Adaptive Method for Blue Carbon Capture and Regulation of Ecological Floating Islands Driven by Offshore Wind Power

Abstract

The present invention relates to the technical field of marine ecological environment regulation, and specifically relates to an adaptive method for blue carbon capture and regulation of an ecological floating island driven by offshore wind power, comprising the following steps: S1: Obtain the flow velocity gradient, chlorophyll a concentration, and dissolved inorganic carbon content of the target sea area, and collect the spindle torque fluctuation data of the wind power device; S2: Calculate the carbon flux threshold per unit area of the floating island; S3: Generate an adjustment instruction for the matrix permeability of the floating island according to the carbon flux threshold; S4: Trigger the salinity gradient power generation module to generate compensatory electric energy; S5: Use the compensatory electric energy to activate the microfluidic chip and control the opening and closing frequency of the mangrove stomata; S6: Dynamically correct the distribution of the counterweight blocks of the floating island to stabilize the blue carbon deposition rate within the target range. In the present invention, through the real-time integration of wind power energy prediction, carbon flux calculation, and floating island adaptive structure regulation, the efficient and stable operation of the floating island during the blue carbon capture process in a complex marine environment is achieved, thereby significantly improving the carbon fixation efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of marine ecological environment regulation, and particularly to an adaptive method for blue carbon capture and regulation of an ecological floating island driven by offshore wind power. Background Art

[0002] In recent years, the rapid development of the offshore wind power industry has provided important support for the utilization of renewable energy, and at the same time has brought new opportunities for the carbon capture and regulation of the marine ecosystem; the construction of wind farms not only changes the local hydrodynamic conditions, but also affects the distribution pattern of marine primary productivity, making it play a positive role in the blue carbon deposition process under specific conditions; as an important carrier of marine carbon sinks, ecological floating islands can improve the carbon fixation efficiency through the synergistic effect of aquatic plants and microbial communities.

[0003] However, the complexity of the marine environment makes the ecological floating island face multiple challenges during operation, including the uncertain impact of external hydrodynamic changes on the carbon capture ability, the inefficiency of the migration process of dissolved inorganic carbon to the floating island, the restriction of the unstable power supply of wind power on the ecosystem regulation ability, etc.; in addition, the stomatal opening and closing state of plants such as mangroves directly affect the carbon fixation process, and the regulation of stomata needs to adapt to different hydrodynamic environments to ensure the stability of the overall carbon flux of the floating island. Therefore, how to achieve the adaptive control of blue carbon capture and regulation of the ecological floating island under the condition of offshore wind power drive has become a technical problem that needs to be solved urgently at present. Summary of the Invention

[0004] Based on the above purpose, the present invention provides an adaptive method for blue carbon capture and regulation of an ecological floating island driven by offshore wind power.

[0005] The adaptive method for blue carbon capture and regulation of an ecological floating island driven by offshore wind power includes the following steps:

[0006] S1: Real-time obtain the flow velocity gradient, chlorophyll a concentration and dissolved inorganic carbon content of the target sea area through a distributed sensor array, and synchronously collect the main shaft torque fluctuation data of the wind power device;

[0007] S2: Predict the future 5-minute energy supply curve based on the main shaft torque fluctuation data of the wind power, and calculate the carbon flux threshold per unit area of the floating island in combination with the chlorophyll a concentration and the flow velocity gradient;

[0008] S3: Generate a regulation instruction for the matrix permeability of the floating island according to the carbon flux threshold, and use it to control the dynamic adjustment of the pore diameter of the bionic fiber membrane layer in the range of 50 - 200 μm;

[0009] S4: Drive the migration of dissolved inorganic carbon into the floating island through the osmotic pressure difference, and at the same time trigger the salinity gradient power generation module to generate compensated electric energy;

[0010] S5: Activate the microfluidic chip using the compensated electric energy, and control the opening and closing frequency of the mangrove stomata according to the photosynthesis intensity corresponding to the chlorophyll a concentration;

[0011] S6: Dynamically correct the distribution of the floating island counterweight blocks based on the opening and closing frequency of the stomata and the real-time flow velocity gradient data, so that the blue carbon deposition rate is stabilized within the target range.

[0012] Optionally, the specific steps of S1 include:

[0013] S11: Install 3 groups of ultrasonic Doppler profilers circumferentially on the underwater section of the wind power pile foundation. Each group is distributed at an interval of 120°. Synchronously measure the flow velocity vectors of each 0.5 m layer within the water depth range of 0 - 20 m, and calculate the vertical flow velocity gradient through a three-dimensional flow velocity interpolation algorithm;

[0014] S12: Suspendedly deploy a CTD temperature-salinity-depth sensor cluster at a depth of 10 m below the floating island, and measure the chlorophyll a concentration through the fluorescence spectrum with an excitation wavelength of 450 nm and a detection wavelength of 685 nm;

[0015] S13: Embed a microcirculation type infrared spectroscopy detection cavity inside the floating island matrix, make seawater flow through the detection cavity at a flow velocity of 0.2 - 0.5 m / s, and invert the dissolved inorganic carbon content using the characteristic absorption peak intensity at a wavelength of 4300 cm - ¹;

[0016] S14: Arrange a strain gauge array at the connection between the main shaft and the gearbox of the wind power device. This strain gauge array contains 12 groups of strain bridge circuits evenly distributed circumferentially. Synchronously collect the main shaft torque fluctuation data, and at the same time obtain the main shaft rotation speed time series signal through an optoelectronic encoder;

[0017] S15. Transmit the flow velocity gradient, chlorophyll a concentration, dissolved inorganic carbon content, and main shaft torque data obtained in S11 - S14 to the central controller of the floating island through a salt spray corrosion-resistant CAN bus, and use the IEEE 1588 precise time protocol to achieve the timestamp synchronization of multi-source data.

[0018] Optionally, the specific steps of S2 include:

[0019] S21: Use the main shaft torque fluctuation data obtained in S1 as the input variable, and predict the energy supply curve of the wind power device within the next 5 minutes based on a long short-term memory neural network;

[0020] S22: Use the chlorophyll a concentration and vertical flow velocity gradient measured in S1 as input parameters. First, calculate the carbon capture potential value per unit area of the floating island using the chlorophyll a concentration , and the formula is: , where represents the carbon capture potential per unit area of the floating island; represents the chlorophyll a concentration; Represents chlorophyll The conversion coefficient between the concentration and the carbon capture potential, with a value of 0.85;

[0021] S23: Then, combine the average energy supply value of the wind power device predicted in the next 5 minutes obtained from S21 and the carbon capture potential value calculated from S22 to calculate the carbon flux threshold per unit area of the floating island , and the calculation formula is: , where represents the carbon flux threshold per unit area of the floating island; represents the average energy supply value of the wind power device in the next 5 minutes; represents the adjustment coefficient between the energy supply and the carbon flux threshold.

[0022] Optionally, the specific steps of S21 include:

[0023] S211: Divide the main shaft torque fluctuation data measured by S1 into time series segments with a length of 30 seconds and perform normalization processing to obtain the input data sequence ;

[0024] S212: Input the normalized input data sequence into the trained long short-term memory neural network for prediction, and output the energy supply prediction sequence of the wind power device at 10-second intervals in the next 5 minutes ;

[0025] S213: Calculate the arithmetic mean of the energy supply prediction sequence obtained in S212 to obtain the average energy supply value of the wind power device in the next 5 minutes , and the formula is: , where represents the average energy supply value of the wind power device in the next 5 minutes; N represents the number of prediction points in the 5-minute prediction period, with a value of 30; represents the energy supply prediction value corresponding to the i-th prediction moment.

[0026] Optionally, the specific steps of S3 include:

[0027] S31: Compare the carbon flux threshold per unit area of the floating island calculated by S2 with the preset carbon flux target interval value ; when the condition is met, it is determined to be in a low flux state; when the condition is met, it is determined to be in a high flux state; when the condition is met, it is determined to be in a normal flux state;

[0028] S32: Based on the determination result of S31, determine the adjustment direction of the permeability of the floating island matrix; generate an adjustment instruction to increase the permeability in the low flux state, generate an adjustment instruction to decrease the permeability in the high flux state, and generate an adjustment instruction to keep the permeability unchanged in the normal flux state;

[0029] S33: Calculate the target adjustment value of the pore diameter of the bionic fiber membrane layer of the floating island matrix according to the adjustment instruction determined in S32 ;

[0030] S34: According to the target adjustment value of the pore diameter obtained in S33 , combined with the vertical flow velocity gradient measured in S1 , determine the actual pore diameter adjustment rate ;

[0031] S35: Based on the target adjustment value of the pore diameter and the actual pore diameter adjustment rate , generate the corresponding adjustment instruction for the permeability of the floating island matrix.

[0032] Optionally, the specific content of S4 includes:

[0033] S41: Use the pore diameter of the bionic fiber membrane layer of the floating island matrix adjusted by S3 to form an osmotic pressure difference between the seawater outside the floating island and the closed cavity inside the floating island ;

[0034] S42: Under the action of the osmotic pressure difference , the seawater rich in dissolved inorganic carbon outside the floating island migrates into the closed cavity inside the floating island at a flow rate of 0.2 - 0.5 m / s through the pores of the bionic fiber membrane layer, forming a continuous and stable directional inflow;

[0035] S43: When the seawater rich in dissolved inorganic carbon flows through the closed cavity inside the floating island, there are two layers of ion-selective nano membranes preset in the closed cavity inside, and there is a salinity difference between the two layers of ion-selective nano membranes, thus generating a salinity gradient potential difference ;

[0036] S44: Drive the ions in the salinity gradient power generation module to migrate directionally between the selective nano membranes with the salinity gradient potential difference , and then trigger the salinity gradient power generation module to generate compensation electric energy .

[0037] Optionally, the specific content of S5 includes:

[0038] S51: Activate the microfluidic chip with the compensation electric energy obtained in S4. The microfluidic chip contains multiple independently controllable microfluidic channels, and each channel is connected to the stomatal regulator of the mangrove leaves inside the floating island;

[0039] S52: Calculate the corresponding photosynthesis intensity value of the mangrove forest based on the chlorophyll a concentration measured in S1. ;

[0040] S53: Based on the photosynthesis intensity value of the mangrove forest obtained in S52 , calculate the target opening and closing frequency of the stomata of the mangrove forest ;

[0041] S54: Using the microfluidic chip activated in S51, according to the target opening and closing frequency of the stomata of the mangrove forest determined in S53 , adjust the delivery rate of the phytohormone in the microfluidic channel , so as to control the actual opening and closing frequency of the stomata of the mangrove leaves to reach the target value. The specific calculation formula is: , where in the formula, represents the delivery rate of the phytohormone abscisic acid; represents the basic delivery rate of the phytohormone abscisic acid; represents the actual opening and closing frequency of the current stomata of the mangrove forest; represents the adjustment coefficient between the opening and closing frequency of the stomata and the delivery rate of the phytohormone abscisic acid.

[0042] Optionally, the specific content of S6 includes:

[0043] S61: Real-time collect the actual opening and closing frequency of the stomata of the mangrove leaves after control in S5, and obtain the current vertical velocity gradient data measured in S1;

[0044] S62: Compare the actual opening and closing frequency of the stomata collected in S61 with the preset optimal opening and closing frequency threshold of the stomata, and determine the deviation direction and deviation amplitude of the current stomata opening and closing state;

[0045] S63: Based on the deviation direction and amplitude of the stomata opening and closing state determined in S62, determine the target adjustment area of the floating island counterweight, and combine the vertical velocity gradient data obtained in step S61 to determine the specific adjustment direction of the counterweight;

[0046] S64: According to the target adjustment area and direction of the counterweight determined in S63, send adjustment instructions to each independent counterweight driving device of the floating island in real time, and dynamically adjust the position and distribution of each counterweight to actively adjust the attitude and immersion depth of the floating island;

[0047] S65: Feed back the data of the attitude and immersion depth of the floating island after adjustment to the central controller, and combine the current real-time blue carbon deposition rate of the floating island to judge whether it is within the target blue carbon deposition rate range. If not, repeat S61 to S64 for continuous adjustment until the blue carbon deposition rate is stable within the target range.

[0048] Optionally, S62 specifically includes:

[0049] S622: Let the actual stomatal opening and closing frequency be , then the deviation between the actual stomatal opening and closing frequency and the target stomatal opening and closing frequency is expressed as: , where represents the deviation value of the stomatal opening and closing frequency; represents the target opening and closing frequency of the mangrove stomata;

[0050] S623: Based on the calculated deviation of the stomatal opening and closing frequency judge the deviation direction: when > 0, it is judged as the over-opening state of the stomata; when < 0, it is judged as the insufficient-opening state of the stomata; when = 0, it means that the stomatal opening and closing frequency is normal;

[0051] S624: Calculate the normalized deviation value of the stomatal opening and closing frequency deviation ;

[0052] S625: Compare the normalized deviation value calculated in S624 with the preset deviation threshold . If is satisfied, it is determined that the deviation of the current stomatal opening and closing state exceeds the normal range, and the distribution of the floating island counterweight blocks needs to be adjusted; if is satisfied, it is considered that the stomatal opening and closing state is within the acceptable range and no adjustment is required.

[0053] Optionally, S63 specifically includes:

[0054] S631: Based on the normalized stomatal opening and closing frequency deviation value obtained in S62, calculate the offset of the current center of gravity position of the floating island according to the pre-calibrated counterweight adjustment ratio to obtain the corresponding center of gravity offset as the reference value for the preliminary adjustment of the floating island counterweight blocks;

[0055] S632: Combine the vertical velocity gradient data obtained in S61, and determine the specific adjustment direction of the floating island counterweight blocks according to the positive and negative directions of the vertical velocity gradient. If the vertical velocity gradient is positive, it offsets in one direction; if the vertical velocity gradient is negative, it offsets in the opposite direction; thus obtaining the final adjustment direction of the counterweight blocks;

[0056] S633: Combine the center of gravity offset calculated in S631 with the adjustment direction determined in S632, define the target adjustment area of the floating island counterweight blocks, and adapt to different degrees of stomatal deviation values and vertical velocity gradients by enlarging or reducing the range of the area, forming an area range capable of adjusting the counterweight distribution in the horizontal plane;

[0057] S634: Select the optimal adjustment point within the target adjustment area, shift the current center of gravity position of the floating island to this point along the direction determined by S632, and complete the distribution of counterweight blocks.

[0058] Advantages of the present invention:

[0059] In the present invention, by integrating offshore wind power data and multi-parameter sensing data of the floating island, real-time adaptive control of the blue carbon capture and regulation process is achieved; using a distributed sensor array and an LSTM neural network, the wind power energy supply is accurately predicted and the carbon flux threshold is calculated, enabling the floating island to quickly respond to environmental changes and improve the blue carbon capture efficiency.

[0060] In the present invention, through intelligent regulation of the matrix permeability of the floating island, triggering salinity gradient power generation, precisely controlling the stomata of mangroves, and adaptively adjusting the distribution of counterweight blocks, the coordinated optimization of carbon migration, energy compensation, and the attitude of the floating island is achieved, thereby stabilizing the blue carbon deposition rate within the target range; effectively breaking through the traditional passive regulation mode and significantly improving the long-term stability and carbon fixation efficiency of the ecological floating island system. Description of the drawings

[0061] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only those of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0062] Figure 1 Schematic diagram of the adaptive method for blue carbon capture and regulation of the ecological floating island according to the embodiment of the present invention;

[0063] Figure 2 Schematic diagram of the method for dynamically correcting the distribution of counterweight blocks of the floating island according to the embodiment of the present invention. Detailed implementation manners

[0064] The following will describe the present invention in detail with reference to the drawings and specific embodiments. At the same time, it should be noted here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments. For some well-known technologies, those skilled in the art can also adopt other alternative methods for implementation; and the drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0065] As Figure 1 - Figure 2 shown, the adaptive method for blue carbon capture and regulation of the ecological floating island driven by offshore wind power includes the following steps:

[0066] S1: Real-time obtain the flow velocity gradient, chlorophyll a concentration, and dissolved inorganic carbon content of the target sea area through a distributed sensor array, and simultaneously collect the main shaft torque fluctuation data of the wind power device;

[0067] S2: Predict the future 5-minute energy supply curve based on the torque fluctuation data of the wind power spindle, and calculate the carbon flux threshold per unit area of the floating island in combination with the chlorophyll a concentration and the flow velocity gradient;

[0068] S3: Generate an adjustment instruction for the matrix permeability of the floating island according to the carbon flux threshold, which is used to control the dynamic adjustment of the pore diameter of the bionic fiber membrane layer within the range of 50 - 200 μm, where the flow velocity gradient is used to determine the pore adjustment rate;

[0069] S4: Drive the migration of dissolved inorganic carbon into the floating island through the osmotic pressure difference, and at the same time trigger the salinity gradient power generation module to generate compensated electric energy;

[0070] S5: Activate the microfluidic chip with the compensated electric energy, and control the opening and closing frequency of the mangrove stomata according to the photosynthesis intensity corresponding to the chlorophyll a concentration;

[0071] S6: Dynamically correct the distribution of the counterweight blocks of the floating island according to the opening and closing frequency of the stomata and the real-time flow velocity gradient data, so that the blue carbon deposition rate is stabilized within the target range.

[0072] S1 specifically includes:

[0073] S11: Install 3 groups of ultrasonic Doppler profilers circumferentially on the underwater section of the wind power pile foundation. Each group is distributed at an interval of 120°, and synchronously measure the flow velocity vectors of each 0.5 m layer within the water depth range of 0 - 20 m. Calculate the vertical flow velocity gradient through a three-dimensional flow velocity interpolation algorithm; Let the vertical flow velocity gradient be , and the formula is: , where represents the flow velocity at water depth z, represents the water depth at the flow velocity, is the layering interval, with a value of 0.5 m;

[0074] S12: Suspendedly deploy a CTD temperature-salinity-depth sensor cluster at a depth of 10 m below the floating island. This CTD temperature-salinity-depth sensor cluster contains 4 detection units distributed in a regular tetrahedron. Each unit integrates a fluorometer module, and measures the chlorophyll a concentration through the fluorescence spectrum with an excitation wavelength of 450 nm / detection wavelength of 685 nm. Take the moving average of the measurement values of the four units as the output value;

[0075] S13: Embed a micro-flow-through infrared spectroscopy detection cavity inside the matrix of the floating island, make seawater flow through the detection cavity at a flow velocity of 0.2 - 0.5 m / s, and invert the content of dissolved inorganic carbon using the characteristic absorption peak intensity at a wavelength of 4300 cm - ¹;

[0076] S14: Arrange a strain gauge array at the connection between the main shaft of the wind power device and the gearbox. The strain gauge array includes 12 groups of strain bridge circuits evenly distributed circumferentially, synchronously collect the main shaft torque fluctuation data, and at the same time obtain the main shaft speed time series signal through an optoelectronic encoder;

[0077] S15. Transmit the flow velocity gradient, chlorophyll a concentration, dissolved inorganic carbon content, and main shaft torque data obtained in S11 - S14 to the floating island central controller through a salt spray corrosion-resistant CAN bus, and use the IEEE 1588 precise time protocol to achieve the timestamp synchronization of multi-source data; Through the above steps, it is ensured that accurate and real-time hydrological and wind power parameter acquisition and data synchronization are achieved in the marine environment, forming a solid data support, and providing a stable and efficient operation basis for the adaptive method of blue carbon capture and regulation.

[0078] S2 specifically includes:

[0079] S21: Use the main shaft torque fluctuation data obtained in S1 as the input variable, and predict the energy supply curve of the wind power device within the next 5 minutes based on the long short-term memory (LSTM) neural network; Among them, the loss function during the prediction model training uses the mean square error (MSE), and the torque fluctuation data input each time is a time series segment with a length of 30 seconds, and the energy supply value at 10-second intervals within the next 5 minutes is output;

[0080] S22: Use the chlorophyll a concentration and vertical flow velocity gradient measured in S1 as input parameters, and first calculate the carbon capture potential value per unit area of the floating island using the chlorophyll a concentration , the formula is: , where represents the carbon capture potential per unit area of the floating island, and the unit is ; represents the chlorophyll a concentration, and the unit is ; represents chlorophyll concentration and the conversion coefficient between the carbon capture potential, with a value of 0.85;

[0081] S23: Then combine the average energy supply value of the wind power device within the next 5 minutes predicted in S21 and the carbon capture potential value calculated in S22 , calculate the carbon flux threshold per unit area of the floating island , the calculation formula is: , where represents the carbon flux threshold per unit area of the floating island, and the unit is ; represents the average energy supply value of the wind power device within the next 5 minutes; represents the adjustment coefficient between the energy supply and the carbon flux threshold, and its expression is: , where is the rated power of the floating island; is the effective carbon capture area of the floating island; Through the above steps, based on the wind turbine main shaft torque fluctuation data, chlorophyll a concentration, and vertical flow velocity gradient, the accurate prediction of future energy supply and the precise calculation of the floating island carbon flux threshold are realized, providing a reliable basis for the adaptive control of subsequent blue carbon capture and regulation by the ecological floating island.

[0082] S21 specifically includes:

[0083] S211: Divide the main shaft torque fluctuation data measured in S1 into time series segments with a length of 30 seconds and perform normalization processing to obtain the input data sequence , and the normalization processing formula is: , where represents the normalized torque fluctuation data; T represents the original main shaft torque fluctuation data; represents the minimum value of the main shaft torque data within the current segment; represents the maximum value of the main shaft torque data within the current segment;

[0084] S212: Input the normalized input data sequence into the trained long short-term memory neural network for prediction, and output the wind power device energy supply prediction sequence at 10-second intervals within the next 5 minutes ;

[0085] The internal calculation process of the long short-term memory neural network is:

[0086] First, according to the input data at the current time t, calculate the input gate , the forget gate , the output gate and the candidate memory cell state , and the formulas are as follows:

[0087] ;

[0088] ;

[0089] ;

[0090] ;

[0091] Then, update the memory cell state and the hidden state at the current time, and the calculation formulas are:

[0092] ;

[0093] ;

[0094] Finally, based on the hidden state at the current moment , the predicted value of the energy supply of the wind power device corresponding to the future moment is output , and the formula is: ; In the formula, represents the normalized main shaft torque input data at time t; , , represent the input gate, forget gate, and output gate respectively; represents the candidate memory cell state; represents the current memory cell state; represents the current hidden state; , , , represent the input weights corresponding to each gate respectively; , , , represent the hidden state weights corresponding to each gate respectively; , , , represent the biases corresponding to each gate respectively; , represent the weights and biases from the hidden state to the predicted energy output respectively; represents the sigmoid function; represents the hyperbolic tangent activation function; the symbol represents element-wise multiplication.

[0095] S213: Arithmetically average the energy supply prediction sequence obtained in S212 to obtain the average energy supply value of the wind power device within the next 5 minutes , and the formula is: , in the formula, represents the average energy supply value of the wind power device within the next 5 minutes; N represents the number of prediction points within the 5-minute prediction period, taking the value of 30; represents the predicted value of the energy supply corresponding to the i-th prediction moment; Through the calculation of the above specific steps, the present invention accurately realizes the prediction of the average energy supply value of the wind power device within the next 5 minutes based on the main shaft torque fluctuation data, providing a clear basis for the accurate calculation of the carbon flux threshold per unit area of the floating island.

[0096] S3 specifically includes:

[0097] S31: Compare the carbon flux threshold per unit area of the floating island calculated in S2 with the preset carbon flux target interval value Compare to determine the current carbon flux state; when the condition is met, it is determined as a low flux state; when the condition is met, it is determined as a high flux state; when the condition is met, it is determined as a normal flux state;

[0098] S32: Based on the determination result of S31, determine the adjustment direction of the floating island matrix permeability; generate an adjustment instruction to increase the permeability in the low flux state, generate an adjustment instruction to decrease the permeability in the high flux state, and generate an adjustment instruction to keep the permeability unchanged in the normal flux state;

[0099] S33: Calculate the target adjustment value of the pore diameter of the floating island matrix bionic fiber membrane layer according to the adjustment instruction determined in S32 , and the formula is: , where in the formula, represents the target pore diameter of the floating island matrix bionic fiber membrane layer; represents the current pore diameter of the floating island matrix bionic fiber membrane layer; represents the optimal setting value of the floating island carbon flux, and the value is ; is the pore diameter adjustment coefficient, and the value is 0.5;

[0100] S34: According to the target adjustment value of the pore diameter obtained in S33, combined with the vertical flow velocity gradient measured in S1, determine the actual pore diameter adjustment rate , and the calculation formula is: , where in the formula; is the vertical flow velocity gradient measured in S1; represents the proportionality coefficient between the flow velocity gradient and the pore diameter adjustment rate;

[0101] S35: Based on the target adjustment value of the pore diameter and the actual pore diameter adjustment rate , generate the corresponding floating island matrix permeability adjustment instruction and transmit it to the floating island central controller to drive the real-time dynamic adjustment of the pore diameter of the bionic fiber membrane layer; through the above steps, it can accurately determine and execute the dynamic adjustment of the pore diameter of the floating island matrix bionic fiber membrane layer according to the real-time calculated floating island unit area carbon flux threshold, realizing the efficient and refined control of the floating island matrix permeability and ensuring the continuous and stable operation of the floating island blue carbon capture process.

[0102] S4 specifically includes:

[0103] S41: Utilize the pore diameter of the floating island matrix bionic fiber membrane layer adjusted by S3 to form an osmotic pressure difference between the seawater outside the floating island and the closed cavity inside the floating island , and its calculation formula is: , where i represents the osmotic van't Hoff factor with a value of 2; R represents the gas constant with a value of ; T represents the absolute temperature of seawater; is the total ionic molar concentration of seawater in the closed cavity inside the floating island; is the total ionic molar concentration of seawater outside the floating island;

[0104] S42: Under the action of the osmotic pressure difference , the seawater rich in dissolved inorganic carbon outside the floating island migrates into the closed cavity inside the floating island at a flow rate of 0.2 - 0.5 m / s through the pores of the bionic fiber membrane layer, forming a continuous and stable directional inflow;

[0105] S43: When the seawater rich in dissolved inorganic carbon flows through the closed cavity inside the floating island, there are two layers of ion-selective nano membranes preset in the closed cavity, and there is a salinity difference between the two layers of ion-selective nano membranes, thus generating a salinity gradient potential difference , and its expression is: , where represents the salinity gradient potential difference; F represents the Faraday constant with a value of ; represents the ionic concentration of the solution on the high-concentration side; represents the ionic concentration of the solution on the low-concentration side;

[0106] S44: Using the salinity gradient potential difference to drive the directional migration of ions between the selective nano membranes in the salinity gradient power generation module, and then triggering the salinity gradient power generation module to generate compensation electric energy , and its expression is: , where represents the compensation electric energy generated by the salinity gradient power generation module; represents the current output by the salinity gradient power generation module; represents the power generation duration of the salinity gradient power generation module; Finally, the compensation electric energy generated in S44 is transmitted to the central controller of the floating island to provide energy support for regulating the opening and closing frequency of the mangrove stomata by the subsequent microfluidic chip; The above steps realize the efficient coordinated operation of carbon capture and energy supply inside the floating island by using the osmotic pressure difference inside and outside the floating island to drive the directional migration of seawater rich in dissolved inorganic carbon, and at the same time triggering the salinity gradient power generation module to provide additional compensation electric energy through the seawater salinity difference.

[0107] S5 specifically includes:

[0108] S51: Activate the microfluidic chip using the compensation electric energy obtained in S4. The microfluidic chip includes multiple independently controllable microfluidic channels, and each channel is connected to the stoma regulator of the mangrove leaves inside the floating island;

[0109] S52: Calculate the corresponding photosynthesis intensity value of the mangrove forest based on the chlorophyll a concentration measured in S1 , and the formula is: , where represents the photosynthesis intensity value of the mangrove forest; represents chlorophyll concentration, and the conversion coefficient between the chlorophyll concentration and the photosynthesis intensity of the mangrove forest, with a value of ;

[0110] S53: Calculate the target opening and closing frequency of the stomata of the mangrove forest based on the photosynthesis intensity value of the mangrove forest obtained in S52 , and the formula is: , where , where represents the target opening and closing frequency of the stomata of the mangrove forest; represents the preset basic opening and closing frequency of the stomata of the mangrove forest, with a value of 20 times / min; represents the reference value of the photosynthesis intensity of the mangrove forest; represents the adjustment coefficient between the photosynthesis intensity and the opening and closing frequency of the stomata;

[0111] S54: Use the microfluidic chip activated in S51 to adjust the delivery rate of the phytohormone (abscisic acid) in the microfluidic channel according to the target opening and closing frequency of the stomata of the mangrove forest determined in S53 , so as to control the actual opening and closing frequency of the stomata of the mangrove forest leaves to reach the target value. The specific calculation formula is: , where , where represents the delivery rate of the phytohormone abscisic acid; represents the basic delivery rate of the phytohormone abscisic acid; represents the actual opening and closing frequency of the current stomata of the mangrove forest; represents the adjustment coefficient between the opening and closing frequency of the stomata and the delivery rate of the phytohormone abscisic acid; Through the above steps, the efficient combination of compensation electric energy and microfluidic technology is realized, and the opening and closing frequency of the stomata of the mangrove forest leaves is accurately regulated according to the real-time chlorophyll a concentration, ensuring the accurate adaptation of the carbon capture performance of the floating island ecosystem to the environmental conditions, and effectively improving the real-time performance and stability of the floating island blue carbon capture.

[0112] S6 specifically includes:

[0113] S61: Real-time collect the actual stomatal opening and closing frequency of the mangrove forest leaves after control in S5, and obtain the current vertical velocity gradient data measured in S1;

[0114] S62: Compare the actual stomatal opening and closing frequency collected in S61 with the preset optimal stomatal opening and closing frequency threshold to determine the deviation direction and amplitude of the current stomatal opening and closing state;

[0115] S63: Based on the deviation direction and amplitude of the stomatal opening and closing state determined in S62, determine the target adjustment area of the floating island counterweight, and combine the vertical flow velocity gradient data obtained in step S61 to determine the specific adjustment direction of the counterweight;

[0116] S64: According to the target adjustment area and direction of the counterweight determined in S63, send adjustment instructions to each independent counterweight driving device of the floating island in real time to dynamically adjust the position and distribution of each counterweight, so as to actively adjust the attitude and immersion depth of the floating island;

[0117] S65: Feed back the data of the floating island attitude and immersion depth after adjustment to the central controller, and combine the current real-time blue carbon deposition rate of the floating island to judge whether it is within the target blue carbon deposition rate range. If not, repeat S61 to S64 for continuous adjustment until the blue carbon deposition rate is stable within the target range; Through the above steps, the spatial distribution of the floating island counterweight is accurately corrected based on the mangrove stomatal opening and closing frequency and real-time flow velocity gradient data, ensuring that the floating island attitude and immersion state are matched with the environmental changes in real time, and effectively maintaining the stability of the blue carbon deposition rate.

[0118] S62 specifically includes:

[0119] S622: Let the actual stomatal opening and closing frequency be , then the deviation between the actual stomatal opening and closing frequency and the target stomatal opening and closing frequency is expressed as: , where represents the deviation value of the stomatal opening and closing frequency; represents the target opening and closing frequency of the mangrove stomata;

[0120] S623: Based on the calculated deviation of the stomatal opening and closing frequency, determine the deviation direction: when >0, it is determined as the state of excessive stomatal opening; when <0, it is determined as the state of insufficient stomatal opening; when =0, it means that the stomatal opening and closing frequency is normal;

[0121] S624: Calculate the normalized deviation value of the stomatal opening and closing frequency deviation for subsequent standardized processing during the adjustment of the floating island counterweight. The calculation formula is: , where represents the normalized stomatal opening and closing frequency deviation value;

[0122] S625: The normalized deviation value Compare with the preset deviation threshold If it meets , it is determined that the deviation of the current stomatal opening and closing state exceeds the normal range, and the distribution of the floating island counterweight blocks needs to be adjusted; if it meets , it is considered that the stomatal opening and closing state is within the acceptable range and no adjustment is required; through the above steps, the accurate determination of the stomatal opening and closing state of mangroves is realized, ensuring that the floating island can detect the deviation of stomatal opening and closing in real time under different flow velocity gradient conditions, providing reliable data support for the subsequent adaptive adjustment of the floating island counterweight blocks, and effectively improving the blue carbon capture efficiency and stability of the floating island system.

[0123] S63 specifically includes:

[0124] S631: Based on the normalized stomatal opening and closing frequency deviation value obtained in S62, calculate the offset of the current center of gravity position of the floating island according to the pre-calibrated counterweight adjustment ratio to obtain the corresponding center of gravity offset, which is used as a reference value for the preliminary adjustment of the floating island counterweight blocks;

[0125] S632: Combine the vertical flow velocity gradient data obtained in S61, and determine the specific adjustment direction of the floating island counterweight blocks according to the positive and negative directions of the vertical flow velocity gradient. If the vertical flow velocity gradient is positive, it will offset in one direction; if the vertical flow velocity gradient is negative, it will offset in the opposite direction; thus obtaining the final counterweight adjustment direction;

[0126] S633: Combine the center of gravity offset calculated in S631 with the adjustment direction determined in S632, define the target adjustment area of the floating island counterweight blocks, and adapt to different degrees of stomatal deviation values and vertical flow velocity gradients by enlarging or reducing the range of the area, forming an area range capable of adjusting the counterweight distribution in the horizontal plane;

[0127] S634: Select the best adjustment point within the target adjustment area, and offset the current center of gravity position of the floating island to this point along the direction determined in S632 to complete the distribution of the counterweight blocks.

[0128] The specific calculation process is as follows:

[0129] First, based on the normalized stomatal opening and closing frequency deviation value , determine the target adjustment area of the floating island counterweight blocks, and calculate the floating island center of gravity offset vector , the formula is: , where k is the counterweight adjustment ratio coefficient; represents the floating island structure stability vector;

[0130] Then, based on the vertical flow velocity gradient , calculate the floating island counterweight adjustment direction vector , the calculation formula is: , where Represents the adjustment direction vector of the floating island counterweight block; Is the floating island counterweight response factor; Represents the sign function of the vertical flow velocity gradient, taking values of +1 (positive gradient) or -1 (negative gradient);

[0131] Next, based on the floating island center of gravity offset vector And the adjustment direction vector , determine the target adjustment area of the floating island counterweight block, with Representing the radius of the adjustment area, and the calculation formula is: , where Represents the radius of the floating island counterweight block adjustment area; Is the adjustment area magnification factor;

[0132] Finally, after determining the counterweight block adjustment area, calculate the optimal adjustment point of the counterweight block within this adjustment area , and the calculation formula is: , where Represents the current center of gravity position of the floating island; Through the above steps, the dynamic adjustment of the floating island counterweight block based on the stomatal opening and closing frequency deviation and the real-time vertical flow velocity gradient is realized, enabling the floating island attitude to be adaptively adjusted to optimize the blue carbon deposition environment and improve the stability of the ecological floating island and the blue carbon capture efficiency.

[0133] This invention covers any substitutions, modifications, equivalent methods, and solutions made within the essence and scope of this invention. To enable the public to have a thorough understanding of this invention, specific details are described in detail in the following preferred embodiments of this invention. However, those skilled in the art can fully understand this invention even without the description of these details. Additionally, to avoid unnecessary confusion to the essence of this invention, well-known methods, processes, procedures, components, and circuits are not described in detail.

[0134] The above description is only a preferred embodiment of this invention. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the principle of this invention, several improvements and refinements can still be made, and these improvements and refinements should also be regarded as the protection scope of this invention.

Claims

1. An adaptive method for blue carbon capture and regulation of an ecological floating island driven by offshore wind power, characterized in that It includes the following steps: S1: Obtain the vertical velocity gradient, chlorophyll a concentration, and dissolved inorganic carbon content of the target sea area in real time through a distributed sensor array, and synchronously collect the main shaft torque fluctuation data of the wind power device; S2: Predict the future 5-minute energy supply curve based on the main shaft torque fluctuation data of the wind power, and calculate the carbon flux threshold per unit area of the floating island in combination with the chlorophyll a concentration and the vertical velocity gradient; S3: Generate an adjustment instruction for the matrix permeability of the floating island according to the carbon flux threshold, which is used to control the dynamic adjustment of the pore diameter of the bionic fiber membrane layer within the range of 50 - 200 μm; S4: Drive the migration of dissolved inorganic carbon into the floating island through the osmotic pressure difference, and at the same time trigger the salinity gradient power generation module to generate compensatory electric energy; The specific content of S4 includes: S41: Using the pore diameter of the floating island matrix bionic fiber membrane layer adjusted in S3, an osmotic pressure difference is formed between the seawater outside the floating island and the closed cavity inside the floating island. ; S42: Under the action of the osmotic pressure difference the seawater rich in dissolved inorganic carbon outside the floating island migrates towards the closed cavity inside the floating island through the pores of the bionic fiber membrane layer at a flow rate of 0.2 - 0.5 m / s, forming a continuous and stable directional inflow; S43: When seawater rich in dissolved inorganic carbon flows through the internal closed cavity of the floating island, there are two preset ion-selective nano membranes in the internal closed cavity, and there is a salinity difference between the two ion-selective nano membranes, thus generating a salinity gradient potential difference ; S44: Using the salinity gradient potential difference to drive the directional migration of ions between selective nanofilms in the salinity gradient power generation module, thereby triggering the salinity gradient power generation module to generate compensatory electric energy ; S5: Activate the microfluidic chip with the compensatory electric energy, and control the opening and closing frequency of the mangrove tree stomata according to the photosynthesis intensity corresponding to the chlorophyll a concentration; The specific content of S5 includes: S51: Activate the microfluidic chip with the compensatory electric energy obtained in S4. The microfluidic chip contains multiple independently controllable microfluidic channels, and each channel is connected to the stomatal regulator of the mangrove tree leaves inside the floating island; S52: Calculate the corresponding photosynthesis intensity value of the mangrove based on the chlorophyll a concentration measured in S1 ; S53: The mangrove photosynthesis intensity value obtained according to S52 , calculate the target opening and closing frequency of the mangrove stomata ; S54: Using the microfluidic chip activated by S51, adjust the delivery rate of phytohormones in the microfluidic channel according to the target opening and closing frequency of the mangrove stomata determined by S53 , so as to control the actual opening and closing frequency of the mangrove leaves stomata to reach the target value. The specific calculation formula is as follows: , where ; in the formula, represents the delivery rate of the phytohormone abscisic acid; represents the basic delivery rate of the phytohormone abscisic acid; represents the actual opening and closing frequency of the current mangrove stomata; represents the adjustment coefficient between the opening and closing frequency of the stomata and the delivery rate of the phytohormone abscisic acid S6: Dynamically correct the distribution of the floating island counterweight blocks according to the opening and closing frequency of the stomata and the real-time vertical velocity gradient data, so that the blue carbon deposition rate is stabilized within the target range.

2. The ecological floating island blue carbon capture and regulation adaptive method driven by offshore wind power according to claim 1, wherein, The specific content of S1 includes: S11: Install 3 sets of ultrasonic Doppler profilers circumferentially on the underwater section of the wind power pile foundation. Each set is distributed at an interval of 120°. Synchronously measure the velocity vectors of each 0.5 m layer within the water depth range of 0 - 20 m, and calculate the vertical velocity gradient through a three-dimensional velocity interpolation algorithm; S12: Suspendedly deploy a CTD temperature-salinity-depth sensor cluster at a depth of 10 m below the floating island, and measure the chlorophyll a concentration through the fluorescence spectrum with an excitation wavelength of 450 nm / a detection wavelength of 685 nm; S13: Embed a micro-flow-through infrared spectroscopy detection cavity inside the floating island matrix, allow seawater to flow through the detection cavity at a flow rate of 0.2 - 0.5 m / s, and use the intensity of the characteristic absorption peak at a wavelength of 4300 cm - ⁻¹ to invert the dissolved inorganic carbon content; S14: Arrange a strain gauge array at the connection between the main shaft and the gearbox of the wind power device. The strain gauge array contains 12 groups of strain bridge circuits evenly distributed circumferentially, synchronously collect the main shaft torque fluctuation data, and at the same time obtain the main shaft rotation speed time series signal through an optoelectronic encoder; S15: Transmit the vertical velocity gradient, chlorophyll a concentration, dissolved inorganic carbon content, and main shaft torque data obtained in S11 - S14 to the central controller of the floating island through a salt spray-resistant CAN bus, and use the IEEE 1588 precise time protocol to achieve the timestamp synchronization of multi-source data.

3. The ecological floating island blue carbon capture and regulation adaptive method driven by offshore wind power according to claim 1, wherein The specific content of S2 includes: S21: Take the main shaft torque fluctuation data obtained in S1 as the input variable, and predict the energy supply curve of the wind power device within the next 5 minutes based on a long short-term memory neural network; S22: Using the chlorophyll a concentration measured in S1 and the vertical flow velocity gradient as input parameters, first calculate the carbon capture potential value per unit area of the floating island using the chlorophyll a concentration , and the formula is: , where represents the carbon capture potential per unit area of the floating island; represents the chlorophyll a concentration; represents chlorophyll is the conversion coefficient between the concentration and the carbon capture potential, with a value of 0.85; S23: Furthermore, combine the average energy supply value of the wind power device predicted in S21 within the next 5 minutes and the carbon capture potential value calculated in S22 , and calculate the carbon flux threshold per unit area of the floating island . The calculation formula is as follows: , where in the formula represents the carbon flux threshold per unit area of the floating island; represents the average energy supply value of the wind power device within the next 5 minutes; represents the adjustment coefficient between the energy supply and the carbon flux threshold, represents the vertical velocity gradient.

4. The ecological floating island blue carbon capture and regulation adaptive method driven by offshore wind power according to claim 3, wherein, The specific content of S21 includes: S211: Divide the spindle torque fluctuation data measured in S1 into time series segments with a length of 30 seconds and perform normalization processing to obtain the input data sequence ; S212: Input the normalized input data sequence , into the trained long short-term memory neural network for prediction, and output the wind power device energy supply prediction sequence at 10-second intervals within the next 5 minutes ; S213: Supply the energy supply prediction sequence obtained in S212 for arithmetic averaging to obtain the average energy supply value of the wind power device within the next 5 minutes , and the formula is: , where represents the average energy supply value of the wind power device within the next 5 minutes; N represents the number of prediction points within the 5-minute prediction period, with a value of 30; represents the energy supply prediction value corresponding to the i-th prediction moment.

5. The ecological floating island blue carbon capture and regulation adaptive method driven by offshore wind power according to claim 3, wherein The specific content of S3 includes: S31: Compare the carbon flux threshold per unit area of the floating island calculated in S2 with the preset carbon flux target range value ; When the condition is met, it is determined to be in a low flux state; when the condition is met, it is determined to be in a high flux state; when the condition is met, it is determined to be in a normal flux state; S32: Based on the determination result of S31, determine the adjustment direction of the matrix permeability of the floating island; generate an adjustment instruction to increase the permeability in the low flux state, generate an adjustment instruction to decrease the permeability in the high flux state, and generate an adjustment instruction to keep the permeability unchanged in the normal flux state; S33: Calculate the target adjustment value of the pore diameter of the floating island matrix bionic fiber membrane layer according to the adjustment instruction determined in S32 ; S34: Target adjustment value of pore diameter obtained according to S33 , combined with the vertical flow velocity gradient measured by S1 , to determine the actual pore diameter adjustment rate ; S35: Generate a corresponding floating island substrate permeability adjustment instruction based on the target adjustment value of the pore diameter and the actual pore diameter adjustment rate. ​ 6. The ecological floating island blue carbon capture and regulation adaptive method driven by offshore wind power according to claim 1, characterized in that The specific content of S6 includes: S61: Real-time collect the actual opening and closing frequency of the mangrove tree leaves controlled in S5, and obtain the current vertical velocity gradient data measured in S1; S62: Compare the actual stomatal opening and closing frequency collected in S61 with the pre-set optimal stomatal opening and closing frequency threshold to determine the deviation direction and deviation amplitude of the current stomatal opening and closing state; S63: Based on the deviation direction and amplitude of the stomatal opening and closing state determined in S62, determine the target adjustment area of the floating island counterweight block, and combine the vertical flow velocity gradient data obtained in step S61 to determine the specific adjustment direction of the counterweight block; S64: According to the target adjustment area and direction of the counterweight block determined in S63, send adjustment instructions to each independent counterweight block driving device of the floating island in real time to dynamically adjust the position and distribution of each counterweight block, so as to actively adjust the attitude and immersion depth of the floating island; S65: Feed back the data of the floating island attitude and immersion depth after adjustment to the central controller, and combine the current real-time blue carbon deposition rate of the floating island to judge whether it is within the target blue carbon deposition rate range. If not, repeat S61 to S64 for continuous adjustment until the blue carbon deposition rate is stabilized within the target range.

7. The ecological floating island blue carbon capture and regulation adaptive method driven by offshore wind power according to claim 6, characterized in that, The specific content of S62 includes: S622: Let the actual stomatal opening and closing frequency be , then the deviation between the actual stomatal opening and closing frequency and the target stomatal opening and closing frequency is expressed as: , where represents the deviation value of the stomatal opening and closing frequency; represents the target opening and closing frequency of the mangrove stomata; S623: Based on the calculated deviation of stomatal opening and closing frequency Determine the deviation direction: When > 0, it is determined as the state of excessive stomatal opening; when < 0, it is determined as the state of insufficient stomatal opening; when = 0, it indicates that the stomatal opening and closing frequency is normal; S624: Calculate the normalized deviation value of the deviation of the stomatal opening and closing frequency ; S625: The normalized deviation value calculated in S624 is compared with a preset deviation threshold . If it satisfies , it is determined that the deviation of the current stomatal opening and closing state exceeds the normal range, and the distribution of the floating island counterweight needs to be adjusted; if it satisfies , it is considered that the stomatal opening and closing state is within the acceptable range and no adjustment is required.

8. The ecological floating island blue carbon capture and regulation adaptive method driven by offshore wind power according to claim 7, characterized in that, The specific content of S63 includes: S631: Based on the normalized stomatal opening and closing frequency deviation value obtained in S62, calculate the offset of the current center of gravity position of the floating island according to the pre-calibrated counterweight adjustment ratio to obtain the corresponding center of gravity offset, which is used as a reference value for the preliminary adjustment of the floating island counterweight block; S632: Combine the vertical flow velocity gradient data obtained in S61, and determine the specific adjustment direction of the floating island counterweight block according to the positive and negative directions of the vertical flow velocity gradient. If the vertical flow velocity gradient is positive, offset in one direction; if the vertical flow velocity gradient is negative, offset in the opposite direction; thus obtaining the final adjustment direction of the counterweight block; S633: Combine the center of gravity offset calculated in S631 with the adjustment direction determined in S632 to define the target adjustment area of the floating island counterweight block, and adapt to different degrees of stomatal deviation values and vertical flow velocity gradients by enlarging or reducing the range of the area, forming a range of area that can adjust the counterweight distribution in the horizontal plane; S634: Select the best adjustment point within the target adjustment area, and offset the current center of gravity position of the floating island to this point along the direction determined in S632 to complete the distribution of the counterweight block.

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