CN-121997707-A - Optimization method, device, equipment and medium for wind farm mooring system

CN121997707ACN 121997707 ACN121997707 ACN 121997707ACN-121997707-A

Abstract

The disclosure provides an optimization method, device, equipment and medium of a wind farm mooring system, wherein the method comprises the steps of constructing a sea state classification model based on acquired historical sea state information of a wind farm; the method comprises the steps of obtaining corresponding mooring rope parameters based on sea state categories output by a sea state classification model, constructing a sea state-mooring rope parameter database based on the sea state categories and the mooring rope parameters, inputting the obtained current sea state information into the sea state classification model according to the obtained current sea state information to obtain the current sea state categories corresponding to the current sea state information, and obtaining target mooring rope parameters corresponding to the current sea state categories based on the sea state-mooring rope parameter database. According to the method, the sea state classification model is built by utilizing the historical sea state information, and the mooring rope parameters can be dynamically adjusted according to the real-time sea state information by combining the sea state-mooring rope parameter database containing the corresponding relation between the sea state types and the mooring rope parameters, so that the mooring requirements under different sea states can be accurately matched.

Inventors

XU MENGYING
WU GAI
JIA XIAOGANG
RAO WEI
SONG ZIMENG

Assignees

海峡发电有限责任公司
上海电气风电集团股份有限公司

Dates

Publication Date: 20260508
Application Date: 20251222

Claims (14)

1. A method of optimizing a wind farm mooring system, the method comprising: acquiring historical sea state information of a wind power plant; Constructing a sea state classification model based on the historical sea state information; Acquiring corresponding mooring rope parameters based on sea state categories output by the sea state classification model; Constructing a sea state-mooring rope parameter database based on the sea state type and the mooring rope parameters, wherein the sea state-mooring rope parameter database at least comprises the corresponding relation between the sea state type and the mooring rope parameters; acquiring current sea state information of a wind power plant; inputting the current sea state information into the sea state classification model to obtain a current sea state class corresponding to the current sea state information; and acquiring target mooring rope parameters corresponding to the current sea state category based on the sea state-mooring rope parameter database.
2. A method of optimizing a wind farm mooring system according to claim 1, wherein the optimizing method further comprises: acquiring current mooring rope parameters corresponding to the current sea state category; And in response to the current mooring line parameter not being consistent with the target mooring line parameter, adjusting the current mooring line parameter based on the target mooring line parameter so that the current mooring line parameter is consistent with the target mooring line parameter.
3. The method of optimizing a wind farm mooring system according to claim 2, wherein the mooring line parameters comprise a mooring line length and a mooring dampening, wherein said adjusting the current mooring line parameter based on the target mooring line parameter to maintain the current mooring line parameter consistent with the target mooring line parameter comprises: and adjusting the current mooring rope length and the current mooring damping through a mooring adjusting unit so as to keep the current mooring rope length consistent with the target mooring rope length and the current mooring damping consistent with the target mooring damping.
4. The method of optimizing a wind farm mooring system according to claim 1, wherein said constructing a sea state classification model based on said historical sea state information comprises: selecting machine learning and deep learning algorithms which can be used for time sequence classification as training algorithms; the historical sea state information is input into the training algorithm to obtain the sea state classification model.
5. The method of optimizing a wind farm mooring system according to claim 4, wherein said entering said historical sea state information into said training algorithm to obtain said sea state classification model comprises the steps of: dividing the historical sea state information according to a preset proportion to obtain a training set, a verification set and a test set; inputting the training set into the training algorithm to obtain the sea state classification model; inputting the verification set into the sea state classification model to adjust parameters of the sea state classification model based on a verification result; inputting the test set into the sea state classification model, and testing sea state classification results of the sea state classification model to optimize the sea state classification model.
6. The method of optimizing a wind farm mooring system according to claim 5, wherein said inputting said test set into said sea state classification model, testing sea state classification results of said sea state classification model to optimize said sea state classification model comprises: Acquiring a real sea state category and a target sea state category corresponding to the test set; Acquiring a loss function based on the target sea state class and the real sea state class; optimizing the sea state classification model based on the loss function.
7. The method of optimizing a wind farm mooring system according to claim 1, wherein said constructing a sea state classification model based on said historical sea state information further comprises: And performing at least one of time stamp alignment, spatial interpolation, coordinate conversion, abnormal value detection and missing value filling on the historical sea state information to obtain preprocessed historical sea state information.
8. The method of optimizing a wind farm mooring system according to claim 1, wherein the historical sea state information comprises at least one of historical wind speed information, wind direction information, wave height information, wave period information, wave direction information, sea current flow rate information, and sea current flow direction information.
9. A method of optimizing a wind farm mooring system according to claim 1, wherein the optimizing method further comprises: And storing the sea state classification model and a sea state-mooring cable parameter database to a cloud network or a fan side.
10. The method of optimizing a wind farm mooring system according to claim 1, wherein the obtaining current sea state information of the wind farm comprises: And based on the data acquisition equipment at the wind power plant or the wind turbine side, acquiring at least one of current wind speed information, wind direction information, wave height information, wave period information, wave direction information, ocean current flow velocity information and ocean current flow direction information of the wind power plant, wherein the data acquisition equipment comprises at least one of a wind measuring tower, an acoustic Doppler current meter and a laser wave meter.
11. An optimization device of a wind farm mooring system, the optimization device comprising: The first acquisition module is used for acquiring historical sea state information of the wind power plant; the first construction module is used for constructing a sea state classification model based on the historical sea state information; the second acquisition module is used for acquiring corresponding mooring rope parameters based on sea state categories output by the sea state classification model; The second construction module is used for constructing a sea state-mooring rope parameter database based on the sea state type and the mooring rope parameters, and the sea state-mooring rope parameter database at least comprises the corresponding relation between the sea state type and the mooring rope parameters; The third acquisition module is used for acquiring current sea state information of the wind power plant; A fourth obtaining module, configured to input the current sea state information into the sea state classification model, to obtain a current sea state category corresponding to the current sea state information; And a fifth obtaining module, configured to obtain a target mooring line parameter corresponding to the current sea state category based on the sea state-mooring line parameter database.
12. An electronic device comprising a memory, a processor and a computer program stored on the memory for running on the processor, characterized in that the processor implements the method of optimizing a wind farm mooring system according to any of claims 1 to 10 when executing the computer program.
13. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program, when executed by a processor, implements a method of optimizing a wind farm mooring system according to any of claims 1 to 10.
14. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements a method of optimizing a wind farm mooring system according to any of claims 1 to 10.

Description

Optimization method, device, equipment and medium for wind farm mooring system Technical Field The disclosure relates to the technical field of wind power plants, in particular to an optimization method, device, equipment and medium of a wind power plant mooring system. Background When the conventional mooring system is designed, static design is carried out according to specific sea condition, the conventional mooring system is difficult to adapt to complex and changeable sea environments, load time changes such as wind, wave and current in the sea environments are obvious, sea environment parameter differences in different seasons and different time periods are usually fixed, the length of a mooring cable of the conventional mooring system cannot be dynamically adjusted according to real-time sea environment data, so that the mooring cable can bear excessive tension and increase fracture risk under extreme sea conditions, and when the sea conditions are stable, the mooring cable can cause excessive displacement of a fan due to overlong, so that the power generation efficiency is influenced. Disclosure of Invention The technical problem to be solved by the present disclosure is that mooring lines in the prior art are usually of a fixed length, and the length of the mooring lines cannot be dynamically adjusted according to real-time marine environment data, and an optimization method, an optimization device and an optimization medium for a wind farm mooring system are provided. The technical problems are solved by the following technical scheme: a first aspect of the present disclosure provides a method of optimizing a wind farm mooring system, the method comprising: acquiring historical sea state information of a wind power plant; Constructing a sea state classification model based on the historical sea state information; Acquiring corresponding mooring rope parameters based on sea state categories output by the sea state classification model; Constructing a sea state-mooring rope parameter database based on the sea state type and the mooring rope parameters, wherein the sea state-mooring rope parameter database at least comprises the corresponding relation between the sea state type and the mooring rope parameters; acquiring current sea state information of a wind power plant; inputting the current sea state information into the sea state classification model to obtain a current sea state class corresponding to the current sea state information; and acquiring target mooring rope parameters corresponding to the current sea state category based on the sea state-mooring rope parameter database. Preferably, the optimizing method further comprises: acquiring current mooring rope parameters corresponding to the current sea state category; And in response to the current mooring line parameter not being consistent with the target mooring line parameter, adjusting the current mooring line parameter based on the target mooring line parameter so that the current mooring line parameter is consistent with the target mooring line parameter. Preferably, the mooring line parameters include a mooring line length and a mooring dampening, and the adjusting the current mooring line parameter based on the target mooring line parameter to keep the current mooring line parameter consistent with the target mooring line parameter comprises: and adjusting the current mooring rope length and the current mooring damping through a mooring adjusting unit so as to keep the current mooring rope length consistent with the target mooring rope length and the current mooring damping consistent with the target mooring damping. Preferably, the constructing a sea state classification model based on the historical sea state information includes: selecting machine learning and deep learning algorithms which can be used for time sequence classification as training algorithms; the historical sea state information is input into the training algorithm to obtain the sea state classification model. Preferably, said inputting said historical sea state information into said training algorithm to obtain said sea state classification model comprises the steps of: dividing the historical sea state information according to a preset proportion to obtain a training set, a verification set and a test set; inputting the training set into the training algorithm to obtain the sea state classification model; inputting the verification set into the sea state classification model to adjust parameters of the sea state classification model based on a verification result; inputting the test set into the sea state classification model, and testing sea state classification results of the sea state classification model to optimize the sea state classification model. Preferably, said inputting the test set into the sea state classification model, testing sea state classification results of the sea state classification model to optimize the sea state classification model co