Offshore wind power generation early warning method and system

Abstract

The application discloses a kind of offshore wind power early warning method and system, wind power early warning field, at present, wind power generation lacks accurate early warning, prone to cause the damage of equipment, the equipment information of offshore wind power generation area is collected in the application, and offshore wind power generation area is divided into multiple power generation blocks.The power generation capacity information in the same historical time node of power generation block is obtained, and the block power generation capacity parameter set is obtained.The elements in the block power generation capacity parameter set are sorted, the highest and lowest block power generation capacity parameters are obtained, the corresponding power generation block is obtained, and the power generation capacity monitoring is carried out for a predetermined time length, and the power generation capacity monitoring result of the corresponding power generation block is obtained;Deviation calculation is carried out according to the power generation capacity monitoring result of the corresponding power generation block, and the power generation capacity difference data is obtained.The difference data is used to warn the offshore wind power block.This technical solution is convenient for timely investigation of potential problems, reduces the failure rate of wind power generation equipment, and reduces the damage of power generation equipment.

Description

Technical Field

[0001] This invention relates to the field of wind power generation early warning, and in particular to a method and system for early warning of offshore wind power generation. Background Technology

[0002] Wind power is the fastest-growing green energy technology. However, onshore wind farms face numerous limitations, such as large land areas and noise pollution, while offshore wind power does not. With the development of offshore wind power technology, more and more offshore wind farms are being built and put into operation. However, in current technology, the distance between offshore wind farms and residential areas makes routine maintenance of wind turbines difficult. Insufficient maintenance leads to decreased power generation, and if not detected and addressed promptly, it can cause damage to the equipment, resulting in greater economic losses. Summary of the Invention

[0003] The technical problem to be solved and the technical task proposed by this invention is to improve and refine existing technical solutions, and to provide a method and system for early warning of offshore wind power generation, so as to achieve the purpose of timely detection of abnormal wind power equipment and reduce damage to wind power equipment. To this end, this invention adopts the following technical solution.

[0004] The first aspect of this application provides a method for early warning of offshore wind power generation, the method being applied to an offshore wind power generation early warning system, the system being communicatively connected to a data acquisition device, the method comprising the following steps:

[0005] 1) Collect equipment information for offshore wind power generation areas using the aforementioned data acquisition device;

[0006] 2) Divide the offshore wind power generation area into multiple power generation blocks based on the equipment information;

[0007] 3) Obtain power generation information within the same historical time node of the power generation block, and obtain the block power generation parameter set based on the power generation information;

[0008] 4) Sort the elements in the block power generation parameter set, obtain the highest and lowest block power generation parameters, and obtain the corresponding power generation blocks;

[0009] 5) Monitor the power generation of the corresponding power generation block for a predetermined period of time, and obtain the power generation monitoring results of the corresponding power generation block;

[0010] 6) Calculate the deviation based on the power generation monitoring results of the corresponding power generation block to obtain power generation difference data;

[0011] 7) Provide early warnings for offshore wind power generation blocks based on the aforementioned difference data.

[0012] As a preferred technical means: In step 2), the offshore wind power generation area is divided into multiple power generation blocks according to the equipment quantity information, including the following steps:

[0013] 21) Collect information on the types of wind power generation equipment and the corresponding quantity information of wind power generation equipment in the offshore wind power generation area through the data acquisition device, construct a set of types and quantities, and obtain regional distribution data of wind power generation equipment types;

[0014] 22) Divide the offshore wind power generation area into regions based on the set of types and the regional distribution data, and obtain the regional division results;

[0015] 23) Based on the regional division results, the power generation block is obtained.

[0016] As a preferred technical means: In step 23), the offshore wind power generation area is divided into regions based on the set of types and the regional distribution data, including the following steps:

[0017] 231) Obtain the number of wind power devices with the smallest number of devices in the set of types, and obtain the greatest common divisor of all elements in the set of types;

[0018] 232) Obtain the number of areas to be divided based on the number of wind power devices with the minimum number of devices and the greatest common divisor;

[0019] 233) Obtain the set of regional division results for each type of equipment in the set of types of equipment based on the number of regional divisions;

[0020] 234) Divide the offshore wind power generation area into regions based on the region division result data set and the region distribution data.

[0021] As a preferred technical means: In step 234), the offshore wind power generation area is divided into regions based on the region division result data set and the region distribution data, including the following steps:

[0022] 2341) Traverse the regional distribution data to obtain a first division region, wherein the number of devices in the first division region corresponds to the set of regional division result data;

[0023] 2342) Remove the first partitioned region device from the regional distribution data, traverse the removed regional distribution data, and obtain the second partitioned region;

[0024] 2343) Repeat the step of obtaining the division area until the nth division area is obtained, where n is the same as the number of division areas. Obtain the first division area, the second division area and so on up to the nth division area to complete the division of the offshore wind power generation area.

[0025] As a preferred technical means: In step 7), an early warning for offshore wind power generation is generated based on the difference data, including the following steps:

[0026] 71) Obtain early warning blocks for offshore wind power generation;

[0027] 72) Obtain the power generation data of each power generation device in the offshore wind power early warning block within a predetermined time period;

[0028] 73) Sort the power generation data and obtain the power generation data sorting result;

[0029] 74) Based on the sorting results of the power generation data, provide early warning for the power generation equipment.

[0030] As a preferred technical means: In step 74), based on the power generation data sorting result, a power generation early warning is issued for the power generation equipment, including the following steps:

[0031] 741) Obtain the sorting result of the power generation data and identify the early warning power generation equipment whose ranking is lower than the preset ranking;

[0032] 742) Obtain adjacent power generation equipment of the same type as the early warning power generation equipment, and obtain standard power generation data of the adjacent power generation equipment within a predetermined time period;

[0033] 743) Obtain the deviation value between the power generation data and the standard power generation data, and obtain the power generation deviation data;

[0034] 744) When the power generation deviation data exceeds the set threshold, a power generation warning is issued to the warning power generation equipment.

[0035] A second aspect of this application provides an offshore wind power generation early warning system, wherein the system is communicatively connected to a data acquisition device, and the system includes:

[0036] The equipment information acquisition module is used to acquire equipment information in the offshore wind power generation area through the data acquisition device;

[0037] A power generation block acquisition module is used to divide the offshore wind power generation area into multiple power generation blocks based on the equipment information.

[0038] The power generation parameter set acquisition module is used to acquire power generation information within the same historical time node of the power generation block, and acquire the power generation parameter set of the block based on the power generation information.

[0039] The power generation parameter sorting module is used to sort the elements in the block power generation parameter set, obtain the highest and lowest block power generation parameters, and obtain the corresponding power generation block.

[0040] The power generation monitoring result acquisition module is used to monitor the power generation of the corresponding power generation block for a predetermined period of time and acquire the power generation monitoring result of the corresponding power generation block.

[0041] The power generation difference data acquisition module is used to calculate the deviation based on the power generation monitoring results of the corresponding power generation block and acquire power generation difference data.

[0042] The early warning module is used to provide early warnings for offshore wind power generation blocks based on the difference data.

[0043] As a preferred technical means: the power generation block acquisition module is also used to: acquire the number of wind power devices with the smallest number of devices in the set of types and acquire the greatest common divisor of each element in the set of types;

[0044] The number of regions is determined based on the minimum number of wind power devices and the greatest common divisor.

[0045] Based on the number of regions, obtain a set of region division results for each type of device in the set of types;

[0046] The offshore wind power generation area is divided into regions based on the region division result data set and the region distribution data.

[0047] As a preferred technical means: when the power generation block acquisition module divides the offshore wind power generation area into regions, it traverses the regional distribution data to obtain a first division region, wherein the number of devices in the first division region corresponds to the set of regional division result data; removes the devices in the first division region from the regional distribution data, traverses the regional distribution data after removal, and obtains a second division region; repeats the step of obtaining division regions until the nth division region is obtained, wherein n is the same as the number of regional divisions, and obtains the first division region, the second division region, and so on up to the nth division region, thus completing the regional division of the offshore wind power generation area.

[0048] As a preferred technical means, the early warning module is also used for:

[0049] Acquire early warning blocks for offshore wind power generation;

[0050] Obtain the power generation data of each power generation device in the offshore wind power early warning block within a predetermined time period;

[0051] The power generation data is sorted to obtain the power generation data sorting result;

[0052] Based on the power generation data sorting results, early warning power generation equipment with a ranking lower than a preset ranking is obtained; adjacent power generation equipment of the same type as the early warning power generation equipment is obtained, and standard power generation data of the adjacent power generation equipment within a predetermined time period is obtained; the deviation value between the power generation data and the standard power generation data is obtained, and power generation deviation data is obtained; power generation early warning is issued to the early warning power generation equipment based on the power generation deviation data.

[0053] Beneficial effects: This technical solution divides the offshore wind power generation area into multiple power generation blocks, facilitating timely investigation of potential problems by subsequent management personnel and reducing the failure rate of wind power equipment. Timely understanding of the equipment's status enables prompt maintenance of malfunctioning equipment, reducing damage and addressing the technical problem of the lack of accurate early warning methods for offshore wind power equipment in existing technologies, which leads to decreased wind power revenue and economic losses. Attached Figure Description

[0054] Figure 1 This is a flowchart illustrating the present invention;

[0055] Figure 2 This is a schematic diagram of the process for obtaining power generation blocks according to the present invention;

[0056] Figure 3 This is a schematic diagram of the process of providing early warning of power generation based on the sorting results of power generation data of the present invention;

[0057] Figure 4 This is a schematic diagram of the system structure of the present invention.

[0058] Figure 4 The module consists of: 1. Equipment information acquisition module; 2. Power generation block acquisition module; 3. Power generation parameter set acquisition module; 4. Power generation parameter sorting module; 5. Power generation monitoring result acquisition module; 6. Power generation difference data acquisition module; and 7. Early warning module. Detailed Implementation

[0059] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings.

[0060] Example 1

[0061] like Figure 1 As shown, this application provides a method for early warning of offshore wind power generation. The method is applied to an offshore wind power generation early warning system, wherein the system and a data acquisition device are communicatively connected. The method includes:

[0062] Step 100: Collect equipment information for offshore wind power generation areas using the data acquisition device;

[0063] Step 200: Divide the offshore wind power generation area into multiple power generation blocks according to the equipment information;

[0064] Specifically, wind power is the fastest-growing green energy technology. While onshore wind farms face numerous limitations, such as large land areas and noise pollution, offshore wind power does not. With the development of offshore wind power technology, more and more offshore wind farms are being built and put into operation. However, in existing technologies, the distance between offshore wind farms and residential areas makes routine maintenance of wind turbines difficult. Insufficient maintenance leads to decreased power generation, and if not detected and addressed promptly, it can cause damage and greater economic losses. Because offshore wind farms are large and wind speeds vary depending on the location of each turbine, instantaneous power generation cannot accurately determine if there are problems with the turbines, making accurate early warning impossible. In this embodiment, a data acquisition device collects equipment information from the offshore wind power generation area, obtaining information such as the number, type, and distribution of equipment. Subsequently, based on the acquired equipment information, the offshore wind power generation area is divided into multiple wind power blocks.

[0065] like Figure 2 As shown, the method step 200 provided in this embodiment further includes:

[0066] Step 210: Collect information on the types of wind power equipment and the corresponding quantity information of wind power equipment in the offshore wind power generation area through the data acquisition device, construct a set of types and quantities, and obtain regional distribution data of wind power equipment types;

[0067] Step 220: Divide the offshore wind power generation area into regions based on the set of types and the regional distribution data, and obtain the regional division results;

[0068] Step 230: Obtain the power generation block based on the area division results.

[0069] Specifically, when dividing the power generation blocks, data acquisition devices collect information on the types and quantities of wind power equipment in the offshore wind power generation area. A set of types and quantities is constructed based on this information, containing information on each type of wind power equipment and its corresponding quantity. Regional distribution data of the wind power equipment types is also obtained, facilitating subsequent regional division of the offshore wind power generation area. Subsequently, the offshore wind power generation area is divided into regions based on the set of types and quantities and the regional distribution data. To facilitate comparison of wind power generation, the division of regions should ensure continuity, and the number of wind power equipment in each region should be the same. The regional division results are then obtained, and finally, power generation blocks are determined based on these results.

[0070] The method step 230 provided in this embodiment further includes:

[0071] Step 231: Obtain the number of wind power devices with the smallest number of devices in the set of types and obtain the greatest common divisor of all elements in the set of types;

[0072] Step 232: Obtain the number of areas to be divided based on the number of wind power devices with the minimum number of devices and the greatest common divisor;

[0073] Step 233: Obtain the set of regional division results for each type of device in the set of types of devices based on the number of regional divisions;

[0074] Step 234: Divide the offshore wind power generation area into regions based on the region division result data set and the region distribution data.

[0075] Specifically, the process involves obtaining the number of wind turbines with the fewest equipment types from the set of equipment types, and then calculating the greatest common divisor (GCD) of the equipment types in this set. Next, based on the number of wind turbines with the fewest equipment types and the GCD, the number of regions is determined. This is achieved by calculating the ratio between the number of wind turbines with the fewest equipment types and the GCD, yielding the number of regions. Obtaining the GCD ensures consistency in the number and type of equipment across all regions, facilitating early warning for problematic wind turbines. Subsequently, the region division result data set for each type of equipment in the set of equipment types is obtained based on the region division result data, i.e., the specific number of each type of equipment in each region is determined. Since wind turbines are installed at different locations and experience varying wind speeds, inconsistencies in the number and type of equipment in different regions make it difficult to determine whether there are problems with the wind turbines in each region. Finally, the offshore wind power generation area is divided into regions based on the region division result data set and the regional distribution data.

[0076] The method step 234 provided in this embodiment further includes:

[0077] Step 234-1: Traverse the regional distribution data to obtain the first division region, wherein the number of devices in the first division region corresponds to the set of regional division result data;

[0078] Step 234-2: Remove the first partitioned region device from the regional distribution data, traverse the removed regional distribution data, and obtain the second partitioned region;

[0079] Step 234-3: Repeat the step of obtaining the division area until the nth division area is obtained, where n is the same as the number of division areas. Obtain the first division area, the second division area and so on up to the nth division area to complete the division of the offshore wind power generation area.

[0080] Specifically, the process involves traversing the regional distribution data, which includes the installation locations of each wind turbine. Based on the regional division result data set, the locations of each wind turbine in the regional distribution data are obtained. When constructing the first regional division, a regional division algorithm is used to construct a wind turbine distribution matrix based on the regional distribution data. Starting from the first element in the top-left corner of the matrix, the locations of various types of equipment in the regional division result data set are obtained through enumeration. Path calculations are performed on the enumeration results, with a distance of 1 between adjacent wind turbines in the vertical direction and a distance of 2 between adjacent wind turbines in the non-vertical direction. The shortest path enumeration result is obtained, which is the first regional division. Subsequently, equipment in the first regional division is removed from the regional distribution data, and new regional distribution data is obtained. The regional division algorithm is repeated to obtain the second regional division, up to the nth regional division, where n is the same as the number of regional divisions, thus completing the regional division of the offshore wind power generation area.

[0081] Step 300: Obtain power generation information within the same historical time node of the power generation block, and obtain the block power generation parameter set based on the power generation information;

[0082] Step 400: Sort the elements in the block power generation parameter set, obtain the highest and lowest block power generation parameters, and obtain the corresponding power generation blocks;

[0083] Specifically, the process involves obtaining power generation information for each power generation block within the same historical timeframe. Since wind power generation is significantly affected by wind force, the deviation in power generation over a historical period can be substantial, making it impossible to evaluate the power generation of individual wind turbines. By acquiring power generation blocks, which contain a larger number of devices, the power generation differences within the same historical timeframe are smaller, facilitating the identification of problematic power generation blocks. Based on the power generation information, a set of power generation parameters for each block is obtained. These parameters are then sorted to identify the blocks with the highest and lowest power generation. The corresponding power generation blocks are then identified. The deviation between the highest and lowest power generation parameters is assessed, and a deviation threshold is set. When the deviation is greater than or equal to the threshold, the power generation difference between the highest and lowest blocks is significant, indicating potential problems in the lower-powered blocks, requiring further evaluation.

[0084] Step 500: Monitor the power generation of the corresponding power generation block for a predetermined period of time, and obtain the power generation monitoring results of the corresponding power generation block;

[0085] Step 600: Calculate the deviation based on the power generation monitoring results of the corresponding power generation block to obtain power generation difference data;

[0086] Step 700: Provide an early warning for offshore wind power generation blocks based on the difference data.

[0087] Specifically, the power generation of the corresponding power generation block is monitored for a predetermined period of time, and the power generation data within that period is monitored to obtain the power generation monitoring results for the corresponding power generation block. Then, based on the power generation monitoring results of the corresponding power generation block, deviation calculation is performed to calculate the deviation data between the power generation of two blocks within the corresponding power generation block, obtaining the power generation difference data. Finally, based on the power generation difference data, an early warning of abnormal power generation in the power generation block is issued. By obtaining the power generation difference data, an early warning of blocks with abnormal power generation is achieved, facilitating timely investigation of potential problems by subsequent management personnel and reducing the failure rate of wind power generation equipment.

[0088] like Figure 3 As shown, the method step 700 provided in this embodiment further includes:

[0089] Step 710: Obtain the offshore wind power early warning block;

[0090] Step 720: Obtain the power generation data of each power generation device in the offshore wind power early warning block within a predetermined time period;

[0091] Step 730: Sort the power generation data to obtain the power generation information sorting result;

[0092] Step 740: Based on the sorting results of the power generation information, issue a power generation warning for the power generation equipment.

[0093] Specifically, the process involves acquiring an offshore wind power early warning block, which is the block where warnings are issued. Then, the power generation data of each generating unit within this early warning block is acquired over a predetermined period. The power generation data is then sorted, and the sorting results are obtained. When multiple categories of generating units exist, the power generation data is sorted according to the unit category. The generating units with the lowest power generation rankings are identified, and warnings are issued to these units. This facilitates timely investigation of potential problems by management personnel, reducing the failure rate of wind power generating units.

[0094] The method step 740 provided in this application embodiment further includes:

[0095] Step 741: Obtain the sorting result of the power generation data and identify the early warning power generation equipment whose ranking is lower than the preset ranking;

[0096] Step 742: Obtain neighboring power generation equipment of the same type as the early warning power generation equipment, and obtain the standard power generation information of the neighboring power generation equipment within a predetermined time period;

[0097] Step 743: Determine the deviation value between the power generation information and the standard power generation information to obtain power generation deviation data;

[0098] Step 744: Issue a power generation warning to the early warning power generation equipment based on the power generation deviation data.

[0099] Specifically, the process involves acquiring and sorting power generation data, setting a preset ranking, and identifying power generation equipment ranked below the preset ranking for early warning. Next, adjacent power generation equipment of the same type as the early warning equipment is acquired, and their power generation data within the same predetermined time period is obtained. The average of these adjacent power generation equipment is then calculated to obtain standard power generation data. Further, the deviation between the power generation data and the standard power generation data is obtained, resulting in power generation deviation data. In other words, the deviation between the power generation data of the early warning equipment and other similar equipment within the same predetermined time period is obtained. When the power generation deviation data exceeds a predetermined deviation, the power generation data of that equipment is considered significantly abnormal, and a power generation warning is issued to the early warning equipment based on the power generation deviation data. This achieves accurate early warning for problematic power generation equipment, facilitating timely investigation of potential problems by subsequent management personnel and reducing the failure rate of wind power generation equipment.

[0100] In summary, the method provided in this application divides the offshore wind power generation area into multiple power generation blocks by collecting equipment information from the area. It obtains power generation information within the same historical time point of each power generation block, thus acquiring a set of power generation parameters for each block. The elements in the set of power generation parameters are sorted, and the highest and lowest power generation parameters are obtained to identify the corresponding power generation blocks. Power generation monitoring is then performed for a predetermined period to obtain the monitoring results for each power generation block. Deviation calculations are performed based on the monitoring results to obtain power generation difference data. Early warning is then issued for the offshore wind power generation blocks based on this difference data. This method achieves accurate early warning for problematic power generation equipment, facilitating timely investigation of potential problems by subsequent management personnel and reducing the failure rate of wind power equipment. It solves the technical problem in existing technologies where there is a lack of accurate early warning methods for offshore wind power equipment, leading to decreased operating revenue and economic losses.

[0101] Example 2

[0102] Based on the same inventive concept as the offshore wind power early warning method in the foregoing embodiments, such as Figure 4 As shown, this application provides an offshore wind power generation early warning system, wherein the system and a data acquisition device are communicatively connected, and the system includes:

[0103] Equipment information acquisition module 1 is used to acquire equipment information in the offshore wind power generation area through the data acquisition device;

[0104] The power generation block acquisition module 2 is used to divide the offshore wind power generation area into multiple power generation blocks according to the equipment information;

[0105] The power generation parameter set acquisition module 3 is used to acquire power generation information within the same historical time node of the power generation block, and acquire the block power generation parameter set based on the power generation information;

[0106] The power generation parameter sorting module 4 is used to sort the elements in the block power generation parameter set, obtain the highest and lowest block power generation parameters, and obtain the corresponding power generation block.

[0107] The power generation monitoring result acquisition module 5 is used to monitor the power generation of the corresponding power generation block for a predetermined period of time and acquire the power generation monitoring result of the corresponding power generation block.

[0108] The power generation difference data acquisition module 6 is used to calculate the deviation based on the power generation monitoring results of the corresponding power generation block and acquire power generation difference data.

[0109] Early warning module 7 is used to provide early warning for offshore wind power generation blocks based on the difference data.

[0110] Furthermore, the power generation block acquisition module 2 is also used for:

[0111] The data acquisition device collects information on the types of wind power equipment and the corresponding quantity information of wind power equipment in the offshore wind power generation area, constructs a set of types and quantities, and obtains regional distribution data of wind power equipment types.

[0112] The offshore wind power generation area is divided into regions based on the set of types and the regional distribution data, and the regional division results are obtained.

[0113] Based on the regional division results, the power generation block is obtained.

[0114] Furthermore, the power generation block acquisition module 2 is also used for:

[0115] Obtain the number of wind power devices with the smallest number of devices in the set of the number of types, and obtain the greatest common divisor of all elements in the set of the number of types;

[0116] The number of regions is determined based on the minimum number of wind power devices and the greatest common divisor.

[0117] Based on the number of regions, obtain a set of region division results for each type of device in the set of types;

[0118] The offshore wind power generation area is divided into regions based on the region division result data set and the region distribution data.

[0119] Furthermore, the power generation block acquisition module 2 is also used for:

[0120] Traverse the regional distribution data to obtain a first partitioned region, wherein the number of devices in the first partitioned region corresponds to the set of regional partitioning result data;

[0121] Remove the first partitioned region device from the regional distribution data, and then traverse the remaining regional distribution data to obtain the second partitioned region.

[0122] Repeat the steps of obtaining the divided areas until the nth divided area is obtained, where n is the same as the number of areas to be divided. Obtain the first divided area, the second divided area, and so on up to the nth divided area to complete the area division of the offshore wind power generation area.

[0123] Furthermore, the early warning module 7 is also used for:

[0124] Acquire early warning blocks for offshore wind power generation;

[0125] Obtain the power generation data of each power generation device in the offshore wind power early warning block within a predetermined time period;

[0126] The power generation data is sorted to obtain the power generation data sorting result;

[0127] Based on the sorting results of the power generation data, an early warning for the power generation equipment is issued.

[0128] Furthermore, the early warning module 7 is also used for:

[0129] Obtain the sorting results of the power generation data and identify early warning power generation equipment whose ranking is lower than the preset ranking.

[0130] Obtain adjacent power generation equipment of the same type as the early warning power generation equipment, and obtain standard power generation data of the adjacent power generation equipment within a predetermined time period;

[0131] Obtain the deviation value between the power generation data and the standard power generation data, and obtain power generation deviation data;

[0132] The power generation deviation data is used to issue early warnings for the power generation equipment.

[0133] The above-described Embodiment 2 is used to execute the method as described in Embodiment 1. Its execution principle and basis can be obtained from the content described in Embodiment 1, and will not be elaborated further here. Although this application has been described in conjunction with specific features and embodiments, this application is not limited to the exemplary embodiments described herein. Based on the embodiments of this application, those skilled in the art can make various modifications and variations to this application without departing from the scope of this application, and the content obtained in this way also falls within the protection scope of this application.

Claims

1. A method for offshore wind power generation early warning, characterized in that, The method is applied to an offshore wind power early warning and management system, wherein the system and a data acquisition device are communicatively connected, and the method includes the following steps: 1) Collect equipment information for offshore wind power generation areas using the aforementioned data acquisition device; 2) Divide the offshore wind power generation area into multiple power generation blocks based on the equipment information; 3) Obtain power generation information within the same historical time node of the power generation block, and obtain the block power generation parameter set based on the power generation information; 4) Sort the elements in the block power generation parameter set, obtain the highest and lowest block power generation parameters, and obtain the corresponding power generation blocks; 5) Monitor the power generation of the corresponding power generation block for a predetermined period of time, and obtain the power generation monitoring results of the corresponding power generation block; 6) Calculate the deviation based on the power generation monitoring results of the corresponding power generation block to obtain power generation difference data; 7) Provide early warnings for offshore wind power generation blocks based on the aforementioned difference data; In step 2), the offshore wind power generation area is divided into multiple power generation blocks according to the equipment quantity information, including the following steps: 21) Collect information on the types of wind power generation equipment and the corresponding quantity information of wind power generation equipment in the offshore wind power generation area through the data acquisition device, construct a set of types and quantities, and obtain regional distribution data of wind power generation equipment types; 22) Divide the offshore wind power generation area into regions based on the set of types and the regional distribution data, and obtain the regional division results; 23) Based on the regional division results, obtain the power generation block; In step 23), the offshore wind power generation area is divided into regions based on the set of types and the regional distribution data, including the following steps: 231) Obtain the number of wind power devices with the smallest number of devices in the set of types, and obtain the greatest common divisor of all elements in the set of types; 232) Obtain the number of areas to be divided based on the number of wind power devices with the minimum number of devices and the greatest common divisor; 233) Obtain the set of regional division results for each type of equipment in the set of types based on the number of regional divisions; 234) Divide the offshore wind power generation area into regions based on the region division result data set and the region distribution data; In step 234), the offshore wind power generation area is divided into regions based on the region division result data set and the region distribution data, including the following steps: 2341) Traverse the regional distribution data to obtain a first division region, wherein the number of devices in the first division region corresponds to the set of regional division result data; 2342) Remove the first partitioned region device from the regional distribution data, traverse the removed regional distribution data, and obtain the second partitioned region; 2343) Repeat the step of obtaining the division area until the nth division area is obtained, where n is the same as the number of division areas. Obtain the first division area, the second division area and so on up to the nth division area to complete the division of the offshore wind power generation area.

2. The method for early warning of offshore wind power generation according to claim 1, characterized in that, In step 7), offshore wind power generation early warning management is performed based on the difference data, including the following steps: 71) Obtain the offshore wind power early warning management block; 72) Obtain the power generation data of each power generation device within a predetermined time period in the offshore wind power early warning management block; 73) Sort the power generation data and obtain the power generation data sorting result; 74) Based on the sorting results of the power generation data, provide early warning for the power generation equipment.

3. A method of offshore wind power generation early warning according to claim 2, characterized in that, In step 74), based on the sorting results of the power generation data, power generation early warning management is performed on the power generation equipment, including the following steps: 741) Obtain the sorting result of the power generation data and identify the early warning power generation equipment whose ranking is lower than the preset ranking; 742) Obtain adjacent power generation equipment of the same type as the early warning power generation equipment, and obtain standard power generation data of the adjacent power generation equipment within a predetermined time period; 743) Obtain the deviation value between the power generation data and the standard power generation data, and obtain power generation deviation data; 744) When the power generation deviation data exceeds the set threshold, a power generation warning is issued to the warning power generation equipment.

4. A marine wind power early warning management system, characterized in that, The system employs an early warning method for offshore wind power generation as described in any one of claims 1-3; The system and the data acquisition device are communicatively connected, and the system includes: The equipment information acquisition module is used to acquire equipment information in the offshore wind power generation area through the data acquisition device; A power generation block acquisition module is used to divide the offshore wind power generation area into multiple power generation blocks based on the equipment information. The power generation parameter set acquisition module is used to acquire power generation information within the same historical time node of the power generation block, and acquire the power generation parameter set of the block based on the power generation information. The power generation parameter sorting module is used to sort the elements in the block power generation parameter set, obtain the highest and lowest block power generation parameters, and obtain the corresponding power generation block. The power generation monitoring result acquisition module is used to monitor the power generation of the corresponding power generation block for a predetermined period of time and acquire the power generation monitoring result of the corresponding power generation block. The power generation difference data acquisition module is used to calculate the deviation based on the power generation monitoring results of the corresponding power generation block and acquire power generation difference data. The early warning management module is used to perform early warning management of offshore wind power generation blocks based on the difference data.

5. A pre-warning management system for offshore wind power generation according to claim 4, characterized in that, The power generation block acquisition module is also used to: acquire the number of wind power devices with the smallest number of devices in the set of types and acquire the greatest common divisor of each element in the set of types; The number of regions is determined based on the minimum number of wind power devices and the greatest common divisor. Based on the number of regions, obtain a set of region division results for each type of device in the set of types; The offshore wind power generation area is divided into regions based on the region division result data set and the region distribution data.

6. The offshore wind power generation early warning management system according to claim 4, characterized in that, When dividing the offshore wind power generation area into regions, the power generation block acquisition module traverses the regional distribution data to obtain a first division region, wherein the number of devices in the first division region corresponds to the regional division result data set; the devices in the first division region are removed from the regional distribution data, and the second division region is obtained by traversing the regional distribution data after removal. Repeat the steps of obtaining the divided areas until the nth divided area is obtained, where n is the same as the number of areas to be divided. Obtain the first divided area, the second divided area, and so on up to the nth divided area to complete the area division of the offshore wind power generation area.

7. A pre-warning management system for offshore wind power generation according to claim 4, characterized in that, The early warning management module is also used for: Obtain the early warning and management block for offshore wind power generation; Obtain the power generation data of each power generation device within a predetermined time period in the offshore wind power early warning management block; The power generation data is sorted to obtain the power generation data sorting result; Based on the power generation data sorting results, early warning power generation equipment with a ranking lower than the preset ranking is obtained; adjacent power generation equipment of the same type as the early warning power generation equipment is obtained, and standard power generation data of the adjacent power generation equipment within a predetermined time period is obtained; the deviation value between the power generation data and the standard power generation data is obtained, and power generation deviation data is obtained; power generation early warning management is performed on the early warning power generation equipment based on the power generation deviation data.

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