An intelligent electric power monitoring system for offshore wind turbines

Abstract

The application relates to the technical field of offshore wind power, in particular to an intelligent electric power monitoring system for offshore wind turbine generators, which comprises a collection module used for collecting first monitoring data; an acquisition module used for receiving data and acquiring meteorological forecast information of an offshore wind farm; a processing module used for judging and correcting abnormal first monitoring data to obtain second monitoring data; a numerical simulation module used for establishing a wind field numerical model and generating offshore wind farm wind energy distribution; a calculation module used for calculating an estimated inclination angle, a real-time inclination angle increase rate and an estimated inclination angle increase rate of the offshore wind turbine generator; an evaluation module used for evaluating the safety of the wind turbine generator and obtaining a first evaluation result and a second evaluation result; and an alarm module used for determining an alarm level according to the evaluation result. The application makes the monitoring system alarm more timely through multi-dimensional safety evaluation of the offshore wind turbine generator.

Description

Technical Field

[0001] This invention relates to the field of offshore wind power technology, and in particular to an intelligent power monitoring system for offshore wind turbines. Background Technology

[0002] Offshore wind power is a new type of power generation that utilizes offshore wind resources. As the world begins large-scale development of offshore wind power, China's offshore wind farm construction has also commenced. China's eastern coast boasts abundant exploitable offshore wind energy resources and favorable market conditions for development and utilization. However, due to the frequent impact of typhoons on coastal areas, various problems arise in offshore wind power generation. Therefore, intelligent monitoring systems for offshore wind turbines play an irreplaceable role in ensuring the safe operation of offshore wind power.

[0003] Patent document CN115017822A discloses an integrated monitoring method for offshore wind turbine foundations and submarine cables. The method includes: Step 1: Acquiring wind turbine pile information and establishing a wind turbine pile model based on the acquired information; acquiring first ultrasonic radar equipment information and determining a first installation location based on the acquired first ultrasonic radar equipment information; marking the first installation location in the wind turbine pile model and supplementing the corresponding first ultrasonic radar model; Step 2: Acquiring second ultrasonic radar information, where the second ultrasonic radar is used to scan the terrain beneath the pile foundation; marking the corresponding second installation location in the wind turbine pile model based on the obtained second ultrasonic radar information and supplementing the corresponding first ultrasonic radar model. Step 3: Install the first and second ultrasonic radars based on the wind turbine pile model; Step 4: Install a fiber optic interferometer on the structure platform and connect two sensing fibers from the submarine cable to the fiber optic interferometer; extend another sensing fiber from the submarine cable to the submarine cable lateral displacement monitoring system; Step 5: Set up a data processing platform on the structure platform to receive the data collected by the acquisition equipment, including the first ultrasonic radar, the second ultrasonic radar, the fiber optic interferometer, and the submarine cable lateral displacement monitoring system; Step 6: The data processing platform fuses the received data, assesses the safety of the entire wind turbine pile foundation, and sends the assessment results to the onshore monitoring center.

[0004] However, the existing monitoring methods are too simplistic, resulting in a limited scope of safety assessment. This leads to insufficient comprehensiveness in the safety assessment of offshore wind turbines and causes the monitoring system to issue alarms in a timely manner. Summary of the Invention

[0005] To address this issue, the present invention provides an intelligent power monitoring system for offshore wind turbines, which solves the problem that the existing technology does not provide a comprehensive enough safety assessment of offshore wind turbines, resulting in untimely alarms from the monitoring system.

[0006] To achieve the above objectives, the present invention provides an intelligent power monitoring system for offshore wind turbines. The system includes: a data acquisition module, used to acquire first monitoring data at set time intervals through a plurality of monitoring devices installed on the offshore wind turbine.

[0007] An acquisition module, connected to the acquisition module, is used to receive the first monitoring data sent by the acquisition module and to obtain the meteorological forecast information of the offshore wind farm through the meteorological observation station;

[0008] The processing module, connected to the acquisition module, is used to compare the actual time interval of the data received by the acquisition module with the time interval set by the acquisition module to determine the abnormal first monitoring data, and to adjust the delay of the first monitoring data according to the comparison method and correct the lost first monitoring data according to the interpolation method to obtain the second monitoring data.

[0009] The numerical simulation module, connected to the processing module, is used to divide the meteorological forecast information into several unit time meteorological forecast information and to establish a wind field numerical model based on the meteorological forecast information of each unit time and generate the simulated wind energy distribution of the offshore wind farm corresponding to each unit time.

[0010] The calculation module is connected to the processing module and the numerical simulation module respectively. It is used to calculate the estimated tilt angle of the offshore wind turbine according to the pre-set wind turbine angle-stress relationship model and the simulated wind energy distribution of the offshore wind farm corresponding to each unit time, and to calculate the real-time tilt angle increase rate according to the increase of the tilt angle at time i compared to time i-1 under the second monitoring data, and to calculate the estimated tilt angle increase rate according to the increase of the simulated tilt angle at time i compared to time i-1 under the simulated wind energy distribution.

[0011] An evaluation module, connected to the calculation module, is used to obtain a first evaluation result by comparing the second monitoring data with the preset standard monitoring data and by comparing the rate of increase of the tilt angle at time i compared to time i-1 with the preset standard tilt angle increase rate; and to obtain a second evaluation result by comparing the simulated tower stress, simulated foundation stress, and simulated foundation pressure under the simulated wind energy distribution at time i with the preset standard monitoring data and by comparing the rate of increase of the simulated tilt angle at time i compared to time i-1 with the preset standard tilt angle increase rate.

[0012] An alarm module, connected to the evaluation module, is used to determine whether to trigger an alarm and the alarm level based on the first evaluation result and the second evaluation result.

[0013] Further, the plurality of monitoring devices include a tower stress sensor, a foundation stress sensor, a foundation pressure sensor, an inclination sensor, and a real-time wind direction and speed monitor; the first monitoring data includes first tower stress data, first foundation stress data, first foundation pressure data, and first inclination angle data, as well as first real-time wind direction and first real-time wind speed; wherein, the tower stress sensor is installed on the offshore wind turbine tower to monitor the wind force received by the tower, and the first tower stress data is the monitoring data of the tower stress sensor; the foundation stress sensor is installed on the offshore wind turbine foundation to monitor the seawater impact stress received by the wind turbine foundation, and the... The first basic stress data is the monitoring data of the basic stress sensor; the pressure sensor is installed on the offshore wind turbine foundation to monitor the pressure of seawater on the wind turbine foundation, and the first basic pressure data is the monitoring data of the pressure sensor; the tilt sensor is installed on the offshore wind turbine tower to monitor the tilt angle of the tower, and the first tilt angle data is the monitoring data of the tilt sensor; the real-time wind direction and speed monitor is installed on the offshore wind turbine monitoring platform to monitor the real-time wind direction and real-time wind speed of the offshore wind farm, and the first real-time wind direction and the first real-time wind speed are the monitoring data of the real-time wind direction and speed monitor.

[0014] Furthermore, the processing module includes a judgment unit and a correction unit, wherein,

[0015] The judgment unit is used to compare the actual time interval ΔTh of the data received by the acquisition module with the time interval ΔTc set by the acquisition module to determine the abnormal first monitoring data; the abnormal first monitoring data is delayed first monitoring data or lost first monitoring data;

[0016] When ΔTh = ΔTc, the judgment unit determines that the first monitoring data received by the acquisition module is normal first monitoring data;

[0017] When ΔTc < ΔTh ≤ 2 × ΔTc, the judgment unit determines that the first monitoring data received by the acquisition module is delayed first monitoring data;

[0018] When ΔTh>2×ΔTc, the judgment unit determines that the first monitoring data received by the acquisition module is lost first monitoring data;

[0019] The correction unit is used to adjust the delayed first monitoring data to the corrected first monitoring data according to the comparison method, and to correct the lost first monitoring data according to the interpolation method to obtain the corrected first monitoring data, the corrected first monitoring data being the second monitoring data; the second monitoring data includes second tower stress data, second foundation stress data, second foundation pressure data, second tilt angle data, second real-time wind direction, and second real-time wind speed.

[0020] Furthermore, the numerical simulation module includes a partitioning unit and a generation unit, wherein,

[0021] The division unit divides the weather forecast information into several unit time weather forecast information, and the unit time weather forecast information includes unit time wind direction forecast information, unit time wind speed forecast information and unit time temperature forecast information.

[0022] The generation unit uses the unit time wind direction forecast information, unit time wind speed forecast information, unit time temperature forecast information, the regional coordinates of the offshore wind farm, and the influence coefficient of the regional temperature inversion of the offshore wind farm on the near-sea wind shear as inlet conditions to calculate the wind energy flow field of the offshore wind farm and generate the simulated wind energy distribution of the offshore wind farm for each unit time; the simulated wind energy distribution includes simulated wind direction, simulated wind speed, and simulated temperature.

[0023] Further, the calculation module includes a first calculation unit and a second calculation unit, wherein the first calculation unit is used to calculate the estimated tilt angle of the offshore wind turbine based on a pre-set wind turbine angle-stress relationship model and the simulated wind energy distribution of the offshore wind farm, including:

[0024] The angle-stress relationship model of the offshore wind turbine is pre-set in the first calculation unit:

[0025]

[0026] , where θ(ti, A11) is the tilt angle at time i under the second real-time wind direction A11, θ(t(i-1), A11) is the tilt angle at time i-1 under the second real-time wind direction A11, Δθ(ti, A11) is the tilt angle increased by time i compared to time i-1 under the second real-time wind direction A11, F11 is the second tower stress, F22 is the second foundation stress, F33 is the second foundation pressure, b1(V11) is the first correction coefficient under the second real-time wind speed V11, b2(V11) is the second correction coefficient under the second real-time wind speed V11, b3(V11) is the third correction coefficient under the second real-time wind speed V11, and λ is the tilt angle correction coefficient increased by time i compared to time i-1.

[0027] Using the simulated wind energy distribution data as known data in the offshore wind turbine angle-stress relationship model, the estimated tilt angle at any time under the simulated wind direction and simulated wind speed is calculated:

[0028]

[0029] , where θm(ti,Am) is the tilt angle at time i under the simulated wind direction Am, θm(t(i-1),Am) is the tilt angle at time i-1 under the simulated wind direction Am, Δθm(ti,Am) is the simulated tilt angle that increases from time i-1 under the simulated wind direction Am, F1m is the simulated tower stress under the simulated wind speed, F2m is the simulated foundation stress under the simulated wind speed, F3m is the simulated foundation pressure under the simulated wind speed, b1(Vm) is the first simulation correction coefficient under the simulated wind speed Vm, b2(Vm) is the second simulation correction coefficient under the simulated wind speed Vm, b3(Vm) is the third simulation correction coefficient under the simulated wind speed Vm, and λm is the simulation tilt angle correction coefficient that increases from time i-1 under the simulated wind direction Am.

[0030] Further, the second calculation unit is used to calculate the real-time tilt increase rate based on the increase in tilt angle at time i compared to time i-1 under the second real-time wind direction A11, and to calculate the estimated tilt increase rate based on the increase in simulated tilt angle at time i compared to time i-1 under the simulated wind direction Am, including:

[0031] The increase in tilt angle at time i compared to time i-1 under the second real-time wind direction A11 is Δθ(ti, A11) = θ(ti, A11) - θ(t(i-1), A11). The real-time tilt angle increase rate is calculated as Vθ(ti) = Δθ(ti, A11) / (ti-t(i-1)).

[0032] The simulated tilt angle increase at time i compared to time i-1 under the simulated wind direction Am is Δθm(ti,Am)=θm(ti,Am)-θm(t(i-1),Am), then the estimated tilt angle increase rate Vθm(ti)=Δθm(ti,Am) / (ti-t(i-1)).

[0033] Further, the evaluation module includes a first evaluation unit and a second evaluation unit, wherein the first evaluation unit is used to obtain a first evaluation result by comparing real-time second monitoring data with pre-set standard monitoring data and by comparing the rate of increase in tilt angle at time i compared to time i-1 with a pre-set standard rate of increase in tilt angle, including:

[0034] The evaluation module pre-sets standard tower stress F10, standard foundation stress F20, standard foundation pressure F30, standard tilt angle θ0, standard increase in tilt angle Δθ0, and standard tilt angle increase rate Vθ0.

[0035] When F11≤F10, the first evaluation unit evaluates the stress of the second tower as a safe stress, denoted as A11=0;

[0036] When F11 > F10, the first evaluation unit evaluates the stress in the second tower as a critical stress, denoted as A11 = 1;

[0037] When F22≤F20, the first evaluation unit evaluates the second foundation stress as a safe stress, denoted as A12=0;

[0038] When F22 > F20, the first evaluation unit evaluates the second basic stress as a critical stress, denoted as A12 = 1;

[0039] When F33≥F30, the first evaluation unit evaluates the second basic pressure as a safe stress, denoted as A13=0;

[0040] When F33 < F30, the first evaluation unit evaluates the second basic pressure as a dangerous stress, denoted as A13 = 1;

[0041] When θ(ti, A11)≤θ0, the first evaluation unit evaluates the second tilt angle as a safe tilt angle, denoted as A21=0;

[0042] When θ(ti, A11) > θ0, the first evaluation unit evaluates the second tilt angle as a safe tilt angle, denoted as A21 = 1;

[0043] When Δθ(ti, A11)≤Δθ0, the first evaluation unit evaluates the increased tilt angle as a safe increase in tilt angle, denoted as A22=0;

[0044] When Δθ(ti, A11)>Δθ0, the first evaluation unit evaluates the increased tilt angle as a dangerous increase in tilt angle, denoted as A22=1;

[0045] When Vθ(ti)≤Vθ0, the first evaluation unit evaluates the real-time tilt angle increase rate as a safe tilt angle increase rate, denoted as A23=0;

[0046] When Vθ(ti) > Vθ0, the first evaluation unit evaluates the real-time tilt angle increase rate as the dangerous tilt angle increase rate, denoted as A23 = 1;

[0047] The first evaluation result obtained based on the pre-set evaluation model is:

[0048]

[0049] Further, the second evaluation unit is used to compare the simulated tower stress, simulated foundation stress, and simulated foundation pressure under the simulated wind energy distribution at time i with pre-set standard monitoring data, and to compare the rate of increase of the simulated tilt angle at time i compared to time i-1 with a pre-set standard tilt angle increase rate to obtain a second evaluation result, including:

[0050] When F1m≤F10, the second evaluation unit evaluates the simulated tower stress as a safe stress, denoted as B11=0;

[0051] When F1m > F10, the second evaluation unit evaluates the simulated tower stress as a dangerous stress, denoted as B11 = 1;

[0052] When F2m≤F20, the second evaluation unit evaluates the simulated foundation stress as a safe stress, denoted as B12=0;

[0053] When F2m > F20, the second evaluation unit evaluates the simulated foundation stress as a dangerous stress, denoted as B12 = 1;

[0054] When F3m≥F30, the second evaluation unit evaluates the simulated foundation pressure as a safe stress, denoted as B13=0;

[0055] When F3m < F30, the second evaluation unit evaluates the simulated foundation pressure as a dangerous stress, denoted as B13 = 1;

[0056] When θm(ti,Am)≤θ0, the second evaluation unit evaluates the simulated tilt angle as a safe tilt angle, denoted as B21=0;

[0057] When θm(ti,Am)>θ0, the second evaluation unit evaluates the simulated tilt angle as a dangerous tilt angle, denoted as B21=1;

[0058] When Δθm(ti, Am)≤Δθ0, the second evaluation unit evaluates the increased tilt angle as a safe increase in tilt angle, denoted as B22=0;

[0059] When Δθm(ti, Am)>Δθ0, the second evaluation unit evaluates the simulated increase in tilt angle as a dangerous increase in tilt angle, denoted as B22=1;

[0060] When Vθm(ti)≤Vθ0, the second evaluation unit evaluates the simulated tilt angle increase rate as a safe tilt angle increase rate, denoted as B23=0;

[0061] When Vθ(ti) > Vθ0, the second evaluation unit evaluates the simulated tilt angle increase rate as the dangerous tilt angle increase rate, denoted as B23 = 1;

[0062] The second evaluation result obtained based on the pre-set evaluation model is:

[0063]

[0064] Furthermore, the alarm module includes a first alarm unit and a second alarm unit, wherein the first alarm unit is used to determine whether to trigger an alarm and the alarm level based on the first evaluation result, including:

[0065] When (A11=0 and A12=0 and A13=0) and (B21=0 and B22=0 and B23=0), the first alarm unit shuts off the alarm;

[0066] When (A11 = 1 or A12 = 1 or A13 = 1) and (B21 = 0 and B22 = 0 and B23 = 0), the first alarm unit determines the alarm level as a first-level emergency alarm;

[0067] When (A11=1 or A12=1 or A13=1) and (B21=1 or B22=1 or B23=1), the first alarm unit determines the alarm level as a level two emergency alarm.

[0068] Furthermore, the second alarm unit is used to determine whether to trigger an alarm and the alarm level based on the second assessment result, including:

[0069] When (B11=0 and B12=0 and B13=0) and (B21=0 and B22=0 and B23=0), the second alarm unit shuts off the alarm;

[0070] When (B11=1 or B12=1 or B13=1) and (B21=0 and B22=0 and B23=0), the second alarm unit determines the alarm level as a level one predictive alarm;

[0071] When (B11=1 or B12=1 or B13=1) and (B21=1 or B22=1 or B23=1), the second alarm unit determines the alarm level as a level two predictive alarm.

[0072] Compared with existing technologies, the advantages of this invention are as follows: By acquiring monitoring data from offshore wind turbines through the acquisition module, the monitoring system can collect real-time data of the offshore wind turbines; by acquiring monitoring data from the acquisition module through the acquisition module, the monitoring system can obtain real-time data of the offshore wind turbines; by acquiring weather forecast information through the acquisition module, the monitoring system can obtain environmental information of the offshore wind farm for future periods; by comparing the actual time interval of data received by the acquisition module with the set time interval of data collected by the acquisition module to obtain abnormal monitoring data and correcting the abnormal monitoring data to obtain corrected monitoring data, the data of the monitoring system is more accurate, improving the accuracy of the monitoring system for offshore wind turbines; and by establishing a numerical simulation module for the wind farm of the offshore wind farm... The system generates wind energy distribution data for offshore wind farms, enabling prediction of wind energy distribution for each unit of time in the future, thus improving the monitoring system's ability to predict wind energy distribution over future periods. The calculation module calculates the estimated tilt angle, real-time tilt angle increase rate, and estimated tilt angle increase rate of the offshore wind turbines, making the monitoring system's tower tilt angle monitoring more accurate and reliable. The evaluation module assesses the real-time tilt angle increase rate to obtain a first evaluation result and the estimated tilt angle increase rate to obtain a second evaluation result, increasing the evaluation dimensions of the tower tilt angle and making the monitoring system's monitoring of wind turbines more timely and reliable. The alarm module determines the alarm level based on the evaluation results of real-time monitoring data and the evaluation results of predicted data, making the monitoring system's alarms more timely.

[0073] In particular, by using tower stress sensors, foundation stress sensors, and foundation pressure sensors on the offshore wind turbine to obtain real-time stress monitoring data, by using tilt sensors to obtain real-time tilt angle monitoring data of the tower, and by using wind direction and speed monitors to obtain real-time wind direction and speed monitoring data, the offshore wind turbine monitoring system can monitor the operating status of the wind turbine in real time, thus improving the real-time performance of the monitoring system.

[0074] In particular, by comparing the actual time of data received by the acquisition module with the set time of data acquisition by the processing module's judgment unit, the delayed and lost data of the offshore wind turbine during data transmission are obtained, which improves the monitoring system's ability to identify abnormal data. The correction unit corrects the abnormal data and obtains the second monitoring data, which makes the monitoring data of the monitoring system more accurate and improves the accuracy of the monitoring system.

[0075] In particular, by dividing the meteorological forecast information into several unit time periods through the division unit of the numerical simulation module, the accuracy of the meteorological forecast information in the monitoring system is improved; by generating the wind energy distribution of the offshore wind farm corresponding to each unit time period through the generation unit, the monitoring system can achieve accurate prediction of the wind energy distribution of each unit time period in the future.

[0076] In particular, the first calculation unit of the calculation module calculates the estimated tilt angle of the wind turbine tower based on the wind energy distribution for each unit of time in the future, enabling the monitoring system to predict the tilt angle of the tower under the predicted wind energy distribution. The second calculation unit calculates the real-time tilt angle increase rate and the estimated tilt angle increase rate, increasing the calculation dimension of the tower tilt angle.

[0077] In particular, the first assessment unit of the assessment module conducts a safety assessment of the wind turbine in six dimensions—tower stress, foundation stress, foundation pressure, tower tilt angle, increased tilt angle, and tilt angle increase rate—based on real-time monitoring data. The second assessment unit conducts a safety assessment of the wind turbine in each unit of time in the future based on the six dimensions—tower stress, foundation stress, foundation pressure, tower tilt angle, increased tilt angle, and tilt angle increase rate—under weather forecast information. This improves the dimensionality of the monitoring system's assessment of the safety of offshore wind turbines, making the assessment results more accurate and reliable.

[0078] In particular, the alarm system's alarms are made more timely by having the first alarm unit of the alarm module alarm the real-time operating status of the wind turbine based on the first assessment result, and the second alarm unit alarm the estimated operating status of the wind turbine for each unit of time in the future based on the first assessment result. Attached Figure Description

[0079] Figure 1 This is a schematic diagram of the structure of the intelligent power monitoring system for offshore wind turbines described in this invention;

[0080] Figure 2 This is a schematic diagram of the processing module structure of the intelligent power monitoring system for offshore wind turbines described in this invention;

[0081] Figure 3 This is a schematic diagram of the numerical simulation module structure of the intelligent power monitoring system for offshore wind turbines described in this invention;

[0082] Figure 4 This is a schematic diagram of the computing module structure of the intelligent power monitoring system for offshore wind turbines described in this invention;

[0083] Figure 5 This is a schematic diagram of the evaluation module structure of the intelligent power monitoring system for offshore wind turbines described in this invention;

[0084] Figure 6This is a schematic diagram of the alarm module structure of the intelligent power monitoring system for offshore wind turbines described in this invention;

[0085] Reference numerals: 1. Acquisition module; 2. Utilization module; 3. Processing module; 4. Numerical simulation module; 5. Calculation module; 6. Evaluation module; 7. Alarm module; 301. Judgment unit; 302. Correction unit; 401. Division unit; 402. Generation unit; 501. First calculation unit; 502. Second calculation unit; 601. First evaluation unit; 602. Second evaluation unit; 701. First alarm unit; 702. Second alarm unit. Detailed Implementation

[0086] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are only for explaining the present invention and are not intended to limit the present invention.

[0087] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0088] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0089] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0090] Please refer to the following: An intelligent power monitoring system for offshore wind turbines. Figure 1-6 As shown, it can be implemented in the following manner: The system includes a data acquisition module 1, which is used to acquire first monitoring data at set time intervals through several monitoring devices installed on the offshore wind turbine.

[0091] The acquisition module 2 is connected to the acquisition module and is used to receive the first monitoring data sent by the acquisition module and to obtain the meteorological forecast information of the offshore wind farm through the meteorological observation station.

[0092] Processing module 3 is connected to the acquisition module and is used to compare the actual time interval of the data received by the acquisition module with the time interval set by the acquisition module to determine the abnormal first monitoring data, and to adjust the delay of the first monitoring data according to the comparison method and correct the lost first monitoring data according to the interpolation method to obtain the second monitoring data.

[0093] The numerical simulation module 4 is connected to the processing module and is used to divide the meteorological forecast information into several unit time meteorological forecast information and to establish a wind field numerical model based on the meteorological forecast information of each unit time and generate the simulated wind energy distribution of the offshore wind farm corresponding to each unit time.

[0094] The calculation module 5 is connected to the processing module and the numerical simulation module respectively. It is used to calculate the estimated tilt angle of the offshore wind turbine according to the pre-set wind turbine angle-stress relationship model and the simulated wind energy distribution of the offshore wind farm corresponding to each unit time. It also calculates the real-time tilt angle increase rate according to the tilt angle increase at time i compared to time i-1 under the second monitoring data, and calculates the estimated tilt angle increase rate according to the simulated tilt angle increase at time i compared to time i-1 under the simulated wind energy distribution.

[0095] Evaluation module 6, connected to the calculation module, is used to compare the second monitoring data with the preset standard monitoring data and to compare the increase rate of the tilt angle at time i compared to time i-1 with the preset standard tilt angle increase rate to obtain a first evaluation result; and to compare the simulated tower stress, simulated foundation stress, and simulated foundation pressure under the simulated wind energy distribution at time i with the preset standard monitoring data and to compare the increase rate of the simulated tilt angle at time i compared to time i-1 with the preset standard tilt angle increase rate to obtain a second evaluation result.

[0096] Alarm module 7 is connected to the evaluation module and is used to determine whether to alarm and the alarm level based on the first evaluation result and the second evaluation result.

[0097] The monitoring system acquires real-time data from offshore wind turbines through a data acquisition module. It also obtains real-time data from the acquisition module and weather forecast information to acquire environmental information for future periods. A processing module compares the actual time interval between data received by the acquisition module with the set time interval of the acquisition module to identify and correct abnormal monitoring data, resulting in more accurate data and improved monitoring precision. Finally, a numerical simulation module generates a numerical model of the offshore wind farm. The wind energy distribution monitoring system can predict the wind energy distribution of offshore wind farms for each unit of time in the future, improving the system's ability to predict wind energy distribution over future periods. The calculation module obtains estimated data, real-time tilt rate increase rate, and estimated tilt rate increase rate for offshore wind turbines, making the monitoring system's tower tilt monitoring more accurate and reliable. The evaluation module assesses the real-time tilt rate increase rate to obtain a first evaluation result and the estimated tilt rate increase rate to obtain a second evaluation result, increasing the evaluation dimensions of the tower tilt and making the monitoring of wind turbines more timely and reliable. The alarm module determines the alarm level based on the evaluation results of real-time monitoring data and the evaluation results of predicted data, making the system's alarms more timely.

[0098] Specifically, the monitoring devices include a tower stress sensor, a foundation stress sensor, a foundation pressure sensor, an inclination sensor, and a real-time wind direction and speed monitor; the first monitoring data includes first tower stress data, first foundation stress data, first foundation pressure data, and first inclination angle data, as well as first real-time wind direction and first real-time wind speed; wherein, the tower stress sensor is installed on the offshore wind turbine tower to monitor the wind force experienced by the tower, and the first tower stress data is the monitoring data from the tower stress sensor; the foundation stress sensor is installed on the offshore wind turbine foundation to monitor the seawater experienced by the wind turbine foundation. Impact stress, the first basic stress data is the monitoring data of the basic stress sensor; the pressure sensor is installed on the offshore wind turbine foundation to monitor the pressure of seawater on the wind turbine foundation, the first basic pressure data is the monitoring data of the pressure sensor; the tilt sensor is installed on the offshore wind turbine tower to monitor the tilt angle of the tower, the first tilt angle data is the monitoring data of the tilt sensor; the real-time wind direction and speed monitor is installed on the offshore wind turbine monitoring platform to monitor the real-time wind direction and real-time wind speed of the offshore wind farm, the first real-time wind direction and first real-time wind speed are the monitoring data of the real-time wind direction and speed monitor.

[0099] Real-time stress monitoring data is obtained by using tower stress sensors, foundation stress sensors, and foundation pressure sensors on offshore wind turbines. Real-time tower tilt angle monitoring data is obtained by using tilt angle sensors. Real-time wind direction and speed monitoring data is obtained by using wind direction and speed monitors. This enables the offshore wind turbine monitoring system to monitor the operating status of the wind turbine in real time, improving the real-time performance of the monitoring system.

[0100] like Figure 2 As shown, specifically, the processing module includes a judgment unit 301 and a correction unit 302. The judgment unit is used to compare the actual time interval ΔTh of the data received by the acquisition module with the time interval ΔTc set by the acquisition module to determine the abnormal first monitoring data. The abnormal first monitoring data is either delayed first monitoring data or lost first monitoring data.

[0101] When ΔTh = ΔTc, the judgment unit determines that the first monitoring data received by the acquisition module is normal first monitoring data;

[0102] When ΔTc<ΔTh≤2×ΔTc, the judgment unit determines that the first monitoring data received by the acquisition module is the delayed first monitoring data;

[0103] When ΔTh>2×ΔTc, the judgment unit determines that the first monitoring data received by the acquisition module is the first monitoring data that has been lost.

[0104] The correction unit is used to adjust the delayed first monitoring data to the corrected first monitoring data according to the comparison method, and to correct the lost first monitoring data according to the interpolation method to obtain the corrected first monitoring data. The corrected first monitoring data is the second monitoring data. The second monitoring data includes the second tower stress data, the second foundation stress data, the second foundation pressure data, the second tilt angle data, the second real-time wind direction, and the second real-time wind speed.

[0105] The processing module's judgment unit compares the actual time the acquisition module receives data with the set time the acquisition module collects data to obtain the delayed and lost data of the offshore wind turbine during data transmission, thus improving the monitoring system's ability to identify abnormal data. The correction unit corrects the abnormal data and obtains the second monitoring data, making the monitoring system's monitoring data more accurate and improving the system's precision.

[0106] like Figure 3 As shown, specifically, the numerical simulation module includes a partitioning unit 401 and a generation unit 402. The partitioning unit divides the meteorological forecast information into several unit time meteorological forecast information. The unit time meteorological forecast information includes unit time wind direction forecast information, unit time wind speed forecast information and unit time temperature forecast information.

[0107] The generation unit uses the wind direction forecast information, wind speed forecast information, temperature forecast information, regional coordinates of the offshore wind farm, and the influence coefficient of regional temperature inversion on near-sea wind shear of the offshore wind farm as inlet conditions to calculate the wind energy flow field of the offshore wind farm and generate the simulated wind energy distribution of the offshore wind farm for each unit time; the simulated wind energy distribution includes simulated wind direction, simulated wind speed, and simulated temperature.

[0108] The numerical simulation module divides the meteorological forecast information into several unit time periods, making the meteorological forecast information in the monitoring system more accurate. The generation unit generates the wind energy distribution of the offshore wind farm corresponding to each unit time, enabling the monitoring system to accurately predict the wind energy distribution for each future unit time.

[0109] like Figure 4 As shown, specifically, the calculation module includes a first calculation unit 501 and a second calculation unit 502. The first calculation unit is used to calculate the estimated tilt angle of the offshore wind turbine based on a pre-set wind turbine angle-stress relationship model and the simulated wind energy distribution of the offshore wind farm, including:

[0110] In the first calculation unit, a model for the angle-stress relationship of offshore wind turbines is pre-set:

[0111] , where θ(ti, A11) is the tilt angle at time i under the second real-time wind direction A11, θ(t(i-1), A11) is the tilt angle at time i-1 under the second real-time wind direction A11, Δθ(ti, A11) is the tilt angle increased by time i compared to time i-1 under the second real-time wind direction A11, F11 is the second tower stress, F22 is the second foundation stress, F33 is the second foundation pressure, b1(V11) is the first correction coefficient under the second real-time wind speed V11, b2(V11) is the second correction coefficient under the second real-time wind speed V11, b3(V11) is the third correction coefficient under the second real-time wind speed V11, and λ is the tilt angle correction coefficient increased by time i compared to time i-1.

[0112] Using simulated wind energy distribution data as known data in the offshore wind turbine angle-stress relationship model, the predicted tilt angle at any time under simulated wind direction and speed is calculated:

[0113]

[0114] , where θm(ti,Am) is the tilt angle at time i under simulated wind direction Am, θm(t(i-1),Am) is the tilt angle at time i-1 under simulated wind direction Am, Δθm(ti,Am) is the simulated tilt angle at time i compared to time i-1 under simulated wind direction Am, F1m is the simulated tower stress under simulated wind speed, F2m is the simulated foundation stress under simulated wind speed, F3m is the simulated foundation pressure under simulated wind speed, b1(Vm) is the first simulation correction coefficient under simulated wind speed Vm, b2(Vm) is the second simulation correction coefficient under simulated wind speed Vm, b3(Vm) is the third simulation correction coefficient under simulated wind speed Vm, and λm is the simulation tilt angle correction coefficient at time i compared to time i-1.

[0115] Specifically, the second calculation unit is used to calculate the real-time tilt increase rate based on the increase in tilt angle at time i compared to time i-1 under the second real-time wind direction A11, and to calculate the estimated tilt increase rate based on the increase in simulated tilt angle at time i compared to time i-1 under the simulated wind direction Am, including:

[0116] The increase in tilt angle at time i compared to time i-1 under the second real-time wind direction A11 is Δθ(ti, A11) = θ(ti, A11) - θ(t(i-1), A11). The real-time tilt angle increase rate is calculated as Vθ(ti) = Δθ(ti, A11) / (ti-t(i-1)).

[0117] The increase in simulated tilt angle at time i compared to time i-1 under simulated wind direction Am is Δθm(ti,Am)=θm(ti,Am)-θm(t(i-1),Am), then the estimated tilt angle increase rate Vθm(ti)=Δθm(ti,Am) / (ti-t(i-1)).

[0118] The first calculation unit of the calculation module calculates the estimated tilt angle of the wind turbine tower based on the wind energy distribution for each unit of time in the future, enabling the monitoring system to predict the tilt angle of the tower under the predicted wind energy distribution. The second calculation unit calculates the real-time tilt angle increase rate and the estimated tilt angle increase rate, increasing the calculation dimension of the tower tilt angle.

[0119] like Figure 5 As shown, specifically, the evaluation module includes a first evaluation unit 601 and a second evaluation unit 602. The first evaluation unit is used to obtain a first evaluation result by comparing real-time second monitoring data with pre-set standard monitoring data and by comparing the rate of increase in tilt angle at time i compared to time i-1 with a pre-set standard rate of increase in tilt angle. This includes:

[0120] The evaluation module pre-sets the standard tower stress F10, standard foundation stress F20, standard foundation pressure F30, standard tilt angle θ0, standard increase in tilt angle Δθ0, and standard tilt angle increase rate Vθ0.

[0121] When F11≤F10, the first evaluation unit evaluates the stress of the second tower as a safe stress, denoted as A11=0;

[0122] When F11 > F10, the first evaluation unit assesses the stress in the second tower as a critical stress, denoted as A11 = 1;

[0123] When F22≤F20, the first evaluation unit evaluates the second foundation stress as a safe stress, denoted as A12=0;

[0124] When F22 > F20, the first assessment unit assesses the second foundation stress as a critical stress, denoted as A12 = 1;

[0125] When F33≥F30, the first assessment unit assesses the second foundation pressure as a safe stress, denoted as A13=0;

[0126] When F33 < F30, the first assessment unit assesses the second foundation pressure as a dangerous stress, denoted as A13 = 1;

[0127] When θ(ti, A11)≤θ0, the first evaluation unit evaluates the second tilt angle as a safe tilt angle, denoted as A21=0;

[0128] When θ(ti, A11) > θ0, the first evaluation unit evaluates the second tilt angle as a safe tilt angle, denoted as A21 = 1;

[0129] When Δθ(ti, A11)≤Δθ0, the first evaluation unit evaluates the increased tilt angle as a safe increase in tilt angle, denoted as A22=0;

[0130] When Δθ(ti, A11)>Δθ0, the first assessment unit assesses the increased tilt angle as the increased danger tilt angle, denoted as A22=1;

[0131] When Vθ(ti)≤Vθ0, the first evaluation unit evaluates the real-time tilt angle increase rate as the safe tilt angle increase rate, denoted as A23=0;

[0132] When Vθ(ti)>Vθ0, the first evaluation unit evaluates the real-time tilt angle increase rate as the dangerous tilt angle increase rate, denoted as A23=1;

[0133] The first evaluation result obtained based on the pre-set evaluation model is:

[0134]

[0135] Specifically, the second evaluation unit is used to compare the simulated tower stress, simulated foundation stress, and simulated foundation pressure under the simulated wind energy distribution at time i with pre-set standard monitoring data, and to compare the rate of increase of the simulated tilt angle at time i compared to time i-1 with the pre-set standard tilt angle increase rate to obtain the second evaluation result, including:

[0136] When F1m≤F10, the second evaluation unit evaluates the simulated tower stress as a safe stress, denoted as B11=0;

[0137] When F1m > F10, the second evaluation unit evaluates the simulated tower stress as a dangerous stress, denoted as B11 = 1;

[0138] When F2m≤F20, the second evaluation unit evaluates the simulated foundation stress as a safe stress, denoted as B12=0;

[0139] When F2m > F20, the second evaluation unit evaluates the simulated foundation stress as a critical stress, denoted as B12 = 1;

[0140] When F3m≥F30, the second evaluation unit evaluates the simulated foundation pressure as safe stress, denoted as B13=0;

[0141] When F3m < F30, the second evaluation unit evaluates the simulated foundation pressure as a dangerous stress, denoted as B13 = 1;

[0142] When θm(ti,Am)≤θ0, the second evaluation unit evaluates the simulated tilt angle as a safe tilt angle, denoted as B21=0;

[0143] When θm(ti,Am)>θ0, the second evaluation unit evaluates the simulated tilt angle as a dangerous tilt angle, denoted as B21=1;

[0144] When Δθm(ti, Am)≤Δθ0, the second evaluation unit evaluates the increased tilt angle as a safe increase in tilt angle, denoted as B22=0;

[0145] When Δθm(ti, Am)>Δθ0, the second evaluation unit evaluates the increased tilt angle in the simulation as the increased tilt angle of danger, denoted as B22=1;

[0146] When Vθm(ti)≤Vθ0, the second evaluation unit evaluates the simulated tilt angle increase rate as the safe tilt angle increase rate, denoted as B23=0;

[0147] When Vθ(ti)>Vθ0, the second evaluation unit evaluates the simulated tilt angle increase rate as the dangerous tilt angle increase rate, denoted as B23=1;

[0148] The second evaluation result obtained based on the pre-set evaluation model is:

[0149]

[0150] The first evaluation unit of the evaluation module conducts a safety assessment of the wind turbine in six dimensions—tower stress, foundation stress, foundation pressure, tower tilt angle, increased tilt angle, and rate of increase of tilt angle—based on real-time monitoring data. The second evaluation unit conducts a safety assessment of the wind turbine in each unit of time in the future based on the six dimensions—tower stress, foundation stress, foundation pressure, tower tilt angle, increased tilt angle, and rate of increase of tilt angle—under weather forecast information. This improves the dimensionality of the monitoring system's assessment of the safety of offshore wind turbines, making the assessment results more accurate and reliable.

[0151] like Figure 6 As shown, specifically, the alarm module includes a first alarm unit 701 and a second alarm unit 702, wherein the first alarm unit is used to determine whether to trigger an alarm and the alarm level based on the first evaluation result, including:

[0152] When (A11=0 and A12=0 and A13=0) and (B21=0 and B22=0 and B23=0), the first alarm unit shuts off the alarm;

[0153] When (A11=1 or A12=1 or A13=1) and (B21=0 and B22=0 and B23=0), the first alarm unit determines the alarm level as a first-level emergency alarm;

[0154] When (A11=1 or A12=1 or A13=1) and (B21=1 or B22=1 or B23=1), the first alarm unit determines the alarm level as a level two emergency alarm.

[0155] Specifically, the second alarm unit is used to determine whether to trigger an alarm and the alarm level based on the second assessment result, including:

[0156] When (B11=0 and B12=0 and B13=0) and (B21=0 and B22=0 and B23=0), the second alarm unit shuts off the alarm;

[0157] When (B11=1 or B12=1 or B13=1) and (B21=0 and B22=0 and B23=0), the second alarm unit determines the alarm level as a level one predictive alarm;

[0158] When (B11=1 or B12=1 or B13=1) and (B21=1 or B22=1 or B23=1), the second alarm unit determines the alarm level as a level two predictive alarm.

[0159] The alarm module's first alarm unit alarms the wind turbine's real-time operating status based on the first assessment result, and the second alarm unit alarms the wind turbine's estimated operating status for each unit of time in the future based on the first assessment result, making the monitoring system's alarms more timely.

[0160] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0161] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An offshore wind turbine generator unit intelligent power monitoring system, characterized by, The method comprises the following steps: a collecting module is configured to collect first monitoring data at a set time interval through a plurality of monitoring devices arranged on the offshore wind turbine; an acquisition module is connected to the collecting module and configured to receive the first monitoring data sent by the collecting module and obtain meteorological forecast information of the offshore wind farm through a meteorological observation station; a processing module is connected to the acquisition module and configured to compare the actual time interval of the data received by the acquisition module with the set time interval of the collecting module to determine abnormal first monitoring data, adjust delayed first monitoring data according to a comparison method, correct missing first monitoring data according to an interpolation method, and obtain second monitoring data; a numerical simulation module is connected to the processing module and configured to divide the meteorological forecast information into a plurality of unit time meteorological forecast information, establish a wind field numerical model according to each unit time meteorological forecast information, and generate a simulated wind energy distribution of the offshore wind farm corresponding to each unit time; a calculation module is connected to the processing module and the numerical simulation module and configured to calculate a predicted inclination of the offshore wind turbine according to a pre-set wind turbine angle-stress relationship model and the simulated wind energy distribution of the offshore wind farm corresponding to each unit time, calculate a real-time inclination increase rate according to the inclination increased at the i th moment compared with the (i-1) th moment under the second monitoring data, and calculate a predicted inclination increase rate according to the predicted inclination increased at the i th moment compared with the (i-1) th moment under the simulated wind energy distribution; an evaluation module is connected to the calculation module and configured to compare the second monitoring data with pre-set standard monitoring data, compare the real-time inclination increase rate calculated according to the inclination increased at the i th moment compared with the (i-1) th moment with a pre-set standard inclination increase rate to obtain a first evaluation result, and compare the simulated tower stress, simulated foundation stress, and simulated foundation pressure under the i th moment simulated wind energy distribution with the pre-set standard monitoring data, and compare the predicted inclination increase rate calculated according to the predicted inclination increased at the i th moment compared with the (i-1) th moment with the pre-set standard inclination increase rate to obtain a second evaluation result; an alarm module is connected to the evaluation module and configured to determine whether to alarm and the alarm level according to the first evaluation result and the second evaluation result.

2. The offshore wind turbine intelligent power monitoring system of claim 1, wherein, The several monitoring devices include a tower stress sensor, a foundation stress sensor, a foundation pressure sensor, an inclination sensor, and a real-time wind direction and speed monitor; the first monitoring data includes first tower stress data, first foundation stress data, first foundation pressure data, and first inclination data, and first real-time wind direction and first real-time wind speed; wherein the tower stress sensor is arranged on the offshore wind tower to monitor the wind force received by the tower, and the first tower stress data is the monitoring data of the tower stress sensor; the foundation stress sensor is arranged on the offshore wind foundation to monitor the seawater impact stress received by the wind foundation, and the first foundation stress data is the monitoring data of the foundation stress sensor; the foundation pressure sensor is arranged on the offshore wind foundation to monitor the pressure of seawater received by the wind foundation, and the first foundation pressure data is the monitoring data of the foundation pressure sensor; the inclination sensor is arranged on the offshore wind tower to monitor the inclination of the tower, and the first inclination data is the monitoring data of the inclination sensor; and the real-time wind direction and speed monitor is arranged on the offshore wind turbine monitoring platform to monitor the real-time wind direction and real-time wind speed of the offshore wind farm, and the first real-time wind direction and the first real-time wind speed are the monitoring data of the real-time wind direction and speed monitor.

3. The offshore wind turbine intelligent power monitoring system of claim 2, wherein, The processing module includes a judging unit and a correction unit, wherein, The judging unit is configured to compare the actual time interval ΔTh of the data received by the acquisition module with the time interval ΔTc set by the collection module to judge abnormal first monitoring data; the abnormal first monitoring data is delayed first monitoring data or missing first monitoring data; When ΔTh = ΔTc, the judging unit judges that the first monitoring data received by the acquisition module is normal first monitoring data; When ΔTc < ΔTh ≤ 2 × ΔTc, the judging unit judges that the first monitoring data received by the acquisition module is delayed first monitoring data; When ΔTh > 2 × ΔTc, the judging unit judges that the first monitoring data received by the acquisition module is missing first monitoring data; The correction unit is configured to adjust the delayed first monitoring data to corrected first monitoring data according to a comparison method, and correct the missing first monitoring data according to an interpolation method to obtain corrected first monitoring data, and the corrected first monitoring data is second monitoring data; the second monitoring data includes second tower stress data, second foundation stress data, second foundation pressure data, and second inclination data, and second real-time wind direction and second real-time wind speed.

4. The offshore wind turbine intelligent power monitoring system of claim 3, wherein, The numerical simulation module includes a division unit and a generation unit, wherein, The division unit divides the weather forecast information into a plurality of unit time weather forecast information, and the unit time weather forecast information includes unit time wind direction forecast information, unit time wind speed forecast information, and unit time temperature forecast information; The generation unit performs offshore wind farm wind energy flow field calculation on the unit time wind direction prediction information, the unit time wind speed prediction information, the unit time temperature prediction information, the regional coordinates of the offshore wind farm, and the regional inversion temperature influence coefficient of the offshore wind farm on the offshore wind shear and generates a corresponding simulation wind energy distribution of the offshore wind farm for each unit time; the simulation wind energy distribution includes simulation wind direction, simulation wind speed, and simulation temperature.

5. The offshore wind turbine intelligent power monitoring system of claim 4, wherein, The calculation module includes a first calculation unit and a second calculation unit, wherein the first calculation unit is configured to calculate the estimated inclination angle of the offshore wind turbine according to a pre-set wind turbine angle-stress relationship model and the simulation wind energy distribution of the offshore wind farm, and includes: The first computing unit is previously set with the wind turbine angle-stress relationship model. , Wherein θ(ti, A11) is the inclination angle at the i-th moment under the second real-time wind direction A11, θ(t(i-1), A11) is the inclination angle at the (i-1)-th moment under the second real-time wind direction A11, Δθ(ti, A11) is the inclination angle increased at the i-th moment than at the (i-1)-th moment under the second real-time wind direction A11, F11 is the second tower stress, F22 is the second foundation stress, F33 is the second foundation pressure, b1(V11) is the first correction coefficient under the second real-time wind speed V11, b2(V11) is the second correction coefficient under the second real-time wind speed V11, b3(V11) is the third correction coefficient under the second real-time wind speed V11, and λ is the correction coefficient of the inclination angle increased at the i-th moment than at the (i-1)-th moment under the second real-time wind direction A11; The data of the simulation wind energy distribution is taken as known condition data of the wind turbine angle-stress relationship model to calculate the estimated inclination angle at any moment under the simulation wind direction and simulation wind speed: where θm(ti, Am) is the estimated inclination at the i-th time under the simulated wind direction Am, θm(t(i-1), Am) is the estimated inclination at the (i-1)-th time under the simulated wind direction Am, Δθm(ti, Am) is the estimated inclination increased at the i-th time than at the (i-1)-th time under the simulated wind direction Am, F1m is the simulated tower stress under the simulated wind speed, F2m is the simulated foundation stress under the simulated wind speed, F3m is the simulated foundation pressure under the simulated wind speed, b1(Vm) is the simulated first correction coefficient under the simulated wind speed Vm, b2(Vm) is the simulated second correction coefficient under the simulated wind speed Vm, b3(Vm) is the simulated third correction coefficient under the simulated wind speed Vm, and λm is the correction coefficient of the estimated inclination increased at the i-th time than at the (i-1)-th time under the simulated wind direction Am.

6. The offshore wind turbine intelligent power monitoring system of claim 5, wherein, The second calculation unit is configured to calculate the real-time inclination angle increase rate according to the inclination angle increased at the i-th moment than at the (i-1)-th moment under the second real-time wind direction A11, and calculate the estimated inclination angle increase rate according to the estimated inclination angle increased at the i-th moment than at the (i-1)-th moment under the simulation wind direction Am, and includes: The inclination angle increased at the i-th moment than at the (i-1)-th moment under the second real-time wind direction A11 is Δθ(ti, A11)=θ(ti, A11)-θ(t(i-1), A11), and the real-time inclination angle increase rate is calculated as Vθ(ti)=Δθ(ti, A11) / (ti-t(i-1)); The estimated inclination angle increased at the i-th moment than at the (i-1)-th moment under the simulation wind direction Am is Δθm(ti, Am)=θm(ti, Am)-θm(t(i-1), Am), and the estimated inclination angle increase rate is calculated as Vθm(ti)=Δθm(ti, Am) / (ti-t(i-1)).

7. The offshore wind turbine intelligent power monitoring system of claim 6, wherein, The evaluation module includes a first evaluation unit and a second evaluation unit, wherein The first evaluation unit is configured to obtain a first evaluation result by comparing the real-time second monitoring data with the preset standard monitoring data and comparing a real-time inclination increase rate calculated according to the inclination at the ith moment and the inclination at the (i-1)th moment with a preset standard inclination increase rate, and comprises: The evaluation module is configured to preset a standard tower stress F10, a standard foundation stress F20, a standard foundation pressure F30, a standard inclination θ0, a standard increased inclination Δθ0, and a standard inclination increase rate Vθ0. When F11 is less than or equal to F10, the first evaluation unit evaluates that the second tower stress is a safe stress, recorded as A111=0. When F11 is greater than F10, the first evaluation unit evaluates that the second tower stress is a dangerous stress, recorded as A111=1. When F22 is less than or equal to F20, the first evaluation unit evaluates that the second foundation stress is a safe stress, recorded as A12=0. When F22 is greater than F20, the first evaluation unit evaluates that the second foundation stress is a dangerous stress, recorded as A12=1. When F33 is less than or equal to F30, the first evaluation unit evaluates that the second foundation pressure is a safe stress, recorded as A13=0. When F33 is greater than F30, the first evaluation unit evaluates that the second foundation pressure is a dangerous stress, recorded as A13=1. When θ(ti, A11) is less than or equal to θ0, the first evaluation unit evaluates that the second inclination is a safe inclination, recorded as A21=0. When θ(ti, A11) is greater than θ0, the first evaluation unit evaluates that the second inclination is a safe inclination, recorded as A21=1. When Δθ(ti, A11) is less than or equal to Δθ0, the first evaluation unit evaluates that the increased inclination is a safe increased inclination, recorded as A22=0. When Δθ(ti, A11) is greater than Δθ0, the first evaluation unit evaluates that the increased inclination is a dangerous increased inclination, recorded as A22=1. When Vθ(ti) is less than or equal to Vθ0, the first evaluation unit evaluates that the real-time inclination increase rate is a safe inclination increase rate, recorded as A23=0. When Vθ(ti) is greater than Vθ0, the first evaluation unit evaluates that the real-time inclination increase rate is a dangerous inclination increase rate, recorded as A23=1. According to the pre-set evaluation model, a first evaluation result is P1= .

8. The offshore wind turbine intelligent power monitoring system of claim 7, wherein, The second evaluation unit is configured to obtain a second evaluation result by comparing a simulated tower stress, a simulated foundation stress, and a simulated foundation pressure under a simulated wind energy distribution at the ith moment with the preset standard monitoring data and comparing a predicted inclination increase rate calculated according to an increased predicted inclination at the ith moment and an increased predicted inclination at the (i-1)th moment with the preset standard inclination increase rate, and comprises: When F1m is less than or equal to F10, the second evaluation unit evaluates that the simulated tower stress is a safe stress, recorded as B11=0. When F1m is greater than F10, the second evaluation unit evaluates that the simulated tower stress is a dangerous stress, recorded as B11=1. When F2m is less than or equal to F20, the second evaluation unit evaluates that the simulated foundation stress is a safe stress, recorded as B12=0. When F2m>F20, the second evaluation unit evaluates the simulated basic stress as a dangerous stress, denoted as B12=1; When F3mF30, the second evaluation unit evaluates the simulated basic stress as a dangerous stress, denoted as B13=1; When F3mF30, the second evaluation unit evaluates the simulated basic stress as a dangerous stress, denoted as B13=1; When θm(ti, Am)≤θ0, the second evaluation unit evaluates the estimated inclination as a safe inclination, denoted as B21=0; When θm(ti, Am)≤θ0, the second evaluation unit evaluates the estimated inclination as a safe inclination, denoted as B21=0; When Δθm(ti, Am)≤Δθ0, the second evaluation unit evaluates the increased estimated inclination as a safe increased inclination, denoted as B22=0; When Δθm(ti, Am)≤Δθ0, the second evaluation unit evaluates the increased estimated inclination as a safe increased inclination, denoted as B22=0; When Vθm(ti)≤Vθ0, the second evaluation unit evaluates the estimated inclination increasing rate as a safe inclination increasing rate, denoted as B23=0; When Vθm(ti)≤Vθ0, the second evaluation unit evaluates the estimated inclination increasing rate as a safe inclination increasing rate, denoted as B23=0; According to the pre-set evaluation model, a second evaluation result P2 is obtained .

9. The offshore wind turbine intelligent power monitoring system of claim 8, wherein, The alarm module comprises a first alarm unit and a second alarm unit, wherein the first alarm unit is used to determine whether to alarm and an alarm level according to the first evaluation result, comprising: When (A111=0 and A12=0 and A13=0) and (A21=0 and A22=0 and A23=0), the first alarm unit is closed; When (A111=1 or A12=1 or A13=1) and (A21=0 and A22=0 and A23=0), the first alarm unit determines that the alarm level is a first-level emergency alarm; When (A111=1 or A12=1 or A13=1) and (A21=1 or A22=1 or A23=1), the first alarm unit determines that the alarm level is a second-level emergency alarm.

10. The offshore wind turbine intelligent power monitoring system of claim 9, wherein, The second alarm unit is used to determine whether to alarm and an alarm level according to the second evaluation result, comprising: When (B11=0 and B12=0 and B13=0) and (B21=0 and B22=0 and B23=0), the second alarm unit is closed; When (B11=1 or B12=1 or B13=1) and (B21=0 and B22=0 and B23=0), the second alarm unit determines that the alarm level is a first-level prediction alarm; When (B11=1 or B12=1 or B13=1) and (B21=1 or B22=1 or B23=1), the second alarm unit determines that the alarm level is a second-level prediction alarm.

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