Photovoltaic power station construction scheme generation system

Abstract

The embodiment of the specification provides a photovoltaic power station construction scheme generation system, wherein the photovoltaic power station construction scheme generation system realizes full-process automation and intelligent planning from design data to construction instructions by constructing an integrated construction scheme generation system; the system intelligently decomposes and optimally sequences construction tasks based on multi-dimensional constraints, and dynamically schedules in combination with real-time resource states, thereby significantly improving the scientificity and delicacy of the construction scheme; through progress simulation and risk prediction, the feasibility and potential bottlenecks of the scheme can be evaluated in a virtual environment in a forward-looking manner, early identification and early avoidance of construction risks are realized; and finally, the generated dynamic visual board and precise instruction file break the closed loop of planning and execution, support real-time rolling adjustment of the construction scheme, and greatly improve the organization efficiency, process controllability and overall economic benefit of the photovoltaic power station modular construction.

Description

Technical Field

[0001] The embodiments in this specification relate to the field of photovoltaic technology, and in particular to a photovoltaic power plant construction plan generation system. Background Technology

[0002] Currently, the planning and organization of modular construction for photovoltaic power plants still largely rely on manual experience. Traditional construction scheme preparation methods suffer from low information integration and a fragmented decision-making process. The lack of real-time coordination between design data, factory production progress, and on-site resource status leads to static and rigid construction planning, making it difficult to cope with dynamic changes on-site. Task decomposition and resource scheduling are mostly based on experience-based estimations, which cannot be accurately quantitatively simulated and optimized, easily causing delays and resource waste. Construction progress monitoring and risk warning are relatively lagging, and scheme adjustments are often reactive and reactive, failing to achieve pre-prediction and proactive intervention, thus limiting the potential advantages of modular construction in terms of efficiency, cost, and controllability.

[0003] Therefore, a better solution is urgently needed. Summary of the Invention

[0004] In view of this, the embodiments of this specification provide a photovoltaic power plant construction plan generation system to solve the technical defects existing in the prior art.

[0005] According to a first aspect of the embodiments of this specification, a photovoltaic power plant construction plan generation system is provided, comprising:

[0006] The construction information integration module is configured to receive modular design results and external input information from photovoltaic power plants; The multidimensional constraint library module is configured to store and manage construction logic constraints and safety constraints; The intelligent decomposition and sequencing module for construction tasks is configured to decompose the construction process into construction tasks and sequence the construction tasks to generate a task sequence based on modular design results, construction logic constraints, and safety constraints. The resource dynamic planning and scheduling module is configured to allocate construction resources to construction tasks based on the task sequence and resource availability information in external input information to form a resource scheduling scheme. The schedule simulation and risk prediction module is configured to perform construction schedule simulation and risk analysis based on task sequences and resource scheduling schemes to generate simulation results; The construction instruction and Kanban output module is configured to generate instruction documents and visual Kanban boards to guide on-site construction based on task sequences, resource scheduling schemes, and simulation results.

[0007] In one possible implementation, the modular design deliverables include a three-dimensional assembly model and module assembly logic. External input information includes overall project timeline requirements, construction team information, construction machinery and equipment information, prefabrication plant production plan, logistics and transportation resource information, and weather warning information.

[0008] In one possible implementation, the intelligent decomposition and sorting module for construction tasks is further configured to decompose the tasks using a single electromechanical module as the basic work unit, and sort the construction tasks according to the module assembly logic and the dependencies between tasks to generate a task sequence containing the critical path.

[0009] In one possible implementation, construction logic constraints and safety constraints include module assembly sequence, heavy module hoisting requirements, work safety intervals, factory prefabrication cycle, transportation time, and extreme weather operation restrictions.

[0010] In one possible implementation, the resource dynamic planning and scheduling module is further configured to dynamically match the types of work and personnel required for the construction task, as well as the type of equipment, in conjunction with resource availability information, and optimize resource allocation to avoid resource idleness or conflicts.

[0011] In one possible implementation, construction resources include construction teams, construction machinery and equipment, and logistics and transportation resources, and resource availability information includes the available time window and status of construction resources.

[0012] In one possible implementation, the schedule simulation and risk prediction module is configured to perform discrete event simulations based on the estimated working hours and resource scheduling schemes of the construction tasks to calculate the expected duration and visualize the simulated construction scenario, and to perform risk analysis to identify schedule bottlenecks, high-risk periods of resource conflicts, and work segments affected by weather.

[0013] In one possible implementation, the construction instruction and Kanban output module is configured to generate instruction files including construction task assignment orders and material requirements plans, and the visualization Kanban is configured to dynamically display current progress, short-term plans, resource availability, and early warning information.

[0014] In one possible implementation, the construction task assignment order specifies the execution team, task content, required material module numbers and drawings, and the material requirements plan is used to guide the production and delivery rhythm of the prefabrication plant.

[0015] In one possible implementation, the system is configured to re-execute the functions of the intelligent decomposition and sorting module for construction tasks, the dynamic planning and scheduling module for resources, the progress simulation and risk prediction module, and the construction instruction and Kanban output module when it receives information about changes in the actual situation at the construction site, in order to generate an adjusted construction plan.

[0016] This specification provides a photovoltaic power plant construction plan generation system. This system, through the construction of an integrated construction plan generation system, achieves fully automated and intelligent planning from design data to construction instructions. Based on multi-dimensional constraints, the system intelligently decomposes and optimizes the sequencing of construction tasks, and dynamically schedules them in conjunction with real-time resource status, significantly improving the scientific rigor and precision of the construction plan. Through progress simulation and risk prediction, it can proactively assess the feasibility and potential bottlenecks of the plan in a virtual environment, enabling early identification and avoidance of construction risks. The resulting dynamic visual dashboard and precise instruction documents establish a closed loop between planning and execution, supporting real-time rolling adjustments to the construction plan, thereby significantly improving the organizational efficiency, process controllability, and overall economic benefits of modular construction of photovoltaic power plants. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of a photovoltaic power station construction plan generation system provided in one embodiment of this specification. Detailed Implementation

[0018] Many specific details are set forth in the following description to provide a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this specification. Therefore, this specification is not limited to the specific implementations disclosed below.

[0019] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this specification. The singular forms “a” and “the” as used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0020] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0021] This specification provides a photovoltaic power plant construction plan generation system, which will be described in detail in the following embodiments.

[0022] See Figure 1 , Figure 1 This diagram illustrates a system schematic of a photovoltaic power plant construction plan generation system according to an embodiment of this specification. Specifically, it includes a construction information integration module for receiving modular design results and external input information of the photovoltaic power plant; a multi-dimensional constraint library module for storing and managing construction logic constraints and safety constraints; a construction task intelligent decomposition and sequencing module for decomposing the construction process into construction tasks and sequencing these tasks to generate a task sequence based on the modular design results and the construction logic and safety constraints; a resource dynamic planning and scheduling module for allocating construction resources to the construction tasks based on the task sequence and resource availability information from the external input information to form a resource scheduling plan; a progress simulation and risk prediction module for performing construction progress simulation and risk analysis based on the task sequence and resource scheduling plan to generate simulation results; and a construction instruction and dashboard output module for generating instruction documents and visual dashboards to guide on-site construction based on the task sequence, resource scheduling plan, and simulation results.

[0023] The photovoltaic power station construction plan generation system can refer to a software platform used to automatically formulate and optimize detailed construction plans for photovoltaic power stations built using a modular approach. The construction information integration module can refer to a functional unit that serves as the system's data entry point, responsible for collecting various information from the design phase and the external environment. Modular design deliverables can refer to the final design documents and data sets output from the photovoltaic power station modular design system. External input information can refer to other dynamic or static data affecting the construction plan, besides the design deliverables. Construction logic constraints and safety constraints can refer to the set of process flow sequences, technical specifications, and safety regulations that must be followed during construction. The intelligent decomposition and sequencing module for construction tasks can refer to an algorithmic component that breaks down the macroscopic construction process into specific executable work units and determines their reasonable sequence. A construction task can refer to an independent work unit in the construction process with clearly defined start and end conditions, such as "hoisting a module with a certain number." A task sequence can refer to an ordered list of construction tasks arranged according to time or logical sequence. The resource dynamic planning and scheduling module can refer to a functional unit that rationally allocates resources such as manpower and equipment along the timeline based on task requirements and resource conditions. Construction resources refer to the personnel, machinery, tools, and transportation vehicles required to complete a construction task. Resource availability information refers to the status data of whether various resources are available for use within a specific time period. A resource scheduling plan refers to a detailed schedule that clearly defines "when, where, and by what resources to perform which task." A schedule simulation and risk prediction module refers to a simulation tool that extrapolates the construction process based on task and resource plans in a virtual environment and assesses potential problems. Simulation results refer to the estimated duration, critical path, resource load chart, and identified risk list obtained after simulation. A construction instruction and Kanban output module refers to a functional component that transforms the optimized plan into specific operational instructions and a dynamic monitoring interface that can be distributed to various executors. Instruction files refer to electronic documents containing detailed work orders. A visual Kanban board refers to a digital interface that dynamically displays plans, progress, and warning information in a graphical manner.

[0024] The present invention will be further described below through a detailed embodiment: This embodiment relates to a modular construction project of a 100MW photovoltaic power plant. The aforementioned photovoltaic power plant construction plan generation system generates a construction plan for the electromechanical installation phase of the project in the following manner.

[0025] After the project commences, the construction information integration module is the first to function. Through a data interface, it automatically receives the final design deliverables package from the photovoltaic power station modular design system. This package includes a complete 3D assembly model, production drawings for all modules, a list of connection relationships, and module assembly logic diagrams. Simultaneously, the project manager inputs external information through the system interface: the total project duration is required to be 60 days; available construction teams include a 20-person electrical installation team, a 15-person crane lifting team, and a 10-person commissioning team; available construction equipment includes two 100-ton truck cranes and several aerial work platforms; the prefabrication plant provides a preliminary production schedule, specifying the delivery dates for each batch of modules; the logistics company provides the available transport vehicle models and quantities; and the system also connects to the local meteorological department's 15-day weather forecast API to obtain weather warning information.

[0026] Next, the multi-dimensional constraint library module provides the rule foundation for scheme generation. This module pre-sets various constraints, such as: module assembly logic constraints (foundation pouring and curing must be completed before the upper module can be hoisted); when hoisting heavy modules (such as transformer prefabricated cabins), the foundation bearing capacity must reach a specific value and the wind speed must be below the safety threshold; when different types of work (such as hoisting and electrical wiring) work in the same area, there must be a safe time interval or spatial isolation; it takes 5 working days to produce a standard inverter cabin module in the prefabrication plant; the transportation time from the factory to the site is set to 1 day based on the distance; when heavy rain or strong winds are forecast, open-air high-altitude work and hoisting work are marked as prohibited.

[0027] Then, the intelligent decomposition and sequencing module for construction tasks begins its core processing. This module reads the module list (e.g., containing 78 inverter compartments, hundreds of combiner boxes, etc.) and assembly logic from the modular design results. It decomposes each electromechanical module's "positioning and fixing" as a basic construction task, while also decomposing auxiliary tasks such as "foundation construction," "cable laying," "pipeline connection," and "system commissioning." Based on the assembly logic (e.g., the brackets and modules for area A can only be installed after the foundation of area A is completed) and safety constraints in the library (e.g., the interval between hoisting and wiring operations), the module performs topological sequencing on all tasks, generating a task sequence containing hundreds of tasks with dependencies, and automatically calculates the critical path within it.

[0028] Subsequently, the resource dynamic planning and scheduling module intervenes. It reads the task sequence generated in the previous step, as well as the resource availability information provided by the construction information integration module. The module matches the required resources for each task: for example, the task of "lifting the inverter compartment INV-001" requires "one 100-ton truck crane" and "three crane lifting team members," with an estimated time of 2 hours. Based on the resource calendar (such as the time slot when a crane has been booked for other projects) and task dependencies, the system schedules tasks using optimization algorithms, aiming to minimize the total project duration and balance resource utilization. This ultimately results in a detailed resource scheduling plan, accurate to the daily work arrangements for each piece of equipment and each team over the next 60 days.

[0029] Next, the schedule simulation and risk prediction module performs a virtual simulation of the above plan. Based on the estimated working hours and resource allocation for each task, it simulates discrete events in "days" or "hours." The simulation process considers dynamic factors such as resource conflicts (e.g., two tasks simultaneously competing for a crane) and weather effects (e.g., all outdoor operations are suspended for one day due to heavy rain on the 10th day). After the simulation, the system outputs the simulation results: the total project duration is expected to be 58 days (slightly better than the target), and several potential risk points are identified, such as "from the 25th to the 28th, continuous high-intensity use of crane resources poses a risk of failure and delay" and "on the 40th day, the peak period of module delivery overlaps with the peak period of cable laying, which may lead to on-site congestion."

[0030] Finally, the construction instruction and dashboard output module transforms the optimal solution into executable results. It generates daily construction task assignment sheets, pushing them to each construction team leader via a mobile app, clearly informing them of the day's task list, required drawings, and material numbers. It generates precise material requirements plans, sending them to the prefabrication plant and logistics providers to guide the module's "just-in-time" production and transportation. Simultaneously, the system generates a dynamic visual dashboard on the project command center's large screen and on the computers of managers at all levels. The dashboard displays real-time planned progress, actual completion status, key tasks for the next three days, resource availability, and early warning information issued by the progress simulation and risk prediction modules.

[0031] Through the processing of the aforementioned system, a complex, multi-factor coupled construction plan can be generated quickly and scientifically, and it has the ability to be dynamically adjusted.

[0032] The beneficial effects of this embodiment are as follows: By constructing an intelligent planning system integrating multi-source information such as design, resources, and constraints, a fundamental shift from experience-driven to data-driven construction schemes is achieved. This system ensures the logical correctness of the construction process through intelligent decomposition and sequencing; achieves efficient utilization of manpower and equipment through dynamic resource scheduling; enables predictive management of the future through progress simulation and risk prediction; and finally generates digital instructions and visual dashboards, allowing for clear communication and dynamic monitoring of complex construction plans. This significantly improves the scientific nature of photovoltaic power station modular construction planning, process controllability, resource utilization, and overall construction efficiency.

[0033] In one possible implementation, the modular design deliverables include a three-dimensional assembly model and module assembly logic. External input information includes overall project timeline requirements, construction team information, construction machinery and equipment information, prefabrication plant production plan, logistics and transportation resource information, and weather warning information.

[0034] The three-dimensional assembly model refers to a digital model file containing the precise three-dimensional shape and spatial relationship of all electromechanical modules. Module assembly logic refers to the rules derived from the design phase describing the installation sequence and spatial dependencies between different modules. The total project duration requirement refers to the total time target set by the owner or project management party from commencement to completion. Construction team information refers to the personnel composition, skill levels, and work schedules of the various professional trades participating in the project. Construction machinery and equipment information refers to the models, quantities, performance, and availability of various types of machinery and equipment (such as cranes, trucks, and welding machines) available for the project. The prefabrication plant production plan refers to the schedule provided by the module prefabrication manufacturer regarding the expected completion and delivery of different types of modules. Logistics and transportation resource information refers to the available transport vehicles, drivers, and their scheduling plans. Weather warning information refers to severe weather forecasts (such as strong winds, heavy rain, and high temperatures) obtained from meteorological services that may affect construction in the near future.

[0035] In conjunction with the aforementioned embodiments, the specific data content received by the construction information integration module is as follows: In the modular design results, the three-dimensional assembly model is a ".ifc" or ".rvt" format file containing the precise coordinates of all inverter compartments, combiner boxes, and other modules in the project. The module assembly logic is a ".json" file exported from the design system, which defines, for example, that "all basic modules in area A have been installed" is a prerequisite for "the bracket in area A has been installed" using data relationships.

[0036] The external input information specifies a total project duration of 60 calendar days. Construction team information is entered in tabular form, clearly indicating that the electrical installation team consists of 20 people divided into 4 groups, including the team leader's contact information and their arrival date as the 5th day of the project. Construction equipment information records a 100-ton truck crane with license plate number XX, currently located in City X, expected to be available for deployment to this project in 3 days. The prefabrication plant production plan is a dynamically linked spreadsheet showing that the first batch of 50 combiner box modules will be completed on the 10th day, and the first batch of 10 inverter module modules will be completed on the 15th day. Logistics and transportation resource information indicates that 5 40-foot flatbed trucks are available for this project, with a one-way transport time of 6 hours per truck from the factory to the site. Weather warnings are obtained in real-time via an API interface; for example, a "blue gale warning" was received during plan development. All this structured and unstructured data constitutes the raw input for generating the construction plan.

[0037] The beneficial effects of this embodiment are as follows: it clarifies the core data input scope driving the intelligent generation of construction plans. By integrating precise 3D design models and assembly logic, it ensures a high degree of consistency between the construction plan and the design intent; by gathering comprehensive external resources and constraint information, it enables the generated plans to closely fit real-world conditions, possessing high executability and adaptability to dynamic environments, thus laying a solid data foundation for generating scientific, pragmatic, and implementable construction plans.

[0038] In one possible implementation, the intelligent decomposition and sorting module for construction tasks is further used to decompose the tasks using a single electromechanical module as the basic work unit, and to sort the construction tasks according to the module assembly logic and the dependencies between tasks, thereby generating a task sequence containing the critical path.

[0039] Decomposing the work using individual electromechanical modules as basic work units refers to defining the on-site installation process of each independent, transportable, and installable prefabricated electromechanical unit (such as an inverter compartment or a combiner box) as an independent construction task. Task dependencies refer to the relationship where, due to space, safety, or process reasons, one task can only proceed after another task has begun or been completed. The critical path refers to the path with the longest total duration among all paths from start to finish in the network diagram; any delay in any task along this path will result in a delay in the overall project duration.

[0040] In conjunction with the aforementioned embodiments, the specific working method of the intelligent decomposition and sorting module for construction tasks is as follows: The module reads the module list from the 3D assembly model, for example, the list contains inverter compartment modules numbered from INV-001 to INV-078. Based on this, the module creates a construction task named "Installation and Initial Adjustment INV-XXX" for each inverter compartment. Meanwhile, for linear modules such as cable trays and pipes, the task is decomposed into a task unit based on an installation section (such as between two support points).

[0041] Subsequently, the module reads the rules from the module assembly logic file and the constraint library. For example, the logic file states that "installing inverter compartment INV-001" depends on "completing the concrete foundation pouring and curing beneath the compartment." Safety rules in the constraint library state that the "electrical wiring" task can only begin after the corresponding equipment has been "hoisted and secured." The module constructs a task network graph by analyzing these dependencies (technical, safety, and resource dependencies) between all tasks. Based on this network graph, the module uses the critical path algorithm to calculate and sort all tasks, determining the earliest start time, latest start time, and time difference for each task. The final output task sequence is not just a simple task list, but a structured data set indicating task number, description, estimated time, predecessor tasks, successor tasks, and whether it is on the critical path. This sequence is the core basis for all subsequent resource scheduling and schedule simulation.

[0042] The beneficial effects of this embodiment are as follows: by decomposing tasks using modules as basic units, the construction plan can be precisely matched with the characteristics of modular construction, achieving refined planning. By strictly sorting according to assembly logic and dependencies and identifying critical paths, the key processes affecting the overall project duration can be accurately grasped, providing project managers with a clear management focus, thereby ensuring a smooth construction process and effectively preventing project delays caused by disordered processes.

[0043] In one possible implementation, construction logic constraints and safety constraints include module assembly sequence, heavy module hoisting requirements, work safety intervals, factory prefabrication cycle, transportation time, and extreme weather operation restrictions.

[0044] The module assembly sequence refers to the order in which different modules or components must be installed, determined by design or process. Heavy module hoisting requirements refer to special regulations concerning hoisting equipment selection, foundation treatment, hoisting techniques, and weather conditions for modules exceeding certain weight or size limits. Workplace safety intervals refer to the time or spatial distance that other workers must maintain during or after certain hazardous operations (such as hot work or hoisting) to ensure construction safety. Factory prefabrication cycle refers to the average time required for a standardized module to complete factory inspection from raw material input. Transportation time refers to the typical time required to transport modules from the prefabrication plant to the project construction site. Extreme weather operation restrictions refer to regulations requiring the cessation of certain outdoor construction activities under specific severe weather conditions (such as winds exceeding a certain level, heavy rain, or lightning).

[0045] Based on the aforementioned embodiments, specific examples of constraints stored in the multi-dimensional constraint library module are as follows: Module assembly sequence constraints might be expressed as "PV module bracket installation completed, PV module installation, string cable laying." Heavy module hoisting requirements for the "35-ton transformer prefabrication compartment" stipulate: "A 200-ton or larger truck crane must be used; the ground wind speed during hoisting must not exceed 10 meters per second; the foundation of the hoisting area must be additionally reinforced." Work type safety interval constraints stipulate: "When fabricating high-voltage cable heads, no other electrical welding operations are allowed within a 5-meter radius." Factory prefabrication cycle data records: "The production cycle for a standard combiner box module is 3 working days." Transportation time data records: "The road transportation time from the Shanghai factory to the Gansu project site is 4 days." Extreme weather operation restrictions stipulate: "When the weather forecast predicts wind speeds of level 6, all high-altitude operations and hoisting operations must be stopped; when a yellow thunderstorm warning is issued, all outdoor operations must be stopped."

[0046] These constraints are not static text, but are encoded by the system into logical rules or data parameters that can be invoked by the algorithm. The intelligent decomposition and sorting module for construction tasks and the dynamic planning and scheduling module for resources will query and follow these constraints in real time during runtime to ensure that the generated construction plan is completely feasible in terms of technology and safety.

[0047] The beneficial effects of this embodiment are as follows: by systematically and structurally managing the construction constraints scattered across various standards, experiences, and contracts, and transforming them into rules that can be recognized and executed by computers, the automatically generated construction plans inherently possess compliance and safety. This avoids oversights or inconsistencies in the understanding of standards that may occur when plans are formulated manually, thus solidifying the safety and technical bottom line of the construction plans from the source.

[0048] In one possible implementation, the resource dynamic planning and scheduling module is further used to dynamically match the types of work and personnel required for the construction task, as well as the type of equipment, in conjunction with resource availability information, and optimize resource allocation to avoid resource idleness or conflict.

[0049] The types of work and personnel required for a construction task can refer to the necessary professional categories of workers (such as electricians and crane operators) and the minimum number of workers required to complete a specific construction task. Equipment type can refer to the types and specifications of machinery or tools required to complete the task (such as cranes of a specific tonnage or welding machines of a specific model). Dynamic matching refers to the process of finding the optimal allocation relationship among multiple tasks and resources based on the attributes of the tasks (required resources, start time, and duration) and the attributes of the resources (capacity and available time). Optimized resource allocation refers to adjusting resource allocation schemes through algorithms to achieve goals such as shortening the overall construction period, improving resource utilization, reducing resource costs, or balancing resource load.

[0050] Based on the aforementioned embodiments, the workflow of the resource dynamic planning and scheduling module is as follows: The module receives a task sequence from the construction task intelligent decomposition and sorting module. For each task in the sequence, the module reads its attributes. For example, the attributes of task "T-025: Install inverter compartment INV-007" include: the required workers are "crane operators (3 people) and installers (2 people)", the required equipment is "100-ton truck crane (1 unit)", the estimated working time is 4 hours, and the earliest start time is the morning of the 8th day of the project.

[0051] Simultaneously, the module reads resource availability information provided by the construction information integration module, which includes a calendar of the busy / idle status of all construction teams and equipment on the project timeline. The module's core algorithm (such as a constraint programming-based scheduling algorithm) then begins to work: it attempts to insert the "100-ton truck crane" resource required for task T-025 into the crane's available time window, provided that its earliest start time is met. At the same time, it needs to check whether the required 5 workers are also "available" within the same time period. If direct insertion would cause delays in subsequent tasks for that crane or worker conflicts, the algorithm will attempt to slightly postpone task T-025 within the time difference allowance, or attempt to allocate another crane of equivalent capacity to the task (if available). The optimization goal is to ensure that no resources are repeatedly allocated (conflict) at the same time, while satisfying all task dependencies and constraints, and to ensure that each resource works continuously as much as possible, reducing intermediate idle waiting time. The final output resource scheduling scheme is a detailed timetable that perfectly matches and seamlessly connects all resources and all tasks in the time dimension.

[0052] The beneficial effects of this embodiment are as follows: it achieves refined, automated, and optimized allocation of construction resources. Through dynamic matching and optimization, it can maximize the utilization rate of key resources (such as large cranes), reduce their idle time, and thus reduce machinery rental costs; it can balance the workload of each construction team and avoid uneven workloads; and it can fundamentally eliminate on-site work stoppages and material shortages caused by resource conflicts, ensuring that the construction process proceeds efficiently according to plan.

[0053] In one possible implementation, construction resources include construction teams, construction machinery and equipment, and logistics and transportation resources, and resource availability information includes the available time window and status of construction resources.

[0054] Here, "construction team" can refer to a work unit composed of workers of a specific trade, dispatched as a whole. "Construction machinery and equipment" can refer to the machinery, vehicles, and tools used to complete construction activities. "Logistics and transportation resources" can refer to vehicles and personnel specifically used to transport prefabricated modules from the factory to the construction site. "Available time window" can refer to a continuous period of time in the project calendar during which a resource can be scheduled for work. "Status" can refer to whether a resource is currently in normal operation, under maintenance, booked, or occupied.

[0055] In conjunction with the aforementioned embodiments, the objects scheduled and planned by the resource dynamic planning and scheduling module specifically cover the following categories: construction teams, such as "Electrical Installation Team 1 (5 people)" and "Lifting and Hoisting Special Task Force"; construction machinery and equipment, such as "100-ton truck crane with license plate A", "40-ton flatbed transport vehicle with license plate B", and "No. 3 high-voltage test equipment"; logistics and transportation resources, such as "5 special module transport vehicles and their drivers of logistics company X".

[0056] The availability information of these resources exists in the form of structured data. For example, the availability window for a "100-ton truck crane with license plate A" is set to start from day 5 of the project and remain available continuously. However, its status calendar shows that it was automatically marked as "unavailable for outdoor hoisting operations" on days 12-13 due to a "strong wind warning." The availability window for "Electrical Installation Team 1" also starts from day 5, but its status calendar may show that it was scheduled to attend safety training on the afternoon of day 15, and its status is "unavailable." The status of logistics and transportation resources is dynamically linked to the production plan of the prefabrication plant. When a batch of modules is completed, the status of the corresponding transport vehicle changes from "standby" to "transporting," and the duration is the transportation time. The resource dynamic planning and scheduling module uses this precise status information down to each individual resource and each point in time to perform accurate matching and scheduling, thereby generating a practical scheduling plan.

[0057] The beneficial effects of this embodiment are that it clearly classifies and refines the management of construction resources down to each individual and its time status, upgrading resource scheduling from extensive "team / equipment management" to refined "manpower / machine time management." This refined management can more realistically reflect resource constraints, and the generated scheduling schemes are more operable, providing key support for achieving "just-in-time" construction and lean construction.

[0058] In one possible implementation, the schedule simulation and risk prediction module is used to perform discrete event simulations based on the estimated working hours and resource scheduling schemes of the construction tasks, to calculate the expected duration and visualize the simulated construction scenario, and to perform risk analysis to identify schedule bottlenecks, high-risk periods of resource conflicts, and work segments affected by weather.

[0059] Discrete event simulation refers to a simulation method where the state changes of a system occur at discrete points in time (triggered by events), used to simulate dynamic processes such as construction, which consist of a series of discrete activities. Estimated time refers to the pre-estimated time required to complete each construction task. Visualized construction scenario simulation refers to dynamically displaying the progress of construction activities over time in three-dimensional space or along a timeline, using animation or Gantt charts. Risk analysis refers to the process of systematically identifying, assessing, and recording uncertainties that may affect project objectives. Schedule bottlenecks refer to links or resources in the construction process that limit the overall progress speed. High-risk periods of resource conflicts refer to time periods in the scheduling plan where multiple resources are used in a highly concentrated manner or where resource load is extremely high, easily leading to cascading delays due to unforeseen circumstances. Weather-affected work segments refer to outdoor construction tasks scheduled during periods susceptible to severe weather.

[0060] In conjunction with the foregoing embodiments, the operating mechanism of the schedule simulation and risk prediction module is as follows: The module acquires a detailed scheduling plan generated by the preceding module, which includes the estimated working hours and specific resource allocation for each task. The simulation engine uses "project start" as the initial event and proceeds according to the timeline of the scheduling plan.

[0061] The simulation process is "event-driven." For example, the event "Task T-010 Start" triggers: the system occupies the crane and worker resources required for the task, and after the virtual clock advances "4 hours" (the estimated working hours of the task), the event "Task T-010 End" is triggered, which then releases the occupied resources and triggers the condition check for the start of subsequent tasks. Through thousands of such event triggers and state changes, the system fully simulates the entire construction process of the project.

[0062] After the simulation, the module outputs the calculation results: the estimated total project duration (e.g., 58 days) and generates a visualized construction scenario, such as a dynamic Gantt chart, clearly showing which tasks are running in parallel and which are on the critical path. Simultaneously, the module performs in-depth risk analysis: by statistically analyzing resource usage intensity at various time points, it identifies "days 25-28, the only 100-ton crane is fully booked," marking it as a "high-risk period for crane resource conflict"; by analyzing task attributes, it identifies "days 35-40, with most high-altitude cable laying operations concentrated," and combined with historical weather warning data, marks it as a "highly sensitive period affected by strong winds"; by analyzing the buffer time of tasks on the critical path, it identifies "task T-201 (main transformer installation) has a buffer time of only 0.5 days," marking it as a "critical schedule bottleneck." These analytical results provide clear targets for proactive intervention by project managers.

[0063] The beneficial effects of this embodiment are as follows: By using discrete event simulation technology to "pre-run" the construction plan in a virtual environment, potential problems and risks in the plan can be exposed in advance, transforming "post-event firefighting" into "pre-event prevention." Visual simulation makes complex schedule plans intuitive and easy to understand, facilitating communication among all parties. Accurate risk identification enables project management to focus on key weak links and develop contingency plans in advance, thereby significantly improving the project's resilience and the certainty of on-time delivery.

[0064] In one possible implementation, the construction instruction and Kanban output module generates instruction files including construction task assignment orders and material requirements plans, and the visual Kanban board is used to dynamically display the current progress, short-term plans, resource availability, and early warning information.

[0065] Among these, a construction task assignment order refers to a list of work tasks issued to specific construction teams or individuals, specifying the tasks they need to complete within a certain period (e.g., one day). A material requirements plan refers to a schedule derived from the construction plan outlining when prefabricated modules and other materials need to be delivered to the site. Dynamic display refers to information on the dashboard that is updated in real-time based on actual data input and plan changes. Current progress refers to the comparison between the actual completion status of each construction task and the plan as of the current moment. Short-term plan refers to the construction tasks planned to be executed in the next few days (e.g., the next 3 days or one week). Resource availability refers to the actual location and working status of various key construction resources (e.g., main cranes, work teams) at the construction site at the current moment. Early warning information refers to notifications automatically issued by the system based on progress deviations, resource anomalies, or risk prediction module outputs, indicating situations requiring attention or action.

[0066] In conjunction with the aforementioned embodiments, the construction instruction and Kanban output module plays a core role in the project execution phase. Every morning, the module automatically generates the day's construction task assignment sheet. For example, the assignment sheet is pushed to the "Electrical Installation Team Leader 2" via the APP, with the following content: "Today's tasks: 1. Complete the DC side cable wiring of inverter compartment INV-021 to INV-025, referring to drawings D-021 to D-025. The required material list has been sent to the warehouse system; 2. Assist the commissioning team in completing the insulation test of area B." At the same time, the module generates a detailed material requirements plan for the coming week and sends it to the prefabrication plant and logistics center, clearly requiring that "the 6 modules numbered INV-030 to INV-035 must be delivered to the designated storage yard on site before noon on the 12th day."

[0067] In the project command center, a visual dashboard continuously operates as the information hub. On the left side of the dashboard is a progress view linked to the 3D model; completed tasks are displayed in green, in progress in yellow, and lagging tasks in red. The center of the dashboard features a scrolling "Short-Term Plan" bar for the next three days, listing upcoming key tasks. The right side of the dashboard is a "Resource Dashboard," displaying information such as "100-ton Crane #1: Located in Area A, currently hoisting INV-028, status normal" and "Electrical Team 1: Located in Area B, currently wiring, team leader Zhang San." When the progress simulation and risk prediction module identifies a high risk, or when on-site personnel report a problem via the app (such as "Module INV-029 found to have external damage"), a prominent warning message immediately pops up at the top of the dashboard, reminding relevant personnel to pay attention and handle the issue. This enables true transparency and real-time project management.

[0068] The beneficial effects of this embodiment are: it transforms the optimized construction plan into precise instructions that can directly drive on-site actions and supply chain collaboration, thus bridging the "last mile" between planning and execution. The dynamic visual dashboard constructs a shared, real-time information environment, greatly improving communication efficiency and collaboration among all project participants, making the on-site situation clear at a glance, and enabling problems to be quickly identified and responded to, thereby ensuring that construction activities are strictly and efficiently executed according to the established plan.

[0069] In one possible implementation, the construction task assignment order specifies the execution team, task content, required material module numbers and drawings, and the material requirements plan is used to guide the production and delivery rhythm of the prefabrication plant.

[0070] The designated execution team refers to the specific construction team or person in charge clearly assigned to the task in the work order. The task content refers to a clear and unambiguous description of the work to be completed. The required material module numbers and drawings refer to the unique identifiers and corresponding installation detail drawing numbers of the specific prefabricated modules necessary to complete the task. Guiding the production and delivery rhythm of the prefabrication plant refers to the material demand plan acting as a pull signal, driving the plant to organize production and arrange delivery according to the precise time requirements of on-site construction, achieving a precise supply model of "what is needed, what is produced, when it is needed, and when it is delivered."

[0071] In conjunction with the aforementioned embodiments, the work orders and material plans generated by the construction instructions and Kanban output module have strong operability and linkage. A typical work order will include the following key fields: "Execution Team: Crane Lifting Team 1 (Team Leader: Li Si)", "Task Content: Use a 100-ton crane to lift the inverter compartment module (No.: INV-030) to the foundation in Area B (coordinates: X, Y, Z) and fix it in place. The installation accuracy requirement is a levelness error of less than one-thousandth", and "Required Materials: Inverter compartment module INV-030 (1 unit), matching anchor bolt package (No.: BOLT-B-030), installation drawings (drawing number: DRW-INV-INST-001)". With this order, workers can clearly know "who, where, what to do, what to use, and what standards to follow".

[0072] Meanwhile, to support the execution of this work order, the material requirements plan generated by the system several days in advance would inevitably include: "Module INV-030, Requirement Date: Day 12, Requirement Location: Area B Yard". This plan is directly synchronized to the manufacturing execution system of the prefabrication plant. The plant then reverse-engineers production accordingly: all inspections and packaging of INV-030 must be completed by Day 11, and the module must be handed over to the logistics provider. The logistics provider, in turn, arranges for vehicles to load the module on the afternoon of Day 11, ensuring its arrival at the site on the morning of Day 12. In this way, when the crane crew prepares to lift the module on the morning of Day 12, Module INV-030 arrives just in time, achieving a seamless "just-in-time" connection between construction and the supply chain, avoiding large stockpiles of materials or work stoppages due to material shortages.

[0073] The beneficial effects of this embodiment are as follows: by refining work orders and accurately planning material requirements, deep collaboration between construction tasks and material supply is achieved. This greatly reduces errors and waiting times caused by unclear information on site, and improves the efficiency of single operations; at the same time, the "pull-style" material supply model reduces the overall project's inventory costs and site occupancy, representing a successful application of lean construction principles in modular construction, and has a significant effect on controlling project costs and schedules.

[0074] In one possible implementation, the system is used to re-execute the functions of the intelligent decomposition and sorting module for construction tasks, the dynamic planning and scheduling module for resources, the progress simulation and risk prediction module, and the construction instruction and Kanban output module when it receives information about changes in the actual situation at the construction site, in order to generate an adjusted construction plan.

[0075] The information regarding changes in the actual situation at the construction site can refer to various events that deviate from the original plan during construction, such as: delays in the transportation of a critical module, a day-long work stoppage due to unforeseen heavy rain, a sudden malfunction of a major piece of equipment, or a task's actual completion time far exceeding the estimate. The re-execution function refers to the system automatically triggering a new round of planning, scheduling, simulation, and output processes, using the changed state as a new starting point. The adjusted construction plan refers to a new version of the construction plan and related instructions recalculated and generated by the system after considering the newly occurring actual situations.

[0076] In conjunction with the aforementioned embodiments, the system's dynamic adjustment capability is specifically manifested as follows: Suppose that on the 20th day of the project, the on-site supervisor reports a message through the system APP: "Due to road control, the transport vehicle carrying inverter compartments INV-050 and INV-051 will be delayed for 24 hours and is expected to arrive tomorrow afternoon." This "actual situation change information" is received by the construction information integration module.

[0077] The system immediately initiates a replanning process: the intelligent task decomposition and sequencing module receives the constraint of "delayed arrival of modules INV-050 / 051," and recalculates the task sequence, automatically postponing all subsequent tasks (such as hoisting and wiring) that depend on these two modules or seeking new parallel tasks. The resource dynamic planning and scheduling module then reschedules, attempting to temporarily allocate the cranes and workers originally planned for hoisting INV-050 / 051 to other tasks that can be brought forward, to fully utilize the time window. The progress simulation and risk prediction module, based on the new task sequence and resource scheduling, performs another simulation, calculating the impact of the delay on the total project duration (which may only be 0.5 days, as the original plan included a buffer), and identifies new potential bottlenecks. Finally, the construction instruction and Kanban output module immediately generates updated work orders, notifying affected teams via the app to adjust their work plans for the following day, while simultaneously updating the planning lines and warning information on the visual Kanban board. The entire process can be completed automatically within minutes; project managers only need to review and confirm the new plan generated by the system. This enables construction management to respond quickly to changes and always maintain the best alignment between plans and reality.

[0078] The beneficial effects of this embodiment are that it endows the construction plan generation system with powerful dynamic response and adaptive capabilities. When unforeseen disturbances occur on site, the system can quickly and scientifically replan and generate feasible adjustment schemes, thereby minimizing the negative impact of changes. This solves the pain point that traditional static construction plans become essentially ineffective once changes occur, greatly improving the resilience and agility of project management in the face of uncertainty, and ensuring that the project can efficiently advance towards its predetermined goals even amidst fluctuations. It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of action combinations. However, those skilled in the art should understand that the embodiments in this specification are not limited to the described order of actions, because according to the embodiments in this specification, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments in this specification.

[0079] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0080] The preferred embodiments disclosed above are merely illustrative of this specification. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the embodiments described herein. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the embodiments, thereby enabling those skilled in the art to better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. A photovoltaic power plant construction plan generation system, characterized in that, include: The construction information integration module is configured to receive modular design results and external input information from photovoltaic power plants; The multidimensional constraint library module is configured to store and manage construction logic constraints and safety constraints; The intelligent decomposition and sorting module for construction tasks is configured to decompose the construction process into construction tasks and sort the construction tasks to generate a task sequence based on the modular design results and the construction logic constraints and safety constraints. The resource dynamic planning and scheduling module is configured to allocate construction resources to the construction task based on the task sequence and the resource availability information in the external input information to form a resource scheduling scheme. The schedule simulation and risk prediction module is configured to perform construction schedule simulation and risk analysis based on the task sequence and the resource scheduling scheme to generate simulation results; The construction instruction and Kanban output module is configured to generate instruction files and visual Kanban boards to guide on-site construction based on the task sequence, the resource scheduling scheme, and the simulation results.

2. The photovoltaic power station construction plan generation system according to claim 1, characterized in that, The modular design deliverables include a three-dimensional assembly model and module assembly logic. The external input information includes total project duration requirements, construction team information, construction machinery and equipment information, prefabrication plant production plan, logistics and transportation resource information, and weather warning information.

3. The photovoltaic power station construction plan generation system according to claim 2, characterized in that, The intelligent decomposition and sorting module for construction tasks is further configured to decompose the tasks using a single electromechanical module as the basic work unit, and to sort the construction tasks according to the module assembly logic and the dependencies between tasks, generating a task sequence containing the critical path.

4. The photovoltaic power station construction plan generation system according to claim 1, characterized in that, The construction logic constraints and safety constraints include module assembly sequence, heavy module hoisting requirements, work safety intervals, factory prefabrication cycle, transportation time, and restrictions on operations in extreme weather.

5. The photovoltaic power station construction plan generation system according to claim 1, characterized in that, The resource dynamic planning and scheduling module is further configured to dynamically match the types of work and personnel required for the construction task, as well as the type of equipment, in conjunction with the available resource information, and optimize resource allocation to avoid resource idleness or conflict.

6. The photovoltaic power station construction plan generation system according to claim 5, characterized in that, The construction resources include construction teams, construction machinery and equipment, and logistics and transportation resources. The resource availability information includes the available time window and status of the construction resources.

7. The photovoltaic power station construction plan generation system according to claim 1, characterized in that, The progress simulation and risk prediction module is configured to perform discrete event simulation based on the estimated working hours of the construction task and the resource scheduling scheme to calculate the expected construction period and visualize the simulated construction scenario, and to perform risk analysis to identify progress bottlenecks, high-risk periods of resource conflicts, and work segments affected by weather.

8. The photovoltaic power station construction plan generation system according to claim 1, characterized in that, The construction instruction and Kanban output module is configured to generate instruction files that include construction task assignment orders and material demand plans, and the visualization Kanban is configured to dynamically display current progress, short-term plans, resource availability, and early warning information.

9. The photovoltaic power station construction plan generation system according to claim 8, characterized in that, The construction task dispatch order specifies the execution team, task content, required material module numbers and drawings, and the material requirements plan is used to guide the production and delivery rhythm of the prefabrication plant.

10. The photovoltaic power station construction plan generation system according to claim 1, characterized in that, The system is configured to re-execute the functions of the intelligent decomposition and sorting module for construction tasks, the dynamic planning and scheduling module for resources, the progress simulation and risk prediction module, and the construction instruction and Kanban output module when it receives information about changes in the actual situation at the construction site, in order to generate an adjusted construction plan.

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