Energy efficiency driving supply and storage integrated offshore intelligent charging pile system and transformation method

Abstract

The energy efficiency driving supply and storage integrated offshore intelligent charging pile system comprises a pile-disc composite single pile foundation, the pile-disc composite single pile foundation comprises a single pile foundation and a friction disc, the friction disc comprises an inner ring area and an outer ring area which are coaxially arranged with the single pile foundation, and the inner ring area is used for placing power supply equipment and a balancing weight; an intelligent power distribution cabinet; an offshore unmanned device; the OpenSees calculation model is used for calculating the excess pore water pressure ratio of the pile-disc composite single pile foundation under different friction disc inner and outer ring radius ratios and thicknesses under the earthquake action according to the pile-disc-soil interaction; the invention discloses a multi-factor-driven intelligent optimization site selection model. According to the method, the offshore wind plant at the optimal transformation position is determined, supply and storage integrated transformation is carried out on the foundation in the offshore wind plant, infrastructure support can be provided for ocean unmanned operation and maintenance facilities, deep and far sea structure platforms, ocean transportation and the like on the basis of reducing transportation loss, and meanwhile zero-carbon construction operation is achieved; and the utilization efficiency of the offshore wind turbine is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of offshore wind power technology, in particular to an energy efficiency driven supply and storage integrated offshore intelligent charging pile system and a reforming method, which comprehensively considers factors such as the distribution of deep-sea power consumption equipment, the endurance and route of offshore unmanned equipment, and optimizes the site selection of the existing offshore wind farm reform, and reforms the foundation structure of the offshore wind turbine to realize local storage and nearby consumption of electric energy. BACKGROUND

[0002] As an important part of marine economy, deep-sea economy, including ocean transportation, deep-sea offshore structure construction and use, and unmanned operation and maintenance facilities, needs electric power to support its normal operation in the process of developing to deep sea. The existing power supply mode through the land power grid via submarine cable transmission leads to cost increase and unstable power supply due to the increase of transmission distance, and other reliable energy sources need to be considered.

[0003] Wind energy is a typical renewable energy with broad development prospects and application potential, which can provide clean and sustainable power supply and reduce dependence on traditional fossil fuels. However, the area suitable for installing offshore wind turbines in near sea area is limited, and offshore wind turbines show three trends of large-scale, clustering and deep-sea. In the process of developing offshore wind turbines to deep sea, the increase of power transmission distance causes the increase of transmission loss and cost, and the laying cost of cable also increases due to the difficulty and distance of deep-sea laying, resulting in the decrease of economic benefit.

[0004] The offshore wind turbine group in the existing offshore wind farm does not have the ability to directly supply power to the surrounding power consumption equipment, and the site selection of the existing offshore wind farm is concentrated on grid connection efficiency, grid connection cost and wind resource distribution. All through long-distance submarine cable transmission to the mainland power grid. Compared with grid connection power transmission, the electric energy generated by it is not planned to be directly supplied to other marine economic facilities around the offshore wind farm, and lacks local power supply and other multi-objective considerations for surrounding economic development activities. SUMMARY

[0005] In view of the deficiencies of the prior art, the technical problem to be solved by the present application is to provide an energy efficiency driven supply and storage integrated offshore intelligent charging pile system and a reforming method. The system and the reforming method determine the optimal reform position of the offshore wind farm and reform the pile-disc composite single pile foundation in the offshore wind farm to realize the supply and storage integration. On the basis of reducing transmission loss, it can provide support for deep-sea unmanned operation and maintenance facilities (including offshore unmanned equipment, etc.), deep-sea structure platform, ocean transportation and other infrastructure. At the same time, by directly reforming the supply and storage integration of the offshore wind turbine, the dependence on traditional fossil fuels for deep-sea economic development can be reduced, zero-carbon construction and operation can be realized, and the utilization efficiency of the offshore wind turbine can be improved.

[0006] The technical solution adopted by the present application to solve the technical problem is: In a first aspect, the present application provides an energy efficiency driven integrated onshore intelligent charging pile system, which comprises: A pile-disc composite single pile foundation, comprising a single pile foundation and a friction disc arranged at the lower part of the single pile foundation, the friction disc comprising an inner ring area and an outer ring area coaxially arranged with the single pile foundation, the inner ring area being used for placing power supply equipment and counterweight blocks; An intelligent power distribution cabinet for monitoring the real-time output power of offshore wind turbines and the load of power equipment, and dynamically allocating the input power of different power equipment; An offshore unmanned device, comprising a drone device and an unmanned ship device, integrating a wireless charging transmitting end at the top of the offshore wind turbine, and deploying a floating wireless charging platform near the offshore wind turbine, the floating wireless charging platform being electrically connected with the offshore wind turbine, and the wireless charging transmitting end being arranged on the floating wireless charging platform, and the unmanned ship device being docked with the floating wireless charging platform for charging; An OpenSees calculation model for calculating the excess pore water pressure ratio of the pile-disc composite single pile foundation under the action of earthquakes under different friction disc inner-outer ring radius ratios R and thickness T according to the pile-disc-soil interaction; eppr A multi-factor driven intelligent optimization site selection model, taking the maximum coverage of offshore wind farms, the minimum power transmission loss, and the minimum comprehensive transformation cost as the target, taking the power supply capacity limit of the maximum output power of the wind turbine, the transformation cost limit of a single offshore wind farm, the safety distance limit of the shipping channel between the offshore wind farm and the shipping cargo ship, and the endurance constraint limit of the offshore unmanned device as the constraints, and performing multi-objective solution to determine whether to select scheme A or scheme B for the offshore wind farm to be transformed; when scheme A is selected, the OpenSees calculation model is called to calculate the excess pore water pressure ratio eppr , and eppr the safety factor is calculated to determine the minimum friction disc inner-outer ring radius ratio and thickness that meet the structural safety requirements, realizing the structural-economic collaborative optimization; when scheme B is selected, the number of wind turbines to be transformed is determined according to the power demand of the surrounding power equipment, the annual average growth rate of the power demand of the surrounding power equipment, the additional power brought by the transformed wind turbine, and the service life of the surrounding power equipment.

[0007] ​Further, the inner ring area of the friction disc is provided with a symmetrical sealing cabin layer, a battery layer is arranged in the inner ring area, a honeycomb alloy framework is arranged in the battery layer, and energy storage batteries are embedded in the honeycomb alloy framework, the arrangement of the energy storage batteries matches the spatial distribution characteristics of the power demand of the peripheral power equipment, and all the energy storage batteries are electrically connected together; a protective layer is arranged on the upper and lower surfaces of the energy storage batteries, all the energy storage batteries are encapsulated into the battery layer by a steel outer cylinder, a steel inner cylinder and the protective layer, and a concrete protective layer is arranged outside the battery layer; the outer ring area is integrally poured with concrete to wrap the inner ring area.

[0008] Further, in the OpenSees calculation model, the model size and the actual size of the pile-disc-soil interaction adopt a scaling relationship of 1:6, the fan body is simplified as a steel rod with a concentrated load at the upper part, the range of the soil body is more than 10 times the diameter of the pile, and the soil body is divided into grids; the inner and outer ring radius ratio and thickness are taken as variables to parameterize the modeling and grid division of the friction disc.

[0009] Further, in the process of minimizing the comprehensive reconstruction cost, an opportunity cost is introduced to balance the difference in construction cost of executing scheme A or scheme B, the opportunity cost considers the annual output value of economic activities of different power equipment, the attenuation coefficient and the economic weight coefficient of different economic development.

[0010] Further, the SSA-NSGA-III algorithm is used for intelligent multi-objective solution.

[0011] In the second aspect, the application provides a method for reconstructing an energy-efficient integrated offshore intelligent charging pile, which comprises the following steps: Obtaining the position coordinates of existing offshore wind farms, driving routes of existing ocean routes and power equipment, wherein the power equipment includes ocean freighters, offshore structure platforms, offshore ranches and data centers, the position coordinates of the ocean freighters on the ocean routes are selected as the points with the maximum appearance probability of the ocean freighters; and the power supply radius of each offshore wind farm and the power demand of each power equipment are obtained; An OpenSees calculation model of pile-disc-soil interaction is constructed, which is used to calculate the excess pore water pressure ratio of the pile-disc composite single pile foundation under the action of an earthquake under different inner and outer ring radius ratios R and thicknesses T of the friction disc eppr ; Maximize the coverage range of the offshore wind farm, minimize the power transmission loss and minimize the comprehensive transformation cost as the target, with the power supply capacity limit of the maximum output power of the wind turbine, the transformation cost limit of a single offshore wind farm, the safety distance limit between the offshore wind farm and the shipping channel of the shipping freighter, and the endurance constraint limit of the offshore unmanned equipment as the constraint, multi-objective solving is carried out to determine whether the offshore wind farm needs to be transformed by scheme A or scheme B; when scheme A is selected, the super-pore water pressure ratio is calculated by calling the OpenSees calculation model eppr , eppr The safety factor is calculated, the inner and outer ring radius ratio and the thickness of the friction disc that meet the minimum structural safety requirement are determined, and structural-economic collaborative optimization is realized; when scheme B is selected, the inner and outer ring radius ratio and the thickness of the friction disc are set, the number of wind turbines that need to be transformed is determined according to the power demand of the surrounding power equipment, the annual average growth rate of the power demand of the surrounding power equipment, the additional power brought by the transformed wind turbine and the service life of the surrounding power equipment, and structural-economic collaborative optimization of the wind turbine is realized.

[0012] Compared with the prior art, the beneficial effects of the present application are: 1、The present application realizes the integration of power supply and storage, and the inner ring area of the friction disc is transformed into a storage area with a higher distribution density of energy storage batteries and gravel counterweights, which is used to ensure the stability of the inner ring area in the face of wind and wave load structures, and store the power of the offshore wind turbine in the foundation friction disc of the offshore wind turbine. Compared with the existing methods of storing power in the wind turbine cabin, the tower drum or externally hanging batteries, the present application uses the annular transformation method of the friction disc space, does not need to occupy the upper space of the tower drum or add other energy storage equipment, does not change the original aerodynamic shape of the wind turbine, and the structure is more stable by replacing part of the friction disc structure with energy storage batteries with higher density (compared with the untransformed structure), and has less impact on the original operation of the offshore wind turbine.

[0013] 2、The present application combines a multi-factor driven intelligent optimization site selection model, comprehensively considers multiple factors such as the operating distance of the offshore unmanned equipment, the distance between the offshore wind farm and the adjacent marine power equipment (such as marine structure platform, offshore pasture, data center, etc.) and the safety of the structure, and takes structural-safety-economic collaborative optimization as the target, so as to form a more intelligent and comprehensive site selection decision, and on the basis of transforming the foundation structure, the site selection decision and the foundation structure transformation are coordinated together to determine the final transformation scheme, solving the problem that the existing technology does not select to transform the offshore wind turbine, resulting in resource mismatch and restricting other economic development activities in the surrounding area.

[0014] 3、The application adopts the friction disc with annular inner and outer partitions, a plurality of energy storage compartments are arranged in the inner ring area, the limitation of the capacity of the existing other energy storage methods is broken through, the direct energy supply capability to large-scale power utilization facilities (or equipment) is achieved, and the application scenarios are widened; meanwhile, for the offshore unmanned equipment, wireless charging and timely energy supplement are adopted to expand the unmanned operation range and operation time, the innovative behavior provides basic support for deep sea economic development activities, reduces power transportation loss, and improves the utilization efficiency of offshore wind turbines.

[0015] 4, SSA-NSGA-III algorithm is used for solving, the SSA algorithm needs to set weight coefficient when solving multiple objective functions to balance the relationship between multiple solving objectives, which leads to insufficient search efficiency and solution set uniformity distribution when solving high-dimensional functions, NSGA-III has problems of high calculation complexity and uneven solution set distribution in high dimension, the behavior of discoverer-follower-sentinel of SSA is introduced into the simulated binary crossover and mutation operation of NSGA-III, the search efficiency of the algorithm is enhanced, and the global optimal solution can be quickly and accurately obtained. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 It is a site selection principle diagram of the intelligent optimization site selection model of multiple factors in the application.

[0017] Figure 2 It is a sea charging pile energy supply modification schematic diagram.

[0018] Figure 3 It is a structure schematic diagram of the friction disc of one embodiment in the application.

[0019] Figure 4 It is a battery layer layering structure schematic diagram of the inner ring area of one embodiment in the application.

[0020] Figure 5 It is a cross section structure schematic diagram of the friction disc after installing the energy storage battery in one embodiment in the application.

[0021] Figure 6 It is a flowchart of the SSA-NSGA-III algorithm.

[0022] In the figure, 1 is a concrete protective layer, 2 is a battery layer, 3 is an outer ring area, 4 is a wind turbine cabin, 5 is a tower drum, 6 is a tower drum and foundation connection part, 7 is a single pile foundation, 8 is a friction disc, 9 is a cable, 10 is a wireless charging transmitting end, 11 is a floating wireless charging platform, 21 is an inner lining layer, 22 is a sealing layer, 23 is an energy storage battery framework, 24 is a steel outer cylinder, 25 is a steel inner cylinder, 201 is a honeycomb alloy framework, and 202 is an energy storage battery. DETAILED DESCRIPTION

[0023] The following gives specific embodiments of the present application. The specific embodiments are only for further detailed description of the present application, and do not limit the protection scope of the present application.

[0024] Based on the trend of offshore wind farm towards the open sea and large-scale, the multi-factor driven intelligent optimization site selection of offshore charging pile is proposed, and the supply and storage integration of offshore wind turbines is carried out for the selected offshore wind farm, which converts the offshore wind turbine from a “power generation unit” to a “deep sea energy hub”, so that it can collect wind energy and directly provide energy support for the surrounding power equipment of the offshore wind farm through the cable 9. The multi-factor driven intelligent optimization site selection of offshore charging pile comprehensively considers the main route of ocean-going freighter, the resource distribution around the offshore wind farm, the operation time and endurance of offshore unmanned equipment and other factors, and optimizes the site selection based on the above factors, so that it can directly provide clean and stable energy for the deep sea economic development activities such as nearby marine structures, ecological development and data center, while reducing the loss and rising output cost caused by long-distance transportation. The specific implementation mainly considers the following three aspects: 1. Supply and storage integration of offshore wind turbine: the existing pile-disc composite single pile foundation is modified, the existing friction disc composed of a whole ring is modified, the friction disc is set as an inner and outer double ring form, part of the inner ring area is replaced with energy storage battery, and wireless charging module (including wireless charging transmitting end 10 and floating wireless charging platform 11) is added on the upper part of the offshore wind turbine or around the offshore wind turbine as needed to realize direct storage and local consumption of electric energy, while ensuring the reliability and stability of the foundation structure.

[0025] 2. Construction of multi-factor driven intelligent optimization site selection model: based on the residual power of unmanned operation facilities such as unmanned aerial vehicle to identify whether charging is needed, the power consumption of surrounding power equipment such as marine ranching, seabed data center and other factors, and combined with the position of offshore wind turbine in the offshore wind farm, the route of passing ships and other factors, a multi-factor target function is constructed, and SSA-NSGA-III algorithm is used for intelligent multi-objective solution, so as to efficiently solve the multi-factor driven intelligent optimization site selection model and ensure the acquisition of global optimal solution.

[0026] 3. Perfect energy supply decision mechanism: the system retains the grid-connected interface with the power grid, ensures that in the non-local energy supply period or the period with high wind turbine power, the unit can be configured as a conventional wind turbine, and the generated power is stably fed into the power grid, so as to maintain its basic function as a core power generation unit of offshore wind farm. At the same time, the power generated by the offshore wind farm is not all transmitted to a remote land, but can directly supply power to the surrounding power equipment through special lines or wireless way.

[0027] Figure 1The schematic diagram of the site selection principle in the process of the multi-factor driven intelligent optimization site selection model in the application is as follows: in the power supply radius of the offshore wind farm, there are multiple power consumption equipment such as offshore structure platform, offshore ranch, unmanned ship, unmanned aerial vehicle, ocean freighter and data center, at least one offshore wind turbine exists in each offshore wind farm, and a plurality of offshore wind farms exist in the ocean area. Each offshore wind turbine (see Figure 2 ) includes a wind turbine cabin 4, a tower drum 5, a composite single pile foundation, and a tower drum and foundation connection part 6, the foundation adopts a pile-disc composite single pile foundation, and the pile-disc composite single pile foundation includes a single pile foundation 7 and a friction disc 8 arranged at the lower part of the single pile foundation.

[0028] A floating wireless charging platform 11 is arranged near the position of the offshore wind turbine, the floating wireless charging platform is connected with the offshore wind turbine through a cable 9, a wireless charging transmitting end 10 is arranged on the floating wireless charging platform, and the unmanned ship equipment is docked on the floating wireless charging platform for stable docking and charging. The wireless charging transmitting end 10 is also integrated on the top of the offshore wind turbine for charging the unmanned aerial vehicle equipment.

[0029] The friction disc (see Figures 3-5) including the inner ring area (not marked in the figure) and the outer ring area 3 coaxially arranged with the single pile foundation, the inner ring area including the battery layer 2 and the concrete protective layer 1, the inner ring area being used for placing the power supply device while placing the counterweight to ensure the overall stress form of itself, the layout of the power supply device matching the spatial distribution characteristics of the power demand of the peripheral power equipment. The friction disc is divided into two annular areas of the inner ring area and the outer ring area 3, and the concrete protective layer 1 is arranged on the upper and lower surfaces of the battery layer 2 in the inner ring area. The inner space of the inner ring area is divided into layers by a symmetrical sealed cabin, which is used to accommodate the energy storage battery. The battery layer 2 is encapsulated as a whole by the inner lining layer 21, the sealing layer 22, the energy storage battery framework 23, the steel outer cylinder 24 and the steel inner cylinder 25. Among them, the inner lining layer 21 and the sealing layer 22 and the waterproof diaphragm constitute a protective layer, which is symmetrically distributed on the upper and lower structures of the energy storage battery framework 23. The energy storage battery framework 23 is composed of energy storage battery group and honeycomb alloy framework, the honeycomb alloy framework is made of high-strength alloy, a plurality of energy storage batteries 202 are respectively embedded in the cells of the honeycomb alloy framework 201, all the energy storage batteries are connected in series to form an energy storage battery group, the honeycomb alloy framework bears the load, ensures the stability of the whole energy supply, and ensures that the energy storage battery group is not affected by the shear force in the earthquake load and the pressure brought by the wind and wave load and the deep sea water, the energy storage battery group only provides self-weight stress to limit the horizontal displacement of the foundation. The energy storage battery group and the honeycomb alloy framework are respectively provided with protective layers on the upper and lower parts, which prevent electrolyte corrosion, ensure air tightness and prevent salt mist penetration. The concrete protective layer 1 is a 5cm concrete partition layer, which is used to block the invasion of seawater. In addition, a temperature control management unit is arranged in the energy storage battery group to ensure the working temperature of the energy storage battery. The outer ring area is integrally poured with concrete, which wraps the inner ring area from the ring, and does not cover the position of the concrete protective layer. The outer whole of the friction disc is covered with waterproof and anticorrosive paint to prevent seepage and corrosion.

[0030] The present application is aimed at the problem of stable supply of deep-sea energy, and carries out intelligent optimization site selection and structural modification of offshore wind farm energy efficiency driven supply and storage integration setting driven by multiple factors. The core lies in: first, the geographic location information of key power equipment such as offshore wind farms, ocean shipping routes, deep-sea structures and the like is integrated and collected, and combined with the endurance and working time data of existing unmanned operation and maintenance equipment, a multi-objective function is constructed with the maximum coverage range of offshore wind farms, the minimum power transmission loss, the minimum comprehensive modification cost and the optimal structural safety as the objectives. An intelligent optimization algorithm combining SSA (Sparrow Search Algorithm) and NSGA-III (Non-dominated Sorting Genetic Algorithm III) is used to solve the multi-objective function, and OpenSees (Ocean Geotechnical Computing Platform) is introduced to calculate the safety factor of the structure, and the final Pareto optimal solution set (Pareto frontier) represents the best offshore wind farm site for intelligent modification. Two modification schemes are specifically set, through decision variables X and modification variables S, the three objective functions of maximum coverage range of offshore wind farms, minimum power transmission loss and minimum comprehensive modification cost are substituted, and the Pareto optimal solution set under the constraint is optimized and solved, at this time the 0 and 1 values of the modification variable S in the Pareto optimal solution set are given, and then the modification scheme can be determined, that is, when the element of the modification variable S is 0, scheme A is adopted: the inner ring area of a single friction disc is modified to expand its energy supply and storage capacity, which is convenient for supporting more power equipment, and the required modification area and thickness (i.e. R and T) are given according to the safety requirement function f 4 and the OpenSees calculation model; when the element of the modification variable S is 1, scheme B is adopted: the system modifies the offshore wind turbine according to the set modification area and thickness (R and T) of the friction disc, the set R and T are selected through safety calculation and do not need to be verified again, and can be directly set, and the number of wind turbines to be modified is given through the objective function f 5. Finally, different modification combinations of multiple offshore wind farms are given, and each offshore wind farm corresponds to a different modification scheme.

[0031] For the low-power density application scenarios (such as small monitoring equipment and intermittent unmanned operation and maintenance platforms) in the deep-sea area, after selecting the target offshore wind farm, the present application innovatively proposes to integrate the friction disc in the pile-disc composite single pile foundation with the energy storage battery, divide the friction disc into an inner ring area and an outer ring area, set a honeycomb alloy framework in the inner ring area, each unit of the honeycomb alloy framework forms a cabin, the energy storage battery can be accommodated in the cabin, and the energy storage battery can be arranged in the unit of the honeycomb alloy framework as needed to realize the integration of supply and storage. The inner and outer ring division of the friction disc can only modify the energy storage of the inner ring cabin, thereby significantly reducing the system modification cost in the low-power density scenario.

[0032] The supply and storage integrated reform in the present application refers to that the friction disc of the pile-disc composite single pile foundation is divided into a coaxial outer ring region and an inner ring region, the inner ring region of the friction disc is subjected to the supply and storage integrated reform, the energy storage battery is placed in the honeycomb alloy framework as needed, and all the energy storage batteries are connected in series to form an energy storage battery pack; the energy storage battery pack is used for storing the electric energy generated by the offshore wind turbine; the input and output power is distributed through the intelligent power distribution cabinet, the intelligent power distribution cabinet and the energy storage battery pack form an energy supply device, the electric equipment is connected by a cable, and the energy supply to the surrounding electric equipment is realized.

[0033] The energy efficiency driven and intelligent optimization site selection in the present application is embodied in the storage, distribution and overall layout optimization of electric power; specifically, the structural form of the pile-disc composite single pile foundation is reconstructed, the electric power generated by the offshore wind turbine is stored in the reconstructed friction disc, the electric equipment is connected by a submarine cable, and the energy transmission path is optimized on the physical layer; after f 1~ f 3 solving and optimization, the overall layout optimization is realized, so that the energy efficiency driven is realized on the planning layer, and the idle resources and sunk costs are avoided; according to f 4 or f 5 solving, the inner and outer ring regions are dynamically divided into cabins, and the energy efficiency driven is realized in operation.

[0034] The safety of the inner and outer ring dynamic cabin division in the present application is given by parameterized modeling of the pile-disc-soil in OpenSees and combining f 4 the radius ratio R and the thickness T of the inner and outer rings of the friction disc are given, which take into account safety and economy.

[0035] The present application realizes efficient conversion of the intermittent electric energy generated by the offshore wind farm into stable and reliable energy supply, and effectively supports the continuous operation of deep sea economic activities.

[0036] Embodiment 1: The energy efficiency driven supply and storage integrated offshore intelligent charging pile reform method of the present embodiment includes supply and storage integrated reform of the pile-disc composite single pile foundation of the existing offshore wind farm, and multi-factor and multi-target intelligent optimization site selection of the offshore wind farm.

[0037] I. Supply and storage integrated reform 1. Dynamic cabin division and energy storage integration of friction disc There are two schemes for energy storage integrated reconstruction of pile-disc composite single pile foundation: the first scheme A is to enhance the energy storage capacity of the pile-disc composite single pile foundation by increasing the radius ratio and thickness of the inner and outer rings of the friction disc, specifically, the area ratio of the inner ring area of the friction disc to the entire friction disc (which can be achieved by the inner and outer ring radius ratio R) or the volume of the entire friction disc (which can be achieved by the thickness of the friction disc) is increased to improve the energy storage capacity of the inner ring area, but there are limitations of maximum output power of offshore wind turbine and structural safety; the second scheme B is to increase the number of wind turbines in the offshore wind farm to be reconstructed to obtain greater power output, but the reconstruction cost will be significantly higher than that of scheme A, when scheme B is selected, the inner and outer ring radius ratio R and the thickness T of the friction disc of the pile-disc composite single pile foundation remain unchanged, and R and T pass the safety check, only the number n of wind turbines to be reconstructed is given.

[0038] In the present application, the site selection process of the offshore wind farm to be reconstructed takes into account the development potential of the surrounding area of the offshore wind farm in the site selection decision, and intelligently selects the appropriate reconstruction scheme from the above A and B schemes.

[0039] 1.1, dynamic compartment energy storage of friction disc Based on the optimized solution set output by the intelligent optimization site selection model, considering the power demand and power consumption characteristics of the power equipment within the power supply radius of the offshore wind farm, the A scheme is adopted for structural reconstruction of the friction disc, according to the inner and outer ring radius ratio R of the friction disc (R value range 0.2-1.0, the inner ring area is used to place power equipment while ensuring the overall stress form of the friction disc, and the area occupied by the power equipment is determined after reconstruction), and the optimization algorithm (such as SSA algorithm) is adopted, the optimization range of R (0.2-1.0) and T (0.5-2.5m) is given, and the most economical compartment range that meets the output power and structural safety is selected, that is, the first optimization of f 1 f 3 selects the offshore wind farm to be reconstructed that meets the constraint limit after optimization, and the second optimization of After optimization, R and T that pass the safety check are selected, which is the most economical compartment range.

[0040] If the offshore wind farm to be reconstructed that meets the constraint limit is selected after the first optimization of f 1 f 3, the B scheme is selected for wind farm reconstruction, the range of compartment design is given, combined with the power demand of the surrounding power equipment and the annual average growth rate of the power demand of the surrounding power equipment, the The number n of wind turbines to be reconstructed is given.

[0041] Different partition designs are adopted for different modification schemes, and the energy storage modification methods of the friction disc in the A scheme and the B scheme are the same. Based on the distribution of electrical equipment and load data, combined with the structural strength analysis of the friction disc and the distribution characteristics of wind and wave load, the entire inner ring area of the friction disc is modified into a new structure that can store the electrical energy generated by offshore wind turbines and supply power to surrounding electrical equipment.

[0042] The physical and mechanical parameters of the modified friction disc can be obtained through physical tests: shear modulus G and elastic modulus E. G and E are used as inputs, and R and T ranges are also input for dynamic partition calculation. The principle is to select the smallest modification range (R) and friction disc thickness (T) that meet the safety requirements of the pile-disc composite single pile foundation structure through optimization algorithm in finite element analysis. Shear modulus and elastic modulus are physical properties of the honeycomb alloy framework. When the material is determined, E and G are also determined. They are used as parameters to determine the inner and outer ring radius ratio and thickness of the friction disc, and finally together to calculate eppr .

[0043] Dynamic partitioning aims to accurately match the spatial distribution characteristics of the power demand of surrounding electrical equipment, and to realize the on-demand configuration of energy storage battery capacity. Under the premise of limited incremental cost of friction disc structure modification, the procurement cost and space occupation of energy storage batteries can be significantly reduced.

[0044] 1.2 Friction disc supply and storage integration At the same time, in order to cope with the inherent temporal and spatial fluctuations and intermittency of offshore wind energy resources, an energy supply decision mechanism is set up to ensure that the power demand of local loads can be met under high and low wind speed conditions, that is, the combined power of wind turbine generation and energy storage discharge ≥ load demand. To regulate the input and output of power, an intelligent power distribution cabinet is set up to coordinate the power allocation of software and hardware. Through power monitoring, decision control and hardware cooperation, dynamic regulation of power is realized. The implementation path is: (1) monitoring: monitoring the real-time output power of offshore wind turbines, monitoring the electrical equipment load with a smart meter, and reporting the SOC (State of Charge) with an embedded IC chip; (2) control: setting different priorities to realize dynamic power allocation of different electrical equipment; (3) key hardware: integrating hardware into an intelligent power distribution cabinet to solve the communication between input and output, report the status of electrical equipment to realize real-time decision, adjust power distribution, convert electrical energy, and set up protection measures. The intelligent power distribution cabinet includes a main control chip, a power distribution module composed of dynamic routing, an electrical energy conversion module for converting 35kV AC power generated by the wind turbine into DC power of the target voltage, and a protection circuit module for realizing safety isolation.

[0045] 2. Wireless charging integration of offshore unmanned equipment This embodiment employs wireless charging technology to enhance the safety, reliability, and convenience of charging operations for unmanned marine equipment (drones and unmanned surface vessels). It effectively avoids the safety hazards of traditional wired charging interfaces, such as aging, corrosion, and water ingress caused by the high salt spray and humidity of the ocean, and significantly simplifies the charging connection process. Different wireless charging devices are used for different types of unmanned marine equipment. For drones, a wireless charging transmitter is integrated on the top of the offshore wind turbine. The drone docks on the turbine and charges itself via the transmitter, minimizing the impact of external charging mechanisms on the drone's aerodynamic shape and avoiding potential difficulties in charging interface alignment and drone stability risks caused by sea wind disturbances. For unmanned surface vessels, a floating wireless charging platform is deployed near the wind turbine. The platform is connected to the wind turbine via a cable, and a wireless charging transmitter is installed on it. The unmanned surface vessel docks on the platform for stable charging. The floating wireless charging platform is positioned at a certain distance from the wind turbine, a distance that ensures both proximity and safe charging, facilitating stable docking and charging for the unmanned surface vessel.

[0046] II. Intelligent Optimization Site Selection for Offshore Wind Farms Based on Multiple Factors and Objectives By establishing a multi-factor driven intelligent optimization site selection model, the power supply requirements of deep-sea electrical equipment, the endurance limitations of offshore unmanned equipment, and the potential for offshore wind farm retrofitting are systematically incorporated into the site selection decision to determine the optimal retrofitting scheme (Scheme A or Scheme B). To evaluate the reliability and safety of retrofitting scheme A, the excess pore water pressure ratio of pile-disk composite monopile foundations with different friction disk inner and outer ring radius ratios and thicknesses is calculated under seismic loading based on a finite element model of pile-disk-soil interaction built in OpenSees (i.e., the OpenSees computational model). eppr And the OpenSees computational model calculates eppr The safety factor serves as a parameter for calculation and is also used as one of the suitability functions for comprehensive evaluation. Finally, the SSA-NSGA-Ⅲ algorithm is employed for a fast and efficient solution of the multi-factor-driven intelligent optimal location selection model; the specific steps are as follows: 2.1 Data Collection and Numerical Model: Collect the existing offshore wind farms, the existing ocean shipping routes, and the location coordinates of electrical equipment, including marine structural platforms, marine ranches, and data centers; obtain the power supply radius of each offshore wind farm and the power demand (i.e., the power demand of each electrical equipment); the location coordinates of ocean-going freighters on ocean shipping routes are selected from the points with the highest probability of occurrence of ocean-going freighters.

[0047] An OpenSees computational model of a pile-soil composite monopile foundation was constructed, which is a model of pile-soil interaction and satisfies... The minimum is calculated according to the OpenSees calculation model of pile-disc-soil interaction eppr . The size of the model is scaled to 1:6 of the actual size. The eppr (Excess pore water pressure ratio) is selected to evaluate the safety factor of the structure, that is, the liquefaction resistance of the foundation structure under seismic load, and thus the fan body (including single pile foundation 7, tower drum 5, tower drum and foundation connection part 6, single pile foundation 7 is a structure embedded in or standing on the seabed, used to support the tower drum and the fan cabin, and the tower drum and foundation connection part connects the tower drum and the foundation. In actual engineering, it is generally connected by flange or grouting, but in finite element simulation, the differences between single pile foundation 7, tower drum 5, and tower drum and foundation connection part 6 are ignored, and simplified as a steel rod with concentrated load on the upper part; The soil body is selected to be 22m x 16m, and the soil body is meshed; Since the friction disc is the main part of the study, during the parameterization modeling and meshing of the friction disc, the variables (thickness and inner-outer ring radius ratio) to be studied are replaced by parameters during modeling, which facilitates optimization and non-dominated sorting in the subsequent process.

[0048] 2.2 Build a multi-factor driven intelligent optimization site selection model to maximize the coverage range of offshore wind farms, minimize power transmission loss, and minimize comprehensive transformation cost. With the power supply capacity limit of the maximum output power of the fan, the transformation cost limit of a single offshore wind farm, the safety distance limit of the shipping channel between the offshore wind farm and the main shipping route of the shipping cargo ship, and the endurance constraint limit of the offshore unmanned equipment, the multi-objective solution determines which scheme A or B needs to be transformed. When selecting scheme A, the excess pore water pressure ratio is calculated by calling the OpenSees calculation model eppr , and eppr to calculate the safety factor to determine the minimum inner-outer ring radius ratio and thickness of the friction disc that meets the structural safety requirements, and complete the structure-economy collaborative optimization. At the same time, the constraint conditions are introduced in the process of building the objective function, so that the solution set is close to the real situation, and the related part of the calculation formula is as follows: 2.2.1 Set variables Offshore wind farm decision variables: ; Wherein , when , it means selecting the th offshore wind farm for transformation; Otherwise, it is not transformed. N is the number of offshore wind farms; Offshore wind farm transformation variables: ; Wherein , when , it means the The offshore wind farm at this location will be upgraded according to Option A. When, it indicates the first Option B was chosen to modify the offshore wind farm at the selected location; Option A represents increasing the ratio and thickness of the inner and outer ring radii of the friction disc, while Option B represents increasing the number of wind turbines that need to be modified.

[0049] Friction disk parameters: The compartmentalization mechanism is determined by the thickness T of the friction disk and the ratio of the inner and outer ring radii R. The modeling simplifies calculations by scaling the pile-disk-soil interaction model and disregarding size effects. Both T and R are continuous variables, and their ranges are given as follows: .

[0050] 2.2.2 Constructing the objective function 2.2.2.1 Maximize the coverage of offshore wind farms, that is, maximize the number of electrical devices used within the coverage area of ​​offshore wind farms, thereby maximizing the number of covered electrical devices;

[0051] in, This indicates an indicator function, and the set of electrical devices is... The formula does not distinguish between electrical equipment and facilities. It refers to electrical facilities such as marine structural platforms, marine ranches and data centers, as well as electrical equipment including drones and unmanned ships, as electrical equipment in the calculation. This indicates the total number of electrical devices that require power. This represents the total number of candidate offshore wind farms. It is a binary variable indicating whether to select an offshore wind farm. To carry out renovations, and These represent the location coordinates of the offshore wind farm and the location coordinates of the electrical equipment, respectively. This indicates the distance between the power-consuming equipment requiring power and the selected offshore wind farm. Its specific value can be calculated using the distance formula between two points, which will not be elaborated here. The function of the indicator is: when the power-consuming equipment is within the power supply radius of the offshore wind farm, the value is assigned as 1, and otherwise it is assigned as 0. For the first The range of electricity that an offshore wind farm can supply; f The purpose of the 1 function is to quantify the coverage capability of offshore wind farms, transforming complex spatial relationships into calculable numerical targets and providing optimization directions; that is, the closer to 1, the more comprehensive the coverage. Specifically... f The value 1 refers to the proportion of electrical equipment that can be covered by a current offshore wind farm to the total number of electrical equipment. The ultimate goal is to transform the complex spatial relationship between offshore wind farms and the electrical equipment they can cover into a simple numerical relationship. f1 the larger, the wider the range that can be covered.

[0052] 2.2.2.2 Minimize the overall retrofit cost

[0053] where N is the total number of candidate offshore wind farms, representing the theoretical maximum cost, used to normalize the function, mapping the value range of the function to the interval [0, 1], represents the fixed retrofit cost of the th offshore wind farm, including the cost of upgrading and retrofitting the basic power supply facilities such as energy storage batteries and intelligent power distribution cabinets; is the cost of connecting different electrical equipment, including cable cost and laying cost; where is a piecewise function used to evaluate the basic cost difference between different retrofit schemes (scheme A or scheme B), and its specific expression is as follows:

[0054] where, , represent the basic cost of scheme A and scheme B respectively, scheme A includes the cost difference caused by different R, T values, energy storage battery installation quantity and installation method, etc. Scheme B includes the cost difference caused by different construction methods due to different number of wind turbines that need to be retrofitted; The construction cost of scheme B will be significantly higher than that of scheme A, but the number of electrical equipment it can support will be significantly higher than that of scheme A, and its future retrofit potential will also increase. By introducing the opportunity cost to balance the difference in construction cost, where

[0055] where, represents the economic weight coefficient of electrical equipment , different values are assigned according to different economic development; represents the annual output value of economic activities of electrical equipment ; decay coefficient, controls the influence range; the closer to 0, the lower the retrofit cost, to quantify the retrofit cost difference between different offshore wind farms, the ratio of the retrofit cost of the currently selected offshore wind farm to the theoretical maximum retrofit cost is used to convert the cost from absolute value to relative value, remove the dimension, so that it can be optimized together with other functions.

[0056] 2.2.2.3 Minimize power transmission loss ​

[0057] wherein, represents the theoretical maximum loss, which is used here as a normalization benchmark for power transmission loss; M represents the total number of power-consuming devices that need to be powered; represents the power requirement of the i-th power-consuming device; represents the transmission loss coefficient per unit distance, which is related to cable resistance, voltage level, and other factors. The function serves to calculate the loss contribution for each selected offshore wind farm location and power-consuming device location , if the power-consuming device is within the power supply radius. The logic of the formula is to first check all offshore wind farms to check whether the selected offshore wind farm covers the power-consuming device, then, for offshore wind farms that cover power-consuming devices, to calculate the loss of each power-consuming device, and finally to normalize the actual loss to map it within the interval, quantifying the transmission loss of electrical energy from the selected offshore wind farm to the power-consuming device. Similarly, f 3 is to compare the transmission loss of the currently selected offshore wind farm with the theoretical maximum loss of all selected offshore wind farms, eliminating dimensional differences, normalizing, and facilitating optimization.

[0058] 2.2.2.4 Structural safety requirement to minimize safety factor

[0059] Excess pore water pressure ratio eppr is an important indicator for judging soil liquefaction, and its calculation formula is as follows:

[0060] In the formula, Δu represents the increment of pore water pressure u at two adjacent times during the earthquake process; is the effective stress; eppr The maximum value of all time histories of the detection point in the centrifuge test is selected in the calculation process of . The results of the OpenSees calculation model can be obtained by python processing, and different eppr can be calculated by inputting different friction disc inner and outer ring radius ratios and thicknesses, and then different ; eppr When f 4 represents the safety factor, eppr the smaller, f 4 is larger, indicating that the improved foundation structure has stronger anti-liquefaction capacity under seismic load, and the structure is safer. According to the solution of the fitness , the wind turbine is improved by A scheme or B scheme.

[0061] ​2.2.2.5 Number of offshore wind turbine retrofits

[0062] When Option B is selected, which involves retrofitting more offshore wind turbines, this function provides the most economical number of turbines that need to be retrofitted. In the formula... To meet the power requirements of surrounding electrical equipment, It represents the average annual growth rate of power demand from surrounding electrical equipment. It refers to the service life of the surrounding electrical equipment. It is the maximum power that the power supply equipment can provide. The additional power generated by modifying the fan The number of wind turbines to be upgraded. Given the average annual growth rate of power demand from surrounding electrical equipment, when... At that time, the most economical number of wind turbines that need to be modified can be obtained.

[0063] 2.3 Setting Constraints This invention takes into account practical situations and sets four constraints: First, a power supply capacity limit for the maximum output power of each modified wind turbine, considering its maximum output power limitation. Second, a cost limit for modifying a single offshore wind farm to avoid economically inefficient modifications. Third, considering the safety of shipping vessels and offshore wind farms, offshore wind farms must maintain a minimum safe distance from major shipping routes. Fourth, considering the endurance and operating time of unmanned offshore equipment, constraints are added to the supply point settings to better reflect real-world conditions. The specific formulas are as follows: 2.3.1 Power supply capacity limitation of the maximum output power of the wind turbine

[0064] In other words, for a selected offshore wind farm, the total power of electrical equipment within its power supply radius should be less than or equal to that of the selected offshore wind farm. The maximum power supply that wind turbines and energy storage battery packs can provide ; Indicates the selected number The number of electrical devices covered in an offshore wind farm.

[0065] 2.3.2 Upper limit of retrofit cost for a single offshore wind farm

[0066] For the selected offshore wind farm, its fixed retrofit cost And the cost of connecting all different electrical devices The sum should be less than or equal to the artificially set cost ceiling. ; 2.3.3 Shipping lane safety distance

[0067] That is, any selected offshore wind farm (i.e. ) must maintain at least a safety distance from the shipping lane to avoid interference with the operation of ships or cause risks, which should be selected according to relevant regulations such as maritime law; 2.3.4 Offshore unmanned device endurance constraint

[0068]

[0069] wherein, is a reduction factor considering the battery attenuation of the offshore unmanned device, the sea state influence, and the aging of the offshore unmanned device to estimate the actual available endurance time; represents the port where the offshore unmanned device departs; , refers to the distance between the departure point of the offshore unmanned device and the modified offshore wind farm, and the distance between the two adjacent offshore wind farms; represents the travel speed of the offshore unmanned device; represents the theoretical endurance time of the u-th device (unmanned aerial vehicle device or unmanned ship device). The meaning of the above formula is that the distance between the port and the modified offshore wind farm, and the distance between the two modified offshore wind farms should be less than the endurance distance of the offshore unmanned device; wherein represents the position set of the offshore wind farm, the position coordinates of the offshore wind farm, and records the spatial information of the offshore wind farm, specifically ; the offshore wind farm decision variable indicates the state of the offshore wind farm during optimization solving, indicating whether the current offshore wind farm is selected to participate in optimization.

[0070] 3 Optimization solving: The SSA-NSGA-III algorithm is used for optimization solving, and the specific solving steps are as follows: Step 1: Set the maximum number of iterations, crossover probability, and mutation probability, set the producer ratio PD, the alarm ratio SD, and the safety threshold ST in the SSA algorithm, use python to link the SSA algorithm and the pile-disc composite single pile foundation, input the range of R and T, ; Step 2: Initialize the population in the SSA algorithm using the Sobol sequence to generate individuals, each individual containing two variables X and S; R and T are related to the modification variable S. R and T are randomly assigned values ​​only when S=0; when S=1, R and T are assigned fixed values. Calculate the number of fans to be upgraded; For variables X and S, a 0,1 binary encoding method is used. For X, its specific meaning is the set of locations of offshore wind farms. Each offshore wind field exists in two states: selected and unselected. Therefore, X can be viewed as an N-dimensional column vector, where each element is distributed as 0 and 1. This indicates that offshore wind farms have been selected for retrofitting. The number of offshore wind farms ultimately selected for retrofitting can be set manually, and the specific offshore wind farms requiring retrofitting need to be determined through an optimization algorithm. Similarly, the retrofitting variable S can be viewed as an N-dimensional column vector composed of 0s and 1s, which is defined in the three objective functions. When performing multi-objective solutions, the distribution of 0 or 1 in the solution set is selected; When choosing At this point, the modification is carried out according to Scheme A. Considering the friction disk variable, research shows that after the thickness and diameter of the friction disk increase to a certain value, further increasing the thickness and diameter can easily lead to a marginal effect on the wind turbine's anti-liquefaction ability. Therefore, this invention studies the compartment modification method with different inner ring area radii under a fixed outer ring radius, that is, using the ratio of inner and outer ring radii and thickness as variables R and T.

[0071] After obtaining the initial population, these individuals serve as parents in the iterative process, and the optimal chromosome values ​​of the parents are calculated and balanced by NSGA-III. The problem of conflicting objectives.

[0072] Step 3: Population Update. The update mechanism from SSA is used to update the positions of producers, followers, and vigilant individuals. Their functions are global search, developing high-quality regions, and avoiding local optima, respectively. Here, we take X as an example to illustrate the update mechanism for individual positions in the population. The position update formula is as follows: Producer location update:

[0073] Where t represents the current iteration; d represents the dimension of the optimization problem, which in this example represents the number of decision variables and modification variables. Indicates the first The sparrow at the (t+1)th iteration Position coordinates in 3D space. It represents the maximum number of iterations. It is a random number. Indicates alarm values ​​and safety thresholds. For random numbers that follow a normal distribution, For matrix, each element of which is 1. denotes the position coordinate of the th Sparrow individual in the th iteration (before updating).

[0074] Follower position update:

[0075] where is the optimal position occupied by the Producer. denotes the current global worst position. A is a 1 x d matrix, each element of which is randomly assigned to be 1 or -1, and . When the size of the population, i.e., the total number of individuals generated in Step 2, , the th follower is most likely in a poor fitness situation and needs to expand the search radius. denotes the position coordinate of the th Sparrow individual in the th iteration (before updating). denotes the worst position vector among all Sparrow individuals in the th iteration (i.e., the position of the individual with the lowest fitness). denotes the position vector of the Producer in the

[0076] th + 1 iteration (i.e., the position of the individual with the highest fitness).

[0077] where is the current global optimal position. denotes the global worst position in the th iteration (the position of the individual with the lowest fitness among all individuals). denotes the position coordinate of the th Sparrow individual in the β th iteration (before updating). is a random number. Here is the fitness value of the current Sparrow. and are the current global optimal and worst fitness values, respectively. is a minimum constant set to avoid division by zero errors.

[0078] Step 4: the parent and offspring populations are combined, and individuals not meeting the set constraints are excluded; the individuals meeting the constraints are subjected to the next step of solving; Step 5: if the solution set of different reconstruction schemes of the offshore wind farm obtained in step 4 , then the inner and outer ring radius ratio and thickness value of the friction disc in the pile-disc composite single pile foundation that need to be reconstructed are optimized, in this step, the range of the inner and outer ring radius ratio R and the thickness T of the friction disc is given, the relevant geological parameters and the E, G and wind turbine material parameters containing the physical properties of the friction disc material are set, the excess pore water pressure ratio eppr is calculated by using the OpenSees calculation model combined with the python program written; optimization is carried out, and the core of the implementation is to use python for the pre-processing and post-processing of the pile-disc-soil and to call the OpenSees calculation model for calculation, and finally the fitness function is called to select the inner and outer ring radius ratio and thickness of the friction disc that can meet the minimum safety requirement of the structure; the non-dominated sorting and crowding distance sorting of the combined population are carried out by using the NSGA-III fast arrangement mechanism, and the Pareto front and the solution set with large crowding distance, i.e. the new population (containing X, S, R and T) are obtained; Step 6: whether the termination condition is met is judged, if not, the new population is taken as the parent individual of the next iteration, the producer, follower and guard mechanism of the SSA algorithm is executed for updating the population, and steps 3-5 are repeated; if the termination condition is met, the front solution set is outputted; Step 7: if the solution set of different reconstruction schemes of the offshore wind farm obtained in step 4 , then the function is directly called for solving, the number of wind turbines that need to be reconstructed is given, and the front solution set is outputted; The termination condition at least meets any one of the following conditions: 1) the maximum number of iterations set is reached ; 2) if the front 1 is unchanged for 50 generations in succession, it is determined that the convergence is reached, and the optimization is terminated in advance.

[0079] The SSA-NSGA-III algorithm in the application outputs the selected solution set of the offshore wind farm (i.e. X, whether to be reconstructed), the solution set of the reconstruction scheme of the offshore wind farm (i.e. S, selecting the A scheme or the B scheme), the reconstruction parameters (the inner and outer ring radius ratio R and the thickness T) of the friction disc or the number n of wind turbines that need to be reconstructed.

[0080] The parts not mentioned in the application are applicable to the prior art.

Claims

1. An energy efficiency driven integrated offshore intelligent charging pile system for storage, characterized in that, The system comprises: A pile-disc composite single pile foundation, comprising a single pile foundation and a friction disc arranged at the lower part of the single pile foundation, the friction disc comprising an inner ring area and an outer ring area coaxially arranged with the single pile foundation, the inner ring area being used for placing power supply equipment and counterweights; An intelligent power distribution cabinet for monitoring real-time output power of the offshore wind turbine and loads of the power-consuming equipment and dynamically allocating input power of different power-consuming equipment; An offshore unmanned equipment, comprising an unmanned aerial vehicle and an unmanned ship, the offshore wind turbine being integrated with a wireless charging transmitting end at the top of the offshore wind turbine, a floating wireless charging platform being arranged near the offshore wind turbine, the floating wireless charging platform being electrically connected with the offshore wind turbine, and the wireless charging transmitting end being arranged on the floating wireless charging platform, the unmanned ship being docked with the floating wireless charging platform for charging; OpenSees computational model for calculating the excess pore water pressure ratio of pile-plate composite single pile foundation under seismic action according to the pile-plate-soil interaction under different friction plate inner and outer ring radius ratio R and thickness T EPPR ; A multi-factor driven intelligent optimization site selection model, aiming to maximize the coverage range of the offshore wind farm, minimize the power transmission loss and minimize the comprehensive transformation cost, and taking the power supply capacity limitation of the maximum output power of the wind turbine, the transformation cost limitation of a single offshore wind farm, the safety distance limitation of the offshore wind farm and the shipping channel of the shipping freighter, and the endurance constraint limitation of the offshore unmanned equipment as constraints, the multi-objective solution is determined to select the offshore wind farm to be transformed by the A or B scheme; Wherein, the A scheme is, calling OpenSees calculation model to calculate the excess pore water pressure ratio EPPR , and EPPR The safety factor is calculated, and the minimum friction disc inner and outer ring radius ratio and thickness meeting the structural safety requirement are determined; the B scheme is, according to the power requirement of the peripheral power utilization equipment, the annual average growth rate of the power requirement of the peripheral power utilization equipment, the new power brought by the modified fan and the service life of the peripheral power utilization equipment, the number of the fans needing to be modified is determined.

2. The energy efficiency driven integrated offshore intelligent charging pile system according to claim 1, characterized in that, The inner ring area of the friction disc is arranged in a symmetrical sealed cabin in layers, a battery layer is arranged in the inner ring area, a honeycomb alloy framework is arranged in the battery layer, energy storage batteries are embedded in the honeycomb alloy framework, the arrangement of the energy storage batteries matches the spatial distribution characteristics of the power demand of the peripheral power-consuming equipment, and all the energy storage batteries are electrically connected together; protective layers are arranged on the upper and lower surfaces of the energy storage batteries, all the energy storage batteries are encapsulated into the battery layer by a steel outer cylinder, a steel inner cylinder and the protective layers, and a concrete protective layer is arranged outside the battery layer; the outer ring area is integrally poured with concrete to wrap the inner ring area.

3. The energy efficiency driven integrated offshore intelligent charging pile system according to claim 1, characterized in that, In the OpenSees calculation model, the model size of the pile-disc-soil interaction adopts a scaling relationship of 1:6 with the actual size, the wind turbine body is simplified as a steel rod with a concentrated load at the upper part, the range of the soil body is more than 10 times the diameter of the pile, and the soil body is divided into grids; the inner and outer ring radius ratio and thickness are taken as variables to parameterize the modeling and grid division of the friction disc.

4. The energy efficiency driven integrated offshore intelligent charging pile system according to claim 1, characterized in that, In the determination process of the minimum comprehensive transformation cost, an opportunity cost is introduced to balance the difference in construction cost of the A scheme or the B scheme, the opportunity cost considering the annual output value, the decay coefficient and the economic weight coefficient of different economic development of the economic activities of different power-consuming equipment.

5. The energy efficiency driven integrated offshore intelligent charging pile system according to claim 1, characterized in that, An SSA-NSGA-III algorithm is used for intelligent multi-objective solution.

6. A method for transforming an energy-efficient, integrated charging pile on a sea, characterized in that, The transformation method comprises: Obtaining the position coordinates of the existing offshore wind farm, the driving route of the existing ocean route and the power-consuming equipment, wherein the power-consuming equipment includes ocean freighters, offshore platforms, offshore ranches and data centers, the position coordinates of the ocean freighter on the ocean route are selected as the points with the maximum appearance probability of the ocean freighter; the power supply radius of each offshore wind farm and the demand for power of each power-consuming equipment are obtained; The OpenSees calculation model of pile-disk-soil interaction is constructed to calculate the excess pore water pressure ratio of pile-disk composite single pile foundation under the action of earthquake under the condition of different friction disk inner and outer ring radius ratio R and thickness T EPPR ; Maximize the coverage range of the offshore wind farm, minimize the power transmission loss and minimize the comprehensive transformation cost as the goal, with the power supply capacity limit of the maximum output power of the wind turbine, the transformation cost limit of a single offshore wind farm, the safety distance limit between the offshore wind farm and the shipping channel of the shipping freighter, and the endurance constraint limit of the offshore unmanned equipment as the constraints, multi-objective solution is carried out to determine whether the offshore wind farm needs to be transformed and which scheme A or B is selected for transformation; Wherein, the A scheme is, calling OpenSees calculation model to calculate the excess pore water pressure ratio EPPR , the B scheme is, setting the inner and outer ring radius ratio and the thickness of the friction disc, and determining the number of wind turbines to be reconstructed according to the power demand of the peripheral power utilization equipment, the annual average growth rate of the power demand of the peripheral power utilization equipment, the newly added power brought by the reconstructed wind turbine and the service life of the peripheral power utilization equipment. EPPR , the B scheme is, setting the inner and outer ring radius ratio and the thickness of the friction disc, and determining the number of wind turbines to be reconstructed according to the power demand of the peripheral power utilization equipment, the annual average growth rate of the power demand of the peripheral power utilization equipment, the newly added power brought by the reconstructed wind turbine and the service life of the peripheral power utilization equipment.

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