchor points are determined based on the distance between the vertices of each of the divided sub-regions and the connecting path. The starting wind turbine, the candidate obstacle avoidance anchor point, and the target wind turbine are connected in sequence to form multiple candidate paths, and the total length of each candidate path is calculated. The obstacle avoidance anchor point is determined based on the sorting result of the total length of the candidate paths.

3. The method for planning the path of a power collection line according to claim 2, characterized in that, The first sensitive region is segmented according to the connection path to obtain multiple sub-regions, including: Based on the straight line of the connecting path, the vertices of the first sensitive region are divided to both sides; Based on the distribution of the vertices of the region on both sides of the connecting path, the vertices of the region located on the same side are grouped into the same set; Based on each vertex set and its connection relationship on the boundary of the sensitive region, the respective closed polygon regions are determined, resulting in the multiple sub-regions.

4. The method for planning the path of a power collection line according to claim 2, characterized in that, The step of determining candidate obstacle avoidance anchor points based on the distance between the vertices of each of the divided sub-regions and the connecting path includes: Based on the vertices of the divided sub-regions, calculate the vertical distance from each region vertex to the connecting path; Based on the vertical distance and the vertical intersection relationship between the vertices of each region and the connecting path, the candidate anchor points for dividing the sub-regions are determined; The candidate anchor points of each sub-region are summarized to obtain the candidate obstacle avoidance anchor points.

5. The method for planning the path of a power collection line according to claim 1, characterized in that, The step of obtaining an obstacle avoidance path based on the obstacle avoidance anchor point and designating the sensitive area traversed by the obstacle avoidance path as a second sensitive area includes: By sequentially connecting the starting fan, obstacle avoidance anchor point and target fan, an obstacle avoidance path composed of several path segments is obtained. Based on the spatial position of each path segment in the obstacle avoidance path and the sensitive area, the path segment that was crossed and the sensitive area corresponding to the path segment are obtained. The sensitive regions are arranged sequentially according to the connection order of the path segments to obtain the second sensitive region.

6. The method for planning the path of a power collection line according to claim 1, characterized in that, The step of determining obstacle avoidance optimization anchor points based on the region vertices of the second sensitive region and the obstacle avoidance path, and updating the obstacle avoidance path using the obstacle avoidance optimization anchor points to obtain a global obstacle avoidance path, includes: Traverse the vertices of the second sensitive region and divide the vertices of the region according to the corresponding path segments to obtain the subset of vertices of the region corresponding to each path segment; Based on the spatial relationship between the subset of region vertices and the target path segment, determine the vertical distance from each region vertex to the path segment; Based on the vertical distances corresponding to the vertices of each region, the obstacle avoidance optimization anchor points corresponding to the path segments are determined; Each obstacle avoidance optimization anchor point is inserted sequentially between the two endpoints of the corresponding path segment in the obstacle avoidance path according to the connection order of its corresponding path segment in the obstacle avoidance path, so as to generate a local obstacle avoidance path that bypasses the boundary of the second sensitive area. The local obstacle avoidance path is replaced with the corresponding path segment in the obstacle avoidance path to obtain the global obstacle avoidance path.

7. A power line path planning device, characterized in that, The power collection line path planning device includes: The path planning module is used to obtain the connection path between the starting wind turbine and the target wind turbine, and to use the sensitive area traversed by the connection path as the first sensitive area. The path planning module is also used to determine obstacle avoidance anchor points based on the regional vertices of the first sensitive area and the connecting path; The path optimization module is used to obtain an obstacle avoidance path based on the obstacle avoidance anchor points, and to use the sensitive area traversed by the obstacle avoidance path as a second sensitive area. The path optimization module is further configured to determine obstacle avoidance optimization anchor points based on the region vertices of the second sensitive region and the obstacle avoidance path, and update the obstacle avoidance path using the obstacle avoidance optimization anchor points to obtain a global obstacle avoidance path.

8. A power line path planning device, characterized in that, The collector line path planning device includes: a memory, a processor, and a collector line path planning program stored in the memory and executable on the processor, the collector line path planning program being configured to implement the collector line path planning method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium stores a collector line path planning program, which, when executed by a processor, implements the collector line path planning method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the collector line path planning method as described in any one of claims 1 to 6.

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