Photovoltaic string construction positioning method and system

Abstract

The application provides a photovoltaic string construction positioning method and system, comprising the following steps: constructing a construction progress model based on obtained point cloud data of a photovoltaic string; constructing a photovoltaic string planning optimization model based on obtained infrastructure planning data of the photovoltaic string; and finely comparing the construction progress model and the photovoltaic string planning optimization model to position the construction progress of the photovoltaic string. The method can accurately position the construction progress of the photovoltaic string, simplifies the construction positioning process, reduces the dependence on manual measurement, and improves work efficiency. Meanwhile, since a digital comparison method is adopted, the evaluation of the construction progress is more objective and accurate, and the interference of human factors is reduced.

Description

Technical Field

[0001] This invention belongs to the field of photovoltaic power generation technology, specifically to a method and system for the construction and positioning of photovoltaic strings. Background Technology

[0002] With increasing emphasis on renewable energy, the photovoltaic industry is developing rapidly, leading to a continuous expansion in the scale of photovoltaic power plant construction. Simultaneously, the construction of photovoltaic power plants places higher demands on the precision and efficiency of photovoltaic strings. Due to the wide applicability of photovoltaic power generation, its lack of geographical limitations, and the complex and varied construction environment of photovoltaic power plants (such as undulating terrain and varying sunlight conditions), the installation of photovoltaic modules in photovoltaic power plants is characterized by a wide range and dispersed locations, posing significant challenges to the positioning of photovoltaic strings during construction. Currently, during the construction of photovoltaic power plants, the positioning of photovoltaic strings is often assessed on-site by supervisors. While this method can achieve the positioning of photovoltaic strings, in a photovoltaic power plant construction site, multiple photovoltaic strings are constructed simultaneously. Supervisors typically need to be physically present on-site to supervise and assess each string individually. Although this method can achieve the positioning of multiple strings, it places a heavy workload on supervisors. Completing the positioning of all photovoltaic strings in a power plant is time-consuming and inefficient. Furthermore, the positioning of each photovoltaic string needs to be recorded individually, resulting in a large amount of data. Errors or distractions during recording can easily lead to inaccurate data, affecting the supervision of the photovoltaic strings and requiring supervisors to spend time rechecking the data. This is time-consuming and inefficient in monitoring and assessing construction progress. Summary of the Invention

[0003] To address the problem of time-consuming, labor-intensive, and large-scale manual supervision and evaluation of the construction positioning of multiple photovoltaic strings in existing photovoltaic modules, this invention provides a photovoltaic string construction positioning method and system.

[0004] To achieve the above objectives, the present invention provides the following technical solution: This invention proposes a method for positioning photovoltaic strings during construction, comprising the following steps: A construction progress model is constructed based on the point cloud data of the acquired photovoltaic strings; An optimal planning model for photovoltaic strings is constructed based on the infrastructure planning data obtained from the photovoltaic strings. The construction progress model is compared with the optimal planning model for the photovoltaic string to determine the construction progress of the photovoltaic string.

[0005] Preferably, the construction progress model based on the acquired point cloud data of the photovoltaic strings includes: Point cloud image data of the photovoltaic string construction site were obtained based on UAV laser scanning; The point cloud image data is preprocessed to obtain preprocessed point cloud data; The point cloud preprocessing data is sorted based on the construction time sequence to obtain time-sorted point cloud data; A construction progress model is constructed based on the time-sorted point cloud data.

[0006] Preferably, the point cloud image data of the photovoltaic string construction site obtained based on UAV laser scanning includes: Obtain the initial construction location and current construction location of the photovoltaic power station; The initial construction location of the photovoltaic power station is set as the initial image acquisition location, and the current construction location is set as the end location of UAV image acquisition. Multiple UAV flight paths are planned. The drone is controlled to fly along multiple drone flight paths to scan the photovoltaic string construction site and obtain the point cloud image data.

[0007] Preferably, the point cloud preprocessing data is sorted based on the construction time sequence to obtain time-sorted point cloud data, including: Obtain the construction timing information corresponding to the point cloud preprocessed data of each photovoltaic string group; Based on the aforementioned construction sequence information, a timeline framework is established; The point cloud preprocessed data is encoded based on the construction time sequence information; The encoded point cloud preprocessed data is arranged in chronological order within a time-series framework to obtain time-sorted point cloud data.

[0008] Preferably, the construction progress model based on the time-sorted point cloud data includes: Extract the temporal order from the time-sorted point cloud data; The modeling order of the current photovoltaic string is planned based on the aforementioned time sequence; Based on the current modeling order of the photovoltaic strings, the number of components installed in each photovoltaic string, the location of each photovoltaic string in the photovoltaic power station, and the starting construction location of each photovoltaic string in the time-sorted point cloud data are sequentially input into the basic model of the photovoltaic power station based on the terrain area where the photovoltaic power station is located, and multiple photovoltaic string point cloud models are constructed. The construction progress model is fitted by fitting multiple photovoltaic string point cloud models.

[0009] Preferably, the step of constructing an optimal photovoltaic string planning model based on the acquired infrastructure planning data includes: Obtain topographic data of the photovoltaic power station construction area and planning data for each photovoltaic string to obtain infrastructure planning data; Extract the planned construction time of all the photovoltaic string data to obtain the planned construction start time dataset; Arrange the planned construction start times in the dataset according to their chronological order to obtain a time sequence code; Based on the aforementioned time-series coding, each group of photovoltaic string data is independently coded to obtain the planned construction schedule data; A schedule sub-model is constructed based on the planned schedule data. All the aforementioned schedule sub-models are fitted sequentially according to the order of the time sequence codes to obtain the fitted planning model; The photovoltaic string planning data is input into the corresponding photovoltaic string construction area location in the fitted planning model to obtain the photovoltaic string planning model; The completed photovoltaic string data corresponding to the historical planning data is input into the fitted planning model for optimization, thereby obtaining the optimal photovoltaic string planning model.

[0010] Preferably, the step of constructing a schedule sub-model based on the planned schedule data includes: A site map of the construction site is determined in advance, and the site map is imported into the engineering simulation model to conduct engineering item analysis and determine the data of the planned engineering items; The planned project item data is matched with the planned construction period data to generate multi-dimensional construction tasks, and the construction period sub-model is constructed based on the multi-dimensional construction tasks.

[0011] Preferably, the detailed comparison between the construction progress model and the optimal photovoltaic string planning model includes: By comparing the construction progress model with the optimal photovoltaic string planning model, the overlapping and non-overlapping areas of the construction progress model and the optimal photovoltaic string planning model are obtained. The overlapping areas are marked as areas that have been completed, and the non-overlapping areas are marked as areas that have not been completed. Based on the photovoltaic string planning data, areas that have not been installed on the current day are marked; All marked areas are collected and displayed to determine the construction progress of the photovoltaic string.

[0012] Preferably, the photovoltaic string planning data includes the planned number of components to be installed, the planned installation parameters of the components, and the planned construction time; wherein, the planned installation parameters of the components include the installation angle, the installation position, and the installation height; and the planned construction time includes the planned construction start time and the planned construction end time.

[0013] The present invention also proposes a photovoltaic string construction positioning system for implementing the above method, the system comprising: a first model construction module, a second model construction module, and a comparison positioning module; The first model building module is used to build a construction progress model based on the point cloud data of the acquired photovoltaic strings. The second model building module is used to build an optimal planning model for photovoltaic strings based on the infrastructure planning data of the acquired photovoltaic strings; The comparison and positioning module is used to make a detailed comparison between the construction progress model and the optimal photovoltaic string planning model to locate the construction progress of the photovoltaic string.

[0014] Compared with the prior art, the present invention has the following beneficial technical effects: This invention proposes a method for locating photovoltaic (PV) strings during construction. This method constructs a construction progress model using point cloud data of the PV strings. Leveraging the high precision and three-dimensional characteristics of point cloud data, it accurately and intuitively reflects the current construction status of the PV strings. Based on the infrastructure planning data of the PV strings, an optimal planning model for the PV strings is further constructed, providing a clear standard for comparing construction progress. By comparing the construction progress model with the optimal planning model, the construction progress of the PV strings can be accurately located, simplifying the construction location process, reducing reliance on manual measurement, and improving work efficiency. Furthermore, the use of a digital comparison method makes the assessment of construction progress more objective and accurate, reducing interference from human factors.

[0015] Furthermore, this method employs UAV laser scanning technology to acquire point cloud image data of the photovoltaic string construction site, improving the efficiency and accuracy of data acquisition while ensuring the comprehensiveness and real-time nature of the data. By preprocessing the point cloud image data, noise and redundant information are effectively removed. The preprocessed point cloud data is then sorted according to the construction sequence to obtain time-sorted point cloud data. This allows the construction progress model to clearly reflect the temporal changes and spatial distribution during the photovoltaic string construction process. The construction progress model constructed based on the time-sorted point cloud data can intuitively display the construction progress and status of the photovoltaic string, improving construction efficiency and quality while reducing construction costs.

[0016] Furthermore, this method first clarifies the initial construction location and current construction location of the photovoltaic power station, providing precise target guidance for the UAV's flight path planning. By setting the initial construction location as the initial image acquisition location and the current construction location as the end location for UAV image acquisition, and planning multiple UAV flight paths, it ensures that the UAV can comprehensively and without omission scan the entire photovoltaic string construction site. By controlling the UAV to fly along the planned flight path, scanning the photovoltaic string construction site, high-precision point cloud image data is obtained, reflecting the actual situation of the construction site. This not only improves the efficiency and accuracy of point cloud image data acquisition, but also ensures the integrity and reliability of the data.

[0017] Furthermore, this method provides an accurate time reference for subsequent sorting by precisely acquiring the construction time sequence information corresponding to the point cloud preprocessing data of each photovoltaic string. Then, a time sequence framework is established, providing a clear structure and logic for the sorting of point cloud data. Encoding the point cloud preprocessing data not only ensures the uniqueness and traceability of the data, but also facilitates subsequent data processing and analysis. The encoded point cloud preprocessing data is arranged in chronological order within the time sequence framework to obtain time-sorted point cloud data. This not only improves the processing efficiency and accuracy of point cloud data, but also enables the construction progress model to more intuitively reflect the temporal changes and spatial distribution during the construction process of the photovoltaic strings, thereby improving the accuracy of positioning construction.

[0018] Furthermore, this method provides a clear timeline for planning the modeling sequence of photovoltaic (PV) strings by using the temporal order of point cloud data. Based on this temporal order, the modeling sequence of the current PV strings is planned, ensuring that the construction progress model can be built according to the actual construction process. Key information from the temporal point cloud data, including the number of components installed in each PV string, the location of each PV string in the PV power station, and the starting construction location of each PV string, is input into the basic model of the PV power station based on the terrain of the PV power station. Multiple PV string point cloud models are successfully constructed, reflecting the actual installation of the PV strings and their specific locations in the terrain. The multiple PV string point cloud models are then fitted into a construction progress model, which can intuitively display the overall construction progress of the PV power station and the specific construction status of each PV string.

[0019] Furthermore, this method independently encodes each set of photovoltaic (PV) string data based on time-series coding to obtain planned construction schedule data. This data not only reflects the construction progress of the PV strings but also closely links it to their position and time nodes in the overall construction. Based on the planned construction schedule data, sub-models of the construction schedule are constructed. These sub-models respectively demonstrate the construction status of the PV strings in different time periods. All the sub-models of the construction schedule are fitted sequentially according to the order of the time-series coding to obtain a fitted planning model. This model initially demonstrates the overall planning and schedule of the PV power plant construction. By inputting the PV string planning data into the corresponding PV string construction area location in the fitted planning model, a PV string planning model is obtained, which refines the specific location and layout of the PV strings in the power plant. To obtain a more accurate and optimized model, the data of completed PV strings corresponding to historical planning data are obtained and input into the fitted planning model for optimization. This not only considers theoretical planning but also combines actual construction experience and data, thus obtaining the optimal PV string planning model. This makes the final positioning of PV string construction more accurate.

[0020] Furthermore, this method determines the site map of the construction site and imports it into the engineering simulation model for project item analysis, thereby identifying the planned project item data, improving the accuracy of construction positioning, and ensuring a high degree of consistency between the model and the actual situation. It matches the planned project item data with the planned construction schedule data, generating multi-dimensional construction tasks that not only cover construction time nodes and schedule requirements but also involve specific construction content and quality requirements. Based on these multi-dimensional construction tasks, a construction schedule sub-model is successfully constructed. This model can intuitively display the progress and status of each stage in the construction of the photovoltaic power station. Then, the overlapping and non-overlapping areas of the two models are identified and marked as currently completed and currently uncompleted areas, respectively, making the monitoring and management of construction progress more intuitive and clear. Simultaneously, based on the photovoltaic string planning data, areas that were not installed on the current day are marked, further refining the positioning of the construction progress. By aggregating and displaying all marked areas, the precise positioning of the photovoltaic string construction progress is achieved.

[0021] This invention also proposes a photovoltaic string construction positioning system. This system integrates a first model construction module, a second model construction module, and a comparison and positioning module to achieve precise positioning and monitoring of the photovoltaic string construction progress. The first model construction module can efficiently construct a construction progress model based on the acquired photovoltaic string point cloud data, reflecting the progress of the construction site in real time. The second model construction module utilizes infrastructure planning data to construct the optimal photovoltaic string planning model, providing a theoretically optimal solution for construction. The comparison and positioning module performs a detailed comparison of the two models, accurately identifying completed and uncompleted construction areas, as well as areas not yet installed on the current day, achieving precise control over the construction progress. This system not only improves the efficiency and accuracy of construction management but also helps optimize resource allocation, reduce construction costs, and improve overall construction progress and quality. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating a photovoltaic string construction positioning method proposed in this invention. Figure 2 This is a connection diagram of a photovoltaic string construction positioning system proposed in this invention. Detailed Implementation

[0023] In the following description, only certain exemplary embodiments are briefly described. As those skilled in the art will recognize, the described embodiments can be modified in various ways without departing from the spirit or scope of the invention. Therefore, the drawings and description are considered to be exemplary in nature and not restrictive.

[0024] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0025] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0026] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection, an electrical connection, or a communication connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0027] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0028] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0029] See Figure 1 This invention discloses a method for positioning photovoltaic strings during construction, comprising the following steps: A construction progress model is constructed based on the point cloud data of the acquired photovoltaic strings; Specifically, point cloud image data of the photovoltaic string construction site were obtained based on UAV laser scanning; Control the drone to fly above the photovoltaic power station under construction to obtain the initial construction location and the current construction location of the photovoltaic power station. Set the initial construction location of the photovoltaic power station as the initial image acquisition location of the drone and set the current construction location as the end image acquisition location of the drone. Plan multiple drone flight paths. After the drone completes the flight along multiple drone flight paths, it can obtain point cloud image data of the same photovoltaic string from different perspectives. The drone is controlled to fly along multiple drone flight paths. The laser scanning equipment on the drone is used to scan the construction site of the photovoltaic string, and to obtain point cloud image data of the number of components installed in each photovoltaic string, the location of each photovoltaic string in the photovoltaic power station, and the starting construction location of each photovoltaic string. In this step, a device with data processing capabilities, such as an onboard computer of a drone, can be used as the main body for point cloud image acquisition. In this embodiment, based on existing data such as site information and construction drawings of the photovoltaic power station, a reasonable flight path is pre-set in the onboard computer of the drone to ensure that the drone's flight range covers the entire photovoltaic power station. This ensures that the drone's lidar can comprehensively and accurately acquire all point cloud images of the photovoltaic power station, which facilitates the subsequent accurate selection of point cloud image data for the number of components installed in each photovoltaic string, the location of each photovoltaic string in the photovoltaic power station, and the starting construction location of each photovoltaic string, thereby improving the accuracy of infrastructure progress survey.

[0030] Preprocessing is performed on the point cloud image data to obtain preprocessed point cloud data; Specifically, point cloud image data of the same set of photovoltaic strings collected along different flight paths are input into an adversarial network for processing to obtain point cloud data. Then, a filtering algorithm is used to remove random noise points generated during the scanning process. These noise points may be caused by equipment errors, environmental factors, or interference during the scanning process, thereby improving the purity and accuracy of the point cloud data and obtaining denoised data. The denoised data is then smoothed to reduce fluctuations and unevenness in the data. Finally, point cloud data collected under different preset paths are merged into a single dataset to ensure the comprehensiveness of the merged dataset, resulting in preprocessed point cloud data.

[0031] The point cloud preprocessing data is sorted based on the construction time sequence to obtain time-sorted point cloud data; Specifically, the construction time sequence information corresponding to the point cloud preprocessing data of each group of photovoltaic strings is obtained. The construction time sequence information includes construction logs and timestamps, and records the start time of the construction phase of each group of photovoltaic strings. Based on the collected construction time sequence information, a time sequence framework is established. Each point cloud preprocessing data is encoded based on construction logs, timestamps, and progress reports; then the encoded point cloud preprocessing data is arranged in chronological order within a time-series framework to obtain time-sorted point cloud data.

[0032] A construction progress model was constructed based on time-sorted point cloud data; Specifically, the time sequence is extracted from the time-sorted point cloud data. Based on the time sequence, the modeling order of the current photovoltaic strings is planned. According to the current modeling order of the photovoltaic strings, the number of components installed in each photovoltaic string, the location of each photovoltaic string in the photovoltaic power station, and the starting construction location of each photovoltaic string are input into the basic model of the photovoltaic power station based on the terrain of the photovoltaic power station, thereby constructing multiple photovoltaic string point cloud models. The multiple photovoltaic string point cloud models are then fitted into a construction progress model.

[0033] An optimal planning model for photovoltaic strings is constructed based on the infrastructure planning data obtained from the photovoltaic strings. Specifically, topographic data of the photovoltaic power station construction area and planning data for each photovoltaic string are obtained to obtain infrastructure planning data; among which, the planning data for each photovoltaic string includes the planned number of components to be installed, the planned installation parameters of the components (installation angle, installation position and installation height) and the planned construction time (planned construction start time and planned construction end time). Extract the planned construction time of all photovoltaic string data, that is, extract the planned construction start time of each photovoltaic string data group within the planned construction time to obtain the planned construction start time dataset. Arrange the planned construction start times in the planned construction start time dataset in chronological order to obtain the time sequence code. Based on the time sequence code, encode each photovoltaic string data group independently to obtain the planned construction period progress data. A schedule sub-model was constructed based on the planned schedule data. Pre-determine the site map of the construction site, import the site map into the engineering simulation model, conduct engineering item analysis, and determine the data of the planned engineering items; The planned project data is matched with the planned construction period data to generate multi-dimensional construction tasks. Based on the multi-dimensional construction tasks, a construction period sub-model is constructed. In practical implementation, this application pre-determines a site map of the construction site, which can be obtained through on-site surveying. Then, the site map is imported into the engineering simulation model for project item analysis, which determines planned project item data, such as quantities, duration, and budget. Next, the planned project item data is matched with the planned duration data to generate multi-dimensional construction tasks, and additional item prediction processing is performed on these tasks. By determining whether additional project items exist, the multi-dimensional construction tasks can be updated as needed. After generating the multi-dimensional construction tasks, a schedule sub-model is constructed based on these tasks. The schedule sub-model can determine the specific start and end times of each task, thereby better managing the project schedule.

[0034] All the schedule sub-models are fitted sequentially according to the order of their time codes to obtain the fitted planning model; The number of components to be installed, the installation parameters (installation angle, installation position and installation height) and the construction time (planned construction start time and planned construction end time) in each set of photovoltaic string planning data are input into the corresponding photovoltaic string construction area location in the fitted planning model to obtain the photovoltaic string planning model; The completed photovoltaic string data corresponding to the historical planning data is input into the fitted planning model for optimization, and the optimal photovoltaic string planning model is obtained. Historical planning data of photovoltaic power plants is obtained, that is, data of photovoltaic strings that have been built in this photovoltaic power plant and have passed multiple manual inspections. The photovoltaic string data is then input into the area corresponding to the photovoltaic string planning model for matching simulation to obtain the optimal photovoltaic string planning model.

[0035] A detailed comparison is made between the construction progress model and the optimal photovoltaic string planning model to determine the construction progress of the photovoltaic string. Specifically, the construction progress model is compared with the optimal photovoltaic string planning model. The overlapping and non-overlapping areas in the construction progress model and the optimal photovoltaic string planning model are marked respectively. The marked overlapping areas are the areas that have been completed, and the non-overlapping areas are the areas that have not been constructed. The areas that have not been installed on the current day are marked based on the number of components to be installed. All marked areas are collected and displayed to complete the positioning of the construction progress of the photovoltaic string.

[0036] This method also includes fine-matching the construction progress model with the optimal photovoltaic string planning model, and then performing parameter adjustments to obtain the real-time construction progress model of the photovoltaic string.

[0037] Specifically, the construction progress model and the photovoltaic string planning model are matched in terms of location and components. The results of location matching and component identification are combined to match the basic components. Based on the results of component identification, the corresponding installation parameters in the photovoltaic string planning model are extracted. The matching basic components are parametrically adjusted based on the installation parameters. Based on the parametrically adjusted basic components, three-dimensional reverse modeling is performed in the three-dimensional point cloud space to obtain the real-time construction progress model. Among them, the parameterization adjustment of the successfully matched device primitives in combination with the installation parameters includes: on the basis of the original construction progress model, replacing the installation parameters corresponding to the device primitives of the construction progress model with the modified installation parameters, thereby updating the construction progress model and obtaining a real-time construction progress model.

[0038] This method also includes developing a construction progress adjustment plan based on the construction progress generated from the construction progress of the location photovoltaic strings.

[0039] The comparison and analysis of real-time construction progress data based on planned construction progress data is used to obtain the comparison results and the construction progress value. The construction progress value is evaluated based on the preset construction progress range. When the construction progress is within the normal range, the construction progress value is evaluated as belonging to the normal construction level, and the normal construction level is fed back. When the construction progress falls within an abnormal range, the construction progress value is evaluated as an abnormal construction level, the abnormal construction level is fed back, and an adjustment plan for the construction progress is formulated based on the abnormal construction level. According to the construction schedule adjustment plan, the construction schedule of the photovoltaic strings will be adjusted.

[0040] Furthermore, this method also includes fine matching of the photovoltaic string point cloud model and the photovoltaic string planning model to obtain the construction deviation data of the photovoltaic string; The photovoltaic strings are rectified based on the construction deviation data of the photovoltaic strings, and real-time rectification progress data is generated based on the obtained rectified photovoltaic string data. Rectification data for photovoltaic strings is generated based on construction deviation data. The rectification data will be sent to the smart terminals of construction workers or construction supervisors so that they can be arranged to carry out the rectification. The construction and rectification completion data of the photovoltaic strings after rectification is obtained by using drone laser scanning. The construction and rectification completion data is then input into the photovoltaic string planning model for verification, generating real-time rectification progress data.

[0041] This invention also discloses a photovoltaic string construction positioning system. This system is used to implement the above-mentioned method and includes: a first model construction module, a second model construction module, and a comparison and positioning module. The first model building module is used to build a construction progress model based on the point cloud data of the acquired photovoltaic strings. The second model building module is used to build the optimal planning model for photovoltaic strings based on the infrastructure planning data of the obtained photovoltaic strings; The comparison and positioning module is used to make a detailed comparison between the construction progress model and the optimal photovoltaic string planning model to locate the construction progress of the photovoltaic string. This system also includes a construction progress model update module and a construction progress adjustment module; Among them, the construction progress model update module performs fine matching between the construction progress model and the optimal planning model of the photovoltaic string, and then performs parameter adjustments to obtain the real-time construction progress model of the photovoltaic string. The construction progress adjustment module is used to formulate a construction progress adjustment plan based on the construction progress evaluation generated by the location of the photovoltaic string.

[0042] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0043] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that can be understood by those skilled in the art. The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A method for positioning photovoltaic strings during construction, characterized in that, Includes the following steps: A construction progress model is constructed based on the point cloud data of the acquired photovoltaic strings; An optimal planning model for photovoltaic strings is constructed based on the infrastructure planning data obtained from the photovoltaic strings. The construction progress model is compared with the optimal planning model for the photovoltaic string to determine the construction progress of the photovoltaic string.

2. The photovoltaic string construction positioning method according to claim 1, characterized in that, The construction progress model based on the acquired point cloud data of the photovoltaic strings includes: Point cloud image data of the photovoltaic string construction site were obtained based on UAV laser scanning; The point cloud image data is preprocessed to obtain preprocessed point cloud data; The point cloud preprocessing data is sorted based on the construction time sequence to obtain time-sorted point cloud data; A construction progress model is constructed based on the time-sorted point cloud data.

3. The photovoltaic string construction positioning method according to claim 2, characterized in that, The point cloud image data of the photovoltaic string construction site obtained based on UAV laser scanning includes: Obtain the initial construction location and current construction location of the photovoltaic power station; The initial construction location of the photovoltaic power station is set as the initial image acquisition location, and the current construction location is set as the end location of UAV image acquisition. Multiple UAV flight paths are planned. The drone is controlled to fly along multiple drone flight paths to scan the photovoltaic string construction site and obtain the point cloud image data.

4. The photovoltaic string construction positioning method according to claim 2, characterized in that, The point cloud preprocessing data is sorted based on the construction time sequence to obtain time-sorted point cloud data, including: Obtain the construction timing information corresponding to the point cloud preprocessed data of each photovoltaic string group; Based on the aforementioned construction sequence information, a timeline framework is established; The point cloud preprocessed data is encoded based on the construction time sequence information; The encoded point cloud preprocessed data is arranged in chronological order within a time-series framework to obtain time-sorted point cloud data.

5. The photovoltaic string construction positioning method according to claim 2, characterized in that, The construction progress model constructed based on the time-sorted point cloud data includes: Extract the temporal order from the time-sorted point cloud data; The modeling order of the current photovoltaic string is planned based on the aforementioned time sequence; Based on the current modeling order of the photovoltaic strings, the number of components installed in each photovoltaic string, the location of each photovoltaic string in the photovoltaic power station, and the starting construction location of each photovoltaic string in the time-sorted point cloud data are sequentially input into the basic model of the photovoltaic power station based on the terrain area where the photovoltaic power station is located, and multiple photovoltaic string point cloud models are constructed. The construction progress model is fitted by fitting multiple photovoltaic string point cloud models.

6. The photovoltaic string construction positioning method according to claim 1, characterized in that, The construction of the optimal photovoltaic string planning model based on the acquired infrastructure planning data includes: Obtain topographic data of the photovoltaic power station construction area and planning data for each photovoltaic string to obtain infrastructure planning data; Extract the planned construction time of all the photovoltaic string data to obtain the planned construction start time dataset; Arrange the planned construction start times in the dataset according to their chronological order to obtain a time sequence code; Based on the aforementioned time-series coding, each group of photovoltaic string data is independently coded to obtain the planned construction schedule data; A schedule sub-model is constructed based on the planned schedule data. All the aforementioned schedule sub-models are fitted sequentially according to the order of the time sequence codes to obtain the fitted planning model; The photovoltaic string planning data is input into the corresponding photovoltaic string construction area location in the fitted planning model to obtain the photovoltaic string planning model; The completed photovoltaic string data corresponding to the historical planning data is input into the fitted planning model for optimization, thereby obtaining the optimal photovoltaic string planning model.

7. The photovoltaic string construction positioning method according to claim 6, characterized in that, The sub-model of the construction schedule, constructed based on the planned construction schedule data, includes: A site map of the construction site is determined in advance, and the site map is imported into the engineering simulation model to conduct engineering item analysis and determine the data of the planned engineering items; The planned project item data is matched with the planned construction period data to generate multi-dimensional construction tasks, and the construction period sub-model is constructed based on the multi-dimensional construction tasks.

8. A photovoltaic string construction positioning method according to claim 6, characterized in that, The detailed comparison between the construction progress model and the optimal photovoltaic string planning model includes: By comparing the construction progress model with the optimal photovoltaic string planning model, the overlapping and non-overlapping areas of the construction progress model and the optimal photovoltaic string planning model are obtained. The overlapping areas are marked as areas that have been completed, and the non-overlapping areas are marked as areas that have not been completed. Based on the photovoltaic string planning data, areas that have not been installed on the current day are marked; All marked areas are collected and displayed to determine the construction progress of the photovoltaic string.

9. A photovoltaic string construction positioning method according to claim 6, characterized in that, The photovoltaic string planning data includes the planned number of components to be installed, the planned installation parameters of the components, and the planned construction time; wherein, the planned installation parameters of the components include the installation angle, installation position, and installation height; and the planned construction time includes the planned construction start time and the planned construction end time.

10. A photovoltaic string construction positioning system, used to implement the method described in any one of claims 1 to 9, characterized in that, The system includes: a first model building module, a second model building module, and a comparison and localization module; The first model building module is used to build a construction progress model based on the point cloud data of the acquired photovoltaic strings. The second model building module is used to build an optimal planning model for photovoltaic strings based on the infrastructure planning data of the acquired photovoltaic strings; The comparison and positioning module is used to make a detailed comparison between the construction progress model and the optimal photovoltaic string planning model to locate the construction progress of the photovoltaic string.

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