Floating fan motion monitoring system and method based on environment prediction correction

Abstract

The invention discloses a floating type fan motion monitoring system and method based on environment prediction and correction, and belongs to the technical field of offshore floating type wind power. The system predicts and corrects monitoring data of an internal environment sensor of a wind power plant and monitoring data of a sensor of a peripheral floating type fan through transmission and superposition of waves; and sensorless motion monitoring of the floating fan in the wind power plant is realized. The device and the method can effectively reduce the use of a wind power plant motion monitoring sensor and reduce the equipment cost.

Description

Technical Field

[0001] The present invention relates to the technical field of offshore floating wind power, and in particular to a floating wind turbine motion monitoring system and method in a floating wind farm based on environmental prediction and correction. Background Art

[0002] According to the Global Wind Energy Council (GWEC), floating offshore wind power will enter the gigawatt-level commercial installation stage from 2026, and by 2030, the global floating offshore wind power installed capacity will reach 16.5 million kilowatts. Floating offshore wind farms have broad development prospects. In the complex marine environment, floating wind turbines are subject to the irregular coupling of wind, waves and currents for a long time, and their survival faces huge challenges. It is necessary to monitor the operating status of floating wind turbines throughout their life cycle.

[0003] At present, floating wind turbines use a complete set of sensor monitoring systems to monitor the operation of wind turbines, floating bodies and moorings. By processing the monitoring data over a period of time, the overall dynamic response of floating offshore wind power is analyzed, and the floating unit is kept in a relatively stable power generation state by changing the wind turbine pitch or adjusting the basic floating posture.

[0004] For floating wind farms with high electricity costs, multiple sensor monitoring systems will bring additional costs. In addition, the data monitored by the floating wind turbines themselves is not conducive to the control system's timely response to harsh environments. Summary of the invention

[0005] In view of the problems existing in the prior art, the present disclosure provides a floating wind turbine motion monitoring system for a floating wind farm based on environmental prediction and correction, so as to realize the monitoring of the wind farm environment and the motion of the peripheral wind turbines;

[0006] At the same time, the present disclosure also provides a floating wind turbine motion monitoring method for a floating wind farm, which realizes sensorless motion monitoring of the floating wind turbines inside the wind farm by predicting and correcting the monitoring data of the internal environmental sensors of the wind farm and the sensors of the peripheral floating wind turbines themselves.

[0007] The above-mentioned floating wind farm includes: a plurality of wind turbines and a plurality of semi-submersible platforms for installing the wind turbines, wherein the wind turbines are installed on the middle column or the side column of the semi-submersible platform, and the semi-submersible platform is connected to the seabed through a mooring device.

[0008] The floating wind turbine motion monitoring system based on environmental prediction and correction provided by the present disclosure includes: an environmental measurement device, an information transmission and control center; wherein:

[0009] The environmental measurement device includes: a wind measuring device and a wave sensor, wherein:

[0010] The wind measuring device is installed on the top of the wind turbine nacelle to measure the size and direction of wind speed;

[0011] The wave sensors include fixed wave sensors and floating wave sensors. The fixed wave sensors are installed on the side columns of the semi-submersible platforms of the wind turbines outside the wind farm, and the floating wave sensors are installed between the wind turbines inside the wind farm. Both are used to measure wave parameters.

[0012] The information transmission and control center is used to receive the data from the environmental measurement device, and based on the wave transmission and superposition principle, perform correction calculations on the wind and wave parameters in the wind farm, and then correspond the calculation results to the wind turbine motion response data under preset full-operating wind and wave conditions to obtain the motion state of the floating wind turbine in the wind farm under the current wind and wave conditions.

[0013] Furthermore, the wind measuring device adopts a wind measuring radar.

[0014] Furthermore, the system also includes: a six-degree-of-freedom inclination and acceleration sensor for measuring the movement of the semi-submersible platform in six directions.

[0015] The present disclosure provides a floating wind turbine motion monitoring method using the above system, comprising the following steps:

[0016] S1, obtaining the wind and wave parameters at the location of the sensor through the environmental measurement device; then based on the wave transmission and superposition principle, using the monitoring data of the floating wave sensor inside the wind farm and the peripheral fixed wave sensor, correcting and calculating the wind and wave parameters at the target wind turbine location;

[0017] S2, the calculated wind and wave parameters of the target wind turbine position are matched to the preset floating wind turbine motion response data under full-operating wind and wave conditions to obtain the motion state of the floating wind turbine in the wind farm under the current wind and wave conditions.

[0018] Furthermore, the step S1 specifically includes:

[0019] S11, using a wind measuring device to obtain wind resource parameters of the wind farm at time t0;

[0020] S12, using a fixed wave sensor to obtain wave parameters at time t0 outside the wind farm;

[0021] S13, calculating the time △t1 that the wave takes to pass from the periphery of the wind farm to the floating wave sensor between the internal wind turbines according to the distance L1 between the fixed wave sensor and the floating wave sensor and the wave speed;

[0022] S14, obtaining the parameters of the internal waves of the wind farm at time t0+△t1 through monitoring by floating wave sensors between the internal wind turbines;

[0023] S15, calculating the attenuation coefficient of the wave inside the wind farm after the wave has passed through the periphery of the wind farm for a period of time △t1;

[0024] S16, calculating the time △t2 for the wave to pass from the floating wave sensor to the target aircraft position according to the distance L2 between the floating wave sensor and the target aircraft position and the wave speed;

[0025] S17, considering the above attenuation coefficient, according to the wave transmission and superposition principle, the wind and wave parameters at the target wind turbine position at time t0+△t1+△t2 are obtained.

[0026] Furthermore, the specific method of step S17 includes:

[0027] For N waves superimposed at the same point, the displacement of each wave can be expressed as:

[0028] y i =A i sin(k i x-ω i t+φ i )

[0029] Among them, i ranges from 1 to N, indicating the i-th wave, A i is the amplitude of the ith wave, k i is the wave number, ω i is the angular frequency, φ i is the phase difference, x is the position, and t is the time;

[0030] The total displacement y after the superposition of N waves is the sum of the displacements of all single waves:

[0031]

[0032] If the frequency of each wave is the same, that is, ω1=ω2=...=ω N , we use trigonometric identities to convert the above sum into a single sine function, namely:

[0033] (1) Expand the sine function of each term into a complex exponential form:

[0034]

[0035] (2) Add all the terms:

[0036]

[0037] (3) Convert the sum into complex form:

[0038]

[0039]

[0040] (4) Convert the complex form back to real form:

[0041] y=|Y|sin(kx-ωt+ψ)

[0042] Here, |Y| is the amplitude of the final wave and ψ is the phase of the final wave.

[0043] Furthermore, the step S2 specifically includes:

[0044] S21, using the parameters of the wind turbine, the semi-submersible platform, and the mooring system of the floating wind turbine, by numerical calculation or actual measurement, the motion response of the floating wind turbine in all directions under the combined action of wind and waves in all working conditions is obtained in advance;

[0045] S22, comparing the wind resource data and wave data obtained in step S1 with the wind and wave conditions of the floating wind turbine motion response data under all working conditions obtained in step S21, to obtain the motion state of the floating wind turbine in the wind farm under the current wind and wave conditions.

[0046] Furthermore, the motion responses of the floating wind turbine in various directions include: the motion responses of the floating wind turbine in one or more directions of surge, sway, heave, roll, pitch, and bow.

[0047] Compared with the prior art, the beneficial effects of the present invention are: (1) providing a floating wind turbine motion monitoring method for a floating wind farm, which realizes sensorless motion monitoring of floating wind turbines in the wind farm by predicting and correcting the monitoring data of floating wave sensors inside the wind farm and sensors of peripheral floating wind turbines themselves; (2) reducing the use of motion monitoring sensors and reducing equipment costs; (3) by processing the wind wave and current monitoring data in advance and predicting the motion response of the target wind turbine in advance, control strategies can be made in advance for environmental changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The above and other objects, features and advantages of the present disclosure will become more apparent through a more detailed description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present disclosure.

[0049] Figure 1 This is the overall schematic diagram of the wind turbines outside the wind farm;

[0050] Figure 2 This is the overall schematic diagram of wind turbines inside the wind farm;

[0051] Figure 3 is an overall schematic diagram of an exemplary wind farm (taking 9 wind turbines as an example);

[0052] Figure 4 The following is a flow chart of a method for monitoring wind turbine motion in a wind farm according to the present disclosure;

[0053] Figure 5 This is an example of the motion response of a floating wind turbine in six directions under the combined action of wind and waves in all working conditions, where a is the surge direction, b is the sway direction, c is the heave direction, d is the roll direction, e is the pitch direction, and f is the bow pitch direction. DETAILED DESCRIPTION

[0054] The preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the preferred embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0055] The present disclosure provides a floating wind turbine motion monitoring system and method based on environmental prediction and correction, which are applied to a floating wind farm.

[0056] According to an exemplary embodiment of the present disclosure:

[0057] The wind farm consists of 9 floating wind turbines. Figure 1-3 As shown, the wind turbines are arranged in 3*3 configurations; relative to the main wave direction, 1, 2, 3, 4, 6, 7, and 9# wind turbines are arranged outside the wind farm, and 5 and 8# wind turbines are arranged inside the wind farm;

[0058] Each floating wind turbine is set up on a relatively independent semi-submersible platform; the wind turbine is installed on the middle column of the semi-submersible platform, with a capacity of 5MW;

[0059] The mooring system of each semi-submersible platform consists of three mooring chains, one end of which is connected to the seabed through an anchor pile, and the other end is connected to the semi-submersible platform. The semi-submersible platform is connected to the seabed through three anchor chains and anchor piles.

[0060] The motion monitoring system for the floating wind farm includes: sensor devices, information transmission and control center. Among them:

[0061] Sensor types include wind radar and wave sensors, among which:

[0062] The wind radar is installed on the top of the wind turbine nacelle to measure the size and direction of wind speed;

[0063] Wave sensors are divided into fixed wave sensors and floating wave sensors. Fixed wave sensors are installed on the side columns of the semi-submersible platform of the wind turbines outside the wind farm (such as the 1# wind turbine), and floating wave sensors are installed between the wind turbines in the wind farm (such as between the 1# and 5# wind turbines). Both are used to measure wave parameters (wave direction, wave period, wave height, flow velocity).

[0064] The information transmission and control center is used to receive and analyze various sensor data.

[0065] For the sensorless motion monitoring method of floating wind turbines in the wind farm, the process is as follows: Figure 4 As shown, it mainly includes the following steps:

[0066] 1. First, the wind resource parameters (wind speed and wind direction) of the wind farm at time t0 are obtained through wind radar monitoring;

[0067] 2. The wave parameters (wave direction, wave period, wave height, wave speed, and flow rate) at the periphery of the wind farm at time t0 are obtained through the fixed wave sensor on the periphery No. 1 wind turbine, and the information transmission and control center analyzes the wave components;

[0068] 3. According to the distance L1 between the fixed wave sensor and the floating wave sensor and the wave speed at time t0, calculate the time △t1 for the wave to be transmitted from the 1# wind turbine to the floating wave sensor between the 1# and 5# wind turbines;

[0069] 4. The internal wave t of the wind farm is obtained by monitoring the floating wave sensor between the 1# and 5# wind turbines. 0+ The parameters at time △t1 (wave direction, wave period, wave height, flow velocity), the information transmission and control center analyzes the wave components; at the same time, the attenuation coefficient of the wave inside the wind farm after the wave passes through the periphery of the wind farm at the time △t1 is calculated;

[0070] 5. According to the distance L2 between the floating wave sensor and the 5# target machine position and the wave speed, the time △t2 for the wave to be transmitted from the floating wave sensor to the 5# wind turbine is calculated. Considering the above attenuation coefficient, the wind and wave parameters at the target wind turbine position are obtained according to the wave transmission and superposition principle.

[0071] The principle of wave transmission and superposition is as follows:

[0072] If N waves are superimposed at the same point, the displacement of each wave can be expressed as:

[0073] y i =A i sin(k i x-ω i t+φ i )

[0074] Among them, i ranges from 1 to N, indicating the i-th wave, A i is the amplitude of the ith wave, k i is the wave number, ω i is the angular frequency, φ i is the phase difference, x is the position, and t is the time;

[0075] The total displacement y after the superposition of N waves is the sum of the displacements of all single waves:

[0076]

[0077] If the frequency of each wave is the same, that is, ω1=ω2=...=ω N , we use trigonometric identities to convert the above sum into a single sine function, namely:

[0078] (1) Expand the sine function of each term into a complex exponential form:

[0079]

[0080] (2) Add all the terms:

[0081]

[0082] (3) Convert the sum into complex form:

[0083]

[0084]

[0085] (4) Convert the complex form back to real form:

[0086] y=|Y|sin(kx-ωt+ψ)

[0087] Here, Y| is the amplitude of the final wave and ψ is the phase of the final wave.

[0088] 6. Based on the parameters of the wind turbine, semi-submersible platform and mooring system of the 5MW floating wind turbine, the motion responses of the floating wind turbine in six directions, namely, sway, heave, pitch, roll and bow, are obtained through numerical calculation or actual measurement under the combined action of wind and waves in all working conditions. Figure 5 As shown;

[0089] The actual measurement can be completed by installing six-degree-of-freedom inclination and acceleration sensors on the outer semi-submersible platform to measure the movement of the platform in six directions.

[0090] 7. Using the wind resource data measured by the wind radar at the above-mentioned 5# position and the wave data analyzed and predicted in step 5 as the working conditions, and comparing them with the motion response results numerically calculated in step 6, the motion state prediction of the floating wind turbine in the wind farm under the current wind and wave conditions can be obtained.

[0091] The above technical scheme is only an exemplary embodiment of the present invention. For those skilled in the art, it is easy to make various types of improvements or modifications based on the application methods and principles disclosed in the present invention, and it is not limited to the method described in the above specific embodiment of the present invention. Therefore, the method described above is only preferred and does not have a restrictive meaning.

Claims

1. A floating wind turbine motion monitoring system based on environmental prediction and correction, comprising: Environmental measurement equipment, information transmission and control center; including: The environmental measurement device includes: a wind measuring device and a wave sensor, wherein: The wind measuring device is installed on the top of the wind turbine nacelle to measure the size and direction of wind speed; The wave sensors include fixed wave sensors and floating wave sensors. The fixed wave sensors are installed on the side columns of the semi-submersible platforms of the wind turbines outside the wind farm, and the floating wave sensors are installed between the wind turbines inside the wind farm. Both are used to measure wave parameters. The information transmission and control center is used to receive the data from the environmental measurement device, and based on the wave transmission and superposition principle, perform correction calculations on the wind and wave parameters in the wind farm, and then correspond the calculation results to the wind turbine motion response data under preset full-operating wind and wave conditions to obtain the motion state of the floating wind turbine in the wind farm under the current wind and wave conditions.

2. The system according to claim 1, characterized in that The wind measuring device adopts a wind measuring radar.

3. The system according to claim 1 or 2, characterized in that: Also includes: Six-degree-of-freedom inclination and acceleration sensors are used to measure the movement of the semi-submersible platform in six directions.

4. A method for monitoring the motion of a floating wind turbine based on environmental prediction correction according to any one of claims 1 to 3, comprising the following steps: S1, obtaining the wind and wave parameters at the location of the sensor through the environmental measurement device; then based on the wave transmission and superposition principle, using the monitoring data of the fixed wave sensors outside the wind farm and the internal floating wave sensors, correcting and calculating the wind and wave parameters at the target wind turbine location; S2, the calculated wind and wave parameters of the target wind turbine position are matched to the preset floating wind turbine motion response data under full-operating wind and wave conditions to obtain the motion state of the floating wind turbine in the wind farm under the current wind and wave conditions.

5. The method according to claim 4, characterized in that The step S1 specifically includes: S11, using a wind measuring device to obtain wind resource parameters of the wind farm at time t0; S12, using a fixed wave sensor to obtain wave parameters at time t0 outside the wind farm; S13, calculating the time △t1 that the wave takes to pass from the periphery of the wind farm to the floating wave sensor between the internal wind turbines according to the distance L1 between the fixed wave sensor and the floating wave sensor and the wave speed; S14, obtaining the parameters of the internal waves of the wind farm at time t0+△t1 through monitoring by floating wave sensors between the internal wind turbines; S15, calculating the attenuation coefficient of the wave inside the wind farm after the wave has passed through the periphery of the wind farm for a period of time △t1; S16, calculating the time △t2 for the wave to pass from the floating wave sensor to the target aircraft position according to the distance L2 between the floating wave sensor and the target aircraft position and the wave speed; S17, considering the above attenuation coefficient, according to the wave transmission and superposition principle, the wind and wave parameters at the target wind turbine position at time t0+△t1+△t2 are obtained.

6. The method according to claim 5, characterized in that The specific method of step S17 includes: For N waves superimposed at the same point, the displacement of each wave can be expressed as: y i =A i sin(k i x-y i t+φ i ) Among them, i ranges from 1 to N, indicating the i-th wave, A i is the amplitude of the ith wave, k i is the wave number, ω i is the angular frequency, φ i is the phase difference, x is the position, and t is the time; The total displacement y after the superposition of N waves is the sum of the displacements of all single waves: If the frequency of each wave is the same, that is, ω1=ω2=...=ω N , we use trigonometric identities to convert the above sum into a single sine function, namely: (1) Expand the sine function of each term into a complex exponential form: (2) Add all the terms: (3) Convert the sum into complex form: and=|Y|e iψ (4) Convert the complex form back to real form: y=|Y|sin(kx-ωt+ψ) Here, |Y| is the amplitude of the final wave and ψ is the phase of the final wave.

7. The method according to any one of claims 4 to 6, characterized in that: The step S2 specifically includes: S21, using the parameters of the wind turbine, the semi-submersible platform, and the mooring system of the floating wind turbine, by numerical calculation or actual measurement, the motion response of the floating wind turbine in all directions under the combined action of wind and waves in all working conditions is obtained in advance; S22, comparing the wind resource data and wave data obtained in step S1 with the wind and wave conditions of the floating wind turbine motion response data under all working conditions obtained in step S21, to obtain the motion state of the floating wind turbine in the wind farm under the current wind and wave conditions.

8. The method according to claim 7, characterized in that The motion responses of the floating wind turbine in various directions include: the motion responses of the floating wind turbine in one or more directions of surge, sway, heave, roll, pitch and bow.

Images