Wave energy device grid cluster interconnection and dynamic optimization method

Abstract

The application discloses a wave energy device grid cluster type interconnection and dynamic optimization method, S1. Collect the marine environment data set in the target sea area; S2. Establish a marine environment database; S3. Based on the marine environment database, an optimization model of wave energy device cluster arrangement is constructed; S4. The optimization model is solved by using the vortex optimization algorithm, and the optimal position distribution of the wave energy device under the initial layout is calculated; S5. The optimal position distribution under the initial layout is taken as input, so that the wave energy device cluster can maintain structural stability under extreme sea conditions; S6. Based on the adjusted device arrangement scheme, the anchoring scheme of the wave energy device is optimized by using the public anchoring, and the wave energy devices are cooperatively stressed through the shared anchoring system. The application optimizes the layout of the public anchoring point, so that multiple wave energy devices can share the anchoring system, thereby improving the structural stability of the overall system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wave energy equipment, in particular to a wave energy equipment grid cluster interconnection and dynamic optimization method. BACKGROUND

[0002] With the development of ocean renewable energy technology, wave energy as a clean and sustainable energy form has gradually attracted attention. Wave energy equipment captures and converts ocean wave energy to generate electricity, which becomes an important supplement in the future energy structure. However, the existing wave energy equipment arrangement and interconnection method still faces many technical challenges, especially in terms of device cluster arrangement, power stability and energy capture efficiency.

[0003] Currently, wave energy equipment is usually deployed in a single machine form, each device is independently anchored in the marine environment and individually converts energy, but there are obvious limitations. First, the single arrangement method is easily affected by uneven wave impact forces in complex marine environments, leading to unstable stress on the device, affecting its long-term operation reliability. Second, the layout of traditional wave energy equipment relies on experience and rough ocean environment assessment, lacking systematic optimization methods, resulting in strong hydrodynamic interference effects between devices, which reduces the energy capture efficiency of some devices and affects the overall power generation capacity. In addition, the independent anchoring of single machine devices increases the cost of marine construction and maintenance difficulty. Once the device drifts or is damaged, it requires a large amount of manpower and resource investment for replacement and repair.

[0004] In recent years, researchers have begun to explore wave energy equipment cluster arrangement and interconnection methods to improve wave energy conversion efficiency and device operation stability. Some research attempts to arrange wave energy equipment through fixed topology to make multiple devices work cooperatively. However, the fixed topology method has exposed a series of problems in practical application. First, due to the dynamic changes of the marine environment, the fixed topology structure is difficult to adapt to extreme sea conditions, leading to uneven stress on the device and even damage in severe weather conditions. Second, the existing device connection method mostly uses rigid connection or independent anchoring, which is difficult to adjust flexibly when the device is replaced or maintained, affecting the overall stability and scalability of the cluster. In addition, the existing optimization method mainly focuses on local arrangement optimization, lacking a systematic method that can combine real-time ocean environment data, globally optimize device layout and connection method.

[0005] In summary, the existing arrangement and connection method of wave energy equipment still has many shortcomings in terms of device stress stability, energy capture efficiency and adaptability to complex sea conditions. There is an urgent need for a cluster arrangement method that can adjust the device connection relationship based on real-time ocean environment data, optimize device layout, improve overall energy conversion efficiency and have good adaptability to overcome the limitations of existing technology. SUMMARY

[0006] An object of the present application is to provide a wave energy device grid cluster interconnection and dynamic optimization method. The present application optimizes the layout of common anchor points, so that multiple wave energy devices can share the anchoring system, thereby improving the structural stability of the overall system.

[0007] According to an embodiment of the present application, a wave energy device grid cluster interconnection and dynamic optimization method comprises the following steps:

[0008] S1. Collecting a set of marine environment data in a target sea area;

[0009] S2. Unifying the format of the set of marine environment data and storing the marine environment data records to form a marine environment database;

[0010] S3. Building an optimization model for the cluster arrangement of wave energy devices based on the marine environment database;

[0011] S4. Solving the optimization model using a vortex optimization algorithm to calculate the optimal position distribution of the wave energy devices under the initial layout, so that each wave energy device can share the wave impact force under the action of waves;

[0012] S5. Taking the optimal position distribution under the initial layout as input, applying a dynamic topology adaptive optimization method to adjust the connection relationship and relative position between devices according to real-time marine environment data, so that the wave energy device cluster remains structurally stable under extreme sea conditions;

[0013] S6. Based on the adjusted device arrangement scheme, optimizing the anchoring scheme of the wave energy devices using a common anchor, realizing the cooperative stress of the wave energy devices through sharing the anchoring system, and realizing the direct connection between the wave energy devices using a modular sleeve connection, so that only the connection of a single wave energy device module is affected when the wave energy device is replaced or locally maintained, without affecting the anchoring system of the overall wave energy device cluster.

[0014] Optionally, the S1 comprises the following steps:

[0015] S11. Collecting wave data of the target sea area, the wave data including the first group of wave heights , wave lengths , wave propagation speeds , and wave propagation directions to form a wave data set ;

[0016] S12. Collecting tide change data of the target sea area, the tide change data including the first tide height of a tide period the rate of rise of the tide for the first tidal cycle the rate of fall of the tide for the first tidal cycle the length of the first tidal cycle to form a tidal variation data set ;

[0017] S13. Collect wind speed data of the target sea area, the wind speed data including a first set of wind speed magnitude, wind speed direction and wind speed variation rate, to form a wind speed data set ;

[0018] S14. Collect current speed data of the target sea area, the current speed data including a first set of current speed magnitude, current direction and current speed variation rate, to form a current speed data set ;

[0019] S15. Combine the wave data set, the tidal variation data set, the wind speed data set and the current speed data set obtained in steps S11 to S14 to construct a marine environment data set of the target sea area, defined as follows:

[0020] .

[0021] Optionally, the S2 includes the following steps:

[0022] S21. Perform data integrity check on the marine environment data set to eliminate missing data, data not meeting measurement standards and repeated data, to form a marine environment data set after data cleaning;

[0023] S22. Perform formatting processing on the marine environment data set after cleaning to convert all data into a unified storage format, keep the time series data of the wave data set, the tidal variation data set, the wind speed data set and the current speed data set synchronized, and form a marine environment data set after formatting;

[0024] S23. Perform data normalization processing on the marine environment data set after formatting, define a normalization transformation function to map all data into a standardized range, to obtain a marine environment data set after normalization ; ​​​​​​​​​​​​​​​​

[0025] S24. Normalized marine environment dataset Optimize data index based on data collection time and geographic coordinates Construct index mapping relationships to form a time-space index matrix :

[0026]

[0027] in, For the The timestamp of the group data, are the latitude and longitude coordinates of the data collection point, is the corresponding marine environment data at this time and space location, is the total amount of marine environmental data;

[0028] S25. Based on the time-space index matrix The marine environment data is stored in the database and the normalized marine environment data set is Stored in the marine environment database with an index structure , and set up the database call interface to query the marine environment database Obtain wave data, tidal change data, wind speed data, and ocean current speed data for different time periods and geographical locations.

[0029] Optionally, S3 includes the following steps:

[0030] S31. Based on the marine environment database Constructing an optimized input parameter set for clustered deployment of wave energy devices ;

[0031] S32. Based on the optimized input parameter set Determine the area for wave energy equipment deployment :

[0032]

[0033] in, Boundary coordinates of the area where wave energy equipment is placed, The specific location of the wave energy equipment within the layout area. The layout area of ​​the wave energy equipment is based on the wave height. The range of changes, tidal cycle The fluctuation range and current direction Determination of impact on stability of wave energy devices;

[0034] S33. Based on wave data and ocean current speed data Calculating the density of wave energy devices , optimize the energy capture capacity per unit area and avoid hydrodynamic interference between wave energy devices:

[0035]

[0036] in, is the total number of wave energy devices, The area of ​​the layout area, the layout density optimization is affected by the wavelength and flow rate impact, minimizing interactions between wave energy devices;

[0037] S34. Combined with the density of wave energy equipment Hydrodynamic interference between wave energy devices and optimize the spacing between wave energy devices :

[0038]

[0039] in, is the optimal solution for device spacing, Indicates the Device and The physical distance between devices, For the The hydrodynamic interaction cost of a wave energy device with surrounding wave energy devices, For wave energy devices The wave energy capture power at For wave energy devices The wave energy capture power at For wave energy devices The ocean current speed at For wave energy devices The current speed at and wind speed direction Influence, To optimize the weight coefficient;

[0040] S35. Calculate the optimal anchor point location of the public anchoring system based on tidal change data and wind speed data ;

[0041] S36. Determine the cluster coordination force strategy of wave energy equipment, calculate the force balance state between wave energy equipment, and set the connection relationship between wave energy equipment :

[0042]

[0043] in, Indicates wave energy equipment Connection relationship between wave energy devices , Force at connection, Maximum allowable connection force threshold, Wave energy device connection optimization combined with current velocity variation rate Influence on relative motion state of wave energy devices;

[0044] S37. Construct an optimization model of wave energy device cluster arrangement according to steps S31-S36 .

[0045] Optionally, the S4 comprises the following steps:

[0046] S41. Determine the wave energy device arrangement area , wave energy device arrangement density , wave energy device spacing , common anchoring point and wave energy device connection relationship in the area according to the optimization model . Each wave energy device position candidate solution set represents an initial position distribution of a group of wave energy devices, and meets the minimum distance constraint between wave energy devices and the flow field adaptability requirement:

[0047]

[0048] S42. Calculate the local wave energy capture power and hydrodynamic interference cost of each wave energy device in each wave energy device position candidate solution set according to the wave data set , calculate the anchoring support force of the wave energy device according to the common anchoring point and the wave energy device force model , and construct an initial objective function to evaluate the overall performance of the wave energy device position candidate solution set:

[0049]

[0050] Where, is the maximum energy capture value in theory without interference, is the weight coefficient reflecting the priority of hydrodynamic interference and energy capture, represents the wave energy device number;

[0051] Solve to get the position distribution under the initial layout ;

[0052] S43. Position distribution under initial layout On this basis, an improved multi-scale vortex flow field model is introduced to calculate the local vortex flow field velocity and vortex intensity at each wave energy device :

[0053]

[0054] wherein, is the physical distance between the wave energy device and , is a small positive number to avoid division by zero, is the vortex attenuation coefficient, which controls the decay rate of the vortex effect with distance, is the coupling factor between the wave energy device and based on dynamic topology adaptive optimization, is the vortex intensity;

[0055] S44. Combined with the improved multi-scale vortex flow field model, a multi-objective dynamic optimization strategy is adopted, and the wave energy device position is iteratively adjusted using the vortex optimization algorithm, with the goal of minimizing local force imbalance and hydrodynamic interference, and maximizing local wave energy capture efficiency. The comprehensive objective function is constructed:

[0056]

[0057] wherein, denotes the force imbalance of the wave energy device under the current layout, is the actual current velocity at the wave energy device , is the corresponding optimization weight coefficient;

[0058] The iterative update formula adopts an adaptive step size strategy:

[0059]

[0060] wherein, is the position information of the wave energy device in the th iteration, is the basic step size adjustment factor, is the maximum force imbalance value allowed in the design, is an additional disturbance term based on real-time environmental feedback;

[0061] S45. In the iteration process, monitor the change of the comprehensive objective function , when the convergence condition is met:

[0062]

[0063] wherein is a preset convergence threshold, determine that the iteration is terminated, and record the solution with the optimal objective function value in the current wave energy device position candidate solution set as the optimal position distribution under the initial layout .

[0064] Optionally, the S5 comprises the following steps:

[0065] S51. According to the optimal position distribution under the initial layout , construct a topological network between the wave energy devices ;

[0066] S52. In combination with the wave data set and the current data set , calculate the force matrix of the wave energy devices under extreme sea conditions:

[0067]

[0068] wherein, is the wave impact force at the wave energy device , is the current force at the wave energy device , is the set of wave energy devices directly connected to the wave energy device , is the connection force between the wave energy device and the wave energy device , is the anchoring support force at the wave energy device . Calculate the overall force balance degree of the wave energy device topological network: wherein,

[0069] is the average force value of all wave energy devices:

[0070] S53. According to the force balance degree

[0071] , adjust the connection relationship , and the optimization objective is to minimize the force imbalance:

[0072]

[0073] ​​​​

[0074] wherein the first term balances the force of the wave energy device, and the second term represents the connection cost of the topological network affected by the distance between wave energy devices and the connection stability, is the topological optimization weight factor;

[0075] S54. Based on the topological optimization, in combination with the real-time changes of the marine environment, the marine environment dataset is used to dynamically and adaptively adjust the topological network, and update the topological network :

[0076]

[0077] wherein, represents the topological change from t to t+1, is the topological network of the wave energy device at time t+1;

[0078] S55. Calculate the force balance after topological optimization , calculate the connection stability after topological optimization :

[0079]

[0080] wherein, is the connection stability between device j and device k after optimization;

[0081] If the force balance after topological optimization is lower than the set value, and the connection stability after topological optimization is lower than the connection cost threshold, then accept the optimization result, otherwise return to S53 for adjustment.

[0082] Optionally, the S53 adopts the following topological adjustment rules:

[0083] Increase connection: if the force of a wave energy device is higher than the average value , increase the connection between it and the adjacent wave energy device, so that the force can be shared;

[0084] Delete connection: if a connection causes excessive force interference or low connection stability, delete the connection;

[0085] Adjust the connection weight: if the force of a wave energy device is uneven, adjust the connection weight of the adjacent wave energy device to optimize the force transmission relationship.

[0086] Optionally, the set rules of the S53 are as follows: ​

[0087] If the wind speed or the tide changes more than a threshold value , the topology is reconfigured;

[0088] If the stress balance is lower than a set value, the connection relationship is optimized ;

[0089] If the wave energy device drift trend exceeds a set value, the connection point is optimized and the anchoring strategy is adjusted.

[0090] The beneficial effects of the present application are:

[0091] (1) The present application proposes a wave energy device arrangement optimization method based on vortex optimization algorithm, which can calculate the optimal position distribution in the initial layout stage to make the wave energy devices reasonably share the wave impact force and improve the energy conversion efficiency. The present application balances between minimizing hydrodynamic interference and maximizing wave energy capture power by constructing a multi-objective optimization function, and realizes dynamic iterative adjustment of device position by combining vortex optimization algorithm. The vortex optimization algorithm simulates the natural motion characteristics of vortex flow field to make the device avoid high interference area in the optimization process, and uses local energy enrichment area for reasonable arrangement to ensure efficient energy capture of the overall system in long-term operation.

[0092] (2) The present application adopts a dynamic topology adaptive optimization method to adjust the connection relationship and relative position between devices according to real-time marine environment data, ensuring that the wave energy device cluster remains structurally stable in extreme sea conditions. Traditional wave energy device connection methods usually use fixed anchoring or rigid connection, which leads to excessive stress on some devices in the case of large changes in sea current, wind speed and tide, thereby affecting the overall stability of the system. The present application establishes a topology network model, calculates the device stress matrix and optimizes the device connection relationship based on the minimum stress imbalance target, so that the device can dynamically adapt to different sea conditions. The present application can automatically adjust the connection mode of the device when extreme sea conditions occur, increase the connection points of high-stress devices to share the impact force, or reduce the connection of low stability to optimize the stress balance.

[0093] (3) The present application adopts a shared anchoring system and modular sleeve connection method to realize cooperative stress and flexible maintenance between wave energy devices. Traditional wave energy devices mostly use independent anchoring, with each device equipped with an anchoring system, which not only increases the construction cost, but also leads to a lack of stress cooperation between devices, making some devices prone to drift or damage in high sea conditions. By optimizing the layout of the common anchoring point, multiple wave energy devices can share the anchoring system, thereby improving the structural stability of the overall system. BRIEF DESCRIPTION OF DRAWINGS

[0094] The accompanying drawings are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and are intended to explain the application, but are not intended to limit the application. In the drawings:

[0095] Figure 1 A flow chart of a wave energy device grid cluster interconnection and dynamic optimization method according to the present application. DETAILED DESCRIPTION

[0096] The application will now be described in further detail with reference to the drawings. These drawings show only the essential features of the application and are therefore to be regarded only as a schematic representation of the basic structure of the application.

[0097] Reference Figure 1 A wave energy device grid cluster interconnection and dynamic optimization method, comprising the following steps:

[0098] S1. Collecting a marine environment data set in a target sea area;

[0099] S2. Uniformly formatting the marine environment data set and storing the marine environment data record to form a marine environment database;

[0100] S3. Constructing an optimization model for wave energy device cluster arrangement based on the marine environment database;

[0101] S4. Solving the optimization model using a vortex optimization algorithm to calculate the optimal position distribution of the wave energy devices under the initial layout, which enables each wave energy device to share the wave impact force under the action of waves;

[0102] S5. Taking the optimal position distribution under the initial layout as input, applying a dynamic topology adaptive optimization method to adjust the connection relationship and relative position between the devices according to real-time marine environment data, so that the wave energy device cluster remains structurally stable under extreme sea conditions;

[0103] S6. Based on the adjusted device arrangement scheme, optimizing the anchoring scheme of the wave energy devices using a common anchor to realize collaborative force bearing between the wave energy devices through the shared anchoring system, and using modular sleeve connection to realize direct connection between the wave energy devices, so that only the connection of a single wave energy device module is affected when the wave energy device is replaced or locally maintained, without affecting the anchoring system of the entire wave energy device cluster.

[0104] In this embodiment, S1 comprises the following steps:

[0105] S11. Collecting wave data of the target sea area, the wave data including the first group wave height , wavelength wave propagation speed and wave propagation direction , forming a wave dataset ;

[0106] S12. Collecting tidal variation data of the target sea area, the tidal variation data including tidal height of the first tidal cycle , rising rate of the first tidal cycle , falling rate of the first tidal cycle , and length of the first tidal cycle , forming a tidal variation dataset ; S13. Collecting wind speed data of the target sea area, the wind speed data including wind speed of the first group , wind direction , and wind speed variation rate , forming a wind speed dataset

[0107] ; S14. Collecting sea current speed data of the target sea area, the sea current speed data including current speed of the first group , sea current direction , and current speed variation rate , forming a sea current speed dataset ;

[0108] S15. Combining the wave dataset , the tidal variation dataset , the wind speed dataset , and the sea current speed dataset obtained in steps S11 to S14, constructing a marine environment dataset of the target sea area , defined as follows:

[0109] . In the embodiment, S2 includes the following steps: S21. Performing data integrity check on the marine environment dataset, eliminating missing data, data not meeting measurement standards, and repeated data, forming a marine environment dataset after data cleaning;

[0110] .

[0111] In the embodiment, S2 includes the following steps:

[0112] S21. Performing data integrity check on the marine environment dataset, eliminating missing data, data not meeting measurement standards, and repeated data, forming a marine environment dataset after data cleaning;

[0113] ​​​S22. Format the cleaned marine environment dataset, convert all data into a unified storage format, synchronize the time series data of the wave dataset, tidal change dataset, wind speed dataset, and current speed dataset, and form a formatted marine environment dataset;

[0114] S23. Perform data normalization based on the formatted marine environment dataset, define a normalization transformation function to map all data into a standardized range, and obtain a normalized marine environment dataset. ;

[0115] S24. Normalized marine environment dataset Optimize data index based on data collection time and geographic coordinates Construct index mapping relationships to form a time-space index matrix :

[0116]

[0117] in, For the The timestamp of the group data, are the latitude and longitude coordinates of the data collection point, is the corresponding marine environment data at this time and space location, is the total amount of marine environmental data;

[0118] S25. Based on the time-space index matrix The marine environment data is stored in the database and the normalized marine environment data set is Stored in the marine environment database with an index structure , and set up the database call interface to query the marine environment database Obtain wave data, tidal change data, wind speed data, and ocean current speed data for different time periods and geographical locations.

[0119] In this embodiment, S3 includes the following steps:

[0120] S31. Based on the marine environment database Constructing an optimized input parameter set for clustered deployment of wave energy devices ;

[0121] S32. Based on the optimized input parameter set Determine the area for wave energy equipment deployment :

[0122]

[0123] in, Boundary coordinates of the area where wave energy equipment is placed, The specific location of the wave energy equipment within the layout area. The layout area of ​​the wave energy equipment is based on the wave height. The range of changes, tidal cycle The amplitude of fluctuation and direction of ocean current Determination of impact on stability of wave energy devices;

[0124] S33. Based on wave data and ocean current speed data Calculating the density of wave energy devices , optimize the energy capture capacity per unit area and avoid hydrodynamic interference between wave energy devices:

[0125]

[0126] in, is the total number of wave energy devices, The area of ​​the layout area, the layout density optimization is affected by the wavelength and flow rate impact, minimizing interactions between wave energy devices;

[0127] S34. Combined with the density of wave energy equipment Hydrodynamic interference between wave energy devices and optimize the spacing between wave energy devices :

[0128]

[0129] in, is the optimal solution for device spacing, Indicates the Device and The physical distance between devices, For the The hydrodynamic interaction cost of a wave energy device with surrounding wave energy devices, For wave energy devices The wave energy capture power at For wave energy devices The wave energy capture power at For wave energy devices The ocean current speed at For wave energy devices The current speed at and wind speed direction Influence, To optimize the weight coefficient;

[0130] S35. Calculate the optimal anchor point location of the public anchoring system based on tidal change data and wind speed data ;

[0131] S36. Determine the cluster coordination force strategy of wave energy equipment, calculate the force balance state between wave energy equipment, and set the connection relationship between wave energy equipment :

[0132]

[0133] in, Indicates wave energy equipment and wave energy equipment The connection relationship between is the force at the connection, The maximum allowable connection stress threshold, wave energy device connection optimization combined with the current velocity change rate Impact on the relative motion state of wave energy equipment;

[0134] S37. Construct an optimization model for the clustered layout of wave energy equipment according to steps S31-S36 .

[0135] In this embodiment, S4 includes the following steps:

[0136] S41. Based on the optimization model The wave energy equipment layout area determined in , wave energy equipment layout density , Wave energy equipment spacing , public anchorage points and connection relationship of wave energy equipment In the area Constructing candidate solution sets for wave energy equipment locations , each wave energy device location candidate solution set Represents the initial position distribution of a group of wave energy devices, and satisfies the minimum distance constraint between wave energy devices and the flow field adaptability requirement:

[0137]

[0138] S42. Based on wave data set Calculate the candidate solution set for each wave energy device location The local wave energy capture power of each wave energy device and hydrodynamic interference costs , based on common anchor points Calculate the anchoring support force of wave energy equipment with the force model of wave energy equipment , and construct the initial objective function To evaluate the overall performance of the candidate solution set of wave energy device locations:

[0139]

[0140] where, is the theoretical maximum energy capture value under non-interference conditions, is the weight coefficient reflecting the water dynamic interference and energy capture priority, represents the wave energy device number;

[0141] By solving the position distribution under the initial layout is obtained;

[0142] S43. On the basis of the position distribution under the initial layout , the improved multi-scale vortex flow field model is introduced to calculate the local vortex flow field velocity and the vortex intensity at each wave energy device :

[0143]

[0144] where, is the physical distance between the wave energy device and , is a small positive number to avoid division by zero, is the vortex decay coefficient, which controls the decay rate of the vortex effect with distance, is the coupling factor between the wave energy device and based on dynamic topology adaptive optimization, is the vortex intensity;

[0145] S44. Combined with the improved multi-scale vortex flow field model, a multi-objective dynamic optimization strategy is adopted, and the vortex optimization algorithm is used to iteratively adjust the wave energy device location, aiming to minimize the local force imbalance and water dynamic interference, and maximize the local wave energy capture efficiency, to construct a comprehensive objective function:

[0146]

[0147] where, represents the force imbalance of the wave energy device under the current layout, is the actual sea current velocity at the wave energy device , is the corresponding optimization weight coefficient;

[0148] The iterative update formula adopts an adaptive step strategy:

[0149]

[0150] wherein, is the wave energy device at the i-th iteration, is the position information of the i-th iteration, is the base step adjustment factor, is the maximum force imbalance value allowed in the design, is the additional disturbance term based on real-time environmental feedback;

[0151] S45. In the iteration process, monitor the change of the comprehensive objective function , when the convergence condition is met:

[0152]

[0153] wherein is the preset convergence threshold, determine that the iteration is terminated, and record the solution with the optimal objective function value in the current wave energy device position candidate solution set as the optimal position distribution under the initial layout .

[0154] In this embodiment, S5 includes the following steps:

[0155] S51. According to the optimal position distribution under the initial layout , construct a topological network between the wave energy devices ;

[0156] S52. Combine the wave data set and the current data set , calculate the force matrix of the wave energy devices under extreme sea conditions:

[0157]

[0158] wherein, is the wave impact force at the wave energy device , is the current force at the wave energy device , is the set of wave energy devices directly connected to the wave energy device , is the connection force between the wave energy device and the wave energy device , is the anchoring support force at the wave energy device . Calculate the overall force balance degree of the wave energy device topological network:

[0159] ​​​​

[0160] wherein, is the average force value of all wave energy devices:

[0161]

[0162] S53. According to the force balance degree Adjust the connection relationship, and the optimization goal is to minimize the force imbalance:

[0163] wherein, the first term balances the force of the wave energy device, and the second term represents the connection cost of the topological network

[0164] Affected by the distance between wave energy devices and the connection stability, is the topological optimization weight factor; S54. On the basis of topological optimization, combined with the real-time changes of the marine environment, use the marine environment data set

[0165] to dynamically and adaptively adjust the topological network, and update the topological network :

[0166]

[0167] wherein, represents the topological change from t to t+1, is the wave energy device topological network at time t+1;

[0168] S55. Calculate the force balance after topological optimization , calculate the connection stability after topological optimization :

[0169]

[0170] wherein, is the connection stability between device j and device k after optimization;

[0171] If the force balance after topological optimization is lower than the set value, and the connection stability after topological optimization is lower than the connection cost threshold value, then the optimization result is accepted, otherwise return to S53 for adjustment.

[0172] In this embodiment, S53 adopts the following topological adjustment rules:

[0173] Increase connection: if the force of a wave energy device is higher than the average value ​If the force on the wave energy device is too large, the connection with the adjacent wave energy device is increased to share the force;

[0174] Delete connection: if a connection causes excessive force interference or low connection stability, delete the connection;

[0175] Adjust the connection weight: if a wave energy device is unevenly stressed, adjust the connection weight of adjacent wave energy devices to optimize the force transmission relationship.

[0176] In this embodiment, the setting rules are:

[0177] If the wind speed or the tide changes more than the threshold value , the topology reconstruction is performed;

[0178] If the force balance degree is lower than the set value, optimize the connection relationship ;

[0179] If the wave energy device drifts beyond the set value, optimize the connection point and adjust the anchoring strategy.

[0180] This embodiment discloses the deletion and addition of connections through modular sleeve connection:

[0181] I. Structural design logic of modular sleeve connection (hardware layer)

[0182] Modular sleeve connection refers to the connection node structure between each wave energy device, which can be plugged, rotated, and locked, and has the following structural characteristics:

[0183] 1. Standardization of sleeve connection interface

[0184] Each wave energy device is pre-set with connection interface slots in multiple directions (such as the four sides of east, south, west, and north), and the interface is a mechanically standardized multi-channel cylindrical sleeve structure; each slot supports bidirectional plugging, allowing connection with devices in different directions.

[0185] 2. Embedded electric control mechanical locking structure

[0186] The sleeve connection head is internally provided with a mechatronic locking structure, which supports release or locking of the plug through remote signals; the unlocking or plugging action can be controlled through electrical signals to complete the connection addition / deletion.

[0187] 3. Elastic buffer and rotation tolerance

[0188] The sleeve is provided with a flexible buffer rubber layer and a universal roller structure, which allows a certain relative rotation and swing between the devices in the connected state to adapt to the dynamic motion of waves and tides, and ensures that stress concentration will not occur between the devices due to rigid connection.

[0189] II. Operation of deleting connection (topology adaptation layer)

[0190] In combination with the dynamic topology optimization mechanism, the essence of deleting connection is to disconnect the sleeve connection structure between two wave energy devices, so that they are separated from the current topology structure.

[0191] The implementation steps are as follows:

[0192] The system calculates the topology redundancy or instability of a certain connection , such as high connection cost and uneven stress; the disconnecting instruction is issued to the connection module between the devices and ; the electric control locking device in the modular sleeve receives the instruction and releases the plug-in part; the connection is naturally slipped out with the wave motion, and the connection relationship is "softly removed"; at this time, the edge is deleted in the topology network .

[0193] III. Operation of increasing connection (control layer + self-organization ability)

[0194] After topology optimization, it is determined that two devices and should be connected, i.e. "increasing connection" is needed, and the implementation mechanism is as follows:

[0195] Scenario one: automatic docking of devices at close distance (high self-organization cluster)

[0196] The topology optimization determines that the connection should be made, and the system sends the approaching and docking instructions to the two devices; the thruster, attitude adjustment system or water flow guiding structure is used to make the two devices slowly approach each other; the connection interface of each device is provided with an intelligent alignment guiding magnetic ring and a rudder fine-tuning system; the two modular sleeves automatically contact and plug together; after the sleeve completes the plugging, the electric control locking system automatically closes to form a new connection edge .

[0197] Scenario two: use relay module to realize connection

[0198] If the distance between two devices is too large, a relay float (connection module) can be used as a bridge node; the relay module is connected to the target device through two sleeves to realize virtual connection.

[0199] IV. Summary of dynamic adaptation characteristics of connection relationship

[0200]

[0201] Example 1: In August 2024, we deployed a group of wave energy device clusters in a certain sea area of the East China Sea (122.4 °E, 29.8 °N), and conducted experiments using the method of the invention to verify its stability, energy capture efficiency and maintenance convenience in complex sea conditions. A total of 20 floating wave energy devices were deployed, of which 10 used the traditional independent anchoring and fixed topology method, and 10 used the shared anchoring and dynamic topology optimization method of the invention. The operation of the two methods was recorded respectively.

[0202] On August 1, 2024, the experimental team began to arrange the equipment in the target sea area. The 10 devices of the traditional method were arranged at equal intervals of 50m, each using a separate seabed anchoring system. The other group used the method of the invention. First, the tidal, current, wind speed and wave characteristics data of the past three years were analyzed using the marine environment database. After vortex optimization algorithm calculation, the optimal device arrangement scheme was obtained, with device spacing adjusted to 40-60m, and a shared anchoring system was used, so that every 3-4 devices share a seabed anchoring point.

[0203] On August 5, after the initial arrangement of the equipment, the experimental team used an unmanned underwater vehicle to detect the hydrodynamic interference between the devices and adjust the connection method. The devices of the traditional method still used rigid fixed connection, while the devices of the invention method used modular sleeve connection, allowing the devices to dynamically adjust the connection relationship when the force changes.

[0204] On September 3, 2024, affected by strong winds (wind speed up to 12.5m / s), the experimental team monitored that the devices arranged in the traditional way had uneven force problems. The force value of device number T-06 reached 2.8kN (exceeded the design limit of 2.5kN), causing the connection structure to deform significantly. While the devices D-03, D-05 and D-07 using the method of the invention had forces between 1.9-2.2kN under the same wind speed, the force balance was significantly improved.

[0205] Because the devices of the traditional method cannot adaptively adjust, T-06 has too much force, so the team decides to maintain it in advance and sends a diver to check the damage. The method of the invention automatically adjusts the connection between D-03 and D-05 due to dynamic topology optimization, allowing them to share more current impact forces. Finally, when the wind speed increases to 15m / s, the devices remain stable.

[0206] On October 2, 2024, a typhoon affected the sea area, with wind speeds reaching 22m / s and wave heights reaching 5.3m, posing a major challenge to all devices.

[0207] Damage to devices arranged in the traditional way:

[0208] The float connecting bolt of T-02 was broken due to excessive force, the device lost stability, and part of it drifted 120 m to the northeast;

[0209] T-06 was damaged in the storm in September, and this time it was due to the impact of the current, causing the fixed anchoring point to loosen and the device to drift;

[0210] T-08 was damaged due to uneven force and connection breakage, causing the entire device to detach from the array and drift 85 m to the southeast.

[0211] Device damage of the method of the present application:

[0212] D-05 and D-07 shared anchoring systems triggered topology adaptive optimization when the force peak was 3.1 kN, and the device connection weight was redistributed, reducing the force to 2.6 kN;

[0213] D-03 automatically adjusts the connection method between devices when the force is too high, and the connection state is stable with no obvious damage;

[0214] All devices drifted no more than 15 m, and no device detached from the array.

[0215] On October 3, after the typhoon, the experimental team checked the device status and found that the devices of the method of the present application were all in working condition, while the devices of the traditional method were damaged 3, drifted 2, and needed to be sent to repair the ship for recovery and re-arrangement.

[0216] From August 2024 to February 2025, we compared the long-term operation data of the two methods, as follows:

[0217]

[0218] The data shows that the method of the present application performs better in energy capture, device stability, and maintenance cost, especially in extreme sea conditions during typhoons, all devices remain normal operation, while the device damage rate of the traditional method is as high as 30%, which needs additional maintenance and recovery work.

[0219] In summary, the wave energy device grid cluster interconnection method of the present application, combined with dynamic topology optimization, shared anchoring, and modular connection technology, achieves higher energy capture efficiency, more stable device operation state, and lower construction and maintenance cost, providing a more efficient and reliable solution for future large-scale ocean renewable energy development.

[0220] The application provides a wave energy device arrangement optimization method based on a vortex optimization algorithm, which can calculate an optimal position distribution in an initial layout stage, so that the wave energy device can reasonably share wave impact force and improve energy conversion efficiency, the application balances between minimizing hydrodynamic interference and maximizing wave energy capture power by constructing a multi-objective optimization function, and realizes dynamic iterative adjustment of the device position in combination with a vortex optimization algorithm, the vortex optimization algorithm simulates natural motion characteristics of a vortex flow field, so that the device can avoid a high interference area in the optimization process, and the device is reasonably arranged by using a local energy enrichment area, and high energy capture efficiency of the overall system in long-term operation is ensured.

[0221] The application adopts a dynamic topology adaptive optimization method, adjusts the connection relationship and relative position between devices according to real-time marine environment data, and ensures that the wave energy device cluster can still maintain structural stability under extreme sea conditions, and a traditional wave energy device connection mode usually adopts fixed anchoring or rigid connection, so that part of the devices bears too high stress under the condition that the current, wind speed and tide change greatly, thereby affecting the overall stability of the system, the application establishes a topology network model, combines device stress matrix calculation and optimizes and adjusts the device connection relationship based on the minimum stress imbalance target, so that the device can dynamically adapt under different sea conditions, the application can automatically adjust the connection mode of the device when extreme sea conditions occur, increase the connection points of high-stress devices to share impact force, or reduce the connection of low stability to optimize stress balance.

[0222] The application adopts a shared anchoring system and a modular sleeve connection mode, realizes collaborative stress and flexible maintenance between wave energy devices, and most traditional wave energy devices adopt independent anchoring, each device is equipped with an anchoring system, which not only increases construction cost, but also causes lack of stress collaboration between devices, so that part of the devices are easy to drift or damaged under high sea conditions, a plurality of wave energy devices can share the anchoring system by optimizing the layout of the common anchoring point, so as to improve the structural stability of the overall system.

[0223] The above is only a preferred specific embodiment of the application, but the protection scope of the application is not limited thereto, any person skilled in the art can make equivalent replacement or change according to the technical solution and the inventive concept of the application within the technical range disclosed by the application, which should be covered in the protection scope of the application.

Claims

1. A method for interconnecting and dynamically optimizing grid clusters of wave energy devices, characterized in that: The steps include: S1. Build an optimization model for the clustered deployment of wave energy devices based on the marine environment database and collect marine environment datasets within the target sea area; S2. Organize the marine environment data set into a unified format, store it into marine environment data records, and establish a marine environment database; S3. Build an optimization model for clustered deployment of wave energy devices based on the marine environment database; S4. Solving the optimization model using an eddy current optimization algorithm to calculate the optimal position distribution of the wave energy devices under the initial layout, wherein the optimal position distribution under the initial layout enables each wave energy device to share the impact force of the waves; S5. Using the optimal position distribution under the initial layout as input, a dynamic topology adaptive optimization method is applied to adjust the connection relationship and relative position between devices based on real-time ocean environmental data, so that the wave energy device cluster maintains structural stability under extreme sea conditions; S6. Based on the adjusted equipment layout, a common anchoring scheme is used to optimize the anchoring scheme of the wave energy equipment, so that the wave energy equipment can be coordinated through a shared anchoring system. A modular sleeve connection is used to achieve direct connection between the wave energy equipment. When the wave energy equipment is replaced or partially maintained, only the connection of a single wave energy equipment module is affected, without affecting the anchoring system of the entire wave energy equipment cluster.

2. A method for interconnecting and dynamically optimizing grid clusters of wave energy devices according to claim 1, characterized in that: Said S1 comprises the following steps: S11. Collect wave data of the target sea area, the wave data including the i-th group of wave height H i , wavelength λ i , wave propagation speed v i and the wave propagation direction θ i , forming a wave data set D wave ; S12. Collect tidal change data of the target sea area, the tidal change data including the tidal height h of the t-th tidal cycle t , the flood rate r of the t-th tidal cycle up,t , the ebb rate r of the t-th tidal cycle down,t and the duration of the t-th tidal cycle T t , forming a tidal variation data set D tide ; S13. Collect wind speed data of the target sea area, the wind speed data includes the wth group of wind speed magnitude V w 、wind speed direction θ w and wind speed change rate ΔV w , forming a wind speed data set D wind ; S14. Collect the ocean current velocity data of the target sea area, the ocean current velocity data includes the velocity magnitude V of the cth group c 、Current direction θ c and the flow rate change rate ΔV c , forming the ocean current velocity data set D current ; S15. Wave data set D obtained by combining steps S11 to S14 wave , Tidal change dataset D tide , wind speed dataset D wind and ocean current velocity dataset D current , build the marine environment dataset D of the target sea area ocean .

3. A method for interconnecting and dynamically optimizing grid clusters of wave energy devices according to claim 1, characterized in that: The S2 comprises the following steps: S21. Perform a data integrity check on the marine environment dataset, remove missing data, data that does not meet measurement standards, and duplicate data, and form a cleaned marine environment dataset; S22. Format the cleaned marine environment dataset, convert all data into a unified storage format, synchronize the time series data of the wave dataset, tidal change dataset, wind speed dataset, and current speed dataset, and form a formatted marine environment dataset; S23. Perform data normalization based on the formatted marine environment dataset, define a normalization transformation function to map all data into a standardized range, and obtain a normalized marine environment dataset. S24. Normalized marine environment dataset Perform data index optimization, build an index mapping relationship based on the data collection time t and the geographic location coordinates (X, Y), and form a time-space index matrix M; S25. Store the marine environment data in a database based on the time-space index matrix M, and store the normalized marine environment data set Stored in the marine environment database D with an index structure ocean , and set up the database call interface to query the marine environment database D ocean Obtain wave data, tidal change data, wind speed data, and ocean current speed data for different time periods and geographical locations.

4. A method for interconnecting and dynamically optimizing grid clusters of wave energy devices according to claim 1, characterized in that: The S3 includes the following steps: S31. Based on the marine environment database Constructing the optimal input parameter set P for clustered deployment of wave energy devices input ; S32. Based on the optimized input parameter set P input Determine the layout area A of wave energy equipment deploy ; S33. Based on wave data D wave and ocean current velocity data D current Calculate the layout density ρ of wave energy devices device , optimize the energy capture capacity per unit area and avoid hydrodynamic interference between wave energy devices; S34. Combined wave energy equipment layout density ρ device and hydrodynamic interference between wave energy devices, optimizing the distance d between wave energy devices device ; S35. Calculate the optimal anchor point position S of the public anchoring system based on tidal change data and wind speed data anchor ; S36. Determine the cluster coordination force strategy of wave energy equipment, calculate the force balance state between wave energy equipment, and set the connection relationship L between wave energy equipment. device ; S37. Construct an optimization model M for clustered arrangement of wave energy equipment according to steps S31-S36 deploy .

5. A method for interconnecting and dynamically optimizing grid clusters of wave energy devices according to claim 1, characterized in that: The S4 comprises the following steps: S41. Based on the optimization model M deploy Wave energy equipment layout area A determined in deploy , wave energy equipment layout density ρ device , Wave energy equipment spacing d device , public anchor point S anchor And the connection relationship of wave energy equipment L device In area A deploy Constructing a candidate solution set for wave energy device locations Each candidate solution set for the location of wave energy equipment Represent the initial position distribution of a group of wave energy devices, and satisfy the minimum distance constraint between wave energy devices and the flow field adaptability requirements; S42. Based on wave data set D wave Calculate the candidate solution set for each wave energy device location The local wave energy capture power P of each wave energy device is wave,j and hydrodynamic interference cost C inter,j , based on the common anchor point S anchor Calculate the anchoring force F of the wave energy device based on the force model of the wave energy device anchor,j , and construct the initial objective function J init (X) used to evaluate the overall performance of the candidate solution set for wave energy device locations; By solving minJ init (X) Get the position distribution X under the initial layout init ; S43. Position distribution X under initial layout init On this basis, an improved multi-scale vortex flow field model is introduced to calculate the local vortex flow field velocity V at each wave energy device j. vortex,j and vortex strength Γ j ; S44. Combining an improved multi-scale vortex flow model, a multi-objective dynamic optimization strategy is employed, using an eddy flow optimization algorithm to iteratively adjust the position of wave energy devices. The goal is to simultaneously minimize local force unevenness and hydrodynamic interference while maximizing local wave energy capture efficiency. A comprehensive objective function is constructed and iteratively updated using an adaptive step-size strategy. S45. During the iteration process, monitor the changes of the comprehensive objective function J(X) when the convergence condition is met.

6. A method for interconnecting and dynamically optimizing grid clusters of wave energy devices according to claim 1, characterized in that: The S5 comprises the following steps: S51. Optimal position distribution based on initial layout Constructing a topological network G between wave energy devices device =(V device ,E device ); S52. Combined with wave data set D wave and ocean current dataset D current , calculate the force matrix F of wave energy equipment under extreme sea conditions net,j ; Calculate the overall force balance S of the wave energy equipment topology network balance ; S53. Based on the force balance S balance Pair connection relationship E device Make adjustments, and the optimization goal is to minimize the imbalance of force; S54. Based on topology optimization, combined with the real-time changes of the ocean environment, the ocean environment dataset D ocean Perform dynamic adaptive adjustment of the topology network and update the topology network G device (t); G device (t+1)=G device (t)+ΔG device (t); Among them, ΔG device (t) represents the topological change from t to t+1, G device (t+1) is the topological network of wave energy devices at time t+1; S55. Calculate the force balance after topology optimization Calculate the stability of connections after topology optimization If the force balance after topology optimization is Lower than the set value, and the connection stability after topology optimization If the connection cost is lower than the connection cost threshold, the optimization result is accepted; otherwise, the process returns to S53 for adjustment.

7. A method for interconnecting and dynamically optimizing grid clusters of wave energy devices according to claim 6, characterized in that: The S53 adopts the following topology adjustment rules: Add connection: If the force on a wave energy device j is higher than the average Then increase the connection between it and the adjacent wave energy equipment so that the force can be shared; Deleting a connection: If the wave energy device j and the wave energy device k cause excessive force interference or the connection stability is lower than a threshold, the connection is deleted; Adjust the connection weight: If the force on a wave energy device j is uneven, adjust the connection weight C of the adjacent wave energy device j and the adjacent wave energy device k. link,j,k , optimize the force transfer relationship.

8. A method for interconnecting and dynamically optimizing grid clusters of wave energy devices according to claim 6, characterized in that: The topological change ΔG device The setting rules for (t) are: If the wind speed V wind (t) or tide h tide (t) changes exceeding the threshold τ env , then perform topology reconstruction; If the force balance S balance (t) is lower than the set value, then optimize the connection relationship E device ; If the drift tendency of the wave energy device exceeds the set value, the connection point is optimized and the anchoring strategy is adjusted.

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