Wind power plant construction progress management method and system
Through the construction progress prediction model and the construction scheduling model, the problems of delays in progress and cost overruns in traditional wind farm construction have been solved, and the goals of project efficiency and sustainable development have been achieved.
Patent Information
- Application Number
- CN202510204552.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-24
- Publication Date
- 2025-07-22
AI Technical Summary
The progress management of traditional wind farm construction relies on experience and manual monitoring, resulting in problems such as delays in progress and cost overruns.
Establish a construction progress prediction model and a construction scheduling model, predict project progress and evaluation scores through data analysis, and provide scheduling references for manpower, material resources and financial resources.
Improve the efficiency and feasibility of wind farm projects, reduce environmental impact, and achieve smooth implementation and sustainable development of the project.
Smart Images
Figure CN120355347A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of wind farms, and more specifically, to a method and system for managing the construction progress of a wind farm. Background Art
[0002] A wind farm is an important facility for generating electricity using wind energy. Wind energy assessment technology is used to measure and analyze the wind speed and direction in a specific area to determine the optimal location. The data monitoring and management system utilizes the Internet of Things and big data analysis to monitor and optimize the operation of the wind farm in real time, ensuring safety and stability. The combination of these technologies enables the wind farm to efficiently and sustainably convert wind energy into electrical energy, promoting the development of renewable energy.
[0003] Among them, the management of the construction progress of a wind farm is a key link to ensure the efficient and timely completion of a wind power project. With the rapid development of renewable energy, wind power, as a clean energy source, has received extensive attention. The construction of a wind farm usually involves multiple stages, including site selection, design, equipment procurement, construction, and grid connection, etc. Each stage requires strict time control and resource allocation. In traditional project management, it often relies on experience and manual monitoring, resulting in problems such as schedule delays and cost overruns. Summary of the Invention
[0004] The purpose of the present invention is to provide a method and system for managing the construction progress of a wind farm to solve the above problems in the prior art.
[0005] The present invention is achieved through the following technical solutions:
[0006] A method for managing the construction progress of a wind farm includes:
[0007] Obtaining the construction progress data of each construction project according to several construction projects of the current wind farm;
[0008] Obtaining the historical construction progress data of each construction project, preprocessing the historical construction progress data, and dividing the preprocessed historical construction progress data into a training set, a validation set, and a test set;
[0009] Establishing a construction progress prediction model, training the construction progress prediction model through the training set, optimizing the construction progress prediction model through the validation set, continuously updating the learning rate and weights, and validating the construction progress prediction model through the test set to output the optimal construction progress prediction model;
[0010] Predicting the current several construction progress data through the construction progress prediction model and outputting the result of whether the current construction project progress meets the standard;
[0011] If the current construction progress meets the standard, no operation is performed. If the current construction progress does not meet the standard, all construction progress data and the construction basic data of each construction project are obtained;
[0012] A construction scheduling model is established. Based on the construction basic data and construction progress data, each construction project is evaluated through the construction scheduling model to obtain several evaluation scores; the evaluation scores are sorted and the sorting results are output.
[0013] Preferably, the preprocessing of the historical construction progress data includes;
[0014] Normalize the historical construction progress data and perform feature selection;
[0015]
[0016] In the formula, X ′ is the normalized data, X is the original data, X max is the maximum value in the feature, X min is the minimum value in the feature.
[0017] Preferably, the division of the training set, validation set and test set includes:
[0018] The proportion of the training set division is 60%-80% of the total data set, the proportion of the validation set division is 10%-20% of the total data set, and the proportion of the test set division is 10%-20% of the total data set.
[0019] Preferably, the establishment of the construction progress prediction model includes:
[0020] An output layer, a hidden layer and an output layer. The output layer is used to receive data and transfer it to the hidden layer. The hidden layer is used to process the input data and extract features. The output layer is mainly used to generate the final output of the model, and an objective function is constructed through the output layer, hidden layer and output layer.
[0021] Preferably, the objective function includes:
[0022]
[0023] In the formula, G s is the predicted value, σ is the activation function, w ij is the input from the i-th input layer to the j-th hidden layer, δ ij is the input from the i-th hidden layer to the j-th output layer, λ is the regularization coefficient, b i is the connection weight from the i-th input layer to the hidden layer, b j is the connection weight from the j-th hidden layer to the output layer, μ is the number of input layers, is the number of hidden layers, xi is the output sample, X is the learning rate, and ψ g is the output of the output layer of the g-th layer, and α s is the bias of the input layer of the s-th layer, and θ r is the bias of the hidden layer of the r-th layer, ζ is the loss function, and η is the number of iterations.
[0024] Preferably, the result of outputting whether the progress of the current construction project meets the standard includes:
[0025] When 0 < G s < 0.5, output the result that the progress of the current construction project does not meet the standard. When 0.5 ≤ G s ≤ 1, output the result that the progress of the current construction project meets the standard.
[0026] Preferably, the establishment of the construction scheduling model includes:
[0027]
[0028] In the formula, W s is the evaluation score, T d is the time that has been constructed for the current project, T z is the planned total construction time of the current project, E is the number of construction personnel for the current project, Q ε is the construction cost of the current project, S m is the equipment failure rate of the equipment involved in the current project, and λ c is the calculation coefficient.
[0029] Preferably, it further includes that when the current construction project can be constructed simultaneously with other construction projects, λ c = 2. When the current construction project cannot be constructed simultaneously with other construction projects, λ c = 1.
[0030] Preferably, the output sorting result includes;
[0031] Obtain the target construction project with the highest score and send a signal that the target construction project can be scheduled.
[0032] In a second aspect, the present invention also provides a construction progress management system for a wind farm, including:
[0033] A data processing module, configured to obtain the construction progress data of each construction project according to several construction projects of the current wind farm; obtain the historical construction progress data of each construction project, preprocess the historical construction progress data, and divide the preprocessed historical construction progress data into a training set, a validation set, and a test set;
[0034] The first model establishment module is configured to establish a construction progress prediction model, train the construction progress prediction model through a training set, optimize the construction progress prediction model through a validation set, continuously update the learning rate and weights, verify the construction progress prediction model through a test set, and output the optimal construction progress prediction model; predict the current several construction progress data through the construction progress prediction model, and output the result of whether the current construction project progress meets the standard; if the current construction progress meets the standard, no operation is performed, and if the current construction progress does not meet the standard, all construction progress data and the construction basic data of each construction project are obtained;
[0035] The second model establishment module is configured to establish a construction scheduling model, evaluate each construction project based on the construction basic data and the construction progress data through the construction scheduling model, and obtain several evaluation scores; sort the evaluation scores and output the sorting result;
[0036] The main control module is connected to the data processing module, the first model establishment module and the second model establishment module, and is used to execute the above-mentioned wind farm construction progress management method.
[0037] The technical solution of the present invention has at least the following advantages and beneficial effects:
[0038] The method provided by the present invention mainly includes establishing a construction progress prediction model, predicting the current several construction progress data through the construction progress prediction model, and outputting the result of whether the current construction project progress meets the standard. Secondly, a construction scheduling model is established, and each construction project is evaluated based on the construction basic data and the construction progress data through the construction scheduling model to obtain several evaluation scores; the evaluation scores are sorted and the sorting result is output. By the above method and through data analysis to predict potential risks, the efficiency and feasibility of the wind farm project are improved. Secondly, if there is a potential risk of not being able to complete, each project can be specifically evaluated, and according to the evaluation scores, a reference basis is provided for the staff to mobilize manpower, material resources and financial resources among each project, realizing effective progress management, which not only helps the smooth implementation of the project, but also helps to reduce environmental impacts and achieve sustainable development goals. BRIEF DESCRIPTION OF THE DRAWINGS
[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.
[0040] Figure 1 It is a flow chart of the present invention. Detailed implementation manners
[0041] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some but not all of the embodiments of the present invention. Generally, the components of the embodiments of the present invention described and illustrated herein can be arranged and designed in various different configurations.
[0042] The division of modules in this application is a logical division. In actual implementation, there may be other division methods. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed.
[0043] The independently described modules or sub-modules may or may not be physically separated: they can be implemented in software or in hardware, and some of the modules or sub-modules can be implemented in software, and the functions of these modules or sub-modules are called by the processor, and other parts of the modules or sub-modules are implemented in hardware, for example, through a hardware circuit. In addition, some or all of the modules can be selected according to actual needs to achieve the objectives of the solution of this application.
[0044] Please refer to Figure 1 , a method for managing the construction progress of a wind farm provided by the present invention includes:
[0045] S101: Obtain the construction progress data of each construction project according to several construction projects of the current wind farm;
[0046] In a wind farm, there are many types of construction projects, such as the installation of wind turbines, the construction of the wind farm, the construction of roads, etc. Each construction project has corresponding progress data, and collecting the corresponding progress data prepares for subsequent data processing and prediction.
[0047] S102: Obtain the historical construction progress data of each construction project, preprocess the historical construction progress data, and divide the preprocessed historical construction progress data into a training set, a validation set and a test set;
[0048] Among them, the preprocessing of the data includes data cleaning: dealing with missing values: you can choose to delete the missing values, fill in the missing values (such as filling with the mean, median, mode) or use interpolation methods, etc.
[0049] Dealing with outliers: identifying and removing outliers or making adjustments to ensure the validity of the data.
[0050] Correcting errors: correcting input errors, such as spelling mistakes or inconsistent formats.
[0051] Data transformation: Standardization and normalization: Scale the data to the same range to facilitate model learning, such as transforming the data to [0, 1].
[0052] Data encoding: Convert categorical variables into numerical variables, for example, using one-hot encoding or label encoding.
[0053] Feature selection: Select features related to the target variable from the original data and remove redundant or irrelevant features.
[0054] Feature construction: Create new features to better represent the data, such as by combining multiple features or extracting time features.
[0055] In this embodiment, the proportion of the training set is 80% of the total data set, the proportion of the validation set is 10% of the total data set, and the proportion of the test set is 10% of the total data set.
[0056] S103: Establish a construction progress prediction model, train the construction progress prediction model with the training set, optimize the construction progress prediction model with the validation set, continuously update the learning rate and weights, and verify the construction progress prediction model with the test set to output the optimal construction progress prediction model;
[0057] S104: Predict the current construction progress data through the construction progress prediction model and output the result of whether the current construction project progress meets the standard;
[0058] S105: If the current construction progress meets the standard, no operation is performed. If the current construction progress does not meet the standard, obtain all construction progress data and the construction basic data of each construction project;
[0059] S106: Establish a construction scheduling model, evaluate each construction project based on the construction basic data and construction progress data through the construction scheduling model to obtain several evaluation scores; sort the evaluation scores and output the sorting result.
[0060] The method provided by the present invention mainly includes establishing a construction progress prediction model, predicting a number of current construction progress data through the construction progress prediction model, and outputting the result of whether the current construction project progress meets the standard. Secondly, a construction scheduling model is established, and each construction project is evaluated through the construction scheduling model based on the construction basic data and the construction progress data to obtain a number of evaluation scores; the evaluation scores are sorted and the sorting result is output. Through the above method and data analysis, potential risks are predicted, thereby improving the efficiency and feasibility of the wind farm project. Secondly, if there is a potential risk of non-completion, each project can be specifically evaluated, and according to the evaluation scores, a reference basis is provided for the transfer of human, material and financial resources between each project for the staff, realizing effective progress management, which not only helps the smooth implementation of the project, but also helps to reduce the environmental impact and achieve the sustainable development goal.
[0061] An exemplary embodiment of the present invention, the preprocessing of historical construction progress data includes;
[0062] Normalize the historical construction progress data and perform feature selection;
[0063]
[0064] In the formula, X ′ is the normalized data, X is the original data, X ma is the maximum value in the feature, X min is the minimum value in the feature.
[0065] An exemplary embodiment of the present invention, establishing a construction progress prediction model includes:
[0066] An input layer, a hidden layer and an output layer, the output layer is used to receive data and transfer it to the hidden layer, the hidden layer is used to process the input data and extract features, and the output layer is used to generate the final output of the model, and the objective function is constructed through the output layer, the hidden layer and the output layer.
[0067] An exemplary embodiment of the present invention, the objective function includes:
[0068]
[0069] In the formula, G s is the predicted value, σ is the activation function, w ij is the input from the i-th input layer to the j-th hidden layer, δ ij is the input from the i-th hidden layer to the j-th output layer, λ is the regularization coefficient, b i the connection weight from the i-th input layer to the hidden layer, b j the connection weight from the j-th hidden layer to the output layer, μ is the number of input layers, To hide the number of hidden layers, x i is the output sample, χ is the learning rate, ψ g is the output of the output layer of the g-th layer, α s is the bias of the input layer of the s-th layer, θ r is the bias of the hidden layer of the r-th layer, ζ is the loss function, and η is the number of iterations.
[0070] Specifically, the result of outputting whether the progress of the current construction project meets the standard includes:
[0071] When 0 < G s < 0.5, output the result that the progress of the current construction project does not meet the standard. When 0.5 ≤ G s ≤ 1, output the result that the progress of the current construction project meets the standard.
[0072] An exemplary implementation of the present invention also establishes a construction scheduling model including:
[0073]
[0074] In the formula, W s is the evaluation score, T d is the time that the current project has been constructed, T z is the planned total construction time of the current project, E is the number of construction workers for the current project, Q ε is the construction cost of the current project, S m is the equipment failure rate of the equipment involved in the current project, λ c is the calculation coefficient.
[0075] Through the above model, more accurate scheduling judgments can be given to the staff. Based on the analysis and calculation of various parameters, an intuitive evaluation score can be obtained for the construction of each project. A construction project with a higher score means that the project can complete the current planned progress more easily, and a construction project with a lower score means that the project has more difficulty in completing the current planned progress, providing a reference for the staff during scheduling to ensure the smooth progress and completion of the entire project.
[0076] Specifically, it also includes that when the current construction project can be constructed simultaneously with other construction projects, λ c = 2, and when the current construction project cannot be constructed simultaneously with other construction projects, λ c = 1.
[0077] Among them, a project that cannot be constructed simultaneously with other projects generally has the possibility of waiting for other projects. Therefore, for this project, time is more urgent, so a smaller value of the calculation coefficient is taken, that is, 1.
[0078] The output sorting result includes: obtaining the target construction project with the highest score and sending a signal that the target construction project can be scheduled.
[0079] In a second aspect, the present invention also provides a wind farm construction progress management system, including:
[0080] A data processing module, configured to obtain the construction progress data of each construction project according to a number of construction projects of the current wind farm; obtain the historical construction progress data of each construction project, preprocess the historical construction progress data, and divide the preprocessed historical construction progress data into a training set, a validation set, and a test set;
[0081] A first model establishment module, configured to establish a construction progress prediction model, train the construction progress prediction model through the training set, optimize the construction progress prediction model through the validation set, continuously update the learning rate and weights, verify the construction progress prediction model through the test set, and output the optimal construction progress prediction model; predict the current number of construction progress data through the construction progress prediction model, and output the result of whether the current construction project progress meets the standard; if the current construction progress meets the standard, no operation is performed, and if the current construction progress does not meet the standard, obtain all construction progress data and the construction basic data of each construction project;
[0082] A second model establishment module, configured to establish a construction scheduling model, evaluate each construction project through the construction scheduling model based on the construction basic data and the construction progress data, obtain a number of evaluation scores; sort the evaluation scores and output the sorting result;
[0083] A main control module, connected to the data processing module, the first model establishment module, and the second model establishment module, for executing the above-mentioned wind farm construction progress management method.
[0084] In addition, in each embodiment of the present invention, each functional unit can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
[0085] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods according to the embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs.
[0086] The foregoing are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.
Claims
1. A method for managing the construction progress of a wind farm, characterized in that, Including: Obtaining the construction progress data of each construction project according to several construction projects of the current wind farm; Obtaining the historical construction progress data of each construction project, preprocessing the historical construction progress data, and dividing the preprocessed historical construction progress data into a training set, a validation set, and a test set; Establishing a construction progress prediction model, training the construction progress prediction model through the training set, optimizing the construction progress prediction model through the validation set, continuously updating the learning rate and weights, validating the construction progress prediction model through the test set, and outputting the optimal construction progress prediction model; Predicting the current several construction progress data through the construction progress prediction model, and outputting the result of whether the current construction project progress meets the standard; If the current construction progress meets the standard, no operation is performed. If the current construction progress does not meet the standard, all construction progress data and the construction basic data of each construction project are obtained; Establishing a construction scheduling model, evaluating each construction project through the construction scheduling model based on the construction basic data and the construction progress data, obtaining several evaluation scores; sorting the evaluation scores, and outputting the sorting result.
2. The method for managing the construction progress of a wind farm according to claim 1, wherein The preprocessing of the historical construction progress data includes: Normalizing the historical construction progress data and performing feature selection; where X ′ is the normalized data, X is the original data, X max is the maximum value in the feature, X mi is the minimum value in the feature.
3. The method for managing the construction progress of a wind farm according to claim 2, characterized in that, The division of the training set, the validation set, and the test set includes: The proportion of the training set division is 60%-80% of the total data set, the proportion of the validation set division is 10%-20% of the total data set, and the proportion of the test set division is 10%-20% of the total data set.
4. The method for wind farm construction progress management according to claim 3, wherein The establishment of the construction progress prediction model includes: An output layer, a hidden layer, and an output layer. The output layer is used to receive data and transfer it to the hidden layer. The hidden layer is used to process the input data and extract features. The output layer is mainly used to generate the final output of the model, and an objective function is constructed through the output layer, the hidden layer, and the output layer.
5. The method for wind farm construction progress management according to claim 4, characterized in that The objective function includes: Where G s is the predicted value, σ is the activation function, w ij is the input from the input layer of the i-th layer to the hidden layer of the j-th layer, δ ij is the input from the hidden layer of the i-th layer to the output layer of the j-th layer, λ is the regularization coefficient, b i is the connection weight from the input layer of the i-th layer to the hidden layer, b j is the connection weight from the hidden layer of the j-th layer to the output layer, μ is the number of input layers, is the number of hidden layers, x i is the output sample, χ is the learning rate, ψ g is the output of the output layer of the g-th layer, α s is the bias of the input layer of the s-th layer, θ r is the bias of the hidden layer of the r-th layer, ζ is the loss function, η is the number of iterations.
6. The method for wind farm construction progress management according to claim 5, wherein, The output of the result of whether the current construction project progress meets the standard includes: When 0 < G s < 0.5, output the result that the current construction project progress does not meet the standard. When 0.5 ≤ G s ≤ 1, output the result that the current construction project progress meets the standard.
7. The method for managing the construction progress of a wind farm according to claim 6, wherein The establishment of the construction scheduling model includes: Where, W s is the evaluation score, T d is the elapsed construction time of the current project, T z is the total planned construction time of the current project, E is the number of construction personnel of the current project, Q ψ is the construction cost of the current project, S m is the equipment failure rate of the equipment involved in the current project, λ c is the calculation coefficient.
8. The method for managing the construction progress of a wind farm according to claim 6, wherein It also includes that when the current construction project can be constructed simultaneously with other construction projects, λ c = 2, and when the current construction project cannot be constructed simultaneously with other construction projects, λ c = 1.
9. The method for managing the construction progress of a wind farm according to claim 7, characterized in that The output of the sorting result includes: Obtaining the target construction project with the highest score and sending a signal that the target construction project can be scheduled.
10. Wind farm construction progress management system, characterized in that, Including: A data processing module configured to obtain the construction progress data of each construction project according to several construction projects of the current wind farm; Obtaining the historical construction progress data of each construction project, preprocessing the historical construction progress data, and dividing the preprocessed historical construction progress data into a training set, a validation set, and a test set; The first model establishment module is configured to establish a construction progress prediction model, train the construction progress prediction model through a training set, optimize the construction progress prediction model through a validation set, continuously update the learning rate and weights, verify the construction progress prediction model through a test set, and output the optimal construction progress prediction model; predict the current several construction progress data through the construction progress prediction model, and output the result of whether the current construction project progress meets the standard; if the current construction progress meets the standard, no operation is performed, and if the current construction progress does not meet the standard, all construction progress data and the construction basic data of each construction project are obtained; The second model establishment module is configured to establish a construction scheduling model, evaluate each construction project based on the construction basic data and the construction progress data through the construction scheduling model, and obtain several evaluation scores; sort the evaluation scores and output the sorting result; The main control module is connected to the data processing module, the first model establishment module and the second model establishment module, and is used to execute the wind farm construction progress management method according to any one of claims 1-8.