Marine ecological environment influence tracking monitoring management method based on offshore wind power engineering

Abstract

The invention relates to the technical field of offshore wind power, in particular to a marine ecological environment influence tracking monitoring management method based on an offshore wind power project, which comprises the following steps: S1, deploying multiple types of sensors at each key position of the offshore wind power project; s2, preprocessing the data acquired by the sensor; s3, establishing a risk assessment model, and performing risk level assessment on the influence of the marine ecological environment; and S4, generating a risk report according to an evaluation result of the risk evaluation model, sending the risk report to a monitoring center, and taking corresponding management measures by the monitoring center according to the risk report. Through comprehensive sensor deployment and data acquisition, in combination with an advanced preprocessing technology and an accurate risk assessment model, the influence of offshore wind power engineering on the marine ecological environment can be monitored in real time.

Description

Technical Field

[0001] The present invention relates to the field of offshore wind power technology, and in particular to a method for tracking, monitoring and managing the impact of offshore wind power projects on the marine ecological environment. Background Art

[0002] As an important component of clean energy, offshore wind power has developed rapidly in recent years. However, the impact of offshore wind power construction on the marine ecological environment cannot be ignored. These impacts include underwater noise pollution, water disturbance, changes in bottom sediments, and the impact of construction on marine life. Rationally managing and tracking these impacts to ensure the harmonious coexistence of offshore wind power projects and the marine ecological environment has become a hot topic of current research. The present invention aims to provide an effective method for tracking, monitoring, and managing the impact of offshore wind power projects on the marine ecological environment, so as to achieve comprehensive protection of the marine ecosystem.

[0003] After searching, a marine ecosystem with the publication number CN111945695B was disclosed, and the publication date was August 25, 2023. The patent proposes a ring-shaped support platform composed of modular connections, which combines multiple functions such as wind power generation, wave power generation, hydraulic power generation, fish farming system, mooring system, artificial algae fish reef ecosystem and offshore city. While using wind and wave energy to generate electricity, the system creates a habitat for marine organisms through artificial algae fish reefs, realizes a natural ecological chain of fish farming and increases the carbon sequestration capacity of the ocean. However, in this technical solution, there is a lack of a systematic tracking and monitoring mechanism for the impact on the marine ecological environment, and it is impossible to grasp the changes in various ecological and environmental parameters in real time, making it difficult to adjust and optimize the system operation in a timely manner to ensure the long-term stability of the ecosystem.

[0004] After searching, an ecologically protected offshore wind power system with publication number CN114271224B was disclosed, with a publication date of September 27, 2022. This patent uses marine ranches to achieve basic protection of the offshore wind farm area by setting up shellfish farming towers and seaweed farming devices upstream of the wind turbines, while using a mixed farming model to achieve a balance between income and expenditure and achieve sustainability. However, in this technical solution, although ecological farming methods are used to protect the ecological environment of the wind farm area, there is a lack of a comprehensive monitoring mechanism for the impact on the ecological environment. It is impossible to monitor and evaluate the impact of long-term operation on the ocean bottom, water quality and biodiversity in real time, making it difficult to provide a scientific basis for management and decision-making.

[0005] These issues demonstrate that existing offshore wind power technologies have shortcomings in terms of ecological and environmental protection. While these technical solutions take ecological and environmental protection into account to a certain extent, they lack systematic and real-time tracking and monitoring mechanisms, making it difficult to ensure long-term ecological balance. Summary of the Invention

[0006] Based on the above objectives, the present invention provides a method for tracking, monitoring and managing the impact of offshore wind power projects on the marine ecological environment.

[0007] The marine ecological and environmental impact tracking, monitoring and management method based on offshore wind power projects includes the following steps: S1: Deploy multiple types of sensors at key locations of offshore wind power projects, including underwater noise sensors, water quality sensors, bottom sediment sensors, and biosensors, to collect real-time marine ecological and environmental data; S2: Preprocess the data collected by the sensor; S3: Establish a risk assessment model to assess the risk level of impacts on the marine ecological environment. The risk assessment model includes underwater noise pollution risk assessment, water disturbance risk assessment, bottom sediment change risk assessment, and biological impact risk assessment; S4: Generate a risk report based on the assessment results of the risk assessment model and send it to the monitoring center. The monitoring center will take corresponding management measures based on the risk report.

[0008] Preferably, in S1, underwater noise sensors are deployed in the underwater area around the wind turbine to detect underwater noise and collect underwater noise intensity data; water quality sensors are installed in the water body around the wind turbine to collect pH value, dissolved oxygen, temperature and salinity data in the water body; bottom sediment sensors are installed in the seabed sediments at the bottom of the wind turbine to collect bottom sediment type and sediment condition data; biological sensors are installed in the sea area around the wind turbine to collect marine life species and quantity data.

[0009] Preferably, in S2, the underwater noise intensity data is pre-processed using a wavelet transform denoising algorithm to remove noise interference, and is calibrated based on data from a reference underwater noise sensor; The pH value data is pre-processed using a moving average filtering algorithm to smooth data fluctuations, and the sensor is calibrated using a standard buffer solution; The dissolved oxygen data is pre-processed using a Kalman filter algorithm to remove measurement noise and is regularly calibrated using a standard saturated aqueous solution; The temperature data is pre-processed by using a low-pass filter to smooth the temperature data and calibrated using a standard temperature source; The salinity data is pre-processed by using a median filter algorithm to remove outliers and is regularly calibrated using a standard salinity solution.

[0010] Preferably, the underwater noise pollution risk assessment takes underwater noise intensity data as input and evaluates the impact on marine life using the following formula: ;in, For the The underwater noise intensity collected by the sensors is As a reference to the underwater noise intensity, is the underwater noise pollution risk value.

[0011] Preferably, the water disturbance risk assessment takes pH, dissolved oxygen, temperature and salinity data as input and evaluates the impact on the water environment using the following formula: ; ; ; in, 、 、 and Respectively pH, dissolved oxygen, temperature and salinity collected by sensors, 、 、 and are the reference pH, dissolved oxygen, temperature and salinity, is the water disturbance risk value, is the number of sensors used to assess the risk of water disturbance.

[0012] Preferably, the risk assessment of seabed change takes seabed type and sediment condition data as input and evaluates the impact on the ocean seabed using the following formula: ;in, They are real-time data of bottom type and sediment condition, are the standard values ​​of the corresponding parameters.

[0013] Preferably, the biological impact risk assessment takes data on species and numbers of marine organisms as input and assesses the impact on biodiversity using the following formula: ;in, For the The number of species, is the total number of organisms, is the number of biological species, is the risk assessment value for biological impacts, n b Indicates the number of biological species actually monitored.

[0014] Preferably, when When the preset threshold is exceeded, the monitoring center will immediately notify the project operation and maintenance personnel and require them to adjust the operating parameters of the wind turbine motor during construction or operation to reduce the generation of underwater noise; when When the preset threshold is exceeded, the monitoring center will notify the water quality management team and require them to promptly adjust the frequency and intensity of underwater construction operations to reduce disturbance to the water body. In addition, the monitoring center will activate water quality treatment equipment to restore the water body to normal.

[0015] Preferably, when When the preset threshold is exceeded, the monitoring center will notify the bottom sediment management team and require them to increase protection measures for seabed sediments during the construction process, set up temporary protective nets, reduce disturbance of the bottom sediment caused by construction, and carry out bottom sediment repair work on a regular basis.

[0016] Preferably, when When the preset threshold is exceeded, the monitoring center will notify the biological protection team and require them to take biological protection measures during construction and operation, set up no-fishing zones, reduce fishing and interference with organisms, and carry out regular biodiversity restoration work.

[0017] Beneficial effects of the present invention: 1. Through comprehensive sensor deployment and data collection, combined with advanced pre-processing technology and accurate risk assessment models, the impact of offshore wind power projects on the marine ecological environment can be monitored in real time.

[0018] 2. Through the organic combination of this sensor system, real-time monitoring and dynamic assessment of the marine ecological environment during the construction and operation of offshore wind power projects can be achieved. The data collected by different sensors complement each other to form a complete ecological and environmental monitoring system.

[0019] 3. The application of algorithms such as wavelet transform denoising and Kalman filtering can significantly improve the accuracy and signal-to-noise ratio of data and reduce the impact of noise on the results.

[0020] 4. Through real-time data collection by sensors, the changing trend of underwater noise pollution can be dynamically tracked, providing a basis for timely implementation of protective measures.

[0021] 5. By accurately calculating the deviations of various water quality parameters and combining them with a sum-of-squares approach, we can effectively quantify the risk of water disturbance, avoiding the one-sidedness of single-parameter analysis. This approach provides a more scientific and accurate basis for judgment. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0023] Figure 1 Flow chart of the steps of the method of the present invention. DETAILED DESCRIPTION

[0024] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. It is also noted that, to provide a more detailed description, the following embodiments are best and preferred embodiments, and those skilled in the art may employ alternative methods for implementing certain known technologies. Furthermore, the accompanying drawings are intended only to provide a more detailed description of the embodiments and are not intended to limit the present invention.

[0025] See Figure 1 The embodiment of the present invention provides a method for tracking, monitoring and managing the impact of offshore wind power projects on the marine ecological environment, comprising the following steps: S1: Deploy multiple types of sensors at key locations of offshore wind power projects, including underwater noise sensors, water quality sensors, bottom sediment sensors, and biosensors, to collect real-time marine ecological and environmental data; S2: Preprocess the data collected by the sensor; S3: Establish a risk assessment model to assess the risk level of impacts on the marine ecological environment. The risk assessment model includes underwater noise pollution risk assessment, water disturbance risk assessment, bottom sediment change risk assessment, and biological impact risk assessment; S4: Generate a risk report based on the assessment results of the risk assessment model and send it to the monitoring center. The monitoring center will take corresponding management measures based on the risk report.

[0026] In one possible implementation, multiple types of sensors are deployed at key locations along offshore wind turbine projects to comprehensively collect marine ecological and environmental data. These sensors include underwater noise sensors, water quality sensors, bottom sediment sensors, and biosensors. Each collects different types of data: underwater noise sensors monitor the noise generated by wind turbine operation; water quality sensors collect real-time data on seawater parameters such as dissolved oxygen, salinity, and temperature; bottom sediment sensors monitor changes in seafloor sediments; and biosensors monitor changes in surrounding biomes. This data provides a foundation for subsequent risk assessments.

[0027] Furthermore, after data collection, the raw data collected by sensors will contain a certain amount of noise and outliers, necessitating preprocessing. This process includes filtering, smoothing, and denoising to improve data accuracy and reliability. For example, water quality data may be affected by changes in the external environment. Using filtering algorithms can effectively remove irrelevant factors, ensuring that the measured water quality data truly reflects the marine environment. Preprocessed data provides more accurate information for subsequent risk assessments, ensuring the scientific and credible nature of the assessments.

[0028] After data preprocessing, a risk assessment model was established to comprehensively evaluate the impact on the marine ecological environment. This model encompasses four key risk assessment subsystems: underwater noise pollution risk assessment, water disturbance risk assessment, bottom sediment change risk assessment, and biological impact risk assessment. Each subsystem analyzes different types of data and classifies risks according to set thresholds. For example, the underwater noise pollution assessment determines its potential impact on marine life based on changes in noise intensity; the water disturbance assessment analyzes possible ecological impacts based on water quality data; the bottom sediment change assessment evaluates the impact of wind turbine construction on the seabed ecological environment by monitoring changes in sediment; and the biological impact assessment assesses the potential threat to biodiversity from construction by monitoring changes in organism species and abundance. The combined results of these assessments will provide a basis for decision-making on subsequent management measures.

[0029] Furthermore, based on the results of the risk assessment, the system automatically generates a detailed risk report and sends it to the monitoring center. After analyzing the risk report, the monitoring center takes targeted management measures based on the specific risk level and assessment results. For example, when the risk of underwater noise pollution is too high, the monitoring center may recommend adjusting the operating mode of the wind turbine to reduce the impact of noise on marine life. When the risk of bottom sediment change is high, measures such as reducing construction intensity or improving construction methods may be taken to reduce interference with the seabed ecosystem. This link is the key to the entire method, ensuring timely response to environmental changes during wind power construction and operation, taking necessary protective measures, and ensuring the sustainability of the marine ecological environment.

[0030] In an embodiment of the present invention, in S1, an underwater noise sensor is deployed in the underwater area around the wind turbine to detect underwater noise and collect underwater noise intensity data; a water quality sensor is installed in the water body around the wind turbine to collect pH value, dissolved oxygen, temperature and salinity data in the water body; a bottom sediment sensor is installed in the seabed sediment at the bottom of the wind turbine to collect bottom sediment type and sediment condition data; a biological sensor is installed in the sea area around the wind turbine to collect marine biological species and quantity data.

[0031] In one possible implementation, underwater noise sensors are located in the underwater area surrounding wind turbines, primarily used to monitor underwater noise generated during wind turbine operation. By continuously collecting underwater noise intensity data, the noise sensors provide information on the potential impact of wind turbines on marine life. Changes in noise data reflect the operating status of the wind turbines and the range of noise propagation, providing a quantitative basis for assessing the impact of underwater noise pollution on the surrounding ecosystem.

[0032] Water quality sensors are installed in the water surrounding wind turbines, primarily collecting water quality indicators such as pH, dissolved oxygen, temperature, and salinity. This data allows for real-time monitoring of the potential impacts of wind turbine construction and operation on water quality, particularly temperature fluctuations, pH fluctuations, and dissolved oxygen levels, all of which directly impact the habitat of marine life. This water quality data provides a scientific basis for assessing the impact of wind turbine projects on the aquatic ecosystem.

[0033] Subsurface sensors are installed in the seafloor sediments beneath wind turbines. They primarily monitor sediment type, sediment changes, and potential disturbances. Wind turbine installation can alter the seafloor environment. Therefore, data from these sensors helps analyze the impact of wind turbine construction on seafloor sediments and mitigate potential contamination or disturbance during construction.

[0034] Biosensors are installed in the waters surrounding wind turbines to monitor changes in the species and abundance of marine life. This monitoring of marine life allows for timely detection of wind turbine impacts on surrounding biomes, particularly during breeding seasons and migration periods, ensuring ecological stability. Biosensor data helps assess biodiversity changes and inform timely conservation measures.

[0035] In an embodiment of the present invention, in S2, the underwater noise intensity data is pre-processed using a wavelet transform denoising algorithm to remove noise interference and is calibrated based on data from a reference underwater noise sensor; The pH value data is pre-processed using a moving average filtering algorithm to smooth data fluctuations, and the sensor is calibrated using a standard buffer solution; The dissolved oxygen data is pre-processed using a Kalman filter algorithm to remove measurement noise and is regularly calibrated using a standard saturated aqueous solution; The temperature data is pre-processed by using a low-pass filter to smooth the temperature data and calibrated using a standard temperature source; The salinity data is pre-processed by using a median filter algorithm to remove outliers and is regularly calibrated using a standard salinity solution.

[0036] In one possible implementation, a wavelet transform denoising algorithm is used during the preprocessing phase of underwater noise intensity data. This algorithm effectively removes the influence of other interference sources (such as wind speed variations and equipment noise) on the underwater noise signal, ensuring that only the true noise signal is retained. Furthermore, data from a reference underwater noise sensor can be used to calibrate the collected data, ensuring consistency and accuracy of measurement results from each sensor.

[0037] pH data is preprocessed using a moving average filter algorithm. This algorithm smooths data fluctuations caused by water quality fluctuations, preventing instantaneous data fluctuations from affecting overall trend analysis. Standard buffer solutions are used to calibrate the sensor, ensuring long-term measurement stability and preventing errors introduced by sensor drift.

[0038] Furthermore, dissolved oxygen data is preprocessed using a Kalman filter algorithm, which effectively removes interference from measurement equipment noise and ensures data accuracy. To ensure sensor accuracy during use, the sensor is regularly calibrated using a standard saturated aqueous solution to ensure that measurement results are consistent with the standard value and avoid deviations caused by environmental changes or sensor aging.

[0039] Furthermore, the temperature data is pre-processed using a low-pass filter. This algorithm removes high-frequency noise and smoothes temperature fluctuations, ensuring that the acquired temperature data accurately reflects long-term trends. To ensure the measurement accuracy of the temperature sensor, it is calibrated using a standard temperature source to avoid inaccurate measurements due to sensor deviation.

[0040] Salinity data is pre-processed using a median filter algorithm, effectively removing occasional outliers, such as those caused by sensor failure or environmental fluctuations. Regular calibration with a standard salinity solution ensures that the sensor continues to provide accurate salinity data even after extended use.

[0041] In an embodiment of the present invention, the underwater noise pollution risk assessment takes underwater noise intensity data as input and evaluates the impact on marine life using the following formula: ;in, For the The underwater noise intensity collected by the sensors is As a reference to the underwater noise intensity, is the underwater noise pollution risk value, Represents the number of sensors used to assess underwater noise pollution risk.

[0042] In one possible implementation, first, multiple underwater noise sensors are deployed in the offshore wind farm area to collect underwater noise intensity data in real time. Each sensor records the corresponding underwater noise intensity value, which represents the noise intensity at different locations and times. These underwater noise intensity data are used as input and brought into the evaluation formula. Through this formula, the difference between all collected data and the reference noise intensity value is calculated, and the average value is obtained. This value This is the underwater noise pollution risk value, which reflects the overall impact of underwater noise. The size of this value can indicate the risk level of underwater noise pollution in the marine environment. According to the calculation results, The value is compared with a certain standard or threshold to determine the potential impact of the current offshore wind power project on the surrounding marine life. If the value exceeds the safety threshold, it means that underwater noise pollution may cause harm to the marine ecology, and corresponding environmental protection measures need to be taken, such as adjusting the operation mode of wind turbines and optimizing the layout location.

[0043] In an embodiment of the present invention, the water disturbance risk assessment takes pH value, dissolved oxygen, temperature and salinity data as input and evaluates the impact on the water environment using the following formula: ; ; ; in, 、 、 and Respectively pH, dissolved oxygen, temperature and salinity collected by sensors, 、 、 and are the reference pH, dissolved oxygen, temperature and salinity, is the water disturbance risk value, is the number of sensors used to assess the risk of water disturbance.

[0044] In one possible implementation, multiple sensors are deployed in the offshore wind farm area to monitor the pH value, dissolved oxygen (DO), temperature (T), and salinity (S) of the water in real time. These sensors record data regularly to ensure that they can reflect changes in the water environment. The value recorded by the sensor is 、 、 and , corresponding to the pH value, dissolved oxygen concentration, temperature and salinity of the water body respectively.

[0045] In order to assess the impact of wind power projects on the water environment, it is necessary to set reference values, which represent typical levels under normal water conditions. Reference values ​​include 、 、 and , these values ​​can be derived from historical data, standard water quality or natural environmental benchmarks in the relevant area.

[0046] Based on the difference between the collected sensor data and the reference value, the water disturbance risk value is calculated using the following formula: ; ; ; in, is the number of sensors. This formula calculates the sum of the squares of the differences in each parameter and then takes the square root to generate a comprehensive water disturbance risk value. This value reflects the average deviation of each parameter (pH, dissolved oxygen, temperature, and salinity) and can intuitively demonstrate the potential impact of wind power projects on the aquatic environment.

[0047] Calculated The value will be compared with the set threshold. If the risk value exceeds the safety threshold, it indicates that the water environment has been significantly disturbed and appropriate management measures need to be taken, such as adjusting the operation mode of wind turbines, changing construction plans, or strengthening ecological restoration.

[0048] In an embodiment of the present invention, the sediment change risk assessment takes sediment type and sediment condition data as input and evaluates the impact on the ocean sediment using the following formula: ;in, They are real-time data of bottom type and sediment condition, are the standard values ​​of the corresponding parameters.

[0049] In one possible implementation, sensors monitoring the ocean floor are deployed to regularly collect real-time data on floor type and sediment condition. Floor type is typically determined through geological surveys, sampling and analysis, or remote sensing, while sediment condition is measured using indicators such as particle size, water content, and organic matter content of seabed sediment samples. This data provides a basis for assessing the risk of floor change. Parameters for floor monitoring include floor type classification and the physical and chemical properties of the sediment.

[0050] Risk assessment requires establishing standard values ​​for substrate type and sediment conditions. These values ​​are typically derived from historical data, baseline conditions in the relevant watershed, or ecological protection requirements. These values ​​reflect the natural state of substrate type and sediment conditions in the absence of wind power project impacts.

[0051] According to the real-time collected values ​​of bottom type and sediment condition With standard value The risk value of sediment change is calculated by the following formula: ; This formula calculates the relative deviation of the bottom sediment change, sums the ratio of the absolute difference between the two and the standard value to measure the degree of disturbance of the bottom sediment environment caused by the wind power project.

[0052] Obtained by calculation The risk of subgrade changes can be determined by monitoring the wind farm's environmental impact. If the value exceeds a preset threshold, it indicates that the wind farm project may have a significant impact on the subgrade, requiring further environmental protection measures. These measures may include adjusting construction methods, introducing subgrade protection technologies, or optimizing wind farm operations through monitoring feedback.

[0053] In an embodiment of the present invention, the biological impact risk assessment takes marine biological species and quantity data as input and evaluates the impact on biodiversity using the following formula: ;in, For the The number of species, is the total number of organisms, is the number of biological species, is the risk assessment value for biological impacts, n b Indicates the number of biological species actually monitored.

[0054] In one possible implementation, first, by deploying underwater monitoring equipment or using remote sensing technology (such as sonar, remote sensing, etc.), regularly collect data on the species and quantity of marine life. This data source can include marine biological surveys, fishing data, ecological monitoring systems, etc. The goal of monitoring is to obtain the number and type of each species in the marine ecosystem. The number of species here is refers to the number of different biological populations in the study area, while is the sum of the numbers of all species.

[0055] According to the formula, the biological impact risk assessment value The calculation involves the proportion of each organism in the entire sample. Indicates the The number of species, and The numerator of the formula calculates biodiversity based on the difference between the number of each species and the number of other species. The denominator compares the total proportion of all species to assess changes in biodiversity.

[0056] The core purpose of this formula is to measure biodiversity using information entropy. During wind turbine construction, the habitats of certain species may be destroyed or altered, leading to changes in biodiversity in the area. The formula compares data before and after construction to calculate the risk of biodiversity impacts.

[0057] Obtained The value reflects the degree of change in biodiversity. If the value is close to 0, it means that the wind power project has little impact on biodiversity; Larger values ​​indicate that wind power projects have significant impacts on ecosystems, potentially leading to the reduction or extinction of certain species. This assessment can be used to develop targeted environmental protection measures and adjust wind power project construction and operation strategies.

[0058] In the embodiment of the present invention, when When the preset threshold is exceeded, the monitoring center will immediately notify the project operation and maintenance personnel and require them to adjust the operating parameters of the wind turbine motor during construction or operation to reduce the generation of underwater noise; when When the preset threshold is exceeded, the monitoring center will notify the water quality management team and require them to promptly adjust the frequency and intensity of underwater construction operations to reduce disturbance to the water body. In addition, the monitoring center will activate water quality treatment equipment to restore the water body to normal state.

[0059] In one possible implementation, when a wind power project is in the construction or operation phase, underwater noise is an important factor affecting the marine ecological environment, especially having a significant impact on the survival and reproduction of marine life such as whales and fish. The monitoring system collects underwater noise data in real time and calculates the noise value. , and compare it with the preset noise threshold. Exceeding the threshold indicates that the current noise level poses a potential risk to the surrounding marine ecosystem. In this case, the monitoring center will immediately alert the project operations and maintenance personnel, requesting adjustments to the wind turbine motor operating parameters, such as reducing the wind turbine speed or adjusting the wind turbine angle, to reduce noise generation. Furthermore, construction methods can be optimized to avoid high-noise operations during sensitive periods, such as during marine breeding seasons.

[0060] During the construction of offshore wind power projects, changes in water quality are mainly caused by the frequency and intensity of underwater operations, such as excavation and piling during construction, which will cause agitation of the water body. The monitoring system uses real-time water quality monitoring equipment to collect water quality data such as suspended matter concentration, dissolved oxygen content, turbidity, etc. in the water body and calculates the water quality change value. .when When water quality exceeds a set threshold, it indicates excessive disturbance of the water body, potentially affecting the stability of the aquatic ecosystem. At this point, the monitoring center notifies the water quality management team and requests adjustments to the frequency and intensity of underwater operations to reduce further disturbance. Furthermore, the monitoring center activates water treatment equipment, such as purification systems, to restore the water to normal conditions and mitigate the negative impacts of deteriorating water quality on biodiversity.

[0061] In the embodiment of the present invention, when When the preset threshold is exceeded, the monitoring center will notify the bottom sediment management team and require them to increase protection measures for seabed sediments during the construction process, set up temporary protective nets, reduce disturbance of the bottom sediment caused by construction, and carry out bottom sediment repair work on a regular basis.

[0062] In one possible implementation, bottom sediment monitoring is an important component of the monitoring system during the pre-construction, construction, and operation phases of offshore wind power projects. The monitoring system collects real-time data on seabed sediments, including sediment type, thickness, particle size distribution, and organic matter content in the sediments. By analyzing this data, the system can calculate the degree of disturbance of the bottom sediment, i.e. Once this value exceeds the preset bottom sediment threshold, it means that the construction activities have caused excessive disturbance to the seabed sediments, which may lead to damage to the seabed ecological environment.

[0063] when If the threshold is exceeded, the monitoring center will immediately alert the sediment management team and request protective measures. Upon receiving the notification, the sediment management team will first assess the construction area and analyze the scope and extent of the disturbance. They will then implement appropriate protective measures, such as setting up temporary protective nets (such as sedimentation nets or fences) to prevent further disturbance or movement of sediment. Protective nets can effectively reduce disturbance of the sediment by water flow and reduce the risk of sediment becoming suspended in the water.

[0064] In addition to protective measures, regular bottom restoration is also an effective management tool. In areas where the bottom is severely disturbed, artificial restoration methods can be used, such as seeding suitable benthic organisms or using specialized materials to restore the bottom to its original sedimentary environment. These restoration efforts should be carried out regularly to ensure that the bottom is restored to its natural state as quickly as possible after construction, minimizing long-term impacts on marine ecosystems.

[0065] In the practice of the present invention, when When the preset threshold is exceeded, the monitoring center will notify the biological protection team and require them to take biological protection measures during construction and operation, set up no-fishing zones, reduce fishing and interference with organisms, and carry out regular biodiversity restoration work.

[0066] In one possible implementation, before, during, and after the construction of an offshore wind power project, the biological monitoring system will continuously collect ecological data related to organisms, including the number, distribution, species, and reproductive status of biological populations. Through data analysis, the biological impact value can be calculated. , which reflects the degree of interference of construction activities on biological populations.

[0067] once If the set threshold is exceeded, the system automatically sends an alert to the monitoring center. The biodiversity conservation team is immediately notified and initiates protective measures. This mechanism ensures a timely response, preventing long-term or severe ecological impacts on biodiversity.

[0068] To minimize the impact of wind turbine projects on marine life, the conservation team will first designate no-fishing zones based on monitoring results. Within these zones, all fishing activities are prohibited to minimize the impact of fishing activities on marine populations during construction and operation. The establishment of no-fishing zones provides an undisturbed habitat for marine life, promoting their natural reproduction and recovery.

[0069] In addition to establishing no-take zones, conservation teams regularly conduct biodiversity restoration work. This includes measures such as artificial breeding and habitat restoration. Habitat restoration, particularly of key species, can accelerate population recovery and mitigate the risk of extinction for some species.

[0070] While implementing conservation measures, the conservation team will continue to monitor and evaluate the impacts on species. By comparing data before and after implementation, they will assess the recovery of species and adjust conservation strategies based on the effectiveness of these measures.

[0071] The present invention encompasses any alternatives, modifications, equivalents, and solutions that fall within the spirit and scope of the present invention. To provide a thorough understanding of the present invention, specific details are described in detail below in connection with the preferred embodiments of the present invention, but those skilled in the art will be able to fully understand the present invention without these detailed descriptions. Furthermore, to avoid unnecessary confusion regarding the essence of the present invention, well-known methods, processes, procedures, components, and circuits have not been described in detail.

[0072] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for tracking, monitoring and managing the impact of offshore wind power projects on the marine ecological environment, characterized in that: The steps include: S1: Deploy multiple types of sensors at key locations of offshore wind power projects, including underwater noise sensors, water quality sensors, bottom sediment sensors, and biosensors, to collect real-time marine ecological and environmental data; S2: Preprocess the data collected by the sensor; S3: Establish a risk assessment model to assess the risk level of impacts on the marine ecological environment. The risk assessment model includes underwater noise pollution risk assessment, water disturbance risk assessment, bottom sediment change risk assessment, and biological impact risk assessment; S4: Generate a risk report based on the assessment results of the risk assessment model and send it to the monitoring center. The monitoring center will take corresponding management measures based on the risk report.

2. The method for tracking, monitoring and managing the impact of offshore wind power projects on the marine ecological environment according to claim 1 is characterized in that: In S1, underwater noise sensors are deployed in the underwater area around the wind turbines to detect underwater noise and collect underwater noise intensity data; water quality sensors are installed in the water bodies around the wind turbines to collect pH value, dissolved oxygen, temperature and salinity data in the water bodies; bottom sediment sensors are installed in the seabed sediments at the bottom of the wind turbines to collect bottom sediment type and sediment condition data; biological sensors are installed in the sea area around the wind turbines to collect data on the species and quantity of marine life.

3. The method for tracking, monitoring and managing the impact of offshore wind power projects on the marine ecological environment according to claim 2, characterized in that: In S2, the underwater noise intensity data is pre-processed using a wavelet transform denoising algorithm to remove noise interference and is calibrated based on data from a reference underwater noise sensor; The pH value data is pre-processed using a moving average filtering algorithm to smooth data fluctuations, and the sensor is calibrated using a standard buffer solution; The dissolved oxygen data is pre-processed using a Kalman filter algorithm to remove measurement noise and is regularly calibrated using a standard saturated aqueous solution; The temperature data is pre-processed by using a low-pass filter to smooth the temperature data and calibrated using a standard temperature source; The salinity data is pre-processed by using a median filter algorithm to remove outliers and is regularly calibrated using a standard salinity solution.

4. The method for tracking, monitoring and managing the impact of offshore wind power projects on the marine ecological environment according to claim 3 is characterized in that: The underwater noise pollution risk assessment takes underwater noise intensity data as input and evaluates the impact on marine life using the following formula: ;in, For the The underwater noise intensity collected by the sensors is As a reference to the underwater noise intensity, is the underwater noise pollution risk value, Represents the number of sensors used to assess underwater noise pollution risk.

5. The method for tracking, monitoring and managing the impact of offshore wind power projects on the marine ecological environment according to claim 4 is characterized in that: The water disturbance risk assessment takes pH, dissolved oxygen, temperature and salinity data as input and evaluates the impact on the water environment using the following formula: ； ； ； in, 、 、 and Respectively pH, dissolved oxygen, temperature and salinity collected by sensors, 、 、 and are the reference pH, dissolved oxygen, temperature and salinity, is the water disturbance risk value, is the number of sensors used to assess the risk of water disturbance.

6. The method for tracking, monitoring and managing the impact of offshore wind power projects on the marine ecological environment according to claim 5 is characterized in that: The aforementioned risk assessment of sediment change takes sediment type and sediment condition data as input and evaluates the impact on the ocean sediment using the following formula: ;in, They are real-time data of bottom type and sediment condition, are the standard values ​​of the corresponding parameters.

7. The method for tracking, monitoring and managing the impact of offshore wind power projects on the marine ecological environment according to claim 6, characterized in that: The biological impact risk assessment takes data on the species and number of marine organisms as input and assesses the impact on biodiversity using the following formula: ;in, For the The number of species, is the total number of organisms, is the number of biological species, is the risk assessment value for biological impacts, n b Indicates the number of biological species actually monitored.

8. The method for tracking, monitoring and managing the impact of offshore wind power projects on the marine ecological environment according to claim 7 is characterized in that: when When the preset threshold is exceeded, the monitoring center will immediately notify the project operation and maintenance personnel and require them to adjust the operating parameters of the wind turbine motor during construction or operation to reduce the generation of underwater noise; when When the preset threshold is exceeded, the monitoring center will notify the water quality management team and require them to promptly adjust the frequency and intensity of underwater construction operations to reduce disturbance to the water body. In addition, the monitoring center will activate water quality treatment equipment to restore the water body to normal.

9. The method for tracking, monitoring and managing the impact of offshore wind power projects on the marine ecological environment according to claim 8, characterized in that: when When the preset threshold is exceeded, the monitoring center will notify the bottom sediment management team and require them to increase protection measures for seabed sediments during the construction process, set up temporary protective nets, reduce disturbance of the bottom sediment caused by construction, and carry out bottom sediment repair work on a regular basis.

10. The method for tracking, monitoring and managing the impact of offshore wind power projects on the marine ecological environment according to claim 9, characterized in that: when When the preset threshold is exceeded, the monitoring center will notify the biological protection team and require them to take biological protection measures during construction and operation, set up no-fishing zones, reduce fishing and interference with organisms, and carry out regular biodiversity restoration work.

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